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.

Identification and validation of core genes associated with intracranial aneurysms through bioinformatics analysis and Mendelian randomization

Intracranial aneurysms (IAs) often go undetected until rupture, leading to significant morbidity and mortality. Identifying biomarkers for early detection of IAs is crucial. The current study attempted to identify core genes linked with IAs and determine their relevance through Mendelian randomization. Limma helped identify differentially expressed genes between IAs and control superficial temporal artery samples. WGCNA was utilized to find IA-related modules and associated genes, which were further evaluated using KEGG and GO analyses to ascertain their potential roles. Five highly associated genes were screened with the CytoHubba plugin of Cytoscape software. ROC curves assessed the diagnostic efficacy of these genes. A two-sample Mendelian randomization evaluated the causal relationship between the core gene PTRPC and IAs, along with its correlation with immune infiltration. WGCNA and differential expression analysis depicted 584 related genes involved in cellular metabolism and chemokine activity. PTPRC was among the top highly associated genes identified through Cytoscape. It showed significant diagnostic value for IAs. Moreover, mendelian randomization depicted that PTPRC in CD4+ T cells is related to IA risk, with an OR of 0.63538 (95 % CI = 0.41636-0.96959, p = 0.03545). No reverse causal relationship was observed between PTPRC and IAs, with an OR of 0.99947 (95 % CI = 0.99719-1.00176, p = 0.65022). Additionally, immune cell infiltration results indicated a positive correlation between PTPRC in IAs with neutrophils and unactivated dendritic cells and a negative association with regulatory T cells (Tregs). PTPRC was identified as a core gene linked with IAs, providing evidence for IA diagnosis and studying molecular mechanisms.

Characterizing the momentary association between loneliness, depression, and social interactions: Insights from an ecological momentary assessment study

Evidence suggests that loneliness causes people to feel more depressed. It is unknown, however, why this association occurs and whether momentary versus chronic experiences of loneliness are implicated. Theoretical accounts suggest that momentary feelings of loneliness produce two competing motivations: social reaffiliation and social withdrawal. Social affiliation is protective against depression; social withdrawal, in contrast, is a risk factor. Thus, engaging in frequent and high-quality interactions following experiences of loneliness may protect against subsequent depression. We tested this hypothesis using a random-interval experience sampling design (5x/day/day, 14 days; Nobs = 6568) with a racially/ethnically diverse sample of adults with elevated depression symptoms (N = 102). Momentary loneliness was associated with depressed mood at the same time point and ∼2.5h and ∼5h later. Frequency and quality of social interaction did not moderate these associations. Findings suggest that momentary feelings of loneliness may be an important target for clinical intervention.

Causal relationship between neuroticism and frailty: A bidirectional Mendelian randomization study

BACKGROUND

Observational studies have shown that neuroticism is associated with frailty, but the causal relationship between them remains unclear.

METHODS

A two-sample Mendelian randomization (MR) study was conducted to explore the bidirectional causal relationship between neuroticism (n = 380,506 for the primary analysis, n = 79,004 for the validation) and frailty (n = 175,226) using publicly available genome-wide association study data. The inverse variance weighted (IVW), weighted median, and MR-Egger were used to obtain the causal estimates. Findings were verified through extensive sensitivity analyses and validated using another dataset. Multivariable MR (MVMR) analysis was performed to estimate the direct causal effects with adjustment of potential confounders. Two-step MR technique was then conducted to explore the mediators in the causal effects of neuroticism on frailty.

RESULTS

Genetically-predicted higher neuroticism score was significantly correlated with higher frailty index (IVW beta: 0.53, 95%CI: 0.48 to 0.59, P = 9.3E-83), and genetically-determined higher frailty index was significantly associated with higher neuroticism score (IVW beta: 0.28, 95%CI: 0.21 to 0.35, P = 1.3E-16). These results remained robust across sensitivity analyses and were reproducible using another dataset. The MVMR analysis indicated that the causal relationships remained significant after adjusting for the potential confounding factors. Mediation analysis revealed that depression, years of schooling, and smoking were significantly mediated the causal effects of neuroticism on frailty.

CONCLUSIONS

A bidirectional causal relationship existed between neuroticism and frailty. Our findings suggested that early intervention and behavioral changes might be helpful to reduce the neuroticism levels and prevent the development of frailty.

Mendelian randomization study of lipid metabolism characteristics and migraine risk

BACKGROUND

The association between serum lipids and migraine is controversial. However, randomized controlled trials have suggested that statins may be efficacious for the prevention of migraine. In this study, we aim to investigate the relationship between lipids metabolism and migraine risk.

METHODS

Single-nucleotide polymorphisms (SNPs), relating to the serum lipid traits and the effect of lipid-lowering drugs that target APOB, CETP, HMGCR, NPC1L1, and PCSK9, were extracted from genome-wide association studies (GWAS) summary data. The GWAS summary data were obtained from the Global Lipids Genetic Consortium (GLGC), the UK Biobank, and the FinnGen study, respectively. Mendelian randomization (MR) analysis was performed to evaluate the association between serum lipid traits and lipid-lowering drugs with migraine risk.

RESULTS

Regarding serum lipids, it was found that SNPs related to high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), non-high-density lipoprotein cholesterol (non-HDL-C), total cholesterol (TC), or triglycerides (TG) levels were not associated with migraine, migraine with aura (MA) or migraine without aura (MO). In addition, genotypes of HMGCR related to higher LDL-C levels were associated with increased risk of migraine (OR = 1.46, p = 0.035) and MA (OR = 2.03, p = 0.008); However, genotypes of PCSK9 related to higher LDL-C levels were associated with decreased risk of migraine (OR = 0.75, p = 0.001) and MA (OR = 0.69, p = 0.004); And genotypes of APOB related to higher LDL-C levels were associated with decreased risk of MO (OR = 0.62, p = 0.000).

CONCLUSIONS

There is a relationship between lipid metabolism characteristics and migraine risk.

SIGNIFICANCE

Based on the genome-wide association summary data, single-nucleotide polymorphisms (SNPs) related to high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), non-high-density lipoprotein cholesterol (non-HDL-C), total cholesterol (TC), or triglycerides (TG) level were not associated with risk of migraine, migraine with aura (MA) or migraine without aura (MO). However, genotypes of HMGCR related to higher LDL-C levels have shown an increased risk on migraine and MA. And genotypes of APOB or PCSK9 related to higher LDL-C levels have shown a decreased risk on MO, or migraine and MA, respectively. These results suggested that there may be a relationship between lipid metabolism characteristics and the risk for migraine development.

Use of Mendelian randomization to assess the causal status of modifiable exposures for rheumatic diseases

The explosion in Mendelian randomization (MR) publications is hard to ignore and shows no signs of slowing. Clinician readers, who may not be familiar with jargon-ridden methods, are expected to discern the good from the many low-quality studies that make overconfident claims of causality or stretch the plausibility of what MR can investigate. We aim to equip readers with foundational concepts, contextualized using examples in rheumatology, to appraise the many MR papers that are or will appear in their journals. We highlight the importance of assessing whether exposures are under plausibly specific genetic influence, whether the hypothesized causal pathways make biological sense, and whether results stand up to replication and use of control outcomes. Quality of research can vary substantially using MR as with any design, and all methods have inherent limitations. MR studies have provided and can still contribute valuable insights in the context of evidence triangulation.

The impact of educational attainment on mental health: A Causal Assessment from the UKB and FinnGen Cohorts

Observational studies report inverse associations between educational attainment and depression/anxiety risks, but confounding hinders causal inference. This study aimed to assess potential causal relationships using Mendelian randomization (MR). Two-sample MR analysis was conducted using genetic instruments for education, smoking, body mass index, and physical activity from published genome-wide association studies. Depression and anxiety data came from the UK Biobank ([UKB] 117,782 individuals) and FinnGen (215,644 individuals) cohorts. Inverse variance weighted regression determined associations between exposures and mental health outcomes. Increased educational attainment was causally associated with reduced risks of depression (odds ratio [OR] = 0.99 per year, 95% confidence interval [CI]: 0.990-0.996, P < .001) and anxiety (OR = 0.99, CI: 0.98-0.991, P < .001) in both cohorts. Smoking initiation conferred higher risks of depression (UKB OR = 1.05, CI: 1.03-1.06, P < .001; FinnGen OR = 1.20, CI: 1.10-1.32, P < .001) and anxiety (FinnGen only, OR = 1.10, CI: 1.01-1.21, P < .05). Likewise, maternal smoking history associated with greater depression (UKB OR = 1.15, CI: 1.10-1.35, P = .027) and anxiety susceptibility (FinnGen OR = 3.02, CI: 1.67-5.46, P = .011). Higher body mass index elevated depression risk in both cohorts. Physical activity showed no clear associations. This MR study provides evidence that education may causally reduce mental health disorder risk. Smoking, obesity, and low activity appear detrimentally linked to depression and anxiety. Improving access to education could offer effective strategies for lowering population psychiatric burden.

