Fatty liver index associates with relative sarcopenia and GH/ IGF- 1 status in obese subjects

Recently the association between hepatic steatosis and sarcopenia has been described. GH/IGF-1 axis has been postulated to play a role in linking fatty liver and low muscle mass. The aim of our study was to explore the association between fatty liver index, sarcopenic obesity, insulin sensitivity, and GH/IGF-1 status

Sirtuins 1–7 expression in human adipose-derived stem cells from subcutaneous and visceral fat depots: influence of obesity and hypoxia

The sirtuin family comprises seven NAD+-dependent deacetylases which control the overall health of organisms through the regulation of pleiotropic metabolic pathways. Sirtuins are important modulators of adipose tissue metabolism and their expression is higher in lean than obese subjects. At present, the role of sirtuins in adipose-derived stem cells has not been investigated yet. Therefore, in this study, we evaluated the expression of the complete panel of sirtuins in adipose-derived stem cells isolated from both subcutaneous and visceral fat of non-obese and obese subjects. We aimed at investigating the influence of obesity on sirtuins' levels, their role in obesity-associated inflammation, and the relationship with the peroxisome proliferator-activated receptor delta, which also plays functions in adipose tissue metabolism. The mRNA levels in the four types of adipose-derived stem cells were evaluated by quantitative polymerase chain reaction, in untreated cells and also after 8 h of hypoxia exposure. Correlations among sirtuins' expression and clinical and molecular parameters were also analyzed. We found that sirtuin1-6 exhibited significant higher mRNA expression in visceral adipose-derived stem cells compared to subcutaneous adipose-derived stem cells of non-obese subjects. Sirtuin1-6 levels were markedly reduced in visceral adipose-derived stem cells of obese patients. Sirtuins' expression in visceral adipose-derived stem cells correlated negatively with body mass index and C-reactive protein and positively with peroxisome proliferator-activated receptor delta. Finally, only in the visceral adipose-derived stem cells of obese patients hypoxia-induced mRNA expression of all of the sirtuins. Our results highlight that sirtuins' levels in adipose-derived stem cells are consistent with protective effects against visceral obesity and inflammation, and suggest a transcriptional mechanism through which acute hypoxia up-regulates sirtuins in the visceral adipose-derived stem cells of obese patients

The European network staff eXchange for integrAting precision health in the health Care sysTems (ExACT): a Marie Curie Research and Innovation Staff Exchange (RISE) project

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Disability, Physical Inactivity, and Impaired Health-Related Quality of Life Are Not Different in Metabolically Healthy vs. Unhealthy Obese Subjects

BACKGROUND: Obesity represents a major health hazard, affecting morbidity, psychological status, physical functionality, quality of life, and mortality. The aim of the present study was to explore the differences between metabolically healthy (MHO) and metabolically unhealthy (MUO) obese subjects with regard to physical activity, disability, and health-related quality of life (HR-QoL). METHODS: All subjects underwent a multidimensional evaluation, encompassing the assessment of body composition, metabolic biomarkers and inflammation, physical activity level (IPAQ questionnaire), disability (TSD-OC test), and HR-QoL (SF-36 questionnaire). MHO and MUO were defined based on the absence or the presence of the metabolic syndrome, respectively. RESULTS: 253 subjects were included (54 men and 199 women; age: 51.7 ± 12.8 vs. 50.3 ± 11.7 years, p = 0.46; BMI: 38.1 ± 5.7 vs. 38.9 ± 6.7 kg/m², p = 0.37). No significant difference was observed in body composition. There was no difference between MHO and MUO considering inflammation (hs-CRP: 6517.1 ± 11,409.9 vs. 5294.1 ± 5612.2 g/L; p = 0.37), physical inactivity (IPAQ score below 3000 METs-min/week in 77.6% of MHO vs. 80% of MUO subjects; p = 0.36), obesity-related disability (TSD-OC score > 33%, indicating a high level of obesity-related disability, in 20.2% of MHO vs. 26.5% of MUO subjects; p = 0.28), and the HR-QoL (SF-36 total score: 60 ± 20.8 vs. 62.8 ± 18.2, p = 0.27). DISCUSSION AND CONCLUSION:The metabolic comorbidity and the impairment of functional ability and psycho-social functioning may have a different timing in the natural history of obesity. Alterations in the physical activity level and mobility disabilities may precede the onset of metabolic abnormalities. (Trial registration 2369 prot 166/12-registered 23 February 2012; Amendment 223/14-registered 13 February 2014)

