Molecular genetics of the transcription factor GLIS3 identifies its dual function in beta cells and neurons

The GLIS family zinc finger 3 isoform (GLIS3) is a risk gene for Type 1 and Type 2 diabetes, glaucoma and Alzheimer's disease endophenotype. We identified GLIS3 binding sites in insulin secreting cells (INS1) (FDR q < 0.05; enrichment range 1.40–9.11 fold) sharing the motif wrGTTCCCArTAGs, which were enriched in genes involved in neuronal function and autophagy and in risk genes for metabolic and neuro-behavioural diseases. We confirmed experimentally Glis3-mediated regulation of the expression of genes involved in autophagy and neuron function in INS1 and neuronal PC12 cells. Naturally-occurring coding polymorphisms in Glis3 in the Goto-Kakizaki rat model of type 2 diabetes were associated with increased insulin production in vitro and in vivo, suggestive alteration of autophagy in PC12 and INS1 and abnormal neurogenesis in hippocampus neurons. Our results support biological pleiotropy of GLIS3 in pathologies affecting β-cells and neurons and underline the existence of trans?nosology pathways in diabetes and its co-morbidities.     

Major effect of retinal short-chain dehydrogenase reductase (RDHE2) on bovine fat colour

Beef with yellow fat is considered undesirable by consumers in most European and Asian markets. β-Carotene is the major carotenoid deposited in the adipose tissue and milk fat of cattle (Bos taurus), which can result in the yellowness. The effects of retinal short-chain dehydrogenase reductase (RDHE2) and β, β-carotene 9',10-dioxygenase (BCO2) were considered jointly as major candidate genes for causing the yellow fat colour, based on their genomic locations in the fat colour quantitative trait loci (QTL) and their roles in the metabolism of β-carotene. In a secondary pathway, BCO2 cleaves β-carotene into retinoic acid, the most potent form of vitamin A. RDHE2 converts trans-retinol to trans-retinal, a less active form of vitamin A. We evaluated the effects of two amino acid variants of the RDHE2 gene (V6A and V33A) along with a mutation in the BCO2 gene that results in a stop codon (W80X) in seven cattle populations. The RDHE2 V6A genotype affected several fat colour traits but the size of the effect varied in the populations studied. The genotype effect of the RDHE2 V33A variant was observed only in New Zealand samples of unknown breed. In general, the individual effects of RDHE2 V6A and V33A SNPs genotypes were greater in the random New Zealand samples than in samples from pedigreed Jersey-Limousin backcross progeny, accounting for 8-17 % of the variance in one population. Epistasis between the BCO2 W80X and RDHE2 variants was observed, and in some populations this explained more of the variation than the effects of the individual RDHE2 variants.     

Estimating Size and Trend of the North Interlake Woodland Caribou Population Using Fecal-DNA and Capture-Recapture Models

A critical step in recovery efforts for endangered and threatened species is the monitoring of population demographic parameters. As part of these efforts, we evaluated the use of fecal-DNA based capture–recapture methods to estimate population sizes and population rate of change for the North Interlake woodland caribou herd (Rangifer tarandus caribou), Manitoba, Canada. This herd is part of the boreal population of woodland caribou, listed as threatened under the federal Species at Risk Act (2003) and the provincial Manitoba Endangered Species Act (2006). Between 2004 and 2009 (9 surveys), we collected 1,080 fecal samples and identified 180 unique genotypes (102 females and 78 males). We used a robust design survey plan with 2 surveys in most years and analysed the data with Program MARK to estimate encounter rates (p), apparent survival rates (φ), rates of population change (λ), and population sizes (N). We estimated these demographic parameters for males and females and for 2 genetic clusters within the North Interlake. The population size estimates were larger for the Lower than the Upper North Interlake area and the proportion of males was lower in the Lower (33%) than the Upper North Interlake (49%). Population rate of change for the entire North Interlake area (2005–2009) using the robust design Pradel model was significantly <1.0 (λ = 0.90, 95% CI: 0.82–0.99) and varied between sex and area with the highest being for males in Lower North Interlake (λ = 0.98, 95% CI: 0.83–1.13) and the lowest being for females in Upper North Interlake (λ = 0.83, 95% CI: 0.69–0.97). The additivity of λ between sex and area is supported on the log scale and translates into males having a λ that is 0.09 greater than females and independent of sex, Lower North Interlake having a λ that is 0.06 greater than Upper North Interlake. Population estimates paralleled these declining trends, which correspond to trends observed in other fragmented populations of woodland caribou along the southern part of their range. The results of this study clearly demonstrate the applicability and success of non-invasive genetic sampling in monitoring populations of woodland caribou. © 2012 The Wildlife Society.     

