Common Methods for Performing Mendelian Randomization

Causal relationships between COVID-19 and venous thromboembolism: A mendelian randomization analysis

Objective: Observational studies show the correlation between COVID-19 and venous thromboembolism (VTE) risk. However, the causal effects remain uncertain. We aimed to explore the potential causal association between COVID-19 and VTE using Mendelian randomization (MR) design. Methods: Two-sample MR was used to evaluate the potential causality between COVID-19 and VTE by selecting single-nucleotide polymorphisms (SNPs) as instrumental variables (IVs) from genome-wide association studies (GWAS). The weighted median, MR-Egger, simple mode, and weighted mode were employed as supplementary methods for MR estimations, with the inverse-variance weighted (IVW) method serving as the principal analysis. In addition, we took sensitivity analyses, including Cochran's test, MR-Pleiotropy Residual Sum and Outlier (MR-PRESSO), and leave-one-out analysis to ensure that we obtained stable and reliable results. Results: Our study selected 26 COVID-19 severity, 31 COVID-19 hospitalization, and 13 COVID-19 susceptibility SNPs as instrumental variables. The IVW analysis results revealed that there was no causal relationship between COVID-19 severity, hospitalization, or susceptibility and VTE, with odds ratios of 0.974 (95%CI: 0.936-1.013, p = 0.19), 0.976 (95%CI: 0.918-1.039, p = 0.447), and 0.908 (95%CI: 0.775-1.065, p = 0.235), respectively. The IVW approach yielded consistent results with MR-Egger, Weighted Median simple mode, and weighted mode. MR-PRESSO and sensitivity analysis further confirmed the stability and consistency of the MR results. Conclusions: This study did not find evidence to support a causal relationship between COVID-19 and VTE at the genetic level. Further investigation is warranted to determine if the significant association reported in previous observational studies between the two is due to confounding factors.

Integrating plasma proteomics with genome-wide association data to identify novel drug targets for inflammatory bowel disease

Inflammatory bowel disease (IBD) is a chronic disease that includes Crohn's disease (CD) and ulcerative colitis (UC). Although genome-wide association studies (GWASs) have identified many relevant genetic risk loci, the impact of these loci on protein abundance and their potential utility as clinical therapeutic targets remain uncertain. Therefore, this study aimed to investigate the pathogenesis of IBD and identify effective therapeutic targets through a comprehensive and integrated analysis. We systematically integrated GWAS data related to IBD, UC and CD (N = 25,305) by the study of de Lange KM with the human blood proteome (N = 7213) by the Atherosclerosis Risk in Communities (ARIC) study. Proteome-wide association study (PWAS), mendelian randomisation (MR) and Bayesian colocalisation analysis were used to identify proteins contributing to the risk of IBD. Integrative analysis revealed that genetic variations in IBD, UC and CD affected the abundance of five (ERAP2, RIPK2, TALDO1, CADM2 and RHOC), three (VSIR, HGFAC and CADM2) and two (MST1 and FLRT3) cis-regulated plasma proteins, respectively (P < 0.05). Among the proteins identified via Bayesian colocalisation analysis, CADM2 was found to be an important common protein between IBD and UC. A drug and five druggable target genes were identified from DGIdb after Bayesian colocalisation analysis. Our study's findings from genetic and proteomic approaches have identified compelling proteins that may serve as important leads for future functional studies and potential drug targets for IBD (UC and CD).

Causal relationships between lung cancer and sepsis: a genetic correlation and multivariate mendelian randomization analysis

Background

Former research has emphasized a correlation between lung cancer (LC) and sepsis, but the causative link remains unclear.

Method

This study used univariate Mendelian Randomization (MR) to explore the causal relationship between LC, its subtypes, and sepsis. Linkage Disequilibrium Score (LDSC) regression was used to calculate genetic correlations. Multivariate MR was applied to investigate the role of seven confounding factors. The primary method utilized was inverse-variance-weighted (IVW), supplemented by sensitivity analyses to assess directionality, heterogeneity, and result robustness.

Results

LDSC analysis revealed a significant genetic correlation between LC and sepsis (genetic correlation = 0.325, p = 0.014). Following false discovery rate (FDR) correction, strong evidence suggested that genetically predicted LC (OR = 1.172, 95% CI 1.083-1.269, p = 8.29 × 10-5, P fdr = 2.49 × 10-4), squamous cell lung carcinoma (OR = 1.098, 95% CI 1.021-1.181, p = 0.012, P fdr = 0.012), and lung adenocarcinoma (OR = 1.098, 95% CI 1.024-1.178, p = 0.009, P fdr = 0.012) are linked to an increased incidence of sepsis. Suggestive evidence was also found for small cell lung carcinoma (Wald ratio: OR = 1.156, 95% CI 1.047-1.277, p = 0.004) in relation to sepsis. The multivariate MR suggested that the partial impact of all LC subtypes on sepsis might be mediated through body mass index. Reverse analysis did not find a causal relationship (p > 0.05 and P fdr > 0.05).

Conclusion

The study suggests a causative link between LC and increased sepsis risk, underscoring the need for integrated sepsis management in LC patients.

Depression and risk of infectious diseases: A mendelian randomization study

Previous observational inquiries have revealed a correlation between depression and infectious maladies. This study seeks to elucidate the causal linkages between depression, specifically Major Depressive Disorder (MDD), and infectious diseases. Nevertheless, the causative nature of the association between MDD and infectious diseases remains elusive. Two-sample Mendelian Randomization (MR) analyses was executed utilizing single nucleotide polymorphisms (SNPs) significantly connected with MDD and infectious diseases as instrumental variables (IVs). A series of sensitivity analyses were subsequently conducted. Genetic variants linked to MDD were employed as instrumental variables sourced from a genome-wide meta-analyses comprising 500,199 individuals. Summary-level data on five infectious diseases, including candidiasis, pneumonia, skin and soft tissue infections (SSTI), upper respiratory tract infections (URTI), and urinary tract infections (UTI), were acquired from the UK Biobank and FinnGen study. Our findings evinced that genetically predicted MDD exhibited a heightened risk of candidiasis (OR = 1.52, 95% CI 1.06-2.17; P = 2.38E-02), pneumonia (OR = 1.14, 95% CI 1.01-1.29; P = 3.16E-02), URTI (OR = 1.23, 95% CI 1.12-1.36; P = 3.71E-05), and UTI (OR = 1.26, 95% CI 1.12-1.42; P = 8.90E-05). Additionally, we identified bidirectional causal relationships between UTI and MDD. The associations between MDD and the risk of URTI and UTI remained consistent in multivariable MR analyses, accounting for genetically predicted smoking and body mass index. In conclusion, this investigation ascertained a causal connection between MDD and the susceptibility to infectious diseases, particularly URTI and UTI.

The impact of bone mineral density on the risk of falling: evidence from genetic correlation and Mendelian randomization analysis

BACKGROUND

Falls are the most common consequence of low bone mineral density (BMD). However, due to limitations inherent in observational studies, the causal relationship between the two remains unestablished.

METHODS

This study utilized Mendelian Randomization (MR) analysis to explore the causal relationship between BMD and the risk of falling, incorporating linkage disequilibrium score (LDSC) regression for genetic correlation assessment. The primary method was inverse-variance weighted (IVW), supplemented with sensitivity analyses and the causal analysis using summary effect estimates (CAUSE) to address heterogeneity and pleiotropy biases.

RESULTS

LDSC analysis indicated significant genetic correlations between BMD at various sites and falling risk (rg range: -0.82 to 0.76, all P < 0.05). IVW analysis, with False Discovery Rate (FDR) correction, showed a protective causal effect of total body BMD (OR = 0.85, 95% CI 0.82-0.88, P = 7.63 × 10-17, PFDR = 1.91 × 10-16), femoral neck BMD (OR = 0.81, 95% CI 0.75-0.88, P = 3.33 × 10-7, PFDR = 5.55 × 10-7), lumbar spine BMD (OR = 0.85, 95% CI 0.79-0.91, P = 9.56 × 10-7, PFDR = 1.20 × 10-6), and heel BMD (OR = 0.82, 95% CI 0.79-0.81, P = 1.69 × 10-39, PFDR = 8.45 × 10-39) on falling risk. No causal relationship was found for forearm BMD (OR = 1.02, 95% CI 0.94-1.11, P = 0.64, PFDR = 0.64). Replication datasets and CAUSE analysis provided causal evidence consistent with the main findings.

CONCLUSION

The study established a causal relationship between BMD at four different sites and the risk of falling, highlighting potential areas for targeted prevention strategies.

DHEA and response to antidepressant treatment: A Mendelian Randomization analysis

Treatment response is hard to predict and detailed mechanisms unknown. Lower levels of the dehydroepiandrosterone sulphate (DHEA(S)) - a precursor to testosterone and estrogen - have been associated to depression and to response to antidepressant treatment. Previous studies however may have been ridden by confounding and reverse causation. The aim of this study is to evaluate whether higher levels of DHEA(S) are causally linked to response to antidepressants using mendelian randomization (MR). We performed a Two-sample MR analysis using data the largest publicly available GWAS of DHEA(S) levels (n = 14,846) using eight common genetic variants associated to DHEA(S) (seven single nucleotide polymorphisms and one variant rs2497306) and the largest GWAS of antidepressant response (n = 5218) using various MR methods (IVW, MR Egger, Weighted mean, weighted mode, MR-PRESSO) and single SNP analysis. We further investigated for pleiotropy conducting a look up on PhenoScanner and GWAS Catalog. Results show no evidence for DHEA(S) gene risk score from any of MR methods, however, we found a significant association on individual variant analysis for rs11761538, rs17277546, and rs2497306. There was some evidence for heterogeneity and pleiotropy. This is the first paper to show some evidence for a causal association of genetically-predicted DHEA and improvement of depressive symptoms. The effect is not a simple linear effect, and we were unable to dissect whether the effect was direct effect of DHEA(S), mediated by DHEA(S) or on the pathway is not yet clear. Further studies using more refined instrumental variables will help clarify this association.

