Use of genetic markers and gene-diet interactions for interrogating population-level causal influences of diet on health

Exploring the genetic causal inference between plasma lipidome and lung carcinoma: a bidirectional mendelian randomization study

BACKGROUND

Clinical observational studies have highlighted differences in plasma lipid profiles between lung carcinoma patients and healthy individuals. However, the causal relationship underlying these differences remains unclear. This study aims to investigate the bidirectional causal relationship between 179 plasma lipids and lung carcinoma.

METHODS

A bivariate two-sample Mendelian randomization (MR) study was conducted using data from public genome-wide association studies (GWAS). The primary analytical technique employed was the inverse variance weighting method (IVW), with MR-Egger, weighted-median, and weighted mode as supplementary methods. Sensitivity analyses including Cochran's Q test and MR-Egger intercept test were performed to ensure the robustness of the results.

RESULTS

Mendelian randomization analysis revealed positive associations between levels of certain plasma lipidome-Sterol ester 27:1/20:5 levels (OR 1.162, 95% confidence interval (CI) 1.077-1254, P 1.15e-4), Phosphatidylcholine (PC) 20:4_0:0 levels (OR 1.112, 95%CI 1.051-1.176, P 2.33e-4), PC 17:0_20:4 levels (OR 1.108, 95%CI 1.051-1.167, P 1.33e-4, PC 18:0_20:4 levels (OR 1.094, 95%CI 1.046-1.144, P 8.08e-5), PC O-16:0:4 levels (OR 1.180, 95%CI 1.089-1.277, P4.61e-5), PC O-16:1_20:4 levels (OR 1.155, 95%CI 1.077-1.239, P 5.00e-5)-with the risk of lung carcinoma. Conversely, PC 15:0_18:2 levels (OR 0.823, 95%CI 0.760-0.892, P1.95e-6), PC 16:0_18:2 levels (OR 0.863, 95%CI 0.801-0.931, P 1.28e-4), PC 16:1_18:2 levels (OR 0.856, 95%CI 0.791-0.926, P 1.13e-4), PC 18:1_18:2 levels (OR 0.847, 95%CI 0.77-0.911, P 9.15e-6) were inversely associated with the risk of lung carcinoma. Reverse Mendelian randomization analysis indicated that lung carcinoma did not have a significant causal effect on the 179 plasma lipids.

CONCLUSION

Our study reveals the causal relationship between plasma lipidome and lung cancer, provides preliminary genetic evidence, and provides a new idea for understanding the pathogenesis of lung cancer and finding promising therapeutic targets.

Summarizing attributable factors and evaluating risk of bias of Mendelian randomization studies for Alzheimer's dementia and cognitive status: a systematic review and meta-analysis

BACKGROUND

No effective treatment is available to delay or reverse the onset and progression of Alzheimer's dementia (AD). Mild cognitive impairment, a clinical state between normal aging and AD, may offer the proper window for AD intervention and treatment. This systematic review aimed to summarize evidence from Mendelian randomization (MR) studies exploring factors attributable to AD and related cognitive status and to assess its credibility.

METHODS

We searched PubMed, Embase, MEDLINE, and the Cochrane Library to identify MR studies investigating the associations between any factor and AD and related cognitive status. The risk of bias in MR studies was evaluated using nine signaling questions tailored to identify potential biases based on the STROBE-MR guidelines.

RESULTS

A total of 125 eligible publications were examined, including 106 AD-related MR studies reporting 674 records and 28 cognition-related MR studies reporting 141 records. We identified 185 unique causal risk factors for AD and 49 for cognitive status. More than half of the MR studies reporting AD or cognitive status outcomes exhibited poor methodological quality, with a high risk of bias observed in 59% of the AD-related studies and 64% of the cognitive-related studies.

CONCLUSIONS

This systematic review summarized modifiable factors and omics signatures, providing a database of MR studies on AD and related cognitive status. The evaluation of bias risk in MR studies serves to raise awareness and improve overall quality. A critical appraisal checklist for assessing the risk of bias may pave the way for the development of a standardized tool.

SYSTEMATIC REVIEW REGISTRATION

The review protocol was registered with the Prospective Register of Systematic Reviews (PROSPERO) under the registration number CRD42023213990.

Association of 25-hydroxyvitamin D with Parkinson's disease based on the results from the NHANES 2007 to 2018 and Mendelian randomization analysis

An abundance of observational researches had suggested that vitamin D insufficient was related to Parkinson's disease (PD) risk. However, their relationships were debatable and the causality remains uncertain. We intended to evaluate the association between 25-hydroxyvitamin D [25(OH)D] and Parkinson's disease (PD) risk using NHANES data (2007-2018) and Mendelian randomization (MR) analyses with the genome-wide association study (GWAS) summary data. Demographic characteristics and multivariable-adjusted logistic regression were conducted to assess the relationship between the serum 25(OH)D levels and risk of PD prevalence by utilizing NHANES database. Besides, a two-sample MR analysis was applied to evaluate the causal association between serum 25(OH)D levels and PD risk. The main analysis was conducted by citing the inverse-variance-weighted (IVW) approach, while additional MR approaches and multiple sensitivity analysis were cited to evaluate the robustness and pleiotropy for the discoveries. In total, 30,796 adults from NHANES 2007-2018 were selected for the present research. As a result, 1.1% participants with PD (mean age: 61.9 ± 15.5 years), while 68.5% reported vitamin D insufficient. Compared with participants without PD, those with PD had a greater level of 25(OH)D (P < 0.01). However, after adjusted for demographic characteristics and comorbid factors, this association was not observed. Furthermore, no potential causal relationships between the serum level of 25(OH)D and PD risk were found via MR analysis (IVW-MR: OR = 1.082; 95% CI, 0.902 to 1.297; P = 0.395). After eliminating variants with horizontal pleiotropy risk, pleiotropy-robust MR analysis presented similar results. In conclusion, this research suggested that serum 25(OH)D levels was not correlated with PD risk. Additionally, the MR analyses revealed no significant causal association between serum 25(OH)D levels and PD risk at the genetic level. Awareness of these findings may improve personalized prevention and treatment of PD.

Erythema nodosum, malignant melanoma and non-melanoma skin cancer in relation to inflammatory bowel disease: a Mendelian randomization study

Inflammatory bowel disease (IBD) is a multisystem condition that could affect the cutaneous systems, namely cutaneous extraintestinal manifestations (EIMs). It has been suggested that IBD is associated with erythema nodosum (EN), malignant melanoma (MM) and non-melanoma skin cancer (NMSC). However, the potential causal relationship between IBD and the mentioned above cutaneous EIMs is still unclear. This study aims to determine the effect of IBD on EN, MM and NMSC within a Mendelian randomization (MR) design. Summary-level data for IBD, EN, MM, NMSC were obtained from large-scale genome-wide association studies. We utilized five different methods, including the inverse variance weighted model (IVW), MR Egger, Weighted median, Simple mode, Weighted mode in the MR analysis, then the Cochran's Q test, the MR-Egger pleiotropy test, the MR-PRESSO global pleiotropy test and leave-one-out sensitivity test were used to evaluate the heterogeneity and pleiotropy of identified IVs. To further ensure the validity of our findings, we evaluated the strength of the instrumental variables using the F-statistic and estimated the statistical power of our study. Findings were verified using an independent validation dataset, as well as through different MR methods with different model assumptions. MR analysis suggested that genetically determined IBD had a detrimental causal effect on NMSC (IVW: odds ratio [OR] = 1.002037, 95% confidence interval [CI] = 1.0001150-1.003962, P = 0.03776677), but not on EN (IVW: [OR] = 1.0937191, 95% [CI] = 0.9685831-1.235022, P = 0.1484349) and MM (IVW: [OR] = 0.9998064, 95% [CI] = 0.9994885-1.000124, P = 0.2326482). Besides, a positive causal effect of IBD on NMSC was verified in an independent validation dataset (IVW: [OR] = 1.002651, 95% [CI] = 1.0006524-1.004654, P = 0.009307506). The present study corroborated the causal relationship between IBD and NMSC. In contrast, our results showed no evidence of a causal association of IBD on EN and MM. These findings provide new insights into increasing attention to patients with IBD to prevent concurrent NMSC.

Causal effect of obesity and adiposity distribution on the risk of pressure ulcers and potential mediation by type 2 diabetes mellitus: insights from multivariable mendelian randomization and mediation analysis

Previous observational studies have identified a link between obesity, adiposity distribution, type 1 Diabetes Mellitus (T1DM), type 2 Diabetes Mellitus (T2DM), and the risk of pressure ulcers (PUs). However, the definitive causality between obesity and PUs, and potential DM mediators remains unclear. Univariable, multivariable, and mediation Mendelian randomization (MR) analyses were conducted to explore the mediating role of T1DM or T2DM in the association between obesity, adiposity distribution, and PUs. Instrumental variables for obesity and adiposity distribution, including Body Mass Index (BMI), waist circumference, hip circumference, trunk fat mass, whole body fat mass, trunk fat percentage, and body fat percentage, were selected from two genome-wide association studies (GWAS). In univariable MR analysis, BMI, hip circumference, and obesity were associated with PUs using inverse variance weighted (IVW) regression. These findings were further corroborated by the replication cohorts and meta-analysis (BMI: OR = 1.537, 95% CI = 1.294-1.824, p < 0.001; Hip circumference: OR = 1.369, 95% CI = 1.147-1.635, p < 0.001; Obesity: OR = 1.235, 95% CI = 1.067-1.431, p = 0.005), respectively. Even after adjusting for confounding factors such as T1DM and T2DM, BMI and hip circumference remained statistically significant in multivariable MR analyses. T2DM may mediate the pathogenesis of BMI-related (OR = 1.106, 95% CI = 1.054-1.160, p = 0.037) and obesity-related PUs (OR = 1.053, 95% CI = 1.034-1.973, p = 0.004). These findings provide insights for the prevention and treatment of PUs, particularly in patients with obesity or DM.

