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BACKGROUND Hypertension is an important risk factor for cardiovascular diseases. Electronic health records (EHRs) may augment chronic disease surveillance. We aimed to develop an electronic phenotype (e-phenotype) for hypertension surveillance. METHODS We included 11,031,368 eligible adults from the 2019 IQVIA Ambulatory Electronic Medical Records-US (AEMR-US) dataset. We identified hypertension using three criteria, alone or in combination: diagnosis codes, blood pressure (BP) measurements, and antihypertensive medications. We compared AEMR-US estimates of hypertension prevalence and control against those from the National Health and Nutrition Examination Survey (NHANES) 2017–18, which defined hypertension as BP ≥130/80 mm Hg or ≥1 antihypertensive medication. RESULTS The study population had a mean (SD) age of 52.3 (6.7) years, and 56.7% were women. The selected three-criteria e-phenotype (≥1 diagnosis code, ≥2 BP measurements of ≥130/80 mm Hg, or ≥1 antihypertensive medication) yielded similar trends in hypertension prevalence as NHANES: 42.2% (AEMR-US) vs. 44.9% (NHANES) overall, 39.0% vs. 38.7% among women, and 46.5% vs. 50.9% among men. The pattern of age-related increase in hypertension prevalence was similar between AEMR-US and NHANES. The prevalence of hypertension control in AEMR-US was 31.5% using the three-criteria e-phenotype, which was higher than NHANES (14.5%). CONCLUSIONS Using an EHR dataset of 11 million adults, we constructed a hypertension e-phenotype using three criteria, which can be used for surveillance of hypertension prevalence and control. [ABSTRACT FROM AUTHOR]

Background: This study quantifies incremental healthcare expenditures of functional impairments and phenotypic frailty in specific healthcare sectors., Methods: Pooled 2023 analysis of 4 prospective cohort studies linked with Medicare claims including 4 318 women and 3 847 men attending an index examination (2002-2011). Annualized inpatient, skilled nursing facility (SNF), home healthcare (HHC), and outpatient costs (2023 dollars) ascertained for 36 months following index examination. Functional impairments (difficulty performing 4 activities of daily living) and frailty phenotype (operationalized using 5 components) derived from cohort data. Weighted multimorbidity index including demographics derived from claims., Results: Mean age at index examination was 79.2 years. After accounting for multimorbidity and each other, average annualized incremental costs of 3-4 functional impairments versus no impairment in women (men) were $2 838 ($5 516) in inpatient, $1 572 ($1 446) in SNF, and $1 349 ($1 060) in HHC sectors; average incremental costs of phenotypic frailty versus robust in women (men) was $4 100 (not significant for men) in inpatient, $1 579 ($1 254) in SNF, and $645 ($526) in HHC sectors. Incremental inpatient costs were primarily due to a higher hospitalization risk, while incremental SNF and HHC costs were related to both increased risks of utilization and higher costs among individuals with utilization. Neither geriatric domain was associated with outpatient costs., Conclusions: In this study of community-dwelling beneficiaries, functional impairments were independently associated with higher subsequent expenditures in inpatient, SNF, and HHC sectors among both sexes. Phenotypic frailty was independently associated with higher subsequent inpatient costs in women, and higher SNF and HHC costs in both sexes., (© The Author(s) 2024. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Background: Chronic hepatitis C virus (HCV) infection is associated with early onset of chronic diseases and increased risk of chronic disorders. Chronic viral infections have been linked to accelerated biological aging based on epigenetic clocks. In this study, we aimed to investigate the association between HCV infection and clinical measures of biological aging among 8 306 adults participating in the 2015-2018 waves of the National Health and Nutrition Examination Survey (NHANES)., Methods: NHANES 2015-2018 participants aged 20 years and older who had complete data on clinical blood markers and HCV-related tests were included in the current study. We estimated biological age using 2 approaches including phenotypic age (PhenoAge) and allostatic load (AL) score based on 9 clinical biomarkers., Results: After adjusting for demographic and other confounding factors, HCV antibody-positivity was associated with advanced PhenoAge (β = 2.43, 95% confidence interval: 1.51-3.35), compared with HCV antibody-negativity. Additionally, both active HCV infection (HCV RNA (+)) and resolved infection were associated with greater PhenoAge acceleration. The positive association with the AL score was not statistically significant. We did not observe any significant interactions of potential effect modifiers, including smoking and use of drug/needle injection, with HCV infection on measures of biological aging., Conclusions: Our findings suggest that HCV infection is independently associated with biological aging measured by phenotypic age in the U.S. general population. Further studies are warranted to confirm the findings., (© The Author(s) 2024. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Context/Objective: Depression is the most common psychological comorbidity associated with spinal cord injury (SCI) and affects healthcare utilization and costs. This study aimed to use an International Classification of Disease (ICD) and prescription drug-based depression phenotypes to classify people with SCI, and to evaluate the prevalence of those phenotypes, associated risk factors, and healthcare utilization. Design: Retrospective Observational Study Setting: Marketscan Database (2000-2019) Participants: Individuals with SCI were classified into six ICD-9/10, and prescription drugs defined phenotypes: Major Depressive Disorder (MDD), Other Depression (OthDep), Antidepressants for Other Psychiatric Conditions (PsychRx), Antidepressants for non-psychiatric condition (NoPsychRx), Other Non-depression Psychiatric conditions only (NonDepPsych), and No Depression (NoDep). Except for the latter, all the other groups were referred to as "depressed phenotypes". Data were screened for 24 months pre- and 24 months post-injury depression. Interventions: None Outcome Measures: Healthcare utilization and payments Results: There were 9,291 patients with SCI classified as follows: 16% MDD, 11% OthDep, 13% PsychRx, 13% NonPsychRx, 14% NonDepPsych, 33% NoDep. Compared with the NoDep group, the MDD group was younger (54 vs. 57 years old), predominantly female (55% vs. 42%), with Medicaid coverage (42% vs. 12%), had increased comorbidities (69% vs. 54%), had fewer traumatic injuries (51% vs. 54%) and had higher chronic 12-month pre-SCI opioid use (19% vs. 9%) (all P  < 0.0001). Classification into a depressed phenotype before SCI was found to be significantly associated with depression phenotype post-SCI, as evidenced by those who experienced a negative change (37%) vs. a positive change (15%, P  < 0.0001). Patients in the MDD cohort had higher healthcare utilization and associated payments at 12 and 24 months after SCI. Conclusion: Increasing awareness of psychiatric history and MDD risk factors may improve identifying and managing higher-risk patients with SCI, ultimately optimizing their post-injury healthcare utilization and cost. This method of classifying depression phenotypes provides a simple and practical way to obtain this information by screening through pre-injury medical records.

Background: Electronic health records (EHRs) commonly contain patient addresses that provide valuable data for geocoding and spatial analysis, enabling more comprehensive descriptions of individual patients for clinical purposes. Despite the widespread use of EHRs in clinical decision support and interventions, no systematic review has examined the extent to which spatial analysis is used to characterize patient phenotypes., Objective: This study reviews advanced spatial analyses that used individual-level health data from EHRs within the United States to characterize patient phenotypes., Methods: We systematically evaluated English-language, peer-reviewed studies from the PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar databases from inception to August 20, 2023, without imposing constraints on study design or specific health domains., Results: A substantial proportion of studies (>85%) were limited to geocoding or basic mapping without implementing advanced spatial statistical analysis, leaving only 49 studies that met the eligibility criteria. These studies used diverse spatial methods, with a predominant focus on clustering techniques, while spatiotemporal analysis (frequentist and Bayesian) and modeling were less common. A noteworthy surge (n=42, 86%) in publications was observed after 2017. The publications investigated a variety of adult and pediatric clinical areas, including infectious disease, endocrinology, and cardiology, using phenotypes defined over a range of data domains such as demographics, diagnoses, and visits. The primary health outcomes investigated were asthma, hypertension, and diabetes. Notably, patient phenotypes involving genomics, imaging, and notes were limited., Conclusions: This review underscores the growing interest in spatial analysis of EHR-derived data and highlights knowledge gaps in clinical health, phenotype domains, and spatial methodologies. We suggest that future research should focus on addressing these gaps and harnessing spatial analysis to enhance individual patient contexts and clinical decision support., (©Abolfazl Mollalo, Bashir Hamidi, Leslie A Lenert, Alexander V Alekseyenko. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 15.10.2024.)

