Distinct germline genetic susceptibility profiles identified for common non-Hodgkin lymphoma subtypes

Abstract

Lymphoma risk is elevated for relatives with common non-Hodgkin lymphoma (NHL) subtypes, suggesting shared genetic susceptibility across subtypes. To evaluate the extent of mutual heritability among NHL subtypes and discover novel loci shared among subtypes, we analyzed data from eight genome-wide association studies within the InterLymph Consortium, including 10,629 cases and 9505 controls. We utilized Association analysis based on SubSETs (ASSET) to discover loci for subsets of NHL subtypes and evaluated shared heritability across the genome using Genome-wide Complex Trait Analysis (GCTA) and polygenic risk scores. We discovered 17 genomewide significant loci (P < 5 × 10 −8 ) for subsets of NHL subtypes, including a novel locus at 10q23.33 (HHEX) (P = 3.27 × 10 −9 ). Most subset associations were driven primarily by only one subtype. Genome-wide genetic correlations between pairs of subtypes varied broadly from 0.20 to 0.86, suggesting substantial heterogeneity in the extent of shared heritability among subtypes. Polygenic risk score analyses of established loci for different lymphoid malignancies identified strong associations with some NHL subtypes (P < 5 × 10 −8 ), but weak or null associations with others. Although our analyses suggest partially shared heritability and biological pathways, they reveal substantial heterogeneity among NHL subtypes with each having its own distinct germline genetic architecture.

Improve the model of disease subtype heterogeneity by leveraging external summary data

“…It has been hypothesized that various NHL subtypes and other lymphoid malignancies might share some degree of genetic susceptibility. Recently, [ 39 ] used eight GWAS within the InterLymph Consortium to study the genetic heritability in four major NHL subtypes, including CLL, DLBCL, FL, and MZL. To explore pleiotropy between NHL subtypes and other lymphoid malignancies (e.g., acute lymphoblastic leukemia and Hodgkin lymphoma), they generated PRS using SNPs that had been established as being associated with each lymphoid malignancy and tested their associations with risk for the four NHL subtypes.…”

“…We utilized PolyGIM to analyze the project described by [ 39 ], using the PRS for Hodgkin lymphoma (HL) as our primary example. This PRS was derived from 21 HL-associated SNPs that were selected by [ 39 ] due to their identification as genome-wide significant SNPs, each with a P -value of less than 5 × 10 −8 from seven previously published GWAS [ 43 – 49 ].…”

“…[ 39 ] collected data from eight GWAS with European ancestry, including six US-based studies and two European studies. Table 3 shows the sample sizes of cases with specific NHL subtypes and controls from each study.…”

“…Beside data from the internal study, we have summary data from multiple external studies. In the NHL example, we consider the PRS defined by a set of 21 SNPs [ 39 ]. For each of those SNPs, we have SNP-level summary statistics from seven external studies.…”

“…To explore pleiotropy between NHL subtypes and other lymphoid malignancies (e.g., acute lymphoblastic leukemia and Hodgkin lymphoma), they generated PRS using SNPs that had been established as being associated with each lymphoid malignancy and tested their associations with risk for the four NHL subtypes. We utilized PolyGIM to analyze the project described by [39], using the PRS for Hodgkin lymphoma (HL) as our primary example. This PRS was derived from 21 HL-associated SNPs that were selected by [39] due to their identification as genome-wide significant SNPs, each with a P-value of less than 5 × 10 −8 from seven previously published GWAS [43][44][45][46][47][48][49].…”