Pharmacoepigenetics of hypertension: genome-wide methylation analysis of responsiveness to four classes of antihypertensive drugs using a double-blind crossover study design

ABSTRACT Essential hypertension remains the leading risk factor of global disease burden, but its treatment goals are often not met. We investigated whether DNA methylation is associated with antihypertensive responses to a diuretic, a beta-blocker, a calcium channel blocker or an angiotensin receptor antagonist. In addition, since we previously showed an SNP at the transcription start site (TSS) of the catecholamine biosynthesis-related ACY3 gene to associate with blood pressure (BP) response to beta-blockers, we specifically analysed the association of methylation sites close to the ACY3 TSS with BP responses to beta-blockers. We conducted an epigenome-wide association study between leukocyte DNA methylation and BP responses to antihypertensive monotherapies in two hypertensive Finnish cohorts: the GENRES (https://clinicaltrials.gov/ct2/show/NCT03276598; amlodipine 5 mg, bisoprolol 5 mg, hydrochlorothiazide 25 mg, or losartan 50 mg daily) and the LIFE-Fin studies (https://clinicaltrials.gov/ct2/show/NCT00338260; atenolol 50 mg or losartan 50 mg daily). The monotherapy groups consisted of approximately 200 individuals each. We identified 64 methylation sites to suggestively associate (P < 1E-5) with either systolic or diastolic BP responses to a particular study drug in GENRES. These associations did not replicate in LIFE-Fin . Three methylation sites close to the ACY3 TSS were associated with systolic BP responses to bisoprolol in GENRES but not genome-wide significantly (P < 0.05). No robust associations between DNA methylation and BP responses to four different antihypertensive drugs were identified. However, the findings on the methylation sites close to the ACY3 TSS may support the role of ACY3 genetic and epigenetic variation in BP response to bisoprolol.

[1]  Steven M. Tommasini,et al.  Systems genetics in diversity outbred mice inform BMD GWAS and identify determinants of bone strength , 2021, Nature Communications.

[2]  D. Arnett,et al.  DNA Methylation and Blood Pressure Phenotypes: A Review of the Literature. , 2021, American journal of hypertension.

[3]  Kathleen M. Jagodnik,et al.  Gene Set Knowledge Discovery with Enrichr , 2021, Current protocols.

[4]  Dan J Stein,et al.  Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019 , 2020, Lancet.

[5]  M. Schulze,et al.  Epigenetic Changes in Islets of Langerhans Preceding the Onset of Diabetes , 2020, Diabetes.

[6]  S. Ripatti,et al.  Human essential hypertension: no significant association of polygenic risk scores with antihypertensive drug responses , 2020, Scientific Reports.

[7]  Yan V. Sun,et al.  Identification, Heritability, and Relation With Gene Expression of Novel DNA Methylation Loci for Blood Pressure , 2020, Hypertension.

[8]  E. Boerwinkle,et al.  Genome‐Wide Meta‐Analysis of Blood Pressure Response to β1‐Blockers: Results From ICAPS (International Consortium of Antihypertensive Pharmacogenomics Studies) , 2019, Journal of the American Heart Association.

[9]  O. Franco,et al.  The role of DNA methylation and histone modifications in blood pressure: a systematic review , 2019, Journal of Human Hypertension.

[10]  P. Bearcroft,et al.  Homozygous Type IX collagen variants (COL9A1, COL9A2, and COL9A3) causing recessive Stickler syndrome—Expanding the phenotype , 2019, American journal of medical genetics. Part A.

[11]  Mingyu Liang Epigenetic Mechanisms and Hypertension. , 2018, Hypertension.

[12]  Z. Shao,et al.  Association of COL9A3 trp3 polymorphism with intervertebral disk degeneration: a meta-analysis , 2018, BMC Musculoskeletal Disorders.

[13]  Christian Gieger,et al.  Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits , 2018, Nature Genetics.

[14]  Y. Dor,et al.  Principles of DNA methylation and their implications for biology and medicine , 2018, The Lancet.

[15]  A. Arredouani,et al.  Inositol 1,4,5-Trisphosphate Receptors in Hypertension , 2018, Front. Physiol..

[16]  T. Lehtimäki,et al.  Genome-wide association study of nocturnal blood pressure dipping in hypertensive patients , 2018, BMC medical genetics.

[17]  Youxin Wang,et al.  Type 2 Diabetes Mellitus: Integrative Analysis of Multiomics Data for Biomarker Discovery. , 2018, Omics : a journal of integrative biology.

[18]  Andrew P Feinberg,et al.  The Key Role of Epigenetics in Human Disease Prevention and Mitigation. , 2018, The New England journal of medicine.

[19]  Charles Wang,et al.  DNA Methylation and Histone Modification in Hypertension , 2018, International journal of molecular sciences.