Atopic Dermatitis (AD) is associated with a number of published disparities, including those related to self-identified racial/ethnic populations. Black/African American populations in the United States experience greater AD prevalence, severity, and persistence compared to other demographic groups, such as those who self-identify as White. There is consistent evidence that healthcare, environmental, and socioeconomic factors affect the prevalence, severity, and/or persistence of AD. Additionally, because of institutional and systemic racism, these same risk factors are more prevalent in racial and ethnic minority populations. Herein, we review the underlying causes of racial/ethnic disparities in AD and potential strategies to improve AD diagnosis and disease control., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: In the ACCORD study, participants with the haptoglobin (Hp) 2-2 phenotype and glycated hemoglobin (HbA 1c ) ≥ 8.0% had a higher risk of coronary artery disease (CAD) compared to those with HbA 1c 7.0-7.9%. However, this association was not observed in participants without the Hp2-2 phenotype. The optimal glycemic target for CAD prevention for the Hp phenotypes remains uncertain and may vary based on demographic and clinical factors., Objective: To investigate how reaching clinically relevant HbA 1c targets relates to the risk of CAD in different Hp phenotype groups among a diverse cohort of individuals with T2DM (the Look AHEAD study, HbA 1c  ≤ 11% at baseline)., Methods: Cox regression models with time-varying covariables were used to quantify the association between time-varying achieved HbA 1c (< 6.5%, 6.5-6.9%, and ≥ 8.0% compared to 7.0-7.9%), updated at years 1-4, 6, 8, and 10, and incident CAD in the Hp2-2 (n = 1,587) and non-Hp2-2 (n = 2,944) phenotypes separately. Further pre-specified subgroup analyses by age, sex, history of cardiovascular disease (CVD), race, and diabetes duration were performed in each Hp phenotype group separately., Results: Compared with HbA 1c 7.0-7.9%, having HbA 1c  < 6.5% was associated with a 29% lower CAD risk among participants with the non-Hp2-2 phenotype (adjusted HR 0.71, 95% CI 0.55-0.90). In subgroup analyses, this association was present in participants with the non-Hp2-2 phenotype who were male (0.60, 0.44-0.83), who did not have a history of CVD (0.65, 0.47-0.90), who were aged ≥ 65 years (0.64, 0.44-0.94), who were White (0.68, 0.51-0.91), or who had diabetes duration > 10 years (0.58, 0.35-0.95). HbA 1c  ≥ 8.0% was associated with CAD risk only among participants with the Hp2-2 phenotype who had a history of CVD (1.79, 1.00-3.20). No associations were found between the other HbA 1c targets and CAD risk when participants with the Hp2-2 phenotype were grouped together or divided into subgroups., Conclusion: The differences in our results compared to our previous findings may be due to variations in the study populations and factors associated with weight loss, making it difficult to draw definitive conclusions. Our current findings should be considered in the context of hypothesis generation, and ideally, will encourage additional research in this field., (© 2024. The Author(s).)

Aims: Abnormalities in specific echocardiographic parameters and cardiac biomarkers have been reported among individuals with diabetes. However, a comprehensive characterization of diabetic cardiomyopathy (DbCM), a subclinical stage of myocardial abnormalities that precede the development of clinical heart failure (HF), is lacking. In this study, we developed and validated a machine learning-based clustering approach to identify the high-risk DbCM phenotype based on echocardiographic and cardiac biomarker parameters., Methods and Results: Among individuals with diabetes from the Atherosclerosis Risk in Communities (ARIC) cohort who were free of cardiovascular disease and other potential aetiologies of cardiomyopathy (training, n = 1199), unsupervised hierarchical clustering was performed using echocardiographic parameters and cardiac biomarkers of neurohormonal stress and chronic myocardial injury (total 25 variables). The high-risk DbCM phenotype was identified based on the incidence of HF on follow-up. A deep neural network (DeepNN) classifier was developed to predict DbCM in the ARIC training cohort and validated in an external community-based cohort (Cardiovascular Health Study [CHS]; n = 802) and an electronic health record (EHR) cohort (n = 5071). Clustering identified three phenogroups in the derivation cohort. Phenogroup-3 (n = 324, 27% of the cohort) had significantly higher 5-year HF incidence than other phenogroups (12.1% vs. 4.6% [phenogroup 2] vs. 3.1% [phenogroup 1]) and was identified as the high-risk DbCM phenotype. The key echocardiographic predictors of high-risk DbCM phenotype were higher NT-proBNP levels, increased left ventricular mass and left atrial size, and worse diastolic function. In the CHS and University of Texas (UT) Southwestern EHR validation cohorts, the DeepNN classifier identified 16% and 29% of participants with DbCM, respectively. Participants with (vs. without) high-risk DbCM phenotype in the external validation cohorts had a significantly higher incidence of HF (hazard ratio [95% confidence interval] 1.61 [1.18-2.19] in CHS and 1.34 [1.08-1.65] in the UT Southwestern EHR cohort)., Conclusion: Machine learning-based techniques may identify 16% to 29% of individuals with diabetes as having a high-risk DbCM phenotype who may benefit from more aggressive implementation of HF preventive strategies., (© 2024 The Author(s). European Journal of Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.)

Introduction: National Institute of Health (NIH) funding is a "gold-standard" of achievement; we examined trends in NIH-funded pediatric surgeons., Methods: NIH Research Portfolio Online Reporting Tools (RePORT) was queried for American Pediatric Surgical Association (APSA) members (2012 vs 2022). Demographics and time-to-award (TTA) from fellowship were compared. Number of grants, funding allotment, award classification, administering institutes/centers, research type were studied., Results: Thirty-eight (4.6%) APSA members were NIH-funded in 2012 compared to 37 (2.9%) in 2022. Of funded surgeons in 2022, 27% were repeat awardees from 2012. TTA was similar (12 vs 14years, p=0.109). At each point, awards were commonly R01 grants (40 vs 52%, p ​= ​0.087) and basic science-related (76 vs 63%, p = ​0.179). Awardees were predominantly men (82% in 2012 vs 78% in 2022, p=0.779) and White (82% in 2012 vs 76% in 2022, p=0.586). Median amount per grant increased: $254,980 (2012) to $364,025 (2022); by $96,711 for men and $390,911 for women. Median awards for White surgeons increased by $215,699 (p=0.035), and decreased by $30,074 for non-White surgeons, though not significantly (p=0.368)., Conclusion: The landscape of NIH-funded pediatric surgeons has remained unchanged between time points. With a substantial number of repeat awardees, predominance of R01 grants, and a median TTA over a decade after fellowship graduation, the phenotypes of early career pediatric surgeon-scientists are facing academic endangerment., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Aims: Heart failure (HF) is a clinical syndrome with no definitive diagnostic tests. HF registries are often based on manual reviews of medical records of hospitalized HF patients identified using International Classification of Diseases (ICD) codes. However, most HF patients are not hospitalized, and manual review of big electronic health record (EHR) data is not practical. The US Department of Veterans Affairs (VA) has the largest integrated healthcare system in the nation, and an estimated 1.5 million patients have ICD codes for HF (HF ICD-code universe) in their VA EHR. The objective of our study was to develop artificial intelligence (AI) models to phenotype HF in these patients., Methods and Results: The model development cohort (n = 20 000: training, 16 000; validation 2000; testing, 2000) included 10 000 patients with HF and 10 000 without HF who were matched by age, sex, race, inpatient/outpatient status, hospital, and encounter date (within 60 days). HF status was ascertained by manual chart reviews in VA's External Peer Review Program for HF (EPRP-HF) and non-HF status was ascertained by the absence of ICD codes for HF in VA EHR. Two clinicians annotated 1000 random snippets with HF-related keywords and labelled 436 as HF, which was then used to train and test a natural language processing (NLP) model to classify HF (positive predictive value or PPV, 0.81; sensitivity, 0.77). A machine learning (ML) model using linear support vector machine architecture was trained and tested to classify HF using EPRP-HF as cases (PPV, 0.86; sensitivity, 0.86). From the 'HF ICD-code universe', we randomly selected 200 patients (gold standard cohort) and two clinicians manually adjudicated HF (gold standard HF) in 145 of those patients by chart reviews. We calculated NLP, ML, and NLP + ML scores and used weighted F scores to derive their optimal threshold values for HF classification, which resulted in PPVs of 0.83, 0.77, and 0.85 and sensitivities of 0.86, 0.88, and 0.83, respectively. HF patients classified by the NLP + ML model were characteristically and prognostically similar to those with gold standard HF. All three models performed better than ICD code approaches: one principal hospital discharge diagnosis code for HF (PPV, 0.97; sensitivity, 0.21) or two primary outpatient encounter diagnosis codes for HF (PPV, 0.88; sensitivity, 0.54)., Conclusions: These findings suggest that NLP and ML models are efficient AI tools to phenotype HF in big EHR data to create contemporary HF registries for clinical studies of effectiveness, quality improvement, and hypothesis generation., (© 2024 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)

Accumulation of heavy metals in the body has been shown to affect the phenotypic age (PhenoAge). However, the combined and threshold effects of blood heavy metals on the risk of PhenoAge acceleration (PhenoAgeAccel) are not well understood. A cross-sectional study was conducted using blood heavy metal data (N = 7763, age ≥18 years) from the 2015-2018 National Health and Nutrition Examination Survey. PhenoAgeAccel was calculated from actual age and nine biomarkers. Multiple regression equations were used to describe the relationship between heavy metals and PhenoAgeAccel. Least Absolute Shrinkage and Selection Operator (LASSO) regression modeling was used to explore the relationship between the combined effects of heavy metals and PhenoAgeAccel. Threshold effect and multiple regression analyses were performed to explore the linear and nonlinear relationships between heavy metals and PhenoAgeAccel. Threshold effect analysis showed that blood mercury (Hg) concentration was linearly associated with PhenoAgeAccel. In contrast, lead (Pb), cadmium (Cd), manganese (Mn), and combined exposure were nonlinearly associated with PhenoAgeAccel. In addition, the combination of Pb, Cd, Hg, and Mn significantly affected PhenoAgeAccel. The risk of PhenoAgeAccel was increased by 207% (P < 0.0001). Meanwhile, a threshold relationship was found between blood Pb, Cd, Mn, and the occurrence of PhenoAgeAccel. Overall, our results indicate that combined exposure to heavy metals may increase the risk of PhenoAgeAccel. This study underscores the need to reduce heavy metal pollution in the environment and provides a reference threshold for future studies., (© 2024. The Author(s), under exclusive licence to Springer Nature B.V.)

