Toward a Universal Definition of Etiologies in Heart Failure: Categorizing Causes and Advancing Registry Science.

Heart failure (HF) is a well-described final common pathway for a broad range of diseases however substantial confusion exists regarding how to describe, study, and track these underlying etiologic conditions. We describe (1) the overlap in HF etiologies, comorbidities, and case definitions as currently used in HF registries led or managed by members of the global HF roundtable; (2) strategies to improve the quality of evidence on etiologies and modifiable risk factors of HF in registries; and (3) opportunities to use clinical HF registries as a platform for public health surveillance, implementation research, and randomized registry trials to reduce the global burden of noncommunicable diseases. Investment and collaboration among countries to improve the quality of evidence in global HF registries could contribute to achieving global health targets to reduce noncommunicable diseases and overall improvements in population health.

A Lung Cancer Mouse Model Database.

Lung cancer, the leading cause of cancer mortality, exhibits diverse histological subtypes and genetic complexities. Numerous preclinical mouse models have been developed to study lung cancer, but data from these models are disparate, siloed, and difficult to compare in a centralized fashion. Here we established the Lung Cancer Mouse Model Database (LCMMDB), an extensive repository of 1,354 samples from 77 transcriptomic datasets covering 974 samples from genetically engineered mouse models (GEMMs), 368 samples from carcinogen-induced models, and 12 samples from a spontaneous model. Meticulous curation and collaboration with data depositors have produced a robust and comprehensive database, enhancing the fidelity of the genetic landscape it depicts. The LCMMDB aligns 859 tumors from GEMMs with human lung cancer mutations, enabling comparative analysis and revealing a pressing need to broaden the diversity of genetic aberrations modeled in GEMMs. Accompanying this resource, we developed a web application that offers researchers intuitive tools for in-depth gene expression analysis. With standardized reprocessing of gene expression data, the LCMMDB serves as a powerful platform for cross-study comparison and lays the groundwork for future research, aiming to bridge the gap between mouse models and human lung cancer for improved translational relevance.

The Science of Precision Prevention: Research Opportunities and Clinical Applications to Reduce Cardiovascular Health Disparities.

Precision prevention embraces personalized prevention but includes broader factors such as social determinants of health to improve cardiovascular health. The quality, quantity, precision, and diversity of data relatable to individuals and communities continue to expand. New analytical methods can be applied to these data to create tools to attribute risk, which may allow a better understanding of cardiovascular health disparities. Interventions using these analytic tools should be evaluated to establish feasibility and efficacy for addressing cardiovascular disease disparities in diverse individuals and communities. Training in these approaches is important to create the next generation of scientists and practitioners in precision prevention. This state-of-the-art review is based on a workshop convened to identify current gaps in knowledge and methods used in precision prevention intervention research, discuss opportunities to expand trials of implementation science to close the health equity gaps, and expand the education and training of a diverse precision prevention workforce.

Research priorities for the secondary prevention and management of acute rheumatic fever and rheumatic heart disease: a National Heart, Lung, and Blood Institute workshop report.

Secondary prevention of acute rheumatic fever (ARF) and rheumatic heart disease (RHD) involves continuous antimicrobial prophylaxis among affected individuals and is recognised as a cornerstone of public health programmes that address these conditions. However, several important scientific issues around the secondary prevention paradigm remain unresolved. This report details research priorities for secondary prevention that were developed as part of a workshop convened by the US National Heart, Lung, and Blood Institute in November 2021. These span basic, translational, clinical and population science research disciplines and are built on four pillars. First, we need a better understanding of RHD epidemiology to guide programmes, policies, and clinical and public health practice. Second, we need better strategies to find and diagnose people affected by ARF and RHD. Third, we urgently need better tools to manage acute RF and slow the progression of RHD. Fourth, new and existing technologies for these conditions need to be better integrated into healthcare systems. We intend for this document to be a reference point for research organisations and research sponsors interested in contributing to the growing scientific community focused on RHD prevention and control.

