about

We are rolling up our sleeves to improve the clinical management of adults with ADHD and cooccurring cardiometabolic conditions. To achieve this goal, TIMESPAN is composed of 10 Work Packages (WPs), each one with one WP leader, who closely supervises the work carried out and works directly with the project office.

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  WP1

  Epidemiology: The consequences of ADHD on the management, disease progression and prognosis of cardiometabolic diseases in adults

  WP1 will use national registers from many countries across the world, as well as Europe’s largest cohorts. The cohort data are complementary to the register data by providing the possibility to study the effects of undetected or untreated ADHD in the general population and high risk groups, …

  Lead: Catharina Hartman UMCG

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  … for example by biomarkers in the cardiometabolic profile; high genetic risk based on genome-wide genotyping, or by subthreshold ADHD status identified from questionnaire data on ADHD symptoms.

  The WP1 will make direct comparisons between countries yielding important insights into differences related to diverging health systems across Europe. Through meta-analysis of these data, we will provide information about shared and common effects. We will also evaluate causal and mediation pathways linking ADHD to cardiometabolic using Mendelian Randomization.

  The overall objective of WP1 is to determine and understand the total impact of ADHD on management, disease progression and prognosis of cardiometabolic diseases in adults.

  • Determine if patients with cardiometabolic disease (T2DM and CVD) and co-occurring ADHD, receive less appropriate, and/or show poorer adherence to, pharmacological and nonpharmacological guideline-indicated treatments for cardiometabolic diseases.
  • Determine if patients with, or at high risk of, cardiometabolic disease (obesity, T2DM and CVD) and co-occurring ADHD,
    • present with a more severe cardiometabolic risk factor profile and
    • have a faster deterioration of the cardiovascular risk profile over time.
  • Estimate the extent to which patients with cardiometabolic disease (obesity, T2DM and CVD) and co-occurring ADHD, compared to patients without ADHD, show poor psychosocial and wellbeing outcomes
  • Estimate the extent to which patients with cardiometabolic disease (obesity, T2DM and CVD) and co-occurring (high liability for) ADHD, show elevated rates of morbidity and mortality.
  • Identify the causal and mediation pathways between ADHD, cardiometabolic disease and death among the outcomes studied as described above
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  WP2

  Study the effectiveness and safety of ADHD medication and combined pharmacotherapy in individuals with ADHD and cardiometabolic disease

  WP2 will investigate how ADHD medication influences cardiometabolic risk profiles, and the management and prognosis of obesity, Type-2 Diabetes (T2DM) and cardiovascular disease (CVD). It will analyse data from high quality disease registers and eight large prescription databases linked with health records across the world.

  Lead: Zheng Chang KI

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  WP2 will also explore the association between concurrent use of ADHD medication and other medications and risk of adverse events from drug-drug interactions, using the novel iDEAS (High Dimensional Empirical Bayes Screening) approach.

  The overarching objective is to study effectiveness and safety of ADHD medication and combined pharmacotherapy in individuals with ADHD and CVD.

  • Determine the extent to which ADHD medication influences the management of chronic obesity, T2DM and CVD and cardiometabolic risk profile.
  • Investigate how ADHD medication influences the prognosis of chronic obesity, T2DM and CVD.
  • Identify socio-demographic and clinical modifiers on the effects of ADHD medication and classify sub-groups of patients who will benefit less or more from the treatment.
  • Explore the association between concurrent use of ADHD medication and other medications in real-world clinical practice and risk of adverse events from drug-drug interactions.
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  WP3

  Characterize the level of treatment discontinuity across the adult lifespan in individuals with ADHD and cardiometabolic disease

  WP3 will use data from eight large-scale ADHD prescription databases to study ADHD medication treatment discontinuity. A novel approach using machine learning and natural language processing approaches, will be used in several data sources to extract dosage information, needed to refine the assessment of treatment discontinuity.

  Lead: Kari Klungsøyr UiB

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  WP3 will estimate long-term ADHD medication trajectories across different health care systems and countries to identify rates of continuity, discontinuity, shorter treatment gaps or nonadherence, as well as detailed descriptions of dosage during titration periods.

  Based on multivariate regression models, we will statistically test if treatment discontinuity rates are different depending on age, sex, socioeconomic status, dosage of ADHD medication, and psychiatric comorbidity. We will also test if treatment discontinuity rates are higher among patients followed in primary care settings than in specialist care settings.

