Blood-based proteomic signatures of spontaneous menopause: Implications for later-life brain aging and Alzheimer’s disease risk

Blood-based proteomic signatures of spontaneous menopause: Implications for later-life brain aging and Alzheimer’s disease risk | Research Square Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Help Center Sign In Submit a Preprint Cite Share Download PDF Article Blood-based proteomic signatures of spontaneous menopause: Implications for later-life brain aging and Alzheimer’s disease risk Kaitlin Casaletto, Madeline Wood Alexander, Jennifer Rabin, Michelle Canuca, and 17 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8752767/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Menopause is a hallmark process in biological aging that has been associated with later life neurodegenerative risk. We leveraged proteomics data from multiple cohorts (N>3,000) to identify biological changes underlying menopause and its links to brain aging. In N=80 rigorously-phenotyped pre-, peri-, and postmenopausal women with serum NULISAseq proteomics, spontaneous menopause was characterized by dysregulation in inflammatory, synaptic, metabolic, and Alzheimer’s disease (AD) biologic processes, which tracked with hormones and not age. Pro-inflammatory protein upregulation was especially pronounced in women with vasomotor symptoms. In two cohorts of older women (N=94; N=100), menopause-related proteomic elevations associated with poorer cognitive outcomes and plasma AD biomarkers. Finally, validation analyses in age-matched pre- and postmenopausal women with plasma Olink proteomics (N=2,814) replicated the observed proteomic shifts and revealed menopause-related upregulation of additional inflammatory and hormone signaling processes. The molecular signatures of menopause may inform biomarkers or therapeutic targets for brain health in women. Biological sciences/Computational biology and bioinformatics/Proteome informatics Biological sciences/Molecular biology/Proteomics/Protein–protein interaction networks Health sciences/Neurology/Neurological disorders/Neurodegenerative diseases/Alzheimer's disease Health sciences/Diseases/Neurological disorders/Dementia/Alzheimer's disease Health sciences/Risk factors Full Text Additional Declarations There is NO Competing Interest. Supplementary Files extdataS14S19.xlsx Extended Data Tables S14-S19 extdataS1S13.xlsx Extended Data Tables S1-S13 spontaneousmenopauseproteomicsextdata.docx Extended Data Methods and Figures Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information

Related documents

• Plasma proteomics link menopause timing to brain aging and dementia risk#221589
• Plasma proteomics link menopause timing to brain aging and dementia risk#169091
• Plasma proteomics link menopause timing to brain aging and dementia risk#165933
• Proteomic analysis in Alzheimer's disease and other dementias: a focus on sex-specific differences.#220848
• Plasma proteomic signatures of cellular aging predict human disease.#297132