Scott Hebert, Eric Nels Pederson, Zhengqing Ouyang
{"title":"Newly Identified Genetic Associations of Alzheimer Disease by Conditional Selective Inference: Potential Implications for the Tau Hypothesis.","authors":"Scott Hebert, Eric Nels Pederson, Zhengqing Ouyang","doi":"10.1177/11779322251358309","DOIUrl":null,"url":null,"abstract":"<p><p>Over 6 million people are estimated to have been living with Alzheimer disease (AD) in 2020, with another 12 million living with Mild Cognitive Impairment (MCI). Research has been conducted to evaluate genetic links to AD, but more research is needed to improve early disease detection and improve patient outcomes. Diagnostic, demographic information, and single nucleotide polymorphism (SNP) data were collected by the Alzheimer's Disease Neuroimaging Initiative (ADNI). We performed LASSO regression with conditional selective inference to perform feature selection on the SNPs and other predictors (which included education, race, and marital status), which reduced the number of SNPs from 55 106 to 13 and removed all non-SNP predictors except years of education and marital status. The included SNPs reside in genes that have clinical significance and may be associated with diseases that affect cognitive performance. The results propose the alternative alleles for 7 SNPs are associated with increased risk of AD/MCI diagnosis, while 6 SNPs are associated with decreased risk of diagnosis. The results point to a new potential pathway of disease regarding the <i>PAK5</i> gene and the <i>Tau</i> protein hypothesis, which is supported by previous research. This research may have clinical implications and should be further studied.</p>","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"19 ","pages":"11779322251358309"},"PeriodicalIF":2.4000,"publicationDate":"2025-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12361727/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioinformatics and Biology Insights","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/11779322251358309","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
Over 6 million people are estimated to have been living with Alzheimer disease (AD) in 2020, with another 12 million living with Mild Cognitive Impairment (MCI). Research has been conducted to evaluate genetic links to AD, but more research is needed to improve early disease detection and improve patient outcomes. Diagnostic, demographic information, and single nucleotide polymorphism (SNP) data were collected by the Alzheimer's Disease Neuroimaging Initiative (ADNI). We performed LASSO regression with conditional selective inference to perform feature selection on the SNPs and other predictors (which included education, race, and marital status), which reduced the number of SNPs from 55 106 to 13 and removed all non-SNP predictors except years of education and marital status. The included SNPs reside in genes that have clinical significance and may be associated with diseases that affect cognitive performance. The results propose the alternative alleles for 7 SNPs are associated with increased risk of AD/MCI diagnosis, while 6 SNPs are associated with decreased risk of diagnosis. The results point to a new potential pathway of disease regarding the PAK5 gene and the Tau protein hypothesis, which is supported by previous research. This research may have clinical implications and should be further studied.
期刊介绍:
Bioinformatics and Biology Insights is an open access, peer-reviewed journal that considers articles on bioinformatics methods and their applications which must pertain to biological insights. All papers should be easily amenable to biologists and as such help bridge the gap between theories and applications.