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THE EFFECT OF NEUROBIOLOGICAL CHANGES IN THE BRAIN OF CHILDREN WITH SCHIZOPHRENIA AND UHR FOR SCHIZOPHRENIA: CLINICAL CORRELATIONS WITH EEG ABNORMALITIES

Autor: Laura Nussbaum Axinia Corcheş Luminiţa Ageu Bianca Micu Șerbu
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Background: Relatively little research has been conducted on QEEG activity in patients with psychosis, especially in populations at-risk for the illness. Further studies are needed, in order to offer a possible endo-phenotypic marker of the cerebral functioning, associated with psychosis, in correlation with the neuroimaging, the neuro-cognitive, biochemical and molecular genetic tests and data obtained and the EEG activity from the same subjects. The aim was to investigate the role, the QEEG abnormalities play in the etiology of psychosis, and whether it can provide an endo-phenotype for psychosis.
Materials and Methods: The prospective research was performed in the University Hospital of Neurology and Psychiatry for Children and Adolescents, Timisoara, involving 55 children with schizophrenia or UHR for psychosis – Group A, B, C, D and 55 children – healthy controls – Group E. Group A and B (28 children) are diagnosed with schizophrenia and group C and D are UHR for psychosis (27 children) and group E – healthy controls.
The group A and C had convulsive seizures in their personal history.
Results We noticed: numerous patterns of theta and delta activity, the diminished amplitude of the alpha band waves and the diminished alpha activity. So that, the onset of psychosis was earlier at those presenting convulsive seizures in their personal history (Group A and C).
Conclusions: The cerebral lesions, appearing during the development, raise the liability for schizophrenia. The high risk for schizophrenia is correlated with the personal history of epilepsy as well as with the family risk for psychosis.

