Whole genome sequencing identifies putative associations between genomic polymorphisms and clinical response to the antiepileptic drug levetiracetam
In the context of pharmacogenomics, whole genome sequencing provides a powerful approach for identifying correlations between response variability to specific drugs and genomic polymorphisms in a population, in an unbiased manner. In this study, we employed whole genome sequencing of DNA samples from patients showing extreme response (n=72) and non-response (n=27) to the antiepileptic drug levetiracetam, in order to identify genomic variants that underlie response to the drug. Although no common SNP (MAF>5%) crossed the conventional genome-wide significance threshold of 5e-8, we found common polymorphisms in genes SPNS3, HDC, MDGA2, NSG1 and RASGEF1C, which collectively predict clinical response to levetiracetam in our cohort with ~91% predictive accuracy. Among these genes, HDC, NSG1, MDGA2 and RASGEF1C are potentially implicated in synaptic neurotransmission, while SPNS3 is an atypical solute carrier transporter homologous to SV2A, the known molecular target of levetiracetam. Furthermore, we performed gene- and pathway-based statistical analysis on sets of rare and low-frequency variants (MAF<5%) and we identified associations between the following genes or pathways and response to levetiracetam: a) genes PRKCB and DLG2, which are involved in glutamatergic neurotransmission, a known target of anticonvulsants, including levetiracetam; b) genes FILIP1 and SEMA6D, which are involved in axon guidance and modelling of neural connections; and c) pathways with a role in synaptic neurotransmission, such as WNT5A-dependent internalization of FZD4 and disinhibition of SNARE formation. In summary, our approach to utilise whole genome sequencing on subjects with extreme response phenotypes is a feasible route to generate plausible hypotheses for investigating the genetic factors underlying drug response variability in cases of pharmaco-resistant epilepsy.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Whole genome single nucleotide polymorphism genotyping of Staphylococcus aureus
Next-generation sequencing technology enables routine detection of bacterial pathogens for clinical diagnostics and genetic research. Whole genome sequencing has been of importance in the epidemiologic analysis of bacter…
ViralQC: A Tool for Assessing Completeness and Contamination of Predicted Viral Contigs
Motivation: Viruses represent the most abundant biological entities on the planet and play vital roles in diverse ecosystems. Cataloging viruses across various environments is essential for understanding their properties…
Analysis of whole mitogenomes from ancient samples
Ancient mitochondrial DNA has been used in a wide variety of palaeontological and archaeological studies, ranging from population dynamics of extinct species to patterns of domestication. Most of these studies have tradi…
Accurate and fast detection of copy number variations from short-read whole-genome sequencing with deep convolutional neural network
A copy number variant (CNV) is a type of genetic mutation where a stretch of DNA is lost or duplicated once or multiple times. CNVs play important roles in the development of diseases and complex traits. CNV detection wi…
BenchmarkingLearning interpretable models of phenotypes from whole genome sequences with the Set Covering Machine
The increased affordability of whole genome sequencing has motivated its use for phenotypic studies. We address the problem of learning interpretable models for discrete phenotypes from whole genomes. We propose a genera…