Utility of blood DNA methylation and immune cell-type estimates to identify clinically relevant links between immunity and health conditions in a large cohort

Marisol Herrera-Rivero^1,2*Jan Homann¹Christina M. Lill^1,3Matthias Nauck^4,5Wolfgang Lieb⁶Jens Kuhle^7,8Heike Minnerup¹Marco Hermesdorf¹Klaus Berger¹

• ¹Institute of Epidemiology and Social Medicine, Faculty of Medicine, University of Münster, Münster, North Rhine-Westphalia, Germany
• ²Joint Institute for Individualisation in a Changing Environment (JICE), University of Münster and Bielefeld University, Münster, Germany
• ³Ageing Epidemiology Research Unit, School of Public Health, Faculty of Medicine, Imperial College London, London, England, United Kingdom
• ⁴Institute for Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Mecklenburg-Vorpommern, Germany
• ⁵Partner Site Greifswald, German Centre for Cardiovascular Research (DZHK), Greifswald, Mecklenburg-Vorpommern, Germany
• ⁶Institute of Epidemiology, Faculty of Medicine, University of Kiel, Kiel, Schleswig-Holstein, Germany
• ⁷Multiple Sclerosis Centre and Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB), Departments of Biomedicine and Clinical Research, University Hospital and University of Basel, Basel, Switzerland
• ⁸Department of Neurology, University Hospital of Basel, Basel, Switzerland

The immune system plays a central role in health and disease. Changes in the proportions of immune cell types have been linked with diverse pathological conditions. However, direct measurements of circulating immune cells are often not available, especially in large human cohorts. Here, whole blood DNA methylation (DNAm) array data might be a feasible solution to study the links between immune cells and human health. This study investigated associations between DNAm estimates of six immune cell types and fifteen circulating serum biomarkers related to health conditions among 1007 participants of the BiDirect Study and then performed follow-up analyses. We found an association between the granulocyte estimates (Gran) and serum levels of high-sensitivity C-reactive protein (hsCRP; beta=0.021, p=3.71x10-5, false discovery rate-FDR=0.0038). This was further confirmed by polygenic score analysis (beta=0.0325, p=0.041). In follow-up analyses, we identified a statistical interaction between Gran and hsCRP linked to the diagnosis of chronic pain (beta = -5.65, p=0.0047, FDR=0.047) and showed significant Gran-hsCRP interaction effects on pain perception as assessed with the pain sensitivity questionnaire (PSQ-minor; beta=0.43, p=0.0125). In addition, by analyzing DNAm levels in granulocyte-expressed genes, we pinpointed potential novel target genes for chronic pain, including PLBD1 and TAPBP. These findings exemplify the utility of blood DNAm and immune cell-type estimates to help identify clinically relevant links between immunity and health outcomes in large cohorts.