Genetic versus Non-Genetic Regulation of miR-103, miR-143 and miR-483-3p Expression in Adipose Tissue and Their Metabolic Implications-A Twin Study.

Murine models suggest that the microRNAs miR-103 and miR-143 may play central roles in the regulation of subcutaneous adipose tissue (SAT) and development of type 2 diabetes (T2D). The microRNA miR-483-3p may reduce adipose tissue expandability and cause ectopic lipid accumulation, insulin resistance and T2D. We aimed to explore the genetic and non-genetic factors that regulate these microRNAs in human SAT, and to investigate their impact on metabolism in humans. Levels of miR-103, miR-143 and miR-483-3p were measured in SAT biopsies from 244 elderly monozygotic and dizygotic twins using real-time PCR. Heritability estimates were calculated and multiple regression analyses were performed to study associations between these microRNAs and measures of metabolism, as well as between these microRNAs and possible regulating factors. We found that increased BMI was associated with increased miR-103 expression levels. In addition, the miR-103 levels were positively associated with 2 h plasma glucose levels and hemoglobin A1c independently of BMI. Heritability estimates for all three microRNAs were low. In conclusion, the expression levels of miR-103, miR-143 and miR-483-3p in adipose tissue are primarily influenced by non-genetic factors, and miR-103 may be involved in the development of adiposity and control of glucose metabolism in humans

Genetic versus Non-Genetic Regulation of miR-103, miR-143 and miR-483-3p Expression in Adipose Tissue and Their Metabolic Implications-A Twin Study.

Murine models suggest that the microRNAs miR-103 and miR-143 may play central roles in the regulation of subcutaneous adipose tissue (SAT) and development of type 2 diabetes (T2D). The microRNA miR-483-3p may reduce adipose tissue expandability and cause ectopic lipid accumulation, insulin resistance and T2D. We aimed to explore the genetic and non-genetic factors that regulate these microRNAs in human SAT, and to investigate their impact on metabolism in humans. Levels of miR-103, miR-143 and miR-483-3p were measured in SAT biopsies from 244 elderly monozygotic and dizygotic twins using real-time PCR. Heritability estimates were calculated and multiple regression analyses were performed to study associations between these microRNAs and measures of metabolism, as well as between these microRNAs and possible regulating factors. We found that increased BMI was associated with increased miR-103 expression levels. In addition, the miR-103 levels were positively associated with 2 h plasma glucose levels and hemoglobin A1c independently of BMI. Heritability estimates for all three microRNAs were low. In conclusion, the expression levels of miR-103, miR-143 and miR-483-3p in adipose tissue are primarily influenced by non-genetic factors, and miR-103 may be involved in the development of adiposity and control of glucose metabolism in humans

Maternal protein intake in pregnancy and offspring metabolic health at age 9-16 y: results from a Danish cohort of gestational diabetes mellitus pregnancies and controls.

To access publisher's full text version of this article click on the hyperlink belowBackground: Recent years have seen strong tendencies toward high-protein diets. However, the implications of higher protein intake, especially during developmentally sensitive periods, are poorly understood. Conversely, evidence on the long-term developmental consequences of low protein intake in free-living populations remains limited.Objective: We examined the association of protein intake in pregnancy with offspring metabolic health at age 9-16 y in a longitudinal cohort that oversampled pregnancies with gestational diabetes mellitus (GDM).Design: Six hundred eight women with an index pregnancy affected by gestational diabetes mellitus and 626 controls enrolled in the Danish National Birth Cohort were used for the analysis. Protein (total, animal, vegetable) intake was assessed by using a food-frequency questionnaire in gestational week 25. The offspring underwent a clinical examination including fasting blood samples and a dual-energy X-ray absorptiometry scan (subset of 650) from which metabolic outcomes were derived. Multivariable analyses were conducted applying a 1:1 substitution of carbohydrates for protein.Results: The mean ± SD protein intake in pregnancy was 93 ± 15 g/d (16% ± 3% of energy) in GDM-exposed women and 90 ± 14 g/d (16% ± 2% of energy) in control women. There were overall no associations between maternal protein intake and offspring fasting insulin and homeostasis model assessment of insulin resistance (HOMA-IR). We found that maternal total protein intake was associated with a tendency for a higher abdominal fat mass percentage (quartile 4 compared with quartile 1: 0.40 SD; 95% CI: -0.03, 0.83 SD; P = 0.07) in GDM-exposed offspring and a tendency for a higher total fat mass percentage among male offspring (quartile 4 compared with quartile 1: 0.33 SD; 95% CI: -0.01, 0.66 SD; P = 0.06), but a small sample size may have compromised the precision of the effect estimates. GDM-exposed offspring of mothers with a protein intake in the lowest decile (≤12.5% of energy compared with >12.5% of energy) had lower fasting insulin (ratio of geometric means: 0.82; 95% CI: 0.68, 0.99; P = 0.04) and a tendency toward lower HOMA-IR (ratio of geometric means: 0.82; 95% CI: 0.66, 1.02; P = 0.07), but there was no evidence of associations with body composition. Male offspring seemed to derive a similar benefit from a maternal low protein intake as did GDM-exposed offspring.Conclusions: Overall, our results provide little support for an association of maternal protein intake in pregnancy with measures of offspring metabolic health. Further studies in larger cohorts are needed to determine whether low maternal protein intake in pregnancy may improve glucose homeostasis in GDM-exposed and male offspring.Danish Diabetes Academy Danish Council for Strategic Research Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development, NIH Novo Nordisk Foundatio

Maternal glycemic index and glycemic load in pregnancy and offspring metabolic health in childhood and adolescence-a cohort study of 68,471 mother-offspring dyads from the Danish National Birth Cohort.

