Cognitive Profiles and Functional Connectivity in First-Episode Schizophrenia Spectrum Disorders - Linking Behavioral and Neuronal Data
Status PubMed-not-MEDLINE Jazyk angličtina Země Švýcarsko Médium electronic-ecollection
Typ dokumentu časopisecké články
PubMed
31001171
PubMed Central
PMC6454196
DOI
10.3389/fpsyg.2019.00689
Knihovny.cz E-zdroje
- Klíčová slova
- cluster analysis, cognitive deficit, cognitive profiles, first episodes, heterogeneity, resting state functional connectivity, schizophrenia,
- Publikační typ
- časopisecké články MeSH
The character of cognitive deficit in schizophrenia is not clear due to the heterogeneity in research results. In heterogeneous conditions, the cluster solution allows the classification of individuals based on profiles. Our aim was to examine the cognitive profiles of first-episode schizophrenia spectrum disorder (FES) subjects based on cluster analysis, and to correlate these profiles with clinical variables and resting state brain connectivity, as measured with magnetic resonance imaging. A total of 67 FES subjects were assessed with a neuropsychological test battery and on clinical variables. The results of the cognitive domains were cluster analyzed. In addition, functional connectivity was calculated using ROI-to-ROI analysis with four groups: Three groups were defined based on the cluster analysis of cognitive performance and a control group with a normal cognitive performance. The connectivity was compared between the patient clusters and controls. We found different cognitive profiles based on three clusters: Cluster 1: decline in the attention, working memory/flexibility, and verbal memory domains. Cluster 2: decline in the verbal memory domain and above average performance in the attention domain. Cluster 3: generalized and severe deficit in all of the cognitive domains. FES diagnoses were distributed among all of the clusters. Cluster comparisons in neural connectivity also showed differences between the groups. Cluster 1 showed both hyperconnectivity between the cerebellum and precentral gyrus, the salience network (SN) (insula cortex), and fronto-parietal network (FPN) as well as between the PreCG and SN (insula cortex) and hypoconnectivity between the default mode network (DMN) and seeds of SN [insula and supramarginal gyrus (SMG)]; Cluster 2 showed hyperconnectivity between the DMN and cerebellum, SN (insula) and precentral gyrus, and FPN and IFG; Cluster 3 showed hypoconnectivity between the DMN and SN (insula) and SN (SMG) and pallidum. The cluster solution confirms the prevalence of a cognitive decline with different patterns of cognitive performance, and different levels of severity in FES. Moreover, separate behavioral cognitive subsets can be linked to patterns of brain functional connectivity.
3rd Faculty of Medicine Charles University Prague Prague Czechia
Department of Psychology Faculty of Arts Charles University Prague Prague Czechia
Department of Psychology Faculty of Arts Masaryk University Brno Czechia
Department of Psychology Faculty of Social Studies Masaryk University Brno Czechia
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Andreasen N. C., Carpenter W. T., Kane J. M. (2005). Remission in schizophrenia: proposed criteria and rationale for consensus. Am. J. Psychiatry 162 441–449. 10.1176/appi.ajp.162.3.441 PubMed DOI
