Extracellular vesicles from cerebrospinal fluid revealed changes in miR-19a-3p and miR-4516 expression in Slovene male suicides.

Suicide is an important public-health concern, with more than 700,000 people dying by suicide yearly. It is a multifactorial phenomenon, shaped by the effects of sociodemographic, environmental and biological factors. The latter two factors can be linked through epigenetic studies, which examine differences in gene expression that are not due to changes in the DNA sequence itself. Epigenetic mechanisms include micro RNAs (miRNAs), which have a direct effect on already translated mRNA, leading to either decay or translational repression of the target mRNA. MiRNA molecules have been identified as cargo of extracellular vesicles (EVs) used by cells for long-distance communication, and pathophysiological changes in miRNA in brain cells may be reflected in cerebrospinal fluid (CSF) vesicles. In this study we investigated the presence and differential expression of selected miRNAs in EVs from the CSF of male suicide completers and controls. Western blot and nanoparticle tracking analyses confirmed the presence of small and medium sized EVs. Of the miRNA analyzed (miR-16-5p, miR-19a-3p, miR-34c-5p, miR-17-5p, miR-4286, miR-26b-5p, miR-381-3p, and miR-4516) miR-19a-3p and miR-4516 reached statistical significance with p-values of 0.0408 and 0.0168, respectively. Mir-4516 and miRNA-19a-3p have been previously studied in suicide, and target SLC6A4 and TNF-α expression, correspondingly. Approximately 70% of known miRNAs are expressed in the central nervous system, and therefore represent an important biomarker potential. Investigating the cargo of CFS and blood EVs would further support the identification of miRNAs with clinical use potential.

DNA Methylation Patterns in Relation to Acute Severity and Duration of Anxiety and Depression.

Depression and anxiety are common mental disorders that often occur together. Stress is an important risk factor for both disorders, affecting pathophysiological processes through epigenetic changes that mediate gene-environment interactions. In this study, we explored two proposed models about the dynamic nature of DNA methylation in anxiety and depression: a stable change, in which DNA methylation accumulates over time as a function of the duration of clinical symptoms of anxiety and depression, or a flexible change, in which DNA methylation correlates with the acute severity of clinical symptoms. Symptom severity was assessed using clinical questionnaires for anxiety and depression (BDI-II, IDS-C, and HAM-A), and the current episode and the total lifetime symptom duration was obtained from patients' medical records. Peripheral blood DNA methylation levels were determined for the BDNF, COMT, and SLC6A4 genes. We found a significant negative correlation between COMT_1 amplicon methylation and acute symptom scores, with BDI-II (R(22) = 0.190, p = 0.033), IDS-C (R(22) = 0.199, p = 0.029), and HAM-A (R(22) = 0.231, p = 0.018) all showing a similar degree of correlation. Our results suggest that DNA methylation follows flexible dynamics, with methylation levels closely associated with acute clinical presentation rather than with the duration of anxiety and depression. These results provide important insights into the dynamic nature of DNA methylation in anxiety and affective disorders and contribute to our understanding of the complex interplay between stress, epigenetics, and individual phenotype.

Epigenetics in psychiatry: Beyond DNA methylation.

The global burden of psychopathologies appears to be underestimated, since the global psychiatric disorder burden is exceeding other medical burdens. To be able to address this problem more effectively, we need to better understand the etiology of psychiatric disorders. One of the hallmarks of psychiatric disorders appears to be epigenetic dysregulation. While some epigenetic modifications (such as DNA methylation) are well known and studied, the roles of others have been investigated much less. DNA hydroxymethylation is a rarely studied epigenetic modification, which as well as being an intermediate stage in the DNA demethylation cycle is also an independent steady cell state involved in neurodevelopment and plasticity. In contrast to DNA methylation, DNA hydroxymethylation appears to be related to an increase in gene expression and subsequent protein expression. Although no particular gene or genetic locus can be at this point linked to changes in DNA hydroxymethylation in psychiatric disorders, the epigenetic marks present good potential for biomarker identification because the epigenetic landscape is a result of the interplay between genes and environment, which both influence the development of psychiatric disorders, and because hydoxymethylation changes are particularly enriched in the brain and in synapse-related genes.

Effects of Mindfulness-Based Therapy on Clinical Symptoms and DNA Methylation in Patients with Polycystic Ovary Syndrome and High Metabolic Risk.

