Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects

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.

Benchmarking Mendelian randomization methods for causal inference using genome-wide association study summary statistics

Mendelian randomization (MR), which utilizes genetic variants as instrumental variables (IVs), has gained popularity as a method for causal inference between phenotypes using genetic data. While efforts have been made to relax IV assumptions and develop new methods for causal inference in the presence of invalid IVs due to confounding, the reliability of MR methods in real-world applications remains uncertain. Instead of using simulated datasets, we conducted a benchmark study evaluating 16 two-sample summary-level MR methods using real-world genetic datasets to provide guidelines for the best practices. Our study focused on the following crucial aspects: type I error control in the presence of various confounding scenarios (e.g., population stratification, pleiotropy, and family-level confounders like assortative mating), the accuracy of causal effect estimates, replicability, and power. By comprehensively evaluating the performance of compared methods over one thousand exposure-outcome trait pairs, our study not only provides valuable insights into the performance and limitations of the compared methods but also offers practical guidance for researchers to choose appropriate MR methods for causal inference.

Polygenic Indices (a.k.a. Polygenic Scores) in Social Science: A Guide for Interpretation and Evaluation

Polygenic indices (PGI)-the new recommended label for polygenic scores (PGS) in social science-are genetic summary scales often used to represent an individual's liability for a disease, trait, or behavior based on the additive effects of measured genetic variants. Enthusiasm for linking genetic data with social outcomes and the inclusion of premade PGIs in social science datasets have facilitated increased uptake of PGIs in social science research-a trend that will likely continue. Yet, most social scientists lack the expertise to interpret and evaluate PGIs in social science research. Here, we provide a primer on PGIs for social scientists focusing on key concepts, unique statistical genetic considerations, and best practices in calculation, estimation, reporting, and interpretation. We summarize our recommended best practices as a checklist to aid social scientists in evaluating and interpreting studies with PGIs. We conclude by discussing the similarities between PGIs and standard social science scales and unique interpretative considerations.

Trauma, adversity, and biological aging: behavioral mechanisms relevant to treatment and theory

Although stress and adversity are largely universal experiences, people exposed to greater hardship are at increased risk for negative health consequences. Recent studies identify accelerated biological aging as a mechanism that could explain how trauma and adversity gives rise to poor health, and advances in this area of study coincide with technological innovations in the measurement of biological aging, particularly epigenetic profiles consistent with accelerated aging derived from DNA methylation. In this review, we provide an overview of the current literature examining how adversity might accelerate biological aging, with a specific focus on social and health behaviors. The most extensive evidence in this area suggests that health-compromising behaviors, particularly smoking, may partially explain the association between adversity and accelerated aging. Although there is relatively less published support for the role of social behaviors, emerging evidence points to the importance of social connection as a mechanism for future study. Our review highlights the need to determine the extent to which the associations from adversity to accelerated aging are consistent with causal processes. As we consider these questions, the review emphasizes methodological approaches from the causal inference literature that can help deepen our understanding of how stress and trauma might result in poor health. The use of these methodologies will help provide evidence as to which behavioral interventions might slow aging and improve health, particularly among populations that more often experience adversity and trauma.

No evidence for causal effects of C-reactive protein (CRP) on chronic pain conditions: a Mendelian randomization study

Objective

We conducted a Mendelian randomization (MR) study to examine causal associations of C-reactive protein (CRP) with (1) spinal pain; (2) extent of multisite chronic pain; and (3) chronic widespread musculoskeletal pain.

Design

Two-sample MR study.

Setting/Subjects

We used summary statistics from publicly available genome-wide association studies (GWAS) conducted in multiple cohorts and biobanks. Genetic instrumental variables were taken from an exposure GWAS of CRP (n=204,402). Outcome GWASs examined spinal pain (n=1,028,947), extent of multisite chronic pain defined as the number of locations with chronic pain (n=387,649), and chronic widespread pain (n=249,843).

Methods

We examined MR evidence for causal associations using inverse-variance weighted (IVW) analysis and sensitivity analyses using other methods. We calculated odds ratios (ORs), 95% confidence intervals (95% CIs), and p-values, using a Bonferroni correction (p<0.0166) to account for 3 primary comparisons.

Results

Greater serum CRP (mg/L) was not significantly causally associated with spinal pain (OR=1.04, 95% CI 1.00-1.08; p=0.07) in IVW analysis. Greater serum CRP also showed no significant causal association with extent of multisite chronic pain in IVW analysis (beta coefficient= 0.014, standard error=0.011; p=0.19). CRP also showed no significant causal association with chronic widespread pain in IVW analysis (OR=1.00, 95% CI 1.00-1.00; p=0.75). All secondary and sensitivity analyses also showed no significant associations.

Conclusions

This MR study found no causal association of CRP on spinal pain, the extent of chronic pain, or chronic widespread pain. Future studies examining mechanistic biomarkers for pain conditions should consider other candidates besides CRP.

Screen time in the development of type 2 diabetes mellitus (T2DM) : a two-sample Mendelian randomization study

OBJECTIVE

This study aimed to investigate the potential causal relationship between screen time and the risk of developing type 2 diabetes mellitus (T2DM) using Mendelian randomization.

METHODS

Two-sample Mendelian randomization was conducted, utilizing genetic variants associated with different types of screen time as instrumental variables. Single nucleotide polymorphisms (SNPs) were used to assess the primary outcome, which was the risk of developing T2DM.

RESULTS

The analysis revealed a significant positive causal association between television viewing time and the risk of T2DM. Specifically, excessive television viewing time was found to increase the risk of developing T2DM (OR: 2.39, 95% CI: 1.90 to 3.00, P < 0.01). However, no significant causal relationship was observed between computer usage time and the risk of T2DM. Additionally, mobile phone use time showed a positive correlation with the risk of T2DM (OR: 1.31, 95% CI: 1.04 to 1.64, P = 0.02), albeit to a lesser extent than television viewing time.

CONCLUSION

The findings of this study indicate a significant causal association between certain types of screen time, specifically television viewing and mobile phone use, and an increased risk of T2DM.

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.

Quantifying the relative importance of genetics and environment on the comorbidity between mental and cardiometabolic disorders using 17 million Scandinavians

Mental disorders are leading causes of disability and premature death worldwide, partly due to high comorbidity with cardiometabolic disorders. Reasons for this comorbidity are still poorly understood. We leverage nation-wide health records and near-complete genealogies of Denmark and Sweden (n = 17 million) to reveal the genetic and environmental contributions underlying the observed comorbidity between six mental disorders and 15 cardiometabolic disorders. Genetic factors contributed about 50% to the comorbidity of schizophrenia, affective disorders, and autism spectrum disorder with cardiometabolic disorders, whereas the comorbidity of attention-deficit/hyperactivity disorder and anorexia with cardiometabolic disorders was mainly or fully driven by environmental factors. In this work we provide causal insight to guide clinical and scientific initiatives directed at achieving mechanistic understanding as well as preventing and alleviating the consequences of these disorders.

C-reactive protein and cognitive impairment: A bidirectional Mendelian randomization study

OBJECTIVES

While C-reactive protein (CRP) has been solidly linked as a risk factor for cognitive impairment, observational research alone cannot definitively demonstrate a causal relationship. This study therefore sought to determine whether there was an association between CRP and the development of cognitive impairment.

METHODS

This study employed bidirectional Mendelian randomization (MR) to investigate the genetic association between CRP and cognitive impairment. genome-wide association studies (GWAS) summary statistics for both were sourced from IEU Open GWAS or prior reports. Cognitive GWAS's used were on tests designed to assess cognitive performance, fluid intelligence, prospective memory, and reaction time. The MR analysis applied several methods, including inverse variance-weighted (IVW), MR Egger, weighted median, simple mode, and weighted mode approaches, then use of MR sensitivity analyses to interrogate findings.