Approaches to estimate bidirectional causal effects using Mendelian randomization with application to body mass index and fasting glucose

Mendelian randomization (MR) is an epidemiological framework using genetic variants as instrumental variables (IVs) to examine the causal effect of exposures on outcomes. Statistical methods based on unidirectional MR (UMR) are widely used to estimate the causal effects of exposures on outcomes in observational studies. To estimate the bidirectional causal effects between two phenotypes, investigators have naively applied UMR methods separately in each direction. However, bidirectional causal effects between two phenotypes create a feedback loop that biases the estimation when UMR methods are naively applied. To overcome this limitation, we proposed two novel approaches to estimate bidirectional causal effects using MR: BiRatio and BiLIML, which are extensions of the standard ratio, and limited information maximum likelihood (LIML) methods, respectively. We compared the performance of the two proposed methods with the naive application of UMR methods through extensive simulations of several scenarios involving varying numbers of strong and weak IVs. Our simulation results showed that when multiple strong IVs are used, the proposed methods provided accurate bidirectional causal effect estimation in terms of median absolute bias and relative median absolute bias. Furthermore, compared to the BiRatio method, the BiLIML method provided a more accurate estimation of causal effects when weak IVs were used. Therefore, based on our simulations, we concluded that the BiLIML should be used for bidirectional causal effect estimation. We applied the proposed methods to investigate the potential bidirectional relationship between obesity and diabetes using the data from the Multi-Ethnic Study of Atherosclerosis cohort. We used body mass index (BMI) and fasting glucose (FG) as measures of obesity and type 2 diabetes, respectively. Our results from the BiLIML method revealed the bidirectional causal relationship between BMI and FG in across all racial populations. Specifically, in the White/Caucasian population, a 1 kg/m2 increase in BMI increased FG by 0.70 mg/dL (95% confidence interval [CI]: 0.3517-1.0489; p = 8.43×10-5), and 1 mg/dL increase in FG increased BMI by 0.10 kg/m2 (95% CI: 0.0441-0.1640; p = 6.79×10-4). Our study provides novel findings and quantifies the effect sizes of the bidirectional causal relationship between BMI and FG. However, further studies are needed to understand the biological and functional mechanisms underlying the bidirectional pathway.

The role of thyroid function in borderline personality disorder and schizophrenia: a Mendelian Randomisation study

BACKGROUND

Genome-wide association studies have reported a genetic overlap between borderline personality disorder (BPD) and schizophrenia (SCZ). Epidemiologically, the direction and causality of the association between thyroid function and risk of BPD and SCZ are unclear. We aim to test whether genetically predicted variations in TSH and FT4 levels or hypothyroidism are associated with the risk of BPD and SCZ.

METHODS

We employed Mendelian Randomisation (MR) analyses using genetic instruments associated with TSH and FT4 levels as well as hypothyroidism to examine the effects of genetically predicted thyroid function on BPD and SCZ risk. Bidirectional MR analyses were employed to investigate a potential reverse causal association.

RESULTS

Genetically predicted higher FT4 was not associated with the risk of BPD (OR: 1.18; P = 0.60, IVW) or the risk of SCZ (OR: 0.93; P = 0.19, IVW). Genetically predicted higher TSH was not associated with the risk of BPD (OR: 1.11; P = 0.51, IVW) or SCZ (OR: 0.98, P = 0.55, IVW). Genetically predicted hypothyroidism was not associated with BPD or SCZ. We found no evidence for a reverse causal effect between BPD or SCZ on thyroid function.

CONCLUSIONS

We report evidence for a null association between genetically predicted FT4, TSH or hypothyroidism with BPD or SCZ risk. There was no evidence for reverse causality.

Association of plasma proteomics with incident coronary heart disease in individuals with and without type 2 diabetes: results from the population-based KORA study

BACKGROUND

Coronary heart disease (CHD) is a major global health concern, especially among individuals with type 2 diabetes (T2D). Given the crucial role of proteins in various biological processes, this study aimed to elucidate the aetiological role and predictive performance of protein biomarkers on incident CHD in individuals with and without T2D.

METHODS

The discovery cohort included 1492 participants from the Cooperative Health Research in the Region of Augsburg (KORA) S4 study with 147 incident CHD cases (45 vs. 102 cases in the group with T2D and without T2D, respectively) during 15.6 years of follow-up. The validation cohort included 888 participants from the KORA-Age1 study with 70 incident CHD cases (19 vs. 51 cases in the group with T2D and without T2D, respectively) during 6.9 years of follow-up. We measured 233 plasma proteins related to cardiovascular disease and inflammation using proximity extension assay technology. Associations of proteins with incident CHD were assessed using Cox regression and Mendelian randomization (MR) analysis. Predictive models were developed using priority-Lasso and were evaluated on top of Framingham risk score variables using the C-index, category-free net reclassification index (cfNRI), and relative integrated discrimination improvement (IDI).

RESULTS

We identified two proteins associated with incident CHD in individuals with and 29 in those without baseline T2D, respectively. Six of these proteins are novel candidates for incident CHD. MR suggested a potential causal role for hepatocyte growth factor in CHD development. The developed four-protein-enriched model for individuals with baseline T2D (ΔC-index: 0.017; cfNRI: 0.253; IDI: 0.051) and the 12-protein-enriched model for individuals without baseline T2D (ΔC-index: 0.054; cfNRI: 0.462; IDI: 0.024) consistently improved CHD prediction in the discovery cohort, while in the validation cohort, significant improvements were only observed for selected performance measures (with T2D: cfNRI: 0.633; without T2D: ΔC-index: 0.038; cfNRI: 0.465).

CONCLUSIONS

This study identified novel protein biomarkers associated with incident CHD in individuals with and without T2D and reaffirmed previously reported protein candidates. These findings enhance our understanding of CHD pathophysiology and provide potential targets for prevention and treatment.

The Impact of Different Intensities of Physical Activity on Serum Urate and Gout: A Mendelian Randomization Study

Physical activity is a potential protective factor against gout, but the role of exercise intensity in this context remains unclear. To overcome the limitations of observational studies in causal inference, this study employed a two-sample Mendelian randomization approach to explore the impact of different genetically proxied/predicted intensities of physical activity on serum urate concentration and the incidence of gout. Our data related to physical activity, serum urate, and gout were obtained from the UK Biobank, the Global Urate Genetics Consortium (GUGC), and the FinnGen dataset, respectively. Walking was included as representative of typical low-intensity physical activity in the analysis, and the other two types were moderate and vigorous physical activities. The estimation methods we used included the inverse-variance-weighted (IVW) method, MR-Egger regression, weighted-median method, simple-mode method, and weighted-mode method. Sensitivity analyses involved Rucker's framework, Cochran's Q test, funnel plots, MR-PRESSO outlier correction, and leave-one-out analysis. We found suggestive evidence from the inverse-variance-weighted method that moderate physical activity was a potential factor in reducing the incidence of gout (OR = 0.628, p = 0.034), and this association became more substantial in our subsequent sensitivity analysis (OR = 0.555, p = 0.006). However, we observed no distinctive effects of physical activity on serum urate concentration. In conclusion, our study supports some findings from observational studies and emphasizes the preventive role of moderate physical activity against gout. Given the limitations of the existing datasets, we call for future reexamination and expansion of our findings using new GWAS data.

Genetic association analysis of dietary intake and idiopathic pulmonary fibrosis: a two-sample mendelian randomization study

BACKGROUND

IPF is a complex lung disease whose aetiology is not fully understood, but diet may have an impact on its development and progression. Therefore, we investigated the potential causal connection between dietary intake and IPF through TSMR to offer insights for early disease prevention recommendations.

METHODS

The study incorporated 29 dietary exposure factors, oily fish intake, bacon intake, processed meat intake, poultry intake, beef intake, pork intake, lamb/mutton intake, non-oily fish intake, fresh fruit intake, cooked vegetable intake, baked bean intake, fresh tomato intake, tinned tomato intake, salad/raw vegetable intake, Fresh fruit intake, coffee intake, tea intake, water intake, red wine intake, average weekly beer plus cider intake, alcoholic drinks per week, cereal intake, bread intake, whole-wheat intake, whole-wheat cereal intake, cheese intake, yogurt intake, salt added to food and whole egg intake. The study explored the causal link between diet and IPF using TSMR analysis, predominantly the IVW method, and performed sensitivity analyses to validate the results.

RESULT

The study revealed that consuming oily fish, yogurt, and dried fruits had a protective effect against IPF, whereas the consumption of alcoholic beverages and beef was linked to an increased risk of IPF.

CONCLUSION

In this MR study, it was discovered that the consumption of oily fish, yogurt, and dried fruits exhibited a protective effect against IPF, whereas the intake of alcoholic beverages and beef was associated with an elevated risk of IPF. These findings underscore the significance of making informed and timely dietary decisions in IPF prevention.

Exploring the impact of computer game playing on cognitive function, Alzheimer's disease risk, and brain-derived neurotrophic factor levels: Basic evidence from Mendelian randomization

Introduction

The potential positive impact of computer game playing on cognitive function and its potential role in reducing the risk of Alzheimer's disease (AD) has been suggested. However, current observational studies have certain limitations. We utilized Mendelian randomization (MR) alongside extensive genome-wide association study (GWAS) data to examine the relationship between computer game playing, cognitive function, risk of AD, and levels of brain-derived neurotrophic factor (BDNF).