Polycystic ovary syndrome (PCOS) is an endocrine and metabolic disorder affecting women of reproductive age. Research has shown that epigenetic alterations such as DNA methylation may play a role in the development and progression of abnormal ovarian function and metabolic disorders in PCOS. Studies have identified specific genes (related with insulin signaling and steroid hormone metabolism) that are methylated in women with PCOS. DNA methylation appears to respond to various interventions aimed at altering health and lifestyle factors. We tested the efficacy of a mindfulness-based stress reduction program (MBSR) in PCOS patients. We examined its effects on anthropometric measurements, mental health and wellbeing, and alterations in DNA methylation in peripheral blood. MBSR was associated with a reduction in body mass index, waist circumference and blood glucose level, an improvement in subjectively perceived general health, emotional role limitation, and levels of pain, as well as mindfulness-like traits. MBSR reduced the expression of anxious symptomatology and subjectively perceived stress. Methylation changes were observed in four genes: COMT, FST, FKBP51, and MAOA. We conclude that MBSR may be a useful supplementary therapy to mitigate the deleterious effects of PCOS on mental health.

Difference in Methylation and Expression of Brain-Derived Neurotrophic Factor in Alzheimer's Disease and Mild Cognitive Impairment.

Due to the increasing number of progressive dementias in the population, numerous studies are being conducted that seek to determine risk factors, biomarkers and pathological mechanisms that could help to differentiate between normal symptoms of aging, mild cognitive impairment (MCI) and dementia. The aim of this study was to investigate the possible association of levels of BDNF and COMT gene expression and methylation in peripheral blood cells with the development of Alzheimer's disease (AD). Our results revealed higher expression levels of BDNF (p < 0.001) in MCI subjects compared to individuals diagnosed with AD. However, no difference in COMT gene expression (p = 0.366) was detected. DNA methylation of the CpG islands and other sequences with potential effects on gene expression regulation revealed just one region (BDNF_9) in the BDNF gene (p = 0.078) with marginally lower levels of methylation in the AD compared to MCI subjects. Here, we show that the level of BDNF expression in the periphery is decreased in subjects with AD compared to individuals with MCI. The combined results from the gene expression analysis and DNA methylation analysis point to the potential of BDNF as a marker that could help distinguish between MCI and AD patients.

Targeted sequencing approach: Comprehensive analysis of DNA methylation and gene expression across blood and brain regions in suicide victims.

OBJECTIVES: Epigenetic mechanisms are involved in regulation of many pathologies, including suicidal behaviour. However, the factors through which epigenetics affect suicidal behaviour are not fully understood. METHODS: We analysed DNA methylation of eight neuropsychiatric genes (NR3C1, SLC6A4, HTR1A, TPH2, SKA2, MAOA, GABRA1, and NRIP3) in brain regions (hippocampus, insula, amygdala, Brodmann area 46) and blood of 25 male suicide victims and 28 male control subjects, using bisulphite next-generation sequencing. RESULTS: Comparing mean methylation values, notable changes were observed in NR3C1 (insula p-value = 0.05), HTR1A (insula p-value < 0.001, blood p-value = 0.001), SKA2 (insula p-value = 0.03, blood p-value = 0.016), MAOA (blood p-value < 0.001), GABRA1 (insula p-value = 0.05, blood p-value = 0.024) and NRIP3 (hippocampus p-value = 0.001, insula p-value = 0.002, amygdala p-value = 0.014). Comparing methylation pattern between blood and brain, similarity was observed between blood and insula for HTR1A. Gene expression analysis in hippocampus revealed changes in expression of NR3C1 (p-value = 0.049), SLC6A4 (p-value = 0.017) and HTR1A (p-value = 0.053). CONCLUSIONS: Results provide an insight into the altered state of DNA methylation in suicidal behaviour. Epigenetic differences could therefore affect suicidal behaviour in both previously known and in novel neuropsychiatric candidate genes.

Depressive disorder and antidepressants from an epigenetic point of view.

