Alzheimer's Disease: Using Proteomics to Discover Synaptic Biomarkers

Dementias, including Alzheimer’s disease (AD), are a serious cause of concern for both members of the aging population and the medical community. Fortunately, the discovery and application of sensitive, specific biomarkers readily available in the cerebrospinal fluid of affected individuals could offer early diagnosis and opportunities to understand the root cause of AD.

Jahn et al.¹ used cerebrospinal fluid samples from 159 individuals. These samples included 17 cognitively healthy controls, 34 samples from patients already diagnosed with sporadic AD, 12 samples from patients with frontotemporal dementia (FTD), 13 samples from patients with schizophrenia, and 100 samples from patients with undiagnosed memory complaints. The researchers used capillary electrophoresis coupled with electrospray ionization time-of-flight mass spectrometry (CE-MS) and tandem MS/MS sequencing (Thermo Scientific) to analyze low-molecular-weight peptides and protein fragments in cerebrospinal fluid. This is a method that has already demonstrated success in many clinical areas, including the diagnoses of renal disease, prostate/urothelial cancer, ureteropelvic junction obstruction, and renal transplant rejection.

Using CE-MS, the researchers identified 1,104 low-molecular-weight peptides. After statistically analyzing the diagnostic value of all potential biomarkers, Jahn et al.¹ whittled the 131 potential biomarkers to 35 and then used leave-one-out cross-validation to refine the set of biomarkers into a usable diagnostic pattern based on 12 discriminatory peptides. This AD pattern correctly classified AD and control samples with a sensitivity of 91 percent and a specificity of 88 percent.

Next, the researchers applied this pattern to the 100 samples derived from patients with undiagnosed memory complaints. These patients had multiple neurodegenerative disorders, including mild cognitive impairment (MCI), vascular dementia, Parkinson’s dementia, FTD, depression, and other dementia syndromes. The researchers used a hierarchical model to test for biomarker patterns for AD, FTD, and schizophrenia, followed by differential diagnostic patterns when a sample scored positive for more than one disease pattern. In this way, Jahn et al.¹ achieved a sensitivity of 87 percent and a specificity of 83 percent for AD diagnosis compared to a sensitivity of 88 percent and a specificity of 67 percent when using traditional measurements of beta-amyloid1-42, total-tau, and phospho¹⁸¹-tau. Thus, the sensitivity and specificity available from the use of peptide patterns for AD diagnosis was in the same range that the three traditional measurements accomplish when combined.

Researchers were also able to identify samples of MCI patients who demonstrated an AD pattern and, by following these patients for 41 to 72 months, found that those MCI patients with a positive AD pattern had a higher conversion rate to AD than did their counterparts who were negative for the AD pattern. Another observation made by Jahn et al.¹ was an overlap in FTD and AD diagnosis, which may be useful for the treatment of FTD using AD treatment standards.

Specifically, Jahn et al.¹ identified five of the 12 peptides used in the AD panel: a neurosecretory protein VGF, phospholemman (FXYD1), glycoprotein Clusterin (apolipoprotein J), prohormone Chromagranin A, and prohormone proSAAS. It is interesting to note that these identified biomarkers are mostly synaptic in origin and generally involved in vesicular transport and synaptic neuropeptide processing. These findings may provide the opportunity for early diagnosis of AD through synaptic biomarkers, as well as provide a vehicle for the monitoring the synaptic-level effects of AD treatments.

References

1. Jahn, H., et al. (2011) ‘Peptide fingerprinting of Alzheimer’s disease in cerebrospinal fluid: Identification and prospective evaluation of new synaptic biomarkers‘, Public Library of Science One, 6 (10), (p. e26540)