Genome-Wide Interaction Analysis with DASH Diet Score Identified Novel Loci for Systolic Blood Pressure

Mélanie Guirette; Jessie Lan; Nicola McKeown; Michael R Brown; Han Chen; Paul S DE Vries; Hyunju Kim; Casey M Rebholz; Alanna C Morrison; Traci M Bartz; Amanda M Fretts; Xiuqing Guo; Rozenn N Lemaitre; Ching-Ti Liu; Raymond Noordam; Renée DE Mutsert; Frits R Rosendaal; Carol A Wang; Lawrence Beilin; Trevor A Mori; Wendy H Oddy; Craig E Pennell; Jin Fang Chai; Clare Whitton; Rob M VAN Dam; Jianjun Liu; E Shyong Tai; Xueling Sim; Marian L Neuhouser; Charles Kooperberg; Lesley Tinker; Nora Franceschini; Tianxiao Huan; Thomas W Winkler; Amy R Bentley; W James Gauderman; Luc Heerkens; Toshiko Tanaka; Jeroen van Rooij; Patricia B Munroe; Helen R Warren; Trudy Voortman; Honglei Chen; D C Rao; Daniel Levy; Jiantao Ma

doi:10.1101/2023.11.10.23298402

Genome-Wide Interaction Analysis with DASH Diet Score Identified Novel Loci for Systolic Blood Pressure

medRxiv [Preprint]. 2023 Nov 11:2023.11.10.23298402. doi: 10.1101/2023.11.10.23298402.

Authors

Mélanie Guirette¹, Jessie Lan¹, Nicola McKeown², Michael R Brown³, Han Chen³, Paul S DE Vries³, Hyunju Kim⁴, Casey M Rebholz⁵, Alanna C Morrison³, Traci M Bartz⁶, Amanda M Fretts⁴, Xiuqing Guo⁷, Rozenn N Lemaitre⁸, Ching-Ti Liu⁹, Raymond Noordam¹⁰, Renée DE Mutsert¹¹, Frits R Rosendaal¹¹, Carol A Wang^{12

13}, Lawrence Beilin¹⁴, Trevor A Mori¹⁴, Wendy H Oddy¹⁵, Craig E Pennell^{12

13}, Jin Fang Chai¹⁶, Clare Whitton^{16

17}, Rob M VAN Dam¹⁶, Jianjun Liu¹⁷, E Shyong Tai^{16

18}, Xueling Sim¹⁶, Marian L Neuhouser¹⁹, Charles Kooperberg¹⁹, Lesley Tinker¹⁹, Nora Franceschini²⁰, Tianxiao Huan²¹, Thomas W Winkler²², Amy R Bentley²³, W James Gauderman²⁴, Luc Heerkens²⁵, Toshiko Tanaka²⁶, Jeroen van Rooij²⁷, Patricia B Munroe²⁸, Helen R Warren²⁸, Trudy Voortman²⁹, Honglei Chen³⁰, D C Rao³¹, Daniel Levy²¹, Jiantao Ma¹

Affiliations

¹ Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA.
² Programs of Nutrition, Department of Health Sciences, Sargent College of Health & Rehabilitation Sciences, Boston University, Boston, MA, USA.
³ Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.
⁴ Cardiovascular Health Research Unit, Department of Epidemiology, University of Washington, Seattle, WA, USA.
⁵ Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
⁶ Cardiovascular Health Research Unit, Departments of Biostatistics and Medicine, University of Washington, Seattle, WA, USA.
⁷ The Lundquist Institute at Harbor-UCLA, Torrance, CA, USA.
⁸ Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA.
⁹ Biostatistics, Boston University School of Public Health, Boston, MA, USA.
¹⁰ Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands.
¹¹ Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.
¹² School of Medicine and Public Health, University of Newcastle, NSW, Australia.
¹³ Hunter Medical Research Institute, NSW, Australia.
¹⁴ Medical School, Royal Perth Hospital Unit, University of Western Australia, Crawley, Western Australia, Australia.
¹⁵ Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia Saw Swee Hock, School of Public Health, National University of Singapore and National University Health System, Singapore.
¹⁶ School of Population Health, Curtin University, Perth, Western Australia, Australia.
¹⁷ Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore.
¹⁸ Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
¹⁹ Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA.
²⁰ Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA.
²¹ Framingham Heart Study and Population Sciences Branch, NHLBI, Framingham, MA, USA.
²² Department of Genetic Epidemiology, University of Regensburg; Regensburg, Germany.
²³ Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
²⁴ Division of Biostatistics, Department of Population and Public Health Sciences, University of Southern California; CA, USA.
²⁵ Division of Human Nutrition and Health, Wageningen University & Research, Wageningen, the Netherlands.
²⁶ Longitudinal Studies Section, National Institute on Aging, Baltimore, MD, USA.
²⁷ Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.
²⁸ Centre of Clinical Pharmacology & Precision Medicine, William Harvey Research Institute, Barts and The London Faculty of Medicine and Dentistry, Queen Mary University of London, London, UK.
²⁹ Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.
³⁰ Department of Epidemiology and Biostatistics College of Human Medicine, Michigan State University, East Lansing, Michigan, USA.
³¹ Center for Biostatistics and Data Science, Institute for Informatics, Data Science, and Biostatistics, Washington University School of Medicine, St. Louis, MO, USA.

Abstract

Objective: We examined interactions between genotype and a Dietary Approaches to Stop Hypertension (DASH) diet score in relation to systolic blood pressure (SBP).

Methods: We analyzed up to 9,420,585 biallelic imputed single nucleotide polymorphisms (SNPs) in up to 127,282 individuals of six population groups (91% of European population) from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (CHARGE; n=35,660) and UK Biobank (n=91,622) and performed European population-specific and cross-population meta-analyses.

Results: We identified three loci in European-specific analyses and an additional four loci in cross-population analyses at P for interaction < 5e-8. We observed a consistent interaction between rs117878928 at 15q25.1 (minor allele frequency = 0.03) and the DASH diet score (P for interaction = 4e-8; P for heterogeneity = 0.35) in European population, where the interaction effect size was 0.42±0.09 mm Hg (P for interaction = 9.4e-7) and 0.20±0.06 mm Hg (P for interaction = 0.001) in CHARGE and the UK Biobank, respectively. The 1 Mb region surrounding rs117878928 was enriched with cis-expression quantitative trait loci (eQTL) variants (P = 4e-273) and cis-DNA methylation quantitative trait loci (mQTL) variants (P = 1e-300). While the closest gene for rs117878928 is MTHFS, the highest narrow sense heritability accounted by SNPs potentially interacting with the DASH diet score in this locus was for gene ST20 at 15q25.1.

Conclusion: We demonstrated gene-DASH diet score interaction effects on SBP in several loci. Studies with larger diverse populations are needed to validate our findings.

Keywords: Association Study; CHARGE consortium; DASH Diet; Gene Environment Interaction; Genome-Wide; MTHFS; ST20; Systolic Pressure; UK Biobank.

Publication types

Preprint

Abstract

Publication types

Grants and funding