Elena I. Ivleva

Identification of Distinct Psychosis Biotypes Using Brain-Based Biomarkers

OBJECTIVE Clinical phenomenology remains the primary means for classifying psychoses despite considerable evidence that this method incompletely captures biologically meaningful differentiations. Rather than relying on clinical diagnoses as the gold standard, this project drew on neurobiological heterogeneity among psychosis cases to delineate subgroups independent of their phenomenological manifestations. METHOD A large biomarker panel (neuropsychological, stop signal, saccadic control, and auditory stimulation paradigms) characterizing diverse aspects of brain function was collected on individuals with schizophrenia, schizoaffective disorder, and bipolar disorder with psychosis (N=711), their first-degree relatives (N=883), and demographically comparable healthy subjects (N=278). Biomarker variance across paradigms was exploited to create nine integrated variables that were used to capture neurobiological variance among the psychosis cases. Data on external validating measures (social functioning, structural magnetic resonance imaging, family biomarkers, and clinical information) were collected. RESULTS Multivariate taxometric analyses identified three neurobiologically distinct psychosis biotypes that did not respect clinical diagnosis boundaries. The same analysis procedure using clinical DSM diagnoses as the criteria was best described by a single severity continuum (schizophrenia worse than schizoaffective disorder worse than bipolar psychosis); this was not the case for biotypes. The external validating measures supported the distinctiveness of these subgroups compared with clinical diagnosis, highlighting a possible advantage of neurobiological versus clinical categorization schemes for differentiating psychotic disorders. CONCLUSIONS These data illustrate how multiple pathways may lead to clinically similar psychosis manifestations, and they provide explanations for the marked heterogeneity observed across laboratories on the same biomarker variables when DSM diagnoses are used as the gold standard.

Genetics and intermediate phenotypes of the schizophrenia-bipolar disorder boundary

Categorization of psychotic illnesses into schizophrenic and affective psychoses remains an ongoing controversy. Although Kraepelinian subtyping of psychosis was historically beneficial, modern genetic and neurophysiological studies do not support dichotomous conceptualization of psychosis. Evidence suggests that schizophrenia and bipolar disorder rather present a clinical continuum with partially overlapping symptom dimensions, neurophysiology, genetics and treatment responses. Recent large scale genetic studies have produced inconsistent findings and exposed an urgent need for re-thinking phenomenology-based approach in psychiatric research. Epidemiological, linkage and molecular genetic studies, as well as studies in intermediate phenotypes (neurocognitive, neurophysiological and anatomical imaging) in schizophrenia and bipolar disorders are reviewed in order to support a dimensional conceptualization of psychosis. Overlapping and unique genetic and intermediate phenotypic signatures of the two psychoses are comprehensively recapitulated. Alternative strategies which may be implicated into genetic research are discussed.

Comparing genes and phenomenology in the major psychoses: schizophrenia and bipolar 1 disorder.

For the last several decades, diagnosis in psychiatry has been rule based, related to phenomenology and standardized. It has given psychiatry an unearned advantage in communicating about its illnesses, unearned because the molecular basis for this standardization has remained elusive. However, it has provided a language for successful communication about psychiatric syndromes and supported practical functions for which categorization is helpful; functions as disparate as insurance reimbursement and drug development have been enabled with this language. Moreover, this standardization has had additional practical advantages beyond communication and labeling, specifically in terms of public familiarity. Further, these standardized categories have been postulated without any real knowledge about the biological nature of the underlying brain disturbances or their mechanisms. Imagine categorizing diabetes by phenomenology before 1922 or infectious disease before the microscope and antibiotics. It is hard to intuit how one might successfully use nonspecific illness descriptors of phenomenology to sort affected individuals into homogeneous enough categories to discover molecular disease mechanisms, whether the diseases involve disorders of the pancreas, heart, or brain. In psychiatry, despite the practical importance of the Diagnostic and Statistical Manual of Mental Disorder (DSM) nomenclature, the diagnostic system remains a hypothesis of disease categories, awaiting a refinement of categorization based on mechanisms and molecules. Not that we should be persuaded to discard this current system, until another one, more biologically based, is in place. But, because this current system may not provide the final correct illness categories, it may be time to experiment with other systems, within research indications. In this context, scientists and clinicians alike have developed an informed skepticism, whose goal is to promote mechanism-oriented research into the major psychoses with the goal of defining the mechanistic basis of the brain diseases with cognitive and affective expression. There is consistent evidence that genes contribute to the etiology of psychosis. Recent findings from genetic studies provide evidence for an overlap in genetic susceptibility across the traditional psychosis categories. Candidate genes show strong associations with component symptom complexes, such as psychosis, that are not projected directly onto Kraepelinian disease entities. Genetic studies suggest that psychosis may be conceptualized as a clinical phenotype with specific genetic etiologies. Hypothetically genes or sets of genes, interacting with environmental factors, may predetermine vulnerability to psychosis. Depending on additional syndrome-specific genetic influence and environmental interactions, psychosis may coexist with other clinical phenotypes, eg, mood symptoms or cognitive dysfunction, composing categorical diagnoses. This conceptualization of psychosis is well illustrated by epidemiological and molecular genetic studies. In this chapter, we will review the phenomenology and genetics of psychosis, across different diagnoses. Other aspects of the psychosis overlap will be presented in other articles in this volume.

