Genetic Landscape of Major Depressive Disorder: Assessment of Potential Diagnostic and Antidepressant Response Markers

Author:

Singh Priyanka12,Srivastava Ankit13,Guin Debleena14,Thakran Sarita12,Yadav Jyoti1,Chandna Puneet5ORCID,Sood Mamta6,Chadda Rakesh Kumar6,Kukreti Ritushree12

Affiliation:

1. Genomics and Molecular Medicine Unit, Council of Scientific and Industrial Research (CSIR) - Institute of Genomics and Integrative Biology (IGIB) , New Delhi , India

2. Academy of Scientific and Innovative Research (AcSIR) , Ghaziabad , India

3. Department of Pharmacology, School of Pharmaceutical Education and Research, Jamia Hamdard , New Delhi , India

4. Department of Biotechnology, Delhi Technological University , Shahbad Daulatpur, Delhi , India

5. Indian Society of Colposcopy and Cervical Pathology (ISCCP), Safdarjung Hospital , New Delhi , India

6. Department of Psychiatry, All India Institute of Medical Sciences , Ansari Nagar, New Delhi , India

Abstract

Abstract Background The clinical heterogeneity in major depressive disorder (MDD), variable treatment response, and conflicting findings limit the ability of genomics toward the discovery of evidence-based diagnosis and treatment regimen. This study attempts to curate all genetic association findings to evaluate potential variants for clinical translation. Methods We systematically reviewed all candidates and genome-wide association studies for both MDD susceptibility and antidepressant response, independently, using MEDLINE, particularly to identify replicated findings. These variants were evaluated for functional consequences using different in silico tools and further estimated their diagnostic predictability by calculating positive predictive values. Results A total of 217 significantly associated studies comprising 1200 variants across 545 genes and 128 studies including 921 variants across 412 genes were included with MDD susceptibility and antidepressant response, respectively. Although the majority of associations were confirmed by a single study, we identified 31 and 18 replicated variants (in at least 2 studies) for MDD and antidepressant response. Functional annotation of these 31 variants predicted 20% coding variants as deleterious/damaging and 80.6% variants with regulatory effect. Similarly, the response-related 18 variants revealed 25% coding variant as damaging and 88.2% with substantial regulatory potential. Finally, we could calculate the diagnostic predictability of 19 and 5 variants whose positive predictive values ranges from 0.49 to 0.66 for MDD and 0.36 to 0.66 for response. Conclusions The replicated variants presented in our data are promising for disease diagnosis and improved response outcomes. Although these quantitative assessment measures are solely directive of available observational evidence, robust homogenous validation studies are required to strengthen these variants for molecular diagnostic application.

Funder

Indian Council of Medical Research

Council of Scientific and Industrial Research, India

Publisher

Oxford University Press (OUP)

Subject

Pharmacology (medical),Psychiatry and Mental health,Pharmacology

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