scholarly journals Heterozygous PRKN mutations are common but do not increase the risk of Parkinson's disease

2021 ◽  
Author(s):  
William Zhu ◽  
Xiaoping Huang ◽  
Esther Yoon ◽  
Sara P Bandres Ciga ◽  
Cornelis Blauwendraat ◽  
...  
Keyword(s):  
Disease Risk ◽  
Cost Effective ◽  
P Value ◽  
Nucleotide Polymorphisms ◽  
Uk Biobank ◽  
Loss Of Function ◽  
Genotyping Array ◽  
Array Data ◽  
Population Scale ◽  
The Uk

PRKN mutations are the most common recessive cause of Parkinson′s disease (PD) and are a promising target for gene and cell replacement therapies. Identification of biallelic PRKN patients (PRKN-PD) at the population scale, however, remains a challenge, as roughly half are copy number variants (CNVs) and many single nucleotide polymorphisms (SNPs) are of unclear significance. Additionally, the true prevalence and disease risk associated with heterozygous PRKN mutations is unclear, as a comprehensive assessment of PRKN SNPs and CNVs has not been performed at a population scale. To address these challenges, we evaluated PRKN mutations in 2 cohorts analyzed with both a genotyping array and exome or genome sequencing: the NIH PD cohort, a deeply phenotyped cohort of PD patients, and the UK Biobank, a population scale cohort with nearly half a million participants. Genotyping array identified the majority of PRKN mutations and at least 1 mutation in most biallelic PRKN mutation carriers in both cohorts. Additionally, in the NIH PD cohort, functional assays of patient fibroblasts resolved variants of unclear significance in biallelic carriers and ruled out cryptic loss of function variants in monoallelic carriers. In the UK Biobank, we identified 2,692 PRKN CNVs from genotyping array data from nearly half a million participants (the largest collection to date). Deletions or duplications involving exons 2 accounted for roughly half of all CNVs and the vast majority (88%) involved exons 2, 3, or 4. Combining estimates from whole exome sequencing (from ~200,000 participants) and genotyping array data, we found a pathogenic PRKN mutation in 1.8% of participants and 2 mutations in ~1/7,800 participants. Those with 1 PRKN pathogenic variant were as likely as non-carriers to have PD (OR = 0.91, CI= 0.58 – 1.38, p-value = 0.76) or a parent with PD (OR = 1.12, CI = 0.94 – 1.31, p-value = 0.19). Together our results demonstrate that heterozygous pathogenic PRKN mutations are common in the population but do not increase the risk of PD. Additionally, they suggest a cost-effective framework to screen for biallelic PRKN patients at the population scale for targeted studies.

scholarly journals Machine Learning Prediction of Biomarkers from SNPs and of Disease Risk from Biomarkers in the UK Biobank

Genes ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 991
Author(s):  
Erik Widen ◽  
Timothy G. Raben ◽  
Louis Lello ◽  
Stephen D. H. Hsu
Keyword(s):  
Disease Risk ◽  
Smoking Status ◽  
Glycated Haemoglobin ◽  
European Ancestry ◽  
Risk Scores ◽  
Common Disease ◽  
Atherosclerotic Cardiovascular Disease ◽  
Uk Biobank ◽  
Lipoprotein A ◽  
The Uk

We use UK Biobank data to train predictors for 65 blood and urine markers such as HDL, LDL, lipoprotein A, glycated haemoglobin, etc. from SNP genotype. For example, our Polygenic Score (PGS) predictor correlates ∼0.76 with lipoprotein A level, which is highly heritable and an independent risk factor for heart disease. This may be the most accurate genomic prediction of a quantitative trait that has yet been produced (specifically, for European ancestry groups). We also train predictors of common disease risk using blood and urine biomarkers alone (no DNA information); we call these predictors biomarker risk scores, BMRS. Individuals who are at high risk (e.g., odds ratio of >5× population average) can be identified for conditions such as coronary artery disease (AUC∼0.75), diabetes (AUC∼0.95), hypertension, liver and kidney problems, and cancer using biomarkers alone. Our atherosclerotic cardiovascular disease (ASCVD) predictor uses ∼10 biomarkers and performs in UKB evaluation as well as or better than the American College of Cardiology ASCVD Risk Estimator, which uses quite different inputs (age, diagnostic history, BMI, smoking status, statin usage, etc.). We compare polygenic risk scores (risk conditional on genotype: PRS) for common diseases to the risk predictors which result from the concatenation of learned functions BMRS and PGS, i.e., applying the BMRS predictors to the PGS output.

scholarly journals A population scale analysis of rare SNCA variation in the UK Biobank

