Pre-Infection Mental Health, but Not Brain Volumetry, Predicts Risk of Post-COVID Condition: A Population-Based Cohort Study in the German National Cohort (NAKO)
Year: 2026
Type: preprint
Study design: Observational Study
Abstract: Background Post-COVID Condition (PCC) affected 10–30% of individuals after SARS-CoV-2 infection, and pre-infection predictors of who goes on to develop it are not well established. We compared pre-infection structural brain variation and baseline psychiatric phenotype as candidate predictors of PCC within a common multi-modal framework in the German National Cohort (NAKO). Both are candidate “first hits” under the second-hit hypothesis, which motivates the comparison; this is a prediction study, not a test of that hypothesis. Methods In 8,464 SARS-CoV-2-infected NAKO neuroimaging participants, of whom 2,304 (27.2%) met PCC criteria (weighted post-COVID syndrome (PCS) score > 10.75) and the rest were symptom-free controls, ten pre-infection modalities (T1-weighted volumetric brain MRI across six parcellations, baseline mental health (PHQ-9, GAD-7), demographics, and seven further biomedical and socioeconomic domains) entered a stacked ensemble with 10 × 5 nested cross-validation (primary metric: the area under the precision–recall curve, PR-AUC). Pre-specified analyses assessed transportability to a non-imaging cohort and robustness to the mental-health symptom trajectory and to unmeasured confounding. SARS-CoV-2 infection status and the PCC outcome were ascertained by self-report; no clinically confirmed diagnoses were available. Results Baseline mental health, assessed 3–8 years before infection, was the strongest predictor (38.0% of feature importance; standalone ROC-AUC = 0.640), whereas all six brain-MRI parcellations performed at or near chance (ROC-AUC 0.496–0.516). The multi-modal model achieved moderate, well-calibrated discrimination (ROC-AUC = 0.665, 95% CI 0.653–0.677; PR-AUC = 0.413, 0.392–0.434; ECE = 0.013). A four-modality non-imaging version, applied without retraining to NAKO participants without MRI, retained discrimination (ROC-AUC = 0.660, 0.654–0.665), meeting all three pre-specified equivalence criteria, the calibration intercept narrowly. The baseline mental-health odds ratio was 2.06 (1.83–2.32; E-value 2.66) and essentially unchanged under an alternative control definition (2.07); adjusting for the full mental-health symptom trajectory reduced it to a conservative lower bound of 1.38 (1.20–1.58) that remained independently significant. Baseline mental health did not predict objectively measured hyposmia in participants screened before their infection (0.89) while predicting self-reported smell loss in the same participants (1.92). Conclusions Baseline mental health years before infection is the strongest pre-infection predictor of PCC among the infected, and the association held across the pre-specified sensitivity analyses. Whether it acts specifically on COVID-19 sequelae is a separate question this design cannot answer, and the indirect evidence points away from specificity: the association is undiminished after mild infection but absent among the hospitalized, and baseline mental health predicts current mental-health symptom load slightly less strongly in infected than in non-infected participants. The volumetric structural candidate is not supported: prepandemic T1-weighted volumetry carried no predictive signal in this single neuroimaging cohort. Risk stratification may benefit from incorporating baseline psychiatric phenotype; whether treating it reduces PCC incidence requires interventional study.
Source: medRxiv
Authors: Claas Flint, Cord Spreckelsen, Christian Otto, Rafael Mikolajczyk, Jonas Frost, Luise Victoria Claaß, Jonathan Mathias Fasshauer, Markus Scholz, Laura Buschmann, Nicole Rübsamen, Marvin N. Wright, Lukas Burk, Fabian Bamberg, Christopher L. Schlett, Thoralf Niendorf, Michael Forsting, Yan Li, Karen Steindorf, Stefan Karrasch, Michael Leitzmann, Stefan Haug, Till W. Bärnighausen, Börge Schmidt, Manuela Harries, Vanessa Melhorn, Lilian Krist, Thomas Keil, Annette Peters, Nils Opel
Institutions: Jena University Hospital, Deutsches Zentrum für Psychische Gesundheit, Martin Luther University Halle-Wittenberg, Charité – Universitätsmedizin Berlin, Leipzig University, University of Münster, University of Bremen, Leibniz Institute for Prevention Research and Epidemiology - BIPS, University of Freiburg, University Medical Center Freiburg, Max Delbrück Center, Essen University Hospital, German Cancer Research Center, Helmholtz Munich, LMU Klinikum, German Center for Lung Research, Institut und Poliklinik für Arbeits-, Sozial- und Umweltmedizin, Ludwig-Maximilians-Universität München, University of Regensburg, Harvard University, Heidelberg University, University Hospital Heidelberg, Africa Health Research Institute, Heidelberg Institute of Global Health, University of Duisburg-Essen, Helmholtz Centre for Infection Research, University of Würzburg, Bayerisches Landesamt für Gesundheit und Lebensmittelsicherheit
Language: English
Subfield: Clinical Neurology
Field: Medicine
Domain: Health Sciences
Open Access status: green
Funder: Leibniz-Gemeinschaft
Awards: G3987985702, G852547542
OpenAlex ID: W7212271675
