Defining the genetic, genomic, cellular, and diagnostic architectures of psychiatric disorders
Open accessAbstract
Studies of the genetics of psychiatric disorders have become one of the most exciting and fast-moving areas in human genetics. A decade ago, there were few reproducible findings, and now there are hundreds. In this review, we focus on the findings that have illuminated the genetic architecture of psychiatric disorders and the challenges of using these findings to inform our understanding of pathophysiology. The evidence is now overwhelming that psychiatric disorders are "polygenic"-that many genetic loci contribute to risk. With the exception of a subset of those with ASD, few individuals with a psychiatric disorder have a single, deterministic genetic cause; rather, developing a psychiatric disorder is influenced by hundreds of different genetic variants, consistent with a polygenic model. As progressively larger studies have uncovered more about their genetic architecture, the need to elucidate additional architectures has become clear. Even if we were to have complete knowledge of the genetic architecture of a psychiatric disorder, full understanding requires deep knowledge of the functional genomic architecture-the implicated loci impact regulatory processes that influence gene expression and the functional coordination of genes that control biological processes. Following from this is cellular architecture: of all brain regions, cell types, and developmental stages, where and when are the functional architectures operative? Given that the genetic architectures of different psychiatric disorders often strongly overlap, we are challenged to re-evaluate and refine the diagnostic architectures of psychiatric disorders using fundamental genetic and neurobiological data.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
0 of 131 cited sources checked · 0 supported · 0 flagged
- Findingnone given
Around 400 protein-coding genes lie in these loci.
“Around 400 protein-coding genes lie in these loci.”
Quote in the paperNot a substantial claim - Findingreasoning
These loci together implicate about 76 Mb of the genome as containing common genetic variants involved in the etiology of these disorders.
“These loci together implicate ~76 Mb of the genome as containing common genetic variants involved in the etiology of these disorders.”
Quote in the paperNot a substantial claim - Findingnone given
When functional genomic data from human brain are overlaid, about 50% of the time genes located in loci are also implicated by functional data.
“If we overlay functional genomic data from human brain (e.g., eQTL or regulatory chromatin interactions), about 50% of the time genes located in loci are also implicated by functional data.”
Quote in the paperNot a substantial claim - Findingown data
SNP-heritability estimates tend to follow traditional heritability.
“Table 1 shows SNP-heritability estimates, and these tend to follow traditional heritability.”
Quote in the paperNot a substantial claim - Findingcitation
In SCZ GRS data, cases in the top decile have 15-fold increased risk compared with the lowest decile.
“Cases in the top decile have 15 fold increased risk for schizophrenia compared to the lowest decile (Schizophrenia Working Group of the Psychiatric Genomics Consortium, 2014).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Schizophrenia Working Group of the Psychiatric Genomics Consortium, 2014
Not checked in the free run.
- Findingcitation
Lifetime major depressive disorder has a genetic correlation of 0.98 with depressive symptoms.
“lifetime MDD has a genetic correlation of 0.98 with depressive symptoms (Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, 2018)”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, 2018
Not checked in the free run.
- Findingnone given
Large copy number variants in severe psychotic disorders will be present in 3-5% of cases.
“Large CNVs in severe psychotic disorders (SCZ and schizoaffective disorder) will be present in 3–5% of cases.”
Quote in the paperNot a substantial claim - Premisecitation
GWAS results for SCZ and MDD are enriched for genes encoding proteins known to interact with pharmacological targets of antipsychotics and antidepressants.
“For example, GWAS results for SCZ (Schizophrenia Working Group of the Psychiatric Genomics Consortium, 2014) and MDD (Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, 2018) are enriched for genes that encode proteins known to interact with pharmacological targets of antipsychotics and antidepressants.”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Schizophrenia Working Group of the Psychiatric Genomics Consortium, 2014
Not checked in the free run.
- cites Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, 2018
Not checked in the free run.
- Premisereasoning
In almost all instances, SNP-heritability is less than twin or pedigree heritability.
“In almost all instances, SNP-heritability is less than twin/pedigree heritability.”
Quote in the paperNot a substantial claim - Premisecitation
Genetic risk for psychiatric disorders is non-specific and shared to varying degrees across many adult- and childhood-onset disorders.
“A key empirical finding is that genetic risk can be non-specific and shared to varying extents across many adult and childhood onset psychiatric disorders (Brainstorm Consortium, 2018; Cross-Disorder Group of the Psychiatric Genomics Consortium, 2013b; Schork et al., In press).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Brainstorm Consortium, 2018
Not checked in the free run.
- cites Cross-Disorder Group of the Psychiatric Genomics Consortium, 2013b
Not checked in the free run.
- cites Schork et al., In press
Not checked in the free run.
- Premisecitation
Incorrect inference from GRS can readily occur if the training and target datasets are from different ancestries.
“As just one example, incorrect inference can readily occur if the GRS training and target datasets are from different ancestries (Martin et al., 2017).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Martin et al., 2017 source
Not checked in the free run.
- Premisecitation
The most reproducible single clue from family studies is that psychiatric disorders run in families, established by more than 50 years of twin, family, and adoption studies.
“The most reproducible single clue that emerged was the tendency for psychiatric disorders to “run” in families – as established by 50+ years of twin, family, and adoption studies (summarized in Table 1) (Polderman et al., 2015).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Polderman et al., 2015 source
Not checked in the free run.
- Premisecitation
Inheriting a notably large number of SCZ risk alleles, such as being in the top versus bottom GRS decile, carries more than a 10-fold increased risk of SCZ.
“Inheriting a notably large number of SCZ risk alleles (e.g., being in the top vs bottom decile for GRS) carries more than a 10-fold increased risk of SCZ (Schizophrenia Working Group of the Psychiatric Genomics Consortium, 2014).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Schizophrenia Working Group of the Psychiatric Genomics Consortium, 2014
Not checked in the free run.
- Premisecitation
Knowledge of genetic architecture can help optimize gene discovery, including study design, ascertainment, and choice of genotyping technology.
“Knowledge of genetic architecture can help optimize gene discovery (e.g., study design, ascertainment, and choice of genotyping technology) (Timpson et al., 2018; Visscher et al., 2012).”
Quote in the paperNot a substantial claim0 of 2 sources checked - Premisereasoning
SNP-heritability can be estimated for traits that are difficult or impossible to assess using twins.
“SNP-heritability can be estimate for traits that are difficult or impossible to assess using twins (e.g., antipsychotic adverse drug reactions).”
Quote in the paperNot a substantial claim - Interpretationreasoning
Psychiatric disorders are broadly similar to other common biomedical diseases in having a polygenic basis.
“In this respect, psychiatric disorders are broadly similar to other common biomedical diseases.”
Quote in the paperNot a substantial claim - Premisecitation
Psychiatric disorders have a polygenic basis: many genetic loci, mostly with small effects, contribute to risk.
“The evidence is now overwhelming that psychiatric disorders are “polygenic”, that many genetic loci contribute to risk.”
- Also stated in: § Introduction · boosted
“The evidence is now overwhelming that psychiatric disorders have a “polygenic” basis – that many genetic loci mostly with small effect sizes contribute to risk (Visscher et al., 2017).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Visscher et al., 2017 source
Not checked in the free run.
- Also stated in: § Introduction · boosted
- Interpretationcitation
The failure of simple models led to recognition that sample sizes beyond any single group were needed to detect generalizable findings.
“The failure of simple models led to widespread acknowledgement of a need for sample sizes that were beyond the reach of any single group to achieve power to detect generalizable findings.”
Quote in the paperSubstantial claim0 of 3 sources checked - Premisecitation
Recent studies show that genes located far outside a locus are often implicated.
“Crucially, recent studies have shown that genes located far outside of a locus are often implicated (see functional architecture section below) (Wang et al., 2018a; Won et al., 2016).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Wang et al., 2018a
Not checked in the free run.
- cites Won et al., 2016 source
Not checked in the free run.
- Premisecitation
The reproducible yield of candidate gene association studies is negligible compared with current knowledge.
“Compared to current knowledge, the reproducible yield of candidate gene association studies is negligible (Farrell et al., 2015).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Farrell et al., 2015 source
Not checked in the free run.
- Premisecitation
Linkage and candidate gene studies produced many claims of gene discovery for SCZ, such as COMT, DISC1, DTNBP1, and NRG1, that were not subsequently supported.
“Linkage and candidate gene studies led to many claims of gene discovery (e.g., COMT, DISC1, DTNBP1, and NRG1 for SCZ) that were not subsequently supported (Border et al., In press; Farrell et al., 2015).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Border et al., In press
Not checked in the free run.
- cites Farrell et al., 2015 source
Not checked in the free run.
- Premisecitation
Linkage analysis is poorly powered for complex traits.
“Linkage analysis is poorly powered for complex traits (Risch and Merikangas, 1996).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Risch and Merikangas, 1996 source
Not checked in the free run.
- Premisecitation
Penetrance of copy number variants can be highly variable, ranging from subtle effects detectable by neuropsychological tests to mild anxiety or ADHD to co-occurrence of severe psychiatric disorders.
“penetrance can be highly variable, ranging from subtle effects detectable by neuropsychological tests to mild degrees of anxiety/ADHD to co-occurrence of severe psychiatric disorders (Kendall et al., 2017; Stefansson et al., 2014; Ulfarsson et al., 2017)”
Quote in the paperNot a substantial claim0 of 3 sources checked - Premisecitation
Many genes carrying rare mutations confer broader phenotype risks rather than being specific to one disorder.
“many confer broader phenotype risks (Abrahams and Geschwind, 2008; Ronemus et al., 2014; Satterstrom et al., 2018b)”
Quote in the paperSubstantial claim0 of 3 sources checked - Premisecitation
Rare variant discovery has been most successful in ASD, where whole-exome sequencing for rare de novo protein truncating variants in mutation intolerant genes has identified around 100 high-confidence connections to specific genes.
“Rare variant discovery has been most successful in ASD where WES for rare, de novo, protein truncating variants (PTVs) in mutation intolerant genes has identified around 100 high-confidence connections to specific genes (Satterstrom et al., 2018b).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Satterstrom et al., 2018b
Not checked in the free run.
- Premisecitation
Copy number variants associated with psychiatric disorders usually contain multiple genes.
“they usually contain multiple genes (with a few exceptions (Bucan et al., 2009; Talkowski et al., 2011))”
Quote in the paperNot a substantial claim0 of 2 sources checked - Premisecitation
Whole-exome sequencing has identified only two genes for schizophrenia at sample sizes that produced dozens of associations for autism spectrum disorder.
“WES has implicated only two genes for SCZ (Singh et al., 2016; Steinberg et al., 2017) at sample sizes that yielded dozens of associations for ASD.”
Quote in the paperSubstantial claim0 of 2 sources checked - Premisecitation
Most copy number variants confer increased risk for multiple psychiatric disorders including intellectual disability, autism spectrum disorder, ADHD, and psychotic disorders.
“most CNVs confer increased risk for multiple psychiatric disorders including ID, ASD, ADHD, and psychotic disorders (Kirov, 2015; Lowther et al., 2017)”
Quote in the paperSubstantial claim0 of 2 sources checked - Premisecitation
A role for de novo gene-disrupting and missense variants has been established in Tourette syndrome.
“In TS, a role for de novo gene disrupting and missense variants has been established (Willsey et al., 2017)”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Willsey et al., 2017 source
Not checked in the free run.
- Premisecitation
Most known pathogenic copy number variants increase risk for multiple disorders.
“Most known pathogenic CNVs increase risk for multiple disorders (de la Torre-Ubieta et al., 2016; Kirov, 2015; Lowther et al., 2017; Malhotra and Sebat, 2012).”
Quote in the paperNot a substantial claim0 of 3 sources checked - Premisenone given
Copy number variants associated with psychiatric disorders are usually larger than 500 kb.
“are usually >500 kb in size (although many expect that smaller CNVs will be found using WGS)”
Quote in the paperNot a substantial claim - Interpretationreasoning
Large-scale resequencing in adult psychiatric disorders has a limited role until sequencing costs decline substantially.
“The sobering experiences in SCZ and type 2 diabetes suggest a limited role of large-scale resequencing in adult disorders until the costs decline substantially.”
Quote in the paperSubstantial claim - Interpretationcitation
Pleiotropic large-effect mutations may act by disrupting key neurodevelopmental processes rather than by specifically causing one defined clinical disorder.
“These pleiotropic large effect mutations may work by disrupting key neurodevelopmental processes rather than specifically causing one defined clinical disorder (Geschwind and Levitt 2007).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Geschwind and Levitt 2007 source
Not checked in the free run.
- Premisecitation
The effects of protein-truncating variants can be assessed in a functional and evolutionary context using loss of one gene copy and degree of constraint.
“the effects of PTVs can be assessed in a functional and evolutionary context (loss of one copy of the gene and the degree of constraint) (Samocha et al., 2014)”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Samocha et al., 2014 source
Not checked in the free run.
- Premisecitation
Larger de novo copy number variants, especially those disrupting genes or changing gene dosages, can carry major risks for neurodevelopmental disorders.
“Larger de novo CNVs, especially ones that disrupt genes or change gene dosages, can carry major risks particularly for neurodevelopmental disorders (Malhotra and Sebat, 2012; Sebat et al., 2007).”
Quote in the paperSubstantial claim0 of 2 sources checked - Premisecitation
Some gene network analyses suggest that molecular processes distinguish autism spectrum disorder from intellectual disability.
“some gene network analyses suggest the existence of molecular processes that distinguish ASD from ID (Parikshak et al., 2013; Satterstrom et al., 2018b)”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Parikshak et al., 2013 source
Not checked in the free run.
- cites Satterstrom et al., 2018b
Not checked in the free run.
- Premisecitation
Major psychiatric disorders have significant and often sizable genetic correlations.
“Notably, the major psychiatric disorders have significant and often sizable genetic correlations (Cross-Disorder Group of the Psychiatric Genomics Consortium, 2013a).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Cross-Disorder Group of the Psychiatric Genomics Consortium, 2013a
Not checked in the free run.
- Premisecitation
Resequencing in autism spectrum disorder yields substantially more findings than in other psychiatric disorders.
“The yield of resequencing in ASD is markedly higher than for other psychiatric disorders.”
Quote in the paperSubstantial claim0 of 2 sources checked - Premisenone given
Many copy number variants are associated with partial disruption of developmental programs and impact multiple organs, including cardiac, gut, immune, endocrine, and brain.
“many CNVs are associated with partial disruption of a range of developmental programs and impact multiple organs (cardiac, gut, immune, and endocrine as well as brain)”
Quote in the paperNot a substantial claim - Interpretationreasoning
Detection of inherited variation may be hindered by ascertainment bias from study designs that favor detection of de novo variants.
“The detection of inherited variation may be further hindered by ascertainment bias from study designs that favor detection of de novo variants.”
Quote in the paperNot a substantial claim - Interpretationcitation
Some pleiotropy of copy number variants may be due to modification by genetic risk scores, because even in individuals with autism spectrum disorder or schizophrenia carrying large-effect de novo mutations there appears to be an additive effect of common variation on phenotypic expression.
“Emerging evidence suggests that among other factors, some of this pleiotropy may be due to modification GRS because even in those with ASD or SCZ carrying large effect de novo mutations, there appears to be an additive effect of common variation on phenotypic expression (Tansey et al., 2016; Weiner et al., 2017).”
Quote in the paperNot a substantial claim0 of 2 sources checked - Premisereasoning
Pleiotropy is the rule: most mutations increase risk for a range of neurodevelopmental outcomes such as intellectual disability, autism spectrum disorder, epilepsy, or psychosis.
“Pleiotropy is more the rule: most mutations increase risk for a range of neurodevelopmental outcomes (e.g., ID, ASD, epilepsy, or psychosis).”
Quote in the paperSubstantial claim - Premisecitation
Major depressive disorder has significant positive genetic correlations with anxiety disorders, autism spectrum disorder, ADHD, bipolar disorder, and anorexia nervosa.
“MDD has significant positive genetic correlations with anxiety disorders, ASD, ADHD, BIP, and AN (Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, 2018)”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, 2018
Not checked in the free run.
- Interpretationreasoning
The genetic overlap between psychiatric disorders necessitates consideration of diagnostic architecture.
“both of which necessitate consideration of diagnostic architecture”
Quote in the paperNot a substantial claim - Premisecitation
Several genes that cause rare forms of autism spectrum disorder regulate expression or splicing of many genes associated with psychiatric disorders.
“Several genes that cause rare forms of ASD (e.g., FMR1, CACNA1C, and TCF4) regulate expression or splicing of many genes associated with psychiatric disorders (Tian et al., 2014; Weyn-Vanhentenryck et al., 2014).”
Quote in the paperSubstantial claim0 of 2 sources checked - Premisecitation
Assigning well-annotated genomic regions to specific genes is not as simple as choosing the closest gene or genes containing variation highly correlated with associated SNPs.
“assigning even well-annotated genomic regions to specific genes is not as simple as choosing the closest gene or genes containing variation that is highly correlated with the associated SNPs which is usually the default approach (Whalen et al., 2016; Won et al., 2016)”
Quote in the paperSubstantial claim0 of 2 sources checked - Premisecitation
In autism spectrum disorder, analyses replicated using different methods and samples implicate synaptic and neuronal signaling pathways overlapping with other causal gene-based network methods.
“In ASD, these analyses, replicated using different methods and samples, implicate synaptic and neuronal signaling pathways overlapping with other causal gene-based network methods (Parikshak et al., 2016; Voineagu et al., 2011).”
Quote in the paperSubstantial claim0 of 2 sources checked - Interpretationcitation
Genetic risk for autism spectrum disorder appears to act primarily in fetal periods, involving cortical glutamatergic neurogenesis and early development.
“Genetic risk for ASD appears act primarily in fetal periods, involving cortical glutamatergic neurogenesis and early development.”
Quote in the paperSubstantial claim - Premisecitation
Autism spectrum disorder risk genes are enriched in upper relative to lower layer neurons.
“ASD risk genes are enriched in upper relative to lower layer neurons.”
Quote in the paperSubstantial claim - Premisecitation
Cross-disorder transcriptome correlations parallel genetic correlations, consistent with common biological processes.
“cross-disorder transcriptome correlations parallel genetic correlations, consistent with common biology processes (Gandal et al., 2018a)”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Gandal et al., 2018a
Not checked in the free run.
- Premisecitation
Many psychiatric genome-wide association studies are under-powered to determine cell type or developmental stage specificity.
“At present, many psychiatric GWAS are under-powered to accomplish these intentions (Skene et al., 2018).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Skene et al., 2018 source
Not checked in the free run.
- Premisecitation
Schizophrenia has significant positive genetic correlations with bipolar disorder, major depressive disorder, ADHD, autism spectrum disorder, and anorexia nervosa.
“SCZ has significant positive genetic correlations with BIP, MDD, ADHD, ASD, and AN (Brainstorm Consortium, 2018)”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Brainstorm Consortium, 2018
Not checked in the free run.
- Premisecitation
All psychiatric disorders in Table 1 have an important contribution from hundreds or thousands of common genetic variants of relatively subtle effect.
“all of the psychiatric disorders in Table 1 have an important contribution from hundreds or thousands of common genetic variants of relatively subtle effect”
Quote in the paperSubstantial claim - Interpretationcitation
4D mapping of chromatin interactions is critical for understanding the functional relationships of regulatory regions to genes.
““4D mapping” of chromatin interactions (i.e., brain regions across developmental time) is critical for understanding the functional relationships of regulatory regions to genes (Dekker et al., 2017)”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Dekker et al., 2017 source
Not checked in the free run.
- Premiseown data
Major depressive disorder risk is clustered in cortical interneurons and embryonic midbrain neurons.
“MDD risk was clustered in cortical interneurons and embryonic midbrain neurons”
Quote in the paperSubstantial claim - Interpretationreasoning
Genetic data are the most fundamental biomarker yet discovered for almost all psychiatric disorders.
“For almost all psychiatric disorders, genetic data are the most fundamental biomarker yet discovered”
Quote in the paperSubstantial claim - Premisecitation
Despite clear genetic heterogeneity, both autism spectrum disorder and schizophrenia risk converge on shared molecular pathways.
