Identification of Pre-frailty Sub-Phenotypes in Elderly Using Metabolomics

Aging is a dynamic process depending on intrinsic and extrinsic factors and its evolution is a continuum of transitions, involving multifaceted processes at multiple levels. It is recognized that frailty and sarcopenia are shared by the major age-related diseases thus contributing to elderly morbidity and mortality. Pre-frailty is still not well understood but it has been associated with global imbalance in several physiological systems, including inflammation, and in nutrition. Due to the complex phenotypes and underlying pathophysiology, the need for robust and multidimensional biomarkers is essential to move toward more personalized care. The objective of the present study was to better characterize the complexity of pre-frailty phenotype using untargeted metabolomics, in order to identify specific biomarkers, and study their stability over time. The approach was based on the NU-AGE project (clinicaltrials.gov, NCT01754012) that regrouped 1,250 free-living elderly people (65–79 y.o., men and women), free of major diseases, recruited within five European centers. Half of the volunteers were randomly assigned to an intervention group (1-year Mediterranean type diet). Presence of frailty was assessed by the criteria proposed by Fried et al. (2001). In this study, a sub-cohort consisting in 212 subjects (pre-frail and non-frail) from the Italian and Polish centers were selected for untargeted serum metabolomics at T0 (baseline) and T1 (follow-up). Univariate statistical analyses were performed to identify discriminant metabolites regarding pre-frailty status. Predictive models were then built using linear logistic regression and ROC curve analyses were used to evaluate multivariate models. Metabolomics enabled to discriminate sub-phenotypes of pre-frailty both at the gender level and depending on the pre-frailty progression and reversibility. The best resulting models included four different metabolites for each gender. They showed very good prediction capacity with AUCs of 0.93 (95% CI = 0.87–1) and 0.94 (95% CI = 0.87–1) for men and women, respectively. Additionally, early and/or predictive markers of pre-frailty were identified for both genders and the gender specific models showed also good performance (three metabolites; AUC = 0.82; 95% CI = 0.72–0.93) for men and very good for women (three metabolites; AUC = 0.92; 95% CI = 0.86–0.99). These results open the door, through multivariate strategies, to a possibility of monitoring the disease progression over time at a very early stage

Physical Activity Assessment Using an Activity Tracker in Patients with Rheumatoid Arthritis and Axial Spondyloarthritis: Prospective Observational Study

International audienceBackground: Physical activity can be tracked using mobile devices and is recommended in rheumatoid arthritis (RA) and axial spondyloarthritis (axSpA) management. The World Health Organization (WHO) recommends at least 150 min per week of moderate to vigorous physical activity (MVPA).Objective: The objectives of this study were to assess and compare physical activity and its patterns in patients with RA and axSpA using an activity tracker and to assess the feasibility of mobile devices in this population.Methods: This multicentric prospective observational study (ActConnect) included patients who had definite RA or axSpA, and a smartphone. Physical activity was assessed over 3 months using a mobile activity tracker, recording the number of steps per minute. The number of patients reaching the WHO recommendations was calculated. RA and axSpA were compared, using linear mixed models, for number of steps, proportion of morning steps, duration of total activity, and MVPA. Physical activity trajectories were identified using the K-means method, and factors related to the low activity trajectory were explored by logistic regression. Acceptability was assessed by the mean number of days the tracker was worn over the 3 months (ie, adherence), the percentage of wearing time, and by an acceptability questionnaire.Results: A total of 157 patients (83 RA and 74 axSpA) were analyzed; 36.3% (57/157) patients were males, and their mean age was 46 (standard deviation [SD] 12) years and mean disease duration was 11 (SD 9) years. RA and axSpA patients had similar physical activity levels of 16 (SD 11) and 15 (SD 12) min per day of MVPA (P=.80), respectively. Only 27.4% (43/157) patients reached the recommendations with a mean MVPA of 106 (SD 77) min per week. The following three trajectories were identified with constant activity: low (54.1% [85/157] of patients), moderate (42.7% [67/157] of patients), and high (3.2% [5/157] of patients) levels of MVPA. A higher body mass index was significantly related to less physical activity (odds ratio 1.12, 95% CI 1.11-1.14). The activity trackers were worn during a mean of 79 (SD 17) days over the 90 days follow-up. Overall, patients considered the use of the tracker very acceptable, with a mean score of 8 out 10.Conclusions: Patients with RA and axSpA performed insufficient physical activity with similar levels in both groups, despite the differences between the 2 diseases. Activity trackers allow longitudinal assessment of physical activity in these patients. The good adherence to this study and the good acceptability of wearing activity trackers confirmed the feasibility of the use of a mobile activity tracker in patients with rheumatic diseases

Fluctuation of pain is frequent in rheumatoid arthritis and axial spondyloarthritis: a 12 weeks prospective study of 165 patients

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Metabolomics enabled the identification of pre-frailty sub-phenotypes in elderly

International audienceContext: Ageing is a dynamic process depending on intrinsic and extrinsic factors and its evolution is a continuum of transitions, involving multifaceted processes at multiple levels. It is recognized that frailty and sarcopenia are shared by the major age-related diseases thus contributing to elderly morbidity and mortality. They are major health issues in aging populations, given their high prevalence and association with several adverse outcomes. Pre-frailty is still not well understood but it has been associated with changes in several physiological systems, including inflammation as well as changes in the balance of micronutrients and vitamins. Due to the complex phenotypes and underlying pathophysiology, the need for robust and multidimensional biomarkers is now essential to move towards more personalized care and prevention. Objective: The objective of the present study was to better characterize the complexity of pre-frailty phenotype using untargeted metabolomics in order to identify specific biomarkers, and study their stability over time. Research design and methods: The approach was based on the NU-AGE project (FP7 EU programme; clinicaltrials.gov, NCT01754012) that regrouped 1,250 free-living elderly people (65-79 y.o., men and women), free of major diseases, recruited within five European centres. Half of the volunteers were randomly assigned to an intervention group (1-year Mediterranean type diet). Presence of frailty was assessed by the criteria proposed by Fried et al (Fried et al. J Gerontol A Biol Sci Med Sci, 2001). In this study, a sub-cohort consisting in 212 subjects (pre-frail and non-frail) from the Italian and Polish centres were selected for mass spectrometry-based untargeted metabolomics. Metabolic profiles were determined from serum samples at T0 (baseline) and T1 (follow-up). All data were processed under the Galaxy web-based platform Worflow4metabolomics, guaranteeing their reproducibility (Giacomoni et al. Bioinformatics, 2015). Univariate statistical analyses were performed to identify discriminant metabolites regarding pre-frailty status. Predictive models were then built using linear logistic regression and ROC curve analyses were used to evaluate multivariate biomarkers. Results: Presence of sub-phenotypes of pre-frailty both at the gender level and depending on the pre-frailty progression and reversibility were revealed by untargeted metabolomics. Additionally, early markers, able to predict the evolution towards pre-frailty within one year, were identified for both genders. Moreover, some of these early biomarkers were found to be still relevant for classification of a ‘light pre-frail’ phenotype after its clinical appearance. Conclusion: These results open the door, through multivariate strategies, to the possibility of monitoring the disease progression over time at a very early stage. Longitudinal analysis of individual time trajectories to detect early deviations of health status would indeed contribute to a better disease prevention

Detection of flares by decrease in physical activity, collected using wearable activity trackers, in rheumatoid arthritis or axial spondyloarthritis: an application of Machine-Learning analyses in rheumatology

