scholarly journals Assessing the Relationship Between Leukocyte Telomere Length and Cancer Risk/Mortality in UK Biobank and TCGA Datasets With the Genetic Risk Score and Mendelian Randomization Approaches

2020 ◽  
Vol 11 ◽  
Author(s):  
Yixin Gao ◽  
Yongyue Wei ◽  
Xiang Zhou ◽  
Shuiping Huang ◽  
Huashuo Zhao ◽  
...  
Keyword(s):  
Cancer Risk ◽  
Telomere Length ◽  
Risk Score ◽  
Genetic Risk ◽  
Mendelian Randomization ◽  
Genetic Risk Score ◽  
Leukocyte Telomere Length ◽  
Uk Biobank ◽  
The Relationship

scholarly journals Using genetics to understand the causal influence of higher BMI on depression

2018 ◽  
Vol 48 (3) ◽  
pp. 834-848 ◽  
Author(s):  
Jessica Tyrrell ◽  
Anwar Mulugeta ◽  
Andrew R Wood ◽  
Ang Zhou ◽  
Robin N Beaumont ◽  
...  
Keyword(s):  
Risk Score ◽  
Genetic Risk ◽  
Mendelian Randomization ◽  
Genetic Risk Score ◽  
Self Report ◽  
Uk Biobank ◽  
Men And Women ◽  
Statistical Confidence ◽  
The Uk ◽  
Genetically Determined

Abstract Background Depression is more common in obese than non-obese individuals, especially in women, but the causal relationship between obesity and depression is complex and uncertain. Previous studies have used genetic variants associated with BMI to provide evidence that higher body mass index (BMI) causes depression, but have not tested whether this relationship is driven by the metabolic consequences of BMI nor for differences between men and women. Methods We performed a Mendelian randomization study using 48 791 individuals with depression and 291 995 controls in the UK Biobank, to test for causal effects of higher BMI on depression (defined using self-report and Hospital Episode data). We used two genetic instruments, both representing higher BMI, but one with and one without its adverse metabolic consequences, in an attempt to ‘uncouple’ the psychological component of obesity from the metabolic consequences. We further tested causal relationships in men and women separately, and using subsets of BMI variants from known physiological pathways. Results Higher BMI was strongly associated with higher odds of depression, especially in women. Mendelian randomization provided evidence that higher BMI partly causes depression. Using a 73-variant BMI genetic risk score, a genetically determined one standard deviation (1 SD) higher BMI (4.9 kg/m2) was associated with higher odds of depression in all individuals [odds ratio (OR): 1.18, 95% confidence interval (CI): 1.09, 1.28, P = 0.00007) and women only (OR: 1.24, 95% CI: 1.11, 1.39, P = 0.0001). Meta-analysis with 45 591 depression cases and 97 647 controls from the Psychiatric Genomics Consortium (PGC) strengthened the statistical confidence of the findings in all individuals. Similar effect size estimates were obtained using different Mendelian randomization methods, although not all reached P < 0.05. Using a metabolically favourable adiposity genetic risk score, and meta-analysing data from the UK biobank and PGC, a genetically determined 1 SD higher BMI (4.9 kg/m2) was associated with higher odds of depression in all individuals (OR: 1.26, 95% CI: 1.06, 1.50], P = 0.010), but with weaker statistical confidence. Conclusions Higher BMI, with and without its adverse metabolic consequences, is likely to have a causal role in determining the likelihood of an individual developing depression.

scholarly journals Mendelian randomization provides evidence for a causal effect of higher serum IGF-1 concentration on risk of hip and knee osteoarthritis

Rheumatology ◽  
2020 ◽  
Author(s):  
April Hartley ◽  
Eleanor Sanderson ◽  
Lavinia Paternoster ◽  
Alexander Teumer ◽  
Robert C Kaplan ◽  
...  
Keyword(s):  
Risk Score ◽  
Genetic Risk ◽  
Odds Ratio ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Genetic Risk Score ◽  
Uk Biobank ◽  
Knee Oa ◽  
Increased Risk