  Finally, WP3 will perform stratified analyses to explore if treatment discontinuity rates and dosage levels are different in patients with co-occurring cardiometabolic disease.

  The overarching objective of WP3 is to better characterize the level of ADHD treatment discontinuity across the adult lifespan in individuals with ADHD and obesity, cardiovascular disease (CVD) and Type-2 Diabetes (T2DM).

  • Identify long-term ADHD medication trajectories across different health systems and countries.
  • Identify clinical and socio-demographic modifiers of ADHD treatment discontinuity and non-adherence across different health care systems and countries.
  • Characterize the level of ADHD treatment discontinuity and non-adherence in patients with co-occurring chronic obesity, CVD and T2DM.
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  WP4

  Identify genetic risk factors for medication treatment discontinuity in ADHD patients

  WP4 will study the genetic contribution and biological mechanisms involved in ADHD treatment discontinuation. This will be done using a range of cutting-edge genetic analyses applied to largescale genetic data from cohorts with large sample sizes and available data on longitudinal prescription data collected via national drug registers and clinical hospital records.

  Lead: Ditte Demontis AU

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  Through genome-wide association studies (GWAS) and rare variant analyses we will, for the first time, identify genetic variant associated with ADHD treatment discontinuation. GWAS results will be integrated with functional genomic methods to infer the biological mechanisms underlying treatment discontinuation. We will further investigate the polygenetic overlap of ADHD medication discontinuation with cardiometabolic diseases and comorbid psychiatric conditions.

  The overarching objective of WP4 is to advance the understanding of the biological mechanisms underpinning ADHD treatment discontinuation. Further objectives are:

  • Identification of the best way to define the biological component of ADHD medication discontinuation based on Single Nucleotide Polymorphism heritability estimates.
  • To generate atlases of the shared genetic architecture of ADHD medication discontinuation and comorbid cardiometabolic disease, like obesity,  Type-2 Diabetes (T2DM) and cardiovascular disease (CVD), by conducting genetic correlation analyses
  • To run polygenic risk scores (PRS) analyses to predict ADHD medication discontinuation and evaluate the extent to which the PRS profiles of medication discontinuation differ in patients with co-occurring obesity, T2DM and CVD.
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  WP5

  ADHD Remote Technology (ART) study of cardiometabolic risk factors and medication adherence // Short title: ART-CARMA

  WP5 will use Remote Measurement Technology (RMT) in adults with ADHD to carry out unobtrusive, real-time data collection over an ongoing period of 12 months.

  Lead: Jonna Kuntsi KCL

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  By recruiting 300 adults from adult ADHD clinic waiting lists and monitoring them remotely, we will obtain objectively measured data relevant to cardiometabolic risk profiles from the patient’s daily life, both when and when not receiving pharmacotherapy. We obtain real-time data on multiple parameters, including side effects, that will inform the personalisation of treatment. Machine learning will be implemented with the whole data obtained in order to build prediction models.

  WP5 benefits from the ADHD Remote Technology (ART) assessment and monitoring battery for adults with ADHD (developed by Kuntsi, Dobson, Hollis, Asherson), and the RADAR-base mobile-health platform to which it is linked (developed by Dobson et al.)

  ART consists of both active (smartphone active app) and passive (smartphone passive app and a wearable device) monitoring. The wearable device included in the current proposal is the new EmbracePlus developed by the SME partner Empatica.

  • To obtain real-world data from the patient’s daily life on the extent to which ADHD medication treatment and physical activity, individually and jointly, may influence cardiometabolic risks in adults with ADHD. This will provide new insights into disease patterns and help improve the safety and effectiveness of pharmacological (i.e. ADHD medication treatment) and nonpharmacological (i.e. physical activity) interventions for patients with ADHD and co-occurring cardiometabolic disease.
  • Our second main aim is to obtain in vivo, real-world data from the patient’s daily life on adherence to pharmacological treatment and its predictors and correlates, over a remote monitoring period of 12 months that starts from pre-treatment initiation.
  • The long-term goal is to use these data to improve the management of cardiometabolic disease in adults with ADHD, and to improve ADHD medication treatment adherence and the personalisation of treatment.
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  WP6

  Predictive Modelling of Cardiometabolic Outcomes and Treatment Discontinuity

  TIMESPAN will apply deep learning neural networks (DLNNs) to existing large-scale cohorts, prescription databases linked with health and sociodemographic records and biobanks with linked genomic data in order to create clinically useful risk stratification models for predicting which ADHD patients are at high risk for poor cardiometabolic outcomes.

