ORCID Profile
0000-0002-3085-5259
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Publisher: Springer Science and Business Media LLC
Date: 27-05-2020
DOI: 10.1038/S41586-020-2267-Z
Abstract: Naturally occurring human genetic variants that are predicted to inactivate protein-coding genes provide an in vivo model of human gene inactivation that complements knockout studies in cells and model organisms. Here we report three key findings regarding the assessment of candidate drug targets using human loss-of-function variants. First, even essential genes, in which loss-of-function variants are not tolerated, can be highly successful as targets of inhibitory drugs. Second, in most genes, loss-of-function variants are sufficiently rare that genotype-based ascertainment of homozygous or compound heterozygous ‘knockout’ humans will await s le sizes that are approximately 1,000 times those presently available, unless recruitment focuses on consanguineous in iduals. Third, automated variant annotation and filtering are powerful, but manual curation remains crucial for removing artefacts, and is a prerequisite for recall-by-genotype efforts. Our results provide a roadmap for human knockout studies and should guide the interpretation of loss-of-function variants in drug development.
Publisher: Springer Science and Business Media LLC
Date: 27-05-2020
DOI: 10.1038/S41586-020-2308-7
Abstract: Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large s le sizes 1 . Here we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases.
Publisher: American Medical Association (AMA)
Date: 26-02-2010
Publisher: Springer Science and Business Media LLC
Date: 27-05-2020
DOI: 10.1038/S41467-019-12438-5
Abstract: Multi-nucleotide variants (MNVs), defined as two or more nearby variants existing on the same haplotype in an in idual, are a clinically and biologically important class of genetic variation. However, existing tools typically do not accurately classify MNVs, and understanding of their mutational origins remains limited. Here, we systematically survey MNVs in 125,748 whole exomes and 15,708 whole genomes from the Genome Aggregation Database (gnomAD). We identify 1,792,248 MNVs across the genome with constituent variants falling within 2 bp distance of one another, including 18,756 variants with a novel combined effect on protein sequence. Finally, we estimate the relative impact of known mutational mechanisms - CpG deamination, replication error by polymerase zeta, and polymerase slippage at repeat junctions - on the generation of MNVs. Our results demonstrate the value of haplotype-aware variant annotation, and refine our understanding of genome-wide mutational mechanisms of MNVs.
Publisher: Public Library of Science (PLoS)
Date: 24-05-2018
Publisher: Springer Science and Business Media LLC
Date: 05-04-2023
DOI: 10.1186/S13073-023-01173-8
Abstract: We previously reported that impaired type I IFN activity, due to inborn errors of TLR3- and TLR7-dependent type I interferon (IFN) immunity or to autoantibodies against type I IFN, account for 15–20% of cases of life-threatening COVID-19 in unvaccinated patients. Therefore, the determinants of life-threatening COVID-19 remain to be identified in ~ 80% of cases. We report here a genome-wide rare variant burden association analysis in 3269 unvaccinated patients with life-threatening COVID-19, and 1373 unvaccinated SARS-CoV-2-infected in iduals without pneumonia. Among the 928 patients tested for autoantibodies against type I IFN, a quarter (234) were positive and were excluded. No gene reached genome-wide significance. Under a recessive model, the most significant gene with at-risk variants was TLR7 , with an OR of 27.68 (95%CI 1.5–528.7, P = 1.1 × 10 −4 ) for biochemically loss-of-function (bLOF) variants. We replicated the enrichment in rare predicted LOF (pLOF) variants at 13 influenza susceptibility loci involved in TLR3-dependent type I IFN immunity (OR = 3.70[95%CI 1.3–8.2], P = 2.1 × 10 −4 ). This enrichment was further strengthened by (1) adding the recently reported TYK2 and TLR7 COVID-19 loci, particularly under a recessive model (OR = 19.65[95%CI 2.1–2635.4], P = 3.4 × 10 −3 ), and (2) considering as pLOF branchpoint variants with potentially strong impacts on splicing among the 15 loci (OR = 4.40[9%CI 2.3–8.4], P = 7.7 × 10 −8 ). Finally, the patients with pLOF/bLOF variants at these 15 loci were significantly younger (mean age [SD] = 43.3 [20.3] years) than the other patients (56.0 [17.3] years P = 1.68 × 10 −5 ). Rare variants of TLR3- and TLR7-dependent type I IFN immunity genes can underlie life-threatening COVID-19, particularly with recessive inheritance, in patients under 60 years old.
