Mendelian randomization

A review on trends in development and translation of omics signatures in cancer

The field of cancer genomics and transcriptomics has evolved from targeted profiling to swift sequencing of individual tumor genome and transcriptome. The steady growth in genome, epigenome, and transcriptome datasets on a genome-wide scale has significantly increased our capability in capturing signatures that represent both the intrinsic and extrinsic biological features of tumors. These biological differences can help in precise molecular subtyping of cancer, predicting tumor progression, metastatic potential, and resistance to therapeutic agents. In this review, we summarized the current development of genomic, methylomic, transcriptomic, proteomic and metabolic signatures in the field of cancer research and highlighted their potentials in clinical applications to improve diagnosis, prognosis, and treatment decision in cancer patients.

A Mendelian randomization-based study of the causal relationship between leisure sedentary behavior and delirium

BACKGROUND

Delirium is an acute or subacute change in mental status caused by various factors. We evaluated the causal relationship between leisure sedentary behaviors (LSBs) and delirium.

METHODS

A two-sample Mendelian randomization (MR) study was performed to evaluate the causal relationship between sedentary behaviors (time spent watching television, time spent using computer, and time spent driving) and delirium. Statistical information for the associations between single nucleotide polymorphisms (SNPs) and the traits of interest was obtained from independent consortia that focused on European populations. The dataset for LSBs was acquired from genome-wide association studies (GWAS) comprising a substantial sample size: 437887 samples for time spent watching television, 360,895 for time spent using computer, and 310,555 for time spent driving. A GWAS with 1269 delirium cases and 209,487 controls was used to identify genetic variation underlying the time of LSBs. We used five complementary MR methods, including inverse variance weighted method (IVW), MR-Egger, weighted median, weighted mode, and simple mode.

RESULTS

Genetically predicted time spent watching television (odds ratio [OR]: 2.921, 95 % confidence interval [CI]: 1.381-6.179) demonstrated significant association with delirium (P = 0.005), whereas no significant associations were observed between time spent using computer (OR: 0.556, 95 % CI: 0.246-1.257, P = 0.158) and time spent driving (OR: 1.747, 95 % CI: 0.09-3. 40, P = 0.713) and delirium. Sensitivity analyses supported a causal interpretation, with limited evidence of significant bias from genetic pleiotropy. Moreover, our MR assumptions appeared to be upheld, enhancing the credibility of our conclusions.

LIMITATIONS

Larger sample sizes are needed to validate the findings of our study.

CONCLUSION

Time spent watching television is a significant risk factor for delirium. Reducing television time may be an important intervention for those at higher risk of delirium.

Mediating effect of metabolic syndrome in the association of educational attainment with intervertebral disc degeneration and low back pain

The causal association of educational attainment (EA) with intervertebral disc degeneration (IVDD) or low back pain (LBP), and the mediating effect of metabolic syndrome (MetS) in this association, is not studied to date. In this study, using summary statistics of genome-wide association studies primarily conducted in the individuals of European ancestry, Mendelian randomization (MR) analyses were performed to investigate: (1) the total and direct effects of EA on IVDD and LBP, (2) bidirectional associations of EA with MetS or the components of MetS, (3) causal effects of MetS or its components on IVDD and LBP, and (4) mediating effects of MetS or its components on the causal associations of EA with IVDD and LBP. Univariable MR analysis demonstrated that genetically proxied EA was inversely associated with IVDD (ORIVW: 0.90; 95 % CI: 0.87-0.92) and LBP (ORIVW: 0.86; 95 % CI: 0.84-0.89). Consistent results were obtained after adjusting for potential confounders (cognition, economic level, smoking traits, and metabolic factors). Mediation analysis proved that the effect of EA on IVDD mediated by MetS, waist circumference, and high-density lipoprotein cholesterol was 11.38 %, 9.22 %, and 2.17 %, respectively. Besides, MetS mediated 8.42 % and waist circumference mediated 5.81 % of the EA effects on LBP, respectively. Our findings provided support for MetS mediating the causal protective effects of EA on IVDD and LBP, which provided causal evidence to the etiology and intervention targets of IVDD and LBP.

Associations of metals and metal mixtures with glucose homeostasis: A combined bibliometric and epidemiological study

This study employs a combination of bibliometric and epidemiological methodologies to investigate the relationship between metal exposure and glucose homeostasis. The bibliometric analysis quantitatively assessed this field, focusing on study design, predominant metals, analytical techniques, and citation trends. Furthermore, we analyzed cross-sectional data from Beijing, examining the associations between 14 blood metals and 6 glucose homeostasis markers using generalized linear models (GLM). Key metals were identified using LASSO-PIPs criteria, and Bayesian kernel machine regression (BKMR) was applied to assess metal mixtures, introducing an "Overall Positive/Negative Effect" concept for deeper analysis. Our findings reveal an increasing research interest, particularly in selenium, zinc, cadmium, lead, and manganese. Urine (27.6%), serum (19.0%), and whole blood (19.0%) were the primary sample types, with cross-sectional studies (49.5%) as the dominant design. Epidemiologically, significant associations were found between 9 metals-cobalt, copper, lithium, manganese, nickel, lead, selenium, vanadium, zinc-and glucose homeostasis. Notably, positive-metal mixtures exhibited a significant overall positive effect on insulin levels, and notable interactions involving nickel were identified. These finding not only map the knowledge landscape of research in this domain but also introduces a novel perspective on the analysis strategies for metal mixtures.

Assessing the causal association between sleep apnea and the human gut microbiome composition: A two-sample Mendelian randomization study

Background

Studies have linked gut microbiota dysbiosis with sleep apnea; however, no causal relationship was found in human subjects. Finding new targets for the pathophysiology of sleep apnea might be made possible by systematically investigating the causal relationship between the human gut microbiota and sleep apnea.

Methods

A two-sample Mendelian randomization analysis was conducted. The human gut microbiome composition data, spanning five taxonomic levels, were acquired from a genome-wide association study that included 18,340 participants from 24 cohorts. Genome-wide association study data for sleep apnea were obtained from the Sleep Disorder Knowledge Portal for primary analysis and the FinnGen consortium for meta-analysis. Sensitivity analyses were conducted to evaluate heterogeneity and pleiotropy.

Results

Using inverse-variance weighted analysis, eight microbial taxa were initially found to be substantially linked with the apnea-hypopnea index. Only three microbial taxa remained significant associations with sleep apnea when combined with the FinnGen consortium (the class Bacilli: B = 8.21%, 95% CI = 0.93%-15.49%; p = 0.03; the order Lactobacillales: B = 7.55%, 95% CI = 0.25%-4.85%; p = 0.04; the genus RuminococcaceaeUCG009: B = -21.63%, 95% CI = -41.47% to -1.80%; p = 0.03).

Conclusions

Sleep apnea may lead to gut dysbiosis as significant reductions in butyrate-producing bacteria and increases in lactate-producing bacteria. By integrating genomes and metabolism, the evidence that three microbiome species are causally linked to sleep apnea may offer a fresh perspective on the underlying mechanisms of the condition.

Genetic architecture of brain morphology and overlap with neuropsychiatric traits

Uncovering the genetic architectures of brain morphology offers valuable insights into brain development and disease. Genetic association studies of brain morphological phenotypes have discovered thousands of loci. However, interpretation of these loci presents a significant challenge. One potential solution is exploring the genetic overlap between brain morphology and disorders, which can improve our understanding of their complex relationships, ultimately aiding in clinical applications. In this review, we examine current evidence on the genetic associations between brain morphology and neuropsychiatric traits. We discuss the impact of these associations on the diagnosis, prediction, and treatment of neuropsychiatric diseases, along with suggestions for future research directions.

Genetic insights into the relationship between immune cell characteristics and ischemic stroke: A bidirectional Mendelian randomization study

BACKGROUND AND PURPOSE

Ischemic stroke, a major contributor to global disability and mortality, is underpinned by intricate pathophysiological mechanisms, notably neuroinflammation and immune cell dynamics. Prior research has identified a nuanced and often paradoxical link between immune cell phenotypes and ischemic stroke susceptibility. The aim of this study was to elucidate the potential causal links between the median fluorescence intensity (MFI) and morphological parameters (MP) of 731 immune cell types and ischemic stroke risk.

METHODS

By analyzing extensive genetic datasets, we conducted comprehensive Mendelian randomization (MR) analyses to discern the genetic correlations between diverse immune cell attributes (MFI and MP) and ischemic stroke risk.

RESULTS

Our study identified key immune cell signatures linked to ischemic stroke risk. Both B cells and T cells, among other immune cell types, have a bidirectional influence on stroke risk. Notably, the regulatory T-cell phenotype demonstrates significant neuroprotective properties, with all odds ratio (OR) values and confidence intervals (CIs) being less than 1. Furthermore, CD39 phenotype immune cells, particularly CD39+ CD8+ T cells (inverse variance weighting [IVW] OR 0.92, 95% CI 0.87-0.97; p = 0.002) and CD39+ activated CD4 regulatory T cells (IVW OR 0.93, 95% CI 0.90-0.97; p < 0.001), show notable neuroprotection against ischemic stroke.

