Most successful gene discovery studies to date have focused on syndromic phenotypes given the availability of large numbers of subjects who fit the clinical definitions of AD, ALS, MS, and PD that can be merged from multiple sources. However, this approach, while convenient and reasonable as a first effort, ignores that large fractions of the control populations used in these studies have subclinical features of the disease. This is particularly true for AD and PD and probably to a lesser extent for ALS. It includes the accumulation of neuritic amyloid plaques, neuronal loss in the substantia nigra and anterior horn, and other pathologies or symptoms, such as subtle cognitive impairment, bradykinesia, and muscle atrophy and weakness, that do not fulfill a syndromic definition.16,17 These asymptomatic, affected subjects have most likely reduced the statistical power of studies of AD and perhaps PD; ALS and MS, because of their low incidence rate in the general population, have been less affected by this problem. Intermediate traits (also referred to as endophenotypes) that capture pertinent features of a neurodegenerative disease have been suggested to have greater statistical power for gene discovery efforts than syndromic phenotypes; for example, the known APOE AD-associated alleles have much larger effects on AD neuropathology and trajectories of cognitive decline than on a syndromic diagnosis of AD when investigated in the same set of deeply phenotyped subjects.18 The endophenotype strategy has been implemented in several studies, but its success is clearly dependent on the quality and statistical properties of the trait being considered. Further, for the more distal phenotypes that capture prediagnosis features of the disease, such studies have been hampered by (1) the lack of consistency in the manner and frequency in which intermediate traits are measured across subject collections and (2) the nature of the subject collections, which range from population-based samples to subjects selected in specialized clinics of tertiary care centers or samples of convenience collected for other purposes. Estimates of the needed sample size for a study of cognitive decline, for example, appear not to be too different from those required for syndromic traits,19 and the recent successful genome-wide association study for loci influencing hippocampal and intracranial volume required in one case a discovery study of more than 9000 subjects and in the other, more than 7000 subjects.20,21 The latter examples speak eloquently to the challenge of combining a trait that is measured in different ways on many different platforms, limiting the power of meta-analysis of different subject collections.