Citations

Abstract Studies in mice and cross-sectional studies in humans support the premise that cellular senescence is a contributing mechanism to age-associated deficits in physical function. We tested the hypotheses that circulating proteins secreted by senescent cells are (i) associated with the incidence of major mobility disability (MMD), the development of persistent mobility disability (PMMD), and decrements in physical functioning in older adults, and (ii) influenced by physical activity (PA). Using samples and data obtained longitudinally from the Lifestyle Interventions in Elders Study clinical trial, we measured a panel of 27 proteins secreted by senescent cells. Among 1 377 women and men randomized to either a structured PA intervention or a healthy aging (HA) intervention, we observed significant associations between several senescence biomarkers, most distinctly vascular endothelial growth factor A (VEGFA), tumor necrosis factor receptor 1 (TNFR1), and matrix metallopeptidase 7 (MMP7), and the onset of both MMD and PMMD. Moreover, VEGFA, GDF15, osteopontin, and other senescence biomarkers were associated with reductions in short physical performance battery scores. The change in senescence biomarkers did not differ between PA and HA participants. In the whole cohort, higher levels of PA were associated with significantly greater reductions in 10 senescence-related proteins at 12 and/or 24 months. These data reinforce cellular senescence as a contributing mechanism of age-associated functional decline and the potential for PA to attenuate this hallmark of aging. Clinical Trials Registration Number: NCT01072500

Background Heart failure (HF) is a complex disease that contributes to a high number of hospitalizations, deaths, and economic health care costs each year. However, among patients with HF, there is a lack of awareness of their HF diagnosis that has not been fully examined. Methods and Results Residents from 3 counties of southeast Minnesota with a first‐ever International Classification of Diseases, Ninth Revision ( ICD‐9 ) code 428 or Tenth Revision ( ICD‐10 ) code I50 between January 1, 2013 and March 31, 2016 (N=2461) were prospectively surveyed to measure HF self‐awareness. A total of 1114 patients returned the survey (response rate, 45%), and 787 had validated HF upon medical record review. Among these 787 patients with HF (mean age, 76 years; 53% men), 37% (n=293) were aware of their HF diagnosis. After adjustment, being a woman (odds ratio [OR], 1.56 [95% CI, 1.10–2.22]), having HF with reduced ejection fraction (OR, 1.58 [95% CI, 1.13–2.22]), attending the HF clinic (OR, 4.07 [95% CI, 2.25–7.36]), and having coronary artery disease (OR, 1.65 [95% CI, 1.16–2.37]) were all associated with increased awareness of an HF diagnosis. Conversely, having diabetes was associated with decreased awareness of an HF diagnosis (adjusted OR, 0.69 [95% CI, 0.50–0.95]). Conclusions Awareness of an HF diagnosis is low in a community population of patients with HF. Strategies to improve patient awareness of their diagnosis should be implemented to improve self‐care behaviors and outcomes in patients with HF.

Background: Multimorbidity is common in atrial fibrillation (AF), particularly among older patients who generally have multiple cardiovascular and non-cardiovascular chronic conditions. However, less is known about the accumulation of chronic conditions in younger patients with AF. Methods: Patients aged <65 with incident AF from 2013-2019 from a 27-county region in the Midwest (N=4907) were matched 1:1 on age (±5 years) and sex to referents from the same community. The index date for the matched pair was the date of first diagnosis of AF. Diagnosis of 20 other chronic conditions was ascertained from 3 years prior to index through 12/31/2022. Mean cumulative function curves were used to visualize the accumulation of conditions; Andersen-Gill models estimated associations between AF/referent status and accumulation of conditions. Results: The mean age was 55 years for both patients with AF and matched referents; 71% were male. In the 3 years leading up to AF diagnosis, only 4% of patients with AF had no additional chronic conditions and 69% had ≥3 chronic conditions. In contrast, 35% of referents had 0 and 32% had ≥3 chronic conditions. The accumulation of chronic conditions was accelerated in patients with AF compared to referents prior to AF diagnosis/index (Figure). After index, patients with AF had increased accumulation of chronic conditions (HR (95% CI): 1.93 (1.71-2.20), 1.82 (1.62-2.05), 1.68 (1.55-1.83), and 1.53 (1.44-1.64) for ages <50, 50-54, 55-59, and 60-64 years, respectively). After 1 year, the differences were attenuated in all age groups with no difference observed between patients with AF and referents in the oldest age group (1.26 (1.08-1.46), 1.28 (1.11-1.47), 1.13 (1.02-1.24), and 1.05 (0.97-1.13) for ages <50, 50-54, 55-59, and 60-64 years). Conclusion: Patients <65 years with AF have an increased accumulation of chronic conditions compared to those without AF, in particular prior to their AF diagnosis and within the first year after AF diagnosis.