CONCLUSION

This investigation provides new genetic insights into the interplay between various immune cells and ischemic stroke, underscoring the complex role of immune processes in stroke pathogenesis. These findings lay a foundation for future research, which may confirm and expand upon these links, potentially leading to innovative immune-targeted therapies for stroke prevention and management.

Genetic evidence for the causal effects of C-reactive protein on self-reported habitual sleep duration

Inflammatory responses to acute stimuli are proposed to regulate sleep, but the relationship between chronic inflammation and habitual sleep duration is elusive. Here, we study this relation using genetically predicted level of chronic inflammation, indexed by CRP and IL6 signaling, and self-reported sleep duration. By Mendelian randomization analysis, we show that elevated CRP level within <10 mg/L has a homeostatic effect that facilitates maintaining 7-8 h sleep duration per day - making short-sleepers sleep longer (p = 2.42 × 10-2) and long-sleepers sleep shorter (1.87 × 10-7); but it is not associated with the overall sleep duration (p = 0.17). This homeostatic effect replicated in an independent CRP dataset. We observed causal effects of the soluble interleukin 6 receptor and gp130 on overall sleep duration (p = 1.62 × 10-8, p = 2.61 × 10-58, respectively), but these effects disappeared when CRP effects were accounted for in the model. Using polygenic score analysis, we found that the homeostatic effect of CRP on sleep duration stems primarily from the genetic variants within the CRP gene region: when genetic variants outside of this region were used to predict CRP levels, the opposite direction of effect was observed. In conclusion, we show that elevated CRP level may causally facilitate maintaining an optimal sleep duration that is beneficial to health, thus updating our current knowledge of immune regulation on sleep.

The impact of exercise on gene regulation in association with complex trait genetics

Endurance exercise training is known to reduce risk for a range of complex diseases. However, the molecular basis of this effect has been challenging to study and largely restricted to analyses of either few or easily biopsied tissues. Extensive transcriptome data collected across 15 tissues during exercise training in rats as part of the Molecular Transducers of Physical Activity Consortium has provided a unique opportunity to clarify how exercise can affect tissue-specific gene expression and further suggest how exercise adaptation may impact complex disease-associated genes. To build this map, we integrate this multi-tissue atlas of gene expression changes with gene-disease targets, genetic regulation of expression, and trait relationship data in humans. Consensus from multiple approaches prioritizes specific tissues and genes where endurance exercise impacts disease-relevant gene expression. Specifically, we identify a total of 5523 trait-tissue-gene triplets to serve as a valuable starting point for future investigations [Exercise; Transcription; Human Phenotypic Variation].

Lifestyle risk factors and all-cause and cause-specific mortality in the Mexico City prospective study: Assessing the influence of reverse causation

BACKGROUND

We examined the association between individual lifestyle risk factors with all-cause and cause-specific mortality.

METHODS

Prospective cohort study including 155,002 participants from the Mexico City Prospective Study. Cox regression models were used to estimate the association between individual lifestyle risk factors and all-cause and cause-specific mortality. Participants with prevalent diseases at baseline and participants who died during the first 2, 5, 10, and 15 years of follow-up were excluded to account for reverse causation.

RESULTS

27,469 people died during 18.3 years of follow-up years. Overweight and moderate alcohol consumption were inversely associated with all-cause mortality, while low physical activity and smoking were positively associated when all participants were included, regardless of prevalent disease or duration of follow-up. The direction of the association of overweight with all-cause mortality changed from inverse to positive after excluding the first 10 years of follow-up. Compared with normal weight, the hazard ratio (95 % confidence interval) was 1.17 (1.13,1.22) for obesity after excluding those who died in the first 5 years of follow-up and 1.71 (1.59,1.84) after excluding the first 15 years of follow-up. The magnitude of the association of alcohol intake, low physical activity, and smoking with mortality attenuated, whereas for fruits and vegetables increased, after excluding longer periods of follow-up.

LIMITATIONS

The data were collected exclusively in Mexico City; lifestyle risk factors were self-reported and thus prone to misclassification bias.

CONCLUSIONS

Reverse causation may influence both the magnitude and the direction of the associations between lifestyle risk factors and mortality.

Editorial: Are government early years learning and development frameworks evidence-based? A scientist's perspective

Not all young children attend nurseries, childminders or other group settings before they start school, but many do. It is common for countries to set out a framework to guide practice for early years providers (such as nurseries) to follow. The conundrum regarding these frameworks for young children is that proving evidence of a causal link between early environments and later outcomes is very challenging scientifically. So how do governments choose what learning and development practices and goals to make mandatory for childcare providers? And is it realistic to expect early years providers to meet the legal requirements that these frameworks impose? We do not know which learning and development practices impact positively on later outcomes, and we certainly do not know if there is a one-size-fits-all approach for an early years framework that is guaranteed to work.

Differential ischemic stroke risk linked to novel subtypes of type 2 diabetes: insights from a Mendelian randomization analysis

PURPOSE

This study employs a two-sample Mendelian randomization (MR) approach to investigate the variation in ischemic stroke risk across novel subtypes of adult-onset type 2 diabetes.

METHODS

Leveraging pooled genome-wide association study (GWAS) data from the Swedish ANDIS cohort, we explored the association of four newly identified type 2 diabetes subtypes-severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD), mild obesity-related diabetes (MOD), and mild age-related diabetes (MARD)-with ischemic stroke risk. The outcome data for ischemic stroke and its three subtypes (large artery, cardioembolic, and small vessel stroke) were sourced from the MEGASTROKE Consortium. Our analysis applied multiple MR methods, focusing on the inverse-variance weighted (IVW) technique, complemented by thorough sensitivity analyses to examine heterogeneity and potential horizontal pleiotropy.

RESULTS

Our findings reveal a significant causal relationship between the SIDD subtype and small vessel stroke (OR = 1.06, 95% CI: 1.01-1.11, p = 0.025), while no causal associations were observed for SIRD with any stroke subtype. MOD was causally linked to small vessel stroke (OR = 1.07, 95% CI: 1.02-1.12, p = 0.004) and large artery stroke (OR = 1.07, 95% CI: 1.01-1.13, p = 0.015). Similarly, MARD showed a causal relationship with small vessel stroke (OR = 1.09, 95% CI: 1.03-1.16, p = 0.006) and overall ischemic stroke risk (OR = 1.04, 95% CI: 1.01-1.08, p = 0.010).

CONCLUSIONS

Our study highlights distinct causal links between specific type 2 diabetes subtypes and ischemic stroke risks, emphasizing the importance of subtype-specific prevention and treatment strategies.

Eosinophils and risk of ulcerative colitis in European population: Evidence from Mendelian randomization study

BACKGROUND

Observational studies have indicated that peripheral blood eosinophil count is elevated in individuals diagnosed with ulcerative colitis (UC) and correlates with the disease activity of UC. However, this conclusion contradicts with findings from other studies. Therefore, we employed Mendelian randomization (MR) method to assess the genetic link between eosinophil count and UC.

METHOD

This MR study utilized summary data from genome-wide association studies (GWAS) on eosinophil count and UC. The main approach used for conducting MR analysis was the inverse variance weighted (IVW) method. Meta-analysis of the IVW results was performed alongside multiple sensitivity analyses to confirm the robustness of the MR analysis results.

RESULTS

The IVW method unveiled a causal relationship between eosinophil count and UC (OR = 1.18, 95% CI: 1.04-1.33, p = .01) in the discovery cohort. This finding was further corroborated by the replication cohorts (OR = 1.16, 95% CI: 1.04-1.29, p = .01; OR = 1.12, 95% CI: 1.01-1.24, p = .03). The meta-analysis indicated that the overall odds ratio (OR) for all studies was 1.15 (common effect model, 95% CI: 1.08-1.23, p < .01). Sensitivity analysis suggested the absence of heterogeneity and horizontal pleiotropy in all MR analyses.

CONCLUSION

Based on bidirectional two-sample MR analysis, there is an indication that elevated eosinophil count may increase the risk of UC. However, potential confounding factors cannot be ruled out, and further research is necessary to explore how eosinophils contribute to the onset and progression of UC.

LDHB contributes to the regulation of lactate levels and basal insulin secretion in human pancreatic β cells

Using 13C6 glucose labeling coupled to gas chromatography-mass spectrometry and 2D 1H-13C heteronuclear single quantum coherence NMR spectroscopy, we have obtained a comparative high-resolution map of glucose fate underpinning β cell function. In both mouse and human islets, the contribution of glucose to the tricarboxylic acid (TCA) cycle is similar. Pyruvate fueling of the TCA cycle is primarily mediated by the activity of pyruvate dehydrogenase, with lower flux through pyruvate carboxylase. While the conversion of pyruvate to lactate by lactate dehydrogenase (LDH) can be detected in islets of both species, lactate accumulation is 6-fold higher in human islets. Human islets express LDH, with low-moderate LDHA expression and β cell-specific LDHB expression. LDHB inhibition amplifies LDHA-dependent lactate generation in mouse and human β cells and increases basal insulin release. Lastly, cis-instrument Mendelian randomization shows that low LDHB expression levels correlate with elevated fasting insulin in humans. Thus, LDHB limits lactate generation in β cells to maintain appropriate insulin release.

