A twin study of schizoaffective-mania, schizoaffective-depression, and other psychotic syndromes

Mental disorders in preadolescent children at familial high-risk of schizophrenia or bipolar disorder - a four-year follow-up study: The Danish High Risk and Resilience Study, VIA 11: The Danish High Risk and Resilience Study, VIA 11

BACKGROUND

Children at familial high-risk of schizophrenia and bipolar disorder have an elevated prevalence of mental disorders but studies of children within a narrow age range are lacking and there are few conjoint studies of these two groups. Knowledge on their mental health is important for prevention and early intervention.

METHODS

The authors examined mental disorders and global functioning in children at familial high-risk of schizophrenia (FHR-SZ) and bipolar disorder (FHR-BP) compared with population-based controls. In a longitudinal cohort study, 450 children (FHR-SZ, n = 171; FHR-BP, n = 104; controls, n = 175), were assessed for Axis I disorders at baseline and four-year follow-up (mean age 11.9, SD 0.2) with the Kiddie Schedule for Affective Disorders and Schizophrenia for School-Age Children and for global functioning with Children's Global Assessment Scale.

RESULTS

Cumulative incidence of Any Axis I disorder was elevated by age 11 in children at FHR-SZ (54.4%, OR 3.0, 95% CI 1.9-4.7, p < .001) and children at FHR-BP (52.9%, OR 2.8, 95% CI 1.7-4.7, p < .001) compared with controls (28.6%). Children at FHR-SZ and FHR-BP had higher rates of affective disorders (OR 4.4, 95% CI 1.4-13.5, p = .009; OR 5.1, 95% CI 1.6-16.4, p = .007), anxiety disorders (OR 2.1, 95% CI 1.1-4.0, p = .02; OR 3.0, 95% CI 1.5-6.1, p = .002), and stress and adjustment disorders (OR 3.3, 95% CI 1.4-7.5, p = .006; OR 5.3, 95% CI 2.2-12.4, p < .001). Disruptive behavior disorders (OR 2.8, 95% CI 1.0-7.3, p = .04) and ADHD (OR 2.9, 95% CI 1.6-5.3, p < .001) were elevated in children at FHR-SZ. Both FHR groups had lower global functioning than controls. Cumulative incidence of disorders increased equally across the three groups from early childhood to preadolescence and level of functioning did not change differentially.

CONCLUSIONS

Children at FHR-SZ and FHR-BP have an elevated prevalence of mental disorders and poorer functioning than controls. Vulnerability in children at FHR manifests early and remains stable throughout childhood. Early attention toward their mental health and identification of those in need of intervention is warranted.

Auditory Oddball Responses Across the Schizophrenia-Bipolar Spectrum and Their Relationship to Cognitive and Clinical Features

OBJECTIVE

Neural activations during auditory oddball tasks may be endophenotypes for psychosis and bipolar disorder. The authors investigated oddball neural deviations that discriminate multiple diagnostic groups across the schizophrenia-bipolar spectrum (schizophrenia, schizoaffective disorder, psychotic bipolar disorder, and nonpsychotic bipolar disorder) and clarified their relationship to clinical and cognitive features.

METHODS

Auditory oddball responses to standard and target tones from 64 sensor EEG recordings were compared across patients with psychosis (total N=597; schizophrenia, N=225; schizoaffective disorder, N=201; bipolar disorder with psychosis, N=171), patients with bipolar disorder without psychosis (N=66), and healthy comparison subjects (N=415) from the second iteration of the Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP2) study. EEG activity was analyzed in voltage and in the time-frequency domain (low, beta, and gamma bands). Event-related potentials (ERPs) were compared with those from an independent sample collected during the first iteration of B-SNIP (B-SNIP1; healthy subjects, N=211; psychosis group, N=526) to establish the repeatability of complex oddball ERPs across multiple psychosis syndromes (r values >0.94 between B-SNIP1 and B-SNIP2).

RESULTS

Twenty-six EEG features differentiated the groups; they were used in discriminant and correlational analyses. EEG variables from the N100, P300, and low-frequency ranges separated the groups along a diagnostic continuum from healthy to bipolar disorder with psychosis/bipolar disorder without psychosis to schizoaffective disorder/schizophrenia and were strongly related to general cognitive function (r=0.91). P50 responses to standard trials and early beta/gamma frequency responses separated the bipolar disorder without psychosis group from the bipolar disorder with psychosis group. P200, N200, and late beta/gamma frequency responses separated the two bipolar disorder groups from the other groups.

