APP protein, human

The primary objective of the A4 study is to test the hypothesis that solanezumab, administered as a 400-mg intravenous infusion every 4 weeks for 168 weeks, will slow cognitive decline compared with placebo in participants with preclinical AD. This objective will be assessed using a mixed model of repeated measures (MMRM) analysis of change in the ADCS-PACC score. The specific hypothesis of the A4 study is that there will be less of a decrease in the ADCS-PACC score at the end of the treatment period for participants treated with solanezumab than for participants treated with placebo.
Based on a review of the literature for cohort studies in “normal controls” who progressed to mild cognitive impairment or Alzheimer dementia, we determined that a composite measure sensitive to change in preclinical AD would likely require assessment of 3 key domains: episodic memory, executive function, and orientation. Previous studies^{19 (link)–21 (link)} have reported evidence that both list learning and paragraph recall (measures of episodic memory) tend to decline 7 to 10 years prior to the diagnosis of MCI or Alzheimer dementia. Recent data from amyloid imaging studies^{25 (link)–29 (link)} have reported a decline in multiple cognitive domains looking retrospectively at cognitive trajectories over 8 to 10 years prior to PET amyloid imaging^{22 (link)–24 (link)} and prospectively over 1- to 3-year longitudinal follow-up.
Based on this review, we propose a composite of 4 measures that are well established as showing sensitivity to decline in prodromal and mild dementia, and with sufficient range to detect early decline in the preclinical stages of the disease. The ADCS-PACC includes:

The Total Recall score from the Free and Cued Selective Reminding Test (FCSRT) (0–48 words),^{20 (link),30 (link)}

The Delayed Recall score on the Logical Memory IIa sub-test from the Wechsler Memory Scale (0–25 story units),³¹

The Digit Symbol Substitution Test score from the Wechsler Adult Intelligence Scale–Revised (0–93 symbols),³² and

The MMSE total score (0–30 points).^{33 (link)}

The composite score is determined from its components using an established normalization method.^{34 (link)} Each of the 4 component change scores is divided by the baseline sample standard deviation of that component, to form standardized z scores. These z scores are summed to form the composite. Thus, a change of 1 baseline standard deviation on each component would correspond to a 4-point change on the composite. In the A4 study, the ADCS-PACC will be administered at baseline and at 24, 48, 72, 96, 120, 144, and 168 weeks, alternating between 3 test versions.

The post-mortem neuropathologic evaluation includes a uniform structured assessment of AD pathology, cerebral infarcts, Lewy body disease, and other pathologies common in aging and dementia. The procedures follow those outlined by the pathologic dataset recommended by the National Alzheimer's Disease Coordinating Center (NACC) [87 (link)]. Pathologic diagnoses of AD use NIA-Reagan and modified CERAD criteria, and the staging of neurofibrillary pathology uses Braak Staging [88 (link)–90 (link)]. The location, size, and age of each macroscopic infarct are recorded as described [91 ]. Microscopic infarctions are identified on H&E stained sections; Lewy bodies are identified on alpha-synuclein immunostained sections [91 ].
Counts of neuritic plaques diffuse plaques, and neurofibrillary tangles based on silver stain from five brain regions are used to create a global measure of AD pathology [70 ]. Amyloid load and the density of paired helical filament tau (PHFtau) are determined in eight brain regions and summarized [70 ].

While all biomarkers and cognitive tests are continuous measures, the NIA-AA criteria for preclinical AD require that every biomarker and cognitive test is designated normal or abnormal [1 ]. This requires that cut-points be created in these continuous distributions. The ideal method for selecting biomarker cut-points would be to use autopsy diagnoses as the reference standard of truth [20 (link)–22 (link)]. Because we do not yet have an adequately large autopsy sample with antemortem 3T MRI, PIB PET and FDG PET, we created cut-points such that a majority of clinically defined AD dementia patients would be deemed abnormal. While we did not have CSF available in our subjects, we had amyloid (PIB-PET) and neurodegenerative (FDG-PET and MRI) biomarkers in all subjects, and were therefore able to stage all subjects in accordance with the NIA-AA criteria (1). We had two sources of data in the neurodegenerative biomarker category (FDG PET and MRI) and we considered a subject positive for evidence of neurodegeneration if either or both fell below the cut-point.
Cut-points were based on estimated percentiles. For example, where higher biomarker values are worse, the cut-point corresponding to 90% sensitivity was the estimated 10^th percentile of the AD distribution. Where lower biomarker values are worse, the cut-point was the estimated 90^th percentile of the AD distribution. In this example, approximately 90% of ADs are considered abnormal. Biomarker cut-points corresponding to other levels of sensitivity were determined similarly.
Because the cognitive impairment seen in AD dementia or even MCI could not be used as an external reference for evidence of subtle cognitive decline in CN subjects, we used percentiles of the global summary score from the 450 CN subjects in this study. These percentiles can also be thought of as corresponding to a specificity level in that the 10^th percentile of the distribution corresponds to a specificity level of 90%. Note that this approach, unlike the approach used for biomarkers, guarantees a certain number of subjects will fall below the subtle “cognitive impairment" cut point.