scholarly journals Using multiple genetic variants as instrumental variables for modifiable risk factors

2011 ◽  
Vol 21 (3) ◽  
pp. 223-242 ◽  
Author(s):  
Tom M Palmer ◽  
Debbie A Lawlor ◽  
Roger M Harbord ◽  
Nuala A Sheehan ◽  
Jon H Tobias ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Missing Data ◽  
Instrumental Variables ◽  
Genetic Variants ◽  
Association Studies ◽  
Mendelian Randomisation ◽  
Modifiable Risk Factors ◽  
Genome Wide Association Studies ◽  
Finite Sample

Mendelian randomisation analyses use genetic variants as instrumental variables (IVs) to estimate causal effects of modifiable risk factors on disease outcomes. Genetic variants typically explain a small proportion of the variability in risk factors; hence Mendelian randomisation analyses can require large sample sizes. However, an increasing number of genetic variants have been found to be robustly associated with disease-related outcomes in genome-wide association studies. Use of multiple instruments can improve the precision of IV estimates, and also permit examination of underlying IV assumptions. We discuss the use of multiple genetic variants in Mendelian randomisation analyses with continuous outcome variables where all relationships are assumed to be linear. We describe possible violations of IV assumptions, and how multiple instrument analyses can be used to identify them. We present an example using four adiposity-associated genetic variants as IVs for the causal effect of fat mass on bone density, using data on 5509 children enrolled in the ALSPAC birth cohort study. We also use simulation studies to examine the effect of different sets of IVs on precision and bias. When each instrument independently explains variability in the risk factor, use of multiple instruments increases the precision of IV estimates. However, inclusion of weak instruments could increase finite sample bias. Missing data on multiple genetic variants can diminish the available sample size, compared with single instrument analyses. In simulations with additive genotype-risk factor effects, IV estimates using a weighted allele score had similar properties to estimates using multiple instruments. Under the correct conditions, multiple instrument analyses are a promising approach for Mendelian randomisation studies. Further research is required into multiple imputation methods to address missing data issues in IV estimation.

scholarly journals Association of Established Blood Pressure Loci With 10‐Year Change in Blood Pressure and Their Ability to Predict Incident Hypertension

2020 ◽  
Vol 9 (16) ◽  
Author(s):  
Alaitz Poveda ◽  
Naeimeh Atabaki‐Pasdar ◽  
Shafqat Ahmad ◽  
Göran Hallmans ◽  
Frida Renström ◽  
...  
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Genetic Variants ◽  
Association Studies ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Swedish Population ◽  
Long Term Changes ◽  
Traditional Risk Factors

Background Genome‐wide association studies have identified >1000 genetic variants cross‐sectionally associated with blood pressure variation and prevalent hypertension. These discoveries might aid the early identification of subpopulations at risk of developing hypertension or provide targets for drug development, amongst other applications. The aim of the present study was to analyze the association of blood pressure‐associated variants with long‐term changes (10 years) in blood pressure and also to assess their ability to predict hypertension incidence compared with traditional risk variables in a Swedish population. Methods and Results We constructed 6 genetic risk scores (GRSs) by summing the dosage of the effect allele at each locus of genetic variants previously associated with blood pressure traits (systolic blood pressure GRS (GRS SBP ): 554 variants; diastolic blood pressure GRS (GRS DBP ): 481 variants; mean arterial pressure GRS (GRS MAP ): 20 variants; pulse pressure GRS (GRS PP ): 478 variants; hypertension GRS (GRS HTN ): 22 variants; combined GRS (GRS com b ): 1152 variants). Each GRS was longitudinally associated with its corresponding blood pressure trait, with estimated effects per GRS SD unit of 0.50 to 1.21 mm Hg for quantitative traits and odds ratios (ORs) of 1.10 to 1.35 for hypertension incidence traits. The GRS comb was also significantly associated with hypertension incidence defined according to European guidelines (OR, 1.22 per SD; 95% CI, 1.10‒1.35) but not US guidelines (OR, 1.11 per SD; 95% CI, 0.99‒1.25) while controlling for traditional risk factors. The addition of GRS comb to a model containing traditional risk factors only marginally improved discrimination (Δarea under the ROC curve = 0.001–0.002). Conclusions GRSs based on discovered blood pressure‐associated variants are associated with long‐term changes in blood pressure traits and hypertension incidence, but the inclusion of genetic factors in a model composed of conventional hypertension risk factors did not yield a material increase in predictive ability.

