4.7 Review

Knowledge gaps in Alzheimer's disease immune biomarker research

Journal

ALZHEIMERS & DEMENTIA
Volume 17, Issue 12, Pages 2030-2042

Publisher

WILEY
DOI: 10.1002/alz.12342

Keywords

Alzheimer' s disease; biomarkers; immunity; natural selection; plasma; protease inhibitors; spinal fluid

Funding

  1. National Institutes of Health [R01 AG 051500, R56 AG058234, R44 AG058330, R01 AG062217, R01 AG051674, U01 AG06786, R01 AG049704, P30 AG062677]
  2. Spectrum-MSU Alliance

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Considerable evidence implicates immune mechanisms in Alzheimer's disease pathology moderation. However, questions about therapeutic targets, manipulation directions, and treatment timing remain unanswered. Knowledge gaps include the relationship between biomarker changes and biology, the role of pathological stage group differences in reflecting response to pathology versus individual trait differences, the predictive value of biomarker levels for subsequent pathology and cognition changes, and the causal relationship between immune biomarker differences and pathology.
Considerable evidence has accumulated implicating a role for immune mechanisms in moderating the pathology in Alzheimer's disease dementia. However, the appropriate therapeutic target, the appropriate direction of manipulation, and the stage of disease at which to begin treatment remain unanswered questions. Part of the challenge derives from the absence of any selective pressure to develop a coordinated beneficial immune response to severe neural injury in adults. Thus, immune responses to the prevailing stimuli are likely to contain both beneficial and detrimental components. Knowledge gaps include: (1) how a biomarker change relates to the underlying biology, (2) the degree to which pathological stage group differences reflect a response to pathology versus trait differences among individuals regulating risk of developing pathology, (3) the degree to which biomarker levels are predictive of subsequent changes in pathology and/or cognition, and (4) experimental manipulations in model systems to determine whether differences in immune biomarkers are causally related to pathology.

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