Socioeconomic position, gender, health behaviours and biomarkers of cardiovascular disease and diabetes

Socio-economic gradients in cardiovascular disease (CVD) and diabetes have been found throughout the developed world and there is some evidence to suggest that these gradients may be steeper for women. Research on social gradients in biological risk factors for CVD and diabetes has received less attention and we do not know the extent to which gradients in biomarkers vary for men and women. We examined the associations between two indicators of socio-economic position (education and household income) and biomarkers of diabetes and cardiovascular disease (CVD) for men and women in a national, population-based study of 11,247 Australian adults. Multi-level linear regression was used to assess associations between education and income and glucose tolerance, dyslipidaemia, blood pressure (BP) and waist circumference before and after adjustment for behaviours (diet, smoking, physical activity, TV viewing time, and alcohol use). Measures of glucose tolerance included fasting plasma glucose and insulin and the results of a glucose tolerance test (2 h glucose) with higher levels of each indicating poorer glucose tolerance. Triglycerides and High Density Lipoprotein (HDL) Cholesterol were used as measures of dyslipidaemia with higher levels of the former and lower levels of the later being associated with CVD risk. Lower education and low income were associated with higher levels of fasting insulin, triglycerides and waist circumference in women. Women with low education had higher systolic and diastolic BP and low income women had higher 2 h glucose and lower HDL cholesterol. With only one exception (low income and systolic BP), all of these estimates were reduced by more than 20% when behavioural risk factors were included. Men with lower education had higher fasting plasma glucose, 2 h glucose, waist circumference and systolic BP and, with the exception of waist circumference, all of these estimates were reduced when health behaviours were included in the models. While low income was associated with higher levels of 2-h glucose and triglycerides it was also associated with better biomarker profiles including lower insulin, waist circumference and diastolic BP. We conclude that low socio-economic position is more consistently associated with a worse profile of biomarkers for CVD and diabetes for women.

Dirichlet process mixture models for unsupervised clustering of symptoms in Parkinson's disease

In this paper, the goal of identifying disease subgroups based on differences in observed symptom profile is considered. Commonly referred to as phenotype identification, solutions to this task often involve the application of unsupervised clustering techniques. In this paper, we investigate the application of a Dirichlet Process mixture (DPM) model for this task. This model is defined by the placement of the Dirichlet Process (DP) on the unknown components of a mixture model, allowing for the expression of uncertainty about the partitioning of observed data into homogeneous subgroups. To exemplify this approach, an application to phenotype identification in Parkinson’s disease (PD) is considered, with symptom profiles collected using the Unified Parkinson’s Disease Rating Scale (UPDRS). Clustering, Dirichlet Process mixture, Parkinson’s disease, UPDRS.

Endophenotype profiles of MTHFR and ACE gene polymorphisms in migraine susceptibility

Background Migraine is a debilitating neurological disorder affecting approximately 12% of the Caucasian population. There are two main sub-types of migraine, migraine without aura (MO) and migraine with aura (MA). Migraine exhibits varied phenotypic expression with sufferers experiencing a range of neurological and other symptoms. It is likely that multiple susceptibility genes play a role in this varied phenotypic expression, thus investigation of genotype-phenotype relationships may provide valuable insights into the role of susceptibility genes in this disorder. Methods This study investigated the links between migraine susceptibility genes, methylenetetrahydrofolate reductase (MTHFR) and angiotensin converting enzyme (ACE), and clinical manifestation through statistical analyses. Results The result showed that for the MTHFR genotypes, there was a statistically significant correlation with the TT homozygous genotype and visual disturbances, unilateral head pain and physical activity discomforts. It was also found that bilateral head pain was associated with the male gender. Conclusion From these study results, it is plausible to state that MTHFR genotypes affect the phenotypic expression of migraine disease manifestation.

Carrot mottle mimic virus (CMoMV): A second umbravirus associated with carrot motley dwarf disease recognised by nucleic acid hybridisation

Carrot mottle umbravirus (CMoV) has always been found co-infecting plants with carrot red leaf luteovirus (CRLV) and in carrot (Daucus carota) these co-infections are associated with carrot motley dwarf disease (CMD). CMD occurs wherever carrots are grown. Hence, CMoV was believed to have a corresponding global distribution. However, little or no hybridisation was detected between cDNA generated from the sequenced Australian isolate of CMoV (CMoV-A) and RNA from the much studied Scottish isolate of CMoV (CMoV-S). A weak hybridisation signal was obtained using cDNA to a conserved part of the RNA-dependent RNA polymerase gene of CMoV-A, but when cDNAs to other parts of the CMoV-A genome were used as probes there was no detectable hybridisation with CMoV-S RNA. This lack of hybridisation suggests that the two virus isolates have relatively divergent genomes and that they should be regarded as distinct virus species. Both viruses are transmitted by Cavariella aegopodii, but only with the help of CRLV, and they yield almost identical double-stranded RNA profiles. For these reasons, we propose that the CMoV isolate from Australia be renamed carrot mottle mimic umbravirus (CMoMV). cDNA to CMoMV RNA hybridised with RNA from an isolate from New Zealand, whereas cDNA to CMoV-S RNA hybridised with RNA from isolates from England and Morocco but not to RNA from the isolate from New Zealand. Although preliminary, these data suggest that CMoV and CMoMV may have different global distributions.

