Genetics and genomics of psychiatric disease
Open accessAbstract
Large-scale genomic investigations have just begun to illuminate the molecular genetic contributions to major psychiatric illnesses, ranging from small-effect-size common variants to larger-effect-size rare mutations. The findings provide causal anchors from which to understand their neurobiological basis. Although these studies represent enormous success, they highlight major challenges reflected in the heterogeneity and polygenicity of all of these conditions and the difficulty of connecting multiple levels of molecular, cellular, and circuit functions to complex human behavior. Nevertheless, these advances place us on the threshold of a new frontier in the pathophysiological understanding, diagnosis, and treatment of psychiatric disease.
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The Psychiatric Genomics Consortium has identified 142 GWAS loci associated with schizophrenia.
“the Psychiatric Genomics Consortium (PGC) has identified 142 GWAS loci associated with schizophrenia (SCZ) (6)”
From Comprehensive functional genomic resource and integrative model for the human brain (2018) · cites this paper as [6]
These results augment a substantial body of research demonstrating that genetic influences on psychopathology do not map cleanly onto the clinical nosology instantiated in the DSM or ICD.
“These results augment a substantial body of research demonstrating that genetic influences on psychopathology do not map cleanly onto the clinical nosology instantiated in the DSM or ICD (Geschwind and Flint, 2015; Smoller et al., 2019)”
From Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders (2019) · cites this paper as Geschwind and Flint, 2015
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.
“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).”
From Defining the genetic, genomic, cellular, and diagnostic architectures of psychiatric disorders (2019) · cites this paper as Geschwind and Flint, 2015
The 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).”
From Defining the genetic, genomic, cellular, and diagnostic architectures of psychiatric disorders (2019) · cites this paper as Geschwind and Flint, 2015
The 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).”
From Defining the genetic, genomic, cellular, and diagnostic architectures of psychiatric disorders (2019) · cites this paper as Geschwind and Flint, 2015
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Duplication of the SLIT3 Locus on 5q35.1 Predisposes to Major Depressive Disorder
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Otte, C., Gold, S. M., Penninx, B. W., Pariante, C. M., Etkin, A., Fava, M., Mohr, D. C., & Schatzberg, A. F. (2016) · Nature Reviews Disease Primers · doi:10.1038/nrdp.2016.65 · Cited by 2,269 · see citing works
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“Cases met criteria for lifetime diagnosis of bipolar disorder as defined by DSM-IV, ICD-9, or ICD-10, which was established using interview-based structured assessment, clinician-administered checklists, or review of medical records.”
BackgroundInfluentialSelf-citationComprehensive functional genomic resource and integrative model for the human brain
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Self-citationShared molecular neuropathology across major psychiatric disorders parallels polygenic overlap
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Self-citationAdvancing the understanding of autism disease mechanisms through genetics
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“Though heritable to various extents (ranging from 35% for MDD to 60% for bipolar disorder; Smoller and Finn, 2003; Geschwind and Flint, 2015), the nature of the vulnerability to these disorders relates to how the individual responds to the environment (Akil et al., 2018).”
BackgroundInherited and de novo genetic risk for autism impacts shared networks
Ruzzo, E. K., Pérez-Cano, L., Jung, J.-Y., Wang, L.-K., Kashef-Haghighi, D., Hartl, C., Singh, C., Xu, J., Hoekstra, J. N., Leventhal, O., et al. (2019) · Cell · doi:10.1016/j.cell.2019.07.015 · Cited by 457 · see citing works
Self-citationDefining the genetic, genomic, cellular, and diagnostic architectures of psychiatric disorders
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“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-citationA small number of abnormal brain connections predicts adult autism spectrum disorder
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Building Models of Brain Disorders with Three-Dimensional Organoids
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The road to precision psychiatry: translating genetics into disease mechanisms
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HCN2 Channels in Cholinergic Interneurons of Nucleus Accumbens Shell Regulate Depressive Behaviors
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The Molecular Basis of Human Brain Evolution
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- Authors
- Geschwind, D. H., & Flint, J.
- Affiliations
- University of California, Los Angeles (US)
- Wellcome Trust Center for Human Genetics, University of Oxford, Oxford, UK.
- Corresponding author
- Geschwind, Daniel H.
- ORCID
- Geschwind, Daniel H.
- Venue
- Science
- Published
- 2015-09-25
- Volume
- 349
- Issue
- 6255
- Pages
- 1489-1494
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC4694563
- OpenAlex
- W2238387778
- Cited by
- 424
- References
- 125
- Citations by year
- 2026: 20 · 2025: 23 · 2024: 25 · 2023: 40 · 2022: 48 · 2021: 33 · 2020: 41 · 2019: 61 · 2018: 57 · 2017: 40 · 2016: 33 · 2015: 2
- FWCI
- 5.57
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Institute of Mental Health (5R01 MH100027, 5R01 MH094714)
- Simons Foundation (206744)
- Wellcome Trust
- 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 › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
- Keywords
- mental illness, molecular genetics, genomics, common genetic variants, rare mutations, polygenicity, disease heterogeneity, neurobiology, pathophysiology, psychiatric diagnosis, psychiatric treatment
- MeSH terms
- Mental Disorders, DNA Mutational Analysis, Humans, Models, Genetic, Mutation, Risk Factors, Genetic Heterogeneity, Genomics
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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.
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