This study did not examine enrichment that could be enabled by combinations of biomarkers, or examine structural outcome measures, as we have done here. In addition to weighing the costs of screen failures against improved trial power, ethical concerns must also be explicitly addressed during the design of a clinical trial that plans to incorporate an enrichment strategy. In such trials, individuals are likely to be informed of their biomarker status, and it is not yet clear what implications that may have for an individual’s future. Institutional review boards will have to be convinced that the risks associated with disclosure of risk status are adequately minimized before such trials can proceed. With the increasing move towards preventive trials, in which risk must be defined on the basis of biomarkers, much attention is currently focused towards development of methods for accurately conveying information regarding biomarker risk to potential participants, while minimizing negative effects of learning one’s risk status. An alternative approach to enrichment strategies, which would ease recruitment and avoid the necessity of informing participants of their risk status, is to 
enroll a broader set of individuals, drawing a balance between selectively enrolling those at high risk while minimizing screen failures, then stratifying participants into biomarker-defined subgroups for analyses. This could determine whether a treatment that might not be effective in the full group showed promise in identifiable subgroups. Such subgroup analyses, and enrichment, could result in drug labeling requirements by regulatory agencies limiting prescription of a successful agent to those with the biomarkers used in the trial. However, given the current lack of any effective therapy for delaying the disease, and the enormous burden the coming epidemic will place on society, establishing efficacy even in a small subgroup would be a development of major importance, and one that could be followed by future trials on less select populations. A different approach to stratification and enrichment for reducing sample sizes for MCI and AD treatment trials was recently proposed that increased effect sizes by reducing interindividual variance through adjustment for several factors, including age, genetics, clinical measures of disease severity, baseline brain measures, and CSF biomarkers. The authors reported a 10�C30% reduction in sample sizes with adjustment for 11 predefined variables. However, some variables might be identified as ��nuisance’ variables, while others might be of crucial importance, depending on therapeutic targeting mechanisms. Thus, for example, if a treatment effect were found for a heterogeneous cohort, it could arise from a strong effect in a particular subset and little or no relevance or effect in another subset of participants. Therefore, though some ��nuisance’ variability could be controlled for, subgroup analysis would still be needed to identify patients that might benefit most from a treatment, and those for whom risks might exceed the benefits. A Lomitapide Mesylate popular model of the sequence of AD biomarkers of the AD pathological cascade postulates that amyloid deposition is an early event followed by neurofibirllary pathology �C though this remains contentions. Since NFT pathology is strongly linked with synaptic and neuronal Benzethonium Chloride injury and loss, next in the postulated sequence of biomarkers is brain atrophy observable on MRI. Consistent with this, we found that in Ab+ MCI individuals, annual atrophy rates were significantly higher for those who tested positive for ptau as compared with those who tested negative for ptau for all subregions examined, except the hippocampus. Interestingly, the hippocampus showed a trend for elevated atrophy rate earlier in the disease process, when evidence of Ab pathology was present.