Even successful normal aging is associated with increasing brain dysfunction in selected cognitive domains. Signs of brain injury- increased atrophy and incidence of hyperintensities seen on imaging studies, cerebral blood flow changes, and neuronal loss and density decreases also accompany aging. To date, attempts to predict cognitive decline in the elderly, from neuroimaging studies have yielded only modest relationships. Using non-invasive proton magnetic resonance spectroscopy (1H-MRS) and quantitative neurocognitive testing in normal young controls, we show exciting preliminary data that variation in cognitive function is strongly related to neurochemical events at the neuronal level. Indeed, these neurochemical findings can account for up to 70 percent of the variability of composite neuropsychological testing results. These results are consistent with findings in other brain injured patient groups we have recently studied: systemic lupus erythematosus and traumatic brain injury. In the current proposal we will use a well established quantitative magnetic resonance imaging and spectroscopic examination of the frontal and occipital lobes and a neuropsychological testing battery designed to assess frontal and attention processes to evaluate a cohort of 60 normal elderly recruited from the University of New Mexico Aging Process Study. It is our initial aim to confirm that neurochemical measures of brain integrity from the frontal lobe predict brain function in normal elderly, and that frontal neurochemistry predicts better than occipital neurochemistry.
Our second aim i s to determine the specific frontal skills most strongly related to frontal lobe neurochemistry. Our outcome measures from 1H-MRS will include N-acetylaspartate, a neuronal marker, and choline, a marker of neurodegeneration and inflammation. The major outcome measures from neurocognitive testing will be measures of executive (frontal) skill, attention, verbal and non-verbal memory, and motor function. An overall measure of functional brain integrity will also be calculated based on a composite of z-scores from individual cognitive domains.
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