δ Scores Identify Subsets of "Mild Cognitive Impairment" with Variable Conversion Risks

Statin use moderates APOE's and CRP's associations with dementia and is associated with lesser dementia severity in ε4 carriers

INTRODUCTION

We tested the effect of statins on C-reactive protein (CRP) and apolipoprotein E (APOE)'s associations with dementia severity.

METHODS

A total of 1725 participants of the Alzheimer's Disease Neuroimaging Initiative (ADNI) were assigned from 12-month follow-up data into the following groups: (1) ε4 (-)/statin (-), (2) ε4 (-)/statin (+), (3) ε4 (+)/statin (-), and (4) ε4 (+)/statin (+). Dementia severity was assessed by a δ homolog: "dHABS." A mediation model was stratified on statin use and moderation effects tested by a chi-square difference.

RESULTS

Plasma CRP level decreased with ε4 allelic dose. Statins had no effect on the dHABS d-score in non-carriers but were associated with better scores in carriers. Treated carriers did not have more severe dementia than non-carriers. Statin use moderated the mutual adjusted effects of APOE and CRP. CRP was not a mediator of APOE's effect.

DISCUSSION

Statins may provide a protective effect on the dementia severity of ε4 carriers.

HIGHLIGHTS

δ is a dementia-specific phenotype related to general intelligence "g" and is assessed via a "d-score." Apolipoprotein E (APOE) and plasma C-reactive protein (CRP) are independently associated with δ. Plasma CRP decreases with ε4 allelic dose. Statins were associated with better (less demented) d-scores in ε4 carriers but had no effect in non-ε4 carriers. Treated ε4 carriers did not have more severe dementia than non-carriers. Statin use moderated the effects of APOE and CRP on δ. CRP was not a mediator of APOE's effect on δ.

Intelligence, cognition, and major neurocognitive disorders: From constructs to measures

The study of intelligence's role in development of major neurocognitive disorders (MND) is influenced by the approaches used to conceptualize and measure these constructs. In the field of cognitive impairment, the use of single 'intelligence' tests is a common approach to estimate intelligence. Despite being a practical compromise between feasibility and constructs, variance of these tests is only partially explained by general intelligence, and some tools (e.g., lexical tasks for premorbid intelligence) presented inherent limitations. Alternatively, factorial models allow an actual measure of intelligence as a latent factor superintending all mental abilities. Royall and colleagues used structural equation modeling to decompose the Spearman's general intelligence factor g in δ (shared variance across cognitive and functional measures) and g' (shared variance across cognitive measures only). Authors defined δ as the 'cognitive correlates of functional status', and thus a 'phenotype for all cause dementia'. Compared to g', δ explained a little rate of cognitive measures' variance, but it demonstrated a higher accuracy in dementia case-finding. From the methodological perspective, given g 'indifference' to its indicators, further studies are needed to identify the minimal set of tools necessary to extract g, and to test also non-cognitive variables as measures of δ. From the clinical perspective, general intelligence seems to influence MND presence and severity more than domain specific cognitive abilities. Giving δ 'blindness' to etiology, its association with biomarkers and contribution to differential diagnosis might be limited. Classical neuropsychological approaches based on patterns of performances at cognitive tests remained fundamental for differential diagnosis.

δ scores predict multiple neuropsychiatric symptoms

OBJECTIVES

Dementia severity is strongly related to Spearman's general intelligence factor "g", via the latent dementia phenotype "δ" and is distinct from domain-specific cognitive impairments arising from disease-specific regional pathologies. It is an empiric question whether behavioral and psychological symptoms of dementia (BPSD) are associated with δ or with domain-specific constructs.

METHODS

A recently developed δ homolog ("dDx") was tested as a predictor of 1 year prospective BPSD in n = 723 Mexican-American and non-Hispanic White participants in the Texas Alzheimer's Research and Care Consortium (TARCC). The informant-rated frequencies of 12 BPSD were rated by the neuropsychiatric inventory (NPI-Q). Baseline BPSD, demographic features, selected biomarkers, and treatment exposure to acetylcholinesterase inhibitors were used as covariates. Composite scores derived from orthogonal latent measures of domain-specific memory (MEM) and executive function (EF) were also tested as predictors.

