Phenome-wide investigation of the causal associations between childhood BMI and adult trait outcomes: a two-sample Mendelian randomization study

Mendelian randomization analysis on the impacts of age at menarche on adult height: A Taiwanese population study

BACKGROUNDS

Ample evidence supports potential influence of age at menarche (AM) on adult height (AH), but multiple confounders may affect causal estimates. To address this issue, the Mendelian randomization (MR) analysis was used to explore the causal impacts of AM on AH.

METHODS

Using data (n = 57,349) from the publicly accessible Taiwan Biobank and randomly splitting them into 2 equal-size subsets, we identified single nucleotide polymorphisms (SNPs) significantly associated with AM in the exploration subset and used these SNPs as instrumental variables to estimate the effects of instruments on AH in the validation subset based on two stage least squares (2SLS) regression. In addition, three more summary statistics-based approaches, namely inverse variance weighted (IVW), MR-Egger, and weighted median (WM) analyses, were used to verify the findings. We also performed heterogeneity and sensitivity analyses to evaluate the robustness of the results.

RESULTS

We identified 4 leading SNPs associated with AM at the genome-wide significant level, whereas rs9409082 may exert some pleiotropic effects on AH. After eliminating rs9409082, the 2SLS analysis indicated that one year delay in genetically determined AM predicted 1.5 cm height gain in adulthood (β = 1.508, 95% confidence interval [0.852, 2.163]). The causal relationship was also supported by WM (β = 1.183, [0.329, 2.038]) and IVW (β = 1.493, [0.523, 2.463]) methods.

CONCLUSIONS

Evidence from the present MR study supports a causal relationship between later AM and taller AH.

A network pharmacological target mendelian randomization study on the neuroprotective effects of active ingredients in mahuang fuzi xixin decoction for multiple sclerosis

Mahuang Fuzi Xixin Decoction (MFX), a traditional Chinese medicine containing 44 volatile components (97.36% total oil), includes key compounds like α-terpenol (13.34%) and 1,2,3-trimethoxy-5-methyl-benzene (22.64%). Using network pharmacology and Mendelian randomization, 24 active compounds were identified targeting MS-related pathways (NF-κB, NLRP3, Toll-like receptor). Genetic variants in CYP450, GSK3B, CYBB, and PON1 correlated with reduced MS risk. In EAE mice, MFX decreased spinal GSK-3B expression (immunofluorescence) and pro-inflammatory factors (ELISA), demonstrating neuroprotection via anti-inflammatory, antioxidative mechanisms and restored GSK-3B levels, highlighting therapeutic potential for MS.

Reassessing the association between age at menarche and cardiovascular disease: observational and Mendelian randomization analyses

AIMS

Observational studies have shown a U-shaped association between age at menarche (AAM) and cardiovascular disease (CVD). We assessed non-linearity of the observational association and the potential causal relationship between AAM and CVD using data from the European Prospective Investigation into Cancer and Nutrition-Cardiovascular Disease (EPIC-CVD) study and the UK Biobank.

METHODS AND RESULTS

We included women without pre-existing myocardial infarction (MI) or stroke at baseline. We estimated hazard ratios for incident MI, ischaemic and haemorrhagic stroke later in life using Cox regression in observational analyses and conducted non-linear Mendelian randomization (MR) based on fractional polynomials and linear MR based on inverse-variance weighted regression. We analysed 283 210 women with a median AAM of 13 (IQR 12-14) years in both EPIC-CVD and the UK Biobank, of which 8468 experienced a MI, 5501 an ischaemic and 1887 a haemorrhagic stroke. The association between AAM and MI and ischaemic stroke was U-shaped with higher risks in women aged ≤12 and ≥16 compared with those aged 13 years at menarche. Our MR analyses found no evidence for non-linearity between genetically proxied AAM and any CVD endpoint later in life, but each year higher genetically proxied AAM was related to a lower risk of MI (hazard ratio 0.92 [95% CI 0.86-0.99]), but not to ischaemic and haemorrhagic stroke.

CONCLUSION

This study supported non-linear observational associations between AAM and MI and ischaemic stroke. MR analyses suggested a causal relationship between higher AAM and risk of MI without an indication for non-linearity. There was no support for a potential causal link with ischaemic and haemorrhagic stroke.

Two-Sample Bidirectional Mendelian Randomization Study With Causal Association Between Metabolic Syndrome and Cerebral Aneurysm

BACKGROUND

We used a two-sample mendelian randomization (MR) method to comprehensively investigate the causality of metabolic syndrome (MetS) or its components, including MetS, triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), fasting blood glucose (FBG), waist circumference (WC), and hypertension (HP), with cerebral aneurysm including nonruptured and ruptured aneurysmal subarachnoid hemorrhage (SAH).

METHODS

By leveraging large-scale genome-wide association study (GWAS) summary statistics of MetS or its components and cerebral aneurysm (nonruptured and SAH) from European, MR, reverse-direction MR, and sensitivity analysis were utilized to quantify the genetic correlations and causal relationships. In addition, we adjusted for multiple comparisons using the false discovery rate (FDR) correction.

RESULTS

Two-sample MR analysis showed that HP was a risk factor for cerebral aneurysm (nonruptured and SAH) with odds ratio (OR) of 58.959 (95% confidence interval [95% CI] = 12.073-287.920, p < 0.001, q < 0.001), and 32.290 (95% CI = 5.615-185.671, p < 0.001, q < 0.001), respectively. HDL-C (OR = 0.836, 95% CI = 0.728-0.960, p = 0.011, q = 0.039) and FBG (OR = 0.626, 95% CI = 0.426-0.919, p = 0.017, q = 0.039) were negatively correlated with cerebral aneurysm (nonruptured). The HDL-C result was inconsistent after adjusting for TG and LDL-C by multivariable MR analysis. In reverse MR analysis, we found that there was no statistical causal association between cerebral aneurysm (nonruptured) and MetS or its components. Genetic liability to cerebral aneurysm (SAH) was inversely associated with HDL-C and FBG but was not associated with others, however, sensitivity analysis showed that few instrumental variables made a big difference.

CONCLUSIONS

Genetically determined elevated FBG level reduces the risk of cerebral aneurysm (nonruptured). However, hypertension increases the risk of cerebral aneurysm (nonruptured and SAH).