CONCLUSIONS

Neural deviations during auditory processing are related to psychosis history and bipolar disorder. There is a powerful transdiagnostic relationship between severity of these neural deviations and general cognitive performance. These results have implications for understanding the neurobiology of clinical syndromes across the schizophrenia-bipolar spectrum that may have an impact on future biomarker research.

Risk Factors, Clinical Features, and Polygenic Risk Scores in Schizophrenia and Schizoaffective Disorder Depressive-Type

There is controversy about the status of schizoaffective disorder depressive-type (SA-D), particularly whether it should be considered a form of schizophrenia or a distinct disorder. We aimed to determine whether individuals with SA-D differ from individuals with schizophrenia in terms of demographic, premorbid, and lifetime clinical characteristics, and genetic liability to schizophrenia, depression, and bipolar disorder. Participants were from the CardiffCOGS sample and met ICD-10 criteria for schizophrenia (n = 713) or SA-D (n = 151). Two samples, Cardiff Affected-sib (n = 354) and Cardiff F-series (n = 524), were used for replication. For all samples, phenotypic data were ascertained through structured interview, review of medical records, and an ICD-10 diagnosis made by trained researchers. Univariable and multivariable logistic regression models were used to compare individuals with schizophrenia and SA-D for demographic and clinical characteristics, and polygenic risk scores (PRS). In the CardiffCOGS, SA-D, compared to schizophrenia, was associated with female sex, childhood abuse, history of alcohol dependence, higher functioning Global Assessment Scale (GAS) score in worst episode of psychosis, lower functioning GAS score in worst episode of depression, and reduced lifetime severity of disorganized symptoms. Individuals with SA-D had higher depression PRS compared to those with schizophrenia. PRS for schizophrenia and bipolar disorder did not significantly differ between SA-D and schizophrenia. Compared to individuals with schizophrenia, individuals with SA-D had higher rates of environmental and genetic risk factors for depression and a similar genetic liability to schizophrenia. These findings are consistent with SA-D being a sub-type of schizophrenia resulting from elevated liability to both schizophrenia and depression.

Auditory paired-stimuli responses across the psychosis and bipolar spectrum and their relationship to clinical features

Background

EEG responses during auditory paired-stimuli paradigms are putative biomarkers of psychosis syndromes. The initial iteration of the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP1) showed unique and common patterns of abnormalities across schizophrenia (SZ), schizoaffective disorder (SAD), and bipolar disorder with psychosis (BDP). This study replicates those findings in new and large samples of psychosis cases and extends them to an important comparison group, bipolar disorder without psychosis (BDNP).

Methods

Paired stimuli responses from 64-sensor EEG recording were compared across psychosis (n = 597; SZ = 225, SAD = 201, BDP = 171), BDNP (n = 66), and healthy (n = 415) subjects from the second iteration of B-SNIP. EEG activity was analyzed in voltage and in the time-frequency domain. Principal component analysis (PCA) over sensors (sPCA) was used to efficiently capture EEG voltage responses to the paired stimuli. Evoked power was calculated via a Morlet wavelet procedure. A frequency PCA divided evoked power data into three frequency bands: Low (4-17 Hz), Beta (18-32 Hz), and Gamma (33-55 Hz). Each time-course (ERP Voltage, Low, Beta, and Gamma) were then segmented into 20 ms bins and analyzed for group differences. To efficiently summarize the multiple EEG components that best captured group differences we used multivariate discriminant and correlational analyses. This approach yields a reduced set of measures that may be useful in subsequent biomarker investigations.

Results

Group ANOVAs identified 17 time-ranges that showed significant group differences (p < .05 after FDR correction), constructively replicating B-SNIP1 findings. Multivariate linear discriminant analysis parsimoniously selected variables that best accounted for group differences: The P50 response to S1 and S2 uniquely separated BDNP from healthy and psychosis subjects (BDNP > all other groups); the S1 N100 response separated groups along an axis of psychopathology severity (HC > BDNP > BDP > SAD > SZ); the S1 P200 response indexed psychosis psychopathology (HC/BDNP > SAD/SZ/BDP); and the preparatory period to the S2 stimulus separated SZ from other groups (SZ > SAD/BDP>HC/BDNP).Canonical correlation identified an association between the neural responses during the S1 N100, S1 N200 and S2 preparatory period and PANSS positive symptoms and social functioning. The neural responses during the S1 P50 and S1 N100 were associated with PANSS Negative/General, MADRS and Young Mania symptoms.