Andreasen N. C., O’Leary D. S., Cizadlo T., Arndt S., Rezai K., Ponto L. L., et al. (1996). Schizophrenia and cognitive dysmetria: a positron-emission tomography study of dysfunctional prefrontal-thalamic-cerebellar circuitry. Proc. Natl. Acad. Sci. U.S.A. 93 9985–9990. 10.1073/pnas.93.18.9985 PubMed DOI PMC
Behzadi Y., Restom K., Liau J., Liu T. T. (2007). A component based noise correction method (CompCor) for BOLD and perfusion based fMRI. Neuroimage 37 90–101. 10.1016/j.neuroimage.2007.04.042 PubMed DOI PMC
Bonzano L., Roccatagliata L., Ruggeri P., Papaxanthis C., Bove M. (2016). Frontoparietal cortex and cerebellum contribution to the update of actual and mental motor performance during the day. Sci. Rep. 6:30126. 10.1038/srep30126 PubMed DOI PMC
Boorman E. D., Rushworth M. F. (2009). Conceptual representation and the making of new decisions. Neuron 63 721–723. 10.1016/j.neuron.2009.09.014 PubMed DOI
Bora E., Murray R. M. (2014). Meta-analysis of cognitive deficits in ultra-high risk to psychosis and first-episode psychosis: do the cognitive deficits progress over, or after, the onset of psychosis? Schizophr. Bull. 40 744–755. 10.1093/schbul/sbt085 PubMed DOI PMC
Bora E., Yücel M., Pantelis C. H. (2009). Cognitive functioning in schizophrenia, schizoaffective disorder and affective psychoses: meta-analytic study. Br. J. Psychiatry 195 475–482. 10.1192/bjp.bp.108.055731 PubMed DOI
Bora E., Yücel M., Pantelis C. H. (2010). Cognitive impairment in schizophrenia and affective psychoses: implications for DSM-V criteria. Schizophr. Bull. 36 36–42. 10.1093/schbul/sbp094 PubMed DOI PMC
Bowie C. R., Reichenberg A., Patterson T. L., Heaton R. K., Harvey P. D. (2006). Determinants of real-world functional performance in schizophrenia subjects: correlations with cognition, functional capacity, and symptoms. Am. J. Psychiatry 163 418–425. 10.1176/appi.ajp.163.3.418 PubMed DOI
Bressler S. L. (2002). Understanding cognition through large-scale cortical networks. Curr. Dir. Psychol. Sci. 11 58–61. 10.1111/1467-8721.00168 DOI
Bressler S. L., Menon V. (2010). Large-scale brain networks in cognition: emerging methods and principles. Trends Cogn. Sci. 14 277–290. 10.1016/j.tics.2010.04.004 PubMed DOI
Brissenden J. A., Levin E. J., Osher D. E., Halko M. A., Somers D. (2016). Functional evidence for a cerebellar node of the dorsal attention network. J. Neurosci. 36 6083–6096. 10.1523/JNEUROSCI.0344-16.2016 PubMed DOI PMC
Chand G. B., Wu J., Hajjar I., Qui D. (2017). Interactions of the salience network and its subsystems with the default mode and the central executive networks in normal aging and mind cognitive impairment. Brain Connect. 7 401–412. 10.1089/brain.2017.0509 PubMed DOI PMC
Dickinson D., Ragland J. D., Calkins M. E., Gold J. M., Gur R. C. (2006). A comparison of cognitive structure in schizophrenia patients and healthy controls using confirmatory factor analysis. Schizophr. Res. 85 20–29. 10.1016/j.schres.2006.03.003 PubMed DOI PMC
Dong D., Wang Y., Chang X., Luo C., Yao D. (2018). Dysfunction of large scale networks in schizophrenia: a meta-analysis of resting state functional connectivity. Schizophr. Bull. 44 168–181. 10.1093/schbul/sbx034 PubMed DOI PMC
Dragomirecká E., Bartonová J. (2006). WHOQOL-BREF. WHOQOL-100. Příručka pro Uživatele České Verze Dotazníku Kvality Života Světové Zdravotnické Organizace. Praha: Psychiatrické centrum Praha.