How do stochastic processes and genetic threshold effects explain incomplete penetrance and inform causal disease mechanisms?

Incomplete penetrance is the rule rather than the exception in Mendelian disease. In syndromic monogenic disorders, phenotypic variability can be viewed as the combination of incomplete penetrance for each of multiple independent clinical features. Within genetically identical individuals, such as isogenic model organisms, stochastic variation at molecular and cellular levels is the primary cause of incomplete penetrance according to a genetic threshold model. By defining specific probability distributions of causal biological readouts and genetic liability values, stochasticity and incomplete penetrance provide information about threshold values in biological systems. Ascertainment of threshold values has been achieved by simultaneous scoring of relatively simple phenotypes and quantitation of molecular readouts at the level of single cells. However, this is much more challenging for complex morphological phenotypes using experimental and reductionist approaches alone, where cause and effect are separated temporally and across multiple biological modes and scales. Here I consider how causal inference, which integrates observational data with high confidence causal models, might be used to quantify the relative contribution of different sources of stochastic variation to phenotypic diversity. Collectively, these approaches could inform disease mechanisms, improve predictions of clinical outcomes and prioritize gene therapy targets across modes and scales of gene function. This article is part of a discussion meeting issue 'Causes and consequences of stochastic processes in development and disease'.

Mendelian randomization study supports positive bidirectional causal relationships between genetically predicted insomnia symptom and liability to benign prostatic hyperplasia

BACKGROUND

Sleep quality may be related to benign prostatic hyperplasia (BPH), however causal associations have not been established. This study aimed to evaluate causal relationships between six sleep traits ([i] day time napping, [ii] daytime sleepiness, [iii] insomnia, [iv] long sleep duration, [v] short sleep duration, and [vi] sleep duration per hour) and BPH through a bidirectional Mendelian randomization (MR) study.

METHODS

Genome-wide association summary statistics of sleep traits and BPH were downloaded from public databases. Inverse variance weighting (IVW) was used as the main approach for causal inference. For causal estimates identified by IVW, various sensitivity analyses were performed to assess the reliability of the results: (i) four additional MR methods to complement IVW; (ii) Cochran's Q test to assess heterogeneity; (iii) MR-Egger intercept test and MR-PRESSO global test to assess horizontal pleiotropy; and (iv) leave-one-out method to assess stability.

RESULTS

Forward MR analyses indicated that genetically predicted insomnia symptom significantly increased BPH risk (OR = 1.267, 95% CI: 1.003-1.601, P = 0.048), while reverse MR analyses identified that genetically predicted liability to BPH significantly increased the incidence of insomnia (OR = 1.026, 95% CI: 1.000-1.052, P = 0.048). In a replicate MR analysis based on summary statistics including exclusively male participants, the finding of increased risk of BPH due to genetically predicted insomnia symptom was further validated (OR = 1.488, 95% CI: 1.096-2.022, P = 0.011). No further causal links were identified. In addition, sensitivity tests demonstrated the reliability of the MR results.

CONCLUSION

This study identified that a higher prevalence of genetically predicted insomnia symptoms may significantly increase the risk of BPH, while genetically predicted liability to BPH may in turn increase the incidence of insomnia symptom. Therefore, improving sleep quality and reducing the risk of insomnia could be a crucial approach for the prevention of BPH.

Comparison of instrumental variable methods with continuous exposure and binary outcome: A simulation study

BACKGROUND

Instrumental variable (IV) methods are widely employed to estimate causal effects when concerns regarding unmeasured confounders. Although comparisons among several IV methods for binary outcomes exist, comprehensive evaluations are insufficient. Therefore, in this study, we aimed to conduct a simulation with some settings for a detailed comparison of these methods, focusing on scenarios where IVs are valid and under effect homogeneity with different instrument strengths.

METHODS

We compared six IV methods under 32 simulation scenarios: two-stage least squares (2SLS), two-stage predictor substitutions (2SPS), two-stage residual inclusions (2SRI), limited information maximum likelihood (LIML), inverse-variance weighted methods with a linear outcome model (IVWLI), and inverse-variance weighted methods with a non-linear model (IVWLL). By comparing these methods, we examined three key estimates: the parameter estimates of the exposure variable, the causal risk ratio, and the causal risk differences.

RESULTS

Based on the results, six IV methods could be classified into three groups: 2SLS and IVWLI, 2SRI and 2SPS, and LIML and IVWLL. The first pair showed a clear bias owing to outcome model misspecification. The second pair showed a relatively good performance when strong IVs are available; however, the estimates suffered from a significant bias when only weak IVs are used. The third pair produced relatively conservative results, although they were less affected by weak IV issues.

CONCLUSIONS

The findings indicate that no panacea is available for the bias associated with IV methods. We suggest using multiple IV methods: one for primary analysis and another for sensitivity analysis.

Mendelian randomization: causal inference leveraging genetic data

Mendelian randomization (MR) leverages genetic information to examine the causal relationship between phenotypes allowing for the presence of unmeasured confounders. MR has been widely applied to unresolved questions in epidemiology, making use of summary statistics from genome-wide association studies on an increasing number of human traits. However, an understanding of essential concepts is necessary for the appropriate application and interpretation of MR. This review aims to provide a non-technical overview of MR and demonstrate its relevance to psychiatric research. We begin with the origins of MR and the reasons for its recent expansion, followed by an overview of its statistical methodology. We then describe the limitations of MR, and how these are being addressed by recent methodological advances. We showcase the practical use of MR in psychiatry through three illustrative examples - the connection between cannabis use and psychosis, the link between intelligence and schizophrenia, and the search for modifiable risk factors for depression. The review concludes with a discussion of the prospects of MR, focusing on the integration of multi-omics data and its extension to delineating complex causal networks.

Role of Inflammation in Depressive and Anxiety Disorders, Affect, and Cognition: Genetic and Non-Genetic Findings in the Lifelines Cohort Study

Background

Low-grade systemic inflammation is implicated in the pathogenesis of various neuropsychiatric conditions affecting mood and cognition. While much of the evidence concerns depression, large-scale population studies of anxiety, affect, and cognitive function are scarce. Importantly, causality remains unclear. We used complementary non-genetic, genetic risk score (GRS), and Mendelian randomization (MR) analyses to examine whether inflammatory markers are associated with affect, depressive and anxiety disorders, and cognitive performance in the Lifelines Cohort; and whether associations are likely to be causal.

Methods

Using data from up to 55,098 (59% female) individuals from the Dutch Lifelines cohort, we tested the cross-sectional and longitudinal associations of C-reactive protein (CRP) with (i) depressive and anxiety disorders; (ii) positive and negative affect scores, and (iii) five cognitive measures assessing attention, psychomotor speed, episodic memory, and executive functioning (figural fluency and working memory). Additionally, we examined the association between inflammatory marker GRSs (CRP, interleukin-6 [IL-6], IL-6 receptor [IL-6R and soluble IL-6R (sIL-6R)], glycoprotein acetyls [GlycA]) on these same outcomes (N max =57,946), followed by MR analysis examining evidence of causality of CRP on outcomes (N max =23,268). In genetic analyses, all GRSs and outcomes were z-transformed.

Results

In non-genetic analyses, higher CRP was associated with diagnosis of any depressive disorder, lower positive and higher negative affect scores, and worse performance on tests of figural fluency, attention, and psychomotor speed after adjusting for potential confounders, although the magnitude of these associations was small. In genetic analyses, CRP GRS was associated with any anxiety disorder (β=0.002, p =0.037, N=57,047) whereas GlycA GRS was associated with major depressive disorder (β=0.001, p =0.036; N=57,047). Both CRP GRS (β=0.006, p =0.035, N=57,946) and GlycA GRS (β=0.006, p =0.049; N=57,946) were associated with higher negative affect score. Inflammatory marker GRSs were not associated with cognitive performance, except sIL-6R GRS which was associated with poorer memory performance (β=-0.009, p =0.018, N=36,783). Further examination of the CRP-anxiety association using MR provided some weak evidence of causality (β=0.12; p =0.054).

Conclusions

Genetic and non-genetic analyses provide consistent evidence for an association between CRP and negative affect. Genetic analyses suggest that IL-6 signaling could be relevant for memory, and that the association between CRP and anxiety disorders could be causal. These results suggest that dysregulated immune physiology may impact a broad range of trans-diagnostic affective symptoms. However, given the small effect sizes and multiple tests conducted, future studies are required to investigate whether effects are moderated by sub-groups and whether these findings replicate in other cohorts.

High temperature and humidity in the environment disrupt bile acid metabolism, the gut microbiome, and GLP-1 secretion in mice

High temperature and humidity in the environment are known to be associated with discomfort and disease, yet the underlying mechanisms remain unclear. We observed a decrease in plasma glucagon-like peptide-1 levels in response to high-temperature and humidity conditions. Through 16S rRNA gene sequencing, alterations in the gut microbiota composition were identified following exposure to high temperature and humidity conditions. Notably, changes in the gut microbiota have been implicated in bile acid synthesis. Further analysis revealed a decrease in lithocholic acid levels in high-temperature and humidity conditions. Subsequent in vitro experiments demonstrated that lithocholic acid increases glucagon-like peptide-1 secretion in NCI-H716 cells. Proteomic analysis indicated upregulation of farnesoid X receptor expression in the ileum. In vitro experiments revealed that the combination of lithocholic acid with farnesoid X receptor inhibitors resulted in a significant increase in GLP-1 levels compared to lithocholic acid alone. In this study, we elucidate the mechanism by which reduced lithocholic acid suppresses glucagon-like peptide 1 via farnesoid X receptor activation under high-temperature and humidity condition.

