Abstract
BackgroundHuman brain aging has received special attention in part because of the elevated risks of neurodegenerative disorders such as Alzheimer's disease in seniors. Recent technological advances enable us to investigate whether similar mechanisms underlie aging and neurodegeneration, by quantifying the similarities and differences in their genome-wide gene expression profiles.Principal FindingsWe have developed a computational method for assessing an individual's “physiological brain age” by comparing global mRNA expression datasets across a range of normal human brain samples. Application of this method to brains samples from select regions in two diseases – Alzheimer's disease (AD, superior frontal gyrus), frontotemporal lobar degeneration (FTLD, in rostral aspect of frontal cortex ∼BA10) – showed that while control cohorts exhibited no significant difference between physiological and chronological ages, FTLD and AD exhibited prematurely aged expression profiles.ConclusionsThis study establishes a quantitative scale for measuring premature aging in neurodegenerative disease cohorts, and it identifies specific physiological mechanisms common to aging and some forms of neurodegeneration. In addition, accelerated expression profiles associated with AD and FTLD suggest some common mechanisms underlying the risk of developing these diseases.
Highlights
Human brain aging and neurodegenerative diseases Among human tissues, the brain in normal aging and in neurodegenerative disease has received special attention
Accelerated expression profiles associated with Alzheimer’s disease (AD) and frontotemporal lobar degeneration (FTLD) suggest some common mechanisms underlying the risk of developing these diseases
We examined neurodegenerative diseases that increase in incidence with age (e.g. AD), and those in which the relationship between age and disease incidence is unclear (e.g. FTLD)
Summary
Human brain aging and neurodegenerative diseases Among human tissues, the brain in normal aging and in neurodegenerative disease has received special attention. This interest stems largely from the observation that as humans age most develop some degree of cognitive decline. Measurable differences in cognitive performance are seen in both cross-sectional and longitudinal-design studies [5]. In daily life, these differences are too small and too common to be considered pathological. Pathological decline in cognitive function in the form of a dementing neurodegenerative illness does develop. Recent technological advances enable us to investigate whether similar mechanisms underlie aging and neurodegeneration, by quantifying the similarities and differences in their genome-wide gene expression profiles
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