Life-course obesity and heart failure: a two-sample Mendelian randomization study

Heart failure is a multifaceted clinical syndrome, with obesity identified as a significant modifiable risk factor. This study employed a two-sample Mendelian randomization (MR) design, incorporating obesity data across life stages, to elucidate the causal link between obesity and heart failure. Data on heart failure from the 2023 Finngen database and genetic predictors of obesity from the IEU OpenGWAS project were analyzed using the IVW method, MR-Egger regression, weighted median, simple mode, weighted mode, and scatter plots. Heterogeneity was assessed with Cochran's Q test, and horizontal pleiotropy with MR-Egger intercept test. Sensitivity to single-nucleotide polymorphisms (SNPs) was tested via leave-one-out analysis, and funnel plots were utilized for visual inspection of horizontal pleiotropy. Statistical powers were also calculated. The MR analysis findings indicate a significant relationship between birth weight and the likelihood of developing heart failure (Odds Ratio [OR] 1.134, 95% Confidence Interval [CI] 1.033-1.245, P = 0.008). In addition, a heightened childhood BMI was found to be a significant predictor of heart failure risk (OR 1.307, 95% CI 1.144-1.494, P = 8.51E-05), as was childhood obesity (OR 1.123, 95% CI 1.074-1.173, P = 2.37E-07). Furthermore, adult BMI sex-combined exhibited a strong correlation with the risk of heart failure (OR 2.365, 95% CI 2.128-2.629, P = 1.91E-57). Sensitivity analyses provided further support for the reliability of these results, with no significant indication of horizontal pleiotropy observed. This study shows that obesity, including childhood obesity, is linked to a higher risk of heart failure. These findings highlight the urgent need for early weight management interventions in public health and clinical settings to reduce heart failure rates.

Inflammatory bowel disease and white matter microstructure: A bidirectional Mendelian randomization study

BACKGROUND

Observational studies have reported changes in the brain white matter (WM) microstructure in patients with inflammatory bowel disease (IBD); however, it remains uncertain whether the relationship between them is causative. The aim of this study is to reveal the potential causal relationship between IBD and WM microstructure through a bidirectional two-sample Mendelian randomization (MR) analysis.

METHODS

We extracted genome-wide association study (GWAS) summary statistics for IBD and WM microstructure from published GWASs. Two-sample MR analysis was conducted to explore the bidirectional causal associations between IBD and WM microstructure, followed by a series of sensitivity analyses to assess the robustness of the results.

RESULTS

Although forward MR analysis results showed no evidence of causality from microstructural WM to IBD, reverse MR showed that genetically predicted IBD, consisting of ulcerative colitis and Crohn's disease, has a significant causal effect on the orientation dispersion index (OD) of the right tapetum (β = -0.029, 95% CI = -0.045 to -0.013, p = 3.63 × 10-4). Further sensitivity analysis confirmed the robustness of the association.

CONCLUSION

Our results suggested the potentially causal association of IBD with reduced OD in the right tapetum.

Relationship between weight-adjusted waist index (WWI) and osteoarthritis: a cross-sectional study using NHANES data

This study aims to evaluate the association between the Weight-Adjusted Waist Index (WWI) and osteoarthritis (OA) utilizing cross-sectional data from the 2005-2014 National Health and Nutrition Examination Survey (NHANES). The study analyzed data from 12,696 participants across the 2005-2014 NHANES cycles to examine differences in demographic, socioeconomic, lifestyle, and health-related variables across WWI quartiles. Multivariable logistic regression models were employed to assess the relationship between WWI and the risk of OA. Receiver Operating Characteristic (ROC) curve analysis was conducted to evaluate and compare the predictive ability of WWI, BMI, waist circumference, and weight in identifying OA risk. Scatter plots were generated to visualize the association between WWI and OA, with linear regression lines illustrating trends and statistical significance. Restricted cubic spline (RCS) analysis was used to further explore the nonlinear relationship between WWI and OA risk. Forest plots were used to display the impact of WWI on OA risk across subgroups such as gender, age, and race, showing that individuals with higher WWI generally exhibit a significantly increased risk of OA. After adjusting for multiple covariates, the findings indicated a significant association between higher WWI and an increased risk of OA. Subgroup analyses, including gender, age, and race, further reinforced the consistent association between WWI and OA risk. In the U.S. adult population, an elevated WWI is significantly associated with an increased risk of OA, suggesting that WWI could serve as a potential indicator for assessing OA risk.

The role of macrophage and adipocyte mitochondrial dysfunction in the pathogenesis of obesity

Obesity has emerged as a prominent global public health concern, leading to the development of numerous metabolic disorders such as cardiovascular diseases, type-2 diabetes mellitus (T2DM), sleep apnea and several system diseases. It is widely recognized that obesity is characterized by a state of inflammation, with immune cells-particularly macrophages-playing a significant role in its pathogenesis through the production of inflammatory cytokines and activation of corresponding pathways. In addition to their immune functions, macrophages have also been implicated in lipogenesis. Additionally, the mitochondrial disorders existed in macrophages commonly, leading to decreased heat production. Meantime, adipocytes have mitochondrial dysfunction and damage which affect thermogenesis and insulin resistance. Therefore, enhancing our comprehension of the role of macrophages and mitochondrial dysfunction in both macrophages and adipose tissue will facilitate the identification of potential therapeutic targets for addressing this condition.

The Association between Obstructive Sleep Apnea and Venous Thromboembolism: A Bidirectional Two-Sample Mendelian Randomization Study

BACKGROUND

 Despite previous observational studies linking obstructive sleep apnea (OSA) to venous thromboembolism (VTE), these findings remain controversial. This study aimed to explore the association between OSA and VTE, including pulmonary embolism (PE) and deep vein thrombosis (DVT), at a genetic level using a bidirectional two-sample Mendelian randomization (MR) analysis.

METHODS

 Utilizing summary-level data from large-scale genome-wide association studies in European individuals, we designed a bidirectional two-sample MR analysis to comprehensively assess the genetic association between OSA and VTE. The inverse variance weighted was used as the primary method for MR analysis. In addition, MR-Egger, weighted median, and MR pleiotropy residual sum and outlier (MR-PRESSO) were used for complementary analyses. Furthermore, a series of sensitivity analyses were performed to ensure the validity and robustness of the results.

RESULTS

 The initial and validation MR analyses indicated that genetically predicted OSA had no effects on the risk of VTE (including PE and DVT). Likewise, the reverse MR analysis did not find substantial support for a significant association between VTE (including PE and DVT) and OSA. Supplementary MR methods and sensitivity analyses provided additional confirmation of the reliability of the MR results.

CONCLUSION

 Our bidirectional two-sample MR analysis did not find genetic evidence supporting a significant association between OSA and VTE in either direction.

Evaluating the distinct effects of body mass index at childhood and adulthood on adult major psychiatric disorders

Children with high body mass index (BMI) are at heightened risk of developing health issues in adulthood, yet the causality between childhood BMI and adult psychiatric disorders remains unclear. Using a life course Mendelian randomization (MR) framework, we investigated the causal effects of childhood and adulthood BMI on adult psychiatric disorders, including Alzheimer's disease, anxiety, major depressive disorder, obsessive-compulsive disorder (OCD), and schizophrenia, using data from the Psychiatric Genomics Consortium and FinnGen study. Childhood BMI was significantly associated with an increased risk of schizophrenia, while adulthood BMI was associated with a decreased risk of OCD and schizophrenia. Multivariable MR analyses indicated a direct causal effect of childhood BMI on schizophrenia, independent of adulthood BMI and lifestyle factors. No evidence of causal associations was found between childhood BMI and other psychiatric outcomes. The sensitivity analyses yielded broadly consistent findings. These findings highlight the critical importance of early-life interventions to mitigate the long-term consequences of childhood adiposity.