RESULTS

Forward MR analysis showed that genetically proxied CRP was associated with prospective memory (P = 0.009), whereas there is little evidence to support an association between CRP and other cognitive tests. Reverse MR analysis indicated a potential association between genetic proxy cognitive performance (P = 0.002) and fluid intelligence score (P = 0.019) with CRP levels. For genetically proxied CRP on prospective memory, the level of pleiotropy (P > 0.05) and no genetic variant heterogeneity (P > 0.05) made bias unlikely, and leave-one-out tests also confirmed robust associations.

CONCLUSIONS

The effect of genetically proxied CRP on prospective memory, with little evidence on other cognitive tests. The reverse MR shows some evidence of genetically proxied cognition (cognitive performance and fluid intelligence) on CRP levels.

Using parent-offspring pairs and trios to estimate indirect genetic effects in education

We investigated indirect genetic effects (IGEs), also known as genetic nurture, in education with a novel approach that uses phased data to include parent-offspring pairs in the transmitted/nontransmitted study design. This method increases the power to detect IGEs, enhances the generalizability of the findings, and allows for the study of effects by parent-of-origin. We validated and applied this method in a family-based subsample of adolescents and adults from the Lifelines Cohort Study in the Netherlands (N = 6147), using the latest genome-wide association study data on educational attainment to construct polygenic scores (PGS). Our results indicated that IGEs play a role in education outcomes in the Netherlands: we found significant associations of the nontransmitted PGS with secondary school level in youth between 13 and 24 years old as well as with education attainment and years of education in adults over 25 years old (β = 0.14, 0.17 and 0.26, respectively), with tentative evidence for larger maternal IGEs. In conclusion, we replicated previous findings and showed that including parent-offspring pairs in addition to trios in the transmitted/nontransmitted design can benefit future studies of parental IGEs in a wide range of outcomes.

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.

Exploring the Fetal Origins Hypothesis Using Genetic Data

Birth weight is a robust predictor of valued life course outcomes, emphasizing the importance of prenatal development. But does birth weight act as a proxy for environmental conditions in utero, or do biological processes surrounding birth weight themselves play a role in healthy development? To answer this question, we leverage variation in birth weight that is, within families, orthogonal to prenatal environmental conditions: one's genes. We construct polygenic scores in two longitudinal studies (Born in Bradford, N = 2008; Wisconsin Longitudinal Study, N = 8488) to empirically explore the molecular genetic correlates of birth weight. A 1 standard deviation increase in the polygenic score is associated with an ~100-grams increase in birth weight and a 1.4 pp (22 percent) decrease in low birth weight probability. Sibling comparisons illustrate that this association largely represents a causal effect. The polygenic score-birth weight association is increased for children who spend longer in the womb and whose mothers have higher body mass index, though we find no differences across maternal socioeconomic status. Finally, the polygenic score affects social and cognitive outcomes, suggesting that birth weight is itself related to healthy prenatal development.

Causal association between particulate matter 2.5 and Alzheimer's disease: a Mendelian randomization study

Background

Although epidemiological evidence implies a link between exposure to particulate matter (PM) and Alzheimer's disease (AD), establishing causality remains a complex endeavor. In the present study, we used Mendelian randomization (MR) as a robust analytical approach to explore the potential causal relationship between PM exposure and AD risk. We also explored the potential associations between PM exposure and other neurodegenerative diseases.

Methods

Drawing on extensive genome-wide association studies related to PM exposure, we identified the instrumental variables linked to individual susceptibility to PM. Using summary statistics from five distinct neurodegenerative diseases, we conducted two-sample MR analyses to gauge the causal impact of PM on the risk of developing these diseases. Sensitivity analyses were undertaken to evaluate the robustness of our findings. Additionally, we executed multivariable MR (MVMR) to validate the significant causal associations identified in the two-sample MR analyses, by adjusting for potential confounding risk factors.

Results

Our MR analysis identified a notable association between genetically predicted PM2.5 (PM with a diameter of 2.5 μm or less) exposure and an elevated risk of AD (odds ratio, 2.160; 95% confidence interval, 1.481 to 3.149; p < 0.001). A sensitivity analysis supported the robustness of the observed association, thus alleviating concerns related to pleiotropy. No discernible causal relationship was identified between PM and any other neurodegenerative diseases. MVMR analyses-adjusting for smoking, alcohol use, education, stroke, hearing loss, depression, and hypertension-confirmed a persistent causal relationship between PM2.5 and AD. Sensitivity analyses, including MR-Egger and weighted median analyses, also supported this causal association.

Conclusion

The present MR study provides evidence to support a plausible causal connection between PM2.5 exposure and AD. The results emphasize the importance of contemplating air quality interventions as a public health strategy for reducing AD risk.

The genetic landscape of substance use disorders

Substance use disorders represent a significant public health concern with considerable socioeconomic implications worldwide. Twin and family-based studies have long established a heritable component underlying these disorders. In recent years, genome-wide association studies of large, broadly phenotyped samples have identified regions of the genome that harbour genetic risk variants associated with substance use disorders. These regions have enabled the discovery of putative causal genes and improved our understanding of genetic relationships among substance use disorders and other traits. Furthermore, the integration of these data with clinical information has yielded promising insights into how individuals respond to medications, allowing for the development of personalized treatment approaches based on an individual's genetic profile. This review article provides an overview of recent advances in the genetics of substance use disorders and demonstrates how genetic data may be used to reduce the burden of disease and improve public health outcomes.

Screening embryos for polygenic disease risk: a review of epidemiological, clinical, and ethical considerations

BACKGROUND

The genetic composition of embryos generated by in vitro fertilization (IVF) can be examined with preimplantation genetic testing (PGT). Until recently, PGT was limited to detecting single-gene, high-risk pathogenic variants, large structural variants, and aneuploidy. Recent advances have made genome-wide genotyping of IVF embryos feasible and affordable, raising the possibility of screening embryos for their risk of polygenic diseases such as breast cancer, hypertension, diabetes, or schizophrenia. Despite a heated debate around this new technology, called polygenic embryo screening (PES; also PGT-P), it is already available to IVF patients in some countries. Several articles have studied epidemiological, clinical, and ethical perspectives on PES; however, a comprehensive, principled review of this emerging field is missing.

OBJECTIVE AND RATIONALE

This review has four main goals. First, given the interdisciplinary nature of PES studies, we aim to provide a self-contained educational background about PES to reproductive specialists interested in the subject. Second, we provide a comprehensive and critical review of arguments for and against the introduction of PES, crystallizing and prioritizing the key issues. We also cover the attitudes of IVF patients, clinicians, and the public towards PES. Third, we distinguish between possible future groups of PES patients, highlighting the benefits and harms pertaining to each group. Finally, our review, which is supported by ESHRE, is intended to aid healthcare professionals and policymakers in decision-making regarding whether to introduce PES in the clinic, and if so, how, and to whom.

SEARCH METHODS

We searched for PubMed-indexed articles published between 1/1/2003 and 1/3/2024 using the terms 'polygenic embryo screening', 'polygenic preimplantation', and 'PGT-P'. We limited the review to primary research papers in English whose main focus was PES for medical conditions. We also included papers that did not appear in the search but were deemed relevant.

