Polymorphism analysis of the CTLA-4 gene in paracoccidioidomycosis patients

The CTLA-4 protein is expressed in activated T cells and plays an essential role in the immune response through its regulatory effect on T cell activation. Polymorphisms of the CTLA-4 gene have been correlated with autoimmune, neoplastic and infectious illnesses. This work aimed to verify possible associations between single nucleotide polymorphisms (SNPs) in CTLA-4, -318C/T in the promoter and +49A/G in exon 1 and paracoccidioidomycosis (PCM) caused by Paracoccidioides brasiliensis. For this purpose, 66 chronic form PCM patients and 76 healthy controls had their allele, genotype and haplotype frequencies determined. The genetic admixture structure of the patients and controls was evaluated to eliminate ancestral bias. The comparison of frequencies indicated no significant differences between patients and controls that could link the SNPs to PCM. Groups were admixture matched with no difference observed in population ancestry inference, indicating that the absence of association between CTLA-4 polymorphisms and PCM could not be attributed to ancestral bias. This study showed that there was no association between the CTLA-4 SNPs -318 and +49 and the resistance or susceptibility to PCM

Co-Housing Rodents with Different Coat Colours as a Simple, Non-Invasive Means of Individual Identification:Validating Mixed-Strain Housing for C57BL/6 and DBA/2 Mice

Standard practice typically requires the marking of laboratory mice so that they can be individually identified. However, many of the common methods compromise the welfare of the individuals being marked (as well as requiring time, effort, and/or resources on the part of researchers and technicians). Mixing strains of different colour within a cage would allow them to be readily visually identifiable, negating the need for more invasive marking techniques. Here we assess the impact that mixed strain housing has on the phenotypes of female C57BL/6 (black) and DBA/2 (brown) mice, and on the variability in the data obtained from them. Mice were housed in either mixed strain or single strain pairs for 19 weeks, and their phenotypes then assessed using 23 different behavioural, morphological, haematological and physiological measures widely used in research and/or important for assessing mouse welfare. No negative effects of mixed strain housing could be found on the phenotypes of either strain, including variables relevant to welfare. Differences and similarities between the two strains were almost all as expected from previously published studies, and none were affected by whether mice were housed in mixed- or single-strain pairs. Only one significant main effect of housing type was detected: mixed strain pairs had smaller red blood cell distribution widths, a measure suggesting better health (findings that now need replicating in case they were Type 1 errors resulting from our multiplicity of tests). Furthermore, mixed strain housing did not increase the variation in data obtained from the mice: the standard errors for all variables were essentially identical between the two housing conditions. Mixed strain housing also made animals very easy to distinguish while in the home cage. Female DBA/2 and C57BL/6 mice can thus be housed in mixed strain pairs for identification purposes, with no apparent negative effects on their welfare or the data they generate. This suggests that there is much value in exploring other combinations of strains

Evidence of causal effect of major depression on alcohol dependence: findings from the psychiatric genomics consortium

BACKGROUND Despite established clinical associations among major depression (MD), alcohol dependence (AD), and alcohol consumption (AC), the nature of the causal relationship between them is not completely understood. We leveraged genome-wide data from the Psychiatric Genomics Consortium (PGC) and UK Biobank to test for the presence of shared genetic mechanisms and causal relationships among MD, AD, and AC. METHODS Linkage disequilibrium score regression and Mendelian randomization (MR) were performed using genome-wide data from the PGC (MD: 135 458 cases and 344 901 controls; AD: 10 206 cases and 28 480 controls) and UK Biobank (AC-frequency: 438 308 individuals; AC-quantity: 307 098 individuals). RESULTS Positive genetic correlation was observed between MD and AD (rgMD−AD = + 0.47, P = 6.6 × 10−10). AC-quantity showed positive genetic correlation with both AD (rgAD−AC quantity = + 0.75, P = 1.8 × 10−14) and MD (rgMD−AC quantity = + 0.14, P = 2.9 × 10−7), while there was negative correlation of AC-frequency with MD (rgMD−AC frequency = −0.17, P = 1.5 × 10−10) and a non-significant result with AD. MR analyses confirmed the presence of pleiotropy among these four traits. However, the MD-AD results reflect a mediated-pleiotropy mechanism (i.e. causal relationship) with an effect of MD on AD (beta = 0.28, P = 1.29 × 10−6). There was no evidence for reverse causation. CONCLUSION This study supports a causal role for genetic liability of MD on AD based on genetic datasets including thousands of individuals. Understanding mechanisms underlying MD-AD comorbidity addresses important public health concerns and has the potential to facilitate prevention and intervention efforts

Integrated analysis of environmental and genetic influences on cord blood DNA methylation in new-borns

Epigenetic processes, including DNA methylation (DNAm), are among the mechanisms allowing integration of genetic and environmental factors to shape cellular function. While many studies have investigated either environmental or genetic contributions to DNAm, few have assessed their integrated effects. Here we examine the relative contributions of prenatal environmental factors and genotype on DNA methylation in neonatal blood at variably methylated regions (VMRs) in 4 independent cohorts (overall n = 2365). We use Akaike’s information criterion to test which factors best explain variability of methylation in the cohort-specific VMRs: several prenatal environmental factors (E), genotypes in cis (G), or their additive (G + E) or interaction (GxE) effects. Genetic and environmental factors in combination best explain DNAm at the majority of VMRs. The CpGs best explained by either G, G + E or GxE are functionally distinct. The enrichment of genetic variants from GxE models in GWAS for complex disorders supports their importance for disease ris