Comments on News and Primary Papers
Comment by: Jose Goikolea
, Eduard Vieta
Submitted 18 July 2013
Posted 18 July 2013
The recent publication of two papers from the B-SNIP group in the American Journal of Psychiatry provides additional high-quality data supporting a dimensional model for psychotic disorders, different from the current Kraepelinian categorical model. These two papers focus on two different putative endophenotypes for schizophrenia and bipolar disorder, namely, cognitive performance and white matter integrity. Interestingly, both endophenotypes show quite similar results.
The work of the B-SNIP group is praiseworthy. Consisting of six centers across the United States, the group has studied quite a large sample of patients with psychotic disorders (schizophrenia, schizoaffective, and psychotic bipolar disorder) using both current categorical diagnostic criteria and a dimensional Schizo-Bipolar Scale approach. Besides that, the group assesses relatives without psychotic or affective disorders, which is essential for further understanding the underlying genetic basis and identifying endophenotypes for these disorders.
Both studies obtain similar results for each endophenotype: Both schizophrenia and bipolar disorder show abnormalities (in cognition and in white matter integrity) compared to healthy controls. There are no qualitative differences in these abnormalities; that is, they share a similar pattern of disturbance, although it is more severe (cognition) or widespread (white matter) in schizophrenia. These disturbances are shared to a lower degree by unaffected relatives, supporting their validity as endophenotypes, even if this is much clearer for relatives of schizophrenia subjects. Undoubtedly, these results support the notion of a single nosological entity with a dimensional nature. On the “schizophrenia edge” of the continuum, a more severe or widespread impairment as well as more abnormalities in unaffected relatives would be found.
However, there are some comments that should be taken into account for a fair interpretation of the results. First of all, the diagnosis of schizoaffective disorder has become somehow a test itself to validate the categorical versus dimensional model for psychotic disorders. The paper by Hill et al. compares the schizoaffective group with the healthy control group and with the other proband groups. The conclusions seem to support the dimensional model, as schizoaffective probands show an intermediate cognitive performance between schizophrenia and bipolar disorder without qualitative differences. Instead, for unclear reasons, the DTI paper splits the schizoaffective group in manic type merged with the bipolar group, and depressive type merged with the schizophrenia group, losing an opportunity to analyze this perspective.
Second, it is a shame that non-psychotic bipolar 1 patients have not been included in these studies. This represents a bias toward the psychotic view, whereas the inclusion of the non-psychotic bipolar subjects would have provided a second enriching view from the “affective” perspective. This second supplementary approach would be more likely to identify possible endophenotypic features that might differentiate schizophrenia from bipolar disorder. In fact, in light of these two papers, schizophrenia and bipolar disorder could be understood as the same disease, bipolar just being a less severe phenotype. Although there is quite large evidence that schizophrenia and bipolar disorder share different genetic, neurobiological, and cognitive features, and that a mixed categorical and dimensional approach may be much closer to reality, differences between both disorders should still be kept in mind. For instance, the unique clinical features of the most prototypical euphoric mania or the circadian rhythm disturbances in bipolar disorder are likely to be based on neurobiological features specific to bipolar disorder that are not yet completely understood or identified.
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Primary Papers: Neuropsychological Impairments in Schizophrenia and Psychotic Bipolar Disorder: Findings from the Bipolar and Schizophrenia Network on Intermediate Phenotypes (B-SNIP) Study.
Comment by: Antonella Trotta
Submitted 5 August 2013
Posted 7 August 2013
I recommend this paper
Despite Kraepelin’s nosological distinction between schizophrenia and bipolar disorder and the categorical classification of current diagnostic systems, recent advances indicate that there is considerable overlap between these disorders. In fact, epidemiological, genetic, and neuroimaging studies comparing schizophrenia and bipolar disorder show a complex range of pathophysiological and phenomenological similarities (Demjaha et al., 2012).
In line with previous findings, the two papers from the B-SNIP group in the American Journal of Psychiatry confirm, respectively, the role of potential cognitive and brain functioning endophenotypes in schizophrenia and bipolar disorder. The findings of Hill and colleagues on cognitive impairment in schizophrenia and psychotic bipolar disorder add an important contribution to a continuum model of cognitive deficits in psychotic disorders in which, on one hand, schizophrenia is characterized by the most severe cognitive impairment, and bipolar disorder, on the other hand, shows less severe but still significant deficits. Moreover, their findings confirm the familiality of cognitive impairment across schizophrenia, while cognitive dysfunction in first-degree relatives of bipolar disorder probands is linked with elevated cluster A or cluster B personality traits.
