CAG Precision Psychiatry (PSYCH)

Psykiatriske sygdomme medfører stor lidelse og tab af funktionsevne for millioner af mennesker, deres nærmeste og samfundet som helhed. På trods af årtiers intensive investeringer og vigtige forskningsresultater inden for psykiatrisk epidemiologi, genetik og celle/molekylær neurovidenskab, mangler vi stadig en mekanistisk forståelse af årsagerne til de fleste psykiatriske lidelser.

Vi har ingen klinisk anvendelige biomarkører og har udfordringer med at tilbyde effektive interventioner. Fremskridt kræver en integreret videnskabelig dagsorden, der samler perspektiver og ekspertise fra datavidenskab, grundvidenskab og klinisk psykiatri. Greater Copenhagen har internationalt unikke ressourcer, eksperter, ambitioner og initiativer, men mangler i øjeblikket det nødvendige koordinerede tværfaglige samarbejde til at forbedre klinisk psykiatri.

Med denne CAG vil vi forene eliteforskere og klinikere i et interdisciplinære samarbejde for at accelerere translationen af videnskabelige opdagelser til klinikken i form af mere effektiv og præcis diagnostik med individualiseret behandling der kan reducere sygeligheden og dødeligheden hos patienter med psykiatriske lidelser. Vi vil organisere denne CAG omkring fem hovedmål:
1) Opbygning af et tværfagligt samarbejde omkring de internationalt unikke
integrerede store sundhedsdatasæt, kliniske kohorter, omics og store genetiske og biobank data, vi har tilgængelige.
2) Identifikation af klinisk anvendelige biomarkører til stratificering af patientundergrupper, forudsige sygdom, forløb og behandlingsrespons samt monitorere risikoen.
3) Identificere mekanistisk forståelse ved detaljerede molekylære og cellulære
undersøgelser, herunder omics teknologier, inklusiv af genetisk risiko.
4) Forfølge både in silico-emuleringsforsøg og kliniske forsøg for at øge præcisionen i vores behandling og forebyggelse af psykiatriske patienter.
5) Facilitere tværfaglig, translationel forskningstræning, med tværgruppeprojekter, årlige møder og mentorprogrammer.

Challenge:
Mental disorders are highly prevalent across the lifespan and are major causes of disability and associated with reduced life expectancy (1-8). A substantial number of patients with mental disorders suffer from unmet needs stemming from imprecise diagnoses and treatment strategies (9-10).
Currently, diagnoses in mental health are mainly based on psychometric measures while paraclinical data supporting diagnosis and treatment are lacking. Thus, the one specific etiology – out of a broad range of many different mechanisms leading to, e.g. schizophrenia – is in most cases not identified. Therefore, guideline-driven clinical treatments apply the same standard regimen irrespective of etiology, which may explain the insufficient current treatments. Currently, many of the treatments provided in mental health services barely exceeds the effect of placebo or active control groups, and have a very broad and unprecise effects, leaving a tremendous unmet need for patients with mental disorders (11-12). Targeting these needs might not only reduce morbidity but also mortality among patients with severe mental disorders.

The likelihood of developing a severe mental disorder with adverse outcomes varies significantly among patients, ranging from rapid and full recovery to chronicity and increased mortality. Effectively allocating resources to those at high risk poses a considerable challenge, requiring the use of risk algorithms grounded in evidence-based data. While significant progress has been made in psychiatric genetics over recent decades, revealing the polygenic nature of mental disorders and significant overlap among current diagnostic categories, this understanding has not yet translated to the development of new diagnostic or therapeutic approaches in psychiatry (9, 13-14).

Opportunities:
To advance mechanistic understandings, biomarker discovery, and treatment outcomes in psychiatry, we will:
• Align an internationally unique collection of data resources from national registers, electronic health records, biobanks and large-scale genetic cohorts, epidemiological surveys, and targeted clinical cohorts
• Translate genetic and epidemiological findings into mechanistic understandings using advanced cellular and molecular bioassays and models
• Identify digital, imaging, or high resolution-omics based biomarkers with prognostic and diagnostic validity
• Identify indicators of heterogeneous treatment response to stratify patients into more homogeneous subgroups
• Test insights in next generation clinical trials that emphasize predictive algorithms, stratification, and individualized interventions to translate the findings into impact for the patients

We believe an organized CAG can systematize and accelerate the path from discovery to implementation, activating an untapped potential in the Greater Copenhagen Area and providing clinical psychiatry with a pipeline to the next generation of treatment and prevention.