Using genetic data to strengthen causal inference in observational research

A mediation analysis framework based on variance component to remove genetic confounding effect

Identification of pleiotropy at the single nucleotide polymorphism (SNP) level provides valuable insights into shared genetic signals among phenotypes. One approach to study these signals is through mediation analysis, which dissects the total effect of a SNP on the outcome into a direct effect and an indirect effect through a mediator. However, estimated effects from mediation analysis can be confounded by the genetic correlation between phenotypes, leading to inaccurate results. To address this confounding effect in the context of genetic mediation analysis, we propose a restricted-maximum-likelihood (REML)-based mediation analysis framework called REML-mediation, which can be applied to either individual-level or summary statistics data. Simulations demonstrated that REML-mediation provides unbiased estimates of the true cross-trait causal effect, assuming certain assumptions, albeit with a slightly inflated standard error compared to traditional linear regression. To validate the effectiveness of REML-mediation, we applied it to UK Biobank data and analyzed several mediator-outcome trait pairs along with their corresponding sets of pleiotropic SNPs. REML-mediation successfully identified and corrected for genetic confounding effects in these trait pairs, with correction magnitudes ranging from 7% to 39%. These findings highlight the presence of genetic confounding effects in cross-trait epidemiological studies and underscore the importance of accounting for them in data analysis.

A Western Dietary Pattern during Pregnancy is Associated with Neurodevelopmental Disorders in Childhood and Adolescence

Despite the high prevalence of neurodevelopmental disorders, there is a notable gap in clinical studies exploring the impact of maternal diet during pregnancy on child neurodevelopment. This observational clinical study examined the association between pregnancy dietary patterns and neurodevelopmental disorders, as well as their symptoms, in a prospective cohort of 10-year-old children (n=508). Data-driven dietary patterns were derived from self-reported food frequency questionnaires. A Western dietary pattern in pregnancy (per SD change) was significantly associated with attention-deficit / hyperactivity disorder (ADHD) (OR 1.66 [1.21 - 2.27], p=0.002) and autism diagnosis (OR 2.22 [1.33 - 3.74], p=0.002) and associated symptoms (p<0.001). Findings for ADHD were validated in three large (n=59725, n=656, n=348), independent mother-child cohorts. Objective blood metabolome modelling at 24 weeks gestation identified 15 causally mediating metabolites which significantly improved ADHD prediction in external validation. Temporal analyses across five blood metabolome timepoints in two independent mother-child cohorts revealed that the association of Western dietary pattern metabolite scores with neurodevelopmental outcomes was consistently significant in early to mid-pregnancy, independent of later child timepoints. These findings underscore the importance of early intervention and provide robust evidence for targeted prenatal dietary interventions to prevent neurodevelopmental disorders in children.

Vitamin D and thyroid function: A mendelian randomization study

BACKGROUND

Numerous organs, including the thyroid gland, depend on vitamin D to function normally. Insufficient levels of serum 25-hydroxyvitamin D [25(OH)D] are seen as a potential factor contributing to the emergence of several thyroid disorders, however, the causal relationship remains unclear. Here we use a Mendelian randomization (MR) approach to investigate the causal effect of serum 25(OH)D concentration on the indicators of thyroid function.

METHODS

We conducted a two-sample MR analysis utilizing summary data from the most extensive genome-wide association studies (GWAS) of serum 25(OH)D concentration (n = 443,734 and 417,580), thyroid-stimulating hormone (TSH, n = 271,040), free thyroxine (fT4, n = 119,120), free triiodothyronine (fT3, n = 59,061), total triiodothyronine (TT3, n = 15,829), as well as thyroid peroxidase antibody levels and positivity (TPOAb, n = 12,353 and n = 18,297), low TSH (n = 153,241), high TSH (n = 141,549), autoimmune hypothyroidism (n = 287,247) and autoimmune hyperthyroidism (n = 257,552). The primary analysis was conducted using the multiplicative random-effects inverse variance weighted (IVW) method. The weighted mode, weighted median, MR-Egger, MR-PRESSO, and Causal Analysis Using Summary Effect estimates (CAUSE) were used in the sensitivity analysis.

RESULTS

The IVW, as well as MR Egger and CAUSE analysis, showed a suggestive causal effect of 25(OH)D concentration on high TSH. Each 1 SD increase in serum 25(OH)D concentration was associated with a 12% decrease in the risk of high TSH (p = 0.02). Additionally, in the MR Egger and CAUSE analysis, we found a suggestive causal effect of 25(OH)D concentration on autoimmune hypothyroidism. Specifically, each 1 SD increase in serum 25(OH)D concentration was associated with a 16.34% decrease in the risk of autoimmune hypothyroidism (p = 0.02).

CONCLUSIONS

Our results support a suggestive causal effect which was negative in direction across all methods used, meaning that higher genetically predicted vitamin D concentration possibly lowers the odds of having high TSH or autoimmune hypothyroidism. Other thyroid parameters were not causally influenced by vitamin D serum concentration.

No Evidence of an Association between Genetic Factors Affecting Response to Vitamin A Supplementation and Myopia: A Mendelian Randomization Study and Meta-Analysis

The relationship between vitamin A supplementation and myopia has been a topic of debate, with conflicting and inconclusive findings. We aimed to determine whether there is a causal relationship between vitamin A supplementation and the risk of myopia using Mendelian randomization (MR) and meta-analytical methods. Genetic variants from the UK Biobank and FinnGen studies associated with the response to vitamin A supplementation were employed as instrumental variables to evaluate the causal relationship between vitamin A supplementation and myopia. Fixed-effects meta-analysis was then used to combine MR estimates from multiple sources for each outcome. The meta-analysis of MR results found no convincing evidence to support a direct causal relationship between vitamin A supplementation and myopia risk (odds ratio (OR) = 0.99, 95% confidence interval (CI) = 0.82-1.20, I2 = 0%, p = 0.40). The analysis of three out of the four sets of MR analyses indicated no direction of causal effect, whereas the other set of results suggested that higher vitamin A supplementation was associated with a lower risk of myopia (OR = 0.002, 95% CI 1.17 × 10-6-3.099, p = 0.096). This comprehensive MR study and meta-analysis did not find valid evidence of a direct association between vitamin A supplementation and myopia. Vitamin A supplementation may not have an independent effect on myopia, but intraocular processes associated with vitamin A may indirectly contribute to its development.

Genetic and phenotypic associations of frailty with cardiovascular indicators and behavioral characteristics

INTRODUCTION

Frailty Index (FI) is a common measure of frailty, which has been advocated as a routine clinical test by many guidelines. The genetic and phenotypic relationships of FI with cardiovascular indicators (CIs) and behavioral characteristics (BCs) are unclear, which has hampered ability to monitor FI using easily collected data.

OBJECTIVES

This study is designed to investigate the genetic and phenotypic associations of frailty with CIs and BCs, and further to construct a model to predict FI.

METHOD

Genetic relationships of FI with 288 CIs and 90 BCs were assessed by the cross-trait LD score regression (LDSC) and Mendelian randomization (MR). The phenotypic data of these CIs and BCs were integrated with a machine-learning model to predict FI of individuals in UK-biobank. The relationships of the predicted FI with risks of type 2 diabetes (T2D) and neurodegenerative diseases were tested by the Kaplan-Meier estimator and Cox proportional hazards model.

RESULTS

MR revealed putative causal effects of seven CIs and eight BCs on FI. These CIs and BCs were integrated to establish a model for predicting FI. The predicted FI is significantly correlated with the observed FI (Pearson correlation coefficient = 0.660, P-value = 4.96 × 10-62). The prediction model indicated "usual walking pace" contributes the most to prediction. Patients who were predicted with high FI are in significantly higher risk of T2D (HR = 2.635, P < 2 × 10-16) and neurodegenerative diseases (HR = 2.307, P = 1.62 × 10-3) than other patients.

CONCLUSION

This study supports associations of FI with CIs and BCs from genetic and phenotypic perspectives. The model that is developed by integrating easily collected CIs and BCs data in predicting FI has the potential to monitor disease risk.

The causal association between maternal depression, anxiety, and infection in pregnancy and neurodevelopmental disorders among 410 461 children: a population study using quasi-negative control cohorts and sibling analysis

BACKGROUND

To address if the long-standing association between maternal infection, depression/anxiety in pregnancy, and offspring neurodevelopmental disorder (NDD) is causal, we conducted two negative-control studies.

METHODS

Four primary care cohorts of UK children (pregnancy, 1 and 2 years prior to pregnancy, and siblings) born between 1 January 1990 and 31 December 2017 were constructed. NDD included autism/autism spectrum disorder, attention-deficit/hyperactivity disorder, intellectual disability, cerebral palsy, and epilepsy. Maternal exposures included depression/anxiety and/or infection. Maternal (age, smoking status, comorbidities, body mass index, NDD); child (gender, ethnicity, birth year); and area-level (region and level of deprivation) confounders were captured. The NDD incidence rate among (1) children exposed during or outside of pregnancy and (2) siblings discordant for exposure in pregnancy was compared using Cox-regression models, unadjusted and adjusted for confounders.