It seems likely that certain risk factors (i.e., susceptibility genes) may predispose an individual to developing psychosis, and then other genetic and/or environmental risks factors may determine if schizophrenia or bipolar disorder symptoms predominate. In fact, birth cohort and conscript studies have shown that schizophrenia and bipolar disorder are distinguished by premorbid cognitive impairment being found in the former but not in the latter. This may reflect a neurodevelopmental abnormality in schizophrenia but not bipolar disorder; thus, on the background of genetic susceptibility to psychosis, additional genes may interact with early environmental stressors, leading to schizophrenia.
However, the findings of Hill and colleagues should be considered in the light of some limitations. First, although they retrospectively assessed cognitive functioning before the illness onset using the WRAT-4 reading test, the authors do not pay much attention to cognitive trajectories in either probands or first-degree relatives. Their results show, in fact, that cognitive impairment precedes the onset of schizophrenia but not bipolar disorder, and a similar pattern is shown by their unaffected relatives. A recent meta-analysis of follow-up studies of cognition in first-episode psychosis and ultra-high-risk groups for psychosis reported no evidence of cognitive decline over, or after, the onset of first-episode psychosis (Bora and Murray, 2013). Therefore, these findings suggest that cognitive deficits are already established before the prodromal phase of psychosis, supporting a neurodevelopmental rather than neurodegenerative model of schizophrenia-like psychosis (Murray et al., 2004).
Moreover, Hill and colleagues underestimate the effect of other potential biological or environmental factors on the association between cognitive performance and schizophrenia or bipolar disorder, such as sociodemographic and clinical variables, as well as the influence of medication on cognitive functioning. Cognitive deficit could be intrinsic to the illnesses but could also be related to other factors such as substance misuse, physical ill health, or prescribed medications (Zipursky et al., 2012).
Therefore, future studies including examining longitudinal changes in cognition using a large sample size and controlling for potential confounders would advance our understanding in identifying the potential causes of the deficits.
Bora E, Murray RM. Meta-analysis of Cognitive Deficits in Ultra-high Risk to Psychosis and First-Episode Psychosis: Do the Cognitive Deficits Progress Over, or After, the Onset of Psychosis? Schizophr Bull . 2013 Jun 14. Abstract
Demjaha A, Maccabe JH, Murray RM. How genes and environmental factors determine the different neurodevelopmental trajectories of schizophrenia and bipolar disorder. Schizophr Bull . 2012 Mar ; 38(2):209-14. Abstract
Murray RM, Sham P, van Os J, Zanelli J, Cannon M, McDonald C. A developmental model for similarities and dissimilarities between schizophrenia and bipolar disorder. Schizophr Res . 2004 Dec 1 ; 71(2-3):405-16. Abstract
Zipursky RB, Reilly TJ, Murray RM. The Myth of Schizophrenia as a Progressive Brain Disease. Schizophr Bull . 2012 Dec 7. Abstract
View all comments by Antonella TrottaComment by: Ole A. Andreassen, SRF Advisor, Martin Tesli
Submitted 3 September 2013
Posted 4 September 2013
The two reports from the B-SNIP consortium elegantly address Kraepelin’s dichotomy in psychosis and provide evidence using a large sample that there are overlapping cognitive deficits across psychotic bipolar disorder and schizophrenia (Hill et al., 2013), and similar patterns of connectivity abnormalities (as measured by diffusion tensor imaging, or DTI) in the two disorders (Skudlarski et al., 2013). Both phenotypes are also found in relatives, supporting the idea that the cognitive and DTI measures are true "endophenotypes."
The finding that cognitive dysfunction in schizophrenia and psychotic bipolar disorder depends more on psychosis than a diagnostic group is a nice replication of our previous findings (Simonsen et al., 2011). This is reassuring and further suggests that it is a robust phenomenon, as the neuropsychological test batteries used in the two studies were quite different. The severity of the deficits is also comparable between the two studies.
The current study also investigated the familiality of cognitive dysfunction, which was quite high, with deficits also seen in non-psychotic relatives of both bipolar disorder and schizophrenia. Quite interestingly, the cognitive deficits were more associated with cluster A (psychosis-like) personality traits in relatives of bipolar disorder than in schizophrenia. This further strengthens the argument that there is a continuum of psychosis across these disorders which is heritable.
