scholarly journals Detecting multiple causal rare variants in exome sequence data

2011 ◽  
Vol 35 (S1) ◽  
pp. S18-S21 ◽  
Author(s):  
Kenny Q. Ye ◽  
Corinne D. Engelman
Keyword(s):  
Rare Variants ◽  
Sequence Data ◽  
Exome Sequence Data ◽  
Exome Sequence

scholarly journals Analysis of 50,000 exome-sequenced UK Biobank subjects fails to identify genes influencing probability of psychiatric referral

2020 ◽  
Author(s):  
David Curtis
Keyword(s):  
Multiple Testing ◽  
Rare Variants ◽  
Sequence Data ◽  
Statistical Significance ◽  
Major Effect ◽  
Self Report ◽  
Uk Biobank ◽  
Functional Variants ◽  
Exome Sequence Data ◽  
Exome Sequence

Background Depression is moderately heritable but there is no common genetic variant which has a major effect on susceptibility. It is possible that some very rare variants could have substantial effect sizes and these could be identified from exome sequence data. Methods Data from 50,000 exome-sequenced UK Biobank participants was analysed. Subjects were treated as cases if they had reported having seen a psychiatrist for "nerves, anxiety, tension or depression". Gene-wise weighted burden analysis was performed to see if there were any genes or sets of genes for which there was an excess of rare, functional variants in cases. Results There were 5,872 cases and 43,862 controls. There were 22,028 informative genes but none produced a statistically significant result after correction for multiple testing. Of the 25 genes individually significant at p<0.001 none appeared to be a biologically plausible candidate. No set of genes achieved statistical significance after correction for multiple testing and those with the lowest p values again did not appear to be biologically plausible candidates. Limitations The phenotype is based on self-report and the cases are likely to somewhat heterogeneous. The number of cases is on the low side for a study of exome sequence data. Conclusions The results conform exactly with the expectation under the null hypothesis. It seems unlikely that depression genetics research will produce findings that might have a substantial clinical impact until far larger samples become available.

scholarly journals Variants in ACE2 and TMPRSS2 genes are not major determinants of COVID-19 severity in UK Biobank subjects

2020 ◽  
Author(s):  
David Curtis
Keyword(s):  
Rare Variants ◽  
Sequence Data ◽  
Severe Disease ◽  
Major Effect ◽  
Uk Biobank ◽  
Exome Sequence Data ◽  
Dna Sequence Variants ◽  
The Uk ◽  
And Function ◽  
Exome Sequence

AbstractIt is plausible that variants in the ACE2 and TMPRSS2 genes might contribute to variation in COVID-19 severity and that these could explain why some people become very unwell whereas most do not. Exome sequence data was obtained for 49,953 UK Biobank subjects of whom 74 had tested positive for SARS-CoV-2 and could be presumed to have severe disease. A weighted burden analysis was carried out using SCOREASSOC to determine whether there were differences between these cases and the other sequenced subjects in the overall burden of rare, damaging variants in ACE2 or TMPRSS2. There were no statistically significant differences in weighted burden scores between cases and controls for either gene. There were no individual DNA sequence variants with a markedly different frequency between cases and controls. Whether there are small effects on severity, or whether there might be rare variants with major effect sizes, would require studies in much larger samples. Genetic variants affecting the structure and function of the ACE2 and TMPRSS2 proteins are not a major determinant of whether infection with SARS-CoV-2 results in severe symptoms. This research has been conducted using the UK Biobank Resource.

scholarly journals Variants in ACE2 and TMPRSS2 Genes Are Not Major Determinants of COVID-19 Severity in UK Biobank Subjects

2021 ◽  
pp. 1-3
Author(s):  
David Curtis
Keyword(s):  
Rare Variants ◽  
Sequence Data ◽  
Severe Disease ◽  
Major Effect ◽  
Uk Biobank ◽  
Exome Sequence Data ◽  
Dna Sequence Variants ◽  
The Uk ◽  
And Function ◽  
Exome Sequence

It is plausible that variants in the ACE2 and TMPRSS2 genes might contribute to variation in COVID-19 severity and that these could explain why some people become very unwell whereas most do not. Exome sequence data was obtained for 49,953 UK Biobank subjects, of whom 82 had tested positive for SARS-CoV-2 and could be presumed to have severe disease. A weighted burden analysis was carried out using SCOREASSOC to determine whether there were differences between these cases and the other sequenced subjects in the overall burden of rare, damaging variants in ACE2 or TMPRSS2. There were no statistically significant differences in weighted burden scores between cases and controls for either gene. There were no individual DNA sequence variants with a markedly different frequency between cases and controls. Whether there are small effects on severity, or whether there might be rare variants with major effect sizes, would require studies in much larger samples. Genetic variants affecting the structure and function of the ACE2 and TMPRSS2 proteins are not the main explanation for why some people develop severe symptoms in response to infection with SARS-CoV-2. This research was conducted using the UK Biobank Resource.