Background

Schizophrenia is a clinically heterogeneous disorder and given the imperfection of current psychiatric diagnostic systems to capture this heterogeneity, family-based high-risk studies should incorporate large subject sample sizes and effective research strategies in which both schizophrenia patients and their unaffected biological relatives are characterized in terms of both the putative vulnerability marker and the clinical disorder because the relatives of patients without the marker may not be at high risk for developing the subtype of the disorder that is associated with the marker under investigation [11].
According to the neurodevelopmental model of schizophrenia, early pre- or perinatal insults may interfere with normal brain development and entail subtle brain abnormalities (Rapoport et al 2005).
Biological and psychosocial environmental influences bring substantial contribution to the risk of this disorder. 20-30% of the variance in liability to schizophrenia may be due to non-genetic factors. Many environmental risk factors appear to operate before, around or soon after birth.
Increasing research attention was given to the role of cognitive development, neurobiological correlates, including biochemical and EEG studies and the effects of pregnancy and birth complications.
According to the neurodevelopmental model of schizophrenia, the biological onset occurs during fetal neurodevelopment.
The “soft” neurological signs may be a childhood manifestation of a genetic susceptibility to schizophrenia. ”High-risk” studies (offspring of schizophrenic parents) revealed an increased incidence of neurosensory and neuro-motor deficits in the children of schizophrenic mothers [16]. These neurobehavioral impairments may be early manifestations of the brain lesions [9]. Longitudinal MRI-studies of normal aging have demonstrated a heterogeneous patterns of cortical maturation in the developing brain (Thompson et al, 2005). Frontal and occipital regions have thinner cortex with increasing age, while this has not been shown for temporal regions (Salat et al, 2004).
In a longitudinal study of childhood-onset schizophrenia, over five years, the patients showed reduction of gray matter volume first in parietal, and later in temporal and prefrontal cortical areas compared to the healthy children (Thompson et al,2001).
So that, the psychotic symptoms emerge as a manifestation of these neurobiological dysfunctions.
It is significant to study the UHR (Ultra High Risk populations). The UHR criteria are:
Attenuated symptoms: having experienced sub-threshold (i.e less severe) psychotic symptoms in the past year
Brief limited intermittent psychotic symptoms: having experienced episodes of frank psychotic symptoms for less then a week wich have solved naturally
Trait and state risk factor: have a first degree relative with a psychotic disorder or meet diagnosis for schizotypal personality disorder and have experienced a significant decrease in social functioning over the past year [16].
About 35% of cases detected in this way would subsequently meet diagnostic criteria for psychotic disorder within a year despite interventions (Ruhrman Schultze-Lutter and Klosterkötter, 2003) or about 16% (Yung et al 2009).
There is also extensive evidence wich suggests that this group commonly shows neurobiological markers of psychotic endophenotypes (Pantellis et al, 2009).
The studies, in this field of early intervention in UHR children and adolescents, proved that some developmental, early precursors of the psychosis onset are detectable. This is why, the evaluation of the premorbid functioning is essential and constitutes a base for the early detection and intervention initiatives [2,16].
The investigation of the vulnerability markers in the high risk population is of high interest, because it can bring informations concerning the biological and environmental causes of psychoses. Both schizophrenia and bipolar disorder are heritable, a high rate of those diagnoses being found in the offspring, this is the reason why the psychiatric family history is important to be known for the UHR-ultra high risk patients [9]. The cronic illness course, the progressive grey matter decline during early disease stages formed the basis for research on the Psychosis Risk Syndrome (PRS) known as “Clinical High Risk” (CHR) or “Ultra-High Risk” (UHR) or Prodrome [2,9].
Some valuable studies reported a rate of transition to psychosis in the UHR patients of 41% by 12 months and 50% by 24 months. Other significant studies suggest a conversion rate to psychosis of 64% in the UHR patients [9].
Further studies are needed that evaluate the empirical relationships among different EEG abnormalities in schizophrenia and the relationships of the individual EEG abnormalities to neuroimaging, neurocognitive, biochemical and molecular genetic data obtained from the same subjects [1,3,4].
Studies utilizing the EEG in conjunction with other research tools will ultimately lead to a more comprehensive description and better understanding of the cognitive and brain functions that are altered in schizophrenia.
The electroencephalogram (EEG) recorded from the human scalp is widely used to study cognitive and brain functions in schizophrenia.
The EEG provides a powerful noninvasive tool for studying the brain mechanisms of attention and information processing in health and disease.
Due to its high temporal resolution, the EEG is ideally suited to examine the rapidly changing patterns of brain activities that underline human cognitive function and dysfunction.
The scalp EEG is believed to reflect mainly the summated postsynaptic potentials from large synchronously activated populations of pyramidal cells in the cerebral cortex. The recorded EEG activities show changes over time, which are often rhythmic or oscillatory in the sense that they alternate regularly. The rhythmic activities in the resting or “spontaneous” EEG are usually divided into several frequency bands (delta: <4 Hz; theta: 4-8 Hz; alpha:8-12 Hz; beta:12-30 Hz; and gamma:30-70 Hz or higher, centered at 40 Hz), which are associated with different behavioral states, ranging from sleep and drowsiness to relaxation and heightened alertness and mental concentration, yet there exists little consensus on the precise frequency limits of each band. The EEG has a well-established value and role in the clinical assessment, diagnosis and management of patients with certain neurological disorders, such as sleep disorders and epilepsy.
The main purpose is to illustrate that these neurophysiological measures can offer valuable quantitative biological markers of basic pathophysiological mechanisms and cognitive dysfunctions in schizophrenia and bipolar disorder, yet they can be utilized to gain deeper theoretical insights into illness etiology and pathophysiology and may lead to improvements in early detection and more effective and targeted treatment of schizophrenia [12].
Electroencephalography (EEG) measures ongoing electrical brain activity, and provides a possible basis for endo-phenotypes of brain function associated with psychosis (Blackwood et al, 2001, Sumich et al 2006, Hall et al 2011). Several such measures are highly heritable (Tang et al 2007) [5, 6, 10, 14, 17].
Relatively little research has been conducted on resting QEEG activity in patients with psychosis, especially in populations at-risk for the illness and results have been inconsistent and sometimes even contradictory (Gross et al 2006; Boutros et al, 2008). Nonetheless, psychotic patients generally exhibit increased slow wave QEEG activity in the delta (1-4 Hz) and theta (4-8 Hz) bands (Harris et al, 2006,Begic et al, 2011; Hong et al, 2012), and decreased alpha (8-13 Hz) activity (Harris et al, 2006;Begic et al 2011). In terms of resting beta (13-21Hz) activity, results are inconsistent, with studies reporting both decreased (John et al, 1994) and increased (Begic et al, 2011) activity, as well as no abnormalities in patients with psychosis (Hong et al, 2012). It is therefore unclear whether resting QEEG represents a useful endo-phenotype for psychosis, which pleads for the need for further research in this area [4, 7, 8, 13, 18].