Depressive disorder is a complex, heterogeneous disease that affects approximately 280 million people worldwide. Environmental, genetic, and neurobiological factors contribute to the depressive state. Since the nervous system is susceptible to shifts in activity of epigenetic modifiers, these allow for significant plasticity and response to rapid changes in the environment. Among the most studied epigenetic modifications in depressive disorder is DNA methylation, with findings centered on the brain-derived neurotrophic factor gene, the glucocorticoid receptor gene, and the serotonin transporter gene. In order to identify biomarkers that would be useful in clinical settings, for diagnosis and for treatment response, further research on antidepressants and alterations they cause in the epigenetic landscape throughout the genome is needed. Studies on cornerstone antidepressants, such as selective serotonin reuptake inhibitors, selective serotonin and norepinephrine reuptake inhibitors, norepinephrine, and dopamine reuptake inhibitors and their effects on depressive disorder are available, but systematic conclusions on their effects are still hard to draw due to the highly heterogeneous nature of the studies. In addition, two novel drugs, ketamine and esketamine, are being investigated particularly in association with treatment of resistant depression, which is one of the hot topics of contemporary research and the field of precision psychiatry.

Suicide and Changes in Expression of Neuronal miRNA Predicted by an Algorithm Search through miRNA Databases.

Suicide is multifactorial and polygenic phenotype, affected by environmental and genetic factors. Among epigenetic mechanisms, miRNAs have been studied, but so far no very concise results exist. To overcome limitations of candidate miRNA and whole genome sequencing approaches, we created an in silico analysis algorithm that would help select the best suitable miRNAs that target the most interesting genes associated with suicidality. We used databases/web algorithms DIANA microT, miRDB, miRmap, miRWalk, and TargetScan and candidate genes SLC6A4, HTR1A, BDNF, NR3C1, ZNF714, and NRIP3. Based on a prediction algorithm, we have chosen miRNAs that are targeting regulation of the genes listed, and are at the same time being expressed in the brain. The highest ranking scores were obtained for hsa-miR-4516, hsa-miR-3135b, hsa-miR-124-3p, hsa-miR-129-5p, hsa-miR-27b-3p, hsa-miR-381-3p, hsa-miR-4286. Expression of these miRNAs was tested in the brain tissue of 40 suicide completers and controls, and hsa-miR-4516 and hsa-miR-381-3p showed a trend for statistical significance. We also checked the expression of the target genes of these miRNAs, and for NR3C1 expression was lower in suicide completers compared to controls, which is in accordance with the available literature results. To determine the miRNAs that are most suitable for further suicidality research, more studies, combining in silico analysis and wet lab experiments, should be performed.

Dynamic Intercell Communication between Glioblastoma and Microenvironment through Extracellular Vesicles.

Glioblastoma is simultaneously the most common and most aggressive primary brain tumor in the central nervous system, with poor patient survival and scarce treatment options. Most primary glioblastomas reoccur and evolve radio- and chemoresistant properties which make them resistant to further treatments. Based on gene mutations and expression profiles, glioblastoma is relatively well classified; however, research shows that there is more to glioblastoma biology than that defined solely by its genetic component. Specifically, the overall malignancy of the tumor is also influenced by the dynamic communication to its immediate and distant environment, as important messengers to neighboring cells in the tumor microenvironment extracellular vesicles (EVs) have been identified. EVs and their cargo can modulate the immune microenvironment and other physiological processes, and can interact with the host immune system. They are involved in tumor cell survival and metabolism, tumor initiation, progression, and therapy resistance. However, on the other hand EVs are thought to become an effective treatment alternative, since they can cross the blood-brain barrier, are able of specific cell-targeting and can be loaded with various therapeutic molecules.

'Omics' of suicidal behaviour: A path to personalised psychiatry.

Psychiatric disorders, including suicide, are complex disorders that are affected by many different risk factors. It has been estimated that genetic factors contribute up to 50% to suicide risk. As the candidate gene approach has not identified a gene or set of genes that can be defined as biomarkers for suicidal behaviour, much is expected from cutting edge technological approaches that can interrogate several hundred, or even millions, of biomarkers at a time. These include the '-omic' approaches, such as genomics, transcriptomics, epigenomics, proteomics and metabolomics. Indeed, these have revealed new candidate biomarkers associated with suicidal behaviour. The most interesting of these have been implicated in inflammation and immune responses, which have been revealed through different study approaches, from genome-wide single nucleotide studies and the micro-RNA transcriptome, to the proteome and metabolome. However, the massive amounts of data that are generated by the '-omic' technologies demand the use of powerful computational analysis, and also specifically trained personnel. In this regard, machine learning approaches are beginning to pave the way towards personalized psychiatry.

