Year: 2026
Type: preprint
Study design: Observational Study
Abstract: The cerebrospinal fluid (CSF) proteome offers a direct readout of central nervous system (CNS) biology but its genetic architecture remains incompletely defined. We conducted the largest single-site CSF genome-wide association study (GWAS) to date, analysing 7,092 SomaScan proteins in 1,259 individuals. Using a covariate-adjusted model including proteomic PCs and disease status, we identified 1,971 genome-wide significant pQTLs (954 cis, 971 trans), 1,409 of which replicated in an independent CSF dataset. We discovered 264 previously unreported loci, replicated 511 associations, refined 80 known loci, and 265 proxy-based associations. Using a previously published reproducibility framework, we show that robust discovery concentrates in reliable measurements, underscoring the importance of rigorous quality control. Enrichment analyses revealed immune/complement and extracellular matrix biology. Mendelian randomization prioritised causal proteins: PILRA, TREM2, IL34, CR2, SHARPIN and ERBB1 (Alzheimer's disease); BST1 and GPNMB (Parkinson's disease); STX6 (Creutzfeldt Jacobs disease); and ATXN3 and B4GALNT1 (Amyotrophic lateral sclerosis), providing a scalable framework for orthogonal target validation in neurodegeneration.
Source: medRxiv
Authors: Raquel Puerta, Pablo Garcia-Gonzalez, Itziar de Rojas, Maria Capdevila-Bayo, Claudia Olive, Alvaro Munoz-Morales, Paula Bayon-Bujan, Alejandro Valenzuela, Chengran Yang, Jigyasha Timsina, Menghan Liu, Sathyaseelan Chakkarai, Oscar Sotolongo-Grau, Berta Calm, Andrea Miguel, Ariadna Solivar, Laura Montrreal, Marta Martinez, Asif Khan, Feiyang Zhao, Natalia Tantinya, Maitee Rosende-Roca, Montserrat Alegret, Sonia Moreno-Grau, Maria Victoria Fernandez, Marta Marquie, Sergi Valero, Jose Enrique Cavazos, Pilar Sanz, Xavier Montalban, Lluis Tarraga, Bart Smets, Merce Boada, Sudha Seshadri, Muralidharan Sargurupremraj, Carlos Cruchaga, Amanda Cano, Alfredo Cabrera-Socorro, Agustin Ruiz
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: green
Funder: National Institutes of Health
OpenAlex ID: W7130957290
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