@article{Jiang:2023aa,
	abstract = {Inflammation biomarkers can provide valuable insight into the role of inflammatory processes in many diseases and conditions. Sequencing based analyses of such biomarkers can also serve as an exemplar of the genetic architecture of quantitative traits. To evaluate the biological insight, which can be provided by a multi-ancestry, whole-genome based association study, we performed a comprehensive analysis of 21 inflammation biomarkers from up to 38,465 individuals with whole-genome sequencing from the Trans-Omics for Precision Medicine (TOPMed) program. We identified 22 distinct single-variant associations across 6 traits - E-selectin, intercellular adhesion molecule 1, interleukin-6, lipoprotein-associated phospholipase A2 activity and mass, and P-selectin - that remained significant after conditioning on previously identified associations for these inflammatory biomarkers. We further expanded upon known biomarker associations by pairing the single-variant analysis with a rare variant set-based analysis that further identified 19 significant rare variant set-based associations with 5 traits. These signals were distinct from both significant single variant association signals within TOPMed and genetic signals observed in prior studies, demonstrating the complementary value of performing both single and rare variant analyses when analyzing quantitative traits. We also confirm several previously reported signals from semi-quantitative proteomics platforms. Many of these signals demonstrate the extensive allelic heterogeneity and ancestry-differentiated variant-trait associations common for inflammation biomarkers, a characteristic we hypothesize will be increasingly observed with well-powered, large-scale analyses of complex traits.},
	author = {Jiang, Min-Zhi and Gaynor, Sheila M and Li, Xihao and Van Buren, Eric and Stilp, Adrienne and Buth, Erin and Wang, Fei Fei and Manansala, Regina and Gogarten, Stephanie M and Li, Zilin and Polfus, Linda M and Salimi, Shabnam and Bis, Joshua C and Pankratz, Nathan and Yanek, Lisa R and Durda, Peter and Tracy, Russell P and Rich, Stephen S and Rotter, Jerome I and Mitchell, Braxton D and Lewis, Joshua P and Psaty, Bruce M and Pratte, Katherine A and Silverman, Edwin K and Kaplan, Robert C and Avery, Christy and North, Kari and Mathias, Rasika A and Faraday, Nauder and Lin, Honghuang and Wang, Biqi and Carson, April P and Norwood, Arnita F and Gibbs, Richard A and Kooperberg, Charles and Lundin, Jessica and Peters, Ulrike and Dupuis, Jos{\'e}e and Hou, Lifang and Fornage, Myriam and Benjamin, Emelia J and Reiner, Alexander P and Bowler, Russell P and Lin, Xihong and Auer, Paul L and Raffield, Laura M and {NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Inflammation Working Group}},
	date-added = {2024-05-19 20:57:28 -0400},
	date-modified = {2024-05-19 20:57:28 -0400},
	doi = {10.1101/2023.09.10.555215},
	journal = {bioRxiv},
	journal-full = {bioRxiv : the preprint server for biology},
	month = {Sep},
	pmc = {PMC10515765},
	pmid = {37745480},
	url = {https://pubmed.ncbi.nlm.nih.gov/37745480/},
	pst = {epublish},
	title = {Whole Genome Sequencing Based Analysis of Inflammation Biomarkers in the Trans-Omics for Precision Medicine (TOPMed) Consortium},
	year = {2023},
	bdsk-url-1 = {https://doi.org/10.1101/2023.09.10.555215}}