AbstractIntroductionStudies have reported a higher risk of suboptimal neurodevelopment among children who are HIV‐exposed uninfected (HEU) compared to children HIV‐unexposed uninfected (HUU). Actual academic performance among school‐aged children by HIV exposure status has not been studied.MethodsAcademic performance in Mathematics, Science, English, Setswana and overall among children enrolled in the Botswana‐based FLOURISH study who were attending public primary school and ranging in age from 7.1 to 14.6 years were compared by HIV exposure status using a Cochran‐Mantel‐Haenszel test. Lower academic performance was defined as a grade of “C” or lower (≤60%). Unadjusted and adjusted logistic regression models were fit to assess for an association between HIV exposure and lower academic performance.ResultsBetween April 2021 and December 2022, 398 children attending public primary school enrolled in the FLOURSH study, 307 (77%) were HEU. Median age was 9.4 years (IQR 8.9–10.2). Only 17.9% of children HEU were breastfeed versus 100% of children HUU. Among children HEU, 80.3% had foetal exposure to three‐drug antiretroviral treatment, 18.7% to zidovudine only and 1.0% had no antiretroviral exposure. Caregivers of children HEU were older compared to caregivers of children HUU (median 42 vs. 36 years) and more likely to have no or primary education only (15.0% vs. 1.1%). In unadjusted analyses, children HEU were more likely to have lower overall academic performance compared to their children HUU (odds ratio [OR]: 1.96 [95% confidence interval (CI): 1.16, 3.30]), and lower performance in Mathematics, Science and English. The association was attenuated after adjustment for maternal education, caregiver income, breastfeeding, low birth weight and child sex (aOR: 1.86 [95% CI: 0.78, 4.43]).ConclusionsIn this Botswana‐based cohort, primary school academic performance was lower among children HEU compared to children HUU. Biological and socio‐demographic factors, including child sex, appear to contribute to this difference. Further research is needed to identify modifiable contributors, develop screening tools to identify the risk of poor academic performance and design interventions to mitigate risk.

AbstractA robust and heterogenous secretory phenotype is a core feature of most senescent cells. In addition to mediators of age‐related pathology, components of the senescence associated secretory phenotype (SASP) have been studied as biomarkers of senescent cell burden and, in turn, biological age. Therefore, we hypothesized that circulating concentrations of candidate senescence biomarkers, including chemokines, cytokines, matrix remodeling proteins, and growth factors, could predict mortality in older adults. We assessed associations between plasma levels of 28 SASP proteins and risk of mortality over a median follow‐up of 6.3 years in 1923 patients 65 years of age or older with zero or one chronic condition at baseline. Overall, the five senescence biomarkers most strongly associated with an increased risk of death were GDF15, RAGE, VEGFA, PARC, and MMP2, after adjusting for age, sex, race, and the presence of one chronic condition. The combination of biomarkers and clinical and demographic covariates exhibited a significantly higher c‐statistic for risk of death (0.79, 95% confidence interval (CI): 0.76–0.82) than the covariates alone (0.70, CI: 0.67–0.74) (p < 0.001). Collectively, these findings lend further support to biomarkers of cellular senescence as informative predictors of clinically important health outcomes in older adults, including death.

PURPOSE The Response Assessment in Neuro-Oncology (RANO) criteria for high-grade gliomas (RANO-HGG) and low-grade gliomas (RANO-LGG) were developed to improve reliability of response assessment in glioma trials. Over time, some limitations of these criteria were identified, and challenges emerged regarding integrating features of the modified RANO (mRANO) or the immunotherapy RANO (iRANO) criteria. METHODS Informed by data from studies evaluating the different criteria, updates to the RANO criteria are proposed (RANO 2.0). RESULTS We recommend a standard set of criteria for both high- and low-grade gliomas, to be used for all trials regardless of the treatment modalities being evaluated. In the newly diagnosed setting, the postradiotherapy magnetic resonance imaging (MRI), rather than the postsurgical MRI, will be used as the baseline for comparison with subsequent scans. Since the incidence of pseudoprogression is high in the 12 weeks after radiotherapy, continuation of treatment and confirmation of progression during this period with a repeat MRI, or histopathologic evidence of unequivocal recurrent tumor, are required to define tumor progression. However, confirmation scans are not mandatory after this period nor for the evaluation of treatment for recurrent tumors. For treatments with a high likelihood of pseudoprogression, mandatory confirmation of progression with a repeat MRI is highly recommended. The primary measurement remains the maximum cross-sectional area of tumor (two-dimensional) but volumetric measurements are an option. For IDH wild-type glioblastoma, the nonenhancing disease will no longer be evaluated except when assessing response to antiangiogenic agents. In IDH-mutated tumors with a significant nonenhancing component, clinical trials may require evaluating both the enhancing and nonenhancing tumor components for response assessment. CONCLUSION The revised RANO 2.0 criteria refine response assessment in gliomas.