The genetic architecture of biological age in nine human organ systems

Investigating the genetic underpinnings of human aging is essential for unraveling the etiology of and developing actionable therapies for chronic diseases. Here, we characterize the genetic architecture of the biological age gap (BAG; the difference between machine learning-predicted age and chronological age) across nine human organ systems in 377,028 participants of European ancestry from the UK Biobank. The BAGs were computed using cross-validated support vector machines, incorporating imaging, physical traits and physiological measures. We identify 393 genomic loci-BAG pairs (P < 5 × 10-8) linked to the brain, eye, cardiovascular, hepatic, immune, metabolic, musculoskeletal, pulmonary and renal systems. Genetic variants associated with the nine BAGs are predominantly specific to the respective organ system (organ specificity) while exerting pleiotropic links with other organ systems (interorgan cross-talk). We find that genetic correlation between the nine BAGs mirrors their phenotypic correlation. Further, a multiorgan causal network established from two-sample Mendelian randomization and latent causal variance models revealed potential causality between chronic diseases (for example, Alzheimer's disease and diabetes), modifiable lifestyle factors (for example, sleep duration and body weight) and multiple BAGs. Our results illustrate the potential for improving human organ health via a multiorgan network, including lifestyle interventions and drug repurposing strategies.

Deciphering the lipid-cancer nexus: comprehensive Mendelian randomization analysis of the associations between lipid profiles and digestive system cancer susceptibility

BACKGROUND

Digestive system cancers represent a significant global health challenge and are attributed to a combination of demographic and lifestyle changes. Lipidomics has emerged as a pivotal area in cancer research, suggesting that alterations in lipid metabolism are closely linked to cancer development. However, the causal relationship between specific lipid profiles and digestive system cancer risk remains unclear.

METHODS

Using a two-sample Mendelian randomization (MR) approach, we elucidated the causal relationships between lipidomic profiles and the risk of five types of digestive system cancer: stomach, liver, esophageal, pancreatic, and colorectal cancers. The aim of this study was to investigate the effect impact of developing lipid profiles on the risk of digestive system cancers utilizing data from public databases such as the GWAS Catalog and the UK Biobank. The inverse‒variance weighted (IVW) method and other strict MR methods were used to evaluate the potential causal links. In addition, we performed sensitivity analyses and reverse MR analyses to ensure the robustness of the results.

RESULTS

Significant causal relationships were identified between certain lipidomic traits and the risk of developing digestive system cancers. Elevated sphingomyelin (d40:1) levels were associated with a reduced risk of developing gastric cancer (odds ratio (OR) = 0.68, P < 0.001), while elevated levels of phosphatidylcholine (16:1_20:4) increased the risk of developing esophageal cancer (OR = 1.31, P = 0.02). Conversely, phosphatidylcholine (18:2_0:0) had a protective effect against colorectal cancer (OR = 0.86, P = 0.036). The bidirectional analysis did not suggest reverse causality between cancer risk and lipid levels. Strict MR methods demonstrated the robustness of the above causal relationships.

CONCLUSION

Our findings underscore the significant causal relationships between specific lipidomic traits and the risk of developing various digestive system cancers, highlighting the potential of lipid profiles in informing cancer prevention and treatment strategies. These results reinforce the value of MR in unraveling complex lipid-cancer interactions, offering new avenues for research and clinical application.

The impact of telomere length on the risk of idiopathic normal pressure hydrocephalus: a bidirectional Mendelian randomization study

Idiopathic normal pressure hydrocephalus (iNPH) affects mainly aged populations. The gradual shortening of telomere length (TL) is one of the hallmarks of aging. Whereas the genetic contribution of TL to the iNPH is incompletely understood. We aimed to investigate the causal relationship between TL and iNPH through the Mendelian randomization (MR) analysis. We respectively obtained 186 qualified single nucleotide polymorphisms (SNPs) of TL and 20 eligible SNPs of iNPH for MR analysis. The result of MR analysis showed that genetically predicted longer TL was significantly associated with a reduced odd of iNPH (odds ratio [OR] = 0.634 95% Confidence interval [CI] 0.447-0.899, p = 0.011). The causal association remained consistent in multivariable MR (OR = 0.530 95% CI 0.327-0.860, p = 0.010). However, there was no evidence that the iNPH was causally associated with the TL (OR = 1.000 95% CI 0.996-1.004, p = 0.955). Our study reveals a potential genetic contribution of TL to the etiology of iNPH, that is a genetically predicted increased TL might be associated with a reduced risk of iNPH.

Do iron homeostasis biomarkers mediate the associations of liability to type 2 diabetes and glycemic traits in liver steatosis and cirrhosis: a two-step Mendelian randomization study

BACKGROUND

Previous studies, including Mendelian randomization (MR), have demonstrated type 2 diabetes (T2D) and glycemic traits are associated with increased risk of metabolic dysfunction-associated steatotic liver disease (MASLD). However, few studies have explored the underlying pathway, such as the role of iron homeostasis.

METHODS

We used a two-step MR approach to investigate the associations of genetic liability to T2D, glycemic traits, iron biomarkers, and liver diseases. We analyzed summary statistics from various genome-wide association studies of T2D (n = 933,970), glycemic traits (n ≤ 209,605), iron biomarkers (n ≤ 246,139), MASLD (n ≤ 972,707), and related biomarkers (alanine aminotransferase (ALT) and proton density fat fraction (PDFF)). Our primary analysis was based on inverse-variance weighting, followed by several sensitivity analyses. We also conducted mediation analyses and explored the role of liver iron in post hoc analysis.

RESULTS

Genetic liability to T2D and elevated fasting insulin (FI) likely increased risk of liver steatosis (ORliability to T2D: 1.14 per doubling in the prevalence, 95% CI: 1.10, 1.19; ORFI: 3.31 per log pmol/l, 95% CI: 1.92, 5.72) and related biomarkers. Liability to T2D also likely increased the risk of developing liver cirrhosis. Genetically elevated ferritin, serum iron, and liver iron were associated with higher risk of liver steatosis (ORferritin: 1.25 per SD, 95% CI 1.07, 1.46; ORliver iron: 1.15 per SD, 95% CI: 1.05, 1.26) and liver cirrhosis (ORserum iron: 1.31, 95% CI: 1.06, 1.63; ORliver iron: 1.34, 95% CI: 1.07, 1.68). Ferritin partially mediated the association between FI and liver steatosis (proportion mediated: 7%, 95% CI: 2-12%).

CONCLUSIONS

Our study provides credible evidence on the causal role of T2D and elevated insulin in liver steatosis and cirrhosis risk and indicates ferritin may play a mediating role in this association.

COVID-19 susceptibility, hospitalization and severity and the risk of brain cortical structure: a Mendelian randomization study

BACKGROUND

Observational studies have reported structural changes in the brains of patients with coronavirus disease 2019 (COVID-19); it remains unclear whether these associations are causal.

AIM

We evaluated the causal effects of COVID-19 susceptibility, hospitalization and severity on cortical structures.

DESIGN

Mendelian randomization (MR) study.

METHODS

Data on the different COVID-19 phenotypes were obtained from the latest large-scale genome-wide association study (R7) of the COVID-19 Host Genetics Initiative. Brain structure data, including cortical thickness (TH) and surface area (SA), were obtained from the ENIGMA Consortium. Additionally, we employed the round 5 dataset released in January 2021 as the validation cohort. The inverse-variance weighted (IVW) method was used as the primary analysis in MR. Sensitivity analyses were conducted to evaluate heterogeneity and pleiotropy. We performed enrichment analysis on the MR analyses that passed the sensitivity analysis filtering.

RESULTS

After IVW and sensitivity analyses, we observed causal associations between COVID-19 susceptibility and rostral middle frontal SAw (P = 0.0308, β = -39.1236), cuneus THw (P = 0.0170, β = -0.0121), medial orbitofrontal THw (P = 0.0002, β = 0.0225), postcentral THw (P = 0.0217, β = -0.0106), temporal pole THw (P = 0.0077, β = 0.0359), medial orbitofrontal SAnw (P = 0.0106, β = -24.0397), medial orbitofrontal THnw (P = 0.0007, β = 0.0232), paracentral SAnw (P = 0.0483, β = -20.1442), rostral middle frontal SAnw (P = 0.0368, β = -81.9719) and temporal pole THnw (P = 0.0429, β = 0.0353). COVID-19 hospitalization had causal effects on medial orbitofrontal THw (P = 0.0053, β = 0.0063), postcentral THw (P = 0.0143, β = -0.0042), entorhinal THnw (P = 0.0142, β = 0.0142), medial orbitofrontal THnw (P = 0.0147, β = 0.0065) and paracentral SAnw (P = 0.0119, β = -7.9970). COVID-19 severity had causal effects on rostral middle frontal SAw (P = 0.0122, β = -11.8296), medial orbitofrontal THw (P = 0.0155, β = 0.0038), superior parietal THw (P = 0.0291, β = -0.0021), lingual SAnw (P = 0.0202, β = -11.5270), medial orbitofrontal THnw (P = 0.0290, β = 0.0039), paracentral SAnw (P = 0.0180, β = -5.7744) and pars triangularis SAnw (P = 0.0151, β = -5.4520).