Assessing causal links between age at menarche and adolescent mental health: a Mendelian randomisation study

BACKGROUND

The timing of puberty may have an important impact on adolescent mental health. In particular, earlier age at menarche has been associated with elevated rates of depression in adolescents. Previous research suggests that this relationship may be causal, but replication and an investigation of whether this effect extends to other mental health domains is warranted.

METHODS

In this Registered Report, we triangulated evidence from different causal inference methods using a new wave of data (N = 13,398) from the Norwegian Mother, Father, and Child Cohort Study. We combined multiple regression, one- and two-sample Mendelian randomisation (MR), and negative control analyses (using pre-pubertal symptoms as outcomes) to assess the causal links between age at menarche and different domains of adolescent mental health.

RESULTS

Our results supported the hypothesis that earlier age at menarche is associated with elevated depressive symptoms in early adolescence based on multiple regression (β =  - 0.11, 95% CI [- 0.12, - 0.09], pone-tailed < 0.01). One-sample MR analyses suggested that this relationship may be causal (β =  - 0.07, 95% CI [- 0.13, 0.00], pone-tailed = 0.03), but the effect was small, corresponding to just a 0.06 standard deviation increase in depressive symptoms with each earlier year of menarche. There was also some evidence of a causal relationship with depression diagnoses during adolescence based on one-sample MR (OR = 0.74, 95% CI [0.54, 1.01], pone-tailed = 0.03), corresponding to a 29% increase in the odds of receiving a depression diagnosis with each earlier year of menarche. Negative control and two-sample MR sensitivity analyses were broadly consistent with this pattern of results. Multivariable MR analyses accounting for the genetic overlap between age at menarche and childhood body size provided some evidence of confounding. Meanwhile, we found little consistent evidence of effects on other domains of mental health after accounting for co-occurring depression and other confounding.

CONCLUSIONS

We found evidence that age at menarche affected diagnoses of adolescent depression, but not other domains of mental health. Our findings suggest that earlier age at menarche is linked to problems in specific domains rather than adolescent mental health in general.

Evaluating the causal relationship between educational attainment and mental health

We investigate the causal relationship between educational attainment (EA) and mental health using two research designs. First, we compare the relationship between EA and 18 psychiatric diagnoses within sibship in Dutch national registry data (N=1.7 million), thereby controlling for unmeasured familial factors. Second, we apply two-sample Mendelian Randomization, which uses genetic variants related to EA or psychiatric diagnosis as instrumental variables, to test whether there is a causal relation in either direction. Our results suggest that lower levels of EA causally increase the risk of MDD, ADHD, alcohol dependence, GAD and PTSD diagnoses. We also find evidence of a causal effect of ADHD on EA. For schizophrenia, anorexia nervosa, OCD, and bipolar disorder, results were inconsistent across the different approaches, highlighting the importance of using multiple research designs to understand complex relationships such as between EA and mental health.

Mendelian randomization analysis identifies druggable genes and drugs repurposing for chronic obstructive pulmonary disease

Background

Chronic obstructive pulmonary disease (COPD) is a prevalent condition that significantly impacts public health. Unfortunately, there are few effective treatment options available. Mendelian randomization (MR) has been utilized to repurpose existing drugs and identify new therapeutic targets. The objective of this study is to identify novel therapeutic targets for COPD.

Methods

Cis-expression quantitative trait loci (cis-eQTL) were extracted for 4,317 identified druggable genes from genomics and proteomics data of whole blood (eQTLGen) and lung tissue (GTEx Consortium). Genome-wide association studies (GWAS) data for doctor-diagnosed COPD, spirometry-defined COPD (Forced Expiratory Volume in one second [FEV1]/Forced Vital Capacity [FVC] <0.7), and FEV1 were obtained from the cohort of FinnGen, UK Biobank and SpiroMeta consortium. We employed Summary-data-based Mendelian Randomization (SMR), HEIDI test, and colocalization analysis to assess the causal effects of druggable gene expression on COPD and lung function. The reliability of these druggable genes was confirmed by eQTL two-sample MR and protein quantitative trait loci (pQTL) SMR, respectively. The potential effects of druggable genes were assessed through the phenome-wide association study (PheWAS). Information on drug repurposing for COPD was collected from multiple databases.

Results

A total of 31 potential druggable genes associated with doctor-diagnosed COPD, spirometry-defined COPD, and FEV1 were identified through SMR, HEIDI test, and colocalization analysis. Among them, 22 genes (e.g., MMP15, PSMA4, ERBB3, and LMCD1) were further confirmed by eQTL two-sample MR and protein SMR analyses. Gene-level PheWAS revealed that ERBB3 expression might reduce inflammation, while GP9 and MRC2 were associated with other traits. The drugs Montelukast (targeting the MMP15 gene) and MARIZOMIB (targeting the PSMA4 gene) may reduce the risk of spirometry-defined COPD. Additionally, an existing small molecule inhibitor of the APH1A gene has the potential to increase FEV1.

Conclusions

Our findings identified 22 potential drug targets for COPD and lung function. Prioritizing clinical trials that target these identified druggable genes with existing drugs or novel medications will be beneficial for the development of COPD treatments.

MetaboAnalyst 6.0: towards a unified platform for metabolomics data processing, analysis and interpretation

We introduce MetaboAnalyst version 6.0 as a unified platform for processing, analyzing, and interpreting data from targeted as well as untargeted metabolomics studies using liquid chromatography - mass spectrometry (LC-MS). The two main objectives in developing version 6.0 are to support tandem MS (MS2) data processing and annotation, as well as to support the analysis of data from exposomics studies and related experiments. Key features of MetaboAnalyst 6.0 include: (i) a significantly enhanced Spectra Processing module with support for MS2 data and the asari algorithm; (ii) a MS2 Peak Annotation module based on comprehensive MS2 reference databases with fragment-level annotation; (iii) a new Statistical Analysis module dedicated for handling complex study design with multiple factors or phenotypic descriptors; (iv) a Causal Analysis module for estimating metabolite - phenotype causal relations based on two-sample Mendelian randomization, and (v) a Dose-Response Analysis module for benchmark dose calculations. In addition, we have also improved MetaboAnalyst's visualization functions, updated its compound database and metabolite sets, and significantly expanded its pathway analysis support to around 130 species. MetaboAnalyst 6.0 is freely available at https://www.metaboanalyst.ca.

MRBEE: A bias-corrected multivariable Mendelian randomization method

Mendelian randomization (MR) is an instrumental variable approach used to infer causal relationships between exposures and outcomes, which is becoming increasingly popular because of its ability to handle summary statistics from genome-wide association studies. However, existing MR approaches often suffer the bias from weak instrumental variables, horizontal pleiotropy and sample overlap. We introduce MRBEE (MR using bias-corrected estimating equation), a multivariable MR method capable of simultaneously removing weak instrument and sample overlap bias and identifying horizontal pleiotropy. Our extensive simulations and real data analyses reveal that MRBEE provides nearly unbiased estimates of causal effects, well-controlled type I error rates and higher power than comparably robust methods and is computationally efficient. Our real data analyses result in consistent causal effect estimates and offer valuable guidance for conducting multivariable MR studies, elucidating the roles of pleiotropy, and identifying total 42 horizontal pleiotropic loci missed previously that are associated with myopia, schizophrenia, and coronary artery disease.

Insights into the Inherited Basis of Valvular Heart Disease

PURPOSE OF REVIEW: Increases in the availability of genetic data and advances in the tools and methods for their analyses have enabled well-powered genetic association studies that have significantly enhanced our understanding of the genetic factors underlying both rare and common valve diseases. Valvular heart diseases, such as congenital valve malformations and degenerative valve lesions, increase the risk of heart failure, arrhythmias, and sudden death. In this review, we provide an updated overview of our current understanding of the genetic mechanisms underlying valvular heart diseases. With a focus on discoveries from the past 5 years, we describe recent insights into genetic risk and underlying biological pathways. RECENT FINDINGS: Recently acquired knowledge around valvular heart disease genetics has provided important insights into novel mechanisms related to disease pathogenesis. Newly identified risk loci associated valvular heart disease mainly regulate the composition of the extracellular matrix, accelerate the endothelial-to-mesenchymal transition, contribute to cilia formation processes, and play roles in lipid metabolism. Large-scale genomic analyses have identified numerous risk loci, genes, and biological pathways associated with degenerative valve disease and congenital valve malformations. Shared risk genes suggest common mechanistic pathways for various valve pathologies. More recent studies have combined cardiac magnetic resonance imaging and machine learning to offer a novel approach for exploring genotype-phenotype relationships regarding valve disease. Progress in the field holds promise for targeted prevention, particularly through the application of polygenic risk scores, and innovative therapies based on the biological mechanisms for predominant forms of valvular heart diseases.

