Ageing and Parkinson's disease: Why is advancing age the biggest risk factor?

Reeve, Amy K.; Simcox, Eve M.; Turnbull, Doug M.

doi:10.1016/j.arr.2014.01.004

Cited by 790 publications

(568 citation statements)

References 141 publications

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“…With an incidence of 2 cases per 10,000 people, PD is caused preferentially by overexposure to different environmental factors (e.g., pesticides, insecticides, some medicines, metals) but also (<5 % of cases) by mutations in some genes encoding for proteins such as α-synuclein, parkin, PINK1 (phosphatase and tensin homologinduced putative kinase 1) and LRRK2 (leucine-rich repeat kinase 2) [104]. PD affects numerous brain structures, then producing different nonmotor (e.g., drooling, changes in taste and smell, nausea and vomiting, constipation, bladder dysfunction, dementia and cognitive impairment, hallucinations, depression and anxiety, and others) and, in particular, motor (e.g., rigidity, bradykinesia, postural instability, tremor) anomalies [105].…”

Section: Cannabinoids and Chronic Neurodegenerative Disorders: II Pdmentioning

confidence: 99%

Cannabinoids in Neurodegenerative Disorders and Stroke/Brain Trauma: From Preclinical Models to Clinical Applications

2015

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Cannabinoids form a singular family of plantderived compounds (phytocannabinoids), endogenous signaling lipids (endocannabinoids), and synthetic derivatives with multiple biological effects and therapeutic applications in the central and peripheral nervous systems. One of these properties is the regulation of neuronal homeostasis and survival, which is the result of the combination of a myriad of effects addressed to preserve, rescue, repair, and/or replace neurons, and also glial cells against multiple insults that may potentially damage these cells. These effects are facilitated by the location of specific targets for the action of these compounds (e.g., cannabinoid type 1 and 2 receptors, endocannabinoid inactivating enzymes, and nonendocannabinoid targets) in key cellular substrates (e.g., neurons, glial cells, and neural progenitor cells). This potential is promising for acute and chronic neurodegenerative pathological conditions. In this review, we will collect all experimental evidence, mainly obtained at the preclinical level, supporting that different cannabinoid compounds may be neuroprotective in adult and neonatal ischemia, brain trauma, Alzheimer's disease, Parkinson's disease, Huntington's chorea, and amyotrophic lateral sclerosis. This increasing experimental evidence demands a prompt clinical validation of cannabinoid-based medicines for the treatment of all these disorders, which, at present, lack efficacious treatments for delaying/arresting disease progression, despite the fact that the few clinical trials conducted so far with these medicines have failed to demonstrate beneficial effects.

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Section: Cannabinoids and Chronic Neurodegenerative Disorders: II Pdmentioning

confidence: 99%

Cannabinoids in Neurodegenerative Disorders and Stroke/Brain Trauma: From Preclinical Models to Clinical Applications

2015

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“…Accumulation of mitochondrial DNA defects, oxidative damage, and aggregation of neuromelanin increases the vulnerability of SN neurons which is amplified by a further insult from alpha-synuclein. [18] Among the comorbid illnesses, gender differences were noted in the incidence of HTN and dyslipidemia as it was significantly greater in males than females. Androgen-mediated chronic increase in renal angiotensinogen stimulates the renin activity.…”

Section: Discussionmentioning

confidence: 99%

Age- and gender-related differences in drug utilization patterns among patients in neurology ward of a tertiary care hospital

Bose¹,

Sushma²,

Agadi³

2017

Natl J Physiol Pharm Pharmacol

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Background: In most of Indian studies gender-specific prevalence rates for neurological disorders were found to be higher in men than women. Different studies revealed age-specific prevalence rates of various neurological disorders increases till fourth decade followed by decline to seventh decade. Aims and Objectives: The present study was taken to evaluate age-and gender-based inequalities in the clinical diagnosis, comorbidities, and drug utilization patterns of patients admitted to the neurology ward. Materials and Methods: The current study was a prospective cohort study. Case records of 200 patients over a period of January-December 2015 were reviewed. The demographic, clinical, and drug consumption data of the patients were evaluated based on age group (18-59 years vs. ≥60 years) and gender. Results: A total of 200 patients were admitted to neurology wards during the study. Of 200 patients, 60% were males, and 18% were ≥60-yearold. Consumption of antiepileptic drugs (AEDs), dopamine agonists, and antidepressants were found to be greater among patients aged >60 years (P < 0.05). Consumption of antiplatelets was significantly more among males, whereas utilization of vitamin was significantly among female (P < 0.05). The incidence of polypharmacy was noted significantly higher among elderly (P < 0.05). The duration of hospital stay was higher for elderly patients than patients aged between 18 and 59 years (P < 0.05). Conclusion: Age-related differences were observed in utilization of AEDs, dopamine agonists, and antidepressants. Gender-related differences were observed in drug utilization of anti-platelets and vitamins. Age-and gender-related differences were observed in the occurrence of polypharmacy.

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“…Dozens of clinical phenotypes, such as Parkinson's (Reeve et al ., 2014), AD (McAuley et al ., 2009), body mass index, blood pressure (Mungreiphy et al ., 2011) and bone mineral density (Warming et al ., 2002), as well as lifestyle parameters, such as nutrition (Wieser et al ., 2011), smoking and physical activity, are strongly related to age (Harman, 1988; Wang et al ., 2009). Composite measures such as the Rockwood frailty index (Rockwood & Mitnitski, 2007) combine several of those clinical traits to form a more homogenous phenotype – frailty – from its diverse appearance.…”

Section: Omics and Agingmentioning

confidence: 99%

Integration of ‘omics’ data in aging research: from biomarkers to systems biology

et al. 2015

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SummaryAge is the strongest risk factor for many diseases including neurodegenerative disorders, coronary heart disease, type 2 diabetes and cancer. Due to increasing life expectancy and low birth rates, the incidence of age‐related diseases is increasing in industrialized countries. Therefore, understanding the relationship between diseases and aging and facilitating healthy aging are major goals in medical research. In the last decades, the dimension of biological data has drastically increased with high‐throughput technologies now measuring thousands of (epi) genetic, expression and metabolic variables. The most common and so far successful approach to the analysis of these data is the so‐called reductionist approach. It consists of separately testing each variable for association with the phenotype of interest such as age or age‐related disease. However, a large portion of the observed phenotypic variance remains unexplained and a comprehensive understanding of most complex phenotypes is lacking. Systems biology aims to integrate data from different experiments to gain an understanding of the system as a whole rather than focusing on individual factors. It thus allows deeper insights into the mechanisms of complex traits, which are caused by the joint influence of several, interacting changes in the biological system. In this review, we look at the current progress of applying omics technologies to identify biomarkers of aging. We then survey existing systems biology approaches that allow for an integration of different types of data and highlight the need for further developments in this area to improve epidemiologic investigations.

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Ageing and Parkinson's disease: Why is advancing age the biggest risk factor?

Abstract: Graphical abstract

Cited by 790 publications

References 141 publications

Cannabinoids in Neurodegenerative Disorders and Stroke/Brain Trauma: From Preclinical Models to Clinical Applications

Cannabinoids in Neurodegenerative Disorders and Stroke/Brain Trauma: From Preclinical Models to Clinical Applications

Age- and gender-related differences in drug utilization patterns among patients in neurology ward of a tertiary care hospital

Integration of ‘omics’ data in aging research: from biomarkers to systems biology

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