Methods

We collected datasets on computer game playing, cognition function, risk of AD, and BDNF level from the IEU Open GWAS project. Causal effects were assessed using various MR methods, including inverse variance weighted (IVW), weighted median, MR-Egger, simple mode, and weighted mode. To ensure the accuracy of the results, sensitivity analyses were conducted.

Results

Our analysis revealed a significant association between computer game playing and cognitive function (β  =  0.801, 95% CI: 0.351, 1.328, P  =  0.001). There was no statistically significant association between computer game playing and either BDNF level or risk of AD (β  =  -0.112, 95%CI: -1.315, 1.091, P  =  0.855; OR = 1.000, 95% CI: 1.004, 0.997, P  =  0.891, respectively). We further confirmed the reliability of our evidence through the MR-Egger intercept test, MR-PRESSO global test, Cochran's Q test, and funnel plots.

Conclusion

The results of our study indicate that engaging in computer game playing may confer a safeguarding influence on cognitive function. This underscores the potential advantages associated with computer gaming. Nevertheless, given the constraints inherent in our research, further investigation is warranted to substantiate our findings and delve into the underlying mechanisms.

Mendelian randomization indicates causal effects of estradiol levels on kidney function in males

Context

Chronic kidney disease (CKD) is a public health burden worldwide. Epidemiological studies observed an association between sex hormones, including estradiol, and kidney function.

Objective

We conducted a Mendelian randomization (MR) study to assess a possible causal effect of estradiol levels on kidney function in males and females.

Design

We performed a bidirectional two-sample MR using published genetic associations of serum levels of estradiol in men (n = 206,927) and women (n = 229,966), and of kidney traits represented by estimated glomerular filtration rate (eGFR, n = 567,460), urine albumin-to-creatinine ratio (UACR, n = 547,361), and CKD (n = 41,395 cases and n = 439,303 controls) using data obtained from the CKDGen Consortium. Additionally, we conducted a genome-wide association study using UK Biobank cohort study data (n = 11,798 men and n = 6,835 women) to identify novel genetic associations with levels of estradiol, and then used these variants as instruments in a one-sample MR.

Results

The two-sample MR indicated that genetically predicted estradiol levels are significantly associated with eGFR in men (beta = 0.077; p = 5.2E-05). We identified a single locus at chromosome 14 associated with estradiol levels in men being significant in the one-sample MR on eGFR (beta = 0.199; p = 0.017). We revealed significant results with eGFR in postmenopausal women and with UACR in premenopausal women, which did not reach statistical significance in the sensitivity MR analyses. No causal effect of eGFR or UACR on estradiol levels was found.

Conclusions

We conclude that serum estradiol levels may have a causal effect on kidney function. Our MR results provide starting points for studies to develop therapeutic strategies to reduce kidney disease.

The impact of COVID-19 on pulmonary, neurological, and cardiac outcomes: evidence from a Mendelian randomization study

Background

Long COVID is a clinical entity characterized by persistent health problems or development of new diseases, without an alternative diagnosis, following SARS-CoV-2 infection that affects a significant proportion of individuals globally. It can manifest with a wide range of symptoms due to dysfunction of multiple organ systems including but not limited to cardiovascular, hematologic, neurological, gastrointestinal, and renal organs, revealed by observational studies. However, a causal association between the genetic predisposition to COVID-19 and many post-infective abnormalities in long COVID remain unclear.

Methods

Here we employed Mendelian randomization (MR), a robust genetic epidemiological approach, to investigate the potential causal associations between genetic predisposition to COVID-19 and long COVID symptoms, namely pulmonary (pneumonia and airway infections including bronchitis, emphysema, asthma, and rhinitis), neurological (headache, depression, and Parkinson's disease), cardiac (heart failure and chest pain) diseases, and chronic fatigue. Using two-sample MR, we leveraged genetic data from a large COVID-19 genome-wide association study and various disorder-specific datasets.

Results

This analysis revealed that a genetic predisposition to COVID-19 was significantly causally linked to an increased risk of developing pneumonia, airway infections, headache, and heart failure. It also showed a strong positive correlation with chronic fatigue, a frequently observed symptom in long COVID patients. However, our findings on Parkinson's disease, depression, and chest pain were inconclusive.

Conclusion

Overall, these findings provide valuable insights into the genetic underpinnings of long COVID and its diverse range of symptoms. Understanding these causal associations may aid in better management and treatment of long COVID patients, thereby alleviating the substantial burden it poses on global health and socioeconomic systems.

Investigating linear and nonlinear associations of LDL cholesterol with incident chronic kidney disease, atherosclerotic cardiovascular disease and all-cause mortality: A prospective and Mendelian randomization study

BACKGROUND AND AIMS

Observational studies suggest potential nonlinear associations of low-density lipoprotein cholesterol (LDL-C) with cardio-renal diseases and mortality, but the causal nature of these associations is unclear. We aimed to determine the shape of causal relationships of LDL-C with incident chronic kidney disease (CKD), atherosclerotic cardiovascular disease (ASCVD) and all-cause mortality, and to evaluate the absolute risk of adverse outcomes contributed by LDL-C itself.

METHODS

Observational analysis and one-sample Mendelian randomization (MR) with linear and nonlinear assumptions were performed using the UK Biobank of >0.3 million participants with no reported prescription of lipid-lowering drugs. Two-sample MR on summary-level data from the Global Lipid Genetics Consortium (N = 296,680) and the CKDGen (N = 625,219) was employed to replicate the relationship for kidney traits. The 10-year probabilities of the outcomes was estimated by integrating the MR and Cox models.

RESULTS

Observationally, participants with low LDL-C were significantly associated with a decreased risk of ASCVD, but an increased risk of CKD and all-cause mortality. Univariable MR showed an inverse total effect of LDL-C on incident CKD (HR [95% CI]:0.84 [0.73-0.96]; p = 0.011), a positive effect on ASCVD (1.41 [1.29-1.53]; p<0.001), and no significant causal effect on all-cause mortality. Multivariable MR, controlling for high-density lipoprotein cholesterol (HDL-C) and triglycerides, identified a positive direct effect on ASCVD (1.32 [1.18-1.47]; p<0.001), but not on CKD and all-cause mortality. These results indicated that genetically predicted low LDL-C had an inverse indirect effect on CKD mediated by HDL-C and triglycerides, which was validated by a two-sample MR analysis using summary-level data from the Global Lipid Genetics Consortium (N = 296,680) and the CKDGen consortium (N = 625,219). Suggestive evidence of a nonlinear causal association between LDL-C and CKD was found. The 10-year probability curve showed that LDL-C concentrations below 3.5 mmol/L were associated with an increased risk of CKD.

CONCLUSIONS

In the general population, lower LDL-C was causally associated with lower risk of ASCVD, but appeared to have a trade-off for an increased risk of CKD, with not much effect on all-cause mortality. LDL-C concentration below 3.5 mmol/L may increase the risk of CKD.

Causal association of gastroesophageal reflux disease with obstructive sleep apnea and sleep-related phenotypes: a bidirectional two-sample Mendelian randomization study

Background

The interactions and associations between obstructive sleep apnea (OSA), sleep-related phenotypes (SRPs), and gastroesophageal reflux disease (GERD) are complex, thus it is hard to explore the effect and direction of causalities.

Study objectives

A bidirectional Mendelian randomization (MR) study was performed to explore causal associations of GERD with OSA and SRPs (including insomnia, morningness, sleep duration, ease of getting up, daytime napping, daytime dozing, and snoring).

Methods

First, we gathered summary statistics from publicly available databases. Subsequently, we identified single-nucleotide polymorphisms without strong linkage (r2 ≤ 0.001) by referencing relevant genome-wide association studies that met genome-wide significance criteria. Our primary analysis relied on inverse variance weighted to estimate the causal relationship. To ensure the validity of our findings, we also conducted several sensitivity analyses. These included MR Pleiotropy RESidual Sum and Outlier to detect and correct for potential pleiotropic effects, MR-Egger to assess directional pleiotropy, and weighted median analysis to further evaluate heterogeneity and pleiotropy. For the initial MR analysis, when causality was indicated by the results, instrumental variables that were significantly linked to the aforementioned confounding factors were removed. We will re-analyze the data after excluding outcome-related single nucleotide polymorphisms to confirm that the results are still consistent with the previous results.

Results

GERD was found to increase the risk of OSA (OR = 1.53, 95% CI = 1.37-1.70, p = 5.3 × 10-15), insomnia (OR = 1.14, 95% CI = 1.10-1.19, p = 1.3 × 10-10), snoring (OR = 1.09, 95% CI = 1.04-1.13, p = 6.3 × 10-5) and less sleep duration (OR = 0.94, 95% CI = 0.91-0.97, p = 3.7 × 10-4). According to the reverse-direction analysis, there is an elevated risk of GERD associated with OSA (OR = 1.07, 95% CI = 1.02-1.12, p = 0.005), insomnia (OR = 1.95, 95% CI = 1.60-2.37, p = 1.92 × 10-11) and snoring (OR = 1.74, 95% CI = 1.37-2.21, p = 4.4 × 10-6).

Conclusion

Genetic susceptibility to GERD can elevate the likelihood of experiencing insomnia, snoring, and OSA, in addition to diminishing sleep duration. Conversely, a reverse MR analysis indicates that ameliorating any one of insomnia, snoring, or OSA can mitigate the risk of developing GERD.

Interplay Between Chronic Kidney Disease, Hypertension, and Stroke: Insights From a Multivariable Mendelian Randomization Analysis

BACKGROUND AND OBJECTIVES

Chronic kidney disease (CKD) increases the risk of stroke, but the extent through which this association is mediated by hypertension is unknown. We leveraged large-scale genetic data to explore causal relationships between CKD, hypertension, and cerebrovascular disease phenotypes.