“Despite clear genetic heterogeneity, both ASD and SCZ risk converge on shared molecular pathways (Network and Pathway Analysis Subgroup of Psychiatric Genomics Consortium, 2015; Parikshak et al., 2015).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Network and Pathway Analysis Subgroup of Psychiatric Genomics Consortium, 2015
Not checked in the free run.
- cites Parikshak et al., 2015 source
Not checked in the free run.
- Premisecitation
At least some rare major gene forms of psychiatric disorders impact pathways that are more generally related to risk in the population.
“at least some of the rare major gene forms of psychiatric disorders impact pathways that are more generally related to risk in the population”
Quote in the paperSubstantial claim - Interpretationnone given
Identification of large-effect mutations in patients has substantial clinical utility.
“identification of large effect mutations in patients is of substantial clinical utility”
Quote in the paperNot a substantial claim - Premisecitation
Common variation dominates heritable risk for schizophrenia and autism spectrum disorder.
“direct comparisons of the contributions of common and rare genetic variation show that common variation dominates heritable risk for SCZ and ASD (Gaugler et al., 2014; Purcell et al., 2014)”
Quote in the paperSubstantial claim0 of 2 sources checked - Premisecitation
Most genetic variation contributing to common psychiatric disorders is not in protein-coding regions.
“most genetic variation that contributes to common psychiatric disorders is not in protein-coding regions”
Quote in the paperSubstantial claim0 of 2 sources checked - Premisecitation
Distinct data types derived in different laboratories and samples show significant overlap in regulatory predictions.
“These distinct data types – often derived in different laboratories in different samples- show significant overlap in regulatory predictions (Gusev et al., 2018).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Gusev et al., 2018 source
Not checked in the free run.
- Premisecitation
Transcriptomic findings for autism spectrum disorder, schizophrenia, bipolar disorder, and major depressive disorder suggest shared and disorder-specific gene expression changes.
“Transcriptomic findings for ASD, SCZ, BIP, and MDD suggested shared and disorder-specific gene expression changes (Gandal et al., 2018a).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Gandal et al., 2018a
Not checked in the free run.
- Premisereasoning
There is important genetic overlap between psychiatric disorders, including substantial components of genetic variation that increase risk for multiple disorders.
“there is also important genetic overlap, including substantial components of genetic variation that increase risk for multiple disorders”
Quote in the paperSubstantial claim - Interpretationreasoning
Pinpointing the genes impacted by risk variants is a crucial step in understanding disease mechanisms.
“a crucial step in understanding disease mechanisms is pinpointing the genes impacted by risk variants”
Quote in the paperSubstantial claim - Premisecitation
Nearly half of the target genes of human regulatory variation are not in genomic loci defined by linkage disequilibrium.
“nearly half of the target genes of human regulatory variation are not in genomic loci defined by LD (Whalen and Pollard, 2018)”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Whalen and Pollard, 2018
Not checked in the free run.
- Premisecitation
In autism spectrum disorder, risk pathways involve regulation of transcription and chromatin structure during neurogenesis, and subsequent synaptic development and function during early fetal cortical development.
“In ASD, these pathways involve regulation of transcription and chromatin structure during neurogenesis, and subsequent processes of synaptic development and function during early fetal cortical development (Parikshak et al., 2015).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Parikshak et al., 2015 source
Not checked in the free run.
- Premisereasoning
Genetic results show fundamental overlaps between many adult and childhood disorders.
“genetic results show fundamental overlaps between many adult and childhood disorders”
Quote in the paperSubstantial claim - Premisecitation
Overlaps with methods that directly assess chromatin are less substantial for comparisons relying on linkage disequilibrium blocks or closest-gene assignment.
“This is in contrast to comparisons relying on LD blocks or the assignment by the closest gene, where the overlaps with methods that directly assess chromatin are less substantial (Short et al., 2018; Whalen and Pollard, 2018).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Short et al., 2018 source
Not checked in the free run.
- cites Whalen and Pollard, 2018
Not checked in the free run.
- Premisecitation
Few genes act in isolation; they affect the function of other genes to influence a phenotype through cellular networks or pathways.
“Few genes act in isolation but rather affect the function of other genes to influence a particular phenotype via in cellular networks or pathways (Barabasi et al., 2011; Geschwind and Konopka, 2009).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Barabasi et al., 2011 source
Not checked in the free run.
- cites Geschwind and Konopka, 2009
Not checked in the free run.
- Premisecitation
Autism spectrum disorder risk variants are enriched in cortical glutamatergic neurons expressed during neurogenesis and neuronal migration during fetal cortical development in human and mouse.
“ASD risk variants are enriched in cortical glutamatergic neurons expressed during neurogenesis and neuronal migration during fetal cortical development in human and mouse (Parikshak et al., 2013; Willsey et al., 2013).”
Quote in the paperSubstantial claim0 of 2 sources checked - Premisecitation
Single-nuclei RNA sequencing from human fetal and adult brain has validated enrichment of genes harboring large-effect de novo mutations associated with autism spectrum disorder in fetal glutamatergic neurons.
“A recent study of single-nuclei RNA sequencing from human fetal and adult brain has validated the enrichment of genes harboring large effect de novo mutations associated with ASD in fetal glutamatergic neurons (Polioudakis et al., 2018).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Polioudakis et al., 2018
Not checked in the free run.
- Premisecitation
Common variant genetic findings for schizophrenia show enrichment in a limited set of major cell types: pyramidal neurons in cortex and hippocampal CA1, striatal medium spiny neurons, and cortical interneurons.
“Common variant genetic findings for SCZ showed enrichment in a limited set of major cell types: pyramidal neurons in cortex and hippocampal CA1, striatal medium spiny neurons, and cortical interneurons.”
Quote in the paperSubstantial claim - Interpretationcitation
Risk profiles in individuals are likely complex even in those harboring large-effect mutations.
“already there are multiple hints that risk profiles in individuals are likely to be complex, even in those harboring large effect mutations.”
Quote in the paperSubstantial claim- Rests on an assumption: Few large-effect mutations are specific to a single disorder, suggesting additional genetic, environmental, and stochastic factors.
- Premisereasoning
Most rare copy number variants and exon variants of strong effect have pleiotropic effects, increasing risk for multiple neurodevelopmental conditions.
“there are pleiotrophic effects for most rare CNV and exon variants of strong effect as many such variants increase risk for multiple neurodevelopmental conditions”
Quote in the paperSubstantial claim - Premisecitation
For ASD, evidence from genetics and functional genomics points to protective factors in females that involve brain function and structure.
“For example, in ASD, genetic and functional genomic evidence suggests the presence of female protective factors based in brain function and structure (Robinson et al., 2013; Werling and Geschwind, 2013; Werling et al., 2016)”
Quote in the paperNot a substantial claim0 of 3 sources checked - Premisecitation
In MDD or ALC, social factors likely have a larger role in sex differences.
“whereas in MDD or ALC, social factors likely may have a larger role (Riecher-Rossler, 2017).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Riecher-Rossler, 2017 source
Not checked in the free run.
- Interpretationreasoning
Genetic results are consistent with a tentative position that a central part of the inherited liability is shared by many psychiatric disorders.
“we posit that the genetic results are consistent with a tentative position: based on pervasive genetic overlap between most childhood and adult-onset psychiatric disorders and their inter-correlations with cognitive ability and personality, a central part of the inherited liability is shared by many psychiatric disorders.”
Quote in the paperSubstantial claim- Rests on an assumption: Genetic correlations between psychiatric disorders reflect shared biological processes rather than diagnostic overlap or other confounds.
- Premisecitation
Lifetime risk differs substantially by sex for ADHD, AN, ASD, MDD, and SCZ.
“For example, marked sex differences in lifetime risk are apparent for ADHD, AN, ASD, MDD, and SCZ (Hudson et al., 2007; Martin et al., 2018b; Philippe et al., 1999).”
Quote in the paperNot a substantial claim0 of 3 sources checked - Interpretationreasoning
The authors favor a model in which many, though not all, large-effect mutations make a person more susceptible to a developmental neuropsychiatric disorder.
“The model that we prefer is that many (but not all) large effect mutations sensitize an individual to manifest a developmental neuropsychiatric disorder.”
Quote in the paperSubstantial claim- Rests on an assumption: Many de novo or Mendelian mutations affect brain development and function so strongly that they are not specific to one disorder.
- Rests on an assumption: Some rare large-effect mutations show clear preferential effects toward a disorder, as with some CNVs and rare protein-altering mutations.
- Premisecitation
In population samples unselected for disease, many large-effect CNVs associated with ASD or SCZ have relatively modest effects on fertility compared with diagnosed individuals.
“Although some large effect CNVs associated with ASD or SCZ have effects on fecundity, when discovered in population surveys in individuals without regard to disease status, many have relatively modest effects on the ability to have offspring, compared with those having the disease diagnosis (Stefansson et al., 2014).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Stefansson et al., 2014 source
Not checked in the free run.
- Premisecitation
When directly examined, polygenic risk combines additively with major mutation burden.
“In the instances where this has been studied directly, polygenic risk acts additively with major mutational burdens (Gaugler et al., 2014; Niemi et al., 2018; Purcell et al., 2014; Weiner et al., 2017).”
Quote in the paperSubstantial claim0 of 3 sources checked - Interpretationreasoning
Available data support three uses of genetic testing in clinical psychiatry.
“we think that the available data support three uses in clinical psychiatry”
Quote in the paperSubstantial claim - Premisecitation
Many psychiatric disorders show different prevalence or onset in males and females.
“Many psychiatric disorders show a different prevalence or onset in males and females (Seedat et al., 2009).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Seedat et al., 2009 source
Not checked in the free run.
- Interpretationreasoning
The authors cannot yet confidently predict disorder phenotypes from genetic risk scores.
“However, we are still a long way from being able to confidently predict disorder phenotypes from measurement of genetic risk.”
- Also stated in: § What’s the end game? · plain
“We are far from being able to confidently predict disorder phenotypes from measurement of genetic risk.”
Quote in the paperSubstantial claim - Also stated in: § What’s the end game? · plain
- Premisereasoning
Other areas of medicine suggest that improving treatment does not require complete understanding of a disease process.
“However, there are indications from other areas of medicine that full understanding of a pathological process is not required to improve therapeutics.”
Quote in the paperSubstantial claim- Rests on an assumption: The causes of melanoma remain incompletely understood, yet checkpoint inhibitors developed from partial insights have greatly improved outcomes in disseminated disease.
- Interpretationreasoning
Current gene discovery efforts are incomplete.
“As noted above, the basic data remain incomplete and our – further genetic discovery efforts are needed to derive secure and enduring answers to these fundamental questions.”
Quote in the paperSubstantial claim
- May combine two claims. 38
- Classified as probably not a substantial claim. 13
May combine two claims.
Findingown dataThere are many controls in the top GRS decile and many cases in the lowest decile.
“Intriguingly, there are many controls in the top decile and many cases in the lowest decile.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataAcross the ten psychiatric disorders, 241 loci have a significant association, and 22 loci are associated with at least two disorders.
“Across all disorders, 241 loci have a significant association with the 10 psychiatric disorders in Table 1 with 22 loci associated with ≥2 psychiatric disorders.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataMost associated loci are disease specific, but many loci increase risk for multiple disorders.
“Although most loci are disease specific, many loci increase risk for multiple disorders.”
Quote in the paperSubstantial claimMay combine two claims.
FindingcitationRare protein-truncating variants in mutation-intolerant genes occurred with equal frequency in autism spectrum disorder and ADHD, and the genes impacted significantly overlapped.
“rare PTV in mutation intolerant genes occurred with equal frequency in both ASD and ADHD and that the genes impacted significantly overlapped”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Satterstrom et al., 2018a
Not checked in the free run.
May combine two claims.
FindingcitationStudying families with multiple children with autism spectrum disorder significantly reduced the signal from de novo variation compared with singleton families, while enhancing the signal from inherited variation for identifying risk genes.
“studying families having multiple children with ASD significantly reduced the signal from de novo variation compared to singleton families, while enhancing that from inherited variation to identify risk genes (Ruzzo et al., 2018)”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Ruzzo et al., 2018
Not checked in the free run.
May combine two claims.
InterpretationreasoningComplete knowledge of genetic architecture is insufficient for full understanding; functional genomic architecture is also required, involving regulatory effects on gene expression and coordination of genes in biological processes.
“Even if we were to have complete knowledge of the genetic architecture of a psychiatric disorder, full understanding requires deep knowledge of the functional genomic architecture – the implicated loci impact regulatory processes that influence gene expression and the functional coordination of genes that control biological processes.”
Quote in the paperSubstantial claimMay combine two claims.
PremisecitationSNP-heritability methods calculate heritability from SNP array data and provide assessments based on genome-wide genotypes, improving on traditional heritability measurements.
“Second, several methods can calculate the heritability of a trait using SNP array data (Bulik-Sullivan et al., 2015; Yang et al., 2011). These provide assessments of heritability based on genome-wide genotypes, and improves upon traditional heritability measurements given their basis in direct genetic measurements.”
Quote in the paperSubstantial claim0 of 2 sources checkedMay combine two claims.
PremisecitationA large-effect genetic variant is present in about 15% of ASD cases, with smaller proportions in TS, ADHD, and SCZ.
“This is particularly salient for ASD where a large effect variant is present in ~15% of cases along with smaller proportions of individuals with TS, ADHD, and SCZ (Iossifov et al., 2012; Sanders et al., 2012; Satterstrom et al., 2018c; Singh et al., 2016; Willsey et al., 2017).”
Quote in the paperNot a substantial claim0 of 3 sources checkedMay combine two claims.
PremisecitationGenetic architecture can inform prospects for clinical utility, but for most psychiatric disorders application is probabilistic rather than deterministic.
“Genetic architecture can inform prospects for clinical utility: although many deterministic monogenetic conditions are predicted or diagnosed using genetic testing, application to most psychiatric disorders traverses far more murky, probabilistic terrain (Timpson et al., 2018).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Timpson et al., 2018 source
Not checked in the free run.
May combine two claims.
PremisecitationResults to date indicate that psychiatric disorder risk is imparted by many common variants of individually small effects, and several disorders also have contributions from rarer variants with larger impact on risk.
“The results to date indicate that psychiatric disorder risk is imparted by many common variants of individually small effects, and several disorders also have contributions from rarer variants with larger impact on risk (Geschwind and Flint, 2015; Sullivan et al., 2018).”
Quote in the paperSubstantial claim0 of 2 sources checkedMay combine two claims.
PremisecitationCommon genetic variants generally have small effects on disease risk (OR <1.15), while rare variants typically have larger effect sizes (>2.0), are more likely deleterious, and tend to be removed by natural selection.
“Given what we know now, common variants generally have small effects on disease risk (OR <1.15), and rare variants typically have larger effect sizes (>2.0), are more likely to be deleterious, and tend to be removed by natural selection (Fu et al., 2013; Nelson et al., 2012; Zeng et al., 2018).”
Quote in the paperNot a substantial claim0 of 3 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationSNP-heritability estimates are available for thousands of traits.
“Indeed, SNP-heritability estimates are available for thousands of traits (Zheng et al., 2017).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Zheng et al., 2017 source
Not checked in the free run.
Probably not a substantial claim: may not pass S1 (asserted), S4 (based).
InterpretationreasoningCellular architecture is required to know where and when functional architectures operate across brain regions, cell types, and developmental stages.
“Following from this is cellular architecture: of all brain regions, cell types, and developmental stages, where and when are the functional architectures operative?”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningSNP-heritability provides strong indications that common genetic variation is important for all complex psychiatric disorders, and more will be discovered with increasing sample sizes.
“These provide exceptionally strong indications that common variation genetic variation is important for all complex psychiatric disorders, and more will be discovered with increasing sample sizes.”
Quote in the paperSubstantial claimMay combine two claims.
PremisecitationThe number of cases is the crucial determinant of the number of loci discovered; increasing sample sizes will identify more loci.
“The crucial determinant of the number of loci discovered is the number of cases; as sample sizes increase, more loci will be identified (Geschwind and Flint, 2015; Sullivan et al., 2018).”
Quote in the paperSubstantial claim0 of 2 sources checkedMay combine two claims.
PremisecitationRare variants can have a continuum of risk, and a fraction of common variants have large effects, such as APOE in Alzheimer's disease.
“This is not an invariant rule, as rare variants may have a continuum of risk (Marouli et al., 2017), and a fraction of common variants have large effects (e.g., APOE and Alzheimer’s disease).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Marouli et al., 2017 source
Not checked in the free run.
May combine two claims.
PremisecitationMDD has had notable difficulties with genetic discovery due to relatively low twin-heritability, but focusing on severe cases and increasing sample sizes has been fruitful.
“As a common disorder with relatively low twin-heritability (Levinson et al., 2014), MDD has had notable difficulties with genetic discovery, but focusing on severe cases (CONVERGE Consortium, 2015) and increasing sample sizes has been particularly fruitful (Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, 2018).”
Quote in the paperNot a substantial claim0 of 3 sources checked- cites Levinson et al., 2014 source
Not checked in the free run.
- cites CONVERGE Consortium, 2015
Not checked in the free run.
- cites Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, 2018
Not checked in the free run.
May combine two claims.
PremisecitationThe past decade has seen remarkable progress in elucidating the genetic underpinnings of psychiatric disorders, with numerous findings meeting modern criteria for significance and reproducibility.
“Despite these challenges, there has been remarkable progress in the past decade in elucidating the genetic underpinnings of psychiatric disorders with numerous findings that meet modern criteria for significance and reproducibility (Geschwind and Flint, 2015; Sullivan et al., 2018).”
Quote in the paperSubstantial claim0 of 2 sources checkedMay combine two claims.
Premisenone givenCommon variant association studies have identified more than 100 loci for SCZ and MDD, 53 loci for BIP, and 5-12 loci for ADHD, AN, and ASD.
“Studies in SCZ and MDD have yielded >100 loci, BIP has 53 loci, and ADHD, AN, and ASD have from 5–12 loci.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationMost of these ASD mutations also decrease IQ, and intellectual disability is an important comorbidity of ASD.
“Most of these mutations also decrease IQ and ID is an important comorbidity of ASD (Buja et al., 2018; Iossifov et al., 2014), which is consistent with previous work identifying dozens of known severe, rare medical genetic syndromes associated with ASD (reviewed in (Abrahams and Geschwind, 2008; Geschwind, 2009)).”
Quote in the paperNot a substantial claim0 of 2 sources checkedMay combine two claims.
PremisecitationComparison of SCZ results between European and East Asian samples indicated a genetic correlation indistinguishable from one, strongly indicating that the common variant genetic basis of SCZ is highly similar across these populations.
“Importantly, comparison of SCZ results between European and East Asian samples indicated that the genetic correlation was indistinguishable from one, strongly indicating that the common variant genetic basis of SCZ is highly similar across these global populations (Lam et al., Submitted).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Lam et al., Submitted
Not checked in the free run.
May combine two claims.
InterpretationreasoningIndirect twin or pedigree heritability estimates are often upwardly biased, and the degree to which SNP-heritability differs from indirect measures is unclear.
“If reviewed critically, indirect twin/pedigree heritability estimates are often upwardly biased, and the degree to which SNP-heritability is different from indirect measures is unclear.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationPrevious work has identified dozens of known severe, rare medical genetic syndromes associated with ASD.
“which is consistent with previous work identifying dozens of known severe, rare medical genetic syndromes associated with ASD (reviewed in (Abrahams and Geschwind, 2008; Geschwind, 2009)).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Abrahams and Geschwind, 2008 source
Not checked in the free run.
- cites Geschwind, 2009
Not checked in the free run.
May combine two claims.
PremisecitationBoth rare missense and inherited mutations contribute to autism spectrum disorder, with smaller effect sizes than de novo variants.
“both rare missense and inherited mutations have been shown to contribute to ASD, simply with smaller effect sizes than de novo variants (Ruzzo et al., 2018; Sanders et al., 2015)”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Ruzzo et al., 2018
Not checked in the free run.
- cites Sanders et al., 2015 source
Not checked in the free run.
May combine two claims.
PremisecitationSeveral dozen rare copy number variants confer relatively strong risks for psychiatric disorders, most commonly in autism spectrum disorder and schizophrenia and less frequently in bipolar disorder, Tourette syndrome, and ADHD.