Isolation of nontuberculous mycobacteria (NTM) from household water and shower aerosols in patients with pulmonary disease caused by NTM

It has been postulated that susceptible individuals may acquire infection with nontuberculous mycobacteria (NTM) from water and aerosol exposure. This study examined household water and shower aerosols of patients with NTM pulmonary disease. The mycobacteria isolated from clinical samples from 20 patients included M. avium (5 patients), M. intracellulare (12 patients), M. abscessus (7 patients), M. gordonae (1 patient), M. lentiflavum (1 patient), M. fortuitum (1 patient), M. peregrinum (1 patient), M. chelonae (1 patient), M. triplex (1 patient), and M. kansasii (1 patient). One-liter water samples and swabs were collected from all taps, and swimming pools or rainwater tanks. Shower aerosols were sampled using Andersen six-stage cascade impactors. For a subgroup of patients, real-time PCR was performed and high-resolution melt profiles were compared to those of ATCC control strains. Pathogenic mycobacteria were isolated from 19 homes. Species identified in the home matched that found in the patient in seven (35%) cases: M. abscessus (3 cases), M. avium (1 case), M. gordonae (1 case), M. lentiflavum (1 case), and M. kansasii (1 case). In an additional patient with M. abscessus infection, this species was isolated from potable water supplying her home. NTM grown from aerosols included M. abscessus (3 homes), M. gordonae (2 homes), M. kansasii (1 home), M. fortuitum complex (4 homes), M. mucogenicum (1 home), and M. wolinskyi (1 home). NTM causing human disease can be isolated from household water and aerosols. The evidence appears strongest for M. avium, M. kansasii, M. lentiflavum, and M. abscessus. Despite a predominance of disease due to M. intracellulare, we found no evidence for acquisition of infection from household water for this species.

Transcriptome analyses of amoebic gill disease-affected atlantic salmon (Salmo salar) tissues reveal localized host gene suppression

The transcriptome response of Atlantic salmon (Salmo salar) displaying advanced stages of amoebic gill disease (AGD) was investigated. Naïve smolt were challenged with AGD for 19 days, at which time all fish were euthanized and their severity of infection quantified through histopathological scoring. Gene expression profiles were compared between heavily infected and naïve individuals using a 17 K Atlantic salmon cDNA microarray with real-time quantitative RT-PCR (qPCR) verification. Expression profiles were examined in the gill, anterior kidney, and liver. Twenty-seven transcripts were significantly differentially expressed within the gill; 20 of these transcripts were down-regulated in the AGD-affected individuals compared with naïve individuals. In contrast, only nine transcripts were significantly differentially expressed within the anterior kidney and five within the liver. Again the majority of these transcripts were down-regulated within the diseased individuals. A down-regulation of transcripts involved in apoptosis (procathepsin L, cathepsin H precursor, and cystatin B) was observed in AGD-affected Atlantic salmon. Four transcripts encoding genes with antioxidant properties also were down-regulated in AGD-affected gill tissue according to qPCR analysis. The most up-regulated transcript within the gill was an unknown expressed sequence tag (EST) whose expression was 218-fold (± SE 66) higher within the AGD affected gill tissue. Our results suggest that Atlantic salmon experiencing advanced stages of AGD demonstrate general down-regulation of gene expression, which is most pronounced within the gill. We propose that this general gene suppression is parasite-mediated, thus allowing the parasite to withstand or ameliorate the host response. © 2008 Springer Science+Business Media, LLC.

Laser capture microdissection and multiplex-tandem PCR analysis of proximal tubular epithelial cell signaling in human kidney disease

