Electroencephalographic Patterns as Biomarkers
Introduction
There has been systematic graduation in the laboratory tests from laboratories to clinics seeking to guide diagnosis, treatment as well as monitoring in the response and treatment of neurodegenerative conditions such as dementia, Alzheimer’s disease (AD), bipolar disorder (BD) and schizophrenia (SZ). Over centuries, psychiatrists have strived to improve on the conventional tools of neuroscience, that is, the microscope, clinical observation, and experimentation during that time. It is imperative to point at the spectacular advances in the past century that have occurred in the genomics, neuroscience, and the pharmacology fields. Careful techniques of interview and behavioral observation are widely employed by clinicians in making inferences regarding the inner experiences of the patients, and making further deductions regarding the impacts on their neural systems (Morris et al. 777). It is however, worth noting that there has been little refining of indirect assessments for the treatment and diagnosis of neurodegenerative conditions over past two centuries.
Traditional biomarkers
The traditional biomarkers used in the cognitive testing in mentally ill patients, for instance, patients suffering from dementia and Alzheimer’s disease (AD) were not effective in the prompt diagnosis and treatment for such conditions (Figley and Stroman 580). They were main antecedent, which was, aimed at predicting the likelihood of an individual developing the disease (Kuntner et al. 238). The mini mental examination of a mental state was not able to enhance reliable identification of prodromal stages and present valued prognosis.
The traditional biomarkers were mainly implemented in rodents. This presented difficulty in implementing episodic memory probed-tasks, which is a cognitive function predominant in patients with neurodegenerative conditions. The achievement of forward translation thus became difficult to implement from animal to patient (Luo et al. 940). Further complications were experienced with the traditional biomarkers crippling advancement. This was because of the idiosyncratic non-standardized approaches present between laboratories with reference to the paradigms used and the animal models chosen (Nicholson et al. 180).
The animal models used in the traditional biomarkers involved reliable mimicking of certain elements of the disease being scrutinized, and a further analysis of potential mechanisms of treatment that can be taken to the clinic (Platt and Riedel 500). This process is known as face validity and predictive validity.
According to a research conducted on animal models, various aspects of mimicked Alzheimer’s disease (AD) pathology existed in the experimental invertebrate and vertebrate models. The pathology was an over expression of amyloid precursor protein (APP) and/or tau, a microtubule-associated protein. Heightened levels of plague-like depositions, βA (β-amyloid) and Inflammation showed in APP human mutated expressed in mice (Valla, Gonzalez-Lima, and Reiman 254). Dystrophic neurites and occasional synapse reduction were also observed in the traditional biomarker approach. It is important to note that memory and learning deficits were reported, however, not a reflective of specific typical domains in AD (Brankačk, Platt, and Riedel 810).
In the early onset of the AD, mutation in one of three genes: Amyloid precursor protein (APP), presenilin 1, or presenilin 2 occurs, resulting to exceptional family related form. On the other hand, the periodic type arises more often than not after 65 years of age, because of the presence of E4 allele of apolipoprotein E (APOE) and gene, and represents the most cases. Amyloid plaques encompass for the most part of the Aβ (A-beta), cleaved one after the other from the superior precursor protein-APP by β-secretase and γ-secretase enzymes. However, if APP cleaved first by α-secretase before β-secretase enzyme then Aβ not formed (Tampellini and Gouras 14).
There was limitation in the use of rodent models because of the front temporal dementia familial mutations introduced in the early tau-based models associated with severe sensory-motor deficits common in tau pathology found in motor areas. More aggressive and accelerated brain pathology were induced by the production of advanced mice which were bi- or tri-genic and over expressed trans genes of both tau, APP, and/or PS1 (McCarley 320). This was a reminiscent of AD in late stage (Dukart et al. 1491). The required trans-genes hyper-expression in rodents is significant in achieving tangle and plague-like pathologies, which is an evident mismatch with AD familial patients. Histopathological changes are caused by such expressions in 3-6 months young adults as shown in Table 1 below expressing quantified tangle/plague burden.
