Report

Teaser, summary, work performed and final results

Periodic Reporting for period 2 - INSOMNIA (Insomnia’s Negative Sequelae On Mood: from Neuroscience to Intervention in the Aged)

Teaser

Major depression is among the most burdening health hazards. Its prevalence is 1-3%, an additional 8-16% have clinically significant symptoms, and prognosis is poor. Unfortunately, less than 20% of the cases are detected and treatment effectiveness is moderate. The Global...

Summary

Major depression is among the most burdening health hazards. Its prevalence is 1-3%, an additional 8-16% have clinically significant symptoms, and prognosis is poor. Unfortunately, less than 20% of the cases are detected and treatment effectiveness is moderate. The Global Consortium for Depression Prevention stresses that our best chance to combat the global burden of depression is provide preventive intervention to identified people at risk. This project targets the strongest modifiable risk factor: insomnia.
With prevalence estimates up to 40%, insomnia is among the most frequent disorders in the elderly population. Meta-analysis shows that no less than 13% of people with insomnia develop depression. This extreme risk and the very high prevalence of insomnia in the ageing population, shows the urgency and promise of: (1) early identification of these 13%, (2) finding mechanisms by quantification of how they differ from insomniacs that do not develop depression with respect to brain structure and function, psychological traits, behavioural habits and environmental exposures; and (3) enrolling them in intervention protocols aimed at sleep improvement and prevention of depression.
The project extends recent findings emerging from the applicant’s pioneering, unconventional and innovative approach to insomnia; the proposal that distinct subtypes exist and can be discriminated data- driven by means of multivariate trait analysis and brain imaging. Ignorance of this heterogeneity has obstructed progress in mechanistic understanding and rational treatment. In an ground-breaking interdisciplinary way the project (1) identifies the insomnia subtype that develops depression; (2) profiles mechanisms involved; and (3) optimizes effectiveness of internet-supported home-applicable interventions to improve sleep and prevent depression. This approach will identify risks and mechanisms, and facilitate immediate implementation of risk-based prevention strategies and policies.

Work performed

\"WP1 (Psychometrics, PSY).
The overarching aim of WP1 is to elucidate psychometric risk factors for the transition from insomnia to major depressive disorder (MDD). Rather than investigating predictors one by one, we aimed to identify the multivariate profile of an individual’s psychometric traits and lifetime exposure to stressful events that promotes vs. wards off the transition from insomnia to depression.
First however, we solved a shortcoming in the available literature to date. Previous prognostic studies did not address the confounding possibility that current insomnia could be a residual symptom of an earlier depressive episode. The studies also did not consider the confounding possibility that insomnia could predict MDD only indirectly instead of directly, i.e. through the association of insomnia with other depression symptoms. Using a longitudinal design in N=768 people that were free from lifetime depression at baseline, we confirmed that insomnia increased the risk of first-onset depression. Using innovative network methods, we moreover confirmed that, among all individual symptoms of depression measured at baseline, only difficulty initiating sleep and psychomotor agitation significantly predicted a full-blown first-onset MDD (Blanken et al., submitted).
After confirming that indeed insomnia is a primary risk factor for first-onset depression in those that have never experienced depression before, we commenced to elucidate the predictive multivariate profile of an individual’s psychometric traits and lifetime exposure We first identified how insomnia complaints relate to personality structure (Dekker et al., 2017) and sensory and autonomic processing (Van Someren et al., 2016). We subsequently further extended the multivariate approach by evaluating relevant variables through systematic review (Benjamins et al., 2017). The resulting total of 34 stable characteristics were then assessed in 4,322 people. Data-driven latent class analysis identified five subtypes among the 2,224 with insomnia (Blanken et al., revision under review-a). Difference profiles concerned life history, affect, personality and sensitivity traits but, interestingly, not primarily differential types or severities of specific sleep complaints (D1.1). Follow-up with a dedicated minimal set of questions integrated in the Insomnia Type Questionnaire, (ITS, D1.2) showed that three subtypes were highly consistent over time, and that the ITS could reliably differentiate the risk of depression. Insomnia disorder (ID) \"\"type 1\"\" has a lifetime probability of p=.54 to experience MDD. This risk is five times higher than the risk of MDD in controls and two \'unaffected\' ID subtypes. Two other subtypes show less extreme, but still quite relevant, increased probability (0.28-0.34) (Blanken et al., revision under review-a).
Using the D1.1. and D1.2 results described above, we have built a uniform multilingual internet platform and database structure for the psychometric assessment parts of participant recruitment, characterization and follow-up in the studies on Behaviour, Environment & Physiology. We have caught up with an initial delay in the development of this tool (D1.3) that is currently in use to recruit and assess psychometric datasets of the volunteers that participate in the investigations of WP2-4 (D1.4). It includes the ITS (D1.2) by means of which we can differentiate people with insomnia that have a low estimated risk of developing MDD versus those that have a high estimated risk. The latter will be included in the Randomized Clinical Trial (RCT) of WP4.

WP2: Ambulatory Assessment of Behaviour, Environment, Physiology, Mood, Stress & Cognition (AMB)
The overarching aim of WP2 is to is to elucidate behavioral, environmental, physiological and subjective risk factors for the transition from insomnia to major depressive disorder (MDD). We have refined our standard operating procedures for a full week of unobtrusive assessment and analysis of env\"

Final results

In summary, the project will provide: a better understanding of the combined effects of factors causing depression in old age; provide tools for stepped risk identification that can be applied immediately; evaluate preventive effectiveness of currently available interventions that can be applied immediately; and generate ground- breaking integrated transdisciplinary knowledge that can be utilized for development of rational, evidence based prevention, diagnosis, therapeutics and other strategies. Intrinsic to the approach, the project will also uncover pathways of healthy ageing, underpinning future strategies for the promotion of healthy ageing, targeted disease prevention and clinical interventions. Depression affects ±120 million people worldwide. According to the World Health Organization (WHO), depression is the leading cause of disability and ranks as the third leading cause of the global burden of disease; it will rank first in 2030. The societal significance of the need to alleviate the burden of depression is beyond questioning. As recently recognized by the Global Consortium for Depression Prevention, identifying subgroups that are at high risk would be among the most effective means to combat the global burden of depression, because it can accelerate research into effective ways of prevention [5]. The scientific impact will likewise be beyond questioning, because of the ground- breaking integrated transdisciplinary approach spanning excellence from trait to environment. The economical impact is manifold. Firstly, the project will provide immediately applicable ways for risk identification and targeted scalable [30] treatment to attain staying healthy for longer, saving health costs and extending productive life years. Secondly, results can be valorised by SME’s that can immediately provide tools for risk assessment & treatment. Thirdly, scientific insights will provide new targets for companies to develop novel interventions. Finally, both insomnia and depression are known to increase the risks of the most important other health hazards of old age including diabetes, cardiovascular disorders and dementia. Mitigation of insomnia and depression will have the spinoff of reducing the risk of these disorders, delaying their onset, reducing their severity, and as a result increase healthy and productive life years.