AVIA v2.0: annotation, visualization and impact analysis of genomic variants and genes

Variant Impact Predictor database (VIPdb), version 2: trends from three decades of genetic variant impact predictors

BACKGROUND

Variant interpretation is essential for identifying patients' disease-causing genetic variants amongst the millions detected in their genomes. Hundreds of Variant Impact Predictors (VIPs), also known as Variant Effect Predictors (VEPs), have been developed for this purpose, with a variety of methodologies and goals. To facilitate the exploration of available VIP options, we have created the Variant Impact Predictor database (VIPdb).

RESULTS

The Variant Impact Predictor database (VIPdb) version 2 presents a collection of VIPs developed over the past three decades, summarizing their characteristics, ClinGen calibrated scores, CAGI assessment results, publication details, access information, and citation patterns. We previously summarized 217 VIPs and their features in VIPdb in 2019. Building upon this foundation, we identified and categorized an additional 190 VIPs, resulting in a total of 407 VIPs in VIPdb version 2. The majority of the VIPs have the capacity to predict the impacts of single nucleotide variants and nonsynonymous variants. More VIPs tailored to predict the impacts of insertions and deletions have been developed since the 2010s. In contrast, relatively few VIPs are dedicated to the prediction of splicing, structural, synonymous, and regulatory variants. The increasing rate of citations to VIPs reflects the ongoing growth in their use, and the evolving trends in citations reveal development in the field and individual methods.

CONCLUSIONS

VIPdb version 2 summarizes 407 VIPs and their features, potentially facilitating VIP exploration for various variant interpretation applications. VIPdb is available at  https://genomeinterpretation.org/vipdb.

Variant Impact Predictor database (VIPdb), version 2: Trends from 25 years of genetic variant impact predictors

Background

Variant interpretation is essential for identifying patients' disease-causing genetic variants amongst the millions detected in their genomes. Hundreds of Variant Impact Predictors (VIPs), also known as Variant Effect Predictors (VEPs), have been developed for this purpose, with a variety of methodologies and goals. To facilitate the exploration of available VIP options, we have created the Variant Impact Predictor database (VIPdb).

Results

The Variant Impact Predictor database (VIPdb) version 2 presents a collection of VIPs developed over the past 25 years, summarizing their characteristics, ClinGen calibrated scores, CAGI assessment results, publication details, access information, and citation patterns. We previously summarized 217 VIPs and their features in VIPdb in 2019. Building upon this foundation, we identified and categorized an additional 186 VIPs, resulting in a total of 403 VIPs in VIPdb version 2. The majority of the VIPs have the capacity to predict the impacts of single nucleotide variants and nonsynonymous variants. More VIPs tailored to predict the impacts of insertions and deletions have been developed since the 2010s. In contrast, relatively few VIPs are dedicated to the prediction of splicing, structural, synonymous, and regulatory variants. The increasing rate of citations to VIPs reflects the ongoing growth in their use, and the evolving trends in citations reveal development in the field and individual methods.

Conclusions

VIPdb version 2 summarizes 403 VIPs and their features, potentially facilitating VIP exploration for various variant interpretation applications.

Availability

VIPdb version 2 is available at https://genomeinterpretation.org/vipdb.

The in-silico evaluation of important GLUT9 residue for uric acid transport based on renal hypouricemia type 2

Uric acid is the end product of purine metabolism. Uric acid transporters in the renal proximal tubule plays a key role in uric acid transport. Functional abnormalities in these transporters could lead to high or low levels of uric acid in the blood plasma, known as hyperuricemia and hypouricemia, respectively. GLUT9 has been reported as a key transporter for uric acid reuptake in renal proximal tubule. GLUT9 mutation is known as causal gene for renal hypouricemia due to defective uric acid uptake, with more severe cases resulting in urolithiasis and exercise induced acute kidney injury (EIAKI). However, the effect of mutation is not fully investigated and hard to predict the change of binding affinity. We comprehensively described the effect of GLUT9 mutation for uric acid transport using molecular dynamics and investigated the specific site for uric acid binding differences. R171C and R380W showed the significant disruption of the structure not affecting transport dynamics whereas L75R, G216R, N333S, and P412R showed the reduced affinity of the extracellular vestibular area towards urate. Interestingly, T125 M showed a significant increase in intracellular binding energy, associated with distorted geometries. We can use this classification to consider the effect mutations by comparing the transport profiles of mutants against those of chemical candidates for transport and providing new perspectives to urate lowering drug discovery using GLUT9.

AVIA 3.0: interactive portal for genomic variant and sample level analysis

SUMMARY

The Annotation, Visualization and Impact Analysis (AVIA) is a web application combining multiple features to annotate and visualize genomic variant data. Users can investigate functional significance of their genetic alterations across samples, genes and pathways. Version 3.0 of AVIA offers filtering options through interactive charts and by linking disease relevant data sources. Newly incorporated services include gene, variant and sample level reporting, literature and functional correlations among impacted genes, comparative analysis across samples and against data sources such as TCGA and ClinVar, and cohort building. Sample and data management is now feasible through the application, which allows greater flexibility with sharing, reannotating and organizing data. Most importantly, AVIA's utility stems from its convenience for allowing users to upload and explore results without any a priori knowledge or the need to install, update and maintain software or databases. Together, these enhancements strengthen AVIA as a comprehensive, user-driven variant analysis portal.