Sequencing of Nucleic Acids: from the First Human Genome to Next Generation Sequencing in {COVID}-19 Pandemic.

Despite being around for more than 40 years, DNA sequencing is regarded as young technology in clinical medicine. As sequencing is becoming cheaper, faster and more accurate, it is rapidly being incorporated into clinical laboratories. In 2003, the completion of the first human genome opened the door to personalized medicine. Ever since it has been expected for genomics to widely impact clinical care and public health. However, many years can pass for genomic discoveries to reflect back and benefit the patients. DNA sequencing represents a less biased approach to diagnostics. It is not only a diagnostic tool, but can also influence clinical management and therapy. As new technologies rapidly emerge it is important for researchers and health professionals to have basic knowledge about the capabilities and drawbacks of the existing sequencing methods, and their use in clinical setting and research. This review provides an overview of nucleic acid sequencing technologies from historical perspective and later focuses on clinical utilization of sequencing. Some of the most promising areas are presented with selected examples from Slovenian researchers.

OligoPrime: An Information System for Oligonucleotide Management.

With the increasing number of molecular biology techniques, large numbers of oligonucleotides are frequently involved in individual research projects. Thus, a dedicated electronic oligonucleotide management system is expected to provide several benefits such as increased oligonucleotide traceability, facilitated sharing of oligonucleotides between laboratories, and simplified (bulk) ordering of oligonucleotides. Herein, we describe OligoPrime, an information system for oligonucleotide management, which presents a computational support for all steps in an oligonucleotide lifecycle, namely, from its ordering and storage to its application, and disposal. OligoPrime is easy to use since it is accessible via a web browser and does not require any installation from the end user's perspective. It allows filtering and search of oligonucleotides by various parameters, which include the exact location of an oligonucleotide, its sequence, and availability. The oligonucleotide database behind the system is shared among the researchers working in the same laboratory or research group. Users might have different roles which define the access permissions and range from students to researchers and primary investigators. Furthermore, OligoPrime is easy to manage and install and is based on open-source software solutions. Its code is freely available at https://github.com/OligoPrime. Moreover, an implementation of OligoPrime, which can be used for testing is available at http://oligoprime.xyz/. To our knowledge, OligoPrime is the only software solution dedicated specifically to oligonucleotide management. We strongly believe that it has a large potential to enhance the transparency of use and to simplify the management of oligonucleotides in academic laboratories and research groups.

Neuroepigenetics of psychiatric disorders: Focus on lncRNA.

Understanding the pathology of psychiatric disorders is challenging due to their complexity and multifactorial origin. However, development of high-throughput technologies has allowed for better insight into their molecular signatures. Advancement of sequencing methodologies have made it possible to study not only the protein-coding but also the noncoding genome. It is now clear that besides the genetic component, different epigenetic mechanisms play major roles in the onset and development of psychiatric disorders. Among them, examining the role of long noncoding RNAs (lncRNAs) is a relatively new field. Here, we present an overview of what is currently known about the involvement of lncRNAs in schizophrenia, major depressive and bipolar disorders, as well as suicide. The diagnosis of psychiatric disorders mainly relies on clinical evaluation without using measurable biomarkers. In this regard, lncRNA may open new opportunities for development of molecular tests. However, so far only a small set of known lncRNAs have been characterized at molecular level, which means they have a long way to go before clinical implementation. Understanding how changes in lncRNAs affect the appearance and development of psychiatric disorders may lead to a more classified and objective diagnostic system, but also open up new therapeutic targets for these patients.

Epigenetics of Alzheimer's Disease.

There are currently no validated biomarkers which can be used to accurately diagnose Alzheimer's disease (AD) or to distinguish it from other dementia-causing neuropathologies. Moreover, to date, only symptomatic treatments exist for this progressive neurodegenerative disorder. In the search for new, more reliable biomarkers and potential therapeutic options, epigenetic modifications have emerged as important players in the pathogenesis of AD. The aim of the article was to provide a brief overview of the current knowledge regarding the role of epigenetics (including mitoepigenetics) in AD, and the possibility of applying these advances for future AD therapy. Extensive research has suggested an important role of DNA methylation and hydroxymethylation, histone posttranslational modifications, and non-coding RNA regulation (with the emphasis on microRNAs) in the course and development of AD. Recent studies also indicated mitochondrial DNA (mtDNA) as an interesting biomarker of AD, since dysfunctions in the mitochondria and lower mtDNA copy number have been associated with AD pathophysiology. The current evidence suggests that epigenetic changes can be successfully detected, not only in the central nervous system, but also in the cerebrospinal fluid and on the periphery, contributing further to their potential as both biomarkers and therapeutic targets in AD.

