The Latent Dementia Phenotype δ is Associated with Cerebrospinal Fluid Biomarkers of Alzheimer's Disease and Predicts Conversion to Dementia in Subjects with Mild Cognitive Impairment

INFLAMMATION's cognitive impact revealed by a novel "Line of Identity" approach

IMPORTANCE

Dementia is an "overdetermined" syndrome. Few individuals are demented by any single biomarker, while several may independently explain small fractions of dementia severity. It may be advantageous to identify individuals afflicted by a specific biomarker to guide individualized treatment.

OBJECTIVE

We aim to validate a psychometric classifier to identify persons adversely impacted by inflammation and replicate it in a second cohort.

DESIGN

Secondary analyses of data collected by the Texas Alzheimer's Research and Care Consortium (TARCC) (N = 3497) and the Alzheimer's Disease Neuroimaging Initiative (ADNI) (N = 1737).

SETTING

Two large, well-characterized multi-center convenience samples.

PARTICIPANTS

Volunteers with normal cognition (NC), Mild Cognitive Impairment (MCI) or clinical "Alzheimer's Disease (AD)".

EXPOSURE

Participants were assigned to "Afflicted" or "Resilient" classes on the basis of a psychometric classifier derived by confirmatory factor analysis.

MAIN OUTCOME(S) AND MEASURE(S)

The groups were contrasted on multiple assessments and biomarkers. The groups were also contrasted regarding 4-year prospective conversions to "AD" from non-demented baseline diagnoses (controls and MCI). The Afflicted groups were predicted to have adverse levels of inflammation-related blood-based biomarkers, greater dementia severity and greater risk of prospective conversion.

RESULTS

In ADNI /plasma, 47.1% of subjects were assigned to the Afflicted class. 44.6% of TARCC's subjects were afflicted, 49.5% of non-Hispanic Whites (NHW) and 37.2% of Mexican Americans (MA). There was greater dementia severity in the Afflicted class [by ANOVA: ADNI /F(1) = 686.99, p <0.001; TARCC /F(1) = 1544.01, p <0.001]. "INFLAMMATION" factor composite scores were significantly higher (adverse) in Afflicted subjects [by ANOVA in ADNI /plasma F(1) = 1642.64, p <0.001 and in TARCC /serum F(1) = 3059.96, p <0.001]. Afflicted cases were more likely to convert to AD in the next four years [by Cox's F, ADNI /plasma: F (252, 268) = 3.74 p < 0.001; TARCC /serum: F (160, 134) = 3.03, p < 0.001 (in TARCC's entire sample), F (110, 90) = 4.92, p <0.001 in NHW, and F(50, 44) = 2.13, p = 0.006 in MA]. The proportions converting were similar among afflicted NHW in both cohorts /biofluids but MA exhibited a lower risk (7% in TARCC /serum at 48 months).

CONCLUSIONS AND RELEVANCE

Our inflammation-specific psychometric classifier selects individuals with pre-specified biomarker profiles and predicts conversion to "AD" across cohorts, biofluids, and ethnicities. This algorithm might be applied to any dementia-related biomarker making the psychometric estimation of individual biomarker effects feasible without biomarker assessment. Our approach also distinguishes individuals resilient to individual biomarker effects allowing for more accurate prediction and precision intervention.

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.

Could Temperamental Features Modulate Participation in Clinical Trials?

