The condition of critically ill patients changes rapidly, involving pathological changes in multiple systems and organs throughout the body. Exploring the causal relationship of mechanisms can further reveal etiology, treatment, and prognosis of diseases. However, traditional prospective studies in the field of critical care are still subject to numerous limitations. As an emerging research method, Mendelian randomization (MR) analysis uses genetic variation to provide causal evidence for instrumental variables, which is expected to provide clues in critical diseases. This article systematically describes the research progresson the application of MR analysis in critical care medicine from four aspects: the principle of MR analysis, the difference between MR analysis and randomized controlled trial (RCT), the use of MR analysis in the field of critical illness, and the possible methods of application, aiming to provide possible directions for the research in this field.
Humans ; Mendelian Randomization Analysis/methods* ; Genetic Variation ; Causality ; Research Design

Mendelian randomization (MR) in epidemiology is the use of genetic variants as instrumental variables (IVs) in non-experimental design to make causality of a modifiable exposure on an outcome or disease. It assesses the causal effect between risk factor and a clinical outcome. The main reason to approach MR is to avoid the problem of residual confounding. There is no association between the genotype of early pregnancy and the disease, and the genotype of an individual cannot be changed. For this reason, it results with randomly assigned case-control studies can be set by regressing the measurements. IVs in MR are used genetic variants for estimating the causality. Usually an outcome is a disease and an exposure is risk factor, intermediate phenotype which may be a biomarker. The choice of the genetic variable as IV (Z) is essential to a successful in MR analysis. MR is named ‘Mendelian deconfounding’ as it gives to estimate of the causality free from biases due to confounding (C). To estimate unbiased estimation of the causality of the exposure (X) on the clinically relevant outcome (Y), Z has the 3 core assumptions (A1-A3). A1) Z is independent of C; A2) Z is associated with X; and A3) Z is independent of Y given X and C; The purpose of this review provides an overview of the MR analysis and is to explain that using an IV is proposed as an alternative statistical method to estimate causal effect of exposure and outcome under controlling for a confounder.
Bias (Epidemiology) ; Case-Control Studies ; Epidemiology ; Genotype ; Mendelian Randomization Analysis ; Methods ; Molecular Epidemiology ; Phenotype ; Pregnancy ; Random Allocation ; Risk Factors

OBJECTIVE: This study aimed to examine whether rheumatoid arthritis (RA) is causally associated with type 2 diabetes (T2D). METHODS: We performed a two-sample Mendelian randomization (MR) analysis using the inverse-variance weighted (IVW), weighted median, and MR-Egger regression methods. We used the publicly available summary statistics datasets from a genome-wide association studies (GWAS) meta-analysis of 5,539 autoantibody-positive individuals with RA and 20,169 controls of European descent, and a GWAS dataset of 10,247 individuals with T2D and 53,924 controls, overwhelmingly of European descent as outcomes. RESULTS: We selected 10 single-nucleotide polymorphisms from GWAS data on RA as instrumental variables to improve the inference. The IVW method supported a causal association between RA and T2D (β=0.044, standard error [SE]=0.022, p=0.047). The MR-Egger analysis showed a causal association between RA and T2D (β=0.093, SE=0.033, p=0.023). In addition, the weighted median approach supported a causal association between RA and T2D (β=0.056, SE=0.025, p=0.028). The association between RA and T2D was consistently observed using IVW, MR Egger, and weighted median methods. Cochran's Q test indicated no evidence of heterogeneity between instrumental variable estimates based on individual variants and MR-Egger regression revealed that directional pleiotropy was unlikely to have biased the results (intercept=−0.030; p=0.101). CONCLUSION: MR analysis supports that RA may be causally associated with an increased risk of T2D.
Arthritis, Rheumatoid ; Bias (Epidemiology) ; Dataset ; Genome-Wide Association Study ; Mendelian Randomization Analysis ; Methods ; Population Characteristics ; Random Allocation

Objective: To explore the causal effects of the serum Vitamin D levels on the risk of systemic lupus erythematosus (SLE). Methods: A two-sample Mendelian randomization (MR) study was performed to infer the causality. Three Genome-wide association studies (GWAS) for circulating Vitamin D levels, including 25-hydroxyvitamin D [25(OH)D], 25-hydroxyvitamin D₃ [25(OH)D₃] and C3-epimer of 25-hydroxyvitamin D₃ [C3-epi-25(OH)D₃] published in 2020, and one GWAS for SLE published in 2015 were utilized to analyze the causal effects of the serum Vitamin D levels on the risk of SLE. MR analyses were conducted using the inverse-variance weighted method (IVW), weighted median, MR-Egger methods, MR-pleiotropy residual sum and outlier (MR-PRESSO) method. Results: 34, 29 and 6 SNPs were respectively selected as instrumental variables to analyze the causal association of total 25 (OH) D level, 25 (OH) D₃ level and C3-epi-25 (OH) D₃ level with the risk of SLE. The MR results showed that each standard deviation decrease in the level of 25(OH)D₃ would result in 14.2% higher risk of SLE (OR, 0.858; 95%CI, 0.753-0.978; P=0.022). The levels of 25(OH)D and C3-epi-25(OH)D₃ had null associations with risk of SLE (OR, 0.849; 95%CI, 0.653-1.104; P=0.222; OR, 0.904; 95%CI, 0.695-1.176; P=0.452). Conclusion: This study have identified a causal effect of 25(OH)D₃ on increased risk of SLE. These findings highlighted the significance of active monitoring and prevention of SLE in population of low Vitamin D levels.
Humans ; Genome-Wide Association Study ; Vitamin D ; Lupus Erythematosus, Systemic/complications* ; Vitamins ; Causality ; Mendelian Randomization Analysis/methods* ; Polymorphism, Single Nucleotide