“Several dozen rare CNVs are known to confer relatively strong risks for psychiatric disorders, most commonly in ASD and SCZ and less frequently in BIP, TS, and ADHD.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationA comprehensive effort of 25 psychiatric and neurological disorders showed that most psychiatric disorders had significant genetic inter-correlations, but there were far fewer for neurological conditions.
“A more comprehensive effort of 25 psychiatric and neurological disorders showed that most psychiatric disorders had significant genetic inter-correlations, but there were far fewer for neurological conditions (Brainstorm Consortium, 2018).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Brainstorm Consortium, 2018
Not checked in the free run.
May combine two claims.
PremisecitationRare de novo variation is predicted to account for about 15% of ASD cases, with each gene accounting for only a small fraction of cases.
“Although each gene accounts for only a small fraction of cases, rare de novo variation is predicted to account for ~15% of ASD cases (Iossifov et al., 2014).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Iossifov et al., 2014 source
Not checked in the free run.
May combine two claims.
Premisenone givenRecurrent copy number variants usually arise de novo, mainly through non-allelic homologous recombination in regions flanked by low-copy-number repeats.
“These recurrent CNVs usually arise de novo, mainly via non-allelic homologous recombination in regions flanked by low copy number repeats.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationcitationThe major pathogenic mechanism of copy number variants is presumed to be dosage sensitivity of genes within the variant, although distal regulatory effects on genes outside the variant are also plausible.
“the major pathogenic mechanism is presumed to be dosage-sensitivity of genes in the CNV although distal regulatory effects on genes outside of the CNV are also plausible (de la Torre-Ubieta et al., 2018)”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites de la Torre-Ubieta et al., 2018 source
Not checked in the free run.
May combine two claims.
PremisecitationUnder specific assumptions, Mendelian Randomization can suggest causality; lower educational attainment and higher body mass were putatively causal for MDD.
“Under a set of specific assumptions, we can also apply Mendelian Randomization (MR) to suggest causality; for two traits with sufficient numbers of significant associations, MR can assess the plausibility of whether one trait has a causal relation with another (e.g., lower educational attainment and higher body mass were putatively causal for MDD) (Major Depressive Disorder Working Group of the P”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, 2018
Not checked in the free run.
- The authors state this as an assumption: The specific assumptions required for Mendelian Randomization hold for the analyzed traits.
Probably not a substantial claim: may not pass S4 (based).
Premisenone givenPsychiatric disorders are not generally associated with brain pathology on gross or microscopic examination.
“Psychiatric disorders are not generally associated with brain pathology on gross or microscopic examination.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningIntegration of functional genomic data from brain yields empirically based hypotheses about regulatory relationships, but experimental validation is required.
“Although integration of functional genomic data from brain yields empirically-based hypotheses about regulatory relationships, experimental validation is required.”
Quote in the paperSubstantial claimMay combine two claims.
PremisecitationAround half of non-coding regions have regulatory functions shared across tissues, meaning that half of the regulatory elements in a given tissue may be relatively specific to a tissue, cell type, or developmental stage.
“around half of non-coding regions have regulatory functions that are shared across tissues meaning that half of the regulatory elements in a given tissue may be relatively specific to a tissue, cell type, or developmental stage (Liu et al., 2017a; Roadmap Epigenomics Consortium, 2015; Won et al., 2016)”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Liu et al., 2017a
Not checked in the free run.
- cites Roadmap Epigenomics Consortium, 2015
Not checked in the free run.
- cites Won et al., 2016 source
Not checked in the free run.
May combine two claims.
PremisecitationNetwork analysis provides an organizing framework that can divide large gene sets into biologically coherent modules for prioritization or add power to genome-wide association studies.
“network analysis provides an organizing framework that can divide large gene sets into biologically coherent modules for prioritization (Parikshak et al., 2015; Parikshak et al., 2013), or add power to GWAS (Horn et al., 2018)”
Quote in the paperSubstantial claim0 of 3 sources checkedProbably not a substantial claim: may not pass S2 (checkable), S4 (based).
Interpretationnone givenRare variants that disrupt genes provide a clear starting point for mechanistic studies.
“rare variants that disrupt genes provide a clear starting point for mechanistic studies”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationGenome-wide association study results integrated with regulatory chromatin interactions and gene expression show enrichment of enhancer marks in fetal brain and higher expression of autism spectrum disorder target genes during fetal corticogenesis.
“GWAS results integrated with regulatory chromatin interactions and gene expression, which show enrichment of enhancer marks in the fetal brain and higher expression of ASD target genes during fetal corticogenesis (Grove et al., In press)”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Grove et al., In press
Not checked in the free run.
May combine two claims.
PremisecitationCurated pathway-based studies using combinations of multiple methods and data sources are more convincing than those using single sources, have yielded evidence for common pathways across psychiatric disorders, but still do not fully overcome biases inherent in literature curation.
“Curated pathway-based studies using combinations of multiple methods and data sources are far more convincing than those using single sources, and have yielded evidence for common pathways across psychiatric disorders (Network and Pathway Analysis Subgroup of Psychiatric Genomics Consortium, 2015), but still do not fully overcome biases inherent in literature curation.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Network and Pathway Analysis Subgroup of Psychiatric Genomics Consortium, 2015
Not checked in the free run.
May combine two claims.
Premisenone givenPublished brain eQTL data have fewer than 1000 samples and contain only a fraction of presumed regulatory relationships.
“Published brain eQTL data have N<1000 and contain only a fraction of presumed regulatory relationships.”
Quote in the paperNot a substantial claimMay combine two claims.
Premiseown dataRare genetic variation plays a role in some psychiatric disorders, particularly autism spectrum disorder and schizophrenia, and also Tourette syndrome and ADHD.
“Empirical data show that rare genetic variation plays a role in some of these psychiatric disorders (ASD and SCZ in particular but also for TS and ADHD).”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
Premisenone givenHow common variants influence gene expression within biological networks is generally unknown.
“Exactly how these variants influence gene expression in the context of biological networks is generally unknown”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Premisenone givenThere are abundant examples of genetic tests now used clinically that have minimal or no scientific basis.
“there are abundant examples of genetic tests that are now being used clinically that have minimal or no scientific basis”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Interpretationnone givenGenetic approaches to psychiatric disorders have yielded more reproducible insights into etiology than any other prior approach.
“genetic approaches to psychiatric disorders have yielded more reproducible insights into etiology than any other prior approach”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Premisenone givenWilson's disease and Huntington's disease can present with psychotic or mood symptoms.
“Classic examples include Wilson’s disease and Huntington’s disease which can present with psychotic or mood symptoms.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based). May combine two claims.
Premisenone givenInexpensive SNP arrays can measure the contributions of the vast majority of common variation and be efficiently assessed in large populations now.
“Inexpensive SNP arrays can measure the contributions of the vast majority of common variation and be efficiently assessed in large populations now.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Premisenone givenIn many countries, genetic tests can be used by consumers without rigorous evaluation of analytical validity, clinical validity, and clinical utility.
“In many countries, genetic tests can be used by consumers without having rigorous evaluation of analytical validity, clinical validity, and clinical utility”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Premisenone givenIndividuals with a wide range of single-gene disorders can initially present with prominent psychiatric features.
“individuals with a wide range of single-gene disorders can initially present with prominent psychiatric features”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningAn individual's phenotype results from environmental influences and/or the combined effects of other rare variants and polygenic risk.
“The resultant phenotype in an individual is dependent on the impact of environmental factors, and/or the additive effects of other rare variation and polygenic risk.”
Quote in the paperSubstantial claim- Rests on an assumption: Many de novo or Mendelian mutations affect brain development and function so strongly that they are not specific to one disorder.
May combine two claims.
InterpretationreasoningIt remains unclear what drives sex differences, and the drivers probably vary by diagnosis.
“Whether sex differences are due to differential vulnerability, diverging behavioral/cognitive manifestations, and/or observer bias is not known with clarity but is likely to differ across diagnoses.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Premisenone givenThe fundamental database is not sufficiently complete to draw unambiguous conclusions.
“The fundamental database is not sufficiently complete to draw unambiguous conclusions”
Quote in the paperSubstantial claim
The paper relies on this without support.
Psychiatric disorders are defined by self-report and observation of cognition and behavior rather than by direct measurement of an etiological factor, making them syndromes rather than single diseases.
“In addition, psychiatric disorders are defined based on self-report and observation of cognition and behavior rather than on direct measurement of an etiological factor, making them syndromes rather than single diseases.”
The paper relies on this without support.
Few diagnostic features from laboratory testing, brain imaging, or pathology have acceptable positive and negative predictive values for routine clinical use.
“Many diagnostic features from laboratory testing, brain imaging, or pathology have been evaluated but few have acceptable positive and negative predictive values to support routine clinical use.”
The paper relies on this without support.
The internationally accepted definitions of psychiatric disorders were crafted by experts and influenced by traditions dating back a century or more.
“Furthermore, the internationally accepted definitions of psychiatric disorders were crafted by experts and influenced by traditions dating back a century or more.”
The authors state this as an assumption.
The specific assumptions required for Mendelian Randomization hold for the analyzed traits.
“Under a set of specific assumptions, we can also apply Mendelian Randomization (MR) to suggest causality; for two traits with sufficient numbers of significant associations, MR can assess the plausibility of whether one trait has a causal relation with another (e.g., lower educational attainment and higher body mass were putatively causal for MDD) (Major Depressive Disorder Working Group of the P”
The paper relies on this without support.
Genetic correlations between psychiatric disorders reflect shared biological processes rather than diagnostic overlap or other confounds.
“cross-disorder transcriptome correlations parallel genetic correlations, consistent with common biology processes (Gandal et al., 2018a)”
The authors state this as an assumption.
Genetic variants are not caused by the psychiatric disease (absence of reverse causation).
“given the plausible absence of reverse causation”
The paper relies on this without support.
Current psychiatric diagnostic categories are valid enough to study genetic overlap and clinical utility.
“the definitions of psychiatric disorders are necessarily based on descriptive data collected via human interactions and organized by expert panels”
The paper relies on this without support.
Few large-effect mutations are specific to a single disorder, suggesting additional genetic, environmental, and stochastic factors.
“For instance, few large effect mutations are specific to a disorder suggesting a possible role for additional genetic, environmental, and stochastic factors.”
The paper relies on this without support.
Many de novo or Mendelian mutations affect brain development and function so strongly that they are not specific to one disorder.
“However, the effects on brain development and function of many de novo or Mendelian mutations are so large as to be non-specific with respect to any single disorder (e.g. epilepsy, ASD, SCZ, ID).”
The paper relies on this without support.
Some rare large-effect mutations show clear preferential effects toward a disorder, as with some CNVs and rare protein-altering mutations.
“We recognize that there are rare large effect mutations that show clear preferential effects towards a disorder as is the case for some CNVs and rare protein altering mutations.”
The paper relies on this without support.
The causes of melanoma remain incompletely understood, yet checkpoint inhibitors developed from partial insights have greatly improved outcomes in disseminated disease.
“For instance, the causes of melanoma are not fully worked out but the advent of checkpoint inhibitors – based on several key pieces of the melanoma puzzle — has markedly improved outcomes for disseminated disease.”
The paper relies on this without support.
Almost every prototypic psychiatric medication was found by chance rather than design.
“as with virtually all prototypic medications used in clinical psychiatry”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Pathogenic variants in the same genes are identified in individuals with a variety of different clinically defined brain disorders, including ASD, ID, epilepsy, schizophrenia, and other neurodevelopmental and neuropsychiatric conditions.
“It has also become clear that pathogenic variants in the same genes are identified in individuals with a variety of different clinically defined brain disorders, including ASD, intellectual disability (ID), epilepsy, schizophrenia, and other neurodevelopmental and neuropsychiatric conditions.”
From Insufficient Evidence for “Autism-Specific” Genes (2020) · cites this paper as [7]
Cites
Vos, T., Abajobir, A. A., Abate, K. H., Abbafati, C., Abbas, K. M., Abd-Allah, F., Abdulkader, R. S., Abdulle, A. M., Abebo, T. A., Abera, S. F., et al. (2017) · The Lancet · doi:10.1016/s0140-6736(17)32154-2 · Cited by 13,220 · see citing works
Why Most Published Research Findings Are False
Ioannidis, J. P. A. (2005) · PLoS Medicine · doi:10.1371/journal.pmed.0020124 · Cited by 10,505 · see citing works
GCTA: a tool for genome-wide complex trait analysis
Yang, J., Lee, S. H., Goddard, M. E., & Visscher, P. M. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2010.11.011 · Cited by 8,279 · cited 2× · see citing works
“Third, we can now readily estimate the genetic correlations between traits using SNP array data (Bulik-Sullivan et al., 2015; Yang et al., 2011).”
BackgroundMethodBiological insights from 108 schizophrenia-associated genetic loci
Schizophrenia Working Group of the Psychiatric Genomics Consortium (2014) · Nature · doi:10.1038/nature13595 · Cited by 7,577 · see citing works
Integrative analysis of 111 reference human epigenomes
Roadmap Epigenomics Consortium, Kundaje, A., Meuleman, W., Ernst, J., Bilenky, M., Yen, A., Heravi-Moussavi, A., Kheradpour, P., Zhang, Z., Wang, J., et al. (2015) · Nature · doi:10.1038/nature14248 · Cited by 6,368 · see citing works
LD Score regression distinguishes confounding from polygenicity in genome-wide association studies
Schizophrenia Working Group of the Psychiatric Genomics Consortium, Bulik-Sullivan, B. K., Loh, P.-R., Finucane, H. K., Ripke, S., Yang, J., Patterson, N., Daly, M. J., Price, A. L., & Neale, B. M. (2015) · Nature Genetics · doi:10.1038/ng.3211 · Cited by 5,559 · see citing works
The Future of Genetic Studies of Complex Human Diseases
Risch, N., & Merikangas, K. (1996) · Science · doi:10.1126/science.273.5281.1516 · Cited by 5,355 · cited 1× · see citing works
“Linkage analysis is poorly powered for complex traits (Risch and Merikangas, 1996).”
BackgroundNetwork medicine: a network-based approach to human disease
Barabási, A.-L., Gulbahce, N., & Loscalzo, J. (2011) · Nature Reviews Genetics · doi:10.1038/nrg2918 · Cited by 5,034 · cited 1× · see citing works
“Few genes act in isolation but rather affect the function of other genes to influence a particular phenotype via in-cellular networks or pathways (Barabási et al., 2011; Geschwind and Konopka, 2009).”
BackgroundThe prevalence and correlates of eating disorders in the National Comorbidity Survey Replication
Hudson, J. I., Hiripi, E., Pope, H. G., & Kessler, R. C. (2007) · Biological Psychiatry · doi:10.1016/j.biopsych.2006.03.040 · Cited by 4,973 · cited 1× · see citing works
“For example, marked sex differences in lifetime risk are apparent for ADHD, AN, ASD, MDD, and SCZ (Hudson et al., 2007; Martin et al., 2018b; Philippe et al., 1999).”
BackgroundCommon polygenic variation contributes to risk of schizophrenia and bipolar disorder
The International Schizophrenia Consortium (2009) · Nature · doi:10.1038/nature08185 · Cited by 4,821 · cited 12× · see citing works
“Common-Variant Association Studies of Psychiatric Disorders Most genetic studies of psychiatric disorders in the past decade have used SNP arrays to assess the role of accessible common variation (also known as genome-wide association studies [GWASs]).”
BackgroundInfluentialWhy Most Published Research Findings Are False
Ioannidis, J. P. A. (2005) · CHANCE · doi:10.1080/09332480.2005.10722754 · Cited by 4,702 · cited 1× · see citing works
“These early successes were a form of ‘‘winner’s curse’’ (Ioannidis, 2005) that led to gross underestimation of the efforts that would ultimately be required (we note that geneticists working on most other complex human diseases were similarly misled).”
BackgroundGenetic effects on gene expression across human tissues
GTEx Consortium (2017) · Nature · doi:10.1038/nature24277 · Cited by 4,036 · see citing works
10 Years of GWAS Discovery: Biology, Function, and Translation
Visscher, P. M., Wray, N. R., Zhang, Q., Sklar, P., McCarthy, M. I., Brown, M. A., & Yang, J. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.06.005 · Cited by 3,719 · cited 2× · see citing works
“Many studies of psychiatric disorders (Corvin et al., 2010; Sullivan et al., 2018; Visscher et al., 2017).”
Background(2013) · The Lancet · doi:10.1016/s0140-6736(12)62129-1 · Cited by 3,010 · see citing works
eQTLGen, Wray, N. R., 23andMe, the Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Ripke, S., Mattheisen, M., Trzaskowski, M., Byrne, E. M., Abdellaoui, A., Adams, M. J., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0090-3 · Cited by 3,005 · see citing works
Khera, A. V., Chaffin, M., Aragam, K. G., Haas, M. E., Roselli, C., Choi, S. H., Natarajan, P., Lander, E. S., Lubitz, S. A., Ellinor, P. T., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0183-z · Cited by 2,953 · cited 1× · see citing works
“, for prostate cancer, breast cancer, cardiovascular disease, and type 2 diabetes mellitus) (Grönberg et al., 2015; Khera et al., 2018; McCarthy and Mahajan, 2018; Shieh et al., 2016).”
BackgroundStrong association of de novo copy number mutations with autism
Sebat, J., Lakshmi, B., Malhotra, D., Troge, J., Lese-Martin, C., Walsh, T., Yamrom, B., Yoon, S., Krasnitz, A., Kendall, J., et al. (2007) · Science · doi:10.1126/science.1138659 · Cited by 2,795 · cited 14× · see citing works
“CNVs associated with psychiatric disorders share several commonalities: (1) they usually contain multiple genes (with a few exceptions; Bucan et al., 2009; Talkowski et al., 2011); (2) they are usually >500 kb in size (although many we expect that many smaller CNVs will be found using WGS), and the major pathogenic me…”
BackgroundInfluentialSelf-citationA survey of best practices for RNA-seq data analysis
Conesa, A., Madrigal, P., Tarazona, S., Gomez-Cabrero, D., Cervera, A., McPherson, A., Szcześniak, M. W., Gaffney, D. J., Elo, L. L., Zhang, X., et al. (2016) · Genome Biology · doi:10.1186/s13059-016-0881-8 · Cited by 2,794 · cited 1× · see citing works
“Many are highly tissue or stage specific (Conesa et al., 2016; Nica and Dermitzakis, 2013).”
BackgroundSynaptic, transcriptional and chromatin genes disrupted in autism
Study, T. D., De Rubeis, S., Autism, H. M. C. F., UK10K Consortium, The Autism Sequencing Consortium, He, X., Goldberg, A. P., Poultney, C. S., Samocha, K., Ercument Cicek, A., et al. (2014) · Nature · doi:10.1038/nature13772 · Cited by 2,746 · see citing works
The accessible chromatin landscape of the human genome
Thurman, R. E., Rynes, E., Humbert, R., Vierstra, J., Maurano, M. T., Haugen, E., Sheffield, N. C., Stergachis, A. B., Wang, H., Vernot, B., et al. (2012) · Nature · doi:10.1038/nature11232 · Cited by 2,679 · cited 1× · see citing works
“From Variant to Gene Becausemost genetic variation that contributes to commonpsychiatric disorders is not in protein-coding regions, a crucial step in understanding disease mechanisms is pinpointing the genes impacted by risk variants (Thurman et al., 2012; Visel et al., 2009).”
BackgroundThe contribution of de novo coding mutations to autism spectrum disorder
Iossifov, I., O’Roak, B. J., Sanders, S. J., Ronemus, M., Krumm, N., Levy, D., Stessman, H. A., Witherspoon, K. T., Vives, L., Patterson, K. E., et al. (2014) · Nature · doi:10.1038/nature13908 · Cited by 2,585 · see citing works
Large-scale copy number polymorphism in the human genome
Sebat, J., Lakshmi, B., Troge, J., Alexander, J., Young, J., Lundin, P., Månér, S., Massa, H., Walker, M., Chi, M., et al. (2004) · Science · doi:10.1126/science.1098918 · Cited by 2,557 · see citing works
Meta-analysis of the heritability of human traits based on fifty years of twin studies
Polderman, T. J. C., Benyamin, B., de Leeuw, C. A., Sullivan, P. F., van Bochoven, A., Visscher, P. M., & Posthuma, D. (2015) · Nature Genetics · doi:10.1038/ng.3285 · Cited by 2,467 · cited 1× · see citing works
“The most reproducible single clue that emerged was the tendency for psychiatric disorders to ‘‘run’’ in families—as established by 50+ years of twin, family, and adoption studies (summarized in Table 1) (Polderman et al., 2015).”
