Pharmacogenomic Discovery Delineating the Genetic Basis of Drug Response

Disease burden and the role of pharmacogenomics in African populations

Background

The burden of communicable and non-communicable diseases in Sub-Saharan Africa poses a challenge in achieving quality healthcare. Although therapeutic drugs have generally improved health, their efficacy differs from individual to individual. Variability in treatment response is mainly because of genetic variants that affect the pharmacokinetics and pharmacodynamics of drugs.

Method

The intersection of disease burden and therapeutic intervention is reviewed, and the status of pharmacogenomics knowledge in African populations is explored.

Results

The most commonly studied variants with pharmacogenomics relevance are discussed, especially in genes coding for enzymes that affect the response to drugs used for HIV, malaria, sickle cell disease and cardiovascular diseases.

Conclusions

The genetically diverse African population is likely to benefit from a pharmacogenomics-based healthcare approach, especially with respect to reduction of drug side effects, and separation of responders and non-responders leading to optimized drug choices and doses for each patient.

Elevated DRD4 promoter methylation increases the risk of Alzheimer's disease in males

Aberrant promoter methylation of multiple genes is associated with various diseases, including Alzheimer's disease (AD). The goal of the present study was to determine whether dopamine receptor D4 (DRD4) promoter methylation is associated with AD. In the current study, the methylation levels of the DRD4 promoter were measured in 46 AD patients and 61 controls using bisulfite pyrosequencing technology. The results of the present study demonstrated that DRD4 promoter methylation was significantly higher in AD patients than in controls. A further breakdown analysis by gender revealed that there was a significant association of DRD4 promoter methylation with AD in males (23 patients and 45 controls). In conclusion, the results of the present study demonstrated that elevated DRD4 promoter methylation was associated with AD risk in males.

Transcriptional similarity in couples reveals the impact of shared environment and lifestyle on gene regulation through modified cytosines

Gene expression is a complex and quantitative trait that is influenced by both genetic and non-genetic regulators including environmental factors. Evaluating the contribution of environment to gene expression regulation and identifying which genes are more likely to be influenced by environmental factors are important for understanding human complex traits. We hypothesize that by living together as couples, there can be commonly co-regulated genes that may reflect the shared living environment (e.g., diet, indoor air pollutants, behavioral lifestyle). The lymphoblastoid cell lines (LCLs) derived from unrelated couples of African ancestry (YRI, Yoruba people from Ibadan, Nigeria) from the International HapMap Project provided a unique model for us to characterize gene expression pattern in couples by comparing gene expression levels between husbands and wives. Strikingly, 778 genes were found to show much smaller variances in couples than random pairs of individuals at a false discovery rate (FDR) of 5%. Since genetic variation between unrelated family members in a general population is expected to be the same assuming a random-mating society, non-genetic factors (e.g., epigenetic systems) are more likely to be the mediators for the observed transcriptional similarity in couples. We thus evaluated the contribution of modified cytosines to those genes showing transcriptional similarity in couples as well as the relationships these CpG sites with other gene regulatory elements, such as transcription factor binding sites (TFBS). Our findings suggested that transcriptional similarity in couples likely reflected shared common environment partially mediated through cytosine modifications.

Methods: for studying pharmacogenetic profiles of combination chemotherapeutic drugs

INTRODUCTION

Molecular and genetic analysis of tumors and individuals has led to patient-centered therapies, through the discovery and identification of genetic markers predictive of drug efficacy and tolerability. Present therapies often include a combination of synergic drugs, each of them directed against different targets. Therefore, the pharmacogenetic profiling of tumor masses and patients is becoming a challenge, and several questions may arise when planning a translational study.

AREAS COVERED

The review presents the different techniques used to stratify oncology patients and to tailor antineoplastic treatments according to individual pharmacogenetic profiling. The advantages of these methodologies are discussed as well as current limits.

EXPERT OPINION

Facing the rapid technological evolution for genetic analyses, the most pressing issues are the choice of appropriate strategies (i.e., from gene candidate up to next-generation sequencing) and the possibility to replicate study results for their final validation. It is likely that the latter will be the major obstacle in the future. However, the present landscape is opening up new possibilities, overcoming those hurdles that have limited result translation into clinical settings for years.

SCAN database: facilitating integrative analyses of cytosine modification and expression QTL

Functional annotation of genetic variants including single nucleotide polymorphisms (SNPs) and copy number variations (CNV) promises to greatly improve our understanding of human complex traits. Previous transcriptomic studies involving individuals from different global populations have investigated the genetic architecture of gene expression variation by mapping expression quantitative trait loci (eQTL). Functional interpretation of genome-wide association studies (GWAS) has identified enrichment of eQTL in top signals from GWAS of human complex traits. The SCAN (SNP and CNV Annotation) database was developed as a web-based resource of genetical genomic studies including eQTL detected in the HapMap lymphoblastoid cell line samples derived from apparently healthy individuals of European and African ancestry. Considering the critical roles of epigenetic gene regulation, cytosine modification quantitative trait loci (mQTL) are expected to add a crucial layer of annotation to existing functional genomic information. Here, we describe the new features of the SCAN database that integrate comprehensive mQTL mapping results generated in the HapMap CEU (Caucasian residents from Utah, USA) and YRI (Yoruba people from Ibadan, Nigeria) LCL samples and demonstrate the utility of the enhanced functional annotation system.

Database URL:http://www.scandb.org/