  Lead: Stephen Faraone SUNY

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  Some areas of medicine, in particular cardiovascular medicine, have developed useful risk prediction scores. Personalized medicine, in the form of risk stratification estimators, has only recently entered the field of psychiatry and studies have now demonstrated the feasibility of developing risk prediction models, but the literature is very limited, and most studies are based on small samples. The only study that we are aware of (TIMESPAN members in lead) applied machine learning (ML) algorithms using the Swedish national register to predict serious substance use disorder events in early adulthood among patients with ADHD. This study found that large-scale data combined with ML may arrive at clinically useful prediction models, but even more detailed predictor information from linked population register or large-scale cohorts is needed to improve the predictive power.

  The overarching objective of WP6 is to create clinically useful models for predicting which ADHD patients are at high risk for cardiometabolic disease and outcomes associated with those diseases. We will also determine if we can predict treatment discontinuity for both ADHD treatments and treatments for cardiometabolic disorders. Further objectives are:

  • Using epidemiology and treatment data, we will combine predictors of ADHD cardiometabolic outcomes and treatment discontinuity into a single predictive model using DLNNs. This will allow us to make predictions that will be useful in clinical settings to identify high risk patients.
  • Use DLNNs to innovate the analysis of genomic data together with WP4, improving adjustments for ancestry, identifying gene-gene interactions, and testing hypotheses about the shared genetic mechanisms of ADHD and its cardiometabolic outcomes. This will allow us to better understand the shared molecular risks for these disorders and may lead to better models for risk prediction in clinical settings.
• WP7

  Ethics and Data Management

  The overall objective of this WP is to develop an overarching ethical strategy addressing information use from the existing databases, but also for newly generated data. This will be an on-going process, particularly with the General Data Protection Regulation (GDPR) as different Member State follow, different interpretations and implementations resulting in different storage and access procedures.

  Lead: Patrick Ip HKU

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  WP 7 will involve ethics experts in decisions that relate to clinical protocols, assessments and data analysis to ensure the highest ethical standard possible.

  Next to ethics WP7 will oversee the Data Management for effective use of all existing, but also newly acquired data. Data protection, data privacy and ethical issues will be carefully considered in TIMESPAN. Due to national regulations that constrain data sharing of large register data, personal data from several different data sources will primarily stay at the local server within country. We will therefore use a specific data management strategy (i.e., common protocol and distributed network approach) to avoid raw or personal data transfer between partners and/or countries. We aim to provide clear information about what is needed to access data and also provide scripts for data management and analyses. The multidisciplinary and intersectoral Scientific Advisory Board and Ethics and Data Advisory Board will be invited to attend the project meetings and to provide feedback on the project progress and research programme.

  The following specific objectives will therefore be actively pursued by WP7:

  • To oversee adherence to all existing ethical and safety provisions. This will include monitoring of protocols, informed consents and approvals as well compliance with national (both EU and Non-EU partners) and EU regulations (for existing databases and newly acquired data within WPs 1-6).
  • To develop a DMP integrating both the re-use of existing data and newly acquired data. This will ensure GDPR conform analysis of existing and new data. We further aim that data are FAIR.
• WP8

  Dissemination, communication, exploitation, guideline development, and training

  Concentris is specialised in the management of EU-funded research projects and highly experienced in supporting dissemination and outreach activities. Their science communication team has experience in medical writing, public relations and organisation of press conferences, social media and web-design.

  Lead: Tamara Breitinger concentris, Co-Lead: Josep Antoni RamosQuiroga VHIR

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  The dissemination team includes all relevant stakeholders and is optimally equipped to bring newly developed knowledge to other scientists, health care professionals, industry, patients, and the public, both during the project and sustainably post-project. The intensive involvement of patient and scientific organizations within TIMESPAN will enable us to collaborate closely with important non-scientific stakeholders, both as partners and as supporters. We provide an ethical strategy and data management plan (DMP) to allow maximal transparency, open access/science, usability and reproducibility, and disseminate the TIMESPAN findings amongst stakeholders (from patients to health authorities).

