Exciting Minds

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Kelli Lehto

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2025 - 2030 • Starting Grant

How has receiving an ERC grant influenced you as a scientist?

The ERC grant significantly strengthens my scientific independence, boosts my confidence as a scientist, and provides a unique opportunity to pursue bold ideas beyond traditional boundaries.

Attention on inattention: Dissecting the causal mechanisms of adult ADHD features (AT‑TENSION)

What causes ADHD symptoms in adults, and how can diagnostic precision be improved? Adult ADHD diagnosis rates are skyrocketing, and no one knows exactly why. ADHD is a highly heritable neurodevelopmental condition with an onset in childhood. However, ADHD features characteristic of adults, such as problems with concentration, organisation, and memory, restlessness, and impulsive behaviours, are also typical of other common mental health conditions. They may be linked to, for example, depression or anxiety, or caused by environmental factors such as stress or poor lifestyle. Currently, it is extremely difficult to differentiate these causes and provide the best health care and support for affected individuals. By combining large biobanks and interdisciplinary methods from genomics, psychology, and data science, Lehto aims to redefine ADHD features in adults and provide a novel framework for developing innovative, biology-informed screening tools for use in psychiatric settings, including more accurate diagnosis of ADHD in adults.

Result

The project has not yet begun. Lehto hypothesises that adult ADHD features don’t always reflect undiagnosed childhood ADHD; many may instead stem from depression, anxiety, substance abuse, or environmental factors such as stress, poor sleep quality or the COVID-19 pandemic. Over the next five years, her group will study the causes of adult ADHD-related features using genetic, environmental and lifestyle data. In addition to the Estonian Biobank, analyses will draw on biobanks in Norway, the Netherlands, Sweden, and the UK. The study will identify which ADHD-related traits are genetically linked to ADHD diagnosed in childhood and which arise from other causes. Since current psychiatric diagnoses rely solely on patient reports, the ultimate aim is to develop a more precise tool. Using machine learning, the team will analyse symptom, lifestyle, and personality data to define clusters of features strongly associated with genetics of ADHD diagnosed in childhood and design a more accurate screening questionnaire for adult ADHD.

Impact

Lehto aims to uncover the genetic and environmental factors shaping ADHD-related features in adults. This knowledge will support the development of a genetics-informed screening tool to distinguish ADHD from other conditions more precisely. Such insights will help societies prevent, detect, and manage ADHD-related features more effectively, improving the well-being of millions. The most direct application lies in psychiatry, where current diagnostic tools rely solely on patient reports rather than biological measures, creating major challenges. With AT-TENSION, the team seeks to clarify the diverse causes of ADHD-like traits in adults and propose a biology-informed framework for more accurate diagnosis. In the long term, this approach will reduce healthcare costs, improve the lives of those struggling with mental health problems, and enable better prevention strategies.