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

Abstract

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.

Using the Alzheimer's Disease Neuroimaging Initiative to improve early detection, diagnosis, and treatment of Alzheimer's disease

“…In two independent cohorts, nine inflammation-associated blood proteins explained ≈10% of the variance in a δ -homolog, dT2A, 105 , 106 constructed from several cognitive measures as a correlate of functional status. 106 Similarly, a panel of CSF AD-associated proteins beyond “classic” CSF biomarkers explained 31% of the variance in Alzheimer’s Disease Assessment Score (ADAS) 11 score compared to 26% explained by CSF A β 42 and t-tau, and was strongly associated with baseline cognition, diagnosis, and cognitive decline. 107 The two sets of biomarkers were largely independent, together explaining 41% of the ADAS11 variance ( Figure S14 in supporting information ).…”

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

“…Another limitation is that TARCC’s biomarkers (at least) are associated with batch effects. We can account for that by the introduction of a BIAS construct in SEM [62], but this approach is conducted outside of SEM (which cannot handle ROC analysis). Similarly, we cannot use a BIAS construct to account for differences in the biofluids in which the biomarker is assessed.…”

APOE Gene Associated with Dementia-Related Traits, Depression, and Anxiety in the Hispanic Population

“…The 2nd set of data was collected from the TARCC, an ethnically diverse convenience sample with annual longitudinal follow-up described in detail in [47][48][49]. TARCC is a longitudinally followed convenience sample of elderly persons diagnosed with AD, MCI, or control subjects recruited from five Texas medical schools.…”

“…The diagnoses of AD, MCI, depression, or anxiety for ISLD-RGV were based on self-reports; however, the diagnoses of AD, MCI, depression, or anxiety for the TARCC data were based on the National Institute for Neurological Communicative Disorders and Stroke-Alzheimer's Disease and Related Disorders Association criteria for AD [51] and site-specific consensus-based clinical diagnoses derived from all available information but without reliance on specific neurocognitive tests and/or cut scores [48,49]. Both databases' demographic information was based on self-reported age, gender, education, ethnicity, and self-explanatory information.…”