Materials and Methods

Through our research, which offered an ethical frame to our daily clinical practice with children and adolescents with schizophrenia and psychosis risk syndrome, we respected the procedural ethics, a notice of acceptance from the ethics committee being obtained.
We considered the ethical foundation of our research, complied with the principles related to the child’s rights, to the respect of the human dignity, the freedom of choice, the right to be informed and tried to solve any possible ethical issues, occurring from the nature of research. In the same time, one of our aims was to ensure the confidentiality and protection of data concerning this vulnerable pediatric population.
The prospective research was performed in the University Hospital of Neurology and Psychiatry for Children and Adolescents, involving 55 children with schizophrenia or UHR for psychosis – Group A, B, C, D and 55 children- healthy controls – Group E). Group A and B (28 children, 16 girls and 12 boys) are diagnosed with schizophrenia and group C and D are UHR for psychosis (27 children, 11 girls and 16 boys) and group E – healthy controls – 27 girls and 28 boys. The UHR-ultra high risk for psychosis children were also referred to our clinic because of their existent psychopathology.
We obtained for each patient under 18 years, the informed consent from the parents/legal guardians and the assent from the child and when the patients turned 18 years we obtained the informed consent signed by them. Our research is in accordance with the Ethical Committee regulations of the University of Medicine and Pharmacy ’Victor Babes’ Timisoara and with the ICH-GCP (Good Clinical Practice) regulations and guidelines. Our followed procedures and the research were in accordance with the ethical standards of the original Helsinki Declaration, revised in 2000.
The 11 children from group A are children with schizophrenia, who had before the schizophrenia onset, cerebral seizures in their personal history. The 17 children from the group B had other psychopathologic disorders pre-morbidly. The C and D groups are represented by the ultra-high risk children for psychosis, having attenuated psychotic symptoms. The C group, represented by 14 children have a personal history of cerebral seizures. The children from the D group represented by 13 children had other psychopathologic disorders before the onset of attenuated psychotic symptoms. The group E, being the healthy control group, is represented by 55 healthy children, 28 boys and 27 girls, who came for EEG evaluation.
In all groups – A, B, C, D, E, the patients were aged between 9 and 18 years.


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Our particular interest was to evaluate the transition of UHR individuals to diagnosable psychosis in a given period of time. Our main focus was to investigate which types of intervention strategies would be most indicated for the UHR population in order to prevent, decline or postpone the transition to diagnosable psychosis.
The aim was to investigate the role, resting QEEG abnormalities play in the etiology of psychosis, and whether it can provide an endo-phenotype for psychosis.
Based on past findings, it was hypothesized that amplitudes in delta and theta frequency bands would be increased, and amplitude in the alpha band would be reduced, in patients with psychosis as well as in populations at risk, compared to healthy controls. In the beta frequency band, no direction of abnormalities was predicted. This study is focused on quantitative EEG (QEEG) at rest, where psychiatric patients have shown abnormal patterns of activity compared to healthy controls. Quantitative EEG amplitudes at rest were compared across four frequency bands between the 4 groups: A, B, C, D.

