Independent Populations Research Articles

Genetically proxied IL-6 receptor inhibition is associated with increased risk of atopic dermatitis

BackgroundDermatitis has been reported after initiation of IL-6 receptor inhibitors (IL-6Ri), while genetic association studies of atopic dermatitis (AD) have implicated IL-6R pathway signalling. However, causality remains unclear. As indications for IL-6Ri expand, so do the clinical importance of determining whether there is mechanistic evidence linking it to AD. ObjectiveTo examine the association between IL-6Ri and risk of AD. MethodsTo genetically mimic IL-6Ri, we selected single nucleotide polymorphisms within or near the IL6R gene associated with C-reactive protein (CRP) at genome-wide significance among 343,524 individuals. Genetic data for AD were obtained from 10,788 cases and 30,047 controls of European ancestry. We used the inverse-variance weighted and pleiotropy-robust methods and examined genetic confounding using colocalization. Analyses were replicated using 13,473 AD Finnish cases and 2,385 East Asian cases. Results from three independent analyses were pooled by meta-analysis. ResultsGenetically proxied IL-6Ri was associated with increased risk of AD (OR 1.78 per 4.4 mg/l reduction in CRP; 95%CI 1.28, 2.48; p=6.5x10-4). Results were replicated using Finnish outcome data (OR 2.07; 95%CI 1.58, 2.72; p=1.57x10-7), and Eastern Asian datasets (OR 1.68; 95%CI 1.12, 2.54; p=0.013). Meta-analysis of three independent populations (OR 1.89; 95%CI 1.57, 2.28; p=2.68x10-11) showed no statistical evidence of heterogeneity (p=0.65). We found no statistical evidence for pleiotropy or genetic confounding. ConclusionThis genetic investigation provides consistent evidence, across independent multi-ancestry populations, that IL-6R signalling is causally implicated in AD susceptibility. Clinicians should remain vigilant for adverse effects resembling AD when using IL-6R inhibitors for immune-mediated inflammatory diseases.

Validation of the International Medical Prevention Registry on Venous Thromboembolism (IMPROVE) risk scores for venous thromboembolism and bleeding in an independent population

BackgroundMultiple guidelines recommend assessment of bleeding and venous thromboembolism (VTE) risk in adult medical inpatients to inform prevention strategies. There is no agreed-upon method for VTE and bleeding risk assessment. ObjectivesTo validate the International Medical Prevention Registry on Venous Thromboembolism (IMPROVE) VTE and bleeding risk scores in an independent population. MethodsIn this retrospective study, we calculated the IMPROVE VTE and bleeding risk scores in medical inpatients admitted between 2010 and 2019 at the University of Vermont Medical Center (UVMMC). Patients were followed for in-hospital bleeding events while hospitalized and VTE events while hospitalized and for 3 months after discharge. We assessed calibration of the risk models by comparing the observed incidence of events in the UVMMC and IMPROVE populations across the published risk categories. We also assessed performance of the IMPROVE risk factors after refitting the models in the UVMMC population. Discrimination was assessed using the area under the receiver operating characteristic curve (AUC). ResultsVTE occurred in 270 (1.1%) of 23,873 admissions, with 92 (34%) occurring during admission, and bleeding occurred in 712 (4.7%) of 15,240 admissions. When the IMPROVE-VTE risk factors were refitted to the UVMMC data, the AUC was 0.64. When the IMPROVE bleeding risk factors were refitted to the UVMMC data, the AUC was 0.67. The IMPROVE-VTE score tended to overestimate risk at higher scores, and the IMPROVE bleeding score underestimated risk at lower scores and overestimated risk at higher scores. ConclusionWhile the refitted IMPROVE VTE and bleeding risk scores had reasonable model fit, the scores were poorly calibrated and did not reliably identify or differentiate patients at risk for VTE and bleeding. Different methods are needed for risk assessment of medical inpatients for VTE and bleeding risk.

Esquemas Maladaptativos Tempranos en Alumnos de Psicología e Ingeniería de Universidades de Lima Metropolitana

The main objective of the study was to identify the significant differences between early maladaptive schemas (EMTs) in samples of university students of psychology and engineering from universities in Metropolitan Lima. This was a descriptive, comparative study with a non-experimental, cross-sectional design. The sample consisted of 406 psychology and engineering students, selected under a non-probabilistic purposive sampling, with prior approval of the informed consent of each participant. A sociodemographic survey and the Early Maladaptive Schema Questionnaire (YSQ - S3) were used as instruments. The results show that there are significant differences in the 18 EMTs between the group of psychology and engineering students. Finally, this study will serve as a baseline for future research to compare EMTs in two or more independent populations, also, thanks to its results, it will be helpful for the creation and implementation of both prevention and intervention programs.