Mediators of the association between depression and migraine: a mendelian randomization study

Background

An association between depression and migraine has been reported in observational studies; however, conventional observational studies are prone to bias. This study aims to investigate the causal relationship between depression and migraine and to quantify the mediating effects of known risk factors.

Methods

We applied two-sample Mendelian randomization and utilized single nucleotide polymorphisms as genetic instruments for exposure (depression) and mediators (sleep traits). We utilized summary data on genome-wide association studies for depression, sleep-related traits mediators and migraine. For depression, genome-wide association studies (depression) were utilized as a test cohort for the primary analysis. Moreover, genome-wide association studies (major depressive disorder) were utilized to test the stability of the results for the validation cohort. IVW and MR-Egger regression were applied to test the heterogeneity, and Cochran's Q statistics were calculated to quantitatively evaluate the heterogeneity. MR-PRESSO analyses were utilized to examine and correct possible horizontal pleiotropy through removing outliers, and leave-one-out analyses were utilized to identify outlier SNPs.

Results

Genetically predicted depression was associated with migraine (OR = 1.321, 95% CI: 1.184-1.473, p < 0.001). Furthermore, risk factors insomnia was associated with migraine risk (OR = 1.766, 95% CI: 1.120-2.784, p = 0.014). The mediator insomnia accounted for 19.5% of the total effect of depression on migraine.

Conclusion

These results support a potential causal effect of depression on migraine, partly mediated by insomnia. Therefore, the enhancement of sleep quality and difficulty in falling asleep may reduce the migraine burden occasioned by depression.

Causal association of blood cell traits with inflammatory bowel diseases: a Mendelian randomization study

Background

Observational studies have found associations between blood cell traits and inflammatory bowel diseases (IBDs), whereas the causality and dose-effect relationships are still undetermined.

Methods

Two-sample Mendelian randomization (MR) analyses using linear regression approaches, as well as Bayesian model averaging (MR-BMA), were conducted to identify and prioritize the causal blood cell traits for Crohn's disease (CD) and ulcerative colitis (UC). An observational study was also performed using restricted cubic spline (RCS) to explore the relationship between important blood cell traits and IBDs.

Results

Our uvMR analysis using the random effects inverse variance weighted (IVW) method identified eosinophil (EOS) as a causal factor for UC (OR = 1.36; 95% CI: 1.13, 1.63). Our MR-BMA analysis further prioritized that high level of lymphocyte (LYM) decreased CD risk (MIP = 0.307; θ ^ MACE = -0.059; PP = 0.189; θ ^ λ = -0.173), whereas high level of EOS increased UC risk (MIP = 0.824; θ ^ MACE = 0.198; PP = 0.627; θ ^ λ = 0.239). Furthermore, the observational study clearly depicts the nonlinear relationship between important blood cell traits and the risk of IBDs.

Conclusion

Using MR approaches, several blood cell traits were identified as risk factors of CD and UC, which could be used as potential targets for the management of IBDs. Stratified genome-wide association studies (GWASs) based on the concentration of traits would be helpful owing to the nonlinear relationships between blood cell traits and IBDs, as demonstrated in our clinical observational study. Together, these findings could shed light on the clinical strategies applied to the management of CD and UC.

Exploring the burden of mixed dyslipidemia in patients with type 2 diabetes mellitus: A cross-sectional study in Kashmir, India

BACKGROUND

Diabetes-related dyslipidemia is a multifaceted, complicated disorder characterized by an abnormal lipid profile in individuals with diabetes. The incidence of different types of dyslipidemia, however, was not a focus of prior investigations. The patients were characterized into three categories of dyslipidemia. Different patterns of dyslipidemia were combined into single dyslipidemia (7 patterns), mixed dyslipidemia (16 patterns), and triple dyslipidemia (4 patterns).

METHODS

In this cross-sectional study, 586 people suffering from type 2 diabetes mellitus (T2DM) were included. We assessed the serum lipid profile and used log (TG/HDL-C) to determine the atherogenic index of plasma (AIP). Dyslipidemia was examined as a categorical variable, and the findings were presented as percentages and numbers. To compare categorical variables, we either utilized Fisher exact tests or Chi square tests.

RESULTS

The study comprised of 586 T2DM patients, with 310 (52.9%) women and 276 (47.1%) men. Women have significantly higher hypertension (33.6%) as compared to men (23.2%). 18.94% (111) of patients were having coronary artery disease (CAD) history consisting of 12.28% (72) females and 6.66% (39) males, a difference which is statistically significant. 98.12% of total individuals had as a minimum of one lipid abnormality. 4.61% (27) of study subjects were having isolated dyslipidemia and 93.51% (548) had dual or triple pattern of dyslipidemia (mixed dyslipidemia). High AIP >0.24 (94.8%) was the most predominant trend of dyslipidemia. The dual combination of AIP (>0.24) and HDL (<50 mg/dL in Females and <40 mg/dL in Males) was found to be the most common pattern of mixed dyslipidemia (68.08%). The most prevalent trend of isolated dyslipidemia was found to be high AIP (>0.24), In patients with CAD history. Among the mixed dyslipidemia, the common pattern of dyslipidemia (71.17%) was the dual combination of high AIP (>0.24) and low HDL (<50 mg/dL women and <40 mg/dL males). The triple combination of TG (≥200 mg/dL) and HDL (<40 and <50 mg/dL) and LDL (≥100 mg/dL) was only found in females.

CONCLUSION

In conclusion, dyslipidemia is highly prevalent in T2DM patients, with mixed dyslipidemia being the most common type observed in the community of Kashmir valley, India. High AIP was the most prevalent pattern in the current investigation.

Pervasive Sharing of Causal Genetic Risk Factors Contributes to Clinical and Molecular Overlap between Sjögren's Disease and Systemic Lupus Erythematosus

SjD (Sjögren's Disease) and SLE (Systemic Lupus Erythematosus) are similar diseases. There is extensive overlap between the two in terms of both clinical features and pathobiologic mechanisms. Shared genetic risk is a potential explanation of this overlap. In this study, we evaluated whether these diseases share causal genetic risk factors. We compared the causal genetic risk for SLE and SjD using three complementary approaches. First, we examined the published GWAS results for these two diseases by analyzing the predicted causal gene protein-protein interaction networks of both diseases. Since this method does not account for overlapping risk intervals, we examined whether such intervals also overlap. Third, we used two-sample Mendelian randomization (two sample MR) using GWAS summary statistics to determine whether risk variants for SLE are causal for SjD and vice versa. We found that both the putative causal genes and the genomic risk intervals for SLE and SjD overlap 28- and 130-times more than expected by chance (p < 1.1 × 10-24 and p < 1.1 × 10-41, respectively). Further, two sample MR analysis confirmed that alone or in aggregate, SLE is likely causal for SjD and vice versa. [SjD variants predicting SLE: OR = 2.56; 95% CI (1.98-3.30); p < 1.4 × 10-13, inverse-variance weighted; SLE variants predicting SjD: OR = 1.36; 95% CI (1.26-1.47); p < 1.6 × 10-11, inverse-variance weighted]. Notably, some variants have disparate impact in terms of effect size across disease states. Overlapping causal genetic risk factors were found for both diseases using complementary approaches. These observations support the hypothesis that shared genetic factors drive the clinical and pathobiologic overlap between these diseases. Our study has implications for both differential diagnosis and future genetic studies of these two conditions.

Socioeconomic status may affect association of vegetable intake with risk of ischemic cardio-cerebral vascular disease: a Mendelian randomization study

Background

Previous studies found that increasing vegetable intake benefits are reduced after adjustment for socioeconomic factors. Using genetic variation as an instrumental variable for vegetable intake and socioeconomic status, we investigated the relationship between vegetable intake and ischemic cardio-cerebral vascular diseases and focused on whether socioeconomic status was a possible confounder.

Methods

From three independent genome-wide association studies, we extracted instrumental variables reflecting raw and cooked vegetable intake, which were used to perform Mendelian randomization analysis. To evaluate the effects of socioeconomic factors on vegetable intake, univariate and multivariate Mendelian randomization analyses were performed using single nucleotide polymorphisms representing education attainment and household income reported in the literature. We also performed outlier assessment and a series of sensitivity analyses to confirm the results.

Results

Genetically predicted raw and cooked vegetable intake were not associated with any ischemic cardio-cerebral vascular diseases and lipid components after Bonferroni correction. Univariate Mendelian randomized analysis revealed that raw vegetable intake was positively correlated with education attainment (β = 0.04, p = 0.029) and household income (β = 0.07, p < 0.001). Multivariate Mendelian randomized model showed a positive correlation between household income and raw vegetable intake (β = 0.06, p = 0.004). Socioeconomic status was closely associated with eating habits and lifestyle related to the risk of cardiovascular diseases.

Conclusion

Genetically determined raw and cooked vegetable intake was not associated with significant benefits in terms of ischemic cardio-cerebral vascular diseases while genetically determined socioeconomic status may have an impact on vegetable intake. Socioeconomic status, which was closely associated with other eating habits and lifestyle, may affect the association between vegetable intake and ischemic cardio-cerebral vascular diseases.