scholarly journals Rare-Variant Extensions of the Transmission Disequilibrium Test: Application to Autism Exome Sequence Data

2014 ◽  
Vol 94 (1) ◽  
pp. 33-46 ◽  
Author(s):  
Zongxiao He ◽  
Brian J. O’Roak ◽  
Joshua D. Smith ◽  
Gao Wang ◽  
Stanley Hooker ◽  
...  
Keyword(s):  
Rare Variant ◽  
Transmission Disequilibrium Test ◽  
Sequence Data ◽  
Transmission Disequilibrium ◽  
Exome Sequence Data ◽  
Test Application ◽  
Exome Sequence

scholarly journals Analysis of exome-sequenced UK Biobank subjects implicates genes affecting risk of hyperlipidaemia

2020 ◽  
Author(s):  
David Curtis
Keyword(s):  
Rare Variants ◽  
Sequence Data ◽  
Lipid Lowering ◽  
P Value ◽  
Data Sets ◽  
Uk Biobank ◽  
Functional Studies ◽  
Exome Sequence Data ◽  
Rare Genetic Variants ◽  
The Uk

Rare genetic variants in LDLR, APOB and PCSK9 are known causes of familial hypercholesterolaemia and it is expected that rare variants in other genes will also have effects on hyperlipidaemia risk although such genes remain to be identified. The UK Biobank consists of a sample of 500,000 volunteers and exome sequence data is available for 50,000 of them. 11,490 of these were classified as hyperlipidaemia cases on the basis of having a relevant diagnosis recorded and/or taking lipid-lowering medication while the remaining 38,463 were treated as controls. Variants in each gene were assigned weights according to rarity and predicted impact and overall weighted burden scores were compared between cases and controls, including population principal components as covariates. One biologically plausible gene, HUWE1, produced statistically significant evidence for association after correction for testing 22,028 genes with a signed log10 p value (SLP) of -6.15, suggesting a protective effect of variants in this gene. Other genes with uncorrected p<0.001 are arguably also of interest, including LDLR (SLP=3.67), RBP2 (SLP=3.14), NPFFR1 (SLP=3.02) and ACOT9 (SLP=-3.19). Gene set analysis indicated that rare variants in genes involved in metabolism and energy can influence hyperlipidaemia risk. Overall, the results provide some leads which might be followed up with functional studies and which could be tested in additional data sets as these become available. This research has been conducted using the UK Biobank Resource.

Simple and Efficient Identification of Rare Recessive Pathologically Important Sequence Variants from Next Generation Exome Sequence Data

2013 ◽  
Vol 34 (7) ◽  
pp. 945-952 ◽  
Author(s):  
Ian M. Carr ◽  
Joanne Morgan ◽  
Christopher Watson ◽  
Svitlana Melnik ◽  
Christine P. Diggle ◽  
...  
Keyword(s):  
Sequence Data ◽  
Sequence Variants ◽  
Next Generation ◽  
Exome Sequence Data ◽  
Exome Sequence

scholarly journals Identity-by-descent filtering as a tool for the identification of disease alleles in exome sequence data from distant relatives

2011 ◽  
Vol 5 (S9) ◽  
Author(s):  
Nirmala Akula ◽  
Sevilla Detera-Wadleigh ◽  
Yin Yao Shugart ◽  
Michael Nalls ◽  
Jo Steele ◽  
...  
Keyword(s):  
Sequence Data ◽  
Identity By Descent ◽  
Exome Sequence Data ◽  
Exome Sequence

scholarly journals The ExAC Browser: Displaying reference data information from over 60,000 exomes

2016 ◽  
Author(s):  
Konrad J. Karczewski ◽  
Ben Weisburd ◽  
Brett Thomas ◽  
Douglas M. Ruderfer ◽  
David Kavanagh ◽  
...  
Keyword(s):  
Reference Data ◽  
Sequence Data ◽  
Large Population ◽  
Clinical Applications ◽  
Data Sets ◽  
Variant Interpretation ◽  
Annotation Data ◽  
Exome Sequence Data ◽  
Exome Aggregation Consortium ◽  
Exome Sequence

AbstractWorldwide, hundreds of thousands of humans have had their genomes or exomes sequenced, and access to the resulting data sets can provide valuable information for variant interpretation and understanding gene function. Here, we present a lightweight, flexible browser framework to display large population datasets of genetic variation. We demonstrate its use for exome sequence data from 60,706 individuals in the Exome Aggregation Consortium (ExAC). The ExAC browser provides gene- and transcript-centric displays of variation, a critical view for clinical applications. Additionally, we provide a variant display, which includes population frequency and functional annotation data as well as short read support for the called variant. This browser is open-source, freely available, and has already been used extensively by clinical laboratories worldwide.

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