Interstitial fibrosis, a histological process common to many kidney diseases, is the precursor state to end stage kidney disease, a devastating and costly outcome for the patient and the health system. Fibrosis is historically associated with chronic kidney disease (CKD) but emerging evidence is now linking many forms of acute kidney disease (AKD) with the development of CKD. Indeed, we and others have observed at least some degree of fibrosis in up to 50% of clinically defined cases of AKD. Epithelial cells of the proximal tubule (PTEC) are central in the development of kidney interstitial fibrosis. We combine the novel techniques of laser capture microdissection and multiplex-tandem PCR to identify and quantitate “real time” gene transcription profiles of purified PTEC isolated from human kidney biopsies that describe signaling pathways associated with this pathological fibrotic process. Our results: (i) confirm previous in-vitro and animal model studies; kidney injury molecule-1 is up-regulated in patients with acute tubular injury, inflammation, neutrophil infiltration and a range of chronic disease diagnoses, (ii) provide data to inform treatment; complement component 3 expression correlates with inflammation and acute tubular injury, (iii) identify potential new biomarkers; proline 4-hydroxylase transcription is down-regulated and vimentin is up-regulated across kidney diseases, (iv) describe previously unrecognized feedback mechanisms within PTEC; Smad-3 is down-regulated in many kidney diseases suggesting a possible negative feedback loop for TGF-β in the disease state, whilst tight junction protein-1 is up-regulated in many kidney diseases, suggesting feedback interactions with vimentin expression. These data demonstrate that the combined techniques of laser capture microdissection and multiplex-tandem PCR have the power to study molecular signaling within single cell populations derived from clinically sourced tissue.

Malnutrition in children with chronic liver disease accepted for liver transplantation : clinical profile and effect on outcome

The nutritional profiles of 37 children (aged 0.5-14.0 years) with chronic liver disease at the time of acceptance for orthotopic liver transplantation (OLTP) have been evaluated using clinical, biochemical and body composition methods. Nutritional progress while waiting for a donor has been related to outcome, whether transplanted or not. At the time of acceptance, most children were underweight (mean standard deviation (s.d.) weight = -1.4 ± 0.2) and stunted (mean s.d. height = - 2.2 ± 0.4), had low serum albumin (27/35) and had reduced body fat and depleted body cell mass (measured by total body potassium - mean % expected for age = 58 ± 5%, n = 15). Mean ad libitum nutrient intake was 63 ± 5% of recommended daily intake (RDI). Those who died while waiting (n = 8) had significantly lower mean initial s.d. weight compared with those transplanted. The overall actuarial 1 year survival of those who were transplanted (mean waiting time = 75 days) was 81% but those who were initially well nourished (s.d. weight >-1.0) had an actuarial 1 year survival of 100%. There were no significant differences in actuarial survival in relationship to age, type of transplant (whole liver or segmental), liver biochemistry or the presence or absence of ascites. Of the total group accepted for OLTP, whether transplanted or not, the overall 1 year survival for those who were relatively well nourished was 88% and for those undernourished (initial s.d. weight <-1.0) was 38% (P<0.003). Declining nutritional status during the waiting period also adversely affected outcome. We conclude that malnutrition and/or declining nutritional status is a major factor adversely affecting survival in children awaiting OLTP. In transplant units where waiting time is greater than 40 days, earlier referral, prioritization of cases and the use of adult donor livers may reduce this risk and efforts to maintain or improve nutritional status deserve further study.

Comparison of decision tree, support vector machines, and Bayesian network approaches for classification of falls in Parkinson’s disease

Being able to accurately predict the risk of falling is crucial in patients with Parkinson’s dis- ease (PD). This is due to the unfavorable effect of falls, which can lower the quality of life as well as directly impact on survival. Three methods considered for predicting falls are decision trees (DT), Bayesian networks (BN), and support vector machines (SVM). Data on a 1-year prospective study conducted at IHBI, Australia, for 51 people with PD are used. Data processing are conducted using rpart and e1071 packages in R for DT and SVM, con- secutively; and Bayes Server 5.5 for the BN. The results show that BN and SVM produce consistently higher accuracy over the 12 months evaluation time points (average sensitivity and specificity > 92%) than DT (average sensitivity 88%, average specificity 72%). DT is prone to imbalanced data so needs to adjust for the misclassification cost. However, DT provides a straightforward, interpretable result and thus is appealing for helping to identify important items related to falls and to generate fallers’ profiles.

Weather variability, tides, and Barmah Forest Virus Disease in the Gladstone region, Australia

In this study we examined the impact of weather variability and tides on the transmission of Barmah Forest virus (BFV) disease and developed a weather-based forecasting model for BFV disease in the Gladstone region, Australia. We used seasonal autoregressive integrated moving-average (SARIMA) models to determine the contribution of weather variables to BFV transmission after the time-series data of response and explanatory variables were made stationary through seasonal differencing. We obtained data on the monthly counts of BFV cases, weather variables (e.g., mean minimum and maximum temperature, total rainfall, and mean relative humidity), high and low tides, and the population size in the Gladstone region between January 1992 and December 2001 from the Queensland Department of Health, Australian Bureau of Meteorology, Queensland Department of Transport, and Australian Bureau of Statistics, respectively. The SARIMA model shows that the 5-month moving average of minimum temperature (β = 0.15, p-value < 0.001) was statistically significantly and positively associated with BFV disease, whereas high tide in the current month (β = −1.03, p-value = 0.04) was statistically significantly and inversely associated with it. However, no significant association was found for other variables. These results may be applied to forecast the occurrence of BFV disease and to use public health resources in BFV control and prevention.