Genetic and Regulatory Mechanisms of Comorbidity of Anxiety, Depression and ADHD: A GWAS Meta-Meta-Analysis Through the Lens of a System Biological and Pharmacogenomic Perspective in 18.5 M Subjects
Authors:
- Kai-Uwe LewandrowskiKLKai-Uwe Lewandrowski
- Kenneth BlumKenneth Blum
- Alireza SharafshahAlireza Sharafshah
- Kyriaki Z. ThanosKTKyriaki Z. Thanos
- Panayotis K. ThanosPanayotis K. Thanos
- Richa ZirathRZRicha Zirath
- Albert PinhasovAPAlbert Pinhasov
- Abdalla BowirratABAbdalla Bowirrat
- Nicole JafariNJNicole Jafari
- Foojan ZeineFoojan Zeine
- Milan MakaleMilan Makale
- Colin HannaCHColin Hanna
Open Access
- 5 March 2025
- journal article
- research article
- Published by MDPI AG in Journal of Personalized Medicine
- Vol. 15 (3) , 103
Abstract
Background: In the United States, approximately 1 in 5 children experience comorbidities with mental illness, including depression and anxiety, which lead to poor general health outcomes. Adolescents with substance use disorders exhibit high rates of co-occurring mental illness, with over 60% meeting diagnostic criteria for another psychiatric condition in community-based treatment programs. Comorbidities are influenced by both genetic (DNA antecedents) and environmental (epigenetic) factors. Given the significant impact of psychiatric comorbidities on individuals’ lives, this study aims to uncover common mechanisms through a Genome-Wide Association Study (GWAS) meta-meta-analysis. Methods: GWAS datasets were obtained for each comorbid phenotype, followed by a GWAS meta-meta-analysis using a significance threshold of p < 5E−8 to validate the rationale behind combining all GWAS phenotypes. The combined and refined dataset was subjected to bioinformatic analyses, including Protein–Protein Interactions and Systems Biology. Pharmacogenomics (PGx) annotations for all potential genes with at least one PGx were tested, and the genes identified were combined with the Genetic Addiction Risk Severity (GARS) test, which included 10 genes and eleven Single Nucleotide Polymorphisms (SNPs). The STRING-MODEL was employed to discover novel networks and Protein–Drug interactions. Results: Autism Spectrum Disorder (ASD) was identified as the top manifestation derived from the known comorbid interaction of anxiety, depression, and attention deficit hyperactivity disorder (ADHD). The STRING-MODEL and Protein–Drug interaction analysis revealed a novel network associated with these psychiatric comorbidities. The findings suggest that these interactions are linked to the need to induce “dopamine homeostasis” as a therapeutic outcome. Conclusions: This study provides a reliable genetic and epigenetic map that could assist healthcare professionals in the therapeutic care of patients presenting with multiple psychiatric manifestations, including anxiety, depression, and ADHD. The results highlight the importance of targeting dopamine homeostasis in managing ASD linked to these comorbidities. These insights may guide future pharmacogenomic interventions to improve clinical outcomes in affected individuals.Keywords
Funding Information
- NIH HHS/United States (R21 DA045640/DA/NIDA, R33 DA045640/DA/NIDA, R41 MD012318/MD/NIMHD, I01 CX002099/CX/CSRD, I01 CX000479/CX/CSRD)
- VA/United States (R21 DA045640/DA/NIDA, R33 DA045640/DA/NIDA, R41 MD012318/MD/NIMHD, I01 CX002099/CX/CSRD, I01 CX000479/CX/CSRD)
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