Background: Productive life (PL) of a cow is the time the cow remains in the milking herd from first calving to exit from the herd due to culling or death and is an important economic trait in U.S. Holstein cattle. The large samples of Holstein genomic evaluation data that have become available recently provided unprecedented statistical power to identify genetic factors affecting PL in Holstein cows using the approach of genome-wide association study (GWAS)., Methods: The GWAS analysis used 1,103,641 Holstein cows with phenotypic observations on PL and genotypes of 75,282 single nucleotide polymorphism (SNP) markers. The statistical tests and estimation of SNP additive and dominance effects used the approximate generalized least squares method implemented by the EPISNPmpi computer program., Results: The GWAS detected 5390 significant additive effects of PL distributed over all 29 autosomes and the X-Y nonrecombining region of the X chromosome (Chr31). Two chromosome regions had the most significant and largest cluster of additive effects, the SLC4A4-GC-NPFFR2 (SGN) region of Chr06 with pleiotropic effects for PL, fertility, somatic cell score and milk yield; and the 32-52 Mb region of Chr10 with peak effects for PL in or near RASGRP1 with many important immunity functions. The dominance tests detected 38 significant dominance effects including 12 dominance effects with sharply negative homozygous recessive genotypes on Chr18, Chr05, Chr23 and Chr24., Conclusions: The GWAS results showed that highly significant genetic effects for PL were in chromosome regions known to have highly significant effects for fertility and health and a chromosome region with multiple genes with reproductive and immunity functions. SNPs with rare but sharply negative homozygous recessive genotypes for PL existed and should be used for eliminating heifers carrying those homozygous recessive genotypes., (© 2024. The Author(s).)

Objective: Polygenic risk scores (PRS) for diverticular disease must be evaluated in diverse cohorts. We sought to explore shared genetic predisposition across the phenome and to assess risk stratification in individuals genetically similar to European, African and Admixed-American reference samples., Methods: A 44-variant PRS was applied to the All of Us Research Program. Phenome-wide association studies (PheWAS) identified conditions linked with heightened genetic susceptibility to diverticular disease. To evaluate the PRS in risk stratification, logistic regression models for symptomatic and for severe diverticulitis were compared with base models with covariates of age, sex, body mass index, smoking and principal components. Performance was assessed using area under the receiver operating characteristic curves (AUROC) and Nagelkerke's R 2 ., Results: The cohort comprised 181 719 individuals for PheWAS and 50 037 for risk modelling. PheWAS identified associations with diverticular disease, connective tissue disease and hernias. Across ancestry groups, one SD PRS increase was consistently associated with greater odds of severe (range of ORs (95% CI) 1.60 (1.27 to 2.02) to 1.86 (1.42 to 2.42)) and of symptomatic diverticulitis ((95% CI) 1.27 (1.10 to 1.46) to 1.66 (1.55 to 1.79)) relative to controls. European models achieved the highest AUROC and Nagelkerke's R 2 (AUROC (95% CI) 0.78 (0.75 to 0.81); R 2 0.25). The PRS provided a maximum R 2 increase of 0.034 and modest AUROC improvement., Conclusion: Associations between a diverticular disease PRS and severe presentations persisted in diverse cohorts when controlling for known risk factors. Relative improvements in model performance were observed, but absolute change magnitudes were modest., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: The objective is to determine whether unsupervised machine learning identifies traumatic brain injury (TBI) phenotypes with unique clinical profiles., Methods: Pilot self-reported survey data of over 10,000 adults were collected from the Centers for Disease Control and Prevention (CDC)'s National Concussion Surveillance System (NCSS). Respondents who self-reported a head injury in the past 12 months ( n  = 1,364) were retained and queried for injury, outcome, and clinical characteristics. An unsupervised machine learning algorithm, partitioning around medoids (PAM), that employed Gower's dissimilarity matrix, was used to conduct a cluster analysis., Results: PAM grouped respondents into five TBI clusters (phenotypes A-E). Phenotype C represented more clinically severe TBIs with a higher prevalence of symptoms and association with worse outcomes. When compared to individuals in Phenotype A, a group with few TBI-related symptoms, individuals in Phenotype C were more likely to undergo medical evaluation (odds ratio [OR] = 9.8, 95% confidence interval[CI] = 5.8-16.6), have symptoms that were not currently resolved or resolved in 8+ days (OR = 10.6, 95%CI = 6.2-18.1), and more likely to report at least moderate impact on social (OR = 54.7, 95%CI = 22.4-133.4) and work (OR = 25.4, 95%CI = 11.2-57.2) functioning., Conclusion: Machine learning can be used to classify patients into unique TBI phenotypes. Further research might examine the utility of such classifications in supporting clinical diagnosis and patient recovery for this complex health condition.

Background: Frailty is a dynamic aging-related syndrome, but measuring frailty transitions is challenging. The Faurot frailty index is a validated Medicare claims-based frailty proxy based on demographic and billing information. We evaluated whether 3-year changes in the Faurot frailty index were consistent with concurrent changes in the frailty phenotype in a cohort of older adults., Methods: We used longitudinal data from the National Health and Aging Trends Study (NHATS) with Medicare claims linkage (2010-2018). We identified older adults (66+ years) in the 2011 and 2015 NHATS cohorts with at least 1 year of Medicare fee-for-service continuous enrollment (N = 6 951). We described annual changes in mean claims-based frailty for up to 3 years, based on concurrent transitions in the frailty phenotype., Results: At baseline, 32% were robust, 48% prefrail, and 19% frail based on the frailty phenotype. Mean claims-based frailty for older adults who were robust at baseline and worsened to frail increased over 3 years (0.09-0.25). Similarly, those who worsened from prefrail to frail experienced an increase in mean claims-based frailty (0.14-0.26). Improvements in the frailty phenotype did not correspond to decreases in claims-based frailty. Older adults whose frailty phenotype improved over time had a lower baseline claims-based frailty score than those who experienced stable or worsening frailty., Conclusions: Older adults who experienced a frailty phenotype worsening over 3 years experienced concurrent increases in the Faurot frailty index. Our results suggest that claims data may be used to identify clinically meaningful worsening in frailty., (© The Author(s) 2024. Published by Oxford University Press on behalf of The Gerontological Society of America.)

Background: Obesity correlates with accelerated aging. This study aims to investigate the association between the visceral adiposity index (VAI) and accelerated aging., Methods: Biological aging was evaluated by phenotypic age acceleration (PhenoAgeAccel). Utilizing data from the National Health and Nutrition Examination Survey (NHANES) conducted between 1999 and 2010, we employed weighted multivariable logistic regression models, along with subgroup analysis, to examine the association between VAI and PhenoAgeAccel. Moreover, smooth curve fitting was utilized to identify potential nonlinear association, complemented by a two-piece linear regression model to investigate threshold effects., Results: Of the included 11,340 participants aged 20 years and older, the mean (95% CI) age was 46.569 (45.946, 47.191) years, and 49.189% were male. The mean (95% CI) VAI for all participants was 2.176 (2.114, 2.238), and the mean (95% CI) PhenoAgeAccel was -6.306 (-6.618, -5.994) years. In the fully adjusted model, each incremental unit increase of VAI was associated with a 0.312-year increase in PhenoAgeAccel (β = 0.312, 95% CI: 0.217, 0.408). This positive association was more statistically significant among individuals with cancer. Furthermore, a segmented association was observed between VAI and PhenoAgeAccel, with a turning point identified at 10.543. Below this threshold, VAI exhibited a positive correlation with PhenoAgeAccel (β = 0.617, 95% CI: 0.499, 0.735), while beyond it, the association became nonsignificant., Conclusion: This study demonstrated a positive association between VAI and accelerated aging within a nationally representative population. The findings suggest that controlling adiposity may exert anti-aging effects and help prevent aging-related diseases., (Copyright © 2024 The Authors. Published by Elsevier Masson SAS.. All rights reserved.)

