Potential risk factors for diabetic neuropathy: a case control study

BACKGROUND: Diabetes mellitus type II afflicts at least 2 million people in Iran. Neuropathy is one of the most common complications of diabetes and lowers the patient's quality of life. Since neuropathy often leads to ulceration and amputation, we have tried to elucidate the factors that can affect its progression. METHODS: In this case-control study, 110 diabetic patients were selected from the Shariati Hospital diabetes clinic. Michigan Neuropathic Diabetic Scoring (MNDS) was used to differentiate cases from controls. The diagnosis of neuropathy was confirmed by nerve conduction studies (nerve conduction velocity and electromyography). The multiple factors compared between the two groups included consumption of angiotensin converting enzyme inhibitors (ACEI), blood pressure, serum lipid level, sex, smoking, method of diabetes control and its quality. RESULTS: Statistically significant relationships were found between neuropathy and age, gender, quality of diabetes control and duration of disease (P values in the order: 0.04, 0.04, < 0.001 and 0.005). No correlation was found with any atherosclerosis risk factor (high BP, hyperlipidemia, cigarette smoking). CONCLUSION: In this study, hyperglycemia was the only modifiable risk factor for diabetic neuropathy. Glycemic control reduces the incidence of neuropathy, slows its progression and improves the diabetic patient's quality of life. More attention must be paid to elderly male diabetic patients with poor diabetes control with regard to regular foot examinations and more practical education

Adolescents' health and health behaviour as predictors of injury death. A prospective cohort follow-up of 652,530 person-years

<p>Abstract</p> <p>Background</p> <p>Injuries represent an important cause of mortality among young adults. Longitudinal studies on risk factors are scarce. We studied associations between adolescents' perceived health and health behaviour and injury death.</p> <p>Methods</p> <p>A prospective cohort of 57,407 Finns aged 14 to 18 years was followed for an average of 11.4 years. The end-point of study was injury death or termination of follow-up in 2001. The relationships of eight health and health behaviour characteristics with injury death were studied with adjusted Cox's proportional hazard model.</p> <p>Results</p> <p>We identified 298 (0.5%) injury deaths, 232 (0.9%) in men and 66 (0.2%) in women. The mean age at death was 23.8 years. In the models adjusted for age, sex and socioeconomic background, the strongest risk factors for injury death were recurring drunkenness (HR 2.1; 95% CI: 1.4–3.1) and daily smoking (HR 1.7; 95% CI: 1.3–2.2). Poor health did not predict injury death. Unintentional and intentional injury deaths had similar health and health behavioural risk factors.</p> <p>Conclusion</p> <p>Health compromising behaviour adopted at adolescence has a clear impact on the risk of injury death in adulthood independent from socioeconomic background. On the other hand, poor health as such is not a significant predictor of injury death. Promotion of healthy lifestyle among adolescents as part of public health programmes would seem an appropriate way to contribute to adolescent injury prevention.</p

A polymorphic variant of the insulin-like growth factor 1 (IGF-1) receptor correlates with male longevity in the Italian population: a genetic study and evaluation of circulating IGF-1 from the "Treviso Longeva (TRELONG)" study

<p>Abstract</p> <p>Background</p> <p>An attenuation of the insulin-like growth factor 1 (IGF-1) signaling has been associated with elongation of the lifespan in simple metazoan organisms and in rodents. In humans, IGF-1 level has an age-related modulation with a lower concentration in the elderly, depending on hormonal and genetic factors affecting the IGF-1 receptor gene (<it>IGF-1R</it>).</p> <p>Methods</p> <p>In an elderly population from North-eastern Italy (<it>n </it>= 668 subjects, age range 70–106 years) we investigated the <it>IGF-1R </it>polymorphism G3174A (<it>rs2229765</it>) and the plasma concentration of free IGF-1. Frequency distributions were compared using χ²-test "Goodness of Fit" test, and means were compared by one-way analysis of variance (ANOVA); multiple regression analysis was performed using JMP7 for SAS software (SAS Institute, USA). The limit of significance for genetic and biochemical comparison was set at α = 0.05.</p> <p>Results</p> <p>Males showed an age-related increase in the A-allele of <it>rs2229765 </it>and a change in the plasma level of IGF-1, which dropped significantly after 85 years of age (85+ group). In the male 85+ group, A/A homozygous subjects had the lowest plasma IGF-1 level. We found no clear correlation between <it>rs2229765 </it>genotype and IGF-1 in the females.</p> <p>Conclusion</p> <p>These findings confirm the importance of the <it>rs2229765 </it>minor allele as a genetic predisposing factor for longevity in Italy where a sex-specific pattern for IGF-1 attenuation with ageing was found.</p

