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1.
Eur J Clin Nutr ; 76(12): 1705-1712, 2022 12.
Article in English | MEDLINE | ID: mdl-35906333

ABSTRACT

Intrauterine environment can influence the offspring's body adiposity whose distribution affect the cardiometabolic risk. Underlying mechanisms may involve the gut microbiome. We investigated associations of gestational weight gain with the adult offspring's gut microbiota, body adiposity and related parameters in participants of the Nutritionists' Health Study. METHODS: This cross-sectional analysis included 114 women who had early life and clinical data, body composition, and biological samples collected. The structure of fecal microbiota was analyzed targeting the V4 region of the 16 S rRNA gene. Beta diversity was calculated by PCoA and PERMANOVA used to test the impact of categorical variables into the diversity. Bacterial clusters were identified based on the Jensen-Shannon divergence matrix and Calinski-Harabasz index. Correlations were tested by Spearman coefficient. RESULTS: Median age was 28 (IQR 24-31) years and BMI 24.5 (IQR 21.4-28.0) kg/m2. Fifty-eight participants were assigned to a profile driven by Prevotella and 56 to another driven by Blautia. Visceral adipose tissue was correlated to abundance of Acidaminococcus genus considering the entire sample (r = 0.37; p < 0.001) and the profiles (Blautia: r = 0.35, p = 0.009, and Prevotella: r = 0.38, p = 0.006). In Blautia-driven profile, the same genus was also correlated to maternal gestational weight gain (r = 0.38, p = 0.006). CONCLUSIONS: Association of Acidaminococcus with gestational weight gain could reinforce the relevance with mothers' nutritional status for gut colonization at the beginning of life. Whether Acidaminococcus abundance could be a marker for central distribution of adiposity in young women requires further investigation.


Subject(s)
Gestational Weight Gain , Adult , Humans , Female , Adiposity , Acidaminococcus , Body Mass Index , Cross-Sectional Studies , Adult Children , Obesity, Abdominal , Obesity
2.
Indian J Pediatr ; 88(4): 336-344, 2021 04.
Article in English | MEDLINE | ID: mdl-32945992

ABSTRACT

OBJECTIVES: To examine the association and predictive capacity of adiponectin levels, HOMA-AD and HOMA-IR indexes with metabolic risk markers in children and adolescents. METHODS: A cross-sectional study was conducted with 691 children and adolescents (7-14 y), of both sexes. Demographic (sex, age), anthropometric (weight, height, body mass index, waist circumference, body fat), biochemical [total cholesterol, high density lipoprotein (HDL), low density lipoprotein (LDL), triglycerides, fasting glycemia, insulin and adiponectin] and clinical parameters (arterial blood pressure) were analyzed. RESULTS: In multiple linear regression models, metabolic risk were analyzed in relation to adiponectin levels, HOMA-AD and HOMA-IR. ROC curve analysis was used to define the cut-off for metabolic syndrome for each method studied. Adiponectin level was inversely correlated with weight (r = -0.12; p = 0.01), waist circumference (WC) (r = -0.12; p = 0.01), and triglycerides (r = -0.11; p = 0.02); it was directly correlated with HDL (r = 0.10; p = 0.03) only in the adolescents. In the final linear regression model, after adjustment, only triglycerides (p = 0.03) and HDL (p = 0.04) remained significant. However, HOMA-AD and HOMA-IR were associated with metabolic risk and were the most suitable methods for metabolic syndrome screening in both age groups. For children, independent variables explained 16.0% and 14.5% of HOMA-AD and HOMA-IR, respectively. For adolescents, R2 was higher in HOMA-AD and HOMA-IR models (R2adjusted = 31.9% and R2adjusted = 29.6%, respectively). CONCLUSIONS: HOMA-AD and HOMA-IR are better explained by metabolic markers than adiponectin levels.


Subject(s)
Insulin Resistance , Metabolic Syndrome , Adiponectin , Adolescent , Blood Glucose , Body Mass Index , Child , Cholesterol, HDL , Cross-Sectional Studies , Female , Humans , Male , Metabolic Syndrome/diagnosis , Metabolic Syndrome/epidemiology , Obesity , Triglycerides
3.
Obes Surg ; 28(1): 226-233, 2018 01.
Article in English | MEDLINE | ID: mdl-28803396

ABSTRACT

PURPOSE: Bariatric surgery (BS) promotes carotid intima-media thickness (C-IMT) regression as early as 6 months post-surgery. To verify whether C-IMT regression occurs even earlier, we aimed at the effect of Roux-en-Y gastric bypass (RYGBP) and biliopancreatic diversion (BPD) on C-IMT 1-2 months and 12 months post-surgery. SUBJECTS/METHODS: Prospective trial. BS was performed on 109 patients either with (RYGBP = 42; BDP = 40) or without type 2 diabetes (RYGBP = 27). Healthy volunteers served as control group. FOLLOW-UP: baseline, 1-2 months, 12 months post-surgery. ENDPOINTS: changes (∆) in C-IMT, weight, body mass index, fat mass, waist and neck circumferences, blood pressure, HbA1c, glucose, insulin, insulin sensitivity [HOMA-IR; OGIS, from meal tolerance test], lipids, C-reactive protein, leptin, adiponectin, MCP-1. RESULTS: All surgery subgroups had similar levels of ∆-C-IMT. C-IMT in the pooled surgery group reduced from [mean (95% confidence interval)] 0.81 (0.77-0.84) mm to 0.66 (0.63-0.69) mm, p < 0.001 [-17.1 (-20.4 to -13.8)%] at 1-2 months, and to 0.63 (0.59-0.66) mm, p < 0.001 [-21.8 (-25.3 to -18.4)%] at 12 months post-surgery. ∆-C-IMT 1-2 months and 12 months post-surgery correlated to baseline C-IMT, and with ∆-leptin at 1-2 months, but not at 12 months post-surgery. In linear regression analysis, ∆-leptin and baseline C-IMT were predictors of ∆-C-IMT 1-2 months post-surgery. CONCLUSIONS: A remarkable C-IMT regression occurred as early as 1-2 months after BS in obese patients either with or without type 2 diabetes, which was associated to the early reduction in leptin, (at least partially) independent of weight loss. Whether this is a causative or correlative association needs further investigation.


Subject(s)
Bariatric Surgery , Carotid Intima-Media Thickness , Diabetes Mellitus, Type 2/surgery , Leptin/blood , Obesity/surgery , Adult , Bariatric Surgery/rehabilitation , Body Mass Index , Carotid Arteries/diagnostic imaging , Carotid Arteries/pathology , Diabetes Mellitus, Type 2/blood , Diabetes Mellitus, Type 2/complications , Diabetes Mellitus, Type 2/physiopathology , Female , Humans , Insulin Resistance/physiology , Male , Middle Aged , Obesity/blood , Obesity/complications , Obesity/physiopathology , Obesity, Morbid/blood , Obesity, Morbid/complications , Obesity, Morbid/physiopathology , Obesity, Morbid/surgery , Time Factors , Tunica Intima/diagnostic imaging , Tunica Intima/pathology , Weight Loss/physiology , Young Adult
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