Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

CHRONIC MYELOPROLIFERATIVE NEOPLASMS

Recurrent germline variant in ATM associated with familial myeloproliferative neoplasms

Leukemia volume 37, pages 627–635 (2023)Cite this article

Subjects

Abstract

Genetic predisposition (familial risk) in the myeloproliferative neoplasms (MPNs) is more common than the risk observed in most other cancers, including breast, prostate, and colon. Up to 10% of MPNs are considered to be familial. Recent genome-wide association studies have identified genomic loci associated with an MPN diagnosis. However, the identification of variants with functional contributions to the development of MPN remains limited. In this study, we have included 630 MPN patients and whole genome sequencing was performed in 64 individuals with familial MPN to uncover recurrent germline predisposition variants. Both targeted and unbiased filtering of single nucleotide variants (SNVs) was performed, with a comparison to 218 individuals with MPN unselected for familial status. This approach identified an ATM L2307F SNV occurring in nearly 8% of individuals with familial MPN. Structural protein modeling of this variant suggested stabilization of inactive ATM dimer, and alteration of the endogenous ATM locus in a human myeloid cell line resulted in decreased phosphorylation of the downstream tumor suppressor CHEK2. These results implicate ATM, and the DNA-damage response pathway, in predisposition to MPN.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Molecular and clinical characteristics of the familial and unselected MPN cohorts.
Fig. 2: The filtering strategies and germline variants identified in the unbiased approach.
Fig. 3: In silico prediction of the effect of Leucine to Phenylalanine substitution in the position 2307 on ATM function.
Fig. 4: The effect of ATM L2307F on ATM and CHEK2 phosphorylation at steady state and after ionizing radiation.

Similar content being viewed by others

Data availability

All data generated or analyzed during this study are either included in this published paper and its supplementary materials or will be made available upon request.

References

  1. Landgren O, Goldin LR, Kristinsson SY, Helgadottir EA, Samuelsson J, Björkholm M. Increased risks of polycythemia vera, essential thrombocythemia, and myelofibrosis among 24,577 first-degree relatives of 11,039 patients with myeloproliferative neoplasms in Sweden. Blood. 2008;112:2199–204.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Rumi E, Passamonti F, Della Porta MG, Elena C, Arcaini L, Vanelli L, et al. Familial chronic myeloproliferative disorders: clinical phenotype and evidence of disease anticipation. JCO. 2007;25:5630–5.

    Article  Google Scholar 

  3. Sud A, Chattopadhyay S, Thomsen H, Sundquist K, Sundquist J, Houlston RS, et al. Familial risks of acute myeloid leukemia, myelodysplastic syndromes, and myeloproliferative neoplasms. Blood. 2018;132:973–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Godley LA. Germline mutations in MDS/AML predisposition disorders. Curr Opin Hematol. 2021;28:86–93.

    Article  CAS  PubMed  Google Scholar 

  5. Furutani E, Shimamura A. Genetic predisposition to MDS: diagnosis and management. Hematology. 2019;2019:110–9.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Jones AV, Cross NCP. Inherited predisposition to myeloproliferative neoplasms. Therapeutic Adv Hematol. 2013;4:237–53.

    Article  CAS  Google Scholar 

  7. Harutyunyan AS, Giambruno R, Krendl C, Stukalov A, Klampfl T, Berg T, et al. Germline RBBP6 mutations in familial myeloproliferative neoplasms. Blood. 2016;127:362–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Babushok DV, Stanley NL, Morrissette JJD, Lieberman DB, Olson TS, Chou ST, et al. Germline duplication of ATG2B and GSKIP genes is not required for the familial myeloid malignancy syndrome associated with the duplication of chromosome 14q32. Leukemia. 2018;32:2720–3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Saliba J, Saint-Martin C, Di Stefano A, Lenglet G, Marty C, Keren B, et al. Germline duplication of ATG2B and GSKIP predisposes to familial myeloid malignancies. Nat Genet. 2015;47:1131–40.

    Article  CAS  PubMed  Google Scholar 

  10. Jones AV, Chase A, Silver RT, Oscier D, Zoi K, Wang YL, et al. JAK2 haplotype is a major risk factor for the development of myeloproliferative neoplasms. Nat Genet. 2009;41:446–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Kilpivaara O, Mukherjee S, Schram AM, Wadleigh M, Mullally A, Ebert BL, et al. A germline JAK2 SNP is associated with predisposition to the development of JAK2V617F-positive myeloproliferative neoplasms. Nat Genet. 2009;41:455–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Olcaydu D, Harutyunyan A, Jäger R, Berg T, Gisslinger B, Pabinger I, et al. A common JAK2 haplotype confers susceptibility to myeloproliferative neoplasms. Nat Genet. 2009;41:450–4.