However, animals are often affected developmentally and lack gradual progression into mild cognitive impairment/ prodromal AD, which is a very critical phase in the classification of dementia and therapeutic intervention (Juréus et al. 785). There is also lack of correlation among various models of mouse evident in the cognitive decline and aggregated βA/tau. Evidently, there is parallel development in intracellular βA with the cognitive effects just before formation of extracellular plaque (Jeong 1500). This connotes that the cause of neuronal toxicity and malfunction is the soluble protein.
This also indicates that there are non-demented βA deposits is a good number of elderly people, while on the other hand, AD patients have a few plagues and cognition severely impaired. Therefore, the early pathological events are sufficed by the cytosolic prefibrillary oligo-mers or βA mono-. Alternatively, higher toxicity is conferred in oligomeric tau proteins than fibrils and tangles and AD patients at Braak stage 0 already present granular oligomers; these are inducible and progressively intensified in cell culture and transgenic animal models (Iranzo et al. 575). To date, most AD tested mouse models were produced through regulatory elements injection of pronuclear mutant transgenic material thus eliciting strong over-expression. A knock-in AD mouse (PLB1) was recently developed to counter the unstable transgenic models. This new model contains human APP, which is single-copy mutated and human tau constructs. Both the fused transgenes were indicated under controlled mouse promoter, αCaMKII (α-Ca2+/ calmodulin-dependent protein kinase) to discover tau expression and APP neuron specificity and postnatal forebrain (Willuweit et al. 7931). Additionally, PLB1Triple mice were created from a crossbreed with the available (asymptomatic) PS1 line (Jackson and Snyder 140). This new mice inhibited intraneuronal amyloid, which is an age-related pathology as well as accumulated hyperphosphorylated tau found in cortex and hippocampus from the age of 6 months (Klunk et al. 10600).
Brain imaging methods are current in use in the examination of cognition (cognitive neuroscience). The brain functions that underlie mental activity can now be mapped out. With this regard, brain imaging methods, such as fMRI (Functional Magnetic Resonance Imaging), PET (Positron emission tomography) and EEG (electroencephalogram) are now some of the ways of examining the cognitive processes. Monitoring brain action all through behavioral or cognitive procedures assists in the localization of the brain regions involved in that definite task. Furthermore, the techniques have allowed observation of the brain changes activation regarding the activity performed in a conscious individual (Prichep 160).
Physiological markers
Physiological markers involve the routinely applied functional neuroimaging in diagnosis in clinics. The technique is widely used as a modern tool for translation in the discovery of drugs (Drzezga 105). The commonly used physiological marker is the magnetic resonance imaging (MRI), however, photon emission tomography (PET), and dual-modality imaging, which combines both techniques like MRI and PET. These techniques induce event-related activation or rest to alter neural activity by emitting high spatial resolution (Jyoti et al. 880).
When Alzheimer’s affects an individual, the level of B Amyloid proteins continues on rising and this causes the degeneration of the tissues in contact with excessive proteins. The proteins consist of insoluble meshwork of neuro-fibrils, which clog up the cortex region of the brain and in the neurons in the cerebrum tissues. In normal persons, the breakdown of the neuro-fibrils is a continuous process, which safeguards persons against the clogging up of their cortex and cerebrum tissues (Drzezga 105).
Alzheimer’s patients are not capable of breaking down the insoluble neuro-fibrils and they cause lacerations on the brain tissues, especially the tissues based in the cerebellum. The gyri shrink while the sulci enlarge. It is the destruction associated with the lacerations, which occasions the changes in behavior of persons suffering from AD. Continued accumulation of the neuro-fibrils on the vascular tissues in the brain damages the integrity of the tissues leading to release of blood fluid into the cerebellum; a situation, which often leads to strokes or extensive hemorrhages. The spread of neurotic plaques is associated with the continued neuron-loss in the patients (Plano et al. 436).
Plaque development in patients provides a functional index for an enabled aggregated βA labeling of amyloid tracers, for instance, [11C] PIB (Pittsburgh compound B) and [18F] flobetapir (AV-45). It also displays non-specific white matter retained in high levels, while detecting load of grey matter plaque. This makes it difficult to detect AD in its early stages. This techniques has the shortcoming of failure of PIB to identify plaque present in murine models expressed in high APP, in the advocated for fibrillary proteins’ conformational differences (Platt and Riedel 156). It is important to note that novel tracers may post better results, for example, [3H]AZD2184, while it has not been taken through tests with in vivo imaging (Plano et al. 437).
Comparably, the usage of radiolabeled, FDG in the diagnosis of cancer in combination with the metabolic imaging have not produced the desired specificity of the disease. However, patterns of regional metabolism elicits its usage in the central nervous system (CNS) disorders as a diagnostic tool suitable for cases where the disease-specific models are directly available (Borchelt et al. 940). In such cases, they are translatable directly for purposes of experiments. In such cases, no specific ligands are required.
EEG biomarkers in neurodegenerative conditions
For over 100 years, EEG, in contrast to neuroimaging has served as tool for diagnosis for various neurodegenerative conditions, for instance, epilepsy and sleep disorders. It is significant to note that the EEG is a procedure, which is relatively cheaper and found in research groups and small clinics. It is therefore, an attractive research and diagnostic tool (Valla, Schneider, and Reiman 195). High temporal resolution makes EEG biomarkers superior to imaging. Its high temporal resolution projects in kHz range (Mayford et al. 1680).
The activity here gets captured only in superficial areas while multiple sites for recording provide some spatial information. In the case of imaging, uncertainty is created using the linear and non-linear algorithms in the complex analysis of data, against the reliability of the results posted. It is however, important to note the recent development of fully standardized and automated procedures courtesy of technological advancements and computational tools in novels and internet (Wang et al. 190).
There is a complementary relationship between EEG and sleep research. This is evident in the high dependency of typical EEG signatures on vigilance stages, sleep phases, and motor activity. This makes this approach highly applicable in clinics and research. An ultradian and circadian cycle determines the sleep phenotypes of the main stages of vigilance namely; rapid eye movement (REM) sleep, paradoxical, wakefulness, as well as non-REM (NREM) sleep or slow wave. The elusive nature of the sleep function remains evident despite physiological and cellular processes comprehension increase, which exists in both the modulation and generation of stages of sleep and its incorporation in the consolidation of memory (Janus 15).
Altered patterns of circadian and ultradian, and sleep disturbances are common symptoms in AD patients. These include frequent naps during the day. This phenomenon correlates positively with power spectrum of EEG as it shift to lower values, and fast incoherent rhythms, arising from cholinergic transmission failure (Gama Sosa, De Gasperi, and Elder 95).
According to suggestion from recent evidence, overt degenerative events are preceded by sleep disturbances in AD. This further suggests that EEG is more suitable and sensitive early degeneration diagnostic tool compared to cognition. There is high accuracy prediction in the quantitative EEG (qEEG) using the novel approaches in the conversion to dementia from mild cognitive impairment (Sahara et al. 3021).
Physiological biomarkers and the birth of electroceuticals
In comparison, there is so far rare application of qEEG in preclinical studies. A recent study conducted a comprehensive analysis of vigilance staging, sleep patterns and changes in qEEG at rest in over expressing mice, APP/PS1 as shown in Table 1. This was conducted through technologies of wireless microchip and elevated observation of pre-plaque’s wakefulness, as well as a low in age-dependent genotype and an increase in high spectral EEG power frequency (Meraz‐Ríos et al. 1360).
A presentation of a reduced REM sleep for various plaque-bearing mice (Tg2576) at 6 and 12 months, but shifts in AD-like spectral power shifts and sleep fragmentation indicated on tope the partial cortex have been seen in a study conducted in PLBB1 (Triple mice) shown in Table 1 and Figure 1. A congruency is also shown with maps showing FDG hypo metabolism shown in Figure 1 below.