High Mortality amongst Adolescents and Adults with Bacterial Meningitis in Sub-Saharan Africa: An Analysis of 715 Cases from Malawi

Mortality from bacterial meningitis in African adults is significantly higher than those in better resourced settings and adjunctive therapeutic interventions such as dexamethasone and glycerol have been shown to be ineffective. We conducted a study analysing data from clinical trials of bacterial meningitis in Blantyre, Malawi to investigate the clinical parameters associated with this high mortality.

Methods

We searched for all clinical trials undertaken in Blantyre investigating bacterial meningitis from 1990 to the current time and combined the data from all included trial datasets into one database. We used logistic regression to relate individual clinical parameters to mortality. Adults with community acquired bacterial meningitis were included if the CSF culture isolate was consistent with meningitis or if the CSF white cell count was >100 cells/mm³ (>50% neutrophils) in HIV negative participants and >5 cells/mm³ in HIV positive participants. Outcome was measured by mortality at discharge from hospital (after 10 days of antibiotic therapy) and community follow up (day 40).

Results

Seven hundred and fifteen episodes of bacterial meningitis were evaluated. The mortality rate was 45% at day 10 and 54% at day 40. The most common pathogens were S.pneumoniae (84% of positive CSF isolates) and N.meningitidis (4%). 607/694 (87%) participants tested were HIV antibody positive. Treatment delays within the hospital system were marked. The median presenting GCS was 12/15, 17% had GCS<8 and 44.9% had a seizure during the illness. Coma, seizures, tachycardia and anaemia were all significantly associated with mortality on multivariate analysis. HIV status and pneumococcal culture positivity in the CSF were not associated with mortality. Adults with community acquired bacterial meningitis in Malawi present with a severe clinical phenotype. Predictors of high mortality are different to those seen in Western settings. Optimising in-hospital care and minimising treatment delays presents an opportunity to improve outcomes considerably.     

The Obesity Epidemic and Its Impact on Urologic Care

Although heart disease and cancer are the number one and two causes of death in the United States, respectively, obesity is gaining speed as a contributing cause to both of those conditions, along with diabetes, arthritis, dyslipidemia, coronary heart disease, gallbladder disease, and certain malignancies. Nearly one-third of the adults in the United States is overweight with a body mass index (BMI) greater than 25 kg/m², and another third of the adult population is obese, with a BMI greater than 30 kg/m². This article reviews the root causes of obesity, the societal implications, and the implications of obesity on various urologic diseases.Key words: Obesity, Morbid obesity, Body mass index, Exercise, Weight loss, Diet, EpidemicMore than 20% of adults in the United States are clinically obese, defined by a body mass index (BMI) of 30 kg/m² or higher, and an additional 30% are overweight, with a BMI between 25 and 30 kg/m².¹ An environment that promotes excessive food intake and discourages physical activity lies at the root of the current obesity epidemic. Although humans have excellent physiologic mechanisms to defend against body weight loss, they have only weak physiologic mechanisms to defend against body weight gain when food is abundant. So much has been discussed about the obesity epidemic that it’s easy to think the issue is being blown out of proportion. After all, people putting on a few pounds may not seem to warrant the proclamation of a national emergency. Although obesity may not attract the degree of attention that heart disease and cancer do, it is a serious public health issue. Experts agree that, as more and more obese children become obese adults, the diseases associated with obesity, such as heart disease, cancer, and particularly diabetes, will surge.The obesity epidemic in the United States is an unintended consequence of the economic, social, and technologic advances realized during the past several decades. The food supply is abundant and low in cost, and palatable foods with high caloric density are readily available in prepackaged forms and at fast-food restaurants. Laborsaving technologies have greatly reduced the amount of physical activity that used to be part of everyday life, and the widespread availability of electronic devices in the home, school, and office has promoted a sedentary lifestyle, particularly among children.A recent study estimated that medical expenditures attributed to overweight and obesity accounted for 9.1% of total US medical expenditures in 1998, and might have reached $78.5 billion dollars.² Today, the healthcare costs attributed to obesity are estimated to be $190 billion—nearly 21% of total US healthcare costs.³ Expenditures will continue to rise, particularly due to increases in the prevalence of obesity and the cost of related healthcare.Total healthcare costs attributable to this obesity epidemic are expected to double every decade, reaching $860.7 to $956.9 billion by 2030, accounting for 16% to 18% of total US healthcare costs, or 1 in every 6 dollars spent on healthcare. ⁴ In addition, obesity is likely to result in a decreased life expectancy for our population. Current US generations may have a shorter life expectancy than their parents if this obesity epidemic cannot be controlled.⁵ Based on nationally representative data and the assumptions of a future of increased obesity rates, along with increased healthcare costs, this paints an alarming picture of the future obesity epidemic. Projections show that if the trends continue, in 15 years, 80% of all American adults will be overweight or obese.⁶