scholarly journals Resilience to dominant genetic disease in the healthy elderly

2019 ◽  
Author(s):  
Paul Lacaze ◽  
Robert Sebra ◽  
Moeen Riaz ◽  
Jane Tiller ◽  
Jerico Revote ◽  
...  

ABSTRACTHere we describe genomic screening of the healthy elderly to identify those resilient to adult-onset genetic disease, despite being at exceptionally high genetic risk. We sequenced 13,131 individuals aged 70 or older (mean age 75 years) from the ASPirin in Reducing Events in the Elderly (ASPREE) trial. Participants had no prior history of cardiovascular disease, life-threatening cancer, persistent physical disability or dementia. We compared the prevalence of pathogenic variants in medically actionable autosomal dominant disease genes with that from the UK Biobank population, and assessed their clinical impact using personal medical history and adjudicated study outcomes during 4.5 years of follow-up. The frequency of pathogenic variants was less than reported among the younger UK Biobank population, suggesting these variants confer a survival disadvantage during the middle years of life. Yet we identified 141 individuals with pathogenic variants free of any associated disease up to average age 79.5 years. Further study of these elderly resilient individuals might help uncover genetic mechanisms that protect against the development of disease.

2020 ◽  
Author(s):  
Sean J. Jurgens ◽  
Seung Hoan Choi ◽  
Valerie N. Morrill ◽  
Mark Chaffin ◽  
James P. Pirruccello ◽  
...  

AbstractBackgroundMany human diseases are known to have a genetic contribution. While genome-wide studies have identified many disease-associated loci, it remains challenging to elucidate causal genes. In contrast, exome sequencing provides an opportunity to identify new disease genes and large-effect variants of clinical relevance. We therefore sought to determine the contribution of rare genetic variation in a curated set of human diseases and traits using a unique resource of 200,000 individuals with exome sequencing data from the UK Biobank.Methods and ResultsWe included 199,832 participants with a mean age of 68 at follow-up. Exome-wide gene-based tests were performed for 64 diseases and 23 quantitative traits using a mixed-effects model, testing rare loss-of-function and damaging missense variants. We identified 51 known and 23 novel associations with 26 diseases and traits at a false-discovery-rate of 1%. There was a striking risk associated with many Mendelian disease genes including: MYPBC3 with over a 100-fold increased odds of hypertrophic cardiomyopathy, PKD1 with a greater than 25-fold increased odds of chronic kidney disease, and BRCA2, BRCA1, ATM and PALB2 with 3 to 10-fold increased odds of breast cancer. Notable novel findings included an association between GIGYF1 and type 2 diabetes (OR 5.6, P=5.35×10−8), elevated blood glucose, and lower insulin-like-growth-factor-1 levels. Rare variants in CCAR2 were also associated with diabetes risk (OR 13, P=8.5×10−8), while COL9A3 was associated with cataract (OR 3.4, P=6.7×10−8). Notable associations for blood lipids and hypercholesterolemia included NR1H3, RRBP1, GIGYF1, SCGN, APH1A, PDE3B and ANGPTL8. A number of novel genes were associated with height, including DTL, PIEZO1, SCUBE3, PAPPA and ADAMTS6, while BSN was associated with body-mass-index. We further assessed putatively pathogenic variants in known Mendelian cardiovascular disease genes and found that between 1.3 and 2.3% of the population carried likely pathogenic variants in known cardiomyopathy, arrhythmia or hypercholesterolemia genes.ConclusionsLarge-scale population sequencing identifies known and novel genes harboring high-impact variation for human traits and diseases. A number of novel findings, including GIGYF1,represent interesting potential therapeutic targets. Exome sequencing at scale can identify a meaningful proportion of the population that carries a pathogenic variant underlying cardiovascular disease.


BMJ ◽  
2021 ◽  
pp. n214
Author(s):  
Weedon MN ◽  
Jackson L ◽  
Harrison JW ◽  
Ruth KS ◽  
Tyrrell J ◽  
...  