    Article  CAS  PubMed  Google Scholar 

  13. Hinds DA, Barnholt KE, Mesa RA, Kiefer AK, Do CB, Eriksson N, et al. Germ line variants predispose to both JAK2 V617F clonal hematopoiesis and myeloproliferative neoplasms. Blood. 2016;128:1121–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Oddsson A, Kristinsson SY, Helgason H, Gudbjartsson DF, Masson G, Sigurdsson A, et al. The germline sequence variant rs2736100_C in TERT associates with myeloproliferative neoplasms. Leukemia. 2014;28:1371–4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Tapper W, Jones AV, Kralovics R, Harutyunyan AS, Zoi K, Leung W, et al. Genetic variation at MECOM, TERT, JAK2 and HBS1L-MYB predisposes to myeloproliferative neoplasms. Nat Commun. 2015;6:6691.

    Article  CAS  PubMed  Google Scholar 

  16. Bao EL, Nandakumar SK, Liao X, Bick AG, Karjalainen J, Tabaka M, et al. Inherited myeloproliferative neoplasm risk affects haematopoietic stem cells. Nature. 2020;586:769–75.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Bick AG, Weinstock JS, Nandakumar SK, Fulco CP, Bao EL, Zekavat SM, et al. Inherited causes of clonal haematopoiesis in 97,691 whole genomes. Nature. 2020;586:763–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Jaiswal S, Fontanillas P, Flannick J, Manning A, Grauman PV, Mar BG, et al. Age-related clonal hematopoiesis associated with adverse outcomes. N. Engl J Med. 2014;371:2488–98.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Xie M, Lu C, Wang J, McLellan MD, Johnson KJ, Wendl MC, et al. Age-related mutations associated with clonal hematopoietic expansion and malignancies. Nat Med. 2014;20:1472–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Genovese G, Kähler AK, Handsaker RE, Lindberg J, Rose SA, Bakhoum SF, et al. Clonal hematopoiesis and blood-cancer risk inferred from blood DNA sequence. N. Engl J Med. 2014;371:2477–87.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Karantanos T, Chaturvedi S, Braunstein EM, Spivak J, Resar L, Karanika S, et al. Sex determines the presentation and outcomes in MPN and is related to sex-specific differences in the mutational burden. Blood Adv. 2020;4:2567–76.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Stein BL, Saraf S, Sobol U, Halpern A, Shammo J, Rondelli D, et al. Age-related differences in disease characteristics and clinical outcomes in polycythemia vera. Leuk Lymphoma. 2013;54:1989–95.

    Article  CAS  PubMed  Google Scholar 

  23. Arber DA. The 2016 WHO classification of acute myeloid leukemia: What the practicing clinician needs to know. Semin Hematol. 2019;56:90–5.

    Article  PubMed  Google Scholar 

  24. Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 2015;17:405–24.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Benjamin D, Sato T, Cibulskis K, Getz G, Stewart C, Lichtenstein L. Calling somatic SNVs and indels with mutect2. Bioinformatics. 2019. https://doi.org/10.1101/861054.

    Article  Google Scholar 

  26. PCAWG Mutational Signatures Working Group, PCAWG Consortium, Alexandrov LB, Kim J, Haradhvala NJ, Huang MN, et al. The repertoire of mutational signatures in human cancer. Nature. 2020;578:94–101.

    Article  Google Scholar 

  27. Putnam DK, Ma X, Rice SV, Liu Y, Newman S, Zhang J, et al. VCF2CNA: a tool for efficiently detecting copy-number alterations in VCF genotype data and tumor purity. Sci Rep. 2019;9:10357.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Chen X, Schulz-Trieglaff O, Shaw R, Barnes B, Schlesinger F, Källberg M, et al. Manta: rapid detection of structural variants and indels for germline and cancer sequencing applications. Bioinformatics. 2016;32:1220–2.

    Article  CAS  PubMed  Google Scholar 

  29. Geoffroy V, Herenger Y, Kress A, Stoetzel C, Piton A, Dollfus H, et al. AnnotSV: an integrated tool for structural variations annotation. Bioinformatics. 2018;34:3572–4.

    Article  CAS  PubMed  Google Scholar 

  30. Schrödinger L. The PyMOL molecular graphics system, Version 1.3r1.

  31. Jumper J, Evans R, Pritzel A, Green T, Figurnov M, Ronneberger O, et al. Highly accurate protein structure prediction with AlphaFold. Nature. 2021;596:583–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Mirdita M, Schütze K, Moriwaki Y, Heo L, Ovchinnikov S, Steinegger M. ColabFold: making protein folding accessible to all. Nat Methods. 2022;19:679–82.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Yang J, Yan R, Roy A, Xu D, Poisson J, Zhang Y. The I-TASSER Suite: protein structure and function prediction. Nat Methods. 2015;12:7–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Roy A, Kucukural A, Zhang Y. I-TASSER: a unified platform for automated protein structure and function prediction. Nat Protoc. 2010;5:725–38.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Baretić D, Pollard HK, Fisher DI, Johnson CM, Santhanam B, Truman CM, et al. Structures of closed and open conformations of dimeric human ATM. Sci Adv. 2017;3:e1700933.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, et al. The protein data bank. Nucleic Acids Res. 2000;28:235–42.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Huang X, Zheng W, Pearce R, Zhang Y. SSIPe: accurately estimating protein-protein binding affinity change upon mutations using evolutionary profiles in combination with an optimized physical energy function. Bioinformatics. 2020;36:2429–37.

    Article  CAS  PubMed  Google Scholar 

  38. Huang X, Pearce R, Zhang Y. EvoEF2: accurate and fast energy function for computational protein design. Bioinformatics. 2020;36:1135–42.

    Article  CAS  PubMed  Google Scholar 

  39. Lyskov S, Chou F-C, Conchúir SÓ, Der BS, Drew K, Kuroda D, et al. Serverification of molecular modeling applications: The Rosetta online server that includes everyone (ROSIE). PLoS ONE. 2013;8:e63906.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Chaudhury S, Berrondo M, Weitzner BD, Muthu P, Bergman H, Gray JJ. Benchmarking and analysis of protein docking performance in Rosetta v3.2. PLoS One. 2011;6:e22477.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Komrokji RS, Verstovsek S, Padron E, List AF. Advances in the management of myelofibrosis. Cancer Control. 2012;19:4–15.

    Article  PubMed  Google Scholar 

  42. Vainchenker W, Kralovics R. Genetic basis and molecular pathophysiology of classical myeloproliferative neoplasms. Blood. 2017;129:667–79.

    Article  CAS  PubMed  Google Scholar 

  43. Mercher T, Wernig G, Moore SA, Levine RL, Gu T-L, Fröhling S, et al. JAK2T875N is a novel activating mutation that results in myeloproliferative disease with features of megakaryoblastic leukemia in a murine bone marrow transplantation model. Blood. 2006;108:2770–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Yoshimitsu M, Hachiman M, Uchida Y, Arima N, Arai A, Kamada Y, et al. Essential thrombocytosis attributed to JAK2-T875N germline mutation. Int J Hematol. 2019;110:584–90.

    Article  CAS  PubMed  Google Scholar 

  45. Karlsson Q, Brook MN, Dadaev T, Wakerell S, Saunders EJ, Muir K, et al. Rare germline variants in ATM predispose to prostate cancer: a PRACTICAL Consortium Study. Eur Urol Oncol. 2021;4:570–9.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Shindo K, Yu J, Suenaga M, Fesharakizadeh S, Cho C, Macgregor-Das A, et al. Deleterious germline mutations in patients with apparently sporadic pancreatic adenocarcinoma. JCO. 2017;35:3382–90.

    Article  CAS  Google Scholar 

  47. Aoude LG, Bonazzi VF, Brosda S, Patel K, Koufariotis LT, Oey H, et al. Pathogenic germline variants are associated with poor survival in stage III/IV melanoma patients. Sci Rep. 2020;10:17687.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Kar SP, Quiros PM, Gu M, Jiang T, Mitchell J, Langdon R, et al. Genome-wide analyses of 200,453 individuals yield new insights into the causes and consequences of clonal hematopoiesis. Nat Genet. 2022;54:1155–66.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Yang F, Long N, Anekpuritanang T, Bottomly D, Savage JC, Lee T, et al. Identification and prioritization of myeloid malignancy germline variants in a large cohort of adult patients with AML. Blood. 2022;139:1208–21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Tiao G, Improgo MR, Kasar S, Poh W, Kamburov A, Landau D-A, et al. Rare germline variants in ATM are associated with chronic lymphocytic leukemia. Leukemia. 2017;31:2244–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Samaraweera SE, Wang PPS, Li KL, Casolari DA, Feng J, Pinese M, et al. Childhood acute myeloid leukemia shows a high level of germline predisposition. Blood. 2021;138:2293–8.

    Article  CAS  PubMed  Google Scholar 

  52. Elbracht M, Meyer R, Kricheldorf K, Gezer D, Thomas E, Betz B, et al. Germline variants in DNA repair genes, including BRCA1/2, may cause familial myeloproliferative neoplasms. Blood Adv. 2021;5:3373–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Pratz KW, Koh BD, Patel AG, Flatten KS, Poh W, Herman JG, et al. Poly (ADP-Ribose) polymerase inhibitor hypersensitivity in aggressive myeloproliferative neoplasms. Clin Cancer Res. 2016;22:3894–902.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Plo I, Nakatake M, Malivert L, de Villartay J-P, Giraudier S, Villeval J-L, et al. JAK2 stimulates homologous recombination and genetic instability: potential implication in the heterogeneity of myeloproliferative disorders. Blood. 2008;112:1402–12.

    Article  CAS  PubMed  Google Scholar 

  55. Chen E, Ahn JS, Sykes DB, Breyfogle LJ, Godfrey AL, Nangalia J, et al. RECQL5 suppresses oncogenic JAK2-induced replication stress and genomic instability. Cell Rep. 2015;13:2345–52.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Patel PR, Senyuk V, Rodriguez NS, Oh AL, Bonetti E, Mahmud D, et al. Synergistic cytotoxic effect of busulfan and the PARP inhibitor veliparib in myeloproliferative neoplasms. Biol Blood Marrow Transplant. 2019;25:855–60.

    Article  CAS  PubMed  Google Scholar 

  57. Tong AS, Stern JL, Sfeir A, Kartawinata M, de Lange T, Zhu X-D, et al. ATM and ATR signaling regulate the recruitment of human telomerase to telomeres. Cell Rep. 2015;13:1633–46.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Tresini M, Warmerdam DO, Kolovos P, Snijder L, Vrouwe MG, Demmers JAA, et al. The core spliceosome as target and effector of non-canonical ATM signalling. Nature. 2015;523:53–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Lee J-H, Mand MR, Kao C-H, Zhou Y, Ryu SW, Richards AL, et al. ATM directs DNA damage responses and proteostasis via genetically separable pathways. Sci Signal. 2018;11:eaan5598.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Ito K, Hirao A, Arai F, Matsuoka S, Takubo K, Hamaguchi I, et al. Regulation of oxidative stress by ATM is required for self-renewal of haematopoietic stem cells. Nature. 2004;431:997–1002.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Institutes of Health (NIH), Heart, Lung and Blood Institute grant K08HL138142 (EMB), K08HL136894 (LPG), R01HL156144 (LPG), and in part by the Intramural Research Program of the National Heart, Lung, and Blood Institute of the National Institutes of Health (JG and CSH).

Author information

Authors and Affiliations

  1. Division of Hematological Malignancies, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA

    Evan M. Braunstein, Sergiu Pasca, Shiyu Wang & Lukasz P. Gondek

  2. Division of Hematology, Department of Medicine, Johns Hopkins Hospital, Baltimore, MD, USA

    Evan M. Braunstein, Hang Chen & Alison Moliterno

  3. Division of Computational and Systems Pathology, Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA

    Eddie Imada & Luigi Marchionni

  4. Committee on Genetics, Genomics and Systems Biology, Biological Sciences Division, University of Chicago, Chicago, IL, USA

    Hang Chen

  5. Henry Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA

    Camille Alba & Dan N. Hupalo

  6. The American Genome Center, Uniformed Services University of the Health Sciences, Bethesda, MD, USA

    Camille Alba & Clifton L. Dalgard

  7. Department of Anatomy Physiology & Genetics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA

    Matthew Wilkerson & Clifton L. Dalgard

  8. Laboratory of Myeloid Malignancies, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA

    Jack Ghannam & Christopher S. Hourigan

  9. Department of Biochemistry and Molecular Biology, Biological Sciences Division, University of Chicago, Chicago, IL, USA

    Yujia Liu

Authors
  1. Evan M. Braunstein
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Eddie Imada
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sergiu Pasca
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Shiyu Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Hang Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Camille Alba
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Dan N. Hupalo
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Matthew Wilkerson
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Clifton L. Dalgard
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Jack Ghannam
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Yujia Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Luigi Marchionni
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Alison Moliterno
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Christopher S. Hourigan
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Lukasz P. Gondek
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

AM, EMB and LPG identified and prepared biospecimens, and collected and annotated clinical data; CA, DH, MW, CLD, JG performed whole genome sequencing; EI and LM processed, analyzed, and interpreted WGS data; SP analyzed and interpreted clinical and sequencing data, performed genomic analysis, wrote and edited the manuscript; SW performed cell culture experiments and interpreted results; HC analyzed and interpreted sequencing data and performed protein modeling experiments; YL designed and performed protein modeling experiments; EMB and LPG supervised the experiments, interpreted the data, wrote and revised the manuscript; EMB, LPG, CH designed and funded the study. All authors critically reviewed the manuscript and approved the final version.

Corresponding author

Correspondence to Lukasz P. Gondek.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Braunstein, E.M., Imada, E., Pasca, S. et al. Recurrent germline variant in ATM associated with familial myeloproliferative neoplasms. Leukemia 37, 627–635 (2023). https://doi.org/10.1038/s41375-022-01797-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41375-022-01797-6

Search

Advanced search

Quick links