Integrating genetic, epigenetic, and phenotypic data offers a promising strategy to guide more effective and individualized heart failure pharmacotherapy.
Abstract
Heart failure is a life-threatening condition affecting approximately 1% of the global population, with its prevalence continuing to rise. Genetic factors, including pathogenic variants in sarcomere, cytoskeletal, and ion channel genes, contribute to disease progression, often following Mendelian inheritance patterns. However, most interindividual variability in disease course and therapeutic response arises from polygenic, non Mendelian patterns, particularly single nucleotide polymorphisms (SNPs). SNPs can modestly influence gene expression, protein function, and downstream signaling pathways, thereby affecting the pharmacokinetics and pharmacodynamics of cardiovascular drugs. Variants in genes such as CYP2D6, ACE, AGT, CYP11B2, ADRB1/2, SLC5A2, and UGT2B4 have been associated with differential responses to β-blockers, SGLT2-inhibitors, and ACE inhibitors. The clinical application of genomic approaches remains limited due to small study sizes, interpatient variability, and the lack of standardized biomarkers. Nevertheless, integrating genetic, epigenetic, and phenotypic data offers a promising strategy to guide more effective and individualized heart failure pharmacotherapy.
The integration of pharmacogenomics into routine healthcare has the potential to optimize individualized drug therapy, minimize preventable ADRs, and accelerate the transition toward precision medicine, ultimately improving clinical outcomes and healthcare quality.
Rayapudi Vasavi Sai Saraswati, U. M. Vattikuti, Arthika Chauhan Laudia et al.· International Journal of Cur...· 0 citations
The integration of artificial intelligence and machine learning approaches for pharmacogenomic prediction, the emergence of polygenic risk scores, and the role of multi-omics integration in refining therapeutic decision-making are examined.
Hao Sun, Zijun Qiao, Jinze Yu et al.· Brazilian Journal of Science· 0 citations
BACKGROUND AND AIMS
Up to half of patients switch or discontinue antihypertensive medications within the first year, but underlying mechanisms remain elusive. This study aimed to identify genetic predictors of antihypertensive medication use trajectories within the first year.
METHODS
Using longitudinal medication data from >400 000 genotyped antihypertensive medication users across three cohorts (FinnGen, the UK Biobank, and the Estonian Biobank), short-term antihypertensive medication use trajectories were classified as Continue, Switch, or Discontinue. Genome-wide association studies were performed across five medication classes.
RESULTS
In total, 14 genome-wide significant loci were identified for switching from angiotensin-converting enzyme inhibitors (ACEI) and dihydropyridine calcium channel blockers (dCCB) to other antihypertensive medications. For ACEI switching, evidence converged on the neurotensin-NTSR1 pathway, including a 320-fold Finnish-enriched protective missense variant in the neurotensin receptor gene NTSR1 (rs148569146 [G301R], odds ratio [OR] 0.49, P = 3.3 × 10-43) and a variant near RASSF9 (rs181941187, OR = 0.74, P = 1.2 × 10-49) tagging the neurotensin gene NTS. In drug-gene interaction analyses, NTSR1 G301R was associated with reduced ACEI-induced cough risk (OR 0.39, P = 8.1 × 10-4). The dCCB switching locus at CYP3A43 was in near-complete linkage (r2 = 0.99) with the functional CYP3A4*22 allele (rs35599367, OR 1.23, P = 6.1 × 10-10). A polygenic risk score (PRS) for ACEI switching predicted two-fold ACEI cough risk in the top 10% PRS compared with the middle 20% in an independent sample of the Estonian Biobank.
CONCLUSIONS
These findings extend the bradykinin hypothesis of ACEI-induced cough by implicating neurotensin-NTSR1 signalling, pinpoint CYP3A4*22 as a novel functional predictor of dCCB switching with potential for genotype-guided prescribing, and validate medication use trajectories as a framework for pharmacogenetic discovery.
