Genome-wide association study identifies pharmacogenomic loci linked with specific antihypertensive drug treatment and new-onset diabetes

Antihypertensives associated adverse events: a review of mechanisms and pharmacogenomic biomarkers available evidence in multi-ethnic populations

Hypertension remains a significant health burden worldwide, re-emphasizing the outstanding need for more effective and safer antihypertensive therapeutic approaches. Genetic variation contributes significantly to interindividual variability in treatment response and adverse events, suggesting pharmacogenomics as a major approach to optimize such therapy. This review examines the molecular mechanisms underlying antihypertensives-associated adverse events and surveys existing research on pharmacogenomic biomarkers associated with these events. The current literature revealed limited conclusive evidence supporting the use of genetic variants as reliable indicators of antihypertensive adverse events. However, several noteworthy associations have emerged, such as 1) the role of ACE variants in increasing the risk of multiple adverse events, 2) the bradykinin pathway's involvement in cough induced by ACE inhibitors, and 3) the impact of CYP2D6 variants on metoprolol-induced bradycardia. Nonetheless, challenges persist in identifying biomarkers for adverse events across different antihypertensive classes, sometimes due to the rarity of certain events, such as ACE inhibitors-induced angioedema. We also highlight the main limitations of previous studies that warrant attention, including using a targeted gene approach with a limited number of tested variants, small sample sizes, and design issues such as overlooking doses or the time between starting treatment and the onset of adverse events. Addressing these challenges requires collaborative efforts and the integration of technological advancements, such as next-generation sequencing, which can significantly enhance research outcomes and provide the needed evidence. Furthermore, the potential combination of genomic biomarker identification and machine learning is a promising approach for tailoring antihypertensive therapy to individual patients, thereby mitigating the risk of developing adverse events. In conclusion, a deeper understanding of the mechanisms and the pharmacogenomics of adverse events in antihypertensive therapy will likely pave the way for more personalized treatment strategies to improve patient outcomes.

Genome-Wide Association Study of Beta-Blocker Survival Benefit in Black and White Patients with Heart Failure with Reduced Ejection Fraction

In patients with heart failure with reduced ejection fraction (HFrEF), individual responses to beta-blockers vary. Candidate gene pharmacogenetic studies yielded significant but inconsistent results, and they may have missed important associations. Our objective was to use an unbiased genome-wide association study (GWAS) to identify loci influencing beta-blocker survival benefit in HFrEF patients. Genetic variant × beta-blocker exposure interactions were tested in Cox proportional hazards models for all-cause mortality stratified by self-identified race. The models were adjusted for clinical risk factors and propensity scores. A prospective HFrEF registry (469 black and 459 white patients) was used for discovery, and linkage disequilibrium (LD) clumped variants with a beta-blocker interaction of p < 5 × 10-5, were tested for Bonferroni-corrected validation in a multicenter HFrEF clinical trial (288 black and 579 white patients). A total of 229 and 18 variants in black and white HFrEF patients, respectively, had interactions with beta-blocker exposure at p < 5 × 10-5 upon discovery. After LD-clumping, 100 variants and 4 variants in the black and white patients, respectively, remained for validation but none reached statistical significance. In conclusion, genetic variants of potential interest were identified in a discovery-based GWAS of beta-blocker survival benefit in HFrEF patients, but none were validated in an independent dataset. Larger cohorts or alternative approaches, such as polygenic scores, are needed.

AC010883.5 promotes cell proliferation, invasion, migration, and epithelial-to-mesenchymal transition in cervical cancer by modulating the MAPK signaling pathway

Homo sapiens chromosome 2 clone RP11-339H12 (AC010883.5) is a dysregulated long non-coding RNA (lncRNA) that has never been investigated in cervical cancer (CC). Thus, the potential function and molecular mechanism remain unclear. Our study explored the biological function of AC010883.5 to determine the underlying mechanisms in CC and provide potential therapeutic targets for improving the clinical treatment strategy. We used quantitative real-time polymerase chain reaction to measure mitochondrial RNA levels and western blot to measure the protein levels of target genes. Further, we used Cell Counting Kit-8 and 5-Bromo-2'-deoxyuridine incorporation assays to evaluate cell proliferation in vitro. Cell apoptosis was analyzed by flow cytometry. Cell invasion was analyzed by wound healing and Transwell migration assays was ued to analyze cell migration. Finally, the biological function and mechanism of AC010883.5 in CC growth were evaluated by in vivo xenograft assay. AC010883.5 was enhanced in CC tissues and cell lines, and enhanced AC010883.5 expression accelerated CC cell proliferation, migration, and invasion and induced epithelial-mesenchymal transition in vitro and in vivo. AC010883.5 also activated the mitogen-activated protein kinase (MAPK) signaling pathway by promoting phosphorylation of extracellular signal-regulated kinase 1/2 (i.e., ERK1/2) and MAPK kinase 1/2 (i.e., MEK1/2). Blocking the MAPK signaling pathway could counteract the pro-proliferative, pro-migrative, and pro-invasive effects of AC010883.5 over-expression. We found that the lncRNA, AC010883.5, is an oncogenic molecule involved in CC tumor progression via dysregulation of the MAPK signaling pathway, implying that AC010883.5 could be a tumor progression and therapeutic response biomarker.

