Morphological Profiling of Schizophrenia: Cluster Analysis of MRI-Based Cortical Thickness Data

Author:

Pan Yunzhi12,Pu Weidan3,Chen Xudong1,Huang Xiaojun1,Cai Yan14,Tao Haojuan1,Xue Zhiming1,Mackinley Michael5,Limongi Roberto56ORCID,Liu Zhening1,Palaniyappan Lena1357

Affiliation:

1. Institute of Mental Health, Second Xiangya Hospital, Central South University, Changsha, PR China

2. Robarts Research Institution, University of Western Ontario, London, Canada

3. Medical Psychological Institute, Second Xiangya Hospital, Central South University, Changsha, PR China

4. The Second People’s Hospital of Hunan Province, Changsha, Hunan, PR China

5. Department of Psychiatry, University of Western Ontario, London, Ontario, Canada

6. Pontificia Universidad Católica de Valparaíso, Región de Valparaíso, Chile

7. Lawson Health Research Institute, London, Ontario, Canada

Abstract

Abstract The diagnosis of schizophrenia is thought to embrace several distinct subgroups. The manifold entities in a single clinical patient group increase the variance of biological measures, deflate the group-level estimates of causal factors, and mask the presence of treatment effects. However, reliable neurobiological boundaries to differentiate these subgroups remain elusive. Since cortical thinning is a well-established feature in schizophrenia, we investigated if individuals (patients and healthy controls) with similar patterns of regional cortical thickness form naturally occurring morphological subtypes. K-means algorithm clustering was applied to regional cortical thickness values obtained from 256 structural MRI scans (179 patients with schizophrenia and 77 healthy controls [HCs]). GAP statistics revealed three clusters with distinct regional thickness patterns. The specific patterns of cortical thinning, clinical characteristics, and cognitive function of each clustered subgroup were assessed. The three clusters based on thickness patterns comprised of a morphologically impoverished subgroup (25% patients, 1% HCs), an intermediate subgroup (47% patients, 46% HCs), and an intact subgroup (28% patients, 53% HCs). The differences of clinical features among three clusters pertained to age-of-onset, N-back performance, duration exposure to treatment, total burden of positive symptoms, and severity of delusions. Particularly, the morphologically impoverished group had deficits in N-back performance and less severe positive symptom burden. The data-driven neuroimaging approach illustrates the occurrence of morphologically separable subgroups in schizophrenia, with distinct clinical characteristics. We infer that the anatomical heterogeneity of schizophrenia arises from both pathological deviance and physiological variance. We advocate using MRI-guided stratification for clinical trials as well as case–control investigations in schizophrenia.

Funder

The China Precision Medicine Initiative

National Natural Science Foundation of China

Publisher

Oxford University Press (OUP)

Subject

Psychiatry and Mental health

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