Filip Spaniel
@nudz.cz
National Institute of Mental Health
National Institute of Mental Health
RESEARCH INTERESTS
schizophrenia
Scopus Publications
Scopus Publications
Patrik Svancer, Vaclav Capek, Antonin Skoch, Miloslav Kopecek, Kristyna Vochoskova, Marketa Fialova, Petra Furstova, Lea Jakob, Eduard Bakstein, Marian Kolenic,et al.
Springer Science and Business Media LLC
Abstract Background Lateral ventricular enlargement represents a canonical morphometric finding in chronic patients with schizophrenia; however, longitudinal studies elucidating complex dynamic trajectories of ventricular volume change during critical early disease stages are sparse. Methods We measured lateral ventricular volumes in 113 first-episode schizophrenia patients (FES) at baseline visit (11.7 months after illness onset, SD = 12.3) and 128 age- and sex-matched healthy controls (HC) using 3T MRI. MRI was then repeated in both FES and HC one year later. Results Compared to controls, ventricular enlargement was identified in 18.6% of patients with FES (14.1% annual ventricular volume (VV) increase; 95%CI: 5.4; 33.1). The ventricular expansion correlated with the severity of PANSS-negative symptoms at one-year follow-up (p = 0.0078). Nevertheless, 16.8% of FES showed an opposite pattern of statistically significant ventricular shrinkage during ≈ one-year follow-up (-9.5% annual VV decrease; 95%CI: -23.7; -2.4). There were no differences in sex, illness duration, age of onset, duration of untreated psychosis, body mass index, the incidence of Schneiderian symptoms, or cumulative antipsychotic dose among the patient groups exhibiting ventricular enlargement, shrinkage, or no change in VV. Conclusion Both enlargement and ventricular shrinkage are equally present in the early stages of schizophrenia. The newly discovered early reduction of VV in a subgroup of patients emphasizes the need for further research to understand its mechanisms.
Andrea Slováková, Jan Kúdelka, Antonín Škoch, Lea Jakob, Markéta Fialová, Petra Fürstová, Eduard Bakštein, Lucie Bankovská Motlová, Pavel Knytl, and Filip Španiel
Elsevier BV
Andrea Slováková, Jan Kúdelka, Antonín Škoch, Lea Jakob, Markéta Fialová, Petra Fürstová, Eduard Bakštein, Lucie Bankovská Motlová, Pavel Knytl, and Filip Španiel
Elsevier BV
Foivos Georgiadis, Sara Larivière, David Glahn, L. Elliot Hong, Peter Kochunov, Bryan Mowry, Carmel Loughland, Christos Pantelis, Frans A. Henskens, Melissa J. Green,et al.
Springer Science and Business Media LLC
AbstractSchizophrenia is a prototypical network disorder with widespread brain-morphological alterations, yet it remains unclear whether these distributed alterations robustly reflect the underlying network layout. We tested whether large-scale structural alterations in schizophrenia relate to normative structural and functional connectome architecture, and systematically evaluated robustness and generalizability of these network-level alterations. Leveraging anatomical MRI scans from 2439 adults with schizophrenia and 2867 healthy controls from 26 ENIGMA sites and normative data from the Human Connectome Project (n = 207), we evaluated structural alterations of schizophrenia against two network susceptibility models: (i) hub vulnerability, which examines associations between regional network centrality and magnitude of disease-related alterations; (ii) epicenter mapping, which identifies regions whose typical connectivity profile most closely resembles the disease-related morphological alterations. To assess generalizability and specificity, we contextualized the influence of site, disease stages, and individual clinical factors and compared network associations of schizophrenia with that found in affective disorders. Our findings show schizophrenia-related cortical thinning is spatially associated with functional and structural hubs, suggesting that highly interconnected regions are more vulnerable to morphological alterations. Predominantly temporo-paralimbic and frontal regions emerged as epicenters with connectivity profiles linked to schizophrenia’s alteration patterns. Findings were robust across sites, disease stages, and related to individual symptoms. Moreover, transdiagnostic comparisons revealed overlapping epicenters in schizophrenia and bipolar, but not major depressive disorder, suggestive of a pathophysiological continuity within the schizophrenia-bipolar-spectrum. In sum, cortical alterations over the course of schizophrenia robustly follow brain network architecture, emphasizing marked hub susceptibility and temporo-frontal epicenters at both the level of the group and the individual. Subtle variations of epicenters across disease stages suggest interacting pathological processes, while associations with patient-specific symptoms support additional inter-individual variability of hub vulnerability and epicenters in schizophrenia. Our work outlines potential pathways to better understand macroscale structural alterations, and inter- individual variability in schizophrenia.