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.


Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Alex Gyftopoulos ◽  
Yi-Ju Chen ◽  
Libin Wang ◽  
Charles H Williams ◽  
Young Wook Chun ◽  
...  

Introduction: Hypertrophic cardiomyopathy (HCM) is the most commonly inherited cardiac disease affecting 1:500 to 1:200 individuals worldwide. HCM has a heterogeneous genetic profile and phenotypic expression. More than 1400 known pathogenic variants have been identified in 11 sarcomere genes. In about 40% of HCM patients, the genetic cause may not be identified. The same mutation may lead to different phenotypes and severity in different individuals. Identification of novel HCM genes and modifiers will expand our understanding of the signaling pathways that are responsible for phenotypic expression of HCM. Methods: The UK Biobank comprises clinical and genetic data for greater than 500,000 individuals. We used OASIS, an information system for analyzing, searching, and visualizing associations between phenotype and genotype data to analyze this data. We compared control individuals to HCM individuals identified by ICD-10 code (I42.1 and I42.2) in a 20-to-1 fashion. Related individuals and those with confounding diagnoses were excluded. Results: The analysis was performed with Plink’s GLM option, and we identified 84 variants with a minor allele frequency of 0.5% or greater in 65 genes associated with HCM with a p < 1x10 -6 , including 4 with p < 5x10 -8 . The identified genes encode lncRNAs, miRNAs, and membrane proteins. Variants with high significance were identified in the genes encoding putative ciliary components DNAL4 (dynein axonemal light chain 4; p = 2.9x10 -8 ), MYO1D (unconventional myosin 1D; p = 3.1x10 -8 ), ITFAP (intraflagellar transport associated protein; p = 9.5x10 -8 ), CABCOCO1 (ciliary associated calcium biding coiled-coil 1; p = 3.7x 10 -7 ), EVL (Enah-Vasp-like; p = 4.4x 10 -7 ) and IFT122 (intraflagellar transport 122; p = 8.0 x10 -7 ). Conclusion: While none of these have previously associated with HCM, our findings suggest ciliary structure and function may play a role in disease manifestation. Our method is unique by pooling individuals in a large population set to identify potential causative or contributing mutations. Bioinformatic tools, such as OASIS, allow for the identification of previously unrecognized variants that may play a role in the development of HCM. This approach has identified numerous novel genes as possible risk loci.


2021 ◽  
Author(s):  
Ravi Shah ◽  
Babken Asatryan ◽  
Ghaith Sharaf Dabbagh ◽  
Nay Aung ◽  
Mohammed Y Khanji ◽  
...  

Background: There is a paucity of data regarding the phenotype of dilated cardiomyopathy (DCM) gene variants in the general population. We aimed to determine the frequency and penetrance of DCM-associated putative pathogenic gene variants in a general, adult population, with a focus on the expression of clinical and subclinical phenotype, including structural, functional and arrhythmic disease features. Methods: UK Biobank participants who had undergone whole exome sequencing (WES), ECG and cardiovascular magnetic resonance (CMR) imaging were selected for study. Three different variant calling strategies (one primary and two secondary) were used to identify subjects with putative pathogenic variants in 44 DCM genes. The observed phenotype was graded to either 1) DCM (clinical or CMR diagnosis); 2) early DCM features, including arrhythmia and/or conduction disease, isolated ventricular dilation, and hypokinetic non-dilated cardiomyopathy; or 3) phenotype-negative. Results: Among 18,665 individuals included in the study, 1,463 (7.8%) subjects possessed ≥1 putative pathogenic variant in 44 DCM genes by the main variant calling strategy. A clinical diagnosis of DCM was present in 0.34% and early DCM features in 5.7% of individuals with putative pathogenic variants. ECG and CMR analysis revealed evidence of subclinical DCM in an additional 1.6% and early DCM features in 15.9% of individuals with putative pathogenic variants. Arrhythmias and/or conduction disease (15.2%) were the most common early DCM features, followed by hypokinetic non-dilated cardiomyopathy (4%). The combined clinical/subclinical penetrance was ≤30% with all three variant filtering strategies. Clinical DCM was slightly more prevalent among participants with putative pathogenic variants in definitive/strong evidence genes, as compared to those with variants in moderate/limited evidence genes. Conclusions: In the UK Biobank, approximately 1/6 of adults with putative pathogenic variants in DCM genes exhibited a subclinical phenotype based on ECG and/or CMR, most commonly manifesting with arrhythmias in the absence of substantial ventricular dilation/dysfunction.


Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Cameron Both ◽  
Julian Acosta ◽  
Natalia Szejko ◽  
Kevin N Vanent ◽  
Audrey C Leasure ◽  
...  

Introduction: Clinically silent cerebrovascular disease is present in 40% of persons over the age of 60. We hypothesize that polygenic susceptibility to atrial fibrillation is associated with the burden of white matter disease in persons without atrial fibrillation or history of ischemic stroke. Methods: We conducted a nested genetic and neuroimaging study within the UK Biobank, a large cohort study that enrolled community dwelling Britons aged 40 to 65 at recruitment. We used data on a subcohort of patients evaluated with brain MRIs. The volume of white matter hyperintensities (WMH) was estimated using the BIANCA lesion segmentation tool. Genomic data was ascertained via genotyping with the Affymetrix UK Biobank Axiom array followed by imputation with 1000 Genomes reference panels. To model the polygenic susceptibility to atrial fibrillation (AFIB), we constructed a polygenic risk score (PRS) using 957 independent genetic risk variants known to significantly associate with atrial fibrillation. We used logistic and linear regression to test for association between the PRS and WMH. Results: A total of 38,914 study participants underwent brain MRI imaging in the UK Biobank. Of these, we excluded 124 (0.3%) with a history of stroke and 926 (2.4%) with AFIB. 37,864 study participants were included in this study, of which 19,059 (50.3%) had WMH. High genetic risk of AFIB was not associated with no-versus-any WMH (p=0.51). When evaluating persons with WMH lesions, high genetic risk of AFIB was associated with higher WMH volume (per 1 SD increase of the PRS, beta 0.019, SE 0.006; p=0.01). Gender was an important effect modifier of this association (interaction p=0.03): while high genetic risk of AFIB was associated with a significant increase in WMH volume in females (per 1 SD increase of the PRS, beta 0.03, SE 0.008; p<0.001), no association was found for males (p=0.99). Conclusions: Polygenic susceptibility to atrial fibrillation is associated with more severe silent cerebrovascular disease in persons without atrial fibrillation. Further research should evaluate whether this genetic information can be used to identify persons for tailored diagnostic or therapeutic interventions.


1993 ◽  
Vol 69 (1) ◽  
pp. 21-27 ◽  
Author(s):  
J. J. Reilly ◽  
A. Lord ◽  
V. W. Bunker ◽  
A. M. Prentice ◽  
W. A. Coward ◽  
...  

There is a paucity of data on which to base estimates of the energy requirements of the elderly. In general, ageing appears to be associated with a reduction in energy requirement arising from a reduction in physical activity and loss of fat-free mass. The aim of the present study was to measure the total energy expenditure (TEE), basal metabolic rate (BMR), and energy expended on physical activity (calculated as TEE–BMR) in a group of healthy elderly women living in the community in Southampton. Mean rates of TEE (9.21 (SD 1.48) MJd) and energy expended on physical activity (4.12 (SD 1.19) MJ/d) were higher than those observed in some studies of younger adults in the UK, and higher than the factors used to estimate the average energy requirement for the elderly. The results suggest that an age-related reduction in energy requirement is not inevitable and support the hypothesis that the effects of ageing on physical activity, body composition, and hence energy requirements, are variable.


2019 ◽  
Author(s):  
Michael N Weedon ◽  
Leigh Jackson ◽  
James W Harrison ◽  
Kate S Ruth ◽  
Jessica Tyrrell ◽  
...  