Conclusions

This study constructively replicated prior B-SNIP1 research on auditory deviations observed during the paired stimuli task in SZ, SAD and BDP. Inclusion of a group of BDNP allows for the identification of biomarkers more closely related to affective versus nonaffective clinical phenotypes and neural distinctions between BDP and BDNP. Findings have implications for nosology and future translational work given that some biomarkers are shared across all psychosis and some are unique to affective syndromes.

Lysosomal Diseases and Neuropsychiatry: Opportunities to Rebalance the Mind

The brain is the physical organ of the mind but efforts to understand mental illness within a neurobiological context have hitherto been unavailing. Mental disorders (anxiety, depression, bipolar disorder, and schizophrenia) affect about one fifth of the population and present an almost endless societal challenge at the frontier of human sciences. Prodigious technological advances in functional neuroimaging and large-scale genetics have not yet delivered the prospect of refined molecular understanding of mental illness beyond early anatomical descriptions of brain metabolism. However, intensive clinical phenotyping and quantitative metabolic studies using sophisticated radio-ligands in positron-emission tomography, persistently favor the neurobiological approach. This Perspective pursues a familiar maxim in Medicine, aptly summarized in the words of Arthur Koestler: “Nature is generous in her senseless experiments on mankind.” Hitherto, studies in neuropsychiatry have largely ignored rare genetic disorders but derangements of specific components within the cerebral laboratory offer rich opportunities for mechanistic exploration. Aberrant psychic behavior is characteristic of many inborn errors of metabolism and although each disorder represents a universe of its own, we are at a threshold for understanding, since contemporary genetics and cell biology furnish abundant materials to take on the perturbing enigma of mental derangement. A further development relates to orphan drugs with actions on defined molecular targets: these represent new ways to study the pathogenesis of psychiatric phenomena associated with rare diseases and in a manner not formerly possible. Here we introduce the frontier of schizophrenia and its strong association with late-onset Tay-Sachs disease as a paradigm to explore.

The effects of age and sex on cognitive impairment in schizophrenia: Findings from the Consortium on the Genetics of Schizophrenia (COGS) study

Recently emerging evidence indicates accelerated age-related changes in the structure and function of the brain in schizophrenia, raising a question about its potential consequences on cognitive function. Using a large sample of schizophrenia patients and controls and a battery of tasks across multiple cognitive domains, we examined whether patients show accelerated age-related decline in cognition and whether an age-related effect differ between females and males. We utilized data of 1,415 schizophrenia patients and 1,062 healthy community collected by the second phase of the Consortium on the Genetics of Schizophrenia (COGS-2). A battery of cognitive tasks included the Letter-Number Span Task, two forms of the Continuous Performance Test, the California Verbal Learning Test, Second Edition, the Penn Emotion Identification Test and the Penn Facial Memory Test. The effect of age and gender on cognitive performance was examined with a general linear model. We observed age-related changes on most cognitive measures, which was similar between males and females. Compared to controls, patients showed greater deterioration in performance on attention/vigilance and greater slowness of processing social information with increasing age. However, controls showed greater age-related changes in working memory and verbal memory compared to patients. Age-related changes (η2p of 0.001 to .008) were much smaller than between-group differences (η2p of 0.005 to .037). This study found that patients showed continued decline of cognition on some domains but stable impairment or even less decline on other domains with increasing age. These findings indicate that age-related changes in cognition in schizophrenia are subtle and not uniform across multiple cognitive domains.