Eliška Kosová, Dita Pajuelo, Iveta Fajnerová, David Greguš, Martin Brunovský, Pavla Stopková, Antonín Škoch, Petra Fürstová, Filip Španiel, and Jiří Horáček
Springer Science and Business Media LLC
Abstract Background The main aim of the present study is to determine the role of metabolites observed using proton magnetic resonance spectroscopy (1H-MRS) in obsessive-compulsive disorder (OCD). As the literature describing biochemical changes in OCD yields conflicting results, we focused on accurate metabolite quantification of total N-acetyl aspartate (tNAA), total creatine (tCr), total choline-containing compounds (tCh), and myo-inositol (mI) in the anterior cingulate cortex (ACC) to capture the small metabolic changes between OCD patients and controls and between OCD patients with and without medication. Methods In total 46 patients with OCD and 46 healthy controls (HC) matched for age and sex were included in the study. The severity of symptoms in the OCD was evaluated on the day of magnetic resonance imaging (MRI) using the Yale-Brown Obsessive-Compulsive Scale (YBOCS). Subjects underwent 1H-MRS from the pregenual ACC (pgACC) region to calculate concentrations of tNAA, tCr, tCho, and mI. Twenty-eight OCD and 28 HC subjects were included in the statistical analysis. We compared differences between groups for all selected metabolites and in OCD patients we analyzed the relationship between metabolite levels and symptom severity, medication status, age, and the duration of illness. Results Significant decreases in tCr (U = 253.00, p = 0.022) and mI (U = 197.00, p = 0.001) in the pgACC were observed in the OCD group. No statistically significant differences were found in tNAA and tCho levels; however, tCho revealed a trend towards lower concentrations in OCD patients (U = 278.00, p = 0.062). Metabolic concentrations showed no significant correlations with the age and duration of illness. The correlation statistics found a significant negative correlation between tCr levels and YBOCS compulsions subscale (cor = -0.380, p = 0.046). tCho and YBOCS compulsions subscale showed a trend towards a negative correlation (cor = -0.351, p = 0.067). Analysis of subgroups with or without medication showed no differences. Conclusions Patients with OCD present metabolic disruption in the pgACC. The decrease in tCr shows an important relationship with OCD symptomatology. tCr as a marker of cerebral bioenergetics may also be considered as a biomarker of the severity of compulsions. The study failed to prove that metabolic changes correlate with the medication status or the duration of illness. It seems that a disruption in the balance between these metabolites and their transmission may play a role in the pathophysiology of OCD.
Barbora Keřková, Karolína Knížková, Monika Večeřová, Petra Šustová, Petra Fürstová, Aleš Hrubý, Filip Španiel, and Mabel Rodriguez
Elsevier BV
Nerisa Banaj, Daniela Vecchio, Fabrizio Piras, Pietro De Rossi, Juan Bustillo, Simone Ciufolini, Paola Dazzan, Marta Di Forti, Erin W. Dickie, Judith M. Ford,et al.
Springer Science and Business Media LLC
AbstractConverging evidence suggests that schizophrenia (SZ) with primary, enduring negative symptoms (i.e., Deficit SZ (DSZ)) represents a distinct entity within the SZ spectrum while the neurobiological underpinnings remain undetermined. In the largest dataset of DSZ and Non-Deficit (NDSZ), we conducted a meta-analysis of data from 1560 individuals (168 DSZ, 373 NDSZ, 1019 Healthy Controls (HC)) and a mega-analysis of a subsampled data from 944 individuals (115 DSZ, 254 NDSZ, 575 HC) collected across 9 worldwide research centers of the ENIGMA SZ Working Group (8 in the mega-analysis), to clarify whether they differ in terms of cortical morphology. In the meta-analysis, sites computed effect sizes for differences in cortical thickness and surface area between SZ and control groups using a harmonized pipeline. In the mega-analysis, cortical values of individuals with schizophrenia and control participants were analyzed across sites using mixed-model ANCOVAs. The meta-analysis of cortical thickness showed a converging pattern of widespread thinner cortex in fronto-parietal regions of the left hemisphere in both DSZ and NDSZ, when compared to HC. However, DSZ have more pronounced thickness abnormalities than NDSZ, mostly involving the right fronto-parietal cortices. As for surface area, NDSZ showed differences in fronto-parietal-temporo-occipital cortices as compared to HC, and in temporo-occipital cortices as compared to DSZ. Although DSZ and NDSZ show widespread overlapping regions of thinner cortex as compared to HC, cortical thinning seems to better typify DSZ, being more extensive and bilateral, while surface area alterations are more evident in NDSZ. Our findings demonstrate for the first time that DSZ and NDSZ are characterized by different neuroimaging phenotypes, supporting a nosological distinction between DSZ and NDSZ and point toward the separate disease hypothesis.