AVAILABILITYAND IMPLEMENTATION

AVIA is accessible online at https://avia-abcc.ncifcrf.gov.

Genome-wide association study of high-sensitivity C-reactive protein, D-dimer, and interleukin-6 levels in multiethnic HIV+ cohorts

OBJECTIVES

Elevated levels of interleukin-6 (IL-6), D-dimer, and C-reactive protein (hsCRP) are associated with increased incidence of comorbid disease and mortality among people living with HIV (PLWH). Prior studies suggest a genetic basis for these biomarker elevations in the general population. The study objectives are to identify the genetic basis for these biomarkers among PLWH.

METHODS

Baseline levels of hsCRP, D-dimer, and IL-6, and single nucleotide polymorphisms (SNPs) were determined for 7768 participants in three HIV treatment trials. Single variant analysis was performed for each biomarker on samples from each of three ethnic groups [African (AFR), Admixed American (AMR), European (EUR)] within each trial including covariates relevant to biomarker levels. For each ethnic group, the results were pooled across trials, then further pooled across ethnicities.

RESULTS

The transethnic analysis identified three, two, and one known loci associated with hsCRP, D-dimer, and IL-6 levels, respectively, and two novel loci, FGB and GCNT1, associated with D-dimer levels. Lead SNPs exhibited similar effects across ethnicities. Additionally, three novel, ethnic-specific loci were identified: CATSPERG associated with D-dimer in AFR and PROX1-AS1 and TRAPPC9 associated with IL-6 in AFR and AMR, respectively.

CONCLUSION

Eleven loci associated with three biomarker levels were identified in PLWH from the three studies including six loci known in the general population and five novel loci associated with D-dimer and IL-6 levels. These findings support the hypothesis that host genetics may partially contribute to chronic inflammation in PLWH and help to identify potential targets for intervention of serious non-AIDS complications.

A causal role for TRESK loss of function in migraine mechanisms

The two-pore potassium channel, TRESK has been implicated in nociception and pain disorders. We have for the first time investigated TRESK function in human nociceptive neurons using induced pluripotent stem cell-based models. Nociceptors from migraine patients with the F139WfsX2 mutation show loss of functional TRESK at the membrane, with a corresponding significant increase in neuronal excitability. Furthermore, using CRISPR-Cas9 engineering to correct the F139WfsX2 mutation, we show a reversal of the heightened neuronal excitability, linking the phenotype to the mutation. In contrast we find no change in excitability in induced pluripotent stem cell derived nociceptors with the C110R mutation and preserved TRESK current; thereby confirming that only the frameshift mutation is associated with loss of function and a migraine relevant cellular phenotype. We then demonstrate the importance of TRESK to pain states by showing that the TRESK activator, cloxyquin, can reduce the spontaneous firing of nociceptors in an in vitro human pain model. Using the chronic nitroglycerine rodent migraine model, we demonstrate that mice lacking TRESK develop exaggerated nitroglycerine-induced mechanical and thermal hyperalgesia, and furthermore, show that cloxyquin conversely is able to prevent sensitization. Collectively, our findings provide evidence for a role of TRESK in migraine pathogenesis and its suitability as a therapeutic target.

VIPdb, a genetic Variant Impact Predictor Database

Genome sequencing identifies vast number of genetic variants. Predicting these variants' molecular and clinical effects is one of the preeminent challenges in human genetics. Accurate prediction of the impact of genetic variants improves our understanding of how genetic information is conveyed to molecular and cellular functions, and is an essential step towards precision medicine. Over one hundred tools/resources have been developed specifically for this purpose. We summarize these tools as well as their characteristics, in the genetic Variant Impact Predictor Database (VIPdb). This database will help researchers and clinicians explore appropriate tools, and inform the development of improved methods. VIPdb can be browsed and downloaded at https://genomeinterpretation.org/vipdb.

Novel analytical methods to interpret large sequencing data from small sample sizes

Background

Targeted therapies have greatly improved cancer patient prognosis. For instance, chronic myeloid leukemia is now well treated with imatinib, a tyrosine kinase inhibitor. Around 80% of the patients reach complete remission. However, despite its great efficiency, some patients are resistant to the drug. This heterogeneity in the response might be associated with pharmacokinetic parameters, varying between individuals because of genetic variants. To assess this issue, next-generation sequencing of large panels of genes can be performed from patient samples. However, the common problem in pharmacogenetic studies is the availability of samples, often limited. In the end, large sequencing data are obtained from small sample sizes; therefore, classical statistical analyses cannot be applied to identify interesting targets. To overcome this concern, here, we described original and underused statistical methods to analyze large sequencing data from a restricted number of samples.

