Cholesterol and the risk of grade-specific prostate cancer incidence: evidence from two large prospective cohort studies with up to 37 years' follow up

<b>Background</b> High cholesterol may be a modifiable risk factor for prostate cancer but results have been inconsistent and subject to potential "reverse causality" where undetected disease modifies cholesterol prior to diagnosis.<p></p> <b>Methods</b> We conducted a prospective cohort study of 12,926 men who were enrolled in the Midspan studies between 1970 and 1976 and followed up to 31st December 2007. We used Cox-Proportional Hazards Models to evaluate the association between baseline plasma cholesterol and Gleason grade-specific prostate cancer incidence. We excluded cancers detected within at least 5 years of cholesterol assay.<p></p> <b>Results</b> 650 men developed prostate cancer in up to 37 years' follow-up. Baseline plasma cholesterol was positively associated with hazard of high grade (Gleason score[greater than or equal to]8) prostate cancer incidence (n=119). The association was greatest among men in the 4th highest quintile for cholesterol, 6.1 to <6.69 mmol/l, Hazard Ratio 2.28, 95% CI 1.27 to 4.10, compared with the baseline of <5.05 mmol/l. This association remained significant after adjustment for body mass index, smoking and socioeconomic status.<p></p> <b>Conclusions</b> Men with higher cholesterol are at greater risk of developing high-grade prostate cancer but not overall risk of prostate cancer. Interventions to minimise metabolic risk factors may have a role in reducing incidence of aggressive prostate cancer

Genome-wide analyses for personality traits identify six genomic loci and show correlations with psychiatric disorders

Personality is influenced by genetic and environmental factors1 and associated with mental health. However, the underlying genetic determinants are largely unknown. We identified six genetic loci, including five novel loci2,3, significantly associated with personality traits in a meta-analysis of genome-wide association studies (N = 123,132–260,861). Of these genomewide significant loci, extraversion was associated with variants in WSCD2 and near PCDH15, and neuroticism with variants on chromosome 8p23.1 and in L3MBTL2. We performed a principal component analysis to extract major dimensions underlying genetic variations among five personality traits and six psychiatric disorders (N = 5,422–18,759). The first genetic dimension separated personality traits and psychiatric disorders, except that neuroticism and openness to experience were clustered with the disorders. High genetic correlations were found between extraversion and attention-deficit– hyperactivity disorder (ADHD) and between openness and schizophrenia and bipolar disorder. The second genetic dimension was closely aligned with extraversion–introversion and grouped neuroticism with internalizing psychopathology (e.g., depression or anxiety)

Dynamics of Kv1 Channel Transport in Axons

Concerted actions of various ion channels that are precisely targeted along axons are crucial for action potential initiation and propagation, and neurotransmitter release. However, the dynamics of channel protein transport in axons remain unknown. Here, using time-lapse imaging, we found fluorescently tagged Kv1.2 voltage-gated K+ channels (YFP-Kv1.2) moved bi-directionally in discrete puncta along hippocampal axons. Expressing Kvβ2, a Kv1 accessory subunit, markedly increased the velocity, the travel distance, and the percentage of moving time of these puncta in both anterograde and retrograde directions. Suppressing the Kvβ2-associated protein, plus-end binding protein EB1 or kinesin II/KIF3A, by siRNA, significantly decreased the velocity of YFP-Kv1.2 moving puncta in both directions. Kvβ2 mutants with disrupted either Kv1.2-Kvβ2 binding or Kvβ2-EB1 binding failed to increase the velocity of YFP-Kv1.2 puncta, confirming a central role of Kvβ2. Furthermore, fluorescently tagged Kv1.2 and Kvβ2 co-moved along axons. Surprisingly, when co-moving with Kv1.2 and Kvβ2, EB1 appeared to travel markedly faster than its plus-end tracking. Finally, using fission yeast S. pombe expressing YFP-fusion proteins as reference standards to calibrate our microscope, we estimated the numbers of YFP-Kv1.2 tetramers in axonal puncta. Taken together, our results suggest that proper amounts of Kv1 channels and their associated proteins are required for efficient transport of Kv1 channel proteins along axons

Prevalence of Metabolic Syndrome and Risks of Abnormal Serum Alanine Aminotransferase in Hispanics: A Population-Based Study