RESULTS

The analysis included 410 461 children of 297 426 mothers and 2 793 018 person-years of follow-up with 8900 NDD cases (incidence rate = 3.2/1000 person years). After adjustments, depression and anxiety consistently associated with NDD (pregnancy-adjusted HR = 1.58, 95% CI 1.46-1.72; 1-year adj. HR = 1.49, 95% CI 1.39-1.60; 2-year adj. HR = 1.62, 95% CI 1.50-1.74); and to a lesser extent, of infection (pregnancy adj. HR = 1.16, 95% CI 1.10-1.22; 1-year adj. HR = 1.20, 95% CI 1.14-1.27; 2-year adj. HR = 1.19, 95% CI 1.12-1.25). NDD risk did not differ among siblings discordant for pregnancy exposure to mental illness HR = 0.97, 95% CI 0.77-1.21 or infection HR = 0.99, 95% CI 0.90-1.08.

CONCLUSIONS

Maternal risk appears to be unspecific to pregnancy: our study provided no evidence of a specific, and therefore causal, link between in-utero exposure to infection, common mental illness, and later development of NDD.

Assessment of bidirectional relationships between autoimmune diseases and primary ovarian insufficiency: insights from a bidirectional two-sample Mendelian randomization analysis

PURPOSE

The simultaneous occurrence of primary ovarian insufficiency (POI) and autoimmune diseases has been noted and debated in some epidemiological research. This bidirectional two-sample Mendelian randomization (MR) study aimed to investigate the causal relationships between autoimmune diseases and POI.

METHODS

We obtained summary-level data for ten autoimmune diseases and POI from published large-scale genome-wide association studies and the FinnGen consortium of European ancestry. A series of filtering steps was performed to discern independent genetic variants. Causal estimates were mainly calculated by the inverse variance weighting method and verified through multiple sensitivity analyses.

RESULTS

Of the ten autoimmune diseases, genetically predicted Addison's disease (odds ratio [OR] = 1.26, 95% confidence interval [CI]: 1.09-1.47, P = 0.003) and systemic lupus erythematosus (OR = 1.12, 95% CI 1.02-1.24, P = 0.021) were associated with an increased risk of POI, and sensitivity analyses confirmed the robustness of the results. In addition, there were weak associations between liability to POI and elevated risks of type 1 diabetes (OR = 1.05, 95% CI 1.00-1.10, P = 0.046) and autoimmune thyroid disease (OR = 1.03, 95% CI 1.01-1.05, P = 0.015).

CONCLUSION

This study revealed that Addison's disease and systemic lupus erythematosus are potential risk factors for POI, underscoring the necessity to consider the impact of autoimmune factors in the diagnosis and treatment of POI.

Recent Advances in Genomic Studies of Gestational Duration and Preterm Birth

Preterm birth (PTB) is the leading cause of infant mortality and morbidity. For several decades, extensive epidemiologic and genetic studies have highlighted the significant contribution of maternal and offspring genetic factors to PTB. This review discusses the challenges inherent in conventional genomic analyses of PTB and underscores the importance of adopting nonconventional approaches, such as analyzing the mother-child pair as a single analytical unit, to disentangle the intertwined maternal and fetal genetic influences. We elaborate on studies investigating PTB phenotypes through 3 levels of genetic analyses: single-variant, multi-variant, and genome-wide variants.

Genetic correlation and causal associations between circulating C-reactive protein levels and lung cancer risk

PURPOSE

We aimed to characterize genetic correlations and causal associations between circulating C-reactive protein (CRP) levels and the risk of lung cancer (LC).

METHODS

Leveraging summary statistics from genome-wide association studies of circulating CRP levels among 575,531 individuals of European ancestry, and LC risk among 29,266 cases and 56,450 controls, we investigated genetic associations of circulating CRP levels with the risk of overall lung cancer and its histological subtypes, by using linkage disequilibrium score (LDSC) regression and Mendelian randomization (MR) analyses.

RESULTS

Significant positive genetic correlations between circulating CRP levels and the risk of LC and its histological subtypes were identified from LDSC regression, with correlation coefficients ranging from 0.12 to 0.26, and all false discovery adjusted p < 0.05. Univariable MR demonstrated a nominal association between CRP levels and an increased risk of lung squamous cell carcinoma (SCC) (inverse variance-weighted OR = 1.15, 95% CI 1.01-1.30). However, this association disappeared when multivariable MR included cigarettes per day and/or body mass index. By using our recently developed constrained maximum likelihood-based MR method, we identified significant associations of CRP levels with the risk of overall LC (OR 1.06, 95% CI 1.03-1.09), SCC (OR 1.06, 95% CI 1.02-1.09), and small cell lung cancer (SCLC, OR 1.09, 95% CI 1.03-1.15). Moreover, most univariable and multivariable MR analyses also revealed consistent CRP-SCLC associations.

CONCLUSION

There may be a genetic and causal association between circulating CRP levels and the risk of SCLC, which is in line with previous population-based observational studies.

Gene-environment interactions in human health

Gene-environment interactions (G × E), the interplay of genetic variation with environmental factors, have a pivotal impact on human complex traits and diseases. Statistically, G × E can be assessed by determining the deviation from expectation of predictive models based solely on the phenotypic effects of genetics or environmental exposures. Despite the unprecedented, widespread and diverse use of G × E analytical frameworks, heterogeneity in their application and reporting hinders their applicability in public health. In this Review, we discuss study design considerations as well as G × E analytical frameworks to assess polygenic liability dependent on the environment, to identify specific genetic variants exhibiting G × E, and to characterize environmental context for these dynamics. We conclude with recommendations to address the most common challenges and pitfalls in the conceptualization, methodology and reporting of G × E studies, as well as future directions.

Brain cell-type shifts in Alzheimer's disease, autism, and schizophrenia interrogated using methylomics and genetics

Few neuropsychiatric disorders have replicable biomarkers, prompting high-resolution and large-scale molecular studies. However, we still lack consensus on a more foundational question: whether quantitative shifts in cell types-the functional unit of life-contribute to neuropsychiatric disorders. Leveraging advances in human brain single-cell methylomics, we deconvolve seven major cell types using bulk DNA methylation profiling across 1270 postmortem brains, including from individuals diagnosed with Alzheimer's disease, schizophrenia, and autism. We observe and replicate cell-type compositional shifts for Alzheimer's disease (endothelial cell loss), autism (increased microglia), and schizophrenia (decreased oligodendrocytes), and find age- and sex-related changes. Multiple layers of evidence indicate that endothelial cell loss contributes to Alzheimer's disease, with comparable effect size to APOE genotype among older people. Genome-wide association identified five genetic loci related to cell-type composition, involving plausible genes for the neurovascular unit (P2RX5 and TRPV3) and excitatory neurons (DPY30 and MEMO1). These results implicate specific cell-type shifts in the pathophysiology of neuropsychiatric disorders.

Genetically predicted fatty liver disease and risk of psychiatric disorders: A mendelian randomization study

BACKGROUND

Non-alcoholic fatty liver disease (NAFLD) and alcohol-related liver disease (ArLD) constitute the primary forms of chronic liver disease, and their incidence is progressively increasing with changes in lifestyle habits. Earlier studies have documented a correlation between the occurrence and development of prevalent mental disorders and fatty liver.

AIM

To investigate the correlation between fatty liver and mental disorders, thus necessitating the implementation of a mendelian randomization (MR) study to elucidate this association.

METHODS

Data on NAFLD and ArLD were retrieved from the genome-wide association studies catalog, while information on mental disorders, including Alzheimer's disease, schizophrenia, anxiety disorder, attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder, multiple personality disorder, obsessive-compulsive disorder (OCD), post-traumatic stress disorder (PTSD), and schizophrenia was acquired from the psychiatric genomics consortium. A two-sample MR method was applied to investigate mediators in significant associations.

RESULTS

After excluding weak instrumental variables, a causal relationship was identified between fatty liver disease and the occurrence and development of some psychiatric disorders. Specifically, the findings indicated that ArLD was associated with a significantly elevated risk of developing ADHD (OR: 5.81, 95%CI: 5.59-6.03, P < 0.01), bipolar disorder (OR: 5.73, 95%CI: 5.42-6.05, P = 0.03), OCD (OR: 6.42, 95%CI: 5.60-7.36, P < 0.01), and PTSD (OR: 5.66, 95%CI: 5.33-6.01, P < 0.01). Meanwhile, NAFLD significantly increased the risk of developing bipolar disorder (OR: 55.08, 95%CI: 3.59-845.51, P < 0.01), OCD (OR: 61.50, 95%CI: 6.69-565.45, P < 0.01), and PTSD (OR: 52.09, 95%CI: 4.24-639.32, P < 0.01).

CONCLUSION

Associations were found between genetic predisposition to fatty liver disease and an increased risk of a broad range of psychiatric disorders, namely bipolar disorder, OCD, and PTSD, highlighting the significance of preventive measures against psychiatric disorders in patients with fatty liver disease.

Causal relationship between serum metabolites and juvenile idiopathic arthritis: a mendelian randomization study

BACKGROUND

Juvenile Idiopathic Arthritis (JIA) is a condition that occurs when individuals under the age of 16 develop arthritis that lasts for more than six weeks, and the cause is unknown. The development of JIA may be linked to serum metabolites. Nevertheless, the association between JIA pathogenesis and serum metabolites is unclear, and there are discrepancies in the findings across studies.