OUTCOMES

The main theoretical benefit of PES is a reduction in lifetime polygenic disease risk for children born after screening. The magnitude of the risk reduction has been predicted based on statistical modelling, simulations, and sibling pair analyses. Results based on all methods suggest that under the best-case scenario, large relative risk reductions are possible for one or more diseases. However, as these models abstract several practical limitations, the realized benefits may be smaller, particularly due to a limited number of embryos and unclear future accuracy of the risk estimates. PES may negatively impact patients and their future children, as well as society. The main personal harms are an unindicated IVF treatment, a possible reduction in IVF success rates, and patient confusion, incomplete counselling, and choice overload. The main possible societal harms include discarded embryos, an increasing demand for 'designer babies', overemphasis of the genetic determinants of disease, unequal access, and lower utility in people of non-European ancestries. Benefits and harms will vary across the main potential patient groups, comprising patients already requiring IVF, fertile people with a history of a severe polygenic disease, and fertile healthy people. In the United States, the attitudes of IVF patients and the public towards PES seem positive, while healthcare professionals are cautious, sceptical about clinical utility, and concerned about patient counselling.

WIDER IMPLICATIONS

The theoretical potential of PES to reduce risk across multiple polygenic diseases requires further research into its benefits and harms. Given the large number of practical limitations and possible harms, particularly unnecessary IVF treatments and discarded viable embryos, PES should be offered only within a research context before further clarity is achieved regarding its balance of benefits and harms. The gap in attitudes between healthcare professionals and the public needs to be narrowed by expanding public and patient education and providing resources for informative and unbiased genetic counselling.

Interpreting disease genome-wide association studies and polygenetic risk scores given eligibility and study design considerations

Genome-wide association studies (GWAS) have been helpful in identifying genetic variants predicting cancer risk and providing new insights into cancer biology. Increasing use of genetically informed care, as well as genetically informed prevention and treatment strategies, have also drawn attention to some of the inherent limitations of cancer genetic data. Specifically, genetic endowment is lifelong. However, those recruited into cancer studies tend to be middle-aged or older people, meaning the exposure most likely starts before recruitment, as opposed to exposure and recruitment aligning, as in a trial or a target trial. Studies in survivors can be biased as a result of depletion of the susceptibles, here specifically due to genetic vulnerability and the cancer of interest or a competing risk. In addition, including prevalent cases in a case-control study will make the genetics of survival with cancer look harmful (Neyman bias). Here, we describe ways of designing GWAS to maximize explanatory power and predictive utility, by reducing selection bias due to only recruiting survivors and reducing Neyman bias due to including prevalent cases alongside using other techniques, such as selection diagrams, age-stratification, and Mendelian randomization, to facilitate GWAS interpretability and utility.

Analysis of admixed Greenlandic siblings shows that the mean genotypic values for metabolic phenotypes differ between Inuit and Europeans

BACKGROUND

Disease prevalence and mean phenotype values differ between many populations, including Inuit and Europeans. Whether these differences are partly explained by genetic differences or solely due to differences in environmental exposures is still unknown, because estimates of the genetic contribution to these means, which we will here refer to as mean genotypic values, are easily confounded, and because studies across genetically diverse populations are lacking.

METHODS

Leveraging the unique genetic properties of the small, admixed and historically isolated Greenlandic population, we estimated the differences in mean genotypic value between Inuit and European genetic ancestry using an admixed sibling design. Analyses were performed across 26 metabolic phenotypes, in 1474 admixed sibling pairs present in a cohort of 5996 Greenlanders.

RESULTS

After FDR correction for multiple testing, we found significantly lower mean genotypic values in Inuit genetic ancestry compared to European genetic ancestry for body weight (effect size per percentage of Inuit genetic ancestry (se), -0.51 (0.16) kg/%), body mass index (-0.20 (0.06) kg/m2/%), fat percentage (-0.38 (0.13) %/%), waist circumference (-0.42 (0.16) cm/%), hip circumference (-0.38 (0.11) cm/%) and fasting serum insulin levels (-1.07 (0.51) pmol/l/%). The direction of the effects was consistent with the observed mean phenotype differences between Inuit and European genetic ancestry. No difference in mean genotypic value was observed for height, markers of glucose homeostasis, or circulating lipid levels.

CONCLUSIONS

We show that mean genotypic values for some metabolic phenotypes differ between two human populations using a method not easily confounded by possible differences in environmental exposures. Our study illustrates the importance of performing genetic studies in diverse populations.

Dissecting the polygenic contribution of attention-deficit/hyperactivity disorder and autism spectrum disorder on school performance by their relationship with educational attainment

Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorders (ASD) are strongly associated with educational attainment (EA), but little is known about their genetic relationship with school performance and whether these links are explained, in part, by the genetic liability of EA. Here, we aim to dissect the polygenic contribution of ADHD and ASD to school performance, early manifestation of psychopathology and other psychiatric disorders and related traits by their relationship with EA. To do so, we tested the association of polygenic scores for EA, ADHD and ASD with school performance, assessed whether the contribution of the genetic liability of ADHD and ASD to school performance is influenced by the genetic liability of EA, and evaluated the role of EA in the genetic overlap between ADHD and ASD with early manifestation of psychopathology and other psychiatric disorders and related traits in a sample of 4,278 school-age children. The genetic liability for ADHD and ASD dissected by their relationship with EA show differences in their association with school performance and early manifestation of psychopathology, partly mediated by ADHD and ASD symptoms. Genetic variation with concordant effects in ASD and EA contributes to better school performance, while the genetic variation with discordant effects in ADHD or ASD and EA is associated with poor school performance and higher rates of emotional and behavioral problems. Our results strongly support the usage of the genetic load for EA to dissect the genetic and phenotypic heterogeneity of ADHD and ASD, which could help to fill the gap of knowledge of mechanisms underlying educational outcomes.

Genetic prediction of the relationship between metabolic syndrome and colorectal cancer risk: a Mendelian randomization study

BACKGROUND

Despite a growing body of observational studies indicating a potential link between metabolic syndrome and colorectal cancer, a definitive causal relationship has yet to be established. This study aimed to elucidate the causal relationship between metabolic syndrome and colorectal cancer through Mendelian randomization.

METHODS

We screened for instrumental variables associated with metabolic syndrome and its diagnostic components and with colorectal cancer through the use of a genome-wide association study database, and conducted a preliminary Mendelian randomization analysis. To corroborate the dependability of our conclusions, an additional dataset was used for replication analysis in a Mendelian randomization method, which was further integrated with a meta-analysis.

RESULTS

Preliminary analysis using the inverse variance weighted method revealed positive correlations between metabolic syndrome (OR [95% CI] = 1.37[1.15-1.63], P = 5.02 × 10-4) and waist circumference (OR [95% CI] = 1.39[1.21-1.61], P = 7.38 × 10-6) and the risk of colorectal cancer. Replication analysis also revealed the same results: metabolic syndrome (OR [95% CI] = 1.24[1.02-1.51], P = 0.030) and waist circumference (OR [95% CI] = 1.23[1.05-1.45], P = 0.013). The meta-analysis results further confirmed the associations between metabolic syndrome (OR [95% CI] = 1.31[1.15-1.49], P < 0.001) and waist circumference (OR [95% CI] = 1.32[1.18-1.47], P < 0.001) and colorectal cancer.

CONCLUSION

Our study indicated that metabolic syndrome increases the risk of CRC, particularly in patients with abdominal obesity.

