Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
Analyses of plasma multi-omic data across ancestries identify novel pathways implicated in Alzheimer's disease.
СтатьяПоддержка исследования: вне правительства СШАПоддержка NIH: внешняя программаНазвание и аннотация: Перевод пока не подготовлен
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Yang Chengran, Timsina Jigyasha, Liu Menghan, Budde John, Kohlfeld Pat, Brock William, Morris John C, Holtzman David M, Sung Yun Ju, Cruchaga Carlos
Аннотация
INTRODUCTION: Few genetic studies on Alzheimer's disease (AD) have incorporated multiple ancestries and omic datasets to pinpoint actionable AD risk effectors for each ancestry.
METHODS: Here, we first performed genetic colocalization between molecular phenotypes (proteomics and metabolomics) from two ancestral groups (European [EUR] and African [AFR]) and the two largest EUR AD genome-wide association studies. We next performed pathway enrichment analyses to identify biological mechanisms.
RESULTS: We found 21 proteins and one metabolite colocalized with AD risk that were shared between the EUR and AFR ancestry groups. We also identified 25% AFR and 60% EUR proteins; 50% AFR and 10% EUR metabolites were unique. The pathway enrichment analyses nominated interleukin-1 production and lipid pathway were shared underlying proteomic and metabolomic findings, respectively.
DISCUSSION: Our findings indicate that these four plasma datasets may pinpoint different effectors of AD risk in diverse populations; findings from AFR participants require validation with AFR-based genome-wide association study data.
HIGHLIGHTS: For proteomics, 61% of findings for European (EUR) ancestry and 72% for African (AFR) ancestry were not previously reported. For metabolomics, 83% of findings for EUR ancestry and 50% AFR ancestry were not previously reported. Both convergent and divergent pathways were identified in EUR- and AFR-ancestry stratified analyses in either proteomics or metabolomics findings.
METHODS: Here, we first performed genetic colocalization between molecular phenotypes (proteomics and metabolomics) from two ancestral groups (European [EUR] and African [AFR]) and the two largest EUR AD genome-wide association studies. We next performed pathway enrichment analyses to identify biological mechanisms.
RESULTS: We found 21 proteins and one metabolite colocalized with AD risk that were shared between the EUR and AFR ancestry groups. We also identified 25% AFR and 60% EUR proteins; 50% AFR and 10% EUR metabolites were unique. The pathway enrichment analyses nominated interleukin-1 production and lipid pathway were shared underlying proteomic and metabolomic findings, respectively.
DISCUSSION: Our findings indicate that these four plasma datasets may pinpoint different effectors of AD risk in diverse populations; findings from AFR participants require validation with AFR-based genome-wide association study data.
HIGHLIGHTS: For proteomics, 61% of findings for European (EUR) ancestry and 72% for African (AFR) ancestry were not previously reported. For metabolomics, 83% of findings for EUR ancestry and 50% AFR ancestry were not previously reported. Both convergent and divergent pathways were identified in EUR- and AFR-ancestry stratified analyses in either proteomics or metabolomics findings.