Geriatric End-of-Life Screening Tool Prediction of 6-Month Mortality in Older Patients

Emergency department (ED) visits by older adults with life-limiting illnesses are a critical opportunity to establish patient care end-of-life preferences, but little is known about the optimal screening criteria for resource-constrained EDs. To externally validate the Geriatric End-of-Life Screening Tool (GEST) in an independent population and compare it with commonly used serious illness diagnostic criteria. This prognostic study assessed a cohort of patients aged 65 years and older who were treated in a tertiary care ED in Boston, Massachusetts, from 2017 to 2021. Patients arriving in cardiac arrest or who died within 1 day of ED arrival were excluded. Data analysis was performed from August 1, 2023, to March 27, 2024. GEST, a logistic regression algorithm that uses commonly available electronic health record (EHR) datapoints and was developed and validated across 9 EDs, was compared with serious illness diagnoses as documented in the EHR. Serious illnesses included stroke/transient ischemic attack, liver disease, cancer, lung disease, and age greater than 80 years, among others. The primary outcome was 6-month mortality following an ED encounter. Statistical analyses included area under the receiver operating characteristic curve, calibration analyses, Kaplan-Meier survival curves, and decision curves. This external validation included 82 371 ED encounters by 40 505 unique individuals (mean [SD] age, 76.8 [8.4] years; 54.3% women, 13.8% 6-month mortality rate). GEST had an external validation area under the receiver operating characteristic curve of 0.79 (95% CI, 0.78-0.79) that was stable across years and demographic subgroups. Of included encounters, 53.4% had a serious illness, with a sensitivity of 77.4% (95% CI, 76.6%-78.2%) and specificity of 50.5% (95% CI, 50.1%-50.8%). Varying GEST cutoffs from 5% to 30% increased specificity (5%: 49.1% [95% CI, 48.7%-49.5%]; 30%: 92.2% [95% CI, 92.0%-92.4%]) at the cost of sensitivity (5%: 89.3% [95% CI, 88.8-89.9]; 30%: 36.2% [95% CI, 35.3-37.1]). In a decision curve analysis, GEST outperformed serious illness criteria across all tested thresholds. When comparing patients referred to intervention by GEST with serious illness criteria, GEST reclassified 45.1% of patients with serious illness as having low risk of mortality with an observed mortality rate 8.1% and 2.6% of patients without serious illness as having high mortality risk with an observed mortality rate of 34.3% for a total reclassification rate of 25.3%. The findings of this study suggest that both serious illness criteria and GEST identified older ED patients at risk for 6-month mortality, but GEST offered more useful screening characteristics. Future trials of serious illness interventions for high mortality risk in older adults may consider transitioning from diagnosis code criteria to GEST, an automatable EHR-based algorithm.

Sociodemographic and Clinical Characteristics of People Living with Dementia and Their Associations with Unmet Healthcare Needs: Insights from the Baseline Assessment of the InDePendent Study.

The healthcare needs of People living with Dementia (PlwD) (such as Alzheimer's disease) are often unmet. Information about the needs of community-dwelling PlwD and their association with sociodemographic and clinical characteristics is needed to fill the knowledge gap regarding factors influencing unmet needs among PlwD and to conduct a comprehensive needs assessment to develop tailored interventions. To describe sociodemographic and clinical characteristics of the InDePendent study population with particular reference to determinants of unmet needs. We analyzed baseline data of the multi-centre cluster-randomized controlled trial (InDePendent) using descriptive statistics to describe patients' sociodemographic and clinical characteristics and Poisson regression models to predict unmet needs, separated by sex. Data were collected personally via face-to-face interviews. Most of the n = 417 participating PlwD were mild to moderately cognitively impaired, were not depressed, had an average of 10.8 diagnoses, took 6.7 medications, and had, on average, 2.4 unmet needs (62% of PlwD had at least one unmet need) measured by the Camberwell Assessment of Need for the Elderly (CANE). Low social support, a high body-mass-index, a lower education, functional impairment, and worse health status were associated with more unmet needs, regardless of sex. In women, higher unmet needs were associated with more depressive symptoms, a poor financial situation, living alone and not being recently treated by a general practitioner. In males, unmet needs increased with the number of medications taken. PlwD had a broad array of unmet healthcare needs, indicating primary healthcare provision improvement potentials. The results underscore the significance of early assessment of patient's clinical characteristics and unmet needs as a basis for individualized gender-sensible intervention strategies.∥ClinicalTrials.gov Identifier: NCT04741932, Registered on February 5, 2021.

Hubungan Desa Wisata Terhadap Kesejahteraan Masyarakat

Tourism is part of economic development aimed at expanding employment opportunities and equalizing people's welfare. Currently, the tourism potential in Ponorogo has not been optimally developed, one of which is Ngebel Lake. Currently, the Ngbel village community, which used to be Ngbel Lake, is full of visitors. . The research aims to determine the relationship between rural tourism and community welfare in Ngebel Village, Ngebel District, Ponorogo Regency, in 2021. The type of research used in this research is quantitative with an explanatory type. The results of the study were obtained by distributing questionnaires to 70 respondents. The population in this study were the people of the Ngbel village and the managers of the Ngbel Lake. The sampling technique uses random sampling where all individuals in the independent population or groups are given the same opportunity to choose sample members. The reason for choosing a tourist object for research was because the ngebel tourist attraction became empty of visitors due to rising ticket prices and the access road to the lake being difficult and the dominant Ngbel village community working as traders around the lake being affected. From the results of the study it was found that the relationship between the two variables was STRONG with a result of 0.690 which stated the degree of strength of the relationship between the two variables was at 0.50-0.75. In this case, it can be interpreted that there is a tourism village relationship to the welfare of the people in Ngebel Village, Ngebel District, Ponorogo Regency, in 2021.

Breast Cancer Polygenic Risk Score Validation and Effects of Variable Imputation.

Breast cancer (BC) is a complex disease affecting one in eight women in the USA. Advances in population genomics have led to the development of polygenic risk scores (PRSs) with the potential to augment current risk models, but replication is often limited. We evaluated 2 robust PRSs with 313 and 3820 SNPs and the effects of multiple genotype imputation replications in BC cases and control populations. Biological samples from BC cases and cancer-free controls were drawn from three European ancestry cohorts. Genotyping on the Illumina Global Screening Array was followed by stringent quality control measures and 20 genotype imputation replications. A total of 468 unrelated cases and 4337 controls were scored, revealing significant differences in mean PRS percentiles between cases and controls (p < 0.001) for both SNP sets (313-SNP PRS: 52.81 and 48.07; 3820-SNP PRS: 55.45 and 49.81), with receiver operating characteristic curve analysis showing area under the curve values of 0.596 and 0.603 for the 313-SNP and 3820-SNP PRS, respectively. PRS fluctuations (from ~2-3% up to 9%) emerged across imputation iterations. Our study robustly reaffirms the predictive capacity of PRSs for BC by replicating their performance in an independent BC population and showcases the need to average imputed scores for reliable outcomes.

Predicting peritoneal recurrence after radical gastrectomy for gastric cancer: Validation of a prediction model (PERI-Gastric 1 and PERI-Gastric 2) on a Korean database

BackgroundPeritoneal recurrence is a significant cause of treatment failure after radical gastrectomy for gastric cancer. The prediction of metachronous peritoneal recurrence would have a significantly impact risk stratification and tailored treatment planning. This study aimed to externally validate the previously established PERI-Gastric 1 and 2 models to assess their generalizability in an independent population. MethodsRetrospective external validation was conducted on a cohort of 8564 patients who underwent elective gastrectomy for stage Ib-IIIc gastric cancer between 1998 and 2018 at the Yonsei Cancer Center. Discrimination was tested using the area under the receiver operating characteristic curves (AUROC). Accuracy was tested by plotting observations against the predicted risk of peritoneal recurrence and analyzing the resulting calibration plots. Clinical usefulness was tested with a decision curve analysis. ResultsIn the validation cohort, PERI-Gastric 1 and PERI-Gastric 2 exhibited an AUROC of 0.766 (95 % C.I. 0.752–0.778) and 0.767 (95 % C.I. 0.755–0.780), a calibration-in-the-large of 0.935 and 0.700, a calibration belt with a 95 % C.I. over the bisector in the risk range of 24%–33 % and 35%–47 %. The decision curve analysis revealed a positive net benefit in the risk range of 10%–42 % and 15%–45 %, respectively. ConclusionsThis study presents the external validation of the PERI-Gastric 1 and 2 scores in an Eastern population. The models demonstrated fair discrimination and satisfactory calibration for predicting the risk of peritoneal recurrence after radical gastrectomy, even in Eastern patients. PERI-Gastric 1 and 2 scores could also be applied to predict the risk of metachronous peritoneal recurrence in Eastern populations.

NMR metabolomic modeling of age and lifespan: A multicohort analysis.

Metabolomic age models have been proposed for the study of biological aging, however, they have not been widely validated. We aimed to assess the performance of newly developed and existing nuclear magnetic resonance spectroscopy (NMR) metabolomic age models for prediction of chronological age (CA), mortality, and age-related disease. Ninety-eight metabolic variables were measured in blood from nine UK and Finnish cohort studies (N ≈31,000 individuals, age range 24-86 years). We used nonlinear and penalized regression to model CA and time to all-cause mortality. We examined associations of four new and two previously published metabolomic age models, with aging risk factors and phenotypes. Within the UK Biobank (N ≈102,000), we tested prediction of CA, incident disease (cardiovascular disease (CVD), type-2 diabetes mellitus, cancer, dementia, and chronic obstructive pulmonary disease), and all-cause mortality. Seven-fold cross-validated Pearson's r between metabolomic age models and CA ranged between 0.47 and 0.65 in the training cohort set (mean absolute error: 8-9 years). Metabolomic age models, adjusted for CA, were associated with C-reactive protein, and inversely associated with glomerular filtration rate. Positively associated risk factors included obesity, diabetes, smoking, and physical inactivity. In UK Biobank, correlations of metabolomic age with CA were modest (r = 0.29-0.33), yet all metabolomic model scores predicted mortality (hazard ratios of 1.01 to 1.06/metabolomic age year) and CVD, after adjustment for CA. While metabolomic age models were only moderately associated with CA in an independent population, they provided additional prediction of morbidity and mortality over CA itself, suggesting their wider applicability.

Genetic evidence for involvement of β2-adrenergic receptor in brown adipose tissue thermogenesis in humans

BackgroundSympathetic activation of brown adipose tissue (BAT) thermogenesis can ameliorate obesity and related metabolic abnormalities. However, crucial subtypes of the β-adrenergic receptor (AR), as well as effects of its genetic variants on functions of BAT, remains unclear in humans. We conducted association analyses of genes encoding β-ARs and BAT activity in human adults.MethodsSingle nucleotide polymorphisms (SNPs) in β1-, β2-, and β3-AR genes (ADRB1, ADRB2, and ADRB3) were tested for the association with BAT activity under mild cold exposure (19 °C, 2 h) in 399 healthy Japanese adults. BAT activity was measured using fluorodeoxyglucose-positron emission tomography and computed tomography (FDG-PET/CT). To validate the results, we assessed the effects of SNPs in the two independent populations comprising 277 healthy East Asian adults using near-infrared time-resolved spectroscopy (NIRTRS) or infrared thermography (IRT). Effects of SNPs on physiological responses to intensive cold exposure were tested in 42 healthy Japanese adult males using an artificial climate chamber.ResultsWe found a significant association between a functional SNP (rs1042718) in ADRB2 and BAT activity assessed with FDG-PET/CT (p < 0.001). This SNP also showed an association with cold-induced thermogenesis in the population subset. Furthermore, the association was replicated in the two other independent populations; BAT activity was evaluated by NIRTRS or IRT (p < 0.05). This SNP did not show associations with oxygen consumption and cold-induced thermogenesis under intensive cold exposure, suggesting the irrelevance of shivering thermogenesis. The SNPs of ADRB1 and ADRB3 were not associated with these BAT-related traits.ConclusionsThe present study supports the importance of β2-AR in the sympathetic regulation of BAT thermogenesis in humans. The present collection of DNA samples is the largest to which information on the donor’s BAT activity has been assigned and can serve as a reference for further in-depth understanding of human BAT function.

A systematic evaluation of population pharmacokinetic models for polymyxin B in patients with liver and/or kidney dysfunction.

Polymyxin B (PMB) is considered a last-line treatment for multidrug-resistant (MDR) gram-negative bacterial infections. Model-informed precision dosing with population pharmacokinetics (PopPK) models could help to individualize PMB dosing regimens and improve therapy. However, the external prediction ability of the established PopPK models has not been fully elaborated. This study aimed to systemically evaluate eleven PMB PopPK models from ten published literature based on a new independent population, which was divided into four different populations, patients with liver dysfunction, kidney dysfunction, liver and kidney dysfunction, and normal liver and kidney function. The whole data set consisted of 146 patients with 391 PMB concentrations. The prediction- and simulation-based diagnostics and Bayesian forecasting were conducted to evaluate model predictability. In the overall evaluation process, none of the models exhibited satisfactory predictive ability in both prediction- and simulation-based diagnostic simultaneously. However, the evaluation of the models in the subgroup of patients with normal liver and kidney function revealed improved predictive performance compared to those with liver and/or kidney dysfunction. Bayesian forecasting demonstrated enhanced predictability with the incorporation of two to three prior observations. The external evaluation highlighted a lack of consistency between the prediction results of published models and the external validation dataset. Nonetheless, Bayesian forecasting holds promise in improving the predictive performance of the models, and feedback from therapeutic drug monitoring is crucial in optimizing individual dosing regimens.

Development and Validation of Prediction Models for the 5-year Risk of Type 2 Diabetes in a Japanese Population: Japan Public Health Center-based Prospective (JPHC) Diabetes Study.

This study aimed to develop models to predict the 5-year incidence of type 2 diabetes mellitus (T2DM) in a Japanese population and validate them externally in an independent Japanese population. Data from 10,986 participants (aged 46-75 years) in the development cohort of the Japan Public Health Center-based Prospective Diabetes Study and 11,345 participants (aged 46-75 years) in the validation cohort of the Japan Epidemiology Collaboration on Occupational Health Study were used to develop and validate the risk scores in logistic regression models. We considered non-invasive (sex, body mass index, family history of diabetes mellitus, and diastolic blood pressure) and invasive (glycated hemoglobin [HbA1c] and fasting plasma glucose [FPG]) predictors to predict the 5-year probability of incident diabetes. The area under the receiver operating characteristic curve was 0.643 for the non-invasive risk model, 0.786 for the invasive risk model with HbA1c but not FPG, and 0.845 for the invasive risk model with HbA1c and FPG. The optimism for the performance of all models was small by internal validation. In the internal-external cross-validation, these models tended to show similar discriminative ability across different areas. The discriminative ability of each model was confirmed using external validation datasets. The invasive risk model with only HbA1c was well-calibrated in the validation cohort. Our invasive risk models are expected to discriminate between high- and low-risk individuals with T2DM in a Japanese population.

Development of Machine Learning Methods for Accurate Prediction of Plant Disease Resistance

The traditional method of screening plants for disease resistance phenotype is both time-consuming and costly. Genomic selection offers a potential solution to improve efficiency, but accurately predicting plant disease resistance remains a challenge. In this study, we evaluated eight different machine learning (ML) methods, including random forest classification (RFC), support vector classifier (SVC), light gradient boosting machine (lightGBM), random forest classification plus kinship (RFC_K), support vector classification plus kinship (SVC_K), light gradient boosting machine plus kinship (lightGBM_K), deep neural network genomic prediction (DNNGP), and densely connected convolutional networks (DenseNet), for predicting plant disease resistance. Our results demonstrate that the three plus kinship (K) methods developed in this study achieved high prediction accuracy. Specifically, these methods achieved accuracies of up to 95% for rice blast (RB), 85% for rice black-streaked dwarf virus (RBSDV), and 85% for rice sheath blight (RSB) when trained and applied to the rice diversity panel I (RDPI). Furthermore, the plus K models performed well in predicting wheat blast (WB) and wheat stripe rust (WSR) diseases, with mean accuracies of up to 90% and 93%, respectively. To assess the generalizability of our models, we applied the trained plus K methods to predict RB disease resistance in an independent population, rice diversity panel II (RDPII). Concurrently, we evaluated the RB resistance of RDPII cultivars using spray inoculation. Comparing the predictions with the spray inoculation results, we found that the accuracy of the plus K methods reached 91%. These findings highlight the effectiveness of the plus K methods (RFC_K, SVC_K, and lightGBM_K) in accurately predicting plant disease resistance for RB, RBSDV, RSB, WB, and WSR. The methods developed in this study not only provide valuable strategies for predicting disease resistance, but also pave the way for using machine learning to streamline genome-based crop breeding.

