A multi-ancestry genome-wide study incorporating gene–smoking interactions identifies multiple new loci for pulse pressure and mean arterial pressure

Abstract

Elevated blood pressure (BP), a leading cause of global morbidity and mortality, is influenced by both genetic and lifestyle factors. Cigarette smoking is one such lifestyle factor. Across five ancestries, we performed a genome-wide gene–smoking interaction study of mean arterial pressure (MAP) and pulse pressure (PP) in 129 913 individuals in stage 1 and follow-up analysis in 480 178 additional individuals in stage 2. We report here 136 loci significantly associated with MAP and/or PP. Of these, 61 were previously published through main-effect analysis of BP traits, 37 were recently reported by us for systolic BP and/or diastolic BP through gene–smoking interaction analysis and 38 were newly identified (P < 5 × 10−8, false discovery rate < 0.05). We also identified nine new signals near known loci. Of the 136 loci, 8 showed significant interaction with smoking status. They include CSMD1 previously reported for insulin resistance and BP in the spontaneously hypertensive rats. Many of the 38 new loci show biologic plausibility for a role in BP regulation. SLC26A7 encodes a chloride/bicarbonate exchanger expressed in the renal outer medullary collecting duct. AVPR1A is widely expressed, including in vascular smooth muscle cells, kidney, myocardium and brain. FHAD1 is a long non-coding RNA overexpressed in heart failure. TMEM51 was associated with contractile function in cardiomyocytes. CASP9 plays a central role in cardiomyocyte apoptosis. Identified only in African ancestry were 30 novel loci. Our findings highlight the value of multi-ancestry investigations, particularly in studies of interaction with lifestyle factors, where genomic and lifestyle differences may contribute to novel findings.

Objectives, design and main findings until 2020 from the Rotterdam Study

“…Among diabetic individuals, we identified 26 blood metabolomic measures to be associated with insufficient glycemic control, the strongest association was with glutamine [98]. Taking into account smoking behavior, multiple new loci for pulse pressure, mean arterial pressure, and blood pressure were identified, highlighting the importance of accounting for lifestyle factors and shared pathophysiology between cardiometabolic and addiction traits [99,100]. We, however, did not find evidence of genetic interactions with body mass index on AF risk [101].…”

A brief history of human disease genetics

“…There are nascent efforts to capture transcriptomic, proteomic and metabolomic phenotypes, although these are not yet at equivalent scale to the genetic data 79,80 . Biobank analyses have provided more generalizable estimates of the relevance of genetic risk factors in the context of the separate and joint effects of non-genetic factors 81 . Increasingly, integration with healthcare data brings a longitudinal dimension to phenotypic characterization, which facilitates analyses of disease progression and lifelong disease risk 82 .…”

Evaluating the promise of inclusion of African ancestry populations in genomics

“…42 The complexities of PRS in the context of ancestry and the potential to exacerbate health disparities has been addressed in-depth in recent articles. 40,42 Importantly, in addition to limitations in transferability conferred by ancestry-related genomic differences, there can be substantial variation in the performance of PRS for complex genetic Lipoprotein(a) 112 Chronic obstructive pulmonary disease 113 Rh antigens 114 Population Architecture using Genomics and Epidemiology II (PAGE II) study Adiposity traits [115][116][117] Serum lipids 118 Glycemic traits 119 QT interval 120 Age of reproductive events among women 121 C-reactive protein 122 Blood pressure 123 Complex traits 107 The Blood pressure 109,126,127 Serum lipids [128][129][130] The traits based on methodological decisions 40 and on environmental context. 44 If PRS do become useful clinically, the limitations of applying data from a subset of the global population to all global populations are clear.…”