scholarly journals MR-LDP: a two-sample Mendelian randomization for GWAS summary statistics accounting for linkage disequilibrium and horizontal pleiotropy

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Qing Cheng ◽  
Yi Yang ◽  
Xingjie Shi ◽  
Kar-Fu Yeung ◽  
Can Yang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Linkage Disequilibrium ◽  
Genetic Variants ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Alternative Methods ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Causal Relationships ◽  
Disease Outcomes

Abstract The proliferation of genome-wide association studies (GWAS) has prompted the use of two-sample Mendelian randomization (MR) with genetic variants as instrumental variables (IVs) for drawing reliable causal relationships between health risk factors and disease outcomes. However, the unique features of GWAS demand that MR methods account for both linkage disequilibrium (LD) and ubiquitously existing horizontal pleiotropy among complex traits, which is the phenomenon wherein a variant affects the outcome through mechanisms other than exclusively through the exposure. Therefore, statistical methods that fail to consider LD and horizontal pleiotropy can lead to biased estimates and false-positive causal relationships. To overcome these limitations, we proposed a probabilistic model for MR analysis in identifying the causal effects between risk factors and disease outcomes using GWAS summary statistics in the presence of LD and to properly account for horizontal pleiotropy among genetic variants (MR-LDP) and develop a computationally efficient algorithm to make the causal inference. We then conducted comprehensive simulation studies to demonstrate the advantages of MR-LDP over the existing methods. Moreover, we used two real exposure–outcome pairs to validate the results from MR-LDP compared with alternative methods, showing that our method is more efficient in using all-instrumental variants in LD. By further applying MR-LDP to lipid traits and body mass index (BMI) as risk factors for complex diseases, we identified multiple pairs of significant causal relationships, including a protective effect of high-density lipoprotein cholesterol on peripheral vascular disease and a positive causal effect of BMI on hemorrhoids.

scholarly journals M88. EVIDENCE FOR INFLAMMATION AS A PUTATIVE SHARED MECHANISM FOR INSULIN RESISTANCE AND SCHIZOPHRENIA

2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S168-S168
Author(s):  
Benjamin Perry ◽  
Stephen Burgess ◽  
Hannah Jones ◽  
Stanley Zammit ◽  
Rachel Upthegrove ◽  
...  
Keyword(s):  
Risk Factors ◽  
Insulin Resistance ◽  
Genetic Variants ◽  
Cardiometabolic Risk ◽  
Association Studies ◽  
Density Lipoprotein ◽  
Cardiometabolic Risk Factors ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Cardiometabolic Disorders

Abstract Background Insulin Resistance (IR) predisposes to cardiometabolic disorders, which are common in schizophrenia and are associated with excess morbidity and mortality. The mechanisms of association remain unknown. We aimed 1) To use genetic data to examine the direction of association between IR and related cardiometabolic risk factors, and schizophrenia; 2) To examine whether inflammation could be a shared mechanism for IR and schizophrenia. Methods We used two-sample uni-variable Mendelian randomization (MR) to examine whether genetically-predicted IR-related cardiometabolic risk factors (Fasting insulin (FI), high-density lipoprotein (HDL), triglycerides (TG), low-density lipoprotein, fasting plasma glucose, glycated haemoglobin, leptin, body mass index, glucose tolerance and type 2 diabetes) may be causally associated with schizophrenia. We used the most recent summary statistics for genetic variants associated with schizophrenia and IR-related cardiometabolic risk factors from publicly-available large genome-wide association studies (GWAS). We used bi-directional MR to examine direction of association. To examine whether inflammation could be a shared mechanism for IR and schizophrenia, we first conducted a sensitivity analysis by performing MR using only cardiometabolic genetic variants that were also associated with inflammation, at genome-wide significance. Second, we used multi-variable MR (MVMR) to examine associations between cardiometabolic risk factors and schizophrenia after adjusting for genetically-predicted levels of C-reactive protein. Results In analyses using all associated genetic variants, genetically predicted levels of leptin were associated with risk of schizophrenia (OR=2.54 per SD increase in leptin; 95% CI, 1.02–6.31). In analyses using inflammation-related variants, genetically predicted levels of FI (OR=2.76 per SD increase in FI; 95% C.I., 1.31–6.17), TG (OR=2.90 per SD increase in TG; 95% C.I., 1.36–6.17), and HDL (OR=0.56 per SD increase in HDL; 95% C.I., 0.37–0.83) were associated with schizophrenia. The associations completely attenuated in MVMR analyses controlling for CRP. There was no evidence of an association between genetically-predicted schizophrenia liability and cardiometabolic factors. Discussion The IR phenotype of FI, TG and HDL could be associated with schizophrenia over and above common sociodemographic and lifestyle factors. This association is likely explained by a common inflammatory mechanism. Interventional studies are required to test whether inflammation could represent a putative therapeutic target for the treatment and prevention of cardiometabolic disorders in schizophrenia.

