Common polygenic variation contributes to risk of schizophrenia and bipolar disorder

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Schizophrenia is a severe mental disorder with a lifetime risk of about 1%, characterized by hallucinations, delusions and cognitive deficits, with heritability estimated at up to 80%. We performed a genome-wide association study of 3,322 European individuals with schizophrenia and 3,587 controls. Here we show, using two analytic approaches, the extent to which common genetic variation underlies the risk of schizophrenia. First, we implicate the major histocompatibility complex. Second, we provide molecular genetic evidence for a substantial polygenic component to the risk of schizophrenia involving thousands of common alleles of very small effect. We show that this component also contributes to the risk of bipolar disorder, but not to several non-psychiatric diseases.

Related collections

Most cited references 25

Record: found
Abstract: found
Article: not found

PLINK: a tool set for whole-genome association and population-based linkage analyses.

Shaun Purcell, Benjamin M. Neale, Kathe Todd-Brown … (2007)

Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.

0 comments Cited 5191 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls.

Neil Walker, Peter Holmans (2007)

There is increasing evidence that genome-wide association (GWA) studies represent a powerful approach to the identification of genes involved in common human diseases. We describe a joint GWA study (using the Affymetrix GeneChip 500K Mapping Array Set) undertaken in the British population, which has examined approximately 2,000 individuals for each of 7 major diseases and a shared set of approximately 3,000 controls. Case-control comparisons identified 24 independent association signals at P < 5 x 10(-7): 1 in bipolar disorder, 1 in coronary artery disease, 9 in Crohn's disease, 3 in rheumatoid arthritis, 7 in type 1 diabetes and 3 in type 2 diabetes. On the basis of prior findings and replication studies thus-far completed, almost all of these signals reflect genuine susceptibility effects. We observed association at many previously identified loci, and found compelling evidence that some loci confer risk for more than one of the diseases studied. Across all diseases, we identified a large number of further signals (including 58 loci with single-point P values between 10(-5) and 5 x 10(-7)) likely to yield additional susceptibility loci. The importance of appropriately large samples was confirmed by the modest effect sizes observed at most loci identified. This study thus represents a thorough validation of the GWA approach. It has also demonstrated that careful use of a shared control group represents a safe and effective approach to GWA analyses of multiple disease phenotypes; has generated a genome-wide genotype database for future studies of common diseases in the British population; and shown that, provided individuals with non-European ancestry are excluded, the extent of population stratification in the British population is generally modest. Our findings offer new avenues for exploring the pathophysiology of these important disorders. We anticipate that our data, results and software, which will be widely available to other investigators, will provide a powerful resource for human genetics research.

0 comments Cited 592 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Schizophrenia as a complex trait: evidence from a meta-analysis of twin studies.

Patrick F Sullivan, Kenneth S Kendler, Michael C Neale (2003)

There are many published twin studies of schizophrenia. Although these studies have been reviewed previously, to our knowledge, no review has provided quantitative summary estimates of the impact of genes and environment on liability to schizophrenia that also accounted for the different ascertainment strategies used. To calculate meta-analytic estimates of heritability in liability and shared and individual-specific environmental effects from the pooled twin data. We used a structured literature search to identify all published twin studies of schizophrenia, including MEDLINE, dissertation, and books-in-print searches. Of the 14 identified studies, 12 met the minimal inclusion criteria of systematic ascertainment. By using a multigroup twin model, we found evidence for substantial additive genetic effects-the point estimate of heritability in liability to schizophrenia was 81% (95% confidence interval, 73%-90%). Notably, there was consistent evidence across these studies for common or shared environmental influences on liability to schizophrenia-joint estimate, 11% (95% confidence interval, 3%-19%). Despite evidence of heterogeneity across studies, these meta-analytic results from 12 published twin studies of schizophrenia are consistent with a view of schizophrenia as a complex trait that results from genetic and environmental etiological influences. These results are broadly informative in that they provide no information about the specific identity of these etiological influences, but they do provide a component of a unifying empirical basis supporting the rationality of searches for underlying genetic and common environmental etiological factors.

0 comments Cited 231 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Journal

Title: Nature

Abbreviated Title: Nature

Publisher: Springer Science and Business Media LLC

ISSN (Print): 0028-0836

ISSN (Electronic): 1476-4687

Publication date Created: August 2009

Publication date (Electronic): July 1 2009

Publication date (Print): August 2009

Volume: 460

Issue: 7256

Pages: 748-752

Article

DOI: 10.1038/nature08185

PMC ID: 3912837

PubMed ID: 19571811

SO-VID: 9dc22146-2c53-4f0e-a972-4c39356d37ad

License:

http://www.springer.com/tdm

History

Data availability:

Comments

Comment on this article

scite_

Cited by 1,343

See all cited by

- Version 1

Common polygenic variation contributes to risk of schizophrenia and bipolar disorder

Read this article at

Abstract

Related collections

African e-Infrastructure Commons

Most cited references 25

PLINK: a tool set for whole-genome association and population-based linkage analyses.

Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls.

Schizophrenia as a complex trait: evidence from a meta-analysis of twin studies.

Author and article information

Journal

Article

History

Comments

Comment on this article

Similar content 2,111

Cited by 1,343