The impact of population heterogeneity on risk estimation in genetic counseling

BACKGROUND: Genetic counseling has been an important tool for evaluating and communicating disease susceptibility for decades, and it has been applied to predict risks for a wide class of hereditary disorders. Most diseases are complex in nature and are affected by multiple genes and environmental conditions; it is highly likely that DNA tests alone do not define all the genetic factors responsible for a disease, so that persons classified into the same risk group by DNA testing actually could have different disease susceptibilities. Ignorance of population heterogeneity may lead to biased risk estimates, whereas additional information on population heterogeneity may improve the precision of such estimates. METHODS: Although DNA tests are widely used, few studies have investigated the accuracy of the predicted risks. We examined the impact of population heterogeneity on predicted disease risks by simulation of three different heterogeneity scenarios and studied the precision and accuracy of the risks estimated from a logistic regression model that ignored population heterogeneity. Moreover, we also incorporated information about population heterogeneity into our original model and investigated the resulting improvement in the accuracy of risk estimation. RESULTS: We found that heterogeneity in one or more categories could lead to biased estimates not only in the "contaminated" categories but also in other homogeneous categories. Incorporating information about population heterogeneity into the original model greatly improved the accuracy of risk estimation. CONCLUSIONS: Our findings imply that without thorough knowledge about genetic basis of the disease, risks estimated from DNA tests may be misleading. Caution should be taken when evaluating the predicted risks obtained from genetic counseling. On the other hand, the improved accuracy of risk estimates after incorporating population heterogeneity information into the model did point out a promising direction for genetic counseling, since more and more new techniques are being invented and disease etiology is being better understood

Identifying Risk Factors in Renal Allografts before Transplant: Machine-Measured Renal Resistance and Posttransplant Allograft Survival

Enhancement of renal allograft function and survival in an era where expanded criteria donors are increasingly used requires validated selection criteria. The goal of this retrospective study was to evaluate the significance of pretransplant donor and allograft parameters to identify risk factors that can be used in a model to predict 1-year allograft outcomes. Donor demographic factors, donor type, and allograft parameters such as biopsy results and machine-measured renal resistance were correlated with 1-year graft outcome. The Kaplan-Meier method was used to estimate graft survival using the categorical predictors of donor type, donor age, and machine-measured renal resistance at 1.5, 3, and 5 hours. The log-rank test was used to test the difference in survival curves between cohorts. The Cox regression analysis was used to estimate hazard ratios for machine-measured renal resistance, donor age, donor terminal creatinine level, donor's estimated glomerular filtration rate, cold ischemia time, and percent glomerulosclerosis. The data show that machine-measured renal resistance at 3 and 5 hours has a statistically significant inverse relationship to 1-year graft survival. All other risk factors had no correlation with 1-year graft survival. The machine-measured renal resistance at 3 hours is the earliest significant predictor of 1-year allograft outcome

Hemoglobin A lc

Aging, higher prevalence of diabetes, worsening obesity, and hyperglycemia among potential donors increase the likelihood that pancreata will be declined by transplant centers. Hemoglobin A1c testing, also known as glycated hemoglobin testing, identifies a donor's average blood glucose concentration for the preceding 2 to 3 months and is the standard test for identifying prolonged periods of hyperglycemia. To compare pancreas utilization rates before and after implementation of hemoglobin A1c testing. A retrospective study of data from the New York Organ Donor Network was conducted. Potential donors were defined as standard criteria donors who had no history of diabetes and were not seropositive for hepatitis B or C. Criteria for "ideal" potential pancreas donors were based on age, body mass index, lipase level, and terminal creatinine level. Potential donors who did not meet the criteria for ideal donors were considered "expanded" potential pancreas donors. Pancreas utilization rate was defined as the number of pancreata transplanted divided by the number of potential pancreas donors. Of 779 standard criteria donors, 691 (89%) were potential pancreas donors: 251 ideal (36%) and 440 expanded (64%) donors. In 2005 and 2006, before hemoglobin A1c testing, pancreas utilization rates were 21% and 18%, respectively. In 2008, 2009, and 2010, after hemoglobin A1c testing was incorporated, utilization rates were 27%, 28%, and 32%, respectively. Utilization of ideal donors increased from 33% to 51% (P= .003), and utilization of expanded donors increased from 11% to 17% (P= .05). Pancreas utilization increased 51.0%, and pancreas discards decreased 50.8% with the implementation of hemoglobin A1c testing. Hemoglobin A1c testing may increase utilization of ideal and expanded criteria pancreata

