Brian N Lee, Junwen Wang, Kwangsik Nho, Andrew J Saykin, Li Shen
{"title":"在遗传驱动的亚群中发现具有不同预后影响的精准AD生物标志物。","authors":"Brian N Lee, Junwen Wang, Kwangsik Nho, Andrew J Saykin, Li Shen","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>Alzheimer's Disease (AD) is a highly heritable neurodegenerative disorder characterized by memory impairments. Understanding how genetic factors contribute to AD pathology may inform interventions to slow or prevent the progression of AD. We performed stratified genetic analyses of 1,574 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants to examine associations between levels of quantitative traits (QT's) and future diagnosis. The Chow test was employed to determine if an individual's genetic profile affects identified predictive relationships between QT's and future diagnosis. Our chow test analysis discovered that cognitive and PET-based biomarkers differentially predicted future diagnosis when stratifying on allelic dosage of AD loci. Post-hoc bootstrapped and association analyses of biomarkers confirmed differential effects, emphasizing the necessity of stratified models to realize individualized AD diagnosis prediction. This novel application of the Chow test allows for the quantification and direct comparison of genetic-based differences. Our findings, as well as the identified QT-future diagnosis relationships, warrant future investigation from a biological context.</p>","PeriodicalId":72181,"journal":{"name":"AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10283147/pdf/2152.pdf","citationCount":"0","resultStr":"{\"title\":\"Discovering Precision AD Biomarkers with Varying Prognosis Effects in Genetics Driven Subpopulations.\",\"authors\":\"Brian N Lee, Junwen Wang, Kwangsik Nho, Andrew J Saykin, Li Shen\",\"doi\":\"\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Alzheimer's Disease (AD) is a highly heritable neurodegenerative disorder characterized by memory impairments. Understanding how genetic factors contribute to AD pathology may inform interventions to slow or prevent the progression of AD. We performed stratified genetic analyses of 1,574 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants to examine associations between levels of quantitative traits (QT's) and future diagnosis. The Chow test was employed to determine if an individual's genetic profile affects identified predictive relationships between QT's and future diagnosis. Our chow test analysis discovered that cognitive and PET-based biomarkers differentially predicted future diagnosis when stratifying on allelic dosage of AD loci. Post-hoc bootstrapped and association analyses of biomarkers confirmed differential effects, emphasizing the necessity of stratified models to realize individualized AD diagnosis prediction. This novel application of the Chow test allows for the quantification and direct comparison of genetic-based differences. Our findings, as well as the identified QT-future diagnosis relationships, warrant future investigation from a biological context.</p>\",\"PeriodicalId\":72181,\"journal\":{\"name\":\"AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10283147/pdf/2152.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Discovering Precision AD Biomarkers with Varying Prognosis Effects in Genetics Driven Subpopulations.
Alzheimer's Disease (AD) is a highly heritable neurodegenerative disorder characterized by memory impairments. Understanding how genetic factors contribute to AD pathology may inform interventions to slow or prevent the progression of AD. We performed stratified genetic analyses of 1,574 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants to examine associations between levels of quantitative traits (QT's) and future diagnosis. The Chow test was employed to determine if an individual's genetic profile affects identified predictive relationships between QT's and future diagnosis. Our chow test analysis discovered that cognitive and PET-based biomarkers differentially predicted future diagnosis when stratifying on allelic dosage of AD loci. Post-hoc bootstrapped and association analyses of biomarkers confirmed differential effects, emphasizing the necessity of stratified models to realize individualized AD diagnosis prediction. This novel application of the Chow test allows for the quantification and direct comparison of genetic-based differences. Our findings, as well as the identified QT-future diagnosis relationships, warrant future investigation from a biological context.