scholarly journals Effect of Loss-of-Function Genetic Variants in PCSK9 on Glycemic Traits, Neurocognitive Impairment, and Hepatobiliary Function

2021 ◽  
Author(s):  
Jonas Ghouse ◽  
Gustav Ahlberg ◽  
Henning Bundgaard ◽  
Morten S. Olesen
Keyword(s):  
Adverse Effects ◽  
Positive Control ◽  
Carrier Status ◽  
Uk Biobank ◽  
Loss Of Function ◽  
Sequencing Data ◽  
Exome Sequencing Data ◽  
Aggregate Effects ◽  
Design And Methods ◽  
Control Association

<strong>OBJECTIVE:</strong> To evaluate the association between <i>PCSK9 </i>predicted loss-of-function variants (pLoF) and glycemic traits, hepatobiliary function and neurocognitive traits. <p><strong>RESEARCH DESIGN AND METHODS:</strong> We identified carriers of <i>PCSK9</i> pLoF in UK Biobank exome sequencing data. We assessed the aggregate effects of these variants on lipid/lipoprotein traits, which served as a positive control. Association of <i>PCSK9 </i>pLoF carrier status and glycemic traits, hepatobiliary function, neurocognitive traits was then evaluated as a measure for adverse effects. </p> <p><strong>RESULTS:</strong> We identified 374 individuals with 41 pLoF variants. As expected, we found that <i>PCSK9</i> pLoF carriers had significantly lower LDL-C (<i>P</i> = 7.4 × 10<sup>-55</sup>) and apoB levels (<i>P</i> = 7.6 × 10<sup>-50</sup>) compared with noncarriers. However, we found no significant associations between pLoF carrier-status and glycemic traits, hepatobiliary function and neurocognitive traits (<i>P</i> > 0.05).</p> <p><strong>CONCLUSIONS</strong>: Our results do not support adverse effects of <i>PCSK9 </i>pLoF on glycemic traits, hepatobiliary function or neurocognitive traits.</p>

scholarly journals Effect of Loss-of-Function Genetic Variants in PCSK9 on Glycemic Traits, Neurocognitive Impairment, and Hepatobiliary Function

2021 ◽  
Author(s):  
Jonas Ghouse ◽  
Gustav Ahlberg ◽  
Henning Bundgaard ◽  
Morten S. Olesen
Keyword(s):  
Adverse Effects ◽  
Positive Control ◽  
Carrier Status ◽  
Uk Biobank ◽  
Loss Of Function ◽  
Sequencing Data ◽  
Exome Sequencing Data ◽  
Aggregate Effects ◽  
Design And Methods ◽  
Control Association

<strong>OBJECTIVE:</strong> To evaluate the association between <i>PCSK9 </i>predicted loss-of-function variants (pLoF) and glycemic traits, hepatobiliary function and neurocognitive traits. <p><strong>RESEARCH DESIGN AND METHODS:</strong> We identified carriers of <i>PCSK9</i> pLoF in UK Biobank exome sequencing data. We assessed the aggregate effects of these variants on lipid/lipoprotein traits, which served as a positive control. Association of <i>PCSK9 </i>pLoF carrier status and glycemic traits, hepatobiliary function, neurocognitive traits was then evaluated as a measure for adverse effects. </p> <p><strong>RESULTS:</strong> We identified 374 individuals with 41 pLoF variants. As expected, we found that <i>PCSK9</i> pLoF carriers had significantly lower LDL-C (<i>P</i> = 7.4 × 10<sup>-55</sup>) and apoB levels (<i>P</i> = 7.6 × 10<sup>-50</sup>) compared with noncarriers. However, we found no significant associations between pLoF carrier-status and glycemic traits, hepatobiliary function and neurocognitive traits (<i>P</i> > 0.05).</p> <p><strong>CONCLUSIONS</strong>: Our results do not support adverse effects of <i>PCSK9 </i>pLoF on glycemic traits, hepatobiliary function or neurocognitive traits.</p>

scholarly journals Use of a gene-based case-control association approach in exome sequencing data to elucidate the molecular basis of a mendelian phenotype

The Lancet ◽  
2017 ◽  
Vol 389 ◽  
pp. S14
Author(s):  
Panagiotis I Sergouniotis ◽  
Anthony G Robson ◽  
Mohammed E El-Asrag ◽  
Manir Ali ◽  
Graham E Holder ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Molecular Basis ◽  
Case Control ◽  
Sequencing Data ◽  
Exome Sequencing Data ◽  
Control Association

