Cognitive Heterogeneity in Schizophrenia Spectrum Disorders: Genetic Variation and Negative Symptom Groups

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Cognitive Heterogeneity in Schizophrenia Spectrum Disorders:

Genetic Variation and Negative Symptom Groups

Cand. Psychol Magnus Johan Engen

NORMENT: Norwegian Centre for Mental Disorders Research Oslo University Hospital

Submitted for the degree of PhD at the Department of Psychology, Faculty of Social Science, University of Oslo

Oslo, Norway 2022


© Magnus Johan Engen, 2023

Series of dissertations submitted to the Faculty of Social Sciences, University of Oslo No. 947

ISSN 1504-3991

All rights reserved. No part of this publication may be

reproduced or transmitted, in any form or by any means, without permission.

Cover: UiO.

Print production: Graphics Center, University of Oslo.




Acknowledgements ... - 6 -

List of studies ... - 8 -

Abbreviations ... - 11 -

Summary ... - 14 -

1. Introduction ... - 18 -

1.1 A brief history of schizophrenia and psychosis ... - 20 -

1.1.1 From theories of mental illness to the establishment of a modern-day psychiatric nosology ... - 20 -

1.1.2 Kurt Schneider’s pragmatic approach and the DSM-III ... - 21 -

1.2 A presentation of symptom domains, diagnostic categories, and concepts ... - 22 -

1.2.1 Symptom domains ... - 22 -

1.2.2 A brief presentation of the DSM-IV diagnoses included in this thesis ... - 23 -

1.2.3 First-episode psychosis ... - 26 -

1.2.4 First-episode psychosis and diagnostic category groups used in this thesis ... - 26 -

1.2.5 Etiology, risk factors and the neurodevelopmental hypothesis of schizophrenia- 27 - 1.3 Heritability and the role of genetics in schizophrenia ... - 29 -

1.3.1 Genome-Wide Association Studies (GWAS) and polygenic score (PGS) for schizophrenia ... - 29 -

1.3.2 Schizophrenia PGS and cognitive impairment as an endophenotype ... - 31 -

1.4 Cognitive symptoms in psychotic disorders ... - 32 -

1.4.1 The course of cognitive functioning in schizophrenia and related psychotic disorders ... - 34 -

1.4.2 Cognitive heterogeneity in schizophrenia ... - 35 -

1.5 Negative symptoms and the relationship with cognitive symptoms ... - 36 -

1.5.1 Negative symptoms ... - 36 -


1.5.2 Negative symptoms: primary or secondary, categorical or on a continuum? ... - 37 -

1.5.3 Negative and cognitive symptoms as correlated dimensions ... - 39 -

1.5.4 Negative and cognitive symptoms as predictors of functional outcome in psychotic disorders ... - 41 -

1.6 Summary and areas in need of further exploration ... - 43 -

2. Objectives ... - 44 -

2.1 The main aim of the thesis ... - 44 -

2.2 The aims of the studies ... - 44 -

3. Materials and Methods ... - 46 -

3.1 NORMENT and the TOP study ... - 46 -

3.2 Ethical considerations ... - 46 -

3.3 Participants ... - 46 -

3.3.2 The study participants ... - 47 -

3.4 Assessments ... - 49 -

3.4.1 Diagnostic assessment and symptom measures ... - 50 -

3.4.2 The negative symptom groups in Study II and Study III ... - 50 -

3.4.3 Cognitive measures ... - 51 -

3.4.3 Measures of functioning ... - 54 -

3.4.4 Genetic analyses and polygenic scores ... - 54 -

3.5 Statistical analyses ... - 56 -

4. Summary of studies ... - 60 -

5. Discussion ... - 66 -

5.1 Summary of main findings ... - 66 -

5.2 Discussion of findings ... - 67 -

5.2.1 Common genetic variants and the association with cognitive phenotypes ... - 67 -

5.2.2 Negative symptom groups and cognitive functioning ... - 71 -

5.2.3 The course of cognitive functioning by symptom groups ... - 74 -


5.2.4 Global functioning and course of global functioning ... - 76 -

5.2.3 Is heterogeneity a result of the schizophrenia definition? ... - 77 -

5.3 Methodological considerations ... - 79 -

5.3.1 Sample representativity ... - 79 -

5.3.2 Handling of possible confounders and internal validity ... - 81 -

5.4 Clinical implications ... - 83 -

6. Conclusions and recommendations for future research ... - 85 -

7. References ... - 87 -




I first became interested in psychosis while working as a clinical psychologist in an outpatient clinic for patients with psychotic disorders in 2011. Some of the most impactful and meaningful meetings with patients I’ve ever had come from working with this group in this period. Beforehand I had feared that it would be very demanding, and that the level of suffering and emotional pain would be challenging to handle. I soon discovered that the emotional impact of working with these patients was not only “manageable” for me as a professional, but that it was deeply meaningful and inspiring. It became a critical period in my professional career where I understood with new depth how intriguing the human psyche is.

I also became much more aware of the need for a richer understanding of mental illness and the need for innovative treatment approaches. Developments that will only come from an increased focus on clinically relevant research.

In 2015, as I was finishing a year working with neuropsychological assessments of children with autism and neurodevelopmental disorders, a PhD position to study schizophrenia and cognition using 10-year follow-up data appeared before me as I was browsing the advertised job opportunities. Given the impact clinical work with psychosis and with my newfound interest in cognitive assessments, I immediately applied for the position. The work presented in this thesis is the result of my journey as a PhD student at NORMENT. On this journey I have been helped and supported by some incredible people along the way. In the following is my best attempt acknowledge these efforts, although the true depth of my gratitude is not possible to express in words.

The work presented in this thesis would not be possible without the support and help from very inspiring, knowledgeable, competent, kind, and patient collaborators. First and foremost, my main supervisor, PhD Torill Ueland. Torill has been a continuous source of support throughout. In addition to communicating great trust in me and my project, she has an impressively keen eye for good scientific writing and always brings a rich perspective from clinical neuropsychology to discussions. As a leader of the cognitive group at NORMENT, she


also fostered a great collaborative atmosphere that we were many who benefited from. My co-supervisors PhD Anja Vaskinn and PhD Carmen Simonsen have both been very important in my project. I have always appreciated the very blunt honesty of Anja when commenting study design, statistics, or lack of clarity in presentation. Her feedback has sharpened my mind, which at times was a bit dull and needed sharpening. She has also been incredibly kind and encouraging at important stages of the work. Carmen has contributed with her incredibly tidy intellect and helped condense text and concepts into formats that are far more efficient and often clearer and more understandable. She also uses this talent to spot inconsistencies in presentation, and always give feedback on ideas or manuscripts that are both fresh and deeply insightful. Professor Ingrid Melle deserves a very special mention in this section. Not only have I learned to know her as a brilliant and knowledgeable professional, but I have also had the great privilege to work closely with her on one of my papers. She is a true role model for me as a scientist and as a person of great integrity. Her intuitive and quick grasp of intricate and complex problems related to research never seizes to amaze. I am proud to call her my colleague and friend. Professor Ole A. Andreassen is the leader of the NORMENT center. I first met him in my first job back in 2009 when I sat next to him as one of the clinicians participating at the hospital Christmas party. Many years later I have come to know him as a leading scientist with an incredible breadth of knowledge within the field of biological psychiatry. The Head of Unit, PhD Trine Vik Lagerberg was my boss while employed as a PhD candidate at Oslo University hospital. Trine has become a close colleague and has offered nothing but support along the way. I want to thank both Ole and Trine for the opportunity to be a PhD student at NORMENT. Professor Kjetil Sundet is a leading figure in Norwegian neuropsychology. I want to thank him for answering my calls and sharing from his vast knowledge and wisdom.