Recurrent epiphytotics of X-disease, caused by ' Candidatus Phytoplasma pruni,' have inflicted significant losses on commercial cherry and peach production across North America in the last century. During this period, there have been multiple studies reporting different disease phenotypes and, more recently, identifying different strains through sequencing core genes, but the symptoms have not, to date, been linked with genotype. Therefore, in this study we collected and assessed differing disease phenotypes from multiple U.S. states and conducted multilocus sequence analysis on these strains. We identified a total of five lineages associated with the induction of X-disease on commercial Prunus species and two lineages that were associated with wild P. virginiana . Despite a century of interstate plant movement, there were regional trends in terms of lineages present, and lineage-specific symptoms were observed on P. avium , P. cerasus , and P. virginiana , but not on P. persica . Cumulatively, these data have allowed us to define "true" X-disease-inducing strains of concern to the stone fruit industry across North America, as well as potential sources of infection that exist in the extraorchard environment., Competing Interests: The author(s) declare no conflict of interest.

Background: Few reports describe the yield of postmortem genetic testing from medical examiners' offices or correlate genetic test results with autopsy-confirmed phenotypes from a large cohort., Objectives: To report results from cardiomyopathy- and cardiac arrhythmia-associated genetic testing in conjunction with autopsy findings of cases investigated at the United States' largest medical examiner office., Methods: Postmortem cases tested from 2015 to 2022 with a cardiomyopathy- and cardiac arrhythmia-associated gene panel were reviewed. American College of Medical Genetics and Genomics/Association for Molecular Pathology guidelines were used to classify variant pathogenicity. Correlations of pathogenic/likely pathogenic variants (P/LPVs) with cardiac pathology were evaluated., Results: The cohort included 1107 decedents of diverse ages and ethnicities. P/LPVs were detected in 87 (7.9%) cases, with 73 and 14 variants in cardiomyopathy and cardiac arrhythmia genes, respectively. Variants of uncertain significance were detected in 437 (39.5%) cases. The diagnostic yield (percentage of P/LPV) in decedents with cardiomyopathy (26.1%) was significantly higher than those without (P<.0001). The diagnostic yield was significantly lower in infants (0.7%) than older age groups (ranging from 1 to 74 years old, 5.7%-25.9%), which had no statistical difference between their yields. The diagnostic yields by cardiac autopsy findings were 54.0% for hypertrophic cardiomyopathy, 47.1% for arrhythmogenic cardiomyopathy, 20.0% for myocardial fibrosis, 19.0% for dilated cardiomyopathy, and 11.3% for myocarditis. Most P/LPVs were in MYBPC3, TTN, PKP2, SCN5A, MYH7, and FLNC. Ten P/LPVs were novel., Conclusions: Our results support the importance of performing postmortem genetic testing on decedents of all ages with cardiomyopathy, cardiac lesions insufficient to diagnosis a specific cardiomyopathy (e.g., myocardial fibrosis), and myocarditis. Combined postmortem cardiac examination and genetic analysis are advantageous in accurately determining the underlying cause of death and informing effective clinical care of family members., Competing Interests: Declaration of competing interest None., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Twenty years after the arrival of soybean aphid, Aphis glycines Matsumura (Hemiptera: Aphididae), in the United States, it remains the most economically important arthropod pest of soybean in the Upper Midwest Region. After years of repeated and sustained insecticidal pressures placed on the aphid, resistance to the pyrethroid class of insecticides has been documented in multiple years over a large geographic area. In this study, the fitness of aphid isolates displaying resistant and susceptible phenotypes to λ-cyhalothrin were compared within several experiments over three soybean-growing seasons. Rates of population increase were evaluated on whole plants in the greenhouse, intrinsic rates of increase were calculated from leaf discs in the laboratory, and aphid size and asymmetry were compared through tibial measurements. No evidence of a fitness cost associated with the resistant phenotype was seen in any of our experiments. In contrast, individual resistant isolates occasionally supported significantly higher fitness values than some susceptible isolates. Additionally, a pooled analysis comparing resistant and susceptible phenotypes across years and isolates revealed that, on average, the resistant phenotype had significantly higher fitness values than the susceptible phenotype in most experiments. The lack of reproductive fitness costs associated with the pyrethroid-resistant phenotype raises concerns for longevity of pyrethroid use in soybean aphid management. [ABSTRACT FROM AUTHOR]

The Mouse Metabolic Phenotyping Center (MMPC)Live Program was established in 2023 by the National Institute for Diabetes, Digestive and Kidney Diseases (NIDDK) at the National Institutes of Health (NIH) to advance biomedical research by providing the scientific community with standardized, high quality phenotyping services for mouse models of diabetes and obesity. Emerging as the next iteration of the MMPC Program which served the biomedical research community for 20 years (2001-2021), MMPCLive is designed as an outwardly-facing consortium of service cores that collaborate to provide reduced-cost consultation and metabolic, physiologic, and behavioral phenotyping tests on live mice for U.S. biomedical researchers. Four MMPCLive Centers located at universities around the country perform complex and often unique procedures in vivo on a fee for service basis, typically on mice shipped from the client or directly from a repository or vendor. Current areas of expertise include energy balance and body composition, insulin action and secretion, whole body carbohydrate and lipid metabolism, cardiovascular and renal function, food intake and behavior, microbiome and xenometabolism, and metabolic pathway kinetics. Additionally, an opportunity arose to reduce barriers to access and expand the diversity of the biomedical research workforce by establishing the VIBRANT Program. Directed at researchers historically underrepresented in the biomedical sciences, VIBRANT-eligible investigators have access to testing services, travel and career development awards, expert advice and experimental design consultation, and short internships to learn test technologies. Data derived from experiments run by the Centers belongs to the researchers submitting mice for testing which can be made publicly available and accessible from the MMPCLive database following publication. In addition to services, MMPCLive staff provide expertise and advice to researchers, develop and refine test protocols, engage in outreach activities, publish scientific and technical papers, and conduct educational workshops and training sessions to aid researchers in unraveling the heterogeneity of diabetes and obesity., (© 2024. The Author(s).)

Background and Objective: Chronic obstructive pulmonary disease (COPD) is a leading cause of death worldwide that frequently presents with concomitant cardiovascular diseases. Despite the pathological distinction between individual COPD phenotypes such as emphysema and chronic bronchitis, there is a lack of knowledge about the impact of COPD phenotype on cardiovascular disease risk. Thus, this study aimed to utilize a nationally representative sample to investigate cardiovascular disease prevalence in patients with COPD with emphysema and chronic bronchitis phenotypes., Methods: Data from 31,560 adults including 2504 individuals with COPD, collected as part of the National Health and Nutrition Examination Survey (1999-2018), were examined., Results: A significantly increased cardiovascular disease risk, including coronary heart disease, heart failure, myocardial infarction and stroke, was identified in patients with COPD among all disease phenotypes. Particularly, compared to those without COPD, individuals with chronic bronchitis presented with 1.76 (95% CI: 1.41-2.20) times greater odds, individuals with emphysema with 2.31 (95% CI: 1.80-2.96) times greater odds, while those with a concurrent phenotype (combined chronic bronchitis and emphysema) exhibited 2.98 (95% CI: 2.11-4.21) times greater odds of reporting cardiovascular diseases., Conclusion: Our data confirms that patients with COPD present an elevated risk of developing cardiovascular disease among all phenotypes, with the most marked increase being in those with concurrent chronic bronchitis and emphysema phenotypes. These findings emphasize the need for awareness and appropriate cardiovascular screening in COPD., (© 2024 The Author(s). Respirology published by John Wiley & Sons Australia, Ltd on behalf of Asian Pacific Society of Respirology.)

Despite the availability of effective medications, the majority of pediatric and adult patients with persistent asthma have uncontrolled symptoms. This has been attributed to patient nonadherence and poor self-management, but clinicians also contribute through inaccurate assessment of asthma and lack of familiarity with best practice guidelines for medication management. Thus, improving patient outcomes will require improving clinical management by health care providers, including utilization of evidence-based practice guidelines. In this report, we briefly summarize key points of the national guidelines for asthma management and delineate important changes enacted by 2020 Expert Panel Report-4 updates. These include revised recommendations on the use of fractional exhaled nitric oxide testing, indoor allergen mitigation, bronchial thermoplasty, adjunctive immunotherapy, and important modifications to medication management that are likely to have widespread impact on prescribing throughout the United States. In particular, for all patients aged five years and older taking stepwise therapy levels 3-4, it is now recommended to use Single Maintenance and Reliever Therapy , whereas the use of intermittent inhaled corticosteroids (ICSs) administered at the same time as short-acting beta agonist is recommended for step 2 to reduce symptom burden, improve control, and minimize total ICS dose. [ABSTRACT FROM AUTHOR]

Key Message: Multi-environmental characterization of flag leaf morphology traits in the US winter wheat revealed nine stable genomic regions for different flag leaf-related traits including a major region governing flag leaf angle. Flag leaf in wheat is the primary contributor to accumulating photosynthetic assimilates. Flag leaf morphology (FLM) traits determine the overall canopy structure and capacity to intercept the light, thus influencing photosynthetic efficiency. Hence, understanding the genetic control of these traits could be useful for breeding desirable ideotypes in wheat. We used a panel of 272 accessions from the hard winter wheat (HWW) region of the USA to investigate the genetic architecture of five FLM traits including flag leaf length (FLL), width (FLW), angle (FLANG), length-width ratio, and area using multilocation field experiments. Multi-environment GWAS using 14,537 single-nucleotide polymorphisms identified 36 marker-trait associations for different traits, with nine being stable across environments. A novel and major stable region for FLANG (qFLANG.1A) was identified on chromosome 1A accounting for 9-13% variation. Analysis of spatial distribution for qFLANG.1A in a set of 2354 breeding lines from the HWW region showed a higher frequency of allele associated with narrow leaf angle. A KASP assay was developed for allelic discrimination of qFLANG.1A and was used for its independent validation in a diverse set of spring wheat accessions. Furthermore, candidate gene analysis for two regions associated with FLANG identified seven putative genes of interest for each of the two regions. The present study enhances our understanding of the genetic control of FLM in wheat, particularly FLANG, and these results will be useful for dissecting the genes underlying canopy architecture in wheat facilitating the development of climate-resilient wheat varieties., (© 2024. The Author(s).)