Causal relationship between obesity and iron deficiency anemia: a two-sample Mendelian randomization study

Background

Observational studies have suggested an association between obesity and iron deficiency anemia, but such studies are susceptible to reverse causation and residual confounding. Here we used Mendelian randomization to assess whether the association might be causal.

Methods

Data on single-nucleotide polymorphisms that might be associated with various anthropometric indicators of obesity were extracted as instrumental variables from genome-wide association studies in the UK Biobank. Data on genetic variants in iron deficiency anemia were extracted from a genome-wide association study dataset within the Biobank. Heterogeneity in the data was assessed using inverse variance-weighted regression, Mendelian randomization Egger regression, and Cochran's Q statistic. Potential causality was assessed using inverse variance-weighted, Mendelian randomization Egger, weighted median, maximum likelihood and penalized weighted median methods. Outlier SNPs were identified using Mendelian randomization PRESSO analysis and "leave-one-out" analysis.

Results

Inverse variance-weighted regression associated iron deficiency anemia with body mass index, waist circumference, trunk fat mass, body fat mass, trunk fat percentage, and body fat percentage (all odds ratios 1.003-1.004, P ≤ 0.001). Heterogeneity was minimal and no evidence of horizontal pleiotropy was found.

Conclusion

Our Mendelian randomization analysis suggests that obesity can cause iron deficiency anemia.

Research gaps and opportunities in precision nutrition: an NIH workshop report

Precision nutrition is an emerging concept that aims to develop nutrition recommendations tailored to different people's circumstances and biological characteristics. Responses to dietary change and the resulting health outcomes from consuming different diets may vary significantly between people based on interactions between their genetic backgrounds, physiology, microbiome, underlying health status, behaviors, social influences, and environmental exposures. On 11-12 January 2021, the National Institutes of Health convened a workshop entitled "Precision Nutrition: Research Gaps and Opportunities" to bring together experts to discuss the issues involved in better understanding and addressing precision nutrition. The workshop proceeded in 3 parts: part I covered many aspects of genetics and physiology that mediate the links between nutrient intake and health conditions such as cardiovascular disease, Alzheimer disease, and cancer; part II reviewed potential contributors to interindividual variability in dietary exposures and responses such as baseline nutritional status, circadian rhythm/sleep, environmental exposures, sensory properties of food, stress, inflammation, and the social determinants of health; part III presented the need for systems approaches, with new methods and technologies that can facilitate the study and implementation of precision nutrition, and workforce development needed to create a new generation of researchers. The workshop concluded that much research will be needed before more precise nutrition recommendations can be achieved. This includes better understanding and accounting for variables such as age, sex, ethnicity, medical history, genetics, and social and environmental factors. The advent of new methods and technologies and the availability of considerably more data bring tremendous opportunity. However, the field must proceed with appropriate levels of caution and make sure the factors listed above are all considered, and systems approaches and methods are incorporated. It will be important to develop and train an expanded workforce with the goal of reducing health disparities and improving precision nutritional advice for all Americans.

Mendelian randomization study of the effect of coronary artery calcification on atherosclerotic cardiovascular diseases

Calcium calcification in the wall of arteries (CAC) leads to a higher risk of atherosclerosis related outcomes, especially myocardial infarction (MI). Nevertheless, the causal role of CAC on other related outcomes is unclear. In this study, we used Mendelian randomization (MR) to systematically investigate the causal role of CAC across a broad range of atherosclerotic cardiovascular diseases including coronary heart disease, angina, MI, ischemic heart disease, stroke, and peripheral vascular disease. Publicly available data from the UK biobank and other data sources were used. Using the two-sample Mendelian randomization (MR) approach, we applied 3 MR models including the inverse variance weighted, the weighted-median, and the weighted-mode methods. Eight SNPs associated with CAC were selected as instrumental variables. We observed causal evidence of CAC on MI consistently across all MR models (P_IVW = 1.0 × 10^-4, P_W-Median = 1.1 × 10^-4, P_W-Mode = 3.8 × 10^-2) and this causation is shown in an acute transmural MI of inferior wall (P_IVW = 1.5 × 10^-4, P_W-Median = 4.8 × 10^-5, P_W-Mode = 3.2 × 10^-2) but not consistently observed in an anterior wall. As each site of acute MI was suggested to have relatively specific mechanisms, our finding suggested that the causal role of CAC on MI is in an inferior wall possibly as a consequence of large calcification from a prolonged process, whereas non-calcified artery plaque or other underlying mechanisms may predominantly play role in an anterior infarction during an advanced atherosclerotic process.

Association Between Brain Structure and Alcohol Use Behaviors in Adults: A Mendelian Randomization and Multiomics Study

Importance

Past studies have identified associations between brain macrostructure and alcohol use behaviors. However, identifying directional associations between these phenotypes is difficult due to the limitations of observational studies.

Objective

To use mendelian randomization (MR) to identify directional associations between brain structure and alcohol use and elucidate the transcriptomic and cellular underpinnings of identified associations.

Design, Setting, and Participants

The main source data comprised summary statistics from population-based and case-control genome-wide association studies (GWAS) of neuroimaging, behavioral, and clinical phenotypes (N = 763 874). Using these data, bidirectional and multivariable MR was performed analyzing associations between brain macrostructure and alcohol use. Downstream transcriptome-wide association studies (TWAS) and cell-type enrichment analyses investigated the biology underlying identified associations. The study approach was data driven and did not test any a priori hypotheses. Data were analyzed August 2021 to May 2022.

Main Outcomes and Measures

Brain structure phenotypes (global cortical thickness [GCT] and global cortical surface area [GCSA] in 33 709 individuals and left-right subcortical volumes in 19 629 individuals) and alcohol use behaviors (alcoholic drinks per week [DPW] in 537 349 individuals, binge drinking frequency in 143 685 individuals, and alcohol use disorder in 8845 individuals vs 20 657 control individuals [total of 29 502]).

Results

The main bidirectional MR analyses were performed in samples totaling 763 874 individuals, among whom more than 94% were of European ancestry, 52% to 54% were female, and the mean cohort ages were 40 to 63 years. Negative associations were identified between genetically predicted GCT and binge drinking (β, -2.52; 95% CI, -4.13 to -0.91) and DPW (β, -0.88; 95% CI, -1.37 to -0.40) at a false discovery rate (FDR) of 0.05. These associations remained significant in multivariable MR models that accounted for neuropsychiatric phenotypes, substance use, trauma, and neurodegeneration. TWAS of GCT and alcohol use behaviors identified 5 genes at the 17q21.31 locus oppositely associated with GCT and binge drinking or DPW (FDR = 0.05). Cell-type enrichment analyses implicated glutamatergic cortical neurons in alcohol use behaviors.

Conclusions and Relevance

The findings in this study show that the associations between GCT and alcohol use may reflect a predispositional influence of GCT and that 17q21.31 genes and glutamatergic cortical neurons may play a role in this association. While replication studies are needed, these findings should enhance the understanding of associations between brain structure and alcohol use.

Proxy gene-by-environment Mendelian randomization study confirms a causal effect of maternal smoking on offspring birthweight, but little evidence of long-term influences on offspring health

Background

A lack of genetic data across generations makes transgenerational Mendelian randomization (MR) difficult. We used UK Biobank and a novel proxy gene-by-environment MR to investigate effects of maternal smoking heaviness in pregnancy on offspring health, using participants’ (generation one: G1) genotype (rs16969968 in CHRNA5) as a proxy for their mothers’ (G0) genotype.

Methods

We validated this approach by replicating an established effect of maternal smoking heaviness on offspring birthweight. Then we applied this approach to explore effects of maternal (G0) smoking heaviness on offspring (G1) later life outcomes and on birthweight of G1 women’s children (G2).

Results

Each additional smoking-increasing allele in offspring (G1) was associated with a 0.018 [95% confidence interval (CI): -0.026, -0.009] kg lower G1 birthweight in maternal (G0) smoking stratum, but no meaningful effect (-0.002 kg; 95% CI: -0.008, 0.003) in maternal non-smoking stratum (interaction P-value = 0.004). The differences in associations of rs16969968 with grandchild’s (G2) birthweight between grandmothers (G0) who did, versus did not, smoke were heterogeneous (interaction P-value = 0.042) among mothers (G1) who did (-0.020 kg/allele; 95% CI: -0.044, 0.003), versus did not (0.007 kg/allele; 95% CI: -0.005, 0.020), smoke in pregnancy.

Conclusions

Our study demonstrated how offspring genotype can be used to proxy for the mother’s genotype in gene-by-environment MR. We confirmed the causal effect of maternal (G0) smoking on offspring (G1) birthweight, but found little evidence of an effect on G1 longer-term health outcomes. For grandchild’s (G2) birthweight, the effect of grandmother’s (G0) smoking heaviness in pregnancy may be modulated by maternal (G1) smoking status in pregnancy.

Synergizing Mouse and Human Studies to Understand the Heterogeneity of Obesity

Obesity is routinely considered as a single disease state, which drives a "one-size-fits-all" approach to treatment. We recently convened the first annual University of North Carolina Interdisciplinary Nutrition Sciences Symposium to discuss the heterogeneity of obesity and the need for translational science to advance understanding of this heterogeneity. The symposium aimed to advance scientific rigor in translational studies from animal to human models with the goal of identifying underlying mechanisms and treatments. In this review, we discuss fundamental gaps in knowledge of the heterogeneity of obesity ranging from cellular to population perspectives. We also advocate approaches to overcoming limitations in the field. Examples include the use of contemporary mouse genetic reference population models such as the Collaborative Cross and Diversity Outbred mice that effectively model human genetic diversity and the use of translational models that integrate -omics and computational approaches from pre-clinical to clinical models of obesity. Finally, we suggest best scientific practices to ensure strong rigor that will allow investigators to delineate the sources of heterogeneity in the population with obesity. Collectively, we propose that it is critical to think of obesity as a heterogeneous disease with complex mechanisms and etiologies, requiring unique prevention and treatment strategies tailored to the individual.