Identifying the main determinants that have an impact on the level of vaccination among children

Background. Thanks to vaccinations, many infections, including whooping cough, diphtheria, tetanus, poliomyelitis, measles, mumps, rubella, hepatitis B, hemophilic infection, pneumococcal infection, meningococcal infection, rotavirus infection, chicken pox, hepatitis A, papillomavirus infection, etc., can be prevented. According to the WHO research, it was established that if the level of vaccination coverage of the country's population drops by several percents, it creates favorable conditions for the spread of infectious diseases, that the lower the collective immunity, the higher the probability of outbreaks and epidemics. The Aim. Тo study and analyze the impact of risk factors on reducing the level of vaccine prophylaxis in the childhood population. Materials and Methods. This study was conducted using the questionnaire method, for which a questionnaire was developed. Group 1 consisted of 280 children who received a vaccination and group 2 consisted of 180 children who were not vaccinated. The parents of these children were interviewed using the author's questionnaire and gave their consent to use the medical data of the children for scientific research. Non-parametric statistical analysis for two independent sample populations was used to compare median values Mann-Whitney test. Fisher's test was used to compare proportions. Results. During the study, it was found that the most frequent reasons for parents' refusal to vaccinate their children were: religious views of family members 2.4 times increase the risk of non-vaccination in children; in single-parent families where the parents are divorced, children did not receive any vaccination 2.6 times more than in full-parent families; unfinished average of 35.7 times and lack of education 24.1 times increase the impact on the lack of vaccination in children. Conclusions. We identified the following risk factors that influence the vaccination rate, namely: demographic, socio-economic, biological and socio-psychological. Keywords: vaccine prevention, statistics, infectious diseases, risk factors.

Mapping and validation of Fusarium wilt race 2 resistance QTL from Citrullus amarus line USVL246-FR2

Key messageFon race 2 resistant QTLs were identified on chromosomes 8 and 9. Families homozygous for resistance alleles at a haplotype of three KASP markers had 42% lower disease severity than those with susceptible alleles in an independent, interspecific validation population confirming their utility for introgression of Fusarium wilt resistance.Fusarium oxysporum f. sp. niveum (Fon) race 2 causes Fusarium wilt in watermelon and threatens watermelon production worldwide. Chemical management options are not effective, and no resistant edible watermelon cultivars have been released. Implementation of marker-assisted selection to develop resistant cultivars requires identifying sources of resistance and the underlying quantitative trait loci (QTL), developing molecular markers associated with the QTL, and validating marker-phenotype associations with an independent population. An intraspecific Citrullus amarus recombinant inbred line population from a cross of resistant USVL246-FR2 and susceptible USVL114 was used for mapping Fon race 2 resistance QTL. KASP markers were developed (N = 51) for the major QTL on chromosome 9 and minor QTL on chromosomes 1, 6, and 8. An interspecific F2:3 population was developed from resistance donor USVL246-FR2 (C. amarus) and a susceptible cultivar ‘Sugar Baby’ (Citrullus lanatus) to validate the utility of the markers for introgression of resistance from the wild crop relative into cultivated watermelon. Only 16 KASP markers segregated in the interspecific C. amarus/lanatus validation population. Four markers showed significant differences in the separation of genotypes based on family-mean disease severity, but together explained only 16% of the phenotypic variance. Genotypes that inherited homozygous resistant parental alleles at three KASP markers had 42% lower family-mean disease severity than homozygous susceptible genotypes. Thus, haplotype analysis was more effective at predicting the mean disease severity of families than single markers. The haplotype identified in this study will be valuable for developing Fon race 2 resistant watermelon cultivars.

Direct and vicarious exposure to healthcare discrimination and erasure among transgender and gender independent individuals: Testing the indirect effect of mistrust in healthcare on utilization behaviors

RationaleDirect exposure to gender identity-related discrimination and erasure among the transgender and gender independent (TGI) population are associated with healthcare underutilization, which may further exacerbate the health disparities that exist between this population and cisgender individuals in the United States (U.S.). Although the impacts of direct exposure to healthcare discrimination and erasure may have on TGI individuals are known, exposure to such harm vicariously (i.e., through observation or report) is underexplored. ObjectiveThe present study examined the relationships among direct and vicarious gender identity-related healthcare discrimination and erasure exposure and past-year healthcare utilization. MethodGender identity-based mistrust in healthcare was also assessed, as a mechanism through which direct and vicarious gender identity-related healthcare discrimination and erasure predict healthcare utilization behaviors among a sample (N = 385) of TGI adults in the U.S., aged 18 to 71 recruited online. ResultsResults indicated direct lifetime and vicarious healthcare discrimination and erasure exposure significantly predicted past-year healthcare underutilization when participants anticipated encountering gender identity-related healthcare discrimination. Mediational analyses indicated that higher levels of exposure to direct lifetime and vicarious healthcare discrimination and erasure were related to higher levels of mistrust in healthcare, through which past-year underutilization was significantly related. ConclusionsThese findings are vital to informing healthcare practice and policy initiatives aimed at ensuring the barriers that deleteriously influence the accessibility of healthcare among TGI individuals are ameliorated.

