Metabolomics and Lipidomics Signatures of Insulin Resistance and Abdominal Fat Depots in People Living with Obesity

The liver, skeletal muscle, and adipose tissue are major insulin target tissues and key players in glucose homeostasis. We and others have described diverse insulin resistance (IR) phenotypes in people at risk of developing type 2 diabetes. It is postulated that identifying the IR phenotype in a patient may guide the treatment or the prevention strategy for better health outcomes in populations at risk. Here, we performed plasma metabolomics and lipidomics in a cohort of men and women living with obesity not complicated by diabetes (mean [SD] BMI 36.0 [4.5] kg/m2, n = 62) to identify plasma signatures of metabolites and lipids that align with phenotypes of IR (muscle, liver, or adipose tissue) and abdominal fat depots. We used 2-step hyperinsulinemic-euglycemic clamp with deuterated glucose, oral glucose tolerance test, dual-energy X-ray absorptiometry and abdominal magnetic resonance imaging to assess muscle-, liver- and adipose tissue- IR, beta cell function, body composition, abdominal fat distribution and liver fat, respectively. Spearman’s rank correlation analyses that passed the Benjamini–Hochberg statistical correction revealed that cytidine, gamma-aminobutyric acid, anandamide, and citrate corresponded uniquely with muscle IR, tryptophan, cAMP and phosphocholine corresponded uniquely with liver IR and phenylpyruvate and hydroxy-isocaproic acid corresponded uniquely with adipose tissue IR (p < 7.2 × 10−4). Plasma cholesteryl sulfate (p = 0.00029) and guanidinoacetic acid (p = 0.0001) differentiated between visceral and subcutaneous adiposity, while homogentisate correlated uniquely with liver fat (p = 0.00035). Our findings may help identify diverse insulin resistance and adiposity phenotypes and enable targeted treatments in people living with obesity

Sensitivity of methods for estimating breeding values using genetic markers to the number of QTL and distribution of QTL variance

The objective of this simulation study was to compare the effect of the number of QTL and distribution of QTL variance on the accuracy of breeding values estimated with genomewide markers (MEBV). Three distinct methods were used to calculate MEBV: a Bayesian Method (BM), Least Angle Regression (LARS) and Partial Least Square Regression (PLSR). The accuracy of MEBV calculated with BM and LARS decreased when the number of simulated QTL increased. The accuracy decreased more when QTL had different variance values than when all QTL had an equal variance. The accuracy of MEBV calculated with PLSR was affected neither by the number of QTL nor by the distribution of QTL variance. Additional simulations and analyses showed that these conclusions were not affected by the number of individuals in the training population, by the number of markers and by the heritability of the trait. Results of this study show that the effect of the number of QTL and distribution of QTL variance on the accuracy of MEBV depends on the method that is used to calculate MEBV

A classification of diabetic foot infections using ICD-9-CM codes: application to a large computerized medical database

<p>Abstract</p> <p>Background</p> <p>Diabetic foot infections are common, serious, and varied. Diagnostic and treatment strategies are correspondingly diverse. It is unclear how patients are managed in actual practice and how outcomes might be improved. Clarification will require study of large numbers of patients, such as are available in medical databases. We have developed and evaluated a system for identifying and classifying diabetic foot infections that can be used for this purpose.</p> <p>Methods</p> <p>We used the (VA) Diabetes Epidemiology Cohorts (DEpiC) database to conduct a retrospective observational study of patients with diabetic foot infections. DEpiC contains computerized VA and Medicare patient-level data for patients with diabetes since 1998. We determined which ICD-9-CM codes served to identify patients with different types of diabetic foot infections and ranked them in declining order of severity: Gangrene, Osteomyelitis, Ulcer, Foot cellulitis/abscess, Toe cellulitis/abscess, Paronychia. We evaluated our classification by examining its relationship to patient characteristics, diagnostic procedures, treatments given, and medical outcomes.</p> <p>Results</p> <p>There were 61,007 patients with foot infections, of which 42,063 were classifiable into one of our predefined groups. The different types of infection were related to expected patient characteristics, diagnostic procedures, treatments, and outcomes. Our severity ranking showed a monotonic relationship to hospital length of stay, amputation rate, transition to long-term care, and mortality.</p> <p>Conclusions</p> <p>We have developed a classification system for patients with diabetic foot infections that is expressly designed for use with large, computerized, ICD-9-CM coded administrative medical databases. It provides a framework that can be used to conduct observational studies of large numbers of patients in order to examine treatment variation and patient outcomes, including the effect of new management strategies, implementation of practice guidelines, and quality improvement initiatives.</p