Dnmt3a-mutated clonal hematopoiesis promotes osteoporosis

2021 ◽  
Vol 218 (12) ◽  
Author(s):  
Peter Geon Kim ◽  
Abhishek Niroula ◽  
Veronica Shkolnik ◽  
Marie McConkey ◽  
Amy E. Lin ◽  
...  
Keyword(s):  
Blood Cells ◽  
Somatic Mutations ◽  
Murine Models ◽  
Uk Biobank ◽  
Sequencing Data ◽  
Mineral Density ◽  
Clonal Hematopoiesis ◽  
Exome Sequencing Data ◽  
Close Proximity ◽  
The Uk

Osteoporosis is caused by an imbalance of osteoclasts and osteoblasts, occurring in close proximity to hematopoietic cells in the bone marrow. Recurrent somatic mutations that lead to an expanded population of mutant blood cells is termed clonal hematopoiesis of indeterminate potential (CHIP). Analyzing exome sequencing data from the UK Biobank, we found CHIP to be associated with increased incident osteoporosis diagnoses and decreased bone mineral density. In murine models, hematopoietic-specific mutations in Dnmt3a, the most commonly mutated gene in CHIP, decreased bone mass via increased osteoclastogenesis. Dnmt3a−/− demethylation opened chromatin and altered activity of inflammatory transcription factors. Bone loss was driven by proinflammatory cytokines, including Irf3-NF-κB–mediated IL-20 expression from Dnmt3a mutant macrophages. Increased osteoclastogenesis due to the Dnmt3a mutations was ameliorated by alendronate or IL-20 neutralization. These results demonstrate a novel source of osteoporosis-inducing inflammation.

scholarly journals Surveying the contribution of rare variants to the genetic architecture of human disease through exome sequencing of 177,882 UK Biobank participants

2020 ◽  
Author(s):  
Quanli Wang ◽  
Ryan S. Dhindsa ◽  
Keren Carss ◽  
Andrew R Harper ◽  
Abhishek Nag ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Drug Targets ◽  
Rare Variants ◽  
Population Based ◽  
Uk Biobank ◽  
Loss Of Function ◽  
Sequencing Data ◽  
Phenotypic Data ◽  
Protein Coding ◽  
The Uk

The UK Biobank (UKB) represents an unprecedented population-based study of 502,543 participants with detailed phenotypic data and linkage to medical records. While the release of genotyping array data for this cohort has bolstered genomic discovery for common variants, the contribution of rare variants to this broad phenotype collection remains relatively unknown. Here, we use exome sequencing data from 177,882 UKB participants to evaluate the association between rare protein-coding variants with 10,533 binary and 1,419 quantitative phenotypes. We performed both a variant-level phenome-wide association study (PheWAS) and a gene-level collapsing analysis-based PheWAS tailored to detecting the aggregate contribution of rare variants. The latter revealed 911 statistically significant gene-phenotype relationships, with a median odds ratio of 15.7 for binary traits. Among the binary trait associations identified using collapsing analysis, 83% were undetectable using single variant association tests, emphasizing the power of collapsing analysis to detect signal in the setting of high allelic heterogeneity. As a whole, these genotype-phenotype associations were significantly enriched for loss-of-function mediated traits and currently approved drug targets. Using these results, we summarise the contribution of rare variants to common diseases in the context of the UKB phenome and provide an example of how novel gene-phenotype associations can aid in therapeutic target prioritisation.

Rare coding variants in MYH6 are associated with atrial fibrillation: results from 45,596 exomes representing the general population

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
O.B Vad ◽  
C Paludan-Muller ◽  
G Ahlberg ◽  
L Andreasen ◽  
L Refsgaard ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Early Onset ◽  
Rare Variants ◽  
Structural Heart Disease ◽  
Uk Biobank ◽  
Structural Genes ◽  
Sequencing Data ◽  
Exome Sequencing Data ◽  
The Uk ◽  
Coding Variants

Abstract Background Atrial Fibrillation (AF) is the most common cardiac arrhythmia, and it is associated with serious complications; including an increased risk of stroke, heart failure, and death. It affects around 5% of the population above 65 years of age, and it is estimated that 2% of healthcare expenses are related to AF. The causes of AF are complex, and includes structural heart disease, hypertension, diabetes and genetic risk factors. To date 166 unique genetic loci have been identified to be associated with AF. While AF has traditionally been regarded as an electrical disease, structural genes, including the sarcomere gene, titin (TTN), has been associated with the disease. Recently, a large genome wide association study associated common variants in the gene MYH6 with AF. The gene encodes the protein alpha myosin heavy chain, and has previously been associated with sick-sinus syndrome and structural heart disease. Purpose We hypothesized that genetic variants in the sarcomere gene MYH6 were more prevalent in AF patients than non-AF patients supporting that this gene is important for the development of AF. Methods We analysed publicly available data from the UK Biobank, combining exome-sequencing data and health-related information on 45,596 participants. Using next-generation sequencing, we then examined the genetic variation in MYH6 in a cohort of 383 Danish, early-onset AF patients. The patients had onset of AF before age 40, had normal echocardiogram, and no other cardiovascular disease at onset of AF. Genetic variants were filtered by minor allele frequency (MAF) in the Genome Aggregation Database (GnomAD), and only rare variants with MAF&lt;1% were included. We then predicted the potential deleteriousness of the variants using combined annotation dependent depletion (CADD) score. Results We found rare coding variants in MYH6 to be significantly associated with AF in exome-sequencing data on 45,596 participants from the UK Biobank (p=0.038). In our cohort of 383 Danish, early-onset AF patients with no other cardiovascular disease, we identified 12 rare, missense variants in MYH6. Of these variants, three were novel, and 11 had CADD scores &gt;20, suggesting them to be in the top 1% of likely deleterious variants. Conclusion We identified rare genetic variants in MYH6 to be significantly associated with AF in a large population-based cohort. We also identified 12 rare coding variants in a highly selected cohort of early-onset AF patients. Most of these variants were predicted to be deleterious. Our results indicate that rare variants in MYH6 may increase susceptibility to AF, thus elaborating on the understanding of the pathophysiological mechanisms of AF, and the role of structural genes in the development of AF. Funding Acknowledgement Type of funding source: Foundation. Main funding source(s): Novo Nordisk Foundation Pre-Graduate Scholarships

How Does the “Cookie-Bite” Audiogram Shape Perform in Discriminating Genetic Hearing Loss in Adults?

2021 ◽  
pp. 019459982110151
Author(s):  
Shadi Ahmadmehrabi ◽  
Binglan Li ◽  
Douglas J. Epstein ◽  
Michael J. Ruckenstein ◽  
Jason A. Brant
Keyword(s):  
Hearing Loss ◽  
Genetic Variant ◽  
Care Center ◽  
Tertiary Care ◽  
Carrier Status ◽  
Loss Of Function ◽  
Wild Type ◽  
Sequencing Data ◽  
Genetic Hearing Loss ◽  
Low Sensitivity

“Cookie-bite” or U-shaped audiograms—specifically, those showing midfrequency sensorineural hearing loss (HL)—are traditionally taught to be associated with genetic HL; however, their utility as a screening tool has not been reported. We aim to determine the performance of a cookie-bite audiogram shape in stratifying patients carrying putative loss-of-function variants in known HL genes from wild-type controls. We merged audiometric and exome sequencing data from adults enrolled in a large biobank at a tertiary care center. Of 321 patients, 50 carried a putative loss-of-function variant in an HL gene. The cookie-bite shape was present in 9 of those patients, resulting in low sensitivity (18%) and positive predictive value (15%) in stratifying genetic carrier status; 84% of patients with a cookie-bite audiogram did not carry a genetic variant. A cookie-bite audiogram should not be used to screen adults for possible genetic testing.

scholarly journals Novel genotyping algorithms for rare variants significantly improve the accuracy of Applied Biosystems™ Axiom™ array genotyping calls

2021 ◽  
Author(s):  
Orna Mizrahi Man ◽  
Marcos H Woehrmann ◽  
Teresa A Webster ◽  
Jeremy Gollub ◽  
Adrian Bivol ◽  
...  
Keyword(s):  
Positive Predictive Value ◽  
Exome Sequencing ◽  
Predictive Value ◽  
Rare Variants ◽  
Uk Biobank ◽  
Sequencing Data ◽  
Data Set ◽  
Array Data ◽  
Exome Sequencing Data ◽  
The Uk

