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1. Using brain structural neuroimaging measures to predict psychosis onset for individuals at clinical high-risk.

Author

Zhu, Yinghan, Maikusa, Norihide, Radua, Joaquim, Sämann, Philipp, Fusar-Poli, Paolo, Agartz, Ingrid, Andreassen, Ole, Bachman, Peter, Baeza, Inmaculada, Chen, Xiaogang, Choi, Sunah, Corcoran, Cheryl, Ebdrup, Bjørn, Fortea, Adriana, Garani, Ranjini, Glenthøj, Birte, Glenthøj, Louise, Haas, Shalaila, Hamilton, Holly, Hayes, Rebecca, He, Ying, Heekeren, Karsten, Kasai, Kiyoto, Katagiri, Naoyuki, Kim, Minah, Kristensen, Tina, Kwon, Jun, Lawrie, Stephen, Lebedeva, Irina, Lee, Jimmy, Loewy, Rachel, Mathalon, Daniel, McGuire, Philip, Mizrahi, Romina, Mizuno, Masafumi, Møller, Paul, Nemoto, Takahiro, Nordholm, Dorte, Omelchenko, Maria, Raghava, Jayachandra, Røssberg, Jan, Rössler, Wulf, Salisbury, Dean, Sasabayashi, Daiki, Smigielski, Lukasz, Sugranyes, Gisela, Takahashi, Tsutomu, Tamnes, Christian, Tang, Jinsong, Theodoridou, Anastasia, Tomyshev, Alexander, Uhlhaas, Peter, Værnes, Tor, van Amelsvoort, Therese, Waltz, James, Westlye, Lars, Zhou, Juan, Thompson, Paul, Hernaus, Dennis, Jalbrzikowski, Maria, and Koike, Shinsuke

Subjects
Humans, Psychotic Disorders, Magnetic Resonance Imaging, Male, Female, Brain, Neuroimaging, Adult, Young Adult, Machine Learning, Adolescent, Prodromal Symptoms
Abstract

Machine learning approaches using structural magnetic resonance imaging (sMRI) can be informative for disease classification, although their ability to predict psychosis is largely unknown. We created a model with individuals at CHR who developed psychosis later (CHR-PS+) from healthy controls (HCs) that can differentiate each other. We also evaluated whether we could distinguish CHR-PS+ individuals from those who did not develop psychosis later (CHR-PS-) and those with uncertain follow-up status (CHR-UNK). T1-weighted structural brain MRI scans from 1165 individuals at CHR (CHR-PS+, n = 144; CHR-PS-, n = 793; and CHR-UNK, n = 228), and 1029 HCs, were obtained from 21 sites. We used ComBat to harmonize measures of subcortical volume, cortical thickness and surface area data and corrected for non-linear effects of age and sex using a general additive model. CHR-PS+ (n = 120) and HC (n = 799) data from 20 sites served as a training dataset, which we used to build a classifier. The remaining samples were used external validation datasets to evaluate classifier performance (test, independent confirmatory, and independent group [CHR-PS- and CHR-UNK] datasets). The accuracy of the classifier on the training and independent confirmatory datasets was 85% and 73% respectively. Regional cortical surface area measures-including those from the right superior frontal, right superior temporal, and bilateral insular cortices strongly contributed to classifying CHR-PS+ from HC. CHR-PS- and CHR-UNK individuals were more likely to be classified as HC compared to CHR-PS+ (classification rate to HC: CHR-PS+, 30%; CHR-PS-, 73%; CHR-UNK, 80%). We used multisite sMRI to train a classifier to predict psychosis onset in CHR individuals, and it showed promise predicting CHR-PS+ in an independent sample. The results suggest that when considering adolescent brain development, baseline MRI scans for CHR individuals may be helpful to identify their prognosis. Future prospective studies are required about whether the classifier could be actually helpful in the clinical settings.