Results

To evaluate the relevance of our method, 48 genes involved in pharmacokinetics were sequenced by next-generation sequencing from 24 chronic myeloid leukemia patients, either sensitive or resistant to imatinib treatment. Using a graphical representation, from 708 identified polymorphisms, a reduced list of 115 candidates was obtained. Then, by analyzing each gene and the distribution of variant alleles, several candidates were highlighted such as UGT1A9, PTPN22, and ERCC5. These genes were already associated with the transport, the metabolism, and even the sensitivity to imatinib in previous studies.

Conclusions

These relevant tests are great alternatives to inferential statistics not applicable to next-generation sequencing experiments performed on small sample sizes. These approaches permit to reduce the number of targets and find good candidates for further treatment sensitivity studies.

Electronic supplementary material

The online version of this article (10.1186/s40246-019-0235-1) contains supplementary material, which is available to authorized users.

Circulating tumor cells capture disease evolution in advanced prostate cancer

Background

Genetic analysis of advanced cancer is limited by availability of representative tissue. Biopsies of prostate cancer metastasized to bone are invasive with low quantity of tumor tissue. The prostate cancer genome is dynamic, however, with temporal heterogeneity requiring repeated evaluation as the disease evolves. Circulating tumor cells (CTCs) offer an alternative, “liquid biopsy”, though single CTC sequencing efforts are laborious with high failure rates.

Methods

We performed exome sequencing of matched treatment-naïve tumor tissue, castrate resistant tumor tissue, and pooled CTC samples, and compared mutations identified in each.

Results

Thirty-seven percent of CTC mutations were private to CTCs, one mutation was shared with treatment-naïve disease alone, and 62% of mutations were shared with castrate-resistant disease, either alone or with treatment-naïve disease. An acquired nonsense mutation in the Retinoblastoma gene, which is associated with progression to small cell cancer, was identified in castrate resistant and CTC samples, but not treatment-naïve disease. This timecourse correlated with the tumor acquiring neuroendocrine features and a change to neuroendocrine-specific therapy.

Conclusions

These data support the use of pooled CTCs to facilitate the genetic analysis of late stage prostate cancer.

Electronic supplementary material

The online version of this article (doi:10.1186/s12967-017-1138-3) contains supplementary material, which is available to authorized users.

Molecular analysis of urothelial cancer cell lines for modeling tumor biology and drug response

The utility of tumor-derived cell lines is dependent on their ability to recapitulate underlying genomic aberrations and primary tumor biology. Here, we sequenced the exomes of 25 bladder cancer (BCa) cell lines and compared mutations, copy number alterations (CNAs), gene expression and drug response to BCa patient profiles in The Cancer Genome Atlas (TCGA). We observed a mutation pattern associated with altered CpGs and APOBEC-family cytosine deaminases similar to mutation signatures derived from somatic alterations in muscle-invasive (MI) primary tumors, highlighting a major mechanism(s) contributing to cancer-associated alterations in the BCa cell line exomes. Non-silent sequence alterations were confirmed in 76 cancer-associated genes, including mutations that likely activate oncogenes TERT and PIK3CA, and alter chromatin-associated proteins (MLL3, ARID1A, CHD6 and KDM6A) and established BCa genes (TP53, RB1, CDKN2A and TSC1). We identified alterations in signaling pathways and proteins with related functions, including the PI3K/mTOR pathway, altered in 60% of lines; BRCA DNA repair, 44% and SYNE1–SYNE2, 60%. Homozygous deletions of chromosome 9p21 are known to target the cell cycle regulators CDKN2A and CDKN2B. This loci was commonly lost in BCa cell lines and we show the deletions extended to the polyamine enzyme methylthioadenosine (MTA) phosphorylase (MTAP) in 36% of lines, transcription factor DMRTA1 (27%) and antiviral interferon epsilon (IFNE, 19%). Overall, the BCa cell line genomic aberrations were concordant with those found in BCa patient tumors. We used gene expression and copy number data to infer pathway activities for cell lines, then used the inferred pathway activities to build a predictive model of cisplatin response. When applied to platinum-treated patients gathered from TCGA, the model predicted treatment-specific response. Together, these data and analysis represent a valuable community resource to model basic tumor biology and to study the pharmacogenomics of BCa.

Genomic variant annotation and prioritization with ANNOVAR and wANNOVAR

Recent developments in sequencing techniques have enabled rapid and high-throughput generation of sequence data, democratizing the ability to compile information on large amounts of genetic variations in individual laboratories. However, there is a growing gap between the generation of raw sequencing data and the extraction of meaningful biological information. Here, we describe a protocol to use the ANNOVAR (ANNOtate VARiation) software to facilitate fast and easy variant annotations, including gene-based, region-based and filter-based annotations on a variant call format (VCF) file generated from human genomes. We further describe a protocol for gene-based annotation of a newly sequenced nonhuman species. Finally, we describe how to use a user-friendly and easily accessible web server called wANNOVAR to prioritize candidate genes for a Mendelian disease. The variant annotation protocols take 5-30 min of computer time, depending on the size of the variant file, and 5-10 min of hands-on time. In summary, through the command-line tool and the web server, these protocols provide a convenient means to analyze genetic variants generated in humans and other species.