[show abstract][hide abstract] ABSTRACT: To determine the relative contributions of genetic, clinical, serologic, sociodemographic, and behavioral/psychological variables to early pulmonary involvement in the Genetics versus Environment in Scleroderma Outcome Study cohort.
At the baseline visit (V0), 203 patients with systemic sclerosis (SSc) were examined (104 whites, 39 African Americans, and 60 Hispanics). We obtained sociodemographic, behavioral/psychological (illness behavior, social support, learned helplessness, smoking, drinking), clinical, serologic (autoantibodies), and genetic (HLA class II and FBN1 genotypes) factors; pulmonary function test results; electrocardiograms; and chest radiographs. Data analysis included Fisher's exact test, chi-square test, Student's t-test, analysis of variance, and stepwise linear and logistic regression methods.
Significant pulmonary involvement was seen in 25% of patients within 2.8 years of SSc diagnosis. At V0, pulmonary fibrosis was significantly higher in African Americans compared with whites or Hispanics. African Americans had significantly lower percent predicted forced vital capacity (FVC) and forced expiratory volume in 1 second (FEV(1)) compared with whites and significantly lower percent predicted diffusing capacity for carbon monoxide (DLCO) compared with whites and Hispanics. Significant, independent associations impacting early pulmonary involvement included African American ethnicity, skin score, serum creatinine and creatine phosphokinase values, hypothyroidism, and cardiac involvement. Anticentromere antibody seropositivity was a significant, independent, protective factor for restrictive lung disease and FVC or DLCO values. African Americans had significantly increased frequencies of anti-topoisomerase I, fibrillarin, and RNP autoantibodies compared with whites. African Americans scored significantly lower on the Interpersonal Support Evaluation List and significantly higher on the Illness Behavior Questionnaire.
Early pulmonary involvement in SSc appears to be influenced by several factors delineated by ethnicity, including racial, socioeconomic, behavioral, and serologic determinants.
[show abstract][hide abstract] ABSTRACT: Fewer than 5% of monozygotic (MZ) and dizygotic (DZ) twin pairs are clinically concordant for systemic sclerosis (SSc), yet the majority of MZ twins are concordant for antinuclear antibodies. To discover genetic versus nongenetic molecular pathways important to the pathogenesis of SSc, we compared global gene expression patterns in twins discordant for SSc.
Total RNA from dermal fibroblasts of 15 discordant twin pairs (10 MZ and 5 DZ) and 5 normal controls were used in microarray analysis. Aberrantly expressed genes were confirmed using quantitative real-time reverse transcriptase-polymerase chain reaction.
Lesional and nonlesional fibroblasts from SSc patients showed no significant differences in gene expression, while SSc patients had gene profiles that were significantly different from those of unaffected DZ twins and normal controls. Unaffected MZ twins, however, were not significantly different from SSc patients. Unsupervised hierarchical clustering segregated the fibroblast samples as originating from 2 major groups. Group A contained 5 discordant MZ twin pairs, 3 affected MZ twins, and 3 affected DZ twins. Group B contained all 5 normal population controls, all 5 healthy DZ twins, 2 discordant MZ twins, and 2 discordant DZ twin pairs. Normal fibroblasts incubated with serum from an SSc-affected patient or with serum from her unaffected MZ twin sister developed the increased expression of COL1A2, SPARC, and CTGF typically seen in SSc fibroblasts.
These results demonstrate that dermal fibroblasts from SSc patients and from 40-50% of their genetically identical but clinically unaffected MZ twins exhibit a similar gene expression pattern which can be induced in normal fibroblasts by sera from both. Thus, a stronger genetic predisposition to SSc (than can be detected clinically) is apparent at the molecular level in skin fibroblasts.
[show abstract][hide abstract] ABSTRACT: Revealing mechanisms underlying complex diseases poses great challenges to biologists. The traditional linkage and linkage disequilibrium analysis that have been successful in the identification of genes responsible for Mendelian traits, however, have not led to similar success in discovering genes influencing the development of complex diseases. Emerging functional genomic and proteomic ('omic') resources and technologies provide great opportunities to develop new methods for systematic identification of genes underlying complex diseases. In this report, we propose a systems biology approach, which integrates omic data, to find genes responsible for complex diseases. This approach consists of five steps: (1) generate a set of candidate genes using gene-gene interaction data sets; (2) reconstruct a genetic network with the set of candidate genes from gene expression data; (3) identify differentially regulated genes between normal and abnormal samples in the network; (4) validate regulatory relationship between the genes in the network by perturbing the network using RNAi and monitoring the response using RT-PCR; and (5) genotype the differentially regulated genes and test their association with the diseases by direct association studies. To prove the concept in principle, the proposed approach is applied to genetic studies of the autoimmune disease scleroderma or systemic sclerosis.