CORRECTING MODEL MISSPECIFICATION IN RELATIONSHIP ESTIMATES

The datasets of large genotyping biobanks and direct-to-consumer genetic testing companies contain many related individuals. Until now, it has been widely accepted that the most distant relationships that can be detected are around fifteen degrees (approximately 8 th cousins) and that practical relationship estimates have a ceiling around ten degrees (approximately 5 th cousins). However, we show that these assumptions are incorrect and that they are due to a misapplication of relationship estimators. In particular, relationship estimators are applied almost exclusively to putative relatives who have been identified because they share detectable tracts of DNA identically by descent (IBD). However, no existing relationship estimator conditions on the event that two individuals share at least one detectable segment of IBD anywhere in the genome. As a result, the relationship estimates obtained using existing estimators are dramatically biased for distant relationships, inferring all sufficiently distant relationships to be around ten degrees regardless of the depth of the true relationship. Moreover, existing relationship estimators are derived under a model that assumes that each pair of related individuals shares a single common ancestor (or mating pair of ancestors). This model breaks down for relationships beyond 10 generations in the past because individuals share many thousands of cryptic common ancestors due to pedigree collapse. We first derive a corrected likelihood that conditions on the event that at least one segment is observed between a pair of putative relatives and we demonstrate that the corrected likelihood largely eliminates the bias in estimates of pairwise relationships and provides a more accurate characterization of the uncertainty in these estimates. We then reformulate the relationship inference problem to account for the fact that individuals share many common ancestors, not just one. We demonstrate that the most distant relationship that can be inferred may be forty degrees or more, rather than ten, extending the time-to-common ancestor from approximately 200 years in the past to approximately 600 years in the past or more. This dramatic increase in the range of relationship estimators makes it possible to infer relationships whose common ancestors lived before historical events such as European settlement of the Americas and the Transatlantic Slave Trade, and possibly much earlier.

Circulating Metabolite Abundances Associated With Risks of Bipolar Disorder, Schizophrenia, and Depression: A Mendelian Randomization Study

BACKGROUND

Preventive measures and treatments for psychiatric disorders are limited. Circulating metabolites are potential candidates for biomarker and therapeutic target identification, given their measurability and essential roles in biological processes.

METHODS

Leveraging large-scale genome-wide association studies, we conducted Mendelian randomization analyses to assess the associations between circulating metabolite abundances and the risks of bipolar disorder, schizophrenia, and depression. Genetic instruments were selected for 94 metabolites measured in the Canadian Longitudinal Study on Aging cohort (N = 8299). We repeated Mendelian randomization analyses based on the UK Biobank, INTERVAL, and EPIC (European Prospective Investigation into Cancer)-Norfolk studies.

RESULTS

After validating Mendelian randomization assumptions and colocalization evidence, we found that a 1 SD increase in genetically predicted circulating abundances of eicosapentaenoate and docosapentaenoate was associated with odds ratios of 0.72 (95% CI, 0.65-0.79) and 0.63 (95% CI, 0.55-0.72), respectively, for bipolar disorder. Genetically increased Ω-3 unsaturated fatty acids abundance and Ω-3-to-total fatty acids ratio, as well as genetically decreased Ω-6-to-Ω-3 ratio, were negatively associated with the risk of bipolar disorder in the UK Biobank. Genetically increased circulating abundances of 3 N-acetyl-amino acids were associated with an increased risk of schizophrenia with a maximum odds ratio of 1.31 (95% CI, 1.18-1.44) per 1 SD increase. Furthermore, a 1 SD increase in genetically predicted circulating abundance of hypotaurine was associated with an odds ratio of 0.85 (95% CI, 0.78-0.93) for depression.

CONCLUSIONS

The biological mechanisms that underlie Ω-3 unsaturated fatty acids, NAT8-catalyzed N-acetyl-amino acids, and hypotaurine warrant exploration to identify new biomarkers and potential therapeutic targets.

Genetics of environmental sensitivity to psychiatric and neurodevelopmental phenotypes: evidence from GWAS of monozygotic twins

Individual sensitivity to environmental exposures may be genetically influenced. This genotype-by-environment interplay implies differences in phenotypic variance across genotypes. However, environmental sensitivity genetic variants have proven challenging to detect. GWAS of monozygotic twin differences is a family-based variance analysis method, which is more robust to systemic biases that impact population-based methods. We combined data from up to 21,792 monozygotic twins (10,896 pairs) from 11 studies to conduct the largest GWAS meta-analysis of monozygotic phenotypic differences in children and adolescents/adults for seven psychiatric and neurodevelopmental phenotypes: attention deficit hyperactivity disorder (ADHD) symptoms, autistic traits, anxiety and depression symptoms, psychotic-like experiences, neuroticism, and wellbeing. The SNP-heritability of variance in these phenotypes were estimated (h2: 0% to 18%), but were imprecise. We identified a total of 13 genome-wide significant associations (SNP, gene, and gene-set), including genes related to stress-reactivity for depression, growth factor-related genes for autistic traits and catecholamine uptake-related genes for psychotic-like experiences. Monozygotic twins are an important new source of evidence about the genetics of environmental sensitivity.

Causal roles of educational duration in bone mineral density and risk factors for osteoporosis: a Mendelian randomization study

BACKGROUND

Educational duration might play a vital role in preventing the occurrence and development of osteoporosis(OP).

PURPOSE

To assess the causal effect of educational duration on bone mineral density(BMD) and risk factors for OP by Mendelian randomization(MR) study.

METHODS

The causal relationship was analyzed using data from genome-wide association study(GWAS). Inverse variance weighting (IVW) was used as the main analysis method. Horizontal pleiotropy was identified by MR-Egger intercept test, MR pleiotropy residual sum and outlier (MR-PRESSO) test. The leave-one-out method was used as a sensitivity analysis.

RESULTS

The IVW results indicated that there was a positive causal relationship between educational duration and BMD (OR = 1.012, 95%CI:1.003-1.022), physical activity(PA) (OR = 1.156, 95%CI:1.032-1.295), calcium consumption (OR = 1.004, 95%CI:1.002-1.005), and coffee intake (OR = 1.019, 95%CI:1.014-1.024). There was a negative association between whole body fat mass (OR = 0.950, 95%CI:0.939-0.961), time for vigorous PA (OR = 0.955, 95%CI:0.939-0.972), sunbath (OR = 0.987, 95%CI:0.986-0.989), salt consumption (OR = 0.965, 95%CI:0.959-0.971), fizzy drink intake (OR = 0.985, 95%CI:0.978-0.992), smoking (OR = 0.969, 95%CI:0.964-0.975), and falling risk (OR = 0.976, 95%CI:0.965-0.987). There was no significant association between educational duration and lean mass, time for light-to-moderate PA, milk intake, and alcohol intake. Horizontal pleiotropy was absent in this study. The results were robust under sensitivity analyses.

CONCLUSION

A longer educational duration was causally linked with increased BMD. No causal relationship had been found between educational duration and lean mass, time for light-to-moderate PA, milk intake, and alcohol consumption as risk factors for osteoporosis.

Evaluating the causal relationship between educational attainment and mental health

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

Pathways between a polygenic index for education and years of completed schooling: the presentation of self and assessment of others

Polygenic scores (PGS) are broadly misconstrued as reflecting direct causal genetic effects on their respective phenotypes. While this assumption might be accurate for some anthropometric traits like height, more complex traits such as educational attainment show very large indirect effects that stem from many sources. One unexplored source of confounding is the possibility of evocative gene-environment correlation (rGE). Using data from the National Longitudinal Study of Adolescent to Adult Health, we examine the relationship between interviewer assessments of respondent appearance as a function of education PGS. We show a bivariate association between educational PGS and 1) perceived grooming, 2) physical attractiveness, and 3) personality. We then regress years of education on the educational PGS and show that very little of the association (~1-2%) is mediated by attractiveness or personality but 7.5% of the baseline association is confounded with how others may perceive grooming. These results highlight the importance of social-behavioral mechanisms that may link specific genotypes to successful transitions through high school and college and continue to bridge research from the social and biological sciences.