Redefining phenotypes to advance psychiatric genetics: Implications from hierarchical taxonomy of psychopathology

Genetic discovery in psychiatry and clinical psychology is hindered by suboptimal phenotypic definitions. We argue that the hierarchical, dimensional, and data-driven classification system proposed by the Hierarchical Taxonomy of Psychopathology (HiTOP) consortium provides a more effective approach to identifying genes that underlie mental disorders, and to studying psychiatric etiology, than current diagnostic categories. Specifically, genes are expected to operate at different levels of the HiTOP hierarchy, with some highly pleiotropic genes influencing higher order psychopathology (e.g., the general factor), whereas other genes conferring more specific risk for individual spectra (e.g., internalizing), subfactors (e.g., fear disorders), or narrow symptoms (e.g., mood instability). We propose that the HiTOP model aligns well with the current understanding of the higher order genetic structure of psychopathology that has emerged from a large body of family and twin studies. We also discuss the convergence between the HiTOP model and findings from recent molecular studies of psychopathology indicating broad genetic pleiotropy, such as cross-disorder SNP-based shared genetic covariance and polygenic risk scores, and we highlight molecular genetic studies that have successfully redefined phenotypes to enhance precision and statistical power. Finally, we suggest how to integrate a HiTOP approach into future molecular genetic research, including quantitative and hierarchical assessment tools for future data-collection and recommendations concerning phenotypic analyses. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Evaluating the Impact of Nonrandom Mating: Psychiatric Outcomes Among the Offspring of Pairs Diagnosed With Schizophrenia and Bipolar Disorder

BACKGROUND

Nonrandom mating has been shown for psychiatric diagnoses, with hypothesized-but not quantified-implications for offspring liability. This national cohort study enumerated the incidence of major psychiatric disorders among the offspring of parent pairs affected with schizophrenia (SCZ) and/or bipolar disorder (BIP) (i.e., dual-affected pairs).

METHODS

Participants were all Swedish residents alive or born between 1968 and 2013 (n = 4,255,196 unique pairs and 8,343,951 offspring). Offspring with dual-affected, single-affected, and unaffected parents were followed (1973-2013) for incidence of broad psychiatric disorders. Primary outcomes included hazard ratio (HR) and cumulative incidence for SCZ and BIP in the offspring. Additional outcomes included any neuropsychiatric, anxiety, depressive, personality, or substance use disorders. Cumulative incidences of SCZ and BIP were used to inform heritability models for these disorders.

RESULTS

Hazards were highest within disorder (e.g., offspring of dual-SCZ pairs had sharply raised hazards for SCZ [HR = 55.3]); however, they were significantly raised for all diagnoses (HR range = 2.89-11.84). Incidences were significantly higher for the majority of outcomes, with 43.4% to 48.5% diagnosed with "any" disorder over follow-up. Risks were retained, with modest attenuations, for the offspring of heterotypic pairs. The estimated heritability of liability for SCZ (h2 = 0.62, 95% confidence interval = 0.55-0.70) and BIP (h2 = 0.52, 95% confidence interval = 0.46-0.58) did not differ significantly from estimates derived from single-affected parents.

CONCLUSIONS

Risks for a broad spectrum of psychiatric diagnoses are significantly raised in the offspring of dual-affected parents, in line with expectations from a polygenic model of liability to disease risk. How these risks may contribute to population maintenance of these disorders is considered.

Meta-analysis of genomic variants and gene expression data in schizophrenia suggests the potential need for adjunctive therapeutic interventions for neuropsychiatric disorders

Schizophrenia (SZ) is a debilitating mental illness with a multigenic aetiology and significant heritability. Despite extensive genetic studies, the molecular aetiology has remained enigmatic. A recent systems biology study suggested a protein-protein interaction network for SZ with 504 novel interactions. The onset of psychiatric disorders is predominant during adolescence, often accompanied by subtle structural abnormalities in multiple regions of the brain. The availability of BrainSpan Atlas data allowed us to re-examine the genes present in the SZ interactome as a function of space and time. The availability of genomes of healthy centenarians and nonpsychiatric Exome Aggregation Consortium database allowed us to identify the variants of criticality. The expression of the SZ candidate genes responsible for cognition and disease onset was studied in different brain regions during particular developmental stages. A subset of novel interactors detected in the network was further validated using gene expression data of post-mortem brains of patients with psychiatric illness. We have narrowed down the list of drug targets proposed by theprevious interactome study to 10 proteins. These proteins belonging to 81 biological pathways are targeted by 34 known Food and Drug Administration-approved drugs that have distinct potential for the treatment of neuropsychiatric disorders. We also report the possibility of targeting key genes belonging to celecoxib pharmacodynamics, Gα signalling and cGMP-PKG signalling pathwaysthat are not known to be specific to SZ aetiology.

