Depressive symptoms in schizophrenic patients

Distinction between true negative and depressive symptoms in schizophrenia is difficult. In the present study we seek to establish the psychological profile of depression-prone schizophrenic patients. We addressed the issue by comparing the expression of psychological indices, such as the feelings of being in control of events, anxiety, mood, and the style of coping with stress in depressive and non-depressive schizophrenics. We also analyzed the strength of the association of these indices with the presence of depressive symptoms. A total of 49 patients (18 women and 31 men, aged 23-59) were enrolled into the study, consisting of a self-reported psychometric survey. We found that the prevalence of clinically significant depression in schizophrenic patients was 61%. The factors which contributed to the intensification of depressive symptoms were the external locus of control, anxiety, gloomy mood, and the emotion-oriented coping with stress. We conclude that psychological testing may discern those schizophrenic patients who would be at risk of depression development and may help separate the blurred boundaries between depressive and negative symptoms of schizophrenia

Confidence set of putative quantitative trait loci in whole genome scans with application to the Genetic Analysis Workshop 17 simulated data

As genetic maps become more highly dense, the ability to sufficiently localize putative disease loci becomes an achievable goal. This has prompted an increased interest in methods for constructing confidence intervals for the location of variants that contribute to a trait. Such intervals are important because, by reducing the number of candidate loci, they can help in the design of cost-effective and time-efficient follow-up studies. We introduce a new approach that can be used in whole-genome scans to obtain a confidence set of loci that contribute at least a predetermined percentage h to the overall genetic variation of a quantitative phenotype. The method is developed in the framework of generalized linear mixed models and can accommodate families of arbitrary size and structure. We apply our method to the Genetic Analysis Workshop 17 simulated data where we scan chromosomes 6, 15, 20, 21, and 22 to uncover loci regulating the simulated phenotype Q2. For the analyses we had prior knowledge of the simulation model used to generate the phenotype

Effective conductivity in association with model structure and spatial inhomogeneity of polymer/carbon black composites

The relationship between effective conductivity and cell structure of polyethylene/carbon composites as well as between effective conductivity and spatial distribution of carbon black are discussed. Following Yoshida's model both structures can, in a way, be said to be intermediate between the well known Maxwell-Garnett (MG) and Bruggeman (BR) limiting structures. Using TEM photographs on composites with various carbon blacks we have observed that the larger is Garncarek's inhomogeneity measure H of two-dimensional (2D) representative distribution of the carbon black, the smaller is the effective conductivity of the composite.Comment: 7 pages, 9 figure

Dietary carbohydrate modifies the inverse association between saturated fat intake and cholesterol on very low-density lipoproteins

We aimed to investigate the relationship between dietary saturated fat on fasting triglyceride (TG) and cholesterol levels, and any mediation of this relationship by dietary carbohydrate intake. Men and women in the NHLBI Genetics of Lipid-Lowering Drugs and Diet Network (GOLDN) study (n = 1036, mean age ± SD = 49 ± 16 y) were included. Mixed linear models were run with saturated fat as a predictor variable and fasting TG, very low density lipoprotein cholesterol (VLDL-C), low density cholesterol (LDL-C) and high density cholesterol (HDL-C) as separate outcome variables. Subsequent models were run which included dietary carbohydrate as a predictor variable, and an interaction term between saturated fat and carbohydrate. All models controlled for age, sex, BMI, blood pressure and dietary covariates. In models that included only saturated fat as a predictor, saturated fat did not show significant associations with fasting lipids. When carbohydrate intake and an interaction term between carbohydrates and saturated fat intake was included, carbohydrate intake did not associate with lipids, but there was an inverse relationship between saturated fat intake and VLDL-C (P = 0.01) with a significant interaction (P = 0.01) between saturated fat and carbohydrate with regard to fasting VLDL-C concentrations. Similar results were observed for fasting TG levels. We conclude that, when controlling for carbohydrate intake, higher saturated fat was associated with lower VLDL-C and TGs. This was not the case at higher intakes of carbohydrate. This has important implications for dietary advice aimed at reducing TG and VLDL-C levels

GSK3787-Loaded poly(Ester Amide) particles for intra-articular drug delivery

© 2020 by the authors. Osteoarthritis (OA) is a debilitating joint disorder affecting more than 240 million people. There is no disease modifying therapeutic, and drugs that are used to alleviate OA symptoms result in side effects. Recent research indicates that inhibition of peroxisome proliferator-activated receptor ffi (PPARffi) in cartilage may attenuate the development or progression of OA. PPARffi antagonists such as GSK3787 exist, but would benefit from delivery to joints to avoid side effects. Described here is the loading of GSK3787 into poly(ester amide) (PEA) particles. The particles contained 8 wt. % drug and had mean diameters of about 600 nm. Differential scanning calorimetry indicated the drug was in crystalline domains in the particles. Atomic force microscopy was used to measure the Young\u27s moduli of individual particles as 2.8 MPa. In vitro drug release studies showed 11% GSK3787 was released over 30 days. Studies in immature murine articular cartilage (IMAC) cells indicated low toxicity from the drug, empty particles, and drug-loaded particles and that the particles were not taken up by the cells. Ex vivo studies on murine joints showed that the particles could be injected into the joint space and resided there for at least 7 days. Overall, these results indicate that GSK3787-loaded PEA particles warrant further investigation as a delivery system for potential OA therapy

