Helix (United States)

Background:Most genetic studies on celiac disease (CeD) have focused on individuals of European descent. Limited data are available for the Hispanic and black populations.Methods:We analyzed whole-genome sequencing data, electronic health records (EHR), and laboratory results from the All of Us Research Program. We identified 3,481 individuals with CeD through EHR, self-reporting, or both. Of these, 2,899 carried one of the four well-established risk haplotypes, including 262 of admixed American (89% Hispanic) and 108 of African (70% black) ancestry. Five sex-, age-, and ancestry-matched controls per case were selected for the assessment of genetic and clinical risk factors.Results:An enrichment in the DQB1*02:01 allele was observed in CeD patients across all ancestries, with the strongest association in Europeans (32.3% vs. 11.6%), followed by Americans (18.5% vs. 8.1%) and Africans (15.7% vs. 8.1%). Among individuals carrying the DQ2.5 (DQA1*05:01-DQB1*02:01 haplotype), HLA-B8 was present in 72.3% of Europeans, 42.3% of Admixed Americans, and lower in Africans. This linkage disequilibrium was higher in CeD patients than in controls across all three ancestries. A polygenic risk score distinguished seropositive CeD from controls with 86% accuracy. Incorporating clinical risk factors, including family history, hypothyroidism, diarrhea, vitamin D deficiency, and anemia, increased predictive accuracy to 92%. The model identified 93% of CeD patients with tTG-IgA levels greater than 10 IU/mL.Conclusion:Linkage between HLA-B8 and DQ2.5 differs significantly among individuals of European, admixed American, and African ancestry, contributing to ancestry-dependent genetic risk for CeD.

Abstract Background Non-ischemic cardiomyopathy (NICM) represents a major cause of heart failure with limited tools for early risk stratification. Atrial fibrillation (AF) is a well-established contributor to cardiomyopathy but is often clinically silent in its early stages. The atrial fibrillation polygenic risk score (AF-PRS) reflects genetic susceptibility to AF and may identify individuals at risk for AF-related cardiomyopathy. We hypothesized that higher AF-PRS is associated with greater risk of NICM. Methods This was a retrospective cohort study of 16,801 individuals of European ancestry from the Sanford Biobank and Imagenetics program with genetic sequencing and longitudinal electronic health record data. AF-PRS was calculated using 315 genome-wide significant single-nucleotide polymorphisms with standard quality control. NICM was defined by International Classification of Diseases, 10th Revision, Clinical Modification codes, excluding ischemic etiologies. Cox regression models evaluated the association between AF-PRS and incident NICM, adjusting for age, sex, smoking status, body mass index (BMI), hypertension, and diabetes. AF-PRS was analyzed both as a quasi-continuous variable (15% quartile increments) and dichotomized at the 85th percentile. Sensitivity analyses assessed associations with all-cause cardiomyopathy and ischemic cardiomyopathy. Survival analysis was used to model time-to-event outcomes. Results Among all participants, 418 (2.5%) had NICM. 99% were Caucasian. NICM cases were older and more often male (both p<0.001) than those without a diagnosis. After multivariable adjustment for sex, smoking status, BMI, and hypertension, a linear AF-PRS (15% increments) was specifically predictive of increased hazard risk of NICM (HR = 1.09 [1.03, 1.15], p < 0.001). Conclusion These findings complement recent evidence of bidirectional genetic relationships between cardiomyopathy and AF, supporting comprehensive genetic risk assessment in cardiovascular disease prevention. Clinical implementation requires validation in diverse populations and prospective evaluation. Future research should investigate the mechanistic pathways linking AF-associated genetic variants to cardiomyopathy development and evaluate whether AF-PRS-guided screening improves clinical outcomes. Visual abstract: Summary of study design, exposure, outcome, key findings, and clinical implications. This graphical abstract provides a comprehensive overview of the study investigating the association between atrial fibrillation polygenic risk score (AF-PRS) and non-ischemic cardiomyopathy (NICM). Abbreviations: AF, atrial fibrillation; AF-PRS, atrial fibrillation polygenic risk score; CI, confidence interval; HR, hazard ratio; ICD-10, International Classification of Diseases, 10th Revision; ICM, ischemic cardiomyopathy; NICM, non-ischemic cardiomyopathy; PPV, positive predictive value; PRS, polygenic risk score; SNP, single nucleotide polymorphism. Created in BioRender. https://BioRender.com/ k3t1w68