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M","NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Inflammation Working Group"],"bibdata":{"bibtype":"article","type":"article","abstract":"Inflammation biomarkers can provide valuable insight into the role of inflammatory processes in many diseases and conditions. Sequencing based analyses of such biomarkers can also serve as an exemplar of the genetic architecture of quantitative traits. To evaluate the biological insight, which can be provided by a multi-ancestry, whole-genome based association study, we performed a comprehensive analysis of 21 inflammation biomarkers from up to 38,465 individuals with whole-genome sequencing from the Trans-Omics for Precision Medicine (TOPMed) program. We identified 22 distinct single-variant associations across 6 traits - E-selectin, intercellular adhesion molecule 1, interleukin-6, lipoprotein-associated phospholipase A2 activity and mass, and P-selectin - that remained significant after conditioning on previously identified associations for these inflammatory biomarkers. We further expanded upon known biomarker associations by pairing the single-variant analysis with a rare variant set-based analysis that further identified 19 significant rare variant set-based associations with 5 traits. These signals were distinct from both significant single variant association signals within TOPMed and genetic signals observed in prior studies, demonstrating the complementary value of performing both single and rare variant analyses when analyzing quantitative traits. We also confirm several previously reported signals from semi-quantitative proteomics platforms. Many of these signals demonstrate the extensive allelic heterogeneity and ancestry-differentiated variant-trait associations common for inflammation biomarkers, a characteristic we hypothesize will be increasingly observed with well-powered, large-scale analyses of complex traits.","author":[{"propositions":[],"lastnames":["Jiang"],"firstnames":["Min-Zhi"],"suffixes":[]},{"propositions":[],"lastnames":["Gaynor"],"firstnames":["Sheila","M"],"suffixes":[]},{"propositions":[],"lastnames":["Li"],"firstnames":["Xihao"],"suffixes":[]},{"propositions":[],"lastnames":["Van","Buren"],"firstnames":["Eric"],"suffixes":[]},{"propositions":[],"lastnames":["Stilp"],"firstnames":["Adrienne"],"suffixes":[]},{"propositions":[],"lastnames":["Buth"],"firstnames":["Erin"],"suffixes":[]},{"propositions":[],"lastnames":["Wang"],"firstnames":["Fei","Fei"],"suffixes":[]},{"propositions":[],"lastnames":["Manansala"],"firstnames":["Regina"],"suffixes":[]},{"propositions":[],"lastnames":["Gogarten"],"firstnames":["Stephanie","M"],"suffixes":[]},{"propositions":[],"lastnames":["Li"],"firstnames":["Zilin"],"suffixes":[]},{"propositions":[],"lastnames":["Polfus"],"firstnames":["Linda","M"],"suffixes":[]},{"propositions":[],"lastnames":["Salimi"],"firstnames":["Shabnam"],"suffixes":[]},{"propositions":[],"lastnames":["Bis"],"firstnames":["Joshua","C"],"suffixes":[]},{"propositions":[],"lastnames":["Pankratz"],"firstnames":["Nathan"],"suffixes":[]},{"propositions":[],"lastnames":["Yanek"],"firstnames":["Lisa","R"],"suffixes":[]},{"propositions":[],"lastnames":["Durda"],"firstnames":["Peter"],"suffixes":[]},{"propositions":[],"lastnames":["Tracy"],"firstnames":["Russell","P"],"suffixes":[]},{"propositions":[],"lastnames":["Rich"],"firstnames":["Stephen","S"],"suffixes":[]},{"propositions":[],"lastnames":["Rotter"],"firstnames":["Jerome","I"],"suffixes":[]},{"propositions":[],"lastnames":["Mitchell"],"firstnames":["Braxton","D"],"suffixes":[]},{"propositions":[],"lastnames":["Lewis"],"firstnames":["Joshua","P"],"suffixes":[]},{"propositions":[],"lastnames":["Psaty"],"firstnames":["Bruce","M"],"suffixes":[]},{"propositions":[],"lastnames":["Pratte"],"firstnames":["Katherine","A"],"suffixes":[]},{"propositions":[],"lastnames":["Silverman"],"firstnames":["Edwin","K"],"suffixes":[]},{"propositions":[],"lastnames":["Kaplan"],"firstnames":["Robert","C"],"suffixes":[]},{"propositions":[],"lastnames":["Avery"],"firstnames":["Christy"],"suffixes":[]},{"propositions":[],"lastnames":["North"],"firstnames":["Kari"],"suffixes":[]},{"propositions":[],"lastnames":["Mathias"],"firstnames":["Rasika","A"],"suffixes":[]},{"propositions":[],"lastnames":["Faraday"],"firstnames":["Nauder"],"suffixes":[]},{"propositions":[],"lastnames":["Lin"],"firstnames":["Honghuang"],"suffixes":[]},{"propositions":[],"lastnames":["Wang"],"firstnames":["Biqi"],"suffixes":[]},{"propositions":[],"lastnames":["Carson"],"firstnames":["April","P"],"suffixes":[]},{"propositions":[],"lastnames":["Norwood"],"firstnames":["Arnita","F"],"suffixes":[]},{"propositions":[],"lastnames":["Gibbs"],"firstnames":["Richard","A"],"suffixes":[]},{"propositions":[],"lastnames":["Kooperberg"],"firstnames":["Charles"],"suffixes":[]},{"propositions":[],"lastnames":["Lundin"],"firstnames":["Jessica"],"suffixes":[]},{"propositions":[],"lastnames":["Peters"],"firstnames":["Ulrike"],"suffixes":[]},{"propositions":[],"lastnames":["Dupuis"],"firstnames":["Josée"],"suffixes":[]},{"propositions":[],"lastnames":["Hou"],"firstnames":["Lifang"],"suffixes":[]},{"propositions":[],"lastnames":["Fornage"],"firstnames":["Myriam"],"suffixes":[]},{"propositions":[],"lastnames":["Benjamin"],"firstnames":["Emelia","J"],"suffixes":[]},{"propositions":[],"lastnames":["Reiner"],"firstnames":["Alexander","P"],"suffixes":[]},{"propositions":[],"lastnames":["Bowler"],"firstnames":["Russell","P"],"suffixes":[]},{"propositions":[],"lastnames":["Lin"],"firstnames":["Xihong"],"suffixes":[]},{"propositions":[],"lastnames":["Auer"],"firstnames":["Paul","L"],"suffixes":[]},{"propositions":[],"lastnames":["Raffield"],"firstnames":["Laura","M"],"suffixes":[]},{"firstnames":[],"propositions":[],"lastnames":["NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Inflammation Working Group"],"suffixes":[]}],"date-added":"2024-05-19 20:57:28 -0400","date-modified":"2024-05-19 20:57:28 -0400","doi":"10.1101/2023.09.10.555215","journal":"bioRxiv","journal-full":"bioRxiv : the preprint server for biology","month":"Sep","pmc":"PMC10515765","pmid":"37745480","url":"https://pubmed.ncbi.nlm.nih.gov/37745480/","pst":"epublish","title":"Whole Genome Sequencing Based Analysis of Inflammation Biomarkers in the Trans-Omics for Precision Medicine (TOPMed) Consortium","year":"2023","bdsk-url-1":"https://doi.org/10.1101/2023.09.10.555215","bibtex":"@article{Jiang:2023aa,\n\tabstract = {Inflammation biomarkers can provide valuable insight into the role of inflammatory processes in many diseases and conditions. Sequencing based analyses of such biomarkers can also serve as an exemplar of the genetic architecture of quantitative traits. To evaluate the biological insight, which can be provided by a multi-ancestry, whole-genome based association study, we performed a comprehensive analysis of 21 inflammation biomarkers from up to 38,465 individuals with whole-genome sequencing from the Trans-Omics for Precision Medicine (TOPMed) program. We identified 22 distinct single-variant associations across 6 traits - E-selectin, intercellular adhesion molecule 1, interleukin-6, lipoprotein-associated phospholipase A2 activity and mass, and P-selectin - that remained significant after conditioning on previously identified associations for these inflammatory biomarkers. We further expanded upon known biomarker associations by pairing the single-variant analysis with a rare variant set-based analysis that further identified 19 significant rare variant set-based associations with 5 traits. These signals were