SNPs located at CpG sites modulate genome-epigenome interaction

DNA methylation is an important molecular-level phenotype that links genotypes and complex disease traits. Previous studies have found local correlation between genetic variants and DNA methylation levels (cis-meQTLs). However, general mechanisms underlying cis-meQTLs are unclear. We conducted a cis-meQTL analysis of the Genetics of Lipid Lowering Drugs and Diet Network data (n = 593). We found that over 80% of genetic variants at CpG sites (meSNPs) are meQTL loci (P-value < 10(−9)), and meSNPs account for over two thirds of the strongest meQTL signals (P-value < 10(−200)). Beyond direct effects on the methylation of the meSNP site, the CpG-disrupting allele of meSNPs were associated with lowered methylation of CpG sites located within 45 bp. The effect of meSNPs extends to as far as 10 kb and can contribute to the observed meQTL signals in the surrounding region, likely through correlated methylation patterns and linkage disequilibrium. Therefore, meSNPs are behind a large portion of observed meQTL signals and play a crucial role in the biological process linking genetic variation to epigenetic changes

Genetic analysis of long-lived families reveals novel variants influencing high density-lipoprotein cholesterol

The plasma levels of high-density lipoprotein cholesterol (HDL) have an inverse relationship to the risks of atherosclerosis and cardiovascular disease, and have also been associated with longevity. We sought to identify novel loci for HDL that could potentially provide new insights into biological regulation of HDL metabolism in healthy-longevous subjects. We performed a genome-wide association scan on HDL using a mixed model approach to account for family structure using kinship coefficients. A total of 4,114 subjects of European descent (480 families) were genotyped at ~2.3 million SNPs and ~38 million SNPs were imputed using the 1000 Genome Cosmopolitan reference panel in MACH. We identified novel variants near-NLRP1 (17p13) associated with an increase of HDL levels at genome-wide significant level (p< 5.0E-08). Additionally, several CETP (16q21) and ZNF259-APOA5-A4-C3-A1 (11q23.3) variants associated with HDL were found, replicating those previously reported in the literature. A possible regulatory variant upstream of NLRP1 that is associated with HDL in these elderly LLFS subjects may also contribute to their longevity and health. Our NLRP1 intergenic SNPs show a potential regulatory function in ENCODE; however, it is not clear whether they regulate NLRP1 or other more remote gene. NLRP1 plays an important role in the induction of apoptosis, and its inflammasome is critical for mediating innate immune responses. Nlrp1a (a mouse ortholog of human NLRP1) interacts with SREBP-1a (17p11) which has a fundamental role in lipid concentration and composition, and is involved in innate immune response in macrophages. The NLRP1 region is conserved in mammals, but also has evolved adaptively showing signals of positive selection in European populations that might confer an advantage. NLRP1 intergenic SNPs have also been associated with immunity/inflammasome disorders which highlights the biological importance of this chromosomal region

Genome-wide contribution of genotype by environment interaction to variation of diabetes-related traits

While genome-wide association studies (GWAS) and candidate gene approaches have identified many genetic variants that contribute to disease risk as main effects, the impact of genotype by environment (GxE) interactions remains rather under-surveyed. To explore the importance of GxE interactions for diabetes-related traits, a tool for Genome-wide Complex Trait Analysis (GCTA) was used to examine GxE variance contribution of 15 macronutrients and lifestyle to the total phenotypic variance of diabetes-related traits at the genome-wide level in a European American population. GCTA identified two key environmental factors making significant contributions to the GxE variance for diabetes-related traits: carbohydrate for fasting insulin (25.1% of total variance, P-nominal = 0.032) and homeostasis model assessment of insulin resistance (HOMA-IR) (24.2% of total variance, P-nominal = 0.035), n-6 polyunsaturated fatty acid (PUFA) for HOMA-β-cell-function (39.0% of total variance, P-nominal = 0.005). To demonstrate and support the results from GCTA, a GxE GWAS was conducted with each of the significant dietary factors and a control E factor (dietary protein), which contributed a non-significant GxE variance. We observed that GxE GWAS for the environmental factor contributing a significant GxE variance yielded more significant SNPs than the control factor. For each trait, we selected all significant SNPs produced from GxE GWAS, and conducted anew the GCTA to estimate the variance they contributed. We noted the variance contributed by these SNPs is higher than that of the control. In conclusion, we utilized a novel method that demonstrates the importance of genome-wide GxE interactions in explaining the variance of diabetes-related traits