The prodromal stages of Alzheimer's disease (AD) are the primary focus of research aimed at slowing disease progression. This study explores the influence of affective temperament on the motivation of people with mild cognitive impairment (MCI) and subjective cognitive decline (SCD) to participate in clinical trials. One hundred four subjects with MCI and SCD were screened for participation in pharmacological and non-pharmacological trials. Affective temperament was assessed based on the Temperament Evaluation of the Memphis, Pisa, Paris and San Diego (TEMPS) scale. Demographic variables and temperament subscales scores were compared between MCI and SCD patients and among patients participating in the pharmacological trial, the non-pharmacological trial and refusing participation. Twenty-one subjects consented to participate in the pharmacological trial, seventy consented to the non-pharmacological trial and thirteen refused to participate in any trial. Patients with SCD had greater education and more depressive temperamental traits than those with MCI. While older age, higher education and anxious temperament were negatively associated with participation in the pharmacological trial, irritable temperamental positively predicted pharmacological trial participation. In conclusion, temperamental features may affect the willingness of patients with MCI and SCD to take part in clinical trials and, especially, the choice to participate in pharmacological studies.

Quantitative informant- and self-reports of subjective cognitive decline predict amyloid beta PET outcomes in cognitively unimpaired individuals independently of age and APOE ε4

INTRODUCTION

Amyloid beta (Aβ) pathology is an Alzheimer's disease early hallmark. Here we assess the value of longitudinal self- and informant reports of cognitive decline to predict Aβ positron emission tomography (PET) outcome in cognitively unimpaired middle-aged individuals.

METHODS

A total of 261 participants from the ALFA+ study underwent [18F]flutemetamol PET and Subjective Cognitive Decline Questionnaire (SCD-Q) concurrently, and 3 years before scan. We used logistic regressions to evaluate the ability of SCD-Q scores (self and informant) to predict Aβ PET visual read, and repeated analysis of variance to assess whether changes in SCD-Q scores relate to Aβ status.

RESULTS

Self-perception of decline in memory (odds ratio [OR] = 1.2), and informant perception of executive decline (OR = 1.6), increased the probability of a positive scan. Informant reports 3 years before scanning predicted Aβ PET outcome. Longitudinal increase of self-reported executive decline was predictive of Aβ in women (P = .003).

DISCUSSION

Subjective reports of cognitive decline are useful to predict Aβ and may improve recruitment strategies.

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.

Serum Adiponectin is Related to Dementia

BACKGROUND

The adipokine adiponectin (APN)'s role in Alzheimer's disease (AD) is controversial. Some studies suggest APN is neuroprotective while others propose it has harmful effects. We have used Multiple Indicators Multiple Causes (MIMIC) models to evaluate the effects of serum protein biomarkers on cognitive performance in the Texas Alzheimer's Research and Care Consortium (TARCC) (Royall DR, Bishnoi RJ, Palmer RF. Serum IGF-BP2 strongly moderates age's effect on cognition: a MIMIC analysis. Neurobiol Aging. 2015;36:2232-2240; Bishnoi RJ, Palmer RF, Royall DR. Vitamin D binding protein as a serum biomarker of Alzheimer's disease. J Alzheimers Dis. 2015;43:37-45; Bishnoi RJ, Palmer RF, Royall DR. Serum interleukin (IL)-15 as a biomarker of Alzheimer's disease. PLoS One. 2015;10:e0117282).

METHODS

MIMIC models were constructed and replicated in randomly selected 50% splits of TARCC's data (Group 1 N = 1,691; Group 2 N = 1,690) and used to evaluate the relationship between serum APN levels and cognition. Our approach has been to divide general intelligence (Spearman's g) (Spearman C. The Abilities of Man: Their Nature and Measurement. 1932) into two latent variables, δ (ie, a dementia-specific phenotype representing the disabling fraction of cognitive variance) and g prime (g') (ie, the residual non-disabling fraction). Only effects on δ are likely to be dementing.

RESULTS

Serum APN was significantly related to δ scores (r = .10, p = .015). APN had no significant effect on g' (r = -.25, p = .66), nor did it have any independent direct effects on cognitive performance. These results were replicated across random subsets (ΔCHISQ = 2.8(7), p > .90).