Kristyna Vochoskova, Sean R. McWhinney, Marketa Fialova, Marian Kolenic, Filip Spaniel, Patrik Svancer, Petra Boron, Yurai Okaji, Pavel Trancik, and Tomas Hajek
Wiley
BACKGROUND
The most common causes of death in schizophrenia are cardiovascular disorders, which are closely related to metabolic syndrome/obesity. To better understand the development of metabolic alterations early in the course of illness, we quantified daily medication exposure in the first days of the first hospitalization for psychosis and related it to changes in weight and metabolic markers.
STUDY DESIGN
We recruited participants with first episode psychosis (FEP, N = 173) during their first psychiatric hospitalization and compared them to controls (N = 204). We prospectively collected weight, body mass index, metabolic markers, and exact daily medication exposure at admission and during hospitalization.
STUDY RESULTS
Individuals with FEP gained on average 0.97 ± 2.26 BMI points or 3.46 ± 7.81 kg of weight after an average of 44.6 days of their first inpatient treatment. Greater antipsychotic exposure was associated with greater BMI increase, but only in people with normal/low baseline BMI. Additional predictors of weight gain included type of medication and duration of treatment. Medication exposure was not directly related to metabolic markers, but higher BMI was associated with higher TGC, TSH, and lower HDL. Following inpatient treatment, participants with FEP had significantly higher BMI, TGC, prolactin, and lower fT4, HDL than controls.
CONCLUSION
During their first admission, people with FEP, especially those with normal/low baseline BMI, showed a rapid and clinically significant weight increase, which was associated with exposure to antipsychotics, and with metabolic changes consistent with metabolic syndrome. These findings emphasize weight monitoring in FEP and suggest a greater need for caution when prescribing metabolically problematic antipsychotics to people with lower BMI.
Dick Schijven, Merel C. Postema, Masaki Fukunaga, Junya Matsumoto, Kenichiro Miura, Sonja M. C. de Zwarte, Neeltje E. M. van Haren, Wiepke Cahn, Hilleke E. Hulshoff Pol, René S. Kahn,et al.
Proceedings of the National Academy of Sciences
Left–right asymmetry is an important organizing feature of the healthy brain that may be altered in schizophrenia, but most studies have used relatively small samples and heterogeneous approaches, resulting in equivocal findings. We carried out the largest case–control study of structural brain asymmetries in schizophrenia, with MRI data from 5,080 affected individuals and 6,015 controls across 46 datasets, using a single image analysis protocol. Asymmetry indexes were calculated for global and regional cortical thickness, surface area, and subcortical volume measures. Differences of asymmetry were calculated between affected individuals and controls per dataset, and effect sizes were meta-analyzed across datasets. Small average case–control differences were observed for thickness asymmetries of the rostral anterior cingulate and the middle temporal gyrus, both driven by thinner left-hemispheric cortices in schizophrenia. Analyses of these asymmetries with respect to the use of antipsychotic medication and other clinical variables did not show any significant associations. Assessment of age- and sex-specific effects revealed a stronger average leftward asymmetry of pallidum volume between older cases and controls. Case–control differences in a multivariate context were assessed in a subset of the data (N = 2,029), which revealed that 7% of the variance across all structural asymmetries was explained by case–control status. Subtle case–control differences of brain macrostructural asymmetry may reflect differences at the molecular, cytoarchitectonic, or circuit levels that have functional relevance for the disorder. Reduced left middle temporal cortical thickness is consistent with altered left-hemisphere language network organization in schizophrenia.
Constantinos Constantinides, Laura K. M. Han, Clara Alloza, Linda Antonella Antonucci, Celso Arango, Rosa Ayesa-Arriola, Nerisa Banaj, Alessandro Bertolino, Stefan Borgwardt, Jason Bruggemann,et al.