A phenome-wide association and Mendelian randomisation study of alcohol use variants in a diverse cohort comprising over 3 million individuals

BACKGROUND

Alcohol consumption is associated with numerous negative social and health outcomes. These associations may be direct consequences of drinking, or they may reflect common genetic factors that influence both alcohol consumption and other outcomes.

METHODS

We performed exploratory phenome-wide association studies (PheWAS) of three of the best studied protective single nucleotide polymorphisms (SNPs) in genes encoding ethanol metabolising enzymes (ADH1B: rs1229984-T, rs2066702-A; ADH1C: rs698-T) using up to 1109 health outcomes across 28 phenotypic categories (e.g., substance-use, mental health, sleep, immune, cardiovascular, metabolic) from a diverse 23andMe cohort, including European (N ≤ 2,619,939), Latin American (N ≤ 446,646) and African American (N ≤ 146,776) populations to uncover new and perhaps unexpected associations. These SNPs have been consistently implicated by both candidate gene studies and genome-wide association studies of alcohol-related behaviours but have not been investigated in detail for other relevant phenotypes in a hypothesis-free approach in such a large cohort of multiple ancestries. To provide insight into potential causal effects of alcohol consumption on the outcomes significant in the PheWAS, we performed univariable two-sample and one-sample Mendelian randomisation (MR) analyses.

FINDINGS

The minor allele rs1229984-T, which is protective against alcohol behaviours, showed the highest number of PheWAS associations across the three cohorts (N = 232, European; N = 29, Latin American; N = 7, African American). rs1229984-T influenced multiple domains of health. We replicated associations with alcohol-related behaviours, mental and sleep conditions, and cardio-metabolic health. We also found associations with understudied traits related to neurological (migraines, epilepsy), immune (allergies), musculoskeletal (fibromyalgia), and reproductive health (preeclampsia). MR analyses identified evidence of causal effects of alcohol consumption on liability for 35 of these outcomes in the European cohort.

INTERPRETATION

Our work demonstrates that polymorphisms in genes encoding alcohol metabolising enzymes affect multiple domains of health beyond alcohol-related behaviours. Understanding the underlying mechanisms of these effects could have implications for treatments and preventative medicine.

FUNDING

MVJ, NCK, SBB, SSR and AAP were supported by T32IR5226 and 28IR-0070. SSR was also supported by NIDA DP1DA054394. NCK and RBC were also supported by R25MH081482. ASH was supported by funds from NIAAA K01AA030083. JLMO was supported by VA 1IK2CX002095. JLMO and JJMM were also supported by NIDA R21DA050160. JJMM was also supported by the Kavli Postdoctoral Award for Academic Diversity. EGA was supported by K01MH121659 from the NIMH/NIH, the Caroline Wiess Law Fund for Research in Molecular Medicine and the ARCO Foundation Young Teacher-Investigator Fund at Baylor College of Medicine. MSA was supported by the Instituto de Salud Carlos III and co-funded by the European Union Found: Fondo Social Europeo Plus (FSE+) (P19/01224, PI22/00464 and CP22/00128).

Pleiotropy, epistasis and the genetic architecture of quantitative traits

Pleiotropy (whereby one genetic polymorphism affects multiple traits) and epistasis (whereby non-linear interactions between genetic polymorphisms affect the same trait) are fundamental aspects of the genetic architecture of quantitative traits. Recent advances in the ability to characterize the effects of polymorphic variants on molecular and organismal phenotypes in human and model organism populations have revealed the prevalence of pleiotropy and unexpected shared molecular genetic bases among quantitative traits, including diseases. By contrast, epistasis is common between polymorphic loci associated with quantitative traits in model organisms, such that alleles at one locus have different effects in different genetic backgrounds, but is rarely observed for human quantitative traits and common diseases. Here, we review the concepts and recent inferences about pleiotropy and epistasis, and discuss factors that contribute to similarities and differences between the genetic architecture of quantitative traits in model organisms and humans.

Metabolic syndrome, its components, and gastrointestinal cancer risk: a meta-analysis of 31 prospective cohorts and Mendelian randomization study

BACKGROUND AND AIM

Cohort studies have linked metabolic syndrome (MetS) to gastrointestinal (GI) cancer risk. We aimed to evaluate the associations between MetS, its components, and combinations of MetS components with eight GI cancers risk.

METHODS

We conducted a systematic search of prospective cohort studies and performed a meta-analysis. Subgroup analyses regarding diagnostic criteria, sex, cancer sites, histological subtypes, ethnic groups, and studies adjusted for alcohol consumption were carried out. Mendelian randomization (MR) was employed to evaluate the causality between 17 MetS-related traits and eight GI cancers among Europeans and Asians separately.

RESULTS

Meta-analyses of 31 prospective studies indicated that MetS was significantly associated with an increased risk of colorectal cancer (CRC) (RR [95% CI] = 1.13 [1.12-1.15]), esophageal cancer (EC) (RR [95% CI] = 1.17 [1.03-1.32]), gallbladder cancer (GBC) (RR [95% CI] = 1.37[1.10-1.71]), liver cancer (LC) (RR [95% CI] = 1.46 [1.29-1.64]), and pancreatic cancer (PaC) (RR [95% CI] = 1.25 [1.20-1.30]), but not gastric cancer (GC) (RR [95% CI] = 1.11 [0.96-1.28]). Regarding the associations between MetS components and GI cancers risk, the following associations showed statistical significance: obesity-CRC/LC/EC/, hypertriglyceridemia-LC/PaC, reduced high-density lipoprotein (HDL)-CRC/LC/GC/PaC, hyperglycemia-CRC/LC/PaC, and hypertension-CRC/LC/EC/PaC. Sex-specific associations were observed between individual MetS components on GI cancers risk. Among the top three common combinations in both sexes, obesity + HTN + hyperglycemia had the strongest association with CRC risk (RR [95% CI] = 1.54 [1.49-1.61] for males and 1.27 [1.21-1.33] for females). MR analyses revealed causality in 16 exposure-outcome pairs: waist-to-hip ratio/BMI/HbA1c-CRC; BMI/childhood obesity/waist circumference/T2DM/glucose-EC; BMI/waist circumference/cholesterol-LC; cholesterol/childhood obesity/waist circumference/HbA1c-PaC; and HbA1c-GBC. These results were robust against sensitivity analyses.

CONCLUSIONS

Since MetS is reversible, lifestyle changes or medical interventions targeting MetS patients might be potential prevention strategies for GI cancers.

ASSESSING THE CAUSAL RELATIONSHIP BETWEEN SEPSIS AND AUTOIMMUNE: A MENDELIAN RANDOMIZATION STUDY

ABSTRACT

Objective : Numerous epidemiological studies have identified a potential link between sepsis and a variety of autoimmune disorders. The primary objective of this study is to delve deeper into this connection, investigating the potential causal relationship between sepsis and autoimmune disorders through the application of Mendelian randomization (MR). Methods : To assess the potential genetic impact on sepsis risk relating to susceptibility toward immune-related outcomes, we used summary data from the largest European genome-wide association studies (GWAS) on these conditions using a two-sample MR framework. Single nucleotide polymorphisms-which had strong associations with the nine traits-were extracted from the GWAS and examined their effects in an extensive European sepsis GWAS (486,484 cases and 474,841 controls). We used inverse-variance weighted MR, weighted median, and MR Egger for analyses, supplementing these with sensitivity analyses and assessing level pleiotropy using MR methodologies. We also executed a reverse MR analysis to test sepsis' causal effects on the designated autoimmune traits. Results : With primary sclerosing cholangitis being the exception, our MR analysis suggests that susceptibility toward most autoimmune diseases does not affect sepsis risks. The reverse MR analysis did not validate any influence of sepsis susceptibility over other autoimmune diseases. Our primary inverse-variance weighted MR analysis outcomes found general confirmation through our sensitivity MR examinations. Variance in the exposures, as dictated by the single nucleotide polymorphism sets used as MR instruments, ranged between 4.88 × 10 -5 to 0.005. Conclusion : Our MR research, centered on a European population, does not validate a correlation between susceptibility to the majority of autoimmune disorders and sepsis risk. Associations discerned in epidemiological studies may owe partly to shared biological or environmental confounders. The risk susceptibility for primary sclerosing cholangitis does relate to sepsis risk, opening doors for personalized precision treatments in the future.

