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.

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 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.

Abstract 607: Clonal hematopoiesis alters blood cell counts in the UK Biobank

2019 ◽  
Author(s):  
Mitchell J. Machiela ◽  
Weiyin Zhou ◽  
Erikka Loftfield ◽  
Meredith Yeager ◽  
Neal D. Freedman ◽  
...  
Keyword(s):  
Blood Cell ◽  
Uk Biobank ◽  
Clonal Hematopoiesis ◽  
Cell Counts ◽  
Blood Cell Counts ◽  
The Uk

scholarly journals Diet-quality and its association with cardiovascular diseases and cancer incidence and all-cause mortality: a prospective cohort study from UK Biobank

2020 ◽  
Vol 79 (OCE2) ◽  
Author(s):  
Fanny Petermann-Rocha ◽  
Stuart R. Gray ◽  
Jill Pell ◽  
Carlos Celis-Morales
Keyword(s):  
Cancer Incidence ◽  
Diet Quality ◽  
Lower Risk ◽  
Quality Score ◽  
Confounding Factors ◽  
Uk Biobank ◽  
Healthy Group ◽  
Oily Fish ◽  
All Cause Mortality ◽  
The Uk

AbstractIntroductionNewly available data from big scale studies conducted in the UK, such as the UK Biobank, offers the possibility to further explore the prospective association between a diet-quality score and health outcomes after accounting for the effect of important confounding factors. The aim of this work, therefore, was to investigate the association between a diet-quality score, with the incidence of cardiovascular diseases (CVDs), cancer and all-cause mortality.Material and methodsThis study includes 345,343 participants (age range: 39–73, 55.1% women) from the UK Biobank, a prospective population-based study. Using 21 standardised variables of diet (alcohol, bread, bread type, cereal, dried fruit, water, coffee, tea, cheese, oily fish, non-oily fish, salt added to food, spread type, fresh fruit, cooked vegetable, raw vegetables, milk type, poultry, beef, lamb, and pork) we created a diet-quality score (very healthy, healthy, unhealthy and very unhealthy) using principal-component factor analysis. Associations between the dietary-quality score (very unhealthy individuals were the reference group) and health outcomes (all-cause mortality, CVD and cancer incidence) were investigated using Cox-proportional hazard models. All analyses were performed using STATA 14 statistical software.ResultsIn comparison to individuals with a very unhealthy diet, those with a better diet-quality had a lower risk of all-cause mortality and cancer as well as incidence of CVD and cancer. For example, individuals classified in the very healthy group had a 12% lower risk of all-cause mortality (HR: 0.88 [95% CI: 0.82 to 0.95]), 12% lower risk of CVD incidence (HR: 0.88 [95% CI: 0.80 to 0.98]), 17% of all-cancer mortality (HR: 0.83 [95% CI: 0.75 to 0.93]), and 10% lower risk all-cancer incidence (HR: 0.90 [95% CI: 0.85 to 0.94]). Those in the healthy group had a 12% lower risk of all-cause (HR: 0.88 [95% CI: 0.83 to 0.93]) and 15% lower risk of all-cancer mortality (HR: 0.85 [95% CI: 0.78 to 0.93]). There was no significant association between CVD mortality and any diet-quality group. These findings were independent of major confounding factors including socio-demographic covariates, prevalent of diseases and lifestyle factors.DiscussionOur findings indicate that individuals with a healthy diet in the UK biobank cohort are associated with a lower risk of premature mortality, and incidence of CVDs and cancer independently of major confounding factors.

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.

The evolutionary dynamics and fitness landscape of clonal hematopoiesis

Science ◽  
2020 ◽  
Vol 367 (6485) ◽  
pp. 1449-1454 ◽  
Author(s):  
Caroline J. Watson ◽  
A. L. Papula ◽  
Gladys Y. P. Poon ◽  
Wing H. Wong ◽  
Andrew L. Young ◽  
...  
Keyword(s):  
Evolutionary Dynamics ◽  
Fitness Landscape ◽  
Sequencing Data ◽  
Driver Genes ◽  
Single Nucleotide ◽  
Hematopoietic Stem ◽  
Clonal Hematopoiesis ◽  
Fitness Advantage ◽  
Pathogenic Variants ◽  
Nucleotide Resolution

Somatic mutations acquired in healthy tissues as we age are major determinants of cancer risk. Whether variants confer a fitness advantage or rise to detectable frequencies by chance remains largely unknown. Blood sequencing data from ~50,000 individuals reveal how mutation, genetic drift, and fitness shape the genetic diversity of healthy blood (clonal hematopoiesis). We show that positive selection, not drift, is the major force shaping clonal hematopoiesis, provide bounds on the number of hematopoietic stem cells, and quantify the fitness advantages of key pathogenic variants, at single-nucleotide resolution, as well as the distribution of fitness effects (fitness landscape) within commonly mutated driver genes. These data are consistent with clonal hematopoiesis being driven by a continuing risk of mutations and clonal expansions that become increasingly detectable with age.

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 Dietary Habit Is Associated with Depression and Intelligence: An Observational and Genome-Wide Environmental Interaction Analysis in the UK Biobank Cohort

Nutrients ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 1150
Author(s):  
Bolun Cheng ◽  
Xiaomeng Chu ◽  
Xuena Yang ◽  
Yan Wen ◽  
Yumeng Jia ◽  
...  
Keyword(s):  
Mental Health ◽  
Fluid Intelligence ◽  
Dietary Habits ◽  
Interaction Analysis ◽  
Dietary Habit ◽  
Polygenic Risk Score ◽  
Uk Biobank ◽  
Study Results ◽  
The Individual ◽  
The Uk

Dietary habits have considerable impact on brain development and mental health. Despite long-standing interest in the association of dietary habits with mental health, few population-based studies of dietary habits have assessed depression and fluid intelligence. Our aim is to investigate the association of dietary habits with depression and fluid intelligence. In total, 814 independent loci were utilized to calculate the individual polygenic risk score (PRS) for 143 dietary habit-related traits. The individual genotype data were obtained from the UK Biobank cohort. Regression analyses were then conducted to evaluate the association of dietary habits with depression and fluid intelligence, respectively. PLINK 2.0 was utilized to detect the single nucleotide polymorphism (SNP) × dietary habit interaction effect on the risks of depression and fluid intelligence. We detected 22 common dietary habit-related traits shared by depression and fluid intelligence, such as red wine glasses per month, and overall alcohol intake. For interaction analysis, we detected that OLFM1 interacted with champagne/white wine in depression, while SYNPO2 interacted with coffee type in fluid intelligence. Our study results provide novel useful information for understanding how eating habits affect the fluid intelligence and depression.

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