CONCLUSION

Our MR results demonstrate a causal relationship between different COVID-19 phenotypes and cortical structures.

The Impact of Blood and Urine Biomarkers on Age-Related Macular Degeneration: Insights from Mendelian Randomization and Cross-sectional Study from NHANES

INTRODUCTION

Age-related macular degeneration (AMD) is a leading cause of blindness, affecting millions worldwide. Its complex pathogenesis involves a variety of risk factors, including lipid metabolism and inflammation. This study aims to elucidate the causal relationships between biomarkers related to these processes and AMD, leveraging Mendelian randomization (MR) and cross-sectional analysis from the National Health and Nutrition Examination Survey (NHANES).

METHOD

We conducted a two-phase study, initially using MR to explore the causality between 35 biomarkers and various AMD subtypes, followed by observational analysis with NHANES data to validate these findings.

RESULTS

MR analysis identified a protective role of TG and a risk factor role of HDL-C and CRP in AMD development. NHANES data corroborated these findings, highlighting a nuanced relationship between these biomarkers and AMD. Notably, lipid metabolism-related biomarkers showed stronger associations with early AMD, whereas CRP's significance was pronounced in late AMD.

CONCLUSION

This comprehensive analysis, combining MR with NHANES data, reinforces the importance of lipid metabolism and inflammation in AMD's etiology. Future research should further investigate these biomarkers' mechanisms and their potential as therapeutic targets for AMD prevention and treatment.

Prediction of causal genes at GWAS loci with pleiotropic gene regulatory effects using sets of correlated instrumental variables

Multivariate Mendelian randomization (MVMR) is a statistical technique that uses sets of genetic instruments to estimate the direct causal effects of multiple exposures on an outcome of interest. At genomic loci with pleiotropic gene regulatory effects, that is, loci where the same genetic variants are associated to multiple nearby genes, MVMR can potentially be used to predict candidate causal genes. However, consensus in the field dictates that the genetic instruments in MVMR must be independent, which is usually not possible when considering a group of candidate genes from the same locus. We used causal inference theory to show that MVMR with correlated instruments satisfies the instrumental set condition. This is a classical result by Brito and Pearl (2002) for structural equation models that guarantees the identifiability of causal effects in situations where multiple exposures collectively, but not individually, separate a set of instrumental variables from an outcome variable. Extensive simulations confirmed the validity and usefulness of these theoretical results even at modest sample sizes. Importantly, the causal effect estimates remain unbiased and their variance small when instruments are highly correlated. We applied MVMR with correlated instrumental variable sets at risk loci from genome-wide association studies (GWAS) for coronary artery disease using eQTL data from the STARNET study. Our method predicts causal genes at twelve loci, each associated with multiple colocated genes in multiple tissues. However, the extensive degree of regulatory pleiotropy across tissues and the limited number of causal variants in each locus still require that MVMR is run on a tissue-by-tissue basis, and testing all gene-tissue pairs at a given locus in a single model to predict causal gene-tissue combinations remains infeasible.

The causal relationship and potential mediators between plasma lipids and atopic dermatitis: a bidirectional two-sample, two-step mendelian randomization

BACKGROUND

Observational studies have indicated that the plasma lipid profiles of patients with atopic dermatitis show significant differences compared to healthy individuals. However, the causal relationship between these differences remains unclear due to the inherent limitations of observational studies. Our objective was to explore the causal effects between 179 plasma lipid species and atopic dermatitis, and to investigate whether circulating inflammatory proteins serve as mediators in this causal pathway.

METHODS

We utilized public genome-wide association studies data to perform a bidirectional two-sample, two-step mendelian randomization study. The inverse variance-weighted method was adopted as the primary analysis technique. MR-Egger and the weighted median were used as supplementary analysis methods. MR-PRESSO, Cochran's Q test, and MR-Egger intercept test were applied for sensitivity analyses to ensure the robustness of our findings.

RESULTS

The Mendelian randomization analysis revealed that levels of Phosphatidylcholine (PC) (18:1_20:4) (OR: 0.950, 95% CI: 0.929-0.972, p = 6.65 × 10- 6), Phosphatidylethanolamine (O-18:1_20:4) (OR: 0.938, 95% CI: 0.906-0.971, p = 2.79 × 10- 4), Triacylglycerol (TAG) (56:6) (OR: 0.937, 95% CI: 0.906-0.969, p = 1.48 × 10- 4) and TAG (56:8) (OR: 0.918, 95% CI: 0.876-0.961, p = 2.72 × 10- 4) were inversely correlated with the risk of atopic dermatitis. Conversely, PC (18:1_20:2) (OR: 1.053, 95% CI: 1.028-1.079, p = 2.11 × 10- 5) and PC (O-18:1_20:3) (OR: 1.086, 95% CI: 1.039-1.135, p = 2.47 × 10- 4) were positively correlated with the risk of atopic dermatitis. The results of the reverse directional Mendelian randomization analysis indicated that atopic dermatitis exerted no significant causal influence on 179 plasma lipid species. The level of circulating IL-18R1 was identified as a mediator for the increased risk of atopic dermatitis associated with higher levels of PC (18:1_20:2), accounting for a mediation proportion of 9.07%.

CONCLUSION

Our research suggests that plasma lipids can affect circulating inflammatory proteins and may serve as one of the pathogenic factors for atopic dermatitis. Targeting plasma lipid levels as a treatment for atopic dermatitis presents a potentially novel approach.

Exploring the Bidirectional Causal Pathways Between Smoking Behaviors and Headache: A Mendelian Randomization Study

INTRODUCTION

Although observational data suggest a relationship between headache and smoking, there remain questions about causality. Smoking may increase headache risk, individuals may smoke to alleviate headaches, or smoking and headache may share common risk factors. Mendelian randomization (MR) is a method that uses genetic variants as instruments for making causal inferences about an exposure and an outcome.

AIMS AND METHODS

First, we conducted logistic regression of observational data in UK Biobank assessing the association between smoking behaviors (smoking status, cigarettes per day amongst daily smokers, and lifetime smoking score) on the risk of self-reported headache (in the last month and for more than 3 months). Second, we used genetic instruments for smoking behaviors and headache (identified in independent genome-wide association studies [GWAS]) to perform bidirectional MR analysis.

RESULTS

Observationally, there is a weak association between smoking behavior and experiencing headache, with increased cigarettes per day associated with increased headache risk. In the MR analysis, genetic liability to smoking initiation and lifetime smoking increased odds of headache in the last month but not odds of headaches lasting more than 3 months. In the opposite direction, there was weak evidence for higher genetic liability to headaches decreasing the chance of quitting.

CONCLUSIONS

There was weak evidence for a partially bidirectional causal relationship between smoking behaviors and headache in the last month. Given this relationship is distinct from smoking heaviness, it suggests headache and smoking may share common risk factors such as personality traits.

IMPLICATIONS

Using MR, this study addresses the uncertainty regarding the observed relationship between headache and smoking. There was evidence for weak causal effects of smoking initiation and lifetime smoking (but not smoking heaviness) on likelihood of experiencing headache in the last month, but not over a prolonged period of more than 3 months. Those with higher genetic liability to headaches were also less likely to successfully stop smoking. This partially bidirectional causal relationship distinct from smoking heaviness suggests that observed associations are unlikely due to biological effects of tobacco smoke exposure and may be explained by shared personality traits.

Serum vitamin D, blood pressure and hypertension risk in the HUNT study using observational and Mendelian randomization approaches

Limited studies have triangulated the relationship between serum 25-hydroxyvitamin D [25(OH)D] levels and systolic blood pressure (SBP), diastolic blood pressure (DBP) or hypertension risk utilizing both observational and Mendelian randomization (MR) approaches. We employed data from the Norwegian Trøndelag Health Study (HUNT) to conduct cross-sectional (n = 5854) and prospective (n = 3592) analyses, as well as one-sample MR (n = 86,324). We also used largest publicly available data for two-sample MR. Our cross-sectional analyses showed a 25 nmol/L increase in 25(OH)D was associated with a 1.73 mmHg decrease in SBP (95% CI - 2.46 to - 1.01), a 0.91 mmHg decrease in DBP (95% CI - 1.35 to - 0.47) and 19% lower prevalence of hypertension (OR 0.81, 95% CI 0.74 to 0.90) after adjusting for important confounders. However, these associations disappeared in prospective analyses. One-sample and two-sample MR results further suggested no causal relationship between serum vitamin D levels and blood pressure or hypertension risk in the general population.