Abstract Objectives How insulin-like growth factor-1 (IGF-1) is related to OA is not well understood. We determined relationships between IGF-1 and hospital-diagnosed hand, hip and knee OA in UK Biobank, using Mendelian randomization (MR) to determine causality. Methods Serum IGF-1 was assessed by chemiluminescent immunoassay. OA was determined using Hospital Episode Statistics. One-sample MR (1SMR) was performed using two-stage least-squares regression, with an unweighted IGF-1 genetic risk score as an instrument. Multivariable MR included BMI as an additional exposure (instrumented by BMI genetic risk score). MR analyses were adjusted for sex, genotyping chip and principal components. We then performed two-sample MR (2SMR) using summary statistics from Cohorts for Heart and Aging Research in Genetic Epidemiology (CHARGE) (IGF-1, N = 30 884) and the recent genome-wide association study meta-analysis (N = 455 221) of UK Biobank and Arthritis Research UK OA Genetics (arcOGEN). Results A total of 332 092 adults in UK Biobank had complete data. Their mean (s.d.) age was 56.5 (8.0) years and 54% were female. IGF-1 was observationally related to a reduced odds of hand OA [odds ratio per doubling = 0.87 (95% CI 0.82, 0.93)], and an increased odds of hip OA [1.04 (1.01, 1.07)], but was unrelated to knee OA [0.99 (0.96, 1.01)]. Using 1SMR, we found strong evidence for an increased risk of hip [odds ratio per s.d. increase = 1.57 (1.21, 2.01)] and knee [1.30 (1.07, 1.58)] OA with increasing IGF-1 concentration. By contrast, we found no evidence for a causal effect of IGF-1 concentration on hand OA [0.98 (0.57, 1.70)]. Results were consistent when estimated using 2SMR and in multivariable MR analyses accounting for BMI. Conclusion We have found evidence that increased serum IGF-1 is causally related to higher risk of hip and knee OA.

Abstract 1288: Telomere length genetic risk score is associated with breast cancer risk

2017 ◽  
Author(s):  
Laurie Grieshober ◽  
Jean Wactawski-Wende ◽  
Rachael Hageman Blair ◽  
Lina Mu ◽  
Leah Preus ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Telomere Length ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Risk Score

Mendelian Randomization Focused Analysis of Vitamin D on the Secondary Prevention of Ischemic Stroke

Stroke ◽  
2021 ◽  
Author(s):  
Yap-Hang Chan ◽  
C. Mary Schooling ◽  
Jie Zhao ◽  
Shiu-Lun Au Yeung ◽  
Jo Jo Hai ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Vitamin D ◽  
Ischemic Stroke ◽  
Risk Score ◽  
Genetic Risk ◽  
Odds Ratio ◽  
Mendelian Randomization ◽  
De Novo ◽  
Genetic Risk Score ◽  
Ischemic Disease

Background and Purpose: Experimental studies showed vitamin D (Vit-D) could promote vascular regeneration and repair. Prior randomized studies had focused mainly on primary prevention. Whether Vit-D protects against ischemic stroke and myocardial infarction recurrence among subjects with prior ischemic insults was unknown. Here, we dissected through Mendelian randomization any effect of Vit-D on the secondary prevention of recurrent ischemic stroke and myocardial infarction. Methods: Based on a genetic risk score for Vit-D constructed from a derivation cohort sample (n=5331, 45% Vit-D deficient, 89% genotyped) via high-throughput exome-chip screening of 12 prior genome-wide association study–identified genetic variants of Vit-D mechanistic pathways ( rs2060793 , rs4588 , and rs7041 ; F statistic, 73; P <0.001), we performed a focused analysis on prospective recurrence of myocardial infarction (MI) and ischemic stroke in an independent subsample with established ischemic disease (n=441, all with prior first ischemic event; follow-up duration, 41.6±14.3 years) under a 2-sample, individual-data, prospective Mendelian randomization approach. Results: In the ischemic disease subsample, 11.1% (n=49/441) had developed recurrent ischemic stroke or MI and 13.3% (n=58/441) had developed recurrent or de novo ischemic stroke/MI. Kaplan-Meier analyses showed that genetic risk score predicted improved event-free survival from recurrent ischemic stroke or MI (log-rank, 13.0; P =0.001). Cox regression revealed that genetic risk score independently predicted reduced risk of recurrent ischemic stroke or MI combined (hazards ratio, 0.62 [95% CI, 0.48–0.81]; P <0.001), after adjusted for potential confounders. Mendelian randomization supported that Vit-D is causally protective against the primary end points of recurrent ischemic stroke or MI (Wald estimate: odds ratio, 0.55 [95% CI, 0.35–0.81]) and any recurrent or de novo ischemic stroke/MI (odds ratio, 0.64 [95% CI, 0.42–0.91]) and recurrent MI alone (odds ratio, 0.52 [95% CI, 0.30–0.81]). Conclusions: Genetically predicted lowering in Vit-D level is causal for the recurrence of ischemic vascular events in persons with prior ischemic stroke or MI.

scholarly journals Strongly enhanced colorectal cancer risk stratification by combining family history and genetic risk score

