4.2 Article

Molecular genetic overlap in bipolar disorder, schizophrenia, and major depressive disorder

期刊

WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY
卷 15, 期 3, 页码 200-208

出版社

INFORMA HEALTHCARE
DOI: 10.3109/15622975.2012.662282

关键词

Genome-wide association; polygenic model; allele burden; psychosis; prediction

资金

  1. National Institute of Mental Health (NIMH), National Institutes of Health, Department of Health and Human Services (IRP-NIMH-NIH-DHHS)
  2. Deutsche Forschungsgemeinschaft (DFG)
  3. National German Genome Research Network (NGFN)
  4. NARSAD
  5. Alfried Krupp von Bohlen und Halbach-Stiftung
  6. Intramural Research Program of the National Institute on Aging, National Institutes of Health, Department of Health and Human Services [Z01 AG000932-02]

向作者/读者索取更多资源

Objectives. Genome-wide association studies (GWAS) in complex phenotypes, including psychiatric disorders, have yielded many replicated findings, yet individual markers account for only a small fraction of the inherited differences in risk. We tested the performance of polygenic models in discriminating between cases and healthy controls and among cases with distinct psychiatric diagnoses. Methods. GWAS results in bipolar disorder (BD), major depressive disorder (MDD), schizophrenia (SZ), and Parkinson's disease (PD) were used to assign weights to individual alleles, based on odds ratios. These weights were used to calculate allele scores for individual cases and controls in independent samples, summing across many single nucleotide polymorphisms (SNPs). How well allele scores discriminated between cases and controls and between cases with different disorders was tested by logistic regression. Results. Large sets of SNPs were needed to achieve even modest discrimination between cases and controls. The most informative SNPs were overlapping in BD, SZ, and MDD, with correlated effect sizes. Little or no overlap was seen between allele scores for psychiatric disorders and those for PD. Conclusions. BD, SZ, and MDD all share a similar polygenic component, but the polygenic models tested lack discriminative accuracy and are unlikely to be useful for clinical diagnosis.

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