METHODS

In this research, the association between JIA in humans and 486 serum metabolites was assessed using genetic variation data and genome-wide association study. The identification of causal relationships was accomplished through the application of univariate Mendelian randomization (MR) analysis. Various statistical methods, including inverse variance weighted and MR-Egger, were applied to achieve this objective. To ensure that the findings from the MR analysis were trustworthy, a number of assessments were carried out. To ensure the accuracy of the obtained results, a range of techniques were utilised including the Cochran Q test, examination of the MR-Egger intercept, implementation of the leave-one-out strategy, and regression analysis of linkage disequilibrium scores. In order to identify the specific metabolic pathways associated with JIA, our primary objective was to perform pathway enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes.

RESULTS

Two-sample summary data MR analyses and sensitivity analyses showed that five metabolites were significantly causally associated with JIA, including two risk factors-kynurenine (odds ratio [OR]: 16.39, 95% confidence interval [CI]: 2.07-129.63, p = 5.11 × 10- 6) and linolenate (OR: 16.48, 95% CI: 1.32-206.22, p = 0.030)-and three protective factors-3-dehydrocarnitine (OR: 0.32, 95% CI: 0.14-0.72, p = 0.007), levulinate (4-oxovalerate) (OR: 0.40, 95% CI: 0.20-0.80, p = 0.010), and X-14,208 (phenylalanylserine) (OR: 0.68, 95% CI: 0.51-0.92, p = 0.010). Furthermore, seven metabolic pathways, including α-linolenic acid metabolism and pantothenate and CoA biosynthesis, are potentially associated with the onset and progression of JIA.

CONCLUSION

Five serum metabolites, including kynurenine and 3-dehydrocarnitine, may be causally associated with JIA. These results provide a theoretical framework for developing effective JIA prevention and screening strategies.

Association between diabetes mellitus and primary biliary cholangitis: a two-sample Mendelian randomization study

Background

Previous observational studies have demonstrated a link between diabetes mellitus(DM) and primary biliary cholangitis (PBC). Nevertheless, since these relationships might be confused, whether there is any causal connection or in which direction it exists is unclear. Our investigation aimed to identify the causal associations between DM and PBC.

Methods

We acquired genome-wide association study (GWAS) datasets for PBC, Type 1 diabetes(T1DM), and Type 2 diabetes(T2DM) from published GWASs. Inverse variance-weighted (IVW), MR-Egger, weighted median (WM), Simple mode, and weighted mode methods were used to determine the causal relationships between DM(T1DM or T2DM) and PBC. Sensitivity analyses were also carried out to ensure the results were robust. To determine the causal relationship between PBC and DM(T1DM or T2DM), we also used reverse MR analysis.

Results

T1DM was associated with a higher risk of PBC (OR 1.1525; 95% CI 1.0612-1.2517; p = 0.0007) in the IVW method, but no evidence of a causal effect T2DM on PBC was found (OR 0.9905; 95% CI 0.8446-1.1616; p = 0.9071) in IVW. Results of the reverse MR analysis suggested genetic susceptibility that PBC was associated with an increased risk of T1DM (IVW: OR 1.1991; 95% CI 1.12-1.2838; p = 1.81E-07), but no evidence of a causal effect PBC on T2DM was found (IVW: OR 1.0101; 95% CI 0.9892-1.0315; p = 0.3420).

Conclusion

The current study indicated that T1DM increased the risk of developing PBC and vice versa. There was no proof of a causal connection between PBC probability and T2DM. Our results require confirmation through additional replication in larger populations.

Running in the FAMILY: understanding and predicting the intergenerational transmission of mental illness

Over 50% of children with a parent with severe mental illness will develop mental illness by early adulthood. However, intergenerational transmission of risk for mental illness in one's children is insufficiently considered in clinical practice, nor is it sufficiently utilised into diagnostics and care for children of ill parents. This leads to delays in diagnosing young offspring and missed opportunities for protective actions and resilience strengthening. Prior twin, family, and adoption studies suggest that the aetiology of mental illness is governed by a complex interplay of genetic and environmental factors, potentially mediated by changes in epigenetic programming and brain development. However, how these factors ultimately materialise into mental disorders remains unclear. Here, we present the FAMILY consortium, an interdisciplinary, multimodal (e.g., (epi)genetics, neuroimaging, environment, behaviour), multilevel (e.g., individual-level, family-level), and multisite study funded by a European Union Horizon-Staying-Healthy-2021 grant. FAMILY focuses on understanding and prediction of intergenerational transmission of mental illness, using genetically informed causal inference, multimodal normative prediction, and animal modelling. Moreover, FAMILY applies methods from social sciences to map social and ethical consequences of risk prediction to prepare clinical practice for future implementation. FAMILY aims to deliver: (i) new discoveries clarifying the aetiology of mental illness and the process of resilience, thereby providing new targets for prevention and intervention studies; (ii) a risk prediction model within a normative modelling framework to predict who is at risk for developing mental illness; and (iii) insight into social and ethical issues related to risk prediction to inform clinical guidelines.

Genetics of migraine: complexity, implications, and potential clinical applications

Migraine is a common neurological disorder with large burden in terms of disability for individuals and costs for society. Accurate diagnosis and effective treatments remain priorities. Understanding the genetic factors that contribute to migraine risk and symptom manifestation could improve individual management. Migraine has a strong genetic basis that includes both monogenic and polygenic forms. Some distinct, rare, familial migraine subtypes are caused by pathogenic variants in genes involved in ion transport and neurotransmitter release, suggesting an underlying vulnerability of the excitatory-inhibitory balance in the brain, which might be exacerbated by disruption of homoeostasis and lead to migraine. For more prevalent migraine subtypes, genetic studies have identified many susceptibility loci, implicating genes involved in both neuronal and vascular pathways. Genetic factors can also reveal the nature of relationships between migraine and its associated biomarkers and comorbidities and could potentially be used to identify new therapeutic targets and predict treatment response.

Genetically Predicted Apolipoprotein E Levels with the Risk of Panvascular Diseases: A Mendelian Randomization Study

The aim of this study was to comprehensively assess the causal relationship between the overall genetic effect of circulating ApoE levels and panvascular lesions using newer genome-wide association data and two-sample bidirectional Mendelian randomization (MR) analysis. Two-way MR using single-nucleotide polymorphisms of circulating ApoE as instrumental variables was performed using the highest-priority Genome-wide association study (GWAS) data, with factor-adjusted and data-corrected statistics, to estimate causal associations between circulating ApoE levels and 10 pan-vascular diseases in > 500,000 UK Biobank participants, > 400,000 participants of Finnish ancestry, and numerous participants in a consortium of predominantly European ancestry. Meta-analysis was conducted to assess positive results. After correcting for statistical results, elevated circulating ApoE levels were shown to have a significant protective effect against Cerebral ischemia (CI) [IVW odds ratio (OR) 0.888, 95% Confidence Interval (CI): 0.823-0.958, p = 2.3 × 10-3], Coronary heart disease [IVW OR 0.950,95% CI: 0.924-0.976, p = 2.0 × 10-4] had a significant protective effect and potentially suggestive protective causality against Angina pectoris [IVW odds ratio (OR) 0.961, 95%CI: 0.931-0.991, p = 1.1 × 10-2]. There was a potential causal effect for increased risk of Heart failure (HF) [IVW ratio (OR) 1.040, 95%CI: 1.006-1.060, p = 1.8 × 10-2]. (Bonferroni threshold p < 0.0026, PFDR < 0.05) Reverse MR analysis did not reveal significant evidence of a causal effect of PVD on changes in circulating ApoE levels. Meta-analysis increases reliability of results. Elevated circulating ApoE levels were particularly associated with an increased risk of heart failure. Elevated ApoE levels reduce the risk of cerebral ischemia, coronary heart disease, and angina pectoris, reflecting a protective effect. The possible pathophysiological role of circulating ApoE levels in the development of panvascular disease is emphasized.

Causal Estimation of Long-term Intervention Cost-effectiveness Using Genetic Instrumental Variables: An Application to Cancer

BACKGROUND

This article demonstrates a means of assessing long-term intervention cost-effectiveness in the absence of data from randomized controlled trials and without recourse to Markov simulation or similar types of cohort simulation.

METHODS

Using a Mendelian randomization study design, we developed causal estimates of the genetically predicted effect of bladder, breast, colorectal, lung, multiple myeloma, ovarian, prostate, and thyroid cancers on health care costs and quality-adjusted life-years (QALYs) using outcome data drawn from the UK Biobank cohort. We then used these estimates in a simulation model to estimate the cost-effectiveness of a hypothetical population-wide preventative intervention based on a repurposed class of antidiabetic drugs known as sodium-glucose cotransporter-2 (SGLT2) inhibitors very recently shown to reduce the odds of incident prostate cancer.

RESULTS

Genetic liability to prostate cancer and breast cancer had material causal impacts on either or both health care costs and QALYs. Mendelian randomization results for the less common cancers were associated with considerable uncertainty. SGLT2 inhibition was unlikely to be a cost-effective preventative intervention for prostate cancer, although this conclusion depended on the price at which these drugs would be offered for a novel anticancer indication.