The paper by Skudlarski et al. reports brain imaging investigations (DTI) from the same sample. Decreased fractional anisotropy was found in multiple brain regions in schizophrenia and psychotic bipolar disorder subjects, and to a smaller extent in their relatives, than in healthy controls. These findings seem consistent, as 15 out of 18 regions have been previously reported in schizophrenia and 10 out of 21 in bipolar disorder. Further, the current results are in line with the continuum model of psychotic disorders and the polygenic architecture reported in recent mega-analyses (Lee et al., 2013).
Intriguingly, the authors found fractional anisotropy to be even better correlated with the "Schizo-Bipolar Scale" than with disease category. This proves the utility of cross-diagnostic clinical dimensions when investigating potential neurobiological mechanisms in psychiatric disorders. To bring this a step further, it would be interesting to know whether this clinical scale also correlates with fractional anisotropy (or neurocognition) within the bipolar disorder or the schizophrenia sub-sample separately.
In the perspective of the psychosis continuum model, it seems slightly contradictory that the investigators did not include schizoaffective disorder as a disease category on its own. Instead, they split this diagnostic group in two, classifying the depressed subgroup in the schizophrenia group and the manic subgroup in the psychotic bipolar disorder group. As a rationale for this classification, the authors reported controversial validity of the diagnostic status of schizoaffective disorder. If this controversy led to a split of the schizoaffective group in the paper by Skudlarski et al., why did the same controversy lead to the inclusion of schizoaffective disorder as its own category in the study by Hill et al.? Both approaches could potentially have been applied in both studies to actually explore this controversy in terms of neurocognition and white matter integrity.
Both studies support the hypothesis that reduced white matter integrity and impaired neurocognition are intermediate phenotypes in psychotic disorders. However, it might be debated whether these two features are causative in nature or merely correlate with the clinical symptomatology. Does reduced white matter integrity cause reduced neurocognition, which in turn gives rise to psychotic symptoms, or are the two latter phenomena independent but correlating effects of the former? Future studies should aim at disentangling these levels of correlating phenomena in biological psychiatric research. In line with this, it would be interesting to investigate the relationship between DTI measures and structural and functional MRI. Is the currently reported reduced white matter integrity reflected in the reductions identified with sMRI? And what consequences do these impairments have for brain activity as assessed with fMRI? Lastly, can these alterations be explained by genetic risk variants individually or in aggregate?
In summary, these two statistically well-powered studies have provided robust evidence for the continuum model in psychotic disorders. This is in accordance with findings from molecular genetics, brain imaging, and clinical studies. Now it is time to look for mechanisms behind these correlations.
Hill SK, Reilly JL, Keefe RS, Gold JM, Bishop JR, Gershon ES, Tamminga CA, Pearlson GD, Keshavan MS, Sweeney JA. Neuropsychological Impairments in Schizophrenia and Psychotic Bipolar Disorder: Findings from the Bipolar and Schizophrenia Network on Intermediate Phenotypes (B-SNIP) Study. Am J Psychiatry . 2013 Jun 17. Abstract
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Simonsen C, Sundet K, Vaskinn A, Birkenaes AB, Engh JA, Faerden A, Jónsdóttir H, Ringen PA, Opjordsmoen S, Melle I, Friis S, Andreassen OA. Neurocognitive dysfunction in bipolar and schizophrenia spectrum disorders depends on history of psychosis rather than diagnostic group. Schizophr Bull . 2011 Jan ; 37(1):73-83. Abstract
Skudlarski P, Schretlen DJ, Thaker GK, Stevens MC, Keshavan MS, Sweeney JA, Tamminga CA, Clementz BA, O'Neil K, Pearlson GD. Diffusion tensor imaging white matter endophenotypes in patients with schizophrenia or psychotic bipolar disorder and their relatives. Am J Psychiatry . 2013 Aug 1 ; 170(8):886-98. Abstract
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Comments on Related News
Related News: New Genetic Variations Link Schizophrenia and Bipolar DisorderComment by: Mary Reid
Submitted 28 September 2006
Posted 29 September 2006
It's of interest that Vazza and colleagues suggest that 15q26 is a new susceptibility locus for schizophrenia and bipolar disorder. I have suggested that reduced function of the anti-inflammatory SEPS1 (selenoprotein S) at 15q26.3 may reproduce the neuropathology seen in schizophrenia.