I would like to thank co-authors, friends and colleagues who have been important at NORMENT (in no particular order): Attila Szabo, Srjan Djurovic, Eivind Bakken, Line Gundersen, Camilla Büchmann, Stine Holmstuel Olsen, Margrethe Collier Høegh, Olav B. Smeland, Francesco Bettella, Rut Kristine Vik, Gina Åsbø, Camilla B. Flaathen, Linn Rødevann, Line Widing, Elina Reponen, Kirsten Wedervang-Resell.


A special mention goes to my dear colleague and former “roommate” Siv Hege Lyngstad. We have been sharing an office for long periods of time, and have been through shifting moods together along the PhD journey. We are now close collaborators in the Bipolar treatment unit at Nydalen DPS, and I could not be happier with our collaboration. Siv Hege is just a very special doctor and human being. Erlend Strand Gardsjord finished his PhD at NORMENT as I was working there. He did not formally contribute as a co-author, but he made my stay at the center very enjoyable and far more exciting than it could have been. Both because he shares my interest for foundational issues with science in general and mental health research in particular, but mostly because we share the same sense of humor. Erlend is now no longer a co-worker, but he remains a dear friend.

My dearest friends and neighbours Hilde and Ivar Goksøyr. We built a house together during the work with this PhD. Now we continue to build our lives together. I could not have wished for better friends and neighbours. Thank you.

Finally, I would like to thank my dear family. To my supportive parents who have always encouraged me to believe in what I do. I am forever grateful to have had such support. To my dearest sister Gro, my brother in-law Fredrik Scheinert and my three nieces. Thank you for all the support. Most of all: Thank you, Kjersti. You are the love of my life. By handing in this thesis, we are getting parts of our life together back. You are the strongest person I know of.

Thank you for being there for me throughout.

To my son Øyvind. No one is dearer.




Study I: Engen, M. J., Lyngstad, S. H., Ueland, T., Simonsen, C. E., Vaskinn, A., Smeland, O., Bettella, F., Lagerberg, T. V., Djurovic, S., Andreassen, O.A., Melle, I. (2020).

Polygenic scores for schizophrenia and general cognitive ability: associations with six cognitive domains, premorbid intelligence, and cognitive composite score in individuals with a psychotic disorder and in healthy controls. Translational psychiatry, 10(1), 1-9.

Study II: Engen, M. J., Simonsen, C., Melle, I., Faerden, A., Lyngstad, S. H., Haatveit, B., Vaskinn, A., Ueland, T. (2019). Cognitive functioning in patients with first- episode psychosis stratified by level of negative symptoms: A 1-year follow-up study. Psychiatry research, 281, 112554.

Study III: Engen, M. J., Vaskinn, A., Melle, I., Færden, A., Lyngstad, S. H., Flaaten, C. B., Widing, L.H., Wold, K.F., Åsbø, G., Haatveit, B., Simonsen, C., Ueland, T. (2022).

Cognitive and Global Functioning in Patients With First-Episode Psychosis Stratified by Level of Negative Symptoms. A 10-Year Follow-Up Study. Frontiers in psychiatry, 545.




ANOVA = Analysis of Variance

ANCOVA = Analysis of Covariance

BD = Bipolar Disorder

CDSS = Calgary Depression Scale for Schizophrenia

CVLT-II = California Verbal Learning Test-II

DDD = Defined Daily Dosage

D-KEFS - Delis-Kaplan Executive Functioning System

FEP = First-Episode Psychosis

GAF-F = Global Assessment of Functioning - Functioning

GAF-S= Global Assessment of Functioning - Symptoms

GWAS = Genome-Wide Association Study


HVLT - Hopkins Verbal Learning Test

IQ = Intelligence Quotient

MAF = Minor Allele Frequency

MANOVA = Multivariate Analysis of Variance

MANCOVA = Multivariate Analysis of Covariance

MDD = Major Depressive Disorder

NART = National Adult Reading Test

NOS = Not Otherwise Specified

PANSS = Positive and Negative Syndrome Scale

PGSCOG = Polygenic Score for Cognition

PGSSCZ = Polygenic Score for Schizophrenia

PRIME-MD = Primary Care Evaluation of Mental Health Disorders


SCID-I = Structured Clinical Interview fro DSM-IV Axis I Disorders

WAIS-III = Wechsler Adult Intelligence Scale III

WASI = Wechsler Abbreviated Scale of Intelligence

WMS-III = Wechsler Memory Scale III




Cognitive impairments are widespread in schizophrenia and related psychotic disorders. A considerable body of research has established that mild cognitive impairment in schizophrenia is evident long before illness onset (as far back as early childhood). Impairments become more marked around the first psychotic episode, whereafter they persist even in periods of symptomatic remission. They constitute a stable core feature of the disorder throughout the illness course and are robustly associated with occupational and social functioning. Moreover, being a core feature in a heritable disorder like schizophrenia, it has been suggested that the impairments may be rooted in the same genetic underpinnings that confer risk for disorder itself. However, schizophrenia is far from a uniform illness entity. A great deal of heterogeneity for most aspects of the disorder, including cognitive impairments, is gaining increased attention. Moreover, transdiagnostic and dimensional approaches to investigate the different phenomena seen in psychotic disorders (non-affective and affective) is increasingly applied.

Negative symptoms have always been considered core to schizophrenia. However, as for cognitive impairments, there is a similar trend in research where these symptoms are increasingly recognized as transdiagnostic phenomena relevant across the spectrum of psychotic disorders. As with cognitive impairments, negative symptoms are also strongly linked to real world functioning and are more stable features than positive symptoms, such as delusions and hallucinations.

It has been underlined for at least four decades that some persons with schizophrenia who suffer from severe and persisting negative symptoms also suffer from more severe cognitive impairments. More recently, this relationship between cognitive impairments and negative symptoms has gained renewed interest, and there is currently ongoing research into the connection between these two important symptom dimensions, investigating both cognitive and negative symptoms as dimensional and transdiagnostic phenomena across psychotic disorders.


Inspired by these findings and recent research trends, the main aim of the current thesis was to increase our understanding of cognitive heterogeneity in psychotic disorders by investigating:

§ How common genetic variants conferring risk for schizophrenia are related to the variation (i.e. heterogeneity) we observe in cognitive functioning in separate cognitive domains both participants with a psychotic disorder and in the healthy population.