The Ontario printed educational message (OPEM) trial to narrow the evidence-practice gap with respect to prescribing practices of general and family physicians: a cluster randomized controlled trial, targeting the care of individuals with diabetes and hypertension in Ontario, Canada

<p>Abstract</p> <p>Background</p> <p>There are gaps between what family practitioners do in clinical practice and the evidence-based ideal. The most commonly used strategy to narrow these gaps is the printed educational message (PEM); however, the attributes of successful printed educational messages and their overall effectiveness in changing physician practice are not clear. The current endeavor aims to determine whether such messages change prescribing quality in primary care practice, and whether these effects differ with the format of the message.</p> <p>Methods/design</p> <p>The design is a large, simple, factorial, unblinded cluster-randomized controlled trial. PEMs will be distributed with <b><it>informed</it></b>, a quarterly evidence-based synopsis of current clinical information produced by the Institute for Clinical Evaluative Sciences, Toronto, Canada, and will be sent to all eligible general and family practitioners in Ontario. There will be three replicates of the trial, with three different educational messages, each aimed at narrowing a specific evidence-practice gap as follows: 1) angiotensin-converting enzyme inhibitors, hypertension treatment, and cholesterol lowering agents for diabetes; 2) retinal screening for diabetes; and 3) diuretics for hypertension.</p> <p>For each of the three replicates there will be three intervention groups. The first group will receive <b><it>informed </it></b>with an attached postcard-sized, short, directive "outsert." The second intervention group will receive <b><it>informed </it></b>with a two-page explanatory "insert" on the same topic. The third intervention group will receive <b><it>informed</it></b>, with both the above-mentioned outsert and insert. The control group will receive <b><it>informed </it></b>only, without either an outsert or insert.</p> <p>Routinely collected physician billing, prescription, and hospital data found in Ontario's administrative databases will be used to monitor pre-defined prescribing changes relevant and specific to each replicate, following delivery of the educational messages. Multi-level modeling will be used to study patterns in physician-prescribing quality over four quarters, before and after each of the three interventions. Subgroup analyses will be performed to assess the association between the characteristics of the physician's place of practice and target behaviours.</p> <p>A further analysis of the immediate and delayed impacts of the PEMs will be performed using time-series analysis and interventional, auto-regressive, integrated moving average modeling.</p> <p>Trial registration number</p> <p>Current controlled trial ISRCTN72772651.</p

Marsh macrophyte responses to inundation anticipate impacts of sea-level rise and indicate ongoing drowning of North Carolina marshes

In situ persistence of coastal marsh habitat as sea level rises depends on whether macrophytes induce compensatory accretion of the marsh surface. Experimental planters in two North Carolina marshes served to expose two dominant macrophyte species to six different elevations spanning 0.75 m (inundation durations 0.4–99 %). Spartina alterniflora and Juncus roemerianus exhibited similar responses—with production in planters suggesting initial increases and then demonstrating subsequent steep declines with increasing inundation, conforming to a segment of the ecophysiological parabola. Projecting inundation levels experienced by macrophytes in the planters onto adjacent marsh platforms revealed that neither species occupied elevations associated with increasing production. Declining macrophyte production with rising seas reduces both bioaccumulation of roots below-ground and baffle-induced sedimentation above-ground. By occupying only descending portions of the parabola, macrophytes in central North Carolina marshes are responding to rising water levels by progressive declines in production, ultimately leading to marsh drowning

The Framingham Heart Study 100K SNP genome-wide association study resource: overview of 17 phenotype working group reports

Background: The Framingham Heart Study (FHS), founded in 1948 to examine the epidemiology of cardiovascular disease, is among the most comprehensively characterized multi-generational studies in the world. Many collected phenotypes have substantial genetic contributors; yet most genetic determinants remain to be identified. Using single nucleotide polymorphisms (SNPs) from a 100K genome-wide scan, we examine the associations of common polymorphisms with phenotypic variation in this community-based cohort and provide a full-disclosure, web-based resource of results for future replication studies. Methods: Adult participants (n = 1345) of the largest 310 pedigrees in the FHS, many biologically related, were genotyped with the 100K Affymetrix GeneChip. These genotypes were used to assess their contribution to 987 phenotypes collected in FHS over 56 years of follow up, including: cardiovascular risk factors and biomarkers; subclinical and clinical cardiovascular disease; cancer and longevity traits; and traits in pulmonary, sleep, neurology, renal, and bone domains. We conducted genome-wide variance components linkage and population-based and family-based association tests. Results: The participants were white of European descent and from the FHS Original and Offspring Cohorts (examination 1 Offspring mean age 32 ± 9 years, 54% women). This overview summarizes the methods, selected findings and limitations of the results presented in the accompanying series of 17 manuscripts. The presented association results are based on 70,897 autosomal SNPs meeting the following criteria: minor allele frequency ≥ 10%, genotype call rate ≥ 80%, Hardy-Weinberg equilibrium p-value ≥ 0.001, and satisfying Mendelian consistency. Linkage analyses are based on 11,200 SNPs and short-tandem repeats. Results of phenotype-genotype linkages and associations for all autosomal SNPs are posted on the NCBI dbGaP website at http:// www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007. Conclusion: We have created a full-disclosure resource of results, posted on the dbGaP website, from a genome-wide association study in the FHS. Because we used three analytical approaches to examine the association and linkage of 987 phenotypes with thousands of SNPs, our results must be considered hypothesis-generating and need to be replicated. Results from the FHS 100K project with NCBI web posting provides a resource for investigators to identify high priority findings for replication.Molecular and Cellular Biolog

