Large-Scale Fusion of Gray Matter and Resting-State Functional MRI Reveals Common and Distinct Biological Markers across the Psychosis Spectrum in the B-SNIP Cohort.
ABSTRACT: To investigate whether aberrant interactions between brain structure and function present similarly or differently across probands with psychotic illnesses [schizophrenia (SZ), schizoaffective disorder (SAD), and bipolar I disorder with psychosis (BP)] and whether these deficits are shared with their first-degree non-psychotic relatives. A total of 1199 subjects were assessed, including 220 SZ, 147 SAD, 180 psychotic BP, 150 first-degree relatives of SZ, 126 SAD relatives, 134 BP relatives, and 242 healthy controls (1). All subjects underwent structural MRI (sMRI) and resting-state functional MRI (rs-fMRI) scanning. Joint-independent component analysis (jICA) was used to fuse sMRI gray matter and rs-fMRI amplitude of low-frequency fluctuations data to identify the relationship between the two modalities. jICA revealed two significantly fused components. The association between functional brain alteration in a prefrontal-striatal-thalamic-cerebellar network and structural abnormalities in the default mode network was found to be common across psychotic diagnoses and correlated with cognitive function, social function, and schizo-bipolar scale scores. The fused alteration in the temporal lobe was unique to SZ and SAD. The above effects were not seen in any relative group (including those with cluster-A personality). Using a multivariate-fused approach involving two widely used imaging markers, we demonstrate both shared and distinct biological traits across the psychosis spectrum. Furthermore, our results suggest that the above traits are psychosis biomarkers rather than endophenotypes.
Project description:The adaptability of the human brain to the constantly changing environment is reduced in patients with psychotic disorders, leading to impaired cognitive functions. Brain signal complexity, which may reflect adaptability, can be readily quantified via resting-state functional magnetic resonance imaging (fMRI) signals. We hypothesized that resting-state brain signal complexity is altered in psychotic disorders, and is correlated with cognitive impairment.We assessed 156 healthy controls (HC) and 330 probands, including 125 patients with psychotic bipolar disorder (BP), 107 patients with schizophrenia (SZ), 98 patients with schizoaffective disorder (SAD) and 230 of their unaffected first-degree relatives (76 BPR, 79 SADR, and 75 SZR) from four sites of the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) consortium. Using multi-scale entropy analysis, we determined whether patients and/or relatives had pathologic differences in complexity of resting-state fMRI signals toward regularity (reduced entropy in all time scales), or toward uncorrelated randomness (increased entropy in fine time scales that decays as the time scale increases) and how these complexity differences might be associated with cognitive impairment.Compared to HC subjects, proband groups showed either decreased complexity toward regularity or toward randomness. SZ probands showed decreased complexity toward regular signal in hypothalamus, and BP probands in left inferior occipital, right precentral and left superior parietal regions, whereas no brain region with decreased complexity toward regularity was found in SAD probands. All proband groups showed significantly increased brain signal randomness in dorsal and ventral prefrontal cortex (PFC), and unaffected relatives showed no complexity differences in PFC regions. SZ had the largest area of involvement in both dorsal and ventral PFC. BP and SAD probands shared increased brain signal randomness in ventral medial PFC, BP and SZ probands shared increased brain signal randomness in ventral lateral PFC, whereas SAD and SZ probands shared increased brain signal randomness in dorsal medial PFC. Only SZ showed increased brain signal randomness in dorsal lateral PFC. The increased brain signal randomness in dorsal or ventral PFC was weakly associated with reduced cognitive performance in psychotic probands.These observations support the loss of brain complexity hypothesis in psychotic probands. Furthermore, we found significant differences as well as overlaps of pathologic brain signal complexity between psychotic probands by DSM diagnoses, thus suggesting a biological approach to categorizing psychosis based on functional neuroimaging data.