Results

Group A
Among the 55 children participating in this study, 11 were included in group A (4 girls and 7 boys). The average age of the onset of the first psychotic episode for the girls included in this study was 13.4 years. The onset of schizophrenia was observed around the age of 15 (Fig 1). The average age of the first psychotic episode for the boys was 14 years while the average age for the onset of schizophrenia was 15.2 years. The average age for having their first psychotic episode was 13.7 years, while the average age for the onset of schizophrenia was 15.14 years (Fig 2).

Group B
From the 17 children that were included in group B, 12 were boys and 5 were girls. The average age registered for the onset of the first psychotic episode in girls was 15 while the onset of schizophrenia occurred at an average age of 16 years. The boys from this group had an average age of onset of the first psychotic episode of 15.6, while the average age for the onset of schizophrenia was 17 years. The average age of the children having their first psychotic episode was 15.6 years while the average age of schizophrenia onset of was 16.5 years. A predominant ratio of boys has been observed in the report of group A (boys / girls = 7:4), while in group B the girls were more predominant (boys/girls = 5:12). These results are aligned with the ones from the literature on the subjects, which underlines the predominance of the presence of neurodevelopmental signs in boys. Comparing both the average age of the first psychotic episode (FEP), and the average age of schizophrenia onset for the 2 groups, a younger age has been observed in both cases in group A: 13.7 years FEP in group A, comparing to 15.3 years FEP in group B and 15.14 for schizophrenia for group A versus 16, 5 for schizophrenia for group B.

Group C
This group has been formed by 14 children and adolescents (10 boys and 4 girls) which registered in their personal history convulsive seizures and developed attenuated psychotic symptoms and decrease in their socio-scholar functioning. A gender based distribution can be observed in Fig 3, Fig 4. It can be observed that the average age for the girls is 14.75 and for the boys is 14.1. The average age for the first psychotic symptoms was 14.42.

Group D
Group D is represented by 13 children CHR (High Risk Converters into Psychosis), from which 7 girls and 6 boys, who did not had premorbid seizures, which present the basis of psycho-social functioning. The average age registered in this group was: 15.42 for the girls and 15.33 for the boys. Comparing the average age of the onset of the psychotic symptoms for the C and D groups we can observe that the age is lower for the group C = 14.42 years (group D = 15.37). In both groups registered with convulsive seizures in their personal history – groups A and C, psychotic symptoms appeared earlier than in groups B and D.


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Study groups characteristics

Regarding the positive family history of psychosis, 63, 63% of the group A patients had a parent with Schizophrenia or Bipolar Disorder, 23, 52% of group B. Meanwhile 73, 85% of group C and 30, 23% of group D patients had a positive family history of psychosis. The youngest age of psychosis and schizophrenia onset was registered in patients whose mothers had schizophrenia, especially if the mother’s schizophrenia onset has been registered before the birth date of the child or in the first 2 or 3 years of the child’s life.

EEG results obtained from the study groups

Figures 5, 6, 7 and 8 present the EEG patterns in the A, B, C, D, study groups.
A low voltage appears in 41.81% of cases, with a little increase for the group B. The beta pattern of EEG has been found in 52.72% of the studied results, registering a higher frequency than in group B (18.18%, and 12.72% in group D). Beta frequencies have been found in 9% of group B subjects, appearing predominantly in girls over 16. Theta rhythms have been registered in 49.09% of the EEG`s, with a higher frequency in group C (20 %) and in groups A and B (12.72%). The lowest frequencies of the Theta rhythm belonged to groups D (3.63) and E (2% of the subjects between 9 and 10 years and 1 % of the subjects between 11 and 12 years). Delta rhythms were registered in 25.45% of cases, the higher frequency being observed in group C (10.90%) while the lowest one was registered in group A (9.09%). 2% of cases were between 9 and 10 years and 1% appeared at the age between 11 and 12. Spikes and Waves oscillations have been found in 21.81% of the studied cases, registering the higher frequency in group C (90.9%) and the lowest one in group D (1.81%).
Among the group E, patients registering Spikes and Waves oscillations, 1% were between 9-10 years old and 2% were between 13-14 years old.
The EEG with occipital alpha rhythm has been found in 18.18% of cases with the age between 8-12 years. These results were the most common in group B (7.28%) and the most rare in groups C (3.63%) and A (1.81%). The EEG with occipital alpha rhythm appeared in 37 % of the cases at an age of over 16 years. Monomorphic generalized alpha rhythm appears in our study in 21.81% of cases from which 12.72% in group B and 9.09% in group D. In group E the monomorphic generalized alpha rhythm appears in 30% of cases.