Tertiary prevention and treatment of rheumatic heart disease: a National Heart, Lung, and Blood Institute working group summary.

Although entirely preventable, rheumatic heart disease (RHD), a disease of poverty and social disadvantage resulting in high morbidity and mortality, remains an ever-present burden in low-income and middle-income countries (LMICs) and rural, remote, marginalised and disenfranchised populations within high-income countries. In late 2021, the National Heart, Lung, and Blood Institute convened a workshop to explore the current state of science, to identify basic science and clinical research priorities to support RHD eradication efforts worldwide. This was done through the inclusion of multidisciplinary global experts, including cardiovascular and non-cardiovascular specialists as well as health policy and health economics experts, many of whom also represented or closely worked with patient-family organisations and local governments. This report summarises findings from one of the four working groups, the Tertiary Prevention Working Group, that was charged with assessing the management of late complications of RHD, including surgical interventions for patients with RHD. Due to the high prevalence of RHD in LMICs, particular emphasis was made on gaining a better understanding of needs in the field from the perspectives of the patient, community, provider, health system and policy-maker. We outline priorities to support the development, and implementation of accessible, affordable and sustainable interventions in low-resource settings to manage RHD and related complications. These priorities and other interventions need to be adapted to and driven by local contexts and integrated into health systems to best meet the needs of local communities.

Rural-Urban Differences in Vaccination and Hesitancy Rates and Trust: US COVID-19 Trends and Impact Survey on a Social Media Platform, May 2021-April 2022.

Objectives. To analyze rural-urban differences in COVID-19 vaccination uptake, hesitancy, and trust in information sources in the United States. Methods. We used data from a large survey of Facebook users. We computed the vaccination, hesitancy, and decline rates and the trust proportions among individuals hesitant toward COVID-19 information sources for rural and urban regions in each state from May 2021 to April 2022. Results. In 48 states with adequate data, on average, two thirds of states showed statistically significant differences in monthly vaccination rates between rural and urban regions, with rural regions having a lower vaccination rate at all times. Far fewer states showed statistically significant differences when comparing monthly hesitancy and decline rates for urban versus rural regions. Doctors and health professionals received the highest level of trust. Friends and family were also among the most trusted sources in rural areas where the vaccination uptake was low. Conclusions. Rural-urban difference in hesitancy rates among those still unvaccinated was much smaller than the rural-urban difference in vaccination rates, suggesting that access to vaccines may be another contributor to the lower vaccination rates in rural areas. (Am J Public Health. 2023;113(6):680-688. https://doi.org/10.2105/AJPH.2023.307274).

Molecular epidemiology of Cryptosporidium species in Kpong and its environs, Ghana.

BACKGROUND: Cryptosporidium is a ubiquitous enteric protozoan pathogen infecting humans, domestic animals, and wildlife worldwide. It is a waterborne pathogen with recognized zoonotic potential and a definite cause of diarrhea and nutritional disorders in institutional and community settings. One challenge facing the world's supply of clean drinking water is contamination from feces and soil. It has been established that small quantities of oocysts, the infective stage, can cause human disease. Also, their resistance to chlorination and other water treatment procedures has been demonstrated. Kpong, a community in the Lower Manya Krobo Municipality of the Eastern Region of Ghana, is one of the primary sources of water supply to Accra, the capital city of Ghana. Being able to determine the effectiveness of water treatment processes and identifying sources of contamination of this pathogen in our water bodies is thus of public health importance. The study aimed to conduct molecular epidemiology of Cryptosporidium spp. in the Lower Manya Krobo Municipality. METHODOLOGY/PRINCIPAL FINDINGS: A total of 230 samples, 180 fecal samples from cattle and 50 water samples (tap water and well water) were collected from the following communities: Kpong, Akwernor, Ablotsi, Nuaso, and Atua, all in the Lower Manya Krobo Municipality. Samples were screened for Cryptosporidium by microscopy and PCR. The 18S rRNA gene was amplified by nested polymerase chain reaction (PCR), and the final product was sequenced. The prevalence of Cryptosporidium from the fecal samples was estimated as 10% (18/180) by microscopy, while all 50 water samples were negative. However, PCR gave the prevalence of Cryptosporidium as 47.8% (86/180) for fecal samples and 20% (10/50) for water samples. Based on the 18S rRNA gene, three sequenced samples showed high homology to C. parvum species. The phylogenetic analysis confirmed this as these sequences clustered with C. parvum sequences from other countries. CONCLUSION/SIGNIFICANCE: Cryptosporidium parvum was identified as the persistent species in the study communities. This outcome supports the evidence that domesticated animals serve as potential reservoirs of zoonotic transmission of cryptosporidiosis. The persistence of cryptosporidiosis in cattle indicates its presence in the human population. In addition, the presence of Cryptosporidium parvum in the wells makes it alarming and necessary to consider a holistic approach such as One Health Strategies to identify and control cases in humans.