Educational attainment impacts drinking behaviors and risk for alcohol dependence: results from a two-sample Mendelian randomization study with ~780,000 participants

Observational studies suggest that lower educational attainment (EA) may be associated with risky alcohol use behaviors; however, these findings may be biased by confounding and reverse causality. We performed two-sample Mendelian randomization (MR) using summary statistics from recent genome-wide association studies (GWAS) with >780,000 participants to assess the causal effects of EA on alcohol use behaviors and alcohol dependence (AD). Fifty-three independent genome-wide significant SNPs previously associated with EA were tested for association with alcohol use behaviors. We show that while genetic instruments associated with increased EA are not associated with total amount of weekly drinks, they are associated with reduced frequency of binge drinking ≥6 drinks (ßIVW = -0.198, 95% CI, -0.297 to -0.099, PIVW = 9.14 × 10-5), reduced total drinks consumed per drinking day (ßIVW = -0.207, 95% CI, -0.293 to -0.120, PIVW = 2.87 × 10-6), as well as lower weekly distilled spirits intake (ßIVW = -0.148, 95% CI, -0.188 to -0.107, PIVW = 6.24 × 10-13). Conversely, genetic instruments for increased EA were associated with increased alcohol intake frequency (ßIVW = 0.331, 95% CI, 0.267-0.396, PIVW = 4.62 × 10-24), and increased weekly white wine (ßIVW = 0.199, 95% CI, 0.159-0.238, PIVW = 7.96 × 10-23) and red wine intake (ßIVW = 0.204, 95% CI, 0.161-0.248, PIVW = 6.67 × 10-20). Genetic instruments associated with increased EA reduced AD risk: an additional 3.61 years schooling reduced the risk by ~50% (ORIVW = 0.508, 95% CI, 0.315-0.819, PIVW = 5.52 × 10-3). Consistency of results across complementary MR methods accommodating different assumptions about genetic pleiotropy strengthened causal inference. Our findings suggest EA may have important effects on alcohol consumption patterns and may provide potential mechanisms explaining reported associations between EA and adverse health outcomes.

Evaluating and Strengthening the Evidence for Nutritional Bone Research: Ready to Break New Ground?

A healthy diet is essential to attain genetically determined peak bone mass and maintain optimal skeletal health across the adult lifespan. Despite the importance of nutrition for bone health, many of the nutritional requirements of the skeleton across the lifespan remain underexplored, poorly understood, or controversial. With increasingly aging populations, combined with rapidly changing diets and lifestyles globally, one anticipates large increases in the prevalence of osteoporosis and incidence of osteoporotic fractures. Robust, transparent, and reproducible nutrition research is a cornerstone for developing reliable public health recommendations to prevent osteoporosis and osteoporotic fractures. However, nutrition research is often criticized or ignored by healthcare professionals due to the overemphasis of weak science, conflicting, confusing or implausible findings, industry interests, common misconceptions, and strong opinions. Conversely, spurious research findings are often overemphasized or misconstrued by the media or prominent figures especially via social media, potentially leading to confusion and a lack of trust by the general public. Recently, reforms of the broader discipline of nutrition science have been suggested and promoted, leading to new tools and recommendations to attempt to address these issues. In this perspective, we provide a brief overview of what has been achieved in the field on nutrition and bone health, focusing on osteoporosis and osteoporotic fractures. We discuss what we view as some of the challenges, including inherent difficulties in assessing diet and its change, disentangling complex interactions between dietary components and between diet and other factors, selection of bone-related outcomes for nutrition studies, obtaining evidence with more unbiased designs, and perhaps most importantly, ensuring the trust of the public and healthcare professionals. This perspective also provides specific recommendations and highlights new developments and future opportunities for scientists studying nutrition and bone health. © 2021 American Society for Bone and Mineral Research (ASBMR).

Educational attainment reduces the risk of suicide attempt among individuals with and without psychiatric disorders independent of cognition: a bidirectional and multivariable Mendelian randomization study with more than 815,000 participants

Rates of suicidal behavior are increasing in the United States and identifying causal risk factors continues to be a public health priority. Observational literature has shown that educational attainment (EA) and cognitive performance (CP) influence suicide attempt risk; however, the causal nature of these relationships is unknown. Using summary statistics from genome-wide association studies (GWAS) of EA, CP, and suicide attempt risk with > 815,000 combined white participants of European ancestry, we performed multivariable Mendelian randomization (MR) to disentangle the effects of EA and CP on attempted suicide. In single-variable MR (SVMR), EA and CP appeared to reduce suicide attempt risk (EA odds ratio (OR) per standard deviation (SD) increase in EA (4.2 years), 0.524, 95% CI, 0.412-0.666, P = 1.07 × 10-7; CP OR per SD increase in standardized score, 0.714, 95% CI, 0.577-0.885, P = 0.002). Conversely, bidirectional analyses found no effect of a suicide attempt on EA or CP. Using various multivariable MR (MVMR) models, EA seems to be the predominant risk factor for suicide attempt risk with the independent effect (OR, 0.342, 95% CI, 0.206-0.568, P = 1.61 × 10-4), while CP had no effect (OR, 1.182, 95% CI, 0.842-1.659, P = 0.333). In additional MVMR analyses accounting simultaneously for potential behavioral and psychiatric mediators (tobacco smoking; alcohol consumption; and self-reported nerves, tension, anxiety, or depression), the effect of EA was little changed (OR, 0.541, 95% CI, 0.421-0.696, P = 3.33 × 10-6). Consistency of results across complementary MR methods accommodating different assumptions about genetic pleiotropy strengthened causal inference. Our results show that even after accounting for psychiatric disorders and behavioral mediators, EA, but not CP, may causally influence suicide attempt risk among white individuals of European ancestry, which could have important implications for health policy and programs aimed at reducing the increasing rates of suicide. Future work is necessary to examine the EA-suicide relationship populations of different ethnicities.

Empirical comparisons of multiple Mendelian randomization approaches in the presence of assortative mating

BACKGROUND

Mendelian randomization (MR) is widely used to unravel causal relationships in epidemiological studies. Whereas multiple MR methods have been developed to control for bias due to horizontal pleiotropy, their performance in the presence of other sources of bias, like non-random mating, has been mostly evaluated using simulated data. Empirical comparisons of MR estimators in such scenarios have yet to be conducted. Pleiotropy and non-random mating have been shown to account equally for the genetic correlation between height and educational attainment. Previous studies probing the causal nature of this association have produced conflicting results.

METHODS

We estimated the causal effect of height on educational attainment in various MR models, including the MR-Egger and the MR-Direction of Causation (MR-DoC) models that correct for, or explicitly model, horizontal pleiotropy.

RESULTS

We reproduced the weak but positive association between height and education in the Netherlands Twin Register sample (P= 3.9 × 10-6). All MR analyses suggested that height has a robust, albeit small, causal effect on education. We showed via simulations that potential assortment for height and education had no effect on the causal parameter in the MR-DoC model. With the pleiotropic effect freely estimated, MR-DoC yielded a null finding.

CONCLUSIONS

Non-random mating may have a bearing on the results of MR studies based on unrelated individuals. Family data enable tests of causal relationships to be conducted more rigorously, and are recommended to triangulate results of MR studies assessing pairs of traits leading to non-random mate selection.

Detecting and correcting for bias in Mendelian randomization analyses using Gene-by-Environment interactions

Background

Mendelian randomization (MR) has developed into an established method for strengthening causal inference and estimating causal effects, largely due to the proliferation of genome-wide association studies. However, genetic instruments remain controversial, as horizontal pleiotropic effects can introduce bias into causal estimates. Recent work has highlighted the potential of gene–environment interactions in detecting and correcting for pleiotropic bias in MR analyses.

Methods

We introduce MR using Gene-by-Environment interactions (MRGxE) as a framework capable of identifying and correcting for pleiotropic bias. If an instrument–covariate interaction induces variation in the association between a genetic instrument and exposure, it is possible to identify and correct for pleiotropic effects. The interpretation of MRGxE is similar to conventional summary MR approaches, with a particular advantage of MRGxE being the ability to assess the validity of an individual instrument.

Results

We investigate the effect of adiposity, measured using body mass index (BMI), upon systolic blood pressure (SBP) using data from the UK Biobank and a single weighted allelic score informed by data from the GIANT consortium. We find MRGxE produces findings in agreement with two-sample summary MR approaches. Further, we perform simulations highlighting the utility of the approach even when the MRGxE assumptions are violated.

Conclusions

By utilizing instrument–covariate interactions in MR analyses implemented within a linear-regression framework, it is possible to identify and correct for horizontal pleiotropic bias, provided the average magnitude of pleiotropy is constant across interaction-covariate subgroups.