Conclusions

Epilepsy or febrile seizure in an individual increases the risk of schizophrenia.
The epileptic seizures damage the brain and a greater number of seizures results in damage to the brain, severe enough to induce the symptoms and signs of schizophrenia.
The increased risk of schizophrenia is associated with both: a personal history of epilepsy and familial history of psychosis that was stronger.

Conclusions concerning – EEG

We observed:
Generalized patterns of increased theta and delta activity
A decrease dimension complexity => The result of the overall brain dysfunction (seen especially in group B)
Decreased alpha activity and reduced peek alpha frequencies
Paradoxical or “forced” EEG normalization (group C) [15]
Comparing group A and B: there is some reason to suspect that there are two clinical phenotypes of schizophrenia: one phenotype associated with a pattern of longstanding developmental abnormality in which the actual psychotic episode develops after some years of preexisting abnormality. Early onset is associated with a worse outcome (group A).
In the group B the disorder develops in the context of previously normal development.
We also noticed:
From the epileptic seizures, 55% were focal seizures, especially partial complex seizures, so that (temporal lobe epilepsy) would be more likely to influence the risk of schizophrenia.
In 45% of the cases we have seen generalized tonico-clonic convulsive seizures or atypical absence type seizures.
the association between a family history of psychosis in the proband (65% from the cases with family history, had schizophrenia and 35% bipolar disorder with psychotic symptoms).
In our study the early onset (13-15 years) was seen for the children with mothers with schizophrenia especially if the mother’s schizophrenia was diagnosed before the birth of the child
In 70% of the cases in group A, an association between febrile seizures during childhood and schizophrenia.
For the children with febrile seizures in the period 1-3 years, the diagnosis of schizophrenia was put later in the period 16-17 years.

Discussions

This study has implications for the neurodevelopmental model of schizophrenia, which posts that brain damage during development increases the liability to this disorder.
So that, a neurodevelopmental lesion increases the risk for this condition. Epileptic seizures damage the brain.
Evaluating the schizophrenia cases with onset during adolescence, retrospectively, we found (group A) an increased risk for schizophrenia in patients with a history of epilepsy (30% cases).
Future studies aiming to identify the environmental factors, particularly childhood infections or potential genes that predispose both to febrile seizures and schizophrenia may be fruitful. Certain genes that increase the risk of epilepsy might also increase the risk of schizophrenia.
The strengths of our study and the limitations
The prospective observation of the children with convulsive seizures, who have a positive family history of epilepsy is highly needed (limitation)
The evaluation of the cases of children with a family history of epilepsy without a personal history of epilepsy, is one of the strengths of our study.