Springer Science and Business Media LLC
AbstractSchizophrenia (SZ) is associated with an increased risk of life-long cognitive impairments, age-related chronic disease, and premature mortality. We investigated evidence for advanced brain ageing in adult SZ patients, and whether this was associated with clinical characteristics in a prospective meta-analytic study conducted by the ENIGMA Schizophrenia Working Group. The study included data from 26 cohorts worldwide, with a total of 2803 SZ patients (mean age 34.2 years; range 18–72 years; 67% male) and 2598 healthy controls (mean age 33.8 years, range 18–73 years, 55% male). Brain-predicted age was individually estimated using a model trained on independent data based on 68 measures of cortical thickness and surface area, 7 subcortical volumes, lateral ventricular volumes and total intracranial volume, all derived from T1-weighted brain magnetic resonance imaging (MRI) scans. Deviations from a healthy brain ageing trajectory were assessed by the difference between brain-predicted age and chronological age (brain-predicted age difference [brain-PAD]). On average, SZ patients showed a higher brain-PAD of +3.55 years (95% CI: 2.91, 4.19; I2 = 57.53%) compared to controls, after adjusting for age, sex and site (Cohen’s d = 0.48). Among SZ patients, brain-PAD was not associated with specific clinical characteristics (age of onset, duration of illness, symptom severity, or antipsychotic use and dose). This large-scale collaborative study suggests advanced structural brain ageing in SZ. Longitudinal studies of SZ and a range of mental and somatic health outcomes will help to further evaluate the clinical implications of increased brain-PAD and its ability to be influenced by interventions.
Sean R. McWhinney, Katharina Brosch, Vince D. Calhoun, Benedicto Crespo-Facorro, Nicolas A. Crossley, Udo Dannlowski, Erin Dickie, Lorielle M. F. Dietze, Gary Donohoe, Stefan Du Plessis,et al.
Springer Science and Business Media LLC
Anastasiya Lahutsina, Filip Spaniel, Jana Mrzilkova, Alexandra Morozova, Marek Brabec, Vladimir Musil, and Petr Zach
MDPI AG
Cortical folding of the anterior cingulate cortex (ACC), particularly the cingulate (CS) and the paracingulate (PCS) sulci, represents a neurodevelopmental marker. Deviations in in utero development in schizophrenia can be traced using CS and PCS morphometry. In the present study, we measured the length of CS, PCS, and their segments on T1 MRI scans in 93 patients with first- episode schizophrenia and 42 healthy controls. Besides the length, the frequency and the left-right asymmetry of CS/PCS were compared in patients and controls. Distribution of the CS and PCS morphotypes in patients was different from controls. Parcellated sulcal pattern CS3a in the left hemisphere was longer in patients (53.8 ± 25.7 mm vs. 32.7 ± 19.4 mm in controls, p < 0.05), while in CS3c it was reversed—longer in controls (52.5 ± 22.5 mm as opposed to 36.2 ± 12.9 mm, n.s. in patients). Non parcellated PCS in the right hemisphere were longer in patients compared to controls (19.4 ± 10.2 mm vs. 12.1 ± 12.4 mm, p < 0.001). Therefore, concurrent presence of PCS1 and CS1 in the left hemisphere and to some extent in the right hemisphere may be suggestive of a higher probability of schizophrenia.
Konstantinos N. Fountoulakis, Elena Dragioti, Antonis T. Theofilidis, Tobias Wiklund, Xenofon Atmatzidis, Ioannis Nimatoudis, Erik Thys, Martien Wampers, Luchezar Hranov, Trayana Hristova,et al.
Cambridge University Press (CUP)
AbstractBackgroundThe aim of the current study was to explore the effect of gender, age at onset, and duration on the long-term course of schizophrenia.MethodsTwenty-nine centers from 25 countries representing all continents participated in the study that included 2358 patients aged 37.21 ± 11.87 years with a DSM-IV or DSM-5 diagnosis of schizophrenia; the Positive and Negative Syndrome Scale as well as relevant clinicodemographic data were gathered. Analysis of variance and analysis of covariance were used, and the methodology corrected for the presence of potentially confounding effects.ResultsThere was a 3-year later age at onset for females (P < .001) and lower rates of negative symptoms (P < .01) and higher depression/anxiety measures (P < .05) at some stages. The age at onset manifested a distribution with a single peak for both genders with a tendency of patients with younger onset having slower advancement through illness stages (P = .001). No significant effects were found concerning duration of illness.DiscussionOur results confirmed a later onset and a possibly more benign course and outcome in females. Age at onset manifested a single peak in both genders, and surprisingly, earlier onset was related to a slower progression of the illness. No effect of duration has been detected. These results are partially in accord with the literature, but they also differ as a consequence of the different starting point of our methodology (a novel staging model), which in our opinion precluded the impact of confounding effects. Future research should focus on the therapeutic policy and implications of these results in more representative samples.