Major Psychiatric Disorders, Substance Use Behaviors, and Longevity

Importance

Observational studies suggest that major psychiatric disorders and substance use behaviors reduce longevity, making it difficult to disentangle their relationships with aging-related outcomes.

Objective

To evaluate the associations between the genetic liabilities for major psychiatric disorders, substance use behaviors (smoking and alcohol consumption), and longevity.

Design, Settings, and Participants

This 2-sample mendelian randomization (MR) study assessed associations between psychiatric disorders, substance use behaviors, and longevity using single-variable and multivariable models. Multiomics analyses were performed elucidating transcriptomic underpinnings of the MR associations and identifying potential proteomic therapeutic targets. This study sourced summary-level genome-wide association study (GWAS) data, gene expression, and proteomic data from cohorts of European ancestry. Analyses were performed from May 2022 to November 2023.

Exposures

Genetic susceptibility for major depression (n = 500 199), bipolar disorder (n = 413 466), schizophrenia (n = 127 906), problematic alcohol use (n = 435 563), weekly alcohol consumption (n = 666 978), and lifetime smoking index (n = 462 690).

Main Outcomes and Measures

The main outcome encompassed aspects of health span, lifespan, and exceptional longevity. Additional outcomes were epigenetic age acceleration (EAA) clocks.

Results

Findings from multivariable MR models simultaneously assessing psychiatric disorders and substance use behaviorsm suggest a negative association between smoking and longevity in cohorts of European ancestry (n = 709 709; 431 503 [60.8%] female; β, -0.33; 95% CI, -0.38 to -0.28; P = 4.59 × 10-34) and with increased EAA (n = 34 449; 18 017 [52.3%] female; eg, PhenoAge: β, 1.76; 95% CI, 0.72 to 2.79; P = 8.83 × 10-4). Transcriptomic imputation and colocalization identified 249 genes associated with smoking, including 36 novel genes not captured by the original smoking GWAS. Enriched pathways included chromatin remodeling and telomere assembly and maintenance. The transcriptome-wide signature of smoking was inversely associated with longevity, and estimates of individual smoking-associated genes, eg, XRCC3 and PRMT6, aligned with the smoking-longevity MR analyses, suggesting underlying transcriptomic mediators. Cis-instrument MR prioritized brain proteins associated with smoking behavior, including LY6H (β, 0.02; 95% CI, 0.01 to 0.03; P = 2.37 × 10-6) and RIT2 (β, 0.02; 95% CI, 0.01 to 0.03; P = 1.05 × 10-5), which had favorable adverse-effect profiles across 367 traits evaluated in phenome-wide MR.

Conclusions

The findings suggest that the genetic liability of smoking, but not of psychiatric disorders, is associated with longevity. Transcriptomic associations offer insights into smoking-related pathways, and identified proteomic targets may inform therapeutic development for smoking cessation strategies.

Integrated mendelian randomization analyses highlight AFF3 as a novel eQTL-mediated susceptibility gene in renal cancer and its potential mechanisms

BACKGROUNDS

A growing number of expression quantitative trait loci (eQTLs) have been found to be linked with tumorigenesis. In this article, we employed integrated Mendelian randomization (MR) analyses to identify novel susceptibility genes in renal cancer (RC) and reveal their potential mechanisms.

METHODS

Two-sample MR analyses were performed to infer causal relationships between eQTLs, metabolites, and RC risks through the "TwoSampleMR" R package. Sensitivity analyses, such as heterogeneity, pleiotropy, and leave-one-out analysis, were used to assess the stability of our outcomes. Summary-data-based MR (SMR) analyses were used to verify the causal relationships among cis-eQTLs and RC risks via the SMR 1.3.1 software.

RESULTS

Our results provided the first evidence for AFF3 eQTL elevating RC risks, suggesting its oncogenic roles (IVW method; odds ratio (OR) = 1.0005; 95% confidence interval (CI) = 1.0001-1.0010; P = 0.0285; heterogeneity = 0.9588; pleiotropy = 0.8397). Further SMR analysis validated the causal relationships among AFF3 cis-eQTLs and RC risks (P < 0.05). Moreover, the TCGA-KIRC, the ICGC-RC, and the GSE159115 datasets verified that the AFF3 gene was more highly expressed in RC tumors than normal control via scRNA-sequencing and bulk RNA-sequencing (P < 0.05). Gene set enrichment analysis (GSEA) analysis identified six potential biological pathways of AFF3 involved in RC. As for the potential mechanism of AFF3 in RC, we concluded in this article that AFF3 eQTL could negatively modulate the levels of the X-11,315 metabolite (IVW method; OR = 0.9127; 95% CI = 0.8530-0.9765; P = 0.0081; heterogeneity = 0.4150; pleiotropy = 0.8852), exhibiting preventive effects against RC risks (IVW method; OR = 0.9987; 95% CI = 0.9975-0.9999; P = 0.0380; heterogeneity = 0.5362; pleiotropy = 0.9808).

CONCLUSIONS

We concluded that AFF3 could serve as a novel eQTL-mediated susceptibility gene in RC and reveal its potential mechanism of elevating RC risks via negatively regulating the X-11,315 metabolite levels.

The causal relationship between sleep and risk of psychiatric disorders: A two-sample mendelian randomization study

Introduction

Sleep is associated with psychiatric disorders. However, their causality remains unknown.

Methods

The study explored the causal relationship between seven sleep parameters (sleep duration, insomnia, sleep apnea, chronotype, daytime dozing, napping during the day, and snoring) and three psychiatric disorders including major depressive disorder (MDD), schizophrenia, and attention-deficit/hyperactivity disorder (ADHD) using two-sample Mendelian randomization (MR). Genome-wide association study (GWAS) summary data for sleep parameters were obtained from the United Kingdom biobank, FinnGen biobank, and EBI databases. MR-Egger, weighted median, inverse-variance weighted (IVW), simple mode, weighted mode, maximum likelihood, penalized weighted median, and IVW(fixed effects) were used to perform the MR analysis. The heterogeneity was detected by Cochran's Q statistic. The horizontal pleiotropy was detected by MR Egger. The sensitivity was investigated by the leave-one-out analysis.

Results

Insomnia (OR = 2.02, 95%CI = 1.34-3.03, p = 0.001, False-discovery rate (FDR) corrected p-value = 0.011) and napping during the day (OR = 1.81, 95%CI = 1.34-2.44, FDR corrected p-value<0.001) were associated with an increased risk of MDD. Longer sleep duration (OR = 2.20, 95%CI = 1.24-3.90, FDR corrected p-value = 0.049) had an association with the increased risk of schizophrenia, while daytime dozing (OR = 4.44, 95%CI = 1.20-16.41, corrected p-value = 0.088)and napping during the day (OR = 2.11, 95%CI = 1.11-4.02, FDR corrected p-value = 0.088) had a suggestive association with an increased risk of schizophrenia. Longer sleep duration had a suggestive association with a decreased risk of ADHD (OR = 0.66, 95%CI = 0.42-0.93, FDR corrected p-value = 0.088).

Conclusion

This study provides further evidence for a complex relationship between sleep and psychiatric disorders. Our findings highlight the potential benefits of addressing sleep problems in the prevention of psychiatric disorders.

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.

Cortisol, Stress, and Disease-Bidirectional Associations; Role for Corticosteroid-Binding Globulin?

Selye described stress as a unified neurohormonal mechanism maintaining homeostasis. Acute stress system activation is adaptive through neurocognitive, catecholaminergic, and immunomodulation mechanisms, followed by a reset via cortisol. Stress system components, the sympathoadrenomedullary system, hypothalamic-pituitary-adrenal axis, and limbic structures are implicated in many chronic diseases by establishing an altered homeostatic state, allostasis. Consequent "primary stress system disorders" were popularly accepted, with phenotypes based on conditions such as Cushing syndrome, pheochromocytoma, and adrenal insufficiency. Cardiometabolic and major depressive disorders are candidates for hypercortisolemic etiology, contrasting the "hypocortisolemic symptom triad" of stress sensitivity, chronic fatigue, and pain. However, acceptance of chronic stress etiology requires cause-and-effect associations, and practical utility such as therapeutics altering stress system function. Inherent predispositions to stress system perturbations may be relevant. Glucocorticoid receptor (GR) variants have been associated with metabolic/neuropsychological states. The SERPINA6 gene encoding corticosteroid-binding globulin (CBG), was the sole genetic factor in a single-nucleotide variation-genome-wide association study linkage study of morning plasma cortisol, a risk factor for cardiovascular disease, with alterations in tissue-specific GR-related gene expression. Studies showed genetically predicted high cortisol concentrations are associated with hypertension and anxiety, and low CBG concentrations/binding affinity, with the hypocortisolemic triad. Acquired CBG deficiency in septic shock results in 3-fold higher mortality when hydrocortisone administration produces equivocal results, consistent with CBG's role in spatiotemporal cortisol delivery. We propose some stress system disorders result from constitutional stress system variants rather than stressors themselves. Altered CBG:cortisol buffering may influence interstitial cortisol ultradian surges leading to pathological tissue effects, an example of stress system variants contributing to stress-related disorders.