The schizophrenia and bipolar twin study in Sweden (STAR)

The schizophrenia and bipolar twin study in Sweden (STAR) is a large nation-wide cohort of monozygotic (MZ) and dizygotic (DZ) same-sex twins with schizophrenia or bipolar disorder and healthy control pairs, extensively characterized with brain imaging, neuropsychological tests, biomarkers, genetic testing, psychiatric symptoms and personality traits. The purpose is to investigate genetic and environmental mechanisms that give rise to schizophrenia and bipolar disorder as well as the intermediate phenotypes. This article describes the design, recruitment, data collection, measures, collected twins' characteristics, diagnostic procedures as well as ongoing and planned analyses. Identification of biomarkers, genetic and epigenetic variation and the development of specific and common endophenotypes for schizophrenia and bipolar disorder are potential gains from this cohort.

Diagnostic Accuracy of the CASI-4R Psychosis Subscale for Children Evaluated in Pediatric Outpatient Clinics

Diagnostic accuracy of the Diagnostic and Statistical Manual of Mental Disorders-oriented Child and Adolescent Symptom Inventory (CASI-4R) Psychotic Symptoms scale was tested using receiver operating characteristic analyses to identify clinically significant psychotic symptoms. Participants were new outpatients (N = 700), ages 6.0 to 12.9 years (M = 9.7, SD = 1.8) at 9 child outpatient mental health clinics, who participated in the Longitudinal Assessment of Manic Symptoms (LAMS) Study baseline assessment. Because LAMS undersampled participants with low mania scores by design, present analyses weighted low scorers to produce unbiased estimates. Psychotic symptoms, operationally defined as a score of 3 or more for hallucinations or 4 or more for delusions based on the Schedule for Affective Disorders and Schizophrenia (K-SADS) psychosis items, occurred in 7% of youth. K-SADS diagnoses for those identified with psychotic symptoms above threshold included major depressive disorder, bipolar spectrum disorder, attention deficit/hyperactivity disorder, posttraumatic stress disorder, psychotic disorders, and autism spectrum disorder. The optimal psychosis screening cut score (maximizing sensitivity and specificity) was 2.75+ (corresponding diagnostic likelihood ratio [DiLR] = 4.29) for the parent version and 3.50+ (DiLR = 5.67) for the teacher version. The Area under the Curve for parent and teacher report was .83 and .74 (both p < .001). Parent report performed significantly better than teacher report for identifying psychotic symptoms above threshold (p = .03). The CASI-4R Psychosis subscale (J) appears clinically useful for identifying psychotic symptoms in children because of its brevity and accuracy.

Interrater reliability of schizoaffective disorder compared with schizophrenia, bipolar disorder, and unipolar depression - A systematic review and meta-analysis

Schizoaffective disorder is a common diagnosis in clinical practice but its nosological status has been subject to debate ever since it was conceptualized. Although it is key that diagnostic reliability is sufficient, schizoaffective disorder has been reported to have low interrater reliability. Evidence based on systematic review and meta-analysis methods, however, is lacking. Using a highly sensitive literature search in Medline, Embase, and PsycInfo we identified studies measuring the interrater reliability of schizoaffective disorder in comparison to schizophrenia, bipolar disorder, and unipolar disorder. Out of 4126 records screened we included 25 studies reporting on 7912 patients diagnosed by different raters. The interrater reliability of schizoaffective disorder was moderate (meta-analytic estimate of Cohen's kappa 0.57 [95% CI: 0.41-0.73]), and substantially lower than that of its main differential diagnoses (difference in kappa between 0.22 and 0.19). Although there was considerable heterogeneity, analyses revealed that the interrater reliability of schizoaffective disorder was consistently lower in the overwhelming majority of studies. The results remained robust in subgroup and sensitivity analyses (e.g., diagnostic manual used) as well as in meta-regressions (e.g., publication year) and analyses of publication bias. Clinically, the results highlight the particular importance of diagnostic re-evaluation in patients diagnosed with schizoaffective disorder. They also quantify a widely held clinical impression of lower interrater reliability and agree with earlier meta-analysis reporting low test-retest reliability.

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.

