Theobald, Jannick

Abstract Peanut allergy is a leading cause of food-induced allergy (prevalence of ∼1%). The diagnosis relies on evaluating clinical symptoms consistent with peanut exposure, supported by the detection of total peanut specific IgE (sIgE) and peanut component IgE antibodies (Ara h1, Ara h2, Ara h3, Ara h6, Ara h8, Ara h9 and Bet v2) through serum or skin testing. However, sensitization patterns across different ages and regions in the United States remain largely unknown. In this study, we investigated regional and demographic patterns of peanut component sensitization in a large U.S. population tested for suspected peanut allergy. Retrospective data were collected from 13,702 individuals tested at Mayo Clinic Laboratories. sIgEs were measured using the ImmunoCAP system (Thermo Fisher Scientific). Samples with detectable total peanut sIgE (≥0.1 kU/L) were reflexed to testing for seven peanut component IgEs. Statistical analyses including linear regression and correlation matrix analysis were conducted using R Studio. Regional differences were assessed using care provider zip code information. Among the study population, 92.0% (12,604 of 13,702) had detectable total peanut sIgE, with the Western U.S. region exhibiting the highest detectable rate (95.6%), and the Southeast the lowest (85.6%) (p < 0.001). On average, 3.38 different component IgEs were detectable per person with a detectable total peanut sIgE; 7.1% (892) had no detectable component IgEs, possibly due to antibodies against other peanut components. Correlation analysis revealed strong associations between Ara h2 and Ara h6 (r = 0.94), with moderate correlations observed between Ara h2, Ara h3, and Ara h6 to Ara h1 (r ranging from 0.72 to 0.77). Age-stratified analysis indicated higher total peanut sIgE detectable rates in children and adolescents (95.2%, ≤18 years) compared to adults (76.5%, >18 years). Interestingly, adults were more likely than children to have negative results for all component IgEs. Sensitization rates to different peanut components varied, with Ara h2 (77.5%) and Ara h6 (73.2%) being the most frequently detected, followed by Ara h1 (56%), and Ara h3 (47.3%). Lower detectable rates were observed for Ara h8, Ara h9, and Bet v2 (34.8%, 26.1% and 22.7%, respectively). Regional analysis showed consistently high detectable rates for Ara h2 and Ara h6 (>70%) across most areas (p < 0.001) with slightly lower rates in the Southwest (<63%). Bet v2, despite its overall low prevalence (<24%), had a relatively higher detectable rate in the Southwest (29%). This study provides valuable insights into potential demographic and geographic factors influencing peanut allergy sensitization. Our study demonstrates that peanut sensitization patterns vary by age and geographic location. Children and adolescents exhibit higher detectable rates for total peanut sIgE and component IgEs compared to adults, with Ara h2 and Ara h6 as the most frequently detected and highly correlated components.