Hypothyroidism and dermato/polymyositis: a two-sample Mendelian randomization study

Objective

Observational studies have revealed a higher probability of hypothyroidism in patients with dermatomyositis (DM) or polymyositis (PM), but there is no consensus on whether hypothyroidism causally influences DM or PM. In the present study, we assessed the causal association between hypothyroidism and the risk of dermatomyositis or polymyositis using two-sample Mendelian randomization (TSMR).

Methods

The genome-wide association data of hypothyroidism and dermatomyositis/polymyositis were obtained from the IEU Open GWAS project. Then, TSMR was used to determine whether hypothyroidism is causally associated with DM or PM. Single-nucleotide polymorphisms (SNPs) significantly associated with hypothyroidism were identified and used as instrumental variables (IVs), and the causal relationship between hypothyroidism and DM/PM was examined using TSMR. MR pleiotropy and Cochran's Q test were used to confirm the heterogeneity and pleiotropy of identified IVs, then four different models, including the inverse variance weighted model (IVW), MR-Egger, weighted median and weighted model were applied in this MR analysis.

Results

Sixty-eight SNPs for DM and 68 SNPs for PM were selected as the IVs (P<5×10-8; linkage disequilibrium R2 <0.001) to assess the causal association between hypothyroidism and DM/PM selected from GWASs on hypothyroidism. The results revealed a positive causal effect of hypothyroidism on both DM and PM (DM: OR 2.563, 95% CI [1.348, 4.874], P = 0.00156; PM: OR1.709, 95% CI [1.157, 2.525], P =0.007). Moreover, there was no heterogeneity or pleiotropy in the results.

Conclusion

In conclusion, the MR analysis results provided strong evidence to indicate that hypothyroidism might be causally associated with DM and PM. These findings may have important implications for the pathogenesis and possible future therapies of DM/PM.

Childhood Adiposity and Risk of Major Clinical Heart Diseases in Adulthood: A Mendelian Randomization Study

BACKGROUND

The causal relationship between childhood adiposity and adult risk of heart diseases has not been clearly demonstrated. This study aims to ascertain whether genetically predicted childhood body mass index (BMI) and childhood obesity are causally associated with adult coronary heart disease, myocardial infarction, heart failure, atrial fibrillation, hypertrophic cardiomyopathy, and pulmonary heart disease.

METHODS AND RESULTS

To investigate the causative relationships and underlying mechanisms between childhood adiposity and adult heart diseases, 3 main methods of Mendelian randomization were used: 2-sample Mendelian randomization, multivariable Mendelian randomization with controlling for several cardiometabolic risk variables, and mediation analysis. Every 1-SD rise in genetically predicted childhood body mass index was associated with 24% (odds ratio [OR], 1.24 [95% CI, 1.12-1.37]), 28% (OR, 1.28 [95% CI, 1.14-1.42]), 28% (OR, 1.28 [95% CI, 1.14-1.42]), and 27% (OR, 1.27 [95% CI, 1.04-1.49]) higher risk of coronary heart disease, myocardial infarction, heart failure, and atrial fibrillation, respectively. Every 1-unit increase in log-odds in childhood obesity was associated with 11% (OR, 1.11 [95% CI, 1.06-1.16]), 14% (OR, 1.14 [95% CI, 1.04-1.23]), 10% (OR, 1.10 [95% CI, 1.03-1.18]), and 20% (OR, 1.20 [95% CI, 1.08-1.32]) higher risk of coronary heart disease, myocardial infarction, heart failure, and atrial fibrillation, respectively. The link between childhood adiposity and adult heart diseases was found to be mediated by high-density lipoprotein cholesterol, triglyceride, hypertension, and type 2 diabetes.

CONCLUSIONS

Our findings support the causal relationships between childhood adiposity and risk of adult coronary heart disease, myocardial infarction, heart failure, and atrial fibrillation. Blood lipids, hypertension, and type 2 diabetes are factors that mediate the aforementioned associations.

Associations Between Temporomandibular Disorders and Brain Imaging-Derived Phenotypes

OBJECTIVE

Temporomandibular disorders (TMD) affect the temporomandibular joint and associated structures. Despite its prevalence and impact on quality of life, the underlying mechanisms of TMD remain unclear. Magnetic resonance imaging studies suggest brain abnormalities in patients with TMD. However, these lines of evidence are essentially observational and cannot infer a causal relationship. This study employs Mendelian randomisation (MR) to probe causal relationships between TMD and brain changes.

METHODS

Genome-wide association study (GWAS) summary statistics for TMD were collected, along with brain imaging-derived phenotypes (IDPs). Instrumental variables were selected from the GWAS summary statistics and used in bidirectional 2-sample MR analyses. The inverse-variance weighted analysis was chosen as the primary method. In addition, false discovery rate (FDR) correction of P value was used.

RESULTS

Eleven IDPs related to brain imaging alterations showed significant causal associations with TMD (P-FDR < .05), validated through sensitivity analysis. In forward MR, the mean thickness of left caudal middle frontal gyrus (OR, 0.76; 95% CI, 0.67-0.87; P-FDR = 1.15  ×  10-2) and the volume of right superior frontal gyrus (OR, 1.24; 95% CI, 1.10-1.39; P-FDR = 2.26  ×  10-2) exerted significant causal effects on TMD. In the reverse MR analysis, TMD exerted a significant causal effect on 9 IDPs, including the mean thickness of the left medial orbitofrontal cortex (β = -0.10; 95% CI, -0.13 to -0.08; P-FDR = 2.06 × 10-11), the volume of the left magnocellular nucleus (β = -0.15; 95% CI, -0.22 to -0.09; P-FDR = 3.26 × 10-4), the mean intensity of the right inferior-lateral ventricle (β = -0.09; 95% CI, -0.14 to -0.04; P-FDR = 2.23 × 10-2), the volume of grey matter in the anterior division of the left superior temporal gyrus (β = 0.09; 95% CI,  0.04-0.14; P-FDR = 1.69 × 10-2), and so forth.

CONCLUSIONS

This study provides genetic evidence supporting the bidirectional causal associations between TMD and brain IDPs, shedding light on potential neurobiological mechanisms underlying TMD development and its relationship with brain structure.

Early sexual activity lowers the incidence of intracranial aneurysm: a Mendelian randomization investigation

Objective

Investigate the potential correlation between the age of initial sexual contact, the lifetime accumulation of sexual partners, and the occurrence of intracranial aneurysm (IA) employing a two-sample Mendelian randomization approach.