Interpreting population- and family-based genome-wide association studies in the presence of confounding

A central aim of genome-wide association studies (GWASs) is to estimate direct genetic effects: the causal effects on an individual's phenotype of the alleles that they carry. However, estimates of direct effects can be subject to genetic and environmental confounding and can also absorb the "indirect" genetic effects of relatives' genotypes. Recently, an important development in controlling for these confounds has been the use of within-family GWASs, which, because of the randomness of mendelian segregation within pedigrees, are often interpreted as producing unbiased estimates of direct effects. Here, we present a general theoretical analysis of the influence of confounding in standard population-based and within-family GWASs. We show that, contrary to common interpretation, family-based estimates of direct effects can be biased by genetic confounding. In humans, such biases will often be small per-locus, but can be compounded when effect-size estimates are used in polygenic scores (PGSs). We illustrate the influence of genetic confounding on population- and family-based estimates of direct effects using models of assortative mating, population stratification, and stabilizing selection on GWAS traits. We further show how family-based estimates of indirect genetic effects, based on comparisons of parentally transmitted and untransmitted alleles, can suffer substantial genetic confounding. We conclude that, while family-based studies have placed GWAS estimation on a more rigorous footing, they carry subtle issues of interpretation that arise from confounding.

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.

Genome-wide association studies have problems due to confounding: Are family-based designs the answer?

Genome-wide association studies (GWASs) can be affected by confounding. Family-based GWAS uses random, within-family genetic variation to avoid this. A study in PLOS Biology details how different sources of confounding affect GWAS and whether family-based designs offer a solution.

Age at menarche and idiopathic pulmonary fibrosis: a two-sample mendelian randomization study

BACKGROUND

Sex difference in the incidence rate of idiopathic pulmonary fibrosis (IPF) indicates that estrogen has a certain protective effect on the disease. Nevertheless, there is a dearth of study investigating the association between factors pertaining to endogenous estrogen exposure level, such as age at menarche (AAM) in women, and IPF. Our study intended to employ Mendelian randomization (MR) method to elucidate the causal association between AAM and IPF.

METHODS

Our study utilized AAM as a measure of endogenous estrogen exposure and investigated its causal effect on the risk of IPF through MR. We employed the inverse variance weighted (IVW) method to assess the causal relationship between AAM and IPF risk, with supplementary analyses conducted using the weighted median estimator (WME) and MR-Egger method. Several sensitivity analyses were performed to assess the dependability of MR estimates.

RESULTS

A total of 9 selected single nucleotide polymorphisms (SNPs) significantly associated with AAM were selected as instrumental variables. The IVW method showed that genetically later AAM was associated with an increased risk of IPF (odds ratio [OR] = 1.0014, 95%confidence interval [CI] = 1.0005-1.0023, p = 0.001). The median weighting method and the MR-Egger method obtained similar estimates, and no heterogeneity or pleiotropy was found, indicating that the results were robust.

CONCLUSIONS

Our MR study suggested a causal relationship between a later onset of menarche and a heightened susceptibility to IPF.

Computer gaming alters resting-state brain networks, enhancing cognitive and fluid intelligence in players: evidence from brain imaging-derived phenotypes-wide Mendelian randomization

The debate on whether computer gaming enhances players' cognitive function is an ongoing and contentious issue. Aiming to delve into the potential impacts of computer gaming on the players' cognitive function, we embarked on a brain imaging-derived phenotypes (IDPs)-wide Mendelian randomization (MR) study, utilizing publicly available data from a European population. Our findings indicate that computer gaming has a positive impact on fluid intelligence (odds ratio [OR] = 6.264, P = 4.361 × 10-10, 95% confidence interval [CI] 3.520-11.147) and cognitive function (OR = 3.322, P = 0.002, 95% CI 1.563-7.062). Out of the 3062 brain IDPs analyzed, only one phenotype, IDP NET100 0378, was significantly influenced by computer gaming (OR = 4.697, P = 1.10 × 10-5, 95% CI 2.357-9.361). Further MR analysis suggested that alterations in the IDP NET100 0378 caused by computer gaming may be a potential factor affecting fluid intelligence (OR = 1.076, P = 0.041, 95% CI 1.003-1.153). Our MR study lends support to the notion that computer gaming can facilitate the development of players' fluid intelligence by enhancing the connectivity between the motor cortex in the resting-state brain and key regions such as the left dorsolateral prefrontal cortex and the language center.

Genetic influences on depression and selection into adverse life experiences

Genome-wide association studies find that a large number of genetic variants jointly influence the risk of depression, which is summarized by polygenic indices (PGIs) of depressive symptoms and major depression. But PGIs by design remain agnostic about the causal mechanisms linking genes to depression. Meanwhile, the role of adverse life experiences in shaping depression risk is well-documented, including via gene-environment correlation. Building on theoretical work on dynamic and contingent genetic selection, we suggest that genetic influences may lead to differential selection into negative life experiences, forging gene-environment correlations that manifest in various permutations of depressive behaviors and environmental adversities. We also examine the extent to which apparent genetic influences may reflect spurious associations due to factors such as indirect genetic effects. Using data from two large surveys of middle-aged and older US adults, we investigate to what extent a PGI of depression predicts the risk of 27 different adversities. Further, to glean insights about the kinds of processes that might lead to gene-environment correlation, we augment these analyses with data from an original preregistered survey to measure cultural understandings of the behavioral dependence of various adversities. We find that the PGI predicts the risk of majority of adversities, net of class background and prior depression, and that the selection risk is greater for adversities typically perceived as being dependent on peoples' own behaviors. Taken together, our findings suggest that the PGI of depression largely picks up the risk of behaviorally-influenced adversities, but to a lesser degree also captures other environmental influences. The results invite further exploration into the behavioral and interactional processes that lie along the pathways intervening between genetic differences and wellbeing.

Quantifying the Relative Importance of Genetics and Environment on the Comorbidity between Mental- and Cardiometabolic Disorders: A Comprehensive Analysis of National Register Data from 17 million Scandinavians

Mental disorders (MDs) are leading causes of disability and premature death worldwide, partly due to high comorbidity with cardiometabolic disorders (CMDs). Reasons for this comorbidity are still poorly understood. We leverage nation-wide health records and complete genealogies of Denmark and Sweden (n=17 million) to reveal the genetic and environmental contributions underlying the observed comorbidity between six MDs and 14 CMDs. Genetic factors contributed about 50% to the comorbidity of schizophrenia, affective disorders, and autism spectrum disorder with CMDs, whereas the comorbidity of attention-deficit/hyperactivity disorder and anorexia with CMDs was mainly or fully driven by environmental factors. These findings provide causal insight to guide clinical and scientific initiatives directed at achieving mechanistic understanding as well as preventing and alleviating the consequences of these disorders.

Genetic and molecular architecture of complex traits

Human genetics has emerged as one of the most dynamic areas of biology, with a broadening societal impact. In this review, we discuss recent achievements, ongoing efforts, and future challenges in the field. Advances in technology, statistical methods, and the growing scale of research efforts have all provided many insights into the processes that have given rise to the current patterns of genetic variation. Vast maps of genetic associations with human traits and diseases have allowed characterization of their genetic architecture. Finally, studies of molecular and cellular effects of genetic variants have provided insights into biological processes underlying disease. Many outstanding questions remain, but the field is well poised for groundbreaking discoveries as it increases the use of genetic data to understand both the history of our species and its applications to improve human health.

