The Maristán stigma scale: a standardized international measure of the stigma of schizophrenia and other psychoses

Background: People with schizophrenia face prejudice and discrimination from a number of sources including professionals and families. The degree of stigma perceived and experienced varies across cultures and communities. We aimed to develop a cross-cultural measure of the stigma perceived by people with schizophrenia.Method: Items for the scale were developed from qualitative group interviews with people with schizophrenia in six countries. The scale was then applied in face-to-face interviews with 164 participants, 103 of which were repeated after 30 days. Principal Axis Factoring and Promax rotation evaluated the structure of the scale; Horn’s parallel combined with bootstrapping determined the number of factors; and intra-class correlation assessed test-retest reliability.Results: The final scale has 31 items and four factors: informal social networks, socio-institutional, health professionals and self-stigma. Cronbach’s alpha was 0.84 for the Factor 1; 0.81 for Factor 2; 0.74 for Factor 3, and 0.75 for Factor 4. Correlation matrix among factors revealed that most were in the moderate range [0.31-0.49], with the strongest occurring between perception of stigma in the informal network and self-stigma and there was also a weaker correlation between stigma from health professionals and self-stigma. Test-retest reliability was highest for informal networks [ICC 0.76 [0.67 -0.83]] and self-stigma [ICC 0.74 [0.64-0.81]]. There were no significant differences in the scoring due to sex or age. Service users in Argentina had the highest scores in almost all dimensions.Conclusions: The MARISTAN stigma scale is a reliable measure of the stigma of schizophrenia and related psychoses across several cultures. A confirmatory factor analysis is needed to assess the stability of its factor structure.We are also grateful for support from the Pan-American Health Office (PAHO), Camden and Islington NHS Foundation Trust and University College London (UCL)

Replication of TCF4 through Association and Linkage Studies in Late-Onset Fuchs Endothelial Corneal Dystrophy

Fuchs endothelial corneal dystrophy (FECD) is a common, late-onset disorder of the corneal endothelium. Although progress has been made in understanding the genetic basis of FECD by studying large families in which the phenotype is transmitted in an autosomal dominant fashion, a recently reported genome-wide association study identified common alleles at a locus on chromosome 18 near TCF4 which confer susceptibility to FECD. Here, we report the findings of our independent validation study for TCF4 using the largest FECD dataset to date (450 FECD cases and 340 normal controls). Logistic regression with sex as a covariate was performed for three genetic models: dominant (DOM), additive (ADD), and recessive (REC). We found significant association with rs613872, the target marker reported by Baratz et al.(2010), for all three genetic models (DOM: P = 9.33×10−35; ADD: P = 7.48×10−30; REC: P = 5.27×10−6). To strengthen the association study, we also conducted a genome-wide linkage scan on 64 multiplex families, composed primarily of affected sibling pairs (ASPs), using both parametric and non-parametric two-point and multipoint analyses. The most significant linkage region localizes to chromosome 18 from 69.94cM to 85.29cM, with a peak multipoint HLOD = 2.5 at rs1145315 (75.58cM) under the DOM model, mapping 1.5 Mb proximal to rs613872. In summary, our study presents evidence to support the role of the intronic TCF4 single nucleotide polymorphism rs613872 in late-onset FECD through both association and linkage studies

Genome Wide Analysis of Inbred Mouse Lines Identifies a Locus Containing Ppar-γ as Contributing to Enhanced Malaria Survival

The genetic background of a patient determines in part if a person develops a mild form of malaria and recovers, or develops a severe form and dies. We have used a mouse model to detect genes involved in the resistance or susceptibility to Plasmodium berghei malaria infection. To this end we first characterized 32 different mouse strains infected with P. berghei and identified survival as the best trait to discriminate between the strains. We found a locus on chromosome 6 by linking the survival phenotypes of the mouse strains to their genetic variations using genome wide analyses such as haplotype associated mapping and the efficient mixed-model for association. This new locus involved in malaria resistance contains only two genes and confirms the importance of Ppar-γ in malaria infection

Bioinformatic analyses identifies novel protein-coding pharmacogenomic markers associated with paclitaxel sensitivity in NCI60 cancer cell lines

<p>Abstract</p> <p>Background</p> <p>Paclitaxel is a microtubule-stabilizing drug that has been commonly used in treating cancer. Due to genetic heterogeneity within patient populations, therapeutic response rates often vary. Here we used the NCI60 panel to identify SNPs associated with paclitaxel sensitivity. Using the panel's GI50 response data available from Developmental Therapeutics Program, cell lines were categorized as either sensitive or resistant. PLINK software was used to perform a genome-wide association analysis of the cellular response to paclitaxel with the panel's SNP-genotype data on the Affymetrix 125 k SNP array. FastSNP software helped predict each SNP's potential impact on their gene product. mRNA expression differences between sensitive and resistant cell lines was examined using data from BioGPS. Using Haploview software, we investigated for haplotypes that were more strongly associated with the cellular response to paclitaxel. Ingenuity Pathway Analysis software helped us understand how our identified genes may alter the cellular response to paclitaxel.</p> <p>Results</p> <p>43 SNPs were found significantly associated (FDR < 0.005) with paclitaxel response, with 10 belonging to protein-coding genes (<it>CFTR</it>, <it>ROBO1</it>, <it>PTPRD</it>, <it>BTBD12</it>, <it>DCT</it>, <it>SNTG1</it>, <it>SGCD</it>, <it>LPHN2</it>, <it>GRIK1</it>, <it>ZNF607</it>). SNPs in <it>GRIK1</it>, <it>DCT</it>, <it>SGCD </it>and <it>CFTR </it>were predicted to be intronic enhancers, altering gene expression, while SNPs in <it>ZNF607 </it>and <it>BTBD12 </it>cause conservative missense mutations. mRNA expression analysis supported these findings as <it>GRIK1</it>, <it>DCT</it>, <it>SNTG1</it>, <it>SGCD </it>and <it>CFTR </it>showed significantly (p < 0.05) increased expression among sensitive cell lines. Haplotypes found in <it>GRIK1, SGCD, ROBO1, LPHN2</it>, and <it>PTPRD </it>were more strongly associated with response than their individual SNPs.</p> <p>Conclusions</p> <p>Our study has taken advantage of available genotypic data and its integration with drug response data obtained from the NCI60 panel. We identified 10 SNPs located within protein-coding genes that were not previously shown to be associated with paclitaxel response. As only five genes showed differential mRNA expression, the remainder would not have been detected solely based on expression data. The identified haplotypes highlight the role of utilizing SNP combinations within genomic loci of interest to improve the risk determination associated with drug response. These genetic variants represent promising biomarkers for predicting paclitaxel response and may play a significant role in the cellular response to paclitaxel.</p