Project description:<h4>Background</h4>We quantified frequency-specific, absolute, and fractional amplitude of low-frequency fluctuations (ALFF/fALFF) across the schizophrenia (SZ)-psychotic bipolar disorder (PBP) psychosis spectrum using resting functional magnetic resonance imaging data from the large BSNIP family study.<h4>Methods</h4>We assessed 242 healthy controls (HC), 547 probands (180 PBP, 220 SZ, and 147 schizoaffective disorder-SAD), and 410 of their first-degree relatives (134 PBPR, 150SZR, and 126 SADR). Following standard preprocessing in statistical parametric mapping (SPM8), we computed absolute and fractional power (ALFF/fALFF) in 2 low-frequency bands: slow-5 (0.01-0.027 Hz) and slow-4 (0.027-0.073 Hz). We evaluated voxelwise post hoc differences across traditional Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition diagnostic categories.<h4>Results</h4>Across ALFF/fALFF, in contrast to HC, BP/SAD showed hypoactivation in frontal/anterior brain regions in the slow-5 band and hypoactivation in posterior brain regions in the slow-4 band. SZ showed consistent hypoactivation in precuneus/cuneus and posterior cingulate across both bands and indices. Increased ALFF/fALFF was noted predominantly in deep subcortical and temporal structures across probands in both bands and indices. Across probands, spatial ALFF/fALFF differences in SAD resembled PBP more than SZ. None of these ALFF/fALFF differences were detected in relatives.<h4>Conclusions</h4>Results suggest ALFF/fALFF is a putative biomarker rather than a familial endophenotype. Overall sensitivity to discriminate proband brain alteration was stronger for fALFF than ALFF. Patterns of differences noted in SAD were more similar to those observed in PBP. Differential effects were noted across the 2 frequency bands, more prominently for BP/SAD compared with SZ, suggesting frequency-sensitive physiologic mechanisms for the former.
Project description:This study examined hippocampal volume as a putative biomarker for psychotic illness in the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) psychosis sample, contrasting manual tracing and semiautomated (FreeSurfer) region-of-interest outcomes. The study sample (n = 596) included probands with schizophrenia (SZ, n = 71), schizoaffective disorder (SAD, n = 70), and psychotic bipolar I disorder (BDP, n = 86); their first-degree relatives (SZ-Rel, n = 74; SAD-Rel, n = 62; BDP-Rel, n = 88); and healthy controls (HC, n = 145). Hippocampal volumes were derived from 3Tesla T1-weighted MPRAGE images using manual tracing/3DSlicer3.6.3 and semiautomated parcellation/FreeSurfer5.1,64bit. Volumetric outcomes from both methodologies were contrasted in HC and probands and relatives across the 3 diagnoses, using mixed-effect regression models (SAS9.3 Proc MIXED); Pearson correlations between manual tracing and FreeSurfer outcomes were computed. SZ (P = .0007-.02) and SAD (P = .003-.14) had lower hippocampal volumes compared with HC, whereas BDP showed normal volumes bilaterally (P = .18-.55). All relative groups had hippocampal volumes not different from controls (P = .12-.97) and higher than those observed in probands (P = .003-.09), except for FreeSurfer measures in bipolar probands vs relatives (P = .64-.99). Outcomes from manual tracing and FreeSurfer showed direct, moderate to strong, correlations (r = .51-.73, P < .05). These findings from a large psychosis sample support decreased hippocampal volume as a putative biomarker for schizophrenia and schizoaffective disorder, but not for psychotic bipolar I disorder, and may reflect a cumulative effect of divergent primary disease processes and/or lifetime medication use. Manual tracing and semiautomated parcellation regional volumetric approaches may provide useful outcomes for defining measurable biomarkers underlying severe mental illness.
Project description:Abnormal neuroanatomic brain networks have been reported in schizophrenia, but their characterization across patients with psychotic disorders, and their potential alterations in nonpsychotic relatives, remain to be clarified. Participants recruited by the Bipolar and Schizophrenia Network for Intermediate Phenotypes consortium included 326 probands with psychotic disorders (107 with schizophrenia (SZ), 87 with schizoaffective disorder (SAD), 132 with psychotic bipolar disorder (BD)), 315 of their nonpsychotic first-degree relatives and 202 healthy controls. Single-subject gray matter graphs were extracted from structural MRI scans, and whole-brain neuroanatomic organization was compared across the participant groups. Compared with healthy controls, psychotic probands showed decreased nodal efficiency mainly in bilateral superior temporal regions. These regions had altered morphological relationships primarily with frontal lobe regions, and their network-level alterations were associated with positive symptoms of psychosis. Nonpsychotic relatives showed lower nodal centrality metrics in the prefrontal cortex and subcortical regions, and higher nodal centrality metrics in the left cingulate cortex and left thalamus. Diagnosis-specific analysis indicated that individuals with SZ had lower nodal efficiency in bilateral superior temporal regions than controls, probands with SAD only exhibited lower nodal efficiency in the left superior and middle temporal gyrus, and individuals with psychotic BD did not show significant differences from healthy controls. Our findings provide novel evidence of clinically relevant disruptions in the anatomic association of the superior temporal lobe with other regions of whole-brain networks in patients with psychotic disorders, but not in their unaffected relatives, suggesting that it is a disease-related trait. Network disorganization primarily involving frontal lobe and subcortical regions in nonpsychotic relatives may be related to familial illness risk.