Publisher: Springer Science and Business Media LLC
Date: 27-05-2020
DOI: 10.1038/S41586-020-2287-8
Abstract: Structural variants (SVs) rearrange large segments of DNA 1 and can have profound consequences in evolution and human disease 2,3 . As national biobanks, disease-association studies, and clinical genetic testing have grown increasingly reliant on genome sequencing, population references such as the Genome Aggregation Database (gnomAD) 4 have become integral in the interpretation of single-nucleotide variants (SNVs) 5 . However, there are no reference maps of SVs from high-coverage genome sequencing comparable to those for SNVs. Here we present a reference of sequence-resolved SVs constructed from 14,891 genomes across erse global populations (54% non-European) in gnomAD. We discovered a rich and complex landscape of 433,371 SVs, from which we estimate that SVs are responsible for 25–29% of all rare protein-truncating events per genome. We found strong correlations between natural selection against damaging SNVs and rare SVs that disrupt or duplicate protein-coding sequence, which suggests that genes that are highly intolerant to loss-of-function are also sensitive to increased dosage 6 . We also uncovered modest selection against noncoding SVs in cis -regulatory elements, although selection against protein-truncating SVs was stronger than all noncoding effects. Finally, we identified very large (over one megabase), rare SVs in 3.9% of s les, and estimate that 0.13% of in iduals may carry an SV that meets the existing criteria for clinically important incidental findings 7 . This SV resource is freely distributed via the gnomAD browser 8 and will have broad utility in population genetics, disease-association studies, and diagnostic screening.
Publisher: Springer Science and Business Media LLC
Date: 27-05-2020
DOI: 10.1038/S41591-020-0893-5
Abstract: Human genetic variants predicted to cause loss-of-function of protein-coding genes (pLoF variants) provide natural in vivo models of human gene inactivation and can be valuable indicators of gene function and the potential toxicity of therapeutic inhibitors targeting these genes 1,2 . Gain-of-kinase-function variants in LRRK2 are known to significantly increase the risk of Parkinson’s disease 3,4 , suggesting that inhibition of LRRK2 kinase activity is a promising therapeutic strategy. While preclinical studies in model organisms have raised some on-target toxicity concerns 5–8 , the biological consequences of LRRK2 inhibition have not been well characterized in humans. Here, we systematically analyze pLoF variants in LRRK2 observed across 141,456 in iduals sequenced in the Genome Aggregation Database (gnomAD) 9 , 49,960 exome-sequenced in iduals from the UK Biobank and over 4 million participants in the 23andMe genotyped dataset. After stringent variant curation, we identify 1,455 in iduals with high-confidence pLoF variants in LRRK2 . Experimental validation of three variants, combined with previous work 10 , confirmed reduced protein levels in 82.5% of our cohort. We show that heterozygous pLoF variants in LRRK2 reduce LRRK2 protein levels but that these are not strongly associated with any specific phenotype or disease state. Our results demonstrate the value of large-scale genomic databases and phenotyping of human loss-of-function carriers for target validation in drug discovery.
Publisher: Springer Science and Business Media LLC
Date: 11-09-2023
Publisher: Springer Science and Business Media LLC
Date: 22-01-2021
Publisher: Springer Science and Business Media LLC
Date: 17-08-2023
Publisher: Springer Science and Business Media LLC
Date: 03-02-2021
DOI: 10.1038/S41586-020-03177-5
Abstract: A Correction to this paper has been published: 0.1038/s41586-020-03177-5
Publisher: Springer Science and Business Media LLC
Date: 03-02-2021
DOI: 10.1038/S41586-020-03175-7
Abstract: A Correction to this paper has been published: 0.1038/s41586-020-03175-7
Publisher: Springer Science and Business Media LLC
Date: 03-02-2021
DOI: 10.1038/S41586-020-03176-6
Abstract: A Correction to this paper has been published: 0.1038/s41586-020-03176-6.
Publisher: Springer Science and Business Media LLC
Date: 03-02-2021
DOI: 10.1038/S41586-020-03174-8
Abstract: A Correction to this paper has been published: 0.1038/s41586-020-03174-8.
