Environmental exposure unit simulates natural seasonal birch pollen exposures while maximizing change in allergic symptoms.

BACKGROUND: Birch pollen is a prevalent aeroallergen during the springtime allergy season. In field studies, variable allergen exposure and environmental factors can affect data quality while environmental exposure units (EEUs) deliver controlled, standardized, and reproducible allergen exposures. OBJECTIVE: To inform study design for EEU trials evaluating antiallergic therapies. METHODS: In this prospective study, 76 participants with birch allergy experienced 3 exposures to birch pollen: (1) an out-of-season EEU challenge (two 3-hour sessions on consecutive days); (2) a natural seasonal exposure; and (3) an in-season EEU challenge (3-hour exposure for 2 weeks after birch pollen season initiation). RESULTS: The total nasal symptom score, total ocular symptom score, and total symptom score (TSS = total nasal symptom score plus total ocular symptom score) were assessed every 30 minutes and daily during EEU and natural exposures. A high association between TSSs and day 2 of the out-of-season and in-season EEU challenges was noted, with a good association between the maximum TSS during the natural and in-season EEU challenges, and natural season and day 2 of the out-of-season EEU challenge (P < .001 for all). Participants had higher maximum change from the baseline TSS during day 2 of the out-of-season EEU challenge (12.4) vs the following: (1) first day (9.8); (2) in-season EEU challenge (8.4); and (3) natural seasonal exposure (7.6) (P < .001 for all). CONCLUSION: A strong association was seen between the presence of allergy symptoms and exposure to birch pollen in the EEU (maximum change in symptom scores during day 2) and in the field. A hybrid trial design may be useful to demonstrate the clinical efficacy of novel antiallergic therapies requiring fewer participants and shorter timelines and expediting treatment availability.

Inclusion of genotype with fundus phenotype improves accuracy of predicting choroidal neovascularization and geographic atrophy.

PURPOSE: The accuracy of predicting conversion from early-stage age-related macular degeneration (AMD) to the advanced stages of choroidal neovascularization (CNV) or geographic atrophy (GA) was evaluated to determine whether inclusion of clinically relevant genetic markers improved accuracy beyond prediction using phenotypic risk factors alone. DESIGN: Cohort study. PARTICIPANTS: White, non-Hispanic subjects participating in the Age-Related Eye Disease Study (AREDS) sponsored by the National Eye Institute consented to provide a genetic specimen. Of 2415 DNA specimens available, 940 were from disease-free subjects and 1475 were from subjects with early or intermediate AMD. METHODS: DNA specimens from study subjects were genotyped for 14 single nucleotide polymorphisms (SNPs) in genes shown previously to associate with CNV: ARMS2, CFH, C3, C2, FB, CFHR4, CFHR5, and F13B. Clinical demographics and established disease associations, including age, sex, smoking status, body mass index (BMI), AREDS treatment category, and educational level, were evaluated. Four multivariate logistic models (phenotype; genotype; phenotype + genotype; and phenotype + genotype + demographic + environmental factors) were tested using 2 end points (CNV, GA). Models were fitted using Cox proportional hazards regression to use time-to-disease onset data. MAIN OUTCOME MEASURES: Brier score (measure of accuracy) was used to identify the model with the lowest prediction error in the training set. The most accurate model was subjected to independent statistical validation, and final model performance was described using area under the receiver operator curve (AUC) or C-statistic. RESULTS: The CNV prediction models that combined genotype with phenotype with or without age and smoking revealed superior performance (C-statistic = 0.96) compared with the phenotype model based on the simplified severity scale and the presence of CNV in the nonstudy eye (C-statistic = 0.89; P<0.01). For GA, the model that combined genotype with phenotype demonstrated the highest performance (AUC = 0.94). Smoking status and ARMS2 genotype had less of an impact on the prediction of GA compared with CNV. CONCLUSIONS: Inclusion of genotype assessment improves CNV prediction beyond that achievable with phenotype alone and may improve patient management. Separate assessments should be used to predict progression to CNV and GA because genetic markers and smoking status do not equally predict both end points. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found after the references.