§ How common genetic variants associated with cognition in the general population are associated to cognitive domains by associating these variants with cognitive domain scores in participants with a psychotic disorder and in healthy controls separately.

§ How groups defined by level of negative symptoms over the short term (1 year) differ in cognitive performance compared to each other and to healthy controls, both at baseline and with respect to cognitive course.

§ How groups defined by level of negative symptoms over the long term (10-year course) differ in cognitive performance compared to each other and to healthy controls, both at baseline and with respect to cognitive course.

§ How groups defined by level of negative symptoms over the long term compare on the course of functioning.

In Study I we sought to gain new knowledge about the genetic underpinnings of cognitive functioning in psychotic disorders. Based on previous research, we investigated how a set of well-defined cognitive domains were associated with common genetic variants conferring risk for schizophrenia (PGSSCZ) as well as common genetic variants shown to explain differences in cognitive ability in the general population (PGSCOG). We also wanted to compare the effects of these genetic influences in participants with a psychotic and healthy controls separately. In Study II we developed a method for stratifying participants with first-episode psychosis (FEP) (defined as non-affective i.e. schizophrenia spectrum disorder included within the first year of adequate treatment) according to level of negative symptoms from baseline to 1-year follow- up. Participants were here grouped together based on whether they had no (NNS), mild (MNS), transitory (TNS), or sustained negative symptoms (SNS). The primary aim was to investigate baseline differences in cognitive functioning, and the course of cognitive


functioning over one year between the negative symptom groups. In Study III we employed the same method for subtyping as in Study II using 10-year follow-up data. Our aim in Study III was to investigate baseline differences in cognitive functioning and 10-year cognitive course between negative symptom groups. To assess functional consequences, we also explored group differences in global functioning and 10-year course of global functioning across groups, and the relation to differences in cognitive functioning.

In Study I we found no association between the PGSSCZ and any of the cognitive domains either in the sample of healthy controls or in participants with a psychotic disorder. The PGSCOG was associated with the working memory domain, but only in healthy controls. The association of PGSCOG with working memory in healthy controls was stronger than in participants with a psychotic disorder with a statistically significant effect. Overall, our findings did not support the notion that variation in well-defined cognitive domains is associated with common genetic variants conferring risk for schizophrenia.

In studies II and III we found that level of negative symptoms over both short- (1-year) and long-term (10-year) follow-up was associated with cognition in FEP participants at baseline.

The largest differences in cognitive functioning were between the NNS and SNS groups, with the SNS group showing the largest impairments. Though the healthy controls performed with mean scores nominally better than all negative symptom groups, the NNS group was not significantly outperformed by healthy controls on any domain or the cognitive composite score. We did not find that the negative symptom groups differed in cognitive course over the short- or long-term follow-up with most groups showing improvement of similar magnitude in cognitive performance. In the 10-year follow-up we observed a cognitive course with statistically significant improvement for the entire sample in verbal learning and memory, executive functioning, and the cognitive composite. Long-term course of global functioning in the FEP sample as a whole also showed significant improvement with no difference between groups in course. At 10-year follow-up the SNS group had the poorest level of functioning.

There was an independent effect of cognition on level of functioning, not accounted for by negative symptoms alone.


From studies II and III, we see that both short- and long-term course of negative symptoms is associated with cognitive functioning in FEP, particularly when contrasting the NNS and SNS subgroups. This implies very different treatment needs and should be taken into consideration in the clinical setting for improved individualization of treatment. Furthermore, individuals who do not show any signs of negative symptoms early in the course of illness may be a group with better cognitive functioning and a better prognosis.


1. I


Difficulties with complex problem-solving, attention, memory, and a range of other cognitive abilities are hallmark features of schizophrenia1 and related psychotic disorders (Heinrichs &

Zakzanis, 1998; Mesholam-Gately et al., 2009; Aas et al., 2014). These signs of impaired cognitive functioning2 are apparent from early childhood (Meier et al., 2014), and children who struggle with academic performance in school are at greater risk of later developing schizophrenia (Maccabe, 2008). Schizophrenia has a prevalence of about 1%, affecting an estimated 21.5 million people across the globe and is a major contributor to the global burden of disease (Whiteford et al., 2015).

The American mathematician John Forbes Nash jr. made groundbreaking contributions to game theory which awarded him the Nobel Prize in Economic Sciences in 1994. While at Yale University, he started to experience hallucinations and formed paranoid delusions around the age of 30 and was diagnosed with schizophrenia at age 31 (Nasar, 2011). Reconciling the brilliance of Nash with a disorder characterized by cognitive impairments might seem a challenge, but heterogeneity – the variation of symptoms, traits, and characteristics – is the rule rather than the exception with psychotic disorders. This also holds true for cognition (Tan et al., 2021; Vaskinn et al., 2020).

Though individuals with schizophrenia vary in their degree of cognitive impairments, it is considered a core feature of the illness, and by some leading researchers considered a distinguishing feature setting it apart from affective psychoses (Kahn & Keefe, 2013). Impaired cognitive function is heritable (Tripathi et al., 2018), apparent before illness onset (Meier et al., 2014) and a crucial predictor of long-term functional outcome (Bowie & Harvey, 2006), especially when accompanied by negative symptoms (Lin et al., 2013). Moreover, the frequent

1 Schizophrenia, psychotic disorders, (broad) schizophrenia spectrum disorders and psychosis are often used interchangeably in the research literature when referring to related research.

2 The terms cognitive impairment and cognitive symptoms are used throughout this thesis.


co-occurrence of cognitive impairments and negative symptoms (e.g. flat affective expression and apathetic withdrawal from healthy activities), has been highlighted as important illness features from the first historical descriptions of schizophrenia (Bleuler, 1950; Hoenig, 1983;

Loch, 2019). Arguably, negative symptoms constitute the chief challenge for the successful treatment of the disorder (Granholm et al., 2022).

Though schizophrenia develops as the result of an interplay between multiple causal factors, it is a disorder well-known to run in families (Kendler & Gardner, 1997; Kendler et al., 1993).

There is also evidence suggesting similar heritability of cognitive functioning in schizophrenia as in non-psychiatric populations (Blokland et al., 2017). Consequently, there is a need to explore the genetic roots of cognitive impairment in schizophrenia to gain understanding of illness mechanisms.

Furthermore, there are no available effective pharmacological treatments for either cognitive (Robbins, 2019) or negative symptoms (Correll & Schooler, 2020). Interestingly, cognitive remediation targeting cognitive impairments has been shown to significantly reduce negative symptoms (Cella et al., 2017), further highlighting the importance of the relationship between these two symptom dimensions.

The main aim of this thesis has thus been to investigate how differences in the genetic risk for schizophrenia and differences in negative symptoms may impact on the cognitive heterogeneity in psychotic disorders. We first (Study I) explored how polygenic risk for schizophrenia and polygenic scores for cognition were related to specific cognitive domains in participants with psychotic disorders (affective and non-affective psychosis) and in healthy controls (Engen et al., 2020). In studies II and III we investigate relationship between cognitive and negative symptoms over the short- (1-year) (Engen et al., 2019) and long-term (10-year) (Engen et al., 2022) course in participants with first-episode psychosis (FEP; schizophrenia spectrum disorders included within the first year of adequate treatment for psychosis).