Methods

This research aims to elucidate the causal relationship between intracranial aneurysm (IA) and sexual variables. Two distinct sexual variables, specifically the age had first sexual intercourse (n = 406,457) and the lifetime number of sexual partners (n = 378,882), were employed as representative parameters in a two-sample Mendelian randomization (MR) study. Outcome data from 23 cohorts, comprising 5,140 cases and 71,934 controls, were gathered through genome-wide association studies (GWAS). To bolster analytical rigor, five distinct methodologies were applied, encompassing MR-Egger technique, weighted median, inverse variance weighted, simple modeling, and weighted modeling.

Results

Our investigation unveiled a causal relationship between the age first had sexual intercourse and the occurrence of intracranial aneurysm (IA), employing the Inverse Variance Weighted (IVW) approach [Odds Ratio (OR): 0.609, p-value: 5.684E-04, 95% Confidence Interval (CI): 0.459-0.807]. This association was notably significant in the context of unruptured intracranial aneurysms (uIA) using the IVW approach (OR: 0.392, p-value: 6.414E-05, 95% CI: 0.248-0.621). Conversely, our findings did not reveal any discernible link between the lifetime number of sexual partners and the occurrence of IA (IA group: OR: 1.346, p-value: 0.415, 95% CI: 0.659-2.749; SAH group: OR: 1.042, p-value: 0.943, 95% CI: 0.338-3.209; uIA group: OR: 1.990, p-value: 0.273, 95% CI: 0.581-6.814).

Conclusion

The two-sample Mendelian Randomization (MR) study presented herein provides evidence supporting a correlation between the age of initial engagement in sexual activity and the occurrence of intracranial aneurysm (IA), with a noteworthy emphasis on unruptured intracranial aneurysms (uIA). Nevertheless, our investigation failed to establish a definitive association between IA and the cumulative lifetime number of sexual partners.

Light pollution during pregnancy influences the growth of offspring in rats

OBJECTIVE

To investigate the effects of excessive light exposure during gestation on intrauterine development and early growth of neonates in rats.

METHODS

Pregnant rats were randomly allocated to three groups: the constant light exposure group, non-light exposure group and control group. Blood samples were collected from the tail vein to analyze melatonin and cortisol levels. Weight, daily food and water consumption were recorded. Uterine weight, placental weight and placental diameter were measured on gestational day 19. Natural birth and neonate growth were also monitored. The expression of NR1D1(nuclear receptor subfamily 1 group D member 1) in offspring's SCN (suprachiasmatic nuclei), liver and adipose tissue was measured. Expression of NR1D1, MT1(melatonin 1 A receptor) and 11β-HSD2 (placental 11β-hydroxysteroid dehydrogenase type 2) in placenta was also measured. Finally, the expression of MT1 and 11β-HSD2 in NR1D1 siRNA transfected JEG-3 cells was evaluated.

RESULTS

There were no significant differences in maternal weight gain, pregnancy duration, uterine weight, placental body weight, placental diameter, fetal number among three groups. There were no significant differences in weights or lengths of offspring at birth. Compared to other two groups, constant light exposure group showed significantly more rapid growth of offspring in 21st day post-birth. The expression of NR1D1 in SCN, liver and adipose tissues of offspring was not significantly different among three groups. The maternal serum melatonin and cortisol levels of the constant light exposure group were lower and higher than other two groups, respectively. The expressions of NR1D1, MT1 and 11β-HSD2 were all decreased in placenta of the constant light exposure group. The expression of MT1 and 11β-HSD2 in JEG-3 cells were decreased after NR1D1 siRNA transfection.

CONCLUSION

Excessive light exposure during pregnancy results in elevated cortisol and reduced melatonin exposure to fetuses in uterus, potentially contributing to an accelerated early growth of offspring in rats.

Methodological approaches, challenges, and opportunities in the application of Mendelian randomisation to lifecourse epidemiology: A systematic literature review

Diseases diagnosed in adulthood may have antecedents throughout (including prenatal) life. Gaining a better understanding of how exposures at different stages in the lifecourse influence health outcomes is key to elucidating the potential benefits of disease prevention strategies. Mendelian randomisation (MR) is increasingly used to estimate causal effects of exposures across the lifecourse on later life outcomes. This systematic literature review explores MR methods used to perform lifecourse investigations and reviews previous work that has utilised MR to elucidate the effects of factors acting at different stages of the lifecourse. We conducted searches in PubMed, Embase, Medline and MedRXiv databases. Thirteen methodological studies were identified. Four studies focused on the impact of time-varying exposures in the interpretation of "standard" MR techniques, five presented methods for repeat measures of the same exposure, and four described methodological approaches to handling multigenerational exposures. A further 127 studies presented the results of an applied research question. Over half of these estimated effects in a single generation and were largely confined to the exploration of questions regarding body composition. The remaining mostly estimated maternal effects. There is a growing body of research focused on the development and application of MR methods to address lifecourse research questions. The underlying assumptions require careful consideration and the interpretation of results rely on select conditions. Whilst we do not advocate for a particular strategy, we encourage practitioners to make informed decisions on how to approach a research question in this field with a solid understanding of the limitations present and how these may be affected by the research question, modelling approach, instrument selection, and data availability.

Causal Factors for Osteoarthritis: A Scoping Review of Mendelian Randomization Studies

OBJECTIVE

Mendelian randomization (MR) has increasingly been utilized as a tool for establishing causal relations between modifiable exposures and osteoarthritis (OA). The goal of this review was to summarize available MR studies of OA that evaluate the causal role of modifiable risk factors on OA.

METHODS

This review was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) Extension for Scoping Reviews model. We performed a literature search for relevant studies published before December 2021 across multiple databases using the search terms "osteoarthritis" and ("Mendelian randomization" or "polygenic risk score"). We reported the MR estimates of causal associations between exposures and OA and then assessed methodologic quality of abstracted studies according to their efforts to validate the three key MR assumptions.

RESULTS

Our search identified 45 studies reporting on 141 exposure-association analyses. All studies performed a formal instrumental variable analysis to estimate the causal effect of exposure on OA. Causal associations (P < 0.05) were reported in 60 of these analyses representing 36 unique publications, and MR-Egger sensitivity analyses were performed in 45 of these analyses. MR studies provided support for causal associations of OA with increased levels of adiposity, coffee consumption, bone mineral density, and sleep disturbance, and decreased levels of serum calcium and low-density lipoprotein cholesterol.

CONCLUSION

These results highlight the potential benefits of weight reduction and improvement of sleep quality to reduce the risk of OA and call for a better understanding of the relations of coffee consumption and serum calcium to OA risk.

The impact of age-specific childhood body-mass index on adult cardiometabolic traits: a Mendelian randomization study

Objective

To evaluate the causal relationship between childhood body-mass index (BMI) at different ages and adult cardiometabolic traits.