Du Y., Fu Z., Calhoun V. D. (2018). Classification and prediction of brain disorders using functional connectivity: promising but challenging. Front. Neurosci. 12:525 10.3389/fnins.2018.00525 PubMed DOI PMC
Fassbender C., Simoes-Franklin C., Murphy K., Hester R., Meaney J., Robertson I. H., et al. (2006). The role of the right fronto-parietal network in cognitive control: common activations for “cues-to-attend” and response inhibition. J. Psychophys. 20 286–296. 10.1027/0269-8803.20.4.286 PubMed DOI
Fatouros-Bergman H., Cervenka S., Flyckt L., Edman G., Farde L. (2014). Meta-analysis of cognitive performance in drug-naive patients with schizophrenia. Schizophr. Res. 158 156–162. 10.1016/j.schres.2014.06.034 PubMed DOI
Fioravanti M., Bianchi V., Cinti M. E. (2012). Cognitive deficits in schizophrenia: an updated metanalysis of the scientific evidence. BMC Psychiatry 12:64. 10.1186/1471-244X-12-64 PubMed DOI PMC
Fornito A., Yoon J., Zalesky A., Bullmore E. T., Carter C. S. (2011). General and specific functional connectivity disturbances in first-episode schizophrenia during cognitive control performance. Biol. Psychiatry 70 64–72. 10.1016/j.biopsych.2011.02.019 PubMed DOI PMC
Fusar-Poli P., Deste G., Smieskova R., Barlati S., Yung A., Howes A., et al. (2012). Cognitive functioning in prodromal psychosis: a meta-analysis. Arch. Gen. Psychiatry 69 562–571. 10.1001/archgenpsychiatry.2011.1592 PubMed DOI
Geisler D., Walton E., Naylor M., Roessner V., Lim K. O., Schulz S. C., et al. (2015). Brain structure and function correlates of cognitive subtypes in schizophrenia. Psychiatry Res. 234 74–83. 10.1016/j.pscychresns.2015.08.008 PubMed DOI PMC
Gilbert E., Merette C., Jomphe V., Emond C., Rouleau N., Bouchard R. H., et al. (2014). Cluster analysis of cognitive deficits may mark heterogeneity in schizophrenia in terms of outcome and response to treatment. Eur. Arch. Psychiatry Clin. Neurosci. 264 333–343. 10.1007/s00406-013-0463-7 PubMed DOI PMC
Goldstein G., Allen D. N., Seaton B. E. (1998). A comparison of clustering solutions for cognitive heterogeneity in schizophrenia. J. Int. Neuropsychol. Soc. 4 353–362. PubMed
Goldstein G., Shemansky W. J. (1995). Influences on cognitive heterogeneity in schizophrenia. Schizophr. Res. 18 59–69. 10.1016/0920-9964(95)00040-2 PubMed DOI
Guo W., Liu F., Chen J., Wu R., Zhan Z., Yu M., et al. (2015). Resting state cerebellar-cerebral networks are differently affected in first episode, drug-naïve schizophrenia patients and unaffected siblings. Sci. Rep. 5:17275. 10.1038/srep17275 PubMed DOI PMC
Guo W., Zhang F., Liu F., Chen J., Wu R., Chen D. Q., et al. (2018). Cerebellar abnormalities in first episode, drug-naive schizophrenia at rest. Psychiatry Res. Neuroimaging 276 73–79. 10.1016/j.pscychresns.2018.03.010 PubMed DOI
He Z., Deng W., Li M., Chen Z., Jiang L., Wang Q., et al. (2013). Aberrant intrinsic brain activity and cognitive deficit in first episode treatment-naive patients with schizophrenia. Psychol. Med. 43 769–780. 10.1017/S0033291712001638 PubMed DOI