ABSTRACTObjectivesTo determine the analytical validity of SNP-chips for genotyping very rare genetic variants.DesignRetrospective study using data from two publicly available resources, the UK Biobank and the Personal Genome Project.SettingResearch biobanks and direct-to-consumer genetic testing in the UK and USA.Participants49,908 individuals recruited to UK Biobank, and 21 individuals who purchased consumer genetic tests and shared their data online via the Personal Genomes Project.Main outcome measuresWe assessed the analytical validity of genotypes from SNP-chips (index test) with sequencing data (reference standard). We evaluated the genotyping accuracy of the SNP-chips and split the results by variant frequency. We went on to select rare pathogenic variants in the BRCA1 and BRCA2 genes as an exemplar for detailed analysis of clinically-actionable variants in UK Biobank, and assessed BRCA-related cancers (breast, ovarian, prostate and pancreatic) in participants using cancer registry data.ResultsSNP-chip genotype accuracy is high overall; sensitivity, specificity and precision are all >99% for 108,574 common variants directly genotyped by the UK Biobank SNP-chips. However, the likelihood of a true positive result reduces dramatically with decreasing variant frequency; for variants with a frequency <0.001% in UK Biobank the precision is very low and only 16% of 4,711 variants from the SNP-chips confirm with sequencing data. Results are similar for SNP-chip data from the Personal Genomes Project, and 20/21 individuals have at least one rare pathogenic variant that has been incorrectly genotyped. For pathogenic variants in the BRCA1 and BRCA2 genes, the overall performance metrics of the SNP-chips in UK Biobank are sensitivity 34.6%, specificity 98.3% and precision 4.2%. Rates of BRCA-related cancers in individuals in UK Biobank with a positive SNP-chip result are similar to age-matched controls (OR 1.28, P=0.07, 95% CI: 0.98 to 1.67), while sequence-positive individuals have a significantly increased risk (OR 3.73, P=3.5×10−12, 95% CI: 2.57 to 5.40).ConclusionSNP-chips are extremely unreliable for genotyping very rare pathogenic variants and should not be used to guide health decisions without validation.SUMMARY BOXSection 1: What is already known on this topicSNP-chips are an accurate and affordable method for genotyping common genetic variants across the genome. They are often used by direct-to-consumer (DTC) genetic testing companies and research studies, but there several case reports suggesting they perform poorly for genotyping rare genetic variants when compared with sequencing.Section 2: What this study addsOur study confirms that SNP-chips are highly inaccurate for genotyping rare, clinically-actionable variants. Using large-scale SNP-chip and sequencing data from UK Biobank, we show that SNP-chips have a very low precision of <16% for detecting very rare variants (i.e. the majority of variants with population frequency of <0.001% are false positives). We observed a similar performance in a small sample of raw SNP-chip data from DTC genetic tests. Very rare variants assayed using SNP-chips should not be used to guide health decisions without validation.


2020 ◽  
Author(s):  
Valentina Bordin ◽  
Ilaria Bertani ◽  
Irene Mattioli ◽  
Vaanathi Sundaresan ◽  
Paul McCarthy ◽  
...  

ABSTRACTLarge scale neuroimaging datasets present the possibility of providing normative distributions for a wide variety of neuroimaging markers, which would vastly improve the clinical utility of these measures. However, a major challenge is our current poor ability to integrate measures across different large-scale datasets, due to inconsistencies in imaging and non-imaging measures across the different protocols and populations. Here we explore the harmonisation of white matter hyperintensity (WMH) measures across two major studies of healthy elderly populations, the Whitehall II imaging sub-study and the UK Biobank. We identify pre-processing strategies that maximise the consistency across datasets and utilise multivariate regression to characterise sample differences contributing to study-level differences in WMH variations. We also present a parser to harmonise WMH-relevant non-imaging variables across the two datasets. We show that we can provide highly calibrated WMH measures from these datasets with: (1) the inclusion of a number of specific standardised processing steps; and (2) appropriate modelling of sample differences through the alignment of demographic, cognitive and physiological variables. These results open up a wide range of applications for the study of WMHs and other neuroimaging markers across extensive databases of clinical data.HIGHLIGHTSWe harmonised measures of WMHs across two studies on healthy ageingSpecific pre-processing strategies can increase comparability across studiesModelling of biological differences is crucial to provide calibrated measures


Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Guido J Falcone ◽  
Julian Acosta ◽  
Audrey C Leasure ◽  
Kevin N Vanent ◽  
Rommell B Noche ◽  
...  

Background and Hypothesis: Driven by aging-related physiological changes, the incidence of stroke and myocardial infarction rises rapidly in persons aged >40 years. A significant proportion of these acute vascular events (AVE) take place in persons without vascular risk factors. We tested the hypothesis that sex and genetic predisposition synergistically increase the risk of AVE in middle-aged persons without vascular risk factors. Methods: We analyzed data from the UK Biobank, a prospective longitudinal study that enrolled persons aged 40 to 69 years. Our analysis was restricted to middle-aged participants, defined as those aged 40 to 60 years. Prevalent and incident cases of stroke (ischemic and hemorrhagic) and myocardial infarction were included. To quantify the genetic predisposition to sustain an AVE, we constructed a polygenic risk score using 68 independent (R 2 <0.1) genetic variants known to associate (p<5x10 -8 ) with AVE. Participants were classified as having low, intermediate or high genetic risk according to tertiles of the score. We used Cox models for association and interaction testing. Results: Of the 502,536 study participants enrolled in the UK Biobank, 303,295 (60%) did not have any vascular risk factors. During the follow-up period, there were 5,746 AVEs, including 1,954 strokes and 3,792 myocardial infarctions. The cumulative risk of AVE was 0.12% (n=352), 0.46% (n = 1,386) and 1.32% (n = 4,008) at ages 40, 50 and 60 years (test-for-trend p<0.001). The risk of AVE was 3 times greater in men than women (HR 3.30, 95%CI 3.08 - 3.53). Compared to persons with low genetic risk, those with intermediate and high genetic risk had a 22% (HR 1.22, 95%CI 1.13 - 1.32) and 52% (HR 1.52, 95%CI 1.41 - 1.65) increase in risk of AVE, respectively. There was significant synergy (interaction) between sex and genetic predisposition: compared to females with low genetic risk, males with high genetic risk had 4 times (HR 3.91, 95%CI 3.58 - 4.26) the risk of AVE (interaction analysis p<0.001). Conclusion: Genetic information constitutes a promising tool to risk stratify middle-aged persons without vascular risk factors. The synergistic effect of sex and genetic predisposition points to specific subgroups that could benefit from aggressive preventive interventions.


2018 ◽  
Author(s):  
Mark Pinese ◽  
Paul Lacaze ◽  
Emma M. Rath ◽  
Andrew Stone ◽  
Marie-Jo Brion ◽  
...  

SummaryPopulation health research is increasingly focused on the genetic determinants of healthy ageing, but there is no public resource of whole genome sequences and phenotype data from healthy elderly individuals. Here we describe the Medical Genome Reference Bank (MGRB), comprising whole genome sequence and phenotype of 2,570 elderly Australians depleted for cancer, cardiovascular disease, and dementia. We analysed the MGRB for single-nucleotide, indel and structural variation in the nuclear and mitochondrial genomes. Individuals in the MGRB had fewer disease-associated common and rare germline variants, relative to both cancer cases and the gnomAD and UK BioBank cohorts, consistent with risk depletion. Pervasive age-related somatic changes were correlated with grip strength in men, suggesting blood-derived whole genomes may also provide a biologic measure of age-related functional deterioration. The MGRB provides a broadly applicable reference cohort for clinical genetics and genomic association studies, and for understanding the genetics of healthy ageing. This research has been conducted using the UK Biobank Resource under Application Number 17984.


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