Body size and composition and site-specific cancers in UK Biobank: a Mendelian randomisation study

2020 ◽  
Author(s):  
Mathew Vithayathil ◽  
Paul Carter ◽  
Siddhartha Kar ◽  
Amy M. Mason ◽  
Stephen Burgess ◽  
...  
Keyword(s):  
Instrumental Variables ◽  
Association Studies ◽  
Genome Wide Association ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Site Specific ◽  
Genome Wide ◽  
Increased Risk ◽  
The Uk

ABSTRACTObjectivesTo investigate the casual role of body mass index, body fat composition and height in cancer.DesignTwo stage mendelian randomisation studySettingPrevious genome wide association studies and the UK BiobankParticipantsGenetic instrumental variables for body mass index (BMI), fat mass index (FMI), fat free mass index (FFMI) and height from previous genome wide association studies and UK Biobank. Cancer outcomes from 367 586 participants of European descent from the UK Biobank.Main outcome measuresOverall cancer risk and 22 site-specific cancers risk for genetic instrumental variables for BMI, FMI, FFMI and height.ResultsGenetically predicted BMI (per 1 kg/m2) was not associated with overall cancer risk (OR 0.99; 95% confidence interval (CI) 0-98-1.00, p=0.105). Elevated BMI was associated with increased risk of stomach cancer (OR 1.15, 95% (CI) 1.05-1.26; p=0.003) and melanoma (OR 0.96, 95% CI 0.92-1.00; p=0.044). For sex-specific cancers, BMI was positively associated with uterine cancer (OR 1.08, 95% CI 1.01-1.14; p=0.015) but inversely associated with breast (OR 0.95, 95% CI 0.92-0.98; p=0.001), prostate (OR 0.95, 95% CI 0.92-0.99; p=0.007) and testicular cancer (OR 0.89, 95% CI 0.81-0.98; p=0.017). Elevated FMI (per 1 kg/m2) was associated with gastrointestinal cancer (stomach cancer OR 4.23, 95% CI 1.18-15.13, p=0.027; colorectal cancer OR 1.94, 95% CI 1.23-3.07; p=0.004). Increased height (per 1 standard deviation, approximately 6.5cm) was associated with increased risk of overall cancer (OR 1.06; 95% 1.04-1.09; p = 2.97×10-8) and most site-specific cancers with the strongest estimates for kidney, non-Hodgkin lymphoma, colorectal, lung, melanoma and breast cancer.ConclusionsThere is little evidence for BMI as a casual risk factor for cancer. BMI may have a causal role for sex-specific cancers, although with inconsistent directions of effect, and FMI for gastrointestinal malignancies. Elevated height is a risk factor for overall cancer and multiple site cancers.

scholarly journals Chemotherapy-Related Cardiac Dysfunction

2018 ◽  
Vol 11 (1) ◽  
Author(s):  
Marijke Linschoten ◽  
Arco J. Teske ◽  
Maarten J. Cramer ◽  
Elsken van der Wall ◽  
Folkert W. Asselbergs
Keyword(s):  
Risk Factors ◽  
Risk Stratification ◽  
Genetic Variants ◽  
Cardiac Dysfunction ◽  
Genetic Risk ◽  
Drug Transport ◽  
Association Studies ◽  
Genetic Risk Factors ◽  
Candidate Gene Approach ◽  
Genome Wide Association Studies

