Human GenomicsGenetic & Genomic MedicinePeer-reviewed journal article
A genome-wide pleiotropy study between atopic dermatitis and neuropsychiatric disorders
Charalabos AntonatosiD, Alexandros PontikasiD, Adam Akritidis, Dimitra Mitsoudi, Sophia GeorgiouiD, Alexander J. StratigosiD, Aikaterini Zacharopoulou, Stamatios GregoriouiD, Katerina GrafanakiiD, Yiannis VasilopoulosiD
Abstract
Comorbidities between atopic dermatitis (AD) and neuropsychiatric disorders are frequently reported, however the extent of shared genetic architecture remains unclear. Here, we performed a large-scale genome-wide pleiotropy approach to investigate the genetic correlations and causal associations between AD and five neuropsychiatric disorders, attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BP), major depressive disorder (MDD), and schizophrenia (SCZ). Using genome-wide association (GWAS) data, we explored genetic overlaps, pleiotropic loci and assessed the capacity of pleiotropic associations to identify drug targets. We identified significant positive genetic correlations between AD and ADHD (rg=0.14, P-value=2x10), MDD (rg=0.13, P-value=1.2x10 3) and BP (rg=0.11, P-value= 4x10 3). Genome-wide pleiotropy scans identified 37 distinct pleiotropic loci between AD and neuropsychiatric traits, with gene-based analyses highlighting 86 unique genes participating in inflammatory pathways. Pleiotropy-informed target prioritization facilitated the identification of novel pathophysiological mechanisms for AD and putative drug targets, such as members of TNF and JAK-STAT3 signaling. Mendelian randomization provided evidence of a causal relationship between genetic liability to MDD and BP with an increased risk of AD, independent of sample overlap. Collectively, our findings elucidate shared molecular mechanisms between AD and neuropsychiatric disorders, emphasizing immune-related pathways as key contributors to both disease categories, with potential implications for therapeutic interventions targeting common inflammatory mechanisms.
- organism: human
- assay: GWAS summary statistics
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 5
- FWCI
- 2.92
- Field percentile
- top 8%
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