Dataset Information

Health effects of milk consumption: phenome-wide Mendelian randomization study.

ABSTRACT:

Background

We performed phenome-wide Mendelian randomization analysis (MR-PheWAS), two-sample MR analysis, and systemic review to comprehensively explore the health effects of milk consumption in the European population.

Methods

Rs4988235 located upstream of the LCT gene was used as the instrumental variable for milk consumption. MR-PheWAS analysis was conducted to map the association of genetically predicted milk consumption with 1081 phenotypes in the UK Biobank study (n=339,197). The associations identified in MR-PheWAS were examined by two-sample MR analysis using data from the FinnGen study (n=260,405) and international consortia. A systematic review of MR studies on milk consumption was further performed.

Results

PheWAS and two-sample MR analyses found robust evidence in support of inverse associations of genetically predicted milk consumption with risk of cataract (odds ratio (OR) per 50 g/day increase in milk consumption, 0.89, 95% confidence interval (CI), 0.84-0.94; p=3.81×10^-5), hypercholesterolemia (OR, 0.91, 95% CI 0.86-0.96; p=2.97×10^-4), and anal and rectal polyps (OR, 0.85, 95% CI, 0.77-0.94; p=0.001). An inverse association for type 2 diabetes risk (OR, 0.92, 95% CI, 0.86-0.97; p=0.003) was observed in MR analysis based on genetic data with body mass index adjustment but not in the corresponding data without body mass index adjustment. The systematic review additionally found evidence that genetically predicted milk consumption was inversely associated with asthma, hay fever, multiple sclerosis, colorectal cancer, and Alzheimer's disease, and positively associated with Parkinson's disease, renal cell carcinoma, metabolic syndrome, overweight, and obesity.

Conclusions

This study suggests several health effects of milk consumption in the European population.

SUBMITTER: Yuan S

PROVIDER: S-EPMC9694907 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Health effects of milk consumption: phenome-wide Mendelian randomization study.

Yuan Shuai S Sun Jing J Lu Ying Y Xu Fengzhe F Li Doudou D Jiang Fangyuan F Wan Zhongxiao Z Li Xue X Qin Li-Qiang LQ Larsson Susanna C SC

BMC medicine 20221123 1

<h4>Background</h4>We performed phenome-wide Mendelian randomization analysis (MR-PheWAS), two-sample MR analysis, and systemic review to comprehensively explore the health effects of milk consumption in the European population.<h4>Methods</h4>Rs4988235 located upstream of the LCT gene was used as the instrumental variable for milk consumption. MR-PheWAS analysis was conducted to map the association of genetically predicted milk consumption with 1081 phenotypes in the UK Biobank study (n=339,197 ...[more]

PMID: 36424608

Similar Datasets

Project description:BackgroundAge at menarche has been associated with various health outcomes. We aimed to identify potential causal effects of age at menarche on health-related traits in a hypothesis-free manner.MethodsWe conducted a Mendelian randomization phenome-wide association study (MR-pheWAS) of age at menarche with 17,893 health-related traits in UK Biobank (n = 181,318) using PHESANT. The exposure of interest was the genetic risk score for age at menarche. We conducted a second MR-pheWAS after excluding SNPs associated with BMI from the genetic risk score, to examine whether results might be due to the genetic overlap between age at menarche and BMI. We followed up a subset of health-related traits to investigate MR assumptions and seek replication in independent study populations.ResultsOf the 17,893 tests performed in our MR-pheWAS, we identified 619 associations with the genetic risk score for age at menarche at a 5% false discovery rate threshold, of which 295 were below a Bonferroni-corrected P value threshold. These included potential effects of younger age at menarche on lower lung function, higher heel bone-mineral density, greater burden of psychosocial/mental health problems, younger age at first birth, higher risk of childhood sexual abuse, poorer cardiometabolic health, and lower physical activity. After exclusion of variants associated with BMI, the genetic risk score for age at menarche was related to 37 traits at a 5% false discovery rate, of which 29 were below a Bonferroni-corrected P value threshold. We attempted to replicate findings for bone-mineral density, lung function, neuroticism, and childhood sexual abuse using 5 independent cohorts/consortia. While estimates for lung function, higher bone-mineral density, neuroticism, and childhood sexual abuse in replication cohorts were consistent with UK Biobank estimates, confidence intervals were wide and often included the null.ConclusionsThe genetic risk score for age at menarche was related to a broad range of health-related traits. Follow-up analyses indicated imprecise evidence of an effect of younger age at menarche on greater bone-mineral density, lower lung function, higher neuroticism score, and greater risk of childhood sexual abuse in the smaller replication samples available; hence, these findings need further exploration when larger independent samples become available.

