The histopathological staging of tau, but not amyloid, corresponds to antemortem cognitive status, dementia stage, functional abilities and neuropsychiatric symptoms

Abstract

Purpose

Alzheimer’s disease (AD) is characterised by two cardinal pathologies, namely the extracellular accumulation amyloid-related aggregates, and the intracellular formation of tau-related neurofibrillary tangles (NFTs). While both pathologies disrupt cognitive function, a large body of evidence suggests that tau-pathology has a stronger relationship with the clinical manifestation of the disease compared to amyloid. Given the ordinal nature of histopathological staging systems, however, it is possible that the effect of amyloid pathology has been underestimated in clinicopathological studies.

Methods

We investigated this possibility using data from the National Alzheimer’s Coordinating Center (NACC) database, which contains data from patients in the United States of America. Bayesian ordinal models were used to directly investigate the relative contribution of Braak NFT, diffuse plaque, and neuritic plaque staging to the severity of antemortem clinical impairment.

Results

Data from 144 participants were included in the final analysis. Bayesian ordinal models revealed that Braak NFT stage was the only predictor of global cognitive status, clinical dementia stage, functional abilities, and neuropsychiatric symptoms. When compared directly, Braak NFT stage was a stronger predictor than diffuse or neuritic plaques across these domains.

Conclusions

These findings confirm that tau-related pathology is more strongly related to clinical status than amyloid pathology. This suggests that conventional clinical markers of disease progression might be insensitive to amyloid-pathology, and hence might be inappropriate for use as outcome measures in therapeutic trials that directly target amyloid.

Keywords:

• Histopathology
• tau
• amyloid
• neurofibrillary tangles
• plaques
• dementia
• cognition

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The NACC database is funded by NIA/NIH Grant U01 AG016976. NACC data are contributed by the NIA-funded ADCs: P30 AG019610 (PI Eric Reiman, MD), P30 AG013846 (PI Neil Kowall, MD), P50 AG008702 (PI Scott Small, MD), P50 AG025688 (PI Allan Levey, MD, PhD), P50 AG047266 (PI Todd Golde, MD, PhD), P30 AG010133 (PI Andrew Saykin, PsyD), P50 AG005146 (PI Marilyn Albert, PhD), P50 AG005134 (PI Bradley Hyman, MD, PhD), P50 AG016574 (PI Ronald Petersen, MD, PhD), P50 AG005138 (PI Mary Sano, PhD), P30 AG008051 (PI Thomas Wisniewski, MD), P30 AG013854 (PI M. Marsel Mesulam, MD), P30 AG008017 (PI Jeffrey Kaye, MD), P30 AG010161 (PI David Bennett, MD), P50 AG047366 (PI Victor Henderson, MD, MS), P30 AG010129 (PI Charles DeCarli, MD), P50 AG016573 (PI Frank LaFerla, PhD), P50 AG005131 (PI James Brewer, MD, PhD), P50 AG023501 (PI Bruce Miller, MD), P30 AG035982 (PI Russell Swerdlow, MD), P30 AG028383 (PI Linda Van Eldik, PhD), P30 AG053760 (PI Henry Paulson, MD, PhD), P30 AG010124 (PI John Trojanowski, MD, PhD), P50 AG005133 (PI Oscar Lopez, MD), P50 AG005142 (PI Helena Chui, MD), P30 AG012300 (PI Roger Rosenberg, MD), P30 AG049638 (PI Suzanne Craft, PhD), P50 AG005136 (PI Thomas Grabowski, MD), P50 AG033514 (PI Sanjay Asthana, MD, FRCP), P50 AG005681 (PI John Morris, MD), P50 AG047270 (PI Stephen Strittmatter, MD, PhD).