IMPLICATIONS

Our new causal estimates of cancer exposures on health economic outcomes may be used as inputs into decision-analytic models of cancer interventions such as screening programs or simulations of longer-term outcomes associated with therapies investigated in randomized controlled trials with short follow-ups. Our method allowed us to rapidly and efficiently estimate the cost-effectiveness of a hypothetical population-scale anticancer intervention to inform and complement other means of assessing long-term intervention value.

HIGHLIGHTS

The article demonstrates a novel method of assessing long-term intervention cost-effectiveness without relying on randomized controlled trials or cohort simulations.Mendelian randomization was used to estimate the causal effects of certain cancers on health care costs and quality-adjusted life-years (QALYs) using data from the UK Biobank cohort.Given causal data on the association of different cancer exposures on costs and QALYs, it was possible to simulate the cost-effectiveness of an anticancer intervention.Genetic liability to prostate cancer and breast cancer significantly affected health care costs and QALYs, but the hypothetical intervention using SGLT2 inhibitors for prostate cancer may not be cost-effective, depending on the drug's price for the new anticancer indication. The methods we propose and implement can be used to efficiently estimate intervention cost-effectiveness and to inform decision making in all manner of preventative and therapeutic contexts.

Examining intergenerational risk factors for conduct problems using polygenic scores in the Norwegian Mother, Father and Child Cohort Study

The aetiology of conduct problems involves a combination of genetic and environmental factors, many of which are inherently linked to parental characteristics given parents' central role in children's lives across development. It is important to disentangle to what extent links between parental heritable characteristics and children's behaviour are due to transmission of genetic risk or due to parental indirect genetic influences via the environment (i.e., genetic nurture). We used 31,290 genotyped mother-father-child trios from the Norwegian Mother, Father and Child Cohort Study (MoBa), testing genetic transmission and genetic nurture effects on conduct problems using 13 polygenic scores (PGS) spanning psychiatric conditions, substance use, education-related factors, and other risk factors. Maternal or self-reports of conduct problems at ages 8 and 14 years were available for up to 15,477 children. We found significant genetic transmission effects on conduct problems for 12 out of 13 PGS at age 8 years (strongest association: PGS for smoking, β = 0.07, 95% confidence interval = [0.05, 0.08]) and for 4 out of 13 PGS at age 14 years (strongest association: PGS for externalising problems, β = 0.08, 95% confidence interval = [0.05, 0.11]). Conversely, we did not find genetic nurture effects for conduct problems using our selection of PGS. Our findings provide evidence for genetic transmission in the association between parental characteristics and child conduct problems. Our results may also indicate that genetic nurture via traits indexed by our polygenic scores is of limited aetiological importance for conduct problems-though effects of small magnitude or effects via parental traits not captured by the included PGS remain a possibility.

Annual Research Review: The power of predictability - patterns of signals in early life shape neurodevelopment and mental health trajectories

The global burden of early life adversity (ELA) is profound. The World Health Organization has estimated that ELA accounts for almost 30% of all psychiatric cases. Yet, our ability to identify which individuals exposed to ELA will develop mental illness remains poor and there is a critical need to identify underlying pathways and mechanisms. This review proposes unpredictability as an understudied aspect of ELA that is tractable and presents a conceptual model that includes biologically plausible mechanistic pathways by which unpredictability impacts the developing brain. The model is supported by a synthesis of published and new data illustrating the significant impacts of patterns of signals on child development. We begin with an overview of the existing unpredictability literature, which has focused primarily on longer patterns of unpredictability (e.g. years, months, and days). We then describe our work testing the impact of patterns of parental signals on a moment-to-moment timescale, providing evidence that patterns of these signals during sensitive windows of development influence neurocircuit formation across species and thus may be an evolutionarily conserved process that shapes the developing brain. Next, attention is drawn to emerging themes which provide a framework for future directions of research including the evaluation of functions, such as effortful control, that may be particularly vulnerable to unpredictability, sensitive periods, sex differences, cross-cultural investigations, addressing causality, and unpredictability as a pathway by which other forms of ELA impact development. Finally, we provide suggestions for prevention and intervention, including the introduction of a screening instrument for the identification of children exposed to unpredictable experiences.

Childhood maltreatment and health in the UK Biobank: triangulation of outcome-wide and polygenic risk score analyses

BACKGROUND

Childhood maltreatment is common globally and impacts morbidity, mortality, and well-being. Our understanding of its impact is constrained by key substantive and methodological limitations of extant research, including understudied physical health outcomes and bias due to unmeasured confounding. We address these limitations through a large-scale outcome-wide triangulation study.

METHODS

We performed two outcome-wide analyses (OWAs) in the UK Biobank. First, we examined the relationship between self-reported maltreatment exposure (number of maltreatment types, via Childhood Trauma Screener) and 414 outcomes in a sub-sample of 157,316 individuals using generalized linear models ("observational OWA"). Outcomes covered a broad range of health themes including health behaviors, cardiovascular disease, digestive health, socioeconomic status, and pain. Second, we examined the relationship between a polygenic risk score for maltreatment and 298 outcomes in a non-overlapping sample of 243,006 individuals ("genetic OWA"). We triangulated results across OWAs based on differing sources of bias.

RESULTS

Overall, 23.8% of the analytic sample for the observational OWA reported at least one maltreatment type. Of 298 outcomes examined in both OWAs, 25% were significant in both OWAs and concordant in the direction of association. Most of these were considered robust in the observational OWA according to sensitivity analyses and included outcomes such as marital separation (OR from observational OWA, ORo = 1.25 (95% CI: 1.21, 1.29); OR from genetic OWA, ORg = 1.06 (1.03, 1.08)), major diet changes due to illness (ORo = 1.27 (1.24, 1.29); ORg = 1.01 (1.00, 1.03)), certain intestinal diseases (ORo = 1.14 (1.10, 1.18); ORg = 1.03 (1.01, 1.06)), hearing difficulty with background noise (ORo = 1.11 (1.11, 1.12); ORg = 1.01 (1.00, 1.01)), knee arthrosis (ORo = 1.13 (1.09, 1.18); ORg = 1.03 (1.01, 1.05)), frequent sleeplessness (ORo = 1.21 (1.20, 1.23); ORg = 1.02 (1.01, 1.03)), and low household income (ORo = 1.28 (1.26, 1.31); ORg = 1.02 (1.01, 1.03)). Approximately 62% of results were significant in the observational OWA but not the genetic OWA, including numerous cardiovascular outcomes. Only 6 outcomes were significant in the genetic OWA and null in the observational OWA; these included diastolic blood pressure and glaucoma. No outcomes were statistically significant in opposite directions in the two analyses, and 11% were not significant in either OWA.

CONCLUSIONS

Our findings underscore the far-reaching negative effects of childhood maltreatment in later life and the utility of an outcome-wide triangulation design with sensitivity analyses for improving causal inference.

ACTN3 XX Genotype Negatively Affects Running Performance and Increases Muscle Injury Incidence in LaLiga Football Players

The aim of this study was to investigate the association of the ACTN3 rs1815739 polymorphism with match running performance and injury incidence in top-level professional football players. A total of 315 top-level professional football players from the first division of Spanish football (i.e., LaLiga) participated in this prospective and descriptive study. The ACTN3 rs1815739 genotype was identified for each player using genomic DNA samples. During LaLiga 2021-2022, players' performance was obtained through a validated camera system in all official matches. Additionally, the incidence of non-contact injuries was obtained by each team's medical staff according to the International Olympic Committee (IOC) statement. From the study sample, 116 (36.8%) players had the RR genotype, 156 (49.5%) had the RX genotype, and 43 (13.7%) had the XX genotype. The anthropometric characteristics of the players were similar across genotypes. However, the total running distance (p = 0.046), the distance at 21.0-23.9 km/h (p = 0.042), and the number of sprints (p = 0.042) were associated with the ACTN3 genotype. In all these variables, XX players had lower match performance values than RR players. Additionally, total and match injury incidences were higher in XX players than in RR players (p = 0.026 and 0.009, respectively). The rate of muscle injuries was also higher in XX players (p = 0.016). LaLiga football players with the ACTN3 XX genotype had lower match running performance and a higher incidence of non-contact injuries over the season.

Evaluating the impact of childhood BMI on the risk of coronavirus disease 2019: A Mendelian randomization study

Introduction

Although the correlation between childhood obesity and coronavirus disease 2019 (COVID-19) has been explored, the causality of these remains uncertain. Thus, we conducted a two-sample Mendelian randomization (MR) analysis to identify the causal association.

Methods

Instrumental variables of childhood obesity were selected from genome-wide association study involving 61,111 Europeans. Besides, we collected summary statistics of different COVID-19 outcomes (susceptibility, hospitalization, and severity) from genome-wide association study including more than 2 million Europeans. The inverse-variance weighted was applied to assess the causality of childhood obesity with COVID-19. Furthermore, we replicated the above association based on another study.

Results

Inverse-variance weighted results suggested that childhood obesity promoted the COVID-19 susceptibility but has not been validated in other approaches. For hospitalization and severity of COVID-19, we found that childhood obesity, respectively, increased 30 and 38% risk (P < 0.001), which were consistent in other MR approaches.

Discussion

Our study provides evidence for a causal relationship between childhood BMI and COVID-19 which is consistent with previous studies. Though these explanations are biologically plausible, further studies are warranted to elucidate the role of these.

