scholarly journals Whole genome sequencing identifies putative associations between genomic polymorphisms and clinical response to the antiepileptic drug levetiracetam

2019 ◽  
Author(s):  
DV Vavoulis ◽  
AT Pagnamenta ◽  
SJL Knight ◽  
MM Pentony ◽  
M Armstrong ◽  
...  
Keyword(s):  
Antiepileptic Drug ◽  
Whole Genome Sequencing ◽  
Clinical Response ◽  
Genome Sequencing ◽  
Drug Response ◽  
Low Frequency ◽  
Response Variability ◽  
Whole Genome ◽  
Extreme Response ◽  
Synaptic Neurotransmission

ABSTRACTIn 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 5×10−8, 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 (∼94% positive predictive value, ∼85% negative predictive value). 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 genes or pathways and response to levetiracetam. Our findings include a) the genes PRKCB and DLG2, which are involved in glutamatergic neurotransmission, a known target of anticonvulsants, including levetiracetam; b) the 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. Targeted analysis of genes involved in neurotransmitter release and transport further supports the possibility of association between drug response and genes NSG1 and DLG2. 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.AUTHOR SUMMARYLevetiracetam (LEV) is a prominent antiepileptic drug prescribed for the treatment of both focal and generalised epilepsy. The molecular mechanism mediating its action is not well understood, but it involves the modulation of synaptic neurotransmition through binding to the synaptic vesicle glycoprotein SV2A. Identifying genomic polymorphisms that predict response to the drug is important, because it can help clinicians prescribe the most appropriate treatment in a patient-specific manner. In this study, we employed whole genome sequencing (WGS) of DNA samples from extreme responders or non-responders to LEV and we identified a small group of common variants, which successfully predict response to the drug in our cohort. These variants are mostly located in genes implicated in synaptic function. Furthermore, we identified significant associations between clinical response to LEV and low-frequency variants in genes and pathways involved in excitatory neurotransmission or in the moulding of neural networks in the brain. Our approach to utilise WGS on subjects with extreme response phenotypes is a feasible route to generate plausible hypotheses on the genomic basis of pharmaco-resistant epilepsy. We expect that the rapidly decreasing cost of WGS will allow conducting similar studies on a larger scale in the near future.

scholarly journals Whole genome sequencing of pharmacogenetic drug response in racially and ethnically diverse children with asthma

2017 ◽  
Author(s):  
Angel C.Y. Mak ◽  
Marquitta J. White ◽  
Zachary A. Szpiech ◽  
Walter L. Eckalbar ◽  
Sam S. Oh ◽  
...  
Keyword(s):  
African Americans ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Drug Response ◽  
Puerto Ricans ◽  
Ethnically Diverse ◽  
Asthma Prevalence ◽  
Whole Genome ◽  
Minority Children ◽  
Children With Asthma

ABSTRACTAsthma is the most common chronic disease of children, with significant racial/ethnic differences in prevalence, morbidity, mortality and therapeutic response. Albuterol, a bronchodilator medication, is the first-line therapy for asthma treatment worldwide. We performed the largest whole genome sequencing (WGS) pharmacogenetics study to date using data from 1,441 minority children with asthma who had extremely high or low bronchodilator drug response (BDR). We identified population-specific and shared pharmacogenetic variants associated with BDR, including genome-wide significant (p < 3.53 x 10-7) and suggestive (p < 7.06 x 10-6) loci near genes previously associated with lung capacity (DNAH5), immunity (NFKB1 and PLCB1), and β-adrenergic signaling pathways (ADAMTS3 and COX18). Functional analyses centered on NFKB1 revealed potential regulatory function of our BDR-associated SNPs in bronchial smooth muscle cells. Specifically, these variants are in linkage disequilibrium with SNPs in a functionally active enhancer, and are also expression quantitative trait loci (eQTL) for a neighboring gene, SLC39A8. Given the lack of other asthma study populations with WGS data on minority children, replication of our rare variant associations is infeasible. We attempted to replicate our common variant findings in five independent studies with GWAS data. The age-specific associations previously found in asthma and asthma-related traits suggest that the over-representation of adults in our replication populations may have contributed to our lack of statistical replication, despite the functional relevance of the NFKB1 variants demonstrated by our functional assays. Our study expands the understanding of pharmacogenetic analyses in racially/ethnically diverse populations and advances the foundation for precision medicine in at-risk and understudied minority populations.AUTHOR SUMMARYAsthma is the most common chronic disease among children. Albuterol, a bronchodilator medication, is the first-line therapy for asthma treatment worldwide. In the U.S., asthma prevalence is the highest among Puerto Ricans, intermediate among African Americans and lowest in Whites and Mexicans. Asthma disparities extend to mortality, which is four- to five-fold higher in Puerto Ricans and African Americans compared to Mexicans [1]. Puerto Ricans and African Americans, the populations with the highest asthma prevalence and death rate, also have the lowest albuterol bronchodilator drug response (BDR). We conducted the largest pharmacogenetic study using whole genome sequencing data from 1,441 minority children with asthma who had extremely high or low albuterol bronchodilator drug response. We identified population-specific and shared pharmacogenetic variants associated with BDR. Our findings help inform the direction of future development of asthma medications and our study advances the foundation of precision medicine for at-risk, yet understudied, racially/ethnically diverse populations.

