RATIONALE: Mean platelet volume (MPV) and platelet count (PLT) are platelet measures that have been linked to cardiovascular disease (CVD) and mortality risk. Identifying protein biomarkers for these measures may yield insights into CVD mechanisms. OBJECTIVE: We aimed to identify causal protein biomarkers for MPV and PLT among 71 CVD-related plasma proteins measured in FHS (Framingham Heart Study) participants. METHODS AND RESULTS: We conducted integrative analyses of genetic variants associated with PLT/MPV with protein quantitative trait locus variants associated with plasma proteins followed by Mendelian randomization to infer causal relations of proteins for PLT/MPV. We also tested protein-PLT/MPV association in FHS participants. Using induced pluripotent stem cell-derived megakaryocyte clones that produce functional platelets, we conducted RNA-sequencing and analyzed expression differences between low- and high-platelet producing clones. We then performed small interfering RNA gene knockdown experiments targeting genes encoding proteins with putatively causal platelet effects in megakaryocyte clones to examine effects on platelet production. In protein-trait association analyses, ten proteins were associated with MPV and 31 with PLT. Mendelian randomization identified 4 putatively causal proteins for MPV and 4 for PLT. GP-5 (Glycoprotein V), GRN (granulin), and MCAM (melanoma cell adhesion molecule) were associated with PLT, while MPO (myeloperoxidase) showed significant association with MPV in both analyses. RNA-sequencing analysis results were directionally concordant with observed and Mendelian randomization-inferred associations for GP-5, GRN, and MCAM. In siRNA gene knockdown experiments, silencing GP-5, GRN, and MPO decreased PLTs. Genome-wide association study results suggest several of these may be linked to CVD risk. CONCLUSIONS: We identified 4 proteins that are causally linked to PLTs. These proteins may also have roles in the pathogenesis of CVD via a platelet/blood coagulation-based mechanism.
RATIONALE: Mean platelet volume (MPV) and platelet count (PLT) are platelet measures that have been linked to cardiovascular disease (CVD) and mortality risk. Identifying protein biomarkers for these measures may yield insights into CVD mechanisms. OBJECTIVE: We aimed to identify causal protein biomarkers for MPV and PLT among 71 CVD-related plasma proteins measured in FHS (Framingham Heart Study) participants. METHODS AND RESULTS: We conducted integrative analyses of genetic variants associated with PLT/MPV with protein quantitative trait locus variants associated with plasma proteins followed by Mendelian randomization to infer causal relations of proteins for PLT/MPV. We also tested protein-PLT/MPV association in FHS participants. Using induced pluripotent stem cell-derived megakaryocyte clones that produce functional platelets, we conducted RNA-sequencing and analyzed expression differences between low- and high-platelet producing clones. We then performed small interfering RNA gene knockdown experiments targeting genes encoding proteins with putatively causal platelet effects in megakaryocyte clones to examine effects on platelet production. In protein-trait association analyses, ten proteins were associated with MPV and 31 with PLT. Mendelian randomization identified 4 putatively causal proteins for MPV and 4 for PLT. GP-5 (Glycoprotein V), GRN (granulin), and MCAM (melanoma cell adhesion molecule) were associated with PLT, while MPO (myeloperoxidase) showed significant association with MPV in both analyses. RNA-sequencing analysis results were directionally concordant with observed and Mendelian randomization-inferred associations for GP-5, GRN, and MCAM. In siRNA gene knockdown experiments, silencing GP-5, GRN, and MPO decreased PLTs. Genome-wide association study results suggest several of these may be linked to CVD risk. CONCLUSIONS: We identified 4 proteins that are causally linked to PLTs. These proteins may also have roles in the pathogenesis of CVD via a platelet/blood coagulation-based mechanism.
Authors: Amarise Little; Yao Hu; Quan Sun; Deepti Jain; Jai Broome; Ming-Huei Chen; Florian Thibord; Caitlin McHugh; Praveen Surendran; Thomas W Blackwell; Jennifer A Brody; Arunoday Bhan; Nathalie Chami; Paul S de Vries; Lynette Ekunwe; Nancy Heard-Costa; Brian D Hobbs; Ani Manichaikul; Jee-Young Moon; Michael H Preuss; Kathleen Ryan; Zhe Wang; Marsha Wheeler; Lisa R Yanek; Goncalo R Abecasis; Laura Almasy; Terri H Beaty; Lewis C Becker; John Blangero; Eric Boerwinkle; Adam S Butterworth; Hélène Choquet; Adolfo Correa; Joanne E Curran; Nauder Faraday; Myriam Fornage; David C Glahn; Lifang Hou; Eric Jorgenson; Charles Kooperberg; Joshua P Lewis; Donald M Lloyd-Jones; Ruth J F Loos; Yuan-I Min; Braxton D Mitchell; Alanna C Morrison; Deborah A Nickerson; Kari E North; Jeffrey R O'Connell; Nathan Pankratz; Bruce M Psaty; Ramachandran S Vasan; Stephen S Rich; Jerome I Rotter; Albert V Smith; Nicholas L Smith; Hua Tang; Russell P Tracy; Matthew P Conomos; Cecelia A Laurie; Rasika A Mathias; Yun Li; Paul L Auer; Timothy Thornton; Alexander P Reiner; Andrew D Johnson; Laura M Raffield Journal: Hum Mol Genet Date: 2022-02-03 Impact factor: 5.121
Authors: Sarah J D Nauwelaerts; Koen De Cremer; Natalia Bustos Sierra; Mathieu Gand; Dirk Van Geel; Maud Delvoye; Els Vandermassen; Jordy Vercauteren; Christophe Stroobants; Alfred Bernard; Nelly D Saenen; Tim S Nawrot; Nancy H C Roosens; Sigrid C J De Keersmaecker Journal: Int J Environ Res Public Health Date: 2022-07-12 Impact factor: 4.614