Conclusions

Our study suggests the potential causal associations of childhood obesity with COVID-19, especially hospitalization and severity of COVID-19.

Sjögren's Disease and Oral Health: A Genetic Instrumental Variable Analysis

Epidemiological studies have consistently shown that Sjögren's disease (SjD) increases the risk of dental caries. Despite similar evidence indicating an elevated risk of periodontitis, SjD remains a disputed risk factor for this disease. The risk of bias in observational research is a major impediment to confirming this link. Within an instrumental variable framework, genetic variants associated with a risk factor can be used to proxy its effect on an outcome while avoiding common sources of observational study bias. In this study, we leveraged an instrumental variable approach to investigate whether SjD affects the risk of caries and periodontitis. A total of 57 genetic variants strongly associated with SjD were identified from a genome-wide association study of 2,247 European descent cases and 332,115 controls. We tested for associations of these genetic instruments with caries (measured as the number of decayed, missing, and filled surfaces in 26,792 individuals) and periodontitis (17,353 clinical periodontitis cases and 28,210 European controls). Several sensitivity analyses were used to further validate the primary inverse variance weighted (IVW) estimate. IVW analysis revealed an adverse effect of SjD on caries (β = 0.039, P = 6.3e-16) and periodontitis (odds ratio = 1.033, P = 2.3e-05). Sensitivity analyses, conducted to assess the robustness to potential violations of instrumental variable assumptions, further support these findings. Our results showed that SjD has a detrimental effect on caries and also suggest that SjD promotes periodontitis.

Bayesian network-based Mendelian randomization for variant prioritization and phenotypic causal inference

Mendelian randomization is a powerful method for inferring causal relationships. However, obtaining suitable genetic instrumental variables is often challenging due to gene interaction, linkage, and pleiotropy. We propose Bayesian network-based Mendelian randomization (BNMR), a Bayesian causal learning and inference framework using individual-level data. BNMR employs the random graph forest, an ensemble Bayesian network structural learning process, to prioritize candidate genetic variants and select appropriate instrumental variables, and then obtains a pleiotropy-robust estimate by incorporating a shrinkage prior in the Bayesian framework. Simulations demonstrate BNMR can efficiently reduce the false-positive discoveries in variant selection, and outperforms existing MR methods in terms of accuracy and statistical power in effect estimation. With application to the UK Biobank, BNMR exhibits its capacity in handling modern genomic data, and reveals the causal relationships from hematological traits to blood pressures and psychiatric disorders. Its effectiveness in handling complex genetic structures and modern genomic data highlights the potential to facilitate real-world evidence studies, making it a promising tool for advancing our understanding of causal mechanisms.

Association of chronic pain with suicide attempt and death by suicide: a two-sample Mendelian randomization

Prior studies have suggested an association between chronic pain and suicidal behavior. However, evidence supporting the causal nature of this association, and the role played by depression, remain difficult to establish due to confounding. We investigated associations of chronic pain with suicide attempt and death by suicide as well as the mediating role of depression in this association using a genetically informed method strengthening causal inference. We conducted a two-sample Mendelian randomization. Independent SNPs (N = 97) from the multisite chronic pain GWAS (NGWAS = 387,649) were used as instrumental variables to test associations of chronic pain with suicide attempt (measured from hospital records; NGWAS = 50,264) and death by suicide (measured from official death causes; NGWAS = 18,085). Indirect associations of chronic pain with suicide attempt and death by suicide via major depressive disorder (NGWAS = 173,005) were estimated. Primary analyses were supported by a range of sensitivity and outlier analyses. We found evidence supporting the contribution of chronic pain to increasing the risk of suicide attempt (OR = 1.67, CI = 1.21-2.35) and death by suicide (OR = 2.00, CI = 1.10-3.62). Associations were consistent across sensitivity analysis methods, and no evidence for outliers driving these associations was found. Through mediation analyses, we found that major depressive disorder explained a substantial proportion of the association between chronic pain and suicide attempt (proportion mediated = 39%; ORindirect association = 1.32, CI = 1.09-1.61) and death by suicide (proportion mediated = 34%; ORindirect association = 1.40, CI = 1.13-1.73). Our findings suggest that both pain management interventions and prevention of depression are likely to be effective strategies to reduce suicide risk in individuals with chronic pain.

Controlling for polygenic genetic confounding in epidemiologic association studies

Epidemiologic associations estimated from observational data are often confounded by genetics due to pervasive pleiotropy among complex traits. Many studies either neglect genetic confounding altogether or rely on adjusting for polygenic scores (PGS) in regression analysis. In this study, we unveil that the commonly employed PGS approach is inadequate for removing genetic confounding due to measurement error and model misspecification. To tackle this challenge, we introduce PENGUIN, a principled framework for polygenic genetic confounding control based on variance component estimation. In addition, we present extensions of this approach that can estimate genetically-unconfounded associations using GWAS summary statistics alone as input and between multiple generations of study samples. Through simulations, we demonstrate superior statistical properties of PENGUIN compared to the existing approaches. Applying our method to multiple population cohorts, we reveal and remove substantial genetic confounding in the associations of educational attainment with various complex traits and between parental and offspring education. Our results show that PENGUIN is an effective solution for genetic confounding control in observational data analysis with broad applications in future epidemiologic association studies.

Cardiovascular diseases consequences of type 1, type 2 diabetes mellitus and glycemic traits: A Mendelian randomization study

OBJECTIVE

This Mendelian randomization (MR) study aimed to investigate the relationships between type 1 diabetes (T1D), type 2 diabetes (T2D), and glycemic traits, including fasting insulin, fasting glucose, and HbA1c, with cardiovascular diseases (CVDs).

METHODS

We selected genetic instruments for predisposition to T1D, T2D, fasting insulin, fasting glucose, and HbA1c based on published genome-wide association studies. Using a 2-Sample MR approach, we assessed associations with 12 common CVDs sourced from the FinnGen and UK Biobank studies, along with stroke subtypes obtained from the GIGASTROKE and MEGASTROKE Consortium.

RESULTS

T1D was associated with SVS. T2D showed associations with AIS, LAA, CES, SVS, coronary heart disease, myocardial infarction, pulmonary embolism, DVT of lower extremities, peripheral vascular diseases. Genetically predicted higher HbA1c levels were associated with eight CVDs. The results of MVMR aligned with the primary findings for T1D and T2D.

CONCLUSIONS

T1D and T2D exhibit different genetic predisposition to CVDs. BMI, LDL, and HDL play intermediary roles in connecting TID and T2D to specific types of CVDs, providing insights into the potential underlying pathways and mechanisms involved in these relationships. Strategies aimed at achieving sustained reductions in HbA1c levels may offer potential for reducing the risk of various CVDs.

Association of Chronic Obstructive Pulmonary Disease with Risk of Psychiatric Disorders: A Two-Sample Mendelian Randomization Study

Background

Chronic obstructive pulmonary disease (COPD) is a prevalent respiratory disorder often accompanied by comorbidities. Although the past few years have witnessed significant scientific progress, the potential relationship between COPD and mental illness remains a subject of debate.

Materials and Methods

We retrieved COPD data from the genome-wide association studies (GWAS) directory and data on mental illnesses, including Alzheimer's disease, schizophrenia, panic disorder, attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder, multiple disabilities, obsessive-compulsive disorder, post-traumatic stress disorder, and schizophrenia, from the Psychiatric Genomics Consortium. A two-sample Mendelian randomization (MR) approach was applied to explore the association between COPD and mental illnesses, with subgroup analyses based on smoking history.

Results

Our two-sample MR analysis revealed no causal link between overall COPD and the development of common psychiatric disorders. Subgroup analyses based on smoking history showed no causal association between never-smokers with COPD and the occurrence of psychiatric disorders. However, ever-smokers with COPD were associated with a significantly increased risk of ADHD (OR: 2.303, 95% CI: 1.558-3.403, P = 0.001) and a modestly reduced risk of Alzheimer's disease (OR: 0.994, 95% CI: 0.988-0.999, P = 0.034).

Conclusion

COPD patients with a history of smoking face a higher risk of developing ADHD but may experience a slight reduction in the risk of Alzheimer's disease. Conversely, there was no observed causal association between COPD and psychiatric disorders among patients who never smoked.

MRSL: a causal network pruning algorithm based on GWAS summary data

Causal discovery is a powerful tool to disclose underlying structures by analyzing purely observational data. Genetic variants can provide useful complementary information for structure learning. Recently, Mendelian randomization (MR) studies have provided abundant marginal causal relationships of traits. Here, we propose a causal network pruning algorithm MRSL (MR-based structure learning algorithm) based on these marginal causal relationships. MRSL combines the graph theory with multivariable MR to learn the conditional causal structure using only genome-wide association analyses (GWAS) summary statistics. Specifically, MRSL utilizes topological sorting to improve the precision of structure learning. It proposes MR-separation instead of d-separation and three candidates of sufficient separating set for MR-separation. The results of simulations revealed that MRSL had up to 2-fold higher F1 score and 100 times faster computing time than other eight competitive methods. Furthermore, we applied MRSL to 26 biomarkers and 44 International Classification of Diseases 10 (ICD10)-defined diseases using GWAS summary data from UK Biobank. The results cover most of the expected causal links that have biological interpretations and several new links supported by clinical case reports or previous observational literatures.

