Optimization of nutritional strategies using a mechanistic computational model in prediabetes: Application to the J-DOIT1 study data.

Lifestyle interventions have been shown to prevent or delay the onset of diabetes; however, inter-individual variability in responses to such interventions makes lifestyle recommendations challenging. We analyzed the Japan Diabetes Outcome Intervention Trial-1 (J-DOIT1) study data using a previously published mechanistic simulation model of type 2 diabetes onset and progression to understand the causes of inter-individual variability and to optimize dietary intervention strategies at an individual level. J-DOIT1, a large-scale lifestyle intervention study, involved 2607 subjects with a 4.2-year median follow-up period. We selected 112 individuals from the J-DOIT1 study and calibrated the mechanistic model to each participant's body weight and HbA1c time courses. We evaluated the relationship of physiological (e.g., insulin sensitivity) and lifestyle (e.g., dietary intake) parameters with variability in outcome. Finally, we used simulation analyses to predict individually optimized diets for weight reduction. The model predicted individual body weight and HbA1c time courses with a mean (±SD) prediction error of 1.0 kg (±1.2) and 0.14% (±0.18), respectively. Individuals with the most and least improved biomarkers showed no significant differences in model-estimated energy balance. A wide range of weight changes was observed for similar model-estimated caloric changes, indicating that caloric balance alone may not be a good predictor of body weight. The model suggests that a set of optimal diets exists to achieve a defined weight reduction, and this set of diets is unique to each individual. Our diabetes model can simulate changes in body weight and glycemic control as a result of lifestyle interventions. Moreover, this model could help dieticians and physicians to optimize personalized nutritional strategies according to their patients' goals.

Autosomal dominant inheritance of a predisposition to thoracic aortic aneurysms and dissections and intracranial saccular aneurysms.

A genetic predisposition for thoracic aortic aneurysms and dissections (TAAD) can be inherited in an autosomal dominant manner with decreased penetrance and variable expression. Four genes identified to date for familial TAAD account for approximately 20% of the heritable predisposition. In a cohort of 514 families with two or more members with presumed autosomal dominant TAAD, 48 (9.3%) families have one or more members who were at 50% risk to inherit the presumptive gene causing TAAD had an intracranial vascular event. In these families, gender is significantly associated with disease presentation (P < 0.001), with intracranial events being more common in women (65.4%) while TAAD events occurred more in men (64.2%,). Twenty-nine of these families had intracranial aneurysms (ICA) that could not be designated as saccular or fusiform due to incomplete data. TGFBR1, TGFBR2, and ACTA2 mutations were found in 4 families with TAAD and predominantly fusiform ICAs. In 15 families, of which 14 tested negative for 3 known TAAD genes, 17 family members who were at risk for inheriting TAAD had saccular ICAs. In 2 families, women who harbored the genetic mutation causing TAAD had ICAs. In 2 additional families, intracranial, thoracic and abdominal aortic aneurysms were observed. This study documents the autosomal dominant inheritance of TAADs with saccular ICAs, a previously recognized association that has not been adequately characterized as heritable. In these families, routine cerebral and aortic imaging for at risk members could prevent cerebral hemorrhages and aortic dissections.

Familial thoracic aortic aneurysms and dissections: three families with early-onset ascending and descending aortic dissections in women.

Ascending thoracic aortic aneurysms leading to type A dissections can be inherited in an autosomal dominant manner with variable age of onset and decreased penetrance, primarily in women. Three families are described with autosomal dominant inheritance of either ascending aortic aneurysms leading to type A dissections or type B dissections, and a young age of onset of aortic dissections in both men and women. Pedigree analysis suggests that a de novo mutation is responsible for the disease in one family. The discordant age of onset of aortic disease in a monozygotic twin pair in a different family indicates that environmental or stochastic factors may influence the variable expression of disease. Genetic analysis of one family excluded linkage to known loci for TAAD (TAAD1, TAAD2, FAA1, or FBN1) and sequence analysis failed to identify mutations in TGFBR2, the gene encoding transforming growth factor beta receptor type II. Thus, a novel unidentified loci may be responsible for the phenotype in these three families.