Project description:Background: Causality between plasma triglyceride (TG) levels and atherosclerotic cardiovascular disease (ASCVD) risk remains controversial despite more than four decades of study and two recent landmark trials, STRENGTH and REDUCE-IT. Further unclear is the association between TG levels and non-atherosclerotic diseases across organ systems.Methods: Here, we conducted a phenome-wide, two-sample Mendelian randomization (MR) analysis using inverse-variance weighted (IVW) regression to systematically infer the causal effects of plasma TG levels on 2,600 disease traits in the European ancestry population of UK Biobank. For replication, we externally tested 221 nominally significant associations (p < 0.05) in an independent cohort from FinnGen. To account for potential horizontal pleiotropy and the influence of invalid instrumental variables, we performed sensitivity analyses using MR-Egger regression, weighted median estimator, and MR-PRESSO. Finally, we used multivariable MR controlling for correlated lipid fractions to distinguish the independent effect of plasma TG levels.Results: Our results identified 7 disease traits reaching Bonferroni-corrected significance in both the discovery (p < 1.92 × 10-5) and replication analyses (p < 2.26 × 10-4), suggesting a causal relationship between plasma TG levels and ASCVDs, including coronary artery disease (OR 1.33, 95% CI 1.24-1.43, p = 2.47 × 10-13). We also identified 12 disease traits that were Bonferroni-significant in the discovery or replication analysis and at least nominally significant in the other analysis (p < 0.05), identifying plasma TG levels as a novel potential risk factor for 9 non-ASCVD diseases, including uterine leiomyoma (OR 1.19, 95% CI 1.10-1.29, p = 1.17 × 10-5).Conclusions: Taking a phenome-wide, two-sample MR approach, we identified causal associations between plasma TG levels and 19 disease traits across organ systems. Our findings suggest unrealized drug repurposing opportunities or adverse effects related to approved and emerging TG-lowering agents, as well as mechanistic insights for future studies.Funding: RD is supported by the National Institute of General Medical Sciences of the National Institutes of Health (NIH) (R35-GM124836) and the National Heart, Lung, and Blood Institute of the NIH (R01-HL139865 and R01-HL155915).

Project description:BackgroundAsialoglycoprotein receptor 1 (ASGR1) is emerging as a potential drug target to reduce low-density lipoprotein (LDL)-cholesterol and coronary artery disease (CAD) risk. Here, we investigated genetically mimicked ASGR1 inhibitors on all-cause mortality and any possible adverse effects.MethodsWe conducted a drug-target Mendelian randomization study to assess genetically mimicked effects of ASGR1 inhibitors on all-cause mortality and 25 a priori outcomes relevant to lipid traits, CAD, and possible adverse effects, i.e. liver function, cholelithiasis, adiposity and type 2 diabetes. We also performed a phenome-wide association study of 1951 health-related phenotypes to identify any novel effects. Associations found were compared with those for currently used lipid modifiers, assessed using colocalization, and replicated where possible.ResultsGenetically mimicked ASGR1 inhibitors were associated with a longer lifespan (3.31 years per standard deviation reduction in LDL-cholesterol, 95% confidence interval 1.01 to 5.62). Genetically mimicked ASGR1 inhibitors were inversely associated with apolipoprotein B (apoB), triglycerides (TG) and CAD risk. Genetically mimicked ASGR1 inhibitors were positively associated with alkaline phosphatase, gamma glutamyltransferase, erythrocyte traits, insulin-like growth factor 1 (IGF-1) and C-reactive protein (CRP), but were inversely associated with albumin and calcium. Genetically mimicked ASGR1 inhibitors were not associated with cholelithiasis, adiposity or type 2 diabetes. Associations with apoB and TG were stronger for ASGR1 inhibitors compared with currently used lipid modifiers, and most non-lipid effects were specific to ASGR1 inhibitors. The probabilities for colocalization were > 0.80 for most of these associations, but were 0.42 for lifespan and 0.30 for CAD. These associations were replicated using alternative genetic instruments and other publicly available genetic summary statistics.ConclusionsGenetically mimicked ASGR1 inhibitors reduced all-cause mortality. Beyond lipid-lowering, genetically mimicked ASGR1 inhibitors increased liver enzymes, erythrocyte traits, IGF-1 and CRP, but decreased albumin and calcium.

