scholarly journals Expanding cancer predisposition genes with ultra-rare cancer-exclusive human variations

Author(s):  
Roni Rasnic ◽  
Nathan Linial ◽  
Michal Linial

AbstractIt is estimated that up to 10% of cancer incidents are attributed to inherited genetic alterations. Despite extensive research, there are still gaps in our understanding of genetic predisposition to cancer. It was theorized that ultra-rare variants partially account for the missing heritable component. We harness the UK BioBank dataset of ∼500,000 individuals, 14% of which were diagnosed with cancer, to detect ultra-rare, possibly high-penetrance cancer predisposition variants. We report on 115 cancer-exclusive ultra-rare variations (CUVs) and nominate 26 variants with additional independent evidence as cancer predisposition variants. We conclude that population cohorts are valuable source for expanding the collection of novel cancer predisposition genes.

2021 ◽  
Author(s):  
Abhishek Nag ◽  
Lawrence Middleton ◽  
Ryan S Dhindsa ◽  
Dimitrios Vitsios ◽  
Eleanor M Wigmore ◽  
...  

Genome-wide association studies have established the contribution of common and low frequency variants to metabolic biomarkers in the UK Biobank (UKB); however, the role of rare variants remains to be assessed systematically. We evaluated rare coding variants for 198 metabolic biomarkers, including metabolites assayed by Nightingale Health, using exome sequencing in participants from four genetically diverse ancestries in the UKB (N=412,394). Gene-level collapsing analysis, that evaluated a range of genetic architectures, identified a total of 1,303 significant relationships between genes and metabolic biomarkers (p<1x10-8), encompassing 207 distinct genes. These include associations between rare non-synonymous variants in GIGYF1 and glucose and lipid biomarkers, SYT7 and creatinine, and others, which may provide insights into novel disease biology. Comparing to a previous microarray-based genotyping study in the same cohort, we observed that 40% of gene-biomarker relationships identified in the collapsing analysis were novel. Finally, we applied Gene-SCOUT, a novel tool that utilises the gene-biomarker association statistics from the collapsing analysis to identify genes having similar biomarker fingerprints and thus expand our understanding of gene networks.


2020 ◽  
Author(s):  
David Curtis

Rare genetic variants in LDLR, APOB and PCSK9 are known causes of familial hypercholesterolaemia and it is expected that rare variants in other genes will also have effects on hyperlipidaemia risk although such genes remain to be identified. The UK Biobank consists of a sample of 500,000 volunteers and exome sequence data is available for 50,000 of them. 11,490 of these were classified as hyperlipidaemia cases on the basis of having a relevant diagnosis recorded and/or taking lipid-lowering medication while the remaining 38,463 were treated as controls. Variants in each gene were assigned weights according to rarity and predicted impact and overall weighted burden scores were compared between cases and controls, including population principal components as covariates. One biologically plausible gene, HUWE1, produced statistically significant evidence for association after correction for testing 22,028 genes with a signed log10 p value (SLP) of -6.15, suggesting a protective effect of variants in this gene. Other genes with uncorrected p<0.001 are arguably also of interest, including LDLR (SLP=3.67), RBP2 (SLP=3.14), NPFFR1 (SLP=3.02) and ACOT9 (SLP=-3.19). Gene set analysis indicated that rare variants in genes involved in metabolism and energy can influence hyperlipidaemia risk. Overall, the results provide some leads which might be followed up with functional studies and which could be tested in additional data sets as these become available. This research has been conducted using the UK Biobank Resource.


BMJ ◽  
2019 ◽  
pp. l4410 ◽  
Author(s):  
Agustin Cerani ◽  
Sirui Zhou ◽  
Vincenzo Forgetta ◽  
John A Morris ◽  
Katerina Trajanoska ◽  
...  

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.


2019 ◽  
Vol 21 (11) ◽  
pp. 1376-1388 ◽  
Author(s):  
Ivo S Muskens ◽  
Chenan Zhang ◽  
Adam J de Smith ◽  
Jaclyn A Biegel ◽  
Kyle M Walsh ◽  
...  

