Causal Association Between Birth Weight and Adult Diseases: Evidence From a Mendelian Randomization Analysis

A computational model to analyze the impact of birth weight-nutritional status pair on disease development and disease recovery

Purpose

The purpose of this work is to analyse the combined impacts of birth weight and nutritional status on development and recovery of various types of diseases. This work aims to computationally establish the facts about the effects of individual birth weight-nutritional status pairs on disease development and disease recovery.

Methods

This work designs a computational model to analyze the impact of birth weight-nutritional status pairs on disease development and disease recovery. Our model works in two phases. The first phase finds the best machine learning model to predict birth weight from "Child Birth Weight Dataset" available at IEEE Dataport (https://dx.doi.org/10.21227/dvd4-3232). The second phase combines the predicted birth weight labels with nutritional status labels and establishes the effects using differential equations.

Results

The experimental results find Gradient boosting (GB) to work the best with Information gain (IGT) and Support Vector Machine (SVM) with Chi-square test (CST) for predicting the birth weights. The simulated results establish that "normal birth weight and normal nutritional status" is the best pair for resisting disease development as well as enhancing disease recovery. The results also depict that "low birth weight and malnutrition" is the worst pair for disease development while "high birth weight and malnutrition" is the worst combination for disease recovery.

Conclusion

The findings computationally establish the facts about the effects of birth weight-nutritional status pairs on disease development and disease recovery. As a social implication, this study can spread awareness about the importance of birth weight and nutritional status. The outcome can be helpful for the concerned authority in making decisions on healthcare cost and expenditure.

Mendelian randomization analyses clarify the effects of height on cardiovascular diseases

An inverse correlation between stature and risk of coronary artery disease (CAD) has been observed in several epidemiologic studies, and recent Mendelian randomization (MR) experiments have suggested causal association. However, the extent to which the effect estimated by MR can be explained by cardiovascular, anthropometric, lung function, and lifestyle-related risk factors is unclear, with a recent report suggesting that lung function traits could fully explain the height-CAD effect. To clarify this relationship, we utilized a well-powered set of genetic instruments for human stature, comprising >1,800 genetic variants for height and CAD. In univariable analysis, we confirmed that a one standard deviation decrease in height (~6.5 cm) was associated with a 12.0% increase in the risk of CAD, consistent with previous reports. In multivariable analysis accounting for effects from up to 12 established risk factors, we observed a >3-fold attenuation in the causal effect of height on CAD susceptibility (3.7%, p = 0.02). However, multivariable analyses demonstrated independent effects of height on other cardiovascular traits beyond CAD, consistent with epidemiologic associations and univariable MR experiments. In contrast with published reports, we observed minimal effects of lung function traits on CAD risk in our analyses, indicating that these traits are unlikely to explain the residual association between height and CAD risk. In sum, these results suggest the impact of height on CAD risk beyond previously established cardiovascular risk factors is minimal and not explained by lung function measures.

Genetically predicted retinal vascular occlusion in relation to cardiovascular diseases: A bidirectional two-sample Mendelian randomization analysis

INTRODUCTION

Increasing evidence implicates retinal vascular occlusions as a susceptibility factor for cardiovascular diseases (CVDs), whereas inconsistent results on the relationship were reported in previous observational studies. This research using a bidirectional two-sample Mendelian randomization (MR) analysis aimed to investigate the potential association between genetically determined central/branch retinal artery and retinal vein occlusions (CRAO/BRAO/RVO) and the risk of CVD.

METHODS

Summary statistics of retinal vascular occlusions from the largest available genome-wide association study of European descent were used to investigate their relationship with CVDs, and vice versa. Primary analyses were conducted using the common inverse-variance weighted approach. Several complementary sensitivity analyses were performed to verify the reliability of our results.

RESULTS

Inverse variance weighted method showed suggestive effects of genetically determined RVO on ischemic stroke (IS) (odds ratio [OR] = 1.021, 95% confidence [CI] = 1.004-1.037, p = 0.012), a genetic liability to CRAO increased the risk of myocardial infarction (MI) (OR = 1.014, 95% CI = 1.006-1.023, p = 7.0 × 10-4). In addition, genetic predisposition to BRAO had a positive effect on stroke (OR = 1.008, 95% CI = 1.002-1.013, p = 0.011), IS (OR = 1.007, 95% CI = 1.001-1.014, p = 0.022), and cardioembolic stroke (CES) (OR = 1.018, 95% CI = 1.006-1.031, p = 0.004). The point estimates from sensitivity analyses were in the same direction. Reverse MR analyses found no significant evidence for the effect of CVDs on retinal vascular occlusions.

CONCLUSION

Our MR study provides potential evidence that retinal vascular occlusions are causally linked to increased risk of CVDs including IS, MI, stroke, and CES. This supports the need for clinical CVD screening in individuals with retinal vascular occlusions. Further investigations are warranted to clarify the effects of CVDs on ocular comorbidities.

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.

Illuminating Shared Genetic Associations Between Oesophageal Carcinoma and Pulmonary Carcinoma Risk

Background: Lung cancer and oesophageal cancer are prevalent malignancies with rising incidence and mortality worldwide. While some environmental and behavioural risk factors for these cancers are established, the contribution of genetic factors to their pathogenesis remains incompletely defined. This study aimed to interrogate the intricate genetic relationship between lung cancer and oesophageal cancer and their potential comorbidity. Methods: We utilised linkage disequilibrium score regression (LDSC) to analyse the genetic correlation between oesophageal carcinoma and lung carcinoma. We then employed several approaches, including pleiotropic analysis under the composite null hypothesis (PLACO), multi-marker analysis of genomic annotation (MAGMA), cis-expression quantitative trait loci (eQTL) analysis, and a pan-cancer assessment to identify pleiotropic loci and genes. Finally, we performed bidirectional Mendelian randomisation (MR) to evaluate the causal relationship between these malignancies. Results: LDSC revealed a significant genetic correlation between oesophageal carcinoma and lung carcinoma. Further analysis identified shared gene loci including PGBD1, ZNF323, and WNK1 using PLACO. MAGMA identified enriched pathways and 9 pleiotropic genes including HIST1H1B, HIST1H4L, and HIST1H2BL. eQTL analysis integrating oesophageal, lung, and blood tissues revealed 26 shared genes including TERT, NKAPL, RAD52, BTN3A2, GABBR1, CLPTM1L, and TRIM27. A pan-cancer exploration of the identified genes was undertaken. MR analysis showed no evidence for a bidirectional causal relationship between oesophageal carcinoma and lung carcinoma. Conclusions: This study provides salient insights into the intricate genetic links between lung carcinoma and oesophageal carcinoma. Utilising multiple approaches for genetic correlation, locus and gene analysis, and causal assessment, we identify shared genetic susceptibilities and regulatory mechanisms. These findings reveal new leads and targets to further elucidate the genetic basis of lung and oesophageal carcinoma, aiding development of preventive and therapeutic strategies.

Evaluating causal influence of maternal educational attainment on offspring birthweight via observational study and Mendelian randomization analyses

Background

Although extensive discussions on the influence of maternal educational attainment on offspring birthweight, the conclusion remains controversial, and it is challenging to comprehensively assess the causal association between them.

Methods

To estimate effect of maternal educational attainment on the birthweight of first child, we first conducted an individual-level analysis with UK Biobank participants of white ancestry (n = 208,162). We then implemented Mendelian randomization (MR) methods including inverse variance weighted (IVW) MR and multivariable MR to assess the causal relation between maternal education and maternal-specific birthweight. Finally, using the UK Biobank parent-offspring trio data (n = 618), we performed a polygenic score based MR to simultaneously adjust for confounding effects of fetal-specific birthweight and paternal educational attainment. We also conducted simulations for power evaluation and sensitivity analyses for horizontal pleiotropy of instruments.