Machine learning as the new approach in understanding biomarkers of suicidal behavior.

In psychiatry, compared to other medical fields, the identification of biological markers that would complement current clinical interview, and enable more objective and faster clinical diagnosis, implement accurate monitoring of treatment response and remission, is grave. Current technological development enables analyses of various biological marks in high throughput scale at reasonable costs, and therefore 'omic' studies are entering the psychiatry research. However, big data demands a whole new plethora of skills in data processing, before clinically useful information can be extracted. So far the classical approach to data analysis did not really contribute to identification of biomarkers in psychiatry, but the extensive amounts of data might get to a higher level, if artificial intelligence in the shape of machine learning algorithms would be applied. Not many studies on machine learning in psychiatry have been published, but we can already see from that handful of studies that the potential to build a screening portfolio of biomarkers for different psychopathologies, including suicide, exists.

BDNF methylation and mRNA expression in brain and blood of completed suicides in Slovenia.

BACKGROUND: Suicide is a major public health problem. Worldwide, around 800000 people die by suicide every year. Suicide is a multifactorial disorder, with numerous environmental and genetic risk factors involved. Among the candidate genes, changes in the BDNF locus at the gene, epigenetic, mRNA, and protein expression levels have been implicated in psychiatric disorders, including suicidal behavior and completed suicides. AIM: To investigate changes in BDNF methylation and expression of four alternative BDNF transcripts for association with completed suicide. METHODS: This case-control study included 42 unrelated male Caucasian subjects, where 20 were control subjects who died following acute cardiac arrest, and 22 were suicide victims who died by hanging. DNA and RNA were extracted from brain tissue (Brodmann area 9 and hippocampus) and from blood. DNA methylation and mRNA expression levels were determined by targeted bisulfite next-generation sequencing and reverse-transcription quantitative PCR. Statistical analysis was done by use of two-tailed Student's t tests for two independent samples, and the Benjamini-Hochberg procedure was implemented for correction for multiple comparisons. RESULTS: In DNA from brain tissue, there were no significant differences in BDNF methylation between the study groups. However, data showed significantly reduced DNA methylation of the BDNF region upstream of exon I in blood samples of suicide victims compared to the controls (5.67 ± 0.57 vs 6.83 ± 0.64, P corr = 0.01). In Brodmann area 9 of the brain of the suicide victims but not in their hippocampus, there was higher expression of BDNF transcript I-IX (NM_170731.4) compared to the controls (0.077 ± 0.024 vs 0.05 ± 0.013, P = 0.042). In blood, expression analysis for the BDNF transcripts was not feasible due to extensive RNA degradation. CONCLUSION: Despite the limitations of the study, the obtained data further support a role for BDNF in suicidality. However, it should be noted that suicidal behavior is a multifactorial disorder with numerous environmental and genetic risk factors involved.

Potential of modern circulating cell-free DNA diagnostic tools for detection of specific tumour cells in clinical practice.

Personalized medicine is a developing field of medicine that has gained in importance in recent decades. New diagnostic tests based on the analysis of circulating cell-free DNA (cfDNA) were developed as a tool of diagnosing different cancer types. By detecting the subpopulation of mutated DNA from cancer cells, it is possible to detect the presence of a specific tumour in early stages of the disease. Mutation analysis is performed by quantitative polymerase chain reaction (qPCR) or the next generation sequencing (NGS), however, cfDNA protocols need to be modified carefully in preanalytical, analytical, and postanalytical stages. To further improve treatment of cancer the Food and Drug Administration approved more than 20 companion diagnostic tests that combine cancer drugs with highly efficient genetic diagnostic tools. Tools detect mutations in the DNA originating from cancer cells directly through the subpopulation of cfDNA, the circular tumour DNA (ctDNA) analysis or with visualization of cells through intracellular DNA probes. A large number of ctDNA tests in clinical studies demonstrate the importance of new findings in the field of cancer diagnosis. We describe the innovations in personalized medicine: techniques for detecting ctDNA and genomic DNA (gDNA) mutations approved Food and Drug Administration companion genetic diagnostics, candidate genes for assembling the cancer NGS panels, and a brief mention of the multitude of cfDNA currently in clinical trials. Additionally, an overview of the development steps of the diagnostic tools will refresh and expand the knowledge of clinics and geneticists for research opportunities beyond the development phases.