Heilbronner U., Samara M., Leucht S., Falkai P., Schulze T. G. (2016). The longitudinal course of schizophrenia across the lifespan: clinical, cognitive, and neurobiological aspects. Harv. Rev. Psychiatry 24 118–128. 10.1097/HRP.0000000000000092 PubMed DOI PMC
Heinrichs R., Zaksanis K. (1998). Neurocognitive deficit in schizophrenia: a quantitative review of the evidence. Neuropsychology 12 426–445. 10.1037/0894-4105.12.3.426 PubMed DOI
Heinrichs R. W., Awad A. G. (1993). Neurocognitive subtypes of chronic schizophrenia. Schizophr. Res. 9 49–58. 10.1016/0920-9964(93)90009-8 PubMed DOI
Heinrichs R. W., Ruttan L., Zakzanis K. K., Case D. (1997). Parsing schizophrenia with neurocognitive tests: evidence of stability and validity. Brain Cogn. 35 207–224. 10.1006/brcg.1997.0938 PubMed DOI
Hill K. S., Ragland J. D., Gur R. C., Gur R. E. (2002). Neuropsychological profiles delineate distinct profiles of schizophrenia, and interaction between memory and executive function, and uneven distribution of clinical subtypes. J. Clin. Exp. Neuropsychol. 24 765–780. 10.1076/jcen.24.6.765.8402 PubMed DOI PMC
Jubault T., Ody C., Koechlin E. (2007). Serial organization of human behaviour in the inferior parietal cortex. J. Neurosci. 27 11028–11036. 10.1523/JNEUROSCI.1986-07.2007 PubMed DOI PMC
Kay S. R., Fiszbein A., Opler L. A. (1987). The positive and negative syndrome scale (PANSS) for schizophrenia. Schizophr. Bull. 1987 261–276. 10.1093/schbul/13.2.261 PubMed DOI
Kim D. J., Bartolomeo L., Bolbecker A., Lundin N., Purcell J., Moussa-Tooks A., et al. (2017). Abnormal cortico-cerebellar resting state connectivity in sensory-motor networks in schizophrenia. Proc. Int. Congr. Schizophr. Res. 43(Suppl. 1):S238. 10.1093/schbul/sbx022.071 DOI
Kobayashi S. (2009). Reward Neurophysiology and Primate Cerebral Cortex/Temporal Cortex in Encyclopedia of Neuroscience, eds Davis J. R., Giles A. C., Rankin C. H., Bell J., Kimura H., Uemura T., et al. (Berlin: Springer; ). 10.1007/978-3-540-29678-2_3 DOI
Kuroki N., Shenton M., Salisbury D. F., Hirayasu Y., Onitsuka T., Hershfield H., et al. (2007). Middle and inferior temporal gyrus gray matter volume abnormalities in first-episode schizophrenia: an MRI study. Am. J. Psychiatry 163 2103–2110. 10.1176/ajp.2006.163.12.2103 PubMed DOI PMC
Lewandowski K. E., Sperry S. H., Cohen B. M., Öngür D. (2014). Cognitive variability in psychotic disorders: a cross-diagnostic cluster analysis. Psychol. Med. 44 3239–3248. 10.1017/S0033291714000774 PubMed DOI PMC
Liang S. G., Greenwood T. A. (2015). The impact of clinical heterogeneity in schizophrenia on genomic analyses. Schizophr. Res. 161 490–495. 10.1016/j.schres.2014.11.019 PubMed DOI PMC
Manoliu A., Meng C., Brandl F., Doll A., Tahmasian M., Scherr M., et al. (2013). Insular dysfunction reflects altered between-network connectivity and severity of negative symptoms in schizophrenia during psychotic remission. Front. Hum. Neurosci. 7:216. 10.3389/fnhum.2013.00216 PubMed DOI PMC
Marques P., Soares J. M., Magalhaes R., Santos N. C., Sousa N. (2015). The bounds of education in the human brain connectome. Sci. Rep. 5:12812. 10.1038/srep12812 PubMed DOI PMC