1.1 A brief history of schizophrenia and psychosis


Hippocrates of Cos in the 5th century BC hypothesized that “diseases of the mind” arise from problems within the organ of the brain. Roughly another two and a half millennia would pass before ‘psychosis’ as a term was first introduced in the psychiatric literature in 18473 (Canstatt, 1847). Shortly afterwards the two types of psychotic disorders, manic-depressive illness and dementia praecox, were described by the German psychiatrist Emil Kraepelin (1856-1926). The former condition was named due to co-occurring affective symptoms, while the latter had two specific characteristics: the presence of cognitive impairment and onset in late adolescence/early adulthood with a more severe course and outcome (Kahn & Keefe, 2013).

Kraepelin had a firm belief that the discrete syndromes of mental illness was based on anatomical, etiological or symptomatologic criteria. Based on this nosology, he conducted groundbreaking longitudinal research by systematically following up his patients and later concluded that dementia praecox was heterogeneous both in terms of symptom formation and outcome. No single symptom could be found in all patients and 12.5 % (16 out of 127) were considered fully recovered at their follow-up (Hoenig, 1983).

Building on Kraepelin’s work, Eugen Bleuler4 (1857-1939) was less convinced that dementia praecox was a distinct mental illness, but rather constituted a group of psychoses in which disintegration between different faculties of the mind was the common feature. Thus, he

3 Canstatt used the term to refer to ‘psychich neurosis’, which at the time referred to any psychological manifestation of disease in the central nervous system.

4 As an interesting side note, Sigmund Freud is viewed by many as representing an opposing view on psychiatry to Emil Kraepelin, by placing the psyche and its contents at the center of his theory. Bleuler is, together with his assistant C. G. Jung, credited with bringing psyche into the understanding of dementia praecox.


introduced a dimensional view, rather than the Kraepelinian categorical “dichotomy”, and also importantly regarded hallucinations and delusions as secondary to the cognitive and negative symptoms. Because fragmentation of mental faculties were central to his theory, he proposed the term schizophrenia, derived from ‘schizein’ which means split and ‘phren’

meaning mind, as an alternative to dementia praecox (Bleuler, 1950).

While Bleuler coined the term ‘schizophrenia’ and made significant contributions to developing terms to describe the syndrome, he also expanded the concept by including a wide range of symptoms bordering on normality (e.g. moodiness, anomalies in personality, anergia hypochondriasis etc.). For this he used the diagnostic term ‘latent schizophrenia’ (Bleuler, 1950). Wyrsch, a former student of Bleuler, recalls how this loosening or widening of the diagnostic criteria led to a more liberal and different diagnostic practice in Switzerland than in Germany which became the topic of a debate held at a congress in Basel in 1929 (Wyrsch, 1966). The need for clear and reliable diagnostic criteria was already then obvious.


Kurt Schneider (1887-1967) followed in the footsteps of predecessors who had developed a phenomenological approach to studying mental illness, in contradiction to the Kraepelinian biological focus (Hoenig, 1983). Schneider firmly held the view that psychiatry was best viewed as a pragmatic science, and that speculation about true etiology was premature and deterring of progress in the field. Building on the concepts developed by Kraepelin and Bleuler, he developed atheoretical diagnostic criteria which were based on operationalizable symptoms further divided into 1st and 2nd rank dependent on qualitative features of the delusions or hallucinations (e.g. delusions of thought withdrawal). He did not attempt to change the underlying concept of schizophrenia, but argued that the criteria for making the diagnosis had to be reliable, atheoretical and devoid of hypotheses about etiological nature (Hoenig, 1983).

This emphasis on operationalizing symptoms to achieve reliability is the reason Schneider is cited to have anticipated the reasoning behind the later versions of the Diagnostic and Statistical manual of Mental disorders (DSM) (Crowhurst & Coles, 1989).


Because the first two versions of the DSM relied heavily on underlying theory and not empirical studies, issues with reliability previously addressed by Schneider persisted.

However, in 1970, a paper proposed a method for validating a psychiatric nosology based on etiology and psychopathological symptoms (Robins & Guze, 1970). Based on these suggestions, a paper proposing a criteria-based diagnostic system for psychiatric disorder was published two years later (Feighner et al., 1972). The ideas put forward in these papers formed the basis of the DSM-III (American Psychiatric Association, 1980), which was based on operationalized diagnostic criteria also tested for inter-rater reliability. This same logical structure followed in the DSM-IV (American Psychiatric Association, 2000) which is used in the current thesis and the more recent DSM-5 (American Psychiatric Association, 2013).

1.2A PRESENTATION OF SYMPTOM DOMAINS, DIAGNOSTIC CATEGORIES, AND CONCEPTS In the following, a brief description of relevant concepts and diagnoses used in the DSM-IV (American Psychiatric Association, 2000) is presented, followed by definitions of the diagnostic spectrum terms used in the thesis. Lastly, the proposed psychosis continuum model is presented and discussed.


Positive and negative symptoms

J. Hughlings Jackson used the terms positive and negative symptoms in neurology to distinguish between effects of damaged nervous tissue. The resulting effect of the damage was either a lack of normal function (e.g. paralysis), called a negative condition or element, or an “excessive nervous discharge (great liberation of energy)” (e.g. post-epileptic mania), which was called a positive condition (Hughlings-Jackson, 1881). The terminology was adopted by psychiatry and is used in current nosology of psychotic disorders (American Psychiatric Association, 2000).


Negative symptoms

The behaviors characterized as negative symptoms in schizophrenia include restrictions in the range and intensity of emotional expression (affective flattening), in the fluency and productivity of thought and speech (alogia), and in the initiation of goal-directed behavior (avolition) (American Psychiatric Association, 2000). However, the more recent conceptualization of negative symptoms include five sub-symptoms: avolition-apathy (a marked reduction in motivation leading to reduced initiation and persistence in goal-directed activity), anhedonia (reduction in the capacity to experience pleasure), asociality (a lack of interest in social activities or engaging in social relations), blunted affect (reduced expression of affect in facial expression, body language or voice prosody), and alogia (reduced production of speech and diminished spontaneous elaboration in conversation) (Correll & Schooler, 2020).

Positive symptoms

Delusions, hallucinations and (sometimes) disorganized thought and behavior, are grouped together under the umbrella term positive symptoms. Delusions are false beliefs about the world which an individual continues to hold despite clear and unambiguous evidence to the contrary. To be characterized as a clear symptom of psychosis the delusion must contain a belief which falls outside the norm of known cultures or subcultures. The definition of a hallucination is quite simply a sensory experience when there is no stimulation of the relevant sensory organ. In psychotic disorders, auditory hallucinations in the form of voice hearing are the most typical, although hallucinations can occur in any sensory modality. Disorganized thoughts and behavior refer to classes of symptoms which reveal the chaotic nature of the patient’s inner world during a psychotic episode. Often expressed indirectly as irrational behaviors or expression of thoughts which are incoherent or formed in a disorganized manner.



