Genetic determinants of blood-cell traits influence susceptibility to childhood acute lymphoblastic leukemia

Kachuri, Linda; Jeon, Soyoung; DeWan, Andrew T.; Metayer, Catherine; Ma, Xiaomei; Witte, John S.; Chiang, Charleston W.K.; Smith, Adam J. de

doi:10.1016/j.ajhg.2021.08.004

Cited by 42 publications

(40 citation statements)

References 74 publications

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“…Childhood ALL provides an ideal test case, as the precise cells of origin remain poorly defined in this disease, given that cell state can be altered as a result of malignancy. After fine-mapping of the GWAS for risk variants underlying this disease 43 , 44 (Supplementary Table 3 ), the causal variants were employed for SCAVENGE analysis with an scATAC-seq dataset of human hematopoiesis ( n = 63,882) that we also used in our validation of hematopoietic trait enrichments (Extended Data Fig. 4b–e ).…”

Section: Resultsmentioning

confidence: 99%

Variant to function mapping at single-cell resolution through network propagation

Cato

Weng

et al. 2022

Nat Biotechnol

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Genome-wide association studies in combination with single-cell genomic atlases can provide insights into the mechanisms of disease-causal genetic variation. However, identification of disease-relevant or trait-relevant cell types, states and trajectories is often hampered by sparsity and noise, particularly in the analysis of single-cell epigenomic data. To overcome these challenges, we present SCAVENGE, a computational algorithm that uses network propagation to map causal variants to their relevant cellular context at single-cell resolution. We demonstrate how SCAVENGE can help identify key biological mechanisms underlying human genetic variation, applying the method to blood traits at distinct stages of human hematopoiesis, to monocyte subsets that increase the risk for severe Coronavirus Disease 2019 (COVID-19) and to intermediate lymphocyte developmental states that predispose to acute leukemia. Our approach not only provides a framework for enabling variant-to-function insights at single-cell resolution but also suggests a more general strategy for maximizing the inferences that can be made using single-cell genomic data.

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Section: Resultsmentioning

confidence: 99%

Variant to function mapping at single-cell resolution through network propagation

Cato

Weng

et al. 2022

Nat Biotechnol

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“…Next, in Latino and non-Latino white subjects with single nucleotide polymorphism (SNP) genotype data (117 cases, 130 controls), we assessed whether SNPs associated with DS-ALL risk in ARID5B (rs7089424), IKZF1 (rs11978267), CDKN2A (rs3731249), or GATA3 (rs3824662) 7 may confound the association with B-cell proportions, as these loci were previously associated with variation in white blood cell traits 12 . We included the genotypes of these four SNPs in the regression model one at a time and also all together, and the significantly increased B-cell proportions in DS-ALL cases remained, with similar effect sizes in Latinos and non-Latino whites (Table S4).…”

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confidence: 99%

“…Results from the current study support that, in the context of DS, children with greater B-cell proportions at birth have an increased risk of developing DS-ALL. A genetic predisposition to overproducing lymphocytes was recently associated with increased ALL risk in the non-DS population 12 . Further studies are required to understand the mechanisms underlying the association between increased B-cells and ALL development in children with and without DS, but these may involve effects on the proliferation of preleukemic clones and generation of leukemia-forming mutations, as well as potential impacts on immune function and response to infections 12,19 .…”

Section: Figure/table Count: 2 Tablesmentioning

confidence: 99%

Epigenome-Wide Association Study of Acute Lymphoblastic Leukemia in Children with Down Syndrome

