Journal of affective disorders · 2025
Unraveling the genetic interplay between sleep disorders and Alzheimer's disease: From shared genes to potential therapeutic targets.
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Gao Xiaoya, Jiang Peixin, Liu Leiyuan, Huang Yanling, Tan Henghui, Guo Wanyun, Xie Haiting, Xing Pengpeng, Wang Qing, Peng Sibo, Hua Junjie, Wang Yuankai, Lan Yufei, Jiang Lingxiao, Lin Hualiang, Guo Hongbo
Аннотация
BACKGROUND: Sleep disorders are potential risk factors for Alzheimer's disease (AD), but their genetic association and shared gene mechanisms remain unclear. This study investigate the genetic correlation between AD and four sleep disorders phenotypes, and examined AD-sleep shared pathways in major depressive disorder (MDD) to assess a broader neuropsychiatric implication.
METHODS: Linkage disequilibrium score regression (LDSC) and high-definition likelihood (HDL) were employed to investigate shared genetic architecture. SNP-Level PLACO analysis identified pleiotropic loci. MAGMA mapped these loci to the genes which implicated in AD pathology, while expression quantitative trait loci (QTL) identified brain-expressed genes involved in key pathways.
RESULTS: Data from 1,862,604 participants, including 71,880 AD or AD-by-proxy cases and 383,378 controls, along with 92,765 individuals with sleep disorders and 1,314,581 controls, revealed positive genetic correlations between combined sleep disorders (CSD) and AD (LDSC: rg = 0.075, P = 0.030; HDL: rg = 0.133, P = 0.024) and between sleep apnea syndrome (SAS) and AD (LDSC: rg = 0.081, P = 0.018; HDL: rg = 0.132, P = 0.027). Nine specific genes including MARK4, GPC2, PVRL2, ACMSD, AC006126.3, BIN1, APOC1, APOC4, and APOC2 were implicated in AD pathology, with common pathways involving complement activation, immune response activation, and protein-lipid complex formation. Crucially, these AD-sleep shared pathways were also significantly enriched for MDD risk.
CONCLUSION: These findings highlight a genetic association between sleep disorders and AD, which extends to MDD through common biological pathways, revealing shared genetic risk factors and mechanisms, which may inform novel therapeutic strategies.
METHODS: Linkage disequilibrium score regression (LDSC) and high-definition likelihood (HDL) were employed to investigate shared genetic architecture. SNP-Level PLACO analysis identified pleiotropic loci. MAGMA mapped these loci to the genes which implicated in AD pathology, while expression quantitative trait loci (QTL) identified brain-expressed genes involved in key pathways.
RESULTS: Data from 1,862,604 participants, including 71,880 AD or AD-by-proxy cases and 383,378 controls, along with 92,765 individuals with sleep disorders and 1,314,581 controls, revealed positive genetic correlations between combined sleep disorders (CSD) and AD (LDSC: rg = 0.075, P = 0.030; HDL: rg = 0.133, P = 0.024) and between sleep apnea syndrome (SAS) and AD (LDSC: rg = 0.081, P = 0.018; HDL: rg = 0.132, P = 0.027). Nine specific genes including MARK4, GPC2, PVRL2, ACMSD, AC006126.3, BIN1, APOC1, APOC4, and APOC2 were implicated in AD pathology, with common pathways involving complement activation, immune response activation, and protein-lipid complex formation. Crucially, these AD-sleep shared pathways were also significantly enriched for MDD risk.
CONCLUSION: These findings highlight a genetic association between sleep disorders and AD, which extends to MDD through common biological pathways, revealing shared genetic risk factors and mechanisms, which may inform novel therapeutic strategies.