Results

We observed that birthweight of first child was positively influenced by maternal education, with 7 years of maternal education as the reference, adjusted effect = 44.8 (95%CIs 38.0-51.6, P = 6.15 × 10-38), 54.9 (95%CIs 47.6-62.2, P = 4.21 × 10-128), and 89.4 (95%CIs 82.1-96.7, P = 4.28 × 10-34) for 10, 15 and 20 years of maternal educational attainment, respectively. A causal relation between maternal education and offspring birthweight was revealed by IVW MR (estimated effect = 0.074 for one standard deviation increase in maternal education years, 95%CIs 0.054-0.093, P = 2.56 × 10-13) and by complementary MR methods. This connection was not substantially affected by paternal education or horizontal pleiotropy. Further, we found a positive but insignificant causal association (adjusted effect = 24.0, 95%CIs -150.1-198.1, P = 0.787) between maternal education and offspring birthweight after simultaneously controlling for fetal genome and paternal education; this null causality was largely due to limited power of small sample sizes of parent-offspring trios.

Conclusion

This study offers supportive evidence for a causal association between maternal education and offspring birthweight, highlighting the significance of enhancing maternal education to prevent low birthweight.

Birth weight influences cardiac structure, function, and disease risk: evidence of a causal association

BACKGROUND AND AIMS

Low birth weight is a common pregnancy complication, which has been associated with higher risk of cardiometabolic disease in later life. Prior Mendelian randomization (MR) studies exploring this question do not distinguish the mechanistic contributions of variants that directly influence birth weight through the foetal genome (direct foetal effects), vs. variants influencing birth weight indirectly by causing an adverse intrauterine environment (indirect maternal effects). In this study, MR was used to assess whether birth weight, independent of intrauterine influences, is associated with cardiovascular disease risk and measures of adverse cardiac structure and function.

METHODS

Uncorrelated (r2 < .001), genome-wide significant (P < 5 × 10-8) single nucleotide polymorphisms were extracted from genome-wide association studies summary statistics for birth weight overall, and after isolating direct foetal effects only. Inverse-variance weighted MR was utilized for analyses on outcomes of atrial fibrillation, coronary artery disease, heart failure, ischaemic stroke, and 16 measures of cardiac structure and function. Multiple comparisons were accounted for by Benjamini-Hochberg correction.

RESULTS

Lower genetically-predicted birth weight, isolating direct foetal effects only, was associated with an increased risk of coronary artery disease (odds ratio 1.21, 95% confidence interval 1.06-1.37; P = .031), smaller chamber volumes, and lower stroke volume, but higher contractility.

CONCLUSIONS

The results of this study support a causal role of low birth weight in cardiovascular disease, even after accounting for the influence of the intrauterine environment. This suggests that individuals with a low birth weight may benefit from early targeted cardiovascular disease prevention strategies, independent of whether this was linked to an adverse intrauterine environment during gestation.

Genetic overlap for ten cardiovascular diseases: A comprehensive gene-centric pleiotropic association analysis and Mendelian randomization study

Recent studies suggest that pleiotropic effects may explain the genetic architecture of cardiovascular diseases (CVDs). We conducted a comprehensive gene-centric pleiotropic association analysis for ten CVDs using genome-wide association study (GWAS) summary statistics to identify pleiotropic genes and pathways that may underlie multiple CVDs. We found shared genetic mechanisms underlying the pathophysiology of CVDs, with over two-thirds of the diseases exhibiting common genes and single-nucleotide polymorphisms (SNPs). Significant positive genetic correlations were observed in more than half of paired CVDs. Additionally, we investigated the pleiotropic genes shared between different CVDs, as well as their functional pathways and distribution in different tissues. Moreover, six hub genes, including ALDH2, XPO1, HSPA1L, ESR2, WDR12, and RAB1A, as well as 26 targeted potential drugs, were identified. Our study provides further evidence for the pleiotropic effects of genetic variants on CVDs and highlights the importance of considering pleiotropy in genetic association studies.

Birth Weight, Cardiometabolic Factors, and Coronary Heart Disease: A Mendelian Randomization Study

CONTEXT

Observational studies have shown associations of birth weight (BW) with coronary heart disease (CHD), but results are inconsistent and do not distinguish the fetal or maternal effect of BW.

OBJECTIVE

This study aims to explore the causal association between BW and CHD, analyze the fetal and maternal contribution, and quantify mediating effects of cardiometabolic factors.

METHODS

Genetic variants from genome-wide association study summary-level data of own BW (N = 298 142), offspring BW (N = 210 267 mothers), and 16 cardiometabolic (anthropometric, glycemic, lipidemic, and blood pressure) factors were extracted as instrumental variables. We used two-sample Mendelian randomization study (MR) to estimate the causal effect of BW on CHD (60 801 cases and 123 504 controls from mixed ancestry) and explore the fetal and maternal contributions. Mediation analyses were conducted to analyze the potential mediating effects of 16 cardiometabolic factors using two-step MR.

RESULTS

Inverse variance weighted analysis showed that lower BW raised the CHD risk (β -.30; 95% CI: -0.40, -0.20) and consistent results were observed in fetal-specific/maternal-specific BW. We identified 5 mediators in the causal pathway from BW to CHD, including body mass index-adjusted hip circumference, triglycerides, fasting insulin, diastolic blood pressure, and systolic blood pressure (SBP), with mediated proportion ranging from 7.44% for triglycerides to 27.75% for SBP. Causality between fetal-specific and maternal-specific BW and CHD was mediated by glycemic factors and SBP, respectively.

CONCLUSION

Our findings supported that lower BW increased CHD risk and revealed that fetal-specific and maternal-specific BW may both contribute to this effect. The causality between BW and CHD was mediated by several cardiometabolic factors.

Appraising the Causal Role of Risk Factors in Coronary Artery Disease and Stroke: A Systematic Review of Mendelian Randomization Studies

BACKGROUND Mendelian randomization (MR) offers a powerful approach to study potential causal associations between exposures and health outcomes by using genetic variants associated with an exposure as instrumental variables. In this systematic review, we aimed to summarize previous MR studies and to evaluate the evidence for causality for a broad range of exposures in relation to coronary artery disease and stroke. METHODS AND RESULTS MR studies investigating the association of any genetically predicted exposure with coronary artery disease or stroke were identified. Studies were classified into 4 categories built on the significance of the main MR analysis results and its concordance with sensitivity analyses, namely, robust, probable, suggestive, and insufficient. Studies reporting associations that did not perform any sensitivity analysis were classified as nonevaluable. We identified 2725 associations eligible for evaluation, examining 535 distinct exposures. Of them, 141 were classified as robust, 353 as probable, 110 as suggestive, and 926 had insufficient evidence. The most robust associations were observed for anthropometric traits, lipids, and lipoproteins and type 2 diabetes with coronary artery; disease and clinical measurements with coronary artery disease and stroke; and thrombotic factors with stroke. CONCLUSIONS Despite the large number of studies that have been conducted, only a limited number of associations were supported by robust evidence. Approximately half of the studies reporting associations presented an MR sensitivity analysis along with the main analysis that further supported the causality of associations. Future research should focus on more thorough assessments of sensitivity MR analyses and further assessments of mediation effects or nonlinearity of associations.

Maternal and fetal origins of offspring blood pressure: statistical analysis using genetic correlation and genetic risk score-based Mendelian randomization

BACKGROUND

Epidemiological studies demonstrated that adverse in utero environment was associated with increased risk of offspring high blood pressure, by using birthweight as the proxy of maternal intrauterine exposure; however, the nature of such association remains less understood.

METHODS

With maternal/fetal-specific summary statistics of birthweight (n = 297 356 for own birthweight and n = 210 248 for offspring birthweight) and summary statistics of blood pressure [i.e. systolic blood pressure (SBP), diastolic blood pressure (DBP) and pulse pressure (PP)] (n = 757 601), we evaluated the genetic correlation between fetal-specific birthweight and blood pressure using cross-trait linkage disequilibrium score regression, and next detected pleiotropic genes for them with a pleiotropy mapping method called mixture-adjusted intersect-union pleiotropy test. Furthermore, we conducted a genetic risk score (GRS)-based Mendelian randomization analysis in parent-offspring pairs (n = 6031) of the UK Biobank cohort, to assess the causal relation between maternal-specific GRS and blood pressure conditioning on fetal genotypes.