Hippocampal Volume Is Reduced in Schizophrenia and Schizoaffective Disorder But Not in Psychotic Bipolar I Disorder Demonstrated by Both Manual Tracing and Automated Parcellation (FreeSurfer)

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.

Cognitive endophenotypes of psychosis within dimension and diagnosis

This study sought to characterize the psychosis phenotype, contrasting cognitive features within traditional diagnosis and psychosis dimension in a family sample containing both schizophrenia and psychotic bipolar I disorder. Seventy-six probands with psychosis [44 probands with schizophrenia, 32 probands with psychotic bipolar I disorder] and 55 first-degree relatives [30 relatives of schizophrenia probands, 25 relatives of bipolar probands] were recruited. Standardized clinical and neuropsychological measures were administered. No differences in cognitive performance emerged between probands with schizophrenia and probands with psychotic bipolar disorder, or between relatives of probands with schizophrenia and relatives of probands with bipolar disorder in the domains of working and declarative memory, executive function and attention. Relatives overall showed higher cognitive performance compared to probands, as expected. However, when we segmented the probands and relatives along a psychosis dimension, independent of diagnostic groups, results revealed lower cognitive performance in probands compared to relatives without psychosis spectrum disorders, whereas relatives with psychosis spectrum disorders showed an intermediate level of performance across all cognitive domains. In this study, cognitive performance did not distinguish either probands or their first-degree relatives within traditional diagnostic groups (schizophrenia and psychotic bipolar disorder), but distinguished probands and relatives with and without lifetime psychosis manifestations independent of diagnostic categories. These data support the notion that schizophrenia and psychotic bipolar disorder present a clinical continuum with overlapping cognitive features defining the psychosis phenotype.

Brain gray matter phenotypes across the psychosis dimension

This study sought to examine whole brain and regional gray matter (GM) phenotypes across the schizophrenia (SZ)-bipolar disorder psychosis dimension using voxel-based morphometry (VBM 8.0 with DARTEL segmentation/normalization) and semi-automated regional parcellation, FreeSurfer (FS 4.3.1/64 bit). 3T T1 MPRAGE images were acquired from 19 volunteers with schizophrenia (SZ), 16 with schizoaffective disorder (SAD), 17 with psychotic bipolar I disorder (BD-P) and 10 healthy controls (HC). Contrasted with HC, SZ showed extensive cortical GM reductions, most pronounced in fronto-temporal regions; SAD had GM reductions overlapping with SZ, albeit less extensive; and BD-P demonstrated no GM differences from HC. Within the psychosis dimension, BD-P showed larger volumes in fronto-temporal and other cortical/subcortical regions compared with SZ, whereas SAD showed intermediate GM volumes. The two volumetric methodologies, VBM and FS, revealed highly overlapping results for cortical GM, but partially divergent results for subcortical volumes (basal ganglia, amygdala). Overall, these findings suggest that individuals across the psychosis dimension show both overlapping and unique GM phenotypes: decreased GM, predominantly in fronto-temporal regions, is characteristic of SZ but not of psychotic BD-P, whereas SAD display GM deficits overlapping with SZ, albeit less extensive.

Frequency-Specific Neural Signatures of Spontaneous Low-Frequency Resting State Fluctuations in Psychosis: Evidence From Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) Consortium

BACKGROUND 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. METHODS 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. RESULTS 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. CONCLUSIONS 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.

