Context Small single-center studies have shown that cerebrospinal fluid (CSF) biomarkers may be useful to identify incipient Alzheimer disease (AD) in patients with mild cognitive impairment (MCI), but large-scale multicenter studies have not been conducted. Objective To determine the diagnostic accuracy of CSF ␤-amyloid 1-42 (A␤42), total tau protein (T-tau), and tau phosphorylated at position threonine 181 (P-tau) for predicting incipient AD in patients with MCI. Design, Setting, and Participants The study had 2 parts: a cross-sectional study involving patients with AD and controls to identify cut points, followed by a prospective cohort study involving patients with MCI, conducted 1990-2007. A total of 750 individuals with MCI, 529 with AD, and 304 controls were recruited by 12 centers in Europe and the United States. Individuals with MCI were followed up for at least 2 years or until symptoms had progressed to clinical dementia. Main Outcome Measures Sensitivity, specificity, positive and negative likelihood ratios (LRs) of CSF A␤42, T-tau, and P-tau for identifying incipient AD. Results During follow-up, 271 participants with MCI were diagnosed with AD and 59 with other dementias. The A␤42 assay in particular had considerable intersite variability. Patients who developed AD had lower median A␤42 (356; range, 96-1075 ng/L) and higher P-tau (81; range, 15-183 ng/L) and T-tau (582; range, 83-2174 ng/L) levels than MCI patients who did not develop AD during follow-up (579; range, 121-1420 ng/L for A␤42; 53; range, 15-163 ng/L for P-tau; and 294; range, 31-2483 ng/L for T-tau, PϽ.001). The area under the receiver operating characteristic curve was 0.78 (95% confidence interval [CI], 0.75-0.82) for A␤42, 0.76 (95% CI, 0.72-0.80) for P-tau, and 0.79 (95% CI, 0.76-0.83) for T-tau. Cutoffs with sensitivity set to 85% were defined in the AD and control groups and tested in the MCI group, where the combination of A␤42/P-tau ratio and T-tau identified incipient AD with a sensitivity of 83% (95% CI, 78%-88%), specificity 72% (95% CI, 68%-76%), positive LR, 3.0 (95% CI, 2.5-3.4), and negative LR, 0.24 (95% CI, 0.21-0.28). The positive predictive value was 62% and the negative predictive value was 88%. Conclusions This multicenter study found that CSF A␤42, T-tau, and P-tau identify incipient AD with good accuracy, but less accurately than reported from single-center studies. Intersite assay variability highlights a need for standardization of analytical techniques and clinical procedures.

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Background-We examined whether cerebral metabolic rates for glucose (CMRglc) on 2-[ 18 F] fluoro-2-deoxy-D-glucose (FDG)-positron emission tomography (PET) and cerebrospinal fluid (CSF) markers of Alzheimer's disease (AD) are altered in cognitively normal apolipoprotein E (ApoE) E4 carriers with subjective memory complaints (SMC).

Background:At cross-section, cognitively normal individuals (NL) with a maternal history of late-

P-tau(231) is the strongest predictor of the decline from MCI to AD. IP levels uniquely show longitudinal progression effects. These results suggest the use of CSF biomarkers in secondary prevention trials.

Background/Aims: Subjective memory complaint (SMC) in normal individuals may predict future cognitive decline. The goal of this study was to examine whether the probability of decline increases with growing intensity of complaint. Methods: Normal subjects over the age of 50 years were included in a longitudinal retrospective study (mean follow-up time = 8 years). All subjects (n = 230) underwent cognitive and medical examination at baseline. The presence of SMC was determined based on Global Deterioration Scale staging. A subgroup of 83 participants also received baseline assessment for the intensity of SMC. Logistic regression was used to predict outcome from baseline variables. Three outcome groups were established at the final visit: nondeclining, declining and diagnostically unstable (i.e. the diagnosis changed over time: from normal to mild cognitive impairment, then back to normal). Results: The presence of SMC was a predictor of future decline but also increased the likelihood of the unstable diagnosis. Increasing intensity of SMC did not further raise the risk for decline. High intensity of complaints and more pronounced affective symptoms predicted the unstable clinical diagnosis. Conclusions: The presence of SMC contributes to the risk of future decline, however, the increasing intensity of the perceived impairment does not further enhance the risk.

It is widely believed that the path to early and effective treatment for Alzheimer's disease (AD) requires the development of early diagnostic markers that are both sensitive and specific. To this aim, using longitudinal study designs, we and others have examined magnetic resonance imaging (MRI), 2-fluoro-2-deoxy-d-glucose-positron emission tomography (FDG/PET), and cerebrospinal fluid (CSF) biomarkers in cognitively normal elderly (NL) subjects and in patients with mild cognitive impairment (MCI). Such investigations have led to the often replicated findings that structural evidence of hippocampal atrophy as determined by MRI, as well as metabolic evidence from FDG-PET scan of hippocampal damage, predicts the conversion from MCI to AD. In this article we present a growing body of evidence of even earlier diagnosis. Brain pathology can be detected in NL subjects and used to predict future transition to MCI. This prediction is enabled by examinations revealing reduced glucose metabolism in the hippocampal formation (hippocampus and entorhinal cortex [EC]) as well as by the rate of medial temporal lobe atrophy as determined by MRI. However, neither regional atrophy nor glucose metabolism reductions are specific for AD. These measures provide secondary not primary evidence for AD. Consequently, we will also summarize recent efforts to improve the diagnostic specificity by combining imaging with CSF biomarkers and most recently by evaluating amyloid imaging using PET. We conclude that the combined use of conventional imaging, that is MRI or FDG-PET, with selected CSF biomarkers incrementally contributes to the early and specific diagnosis of AD. Moreover, selected combinations of imaging and CSF biomarkers measures are of importance in monitoring the course of AD and thus relevant to evaluating clinical trials.

Although the diagnostic accuracies for AD decreased with age, the predictive values for a combination of biomarkers remained essentially stable. The findings highlight biomarker variability across ages, but support the use of CSF biomarkers for AD even in older populations.