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A Local Genetic Correlation Analysis Provides Biological Insights Into the Shared Genetic Architecture of Psychiatric and Substance Use Phenotypes

      Abstract

      Background

      Global genetic correlation analysis has provided valuable insight into the shared genetic basis between psychiatric and substance use disorders. However, little is known about which regions disproportionately contribute to the global correlation.

      Methods

      We used Local Analysis of [co]Variant Annotation to calculate bivariate local genetic correlations across 2495 approximately equal-sized, semi-independent genomic regions for 20 psychiatric and substance use phenotypes. We performed a transcriptome-wide association study using expression weights from the prefrontal cortex to identify risk genes for each phenotype, followed by probabilistic fine-mapping to prioritize credible causal genes within each bivariate locus.

      Results

      We detected 80 significant (p < 2.08 × 10−6) bivariate local genetic correlations across 61 loci. The expression effect directions for risk genes within each bivariate locus were largely consistent with the local correlation coefficients, suggesting that genetically regulated gene expression may be used in the functional interpretation of local genetic correlations. Probabilistic fine-mapping identified several genes that may drive pleiotropic mechanisms for genetically correlated phenotypes. For example, we confirmed a local genetic correlation between schizophrenia and smoking behavior at 15q25 and prioritized PSMA4 as the most credible gene candidate underlying both phenotypes.

      Conclusions

      Our study reveals previously unreported local bivariate genetic correlations between psychiatric and substance use phenotypes, which we fine-mapped to identify shared credible causal genes underlying genetically correlated phenotypes.

      Keywords

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      Linked Article

      • Using Local and Global Genetic Correlation Approaches to Help Elucidate the Shared Genetic Etiology of Psychiatric and Substance Use Traits
        Biological PsychiatryVol. 92Issue 7
        • Preview
          Recent years have brought substantial progress in understanding the genetic etiology of psychiatric disorders, substance use traits, and substance use disorders (SUDs) (1–4). Genome-wide association studies (GWASs) have benefited greatly from large-scale datasets generated across international consortia and mega-biobanks allowing for well-powered GWASs of many psychiatric and substance use traits. These efforts have resulted in the discovery of thousands of genetic loci that influence these traits, have helped researchers understand the genetic architecture and polygenicity across disorders, and have informed our knowledge of patterns of shared genetic influences—largely through the application of global genetic correlation approaches (1–4).
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