Methods

We retrieved genetic instrument variables (IVs) for exposures (standardized BMI at newborn, infant, toddler and late childhood), cardiometabolic traits and potential confounders or mediators (adult BMI, SHBG, testosterone and age at menarche) from the corresponding genome-wide association analysis. We performed univariate and multivariable Mendelian randomization (MR) to dissect associations between age-specific childhood BMI and adult cardiometabolic outcomes. Odds ratio was used to present the direction of the causal association.

Results

In univariate MR, higher newborn BMI was causally associated with reduced risk for type 2 diabetes in women. Late childhood BMI was associated with increased risk for female diabetes and coronary artery disease (CAD), myocardial infarction (MI), and chronic kidney disease (CKD) in general population. Among these associations, only association between late childhood BMI with MI remained significant after adjusting for adult male BMI and sex hormones, (OR = 1.120, 95% CI 1.023-1.226, p = 0.014). Besides, in multivariable MR, we found evidence for causal association between newborn BMI with reduced risk for CAD (OR = 0.862, 95% CI 0.751-0.989, p = 0.034) and MI (OR = 0.864, 95% CI 0.752-0.991, p = 0.037) in men. No obvious impact of infant or toddler BMI was identified on the above-mentioned diseases. For continuous cardiometabolic traits, in all age epochs except infant, higher BMI was associated with increased level of fasting glucose in women.

Conclusion

BMI at birth and late childhood exerts different impact on adult cardiometabolic diseases, while BMI at infant and toddler ages is not causally associated with these outcomes. The effect of childhood BMI may be influenced by sex disparities.

DNA methylation regulator-mediated modification patterns and risk of intracranial aneurysm: a multi-omics and epigenome-wide association study integrating machine learning, Mendelian randomization, eQTL and mQTL data

BACKGROUND

Intracranial aneurysms (IAs) pose a significant and intricate challenge. Elucidating the interplay between DNA methylation and IA pathogenesis is paramount to identify potential biomarkers and therapeutic interventions.

METHODS

We employed a comprehensive bioinformatics investigation of DNA methylation in IA, utilizing a transcriptomics-based methodology that encompassed 100 machine learning algorithms, genome-wide association studies (GWAS), Mendelian randomization (MR), and summary-data-based Mendelian randomization (SMR). Our sophisticated analytical strategy allowed for a systematic assessment of differentially methylated genes and their implications on the onset, progression, and rupture of IA.

RESULTS

We identified DNA methylation-related genes (MRGs) and associated molecular pathways, and the MR and SMR analyses provided evidence for potential causal links between the observed DNA methylation events and IA predisposition.

CONCLUSION

These insights not only augment our understanding of the molecular underpinnings of IA but also underscore potential novel biomarkers and therapeutic avenues. Although our study faces inherent limitations and hurdles, it represents a groundbreaking initiative in deciphering the intricate relationship between genetic, epigenetic, and environmental factors implicated in IA pathogenesis.

Unravelling the genetic causality of immunoglobulin G N-glycans in ischemic stroke

BACKGROUND

Evidence suggests that immunoglobulin G (IgG) N-glycosylation is associated with ischemic stroke (IS). However, the causality of IgG N-glycosylation for IS remains unknown.

METHODS

Two-sample Mendelian randomization (MR) analyses were performed to investigate the potential causal effects of genetically determined IgG N-glycans on IS using publicly available summarized genetic data from East Asian and European populations. Genetic instruments were used as proxies for IgG N-glycan traits. IgG N-glycans were analysed using ultra-performance liquid chromatography. Four complementary MR methods were performed, including the inverse variance weighted method (IVW), MR‒Egger, weighted median and penalized weighted median. Furthermore, to further test the robustness of the results, MR based on Bayesian model averaging (MR-BMA) was then applied to select and prioritize IgG N-glycan traits as risk factors for IS.

RESULTS

After correcting for multiple testing, in two-sample MR analyses, genetically predicted IgG N-glycans were unrelated to IS in both East Asian and European populations, and the results remained consistent and robust in the sensitivity analysis. Moreover, MR-BMA also showed consistent results in both East Asian and European populations.

CONCLUSIONS

Contrary to observational studies, the study did not provide enough genetic evidence to support the causal associations of genetically predicted IgG N-glycan traits and IS, suggesting that N-glycosylation of IgG might not directly involve in the pathogenesis of IS.

mGWAS-Explorer 2.0: Causal Analysis and Interpretation of Metabolite-Phenotype Associations

Metabolomics-based genome-wide association studies (mGWAS) are key to understanding the genetic regulations of metabolites in complex phenotypes. We previously developed mGWAS-Explorer 1.0 to link single-nucleotide polymorphisms (SNPs), metabolites, genes and phenotypes for hypothesis generation. It has become clear that identifying potential causal relationships between metabolites and phenotypes, as well as providing deep functional insights, are crucial for further downstream applications. Here, we introduce mGWAS-Explorer 2.0 to support the causal analysis between >4000 metabolites and various phenotypes. The results can be interpreted within the context of semantic triples and molecular quantitative trait loci (QTL) data. The underlying R package is released for reproducible analysis. Using two case studies, we demonstrate that mGWAS-Explorer 2.0 is able to detect potential causal relationships between arachidonic acid and Crohn's disease, as well as between glycine and coronary heart disease.

Hypothyroidism and rheumatoid arthritis: a two-sample Mendelian randomization study

Background

Meta-analysis of genome-wide association studies (GWAS) data showed that the relationship between hypothyroidism and rheumatoid arthritis (RA) risk remains under debate. This study is conducted to test the causal relationship of hypothyroidism and RA.

Methods

A two-sample Mendelian randomization (TSMR) analysis was employed to estimate the causality of hypothyroidism and rheumatoid arthritis in European ancestry and Asian ancestry. Integrating the effects generated by TSMR, functional annotations and noncoding variant prediction framework were applied to analyze and interpret the functional instrument variants (IVs).

Results

The results of the inverse variance weighted method showed a strong significant causal relationship between hypothyroidism and risk of RA in European ancestry [odds ratio (OR) = 1.96; 95% confidence interval (CI) 1.49, 2.58; p < 0.001]. The outcomes of MR-Egger, weighted median, weighted mode, and simple mode also showed that hypothyroidism was significantly associated with increased risk of RA in European ancestry. The MR-PRESSO method also showed significant results [Outlier-corrected Causal Estimate = 0.70; standard error (SE) = 0.06; p < 0.001]. An independent dataset and an Asian ancestry dataset were applied to estimate and obtain the coincident results. Furthermore, we integrated the effect of variants in TSMR analysis, functional annotations, and prediction methods to pinpoint the single-nucleotide polymorphism (SNP) rs4409785 as one of the causal variants, which suggested that this variant could impact the binding of CTCF-cohesin and play a vital role in immune cells.

Conclusion

In this study, we prove that hypothyroidism is significantly causally associated with increased RA risk, which has not been shown in previous studies. Furthermore, we pinpoint the potential causal variants in RA.