BINET - Analisi di dati sanitari mediante SNA Validit? degli indicatori statistici ottenuti rispetto a metodologie tradizionali

Social Network technology in the healthcare field aims to establish a non-conventional graph analysis methodology. BINET project (Business Intelligence framework based on Social Network technology) has developed an application framework to test SN methodologies on health data. Scientific validation of the methodology focuses on analyzing therapeutic, time and spatial associations among treatments, e.g. drug prescriptions and diagnosis made during hospitalization, to find correlations between treatments of individuals and patient outcome. In this report, following the testing of the BINET application framework, we compare the validity and accuracy of network statistical indicators with those obtained through traditional methods

Beneficial effects of the ketogenic diet on nonalcoholic fatty liver disease: A comprehensive review of the literature

Nonalcoholic fatty liver disease (NAFLD) is a major cause of chronic liver disease, characterized by hepatic fat accumulation and possible development of inflammation, fibrosis, and cancer. The ketogenic diet (KD), with its drastic carbohydrate reduction, is a now popular weight loss intervention, despite safety concerns on a possible association with fatty liver. However, KDs were also reported to be beneficial on hepatic pathology, with ketone bodies recently proposed as effective modulators of inflammation and fibrosis. If the beneficial impact of weight loss on NAFLD is established, less is known on the effect of macronutrient distribution on such outcome. In a hypocaloric regimen, the latter seems not to be crucial, whereas at higher calorie intake, macronutrient ratio and, theoretically, ketosis, may become important. KDs could positively impact NAFLD for their very low carbohydrate content, and whether ketosis plays an additional role is unknown. Indeed, several mechanisms may directly link ketosis and NAFLD improvement, and elucidating these aspects would pave the way for new therapeutic strategies. We herein aimed at providing an accurate revision of current literature on KDs and NAFLD, focusing on clinical evidence, metabolic pathways involved, and strict categorization of dietary interventions

The decline in muscle strength and muscle quality in relation to metabolic derangements in adult women with obesity

Background & aims: The metabolic and functional characteristics related to sarcopenic obesity have not been thoroughly explored in the earlier stages of the aging process. The aim of the present study was to examine the phenotype of sarcopenic obesity, in terms of lean body mass, muscle strength and quality, in adult women with and without the Metabolic Syndrome (MetS), and its relationship with the features of myosteatosis. Methods: Study participants were enrolled at the Sapienza University, Rome, Italy. Body composition was assessed by DXA. The Handgrip strength test (HGST) was performed. HGST was normalized to arm lean mass to indicate muscle quality; intermuscular adipose tissue (IMAT) and intramyocellular lipid content (IMCL) were measured by magnetic resonance imaging and spectroscopy, as indicators of myosteatosis. Different indices of sarcopenia were calculated, based on appendicular lean mass (ALM, kg) divided by height squared, or weight. The NCEP-ATPIII criteria were used to diagnose the MetS. HOMA-IR was calculated. The physical activity level (PAL) was assessed through the IPAQ questionnaire. Results: 54 women (age: 48 ± 14 years, BMI: 37.9 ± 5.4 kg/m 2 ) were included. 54% had the MetS (metabolically unhealthy, MUO). HGST/arm lean mass was lower in MUO women than women without the MetS (6.3 ± 1.8 vs. 7.8 ± 1.6, p = 0.03). No differences emerged in terms of absolute ALM (kg) or other indices of sarcopenia (ALM/h 2 or ALM/weight) between metabolically healthy (MHO) vs. MUO women (p > 0.05). Muscle quality was negatively associated with HOMA-IR (p = 0.02), after adjustment for age, body fat, hs-CRP levels, and PAL. IMAT, but not IMCL, was significantly higher in obese women with the MetS compared to women without the MetS (p > 0.05). No association emerged between HGST/arm lean mass and IMAT or IMCL when HOMA-IR was included in the models. Conclusion: Insulin resistance, and not sarcopenia or myosteatosis per se, was associated with muscle weakness, resulting in the phenotype of “dynapenic obesity” in middle-aged women with the metabolic syndrome