Published
2024

2. Cortical and subcortical neuroanatomical signatures of schizotypy in 3004 individuals assessed in a worldwide ENIGMA study

Author

Kirschner, Matthias, Hodzic-Santor, Benazir, Antoniades, Mathilde, Nenadic, Igor, Kircher, Tilo, Krug, Axel, Meller, Tina, Grotegerd, Dominik, Fornito, Alex, Arnatkeviciute, Aurina, Bellgrove, Mark A, Tiego, Jeggan, Dannlowski, Udo, Koch, Katharina, Hülsmann, Carina, Kugel, Harald, Enneking, Verena, Klug, Melissa, Leehr, Elisabeth J, Böhnlein, Joscha, Gruber, Marius, Mehler, David, DeRosse, Pamela, Moyett, Ashley, Baune, Bernhard T, Green, Melissa, Quidé, Yann, Pantelis, Christos, Chan, Raymond, Wang, Yi, Ettinger, Ulrich, Debbané, Martin, Derome, Melodie, Gaser, Christian, Besteher, Bianca, Diederen, Kelly, Spencer, Tom J, Fletcher, Paul, Rössler, Wulf, Smigielski, Lukasz, Kumari, Veena, Premkumar, Preethi, Park, Haeme RP, Wiebels, Kristina, Lemmers-Jansen, Imke, Gilleen, James, Allen, Paul, Kozhuharova, Petya, Marsman, Jan-Bernard, Lebedeva, Irina, Tomyshev, Alexander, Mukhorina, Anna, Kaiser, Stefan, Fett, Anne-Kathrin, Sommer, Iris, Schuite-Koops, Sanne, Paquola, Casey, Larivière, Sara, Bernhardt, Boris, Dagher, Alain, Grant, Phillip, van Erp, Theo GM, Turner, Jessica A, Thompson, Paul M, Aleman, André, and Modinos, Gemma

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Psychology, Brain Disorders, Neurosciences, Serious Mental Illness, Schizophrenia, Clinical Research, Mental Health, Mental health, Good Health and Well Being, Bipolar Disorder, Female, Humans, Magnetic Resonance Imaging, Male, Psychotic Disorders, Schizotypal Personality Disorder, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

Neuroanatomical abnormalities have been reported along a continuum from at-risk stages, including high schizotypy, to early and chronic psychosis. However, a comprehensive neuroanatomical mapping of schizotypy remains to be established. The authors conducted the first large-scale meta-analyses of cortical and subcortical morphometric patterns of schizotypy in healthy individuals, and compared these patterns with neuroanatomical abnormalities observed in major psychiatric disorders. The sample comprised 3004 unmedicated healthy individuals (12-68 years, 46.5% male) from 29 cohorts of the worldwide ENIGMA Schizotypy working group. Cortical and subcortical effect size maps with schizotypy scores were generated using standardized methods. Pattern similarities were assessed between the schizotypy-related cortical and subcortical maps and effect size maps from comparisons of schizophrenia (SZ), bipolar disorder (BD) and major depression (MDD) patients with controls. Thicker right medial orbitofrontal/ventromedial prefrontal cortex (mOFC/vmPFC) was associated with higher schizotypy scores (r = 0.067, pFDR = 0.02). The cortical thickness profile in schizotypy was positively correlated with cortical abnormalities in SZ (r = 0.285, pspin = 0.024), but not BD (r = 0.166, pspin = 0.205) or MDD (r = -0.274, pspin = 0.073). The schizotypy-related subcortical volume pattern was negatively correlated with subcortical abnormalities in SZ (rho = -0.690, pspin = 0.006), BD (rho = -0.672, pspin = 0.009), and MDD (rho = -0.692, pspin = 0.004). Comprehensive mapping of schizotypy-related brain morphometry in the general population revealed a significant relationship between higher schizotypy and thicker mOFC/vmPFC, in the absence of confounding effects due to antipsychotic medication or disease chronicity. The cortical pattern similarity between schizotypy and schizophrenia yields new insights into a dimensional neurobiological continuity across the extended psychosis phenotype.

