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Schizophrenia and Bipolar With Psychosis Share Cognition, Connectivity

5 July 2013. Schizophrenia and bipolar disorder with psychosis share cognitive features and connectivity patterns, according to two studies from the Bipolar and Schizophrenia Network on Intermediate Phenotypes (B-SNIP) published online June 17 in the American Journal of Psychiatry. The first study, led by Scot Kristian Hill of Rosalind Franklin University, Chicago, Illinois, finds cognitive impairments in psychotic disorders relative to controls, with schizophrenia subjects worse off than those with schizoaffective disorder, which in turn were worse than subjects with psychotic bipolar disorder. In the second study, Pawel Skudlarski of Yale University, New Haven, Connecticut, and colleagues report differences in the brain’s communication byways relative to controls, with degradation of white matter integrity somewhat more pronounced for schizophrenia than for bipolar disorder. Both studies also found less severe cognitive and white matter impairments in unaffected relatives, which could flag inherited features amenable to gene finding.

The results suggest that boundaries between schizophrenia and bipolar disorder with psychosis reflect differences in degree rather than kind. Although overlaps between the two disorders have long been recognized (e.g., see SRF related news story), the studies reflect the first attempts of the B-SNIP group, consisting of six centers across the United States, to pinpoint similarities and differences between the two in a standardized setting. Distilling the symptoms of these disorders into specific component parts (also called intermediate phenotypes), such as a working memory impairment or an abnormal brain structure, could reveal underlying brain pathologies more clearly than a direct comparison of the two disorders (Meyer-Lindenberg et al., 2006).

Finding these component parts also marks the first step in looking for endophenotypes—those distilled features of an illness that are also inherited. Endophenotypes may lie closer to an originating genetic glitch than the complicated symptoms that define a diagnosis, making it easier to link genotype to phenotype. To this end, the B-SNIP project also examines unaffected relatives of people with schizophrenia and bipolar disorder.

Cognitive profiling
Hill and colleagues assembled 293 participants with schizophrenia and 316 of their first-degree relatives, 227 with psychotic bipolar disorder and 259 of their relatives, 165 with schizoaffective disorder and 197 relatives, and 295 healthy controls. The researchers evaluated all participants with the Brief Assessment of Cognition in Schizophrenia (BACS), a 30-minute test of verbal memory, processing speed, reasoning, and working memory. The average scores for schizophrenia, schizoaffective disorder, and psychotic bipolar disorder were lower than those for healthy controls, indicating cognitive impairments. But within the psychotic disorders, the scores fell off progressively, with the psychotic bipolar group scoring highest, followed by schizoaffective disorder, then schizophrenia. Across the six different domains tested by the BACS, the psychotic disorders shared a similar profile of performance, differing only in the magnitude of impairment. Scores on the Schizo-Bipolar Scale revealed that more prominent mood symptoms and less persistent psychosis were associated with less severe cognitive impairments.

Among the first-degree relatives with no history of psychosis, those related to someone with schizophrenia showed cognitive impairments, whereas those related to someone with schizoaffective or bipolar disorder did not, as their scores were not significantly different from controls. Heritability testing revealed that performance on the BACS was potentially inherited, with heritability estimated at 0.5 for the schizophrenia families and 0.61 in the psychotic bipolar families. This indicates that these cognitive abilities might be worthy endophenotypes.

The researchers further parsed the relatives according to their personality traits, as measured by the DSM-IV. Among relatives of participants with schizophrenia, those who showed elevated personality traits for cluster A (odd or eccentric) or cluster B (dramatic, emotional, or erratic) performed just as poorly on the BACS as those who did not meet these personality criteria. Among relatives of participants with psychotic bipolar disorder, however, only the groups with elevated cluster A or cluster B traits showed cognitive impairments. This difference hints at a qualitative difference between the disorders and suggests that, for psychotic bipolar disorder, tracking both cognitive impairments and personality traits would be important for unearthing the relevant risk factors.

Covering tracts
In the second study, Skudlarski and colleagues used brain imaging to try to discern features of brain structure that characterize psychotic disorders. Prompted by their previous findings of impaired functional connectivity in schizophrenia and psychotic bipolar disorder (Meda et al., 2012), the researchers used diffusion-tensor imaging to delineate the structure of the white matter tracts that connect different brain regions in 513 participants total, including first-degree relatives.

The researchers found signs of disrupted white matter structure—as indicated by lower than normal fractional anisotropy (FA) values, which measure how aligned connections are within a tract. These disruptions mapped to 29 of 76 regions analyzed, with the genu, or anterior bend, of the corpus callosum showing the greatest difference relative to controls. The pattern of disruption mostly overlapped between the two disorders, and the magnitude of the disruptions was largely the same. But schizophrenia registered more low FA regions, suggesting a slightly worse pattern. White matter differences also showed up in the relatives in attenuated form, and whole-brain FA had a heritability of 0.45, along with several individual regions weighing in with similar heritability. This suggests that white matter structure as reflected by FA might warrant pursuing as an endophenotype for psychotic disorders.

