Neurology: Complementary biomarkers may predict Alzheimers

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FDG-PET and episodic memory performance predict conversion from mild cognitive impairment to Alzheimer’s disease (AD), according to a study published in the July edition of Neurology. Physicians and researchers could use the biomarker combination to identify patients who would benefit from treatment when it becomes available and also to select subjects for clinical trials of therapeutic agents.

Although a variety of measures are associated with decline in mild cognitive impairment, researchers have not yet identified optimal markers for predicting progression from mild cognitive impairment to AD.

The study sought to evaluate the prognostic ability of a number of candidate biomarkers--genetic, CSF, neuroimaging and cognitive measurements--in the same participants over a two year follow-up to determine which marker or combination of markers is optimal for predicting conversion to AD and cognitive decline, explained Susan Landau, PhD, of University of California at Berkeley, Calif., and colleagues.

The study population included 200 cognitively normal subjects, 400 subjects with mild cognitive impairment and 200 patients with early AD enrolled in the Alzheimer’s Disease Neuroimaging Initiative (ADNI).

By April 2009, a subset of 85 participants with MCI between the ages of 55 and 90 had baseline data for all selected measures. Serial clinical assessments were carried out at six, 12, 18, 24 and 36 months. The Alzheimer’s Disease Assessment Scale-Cognitive Subscale and diagnostic status of stable as mild cognitive impairment or converting to AD were outcome variables of interest.

Study participants with mild cognitive impairment with abnormal results on both FDG-PET and AVLT (an episodic memory assessment) were 11.7 more likely to convert to Alzheimer’s than subjects who were normal on both measures. In addition, in multivariate models predicting conversion to AD, glucose metabolism and memory function were significant, according to the authors. CSF proteins (p-tau181p/AB1-42) and, marginally FDG-PET, were significant in predicting longitudinal cognitive decline.

“The fact that different combinations of markers predict conversion status and cognitive decline suggests that these markers may track different aspects of disease progression,” wrote Landau and colleagues. “Predictors associated with conversion (AVLT and FDG-PET) likely reflect disease severity…Predictors associated with cognitive decline (CSF p-tau181p/AB1-42 and secondarily FDG-PET) likely reflect rate of change, independent of absolute disease severity.”