  WP8 will provide recommendations for guidelines for the clinical management of adult ADHD patients with co-occurring cardiometabolic disease and train clinicians and real-world data scientist as well as a new generation of interdisciplinary researchers. In order to match this ambition, our team has a broad scope of knowledge and expertise which can only be provided when experts from several sectors work closely together from the beginning to implementation and dissemination of the project results.

  TIMESPAN currently leads one special interest group within the EUNETHYDIS with a focus on and “risk prediction in the context of ADHD”. These previous and ongoing collaborations have built up for TIMESPAN’s focus on ADHD and cardiometabolic disease, with several studies establishing a link between ADHD and cardiometabolic disease. The combined expertise in TIMESPAN provides an opportunity for synergistic efforts to maximize the exploitation potential of TIMESPAN results.

  In addition to this longstanding successful scientific interaction history including joint projects and publications, TIMESPAN also has common supervision, dissemination and research administration experience.

  Thus the overarching goal of WP8 is to develop and execute a detailed plan for dissemination and exploitation of TIMESPAN results, incorporating communication to diverse scientists, clinicians (medical community/ health professionals), patients and their families, pharmaceutical industry, and health authorities such as regulatory agencies (e.g., EMA).

  Specific objectives for WP8 are:

  • To make TIMESPAN known to all stakeholders by developing a communication and outreach plan for activities to communicate knowledge of ADHD and co-occurring cardiometabolic diseases.
  • To disseminate the TIMESPAN results and foster interaction and exchange with the scientific and medical community, health authorities such as regulators (e.g. EMA), pharmaceutical industry, and patients and their families.
  • To directly interact with the EMA to ensure the protocols and results are able to aid the EMA in making regulatory decisions regarding pharmacological treatment for ADHD and cardiometabolic disease.
  • To identify and valorize the intellectual property rights (IPR) generated within WP1-6 and govern the sustainability of TIMESPAN results.
  • To review existing European clinical guidelines (e.g. NICE and EMA) and consensus statements (e.g., ENAA, WFA EUNETHYDIS) guidelines group for ADHD treatment and cardiometabolic diseases and start incorporating TIMESPAN results into (inter)national clinical guidelines and consensus statements to improve the management of patients with ADHD and co-occurring cardiometabolic diseases. Therefore, recommendations will be developed to update existing guidelines and consensus statements.
  • To educate, train, and connect a new generation of ADHD researchers and clinicians working inter- and transdisciplinarily and to foster the career development of all TIMESPAN early career researchers (ECRs).
• WP9

  Project Management

  The coordinator and concentris together form the project management office. The project management office at concentris is the first point of reference for researchers involved in TIMESPAN. The coordinator (ORU) will be responsible for the tasks defined in the grant agreement and represents the consortium vis-à-vis the European Commission (EC).

  Lead: Henrik Larsson ORU

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  Management tasks include:

  • Monitoring that the action is implemented properly.
  • Acting as the intermediary for all communications between the beneficiaries and the EC.
  • Requesting and reviewing any documents or information required by the EC and verify their completeness and correctness.
  • Submitting the deliverables and reports to the EC in accordance with the timing and conditions set out in the grant agreement.
  • Receiving payments from the EC and distributing the payments to the beneficiaries without unjustified delay.
  • Informing the EC of the amounts paid to each beneficiary when requested by the EC.
  • Providing any information relevant to checks, reviews, and audits or the evaluation of impact.
  • Submitting any required ethical documents to the EC.
• WP10

  Ethics requirements

  This WP will be led by ORU together with all TIMESPAN partners will ensure compliance with the ‘ethics requirements’ set out in this work package.

  Lead: Henrik Larsson ORU

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  • Support the ethically and legally responsible implementation of research particularly by ongoing risk-benefit analysis of recruitment.
  • Monitor informed consent procedures that will be implemented for patients recruited to the prospective project study.
  • Ensure proper handling of personal data incl. the rights of data subjects or the processing of genetic, biometric and/or health data that have been established under the national legislation of the participating EU countries .
  • Evaluate the ethics risks related to the data processing activities of the project regularly.
  • Monitor data access and control copies of transfer authorisations.
  • Prevent misuse of research findings related to collection of data on antisocial behaviour through remote technology.
  • Implemented to safeguard the rights and freedoms of the data subjects/research participants and prevent unauthorised access to personal data or the equipment used for processing must be submitted as a deliverable.