Education leads to a more physically active lifestyle: Evidence based on Mendelian randomization

Physical inactivity is a major health risk worldwide. Observational studies suggest that higher education is positively related to physical activity, but it is not clear whether this relationship constitutes a causal effect. Using participants (N = 1651) drawn from the Cardiovascular Risk in Young Finns Study linked to nationwide administrative data from Statistics Finland, this study examined whether educational attainment, measured by years of education, is related to adulthood physical activity in terms of overall physical activity, weekly hours of intensive activity, total steps per day, and aerobic steps per day. We employed ordinary least squares (OLS) models and extended the analysis using an instrumental variables approach (Mendelian randomization, MR) with a genetic risk score as an instrument for years of education. Based on the MR results, it was found that years of education is positively related to physical activity. On average, one additional year of education leads to a 0.62-unit higher overall physical activity (P < .01), 0.26 more hours of weekly intensive activity (P < .05), 560 more steps per day (P < .10), and 390 more aerobic steps per day (P < .09). The findings indicate that education may be a factor leading to higher leisure-time physical activity and thus promoting global health.

Cigarette smoking and personality: interrogating causality using Mendelian randomisation

BACKGROUND

Despite the well-documented association between smoking and personality traits such as neuroticism and extraversion, little is known about the potential causal nature of these findings. If it were possible to unpick the association between personality and smoking, it may be possible to develop tailored smoking interventions that could lead to both improved uptake and efficacy.

METHODS

Recent genome-wide association studies (GWAS) have identified variants robustly associated with both smoking phenotypes and personality traits. Here we use publicly available GWAS summary statistics in addition to individual-level data from UK Biobank to investigate the link between smoking and personality. We first estimate genetic overlap between traits using LD score regression and then use bidirectional Mendelian randomisation methods to unpick the nature of this relationship.

RESULTS

We found clear evidence of a modest genetic correlation between smoking behaviours and both neuroticism and extraversion. We found some evidence that personality traits are causally linked to certain smoking phenotypes: among current smokers each additional neuroticism risk allele was associated with smoking an additional 0.07 cigarettes per day (95% CI 0.02-0.12, p = 0.009), and each additional extraversion effect allele was associated with an elevated odds of smoking initiation (OR 1.015, 95% CI 1.01-1.02, p = 9.6 × 10-7).

CONCLUSION

We found some evidence for specific causal pathways from personality to smoking phenotypes, and weaker evidence of an association from smoking initiation to personality. These findings could be used to inform future smoking interventions or to tailor existing schemes.

A Birth Cohort Study on the Genetic Modification of the Association of Prenatal Methylmercury With Child Cognitive Development

Genetic predisposition might affect neurodevelopmental outcomes of prenatal methylmercury exposure. We examined suspected heterogeneities for modification of exposure-related neurodevelopment in children from the Avon Longitudinal Study of Parents and Children (1991-2000), Bristol, United Kingdom. A subgroup (n = 1,127 from a pilot study and 1,045 from the present study) was identified based on the availability of the mercury concentration of cord tissue as a measure of prenatal methylmercury exposure, data on 247 single-nucleotide polymorphisms (SNPs), and Wechsler Intelligence Scale for Children intelligence quotient (IQ) scores. Log10-transformed mercury concentration was positively associated with IQ, but adjustment for confounding cofactors attenuated this association. A finding of enhanced interaction with methylmercury was replicated in this study for the minor allele of rs1042838 (progesterone receptor) (β = -11.8, 95% confidence interval: -23.0, -0.6; P for interaction = 0.004) and weakly for rs662 (paraoxonase 1) (β = -3.6, 95% confidence interval: -11.4, 4.3; P = 0.117). In the joint sample, new interacting single-nucleotide polymorphisms were discovered in relation to superoxide dismutase 2, ATP binding cassette subfamily A member 1, and metallothionein 1M genes. While the low-level prenatal exposure to methylmercury was not associated with child cognition, progesterone receptor rs1042838 minor alleles revealed a negative association of mercury exposure with IQ.

MR-pheWAS with stratification and interaction: Searching for the causal effects of smoking heaviness identified an effect on facial aging

Mendelian randomization (MR) is an established approach to evaluate the effect of an exposure on an outcome. The gene-by-environment (GxE) study design can be used to determine whether the genetic instrument affects the outcome through pathways other than via the exposure of interest (horizontal pleiotropy). MR phenome-wide association studies (MR-pheWAS) search for the effects of an exposure, and can be conducted in UK Biobank using the PHESANT package. In this proof-of-principle study, we introduce the novel GxE MR-pheWAS approach, that combines MR-pheWAS with the use of GxE interactions. This method aims to identify the presence of effects of an exposure while simultaneously investigating horizontal pleiotropy. We systematically test for the presence of causal effects of smoking heaviness-stratifying on smoking status (ever versus never)-as an exemplar. If a genetic variant is associated with smoking heaviness (but not smoking initiation), and this variant affects an outcome (at least partially) via tobacco intake, we would expect the effect of the variant on the outcome to differ in ever versus never smokers. We used PHESANT to test for the presence of effects of smoking heaviness, instrumented by genetic variant rs16969968, among never and ever smokers respectively, in UK Biobank. We ranked results by the strength of interaction between ever and never smokers. We replicated previously established effects of smoking heaviness, including detrimental effects on lung function. Novel results included a detrimental effect of heavier smoking on facial aging. We have demonstrated how GxE MR-pheWAS can be used to identify potential effects of an exposure, while simultaneously assessing whether results may be biased by horizontal pleiotropy.

Multivariable two-sample Mendelian randomization estimates of the effects of intelligence and education on health

Intelligence and education are predictive of better physical and mental health, socioeconomic position (SEP), and longevity. However, these associations are insufficient to prove that intelligence and/or education cause these outcomes. Intelligence and education are phenotypically and genetically correlated, which makes it difficult to elucidate causal relationships. We used univariate and multivariable Mendelian randomization to estimate the total and direct effects of intelligence and educational attainment on mental and physical health, measures of socioeconomic position, and longevity. Both intelligence and education had beneficial total effects. Higher intelligence had positive direct effects on income and alcohol consumption, and negative direct effects on moderate and vigorous physical activity. Higher educational attainment had positive direct effects on income, alcohol consumption, and vigorous physical activity, and negative direct effects on smoking, BMI and sedentary behaviour. If the Mendelian randomization assumptions hold, these findings suggest that both intelligence and education affect health.

FADS and PPARG2 Single Nucleotide Polymorphisms are Associated with Plasma Lipids in 9-Mo-Old Infants

BACKGROUND

Dietary intake of polyunsaturated fatty acids (PUFAs), e.g., linoleic acid and n-3 (ω-3) long-chain PUFAs, has been shown in adults to affect plasma cholesterol and triglycerides (TGs), respectively. Little is known about the effects of PUFAs on plasma lipids in early life.

OBJECTIVE

The aim of this study was to explore the associations between plasma concentrations of total, LDL, and HDL cholesterol and TGs in infants and 2 single nucleotide polymorphisms (SNPs) in the fatty acid desaturase genes (FADS) oppositely associated with docosahexaenoic acid (rs1535 and rs174448) and potential effect modification by a functional peroxisome proliferator-activated receptor-γ2 gene variant (PPARG2 Pro12Ala).

METHODS

In 9-mo-old infants (n = 561) from 3 Danish cohorts, we analyzed associations between plasma lipids, erythrocyte PUFAs, and FADS SNPs, and interactions with PPARG2 Pro12Ala genotype, by multiple linear regression. We also examined potential effect modification by breastfeeding, as 46% of the infants were still being breastfed.

RESULTS

Minor allele carriage of rs174448 was associated with lower total cholesterol (difference: -0.22 mmol/L; 95% CI: -0.37, -0.06 mmol/L; P = 0.006) and LDL cholesterol (difference: -0.15 mmol/L; 95% CI: -0.29, -0.01 mmol/L; P = 0.035), but no associations were observed with TGs or for rs1535. Minor allele carriage of both FADS SNPs was associated with 1 SD lower HDL cholesterol, but only in currently breastfed infants (rs174448 × breastfeeding, P = 0.080; rs1535 × breastfeeding, P = 0.030) and PPARG2 minor allele carriers (rs174448 × PPARG2, P = 0.001; rs1535 × PPARG2, P = 0.004). Erythrocyte arachidonic acid and eicosapentaenoic acid were inversely associated with LDL cholesterol [estimated effect (β): -0.3 mmol/L; 95% CI: -0.06, -0.00 mmol/L per percentage of fatty acids (FA%); P = 0.035] and TGs (β: -0.23 mmol/L; 95% CI: -0.41, -0.05 mmol/L per FA%; P = 0.015), respectively.

CONCLUSIONS

The observed associations with FADS variants indicate that PUFAs are involved in plasma lipid regulation in 9-mo-old infants. Observed FADS SNP differences and interactions with breastfeeding and PPARG2 warrant additional studies to explore the effects of individual FADS SNPs on PUFA status and potential genetic modification of dietary PUFA effects.

Investigating causality in the association between vitamin D status and self-reported tiredness

Self-reported tiredness or low energy, often referred to as fatigue, has been linked to low levels of circulating 25-hydroxyvitamin D (25OHD), a biomarker of vitamin D status. Although it is uncertain if the association is causal, fatigue is a common indication for testing, and correcting, low 25OHD-levels. We used two-sample Mendelian randomization to test for genetic evidence of a causal association between low 25OHD-levels and fatigue. Genetic-25OHD associations were estimated from the largest genome-wide association study of vitamin D to date, and genetic-fatigue associations were estimated in 327,478 individuals of European descent in UK Biobank, of whom 19,526 (5.96%) reported fatigue (tiredness or low energy nearly every day over the past two weeks). Using seven genome-wide significant 25OHD-reducing genetic variants, there was little evidence for a causal effect of 25OHD on fatigue (odds ratio for fatigue was 1.05 with 95% confidence interval of 0.87–1.27 per 1-SD decrease in log-transformed 25OHD). There was also little evidence of association between any individual 25OHD-reducing variant and fatigue. Our results suggest that a clinically relevant protective effect of 25OHD-levels on fatigue is unlikely. Therefore, vitamin D supplementation of the general population to raise 25OHD-levels is not likely to be useful in preventing fatigue.