Attention-deficit/hyperactivity disorder

Attention-deficit/hyperactivity disorder (ADHD; also known as hyperkinetic disorder) is a common neurodevelopmental condition that affects children and adults worldwide. ADHD has a predominantly genetic aetiology that involves common and rare genetic variants. Some environmental correlates of the disorder have been discovered but causation has been difficult to establish. The heterogeneity of the condition is evident in the diverse presentation of symptoms and levels of impairment, the numerous co-occurring mental and physical conditions, the various domains of neurocognitive impairment, and extensive minor structural and functional brain differences. The diagnosis of ADHD is reliable and valid when evaluated with standard diagnostic criteria. Curative treatments for ADHD do not exist but evidence-based treatments substantially reduce symptoms and/or functional impairment. Medications are effective for core symptoms and are usually well tolerated. Some non-pharmacological treatments are valuable, especially for improving adaptive functioning. Clinical and neurobiological research is ongoing and could lead to the creation of personalized diagnostic and therapeutic approaches for this disorder.

PheWAS-based clustering of Mendelian Randomisation instruments reveals distinct mechanism-specific causal effects between obesity and educational attainment

Mendelian Randomisation (MR) estimates causal effects between risk factors and complex outcomes using genetic instruments. Pleiotropy, heritable confounders, and heterogeneous causal effects violate MR assumptions and can lead to biases. To alleviate these, we propose an approach employing a Phenome-Wide association Clustering of the MR instruments (PWC-MR) and apply this method to revisit the surprisingly large apparent causal effect of body mass index (BMI) on educational attainment (EDU): [Formula: see text] = -0.19 [-0.22, -0.16]. First, we cluster 324 BMI-associated genetic instruments based on their association with 407 traits in the UK Biobank, which yields six distinct groups. Subsequent cluster-specific MR reveals heterogeneous causal effect estimates on EDU. A cluster enriched for socio-economic indicators yields the largest BMI-on-EDU causal effect estimate ([Formula: see text] = -0.49 [-0.56, -0.42]) whereas a cluster enriched for body-mass specific traits provides a more likely estimate ([Formula: see text] = -0.09 [-0.13, -0.05]). Follow-up analyses confirms these findings: within-sibling MR ([Formula: see text] = -0.05 [-0.09, -0.01]); MR for childhood BMI on EDU ([Formula: see text] = -0.03 [-0.06, -0.002]); step-wise multivariable MR ([Formula: see text] = -0.05 [-0.07, -0.02]) where socio-economic indicators are jointly modelled. Here we show how the in-depth examination of the BMI-EDU causal relationship demonstrates the utility of our PWC-MR approach in revealing distinct pleiotropic pathways and confounder mechanisms.

Socio-cultural practices may have affected sex differences in stature in Early Neolithic Europe

The rules and structure of human culture impact health as much as genetics or environment. To study these relationships, we combine ancient DNA (n = 230), skeletal metrics (n = 391), palaeopathology (n = 606) and dietary stable isotopes (n = 873) to analyse stature variation in Early Neolithic Europeans from North Central, South Central, Balkan and Mediterranean regions. In North Central Europe, stable isotopes and linear enamel hypoplasias indicate high environmental stress across sexes, but female stature is low, despite polygenic scores identical to males, and suggests that cultural factors preferentially supported male recovery from stress. In Mediterranean populations, sexual dimorphism is reduced, indicating male vulnerability to stress and no strong cultural preference for males. Our analysis indicates that biological effects of sex-specific inequities can be linked to cultural influences at least as early as 7,000 yr ago, and culture, more than environment or genetics, drove height disparities in Early Neolithic Europe.

Causal Associations of Modifiable Risk Factors With Migraine: Evidence From Mendelian Randomization Analysis

Background and objectives The exact etiology of migraine is unknown; however, it is likely a mixture of genetic and non-genetic factors including lifestyle variables like smoking and diet. This study aims to assess the causal effect of modifiable risk factors on the risk of migraine using two-sample Mendelian randomization. Materials and methods The study used publicly available genome-wide significant single nucleotide polymorphisms (SNPs). The study evaluated a diverse smoking exposure, encompassing age at smoking initiation, smoking intensity, and maternal smoking, alongside other pertinent risk factors, namely key dietary aspects, coffee consumption, BMI, and physical activity. Self-reported migraine was the outcome of the study. The genetic data for migraine were obtained from the FinnGen (Finland) and the UK Biobank (United Kingdom) cohorts. Results With sample sizes ranging from 64,949 to 632,802 for each risk factor collected from several consorts, the study included a total of 282 SNPs for all risk factors. The findings demonstrated that in the FinnGen consortium, genetically estimated dietary factors as well as BMI, were significantly associated with the risk of migraine (OR 0.765 per single unit of BMI, p = 0.011; OR 0.468 per one SD higher cheese intake, p = 0.012; OR 0.286 per one SD higher salad intake, p = 0.004, and 0.625 per one SD higher coffee consumption, p = 0.003, respectively). The results also showed that in the UK Biobank specifically, a genetically estimated history of maternal smoking was significantly associated with an elevated risk of migraine (OR=1.02, p=0.004). Conclusions The latest study implies a connection between maternal smoking and a heightened risk of migraines, whereas cheese intake, salad intake, coffee consumption, BMI, and physical activity are associated with a lower risk of migraine development.

The effects of psychiatric disorders on the risk of chronic heart failure: a univariable and multivariable Mendelian randomization study

Background

Substantial evidence suggests an association between psychiatric disorders and chronic heart failure. However, further investigation is needed to confirm the causal relationship between these psychiatric disorders and chronic heart failure. To address this, we evaluated the potential effects of five psychiatric disorders on chronic heart failure using two-sample Mendelian Randomization (MR).

Methods

We selected single nucleotide polymorphisms (SNPs) associated with chronic heart failure and five psychiatric disorders (Attention-Deficit Hyperactivity Disorder (ADHD), Autism Spectrum Disorder (ASD), Major Depression, Bipolar Disorder and Schizophrenia (SCZ)). Univariable (UVMR) and multivariable two-sample Mendelian Randomization (MVMR) were employed to assess causality between these conditions. Ever smoked and alcohol consumption were controlled for mediating effects in the multivariable MR. The inverse variance weighting (IVW) and Wald ratio estimator methods served as the primary analytical methods for estimating potential causal effects. MR-Egger and weighted median analyses were also conducted to validate the results. Sensitivity analyses included the funnel plot, leave-one-out, and MR-Egger intercept tests. Additionally, potential mediators were investigated through risk factor analyses.

Results

Genetically predicted heart failure was significantly associated with ADHD (odds ratio (OR), 1.12; 95% CI, 1.04-1.20; p = 0.001), ASD (OR, 1.29; 95% CI, 1.07-1.56; p = 0.008), bipolar disorder (OR, 0.89; 95% CI, 0.83-0.96; p = 0.001), major depression (OR, 1.15; 95% CI, 1.03-1.29; p = 0.015), SCZ (OR, 1.04; 95% CI, 1.00-1.07; p = 0.024). Several risk factors for heart failure are implicated in the above cause-and-effect relationship, including ever smoked and alcohol consumption.

Conclusion

Our study demonstrated ADHD, ASD, SCZ and major depression may have a causal relationship with an increased risk of heart failure. In contrast, bipolar disorder was associated with a reduced risk of heart failure, which could potentially be mediated by ever smoked and alcohol consumption. Therefore, prevention strategies for heart failure should also incorporate mental health considerations, and vice versa.

