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Fine-mapping genomic loci refines bipolar disorder risk genes.

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Title: Fine-mapping genomic loci refines bipolar disorder risk genes.
Authors: Koromina, Maria (AUTHOR), Ravi, Ashvin (AUTHOR), Panagiotaropoulou, Georgia (AUTHOR), Schilder, Brian M. (AUTHOR), Humphrey, Jack (AUTHOR), Braun, Alice (AUTHOR), Bidgeli, Tim (AUTHOR), Chatzinakos, Chris (AUTHOR), Coombes, Brandon J. (AUTHOR), Kim, Jaeyoung (AUTHOR), Liu, Xiaoxi (AUTHOR), Terao, Chikashi (AUTHOR), O'Connell, Kevin S. (AUTHOR), Adams, Mark J. (AUTHOR), Adolfsson, Rolf (AUTHOR), Alda, Martin (AUTHOR), Alfredsson, Lars (AUTHOR), Andlauer, Till F. M. (AUTHOR), Andreassen, Ole A. (AUTHOR), Antoniou, Anastasia (AUTHOR)
Source: Nature Neuroscience. Jul2025, Vol. 28 Issue 7, p1393-1403. 11p.
Abstract: Bipolar disorder is a heritable mental illness with complex etiology. While the largest published genome-wide association study identified 64 bipolar disorder risk loci, the causal SNPs and genes within these loci remain unknown. We applied a suite of statistical and functional fine-mapping methods to these loci and prioritized 17 likely causal SNPs for bipolar disorder. We mapped these SNPs to genes and investigated their likely functional consequences by integrating variant annotations, brain cell-type epigenomic annotations, brain quantitative trait loci and results from rare variant exome sequencing in bipolar disorder. Convergent lines of evidence supported the roles of genes involved in neurotransmission and neurodevelopment, including SCN2A, TRANK1, DCLK3, INSYN2B, SYNE1, THSD7A, CACNA1B, TUBBP5, FKBP2, RASGRP1, FURIN, FES, MED24 and THRA among others in bipolar disorder. These represent promising candidates for functional experiments to understand biological mechanisms and therapeutic potential. Additionally, we demonstrated that fine-mapping effect sizes can improve performance of bipolar disorder polygenic risk scores across diverse populations and present a high-throughput fine-mapping pipeline. This study used fine-mapping to analyze genetic regions associated with bipolar disorder, identifying specific risk genes and providing new insights into the biology of the condition that may guide future research and treatment approaches. [ABSTRACT FROM AUTHOR]
Copyright of Nature Neuroscience is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Bipolar disorder is a heritable mental illness with complex etiology. While the largest published genome-wide association study identified 64 bipolar disorder risk loci, the causal SNPs and genes within these loci remain unknown. We applied a suite of statistical and functional fine-mapping methods to these loci and prioritized 17 likely causal SNPs for bipolar disorder. We mapped these SNPs to genes and investigated their likely functional consequences by integrating variant annotations, brain cell-type epigenomic annotations, brain quantitative trait loci and results from rare variant exome sequencing in bipolar disorder. Convergent lines of evidence supported the roles of genes involved in neurotransmission and neurodevelopment, including SCN2A, TRANK1, DCLK3, INSYN2B, SYNE1, THSD7A, CACNA1B, TUBBP5, FKBP2, RASGRP1, FURIN, FES, MED24 and THRA among others in bipolar disorder. These represent promising candidates for functional experiments to understand biological mechanisms and therapeutic potential. Additionally, we demonstrated that fine-mapping effect sizes can improve performance of bipolar disorder polygenic risk scores across diverse populations and present a high-throughput fine-mapping pipeline. This study used fine-mapping to analyze genetic regions associated with bipolar disorder, identifying specific risk genes and providing new insights into the biology of the condition that may guide future research and treatment approaches. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Nature Neuroscience is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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