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Related News: New Genetic Variations Link Schizophrenia and Bipolar Disorder
Comment by: Patricia Estani
Submitted 5 October 2006
Posted 6 October 2006
I recommend the Primary Papers
Related News: Data Support Kraepelinian Boundary Between Psychotic Disorders
Comment by: Irving Gottesman, SRF Advisor, Aksel Bertelsen
Submitted 23 October 2013
Posted 23 October 2013
Invigorating intellectual and heuristic debate in this Forum is kept alive by the challenging and informed summary of Kotov et al. by Michele Solis. The nagging problem of the status of schizoaffective disorder cannot be concluded by the evidence in hand from this study or others that are more biologically and genetically informed (e.g., B-SNIP data) because none are dispositive, to borrow a term from the lawyers. We applaud Kendler’s erudite and friendly dissection of Kotov et al. (Kendler, 2013) and concur with his conclusion that it would be premature to eliminate the Kraepelinian dichotomy. After all, the Alte Meister did not have access to GWAS or to DTI data from probands and their relatives, and ENCODE (Maurano et al., 2012) could not have been envisioned, either. We hope to supplement the SRF discussion with our twin (Cardno et al., 2012) and Scandinavian experiences (Bertelsen and Gottesman, 1995; Laursen et al., 2005; Gottesman et al., 2010; Lichtenstein et al., 2009). The last have cautioned against the tyranny of technology, while a British curmudgeon with a 2002 Nobel Prize, Sydney Brenner, has reminded us that one person’s junk is another’s treasure—the real task being how to organize data so that they yield knowledge.
First, we must compliment Kotov et al. for accomplishing the daunting task of successfully following up their U.S. cohort with 10 years of data. True, Manfred Bleuler completed an exhaustive 23-year follow-up with a much more captive audience in the Burghölzli Hospital, in which he reported course changes both for better and worse even after 20 years for a majority of his cases (Bleuler, 1978). Thus, “outcome” cannot be equated with Bleuler’s “end state.” No clear distinction was seen in the Kotov study between the outcome of schizoaffective disorder and schizophrenia, indicating that the DSM-IV/-5 diagnostic differentiation is not valid. Instead, co-morbidity between affective disorder and schizophrenia in the nonhierarchical DSM classification system is proposed.
The co-appearance of affective disorder and schizophrenia has always been acknowledged. Papa Bleuler included attacks of mania or melancholia in his list of etiopathogenetic “primary symptoms” (not to be confused with his symptomatological “basic disturbances”; see Bleuler, 1911). Kraepelin mentioned that episodes of mania and depression were not uncommon in schizophrenic patients and that quite a number of patients presented with symptoms that did not allow a confident distinction between manic-depressive insanity and dementia praecox (Kraepelin, 1920). He proposed as a plausible explanation that the presentation of symptoms was determined by predisposing factors in the patients’ personalities for emotional or schizophrenic manifestation of the manic-depressive or schizophrenic illness.
Odegaard, unconstrained by either DSM or ICD, and using the national Norwegian psychiatric register which he had tirelessly constructed, observed the diagnostic distribution of probands and (only) their psychotic relatives (Odegaard, 1972). He routinely saw affective psychoses in the relatives of schizophrenics, and schizophrenic psychoses in the relatives of atypical affective psychoses plus manic-depressive psychoses. He favored some kind of a polygenic theory for his results (compare to Gottesman and Shields, 1967).
Having prominent affective symptoms or syndromes in patients with schizophrenia eventually was considered to be a schizoaffective subtype of schizophrenia, and since DSM-III/III-R and –IV and ICD-10, schizoaffective disorder has been differentiated as an independent category; in DSM it is nearer to schizophrenia than in ICD because DSM requires at least two weeks of non-affective psychosis. The separate classification has been supported by validating genetic studies (Bertelsen and Gottesman, 1995; Hamshere et al., 2009) and a major register-based cohort study, indicating that schizoaffective disorder is genetically linked to both mood disorder and schizophrenia as an intermediate form (Laursen et al., 2005).
In a recent Danish register-based study of schizophrenia and bipolar disorder in offspring of two, one, or no parent likewise affected (Gottesman et al., 2010), we observed a cumulative incidence of bipolar disorder in offspring of two schizophrenic parents that was 10 times higher than in the general population, and of schizophrenia in offspring of two parents with bipolar disorder four times higher than the population value. In children of one schizophrenic parent and the other with bipolar disorder, the incidence of schizophrenia and of bipolar disorder was two to three times the incidence from only one parent affected with either disorder. A major Swedish population-based study provided similar evidence that schizophrenia and bipolar disorder share a common genetic cause (Lichtenstein et al., 2009). In a sophisticated, eclectic discussion of the not yet disappearing dichotomy, Craddock and Owen conclude that a broadly defined schizoaffective illness “may be particularly useful for genetic studies” (Craddock and Owen, 2010), reprising their earlier empirical results with the WTCCC cohort (Hamshere et al., 2009).