Causal relationships between migraine and microstructural white matter: a Mendelian randomization study

BACKGROUND

Migraine is a disabling neurological disorder with the pathophysiology yet to be understood. The microstructural alteration in brain white matter (WM) has been suggested to be related to migraine in recent studies, but these evidence are observational essentially and cannot infer a causal relationship. The present study aims to reveal the causal relationship between migraine and microstructural WM using genetic data and Mendelian randomization (MR).

METHODS

We collected the Genome-wide association study (GWAS) summary statistics of migraine (48,975 cases / 550,381 controls) and 360 WM imaging-derived phenotypes (IDPs) (31,356 samples) that were used to measure microstructural WM. Based on instrumental variables (IVs) selected from the GWAS summary statistics, we conducted bidirectional two-sample MR analyses to infer bidirectional causal associations between migraine and microstructural WM. In forward MR analysis, we inferred the causal effect of microstructural WM on migraine by reporting the odds ratio (OR) that quantified the risk change of migraine for per 1 standard deviation (SD) increase of IDPs. In reverse MR analysis, we inferred the causal effect of migraine on microstructural WM by reporting the β value that represented SDs of changes in IDPs were caused by migraine.

RESULTS

Three WM IDPs showed significant causal associations (p < 3.29 × 10- 4, Bonferroni correction) with migraine and were proved to be reliable via sensitivity analysis. The mode of anisotropy (MO) of left inferior fronto-occipital fasciculus (OR = 1.76, p = 6.46 × 10- 5) and orientation dispersion index (OD) of right posterior thalamic radiation (OR = 0.78, p = 1.86 × 10- 4) exerted significant causal effects on migraine. Migraine exerted a significant causal effect on the OD of left superior cerebellar peduncle (β = - 0.09, p = 2.78 × 10- 4).

CONCLUSIONS

Our findings provided genetic evidence for the causal relationships between migraine and microstructural WM, bringing new insights into brain structure for the development and experience of migraine.

BMI growth trajectory from birth to 5 years and its sex-specific association with prepregnant BMI and gestational weight gain

Objective

The purpose of the study was to identify the latent body mass index (BMI) z-score trajectories of children from birth to 5 years of age and evaluate their sex-specific association with prepregnant BMI and gestational weight gain (GWG).

Methods

This was a retrospective longitudinal cohort study performed in China. In total, three distinct BMI-z trajectories from birth to 5 years of age were determined for both genders using the latent class growth modeling. The logistic regression model was used to assess the associations of maternal prepregnant BMI and GWG with childhood BMI-z growth trajectories.

Results

Excessive GWG increased the risks of children falling into high-BMI-z trajectory relative to adequate GWG (OR = 2.04, 95% CI: 1.29, 3.20) in boys; girls born to mothers with prepregnancy underweight had a higher risk of low-BMI-z trajectory than girls born to mothers with prepregnancy adequate weight (OR = 1.85, 95% CI: 1.22, 2.79).

Conclusion

BMI-z growth trajectories of children from 0 to 5 years of age have population heterogeneity. Prepregnant BMI and GWG are associated with child BMI-z trajectories. It is necessary to monitor weight status before and during pregnancy to promote maternal and child health.

Immunoglobulin G N-glycan, inflammation and type 2 diabetes in East Asian and European populations: a Mendelian randomization study

Background

Immunoglobulin G (IgG) N-glycans have been shown to be associated with the risk of type 2 diabetes (T2D) and its risk factors. However, whether these associations reflect causal effects remain unclear. Furthermore, the associations of IgG N-glycans and inflammation are not fully understood.

Methods

We examined the causal associations of IgG N-glycans with inflammation (C-reactive protein (CRP) and fibrinogen) and T2D using two-sample Mendelian randomization (MR) analysis in East Asian and European populations. Genetic variants from IgG N-glycan quantitative trait loci (QTL) data were used as instrumental variables. Two-sample MR was conducted for IgG N-glycans with inflammation (75,391 and 18,348 participants of CRP and fibrinogen in the East Asian population, 204,402 participants of CRP in the European population) and T2D risk (77,418 cases and 356,122 controls of East Asian ancestry, 81,412 cases and 370,832 controls of European ancestry).

Results

After correcting for multiple testing, in the East Asian population, genetically determined IgG N-glycans were associated with a higher risk of T2D, the odds ratios (ORs) were 1.009 for T2D per 1- standard deviation (SD) higher GP5, 95% CI = 1.003–1.015; P = 0.0019; and 1.013 for T2D per 1-SD higher GP13, 95% CI = 1.006–1.021; P = 0.0005. In the European population, genetically determined decreased GP9 was associated with T2D (OR = 0.899 per 1-SD lower GP9, 95% CI: 0.845–0.957). In addition, there was suggestive evidence that genetically determined IgG N-glycans were associated with CRP in both East Asian and European populations after correcting for multiple testing, but no associations were found between IgG N-glycans and fibrinogen. There was limited evidence of heterogeneity and pleiotropy bias.

Conclusions

Our results provided novel genetic evidence that IgG N-glycans are causally associated with T2D.

Supplementary Information

The online version contains supplementary material available at 10.1186/s10020-022-00543-z.

Analysis of the gut microbiome in obese native Tibetan children living at different altitudes: A case-control study

Objective

To explore the relationship between intestinal flora and obesity in Tibetan children at different altitudes.

Methods

Using16S rRNA gene sequencing results and blood lipid metabolism indexes to study the characteristics of the intestinal flora present in faeces and changes in blood lipid metabolism in obese children in Tibet who reside at different altitudes and to study correlations between blood lipid metabolism indicators and the intestinal flora composition.

Results

The results showed the following. (a) The triglyceride (TG) and low-density lipoprotein cholesterol (LDL-C) levels in the obesity groups were higher than those in the normal-weight groups, and those in the high-altitude obesity groups were lower than those in the low-altitude obesity groups. (b) The 16S rRNA gene sequencing results showed that altitude affected the composition and relative abundance of the gut microbiota. These parameters were basically the same among the low-altitude groups, while they were significantly lower in the high-altitude groups than in the low-altitude groups. (c) Groups that lived at different altitudes and had different body weights had different dominant bacterial genera. Megamonas was closely related to obesity, and its relative abundance in the low-altitude groups was higher than that in the high-altitude groups. Prevotella was associated with altitude, and its relative abundance in the high-altitude groups was higher than that in the low-altitude groups. In addition, Prevotella elicited changes in the abundance of Escherichia-Shigella. The lower prevalence of obesity and incidence of intestinal inflammation in those living at high altitudes were related to the abundance of Prevotella. (d) There were correlations between the gut microbiota composition and lipid metabolism indicators. The abundance of Romboutsia was positively correlated with TG and LDL-C levels but negatively correlated with high-density lipoprotein cholesterol (HDL-C) levels. The abundance of Akkermansia was negatively correlated with LDL-C levels, and the abundance of Blautia was negatively correlated with body mass index (BMI) and LDL-C levels.