Fetal Origins of Mental Disorders? An Answer Based on Mendelian Randomization

The Barker hypothesis states that low birth weight (BW) is associated with higher risk of adult onset diseases, including mental disorders like schizophrenia, major depressive disorder (MDD), and attention deficit hyperactivity disorder (ADHD). The main criticism of this hypothesis is that evidence for it comes from observational studies. Specifically, observational evidence does not suffice for inferring causality, because the associations might reflect the effects of confounders. Mendelian randomization (MR) - a novel method that tests causality on the basis of genetic data - creates the unprecedented opportunity to probe the causality in the association between BW and mental disorders in observation studies. We used MR and summary statistics from recent large genome-wide association studies to test whether the association between BW and MDD, schizophrenia and ADHD is causal. We employed the inverse variance weighted (IVW) method in conjunction with several other approaches that are robust to possible assumption violations. MR-Egger was used to rule out horizontal pleiotropy. IVW showed that the association between BW and MDD, schizophrenia and ADHD is not causal (all p > .05). The results of all the other MR methods were similar and highly consistent. MR-Egger provided no evidence for pleiotropic effects biasing the estimates of the effects of BW on MDD (intercept = -0.004, SE = 0.005, p = .372), schizophrenia (intercept = 0.003, SE = 0.01, p = .769), or ADHD (intercept = 0.009, SE = 0.01, p = .357). Based on the current evidence, we refute the Barker hypothesis concerning the fetal origins of adult mental disorders. The discrepancy between our results and the results from observational studies may be explained by the effects of confounders in the observational studies, or by the existence of a small causal effect not detected in our study due to weak instruments. Our power analyses suggested that the upper bound for a potential causal effect of BW on mental disorders would likely not exceed an odds ratio of 1.2.

Use of Mendelian andomization for dentifying isk actors for rain umors

Gliomas are a group of primary brain tumors, the most common and aggressive subtype of which is glioblastoma. Glioblastoma has a median survival of just 15 months after diagnosis. Only previous exposure to ionizing radiation and particular inherited genetic syndromes are accepted risk factors for glioma; the vast majority of cases are thought to occur spontaneously. Previous observational studies have described associations between several risk factors and glioma, but studies are often conflicting and whether these associations reflect true casual relationships is unclear because observational studies may be susceptible to confounding, measurement error and reverse causation. Mendelian randomization (MR) is a form of instrumental variable analysis that can be used to provide supporting evidence for causal relationships between exposures (e.g., risk factors) and outcomes (e.g., disease onset). MR utilizes genetic variants, such as single nucleotide polymorphisms (SNPs), that are robustly associated with an exposure to determine whether there is a causal effect of the exposure on the outcome. MR is less susceptible to confounding, reverse causation and measurement errors as it is based on the random inheritance during conception of genetic variants that can be relatively accurately measured. In previous studies, MR has implicated a genetically predicted increase in telomere length with an increased risk of glioma, and found little evidence that obesity related factors, vitamin D or atopy are causal in glioma risk. In this review, we describe MR and its potential use to discover and validate novel risk factors, mechanistic factors, and therapeutic targets in glioma.

Bias in Mendelian randomization due to assortative mating

Mendelian randomization (MR) has been increasingly used to strengthen causal inference in observational epidemiology. Methodological developments in the field allow detecting and/or adjusting for different potential sources of bias, mainly bias due to horizontal pleiotropy (or "off-target" genetic effects). Another potential source of bias is nonrandom matching between spouses (i.e., assortative mating). In this study, we performed simulations to investigate the bias caused in MR by assortative mating. We found that bias can arise due to either cross-trait assortative mating (i.e., assortment on two phenotypes, such as highly educated women selecting taller men) or single-trait assortative mating (i.e., assortment on a single phenotype), even if the exposure and outcome phenotypes are not the phenotypes under assortment. The simulations also indicate that bias due to assortative mating accumulates over generations and that MR methods robust to horizontal pleiotropy are also affected by this bias. Finally, we show that genetic data from mother-father-offspring trios can be used to detect and correct for this bias.

Plasma urate and risk of Parkinson's disease: A mendelian randomization study

OBJECTIVE

Urate is a potent antioxidant, and high plasma urate has been associated with lower incidence of Parkinson's disease (PD) in epidemiological studies. We tested the hypothesis that high concentrations of plasma urate are associated with low incidence of PD.

METHODS

We performed observational and genetic analyses using plasma urate and the urate SLC2A9 rs7442295 and ABCG2 rs2231142 genotype in >102,000 individuals from the CGPS (Copenhagen General Population Study). Information on PD and mortality was from national patient and death registries. Incidences of PD were calculated using Cox regression, Fine and Gray competing-risks regression, and instrumental variable analyses.

RESULTS

In total, 398 individuals were diagnosed with PD, of which 285 were incident cases. The multivariable adjusted hazard ratio for PD was 0.56 (95% confidence interval [CI], 0.41-0.77) for the highest versus the lowest tertile of plasma urate (p for trend across 3 groups, 8 × 10^-5 ). Each one-allele increase in the combined allele score was associated with 19μmol/l (95% CI, 18.5-19.9) higher plasma urate. In observational analyses, a 50μmol/l higher plasma urate was associated with a hazard ratio of 0.85 (0.77-0.92) for PD; in instrumental variable analyses, 50μmol/l higher plasma urate was associated with an odds ratio of 1.20 (0.85-1.71) for PD.

INTERPRETATION

High plasma urate was associated with lower risk of PD in observational analyses; however, in instrumental variable analysis, high plasma urate was not associated with low risk of PD. Thus, our data do not support a causal relationship between high plasma urate and low risk of PD. Ann Neurol 2018;84:178-190.

Mendelian randomization: a novel approach for the prediction of adverse drug events and drug repurposing opportunities

Identification of unintended drug effects, specifically drug repurposing opportunities and adverse drug events, maximizes the benefit of a drug and protects the health of patients. However, current observational research methods are subject to several biases. These include confounding by indication, reverse causality and missing data. We propose that Mendelian randomization (MR) offers a novel approach for the prediction of unintended drug effects. In particular, we advocate the synthesis of evidence from this method and other approaches, in the spirit of triangulation, to improve causal inferences concerning drug effects. MR addresses some of the limitations associated with the existing methods in this field. Furthermore, it can be applied either before or after approval of the drug, and could therefore prevent the potentially harmful exposure of patients in clinical trials and beyond. The potential of MR as a pharmacovigilance and drug repurposing tool is yet to be realized, and could both help prevent adverse drug events and identify novel indications for existing drugs in the future.

Pleiotropy-robust Mendelian randomization

Background

The potential of Mendelian randomization studies is rapidly expanding due to: (i) the growing power of genome-wide association study (GWAS) meta-analyses to detect genetic variants associated with several exposures; and (ii) the increasing availability of these genetic variants in large-scale surveys. However, without a proper biological understanding of the pleiotropic working of genetic variants, a fundamental assumption of Mendelian randomization (the exclusion restriction) can always be contested.

Methods

We build upon and synthesize recent advances in the literature on instrumental variables (IVs) estimation that test and relax the exclusion restriction. Our pleiotropy-robust Mendelian randomization (PRMR) method first estimates the degree of pleiotropy, and in turn corrects for it. If (i) a subsample exists for which the genetic variants do not affect the exposure; (ii) the selection into this subsample is not a joint consequence of the IV and the outcome; (iii) pleiotropic effects are homogeneous, PRMR obtains unbiased estimates of causal effects.

Results

Simulations show that existing MR methods produce biased estimators for realistic forms of pleiotropy. Under the aforementioned assumptions, PRMR produces unbiased estimators. We illustrate the practical use of PRMR by estimating the causal effect of: (i) tobacco exposure on body mass index (BMI); (ii) prostate cancer on self-reported health; and (iii) educational attainment on BMI in the UK Biobank data.

Conclusions

PRMR allows for instrumental variables that violate the exclusion restriction due to pleiotropy, and it corrects for pleiotropy in the estimation of the causal effect. If the degree of pleiotropy is unknown, PRMR can still be used as a sensitivity analysis.

Extending Causality Tests with Genetic Instruments: An Integration of Mendelian Randomization with the Classical Twin Design

Although experimental studies are regarded as the method of choice for determining causal influences, these are not always practical or ethical to answer vital questions in health and social research (e.g., one cannot assign individuals to a "childhood trauma condition" in studying the causal effects of childhood trauma on depression). Key to solving such questions are observational studies. Mendelian Randomization (MR) is an influential method to establish causality in observational studies. MR uses genetic variants to test causal relationships between exposures/risk factors and outcomes such as physical or mental health. Yet, individual genetic variants have small effects, and so, when used as instrumental variables, render MR liable to weak instrument bias. Polygenic scores have the advantage of larger effects, but may be characterized by horizontal pleiotropy, which violates a central assumption of MR. We developed the MR-DoC twin model by integrating MR with the Direction of Causation twin model. This model allows us to test pleiotropy directly. We considered the issue of parameter identification, and given identification, we conducted extensive power calculations. MR-DoC allows one to test causal hypotheses and to obtain unbiased estimates of the causal effect given pleiotropic instruments, while controlling for genetic and environmental influences common to the outcome and exposure. Furthermore, the approach allows one to employ strong instrumental variables in the form of polygenic scores, guarding against weak instrument bias, and increasing the power to detect causal effects of exposures on potential outcomes. Beside allowing to test pleiotropy directly, incorporating in MR data collected from relatives provide additional within-family data that resolve additional assumptions like random mating, the absence of the gene-environment interaction/covariance, no dyadic effects. Our approach will enhance and extend MR's range of applications, and increase the value of the large cohorts collected at twin/family registries as they correctly detect causation and estimate effect sizes even in the presence of pleiotropy.

