{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T06:28:35Z","timestamp":1761632915787,"version":"build-2065373602"},"reference-count":60,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T00:00:00Z","timestamp":1761609600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100010269","name":"Wellcome Trust","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100010269","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Neurosci."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Alzheimer\u2019s disease involves progressive white matter microstructural degeneration that may precede clinical symptoms by decades. While polygenic risk scores (PRS) quantify cumulative genetic liability for AD, genome-wide PRS lack mechanistic specificity. We tested whether pathway-specific PRS, targeting areas of biology including tau binding, lipid metabolism, and immune response, are differentially associated with diffusion MRI measures across the lifespan.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      We analyzed two population-based cohorts: the Avon Longitudinal Study of Parents and Children (ALSPAC; mean age = 19.8 years,\n                      <jats:italic>n<\/jats:italic>\n                      = 517) and UK Biobank (mean age = 64.2 years,\n                      <jats:italic>n<\/jats:italic>\n                      = 18,172). Genome-wide and nine pathway-specific PRS for Alzheimer\u2019s disease were constructed using GWAS summary statistics and a clumping threshold of r\n                      <jats:sup>2<\/jats:sup>\n                      &amp;lt; 0.2 at\n                      <jats:italic>p<\/jats:italic>\n                      &amp;lt; 0.001. Diffusion MRI data were processed separately within each cohort: in ALSPAC, tract-based fractional anisotropy (FA) and mean diffusivity (MD) were extracted using probabilistic tractography from native-space regions of interest; in UK Biobank, diffusion metrics were derived from TBSS-aligned skeletons and standard atlas-based ROIs. Analyses focused on three tracts vulnerable to early AD pathology: the dorsal cingulum, parahippocampal cingulum, and fornix. Multiple linear regression models were used to assess PRS associations with FA and MD, adjusting for demographic, scanner, and genetic ancestry covariates. False discovery rate correction addressed multiple comparisons, and sensitivity analyses were performed excluding the APOE region.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      In UK Biobank, higher PRS for protein\u2013lipid complex assembly and tau protein binding were robustly associated with lower fractional anisotropy and higher mean diffusivity in both dorsal and parahippocampal cingulum segments (False discovery rate-corrected\n                      <jats:italic>p<\/jats:italic>\n                      &amp;lt; 0.05), explaining more variance than\n                      <jats:italic>APOE<\/jats:italic>\n                      alone; no significant effects emerged in the fornix. Genome-wide PRS showed weaker, non-significant associations. In ALSPAC, no PRS metric survived FDR correction, though nominal trends appeared in the dorsal cingulum. Sensitivity analyses confirmed that key cingulum associations in older adults persisted after omitting\n                      <jats:italic>APOE<\/jats:italic>\n                      .\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Pathway-specific polygenic risk for Alzheimer\u2019s disease manifests in white matter microstructure by mid- to late adulthood but not in early adulthood, suggesting an age-dependent emergence of genetic effects. dMRI phenotypes may thus serve as intermediate biomarkers for dissecting mechanistic pathways of preclinical Alzheimer\u2019s disease vulnerability.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fnins.2025.1638503","type":"journal-article","created":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T06:24:55Z","timestamp":1761632695000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["White matter microstructure in mid- to late adulthood is influenced by pathway-stratified polygenic risk for Alzheimer\u2019s disease"],"prefix":"10.3389","volume":"19","author":[{"given":"Judith R.","family":"Harrison","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sonya F.","family":"Foley","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Emily","family":"Simmonds","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Matthew","family":"Bracher-Smith","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peter","family":"Holmans","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Evie","family":"Stergiakouli","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xavier","family":"Caseras","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Valentina","family":"Escott-Price","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Derek K.","family":"Jones","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2025,10,28]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1038\/nature15393","article-title":"A global reference for human genetic variation.","volume":"526","author":"1000 Genomes Project Consortium","year":"2015","journal-title":"Nature"},{"key":"B2","doi-asserted-by":"publisher","first-page":"e49072","DOI":"10.1371\/journal.pone.0049072","article-title":"Diffusion tensor metrics as biomarkers in Alzheimer\u2019s disease.","volume":"7","author":"Acosta-Cabronero","year":"2012","journal-title":"PLoS One"},{"key":"B3","doi-asserted-by":"publisher","first-page":"848","DOI":"10.1016\/j.jalz.2018.01.005","article-title":"Disentangling the biological pathways involved in early features of Alzheimer\u2019s disease in the Rotterdam study.","volume":"14","author":"Ahmad","year":"2018","journal-title":"Alzheimers Dement."},{"key":"B4","doi-asserted-by":"publisher","first-page":"400","DOI":"10.1016\/j.neuroimage.2017.10.034","article-title":"Image processing and quality control for the first 10,000 brain imaging datasets from UK Biobank.","volume":"166","author":"Alfaro-Almagro","year":"2018","journal-title":"Neuroimage"},{"key":"B5","doi-asserted-by":"publisher","first-page":"965","DOI":"10.3233\/JAD-181210","article-title":"Relationships between diffusion tensor imaging and cerebrospinal fluid metrics in early stages of the Alzheimer\u2019s disease continuum.","volume":"70","author":"Alm","year":"2019","journal-title":"J. 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