2018 ◽  
Vol Volume 10 ◽  
pp. 143-152 ◽  
Author(s):  
Korbinian Weigl ◽  
Jenny Chang-Claude ◽  
Phillip Knebel ◽  
Li Hsu ◽  
Michael Hoffmeister ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Family History ◽  
Cancer Risk ◽  
Risk Stratification ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Colorectal Cancer Risk

Evaluating the effect of multiple genetic risk score models on colorectal cancer risk prediction

Gene ◽  
2018 ◽  
Vol 673 ◽  
pp. 174-180 ◽  
Author(s):  
Junyi Xin ◽  
Haiyan Chu ◽  
Shuai Ben ◽  
Yuqiu Ge ◽  
Wei Shao ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cancer Risk ◽  
Risk Prediction ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Colorectal Cancer Risk

scholarly journals Long Leukocyte Telomere Length Is Associated with Increased Risks of Soft Tissue Sarcoma: A Mendelian Randomization Study

Cancers ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 594 ◽  
Author(s):  
Yifan Xu ◽  
Junfeng Xu ◽  
Haidee Chancoco ◽  
Maosheng Huang ◽  
Keila E. Torres ◽  
...  
Keyword(s):  
Soft Tissue ◽  
Soft Tissue Sarcoma ◽  
Telomere Length ◽  
Mendelian Randomization ◽  
Genetic Risk Score ◽  
Leukocyte Telomere Length ◽  
Nucleotide Polymorphisms ◽  
Individual Snps ◽  
Increased Risk ◽  
Weighted Genetic Risk Score

Background: Leukocyte telomere length (LTL) has been associated with the risks of several cancers in observational studies. Mendelian randomization (MR) studies, using genetic variants as instrumental variables, have also shown associations of genetically predicted LTL with cancer risks. In this study, we performed the first MR analysis on soft tissue sarcoma (STS) to investigate the causal relationship between LTL and the risk of STS. Methods: Genotypes from eleven LTL-associated single nucleotide polymorphisms (SNPs) in 821 STS cases and 851 cancer-free controls were aggregated into a weighted genetic risk score (GRS) to predict LTL. Multivariate logistic regression was used to assess the association of STS risk with individual SNPs and aggregated GRS. Results: Four SNPs displayed evidence for an individual association between long LTL-conferring allele and increased STS risk: rs7675998 (odds ratio (OR) = 1.21, 95% confidence interval (CI) = 1.02–1.43), rs9420907 (OR = 1.31, 95% CI = 1.08–1.59), rs8105767 (OR = 1.18, 95% CI = 1.02–1.37), and rs412658 (OR = 1.18, 95% CI = 1.02–1.36). Moreover, longer genetically predicted LTL, calculated as GRS, was strongly associated with an increased risk of STS (OR = 1.44, 95% CI = 1.18–1.75, p < 0.001), and there was a significant dose-response association (p for trend <0.001 in tertile and quartile analyses). The association of longer LTL with higher STS risk was more evident in women than in men. In stratified analyses by major STS subtypes, longer LTL was significantly associated with higher risks of leiomyosarcoma and gastrointestinal stromal tumors. Conclusions: Longer LTL is associated with increased risks of STS.

scholarly journals Genetic Risk Score for Predicting Schizophrenia Using Human Chromosomal-Scale Length Variation

2021 ◽  
Author(s):  
Christopher Toh ◽  
James P. Brody
Keyword(s):  
Risk Score ◽  
Genetic Risk ◽  
Germ Line ◽  
Genetic Risk Score ◽  
Single Gene ◽  
Characteristic Curve ◽  
Machine Learning Algorithms ◽  
Length Variation ◽  
Uk Biobank ◽  
Scale Length

Abstract Studies indicate that schizophrenia has a genetic component, however it cannot be isolated to a single gene. We aimed to determine how well one could predict that a person will develop schizophrenia based on their germ line genetics. We compared 1129 people from the UK Biobank dataset who had a diagnosis of schizophrenia to an equal number of age matched people drawn from the general UK Biobank population. For each person, we constructed a profile consisting of numbers. Each number characterized the length of segments of chromosomes. We tested several machine learning algorithms to determine which was most effective in predicting schizophrenia and if any improvement in prediction occurs by breaking the chromosomes into smaller chunks. We found that the stacked ensemble, performed best with an area under the receiver operating characteristic curve (AUC) of 0.545 (95% CI 0.539-0.550). We noted an increase in the AUC by breaking the chromosomes into smaller chunks for analysis. Using SHAP values, we identified the X chromosome as the most important contributor to the predictive model. We conclude that germ line chromosomal scale length variation data could provide an effective genetic risk score for schizophrenia which performs better than chance.

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