The three studies in this thesis are part of a larger umbrella project, the Thematically Organized Psychosis (TOP) study. The first participants were recruited in 2003, using the then available DSM-IV (American Psychiatric Association, 2000) for diagnostic purposes. To ensure continuity and consistency in the diagnostic practice, participants interviewed at follow-up are also evaluated with the DSM-IV. The TOP study includes participants meeting criteria for the diagnoses presented below:


There are six criteria (A-F) necessary to be met for a diagnosis to be given. These specify (A) a clear level of psychotic symptomatology, (B) a requirement that these symptoms cause social, occupational or academic impairment, and (C) that continuous signs of the illness have been present for a minimum of 6 months. Moreover, the diagnosis requires that the symptoms (D) do not significantly overlap with affective episodes, (E) are not better explained by substance abuse or a general medical condition, or (F) are not better understood as symptoms of a pervasive developmental disorder. The A-criterion requires a minimum of two out of the following symptoms5: delusions, hallucinations, disorganized speech, grossly disorganized or catatonic behavior. In the diagnostic system schizophrenia, along with schizoaffective disorder, requires more and longer lasting psychotic symptoms than any other mental illness.

In any given adult population, the prevalence of schizophrenia is approximately 1% (Lauriello et al., 2004). The disorder has a typical onset around adolescence and early adulthood, affecting males somewhat more frequently than women.

Schizophreniform disorder

The main difference between schizophrenia and schizophreniform disorder is the symptom duration and the impact on functioning. The total duration of symptoms (including the

5 An exception to this is if a person has bizarre delusions. Then, this symptom alone suffices to meet the A-crierion.


prodromal, active and residual phases) is more than one month but less than 6 months.

Moreover, significant impairment in functioning as described for schizophrenia may occur but is not required.

Schizoaffective disorder

When criteria for schizophrenia are met, however with significant overlap with episodes meeting the criteria for either a major depressive episode or for mania, a diagnosis of schizoaffective disorder is given if there is at least two weeks with active psychotic symptoms without concurrent affective symptoms. Significant impairment in functioning is common but not a requirement.

Brief psychotic disorder

As the name suggests, brief psychotic disorder is a diagnostic category for psychotic symptoms of relatively short duration. One or more of the following symptoms for less than a one-month period qualifies for the diagnosis; delusions, hallucinations, disorganized speech, grossly disorganized or catatonic behavior. Functional impairment is not a diagnostic requirement but may occur.

Delusional disorder

This disorder is mainly characterized by non-bizarre delusions. If hallucinations occur, they are not prominent, and must be related to the theme of the delusions. Functional impairment is limited and only related to consequences of the delusions.

Psychosis not otherwise specified (NOS)

This diagnostic category is characterized by psychotic symptomatology which does not meet criteria for any other psychotic disorder (e.g. hallucinations lasting longer than one month). It


is also a category that is used when information about symptoms is insufficient to make a specific diagnosis, or for when there is contradictory information which makes it difficult to make a specific diagnosis.


Up until the turn of the millennium participants in schizophrenia studies were largely recruited as samples of convenience based on those receiving psychiatric health care services throughout the world. These studies have thus included individuals with long histories of illness and chronicity. Research questions related to the early clinical course of the illness, treatment effects, biological correlates and phenomenological aspects related to the illness duration were thus confounded by morbidity and chronicity, and the need for systematic inclusion of first-episode psychosis (FEP) participants was increasingly recognized (Kirch, Keith, et al., 1992; Kirch, Lieberman, et al., 1992).

Inclusion criteria vary between so-called first-episode studies. Based on the potential diagnostic instability in the early illness phases, some studies include all participants meeting the criteria for broad psychosis spectrum episode while other studies limit their inclusion to more narrowly defined first-episode schizophrenia (Keshavan & Schooler, 1992). There are also variations in the definition of “first episode”, which can be defined as the first treatment contact in some studies, a limited time on adequate antipsychotic medication use in others or a limited duration of psychosis in a third groups of studies (Breitborde et al., 2009). Since the duration of untreated psychosis is a significant predictor of course and outcome (Friis et al., 2015), the latter definition will however significantly impact the generalizability of findings.


The term FEP in this thesis is used to describe participants with a non-affective psychotic disorder included within their first year of receiving adequate treatment for psychosis. In this thesis the term psychotic disorders is defined as both affective and non-affective (i.e. bipolar spectrum disorders) with a history of psychosis. This term covers the clinical sample of Study


I. Schizophrenia spectrum disorder is defined as all non-affective psychoses. This term describes the clinical samples in studies II and III. The term schizophrenia and related psychotic disorders is used interchangeably with psychotic disorders a select few times for the purpose of clarity, underscoring the breadth.


The precise etiology of schizophrenia is still not understood but is thought to be based in the interplay between a genetic vulnerability and environmental risk factors (Lieberman & First, 2018; Owen et al., 2016). With the growing understanding of how complex this disorder is, the models used to describe the etiology have evolved.

By the late 1980s there was accumulating evidence suggesting the crucial role of early life environmental hazards in the risk of developing schizophrenia. Findings from monozygotic twins discordant for schizophrenia showed that the affected twin had larger cerebral ventricles in the brain and a seemingly higher exposure to severe perinatal hazards (Reveley et al., 1982). This association with pre- and perinatal hazards in discordant monozygotic twins was reproduced (Reveley et al., 1984) and confirmed in singletons (Lewis & Murray, 1987).

These findings suggested that individuals with genetic risk were sent on the path to develop schizophrenia through the interaction with early environmental stressors. Based on these and similar findings, the first formulations of the neurodevelopmental hypothesis of schizophrenia were proposed (Murray & Lewis, 1987; Weinberger, 1987).

The neurodevelopmental hypothesis is currently the most widely accepted model for integrating genetic, neuroscientific, cognitive, and clinical evidence, and is by far the most influential theory in recent decades (Fatemi & Folsom, 2009; Murray et al., 2017). This wide impact has by some been attributed to its simplicity and flexibility (Murray et al., 2017). Going against the Kraepelinian view of schizophrenia as a degenerative and discrete illness, the hypothesis allows for a wide range of evidence to be integrated to describe the path to schizophrenia. Starting with an early focus on pre- and perinatal risks and insults, the


development of schizophrenia is currently found to be associated with a wide range of environmental risk factors from pregnancy to the typical illness onset in late adolescence or early adulthood (Insel, 2010; Murray et al., 2017; Owen & O'Donovan, 2017). Childhood trauma, smoking tobacco, cannabis use, migration, and living in a dense urban environment are a selection of risk factors currently known to associate with schizophrenia (Cantor-Graae

& Selten, 2005; Heinz et al., 2013; Popovic et al., 2019; Stanton et al., 2020; van Os et al., 2010;

Wootton et al., 2020). However, the task of disentangling true risk factors from risk indicators and possible confounders, and proposing models specifying causal mechanisms, remains challenging. In line with the increased recognition of the complex nature of the disorder, more nuanced formulations of the neurodevelopmental hypothesis have been proposed in recent years. Arguing that the heterogeneity of schizophrenia separates it from other neurodevelopmental disorders such as autism, Thomas Insel proposed the view of schizophrenia as a collection of neurodevelopmental disorders with unknown cause (Insel, 2010). More recently, reformulations of the hypothesis into the neurodevelopmental continuum (Owen & O'Donovan, 2017), or the developmental risk factor model (Murray et al., 2017) have been made. These changes also integrate the view that psychotic disorders are best understood as lying on a continuum of disorders (Owen & O'Donovan, 2017; van Os et al., 2009).