Top 10 Replicated Findings From Behavioral Genetics

In the context of current concerns about replication in psychological science, we describe 10 findings from behavioral genetic research that have replicated robustly. These are "big" findings, both in terms of effect size and potential impact on psychological science, such as linearly increasing heritability of intelligence from infancy (20%) through adulthood (60%). Four of our top 10 findings involve the environment, discoveries that could have been found only with genetically sensitive research designs. We also consider reasons specific to behavioral genetics that might explain why these findings replicate.

A Danish Twin Study of Schizophrenia Liability: Investigation from Interviewed Twins for Genetic Links to Affective Psychoses and for Cross-Cohort Comparisons

We studied schizophrenia liability in a Danish population-based sample of 44 twin pairs (13 MZ, 31 DZ, SS plus OS) in order to replicate previous twin study findings using contemporary diagnostic criteria, to examine genetic liability shared between schizophrenia and other disorders, and to explore whether variance in schizophrenia liability attributable to environmental factors may have decreased with successive cohorts exposed to improvements in public health. ICD-10 diagnoses were determined by clinical interview. Although the best-fitting, most parsimonious biometric model of schizophrenia liability specified variance attributable to additive genetic and non-shared environmental factors, this model did not differ significantly from a model that also included non-additive genetic factors, consistent with recent interview-based twin studies. Schizophrenia showed strong genetic links to other psychotic disorders but much less so for the broader category of psychiatric disorders in general. We also observed a marginally significant decline in schizophrenia variance attributable to environmental factors over successive Western European cohorts, consistent perhaps with improvements in diagnosis and in prenatal and perinatal care and with a secular decline in the prevalence of schizophrenia in that region.

Genetic relationships between schizophrenia, bipolar disorder, and schizoaffective disorder

There is substantial evidence for partial overlap of genetic influences on schizophrenia and bipolar disorder, with family, twin, and adoption studies showing a genetic correlation between the disorders of around 0.6. Results of genome-wide association studies are consistent with commonly occurring genetic risk variants, contributing to both the shared and nonshared aspects, while studies of large, rare chromosomal structural variants, particularly copy number variants, show a stronger influence on schizophrenia than bipolar disorder to date. Schizoaffective disorder has been less investigated but shows substantial familial overlap with both schizophrenia and bipolar disorder. A twin analysis is consistent with genetic influences on schizoaffective episodes being entirely shared with genetic influences on schizophrenic and manic episodes, while association studies suggest the possibility of some relatively specific genetic influences on broadly defined schizoaffective disorder, bipolar subtype. Further insights into genetic relationships between these disorders are expected as studies continue to increase in sample size and in technical and analytical sophistication, information on phenotypes beyond clinical diagnoses are increasingly incorporated, and approaches such as next-generation sequencing identify additional types of genetic risk variant.

Risk of mental illness in offspring of parents with schizophrenia, bipolar disorder, and major depressive disorder: a meta-analysis of family high-risk studies

OBJECTIVE

Offspring of parents with severe mental illness (SMI; schizophrenia, bipolar disorder, major depressive disorder) are at an increased risk of developing mental illness. We aimed to quantify the risk of mental disorders in offspring and determine whether increased risk extends beyond the disorder present in the parent.

METHOD

Meta-analyses of absolute and relative rates of mental disorders in offspring of parents with schizophrenia, bipolar disorder, or depression in family high-risk studies published by December 2012.

RESULTS

We included 33 studies with 3863 offspring of parents with SMI and 3158 control offspring. Offspring of parents with SMI had a 32% probability of developing SMI (95% CI: 24%-42%) by adulthood (age >20). This risk was more than twice that of control offspring (risk ratio [RR] 2.52; 95% CI 2.08-3.06, P < .001). High-risk offspring had a significantly increased rate of the disorder present in the parent (RR = 3.59; 95% CI: 2.57-5.02, P < .001) and of other types of SMI (RR = 1.92; 95% CI: 1.48-2.49, P < .001). The risk of mood disorders was significantly increased among offspring of parents with schizophrenia (RR = 1.62; 95% CI: 1.02-2.58; P = .042). The risk of schizophrenia was significantly increased in offspring of parents with bipolar disorder (RR = 6.42; 95% CI: 2.20-18.78, P < .001) but not among offspring of parents with depression (RR = 1.71; 95% CI: 0.19-15.16, P = .631).

CONCLUSIONS

Offspring of parents with SMI are at increased risk for a range of psychiatric disorders and one third of them may develop a SMI by early adulthood.