Polygenic risk prediction models for colorectal cancer: a systematic review

Background Risk prediction models incorporating single nucleotide polymorphisms (SNPs) could lead to individualized prevention of colorectal cancer (CRC). However, the added value of incorporating SNPs into models with only traditional risk factors is still not clear. Hence, our primary aim was to summarize literature on risk prediction models including genetic variants for CRC, while our secondary aim was to evaluate the improvement of discriminatory accuracy when adding SNPs to a prediction model with only traditional risk factors. Methods We conducted a systematic review on prediction models incorporating multiple SNPs for CRC risk prediction. We tested whether a significant trend in the increase of Area Under Curve (AUC) according to the number of SNPs could be observed, and estimated the correlation between AUC improvement and number of SNPs. We estimated pooled AUC improvement for SNP-enhanced models compared with non-SNP-enhanced models using random effects meta-analysis, and conducted meta-regression to investigate the association of specific factors with AUC improvement. Results We included 33 studies, 78.79% using genetic risk scores to combine genetic data. We found no significant trend in AUC improvement according to the number of SNPs (p for trend = 0.774), and no correlation between the number of SNPs and AUC improvement (p = 0.695). Pooled AUC improvement was 0.040 (95% CI: 0.035, 0.045), and the number of cases in the study and the AUC of the starting model were inversely associated with AUC improvement obtained when adding SNPs to a prediction model. In addition, models constructed in Asian individuals achieved better AUC improvement with the incorporation of SNPs compared with those developed among individuals of European ancestry. Conclusions Though not conclusive, our results provide insights on factors influencing discriminatory accuracy of SNP-enhanced models. Genetic variants might be useful to inform stratified CRC screening in the future, but further research is needed

Ontologie e modellazione di dati sanitari - Attivit? di ricerca nell\u27ambito del progetto ODINET

The Odinet project has as its primary objective to conduct research and development aimed at defining a technological framework for online access and dissemination of structured and heterogeneous data. This report carried out a survey of the main methods of modeling for the identification, cataloging and presentation of data on the Web. In particular, the purpose is to provide guidance on what specific technologies to be adopted in the field of Semantic Web and Linked Open Data, in order to be able to exploit the best information contained in the Public Administration data regarding the healthcare domain

Analisi di rete basata sul modello matematico dei grafi, sperimentazione nell\u27ambito del progetto BINET

The research activity carried out in BINET project aims at designing a Business Intelligence framework based on Social Network technology, better known as Complex Networks in the healthcare field, in order to establish a platform to analyze data through non-conventional graph methodologies and interfaces (graph data-browsing). Scientific validation of methodologies used by the framework is carried out in the healthcare field and focuses on the analysis of therapeutic, time and spatial associations among the various treatments, such as outpatient, drug prescriptions, length of hospital stays etc., received by the patients recruited for the study, to find out correlations between treatments at the individual level and enabling patient "follow-up". Another aspect of the validation concerns the analysis of papers extracted from epidemiological and clinical databases in order to identify emerging technologies, standard of care, "benchmarking" among various operational units dealing with the same pathologies, as well as population profiling to enable identification of homogeneous groups, from a socio-demographic point of view and healthcare demand, subject to tailored prevention campaigns. A more specific application deals with the analysis of drug prescriptions to find out correlations between patient pathology profiles (derived from all treatments and diagnosis received by patients) and prescriptive behaviors of their general practitioners in order to define shared "guidelines" and identify standard practices to compare with practice guidelines. The document describe some sperimentation in these area