Objective: A Mendelian randomization (MR) analysis was performed to assess the relationship between tea consumption and cancer. Methods: There were 100 639 participants with the information of gene sequencing of whole genome in the China Kadoorie Biobank. After excluding those with cancer at baseline survey, a total of 100 218 participants were included in this study. The baseline information about tea consumption were analyzed, including daily tea consumption or not, cups of daily tea consumption, and grams of daily tea consumption. We used the two-stage least square method to evaluate the associations between three tea consumption variables and incidence of cancer and some subtypes, including stomach cancer, liver and intrahepatic bile ducts cancer, colorectal cancer, tracheobronchial and lung cancer, and female breast cancer. Multivariable MR and analysis only among nondrinkers were used to control the impact of alcohol consumption. Sensitivity analyses were also performed, including inverse variance weighting, weighted median, and MR-Egger. Results: We used 54, 42, and 28 SNPs to construct non-weighted genetic risk scores as instrumental variables for daily tea consumption or not, cups of daily tea consumption, and grams of daily tea consumption, respectively. During an average of (11.4±3.0) years of follow-up, 6 886 cases of cancer were recorded. After adjusting for age, age², sex, region, array type, and the first 12 genetic principal components, there were no significant associations of three tea consumption variables with the incidence of cancer and cancer subtypes. Compared with non-daily tea drinkers, the HR (95%CI) of daily tea drinkers for cancer and some subtypes, including stomach cancer, liver and intrahepatic bile ducts cancer, colorectal cancer, tracheobronchial and lung cancer, and female breast cancer, are respectively 0.99 (0.78-1.26), 1.17 (0.58-2.36), 0.86 (0.40-1.84), 0.85 (0.42-1.73), 1.39 (0.85-2.26) and 0.63 (0.28-1.38). After controlling the impact of alcohol consumption and performing multiple sensitivity analyses, the results were similar. Conclusion: There is no causal relationship between tea consumption and risk of cancer in population in China.
Humans ; Female ; Stomach Neoplasms/epidemiology* ; Mendelian Randomization Analysis/methods* ; Tea ; Breast Neoplasms ; Lung Neoplasms ; Colorectal Neoplasms ; Polymorphism, Single Nucleotide ; Genome-Wide Association Study

Objective: Based on the Mendelian randomization analysis, to assess the causal relationship between DNA methylation levels of Janus kinase 2 (JAK2) and obesity. Methods: A case-control study was carried out, including 1 021 individuals [obesity (visceral fat index ≥10) vs. no obesity (visceral fat index <10) was 440 vs. 581] from the Henan Rural Cohort Study. MethylTarget^TM target region methylation sequencing technology was used for testing the DNA methylation level of JAK2. logistic regression models were used to assess the association between the DNA methylation level of JAK2 and obesity. With SNP as the instrumental variable, the association between the DNA methylation level of JAK2 and obesity was explored by using the Mendelian randomization analysis method. Results: There was a positive association between Chr9:4984943 (one DNA methylation site in the promoter of JAK2) and obesity, and the OR (95%CI) was 1.22(1.04-1.42). Methylation level of five sites in the exon of JAK2 (Chr9:4985378, Chr9:4985404, Chr9:4985407, Chr9:4985409 and Chr9:4985435) were negatively associated with obesity, the corresponding OR (95%CI) were 0.53 (0.29-0.95), 0.58(0.36-0.93), 0.69 (0.49-0.97), 0.72 (0.53-0.99) and 0.58 (0.35-0.98) , respectively. Mendelian randomization analysis showed that there was a causal relationship between the DNA methylation levels of JAK2 and obesity, and the corresponding β (95%CI) were -1.985 (-3.520 - -0.450),-3.547 (-6.301 - -0.792) and -3.900 (-6.328 - -1.472) for Mendelian randomization method of inverse variance weighted, Mendelian randomization method of median based and Maximum-likelihood method, respectively. Conclusion: This study supported there was a causal relationship between the DNA methylation level of JAK2 and obesity.
Case-Control Studies ; Cohort Studies ; DNA Methylation ; Genome-Wide Association Study ; Humans ; Janus Kinase 2/genetics* ; Mendelian Randomization Analysis/methods* ; Obesity/genetics* ; Polymorphism, Single Nucleotide