A Revised Definition of Left Bundle Branch Block Using Time to Notch in Lead I

Current left bundle branch block (LBBB) criteria are based on animal experiments or mathematical models of cardiac tissue conduction and may misclassify patients. Improved criteria would impact referral decisions and device type for cardiac resynchronization therapy. To develop a simple new criterion for LBBB based on electrophysiological studies of human patients, and then to validate this criterion in an independent population. In this diagnostic study, the derivation cohort was from a single-center, prospective study of patients undergoing electrophysiological study from March 2016 through November 2019. The validation cohort was assembled by retrospectively reviewing medical records for patients from the same center who underwent transcatheter aortic valve replacement (TAVR) from October 2015 through May 2022. Patients were classified as having LBBB or intraventricular conduction delay (IVCD) as assessed by intracardiac recording. Sensitivity and specificity of the electrocardiography (ECG) criteria assessed in patients with LBBB or IVCD. A total of 75 patients (median [IQR] age, 63 [53-70.5] years; 21 [28.0%] female) with baseline LBBB on 12-lead ECG underwent intracardiac recording of the left ventricular septum: 48 demonstrated complete conduction block (CCB) and 27 demonstrated intact Purkinje activation (IPA). Analysis of surface ECGs revealed that late notches in the QRS complexes of lateral leads were associated with CCB (40 of 48 patients [83.3%] with CCB vs 13 of 27 patients [48.1%] with IPA had a notch or slur in lead I; P = .003). Receiver operating characteristic curves for all septal and lateral leads were constructed, and lead I displayed the best performance with a time to notch longer than 75 milliseconds. Used in conjunction with the criteria for LBBB from the American College of Cardiology/American Heart Association/Heart Rhythm Society, this criterion had a sensitivity of 71% (95% CI, 56%-83%) and specificity of 74% (95% CI, 54%-89%) in the derivation population, contrasting with a sensitivity of 96% (95% CI, 86%-99%) and specificity of 33% (95% CI, 17%-54%) for the Strauss criteria. In an independent validation cohort of 46 patients (median [IQR] age, 78.5 [70-84] years; 21 [45.7%] female) undergoing TAVR with interval development of new LBBB, the time-to-notch criterion demonstrated a sensitivity of 87% (95% CI, 74%-95%). In the subset of 10 patients with preprocedural IVCD, the criterion correctly distinguished IVCD from LBBB in all cases. Application of the Strauss criteria performed similarly in the validation cohort. The findings suggest that time to notch longer than 75 milliseconds in lead I is a simple ECG criterion that, when used in conjunction with standard LBBB criteria, may improve specificity for identifying patients with LBBB from conduction block. This may help inform patient selection for cardiac resynchronization or conduction system pacing.

Abstract 2264: Identifying and analyzing independent clonal populations in single Barrett’s esophagus biopsies

Abstract Barrett’s esophagus (BE) is a non-obligate precursor of esophageal adenocarcinoma (EAC), often measuring multiple centimeters in length and characterized by columnar epithelium replacing normal squamous epithelium in the distal esophagus. Early studies in BE suggested that all cells within a patient’s Barrett’s segment are progenies of a single founder cell. However, in recent years this previously accepted model of BE as a monoclonal disease has been retired in favor of a multiclonal model with new evidence suggesting that a patient’s Barrett’s segment can be composed of multiple independent clones with independent founder cells. Nonetheless, single BE samples are still routinely assumed to be monoclonal, leading to independent sets of genomic aberrations erroneously being analyzed as a single set in the case of multiclonal samples. Here, we utilize a previously generated whole-genome sequenced BE dataset and repurpose an established pipeline for detecting subclonal populations to identify BE samples that are comprised of multiple independent clones. Additionally, we present a novel approach for validating multiclonality from sequencing data by phasing pair-end sequencing reads using germline variants. We demonstrate that 20/80 patients have at least one multiclonal sample and that the independent clones contained in these single biopsies can have drastically different genomic profiles. Further, we speculate that these multiclonal samples capture a snapshot of clonal competition and evolution within BE. These findings highlight the importance of accounting for multiclonality when studying BE and provide the first systematic analysis of multiclonal BE samples. Citation Format: Mariya Kazachkova, Phoebe He, Ludmil B. Alexandrov. Identifying and analyzing independent clonal populations in single Barrett’s esophagus biopsies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2264.