[20]  May E. Montasser,et al.  DNA Methylation Analysis Identifies Loci for Blood Pressure Regulation. , 2017, American journal of human genetics.

[21]  Kathryn S. Burch,et al.  Leveraging polygenic functional enrichment to improve GWAS power , 2017, bioRxiv.

[22]  Antti-Pekka Sarin,et al.  Replicated evidence for aminoacylase 3 and nephrin gene variations to predict antihypertensive drug responses. , 2017, Pharmacogenomics.

[23]  Hong Wang,et al.  IP3 receptors regulate vascular smooth muscle contractility and hypertension. , 2016, JCI insight.

[24]  M. Mora,et al.  DNAJB6 Myopathies: Focused Review on an Emerging and Expanding Group of Myopathies , 2016, Front. Mol. Biosci..

[25]  C. Allis,et al.  The molecular hallmarks of epigenetic control , 2016, Nature Reviews Genetics.

[26]  Andrew D. Rouillard,et al.  Enrichr: a comprehensive gene set enrichment analysis web server 2016 update , 2016, Nucleic Acids Res..

[27]  E. Boerwinkle,et al.  PTPRD gene associated with blood pressure response to atenolol and resistant hypertension , 2015, Journal of hypertension.

[28]  Jing He,et al.  Trans-ancestry genome-wide association study identifies 12 genetic loci influencing blood pressure and implicates a role for DNA methylation , 2015, Nature Genetics.

[29]  E. Boerwinkle,et al.  TET2 and CSMD1 genes affect SBP response to hydrochlorothiazide in never-treated essential hypertensives , 2015, Journal of hypertension.

[30]  E. Boerwinkle,et al.  Genome-wide association study identifies CAMKID variants involved in blood pressure response to losartan: the SOPHIA study. , 2014, Pharmacogenomics.

[31]  Rafael A. Irizarry,et al.  Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays , 2014, Bioinform..

[32]  E. Boerwinkle,et al.  Genomic Association Analysis of Common Variants Influencing Antihypertensive Response to Hydrochlorothiazide , 2013, Hypertension.

[33]  Edward Y. Chen,et al.  Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool , 2013, BMC Bioinformatics.

[34]  R. Weksberg,et al.  Discovery of cross-reactive probes and polymorphic CpGs in the Illumina Infinium HumanMethylation450 microarray , 2013, Epigenetics.

[35]  A. Oshlack,et al.  SWAN: Subset-quantile Within Array Normalization for Illumina Infinium HumanMethylation450 BeadChips , 2012, Genome Biology.

[36]  Devin C. Koestler,et al.  DNA methylation arrays as surrogate measures of cell mixture distribution , 2012, BMC Bioinformatics.

[37]  Marcelo Bento Soares,et al.  Report of the National Heart, Lung, and Blood Institute Working Group on epigenetics and hypertension. , 2012, Hypertension.

[38]  P. M. Long,et al.  Differential aminoacylase expression in neuroblastoma , 2011, International journal of cancer.

[39]  E. Boerwinkle,et al.  Plasma renin activity predicts blood pressure responses to beta-blocker and thiazide diuretic as monotherapy and add-on therapy for hypertension. , 2010, American journal of hypertension.

[40]  A. Kurtz,et al.  Substitution of connexin40 with connexin45 prevents hyperreninemia and attenuates hypertension. , 2009, Kidney international.

[41]  T. Strandberg,et al.  Laboratory tests as predictors of the antihypertensive effects of amlodipine, bisoprolol, hydrochlorothiazide and losartan in men: results from the randomized, double-blind, crossover GENRES Study , 2008, Journal of hypertension.

[42]  T. Strandberg,et al.  Predictors of antihypertensive drug responses: initial data from a placebo-controlled, randomized, cross-over study with four antihypertensive drugs (The GENRES Study). , 2007, American journal of hypertension.

[43]  W. Dekant,et al.  Specificity of Aminoacylase III-Mediated Deacetylation of Mercapturic Acids , 2007, Drug Metabolism and Disposition.

[44]  S. Ryazantsev,et al.  Structural characterization, tissue distribution, and functional expression of murine aminoacylase III. , 2004, American journal of physiology. Cell physiology.

[45]  M. Nieminen,et al.  For Personal Use. Only Reproduce with Permission from the Lancet Publishing Group , 2022 .

[46]  G. Stergiou,et al.  May Measurement Month 2019 The Global Blood Pressure Screening Campaign of the International Society of Hypertension , 2020 .

[47]  E. Boerwinkle,et al.  Genome-Wide and Gene-Based Meta-Analyses Identify Novel Loci Influencing Blood Pressure Response to Hydrochlorothiazide , 2017, Hypertension.

[48]  E. Boerwinkle,et al.  Pharmacogenomics of hypertension: a genome‐wide, placebo‐controlled cross‐over study, using four classes of antihypertensive drugs. , 2015, Journal of the American Heart Association.

[49]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .