Contribution of genetic polymorphisms on functional status at very old age: a gene-based analysis of 38 genes (311 SNPs) in the oxidative stress pathway.

Preservation of functional ability is a well-recognized marker of longevity. At a molecular level, a major determinant of the physiological decline occurring with aging is the imbalance between production and accumulation of oxidative damage to macromolecules, together with a decreased efficiency of stress response to avoid or repair such damage. In this paper we investigated the association of 38 genes (311 SNPs) belonging to the pro-antioxidant pathways with physical and cognitive performances, by analyzing single SNP and gene-based associations with Hand Grip strength (HG), Activities of Daily Living (ADL), Walking Speed (WS), Mini Mental State Examination (MMSE) and Composite Cognitive Score (CCS) in a Cohort of 1089 Danish nonagenarians. Moreover, for each gene analyzed in the pro-antioxidant pathway, we tested the influence on longitudinal survival. In the whole sample, nominal associations were found for TXNRD1 variability with ADL and WS, NDUFS1 and UCP3 with HG and WS, GCLC and UCP2 with WS (p<0.05). Stronger associations although not holding the multiple comparison correction, were observed between MMSE and NDUFV1, MT1A and GSTP1 variability (p<0.009). Moreover, we found that association between genetic variability in the pro-antioxidant pathway and functional status at old age is influenced by sex. In particular, most significant associations were observed in nonagenarian females, between HG scores and GLRX and UCP3 variability, between ADL levels and TXNRD1, MMSE and MT1A genetic variability. In males, a borderline statistically significant association with ADL level was found for UQCRFS1 gene. Nominally significant associations in relation to survival were found in the female sample only with SOD2, NDUFS1, UCP3 and TXNRD1 variability, the latter two confirming previous observations reported in the same cohort. Overall, our work supports the evidence that genes belonging to the pro-anti-oxidant pathway are able to modulate physical and cognitive performance after the ninth decade of life, finally influencing extreme survival.

Clinical signs and early prognosis in vegetative state: a decisional tree, data-mining study.

BACKGROUND AND PURPOSE: Residual brain function has been documented in vegetative state patients, yet early prognosis remains difficult. The purpose of this study was to identify by artificial intelligence procedures (classification and regression trees, data-mining) the significant neurological signs correlated to and predictive of outcome. METHODS: Three hundred and thirty-three patients in vegetative state of traumatic or non-traumatic aetiology referred to the S.Anna Institute were retrospectively studied. Twenty-two neurological signs were assessed according to criteria included in the UNI ENI ISO 9001 : 2000 quality standards at admission (Time(0)) and after 50, 100 or 180 days and entered into a CART (classification and regression tree) data-mining procedure with a decisional tree j48 (Weka software and 10-fold cross-validation). Outcome was conventionally rated by the Glasgow outcome scale. RESULTS AND CONCLUSIONS: Re-appearance with proper timing of spontaneous motility, eye tracking and oculo-cephalic reflex and disappearance of oral automatisms proved highly correlated to outcome and allowed early and reliable prognosis. These findings are consistent with the brain functional organization thought to sustain consciousness and warrant systematic investigation. Classification and regression trees and data-mining procedures proved applicable in neurology to sort out significant clinical signs also in clinical conditions characterized by paucity of signs such as the vegetative state. Extended application in clinical medicine is conceivable based on the approach peculiarities.