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.

Abstract 16686: Improved Diet Quality is Associated With Lower Prevalence of Clonal Hematopoiesis of Indeterminate Potential

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Romit Bhattacharya ◽  
Seyedeh M Zekavat ◽  
James Pirruccello ◽  
Gabriel K Griffin ◽  
Alexander G Bick ◽  
...  
Keyword(s):  
Diet Quality ◽  
Dietary Habits ◽  
Heart Association ◽  
Trend Test ◽  
Uk Biobank ◽  
Sequencing Data ◽  
Hematopoietic Stem ◽  
Clonal Hematopoiesis ◽  
Vegetarian Diets ◽  
The Uk

Introduction: Clonal Hematopoiesis of Indeterminate Potential (CHIP) is a pre-cancerous age-associated condition characterized by somatic mutations (typically in DNMT3A , TET2 , ASXL1 , JAK2 ) in hematopoietic stem cells and is a novel cardiovascular risk factor. Besides tobacco smoking, lifestyle factors that lead to the development of CHIP are currently poorly understood. Hypothesis: We hypothesize that healthy dietary habits are associated with reduced CHIP prevalence. Methods: We analyzed whole exome sequencing data from blood DNA in the UK Biobank to identify CHIP mutations with a variant allele fraction (VAF) >2% in DNMT3A or TET2 . We scored diet quality (unhealthy, intermediate, healthy, and healthy vegetarian) based on American Heart Association guidelines. We associated diet quality with CHIP using multivariate logistic regression adjusting for age, age 2 , sex, smoking, coronary artery disease, type 2 diabetes, Townsend Deprivation Index score, and genetic ancestry. We used the Cochran-Armitage trend test assessed to associate large CHIP (VAF>10%) with diet quality. Results: Among 48,389 individuals in the UK Biobank, CHIP prevalence was 1168 (3.14%). Of these, 543 (1.1%) had unhealthy, 44314 (91.6%) had intermediate, 3111 (6.4%) had healthy, and 421 (0.9%) had healthy vegetarian diets. Poor diet quality was significantly associated with increased prevalence of CHIP. Individuals with an unhealthy diet had higher rates of CHIP (5.0%), compared to intermediate (3.2%, OR 0.63, p=0.05), healthy (2.8%, OR 0.58, p=0.04), and vegetarian diets (1.1%, OR 0.25, p=0.03). Large CHIP clones demonstrated a significant trend with improved diet quality associated with lower CHIP prevalence (p=0.009) among those with unhealthy (1.9%), intermediate (1.3%), healthy (1.0%), and vegetarian (0.0%) diets. Conclusions: Diet quality is associated with CHIP prevalence among 48,389 individuals in the UK Biobank.

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<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 >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

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.

Characterization of clonal hematopoiesis of indeterminate potential mutations from germline whole exome sequencing data.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 1525-1525
Author(s):  
Hsin-Ta Wu ◽  
Ekaterina Kalashnikova ◽  
Samay Mehta ◽  
Raheleh Salari ◽  
Himanshu Sethi ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Allele Frequency ◽  
Whole Exome Sequencing ◽  
Somatic Mutations ◽  
Sequencing Data ◽  
Clonal Hematopoiesis ◽  
Exome Sequencing Data ◽  
Whole Exome ◽  
Whole Exome Sequencing Data ◽  
Ctdna Analysis

1525 Background: Clonal hematopoiesis of Indeterminate Potential (CHIP) is an age-related phenomenon where somatic mutations accumulate in cells of the blood or bone marrow. It is a source of biological noise that causes false-positives in ctDNA analysis and is present in up to 20% of individuals over the age of 70. The presence of CHIP has been linked to an increased risk of hematologic cancers and cardiovascular disease. The Signatera assay filters CHIP mutations through tumor tissue and germline sequencing thereby reducing false-positive results and focuses on tumor-specific mutations for each patient. Methods: Whole exome sequencing data (average depth ~250x) analyzed from patients’ buffy coat (n = 159) was used to characterize CHIP mutations. Variant calling was performed using Freebayes variant caller with allele frequency threshold between 1% and 10%. Following which variant annotation and selection was performed based on the top 54 genes that are most implicated in myeloid disorders. The selected variants were further screened based on the reported variants in the literature and/or the Catalog of Somatic Mutations in Cancer (COSMIC). Results: The analysis revealed an average of 0.14 (0-2) CHIP mutations per patient with an average variant allele frequency of 3.49% (1%-8.5%). The most common CHIP mutations were observed in DNMT3A, (n = 17), TET2 (n = 7) and TP53 (n = 7) genes. The percentage of patients with at least 1 mutation found in DNMT3A, TET2, and TP53 were 4.2%, 1.94%, and 1.38%, respectively. Other genes containing CHIP mutation included CEBPA, ETV6, HRAS, PDGFRA, NRAS, KMT2A, EZH2, GATA2, GNAS at a frequency below 1%. CHIP mutations were not observed in patients younger than 40 years, but they increased in frequency with every decade of life thereafter. The incidence of CHIP increased from 0.04 for the 40-50 yrs age group to 0.18 for individuals older than 60. Further analysis of associations between incidence of CHIP and cancer type, prior exposure to chemotherapy as well as longitudinal evolution of CHIP mutations during cytotoxic treatment are underway and will be presented. Conclusions: CHIP, a common finding in the elderly population is an important factor to consider in ctDNA analysis and most frequently involves DNMT3A, TET2, and TP53 genes. The frequency of CHIP can be impacted by a number of other factors such as cytotoxic chemo- or radiotherapy.

scholarly journals Use of SNP chips to detect rare pathogenic variants: retrospective, population based diagnostic evaluation

BMJ ◽  
2021 ◽  
pp. n214
Author(s):  
Weedon MN ◽  
Jackson L ◽  
Harrison JW ◽  
Ruth KS ◽  
Tyrrell J ◽  
...  
Keyword(s):  
Positive Predictive Value ◽  
Predictive Value ◽  
Population Based ◽  
Genome Project ◽  
Personal Genome ◽  
Uk Biobank ◽  
Sequencing Data ◽  
Snp Chip ◽  
Pathogenic Variants ◽  
The Uk

Abstract Objective To determine whether the sensitivity and specificity of SNP chips are adequate for detecting rare pathogenic variants in a clinically unselected population. Design Retrospective, population based diagnostic evaluation. Participants 49 908 people recruited to the UK Biobank with SNP chip and next generation sequencing data, and an additional 21 people who purchased consumer genetic tests and shared their data online via the Personal Genome Project. Main outcome measures Genotyping (that is, identification of the correct DNA base at a specific genomic location) using SNP chips versus sequencing, with results split by frequency of that genotype in the population. Rare pathogenic variants in the BRCA1 and BRCA2 genes were selected as an exemplar for detailed analysis of clinically actionable variants in the UK Biobank, and BRCA related cancers (breast, ovarian, prostate, and pancreatic) were assessed in participants through use of cancer registry data. Results Overall, genotyping using SNP chips performed well compared with sequencing; sensitivity, specificity, positive predictive value, and negative predictive value were all above 99% for 108 574 common variants directly genotyped on the SNP chips and sequenced in the UK Biobank. However, the likelihood of a true positive result decreased dramatically with decreasing variant frequency; for variants that are very rare in the population, with a frequency below 0.001% in UK Biobank, the positive predictive value was very low and only 16% of 4757 heterozygous genotypes from the SNP chips were confirmed with sequencing data. Results were similar for SNP chip data from the Personal Genome Project, and 20/21 individuals analysed had at least one false positive rare pathogenic variant that had been incorrectly genotyped. For pathogenic variants in the BRCA1 and BRCA2 genes, which are individually very rare, the overall performance metrics for the SNP chips versus sequencing in the UK Biobank were: sensitivity 34.6%, specificity 98.3%, positive predictive value 4.2%, and negative predictive value 99.9%. Rates of BRCA related cancers in UK Biobank participants with a positive SNP chip result were similar to those for age matched controls (odds ratio 1.31, 95% confidence interval 0.99 to 1.71) because the vast majority of variants were false positives, whereas sequence positive participants had a significantly increased risk (odds ratio 4.05, 2.72 to 6.03). Conclusions SNP chips are extremely unreliable for genotyping very rare pathogenic variants and should not be used to guide health decisions without validation.

scholarly journals Lifetime depression and age-related changes in body composition, cardiovascular function, grip strength and lung function: sex-specific analyses in the UK Biobank

BJPsych Open ◽  
2021 ◽  
Vol 7 (S1) ◽  
pp. S44-S44
Author(s):  
Julian Mutz ◽  
Cathryn M Lewis
Keyword(s):  
Body Composition ◽  
Lung Function ◽  
Cardiovascular Function ◽  
Healthy Controls ◽  
Physiological Measures ◽  
Uk Biobank ◽  
Mineral Density ◽  
Age Related ◽  
The Uk ◽  
Age Related Changes

AimsIndividuals with mental disorders, on average, die prematurely, have higher levels of physical comorbidities and may experience accelerated ageing. In individuals with lifetime depression and healthy controls, we examined associations between age and multiple physiological measures.MethodThe UK Biobank study recruited >500,000 participants, aged 37–73 years, between 2006–2010. Generalised additive models were used to examine associations between age and grip strength, cardiovascular function, body composition, lung function and bone mineral density. Analyses were conducted separately in males and females with depression compared to healthy controls.ResultAnalytical samples included up to 342,393 adults (mean age = 55.87 years; 52.61% females). We found statistically significant differences between individuals with depression and healthy controls for most physiological measures, with standardised mean differences between -0.145 and 0.156. There was some evidence that age-related changes in body composition, cardiovascular function, lung function and heel bone mineral density followed different trajectories in individuals with depression. These differences did not uniformly narrow or widen with age. For example, BMI in female cases was 1.1 kg/m2 higher at age 40 and this difference narrowed to 0.4 kg/m2 at age 70. In males, systolic blood pressure was 1 mmHg lower in cases at age 45 and this difference widened to 2.5 mmHg at age 65.ConclusionIndividuals with depression differed from healthy controls across a broad range of physiological measures. Differences in ageing trajectories differed by sex and were not uniform across physiological measures, with evidence of both age-related narrowing and widening of case-control differences.

scholarly journals Genetic predisposition to increased serum calcium, bone mineral density, and fracture risk in individuals with normal calcium levels: mendelian randomisation study

BMJ ◽  
2019 ◽  
pp. l4410 ◽  
Author(s):  
Agustin Cerani ◽  
Sirui Zhou ◽  
Vincenzo Forgetta ◽  
John A Morris ◽  
Katerina Trajanoska ◽  
...  
Keyword(s):  
Bone Mineral Density ◽  
Bone Mineral ◽  
Serum Calcium ◽  
Genetic Predisposition ◽  
Calcium Supplementation ◽  
Meta Analysis ◽  
Mendelian Randomisation ◽  
Uk Biobank ◽  
Mineral Density ◽  
The Uk

Abstract Objective To determine if genetically increased serum calcium levels are associated with improved bone mineral density and a reduction in osteoporotic fractures. Design Mendelian randomisation study. Setting Cohorts used included: the UK Biobank cohort, providing genotypic and estimated bone mineral density data; 25 cohorts from UK, USA, Europe, and China, providing genotypic and fracture data; and 17 cohorts from Europe, providing genotypic and serum calcium data (summary level statistics). Participants A genome-wide association meta-analysis of serum calcium levels in up to 61 079 individuals was used to identify genetic determinants of serum calcium levels. The UK Biobank study was used to assess the association of genetic predisposition to increased serum calcium with estimated bone mineral density derived from heel ultrasound in 426 824 individuals who had, on average, calcium levels in the normal range. A fracture genome-wide association meta-analysis comprising 24 cohorts and the UK Biobank including a total of 76 549 cases and 470 164 controls, who, on average, also had calcium levels in the normal range was then performed. Results A standard deviation increase in genetically derived serum calcium (0.13 mmol/L or 0.51 mg/dL) was not associated with increased estimated bone mineral density (0.003 g/cm 2 , 95% confidence interval −0.059 to 0.066; P=0.92) or a reduced risk of fractures (odds ratio 1.01, 95% confidence interval 0.89 to 1.15; P=0.85) in inverse-variance weighted mendelian randomisation analyses. Sensitivity analyses did not provide evidence of pleiotropic effects. Conclusions Genetic predisposition to increased serum calcium levels in individuals with normal calcium levels is not associated with an increase in estimated bone mineral density and does not provide clinically relevant protection against fracture. Whether such predisposition mimics the effect of short term calcium supplementation is not known. Given that the same genetically derived increase in serum calcium is associated with an increased risk of coronary artery disease, widespread calcium supplementation in the general population could provide more risk than benefit.

scholarly journals Genetic basis of falling risk susceptibility in the UK Biobank Study

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Katerina Trajanoska ◽  
Lotta J. Seppala ◽  
Carolina Medina-Gomez ◽  
Yi-Hsiang Hsu ◽  
Sirui Zhou ◽  
...  
Keyword(s):  
Genetic Correlations ◽  
Well Being ◽  
Risk Scores ◽  
Subjective Well Being ◽  
Uk Biobank ◽  
Mineral Density ◽  
Polygenic Inheritance ◽  
Intrinsic Factors ◽  
A Genome ◽  
The Uk

Abstract Both extrinsic and intrinsic factors predispose older people to fall. We performed a genome-wide association analysis to investigate how much of an individual’s fall susceptibility can be attributed to genetics in 89,076 cases and 362,103 controls from the UK Biobank Study. The analysis revealed a small, but significant SNP-based heritability (2.7%) and identified three novel fall-associated loci (Pcombined ≤ 5 × 10−8). Polygenic risk scores in two independent settings showed patterns of polygenic inheritance. Risk of falling had positive genetic correlations with fractures, identifying for the first time a pathway independent of bone mineral density. There were also positive genetic correlations with insomnia, neuroticism, depressive symptoms, and different medications. Negative genetic correlations were identified with muscle strength, intelligence and subjective well-being. Brain, and in particular cerebellum tissue, showed the highest gene expression enrichment for fall-associated variants. Overall, despite the highly heterogenic nature underlying fall risk, a proportion of the susceptibility can be attributed to genetics.

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