Irritable Bowel Syndrome Is Associated With Brain Health by Neuroimaging, Behavioral, Biochemical, and Genetic Analyses

BACKGROUND

Irritable bowel syndrome (IBS) interacts with psychopathology in a complex way; however, little is known about the underlying brain, biochemical, and genetic mechanisms.

METHODS

To clarify the phenotypic and genetic associations between IBS and brain health, we performed a comprehensive retrospective cohort study on a large population. Our study included 171,104 participants from the UK Biobank who underwent a thorough assessment of IBS, with the majority also providing neuroimaging, behavioral, biochemical, and genetic information. Multistage linked analyses were conducted, including phenome-wide association analysis, polygenic risk score calculation, and 2-sample Mendelian randomization analysis.

RESULTS

The phenome-wide association analysis showed that IBS was linked to brain health problems, including anxiety and depression, and poor cognitive performance. Significantly lower brain volumes associated with more severe IBS were found in key areas related to emotional regulation and higher-order cognition, including the medial orbitofrontal cortex/ventromedial prefrontal cortex, anterior insula, anterior and mid-cingulate cortices, dorsolateral prefrontal cortex, and hippocampus. Higher triglycerides, lower high-intensity lipoprotein, and lower platelets were also related (p < 1 × 10-10) to more severe IBS. Finally, Mendelian randomization analyses demonstrated potential causal relationships between IBS and brain health and indicated possible mediating effects of dyslipidemia and inflammation.

CONCLUSIONS

For the first time, this study provides a comprehensive understanding of the relationship between IBS and brain health phenotypes, integrating perspectives from neuroimaging, behavioral performance, biochemical factors, and genetics, which is of great significance for clinical applications to potentially address brain health impairments in patients with IBS.

Dietary factors and the risk of atopic dermatitis: a Mendelian randomisation study

Previous studies have revealed an association between dietary factors and atopic dermatitis (AD). To explore whether there was a causal relationship between diet and AD, we performed Mendelian randomisation (MR) analysis. The dataset of twenty-one dietary factors was obtained from UK Biobank. The dataset for AD was obtained from the publicly available FinnGen consortium. The main research method was the inverse-variance weighting method, which was supplemented by MR‒Egger, weighted median and weighted mode. In addition, sensitivity analysis was performed to ensure the accuracy of the results. The study revealed that beef intake (OR = 0·351; 95 % CI 0·145, 0·847; P = 0·020) and white bread intake (OR = 0·141; 95 % CI 0·030, 0·656; P = 0·012) may be protective factors against AD. There were no causal relationships between AD and any other dietary intake factors. Sensitivity analysis showed that our results were reliable, and no heterogeneity or pleiotropy was found. Therefore, we believe that beef intake may be associated with a reduced risk of AD. Although white bread was significant in the IVW analysis, there was large uncertainty in the results given the wide 95 % CI. Other factors were not associated with AD in this study.

Investigating the causal effect of previously reported therapeutic agents for colorectal cancer prevention: protocol for a Mendelian randomization analysis

Background

Colorectal cancer (CRC) is the third most common cancer worldwide, with 1.9 million new cases in 2020 and a predicted rise to 3.2 million in 2040. Screening programmes are already in place to aid early detection and secondary prevention of CRC, but the rising prevalence means additional approaches are required in both primary and secondary prevention settings. Preventive therapy, whereby natural or synthetic agents are used to prevent, reverse or delay disease development, could be an effective strategy to further reduce cancer risk and potential agents have already been identified in conventional observational studies. However, as such studies are vulnerable to confounding and reverse causation, we aim to evaluate these observed relationships using Mendelian randomization (MR), an alternative causal inference approach which should be less susceptible to these biases.

Methods and analysis

We will use two-sample MR, which uses two independent samples for the exposure and outcome data, to investigate previously reported observational associations of multiple potential preventive agents with CRC risk. We define preventive agents as any synthetic (e.g. approved medication) or natural (e.g. micronutrient, endogenous hormone) molecule used to reduce the risk of cancer. We will first extract potential preventive agents that have been previously linked to CRC risk in observational studies from reviews of the literature. We will then evaluate whether we can develop a genetic instrument for each preventive agent from previously published genome-wide association studies (GWASs) of direct measures of molecular traits (e.g. circulating levels of protein drug targets, blood-based biomarkers of dietary vitamins). The summary statistics from these GWASs, and a large GWAS of CRC, will be used in two-sample MR analyses to investigate the causal effect of putative preventive therapy agents on CRC risk. Sensitivity analyses will be conducted to evaluate the robustness of findings to potential violations of MR assumptions.

Causality Investigation between Gut Microbiome and Sleep-Related Traits: A Bidirectional Two-Sample Mendelian Randomization Study

Recent research has highlighted associations between sleep and microbial taxa and pathways. However, the causal effect of these associations remains unknown. To investigate this, we performed a bidirectional two-sample Mendelian randomization (MR) analysis using summary statistics of genome-wide association studies (GWAS) from 412 gut microbiome traits (N = 7738) and GWAS studies from seven sleep-associated traits (N = 345,552 to 386,577). We employed multiple MR methods to assess causality, with Inverse Variance Weighted (IVW) as the primary method, alongside a Bonferroni correction ((p < 2.4 × 10-4) to determine significant causal associations. We further applied Cochran's Q statistical analysis, MR-Egger intercept, and Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) for heterogeneity and pleiotropy assessment. IVW estimates revealed 79 potential causal effects of microbial taxa and pathways on sleep-related traits and 45 inverse causal relationships, with over half related to pathways, emphasizing their significance. The results revealed two significant causal associations: genetically determined relative abundance of pentose phosphate decreased sleep duration (p = 9.00 × 10-5), and genetically determined increase in fatty acid level increased the ease of getting up in the morning (p = 8.06 × 10-5). Sensitivity analyses, including heterogeneity and pleiotropy tests, as well as a leave-one-out analysis of single nucleotide polymorphisms, confirmed the robustness of these relationships. This study explores the potential causal relationships between sleep and microbial taxa and pathways, offering novel insights into their complex interplay.

Executive Function as an Underlying Mechanism of Alcohol Use, Aggression, and ADHD

Background

Executive functioning (EF) has been proposed as a transdiagnostic risk factor for externalizing disorders and behavior more broadly, including attention-deficit/hyperactivity disorder (ADHD), aggression, and alcohol use. Previous research has demonstrated both phenotypic and genetic overlap among these behaviors, but has yet to examine EF as a common causal mechanism. The current study examined reciprocal causal associations between EF and several externalizing behaviors using a Mendelian randomization (MR) approach.

Methods

Two-sample MR was conducted to test causal associations between EF and externalizing behaviors. Summary statistics from several genome-wide association studies (GWASs) were used in these analyses, including GWASs of EF, ADHD diagnostic status, drinks per week, aggressive behavior, and alcohol use disorder (AUD) diagnostic status. Multiple estimation methods were employed to account for horizontal pleiotropy (e.g., inverse variance weighted, MR-PRESSO, MR-MIX).

Results

EF demonstrated significant causal relationships with ADHD (P < 0.01), AUD (P < 0.03), and alcohol consumption (P < 0.01) across several estimation methods. Reciprocally, ADHD showed a significant causal influence on EF (P < 0.03). Nonetheless, caution should be used when interpreting these findings as there was some evidence for horizontal pleiotropy in the effect of EF on ADHD and significant heterogeneity in variant effects in the other relations tested. There were no significant findings for aggression.

Conclusions

Findings suggest that EF may be a causal mechanism underlying some externalizing behaviors, including ADHD and alcohol use, and that ADHD may also lead to lower performance on EF tasks.

Integrated multi-omics analyses revealed the association between rheumatoid arthritis and colorectal cancer: MYO9A as a shared gene signature and an immune-related therapeutic target

BACKGROUND

Our study aims to explore the relationship, shared gene signature, and the underlying mechanisms that connect rheumatoid arthritis (RA) to colorectal cancer (CRC).

METHODS

Mendelian randomization (MR) analysis was conducted to assess the causality between RA and CRC. Summary statistic data-based Mendelian randomization (SMR) leveraging eQTL data was employed to identify the CRC-related causal genes. Integrated analyses of single-cell RNA sequencing and bulk RNA sequencing were employed to comprehensively investigate the shared gene signature and potential mechanisms underlying the pathogenesis of both RA and CRC. Predictive analysis of the shared hub gene in CRC immunotherapy response was performed. Pan-cancer analyses were conducted to explore the potential role of MYO9A in 33 types of human tumors.

