Multi-ancestry multi-trait analysis reveals shared genetics across major psychiatric disorders and Alzheimer’s disease

The clinical overlap between major psychiatric disorders (MPDs) and Alzheimer's disease (AD) implicates complex shared etiology. Previous studies demonstrated that both diseases are genetically complex and highly heritable, suggesting that more endeavors are necessary to be made from the very bottom to understand their genetic basis. With the advance of post-genomic analysis, multi-ancestry meta-analysis allows the generalizability of the genetic architecture across different populations to uncover ancestry-specific variants, while multi-trait analysis enables the discovery of the co-colocalized risk genomic regions across diseases. Therefore, in this study, we leveraged published GWAS summary statistics from European, East Asian, Hispanic and African American populations to report schizophrenia, major depressive disorders, and Alzheimer's disease risk loci and further fine-mapping to credible sets with >95% PP inclusion of the causal variant. We distilled 2871 potential traits from publicly available and found 134 traits significantly genetically correlated with both MPDs and AD using batch LD score regression. We then prioritized the identified loci from multi-ancestry results for cross-trait colocalization analysis to assess shared genetic etiology and further nominated 2 colocalized loci across both conditions, including rs2532240 and rs6504163. In the end, we finalized our analysis by validation and functional inference of the underlying susceptibility genes as well as putative mechanisms using evidence from multiple resources, including FIVEx, Open Targets, and scQTLbase.

Authors

Institutions

Publication Details

Journal
Translational Psychiatry
Published
2026-06-26
DOI
https://doi.org/10.1038/s41398-026-04213-0
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Multi-ancestry multi-trait analysis reveals shared genetics across major psychiatric disorders and Alzheimer’s disease

Xin Zheng, Yu Zhang, Lijie Ren, Hongye Feng
Translational Psychiatry
Genetic Associations and Epidemiology
article

Multi-ancestry multi-trait analysis reveals shared genetics across major psychiatric disorders and Alzheimer’s disease

Xin Zheng, Yu Zhang, Lijie Ren, Hongye Feng
article en

Abstract

The clinical overlap between major psychiatric disorders (MPDs) and Alzheimer's disease (AD) implicates complex shared etiology. Previous studies demonstrated that both diseases are genetically complex and highly heritable, suggesting that more endeavors are necessary to be made from the very bottom to understand their genetic basis. With the advance of post-genomic analysis, multi-ancestry meta-analysis allows the generalizability of the genetic architecture across different populations to uncover ancestry-specific variants, while multi-trait analysis enables the discovery of the co-colocalized risk genomic regions across diseases. Therefore, in this study, we leveraged published GWAS summary statistics from European, East Asian, Hispanic and African American populations to report schizophrenia, major depressive disorders, and Alzheimer's disease risk loci and further fine-mapping to credible sets with >95% PP inclusion of the causal variant. We distilled 2871 potential traits from publicly available and found 134 traits significantly genetically correlated with both MPDs and AD using batch LD score regression. We then prioritized the identified loci from multi-ancestry results for cross-trait colocalization analysis to assess shared genetic etiology and further nominated 2 colocalized loci across both conditions, including rs2532240 and rs6504163. In the end, we finalized our analysis by validation and functional inference of the underlying susceptibility genes as well as putative mechanisms using evidence from multiple resources, including FIVEx, Open Targets, and scQTLbase.

Translational Psychiatry
Shenzhen Institutes of Advanced Technology (CN), Shenzhen Second People's Hospital (CN)
Natural Science Foundation of Guangdong Province, National Science and Technology Major Project
Openalex Percentile: Top 7%
Genetic Associations and Epidemiology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.