CONCLUSIONS

APN's effect on cognition is mediated through intelligence (ie, δ), likely to be disabling, and therefore to mediate one or more dementing processes. We have previously shown APN to partially mediate age's-specific effect on δ (Royall DR, Al-Rubaye S, Bishnoi R, Palmer RF. Serum protein mediators of dementia and aging proper. Aging (Albany NY). 2016;8:3241-3254). However, because the current model is age adjusted, APN must mediate one or more additional age-independent dementing process(es), possibly AD.

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.

Selection for depression-specific dementia cases with replication in two cohorts

The latent variable "δ" (for "dementia") provides an etiologically "agnostic" omnibus dementia severity metric capable of recognizing the dementing potential of any condition. Depressive symptoms are independent predictors of δ and are thereby implicated as "dementing". Serum resistin levels partially mediate the association between depressive symptoms and δ. We use a novel "off-diagonal" CHI SQ algorithm to demonstrate our ability to select individuals demented solely by depression's effect in both the Texas Alzheimer's Research and Care Consortium (TARCC) (N ≌ 3,500), and the Alzheimer's Disease Neuroimaging Initiative (ADNI (N ≌ 1,750), and demonstrate the higher resistin levels of such cases in TARCC. This approach can be adapted to any δ-related dementia risk factor or biomarker and used identify individuals who might revert back to non-demented states after its successful treatment.

A δ Homolog for Dementia Case Finding with Replication in the Alzheimer's Disease Neuroimaging Initiative

Dementia 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 have engineered a δ homolog from observed cognitive performance measures common to both projects. Our findings were replicated in randomly selected 50% splits of TARCC data (Group 1, N = 1,747; Group 2, N = 1,755), and then independently in ADNI (N = 1,737). The new δ homolog, i.e., "dT2A" (d-TARCC to ADNI), fit the data of both studies well, and was strongly correlated with dementia severity, as rated by the Clinical Dementia Rating Scale "sum of boxes" (TARCC: r = 0.99, p < 0.001; ADNI: r = 0.96, p < 0.001). dT2A achieved an area under the receiver operating characteristic curve of 0.981 (0.976-0.985) for the discrimination of Alzheimer's disease from normal controls in TARCC, and 0.988 (0.983-0.993) in ADNI. dT2A is the 12th δ homolog published to date, and opens the door to independent replications across these and similar studies.

Exportation and Validation of Latent Constructs for Dementia Case Finding in a Mexican American Population-based Cohort

BACKGROUND

The latent variable "δ" has been validated as a dementia phenotype. δ can be extracted from Spearman's general intelligence factor "g" in any data set that contains measures of cognition and instrumental activities of daily living (IADL). We used δ composites ("d-scores") to estimate the prevalence of dementia in the Hispanic Established Population for Epidemiological Studies in the Elderly (H-EPESE).

METHOD

δ was constructed from Mini-Mental State Examination, a clock-drawing task (CLOX), and IADL. δ's H-EPESE factor weights were validated in the well-characterized Texas Alzheimer's Research and Care Consortium (TARCC). Optimal thresholds for the discrimination between "Alzheimer's disease" (AD) versus normal controls (NCs) were determined by receiver operating characteristic curve. Those thresholds were used to estimate the prevalence of dementia in H-EPESE.

RESULTS

Each δ homolog fits its source's data well. d-scores were strongly associated with Clinical Dementia Rating scale Sum of Boxes (r = .74-.85, all p < .001], and accurately distinguished AD cases from NCs, in both Mexican Americans (MAs) and non-Hispanic Whites (NHWs) [c = 0.94-0.96]. The TARCC MA threshold estimated the prevalence of dementia at 21.4% in H-EPESE. The NHW threshold estimated the prevalence of dementia at 21.0%.

CONCLUSIONS

It is possible to export δ composites from populations to well-characterized cohorts for validation.

