{"id":244210,"date":"2026-09-18T09:09:24","date_gmt":"2026-09-18T14:09:24","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2026\/09\/longitudinal-dynamics-of-gene-expression-and-metabolomics-in-an-aging-population-cohort"},"modified":"2026-09-18T09:09:24","modified_gmt":"2026-09-18T14:09:24","slug":"longitudinal-dynamics-of-gene-expression-and-metabolomics-in-an-aging-population-cohort","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2026\/09\/longitudinal-dynamics-of-gene-expression-and-metabolomics-in-an-aging-population-cohort","title":{"rendered":"Longitudinal dynamics of gene expression and metabolomics in an aging population cohort"},"content":{"rendered":"<p><a class=\"aligncenter blog-photo\" href=\"https:\/\/lifeboat.com\/blog.images\/longitudinal-dynamics-of-gene-expression-and-metabolomics-in-an-aging-population-cohort2.jpg\"><\/a><\/p>\n<p>Multiomic profiling provides a comprehensive physiological overview at the molecular level, but understanding of its spatiotemporal dynamics remains limited in human populations. We profiled longitudinal whole-blood gene expression and metabolite levels in 335 females over 8 years. Levels of 5,061 genes and 181 metabolites changed over time, with individual trajectories often diverging from population-level trends. Longitudinally variable genes showed cell type specificity and enrichment for aging-relevant pathways, including cardiometabolic and neurodegenerative disorders. Longitudinal trajectories were further shaped by genetics, circadian rhythm, seasonality, and environmental pollutant exposures. Integrative analyses revealed extensive static and time-variable cross-omic connectivity.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Multiomic profiling provides a comprehensive physiological overview at the molecular level, but understanding of its spatiotemporal dynamics remains limited in human populations. We profiled longitudinal whole-blood gene expression and metabolite levels in 335 females over 8 years. Levels of 5,061 genes and 181 metabolites changed over time, with individual trajectories often diverging from population-level trends. [\u2026]<\/p>\n","protected":false},"author":662,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11,412,269,47],"tags":[],"class_list":["post-244210","post","type-post","status-publish","format-standard","hentry","category-biotech-medical","category-genetics","category-life-extension","category-neuroscience"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/244210","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/users\/662"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=244210"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/244210\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=244210"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=244210"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=244210"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}