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1.
Front Public Health ; 9: 726617, 2021.
Article in English | MEDLINE | ID: covidwho-1775848

ABSTRACT

The associations between absolute vs. relative income at the household or neighborhood level and cardiovascular disease (CVD) risk remain understudied in the Chinese context. Further, it is unclear whether stress biomarkers, such as cortisol, are on the pathway from income to CVD risk. We examined the associations of absolute and relative income with CVD risk observationally, as well as the mediating role of cortisol, and validated the role of cortisol using Mendelian Randomization (MR) in Hong Kong Chinese. Within Hong Kong's FAMILY Cohort, associations of absolute and relative income at both the individual and neighborhood levels with CVD risk [body mass index (BMI), body fat percentage, systolic blood pressure, diastolic blood pressure, self-reported CVD and self-reported diabetes] were examined using multilevel logistic or linear models (n = 17,607), the mediating role of cortisol using the mediation analysis (n = 1,562), and associations of genetically predicted cortisol with CVD risk using the multiplicative generalized method of moments (MGMMs) or two-stage least squares regression (n = 1,562). In our cross-sectional observational analysis, relative household income deprivation (per 1 SD, equivalent to USD 128 difference in Yitzhaki index) was associated with higher systolic blood pressure (0.47 mmHg, 95% CI 0.30-0.64), but lower BMI (-0.07 kg/m2, 95% CI -0.11 to -0.04), independent of absolute income. Neighborhood income inequality was generally unrelated to CVD and its risk factors, nor was absolute income at the household or neighborhood level. Cortisol did not clearly mediate the association of relative household income deprivation with systolic blood pressure. Using MR, cortisol was unrelated to CVD risk. Based on our findings, relative household income deprivation was not consistently associated with cardiovascular health in Hong Kong Chinese, nor were neighborhood income inequality and absolute income, highlighting the context-specific ways in which relative and absolute income are linked to CVD risk.


Subject(s)
Mendelian Randomization Analysis , Cross-Sectional Studies , Hong Kong/epidemiology , Humans , Income , Mendelian Randomization Analysis/methods
2.
J Glob Health ; 12: 05010, 2022.
Article in English | MEDLINE | ID: covidwho-1726723

ABSTRACT

Background: In this study, we performed a bidirectional mendelian randomization analysis on circulating cytokines and critically ill COVID-19. Methods: Both the exposure and outcome data were obtained from public genome wide association study (GWAS) database. We extracted independent instrumental variables from exposure at genome level significance (P < 5 × 10-8). Wald ratio or inverse variance weighted (IVW) method were used for estimating the causal relationships between circulating cytokines and critically ill COVID-19. Results: Only IL5 (cytokines to critically ill COVID-19 direction) and bNGF, IL8 (critically ill COVID-19 to cytokines direction) showed suggestive causal relations. However, these associations lost significance after FDR correction. Another validation data set of critically ill COVID-19 did not confirm these associations, either. Conclusions: Our Mendelian randomization did not find causal relationships between analyzable circulating cytokines and critically ill COVID-19.


Subject(s)
COVID-19 , Mendelian Randomization Analysis , Critical Illness , Cytokines/genetics , Genome-Wide Association Study , Humans , Mendelian Randomization Analysis/methods , Polymorphism, Single Nucleotide
3.
Genet Epidemiol ; 46(3-4): 159-169, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1699896

ABSTRACT

Mendelian randomization (MR) is a statistical method exploiting genetic variants as instrumental variables to estimate the causal effect of modifiable risk factors on an outcome of interest. Despite wide uses of various popular two-sample MR methods based on genome-wide association study summary level data, however, those methods could suffer from potential power loss or/and biased inference when the chosen genetic variants are in linkage disequilibrium (LD), and also have relatively large direct effects on the outcome whose distribution might be heavy-tailed which is commonly referred to as the idiosyncratic pleiotropy phenomenon. To resolve those two issues, we propose a novel Robust Bayesian Mendelian Randomization (RBMR) model that uses the more robust multivariate generalized t $t$ -distribution to model such direct effects in a probabilistic model framework which can also incorporate the LD structure explicitly. The generalized t $t$ -distribution can be represented as a Gaussian scaled mixture so that our model parameters can be estimated by the expectation maximization (EM)-type algorithms. We compute the standard errors by calibrating the evidence lower bound using the likelihood ratio test. Through extensive simulation studies, we show that our RBMR has robust performance compared with other competing methods. We further apply our RBMR method to two benchmark data sets and find that RBMR has smaller bias and standard errors. Using our proposed RBMR method, we find that coronary artery disease is associated with increased risk of critically ill coronavirus disease 2019. We also develop a user-friendly R package RBMR (https://github.com/AnqiWang2021/RBMR) for public use.


Subject(s)
COVID-19 , Mendelian Randomization Analysis , Bayes Theorem , COVID-19/genetics , Genetic Pleiotropy , Genome-Wide Association Study , Humans , Linkage Disequilibrium , Mendelian Randomization Analysis/methods , Models, Genetic
4.
Pregnancy Hypertens ; 26: 17-23, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1364411

ABSTRACT

AIMS: The aim of this study was to apply the Mendelian randomization (MR) design to explore the potential causal association between COVID-19 and the risk of hypertension disorders in pregnancy. METHODS: Our primary genetic instrument comprised 8 single-nucleotide polymorphisms (SNPs) associated with COVID-19 at genome-wide significance. Data on the associations between the SNPs and the risk of hypertension disorders in pregnancy were obtained from study based on a very large cohort of European population. The random-effects inverse-variance weighted method was conducted for the main analyses, with a complementary analysis of the weighted median and MR-Egger approaches. RESULTS: Using IVW, we found that genetically predicted COVID-19 was significantly positively associated with hypertension disorders in pregnancy, with an odds ratio (OR) of 1.111 [95% confidence interval (CI) 1.042-1.184; P = 0.001]. Weighted median regression also showed directionally similar estimates [OR 1.098 (95% CI, 1.013-1.190), P = 0.023]. Both funnel plots and MR-Egger intercepts suggest no directional pleiotropic effects observed. CONCLUSIONS: Our findings provide direct evidence that there is a shared genetic predisposition so that patients infected with COVID-19 may be causally associated with increased risk of hypertension disorders in pregnancy.


