Biobank Scale Pharmacogenomics Informs the Genetic Underpinnings of Simvastatin Use

Research on genetic variant characteristics in ADME genes based on whole-exome sequencing in the Han Chinese population

BACKGROUND

Genetic variants in absorption, distribution, metabolism, and excretion (ADME) genes affect drug efficacy and side effects. Whole-exome sequencing (WES) effectively identifies these variants. Findings from Western populations may not apply to the Han Chinese population due to ethnic differences.

OBJECTIVE

This study aimed to investigate genetic variants, metabolic phenotypes, and drug impacts related to ADME genes in the Han Chinese population using WES data.

METHODS

ADME genes and drug profiles were sourced from multiple databases. WES data were collected from 357 samples at Third Xiangya Hospital and 5,000 samples from the "HuaBiao Project." After WES, fastp was used for quality control; BWA, samtools, and the Picard software were used for comparison, sequencing, and de-duplication; GATK was used for base quality score recalibration; and variant quality score recalibration was carried out after detecting the variants, and the variants were annotated using ANNOVAR. ADME genes and drug profiles were obtained through PharmGKB and other databases, and then all variants in the exonic regions of ADME genes were extracted. The distributional characteristics of these variants, ethnic differences, and metabolic phenotype distribution of important ADME genes, such as CYP2B6, were analyzed. Prediction of deleterious variants of ADME gene employed the ADME gene variant prediction framework, and western blotting and enzyme assays were used to validate the impact of harmful variants.

RESULTS

We integrated 604 ADME genes and 972 drugs. There were 33,925 single nucleotide polymorphisms (SNPs) and 484 insertion-deletions (InDels) in 5,357 Han Chinese WES samples; 88.9 % were rare. Of the SNPs, 60.9 % are new functional mutations in enzyme and transporter genes; InDels also affected these genes. We discovered Chinese-specific variants in key ADME genes and ethnic-specific metabolic phenotypes that could affect drug use. Finally, we screened 3,657 potentially harmful mutations; 45.6 % are novel. Western blotting and enzyme activity assays confirmed several harmful mutations significantly reduced CYP2C19 gene expression and function (P < 0.01).

Pharmacogenomics Beyond Single Common Genetic Variants: The Way Forward

Interindividual variability in genes encoding drug-metabolizing enzymes, transporters, receptors, and human leukocyte antigens has a major impact on a patient's response to drugs with regard to efficacy and safety. Enabled by both technological and conceptual advances, the field of pharmacogenomics is developing rapidly. Major progress in omics profiling methods has enabled novel genotypic and phenotypic characterization of patients and biobanks. These developments are paralleled by advances in machine learning, which have allowed us to parse the immense wealth of data and establish novel genetic markers and polygenic models for drug selection and dosing. Pharmacogenomics has recently become more widespread in clinical practice to personalize treatment and to develop new drugs tailored to specific patient populations. In this review, we provide an overview of the latest developments in the field and discuss the way forward, including how to address the missing heritability, develop novel polygenic models, and further improve the clinical implementation of pharmacogenomics.

From pharmacogenetics to pharmaco-omics: Milestones and future directions

The origins of pharmacogenetics date back to the 1950s, when it was established that inter-individual differences in drug response are partially determined by genetic factors. Since then, pharmacogenetics has grown into its own field, motivated by the translation of identified gene-drug interactions into therapeutic applications. Despite numerous challenges ahead, our understanding of the human pharmacogenetic landscape has greatly improved thanks to the integration of tools originating from disciplines as diverse as biochemistry, molecular biology, statistics, and computer sciences. In this review, we discuss past, present, and future developments of pharmacogenetics methodology, focusing on three milestones: how early research established the genetic basis of drug responses, how technological progress made it possible to assess the full extent of pharmacological variants, and how multi-dimensional omics datasets can improve the identification, functional validation, and mechanistic understanding of the interplay between genes and drugs. We outline novel strategies to repurpose and integrate molecular and clinical data originating from biobanks to gain insights analogous to those obtained from randomized controlled trials. Emphasizing the importance of increased diversity, we envision future directions for the field that should pave the way to the clinical implementation of pharmacogenetics.

Pharmacogenomics Informs Cardiovascular Pharmacotherapy

Precision medicine exemplifies the emergence of personalized treatment options which may benefit specific patient populations based upon their genetic makeup. Application of pharmacogenomics requires an understanding of how genetic variations impact pharmacokinetic and pharmacodynamic properties. This particular approach in pharmacotherapy is helpful because it can assist in and improve clinical decisions. Application of pharmacogenomics to cardiovascular pharmacotherapy provides for the ability of the medical provider to gain critical knowledge on a patient's response to various treatment options and risk of side effects.

Pharmacogenomics Variability of Lipid-Lowering Therapies in Familial Hypercholesterolemia

The exponential expansion of genomic data coupled with the lack of appropriate clinical categorization of the variants is posing a major challenge to conventional medications for many common and rare diseases. To narrow this gap and achieve the goals of personalized medicine, a collaborative effort should be made to characterize the genomic variants functionally and clinically with a massive global genomic sequencing of "healthy" subjects from several ethnicities. Familial-based clustered diseases with homogenous genetic backgrounds are amongst the most beneficial tools to help address this challenge. This review will discuss the diagnosis, management, and clinical monitoring of familial hypercholesterolemia patients from a wide angle to cover both the genetic mutations underlying the phenotype, and the pharmacogenomic traits unveiled by the conventional and novel therapeutic approaches. Achieving a drug-related interactive genomic map will potentially benefit populations at risk across the globe who suffer from dyslipidemia.