RESULTS

MR analysis suggested that RA might be associated with a slight increased risk of CRC (Odds Ratio = 1.04, 95% Confidence Interval = 1.01-1.07, P = 0.005). SMR analysis combining transcriptome analyses identified MYO9A as a causal gene in CRC and a shared gene signature in both RA and CRC. MYO9A may contribute to tumor suppression, while downregulation of MYO9A may impact CRC tumorigenesis by disrupting epithelial polarity and architecture, resulting in a worse prognosis in CRC. Additionally, MYO9A shows promise as a powerful predictive biomarker for cancer prognosis and immunotherapy response in CRC. Pan-cancer analyses demonstrated MYO9A may have a protective role in the occurrence and progression of various human cancers.

CONCLUSION

RA might be associated with a slight increased risk of CRC. MYO9A is a shared gene signature and a potential immune-related therapeutic target for both CRC and RA. Targeting the MYO9A-mediated loss of polarity and epithelial architecture could be a novel therapeutic approach for CRC.

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.

Bidirectional Two-Sample Mendelian Randomization Study of Immunoglobulin G N-Glycosylation and Senescence-Associated Secretory Phenotype

Observational studies revealed changes in Immunoglobulin G (IgG) N-glycosylation during the aging process. However, it lacks causal insights and remains unclear in which direction causal relationships exist. The two-sample bidirectional Mendelian randomization (MR) design was adopted to explore causal associations between IgG N-glycans and the senescence-associated secretory phenotype (SASP). Inverse variance weighted (IVW) and Wald ratio methods were used as the main analyses, supplemented by sensitivity analyses. Forward MR analyses revealed causal associations between the glycan peak (GP) and SASP, including GP6 (odds ratio [OR] = 0.428, 95% confidence interval [CI] = 0.189-0.969) and GP17 (OR = 0.709, 95%CI = 0.504-0.995) with growth/differentiation factor 15 (GDF15), GP19 with an advanced glycosylation end-product-specific receptor (RAGE) (OR = 2.142, 95%  CI  = 1.384-3.316), and GP15 with matrix metalloproteinase 2 (MMP2) (OR = 1.136, 95%  CI =1.008-1.282). The reverse MR indicated that genetic liability to RAGE was associated with increased levels of GP17 (OR = 1.125, 95%  CI  = 1.003-1.261) and GP24 (OR = 1.222, 95%  CI  = 1.046-1.428), while pulmonary and activation-regulated chemokines (PARC) exhibited causal associations with GP10 (OR = 1.269, 95%  CI  = 1.048-1.537) and GP15 (OR = 1.297, 95%  CI = 1.072-1.570). The findings provided suggested evidence on the bidirectional causality between IgG N-glycans and SASP, which might reveal potential regulatory mechanisms.

Therapeutic targets for age-related macular degeneration: proteome-wide Mendelian randomization and colocalization analyses

Background

Currently, effective therapeutic drugs for age-related macular degeneration (AMD) are urgently needed, and it is crucial to explore new treatment targets. The proteome is indispensable for exploring disease targets, so we conducted a Mendelian randomization (MR) of the proteome to identify new targets for AMD and its related subtypes.

Methods

The plasma protein level data used in this study were obtained from two large-scale studies of protein quantitative trait loci (pQTL), comprising 35,559 and 54,219 samples, respectively. The expression quantitative trait loci (eQTL) data were sourced from eQTLGen and GTEx Version 8. The discovery set for AMD data and subtypes was derived from the FinnGen study, consisting of 9,721 AMD cases and 381,339 controls, 5,239 wet AMD cases and 273,920 controls, and 6,651 dry AMD cases and 272,504 controls. The replication set for AMD data was obtained from the study by Winkler TW et al., comprising 14,034 cases and 91,234 controls. Summary Mendelian randomization (SMR) analysis was employed to assess the association between QTL data and AMD and its subtypes, while colocalization analysis was performed to determine whether they share causal variants. Additionally, chemical exploration and molecular docking were utilized to validate potential drugs targeting the identified proteins.

Results

SMR and colocalization analysis jointly identified risk-associated proteins for AMD and its subtypes, including 5 proteins (WARS1, BRD2, IL20RB, TGFB1, TNFRSF10A) associated with AMD, 2 proteins (WARS1, IL20RB) associated with Dry-AMD, and 9 proteins (COL10A1, WARS1, VTN, SDF2, LBP, CD226, TGFB1, TNFRSF10A, CSF2) associated with Wet-AMD. The results revealed potential therapeutic chemicals, and molecular docking indicated a good binding between the chemicals and protein structures.

Conclusion

Proteome-wide MR have identified risk-associated proteins for AMD and its subtypes, suggesting that these proteins may serve as potential therapeutic targets worthy of further clinical investigation.

Brain lesions causing parkinsonism versus seizures map to opposite brain networks

Recent epidemiological studies propose an association between parkinsonism and seizures, but the direction of this association is unclear. Focal brain lesions causing new-onset parkinsonism versus seizures may provide a unique perspective on the causal relationship between the two symptoms and involved brain networks. We studied lesions causing parkinsonism versus lesions causing seizures and used the human connectome to identify their connected brain networks. Brain networks for parkinsonism and seizures were compared using spatial correlations on a group and individual lesion level. Lesions not associated with either symptom were used as controls. Lesion locations from 29 patients with parkinsonism were connected to a brain network with the opposite spatial topography (spatial r = -0.85) compared to 347 patients with lesions causing seizures. A similar inverse relationship was found when comparing the connections that were most specific on a group level (spatial r = -0.51) and on an individual lesion level (average spatial r = -0.042; P < 0.001). The substantia nigra was found to be most positively correlated to the parkinsonism network but most negatively correlated to the seizure network (spatial r > 0.8). Brain lesions causing parkinsonism versus seizures map to opposite brain networks, providing neuroanatomical insight into conflicting epidemiological evidence.

Entertainment activities and the risk of Alzheimer's disease: a Mendelian randomization analysis

Background

Effective prevention is key to addressing the increasing prevalence and mortality of Alzheimer's disease. Assessing the causal relationship between modifiable entertainment activity factors and the risk of Alzheimer's disease is important for developing public health measures, but establishing causal relationships in epidemiological data may be challenging.

Methods

This study using the two-sample Mendelian randomization analysis aimed to investigate the causal effect of entertainment activity factors on the risk of Alzheimer's disease. Summary statistics from publicly available genome-wide association studies were used to analyze 14 modifiable entertainment activity. The inverse variance weighted random effects method as the primary analytical method to estimate causal effects was used. Additionally performed MR-Egger, weighted median and weighted model methods to assess the robustness of the results. The reliability of our findings was validated through systematic sensitivity analyses and tests for heterogeneity.

Results

We found significant correlation between time spent using computer (odds ratio 0.998; 95% confidence interval 0.996-0.999; p = 0.013) and Alzheimer's disease, compared to other studied entertainment activities that had no significant causal relationship with Alzheimer's disease.

Conclusion

Our findings support the hypothesis that increased computer use may reduce the risk of Alzheimer's disease, providing potential strategic directions for the prevention of neurodegenerative diseases.

Telomere length in relation to fecundability and use of assisted reproductive technologies: the Norwegian Mother, Father, and Child Cohort Study

In women, shorter telomeres have been reported to be associated with conditions such as endometriosis and polycystic ovary syndrome, whereas other studies have reported the opposite. In men, studies mostly report associations between shorter telomeres and sperm quality. To our knowledge, no studies have thus far investigated the associations between TL and fecundability or the use of ART. This study is based on the Norwegian Mother, Father, and Child Cohort (MoBa) Study and uses data from the Medical Birth Registry of Norway (MBRN). We included women (24,645 with genotype data and 1,054 with TL measurements) and men (18,339 with genotype data and 965 with TL measurements) participating between 1998 and 2008. We investigated the associations between leukocyte TL and fecundability, infertility, and the use of ART. We also repeated the analyses using instrumental variables for TL, including genetic risk scores for TL and genetically predicted TL. Approximately 11% of couples had experienced infertility and 4% had used ART. TL was not associated with fecundability among women (fecundability ratio [FR], 0.98; 95% confidence interval [CI], 0.92-1.04) or men (FR, 0.99; CI, 0.93-1.06), nor with infertility among women (odds ratio [OR], 1.03; CI, 0.85-1.24) or men (OR, 1.05; CI, 0.87-1.28). We observed an increased likelihood of using ART with increasing TL among men (OR, 1.22; CI, 1.03-1.46), but not among women (OR, 1.10; CI, 0.92-1.31). No significant associations were observed using the instrumental variables. Our results indicate that TL is a poor biomarker of fecundability, infertility and use of ART in MoBa. Additional studies are required to replicate the association observed between TL and ART in men.