BackgroundSelf-citationIdentification of common genetic risk variants for autism spectrum disorder
Autism Spectrum Disorder Working Group of the Psychiatric Genomics Consortium, Grove, J., BUPGEN, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, 23andMe Research Team, Ripke, S., Als, T. D., Mattheisen, M., Walters, R. K., Won, H., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0344-8 · Cited by 2,421 · cited 1× · see citing works
“The importance of the fetal period for ASD is supported by GWAS results integrated with regulatory chromatin interactions and gene expression, which show enrichment of enhancer marks in the fetal brain and higher expression of ASD target genes during fetal corticogenesis (Grove et al., 2019).”
ResultSelf-citationSchizophrenia risk from complex variation of complement component 4
Sekar, A., Bialas, A. R., de Rivera, H., Davis, A., Hammond, T. R., Kamitaki, N., Tooley, K., Presumey, J., Baum, M., Van Doren, V., et al. (2016) · Nature · doi:10.1038/nature16549 · Cited by 2,394 · see citing works
Satterstrom, F. K., Kosmicki, J. A., Wang, J., Breen, M. S., De Rubeis, S., An, J.-Y., Peng, M., Collins, R., Grove, J., Klei, L., et al. (2018) · doi:10.1101/484113 · Cited by 2,323 · see citing works
Self-citationSatterstrom, F. K., Kosmicki, J. A., Wang, J., Breen, M. S., De Rubeis, S., An, J.-Y., Peng, M., Collins, R., Grove, J., Klei, L., et al. (2020) · Cell · doi:10.1016/j.cell.2019.12.036 · Cited by 2,321 · see citing works
Self-citationGenetic relationship between five psychiatric disorders estimated from genome-wide SNPs
Cross-Disorder Group of the Psychiatric Genomics Consortium (2013) · Nature Genetics · doi:10.1038/ng.2711 · Cited by 2,263 · see citing works
Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations
O’Roak, B. J., Vives, L., Girirajan, S., Karakoc, E., Krumm, N., Coe, B. P., Levy, R., Ko, A., Lee, C., Smith, J. D., et al. (2012) · Nature · doi:10.1038/nature10989 · Cited by 2,165 · cited 3× · see citing works
“Despite these limitations, several studies in ASD and SCZ highlight the power of using transcriptional networks based on normal human brain tissue across development or brain regions ormore generalized PPIs (Hormozdiari et al., 2015; Li et al., 2014; Lin et al., 2015) to identify molecular pathways, developmental epoc…”
BackgroundDe novo mutations revealed by whole-exome sequencing are strongly associated with autism
Sanders, S. J., Murtha, M. T., Gupta, A. R., Murdoch, J. D., Raubeson, M. J., Willsey, A. J., Ercan-Sencicek, A. G., DiLullo, N. M., Parikshak, N. N., Stein, J. L., et al. (2012) · Nature · doi:10.1038/nature10945 · Cited by 2,084 · cited 1× · see citing works
“This is particularly salient for autism spectrum disorder (ASD), where a large effect variant is present in 15% of cases, along with smaller proportions of individuals with Tourette’s syndrome (TS), attention-deficit hyperactivity disorder (ADHD), and schizophrenia (SCZ) (Iossifov et al., 2012; Sanders et al., 2012; S…”
BackgroundSelf-citationOrigins and functional impact of copy number variation in the human genome
The Wellcome Trust Case Control Consortium, Conrad, D. F., Pinto, D., Redon, R., Feuk, L., Gokcumen, O., Zhang, Y., Aerts, J., Andrews, T. D., Barnes, C., et al. (2010) · Nature · doi:10.1038/nature08516 · Cited by 1,970 · see citing works
Analysis of shared heritability in common disorders of the brain
The Brainstorm Consortium, Anttila, V., Bulik-Sullivan, B., Finucane, H. K., Walters, R. K., Bras, J., Duncan, L., Escott-Price, V., Falcone, G. J., Gormley, P., et al. (2018) · Science · doi:10.1126/science.aap8757 · Cited by 1,924 · see citing works
Self-citationTranscriptomic Analysis of Autistic Brain Reveals Convergent Molecular Pathology
Voineagu, I., Wang, X., Johnston, P., Lowe, J. K., Tian, Y., Horvath, S., Mill, J., Cantor, R. M., Blencowe, B. J., & Geschwind, D. H. (2011) · Nature · doi:10.1038/nature10110 · Cited by 1,874 · cited 1× · see citing works
“In ASD, these analyses, replicated using different methods and samples, implicate synaptic and neuronal signaling pathways overlapping with other causal gene-based network methods (Parikshak et al., 2016; Voineagu et al., 2011).”
ResultSelf-citationAdvances in autism genetics: on the threshold of a new neurobiology
Abrahams, B. S., & Geschwind, D. H. (2008) · Nature Reviews Genetics · doi:10.1038/nrg2346 · Cited by 1,866 · see citing works
Self-citationThe personal and clinical utility of polygenic risk scores
Torkamani, A., Wineinger, N. E., & Topol, E. J. (2018) · Nature Reviews Genetics · doi:10.1038/s41576-018-0018-x · Cited by 1,605 · cited 1× · see citing works
“Multiple clinical questions could be addressed: for an individual with multiple comorbidities (ADHD, ASD, OCD), do the three GRSs indicate that one is the logical focus of treatment? Should this person with MDD and a high BIP GRS receive a mood stabilizer, as well as an antidepressant? Can we identify people with post…”
BackgroundSeedat, S., Scott, K. M., Angermeyer, M. C., Berglund, P., Bromet, E. J., Brugha, T. S., Demyttenaere, K., de Girolamo, G., Haro, J. M., Jin, R., et al. (2009) · Archives of General Psychiatry · doi:10.1001/archgenpsychiatry.2009.36 · Cited by 1,518 · cited 1× · see citing works
“Many psychiatric disorders show a different prevalence or onset in males and females (Seedat et al., 2009).”
BackgroundA User's Guide to the Encyclopedia of DNA Elements (ENCODE)
The ENCODE Project Consortium (2011) · PLoS Biology · doi:10.1371/journal.pbio.1001046 · Cited by 1,495 · see citing works
De Novo Gene Disruptions in Children on the Autistic Spectrum
Iossifov, I., Ronemus, M., Levy, D., Wang, Z., Hakker, I., Rosenbaum, J., Yamrom, B., Lee, Y.-H., Narzisi, G., Leotta, A., et al. (2012) · Neuron · doi:10.1016/j.neuron.2012.04.009 · Cited by 1,446 · see citing works
Insights into autism spectrum disorder genomic architecture and biology from 71 risk loci
Sanders, S. J., He, X., Willsey, A. J., Ercan-Sencicek, A. G., Samocha, K. E., Cicek, A. E., Murtha, M. T., Bal, V. H., Bishop, S. L., Dong, S., et al. (2015) · Neuron · doi:10.1016/j.neuron.2015.09.016 · Cited by 1,430 · see citing works
Self-citationAutism spectrum disorders: developmental disconnection syndromes
Geschwind, D. H., & Levitt, P. (2007) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2007.01.009 · Cited by 1,411 · cited 1× · see citing works
“These pleiotropic large-effect mutations may work by disrupting key neurodevelopmental processes rather than specifically causing one defined clinical disorder (Geschwind and Levitt, 2007).”
BackgroundSelf-citationHuman Demographic History Impacts Genetic Risk Prediction across Diverse Populations
Martin, A. R., Gignoux, C. R., Walters, R. K., Wojcik, G. L., Neale, B. M., Gravel, S., Daly, M. J., Bustamante, C. D., & Kenny, E. E. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.03.004 · Cited by 1,391 · see citing works
A polygenic burden of rare disruptive mutations in schizophrenia
Purcell, S. M., Moran, J. L., Fromer, M., Ruderfer, D., Solovieff, N., Roussos, P., O’Dushlaine, C., Chambert, K., Bergen, S. E., Kähler, A., et al. (2014) · Nature · doi:10.1038/nature12975 · Cited by 1,385 · cited 2× · see citing works
“However, direct comparisons of the contributions of common and rare genetic variation show that common variation dominates heritable risk for SCZ and ASD (Gaugler et al., 2014; Purcell et al., 2014).”
BackgroundSelf-citationSanders, S. J., Ercan-Sencicek, A. G., Hus, V., Luo, R., Murtha, M. T., Moreno-De-Luca, D., Chu, S. H., Moreau, M. P., Gupta, A. R., Thomson, S. A., et al. (2011) · Neuron · doi:10.1016/j.neuron.2011.05.002 · Cited by 1,263 · see citing works
Self-citationTranscriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder
Gandal, M. J., Zhang, P., Hadjimichael, E., Walker, R. L., Chen, C., Liu, S., Won, H., van Bakel, H., Varghese, M., Wang, Y., et al. (2018) · Science · doi:10.1126/science.aat8127 · Cited by 1,247 · see citing works
Self-citationMost genetic risk for autism resides with common variation
Gaugler, T., Klei, L., Sanders, S. J., Bodea, C. A., Goldberg, A. P., Lee, A. B., Mahajan, M., Manaa, D., Pawitan, Y., Reichert, J., et al. (2014) · Nature Genetics · doi:10.1038/ng.3039 · Cited by 1,239 · cited 2× · see citing works
“However, direct comparisons of the contributions of common and rare genetic variation show that common variation dominates heritable risk for SCZ and ASD (Gaugler et al., 2014; Purcell et al., 2014).”
BackgroundGenetic architectures of psychiatric disorders: the emerging picture and its implications
Sullivan, P. F., Daly, M. J., & O'Donovan, M. (2012) · Nature Reviews Genetics · doi:10.1038/nrg3240 · Cited by 1,177 · see citing works
Self-citationOrganizational principles of 3D genome architecture
Rowley, M. J., & Corces, V. G. (2018) · Nature Reviews Genetics · doi:10.1038/s41576-018-0060-8 · Cited by 1,171 · see citing works
Mapping copy number variation by population-scale genome sequencing
1000 Genomes Project, Mills, R. E., Walter, K., Stewart, C., Handsaker, R. E., Chen, K., Alkan, C., Abyzov, A., Yoon, S. C., Ye, K., et al. (2011) · Nature · doi:10.1038/nature09708 · Cited by 1,140 · see citing works
Genome-Wide Quantitative Enhancer Activity Maps Identified by STARR-seq
Arnold, C. D., Gerlach, D., Stelzer, C., Boryń, Ł. M., Rath, M., & Stark, A. (2013) · Science · doi:10.1126/science.1232542 · Cited by 1,125 · cited 1× · see citing works
“Techniques such as self-transcribing active-regulatory-region sequencing (STARR-seq) permit large-scale validation (which suggests enhancer functionality) (Arnold et al., 2013; Liu et al., 2017b), while analysis in an appropriate cell type with epigenome-editing technologies can confirm target identity (de la Torre-Ub…”
MethodFinucane, H. K., Reshef, Y. A., Anttila, V., Slowikowski, K., Gusev, A., Byrnes, A., Gazal, S., Loh, P.-R., Lareau, C., Shoresh, N., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0081-4 · Cited by 1,097 · see citing works
Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlap
Gandal, M. J., Haney, J. R., Parikshak, N. N., Leppa, V., Ramaswami, G., Hartl, C., Schork, A. J., Appadurai, V., Buil, A., Werge, T. M., et al. (2018) · Science · doi:10.1126/science.aad6469 · Cited by 1,095 · see citing works
Self-citationGene expression elucidates functional impact of polygenic risk for schizophrenia
Fromer, M., Roussos, P., Sieberts, S. K., Johnson, J. S., Kavanagh, D. H., Perumal, T. M., Ruderfer, D. M., Oh, E. C., Topol, A., Shah, H. R., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4399 · Cited by 1,091 · cited 1× · see citing works
“Similar network analysis based on gene co-expression identifies transcriptional networks dysregulated in SCZ, including co-expressed neuronal genes enriched for both common and rare SCZ-associated variants (Fromer et al., 2016).”
BackgroundSelf-citationExploring the three-dimensional organization of genomes: Interpreting chromatin interaction data
Dekker, J., Marti-Renom, M. A., & Mirny, L. A. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3454 · Cited by 1,068 · see citing works
Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects
Marshall, C. R., Howrigan, D. P., Merico, D., Thiruvahindrapuram, B., Wu, W., Greer, D. S., Antaki, D., Shetty, A., Holmans, P. A., Pinto, D., et al. (2017) · Nature Genetics · doi:10.1038/ng.3725 · Cited by 1,058 · see citing works
Integrative functional genomic analyses implicate specific molecular pathways and circuits in autism
Parikshak, N. N., Luo, R., Zhang, A., Won, H., Lowe, J. K., Chandran, V., Horvath, S., & Geschwind, D. H. (2013) · Cell · doi:10.1016/j.cell.2013.10.031 · Cited by 1,039 · cited 5× · see citing works
“One approach to this problem integrates prior information, such as gene or protein-protein interaction (PPI) networks to boost the signal of missense variation (Parikshak et al., 2013).”
BackgroundInfluentialSelf-citationA framework for the interpretation of de novo mutation in human disease
Samocha, K. E., Robinson, E. B., Sanders, S. J., Stevens, C., Sabo, A., McGrath, L. M., Kosmicki, J. A., Rehnström, K., Mallick, S., Kirby, A., et al. (2014) · Nature Genetics · doi:10.1038/ng.3050 · Cited by 979 · cited 1× · see citing works
“Furthermore, the effects of PTVs can be assessed in a functional and evolutionary context (loss of one copy of the gene and the degree of constraint) (Samocha et al., 2014), while the functional impact of individual missense mutations is harder to determine.”
BackgroundComprehensive functional genomic resource and integrative model for the human brain
Wang, D., Liu, S., Warrell, J., Won, H., Shi, X., Navarro, F. C. P., Clarke, D., Gu, M., Emani, P., Yang, Y. T., et al. (2018) · Science · doi:10.1126/science.aat8464 · Cited by 965 · see citing works
Self-citationAnalysis of 6,515 exomes reveals the recent origin of most human protein-coding variants
Fu, W., O’Connor, T. D., Jun, G., Kang, H. M., Abecasis, G. R., Leal, S. M., Gabriel, S., Rieder, M. J., Altshuler, D., Shendure, J., et al. (2012) · Nature · doi:10.1038/nature11690 · Cited by 951 · see citing works
Willsey, A. J., Sanders, S. J., Li, M., Dong, S., Tebbenkamp, A. T., Muhle, R. A., Reilly, S. K., Lin, L., Fertuzinhos, S., Miller, J. A., et al. (2013) · Cell · doi:10.1016/j.cell.2013.10.020 · Cited by 934 · see citing works
Zheng, J., Erzurumluoglu, A. M., Elsworth, B. L., Kemp, J. P., Howe, L., Haycock, P. C., Hemani, G., Tansey, K., Laurin, C., Early Genetics and Lifecourse Epidemiology (EAGLE) Eczema Consortium, et al. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btw613 · Cited by 869 · see citing works
Sparse whole-genome sequencing identifies two loci for major depressive disorder
CONVERGE consortium, Cai, N., Bigdeli, T. B., Kretzschmar, W., Li, Y., Liang, J., Song, L., Hu, J., Li, Q., Jin, W., et al. (2015) · Nature · doi:10.1038/nature14659 · Cited by 864 · see citing works
CNVs: Harbingers of a Rare Variant Revolution in Psychiatric Genetics
Malhotra, D., & Sebat, J. (2012) · Cell · doi:10.1016/j.cell.2012.02.039 · Cited by 854 · cited 2× · see citing works
“Larger de novo CNVs, especially ones that disrupt genes or change gene dosages, can carry major risks, particularly for neurodevelopmental disorders (Malhotra and Sebat, 2012; Sebat et al., 2007).”
BackgroundAdvancing the understanding of autism disease mechanisms through genetics
de la Torre-Ubieta, L., Won, H., Stein, J. L., & Geschwind, D. H. (2016) · Nature Medicine · doi:10.1038/nm.4071 · Cited by 827 · see citing works
Self-citationIntegrative functional genomic analysis of human brain development and neuropsychiatric risks
Li, M., Santpere, G., Imamura Kawasawa, Y., Evgrafov, O. V., Gulden, F. O., Pochareddy, S., Sunkin, S. M., Li, Z., Shin, Y., Zhu, Y., et al. (2018) · Science · doi:10.1126/science.aat7615 · Cited by 810 · see citing works
Self-citationA Single-Cell Atlas of In Vivo Mammalian Chromatin Accessibility
Cusanovich, D. A., Hill, A. J., Aghamirzaie, D., Daza, R. M., Pliner, H. A., Berletch, J. B., Filippova, G. N., Huang, X., Christiansen, L., DeWitt, W. S., et al. (2018) · Cell · doi:10.1016/j.cell.2018.06.052 · Cited by 759 · see citing works
Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways
The Network and Pathway Analysis Subgroup of the Psychiatric Genomics Consortium (2015) · Nature Neuroscience · doi:10.1038/nn.3922 · Cited by 755 · see citing works
the 4D Nucleome Network, Dekker, J., Belmont, A. S., Guttman, M., Leshyk, V. O., Lis, J. T., Lomvardas, S., Mirny, L. A., O’Shea, C. C., Park, P. J., et al. (2017) · Nature · doi:10.1038/nature23884 · Cited by 732 · see citing works
The Simons Simplex Collection: a resource for identification of autism genetic risk factors
Fischbach, G. D., & Lord, C. (2010) · Neuron · doi:10.1016/j.neuron.2010.10.006 · Cited by 725 · cited 2× · see citing works
“The need for unprecedented levels of cooperation became widely recognized (Cichon et al., 2009; Fischbach and Lord, 2010; Geschwind et al., 2001; Lajonchere and AGRE Consortium, 2010; Moldin, 2003; Psychiatric GWAS Consortium Steering Committee, 2009).”
BackgroundGilman, S. R., Iossifov, I., Levy, D., Ronemus, M., Wigler, M., & Vitkup, D. (2011) · Neuron · doi:10.1016/j.neuron.2011.05.021 · Cited by 701 · cited 1× · see citing works
“, 2012); integration of protein, gene expression, and phenotype data (Gilman et al., 2011; Hormozdiari et al., 2015); and chromatin marks (Sun et al.”
BackgroundCNVs conferring risk of autism or schizophrenia affect cognition in controls
Stefansson, H., Meyer-Lindenberg, A., Steinberg, S., Magnusdottir, B., Morgen, K., Arnarsdottir, S., Bjornsdottir, G., Walters, G. B., Jonsdottir, G. A., Doyle, O. M., et al. (2014) · Nature · doi:10.1038/nature12818 · Cited by 699 · cited 2× · see citing works
“variable, ranging from subtle effects detectable by neuropsychological tests to mild degrees of anxiety/ADHD to co-occurrence of severe psychiatric disorders (Kendall et al., 2017; Stefansson et al., 2014; Ulfarsson et al., 2017).”
