Neurobiology of aging
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Neurobiology of aging · Aug 2012
Testing the white matter retrogenesis hypothesis of cognitive aging.
The retrogenesis hypothesis postulates that late-myelinated white matter fibers are most vulnerable to age- and disease-related degeneration, which in turn mediate cognitive decline. While recent evidence supports this hypothesis in the context of Alzheimer's disease, it has not been tested systematically in normal cognitive aging. In the current study, we examined the retrogenesis hypothesis in a group (n = 282) of cognitively normal individuals, ranging in age from 7 to 87 years, from the Brain Resource International Database. ⋯ FA and RD in most fiber tracts showed reliable age-associated differences in the older age group, but the magnitudes were greatest for the late-myelinated tract summary measure, inferior longitudinal fasciculus (late fiber tract), and cerebral peduncles (early fiber tract). Finally, FA in the inferior longitudinal fasciculus and cerebral peduncles and RD in the cerebral peduncles mediated age-associated differences in an executive functioning factor. Taken together, the findings highlight the importance of white matter coherence in cognitive aging and provide some, but not complete, support for the white matter retrogenesis hypothesis in normal cognitive aging.
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Neurobiology of aging · Aug 2012
Genetic variants influencing human aging from late-onset Alzheimer's disease (LOAD) genome-wide association studies (GWAS).
Genetics plays a crucial role in human aging with up to 30% of those living to the mid-80s being determined by genetic variation. Survival to older ages likely entails an even greater genetic contribution. There is increasing evidence that genes implicated in age-related diseases, such as cancer and neuronal disease, play a role in affecting human life span. ⋯ No genome-wide significant SNPs were discovered. Increasing sample size and statistical power will be imperative to detect genuine aging-associated variants in the future. In this report, we also discuss issues relating to the analysis of genome-wide association studies data from different centers and the bioinformatic approach required to distinguish spurious genome-wide significant signals from real SNP associations.