Since the mid-1980s of the last century, positron emission tomography (PET) and magnetic resonance imaging (MR), both structural and functional, have been used to measure phenotypic variations of the molecular or cellular targets of mental diseases or to highlight changes in brain circuits representative of specific behavioral alterations. These methods of investigation of brain structure and function can contribute to a nosological classification for diagnostic purposes, precisely as in other branches of medicine, such as oncology or cardiology.

It cannot be ruled out that, in the near future, psychiatric patients will be able to wear brain monitoring instruments to obtain clinically helpful measurements, in the same way, that heart patients wear cardiac monitoring instruments today.

However, the use of neuroimaging as a biomarker in clinical routine still presents difficulties.

A first obstacle is that many of the characteristics of mental illnesses are not evident from a purely structural point of view. The brains of these patients may appear morphologically normal and exhibit pathological phenotypes only during specific functional tasks. This makes the use of functional paradigms an essential requirement to detect distinct aspects of the disease, complicating the applicability of such measurements in clinical practice. Indeed, an ideal marker requires using a simple and easy to-apply test.

The second problem is that, given the extreme phenotypic complexity of mental illnesses related to polygenic vulnerability modulated by multiple environmental factors, a single biomarker may not be sufficient to diagnose or monitor the response to treatment. It is necessary, therefore, to have multiple biomarkers to test, each indicative of a different phenotypic aspect of the disease. The best markers, therefore, will be those that require relatively simple instrumentation for their measurement.

The Concept of Endophenotype

Images obtained by MRI can be very useful as intermediate phenotypes or endophenotypes to identify other biomarkers.

An endophenotype is a quantitative, measurable trait intermediate between the “disease” phenotype and its under lying biological processes. Several endophenotypes combine to form the complexity of the disease, and each of them is more easily traceable, compared to the complex phenotype, to a precise molecular mechanism underlying the same disease.

For an endophenotype to become a biomarker, however, it must be as independent as possible from environmental influences. For example, an increase in the concentration of b-endorphin can be a biochemical marker of alcohol dependence, but b-endorphin levels can also be strongly altered by an isolated, albeit excessive, consumption of alcohol. Therefore, the measurement of this biomarker must be con textualized to be clinically useful.

In the case of brain imaging, their use as endophenotypes may allow biochemical parameters or genetic variants to be related to complex disease phenotypes. For example, the ε4 allele of the ApoE gene is known to be a risk factor for Alzheimer’s disease. An explanation for this association is provided by functional magnetic resonance imaging (fMRI) studies, in which more extensive brain activation during memory tasks was observed in healthy subjects carrying the ε4 allele than in subjects carrying the ε3 allele. This indicates a compensatory response in subjects with ε4, i.e., the need to use additional brain resources to cope with similar cognitive tasks. The endo phenotype, consisting of fMRI images, shows, therefore, the existence of a link between the ApoE genotype and a deficit in memory functions, which increases the risk of Alzheimer’s disease. This observation, therefore, confirms the validity of the ApoE genotype as a predictor of Alzheimer’s risk.

Another example of the use of fMRI images as endo phenotypes useful to identify biochemical markers of disease is given by a very recent work in which it was seen that, both in healthy subjects and in patients with mild cognitive impairment (MCI), the activation of the dorsal portion of the anterior cingulate cortex (dACC) in response to tasks of visuospatial attention correlates with the levels of vitamin B12. Again, an endophenotype, consisting of functional MRI findings, relates a biochemical parameter, vitamin B12 concentration, to cognitive abilities. The relationship between B12 and visuospatial abilities emerges only by including brain activity measured by functional magnetic resonance imaging in the correlation analysis. This finding explains the clinical utility of vitamin B12 dosage as a predictor of reduced cognitive ability.

Therefore, brain images represent excellent endophenotypes, which are useful for identifying the relationships between molecular mechanisms and complex phenotypes. This does not exclude, however, that they can be disease bio markers in combination with other neurophysiological parameters.

Recent studies, for example, have found a reduction in hippocampal volume in depressed patients compared to healthy control subjects. This reduction has been observed in adult patients and adolescents, both at the first and subsequent episodes. Hippocampal atrophy may be due to neuro degenerative phenomena resulting from the increased glucocorticoid levels in depression. Studies in larger patient populations are needed to verify whether reduced hippocampal volume may be a valid biological marker of depression and risk of depressive episodes.

The Omics Sciences

Given the phenotypic complexity of psychiatric diseases, a promising approach for understanding the mechanisms underlying these diseases and identifying new biological markers is represented by omics sciences, i.e., genomics, proteomics, metabolomics, lipidomics, and epigenomics.