To access publisher's full text version of this article click on the hyperlink belowBACKGROUND: High glycemic index (GI) and glycemic load (GL) as indicators of carbohydrate quality and quantity have been found to increase risk of metabolic outcomes in adults. Whether carbohydrate quality may influence metabolic programming already in early life is unknown. We examined the association of maternal GI and GL with offspring body mass index (BMI) in the first 7 years of life among 68,471 mother-offspring dyads from the Danish National Birth Cohort (DNBC). In a sub-cohort of offspring with clinical data (n = 1234) that included 608 dyads exposed to gestational diabetes mellitus (GDM), we also examined the relation to metabolic health at 9-16 years. METHODS: Maternal GI and GL were quantified using a mid-pregnancy food frequency questionnaire. We used birth weight and length to calculate offspring's ponderal index. Age- and sex-specific BMI z scores at 5 mo, 12 mo, and 7 y were standardized against WHO reference data. In the clinical cohort, we quantified body composition, HOMA-IR, and HOMA-B. We used multivariable mixed linear and Poisson regression to model the associations. RESULTS: Median (IQR) of GI and GL were 83 (63-111) and 241 (180-333) g/day, respectively. We found that GI (Q4 vs. Q1:1.09, 95%CI: 1.03, 1.15) and GL (Q4 vs. Q1:1.10, 95%CI: 1.05, 1.16) modestly increased the relative risk of large-for gestational age (LGA). In the clinical sub-cohort, we observed a potential increase in offspring HOMA-IR, adiposity, and metabolic syndrome z score with higher maternal GI and GI. These associations were stronger among the GDM-exposed offspring, but the CI included the null value. CONCLUSION: We found associations of GI and GL in pregnancy with offspring LGA. Potential long-term benefits to offspring exposed to GDM need to be confirmed in larger, well-powered studies.Danish Diabetes Academy - Novo Nordisk Foundation Danish Council for Strategic Research Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health Innovation Fund Denmark Rigshospitalet, Copenhagen University Hospita

Identification of pathogenic GCK variants in patients with common type 2 diabetes can lead to discontinuation of pharmacological treatment

Background: Functionally disruptive variants in the glucokinase gene (GCK) cause a form of mild non-progressive hyperglycemia, which does not require pharmacological treatment. A substantial proportion of patients with type 2 diabetes (T2D) carry GCK variants. We aimed to investigate whether carriers of rare GCK variants diagnosed with T2D have a glycemic phenotype and treatment response consistent with GCK-diabetes. Methods: Eight patients diagnosed with T2D from the Danish DD2 cohort who had previously undergone sequencing of GCK participated. Clinical examinations at baseline included an oral glucose tolerance test and continuous glucose monitoring. Carriers with a glycemic phenotype consistent with GCK-diabetes took part in a three-month treatment withdrawal. Results: Carriers of pathogenic and likely pathogenic variants had lower median fasting glucose and C-peptide levels compared to carriers of variants of uncertain significance and benign variants (median fasting glucose: 7.3 (interquartile range: 0.4) mmol/l vs. 9.5 (1.6) mmol/l, p = 0.04; median fasting C-peptide 902 (85) pmol/l vs. 1535 (295) pmol/l, p = 0.03). Four participants who discontinued metformin treatment and one diet-treated participant were reevaluated after three months. There was no deterioration of HbA1c or fasting glucose (median baseline HbA1c: 49 (3) vs. 51 (6) mmol/mol after three months, p = 0.4; median baseline fasting glucose: 7.3 (0.4) mmol/l vs. 7.0 (0.6) mmol/l after three months, p = 0.5). Participants did not consistently fulfill best practice guidelines for GCK screening nor clinical criteria for monogenic diabetes. Discussion: Carriers of pathogenic or likely pathogenic GCK variants identified by unselected screening in T2D should be reported, as they have a glycemic phenotype and treatment response consistent with GCK-diabetes. Variants of uncertain significance should be interpreted with care. Systematic genetic screening of patients with common T2D receiving routine care can lead to the identification and precise care of patients with misclassified GCK-diabetes who are not identifiable through common genetic screening criteria

Precision subclassification of type 2 diabetes: a systematic review.

BACKGROUND: Heterogeneity in type 2 diabetes presentation and progression suggests that precision medicine interventions could improve clinical outcomes. We undertook a systematic review to determine whether strategies to subclassify type 2 diabetes were associated with high quality evidence, reproducible results and improved outcomes for patients. METHODS: We searched PubMed and Embase for publications that used 'simple subclassification' approaches using simple categorisation of clinical characteristics, or 'complex subclassification' approaches which used machine learning or 'omics approaches in people with established type 2 diabetes. We excluded other diabetes subtypes and those predicting incident type 2 diabetes. We assessed quality, reproducibility and clinical relevance of extracted full-text articles and qualitatively synthesised a summary of subclassification approaches. RESULTS: Here we show data from 51 studies that demonstrate many simple stratification approaches, but none have been replicated and many are not associated with meaningful clinical outcomes. Complex stratification was reviewed in 62 studies and produced reproducible subtypes of type 2 diabetes that are associated with outcomes. Both approaches require a higher grade of evidence but support the premise that type 2 diabetes can be subclassified into clinically meaningful subtypes. CONCLUSION: Critical next steps toward clinical implementation are to test whether subtypes exist in more diverse ancestries and whether tailoring interventions to subtypes will improve outcomes