RESULTS

We found fetal-specific birthweight had a negative genetic correlation with DBP (ρ^g = -0.174, P = 1.68 × 10-10), SBP (ρ^g = -0.198, P = 8.09 × 10-12), and PP (ρ^g = -0.152, P = 6.04 × 10-8), and detected 143, 137 and 135 pleiotropic genes shared between fetal-specific birthweight and PP, SBP and DBP, respectively. These genes often exhibited opposite genetic effects, and were more likely to be differentially expressed in pancreas, liver, heart, brain, whole blood and muscle skeletal tissues. A causal negative association of maternal-specific birthweight was identified with SBP (P = 2.20 × 10-2) and PP (P = 7.67 × 10-3) but not DBP (P = 0.396) in mother-offspring pairs, after accounting for the influence of fetal-specific GRS; and the two significant relations were robust against the horizontal pleiotropy of instruments and the confounding influence of gestational duration and preterm birth. However, these causal associations could not be detected in father-offspring pairs.

CONCLUSIONS

This study revealed common genetic components underlying birthweight and blood pressure, and provided important insight into aetiology and early prevention of high blood pressure.

Fetal genome predicted birth weight and polycystic ovary syndrome in later life: a Mendelian randomization study

Associations between lower birth weight and higher polycystic ovary syndrome (PCOS) risk have been reported in previous observational studies, however, the causal relationship is still unknown. Based on decomposed fetal and maternal genetic effects on birth weight (n  =  406,063), we conducted a two-sample Mendelian randomization (MR) analysis to assess potential causal relationships between fetal genome predicted birth weight and PCOS risk using a large-scale genome-wide association study (GWAS) including 4,138 PCOS cases and 20,129 controls. To further eliminate the maternally transmitted or non-transmitted effects on fetal growth, we performed a secondary MR analysis by utilizing genetic instruments after excluding maternally transmitted or non-transmitted variants, which were identified in another birth weight GWAS (n = 63,365 parent-offspring trios from Icelandic birth register). Linkage disequilibrium score regression (LDSR) analysis was conducted to estimate the genetic correlation. We found little evidence to support a causal effect of fetal genome determined birth weight on the risk of developing PCOS (primary MR analysis, OR: 0.86, 95% CI: 0.52 to 1.43; secondary MR analysis, OR: 0.86, 95% CI: 0.54 to 1.39). In addition, a marginally significant genetic correlation (rg = -0.14, se = 0.07) between birth weight and PCOS was revealed via LDSR analysis. Our findings indicated that observed associations between birth weight and future PCOS risk are more likely to be attributable to genetic pleiotropy driven by the fetal genome rather than a causal mechanism.

Mendelian randomization analyses clarify the effects of height on cardiovascular diseases

An inverse correlation between stature and risk of coronary artery disease (CAD) has been observed in several epidemiologic studies, and recent Mendelian randomization (MR) experiments have suggested causal association. However, the extent to which the effect estimated by MR can be explained by established cardiovascular risk factors is unclear, with a recent report suggesting that lung function traits could fully explain the height-CAD effect. To clarify this relationship, we utilized a well-powered set of genetic instruments for human stature, comprising >1,800 genetic variants for height and CAD. In univariable analysis, we confirmed that a one standard deviation decrease in height (~6.5 cm) was associated with a 12.0% increase in the risk of CAD, consistent with previous reports. In multivariable analysis accounting for effects from up to 12 established risk factors, we observed a >3-fold attenuation in the causal effect of height on CAD susceptibility (3.7%, p = 0.02). However, multivariable analyses demonstrated independent effects of height on other cardiovascular traits beyond CAD, consistent with epidemiologic associations and univariable MR experiments. In contrast with published reports, we observed minimal effects of lung function traits on CAD risk in our analyses, indicating that these traits are unlikely to explain the residual association between height and CAD risk. In sum, these results suggest the impact of height on CAD risk beyond previously established cardiovascular risk factors is minimal and not explained by lung function measures.

The early life course-related traits with three psychiatric disorders: A two-sample Mendelian randomization study

Objectives

Several studies have indicated a potential association between early life course-related traits and neurological and psychiatric disorders in adulthood, but the causal link remains unclear.

Methods

Instrumental variables (IVs) that have been shown to be strongly associated with exposure were obtained from summary data of genome-wide association studies (GWASs). Four early life course-related traits [i.e., birthweight (BW), childhood body mass index (BMI), early body size, and age at first birth (AFB)] were used as exposure IVs to estimate their causal associations with three neurological and psychiatric diseases [i.e., Alzheimer's disease (AD), major depressive disorder (MDD), and attention-deficit hyperactivity disorder (ADHD)]. Four different statistical methods, i.e., inverse-variance weighting (IVW), MR-Egger (MRE), weighted median (WM), and weighted mode (Wm), were performed in our MR analysis. Sensitivity analysis was performed by using the leave-one-out method, and horizontal pleiotropy was assessed using the MR-PRESSO package.

Results

There was evidence suggesting that BW has a causal effect on AD (OR_MR-PRESSO = 1.05, p = 1.14E-03), but this association was not confirmed via multivariable Mendelian randomization (MVMR) (OR_MVMR = 0.97, 95% CI 0.92-1.02, p = 3.00E-01). A strong relationship was observed between childhood BMI and ADHD among both sexes; a 1-SD increase in BMI significantly predicted a 1.46-fold increase in the OR for ADHD (p = 9.13E-06). In addition, a similar relationship was found between early life body size and ADHD (OR_MR-PRESSO = 1.47, p = 9.62E-05), and this effect was mainly driven by male participants (OR_MR-PRESSO = 1.50, p = 1.28E-3). Earlier AFB could significantly predict a higher risk of MDD (OR_MR-PRESSO = 1.19, p = 1.96E-10) and ADHD (OR_MR-PRESSO = 1.45, p = 1.47E-15). No significant causal associations were observed between the remaining exposures and outcomes.

Conclusion

Our results reveal the adverse effects of childhood obesity and preterm birth on the risk of ADHD later in life. The results of MVMR also show that lower BW may have no direct relationship with AD after adjusting for BMI. Furthermore, AFB may predict a higher risk of MDD.

Maternal Testosterone and Offspring Birth Weight: A Mendelian Randomization Study

CONTEXT

Evidence has shown maternal androgen levels in both the general population and populations with hyperandrogenic disorders are inversely associated with offspring birth weight.

CONTEXT

We aimed to investigate the causal effect of maternal testosterone levels in the general population on offspring birth weight and preterm delivery risk using a two-sample Mendelian randomization (MR) method.

METHODS

We obtained independent genetic instruments from a sex-specific genome-wide association study with up to 230 454 females of European descent from the UK Biobank. Genetic instruments with consistent testosterone effects but no aggregate effect on sex hormone-binding globulin were used to perform the main analysis. Summary-level data of offspring birth weight adjusted for genotype were obtained from a study with 210 406 females of European descent. Summary-level data of preterm delivery were obtained from the FinnGen study (6736 cases and 116 219 controls).

RESULTS

MR analysis showed that each SD (0.62 nmol/L) increase in testosterone levels could reduce the offspring birth weight by 37.26 g (95% CI, 19.59-54.94 g; P = 3.62 × 10-5). Each SD increase in testosterone levels was also associated with an increased risk of preterm delivery (odds ratio = 1.329; 95% CI, 1.161-1.520; P = 3.57 × 10-5). Similar results were found using different MR methods and multivariable MR analyses.

CONCLUSION

This two-sample MR study showed genetically determined higher circulating testosterone levels in females from the general population were associated with low birth weight of offspring and increased risk of preterm delivery.

The Causal Evidence of Birth Weight and Female-Related Traits and Diseases: A Two-Sample Mendelian Randomization Analysis

Objectives: A large meta-analysis indicated a more pronounced association between lower birth weight (BW) and diseases in women but less concern about the causality between BW and female-related phenotypes and diseases.

Methods: Mendelian randomization (MR) analysis was used to estimate the causal relationship between two traits or diseases using summary datasets from genome-wide association studies. Exposure instrumental variables are variants that are strongly associated with traits and are tested using four different statistical methods, including the inverse variance weighting, MR-Egger, weighted median, and weighted mode in MR analysis. Next, sensitivity analysis and horizontal pleiotropy were assessed using leave-one-out and MR-PRESSO packages.