Vascular streak dieback (VSD) poses a significant threat to the sustainability of woody ornamentals in the United States, particularly Cercis spp. (redbud). This study aimed to develop reliable molecular diagnostic tools for detecting Ceratobasidium sp. D.P. Rogers (Csp), the fungus consistently detected from VSD-symptomatic redbuds and other woody ornamentals. Molecular markers can provide rapid and accurate detection for fastidious fungi such as Csp that are challenging to recover in culture media. However, current molecular tools for Csp detection lack sensitivity and specificity. To address this, specific PCR and quantitative PCR (qPCR) primers were developed, targeting the internal transcribed spacer (ITS) genetic region. The existing primers for the second-largest subunit of RNA polymerase II (RPB2), translation elongation factor 1-alpha (TEF1-α), and ATP synthase subunit 6 (ATP6) genetic regions of Rhizoctonia fungi were also redesigned to enhance the sensitivity and accuracy of detection for Csp. The CP-qP-Csp primer set, with a detection limit of 86.02 pg/μl, effectively detected Csp in VSD-symptomatic tissues, cultures, and soils and is recommended for molecular detection of Csp from woody ornamentals in the U.S. Cross-platform validation across seven laboratories confirmed the robustness of the assays. These findings provide nursery producers with critical early-detection capabilities, potentially preventing significant economic losses and contributing to the sustainability of woody ornamental production. Future research will focus on refining these assays for field applications and exploring the genetic characteristics of Csp across different hosts and pathogen interactions to better understand the epidemiology of VSD.

Introduction: Lipoprotein a (Lp(a)) levels are an often unmeasured predictor of future risk of cardiovascular disease. Unlike LDL, HDL, and triglycerides, Lp(a) levels are believed to be genetically determined; they are not altered by lipid-lowering medications or dietary changes, and are consistent over a lifetime, making them a potential early-life predictor of adult morbidity. However, genetic predictors of Lp(a) are challenging to design. Repeats of the kringle IV subtype 2 domain (KIV-2) contribute significantly but are extremely challenging to quantify via next-generation sequencing; this variability is particularly impactful in non-European ancestries. Methods: We analyzed ~110K individuals with paired clinical and exome sequencing data from six medical centers. We developed a coverage-based method to determine KIV-2 repeat counts. We validated that these counts associated with clinical Lp(a) measurements derived from the course of care (n = 2039 individuals). We calculated an expected Lp(a) in units of nmol/L using a genetic risk score (GRS) based on 43 variants in the Lp(a) gene. We identified instances of CAD via ICD9CM, ICD10CM and SNOMED terms present in the medical record. Results: Adding the number of KIV-2 repeats to the GRS substantially improved prediction of clinical Lp(a) measurements, for example improving the r-squared for non-Europeans five-fold (from 0.05 to 0.22). Individuals with fewer than 15 estimated KIV-2 repeats and a high GRS-predicted Lp(a) (high risk group) have a mean measured Lp(a) of that is 10-fold that of those in the lowest category of GRS-predicted Lp(a) (low risk group). In the full cohort, most of whom had not been measured for Lp(a), we find that relative to the low risk group, the high risk individuals are 1.6x more likely to have CAD. Conclusion: Lp(a) is a potentially useful biomarker with consistency over a lifetime and implications for future cardiovascular morbidity. We developed a method for estimating the number of KIV-2 repeats, a challenging component of genetic prediction of Lp(a). This estimate can be used in combination with a GRS to predict Lp(a), especially in individuals with non-European ancestry where GRS-based estimates fall short. The final prediction is associated with increased risk of CAD.

