Genome-Wide Interaction Analysis With DASH Diet Score Identified Novel Loci for Systolic Blood Pressure-Reference-Cited by-同舟云学术

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

Published:2024-03 Issue:3 Volume:81 Page:552-560
ISSN:0194-911X
Container-title:Hypertension
language:en
Short-container-title:Hypertension

Author:

Guirette Mélanie¹^ORCID,Lan Jessie¹,McKeown Nicola M.²,Brown Michael R.³^ORCID,Chen Han³^ORCID,de Vries Paul S.³^ORCID,Kim Hyunju⁴^ORCID,Rebholz Casey M.⁵^ORCID,Morrison Alanna C.³^ORCID,Bartz Traci M.⁶^ORCID,Fretts Amanda M.⁴^ORCID,Guo Xiuqing⁷^ORCID,Lemaitre Rozenn N.⁸^ORCID,Liu Ching-Ti⁹^ORCID,Noordam Raymond¹⁰^ORCID,de Mutsert Renée¹¹,Rosendaal Frits R.¹¹^ORCID,Wang Carol A.¹²¹³^ORCID,Beilin Lawrence J.¹⁴^ORCID,Mori Trevor A.¹⁴^ORCID,Oddy Wendy H.¹⁵,Pennell Craig E.¹²¹³^ORCID,Chai Jin Fang¹⁶^ORCID,Whitton Clare¹⁶¹⁷^ORCID,van Dam Rob M.¹⁶¹⁸^ORCID,Liu Jianjun¹⁹^ORCID,Tai E. Shyong¹⁶²⁰^ORCID,Sim Xueling¹⁶^ORCID,Neuhouser Marian L.²¹,Kooperberg Charles²¹,Tinker Lesley F.²¹,Franceschini Nora²²^ORCID,Huan TianXiao²³,Winkler Thomas W.²⁴^ORCID,Bentley Amy R.²⁵^ORCID,Gauderman W. James²⁶^ORCID,Heerkens Luc²⁷^ORCID,Tanaka Toshiko²⁸,van Rooij Jeroen²⁹,Munroe Patricia B.³⁰^ORCID,Warren Helen R.³⁰^ORCID,Voortman Trudy³¹^ORCID,Chen Honglei³²^ORCID,Rao D.C.³³^ORCID,Levy Daniel²³^ORCID,Ma Jiantao¹^ORCID,

Affiliation:

1. Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA (M.G., J.L., J.M.).

2. Programs of Nutrition, Department of Health Sciences, Sargent College of Health & Rehabilitation Sciences, Boston University, MA (N.M.M.).

3. Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston (M.R.B., H.C., P.S.d.V., A.C.M.).

4. Department of Epidemiology (H.K., A.M.F.), Cardiovascular Health Research Unit, University of Washington, Seattle, WA.

5. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (C.M.R.).

6. Departments of Biostatistics and Medicine (T.M.B.), Cardiovascular Health Research Unit, University of Washington, Seattle, WA.

7. The Lundquist Institute at Harbor-University of California, Los Angeles, Torrance, CA (X.G.).

8. Department of Medicine (R.N.L.), Cardiovascular Health Research Unit, University of Washington, Seattle, WA.

9. Biostatistics, Boston University School of Public Health, MA (C.-T.L.).

10. Department of Internal Medicine, Section of Gerontology and Geriatrics (R.N.), Leiden University Medical Center, the Netherlands.

11. Department of Clinical Epidemiology (R.d.M., F.R.R.), Leiden University Medical Center, the Netherlands.

12. School of Medicine and Public Health, University of Newcastle, NSW, Australia (C.A.W., C.E.P).

13. Mothers’ and Babies’ Research Program, Hunter Medical Research Institute, NSW, Australia (C.A.W., C.E.P.).

14. Medical School, Royal Perth Hospital Unit, University of Western Australia, Crawley (L.J.B., T.A.M.).

15. Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia (W.H.O.).

16. Saw Swee Hock School of Public Health, National University of Singapore and National University Health System (J.F.C., C.W., R.M.v.D., E.S.T., X.S.).

17. School of Population Health, Curtin University, Perth, Western Australia, Australia (C.W.).

18. Department of Exercise and Nutrition Sciences, Milken Institute School of Public Health, The George Washington University (R.M.v.D.).

19. Genome Institute of Singapore, Agency for Science, Technology and Research (J.L.).

20. Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore (E.S.T.).

21. Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA (M.L.N., C.K., L.F.T.).

22. Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill (N.F.).

23. Framingham Heart Study and Population Sciences Branch, National Heart, Lung, and Blood Institute, MA (T.H., D.L.).

24. Department of Genetic Epidemiology, University of Regensburg, Germany (T.W.W.).

25. Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD (A.R.B.).

26. Division of Biostatistics, Department of Population and Public Health Sciences, University of Southern California (W.J.G.).

27. Division of Human Nutrition and Health, Wageningen University & Research, the Netherlands (L.H.).

28. Longitudinal Studies Section, National Institute on Aging, Baltimore, MD (T.T.).

29. Department of Internal Medicine (J.v.R.), Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.

30. Centre of Clinical Pharmacology & Precision Medicine, William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, United Kingdom (P.B.M., H.R.W.).

31. Department of Epidemiology (T.V.), Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.

32. Department of Epidemiology and Biostatistics College of Human Medicine, Michigan State University, East Lansing (H.C.).

33. Center for Biostatistics and Data Science, Institute for Informatics, Data Science, and Biostatistics, Washington University School of Medicine, St. Louis, MO (D.C.R.).

Abstract

BACKGROUND: The Dietary Approaches to Stop Hypertension (DASH) diet score lowers blood pressure (BP). We examined interactions between genotype and the DASH diet score in relation to systolic BP. METHODS: We analyzed up to 9 420 585 single nucleotide polymorphisms in up to 127 282 individuals of 6 population groups (91% of European population) from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (n=35 660) and UK Biobank (n=91 622) and performed European population-specific and cross-population meta-analyses. RESULTS: We identified 3 loci in European-specific analyses and an additional 4 loci in cross-population analyses at P interaction <5e−8. We observed a consistent interaction between rs117878928 at 15q25.1 (minor allele frequency, 0.03) and the DASH diet score ( P interaction =4e−8; P for heterogeneity, 0.35) in European population, where the interaction effect size was 0.42±0.09 mm Hg ( P interaction =9.4e−7) and 0.20±0.06 mm Hg ( P interaction =0.001) in Cohorts for Heart and Aging Research in Genomic Epidemiology 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 variants ( P =1e−300). Although the closest gene for rs117878928 is MTHFS , the highest narrow sense heritability accounted by single nucleotide polymorphisms potentially interacting with the DASH diet score in this locus was for gene ST20 at 15q25.1. CONCLUSIONS: We demonstrated gene-DASH diet score interaction effects on systolic BP in several loci. Studies with larger diverse populations are needed to validate our findings.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Reference34 articles.

1. A Clinical Trial of the Effects of Dietary Patterns on Blood Pressure

2. Effects of Protein, Monounsaturated Fat, and Carbohydrate Intake on Blood Pressure and Serum Lipids

3. DASH (Dietary Approaches to Stop Hypertension) Diet and Risk of Subsequent Kidney Disease

4. Diet Quality and Cardiovascular Disease Risk in Postmenopausal Women With Type 2 Diabetes Mellitus: The Women's Health Initiative

5. Degree of Concordance With DASH Diet Guidelines and Incidence of Hypertension and Fatal Cardiovascular Disease

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Diet to Stop Hypertension: Should Fats be Included?;Current Hypertension Reports;2024-05-07