Epigenome-wide association study identifies a specific panel of DNA methylation signatures for antenatal and postpartum depressive symptoms.

Journal: Journal of affective disorders
Published Date:

Abstract

Depression during pregnancy and postpartum poses significant risks to both maternal and child well-being. The underlying biological mechanisms are unclear, but epigenetic variation could be exploited as a plausible candidate for early detection. We investigated whether DNA methylation signatures are associated with antenatal depressive symptoms (ADS) and whether early alterations in methylation patterns could be used to predict postpartum depressive symptoms (PDS). 201 pregnant women in early pregnancy, without a prior history of depressive disorders, from the STratification of Risk of Diabetes in Early Pregnancy study (STRiDE) were recruited. Using the Patient Health Questionnaire-9 (PHQ-9), 92 women were identified with ADS, while 109 served as controls. Edinburgh Postnatal Depression Scale (EPDS) was used to assess PDS during 6-12 weeks after delivery. The dataset was split into 80 % for training and testing and 20 % for validation, to discern potential CpGs for ADS using a support vector machine classifier. Analysis revealed 591 CpGs significantly associated with ADS, from which a panel of 7 CpGs was identified to discriminate between ADS and controls with high sensitivity and specificity (AUC: 0.85 in test, 0.73 in validation). Pathway analysis highlighted involvement in inositol phosphate metabolism, notch, and calcium signaling. The same 7 CpGs predicted PDS with an AUC of 0.76 (95 % CI: 0.66-0.87). Integration of CpG data with patient-reported information significantly enhanced PDS prediction. Our study identified DNA methylation signatures that could potentially differentiate ADS from controls and predict PDS. This suggests potential for developing a CpG panel for diagnostic and preventive strategies for perinatal depression.

Authors

  • Chinnasamy Thirumoorthy
    Department of Neurochemistry, National Institute of Mental Health & Neuro Sciences (NIMHANS), Bengaluru, India.
  • Kuldeep Kumar Sharma
    Biostatistics, National Institute of Mental Health & Neuro Sciences (NIMHANS), Bengaluru, India.
  • Mohan Deepa
    Department of Diabetology, Madras Diabetes Research Foundation (MDRF), Chennai, India.
  • Saravanan Yogaprabhu
    Department of Molecular Genetics, Madras Diabetes Research Foundation (MDRF), Affiliated to University of Madras, Chennai, India.
  • Janaki Sneha
    Department of Molecular Genetics, Madras Diabetes Research Foundation (MDRF), Affiliated to University of Madras, Chennai, India.
  • Ravikumar Pavithra Rekha
    Department of Neurochemistry, National Institute of Mental Health & Neuro Sciences (NIMHANS), Bengaluru, India.
  • Ulagamadesan Venkatesan
    Department of Diabetology, Madras Diabetes Research Foundation (MDRF), Chennai, India.
  • Saite Hemavathy
    Department of Diabetology, Madras Diabetes Research Foundation (MDRF), Chennai, India.
  • Joyappa Nikhil
    Department of Neurochemistry, National Institute of Mental Health & Neuro Sciences (NIMHANS), Bengaluru, India.
  • Bettadapura N Srikumar
    Neurophysiology, National Institute of Mental Health & Neuro Sciences (NIMHANS), Bengaluru, India.
  • Bhaskarapillai Binukumar
    Biostatistics, National Institute of Mental Health & Neuro Sciences (NIMHANS), Bengaluru, India.
  • Venkatesan Radha
    Department of Molecular Genetics, Madras Diabetes Research Foundation (MDRF), Affiliated to University of Madras, Chennai, India.
  • Sapna Sharma
    German Center for Diabetes Research, Neuherberg, Germany.
  • Harald Grallert
    Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany.
  • Graham Ball
    John van Geest Cancer Research Centre, School of Science and Technology, Nottingham Trent University, Nottingham, United Kingdom.
  • Uma Ram
    Seethapathy Clinic & Hospital, Chennai, India.
  • Ranjit Mohan Anjana
    Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, Gopalapuram, Chennai 600086, India.
  • Muthuswamy Balasubramanyam
    Department of Cell and Molecular Biology, Madras Diabetes Research Foundation (MDRF), Chennai, India.
  • Nikhil Tandon
    Department of Endocrinology and Metabolism, All India Institute of Medical Sciences, New Delhi, India.
  • Viswanathan Mohan
    Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, Gopalapuram, Chennai 600086, India.
  • Ponnusamy Saravanan
    Populations, Evidence and Technologies, Division of Health Sciences, Warwick Medical School, University of Warwick, UK; Department of Diabetes, Endocrinology and Metabolism, George Eliot Hospital, Nuneaton, UK; Centre for Global Health, University of Warwick, UK. Electronic address: p.saravanan@warwick.ac.uk.
  • Kuppan Gokulakrishnan
    Department of Neurochemistry, National Institute of Mental Health & Neuro Sciences (NIMHANS), Bengaluru, India. Electronic address: gokul@nimhans.ac.in.