Usual Dietary Intake Estimation Based on a Combination of Repeated 24-H Food Lists and a Food Frequency Questionnaire in the KORA FF4 Cross-Sectional Study.

Background: Estimation of usual dietary intake poses a challenge in epidemiological studies. We applied a blended approach that combines the strengths provided by repeated 24-h food lists (24HFLs) and a food frequency questionnaire (FFQ). Methods: At least two web-based 24HFLs and one FFQ were completed by 821 participants in the KORA FF4 study. Consumption probabilities were estimated using logistic mixed models, adjusting for covariates and the FFQ data on consumption frequency. Intake amount of a consumed food item was predicted for each participant based on the results of the second Bavarian Food Consumption Survey (BVS II). By combining consumption probability and estimated consumption amount, the usual food intake for each participant was estimated. These results were compared to results obtained without considering FFQ information for consumption probability estimation, as well as to conventional FFQ data. Results: The results of the blended approach for food group intake were often higher than the FFQ-based results. Intraclass correlation coefficients between both methods ranged between 0.21 and 0.86. Comparison of both methods resulted in weighted kappa values based on quintiles ranging from fair (0.34) to excellent agreement (0.84). Omission of FFQ information in the consumption probability models distinctly affected the results at the group level, though individual intake data were slightly affected, for the most part. Conclusions: Usual dietary intake data based on the blended approach differs from the FFQ-based results both in absolute terms and in classification according to quintiles. The application of the blended approach has been demonstrated as a possible tool in nutritional epidemiology, as a comparison with published studies showed that the blended approach yields reasonable estimates. The inclusion of the FFQ information is valuable especially with regard to irregularly consumed foods. A validation study including biomarkers of dietary intake is warranted.

Treatment of Thyroid Dysfunctions Decreases the Risk of Cerebrovascular Events in Men but Not in Women: Results of the MONICA/KORA Cohort Study.

OBJECTIVE: Thyroid disorders are well known to be associated with cardiovascular diseases. Some studies have shown that the negative effects of thyroid disorders are partially reversible after adequate treatment. The aim of this analysis was to assess the risk of incident ischemic cerebrovascular diseases in study participants treated for thyroid dysfunctions in a population-based cohort study. METHODS: For the presented analyses data from 8564 male and 8714 female individuals aged 25 to 74 years of the MONICA/KORA cohort were used (median follow-up 14.0 years). A combined binary variable "thyroid disorder" (TDC) was created utilizing data on self-reported physician-treated thyroid disorders and information about medication use. To examine the association between TDC and incident ischemic cerebrovascular events, we performed multiple adjusted Cox proportional hazard regression models and calculated hazard ratios and corresponding 95% confidence intervals (HR, 95%CI). RESULTS: During follow-up between 1984 and 2008/2009, 514 incident fatal and non-fatal ischemic cerebrovascular events occurred in men and 323 in women. At baseline, 3.5% of men and 15.6% of women reported TDC. In the fully adjusted model, males who reported TDC had a significantly reduced risk of ischemic cerebrovascular events (HR = 0.52, 95%CI = 0.29-0.92). A similar result was obtained in men, when we utilized information on thyroid hormones use only. For the total study population and for women with TDC we found no association with ischemic cerebrovascular events. CONCLUSIONS: In our longitudinal analyses subjects with treated thyroid diseases had no increased risk of incident ischemic cerebrovascular events. Surprisingly in males, even a significantly reduced risk of incident ischemic cerebrovascular events was found, a result that deserves further clarification.

Multi-omic signature of body weight change: results from a population-based cohort study.