Results: The body mass index (BMI) in adulthood was determined by BW (corrected β = 0.071, p = 3.19E-03). Lower BW could decrease the adult sex hormone-binding globulin (SHBG) level (β = −0.081, p = 2.08E-06), but it resulted in increased levels of bioavailable testosterone (bio-T) (β = 0.105, p = 1.25E-05). A potential inverse effect was observed between BW and menarche (corrected β = −0.048, p = 4.75E-03), and no causal association was confirmed between BW and the risk of endometriosis, leiomyoma, and polycystic ovary syndrome.

Conclusion: Our results suggest that BW may play an important role and demonstrates a significant direct influence on female BMI, SHBG and bio-T levels, and menarche.

A Mendelian Randomization Study of the Effect of Tea Intake on Type 2 Diabetes

Background: The association reported between tea intake and type 2 diabetes (T2D) is inconsistent in previous studies and remains controversial. We aimed to explore the causal relationship between tea intake, T2D, and glycemic traits including hemoglobin A1c (HbA1c), fasting plasma glucose (FPG), fasting serum insulin (FSI), and homeostasis model of insulin resistance (HOMA-IR) levels. Methods: A 2-sample Mendelian randomization (MR) was performed using summary statistics from large-scale genome-wide association studies of tea intake from the UK Biobank, T2D from the DIAGRAM consortium, and glycemic traits from the Magic consortium. The findings were verified through sensitivity analyses using various MR methods with different model assumptions and by comprehensively evaluating the influence of pleiotropy effects and outliers. Results: With the use of a two-sample MR with inverse variance-weighted method, the odds ratio per unit SD change of tea intake (SD: 2.85 cups/day) for T2D, HbA1c, FPG, FSI, and HOMA-IR levels was 0.949 (95% CI 0.844-1.067, p = 0.383), 0.994 (95% CI 0.975-1.013, p = 0.554), 0.996 (95% CI 0.978-1.015, p = 0.703), 0.968 (95% CI 0.948-0.986, p = 0.001), and 0.953 (95% CI 0.900-1.009, p = 0.102), respectively. The results were consistent with those of the other six methods that we used with different model assumptions, suggesting that the findings were robust and convincing. We also performed various sensitivity analyses for outlier removal, pleiotropy detection, and leave-one-out analysis. Conclusion: Our MR results did not support the causal effect of tea intake on T2D and crucial glycemic traits. These findings suggest that previous observational studies may have been confounded.

Admixture mapping of anthropometric traits in the Black Women's Health Study: evidence of a shared African ancestry component with birth weight and type 2 diabetes

Prevalence of obesity, type 2 diabetes (T2D), and being born with low birth weight are much higher in African American women compared to U.S. white women. Genetic factors may contribute to the excess risk of these conditions. We conducted admixture mapping of body mass index (BMI) at age 18, adult BMI, and adult waist circumference and waist-to-hip ratio adjusted for BMI using 2918 ancestral informative markers in 2596 participants of the Black Women's Health Study. We also searched for evidence of shared African genetic ancestry components among the four examined anthropometric traits and among birth weight and T2D. We found that global percent African ancestry was associated with higher adult BMI. We also found that African ancestry at 9q34 was associated with lower BMI at age 18. Our shared ancestry analysis identified ten genomic regions with local African ancestry associated with multiple traits. Seven out of these ten genomic loci were related to T2D risk. Of special interest is the 12q14-21 region where local African ancestry was associated with low birth weight, low BMI, high BMI-adjusted waist-to-hip ratio, and high T2D risk. Findings in the 12q14-21 genomic locus are consistent with the fetal insulin hypothesis that postulates that low birth weight and T2D have a common genetic basis, and they support the hypothesis of a shared African genetic ancestry component linking low birth weight and T2D in African Americans. Future studies should identify the actual genetic variants responsible for the clustering of these conditions in African Americans.

Day-3-embryo fragmentation is associated with singleton birth weight following fresh single blastocyst transfer: A retrospective study

BACKGROUND

Previous studies have arguably associated poor embryo morphology with low birth weight in singletons following single embryo transfer. However, the association between birth weight and specific morphological features in the cleavage stage remains less known. The purpose of the study was to investigate whether morphological features of embryos at the cleavage stage affect birth weight following blastocyst transfer.

METHODS

The single-center retrospective cohort study included 4,226 singletons derived from fresh single cleavage-stage embryo transfer (ET; n = 1,185), fresh single blastocyst transfer (BT; n = 787), or frozen-thawed single blastocyst transfer (FBT; n = 2,254) between 2016 and 2019. Morphological parameters including early cleavage, day-3 fragmentation, symmetry, blastomere number, and blastocyst morphology were associated with neonatal birth weight and birth weight z-score in multivariate regression models. The models were adjusted for maternal age, body mass index (BMI), parity, peak estradiol level, endometrial thickness, insemination protocol, female etiologies, order of transfer, mode of delivery, and year of treatment.

RESULTS

Adjusted for confounders, day-3 fragmentation was the only morphological feature associated with birth weight and birth weight z-score, while early cleavage, symmetry, blastomere number, and blastocyst morphology were not. Day-3 fragmentation increased the birth weight in both the ET (115.4 g, 95% CI: 26.6-204.2) and BT groups (168.8 g, 95% CI: 48.8-288.8) but not in the FBT group (7.47 g, 95% CI: -46.4 to 61.3). The associations between birth weight and these morphological parameters were confirmed through birth weight z-score analyses. The adjusted odds of large for gestational age (LGA) and high birth weight were also significantly greater in singletons following the transfer of fragmented embryos in the BT group [odds ratio (OR) 3, 95% CI: 1.2-7.51 and OR 3.65, 95% CI: 1.33-10, respectively]. The presence of fragmentation at the cleavage stage also affected the association between the blastocyst morphology and birth weight. Inner cell mass grades were negatively associated with birth weight in blastocysts with day-3 fragmentation but not in blastocysts without.

CONCLUSIONS

The birth weight following blastocyst transfer was found to be positively associated with fragmentation at the cleavage stage. The data did not support the argument that transferring a poor-looking embryo may increase the risks of low birth weight. However, concerns for LGA infants remain.

Assessing Causal Relationship Between Human Blood Metabolites and Five Neurodegenerative Diseases With GWAS Summary Statistics

Background: Neurodegenerative diseases (NDDs) are the leading cause of disability worldwide while their metabolic pathogenesis is unclear. Genome-wide association studies (GWASs) offer an unprecedented opportunity to untangle the relationship between metabolites and NDDs.

Methods: By leveraging two-sample Mendelian randomization (MR) approaches and relying on GWASs summary statistics, we here explore the causal association between 486 metabolites and five NDDs including Alzheimer’s Disease (AD), amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), Parkinson’s disease (PD), and multiple sclerosis (MS). We validated our MR results with extensive sensitive analyses including MR-PRESSO and MR-Egger regression. We also performed linkage disequilibrium score regression (LDSC) and colocalization analyses to distinguish causal metabolite-NDD associations from genetic correlation and LD confounding of shared causal genetic variants. Finally, a metabolic pathway analysis was further conducted to identify potential metabolite pathways.

Results: We detected 164 metabolites which were suggestively associated with the risk of NDDs. Particularly, 2-methoxyacetaminophen sulfate substantially affected ALS (OR = 0.971, 95%CIs: 0.961 ∼ 0.982, FDR = 1.04E-4) and FTD (OR = 0.924, 95%CIs: 0.885 ∼ 0.964, FDR = 0.048), and X-11529 (OR = 1.604, 95%CIs: 1.250 ∼ 2.059, FDR = 0.048) and X-13429 (OR = 2.284, 95%CIs: 1.457 ∼ 3.581, FDR = 0.048) significantly impacted FTD. These associations were further confirmed by the weighted median and maximum likelihood methods, with MR-PRESSO and the MR-Egger regression removing the possibility of pleiotropy. We also observed that ALS or FTD can alter the metabolite levels, including ALS and FTD on 2-methoxyacetaminophen sulfate. The LDSC and colocalization analyses showed that none of the identified associations could be driven by genetic correlation or confounding by LD with common causal loci. Multiple metabolic pathways were found to be involved in NDDs, such as “urea cycle” (P = 0.036), “arginine biosynthesis” (P = 0.004) on AD and “phenylalanine, tyrosine and tryptophan biosynthesis” (P = 0.046) on ALS.