Project description:Thought disorder (TD) has long been associated with schizophrenia (SZ) and is now widely recognized as a symptom of mania and other psychotic disorders as well. Previous studies have suggested that the TD found in the clinically unaffected relatives of SZ, schizoaffective and bipolar probands is qualitatively similar to that found in the probands themselves. Here, we examine which quantitative measures of TD optimize the distinction between patients with diagnoses of SZ and bipolar disorder with psychotic features (BP) from nonpsychiatric controls (NC) and from each other. In addition, we investigate whether these same TD measures also distinguish their respective clinically unaffected relatives (RelSZ, RelBP) from controls as well as from each other. We find that deviant verbalizations are significantly associated with SZ and are co-familial in clinically unaffected RelSZ, but are dissociated from, and are not co-familial for, BP disorder. In contrast, combinatory thinking was nonspecifically associated with psychosis, but did not aggregate in either group of relatives. These results provide further support for the usefulness of TD for identifying potential non-penetrant carriers of SZ-risk genes, in turn enhancing the power of genetic analyses. These findings also suggest that further refinement of the TD phenotype may be needed in order to be suitable for use in genetic studies of bipolar disorder.
Project description:Several laboratories, including ours, have reported an overrepresentation of craniofacial (CF) anomalies in schizophrenia (SZ). How might this dysmorphology arise in a brain-based disorder? Because the brain and face derive from shared embryologic primordia and morphogenetic forces, maldevelopmental processes may result in both CF and brain dysmorphology.Our approach is 2-pronged. First, we have employed, for the first time in the study of psychiatric disorders, objective measures of CF morphology that utilize an extensive normative database, permitting computation of standardized scores for each subject. Second, we have rendered these findings biologically interpretable by adopting principles of embryology in the analysis of dysmorphology.Dependent measures in this investigation focused on derivatives of specific embryonic primordia and were contrasted among probands with psychotic disorders, their first-degree relatives, and normal controls (NC). Subject groups included patients with a diagnosis of SZ (N = 39) or bipolar (BP) disorder with psychotic features (N = 32), their clinically unaffected relatives (N = 82 and N = 41, respectively), and NC (N = 95) subjects.Anomalies involving derivatives of frontonasal and mandibular embryonic primordia showed a clear association with psychotic illness, as well as familial aggregation in relatives in both diagnostic groups. In contrast, one class of CF anomalies emerged only among SZ probands and their first-degree relatives: dysmorphology arising along the junction of the frontonasal and maxillary prominence derivatives, manifested as marked asymmetries. This class was not overrepresented among the BP patients nor among their relatives, indicating that this dysmorphology appears to be specific to SZ and not a generalized feature of psychosis. We discuss these findings in light of embryologic models that relate brain regions to specific CF areas.
Project description:The corpus callosum has been implicated in the pathogenesis of schizophrenia and bipolar disorder. However, it is unclear whether corpus callosum alterations are related to the underlying familial diathesis for psychotic disorders. We examined the corpus callosum and its subregion volumes and their relationship to cognition, psychotic symptoms, and age in probands with schizophrenia (SZ), psychotic bipolar disorder (PBD), and schizoaffective disorder; their first-degree relatives; and healthy control subjects.We present findings from morphometric and neurocognitive analyses of 1381 subjects (SZ probands, n = 224; PBD probands, n = 190; schizoaffective disorder probands, n = 142; unaffected relatives, n = 483 [SZ relatives, n = 195; PBD relatives, n = 175; schizoaffective disorder relatives, n = 113]; control subjects, n = 342). Magnetization prepared rapid acquisition gradient-echo T1 scans across five sites were obtained using 3-tesla magnets. Image processing was done using FreeSurfer Version 5.1. Neurocognitive function was measured using the Brief Assessment of Cognition in Schizophrenia scale.Anterior and posterior splenial volumes were significantly reduced across the groups. The SZ and PBD probands showed robust and significant reductions, whereas relatives showed significant reductions of intermediate severity. The splenial volumes were positively but differentially correlated with aspects of cognition in the probands and their relatives. Proband groups showed a significant age-related decrease in the volume of the anterior splenium compared with control subjects. Among the psychosis groups, the anterior splenium in probands with PBD showed a stronger correlation with psychotic symptoms, as shown by the Positive and Negative Syndrome Scale. All five subregions showed significantly high familiality.The splenial volumes were significantly reduced across the psychosis dimension. However, this volume reduction impacts cognition and clinical manifestation of the illnesses differentially.