METHODS

We used data from genome-wide association studies of European ancestry to identify genetic proxies for kidney function (CKD diagnosis, estimated glomerular filtration rate [eGFR], and urinary albumin-to-creatinine ratio [UACR]), systolic blood pressure (SBP), and cerebrovascular disease (ischemic stroke and its subtypes and intracerebral hemorrhage). We then conducted univariable, multivariable, and mediation Mendelian randomization (MR) analyses to investigate the effect of kidney function on stroke risk and the proportion of this effect mediated through hypertension.

RESULTS

Univariable MR revealed associations between genetically determined lower eGFR and risk of all stroke (odds ratio [OR] per 1-log decrement in eGFR, 1.77; 95% CI 1.31-2.40; p < 0.001), ischemic stroke (OR 1.81; 95% CI 1.31-2.51; p < 0.001), and most strongly with large artery stroke (LAS) (OR 3.00; 95% CI 1.33-6.75; p = 0.008). These associations remained significant in the multivariable MR analysis, controlling for SBP (OR 1.98; 95% CI 1.39-2.82; p < 0.001 for all stroke; OR 2.16; 95% CI 1.48-3.17; p < 0.001 for ischemic stroke; OR 4.35; 95% CI 1.84-10.27; p = 0.001 for LAS), with only a small proportion of the total effects mediated by SBP (6.5% [0.7%-16.8%], 6.6% [0.8%-18.3%], and 7.2% [0.5%-24.8%], respectively). Total, direct and indirect effect estimates were similar across a number of sensitivity analyses (weighted median, MR-Egger regression).

DISCUSSION

Our results demonstrate an independent causal effect of impaired kidney function, as assessed by decreased eGFR, on stroke risk, particularly LAS, even when controlled for SBP. Targeted prevention of kidney disease could lower atherosclerotic stroke risk independent of hypertension.

Borderline personality disorder and thyroid diseases: a Mendelian randomization study

Background

Previous studies have shown that there is a correlation between diseases of the thyroid gland and mental illnesses; however, any causal relationship between them remains unclear. This study aimed to evaluate the causal relationship between borderline personality disorder and four thyroid diseases.

Methods

The causal relationship was inferred using double-sample Mendelian randomization analysis of appropriate instrumental variables from genome-wide association studies. We calculated the estimated value of the effect using various statistical methods.

Results

Borderline personality disorder was a risk factor for non-toxic single thyroid nodules with each increase in standard deviation increasing the risk of a non-toxic single thyroid nodule by 1.13 times (odds ratio = 1.131; 95% confidence interval, 1.006-1.270; P=0.039). There was no evidence of a correlation between borderline personality disorder and hyperthyroidism/thyrotoxicosis, hypothyroidism, and autoimmune thyroiditis.

Conclusion

This study showed that there is a positive causal correlation between borderline personality disorder and non-toxic single thyroid nodules but not with other thyroid diseases. This means that thyroid status should be monitored in patients with borderline personality disorder. However, the possibility of a causal relationship between other mental illnesses and thyroid diseases requires further research.

Associations of plasma proteomics with type 2 diabetes and related traits: results from the longitudinal KORA S4/F4/FF4 Study

AIMS/HYPOTHESIS

This study aimed to elucidate the aetiological role of plasma proteins in glucose metabolism and type 2 diabetes development.

METHODS

We measured 233 proteins at baseline in 1653 participants from the Cooperative Health Research in the Region of Augsburg (KORA) S4 cohort study (median follow-up time: 13.5 years). We used logistic regression in the cross-sectional analysis (n=1300), and Cox regression accounting for interval-censored data in the longitudinal analysis (n=1143). We further applied two-level growth models to investigate associations with repeatedly measured traits (fasting glucose, 2 h glucose, fasting insulin, HOMA-B, HOMA-IR, HbA1c), and two-sample Mendelian randomisation analysis to investigate causal associations. Moreover, we built prediction models using priority-Lasso on top of Framingham-Offspring Risk Score components and evaluated the prediction accuracy through AUC.

RESULTS

We identified 14, 24 and four proteins associated with prevalent prediabetes (i.e. impaired glucose tolerance and/or impaired fasting glucose), prevalent newly diagnosed type 2 diabetes and incident type 2 diabetes, respectively (28 overlapping proteins). Of these, IL-17D, IL-18 receptor 1, carbonic anhydrase-5A, IL-1 receptor type 2 (IL-1RT2) and matrix extracellular phosphoglycoprotein were novel candidates. IGF binding protein 2 (IGFBP2), lipoprotein lipase (LPL) and paraoxonase 3 (PON3) were inversely associated while fibroblast growth factor 21 was positively associated with incident type 2 diabetes. LPL was longitudinally linked with change in glucose-related traits, while IGFBP2 and PON3 were linked with changes in both insulin- and glucose-related traits. Mendelian randomisation analysis suggested causal effects of LPL on type 2 diabetes and fasting insulin. The simultaneous addition of 12 priority-Lasso-selected biomarkers (IGFBP2, IL-18, IL-17D, complement component C1q receptor, V-set and immunoglobulin domain-containing protein 2, IL-1RT2, LPL, CUB domain-containing protein 1, vascular endothelial growth factor D, PON3, C-C motif chemokine 4 and tartrate-resistant acid phosphatase type 5) significantly improved the predictive performance (ΔAUC 0.0219; 95% CI 0.0052, 0.0624).

CONCLUSIONS/INTERPRETATION

We identified new candidates involved in the development of derangements in glucose metabolism and type 2 diabetes and confirmed previously reported proteins. Our findings underscore the importance of proteins in the pathogenesis of type 2 diabetes and the identified putative proteins can function as potential pharmacological targets for diabetes treatment and prevention.

Prospective Blood Transcriptomics Study in a Motor Vehicle Collision Cohort Identified a Protective Function of the SAMD15 Gene Against Chronic Pain

Traumatic brain injuries following motor vehicle collisions (MVCs) are ubiquitous. Surprisingly, there are no correlates between concussion impact force and long-term pain outcomes. To study the molecular underpinnings of chronic pain after MVC, we assembled a prospective cohort of 36 subjects that experienced MVC and suffered documented mild traumatic brain injuries. For each participant, a first blood sample was drawn within 72 hours of the collision, then a second one at the 6-month mark. Pain was also assessed at the second blood draw to determine if pain became chronic or resolved. Blood samples enabled transcriptomics analyses for immune cells. At the transcriptome-wide level, we found that Sterile Alpha Motif Domain Containing 15 (SAMD15) mRNA was significantly upregulated with time in subjects who resolved their pain whereas unregulated in those with persistent pain. Using several large publicly available datasets, such as the UK Biobank and the GTeX portal, we then linked elevated SAMD15 gene expression, elevated neutrophils cell counts, and decreased risk for chronic pain to increased dosage of the T allele at SNP rs4903580, situated within SAMD15's gene locus. The causality between the components of our model was established and supported by Mendelian randomization. Overall, our results support the role of SAMD15 as a potential gene effector for neutrophil-dependent chronic pain development. PERSPECTIVE: This article highlights the potential protective role of the SAMD15 gene against chronic pain following a mild traumatic brain injury. The expression of the gene is associated with a SNP rs4903580, which is itself associated with neutrophils counts as well as chronic pain in large genetic studies.

Genome-wide associations, polygenic risk, and Mendelian randomization reveal limited interactions between John Henryism and cynicism

BACKGROUND

John Henryism (JH) is a strategy for dealing with chronic psychological stress characterized by high levels of physical effort and work. Cynicism is a belief that people are motivated primarily by self-interest. High scores on the JH scale and cynicism measures correlate with an increased risk of cardiovascular disease. High cynicism is also a hallmark of burnout syndrome, another known risk factor for heart disease.

AIM

To evaluate possible interactions between JH and cynicism hoping to clarify risk factors of burnout.

METHODS

We analyzed genetic and psychological data available from the Database of Genotypes and Phenotypes for genome-wide associations with these traits. We split the total available samples and used plink to perform the association studies on the discovery set (n = 1852, 80%) and tested for replication using the validation set (n = 465). We used scikit-learn to perform supervised machine learning for developing genetic risk algorithms.

RESULTS

We identified 2, 727, and 204 genetic associations for scores on the JH, cynicism and cynical distrust (CD) scales, respectively. We also found 173 associations with high cynicism, 109 with high CD, but no associations with high JH. We also produced polygenic classifiers for high cynicism using machine learning with areas under the receiver operator characteristics curve greater than 0.7.

CONCLUSION

We found significant genetic components to these traits but no evidence of an interaction. Therefore, while there may be a genetic risk, JH is not likely a burnout risk factor.

C-Reactive Protein Levels and Risk of Cardiovascular Diseases: A Two-Sample Bidirectional Mendelian Randomization Study

Elevated C-reactive protein (CRP) levels are an indicator of inflammation, a major risk factor for cardiovascular disease (CVD). However, this potential association in observational studies remains inconclusive. We performed a two-sample bidirectional Mendelian randomization (MR) study using publicly available GWAS summary statistics to evaluate the relationship between CRP and CVD. Instrumental variables (IVs) were carefully selected, and multiple approaches were used to make robust conclusions. Horizontal pleiotropy and heterogeneity were evaluated using the MR-Egger intercept and Cochran's Q-test. The strength of the IVs was determined using F-statistics. The causal effect of CRP on the risk of hypertensive heart disease (HHD) was statistically significant, but we did not observe a significant causal relationship between CRP and the risk of myocardial infarction, coronary artery disease, heart failure, or atherosclerosis. Our primary analyses, after performing outlier correction using MR-PRESSO and the Multivariable MR method, revealed that IVs that increased CRP levels also increased the HHD risk. However, after excluding outlier IVs identified using PhenoScanner, the initial MR results were altered, but the sensitivity analyses remained congruent with the results from the primary analyses. We found no evidence of reverse causation between CVD and CRP. Our findings warrant updated MR studies to confirm the role of CRP as a clinical biomarker for HHD.