Mesholam-Gately R. I., Giuliano A. J., Goff K. P., Faraone S. V., Seidman L. J. (2009). Neurocognition in first-episode schizophrenia: a meta-analytic review. Neuropsychology 23 315–336. 10.1037/a0014708 PubMed DOI
Mwansisya T. E., Wang Z., Tao H., Zhang H., Hu A., Guo S., et al. (2013). The diminished interhemispheric connectivity correlates with negative symptoms and cognitive impairment in first-episode schizophrenia. Schizophr. Res. 150 144–150. 10.1016/j.schres.2013.07.018 PubMed DOI
Nelson S., Dosenbach N. U. F., Cohen A. L., Wheeler M. E., Schlaggar B. L. (2010). Role of the anterior insula in task-level control and focal attention. Brain Struct. Funct. 2014 669–680. 10.1007/s00429-010-0260-2 PubMed DOI PMC
Nielsen J. D., Madsen K. H., Wang Z., Liu Z., Friston K. J., Zhou Y. (2017). Working memory modulation in frontoparietal network connectivity in first episode of schizophrenia. Cereb. Cortex 27 3832–3841. 10.1093/cercor/bhx050 PubMed DOI
Nuechterlein K. H., Barch D. M., Gold J. M., Goldberg T. E., Green M. F., Heaton R. K. (2004). Identification of separable cognitive factors in schizophrenia. Schizophr. Res. 72 29–39. 10.1016/j.schres.2004.09.007 PubMed DOI
Nuechterlein K. H., Green M. F., Kern R. S., Baade L. E., Barch D. M., Cohen J. D., et al. (2008). The MATRICS Consensus Cognitive Battery, part 1: test selection, reliability, and validity. Am. J. Psychiatry 165 203–213. 10.1176/appi.ajp.2007.07010042 PubMed DOI
Ohi K., Shimada T., Nemoto K., Kataoka Y., Yasuyama T., Kimura K., et al. (2017). Cognitive clustering in schizophrenia patients, their first-degree relatives and healthy subjects is associated with anterior cingulate cortex volume. Neuroimage Clin. 16 248–256. 10.1016/j.nicl.2017.08.008 PubMed DOI PMC
Onitsuka T., Shenton M., Salsbery D. F., Dickey C. C., Kasai K., Toner S. K., et al. (2004). Middle and inferior temporal gyrus gray matter volume abnormalities in chronic schizophrenia: an fMRI study. Am. J. Psychiatry 161 1603–1611. 10.1176/appi.ajp.161.9.1603 PubMed DOI PMC
Owen M. J., Sawa A., Mortensen P. B. (2016). Schizophrenia. Lancet 388 86–97. 10.1016/S0140-6736(15)01121-6 PubMed DOI PMC
Palaniyappan L., Liddle P. F. (2012). Dissociable morphometric differences of the inferior parietal lobule in schizophrenia. Eur. Arch. Psychiatry Clin. Neurosci. 262 579–587. 10.1007/s00406-012-0314-y PubMed DOI
Quee P. J., Alizadeh B. Z., Aleman A., van den Heuvel E. R. and Group Investigators (2014). Cognitive subtypes in non-affected siblings of schizophrenia patients: characteristics and profile congruency with affected family members. Psychol. Med. 44 395–405. 10.1017/S0033291713000809 PubMed DOI
Rodriguez M., Fajnerová I., Sedláková K., Dorazilová A., Vorácková V., Paštrnák M., et al. (2017). Cluster analysis and correlations between cognitive domains: cognitive performance in a Czech sample of first episodes schizophrenia spectrum disorders - Preliminary results. Psychiatrie 21 4–11.
Rodriguez M., Vorácková V., Knytl P., Šustová P., Dorazilová A., Cvrčková A., et al. (2018). Cognitive profile of healthy siblings of patients with first-episode psychosis as a candidate endophenotype. Nice, France, 03.03.2018 - 06.03.2018. Eur. Psychiatry 48:S129.
