Genome-Wide Interaction Analysis With DASH Diet Score Identified Novel Loci for Systolic Blood Pressure-Reference-Cited by-全球学者库

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

Published:2024-01-16 Issue: Volume: Page:
ISSN:0194-911X
Container-title:Hypertension
language:en
Short-container-title:Hypertension

Author:

Guirette Mélanie¹^ORCID,Lan Jessie¹,Mckeown Nicola²,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 Lawrence¹⁴^ORCID,Mori Trevor A.¹⁴^ORCID,Oddy Wendy H.¹⁵,Pennell Craig E.¹²¹³^ORCID,Fang Chai Jin¹⁶^ORCID,Whitton Clare¹⁶¹⁷^ORCID,Van Dam Rob M.¹⁶^ORCID,Liu Jianjun¹⁷^ORCID,Shyong Tai E.¹⁶¹⁸^ORCID,Sim Xueling¹⁶^ORCID,Neuhouser Marian L.¹⁹,Kooperberg Charles¹⁹,Tinker Lesley¹⁹,Franceschini Nora²⁰^ORCID,Huan Tianxiao²¹,Winkler Thomas W.²²^ORCID,Bentley Amy R.²³^ORCID,James Gauderman W.²⁴^ORCID,Heerkens Luc²⁵^ORCID,Tanaka Toshiko²⁶,van Rooij Jeroen²⁷,Munroe Patricia B.²⁸^ORCID,Warren Helen R.²⁸^ORCID,Voortman Trudy²⁹^ORCID,Chen Honglei³⁰^ORCID,Rao D.C.³¹^ORCID,Levy Daniel²¹^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.).

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

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

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

7. The Lundquist Institute at Harbor-UCLA, Torrance, CA (X.G.).

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

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

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

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

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.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., J.L.).

18. Department of Exercise and Nutrition Sciences, Milken Institute School of Public Health, The George Washington University (E.S.T.).

19. Genome Institute of Singapore, Agency for Science, Technology and Research (M.L.N., C.K., L.T.).

20. Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA (N.F.).

21. Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill (T.H., D.L.).

22. Framingham Heart Study and Population Sciences Branch, NHLBI, MA (T.W.W.).

23. Department of Genetic Epidemiology, University of Regensburg, Germany (A.R.B.).

24. Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD (W.J.G.).

25. Division of Biostatistics, Department of Population and Public Health Sciences, University of Southern California (L.H.).

26. Division of Human Nutrition and Health, Wageningen University & Research, the Netherlands (T.T.).

27. Longitudinal Studies Section, National Institute on Aging, Baltimore, MD (J.v.R.).

28. Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands. (P.B.M., H.R.W.)

29. 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 (T.V.).

30. Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands. (H.C.)

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

Subject

Internal Medicine

Link

https://www.ahajournals.org/doi/pdf/10.1161/HYPERTENSIONAHA.123.22334