PG-path: Modeling and personalizing pharmacogenomics-based pathways

Influence of Metabolic, Transporter, and Pathogenic Genes on Pharmacogenetics and DNA Methylation in Neurological Disorders

Pharmacogenetics and DNA methylation influence therapeutic outcomes and provide insights into potential therapeutic targets for brain-related disorders. To understand the effect of genetic polymorphisms on drug response and disease risk, we analyzed the relationship between global DNA methylation, drug-metabolizing enzymes, transport genes, and pathogenic gene phenotypes in serum samples from two groups of patients: Group A, which showed increased 5-methylcytosine (5mC) levels during clinical follow-up, and Group B, which exhibited no discernible change in 5mC levels. We identified specific SNPs in several metabolizing genes, including CYP1A2, CYP2C9, CYP4F2, GSTP1, and NAT2, that were associated with differential drug responses. Specific SNPs in CYP had a significant impact on enzyme activity, leading to changes in phenotypic distribution between the two patient groups. Group B, which contained a lower frequency of normal metabolizers and a higher frequency of ultra-rapid metabolizers compared to patients in Group A, did not show an improvement in 5mC levels during follow-up. Furthermore, there were significant differences in phenotype distribution between patient Groups A and B for several SNPs associated with transporter genes (ABCB1, ABCC2, SLC2A9, SLC39A8, and SLCO1B1) and pathogenic genes (APOE, NBEA, and PTGS2). These findings appear to suggest that the interplay between pharmacogenomics and DNA methylation has important implications for improving treatment outcomes in patients with brain-related disorders.

Integrative PheWAS analysis in risk categorization of major depressive disorder and identifying their associations with genetic variants using a latent topic model approach

Major depressive disorder (MDD) is the most prevalent mental disorder that constitutes a major public health problem. A tool for predicting the risk of MDD could assist with the early identification of MDD patients and targeted interventions to reduce the risk. We aimed to derive a risk prediction tool that can categorize the risk of MDD as well as discover biologically meaningful genetic variants. Data analyzed were from the fourth and fifth data collections of a longitudinal community-based cohort from Southwest Montreal, Canada, between 2015 and 2018. To account for high dimensional features, we adopted a latent topic model approach to infer a set of topical distributions over those studied predictors that characterize the underlying meta-phenotypes of the MDD cohort. MDD probability derived from 30 MDD meta-phenotypes demonstrated superior prediction accuracy to differentiate MDD cases and controls. Six latent MDD meta-phenotypes we inferred via a latent topic model were highly interpretable. We then explored potential genetic variants that were statistically associated with these MDD meta-phenotypes. The genetic heritability of MDD meta-phenotypes was 0.126 (SE = 0.316), compared to 0.000001 (SE = 0.297) for MDD diagnosis defined by the structured interviews. We discovered a list of significant MDD - related genes and pathways that were missed by MDD diagnosis. Our risk prediction model confers not only accurate MDD risk categorization but also meaningful associations with genetic predispositions that are linked to MDD subtypes. Our findings shed light on future research focusing on these identified genes and pathways for MDD subtypes.

Genophenotypic Factors and Pharmacogenomics in Adverse Drug Reactions

Adverse drug reactions (ADRs) rank as one of the top 10 leading causes of death and illness in developed countries. ADRs show differential features depending upon genotype, age, sex, race, pathology, drug category, route of administration, and drug–drug interactions. Pharmacogenomics (PGx) provides the physician effective clues for optimizing drug efficacy and safety in major problems of health such as cardiovascular disease and associated disorders, cancer and brain disorders. Important aspects to be considered are also the impact of immunopharmacogenomics in cutaneous ADRs as well as the influence of genomic factors associated with COVID-19 and vaccination strategies. Major limitations for the routine use of PGx procedures for ADRs prevention are the lack of education and training in physicians and pharmacists, poor characterization of drug-related PGx, unspecific biomarkers of drug efficacy and toxicity, cost-effectiveness, administrative problems in health organizations, and insufficient regulation for the generalized use of PGx in the clinical setting. The implementation of PGx requires: (i) education of physicians and all other parties involved in the use and benefits of PGx; (ii) prospective studies to demonstrate the benefits of PGx genotyping; (iii) standardization of PGx procedures and development of clinical guidelines; (iv) NGS and microarrays to cover genes with high PGx potential; and (v) new regulations for PGx-related drug development and PGx drug labelling.