Abstract Background Alzheimer’s disease (AD) cerebrospinal fluid (CSF) biomarkers, including the Aß42/40 and p-tau181/Aß42 ratios, are used in clinical practice to detect the presence of amyloid pathology for the diagnosis of AD. However, in some instances, discrepancies between Aß42/40 and p-tau181/Aß42 are observed. Such discrepancies may introduce uncertainties in the clinical management of patients presenting with cognitive decline. Identifying the underlying causes of these discrepancies and determining which biomarker abnormalities better predict disease progression is crucial to enhancing confidence in the use of these CSF biomarkers for the diagnosis of AD. This study aims to investigate the discordance between the Aß42/40 and p-tau181/Aß42 ratios, evaluate the frequency of these discrepancies, and identify potential causes. Methods Data from 958 individuals who had both CSF Aß42/40 and p-tau181/Aß42 tested at Mayo Clinic Laboratories between 2022 and 2024 and where the tests were ordered in CSF collected during the same lumbar puncture procedure were included. Cases with an inadequate sample collection, which could cause a false decrease in Aß42 concentrations, were excluded from the analysis. Aß42/40 was measured using the Fujirebio LUMIPULSE assays and reported as negative, likely positive, or positive. For this analysis, likely positive and positive results were combined and considered as positive (<0.072). P-tau181/Aß42 was measured using the Roche Elecsys assays and above 0.028 was considered positive. Statistical analyses were conducted using R Studio. Results Aß42/40 was positive in 69.1% of cases (n=661), while p-tau181/Aß42 was positive in 62.1% (n=594). There were 8.0% discordant cases (n=77). Most frequently, the discordant cases had an abnormal Aß42/40 with a normal p-tau181/Aß42 (Aß42/40+/p-tau181/Aß42-; n=72, 94%). Compared to the concordant Aß42/40+/p-tau181/Aß42+ group, the discordant Aß42/40+/p-tau181/Aß42- group showed significantly higher Aß42 concentrations (p <0.001, median [pg/mL]: 878.5 vs 587.0, respectively); whereas p-tau181 concentrations were significantly lower (p <0.001, median [pg/mL]: 19.3 vs 32.1, respectively). Among the Aß42/40+/p-tau181/Aß42- group, 30 cases exhibited abnormally low Aß42 and normal p-tau181, possibly reflecting early-stage AD. There were 41 cases with a normal Aß42 concentration despite an abnormal Aß42/40, possibly reflecting an overall higher production of Aß peptides resulting in an increased Aß40 peptide (median [pg/mL]: 12627 compared to 9487 in the low Aß42 and normal p-tau181 cases (n=30); p <0.001). Of these 41, 19 showed normal Aß42 but elevated p-tau181 concentrations where the use of Aß42/40 compensated for the overall higher production of Aß peptides, resulting in an abnormal ratio. In contrast, the p-tau181/Aß42 ratio was not able to normalize for these differences, leading to a normal ratio. Conclusion While overall concordance was 92.0%, our findings suggest that discrepancies between CSF Aß42/40 and p-Tau181/Aß42 are more often due to the presence of an abnormal Aß42/40 and a normal p-Tau181/Aß42. Two potential explanations for these discrepancies are early-stage AD or higher production of Aß peptides in some individuals. In the latter, differences in amyloid production would be normalized by ratios of the same biomarker (i.e. Aß42/40) but not by ratios of different biomarkers (i.e. p-Tau181/Aß42).

Abstract Background: The GALAD score is a serum biomarker–based model that predicts the probability of having hepatocellular carcinoma (HCC) in patients with chronic liver disease. We aimed to assess the performance of the GALAD score in comparison with liver ultrasound for detection of HCC. Methods: A single-center cohort of 111 HCC patients and 180 controls with cirrhosis or chronic hepatitis B and a multicenter cohort of 233 early HCC and 412 cirrhosis patients from the Early Detection Research Network (EDRN) phase II HCC Study were analyzed. Results: The area under the ROC curve (AUC) of the GALAD score for HCC detection was 0.95 [95% confidence interval (CI), 0.93–97], which was higher than the AUC of ultrasound (0.82, P <0.01). At a cutoff of −0.76, the GALAD score had a sensitivity of 91% and a specificity of 85% for HCC detection. The AUC of the GALAD score for early-stage HCC detection remained high at 0.92 (95% CI, 0.88–0.96; cutoff −1.18, sensitivity 92%, specificity 79%). The AUC of the GALAD score for HCC detection was 0.88 (95% CI, 0.85–0.91) in the EDRN cohort. The combination of GALAD and ultrasound (GALADUS score) further improved the performance of the GALAD score in the single-center cohort, achieving an AUC of 0.98 (95% CI, 0.96–0.99; cutoff −0.18, sensitivity 95%, specificity 91%). Conclusions: The performance of the GALAD score was superior to ultrasound for HCC detection. The GALADUS score further enhanced the performance of the GALAD score. Impact: The GALAD score was validated in the United States.