Publisher: Cold Spring Harbor Laboratory
Date: 25-09-2016
DOI: 10.1101/077180
Abstract: As part of a broader collaborative network of exome sequencing studies, we developed a jointly called data set of 5,685 Ashkenazi Jewish exomes. We make publicly available a resource of site and allele frequencies, which should serve as a reference for medical genetics in the Ashkenazim. We estimate that 30% of protein-coding alleles present in the Ashkenazi Jewish population at frequencies greater than 0.2% are significantly more frequent (mean 7.6-fold) than their maximum frequency observed in other reference populations. Arising via a well-described founder effect, this catalog of enriched alleles can contribute to differences in genetic risk and overall prevalence of diseases between populations. As validation we document 151 AJ enriched protein-altering alleles that overlap with “pathogenic” ClinVar alleles, including those that account for 10-100 fold differences in prevalence between AJ and non-AJ populations of some rare diseases including Gaucher disease ( GBA , p.Asn409Ser, 8-fold enrichment) Canavan disease ( ASPA , p.Glu285Ala, 12-fold enrichment) and Tay-Sachs disease ( HEXA , c.1421+1G C, 27-fold enrichment p.Tyr427IlefsTer5, 12-fold enrichment). We next sought to use this catalog, of well-established relevance to Mendelian disease, to explore Crohn’s disease, a common disease with an estimated two to four-fold excess prevalence in AJ. We specifically evaluate whether strong acting rare alleles, enriched by the same founder-effect, contribute excess genetic risk to Crohn’s disease in AJ, and find that ten rare genetic risk factors in NOD2 and LRRK2 are strongly enriched in AJ, including several novel contributing alleles, show evidence of association to CD. Independently, we find that genomewide common variant risk defined by GWAS shows a strong difference between AJ and non-AJ European control population s les (0.97 s.d. higher, p −16 ). Taken together, the results suggest coordinated selection in AJ population for higher CD risk alleles in general. The results and approach illustrate the value of exome sequencing data in case-control studies along with reference data sets like ExAC to pinpoint genetic variation that contributes to variable disease predisposition across populations.
Publisher: Springer Science and Business Media LLC
Date: 27-05-2020
DOI: 10.1038/S41467-019-10717-9
Abstract: Upstream open reading frames (uORFs) are tissue-specific cis -regulators of protein translation. Isolated reports have shown that variants that create or disrupt uORFs can cause disease. Here, in a systematic genome-wide study using 15,708 whole genome sequences, we show that variants that create new upstream start codons, and variants disrupting stop sites of existing uORFs, are under strong negative selection. This selection signal is significantly stronger for variants arising upstream of genes intolerant to loss-of-function variants. Furthermore, variants creating uORFs that overlap the coding sequence show signals of selection equivalent to coding missense variants. Finally, we identify specific genes where modification of uORFs likely represents an important disease mechanism, and report a novel uORF frameshift variant upstream of NF2 in neurofibromatosis. Our results highlight uORF-perturbing variants as an under-recognised functional class that contribute to penetrant human disease, and demonstrate the power of large-scale population sequencing data in studying non-coding variant classes.
Publisher: Springer Science and Business Media LLC
Date: 23-09-2021
Publisher: Springer Science and Business Media LLC
Date: 27-05-2020
DOI: 10.1038/S41586-020-2329-2
Abstract: The acceleration of DNA sequencing in s les from patients and population studies has resulted in extensive catalogues of human genetic variation, but the interpretation of rare genetic variants remains problematic. A notable ex le of this challenge is the existence of disruptive variants in dosage-sensitive disease genes, even in apparently healthy in iduals. Here, by manual curation of putative loss-of-function (pLoF) variants in haploinsufficient disease genes in the Genome Aggregation Database (gnomAD) 1 , we show that one explanation for this paradox involves alternative splicing of mRNA, which allows exons of a gene to be expressed at varying levels across different cell types. Currently, no existing annotation tool systematically incorporates information about exon expression into the interpretation of variants. We develop a transcript-level annotation metric known as the ‘proportion expressed across transcripts’, which quantifies isoform expression for variants. We calculate this metric using 11,706 tissue s les from the Genotype Tissue Expression (GTEx) project 2 and show that it can differentiate between weakly and highly evolutionarily conserved exons, a proxy for functional importance. We demonstrate that expression-based annotation selectively filters 22.8% of falsely annotated pLoF variants found in haploinsufficient disease genes in gnomAD, while removing less than 4% of high-confidence pathogenic variants in the same genes. Finally, we apply our expression filter to the analysis of de novo variants in patients with autism spectrum disorder and intellectual disability or developmental disorders to show that pLoF variants in weakly expressed regions have similar effect sizes to those of synonymous variants, whereas pLoF variants in highly expressed exons are most strongly enriched among cases. Our annotation is fast, flexible and generalizable, making it possible for any variant file to be annotated with any isoform expression dataset, and will be valuable for the genetic diagnosis of rare diseases, the analysis of rare variant burden in complex disorders, and the curation and prioritization of variants in recall-by-genotype studies.
No related grants have been discovered for Nyaradzo Mavis Mgodi.