Multi-ancestry modeling improves fine-mapping resolution, protein prediction, and discovery for proteome-wide association studies.

Saved in:
Bibliographic Details
Title: Multi-ancestry modeling improves fine-mapping resolution, protein prediction, and discovery for proteome-wide association studies.
Authors: Krueger CJ; Program in Bioinformatics, Loyola University Chicago, Chicago, IL, 60660, USA., Fischer M; Program in Bioinformatics, Loyola University Chicago, Chicago, IL, 60660, USA., Rizwan T; Program in Bioinformatics, Loyola University Chicago, Chicago, IL, 60660, USA., Kumar MM; Program in Bioinformatics, Loyola University Chicago, Chicago, IL, 60660, USA., Bhargava S; Program in Bioinformatics, Loyola University Chicago, Chicago, IL, 60660, USA., Gerszten R; Beth Israel Deaconess Medical Center, Boston, MA, 02215, USA., Taylor KD; The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA., Cho MH; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA., Rotter JI; The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA., Perera MA; Department of Pharmacology, Northwestern University, Chicago IL, 60611, USA., Hu X; Department of Genome Sciences, University of Virginia, Charlottesville, VA, 22908, USA., Manichaikul A; Department of Genome Sciences, University of Virginia, Charlottesville, VA, 22908, USA., Im HK; Section of Genetic Medicine, The University of Chicago, Chicago, IL, 60637, USA., Wheeler HE; Program in Bioinformatics, Loyola University Chicago, Chicago, IL, 60660, USA.; Department of Biology, Loyola University Chicago, Chicago, IL, 60660, USA.
Corporate Authors: NHLBI TOPMed Consortium
Source: MedRxiv : the preprint server for health sciences [medRxiv] 2026 Jul 01. Date of Electronic Publication: 2026 Jul 01.
Publication Type: Journal Article; Preprint
Journal Info: Country of Publication: United States NLM ID: 101767986 Publication Model: Electronic Cited Medium: Internet NLM ISO Abbreviation: medRxiv Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
DOI:10.64898/2026.06.29.26356716