Interactive effects of polygenic risk and cognitive subtype on brain morphology in schizophrenia spectrum and bipolar disorders

Abstract

Grey matter volume (GMV) may be associated with polygenic risk for schizophrenia (PRS-SZ) and severe cognitive deficits in people with schizophrenia, schizoaffective disorder (collectively SSD), and bipolar disorder (BD). This study examined the interactive effects of PRS-SZ and cognitive subtypes of SSD and BD in relation to GMV. Two-step cluster analysis was performed on 146 clinical cases (69 SSD and 77 BD) assessed on eight cognitive domains (verbal and visual memory, executive function, processing speed, visual processing, language ability, working memory, and planning). Among them, 55 BD, 51 SSD, and 58 healthy controls (HC), contributed to focal analyses of the relationships between cognitive subtypes, PRS-SZ and their interaction on GMV. Two distinct cognitive subtypes were evident among the combined sample of cases: a ‘cognitive deficit’ group (CD; N = 31, 20SSD/11BD) showed severe impairment across all cognitive indices, and a ‘cognitively spared’ (CS; N = 75; 31SSD/44BD) group showed intermediate cognitive performance that was significantly worse than the HC group but better than the CD subgroup. A cognitive subgroup-by-PRS-SZ interaction was significantly associated with GMV in the left precentral gyrus. Moderation analyses revealed a significant negative relationship between PRS-SZ and GMV in the CD group only. At low and average (but not high) PRS-SZ, larger precentral GMV was evident in the CD group compared to both CS and HC groups, and in the CS group compared to HCs. This study provides evidence for a relationship between regional GMV changes and PRS-SZ in psychosis spectrum cases with cognitive deficits, but not in cases cognitively spared.

Cortical similarities in psychiatric and mood disorders identified in federated VBM analysis via COINSTAC

“…This study included data from 4,102 individuals: 572 individuals with SZ, 259 individuals with MCI, 147 unaffected relatives of an individual diagnosed with psychosis, 121 individuals with BP, 96 individuals classified as spectrum (further information about this category can be found in the supplemental experimental procedures ), 88 individuals with ASD, 44 individuals diagnosed with MDD, 32 individuals with PTSD, and 2,743 HCs from the following datasets, many previously described in the literature: 1000 BRAINS study (1000BRAINS 88 ), the Australian Schizophrenia Research Bank, 89 Emory University Grady Trauma Project, 90 , 91 , 92 Imaging Genetics in Psychosis, 93 Centre for Healthy Brain Aging-Sydney Memory and Aging Study, 94 Older Australian Twins Study, 95 Cognitive Genetics Collaborative Research Organization consortium, 96 and Bipolar Kids and Sibs-Sydney. 97 Diagnoses were confirmed by clinical physicians at each respective site as part of the study’s protocol (note that in the population-based cohort 1000BRAINS, a dementia screening test was employed to detect individuals with suspected cognitive impairment [DemTect score < 12 98 ]; please refer to the supplemental experimental procedures for more details).…”

Cortical Similarities in Psychiatric and Mood Disorders Identified in Federated VBM Analysis via COINSTAC

“…This study included data from 3,287 individuals; 572 individuals with schizophrenia (SZ), 189 individuals with mild cognitive impairment (MCI), 147 unaffected relatives of an individual diagnosed with psychosis, 121 individuals with bipolar disorder (BP), 96 individuals classified as spectrum (further information about this category can be found in the Supplemental Material), 88 individuals with autism spectrum disorder (ASD), 44 individuals diagnosed with major depressive disorder (MDD), 32 individuals with post-traumatic stress disorder (PTSD), and 1,998 healthy controls (HC) from the following datasets, many previously described in the literature; the Australian Schizophrenia Research Bank (ASRB; Loughland et al, 2010), Emory University Grady Trauma Project (Emory; Fani et al, 2012, 2019; Stevens et al, 2013), Imaging Genetics in Psychosis (IGP; Quidé et al, 2022), Centre for Healthy Brain Aging-Sydney Memory and Aging Study (MAS; Sachdev et al, 2010), Older Australian Twins Study (OATS; Sachdev et al, 2009) Cognitive Genetics Collaborative Research Organization (COCORO consortium; (Koshiyama et al, 2020), and Bipolar Kids and Sibs-Sydney (Sydney; (Roberts et al, 2013). Diagnoses were confirmed by clinical physicians at each respective site as part of the study’s protocol.…”

Polygenic Risk Scores for Bipolar Disorder: Progress and Perspectives

“… 38 Another study also related the cognitive subtypes of SCZ and BD to brain structure, Quidé et al examined the effect of the interaction of SCZ-PRS with two cognitive subtype groups of the schizophrenia spectrum and BD on brain gray matter volume (GMV) and found that higher SCZ-PRS was associated with reduced precentral gyrus volume in both cognitive impairment subgroups. 39 This suggests that our future studies should further explore the common genetic risk for intermediate phenotypes of SCZ, schizoaffective disorder and BD. As the sample size of psychiatric disease genetics increases, the PRS predictive power will become stronger, and other research directions in psychiatric genetics can be expanded on this basis, to provide stronger evidence for psychiatric disease mapping studies.…”