2021 ◽  
Vol 148 ◽  
pp. 105182
Author(s):  
Cornelis Blauwendraat ◽  
Mary B. Makarious ◽  
Hampton L. Leonard ◽  
Sara Bandres-Ciga ◽  
Hirotaka Iwaki ◽  
...  
Keyword(s):  
Scale Analysis ◽  
Uk Biobank ◽  
Population Scale ◽  
The Uk

scholarly journals Prevalence and cardiometabolic correlates of ketohexokinase gene variants among UK Biobank participants

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0247683
Author(s):  
Joseph A. Johnston ◽  
David R. Nelson ◽  
Pallav Bhatnagar ◽  
Sarah E. Curtis ◽  
Yu Chen ◽  
...  
Keyword(s):  
Autosomal Recessive ◽  
Compound Heterozygous ◽  
Gene Variants ◽  
Uk Biobank ◽  
Loss Of Function ◽  
Recessive Condition ◽  
Clinical Consequences ◽  
Autosomal Recessive Condition ◽  
Clinically Significant ◽  
The Uk

Essential fructosuria (EF) is a benign, asymptomatic, autosomal recessive condition caused by loss-of-function variants in the ketohexokinase gene and characterized by intermittent appearance of fructose in the urine. Despite a basic understanding of the genetic and molecular basis of EF, relatively little is known about the long-term clinical consequences of ketohexokinase gene variants. We examined the frequency of ketohexokinase variants in the UK Biobank sample and compared the cardiometabolic profiles of groups of individuals with and without these variants alone or in combination. Study cohorts consisted of groups of participants defined based on the presence of one or more of the five ketohexokinase gene variants tested for in the Affymetrix assays used by the UK Biobank. The rs2304681:G>A (p.Val49Ile) variant was present on more than one-third (36.8%) of chromosomes; other variant alleles were rare (<1%). No participants with the compound heterozygous genotype present in subjects exhibiting the EF phenotype in the literature (Gly40Arg/Ala43Thr) were identified. The rs2304681:G>A (p.Val49Ile), rs41288797 (p.Val188Met), and rs114353144 (p.Val264Ile) variants were more common in white versus non-white participants. Otherwise, few statistically or clinically significant differences were observed after adjustment for multiple comparisons. These findings reinforce the current understanding of EF as a rare, benign, autosomal recessive condition.

scholarly journals Development and Validation of a Novel Dementia Risk Score in the UK Biobank Cohort

2021 ◽  
Author(s):  
Melis Anatürk ◽  
Raihaan Patel ◽  
Georgios Georgiopoulos ◽  
Danielle Newby ◽  
Anya Topiwala ◽  
...  
Keyword(s):  
At Risk ◽  
Cardiovascular Risk ◽  
Risk Score ◽  
Disease Risk ◽  
Risk Index ◽  
Risk Scores ◽  
Uk Biobank ◽  
Dementia Risk ◽  
History Of ◽  
The Uk

INTRODUCTION: Current prognostic models of dementia have had limited success in consistently identifying at-risk individuals. We aimed to develop and validate a novel dementia risk score (DRS) using the UK Biobank cohort.METHODS: After randomly dividing the sample into a training (n=166,487, 80%) and test set (n=41,621, 20%), logistic LASSO regression and standard logistic regression were used to develop the UKB-DRS.RESULTS: The score consisted of age, sex, education, apolipoprotein E4 genotype, a history of diabetes, stroke, and depression, and a family history of dementia. The UKB-DRS had good-to-strong discrimination accuracy in the UKB hold-out sample (AUC [95%CI]=0.79 [0.77, 0.82]) and in an external dataset (Whitehall II cohort, AUC [95%CI]=0.83 [0.79,0.87]). The UKB-DRS also significantly outperformed four published risk scores (i.e., Australian National University Alzheimer’s Disease Risk Index (ANU-ADRI), Cardiovascular Risk Factors, Aging, and Dementia score (CAIDE), Dementia Risk Score (DRS), and the Framingham Cardiovascular Risk Score (FRS) across both test sets.CONCLUSION: The UKB-DRS represents a novel easy-to-use tool that could be used for routine care or targeted selection of at-risk individuals into clinical trials.

scholarly journals Reproducibility in the UK Biobank of Genome-Wide Significant Signals Discovered in Earlier Genome-wide Association Studies

2020 ◽  
Author(s):  
Jack W. O’Sullivan ◽  
John P. A. Ioannidis
Keyword(s):  
Effect Size ◽  
Association Studies ◽  
Genome Wide Association ◽  
P Value ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Single Nucleotide ◽  
Genome Wide ◽  
The Uk ◽  
Open Question

