ArticleBMC medical genomics2019
Gene-based analysis of ADHD using PASCAL: a biological insight into the novel associated genes.
Article in BMC medical genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 28 citations in OpenAlex.
- Multi-tissue transcriptome-wide association study identifies 29 risk genes associated with attention-deficit/hyperactivity disorder.medRxiv : the preprint server for health sciences · 2026Article
- cfGWAS reveal genetic basis of cell-free DNA end motifs.Nature communications · 2026Article
- Examining Differences in the Genetic and Functional Architecture of Attention-Deficit/Hyperactivity Disorder Diagnosed in Childhood and Adulthood.Biological psychiatry global open science · 2024Article
- Biological Predictors of Treatment Response in Adult Attention Deficit Hyperactivity Disorder (ADHD): A Systematic Review.Journal of personalized medicine · 2022Review
- A machine learning-based SNP-set analysis approach for identifying disease-associated susceptibility loci.Scientific reports · 2022Article
- Mapping gene and gene pathways associated with coronary artery disease: a CARDIoGRAM exome and multi-ancestry UK biobank analysis.Scientific reports · 2021Article
- Genome-wide association study identifies 7q11.22 and 7q36.3 associated with noise-induced hearing loss among Chinese population.Journal of cellular and molecular medicine · 2021Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAttention-Deficit Hyperactivity Disorder (ADHD) is a complex neurodevelopmental disorder (NDD) which may significantly impact on the affected individual's life. ADHD is acknowledged to have a high heritability component (70-80%). Recently, a meta-analysis of GWAS (Genome Wide Association Studies) has demonstrated the association of several independent loci. Our main aim here, is to apply PASCAL (pathway scoring algorithm), a new gene-based analysis (GBA) method, to the summary statistics obtained in this meta-analysis. PASCAL will take into account the linkage disequilibrium (LD) across genomic regions in a different way than the most commonly employed GBA methods (MAGMA or VEGAS (Versatile Gene-based Association Study)). In addition to PASCAL analysis a gene network and an enrichment analysis for KEGG and GO terms were carried out. Moreover, GENE2FUNC tool was employed to create gene expression heatmaps and to carry out a (DEG) (Differentially Expressed Gene) analysis using GTEX v7 and BrainSpan data.
resultsPASCAL results have revealed the association of new loci with ADHD and it has also highlighted other genes previously reported by MAGMA analysis. PASCAL was able to discover new associations at a gene level for ADHD: FEZF1 (p-value: 2.2 × 10
conclusionsPASCAL has been revealed as an efficient tool to extract additional information from previous GWAS using their summary statistics. This study has identified novel ADHD associated genes that were not previously reported when other GBA methods were employed. Moreover, a biological insight into the biological function of the ADHD associated genes across brain regions and neurodevelopmental stages is provided.
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