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Attention on inattention: Dissecting the causal mechanisms of adult ADHD features

Grant number: 101222412

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Key facts

  • Disease

    COVID-19
  • Start & end year

    2026
    2031
  • Known Financial Commitments (USD)

    $178,755,202.5
  • Funder

    Estonian Research Council
  • Principal Investigator

    Lehto, Kelli
  • Research Location

    Estonia
  • Lead Research Institution

    University of Tartu
  • Research Priority Alignment

    N/A
  • Research Category

    N/A

  • Research Subcategory

    N/A

  • Special Interest Tags

    N/A

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Not Applicable

  • Vulnerable Population

    Not applicable

  • Occupations of Interest

    Not applicable

Abstract

The world is witnessing a sharp rise in adult attention deficit hyperactivity disorder (ADHD) diagnoses, especially after the COVID-19 pandemic. While historically considered a childhood neurodevelopmental disorder, an increasing number of adults are now seeking help for impairing ADHD-like features like inattention, disorganization, restlessness, impulsivity, forgetfulness and emotional dysregulation. Strikingly little is known about the mechanisms causing specific adult ADHD features, raising a key question: Are adult ADHD features truly the same as childhood ADHD, or do they rather reflect other mental conditions with overlapping symptoms? Substantial phenotypic overlap of mental health conditions and lack of precise screening tools make accurate detection of adult ADHD extremely challenging and error prone. Modern mental health care critically needs advanced, biology-informed methods to differentiate mental conditions with greater accuracy. AT-TENSION combines psychology, genomics and data science to dissect the causal mechanisms underlying adult ADHD features and to propose an innovative framework for genomics-informed screening tool development. We will (i) determine diverse genetic mechanisms and causal links with other mental conditions by conducting a pioneering genome-wide investigation of specific adult ADHD features across five large biobanks; (ii) quantify the impact of diverse environmental factors like stress, lifestyle and COVID-19 pandemic on adult ADHD features across life stages and genders; (iii) develop and test a novel genomics-informed screening tool for more accurate ADHD detection in adults by using machine learning and genomics. The goals are achieved by innovatively combining three large-scale data layers: self-reported, electronic health records and genetic data. AT-TENSION aims to redefine our current conceptualization of adult ADHD and revolutionize mental health psychometrics by integrating genomics into screening tool development