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WCPG 2013—The Influence of Genetics on Psychiatric Nosology

October 23, 2013. The release of the latest version of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) earlier this year kicked off a round of public debate about how psychiatric disorders should be classified, though the discussion in the clinical and research communities has been going on for several years (see SRF related news story; SRF Live Discussion). The World Congress of Psychiatric Genetics kicked off on October 18, 2013, with a morning plenary session titled “Defining Mental Illness Through Genetics,” wherein panelists from a broad range of backgrounds discussed the role of genetics in this classification, or nosology, of mental illnesses.

Moderator Steven Hyman from the Broad Institute just across the Charles River in Cambridge, Massachusetts, set the stage by outlining the challenges faced by the psychiatric genetics field. Hyman emphasized that the DSM and its global counterpart, the International Classification of Diseases (ICD), are not psychiatric “bibles”—as they are so often pegged in the media—but rather medical classifications. As cognitive schema imposed on data in order to make them useful, classifications are frequently complicated and messy, he said. So it’s not necessarily surprising that the current categorical system doesn’t map well onto psychiatric genetics (see SRF related news story).

In a preview of the talks to come, Hyman noted that “disorders that turn out to be heterogeneous and polygenic [like mental illnesses] are often better mapped either as spectra or as quantitative dimensions.” Given that so many genes contribute to psychiatric illness, he doubted that genetics would ever be used on its own to diagnose, but suggested that it could be used to identify useful biomarkers.

Historical and epidemiological perspectives
The first panelist was Ken Kendler of Virginia Commonwealth University in Richmond, who provided a historical framework for how genetics has influenced the classification of psychiatric disorders. Kendler, a self-proclaimed “DSM warrior,” described six phases in the relationship between nosology and genetics, beginning with early clinicians who took family history into account when assigning diagnoses. Subsequent "traditional" genetic epidemiological methods of family and twin studies and model fitting have given way—in the molecular genetic era—to candidate gene studies, genomewide association studies, and, most recently, polygenic analyses, he said. The phases have yielded three major levels of nosologically relevant genetic data: familial aggregation/heritability, single variants and aggregates of variants, and polygene scores.

Kendler emphasized that genetics has played an important and increasing role in psychiatric nosology, saying, “I don’t think this shows any signs of changing.” A critical question moving forward, he suggested, is for nosologists to determine what they want from genetics, adding that it depends on the model of psychiatric illness used. For syndromal diagnoses like DSM, nosologists generally want aggregate data, he said, so polygene scores are more useful than single variants. However, the move “toward a more etiologically based diagnosis shifts the picture,” said Kendler, “and the kind of information we get from the single variants could potentially be one of a variety of inferences” that help to clarify the disease mechanisms.

Myrna Weissman of New York’s Columbia University introduced herself as the token epidemiologist of the group. She called for the inclusion of more somatic diseases into the phenotypes of psychiatric illnesses and the consideration of pleiotropy, in which a single gene affects multiple phenotypic traits. The action of genes extends below the neck to affect the rest of the body, she noted, citing the genetic association of interstitial cystitis—a chronic inflammation of the bladder—with panic disorder as an example.

“Epidemiology is an observational science,” said Weissman, which makes it hard to address underlying disease mechanisms. She went on to describe several ways in which epidemiology can inform disease pathophysiology. Existing large, representative sample sizes can be used to generate novel phenotypes. An example of this approach is a recent study in the famous Dunedin cohort (see SRF related news story) that proposes a general “p factor” that marks risk for psychopathology (Caspi et al., 2013, in press). Longitudinal, developmental designs can help to determine the earliest phenotypes. In addition, family studies as well as those conducted on high-risk subjects can identify endophenotypes that are independent of disease expression, said Weissman. Finally, the effect of environmental exposures can be examined through birth cohort studies. “However, for any of these observations to be successful,” she cautioned, “they need to be linked to clinical and basic science approaches.”

Defining definition
Echoing Weissman, Jan Buitelaar from Radboud University Nijmegen in the Netherlands called for a reconceptualization of mental illnesses as diseases of both the brain and body. Another issue, he said, is that the psychiatric genetics field has been focused too much on identifying main gene effects. While important, these effects are sparse and relatively small. A better approach, he said, is to identify more complicated gene interactions, both with other genes and with the environment.

Buitelaar also praised the efforts to date. “So far, genetics has brought huge conceptual innovations to psychiatry,” he said, pointing to the current notion of schizophrenia as a synaptic disease. He also distinguished between two different meanings of the word “definition” in psychiatry. One meaning is concerned with describing the essence and underlying mechanisms of an illness, while the other pertains to delineating and describing the boundaries between disorders. “I think genetics is a very powerful entry into identifying these disease mechanisms at the molecular/cellular level and the neural systems level,” he said. On the other hand, he predicted that genetics would not be useful in further delineating current nosological categories (the second definition).

Buitelaar suggested that uncovering disease mechanisms will require investigations of functionality, rather than a sole focus on structure variants. In line with this, he also emphasized the importance of integrating genetics with other systems such as immunology and energy metabolism, and reiterated the need to study gene-by-environment interactions.

In contrast to Buitelaar, Michael Owen of Cardiff University in the United Kingdom focused on a slightly different use of the word “definition”: how clinicians could use genetics to diagnose mental illnesses. He first turned to the finding that genes operate across diagnostic boundaries. While Owen had expected genetic overlap between schizophrenia and bipolar disorder, he was surprised that it extended into childhood psychiatric disorders such as intellectual disability. Like earlier speakers, Owen also highlighted the pleiotropy of psychiatric illnesses.

