Clustering of risk behaviours and associations between risk behaviours and cardio-metabolic risk factors in adult individuals with type 1 diabetes.

AIMS: To assess clustering of risk behaviours and their health determinants. METHODS: Cross-sectional health behaviour and health data were collected from individuals with type 1 diabetes, in the FinnDiane Study. Clustering of risk behaviours was assessed and associations between behaviours and health variables were investigated. RESULTS: Data were available from 956 participants (40 % men, mean age 46 years). Altogether, 4.3 % individuals reported no risk behaviours, while 25.7 %, 37.4 %, 24.7 %, 6.8 %, and 1.0 % reported 1, 2, 3, 4, and 5 risk behaviours, respectively. Reporting ≥4 risk behaviours occurred more frequently than expected by chance. Dietary non-adherence was most frequently reported (84.4 %), followed by low LTPA (54.4 %), poor sleep (41.9 %), high alcohol consumption (15.2 %), and smoking (11.2 %). Adjusted for confounders, relative to ≤1 risk behaviour, reporting ≥2 risk behaviours was associated with higher BMI, waist circumference, and diastolic blood pressure. Having ≥3 risk behaviours was associated with larger waist-hip ratio, and higher HbA1c and triglyceride concentration; ≥4 risk behaviours was associated with higher cholesterol concentration. Of the health behaviours, low LTPA had the highest number of deleterious health associations. CONCLUSIONS: Accumulation of risk behaviors increases negative health outcomes. Exhibiting ≥2 risk behaviours or low LTPA was associated with multiple adverse outcomes.

Computational modelling of self-reported dietary carbohydrate intake on glucose concentrations in patients undergoing Roux-en-Y gastric bypass versus one-anastomosis gastric bypass.

OBJECTIVES: Our aim was to investigate in a real-life setting the use of machine learning for modelling the postprandial glucose concentrations in morbidly obese patients undergoing Roux-en-Y gastric bypass (RYGB) or one-anastomosis gastric bypass (OAGB). METHODS: As part of the prospective randomized open-label trial (RYSA), data from obese (BMI ≥35 kg/m2) non-diabetic adult participants were included. Glucose concentrations, measured with FreeStyle Libre, were recorded over 14 preoperative and 14 postoperative days. During these periods, 3-day food intake was self-reported. A machine learning model was applied to estimate glycaemic responses to the reported carbohydrate intakes before and after the bariatric surgeries. RESULTS: Altogether, 10 participants underwent RYGB and 7 participants OAGB surgeries. The glucose concentrations and carbohydrate intakes were reduced postoperatively in both groups. The relative time spent in hypoglycaemia increased regardless of the operation (RYGB, from 9.2 to 28.2%; OAGB, from 1.8 to 37.7%). Postoperatively, we observed an increase in the height of the fitted response curve and a reduction in its width, suggesting that the same amount of carbohydrates caused a larger increase in the postprandial glucose response and that the clearance of the meal-derived blood glucose was faster, with no clinically meaningful differences between the surgeries. CONCLUSIONS: A detailed analysis of the glycaemic responses using food diaries has previously been difficult because of the noisy meal data. The utilized machine learning model resolved this by modelling the uncertainty in meal times. Such an approach is likely also applicable in other applications involving dietary data. A marked reduction in overall glycaemia, increase in postprandial glucose response, and rapid glucose clearance from the circulation immediately after surgery are evident after both RYGB and OAGB. Whether nondiabetic individuals would benefit from monitoring the post-surgery hypoglycaemias and the potential to prevent them by dietary means should be investigated.KEY MESSAGESThe use of a novel machine learning model was applicable for combining patient-reported data and time-series data in this clinical study.Marked increase in postprandial glucose concentrations and rapid glucose clearance were observed after both Roux-en-Y gastric bypass and one-anastomosis gastric bypass surgeries.Whether nondiabetic individuals would benefit from monitoring the post-surgery hypoglycaemias and the potential to prevent them by dietary means should be investigated.

High-fat meals induce systemic cytokine release without evidence of endotoxemia-mediated cytokine production from circulating monocytes or myeloid dendritic cells.

AIMS: Dietary fats have been shown to promote the translocation of bacterial endotoxins from the gut into circulation, which may induce systemic inflammation and modulate the inflammatory response of circulating immune cells. The aim of this study was to determine the effect of the postprandial milieu on inflammation and the inflammatory response of antigen presenting cells in the context of type 1 diabetes (T1D). MATERIALS AND METHODS: Eleven patients with T1D and eleven nondiabetic controls were recruited as part of the FinnDiane study and given two fatty meals during 1 day. Cytokine responses in monocytes and myeloid dendritic cells (mDCs) as well as serum lipopolysaccharide activity levels, triglyceride concentrations and cytokine concentrations were measured from fasting and postprandial blood samples. RESULTS: Postprandially, patients with T1D and controls showed significant increases in eight inflammatory cytokines (IL-6, TNF-α, IL-1ß, IFN-α, IL-10, IFN-γ, IL-12 and MIP-1ß) without concomitant increase in serum LPS activity. Serum cytokine production was similar in both groups. No postprandial change was seen in the IL-6, TNF-α or IL-1ß production of mDCs or monocytes. At fasting, diabetic mDCs exhibited higher LPS-induced IL-6 and IL-1ß production than controls. CONCLUSIONS: Acute high-fat meals increase circulating cytokines but have no effect on serum lipopolysaccharide activity levels or cytokine production in circulating mDCs or monocytes. Our results suggest that postprandial increase in serum cytokine levels is neither mediated by circulating endotoxins nor the activation of circulating innate cells. The production of high-fat meal-induced inflammatory markers is most likely regulated at the tissue level.