Multi-omics inference of differential breast cancer-related transcriptional regulatory network gene hubs between young Black and White patients.

OBJECTIVE: Breast cancers (BrCA) are a leading cause of illness and mortality worldwide. Black women have a higher incidence rate relative to white women prior to age 40 years, and a lower incidence rate after 50 years. The objective of this study is to identify -omics differences between the two breast cancer cohorts to better understand the disparities observed in patient outcomes. MATERIALS AND METHODS: Using Standard SQL, we queried ISB-CGC hosted Google BigQuery tables storing TCGA BrCA gene expression, methylation, and somatic mutation data and analyzed the combined multi-omics results using a variety of methods. RESULTS: Among Stage II patients 50 years or younger, genes PIK3CA and CDH1 are more frequently mutated in White (W50) than in Black or African American patients (BAA50), while HUWE1, HYDIN, and FBXW7 mutations are more frequent in BAA50. Over-representation analysis (ORA) and Gene Set Enrichment Analysis (GSEA) results indicate that, among others, the Reactome Signaling by ROBO Receptors gene set is enriched in BAA50. Using the Virtual Inference of Protein-activity by Enriched Regulon analysis (VIPER) algorithm, putative top 20 master regulators identified include NUPR1, NFKBIL1, ZBTB17, TEAD1, EP300, TRAF6, CACTIN, and MID2. CACTIN and MID2 are of prognostic value. We identified driver genes, such as OTUB1, with suppressed expression whose DNA methylation status were inversely correlated with gene expression. Networks capturing microRNA and gene expression correlations identified notable microRNA hubs, such as miR-93 and miR-92a-2, expressed at higher levels in BAA50 than in W50. DISCUSSION/CONCLUSION: The results point to several driver genes as being involved in the observed differences between the cohorts. The findings here form the basis for further mechanistic exploration.

Implementation Research at NHLBI: Methodological and Design Challenges and Lessons Learned from the DECIPHeR Initiative.

NHLBI funded seven projects as part of the Disparities Elimination through Coordinated Interventions to Prevent and Control Heart and Lung Disease Risk (DECIPHeR) Initiative. They were expected to collaborate with community partners to (1) employ validated theoretical or conceptual implementation research frameworks, (2) include implementation research study designs, (3) include implementation measures as primary outcomes, and (4) inform our understanding of mediators and mechanisms of action of the implementation strategy. Several projects focused on late-stage implementation strategies that optimally and sustainably delivered two or more evidence-based multilevel interventions to reduce or eliminate cardiovascular and/or pulmonary health disparities and to improve population health in high-burden communities. Projects that were successful in the three-year planning phase transitioned to a 4-year execution phase. NHLBI formed a Technical Assistance Workgroup during the planning phase to help awardees refine study aims, strengthen research designs, detail analytic plans, and to use valid sample size methods. This paper highlights methodological and study design challenges encountered during this process. Important lessons learned included (1) the need for greater emphasis on implementation outcomes, (2) the need to clearly distinguish between intervention and implementation strategies in the protocol, (3) the need to address clustering due to randomization of groups or clusters, (4) the need to address the cross-classification that results when intervention agents work across multiple units of randomization in the same arm, (5) the need to accommodate time-varying intervention effects in stepped-wedge designs, and (6) the need for data-based estimates of the parameters required for sample size estimation.