Conclusions

The intestinal flora diversity varied by body weight and altitude, with lower diversity in those at higher altitudes and with lower body weights. Prevotella likely plays a role in suppressing obesity at high altitudes.

Mendelian Randomization Studies of Lifestyle-Related Risk Factors for Osteoarthritis: A PRISMA Review and Meta-Analysis

Risk factors for osteoarthritis (OA) often exert effects over protracted time-courses. Mendelian randomization (MR) studies therefore have an advantage over conventional observational studies when studying the causal effect of long-term lifestyle-related risk factors on OA. However, given the heterogeneous design of existing MR studies on OA, the reported causal estimates of these effects remain inconsistent, thus obscuring the true extent of the biological effects of OA lifestyle-risk factors. We conducted a PRISMA systematic review and specifically included MR studies that investigated the causal effect between lifestyle-related risk factors and OA, where causal estimates for various lifestyle factors were pooled for meta-analysis. Quality of studies was assessed according to STROBE-MR guidelines. A total of 1576 studies were evaluated and 23 were included. Overall, the studies included were of high quality and had a low risk of bias. Our meta-analysis demonstrates the positive causal effect of BMI (ORIVW-random effects 1.49 [1.23-1.80]) and negative causal effects of serum calcium (ORIVW-random effects 0.69 [0.57-0.83]) and LDL levels (ORIVW-random effects 0.93 [0.90-0.96]) on OA. Despite the heterogeneous designs and estimates of causal effects provided by various MR studies, our meta-analysis suggests that lifestyle-related risk factors in the form of BMI, serum calcium, and LDL have true biological effects on the development of OA.

Exploring the clinical and genetic associations of adult weight trajectories using electronic health records in a racially diverse biobank: a phenome-wide and polygenic risk study

BACKGROUND

Weight trajectories might reflect individual health status. In this study, we aimed to examine the clinical and genetic associations of adult weight trajectories using electronic health records (EHRs) in the BioMe Biobank.

METHODS

We constructed four weight trajectories based on a-priori definitions of weight changes (5% or 10%) using annual weight in EHRs (stable weight, weight gain, weight loss, and weight cycle); the final weight dataset included 21 487 participants with 162 783 annual weight measures. To confirm accurate assignment of weight trajectories, we manually reviewed weight trajectory plots for 100 random individuals. We then did a hypothesis-free phenome-wide association study (PheWAS) to identify diseases associated with each weight trajectory. Next, we estimated the single-nucleotide polymorphism-based heritability (hSNP2) of weight trajectories using GCTA-GREML, and we did a hypothesis-driven analysis of anorexia nervosa and depression polygenic risk scores (PRS) on these weight trajectories, given both diseases are associated with weight changes. We extended our analyses to the UK Biobank to replicate findings from a patient population to a generally healthy population.

FINDINGS

We found high concordance between manually assigned weight trajectories and those assigned by the algorithm (accuracy ≥98%). Stable weight was consistently associated with lower disease risks among those passing Bonferroni-corrected p value in our PheWAS (p≤4·4 × 10-5). Additionally, we identified an association between depression and weight cycle (odds ratio [OR] 1·42, 95% CI 1·31-1·55, p≤7·7 × 10-16). The adult weight trajectories were heritable (using 5% weight change as the cutoff: hSNP2 of 2·1%, 95% CI 0·9-3·3, for stable weight; 4·1%, 1·4-6·8, for weight gain; 5·5%, 2·8-8·2, for weight loss; and 4·7%, 2·3-7·1%, for weight cycle). Anorexia nervosa PRS was positively associated with weight loss trajectory among individuals without eating disorder diagnoses (OR1SD 1·16, 95% CI 1·07-1·26, per 1 SD higher PRS, p=0·011), and the association was not attenuated by obesity PRS. No association was found between depression PRS and weight trajectories after permutation tests. All main findings were replicated in the UK Biobank (p<0·05).

INTERPRETATION

Our findings suggest the importance of considering weight from a longitudinal aspect for its association with health and highlight a crucial role of weight management during disease development and progression.

FUNDING

Klarman Family Foundation, US National Institute of Mental Health (NIMH).

Causal Associations of Obesity With Achilles Tendinopathy: A Two-Sample Mendelian Randomization Study

BACKGROUND

Achilles tendinopathy (AT) is associated with severe pain and is the cause of dysfunction and disability that are associated with significant reduction in social and economic benefits. Several potential risk factors have been proposed to be responsible for AT development; however, the results of observational epidemiological studies remain controversial, presumably because the designs of these studies are subject to residual confounding and reverse causality. Mendelian randomization (MR) can infer the causality between exposure and disease outcomes using genetic variants as instrumental variables, and identification of the causal risk factors for AT is beneficial for early intervention. Thus, we employed the MR strategy to evaluate the causal associations between previously reported risk factors (anthropometric parameters, lifestyle factors, blood biomarkers, and systemic diseases) and the risk of AT.

METHODS

Univariable MR was performed to screen for potential causal associations between the putative risk factors and AT. Bidirectional MR was used to infer reverse causality. Multivariable MR was conducted to investigate the body mass index (BMI)-independent causal effect of other obesity-related traits, such as the waist-hip ratio, on AT.

RESULTS

Univariable MR analyses with the inverse-variance weighted method indicated that the genetically predicted BMI was significantly associated with the risk of AT (P=2.0×10^-3), and the odds ratios (95% confidence intervals) is 1.44 (1.14-1.81) per 1-SD increase in BMI. For the other tested risk factors, no causality with AT was identified using any of the MR methods. Bidirectional MR suggested that AT was not causally associated with BMI, and multivariable MR indicated that other anthropometric parameters included in this study were not likely to causally associate with the risk of AT after adjusting for BMI.

CONCLUSIONS

The causal association between BMI and AT risk suggests that weight control is a promising strategy for preventing AT and alleviating the corresponding disease burden.

The Causal Effects of Primary Biliary Cholangitis on Thyroid Dysfunction: A Two-Sample Mendelian Randomization Study

Background: Primary biliary cholangitis (PBC) is an autoimmune disease and is often accompanied by thyroid dysfunction. Understanding the potential causal relationship between PBC and thyroid dysfunction is helpful to explore the pathogenesis of PBC and to develop strategies for the prevention and treatment of PBC and its complications.

Methods: We used a two-sample Mendelian randomization (MR) method to estimate the potential causal effect of PBC on the risk of autoimmune thyroid disease (AITD), thyroid-stimulating hormone (TSH) and free thyroxine (FT4), hyperthyroidism, hypothyroidism, and thyroid cancer (TC) in the European population. We collected seven datasets of PBC and related traits to perform a series MR analysis and performed extensive sensitivity analyses to ensure the reliability of our results.

