Cognitive frailty: rational and definition from an (I.A.N.A./I.A.G.G.) international consensus group.

The frailty syndrome has recently attracted attention of the scientific community and public health organizations as precursor and contributor of age-related conditions (particularly disability) in older persons. in parallel, dementia and cognitive disorders also represent major healthcare and social priorities. although physical frailty and cognitive impairment have shown to be related in epidemiological studies, their pathophysiological mechanisms have been usually studied separately. an international Consensus Group on “Cognitive Frailty” was organized by the international academy on nutrition and aging (i.a.n.a) and the international association of Gerontology and Geriatrics (i.a.G.G) on april 16th, 2013 in toulouse (France). the present report describes the results of the Consensus Group and provides the first definition of a “Cognitive Frailty” condition in older adults. specific aim of this approach was to facilitate the design of future personalized preventive interventions in older persons. Finally, the Group discussed the use of multidomain interventions focused on the physical, nutritional, cognitive and psychological domains for improving the well-being and quality of life in the elderly. the consensus panel proposed the identification of the so-called “cognitive frailty” as an heterogeneous clinical manifestation characterized by the simultaneous presence of both physical frailty and cognitive impairment. in particular, the key factors defining such a condition include: 1) presence of physical frailty and cognitive impairment (Cdr=0.5); and 2) exclusion of concurrent ad dementia or other dementias. under different circumstances, cognitive frailty may represent a precursor of neurodegenerative processes. a potential for reversibility may also characterize this entity. a psychological component of the condition is evident and concurs at increasing the vulnerability of the individual to stressors

A robust machine learning framework to identify signatures for frailty: a nested case-control study in four aging European cohorts

Phenotype-specific omic expression patterns in people with frailty could provide invaluable insight into the underlying multi-systemic pathological processes and targets for intervention. Classical approaches to frailty have not considered the potential for different frailty phenotypes. We characterized associations between frailty (with/without disability) and sets of omic factors (genomic, proteomic, and metabolomic) plus markers measured in routine geriatric care. This study was a prevalent case control using stored biospecimens (urine, whole blood, cells, plasma, and serum) from 1522 individuals (identified as robust (R), pre-frail (P), or frail (F)] from the Toledo Study of Healthy Aging (R=178/P=184/F=109), 3 City Bordeaux (111/269/100), Aging Multidisciplinary Investigation (157/79/54) and InCHIANTI (106/98/77) cohorts. The analysis included over 35,000 omic and routine laboratory variables from robust and frail or pre-frail (with/without disability) individuals using a machine learning framework. We identified three protective biomarkers, vitamin D3 (OR: 0.81 [95% CI: 0.68–0.98]), lutein zeaxanthin (OR: 0.82 [95% CI: 0.70–0.97]), and miRNA125b-5p (OR: 0.73, [95% CI: 0.56–0.97]) and one risk biomarker, cardiac troponin T (OR: 1.25 [95% CI: 1.23–1.27]). Excluding individuals with a disability, one protective biomarker was identified, miR125b-5p (OR: 0.85, [95% CI: 0.81–0.88]). Three risks of frailty biomarkers were detected: pro-BNP (OR: 1.47 [95% CI: 1.27–1.7]), cardiac troponin T (OR: 1.29 [95% CI: 1.21–1.38]), and sRAGE (OR: 1.26 [95% CI: 1.01–1.57]). Three key frailty biomarkers demonstrated a statistical association with frailty (oxidative stress, vitamin D, and cardiovascular system) with relationship patterns differing depending on the presence or absence of a disability