Heavier smoking increases coffee consumption: findings from a Mendelian randomization analysis

Background

There is evidence for a positive relationship between cigarette and coffee consumption in smokers. Cigarette smoke increases metabolism of caffeine, so this may represent a causal effect of smoking on caffeine intake.

Methods

We performed Mendelian randomization analyses in the UK Biobank (N = 114 029), the Norwegian HUNT study (N = 56 664) and the Copenhagen General Population Study (CGPS) (N = 78 650). We used the rs16969968 genetic variant as a proxy for smoking heaviness in all studies and rs4410790 and rs2472297 as proxies for coffee consumption in UK Biobank and CGPS. Analyses were conducted using linear regression and meta-analysed across studies.

Results

Each additional cigarette per day consumed by current smokers was associated with higher coffee consumption (0.10 cups per day, 95% CI: 0.03, 0.17). There was weak evidence for an increase in tea consumption per additional cigarette smoked per day (0.04 cups per day, 95% CI: -0.002, 0.07). There was strong evidence that each additional copy of the minor allele of rs16969968 (which increases daily cigarette consumption) in current smokers was associated with higher coffee consumption (0.16 cups per day, 95% CI: 0.11, 0.20), but only weak evidence for an association with tea consumption (0.04 cups per day, 95% CI: -0.01, 0.09). There was no clear evidence that rs16969968 was associated with coffee or tea consumption in never or former smokers or that the coffee-related variants were associated with cigarette consumption.

Conclusions

Higher cigarette consumption causally increases coffee intake. This is consistent with faster metabolism of caffeine by smokers, but could also reflect a behavioural effect of smoking on coffee drinking.

Inflammatory Biomarkers and Risk of Schizophrenia: A 2-Sample Mendelian Randomization Study

IMPORTANCE

Positive associations between inflammatory biomarkers and risk of psychiatric disorders, including schizophrenia, have been reported in observational studies. However, conventional observational studies are prone to bias, such as reverse causation and residual confounding, thus limiting our understanding of the effect (if any) of inflammatory biomarkers on schizophrenia risk.

OBJECTIVE

To evaluate whether inflammatory biomarkers have an effect on the risk of developing schizophrenia.

DESIGN, SETTING, AND PARTICIPANTS

Two-sample mendelian randomization study using genetic variants associated with inflammatory biomarkers as instrumental variables to improve inference. Summary association results from large consortia of candidate gene or genome-wide association studies, including several epidemiologic studies with different designs, were used. Gene-inflammatory biomarker associations were estimated in pooled samples ranging from 1645 to more than 80 000 individuals, while gene-schizophrenia associations were estimated in more than 30 000 cases and more than 45 000 ancestry-matched controls. In most studies included in the consortia, participants were of European ancestry, and the prevalence of men was approximately 50%. All studies were conducted in adults, with a wide age range (18 to 80 years).

EXPOSURES

Genetically elevated circulating levels of C-reactive protein (CRP), interleukin-1 receptor antagonist (IL-1Ra), and soluble interleukin-6 receptor (sIL-6R).

MAIN OUTCOMES AND MEASURES

Risk of developing schizophrenia. Individuals with schizophrenia or schizoaffective disorders were included as cases. Given that many studies contributed to the analyses, different diagnostic procedures were used.

RESULTS

The pooled odds ratio estimate using 18 CRP genetic instruments was 0.90 (random effects 95% CI, 0.84-0.97; P = .005) per 2-fold increment in CRP levels; consistent results were obtained using different mendelian randomization methods and a more conservative set of instruments. The odds ratio for sIL-6R was 1.06 (95% CI, 1.01-1.12; P = .02) per 2-fold increment. Estimates for IL-1Ra were inconsistent among instruments, and pooled estimates were imprecise and centered on the null.

CONCLUSIONS AND RELEVANCE

Under mendelian randomization assumptions, our findings suggest a protective effect of CRP and a risk-increasing effect of sIL-6R (potentially mediated at least in part by CRP) on schizophrenia risk. It is possible that such effects are a result of increased susceptibility to early life infection.

Mendelian randomization shows sex-specific associations between long-chain PUFA-related genotypes and cognitive performance in Danish schoolchildren

Background: Dietary and endogenously formed long-chain polyunsaturated fatty acids (LCPUFAs) are hypothesized to improve cognitive development, but results are inconclusive, with suggestions of sex specificity. One study suggested that single-nucleotide polymorphisms (SNPs) rs1535 and rs174448 in the fatty acid desaturase (FADS) gene cluster have opposite effects on erythrocyte LCPUFAs at 9 mo.Objective: To explore whether SNPs in FADS and elongase (ELOVL) genes were associated with school performance in a sex-specific manner, we performed a Mendelian randomization study using data from the Optimal well-being, development and health for Danish children through a healthy New Nordic Diet (OPUS) School Meal Study with 765 Danish schoolchildren 8-11 y old.Design: Associations between selected FADS1/2 SNPs (rs1535, rs174448, and rs174468) and ELOVL5 rs2397142, whole-blood fatty acid composition, and performance in the d2 Test of Attention and a reading test were analyzed in multiple regression models including all SNPs, SNP-sex interactions, and covariates related to testing conditions.Results:FADS, rs1535 minor allele carriage associated with lower whole-blood arachidonic acid (P ≤ 0.002), and minor alleles of rs174448 tended to associate with lower docosahexaenoic acid (DHA) (P = 0.052). We identified sex interactions in 50% of the SNP performance sets. Sex-dependent associations were observed for rs174448 and rs1535 on the d2 Test of Attention outcomes (P < 0.03) and for the associations between reading scores and rs174448 and rs2397142 (P < 0.01). All of the sex-specific analyses showed associations in opposite directions in girls and boys. The minor allele carriage of rs174448 was associated with lower d2 Test of Attention performance (P < 0.02) and reading scores (P < 0.001) in boys but with better reading scores in girls (P ≤ 0.002). The associations were consistently the opposite for rs1535 minor allele carriage (P < 0.05). Associations with rs2397142 also appeared to be opposite of those of rs174448, but only for reading and not significant after adjustment for parental educational level and whole-blood DHA.Conclusions: This study showed associations between rs1535 minor allele homozygosity and rs174448 major allele carriage and improved performance in 8- to 11-y-old boys but not in girls, thereby counteracting existing sex differences. This may be a consequence of increased endogenous DHA synthesis in infancy but not at school-age. This trial was registered at clinicaltrials.gov as NCT01457794.

Mendelian randomization in cardiometabolic disease: challenges in evaluating causality

Mendelian randomization (MR) is a burgeoning field that involves the use of genetic variants to assess causal relationships between exposures and outcomes. MR studies can be straightforward; for example, genetic variants within or near the encoding locus that is associated with protein concentrations can help to assess their causal role in disease. However, a more complex relationship between the genetic variants and an exposure can make findings from MR more difficult to interpret. In this Review, we describe some of these challenges in interpreting MR analyses, including those from studies using genetic variants to assess causality of multiple traits (such as branched-chain amino acids and risk of diabetes mellitus); studies describing pleiotropic variants (for example, C-reactive protein and its contribution to coronary heart disease); and those investigating variants that disrupt normal function of an exposure (for example, HDL cholesterol or IL-6 and coronary heart disease). Furthermore, MR studies on variants that encode enzymes responsible for the metabolism of an exposure (such as alcohol) are discussed, in addition to those assessing the effects of variants on time-dependent exposures (extracellular superoxide dismutase), cumulative exposures (LDL cholesterol), and overlapping exposures (triglycerides and non-HDL cholesterol). We elaborate on the molecular features of each relationship, and provide explanations for the likely causal associations. In doing so, we hope to contribute towards more reliable evaluations of MR findings.

Causal relationship between obesity and serum testosterone status in men: A bi-directional mendelian randomization analysis

CONTEXT

Obesity in men is associated with low serum testosterone and both are associated with several diseases and increased mortality.

OBJECTIVES

Examine the direction and causality of the relationship between body mass index (BMI) and serum testosterone.

DESIGN

Bi-directional Mendelian randomization (MR) analysis on prospective cohorts.

SETTING

Five cohorts from Denmark, Germany and Sweden (Inter99, SHIP, SHIP Trend, GOOD and MrOS Sweden).

PARTICIPANTS

7446 Caucasian men, genotyped for 97 BMI-associated SNPs and three testosterone-associated SNPs.

MAIN OUTCOME MEASURES

BMI and serum testosterone adjusted for age, smoking, time of blood sampling and site.

RESULTS

1 SD genetically instrumented increase in BMI was associated with a 0.25 SD decrease in serum testosterone (IV ratio: -0.25, 95% CI: -0.42--0.09, p = 2.8*10-3). For a body weight reduction altering the BMI from 30 to 25 kg/m2, the effect would equal a 13% increase in serum testosterone. No association was seen for genetically instrumented testosterone with BMI, a finding that was confirmed using large-scale data from the GIANT consortium (n = 104349).

CONCLUSIONS

Our results suggest that there is a causal effect of BMI on serum testosterone in men. Population level interventions to reduce BMI are expected to increase serum testosterone in men.