Background: Chronological age (CA) is an imperfect proxy for the true biological aging state of the body. As novel measures of biological aging, Phenotypic age (PhenoAge) and Phenotypic age acceleration (PhenoAgeAccel), have been shown to identify morbidity and mortality risks in the general population., Hypothesis: PhenoAge and PhenoAgeAccel might be associated with mortality in heart failure (HF) patients., Methods: This cohort study extracted adult data from the National Health and Nutrition Examination Survey (NHANES) databases. Weighted univariable and multivariable Cox models were performed to analyze the effect of PhenoAge and PhenoAgeAccel on all-cause mortality in HF patients, and hazard ratio (HR) with 95% confidence intervals (CI) was calculated., Results: In total, 845 HF patients were identified, with 626 all-cause mortality patients. The findings suggested that (1) each 1- and 10-year increase in PhenoAge were associated with a 3% (HR = 1.03, 95% CI: 1.03-1.04) and 41% (HR = 1.41, 95% CI: 1.29-1.54) increased risk of all-cause mortality, respectively; (2) when the PhenoAgeAccel < 0 as reference, the ≥ 0 group was associated with higher risk of all-cause mortality (HR = 1.91, 95% CI = 1.49-2.45). Subgroup analyses showed that (1) older PhenoAge was associated with an increased risk of all-cause mortality in all subgroups; (2) when the PhenoAgeAccel < 0 as a reference, PhenoAgeAccel ≥ 0 was associated with a higher risk of all-cause mortality in all subgroups., Conclusion: Older PhenoAge was associated with an increased risk of all-cause mortality in HF patients. PhenoAge and PhenoAgeAccel can be used as convenient tools to facilitate the identification of at-risk individuals with HF and the evaluation of intervention efficacy., (© 2024 The Author(s). Clinical Cardiology published by Wiley Periodicals, LLC.)

Over the past three decades, high-throughput phenotypic cancer cell line screens have revealed unanticipated small-molecule activities and illuminated connections between tumor genotypes and anticancer efficacy. Founded in 1984, the National Cancer Institute's "NCI60" screen laid the conceptual groundwork for the contemporary landscape of phenotypic drug discovery. NCI60 first operated as a primary bioactivity screen, but molecular characterization of the NCI60 cell line panel and development of a small-molecule sensitivity pattern recognition algorithm (called "COMPARE") have enabled subsequent studies into drug mechanisms of action and biomarker identification. In this issue of Cancer Research, Kunkel and colleagues report an updated version of the NCI60 screen, dubbed "HTS384" NCI60, that better aligns with current cell proliferation assay standards and has higher throughput. Changes include the use of a 384-well plate format, automated laboratory equipment, 3 days of compound exposure, and a CellTiter-Glo luminescent endpoint. To confirm that data from the HTS384 and classic NCI60 screen are comparable, the authors tested a library of 1,003 anticancer agents using both protocols and applied COMPARE to analyze patterns of cell line sensitivities. More than three dozen groups of targeted therapies showed high comparability between screens. Modernization of NCI60, and closer integration with other large-scale pharmacogenomic screens and molecular feature sets, will help this public screening service remain pertinent for cancer drug discovery efforts for years to come. See related article by Kunkel et al., p. 2403., (©2024 American Association for Cancer Research.)

The Department of Veterans Affairs (VA) utilizes a pharmacogenomic (PGx) program that analyzes specific "pharmacogenes." This study evaluates the effect that pharmacogenes may have on prevalence of polypharmacy. This retrospective cohort study included patients with VA prescriptions who underwent PGx testing. We quantified prescriptions active or recently expired at the time of PGx testing. We constructed two co-primary polypharmacy (≥10 medications) end points: (i) based on all medications and (ii) requiring that at least one medication was affected by a pharmacogene of interest. Pharmacogenes and actionable phenotypes of interest included poor and ultrarapid metabolizers for CYP2D6, CYP2C9, and CYP2C19 and intermediate and normal metabolizers for CYP3A5. Patients were classified as having 0, 1, and 2+ total phenotypes across all genes. Of the 15,144 patients screened, 13,116 met eligibility criteria. Across phenotype cohorts, there was no significant association with polypharmacy using all medications, number of total medications, or number of medications affected by phenotypes. However, there was a significant difference in patients with polypharmacy prescribed ≥1 medication impacted by PGx across phenotype groups: 2,514/4,949 (51%), 1,349/2,595 (52%), 204/350 (58%) (P = 0.03, OR 1.31, 95% CI 1.02-1.67). The median number of medications affected by PGx phenotypes with ≥1 PGx-impacted medication across phenotype groups was a median of 0 (IQR 0, 0), 0 (IQR 0, 0), and 1 (IQR 0, 1) (P < 0.001). In patients prescribed ≥1 medication impacted by PGx, those with more actionable pharmacogenomic phenotypes were more likely to meet polypharmacy criteria., (Published 2024. This article is a U.S. Government work and is in the public domain in the USA.)

Background: Adverse events associated with vaccination have been evaluated by epidemiological studies and more recently have gained additional attention with the emergency use authorization of several COVID-19 vaccines. As part of its responsibility to conduct postmarket surveillance, the US Food and Drug Administration continues to monitor several adverse events of special interest (AESIs) to ensure vaccine safety, including for COVID-19., Objective: This study is part of the Biologics Effectiveness and Safety Initiative, which aims to improve the Food and Drug Administration's postmarket surveillance capabilities while minimizing public burden. This study aimed to enhance active surveillance efforts through a rules-based, computable phenotype algorithm to identify 5 AESIs being monitored by the Center for Disease Control and Prevention for COVID-19 or other vaccines: anaphylaxis, Guillain-Barré syndrome, myocarditis/pericarditis, thrombosis with thrombocytopenia syndrome, and febrile seizure. This study examined whether these phenotypes have sufficiently high positive predictive value (PPV) to ensure that the cases selected for surveillance are reasonably likely to be a postbiologic adverse event. This allows patient privacy, and security concerns for the data sharing of patients who had nonadverse events can be properly accounted for when evaluating the cost-benefit aspect of our approach., Methods: AESI phenotype algorithms were developed to apply to electronic health record data at health provider organizations across the country by querying for standard and interoperable codes. The codes queried in the rules represent symptoms, diagnoses, or treatments of the AESI sourced from published case definitions and input from clinicians. To validate the performance of the algorithms, we applied them to electronic health record data from a US academic health system and provided a sample of cases for clinicians to evaluate. Performance was assessed using PPV., Results: With a PPV of 93.3%, our anaphylaxis algorithm performed the best. The PPVs for our febrile seizure, myocarditis/pericarditis, thrombocytopenia syndrome, and Guillain-Barré syndrome algorithms were 89%, 83.5%, 70.2%, and 47.2%, respectively., Conclusions: Given our algorithm design and performance, our results support continued research into using interoperable algorithms for widespread AESI postmarket detection., (©Ashley A Holdefer, Jeno Pizarro, Patrick Saunders-Hastings, Jeffrey Beers, Arianna Sang, Aaron Zachary Hettinger, Joseph Blumenthal, Erik Martinez, Lance Daniel Jones, Matthew Deady, Hussein Ezzeldin, Steven A Anderson. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 15.07.2024.)

Obesity is a heritable disease, characterised by excess adiposity that is measured by body mass index (BMI). While over 1,000 genetic loci are associated with BMI, less is known about the genetic contribution to adiposity trajectories over adulthood. We derive adiposity-change phenotypes from 24.5 million primary-care health records in over 740,000 individuals in the UK Biobank, Million Veteran Program USA, and Estonian Biobank, to discover and validate the genetic architecture of adiposity trajectories. Using multiple BMI measurements over time increases power to identify genetic factors affecting baseline BMI by 14%. In the largest reported genome-wide study of adiposity-change in adulthood, we identify novel associations with BMI-change at six independent loci, including rs429358 (APOE missense variant). The SNP-based heritability of BMI-change (1.98%) is 9-fold lower than that of BMI. The modest genetic correlation between BMI-change and BMI (45.2%) indicates that genetic studies of longitudinal trajectories could uncover novel biology of quantitative traits in adulthood., (© 2024. The Author(s).)

Johne's disease (JD) is an infectious enteric disease in ruminants, causing substantial economic loss annually worldwide. This work aimed to estimate JD's genetic parameters and the phenotypic and genetic trends by incorporating recent data. It also explores the feasibility of a national genetic evaluation for JD susceptibility in Holstein cattle in the United States. The data were extracted from a JD data repository, maintained at the Council on Dairy Cattle Breeding, and initially supplied by 2 dairy record processing centers. The data comprised 365,980 Holstein cows from 1,048 herds participating in a voluntary control program for JD. Two protocol kits, IDEXX Paratuberculosis Screening Ab Test (IDX) and Parachek 2 (PCK), were used to analyze milk samples with the ELISA technique. Test results from the first 5 parities were considered. An animal was considered infected if it had at least one positive outcome. The overall average of JD incidence was 4.72% in these US Holstein cattle. Genotypes of 78,964 SNP markers were used for 25,000 animals randomly selected from the phenotyped population. Variance components and genetic parameters were estimated based on 3 models, namely, a pedigree-only threshold model (THR), a single-step threshold model (ssTHR), and a single-step linear model (ssLR). The posterior heritability estimates of JD susceptibility were low to moderate: 0.11 to 0.16 based on the 2 threshold models and 0.05 to 0.09 based on the linear model. The average reliability of EBVs of JD susceptibility using single-step analysis for animals with or without phenotypes varied from 0.18 (THR) to 0.22 (ssLR) for IDX and from 0.14 (THR) to 0.18 (ssTHR and ssLR) for PCK. Despite no prior direct genetic selection against JD, the estimated genetic trends of JD susceptibility were negative and highly significant. The correlations of bulls' PTA with economically important traits such as milk yield, milk protein, milk fat, somatic cell score, and mastitis were low, indicating a nonoverlapping genetic selection process with traits in current genetic evaluations. Our results suggest the feasibility of reducing the JD incidence rate by incorporating it into the national genetic evaluation programs., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Widespread species often experience significant environmental clines over the area they naturally occupy. We investigated a widespread livebearing fish, the Sailfin molly (Poecilia latipinna) combining genetic, life-history, and environmental data, asking how structured populations are. Sailfin mollies can be found in coastal freshwater and brackish habitats from roughly Tampico, Veracruz in Mexico to Wilmington, North Carolina, in the USA. In addition, they are found inland on the Florida peninsula. Using microsatellite DNA, we genotyped 168 individuals from 18 populations covering most of the natural range of the Sailfin molly. We further determined standard life-history parameters for both males and females for these populations. Finally, we measured biotic and abiotic parameters in the field. We found six distinct genetic clusters based on microsatellite data, with very strong indication of isolation by distance. However, we also found significant numbers of migrants between adjacent populations. Despite genetic structuring we did not find evidence of cryptic speciation. The genetic clusters and the migration patterns do not match paleodrainages. Life histories vary between populations but not in a way that is easy to interpret. We suggest a role of humans in migration in the sailfin molly, for example in the form of a ship channel that connects southern Texas with Louisiana which might be a conduit for fish migration., (© 2024. The Author(s).)

Background and Aims: Hepatic steatosis is known to be heritable, but its genetic basis is mostly uncharacterized. Steatosis is associated with metabolic and adiposity features; recent studies hypothesize that shared genetic effects between these traits could account for some of the unexplained heritability. This study aimed to quantify these genetic associations in a family-based sample of non-Hispanic white adults., Methods and Results: 704 participants (18-95 years, 55.8% female) from the Fels Longitudinal Study with an MRI assessment of liver fat were included. Quantitative genetic analyses estimated the age- and sex-adjusted heritability of individual traits and the genetic correlations within trait pairs. Mean liver fat was 5.95% (SE = 0.23) and steatosis (liver fat >5.56%) was present in 29.8% of participants. Heritability (h 2 ± SE) of steatosis was 0.72 ± 0.17 (p = 6.80e -6 ). All other traits including liver enzymes, fasting glucose, HOMA-IR, visceral and subcutaneous adipose tissue (VAT, SAT), body mass index, body fat percent, waist circumference, lipids and blood pressure were also heritable. Significant genetic correlations were found between liver fat and all traits except aspartate aminotransferase (AST), and among most trait pairs. Highest genetic correlations were between liver fat and HOMA-IR (0.85 ± 0.08, p = 1.73e -8 ), fasting glucose and ALT (0.89 ± 0.26, p = 6.68e -5 ), and HOMA-IR with: waist circumference (0.81 ± 0.12, p = 3.76e -6 ), body fat percent (0.78 ± 0.12 p = 2.42e -5 ) and VAT (0.73 ± 0.07, p = 6.37e -8 )., Conclusions: Common genes may exist between liver fat accumulation, metabolic features and adiposity phenotypes., Competing Interests: Declaration of competing interest The authors declare that they have no conflicts of interest concerning this article., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Objective: The primary objective was to describe rates of general and pain-related psychological distress for individuals with low back pain (LBP) in the Military Health System (MHS). We identified common phenotypes defined by rates of general and pain-related psychological distress and compared phenotypes on their level of pain interference, physical function, anxiety, and depression., Methods: We created a cohort from two completed trials assessing nonpharmacological treatment for LBP in the MHS (n = 510 total). The Optimal Screening for Prediction of Referral and Outcome Yellow Flag assessment tool identified the presence of 11 different yellow flags. Latent class analysis (LCA) used yellow flag indicators to identify common psychological phenotypes. We then compared Patient-Reported Outcomes Measurement Information Systems measures of pain interference, physical function, sleep disturbance, depression, and anxiety across phenotypes., Results: LCA identified five phenotypes (percentage of the sample): low distress (32%), high distress (27%), poor pain coping and low self-efficacy (18%), low self-efficacy and acceptance (14%), and poor pain coping (10%). Highly distressed phenotypes reported higher levels of pain interference, sleep disturbance, depression, and anxiety than those with other phenotypes, whereas the low distress phenotype had significantly lower pain interference and higher physical function scores than those characterized by all other phenotypes., Conclusion: These phenotypes provide opportunities for clinicians and researchers to develop novel LBP treatment pathways tailored to patients with different profiles of psychological distress. Future work is needed to validate their predictive capabilities for clinical outcomes., (© 2024 American College of Rheumatology. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)

Background: Social psychoneuroimmunology suggests an interplay between social deficits (loneliness and isolation) and chronic inflammation, but the direction of these relationships remains unclear. We estimated the reciprocal associations of social deficits and social engagement with levels of C-reactive protein (CRP), compared the consistency of the findings depending on the biological sampling method used, and examined the modifying role of phenotypic and genotypic depression., Methods: We used longitudinal nationally representative data from the US (Health and Retirement Study, 3 waves, 2006-16) and England (English Longitudinal Study of Ageing, 4 waves, 2004-18). Loneliness, social isolation, and social engagement were self-reported. CRP was measured using dried blood spots (US) and venous blood samples (England). Cross-lagged panel models were fitted and tested interactions with phenotypic depression (above-threshold depressive symptom scores) and genotypic depression (polygenic score for major depressive disorder)., Results: We included 15,066 participants (mean age = 66.1 years, SD = 9.8) in the US and 10,290 (66.9 years, SD = 10.5) in England. We found reciprocal associations between loneliness and CRP using dried blood spots and venous blood samples. Higher CRP predicted higher subsequent loneliness and higher loneliness predicted elevated CRP. Both phenotypic and genotypic depression modified this reciprocal association. There were also reciprocal associations for social engagement in venous blood samples: higher CRP predicted lower social engagement and greater social engagement predicted lower subsequent CRP. Associations between social isolation and CRP were inconsistent and unidirectional., Conclusions: Loneliness may increase chronic inflammation, whereas social engagement may reduce inflammation. As these relationships were reciprocal, there may be a loop between inflammation, loneliness, and social engagement. This loop was stronger in those with depression or at high genetic risk for major depressive disorder. This relationship for loneliness was present in both blood sampling methods despite contrasting methods of CRP measurement, indicating that the finding is not attributable to measurement bias in biomarkers., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Puccinia coronata f. sp. avenae is the causal agent of the disease known as crown rust, which represents a bottleneck in oat production worldwide. Characterization of pathogen populations often involves race (pathotype) assignments using differential sets, which are not uniform across countries. This study compared the virulence profiles of 25 P. coronata f. sp. avenae isolates from Australia using two host differential sets, one from Australia and one from the United States. These differential sets were also genotyped using diversity arrays technology sequencing technology. Phenotypic and genotypic discrepancies were detected on 8 out of 29 common lines between the two sets, indicating that pathogen race assignments based on those lines are not comparable. To further investigate molecular markers that could assist in the stacking of rust resistance genes important for Australia, four published Pc91 -linked markers were validated across the differential sets and then screened across a collection of 150 oat cultivars. Drover, Aladdin, and Volta were identified as putative carriers of the Pc91 locus. This is the first report to confirm that the cultivar Volta carries Pc91 and demonstrates the value of implementing molecular markers to characterize materials in breeding pools of oat. Overall, our findings highlight the necessity of examining seed stocks using pedigree and molecular markers to ensure seed uniformity and bring robustness to surveillance methodologies. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license., Competing Interests: The author(s) declare no conflict of interest.