Evaluating Social Determinants of Health Variables in Advanced Analytic and Artificial Intelligence Models for Cardiovascular Disease Risk and Outcomes: A Targeted Review.

Introduction/Purpose: Predictive models incorporating relevant clinical and social features can provide meaningful insights into complex interrelated mechanisms of cardiovascular disease (CVD) risk and progression and the influence of environmental exposures on adverse outcomes. The purpose of this targeted review (2018-2019) was to examine the extent to which present-day advanced analytics, artificial intelligence, and machine learning models include relevant variables to address potential biases that inform care, treatment, resource allocation, and management of patients with CVD. Methods: PubMed literature was searched using the prespecified inclusion and exclusion criteria to identify and critically evaluate primary studies published in English that reported on predictive models for CVD, associated risks, progression, and outcomes in the general adult population in North America. Studies were then assessed for inclusion of relevant social variables in the model construction. Two independent reviewers screened articles for eligibility. Primary and secondary independent reviewers extracted information from each full-text article for analysis. Disagreements were resolved with a third reviewer and iterative screening rounds to establish consensus. Cohen's kappa was used to determine interrater reliability. Results: The review yielded 533 unique records where 35 met the inclusion criteria. Studies used advanced statistical and machine learning methods to predict CVD risk (10, 29%), mortality (19, 54%), survival (7, 20%), complication (10, 29%), disease progression (6, 17%), functional outcomes (4, 11%), and disposition (2, 6%). Most studies incorporated age (34, 97%), sex (34, 97%), comorbid conditions (32, 91%), and behavioral risk factor (28, 80%) variables. Race or ethnicity (23, 66%) and social variables, such as education (3, 9%) were less frequently observed. Conclusions: Predictive models should adjust for race and social predictor variables, where relevant, to improve model accuracy and to inform more equitable interventions and decision making.

Deciphering Disparities: The NHLBI Program on Disparities Elimination through Coordinated Interventions to Prevent and Control Heart and Lung Disease Risk (DECIPHeR).

Despite several ambitious national health initiatives to eliminate health disparities, spanning more than 4 decades, health disparities remain pervasive in the United States. In an attempt to bend the curve in disparities elimination, the National Heart, Lung, and Blood Institute (NHLBI) issued a funding opportunity on Disparities Elimination through Coordinated Interventions to Prevent and Control Heart and Lung Disease Risk (DECIPHeR) in March 2019. Seven implementation research centers and 1 research coordinating center were funded in September 2020 to plan, develop, and test effective implementation strategies for eliminating disparities in heart and lung disease risk. In the 16 articles presented in this issue of Ethnicity & Disease, the DECIPHeR Alliance investigators and their NHLBI program staff address the work accomplished in the first phase of this biphasic research endeavor. Included in the collection are an article on important lessons learned during technical assistance sessions designed to ensure scientific rigor in clinical study designs, and 2 examples of clinical study process articles. Several articles show the diversity of clinical and public health settings addressed including schools, faith-based settings, federally qualified health centers, and other safety net clinics. All strategies for eliminating disparities tackle a cardiovascular or pulmonary disease and related risk factors. In an additional article, NHLBI program staff address expectations in phase 2 of the DECIPHeR program, strategies to ensure feasibility of scaling and spreading promising strategies identified, and opportunities for translating the DECIPHeR research model to other chronic diseases for the elimination of related health disparities.