What can Mendelian randomization contribute to biological anthropology?

Uncovering causal relationships between exposures and outcomes can be difficult in observational studies because of the potential for confounding and reverse causation to produce biased estimates. Conversely, randomized controlled trials (RCTs) provide the strongest evidence for causality but they are not always feasible. Mendelian randomization (MR) is a method that aims to strengthen causal inference using genetic variants as proxies or instrumental variables (IVs) for exposures, to overcome the above-mentioned biases. Since allele segregation occurs at random from parents to offspring, and alleles for a trait assort independently from those for other traits, MR studies have frequently been compared to "natural" RCTs. In biological anthropology (BA) relationships between variables of interest are usually evaluated using observational data, often remaining descriptive, and other approaches to causal inference have seldom been implemented. Here, we propose the use of MR to investigate cause and effect relationships in BA studies and provide examples to show how that can be done across areas of BA relevance, such as adaptation to the environment, nutrition and life history theory. While we consider MR a useful addition to the biological anthropologist's toolbox, we advocate the adoption of a wide range of methods, affected by different types of biases, in order to better answer the important causal questions for the discipline.

Schizophrenia and cardiometabolic abnormalities: A Mendelian randomization study

Background: Individuals with a diagnosis of schizophrenia are known to be at high risk of premature mortality due to poor physical health, especially cardiovascular disease, diabetes, and obesity. The reasons for these physical health outcomes within this patient population are complex. Despite well-documented cardiometabolic adverse effects of certain antipsychotic drugs and lifestyle factors, schizophrenia may have an independent effect. Aims: To investigate if there is evidence that schizophrenia is causally related to cardiometabolic traits (blood lipids, anthropometric traits, glycaemic traits, blood pressure) and vice versa using bi-directional two-sample Mendelian randomization (MR) analysis. Methods: We used 185 genetic variants associated with schizophrenia from the latest Psychiatric Genomics Consortium GWAS (n = 130,644) in the forward analysis (schizophrenia to cardiometabolic traits) and genetic variants associated with the cardiometabolic traits from various consortia in the reverse analysis (cardiometabolic traits to schizophrenia), both at genome-wide significance (5 × 10-8). The primary method was inverse-variance weighted MR, supported by supplementary methods such as MR-Egger, as well as median and mode-based methods. Results: In the forward analysis, schizophrenia was associated with slightly higher low-density lipoprotein (LDL) cholesterol levels (0.013 SD change in LDL per log odds increase in schizophrenia risk, 95% CI, 0.001-0.024 SD; p = 0.027) and total cholesterol levels (0.013 SD change in total cholesterol per log odds increase in schizophrenia risk, 95% CI, 0.002-0.025 SD; p = 0.023). However, these associations did not survive multiple testing corrections. There was no evidence of a causal effect of cardiometabolic traits on schizophrenia in the reverse analysis. Discussion: Dyslipidemia and obesity in schizophrenia patients are unlikely to be driven primarily by schizophrenia itself. Therefore, lifestyle, diet, antipsychotic drugs side effects, as well as shared mechanisms for metabolic dysfunction and schizophrenia such as low-grade systemic inflammation could be possible reasons for the apparent increased risk of metabolic disease in people with schizophrenia. Further research is needed to examine the shared immune mechanism hypothesis.

Exploration of the Causal Association Between Behavioral Risk Factors and Gallstone Disease Development in Two European Ancestry Populations

Introduction Risk factors for developing gallstones are related to disturbances in either cholesterol or bilirubin metabolism in the biliary tract. The risk of forming gallstones can be associated with chronic illnesses, dietary habits, reduced gallbladder motility, and medications. Our study aims to explore the causal relationship between multiple risk factors, including nutritional habits (cheese intake, salad intake, processed meat intake, coffee drinking), smoking behavior, overall obesity measured by body mass index (BMI), lipid biomarkers, total bilirubin and maternal diabetes mellitus (DM) and the development of gallstone disease in two different populations of European ancestry (United Kingdom Biobank (UKB) and FinnGen). Materials and methods Using publicly available genome-wide association studies (GWAS) data, we performed a two-sample Mendelian randomization (MR) to examine the association between risk factors and gallstone development. Exposures used in this study included age of smoking initiation, smoking intensity, coffee intake, cheese intake, salad intake, processed meat intake, BMI, and lipid biomarkers (cholesterol, low-density lipoproteins (LDL), triglycerides (TG), and high-density lipoproteins (HDL)). Current analyses were based on 93 single nucleotide polymorphisms (SNPs) for smoking initiation, four SNPs for smoking intensity, 65 SNPs for cheese intake, three SNPs for coffee intake, 22 SNPs for salad intake, 23 SNPs for processed meat intake, 79 SNPs for BMI, 26 SNPs for maternal DM, 89 SNPs for total bilirubin, 46 SNPs for cholesterol, 41 SNPs for LDL, 55 SNPs for TG, and 89 SNPs for HDL. The outcome in this study is gallstones/cholelithiasis. To evaluate the causal relationships between these risk factors and gallstones, two-sample MR methods were used. TwoSampleMR package in R software version 4.0.5 (R Foundation for Statistical Computing, Vienna, Austria) was used to obtain MR analyses and sensitivity analyses. Results  In the UKB, genetic predispositions to smoking initiation, BMI, and total bilirubin were significantly associated with an increased risk of gallstones. The odds of gallstones would increase per 1-SD increase of genetically estimated smoking initiation (OR: 1.004, P=0.008), BMI (OR: 1.02, P<0.001), and total bilirubin (OR: 1.0001, P=0.025). Conversely, genetic predispositions to cheese intake, coffee intake, cholesterol, LDL, and TG were statistically significantly associated with a decreased risk of gallstones (OR=0.99, P=0.014; OR=0.97, P=0.009; OR=0.99, P=0.006; OR=0.99, P=0.01; and OR=0.99, P<0.001, respectively). In FinnGen, genetic predispositions to BMI and total bilirubin were significantly associated with an increased risk of gallstones. The odds of gallstones would increase per 1-SD increase of genetically estimated BMI (OR: 1.7, P<0.001) and total bilirubin (OR: 1.02, P=0.002). Conversely, genetic predispositions to cheese intake, coffee intake, cholesterol, LDL, and TG were statistically significantly associated with a decreased risk of gallstones (OR=0.23, P=0.006; OR=0.42, P=0.041; OR=0.77, P=0.034; OR=0.88, P=0.008; and OR=0.70, P=0.005, respectively). Conclusion  Genetically estimated BMI and total bilirubin levels were associated with increased risk of gallstones among the two populations while genetically estimated cheese intake, coffee intake, and cholesterol, LDL, and TG levels factors were consistently associated with reduced risk of gallstones among the two populations.

The Association Between Insulin Use and Asthma: An Epidemiological Observational Analysis and Mendelian Randomization Study

BACKGROUND

Asthma is a common respiratory disease caused by genetic and environmental factors, but the contribution of insulin use to the risk of asthma remains unclear. This study aimed to investigate the association between insulin use and asthma in a large population-based cohort, and further explore their causal relationship by Mendelian randomization (MR) analysis.

METHODS

An epidemiological study including 85,887 participants from the National Health and Nutrition Examination Survey (NHANES) 2001-2018 was performed to evaluate the association between insulin use and asthma. Based on the inverse-variance weighted approach, MR analysis were conducted to estimate the causal effect of insulin use on asthma from the UKB and FinnGen datasets, respectively.

RESULTS

In the NHANES cohort, we found that insulin use was associated with an increased risk of asthma [odd ratio (OR) 1.38; 95% CI 1.16-1.64; p < 0.001]. For the MR analysis, we found a causal relationship between insulin use and a higher risk of asthma in both Finn (OR 1.10; p < 0.001) and UK Biobank cohorts (OR 1.18; p < 0.001). Meanwhile, there was no causal association between diabetes and asthma. After multivariable adjustment for diabetes in UKB cohort, the insulin use remained significantly associated with an increased risk of asthma (OR 1.17, p < 0.001).

CONCLUSIONS

An association between insulin use and an increased risk of asthma was found via the real-world data from the NHANES. In addition, the current study identified a causal effect and provided a genetic evidence of insulin use and asthma. More studies are needed to elucidate the mechanisms underlying the association between insulin use and asthma.

Causal association between vitamin D and diabetic neuropathy: a Mendelian randomization analysis

OBJECTIVES

Vitamin D has been linked to diabetic neuropathy (DN) in previous epidemiological observational studies, however, their findings are inconsistent. The causal relationship between vitamin D and DN remains unknown. In this study we aim to investigate the causal association of serum 25-hydroxyvitamin D (25OHD) and DN.

METHODS

Based on summary statistics from publicly available genome-wide association studies (GWAS) database, we detected the genetic correlation between serum 25OHD levels and DN by a two-sample Mendelian randomization (MR) analysis. The inverse-variance weighted (IVW) method was used as the primary analysis, weighted median and MR-Egger were applied as complementary methods for MR estimates. In addition, we took sensitivity analyses including Cochran's Q test, MR-Pleiotropy Residual Sum and Outlier (MR-PRESSO) and leave-one-out analysis to ensure that we obtained stable and reliable results.

RESULTS

Our MR study showed no significant genetic association between serum 25OHD levels and DN (OR = 1.13, 95% CI = 0.81-1.57, P = 0.46). Furthermore, in the reverse direction analysis, we did not find a significant causal effect of DN and serum 25OHD levels (OR = 0.99, 95% CI = 0.98-1.00, P = 0.09). Results of MR-Egger, Weighted Median were consistent with those of the IVW method. The sensitivity analysis suggesting that no significant heterogeneity and genetic pleiotropy was observed.

