Prospective observational study for frailty in older patients of colorectal cancer surgery.
Ontology highlight
ABSTRACT:
DISEASE(S): Colorectal Cancer Surgery
PROVIDER: 2641908 | ecrin-mdr-crc |
REPOSITORIES: ECRIN MDR
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Project description:Frailty in elderly cardiovascular disease (CVD) patients is linked to declining functional capacity and procedural complications. This study investigated the transcriptomic signature of frailty in patients ≥70 years undergoing cardiac surgery or TAVI. Frailty was assessed using mobility, gait speed, and handgrip strength. Muscle samples were collected during surgery for RNA sequencing, and gene expression was analyzed. Transcriptomic analysis identified 10 frailty-associated genes, with S100A1 showing the strongest association. Functional studies confirmed S100A1’s role in muscle function, and higher blood S100A1 levels correlated with handgrip strength in a second cohort. S100A1 is a potential target for addressing frailty in elderly CVD patients and offers insights into genetic factors contributing to frailty.
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Project description:The incidence of perioperative neurocognitive disorders (PND) is high, especially after cardiac surgeries, and the underlying mechanisms remain elusive. Here, we conducted a prospective observational study to observe serum proteomics differences in PND patients after cardiac valve replacement surgery.
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Project description:Physical frailty's impact on hemagglutination inhibition antibody titers (HAI) and peripheral blood mononuclear cell (PBMC) transcriptional responses after influenza vaccination is unclear. Physical frailty was assessed using the 5-item Fried frailty phenotype in 168 community- and assisted-living adults ≥55 years of age during an observational study. Blood was drawn before, 3, 7, and 28 days post-vaccination with the 2017-2018 inactivated influenza vaccine. HAI response to the A/H1N1 strain was measured at Days 0 and 28 using seropositivity, seroconversion, log2 HAI titers, and fold-rise in log2 HAI titers. RNA sequencing of PBMCs from Days 0, 3 and 7 was measured in 28 participants and compared using pathway analyses. Frailty was not significantly associated with any HAI outcome in multivariable models. Compared with non-frail participants, frail participants expressed decreased cell proliferation, metabolism, antibody production, and interferon signaling genes. Conversely, frail participants showed elevated gene expression in IL-8 signaling, T-cell exhaustion, and oxidative stress pathways compared with non-frail participants. These results suggest that reduced effectiveness of influenza vaccine among older, frail individuals may be attributed to immunosenescence-related changes in PBMCs that are not reflected in antibody levels.
2022-02-16 | GSE196793 | GEO
Project description:Frailty affects the physical, cognitive, and social domains exposing older adults to an increased risk of cardiovascular disease (CVD) and death. The mechanisms linking frailty and cardiovascular outcomes are mostly unknown. Here, we studied the association of abundance (flow cytometry) and gene expression profile (RNAseq) of stem/progenitor cells (HSPCs) and molecular markers of inflammaging (ELISA) with the cardiorespiratory phenotype and prospective adverse events of individuals classified according to levels of frailty. Two cohorts of older adults were enrolled in the study. In a cohort of pre-frail 35 individuals (average age: 75 years), a physical frailty score above the median identified subjects with initial alterations in cardiorespiratory function. RNA sequencing revealed S100A8/A9 upregulation in HSPCs from the bone marrow (>10-fold) and peripheral blood (>200-fold) of individuals with greater physical frailty. Moreover higher frailty was associated with increased alarmins S100A8/A9 and inflammatory cytokines in peripheral blood. We then studied a cohort of 104 more frail individuals (average age: 81 years) with multi-domain health deficits. Reduced levels of circulating HSPCs and increased S100A8/A9 concentrations were independently associated with the frailty index. Remarkably, low HSPCs and high S100A8/A9 simultaneously predicted major adverse cardiovascular events at 1-year follow-up after adjustment for age and frailty index. In conclusion, inflammaging characterized by alarmin and pro-inflammatory cytokines in pre-frail individuals is mirrored by the pauperization of HSPCs in frail older people with comorbidities. S100A8/A9 is upregulated within HSPCs, identifying a phenotype that associates with poor cardiovascular outcomes.