Social isolation, loneliness, and inflammation: A multi-cohort investigation in early and mid-adulthood

Social isolation and loneliness have been associated with poor health and increased risk for mortality, and inflammation might explain this link. We used data from the Danish TRIAGE Study of acutely admitted medical patients (N = 6,144, mean age 60 years), and from two population-representative birth cohorts: the New Zealand Dunedin Longitudinal Study (N = 881, age 45) and the UK Environmental Risk (E-Risk) Longitudinal Twin Study (N = 1448, age 18), to investigate associations of social isolation with three markers of systemic inflammation: C-reactive protein (CRP), interleukin-6 (IL-6), and a newer inflammation marker, soluble urokinase plasminogen activator receptor (suPAR), which is thought to index systemic chronic inflammation. In the TRIAGE Study, socially isolated patients (those living alone) had significantly higher median levels of suPAR (but not CRP or IL-6) compared with patients not living by themselves. Social isolation prospectively measured in childhood was longitudinally associated with higher CRP, IL-6, and suPAR levels in adulthood (at age 45 in the Dunedin Study and age 18 in the E-Risk Study), but only suPAR remained associated after controlling for covariates. Dunedin Study participants who reported loneliness at age 38 or age 45 had elevated suPAR at age 45. In contrast, E-Risk Study participants reporting loneliness at age 18 did not show any elevated markers of inflammation. In conclusion, social isolation was robustly associated with increased inflammation in adulthood, both in medical patients and in the general population. It was associated in particular with systemic chronic inflammation, evident from the consistently stronger associations with suPAR than other inflammation biomarkers.

The relationship of school performance with self-control and grit is strongly genetic and weakly causal

The non-cognitive skills self-control and grit are often considered predictors of school performance, but whether this relationship is causal remains unclear. We investigated the causality of this association using a twin design. Specifically, we evaluated the direct impact of self-control and grit on school performance, while controlling for genetic or environmental influences common to all three traits (i.e., confounding). Teachers of 4891 Dutch 12-year-old twin pairs (of which 3837 were complete pairs) completed a survey about school performance (school grades), self-control (ASEBA self-control scale), and the perseverance aspect of grit. Our analysis aimed to determine the direct impact of self-control and grit on school performance, while simultaneously controlling for genetic or environmental confounding. Establishing the regression relationship corrected for confounding supports the interpretation of the regression relationship as causal. In all analyses, we corrected for sex, rater bias of the teachers, and parental socioeconomic status. Initially, in the standard regression, self-control, and grit explained 28.4% of the school performance variance. However, allowing for genetic confounding (due to genetic pleiotropy) revealed that most of this association could be attributed to genetic influences that the three traits share. In the presence of genetic pleiotropy, the phenotypic regression of school performance on self-control and grit accounted for only 4.4% (i.e., the effect size association with the causal hypothesis). In conclusion, self-control and grit predict school performance primarily due to genetic pleiotropy, with a much smaller causal effect (R2 = 4.4%). This suggests that interventions targeting self-control and grit alone may yield limited improvements in school performance.

Linking Prenatal Environmental Exposures to Lifetime Health with Epigenome-Wide Association Studies: State-of-the-Science Review and Future Recommendations

BACKGROUND

The prenatal environment influences lifetime health; epigenetic mechanisms likely predominate. In 2016, the first international consortium paper on cigarette smoking during pregnancy and offspring DNA methylation identified extensive, reproducible exposure signals. This finding raised expectations for epigenome-wide association studies (EWAS) of other exposures.

OBJECTIVE

We review the current state-of-the-science for DNA methylation associations across prenatal exposures in humans and provide future recommendations.

METHODS

We reviewed 134 prenatal environmental EWAS of DNA methylation in newborns, focusing on 51 epidemiological studies with meta-analysis or replication testing. Exposures spanned cigarette smoking, alcohol consumption, air pollution, dietary factors, psychosocial stress, metals, other chemicals, and other exogenous factors. Of the reproducible DNA methylation signatures, we examined implementation as exposure biomarkers.

RESULTS

Only 19 (14%) of these prenatal EWAS were conducted in cohorts of 1,000 or more individuals, reflecting the still early stage of the field. To date, the largest perinatal EWAS sample size was 6,685 participants. For comparison, the most recent genome-wide association study for birth weight included more than 300,000 individuals. Replication, at some level, was successful with exposures to cigarette smoking, folate, dietary glycemic index, particulate matter with aerodynamic diameter < 10 μ m and < 2.5 μ m , nitrogen dioxide, mercury, cadmium, arsenic, electronic waste, PFAS, and DDT. Reproducible effects of a more limited set of prenatal exposures (smoking, folate) enabled robust methylation biomarker creation.

DISCUSSION

Current evidence demonstrates the scientific premise for reproducible DNA methylation exposure signatures. Better powered EWAS could identify signatures across many exposures and enable comprehensive biomarker development. Whether methylation biomarkers of exposures themselves cause health effects remains unclear. We expect that larger EWAS with enhanced coverage of epigenome and exposome, along with improved single-cell technologies and evolving methods for integrative multi-omics analyses and causal inference, will expand mechanistic understanding of causal links between environmental exposures, the epigenome, and health outcomes throughout the life course. https://doi.org/10.1289/EHP12956.

Urbanicity and psychotic disorders: Facts and hypotheses

In the present qualitative literature review, we summarise data on psychotic disorders and urbanicity, focusing particularly on recent findings. Longitudinal studies of the impact of urbanicity on the risk for psychotic disorders have consistently shown a significant association, with a relative risk between 2 and 2.5. However, most of the original studies were conducted in Western Europe, and no incidence studies were conducted in low- and middle-income countries. European studies suggest that neighbourhood-level social fragmentation and social capital may partly explain this association. Exposure to air pollution (positive association) and green space (negative association) may also be part of the explanation, but to date, available data do not make it possible to conclude if they act independently from urbanicity, or as part of the effect of urbanicity on psychotic disorders. Finally, several studies have consistently shown significant associations between the polygenic risk score for schizophrenia and urbanicity, with several possible explanations (pleiotropic effects, results of prodromic symptoms, or selection/intergenerational hypothesis). Thus, more studies are needed to understand the factors that explain the association between urbanicity and the risk of psychotic disorders. Further studies should account for the interdependence and/or interactions of different psychosocial and physical exposures (as well as gene-environment interactions), and explore this association in low- and middle-income countries.

Research Reviews: Advances in methods for evaluating child and adolescent mental health interventions

BACKROUND

The evidence base for interventions for child mental health and neurodevelopment is weak and the current capacity for rigorous evaluation limited. We describe some of the challenges that make this field particularly difficult and expensive for evaluation studies.

METHODS

We describe and review the use of novel study designs and analysis methodology for their potential to improve this situation.

RESULTS

While several novel designs appeared ill-suited to our field, systematic review found others that offered potential but had yet to be widely adopted, some not at all.

CONCLUSIONS

While funding is inevitably a constraint, we argue that improvements in the evidence base of both current and new treatments will only be achieved by the adoption of a number of these new technologies and study designs, the consistent application of rigorous constructive but demanding standards, and the engagement of the public, patients, clinical and research services to build a design, recruitment, and analysis infrastructure.

Integrative genome-wide analyses identify novel loci associated with kidney stones and provide insights into its genetic architecture

Kidney stone disease (KSD) is a complex disorder with high heritability and prevalence. We performed a large genome-wide association study (GWAS) meta-analysis for KSD to date, including 720,199 individuals with 17,969 cases in European population. We identified 44 susceptibility loci, including 28 novel loci. Cell type-specific analysis pinpointed the proximal tubule as the most relevant cells where susceptibility variants might act through a tissue-specific fashion. By integrating kidney-specific omics data, we prioritized 223 genes which strengthened the importance of ion homeostasis, including calcium and magnesium in stone formation, and suggested potential target drugs for the treatment. The genitourinary and digestive diseases showed stronger genetic correlations with KSD. In this study, we generate an atlas of candidate genes, tissue and cell types involved in the formation of KSD. In addition, we provide potential drug targets for KSD treatment and insights into shared regulation with other diseases.

Thyroid Function and Metabolic Syndrome: A Two-Sample Bidirectional Mendelian Randomization Study

CONTEXT

Thyroid function has been associated with metabolic syndrome (MetS) in a number of observational studies but the direction of effects and the exact causal mechanism of this relationship is still unknown.

OBJECTIVE

To examine genetically predicted effects of thyroid function on MetS risk and its components, and vice versa, using large-scale summary genetic association data.

METHODS

We performed a two-sample bidirectional Mendelian randomization (MR) study using summary statistics from the most comprehensive genome-wide association studies (GWAS) of thyroid-stimulating hormone (TSH, n = 119 715), free thyroxine (fT4, n = 49 269), MetS (n = 291 107), and components of MetS: waist circumference (n = 462 166), fasting blood glucose (n = 281 416), hypertension (n = 463 010), triglycerides (TG, n = 441 016) and high-density lipoprotein cholesterol (HDL-C, n = 403 943). We chose the multiplicative random effects inverse variance weighted (IVW) method as the main analysis. Sensitivity analysis included weighted median and mode analysis, as well as MR-Egger and Causal Analysis Using Summary Effect estimates (CAUSE).