BackgroundGenome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism
Parikshak, N. N., Swarup, V., Belgard, T. G., Irimia, M., Ramaswami, G., Gandal, M. J., Hartl, C., Leppa, V., Ubieta, L. D. L. T., Huang, J., et al. (2016) · Nature · doi:10.1038/nature20612 · Cited by 685 · see citing works
Self-citationPsychiatric Genomics: An Update and an Agenda
Sullivan, P. F., Agrawal, A., Bulik, C. M., Andreassen, O. A., Børglum, A. D., Breen, G., Cichon, S., Edenberg, H. J., Faraone, S. V., Gelernter, J., et al. (2018) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2017.17030283 · Cited by 676 · see citing works
Self-citationComparative genetic architectures of schizophrenia in East Asian and European populations
Schizophrenia Working Group of the Psychiatric Genomics Consortium, Lam, M., Indonesia Schizophrenia Consortium, Genetic REsearch on schizophreniA neTwork-China and the Netherlands (GREAT-CN), Chen, C.-Y., Li, Z., Martin, A. R., Bryois, J., Ma, X., Gaspar, H., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0512-x · Cited by 655 · see citing works
Self-citationGenetic identification of brain cell types underlying schizophrenia
Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Skene, N. G., Bryois, J., Bakken, T. E., Breen, G., Crowley, J. J., Gaspar, H. A., Giusti-Rodriguez, P., Hodge, R. D., Miller, J. A., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0129-5 · Cited by 651 · see citing works
Self-citationAn abundance of rare functional variants in 202 drug target genes sequenced in 14,002 people
Nelson, M. R., Wegmann, D., Ehm, M. G., Kessner, D., St. Jean, P., Verzilli, C., Shen, J., Tang, Z., Bacanu, S.-A., Fraser, D., et al. (2012) · Science · doi:10.1126/science.1217876 · Cited by 647 · see citing works
Searching for missing heritability: Designing rare variant association studies
Zuk, O., Schaffner, S. F., Samocha, K., Do, R., Hechter, E., Kathiresan, S., Daly, M. J., Neale, B. M., Sunyaev, S. R., & Lander, E. S. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1322563111 · Cited by 635 · see citing works
Border, R., Johnson, E. C., Evans, L. M., Smolen, A., Berley, N., Sullivan, P. F., & Keller, M. C. (2019) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2018.18070881 · Cited by 629 · see citing works
Self-citationRare and low-frequency coding variants alter human adult height
Marouli, E., Graff, M., Medina-Gomez, C., Lo, K. S., Wood, A. R., Kjaer, T. R., Fine, R. S., Lu, Y., Schurmann, C., Highland, H. M., et al. (2017) · Nature · doi:10.1038/nature21039 · Cited by 610 · see citing works
Genomic views of distant-acting enhancers
Visel, A., Rubin, E. M., & Pennacchio, L. A. (2009) · Nature · doi:10.1038/nature08451 · Cited by 610 · see citing works
Diagnostic Clinical Genome and Exome Sequencing
Biesecker, L. G., & Green, R. (2014) · New England Journal of Medicine · doi:10.1056/nejmra1312543 · Cited by 607 · cited 1× · see citing works
“WES has identified 100 genes for ASD and an increased ‘‘burden’’ of rare, protein-altering genetic variation differing between cases and controls in SCZ and a few other disorders (Biesecker and Green, 2014; Warr et al. 2015).”
BackgroundExcess of rare, inherited truncating mutations in autism
Krumm, N., Turner, T. N., Baker, C., Vives, L., Mohajeri, K., Witherspoon, K., Raja, A., Coe, B. P., Stessman, H. A., He, Z.-X., et al. (2015) · Nature Genetics · doi:10.1038/ng.3303 · Cited by 587 · cited 1× · see citing works
“Although there is likely a role for rare inherited variation in ASD (Krumm et al., 2015), few studies have identified significant signals based on inherited risk variants for specific genes.”
BackgroundChromosome conformation elucidates regulatory relationships in developing human brain
Won, H., de la Torre-Ubieta, L., Stein, J. L., Parikshak, N. N., Huang, J., Opland, C. K., Gandal, M. J., Sutton, G. J., Hormozdiari, F., Lu, D., et al. (2016) · Nature · doi:10.1038/nature19847 · Cited by 584 · cited 8× · see citing works
“Crucially, recent studies have shown that genes located far outside of a locus are often implicated (see Functional Architecture section below) (Wang et al., 2018a; Won et al., 2016).”
BackgroundInfluentialSelf-citationSex and gender differences in mental disorders
Riecher-Rössler, A. (2017) · The Lancet Psychiatry · doi:10.1016/s2215-0366(16)30348-0 · Cited by 560 · cited 2× · see citing works
“…genetic and functional genomic evidence suggests the presence of female protective factors based in brain function and structure (Robinson et al., 2013; Werling and Geschwind, 2013; Werling et al., 2016), whereas in MDD or ALC, social factors likely may have a larger role (Riecher-Rössler, 2017).”
BackgroundGulsuner, S., Walsh, T., Watts, A. C., Lee, M. K., Thornton, A. M., Casadei, S., Rippey, C., Shahin, H., Braff, D., Cadenhead, K. S., et al. (2013) · Cell · doi:10.1016/j.cell.2013.06.049 · Cited by 536 · see citing works
Diagnostic Clinical Genome and Exome Sequencing
Westerink, J., Visseren, F. L. J., & Spiering, W. (2014) · New England Journal of Medicine · doi:10.1056/nejmc1408914 · Cited by 532 · see citing works
Examining and interpreting the female protective effect against autistic behavior
Robinson, E. B., Lichtenstein, P., Anckarsäter, H., Happé, F., & Ronald, A. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1211070110 · Cited by 531 · cited 1× · see citing works
“For example, in ASD, genetic and functional genomic evidence suggests the presence of female protective factors based in brain function and structure (Robinson et al., 2013; Werling and Geschwind, 2013; Werling et al., 2016), whereas in MDD or ALC, social factors likely may have a larger role (Riecher-Rössler, 2017).”
BackgroundCortical Evolution: Judge the Brain by Its Cover
Geschwind, D. H., & Rakic, P. (2013) · Neuron · doi:10.1016/j.neuron.2013.10.045 · Cited by 519 · cited 2× · see citing works
“…genetic and functional genomic evidence suggests the presence of female protective factors based in brain function and structure (Robinson et al., 2013; Werling and Geschwind, 2013; Werling et al., 2016), whereas in MDD or ALC, social factors likely may have a larger role (Riecher-Rössler, 2017).”
BackgroundSelf-citationiPSYCH-Broad Autism Group, Weiner, D. J., Psychiatric Genomics Consortium Autism Group, Wigdor, E. M., Ripke, S., Walters, R. K., Kosmicki, J. A., Grove, J., Samocha, K. E., Goldstein, J. I., et al. (2017) · Nature Genetics · doi:10.1038/ng.3863 · Cited by 516 · see citing works
A Single-Cell Transcriptomic Atlas of Human Neocortical Development during Mid-gestation
Polioudakis, D., de la Torre-Ubieta, L., Langerman, J., Elkins, A. G., Shi, X., Stein, J. L., Vuong, C. K., Nichterwitz, S., Gevorgian, M., Opland, C. K., et al. (2019) · Neuron · doi:10.1016/j.neuron.2019.06.011 · Cited by 513 · see citing works
Self-citationGeschwind, D. H. (2009) · Annual Review of Medicine · doi:10.1146/annurev.med.60.053107.121225 · Cited by 512 · cited 2× · see citing works
“…also decrease IQ, and ID is an important comorbidity of ASD (Buja et al., 2018; Iossifov et al., 2014), which is consistent with previous work identifying dozens of known severe, rare medical genetic syndromes associated with ASD (reviewed in Abrahams and Geschwind, 2008; Geschwind, 2009).”
ResultSelf-citationHigh Rates of Psychiatric Co-Morbidity in PDD-NOS
de Bruin, E. I., Ferdinand, R. F., Meester, S., de Nijs, P. F. A., & Verheij, F. (2006) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-006-0215-x · Cited by 509 · see citing works
Expression quantitative trait loci: present and future
Nica, A. C., & Dermitzakis, E. T. (2013) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2012.0362 · Cited by 498 · cited 1× · see citing works
“Many are highly tissue or stage specific (Conesa et al., 2016; Nica and Dermitzakis, 2013).”
BackgroundGusev, A., Mancuso, N., Won, H., Kousi, M., Finucane, H. K., Reshef, Y., Song, L., Safi, A., Schizophrenia Working Group of the Psychiatric Genomics Consortium, McCarroll, S., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0092-1 · Cited by 491 · see citing works
Self-citationGenome-Wide Scan for Autism Susceptibility Genes
Philippe, A., Martinez, M., Guilloud-Bataille, M., Gillberg, C., Rastam, M., Sponheim, E., Coleman, M., Zappella, M., Aschauer, H., Van Maldergem, L., et al. (1999) · Human Molecular Genetics · doi:10.1093/hmg/8.5.805 · Cited by 471 · see citing works
SPARK: A US Cohort of 50,000 Families to Accelerate Autism Research
Feliciano, P., Daniels, A. M., Snyder, L. G., Beaumont, A. L., Camba, A., Esler, A., Gulsrud, A., Mason, A., Gutierrez, A., Nicholson, A. G., et al. (2018) · Neuron · doi:10.1016/j.neuron.2018.01.015 · Cited by 462 · see citing works
Autism spectrum disorder: outcomes in adulthood
Howlin, P., & Magiati, I. (2017) · Current Opinion in Psychiatry · doi:10.1097/yco.0000000000000308 · Cited by 457 · cited 1× · see citing works
“Most people with ASD in childhood continue to have ASD in adulthood (Billstedt et al., 2007; Howlin and Magiati, 2017).”
BackgroundEnhancer-promoter interactions are encoded by complex genomic signatures on looping chromatin
Whalen, S., Truty, R. M., & Pollard, K. S. (2016) · Nature Genetics · doi:10.1038/ng.3539 · Cited by 456 · cited 1× · see citing works
“A complicating factor is that assigning even well-annotated genomic regions to specific genes is not as simple as choosing the closest gene or genes containing variation that is highly correlated with the associated SNPs, which is usually the default approach (Whalen et al., 2016; Won et al., 2016).”
BackgroundA Genomewide Screen for Autism: Strong Evidence for Linkage to Chromosomes 2q, 7q, and 16p
(2001) · The American Journal of Human Genetics · doi:10.1086/323264 · Cited by 453 · see citing works
Study, S. S., Singh, T., Study, I., Study, D., UK10 K Consortium, Kurki, M. I., Curtis, D., Purcell, S. M., Crooks, L., McRae, J., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4267 · Cited by 452 · see citing works
Self-citationGenomewide Association Studies: History, Rationale, and Prospects for Psychiatric Disorders
Psychiatric GWAS Consortium Coordinating Committee (2009) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2008.08091354 · Cited by 450 · see citing works
Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia
Genovese, G., Fromer, M., Stahl, E. A., Ruderfer, D. M., Chambert, K., Landén, M., Moran, J. L., Purcell, S. M., Sklar, P., Sullivan, P. F., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4402 · Cited by 444 · cited 1× · see citing works
“As noted above, resequencing technologies enable rare-variant discovery in ever-larger samples, and we know now that ultra-rare and de novo single-nucleotide variants contribute to risk (Genovese et al., 2016; Sanders et al., 2015; Satterstrom et al., 2018a; Singh et al., 2016; Wang et al., 2018b; Willsey et al., 2017…”
BackgroundSelf-citationGenetic architecture: the shape of the genetic contribution to human traits and disease
Timpson, N. J., Greenwood, C. M. T., Soranzo, N., Lawson, D. J., & Richards, J. B. (2018) · Nature Reviews Genetics · doi:10.1038/nrg.2017.101 · Cited by 434 · cited 3× · see citing works
“, study design, ascertainment, choice of genotyping technology) (Timpson et al., 2018; Visscher et al., 2012).”
BackgroundSystems biology and gene networks in neurodevelopmental and neurodegenerative disorders
Parikshak, N. N., Gandal, M. J., & Geschwind, D. H. (2015) · Nature Reviews Genetics · doi:10.1038/nrg3934 · Cited by 430 · cited 5× · see citing works
“Despite clear genetic heterogeneity, both ASD risk and SCZ risk converge on shared molecular pathways (Network and Pathway Analysis Subgroup of Psychiatric Genomics Consortium, 2015; Parikshak et al., 2015).”
BackgroundMethodInfluentialSelf-citationGenetics and genomics of psychiatric disease
Geschwind, D. H., & Flint, J. (2015) · Science · doi:10.1126/science.aaa8954 · Cited by 424 · cited 3× · see citing works
“The results to date indicate that psychiatric disorder risk is imparted by many common variants of individually small effects, and several disorders also have contributions from rarer variants with larger impact on risk (Geschwind and Flint, 2015; Sullivan et al., 2018).”
BackgroundInfluentialSelf-citationBucan, M., Abrahams, B. S., Wang, K., Glessner, J. T., Herman, E. I., Sonnenblick, L. I., Alvarez Retuerto, A. I., Imielinski, M., Hadley, D., Bradfield, J. P., et al. (2009) · PLoS Genetics · doi:10.1371/journal.pgen.1000536 · Cited by 424 · cited 1× · see citing works
“CNVs associated with psychiatric disorders share several commonalities: (1) they usually contain multiple genes (with a few exceptions; Bucan et al., 2009; Talkowski et al., 2011); (2) they are usually >500 kb in size (although many we expect that many smaller CNVs will be found using WGS), and the major pathogenic me…”
BackgroundSelf-citationGrönberg, H., Adolfsson, J., Aly, M., Nordström, T., Wiklund, P. N., Brandberg, Y., Thompson, J., Wiklund, F. E., Lindberg, J., Clements, M., et al. (2015) · The Lancet Oncology · doi:10.1016/s1470-2045(15)00361-7 · Cited by 410 · cited 1× · see citing works
“, for prostate cancer, breast cancer, cardiovascular disease, and type 2 diabetes mellitus) (Grönberg et al., 2015; Khera et al., 2018; McCarthy and Mahajan, 2018; Shieh et al., 2016).”
BackgroundSignatures of negative selection in the genetic architecture of human complex traits
Zeng, J., de Vlaming, R., Wu, Y., Robinson, M. R., Lloyd-Jones, L. R., Yengo, L., Yap, C. X., Xue, A., Sidorenko, J., McRae, A. F., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0101-4 · Cited by 391 · cited 1× · see citing works
“0), are more likely to be deleterious, and tend to be removed by natural selection (Fu et al., 2013; Nelson et al., 2012; Zeng et al., 2018).”
BackgroundThe role of de novo mutations in the genetics of autism spectrum disorders
Ronemus, M., Iossifov, I., Levy, D., & Wigler, M. (2014) · Nature Reviews Genetics · doi:10.1038/nrg3585 · Cited by 390 · cited 1× · see citing works
“While some of these genes are relatively specific to a disorder like ASD, many confer broader phenotype risks (Abrahams and Geschwind, 2008; Ronemus et al., 2014; Satterstrom et al., 2018a).”
BackgroundThe cis-regulatory dynamics of embryonic development at single-cell resolution
Cusanovich, D. A., Reddington, J. P., Garfield, D. A., Daza, R. M., Aghamirzaie, D., Marco-Ferreres, R., Pliner, H. A., Christiansen, L., Qiu, X., Steemers, F. J., et al. (2018) · Nature · doi:10.1038/nature25981 · Cited by 363 · see citing works
The Dynamic Landscape of Open Chromatin during Human Cortical Neurogenesis
de la Torre-Ubieta, L., Stein, J. L., Won, H., Opland, C. K., Liang, D., Lu, D., & Geschwind, D. H. (2018) · Cell · doi:10.1016/j.cell.2017.12.014 · Cited by 353 · see citing works
Self-citationCotney, J., Muhle, R. A., Sanders, S. J., Liu, L., Willsey, A. J., Niu, W., Liu, W., Klei, L., Lei, J., Yin, J., et al. (2015) · Nature Communications · doi:10.1038/ncomms7404 · Cited by 350 · cited 1× · see citing works
“Analysis of transcriptional (Cotney et al., 2015; Sugathan et al., 2014), splicing (Berto et al.”
BackgroundSugathan, A., Biagioli, M., Golzio, C., Erdin, S., Blumenthal, I., Manavalan, P., Ragavendran, A., Brand, H., Lucente, D., Miles, J., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1405266111 · Cited by 342 · cited 1× · see citing works
“Analysis of transcriptional (Cotney et al., 2015; Sugathan et al., 2014), splicing (Berto et al.”
BackgroundCommon genetic variants contribute to risk of rare severe neurodevelopmental disorders
Niemi, M. E. K., Martin, H. C., Rice, D. L., Gallone, G., Gordon, S., Kelemen, M., McAloney, K., McRae, J., Radford, E. J., Yu, S., et al. (2018) · Nature · doi:10.1038/s41586-018-0566-4 · Cited by 340 · cited 1× · see citing works
“In the instances where this has been studied directly, polygenic risk acts additively with major mutational burdens (Gaugler et al., 2014; Niemi et al., 2018; Purcell et al., 2014; Weiner et al., 2017).”
BackgroundRedin, C., Brand, H., Collins, R. L., Kammin, T., Mitchell, E., Hodge, J. C., Hanscom, C., Pillalamarri, V., Seabra, C. M., Abbott, M.-A., et al. (2017) · Nature Genetics · doi:10.1038/ng.3720 · Cited by 334 · cited 1× · see citing works
“WGSprovides substantially more genome coverage and resolution, especially with regard to certain forms of chromosomal structural variation (Redin et al., 2017), but at an order of magnitude cost more than SNP arrays.”
BackgroundWeyn-Vanhentenryck, S. M., Mele, A., Yan, Q., Sun, S., Farny, N., Zhang, Z., Xue, C., Herre, M., Silver, P. A., Zhang, M. Q., et al. (2014) · Cell Reports · doi:10.1016/j.celrep.2014.02.005 · Cited by 333 · cited 1× · see citing works
“, 2014), splicing (Berto et al., 2016; Fogel et al., 2012; Weyn-Vanhentenryck et al., 2014), or signaling (Tian et al.”
BackgroundEvaluating historical candidate genes for schizophrenia
Farrell, M. S., Werge, T., Sklar, P., Owen, M. J., Ophoff, R. A., O'Donovan, M. C., Corvin, A., Cichon, S., & Sullivan, P. F. (2015) · Molecular Psychiatry · doi:10.1038/mp.2015.16 · Cited by 315 · cited 2× · see citing works
“Compared to current knowledge, the reproducible yield of candidate gene-association studies is negligible (Farrell et al., 2015).”
BackgroundSelf-citationBillstedt, E., Carina Gillberg, I., & Gillberg, C. (2007) · Journal of Child Psychology and Psychiatry · doi:10.1111/j.1469-7610.2007.01774.x · Cited by 309 · see citing works
Histone Acetylome-wide Association Study of Autism Spectrum Disorder
Sun, W., Poschmann, J., Cruz-Herrera del Rosario, R., Parikshak, N. N., Hajan, H. S., Kumar, V., Ramasamy, R., Belgard, T. G., Elanggovan, B., Wong, C. C. Y., et al. (2016) · Cell · doi:10.1016/j.cell.2016.10.031 · Cited by 306 · see citing works
Self-citationGeschwind, D. H., Sowinski, J., Lord, C., Iversen, P., Shestack, J., Jones, P., Ducat, L., & Spence, S. J. (2001) · The American Journal of Human Genetics · doi:10.1086/321292 · Cited by 302 · see citing works
Self-citationGene expression in human brain implicates sexually dimorphic pathways in autism spectrum disorders
Werling, D. M., Parikshak, N. N., & Geschwind, D. H. (2016) · Nature Communications · doi:10.1038/ncomms10717 · Cited by 296 · cited 1× · see citing works
“For example, in ASD, genetic and functional genomic evidence suggests the presence of female protective factors based in brain function and structure (Robinson et al., 2013; Werling and Geschwind, 2013; Werling et al., 2016), whereas in MDD or ALC, social factors likely may have a larger role (Riecher-Rössler, 2017).”
Self-citationEcker, J. R., Bickmore, W. A., Barroso, I., Pritchard, J. K., Gilad, Y., & Segal, E. (2012) · Nature · doi:10.1038/489052a · Cited by 278 · cited 3× · see citing works
“Main methods are ATAC-seq and DNase-seq (Ecker et al., 2012).”
BackgroundInfluentialDe novo mutations in regulatory elements in neurodevelopmental disorders
Short, P. J., McRae, J. F., Gallone, G., Sifrim, A., Won, H., Geschwind, D. H., Wright, C. F., Firth, H. V., FitzPatrick, D. R., Barrett, J. C., et al. (2018) · Nature · doi:10.1038/nature25983 · Cited by 274 · cited 1× · see citing works
“This is in contrast to comparisons relying on LD blocks or the assignment by the closest gene, where the overlaps with methods that directly assess chromatin are less substantial (Short et al., 2018; Whalen and Pollard, 2018).”