Valid instrumental variable selection method using negative control outcomes and constructing efficient estimator

In observational studies, instrumental variable (IV) methods are commonly applied when there are unmeasured covariates. In Mendelian randomization, constructing an allele score using many single nucleotide polymorphisms is often implemented; however, estimating biased causal effects by including some invalid IVs poses some risks. Invalid IVs are those IV candidates that are associated with unobserved variables. To solve this problem, we developed a novel strategy using negative control outcomes (NCOs) as auxiliary variables. Using NCOs, we are able to select only valid IVs and exclude invalid IVs without knowing which of the instruments are invalid. We also developed a new two-step estimation procedure and proved the semiparametric efficiency of our estimator. The performance of our proposed method was superior to some previous methods through simulations. Subsequently, we applied the proposed method to the UK Biobank dataset. Our results demonstrate that the use of an auxiliary variable, such as an NCO, enables the selection of valid IVs with assumptions different from those used in previous methods.

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.

Metformin treatment reduces the incidence of osteoporosis: a two-sample Mendelian randomized study

It remains unclear whether the association between metformin and osteoporosis (OP) risk is causal. This two-sample Mendelian randomization (MR) study suggests a causal relationship between metformin treatment and a decrease in OP and fracture incidence, as well as an increase in bone mineral density (BMD) in the lumbar spine, femoral neck, and heel. Nonetheless, no significant causal effect is observed on forearm BMD.

PURPOSE

We utilize a MR approach to investigate the association between metformin treatment and the risk of OP.

METHODS

Metformin treatment was selected as exposures. Outcomes included OP; BMD at the forearm (FA), femoral neck (FN), and lumbar spine (LS); estimated heel bone mineral density (eBMD); and fracture. Summary statistics for exposures and outcomes were obtained from corresponding genome-wide association studies. Inverse variance-weighted (IVW) analysis was mainly applied; the weighted median (WM), penalized weighted median (PWM), maximum likelihood (ML), and MR-Egger regression (MR-Egger) method were also used to obtain robust estimates. A series of sensitivity analyses including Cochran's Q test, MR-Egger regression, leave-one-out analysis, and Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) were used to detect pleiotropy or heterogeneity.

RESULTS

In the main analysis, IVW estimates demonstrated that metformin treatment had a definite causal effect on the risk of OP (odds ratio (OR): 0.859, 95% CI: 0.774-0.953, P = 0.004), LS-BMD (OR: 1.063, 95% CI: 1.023-1.105, P = 0.002), FN-BMD (OR: 1.034, 95% CI: 1.000-1.069, P = 0.049), eBMD (OR: 1.035, 95% CI: 1.023-1.047, P ≤ 0.001), and fracture(OR: 0.958, 95% CI: 0.928-0.989, P = 0.008). However, it did not have an effect on FA-BMD(OR: 1.050, 95% CI: 0.969-1.138, P = 0.237).

CONCLUSIONS

This study indicated that metformin treatment is significantly associated with a reduction in the risk of OP, fracture and higher LS-BMD, FN-BMD, and eBMD. However, there was no significant association with FA-BMD.

The association between lipid parameters and erectile dysfunction: a two-sample Mendelian randomization and case-control study

PURPOSE

Lipid parameters have been shown to have significant predictive value for cardiovascular disease, but few studies have evaluated their correlation with erectile dysfunction (ED) in young men.

METHODS

The case-control study encompassed 186 young ED patients (ages 20-40) and 186 healthy controls. Lipid parameters, including total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), TC/HDL ratio, TG/HDL ratio, and LDL-C/HDL-C ratio, were assessed in all participants. The International Index of Erectile Function (IIEF-5) scores were collected for all participants to evaluate erectile status. Multivariate logistic regression analysis was utilized to appraise the association of lipid-related parameters with ED. Single-nucleotide polymorphisms (SNPs) significantly correlated with lipid parameters (TC, TG, LDL-C, HDL-C) were selected from genome-wide association studies (GWAS) as instrumental variables (IV) (P < 5.0 × 10-8). Summary data for ED was gathered from a GWAS with a sample size of (n = 17,353 cases/28,210 controls). The inverse variance weighted (IVW) method was employed as the primary mendelian randomization (MR) analysis method to assess causal effects. Causal estimates were represented as odds ratios (OR) with 95% confidence intervals (CI).

RESULTS

Results from the case-control study revealed that, when compared with the control group, levels of LDL-C, TG, UA, LDL-C/HDL-C, TG/HDL-C, and TC/HDL-C in the ED group were significantly elevated (P < 0.01), while HDL-C was significantly decreased (P < 0.01) in the ED group. Multivariate logistic regression analysis indicated LDL-C/HDL-C as a risk factor for both the incidence and severity of ED (P < 0.001). Two-sample MR analysis demonstrated no significant causal correlation between lipid parameters-LDL-C (OR, 0.98, 95% CI, 0.88-1.08, P = 0.616), HDL-C (OR, 1.07, 95% CI: 0.96-1.19, P = 0.249), TC (OR, 1.07, 95% CI, 0.96-1.18, P = 0.208), TG (OR, 0.98, 95% CI, 0.80-1.13, P = 0.579) -and an increased risk of ED (all P > 0.05).

CONCLUSIONS

The case-control analysis ascertained a significant association between LDL-C, HDL-C, LDL-C/HDL-C, and ED and its severity. However, results from the MR study do not support a causal role of lipid parameters in ED.

The causal associations of inflammatory cytokines with obesity and systemic lupus erythematosus: A Mendelian randomization study

OBJECTIVE

Previous studies have partly discussed the roles of inflammatory cytokines in obesity and systemic lupus erythematosus (SLE), but the causal relationship among inflammatory cytokines, obesity, and SLE is unclear. It is challenging to comprehensively evaluate the causal relationship between these variables. This study aimed to investigate the role of cytokines as intermediates between obesity and SLE.

METHODS

The inverse-variance weighted method (IVW) of mendelian randomization (MR) is mainly used to explore the causal relationship between exposure and outcome by using the genetic variation of the open large genome-wide association studies (GWAS), namely single-nucleotide polymorphisms (SNPs) related to obesity (more than 600 000 participants), inflammatory cytokines (8293 healthy participants) and SLE (7219 cases). Methods such as weighted median, MR-Egger are used to evaluate the reliability of causality. Reverse analysis is performed for each MR analysis to avoid reverse causality. Cochran's Q statistic and funnel chart are used to detect heterogeneity, MR-Egger intercept test and leave-one-out sensitivity analyses evaluated pleiotropy.

RESULTS

Obesity was associated with 25 cytokines, and 3 cytokines were associated with SLE, including CTACK (OR = 1.19, 95% CI: 1.06, 1.33, p = .002), IL-18 (OR = 1.13, 95% CI: 1.01, 1.26, p = .027), SCGFb (OR = 0.89, 95% CI: 0.79, 0.99, p = .044). In the opposite direction, SLE was associated with 18 cytokines, and 2 cytokines were associated with obesity, including IP-10 (βIVW = -.03, 95% CI: -0.05, -0.01, p = .002), MIP-1B (βIVW = -.03, 95% CI: -0.05, -0.01, p = .004).

CONCLUSION

Our MR study suggested that CTACK, IL-18 and SCGFb may play an intermediary role in obesity to SLE, while IP-10 and MIP-1B may play an intermediary role in SLE to obesity.

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.

Lipid traits and lipid-lowering drug target genes and risk of melanoma: a mendelian randomization study

Our study aimed to investigate the role of lipids in melanoma risk and the effect of lipid-lowering drug targets on melanoma. Using Mendelian Randomization analysis, we examined the genetic agents of nine lipid-lowering drugs and their association with melanoma risk. We found that genetically proxied inhibition of HMGCR, ABCG5/ABCG8, and ANGPTL3 was associated with a reduced risk of melanoma. On the other hand, inhibition of LPL and Apo-B100 was significantly associated with an increased risk of melanoma. Sensitivity analyses did not reveal any statistical evidence of bias from pleiotropy or genetic confounding. We did not find a robust association between lipid traits NPC1L1, PCSK9, APOC3 inhibition, and melanoma risk. These findings were validated using two independent lipid datasets. Our analysis also revealed that HMGCR, ANGPTL3, and ABCG5/ABCG8 inhibitors reduced melanoma risk independent of their effects on lipids. This suggests that these targets may have potential for melanoma prevention or treatment. In conclusion, our study provides evidence for a causal role of lipids in melanoma risk and highlights specific lipid-lowering drug targets that may be effective in reducing the risk of melanoma. These findings contribute to the understanding of the underlying mechanisms of melanoma development and provide potential avenues for further research and therapeutic interventions.

Unraveling the causal relationships between depression and brain structural imaging phenotypes: A bidirectional Mendelian Randomization study

BACKGROUND

Previous studies have revealed structural brain abnormalities in individuals with depression, but the causal relationship between depression and brain structure remains unclear.

METHODS

A genetic correlation analysis was conducted using summary statistics from the largest genome-wide association studies for depression (N = 674,452) and 1,265 brain structural imaging-derived phenotypes (IDPs, N = 33,224). Subsequently, a bidirectional two-sample Mendelian Randomization (MR) approach was employed to explore the causal relationships between depression and the IDPs that showed genetic correlations with depression. The main MR results were obtained using the inverse variance weighted (IVW) method, and other MR methods were further employed to ensure the reliability of the findings.