Subject(s)
COVID-19/genetics , Genetic Predisposition to Disease , Hypertension/etiology , Mendelian Randomization Analysis/methods , Polymorphism, Single Nucleotide , Risk Assessment/methods , SARS-CoV-2 , COVID-19/complications , COVID-19/epidemiology , Female , Global Health , Humans , Hypertension/epidemiology , Hypertension/genetics , Incidence , Pregnancy , Risk Factors
5.
Nat Med ; 27(4): 668-676, 2021 04.
Article in English | MEDLINE | ID: covidwho-1174686

ABSTRACT

Drug repurposing provides a rapid approach to meet the urgent need for therapeutics to address COVID-19. To identify therapeutic targets relevant to COVID-19, we conducted Mendelian randomization analyses, deriving genetic instruments based on transcriptomic and proteomic data for 1,263 actionable proteins that are targeted by approved drugs or in clinical phase of drug development. Using summary statistics from the Host Genetics Initiative and the Million Veteran Program, we studied 7,554 patients hospitalized with COVID-19 and >1 million controls. We found significant Mendelian randomization results for three proteins (ACE2, P = 1.6 × 10-6; IFNAR2, P = 9.8 × 10-11 and IL-10RB, P = 2.3 × 10-14) using cis-expression quantitative trait loci genetic instruments that also had strong evidence for colocalization with COVID-19 hospitalization. To disentangle the shared expression quantitative trait loci signal for IL10RB and IFNAR2, we conducted phenome-wide association scans and pathway enrichment analysis, which suggested that IFNAR2 is more likely to play a role in COVID-19 hospitalization. Our findings prioritize trials of drugs targeting IFNAR2 and ACE2 for early management of COVID-19.


Subject(s)
COVID-19/genetics , Drug Repositioning , Mendelian Randomization Analysis/methods , SARS-CoV-2 , Angiotensin-Converting Enzyme 2/genetics , Angiotensin-Converting Enzyme 2/physiology , COVID-19/drug therapy , Genome-Wide Association Study , Humans , Interleukin-10 Receptor beta Subunit/genetics , Interleukin-10 Receptor beta Subunit/physiology , Quantitative Trait Loci , Receptor, Interferon alpha-beta/genetics , Receptor, Interferon alpha-beta/physiology
6.
Metabolism ; 118: 154732, 2021 05.
Article in English | MEDLINE | ID: covidwho-1096162

ABSTRACT

OBJECTIVES: Recent studies suggested obesity to be a possible risk factor for COVID-19 disease in the wake of the coronavirus (SARS-CoV-2) infection. However, the causality and especially the role of body fat distribution in this context is still unclear. Thus, using a univariable as well as multivariable two-sample Mendelian randomization (MR) approach, we investigated for the first time the causal impact of body composition on the susceptibility and severity of COVID-19. METHODS: As indicators of overall and abdominal obesity we considered the measures body mass index (BMI), waist circumference (WC), and trunk fat ratio (TFR). Summary statistics of genome-wide association studies (GWASs) for these body composition measures were drawn from the GIANT consortium and UK Biobank, while for susceptibility and severity due to COVID-19 disease data from the COVID-19 Host Genetics Initiative was used. For the COVID-19 cohort neither age nor gender was available. Total and direct causal effect estimates were calculated using Single Nucleotide Polymorphisms (SNPs), sensitivity analyses were done applying several robust MR techniques and mediation effects of type 2 diabetes (T2D) and cardiovascular diseases (CVD) were investigated within multivariable MR analyses. RESULTS: Genetically predicted BMI was strongly associated with both, susceptibility (OR = 1.31 per 1 SD increase; 95% CI: 1.15-1.50; P-value = 7.3·10-5) and hospitalization (OR = 1.62 per 1 SD increase; 95% CI: 1.33-1.99; P-value = 2.8·10-6) even after adjustment for genetically predicted visceral obesity traits. These associations were neither mediated substantially by T2D nor by CVD. Finally, total but not direct effects of visceral body fat on outcomes could be detected. CONCLUSIONS: This study provides strong evidence for a causal impact of overall obesity on the susceptibility and severity of COVID-19 disease. The impact of abdominal obesity was weaker and disappeared after adjustment for BMI. Therefore, obese people should be regarded as a high-risk group. Future research is necessary to investigate the underlying mechanisms linking obesity with COVID-19.


Subject(s)
Body Composition , COVID-19/etiology , Mendelian Randomization Analysis/methods , Obesity/complications , SARS-CoV-2 , Body Mass Index , COVID-19/metabolism , Disease Susceptibility , Genome-Wide Association Study , Humans , Polymorphism, Single Nucleotide , Severity of Illness Index
7.
BMC Med Genomics ; 14(1): 38, 2021 02 03.
Article in English | MEDLINE | ID: covidwho-1063194

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.


Subject(s)
COVID-19/diagnosis , Life Style , Mendelian Randomization Analysis/methods , Alcohol Drinking , Body Mass Index , COVID-19/genetics , COVID-19/virology , Exercise , Genetic Variation , Genome-Wide Association Study , Humans , Linkage Disequilibrium , Odds Ratio , Risk Factors , SARS-CoV-2/isolation & purification , Severity of Illness Index , Smoking
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