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Project description:Frailty is an age-related geriatric syndrome with largely unknown mechanisms. We conducted a longitudinal study of aging C57BL/6JNIA mice, measured frailty index and derived DNA methylation data from PBMCs. We selected frailty-related differentially methylated CpGs and determined differentially methylated regions (DMRs), focusing on both age-independent and -dependent frailty, and using both mixed-sex and sex-stratified subgroups. We propose a joint set of 925 frailty-related DMRs, perform an association study with frailty outcomes, build epigenetic frailty clocks and validate in mice with interventions. Notably, age-independent frailty DMRs are enriched in nervous and endocrine pathways, distinct from signaling and lipid metabolism pathways identified from age-dependent DMRs. We observe hypermethylation in signaling pathways and hypomethylation in lipid metabolism and cytochrome P450 pathways with frailty progression. 36 DMRs show consistent associations in validation. These findings highlight distinct epigenetic signatures underlying frailty and aging, with potential sex-specific mechanisms.
2026-01-15 | GSE316651 | GEO
Project description:Frailty is defined as a clinical syndrome. It reflects a decrease in physiological reserve capacities that alters the mechanisms of adaptation to stress. Its clinical expression is modulated by biological, physiological, social and environmental changes. Thus, the accumulation of declines in these multiple systems leads to vulnerability to adverse outcomes (Fried et al., 2001; Nourhashémi et al., 2001). Indeed, frailty increases the risk of disability, falls, hospitalization and death. Age is currently a major determinant of frailty but does not explain this syndrome alone. It has been estimated that the prevalence of frailty is 4% in people aged 65-69 years and increases to 26% in people aged over 85 years (Clegg et al., 2013). However, this parameter is not sufficient to understand why long-lived people can preserve their physical function even at extreme ages (Ayers et al., 2017). The characterization of frailty has therefore become a priority in order to put in place actions to reduce or delay its harmful consequences. Early diagnostic methods are needed to identify those at risk. The search for biomarkers is part of this approach. As a result, the search for biomarkers of frailty has led to the identification of several types of molecules linked to the inflammatory response (e.g. IL-6, CRP, TNF-α and homocysteine), to nutritional status (e.g. vitamin D, albumin) or even endocrine. metabolism (e.g. IGF-1 and testosterone) (Picca et al., 2022; Mailliez et al., 2020; Alvarez-Sanchez et al, 2020). The development of new analytical techniques now allows multiplexed analysis rather than an individual biomarker to characterize a biological profile of this complex and dynamic frailty syndrome (Picca et al., 2022). Proteomic analysis is the technique of choice for studying the complete protein content of a biological sample. This technique has already proven itself in the discovery of new biomarkers in age-related diseases such as Parkinson's disease (Raghunathan et al., 2022) and Alzheimer's disease (Bai et al., 2021). Several studies have already described the plasma proteomic profile of frailty (Shamsi et al., 2012; Lin et al., 2017; Landino et al., 2021; Sathyan et al., 2020; Verghese et al., 2021), highlighting the importance of biological pathways associated with frailty: immune response, coagulation pathway or lipid metabolism. On the other hand, the determination of the level of frailty of the patients thanks to a proteomic analysis could also make it possible to improve the prediction of this syndrome as well as its phenotyping. In a first work on plasma samples, Sathyan et al. constructed a frailty prediction model that was more strongly correlated with chronological age than observed clinical frailty (Sathyan et al., 2020). Cognitive impairment plays a key role in determining vulnerability to adverse outcomes (Cesari et al., 2013), leading to the proposal in 2013 of a concept and operational definition of “cognitive frailty”. (Sugimoto et al., 2022). Proteomic analysis of cerebrospinal fluid (CSF) is therefore an approach of choice for understanding brain responses to aging and frailty syndrome. Its analysis could allow the identification of new biomarkers linked to the frailty syndrome. Indeed, many of the CSF proteins are released by the various cells of the central nervous system (CNS). This biofluid thus reflects the molecular content of neuronal and glial cells. For this reason, any change in the composition of the CSF reflects the pathophysiological state of the brain (inflammation, infection, neurodegeneration...). CSF proteomics is therefore a technique of choice to comprehensively understand the cerebral pathogenic pathways linked to frailty. The PROLIPHYC cohort is composed of patients suspected of normal pressure hydrocephalus (NPH). We have previously shown that there is an association in these patients between an alteration of the biomechanical properties of the CNS and the frailty index, and that homocysteine is the only plasma macromolecule associated with these two clinical and biomechanical parameters (Vallet et al., 2020; Guillotin et al., 2022). In this new study, we sought to characterize the protein composition of CSF related to frailty by quantitative proteomic analysis. The second objective was to develop a model for predicting frailty from the abundance of CSF proteins. This model was then compared to the frailty estimated by the frailty index. Together, our results enabled us to highlight a possible link between inhibition of the expression of proteins involved in neurogenesis and the frailty index, then to propose a first proteomic profile of frailty in the CSF and a model for predicting frailty based on the biological signature of the CNS.