International audienceOBJECTIVE:Flares in rheumatoid arthritis (RA) and axial spondyloarthritis (SpA) may influence physical activity. The aim of this study was to assess longitudinally the association between patient-reported flares and activity-tracker-provided steps per minute, using machine learning.METHODS:This prospective observational study (ActConnect) included patients with definite RA or axial SpA. For a 3-month time period, physical activity was assessed continuously by number of steps/minute, using a consumer grade activity tracker, and flares were self-assessed weekly. Machine-learning techniques were applied to the data set. After intrapatient normalization of the physical activity data, multiclass Bayesian methods were used to calculate sensitivities, specificities, and predictive values of the machine-generated models of physical activity in order to predict patient-reported flares.RESULTS:Overall, 155 patients (1,339 weekly flare assessments and 224,952 hours of physical activity assessments) were analyzed. The mean ± SD age for patients with RA (n = 82) was 48.9 ± 12.6 years and was 41.2 ± 10.3 years for those with axial SpA (n = 73). The mean ± SD disease duration was 10.5 ± 8.8 years for patients with RA and 10.8 ± 9.1 years for those with axial SpA. Fourteen patients with RA (17.1%) and 41 patients with axial SpA (56.2%) were male. Disease was well-controlled (Disease Activity Score in 28 joints mean ± SD 2.2 ± 1.2; Bath Ankylosing Spondylitis Disease Activity Index score mean ± SD 3.1 ± 2.0), but flares were frequent (22.7% of all weekly assessments). The model generated by machine learning performed well against patient-reported flares (mean sensitivity 96% [95% confidence interval (95% CI) 94-97%], mean specificity 97% [95% CI 96-97%], mean positive predictive value 91% [95% CI 88-96%], and negative predictive value 99% [95% CI 98-100%]). Sensitivity analyses were confirmatory.CONCLUSION:Although these pilot findings will have to be confirmed, the correct detection of flares by machine-learning processing of activity tracker data provides a framework for future studies of remote-control monitoring of disease activity, with great precision and minimal patient burden

Temporal Trends in Transcatheter Aortic Valve Replacement in France: FRANCE 2 to FRANCE TAVI

International audienceBackground - Transcatheter aortic valve replacement (TAVR) is standard therapy for patients with severe aortic stenosis who are at high surgical risk. However, national data regarding procedural characteristics and clinical outcomes over time are limited. Objectives - The aim of this study was to assess nationwide performance trends and clinical outcomes of TAVR during a 6-year period. Methods - TAVRs performed in 48 centers across France between January 2013 and December 2015 were prospectively included in the FRANCE TAVI (French Transcatheter Aortic Valve Implantation) registry. Findings were further compared with those reported from the FRANCE 2 (French Aortic National CoreValve and Edwards 2) registry, which captured all TAVRs performed from January 2010 to January 2012 across 34 centers. Results - A total of 12,804 patients from FRANCE TAVI and 4,165 patients from FRANCE 2 were included in this analysis. The median age of patients was 84.6 years, and 49.7% were men. FRANCE TAVI participants were older but at lower surgical risk (median logistic European System for Cardiac Operative Risk Evaluation [EuroSCORE]: 15.0% vs. 18.4%; p < 0.001). More than 80% of patients in FRANCE TAVI underwent transfemoral TAVR. Transesophageal echocardiography guidance decreased from 60.7% to 32.3% of cases, whereas more recent procedures were increasingly performed in hybrid operating rooms (15.8% vs. 35.7%). Rates of Valve Academic Research Consortium-defined device success increased from 95.3% in FRANCE 2 to 96.8% in FRANCE TAVI (p < 0.001). In-hospital and 30-day mortality rates were 4.4% and 5.4%, respectively, in FRANCE TAVI compared with 8.2% and 10.1%, respectively, in FRANCE 2 (p < 0.001 for both). Stroke and potentially life-threatening complications, such as annulus rupture or aortic dissection, remained stable over time, whereas rates of cardiac tamponade and pacemaker implantation significantly increased. Conclusions - The FRANCE TAVI registry provided reassuring data regarding trends in TAVR performance in an all-comers population on a national scale. Nonetheless, given that TAVR indications are likely to expand to patients at lower surgical risk, concerns remain regarding potentially life-threatening complications and pacemaker implantation. (Registry of Aortic Valve Bioprostheses Established by Catheter [FRANCE TAVI]; NCT01777828)