ResultSelf-citationMcConnell, M. J., Moran, J. V., Abyzov, A., Akbarian, S., Bae, T., Cortes-Ciriano, I., Erwin, J. A., Fasching, L., Flasch, D. A., Freed, D., et al. (2017) · Science · doi:10.1126/science.aal1641 · Cited by 262 · cited 1× · see citing works
“Although very expensive and technically complex, single-cell resequencing of nuclei from a tissue can identify somatic mutations that arose during development (these changes are not heritable but may contribute to illness in some individuals) (Evrony et al., 2016; McConnell et al., 2017).”
BackgroundPorter, R. S. (2002) · Cited by 257 · see citing works
Ecker, J. R., Geschwind, D. H., Kriegstein, A. R., Ngai, J., Osten, P., Polioudakis, D., Regev, A., Šestan, N., Wickersham, I. R., & Zeng, H. (2017) · Neuron · doi:10.1016/j.neuron.2017.10.007 · Cited by 254 · cited 1× · see citing works
“This effort is complemented by the BRAIN single-cell atlas of cell types and gene expression in human and mouse (Ecker et al., 2017).”
MethodSelf-citationThe discovery of integrated gene networks for autism and related disorders
Hormozdiari, F., Penn, O., Borenstein, E., & Eichler, E. E. (2015) · Genome Research · doi:10.1101/gr.178855.114 · Cited by 249 · cited 3× · see citing works
“Despite these limitations, several studies in ASD and SCZ highlight the power of using transcriptional networks based on normal human brain tissue across development or brain regions ormore generalized PPIs (Hormozdiari et al., 2015; Li et al., 2014; Lin et al., 2015) to identify molecular pathways, developmental epoc…”
BackgroundTalkowski, M. E., Mullegama, S. V., Rosenfeld, J. A., van Bon, B. W. M., Shen, Y., Repnikova, E. A., Gastier-Foster, J., Thrush, D. L., Kathiresan, S., Ruderfer, D. M., et al. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2011.09.011 · Cited by 249 · cited 1× · see citing works
“CNVs associated with psychiatric disorders share several commonalities: (1) they usually contain multiple genes (with a few exceptions; Bucan et al., 2009; Talkowski et al., 2011); (2) they are usually >500 kb in size (although many we expect that many smaller CNVs will be found using WGS), and the major pathogenic me…”
BackgroundKendall, K. M., Rees, E., Escott-Price, V., Einon, M., Thomas, R., Hewitt, J., O’Donovan, M. C., Owen, M. J., Walters, J. T. R., & Kirov, G. (2017) · Biological Psychiatry · doi:10.1016/j.biopsych.2016.08.014 · Cited by 226 · see citing works
Exome Sequencing: Current and Future Perspectives
Warr, A., Robert, C., Hume, D. A., Archibald, A. L., Deeb, N., & Watson, M. (2015) · G3 Genes Genomes Genetics · doi:10.1534/g3.115.018564 · Cited by 226 · cited 1× · see citing works
“WES has identified 100 genes for ASD and an increased ‘‘burden’’ of rare, protein-altering genetic variation differing between cases and controls in SCZ and a few other disorders (Biesecker and Green, 2014; Warr et al. 2015).”
BackgroundSchork, A. J., Won, H., Appadurai, V., Nudel, R., Gandal, M., Delaneau, O., Revsbech Christiansen, M., Hougaard, D. M., Bækved-Hansen, M., Bybjerg-Grauholm, J., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-018-0320-0 · Cited by 223 · see citing works
Self-citationThe road to precision psychiatry: translating genetics into disease mechanisms
Gandal, M. J., Leppa, V., Won, H., Parikshak, N. N., & Geschwind, D. H. (2016) · Nature Neuroscience · doi:10.1038/nn.4409 · Cited by 223 · cited 1× · see citing works
“Combining network approaches with systems neuroscience permits the methodical connection of heterogeneous genetic risk factors to brain mechanisms (Gandal et al., 2016; Geschwind and Konopka, 2009).”
BackgroundSelf-citationReference standards for next-generation sequencing
Hardwick, S. A., Deveson, I. W., & Mercer, T. R. (2017) · Nature Reviews Genetics · doi:10.1038/nrg.2017.44 · Cited by 223 · see citing works
RBFOX1 regulates both splicing and transcriptional networks in human neuronal development
Fogel, B. L., Wexler, E., Wahnich, A., Friedrich, T., Vijayendran, C., Gao, F., Parikshak, N., Konopka, G., & Geschwind, D. H. (2012) · Human Molecular Genetics · doi:10.1093/hmg/dds240 · Cited by 216 · cited 1× · see citing works
“, 2014), splicing (Berto et al., 2016; Fogel et al., 2012; Weyn-Vanhentenryck et al., 2014), or signaling (Tian et al.”
BackgroundSelf-citationNeuroscience in the era of functional genomics and systems biology
Geschwind, D. H., & Konopka, G. (2009) · Nature · doi:10.1038/nature08537 · Cited by 213 · cited 3× · see citing works
“Few genes act in isolation but rather affect the function of other genes to influence a particular phenotype via in-cellular networks or pathways (Barabási et al., 2011; Geschwind and Konopka, 2009).”
BackgroundResultSelf-citationShared Molecular Neuropathology Across Major Psychiatric Disorders Parallels Polygenic Overlap
Gandal, M. J., Haney, J. R., Parikshak, N., Leppä, V., Ramaswami, G., Hartl, C., Schork, A. J., Appadurai, V., Buil, A., Werge, T. M., et al. (2019) · FOCUS The Journal of Lifelong Learning in Psychiatry · doi:10.1176/appi.focus.17103 · Cited by 209 · see citing works
Self-citationiPSYCH-Broad Consortium, Satterstrom, F. K., Walters, R. K., Singh, T., Wigdor, E. M., Lescai, F., Demontis, D., Kosmicki, J. A., Grove, J., Stevens, C., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0527-8 · Cited by 209 · see citing works
A framework for interpreting genome-wide association studies of psychiatric disorders
The Psychiatric GWAS Consortium Steering Committee (2008) · Molecular Psychiatry · doi:10.1038/mp.2008.126 · Cited by 208 · see citing works
Diverse types of genetic variation converge on functional gene networks involved in schizophrenia
Gilman, S. R., Chang, J., Xu, B., Bawa, T. S., Gogos, J. A., Karayiorgou, M., & Vitkup, D. (2012) · Nature Neuroscience · doi:10.1038/nn.3261 · Cited by 200 · cited 1× · see citing works
“These efforts point at similar pathways and/or convergence of risk loci on similar biological processes (Corominas et al., 2014; Gilman et al., 2012; Li et al., 2014).”
BackgroundA Genetic Investigation of Sex Bias in the Prevalence of Attention-Deficit/Hyperactivity Disorder
Martin, J., Walters, R. K., Demontis, D., Mattheisen, M., Lee, S., Robinson, E., Brikell, I., Ghirardi, L., Larsson, H., Lichtenstein, P., et al. (2017) · Biological Psychiatry · doi:10.1016/j.biopsych.2017.11.026 · Cited by 190 · see citing works
De Novo Coding Variants Are Strongly Associated with Tourette Disorder
Willsey, A. J., Fernandez, T. V., Yu, D., King, R. A., Dietrich, A., Xing, J., Sanders, S. J., Mandell, J. D., Huang, A. Y., Richer, P., et al. (2017) · Neuron · doi:10.1016/j.neuron.2017.04.024 · Cited by 187 · see citing works
Buxbaum, J. D., Daly, M. J., Devlin, B., Lehner, T., Roeder, K., & State, M. W. (2012) · Neuron · doi:10.1016/j.neuron.2012.12.008 · Cited by 185 · see citing works
An atlas of chromatin accessibility in the adult human brainPreprint
Fullard, J. F., Hauberg, M. E., Bendl, J. M., Egervári, G., Cirnaru, M., Reach, S. M., Motl, J., Ehrlich, M. E., Hurd, Y. L., & Roussos, P. (2018) · Genome Research · doi:10.1101/gr.232488.117 · Cited by 180 · cited 1× · see citing works
“Orthogonal functional genomic data are consistent with these findings, as open chromatin in neuronal nuclei (NeuN+) from 14 regions from human adult brain showed significant enrichment of SCZ GWAS findings in cortex and striatum (Fullard et al., 2018), and open chromatin inmouse cortical layers showed SCZ enrichment i…”
ResultProspects for using risk scores in polygenic medicine
Lewis, C., & Vassos, E. (2017) · Genome Medicine · doi:10.1186/s13073-017-0489-y · Cited by 172 · cited 1× · see citing works
“Multiple clinical questions could be addressed: for an individual with multiple comorbidities (ADHD, ASD, OCD), do the three GRSs indicate that one is the logical focus of treatment? Should this person with MDD and a high BIP GRS receive a mood stabilizer, as well as an antidepressant? Can we identify people with post…”
BackgroundLuo, R., Sanders, S. J., Tian, Y., Voineagu, I., Huang, N., Chu, S. H., Klei, L., Cai, C., Ou, J., Lowe, J. K., et al. (2012) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2012.05.011 · Cited by 167 · see citing works
Self-citationResolving rates of mutation in the brain using single-neuron genomics
Evrony, G. D., Lee, E., Park, P. J., & Walsh, C. A. (2016) · eLife · doi:10.7554/elife.12966 · Cited by 163 · cited 1× · see citing works
“Although very expensive and technically complex, single-cell resequencing of nuclei from a tissue can identify somatic mutations that arose during development (these changes are not heritable but may contribute to illness in some individuals) (Evrony et al., 2016; McConnell et al., 2017).”
BackgroundCNVs in neuropsychiatric disorders
Kirov, G. (2015) · Human Molecular Genetics · doi:10.1093/hmg/ddv253 · Cited by 159 · cited 3× · see citing works
“Most known pathogenic CNVs increase risk for multiple disorders (de la TorreUbieta et al., 2016; Kirov, 2015; Lowther et al., 2017; Malhotra and Sebat, 2012).”
BackgroundLevinson, D. F., Mostafavi, S., Milaneschi, Y., Rivera, M., Ripke, S., Wray, N. R., & Sullivan, P. F. (2014) · Biological Psychiatry · doi:10.1016/j.biopsych.2014.07.029 · Cited by 159 · see citing works
Self-citationBreast cancer risk prediction using a clinical risk model and polygenic risk score
Shieh, Y., Hu, D., Ma, L., Huntsman, S., Gard, C. C., Leung, J. W. T., Tice, J. A., Vachon, C. M., Cummings, S. R., Kerlikowske, K. M., et al. (2016) · Breast Cancer Research and Treatment · doi:10.1007/s10549-016-3953-2 · Cited by 157 · cited 1× · see citing works
“, for prostate cancer, breast cancer, cardiovascular disease, and type 2 diabetes mellitus) (Grönberg et al., 2015; Khera et al., 2018; McCarthy and Mahajan, 2018; Shieh et al., 2016).”
BackgroundLin, G. N., Corominas, R., Lemmens, I., Yang, X., Tavernier, J., Hill, D. E., Vidal, M., Sebat, J., & Iakoucheva, L. M. (2015) · Neuron · doi:10.1016/j.neuron.2015.01.010 · Cited by 155 · see citing works
Rare and low-frequency coding variants alter human adult height
Marouli, E., Graff, M., Medina‐Gómez, C., Lo, K. S., Wood, A. R., Kjær, T. R., Fine, R. S., Lu, Y., Schurmann, C., Highland, H. M., et al. (2017) · Carolina Digital Repository (University of North Carolina at Chapel Hill) · doi:10.17615/xzar-z180 · Cited by 151 · see citing works
Corominas, R., Yang, X., Lin, G. N., Kang, S., Shen, Y., Ghamsari, L., Broly, M., Rodriguez, M., Tam, S., Wanamaker, S. A., et al. (2014) · Nature Communications · doi:10.1038/ncomms4650 · Cited by 140 · cited 1× · see citing works
“These efforts point at similar pathways and/or convergence of risk loci on similar biological processes (Corominas et al., 2014; Gilman et al., 2012; Li et al., 2014).”
BackgroundVisscher, P. M., Goddard, M. E., Derks, E. M., & Wray, N. R. (2012) · Molecular Psychiatry · doi:10.1038/mp.2011.65 · Cited by 138 · see citing works
Assessing the evidence for shared genetic risks across psychiatric disorders and traits
Martin, J., Taylor, M. J., & Lichtenstein, P. (2017) · Psychological Medicine · doi:10.1017/s0033291717003440 · Cited by 138 · cited 6× · see citing works
“Multiple clinical questions could be addressed: for an individual with multiple comorbidities (ADHD, ASD, OCD), do the three GRSs indicate that one is the logical focus of treatment?”
ResultInfluentialFunctional assessment of human enhancer activities using whole-genome STARR-sequencing
Liu, Y., Yu, S., Dhiman, V. K., Brunetti, T., Eckart, H., & White, K. P. (2017) · Genome Biology · doi:10.1186/s13059-017-1345-5 · Cited by 136 · cited 1× · see citing works
“Techniques such as self-transcribing active-regulatory-region sequencing (STARR-seq) permit large-scale validation (which suggests enhancer functionality) (Arnold et al., 2013; Liu et al., 2017b), while analysis in an appropriate cell type with epigenome-editing technologies can confirm target identity (de la Torre-Ub…”
MethodUnderstanding sex bias in autism spectrum disorder
Werling, D. M., & Geschwind, D. H. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1301602110 · Cited by 135 · cited 1× · see citing works
“For example, in ASD, genetic and functional genomic evidence suggests the presence of female protective factors based in brain function and structure (Robinson et al., 2013; Werling and Geschwind, 2013; Werling et al., 2016), whereas in MDD or ALC, social factors likely may have a larger role (Riecher-Rössler, 2017).”
BackgroundSelf-citationIntegrated systems analysis reveals a molecular network underlying autism spectrum disorders
Li, J., Shi, M., Ma, Z., Zhao, S., Euskirchen, G., Ziskin, J., Urban, A., Hallmayer, J., & Snyder, M. (2014) · Molecular Systems Biology · doi:10.15252/msb.20145487 · Cited by 132 · cited 3× · see citing works
“These efforts point at similar pathways and/or convergence of risk loci on similar biological processes (Corominas et al., 2014; Gilman et al., 2012; Li et al., 2014).”
BackgroundCommon alleles contribute to schizophrenia in CNV carriers
Tansey, K. E., Rees, E., Linden, D. E., Ripke, S., Chambert, K. D., Moran, J. L., McCarroll, S. A., Holmans, P., Kirov, G., Walters, J., et al. (2016) · Molecular Psychiatry · doi:10.1038/mp.2015.143 · Cited by 132 · see citing works
The Neurodevelopmental Hypothesis of Schizophrenia
Piper, M., Beneyto, M., Burne, T. H. J., Eyles, D. W., Lewis, D. A., & McGrath, J. J. (2012) · Psychiatric Clinics of North America · doi:10.1016/j.psc.2012.06.002 · Cited by 128 · cited 1× · see citing works
“174 Cell 177, March 21, 2019 studies (Glausier and Lewis, 2018; Piper et al., 2012).”
Whole genome sequencing in psychiatric disorders: the WGSPD consortium
(WGSPD), W. G. S. F. P. D., Sanders, S., Neale, B. M., Huang, H., Werling, D. M., An, J., Dong, S., Abecasis, G. R., Arguello, P. A., Blangero, J., et al. (2017) · Nature Neuroscience · doi:10.1038/s41593-017-0017-9 · Cited by 125 · see citing works
Self-citationWang, S., Mandell, J. D., Kumar, Y., Sun, N., Morris, M. T., Arbelaez, J., Nasello, C., Dong, S., Duhn, C., Zhao, X., et al. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.08.082 · Cited by 119 · see citing works
Genome-wide association studies: a primer
Corvin, A. P., Craddock, N. J., & Sullivan, P. F. (2009) · Psychological Medicine · doi:10.1017/s0033291709991723 · Cited by 111 · cited 1× · see citing works
“Many studies of psychiatric disorders (Corvin et al., 2010; Sullivan et al., 2018; Visscher et al., 2017).”
Self-citationNetSig: network-based discovery from cancer genomes
Horn, H., Lawrence, M. S., Chouinard, C. R., Shrestha, Y., Hu, J. X., Worstell, E., Shea, E., Ilic, N., Kim, E., Kamburov, A., et al. (2018) · Nature Methods · doi:10.1038/nmeth.4514 · Cited by 105 · see citing works
Tian, Y., Voineagu, I., Paşca, S. P., Won, H., Chandran, V., Horvath, S., Dolmetsch, R. E., & Geschwind, D. H. (2014) · Genome Medicine · doi:10.1186/s13073-014-0075-5 · Cited by 93 · see citing works
Self-citationChanging the Landscape of Autism Research: The Autism Genetic Resource Exchange
Lajonchere, C. M. (2010) · Neuron · doi:10.1016/j.neuron.2010.10.009 · Cited by 91 · see citing works
Functional Architectures of Local and Distal Regulation of Gene Expression in Multiple Human Tissues
Liu, X., Finucane, H. K., Gusev, A., Bhatia, G., Gazal, S., O’Connor, L. J., Bulik-Sullivan, B. K., Wright, F. A., Sullivan, P. F., Neale, B. M., et al. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.03.002 · Cited by 86 · see citing works
Self-citationLarge-Scale Identification of Common Trait and Disease Variants Affecting Gene Expression
Hauberg, M. E., Zhang, W., Giambartolomei, C., Franzén, O., Morris, D. L., Vyse, T. J., Ruusalepp, A., Sklar, P. B., Schadt, E. E., Björkegren, J., et al. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.04.016 · Cited by 83 · see citing works
Comparative genetic architectures of schizophrenia in East Asian and European populations
Schizophrenia Working Group of the Psychiatric Genomics Consortium, Chen, C.-Y., Li, Z., Martin, A. R., Bryois, J., Ma, X., Gaspar, H. A., Ikeda, M., Benyamin, B., Brown, B. C., et al. (2019) · Lancaster EPrints (Lancaster University) · Cited by 82 · see citing works
Self-citationBerto, S., Usui, N., Konopka, G., & Fogel, B. L. (2016) · Human Molecular Genetics · doi:10.1093/hmg/ddw110 · Cited by 80 · cited 1× · see citing works
“, 2014), splicing (Berto et al., 2016; Fogel et al., 2012; Weyn-Vanhentenryck et al., 2014), or signaling (Tian et al.”
Background15q11.2 CNV affects cognitive, structural and functional correlates of dyslexia and dyscalculia
Ulfarsson, M. O., Walters, G. B., Gustafsson, O., Steinberg, S., Silva, A., Doyle, O. M., Brammer, M., Gudbjartsson, D. F., Arnarsdottir, S., Jonsdottir, G. A., et al. (2017) · Translational Psychiatry · doi:10.1038/tp.2017.77 · Cited by 78 · cited 1× · see citing works
“variable, ranging from subtle effects detectable by neuropsychological tests to mild degrees of anxiety/ADHD to co-occurrence of severe psychiatric disorders (Kendall et al., 2017; Stefansson et al., 2014; Ulfarsson et al., 2017).”
BackgroundTruncating mutations in RBM12 are associated with psychosis
Steinberg, S., Gudmundsdottir, S., Sveinbjornsson, G., Suvisaari, J., Paunio, T., Torniainen-Holm, M., Frigge, M. L., Jonsdottir, G. A., Huttenlocher, J., Arnarsdottir, S., et al. (2017) · Nature Genetics · doi:10.1038/ng.3894 · Cited by 70 · cited 1× · see citing works
“WES has implicated only two genes for SCZ (Singh et al., 2016; Steinberg et al., 2017) at sample sizes that yielded dozens of associations for ASD.”
BackgroundDamaging de novo mutations diminish motor skills in children on the autism spectrum
Buja, A., Volfovsky, N., Krieger, A. M., Lord, C., Lash, A. E., Wigler, M., & Iossifov, I. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1715427115 · Cited by 64 · cited 1× · see citing works
“Most of these mutations also decrease IQ, and ID is an important comorbidity of ASD (Buja et al., 2018; Iossifov et al., 2014), which is consistent with previous work identifying dozens of known severe, rare medical genetic syndromes associated with ASD (reviewed in Abrahams and Geschwind, 2008; Geschwind, 2009).”
ResultMapping pathologic circuitry in schizophrenia
Glausier, J. R., & Lewis, D. A. (2018) · Handbook of clinical neurology · doi:10.1016/b978-0-444-63639-3.00025-6 · Cited by 52 · cited 1× · see citing works
“174 Cell 177, March 21, 2019 studies (Glausier and Lewis, 2018; Piper et al., 2012).”