2024-08-10 | PXD043497 | Pride
Project description:This work describes for the first time a different circular RNA (circRNAs) expression pattern between frail and robust individuals. Moreover, the level of some circRNAs is modulated after a physical intervention. These results suggest that they could be used as minimally invasive biomarkers of frailty. Frailty is an intermediate and reversible geriatric syndrome that often precedes dependency. Therefore, its identification is essential to prevent dependency. Diverse molecules have been proposed as biomarkers of frailty, but none of them has reached clinical practice. Recently, circular RNAs have emerged as new non-coding RNAs. Their regulatory role together with their high stability in biofluids makes them good candidates as biomarkers for several processes, but, to date, no studies have characterized circRNA expression in frailty. We studied RNA from leukocytes of 35 frail and 35 robust individuals. After RNA-Sequencing, circRNA detection was performed by CIRI2 and Circexplorer2 and differential expression analysis by DESeq2. Validation was performed by Quantitative-PCR. A Linear Discriminant Analysis was performed to determine the best circRNA combination to discriminate frails from robusts. Besides, CircRNA candidates were studied in 13 additional elder donors before and after a 3-month physical intervention. We found 89 differentially expressed circRNAs (p-value<0.05, FC>|1.5|) with frailty. The upregulation of hsa_circ_0007817, hsa_circ_0101802 and hsa_circ_0060527 in frail individuals was validated. The combination of hsa_circ_0079284, hsa_circ_0007817 and hsa_circ_0075737 levels showed a great biomarker value with a 95.9% probability of correctly classifying frail and robust individuals. Moreover, hsa_circ_0079284 levels decreased after physical intervention in concordance with an improvement in frailty scores.
2023-01-31 | GSE206762 | GEO
Project description: Not available
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Project description:Low-grade, chronic inflammation during ageing (“inflammageing”) is suggested to be involved in the development of frailty in older age. However, studies on the association between frailty, using the frailty index definition, and inflammatory markers are limited. The aim of this study was to investigate the relationship between inflammatory markers and frailty index (FI) in older, home-dwelling adults. Home-dwelling men and women aged ≥ 70 years old, living in South-East Norway were recruited and included in a cross-sectional study. The FI used in the current study was developed according to Rockwood’s frailty index and included 38 variables, resulting in an FI score between 0 and 1 for each participant. Circulating inflammatory markers (IL-6, CRP, IGF-1, cystatin C, cathepsin S, and glycoprotein Acetyls) were analyzed from non-fasting blood samples using ELISA. Whole-genome PBMC transcriptomics was used to study the association between FI score and inflammation. The present study was a cross-sectional study that included home-dwelling men and women aged ≥ 70 years old, living in the Skedsmo area, South-East Norway. The study was conducted in 2014/2015 and has been described previously [Ottestad I, Ulven SM, Øyri LKL, Sandvei KS, Gjevestad GO, Bye A, et al. Reduced plasma concentration of branched-chain amino acids in sarcopenic older subjects: a cross-sectional study. Br J Nutr. 2018;120(4):445-53]. The participants were recruited by the National Register and received an invitation letter by mail. Briefly, a total of 2820 subjects were invited, and 437 subjects participated in the study. The participants met for a single study visit, and data was collected on dietary intake, body weight and composition, physical performance, medical history, cognitive function, risk of malnutrition, anthropometric measurements, blood pressure, heart rate, and quality of life. Non-fasting blood samples were also collected.
2023-09-01 | GSE236927 | GEO