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  • Review Article
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Biomarkers of neurodegeneration for diagnosis and monitoring therapeutics

Key Points

  • A major impediment to the conduct of cost-effective and informative clinical trials of potential disease-modifying therapies for neurodegenerative disorders such as Alzheimer's disease (AD) is the absence of robust biomarkers for the early diagnosis of these disorders and for monitoring patient responses to new therapeutic interventions.

  • The complexity of neurodegenerative diseases, a number of which overlap, further adds to the challenge of identifying appropriate biomarkers.

  • Driven in part by drug discovery research, AD is at the forefront of biomarker development for neurodegenerative diseases, and many current concepts about ideal biomarkers for these disorders have come from AD research.

  • Ideal AD biomarkers should be: linked to fundamental features of AD neuropathology; validated in neuropathologically confirmed AD cases; able to detect AD early in its course and distinguish it from other dementias; reliable; non-invasive; simple to use; and inexpensive.

  • On the basis of extensive studies to date on potential AD biomarkers, it is highly likely that a combination of biomarkers will provide greater diagnostic accuracy than any single analyte.

  • A number of candidate AD biomarkers have emerged during the past decade Isoprostanes, tau, Aβ, sulphatides and homocysteine are among the most promising AD biomarker candidates, but there are also other potential AD biomarkers, such as Aβ precursor proteins, apolipoprotein E (APOE), 8-hydroxy-2′-deoxyguanosine, α1-antichymotrypsin, interleukin-6 (IL-6) and IL-6 receptor complex proteins, C-reactive protein, and C1q protein.

  • There is reason to be optimistic that a validated panel of AD biomarkers will be the outcome of the Alzheimer's Disease Neuroimaging Initiative and other research programmes. The successful accomplishment of this goal will enable the reliable diagnosis of AD in its early stages or even in its prodromal stages, as well as provide tests for reliably distinguishing AD from other forms of dementia.

Abstract

Rapid progress towards understanding the molecular underpinnings of neurodegenerative disorders such as Alzheimer's disease is revolutionizing drug discovery for these conditions. Furthermore, the development of models for these disorders is accelerating efforts to translate insights related to neurodegenerative mechanisms into disease-modifying therapies. However, there is an urgent need for biomarkers to diagnose neurodegenerative disorders early in their course, when therapy is likely to be most effective, and to monitor responses of patients to new therapies. As research related to this need is currently most advanced for Alzheimer's disease, this Review focuses on progress in the development and validation of biomarkers to improve the diagnosis and treatment of Alzheimer's disease and related disorders.

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Figure 1: Proposed mechanisms underlying Alzheimer's disease.
Figure 2: An algorithm for the neuropathological diagnosis of patients with clinical frontotemporal dementia.
Figure 3: An algorithm for the neuropathological diagnosis of sporadic or familial neurodegenerative movement disorders including Parkinson's disease, Parkinson's disease with dementia and dementia with Lewy bodies.
Figure 4: Possible targets for therapeutic intervention in A β and tau metabolic pathways.
Figure 5: Hypothetical timeline for the onset and progression of sporadic as well as familial AD neurodegeneration and dementia.

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Acknowledgements

We thank M. Leonard for expert graphics and our colleagues for their contributions to the work summarized here, which has been supported by grants from the US National Institutes of Health, and the Marian S. Ware Alzheimer Program. Last, we are indebted to our patients and their families whose commitment to research has made our work possible.

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Correspondence to Leslie M. Shaw or John Q. Trojanowski.

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Diagnostic performance of laboratory tests for AD (PDF 143 kb)

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DATABASES

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Glossary

Biomarker

A characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes or pharmacological responses to a therapeutic intervention.

Sensitivity

In this case, a sensitivity of 100% indicates that a diagnostic test identifies all patients with AD.

Specificity

In this case, a test with 100% specificity identifies all individuals free of AD.

Prior probability

The background prevalence of the disease in the population tested.

Positive predictive value

The positive predictive value of an AD biomarker refers to the percentage of people who are positive for the biomarker and have definite AD at autopsy. A positive predictive value of 100% indicates that all patients with a positive test have the disease.

Negative predictive value

The percentage of people with a negative test who, at autopsy, prove not to have the disease. A negative predictive value of 100% indicates that the test completely rules out the possibility that the individual has the disease when the test is performed.

ELISA

Enzyme-linked immunosorbant assay. An immunochemical technique using antibodies to detect and quantify the presence of an antigen in a sample.

APOE4

Apolipoprotein E4 allele. The susceptibility gene variant that is the most robust genetic risk factor for common, late-onset AD.

Autosomal dominant

In this context, autosomal dominant refers to mutations (that is, changes in a gene) that are sufficient to cause disease when a single copy of the gene is affected by the mutation, and it is inherited by an individual who will develop the disease if he/she lives to the age of onset of the disease.

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Shaw, L., Korecka, M., Clark, C. et al. Biomarkers of neurodegeneration for diagnosis and monitoring therapeutics. Nat Rev Drug Discov 6, 295–303 (2007). https://doi.org/10.1038/nrd2176

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