Sense of coherence, food selection and leisure time physical activity in type 1 diabetes.

BACKGROUND: Successful management of type 1 diabetes depends on the self-care practices. Sense of coherence has been associated with various measures of lifestyle choices. We aimed to study the associations between sense of coherence and self-care practices in patients with type 1 diabetes. We hypothesized that patients with weak sense of coherence have less prudent food choices and lower physical activity. METHODS: Cross-sectional data from 1104 patients (44% men, mean age 45±12 years) from the FinnDiane Study were available. Sense of coherence, dietary intake, and leisure time physical activity were evaluated using self-reported questionnaires. Diet score was calculated based on the degree to which food choices complied with dietary guidelines. Weekly metabolic equivalent hours were calculated by multiplying the activity duration by the activity- and intensity-specific metabolic equivalent. RESULTS: The sense of coherence score correlated positively both with the diet score and the weekly metabolic equivalent hours. Those in the lowest sense of coherence tertile had both the lowest diet scores and the lowest weekly metabolic equivalent hours values. Among women, the sense of coherence score was associated with the diet score when adjusted for age, socioeconomic status, received dietary guidance, and nephropathy status. The sense of coherence score independently predicted the metabolic equivalent hours value in men. CONCLUSIONS: A higher sense of coherence score predicted more prudent food choices in women and higher physical activity in men. In the future, the health consequences associated with a weak sense of coherence should be studied prospectively. Also, the possibility to use the sense of coherence questionnaire as a screening instrument to identify patients who could benefit from intensified counseling should be investigated.

New susceptibility loci associated with kidney disease in type 1 diabetes.

Diabetic kidney disease, or diabetic nephropathy (DN), is a major complication of diabetes and the leading cause of end-stage renal disease (ESRD) that requires dialysis treatment or kidney transplantation. In addition to the decrease in the quality of life, DN accounts for a large proportion of the excess mortality associated with type 1 diabetes (T1D). Whereas the degree of glycemia plays a pivotal role in DN, a subset of individuals with poorly controlled T1D do not develop DN. Furthermore, strong familial aggregation supports genetic susceptibility to DN. However, the genes and the molecular mechanisms behind the disease remain poorly understood, and current therapeutic strategies rarely result in reversal of DN. In the GEnetics of Nephropathy: an International Effort (GENIE) consortium, we have undertaken a meta-analysis of genome-wide association studies (GWAS) of T1D DN comprising ~2.4 million single nucleotide polymorphisms (SNPs) imputed in 6,691 individuals. After additional genotyping of 41 top ranked SNPs representing 24 independent signals in 5,873 individuals, combined meta-analysis revealed association of two SNPs with ESRD: rs7583877 in the AFF3 gene (P = 1.2 × 10(-8)) and an intergenic SNP on chromosome 15q26 between the genes RGMA and MCTP2, rs12437854 (P = 2.0 × 10(-9)). Functional data suggest that AFF3 influences renal tubule fibrosis via the transforming growth factor-beta (TGF-ß1) pathway. The strongest association with DN as a primary phenotype was seen for an intronic SNP in the ERBB4 gene (rs7588550, P = 2.1 × 10(-7)), a gene with type 2 diabetes DN differential expression and in the same intron as a variant with cis-eQTL expression of ERBB4. All these detected associations represent new signals in the pathogenesis of DN.

Depression is associated with the metabolic syndrome among patients with type 1 diabetes.

BACKGROUND: Both depression and the metabolic syndrome are frequently found among patients with type 1 diabetes, but their potential association has not yet been investigated. In this paper the relationship between depression and the metabolic syndrome among patients with type 1 diabetes was evaluated. METHODS: A total of 1226 patients participating in the Finnish Diabetic Nephropathy Study between 2003 and 2009 were included. Depression was defined as use of antidepressive medication or Beck Depression Inventory (BDI) score ≥16. The metabolic syndrome was defined using the criteria established by the International Diabetes Federation Task Force on Epidemiology and Prevention (IDF); National Heart, Lung, and Blood Institute (NHLBI); American Heart Association (AHA); World Heart Federation (WHF); International Atherosclerosis Society (IAS); and International Association for the Study of Obesity (IASO). RESULTS: The metabolic syndrome was more frequently observed among depressed patients (57% versus 46%, P = 0.008). Of the individual components of the metabolic syndrome, waist, triglyceride, and HDL components were more frequently fulfilled among patients with depression. The BDI score increased with the number of components of the metabolic syndrome present. The BDI score was independently associated with the waist component (odds ratio 1.03, 95% confidence interval 1.01-1.05) when adjusted for gender, age, socio-economic status, smoking, nephropathy, and HbA(1c). CONCLUSION: The metabolic syndrome is frequently found among depressed patients with type 1 diabetes. Whether this association influences the development of diabetic complications is not known.