ABSTRACT
OBJECTIVE: MRI is established for measurement of body fat mass (FM) and abdominal visceral adipose tissue (VAT). Anthropometric measurements and bioelectrical impedance analysis (BIA) have been proposed as surrogates to estimation by MRI. Aim of this work is to assess the predictive value of these methods for FM and VAT measured by MRI. METHODS: Patients were selected from cohort study PPS-Diab (prediction, prevention and subclassification of Type 2 diabetes). Total FM and VAT were quantified by MRI and BIA together with clinical variables like age, waist and hip circumference and height. Least-angle regressions were utilized to select anthropometric and BIA parameters for their use in multivariable linear regression models to predict total FM and VAT. Bland-Altman plots, Pearson correlation coefficients, Wilcoxon signed-rank tests and univariate linear regression models were applied. RESULTS: 116 females with 35 ± 3 years and a body mass index of 25.1 ± 5.3 kg/m2 were included into the analysis. A multivariable model revealed weight (ß = 0.516, p < 0.001), height (ß = -0.223, p < 0.001) and hip circumference (ß = 0.156, p = 0.003) as significantly associated with total FM measured by MRI. A additional multivariable model also showed a significant predictive value of FMBIA (ß = 0.583, p < 0.001) for FM. In addition, waist circumference (ß = 0.054, p < 0.001), weight (ß = 0.016, p = 0.031) in one model and FMBIA (ß = 0.026, p = 0.018) in another model were significantly associated with VAT quantified by MRI. However, deviations reached more than 5 kg for total FM and more than 1 kg for VAT. CONCLUSION: Anthropometric measurements and BIA show significant association with total FM and VAT. ADVANCES IN KNOWLEDGE: As these measurements show significant deviations from the absolute measured values determined by MRI, MRI should be considered the gold-standard for quantification.
Subject(s)
Adipose Tissue/anatomy & histology , Electric Impedance , Magnetic Resonance Imaging , Adipose Tissue/diagnostic imaging , Adult , Age Factors , Body Height , Body Mass Index , Body Weight , Diabetes Mellitus, Type 2/etiology , Female , Humans , Intra-Abdominal Fat/anatomy & histology , Intra-Abdominal Fat/diagnostic imaging , Linear Models , Middle Aged , Predictive Value of Tests , Waist Circumference , Waist-Height Ratio , Waist-Hip RatioABSTRACT
BACKGROUND: Serum nonesterified fatty acids (NEFA) are known to be associated with the development of insulin resistance. Recently, differences in the NEFA profile were found in subjects with history of gestational diabetes (postGDM) and healthy controls. Little is known about the NEFA sources in the postprandial state, which prevails most of the day in humans in modern societies. In the present study, we aimed to explore the potential contributions of glycerophospholipid (GPL) and sphingomyelin (SM) fatty acids to the circulating NEFA. METHODS: Serum-samples of 19 postGDM women and 20 controls were obtained in fasting state (t0) and 90 minutes (t90) after an oral glucose tolerance test. Fatty acid composition of NEFA and SM were analyzed with liquid chromatography coupled to triple quadrupole mass spectrometry and GPL by gas chromatography. RESULTS: The ratio of individual NEFA at t90 vs. t0 (t90/0-ratio) showed no difference between the two groups but increased with chain-length (7% for C16:1, 82% for C26:3). Only NEFA 10:0 was found with lower concentration at t0 and t90 in postGDM. At t90, long-chain polyunsaturated fatty acid correlated closely between NEFA and GPL in postGDM (20:5, 22:4, 22:5 and 22:6) and controls (20:3, 20:4 and 20:5). Very long-chain fatty acid 24:0 correlated significantly between NEFA and SM in postGDM and controls. Saturated and monounsaturated fatty acids correlated less between NEFA and GPL or SM. CONCLUSIONS: The NEFA composition varied highly between fasting and fed state in both groups. GPL appeared to contribute long-chain polyunsaturated fatty acid, while SM appeared to contribute very long-chain fatty acids to the NEFA pool.