More than nature and nurture, indirect genetic effects on children's academic achievement are consequences of dynastic social processes

Families transmit genes and environments across generations. When parents' genetics affect their children's environments, these two modes of inheritance can produce an 'indirect genetic effect'. Such indirect genetic effects may account for up to half of the estimated genetic variance in educational attainment. Here we tested if indirect genetic effects reflect within-nuclear-family transmission ('genetic nurture') or instead a multi-generational process of social stratification ('dynastic effects'). We analysed indirect genetic effects on children's academic achievement in their fifth to ninth years of schooling in N = 37,117 parent-offspring trios in the Norwegian Mother, Father, and Child Cohort Study (MoBa). We used pairs of genetically related families (parents were siblings, children were cousins; N = 10,913) to distinguish within-nuclear-family genetic-nurture effects from dynastic effects shared by cousins in different nuclear families. We found that indirect genetic effects on children's academic achievement cannot be explained by processes that operate exclusively within the nuclear family.

Causality between rheumatoid arthritis and the risk of cognitive impairment: a Mendelian randomization study

BACKGROUND

There is mounting proof that rheumatoid arthritis (RA) and cognitive decline are related. These studies, however, have not all been uniform, and others have not discovered such a correlation. It is essential to investigate the link between RA and cognitive decline.

METHOD

We conducted a Mendelian randomization analysis utilizing three different publicly accessible RA GWAS summary datasets and a variety of meticulously verified instrumental variables. We mostly used inverse variance weighting (IVW), as well as MR-Egger, weighted median, MR-PRESSO, and several sensitivity analyses, to figure out the link between RA and cognitive impairment (CI).

RESULTS

Our MR study identified the causality between RA and declining cognitive performance (β = - 0.010, 95% CI of - 0.017 to - 0.003, P = 4.33E-03) and cognitive function (β = - 0.029, 95% CI of - 0.053 to - 0.005, P = 1.93E-02). The consistent direction of the connection is revealed by sensitivity analysis utilizing the weighted median and the MR-Egger method. Furthermore, we reproduced our findings across two additional RA datasets and found identical outcomes, strengthening the validity of our findings.

CONCLUSION

This study offers proof of causality between RA and an increased risk of CI. Our findings highlight the importance of examining RA patients for cognitive ability, which may open up fresh ideas for the prevention of CI.

The selection landscape and genetic legacy of ancient Eurasians

The Holocene (beginning around 12,000 years ago) encompassed some of the most significant changes in human evolution, with far-reaching consequences for the dietary, physical and mental health of present-day populations. Using a dataset of more than 1,600 imputed ancient genomes1, we modelled the selection landscape during the transition from hunting and gathering, to farming and pastoralism across West Eurasia. We identify key selection signals related to metabolism, including that selection at the FADS cluster began earlier than previously reported and that selection near the LCT locus predates the emergence of the lactase persistence allele by thousands of years. We also find strong selection in the HLA region, possibly due to increased exposure to pathogens during the Bronze Age. Using ancient individuals to infer local ancestry tracts in over 400,000 samples from the UK Biobank, we identify widespread differences in the distribution of Mesolithic, Neolithic and Bronze Age ancestries across Eurasia. By calculating ancestry-specific polygenic risk scores, we show that height differences between Northern and Southern Europe are associated with differential Steppe ancestry, rather than selection, and that risk alleles for mood-related phenotypes are enriched for Neolithic farmer ancestry, whereas risk alleles for diabetes and Alzheimer's disease are enriched for Western hunter-gatherer ancestry. Our results indicate that ancient selection and migration were large contributors to the distribution of phenotypic diversity in present-day Europeans.

Lifestyle differences between co-twins are associated with decreased similarity in their internal and external exposome profiles

Whether differences in lifestyle between co-twins are reflected in differences in their internal or external exposome profiles remains largely underexplored. We therefore investigated whether within-pair differences in lifestyle were associated with within-pair differences in exposome profiles across four domains: the external exposome, proteome, metabolome and epigenetic age acceleration (EAA). For each domain, we assessed the similarity of co-twin profiles using Gaussian similarities in up to 257 young adult same-sex twin pairs (54% monozygotic). We additionally tested whether similarity in one domain translated into greater similarity in another. Results suggest that a lower degree of similarity in co-twins' exposome profiles was associated with greater differences in their behavior and substance use. The strongest association was identified between excessive drinking behavior and the external exposome. Overall, our study demonstrates how social behavior and especially substance use are connected to the internal and external exposomes, while controlling for familial confounders.

Unraveling the Complex Relationship Between Gastroesophageal Reflux Disease, Lifestyle Factors, and Interstitial Lung Disease: Insights From Two-Sample Mendelian Randomization Analyses

Background Although the cause of interstitial lung disease (ILD) remains uncertain, it is believed to be a combination of genetic and non-inherited factors, such as smoking and diet. This research aims to evaluate the impact of gastroesophageal reflux disease (GERD) and other modifiable risk factors on the likelihood of developing ILD by utilizing two-sample Mendelian randomization. Methodology The research utilized publicly accessible single-nucleotide polymorphisms (SNPs) that were deemed significant on a genome-wide scale. These SNPs were chosen from prior studies conducted by various consortia. The study examined GERD and a wide range of smoking habits, including the age at which individuals started smoking, the intensity of their smoking, and whether their mothers smoked. Additionally, the study considered other relevant risk factors such as key dietary factors, coffee consumption, body mass index (BMI), and physical activity. The study focused on self-reported ILD as its outcome measure. The genetic information for ILD was sourced from the FinnGen and UK Biobank (UKB) cohorts. Results The study encompassed a wide range of sample sizes, varying from 64,949 to 632,802, for each risk factor collected from multiple consortia. In total, 593 SNPs were included for all risk factors. The findings revealed significant associations between genetically estimated GERD, dietary factors, BMI, and the risk of ILD within the FinnGen consortium. The odds ratios (ORs) indicated an increase in the risk of ILD per unit of GERD (OR = 1.17, p = 0.001), smoking initiation (OR = 1.10, p < 0.05), BMI (OR = 1.15, p = 0.006), and low-density lipoprotein (LDL) (OR = 1.10, p = 0.02). On the other hand, there was a decrease in the risk of ILD per unit increase in coffee intake (OR = 0.64, p = 0.01) and physical activity (OR = 0.79, p=0.03). Additionally, the results demonstrated a significant association between genetically estimated GERD (OR = 1.01, p < 0.05), coffee intake (OR = 1.14, p=0.03), and high-density lipoproteins (HDL) (OR = 1.01, p=0.04) and increased risk of ILD specifically within the UKB. Conclusions This research indicates that the development of ILDs may be causally associated with GERD and various factors such as coffee intake, smoking, BMI, physical activity, LDL, and HDL These results hold great importance in terms of devising effective strategies for the treatment and prevention of ILDs.

Understanding Internal Migration: A Research Note Providing an Assessment of Migration Selection With Genetic Data

Migration is selective, resulting in inequalities between migrants and nonmigrants. However, investigating migration selection is empirically challenging because combined pre- and post-migration data are rarely available. We propose an alternative approach to assessing internal migration selection by integrating genetic data, enabling an investigation of migration selection with cross-sectional data collected post-migration. Using data from the UK Biobank, we utilized standard tools from statistical genetics to conduct a genome-wide association study (GWAS) for migration distance. We then calculated genetic correlations to compare GWAS results for migration with those for other characteristics. Given that individual genetics are determined at conception, these analyses allow a unique exploration of the association between pre-migration characteristics and migration. Results are generally consistent with the healthy migrant literature: genetics correlated with longer migration distance are associated with higher socioeconomic status and better health. We also extended the analysis to 53 traits and found novel correlations between migration and several physical health, mental health, personality, and sociodemographic traits.