Coding of Glioblastoma Progression and Therapy Resistance through Long Noncoding RNAs.

Glioblastoma is the most aggressive and lethal primary brain malignancy, with an average patient survival from diagnosis of 14 months. Glioblastoma also usually progresses as a more invasive phenotype after initial treatment. A major step forward in our understanding of the nature of glioblastoma was achieved with large-scale expression analysis. However, due to genomic complexity and heterogeneity, transcriptomics alone is not enough to define the glioblastoma "fingerprint", so epigenetic mechanisms are being examined, including the noncoding genome. On the basis of their tissue specificity, long noncoding RNAs (lncRNAs) are being explored as new diagnostic and therapeutic targets. In addition, growing evidence indicates that lncRNAs have various roles in resistance to glioblastoma therapies (e.g., MALAT1, H19) and in glioblastoma progression (e.g., CRNDE, HOTAIRM1, ASLNC22381, ASLNC20819). Investigations have also focused on the prognostic value of lncRNAs, as well as the definition of the molecular signatures of glioma, to provide more precise tumor classification. This review discusses the potential that lncRNAs hold for the development of novel diagnostic and, hopefully, therapeutic targets that can contribute to prolonged survival and improved quality of life for patients with glioblastoma.

Nanomedicine and Immunotherapy: A Step Further towards Precision Medicine for Glioblastoma.

Owing to the advancement of technology combined with our deeper knowledge of human nature and diseases, we are able to move towards precision medicine, where patients are treated at the individual level in concordance with their genetic profiles. Lately, the integration of nanoparticles in biotechnology and their applications in medicine has allowed us to diagnose and treat disease better and more precisely. As a model disease, we used a grade IV malignant brain tumor (glioblastoma). Significant improvements in diagnosis were achieved with the application of fluorescent nanoparticles for intraoperative magnetic resonance imaging (MRI), allowing for improved tumor cell visibility and increasing the extent of the surgical resection, leading to better patient response. Fluorescent probes can be engineered to be activated through different molecular pathways, which will open the path to individualized glioblastoma diagnosis, monitoring, and treatment. Nanoparticles are also extensively studied as nanovehicles for targeted delivery and more controlled medication release, and some nanomedicines are already in early phases of clinical trials. Moreover, sampling biological fluids will give new insights into glioblastoma pathogenesis due to the presence of extracellular vesicles, circulating tumor cells, and circulating tumor DNA. As current glioblastoma therapy does not provide good quality of life for patients, other approaches such as immunotherapy are explored. To conclude, we reason that development of personalized therapies based on a patient's genetic signature combined with pharmacogenomics and immunogenomic information will significantly change the outcome of glioblastoma patients.

Genome-Wide DNA Methylation Patterns in Suicide Victims: Identification of New Candidate Genes.

Suicide is a major global public health problem with significant impact on society. According to the World Health Organization, every year about 800.000 people commit suicide, while at the global level suicide accounts for 50% of all violent deaths among men and for 71% among women. Suicide is a complex phenomenon which cannot be attributed to a single causal factor, but to a combination of simultaneous effects of multiple factors which are expressed in the form of psychological, biological and sociological indicators. Analysis of epigenetic mechanisms (methylation of the DNA, modifications of histone proteins and (networks of) miRNA), which link the interaction between genes and the environment, could importantly contribute to better understanding of suicidal behaviour. Recent studies on suicidal behaviour and DNA methylation show differences in DNA methylation pattern, with numerous sites among suicide victims. Using next generation sequencing, genome-wide studies helped identify novel candidate genes while studies of already known candidate genes (such as glucocorticoid receptor and BDNF) gave us better insight into the interplay of genetics and epigenetics. Epigenetic studies importantly contribute to elucidation of new biomarkers for suicidal behaviour. However, present studies are very different in design and often performed on very small samples, and these limitations could be overcome with more careful study preparation.