Genomics

Since the human genome sequence was completed in 2003, genomics studies have also been an essential resource for identifying new biomarkers in psychiatry. Mental illnesses are mainly heritable. In the last 20 years, genome-wide association studies (GWAS), in which whole genomes of thousands of patients and controls have been compared, have identified some genetic loci associated with schizophrenia, bipolar disorder, major depression, ADHD (attention deficit hyperactivity disorder), autism spectrum disorders, and, even, some loci associated with all five diseases, indicative of shared pathological mechanisms. Nevertheless, it has not yet been possible in these genomic regions to identify the genes responsible for the increased risk of disease, nor any other sequences involved. Researchers initially focused on coding regions and non-synonymous sequence variants. However, non-coding regions of the genome, such as those responsible for splicing mechanisms, may also play important roles in promoting behavioral disorders. About 93% of the variants identified by GWAS are located outside coding regions.

However, the genome study alone is insufficient for a complete characterization of the molecular mechanisms at the basis of mental processes. It is known that the same gene sequence can encode different proteins by post- transcriptional and post-translational modifications, so it has become necessary to flank the study of the genome with that of the proteome.

Proteomics

Studying the proteome means studying all the proteins a given cell expresses at a particular time or their changes in response to environmental factors or following the onset of disease or drug intake. Comparing the proteomes of psychiatric patients and healthy subjects or those of the same patient in different stages of disease aims to identify differentially expressed proteins, which could become good diagnostic or prognostic markers.

Proteomics uses different technologies, such as two- dimensional electrophoresis, image analysis, mass spectrometry, amino acid sequencing, and bioinformatics tools, to isolate, quantify, and characterize proteins of interest. In the case of mental diseases, the most informative biological material for proteomics studies is represented by postmortem brain tissue. However, in addition to the objective complexity of finding a large number of this type of sample, the postmortem brain tissue has the great difficulty of having to be processed immediately. After death, there is rapid dephosphorylation of proteins, which produces differences in results, the more evident, the greater the time elapsed between the time of death and the autopsy. This makes the feasibility of this type of study particularly complicated. This difficulty can be circumvented by studying the brains of animal models taken immediately after the sacrifice. In the case of mental illnesses, however, animal models have their limits since they cannot perfectly reproduce the pathological phenotype precisely because of the clinical complexity of mental illnesses. However, there are some animal models, such as the mouse with “social defeat,” which has been described as a good model of depression even at the molecular level. Indeed, it shows differential protein expression pat terns in the brain overlapping with those found in depressed patients studied postmortem.

Despite the difficulties described, the study of postmortem brains has allowed the identification of some proteins, which could represent good clinical markers. These are mainly growth factors, hormones, metabolic enzymes, and proteins involved in cellular architecture or synaptic trans mission (Table 1). The same differential expression of some of these factors is observed in different pathologies, such as major depression, bipolar disorder, and schizophrenia, thus demonstrating a limited diagnostic specificity, whereas other proteins seem to be a disorder-specific phenomenon (Table 1). Finally, some of these proteins, such as NADPH oxidase 2 (NOX2) or others involved in (GABA) ergic neurotransmission, would seem to be good predictors of suicidal behavior.

Table1. Major proteomic biomarkers detectable in the postmortem brain potentially useful in psychiatry

The differential expression of many of these proteins can also be observed in cerebrospinal fluid (CSF) (Table 1), whose collection by lumbar puncture also allows the study in vivo in patients, contrary to what happens in studies on brain tissue taken postmortem. However, CSF collection is relatively invasive and not easy to apply to the diagnostic routine. It is unclear to what extent blood or saliva can represent the molecular processes occurring in the brain. Good indications in this sense derive from recent evidence showing the involvement of pro-inflammatory and immunoregulatory proteins in the pathophysiology of psychiatric disorders (Table 2). For example, increased levels of pro- inflammatory cytokines, such as IL-1b, IL-6, IL-12, IL-18, TNF-α, FN-g, and C-reactive protein, and reduced levels of anti-inflammatory cytokines, such as IL-10, IFN-α, and TGF-b, have been observed in both bipolar and schizophrenic patients. An increase in pro-inflammatory and oxidative stress response proteins, such as ceruloplasmin, ferritin, interleukin-1 receptor antagonist, macrophage migration inhibitory factor, and superoxide dismutase 1, has been associated with depression. In contrast, alterations in the concentration of growth factors, hormones, transport molecules, and components of hemostasis would appear to be predictive of the severity of depressive symptoms (Table 2). Finally, peripheral cytokine levels have also been related to the treatment response with antidepressant drugs, in particular, tumor necrosis factor (TNF) or lithium in the case of bipolar disorder (Table 2). What is not yet known, however, is whether these changes in the expression of markers of inflammation are a consequence or cause of mental pathology. The possible co-occurrence of different inflammation causes represents a non-negligible confounding factor, which makes these markers too non-specific to have any actual diagnostic usefulness in psychiatry.