Published
2022

3. Neuroanatomical heterogeneity and homogeneity in individuals at clinical high risk for psychosis

Author

Baldwin, Helen, Radua, Joaquim, Antoniades, Mathilde, Haas, Shalaila S, Frangou, Sophia, Agartz, Ingrid, Allen, Paul, Andreassen, Ole A, Atkinson, Kimberley, Bachman, Peter, Baeza, Inmaculada, Bartholomeusz, Cali F, Chee, Michael WL, Colibazzi, Tiziano, Cooper, Rebecca E, Corcoran, Cheryl M, Cropley, Vanessa L, Ebdrup, Bjørn H, Fortea, Adriana, Glenthøj, Louise Birkedal, Hamilton, Holly K, Haut, Kristen M, Hayes, Rebecca A, He, Ying, Heekeren, Karsten, Kaess, Michael, Kasai, Kiyoto, Katagiri, Naoyuki, Kim, Minah, Kindler, Jochen, Klaunig, Mallory J, Koike, Shinsuke, Koppel, Alex, Kristensen, Tina D, Bin Kwak, Yoo, Kwon, Jun Soo, Lawrie, Stephen M, Lebedeva, Irina, Lee, Jimmy, Lin, Ashleigh, Loewy, Rachel L, Mathalon, Daniel H, Michel, Chantal, Mizrahi, Romina, Møller, Paul, Nelson, Barnaby, Nemoto, Takahiro, Nordholm, Dorte, Omelchenko, Maria A, Pantelis, Christos, Raghava, Jayachandra M, Røssberg, Jan I, Rössler, Wulf, Salisbury, Dean F, Sasabayashi, Daiki, Schall, Ulrich, Smigielski, Lukasz, Sugranyes, Gisela, Suzuki, Michio, Takahashi, Tsutomu, Tamnes, Christian K, Tang, Jinsong, Theodoridou, Anastasia, Thomopoulos, Sophia I, Tomyshev, Alexander S, Uhlhaas, Peter J, Værnes, Tor G, van Amelsvoort, Therese AMJ, Van Erp, Theo GM, Waltz, James A, Westlye, Lars T, Wood, Stephen J, Zhou, Juan H, McGuire, Philip, Thompson, Paul M, Jalbrzikowski, Maria, Hernaus, Dennis, and Fusar-Poli, Paolo

Subjects
Serious Mental Illness, Prevention, Biomedical Imaging, Mental Health, Clinical Research, Neurosciences, Brain, Humans, Magnetic Resonance Imaging, Psychotic Disorders, ENIGMA Clinical High Risk for Psychosis Working Group, Clinical Sciences, Public Health and Health Services, Psychology
Abstract

Individuals at Clinical High Risk for Psychosis (CHR-P) demonstrate heterogeneity in clinical profiles and outcome features. However, the extent of neuroanatomical heterogeneity in the CHR-P state is largely undetermined. We aimed to quantify the neuroanatomical heterogeneity in structural magnetic resonance imaging measures of cortical surface area (SA), cortical thickness (CT), subcortical volume (SV), and intracranial volume (ICV) in CHR-P individuals compared with healthy controls (HC), and in relation to subsequent transition to a first episode of psychosis. The ENIGMA CHR-P consortium applied a harmonised analysis to neuroimaging data across 29 international sites, including 1579 CHR-P individuals and 1243 HC, offering the largest pooled CHR-P neuroimaging dataset to date. Regional heterogeneity was indexed with the Variability Ratio (VR) and Coefficient of Variation (CV) ratio applied at the group level. Personalised estimates of heterogeneity of SA, CT and SV brain profiles were indexed with the novel Person-Based Similarity Index (PBSI), with two complementary applications. First, to assess the extent of within-diagnosis similarity or divergence of neuroanatomical profiles between individuals. Second, using a normative modelling approach, to assess the 'normativeness' of neuroanatomical profiles in individuals at CHR-P. CHR-P individuals demonstrated no greater regional heterogeneity after applying FDR corrections. However, PBSI scores indicated significantly greater neuroanatomical divergence in global SA, CT and SV profiles in CHR-P individuals compared with HC. Normative PBSI analysis identified 11 CHR-P individuals (0.70%) with marked deviation (>1.5 SD) in SA, 118 (7.47%) in CT and 161 (10.20%) in SV. Psychosis transition was not significantly associated with any measure of heterogeneity. Overall, our examination of neuroanatomical heterogeneity within the CHR-P state indicated greater divergence in neuroanatomical profiles at an individual level, irrespective of psychosis conversion. Further large-scale investigations are required of those who demonstrate marked deviation.

