Over the past 10 years, the attraction of proteomic approaches for the neurochemical diagnosis of neurodegenerative disorders has increased enormously. Neurodegenerative disorders are characterized by progressive neuronal decay, producing a broad spectrum of clinical syndromes. The underlying disease has no cure and its course is usually fatal. Alzheimer’s disease (AD) is the most common cause for neurodegeneration and consecutive dementia syndrome. Current advances in therapeutic research raise the hope for forthcoming disease-modifying concepts in AD therapy Citation[1]. The probable diagnosis of neurodegenerative disorders is mainly based on clinical criteria, while definite diagnosis can only be made by neuropathological examination. The neuropathological hallmarks of AD are senile plaques and neurofibrillar tangles Citation[2]. Since their first microscopic description, proteomic analyses from post-mortem brain tissue have increasingly clarified the molecular composition of these neuropathological structures: aggregated forms of amyloid-β peptides and tau-protein form senile plaques and neurofibrillar tangles, respectively Citation[3,4].
Proteomics is a rapidly expanding field of research, which aims to characterize the protein expression in biological fluids and tissues under certain conditions. Protein expression is a very dynamic process that, in contrast to the genome, may change profoundly during disease conditions. This provides the unique opportunity to detect and track a disease using altered expression patterns of proteins that are involved in pathogenic mechanisms of the disease. By contrast, expressional changes of certain proteins during clinical disease conditions may indicate their role in pathogenesis. However, the variability of the proteome often makes it difficult to define the standard in relation to ‘normal’.
The results of proteomics depend on disease status, the biomaterial examined and the methods applied. In order to detect and characterize as many proteins as possible, proteomics uses a variety of methods, the most important of which are:
| • | 2D gel electrophoresis: this allows the separation of proteins according to their isoelectric point and molecular radius in the first and second dimension, respectively; | ||||
| • | Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry analysis: this uses physico–chemical or immunological enrichment of antigens on specially prepared chips prior to a matrix-assisted laser desorption/ionization time-of-flight mass spectroscopy; | ||||
| • | 2D gel electrophoresis coupled with mass spectrometry: this allows detailed mass information about electrophoretically allocated spots to be obtained. | ||||
The weakness of all of these methods is to reproducibly quantify the antigen’s concentration. Moreover, they are highly time-consuming, require specially trained personnel or apparatus and are fairly expensive. Thus, their application for high-throughput screening purposes in routine diagnostics is limited, and appropriate quantification of well-characterized antigens usually employs immunological methods, such as ELISA, electrochemiluminescence or multiplexing assay formats. The latter allows the simultaneous quantification of up to 100 analytes in a minute volume of a single sample.
To date, proteomic approaches have worked well for AD. From when Alois Alzheimer first described the neuropathological features of the disease, it took decades to unravel the major molecular components of senile plaques and neurofibrillar tangles, respectively Citation[3,4]. This was followed by the search for Aβ peptides and tau protein in biological fluids, and major breakthroughs included the measurement of elevated tau and its phosphorylated forms (p-tau), as well as decreased Aβ peptides, ending at amino acid 42 (Aβ42) in cerebrospinal fluid (CSF) of AD patients Citation[5–7]. In 1998, a consensus paper stated that an applicable biomarker test in AD should be precise, reliable, inexpensive and noninvasive. Moreover, it should be validated in neuropathologically confirmed cases and detect a fundamental feature of AD pathology. The test should detect AD with a minimum sensitivity of 80% and provide a reasonable specificity for exclusion of other neurodegenerative disorders, commonly understood as a figure of 75–85% Citation[8].
To date, various independent studies have confirmed characteristic derangements of elevated tau and p-tau, accompanied by decreased Aβ42 levels in the CSF of AD sufferers. Accordingly, these have been quoted as a supportive feature for AD diagnosis in the latest proposal for AD clinical criteria Citation[9]. The majority of studies, where patients without dementia or mentally healthy controls (controls) were investigated in comparison to AD, reported accuracies of 80% or more. Otherwise, the specificity for AD of each biomarker considerably declined in comparison with other neurodegenerative diseases, especially dementias Citation[10]. Various combinations of biomarkers have been suggested by different groups to improve the accuracy of each biomarker alone: tau × Aβ40/Aβ42 – the AD index Citation[11], Aβ1–42/tau Citation[12] or Aβ1–42/p-tau Citation[13], Aβ40/Aβ42 Citation[14]. In most studies, the investigated combinations gave higher contrasts than each biomarker alone, but the statistical significance of their findings has rarely been assessed by the authors. Using urea-based SDS-PAGE with immunoblotting (Aβ-SDS-PAGE/immunoblot), we were able to reveal a regular pattern of Aβ peptides 1–37, 1–38, 1–39, 1–40, 1–40ox and 1–42 in CSF Citation[15,16]. Most interestingly, we observed disease-specific derangements, particularly in the relative abundances of these peptide species for controls, AD and other neurodegenerative dementias; for example, dementia with Lewy bodies and frontotemproral dementias Citation[15–19]. The disease-specific pattern information was clearly superior to the measurement of a single peptide’s concentration: low percentages of CSF Aβ1–38 and Aβ1–42 were indicative of frontotemproral dementias and AD, respectively, whilst a high percentage of Aβ1–40ox was characteristic for dementia with Lewy bodies Citation[19].
