Genetic Risk of Diverticular Disease Predicts Early Stoppage of Nicorandil

Genetic, epigenetic and environmental factors in diverticular disease: systematic review

BACKGROUND

Diverticulosis is a normal anatomical variant of the colon present in more than 70% of the westernized population over the age of 80. Approximately 3% will develop diverticulitis in their lifetime. Many patients present emergently, suffer high morbidity rates and require substantial healthcare resources. Diverticulosis is the most common finding at colonoscopy and has the potential for causing a significant morbidity rate and burden on healthcare. There is a need to better understand the aetiology and pathogenesis of diverticular disease. Research suggests a genetic susceptibility of 40-50% in the formation of diverticular disease. The aim of this review is to present the hypothesized functional effects of the identified gene loci and environmental factors.

METHODS

A systematic literature review was performed using PubMed, MEDLINE and Embase. Medical subject headings terms used were: 'diverticular disease, diverticulosis, diverticulitis, genomics, genetics and epigenetics'. A review of grey literature identified environmental factors.

RESULTS

Of 995 articles identified, 59 articles met the inclusion criteria. Age, obesity and smoking are strongly associated environmental risk factors. Intrinsic factors of the colonic wall are associated with the presence of diverticula. Genetic pathways of interest and environmental risk factors were identified. The COLQ, FAM155A, PHGR1, ARHGAP15, S100A10, and TNFSF15 genes are the strongest candidates for further research.

CONCLUSION

There is increasing evidence to support the role of genomics in the spectrum of diverticular disease. Genomic, epigenetic and omic research with demographic context will help improve the understanding and management of this complex disease.

Applying polygenic risk score methods to pharmacogenomics GWAS: challenges and opportunities

Polygenic risk scores (PRSs) have emerged as promising tools for the prediction of human diseases and complex traits in disease genome-wide association studies (GWAS). Applying PRSs to pharmacogenomics (PGx) studies has begun to show great potential for improving patient stratification and drug response prediction. However, there are unique challenges that arise when applying PRSs to PGx GWAS beyond those typically encountered in disease GWAS (e.g. Eurocentric or trans-ethnic bias). These challenges include: (i) the lack of knowledge about whether PGx or disease GWAS/variants should be used in the base cohort (BC); (ii) the small sample sizes in PGx GWAS with corresponding low power and (iii) the more complex PRS statistical modeling required for handling both prognostic and predictive effects simultaneously. To gain insights in this landscape about the general trends, challenges and possible solutions, we first conduct a systematic review of both PRS applications and PRS method development in PGx GWAS. To further address the challenges, we propose (i) a novel PRS application strategy by leveraging both PGx and disease GWAS summary statistics in the BC for PRS construction and (ii) a new Bayesian method (PRS-PGx-Bayesx) to reduce Eurocentric or cross-population PRS prediction bias. Extensive simulations are conducted to demonstrate their advantages over existing PRS methods applied in PGx GWAS. Our systematic review and methodology research work not only highlights current gaps and key considerations while applying PRS methods to PGx GWAS, but also provides possible solutions for better PGx PRS applications and future research.

A systematic review and analysis of the use of polygenic scores in pharmacogenomics

Polygenic scores (PGS) have emerged as promising tools for complex trait risk prediction. The application of these scores to pharmacogenomics provides new opportunities to improve the prediction of treatment outcomes. To gain insight into this area of research, we conducted a systematic review and accompanying analysis. This review uncovered 51 papers examining the use of PGS for drug-related outcomes, with the majority of these papers focusing on the treatment of psychiatric disorders (n=30). Due to difficulties in collecting large cohorts of uniformly treated patients, the majority of pharmacogenomic PGS were derived from large-scale genome-wide association studies of disease phenotypes that were related to the pharmacogenomic phenotypes under investigation (e.g. schizophrenia-derived PGS for antipsychotic response prediction). Examination of the research participants included in these studies revealed that the majority of cohort participants were of European descent (78.4%). These biases were also reflected in research affiliations, which were heavily weighted towards institutions located in Europe and North America, with no first or last authors originating from institutions in Africa or South Asia. There was also substantial variability in the methods used to develop PGS, with between 3 and 6.6 million variants included in the PGS. Finally, we observed significant inconsistencies in the reporting of PGS analyses and results, particularly in terms of risk model development and application, coupled with a lack of data transparency and availability, with only three pharmacogenomics PGS deposited on the PGS Catalog. These findings highlight current gaps and key areas for future pharmacogenomic PGS research.

Precision Medicine and Adverse Drug Reactions Related to Cardiovascular Drugs

Cardiovascular disease remains the leading global cause of death. Early intervention, with lifestyle advice alongside appropriate medical therapies, is fundamental to reduce patient mortality among high-risk individuals. For those who live with the daily challenges of cardiovascular disease, pharmacological management aims to relieve symptoms and prevent disease progression. Despite best efforts, prescription drugs are not without their adverse effects, which can cause significant patient morbidity and consequential economic burden for healthcare systems. Patients with cardiovascular diseases are often among the most vulnerable to adverse drug reactions due to multiple co-morbidities and advanced age. Examining a patient's genome to assess for variants that may alter drug efficacy and susceptibility to adverse reactions underpins pharmacogenomics. This strategy is increasingly being implemented in clinical cardiology to tailor patient therapies. The identification of specific variants associated with adverse drug effects aims to predict those at greatest risk of harm, allowing alternative therapies to be given. This review will explore current guidance available for pharmacogenomic-based prescribing as well as exploring the potential implementation of genetic risk scores to tailor treatment. The benefits of large databases and electronic health records will be discussed to help facilitate the integration of pharmacogenomics into primary care, the heartland of prescribing.

Nicorandil-induced colovesical fistula in a patient with diverticular disease

Nicorandil's adverse effects can cause severe patient morbidity and can present to any specialty. Those with underlying diverticular disease are most susceptible. Medication reviews are vital for patients presenting with ulcer or fistula symptoms.