CONCLUSIONS

Our results provided no evidence to support the causal association of serum 25OHD levels with DN.

Mendelian randomization as a tool to inform drug development using human genetics

Drug development is essential to the advancement of human health, however, the process is slow, costly, and at high risk of failure at all stages. A promising strategy for expediting and improving the probability of success in the drug development process is the use of naturally randomized human genetic variation for drug target identification and validation. These data can be harnessed using the Mendelian randomization (MR) analytic paradigm to proxy the lifelong consequences of genetic perturbations of drug targets. In this review, we discuss the myriad applications of the MR paradigm for human drug target identification and validation. We review the methodology and applications of MR, key limitations of MR, and potential future opportunities for research. Throughout the review, we refer to illustrative examples of MR analyses investigating the consequences of genetic inhibition of interleukin 6 signaling which, in some cases, have anticipated results from randomized controlled trials. As human genetic data become more widely available, we predict that MR will serve as a key pillar of support for drug development efforts.

Mendelian randomization on the association of obesity with vitamin D: Guangzhou Biobank Cohort Study

BACKGROUND

Mendelian randomization (MR) analyses from the West provide evidence that obesity causes lower 25-hydroxyvitamin D [25(OH)D]. As Asian populations are prone to metabolic disorders at a lower body mass index (BMI), whether the association remains in Asian is unclear. We studied whether obesity causes vitamin D deficiency using MR analysis in Chinese.

METHODS

We used data from the Guangzhou Biobank Cohort Study. A genetic score including seven BMI-related single-nucleotide polymorphisms (n = 15,249) was used as the instrumental variable (IV) for BMI. Two-stage least square regression and conventional multivariable linear regression in 2,036 participants with vitamin D data were used to analyze association of BMI with vitamin D.

RESULTS

Proportion of variation explained by the genetic score was 0.7% and the first stage F-statistic for MR analysis was 103. MR analyses showed that each 1 kg/m² higher BMI was associated with lower 25(OH)D by -2.35 (95% confidence interval (CI) -4.68 to -0.02) nmol/L. In conventional multivariable linear regression, higher BMI was also associated with lower 25(OH)D (β = -0.26 nmol/L per 1 kg/m² increase in BMI, 95% CI -0.46 to -0.06). Sensitivity analyses using two-sample IV analysis and leave-one-out method showed similar results.

CONCLUSION

We have first shown by MR and conventional multivariable linear regression that higher BMI causes vitamin D deficiency in Chinese. Our findings highlight the importance of weight control and suggest that vitamin D supplementation may be needed in individuals with overweight or obesity.

Can Intelligence Affect Alcohol-, Smoking-, and Physical Activity-Related Behaviors? A Mendelian Randomization Study

People with high levels of intelligence are more aware of risk factors, therefore choosing a healthier lifestyle. This assumption seems reasonable, but is it true? Previous studies appear to agree and disagree. To cope with the uncertainty, we designed a mendelian randomization (MR) study to examine the causal effects of genetically proxied intelligence on alcohol-, smoking-, and physical activity (PA)-related behaviors. We obtained genome-wide association study (GWAS) datasets concerning these variables from separate studies or biobanks and used inverse-variance weighted (IVW) or MR-Egger estimator to evaluate the causal effects according to an MR protocol. The MR-Egger intercept test, MR-PRESSO, and funnel plots were employed for horizontal pleiotropy diagnosis. The Steiger test (with reliability test), Cochran's Q test, MR-PRESSO, and leave-one-out method were employed for sensitivity analysis. We found significant or potential effects of intelligence on alcohol dependence (OR = 0.749, p = 0.003), mental and behavioral disorders due to alcohol (OR = 0.814, p = 0.009), smoking (OR = 0.585, p = 0.005), and smoking cessation (OR = 1.334, p = 0.001). Meanwhile, we found significant or potential effects on walking duration (B = -0.066, p < 0.001), walking frequency (B = -0.055, p = 0.031), moderate PA frequency (B = -0.131, p < 0.001), and vigorous PA frequency (B = -0.070, p = 0.001), but all in a negative direction. In conclusion, our findings reinforce some existing knowledge, indicate the complexity of the health impacts of human intelligence, and underline the value of smoking and alcohol prevention in less intelligent populations. Given the existing limitations in this study, particularly the potential reverse causality in some estimations, re-examinations are warranted in future research.

Causal associations between site-specific cancer and diabetes risk: A two-sample Mendelian randomization study

BACKGROUND

Both cancer and diabetes are complex chronic diseases that have high economic costs for society. The co-occurrence of these two diseases in people is already well known. The causal effects of diabetes on the development of several malignancies have been established, but the reverse causation of these two diseases (e.g., what type of cancer can cause T2D) has been less investigated.

METHODS

Multiple Mendelian randomization (MR) methods, such as the inverse-variance weighted (IVW) method, weighted median method, MR-Egger, and MR pleiotropy residual sum and outlier test, were performed to evaluate the causal association of overall and eight site-specific cancers with diabetes risk using genome-wide association study summary data from different consortia, such as Finngen and UK biobank.

RESULTS

A suggestive level of evidence was observed for the causal association between lymphoid leukaemia and diabetes by using the IVW method in MR analyses (P = 0.033), indicating that lymphoid leukaemia increased diabetes risk with an odds ratio of 1.008 (95% confidence interval, 1.001-1.014). Sensitivity analyses using MR-Egger and weighted median methods showed consistent direction of the association compared with the IVW method. Overall and seven other site-specific cancers under investigation (i.e., multiple myeloma, non-Hodgkin lymphoma, and cancer of bladder, brain, stomach, lung, and pancreas) were not causally associated with diabetes risk.

CONCLUSIONS

The causal relationship between lymphoid leukaemia and diabetes risk points to the necessity of diabetes prevention amongst leukaemia survivors as a strategy for ameliorating the associated disease burden.

Inference for a Large Directed Acyclic Graph with Unspecified Interventions

Statistical inference of directed relations given some unspecified interventions (i.e., the intervention targets are unknown) is challenging. In this article, we test hypothesized directed relations with unspecified interventions. First, we derive conditions to yield an identifiable model. Unlike classical inference, testing directed relations requires to identify the ancestors and relevant interventions of hypothesis-specific primary variables. To this end, we propose a peeling algorithm based on nodewise regressions to establish a topological order of primary variables. Moreover, we prove that the peeling algorithm yields a consistent estimator in low-order polynomial time. Second, we propose a likelihood ratio test integrated with a data perturbation scheme to account for the uncertainty of identifying ancestors and interventions. Also, we show that the distribution of a data perturbation test statistic converges to the target distribution. Numerical examples demonstrate the utility and effectiveness of the proposed methods, including an application to infer gene regulatory networks. The R implementation is available at https://github.com/chunlinli/intdag.

Metabolically favorable adiposity and bone mineral density: a Mendelian randomization analysis

OBJECTIVE

This analysis assessed the putative causal association between genetically predicted percent body fat and areal bone mineral density (aBMD) and, more specifically, the association between genetically predicted metabolically "favorable adiposity" (MFA) and aBMD at clinically relevant bone sites.

METHODS

Mendelian randomization was used to assess the relationship of MFA and percent body fat with whole-body, lumbar spine, femoral neck, and forearm aBMD. Sex-stratified and age-stratified exploratory analyses were conducted.

RESULTS

In all MR analyses, genetically predicted MFA was inversely associated with aBMD for the whole body (β = -0.053, p = 0.0002), lumbar spine (β = -0.075; p = 0.0001), femoral neck (β = -0.045; p = 0.008), and forearm (β = -0.115; p = 0.001). This negative relationship was strongest in older individuals and did not differ by sex. The relationship between genetically predicted percent body fat and aBMD was nonsignificant across all Mendelian randomization analyses. Several loci that were associated at a genome-wide significance level (p < 5 × 10^-8 ) in opposite directions with body fat and aBMD measures were also identified.

CONCLUSIONS

This study did not support the hypothesis that MFA protects against low aBMD. Instead, it showed that MFA may result in lower aBMD. Further research is needed to understand how MFA affects aBMD and other components of bone health such as bone turnover, bone architecture, and osteoporotic fractures.

Genetic and clinical determinants of abdominal aortic diameter: genome-wide association studies, exome array data and Mendelian randomization study

Progressive dilation of the infrarenal aortic diameter is a consequence of the ageing process and is considered the main determinant of abdominal aortic aneurysm (AAA). We aimed to investigate the genetic and clinical determinants of abdominal aortic diameter (AAD). We conducted a meta-analysis of genome-wide association studies in 10 cohorts (n = 13 542) imputed to the 1000 Genome Project reference panel including 12 815 subjects in the discovery phase and 727 subjects [Partners Biobank cohort 1 (PBIO)] as replication. Maximum anterior-posterior diameter of the infrarenal aorta was used as AAD. We also included exome array data (n = 14 480) from seven epidemiologic studies. Single-variant and gene-based associations were done using SeqMeta package. A Mendelian randomization analysis was applied to investigate the causal effect of a number of clinical risk factors on AAD. In genome-wide association study (GWAS) on AAD, rs74448815 in the intronic region of LDLRAD4 reached genome-wide significance (beta = -0.02, SE = 0.004, P-value = 2.10 × 10-8). The association replicated in the PBIO1 cohort (P-value = 8.19 × 10-4). In exome-array single-variant analysis (P-value threshold = 9 × 10-7), the lowest P-value was found for rs239259 located in SLC22A20 (beta = 0.007, P-value = 1.2 × 10-5). In the gene-based analysis (P-value threshold = 1.85 × 10-6), PCSK5 showed an association with AAD (P-value = 8.03 × 10-7). Furthermore, in Mendelian randomization analyses, we found evidence for genetic association of pulse pressure (beta = -0.003, P-value = 0.02), triglycerides (beta = -0.16, P-value = 0.008) and height (beta = 0.03, P-value < 0.0001), known risk factors for AAA, consistent with a causal association with AAD. Our findings point to new biology as well as highlighting gene regions in mechanisms that have previously been implicated in the genetics of other vascular diseases.

