Two high-risk susceptibility loci at 6p25.3 and 14q32.13 for Waldenström macroglobulinemia

Abstract

Waldenström macroglobulinemia (WM)/lymphoplasmacytic lymphoma (LPL) is a rare, chronic B-cell lymphoma with high heritability. We conduct a two-stage genome-wide association study of WM/LPL in 530 unrelated cases and 4362 controls of European ancestry and identify two high-risk loci associated with WM/LPL at 6p25.3 (rs116446171, near EXOC2 and IRF4; OR = 21.14, 95% CI: 14.40–31.03, P = 1.36 × 10−54) and 14q32.13 (rs117410836, near TCL1; OR = 4.90, 95% CI: 3.45–6.96, P = 8.75 × 10−19). Both risk alleles are observed at a low frequency among controls (~2–3%) and occur in excess in affected cases within families. In silico data suggest that rs116446171 may have functional importance, and in functional studies, we demonstrate increased reporter transcription and proliferation in cells transduced with the 6p25.3 risk allele. Although further studies are needed to fully elucidate underlying biological mechanisms, together these loci explain 4% of the familial risk and provide insights into genetic susceptibility to this malignancy.

Artificial Intelligence in Epigenetic Studies: Shedding Light on Rare Diseases

“…Through PICS, the authors identified that about 90% of causal variants are non-coding, with 60% mapping to immunecell enhancers and gained histone acetylation (Farh et al, 2015). McMaster et al (2018) used CHiCAGO, a convolution background model, to analyze significant chromatin interactions between patients with Waldenström macroglobulinemia (WM, ORPHA:33226) and controls in a two-stage GWAS. They identified two high-risk non-coding SNPs, rs116446171 and rs117410836 at 6p25.3 and 14q32.13, respectively.…”

“…They identified two high-risk non-coding SNPs, rs116446171 and rs117410836 at 6p25.3 and 14q32.13, respectively. Rs116446171 is located near IRF4, DUSP22, and EXOC2, which are implicated in a variety of lymphoid cancers and might represent an important non-coding variant for WM risk (McMaster et al, 2018). Crippa et al (2014) used a probabilistic HMM applied to human embryonic stem cell (HMES) to identify putative regulatory sequences in ChIP-seq data of a patient with trichorhinophalangeal syndrome (TRPS, ORPHA:324764), a complex autosomal dominant malformative disorder, characterized by distinctive craniofacial and skeletal abnormalities.…”

“… McMaster et al (2018) used CHiCAGO, a convolution background model, to analyze significant chromatin interactions between patients with Waldenström macroglobulinemia (WM, ORPHA:33226) and controls in a two-stage GWAS. They identified two high-risk non-coding SNPs, rs116446171 and rs117410836 at 6p25.3 and 14q32.13, respectively.…”

“…They identified two high-risk non-coding SNPs, rs116446171 and rs117410836 at 6p25.3 and 14q32.13, respectively. Rs116446171 is located near IRF4 , DUSP22 , and EXOC2 , which are implicated in a variety of lymphoid cancers and might represent an important non-coding variant for WM risk ( McMaster et al, 2018 ).…”

“…Supervised analysis has been restricted to biological problems in which a good balance between variables and data is observed ( Esteban-Medina et al, 2019 ). In this work, most supervised tools have been applied for diagnosis ( Mo et al, 2014 ; Crippa et al, 2014 ; Fu et al, 2014 ; Farh et al, 2015 ; McMaster et al, 2018 ; Aref-Eshghi et al, 2019 ; Pranckėnienė et al, 2019 ; Cochran et al, 2020 ; Kurkiewicz et al, 2020 ). In RDs, small sample sizes allied to complex levels of data structure and differences among the characteristics of patients can hinder the application of AI tools.…”