The Paquid Epidemiological Program on Brain Ageing

1992 ◽  
Vol 11 (1) ◽  
pp. 14-18 ◽  
Author(s):  
J.-F. Dartigues ◽  
M. Gagnon ◽  
P. Barberger-Gateau ◽  
L. Letenneur ◽  
D. Commenges ◽  
...  
Keyword(s):  
Author(s):  
Lucy Beishon ◽  
Rebecca H. Clough ◽  
Meeriam Kadicheeni ◽  
Tamara Chithiramohan ◽  
Ronney B. Panerai ◽  
...  

AbstractThe population is ageing worldwide, thus increasing the burden of common age-related disorders to the individual, society and economy. Cerebrovascular diseases (stroke, dementia) contribute a significant proportion of this burden and are associated with high morbidity and mortality. Thus, understanding and promoting healthy vascular brain ageing are becoming an increasing priority for healthcare systems. In this review, we consider the effects of normal ageing on two major physiological processes responsible for vascular brain function: Cerebral autoregulation (CA) and neurovascular coupling (NVC). CA is the process by which the brain regulates cerebral blood flow (CBF) and protects against falls and surges in cerebral perfusion pressure, which risk hypoxic brain injury and pressure damage, respectively. In contrast, NVC is the process by which CBF is matched to cerebral metabolic activity, ensuring adequate local oxygenation and nutrient delivery for increased neuronal activity. Healthy ageing is associated with a number of key physiological adaptations in these processes to mitigate age-related functional and structural declines. Through multiple different paradigms assessing CA in healthy younger and older humans, generating conflicting findings, carbon dioxide studies in CA have provided the greatest understanding of intrinsic vascular anatomical factors that may mediate healthy ageing responses. In NVC, studies have found mixed results, with reduced, equivalent and increased activation of vascular responses to cognitive stimulation. In summary, vascular and haemodynamic changes occur in response to ageing and are important in distinguishing “normal” ageing from disease states and may help to develop effective therapeutic strategies to promote healthy brain ageing.


2021 ◽  
pp. 102776
Author(s):  
Emily Wheater ◽  
Susan D Shenkin ◽  
Susana Muñoz Maniega ◽  
Maria Valdés Hernández ◽  
Joanna M Wardlaw ◽  
...  

2009 ◽  
Vol 27 (5) ◽  
pp. 465-473 ◽  
Author(s):  
S.B. Wharton ◽  
J.P. O’Callaghan ◽  
G.M. Savva ◽  
J.A.R. Nicoll ◽  
F. Matthews ◽  
...  

2021 ◽  
pp. 1-8
Author(s):  
Yi-Bin Xi ◽  
Xu-Sha Wu ◽  
Long-Biao Cui ◽  
Li-Jun Bai ◽  
Shuo-Qiu Gan ◽  
...  

Background Neuroimaging- and machine-learning-based brain-age prediction of schizophrenia is well established. However, the diagnostic significance and the effect of early medication on first-episode schizophrenia remains unclear. Aims To explore whether predicted brain age can be used as a biomarker for schizophrenia diagnosis, and the relationship between clinical characteristics and brain-predicted age difference (PAD), and the effects of early medication on predicted brain age. Method The predicted model was built on 523 diffusion tensor imaging magnetic resonance imaging scans from healthy controls. First, the brain-PAD of 60 patients with first-episode schizophrenia, 60 healthy controls and 21 follow-up patients from the principal data-set and 40 pairs of individuals in the replication data-set were calculated. Next, the brain-PAD between groups were compared and the correlations between brain-PAD and clinical measurements were analysed. Results The patients showed a significant increase in brain-PAD compared with healthy controls. After early medication, the brain-PAD of patients decreased significantly compared with baseline (P < 0.001). The fractional anisotropy value of 31/33 white matter tract features, which related to the brain-PAD scores, had significantly statistical differences before and after measurements (P < 0.05, false discovery rate corrected). Correlation analysis showed that the age gap was negatively associated with the positive score on the Positive and Negative Syndrome Scale in the principal data-set (r = −0.326, P = 0.014). Conclusions The brain age of patients with first-episode schizophrenia may be older than their chronological age. Early medication holds promise for improving the patient's brain ageing. Neuroimaging-based brain-age prediction can provide novel insights into the understanding of schizophrenia.


2017 ◽  
Vol 40 (12) ◽  
pp. 681-690 ◽  
Author(s):  
James H. Cole ◽  
Katja Franke
Keyword(s):  

2022 ◽  
Vol 17 (7) ◽  
pp. 0
Author(s):  
ItzelOrtiz Flores ◽  
Samuel Treviño ◽  
Alfonso Díaz

2018 ◽  
Vol 8 (9) ◽  
pp. 175 ◽  
Author(s):  
Wajana Labisso ◽  
Ana-Caroline Raulin ◽  
Lucky Nwidu ◽  
Artur Kocon ◽  
Declan Wayne ◽  
...  

Repetitive excessive alcohol intoxication leads to neuronal damage and brain shrinkage. We examined cytoskeletal protein expression in human post-mortem tissue from Brodmann’s area 9 of the prefrontal cortex (PFC). Brain samples from 44 individuals were divided into equal groups of 11 control, 11 alcoholic, 11 non-alcoholic suicides, and 11 suicide alcoholics matched for age, sex, and post-mortem delay. Tissue from alcoholic cohorts displayed significantly reduced expression of α- and β-tubulins, and increased levels of acetylated α-tubulin. Protein levels of histone deacetylase-6 (HDAC6), and the microtubule-associated proteins MAP-2 and MAP-tau were reduced in alcoholic cohorts, although for MAPs this was not significant. Tubulin gene expressions increased in alcoholic cohorts but not significantly. Brains from rats administered alcohol for 4 weeks also displayed significantly reduced tubulin protein levels and increased α-tubulin acetylation. PFC tissue from control subjects had reduced tubulin protein expression that was most notable from the sixth to the eighth decade of life. Collectively, loss of neuronal tubulin proteins are a hallmark of both chronic alcohol consumption and natural brain ageing. The reduction of cytosolic tubulin proteins could contribute to the brain volumetric losses reported for alcoholic patients and the elderly.


2019 ◽  
Vol 145 ◽  
pp. 136-141 ◽  
Author(s):  
Rufus O. Akinyemi ◽  
Ayodeji Salami ◽  
Joshua Akinyemi ◽  
Akin Ojagbemi ◽  
Funmi Olopade ◽  
...  

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