Continuing a theme of the session, Owen commented, “I think it’s unlikely that genetic effects are going to map onto clinically useful phenotypes, though this is still a matter for empirical inquiry.” He suggested that genetic variation may be more closely related to illness course, outcome, and response to treatment—areas that need further research. In that case, genetics may play a role, but as “part of a multilevel psychiatric diagnosis” alongside other modalities of information such as imaging, where it could be used to target treatment and possibly to indicate prognosis.

A major goal of future genetics will be to try to identify both pathogenic and protective mechanisms, an important source of clues to new interventions, he said. Only by understanding the biology will we be able to solve the problems of nosology, he added. “But clearly there’s a long way to go.”

Classifications of the future
Owen acknowledged that the DSM is the best available approach, but added, “where it’s really toxic is if we let it drive our research.” On that note, the session wrapped up with a highly anticipated presentation from Bruce Cuthbert of the National Institute of Mental Health.

“We have all been serving as a prefiguration for the final panelist,” said Hyman as Cuthbert approached the microphone. Cuthbert detailed his institute’s recent undertaking to re-conceptualize mental illness manifestations for research—an effort termed the Research Domain Criteria (RDoC) project. The earlier presentations in the session focused on the need to use genetics, neuroscience, and behavioral science to inform etiology—strategies that will move toward a “true precision approach to diagnosis and treatment,” he said. However, a major roadblock of this personalized medicine is that the current standards and, indeed, “the whole machinery of our system,” are based on DSM diagnoses.

The goal of RDoC is to move beyond the DSM to classify psychiatric illnesses based on “dimensions of observable behavior … and neurobiological measures that implement these kinds of behaviors,” explained Cuthbert. The new framework is based on five domains of functioning, each consisting of component constructs that can be measured at various levels of analysis: genes, molecules, cells, circuits, physiology, behaviors, and self-reports. But the current matrix is not the final version, said Cuthbert. It’s really just a beginning framework. “We have to go back to ground zero and figure out a new way to start, and this looks like a reasonable starting place,” he added. New constructs will likely be added in the future as research progresses.

Cuthbert also emphasized that, beyond a conceptual framework, RDoC is also a research grant funding mechanism. Although the project was introduced slowly, NIMH in the future will be increasingly funding RDoC-based studies over ones that use traditional DSM diagnoses. He concluded by outlining the implications of RDoC for genetic studies. There will be a move toward studying the genetics of complex traits that cut across diagnostic boundaries, he said, an approach that will require new sampling methods and research designs.—Allison A. Curley.

Comments on Related News

Related News: Forty-Year Study Reveals Patterns of Cognitive Decline in Schizophrenia

Comment by:  Angus MacDonald, SRF Advisor
Submitted 23 September 2013
Posted 23 September 2013

The Dunedin study is not only a rich and rare resource for testing developmental hypotheses, but it has also been mined with ingenuity and resourcefulness over the years by Avshalom Caspi, Terrie Moffitt, and their colleagues to provide a number of provocative findings. In this case, they use the continuity of the sample and its multiple-informant design to test a number of useful hypotheses about the development of cognitive impairments in schizophrenia. Their population-based cohort of over 1,000 children yielded 31 cases of tightly defined schizophrenia by age 38. (The fact that this is over 3 percent of the sample, the authors argue, is explained by the comprehensiveness of their methods, suggesting that lower epidemiological estimates may underrepresent lifetime population risks.)

Their findings provide a particularly clear example of a moderate, generalized deficit in cognitive ability well before the onset of illness that, after onset, leads to further declines in fluid, but not crystalized intelligence. The example is clear because it addresses the diagnostic specificity of the deficit—the pattern was different for children later diagnosed with depression or mild cognitive impairments—and it is corroborated by the reports from others’ throughout their lives. The findings reinforce efforts by the U.S. NIH and FDA to target cognitive impairments as a symptom of interest for patients with schizophrenia.

The findings hold important methodological lessons for schizophrenia researchers, too. As pointed out by Paul Meehl in 1971, psychopathologists who co-vary or control for factors influenced by the illness may make a systematic mistake. This kind of control variable sets up false equivalences by comparing the most able patients to the least able controls.

View all comments by Angus MacDonald

Related News: Forty-Year Study Reveals Patterns of Cognitive Decline in Schizophrenia

Comment by:  James Gold, SRF Advisor
Submitted 25 September 2013
Posted 25 September 2013

The recent paper by Meier et al. is a powerful confirmation of several observations that have been in the literature for many years. First, cognitive impairment is evident from early in development in people who go on to develop schizophrenia. Second, there is a loss of intellectual function that occurs in those people at risk who later become ill. Third, this "illness-associated" impairment appears to maximally impact more "fluid" intellectual functions and largely spares "crystallized" forms of verbal knowledge (however, those functions are not fully spared, as there is evidence of subnormal performance levels from early in development).

Thus, what Meier et al. have shown is not new, but it is the first time that these key findings have all been demonstrated in the same subjects followed over time in a population-based sample. The inclusion of a group of depressed patients as well as a mild cognitive impairment control group are innovations that enhance confidence that this is an effect related to schizophrenia in particular rather than psychopathology or cognitive limitations in general. Unexpectedly, this study also found a very sizeable number of people meeting diagnostic criteria for schizophrenia who appear to have been untreated with antipsychotics for extended time periods but did receive treatment for other mental health problems. It will be interesting to learn more about the life course and treatment history of this unusual group of people.

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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."


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