scholarly journals Revealing the causative variant in Mendelian patient genomes without revealing patient genomes

2017 ◽  
Author(s):  
Karthik A. Jagadeesh ◽  
David J. Wu ◽  
Johannes A. Birgmeier ◽  
Dan Boneh ◽  
Gill Bejerano
Keyword(s):  
Health Information ◽  
Genome Sequencing ◽  
Causal Variant ◽  
Multiparty Computation ◽  
Genomic Information ◽  
Causative Variant ◽  
Causal Variants ◽  
Small Patient ◽  
Yao’S Protocol ◽  
Proof Of Principle

AbstractGiven the rapidly growing utility of critical health information revealed in the human genome, secure genomic computation is essential to moving forward, especially as genome sequencing becomes commonplace. We devise and implement proof-of-principle computational operations for precisely identifying causal variants in Mendelian patients using secure multiparty computation methods based on Yao’s protocol. We show multiple real scenarios (small patient cohorts, trio analysis, two hospital collaboration) where the causal variant is discovered jointly, while keeping up to 99.7% of all participants’ most sensitive genomic information private. All similar operations performed today to diagnose such cases are done openly, keeping 0% of participants’ genomic information private. Our work will help usher in an era where genomes can be both utilized and truly protected.

scholarly journals Identification and prioritisation of causal variants in human genetic disorders from exome or whole genome sequencing data

2017 ◽  
Author(s):  
Nagarajan Paramasivam ◽  
Martin Granzow ◽  
Christina Evers ◽  
Katrin Hinderhofer ◽  
Stefan Wiemann ◽  
...  
Keyword(s):  
Genome Sequencing ◽  
Genetic Disorders ◽  
Causal Variant ◽  
Whole Genome Sequencing Data ◽  
Sequencing Data ◽  
Causal Variants ◽  
Small Set ◽  
Downstream Analysis ◽  
Human Genetic Disorders ◽  
Variant Identification

AbstractWith genome sequencing entering the clinics as diagnostic tool to study genetic disorders, there is an increasing need for bioinformatics solutions that enable precise causal variant identification in a timely manner.BackgroundWorkflows for the identification of candidate disease-causing variants perform usually the following tasks: i) identification of variants; ii) filtering of variants to remove polymorphisms and technical artifacts; and iii) prioritization of the remaining variants to provide a small set of candidates for further analysis.MethodsHere, we present a pipeline designed to identify variants and prioritize the variants and genes from trio sequencing or pedigree-based sequencing data into different tiers.ResultsWe show how this pipeline was applied in a study of patients with neurodevelopmental disorders of unknown cause, where it helped to identify the causal variants in more than 35% of the cases.ConclusionsClassification and prioritization of variants into different tiers helps to select a small set of variants for downstream analysis.

scholarly journals The Genetics of Circulating Resistin Level, A Biomarker for Cardiovascular Diseases, Is Informed by Mendelian Randomization and the Unique Characteristics of African Genomes

2020 ◽  
Author(s):  
Karlijn A.C. Meeks ◽  
Ayo P. Doumatey ◽  
Amy R. Bentley ◽  
Mateus H. Gouveia ◽  
Guanjie Chen ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Fine Mapping ◽  
Mendelian Randomization ◽  
African Ancestry ◽  
Resistance Index ◽  
Causal Variant ◽  
Transcriptomic Data ◽  
Causal Variants

Background - Resistin, a protein linked with inflammation and cardiometabolic diseases, is one of few proteins for which GWAS consistently report variants within and near the coding gene ( RETN ). Here, we took advantage of the reduced linkage disequilibrium in African populations to infer genetic causality for circulating resistin levels by performing GWAS, whole-exome analysis, fine-mapping, Mendelian randomization and transcriptomic data analyses. Methods - GWAS and fine-mapping analyses for resistin were performed in 5621 African ancestry individuals, including 3754 continental Africans (AF) and 1867 African Americans (AA). Causal variants identified were subsequently used as an instrumental variable in Mendelian randomization analyses for homeostatic modelling (HOMA) derived insulin resistance index, BMI and type 2 diabetes. Results - The lead variant (rs3219175, in the promoter region of RETN ) for the single locus detected was the same for AF ( P -value 5.0×10 -111 ) and for AA (9.5×10 -38 ), respectively explaining 12.1% and 8.5% of variance in circulating resistin. Fine-mapping analyses and functional annotation revealed this variant as likely causal affecting circulating resistin levels as a cis -eQTL increasing RETN expression. Additional variants regulating resistin levels were upstream of RETN with genes PCP2 , STXBP2 and XAB2 showing the strongest association using integrative analysis of GWAS with transcriptomic data. Mendelian randomization analyses did not provide evidence for resistin increasing insulin resistance, BMI or type 2 diabetes risk in African-ancestry populations. Conclusions - Taking advantage of the fine-mapping resolution power of African genomes, we identified a single variant (rs3219175) as the likely causal variant responsible for most of the variability in circulating resistin levels. In contrast to findings in some other ancestry populations, we showed that resistin does not seem to increase insulin resistance and related cardiometabolic traits in African-ancestry populations.