Conclusion: our study reveals robust bidirectional causal associations between servaral metabolites and neurodegenerative diseases, and provides a novel insight into metabolic mechanism for pathogenesis and therapeutic strategies of these diseases.

A comprehensive gene-centric pleiotropic association analysis for 14 psychiatric disorders with GWAS summary statistics

BACKGROUND

Recent genome-wide association studies (GWASs) have revealed the polygenic nature of psychiatric disorders and discovered a few of single-nucleotide polymorphisms (SNPs) associated with multiple psychiatric disorders. However, the extent and pattern of pleiotropy among distinct psychiatric disorders remain not completely clear.

METHODS

We analyzed 14 psychiatric disorders using summary statistics available from the largest GWASs by far. We first applied the cross-trait linkage disequilibrium score regression (LDSC) to estimate genetic correlation between disorders. Then, we performed a gene-based pleiotropy analysis by first aggregating a set of SNP-level associations into a single gene-level association signal using MAGMA. From a methodological perspective, we viewed the identification of pleiotropic associations across the entire genome as a high-dimensional problem of composite null hypothesis testing and utilized a novel method called PLACO for pleiotropy mapping. We ultimately implemented functional analysis for identified pleiotropic genes and used Mendelian randomization for detecting causal association between these disorders.

RESULTS

We confirmed extensive genetic correlation among psychiatric disorders, based on which these disorders can be grouped into three diverse categories. We detected a large number of pleiotropic genes including 5884 associations and 2424 unique genes and found that differentially expressed pleiotropic genes were significantly enriched in pancreas, liver, heart, and brain, and that the biological process of these genes was remarkably enriched in regulating neurodevelopment, neurogenesis, and neuron differentiation, offering substantial evidence supporting the validity of identified pleiotropic loci. We further demonstrated that among all the identified pleiotropic genes there were 342 unique ones linked with 6353 drugs with drug-gene interaction which can be classified into distinct types including inhibitor, agonist, blocker, antagonist, and modulator. We also revealed causal associations among psychiatric disorders, indicating that genetic overlap and causality commonly drove the observed co-existence of these disorders.

CONCLUSIONS

Our study is among the first large-scale effort to characterize gene-level pleiotropy among a greatly expanded set of psychiatric disorders and provides important insight into shared genetic etiology underlying these disorders. The findings would inform psychiatric nosology, identify potential neurobiological mechanisms predisposing to specific clinical presentations, and pave the way to effective drug targets for clinical treatment.

Association between maximum temperature and PM2.5 with pregnancy outcomes in Lima, Peru

BACKGROUND

We have previously documented an inverse relationship between PM2.5 in Lima, Peru, and reproductive outcomes. Here, we investigate the effect of temperature on birth weight, birth weight-Z-score adjusted for gestational age, low birth weight, and preterm birth. We also explore interactions between PM2.5 and temperature.

METHODS

We studied 123,034 singleton births in three public hospitals of Lima with temperature and PM2.5 during gestation between 2012 and 2016. We used linear, logistic, and Cox regression to estimate associations between temperature during gestation and birth outcomes and explored possible modification of the temperature effect by PM2.5.

RESULTS

Exposure to maximum temperature in the last trimester was inversely associated with both birth weight [β: -23.7; 95% confidence interval [CI]: -28.0, -19.5] and z-score weight-for-gestational-age (β: -0.024; 95% CI: -0.029, -0.020) with an interquartile range of 5.32 °C. There was also an increased risk of preterm birth with higher temperature (interquartile range) in the first trimester (hazard ratio: 1.04; 95% CI: 1.001, 1.070). The effect of temperature on birthweight was primarily seen at higher PM2.5 levels. There were no statistically significant associations between temperature exposure with low birth weight.

CONCLUSIONS

Exposition to maximum temperature was associated with lower birth weight and z-score weight-for-gestational-age and higher risk of preterm birth, in accordance with much of the literature. The effects on birth weight were seen only in the third trimester.

Evaluating Causal Relationship Between Metabolites and Six Cardiovascular Diseases Based on GWAS Summary Statistics

Cardiovascular diseases (CVDs) remain the main cause of morbidity and mortality worldwide. The pathological mechanism and underlying biological processes of these diseases with metabolites remain unclear. In this study, we conducted a two-sample Mendelian randomization (MR) analysis to evaluate the causal effect of metabolites on these diseases by making full use of the latest GWAS summary statistics for 486 metabolites and six major CVDs. Extensive sensitivity analyses were implemented to validate our MR results. We also conducted linkage disequilibrium score regression (LDSC) and colocalization analysis to investigate whether MR findings were driven by genetic similarity or hybridization between LD and disease-associated gene loci. We identified a total of 310 suggestive associations across all metabolites and CVDs, and finally obtained four significant associations, including bradykinin, des-arg(9) (odds ratio [OR] = 1.160, 95% confidence intervals [CIs]: 1.080-1.246, false discovery rate [FDR] = 0.022) on ischemic stroke, N-acetylglycine (OR = 0.946, 95%CIs: 0.920-0.973, FDR = 0.023), X-09026 (OR = 0.845, 95%CIs: 0.779-0.916, FDR = 0.021) and X-14473 (OR = 0.938, 95%CIs = 0.907-0.971, FDR = 0.040) on hypertension. Sensitivity analyses showed that these causal associations were robust, the LDSC and colocalization analyses demonstrated that the identified associations were unlikely confused by LD. Moreover, we identified 15 important metabolic pathways might be involved in the pathogenesis of CVDs. Overall, our work identifies several metabolites that have a causal relationship with CVDs, and improves our understanding of the pathogenesis and treatment strategies for these diseases.

Genetic Determinants of Increased Body Mass Index Partially Mediate the Effect of Elevated Birth Weight on the Increased Risk of Atrial Fibrillation

Background: Although several observational studies have shown an association between birth weight (BW) and atrial fibrillation (AF), controversy remains. In this study, we aimed to explore the role of elevated BW on the etiology of AF.

Methods: A two-sample Mendelian randomization (MR) study was designed to infer the causality. The genetic data on the associations of single-nucleotide polymorphisms (SNPs) with BW and AF were separately obtained from two large-scale genome-wide association studies with up to 321,223 and 1,030,836 individuals, respectively. SNPs were identified at a genome-wide significant level (p <5 × 10⁻⁸). The inverse variance-weighted (IVW) method was employed to obtain causal estimates as our primary analysis. Sensitivity analyses with various statistical methods were applied to evaluate the robustness of the results, and multivariable MR analysis was conducted to determine whether this association was mediated by the body mass index (BMI).

Results: In total, 144 SNPs were identified as the genetic instrumental variables. MR analysis revealed a causal effect of elevated BW on AF (OR = 1.27, 95% CI = 1.14–1.40, p = 5.70 × 10⁻⁶). All the results in sensitivity analyses were consistent with the primary result. The effect of BW on AF was attenuated when adjusted for BMI (OR = 1.16, 95% CI = 1.01–1.33, p = 0.04).

Conclusions: This study indicated that elevated BW was significantly associated with increased lifelong risk of AF, which may be partially mediated by BMI.

Mendelian randomization under the omnigenic architecture

Mendelian randomization (MR) is a common analytic tool for exploring the causal relationship among complex traits. Existing MR methods require selecting a small set of single nucleotide polymorphisms (SNPs) to serve as instrument variables. However, selecting a small set of SNPs may not be ideal, as most complex traits have a polygenic or omnigenic architecture and are each influenced by thousands of SNPs. Here, motivated by the recent omnigenic hypothesis, we present an MR method that uses all genome-wide SNPs for causal inference. Our method uses summary statistics from genome-wide association studies as input, accommodates the commonly encountered horizontal pleiotropy effects and relies on a composite likelihood framework for scalable computation. We refer to our method as the omnigenic Mendelian randomization, or OMR. We examine the power and robustness of OMR through extensive simulations including those under various modeling misspecifications. We apply OMR to several real data applications, where we identify multiple complex traits that potentially causally influence coronary artery disease (CAD) and asthma. The identified new associations reveal important roles of blood lipids, blood pressure and immunity underlying CAD as well as important roles of immunity and obesity underlying asthma.