Abstract P493: A Multivariate Analysis of Genetic Risk Scores for Heart Failure and Left Ventricular Mass Derived From Multi-Ancestry Populations and Left Ventricular Mass Amongst African Americans: The Jackson Heart Study

Background: Increased left ventricular (LV) mass is an outcome of LV remodeling that can result in development of left ventricular hypertrophy (LVH), a maladaptive disorder that increases the risk of heart failure. Elevated LV mass is a sensitive predictor of adverse cardiovascular events. African Americans experience a disproportionate burden of heart failure risk and development of LVH. The influence of genetics on this health disparity is unclear and a topic of interest. Genome-wide association studies (GWAS) have uncovered many variants associated with numerous adverse cardiovascular outcomes, such as heart failure and LV phenotypes. However, the relevance of these studies for African Americans may be limited as these analyses have been conducted in multi-ancestry populations with limited representation of African heritage. The question of whether these genetic risk variants can be used to predict LV phenotypes in an independent African American population remains unanswered. Hypothesis: Variant loci that have been associated with heart failure and LV mass in multi-ancestry populations will be associated with LV mass amongst African Americans in the Jackson Heart Study (JHS). Methods: Thirty-nine (39) SNPs associated with heart failure and ten (10) SNPs associated with LV mass were identified from two published studies in which participants of African ancestry or Black individuals comprised less than 15% and 2%, respectively. Using the published effect size estimates, genetic risk scores (GRSs) for heart failure and LV mass were computed for 2,175 African American participants (mean age 55, 63% female) in the JHS with complete data and consent for genetic research. We assessed the linear association of heart failure and LV mass GRSs with LV mass indexed to height (LVM h ) and indexed to body surface area (LVM bsa ). A multivariate general linear model was fit to both LVM h and LVM bsa containing both GRS predictors and accounting for age, sex, BMI (mean 31.5), diabetes (22%), and hypertension (52%). No multicollinearity was noted among these explanatory variables using variance inflation factors. Due to non-constant error variance, a log transformation was conducted on both LV mass response variables. Type III MANOVA Pillai tests were run to assess the effects of the GRSs on the log LVM bsa and log LVM h values. Conclusion: When accounting for age, BMI, sex, diabetes, and hypertension, we found that neither the heart failure GRS (p-val = 0.4012) nor the LV mass GRS (p-val = 0.8332) had an effect on both log LVM bsa and log LVM h . There is insufficient evidence to suggest that heart failure and LV mass variants derived from predominantly European multi-ancestry populations are linearly associated with log LV mass amongst African Americans in the Jackson Heart Study. Our work highlights the need for greater recruitment and targeted studies of populations with African ancestry for GWAS of LV phenotypes.

Impact of physical and sexual abuse on risk of hospitalisations for physical and mental illnesses: insights from two large prospective cohort studies

Physical abuse can lead to severe health consequences that extend beyond immediate harm. We explored the associations of physical abuse experienced during childhood and adulthood with a wide range of adult health conditions requiring hospital treatment. We utilised data from a sub-cohort of 157,366 UK Biobank participants (46.4% of the baseline population; age range 45-81; 89,101 women) and repeated analyses in an independent population of 85,929 adults from the Finnish Public Sector (FPS) study (age range 17-78; 68,544 women). Participants in both cohorts reported instances of physical and sexual abuse at study baseline. Follow-up included 77 common health conditions ascertained from linkage data to national hospital and mortality registries. Mean follow-up duration was 4.6 years (SD 0.14) in UK Biobank and 10.6 years (4.3) in FPS. Physical and sexual abuse was associated with 22 mental and physical health conditions. After multivariable adjustments, participants who experienced abuse during both early and later stages of life had a 2.12- (95% confidence interval 1.39-3.23) to 3.37-fold (1.52-7.45) increased risk of mental and behavioural disorders, a 1.46 (1.20-1.79) to 1.83 (1.05-3.20) times increased risk of metabolic, haematologic, and respiratory diseases, and a 1.24 (1.07-1.45) times higher risk of inflammatory diseases compared with non-exposed participants. The absolute risk difference between these groups was greatest for metabolic and haematologic conditions (rate 381 and risk difference 160 per 100,000 person-years). Frailty, comorbidities, and competing risk of death did not modify these associations, but the possibility of bias or residual confounding cannot be excluded. Repeated exposure to physical and sexual abuse amplifies the risk of hospitalisations from mental disorders and physical diseases spanning diverse organ systems. Addressing this issue may necessitate multifaceted strategies, including shifts in societal norms, legal measures, and increased healthcare provision for affected individuals and their families. Wellcome Trust, UK Medical Research Council, U.S. National Institute on Aging, Academy of Finland.