4.6 Article

Joint analysis of cognitive and circadian variation in Schizophrenia and Bipolar I Disorder

Journal

ASIAN JOURNAL OF PSYCHIATRY
Volume 38, Issue -, Pages 96-101

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.ajp.2017.11.006

Keywords

Schizophrenia; Bipolar disorder; Circadian rhythm; Cognitive function; Cluster analysis; Clinical severity

Categories

Funding

  1. National Institute of Health, NIH (A Neurobehavioral Family Study of Schizophrenia) [NIH R01MH063480]
  2. National Institute of Health, NIH (Tri National Training Program in Psychiatric Genetics Fogarty International Center) [D43TW008302]
  3. National Institute of Health, NIH (Training Program for Psychiatric Genetics in India) [5D43 TW006167-02]
  4. Central Council for Research in Yoga and Naturopathy, AYUSH
  5. MoHFW, India [12-1/CCRYN/2005-2006/Res.P-III]

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Background: Impairment in cognitive variables and alterations in circadian function have been documented among patients with schizophrenia (SZ) and bipolar I disorder (BP1), but it is not known whether joint analysis of these variables can define clinically relevant sub-groups in either disorder. Objectives: To evaluate the pattern and relationship of cognitive and circadian function in SZ and BP1 patients with respect to diagnosis and indices of clinical severity. Methods: Among patients with SZ and BP1, cognitive function was evaluated using the Penn Computerized Neurocognitive Battery and circadian function was assessed using the Composite Scale of Morningness/Eveningness (CSM). Clinical severity was estimated using the Global Assessment of Function (GAF) scale, and age at onset of illness (AAO). The patients were compared with community based non-psychotic control individuals and non-psychotic first degree relatives of the SZ patients. The cluster distributions of cognitive function, circadian function and clinical severity were investigated and identified clusters compared across diagnostic groups. Results: Across participants, the cognitive domains could be separated into two clusters. Cluster 1 included the majority of control individuals and non-psychotic relatives, while SZ patients predominated in Cluster 2. BP1 patients were distributed across both clusters. The clusters could be differentiated by GAF scores, but not AAO. CSM scores were not significantly correlated with individual cognitive domains or with the clusters. Conclusions: Clusters based on levels of cognitive function can discriminate SZ patients from control individuals, but not BP1 patients. CSM scores do not contribute to such discrimination.

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