Application of Concordance Probability Estimate to Predict Conversion from Mild Cognitive Impairment to Alzheimer's Disease

Subjects with mild cognitive impairment (MCI) have a substantially increased risk of developing dementia due to Alzheimer's disease (AD). Identifying MCI subjects who have high progression risk to AD is important in clinical management. Existing risk prediction models of AD among MCI subjects generally use either the AUC or Harrell's C-statistic to evaluate predictive accuracy. AUC is aimed at binary outcome and Harrell's C-statistic depends on the unknown censoring distribution. Gönen & Heller's K-index, also known as concordance probability estimate (CPE), is another measure of overall predictive accuracy for Cox proportional hazards (PH) models, which does not depend on censoring distribution. As a comprehensive example, using Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, we built a Cox PH model to predict the conversion from MCI to AD where the prognostic accuracy was evaluated using K-index.

δ scores predict mild cognitive impairment and Alzheimer's disease conversions from nondemented states

INTRODUCTION

We tested the latent variable "δ" (for "dementia")'s ability to predict conversion to "mild cognitive impairment" (MCI) and Alzheimer's disease (AD).

METHODS

An ethnicity equivalent d homolog ("dEQ") was constructed in n = 1113 Mexican- American (MA) and n = 1958 non-Hispanic white (NHW) participants in the Texas Alzheimer's Research and Care Consortium. "Normal Controls" (NC) (n = 1276) and MCI cases (n = 611) were followed annually for up to 6 years [m = 4.7(0.6)].

RESULTS

22.0% (n = 281) of NC converted to "MCI" or "AD". 17.3%( n = 106) of MCI converted to "AD." Independently of covariates, each quintile increase in the dEQ scores of NC increased the odds of conversion by 52%. Each quintile increase in the dEQ scores of MCI cases increased the odds of conversion to AD almost three-fold.

DISCUSSION

Baseline δ scores predict MCI and AD conversions from nondemented states in MA and NHW.

Validation of a Latent Construct for Dementia in a Population-Wide Dataset from Singapore

BACKGROUND

The latent variable δ has been proposed as a proxy for dementia. Previous validation studies have been conducted using convenience samples. It is currently unknown how δ performs in population-wide data.

OBJECTIVE

To validate δ in Singapore using population-wide epidemiological study data on persons aged 60 and above.

METHODS

δ was constructed using items from the Community Screening Instrument for Dementia (CSI'D) and World Health Organization Disability Assessment Schedule (WHODAS II). Confirmatory factor analysis (CFA) was conducted to examine δ model fit. Convergent validity was examined with the Clinical Dementia Rating scale (CDR) and GMS-AGECAT dementia. Divergent validity was examined with GMS-AGECAT depression.

RESULTS

The δ model demonstrated fit to the data, χ2(df) = 249.71(55), p < 0.001, CFI = 0.990, TLI = 0.997, RMSEA = 0.037. Latent variable δ was significantly associated with CDR and GMS-AGECAT dementia (range: β= 0.32 to 0.63), and was not associated with GMS-AGECAT depression. Compared to unadjusted models, δ model fit was poor when adjusted for age, gender, ethnicity, and education.

CONCLUSION

The study found some support for δ as a proxy for dementia in Singapore based on population data. Both convergent and divergent validity were established. In addition, the δ model structure appeared to be influenced by age, gender, ethnicity, and education covariates.

The effectiveness and unique contribution of neuropsychological tests and the δ latent phenotype in the differential diagnosis of dementia in the uniform data set

OBJECTIVE

Two main approaches to the interpretation of cognitive test performance have been utilized for the characterization of disease: evaluating shared variance across tests, as with measures of severity, and evaluating the unique variance across tests, as with pattern and error analysis. Both methods provide necessary information, but the unique contributions of each are rarely considered. This study compares the 2 approaches on their ability to differentially diagnose with accuracy, while controlling for the influence of other relevant demographic and risk variables.