scholarly journals Statistical Colocalization of Genetic Risk Variants for Related Autoimmune Diseases in the Context of Common Controls

2015 ◽  
Author(s):  
Mary D Fortune ◽  
Hui Guo ◽  
Oliver Burren ◽  
Ellen Schofield ◽  
Neil M Walker ◽  
...  
Keyword(s):  
Autoimmune Diseases ◽  
Genetic Risk ◽  
Control Design ◽  
Causal Variant ◽  
The Other ◽  
Risk Variants ◽  
Immune Attack ◽  
Disease Associations ◽  
Causal Variants

Identifying whether potential causal variants for related diseases are shared can increase understanding of the shared etiology between diseases. Colocalization methods are designed to disentangle shared and distinct causal variants in regions where two diseases show association, but existing methods are limited by assuming independent datasets. We extended existing methods to allow for the shared control design common in GWAS and applied them to four autoimmune diseases: type 1 diabetes (T1D); rheumatoid arthritis; celiac disease (CEL) and multiple sclerosis (MS). Ninety regions associated with at least one disease. In 22 regions (24%), we identify association to precisely one of our four diseases and can find no published association of any other disease to the same region; some of these may reflect effects mediated by the target of immune attack. Thirty-three regions (37%) were associated with two or more, but in 14 of these there was evidence that causal variants differed between diseases. By leveraging information across datasets, we identified novel disease associations to 12 regions previously associated with one or more of the other three autoimmune disorders. For instance, we link the CEL-associatedFASLGregion to T1D and identify a single SNP, rs78037977, as a likely causal variant. We also highlight several particularly complex association patterns, including theCD28-CTLA4-ICOSregion, in which it appears that three distinct causal variants associate with three diseases in three different patterns. Our results underscore the complexity in genetic variation underlying related but distinct autoimmune diseases and help to approach its dissection.

scholarly journals MutantHuntWGS: A Pipeline for Identifying Saccharomyces cerevisiae Mutations

2020 ◽  
Vol 10 (9) ◽  
pp. 3009-3014 ◽  
Author(s):  
Mitchell A Ellison ◽  
Jennifer L Walker ◽  
Patrick J Ropp ◽  
Jacob D Durrant ◽  
Karen M Arndt
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Sequence Alignments ◽  
Causal Variants ◽  
User Friendly ◽  
Analyze Data

Abstract MutantHuntWGS is a user-friendly pipeline for analyzing Saccharomyces cerevisiae whole-genome sequencing data. It uses available open-source programs to: (1) perform sequence alignments for paired and single-end reads, (2) call variants, and (3) predict variant effect and severity. MutantHuntWGS outputs a shortlist of variants while also enabling access to all intermediate files. To demonstrate its utility, we use MutantHuntWGS to assess multiple published datasets; in all cases, it detects the same causal variants reported in the literature. To encourage broad adoption and promote reproducibility, we distribute a containerized version of the MutantHuntWGS pipeline that allows users to install and analyze data with only two commands. The MutantHuntWGS software and documentation can be downloaded free of charge from https://github.com/mae92/MutantHuntWGS.

scholarly journals “…This Has to Do With My Identity. And I Don't Want to Make it Totally Transparent.” Identity Relevance in the Attitudes of Affected People and Laypersons to the Handling of High-Throughput Genomic Data

2020 ◽  
Vol 5 ◽  
Author(s):  
Alexander Urban
Keyword(s):  
Genetic Testing ◽  
Identity Construction ◽  
Genome Sequencing ◽  
Qualitative Content Analysis ◽  
Genomic Data ◽  
Genomic Information ◽  
Genetic Tests ◽  
The Public ◽  
Theoretical Approaches ◽  
Scientific Context

With the establishment of genome sequencing, the influence of genomic information on self-understanding and identity construction has become increasingly important. New sequencing methods far exceed previous genetic tests in terms of scope and quantity. Despite theoretical approaches, however, there are few empirical findings on the identity-relevant influence of genomic information. The present study examines genomic information's identity-relevant influences and considers whether developments in the field of genome sequencing may generate problems that are not yet addressed by existing identity concepts based on traditional genetic tests. The study is based on 10 partially standardized interviews with personally affected persons and four focus groups with medical laypersons as representatives of the public, which were evaluated on the basis of qualitative content analysis. As a result, this paper presents five thematic areas with identity-relevant references within subjective attitudes toward the handling of genomic information, and also derives two basic identity concepts. The results indicate that the lay discourse is still strongly based on older debates about genetic testing and that the view on the complexity of genomic information established in the scientific context has thus far no influence on the perspectives either of those affected or laypersons.

