Full speed ahead on indicated prevention of psychosis

Harmonizing the structured interview for psychosis-risk syndromes (SIPS) and the comprehensive assessment of at-risk mental states (CAARMS): An initial approach

The two most used semi-structured psychometric instruments that define criteria for being at clinical high risk (CHR) for psychosis are the Comprehensive Assessment of At-Risk Mental States (CAARMS) and the Structured Interview for Psychosis-Risk Syndromes (SIPS). Although very similar there are important differences between these two measures. Developing harmonized psychometric criteria for defining CHR and associated outcomes would be beneficial for future research. This article describes the first step in this process by reporting on a NIMH workshop held in Washington DC, in February 2019 that was attended by experts in the field. The aim of this workshop was to examine the similarities and differences between the two measures and consider how the harmonization process could proceed.

Development of the PSYCHS: Positive SYmptoms and Diagnostic Criteria for the CAARMS Harmonized with the SIPS

AIM

To harmonize two ascertainment and severity rating instruments commonly used for the clinical high risk syndrome for psychosis (CHR-P): the Structured Interview for Psychosis-risk Syndromes (SIPS) and the Comprehensive Assessment of At-Risk Mental States (CAARMS).

METHODS

The initial workshop is described in the companion report from Addington et al. After the workshop, lead experts for each instrument continued harmonizing attenuated positive symptoms and criteria for psychosis and CHR-P through an intensive series of joint videoconferences.

RESULTS

Full harmonization was achieved for attenuated positive symptom ratings and psychosis criteria, and modest harmonization for CHR-P criteria. The semi-structured interview, named Positive SYmptoms and Diagnostic Criteria for the CAARMS Harmonized with the SIPS (PSYCHS), generates CHR-P criteria and severity scores for both CAARMS and SIPS.

CONCLUSIONS

Using the PSYCHS for CHR-P ascertainment, conversion determination, and attenuated positive symptom severity rating will help in comparing findings across studies and in meta-analyses.

Development of the PSYCHS: Positive SYmptoms and Diagnostic Criteria for the CAARMS Harmonized with the SIPS

Aim

To harmonize two ascertainment and severity rating instruments commonly used for the clinical high risk syndrome for psychosis (CHR-P): the Structured Interview for Psychosis-risk Syndromes (SIPS) and the Comprehensive Assessment of At-Risk Mental States (CAARMS).

Methods

The initial workshop is described in the companion report from Addington et al. After the workshop, lead experts for each instrument continued harmonizing attenuated positive symptoms and criteria for psychosis and CHR-P through an intensive series of joint videoconferences.

Results

Full harmonization was achieved for attenuated positive symptom ratings and psychosis criteria, and partial harmonization for CHR-P criteria. The semi-structured interview, named P ositive SY mptoms and Diagnostic Criteria for the C AARMS H armonized with the S IPS (PSYCHS), generates CHR-P criteria and severity scores for both CAARMS and SIPS.

Conclusion

Using the PSYCHS for CHR-P ascertainment, conversion determination, and attenuated positive symptom severity rating will help in comparing findings across studies and in meta-analyses.

Neurodevelopmental trajectories, polygenic risk, and lipometabolism in vulnerability and resilience to schizophrenia

BACKGROUND

Schizophrenia (SZ) arises from a complex interplay involving genetic and molecular factors. Early intervention of SZ hinges upon understanding its vulnerability and resiliency factors in study of SZ and genetic high risk for SZ (GHR).

METHODS

Herein, using integrative and multimodal strategies, we first performed a longitudinal study of neural function as measured by amplitude of low frequency function (ALFF) in 21 SZ, 26 GHR, and 39 healthy controls to characterize neurodevelopmental trajectories of SZ and GHR. Then, we examined the relationship between polygenic risk score for SZ (SZ-PRS), lipid metabolism, and ALFF in 78 SZ, and 75 GHR in cross-sectional design to understand its genetic and molecular substrates.

RESULTS

Across time, SZ and GHR diverge in ALFF alterations of the left medial orbital frontal cortex (MOF). At baseline, both SZ and GHR had increased left MOF ALFF compared to HC (P < 0.05). At follow-up, increased ALFF persisted in SZ, yet normalized in GHR. Further, membrane genes and lipid species for cell membranes predicted left MOF ALFF in SZ; whereas in GHR, fatty acids best predicted and were negatively correlated (r = -0.302, P < 0.05) with left MOF.

CONCLUSIONS

Our findings implicate divergence in ALFF alteration in left MOF between SZ and GHR with disease progression, reflecting vulnerability and resiliency to SZ. They also indicate different influences of membrane genes and lipid metabolism on left MOF ALFF in SZ and GHR, which have important implications for understanding mechanisms underlying vulnerability and resiliency in SZ and contribute to translational efforts for early intervention.

Racism and psychosis: an umbrella review and qualitative analysis of the mental health consequences of racism

Black people and People of Color are disproportionately affected by racism and show increased rates of psychosis. To examine whether racialized migrant groups are particularly exposed to racism and therefore have higher risks for psychosis, this paper (1) systematically assesses rates of psychosis among racialized migrant groups concerning the country of origin, and (2) analyzes interviews regarding the association of racism experiences with psychosis-related symptoms in racialized Black people and People of Color populations in Germany. We present an umbrella review of meta-analyses that report the incidence of positive symptoms (e.g., hallucinations and delusions) and negative symptoms (e.g., apathy and incoherent speech) of diagnosed schizophrenia, other non-affective psychotic disorders (e.g., schizoaffective disorder) or first-episode psychosis among migrants by country of origin. We also report 20 interviews with first- and second-generation migrants racialized as Black and of Color in Germany to capture and classify their experiences of racism as well as racism-associated mental health challenges. In the umbrella review, psychosis risk was greatest when migration occurred from developing countries. Effect size estimates were even larger among Caribbean and African migrants. In the qualitative study, the application of the constant comparative method yielded four subordinate themes that form a subclinical psychosis symptomatology profile related to experiences of racism: (1) a sense of differentness, (2) negative self-awareness, (3) paranoid ideation regarding general persecution, and (4) self-questioning and self-esteem instability. We here provide converging evidence from a quantitative and qualitative analysis that the risk of poor mental health and psychotic experiences is related to racism associated with minority status and migration.

Annual Research Review: Translational machine learning for child and adolescent psychiatry

Children and adolescents could benefit from the use of predictive tools that facilitate personalized diagnoses, prognoses, and treatment selection. Such tools have not yet been deployed using traditional statistical methods, potentially due to the limitations of the paradigm and the need to leverage large amounts of digital data. This review will suggest that a machine learning approach could address these challenges and is designed to introduce new readers to the background, methods, and results in the field. A rationale is first introduced followed by an outline of fundamental elements of machine learning approaches. To provide an overview of the use of the techniques in child and adolescent literature, a scoping review of broad trends is then presented. Selected studies are also highlighted in order to draw attention to research areas that are closest to translation and studies that exhibit a high degree of experimental innovation. Limitations to the research, and machine learning approaches generally, are outlined in the penultimate section highlighting issues related to sample sizes, validation, clinical utility, and ethical challenges. Finally, future directions are discussed that could enhance the possibility of clinical implementation and address specific questions relevant to the child and adolescent psychiatry. The review gives a broad overview of the machine learning paradigm in order to highlight the benefits of a shift in perspective towards practically oriented statistical solutions that aim to improve clinical care of children and adolescents.