AbstractWith the establishment of large biobanks, discovery of single nucleotide polymorphism (SNPs) that are associated with various phenotypes has been accelerated. An open question is whether SNPs identified with genome-wide significance in earlier genome-wide association studies (GWAS) are replicated also in later GWAS conducted in biobanks. To address this question, the authors examined a publicly available GWAS database and identified two, independent GWAS on the same phenotype (an earlier, “discovery” GWAS and a later, replication GWAS done in the UK biobank). The analysis evaluated 136,318,924 SNPs (of which 6,289 had reached p<5e-8 in the discovery GWAS) from 4,397,962 participants across nine phenotypes. The overall replication rate was 85.0% and it was lower for binary than for quantitative phenotypes (58.1% versus 94.8% respectively). There was a18.0% decrease in SNP effect size for binary phenotypes, but a 12.0% increase for quantitative phenotypes. Using the discovery SNP effect size, phenotype trait (binary or quantitative), and discovery p-value, we built and validated a model that predicted SNP replication with area under the Receiver Operator Curve = 0.90. While non-replication may often reflect lack of power rather than genuine false-positive findings, these results provide insights about which discovered associations are likely to be seen again across subsequent GWAS.

scholarly journals Analysis of exome-sequenced UK Biobank subjects implicates genes affecting risk of hyperlipidaemia

2020 ◽  
Author(s):  
David Curtis
Keyword(s):  
Rare Variants ◽  
Sequence Data ◽  
Lipid Lowering ◽  
P Value ◽  
Data Sets ◽  
Uk Biobank ◽  
Functional Studies ◽  
Exome Sequence Data ◽  
Rare Genetic Variants ◽  
The Uk

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.

scholarly journals The Validity and Value of Self-reported Physical Activity and Accelerometry in People With Schizophrenia: A Population-Scale Study of the UK Biobank

2017 ◽  
Vol 44 (6) ◽  
pp. 1293-1300 ◽  
Author(s):  
Joseph Firth ◽  
Brendon Stubbs ◽  
Davy Vancampfort ◽  
Felipe B Schuch ◽  
Simon Rosenbaum ◽  
...  
Keyword(s):  
Physical Activity ◽  
Uk Biobank ◽  
Population Scale ◽  
The Uk

scholarly journals Polygenic Hyperlipidemia Increases Coronary Artery Disease Risk In The Uk Biobank

2019 ◽  
Vol 287 ◽  
pp. e92
Author(s):  
P. Ripatti ◽  
J.T. Rämö ◽  
S. Söderlund ◽  
I. Surakka ◽  
A.S. Havulinna ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Disease Risk ◽  
Coronary Artery Disease Risk ◽  
Uk Biobank ◽  
Artery Disease ◽  
The Uk

scholarly journals MassARRAY-based single nucleotide polymorphism analysis in breast cancer of north Indian population

BMC Cancer ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Divya Bakshi ◽  
Ashna Nagpal ◽  
Varun Sharma ◽  
Indu Sharma ◽  
Ruchi Shah ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Mutations ◽  
Cost Effective ◽  
P Value ◽  
Polymorphism Analysis ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Cost Effective Method ◽  
Common Genetic Variants ◽  
Underlying Causes

Abstract Background Breast Cancer (BC) is associated with inherited gene mutations. High throughput genotyping of BC samples has led to the identification and characterization of biomarkers for the diagnosis of BC. The most common genetic variants studied are SNPs (Single Nucleotide Polymorphisms) that determine susceptibility to an array of diseases thus serving as a potential tool for identifying the underlying causes of breast carcinogenesis. Methods SNP genotyping employing the Agena MassARRAY offers a robust, sensitive, cost-effective method to assess multiple SNPs and samples simultaneously. In this present study, we analyzed 15 SNPs of 14 genes in 550 samples (150 cases and 400 controls). We identified four SNPs of genes TCF21, SLC19A1, DCC, and ERCC1 showing significant association with BC in the population under study. Results The SNPs were rs12190287 (TCF21) having OR 1.713 (1.08–2.716 at 95% CI) p-value 0.022 (dominant), rs1051266 (SLC19A1) having OR 3.461 (2.136–5.609 at 95% CI) p-value 0.000000466 (dominant), rs2229080 (DCC) having OR 0.6867 (0.5123–0.9205 at 95% CI) p-value 0.0116 (allelic) and rs2298881 (ERCC1) having OR 0.669 (0.46–0.973 at 95% CI), p-value 0.035 (additive) respectively. The in-silico analysis was further used to fortify the above findings. Conclusion It is further anticipated that the variants should be evaluated in other population groups that may aid in understanding the genetic complexity and bridge the missing heritability.

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