Published
2022

7. Normative Modeling of Brain Morphometry in Clinical High Risk for Psychosis

Author

Haas, Shalaila S., Ge, Ruiyang, Agartz, Ingrid, Amminger, G. Paul, Andreassen, Ole A., Bachman, Peter, Baeza, Inmaculada, Choi, Sunah, Colibazzi, Tiziano, Cropley, Vanessa L., De La Fuente-Sandoval, Camilo, Ebdrup, Bjørn H., Fortea, Adriana, Fusar-Poli, Paolo, Glenthøj, Birte Yding, Glenthøj, Louise Birkedal, Haut, Kristen M., Hayes, Rebecca A., Heekeren, Karsten, Hooker, Christine I., Hwang, Wu Jeong, Jahanshad, Neda, Kaess, Michael, Kasai, Kiyoto, Katagiri, Naoyuki, Kim, Minah, Kindler, Jochen, Koike, Shinsuke, Kristensen, Tina D., Kwon, Jun Soo, Lawrie, Stephen M., Lebedeva, Irina, Lee, Jimmy, Lemmers-Jansen, Imke L.J., Lin, Ashleigh, Ma, Xiaoqian, Mathalon, Daniel H., McGuire, Philip, Michel, Chantal, Mizrahi, Romina, Mizuno, Masafumi, Møller, Paul, Mora-Durán, Ricardo, Nelson, Barnaby, Nemoto, Takahiro, Nordentoft, Merete, Nordholm, Dorte, Omelchenko, Maria A., Pantelis, Christos, Pariente, Jose C., Raghava, Jayachandra M., Reyes-Madrigal, Francisco, Røssberg, Jan I., Rössler, Wulf, Salisbury, Dean F., Sasabayashi, Daiki, Schall, Ulrich, Smigielski, Lukasz, Sugranyes, Gisela, Suzuki, Michio, Takahashi, Tsutomu, Tamnes, Christian K., Theodoridou, Anastasia, Thomopoulos, Sophia I., Thompson, Paul M., Tomyshev, Alexander S., Uhlhaas, Peter J., Værnes, Tor G., Van Amelsvoort, Therese A.M.J., Van Erp, Theo G.M., Waltz, James A., Wenneberg, Christina, Westlye, Lars T., Wood, Stephen J., Zhou, Juan H., Hernaus, Dennis, Jalbrzikowski, Maria, Kahn, René S., Corcoran, Cheryl M., Frangou, Sophia, Haas, Shalaila S., Ge, Ruiyang, Agartz, Ingrid, Amminger, G. Paul, Andreassen, Ole A., Bachman, Peter, Baeza, Inmaculada, Choi, Sunah, Colibazzi, Tiziano, Cropley, Vanessa L., De La Fuente-Sandoval, Camilo, Ebdrup, Bjørn H., Fortea, Adriana, Fusar-Poli, Paolo, Glenthøj, Birte Yding, Glenthøj, Louise Birkedal, Haut, Kristen M., Hayes, Rebecca A., Heekeren, Karsten, Hooker, Christine I., Hwang, Wu Jeong, Jahanshad, Neda, Kaess, Michael, Kasai, Kiyoto, Katagiri, Naoyuki, Kim, Minah, Kindler, Jochen, Koike, Shinsuke, Kristensen, Tina D., Kwon, Jun Soo, Lawrie, Stephen M., Lebedeva, Irina, Lee, Jimmy, Lemmers-Jansen, Imke L.J., Lin, Ashleigh, Ma, Xiaoqian, Mathalon, Daniel H., McGuire, Philip, Michel, Chantal, Mizrahi, Romina, Mizuno, Masafumi, Møller, Paul, Mora-Durán, Ricardo, Nelson, Barnaby, Nemoto, Takahiro, Nordentoft, Merete, Nordholm, Dorte, Omelchenko, Maria A., Pantelis, Christos, Pariente, Jose C., Raghava, Jayachandra M., Reyes-Madrigal, Francisco, Røssberg, Jan I., Rössler, Wulf, Salisbury, Dean F., Sasabayashi, Daiki, Schall, Ulrich, Smigielski, Lukasz, Sugranyes, Gisela, Suzuki, Michio, Takahashi, Tsutomu, Tamnes, Christian K., Theodoridou, Anastasia, Thomopoulos, Sophia I., Thompson, Paul M., Tomyshev, Alexander S., Uhlhaas, Peter J., Værnes, Tor G., Van Amelsvoort, Therese A.M.J., Van Erp, Theo G.M., Waltz, James A., Wenneberg, Christina, Westlye, Lars T., Wood, Stephen J., Zhou, Juan H., Hernaus, Dennis, Jalbrzikowski, Maria, Kahn, René S., Corcoran, Cheryl M., and Frangou, Sophia