METHOD

Archival data requested from the NACC provided clinical diagnostic groups that were paired to 1 another through a genetic matching procedure. For each diagnostic pairing, 2 separate logistic regression models predicting clinical diagnosis were performed and compared on their predictive ability. The shared variance approach was represented through the latent phenotype δ, which served as the lone predictor in 1 set of models. The unique variance approach was represented through raw score values for the 12 neuropsychological test variables comprising δ, which served as the set of predictors in the second group of models.

RESULTS

Examining the unique patterns of neuropsychological test performance across a battery of tests was the superior method of differentiating between competing diagnoses, and it accounted for 16-30% of the variance in diagnostic decision making.

CONCLUSION

Implications for clinical practice are discussed, including test selection and interpretation. (PsycINFO Database Record

Welcome Back to Your Future: The Assessment of Dementia by the Latent Variable "δ"

The latent variable "δ" (for "dementia") has been proposed as a phenotype for all cause dementia. δ is extracted from cognitive batteries by a specific confirmatory factor analysis in a structural equation modeling framework. δ appears to be uniquely responsible for cognition's association with functional status. Because it is extracted from Spearman's general intelligence factor "g", this has broad implications for dementia's assessment and pathophysiology. This issue of the Journal of Alzheimer's Disease brings together several demonstrations of δ's psychometric properties by investigative groups from three continents. In their aggregate, they suggest that δ homologs may have far ranging applications in dementia's clinical assessment and biomarker selection.

[Neurocognitive disorders in old age : Role of pharmacotherapy in prevention and treatment]

Neurocognitive disorders (e.g. dementia, mild cognitive impairment and delirium) belong to the most frequently occurring problems in older patients. For most types of dementia as well as for mild cognitive impairment no causal pharmacotherapy is currently available. This also applies to delirium, which should be primarily treated through the identification and elimination of predisposing factors while cautiously using symptomatic therapy with psychotropic drugs. Despite intensive ongoing research efforts the search for disease-modifying drugs for the treatment of Alzheimer's dementia has not been successful. In the prevention and treatment of neurocognitive disorders, rational and evidence-based pharmacological interventions can nonetheless play an important role. Besides the limited benefits of symptomatic treatment with currently available anti-dementia drugs, this includes the strict management of medical risk factors as well as the avoidance of drugs with delirogenic and dementing side effects.

Thrombopoietin is associated with δ's intercept, and only in Non-Hispanic Whites

Introduction

Serum thrombopoietin (THPO) is a biomarker of Alzheimer's disease (AD) and the latent dementia phenotype, “δ”. Both associations may be specific to non-Hispanic whites (NHW), not Mexican-Americans (MA). In this analysis, we examine ethnicity's effect on THPO's association with change in δ scores, in the Texas Alzheimer's Research and Care Consortium (TARCC).

Methods

We constructed an ethnicity equivalent δ homolog (“dEQ”) among n = 1113 MA and n = 1958 NHW. dEQ was output as a composite “dEQ-score” for each of five annual TARCC waves. Those composites were used as indicators of a latent growth curve (LGC). The mean dEQ intercept (idEQ) and slope (ΔdEQ) were estimated in a random subset of N = 1528 participants and replicated in the remainder (n = 1544). THPO was regressed onto idEQ and ΔdEQ. Those associations were tested separately in MA and NHW.

Results

dEQ correlated strongly with CDR-SB (r = 0.99, P < .001) and achieved high AUCs for AD diagnosis at each wave (range = 0.95–0.99). THPO was significantly associated with idEQ but not ΔdEQ. That effect was observed in NHW only. In MA, THPO had no associations with either idEQ or ΔdEQ.

Discussion

We confirm THPO's ethnicity-specific association with δ in NHW. It is further clarified that this association is specific to δ's intercept and not its slope. This analysis provides a model for how dementia's specific serum biomarkers can be characterized.

High-throughput metabolomics analysis discovers salivary biomarkers for predicting mild cognitive impairment and Alzheimer's disease

Mild cognitive impairment (MCI) confers an increased risk of developing Alzheimer's disease (AD).