Metabolome-defined obesity and the risk of future diabetes and mortality

Background Obesity is a key risk factor for type 2 diabetes, however, up to 20% of patients are normal weight. Our aim was to identify metabolite patterns reproducibly predictive of BMI, and subsequently to test if lean individuals who carry an obese metabolome are at hidden high risk of obesity related diseases, such as diabetes. Methods We measured 109 metabolites in fasted plasma samples of 7663 individuals from two Swedish and one Italian population-based cohort. Ridge regression models were used to predict BMI using the plasma metabolites. Individuals with a predicted BMI either more than 5 kg/m2 higher (overestimated) or lower (underestimated) than their actual BMI were characterized as outliers and further investigated for obesity related risk factors and future risk of diabetes and mortality. Results The plasma metabolome could predict BMI in all cohorts (r2 = 0.48, 0.26 and 0.19). The overestimated group had a BMI similar to individuals correctly predicted as normal weight, similar waist circumference, were not more likely to change weight over time but had a 2 times higher risk of future diabetes and an 80 % increased risk of all-cause mortality. These associations remained after adjustments for obesity-related risk factors and lifestyle parameters. Conclusions We found that lean individuals with an obese metabolome, have an increased risk for diabetes and all-cause mortality compared to lean individuals with a healthy metabolome. Metabolomics may be used to identify hidden high-risk individuals, in order to initiate lifestyle and pharmacological interventions.

Postpartum dietary and physical activity-related beliefs and behaviors among women with recent gestational diabetes mellitus: a qualitative study from Singapore

Background A woman with a history of GDM has at least seven-fold increased lifetime risk of developing type 2 diabetes mellitus (T2DM), compared to women who have normoglycemic pregnancies. Postpartum lifestyle modification has been shown to reduce postpartum weight retention and prevent the progression to T2DM. The aim of this study was to explore the postpartum dietary and physical activity-related beliefs and behaviors among women in Singapore who had GDM in their most recent pregnancies. Methods Semi-structured in-depth interviews were conducted with 14 women, who were up to four months postpartum and had GDM in their most recent pregnancies. Interview data were analyzed using thematic analysis. Results Three themes were identified in the analysis: (1) risk perception and knowledge regarding future diabetes, (2) suboptimal diet and physical activity after delivery and (3) factors influencing the postpartum lifestyle. Conclusions The study findings provided useful information on the postpartum lifestyle beliefs and behaviors among women with a history of GDM. Most participants had low risk perception of future diabetes and their diet and physical activity after delivery were suboptimal due to various influences. These insights can be used to design tailored materials and programs to support women who have had GDM reduce their risk of developing future T2DM.

Understanding Gestational Diabetes, Future Diabetes Risk, and Diabetes Prevention: A Qualitative Study of Patient, Provider and Staff Perspectives

Gestational diabetes mellitus (GDM) increases type 2 diabetes risk; however, postpartum diabetes screening rates are low. Using semi-structured interviews and focus groups, this study investigates the understanding of GDM and its relationship to future diabetes risk and diabetes prevention among patients with public or no insurance (<i>n </i>= 36), health care providers (<i>n </i>= 21), and clinic staff (<i>n </i>= 9) from Federally Qualified Health Centers. Five main themes emerged: <i>1</i>) general understanding of GDM diagnosis with focus on neonatal complications; <i>2</i>) variable recall of diet, exercise, and weight recommendations; <i>3</i>) overwhelming medication and self-monitoring routines; <i>4</i>) short-term focus of type 2 diabetes risk and screening; and <i>5</i>) limited understanding of all options for diabetes prevention. The results may inform diabetes screening and prevention interventions in primary care settings.

Understanding Gestational Diabetes, Future Diabetes Risk, and Diabetes Prevention: A Qualitative Study of Patient, Provider and Staff Perspectives

Gestational diabetes mellitus (GDM) increases type 2 diabetes risk; however, postpartum diabetes screening rates are low. Using semi-structured interviews and focus groups, this study investigates the understanding of GDM and its relationship to future diabetes risk and diabetes prevention among patients with public or no insurance (<i>n </i>= 36), health care providers (<i>n </i>= 21), and clinic staff (<i>n </i>= 9) from Federally Qualified Health Centers. Five main themes emerged: <i>1</i>) general understanding of GDM diagnosis with focus on neonatal complications; <i>2</i>) variable recall of diet, exercise, and weight recommendations; <i>3</i>) overwhelming medication and self-monitoring routines; <i>4</i>) short-term focus of type 2 diabetes risk and screening; and <i>5</i>) limited understanding of all options for diabetes prevention. The results may inform diabetes screening and prevention interventions in primary care settings.

Novel HumanMethylatyion450 Analyses Reveal DNA Methylation Predictors of Future Diabetes Onset in Women With Polycystic Ovarian Syndrome

Aims. Polycystic ovarian syndrome (PCOS) is a common endocrine disorder characterised by ovarian morphological, systemic biochemical, and menstrual changes. Women with PCOS are at significantly increased risk of raised fasting glucose, impaired glucose tolerance, and diabetes. Recognition of these complications and early intervention are key to good health outcomes. We sought to identify DNA methylation patterns that may predict future diabetes onset in this high-risk PCOS population. Patients and Methods. Peripheral blood samples from women with PCOS and women with PCOS who later developed diabetes, were analysed by Illumina HumanMethylation450 BeadChip-arrays. Bisulphite-Pyrosequencing™ was used to validate and confirm array methylation data. Results. Array analyses identified 273 differentially methylated CpG loci (≥ 0.2 β-value change) at initial diagnosis of PCOS, between women who did or did not later develop diabetes. 19 of these sites demonstrated differential methylation in the same direction in ≥ five sample pairs. Methylation in three of the candidates (cg11897887, cg02819655, and cg25542007) showed the best concordance with corresponding array β-values, and, most clearly differentiated ‘cases’ from ‘controls’. Conclusions. We have identified novel methylation biomarkers that could predict future onset of diabetes in this high-risk population. Use of methylation analyses to identify women who are likely to develop diabetes at diagnosis of PCOS may facilitate timely lifestyle interventions to reduce future morbidity.