Study the prevalence of metabolic syndrome (MS) and risk factors for and association with elevated alanine aminotransferase (ALT) as markers of hepatic injury in a large Hispanic health disparity cohort with high rates of obesity.Analysis of data from a prospective cross-sectional population based study. From 2004-7, we randomly recruited 2000 community participants to the Cameron County Hispanic Cohort collecting extensive socioeconomic, clinical and laboratory data. We excluded 153 subjects due to critical missing data. Pearson chi-square tests and Student's t-tests were used for categorical and continuous variable analysis, respectively. Logistic regression analysis was performed to determine the risk factors for elevated ALT.The mean age of the cohort was 45 years and 67% were females. The majority of the cohort was either overweight (32.4%) or obese (50.7%). Almost half (43.7%) had MS and nearly one-third diabetes. Elevated ALT level was more prevalent in males than females. Obesity was a strong risk for abnormal ALT in both genders. Hypertriglyceridemia, hypercholesterolemia and young age were risks for elevated ALT in males only, whereas increased fasting plasma glucose was associated with elevated ALT in females only.We identified high prevalence of MS and markers of liver injury in this large Mexican American cohort with gender differences in prevalence and risk factors, with younger males at greatest risk

A population-specific reference panel empowers genetic studies of Anabaptist populations

Genotype imputation is a powerful strategy for achieving the large sample sizes required for identification of variants underlying complex phenotypes, but imputation of rare variants remains problematic. Genetically isolated populations offer one solution, however population-specific reference panels are needed to assure optimal imputation accuracy and allele frequency estimation. Here we report the Anabaptist Genome Reference Panel (AGRP), the first whole-genome catalogue of variants and phased haplotypes in people of Amish and Mennonite ancestry. Based on high-depth whole-genome sequence (WGS) from 265 individuals, the AGRP contains >12 M high-confidence single nucleotide variants and short indels, of which ~12.5% are novel. These Anabaptist-specific variants were more deleterious than variants with comparable frequencies observed in the 1000 Genomes panel. About 43,000 variants showed enriched allele frequencies in AGRP, consistent with drift. When combined with the 1000 Genomes Project reference panel, the AGRP substantially improved imputation, especially for rarer variants. The AGRP is freely available to researchers through an imputation server

Improved imputation accuracy of rare and low-frequency variants using population-specific high-coverage WGS-based imputation reference panel

Genetic imputation is a cost-efficient way to improve the power and resolution of genome-wide association (GWA) studies. Current publicly accessible imputation reference panels accurately predict genotypes for common variants with minor allele frequency (MAF) >= 5% and low-frequency variants (0.5Peer reviewe

Entering a new era of body indices: the feasibility of a body shape index and body roundness index to identify cardiovascular health status.

BACKGROUND: The Body Mass Index (BMI) and Waist Circumference (WC) are well-used anthropometric predictors for cardiovascular diseases (CVD), but their validity is regularly questioned. Recently, A Body Shape Index (ABSI) and Body Roundness Index (BRI) were introduced as alternative anthropometric indices that may better reflect health status. OBJECTIVE: This study assessed the capacity of ABSI and BRI in identifying cardiovascular diseases and cardiovascular disease risk factors and determined whether they are superior to BMI and WC. DESIGN AND METHODS: 4627 Participants (54±12 years) of the Nijmegen Exercise Study completed an online questionnaire concerning CVD health status (defined as history of CVD or CVD risk factors) and anthropometric characteristics. Quintiles of ABSI, BRI, BMI, and WC were used regarding CVD prevalence. Odds ratios (OR), adjusted for age, sex, and smoking, were calculated per anthropometric index. RESULTS: 1332 participants (27.7%) reported presence of CVD or CVD risk factors. The prevalence of CVD increased across quintiles for BMI, ABSI, BRI, and WC. Comparing the lowest with the highest quintile, adjusted OR (95% CI) for CVD were significantly different for BRI 3.2 (1.4-7.2), BMI 2.4 (1.9-3.1), and WC 3.0 (1.6-5.6). The adjusted OR (95% CI) for CVD risk factors was for BRI 2.5 (2.0-3.3), BMI 3.3 (1.6-6.8), and WC 2.0 (1.6-2.5). No association was observed for ABSI in both groups. CONCLUSIONS: BRI, BMI, and WC are able to determine CVD presence, while ABSI is not capable. Nevertheless, the capacity of BRI as a novel body index to identify CVD was not superior compared to established anthropometric indices like BMI and WC

Scanning and filling : ultra-dense SNP genotyping combining genotyping-by-sequencing, SNP array and whole-genome resequencing data

