Investigating the common genetic architecture and causality of metabolic disorders with neurodegenerative diseases

• Published in: Diabetes, obesity & metabolism obesity & metabolism, 2024-12
• Main Authors: Hong, Hao, Fu, Qi, Gu, Pan, Zhao, Jingyi, Dai, Jinglan, Xu, Kuanfeng, Yang, Tao, Dai, Hao, Shen, Sipeng
• Format: Article
• Language: English
• ISSN: 1462-8902; 1463-1326; 1463-1326
• DOI: 10.1111/dom.16130

The co-occurrence of metabolic dysfunction and neurodegenerative diseases suggests a genetic link, yet the shared genetic architecture and causality remain unclear. We aimed to comprehensively characterise these genetic relationships. We investigated genetic correlations among four neurodegenerative diseases and seven metabolic dysfunctions, followed by bidirectional Mendelian randomisation (MR) to assess potential causal relationships. Pleiotropy analysis (PLACO) was used to detect the pleiotropic effects of genetic variants. Significant pleiotropic loci were refined and annotated using functional mapping and annotation (FUMA) and Bayesian colocalisation analysis. We further explored mapped genes with tissue-specific expression and gene set enrichment analyses. We identified significant genetic correlations in nine out of 28 trait pairs. MR suggested causal relationships between specific trait pairs. Pleiotropy analysis revealed 25 931 significant single-nucleotide polymorphisms, with 246 pleiotropic loci identified via FUMA and 55 causal loci through Bayesian colocalisation. These loci are involved in neurotransmitter transport and immune response mechanisms, notably the missense variant rs41286192 in SLC18B1. The tissue-specific analysis highlighted the pancreas, left ventricle, amygdala, and liver as critical organs in disease progression. Drug target analysis linked 74 unique genes to existing therapeutic agents, while gene set enrichment identified 189 pathways related to lipid metabolism, cell differentiation and immune responses. Our findings reveal a shared genetic basis, pleiotropic loci, and potential causal relationships between metabolic dysfunction and neurodegenerative diseases. These insights highlight the biological connections underlying their phenotypic association and offer implications for future research to reduce the risk of neurodegenerative diseases.