Lipoprotein lipase activity and mass, apolipoprotein C-II mass and polymorphisms of apolipoproteins E and A5 in subjects with prior acute hypertriglyceridaemic pancreatitis

BACKGROUND Severe hypertriglyceridaemia due to chylomicronemia may trigger an acute pancreatitis. However, the basic underlying mechanism is usually not well understood. We decided to analyze some proteins involved in the catabolism of triglyceride-rich lipoproteins in patients with severe hypertriglyceridaemia. METHODS Twenty-four survivors of acute hypertriglyceridaemic pancreatitis (cases) and 31 patients with severe hypertriglyceridaemia (controls) were included. Clinical and anthropometrical data, chylomicronaemia, lipoprotein profile, postheparin lipoprotein lipase mass and activity, hepatic lipase activity, apolipoprotein C II and CIII mass, apo E and A5 polymorphisms were assessed. RESULTS Only five cases were found to have LPL mass and activity deficiency, all of them thin and having the first episode in childhood. No cases had apolipoprotein CII deficiency. No significant differences were found between the non-deficient LPL cases and the controls in terms of obesity, diabetes, alcohol consumption, drug therapy, gender distribution, evidence of fasting chylomicronaemia, lipid levels, LPL activity and mass, hepatic lipase activity, CII and CIII mass or apo E polymorphisms. However, the SNP S19W of apo A5 tended to be more prevalent in cases than controls (40% vs. 23%, NS). CONCLUSION Primary defects in LPL and C-II are rare in survivors of acute hypertriglyceridaemic pancreatitis; lipase activity measurements should be restricted to those having their first episode during childhood.

Development and validation of a risk score predicting substantial weight gain over 5 years in middle-aged European men and women.

BACKGROUND Identifying individuals at high risk of excess weight gain may help targeting prevention efforts at those at risk of various metabolic diseases associated with weight gain. Our aim was to develop a risk score to identify these individuals and validate it in an external population. METHODS We used lifestyle and nutritional data from 53°758 individuals followed for a median of 5.4 years from six centers of the European Prospective Investigation into Cancer and Nutrition (EPIC) to develop a risk score to predict substantial weight gain (SWG) for the next 5 years (derivation sample). Assuming linear weight gain, SWG was defined as gaining ≥ 10% of baseline weight during follow-up. Proportional hazards models were used to identify significant predictors of SWG separately by EPIC center. Regression coefficients of predictors were pooled using random-effects meta-analysis. Pooled coefficients were used to assign weights to each predictor. The risk score was calculated as a linear combination of the predictors. External validity of the score was evaluated in nine other centers of the EPIC study (validation sample). RESULTS Our final model included age, sex, baseline weight, level of education, baseline smoking, sports activity, alcohol use, and intake of six food groups. The model's discriminatory ability measured by the area under a receiver operating characteristic curve was 0.64 (95% CI = 0.63-0.65) in the derivation sample and 0.57 (95% CI = 0.56-0.58) in the validation sample, with variation between centers. Positive and negative predictive values for the optimal cut-off value of ≥ 200 points were 9% and 96%, respectively. CONCLUSION The present risk score confidently excluded a large proportion of individuals from being at any appreciable risk to develop SWG within the next 5 years. Future studies, however, may attempt to further refine the positive prediction of the score.

Structural and functional brain changes in middle-aged type 2 diabetic patients: a cross-sectional study.

BACKGROUND Type 2 diabetes mellitus (T2DM) is an emerging risk factor for cognitive impairment. Whether this impairment is a direct effect of this metabolic disorder on brain function, a consequence of vascular disease, or both, remains unknown. Structural and functional neuroimaging studies in patients with T2DM could help to elucidate this question. OBJECTIVE We designed a cross-sectional study comparing 25 T2DM patients with 25 age- and gender-matched healthy control participants. Clinical information, APOE genotype, lipid and glucose analysis, structural cerebral magnetic resonance imaging including voxel-based morphometry, and F-18 fluorodeoxyglucose positron emission tomography were obtained in all subjects. METHODS Gray matter densities and metabolic differences between groups were analyzed using statistical parametric mapping. In addition to comparing the neuroimaging profiles of both groups, we correlated neuroimaging findings with HbA1c levels, duration of T2DM, and insulin resistance measurement (HOMA-IR) in the diabetic patients group. Results: Patients with T2DM presented reduced gray matter densities and reduced cerebral glucose metabolism in several fronto-temporal brain regions after controlling for various vascular risk factors. Furthermore, within the T2DM group, longer disease duration, and higher HbA1c levels and HOMA-IR were associated with lower gray matter density and reduced cerebral glucose metabolism in fronto-temporal regions. CONCLUSION In agreement with previous reports, our findings indicate that T2DM leads to structural and metabolic abnormalities in fronto-temporal areas. Furthermore, they suggest that these abnormalities are not entirely explained by the role of T2DM as a cardiovascular risk factor.