New perspectives in the search for reliable biomarkers in alzheimer disease

Background and Objectives: The search for accurate biomarkers in Alzheimer Disease (AD), on of the most devastating neurodegenerative diseases, remains essential to enable an early prognosis and diagnosis of the disease and to provide more efficient therapeutic strategies. A wide variety of potential biomarkers are has been identified by neuroimaging techniques and by the analysis of fluid samples, such as cerebrospinal fluid (CSF) or blood. Recently, a growing number of studies are focused on the discovery of reliable bloodbased biomarkers in blood, especially in the prodromal stage of AD, which can predict the conversion of asymptomatic cases to AD demented cases. In this review, the latest challenges in the search for accurate biomarkers of AD is revised, in particular, an update in blood-based biomarkers is described in depth. Conclusions: Finally, the close link among AD and other neurodegenerative diseases is discussed, mainly based on the last discovered mutation, the chromosome 9 open reading frame 72, C9ORF72. Received: 16 January 2015 Revised: 18 February 2015 Accepted: 19 February 2015 52 LAURA MORENO ET AL. Challenges in the discovery of potential biomarkers in Alzheimer Disease To date there are no effective therapies to preserve normal brain function in potential future Alzheimer’s disease (AD) patients. The absence of reliable biomarkers to identify cognitive normal individuals that will become early-stage AD patients support this fact. Therefore, this overlap between demented and non-demented population has limited the diagnostic accuracy of the current known biomarkers for AD. Due to the fact that neurological processes that finally result in dementia are assumed to be actively long before the first symptoms appear, the availability of diagnostic biomarkers could make a preclinical diagnostic testing and an early treatment of AD possible. A great variety of biomarkers of AD has been described using different approaches (Table 1). As Figure 1 shows, different strategies can be studied along AD progression for a better understanding of the disease and to enable an accurate identification of potential AD biomarkers. Currently, the most studied methods to identify markers of mild cognitive impairment (MCI) and AD are neuroimaging and molecular techniques based on cerebrospinal fluid (CSF). A systematic search on PubMed and Scopus databases was performed to find the most relevant studies and review papers. The key words used for this purpose were: “Alzheimer’s disease”, “Mild Cognitive Impairment”, “biomarkers”, “blood”, “neuroimaging” and “neurodegenerative diseases” in various combinations. The articles selected were published in English from 2004 to 2015. Neuroimaging is a non-invasive technique which monitors brain regions and allows the subsequent identification and quantification of diagnostic and candidate biomarkers of dementia progression1. Magnetic resonance imaging (MRI) is the most widely used neuroimaging technique to investigate brain changes and neurodegeneration. Several longitudinal studies using MRI have been conducted with positive results2,3. After followup assessments, these studies supported that MRI is a valuable biomarker to predict early conversion to dementia in patients with MCI. In particular, a maximum value of 1.61 for the occipital cortex N-acetylaspartate / creatine ratio was useful to predict dementia at 100% sensitivity and 75% specificity, yielding a positive predictive value of 83% and a negative predictive value of 100%2. The same ratio in the posteromedial bilateral parietal cortex could enable a predicted conversion rate to probable AD with a sensitivity of 74.1% and a specificity of 83.7%3. Furthermore, MRI is capable of measuring both regional and global brain atrophy, determining the extent of the brain degeneration in patients with dementia4,5. Based on this, several groups have proposed the rate of hippocampal atrophy in MCI patients as a predictor for the conversion to AD6,7. Other measurements by MRI, like cortical thickness, have been performed in amnestic MCI (aMCI) patients, which have the highest conversion rate to AD8. However, these measurements alone could not distinguish among aMCI subtypes and controls. White matter (WM) and grey matter (GM) have also been studied using MRI, which showed lower volumes of WM and GM in different brain regions in MCI patients who converted to AD9. A more sensitive to microscope WM changes technique is diffusion tension imaging (DTI). Nir et al. (2013) showed widespread diffusivity disruptions associated with neuropsychological and cognitive deficits in specific tracts that passed through the temporal lobe and posterior brain regions in AD and MCI patients10. Despite MRI is widely used for AD, the accuracy of MRI as biomarker of early AD generally reaches an accuracy of 80%11, what encourages the search of better biomarkers and more accurate diagnostic tools. Several studies demonstrated that the accuracy to predict conversion from MCI to AD in MRI was enhanced when combined with positron emission tomography (PET)12,13, where the best brain region for MRI and PET was the temporal cortex13. Currently, PET is one of the most sensitive tests for and early AD detection comparing to other biomarkers, such as CSF measures of Aβ-42 or Aβ-42/tau14,15. However, its high cost hampers its regular clinical use. PET can determine the presence or activity of proteins, enzymes and metabolic pathways involved in dementia16, and it has been used for prediction of progression from MCI to AD showing promising results. Particularly, 11CPittsburgh compound B positron emission tomography (11C-PIB-PET) may play a role in stratifying patients with MCI into risk levels for developing AD, yielding a 83.3% to 100% sensitivity and a 41.1% to 100% specificity for predicting conversion to AD17. In addition, in a recent study, fluorodeoxyglucose PET (FDG-PET) images were used to investigate MCI to AD conversion at different prodromal stages18. The results showed that MCI to AD conversion can be predicted as early as 24 months prior to conversion. Another molecular imaging technique suggested as a predictor of conversion to dementia is proton magnetic resonance spectroscopy (1HMRS)19. In particular, five metabolite ratios were calculated in four different brain regions in MCI patients, but only mI/CR ratio RELIABLE BIOMARKERS IN MCI AND AD 53 Figure 1. Overview of the main categories of biomarkers that can be identified along AD progression. Biomarkers of exposure can be indicative of disease risk factors, while biomarkers of disease are useful in the screening (prognostic biomarkers), in the early stages of the disease (diagnostic biomarkers) and in the monitoring of disease progression. 54 LAURA MORENO ET AL. U se fu l b io m ar ke rs a nd te ch ni qu es fo r e ar ly R el ev an t f in di ng s Pr ed ic tiv e ca pa ci ty fo r A D a nd M C I de te ct io n of A D a nd M C I N eu ro im ag in g te ch ni qu es M ag ne tic re so na nc e im ag in g (M R I) D iff us io n te ns io n im ag in g (D TI ) po si tro n em is si on to m og ra ph y (P ET ) a nd M R I 11 C -P itt sb ur gh c om po un d B p os itr on e m is si on to m og ra ph y (1 1C -P IB -P ET ) flu or od eo xy gl uc os e PE T (F D G -P ET ) pr ot on m ag ne tic re so na nc e sp ec tro sc op y (1 H -M R S) C SF b io m ar ke rs am yl oi d β pe pt id e 42 (A β42 )