distinct from both significant single variant association signals within TOPMed and genetic signals observed in prior studies, demonstrating the complementary value of performing both single and rare variant analyses when analyzing quantitative traits. We also confirm several previously reported signals from semi-quantitative proteomics platforms. Many of these signals demonstrate the extensive allelic heterogeneity and ancestry-differentiated variant-trait associations common for inflammation biomarkers, a characteristic we hypothesize will be increasingly observed with well-powered, large-scale analyses of complex traits.},\n\tauthor = {Jiang, Min-Zhi and Gaynor, Sheila M and Li, Xihao and Van Buren, Eric and Stilp, Adrienne and Buth, Erin and Wang, Fei Fei and Manansala, Regina and Gogarten, Stephanie M and Li, Zilin and Polfus, Linda M and Salimi, Shabnam and Bis, Joshua C and Pankratz, Nathan and Yanek, Lisa R and Durda, Peter and Tracy, Russell P and Rich, Stephen S and Rotter, Jerome I and Mitchell, Braxton D and Lewis, Joshua P and Psaty, Bruce M and Pratte, Katherine A and Silverman, Edwin K and Kaplan, Robert C and Avery, Christy and North, Kari and Mathias, Rasika A and Faraday, Nauder and Lin, Honghuang and Wang, Biqi and Carson, April P and Norwood, Arnita F and Gibbs, Richard A and Kooperberg, Charles and Lundin, Jessica and Peters, Ulrike and Dupuis, Jos{\\'e}e and Hou, Lifang and Fornage, Myriam and Benjamin, Emelia J and Reiner, Alexander P and Bowler, Russell P and Lin, Xihong and Auer, Paul L and Raffield, Laura M and {NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Inflammation Working Group}},\n\tdate-added = {2024-05-19 20:57:28 -0400},\n\tdate-modified = {2024-05-19 20:57:28 -0400},\n\tdoi = {10.1101/2023.09.10.555215},\n\tjournal = {bioRxiv},\n\tjournal-full = {bioRxiv : the preprint server for biology},\n\tmonth = {Sep},\n\tpmc = {PMC10515765},\n\tpmid = {37745480},\n\turl = {https://pubmed.ncbi.nlm.nih.gov/37745480/},\n\tpst = {epublish},\n\ttitle = {Whole Genome Sequencing Based Analysis of Inflammation Biomarkers in the Trans-Omics for Precision Medicine (TOPMed) Consortium},\n\tyear = {2023},\n\tbdsk-url-1 = {https://doi.org/10.1101/2023.09.10.555215}}\n\n","author_short":["Jiang, M.","Gaynor, S. 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M","NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Inflammation Working Group"],"key":"Jiang:2023aa","id":"Jiang:2023aa","bibbaseid":"jiang-gaynor-li-vanburen-stilp-buth-wang-manansala-etal-wholegenomesequencingbasedanalysisofinflammationbiomarkersinthetransomicsforprecisionmedicinetopmedconsortium-2023","role":"author","urls":{"Paper":"https://pubmed.ncbi.nlm.nih.gov/37745480/"},"metadata":{"authorlinks":{}},"downloads":0,"html":""},"bibtype":"article","biburl":"https://bibbase.org/network/files/gqwqyBJuHtD7EvhhG","dataSources":["Y9DJHroPCz3Lqc5T2"],"keywords":[],"search_terms":["whole","genome","sequencing","based","analysis","inflammation","biomarkers","trans","omics","precision","medicine","topmed","consortium","jiang","gaynor","li","van buren","stilp","buth","wang","manansala","gogarten","li","polfus","salimi","bis","pankratz","yanek","durda","tracy","rich","rotter","mitchell","lewis","psaty","pratte","silverman","kaplan","avery","north","mathias","faraday","lin","wang","carson","norwood","gibbs","kooperberg","lundin","peters","dupuis","hou","fornage","benjamin","reiner","bowler","lin","auer","raffield","nhlbi trans-omics for precision medicine (topmed) consortium"],"title":"Whole Genome Sequencing Based Analysis of Inflammation Biomarkers in the Trans-Omics for Precision Medicine (TOPMed) Consortium","year":2023}