Familial hypertriglyceridemia: an entity with distinguishable features from other causes of hypertriglyceridemia.

BACKGROUND: Familial hypertriglyceridemia (FHTG) is a partially characterized primary dyslipidemia which is frequently confused with other forms hypertriglyceridemia. The aim of this work is to search for specific features that can help physicians recognize this disease. METHODS: This study included 84 FHTG cases, 728 subjects with common mild-to-moderate hypertriglyceridemia (CHTG) and 609 normotriglyceridemic controls. All subjects underwent genetic, clinical and biochemical assessments. A set of 53 single nucleotide polymorphisms (SNPs) previously associated with triglycerides levels, as well as 37 rare variants within the five main genes associated with hypertriglyceridemia (i.e. LPL, APOC2, APOA5, LMF1 and GPIHBP1) were analyzed. A panel of endocrine regulatory proteins associated with triglycerides homeostasis were compared between the FHTG and CHTG groups. RESULTS: Apolipoprotein B, fibroblast growth factor 21(FGF-21), angiopoietin-like proteins 3 (ANGPTL3) and apolipoprotein A-II concentrations, were independent components of a model to detect FHTG compared with CHTG (AUC 0.948, 95%CI 0.901-0.970, 98.5% sensitivity, 92.2% specificity, P < 0.001). The polygenic set of SNPs, accounted for 1.78% of the variance in triglyceride levels in FHTG and 6.73% in CHTG. CONCLUSIONS: The clinical and genetic differences observed between FHTG and CHTG supports the notion that FHTG is a unique entity, distinguishable from other causes of hypertriglyceridemia by the higher concentrations of insulin, FGF-21, ANGPTL3, apo A-II and lower levels of apo B. We propose the inclusion of these parameters as useful markers for differentiating FHTG from other causes of hypertriglyceridemia.

Adaptation of the medical-nutrition therapy for patients with intestinal failure in a developing country: A modified Delphi survey.

BACKGROUND & AIMS: Intestinal Failure (IF) is a complex disease with huge impacts on our society due to complications. Therefore, in a developing country like Mexico without specialized IF clinics, health care professionals must provide evidence-based interventions for the IF patient. This study aims to achieve consensus on how to adapt the existing guidelines for IF to the local practices considering the available resources and local practices. METHODS: A three-round modified Delphi process was used to build consensus on the most important interventions for our IF patients. For each round, data was collected and consensus was defined as ≥80% of agreement for each item. Descriptive statistics were used to determine whether a consensus was achieved. RESULTS: Ten content experts completed the three-round modified Delphi survey. Consensus was achieved for 98% of the items related to the hospitalized patient, ambulatory care management, and drug therapy. Some of these items are not included in the ESPEN guidelines for IF, but we considered that they are relevant in our clinical practice, like the calculation of fluids for patients with very low body weight, screening for refeeding syndrome and the use of some conventional drugs to promote intestinal rehabilitation. CONCLUSIONS: Using a three-round modified Delphi process, consensus was achieved for nearly all items. This represents a starting point for the improvement of our local practices towards this complex disease, leading to better outcomes and the implementation of evidence-based protocolized interventions which can have an important impact due to the lack of access to some of the most novel pharmacological therapies like the glucagon-like-peptide (GLP-2) analog.

Short article: Frequency, pathophysiology, and clinical classification of intestinal failure type II and III at a tertiary referral center.

OBJECTIVE: Intestinal failure (IF) is a complex disease that is gaining significance and attention throughout the world. In Mexico, there are no available data on this condition. The aim of this study was to determine the frequency and characteristics of patients with IF type II and III hospitalized at a tertiary referral center in our country. PATIENTS AND METHODS: A cross-sectional study was carried out from August 2016 to July 2017. Adult patients hospitalized in noncritical areas with a recent diagnosis of IF type II or III according to the European Society for Clinical Nutrition and Metabolism classification were included. Demographic, anthropometric, nutritional therapy, biochemical, and clinical characteristics were registered. Nutritional risk was determined by the Nutritional Risk Score 2002. RESULTS: During the study, 4144 patients were admitted to noncritical areas; 21 (5/1000) of these patients were included. The mean age of the patients was 51±18.8 years, and the mean BMI was 17.6±5.5 kg/m. Fifteen (71.5%) patients were diagnosed with IF type II and six (28.5%) with IF type III. The primary diagnosis was surgical complications in seven (33.3%) of the cases and the principal pathophysiological mechanism was short bowel syndrome in nine (42.8%) patients. The most frequent (37%) clinical classification was D2: more than 20 kcal/kg/day and 1001-2000 ml/day and parenteral nutrition and PN2: 1001-2000 ml/day (52.3%) based on the modified European Society for Clinical Nutrition and Metabolism clinical classification. CONCLUSION: In this study, a high frequency of IF was found; surgical complications and short bowel syndrome were the main mechanisms involved, and D2 was the most frequent clinical category.

Optimization of kidney dysfunction prediction in diabetic kidney disease using targeted metabolomics.

AIMS: Metabolomics have been used to evaluate the role of small molecules in human disease. However, the cost and complexity of the methodology and interpretation of findings have limited the transference of knowledge to clinical practice. Here, we apply a targeted metabolomics approach using samples blotted in filter paper to develop clinical-metabolomics models to detect kidney dysfunction in diabetic kidney disease (DKD). METHODS: We included healthy controls and subjects with type 2 diabetes (T2D) with and without DKD and investigated the association between metabolite concentrations in blood and urine with eGFR and albuminuria. We also evaluated performance of clinical, biochemical and metabolomic models to improve kidney dysfunction prediction in DKD. RESULTS: Using clinical-metabolomics models, we identified associations of decreased eGFR with body mass index (BMI), uric acid and C10:2 levels; albuminuria was associated to years of T2D duration, A1C, uric acid, creatinine, protein intake and serum C0, C10:2 and urinary C12:1 levels. DKD was associated with age, A1C, uric acid, BMI, serum C0, C10:2, C8:1 and urinary C12:1. Inclusion of metabolomics increased the predictive and informative capacity of models composed of clinical variables by decreasing Akaike's information criterion, and was replicated both in training and validation datasets. CONCLUSIONS: Targeted metabolomics using blotted samples in filter paper is a simple, low-cost approach to identify outcomes associated with DKD; the inclusion of metabolomics improves predictive capacity of clinical models to identify kidney dysfunction and DKD-related outcomes.