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Abstract
Background
High milk intake has been associated with cardio-metabolic risk. We conducted a Mendelian Randomization (MR) study to obtain evidence for the causal relationship between milk consumption and cardio-metabolic traits using the lactase persistence (LCT-13910 C > T, rs4988235) variant as an instrumental variable.
Methods
We tested the association of LCT genotype with milk consumption (for validation) and with cardio-metabolic traits (for a possible causal association) in a meta-analysis of the data from three large-scale population-based studies (1958 British Birth Cohort, Health and Retirement study, and UK Biobank) with up to 417,236 participants and using summary statistics from consortia meta-analyses on intermediate traits (N = 123,665–697,307) and extended to cover disease endpoints (N = 86,995–149,821).
Results
In the UK Biobank, carriers of ‘T’ allele of LCT variant were more likely to consume milk (P = 7.02 × 10−14). In meta-analysis including UK Biobank, the 1958BC, the HRS, and consortia-based studies, under an additive model, ‘T’ allele was associated with higher body mass index (BMI) (Pmeta-analysis = 4.68 × 10−12) and lower total cholesterol (TC) (P = 2.40 × 10−36), low-density lipoprotein cholesterol (LDL-C) (P = 2.08 × 10−26) and high-density lipoprotein cholesterol (HDL-C) (P = 9.40 × 10−13). In consortia meta-analyses, ‘T’ allele was associated with a lower risk of coronary artery disease (OR:0.86, 95% CI:0.75–0.99) but not with type 2 diabetes (OR:1.06, 95% CI:0.97–1.16). Furthermore, the two-sample MR analysis showed a causal association between genetically instrumented milk intake and higher BMI (P = 3.60 × 10−5) and body fat (total body fat, leg fat, arm fat and trunk fat; P < 1.37 × 10−6) and lower LDL-C (P = 3.60 × 10−6), TC (P = 1.90 × 10−6) and HDL-C (P = 3.00 × 10−5).
Conclusions
Our large-scale MR study provides genetic evidence for the association of milk consumption with higher BMI but lower serum cholesterol levels. These data suggest no need to limit milk intakes with respect to cardiovascular disease risk, with the suggested benefits requiring confirmation in further studies.
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1 University of Reading, Hugh Sinclair Unit of Human Nutrition, Reading, UK (GRID:grid.9435.b) (ISNI:0000 0004 0457 9566); UCL Institute of Child Health, Population, Policy and Practice, London, UK (GRID:grid.83440.3b) (ISNI:0000000121901201); University of Reading, Institute for Food, Nutrition, and Health, Reading, UK (GRID:grid.9435.b) (ISNI:0000 0004 0457 9566)
2 University of South Australia, Australian Centre for Precision Health, Unit of Clinical and Health Sciences, Adelaide, Australia (GRID:grid.1026.5) (ISNI:0000 0000 8994 5086)
3 University of Auckland, Section of Epidemiology and Biostatistics, School of Population Health, Auckland, New Zealand (GRID:grid.9654.e) (ISNI:0000 0004 0372 3343)
4 UCL Institute of Child Health, Population, Policy and Practice, London, UK (GRID:grid.83440.3b) (ISNI:0000000121901201); University of South Australia, Australian Centre for Precision Health, Unit of Clinical and Health Sciences, Adelaide, Australia (GRID:grid.1026.5) (ISNI:0000 0000 8994 5086); South Australian Health and Medical Research Institute, Adelaide, Australia (GRID:grid.430453.5) (ISNI:0000 0004 0565 2606)