Journal
BIOMEDICINES
Volume 10, Issue 8, Pages -Publisher
MDPI
DOI: 10.3390/biomedicines10081782
Keywords
Alzheimer's disease; mitochondria; association studies in genetics; epistasis; weighted gene co-expression network analysis
Categories
Funding
- National Natural Science Foundation of China [31670779]
- Fundamental Research Funds for the Central Universities [2662021JC008]
- National Institutes of Health [P30AG10161, P30AG072975, R01AG15819, R01AG17917, U01AG46152, U01AG61356]
- Illinois Department of Public Health
- Translational Genomics Research Institute (Kronos Science)
- Alzheimer's Disease Neuroimaging Initiative - Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health) [U01 AG024904]
- DOD ADNI (Department of Defense) [W81XWH-12-2-0012]
- [R01AG30146]
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Using systems genetics methods, mitochondrial-associated nuclear genes involved in the pathogenesis of AD were identified and AD risk prediction models were constructed.
Cumulative evidence has revealed the association between mitochondrial dysfunction and Alzheimer's disease (AD). Because the number of mitochondrial genes is very limited, the mitochondrial pathogenesis of AD must involve certain nuclear genes. In this study, we employed systems genetic methods to identify mitochondrion-associated nuclear genes that may participate in the pathogenesis of AD. First, we performed a mitochondrial genome-wide association study (MiWAS, n = 809) to identify mitochondrial single-nucleotide polymorphisms (MT-SNPs) associated with AD. Then, epistasis analysis was performed to examine interacting SNPs between the mitochondrial and nuclear genomes. Weighted co-expression network analysis (WGCNA) was applied to transcriptomic data from the same sample (n = 743) to identify AD-related gene modules, which were further enriched by mitochondrion-associated genes. Using hub genes derived from these modules, random forest models were constructed to predict AD risk in four independent datasets (n = 743, n = 542, n = 161, and n = 540). In total, 9 potentially significant MT-SNPs and 14,340 nominally significant MT-nuclear interactive SNPs were identified for AD, which were validated by functional analysis. A total of 6 mitochondrion-related modules involved in AD pathogenesis were found by WGCNA, from which 91 hub genes were screened and used to build AD risk prediction models. For the four independent datasets, these models perform better than those derived from AD genes identified by genome-wide association studies (GWASs) or differential expression analysis (DeLong's test, p < 0.05). Overall, through systems genetics analyses, mitochondrion-associated SNPs/genes with potential roles in AD pathogenesis were identified and preliminarily validated, illustrating the power of mitochondrial genetics in AD pathogenesis elucidation and risk prediction.
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