Background and Aim: Left ventricular hypertrophy (LVH) has been shown to be associated with the occurrence of atrial fibrillation (AF). However, the predictive value of the LVH phenotype for incident AF remains uncertain. This study aimed to investigate the predictive value of LVH phenotype for incident AF., Methods and Results: This study utilized the Multi-Ethnic Study of Atherosclerosis (MESA) data. LVH was defined by cardiac magnetic resonance measured LV mass index. Isolated LVH was determined as LVH without elevated cardiac biomarker and malignant LVH was determined as LVH with at least 1 elevated biomarker. Receiver-operating characteristic (ROC) analysis was performed to calculate areas under the curves (AUC) for predicting AF. A total of 4983 community-dwelling participants were included, with a mean age of 61.5 years. 279 (5.6 %) had isolated LVH, and 222 (4.5 %) had malignant LVH. During a median follow-up of 8.5 years, 272 incident AF was observed. Compared to participants without LVH and elevated cardiac biomarkers, those with isolated LVH (HR, 1.82; 95 % CI, 1.03-3.20) and malignant LVH (HR, 4.13; 95 % CI, 2.77-6.16) had a higher risk of incident AF. Malignant LVH carried a 1.5-fold increased risk of AF compared to isolated LVH (HR: 2.48, 95 % CI: 1.30-4.73). Including the LVH phenotype in the CHARGE-AF model improved model discrimination (AUC increase: 0.03, p < 0.001)., Conclusions: The risks of AF incidence varied across LVH phenotypes. Malignant LVH carried the highest risk among LVH phenotypes. LVH phenotype provides incremental predictive value over the variables included in the CHARGE-AF model., (Copyright © 2024 The Italian Diabetes Society, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.)

The limited literature and increasing interest in studies on cardiac electrophysiology, explicitly focusing on cardiac ion channelopathies and sudden cardiac death in diverse populations, has prompted a comprehensive examination of existing research. Our review specifically targets Hispanic/Latino and Indigenous populations, which are often underrepresented in healthcare studies. This review encompasses investigations into genetic variants, epidemiology, etiologies, and clinical risk factors associated with arrhythmias in these demographic groups. The review explores the Hispanic paradox, a phenomenon linking healthcare outcomes to socioeconomic factors within Hispanic communities in the United States. Furthermore, it discusses studies exemplifying this observation in the context of arrhythmias and ion channelopathies in Hispanic populations. Current research also sheds light on disparities in overall healthcare quality in Indigenous populations. The available yet limited literature underscores the pressing need for more extensive and comprehensive research on cardiac ion channelopathies in Hispanic/Latino and Indigenous populations. Specifically, additional studies are essential to fully characterize pathogenic genetic variants, identify population-specific risk factors, and address health disparities to enhance the detection, prevention, and management of arrhythmias and sudden cardiac death in these demographic groups., (© 2024 The Authors. Journal of Cardiovascular Electrophysiology published by Wiley Periodicals LLC.)

Engaging with debates about the re-emergence of the race concept in science, this article opens up facial plastic surgery's expertise of racial phenotypes to inquiry. Drawing on ethnographic fieldwork and analysis of medical discourse, it analyses how this expertise is made and put into practice in three nations with large cosmetic surgery markets: the US, Korea, and Brazil. Plastic surgery has drawn on the scientific knowledge of race from fields such as anthropology and anthropometry to make racial features (nose and eyes) into an object of medical intervention. Race has been enacted differently, however, in the three national contexts we discuss according to the changing politics of difference and beauty ideals. While contemporary surgery attempts to sidestep the ethical problems raised by earlier scientific racism and whitening practices, it continues to pathologize non-white racial features by operating on traits it sees as "excessive" or merely typical, rather than beautiful. [ABSTRACT FROM AUTHOR]

Objectives: Assess the impact of heterogeneity among established sepsis criteria (Sepsis-1, Sepsis-3, Centers for Disease Control and Prevention Adult Sepsis Event, and Centers for Medicare and Medicaid severe sepsis core measure 1) through the comparison of corresponding sepsis cohorts.Design: Retrospective analysis of data extracted from electronic health record.Setting: Single, tertiary-care center in St. Louis, MO.Patients: Adult, nonsurgical inpatients admitted between January 1, 2012, and January 6, 2018.Interventions: None.Measurements and Main Results: In the electronic health record data, 286,759 encounters met inclusion criteria across the study period. Application of established sepsis criteria yielded cohorts varying in prevalence: Centers for Disease Control and Prevention Adult Sepsis Event (4.4%), Centers for Medicare and Medicaid severe sepsis core measure 1 (4.8%), International Classification of Disease code (7.2%), Sepsis-3 (7.5%), and Sepsis-1 (11.3%). Between the two modern established criteria, Sepsis-3 (n = 21,550) and Centers for Disease Control and Prevention Adult Sepsis Event (n = 12,494), the size of the overlap was 7,763. The sepsis cohorts also varied in time from admission to sepsis onset (hr): Sepsis-1 (2.9), Sepsis-3 (4.1), Centers for Disease Control and Prevention Adult Sepsis Event (4.6), and Centers for Medicare and Medicaid severe sepsis core measure 1 (7.6); sepsis discharge International Classification of Disease code rate: Sepsis-1 (37.4%), Sepsis-3 (40.1%), Centers for Medicare and Medicaid severe sepsis core measure 1 (48.5%), and Centers for Disease Control and Prevention Adult Sepsis Event (54.5%); and inhospital mortality rate: Sepsis-1 (13.6%), Sepsis-3 (18.8%), International Classification of Disease code (20.4%), Centers for Medicare and Medicaid severe sepsis core measure 1 (22.5%), and Centers for Disease Control and Prevention Adult Sepsis Event (24.1%).Conclusions: The application of commonly used sepsis definitions on a single population produced sepsis cohorts with low agreement, significantly different baseline demographics, and clinical outcomes. [ABSTRACT FROM AUTHOR]

Feralization of genetically engineered (GE) crops increases the risk that transgenes will become integrated into natural and naturalizing plant populations. A key assumption of the management of GE crops is that populations of escaped plants are short-lived and therefore the risks they pose are limited. However, few populations of escaped crop plants have been tracked over the long term so our understanding of their persistence in ruderal or natural landscapes is limited. We repeated a large-scale road survey of feral GE canola populations in North Dakota, USA, initially conducted in 2010. Our objectives in 2021 were to determine the current distribution of feral canola populations, and to establish the relative frequency of GE and non-GE phenotypes in populations of canola throughout North Dakota. Our results indicate that, although the incidence of feral canola was less in 2021 than 2010, escaped canola populations remain common throughout the state. The prevalence of alternate forms of GE herbicide resistance changed between surveys, and we found an overabundance of non-GE plants compared to the frequency of non-transgenic forms in cultivation. Indirect evidence of persistence includes sampling plants with multiple transgenic traits, and finding populations far from transportation routes. We conclude that feral canola populations expressing transgenic herbicide resistance are established outside of cultivation, that they may be under selection for loss of the transgene, but that they nonetheless pose long-term risks by harboring transgenes in the unmanaged landscape., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Travers et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

There are no studies regarding the estimation of genetic parameters and genetic trends for reproductive traits and somatic cells in goats. Their knowledge allows optimization of selection schemes. The objective of this study was to estimate genetic parameters and genetic and phenotypic trends for age at first kidding (AFK), kidding interval (KIN) and somatic cell score (SCS). Analyses were conducted within and across seven US goat breeds, namely, Nubian (NU), Alpine (AL), LaMancha (LM), Toggenburg (TO), Saanen (SA), Nigerian Dwarf (ND) and Oberhasli (OB), and a set of all of these breeds (AB). The restricted maximum likelihood methodology and trivariate animal models were used. Genetic and phenotypic trends were estimated using regression models. The average and standard deviation of AFK, KIN and SCS for AB were 573.6 ± 178.5 days, 418.8 ± 125.5 days and 4.67 ± 2.23 Log2, respectively. The heritabilities (h 2 ) and standard errors of AFK, KIN and SCS for AB were 0.28 ± 0.02, 0.04 ± 0.02 and 0.22 ± 0.01, respectively. The h 2 ranged from 0.15 (SA) to 0.37 (NU) for AFK, from 0.04 (AB) to 0.10 (AL) for KIN, and from 0.11 (TO) to 0.26 (LM and ND) for SCS. Genetic correlations between AFK and KIN and between AFK and SCS for AB were positive and weak (0.07 and 0.12, respectively) but significant (P < 0.01). Genetic correlations between SCS and KIN were significant (P < 0.01) for all the breeds and ranged from -0.15 (NU) to 0.44 (AL). Genetic correlations between AFK and SCS in the NU and AL breeds were similar (approximately 0.21). A positive genetic trend was found for KIN in the SA breed, which caused an increase in the number of days between consecutive kiddings. The genetic trend of SCS for the NU, AL and ND breeds was negative and decreased annually, which is beneficial for producers. These first results show the intensity and direction of some favorable/unfavorable relationships between AFK or KIN and SCS Log2 in some U.S. goat genetic groups., (© 2024. The Author(s), under exclusive licence to Springer Nature B.V.)