Abstract

Question Are brain morphometric changes that deviate significantly from healthy variation associated with the risk of psychosis? Findings In this case-control study of 1340 individuals at clinical high risk for psychosis and 1237 healthy participants, individual-level variation in macroscale neuromorphometric measures in the group at clinical high risk for psychosis was largely nested within healthy variation and was not associated with the severity of positive symptoms or conversion to a psychotic disorder. Meaning The findings suggest the macroscale neuromorphometric measures have limited utility as diagnostic biomarkers of psychosis risk. Abstract Importance The lack of robust neuroanatomical markers of psychosis risk has been traditionally attributed to heterogeneity. A complementary hypothesis is that variation in neuroanatomical measures in individuals at psychosis risk may be nested within the range observed in healthy individuals. Objective To quantify deviations from the normative range of neuroanatomical variation in individuals at clinical high risk for psychosis (CHR-P) and evaluate their overlap with healthy variation and their association with positive symptoms, cognition, and conversion to a psychotic disorder. Design, Setting, and Participants This case-control study used clinical-, IQ-, and neuroimaging software (FreeSurfer)–derived regional measures of cortical thickness (CT), cortical surface area (SA), and subcortical volume (SV) from 1340 individuals with CHR-P and 1237 healthy individuals pooled from 29 international sites participating in the Enhancing Neuroimaging Genetics Through Meta-analysis (ENIGMA) Clinical High Risk for Psychosis Working Group. Healthy individuals and individuals with CHR-P were matched on age and sex within each recruitment site. Data were analyzed between September 1, 2021, and November 30, 2022. Main Outcomes and Measures For each regional morphometric measure, Importance: The lack of robust neuroanatomical markers of psychosis risk has been traditionally attributed to heterogeneity. A complementary hypothesis is that variation in neuroanatomical measures in individuals at psychosis risk may be nested within the range observed in healthy individuals. Objective: To quantify deviations from the normative range of neuroanatomical variation in individuals at clinical high risk for psychosis (CHR-P) and evaluate their overlap with healthy variation and their association with positive symptoms, cognition, and conversion to a psychotic disorder. Design, Setting, and Participants: This case-control study used clinical-, IQ-, and neuroimaging software (FreeSurfer)-derived regional measures of cortical thickness (CT), cortical surface area (SA), and subcortical volume (SV) from 1340 individuals with CHR-P and 1237 healthy individuals pooled from 29 international sites participating in the Enhancing Neuroimaging Genetics Through Meta-analysis (ENIGMA) Clinical High Risk for Psychosis Working Group. Healthy individuals and individuals with CHR-P were matched on age and sex within each recruitment site. Data were analyzed between September 1, 2021, and November 30, 2022. Main Outcomes and Measures: For each regional morphometric measure, deviation scores were computed as z scores indexing the degree of deviation from their normative means from a healthy reference population. Average deviation scores (ADS) were also calculated for regional CT, SA, and SV measures and globally across all measures. Regression analyses quantified the association of deviation scores with clinical severity and cognition, and 2-proportion z tests identified case-control differences in the proportion of individuals with infranormal (z < -1.96) or supranormal (z > 1.96) scores. Results: Among 1340 individuals with CHR-P, 709 (52.91%) were male, and the mean (SD) age was 20.75 (4.74) years. Among 1237 healthy individuals, 684 (55.30%) were male, and the