The time in experimental acquisition’s vast difference is intriguing (24 h in qEEG, minutes in PET), this points to the knowledge that express robust translational biomarkers are accessed by both physiological and metabolic imaging by PLB1Triple mice. Spectral power shift will be determined by a staged correlate altered vigilance with histopathology and cognition in PLB1 mice as well as its therapeutic intervention sensitivity (Magrané et al. 1705). Earlier data point that cognitive decline emergence precedes it by a number of months thereby serving as reliable and convenient prognostic biomarkers that help in prediction of accurate AD-like symptomatology monitoring and onset progression (Humpel 27).
Discussion
All Cognition is a consequence of neurological activity most closely linked to the cerebral cortex. However, the study flanked by the neuroscience and cognitive psychology, particularly those theories of the min-brain problem (memory, problem solving, sensation and perception, motor functions, language processing, and cognition) has advanced in the contemporary society (Tampellini and Gouras 13). However, with a boost of techniques development, the Neuroscience field allows us to examine the human brain, disclose formations as well as processes that were never before. Nevertheless, the mostly noninvasive tools today remain possible because of advances in information technology as well as brain scanning methods (McGowan, Eriksen, and Hutton 285).
On the same note, methods that are employed in cognitive neuroscience comprises of functional neuroimaging; psychophysical experiments; neural systems electrophysiological studies; as well as increasingly, behavioral genetics and cognitive genomics. Clinical studies in psychopathology concerning patients with cognitive deficits form a significant aspect of cognitive neuroscience. The major theoretical approaches remain computational neuroscience as well as the more traditional, evocative cognitive psychology theories, for instance, psychometric (Oddo et al. 410-411).
The non-invasive nature of the in vivo FDG–PET imaging serves as its advantage, coupled with its ability to provide functional/physiological information, and the avenue for repetitive scans that enable comparison of subjects and longitudinal studies (Weiner et al. 204). The shortcomings of this technique manifests in the small size of the mouse’ brain (approximately 3000 times less that of human brain) making it essential to make accurate registration, coupled with absence of anatomical detail hence limiting resolution and making it difficult to decipher region-specific effects (Lee, Goedert, and Trojanowski 1150).
Acquisition of image in animals requires anesthesia administration, thus behavioral context functional information recording precluded, for instance, performance of cognitive tasks. RatCap devices are normally used to diffuse such problems; however, they do not provide unrestricted genuine conditions, thus unsuitable for mice (Morrissette et al. 635).
Determination and validation of disease-specific, sensitive PET signatures mapped on to animals from patients is a long process, which is also expensive especially, the maintenance and purchase of the facilities. The analysis of the images also requires specialized knowledge and is non-standardized. A powerful tool is provided using a priori defined seed
voxel analysis, however, principal or independent component analysis in data-driven or exploratory approaches may show the dynamics in not immediately intuitive metabolism, for instance, during the process of hyper-metabolism normalization in some areas of a diseased brain like cerebellum or whole brain (Epis et al. 58-59). This may result into emergence of metabolic phenotypes because of confounding factors, fluctuations because of metabolic and inflammation activity of glia (28) and neuronal compensatory display activity (Woodruff-Pak 510).
Conclusion
There is an evident lagging behind of preclinical in vivo imaging against its clinical counterpart. This is because it is still in conceptualization stage. It is however, noteworthy the increasing translational applications demand owing to improvements in the technology of imaging. The tracer development in the EEG makes this technique a ripe area for further research. Comparably, the recordings from EEG are crucial in diagnosis in clinical settings and are easy to find. There is a revival in this field of translational research because of the computational capabilities that have advanced coupled by recordings in novel devices. It is important for harmonization of analysis techniques and recording techniques between applications of rodent monkey and human in order to enhance clearer analysis in the various fields.
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