Chemotherapy-related cardiac dysfunction is a significant side effect of anticancer treatment. Risk stratification is based on clinical- and treatment-related risk factors that do not adequately explain individual susceptibility. The addition of genetic variants may improve risk assessment. We conducted a systematic literature search in PubMed and Embase, to identify studies investigating genetic risk factors for chemotherapy-related cardiac dysfunction. Included were articles describing genetic variants in humans altering susceptibility to chemotherapy-related cardiac dysfunction. The validity of identified studies was assessed by 10 criteria, including assessment of population stratification, statistical methodology, and replication of findings. We identified 40 studies: 34 exploring genetic risk factors for anthracycline-induced cardiotoxicity (n=9678) and 6 studies related to trastuzumab-associated cardiotoxicity (n=642). The majority (35/40) of studies had a candidate gene approach, whereas 5 genome-wide association studies have been performed. We identified 25 genetic variants in 20 genes and 2 intergenic variants reported significant at least once. The overall validity of studies was limited, with small cohorts, failure to assess population ancestry and lack of replication. SNPs with the most robust evidence up to this point are CELF4 rs1786814 (sarcomere structure and function), RARG rs2229774 (topoisomerase-2β expression), SLC28A3 rs7853758 (drug transport), UGT1A6 rs17863783 (drug metabolism), and 1 intergenic variant (rs28714259). Existing evidence supports the hypothesis that genetic variation contributes to chemotherapy-related cardiac dysfunction. Although many variants identified by this systematic review show potential to improve risk stratification, future studies are necessary for validation and assessment of their value in a diagnostic and prognostic setting.

scholarly journals Modifiable lifestyle factors and severe COVID-19 risk: a Mendelian randomisation study

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Shuai Li ◽  
Xinyang Hua
Keyword(s):  
Physical Activity ◽  
Alcohol Consumption ◽  
Genetic Variants ◽  
Association Studies ◽  
Lifestyle Factors ◽  
Mendelian Randomisation ◽  
Severe Illness ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Increased Risk

Abstract Background Lifestyle factors including obesity and smoking are suggested to be correlated with increased risk of COVID-19 severe illness or related death. However, whether these relationships are causal is not well known; neither for the relationships between COVID-19 severe illness and other common lifestyle factors, such as physical activity and alcohol consumption. Methods Genome-wide significant genetic variants associated with body mass index (BMI), lifetime smoking, physical activity and alcohol consumption identified by large-scale genome-wide association studies (GWAS) of up to 941,280 individuals were selected as instrumental variables. Summary statistics of the genetic variants on severe illness of COVID-19 were obtained from GWAS analyses of up to 6492 cases and 1,012,809 controls. Two-sample Mendelian randomisation analyses were conducted. Results Both per-standard deviation (SD) increase in genetically predicted BMI and lifetime smoking were associated with about two-fold increased risks of severe respiratory COVID-19 and COVID-19 hospitalization (all P < 0.05). Per-SD increase in genetically predicted physical activity was associated with decreased risks of severe respiratory COVID-19 (odds ratio [OR] = 0.19; 95% confidence interval [CI], 0.05, 0.74; P = 0.02), but not with COVID-19 hospitalization (OR = 0.44; 95% CI 0.18, 1.07; P = 0.07). No evidence of association was found for genetically predicted alcohol consumption. Similar results were found across robust Mendelian randomisation methods. Conclusions Evidence is found that BMI and smoking causally increase and physical activity might causally decrease the risk of COVID-19 severe illness. This study highlights the importance of maintaining a healthy lifestyle in protecting from COVID-19 severe illness and its public health value in fighting against COVID-19 pandemic.

scholarly journals Is Schizophrenia a Risk Factor for Breast Cancer?—Evidence From Genetic Data

2018 ◽  
Vol 45 (6) ◽  
pp. 1251-1256 ◽  
Author(s):  
Enda M Byrne ◽  
Manuel A R Ferreira ◽  
Angli Xue ◽  
Sara Lindström ◽  
Xia Jiang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Genetic Variants ◽  
Genetic Risk ◽  
Causal Effect ◽  
Association Studies ◽  
Genetic Risk Factors ◽  
Epidemiological Studies ◽  
Genome Wide Association Studies ◽  
Shared Genetic