Published
2024

8. Model-based testing for space-time interaction using point processes: An application to psychiatric hospital admissions in an urban area

Author

Meyer, Sebastian, Warnke, Ingeborg, Rössler, Wulf, and Held, Leonhard

Subjects
Statistics - Methodology, Physics - Physics and Society, Statistics - Applications
Abstract

Spatio-temporal interaction is inherent to cases of infectious diseases and occurrences of earthquakes, whereas the spread of other events, such as cancer or crime, is less evident. Statistical significance tests of space-time clustering usually assess the correlation between the spatial and temporal (transformed) distances of the events. Although appealing through simplicity, these classical tests do not adjust for the underlying population nor can they account for a distance decay of interaction. We propose to use the framework of an endemic-epidemic point process model to jointly estimate a background event rate explained by seasonal and areal characteristics, as well as a superposed epidemic component representing the hypothesis of interest. We illustrate this new model-based test for space-time interaction by analysing psychiatric inpatient admissions in Zurich, Switzerland (2007-2012). Several socio-economic factors were found to be associated with the admission rate, but there was no evidence of general clustering of the cases., Comment: 21 pages including 4 figures and 5 tables; methods are implemented in the R package surveillance (https://CRAN.R-project.org/package=surveillance)

Published
2015
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16. Who Is Contributing?

Author

Loch, Alexandre Andrade, Rössler, Wulf, Gaebel, Wolfgang, editor, Rössler, Wulf, editor, and Sartorius, Norman, editor

Published
2017
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18. Polygenic risk scores across the extended psychosis spectrum

Author

Smigielski, Lukasz, Papiol, Sergi, Theodoridou, Anastasia, Heekeren, Karsten, Gerstenberg, Miriam, Wotruba, Diana, Buechler, Roman, Hoffmann, Per, Herms, Stefan, Adorjan, Kristina, Anderson-Schmidt, Heike, Budde, Monika, Comes, Ashley L., Gade, Katrin, Heilbronner, Maria, Heilbronner, Urs, Kalman, Janos L., Klöhn-Saghatolislam, Farahnaz, Reich-Erkelenz, Daniela, Schaupp, Sabrina K., Schulte, Eva C., Senner, Fanny, Anghelescu, Ion-George, Arolt, Volker, Baune, Bernhard T., Dannlowski, Udo, Dietrich, Detlef E., Fallgatter, Andreas J., Figge, Christian, Jäger, Markus, Juckel, Georg, Konrad, Carsten, Nieratschker, Vanessa, Reimer, Jens, Reininghaus, Eva, Schmauß, Max, Spitzer, Carsten, von Hagen, Martin, Wiltfang, Jens, Zimmermann, Jörg, Gryaznova, Anna, Flatau-Nagel, Laura, Reitt, Markus, Meyers, Milena, Emons, Barbara, Haußleiter, Ida Sybille, Lang, Fabian U., Becker, Thomas, Wigand, Moritz E., Witt, Stephanie H., Degenhardt, Franziska, Forstner, Andreas J., Rietschel, Marcella, Nöthen, Markus M., Andlauer, Till F. M., Rössler, Wulf, Walitza, Susanne, Falkai, Peter, Schulze, Thomas G., and Grünblatt, Edna