F. Vaura, Kristi Krebs, T. Kiiskinen et al.· European Heart Journal· 0 citations
Obesity is a major global health crisis with rising prevalence in both pediatric and adult populations, leading to an increased risk of cardiovascular, metabolic, and other chronic complications affecting all organ systems. A clear understanding of the genetic contributors to polygenic, syndromic, and monogenic obesity is essential for early diagnosis and targeted management. Advances in genome-wide association studies (GWAS) and sequencing technologies have greatly expanded our understanding of the genetic alterations underlying this multifaceted disease and have helped in delivering personalized treatment. The pathogenesis of common, polygenic obesity is related to a complex interplay between genetic susceptibility and environmental factors. Syndromic obesity, a less common form, is characterized by early-onset accompanied by additional features such as developmental delay, dysmorphic traits, and various organ system involvement. The rarest form, monogenic obesity, is characterized by severe early-onset non-syndromic obesity caused by mutations in single genes regulating appetite within the hypothalamus. These monogenic obesity cases, though infrequent, have been instrumental in elucidating key pathways involved in hunger and satiety. This review provides a comprehensive summary of the most recent findings on the genetic basis of obesity across all age groups, highlighting clinical implications and emerging therapeutic opportunities.
Cardio-oncology patients may face complex treatment regimens due to the concurrent existence of cancer and cardiovascular disease, leading to a considerable polypharmacy burden. This significantly increases the prospect of drug-drug interactions (DDIs) and gene-drug interactions. The majority of these interactions arise from comparable pharmacokinetic and pharmacological pathways associated with drug transporters and cytochrome P450 enzymes. The significance of pharmacogenomics in tailored treatment strategies are emphasised by the fact that genetic variability enhances individual differences in drug response, safety, and efficacy. This narrative review focus on the effects of key genetic polymorphisms (e.g., DPYD, CYP2C19, and CYP2C9) on the metabolism and efficacy of commonly prescribed anticancer and cardiovascular medications such as fluoropyrimidines, clopidogrel, and warfarin. In addition it explore the role of pharmacogenomic variants on drug-drug interactions within the field of cardio-oncology. The study ultimately emphasizes the necessity of precision medicine in India to address the genetic diversity and underrepresentation in global genomic databases. The absence of pharmacogenomic testing, infrastructural deficiencies, financial constraints, and insufficient clinical integration hinder the widespread use of this technology in India. The Genome India Project and other national initiatives establish the foundation for pharmacogenomic-guided therapy. Utilizing genetic data, together with artificial intelligence-based predictive tools, for clinical decision-making may enhance medication safety and yield optimal outcomes in Indian cardio-oncology patients.
Aanya Verma, P. D.· Current problems in cardiolo...· 0 citations
Human genetic variation plays a fundamental role in determining differences among individuals in disease susceptibility, clinical characteristics and responses to medical treatments. Advances in genomic technologies have significantly improved our ability to identify and characterize genetic differences, including single nucleotide variants, insertions and deletions, copy number variations and larger structural changes within the genome. These variations influence biological processes and contribute to both health and disease outcomes, making them essential to the development of precision medicine. This review examines the major forms of human genetic variation and their impact on disease development and pharmacological responses. It explores how genetic variants arise, their distribution across populations, and their involvement in monogenic, oligogenic and polygenic disorders. The review also highlights the importance of gene–environment interactions and epigenetic factors in shaping disease risk and progression. In addition, the paper discusses the growing field of pharmacogenomics, which investigates how genetic differences affect drug metabolism, efficacy and toxicity. Particular attention is given to clinically important variants in drug-metabolizing enzymes, transport proteins, and therapeutic targets that contribute to variability in treatment outcomes among patients. By linking disease genetics with pharmacogenomics, genetic information can be used both to predict disease risk and to guide individualized treatment strategies.
Peer Review History:
Received 5 April 2026; Reviewed 11 May 2026; Accepted 9 June; Available online 15 July 2026
Academic Editor: Dr. Muhammad Zahid Iqbal, AIMST University, Malaysia, drmmziqbal@gmail.com
Reviewers:
Dr. Hasniza Zaman Huri, University of Malaya Medical Centre, Kuala Lumpur, hasnizazh@ummc.edu.my
Dr. Hayriye Eda Şatana Kara, Gazi University, Turkey, eda@gazi.edu.tr
Fathiah O. Oladele, Gloria E. Ebimo-Moko, Jochebed D. Joel et al.· Universal Journal of Pharmac...· 0 citations
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