RESULTS

Our results suggest that higher fT4 levels lower the risk of developing MetS (OR = 0.96, P = .037). Genetically predicted fT4 was also positively associated with HDL-C (β = 0.02, P = .008), while genetically predicted TSH was positively associated with TG (β = 0.01, P = .044). These effects were consistent across different MR analyses and confirmed with the CAUSE analysis. In the reverse direction MR analysis, genetically predicted HDL-C was negatively associated with TSH (β = -0.03, P = .046) in the main IVW analysis.

CONCLUSION

Our study suggests that variations in normal-range thyroid function are causally associated with the diagnosis of MetS and with lipid profile, while in the reverse direction, HDL-C has a plausible causal effect on reference-range TSH levels.

Causal relationships between type 2 diabetes, glycemic traits and keratoconus

Purpose

The relationship between diabetes mellitus and keratoconus remains controversial. This study aimed to assess the potential causal relationships among type 2 diabetes, glycemic traits, and the risk of keratoconus.

Methods

We used a two-sample Mendelian randomization (MR) design based on genome-wide association summary statistics. Fasting glucose, proinsulin levels, adiponectin, hemoglobin A1c (HbA1c) and type 2 diabetes with and without body mass index (BMI) adjustment were used as exposures and keratoconus was used as the outcome. MR analysis was performed using the inverse-variance weighted method, MR-Egger regression method, weighted-mode method, weighted median method and the MR-pleiotropy residual sum and outlier test (PRESSO).

Results

Results showed that genetically predicted lower fasting glucose were significantly associated with a higher risk of keratoconus [IVW: odds ratio (OR) = 0.382; 95% confidence interval (CI) = 0.261-0.560; p = 8.162 × 10-7]. Genetically predicted lower proinsulin levels were potentially linked to a higher risk of keratoconus (IVW: OR = 0.739; 95% CI = 0.568-0.963; p = 0.025). In addition, genetically predicted type 2 diabetes negatively correlated with keratoconus (IVW: BMI-unadjusted: OR = 0.869; 95% CI = 0.775-0.974, p = 0.016; BMI-adjusted: OR = 0.880, 95% CI = 0.789-0.982, p = 0.022). These associations were further corroborated by the evidence from all sensitivity analyses.

Conclusion

These findings provide genetic evidence that higher fasting glucose levels are associated with a lower risk of keratoconus. However, further studies are required to confirmed this hypothesis and to understand the mechanisms underlying this putative causative relationship.

Fetal Exposure to Preeclampsia and Later Risk of Cardiometabolic Disorders: A Population-Based Cohort Study

BACKGROUND

Fetal preeclampsia exposure has been associated with later cardiometabolic disease. However, this association has been investigated in few large population-wide studies, and it is unknown whether the association represents a causal relationship or is the result of shared etiological factors.

METHODS

To further investigate the relationship between preeclampsia exposure and later cardiometabolic disease, we identified 1 692 944 singleton infants born in Norway during 1967 to 1997, where 44 299 were exposed to preeclampsia in utero. The individuals were followed for hypertension, diabetes, and dyslipidemia as defined by dispensed medication. We used Cox regression models to calculate the association between preeclampsia exposure and cardiometabolic outcomes adjusting for measured confounders. We also used full sibling comparisons and stratified Cox regression to control for unmeasured familial confounders.

RESULTS

On the population level, exposed individuals had increased risk of hypertension (adjusted hazard ratio [aHR] 1.51 [95% CI, 1.41-1.63]), diabetes (aHR 1.33 [95% CI, 1.24-1.43], and dyslipidemia (aHR 1.28 [95% CI, 1.13-1.45]) compared with unexposed individuals. In sibling data, individuals not exposed to preeclampsia, but with an exposed sibling, had higher risk of hypertension and diabetes than individuals where no siblings were exposed to preeclampsia. Moreover, when comparing siblings discordant on preeclampsia exposure, there were no associations between preeclampsia and hypertension (aHR 1.05 [95% CI, 0.88-1.26]), diabetes (aHR 0.96 [95% CI, 0.80-1.14]), and dyslipidemia (aHR 0.86 [95% CI, 0.62-1.20]).

CONCLUSIONS

Fetal preeclampsia exposure was associated with adult life hypertension, diabetes, and dyslipidemia, but these associations were likely due to shared etiological factors, rather than exposure to the preeclamptic condition itself.

Shared Genetic Risk in the Association of Screen Time With Psychiatric Problems in Children

Importance

Children's exposure to screen time has been associated with poor mental health outcomes, yet the role of genetic factors remains largely unknown.

Objective

To assess the extent of genetic confounding in the associations between screen time and attention problems or internalizing problems in preadolescent children.

Design, Setting, and Participants

This cohort study analyzed data obtained between 2016 and 2019 from the Adolescent Brain Cognitive Development Study at 21 sites in the US. The sample included children aged 9 to 11 years of genetically assigned European ancestry with self-reported screen time. Data were analyzed between November 2021 and September 2023.

Exposure

Child-reported daily screen time (in hours) was ascertained from questionnaires completed by the children at baseline.

Main Outcomes and Measures

Child psychiatric problems, specifically attention and internalizing problems, were measured with the parent-completed Achenbach Child Behavior Checklist at the 1-year follow-up. Genetic sensitivity analyses model (Gsens) was used, which incorporated polygenic risk scores (PRSs) of both exposure and outcomes as well as either single-nucleotide variant (SNV; formerly single-nucleotide polymorphism)-based heritability or twin-based heritability to estimate genetic confounding.

Results

The 4262 children in the sample included 2269 males (53.2%) with a mean (SD) age of 9.9 (0.6) years. Child screen time was associated with attention problems (β = 0.10 SD; 95% CI, 0.07-0.13 SD) and internalizing problems (β = 0.03 SD; 95% CI, 0.003-0.06 SD). The television time PRS was associated with child screen time (β = 0.18 SD; 95% CI, 0.14-0.23 SD), the attention-deficit/hyperactivity disorder PRS was associated with attention problems (β = 0.13 SD; 95% CI, 0.10-0.16 SD), and the depression PRS was associated with internalizing problems (β = 0.10 SD; 95% CI, 0.07-0.13 SD). These PRSs were associated with cross-traits, suggesting genetic confounding. Estimates using PRSs and SNV-based heritability showed that genetic confounding accounted for most of the association between child screen time and attention problems and for 42.7% of the association between child screen time and internalizing problems. When PRSs and twin-based heritability estimates were used, genetic confounding fully explained both associations.

Conclusions and Relevance

Results of this study suggest that genetic confounding may explain a substantial part of the associations between child screen time and psychiatric problems. Genetic confounding should be considered in sociobehavioral studies of modifiable factors for youth mental health.

New evidence for the effect of type 2 diabetes and glycemic traits on testosterone levels: a two-sample Mendelian randomization study

Objective

Type 2 diabetes mellitus (T2DM) is an endocrine-related disease with an increasing incidence worldwide. Male sexual dysfunction is common in diabetic patients. Therefore, we designed a Mendelian randomization (MR) study to investigate the association of type 2 diabetes and 3 glycemic traits with testosterone levels.

Methods

Uncorrelated single nucleotide polymorphisms (SNPs) associated with T2DM (N = 228), fasting insulin (N = 38), fasting glucose (N = 71), and HbA1c (N = 75) at the genome-wide significance were selected as instrument variables. Genetic associations with testosterone levels (total testosterone, TT, bioavailable testosterone, BT, and sex hormone-binding globulin, SHBG) were obtained from the UK Biobank studies and other large consortia. Two-sample MR analysis was used to minimize the bias caused by confounding factors and response causality. Multivariable MR analysis was performed using Body mass index (BMI), Triglycerides (TG), LDL cholesterol (LDL), and adiponectin to adjust for the effects of potential confounders.

Results

Type 2 diabetes mellitus was associated with the decrease of total testosterone (β: -0.021,95%CI: -0.032, -0.010, p<0.001) and sex hormone binding globulin (β: -0.048,95%CI: -0.065, -0.031, p<0.001). In males, total testosterone (β: 0.058, 95% CI: 0.088, 0.028, p < 0.001) decreased. In females, it was associated with an increase in bioavailable testosterone (β: 0.077,95%CI: 0.058,0.096, p<0.001). Each unit (pmol/L) increase in fasting insulin was associated with 0.283nmol/L decrease in sex hormone-binding globulin (95%CI: -0.464, -0.102, p=0.002) and 0.260nmol/L increase in bioavailable testosterone (95%CI: -0.464, -0.102, p= 0.002). In males, sex hormone binding globulin decreased by 0.507nmol/L (95%CI: -0.960, -0.054, p= 0.028) and bioavailable testosterone increased by 0.216nmol/L (95%CI: 0.087,0.344, p= 0.001). In females, sex hormone binding globulin decreased by 0.714 nmol/L (95%CI: -1.093, -0.335, p<0.001) and bioavailable testosterone increased by 0.467nmol/L (95%CI: 0.286,0.648, p<0.001). Each unit (%) increase in HbA1c was associated with 0.060nmol/L decrease in sex hormone-binding globulin (95%CI: -0.113, -0.007, p= 0.026). In males, total testosterone decreased by 0.171nmol/L (95%CI: -0.288, -0.053, p=0.005) and sex hormone binding globulin decreased by 0.206nmol/L (95%CI: -0.340, -0.072, p=0.003). Total testosterone increased by 0.122nmol/L (95%CI: 0.012,0.233, p=0.029) and bioavailable testosterone increased by 0.163nmol/L (95%CI: 0.042,0.285, p=0.008) in females.