COX7A2L genetic variants determine cardiorespiratory fitness in mice and human

Mitochondrial respiratory complexes form superassembled structures called supercomplexes. COX7A2L is a supercomplex-specific assembly factor in mammals, although its implication for supercomplex formation and cellular metabolism remains controversial. Here we identify a role for COX7A2L for mitochondrial supercomplex formation in humans. By using human cis-expression quantitative trait loci data, we highlight genetic variants in the COX7A2L gene that affect its skeletal muscle expression specifically. The most significant cis-expression quantitative trait locus is a 10-bp insertion in the COX7A2L 3' untranslated region that increases messenger RNA stability and expression. Human myotubes harboring this insertion have more supercomplexes and increased respiration. Notably, increased COX7A2L expression in the muscle is associated with lower body fat and improved cardiorespiratory fitness in humans. Accordingly, specific reconstitution of Cox7a2l expression in C57BL/6J mice leads to higher maximal oxygen consumption, increased lean mass and increased energy expenditure. Furthermore, Cox7a2l expression in mice is induced specifically in the muscle upon exercise. These findings elucidate the genetic basis of mitochondrial supercomplex formation and function in humans and show that COX7A2L plays an important role in cardiorespiratory fitness, which could have broad therapeutic implications in reducing cardiovascular mortality.

Retinol and Retinol Binding Protein 4 Levels and Cardiometabolic Disease Risk

BACKGROUND

Despite mechanistic studies linking retinol and RBP4 (retinol binding protein 4) to the pathogenesis of cardiovascular diseases (CVD) and type 2 diabetes (T2D), epidemiological evidence is still conflicting. We investigated whether conflicting results of previous studies may be explained by differences in the association of retinol and RBP4 with cardiometabolic risk across subgroups with distinct sex, hypertension state, liver, or kidney function.

METHODS

We used case-cohorts nested in the EPIC (European Prospective Investigation Into Cancer and Nutrition)-Potsdam cohort (N=27 548) comprising a random sample of participants (n=2500) and all physician-verified cases of incident CVD (n=508, median follow-up time 8.2 years) and T2D (n=820, median follow-up time 6.3 years). We estimated nonlinear and linear multivariable-adjusted associations between the biomarkers and cardiometabolic diseases by restricted cubic splines and Cox regression, respectively, testing potential interactions with hypertension, liver, and kidney function. Additionally, we performed 2-sample Mendelian Randomization analyses in publicly available data.

RESULTS

The association of retinol with cardiometabolic risk was modified by hypertension state (P interaction CVD<0.001; P interaction T2D<0.001). Retinol was associated with lower cardiometabolic risk in participants with treated hypertension (hazard ratio_{per SD} [95% CI]: CVD, 0.71 [0.56-0.90]; T2D, 0.81 [0.70-0.94]) but with higher cardiometabolic risk in normotensive participants (CVD, 1.32 [1.06-1.64]; T2D, 1.15 [0.98-1.36]). Our analyses also indicated a significant interaction between RBP4 and hypertension on CVD risk (P interaction=0.04). Regarding T2D risk, we observed a u-shaped association with RBP4 in women (P nonlinearity=0.01, P effect=0.02) and no statistically significant association in men. The biomarkers' interactions with liver or kidney function were not statistically significant. Hypertension state-specific associations for retinol concentrations with cardiovascular mortality risk were replicated in National Health and Nutrition Examination Survey III.

CONCLUSIONS

Our findings suggest a hypertension-dependent relationship between plasma retinol and cardiometabolic risk and complex interactions of RBP4 with sex and hypertension on cardiometabolic risk.

An Overview of Methods and Exemplars of the Use of Mendelian Randomisation in Nutritional Research

Objectives: It is crucial to elucidate the causal relevance of nutritional exposures (such as dietary patterns, food intake, macronutrients intake, circulating micronutrients), or biomarkers in non-communicable diseases (NCDs) in order to find effective strategies for NCD prevention. Classical observational studies have found evidence of associations between nutritional exposures and NCD development, but such studies are prone to confounding and other biases. This has direct relevance for translation research, as using unreliable evidence can lead to the failure of trials of nutritional interventions. Facilitated by the availability of large-scale genetic data, Mendelian randomization studies are increasingly used to ascertain the causal relevance of nutritional exposures and biomarkers for many NCDs. Methods: A narrative overview was conducted in order to demonstrate and describe the utility of Mendelian randomization studies, for individuals with little prior knowledge engaged in nutritional epidemiological research. Results: We provide an overview, rationale and basic description of the methods, as well as strengths and limitations of Mendelian randomization studies. We give selected examples from the contemporary nutritional literature where Mendelian randomization has provided useful evidence on the potential causal relevance of nutritional exposures. Conclusions: The selected exemplars demonstrate the importance of well-conducted Mendelian randomization studies as a robust tool to prioritize nutritional exposures for further investigation.

Adipose methylome integrative-omic analyses reveal genetic and dietary metabolic health drivers and insulin resistance classifiers

BACKGROUND

There is considerable evidence for the importance of the DNA methylome in metabolic health, for example, a robust methylation signature has been associated with body mass index (BMI). However, visceral fat (VF) mass accumulation is a greater risk factor for metabolic disease than BMI alone. In this study, we dissect the subcutaneous adipose tissue (SAT) methylome signature relevant to metabolic health by focusing on VF as the major risk factor of metabolic disease. We integrate results with genetic, blood methylation, SAT gene expression, blood metabolomic, dietary intake and metabolic phenotype data to assess and quantify genetic and environmental drivers of the identified signals, as well as their potential functional roles.

METHODS

Epigenome-wide association analyses were carried out to determine visceral fat mass-associated differentially methylated positions (VF-DMPs) in SAT samples from 538 TwinsUK participants. Validation and replication were performed in 333 individuals from 3 independent cohorts. To assess functional impacts of the VF-DMPs, the association between VF and gene expression was determined at the genes annotated to the VF-DMPs and an association analysis was carried out to determine whether methylation at the VF-DMPs is associated with gene expression. Further epigenetic analyses were carried out to compare methylation levels at the VF-DMPs as the response variables and a range of different metabolic health phenotypes including android:gynoid fat ratio (AGR), lipids, blood metabolomic profiles, insulin resistance, T2D and dietary intake variables. The results from all analyses were integrated to identify signals that exhibit altered SAT function and have strong relevance to metabolic health.

RESULTS

We identified 1181 CpG positions in 788 genes to be differentially methylated with VF (VF-DMPs) with significant enrichment in the insulin signalling pathway. Follow-up cross-omic analysis of VF-DMPs integrating genetics, gene expression, metabolomics, diet, and metabolic traits highlighted VF-DMPs located in 9 genes with strong relevance to metabolic disease mechanisms, with replication of signals in FASN, SREBF1, TAGLN2, PC and CFAP410. PC methylation showed evidence for mediating effects of diet on VF. FASN DNA methylation exhibited putative causal effects on VF that were also strongly associated with insulin resistance and methylation levels in FASN better classified insulin resistance (AUC=0.91) than BMI or VF alone.

CONCLUSIONS

Our findings help characterise the adiposity-associated methylation signature of SAT, with insights for metabolic disease risk.

Your height affects your health: genetic determinants and health-related outcomes in Taiwan

BACKGROUND

Height is an important anthropometric measurement and is associated with many health-related outcomes. Genome-wide association studies (GWASs) have identified hundreds of genetic loci associated with height, mainly in individuals of European ancestry.

METHODS

We performed genome-wide association analyses and replicated previously reported GWAS-determined single nucleotide polymorphisms (SNPs) in the Taiwanese Han population (Taiwan Biobank; n = 67,452). A genetic instrument composed of 251 SNPs was selected from our GWAS, based on height and replication results as the best-fit polygenic risk score (PRS), in accordance with the clumping and p-value threshold method. We also examined the association between genetically determined height (PRS₂₅₁) and measured height (phenotype). We performed observational (phenotype) and genetic PRS₂₅₁ association analyses of height and health-related outcomes.

RESULTS

GWAS identified 6843 SNPs in 89 genomic regions with genome-wide significance, including 18 novel loci. These were the most strongly associated genetic loci (EFEMP1, DIS3L2, ZBTB38, LCORL, HMGA1, CS, and GDF5) previously reported to play a role in height. There was a positive association between PRS₂₅₁ and measured height (p < 0.001). Of the 14 traits and 49 diseases analyzed, we observed significant associations of measured and genetically determined height with only eight traits (p < 0.05/[14 + 49]). Height was positively associated with body weight, waist circumference, and hip circumference but negatively associated with body mass index, waist-hip ratio, body fat, total cholesterol, and low-density lipoprotein cholesterol (p < 0.05/[14 + 49]).

CONCLUSIONS

This study contributes to the understanding of the genetic features of height and health-related outcomes in individuals of Han Chinese ancestry in Taiwan.