Abstract Observational epidemiological studies have found an association between schizophrenia and breast cancer, but it is not known if the relationship is a causal one. We used summary statistics from very large genome-wide association studies of schizophrenia (n = 40675 cases and 64643 controls) and breast cancer (n = 122977 cases and 105974 controls) to investigate whether there is evidence that the association is partly due to shared genetic risk factors and whether there is evidence of a causal relationship. Using LD-score regression, we found that there is a small but significant genetic correlation (rG) between the 2 disorders (rG = 0.14, SE = 0.03, P = 4.75 × 10–8), indicating shared genetic risk factors. Using 142 genetic variants associated with schizophrenia as instrumental variables that are a proxy for having schizophrenia, we estimated a causal effect of schizophrenia on breast cancer on the observed scale as bxy = 0.032 (SE = 0.009, P = 2.3 × 10–4). A 1 SD increase in liability to schizophrenia increases risk of breast cancer 1.09-fold. In contrast, the estimated causal effect of breast cancer on schizophrenia from 191 instruments was not significantly different from zero (bxy = −0.005, SE = 0.012, P = .67). No evidence for pleiotropy was found and adjusting for the effects of smoking or parity did not alter the results. These results provide evidence that the previously observed association is due to schizophrenia causally increasing risk for breast cancer. Genetic variants may provide an avenue to elucidating the mechanism underpinning this relationship.

AlzRiskMR database: an online database for the impact of exposure factors on Alzheimer’s disease

2020 ◽  
Author(s):  
Zhe Wang ◽  
Lei Meng ◽  
Hong Liu ◽  
Liang Shen ◽  
Hong-Fang Ji
Keyword(s):  
Risk Factors ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Association Studies ◽  
Modifiable Risk Factors ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Inverse Variance ◽  
Weighted Median ◽  
The Impact

Abstract In view of great difficulties in the pathogenesis analysis of Alzheimer’s disease (AD) presently, profiling the modifiable risk factors is crucial for early detection and intervention of AD. However, the causal associations among them have yet to be identified, and the effective integration and application of these data also remain considerable challenges due to the lack of efficient collection and analysis procedures. To address this issue, we performed comprehensive analyses by two-sample Mendelian randomization (2SMR) and established the AlzRiskMR database (https://github.com/SDBMC/RiskFactors2AD). Four 2SMR analysis methods, including inverse variance weighted (IVW), MR-Egger, weighted median, and weighted mode, were used for the complementary calculation to test the reliability of the results. The database currently comprises 1870 sets of data of Genome-Wide Association Studies (GWAS) from the MR-Base and NHGRI-EBI GWAS Catalog database. AlzRiskMR database not only estimates causal associations between modifiable risk factors and AD but also offers a useful and timely resource for early intervention of AD development incidence.

Mendelian randomisation study of the effects of known and putative risk factors on pancreatic cancer

2020 ◽  
Vol 57 (12) ◽  
pp. 820-828 ◽  
Author(s):  
Ye Lu ◽  
Manuel Gentiluomo ◽  
Justo Lorenzo-Bermejo ◽  
Luca Morelli ◽  
Ofure Obazee ◽  
...  
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
Pancreatic Cancer ◽  
Association Studies ◽  
Dietary Factors ◽  
Causal Effects ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Fasting Insulin

BackgroundObservational studies have reported multiple risk factors for pancreatic ductal adenocarcinoma (PDAC). Some are well established, like tobacco smoking, alcohol drinking, obesity and type 2 diabetes, whereas some others are putative, such as allergy and dietary factors. Identifying causal risk factors can help establishing those that can be targeted to contribute to prevent PDAC.ObjectiveWe sought to investigate the possible causal effects of established and putative factors on PDAC risk.MethodsWe conducted a two-sample Mendelian randomisation (MR) study using publicly available data for genetic variants associated with the factors of interest, and summary genetic data from genome-wide association studies of the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4), including in total 8769 cases and 7055 controls. Causality was assessed using inverse-variance weighted, MR-Egger regression and weighted median methods, complemented with sensitivity and radial MR analyses.ResultsWe found evidence for a causal effect of body mass index (BMI) on PDAC risk (OR 1.43, 95% CI 1.20 to 1.71, p=8.43×10−5). Fasting insulin (OR 2.84, 95% CI 1.23 to 6.56, p=0.01), low-density lipoprotein cholesterol (OR 1.16, 95% CI 1.02 to 1.32, p=0.03) and type 2 diabetes (OR 1.09, 95% CI 1.01 to 1.17, p=0.02) were also causally associated with PDAC risk. BMI showed both direct and fasting insulin-mediated causal effects.ConclusionWe found strong evidence that BMI is causally associated with PDAC risk, providing support that obesity management may be a potential prevention strategy for reducing pancreatic cancer risk while fasting insulin and type 2 diabetes showed a suggestive association that should be further investigated.

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