Most patients with pathogenic or likely pathogenic (P/LP) variants for breast cancer have not undergone genetic testing. To identify patients meeting family history criteria for genetic testing in the electronic health record (EHR). This study included both cross-sectional (observation date, February 1, 2024) and retrospective cohort (observation period, January 1, 2018, to February 1, 2024) analyses. Participants included patients aged 18 to 79 years enrolled in Renown Health, a large health system in Northern Nevada. Genotype was known for 38 003 patients enrolled in Healthy Nevada Project (HNP), a population genomics study. An EHR indicating that a patient is positive for criteria according to the Seven-Question Family History Questionnaire (hereafter, FHS7 positive) assessing familial risk for hereditary breast and ovarian cancer (HBOC). The primary outcomes were the presence of P/LP variants in the ATM, BRCA1, BRCA2, CHEK2, or PALB2 genes (cross-sectional analysis) or a diagnosis of cancer (cohort analysis). Age-adjusted cancer incidence rates per 100 000 patients per year were calculated using the 2020 US population as the standard. Hazard ratios (HRs) for cancer attributable to FHS7-positive status were estimated using cause-specific hazard models. Among 835 727 patients, 423 393 (50.7%) were female and 29 913 (3.6%) were FHS7 positive. Among those who were FHS7 positive, 24 535 (82.0%) had no evidence of prior genetic testing for HBOC in their EHR. Being FHS7 positive was associated with increased prevalence of P/LP variants in BRCA1/BRCA2 (odds ratio [OR], 3.34; 95% CI, 2.48-4.47), CHEK2 (OR, 1.62; 95% CI, 1.05-2.43), and PALB2 (OR, 2.84; 95% CI, 1.23-6.16) among HNP female individuals, and in BRCA1/BRCA2 (OR, 3.35; 95% CI, 1.93-5.56) among HNP male individuals. Being FHS7 positive was also associated with significantly increased risk of cancer among 131 622 non-HNP female individuals (HR, 1.44; 95% CI, 1.22-1.70) but not among 114 982 non-HNP male individuals (HR, 1.11; 95% CI, 0.87-1.42). Among 1527 HNP survey respondents, 352 of 383 EHR-FHS7 positive patients (91.9%) were survey-FHS7 positive, but only 352 of 883 survey-FHS7 positive patients (39.9%) were EHR-FHS7 positive. Of the 29 913 FHS7-positive patients, 19 764 (66.1%) were identified only after parsing free-text family history comments. Socioeconomic differences were also observed between EHR-FHS7-negative and EHR-FHS7-positive patients, suggesting disparities in recording family history. In this cross-sectional study, EHR-derived FHS7 identified thousands of patients with familial risk for breast cancer, indicating a substantial gap in genetic testing. However, limitations in EHR family history data suggested that other identification methods, such as direct-to-patient questionnaires, are required to fully address this gap.

Abstract IntroductionRegulation is important for medical software, but advances in software, notably developments in artificial intelligence (AI), are developing quickly. There are concerns that regulatory processes are not keeping up and that there is a need for more pro-innovation approaches.MethodsWe conducted a survey (n = 34) and four focus groups to discuss experiences of regulation among UK-based developers.ResultsIn the survey, 35% agreed/strongly agreed that they were confident in their knowledge of relevant regulation, while 50% agreed/strongly agreed that poor regulation was allowing bad products to come to market. The focus groups identified 10 themes around challenges with current processes: the process of obtaining regulatory approval is uncertain; lack of knowledge about regulatory approval; difficulties in obtaining reliable advice; complexity and slow pace of approvals; difficult to get NHS clinician involvement; process is costly and difficult to fund; implications for competition; international differences; incentives to develop lower classification products; and lack of harmonisation between NHS and MHRA. Respondents’ suggestions for solutions to improve processes fell under four themes: financial and structural support; regulatory collaboration and commissioner involvement; process efficiency and adaptability; and education and guidance.DiscussionDevelopers are unhappy with the process of regulation for medical software in the UK, finding it confusing and expensive. They feel systems compare poorly to international comparators. Integration between the MHRA system and NHS commissioning is considered poor.

Viral SARS-CoV-2 rebound (viral RNA rebound) is challenging to characterize in large cohorts due to the logistics of collecting frequent and regular diagnostic test results. Pharmacy-based testing data provide an opportunity to study the phenomenon in a large population, also enabling subgroup analyses. The current real-world evidence approach complements approaches focused on smaller, prospective study designs. We linked real-time reverse transcription quantitative polymerase chain reaction test data from national pharmacy-based testing to health care claims data via tokenization to calculate the cumulative incidence of viral RNA rebound within 28 days following positive test results in nirmatrelvir/ritonavir (NMV-r)-treated and untreated individuals during the Omicron era (December 2021-November 2022) and prior to the Omicron era (October 2020-November 2021). Among 30 646 patients, the rate of viral RNA rebound was 3.5% (95% CI, 2.0%-5.7%) in NMV-r-treated infections as compared with 1.5% (95% CI, 1.3%-1.7%) in untreated infections during the Omicron era and 1.9% (95% CI, 1.7%-2.1%) prior to the Omicron era. Viral RNA rebound in patients who were vaccinated (n = 8151), high risk (n = 4411), or older (≥65 years, n = 4411) occurred at comparable rates to the overall cohort (range, 1.1%-4.8%). Viral rebounds to high RNA levels in NMV-r-treated infections occurred in 8% of viral rebounds as compared with 5% to 11% in untreated infections. Rates of hospitalization were comparable between patients with NMV-r-treated infections with viral RNA rebound (0%) and untreated patients with viral RNA rebound (0%-1.2%). Our findings suggest viral RNA rebound is rare (< 5%), with rates that were consistent with those from the EPIC-HR trial (Evaluation of Protease Inhibition for COVID-19 in High-Risk Patients). Most occurrences of viral RNA rebound were associated with low viral RNA levels, and viral RNA rebound progression to severe disease was not observed.