Intergenerational effects of preconception opioids on glucose homeostasis and hepatic transcription in adult male rats

Adolescence represents a period of significant neurodevelopment during which adverse experiences can lead to prolonged effects on disease vulnerability, including effects that can impact future offspring. Adolescence is a common period for the initiation of drug use, including the use of opioids. Beyond effects on central reward, opioids also impact glucose metabolism, which can impact the risk of diabetes. Moreover, recent animal models suggest that the effects of adolescent opioids can effect glucose metabolism in future offspring. Indeed, we demonstrated that the adult male offspring of females exposed to morphine for 10 days during adolescence (referred to as MORF1 males) are predisposed to the adverse effects of an obesogenic diet. As adults, MORF1 males fed a high fat moderate sucrose diet (FSD) for just 6 weeks had increased fasting glucose and insulin levels when compared to age-matched offspring of females exposed to saline during adolescence (SALF1 males). Clinically, a similar profile of impaired fasting glucose has been associated with hepatic insulin resistance and an increased risk of non-alcoholic fatty liver disease. Thus, in the current study, we used RNA sequencing to determine whether adult MORF1 males demonstrate significant alterations in the hepatic transcriptome suggestive of alterations in metabolism. Age-matched SALF1 and MORF1 males were fed either FSD or control diet (CD) for 8 weeks. Similar to our previous observations, FSD-maintained MORF1 males gained more weight and displayed both fasting hyperglycemia and hyperinsulinemia when compared to FSD-maintained SALF1 males, with no significant effect on glucagon. No differences in bodyweight or fasting-induce glucose were observed in control diet (CD)-maintained F1 males, although there was a trend for CD MORF1 males to display elevated levels of fasting insulin. Unexpectedly, transcriptional analyses revealed profound differences in the hepatic transcriptome of CD-maintained MORF1 and SALF1 (1686 differentially expressed genes) with no significant differences between FSD-maintained MORF1 and SALF1 males. As changes in the hepatic transcriptome were not revealed under 8 weeks FSD conditions, we extended the feeding paradigm and conducted a glucose tolerance test to determine whether impaired fasting glucose observed in FSD MORF1 males was due to peripheral insulin resistance. Impaired glucose tolerance was observed in both CD and FSD MORF1 males, and to a more limited extent in FSD SALF1 males. These findings implicate intergenerational effects of adolescent morphine exposure on the risk of developing insulin resistance and associated comorbidities, even in the absence of an obesogenic diet.

Integrating disease and drug-related phenotypes for improved identification of pharmacogenomic variants

Aim: To improve the identification and interpretation of pharmacogenetic variants through the integration of disease and drug-related traits. Materials & methods: We hypothesized that integrating genome-wide disease and pharmacogenomic data may drive new insights into drug toxicity and response by identifying shared genetic architecture. Pleiotropic variants were identified using a methodological framework incorporating colocalization analysis. Results: Using genome-wide association studies summary statistics from the UK Biobank, European Bioinformatics Institute genome-wide association studies catalog and the Pharmacogenomics Research Network, we validated pleiotropy at the ABCG2 locus between allopurinol response and gout and identified novel pleiotropy between antihypertensive-induced new-onset diabetes, Crohn's disease and inflammatory bowel disease at the IL18RAP/SLC9A4 locus. Conclusion: New mechanistic insights and genetic loci can be uncovered by identifying pleiotropy between disease and drug-related traits.

Drug-induced hyperglycaemia and diabetes: pharmacogenomics perspectives

Drug-induced diabetes is widely reported in clinical conditions, and it is becoming a global issue because of its potential to increase the risk of severe cardiovascular complications. However, which drug mechanisms exert their diabetogenic effects and why the effects present significant inter-individual differences remain largely unknown. Pharmacogenomics, which is the study of how genomic variation influences drug responses, provides an explanation for individual differences in drug-induced diabetes. We highlight that pharmacogenomics can be involved in regulating the expression of genes in signaling pathways related to the pharmacokinetics or pharmacodynamics of drugs or the pathogenesis of diabetes, contributing to the differences in drug-induced glucose impairment. The pharmacogenomics studies of the major diabetogenic drugs are reviewed, including calcineurin inhibitors, antipsychotics, hormones, and antihypertensive drugs. We intend to elucidate the genetic basis of drug-induced diabetes and pave the way for the precise use of these drugs in the clinic.