Published
2021
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21. Childhood trauma moderates schizotypy-related brain morphology: analyses of 1182 healthy individuals from the ENIGMA schizotypy working group

Author

Quidé, Yann, primary, Watkeys, Oliver J., additional, Tonini, Emiliana, additional, Grotegerd, Dominik, additional, Dannlowski, Udo, additional, Nenadić, Igor, additional, Kircher, Tilo, additional, Krug, Axel, additional, Hahn, Tim, additional, Meinert, Susanne, additional, Goltermann, Janik, additional, Gruber, Marius, additional, Stein, Frederike, additional, Brosch, Katharina, additional, Wroblewski, Adrian, additional, Thomas-Odenthal, Florian, additional, Usemann, Paula, additional, Straube, Benjamin, additional, Alexander, Nina, additional, Leehr, Elisabeth J., additional, Bauer, Jochen, additional, Winter, Nils R., additional, Fisch, Lukas, additional, Dohm, Katharina, additional, Rössler, Wulf, additional, Smigielski, Lukasz, additional, DeRosse, Pamela, additional, Moyett, Ashley, additional, Houenou, Josselin, additional, Leboyer, Marion, additional, Gilleen, James, additional, Thomopoulos, Sophia I., additional, Thompson, Paul M., additional, Aleman, André, additional, Modinos, Gemma, additional, and Green, Melissa J., additional

Published
2023
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24. Versorgungsstrukturen in der Psychiatrie

Author

Kallert, Thomas, Gühne, Uta, Harter, Christian, Lang, Fabian U., Puschner, Bernd, Riedel-Heller, Steffi G., Weisbrod, Matthias, Becker, Thomas, Rössler, Wulf, Möller, Hans-Jürgen, editor, Laux, Gerd, editor, and Kapfhammer, Hans-Peter, editor

Published
2017
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41. Mismatch negativity generation in subjects at risk for psychosis: source analysis is more sensitive than surface electrodes in risk prediction

Author

Aeberli, Tina, Müller, Mario, Theodoridou, Anastasia, Hagenmuller, Florence, Seifritz, Erich, Walitza, Susanne, Rössler, Wulf, Kawohl, Wolfram, Heekeren, Karsten, Aeberli, Tina, Müller, Mario, Theodoridou, Anastasia, Hagenmuller, Florence, Seifritz, Erich, Walitza, Susanne, Rössler, Wulf, Kawohl, Wolfram, and Heekeren, Karsten

Abstract

Background: Deficits of mismatch negativity (MMN) in patients with schizophrenia have been demonstrated many times and there is growing evidence that alterations of MMN already exist in individuals at risk for psychosis. The present study examines differences in MMN between subjects fulfilling ultra-high risk (UHR) or only basic symptoms criteria and it addresses the question, if MMN source analysis can improve prediction of transition to psychosis. Methods: The MMN to duration, frequency, and intensity deviants was recorded in 50 healthy controls and 161 individuals at risk for psychosis classified into three subgroups: only basic symptoms (n = 74), only ultra-high risk (n = 13) and persons who fulfill both risk criteria (n = 74). Based on a three-source model of MMN generation, we conducted an MMN source analysis and compared the amplitudes of surface electrodes and sources among the three groups. Results: Significant differences in MMN generation among the four groups were revealed at surface electrodes Cz and C4 (p < 0.05) and at the frontal source (p < 0.001) for duration deviant stimuli. The 15 subjects from the risk groups who subsequently developed a manifest psychosis had a significantly lower MMN amplitude at frontal source (p = 0.019) without showing significant differences at surface electrodes. Low activity at frontal MMN source increased the risk of transition to manifest disease by the factor 3.12 in UHR subjects. Conclusion: MMN activity differed significantly between subjects presenting only basic symptoms and subjects which additionally meet UHR criteria. The largest differences between groups as well as between individuals with and without transition were observed at the frontal source. The present results suggest that source analysis is more sensitive than surface electrodes in psychosis risk prediction by MMN.

Published
2023

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