Clinical validation of a genetic model to estimate the risk of developing choroidal neovascular age-related macular degeneration.

Predictive tests for estimating the risk of developing late-stage neovascular age-related macular degeneration (AMD) are subject to unique challenges. AMD prevalence increases with age, clinical phenotypes are heterogeneous and control collections are prone to high false-negative rates, as many control subjects are likely to develop disease with advancing age. Risk prediction tests have been presented previously, using up to ten genetic markers and a range of self-reported non-genetic variables such as body mass index (BMI) and smoking history. In order to maximise the accuracy of prediction for mainstream genetic testing, we sought to derive a test comparable in performance to earlier testing models but based purely on genetic markers, which are static through life and not subject to misreporting. We report a multicentre assessment of a larger panel of single nucleotide polymorphisms (SNPs) than previously analysed, to improve further the classification performance of a predictive test to estimate the risk of developing choroidal neovascular (CNV) disease. We developed a predictive model based solely on genetic markers and avoided inclusion of self-reported variables (eg smoking history) or non-static factors (BMI, education status) that might otherwise introduce inaccuracies in calculating individual risk estimates. We describe the performance of a test panel comprising 13 SNPs genotyped across a consolidated collection of four patient cohorts obtained from academic centres deemed appropriate for pooling. We report on predictive effect sizes and their classification performance. By incorporating multiple cohorts of homogeneous ethnic origin, we obtained >80 per cent power to detect differences in genetic variants observed between cases and controls. We focused our study on CNV, a subtype of advanced AMD associated with a severe and potentially treatable form of the disease. Lastly, we followed a two-stage strategy involving both test model development and test model validation to present estimates of classification performance anticipated in the larger clinical setting. The model contained nine SNPs tagging variants in the regulators of complement activation (RCA) locus spanning the complement factor H (CFH), complement factor H-related 4 (CFHR4), complement factor H-related 5 (CFHR5) and coagulation factor XIII B subunit (F13B) genes; the four remaining SNPs targeted polymorphisms in the complement component 2 (C2), complement factor B (CFB), complement component 3 (C3) and age-related maculopathy susceptibility protein 2 (ARMS2) genes. The pooled sample size (1,132 CNV cases, 822 controls) allowed for both model development and model validation to confirm the accuracy of risk prediction. At the validation stage, our test model yielded 82 per cent sensitivity and 63 per cent specificity, comparable with metrics reported with earlier testing models that included environmental risk factors. Our test had an area under the curve of 0.80, reflecting a modest improvement compared with tests reported with fewer SNPs.

Cellular and tissue localization of globotriaosylceramide in Fabry disease.

The pathogenesis of Fabry disease is poorly understood. We used a variety of immunohistological techniques to localize globotriaosylceramide, the main glycolipid that accumulates in Fabry disease. Globotriaosylceramide immunoreactivity in a heterogenous pattern was present in all organs examined of a patient on long-term enzyme replacement therapy. In the brain, immmunopositivity was found only in the parahippocampal region. Globotriaosylceramide immunostaining was present in the cell membrane and cytoplasm of endothelial cells, even in the absence of lysosomal inclusions. In kidney tissue, globotriaosylceramide colocalized with lysosomal, endoplasmic reticulum, and nuclear markers. Pre- and postembedding immunogold electron microscopy of skin biopsies and untreated patient cultured skin fibroblasts confirmed the presence of globotriaosylceramide in the cell membrane, in various cytoplasmic structures, and in the nucleus. Control organ tissues and cultured fibroblasts from five unaffected subjects were uniformly negative for globotriaosylceramide by immunohistochemistry and immunogold electron microscopy. We conclude that a substantial amount of lysosomal and extralysosomal globotriaosylceramide immunoreactivity remains in cells and tissues even after years of enzyme replacement therapy in Fabry disease. These findings are crucial for the understanding of the disease mechanism and suggest the usefulness of immunostaining for globotriaosylceramide as a means to assess response to novel, specific therapies.