Distilling causality between physical activity traits and obesity via Mendelian randomization

BACKGROUND

Whether obesity is a cause or consequence of low physical activity levels and more sedentary time has not yet been fully elucidated. Better instrumental variables and a more thorough consideration of potential confounding variables that may influence the causal inference between physical activity and obesity are needed.

METHODS

Leveraging results from our recent genome-wide association study for leisure time moderate-to-vigorous intensity (MV) physical activity and screen time, we here disentangle the causal relationships between physical activity, sedentary behavior, education-defined by years of schooling-and body mass index (BMI), using multiple univariable and multivariable Mendelian Randomization (MR) approaches.

RESULTS

Univariable MR analyses suggest bidirectional causal effects of physical activity and sedentary behavior with BMI. However, multivariable MR analyses that take years of schooling into account suggest that more MV physical activity causes a lower BMI, and a higher BMI causes more screen time, but not vice versa. In addition, more years of schooling causes higher levels of MV physical activity, less screen time, and lower BMI.

CONCLUSIONS

In conclusion, our results highlight the beneficial effect of education on improved health and suggest that a more physically active lifestyle leads to lower BMI, while sedentary behavior is a consequence of higher BMI.

Socioeconomic status and severe mental disorders: a bidirectional multivariable Mendelian randomisation study

BACKGROUND

Despite the evidence supporting the relationship between socioeconomic status (SES) and severe mental disorders (SMD), the directionality of the associations between income or education and mental disorders is still poorly understood.

OBJECTIVE

To investigate the potential bidirectional causal relationships between genetic liability to the two main components of SES (income and educational attainment (EA)) on three SMD: schizophrenia, bipolar disorder (BD) and depression.

METHODS

We performed a bidirectional, two-sample univariable Mendelian randomisation (UVMR) and multivariable Mendelian randomisation (MVMR) study using SES phenotypes (income, n=397 751 and EA, n=766 345) and SMD (schizophrenia, n=127 906; BD, n=51 710 and depression, n=500 119) genome-wide association studies summary-statistics to dissect the potential direct associations of income and EA with SMD.

FINDINGS

UVMR showed that genetic liability to higher income was associated with decreased risk of schizophrenia and depression, with a smaller reverse effect of schizophrenia and depression on income. Effects were comparable after adjusting for EA in the MVMR. UMVR showed bidirectional negative associations between genetic liability to EA and depression and positive associations between genetic liability to EA and BD, with no significant effects on schizophrenia. After accounting for income, MVMR showed a bidirectional positive direction between genetic liability to EA and BD and schizophrenia but not with depression.

CONCLUSIONS

Our results suggest a heterogeneous link pattern between SES and SMD. We found a negative bidirectional association between genetic liability to income and the risk of schizophrenia and depression. On the contrary, we found a positive bidirectional relationship of genetic liability to EA with schizophrenia and BD, which only becomes apparent after adjusting for income in the case of schizophrenia.

CLINICAL IMPLICATIONS

These findings shed light on the directional mechanisms between social determinants and mental disorders and suggest that income and EA should be studied separately in relation to mental illness.

Causal interpretations of family GWAS in the presence of heterogeneous effects

Family-based genome-wide association studies (GWAS) have emerged as a gold standard for assessing causal effects of alleles and polygenic scores. Notably, family studies are often claimed to provide an unbiased estimate of the average causal effect (or average treatment effect; ATE) of an allele, on the basis of an analogy between the random transmission of alleles from parents to children and a randomized controlled trial. Here, we show that this interpretation does not hold in general. Because Mendelian segregation only randomizes alleles among children of heterozygotes, the effects of alleles in the children of homozygotes are not observable. Consequently, if an allele has different average effects in the children of homozygotes and heterozygotes, as can arise in the presence of gene-by-environment interactions, gene-by-gene interactions, or differences in LD patterns, family studies provide a biased estimate of the average effect in the sample. At a single locus, family-based association studies can be thought of as providing an unbiased estimate of the average effect in the children of heterozygotes (i.e., a local average treatment effect; LATE). This interpretation does not extend to polygenic scores, however, because different sets of SNPs are heterozygous in each family. Therefore, other than under specific conditions, the within-family regression slope of a PGS cannot be assumed to provide an unbiased estimate for any subset or weighted average of families. Instead, family-based studies can be reinterpreted as enabling an unbiased estimate of the extent to which Mendelian segregation at loci in the PGS contributes to the population-level variance in the trait. Because this estimate does not include the between-family variance, however, this interpretation applies to only (roughly) half of the sample PGS variance. In practice, the potential biases of a family-based GWAS are likely smaller than those arising from confounding in a standard, population-based GWAS, and so family studies remain important for the dissection of genetic contributions to phenotypic variation. Nonetheless, the causal interpretation of family-based GWAS estimates is less straightforward than has been widely appreciated.

Repurposing Antihypertensive and Statin Medications for Spinal Pain: A Mendelian Randomization Study

STUDY DESIGN

Mendelian randomization (MR) study.

OBJECTIVE

To examine whether antihypertensive medications (beta-blockers, calcium channel blockers, and angiotensin-converting enzyme inhibitors) and statins can be repurposed to prevent or treat spinal pain (back or neck pain).

SUMMARY OF BACKGROUND DATA

Observational studies and a recent MR study have found associations between elevated blood pressure and a greater risk of back pain. Observational studies have found associations between hyperlipidemia and statin use and greater risk of back pain. No prior MR studies have examined the effects of antihypertensives or statins on spinal pain.

MATERIALS AND METHODS

This was a two-sample MR study using publicly available summary statistics from large-scale genome-wide association studies (GWAS). Sample sizes in exposure GWASs were n=757,601 (systolic blood pressure) and n=173,082 (low-density lipoprotein cholesterol), and n=1,028,947 for the outcome GWAS of spinal pain defined as health care seeking for any spinal pain-related diagnosis. Genes and cis-acting variants were identified as proxies for the drug targets of interest. MR analyses used inverse-variance weighted meta-analysis. The threshold for statistical significance after correction for multiple testing was P <0.0125.

RESULTS

No statistically significant associations of these medications with spinal pain were found. However, findings were suggestive of a protective effect of beta-blockers on spinal pain risk (odds ratio [OR] 0.84, 95% confidence interval [CI] 0.72-0.98; P =0.03), and calcium channel blockers on greater spinal pain risk (OR 1.12, 95% CI 1.02-1.24; P =0.02).

CONCLUSIONS

A protective effect of beta-blockers on spinal pain was suggested in the current study, consistent with findings from observational studies of various other pain phenotypes. The detrimental effect of calcium channel blockers on spinal pain suggested in the current study must be interpreted in the context of conflicting directions of effect on nonspinal pain phenotypes in other observational studies.This Mendelian randomization study examined whether antihypertensive medications (beta-blockers, calcium channel blockers, and angiotensin-converting enzyme inhibitors) and statins can be repurposed to prevent or treat spinal.This was a two-sample MR study using publicly available summary statistics from large-scale genome-wide association studies ranging size from 173,082 to 1,028,947 adults.While no statistically significant associations were found, a protective effect of beta-blockers on spinal pain was suggested (odds ratio [OR] 0.84, 95% confidence interval [CI] 0.72 to 0.98; p= 0.03), as was a detrimental effect of calcium channel blockers on spinal pain (OR 1.12, 95% CI 1.02 to 1.24; p= 0.02).