Sophie E. Smart, Deborah Agbedjro, Antonio F. Pardiñas, Olesya Ajnakina, Luis Alameda, Ole A. Andreassen, Thomas R.E. Barnes, Domenico Berardi, Sara Camporesi, Martine Cleusix,et al.
Elsevier BV
Antonín Škoch, Barbora Rehák Bučková, Jan Mareš, Jaroslav Tintěra, Pavel Sanda, Lucia Jajcay, Jiří Horáček, Filip Španiel, and Jaroslav Hlinka
Springer Science and Business Media LLC
AbstractThe human brain represents a complex computational system, the function and structure of which may be measured using various neuroimaging techniques focusing on separate properties of the brain tissue and activity. We capture the organization of white matter fibers acquired by diffusion-weighted imaging using probabilistic diffusion tractography. By segmenting the results of tractography into larger anatomical units, it is possible to draw inferences about the structural relationships between these parts of the system. This pipeline results in a structural connectivity matrix, which contains an estimate of connection strength among all regions. However, raw data processing is complex, computationally intensive, and requires expert quality control, which may be discouraging for researchers with less experience in the field. We thus provide brain structural connectivity matrices in a form ready for modelling and analysis and thus usable by a wide community of scientists. The presented dataset contains brain structural connectivity matrices together with the underlying raw diffusion and structural data, as well as basic demographic data of 88 healthy subjects.
Sean R. McWhinney, Katharina Brosch, Vince D. Calhoun, Benedicto Crespo-Facorro, Nicolas A. Crossley, Udo Dannlowski, Erin Dickie, Lorielle M. F. Dietze, Gary Donohoe, Stefan Du Plessis,et al.
Springer Science and Business Media LLC
Sean R. McWhinney, Katharina Brosch, Vince D. Calhoun, Benedicto Crespo-Facorro, Nicolas A. Crossley, Udo Dannlowski, Erin Dickie, Lorielle M. F. Dietze, Gary Donohoe, Stefan Du Plessis,et al.
Springer Science and Business Media LLC
AbstractSchizophrenia is frequently associated with obesity, which is linked with neurostructural alterations. Yet, we do not understand how the brain correlates of obesity map onto the brain changes in schizophrenia. We obtained MRI-derived brain cortical and subcortical measures and body mass index (BMI) from 1260 individuals with schizophrenia and 1761 controls from 12 independent research sites within the ENIGMA-Schizophrenia Working Group. We jointly modeled the statistical effects of schizophrenia and BMI using mixed effects. BMI was additively associated with structure of many of the same brain regions as schizophrenia, but the cortical and subcortical alterations in schizophrenia were more widespread and pronounced. Both BMI and schizophrenia were primarily associated with changes in cortical thickness, with fewer correlates in surface area. While, BMI was negatively associated with cortical thickness, the significant associations between BMI and surface area or subcortical volumes were positive. Lastly, the brain correlates of obesity were replicated among large studies and closely resembled neurostructural changes in major depressive disorders. We confirmed widespread associations between BMI and brain structure in individuals with schizophrenia. People with both obesity and schizophrenia showed more pronounced brain alterations than people with only one of these conditions. Obesity appears to be a relevant factor which could account for heterogeneity of brain imaging findings and for differences in brain imaging outcomes among people with schizophrenia.
Yash Patel, Jean Shin, Christoph Abé, Ingrid Agartz, Clara Alloza, Dag Alnæs, Sonia Ambrogi, Linda A. Antonucci, Celso Arango, Volker Arolt,et al.
Biological Psychiatry Elsevier BV
Lucia Jajcay, David Tomeček, Jiří Horáček, Filip Španiel, and Jaroslav Hlinka
MDPI AG
Graph-theoretical approaches are increasingly used to study the brain and may enhance our understanding of its asymmetries. In this paper, we hypothesize that the structure of the left hemisphere is, on average, more modular. To this end, we analyzed resting-state functional magnetic resonance imaging data of 90 healthy subjects. We computed functional connectivity by Pearson’s correlation coefficient, turned the matrix into an unweighted graph by keeping a certain percentage of the strongest connections, and quantified modularity separately for the subgraph formed by each hemisphere. Our results show that the left hemisphere is more modular. The result is consistent across a range of binarization thresholds, regardless of whether the two hemispheres are thresholded together or separately. This illustrates that graph-theoretical analysis can provide a robust characterization of lateralization of brain functional connectivity.