Table2. Major proteomic biomarkers detectable in peripheral blood, potentially useful in psychiatry

Another peripheral biomarker of altered brain function appears to be the growth factor BDNF (brain-derived neuro trophic factor). Its serum concentration is decreased in patients with bipolar disorder and seems to be inversely related to the patient’s age and the disease’s duration. BDNF has been reported to distinguish late stages from early stages of the disease with a sensitivity of 100%, specificity of 89%, and accuracy of 95%. BDNF also appears to be useful for the differential diagnosis between bipolar disorder and unipolar depression or as a predictor of treatment response. Patients treated with lithium who show the best response are those with the highest serum BDNF levels. Definitive evidence, however, regarding their usefulness as biomarkers does not exist for BDNF or other neurotrophic factors either.

Metabolomics

Even the combination of genomics and proteomics, although more informative than genomics studies alone, is still insufficient to represent the biochemical and molecular mechanisms underlying brain functioning comprehensively.

A further advance in this sense could derive, instead, from the study of the metabolome, i.e., the set of all metabolic processes essential for the organism’s life, which reflect the complex interaction among genes, proteins, and environment. Analyses of the metabolome, conducted by NMR (nuclear magnetic resonance) spectroscopy or mass spectrometry on the serum of psychiatric patients, were found to be indicative of the presence of alterations in the citric acid cycle, the urea cycle, amino acid metabolism, or mitochondrial metabolism (Table 3), all essential processes for growth, proliferation, survival, and motility of cells and, therefore, likely indicators of altered neurogenesis and dendritic arborization. Metabolomics studies aim to define the so-called metabotypes, i.e., biochemical entities resulting from all metabolic interactions, predictive of a pathological state or the type of response to specific drug treatment.

Table3. Main metabolomic biomarkers detectable in peripheral blood, potentially useful in psychiatry

Lipidomics

 Lipids are also essential for brain function. Phospholipids are, in fact, the main components of cell membranes and constitute 60% of the brain’s dry weight. Changes in lipid metabolism or lipid-mediated signal transmission processes alter cellular homeostasis, contributing to developing pathological states, including mental illness. In particular, polyunsaturated fatty acids such as omega-3 and omega-6 appear to play important roles in the pathogenesis of major affective and psychotic disorders (Table 4) and in response to treatment with antidepressants. Conditions such as metabolic syndrome, obesity, diabetes, and cardiovascular dis ease are frequently observed in psychiatric patients. However, it is unclear to what extent they are a consequence of treatment with psychotropic medications, which can cause weight gain, insulin resistance, and hypertriglyceridemia, or whether they are clinical conditions that preexist treatment.

Table4. Main lipidomic biomarkers detectable in peripheral blood, potentially useful in psychiatry

Epigenomics

 Epigenomics is a further discipline that can promote an understanding of molecular mechanisms underlying altered mental processes and the identification of new diagnostic or prognostic biomarkers. Epigenomics studies mechanisms that, without modifying the DNA sequence, affect the expression of genes. Among these, we find the addition of methyl groups (-CH3) at specific sequences in the promoters of genes, the CpG islands, capable of reducing gene expression, or post-translational modifications of histones – the basic proteins around which DNA is wrapped to form chromatin – such as acetylation which, by neutralizing the positive charges of histones, promotes the decondensation of chromatin and the consequent attachment of transcription factors to DNA.

Finally, microRNAs (miRNAs) are short non-coding RNA sequences, complementary to the 3′ untranslated ends (UTRs) of messenger RNAs (mRNAs), capable of temporarily or permanently blocking the synthesis of specific proteins by binding to their corresponding mRNAs and preventing them from being used as translation molds. miRNAs are tissue- specific and contribute to the development and plasticity of synapses, neurogenesis, and the arborization and formation of dendritic spines. Differential expression of some miRNAs has been observed in the prefrontal cortex of schizophrenic patients, while other miRNAs have been shown to be good predictors of response to treatment with antidepressants.

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مواضيع ذات صلة

Parallels to brain control of thermoregulation

Glucose sensing and brain control of energy balance

Overview of brain control of glucose homeostasis in normal physiology

Neurally Mediated Syncope

Special Characteristics of Signal Transmission in Nerve Trunks

Peripheral nerves

خواص الإيعاز العصبي

العوامل التي تؤدي إلى تكون جهد الراحة

Astrocytes

المستقبلات الكولنيرجية والأدرينرجية

الجهاز العصبي الذاتي

الأعصاب الدماغية