Sok

et al. 2021

Blood

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Background: Down syndrome (DS) is associated with an up to 30-fold increased risk of B-cell acute lymphoblastic leukemia (ALL), and DS-ALL patients have worse overall survival and increased long-term treatment-related health conditions compared with non-DS ALL patients. In a recent genome-wide association study of DS-ALL, established ALL genetic risk loci were associated with DS-ALL, with several single nucleotide polymorphisms (SNPs) conferring a larger effect on ALL risk in the context of DS than in euploidy. We performed an epigenome-wide association study (EWAS) to elucidate whether epigenetic differences at birth are associated with risk of subsequent DS-ALL. Methods: The DS-ALL Discovery Study included 147 DS-ALL cases and 198 DS controls from the International Study of Down Syndrome Acute Leukemia, with newborn dried bloodspots (DBS) obtained from California (n=326) and Washington state (n=19) biobanks. The DS-ALL Replication Study included 24 DS-ALL cases and 24 DS controls with newborn DBS from the Michigan Neonatal Biobank. DNA was isolated from DBS, bisulfite converted, and assayed using Illumina Infinium MethylationEPIC Beadchip genome-wide DNA methylation arrays. Raw data were processed using "minfi" and "noob" packages in R. Reference-based deconvolution of blood cell proportions was performed using the Identifying Optimal DNA methylation Libraries (IDOL) algorithm, using DNA methylation data from cord blood reference samples, to estimate proportions of B cells, T cells (CD4+ and CD8+), monocytes, granulocytes, natural killer cells, and nucleated red blood cells. We compared each cell type proportion between DS-ALL cases and DS controls using linear regression adjusting for sex, plate, and principal components (PCs) to account for genetic ancestry. To identify single CpG probes associated with DS-ALL risk, we performed a multiethnic EWAS of DS-ALL in each study using linear regression adjusting for sex, plate, and PCs related to: 1) cell-type proportions and 2) genetic ancestry. Differentially methylated regions (DMRs) were identified using DMRcate and comb-p methods. In the Discovery Study, genome-wide SNP array data were available for 131 cases and 130 controls, and data from targeted sequencing of somatic mutations in exons 2/3 of GATA1 were available for 184/198 DS controls. Results: Deconvolution of blood cell proportions in the DS-ALL Discovery Study showed significantly higher B cell proportions in newborns with DS who later developed ALL (mean=0.0128, sd=0.0151) compared with DS controls (mean=0.00826, sd=0.0115) (P=6.4x10 -4, coefficient=0.0052). A significantly higher B cell proportion at birth was also found in DS-ALL cases in the independent Replication Study (cases mean=0.048, sd=0.024; controls mean=0.039, sd=0.028; P=0.03, coefficient=0.015). In the Discovery Study, the B cell difference remained significant (P=5.8x10 -3) with a similar effect size (coefficient=0.0045) after removal of GATA1 mutation-positive DS controls (n=30). We also investigated whether DS-ALL risk SNPs at ARID5B, IKZF1, GATA3, and CDKN2A may confound the association, but the increased B cell proportions in DS-ALL remained significant and effect estimates slightly increased in SNP genotype-adjusted models (coefficient range:0.0055-0.0059). In the EWAS of DS-ALL, 9 CpGs reached epigenome-wide significance (P<7.67x10 -8), including 2 CpGs overlapping the promoter of the tumor suppressor gene TRIM13, frequently deleted in B-CLL, although none of these showed evidence of association (P<0.05) in the Replication Study. We identified 125 DMRs associated with DS-ALL in the Discovery Study. For 3 DMRs, overlapping genes HOPX, SMIM24, and PPP1R10, all implicated in normal and leukemic stem cell function, there were multiple significant CpGs in the Replication Study (P<0.05) all with effects in the same direction as the Discovery Study DMRs. Conclusions: Increased B cell proportions in newborns with DS may be a risk factor for development of DS-ALL in childhood. This finding, based on DNA methylation data, requires confirmation using conventional cell count measures, and should be explored as a novel biomarker for ALL risk in the non-DS population. Single CpGs and DMRs associated with DS-ALL risk in our Discovery Study require further investigation, including in additional ALL case-control studies in DS and non-DS populations. Disclosures Ma: Celgene/Bristol Myers Squibb: Consultancy, Research Funding.

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“…Next, in Latino and non-Latino White subjects with single nucleotide polymorphism (SNP) genotype data (117 cases, 130 control subjects), we assessed whether SNPs associated with DS-ALL risk in ARID5B (rs7089424), IKZF1 (rs11978267), CDKN2A (rs3731249), or GATA3 (rs3824662) 7 may confound the association with B-cell proportions, as these loci were previously associated with variation in white blood cell traits. 14 We included the genotypes of these 4 SNPs in the regression model one at a time and also all together, and the significantly increased B-cell proportions in DS-ALL cases remained, with similar effect sizes in Latinos and non-Latino Whites (supplemental Table 4).…”

mentioning

confidence: 99%

“…A genetic predisposition to overproducing lymphocytes was recently associated with increased ALL risk in the non-DS population. 14 Further studies are required to understand the mechanisms underlying the association between increased B cells and ALL development in children with and without DS, but these may involve effects on the proliferation of preleukemic clones and generation of leukemia-forming mutations, as well as potential impacts on immune function and response to infections. 14,21 …”

mentioning

confidence: 99%

Genetic determinants of blood-cell traits influence susceptibility to childhood acute lymphoblastic leukemia

Cited by 42 publications

References 74 publications

Variant to function mapping at single-cell resolution through network propagation

Variant to function mapping at single-cell resolution through network propagation

Epigenome-Wide Association Study of Acute Lymphoblastic Leukemia in Children with Down Syndrome

Epigenome-wide association study of acute lymphoblastic leukemia in children with Down syndrome

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