In order to get nearer to the relation to the genetic predisposition than the present classification allows, it has been suggested to study domains of symptoms, (the NIMH Research Domains Criteria project [RDoC]; see Insel et al., 2010), particularly in endophenotype studies (Insel and Cuthbert, 2009; Gottesman and Gould, 2003) as a promising way of future research of the basic relationships among the disorders behind what we, for the time being, term schizophrenia, schizoaffective disorder, and bipolar disorder. The earlier Research Diagnostic Criteria (RDC) of Spitzer et al. (Spitzer et al., 1978) and the OPCRIT of McGuffin et al. (McGuffin et al., 1991) anticipated less constrained approaches to diagnosis that have shown their merit in genetically promising research. We find the conclusions of Hamshere et al. (Hamshere et al., 2009) compatible with our current understanding: "We hope that psychiatry is moving towards the time when our patients can benefit from diagnostic concepts that are built on solid foundations of empirical biological evidence rather than being perched precariously on the shifting sands of expert opinion."
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Related News: Mental Illnesses Share Common Brain Changes
Comment by: John Krystal, SRF Advisor
Submitted 10 February 2015
Posted 10 February 2015
I think that this is a fascinating paper that provocatively asks the question of whether there might be common cross-diagnostic neural substrates of illness. The authors analyzed data from 193 studies and found that gray matter volume reductions in the dorsal anterior cingulate and insula were common across diagnoses. Since the six disorders studied are associated with differing symptom profiles, differing pharmacologic treatments, and differing prognoses for good outcomes, one might reasonably wonder how to interpret the common findings. The conceptual and practical challenges are enormous, and the list of potential confounding factors is long.
Although this paper is very limited in its ability to answer this question, Goodkind et al. wrestle valiantly to consider the implications of their study. For example, they raise the possibility that these regional changes in gray matter volume might be non-specific sequelae of chronic mental illness or, alternatively, that certain brain circuits are particularly vulnerable to the detrimental effects of chronic stress. They note that gray matter reductions may have functional significance, as they were associated with alterations in brain function and executive cognitive functions. From this perspective, chronic mental illness may, beyond the impact of diagnosis-specific alterations, independently contribute to functional impairment through these detrimental effects of stress on brain biology. Alternatively, the commonality of brain changes across diagnoses could suggest that, to some degree, psychiatric disorders differ by the degree rather than the locality of brain structural changes. This notion, again, points to the presence of vulnerable circuits in vulnerable people.
However, this convergence of diagnoses on common changes in common circuits might also be related to the mechanisms underlying the etiology of these disorders. For example, psychiatric disorders are heterogeneous and highly polygenic. Gene variants implicated in one psychiatric disorder are often implicated in the risk for other psychiatric disorders (see Krystal and State, 2014); thus, the commonly affected regions could reflect genetic risk mechanisms that cross disorders.
Why aren't the diagnosis-specific abnormalities more prominent? While there were some diagnosis-related findings, they were not as robust as one might have expected, given the enormity of the neuroimaging literature describing specific differences between disease groups and healthy populations. As noted above, there are signs in the neuroimaging literature that specific diagnoses differ both categorically (i.e., distinct disease processes) and dimensionally (i.e., differ by severity of circuit alterations). The nature of the findings in this meta-analysis depend, in part, on the extent to which research has tapped into elements of the neurobiology of psychiatric disorders that tap into their categorical or dimensional qualities. Traditionally, psychiatry has tended to leap upon categorical differences in brain structure and function that reinforce the categorical diagnostic system employed by psychiatry and to downplay dimensional relationships that would tend to undermine the assumptions of its categorical diagnoses. Yet dimensional aspects of the neurobiology of psychiatric disorders are targeted specifically by the NIMH Research Domain Criteria. Thus, there is an emerging generation of psychiatry research that will help us all to understand the diagnostic, prognostic, and therapeutic implications of the dimensional features of the neurobiology of psychiatric disorders.
This was an important and provocative paper that is likely to stimulate a great deal of thought and future research.
Krystal JH, State MW. Psychiatric disorders: diagnosis to therapy. Cell. 2014 Mar 27;157(1):201-14. Abstract
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