Identification and Prioritization of Causal Variants of Human Genetic Disorders from Exome or Whole Genome Sequencing Data

2018 ◽  
Vol 2 (2) ◽  
pp. 1-1
Author(s):  
Nagarajan Paramasivam ◽  
◽  
Martin Granzow ◽  
Christina Evers ◽  
Katrin Hinderhofer ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Genetic Disorders ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Causal Variants ◽  
Human Genetic Disorders

A case of the utilization of genomic information in the management of metastatic colorectal cancer.

2013 ◽  
Vol 31 (4_suppl) ◽  
pp. 444-444
Author(s):  
Renata D'Alpino Peixoto ◽  
Yvonne Li ◽  
Erin Pleasance ◽  
Stephen Yip ◽  
Yongjun Zhao ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Metastatic Colorectal Cancer ◽  
Genome Sequencing ◽  
Metastatic Disease ◽  
Copy Number ◽  
Braf V600e ◽  
Gene Copy ◽  
Genomic Information ◽  
Egfr Inhibition ◽  
Rare Tumours

444 Background: Anectodal success using genomic information to personalize and guide cancer therapy in rare tumours has been reported. This is a case report of the use of genomic information in the management of metastatic colorectal cancer. Methods: A 31 year old female presented with metastatic disease from the colon to the liver and retroperitoneal lymph nodes. She was treated with aspirin and 4 cycles of 5FU/Irinotecan/Bevacizumab before blood and liver biopsies were taken. Sections from the primary tissue embedded in paraffin were compared to metastatic disease in the liver and blood. Two platforms were used: a targeted deep sequencing of 46 genes via a cancer specific amplicon assay and whole genome sequencing and RNA sequencing followed by bioinformatics approaches were employed to identify genes with somatic variants, copy number variations, losses of heterozygosity, structural variation, and expression changes. Results: Genome sequencing followed by bioinformatics analysis detected ~100 somatic mutations, ~100 amplified genes with increased expression, and ~90 down-regulated genes with copy number loss in the metastasis. Other interesting observations included increased allelic frequencies in BRAF V600E, and SMAD4 R361C as well as high gene copy amplifications in VEGFA and MAGI from the primary to the metastasis, and lack of somatic mutation in KRAS. Conclusions: The upregulation of VEGF pathways from the primary compared to the metastasis suggests a significant shift in tumour biology likely as a result of the bevacizumab and COX-2 inhibition from aspirin; this may have implications when anti-VEGF therapy is withdrawn. The BRAF mutation and wild type KRAS status may suggest that combination of a BRAF inhibitor with EGFR inhibition is warranted. This information demonstrated the benefit of therapy on a genomic level and aided in determining possible future targets and modifications to conventional therapy.

scholarly journals A more accurate method for colocalisation analysis allowing for multiple causal variants

2021 ◽  
Author(s):  
Chris Wallace
Keyword(s):  
Association Studies ◽  
Accurate Method ◽  
Causal Variant ◽  
Genomic Region ◽  
Genome Wide Association Studies ◽  
Novel Approach ◽  
Genome Wide ◽  
Close Proximity ◽  
Regression Framework ◽  
Causal Variants

AbstractIn genome-wide association studies (GWAS) it is now common to search for, and find, multiple causal variants located in close proximity. It has also become standard to ask whether different traits share the same causal variants, but one of the popular methods to answer this question, coloc, makes the simplifying assumption that only a single causal variant exists for any given trait in any genomic region. Here, we examine the potential of the recently proposed Sum of Single Effects (SuSiE) regression framework, which can be used for fine-mapping genetic signals, for use with coloc. SuSiE is a novel approach that allows evidence for association at multiple causal variants to be evaluated simultaneously, whilst separating the statistical support for each variant conditional on the causal signal being considered. We show this results in more accurate coloc inference than other proposals to adapt coloc for multiple causal variants based on conditioning or masking. We therefore recommend that coloc be used in combination with SuSiE to optimise accuracy of colocalisation analyses when multiple causal variants exist.

Detecting Causal Variants in Mendelian Disorders Using Whole-Genome Sequencing

2021 ◽  
pp. 1-25
Author(s):  
Abdul Rezzak Hamzeh ◽  
T. Daniel Andrews ◽  
Matt A. Field
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Whole Genome ◽  
Mendelian Disorders ◽  
Causal Variants
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