Circulation. Genomic and precision medicine · 2026
Phenome-Wide Mendelian Randomization Identifying Circulating Proteins for Cardiovascular Traits in Populations of African Ancestry.
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Selber-Hnatiw Susannah, Trajanoska Katerina, Pelletier Justin, Su Chen-Yang, McClelland Peyton, Taliun Daniel, Yoshiji Satoshi, Mooser Vincent, Bhérer Claude, Zhou Sirui
Аннотация
BACKGROUND: Circulating proteins represent robust drug targets with therapeutic potential. Many discoveries have focused on European-ancestry populations, disregarding minuscule yet substantial proteomic differences that may contribute to disease and alter drug generalizability in other ancestry groups.
METHODS: Using 2-sample Mendelian randomization and colocalization, we analyzed the effects of 1562 circulating proteins on 145 cardiometabolic-centric outcomes to identify robust protein-phenotype associations in African-ancestry populations and reveal African-ancestry associations with heterogeneous effects. We further replicated these findings using the proteomic data available from the UK Biobank Pharma Proteomics Project and tested the effect of protein quantity in association with select phenotypes. Population branch statistics were also constructed to examine whether protein-genetic instruments under natural selection could lead to significant protein-outcome associations specific to the African ancestry.
RESULTS: We identified 115 robust protein target-outcome associations in African-ancestry populations. Among these, 51 demonstrated heterogeneous effects between African- and European-ancestry populations. We further replicated 4 cross-platform African-ancestry associations in the UK Biobank Pharma Proteomics Project and also revealed 4 significant, direct associations between protein levels and phenotypes. Ultimately, based on our prioritization criteria, we found that CD36 (glycoprotein IIIb), APOC1 (apolipoprotein C1), GSTA1 (glutathione S-transferase alpha 1), and FOLH1 (folate hydrolase 1) were shown to influence lipids and heart diseases, and were uniquely represented in African-ancestry populations. In addition, using population branch statistics, we showed that 47.5% of the 115 significant protein-outcome associations were possibly driven by cis-acting protein quantitative trait loci under natural selection.
CONCLUSIONS: Multiple lines of evidence were used to interrogate proteomic determinants of cardiometabolic diseases and traits in African-ancestry populations. We highlighted actionable circulating protein targets that could represent potential drug targets for cardiovascular diseases specific to populations with African ancestry.
METHODS: Using 2-sample Mendelian randomization and colocalization, we analyzed the effects of 1562 circulating proteins on 145 cardiometabolic-centric outcomes to identify robust protein-phenotype associations in African-ancestry populations and reveal African-ancestry associations with heterogeneous effects. We further replicated these findings using the proteomic data available from the UK Biobank Pharma Proteomics Project and tested the effect of protein quantity in association with select phenotypes. Population branch statistics were also constructed to examine whether protein-genetic instruments under natural selection could lead to significant protein-outcome associations specific to the African ancestry.
RESULTS: We identified 115 robust protein target-outcome associations in African-ancestry populations. Among these, 51 demonstrated heterogeneous effects between African- and European-ancestry populations. We further replicated 4 cross-platform African-ancestry associations in the UK Biobank Pharma Proteomics Project and also revealed 4 significant, direct associations between protein levels and phenotypes. Ultimately, based on our prioritization criteria, we found that CD36 (glycoprotein IIIb), APOC1 (apolipoprotein C1), GSTA1 (glutathione S-transferase alpha 1), and FOLH1 (folate hydrolase 1) were shown to influence lipids and heart diseases, and were uniquely represented in African-ancestry populations. In addition, using population branch statistics, we showed that 47.5% of the 115 significant protein-outcome associations were possibly driven by cis-acting protein quantitative trait loci under natural selection.
CONCLUSIONS: Multiple lines of evidence were used to interrogate proteomic determinants of cardiometabolic diseases and traits in African-ancestry populations. We highlighted actionable circulating protein targets that could represent potential drug targets for cardiovascular diseases specific to populations with African ancestry.