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The number of people diagnosed with autism spectrum disorder (ASD) in childhood or adulthood has strongly increased over the past decades. While research demonstrates that people with ASD are at risk of adverse health outcomes including preterm mortality, scientific knowledge on the pathways leading to adverse health outcomes and an increased health care consumption, along with the effectiveness of different pharmacotherapies, is limited.The overall aim is to characterize pathways to increased health care consumption and adverse health outcomes in individuals with ASD diagnosed in childhood, as compared to those diagnosed in adulthood, and to examine the influence of various individual factors as well as treatment effectiveness in lowering the risk of adverse health outcomes and elevated health care needs.Data and method: The studies build on linked register data in Sweden and Finland. The study populations in Sweden include 84,012 individuals diagnosed with ASD during 2003-2018 as well as two comparison groups: 1) individuals from the general population

and 2) full-siblings. Cutting edge methodology such as network- and machine learning models as well as novel methods in pharmacoepidemiology will be applied. The five-year project involves interdisciplinary collaboration including clinicians and epidemiologists.This project provides crucial scientific knowledge necessary to design optimal health care and pharmacological treatment for patients with ASD.

Cannabis use is increasing worldwide and also certain European countries plan to legalize or decriminalize cannabis. This will further increase use rates and also result into higher number of people with cannabis use disorder. Cannabis use in persons with severe mental disorders, namely schizophrenia-spectrum disorders, bipolar disorders and major depressive disorder, has been reported to adversely impact on illness course and associate with non-adherence to treatments. However, impacts of cannabis use disorder on long-term treatment outcomes in severe mental disorders are not known.  The overall aim of this project is to investigate long-term treatment pathways and outcomes of patients with severe mental disorder and comorbid cannabis use disorder, to help in designing optimal health care for these patients. We aim to investigate healthcare service and medication use and work disability during first five years of illness, compared to patients with severe mental disorder without cannabis use disorder. We will also investigate risk of mortality and effectiveness of medications associated with decreased risk of illness relapse, and mortality. Finally, we will develop a prediction model for adverse clinical outcomes to help clinical practice to inform which patients are at the highest risk and in need of enhanced monitoring and effective interventions. Further, we will investigate whether treatment can be tailored based on the predicted risk level.

Research problem and specific questionsKnowledge is limited on the role of multimorbidity, work-related and social factors as well as treatment on the path to labor market marginalization after sick leave due to common mental disorders (CMDs), i.e., depression, anxiety, and stress-related disorders. This project aims to gain knowledge on how (1) social- and work-related factors, multi-morbidity, and (2) sick-leave patterns and treatment are associated with subsequent labor market marginalization after sick leave due to CMDs.Data and methodWe will use individually linked Swedish register data. Individuals, between the age of 21-50, residing in Sweden in 2006-09 (n=3,661,300), and among them those who started sick leave due to CMDs (49,903) will be included and followed regarding labor market outcomes. We will use sequence analysis and multi-state models to examine labor market marginalization patterns and transitions between labor market states in relation to prognostic factors after sick leave due to CMDs. Furthermore, all individuals living in the Stockholm region in 2014-19 (n=1,215,437) will form an additional study base. Network- and regression analyses will be used to examine the association between multi-morbidity patterns, treatment options and labor market marginalization.Plan for project realizationThis interdisciplinary project involves international collaborations analyzing data that has already been acquired. The three year project budget will cover 50% of the salaries for a postdoctoral researcher and the main applicant, 5% of salaries for co-applicants and costs including drug use modeling, data management, administrative costs such as knowledge exchange and dissemination, publication and premises.RelevanceThere is a large number of individuals with work disability and sick leave due to CMDs in Europe and in Sweden. Keeping individuals in the labor market and avoiding their labor market marginalization after sick leave due to CMDs is important both from a societal and an individual’s perspective and for achieving sustainable working life goals. Knowledge on risk factors and treatment can provide the basis for tailor-made, person-centered interventions.