Though the neurodevelopmental model is widely recognized, the question of whether progressive brain changes follow the onset of schizophrenia, making it a neurodegenerative disorder, persists in the literature. Recent studies suggesting possible accelerated aging effects apparent at long follow-up intervals have led some authors to suggest that schizophrenia is a neurodegenerative disorder (Stone et al., 2022). In contention of this view, critics hold that these findings do not result from direct genetic effects but the vicious cycle of deterioration caused by hazardous life style after illness onset (e.g. stress, poor nutrition, poor exercise, tobacco, cannabis, over-medication etc.) (Murray et al., 2022).



It has long been known that severe mental illness runs in families. Twin studies have confirmed the important role of genes in the liability to develop schizophrenia. The concordance rate for monozygotic twins is 33% and 7% for dizygotic twins, with a heritability of around 80% (Hilker et al., 2018; Sullivan et al., 2003). Though these estimates have been called into question on methodological grounds (Torrey & Yolken, 2019), there is little doubt that genetics play a central role in the disorder. Nevertheless, the search for replicable findings proved fruitless for many years using methods such as linkage analysis (Risch & Merikangas, 1996) and the

“candidate gene” approach (Gejman et al., 2011). Several reasons for the failed early attempts to make discoveries in molecular genetics have been offered, but perhaps the most important is the lack of knowledge about the genes themselves (Henriksen et al., 2017).

This realization, combined with new technology enabling more efficient genotyping, set the stage for transnational collaborations to increase sample sizes. Together, this has enabled a new type of genetic study, the genome-wide association study (GWAS), where genetic variants associated with a select phenotype can be discovered without prior knowledge or hypotheses about the genetic variants themselves.


The human genome contains almost 3 billion base pairs (Venter et al., 2001). Even though only a fraction of these variants is relevant for individual variation on phenotypic traits (alleles on most loci on the genome is shared between humans and animals), the variants investigated in a GWAS, termed single nucleotide polymorphisms (SNPs), amount to the hundreds of thousands and more (Bush & Moore, 2012; Visscher et al., 2017). These SNPs are defined by frequency of the second most common allele (e.g. > 1% occurrence), called minor allele frequency (MAF) (Turnpenny, 2016). This threshold excludes the rarest genetic variants and is the reason why SNPs are also termed “common variants”.


A GWAS is most commonly set up with a case-control design where the phenotypic trait of interest (e.g. schizophrenia) is present in the case population and then compared with a sample which does not have this trait (controls). Because the number of variants studied is so large, and because the effect of each SNP on the phenotypic expression is so small, statistical power is crucial to the success of a GWAS. The number of tests for associations performed on SNPs introduces a multiple comparisons issue which requires the significance threshold for detection of true variants to be set at the strict level of 5x10-8 (Pe'er et al., 2008) to avoid large amounts of false positives. The strength of the method is that genotyped data can be used to detect significant associations between genetic variants and any phenotype of interest.

Associations are usually made to SNPs, but copy number variants, mosaic events, haplotypes or any other type of genetic data may also be utilized (Tam et al., 2019).

Since the GWAS method was introduced a little more than 10 years ago it has proved to be a promising tool for genetic research (Visscher et al., 2017). Since it is a method that allows for the hypothesis-free search for genetic variants associated with a phenotype, it has allowed researchers to inquire the genome for knowledge without prior assumptions, reducing the risk of studying false positives, which was a common problem with the candidate gene approach (Uffelmann et al., 2021). In contrast to previous methods the GWAS approach has proven to detect genetic variants in discovery samples that replicate in independent samples, which is the gold standard in validating findings (McGuire et al., 2021). The number of potential associations are however very high, leading to a need for correction for the potential of spurious associations. The correct p value for a statistically significant finding in a GWAS study is thus most often set at 5 x 10-8.

Variants with lower levels of association to schizophrenia may however also impact on genetic risk. One way of including this information is to summarize the number of risk alleles with the effect size of variants at different levels of significance, into an individual risk score for the individual in the form of a polygenic score (PGS) (Smeland et al., 2020; Torkamani et al., 2018;

Uffelmann et al., 2021; Zheutlin & Ross, 2018). Currently, the utility of the PGS for the majority of disease phenotypes is limited in a clinical settings (Torkamani et al., 2018; Zheutlin & Ross,


2018), with one of the best-performing PGSs to date being for glaucoma where individuals at risk in the top decile of quantified risk have a 4.2-fold increase over the bottom 90% (Craig et al., 2020). However, PGSs hold promise as tools for improved understanding of the genetic architecture of psychiatric phenotypes (Zheutlin & Ross, 2018).


In 2009 the first use of the polygenic score was described using data from a schizophrenia GWAS of 3,322 cases and 3,587 healthy controls from the Psychiatric Genetics Consortium PGC) (Purcell et al., 2009). However, in 2014 the PGC had grown to 36,989 cases and 113,075 healthy controls, and SNPs associated with 108 unique genetic loci were detected (Schizophrenia Working Group of the Psychiatric Genomics, 2014). Although a breakthrough for psychiatric genomics, the findings only explain about 7% of the risk for developing schizophrenia (Schizophrenia Working Group of the Psychiatric Genomics, 2014).

Both cognitive ability and schizophrenia are considered complex traits substantially influenced by genetic factors (Lichtenstein et al., 2009; Polderman et al., 2015). Moreover, cognitive symptoms are found in attenuated form in first-degree relatives of probands with schizophrenia (D. C. Glahn et al., 2010; Sitskoorn et al., 2004; Snitz et al., 2006). This indicates that unaffected relatives may carry susceptibility variants to schizophrenia influencing cognitive functioning. Moreover, it suggests cognitive impairment may be a promising endophenotype (i.e. feature of the disorder strongly linked to genetics) for schizophrenia (D.

