{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"medRxiv"}],"indexed":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T07:31:19Z","timestamp":1787729479732,"version":"build-2784847793"},"posted":{"date-parts":[[2026,7,15]]},"group-title":"Genetic and Genomic Medicine","reference-count":55,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T00:00:00Z","timestamp":1784073600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"award":["R01MH117646"],"award-info":[{"award-number":["R01MH117646"]}],"id":[{"id":"https:\/\/ror.org\/04xeg9z08","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,7,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:p>\n                  With recent advances in high-throughput proteomic technologies, population-scale plasma proteomics datasets, often linked to extensive genetic and phenotypic information, have become increasingly accessible. Yet the relationships between circulating protein levels, brain imaging phenotypes, and risk for neurological and psychiatric disorders remain largely unexplored. Proteome-wide association studies offer a promising approach for elucidating biological mechanisms that connect genetic variation to complex brain-related traits and diseases. In this study, we integrated protein quantitative trait loci (pQTLs) from the two largest plasma proteomic resources (the UK Biobank Pharma Proteomics Project [UKB-PPP] and Ferkingstad\n                  <jats:italic>et al.<\/jats:italic>\n                  [deCODE]) with genome-wide association studies of brain imaging-derived phenotypes in UK Biobank using Mendelian randomization and colocalization analyses. We identified 120 cis and 20 trans associations between plasma proteins and imaging phenotypes and validated these findings using brain tissue-derived proteomic and transcriptomic datasets. Multivariable Mendelian randomization revealed eleven plasma proteins (coding genes\n                  <jats:italic>APOE, ARL3, MICB, NSF, RHOC, RSPO3, ENPP2, BTN2A1, EIF2AK3, MRVI1,<\/jats:italic>\n                  and\n                  <jats:italic>OPLAH<\/jats:italic>\n                  ) with significant direct effects on the risk of Alzheimer\u2019s disease, Parkinson\u2019s disease, multiple sclerosis, bipolar disorder, and schizophrenia. Single-cell expression and pathway enrichment analyses further revealed cell-type-specific effects and distinct biological processes underlying these protein- disease associations. Together, these findings demonstrate robust links between plasma protein variation and brain structure, delineate protein-disease pathways, and highlight the cellular and molecular mechanisms that contribute to neurobiological diversity and pathology.\n                <\/jats:p>","DOI":"10.64898\/2026.07.13.26358006","type":"posted-content","created":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T00:11:02Z","timestamp":1784160662000},"source":"Crossref","is-referenced-by-count":1,"title":["Characterizing the impact of plasma protein levels on human brain structure and disorders leveraging integrative multi-omics analysis"],"prefix":"10.64898","author":[{"given":"Cyrus","family":"Ayubcha","sequence":"first","affiliation":[{"name":"Harvard Medical School, Boston, MA, USA"},{"name":"Harvard T.H. 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