Clinical and molecular genetics of psychotic depression

This review provides a comprehensive overview of clinical and molecular genetic as well as pharmacogenetic studies regarding the clinical phenotype of "psychotic depression." Results are discussed with regard to the long-standing debate on categorical vs dimensional disease models of affective and psychotic disorders on a continuum from unipolar depression over bipolar disorder and schizoaffective disorder to schizophrenia. Clinical genetic studies suggest a familial aggregation and a considerable heritability (39%) of psychotic depression partly shared with schizoaffective disorder, schizophrenia, and affective disorders. Molecular genetic studies point to potential risk loci of psychotic depression shared with schizoaffective disorder (1q42, 22q11, 19p13), depression, bipolar disorder, and schizophrenia (6p, 8p22, 10p13-12, 10p14, 13q13-14, 13q32, 18p, 22q11-13) and several vulnerability genes possibly contributing to an increased risk of psychotic symptoms in depression (eg, BDNF, DBH, DTNBP1, DRD2, DRD4, GSK-3beta, MAO-A). Pharmacogenetic studies implicate 5-HTT, TPH1, and DTNBP1 gene variation in the mediation of antidepressant treatment response in psychotic depression. Genetic factors are suggested to contribute to the disease risk of psychotic depression in partial overlap with disorders along the affective-psychotic spectrum. Thus, genetic research focusing on psychotic depression might inspire a more dimensional, neurobiologically and symptom-oriented taxonomy of affective and psychotic disorders challenging the dichotomous Kraepelinian view. Additionally, pharmacogenetic studies might aid in the development of a more personalized treatment of psychotic depression with an individually tailored antidepressive/antipsychotic pharmacotherapy according to genotype.

Cholinergic muscarinic M4 receptor gene polymorphisms: a potential risk factor and pharmacogenomic marker for schizophrenia

Although schizophrenia is a widespread disorder of unknown aetiology, we have previously shown that muscarinic M4 receptor (CHRM4) expression is decreased in the hippocampus and caudate-putamen from subjects with the disorder, implicating the receptor in its pathophysiology. These findings led us to determine whether variation in the CHRM4 gene sequence was associated with an altered risk of schizophrenia by sequencing the CHRM4 gene from the brains of 76 people with the disorder and 74 people with no history of psychiatric disorders. In addition, because the CHRM4 is a potential target for antipsychotic drug development, we investigated whether variations in CHRM4 sequence were associated with final recorded doses of, and life-time exposure to, antipsychotic drugs. Gene sequencing identified two single nucleotide polymorphisms (SNPs; rs2067482 and rs72910092) in the CHRM4 gene. For rs2067482, our data suggested that both genotype (1341C/C; p = 0.05) and allele (C; p = 0.03) were associated with an increased risk of schizophrenia. In addition, there was a strong trend (p = 0.08) towards an association between CHRM4 sequence and increased lifetime exposure to antipsychotic drugs. Furthermore, there was a trend for people with the C allele to be prescribed benzodiazepines more frequently (p = 0.06) than those with the T allele. These data, albeit on small cohorts, are consistent with genetic variance at rs2067482 contributing to an altered risk of developing schizophrenia which requires more forceful pharmacotherapy to achieve a clinical response.

Brain functional abnormality in schizo-affective disorder: an fMRI study

BACKGROUND

Schizo-affective disorder has not been studied to any significant extent using functional imaging. The aim of this study was to examine patterns of brain activation and deactivation in patients meeting strict diagnostic criteria for the disorder.

METHOD

Thirty-two patients meeting research diagnostic criteria (RDC) for schizo-affective disorder (16 schizomanic and 16 schizodepressive) and 32 matched healthy controls underwent functional magnetic resonance imaging (fMRI) during performance of the n-back task. Linear models were used to obtain maps of activations and deactivations in the groups.

RESULTS

Controls showed activation in a network of frontal and other areas and also deactivation in the medial frontal cortex, the precuneus and the parietal cortex. Schizo-affective patients activated significantly less in prefrontal, parietal and temporal regions than the controls, and also showed failure of deactivation in the medial frontal cortex. When task performance was controlled for, the reduced activation in the dorsolateral prefrontal cortex (DLPFC) and the failure of deactivation of the medial frontal cortex remained significant.

