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

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.

Aptamer-Based Proteomics Measuring Preoperative Cerebrospinal Fluid Protein Alterations Associated with Postoperative Delirium

Delirium is a common postoperative complication among older patients with many adverse outcomes. Due to a lack of validated biomarkers, prediction and monitoring of delirium by biological testing is not currently feasible. Circulating proteins in cerebrospinal fluid (CSF) may reflect biological processes causing delirium. Our goal was to discover and investigate candidate protein biomarkers in preoperative CSF that were associated with the development of postoperative delirium in older surgical patients. We employed a nested case-control study design coupled with high multiplex affinity proteomics analysis to measure 1305 proteins in preoperative CSF. Twenty-four matched delirium cases and non-delirium controls were selected from the Healthier Postoperative Recovery (HiPOR) cohort, and the associations between preoperative protein levels and postoperative delirium were assessed using t-test statistics with further analysis by systems biology to elucidate delirium pathophysiology. Proteomics analysis identified 32 proteins in preoperative CSF that significantly associate with delirium (t-test p < 0.05). Due to the limited sample size, these proteins did not remain significant by multiple hypothesis testing using the Benjamini-Hochberg correction and q-value method. Three algorithms were applied to separate delirium cases from non-delirium controls. Hierarchical clustering classified 40/48 case-control samples correctly, and principal components analysis separated 43/48. The receiver operating characteristic curve yielded an area under the curve [95% confidence interval] of 0.91 [0.80-0.97]. Systems biology analysis identified several key pathways associated with risk of delirium: inflammation, immune cell migration, apoptosis, angiogenesis, synaptic depression and neuronal cell death. Proteomics analysis of preoperative CSF identified 32 proteins that might discriminate individuals who subsequently develop postoperative delirium from matched control samples. These proteins are potential candidate biomarkers for delirium and may play a role in its pathophysiology.

Multiple Adipokines Predict Dementia Severity as Measured by δ: Replication Across Biofluids and Cohorts

BACKGROUND

We have explored dementia's blood-based protein biomarkers in the Texas Alzheimer's Research and Care Consortium (TARCC) study. Among them are adipokines, i.e., proteins secreted by adipose tissue some of which have been associated with cognitive impairment.

OBJECTIVE

To associate adipokines with dementia severity and replicate their association across cohorts and biofluids (serum /plasma).

METHODS

We used eight rationally chosen blood-based protein biomarkers as indicators of a latent variable, i.e., "Adipokines". We then associated that construct with dementia severity as measured by the latent dementia-specific phenotype "δ" in structural equation models (SEM). Significant factor loadings and Adipokines' association with δ were replicated across biofluids in the Alzheimer's Disease Neuroimaging Initiative (ADNI).

RESULTS

Eight adipokine proteins loaded significantly on the Adipokines construct. Adipokines measured in plasma (ADNI) or serum (TARCC) explained 24 and 70% of δ's variance, respectively. An Adipokine composite score, derived from the latent variables, rose significantly across clinical diagnoses and achieved high areas under the receiver operating characteristic curve (ROC/AUC) for discrimination of Alzheimer's disease from normal controls (NC) or cases of mild cognitive impairment (MCI) and between NC and MCI.

CONCLUSION

These results again suggest that SEM can be used to create latent biomarker classifiers that replicate across samples and biofluids, and that a substantial fraction of dementia's variance is attributable to peripheral blood-based protein levels via the patterns codified in those latent constructs.

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.

Blood-based protein mediators of senility with replications across biofluids and cohorts

Dementia severity can be quantitatively described by the latent dementia phenotype 'δ' and its various composite 'homologues'. We have explored δ's blood-based protein biomarkers in the Texas Alzheimer's Research and Care Consortium. However, it would be convenient to replicate them in the Alzheimer's Disease Neuroimaging Initiative. To that end, we have engineered a δ homologue from the observed cognitive performance measures common to both projects [i.e. 'd:Texas Alzheimer's Research and Care Consortium to Alzheimer's Disease Neuroimaging Initiative' (dT2A)]. In this analysis, we confirm 13/22 serum proteins as partial mediators of age's effect on dementia severity as measured by dT2A in the Texas Alzheimer's Research and Care Consortium and then replicate 4/13 in the Alzheimer's Disease Neuroimaging Initiative's plasma data. The replicated mediators of age-specific effects on dementia severity are adiponectin, follicle-stimulating hormone, pancreatic polypeptide and resistin. In their aggregate, the 13 confirmed age-specific mediators suggest that 'cognitive frailty' pays a role in dementia severity as measured by δ. We provide both discriminant and concordant support for that hypothesis. Weight, calculated low-density lipoprotein and body mass index are partial mediators of age's effect in the Texas Alzheimer's Research and Care Consortium. Biomarkers related to other disease processes (e.g. cerebrospinal fluid Alzheimer's disease-specific biomarkers in the Alzheimer's Disease Neuroimaging Initiative) are not. It now appears that dementia severity is the sum of multiple independent processes impacting δ. Each may have a unique set of mediating biomarkers. Age's unique effect appears to be at least partially mediated through proteins related to frailty. Age-specific mediation effects can be replicated across cohorts and biofluids. These proteins may offer targets for the remediation of age-specific cognitive decline (aka 'senility'), help distinguish it from other determinants of dementia severity and/or provide clues to the biology of Aging Proper.