Revealing the brain's molecular architecture
Ashley‐Koch, A. E., Crawford, G. E., Garrett, M. E., et al. (2018) · Science · doi:10.1126/science.362.6420.1262 · Cited by 49 · see citing works
Self-citationCryptic and Complex Chromosomal Aberrations in Early-Onset Neuropsychiatric Disorders
Brand, H., Pillalamarri, V., Collins, R. L., Eggert, S., O'Dushlaine, C. T., Braaten, E. B., Stone, M. R., Chambert, K., Doty, N. D., Hanscom, C., et al. (2014) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2014.09.005 · Cited by 44 · cited 1× · see citing works
“Approximately 4% of the genome comprises such structural variation, much of which is common, inherited, and relatively benign with regards to imparting disease risk (Brand et al., 2014; Conrad et al., 2010; Mills et al., 2011; Sebat et al., 2004).”
BackgroundGenomic Disorders in Psychiatry-What Does the Clinician Need to Know?
Lowther, C., Costain, G., Baribeau, D. A., & Bassett, A. S. (2017) · Current Psychiatry Reports · doi:10.1007/s11920-017-0831-5 · Cited by 41 · see citing works
Wang, S., Mandell, J. D., Kumar, Y., et al. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.12.024 · Cited by 38 · see citing works
Most chromatin interactions are not in linkage disequilibriumPreprint
Whalen, S., & Pollard, K. S. (2019) · Genome Research · doi:10.1101/gr.238022.118 · Cited by 35 · see citing works
Hook, P. W., & McCallion, A. S. (2020) · Genome Research · doi:10.1101/gr.256578.119 · Cited by 33 · see citing works
ASD and ADHD have a similar burden of rare protein-truncating variantsPreprint
Satterstrom, F., Walters, R. K., Singh, T., Wigdor, E., Lescai, F., Demontis, D., Kosmicki, J. A., Grove, J., Stevens, C. R., Bybjerg-Grauholm, J., et al. (2018) · bioRxiv · doi:10.1101/277707 · Cited by 30 · see citing works
Bryois, J., Skene, N., Hansen, T. F., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/528463 · Cited by 29 · see citing works
Self-citationNIMH Human Genetics Initiative: 2003 Update
Moldin, S. O. (2003) · American Journal of Psychiatry · doi:10.1176/appi.ajp.160.4.621 · Cited by 27 · see citing works
The value of genetic risk scores in precision medicine for diabetes
McCarthy, M. I., & Mahajan, A. (2018) · Expert Review of Precision Medicine and Drug Development · doi:10.1080/23808993.2018.1510732 · Cited by 17 · see citing works
Schork, A. J., Won, H., Appadurai, V., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/240911 · Cited by 14 · cited 1× · see citing works
“A key empirical finding is that genetic risk can be non-specific and shared to varying extents across many adult- and childhood-onset psychiatric disorders (Antilla et al., 2018; Cross-Disorder Group of the Psychiatric Genomics Consortium, 2013; Schork et al., 2019).”
BackgroundSelf-citationSizing up whole-genome sequencing studies of common diseases
Wray, N. R., & Gratten, J. (2018) · Nature Genetics · doi:10.1038/s41588-018-0113-0 · Cited by 11 · cited 1× · see citing works
“Few studies of psychiatric disorders to date (Wray and Gratten, 2018).”
BackgroundMost regulatory interactions are not in linkage disequilibriumPreprint
Whalen, S., & Pollard, K. S. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/272245 · Cited by 8 · cited 2× · see citing works
“, 2016), nearly half of the target genes of human regulatory variation are not in genomic loci defined by linkage disequilibrium (LD) (Whalen and Pollard, 2018) (Table 3).”
BackgroundResultRuzzo, E. K., Pérez‐Cano, L., Jung, J.-Y., Wang, L.-K., Kashef-Haghighi, D., Hartl, C., Hoekstra, J. N., Leventhal, O., Gandal, M. J., Paskov, K. M., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/338855 · Cited by 7 · see citing works
Self-citationA single cell transcriptomic analysis of human neocortical developmentPreprint
Polioudakis, D., de la Torre-Ubieta, L., Langerman, J., Elkins, A. G., Stein, J. L., Vuong, C. K., Opland, C. K., Lu, D., Connell, W., Ruzzo, E. K., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/401885 · Cited by 7 · cited 4× · see citing works
“A recent study of single-nuclei RNA-seq from human fetal and adult brain has validated the enrichment of genes harboring large-effect de novo mutations associated with ASD in fetal glutamatergic neurons (Polioudakis et al., 2018).”
BackgroundInfluentialSelf-citationGenetic control of gene expression and splicing in the developing human brainPreprint
Walker, R. L., Ramaswami, G., Hartl, C., Mancuso, N., Gandal, M. J., de la Torre-Ubieta, L., Paşaniuc, B., Stein, J. L., & Geschwind, D. H. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/471193 · Cited by 5 · see citing works
Self-citationPublisher Correction: Whole genome sequencing in psychiatric disorders: the WGSPD consortium
(WGSPD), W. G. S. F. P. D., Sanders, S., Neale, B. M., et al. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0102-8 · Cited by 4 · see citing works
Self-citationHook, P. W., & McCallion, A. S. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/427484 · Cited by 3 · see citing works
Flagged first, then by citations
11 of the 201 references couldn’t be matched to a known paper.
Research works printed but not linked: 2
- Hook, 2018, Heritability enrichment in open chromatin reveals cortical layer contributions to schizophrenia, bioRxiv
- Satterstrom, 2018, Novel genes for autism implicate both excitatory and inhibitory cell lineages in risk, bioRxiv
Cited by
Sorted by citations
Structural variation in the sequencing era
Ho, S. S., Urban, A. E., & Mills, R. E. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-019-0180-9 · Cited by 608 · see citing works
New insights into the development of the human cerebral cortex
Molnár, Z., Clowry, G. J., Šestan, N., Alzu’bi, A., Bakken, T. E., Hevner, R. F., Hüppi, P. S., Kostović, I., RAKIC, P. T., Anton, E. S., et al. (2019) · Journal of Anatomy · doi:10.1111/joa.13055 · Cited by 401 · see citing works
“Recent advances in genetics and genomics have identified hundreds of genetic coding and non-coding variants that increase the risk for major neuropsychiatric disorders, including autism spectrum disorder (ASD; Sestan & State, 2018; Sullivan & Geschwind, 2019).”
BackgroundFrom Basic Science to Clinical Application of Polygenic Risk Scores: A Primer
Wray, N. R., Lin, T., Austin, J., McGrath, J. J., Hickie, I. B., Murray, G. K., & Visscher, P. M. (2021) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2020.3049 · Cited by 367 · see citing works
Bryois, J., Skene, N., Hansen, T. F., Kogelman, L. J. A., Watson, H. J., Liu, Z., Adan, R. A. H., Alfredsson, L. S., Ando, T., Andreassen, O. A., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-0610-9 · Cited by 375 · see citing works
“These biological findings are consistent with genetic and epidemiological evidence of a general psychopathy factor underlying diverse psychiatric disorders 24,45,46 .”
Transcriptomic and cellular decoding of regional brain vulnerability to neurogenetic disorders
Seidlitz, J., Nadig, A., Liu, S., Bethlehem, R. A. I., Vértes, P. E., Morgan, S. E., Váša, F., Romero-García, R., Lalonde, F. M., CLASEN, L. S., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-17051-5 · Cited by 322 · see citing works
Self-citationBroad transcriptomic dysregulation occurs across the cerebral cortex in ASD
Gandal, M. J., Haney, J. R., Wamsley, B., Yap, C. X., Parhami, S., Emani, P. S., Chang, N., Chen, G. T., Hoftman, G. D., de Alba, D., et al. (2022) · Nature · doi:10.1038/s41586-022-05377-7 · Cited by 281 · see citing works
Self-citationCould Polygenic Risk Scores Be Useful in Psychiatry?
Murray, G. K., Lin, T., Austin, J., McGrath, J. J., Hickie, I. B., & Wray, N. R. (2020) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2020.3042 · Cited by 274 · see citing works
Andreassen, O. A., Hindley, G., Frei, O., & Smeland, O. B. (2023) · World Psychiatry · doi:10.1002/wps.21034 · Cited by 255 · see citing works
Human brain organogenesis: Toward a cellular understanding of development and disease
Kelley, K. W., & Pașca, S. P. (2021) · Cell · doi:10.1016/j.cell.2021.10.003 · Cited by 233 · see citing works
“Modeling human neuropsychiatric disorders Recent progress in gene discovery using large patient cohorts has begun to outline the genetic underpinnings of neuropsychiatric disorders (Sullivan and Geschwind, 2019).”
BackgroundThe polygenic architecture of schizophrenia — rethinking pathogenesis and nosology
Smeland, O. B., Frei, O., Dale, A. M., & Andreassen, O. A. (2020) · Nature Reviews Neurology · doi:10.1038/s41582-020-0364-0 · Cited by 202 · see citing works
Morton, J. T., Jin, D.-M., Mills, R. H., Shao, Y., Rahman, G., McDonald, D. T., Zhu, Q., Balaban, M., Jiang, Y., Cantrell, K., et al. (2023) · Nature Neuroscience · doi:10.1038/s41593-023-01361-0 · Cited by 229 · see citing works
Ni, G., Zeng, J., Revez, J. A., Wang, Y., Zheng, Z., Ge, T., Restuadi, R., Kiewa, J., Nyholt, D. R., Coleman, J. R. I., et al. (2021) · Biological Psychiatry · doi:10.1016/j.biopsych.2021.04.018 · Cited by 203 · see citing works
“to date but are diverse in lifetime risk, and are representative of psychiatric disorders which have all been shown to be highly polygenic (27).”
Fuentes, J., Amaia Hervas, G., Howlin, P., & Party), (. A. W. (2020) · European Child & Adolescent Psychiatry · doi:10.1007/s00787-020-01587-4 · Cited by 211 · see citing works
An atlas of gene regulatory elements in adult mouse cerebrum
Li, Y. E., Preissl, S., Hou, X., Zhang, Z., Zhang, K., Qiu, Y., Poirion, O. B., Li, B., Chiou, J., Liu, H., et al. (2021) · Nature · doi:10.1038/s41586-021-03604-1 · Cited by 185 · see citing works
Uncovering the Genetic Architecture of Major Depression
McIntosh, A. M., Sullivan, P. F., & Lewis, C. M. (2019) · Neuron · doi:10.1016/j.neuron.2019.03.022 · Cited by 160 · see citing works
“In the past 40 years, many twin and family studies ofMD have established that liability to MD has a non-deterministic genetic component to its etiology as substantiated by a twin heritability of 31%–42% (Sullivan et al., 2000).”
BackgroundSelf-citationInsufficient Evidence for “Autism-Specific” Genes
Myers, S. M., Challman, T. D., Bernier, R., Bourgeron, T., Chung, W. K., Constantino, J. N., Eichler, E. E., Jacquemont, S., Miller, D. T., Mitchell, K. J., et al. (2020) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2020.04.004 · Cited by 165 · see citing works
Genetics of human brain development
Zhou, Y. F., Song, H., & Ming, G. (2023) · Nature Reviews Genetics · doi:10.1038/s41576-023-00626-5 · Cited by 173 · see citing works
Brain organoids: an ensemble of bioassays to investigate human neurodevelopment and disease
Sidhaye, J., & Knoblich, J. A. (2020) · Cell Death and Differentiation · doi:10.1038/s41418-020-0566-4 · Cited by 167 · see citing works
“structural variants associated with diverse brain diseases [34, 35].”
BackgroundSingle-cell genomics and regulatory networks for 388 human brains
Emani, P. S., Liu, J. J., Clarke, D., Jensen, M., Warrell, J., Gupta, C., Meng, R., Lee, C.-Y., Xu, S., Dursun, C., et al. (2024) · Science · doi:10.1126/science.adi5199 · Cited by 168 · see citing works
Self-citationGenetic architecture of schizophrenia: a review of major advancements
Legge, S. E., Santoro, M. L., Periyasamy, S., Okewole, A., Arsalan, A., & Kowalec, K. (2021) · Psychological Medicine · doi:10.1017/s0033291720005334 · Cited by 146 · see citing works
“This pleiotropy further adds to the existing complex picture emerging out of these studies (Sullivan & Geschwind, 2019).”
Polimanti, R. A., Walters, R. K., Johnson, E. C., McClintick, J. N., Adkins, A. E., Adkins, D. E., Bacanu, S., Bierut, L. J., Bigdeli, T. B., Brown, S. A., et al. (2020) · Molecular Psychiatry · doi:10.1038/s41380-020-0677-9 · Cited by 123 · see citing works
Shadrin, A. A., Kaufmann, T., van der Meer, D., Palmer, C. E., Makowski, C., Loughnan, R. J., Jernigan, T. L., Seibert, T. M., Hagler, D. J., Smeland, O. B., et al. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118603 · Cited by 108 · see citing works
Shen, X., Howard, D. M., Adams, M. J., Hill, W. D., Clarke, T.-K., Adams, M. J., Clarke, T., McIntosh, A. M., Deary, I. J., Wray, N. R., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-16022-0 · Cited by 111 · see citing works
“The current data set has considerable advantages in terms of its large sample size and was focussed on whether polygenic associations can be replicated across neuroimaging samples, improving on an area of previously identi fi ed methodological weakness 37 .”
BackgroundThe Role of Astrocytes in the Neurorepair Process
Chiareli, R. A., Carvalho, G. A., Marques, B. L., Mota, L. S., Oliveira‐Lima, O. C., Gomes, R. M., Birbrair, A., Gomez, R. S., Simão, F., Klempin, F., et al. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.665795 · Cited by 126 · see citing works
Leveraging base-pair mammalian constraint to understand genetic variation and human disease
Sullivan, P. F., Meadows, J. R. S., Gazal, S., Phan, B. N., Li, X., Genereux, D. P., Dong, M. X., Bianchi, M., Andrews, G., Sakthikumar, S., et al. (2023) · Science · doi:10.1126/science.abn2937 · Cited by 110 · see citing works
“Given that CNVs are known risk factors for schizophrenia (53), we obtained the CNV call set from the largest published study (21,094 cases, 20,227 controls) (54).”
Self-citationMulti-omic profiling of the developing human cerebral cortex at the single-cell level
Zhu, K., Bendl, J. M., Rahman, S., Vicari, J. M., Coleman, C., Clarence, T., Latouche, O., Tsankova, N. M., Li, A., Brennand, K., et al. (2023) · Science Advances · doi:10.1126/sciadv.adg3754 · Cited by 116 · see citing works
“Despite the notable progress in exploring the genetic causes of neuropsychiatric disorders, their underlying molecular mechanisms are still not fully understood ( 39 ).”
Peyrot, W. J., & Price, A. L. (2021) · Nature Genetics · doi:10.1038/s41588-021-00787-1 · Cited by 106 · see citing works
Kostović, I. (2020) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2020.101883 · Cited by 102 · see citing works
Johnson, D., Thurairajasingam, S., Letchumanan, V., Chan, K., & Lee, L. (2021) · Nutrients · doi:10.3390/nu13051728 · Cited by 112 · see citing works
Liang, D., Elwell, A. L., Aygün, N., Krupa, O., Wolter, J. M., Kyere, F. A., Lafferty, M. J., Cheek, K. E., Courtney, K. P., Yusupova, M., et al. (2021) · Nature Neuroscience · doi:10.1038/s41593-021-00858-w · Cited by 83 · see citing works
Self-citationWolfers, T., Rokicki, J., Alnæs, D., Berthet, P., Agartz, I., Kia, S. M., Kaufmann, T., Zabihi, M., Moberget, T., Melle, I. S., et al. (2021) · Human Brain Mapping · doi:10.1002/hbm.25386 · Cited by 84 · see citing works
“, 2019] and also comply with accumulating evidence from psychiatric genetics strongly suggesting that mental illnesses are complex and heterogeneous disorders associated with a large number of genetic variants as well as environmental risk factors [Sullivan and Geschwind, 2019].”
BackgroundChromatin Remodeling Complex NuRD in Neurodevelopment and Neurodevelopmental Disorders
Hoffmann, A., & Spengler, D. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00682 · Cited by 82 · see citing works
“Model adapted from (Sun et al., 2014), license number 4578150712067.”
Yuan, S., Yao, H., & Larsson, S. C. (2020) · Scientific Reports · doi:10.1038/s41598-020-70458-4 · Cited by 94 · see citing works
DOMINO: a network‐based active module identification algorithm with reduced rate of false calls
Levi, H., Elkon, R., & Ron Shamir, A. (2021) · Molecular Systems Biology · doi:10.15252/msb.20209593 · Cited by 74 · see citing works
“We calculated this measure using different similarity cutoffs (1.0 to 4.0 in REVIGO).”
MethodInfluentialJohansson, Å., Andreassen, O. A., Brunak, S., Franks, P. W., Hedman, H., Loos, R. J. F., Meder, B., Melén, E., Wheelock, C. E., & Jacobsson, B. (2023) · Journal of Internal Medicine · doi:10.1111/joim.13640 · Cited by 98 · see citing works
Halvorsen, M., Huh, R., Oskolkov, N., Wen, J., Netotea, S., Giusti‐Rodríguez, P., Karlsson, R., Bryois, J., Nystedt, B., Ameur, A., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-15707-w · Cited by 81 · see citing works
Self-citationTranslating insights from neuropsychiatric genetics and genomics for precision psychiatry
Rees, E., & Owen, M. J. (2020) · Genome Medicine · doi:10.1186/s13073-020-00734-5 · Cited by 84 · see citing works
Pak, C., Dankó, T., Mirabella, V. R., Wang, J., Liu, Y., Vangipuram, M., Grieder, S. D., Zhang, X., Ward, T., Huang, Y. A., et al. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2025598118 · Cited by 80 · see citing works
Giusti‐Rodríguez, P., & Sullivan, P. F. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/406330 · Cited by 72 · see citing works
Self-citationCulotta, L., & Penzes, P. (2020) · Molecular Autism · doi:10.1186/s13229-020-00339-0 · Cited by 77 · see citing works
Guan, F., Ni, T., Zhu, W., Williams, L. K., Cui, L., Li, M., Tubbs, J. D., Sham, P. C., & Gui, H. (2021) · Molecular Psychiatry · doi:10.1038/s41380-021-01201-2 · Cited by 75 · see citing works
Genetic contributions to suicidal thoughts and behaviors
DiBlasi, E., Kang, J., & Docherty, A. R. (2021) · Psychological Medicine · doi:10.1017/s0033291721001720 · Cited by 83 · see citing works
“Genetic discovery of psychiatric risk generally increases with larger sample sizes (Sullivan & Geschwind, 2019).”
BackgroundMeta-Analyses of Genome-Wide Association Studies for Postpartum Depression
Guintivano, J., Byrne, E. M., Kiewa, J., Yao, S., Bauer, A. E., Åberg, K. A., Adams, M. J., Campbell, A. I., Campbell, M. L., Choi, K. W., et al. (2023) · American Journal of Psychiatry · doi:10.1176/appi.ajp.20230053 · Cited by 76 · see citing works
Self-citationSterling, P. (2020) · The MIT Press eBooks · doi:10.7551/mitpress/11472.001.0001 · Cited by 117 · see citing works
Massively parallel characterization of regulatory elements in the developing human cortex
Deng, C., Whalen, S., Steyert, M., Ziffra, R., Przytycki, P. F., Inoue, F., Pereira, D. A., Capauto, D., Norton, S., Vaccarino, F. M., et al. (2024) · Science · doi:10.1126/science.adh0559 · Cited by 72 · see citing works
“sychiatric disorders affect nearly one in five adolescents worldwide ( 1 ) and have a strong genetic etiology ( 2 ).”