Human Serum Metabolites as Potential Mediators from Type 2 Diabetes and Obesity to COVID-19 Severity and Susceptibility: Evidence from Mendelian Randomization Study

Obesity, type 2 diabetes (T2D), and severe coronavirus disease 2019 (COVID-19) are closely associated. The aim of this study was to elucidate the casual and mediating relationships of human serum metabolites on the pathways from obesity/T2D to COVID-19 using Mendelian randomization (MR) techniques. We performed two-sample MR to study the causal effects of 309 metabolites on COVID-19 severity and susceptibility, based on summary statistics from genome-wide association studies (GWAS) of metabolites (n = 7824), COVID-19 phenotypes (n = 2,586,691), and obesity (n = 322,154)/T2D traits (n = 898,130). We conducted two-sample network MR analysis to determine the mediating metabolites on the causal path from obesity/T2D to COVID-19 phenotypes. We used multivariable MR analysis (MVMR) to discover causal metabolites independent of body mass index (BMI). Our MR analysis yielded four causal metabolites that increased the risk of severe COVID-19, including 2-stearoylglycerophosphocholine (OR 2.15; 95% CI 1.48–3.11), decanoylcarnitine (OR 1.32; 95% CI 1.17–1.50), thymol sulfate (OR 1.20; 95% CI 1.10–1.30), and bradykinin-des-arg(9) (OR 1.09; 95% CI 1.05–1.13). One significant mediator, gamma-glutamyltyrosine, lay on the causal path from T2D/obesity to severe COVID-19, with 16.67% (0.64%, 32.70%) and 6.32% (1.76%, 10.87%) increased risk, respectively, per one-standard deviation increment of genetically predicted T2D and BMI. Our comprehensive MR analyses identified credible causative metabolites, mediators of T2D and obesity, and obesity-independent causative metabolites for severe COVID-19. These biomarkers provide a novel basis for mechanistic studies for risk assessment, prognostication, and therapeutic purposes in COVID-19.

Understanding the assumptions underlying Mendelian randomization

With the rapidly increasing availability of large genetic data sets in recent years, Mendelian Randomization (MR) has quickly gained popularity as a novel secondary analysis method. Leveraging genetic variants as instrumental variables, MR can be used to estimate the causal effects of one phenotype on another even when experimental research is not feasible, and therefore has the potential to be highly informative. It is dependent on strong assumptions however, often producing biased results if these are not met. It is therefore imperative that these assumptions are well-understood by researchers aiming to use MR, in order to evaluate their validity in the context of their analyses and data. The aim of this perspective is therefore to further elucidate these assumptions and the role they play in MR, as well as how different kinds of data can be used to further support them.

Resting heart rate and incident atrial fibrillation: A stratified Mendelian randomization in the AFGen consortium

Background

Both elevated and low resting heart rates are associated with atrial fibrillation (AF), suggesting a U-shaped relationship. However, evidence for a U-shaped causal association between genetically-determined resting heart rate and incident AF is limited. We investigated potential directional changes of the causal association between genetically-determined resting heart rate and incident AF.

Method and results

Seven cohorts of the AFGen consortium contributed data to this meta-analysis. All participants were of European ancestry with known AF status, genotype information, and a heart rate measurement from a baseline electrocardiogram (ECG). Three strata of instrumental variable-free resting heart rate were used to assess possible non-linear associations between genetically-determined resting heart rate and the logarithm of the incident AF hazard rate: <65; 65–75; and >75 beats per minute (bpm). Mendelian randomization analyses using a weighted resting heart rate polygenic risk score were performed for each stratum.

We studied 38,981 individuals (mean age 59±10 years, 54% women) with a mean resting heart rate of 67±11 bpm. During a mean follow-up of 13±5 years, 4,779 (12%) individuals developed AF. A U-shaped association between the resting heart rate and the incident AF-hazard ratio was observed. Genetically-determined resting heart rate was inversely associated with incident AF for instrumental variable-free resting heart rates below 65 bpm (hazard ratio for genetically-determined resting heart rate, 0.96; 95% confidence interval, 0.94–0.99; p = 0.01). Genetically-determined resting heart rate was not associated with incident AF in the other two strata.

Conclusions

For resting heart rates below 65 bpm, our results support an inverse causal association between genetically-determined resting heart rate and incident AF.

Disentangling Independent and Mediated Causal Relationships Between Blood Metabolites, Cognitive Factors, and Alzheimer's Disease

Background

Education and cognition demonstrate consistent inverse associations with Alzheimer's disease (AD). The biological underpinnings, however, remain unclear. Blood metabolites reflect the end point of biological processes and are accessible and malleable. Identifying metabolites with etiological relevance to AD and disentangling how these relate to cognitive factors along the AD causal pathway could, therefore, offer unique insights into underlying causal mechanisms.

Methods

Using data from the largest metabolomics genome-wide association study (N ≈ 24,925) and three independent AD cohorts (N = 4725), cross-trait polygenic scores were generated and meta-analyzed. Metabolites genetically associated with AD were taken forward for causal analyses. Bidirectional two-sample Mendelian randomization interrogated univariable causal relationships between 1) metabolites and AD; 2) education and cognition; 3) metabolites, education, and cognition; and 4) education, cognition, and AD. Mediating relationships were computed using multivariable Mendelian randomization.

Results

Thirty-four metabolites were genetically associated with AD at p < .05. Of these, glutamine and free cholesterol in extra-large high-density lipoproteins demonstrated a protective causal effect (glutamine: 95% confidence interval [CI], 0.70 to 0.92; free cholesterol in extra-large high-density lipoproteins: 95% CI, 0.75 to 0.92). An AD-protective effect was also observed for education (95% CI, 0.61 to 0.85) and cognition (95% CI, 0.60 to 0.89), with bidirectional mediation evident. Cognition as a mediator of the education-AD relationship was stronger than vice versa, however. No evidence of mediation via any metabolite was found.

Conclusions

Glutamine and free cholesterol in extra-large high-density lipoproteins show protective causal effects on AD. Education and cognition also demonstrate protection, though education's effect is almost entirely mediated by cognition. These insights provide key pieces of the AD causal puzzle, important for informing future multimodal work and progressing toward effective intervention strategies.

Asthma and the risk of gastrointestinal disorders: a Mendelian randomization study

BACKGROUND

The question of whether asthma is causally related to gastrointestinal disorders remained unanswered so far. Thus, this study investigated whether there is such a relation and whether the time of onset of asthma plays a role in the occurrence of the following gastrointestinal disorders: peptic ulcer disease (PUD), gastroesophageal reflux disease (GORD), irritable bowel syndrome (IBS), and inflammatory bowel disease (IBD) including the distinction between Crohn's disease (CD) and ulcerative colitis (UC).

METHODS

Using summary data of genome-wide association studies (GWASs), we ran Mendelian randomization analyses based on up to 456,327 European participants. Outlier assessment, a series of sensitivity analyses and validation of IBD results in a second GWAS were performed to confirm the results.

RESULTS

Presented ORs represent the average change in the outcome per 2.72-fold increase in the prevalence of the exposure. Genetically predicted childhood-onset asthma was positively associated with PUD, GORD, and IBS with similar odds ratios near 1.003 and adjusted P-values from 0.007 (GORD) to 0.047 (PUD). Furthermore, it was inversely related to IBD (OR = 0.992, 95% CI: 0.986, 0.998, adjusted P = 0.023) and suggestively associated with its UC subtype (OR = 0.990, 95% CI: 0.982, 0.998, adjusted P = 0.059). There were no associations between genetically predicted adult-onset asthma and the mentioned gastrointestinal disorders.

CONCLUSIONS

This study provides evidence that the presence of asthma onset in childhood increases the risk for GORD, PUD, and IBS but decreases the risk for IBD in adults. The lower risk for IBD may be attributed to a lower risk primarily for UC.

NMR in Metabolomics: From Conventional Statistics to Machine Learning and Neural Network Approaches

NMR measurements combined with chemometrics allow achieving a great amount of information for the identification of potential biomarkers responsible for a precise metabolic pathway. These kinds of data are useful in different fields, ranging from food to biomedical fields, including health science. The investigation of the whole set of metabolites in a sample, representing its fingerprint in the considered condition, is known as metabolomics and may take advantage of different statistical tools. The new frontier is to adopt self-learning techniques to enhance clustering or classification actions that can improve the predictive power over large amounts of data. Although machine learning is already employed in metabolomics, deep learning and artificial neural networks approaches were only recently successfully applied. In this work, we give an overview of the statistical approaches underlying the wide range of opportunities that machine learning and neural networks allow to perform with accurate metabolites assignment and quantification.Various actual challenges are discussed, such as proper metabolomics, deep learning architectures and model accuracy.

Proteome-wide Mendelian randomization identifies causal links between blood proteins and severe COVID-19

In November 2021, the COVID-19 pandemic death toll surpassed five million individuals. We applied Mendelian randomization including >3,000 blood proteins as exposures to identify potential biomarkers that may indicate risk for hospitalization or need for respiratory support or death due to COVID-19, respectively. After multiple testing correction, using genetic instruments and under the assumptions of Mendelian Randomization, our results were consistent with higher blood levels of five proteins GCNT4, CD207, RAB14, C1GALT1C1, and ABO being causally associated with an increased risk of hospitalization or respiratory support/death due to COVID-19 (ORs = 1.12-1.35). Higher levels of FAAH2 were solely associated with an increased risk of hospitalization (OR = 1.19). On the contrary, higher levels of SELL, SELE, and PECAM-1 decrease risk of hospitalization or need for respiratory support/death (ORs = 0.80-0.91). Higher levels of LCTL, SFTPD, KEL, and ATP2A3 were solely associated with a decreased risk of hospitalization (ORs = 0.86-0.93), whilst higher levels of ICAM-1 were solely associated with a decreased risk of respiratory support/death of COVID-19 (OR = 0.84). Our findings implicate blood group markers and binding proteins in both hospitalization and need for respiratory support/death. They, additionally, suggest that higher levels of endocannabinoid enzymes may increase the risk of hospitalization. Our research replicates findings of blood markers previously associated with COVID-19 and prioritises additional blood markers for risk prediction of severe forms of COVID-19. Furthermore, we pinpoint druggable targets potentially implicated in disease pathology.