CONCLUSIONS

Schizo-affective disorder shows a similar pattern of reduced frontal activation to schizophrenia. The disorder is also characterized by failure of deactivation suggestive of default mode network dysfunction.

The genetic basis of mood and anxiety disorders - changing paradigms

Family, twin and epidemiologic studies all point to an important genetic contribution to the risk to develop mood and anxiety disorders. While some progress has been made in identifying relevant pathomechanisms for these disorders, candidate based strategies have often yielded controversial findings. Hopes were thus high when genome-wide genetic association studies became available and affordable and allowed a hypothesis-free approach to study genetic risk factors for these disorders. In an unprecendented scientific collaborative effort, large international consortia formed to allow the analysis of these genome-wide association datasets across thousands of cases and controls ([1] and see also http://www.broadinstitute.org/mpg/ricopili/). Now that large meta-analyses of genome-wide association studies (GWAS) have been published for bipolar disorder and major depression it has become clear that main effects of common variants are difficult to identify in these disorders, suggesting that additional approaches maybe needed to understand the genetic basis of these disorders [2,3].

Using summary data from the danish national registers to estimate heritabilities for schizophrenia, bipolar disorder, and major depressive disorder

Estimates of heritability of psychiatric disorders quantify the genetic contribution to their etiology. Estimation of these parameters requires affected status on probands and their family members. Traditionally, heritabilities have been estimated from families ascertained from specific hospital registers, but accumulating sufficient numbers of families can be difficult. Larger sample sizes are achievable from national registries, but calculation of heritability from individual level data from these data sets is accompanied by other problems. Here, we use published summary data from a national population-based cohort of >2.6 million persons in Denmark to estimate heritabilities of schizophrenia, bipolar disorder, and major depressive disorder (MDD). The summary data comprised cumulative incidences up to 52 years of age for schizophrenia and bipolar disorder and up to 51 years for MDD in offspring where either one or both parents were diagnosed with one of these disorders. Estimates of the heritabilities of the liability to developing schizophrenia, bipolar disorder, and MDD are 0.67 (95% confidence interval (CI) 0.64–0.71), 0.62 (95% CI 0.58–0.65), and 0.32 (95% CI 0.30–0.34) respectively. The estimates may be inflated by common environmental effects, but despite this, they are somewhat lower for schizophrenia and bipolar disorder than those estimated from contemporary twin samples. The lower estimates may reflect the diverse environments (including diagnostic interpretation) that contribute to national data, compared to twin/family studies. Our estimates are similar to those estimated previously from national data of Sweden, and they may be more representative of the international samples brought together for large-scale genome-wide association studies. We investigated the estimation of genetic correlations from these data. We used simulation to conclude that estimates may not be interpretable and so report them only in the Section “Appendix.”

A proton magnetic resonance spectroscopy study in schizoaffective disorder: comparison of bipolar disorder and schizophrenia

The aim of this study was to compare schizoaffective disorder, bipolar disorder and schizophrenia based on (1)H-MRS metabolite values in dorsolateral prefrontal cortex and executive functions. The subjects comprised 15 patients with bipolar disorder type I (BD), 15 with schizophrenia (SCH), 15 with schizoaffective disorder (SAD) and 15 healthy controls. We performed proton magnetic resonance spectroscopy ((1)H-MRS) of the dorsolateral prefrontal cortex (DLPFC) bilaterally. Levels of N-acetyl aspartate (NAA), choline-containing compounds (Cho) and creatine-containing compounds (Cr) were measured in the DLPFC using (1)H-MRS. We administered the Wisconsin Card Sorting Test (WCST) and the Stroop Test (ST) to evaluate executive functions. The SAD, BD and SCH patients had lower levels of NAA than the control group. The SAD and BD patients had low levels of Cho compared to the control group. The left DLPFC Cr levels in all of the patient groups and the right DLPFC Cr levels in the BD and SAD groups were lower than in the control group. The levels of NAA Cho and Cr were not related to executive functions and attention performance. Cr level were related to attention processes, only in SCH. Our results indicate that NAA levels are reduced in schizoaffective disorder, bipolar disorder and schizophrenia, but the reduction in the levels of NAA is not a distinctive feature among these three illnesses. Schizoaffective and bipolar disorders have similar features related to the levels of compounds containing Cho and Cr. This similarity may be related to these illnesses both having an affective basis.