Project description:Even though autoimmune diseases are heterogeneous, believed to result from the interaction between genetic and environmental components, patients with these disorders exhibit reproducible patterns of gene expression in their peripheral blood mononuclear cells. A portion of this gene expression profile reflects family resemblance rather than the actual presence of an autoimmune disease. Here we wanted to identify that portion of this gene expression pattern that is independent of family resemblance and determine if it is a product of disease duration, disease onset, or other factors. By increasing the number of autoimmune samples in our analysis and employing supervised clustering algorithms, we identified 100 genes whose expression profiles are shared in individuals with various autoimmune diseases but are not shared by first-degree relatives of individuals with autoimmune disease or by controls. Individuals with early disease (1 yr after onset) and established disease (10 yr after onset) exhibit a near identical expression pattern suggesting that this unique profile reflects disease onset rather than disease duration. supervised gene expression profiling were performed to a cohort sample pool: control individuals(8), unaffected family members of autoimmune diseases patients (8), and individuals with autoimmune diseases (54). we try to identify a gene expression signatures that were exclusively associated with autoimmune diseases but not infulenced by genetic components
Project description:Patients with autoimmune disorders exhibit highly reproducible gene expression profiles in their peripheral blood mononuclear cells. These signatures may result from chronic inflammation, other disease manifestations, or may reflect family resemblance. To test the latter hypothesis, we determined gene expression profiles in unaffected first-degree relatives of individuals with autoimmune disease. Gene expression profiles in unaffected first-degree relatives resembled the profiles found in individuals with autoimmune diseases. A high percentage of differentially expressed genes in unaffected first-degree relatives were previously identified as autoimmune signature genes. Examination of the linear regression relationship of gene transcript levels between parent-offspring pairs revealed that autoimmune signature genes display high levels of family resemblance. Taken together, these results support the hypothesis that these variations in gene transcript levels are associated with family resemblance rather than clinical manifestations of disease. Gene expression profiling of autoimmune families
Project description:Patients with autoimmune disorders exhibit highly reproducible gene expression profiles in their peripheral blood mononuclear cells. These signatures may result from chronic inflammation, other disease manifestations, or may reflect family resemblance. To test the latter hypothesis, we determined gene expression profiles in unaffected first-degree relatives of individuals with autoimmune disease. Gene expression profiles in unaffected first-degree relatives resembled the profiles found in individuals with autoimmune diseases. A high percentage of differentially expressed genes in unaffected first-degree relatives were previously identified as autoimmune signature genes. Examination of the linear regression relationship of gene transcript levels between parent-offspring pairs revealed that autoimmune signature genes display high levels of family resemblance. Taken together, these results support the hypothesis that these variations in gene transcript levels are associated with family resemblance rather than clinical manifestations of disease. Keywords: Gene expression profiling
Project description:Transcriptional profiling of Homo sapiens inflammatory skin diseases (whole skin biospies): Psoriasis (Pso), vs Atopic Dermatitis (AD) vs Lichen planus (Li), vs Contact Eczema (KE), vs Healthy control (KO) In recent years, different genes and proteins have been highlighted as potential biomarkers for psoriasis, one of the most common inflammatory skin diseases worldwide. However, most of these markers are not psoriasis-specific but also found in other inflammatory disorders. We performed an unsupervised cluster analysis of gene expression profiles in 150 psoriasis patients and other inflammatory skin diseases (atopic dermatitis, lichen planus, contact eczema, and healthy controls). We identified a cluster of IL-17/TNFα-associated genes specifically expressed in psoriasis, among which IL-36γ was the most outstanding marker. In subsequent immunohistological analyses IL-36γ was confirmed to be expressed in psoriasis lesions only. IL-36γ peripheral blood serum levels were found to be closely associated with disease activity, and they decreased after anti-TNFα-treatment. Furthermore, IL-36γ immunohistochemistry was found to be a helpful marker in the histological differential diagnosis between psoriasis and eczema in diagnostically challenging cases. These features highlight IL-36γ as a valuable biomarker in psoriasis patients, both for diagnostic purposes and measurement of disease activity during the clinical course. Furthermore, IL-36γ might also provide a future drug target, due to its potential amplifier role in TNFα- and IL-17 pathways in psoriatic skin inflammation. In recent years, different genes and proteins have been highlighted as potential biomarkers for psoriasis, one of the most common inflammatory skin diseases worldwide. However, most of these markers are not psoriasis-specific but also found in other inflammatory disorders. We performed an unsupervised cluster analysis of gene expression profiles in 150 psoriasis patients and other inflammatory skin diseases (atopic dermatitis, lichen planus, contact eczema, and healthy controls). We identified a cluster of IL-17/TNFα-associated genes specifically expressed in psoriasis, among which IL-36γ was the most outstanding marker. In subsequent immunohistological analyses IL-36γ was confirmed to be expressed in psoriasis lesions only. IL-36γ peripheral blood serum levels were found to be closely associated with disease activity, and they decreased after anti-TNFα-treatment. Furthermore, IL-36γ immunohistochemistry was found to be a helpful marker in the histological differential diagnosis between psoriasis and eczema in diagnostically challenging cases. These features highlight IL-36γ as a valuable biomarker in psoriasis patients, both for diagnostic purposes and measurement of disease activity during the clinical course. Furthermore, IL-36γ might also provide a future drug target, due to its potential amplifier role in TNFα- and IL-17 pathways in psoriatic skin inflammation.