REFERENCES

  1. Coburn KL, Lauterbach EC, Boutros NN, Black KJ, Arciniegras DB, Coffey CE. The value of quantitative electroencephalography in clinical psychiatry: a report by the committee on research of the American Neuropsychiatric Association. J. Neuropsychiatry Clin. Neurosci. 2006; 18:460-500. [PubMed]
  2. Correll CU, Hauser M, Auther AM, Cornblatt BA. Research in People with the Psychosis Risk Syndrome: A Review of the Current Evidence and Future Directions. J Child Psychol Psychiatry. 2010 April. 51(4): 390-431. doi:10.1111/j.1496-7610.2010.02235.x.
  3. Gross A, Joutsiniemi SL, Rimon R, Appelberg B. Correlation of symptom clusters of schizophrenia with absolute powers of main frequency bands in quantitative EEG. Behav. Brain Funct. 2006; 2 [PMC free article]
  4. Gschwandtner U, Pflueger MO, Semenin V, Gaggiotti M, Riecher-Rossler A, Fuhr P. EEG: a helpful tool in the prediction of psychosis. Eur. Arch. Psychiatry Clin Neurosci.2009; 259:257-262. [PubMed]
  5. Lavoie S, Schafer MR, Whitford TJ, Benninger F, Feuch M, Klier CM, Yuen HP, Pantelis C, McGorry PD, Amminger GP. Frontal delta power associated with negative symptoms in ultra-high risk individuals who transitioned to psychosis. Schizophr.Res.2012;138:206-211.[PubMed]
  6. Merrin EL, Floyd TC. Negative symptoms and EEG alpha in schizophrenia: a replication.Schizophr.Res. 1996;19:151-161.[PubMed]
  7. Qin P, Xu H, Laursen TM, Vestergaard M, Mortesen PB. Risk for schizophrenia and schizophrenia-like psychosis among patients with epilepsy: population-based cohort study. BMJ 2005; 331:23-8.
  8. Ranlund S, Nottage J, Shaikh M, Dutt A, Constante M, Walshe M, Hall MH, Friston K, Murray R, Bramon E. Resting EEG in psychosis and at-risk populations – A possible endophenotype? Schizophr Res. Mar 2014; 153(1-3):96-102.
  9. Ruhrmann S, Schultze-Lutter F, Salokangas RKR, et al. Prediction of psychosis in adolescents and young adults at high risk. Results from the prospective European prediction of psychosis study. Arch Gen Psychiatry. 2010. 67:241-251.
  10. Singh F, Pineda J, Cadenhead KS. Association of impaired EEG mu wave suppression, negative symptoms and social functioning in biological motion processing in first episode of psychosis. Schizophr.Res. 2011;130:182-186.[PubMed]
  11. Thaker G, Carpenter WT. The year in schizophrenia. Volume I. 2007. Clinical Publishing. Oxford Centre for Innovation, Mill Street, Oxford OX2 OJX, UK.
  12. van der Stelt O, Berger A. Application of Electroencephalography to the Study of Cognitive and Brain Functions in Schizophrenia. Schizophrenia Bulletin, vol 33, no. 4, pp 955-970, 2007. doi:10.1093/schbul/sbm016 .
  13. Vestergaard M, Pedersen CB, Christensen J, Madsen DM, Olsen J, Mortesen PB. Febrile seizures and risk of schizophrenia. Schizophr.Res.2010;73:343-9.
  14. Winterer G, Egan MF, Radler T, Hyde T, Coppola R, Weinberger DR. in association between reduced interhemispheric EEG coherence in the temporal lobe and genetic risk for schizophrenia.
  15. Schizophr.Res.2001;49:129-143.[PubMed]
    Wolf P. Acute behavioral symptomatology at disappearance of epileptiform EEG abnormality. Paradoxical or “forced” normalization. Advances in Neurology. 1991, 55:127-142.
  16. Yung AR, Phillips LJ, Yuen HP, McGorry PD. Risk factors for psychosis in an ultra high-risk group: psychopathology and clinical features. Schizophr Res. 2004. 67:131-142.
  17. Zietsch BP, Hansen JL, Hansell NK, Geffen GM, Martin NG, Wright MJ. Common and specific genetic influences on EEG power bands delta, theta, alpha, and beta. Biol. Psychol.2007;75:154-164.[PubMed]
  18. Zimmermann R, Gschwandtner U, Wilhelm FH, Pflueger MO, Riecher-Rossler A, Fuhr P. EEG spectral power and negative symptoms in at-risk individuals predict transition to psychosis. Schizophr.Res.2010;123:208-216.[PubMed]