AbstractCentral nervous system (CNS) tumors are the second most common type of cancer among children. Depending on histopathology, anatomic location, and genomic factors, specific subgroups of brain tumors have some of the highest cancer-related mortality rates or result in considerable lifelong morbidity. Pediatric CNS tumors often occur in patients with genetic predisposition, at times revealing underlying cancer predisposition syndromes. Advances in next-generation sequencing (NGS) have resulted in the identification of an increasing number of cancer predisposition genes. In this review, the literature on genetic predisposition to pediatric CNS tumors is evaluated with a discussion of potential future targets for NGS and clinical implications. Furthermore, we explore potential strategies for enhancing the understanding of genetic predisposition of pediatric CNS tumors, including evaluation of non-European populations, pan-genomic approaches, and large collaborative studies.


2016 ◽  
Vol 37 (4) ◽  
pp. 331-336 ◽  
Author(s):  
Setareh Moghadasi ◽  
Diana M. Eccles ◽  
Peter Devilee ◽  
Maaike P.G. Vreeswijk ◽  
Christi J. van Asperen

2020 ◽  
Vol 41 (35) ◽  
pp. 3304-3310 ◽  
Author(s):  
Susanna C Larsson ◽  
Amy M Mason ◽  
Magnus Bäck ◽  
Derek Klarin ◽  
Scott M Damrauer ◽  
...  

Abstract Aims The aim of this study was to use Mendelian randomization (MR) to determine the causality of the association between smoking and 14 different cardiovascular diseases (CVDs). Methods and results Our primary genetic instrument comprised 361 single-nucleotide polymorphisms (SNPs) associated with smoking initiation (ever smoked regularly) at genome-wide significance. Data on the associations between the SNPs and 14 CVDs were obtained from the UK Biobank study (N = 367 643 individuals), CARDIoGRAMplusC4D consortium (N = 184 305 individuals), Atrial Fibrillation Consortium (2017 dataset; N = 154 432 individuals), and Million Veteran Program (MVP; N = 190 266 individuals). The main analyses were conducted using the random-effects inverse-variance weighted method and complemented with multivariable MR analyses and the weighted median and MR-Egger approaches. Genetic predisposition to smoking initiation was most strongly and consistently associated with higher odds of coronary artery disease, heart failure, abdominal aortic aneurysm, ischaemic stroke, transient ischaemic attack, peripheral arterial disease, and arterial hypertension. Genetic predisposition to smoking initiation was additionally associated with higher odds of deep vein thrombosis and pulmonary embolism in the UK Biobank but not with venous thromboembolism in the MVP. There was limited evidence of causal associations of smoking initiation with atrial fibrillation, aortic valve stenosis, thoracic aortic aneurysm, and intracerebral and subarachnoid haemorrhage. Conclusion This MR study supports a causal association between smoking and a broad range of CVDs, in particular, coronary artery disease, heart failure, abdominal aortic aneurysm, ischaemic stroke, transient ischaemic attack, peripheral arterial disease, and arterial hypertension.


2021 ◽  
Vol 5 (Supplement_2) ◽  
pp. 1090-1090
Author(s):  
Christina-Alexandra Schulz ◽  
Leonie Weinhold ◽  
Matthias Schmid ◽  
Ute Nöthlings ◽  
Marcus M Nöthen

