Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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Group, Mendelian Randomization Of Dairy Consumption Working

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in Cooperation with on an Cooperation-Score of 37%

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  • 2019Dairy Intake and Body Composition and Cardiometabolic Traits among Adults24citations

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Overvad, Kim
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2019

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  • Consortium, Charge
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article

Dairy Intake and Body Composition and Cardiometabolic Traits among Adults

  • Group, Mendelian Randomization Of Dairy Consumption Working
  • Consortium, Charge
  • Overvad, Kim
Abstract

<p>BACKGROUND: Associations between dairy intake and body composition and cardiometabolic traits have been inconsistently observed in epidemiological studies, and the causal relationship remains ill-defined. METHODS: We performed Mendelian randomization analysis using an established genetic variant located upstream of the lactase gene (LCT-13910 C/T, rs4988235) associated with dairy intake as an instrumental variable (IV). The causal effects of dairy intake on body composition and cardiometabolic traits (lipids, glycemic traits, and inflammatory factors) were quantified by IV estimators among 182041 participants from 18 studies. RESULTS: Each 1 serving/day higher dairy intake was associated with higher lean mass [β (SE) = 0.117 kg (0.035); P = 0.001], higher hemoglobin A<sub>1c</sub> [0.009% (0.002); P &lt; 0.001], lower LDL [-0.014 mmol/L (0.006); P = 0.013], total cholesterol (TC) [-0.012 mmol/L (0.005); P = 0.023], and non-HDL [-0.012 mmol/L (0.005); P = 0.028]. The LCT-13910 C/T CT + TT genotype was associated with 0.214 more dairy servings/day (SE = 0.047; P &lt; 0.001), 0.284 cm higher waist circumference (SE = 0.118; P = 0.017), 0.112 kg higher lean mass (SE = 0.027; P = 3.8 × 10-5), 0.032 mmol/L lower LDL (SE = 0.009; P = 0.001), and 0.032 mmol/L lower TC (SE = 0.010; P = 0.001). Genetically higher dairy intake was associated with increased lean mass [0.523 kg per serving/day (0.170); P = 0.002] after correction for multiple testing (0.05/18). However, we find that genetically higher dairy intake was not associated with lipids and glycemic traits. CONCLUSIONS: The present study provides evidence to support a potential causal effect of higher dairy intake on increased lean mass among adults. Our findings suggest that the observational associations of dairy intake with lipids and glycemic traits may be the result of confounding.</p>

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