Screening for depression in the general population through lipid biomarkersResearch in context
Anna Tkachev,
Elena Stekolshchikova,
Anastasia Golubova,
Anna Serkina,
Anna Morozova,
Yana Zorkina,
Daria Riabinina,
Elizaveta Golubeva,
Aleksandra Ochneva,
Valeria Savenkova,
Daria Petrova,
Denis Andreyuk,
Anna Goncharova,
Irina Alekseenko,
Georgiy Kostyuk,
Philipp Khaitovich
Affiliations
Anna Tkachev
Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Skolkovo Institute of Science and Technology, Moscow, 121205, Russia; LLC NeurOmix, Moscow, 119571, Russia
Elena Stekolshchikova
Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Skolkovo Institute of Science and Technology, Moscow, 121205, Russia
Anastasia Golubova
Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Skolkovo Institute of Science and Technology, Moscow, 121205, Russia
Anna Serkina
Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Skolkovo Institute of Science and Technology, Moscow, 121205, Russia
Anna Morozova
Mental-health Clinic No. 1, Named After N.A. Alekseev, Moscow, 117152, Russia; Department of Basic and Applied Neurobiology, V. Serbsky Federal Medical Research Centre of Psychiatry and Narcology, 119034, Moscow, Russia
Yana Zorkina
Mental-health Clinic No. 1, Named After N.A. Alekseev, Moscow, 117152, Russia; Department of Basic and Applied Neurobiology, V. Serbsky Federal Medical Research Centre of Psychiatry and Narcology, 119034, Moscow, Russia
Daria Riabinina
Mental-health Clinic No. 1, Named After N.A. Alekseev, Moscow, 117152, Russia
Elizaveta Golubeva
Mental-health Clinic No. 1, Named After N.A. Alekseev, Moscow, 117152, Russia
Aleksandra Ochneva
Mental-health Clinic No. 1, Named After N.A. Alekseev, Moscow, 117152, Russia; Department of Basic and Applied Neurobiology, V. Serbsky Federal Medical Research Centre of Psychiatry and Narcology, 119034, Moscow, Russia
Valeria Savenkova
Mental-health Clinic No. 1, Named After N.A. Alekseev, Moscow, 117152, Russia
Daria Petrova
Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Skolkovo Institute of Science and Technology, Moscow, 121205, Russia
Denis Andreyuk
Mental-health Clinic No. 1, Named After N.A. Alekseev, Moscow, 117152, Russia; Economy Faculty, M.V. Lomonosov Moscow State University, 119991, Moscow, Russia
Anna Goncharova
Moscow Center for Healthcare Innovations, Moscow, 123473, Russia
Irina Alekseenko
Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Science, Moscow Region, 142290, Russia
Georgiy Kostyuk
Mental-health Clinic No. 1, Named After N.A. Alekseev, Moscow, 117152, Russia; Corresponding author.
Philipp Khaitovich
Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Skolkovo Institute of Science and Technology, Moscow, 121205, Russia; LLC NeurOmix, Moscow, 119571, Russia; Corresponding author. Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Skolkovo Institute of Science and Technology, Moscow, 121205, Russia.
Summary: Background: Anxiety and depression significantly contribute to the overall burden of mental disorders, with depression being one of the leading causes of disability. Despite this, no biochemical test has been implemented for the diagnosis of these mental disorders, while recent studies have highlighted lipids as potential biomarkers. Methods: Using a streamlined high-throughput lipidome analysis method, direct-infusion mass spectrometry, we evaluated blood plasma lipid levels in 604 individuals from a general urban population and analysed their association with self-reported anxiety and depression symptoms. We also assessed lipidome profiles in 32 patients with clinical depression, matched to 21 healthy controls. Findings: We found a significant correlation between lipid abundances and the severity of self-reported depression symptoms. Moreover, lipid alterations detected in high scoring volunteers mirrored the lipidome profiles identified in patients with clinical depression included in our study. Based on these findings, we developed a lipid-based predictive model distinguishing individuals reporting severe depressive symptoms from non-depressed subjects with high accuracy. Interpretation: This study demonstrates the possibility of generalizing lipid alterations from a clinical cohort to the general population and underscores the potential of lipid-based biomarkers in assessing depressive states. Funding: This study was sponsored by the Moscow Center for Innovative Technologies in Healthcare, №2707-2, №2102-11.