Project description:Disrupted sensory processing is a core feature of psychotic disorders. Auditory paired stimuli (PS) evoke a complex neural response, but it is uncertain which aspects reflect shared and/or distinct liability for the most common severe psychoses, schizophrenia (SZ) and psychotic bipolar disorder (BDP). Evoked time-voltage/time-frequency domain responses quantified with EEG during a typical PS paradigm (S1-S2) were compared among proband groups (SZ [n?=?232], BDP ), their relatives (SZrel , BDPrel ), and healthy participants (H ). Early S1-evoked responses were reduced in SZ and BDP, while later/S2 abnormalities showed SZ/SZrel and BDP/BDPrel specificity. Relatives' effects were absent/small despite significant familiality of the entire auditorineural response. This pattern suggests general and divergent biological pathways associated with psychosis, yet may reflect complications with conditioning solely on clinical phenomenology.
Project description:The investigators compared event-related potential (ERP) amplitudes and event-related oscillations across a broad frequency range during an auditory oddball task using a comprehensive analysis approach to describe shared and unique neural auditory processing characteristics among healthy subjects (HP), schizophrenia probands (SZ) and their first-degree relatives, and bipolar disorder I with psychosis probands (BDP) and their first-degree relatives.This Bipolar-Schizophrenia Network on Intermediate Phenotypes sample consisted of clinically stable SZ (n = 229) and BDP (n = 188), HP (n = 284), first-degree relatives of schizophrenia probands (n = 264), and first-degree relatives of bipolar disorder I with psychosis probands (n = 239). They were administered an auditory oddball task in the electroencephalography environment. Principal components analysis derived data-driven frequency bands evoked power. Spatial principal components analysis reduced ERP and frequency data to component waveforms for each subject. Clusters of time bins with significant group differences on response magnitude were assessed for proband/relative differences from HP and familiality.Nine variables survived a linear discriminant analysis between HP, SZ, and BDP. Of those, two showed evidence (deficit in relatives and familiality) as genetic risk markers more specific to SZ (N1, P3b), one was specific to BDP (P2) and one for psychosis in general (N2).This study supports for both shared and unique deficits in early sensory and late cognitive processing across psychotic diagnostic groups. Additional ERP and time-frequency component alterations (frontal N2/P2, late high, early, mid, and low frequency) may provide insight into deficits in underlying neural architecture and potential protective/compensatory mechanisms in unaffected relatives.
Project description:Schizophrenia (SZ), bipolar disorder (BP) and schizoaffective disorder (SAD) share some common symptoms, and there is still a debate about whether SAD is an independent category. To the best of our knowledge, no study has been done to differentiate these three disorders or to investigate the distinction of SAD as an independent category using fMRI data. This study is aimed to explore biomarkers from resting-state fMRI networks for differentiating these disorders and investigate the relationship among these disorders based on fMRI networks with an emphasis on SAD. Firstly, a novel group ICA method, group information guided independent component analysis (GIG-ICA), was applied to extract subject-specific brain networks from fMRI data of 20 healthy controls (HC), 20 SZ patients, 20 BP patients, 20 patients suffering from SAD with manic episodes (SADM), and 13 patients suffering from SAD with depressive episodes exclusively (SADD). Then, five-level one-way analysis of covariance and multiclass support vector machine recursive feature elimination were employed to identify discriminative regions from the networks. Subsequently, the t-distributed stochastic neighbor embedding (t-SNE) projection and the hierarchical clustering were implemented to investigate the relationship among those groups. Finally, to evaluate the generalization ability, 16 new subjects were classified based on the found regions and the trained model using original 93 subjects. Results show that the discriminative regions mainly included frontal, parietal, precuneus, cingulate, supplementary motor, cerebellar, insula and supramarginal cortices, which performed well in distinguishing different groups. SADM and SADD were the most similar to each other, although SADD had greater similarity to SZ compared to other groups, which indicates that SAD may be an independent category. BP was closer to HC compared with other psychotic disorders. In summary, resting-state fMRI brain networks extracted via GIG-ICA provide a promising potential to differentiate SZ, BP, and SAD.