Association between colony-stimulating factor 1 receptor gene polymorphisms and asthma risk

Colony-stimulating factor 1 receptor (CSF1R) is expressed in monocytes/macrophages and dendritic cells. These cells play important roles in the innate immune response, which is regarded as an important aspect of asthma development. Genetic alterations in the CSF1R gene may contribute to the development of asthma. We investigated whether CSF1R gene polymorphisms were associated with the risk of asthma. Through direct DNA sequencing of the CSF1R gene, we identified 28 single nucleotide polymorphisms (SNPs) and genotyped them in 303 normal controls and 498 asthmatic patients. Expression of CSF1R protein and mRNA were measured on CD14-positive monocytes and neutrophils in peripheral blood of asthmatic patients using flow cytometry and real-time PCR. Among the 28 polymorphisms, two intronic polymorphism (+20511C>T and +22693T>C) were associated with the risk of asthma by logistic regression analysis. The frequencies of the minor allele at CSF1R +20511C>T and +22693T>C were higher in asthmatic subjects than in normal controls (4.6 vs. 7.7%, p = 0.001 in co-dominant and dominant models; 16.4 vs. 25.8%, p = 0.0006 in a recessive model). CSF1R mRNA levels in neutrophils of the asthmatic patients having the +22693CC allele were higher than in those having the +22693TT allele (p = 0.026). Asthmatic patients with the +22693CC allele also showed significantly higher CSF1R expression on CD14-positive monocytes and neutrophils than did those with the +22693TT allele (p = 0.045 and p = 0.044). The +20511C>T SNP had no association with CSF1R mRNA or protein expression. In conclusion, the minor allele at CSF1R +22693T>C may have a susceptibility effect in the development of asthma, via increased CSF1R protein and mRNA expression in inflammatory cells

Clinical Model for NASH and Advanced Fibrosis in Adult Patients With Diabetes and NAFLD: Guidelines for Referral in NAFLD.

ObjectiveApproximately 18 million people in the U.S. have coexisting type 2 diabetes and nonalcoholic fatty liver disease (NAFLD). It is not known who among these patients has nonalcoholic steatohepatitis (NASH) with advanced fibrosis. Therefore, we aimed to determine factors that are associated with both NASH and advanced fibrosis in patients with diabetes and NAFLD in order to identify who should be prioritized for referral to a hepatologist for further diagnostic evaluation and treatment.Research design and methodsThis study was derived from the NASH Clinical Research Network studies and included 1,249 patients with biopsy-proven NAFLD (including a model development cohort of 346 patients and an independent validation cohort of 100 patients with type 2 diabetes as defined by the American Diabetes Association criteria). Outcome measures were presence of NASH or advanced fibrosis (stage 3 or 4) using cross-validated, by jackknife method, multivariable-adjusted area under the receiver operating characteristic curve (AUROC) and 95% CI.ResultsThe mean ± SD age and BMI of patients with diabetes and NAFLD was 52.5 ± 10.3 years and 35.8 ± 6.8 kg/m(2), respectively. The prevalence of NASH and advanced fibrosis was 69.2% and 41.0%, respectively. The model for NASH included white race, BMI, waist, alanine aminotransferase (ALT), Aspartate aminotransferase (AST), albumin, HbA1c, HOMA of insulin resistance, and ferritin with an AUROC of 0.80 (95% CI 0.75-0.84, P = 0.007). The specificity, sensitivity, negative predictive values (NPVs), and positive predictive values (PPVs) were 90.0%, 56.8%, 47.7%, and 93.2%, respectively, and the model correctly classified 67% of patients as having NASH. The model for predicting advanced fibrosis included age, Hispanic ethnicity, BMI, waist-to-hip ratio, hypertension, ALT-to-AST ratio, alkaline phosphatase, isolated abnormal alkaline phosphatase, bilirubin (total and direct), globulin, albumin, serum insulin, hematocrit, international normalized ratio, and platelet count with an AUROC of 0.80 (95% CI 0.76-0.85, P < 0.001). The specificity, sensitivity, NPV, and PPV were 90.0%, 57%, 75.1%, and 80.2%, respectively, and the model correctly classified 76.6% of patients as having advanced fibrosis. Results remained consistent for both models in the validation cohort. The proposed model performed better than the NAFLD fibrosis score in detecting advanced fibrosis.ConclusionsRoutinely available clinical variables can be used to quantify the likelihood of NASH or advanced fibrosis in adult diabetic patients with NAFLD. The clinical models presented can be used to guide clinical decision making about referrals of patients with diabetes and NAFLD to hepatologists

Clinical Model for NASH and Advanced Fibrosis in Adult Patients With Diabetes and NAFLD: Guidelines for Referral in NAFLD

OBJECTIVE: Approximately 18 million people in the U.S. have coexisting type 2 diabetes and nonalcoholic fatty liver disease (NAFLD). It is not known who among these patients has nonalcoholic steatohepatitis (NASH) with advanced fibrosis. Therefore, we aimed to determine factors that are associated with both NASH and advanced fibrosis in patients with diabetes and NAFLD in order to identify who should be prioritized for referral to a hepatologist for further diagnostic evaluation and treatment. RESEARCH DESIGN AND METHODS: This study was derived from the NASH Clinical Research Network studies and included 1,249 patients with biopsy-proven NAFLD (including a model development cohort of 346 patients and an independent validation cohort of 100 patients with type 2 diabetes as defined by the American Diabetes Association criteria). Outcome measures were presence of NASH or advanced fibrosis (stage 3 or 4) using cross-validated, by jackknife method, multivariable-adjusted area under the receiver operating characteristic curve (AUROC) and 95% CI. RESULTS: The mean ± SD age and BMI of patients with diabetes and NAFLD was 52.5 ± 10.3 years and 35.8 ± 6.8 kg/m(2), respectively. The prevalence of NASH and advanced fibrosis was 69.2% and 41.0%, respectively. The model for NASH included white race, BMI, waist, alanine aminotransferase (ALT), Aspartate aminotransferase (AST), albumin, HbA(1c), HOMA of insulin resistance, and ferritin with an AUROC of 0.80 (95% CI 0.75–0.84, P = 0.007). The specificity, sensitivity, negative predictive values (NPVs), and positive predictive values (PPVs) were 90.0%, 56.8%, 47.7%, and 93.2%, respectively, and the model correctly classified 67% of patients as having NASH. The model for predicting advanced fibrosis included age, Hispanic ethnicity, BMI, waist-to-hip ratio, hypertension, ALT-to-AST ratio, alkaline phosphatase, isolated abnormal alkaline phosphatase, bilirubin (total and direct), globulin, albumin, serum insulin, hematocrit, international normalized ratio, and platelet count with an AUROC of 0.80 (95% CI 0.76–0.85, P < 0.001). The specificity, sensitivity, NPV, and PPV were 90.0%, 57%, 75.1%, and 80.2%, respectively, and the model correctly classified 76.6% of patients as having advanced fibrosis. Results remained consistent for both models in the validation cohort. The proposed model performed better than the NAFLD fibrosis score in detecting advanced fibrosis. CONCLUSIONS: Routinely available clinical variables can be used to quantify the likelihood of NASH or advanced fibrosis in adult diabetic patients with NAFLD. The clinical models presented can be used to guide clinical decision making about referrals of patients with diabetes and NAFLD to hepatologists