Subject(s)
Diabetes, Gestational/blood , Fasting/blood , Fatty Acids, Nonesterified/blood , Glycerophospholipids/analysis , Sphingomyelins/analysis , Adult , Animals , Case-Control Studies , Chromatography, Liquid , Fatty Acids, Nonesterified/analysis , Female , Glucose Tolerance Test , Glycerophospholipids/blood , Humans , Postprandial Period , Pregnancy , Sphingomyelins/blood , Tandem Mass SpectrometryABSTRACT
The gut microbiota has been linked to metabolic diseases. However, information on the microbiome of young adults at risk for type 2 diabetes (T2D) is lacking. The aim of this cross-sectional analysis was to investigate whether insulin resistant women with previous gestational diabetes (pGDM), a high risk group for T2D, differ in their stool microbiota from women after a normoglycemic pregnancy (controls). Bacterial communities were analyzed by high-throughput 16S rRNA gene sequencing using fecal samples from 42 pGDM and 35 control subjects 3-16 months after delivery. Clinical characterization included a 5-point OGTT, anthropometrics, clinical chemistry markers and a food frequency questionnaire. Women with a Prevotellaceae-dominated intestinal microbiome were overrepresented in the pGDM group (p < 0.0001). Additionally, the relative abundance of the phylum Firmicutes was significantly lower in women pGDM (median 48.5 vs. 56.8%; p = 0.013). Taxa richness (alpha diversity) was similar between the two groups and with correction for multiple testing we observed no significant differences on lower taxonomic levels. These results suggest that distinctive features of the intestinal microbiota are already present in young adults at risk for T2D and that further investigations of a potential pathophysiological role of gut bacteria in early T2D development are warranted.
Subject(s)
Diabetes Mellitus, Type 2/etiology , Diabetes, Gestational/pathology , Feces/microbiology , Actinobacteria/isolation & purification , Adult , Bacteroidetes/isolation & purification , Cross-Sectional Studies , Demography , Diabetes, Gestational/microbiology , Female , Firmicutes/isolation & purification , Glucose Tolerance Test , Humans , Insulin Resistance , Intestines/microbiology , Microbiota , Pregnancy , RNA, Ribosomal, 16S/chemistry , RNA, Ribosomal, 16S/genetics , Risk Factors , Sequence Analysis, DNA , Young AdultABSTRACT
BACKGROUND: Nonesterified fatty acids (NEFA) play pathophysiological roles in metabolic syndrome and type 2 diabetes (T2D). In this study, we analyzed the fasting NEFA profiles of normoglycemic individuals at risk for T2D (women with a recent history of gestational diabetes (GDM)) in comparison to controls (women after a normoglycemic pregnancy). We also examined the associations of NEFA species with overweight/obesity, body fat distribution and insulin sensitivity. SUBJECTS AND METHODS: Using LC-MS/MS, we analyzed 41 NEFA species in the fasting sera of 111 women (62 post-GDM, 49 controls). Clinical characterization included a five-point oral glucose tolerance test (OGTT), biomarkers and anthropometrics, magnetic resonance imaging (n = 62) and a food frequency questionnaire. Nonparametric tests with Bonferroni correction, binary logistic regression analyses and rank correlations were used for statistical analysis. RESULTS: Women after GDM had a lower molar percentage of total saturated fatty acids (SFA; 38.55% vs. 40.32%, p = 0.0002) than controls. At an explorative level of significance several NEFA species were associated with post-GDM status (with and without adjustment for body mass index (BMI) and HbA1c): The molar percentages of 14:0, 16:0, 18:0 and 18:4 were reduced, whereas those of 18:1, 18:2, 20:2, 24:4, monounsaturated fatty acids (MUFA), polyunsaturated fatty acids (PUFA) and total n-6 NEFA were increased. BMI and the amount of body fat correlated inversely with several SFA and MUFA and positively with various PUFA species over the whole study cohort (abs(ρ)≥0.3 for all). 14:0 was inversely and BMI-independently associated with abdominal visceral adiposity. We saw no correlations of NEFA species with insulin sensitivity and the total NEFA concentration was similar in the post-GDM and the control group. CONCLUSION: In conclusion, we found alterations in the fasting NEFA profile associated with a recent history of gestational diabetes, a risk marker for T2D. NEFA composition also varied with overweight/obesity and with body fat distribution, but not with insulin sensitivity.
