Abstract
Background: Alzheimer’s disease (AD) is a significant public health issue. AD has been linked with methylenetetrahydrofolate reductase (MTHFR) C677T polymorphism, but the findings have been inconsistent. The purpose of this meta-predictive analysis is to examine the associations between MTHFR polymorphisms and epigenetic factors, including air pollution, with AD risk using big data analytics approaches. Methods and Results: Forty-three studies (44 groups) were identified by searching various databases. MTHFR C677T TT and CT genotypes had significant associations with AD risk in all racial populations (RR = 1.13, p = 0.0047; and RR = 1.12, p < 0.0001 respectively). Meta-predictive analysis showed significant increases of percentages of MTHFR C677T polymorphism with increased air pollution levels in both AD case group and control group (p = 0.0021–0.0457); with higher percentages of TT and CT genotypes in the AD case group than that in the control group with increased air pollution levels. Conclusions: The impact of MTHFR C677T polymorphism on susceptibility to AD was modified by level of air pollution. Future studies are needed to further examine the effects of gene-environment interactions including air pollution on AD risk for world populations.
Highlights
Alzheimer’s disease (AD) is a degenerative brain disease and the leading cause of dementia [1], causing great public health concerns
Given that air pollution could be one of the factors involved in AD causality, for its significant impact on public health, the aim of the present study was to conduct a meta-predictive analysis to examine the association between methylenetetrahydrofolate reductase (MTHFR) polymorphisms and AD in the context of gene-environment interaction
For pooled analyses on MTHFR C677T polymorphism, we included a total of 4732 AD cases and 5979 controls from 44 study groups
Summary
Alzheimer’s disease (AD) is a degenerative brain disease and the leading cause of dementia [1], causing great public health concerns. In 2016, an estimated 5.3 million people in the U.S were affected by AD, and approximately 10 million U.S residents will live with AD by 2050 [2]. 2015 and 2016, the estimated direct U.S costs of AD were $236 billion [1], and the indirect costs (e.g., unpaid caregiving, loss or reduction of income, and benefits for caregivers) amounted to another. Alzheimer’s disease (AD) is a significant public health issue. AD has been linked with methylenetetrahydrofolate reductase (MTHFR) C677T polymorphism, but the findings have been inconsistent. The purpose of this meta-predictive analysis is to examine the associations between MTHFR polymorphisms and epigenetic factors, including air pollution, with AD risk using big data analytics approaches.
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