BackgroundSelf-citationLu, H., Qiao, J., Shao, Z., Wang, T., Huang, S., & Zeng, P. (2021) · BMC Medicine · doi:10.1186/s12916-021-02186-z · Cited by 65 · see citing works
Takahashi, N., Harada, T., Nishimura, T., Okumura, A., Choi, D., Iwabuchi, T., Kuwabara, H., Takagai, S., Nomura, Y., Takei, N., et al. (2020) · JAMA Network Open · doi:10.1001/jamanetworkopen.2019.21644 · Cited by 58 · see citing works
Heterogeneity and Polygenicity in Psychiatric Disorders: A Genome-Wide Perspective
Wendt, F. R., Pathak, G. A., Tylee, D. S., Goswami, A., & Polimanti, R. A. (2020) · Chronic Stress · doi:10.1177/2470547020924844 · Cited by 59 · see citing works
Clements, C. C., Karlsson, R., Lu, Y., Juréus, A., Rück, C., Andersson, E., Boberg, J., Pedersen, N. L., Bulik, C. M., Nordenskjöld, A., et al. (2021) · Molecular Psychiatry · doi:10.1038/s41380-020-00984-0 · Cited by 58 · see citing works
Self-citationMarcogliese, P. C., Deal, S. L., Andrews, J. C., Harnish, J. M., Bhavana, V. H., Graves, H. K., Jangam, S. V., Luo, X., Liu, N., Bei, D., et al. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.110517 · Cited by 59 · see citing works
“Loss- or gain-of-function alleles in GLRA2 cause X-linked neurodevelopmental disorders Many genes implicated in ASD are also associated with neurodevelopmental disorders beyond autism (Levitt and Campbell, 2009; Sullivan and Geschwind, 2019).”
Johnson, D., Letchumanan, V., Thum, C. C., Thurairajasingam, S., & Lee, L. (2023) · Nutrients · doi:10.3390/nu15061382 · Cited by 65 · see citing works
Polygenic risk score as clinical utility in psychiatry: a clinical viewpoint
Ikeda, M., Saito, T., Kanazawa, T., & Iwata, N. (2020) · Journal of Human Genetics · doi:10.1038/s10038-020-0814-y · Cited by 53 · see citing works
Population-level variation in enhancer expression identifies disease mechanisms in the human brain
Dong, P., Hoffman, G. E., Apontes, P., Bendl, J. M., Rahman, S., Fernando, M. B., Zeng, B., Vicari, J. M., Zhang, W., Girdhar, K., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01170-4 · Cited by 45 · see citing works
Restoring the missing person to personalized medicine and precision psychiatry
Gómez-Carrillo, A., Paquin, V., Dumas, G., & Kirmayer, L. J. (2023) · Frontiers in Neuroscience · doi:10.3389/fnins.2023.1041433 · Cited by 59 · see citing works
“Given the fact that most psychiatric disorders appear to have many genetic factors that each make a small contribution to the phenotype (Sullivan and Geschwind, 2019; Rees and Owen, 2020), the influence of any one factor is even more likely to depend crucially on its context within the whole genome, its epigenetic reg…”
BackgroundKoi, P. (2021) · Studies in History and Philosophy of Science Part A · doi:10.1016/j.shpsa.2021.07.006 · Cited by 57 · see citing works
“This is unsurprising, because there is also genetic overlap among psychiatric diagnoses in general (Gandal et al., 2018; Sullivan & Geschwind, 2019).”
BackgroundChen, X., Yao, T., Cai, J., Fu, X., Li, H., & Wu, J. (2022) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2022.110534 · Cited by 59 · see citing works
Identification of novel genomic risk loci shared between common epilepsies and psychiatric disorders
Karadag, N., Shadrin, A. A., O’Connell, K. S., Hindley, G., Rahman, Z., Parker, N., Bahrami, S., Fominykh, V., Cheng, W., Holen, B., et al. (2023) · Brain · doi:10.1093/brain/awad038 · Cited by 57 · see citing works
The Genetically Informed Neurobiology of Addiction (GINA) model
Bogdan, R., Hatoum, A. S., Johnson, E. C., & Arpana Agrawal, A. (2022) · Nature reviews. Neuroscience · doi:10.1038/s41583-022-00656-8 · Cited by 54 · see citing works
Schizophrenia genomics: genetic complexity and functional insights
Sullivan, P. F., Yao, S., & Hjerling‐Leffler, J. (2024) · Nature reviews. Neuroscience · doi:10.1038/s41583-024-00837-7 · Cited by 62 · see citing works
“The genetic architecture 19 of schizophrenia — the number of genetic variants , their frequencies in individuals with schizophrenia and neuro-typical control individuals and the degree of risk conferred — is clearer now than ever before.”
Self-citationThe schizophrenia-associated variant in SLC39A8 alters protein glycosylation in the mouse brain
Mealer, R. G., Williams, S., Noël, M., Yang, B., D’Souza, A. K., Nakata, T., Graham, D. B., Creasey, E. A., Çetinbaş, M., Sadreyev, R. I., et al. (2022) · Molecular Psychiatry · doi:10.1038/s41380-022-01490-1 · Cited by 46 · see citing works
Modeling the complex genetic architectures of brain disease
Fernando, M. B., Ahfeldt, T., & Brennand, K. (2020) · Nature Genetics · doi:10.1038/s41588-020-0596-3 · Cited by 47 · see citing works
Clinical and Translational Implications of an Emerging Developmental Substructure for Autism
Constantino, J. N., Charman, T., & Jones, E. J. H. (2021) · Annual Review of Clinical Psychology · doi:10.1146/annurev-clinpsy-081219-110503 · Cited by 50 · see citing works
“…al. 2016) and also in children and adults with a diagnosis relative to neurotypical controls (Kang et al. 2018), although the experimental results in relation to the latter group are mixed and highly dependent on localization of brain regions in which the signals are recorded (Sysoeva et al. 2018).”
ResultPsychiatric Genetics Begins to Find Its Footing
Smoller, J. W. (2019) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2019.19060643 · Cited by 49 · see citing works
Biotyping in psychosis: using multiple computational approaches with one data set
Tamminga, C. A., Clementz, B. A., Pearlson, G. D., Keshavan, M. S., Gershon, E. S., Ivleva, E. I., McDowell, J. E., Meda, S. A., Keedy, S., Calhoun, V. D., et al. (2020) · Neuropsychopharmacology · doi:10.1038/s41386-020-00849-8 · Cited by 48 · see citing works
Cognitive impairment in psychiatric diseases: Biomarkers of diagnosis, treatment, and prevention
Wang, Y., Meng, W., Liu, Z., An, Q., & Hu, X. (2022) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2022.1046692 · Cited by 49 · see citing works
“They are characterized by persistent, universal, and pathological patterns of abnormal moods, perceptions, behaviors, or higher levels of cognition (Sullivan and Geschwind, 2019; First et al., 2021).”
BackgroundMoysés‐Oliveira, M., Yadav, R., Erdin, S., & Talkowski, M. E. (2020) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2020.07.001 · Cited by 46 · see citing works
Pinzón-Espinosa, J., van der Horst, M. Z., Zinkstok, J., Austin, J., Aalfs, C. M., Batalla, A., Sullivan, P. F., Vorstman, J. A. S., & Luykx, J. J. (2022) · Translational Psychiatry · doi:10.1038/s41398-022-02203-6 · Cited by 49 · see citing works
“2 deletion syndrome) and— in research settings—to provide insight into prognosis and treatment response, particularly for disorders with high heritability estimates, such as ASD, attention deficit and hyperactivity disorder, schizophrenia, and bipolar disorder [25, 26].”
BackgroundSelf-citationVLDL-specific increases of fatty acids in autism spectrum disorder correlate with social interaction
Usui, N., Iwata, K., Miyachi, T., Takagai, S., Wakusawa, K., Nara, T., Tsuchiya, K. J., Matsumoto, K., Kurita, D., Kameno, Y., et al. (2020) · EBioMedicine · doi:10.1016/j.ebiom.2020.102917 · Cited by 45 · see citing works
Chen, W., Feng, J., Jiang, S., Guo, J., Zhang, X., Zhang, X., Wang, C., Ma, Y., & Dong, Z. (2023) · Journal of Affective Disorders · doi:10.1016/j.jad.2023.07.044 · Cited by 48 · see citing works
Human CRY1 variants associate with attention deficit/hyperactivity disorder
Onat, O. E., Kars, M. E., Gül, Ş., Bilguvar, K., Wu, Y., Özhan, A., Aydın, C., Başak, A. N., Trusso, M. A., Goracci, A., et al. (2020) · Journal of Clinical Investigation · doi:10.1172/jci135500 · Cited by 47 · see citing works
“5 kg, and other neurological or systemic disorders that might explain ADHD symptoms (11, 13).”
BackgroundMethodInfluentialSZDB2.0: an updated comprehensive resource for schizophrenia research
Wu, Y., Li, X., Liu, J., Luo, X., & Yao, Y. (2020) · Human Genetics · doi:10.1007/s00439-020-02171-1 · Cited by 43 · see citing works
Yang, G., & Shcheglovitov, A. (2019) · Developmental Dynamics · doi:10.1002/dvdy.100 · Cited by 44 · see citing works
“6%15%.(9,12) However, the identification of specific common variants has been difficult due to an insufficient number of cases, and only recently, a study of 18 381 patients and 27 969 controls has found 12 common variants that implicate around 30 neighboring genes in ASD pathogenesis.”
ResultElanzew, A., Nießing, B., Langendoerfer, D., Rippel, O., Piotrowski, T., Schenk, F., Kulik, M., Peitz, M., Breitkreuz, Y., Jung, S., et al. (2020) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2020.580352 · Cited by 47 · see citing works
Three decades of ASD genetics: building a foundation for neurobiological understanding and treatment
Eyring, K. W., & Geschwind, D. H. (2021) · Human Molecular Genetics · doi:10.1093/hmg/ddab176 · Cited by 41 · see citing works
“The genetic architecture of psychiatric diseases, including ASD, has been extensively reviewed and this range of heritability observed in ASD is very similar to, but on the higher end of, the range of heritability for other common neuropsychiatric disorders (31,32).”
ResultSelf-citationBrain structural associations with depression in a large early adolescent sample (the ABCD study®)
Shen, X., MacSweeney, N., Chan, S. W. Y., Barbu, M. C., Adams, M. J., Lawrie, S. M., Romaniuk, L., McIntosh, A. M., & Whalley, H. C. (2021) · EClinicalMedicine · doi:10.1016/j.eclinm.2021.101204 · Cited by 42 · see citing works
“Reasons for this may include shared genetic and environmental risk factors between major psychiatric disorders [57].”
BackgroundFocus on your locus with a massively parallel reporter assay
McAfee, J. C., Bell, J., Krupa, O., Matoba, N., Stein, J. L., & Won, H. (2022) · Journal of Neurodevelopmental Disorders · doi:10.1186/s11689-022-09461-x · Cited by 39 · see citing works
Genetic Influences on the Developing Young Brain and Risk for Neuropsychiatric Disorders
Alex, A. M., Buß, C., Davis, E. P., Campos, G. D. L., Donald, K. A., Fair, D. A., Gaab, N., Gao, W., Gilmore, J. H., Girault, J. B., et al. (2023) · Biological Psychiatry · doi:10.1016/j.biopsych.2023.01.013 · Cited by 41 · see citing works
Jiang, T., Liu, S., Cao, S., Liu, Y., Cui, Z., Wang, Y., & Guo, H. (2021) · BMC Bioinformatics · doi:10.1186/s12859-021-04422-y · Cited by 39 · see citing works
Epigenetic Basis of Psychiatric Disorders: A Narrative Review
Panariello, F., Fanelli, G., Fabbri, C., Atti, A. R., Ronchi, D. D., & Serretti, A. (2021) · CNS & Neurological Disorders - Drug Targets · doi:10.2174/1871527320666210825101915 · Cited by 31 · see citing works
A comprehensive evaluation of polygenic score methods across cohorts in psychiatric disordersPreprint
Ni, G.-Y., Zeng, J., Revez, J., Wang, Y., Ge, T., Restaudi, R., Kiewa, J., Nyholt, D., Coleman, J., Smoller, J., et al. (2020) · medRxiv · doi:10.1101/2020.09.10.20192310 · Cited by 18 · see citing works
Striessnig, J. (2021) · Frontiers in Synaptic Neuroscience · doi:10.3389/fnsyn.2021.634760 · Cited by 41 · see citing works
“…whole exome sequencing the diagnostic yield of characterized disease genes is > 30% (Helbig et al., 2016; Symonds and McTague, 2020) and genetic diagnosis has significant impact on patient management, such as choosing or avoiding certain antiepileptic medications (Symonds and McTague, 2020).”
BackgroundGerasimenko, M., Михайлович, Ч. С., Furuhara, K., Lopatina, O. L., Salmina, A. B., Shabalova, A. A., Tsuji, C., Yokoyama, S., Ishihara, K., Brenner, C., et al. (2020) · Scientific Reports · doi:10.1038/s41598-019-57236-7 · Cited by 40 · see citing works
Examining the shared etiology of psychopathology with genome-wide association studies
Mallard, T. T., Grotzinger, A. D., & Smoller, J. W. (2023) · Physiological Reviews · doi:10.1152/physrev.00016.2022 · Cited by 38 · see citing works
Battaglia, S., Nazzi, C., & Thayer, J. F. (2024) · Translational Psychiatry · doi:10.1038/s41398-024-02737-x · Cited by 37 · see citing works
“There is a high level of genetic heritability for different disorders [29], and there is evidence that some genetic risk factors are shared among different psychiatric illnesses [30].”
Backgroundvan der Meer, D., & Kaufmann, T. (2022) · Translational Psychiatry · doi:10.1038/s41398-022-02193-5 · Cited by 34 · see citing works
“Last, uncovering genetic determinants only solves one piece of the puzzle; A true understanding of cortical development and its role in human behavior will require a multi-omics approach, integrating genomics with epigenomics, transcriptomics and proteomics to discover how these regulate molecular, cellular, and neura…”
BackgroundYao, S., Harder, A., Darki, F., Chang, Y.-W., Li, A., Nikouei, K., Volpe, G., Lundström, J. N., Zeng, J., Wray, N. R., et al. (2025) · Nature Communications · doi:10.1038/s41467-024-55611-1 · Cited by 52 · see citing works
Self-citationShen, X.-Y., Caramaschi, D., Adams, M., Walker, R., Min, J. L., Kwong, A., Hemani, G., Barbu, M., Whalley, H., Harris, S., et al. (2021) · Genome Medicine · doi:10.1186/s13073-022-01039-5 · Cited by 26 · see citing works
Akingbuwa, W. A., Hammerschlag, A. R., Bartels, M., & Middeldorp, C. M. (2021) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2021.03.020 · Cited by 36 · see citing works
“Commonly occurring symptom overlap combined with substantial genetic overlap across disorders suggests a spectrum of psychopathology and thus the need for a re-evaluation of current diagnostic categories, as they may not be accurate.(135,136) Along with pleiotropic effects, recent studies have also provided evidence o…”
BackgroundDimensional and transdiagnostic phenotypes in psychiatric genome-wide association studies
Waszczuk, M. A., Jonas, K. G., Bornovalova, M. A., Breen, G. D., Bulik, C. M., Docherty, A. R., Eley, T. C., Hettema, J. M., Kotov, R., Krueger, R. F., et al. (2023) · Molecular Psychiatry · doi:10.1038/s41380-023-02142-8 · Cited by 32 · see citing works
Progress in iPSC-Based Modeling of Psychiatric Disorders
Hoffmann, A., Ziller, M. J., & Spengler, D. (2019) · International Journal of Molecular Sciences · doi:10.3390/ijms20194896 · Cited by 39 · see citing works
Gordon, A., Forsingdal, A., Klewe, I. V., Nielsen, J., Didriksen, M., Werge, T. M., & Geschwind, D. H. (2019) · Molecular Psychiatry · doi:10.1038/s41380-019-0576-0 · Cited by 36 · see citing works
Self-citationReynolds, T., Johnson, E. C., Huggett, S. B., Bubier, J. A., Palmer, R. H. C., Arpana Agrawal, A., Baker, E. J., & Chesler, E. J. (2020) · Neuropsychopharmacology · doi:10.1038/s41386-020-00795-5 · Cited by 31 · see citing works
Frei, O., Hindley, G., Shadrin, A. A., van der Meer, D., Akdeniz, B. C., Hagen, E., Cheng, W., O’Connell, K. S., Bahrami, S., Parker, N., et al. (2024) · Nature Genetics · doi:10.1038/s41588-024-01771-1 · Cited by 36 · see citing works
“Genome-wide association studies (GWAS) have discovered thousands of genomic loci associated with complex human traits and disorders, highlighting their polygenic nature and the predominance of small individual effects of common genetic variants 1 .”
From Personalized Medicine to Precision Psychiatry?
Češková, E., & Petr, Š. (2021) · Neuropsychiatric Disease and Treatment · doi:10.2147/ndt.s337814 · Cited by 35 · see citing works
Publicly Available hiPSC Lines with Extreme Polygenic Risk Scores for Modeling Schizophrenia
Dobrindt, K., Zhang, H., Das, D., Abdollahi, S., Prorok, T., Ghosh, S. D., Weintraub, S. J., Genovese, G., Powell, S. K., Lund, A. N., et al. (2020) · Complex Psychiatry · doi:10.1159/000512716 · Cited by 32 · see citing works
Technological readiness and implementation of genomic‐driven precision medicine for complex diseases
Franks, P. W., Melén, E., Friedman, M., Sundström, J., Kockum, I. S., Klareskog, L., Almqvist, C., Bergen, S. E., Czene, K., Hägg, S., et al. (2021) · Journal of Internal Medicine · doi:10.1111/joim.13330 · Cited by 32 · see citing works
Self-citationLongo, P., Marzola, E., De Bacco, C., Demarchi, M., & Abbate-Daga, G. (2020) · Medicina · doi:10.3390/medicina57010002 · Cited by 33 · see citing works
Dunbar, E. K., Greer, P. J., Melhem, N., Alkaade, S., Amann, S. T., Brand, R. E., Coté, G. A., Forsmark, C. E., Gardner, T. B., Gelrud, A., et al. (2020) · Journal of Gastroenterology · doi:10.1007/s00535-020-01703-w · Cited by 34 · see citing works
Transcriptomic and Cellular Decoding of Regional Brain Vulnerability to Neurodevelopmental DisordersPreprint
Seidlitz, J., Nadig, A., Liu, S., Bethlehem, R. A. I., Vértes, P. E., Morgan, S. E., Váša, F., Romero-García, R., Lalonde, F. M., CLASEN, L. S., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/573279 · Cited by 25 · see citing works
Self-citationLaBianca, S., Brikell, I., Helenius, D., Loughnan, R., Mefford, J., Palmer, C., Walker, R. L., Gådin, J., Krebs, M., Appadurai, V., et al. (2023) · Nature Genetics · doi:10.1038/s41588-023-01593-7 · Cited by 23 · see citing works
“These insights come predominantly from consortia-driven meta-analyses 21,22 that aggregate multiple cohorts sampled via different ascertainment criteria, case-control definitions and healthcare contexts.”
Self-citation
- Authors
- Sullivan, P. F., & Geschwind, D. H.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- University of California, Los Angeles (US)
- Corresponding author
- Sullivan, Patrick F.
- Geschwind, Daniel H.
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2019-03
- Volume
- 177
- Issue
- 1
- Pages
- 162-183
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC6432948
- OpenAlex
- W2923203084
- Cited by
- 452
- References
- 201
- Citations by year
- 2026: 48 · 2025: 37 · 2024: 63 · 2023: 69 · 2022: 69 · 2021: 70 · 2020: 69 · 2019: 26 · 2018: 1
- FWCI
- 7.75
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- Swedish Research Council (D0886501)
- Horizon 2020 Program of the European Union (610307)
- NIMH (U01 MH109528, R01 MH077139, R01 MH100027, R01 MH081754, U01 MH115746U01, MH105991, R01 MH109912, R01 MH110927)
- National Institute on Drug Abuse
- National Institute of Mental Health (U01 MH109532)
- Hartwell Foundation
- Simons Foundation (206744, 239766)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Keywords
- mental illness, genetic architecture, polygenic risk, genetic loci, functional genomics, gene expression regulation, gene expression, brain cell types, brain development, pathophysiology, autism spectrum disorder
- MeSH terms
- Alleles, Mental Disorders, Gene Frequency, Humans, Mental Health, Genetic Variation, Genetic Predisposition to Disease, Multifactorial Inheritance, Genomics, Genome-Wide Association Study
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-06.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-06.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review