Genotyping-by-sequencing (GBS) represents a highly cost-effective high-throughput genotyping approach. By nature, however, GBS is subject to generating sizeable amounts of missing data and these will need to be imputed for many downstream analyses. The extent to which such missing data can be tolerated in calling SNPs has not been explored widely. In this work, we first explore the use of imputation to fill in missing genotypes in GBS datasets. Importantly, we use whole genome resequencing data to assess the accuracy of the imputed data. Using a panel of 301 soybean accessions, we show that over 62,000 SNPs could be called when tolerating up to 80% missing data, a five-fold increase over the number called when tolerating up to 20% missing data. At all levels of missing data examined (between 20% and 80%), the resulting SNP datasets were of uniformly high accuracy (96– 98%). We then used imputation to combine complementary SNP datasets derived from GBS and a SNP array (SoySNP50K). We thus produced an enhanced dataset of >100,000 SNPs and the genotypes at the previously untyped loci were again imputed with a high level of accuracy (95%). Of the >4,000,000 SNPs identified through resequencing 23 accessions (among the 301 used in the GBS analysis), 1.4 million tag SNPs were used as a reference to impute this large set of SNPs on the entire panel of 301 accessions. These previously untyped loci could be imputed with around 90% accuracy. Finally, we used the 100K SNP dataset (GBS + SoySNP50K) to perform a GWAS on seed oil content within this collection of soybean accessions. Both the number of significant marker-trait associations and the peak significance levels were improved considerably using this enhanced catalog of SNPs relative to a smaller catalog resulting from GBS alone at 20% missing data. Our results demonstrate that imputation can be used to fill in both missing genotypes and untyped loci with very high accuracy and that this leads to more powerful genetic analyses

A multilevel analysis on the relationship between neighbourhood poverty and public hospital utilization: is the high Indigenous morbidity avoidable?

<p>Abstract</p> <p>Background</p> <p>The estimated life expectancy at birth for Indigenous Australians is 10-11 years less than the general Australian population. The mean family income for Indigenous people is also significantly lower than for non-Indigenous people. In this paper we examine poverty or socioeconomic disadvantage as an explanation for the Indigenous health gap in hospital morbidity in Australia.</p> <p>Methods</p> <p>We utilised a cross-sectional and ecological design using the Northern Territory public hospitalisation data from 1 July 2004 to 30 June 2008 and socio-economic indexes for areas (SEIFA) from the 2006 census. Multilevel logistic regression models were used to estimate odds ratios and confidence intervals. Both total and potentially avoidable hospitalisations were investigated.</p> <p>Results</p> <p>This study indicated that lifting SEIFA scores for family income and education/occupation by two quintile categories for low socio-economic Indigenous groups was sufficient to overcome the excess hospital utilisation among the Indigenous population compared with the non-Indigenous population. The results support a reframing of the Indigenous health gap as being a consequence of poverty and not simplistically of ethnicity.</p> <p>Conclusions</p> <p>Socio-economic disadvantage is a likely explanation for a substantial proportion of the hospital morbidity gap between Indigenous and non-Indigenous populations. Efforts to improve Indigenous health outcomes should recognise poverty as an underlying determinant of the health gap.</p

Effects of the 5-HT2C receptor agonist meta-chlorophenylpiperazine on appetite, food intake and emotional processing in healthy volunteers

RATIONALE: The treatment of obesity is an increasing global health priority, yet few effective drug treatments are currently available. The discovery of novel anti-obesity therapies could be assisted by the validation of experimental (translational) medicine models in healthy volunteers that assess efficacy and safety at an early stage of drug development. OBJECTIVES: The aim of this study was to examine the effects of the 5-HT2C receptor agonist meta-chlorophenylpiperazine (mCPP) in an experimental medicine model assessing both appetite and mood. METHODS: Using a between-subjects, double-blind, placebo-controlled design, 24 male and 24 female participants were randomly assigned to either placebo, 15- or 30-mg mCPP treatment groups. Lunch was eaten from a Universal Eating Monitor (UEM) that measured eating rate, and the participants completed the P1vital® Oxford Emotional Test Battery (ETB) and a series of appetite and mood ratings. RESULTS: mCPP reduced appetite and, in women, enhanced measures of satiation. The drug also enhanced memory for emotional material in the word recall and recognition memory tasks of the ETB. CONCLUSIONS: The results provide new insight into the effects of mCPP on appetite, satiety and memory in humans. In addition, our data provide an illustration of the value of measuring changes in appetite and mood in healthy volunteers to determine the potential efficacy and safety of novel anti-obesity drugs