Smooth Pursuit Eye Movement, Prepulse Inhibition, and Auditory Paired Stimuli Processing Endophenotypes Across the Schizophrenia-Bipolar Disorder Psychosis Dimension

BACKGROUND This study examined smooth pursuit eye movement (SPEM), prepulse inhibition (PPI), and auditory event-related potentials (ERP) to paired stimuli as putative endophenotypes of psychosis across the schizophrenia-bipolar disorder dimension. METHODS Sixty-four schizophrenia probands (SZP), 40 psychotic bipolar I disorder probands (BDP), 31 relatives of SZP (SZR), 26 relatives of BDP (BDR), and 53 healthy controls (HC) were tested. Standard clinical characterization, SPEM, PPI, and ERP measures were administered. RESULTS There were no differences between either SZP and BDP or SZR and BDR on any of the SPEM, PPI, or ERP measure. Compared with HC, SZP and BDP had lower SPEM maintenance and predictive pursuit gain and ERP theta/alpha and beta magnitudes to the initial stimulus. PPI did not differ between the psychosis probands and HC. Compared with HC, SZR and BDR had lower predictive pursuit gain and ERP theta/alpha and beta magnitudes to the first stimulus with differences ranging from a significant to a trend level. Neither active symptoms severity nor concomitant medications were associated with neurophysiological outcomes. SPEM, PPI, and ERP scores had low intercorrelations. CONCLUSION These findings support SPEM predictive pursuit and lower frequency auditory ERP activity in a paired stimuli paradigm as putative endophenotypes of psychosis common to SZ and BD probands and relatives. PPI did not differ between the psychosis probands and HC. Future studies in larger scale psychosis family samples targeting putative psychosis endophenotypes and underlying molecular and genetic mediators may aid in the development of biology-based diagnostic definitions.

Alterations in hippocampal connectivity across the psychosis dimension

Recent evidence demonstrates that hippocampal hyperactivity helps mediate psychosis. Using resting state functional magnetic resonance imaging (rsfMRI), we examined hippocampal connectivity alterations in individuals with psychosis (PS) versus healthy controls (HC). Because of its putative greater involvement in psychiatric disorders, we hypothesized that the anterior hippocampus network would show greater dysconnectivity in psychosis. We tested rsfMRI connectivity in 88 PS (including 21 with schizophrenia; 40 with schizoaffective disorder; 27 with psychotic bipolar I disorder) and 65 HC. Seed-based voxel-wise connectivity analyses were carried out using whole, anterior, and posterior hippocampal seeds. No significant differences in functional hippocampal connectivity were found across the three conventional diagnoses. PS were then contrasted with HC, showing strong reductions in anterior hippocampal connectivity to anterior neocortical regions, including medial frontal and anterior cingulate cortices, as well as superior temporal gyrus, precuneus, thalamus and cerebellum. Posterior hippocampal seeds also demonstrated decreased connectivity in PS, with fewer dysconnected regions and a posterior/cerebellar distribution. Whole hippocampal outcomes were consistent with anterior/posterior hippocampal connectivity changes. Connectivity alterations did not correlate with cognition, clinical symptoms, or medication effect variables. Our results suggest a psychosis network of decreased hippocampal connectivity with limbic and frontal contributions, independent of diagnostic categories.

Brain Structure Biomarkers in the Psychosis Biotypes: Findings From the Bipolar-Schizophrenia Network for Intermediate Phenotypes

BACKGROUND The current definitions of psychotic illness lack biological validity, motivating alternative biomarker-driven disease entities. Building on experimental constructs-Biotypes-that were previously developed from cognitive and neurophysiologic measures, we contrast brain anatomy characteristics across Biotypes alongside conventional diagnoses, examining gray matter density (GMD) as an independent validator for the Biotypes. METHODS Whole brain GMD measures were examined in probands, their relatives, and healthy subjects organized by Biotype and then by DSM-IV-TR diagnosis (n = 1409) using voxel-based morphometry with subsequent subject-level regional characterization and distribution analyses. RESULTS Probands grouped by Biotype versus healthy controls showed a stepwise pattern of GMD reductions as follows: Biotype1, extensive and diffusely distributed GMD loss, with the largest effects in frontal, anterior/middle cingulate cortex, and temporal regions; Biotype2, intermediate and more localized reductions, with the largest effects in insula and frontotemporal regions; and Biotype3, small reductions localized to anterior limbic regions. Relatives showed regionally distinct GMD reductions versus healthy controls, with primarily anterior (frontotemporal) effects in Biotype1; posterior (temporo-parieto-cerebellar) in Biotype2; and normal GMD in Biotype3. Schizophrenia and schizoaffective probands versus healthy controls showed overlapping GMD reductions, with the largest effects in frontotemporal and parietal regions; psychotic bipolar probands had small reductions, primarily in frontal regions. GMD changes in relatives followed regional patterns observed in probands, albeit less extensive. Biotypes showed stronger between-group separation based on GMD than the conventional diagnoses and were the strongest predictor of GMD change. CONCLUSIONS GMD biomarkers depicted unique brain structure characteristics within Biotypes, consistent with their cognitive and sensorimotor profiles, and provided stronger discrimination for biologically driven biotypes than symptom-based diagnoses.