RESULTS

"Functionally salient cognitive impairment (FSCI)" that is, categorical "dementia" as diagnosed by dDx was associated with increased prospective frequency of 11/12 BPSD, independently of baseline behavior and covariates. Age, depressive symptoms, and EF were associated with individual BPSD. MEM was not associated with any. Dementia severity, as measured by dDx, was also associated with a prospective increase in total NPI-Q scores.

CONCLUSION

δ is associated non-specifically with multiple BPSD. This suggests the existence of a dementia-specific behavioral profile, arising from insults to general intelligence, and unrelated to disease-specific regional pathology(ies).

δ-Related Biomarkers Attenuate Multiple Alzheimer's Disease Conversion Risks and Offer Targets for Intervention

BACKGROUND

We tested certain serum proteins' ability to mediate the effects of demographic variables on prospective 5-year conversion to clinical "Alzheimer's disease" from non-demented states (i.e. normal control and mild cognitive impairment). The proteins were rationally selected from previously published mediators of those same variables' (plural posessive) association with the latent variable "δ," a novel omnibus dementia severity metric.

METHODS

Each protein's attenuation of its risk factor's independent association with conversion was performed using logistic regression, adjusted for education, ethnicity, self-reported diabetes mellitus, and hypertension, among initially non-demented Mexican American and non-Hispanic white (N = 772) participants in the Texas Alzheimer's Research and Care Consortium.

RESULTS

A total of 70 (9.1%) non-demented participants at baseline converted to "Alzheimer's disease", with a mean follow-up of 5.4 years. Age >80 years (odds ratio = 3.1), 30-item Geriatric Depression Scale >10/30 (odds ratio = 2.3), female gender (odds ratio = 2.2), and the presence of an apolipoprotein E ε4 allele (odds ratio = 2.4) were independently associated with prospective conversion. These effects were fully attenuated by five serum proteins: age: insulin-like growth factor-binding protein 2 and epidermal growth factor receptor 1; depression: resistin; gender: thrombopoietin; and apolipoprotein E: C-reactive protein.

CONCLUSION

Clinical dementia arises from the sum of independent δ-related processes. This analysis provides proof of concept for the rational selection of antidementia targets and offers a foundation for precision antidementia therapy.

Blood-based protein predictors of dementia severity as measured by δ: Replication across biofluids and cohorts

INTRODUCTION

Dementia severity can be empirically described by the latent dementia phenotype "δ" and its various composite "homologs". We have explored δ's blood-based protein biomarkers in the Texas Alzheimer's Research and Care Consortium (TARCC) study. However, it would be convenient to replicate those associations in the Alzheimer's Disease Neuroimaging Initiative (ADNI). To this end, we recently engineered a δ homolog from observed cognitive performance measures common to both projects (i.e., "dT2A").

METHODS

We used nine rationally chosen peripheral blood-based protein biomarkers as indicators of a latent variable "INFLAMMATION". We then associated that construct with dT2A in structural equation models adjusted for age, gender, depressive symptoms, and apolipoprotein E (APOE) ε4 allelic burden. Significant factor loadings and INFLAMMATION's association with dT2A were confirmed in random splits of TARCC's relatively large sample, and across biofluids in the ADNI.

RESULTS

Nine proteins measured in serum (TARCC) or plasma (ADNI) explained ≅10% of dT2A's variance in both samples, independently of age, APOE, education, and gender. All loaded significantly on INFLAMMATION, and positively or negatively, depending on their known roles are PRO- or ANTI-inflammatory proteins, respectively. The parameters of interest were confirmed across random 50% splits of the TARCC's sample, and replicated across biofluids in the ADNI.

DISCUSSION

These results suggest that SEM can be used to replicate biomarker findings across samples and biofluids, and that a substantial fraction of dementia's variance is attributable to peripheral blood-based protein levels.