Objective: To significantly improve the positive predictive value (PPV) and sensitivity of Applied Biosystems™ Axiom™ array variant calling, by means of novel improvement to genotyping algorithms and careful quality control of array probesets. The improvement makes array genotyping more suitable for very rare variants. Design: Retrospective evaluation of UK Biobank array data re-genotyped with improved algorithms for rare variants. Participant: 488,359 people recruited to the UK Biobank with Axiom array genotyping data including 200,630 with exome sequencing data. Main Outcome Measures: A comparison of genotyping calls from array data to genotyping calls on a subset of variants with exome sequencing data. Results: Axiom genotyping [18] performed well, based on comparison to sequencing data, for over 100,000 common variants directly genotyped on the Axiom UK Biobank array and also exome sequenced by the UK Biobank Exome Sequencing Consortium. However, in a comparison to the initial exome sequencing results of the first 50K individuals, Weedon et al. [1] observed that when grouping these variants by the minor allele frequency (MAF) observed in UK Biobank, the concordance with sequencing and resulting positive predictive value (PPV) decreased with the number of heterozygous (Het) array calls per variant. An improved genotyping algorithm, Rare Heterozygous Adjustment (RHA) [16], released mid-2020 for genotyping on Axiom arrays, significantly improves PPV in all MAF ranges for the 50K data as well as when compared to the exome sequencing of 200K individuals, released after Weedon et al. [1] performed their comparison. The RHA algorithm improved PPVs in the 200K data in the lowest three frequency groups [0, 0.001%), [0.001%, 0.005%) and [0.005%, 0.01%) to 83%, 82% and 88%; respectively. PPV was above 95% for higher MAF ranges without algorithm improvement. PPVs are somewhat higher in the 200K dataset, due to a different "truth set" from exome sequencing and because monomorphic exome loci are not included in the joint genotyping calls for the 200K data set, as explained in the methods section. Sensitivity was higher in the 200K data set than in the original 50K data as well, especially for low MAF ranges. This increase is in part due to the larger data set over which sensitivity could be computed and in part due to the different WES algorithms used for the 200K data [7]. Filtering of a relatively small number of non-performing probesets (determined without reference to the exome sequencing data) significantly improved sensitivities for all MAF ranges, resulting in 70%, 88% and 94% respectively in the three lowest MAF ranges and greater than 98% and 99.9% for the two higher MAF ranges ([0.01%, 1%), [1%, 50%]). Conclusions: Improved algorithms for genotyping along with enhanced quality control of array probesets, significantly improve the positive predictive value and the sensitivity of array data, making it suitable for the detection of very rare variants. The probeset filtering methods developed have resulted in better probe designs for arrays and the new genotyping algorithm is part of the standard algorithm for all Axiom arrays since early 2020.

scholarly journals Rare variant contribution to human disease in 281,104 UK Biobank exomes

Nature ◽  
2021 ◽  
Author(s):  
Quanli Wang ◽  
Ryan S. Dhindsa ◽  
Keren Carss ◽  
Andrew R. Harper ◽  
Abhishek Nag ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Human Disease ◽  
European Ancestry ◽  
Common Disease ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Sequencing Data ◽  
Rare Variation ◽  
Exome Sequencing Data ◽  
The Impact

AbstractGenome-wide association studies have uncovered thousands of common variants associated with human disease, but the contribution of rare variation to common disease remains relatively unexplored. The UK Biobank (UKB) contains detailed phenotypic data linked to medical records for approximately 500,000 participants, offering an unprecedented opportunity to evaluate the impact of rare variation on a broad collection of traits1,2. Here, we studied the relationships between rare protein-coding variants and 17,361 binary and 1,419 quantitative phenotypes using exome sequencing data from 269,171 UKB participants of European ancestry. Gene-based collapsing analyses revealed 1,703 statistically significant gene-phenotype associations for binary traits, with a median odds ratio of 12.4. Furthermore, 83% of these associations were undetectable via single variant association tests, emphasizing the power of gene-based collapsing analysis in the setting of high allelic heterogeneity. Gene-phenotype associations were also significantly enriched for loss-of-function-mediated traits and approved drug targets. Finally, we performed ancestry-specific and pan-ancestry collapsing analyses using exome sequencing data from 11,933 UKB participants of African, East Asian, or South Asian ancestry. Together, our results highlight a significant contribution of rare variants to common disease. Summary statistics are publicly available through an interactive portal (http://azphewas.com/).

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