Alireza Nazarian, Marissa Morado, Alexander M. Kulminski
{"title":"复杂的遗传相互作用影响BIN1和MS4A6A基因座对阿尔茨海默病风险的易感性","authors":"Alireza Nazarian, Marissa Morado, Alexander M. Kulminski","doi":"10.1007/s11357-024-01477-6","DOIUrl":null,"url":null,"abstract":"<p>Genetics is the second strongest risk factor for Alzheimer’s disease (AD) after age. More than 70 loci have been implicated in AD susceptibility so far, and the genetic architecture of AD entails both additive and nonadditive contributions from these loci. To better understand nonadditive impact of single-nucleotide polymorphisms (SNPs) on AD risk, we examined individual, joint, and interacting (SNPxSNP) effects of 139 and 66 SNPs mapped to the <i>BIN1</i> and <i>MS4A6A</i> AD-associated loci, respectively. The analyses were conducted by fitting three respective dominant allelic-effect models using data from four independent studies. Joint effects were analyzed by considering pairwise combinations of genotypes of the selected SNPs, i.e., compound genotypes (CompG). The individual SNP analyses showed associations of 18 <i>BIN1</i> SNPs and 4 <i>MS4A6A</i> SNPs with AD. We identified 589 <i>BIN1</i> and 217 <i>MS4A6A</i> SNP pairs associated with AD in the CompG analysis, although their individual SNPs were not linked to AD independently. Notably, 34 <i>BIN1</i> and 10 <i>MS4A6A</i> SNP pairs exhibited both significant SNPxSNP interaction effects and significant CompG effects. The vast majority of nonadditive effects were captured through the CompG analysis. These results expand the current understanding of the contributions of the <i>BIN1</i> and <i>MS4A6A</i> loci to AD susceptibility. The identified nonadditive effects suggest a significant genetic modulation mechanism underlying the genetic heterogeneity of AD in these loci. Our findings highlight the importance of considering nonadditive genetic impacts on AD risk beyond the traditional SNPxSNP approximation, as they may uncover critical mechanisms not apparent when examining SNPs individually.</p>","PeriodicalId":12730,"journal":{"name":"GeroScience","volume":"28 1","pages":""},"PeriodicalIF":5.3000,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Complex genetic interactions affect susceptibility to Alzheimer's disease risk in the BIN1 and MS4A6A loci\",\"authors\":\"Alireza Nazarian, Marissa Morado, Alexander M. Kulminski\",\"doi\":\"10.1007/s11357-024-01477-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Genetics is the second strongest risk factor for Alzheimer’s disease (AD) after age. More than 70 loci have been implicated in AD susceptibility so far, and the genetic architecture of AD entails both additive and nonadditive contributions from these loci. To better understand nonadditive impact of single-nucleotide polymorphisms (SNPs) on AD risk, we examined individual, joint, and interacting (SNPxSNP) effects of 139 and 66 SNPs mapped to the <i>BIN1</i> and <i>MS4A6A</i> AD-associated loci, respectively. The analyses were conducted by fitting three respective dominant allelic-effect models using data from four independent studies. Joint effects were analyzed by considering pairwise combinations of genotypes of the selected SNPs, i.e., compound genotypes (CompG). The individual SNP analyses showed associations of 18 <i>BIN1</i> SNPs and 4 <i>MS4A6A</i> SNPs with AD. We identified 589 <i>BIN1</i> and 217 <i>MS4A6A</i> SNP pairs associated with AD in the CompG analysis, although their individual SNPs were not linked to AD independently. Notably, 34 <i>BIN1</i> and 10 <i>MS4A6A</i> SNP pairs exhibited both significant SNPxSNP interaction effects and significant CompG effects. The vast majority of nonadditive effects were captured through the CompG analysis. These results expand the current understanding of the contributions of the <i>BIN1</i> and <i>MS4A6A</i> loci to AD susceptibility. The identified nonadditive effects suggest a significant genetic modulation mechanism underlying the genetic heterogeneity of AD in these loci. 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Complex genetic interactions affect susceptibility to Alzheimer's disease risk in the BIN1 and MS4A6A loci
Genetics is the second strongest risk factor for Alzheimer’s disease (AD) after age. More than 70 loci have been implicated in AD susceptibility so far, and the genetic architecture of AD entails both additive and nonadditive contributions from these loci. To better understand nonadditive impact of single-nucleotide polymorphisms (SNPs) on AD risk, we examined individual, joint, and interacting (SNPxSNP) effects of 139 and 66 SNPs mapped to the BIN1 and MS4A6A AD-associated loci, respectively. The analyses were conducted by fitting three respective dominant allelic-effect models using data from four independent studies. Joint effects were analyzed by considering pairwise combinations of genotypes of the selected SNPs, i.e., compound genotypes (CompG). The individual SNP analyses showed associations of 18 BIN1 SNPs and 4 MS4A6A SNPs with AD. We identified 589 BIN1 and 217 MS4A6A SNP pairs associated with AD in the CompG analysis, although their individual SNPs were not linked to AD independently. Notably, 34 BIN1 and 10 MS4A6A SNP pairs exhibited both significant SNPxSNP interaction effects and significant CompG effects. The vast majority of nonadditive effects were captured through the CompG analysis. These results expand the current understanding of the contributions of the BIN1 and MS4A6A loci to AD susceptibility. The identified nonadditive effects suggest a significant genetic modulation mechanism underlying the genetic heterogeneity of AD in these loci. Our findings highlight the importance of considering nonadditive genetic impacts on AD risk beyond the traditional SNPxSNP approximation, as they may uncover critical mechanisms not apparent when examining SNPs individually.
GeroScienceMedicine-Complementary and Alternative Medicine
CiteScore
10.50
自引率
5.40%
发文量
182
期刊介绍:
GeroScience is a bi-monthly, international, peer-reviewed journal that publishes articles related to research in the biology of aging and research on biomedical applications that impact aging. The scope of articles to be considered include evolutionary biology, biophysics, genetics, genomics, proteomics, molecular biology, cell biology, biochemistry, endocrinology, immunology, physiology, pharmacology, neuroscience, and psychology.