The challenge for genetic epidemiologists: how to analyze large numbers of SNPs in relation to complex diseases

Genetic epidemiologists have taken the challenge to identify genetic polymorphisms involved in the development of diseases. Many have collected data on large numbers of genetic markers but are not familiar with available methods to assess their association with complex diseases. Statistical methods have been developed for analyzing the relation between large numbers of genetic and environmental predictors to disease or disease-related variables in genetic association studies. In this commentary we discuss logistic regression analysis, neural networks, including the parameter decreasing method (PDM) and genetic programming optimized neural networks (GPNN) and several non-parametric methods, which include the set association approach, combinatorial partitioning method (CPM), restricted partitioning method (RPM), multifactor dimensionality reduction (MDR) method and the random forests approach. The relative strengths and weaknesses of these methods are highlighted. Logistic regression and neural networks can handle only a limited number of predictor variables, depending on the number of observations in the dataset. Therefore, they are less useful than the non-parametric methods to approach association studies with large numbers of predictor variables. GPNN on the other hand may be a useful approach to select and model important predictors, but its performance to select the important effects in the presence of large numbers of predictors needs to be examined. Both the set association approach and random forests approach are able to handle a large number of predictors and are useful in reducing these predictors to a subset of predictors with an important contribution to disease. The combinatorial methods give more insight in combination patterns for sets of genetic and/or environmental predictor variables that may be related to the outcome variable. As the non-parametric methods have different strengths and weaknesses we conclude that to approach genetic association studies using the case-control design, the application of a combination of several methods, including the set association approach, MDR and the random forests approach, will likely be a useful strategy to find the important genes and interaction patterns involved in complex diseases

Amyotrophic Lateral Sclerosis Multiprotein Biomarkers in Peripheral Blood Mononuclear Cells

Amyotrophic lateral sclerosis (ALS) is a fatal progressive motor neuron disease, for which there are still no diagnostic/prognostic test and therapy. Specific molecular biomarkers are urgently needed to facilitate clinical studies and speed up the development of effective treatments.We used a two-dimensional difference in gel electrophoresis approach to identify in easily accessible clinical samples, peripheral blood mononuclear cells (PBMC), a panel of protein biomarkers that are closely associated with ALS. Validations and a longitudinal study were performed by immunoassays on a selected number of proteins. The same proteins were also measured in PBMC and spinal cord of a G93A SOD1 transgenic rat model. We identified combinations of protein biomarkers that can distinguish, with high discriminatory power, ALS patients from healthy controls (98%), and from patients with neurological disorders that may resemble ALS (91%), between two levels of disease severity (90%), and a number of translational biomarkers, that link responses between human and animal model. We demonstrated that TDP-43, cyclophilin A and ERp57 associate with disease progression in a longitudinal study. Moreover, the protein profile changes detected in peripheral blood mononuclear cells of ALS patients are suggestive of possible intracellular pathogenic mechanisms such as endoplasmic reticulum stress, nitrative stress, disturbances in redox regulation and RNA processing.Our results indicate that PBMC multiprotein biomarkers could contribute to determine amyotrophic lateral sclerosis diagnosis, differential diagnosis, disease severity and progression, and may help to elucidate pathogenic mechanisms

Cross-National Analysis of the Associations among Mental Disorders and Suicidal Behavior: Findings from the WHO World Mental Health Surveys

Using data from over 100,000 individuals in 21 countries participating in the WHO World Mental Health Surveys, Matthew Nock and colleagues investigate which mental health disorders increase the odds of experiencing suicidal thoughts and actual suicide attempts, and how these relationships differ across developed and developing countries