Genetic architecture of type 2 diabetes and its shared genetic component with low birth weight in African Americans

PURPOSE OF REVIEW

Recent large-scale multiancestry efforts has contributed to our knowledge of the hereditary basis of type 2 diabetes (T2D). The present review will summarize findings of the genetic basis of T2D in African Americans, a population group with a disproportionate burden of this disease.

RECENT FINDINGS

To date, >400 risk genetic variants have been found to be associated with the risk of T2D across populations of different ancestries. Although these findings are based on primarily European-ancestry populations, most of the identified loci show similar associations in African Americans. Ancestry-specific analyses including genome-wide associations studies (GWAS) in African Americans, Africans; as well as admixture mapping scans in African Americans have identified additional risk variants and genomic loci associate with the risk of T2D. These efforts have also uncovered new genetic links between low birth weight and T2D. In particular, admixture mapping approaches have identified a shared genetic ancestry component of both phenotypic traits in African Americans.

SUMMARY

Recent findings have helped us to better understand the genetic basis of T2D in African Americans. Of particular interest are new genetic discoveries linking low birth weight and T2D, two conditions with a much higher prevalence in African Americans compared to U.S. whites. Continuing work, including large-scale sequencing efforts would add to our knowledge of the genetic architecture of T2D in African Americans, as well as genetic links with other conditions.

The role of genetics in fetal programming of adult cardiometabolic disease

Disturbances affecting early development have broad repercussions on the individual's health during infancy and adulthood. Multiple observational studies throughout the years have shown that alterations of fetal growth are associated with increased cardiometabolic disease risks. However, the genetic component of this association only started to be investigated in the last 40 years, when single genes with distinct effects were investigated. Birth weight (BW), commonly reported as the outcome of developmental growth, has been estimated to be 20% to 60% heritable. Through Genome-Wide Association (GWA) meta-analyses, 190 different loci have been identified being associated with BW, and while many of these loci designate genes involved in glucose and lipid metabolism, with clear ties to fetal development, the role of others is not yet understood. In addition, due to its influence over the intrauterine environment, the maternal genotype also plays an important part in the determination of offspring BW, with the same loci having independent effects of different magnitude or even direction. There is still much to uncover regarding the genetic determinants of BW and the interactions between maternal, offspring, and even paternal genotype. To fully understand these, diverse and novel cohorts from multiple ancestries collecting extensive neonatal phenotype will be needed. This review compiles, chronologically, the main findings in the investigation of the genetics of BW.

Instrumental Heterogeneity in Sex-Specific Two-Sample Mendelian Randomization: Empirical Results From the Relationship Between Anthropometric Traits and Breast/Prostate Cancer

Background

In two-sample Mendelian randomization (MR) studies, sex instrumental heterogeneity is an important problem needed to address carefully, which however is often overlooked and may lead to misleading causal inference.

Methods

We first employed cross-trait linkage disequilibrium score regression (LDSC), Pearson's correlation analysis, and the Cochran's Q test to examine sex genetic similarity and heterogeneity in instrumental variables (IVs) of exposures. Simulation was further performed to explore the influence of sex instrumental heterogeneity on causal effect estimation in sex-specific two-sample MR analyses. Furthermore, we chose breast/prostate cancer as outcome and four anthropometric traits as exposures as an illustrative example to illustrate the importance of taking sex heterogeneity of instruments into account in MR studies.

Results

The simulation definitively demonstrated that sex-combined IVs can lead to biased causal effect estimates in sex-specific two-sample MR studies. In our real applications, both LDSC and Pearson's correlation analyses showed high genetic correlation between sex-combined and sex-specific IVs of the four anthropometric traits, while nearly all the correlation coefficients were larger than zero but less than one. The Cochran's Q test also displayed sex heterogeneity for some instruments. When applying sex-specific instruments, significant discrepancies in the magnitude of estimated causal effects were detected for body mass index (BMI) on breast cancer (P = 1.63E-6), for hip circumference (HIP) on breast cancer (P = 1.25E-20), and for waist circumference (WC) on prostate cancer (P = 0.007) compared with those generated with sex-combined instruments.

Conclusion

Our study reveals that the sex instrumental heterogeneity has non-ignorable impact on sex-specific two-sample MR studies and the causal effects of anthropometric traits on breast/prostate cancer would be biased if sex-combined IVs are incorrectly employed.

Leveraging Methylation Alterations to Discover Potential Causal Genes Associated With the Survival Risk of Cervical Cancer in TCGA Through a Two-Stage Inference Approach

BACKGROUND

Multiple genes were previously identified to be associated with cervical cancer; however, the genetic architecture of cervical cancer remains unknown and many potential causal genes are yet to be discovered.

METHODS

To explore potential causal genes related to cervical cancer, a two-stage causal inference approach was proposed within the framework of Mendelian randomization, where the gene expression was treated as exposure, with methylations located within the promoter regions of genes serving as instrumental variables. Five prediction models were first utilized to characterize the relationship between the expression and methylations for each gene; then, the methylation-regulated gene expression (MReX) was obtained and the association was evaluated via Cox mixed-effect model based on MReX. We further implemented the aggregated Cauchy association test (ACAT) combination to take advantage of respective strengths of these prediction models while accounting for dependency among the p-values.

RESULTS

A total of 14 potential causal genes were discovered to be associated with the survival risk of cervical cancer in TCGA when the five prediction models were separately employed. The total number of potential causal genes was brought to 23 when conducting ACAT. Some of the newly discovered genes may be novel (e.g., YJEFN3, SPATA5L1, IMMP1L, C5orf55, PPIP5K2, ZNF330, CRYZL1, PPM1A, ESCO2, ZNF605, ZNF225, ZNF266, FICD, and OSTC). Functional analyses showed that these genes were enriched in tumor-associated pathways. Additionally, four genes (i.e., COL6A1, SYDE1, ESCO2, and GIPC1) were differentially expressed between tumor and normal tissues.

CONCLUSION

Our study discovered promising candidate genes that were causally associated with the survival risk of cervical cancer and thus provided new insights into the genetic etiology of cervical cancer.

Stumped by the Hump: The Curious Rise and Fall of Norwegian Birthweights, 1991-2007

BACKGROUND

There was a distinct rise in mean birthweights in Norway starting in 1991 that plateaued in 1996-2002 and then declined to previous levels. We investigated whether these changes corresponded to trends in neonatal mortality or other birthweight-associated pregnancy outcomes. We also explored known predictors of birthweight and examined whether these could explain the birthweight trends.

METHODS

We calculated mean birthweight for all live births in Norway in each year from 1982 to 2016, together with annual neonatal mortality and proportion of infants born preterm, or with low Apgar score. We stratified mean birthweight over time by factors including parity, gestational age, and Scandinavian versus non-Scandinavian origin of mother, to test robustness of the pattern. In addition, we used multivariable linear regression to obtain adjusted estimates for mean birthweight per year.

RESULTS

A 50-g rise and fall of mean birthweights during a 25-year period was not accompanied by corresponding changes in neonatal mortality, preterm births, or Apgar scores. The distinct hump pattern was restricted to term births and was not apparent among infants of mothers born outside Scandinavia. We saw a similar pattern for Sweden but not Finland. Known predictors of birthweight (such as parity, mode of onset of delivery, and marital status) did not explain the hump.

CONCLUSIONS

A distinct temporal hump in mean birthweight among Norwegian term births had no obvious explanations. Furthermore, these fluctuations in birthweight were not associated indirectly with adverse outcomes in measures of infant health.

Aggregating multiple expression prediction models improves the power of transcriptome-wide association studies

Transcriptome-wide association study (TWAS) is an important integrative method for identifying genes that are causally associated with phenotypes. A key step of TWAS involves the construction of expression prediction models for every gene in turn using its cis-SNPs as predictors. Different TWAS methods rely on different models for gene expression prediction, and each such model makes a distinct modeling assumption that is often suitable for a particular genetic architecture underlying expression. However, the genetic architectures underlying gene expression vary across genes throughout the transcriptome. Consequently, different TWAS methods may be beneficial in detecting genes with distinct genetic architectures. Here, we develop a new method, HMAT, which aggregates TWAS association evidence obtained across multiple gene expression prediction models by leveraging the harmonic mean P-value combination strategy. Because each expression prediction model is suited to capture a particular genetic architecture, aggregating TWAS associations across prediction models as in HMAT improves accurate expression prediction and enables subsequent powerful TWAS analysis across the transcriptome. A key feature of HMAT is its ability to accommodate the correlations among different TWAS test statistics and produce calibrated P-values after aggregation. Through numerical simulations, we illustrated the advantage of HMAT over commonly used TWAS methods as well as ad hoc P-value combination rules such as Fisher's method. We also applied HMAT to analyze summary statistics of nine common diseases. In the real data applications, HMAT was on average 30.6% more powerful compared to the next best method, detecting many new disease-associated genes that were otherwise not identified by existing TWAS approaches. In conclusion, HMAT represents a flexible and powerful TWAS method that enjoys robust performance across a range of genetic architectures underlying gene expression.

