Sensitivity of memory subtests and learning slopes from the ADAS-Cog to distinguish along the continuum of the NIA-AA Research Framework for Alzheimer's Disease.

Despite extensive use of the Alzheimer's Disease (AD) Assessment Scale - Cognitive Subscale (ADAS-Cog) in AD research, exploration of memory subtests or process scores from the measure has been limited. The current study sought to establish validity for the ADAS-Cog Word Recall Immediate and Delayed Memory subtests and learning slope scores by showing that they are sensitive to AD biomarker status. Word Recall subtest and learning slope scores were calculated for 441 participants from the Alzheimer's Disease Neuroimaging Initiative (aged 55 to 90). All participants were categorized using the NIA-AA Research Framework - based on PET-imaging of ß-amyloid (A) and tau (T) deposition - as Normal AD Biomarkers (A-T-), Alzheimer's Pathologic Change (A + T-), or Alzheimer's disease (A + T+). Memory subtest and learning slope performances were compared between biomarker status groups, and with regard to how well they discriminated samples with (A + T+) and without (A-T-) biomarkers. Lower Word Recall memory subtest scores - and scores for a particular learning slope calculation, the Learning Ratio - were observed for the AD (A + T+) group than the other biomarker groups. Memory subtest and Learning Ratio scores further displayed fair to good receiver operator characteristics when differentiating those with and without AD biomarkers. When comparing across learning slopes, the Learning Ratio metric consistently outperformed others. ADAS-Cog memory subtests and the Learning Ratio score are sensitive to AD biomarker status along the continuum of the NIA-AA Research Framework, and the results offer criterion validity for use of these subtests and process scores as unique markers of memory capacity.

Assessing and validating reliable change across ADNI protocols.

OBJECTIVE: Reliable change methods can aid in determining whether changes in cognitive performance over time are meaningful. The current study sought to develop and cross-validate 12-month standardized regression-based (SRB) equations for the neuropsychological measures commonly administered in the Alzheimer's Disease Neuroimaging Initiative (ADNI) longitudinal study. METHOD: Prediction algorithms were developed using baseline score, retest interval, the presence/absence of a 6-month evaluation, age, education, sex, and ethnicity in two different samples (n = 192 each) of robustly cognitively intact community-dwelling older adults from ADNI - matched for demographic and testing factors. The developed formulae for each sample were then applied to one of the samples to determine goodness-of-fit and appropriateness of combining samples for a single set of SRB equations. RESULTS: Minimal differences were seen between Observed 12-month and Predicted 12-month scores on most neuropsychological tests from ADNI, and when compared across samples the resultant Predicted 12-month scores were highly correlated. As a result, samples were combined and SRB prediction equations were successfully developed for each of the measures. CONCLUSIONS: Establishing cross-validation for these SRB prediction equations provides initial support of their use to detect meaningful change in the ADNI sample, and provides the basis for future research with clinical samples to evaluate potential clinical utility. While some caution should be considered for measuring true cognitive change over time - particularly in clinical samples - when using these prediction equations given the relatively lower coefficients of stability observed, use of these SRBs reflects an improvement over current practice in ADNI.

Specific immune responses in workers exposed to benzene.

UNLABELLED: The aim of this study was to elaborate a method for detection of specific IgG antibodies (Abs) to the haptenes p-benzoquinone (p-BQ) and hydroquinone (HQ) for assessment of specific humoral immune responses. Plasma and urine, collected from petrochemical plant workers have been analyzed. The workers were divided into three professional groups in ascending order of benzene exposure. The concentration of benzene in the air was determined by gas chromatography with mass-spectrometry and trans,trans-muconic acid (biomarker of benzene exposure) in urine-by liquid chromatography with UV-detection. Specific IgG Abs to haptenes p-BQ and HQ in plasma were determined with newly developed ELISA. The relationships "exposure-effect," revealed increased levels of specific IgG to haptens correlating with the benzene exposure. The "exposure-response" relationships demonstrated that workers with value of OD over X+2SD were 62% low exposure group, 68% in group with level of exposure on Threshold Limit Value (TLV) and 91% in the highest exposure group. The data obtained show that there is a good correlation between antibody production and the biomarker of exposure t,t-muconic acid. CONCLUSION: The newly developed method is applicable for assessment of specific humoral immune responses in workers exposed to benzene. There was a good correlation between benzene exposure and formation of antibodies against benzene metabolites.