The findings in both studies obscure diagnostic boundaries and add heft to the idea that differences among psychiatric disorders are more quantitative than qualitative in nature. Though the search space for the core pathological components is vast, the studies here take steps toward defining them. Even if the cognitive and white matter features explored here do not turn out to be core features of psychotic disorders, they may still help define useful disease subtypes that can inform genetic studies as well as treatment plans.—Michele Solis.

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

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 Jun 17. Abstract

Comments on News and Primary Papers
Comment by:  Jose GoikoleaEduard 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 AdvisorMartin 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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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 Disorder

Comment 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.

View all comments by Mary Reid

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 AdvisorAksel 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."


Kendler KS (2013) Psychosis Within vs. Outside of Major Mood Episodes: A Key Prognostic and Diagnostic Criterion. JAMA Psychiatry. Abstract

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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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Related News: Will Biotypes Redefine Psychosis Research?

Comment by:  David Braff
Submitted 15 January 2016
Posted 15 January 2016

Biotypes, as described in the study by Clementz and colleagues, offer a rational way of parsing psychotic patients based on biomarkers or related deficits of heritable endophenotypes seen in patients and their family members. The study is a good example of incremental advances in trying to parse psychotic disordered patients into rationally determined groups with genetic and treatment implications. The sorting of patients into three biotypes depends on the measures used, and for related projects such as COGS, using different neurocognitive and neurophysiological measures (biomarkers), we may see a different clustering of patients and measures into biotypes from those found with the B-SNIP battery. Eventually, we will reach a biotype-related nosology, but this will take time as our science advances.

Biotypes offer insight into neural circuit dysfunction in psychosis and may well illuminate related gene network abnormalities, where both ancient common and de novo mutations contribute to polygenic risk. It may also someday guide treatment—someday. For now, the DSM is by far our most usable nosology for clinical practice since so many clinical trials use the DSM nosology. The future may allow us to sort psychotic patients in a "better" way, but for now, biotypes and endophenotypes are important research, not treatment approaches.

Bleuler wisely coined the term "the group of schizophrenias," so this research is actually following and expanding a more than 100-year-old story, using modern biomarkers and relatively new statistical measures. Our patients and their families can draw hope from this work, but our ability to transfer it into new, effective treatments or precision-guided differential treatments using current medication and psychosocial treatments is still a work in progress. The study by Clementz et al. offers one robust method in advancing our ability to subtype the confusing and toxic psychotic disorders. Progress toward precision-based treatment in psychotic disorders will probably take significant time to bear practical fruit and ease suffering. But that's how biomedical research progresses: often incrementally and almost always too slowly for patients and families waiting at the end of the laboratory-to-clinic path. Added to this, unlike cancer, psychotic disorders reside in 75 billion neurons encased in a cranial vault with dysfunctions occurring across wide-ranging neural circuits.

The biomarker-endophenotype approach allows us to assay brain function based on laboratory behaviors—a significant point of leverage for research advances. Still, we need to educate policy and budgetary officials about these terrible disorders that cause inestimable emotional pain and suffering and profound economic burden for patients and their families. Our current, exciting scientific advances are a key public educational tool to having the resources needed to advance our science and ease suffering.

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Related News: Will Biotypes Redefine Psychosis Research?

Comment by:  Irving Gottesman, SRF Advisor
Submitted 15 January 2016
Posted 22 January 2016
  I recommend the Primary Papers

Professors Braff and Kendler add to drawing a larger framework for aspirants to other novel typologies.

Time and twin studies using their typologies will be of interest to our mission. Peter McGuffin and colleagues at the Institute of Psychiatry in London, UK, devised the OPCRIT strategy for generating multiple diagnoses across multiple existing diagnostic schemes (e.g., French, German, ICD, DSM, etc.) starting from a systematic collection of essential elements of "intelligence" from history, interview, and chart data points. OPCRIT has achieved many uses across the globe, and a data base search would be rewarding to complement these discussions.


Rucker J, Newman S, Gray J, Gunasinghe C, Broadbent M, Brittain P, Baggaley M, Denis M, Turp J, Stewart R, Lovestone S, Schumann G, Farmer A, McGuffin P. OPCRIT+: an electronic system for psychiatric diagnosis and data collection in clinical and research settings. Br J Psychiatry. 2011 Aug; 199(2):151-5. Abstract

McGuffin P, Farmer A, Harvey I. A polydiagnostic application of operational criteria in studies of psychotic illness. Development and reliability of the OPCRIT system. Arch Gen Psychiatry. 1991 Aug; 48(8):764-70. Abstract

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Related News: Will Biotypes Redefine Psychosis Research?

Comment by:  Marilyn Baker
Submitted 24 January 2016
Posted 26 January 2016

I love David Braff's comments. He nails it precisely. There is unbelievable pain and suffering by patients and their families, but the recent news on biomarkers does give patients' families hope for the future. I just wish it would occur faster, but understand that it all takes time.

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