Project description:Blood levels of iron and copper, even within their normal ranges, have been associated with a wide range of clinical outcomes. The available epidemiological evidence for these associations is often inconsistent and suffers from confounding and reverse causation. This study aims to examine the causal clinical effects of blood iron and copper with Mendelian randomization (MR) analyses. Genetic instruments for the blood levels of iron and copper were curated from existing genome-wide association studies. Candidate clinical outcomes were identified based on a phenome-wide association study (PheWAS) between these genetic instruments and a wide range of phenotypes in 310,999 unrelated individuals of European ancestry from the UK Biobank. All signals passing stringent correction for multiple testing were followed by MR analyses, with replication in independent data sources where possible. We found that genetically predicted higher blood levels of iron and copper are both associated with lower risks of iron deficiency anemia (odds ratio (OR) = 0.75, 95% confidence interval (CI): 0.67-0.85, p = 1.90 × 10-6 for iron; OR = 0.88, 95% CI: 0.78-0.98, p = 0.032 for copper), lipid metabolism disorders, and its two subcategories, hyperlipidemia (OR = 0.90, 95% CI: 0.85-0.96, p = 6.44 × 10-4; OR = 0.92, 95% CI: 0.87-0.98, p = 5.51 × 10-3) and hypercholesterolemia (OR = 0.90, 95% CI: 0.84-0.95, p = 5.34 × 10-4; OR = 0.93, 95% CI: 0.89-0.99, p = 0.022). Consistently, they are also associated with lower blood levels of total cholesterol and low-density lipoprotein cholesterol. Multiple sensitivity tests were applied to assess the presence of pleiotropy and the robustness of causal estimates. Regardless of the approaches, consistent evidence was obtained. Moreover, the unique clinical effects of each blood mineral were identified. Notably, genetically predicated higher blood iron is associated with an enhanced risk of varicose veins (OR = 1.28, 95% CI: 1.15-1.42, p = 4.34 × 10-6), while blood copper is positively associated with the risk of osteoarthrosis (OR = 1.07, 95% CI: 1.02-1.13, p = 0.010). Sex-stratified MR analysis further revealed some degree of sex differences in their clinical effects. Our comparative PheWAS-MR study of iron and copper comprehensively characterized their shared and unique clinical effects, highlighting their potential causal roles in hyperlipidemia and hypercholesterolemia. Given the modifiable nature of blood mineral status and the potential for clinical intervention, these findings warrant further investigation.

Project description:BackgroundCaffeine is one of the most utilized drugs in the world, yet its clinical effects are not fully understood. Circulating caffeine levels are influenced by the interplay between consumption behaviour and metabolism. This study aimed to investigate the effects of circulating caffeine levels by considering genetically predicted variation in caffeine metabolism.MethodsLeveraging genetic variants related to caffeine metabolism that affect its circulating levels, we investigated the clinical effects of plasma caffeine in a phenome-wide association study (PheWAS). We validated novel findings using a two-sample Mendelian randomization framework and explored the potential mechanisms underlying these effects in proteome-wide and metabolome-wide Mendelian randomization.ResultsHigher levels of genetically predicted circulating caffeine among caffeine consumers were associated with a lower risk of obesity (odds ratio (OR) per standard deviation increase in caffeine = 0.97, 95% confidence interval (CI) CI: 0.95-0.98, p = 2.47 × 10-4), osteoarthrosis (OR = 0.97, 95% CI: 0.96-0.98, P=1.10 × 10-8) and osteoarthritis (OR: 0.97, 95% CI: 0.96 to 0.98, P = 1.09 × 10-6). Approximately one third of the protective effect of plasma caffeine on osteoarthritis risk was estimated to be mediated through lower bodyweight. Proteomic and metabolomic perturbations indicated lower chronic inflammation, improved lipid profiles, and altered protein and glycogen metabolism as potential biological mechanisms underlying these effects.ConclusionsWe report novel evidence suggesting that long-term increases in circulating caffeine may reduce bodyweight and the risk of osteoarthrosis and osteoarthritis. We confirm prior genetic evidence of a protective effect of plasma caffeine on risk of overweight and obesity. Further clinical study is warranted to understand the translational relevance of these findings before clinical practice or lifestyle interventions related to caffeine consumption are introduced.

Dataset Information

Health effects of milk consumption: phenome-wide Mendelian randomization study.

Background

Methods

Results

Conclusions

Publications

Health effects of milk consumption: phenome-wide Mendelian randomization study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets