Power calculation for the general two-sample Mendelian randomization analysis.
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ABSTRACT:
SUBMITTER: Deng L
PROVIDER: S-EPMC8766247 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Mendelian randomization analyses are often performed using summarized data. The causal estimate from a one-sample analysis (in which data are taken from a single data source) with weak instrumental variables is biased in the direction of the observational association between the risk factor and outcome, whereas the estimate from a two-sample analysis (in which data on the risk factor and outcome are taken from non-overlapping datasets) is less biased and any bias is in the direction of the null. When using genetic consortia that have partially overlapping sets of participants, the direction and extent of bias are uncertain. In this paper, we perform simulation studies to investigate the magnitude of bias and Type 1 error rate inflation arising from sample overlap. We consider both a continuous outcome and a case-control setting with a binary outcome. For a continuous outcome, bias due to sample overlap is a linear function of the proportion of overlap between the samples. So, in the case of a null causal effect, if the relative bias of the one-sample instrumental variable estimate is 10% (corresponding to an F parameter of 10), then the relative bias with 50% sample overlap is 5%, and with 30% sample overlap is 3%. In a case-control setting, if risk factor measurements are only included for the control participants, unbiased estimates are obtained even in a one-sample setting. However, if risk factor data on both control and case participants are used, then bias is similar with a binary outcome as with a continuous outcome. Consortia releasing publicly available data on the associations of genetic variants with continuous risk factors should provide estimates that exclude case participants from case-control samples.
| S-EPMC5082560 | biostudies-literature
Project description:BackgroundObservational studies have suggested that there may be an association between telomere length (TL) and hearing loss (HL). However, inferring causality from observational studies is subject to residual confounding effects, reverse causation, and bias. This study adopted a two-sample Mendelian randomization (MR) approach to evaluate the causal relationship between TL and increased risk of HL.MethodsA total of 16 single nucleotide polymorphisms (SNPs) associated with TL were identified from a genome-wide association study (GWAS) meta-analysis of 78,592 European participants and applied to our modeling as instrumental variables. Summary-level data for hearing loss (HL), age-related hearing loss (ARHL), and noise-induced hearing loss (NIHL) were obtained from the recent largest available GWAS and five MR analyses were used to investigate the potential causal association of genetically predicted TL with increased risk for HL, including the inverse-variance-weighted (IVW), weighted median, MR-Egger regression, simple mode, and weighted mode. In addition, sensitivity analysis, pleiotropy, and heterogeneity tests were also used to evaluate the robustness of our findings.ResultsThere was no causal association between genetically predicted TL and HL or its subtypes (by the IVW method, HL: odds ratio (OR) = 1.216, p = 0.382; ARHL: OR = 0.934, p = 0.928; NIHL: OR = 1.003, p = 0.776). Although heterogenous sites rs2736176, rs3219104, rs8105767, and rs2302588 were excluded for NIHL, the second MR analysis was consistent with the first analysis (OR = 1.003, p = 0.572).ConclusionThere was no clear causal relationship between shorter TLs and increased risk of HL or its subtypes in this dataset.
| S-EPMC9330868 | biostudies-literature
Project description:Celiac disease (CeD) is a complex immune-mediated inflammatory condition triggered by the ingestion of gluten in genetically predisposed individuals. Literature suggests that alterations in gut microbiota composition and function precede the onset of CeD. Considering that microbiota is partly determined by host genetics, we speculated that the genetic makeup of CeD patients could elicit disease development through alterations in the intestinal microbiota. To evaluate potential causal relationships between gut microbiota and CeD, we performed a two-sample Mendelian randomization analysis (2SMR). Exposure data were obtained from the raw results of a previous genome-wide association study (GWAS) of gut microbiota and outcome data from summary statistics of CeD GWAS and Immunochip studies. We identified a number of putative associations between gut microbiota single nucleotide polymorphisms (SNPs) associated with CeD. Regarding bacterial composition, most of the associated SNPs were related to Firmicutes phylum, whose relative abundance has been previously reported to be altered in CeD patients. In terms of functional units, we linked a number of SNPs to several bacterial metabolic pathways that seemed to be related to CeD. Overall, this study represented the first 2SMR approach to elucidate the relationship between microbiome and CeD.
| S-EPMC7284592 | biostudies-literature
Project description:BackgroundObservational studies indicate that periodontal disease may increase the risk of colorectal, lung, and pancreatic cancers. Using a 2-sample Mendelian randomization (MR) analysis, we assessed whether a genetic predisposition index for periodontal disease was associated with colorectal, lung, or pancreatic cancer risks.MethodsOur primary instrument included single nucleotide polymorphisms with strong genome-wide association study evidence for associations with chronic, aggressive, and/or severe periodontal disease (rs729876, rs1537415, rs2738058, rs12461706, rs16870060, rs2521634, rs3826782, and rs7762544). We used summary-level genetic data for colorectal cancer (n = 58 131 cases; Genetics and Epidemiology of Colorectal Cancer Consortium, Colon Cancer Family Registry, and Colorectal Transdisciplinary Study), lung cancer (n = 18 082 cases; International Lung Cancer Consortium), and pancreatic cancer (n = 9254 cases; Pancreatic Cancer Consortia). Four MR approaches were employed for this analysis: random-effects inverse-variance weighted (primary analyses), Mendelian Randomization-Pleiotropy RESidual Sum and Outlier, simple median, and weighted median. We conducted secondary analyses to determine if associations varied by cancer subtype (colorectal cancer location, lung cancer histology), sex (colorectal and pancreatic cancers), or smoking history (lung and pancreatic cancer). All statistical tests were 2-sided.ResultsThe genetic predisposition index for chronic or aggressive periodontitis was statistically significantly associated with a 3% increased risk of colorectal cancer (per unit increase in genetic index of periodontal disease; P = .03), 3% increased risk of colon cancer (P = .02), 4% increased risk of proximal colon cancer (P = .01), and 3% increased risk of colorectal cancer among females (P = .04); however, it was not statistically significantly associated with the risk of lung cancer or pancreatic cancer, overall or within most subgroups.ConclusionsGenetic predisposition to periodontitis may be associated with colorectal cancer risk. Further research should determine whether increased periodontitis prevention and increased cancer surveillance of patients with periodontitis is warranted.
| S-EPMC8242136 | biostudies-literature
Project description:AbstractMotivationIn recent years, Mendelian randomization analysis using summary data from genome-wide association studies has become a popular approach for investigating causal relationships in epidemiology. The mrrobust Stata package implements several of the recently developed methods.Implementationmrrobust is freely available as a Stata package.General featuresThe package includes inverse variance weighted estimation, as well as a range of median, modal and MR-Egger estimation methods. Using mrrobust, plots can be constructed visualizing each estimate either individually or simultaneously. The package also provides statistics such as IGX2, which are useful in assessing attenuation bias in causal estimates.AvailabilityThe software is freely available from GitHub [https://raw.github.com/remlapmot/mrrobust/master/].
| S-EPMC6659377 | biostudies-other
Project description:IntroductionWe conducted a two-sample Mendelian randomization study to determine the associations of modifiable risk factors with epilepsy.MethodsFourteen potential risk factors for epilepsy were selected based on a systematic review of risk factors for epilepsy. Single-nucleotide polymorphisms associated with each exposure at the genome-wide significance threshold (p < 5×10-8 ) were proposed as instrumental variables from corresponding genome-wide association studies. Summary-level data for epilepsy were obtained from the FinnGen consortium (4,588 cases and 144 780 noncases). Potential causal associations (p < .05) were attempted for replication using UK Biobank data (901 cases and 395 209 controls).ResultsAmong 14 potential risk factors, 4 showed significant associations with epilepsy in FinnGen. All associations were directionally similar in UK Biobank and associated with epilepsy at p ≤ .004 in meta-analyses of FinnGen and UK Biobank data. The odds ratios of epilepsy were 1.46 (95% CI, 1.18, 1.82) for one unit increase in log odds ratio of having depression, 1.44 (95% CI, 1.13, 1.85) for one standard deviation increase in serum ferritin, 1.12 (95% CI, 1.04, 1.21) for one standard deviation increase in transferrin saturation, and 1.25 (95% CI, 1.09, 1.43) for one standard deviation increase in the prevalence of smoking initiation. There were suggestive associations of serum iron and magnesium with epilepsy. No association was observed for insomnia, blood pressure, alcohol consumption, or serum vitamin B12, 25-hydroxyvitamin D and calcium levels.ConclusionThis MR study identified several modifiable risk factors for adulthood epilepsy. Reducing prevalence of depression and smoking initiation should be considered as primary prevention strategies for epilepsy.