However, these investigations have been carried out using the CSF of demented patients; that is, at a time point when the disease was clinically overt. The subclinical course of neurodegenerative disorders probably precedes their clinical manifestation for decades, which calls for preclinical diagnostics to initiate an adequate preventive therapy. Therefore, it is notable that a growing body of evidence indicates the usefulness of CSF biomarkers for predicting AD in prodromal states, such as mild cognitive impairment. As for differential dementia diagnostics, combining biomarkers seems to enhance the accuracy of AD prediction Citation[20–22]. Multiplex assay formats make multiparametric biomarker assessment applicable in routine dementia diagnostics and may potentially replace ELISA in the future Citation[21].
While all these achievements have been established for CSF-based neurochemical diagnosis of AD, the inconvenience of lumbar puncture and its potential hazards for the patient alternatively call for blood-based biomarkers. To our excitement, recent publications have reported promising results on the usefulness of plasma Aβ peptides in early and differential diagnosis of dementias Citation[23,24]. Most recently, Ray et al. (2007) reported a set of 18 signaling proteins in plasma that identified discriminated controls from patients with mild cognitive impairment, who converted to AD during a 2–6-year follow-up period. These proteins were functionally involved in systemic regulation of hematopoiesis, immune responses, apoptosis and neuronal support Citation[25].
Despite the enormous progression in the field and the promising results of recent biomarker studies, ongoing research is required in order to create a biomarker that completely satisfies the requirements of the 1998 paper. Although lumbar puncture can be considered a low-risk procedure, it is still invasive. Moreover, we are still missing validated biomarkers for the antecedent AD diagnosis, especially in comparison to preclinical or prodromal states of other neurodegenerative disorders. Standardizing the currently available CSF biomarkers is on the way, but establishing and consequently fulfilling one sample handling protocol is challenging Citation[26]. In a recent international survey study, we observed inter-laboratory coefficients of variation of biomarkers in the range of 20–30%, clearly indicating the necessity of further optimization Citation[27].
In blood, obtained by less invasive venous puncture, most results have not yet been reproduced by independent groups and validation of biomarkers in neuropathologically confirmed cases is still lacking. Consequently, one could only speculate on test precision and the reliability of results.
It is neither clear in CSF nor in blood, whether the ideal diagnostic biomarker may also serve for tracking the disease during its course and eventual response to hopefully forthcoming causal treatment.
Thus, the track record of AD impressively demonstrates how proteomics may successfully work in the diagnosis of neurodegenerative disorders, but still displays vast areas terra incognita. An apparatus that can analyze any panel of human proteins in a minimally invasive manner and comparatively screen a huge database of different protein spots, each specific for a certain disease process and all well characterized (including mass, protein sequence and reference concentrations for various human specimens) is desirable. The pattern of up- and downregulated proteins, respectively, would lead us to the underlying pathomechanisms of symptoms and thus to the correct diagnosis and adequate treatment of the patient. In addition, repeated measurements will enable optimal monitoring of the disease process and its response to treatment.
Many components of this proteomic apparatus already exist and technology advances towards linking stand-alone methods (e.g., 2D gel electrophoresis with mass spectrometry). In large and specialized proteome centers, many technical achievements in proteomics are occuring and proteins of interest may be quantified by multiplexing assays after full chemical characterization.
What we are missing most urgently is the previously mentioned database, where reference values of fully characterized proteins are laid down, ready to scan. This is easily said, but the conditions for such databases are hard to achieve:
| • | Acquirement of biomaterials will have to comply with unifying standards, probably individually set up for each protein and biomaterial, respectively; | ||||
| • | Reference values for different human specimens require biomaterial from hundreds of healthy volunteers; | ||||
| • | Measurements of values will have to periodically undergo quality surveys; | ||||
| • | Reference values will probably have to be adapted for potential confounders, such as age, sex, fasting state, diet and circadian rhythms; | ||||
| • | If the concentration of one specific protein is not pathognomonic for a single disease, a whole pattern of different protein concentrations will have to be determined for each neurodegenerative disease; | ||||
| • | Patient groups will have to be finely selected following clinical criteria and neuropathological confirmation. | ||||
Financial & competing interests disclosure
This contribution was supported by the following grants from the German Federal Ministry of Education and Research (BMBF): Kompetenznetz Demenzen (01 GI 0420), HBPP-NGFN2 (01 GR 0447), the Forschungsnetz der Früh- und Differenzialdiagnose der Creutzfeldt-Jakob-Krankheit und der neuen Variante der CJK (01 GI 0301), the EU grants cNEUPRO (contract no. LSHM-CT-2007–037950) and neuroTAS (contract no. LSHB-CT-2006- 037953). The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.
No writing assistance was utilized in the production of this manuscript.
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