Habitual consumption of alcohol with meals and lung cancer: a Mendelian randomization study

Background

The objective of this study was to determine the causal relationship between habitual alcohol consumption with meals and lung cancer.

Methods

Public genetic summary data from two large consortia [the Neale Lab and the International Lung Cancer Consortium (ILCCO)] were used for analysis. As the instrumental variables of habitual alcohol consumption with meals, data on genetic variants were retrieved from Neale Lab. Additionally, genetic data from other consortia [Global Lipid Genetics Consortium (GLGC), Tobacco, Alcohol and Genetics (TAG), Genetic Investigation of Anthropocentric Traits (GIANT)] were utilized to determine whether alcohol could causally alter some general risk factors for lung cancer. The primary outcome was the risk of lung cancer (11,348 cases and 15,861 controls in the ILCCO). The R package TwoSampleMR was used for analysis.

Results

Based on the inverse variance weighted method, the results of the two-sample Mendelian randomization (MR) analyses indicated that commonly consuming alcohol with meals was a protective factor, reducing lung cancer risk [odds ratio (OR) 0.175, 95% confidence interval (CI): 0.045–0.682, P=0.012]. The heterogeneity analysis revealed that the causal relationship analyses of different types of lung cancer all had low heterogeneity (P>0.05). The horizontal pleiotropic study showed that major bias was unlikely. The MR assumptions did not seem to be violated. The causal relationship analyses between habitual alcohol consumption with meals and some risk factors for cancers showed that this alcohol consumption habit was a beneficial factor for reducing body mass index (BMI) and the number of cigarettes smoked per day.

Conclusions

Habitual appropriate alcohol consumption with meals is a protective factor for the development of lung cancer.

Evaluation of the causal effects of blood lipid levels on gout with summary level GWAS data: two-sample Mendelian randomization and mediation analysis

Observational studies have identified gout patients are often comorbid with dyslipidemia. However, the relationship between dyslipidemia and gout is still unclear. We first performed Mendelian randomization (MR) to evaluate the causal effect of four lipid traits on gout and serum urate based on publicly available GWAS summary statistics (n ~100,000 for lipid, 69,374 for gout and 110,347 for serum urate). MR showed each standard deviation (SD) (~12.26 mg/dL) increase in HDL resulted in about 25% (95% CI 9.0%-38%, p = 3.31E-3) reduction of gout risk, with 0.09 mg/dL (95% CI: -0.12 to -0.05, p = 7.00E-04) decrease in serum urate, and each SD (~112.33 mg/dL) increase of TG was associated with 0.10 mg/dL (95% CI: 0.06-0.14, p = 9.87E-05) increase in serum urate. Those results were robust against various sensitive analyses. Additionally, independent effects of HDL and TG on gout/serum urate were confirmed with multivariable MR. Finally, mediation analysis demonstrated HDL or TG could also indirectly affect gout via the pathway of serum urate. In conclusion, our study confirmed the causal associations between HDL (and TG) and gout, and further revealed the effect of HDL or TG on gout could also be mediated via serum urate.

Assessing the Relationship Between Leukocyte Telomere Length and Cancer Risk/Mortality in UK Biobank and TCGA Datasets With the Genetic Risk Score and Mendelian Randomization Approaches

Background

Telomere length is an important indicator of tumor progression and survival for cancer patients. Previous work investigated the associations between genetically predicted telomere length and cancers; however, the types of cancers investigated in those studies were relatively limited or the telomere length-associated genetic variants employed often came from genome-wide association studies (GWASs) with small sample sizes.

Methods

We constructed the genetic risk score (GRS) for leukocyte telomere length based on 17 associated genetic variants available from the largest telomere length GWAS up to 78,592 individuals. Then, a comprehensive analysis was undertaken to evaluate the association between the constructed GRS and the risk or mortality of a wide range of cancers [i.e., 37 cancers in the UK Biobank and 33 cancers in The Cancer Genome Atlas (TCGA)]. We further applied the two-sample Mendelian randomization (MR) to estimate the causal effect of leukocyte telomere length on UK Biobank cancers via summary statistics.

Results

In the UK Biobank dataset, we found that the GRS of leukocyte telomere length was associated with a decreased risk of nine types of cancer (i.e., significant association with multiple myeloma, chronic lymphocytic leukemia, kidney/renal cell cancer, bladder cancer, malignant melanoma, basal cell carcinoma, and prostate cancer and suggestive association with sarcoma/fibrosarcoma and Hodgkin’s lymphoma/Hodgkin’s disease). In addition, we found that the GRS was suggestively associated with an increased risk of leukemia. In the TCGA dataset, we observed suggestive evidence that the GRS was associated with a high death hazard of rectum adenocarcinoma (READ), sarcoma (SARC), and skin cutaneous melanoma (SKCM), while the GRS was associated with a low death hazard of kidney renal papillary cell carcinoma (KIRP). The results of MR further supported the association for leukocyte telomere length on the risk of malignant melanoma, Hodgkin’s lymphoma/Hodgkin’s disease, chronic lymphocytic leukemia and multiple myeloma.

Conclusion

Our study reveals that telomere played diverse roles in different types of cancers. However, further validations in large-scale prospective studies and deeper investigations of the biologic mechanisms are warranted.

Higher Fibroblast Growth Factor 23 Levels Are Causally Associated With Lower Bone Mineral Density of Heel and Femoral Neck: Evidence From Two-Sample Mendelian Randomization Analysis

Background: Previous observational studies have indicated that high levels of fibroblast growth factor 23 (FGF23), a phosphoric hormone that inhibits calcitriol synthesis, in the blood is associated with the reduced bone mineral density (BMD); however, whether this association is causal remains unclear. In this study, we conducted a Mendelian Random (MR) study to investigate whether the genetic predisposition of higher FGF23 levels was causally associated with lower BMD in adults.

Methods: A two-sample MR was performed with five single nucleotide polymorphisms significantly associated with FGF23, selected as instrumental variables. Two-sample MR estimates were derived from summary-level data of large-sample genome-wide association studies for BMD and the levels of bone metabolism characteristics.

Results: The two-sample MR analysis showed that for every 1-unit increase in the log-transformed blood FGF23 level (pg/mL), the decreased levels of adult heel BMD (β = −0.201, se = 0.084, P = 0.016) and femoral neck BMD (β = −0.286, se = 0.126, P = 0.022) were noted, indicative of a causal relationship based on the inverse variance weighting method. However, FGF23 levels were not correlated with adult lumbar spine BMD (β = −0.166, se = 0.193, P = 0.389), and forearm BMD (β = −0.186, se = 0.366, P = 0.610). Moreover, the two-sample MR analysis suggested that there was no evidence for associations between FGF23 and adult calcium, phosphorus, 25(OH)D, creatinine, and magnesium levels.

Conclusions: This study suggests that there may be a causal relationship between blood FGF23 levels and BMD of the heel and femoral neck in adults; however, more investigations are necessary to determine whether FGF23 may be a potential biomarker and/or therapeutic target for diseases that affect bone mineralization.

The association between prenatal exposure to polycyclic aromatic hydrocarbons and birth weight: A meta-analysis

Background

Polycyclic aromatic hydrocarbons (PAHs) are a kind of endocrine disruptors, which can enter human body by the inhalation of PAH-containing matter and the ingestion of PAH-containing foodstuffs. Studies showed that PAHs can cross the placental barrier and might cause adverse effects on the fetus.

Objectives

This meta-analysis aimed to estimate the associations between prenatal exposure to PAHs and birth weight.