BACKGROUND: Excess body weight is a major risk factor for cardiometabolic diseases. The complex molecular mechanisms of body weight change-induced metabolic perturbations are not fully understood. Specifically, in-depth molecular characterization of long-term body weight change in the general population is lacking. Here, we pursued a multi-omic approach to comprehensively study metabolic consequences of body weight change during a seven-year follow-up in a large prospective study. METHODS: We used data from the population-based Cooperative Health Research in the Region of Augsburg (KORA) S4/F4 cohort. At follow-up (F4), two-platform serum metabolomics and whole blood gene expression measurements were obtained for 1,631 and 689 participants, respectively. Using weighted correlation network analysis, omics data were clustered into modules of closely connected molecules, followed by the formation of a partial correlation network from the modules. Association of the omics modules with previous annual percentage weight change was then determined using linear models. In addition, we performed pathway enrichment analyses, stability analyses, and assessed the relation of the omics modules with clinical traits. RESULTS: Four metabolite and two gene expression modules were significantly and stably associated with body weight change (P-values ranging from 1.9 × 10(-4) to 1.2 × 10(-24)). The four metabolite modules covered major branches of metabolism, with VLDL, LDL and large HDL subclasses, triglycerides, branched-chain amino acids and markers of energy metabolism among the main representative molecules. One gene expression module suggests a role of weight change in red blood cell development. The other gene expression module largely overlaps with the lipid-leukocyte (LL) module previously reported to interact with serum metabolites, for which we identify additional co-expressed genes. The omics modules were interrelated and showed cross-sectional associations with clinical traits. Moreover, weight gain and weight loss showed largely opposing associations with the omics modules. CONCLUSIONS: Long-term weight change in the general population globally associates with serum metabolite concentrations. An integrated metabolomics and transcriptomics approach improved the understanding of molecular mechanisms underlying the association of weight gain with changes in lipid and amino acid metabolism, insulin sensitivity, mitochondrial function as well as blood cell development and function.

Associations between thyroid hormones and serum metabolite profiles in an euthyroid population.

The aim was to characterise associations between circulating thyroid hormones-free thyroxine (FT4) and thyrotropin (TSH)-and the metabolite profiles in serum samples from participants of the German population-based KORA F4 study. Analyses were based on the metabolite profile of 1463 euthyroid subjects. In serum samples, obtained after overnight fasting (≥8), 151 different metabolites were quantified in a targeted approach including amino acids, acylcarnitines (ACs), and phosphatidylcholines (PCs). Associations between metabolites and thyroid hormone concentrations were analysed using adjusted linear regression models. To draw conclusions on thyroid hormone related pathways, intra-class metabolite ratios were additionally explored. We discovered 154 significant associations (Bonferroni p < 1.75 × 10-04) between FT4 and various metabolites and metabolite ratios belonging to AC and PC groups. Significant associations with TSH were lacking. High FT4 levels were associated with increased concentrations of many ACs and various sums of ACs of different chain length, and the ratio of C2 by C0. The inverse associations observed between FT4 and many serum PCs reflected the general decrease in PC concentrations. Similar results were found in subgroup analyses, e.g., in weight-stable subjects or in obese subjects. Further, results were independent of different parameters for liver or kidney function, or inflammation, which supports the notion of an independent FT4 effect. In fasting euthyroid adults, higher serum FT4 levels are associated with increased serum AC concentrations and an increased ratio of C2 by C0 which is indicative of an overall enhanced fatty acyl mitochondrial transport and ß-oxidation of fatty acids.

Body fat free mass is associated with the serum metabolite profile in a population-based study.

OBJECTIVE: To characterise the influence of the fat free mass on the metabolite profile in serum samples from participants of the population-based KORA (Cooperative Health Research in the Region of Augsburg) S4 study. SUBJECTS AND METHODS: Analyses were based on metabolite profile from 965 participants of the S4 and 890 weight-stable subjects of its seven-year follow-up study (KORA F4). 190 different serum metabolites were quantified in a targeted approach including amino acids, acylcarnitines, phosphatidylcholines (PCs), sphingomyelins and hexose. Associations between metabolite concentrations and the fat free mass index (FFMI) were analysed using adjusted linear regression models. To draw conclusions on enzymatic reactions, intra-metabolite class ratios were explored. Pairwise relationships among metabolites were investigated and illustrated by means of Gaussian graphical models (GGMs). RESULTS: We found 339 significant associations between FFMI and various metabolites in KORA S4. Among the most prominent associations (p-values 4.75 × 10(-16)-8.95 × 10(-06)) with higher FFMI were increasing concentrations of the branched chained amino acids (BCAAs), ratios of BCAAs to glucogenic amino acids, and carnitine concentrations. For various PCs, a decrease in chain length or in saturation of the fatty acid moieties could be observed with increasing FFMI, as well as an overall shift from acyl-alkyl PCs to diacyl PCs. These findings were reproduced in KORA F4. The established GGMs supported the regression results and provided a comprehensive picture of the relationships between metabolites. In a sub-analysis, most of the discovered associations did not exist in obese subjects in contrast to non-obese subjects, possibly indicating derangements in skeletal muscle metabolism. CONCLUSION: A set of serum metabolites strongly associated with FFMI was identified and a network explaining the relationships among metabolites was established. These results offer a novel and more complete picture of the FFMI effects on serum metabolites in a data-driven network.