scholarly journals Whole-Genome and Transcriptome Sequencing Identified NOTCH2 and HES1 As Potential Markers of Response to Imatinib in Desmoid Tumor (Aggressive Fibromatosis): A Phase II Trial Study

2021 ◽  
Author(s):  
Joonha Kwon ◽  
Jun Hyeong Lee ◽  
Young Han Lee ◽  
Jeeyun Lee ◽  
Jin-Hee Ahn ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Clinical Response ◽  
Rna Sequencing ◽  
Genome Sequencing ◽  
Desmoid Tumor ◽  
Large Scale ◽  
Genetic Interaction ◽  
Statistical Significance ◽  
Aggressive Fibromatosis ◽  
Whole Genome

Abstract Background: Desmoid tumor, also known as aggressive fibromatosis, is well-characterized by abnormal Wnt/β-catenin signaling. Various therapeutic options, including imatinib, are available to efficiently treat desmoid tumor. However, molecular mechanism of why imatinib works remains poorly understood. Here, we describe the potential roles of NOTCH2 and HES1 in association with clinical response to imatinib as in genome and transcriptome levels. Methods: We identified all somatic mutations in coding and non-coding regions via whole genome sequencing using desmoid tumor samples. To validate the genetic interaction with expression level in desmoid-tumor condition, we utilized large-scale Whole-genome sequencing (WGS) and transcriptome datasets from the Pan-Cancer Analysis of Whole Genomes (PCAWG) project. RNA-sequencing was performed using prospective and retrospective cohort samples to evaluate the expressional relevance with clinical response. Results: Among 20 patients, 4 (20%) had a partial response and 14 (66.7%) had stable disease, 11 of which continued for ≥1 year. With gene-wise functional analyses, we detected significant correlation between recurrent NOTCH2 noncoding mutations and clinical response to imatinib. Based on PCAWG data analyses, NOTCH2 mutations affect its expression levels particularly in the presence of CTNNB1 missense mutations. By analyzing RNA-sequencing with additional desmoid tumor samples, we found that NOTCH2 expression was significantly correlated with HES1 expression. Interestingly, NOTCH2 had no statistical power to discriminate responders and non-responders. Instead, HES1 was differentially expressed with statistical significance between responders and non-responders Conclusions: Imatinib was effective and well tolerated for advanced desmoid tumor treatment. Our results show that HES1, regulated by NOTCH2, as an indicator of sensitivity to imatinib, which provides an important therapeutic consideration for desmoid tumor. Trial Registration: ClinicalTrials.gov, NCT02495519, Registered July 13, 2015- Retrospectively registered, https://www.clinicaltrials.gov/ct2/show/NCT02495519

scholarly journals Very low depth whole genome sequencing in complex trait association studies

2017 ◽  
Author(s):  
Arthur Gilly ◽  
Lorraine Southam ◽  
Daniel Suveges ◽  
Karoline Kuchenbaecker ◽  
Rachel Moore ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Association Studies ◽  
Low Frequency ◽  
Cost Effective ◽  
Complex Trait ◽  
Whole Genome ◽  
Supplementary Data ◽  
Trait Association ◽  
High Depth

AbstractMotivationVery low depth sequencing has been proposed as a cost-effective approach to capture low-frequency and rare variation in complex trait association studies. However, a full characterisation of the genotype quality and association power for very low depth sequencing designs is still lacking.ResultsWe perform cohort-wide whole genome sequencing (WGS) at low depth in 1,239 individuals (990 at 1x depth and 249 at 4x depth) from an isolated population, and establish a robust pipeline for calling and imputing very low depth WGS genotypes from standard bioinformatics tools. Using genotyping chip, whole-exome sequencing (WES, 75x depth) and high-depth (22x) WGS data in the same samples, we examine in detail the sensitivity of this approach, and show that imputed 1x WGS recapitulates 95.2% of variants found by imputed GWAS with an average minor allele concordance of 97% for common and low-frequency variants. In our study, 1x further allowed the discovery of 140,844 true low-frequency variants with 73% genotype concordance when compared to high-depth WGS data. Finally, using association results for 57 quantitative traits, we show that very low depth WGS is an efficient alternative to imputed GWAS chip designs, allowing the discovery of up to twice as many true association signals than the classical imputed GWAS design.Supplementary DataSupplementary Data are appended to this manuscript.

scholarly journals Clinical-grade validation of whole genome sequencing reveals robust detection of low-frequency variants and copy number alterations in CLL

2018 ◽  
Vol 182 (3) ◽  
pp. 412-417 ◽  
Author(s):  
Jenny Klintman ◽  
Katerina Barmpouti ◽  
Samantha J. L. Knight ◽  
Pauline Robbe ◽  
Hélène Dreau ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Copy Number ◽  
Low Frequency ◽  
Whole Genome ◽  
Clinical Grade ◽  
Copy Number Alterations ◽  
Robust Detection

scholarly journals Genome-Wide Association of Kidney Traits in Hispanics/Latinos Using Dense Imputed Whole-Genome Sequencing Data

2020 ◽  
Vol 13 (4) ◽  
Author(s):  
Huijun Qian ◽  
Madeline H. Kowalski ◽  
Holly J. Kramer ◽  
Ran Tao ◽  
James P. Lash ◽  
...  
Keyword(s):  
Glomerular Filtration Rate ◽  
Whole Genome Sequencing ◽  
Glomerular Filtration ◽  
Genome Sequencing ◽  
Filtration Rate ◽  
Estimated Glomerular Filtration Rate ◽  
Low Frequency ◽  
Whole Genome ◽  
Creatinine Ratio ◽  
Urine Albumin

Background: Genetic factors that influence kidney traits have been understudied for low-frequency and ancestry-specific variants. Methods: This study used imputed whole-genome sequencing from the Trans-Omics for Precision Medicine project to identify novel loci for estimated glomerular filtration rate and urine albumin-to-creatinine ratio in up to 12 207 Hispanics/Latinos. Replication was performed in the Women’s Health Initiative and the UK Biobank when variants were available. Results: Two low-frequency intronic variants were associated with estimated glomerular filtration rate (rs58720902 at AQR , minor allele frequency=0.01, P =1.6×10 −8 ) or urine albumin-to-creatinine ratio (rs527493184 at ZBTB16 , minor allele frequency=0.002, P =1.1×10 −8 ). An additional variant at PRNT (rs2422935, minor allele frequency=0.54, P =2.89×10 −8 ) was significantly associated with estimated glomerular filtration rate in meta-analysis with replication samples. We also identified 2 known loci for urine albumin-to-creatinine ratio ( BCL2L11 rs116907128, P =5.6×10 −8 and HBB rs344, P =9.3×10 −11 ) and validated 8 loci for urine albumin-to-creatinine ratio previously identified in the UK Biobank. Conclusions: Our study shows gains in gene discovery when using dense imputation from multi-ethnic whole-genome sequencing data in admixed Hispanics/Latinos. It also highlights limitations in genetic research of kidney traits, including the lack of suitable replication samples for variants that are more common in non-European ancestry and those at low frequency in populations.

scholarly journals Whole-Genome Sequencing of Pharmacogenetic Drug Response in Racially Diverse Children with Asthma

2018 ◽  
Vol 197 (12) ◽  
pp. 1552-1564 ◽  
Author(s):  
Angel C. Y. Mak ◽  
Marquitta J. White ◽  
Walter L. Eckalbar ◽  
Zachary A. Szpiech ◽  
Sam S. Oh ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Drug Response ◽  
Whole Genome ◽  
Racially Diverse ◽  
Children With Asthma ◽  
Diverse Children

EP828 Whole genome sequencing and clinical drug response data of 142 ovarian cancer samples

2019 ◽  
Author(s):  
CJ de Witte ◽  
J Kutzera ◽  
J Espejo Valle-Inclan ◽  
MJ van Roosmalen ◽  
S Boymans ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Drug Response ◽  
Whole Genome ◽  
Response Data ◽  
Clinical Drug

scholarly journals Integrating DNA sequencing and transcriptomic data for association analyses of low-frequency variants and lipid traits

2020 ◽  
Vol 29 (3) ◽  
pp. 515-526 ◽  
Author(s):  
Tianzhong Yang ◽  
Chong Wu ◽  
Peng Wei ◽  
Wei Pan
Keyword(s):  
Gene Expression ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Association Studies ◽  
Low Frequency ◽  
Genome Wide Association Studies ◽  
Whole Genome ◽  
Common Variants ◽  
Transcriptomic Data ◽  
Genome Wide

Abstract Transcriptome-wide association studies (TWAS) integrate genome-wide association studies (GWAS) and transcriptomic data to showcase their improved statistical power of identifying gene–trait associations while, importantly, offering further biological insights. TWAS have thus far focused on common variants as available from GWAS. Compared with common variants, the findings for or even applications to low-frequency variants are limited and their underlying role in regulating gene expression is less clear. To fill this gap, we extend TWAS to integrating whole genome sequencing data with transcriptomic data for low-frequency variants. Using the data from the Framingham Heart Study, we demonstrate that low-frequency variants play an important and universal role in predicting gene expression, which is not completely due to linkage disequilibrium with the nearby common variants. By including low-frequency variants, in addition to common variants, we increase the predictivity of gene expression for 79% of the examined genes. Incorporating this piece of functional genomic information, we perform association testing for five lipid traits in two UK10K whole genome sequencing cohorts, hypothesizing that cis-expression quantitative trait loci, including low-frequency variants, are more likely to be trait-associated. We discover that two genes, LDLR and TTC22, are genome-wide significantly associated with low-density lipoprotein cholesterol based on 3203 subjects and that the association signals are largely independent of common variants. We further demonstrate that a joint analysis of both common and low-frequency variants identifies association signals that would be missed by testing on either common variants or low-frequency variants alone.

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