Curtobacterium flaccumfaciens (Microbacteriaceae), a plant-pathogenic coryneform species includes five pathovars with valid names and a number of proposed - but unvalidated - new members. In this study, phenotypic features and DNA similarity indexes were investigated among all C. flaccumfaciens members. Results showed that the C. flaccumfaciens pv. poinsettiae strains causing bacterial canker of Euphorbia pulcherrima in the USA as well as the orange-/red-pigmented strains of C. flaccumfaciens pv. flaccumfaciens pathogenic on dry beans in Iran are too distinct from each other and from the type strain of the species to be considered members of C. flaccumfaciens. Hence, the latter two groups were elevated at the species level as C. poinsettiae sp. nov. (ATCC 9682 T  = CFBP 2403 T  = ICMP 2566 T  = LMG 3715 T  = NCPPB 854 T as type strain), and C. aurantiacum sp. nov. (50R T  = CFBP 8819 T  = ICMP 22071 T as type strain). Within the emended species C. flaccumfaciens comb. nov., yellow-pigmented strains causing bacterial wilt of dry beans and those causing bacterial canker of Euphorbia pulcherrima in Europe were retained as C. flaccumfaciens pv. flaccumfaciens and C. flaccumfaciens pv. poinsettiae, respectively; while taxonomic position of the sugar beet pathogen C. flaccumfaciens pv. beticola ATCC BAA144 PT was confirmed. The newly described onion pathogen C. allii was also reclassified as C. flaccumfaciens pv. allii with the pathotype strain LMG 32517 PT . Furthermore, C. flaccumfaciens pv. basellae causing bacterial leaf spot of malabar spinach (Basella rubra) was transferred to C. citreum pv. basellae with ATCC BAA143 PT as pathotype., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier GmbH. All rights reserved.)

Competing theories have been proposed to explain the considerable overlap in social-cognitive features and risk factors across schizotypy and autism spectrum conditions (ASCs). Six previous factor analyses have been reported in the literature, yet all have major limitations; evidence for the clear superiority of any of the competing theories is insufficient and warrants further investigation. The primary aim of the present research was to identify dimensions that cut across schizotypy and ASCs while addressing limitations of past research. Data were collected from three independent samples (n = 1006, 544, and 2469) in the U.S. and China using the Autism-Spectrum Quotient, the Schizotypal Personality Questionnaire, and the Wisconsin Schizotypy Scales. Exploratory factor analyses in Sample 1 identified an interpretable three-factor structure, which was replicated in Samples 2 and 3 using confirmatory factor analyses. We found consistent evidence for three dimensions (Aberrant Salience, Asociality, and Concrete Thinking) underlying schizotypy and ASCs. This three-dimension model is consistent with a common vulnerability model of schizotypy and ASCs. Implications of these findings for the schizotypy and ASCs literature are discussed., Competing Interests: Declaration of competing interest None., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Study Objectives: We examined the prevalence of multiple hypnotic prescriptions and its association with clinical and demographic characteristics from the electronic health record (EHR) in the Mayo Clinic Biobank., Methods: Adult participants enrolled in the Mayo Clinic Biobank with an EHR number of ≥ 1 year were included (n = 52,940). Clinical and demographic characteristics were compared between participants who were and were not prescribed any hypnotic approved for insomnia by the US Food and Drug Administration and/or trazodone and in those prescribed a single vs multiple (≥ 2) hypnotics. A phenotype-based, phenome-wide association study (PheWAS) examining associations between hypnotic prescriptions and diagnoses across the EHR was performed adjusting for demographic and other confounders., Results: A total of 17,662 (33%) participants were prescribed at least 1 hypnotic and 5,331 (10%) received ≥ 2 hypnotics. Participants who were prescribed a hypnotic were more likely to be older, female, White, with a longer EHR, and a greater number of diagnostic codes (all P < .001). Those with multiple hypnotic prescriptions were more likely to be younger, female, with a longer EHR, and a greater number of diagnostic codes (all P < .001) compared with those prescribed a single hypnotic. The PheWAS revealed that participants with multiple hypnotic prescriptions had higher rates of mood disorders, anxiety disorders, suicidal ideation, restless legs syndrome, and chronic pain (all P < 1 e -10 )., Conclusions: Receiving multiple hypnotic prescriptions is common and associated with a greater prevalence of psychiatric, chronic pain, and sleep-related movement disorders. Future studies should examine potential genetic associations with multiple hypnotic prescriptions to personalize treatments for chronic insomnia., Citation: Kolla BP, Mansukhani MP, Chakravorty S, Frank JA, Coombes BJ. Prevalence and associations of multiple hypnotic prescriptions in a clinical sample. J Clin Sleep Med . 2024;20(5):793-800., (© 2024 American Academy of Sleep Medicine.)

Objective: To identify distinct sleep health phenotypes in adults, examine transitions in sleep health phenotypes over time, and subsequently relate these to the risk of chronic conditions., Methods: A national sample of adults from the Midlife in the United States study ( N = 3683) provided longitudinal data with two time points (T1: 2004-2006, T2: 2013-2017). Participants self-reported on sleep health (regularity, satisfaction, alertness, efficiency, duration) and the number and type of chronic conditions. Covariates included age, sex, race, education, education, partnered status, number of children, work status, smoking, alcohol, and physical activity., Results: Latent transition analysis identified four sleep health phenotypes across both time points: good sleepers, insomnia sleepers, weekend catch-up sleepers, and nappers. Between T1 and T2, the majority (77%) maintained their phenotype, with the nappers and insomnia sleepers being the most stable. In fully adjusted models with good sleepers at both time points as the reference, being an insomnia sleeper at either time point was related to having an increased number of total chronic conditions by 28%-81% at T2, adjusting for T1 conditions. Insomnia sleepers at both time points were at 72%-188% higher risk for cardiovascular disease, diabetes, depression, and frailty. Being a napper at any time point related to increased risks for diabetes, cancer, and frailty. Being a weekend catch-up sleeper was not associated with chronic conditions. Those with lower education and unemployed were more likely to be insomnia sleepers; older adults and retirees were more likely to be nappers., Conclusion: Findings indicate a heightened risk of chronic conditions involved in suboptimal sleep health phenotypes, mainly insomnia sleepers., (Copyright © 2024 by the American Psychosomatic Society.)

Background: Familial hypercholesterolemia is a treatable genetic condition but remains underdiagnosed. We reviewed the frequency of pathogenic or likely pathogenic (P/LP) variants in the LDLR gene in female individuals receiving reproductive carrier screening., Methods: This retrospective observational study included samples from female patients (aged 18-55 years) receiving a 274-gene carrier screening panel from January 2020 to September 2022. LDLR exons and their 10 base pair flanking regions were sequenced. Carrier frequency for P/LP variants was calculated for the entire population and by race/ethnicity. The most common variants and their likely functional effects were evaluated., Results: A total of 91 637 tests were performed on women with race/ethnicity reported as Asian (8.8%), Black (6.1%), Hispanic (8.5%), White (29.0%), multiple or other (15.0%), and missing (33.0%). Median age was 32.8 years with 83 728 (91%) <40 years. P/LP LDLR variants were identified in 283 samples (1 in 324). No patients were identified with >1 P/LP variant. LDLR carrier frequency was higher in Asian (1 in 191 [95% CI, 1 in 142-258]) compared with White (1 in 417 [95% CI, 1 in 326-533]; P <0.001) or Black groups (1 in 508 [95% CI, 1 in 284-910]; P =0.004). The most common variants differed between populations. Of all variants, at least 25.0% were predicted as null variants., Conclusions: P/LP variants in LDLR are common. Expanding the use of reproductive carrier screening to include genes associated with FH presents another opportunity to identify people predisposed to cardiovascular disease., Competing Interests: Disclosures Drs Souter, Gall, Wang and B. Prigmore, E. Becraft, and S. Brummitt are employees of Natera, Inc with stocks or options to own stocks in the company. P. Benn is a consultant for Natera, Inc with options to own stocks in the company. Natera, Inc also covers travel expenses to educational meetings.