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Contrasting genetic architectures of schizophrenia and other complex diseases using fast variance-components analysis
Open accessAbstract
Heritability analyses of genome-wide association study (GWAS) cohorts have yielded important insights into complex disease architecture, and increasing sample sizes hold the promise of further discoveries. Here we analyze the genetic architectures of schizophrenia in 49,806 samples from the PGC and nine complex diseases in 54,734 samples from the GERA cohort. For schizophrenia, we infer an overwhelmingly polygenic disease architecture in which ≥71% of 1-Mb genomic regions harbor ≥1 variant influencing schizophrenia risk. We also observe significant enrichment of heritability in GC-rich regions and in higher-frequency SNPs for both schizophrenia and GERA diseases. In bivariate analyses, we observe significant genetic correlations (ranging from 0.18 to 0.85) for several pairs of GERA diseases; genetic correlations were on average 1.3 tunes stronger than the correlations of overall disease liabilities. To accomplish these analyses, we developed a fast algorithm for multicomponent, multi-trait variance-components analysis that overcomes prior computational barriers that made such analyses intractable at this scale.
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“As a class of variation, common variants explain ~24% of the variance in disease liability 11 .”
From Exome sequencing identifies rare coding variants in 10 genes which confer substantial risk for schizophrenia (2020) · cites this paper as [11]
In the citing paper
“This has been borne out by genome-wide association studies (GWAS) which have now, in a companion paper, identified 270 common (minor allele frequency [MAF] > 1%) risk loci of individually small effect (median odds ratio [OR] < 1.05)13.”
From Rare coding variants in ten genes confer substantial risk for schizophrenia (2022) · cites this paper as [13]
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“In tandem with a companion paper from the Psychiatric Genomics Consortium13, we provide evidence that common and ultra-rare coding variants identify an overlapping set of genes.”
From Rare coding variants in ten genes confer substantial risk for schizophrenia (2022) · cites this paper as [13]
In the citing paper
“To evaluate the overlap of schizophrenia associations from common variants and ultra-rare coding variant analyses, we jointly analyzed our results with the largest GWAS of schizophrenia to date, which identified common variant associations at 270 distinct loci from the analysis of 69,369 cases and 236,642 controls13.”
From Rare coding variants in ten genes confer substantial risk for schizophrenia (2022) · cites this paper as [13]
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Metadata
- Authors
- Schizophrenia Working Group of the Psychiatric Genomics Consortium, Loh, P.-R., Bhatia, G., Gusev, A., Finucane, H. K., Bulik-Sullivan, B. K., Pollack, S. J., de Candia, T. R., Lee, S. H., Wray, N. R., Kendler, K. S., O'Donovan, M. C., Neale, B. M., Patterson, N., & Price, A. L.
- Affiliations
- Broad Institute (US)
- Massachusetts Institute of Technology (US)
- The University of Queensland (AU)
- Virginia Commonwealth University (US)
- Corresponding author
- Loh, Po-Ru
- Price, Alkes L
- ORCID
- Venue
- Nature Genetics
- Published
- 2015-11-02
- Volume
- 47
- Issue
- 12
- Pages
- 1385-1392
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- PMC
- PMC4666835
- OpenAlex
- W2168354474
- Cited by
- 449
- References
- 69
- Citations by year
- 2026: 21 · 2025: 27 · 2024: 30 · 2023: 42 · 2022: 46 · 2021: 61 · 2020: 50 · 2019: 52 · 2018: 49 · 2017: 43 · 2016: 25 · 2015: 3
- FWCI
- 27.33
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Genetics (publishedVersion)
- PubMed (publishedVersion)
- Research Publications (Maastricht University) (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- EPubDev Repository (submittedVersion)
- Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion)
- Lancaster EPrints (Lancaster University) (submittedVersion)
- ORCA Online Research @Cardiff (Cardiff University) (submittedVersion)
- Institutional Research Information System (Università degli Studi di Trento) (submittedVersion)
- Minerva Access (University of Melbourne) (submittedVersion)
- Lirias (KU Leuven) (submittedVersion)
- RUNE (Research UNE) (submittedVersion)
- Research Publications (Maastricht University) (submittedVersion)
- NOVA (University of Newcastle Australia) (submittedVersion)
- Funders
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (480- 05-003)
- Lundbeckfonden (R155-2014-1724)
- National Institutes of Health (1s10rr028832-01)
- Medical Research Council (MR/L010305/1)
- National Institute of Mental Health (R01MH085548, R01MH101244)
- National Human Genome Research Institute (R01HG006399, F32HG007805)
- National Center for Research Resources (S10 RR028832, 1S10RR028832-01)
- 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 › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- schizophrenia, genetic architecture, polygenic architecture, complex diseases, genetic correlation, heritability, variance component analysis, multi-trait analysis, GC-rich regions, single nucleotide polymorphisms, genetic risk variants
- MeSH terms
- Aging, Algorithms, Analysis of Variance, Humans, Phenotype, Risk Factors, Schizophrenia, Genetic Predisposition to Disease, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Genome-Wide Association Study
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