C. Glahn et al., 2010). Hence, a growing literature has been published investigating the genetic overlap between cognitive function and schizophrenia (Lencz et al., 2014; Smeland et al., 2019) and how the schizophrenia PGS associate with cognitive phenotypes (Nakahara et al., 2018; Ranlund et al., 2018; Shafee et al., 2018; Toulopoulou et al., 2019; Walton et al., 2014;

Wang et al., 2018; Xavier et al., 2018). While associations between schizophrenia PGS and cognitive phenotypes have been reported for several cognitive domains from the MATRICS Consensus Cognitive Battery (MCCB) in one study (Nakahara et al., 2018; Schaupp et al., 2018), several others have not found the PGS associated with cognitive phenotypes (Terwisscha van Scheltinga et al., 2013; Walton et al., 2014; Whalley et al., 2016; Xavier et al., 2018). One study


reported the PGS to correlate negatively with a measure of general cognitive ability, but only in healthy controls and not in individuals with psychosis (Shafee et al., 2018). This latter finding was interpreted to suggest that cognitive variation in individuals with psychosis might be more affected by environmental factors of the illness, making the genetic link to PGS weaker.

In a paper giving a narrative review of findings on the PGS and cognition, the authors describe problems concerning the heterogeneity of test batteries and the frequent use of underpowered samples (Schaupp et al., 2018). The authors encourage further study of well- defined cognitive domains in large samples for improved insight into how genetic risk of schizophrenia is linked to impairments cognitive phenotypes.

Both cognitive and negative symptoms are frequently apparent before onset of the first episode (Lyne et al., 2018; Woodberry et al., 2008), and genetic variants conferring risk for schizophrenia are found to be associated with both of these symptom dimensions in larger studies (Mistry et al., 2018; Smeland et al., 2019), even though findings are yet inconclusive (Richards et al., 2019). The potential interaction of genetic and environmental risk leading to the development of negative and/or cognitive symptoms thus remain an important topic. In particular, the early manifestation of cognitive symptoms may offer opportunities for early intervention in populations at clinical high risk in the future (Seidman & Mirsky, 2017).


The Latin word cognoscere (to know), means to recognize, cognition means to conceptualize or to think (Sternberg & Sternberg, 2016). The field of neuropsychology is concerned with the measurement of cognition. To this end numerous tests and methods have been developed to map cognitive functions with the ambition to understand how these functions are processed in the brain (Lezak et al., 2004). The neuropsychological assessment of patients with schizophrenia began as early as the 1940s using tests for word association, proverbs and object sorting (Mirsky, 1969; Seidman, 1983). Describing what was then termed ‘formal thought disorder’, assessment of cognitive functions expanded in focus in the decades to


follow (Nuechterlein & Dawson, 1984). The increasing variation of tests used across studies and uncertainty regarding their psychometric properties made interpretation of results challenging. Recognizing the need to develop improved treatments for cognitive symptoms in schizophrenia, the National Institute of Mental Health launched the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) initiative (Marder &

Fenton, 2004; Nuechterlein et al., 2008). As an important part of this initiative, a group collaborated to evaluate numerous tests used in the field to cover seven cognitive domains, which resulted in the MCCB (Nuechterlein et al., 2008).

Meta-analyses from the large number of studies on cognitive symptoms in schizophrenia confirm that impairments in schizophrenia are found in the cognitive domains of learning, memory, working memory, vigilance/attention, processing speed, executive function and general cognitive ability in both chronic samples (Heinrichs & Zakzanis, 1998) and in first- episode schizophrenia (Mesholam-Gately et al., 2009). These global cognitive impairments are found in samples across the world and are strongly associated with poor functional outcome (Bowie & Harvey, 2006; Hill et al., 2013; Mesholam-Gately et al., 2009; Schaefer et al., 2013).

Moreover, in line with the previously described continuum of symptom severity within the broader psychosis spectrum, cognitive symptoms have increasingly been studied in bipolar disorders (Bora & Pantelis, 2015; Bortolato et al., 2015; Grande et al., 2016; Green, 2006). As for schizophrenia, mild cognitive impairments have also been detected in first-degree relatives of probands with bipolar disorder (David C Glahn et al., 2010). In general, the cognitive impairments seen across psychotic disorders seem to follow a gradient of severity from most impaired in schizophrenia, intermediate impairments in bipolar disorder and the least severe impairments in MDD with psychotic features (Sheffield et al., 2018). In bipolar disorder, impairments have also been documented in first treatment mania participants (Demmo et al., 2016; Demmo et al., 2018). Furthermore, some studies have found history of psychosis to be associated with greater cognitive impairment (Martinez-Aran et al., 2008;

Simonsen et al., 2011) although this has not been shown consistently across all samples (Demmo et al., 2016; Sanchez-Morla et al., 2009). Authors of a meta-analysis on the topic concluded that the effects of psychosis are too modest to make a clear categorical distinction (Bora et al., 2010).



It seems clear that the question of cognitive impairment as a feature of psychotic disorders is one of magnitude. However, there is some discussion on the matter of whether the cognitive impairments in schizophrenia are qualitatively different from those observed in other mental disorders in general, and in bipolar disorder in particular (Kahn & Keefe, 2013). Central to the discussion are differences in cognitive functioning in the premorbid phase (Kahn & Keefe, 2013). While both disorders are characterized by deficits after illness onset, only schizophrenia is characterized by an unequivocal impairment in the premorbid phase (Trotta et al., 2015).

Furthermore, central to the question of whether schizophrenia is a neurodegenerative disorder in the Kraepelinian sense, is the question of how cognitive abilities evolve through the course of illness (Keefe & Kahn, 2017). At present, much is known about the early course of cognition, which is mostly found to be stable or even improving (Bora & Murray, 2014;

Bozikas & Andreou, 2011; Hedman et al., 2013; Leeson et al., 2011). The available data from long-term follow-up studies (∼10 years) present a mixed picture. Most of these studies have reported a stable cognitive course (Barder et al., 2013; Bergh et al., 2016; Rodríguez-Sánchez et al., 2020). Others point to cognitive decline, at least in some domains (Zanelli et al., 2019).

One recent study found cognitive stability in the overall sample but reported on a subgroup experiencing decline without being able to detect predictor for the declining course (Rodríguez-Sánchez et al., 2020). A recent study with a 20-year follow-up measuring cognition on 11 separate tests, showed significant declines on all cognitive tests except for verbal fluency and verbal knowledge (Fett et al., 2020). The authors concluded that the results were consistent with a hypothesis of accelerated ageing in psychotic disorders compared to healthy controls which becomes apparent with longer term follow-up (Fett et al., 2020). This study broadly included all participants with first admission for a psychosis, but most participants had a schizophrenia spectrum or non-affective psychotic disorder.

Currently the evidence indicates a stable early cognitive course in schizophrenia and related psychotic disorders up to about 10 years, after which there may be signs of accelerated ageing as seen by cognitive decline compared to healthy controls (Fett et al., 2020; Harvey &


Rosenthal, 2018). Also, there may be subgroups who experience cognitive decline within 10 years of the illness onset who are not yet identified by known predictors (Rodríguez-Sánchez et al., 2020).


Though cognitive impairments are found in most patients with schizophrenia (Keefe & Harvey, 2012), there is a great deal of variability (Carruthers et al., 2019). In recent years, the field has moved from a focus on establishing facts about the different aspects of cognitive impairments for the schizophrenia group as a whole (e.g. global vs. domain specific, premorbid level of intellectual functioning), to an increased focus on identifying cognitive subgroups. These studies of cognitive heterogeneity vary in approach and methodology but fall into two broad categories: 1) studies that define subgroups based on theory-driven a priori assumptions, and 2) studies that use data driven methods to detect clusters based on statistical criteria.