| S-EPMC8119863 | biostudies-literature
Project description:Cerebral small vessel disease (cSVD) is correlated with a high risk of stroke and cognitive impairment. Previous studies between heart rate variability (HRV) and cSVD revealed paradoxical results. The authors aimed to investigate the relationship between HRV and cSVD using Mendelian randomization analysis. Genetic instruments for HRV were obtained from previous genome-wide association studies. They applied inverse variance-weighted analysis, weighted median analysis, simple median analysis, and Mendelian randomization-Egger regression to evaluate the associations of HRV with white matter hyperintensity (WMH) and small vessel stroke (SVS) in the UK Biobank neuroimaging dataset and the MEGASTROKE genome-wide association study dataset. Two genetically predicted traits of HRV (the root mean square of the successive differences of inter beat intervals [RMSSD] and the peak-valley respiratory sinus arrhythmia or high frequency power [pvRSA/HF]) were suggestively associated with WMH (β 0.26, 95% confidence interval [CI] 0.04-0.49, p = .02; β 0.14, 95% CI 0.02-0.27, p = .03, respectively). Genetically predicted traits of HRV were not significantly associated with SVS. This study provides genetic support for a suggestive causal effect of HRV (RMSSD, pvRSA/HF) on WMH but not SVS.
| S-EPMC8678680 | biostudies-literature
Project description:Background: Previous observational studies have reported a bidirectional association between periodontitis and type 2 diabetes, but the causality of these relationships remains unestablished. We clarified the bidirectional causal association through two-sample Mendelian randomization (MR). Methods: We obtained summary-level data for periodontitis and type 2 diabetes from several published large-scale genome-wide association studies (GWAS) of individuals of European ancestry. For the casual effect of periodontitis on type 2 diabetes, we used five independent single-nucleotide polymorphisms (SNPs) specific to periodontitis from three GWAS. The summary statistics for the associations of exposure-related SNPs with type 2 diabetes were drawn from the GWAS in the Diabetes Genetics Replication and Meta-analysis (DIAGRAM) consortium and the FinnGen consortium R5 release, respectively. For the reversed causal inference, 132 and 49 SNPs associated with type 2 diabetes from the DIAGRAM consortium and the FinnGen consortium R5 release were included, and the summary-level statistics were obtained from the Gene-Lifestyle Interactions in Dental Endpoints consortium. Multiple approaches of MR were carried out. Results: Periodontitis was not causally related with the risk of type 2 diabetes (all p > 0.05). No causal effect of type 2 diabetes on periodontitis was found (all p > 0.05). Estimates were consistent across multiple MR analyses. Conclusion: This study based on genetic data does not support a bidirectional causal association between periodontitis and type 2 diabetes.
| S-EPMC8784400 | biostudies-literature
Project description:Mendelian randomization (MR) is becoming more and more popular for inferring causal relationship between an exposure and a trait. Typically, instrument SNPs are selected from an exposure GWAS based on their summary statistics and the same summary statistics on the selected SNPs are used for subsequent analyses. However, this practice suffers from selection bias and can invalidate MR methods, as showcased via two popular methods: the summary data-based MR (SMR) method and the two-sample MR Steiger method. The SMR method is conservative while the MR Steiger method can be either conservative or liberal. A simple and yet more powerful alternative to SMR is proposed.
| S-EPMC8027662 | biostudies-literature
Project description:BACKGROUND AND OBJECTIVES:Associations between blood lipids and risk of ischemic heart disease (IHD) have been reported in observational studies. However, due to confounding and reverse causation, observational studies are influenced by bias, thus their results show inconsistency in the effects of lipid levels on IHD. In this study, we evaluate whether lipid levels have an effect on the risk of IHD in a Korean population. METHODS:A 2-sample Mendelian randomization (MR) study, using the genetic variants associated with lipid levels as the instrumental variables was performed. Genetic variants significantly associated with lipid concentrations were obtained from the Korean Genome and Epidemiology Study (n=35,000), and the same variants on IHD were obtained from the Korean Cancer Prevention Study-II (n=13,855). Inverse variance weighting (IVW), weighted median, and MR-Egger approaches were used to assess the causal association between lipid levels and IHD. Radial MR methods were applied to remove outliers subject to pleiotropic bias. RESULTS:Causal association between low-density lipoprotein-cholesterol (LDL-C) and IHD was observed in the IVW method (odds ratio, 1.013; 95% confidence interval, 1.007-1.109). However, high-density lipoprotein-cholesterol (HDL-C) and triglyceride (TG) did not show causal association with IHD. In the Radial MR analysis of the relationship between HDL-C, TG and IHD, outliers were detected. Interestingly, after removing the outliers, a causal association between TG and IHD was found. CONCLUSIONS:High levels LDL-C and TG were causally associated with increased IHD risk in a Korean population, these results are potentially useful as evidence of a significant causal relationship.
| S-EPMC7515757 | biostudies-literature