Causal effect of interleukin (IL)-6 on blood pressure and hypertension: A mendelian randomization study

To examine whether circulating interleukin-6 (IL-6) levels (CirIL6) have a causal effect on blood pressure using Mendelian randomization (MR) methods. We used data from genome-wide association studies (GWAS) of European ancestry to obtain genetic instruments for circulating IL-6 levels and blood pressure measurements. We applied several robust MR methods to estimate the causal effects and to test for heterogeneity and pleiotropy. We found that circulating IL-6 had a significant positive causal effect on systolic blood pressure (SBP) and pulmonary arterial hypertension (PAH), but not on diastolic blood pressure (DBP) or hypertension. We found that as CirIL6 genetically increased, SBP increased using Inverse Variance Weighted (IVW) method (for ukb-b-20175, β = 0.082 with SE = 0.032, P = 0.011; for ukb-a-360, β = 0.075 with SE = 0.031, P = 0.014) and weighted median (WM) method (for ukb-b-20175, β = 0.061 with SE = 0.022, P = 0.006; for ukb-a-360, β = 0.065 with SE = 0.027, P = 0.014). Moreover, CirIL6 may be associated with an increased risk of PAH using WM method (odds ratio (OR) = 15.503, 95% CI, 1.025-234.525, P = 0.048), but not with IVW method. Our study provides novel evidence that circulating IL-6 has a causal role in the development of SBP and PAH, but not DBP or hypertension. These findings suggest that IL-6 may be a potential therapeutic target for preventing or treating cardiovascular diseases and metabolic disorders. However, more studies are needed to confirm the causal effects of IL-6 on blood pressure and to elucidate the underlying mechanisms and pathways.

The Relationship Between Systemic Lupus Erythematosus and Osteoporosis Based on Different Ethnic Groups: a Two-Sample Mendelian Randomization Analysis

The previous observational studies could not overcome the effects of confounding variables and reverse causality. We aimed to determine whether there is a causal relationship between systemic lupus erythematosus and osteoporosis in East Asian and European populations, respectively, by two-sample Mendelian Randomization analysis. We obtained and downloaded data from publicly available genome-wide association study databases and analyses for East Asian and European populations, including systemic lupus erythematosus (SLE), osteoporosis (OP), multisite bone mineral density (BMD), and OP with fracture. After screening for instrumental single-nucleotide polymorphisms (SNPs) significantly correlated to SLE, the inverse-variance weighted (IVW) method was used for calculating the ratio and 95% confidence interval, besides utilizing MR-Egger, weighted median, and weighted mode to assess the robustness of the primary outcome. Moreover, multiple analyses, including MR-PRESSO, MR-Egger intercept, Cochran's Q test, as well as "leave-one-out" sensitivity, were used for evaluating horizontal pleiotropy, heterogeneity, and stability. Finally, we exchanged exposure and outcome and performed a reverse MR analysis. IVW (OR = 1.05, 95% CI = 1.01-1.09, P = 0.009) indicated a significant positive correlation between genetically predicted SLE and OP in East Asians. Furthermore, neither heterogeneity nor horizontal pleiotropy was observed. In Europe, there was no significant genetically predicted causal relation between SLE and OP. Bi-directional MR analysis showed no reverse causality between SLE and OP. In the East Asian population, genetically predicted SLE may have had a positive causal relationship with OP. In Europe, there is insufficient evidence for a potential causal relation between SLE and OP or BMD and fracture, and the correlations currently observed may be attributed to a variety of confounder variables.

Causal effects of blood pressure and the risk of frailty: a bi-directional two-sample Mendelian randomization study

Observational studies have indicated that high blood pressure (BP) may be a risk factor to frailty. However, the causal association between BP and frailty remains not well determined. The purpose of this bi-directional two-sample Mendelian randomization (MR) study was to investigate the causal relationship between BP and frailty. Independent single nucleotide polymorphisms (SNPs) strongly (P < 5E-08) associated with systolic BP (SBP), diastolic BP (DBP), and pulse pressure (PP) were selected as instrumental variables. Two different published genome-wide association studies (GWAS) on BP from the CHARGE (n = 810,865) and ICBP (n = 757,601) consortia were included. Summary-level data on frailty index (FI) were obtained from the latest GWAS based on UK Biobank and Swedish TwinGene cohorts (n = 175,226). Inverse variance weighted (IVW) approach with other sensitivity analyses were used to calculate the causal estimate. Using the CHARGE dataset, genetic predisposition to increased SBP (β = 0.135, 95% CI = 0.093 to 0.176, P = 1.73E-10), DBP (β = 0.145, 95% CI = 0.104 to 0.186, P = 3.14E-12), and PP (β = 0.114, 95% CI = 0.070 to 0.157, p = 2.87E-07) contributed to a higher FI, which was validated in the ICBP dataset. There was no significant causal effect of FI on SBP, DBP, and PP. Similar results were obtained from different MR methods, indicating good stability. There was potential heterogeneity detected by Cochran's Q test, but no horizontal pleiotropy was observed in MR-Egger intercept test (P > 0.05). These findings evinced that higher BP and PP were causally associated with an increased risk of frailty, suggesting that controlling hypertension could reduce the risk of frailty.

Exploiting integrative metabolomics to study host-parasite interactions in Plasmodium infections

Despite years of research, malaria remains a significant global health burden, with poor diagnostic tests and increasing antimalarial drug resistance challenging diagnosis and treatment. While 'single-omics'-based approaches have been instrumental in gaining insight into the biology and pathogenicity of the Plasmodium parasite and its interaction with the human host, a more comprehensive understanding of malaria pathogenesis can be achieved through 'multi-omics' approaches. Integrative methods, which combine metabolomics, lipidomics, transcriptomics, and genomics datasets, offer a holistic systems biology approach to studying malaria. This review highlights recent advances, future directions, and challenges involved in using integrative metabolomics approaches to interrogate the interactions between Plasmodium and the human host, paving the way towards targeted antimalaria therapeutics and control intervention methods.

The Role of Endothelial Cells in Atherosclerosis: Insights from Genetic Association Studies

Endothelial cells (ECs) mediate several biological functions that are relevant to atherosclerosis and coronary artery disease (CAD), regulating an array of vital processes including vascular tone, wound healing, reactive oxygen species, shear stress response, and inflammation. Although which of these functions is linked causally with CAD development and/or progression is not yet known, genome-wide association studies have implicated more than 400 loci associated with CAD risk, among which several have shown EC-relevant functions. Given the arduous process of mechanistically interrogating single loci to CAD, high-throughput variant characterization methods, including pooled Clustered Regularly Interspaced Short Palindromic Repeats screens, offer exciting potential to rapidly accelerate the discovery of bona fide EC-relevant genetic loci. These discoveries in turn will broaden the therapeutic avenues for CAD beyond lipid lowering and behavioral risk modification to include EC-centric modalities of risk prevention and treatment.

Sedentary behavior and lifespan brain health

Higher levels of physical activity are known to benefit aspects of brain health across the lifespan. However, the role of sedentary behavior (SB) is less well understood. In this review we summarize and discuss evidence on the role of SB on brain health (including cognitive performance, structural or functional brain measures, and dementia risk) for different age groups, critically compare assessment approaches to capture SB, and offer insights into emerging opportunities to assess SB via digital technologies. Across the lifespan, specific characteristics of SB (particularly whether they are cognitively active or cognitively passive) potentially act as moderators influencing the associations between SB and specific brain health outcomes. We outline challenges and opportunities for future research aiming to provide more robust empirical evidence on these observations.

Meta-analysis: Risk of pancreatic cancer in patients with inflammatory bowel disease

BACKGROUND

Studies exploring the association between inflammatory bowel disease (IBD) and pancreatic cancer have reported inconsistent results.

AIMS

To provide a comprehensive overview of the risk of pancreatic cancer development in patients with IBD.

METHODS

We searched Embase, PubMed, Scopus and ProQuest from inception to 31 October 2023. We included population-based cohort studies examining the risk of incident pancreatic cancer in adult patients with IBD compared to the non-IBD population. We also retrieved Mendelian randomisation (MR) studies investigating the relationship of IBD with pancreatic cancer risk. We conducted random-effects meta-analyses and provided pooled relative risks (RRs) with 95% confidence intervals (CIs).

RESULTS

We included 13 studies. Among 11 cohort studies, the risk of developing pancreatic cancer increased by 79% in patients with IBD (RR = 1.79 [95% CI: 1.16-2.75]; I2 = 95.7%). Patients either with Crohn's disease (RR = 1.42 [95% CI: 1.24-1.63]) or ulcerative colitis (RR = 1.50 [95% CI: 1.17-1.92]) had increased risk (p for interaction = 0.72). The annual incidence of pancreatic cancer potentially attributable to IBD increased by 55 cases (95% CI: 17-103) per million. Two MR studies demonstrated that genetic liability to IBD was associated with an increased risk of pancreatic cancer.

CONCLUSIONS

Our results suggest a moderate increase in the risk of pancreatic cancer in patients with IBD, which may be further heightened by genetic predisposition to IBD. The increased risk of pancreatic cancer is probably similar in Crohn's disease and ulcerative colitis.

Causal role of immune cells in chronic obstructive pulmonary disease: Mendelian randomization study

OBJECTIVES

Innate and adaptive immunity play different roles in the pathogenesis of chronic obstructive pulmonary disease (COPD). However, previous studies on the relationship between immune cells and COPD reported inconsistent results.

METHODS

The causal connection between 731 immune cells and COPD was established using a two-sample Mendelian randomization (MR) analysis through publicly accessible genetic data. The heterogeneity and horizontal pleiotropism of the findings were confirmed using sensitivity analysis.

RESULTS

In the B-cell panel, B-cell activating factor receptor (BAFF-R) on CD20- and CD20 on IgD-CD38bright (OR (95% CI): 0.93 (0.88, 0.99) and 0.97 (0.95, 0.98), respectively) were discovered to be protective. In the cDC panel, CD62L- plasmacytoid DC AC, CD80 on monocytes and CD11c on myeloid DCs (OR (95% CI): 0.94 (0.92, 0.97), 0.97 (0.94, 0.99) and (0.97 (0.95, 0.98), respectively) exerted protective effects. However, unswitched memory AC (OR (95%CI): 1.08 (1.01,1.15)) and CD 19 on IgD- CD 27- (OR (95%CI): 1.06 (1.02,1.10)) were hazardous in the B-cell panel. However, among the 731 immune cell phenotypes, no causal relationship was found for COPD on immune cells.

CONCLUSION

This study found a potential causal relationship between immune cells in COPD, ruling out reverse causation. This study provides new avenues for studying the mechanisms of COPD.

Evidence for Genetic Causal Relationships Between Multiple Immune-Mediated Inflammatory Diseases and Age-Related Macular Degeneration: A Univariable and Multivariable Mendelian Randomization Study

INTRODUCTION

With the global aging population on the rise, age-related macular degeneration (AMD) poses a growing healthcare burden. Prior research hints at immune-mediated inflammatory diseases (IMIDs) potentially elevating AMD risk via diverse mechanisms. However, causality remains disputed as a result of confounding factors. Hence, our Mendelian randomization (MR) study aims to untangle this link, mitigating confounding effects to explore the IMID-AMD causal relationship. This study aims to investigate the causal relationship between IMIDs and AMD, providing new strategies for the prevention and treatment of AMD in clinical practice.

METHODS

This study was registered with PROSPERO, CRD42023469815. We obtained data on IMIDs and AMD from Genome-Wide Association Studies (GWAS) summary statistics and the FinnGen consortium. Rigorous selection steps were applied to screen for eligible instrumental single nucleotide polymorphisms (SNPs). We conducted univariate Mendelian randomization, inverse variance-weighted (IVW), weighted median, Mendelian randomization-Egger (MR-Egger), and multivariate Mendelian randomization (MVMR) analyses. Various sensitivity analysis methods were employed to assess pleiotropy and heterogeneity. The aim was to explore the causal relationships between IMIDs and AMD.

RESULTS

The MR analysis revealed that Crohn's disease (CD) (IVW: odd ratios (OR) 1.05, 95% CI (confidence interval) 1.01-1.10, p = 0.007), rheumatoid arthritis (RA) (IVW: OR 1.09, 95% CI 1.04-1.15, p = 0.0001), and type 1 diabetes (T1D) (IVW: OR 1.05, 95% CI 1.02-1.09, p = 0.001) were correlated with an elevated risk of AMD, while multiple sclerosis (MS) (IVW: OR 2.78E-18, 95% CI 2.23E-31 to 3.48E-05, p = 0.008) appeared to be protective against AMD. These findings were supported by an array of MR analysis methodologies and the MVMR approach.

CONCLUSION

Our study results, based on MR, provide genetic evidence indicating a causal relationship between specific IMIDs and AMD. CD, RA, and T1D are factors increasing the risk of AMD, while MS may have a protective effect.

Gastroesophageal reflux disease with 6 neurodegenerative and psychiatric disorders: Genetic correlations, causality, and potential molecular mechanisms

The comorbidities between gastroesophageal reflux disease (GERD) and various neurodegenerative and psychiatric disorders have been widely reported. However, the genetic correlations, causal relationships, and underlying mechanisms linking GERD to these disorders remain largely unknown. Here, we conducted a bidirectional Mendelian randomization (MR) analysis to determine the causality between GERD and 6 neurodegenerative and psychiatric disorders. Sensitivity analyses and multivariable MR were performed to test the robustness of our findings. Linkage disequilibrium score regression was used to assess the genetic correlation between these diseases as affected by heredity. Multiple bioinformatics tools combining two machine learning algorithms were applied to further investigate the potential mechanisms underlying these diseases. We found that genetically predicted GERD significantly increased the risk of Alzheimer's disease, major depressive disorder, and anxiety disorders. There might be a bidirectional relationship between GERD and insomnia. GERD has varying degrees of genetic correlations with AD, ALS, anxiety disorders, insomnia, and depressive disorder. Bioinformatics analyses revealed the hub shared genes and the common pathways between GERD and 6 neurodegenerative and psychiatric disorders. Our findings demonstrated the complex nature of the genetic architecture across these diseases and clarified their causality, highlighting that treatments for the cure or remission of GERD may serve as potential strategies for preventing and managing neurodegenerative and psychiatric disorders.

Effects of loneliness and isolation on cardiovascular diseases: a two sample Mendelian Randomization Study

BACKGROUND

Loneliness and isolation are associated with multiple cardiovascular diseases (CVDs), but there is a lack of research on whether they were causally linked. We conducted a Mendelian Randomization (MR) study to explore causal relationships between loneliness and isolation and multiple CVDs.

METHODS

Single nucleotide polymorphisms associated with loneliness and isolation were identified from a genome-wide association study (GWAS) of 455,364 individuals of European ancestry in the IEU GWAS database. Summary data for 15 CVDs were also obtained from the IEU GWAS database. We used three MR methods including inverse variance weighting, MR-Egger, and weighted median estimation to assess the causal effect of exposure on outcomes. Cochran's Q test and MR-Egger intercept test were used to evaluate the heterogeneity and pleiotropy.

RESULTS

MR analysis showed that loneliness and isolation were significantly associated with essential hypertension (OR = 1.07, 95% CI: 1.03-1.12), atherosclerotic heart disease (OR = 1.04; 95% CI: 1.02-1.06), myocardial infarction (OR = 1.02; 95% CI: 1-1.04) and angina (OR = 1.04; 95% CI =1.02-1.06). No heterogeneity and pleiotropy effects were found in this study.

CONCLUSIONS

Causal relationship of loneliness and isolation with CVDs were found in this study.

Unraveling the immunological landscape in acute pancreatitis progression to sepsis: insights from a Mendelian randomization study on immune cell traits

Background

Acute pancreatitis (AP) is a severe digestive system disorder with a significant risk of progressing to sepsis, a major cause of mortality. Unraveling the immunological pathways in AP is essential for developing effective treatments, particularly understanding the role of specific immune cell traits in this progression.

Methods

Employing a bidirectional two-sample Mendelian Randomization (MR) approach, this study first examined the causal relationship between AP and 731 immune cell traits to identify those significantly associated with AP. Subsequently, we explored the causal associations between 731 immune cell traits and sepsis. The analysis utilized extensive genome-wide association studies (GWAS) summary datasets, with a focus on identifying common immune cell traits with statistically significant causal associations between AP and sepsis.

Results

Our investigation identified 44 immune cell traits unidirectionally associated with AP and 36 traits unidirectionally associated with sepsis. Among these, CD127 on CD28+ CD45RA- CD8+ T cells emerged as a common mediator, accounting for 5.296% of the increased risk of sepsis in AP patients. This finding highlights the significant role of specific memory CD8+ T cells in the pathophysiology of AP and its progression to sepsis.

Conclusion

This study elucidates the critical role of specific immune cell traits, particularly CD127hi memory CD8+ T cells, in the progression of AP to sepsis. Our findings provide a foundation for future research into targeted immune-modulatory therapies, potentially improving patient outcomes in AP-related sepsis and offering new insights into the complex immunological dynamics of this condition.

Genetic insight into putative causes of xanthelasma palpebrarum: a Mendelian randomization study

Xanthelasma palpebrarum (XP) is the most common form of cutaneous xanthoma, with a prevalence of 1.1%~4.4% in the population. However, the cause of XP remains largely unknown. In the present study, we used Mendelian randomization to assess the genetic association between plasma lipids, metabolic traits, and circulating protein with XP, leveraging summary statistics from large genome-wide association studies (GWAS). Genetically predicted plasma cholesterol and LDL-C, but not HDL-C or triglyceride, were significantly associated with XP. Metabolic traits, including BMI, fasting glucose, type 2 diabetes, systolic and diastolic blood pressure, were not significantly associated with XP. Furthermore, we found genetically predicted 12 circulating proteins were associated with XP, including FN1, NTM, FCN2, GOLM1, ICAM5, PDE5A, C5, CLEC11A, CXCL1, CCL2, CCL11, CCL13. In conclusion, this study identified plasma cholesterol, LDL-C, and 12 circulating proteins to be putative causal factors for XP, highlighting the role of plasma cholesterol and inflammatory response in XP development.

A genetic exploration of the relationship between Posttraumatic Stress Disorder and cardiovascular diseases

Background and Aims

Experiencing a traumatic event may lead to Posttraumatic Stress Disorder (PTSD), including symptoms such as flashbacks and hyperarousal. Individuals suffering from PTSD are at increased risk of cardiovascular disease (CVD), but it is unclear why. This study assesses shared genetic liability and potential causal pathways between PTSD and CVD.

Methods

We leveraged summary-level data of genome-wide association studies (PTSD: N= 1,222,882; atrial fibrillation (AF): N=482,409; coronary artery disease (CAD): N=1,165,690; hypertension: N=458,554; heart failure (HF): N=977,323). First, we estimated genetic correlations and utilized genomic structural equation modeling to identify a common genetic factor for PTSD and CVD. Next, we assessed biological, behavioural, and psychosocial factors as potential mediators. Finally, we employed multivariable Mendelian randomization to examine causal pathways between PTSD and CVD, incorporating the same potential mediators.