The former category of studies has typically focused on groups forming the highest to lowest performers within predefined tests or domains. This has been done for level of intellectual functioning, both current (Vaskinn et al., 2014) and premorbid (Ayesa-Arriola et al., 2018), as well as for a range of other specified cognitive tests and test profiles (Ammari et al., 2010;

Carruthers et al., 2019; González-Blanch et al., 2010). Studies of this kind have most frequently defined two to three groups.

The latter category of data-driven studies has been conducted on a wide variety of study samples (Carruthers et al., 2019). Interestingly, studies on both first-episode schizophrenia (Tan et al., 2021) and mixed samples including both schizophrenia and bipolar I disorder (Vaskinn et al., 2020) have reported three clusters. This is also the overall conclusion from a comprehensive review synthesizing both data-driven and studies with predefined groups (Carruthers et al., 2019). That is, for schizophrenia the cognitive profile is either: relatively intact, moderately impaired, or severely impaired (Carruthers et al., 2019; Tan et al., 2021),.

Furthermore, it seems that premorbid scholastic performance may be related to impairment


after illness onset and prognosis (Tan et al., 2021). This latter finding highlights the need to be aware of cognitive subgroups even in high-risk populations and early after the illness onset.


The current conceptualization of negative symptoms involves behaviors that fall into five symptom categories: blunted affect, alogia (impoverished speech), anhedonia (lack of capacity to experience positive emotions), asociality (social withdrawal) and avolition (apathy)(Galderisi et al., 2018; Marder & Galderisi, 2017). The presence of avolition in dementia praecox, and its absence in manic-depressive psychosis, led Kraepelin to emphasize it as a distinguishing feature of schizophrenia (Kraepelin, 1919). Negative symptoms are also today increasingly recognized as core to schizophrenia (Andreasen, 1982; Andreasen et al., 1995; Galderisi et al., 2018; Tandon et al., 2009). Although a diagnosis of schizophrenia can be made in the absence of negative symptoms, they were included as an A-criterion in DSM-IV.

Negative symptoms are frequently among the first symptoms to appear in the course of schizophrenia (an der Heiden & Häfner, 2000). They are also reported to occur in up to 90 % of individuals having a first psychotic episode, with persistent significant negative symptoms after treatment in 35-70% (An der Heiden et al., 2016). Although the pathophysiology and causal mechanisms are not fully understood, it is likely that genetic contributions, prenatal events, and problems with premorbid adjustment all contribute to the development and evolution of negative symptoms early in the course of the psychotic illness (Lyne et al., 2018).

Negative symptoms are consistently found to be strong predictors of functional outcome (Fervaha, Foussias, et al., 2014; Kaneko, 2018; Milev et al., 2005), more so than positive symptoms (Rabinowitz et al., 2012). However, despite recognition of the importance of negative symptoms, available treatment options are few and often with modest and uncertain effects (Fusar-Poli et al., 2015). Thus, improved understanding of these core symptoms is arguably among the most important areas of research on severe mental illness.



An important topic for theory and research on negative symptoms has been on the differentiation of primary from secondary symptoms (Carpenter Jr et al., 1988). Primary negative symptoms are thought to be intrinsic to the underlying pathophysiology of schizophrenia, whereas secondary negative symptoms are related to adverse treatment effects (e.g. extrapyramidal side effects from antipsychotics), medical or psychiatric comorbidities (e.g. neurological disorder, depression, positive symptoms), or other environmental factors (e.g. extreme deprivation of stimuli) (Correll & Schooler, 2020). As straightforward as this distinction may seem, it is a difficult one to make. Because there are no valid biomarkers available or pathognomonic characteristic distinguishing primary from secondary negative symptoms, concepts with specified criteria have been developed to identify patients who show primary and enduring negative symptoms (Mucci et al., 2017).

An early concept was developed where patients were divided into type I and type II schizophrenia, with the latter group defined by prominent negative symptoms, among other features. This was followed by the more direct approach developed by Andreasen and Olsen (1982) where a subtype called negative schizophrenia was defined by a clinical picture dominated by prominent negative symptoms, with a specified upper level of positive symptoms (Andreasen & Olsen, 1982). With the later concept of deficit schizophrenia, a subtype specifying both level of negative symptoms, their endurance and primacy, e.g. ruling out depression, extrapyramidal side effects or environmental deprivation as causal factors, was put forward (Carpenter Jr et al., 1988). In part for pragmatic reasons, this concept was further developed into the more recent persistent negative symptoms, where criteria for symptom level and duration were more flexible (Buchanan, 2007).

One of the most important reasons for developing the concept of persistent negative symptoms was to enable researchers to target primary negative symptoms in clinical trials (Buchanan, 2007). Persistent negative symptoms are therefore sometimes referred to as


‘unconfounded’ (Bucci et al., 2020), which emphasizes their status as primary and not explained by other clinical or environmental factors. Hence, improvement in patients with persistent negative symptoms in a clinical trial strengthens the interpretation that the treatment has had a targeted effect on primary negative symptoms. Although this reasoning is sound, most conceptualizations rest on the assumption that negative symptoms form distinct and categorical symptom entities restricted to schizophrenia. This may not be the case. In line with the previously described psychosis continuum model (Guloksuz & van Os, 2018; van Os et al., 2009), negative symptoms could also be viewed as dimensional (Kaiser et al., 2011), and there is ample evidence to suggest that they are.

A study using a mixed diagnostic sample found that a negative symptom factor also emerged for participants with affective disorders (Kitamura & Suga, 1991). Moreover, when investigating schizotypy (i.e., attenuated psychotic symptoms) in the general population, a three-factor structure of schizotypal symptoms like the positive, negative and disorganized type emerged, and was replicated in an independent sample (Gruzelier, 1996). This suggests that negative symptoms, at least in some attenuated form, seem to form a continuum across diagnostic borders and extend into the general population. Furthermore, also the more prominent and enduring negative symptoms defined by deficit schizophrenia seem to cut across diagnostic borders, and are found to be relatively prevalent across non-affective psychoses (Peralta & Cuesta, 2004). Overall, findings suggest negative symptoms are most prominent and prevalent in non-affective psychoses, but not restricted to specific diagnoses (Kaiser et al., 2011; Peralta & Cuesta, 2004). Although it is important to know that some negative symptoms are primary and intrinsic to the disorder, it may in many cases be impossible to clearly separate them from secondary symptoms (Correll & Schooler, 2020). It has also been found that enduring negative symptoms are important and indistinguishable on clinical characteristics whether primary or secondary (Peralta & Cuesta, 2004). However, no matter of the perspective, enduring negative symptoms warrant increased attention in the clinical treatment setting and the longitudinal development of these symptoms are an important focus for future research (Bègue et al., 2020).




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