Prevalence of vitamin D deficiency among Turkish, Moroccan, Indian and sub-Sahara African populations in Europe and their countries of origin: an overview

Public Health and primary carePrevention and community carePrevention, Population and Disease management (PrePoD

Immunogenicity and efficacy of oral vaccines in developing countries: lessons from a live cholera vaccine

Oral vaccines, whether living or non-living, viral or bacterial, elicit diminished immune responses or have lower efficacy in developing countries than in developed countries. Here I describe studies with a live oral cholera vaccine that include older children no longer deriving immune support from breast milk or maternal antibodies and that identify some of the factors accounting for the lower immunogenicity, as well as suggesting counter-measures that may enhance the effectiveness of oral immunization in developing countries. The fundamental breakthrough is likely to require reversing effects of the 'environmental enteropathy' that is often present in children living in fecally contaminated, impoverished environments

Use of haplotypes to identify regions harbouring lethal recessive variants in pigs

Additional file 2: Figure S1. Heatmap of the linkage disequilibrium r 2 values between each of the SNPs located within regions 1.1. and 1.2 on SSC1

Assessing treatment outcomes in multiple sclerosis trials and in the clinical setting

Increasing numbers of drugs are being developed for the treatment of multiple sclerosis (MS). Measurement of relevant outcomes is key for assessing the efficacy of new drugs in clinical trials and for monitoring responses to disease-modifying drugs in individual patients. Most outcomes used in trial and clinical settings reflect either clinical or neuroimaging aspects of MS (such as relapse and accrual of disability or the presence of visible inflammation and brain tissue loss, respectively). However, most measures employed in clinical trials to assess treatment effects are not used in routine practice. In clinical trials, the appropriate choice of outcome measures is crucial because the results determine whether a drug is considered effective and therefore worthy of further development; in the clinic, outcome measures can guide treatment decisions, such as choosing a first-line disease-modifying drug or escalating to second-line treatment. This Review discusses clinical, neuroimaging and composite outcome measures for MS, including patient-reported outcome measures, used in both trials and the clinical setting. Its aim is to help clinicians and researchers navigate through the multiple options encountered when choosing an outcome measure. Barriers and limitations that need to be overcome to translate trial outcome measures into the clinical setting are also discussed

Physiotherapy Intervention for Joint Hypermobility in Three Cases with Heritable Connective Tissue Disorders

peer reviewedIntroduction: In Joint Hypermobility Syndromes, chronic pain is the most disabling symptom. Its origin can be multiple (i.e. subluxations, sprains, pathologies of tendons, ligaments, peripheral nerves, multiple operations). The goal of this article was intended to discuss appropriate physiotherapy in hyperlax patients. Patients and Method: The recovery process was analyzed in three cases (Marfan Syndrome, Ehlers-Danlos Syndrome and Osteogenesis Imperfecta). Hypermobility was assessed using the Brighton scale, pain using the Visual Analogue Scale and quality of life using the Medical Outcome Study Short Form-36. Bone density was evaluated by QDR X-ray absorptiometry. We emphasized that it was important to avoid stretching and to train the patient within a controlled range of motion. Submaximal eccentric exercises within a safe range of motion were incorporated to increase the active control of the joint positioning. Thus, in one patient, isokinetic rehabilitation was successfully undertaken. Each treatment had to be adapted to the individual patient and had to include specific home exercises. Conclusion: In each case, physiotherapy gave good results in relation to pain, quality of life and stability of rehabilitated joints. Safety must be assured and specific evaluations such osteodensitometry, cardiac explorations and interventions of bracing, proprioceptive and functional strengthening can be very helpful