Conclusions

Using MR Analysis, we found independent effects of type 2 diabetes, fasting insulin, and HbA1c on total testosterone and sex hormone-binding globulin after maximum exclusion of the effects of obesity, BMI, TG, LDL and Adiponectin.

Well-being spectrum traits are associated with polygenic scores for autism

Individuals with autism spectrum disorder (ASD) tend to experience lower well-being as demonstrated mostly for children and adolescents in epidemiological studies. A further investigation of inclusive well-being, in terms of five well-being spectrum (5-WBS) traits including neuroticism, depression, loneliness, life satisfaction, and positive affect, among adults with ASD may deepen our understanding of their well-being, and lead to the possibility to further modify societal supportive mechanisms for individuals with ASD. This study aims to investigate if a genetic predisposition for ASD is associated with 5-WBS traits using polygenic risk score (PRS) analysis. PRS for ASD were calculated based on the latest genome-wide association study of ASD by the Psychiatric Genetics Consortium (18,381 cases, 27,969 controls) and were created in the independent cohort UK Biobank. Regression analyses were performed to investigate the association between ASD PRS and 5-WBS traits in the UK Biobank population including 337,423 individuals. ASD PRS were significantly associated with all 5-WBS traits, showing a positive association with the negative WBS traits, neuroticism (max R2  = 0.04%, p < 1 × 10-4 ), depression (max R2  = 0.06%, p < 1 × 10-4 ), loneliness (max R2  = 0.04%, p < 1 × 10-4 ), and a negative association with the positive WBS traits, life satisfaction (max R2  = 0.08%, p < 1 × 10-4 ), positive affect (max R2  = 0.10%, p < 1 × 10-4 ). The findings suggest that adults carrying a high load of risk single nucleotide peptides (SNPs) for ASD are more likely to report decreased well-being. The study demonstrates a considerable connection between susceptibility to ASD, its underlying genetic etiology and well-being.

The providential randomisation of genotypes

When building causal knowledge in behavioural genetics, the natural randomisation of genotypes at conception (approximately analogous to the artificial randomisation occurring in randomised controlled trials) facilitates the discovery of genetic causes. More importantly, the randomisation of genetic material within families also enables a better identification of (environmental) risk factors and aetiological pathways to diseases and behaviours.

Allergic Rhinitis and Cancer Risk: A Two-Sample Mendelian Randomization Study

Background: There is increasing evidence that allergic rhinitis (AR) is associated with cancer. However, these results are inconsistent. Because of common risk factors, there may be reverse causality and confounding factors that affect our understanding of the relationship between AR and cancer. We aimed to explore the role of AR in cancer development using Mendelian randomization (MR) analysis. Materials and Methods: We performed a two-sample MR analysis using summary data from genome-wide association studies (GWAS). Single nucleotide polymorphisms (SNPs) strongly associated with AR (or hay fever) were used as instrumental variables, mainly using the inverse variance weighted analysis method, supplemented by MR Egger, maximum likelihood, weighted media, and penalized weighted media for MR analysis. Sensitivity analyses included heterogeneity and horizontal pleiotropy; and leave-one-out analyses were performed to test the robustness of our results. Results: MR analysis revealed no evidence of a causal relationship between AR and any of the examined cancers (all p > 0.05). The results using five different analytical approaches were similar. Sensitivity analyses showed no evidence of heterogeneity nor horizontal pleiotropy. According to the leave-one-out sensitivity analyses, no individual SNP was significantly influencing the causal effect of AR on cancers. Conclusions: These findings do not provide evidence to support that AR has a large impact on the risk of eight common cancers in the European population. However, we cannot rule out a very minor effect of AR on cancer. Further large-scale studies are necessary to validate our findings.

Amyotrophic lateral sclerosis: translating genetic discoveries into therapies

Recent advances in sequencing technologies and collaborative efforts have led to substantial progress in identifying the genetic causes of amyotrophic lateral sclerosis (ALS). This momentum has, in turn, fostered the development of putative molecular therapies. In this Review, we outline the current genetic knowledge, emphasizing recent discoveries and emerging concepts such as the implication of distinct types of mutation, variability in mutated genes in diverse genetic ancestries and gene-environment interactions. We also propose a high-level model to synthesize the interdependent effects of genetics, environmental and lifestyle factors, and ageing into a unified theory of ALS. Furthermore, we summarize the current status of therapies developed on the basis of genetic knowledge established for ALS over the past 30 years, and we discuss how developing treatments for ALS will advance our understanding of targeting other neurological diseases.

Early risk factors for joint trajectories of bullying victimisation and perpetration

Bullying victimisation is a prevalent stressor associated with serious health problems. To inform intervention strategies, it is important to understand children's patterns of involvement in bullying victimisation and perpetration across development, and identify early risk factors for these developmental trajectories. We analysed data from the Millennium Cohort Study (N = 14,525; 48.6% female, 82.6% White), a representative birth cohort of British children born in 2000-2002 across the UK. Bullying victimisation and perpetration were assessed via child, mother, and teacher reports at ages 5, 7, 11, and 14 years. Early risk factors (child emotional, cognitive, and physical vulnerabilities, and adverse family environments) were assessed at ages 9 months, 3, and 5 years. Using k-means for longitudinal data, we identified five joint trajectories of victimisation and perpetration across ages 5, 7, 11, and 14: uninvolved children (59.78%), early child victims (9.96%), early adolescent victims (15.07%), early child bullies (8.01%), and bully- victims (7.19%). Individual vulnerabilities (e.g., emotional dysregulation, cognitive difficulties) and adverse family environments (maternal psychopathology, low income) in pre-school years independently forecast multiple trajectories of bullying involvement. Compared to victims, bully-victims were more likely to be male, have cognitive difficulties, and experience harsh discipline and low income. Interventions addressing these risk factors (e.g., via accessible mental health care, stigma-based interventions, or programs to support low-income families) may help to prevent bullying involvement and its associated sequelae.

Minimal effect of sleep on the risk of age-related macular degeneration: a Mendelian randomization study

Aims

Observational studies have shown that sleep pattern is associated with age-related macular degeneration (AMD), but whether sleep pattern is a causal factor for AMD remains unclear. This study aims to use Mendelian randomization (MR) analysis to investigate the potential causal relationship between sleep traits and AMD.

Methods

This is a two-sample MR study. The single-nucleotide polymorphisms associated with AMD and early AMD were selected as the outcome from two different genome-wide association studies (GWAS): the early AMD GWAS with 14,034 cases and 91,214 controls, and AMD GWAS with 3,553 cases and 147,089 controls. The datasets of sleep duration, daytime dozing, and sleeplessness were used as exposure, which comprised nearly 0.46 million participants. Inverse-variance weighted method was used as the main result, and comprehensive sensitivity analyses were conducted to estimate the robustness of identified associations and the impact of potential horizontal pleiotropy.

Results

Through MR analysis, we found that sleep duration was significantly associated with AMD (OR = 0.983, 95% CI = 0.970-0.996, P-value = 0.01). We also found suggestive evidence for the association of genetically predicted sleep duration with early AMD, which showed a consistent direction of effect with a marginal significance (OR = 0.724, 95% CI = 0.503-1.041, P-value = 0.08). Sensitivity analyses further supported the robustness of the causal relationship between sleep duration and AMD. However, we were unable to determine the relationship between daytime dozing or sleeplessness and AMD (including early AMD) (P-value > 0.05).

Conclusion

Sleep duration affects the causal risk for AMD; that is, longer sleep duration reduces the risk of AMD, while shorter sleep duration increases the risk of AMD. Although the influence is minimal, keeping adequate sleep duration is recommended, especially for patients with intermediate or advanced AMD.

Stressful life events increase the risk of major depressive episodes: A population-based twin study

BACKGROUND

Previous studies have found that stressful life events (SLEs) are associated with an increased risk of adult depression. However, many studies are observational in nature and limited by methodological issues, such as potential confounding by genetic factors. Genetically informative research, such as the co-twin control design, can strengthen causal inference in observational studies. Discrete-time survival analysis has several benefits and multilevel survival analysis can incorporate frailty terms (random effects) to estimate the components of the biometric model. In the current study, we investigated associations between SLEs and depression risk in a population-based twin sample (N = 2299).

METHODS

A co-twin control design was used to investigate the influence of the occurrence of SLEs on depression risk. The co-twin control design involves comparing patterns of associations in the full sample and within dizygotic (DZ) and monozygotic twins (MZ). Associations were modelled using discrete-time survival analysis with biometric frailty terms. Data from two time points were used in the analyses. Mean age at Wave 1 was 28 years and mean age at Wave 2 was 38 years.

RESULTS

SLE occurrence was associated with increased depression risk. Co-twin control analyses indicated that this association was at least in part due to the causal influence of SLE exposure on depression risk for event occurrence across all SLEs and for violent SLEs. A minor proportion of the total genetic risk of depression reflected genetic effects related to SLEs.

CONCLUSIONS

The results support previous research in implicating SLEs as important risk factors with probable causal influence on depression risk.