Bilirubin and Stroke Risk Using a Mendelian Randomization Design

BACKGROUND AND PURPOSE

Circulating bilirubin, a natural antioxidant, is associated with decreased risk of stroke. However, the nature of the relationship between the two remains unknown. We used a Mendelian randomization analysis to assess the causal effect of serum bilirubin on stroke risk in Koreans.

METHODS

The 14 single-nucleotide polymorphisms (SNPs) (<10^-7) including rs6742078 of uridine diphosphoglucuronyl-transferase were selected from genome-wide association study of bilirubin level in the KCPS-II (Korean Cancer Prevention Study-II) Biobank subcohort consisting of 4793 healthy Korean and 806 stroke cases. Weighted genetic risk score was calculated using 14 SNPs selected from the top SNPs.

RESULTS

Both rs6742078 (F statistics=138) and weighted genetic risk score with 14 SNPs (F statistics=187) were strongly associated with bilirubin levels. Simultaneously, serum bilirubin level was associated with decreased risk of stroke in an ordinary least-squares analysis. However, in 2-stage least-squares Mendelian randomization analysis, no causal relationship between serum bilirubin and stroke risk was found.

CONCLUSIONS

There is no evidence that bilirubin level is causally associated with risk of stroke in Koreans. Therefore, bilirubin level is not a risk determinant of stroke.

Mediterranean diet-gene interactions: A targeted metabolomics study in Greek-Cypriot women

SCOPE

A high adherence to the Mediterranean diet (MD) was previously associated with a decreased risk of breast cancer (BC) among Greek-Cypriot women. Additionally, particular polymorphisms were shown to modulate this MD-BC association. Herein, we aimed to investigate the effect of polymorphisms-MD interactions on the levels of specific metabolites that could be related to dietary adherence or enzymatic activity, which is itself modulated by polymorphisms.

METHODS AND RESULTS

Greek-Cypriot women who were BC controls and had the lowest or the highest MD adherence (vegetables, fruit, legumes, fish) as assessed by principal component analysis (n = 564) were included. Participants were previously genotyped for nine polymorphisms of the one-carbon metabolism, oxidative stress, and xenobiotic metabolism. The serum levels of 14 metabolites that are key players in the aforementioned pathways were measured by UPLC-MS/MS. ANCOVA was used to assess polymorphism-MD interactions on metabolites' levels within a multivariate linear regression model. Statistically significant interactions between GSTM1 (where GST is glutathione S-transferase) deletion polymorphism and MD on flavin mononucleotide and on 5-methyltetrahydrofolate (5-MTHF) concentrations were observed. The MTHFR rs1801133 interacted significantly with MD on 5-MTHF concentration.

CONCLUSION

Serum levels of flavin mononucleotide and 5-MTHF were shown to be influenced by interactions between GSTM1 deletion or MTHFR (rs1801133) polymorphisms and a dietary pattern, characteristic of MD.

Association of timing of menarche with depressive symptoms and depression in adolescence: Mendelian randomisation study

BACKGROUND

Observational studies report associations between early menarche and higher levels of depressive symptoms and depression. However, no studies have investigated whether this association is causal.

AIMS

To determine whether earlier menarche is a causal risk factor for depressive symptoms and depression in adolescence.

METHOD

The associations between a genetic score for age at menarche and depressive symptoms at 14, 17 and 19 years, and depression at 18 years, were examined using Mendelian randomisation analysis techniques.

RESULTS

Using a genetic risk score to indicate earlier timing of menarche, we found that early menarche is associated with higher levels of depressive symptoms at 14 years (odds ratio per risk allele 1.02, 95% CI 1.005-1.04, n = 2404). We did not find an association between the early menarche risk score and depressive symptoms or depression after age 14.

CONCLUSIONS

Our results provide evidence for a causal effect of age at menarche on depressive symptoms at age 14.

Estimating Marginal Healthcare Costs Using Genetic Variants as Instrumental Variables: Mendelian Randomization in Economic Evaluation

Accurate measurement of the marginal healthcare costs associated with different diseases and health conditions is important, especially for increasingly prevalent conditions such as obesity. However, existing observational study designs cannot identify the causal impact of disease on healthcare costs. This paper explores the possibilities for causal inference offered by Mendelian randomization, a form of instrumental variable analysis that uses genetic variation as a proxy for modifiable risk exposures, to estimate the effect of health conditions on cost. Well-conducted genome-wide association studies provide robust evidence of the associations of genetic variants with health conditions or disease risk factors. The subsequent causal effects of these health conditions on cost can be estimated using genetic variants as instruments for the health conditions. This is because the approximately random allocation of genotypes at conception means that many genetic variants are orthogonal to observable and unobservable confounders. Datasets with linked genotypic and resource use information obtained from electronic medical records or from routinely collected administrative data are now becoming available and will facilitate this form of analysis. We describe some of the methodological issues that arise in this type of analysis, which we illustrate by considering how Mendelian randomization could be used to estimate the causal impact of obesity, a complex trait, on healthcare costs. We describe some of the data sources that could be used for this type of analysis. We conclude by considering the challenges and opportunities offered by Mendelian randomization for economic evaluation.

Alcohol Intake and Serum Glucose Levels from the Perspective of a Mendelian Randomization Design: The KCPS-II Biobank

Background

Previous studies have suggested that alcohol intake is associated with increased fasting serum glucose (FSG), but the nature of the relationship remains unknown. We used Mendelian randomization analysis to assess the causal effect of alcohol intake on FSG in a middle-aged Korean population.

Methods

Clinical data including FSG and alcohol intake were collected from 156,386 Koreans aged 20 years or older who took part in the Korean Cancer Prevention Study-II (KCPS-II) Biobank Cohort. The single nucleotide polymorphism rs671 in ALDH2 was genotyped among 2,993 men and 1,374 women in 2016. This was a randomly selected subcohort of KCPS-II Biobank participants.

Results

Alcohol consumption was positively associated with FSG level in men, but not in women. The rs671 major G allele was associated with increased alcohol intake (F-statistic = 302.62) and an increase in FSG in men. Using Mendelian randomization analysis, alcohol intake increased FSG by 1.78 mg/dL per alcohol unit (10 g ethanol) per day (95% CI: 0.97–2.59) in men. The associations became stronger when we excluded heavy drinkers and the elderly. However, in women, no significant association between rs671 and alcohol or serum glucose was found.

Conclusion

Using Mendelian randomization analysis, we suggest a causal relationship between alcohol intake and FSG among Korean men. Moreover, we found that the ALDH2 variant rs671 was not associated with FSG among Korean women.

Body mass index and psychiatric disorders: a Mendelian randomization study

Obesity is a highly prevalent risk factor for cardiometabolic diseases. Observational studies suggest that obesity is associated with psychiatric traits, but causal inference from such studies has several limitations. We used two-sample Mendelian randomization methods (inverse variance weighting, weighted median and MR-Egger regression) to evaluate the association of body mass index (BMI) with three psychiatric traits using data from the Genetic Investigation of Anthropometric Traits and Psychiatric Genomics consortia. Causal odds ratio estimates per 1-standard deviation increment in BMI ranged from 0.88 (95% CI: 0.62; 1.25) to 1.23 (95% CI: 0.65; 2.31) for bipolar disorder; 0.93 (0.78; 1.11) to 1.41 (0.87; 2.27) for schizophrenia; and 1.15 (95% CI: 0.92; 1.44) to 1.40 (95% CI: 1.03; 1.90) for major depressive disorder. Analyses removing potentially influential SNPs suggested that the effect estimates for depression might be underestimated. Our findings do not support the notion that higher BMI increases risk of bipolar disorder and schizophrenia. Although the point estimates for depression were consistent in all sensitivity analyses, the overall statistical evidence was weak. However, the fact that SNP-depression associations were estimated in relatively small samples reduced power to detect causal effects. This should be re-addressed when SNP-depression associations from larger studies become available.

Association of lactase persistence genotype with milk consumption, obesity and blood pressure: a Mendelian randomization study in the 1982 Pelotas (Brazil) Birth Cohort, with a systematic review and meta-analysis

Background: Milk intake has been associated with lower blood pressure (BP) in observational studies, and randomized controlled trials suggested that milk-derived tripeptides have BP-lowering effects. Milk intake has also been associated with body mass index (BMI). Nevertheless, it is unclear whether increasing milk consumption would reduce BP in the general population.

Methods: We investigated the association of milk intake with obesity and BP using genetically-defined lactase persistence (LP) based on the rs4988235 polymorphism in a Mendelian randomization design in the 1982 Pelotas (Southern Brazil) Birth Cohort. These results were combined with published reports identified through a systematic review using meta-analysis.

Results: In the 1982 Pelotas Birth Cohort, milk intake was 42 [95% confidence interval (CI): 18; 67) ml/day higher in LP individuals. In conventional observational analysis, each 1-dl/day increase in milk intake was associated with −0.26 (95% CI: −0.33; −0.19) kg/m² in BMI and −0.31 (95% CI: −0.46; −0.16) and -0.35 (95% CI: −0.46; −0.23) mmHg in systolic and diastolic BP, respectively. These results were not corroborated when analysing LP status, but confidence intervals were large. In random effects meta-analysis, LP individuals presented higher BMI [0.17 (95% CI: 0.07; 0.27) kg/m²] and higher odds of overweight-obesity [1.09 (95% CI: 1.02; 1.17)]. There were no reliable associations for BP.

Conclusions: Our study supports that LP is positively associated with obesity, suggesting that the negative association of milk intake with obesity is likely due to limitations of conventional observational studies. Our findings also do not support that increased milk intake leads to lower BP.