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Comment on Andrews et al.

To the Editor: We read with interest a recent paper by Andrews et al.1 They report the relative effects of the Australian National University Alzheimer’s Disease Risk Index (ANU-ADRI) (an index of dementia risk factors) and an Alzheimer disease (AD)-specific genetic risk score (GRS) on a latent δ homolog derived from observed cognitive performance. δ (for “dementia”) is a latent variable derived by a specific bifactor confirmatory factor analysis in a structural equation model framework and which represents “the cognitive correlates of functional status.” Because δ is derived from Spearman’s general intelligence factor “g,” it can be estimated in any cognitive battery that contains a measure of Instrumental Activities of Daily Living. So many batteries are available, that we refer to each embodiment as a “homolog.” In genetics, a homolog is a gene descended from an ancestral gene in the same species and with a similar function. To our knowledge, this is the 14th δ homolog published to date. Although Andrews and colleagues did not explicitly validate their new construct, all δ homologs validated to date are strongly correlated with dementia severity as measured by the Clinical Dementia Rating Scale “Sum of Boxes” (CDR-SB) (both cross-sectionally and longitudinally)2,3 and achieve high areas under the receiver operating characteristic curve for dementia’s discrimination from normal controls. We wish to make two observations on this study. First, δ’s model fit the data better than either of the competing models they proposed and was more strongly associated with the ANU-ADRI and GRS than almost every other latent factor. Model 3 purports to describe “domain-specific” cognitive factors. However, that is not the case. The factors were densely intercorrelated, which betrays g’s (and possibly δ’s) contribution to the observed variance (without explicitly modeling it). To validly test the environmental and genetic determinants of domain-specific function(s), the indicators of those domains would need adjustment for g.4 Thus, the apparent association between multiple domains and the ANU-ADRI or between episodic memory and the GRS may yet have been mediated via g (or δ). Second, δ is a dementia-specific cognitive phenotype. It is agnostic to dementia’s etiology.3 This may explain why the ANU-ADRI explains more of δ’s variance than the GRS. Although the ANU-ADRI purports to be an “Alzheimer’s Disease Risk Index,” the conditions it references (eg, age, sex, alcohol consumption, diabetes, education, depression, traumatic brain injury, etc.) are less likely to be predictors of AD specifically, than they are to be predictors of dementia broadly. In contrast, the GRS has been engineered to be indicative of AD, and the authors cite evidence of its association with abeta deposition in nondemented persons. The GRS’ relatively weak effect on δ suggests that not all of AD’s biomarkers may contribute to its dementing effects. Abeta deposition in particular may be no more than weakly associated with that syndrome (as is GRS with δ). δ’s AD-specific biomarkers should mediate AD’s dementing effects. AD-specific biomarkers unrelated to δ may mediate AD’s nondementing aspects.