👤 Arn M J M van den Maagdenberg

High-dose methotrexate for pediatric cancer treatment is frequently associated with mucositis, which can lead to delayed or discontinued treatment and impact survival. While individual genetic variants have been implicated, the cumulative impact of genetic variation within relevant biological pathways remains unexplored. We evaluated single nucleotide polymorphisms across 18 pathways previously identified as relevant to mucositis in 278 pediatric patients with acute lymphoblastic leukemia from six academic health centers across Canada. Pathway enrichment was assessed using the Joint Association of Genetic variants tool, and a predictive model was developed using XGBoost, a supervised machine learning algorithm based on gradient-boosted decision trees. Pathway enrichment identified significant associations in IL6 (P = 0.04) and WNT/β-catenin (P = 0.048) signaling pathways. The predictive model (area under the curve [AUC] = 0.76) highlighted single nucleotide polymorphisms associated with inflammation- and mucosa-related genes, including PRKCD, IL17B, MAST3, and CAPN9, with both risk and protective effects. Model performance dropped by 0.15 in AUC (from 0.76 to 0.61) after removing single nucleotide polymorphism features, underscoring their predictive value. This pathway-informed approach identifies genetic contributors to methotrexate-induced mucositis and supports polygenic risk prediction. Our findings provide a foundation for individualized toxicity risk profiling and suggest potential therapeutic targets to mitigate treatment-limiting mucositis in pediatric oncology. Show less

Migraine affects over a billion individuals worldwide but its genetic underpinning remains largely unknown. Here, we performed a genome-wide association study of 102,084 migraine cases and 771,257 controls and identified 123 loci, of which 86 are previously unknown. These loci provide an opportunity to evaluate shared and distinct genetic components in the two main migraine subtypes: migraine with aura and migraine without aura. Stratification of the risk loci using 29,679 cases with subtype information indicated three risk variants that seem specific for migraine with aura (in HMOX2, CACNA1A and MPPED2), two that seem specific for migraine without aura (near SPINK2 and near FECH) and nine that increase susceptibility for migraine regardless of subtype. The new risk loci include genes encoding recent migraine-specific drug targets, namely calcitonin gene-related peptide (CALCA/CALCB) and serotonin 1F receptor (HTR1F). Overall, genomic annotations among migraine-associated variants were enriched in both vascular and central nervous system tissue/cell types, supporting unequivocally that neurovascular mechanisms underlie migraine pathophysiology. Show less

Migraine and major depressive disorder (MDD) are common brain disorders that frequently co-occur. Despite epidemiological evidence that migraine and MDD share a genetic basis, their overlap at the molecular genetic level has not been thoroughly investigated. Using single-nucleotide polymorphism (SNP) and gene-based analysis of genome-wide association study (GWAS) genotype data, we found significant genetic overlap across the two disorders. LD Score regression revealed a significant SNP-based heritability for both migraine (h Show less

Metabolite quantitative traits carry great promise for epidemiological studies, and their genetic background has been addressed using Genome-Wide Association Studies (GWAS). Thus far, the role of less common variants has not been exhaustively studied. Here, we set out a GWAS for metabolite quantitative traits in serum, followed by exome sequence analysis to zoom in on putative causal variants in the associated genes. 1H Nuclear Magnetic Resonance (1H-NMR) spectroscopy experiments yielded successful quantification of 42 unique metabolites in 2,482 individuals from The Erasmus Rucphen Family (ERF) study. Heritability of metabolites were estimated by SOLAR. GWAS was performed by linear mixed models, using HapMap imputations. Based on physical vicinity and pathway analyses, candidate genes were screened for coding region variation using exome sequence data. Heritability estimates for metabolites ranged between 10% and 52%. GWAS replicated three known loci in the metabolome wide significance: CPS1 with glycine (P-value  = 1.27×10-32), PRODH with proline (P-value  = 1.11×10-19), SLC16A9 with carnitine level (P-value  = 4.81×10-14) and uncovered a novel association between DMGDH and dimethyl-glycine (P-value  = 1.65×10-19) level. In addition, we found three novel, suggestively significant loci: TNP1 with pyruvate (P-value  = 1.26×10-8), KCNJ16 with 3-hydroxybutyrate (P-value  = 1.65×10-8) and 2p12 locus with valine (P-value  = 3.49×10-8). Exome sequence analysis identified potentially causal coding and regulatory variants located in the genes CPS1, KCNJ2 and PRODH, and revealed allelic heterogeneity for CPS1 and PRODH. Combined GWAS and exome analyses of metabolites detected by high-resolution 1H-NMR is a robust approach to uncover metabolite quantitative trait loci (mQTL), and the likely causative variants in these loci. It is anticipated that insight in the genetics of intermediate phenotypes will provide additional insight into the genetics of complex traits. Show less