Obesity's effect on asthma extends to diagnostic criteria

BackgroundThe use of inflammatory biomarkers to delineate the type of lung inflammation present in asthmatic subjects is increasingly common. However, the effect of obesity on these markers is unknown.ObjectivesWe aimed to determine the effect of obesity on conventional markers of inflammation in asthmatic subjects.MethodsWe performed secondary analysis of data from 652 subjects previously enrolled in 2 Asthma Clinical Research Network trials. We performed linear correlations between biomarkers and logistic regression analysis to determine the predictive value of IgE levels, blood eosinophil counts, and fraction of exhaled nitric oxide values in relationship to sputum eosinophil counts (>2%), as well as to determine whether cut points existed that would maximize the sensitivity and specificity for predicting sputum eosinophilia in the 3 weight groups.ResultsOverall, statistically significant but relatively weak correlations were observed among all 4 markers of inflammation. Within obese subjects, the only significant correlation found was between IgE levels and blood eosinophil counts (r = 0.33, P < .001); furthermore, all other correlations between inflammatory markers were approximately 0, including correlations with sputum eosinophil counts. In addition, the predictive value of each biomarker alone or in combination was poor in obese subjects. In fact, in obese subjects none of the biomarkers of inflammation significantly predicted the presence of high sputum eosinophil counts. Obese asthmatic subjects have lower cut points for IgE levels (268 IU), fraction of exhaled nitric oxide values (14.5 ppb), and blood eosinophil counts (96 cells/μL) than all other groups.ConclusionsIn obese asthmatic subjects conventional biomarkers of inflammation are poorly predictive of eosinophilic airway inflammation. As such, biomarkers currently used to delineate eosinophilic inflammation in asthmatic subjects should be approached with caution in these subjects

Predictors of response to tiotropium versus salmeterol in asthmatic adults

BackgroundTiotropium has activity as an asthma controller. However, predictors of a positive response to tiotropium have not been described.ObjectiveWe sought to describe individual and differential responses of asthmatic patients to salmeterol and tiotropium when added to an inhaled corticosteroid, as well as predictors of a positive clinical response.MethodsData from the double-blind, 3-way, crossover National Heart, Lung, and Blood Institute's Asthma Clinical Research Network's Tiotropium Bromide as an Alternative to Increased Inhaled Glucocorticoid in Patients Inadequately Controlled on a Lower Dose of Inhaled Corticosteroid (ClinicalTrials.gov number, NCT00565266) trial were analyzed for individual and differential treatment responses to salmeterol and tiotropium and predictors of a positive response to the end points FEV1, morning peak expiratory flow (PEF), and asthma control days (ACDs).ResultsAlthough approximately equal numbers of patients showed a differential response to salmeterol and tiotropium in terms of morning PEF (n = 90 and 78, respectively) and ACDs (n = 49 and 53, respectively), more showed a differential response to tiotropium for FEV1 (n = 104) than salmeterol (n = 62). An acute response to a short-acting bronchodilator, especially albuterol, predicted a positive clinical response to tiotropium for FEV1 (odds ratio, 4.08; 95% CI, 2.00-8.31; P < .001) and morning PEF (odds ratio, 2.12; 95% CI, 1.12-4.01; P = 0.021), as did a decreased FEV1/forced vital capacity ratio (FEV1 response increased 0.39% of baseline for every 1% decrease in FEV1/forced vital capacity ratio). Higher cholinergic tone was also a predictor, whereas ethnicity, sex, atopy, IgE level, sputum eosinophil count, fraction of exhaled nitric oxide, asthma duration, and body mass index were not.ConclusionAlthough these results require confirmation, predictors of a positive clinical response to tiotropium include a positive response to albuterol and airway obstruction, factors that could help identify appropriate patients for this therapy