Results

Significant genetic correlations were found between PTSD and CAD, HT, and HF (rg =0.21-0.32, p≤ 3.08 · 10-16), but not between PTSD and AF. Insomnia, smoking, alcohol dependence, waist-to-hip ratio, and inflammation (IL6, C-reactive protein) partly mediated these associations. Mendelian randomization indicated that PTSD causally increases CAD (IVW OR=1.53, 95% CIs=1.19-1.96, p=0.001), HF (OR=1.44, CIs=1.08-1.92, p=0.012), and to a lesser degree hypertension (OR=1.25, CIs=1.05-1.49, p=0.012). While insomnia, smoking, alcohol, and inflammation were important mediators, independent causal effects also remained.

Conclusions

In addition to shared genetic liability between PTSD and CVD, we present strong evidence for causal effects of PTSD on CVD. Crucially, we implicate specific lifestyle and biological mediators (insomnia, substance use, inflammation) which has important implications for interventions to prevent CVD in PTSD patients.

Association between non-scarring alopecia and hypothyroidism: a bidirectional two-sample Mendelian randomization study

Background

Non-scarring alopecia is typically represented by two main types: alopecia areata (AA) and androgenetic alopecia (AGA). While previous observational studies have indicated a link between non-scarring alopecia and hypothyroidism, the precise causal relationship remains uncertain. To determine the potential links between non-scarring alopecia and hypothyroidism, we conducted a bidirectional two-sample Mendelian randomization (MR) analysis.

Methods

We used independent genetic instruments from the FinnGen consortium for AA (682 cases, 361,140 controls) and AGA (195 cases, 201,019 controls) to investigate the association with hypothyroidism in the UK Biobank study (22,687 cases, 440,246 controls). The primary analysis was performed using the inverse variance-weighted method. Complementary approaches were employed to evaluate the pleiotropy and heterogeneity.

Results

Genetically predicted AA exhibited a positive causal effect on hypothyroidism (odds ratio [OR], 1.0017; 95% confidence interval [CI], 1.0004-1.0029; P = 0.0101). Additionally, hypothyroidism was found to be strongly correlated with an increase in the risk of AA (OR, 45.6839; 95% CI, 1.8446-1131.4271, P = 0.0196). However, no causal relationship was demonstrated between AGA and hypothyroidism. A sensitivity analysis validated the integrity of these causal relationships.

Conclusion

This MR study supports a bidirectional causal link between AA and hypothyroidism. Nevertheless, additional research is needed to gain a more thorough comprehension of the causal relationship between non-scarring alopecia and hypothyroidism.

Lipid levels and risk of acute pancreatitis using bidirectional Mendelian randomization

Previous studies found lipid levels, especially triglycerides (TG), are associated with acute pancreatitis, but their causalities and bi-directions were not fully examined. We determined whether abnormal levels of TG, high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) are precursors and/or consequences of acute pancreatitis using bidirectional two-sample Mendelian randomization (MR) with two non-overlapping genome-wide association study (GWAS) summary statistics for lipid levels and acute pancreatitis. We found phenotypic associations that both higher TG levels and lower HDL-C levels contributed to increased risk of acute pancreatitis. Our GWAS meta-analysis of acute pancreatitis identified seven independent signals. Genetically predicted TG was positively associated with acute pancreatitis when using the variants specifically associated with TG using univariable MR [Odds ratio (OR), 95% CI 2.02, 1.22-3.31], but the reversed direction from acute pancreatitis to TG was not observed (mean difference = 0.003, SE = 0.002, P-value = 0.138). However, a bidirectional relationship of HDL-C and acute pancreatitis was observed: A 1-SD increment of genetically predicted HDL-C was associated with lower risk of acute pancreatitis (OR, 95% CI 0.84, 0.76-0.92) and genetically predisposed individuals with acute pancreatitis have, on average, 0.005 SD lower HDL-C (mean difference = - 0.005, SE = 0.002, P-value = 0.004). Our MR analysis confirms the evidence of TG as a risk factor of acute pancreatitis but not a consequence. A potential bidirectional relationship of HDL-C and acute pancreatitis occurs and raises the prospect of HDL-C modulation in the acute pancreatitis prevention and treatment.

Premorbid brain structure influences risk of amyotrophic lateral sclerosis

BACKGROUND

Amyotrophic lateral sclerosis (ALS) is a disease of the motor network associated with brain structure and functional connectivity alterations that are implicated in disease progression. Whether such changes have a causal role in ALS, fitting with a postulated influence of premorbid cerebral architecture on the phenotypes associated with neurodegenerative disorders is not known.

METHODS

This study considered causal effects and shared genetic risk of 2240 structural and functional MRI brain scan imaging-derived phenotypes (IDPs) on ALS using two sample Mendelian randomisation, with putative associations further examined with extensive sensitivity analysis. Shared genetic predisposition between IDPs and ALS was explored using genetic correlation analysis.

RESULTS

Increased white matter volume in the cerebral hemispheres was causally associated with ALS. Weaker causal associations were observed for brain stem grey matter volume, parieto-occipital white matter surface and volume of the left thalamic ventral anterior nucleus. Genetic correlation was observed between ALS and intracellular volume fraction and isotropic free water volume fraction within the posterior limb of the internal capsule.

CONCLUSIONS

This study provides evidence that premorbid brain structure, in particular white matter volume, contributes to the risk of ALS.

Deciphering the effect of phytosterols on Alzheimer's disease and Parkinson's disease: the mediating role of lipid profiles

BACKGROUND

Studies have suggested that blood circulating phytosterols, plant-derived sterols analogous to cholesterol, were associated with blood lipid levels and the risk of Alzheimer's disease (AD) and Parkinson's disease (PD). This Mendelian randomization (MR) study is performed to determine the causal effect of circulating phytosterols on AD and PD and evaluate the mediation effect of blood lipids.

METHODS

Leveraging genome-wide association studies summary-level data for phytosterols, blood lipids, AD, and PD, univariable and multivariable MR (MVMR) analyses were conducted. Four types of phytosterols (brassicasterol, campesterol, sitosterol, and stigmasterol), three blood lipids parameters (high-density lipoprotein cholesterol [HDL-C], non-HDL-C, and triglyceride), two datasets for AD and PD were used. Inverse-variance weighted method was applied as the primary analysis, and false discovery rate method was used for adjustment of multiple comparisons.

RESULTS

Using the largest AD dataset, genetically proxied higher levels of stigmasterol (OR = 0.593, 95%CI = 0.431-0.817, P = 0.004) and sitosterol (OR = 0.864, 95%CI = 0.791-0.943, P = 0.004) significantly correlated with a lower risk of AD. No significant associations were observed between all four types of phytosterols levels and PD. MVMR estimates showed that the above causal associations were missing after integrating the blood lipids as exposures. Sensitivity analyses confirmed the robustness of these associations, with no evidence of pleiotropy and heterogeneity.

CONCLUSION

The study supports a potential beneficial role of blood stigmasterol and sitosterol in reducing the risk of AD, but not PD, which is dependent on modulating blood lipids. These insights highlight circulating stigmasterol and sitosterol as possible biomarkers and therapeutic targets for AD.

Genetic correlations and causal relationships between cardio-metabolic traits and sepsis

Cardio-metabolic traits have been reported to be associated with the development of sepsis. It is, however, unclear whether these co-morbidities reflect causal associations, shared genetic heritability, or are confounded by environmental factors. We performed three analyses to explore the relationships between cardio-metabolic traits and sepsis. Mendelian randomization (MR) study to evaluate the causal effects of multiple cardio-metabolic traits on sepsis. Global genetic correlation analysis to explore the correlations between cardio-metabolic traits and sepsis. Local genetic correlation (GC) analysis to explore shared genetic heritability between cardio-metabolic traits and sepsis. Some loci were further examined for related genes responsible for the causal relationships. Genetic associations were obtained from the UK Biobank data or published large-scale genome-wide association studies with sample sizes between 200,000 to 750,000. In MR, we found causality between BMI and sepsis (OR: 1.53 [1.4-1.67]; p < 0.001). Body mass index (BMI), which is confirmed by sensitivity analyses and multivariable MR adjusting for confounding factors. Global GC analysis showed a significant correlation between BMI and sepsis (rg = 0.55, p < 0.001). More cardio-metabolic traits were identified to be correlated to the sepsis onset such as CRP (rg = 0.37, p = 0.035), type 2 diabetes (rg = 0.33, p < 0.001), HDL (rg = - 0.41, p < 0.001), and coronary artery disease (rg = 0.43, p < 0.001). Local GC revealed some shared genetic loci responsible for the causality. The top locus 1126 was located at chromosome 7 and comprised genes HIBADH, JAZF1, and CREB5. The present study provides evidence for an independent causal effect of BMI on sepsis. Further detailed analysis of the shared genetic heritability between cardio-metabolic traits and sepsis provides the opportunity to improve the preventive strategies for sepsis.