Results: Using a sensitivity analysis, we found that PBC was a risk factor for AITD, TSH, hypothyroidism, and TC with odds ratio (OR) of 1.002 (95% CI: 1.000–1.005, p = 0.042), 1.016 (95% CI: 1.006–1.027, p = 0.002), 1.068 (95% CI: 1.022–1.115, p = 0.003), and 1.106 (95% CI: 1.019–1.120, p = 0.042), respectively. Interestingly, using reverse-direction MR analysis, we also found that AITD had a significant potential causal association with PBC with an OR of 0.021 (p = 5.10E−4) and that the other two had no significant causal relation on PBC.

Conclusion: PBC causes thyroid dysfunction, specifically as AITD, mild hypothyroidism, and TC. The potential causal relationship between PBC and thyroid dysfunction provides a new direction for the etiology of PBC.

Association between serum iron status and primary liver cancer risk: a Mendelian randomization analysis

Background

Serum iron status has been reported as associated with primary liver cancer (PLC) risk. However, whether iron status plays a role in the development of PLC remains inconclusive.

Methods

Genetic summary statistics of the four biomarkers (serum iron, ferritin, transferrin saturation, and transferrin) of iron status and PLC were retrieved from two independent genome-wide association studies (GWAS) that had been performed in European populations. Two-sample univariate and multivariate Mendelian randomization (MR) analyses were conducted to determine the causal link between iron status and PLC risk.

Results

No significant horizontal pleiotropy was detected for the four biomarkers according to the Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) global test. No evidence of between-single nucleotide polymorphism (SNP) heterogeneity and directional pleiotropy was detected by the Cochran’s Q test and MR-Egger regression for serum iron, ferritin, and transferrin. For transferrin saturation, although no heterogeneity was detected, the directional pleiotropy was significant (P value for intercept of MR-Egger regression =0.033). Univariate MR estimates based on inverse variance weighting (IVW) method suggested that there was no causal link between serum iron [odds ratio (OR) =0.71, 95% confidence interval (CI): 0.45 to 1.11], ferritin (OR =0.56, 95% CI: 0.16 to 2.04), and transferrin (OR =0.91, 95% CI: 0.72 to 1.15) and PLC risk. We found a significant causal relationship between transferrin saturation and PLC risk (OR =0.45, 95% CI: 0.22 to 0.90), although this link was non-significant in multivariate MR analysis.

Conclusions

There might be no causal relationship between iron status and PLC risk. However, data from larger sample size and people with different ethnic background were needed to further validate our findings.

Disentangling sex differences in the shared genetic architecture of posttraumatic stress disorder, traumatic experiences, and social support with body size and composition

There is a well-known association of traumatic experiences and posttraumatic stress disorder (PTSD) with body size and composition, including consistent differences between sexes. However, the biology underlying these associations is unclear. To understand the genetic underpinnings of this complex relationship, we investigated genome-wide datasets informative of African and European ancestries from the Psychiatric Genomic Consortium, the UK Biobank, the GIANT Consortium, and the Million Veteran Program. We used genome-wide association statistics to estimate sex-specific genetic correlations (r g ) of traumatic experiences, social support, and PTSD with multiple anthropometric traits. After multiple testing corrections (false discovery rate, FDR q < 0.05), we observed 58 significant r g relationships in females (e.g., childhood physical abuse and body mass index, BMI r g  = 0.245, p = 3.88 × 10-10) and 21 significant r g relationships in males (e.g., been involved in combat or exposed to warzone and leg fat percentage; r g  = 0.405, p = 4.42 × 10-10). We performed causal inference analyses of these genetic overlaps using Mendelian randomization and latent causal variable approaches. Multiple female-specific putative causal relationships were observed linking body composition/size with PTSD (e.g., leg fat percentage→PTSD; beta = 0.319, p = 3.13 × 10-9), traumatic experiences (e.g., childhood physical abuse→waist circumference; beta = 0.055, p = 5.07 × 10-4), and childhood neglect (e.g., "someone to take you to doctor when needed as a child"→BMI; beta = -0.594, p = 1.09 × 10-5). In males, we observed putative causal effects linking anthropometric-trait genetic liabilities to traumatic experiences (e.g., BMI→childhood physical abuse; beta = 0.028, p = 8.19 × 10-3). Some of these findings were replicated in individuals of African descent although the limited sample size available did not permit us to conduct a sex-stratified analysis in this ancestry group. In conclusion, our findings provide insights regarding sex-specific causal networks linking anthropometric traits to PTSD, traumatic experiences, and social support.

The Causal Effects of Insomnia on Bipolar Disorder, Depression, and Schizophrenia: A Two-Sample Mendelian Randomization Study

Psychiatric disorder, including bipolar disorder (BD), major depression (MDD), and schizophrenia (SCZ), affects millions of persons around the world. Understanding the disease causal mechanism underlying the three diseases and identifying the modifiable risk factors for them hold the key for the development of effective preventative and treatment strategies. We used a two-sample Mendelian randomization method to assess the causal effect of insomnia on the risk of BD, MDD, and SCZ in a European population. We collected one dataset of insomnia, three of BD, one of MDD, and three of SCZ and performed a meta-analysis for each trait, further verifying the analysis through extensive complementarity and sensitivity analysis. Among the three psychiatric disorders, we found that only insomnia is causally associated with MDD and that higher insomnia increases the risk of MDD. Specifically, the odds ratio of MDD increase of insomnia is estimated to be 1.408 [95% confidence interval (CI): 1.210–1.640, p = 1.03E-05] in the European population. The identified causal relationship between insomnia and MDD is robust with respect to the choice of statistical methods and is validated through extensive sensitivity analyses that guard against various model assumption violations. Our results provide new evidence to support the causal effect of insomnia on MDD and pave ways for reducing the psychiatric disorder burden.

Body Mass Index and Birth Weight Improve Polygenic Risk Score for Type 2 Diabetes

One of the major challenges in the post-genomic era is elucidating the genetic basis of human diseases. In recent years, studies have shown that polygenic risk scores (PRS), based on aggregated information from millions of variants across the human genome, can estimate individual risk for common diseases. In practice, the current medical practice still predominantly relies on physiological and clinical indicators to assess personal disease risk. For example, caregivers mark individuals with high body mass index (BMI) as having an increased risk to develop type 2 diabetes (T2D). An important question is whether combining PRS with clinical metrics can increase the power of disease prediction in particular from early life. In this work we examined this question, focusing on T2D. We present here a sex-specific integrated approach that combines PRS with additional measurements and age to define a new risk score. We show that such approach combining adult BMI and PRS achieves considerably better prediction than each of the measures on unrelated Caucasians in the UK Biobank (UKB, n = 290,584). Likewise, integrating PRS with self-reports on birth weight (n = 172,239) and comparative body size at age ten (n = 287,203) also substantially enhance prediction as compared to each of its components. While the integration of PRS with BMI achieved better results as compared to the other measurements, the latter are early-life measurements that can be integrated already at childhood, to allow preemptive intervention for those at high risk to develop T2D. Our integrated approach can be easily generalized to other diseases, with the relevant early-life measurements.