Methods

Articles published in English until May 8, 2020 and reported the effects of prenatal exposure to PAHs on birth weight were searched in multiple electronic databases including PubMed, the Web of Science, EMBASE and the Cochrane Library. The included studies were divided into three groups in accordance with the measurement of PAHs exposure. Then coefficient was extracted, conversed and synthesized by random-effects meta-analysis. And risk of bias was assessed for each study.

Results

A total of 3488 citations were searched and only 11 studies were included finally after double assessment. We found that there were no association between PAH-DNA adducts in cord blood (low/high) (OR: 1.0, 95%CI: 0.97, 1.03), 1-hydroxy pyrene (1-HP) concentration in maternal urine (OR: 1.0, 95%CI: 0.97, 1.03) and prenatal maternal airborne PAHs exposure (OR: 0.97, 95%CI: 0.93, 1.01) and birth weight. However, we observed ethnicity may change the effects of PAHs exposure on birth weight.

Conclusions

There is no significant relationship between prenatal exposure to PAHs and birth weight in our meta-analysis. Further studies are still needed for determining the effects of prenatal PAHs exposure on birth weight.

Mendelian randomization implies no direct causal association between leukocyte telomere length and amyotrophic lateral sclerosis

We employed Mendelian randomization (MR) to evaluate the causal relationship between leukocyte telomere length (LTL) and amyotrophic lateral sclerosis (ALS) with summary statistics from genome-wide association studies (n = ~ 38,000 for LTL and ~ 81,000 for ALS in the European population; n = ~ 23,000 for LTL and ~ 4,100 for ALS in the Asian population). We further evaluated mediation roles of lipids in the pathway from LTL to ALS. The odds ratio per standard deviation decrease of LTL on ALS was 1.10 (95% CI 0.93–1.31, p = 0.274) in the European population and 0.75 (95% CI 0.53–1.07, p = 0.116) in the Asian population. This null association was also detected between LTL and frontotemporal dementia in the European population. However, we found that an indirect effect of LTL on ALS might be mediated by low density lipoprotein (LDL) or total cholesterol (TC) in the European population. These results were robust against extensive sensitivity analyses. Overall, our MR study did not support the direct causal association between LTL and the ALS risk in neither population, but provided suggestive evidence for the mediation role of LDL or TC on the influence of LTL and ALS in the European population.

Genetics Insights in the Relationship Between Type 2 Diabetes and Coronary Heart Disease

Diabetes mellitus is a major risk factor for coronary heart disease (CHD). The major form of diabetes mellitus is type 2 diabetes mellitus (T2D), which is thus largely responsible for the CHD association in the general population. Recent years have seen major advances in the genetics of T2D, principally through ever-increasing large-scale genome-wide association studies. This article addresses the question of whether this expanding knowledge of the genomics of T2D provides insight into the etiologic relationship between T2D and CHD. We will investigate this relationship by reviewing the evidence for shared genetic loci between T2D and CHD; by examining the formal testing of this interaction (Mendelian randomization studies assessing whether T2D is causal for CHD); and then turn to the implications of this genetic relationship for therapies for CHD, for therapies for T2D, and for therapies that affect both. In conclusion, the growing knowledge of the genetic relationship between T2D and CHD is beginning to provide the promise for improved prevention and treatment of both disorders.

Mendelian randomization analysis does not support causal associations of birth weight with hypertension risk and blood pressure in adulthood

Epidemiology studies suggested that low birthweight was associated with a higher risk of hypertension in later life. However, little is known about the causality of such associations. In our study, we evaluated the causal association of low birthweight with adulthood hypertension following a standard analytic protocol using the study-level data of 183,433 participants from 60 studies (CHARGE-BIG consortium), as well as that with blood pressure using publicly available summary-level genome-wide association data from EGG consortium of 153,781 participants, ICBP consortium and UK Biobank cohort together of 757,601 participants. We used seven SNPs as the instrumental variable in the study-level analysis and 47 SNPs in the summary-level analysis. In the study-level analyses, decreased birthweight was associated with a higher risk of hypertension in adults (the odds ratio per 1 standard deviation (SD) lower birthweight, 1.22; 95% CI 1.16 to 1.28), while no association was found between genetically instrumented birthweight and hypertension risk (instrumental odds ratio for causal effect per 1 SD lower birthweight, 0.97; 95% CI 0.68 to 1.41). Such results were consistent with that from the summary-level analyses, where the genetically determined low birthweight was not associated with blood pressure measurements either. One SD lower genetically determined birthweight was not associated with systolic blood pressure (β = - 0.76, 95% CI - 2.45 to 1.08 mmHg), 0.06 mmHg lower diastolic blood pressure (β = - 0.06, 95% CI - 0.93 to 0.87 mmHg), or pulse pressure (β = - 0.65, 95% CI - 1.38 to 0.69 mmHg, all p > 0.05). Our findings suggest that the inverse association of birthweight with hypertension risk from observational studies was not supported by large Mendelian randomization analyses.

Does Maternal Normal Range Thyroid Function Play a Role in Offspring Birth Weight? Evidence From a Mendelian Randomization Analysis

BACKGROUND

The association between normal range thyroid function and offspring birth weight has been postulated, but evidence from observational studies is prone to be confounded. We conducted a two-sample Mendelian randomization (MR) study to explore the causal effects of maternal thyroid stimulating hormone (TSH) and free thyroxine (FT4) on birth weight.

METHODS

We utilized public shared summary-level statistics from European-ancestry genome wide association studies. We obtained 40 and 21 single nucleotide polymorphisms as instrumental variables, which were associated with TSH and FT4 levels at genome-wide significance (P < 5 × 10^-8). Partitioned maternal effects on birth weight were retrieved from datasets contributed by the Early Growth Genetics Consortium. Inverse-variance weighted method was employed in the primary MR analysis and multiple sensitivity analyses were implemented.

RESULTS

Genetically determined normal range thyroid function was not causally associated with offspring birth weight. Each one standard deviation (SD) increase in maternal TSH was associated with 0.002 SD higher of birth weight (95% confidence interval [CI], -0.021 to 0.025; P = 0.87). Similarly, change in birth weight was -0.001 SD (95% CI, -0.031 to 0.029; P = 0.94) per one SD higher in maternal FT4. Consistent results were yielded via additional MR methods. Sensitivity analyses demonstrated no presence of horizontal pleiotropy or heterogeneity.

CONCLUSION

This MR study did not identify a causality between normal range thyroid function and offspring birth weight in the Europeans.

Causal association of type 2 diabetes with amyotrophic lateral sclerosis: new evidence from Mendelian randomization using GWAS summary statistics

BACKGROUND

Associations between type 2 diabetes (T2D) and amyotrophic lateral sclerosis (ALS) were discovered in observational studies in both European and East Asian populations. However, whether such associations are causal remains largely unknown.

METHODS

We employed a two-sample Mendelian randomization approach to evaluate the causal relationship of T2D with the risk of ALS in both European and East Asian populations. Our analysis was implemented using summary statistics obtained from large-scale genome-wide association studies with ~660,000 individuals for T2D and ~81,000 individuals for ALS in the European population, and ~191,000 individuals for T2D and ~4100 individuals for ALS in the East Asian population. The causal relationship between T2D and ALS in both populations was estimated using the inverse-variance-weighted methods and was further validated through extensive complementary and sensitivity analyses.

RESULTS

Using multiple instruments that were strongly associated with T2D, a negative association between T2D and ALS was identified in the European population with the odds ratio (OR) estimated to be 0.93 (95% CI 0.88-0.99, p = 0.023), while a positive association between T2D and ALS was observed in the East Asian population with OR = 1.28 (95% CI 0.99-1.62, p = 0.058). These results were robust against instrument selection, various modeling misspecifications, and estimation biases, with the Egger regression and MR-PRESSO ruling out the possibility of horizontal pleiotropic effects of instruments. However, no causal association was found between T2D-related exposures (including glycemic traits) and ALS in the European population.

CONCLUSION

Our results provide new evidence supporting the causal neuroprotective role of T2D on ALS in the European population and provide empirically suggestive evidence of increasing risk of T2D on ALS in the East Asian population. Our results have an important implication on ALS pathology, paving ways for developing therapeutic strategies across multiple populations.