RESULTS

Ninety structural IDPs were identified as being genetically correlated with depression and were included in the MR analyses. The IVW MR results indicated that reductions in the volume of several brain regions, including the bilateral subcallosal cortex, right medial orbitofrontal cortex, and right middle-posterior part of the cingulate cortex, were causally linked to an increased risk of depression. Additionally, decreases in surface area of the right middle temporal visual area, right middle temporal cortex, right inferior temporal cortex, and right middle-posterior part of the cingulate cortex were causally associated with a heightened risk of depression. Validation and sensitivity analyses supported the robustness of these findings. However, no evidence was found for a causal effect of depression on structural IDPs.

CONCLUSIONS

Our findings reveal the causal influence of specific brain structures on depression, providing evidence to consider brain structural changes in the etiology and treatment of depression.

Cathepsin-mediated regulation of alpha-synuclein in Parkinson's disease: a Mendelian randomization study

Objective

The observational association between cathepsin and Parkinson's disease (PD) has been partially explored in previous research. However, the causal relationship remains unclear. In this study, our objective is to investigate the causal link between cathepsin and PD using Mendelian randomization (MR) analysis and elucidate the underlying mechanisms governing their interaction.

Methods

Utilizing bidirectional two-sample MR and multivariable MR, we systematically investigates the causal relationship between nine cathepsins and PD. The data pertaining to cathepsins were obtained from the Integrative Epidemiology Unit (IEU) Open GWAS Project, while data related to PD were sourced from versions R9 and R10 of the FinnGen database. The primary analytical method utilized was the inverse variance weighted (IVW), with MR analysis initially conducted using PD data from R9, complemented by a series of sensitivity analyses. Subsequently, replication analysis was performed on the R10 dataset, and meta-analysis were employed to merge the findings from both datasets. To explore potential mechanisms by which Cathepsins may impact PD, MR analyses were performed on significant Cathepsins with alpha-synuclein. MR analysis and colocalization analysis were conducted on expression quantitative trait loci (eQTL) data of gene related to alpha-synuclein with PD data.

Result

Forward MR analyses revealed more cathepsin B (CTSB) associated with less PD risk (OR = 0.898, 95%CI: 0.834-0.966, p = 0.004), while more cathepsin H (CTSH) (OR = 1.076, 95%CI: 1.007-1.149, p = 0.029) and more cathepsin S (CTSS) (OR = 1.076, 95%CI: 1.007-1.150, p = 0.030) associated with increasing PD risk. Meta-analyses validated these associations. Multivariate MR Results were consistent with those before adjustment. No significant results were observed in bidirectional MR analysis. In the investigation of the underlying mechanism, our findings demonstrate that CTSB significantly reduces the levels of alpha-synuclein (OR = 0.909, 95%CI: 0.841-0.983, p = 0.017). Concurrently, a genetically determined positive correlation between alpha-synuclein and PD is illuminated by both eQTL MR and colocalization analysis.

Conclusion

In conclusion, this MR study yields robust evidence suggesting an association between elevated levels of CTSB and reduced PD risk, mediated by the downregulation of alpha-synuclein levels. Conversely, higher levels of CTSH and CTSS are associated with an increased risk of PD. These findings offer novel insights into the pathophysiological mechanisms of PD and identify potential drug targets for disease prevention and treatment warranting further clinical investigations.

Causal effect between gut microbiota and metabolic syndrome in European population: a bidirectional mendelian randomization study

BACKGROUND

Observational studies have reported that gut microbiota composition is associated with metabolic syndrome. However, the causal effect of gut microbiota on metabolic syndrome has yet to be confirmed.

METHODS

We performed a bidirectional Mendelian randomization study to investigate the causal effect between gut microbiota and metabolic syndrome in European population. Summary statistics of gut microbiota were from the largest available genome-wide association study meta-analysis (n = 13,266) conducted by the MiBioGen consortium. The summary statistics of outcome were obtained from the most comprehensive genome-wide association studies of metabolic syndrome (n = 291,107). The inverse-variance weighted method was applied as the primary method, and the robustness of the results was assessed by a series of sensitivity analyses.

RESULTS

In the primary causal estimates, Actinobacteria (OR = 0.935, 95% CI = 0.878-0.996, P = 0.037), Bifidobacteriales (OR = 0.928, 95% CI = 0.868-0.992, P = 0.028), Bifidobacteriaceae (OR = 0.928, 95% CI = 0.868-0.992, P = 0.028), Desulfovibrio (OR = 0.920, 95% CI = 0.869-0.975, P = 0.005), and RuminococcaceaeUCG010 (OR = 0.882, 95% CI = 0.803-0.969, P = 0.009) may be associated with a lower risk of metabolic syndrome, while Lachnospiraceae (OR = 1.130, 95% CI = 1.016-1.257, P = 0.025), Veillonellaceae (OR = 1.055, 95% CI = 1.004-1.108, P = 0.034) and Olsenella (OR = 1.046, 95% CI = 1.009-1.085, P = 0.015) may be linked to a higher risk for metabolic syndrome. Reverse MR analysis demonstrated that abundance of RuminococcaceaeUCG010 (OR = 0.938, 95% CI = 0.886-0.994, P = 0.030) may be downregulated by metabolic syndrome. Sensitivity analyses indicated no heterogeneity or horizontal pleiotropy.

CONCLUSIONS

Our Mendelian randomization study provided causal relationship between specific gut microbiota and metabolic syndrome, which might provide new insights into the potential pathogenic mechanisms of gut microbiota in metabolic syndrome and the assignment of effective therapeutic strategies.

Non-linear Mendelian randomization: detection of biases using negative controls with a focus on BMI, Vitamin D and LDL cholesterol

Mendelian randomisation (MR) is an established technique in epidemiological investigation, using the principle of random allocation of genetic variants at conception to estimate the causal linear effect of an exposure on an outcome. Extensions to this technique include non-linear approaches that allow for differential effects of the exposure on the outcome depending on the level of the exposure. A widely used non-linear method is the residual approach, which estimates the causal effect within different strata of the non-genetically predicted exposure (i.e. the "residual" exposure). These "local" causal estimates are then used to make inferences about non-linear effects. Recent work has identified that this method can lead to estimates that are seriously biased, and a new method-the doubly-ranked method-has been introduced as a possibly more robust approach. In this paper, we perform negative control outcome analyses in the MR context. These are analyses with outcomes onto which the exposure should have no predicted causal effect. Using both methods we find clearly biased estimates in certain situations. We additionally examined a situation for which there are robust randomised controlled trial estimates of effects-that of low-density lipoprotein cholesterol (LDL-C) reduction onto myocardial infarction, where randomised trials have provided strong evidence of the shape of the relationship. The doubly-ranked method did not identify the same shape as the trial data, and for LDL-C and other lipids they generated some highly implausible findings. Therefore, we suggest there should be extensive simulation and empirical methodological examination of performance of both methods for NLMR under different conditions before further use of these methods. In the interim, use of NLMR methods needs justification, and a number of sanity checks (such as analysis of negative and positive control outcomes, sensitivity analyses excluding removal of strata at the extremes of the distribution, examination of biological plausibility and triangulation of results) should be performed.

Shared genetics linking sociability with the brain's default mode network

The brain's default mode network (DMN) plays a role in social cognition, with altered DMN function being associated with social impairments across various neuropsychiatric disorders. In the present study, we examined the genetic relationship between sociability and DMN-related resting-state functional magnetic resonance imaging (rs-fMRI) traits. To this end, we used genome-wide association summary statistics for sociability and 31 activity and 64 connectivity DMN-related rs-fMRI traits (N=34,691-342,461). First, we examined global and local genetic correlations between sociability and the rs-fMRI traits. Second, to assess putatively causal relationships between the traits, we conducted bi-directional Mendelian randomisation (MR) analyses. Finally, we prioritised genes influencing both sociability and rs-fMRI traits by combining three methods: gene-expression eQTL MR analyses, the CELLECT framework using single-nucleus RNA-seq data, and network propagation in the context of a protein-protein interaction network. Significant local genetic correlations were found between sociability and two rs-fMRI traits, one representing spontaneous activity within the temporal cortex, the other representing connectivity between the frontal/cingulate and angular/temporal cortices. Sociability affected 12 rs-fMRI traits when allowing for weakly correlated genetic instruments. Combing all three methods for gene prioritisation, we defined 17 highly prioritised genes, with DRD2 and LINGO1 showing the most robust evidence across all analyses. By integrating genetic and transcriptomics data, our gene prioritisation strategy may serve as a blueprint for future studies. The prioritised genes could be explored as potential biomarkers for social dysfunction in the context of neuropsychiatric disorders and as drug target genes.