Proteomic signatures of BMI generalize across ancestries and reveal cardiometabolic heterogeneity beyond measured BMI
Year: 2026
Type: preprint
Study design: Observational Study
Abstract: Plasma proteomic scores for body mass index have been derived primarily in European populations, and it is unclear whether these scores are generalizable and useful in other ancestries. Here, we show that plasma proteomic BMI scores developed in participants of European, East Asian, South Asian and African ancestries from the UK Biobank (UKBB; N=50,621) and the South African Middle-Aged Soweto Cohort (MASC; N=948) are portable across ancestries, explain up to 48.7% of trait variance and significantly predict incident obesity. We identified eight protein biomarkers common across all scores, six of which showed causal associations with BMI in Mendelian randomization analyses and were associated with BMI across the Olink (UKBB, MASC) and SomaScan platforms (Qatar Biobank; N= 2410). Discrepancy analysis between the high predicted proteomic BMI and low measured BMI revealed metabolically unhealthy normal weight (MUNW) individuals, with higher visceral fat, elevated triglycerides, and low insulin sensitivity. Thus, plasma proteomic BMI scores may enhance the precision of cardiometabolic risk stratification across diverse populations.
Source: medRxiv
Authors: Monica Muti, Yann Ilboudo, Usama Aliyu, Chengyue Zhang, Lisa Ware, Michael Chong, Lisa K. Micklesfield, Julia H. Goedecke, Robert Ntozini, Guillaume Pare, Michael H. Cho, Michele Ramsay, Andrew P. Morris, Paul W. Franks, Abram B. Kamiza, Shane A. Norris, Omar M. E. Albagha, Matthew Moll, Tinashe Chikowore
Institutions: South African Medical Research Council, University of the Witwatersrand, Cornell University, New York State College of Veterinary Medicine, Brigham and Women's Hospital, Harvard University, Hamad bin Khalifa University, Qatar Foundation, Population Health Research Institute, Umeå University, Zvitambo Institute for Maternal and Child Health Research, University of Manchester, Arthritis UK, Queen Mary University of London, Lund University, Kamuzu University of Health Sciences, University of Southampton, Veterans Health Administration, VA Boston Healthcare System, Mass General Brigham
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: green
Awards: G2691696261, G871103516
OpenAlex ID: W7212258831