Importance Germline gene panel testing is recommended for men with advanced prostate cancer (PCa) or a family history of cancer. While evidence is limited for some genes currently included in panel testing, gene panels are also likely to be incomplete and missing genes that influence PCa risk and aggressive disease. Objective To identify genes associated with aggressive PCa. Design, Setting, and Participants A 2-stage exome sequencing case-only genetic association study was conducted including men of European ancestry from 18 international studies. Data analysis was performed from January 2021 to March 2023. Participants were 9185 men with aggressive PCa (including 6033 who died of PCa and 2397 with confirmed metastasis) and 8361 men with nonaggressive PCa. Exposure Sequencing data were evaluated exome-wide and in a focused investigation of 29 DNA repair pathway and cancer susceptibility genes, many of which are included on gene panels. Main Outcomes and Measures The primary study outcomes were aggressive (category T4 or both T3 and Gleason score ≥8 tumors, metastatic PCa, or PCa death) vs nonaggressive PCa (category T1 or T2 and Gleason score ≤6 tumors without known recurrence), and metastatic vs nonaggressive PCa. Results A total of 17 546 men of European ancestry were included in the analyses; mean (SD) age at diagnosis was 65.1 (9.2) years in patients with aggressive PCa and 63.7 (8.0) years in those with nonaggressive disease. The strongest evidence of association with aggressive or metastatic PCa was noted for rare deleterious variants in known PCa risk genes BRCA2 and ATM ( P ≤ 1.9 × 10 −6 ), followed by NBN ( P = 1.7 × 10 −4 ). This study found nominal evidence ( P &amp;lt; .05) of association with rare deleterious variants in MSH2 , XRCC2 , and MRE11A . Five other genes had evidence of greater risk (OR≥2) but carrier frequency differences between aggressive and nonaggressive PCa were not statistically significant: TP53 , RAD51D , BARD1 , GEN1 , and SLX4 . Deleterious variants in these 11 candidate genes were carried by 2.3% of patients with nonaggressive, 5.6% with aggressive, and 7.0% with metastatic PCa. Conclusions and Relevance The findings of this study provide further support for DNA repair and cancer susceptibility genes to better inform disease management in men with PCa and for extending testing to men with nonaggressive disease, as men carrying deleterious alleles in these genes are likely to develop more advanced disease.

A large number of variants identified through clinical genetic testing in disease susceptibility genes are of uncertain significance (VUS). Following the recommendations of the American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP), the frequency in case-control datasets (PS4 criterion) can inform their interpretation. We present a novel case-control likelihood ratio-based method that incorporates gene-specific age-related penetrance. We demonstrate the utility of this method in the analysis of simulated and real datasets. In the analysis of simulated data, the likelihood ratio method was more powerful compared to other methods. Likelihood ratios were calculated for a case-control dataset of BRCA1 and BRCA2 variants from the Breast Cancer Association Consortium (BCAC) and compared with logistic regression results. A larger number of variants reached evidence in favor of pathogenicity, and a substantial number of variants had evidence against pathogenicity—findings that would not have been reached using other case-control analysis methods. Our novel method provides greater power to classify rare variants compared with classical case-control methods. As an initiative from the ENIGMA Analytical Working Group, we provide user-friendly scripts and preformatted Excel calculators for implementation of the method for rare variants in BRCA1, BRCA2, and other high-risk genes with known penetrance.

Introduction The Florida-California Cancer Research, Education, and Engagement (CaRE 2 ) Health Equity Center is a triad partnership committed to increasing institutional capacity for cancer disparity research, the diversity of the cancer workforce, and community empowerment. This article provides an overview of the structure, process innovations, and initial outcomes from the first 4 years of the CaRE 2 triad partnership. Methods CaRE 2 serves diverse populations in Florida and California using a “molecule to the community and back” model. We prioritize research on the complex intersection of biological, environmental, and social determinants health, working together with scientific and health disparities communities, sharing expertise across institutions, bidirectional training, and community outreach. Partnership progress and outcomes were assessed using mixed methods and four Program Steering Committee meetings. Results Research capacity was increased through development of a Living Repository of 81 cancer model systems from minority patients for novel cancer drug development. CaRE 2 funded 15 scientific projects resulting in 38 publications. Workforce diversity entailed supporting 94 cancer trainees (92 URM) and 34 ESIs (32 URM) who coauthored 313 CaRE 2 -related publications and received 48 grants. Community empowerment was promoted via outreaching to more than 3000 individuals, training 145 community cancer advocates (including 28 Community Scientist Advocates), and publishing 10 community reports. CaRE 2 members and trainees together have published 639 articles, received 61 grants, and 57 awards. Conclusion The CaRE 2 partnership has achieved its initial aims. Infrastructure for translational cancer research was expanded at one partner institution, and cancer disparities research was expanded at the two cancer centers.