Characterization of the Multiple Conformational States of Free Monomeric and Trimeric Human Immunodeficiency Virus Envelope Glycoproteins after Fixation by Cross-Linker

The human immunodeficiency virus type 1 (HIV-1) gp120 exterior and gp41 transmembrane envelope glycoproteins assemble into trimers on the virus surface that represent potential targets for antibodies. Potent neutralizing antibodies bind the monomeric gp120 glycoprotein with small changes in entropy, whereas unusually large decreases in entropy accompany gp120 binding by soluble CD4 and less potent neutralizing antibodies. The high degree of conformational flexibility in the free gp120 molecule implied by these observations has been suggested to contribute to masking the trimer from antibodies that recognize the gp120 receptor-binding regions. Here we use cross-linking and recognition by antibodies to investigate the conformational states of gp120 monomers and soluble and cell surface forms of the trimeric HIV-1 envelope glycoproteins. The fraction of monomeric and trimeric envelope glycoproteins able to be recognized after fixation was inversely related to the entropic changes associated with ligand binding. In addition, fixation apparently limited the access of antibodies to the V3 loop and gp41-interactive surface of gp120 only in the context of trimeric envelope glycoproteins. The results support a model in which the unliganded monomeric and trimeric HIV-1 envelope glycoproteins sample several different conformations. Depletion of particular fixed conformations by antibodies allowed characterization of the relationships among the conformational states. Potent neutralizing antibodies recognize the greatest number of conformations and therefore can bind the virion envelope glycoproteins more rapidly and completely than weakly neutralizing antibodies. Thus, the conformational flexibility of the HIV-1 envelope glycoproteins creates thermodynamic and kinetic barriers to neutralization by antibodies directed against the receptor-binding regions of gp120

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