No evidence linking sleep traits with white blood cell counts: Multivariable-adjusted and Mendelian randomization analyses.

BACKGROUND: Disturbances in habitual sleep have been associated with multiple age-associated diseases. However, the biological mechanisms underpinning these associations remain largely unclear. We assessed the possible involvement of the circulating immune system by determining the associations between sleep traits and white blood cell counts using multivariable-adjusted linear regression and Mendelian randomization. METHODS: Cross-sectional multivariable-adjusted linear regression analyses were done using participants within the normal range of total white blood cell counts (>4.5 × 109 and <11.0 × 109/µL) from UK Biobank. For the sleep traits, we examined (short and long) sleep duration, chronotype, insomnia symptoms and daytime dozing. Two-sample Mendelian randomization analyses were done using instruments for sleep traits derived from European-ancestry participants from UK Biobank (over 410,000 participants) and using SNP-outcome data derived from European-ancestry participants from the Blood Cell Consortium (N = 563,946) to which no data from UK Biobank contributed. RESULTS: Using data from 357,656 participants (mean [standard deviation] age: 56.5 [8.1] years, and 44.4% men), we did not find evidence that disturbances in any of the studied sleep traits were associated with differences in blood cell counts (total, lymphocytes, neutrophiles, eosinophiles and basophiles). Also, we did not find associations between disturbances in any of the studied sleep traits and white blood cell counts using Mendelian Randomization. CONCLUSION: Based on the results from two different methodologies, disturbances in habitual sleep are unlikely to cause changes in blood cell counts and thereby differences in blood cell counts are unlikely to be underlying the observed sleep-disease associations.

The role of genetically-influenced phospholipid transfer protein activity in lipoprotein metabolism and coronary artery disease.

BACKGROUND: Phospholipid transfer protein (PLTP) transfers surface phospholipids between lipoproteins and as such plays a role in lipoprotein metabolism, but with unclear effects on coronary artery disease (CAD) risk. We aimed to investigate the associations of genetically-influenced PLTP activity with 1-H nuclear magnetic resonance (1H-NMR) metabolomic measures and with CAD. Furthermore, using factorial Mendelian randomization (MR), we examined the potential additional effect of genetically-influenced PLTP activity on CAD risk on top of genetically-influenced low-density lipoprotein-cholesterol (LDL-C) lowering. METHODS: Using data from UK Biobank, genetic scores for PLTP activity and LDL-C were calculated and dichotomised based on the median, generating four groups with combinations of high/low PLTP activity and high/low LDL-C levels for the factorial MR. Linear and logistic regressions were performed on 168 metabolomic measures (N = 58,514) and CAD (N = 318,734, N-cases=37,552), respectively, with results expressed as ß coefficients (in standard deviation units) or odds ratios (ORs) and 95% confidence interval (CI). RESULTS: Irrespective of the genetically-influenced LDL-C, genetically-influenced low PLTP activity was associated with a higher HDL particle concentration (ß [95% CI]: 0.03 [0.01, 0.05]), smaller HDL size (-0.14 [-0.15, -0.12]) and higher triglyceride (TG) concentration (0.04 [0.02, 0.05]), but not with CAD (OR 0.99 [0.97, 1.02]). In factorial MR analyses, genetically-influenced low PLTP activity and genetically-influenced low LDL-C had independent associations with metabolomic measures, and genetically-influenced low PLTP activity did not show an additional effect on CAD risk. CONCLUSIONS: Low PLTP activity associates with higher HDL particle concentration, smaller HDL particle size and higher TG concentration, but no association with CAD risk was observed.

The association between body mass index and metabolite response to a liquid mixed meal challenge: a Mendelian randomization study.

BACKGROUND: Metabolite abundance is a dynamic trait that varies in response to environmental stimuli and phenotypic traits, such as food consumption and body mass index (BMI, kg/m2). OBJECTIVES: In this study, we used the Netherlands Epidemiology of Obesity (NEO) study data to identify observational and causal associations between BMI and metabolite response to a liquid meal. METHODS: A liquid meal challenge was performed, and Nightingale Health metabolite profiles were collected in 5744 NEO participants. Observational and one-sample Mendelian randomization (MR) analysis were conducted to estimate the effect of BMI on metabolites (n = 229) in the fasting, postprandial, and response (or change in abundance) states. RESULTS: We observed 473 associations with BMI (175 fasting, 188 postprandial, and 110 response) in observational analyses. In MR analyses, we observed 20 metabolite traits (5 fasting, 12 postprandial, and 3 response) to be associated with BMI. MR associations included the glucogenic amino acid alanine, which was inversely associated with BMI in the response state (ß: -0.081; SE: 0.023; P = 5.91 × 10-4), suggesting that as alanine increased in postprandial abundance, that increase was attenuated with increasing BMI. CONCLUSIONS: Overall, this study showed that MR estimates were strongly correlated with observational effect estimates, suggesting that the broad associations seen between BMI and metabolite variation has a causal underpinning. Specific effects in previously unassessed postprandial and response states are detected, and these may likely mark novel life course risk exposures driven by regular nutrition.