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. 2025 Feb;39(2):400-411.
doi: 10.1038/s41375-024-02436-y. Epub 2024 Nov 6.

Genome-first determination of the prevalence and penetrance of eight germline myeloid malignancy predisposition genes: a study of two population-based cohorts

Rachel M Hendricks  1 , Jung Kim #  1 , Jeremy S Haley #  2 , Mark Louie Ramos #  3 , Uyenlinh L Mirshahi #  2 , David J Carey  2 , Douglas R Stewart  1 , Lisa J McReynolds  4
Affiliations

Genome-first determination of the prevalence and penetrance of eight germline myeloid malignancy predisposition genes: a study of two population-based cohorts

Rachel M Hendricks et al. Leukemia. 2025 Feb.

Abstract

It is estimated that 10% of individuals with a myeloid malignancy carry a germline susceptibility. Using the genome-first approach, in which individuals were ascertained on genotype alone, rather than clinical phenotype, we quantified the prevalence and penetrance of pathogenic germline variants in eight myeloid malignancy predisposition (gMMP) genes. ANKRD26, CEBPA, DDX41, MECOM, SRP72, ETV6, RUNX1 and GATA2, were analyzed from the Geisinger MyCode DiscovEHR (n = 170,503) and the United Kingdom Biobank (UKBB, n = 469,595). We identified a high risk of myeloid malignancies (MM) (odds ratio[OR] all genes: DiscovEHR, 4.6 [95% confidential interval (CI) 2.1-9.7], p < 0.0001; UKBB, 6.0 [95% CI 4.3-8.2], p = 3.1 × 10-27), and decreased overall survival (hazard ratio [HR] DiscovEHR, 1.8 [95% CI 1.3-2.6], p = 0.00049; UKBB, 1.4 [95% CI 1.2-1.8], p = 8.4 × 10-5) amongst heterozygotes. Pathogenic DDX41 variants were the most commonly identified, and in UKBB showed a significantly increased risk of MM (OR 5.7 [95% CI 3.9-8.3], p = 6.0 × 10-20) and increased all-cause mortality (HR 1.35 [95% CI 1.1-1.7], p = 0.0063). Through a genome-first approach, this study genetically ascertained individuals with a gMMP and determined their MM risk and survival.

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Conflict of interest statement

Competing interests: The authors declare no conflict of interest. DJ Carey is the principal investigator or co-investigator and draws partial salary support for three studies funded by Regeneron Pharmaceuticals to Geisinger Clinic. One of these supports the enrollment of patients into the MyCode biobank and exome sequencing; the others are studies of individuals with genetic variants associated with clonal hematopoiesis of indeterminate potential and GAA deficiency (Pompe disease). R Hendricks, J Kim, ML Ramos, DR Stewart and LJ McReynolds’ work has been funded by the Intramural Research Program of the National Cancer Institute. JS Haley, UL Mirshahi and DJ Carey’s work is funded by Geisinger Medical Center.

Figures

Fig. 1
Fig. 1. Estimated prevalence of germline myeloid malignancy predisposition genes in DiscovEHR (black) and UKBB (pink).
Absolute number of heterozygotes listed per gene in each cohort above bar. Ratios, 95% confidence intervals and p-values are listed in Supplementary Table S4 and frequencies in Supplementary Table S5.
Fig. 2
Fig. 2. Estimated penetrance for hematological malignancies in heterozygotes of germline pathogenic/likely pathogenic myeloid malignancy predisposition gene variants in DiscovEHR (black) and UKBB (pink) is shown.
Penetrance was estimated as the frequency (percentage) of HM ever recorded in heterozygote individuals in the electronic health record and/or the tumor registry. Absolute number of heterozygotes with a hematological malignancy listed per gene in each cohort above the bar. Below each bar is the number of heterozygotes for each cohort per gene/gene group. Ratios, 95% confidence intervals and p-values are listed in Supplementary Table S4.
Fig. 3
Fig. 3. Risk of hematological and myeloid malignancy development in heterozygotes of germline pathogenic/likely pathogenic myeloid malignancy predisposition gene variants in both cohorts.
The DiscovEHR cohort is shown in A, B and UKBB cohort in C, D. Logistic regression odds ratios (OR) and 95% confidence intervals were adjusted for age, sex, body mass index (BMI) and smoking. For MM in DiscovEHR ETV6 is adjusted for sex, BMI and smoking only. Hem TFs, hematological transcription factors: RUNX1, GATA2, CEBPA, ETV6, MECOM. No MECOM heterozygotes in DiscovEHR had hematological malignancy, and only 1 in UKBB. *p ≤ 0.05; **p ≤ 0.01; ***p ≤ 0.001; and ****p ≤ 0.0001.
Fig. 4
Fig. 4. Kaplan-Meier overall survival of heterozygotes (red) and non-heterozygotes (gray) in DiscovEHR.
Curves for heterozygotes and non-heterozygotes of all genes for all-cause mortality (A), all genes for individuals with hematological malignancy (B), all genes for individuals with a myeloid malignancy (C), DDX41 heterozygotes for all-cause mortality (D) and all-cause mortality for the combined group GATA2, ETV6 and RUNX1 (E). Adjusted Cox proportional hazards and log-rank p-values compared the heterozygote curve to non-heterozygote curve. p < 0.05. HR Hazard ratio, CI Confidence interval.
Fig. 5
Fig. 5
Kaplan-Meier overall survival of heterozygotes (red) and non-heterozygotes (gray) in UKBB. Curves for heterozygotes and non-heterozygotes of all genes for all-cause mortality (A), all genes for individuals with hematological malignancy (B), all genes for individuals with a myeloid malignancy (C), DDX41 heterozygotes for all-cause mortality (D) and all-cause mortality for the combined group GATA2, ETV6 and RUNX1 (E). Adjusted Cox proportional hazards and log-rank p-values compared the heterozygote curve to non-heterozygote curve. p < 0.05. HR hazard ratio, CI confidence interval.
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