{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T23:56:00Z","timestamp":1779148560542,"version":"3.51.4"},"reference-count":70,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2024,9,30]],"date-time":"2024-09-30T00:00:00Z","timestamp":1727654400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"University of Maryland Grand Challenge grant","award":["1K01DA059603"],"award-info":[{"award-number":["1K01DA059603"]}]},{"name":"University of Maryland Grand Challenge grant","award":["1DP1DA048968"],"award-info":[{"award-number":["1DP1DA048968"]}]},{"name":"University of Maryland Grand Challenge grant","award":["R01MH123163"],"award-info":[{"award-number":["R01MH123163"]}]},{"name":"University of Maryland Grand Challenge grant","award":["R01EB015611"],"award-info":[{"award-number":["R01EB015611"]}]},{"name":"University of Maryland Grand Challenge grant","award":["S10OD023696"],"award-info":[{"award-number":["S10OD023696"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Genes"],"abstract":"<jats:p>Background\/Objectives: Human brain aging is a complex process that affects various aspects of brain function and structure, increasing susceptibility to neurological and psychiatric disorders. A number of nongenetic (e.g., environmental and lifestyle) and genetic risk factors are found to contribute to the varying rates at which the brain ages among individuals. Methods: In this paper, we conducted both an exposome-wide association study (XWAS) and a genome-wide association study (GWAS) on white matter brain aging in the UK Biobank, revealing the multifactorial nature of brain aging. We applied a machine learning algorithm and leveraged fractional anisotropy tract measurements from diffusion tensor imaging data to predict the white matter brain age gap (BAG) and treated it as the marker of brain aging. For XWAS, we included 107 variables encompassing five major categories of modifiable exposures that potentially impact brain aging and performed both univariate and multivariate analysis to select the final set of nongenetic risk factors. Results: We found current tobacco smoking, dietary habits including oily fish, beef, lamb, cereal, and coffee intake, length of mobile phone use, use of UV protection, and frequency of solarium\/sunlamp use were associated with the BAG. In genetic analysis, we identified several SNPs on chromosome 3 mapped to genes IP6K1, GMNC, OSTN, and SLC25A20 significantly associated with the BAG, showing the high heritability and polygenic architecture of human brain aging. Conclusions: The critical nongenetic and genetic risk factors identified in our study provide insights into the causal relationship between white matter brain aging and neurodegenerative diseases.<\/jats:p>","DOI":"10.3390\/genes15101285","type":"journal-article","created":{"date-parts":[[2024,9,30]],"date-time":"2024-09-30T03:12:28Z","timestamp":1727665948000},"page":"1285","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Nongenetic and Genetic Factors Associated with White Matter Brain Aging: Exposome-Wide and Genome-Wide Association Study"],"prefix":"10.3390","volume":"15","author":[{"given":"Li","family":"Feng","sequence":"first","affiliation":[{"name":"Department of Nutrition and Food Science, College of Agriculture & Natural Resources, University of Maryland, College Park, MD 20740, USA"},{"name":"Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, MD 20740, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Halley S.","family":"Milleson","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, MD 20740, USA"},{"name":"Department of Mathematics, The College of Computer, Mathematical, and Natural Sciences, University of Maryland, College Park, MD 20740, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenyao","family":"Ye","sequence":"additional","affiliation":[{"name":"Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, MD 21228, USA"},{"name":"Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, School of Medicine, University of Maryland, Baltimore, MD 21201, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Travis","family":"Canida","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, MD 20740, USA"},{"name":"Department of Mathematics, The College of Computer, Mathematical, and Natural Sciences, University of Maryland, College Park, MD 20740, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongjie","family":"Ke","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, MD 20740, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0185-8557","authenticated-orcid":false,"given":"Menglu","family":"Liang","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, MD 20740, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4473-1142","authenticated-orcid":false,"given":"Si","family":"Gao","sequence":"additional","affiliation":[{"name":"Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, MD 21228, USA"},{"name":"Louis A. Faillace Department of Psychiatry & Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX 77030, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuo","family":"Chen","sequence":"additional","affiliation":[{"name":"Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, MD 21228, USA"},{"name":"Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, School of Medicine, University of Maryland, Baltimore, MD 21201, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"L. Elliot","family":"Hong","sequence":"additional","affiliation":[{"name":"Louis A. Faillace Department of Psychiatry & Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX 77030, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peter","family":"Kochunov","sequence":"additional","affiliation":[{"name":"Louis A. Faillace Department of Psychiatry & Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX 77030, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1544-8898","authenticated-orcid":false,"given":"David K. Y.","family":"Lei","sequence":"additional","affiliation":[{"name":"Department of Nutrition and Food Science, College of Agriculture & Natural Resources, University of Maryland, College Park, MD 20740, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3605-0811","authenticated-orcid":false,"given":"Tianzhou","family":"Ma","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, MD 20740, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Shanmugasundaram, M., and Tamilarasu, A. (2023). The impact of digital technology, social media, and artificial intelligence on cognitive functions: A review. Front. 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