Abstract Objectives Elucidating the role of dietary intake in cognitive function, and neurodegenerative disease development is important for prevention. The Mediterranean diet has shown to be beneficial for cognitive function and prevention of neurodegenerative disease. Yet, evidence for other dietary patterns are inconclusive. Since heritability of cognitive functions is substantial, a beneficial diet might mitigate genetic disposition. Therefore, we investigate if dietary patterns are associated with general cognitive function, considering individual genetic disposition. This research has been conducted using the UK Biobank Resource. Methods At baseline, participants reported the frequency of consumption of main foods via a dietary touchscreen questionnaire and filled in a verbal-numerical reasoning (VNR) test, which measures fluid intelligence. A diet score including 7 components: vegetables, fruit, fish, processed meat, unprocessed meat, whole grain, and refined grain was constructed. Participants were categorized into a low (0–1), intermediate (2–5), and high (6–7) diet score. A polygenic score (PGS), previously associated in GWAS with general cognitive function, was constructed. Participants were categorized into low (Quintile 1), intermediate (Q 2–4), and high (Q 5) PGS group. Linear regression was used to test whether the diet score associates with fluid intelligence, and to test if genetic predisposition modifies the association. Results The mean diet score of the 104,898 participants (46% male, mean age 57.1 (SD 8.0) years) was 3.9 (SD 1.4) points. In the VNR-test on average 6.1 (SD 2.1) questions were answered correctly. After multivariate adjustment a positive association between fluid intelligence and the PGS (P &lt; 0.001), but no association between fluid intelligence and the diet score (P = 0.703) was observed. When stratified according to PGS groups, similar results were observed for the association between fluid intelligence and the diet score. Conclusions No evidence was found that the investigated diet score was associated with fluid intelligence. As previously reported, genetic disposition was strongly associated with cognitive performance. Funding Sources This work was partly supported by Diet–Body–Brain (DietBB), the Competence Cluster in Nutrition Research funded by the Federal Ministry of Education and Research (FKZ: 01EA1410A).


2020 ◽  
Author(s):  
Quanli Wang ◽  
Ryan S. Dhindsa ◽  
Keren Carss ◽  
Andrew R Harper ◽  
Abhishek Nag ◽  
...  

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.


Author(s):  
David Curtis

AbstractIt is plausible that variants in the ACE2 and TMPRSS2 genes might contribute to variation in COVID-19 severity and that these could explain why some people become very unwell whereas most do not. Exome sequence data was obtained for 49,953 UK Biobank subjects of whom 74 had tested positive for SARS-CoV-2 and could be presumed to have severe disease. A weighted burden analysis was carried out using SCOREASSOC to determine whether there were differences between these cases and the other sequenced subjects in the overall burden of rare, damaging variants in ACE2 or TMPRSS2. There were no statistically significant differences in weighted burden scores between cases and controls for either gene. There were no individual DNA sequence variants with a markedly different frequency between cases and controls. Whether there are small effects on severity, or whether there might be rare variants with major effect sizes, would require studies in much larger samples. Genetic variants affecting the structure and function of the ACE2 and TMPRSS2 proteins are not a major determinant of whether infection with SARS-CoV-2 results in severe symptoms. This research has been conducted using the UK Biobank Resource.


2021 ◽  
Author(s):  
David Curtis

AbstractIntroductionA number of genes have been identified in which rare variants can cause obesity. Here we analyse a sample of exome sequenced subjects from UK Biobank using BMI as a phenotype.MethodsThere were 199,807 exome sequenced subjects for whom BMI was recorded. Weighted burden analysis of rare, functional variants was carried out, incorporating population principal components and sex as covariates. For selected genes, additional analyses were carried out to clarify the contribution of different categories of variant. Statistical significance was summarised as the signed log 10 of the p value (SLP), given a positive sign if the weighted burden score was positively correlated with BMI.ResultsTwo genes were exome-wide significant, MC4R (SLP = 15.79) and PCSK1 (SLP = 6.61). In MC4R, disruptive variants were associated with an increase in BMI of 2.72 units and probably damaging nonsynonymous variants with an increase of 2.02 units. In PCSK1, disruptive variants were associated with a BMI increase of 2.29 and protein-altering variants with an increase of 0.34. Results for other genes were not formally significant after correction for multiple testing, although SIRT1, ZBED6 and NPC2 were noted to be of potential interest.ConclusionBecause the UK Biobank consists of a self-selected sample of relatively healthy volunteers, the effect sizes noted may be underestimates. The results demonstrate the effects of very rare variants on BMI and suggest that other genes and variants will be definitively implicated when the sequence data for additional subjects becomes available.This research has been conducted using the UK Biobank Resource.


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