Seaton B. E., Allen D. N., Goldstein G., Kelley M. E., van Kammen D. P. (1999). Relations between cognitive and symptom profile heterogeneity in schizophrenia. J. Nerv. Ment. Dis. 187 414–419. 10.1097/00005053-199907000-00004 PubMed DOI
Seaton B. E., Goldstein G., Allen D. N. (2001). Sources of heterogeneity in schizophrenia: the role of neuropsychological functioning. Neuropsychol. Rev. 11 45–67. 10.1023/A:1009013718684 PubMed DOI
Seidman L. J., Rosso I. M., Thermenos H. W., Markis N., Juelish R., Gabrieli J. D. (2014). Medial temporal lobe default mode functioning and hippocampal structure as vulnerability indicators for schizophrenia: a MRI study of non-psychotic adolescent first-degree relatives. Schizophr. Res. 159 426–434. 10.1016/j.schres.2014.09.011 PubMed DOI
Sheffield J. M., Barch D. M. (2016). Cognition and resting-state functional connectivity in schizophrenia. Neurosci. Biobehav. Rev. 61 108–120. 10.1016/neubiorev.2015.12.007 PubMed DOI PMC
Skudlarski P., Jagannathan K., Anderson K., Stevens M. C., Calhoun V. D., Skudlarska B. A., et al. (2010). Brain connectivity is not only lower but different in schizophrenia: a combined anatomical and functional approach. Biol. Psychiatry 68 61–69. 10.1016/j.biopsych.2010.03.035 PubMed DOI PMC
Stephan K. E., Mattout J., David O., Friston K. J. (2006). Models of functional neuroimaging data. Curr. Med. Imaging Rev. 2 15–34. 10.2174/157340506775541659 PubMed DOI PMC
Stoeckel C., Gough P. M., Watkins K. E., Delvin J. T. (2009). Supramarginal gyrus involvement in visual word recognition. Cortex 45 1091–1096. 10.1016/j.cortex.2008.12.004 PubMed DOI PMC
Szöke A., Trandafir A., Dupont M., Méary A., Schürhoff F., Leboyer M. (2008). Longitudinal studies of cognition in schizophrenia: meta-analysis. Br. J. Psychiatry 192 248–257. 10.1192/bjp.bp.106.029009 PubMed DOI
Tandon R., Nasrallah H. A., Keshavan M. S. (2009). Schizophrenia, “just the facts” 4. Clinical features and conceptualization. Schizophr. Res. 110 1–23. 10.1016/j.schres.2009.03.005 PubMed DOI
Tian Y., Zalesky A., Bousman C., Everall I., Pantelis C. (2018). Insula functional connectivity in schizophrenia: subregions, gradients and symptoms. Biol. Psychiatry 10.1016/j.bpsc.2018.12.003 [Epub ahead of print]. PubMed DOI
Tops M., Boksem M. A. S. (2011). A potential role of the inferior frontal gyrus and anterior insula in cognitive control, brain rhythms, and event-related potentials. Front. Psychol. 2:330. 10.3389/fpsyg.2011.00330 PubMed DOI PMC
Uren J., Cotton S. M., Killackey E., Saling M. M., Allott K. (2017). Cognitive clusters in first-episode psychosis: overlap with healthy controls and relationship to concurrent and prospective symptoms and functioning. Neuropsychology 31 787–797. 10.1037/neu0000367 PubMed DOI
Volavka J., Vevera J. (2018). Very long-term outcome of schizophrenia. Int. J. Clin. Pract. 72:e13094. 10.1111/ijcp.13094 PubMed DOI
Wang H. L., Huang H., Chen C., Li P. F., Zhou Y., Jiang T. Z. (2015). Aberrant functional connectivity within and across the default mode, central-executive and salience network in patients with schizophrenia: a resting state fMRI study. Eur. Psychiatry 30(Suppl. 1):253. 10.1016/j.pnpbp.2017.07.007 PubMed DOI
Whitfield-Gabrieli S., Nieto-Castanon A. (2012). Conn: a functional connectivity toolbox for correlated and anticorrelated brain networks. Brain Connect. 2 125–141. 10.1089/brain.2012.0073 PubMed DOI
The WHOQOL Group (1998). Development of the World Health Organization WHOQOL-BREF quality of life assessment. Psychol. Med. 28 551–558. PubMed
Wölwer W., Brinkmeyer J., Riesbeck M., Freimüller L., Klimke A., Wagner A., et al. (2008). Neuropsychological impairments predict the clinical course in schizophrenia. Eur. Arch. Psychiatry Clin. Neurosci. 258 28–34. 10.1007/s00406-008-5006-2 PubMed DOI
Zanto T. P., Gazzaley A. (2013). Fronto-parietal network: flexible hub of cognitive control. Trends Cogn. Sci. 33 16268–16274. 10.1016/j.tics.2013.10.001 PubMed DOI PMC
Zhou L., Pu W., Wang J., Liu H., Wu G., Liu C., et al. (2016). Inefficient DMN suppression in schizophrenia patients with impaired cognitive function but not patients with preserved cognitive function. Sci. Rep. 6:21657. 10.1038/srep21657 PubMed DOI PMC