Subject(s)
Diabetes, Gestational/blood , Fatty Acids/blood , Insulin Resistance , Obesity/blood , Adult , Biomarkers/blood , Diabetes Mellitus, Type 2/blood , Diabetes Mellitus, Type 2/diagnostic imaging , Diabetes, Gestational/diagnostic imaging , Female , Humans , Magnetic Resonance Imaging , Obesity/diagnostic imaging , Pregnancy , RadiographyABSTRACT
CONTEXT: The pathogenesis of type 2 diabetes (T2D) is still incompletely understood. In-depth phenotyping of young individuals at risk for T2D can contribute to the understanding of this process. OBJECTIVE: The purpose of this study was to metabolically characterize women with recent gestational diabetes (GDM), an at-risk cohort for T2D. STUDY PARTICIPANTS: Participants were 147 women consecutively recruited 3 to 16 months after pregnancy: women who had GDM and women after a normoglycemic pregnancy (control subjects) in a 2:1 ratio. DESIGN: This was a monocenter cross-sectional analysis (Prediction, Prevention and Subclassification of Type 2 Diabetes Study [PPS-Diab]). METHODS: A 5-point oral glucose tolerance test with calculation of the insulin sensitivity index and disposition index (validation by euglycemic clamp and intravenous glucose tolerance test) was performed. In addition, anthropometrics, medical and family history, clinical chemistry and biomarkers, statistical modeling, and a magnetic resonance imaging/magnetic resonance spectroscopy substudy (body fat distribution and liver and muscle fat; n = 66) were obtained. RESULTS: Compared with control subjects, women after GDM had a reduced disposition index, higher levels of plasma fetuin-A, and a lower insulin sensitivity index. A low insulin sensitivity index was also the major determinant of pathological glucose tolerance after GDM. The factors most strongly predictive of low insulin sensitivity were high plasma leptin, body mass index, triglycerides, and waist circumference. Ectopic lipids showed no body mass index-independent associations with having had GDM or low insulin sensitivity in a magnetic resonance imaging substudy. CONCLUSIONS: We found that ß-cell function is already impaired in women with recent GDM, a young at-risk cohort for T2D. In addition, our data suggest that fetuin-A and leptin signaling may be important early contributors to the pathogenesis of T2D, at this disease stage equally or more relevant than ectopic lipids and low-grade inflammation.
Subject(s)
Diabetes Mellitus, Type 2/etiology , Diabetes, Gestational/epidemiology , Phenotype , Adult , Body Composition , Case-Control Studies , Cross-Sectional Studies , Diabetes Mellitus, Type 2/epidemiology , Diabetes, Gestational/metabolism , Female , Glucose Tolerance Test , Humans , Insulin Resistance , Postpartum Period , Pregnancy , Risk FactorsABSTRACT
BACKGROUND: Information regarding the variability of metabolite levels over time in an individual is required to estimate the reproducibility of metabolite measurements. In intervention studies, it is critical to appropriately judge changes that are elicited by any kind of intervention. The pre-analytic phase (collection, transport and sample processing) is a particularly important component of data quality in multi-center studies. METHODS: Reliability of metabolites (within-and between-person variance, intraclass correlation coefficient) and stability (shipment simulation at different temperatures, use of gel-barrier collection tubes, freeze-thaw cycles) were analyzed in fasting serum and plasma samples of 22 healthy human subjects using a targeted LC-MS approach. RESULTS: Reliability of metabolite measurements was higher in serum compared to plasma samples and was good in most saturated short-and medium-chain acylcarnitines, amino acids, biogenic amines, glycerophospholipids, sphingolipids and hexose. The majority of metabolites were stable for 24 h on cool packs and at room temperature in non-centrifuged tubes. Plasma and serum metabolite stability showed good coherence. Serum metabolite concentrations were mostly unaffected by tube type and one or two freeze-thaw cycles. CONCLUSION: A single time point measurement is assumed to be sufficient for a targeted metabolomics analysis of most metabolites. For shipment, samples should ideally be separated and frozen immediately after collection, as some amino acids and biogenic amines become unstable within 3 h on cool packs. Serum gel-barrier tubes can be used safely for this process as they have no effect on concentration in most metabolites. Shipment of non-centrifuged samples on cool packs is a cost-efficient alternative for most metabolites.