Mabel Rodriguez, Karolína Knížková, Barbora Keřková, Aneta Siroňová, Petra Šustová, Juraj Jonáš, and Filip Španiel
Elsevier BV
Antonio F. Pardiñas, Sophie E. Smart, Isabella R. Willcocks, Peter A. Holmans, Charlotte A. Dennison, Amy J. Lynham, Sophie E. Legge, Bernhard T. Baune, Tim B. Bigdeli, Murray J. Cairns,et al.
American Medical Association (AMA)
Key Points Question Can common genetic variants be used to differentiate between treatment-resistant schizophrenia (TRS) and other forms of this disorder? Findings Data from this genome-wide association study including 85 490 participants were used to estimate genome-wide single-nucleotide variation effect size differences between individuals with and without TRS, which were compatible with a polygenic model of treatment resistance. Results were used to generate a polygenic risk score, which was significantly associated with TRS status in independent incidence and prevalence samples. Meaning Findings of this study based on common genetic variants indicate that TRS is heritable with a modest but significant single-nucleotide variation–based heritability.
Jakub Schneider, Eduard Bakštein, Marian Kolenič, Pavel Vostatek, Christoph U. Correll, Daniel Novák, and Filip Španiel
Cambridge University Press (CUP)
AbstractBackgroundBipolar disorder (BD) is linked to circadian rhythm disruptions resulting in aberrant motor activity patterns. We aimed to explore whether motor activity alone, as assessed by longitudinal actigraphy, can be used to classify accurately BD patients and healthy controls (HCs) into their respective groups.MethodsNinety-day actigraphy records from 25 interepisode BD patients (ie, Montgomery–Asberg Depression Rating Scale (MADRS) and Young Mania Rating Scale (YMRS) < 15) and 25 sex- and age-matched HCs were used in order to identify latent actigraphic biomarkers capable of discriminating between BD patients and HCs. Mean values and time variations of a set of standard actigraphy features were analyzed and further validated using the random forest classifier.ResultsUsing all actigraphy features, this method correctly assigned 88% (sensitivity = 85%, specificity = 91%) of BD patients and HCs to their respective group. The classification success may be confounded by differences in employment between BD patients and HCs. When motor activity features resistant to the employment status were used (the strongest feature being time variation of intradaily variability, Cohen’s d = 1.33), 79% of the subjects (sensitivity = 76%, specificity = 81%) were correctly classified.ConclusionA machine-learning actigraphy-based model was capable of distinguishing between interepisode BD patients and HCs solely on the basis of motor activity. The classification remained valid even when features influenced by employment status were omitted. The findings suggest that temporal variability of actigraphic parameters may provide discriminative power for differentiating between BD patients and HCs while being less affected by employment status.
Katerina Hirschfeldova, Jiri Cerny, Paulina Bozikova, Viktor Kuchtiak, Tobias Rausch, Vladimir Benes, Filip Spaniel, David Gregus, Jiri Horacek, Ladislav Vyklicky,et al.
MDPI AG
The heritable component of schizophrenia (SCH) as a polygenic trait is represented by numerous variants from a heterogeneous group of genes each contributing a relatively small effect. Various SNPs have already been found and analyzed in genes encoding the NMDAR subunits. However, less is known about genetic variations of genes encoding the AMPA and kainate receptor subunits. We analyzed sixteen iGluR genes in full length to determine the sequence variability of iGluR genes. Our aim was to describe the rate of genetic variability, its distribution, and the co-occurrence of variants and to identify new candidate risk variants or haplotypes. The cumulative effect of genetic risk was then estimated using a simple scoring model. GRIN2A-B, GRIN3A-B, and GRIK4 genes showed significantly increased genetic variation in SCH patients. The fixation index statistic revealed eight intronic haplotypes and an additional four intronic SNPs within the sequences of iGluR genes associated with SCH (p < 0.05). The haplotypes were used in the proposed simple scoring model and moreover as a test for genetic predisposition to schizophrenia. The positive likelihood ratio for the scoring model test reached 7.11. We also observed 41 protein-altering variants (38 missense variants, four frameshifts, and one nonsense variant) that were not significantly associated with SCH. Our data suggest that some intronic regulatory regions of iGluR genes and their common variability are among the components from which the genetic predisposition to SCH is composed.