Jaime E Hale1, Craig D Platt2, Francisco A Bonilla3, Beverly N Hay4, John L Sullivan5, Alicia M Johnston6, Mark S Pasternack7, Paul E Hesterberg8, H Cody Meissner9, Ellen R Cooper10, Sara Barmettler11, Jocelyn R Farmer11, Donna Fisher12, Jolan E Walter13, Nancy J Yang11, Inderneel Sahai14, Roger B Eaton14, Alfred DeMaria15, Luigi D Notarangelo16, Sung-Yun Pai17, Anne Marie Comeau18. 1. New England Newborn Screening Program, Commonwealth Medicine, University of Massachusetts Medical School, Worcester, Mass. 2. Division of Immunology, Boston Children's Hospital, Boston, Mass; Harvard Medical School, Boston, Mass. 3. Division of Immunology, Boston Children's Hospital, Boston, Mass; Harvard Medical School, Boston, Mass; Northeast Allergy, Asthma & Immunology, Leominster, Mass. 4. Department of Pediatrics, University of Massachusetts Medical School, Worcester, Mass. 5. Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, Mass. 6. Harvard Medical School, Boston, Mass; Division of Infectious Disease, Boston Children's Hospital, Boston, Mass. 7. Harvard Medical School, Boston, Mass; Pediatric Infectious Disease Unit, MassGeneral Hospital for Children, Boston, Mass. 8. Division of Allergy and Immunology, MassGeneral Hospital for Children, Boston, Mass. 9. Department of Pediatrics, Tufts Children's Hospital, Tufts University School of Medicine, Boston, Mass. 10. Division of Pediatric Infectious Diseases, Boston Medical Center, Boston University School of Medicine, Boston, Mass. 11. Division of Rheumatology, Allergy & Immunology, Massachusetts General Hospital, Boston, Mass. 12. Division of Pediatric Infectious Diseases, Baystate Children's Hospital, University of Massachusetts Medical School-Baystate, Springfield, Mass. 13. Division of Allergy and Immunology, MassGeneral Hospital for Children, Boston, Mass; Division of Allergy & Immunology, Department of Pediatrics, University of South Florida at Johns Hopkins All Children's Hospital, St. Petersburg, Fla. 14. New England Newborn Screening Program, Commonwealth Medicine, University of Massachusetts Medical School, Worcester, Mass; Department of Pediatrics, University of Massachusetts Medical School, Worcester, Mass. 15. Bureau of Infectious Disease and Laboratory Sciences, Massachusetts Department of Public Health, Boston, Mass. 16. Laboratory of Clinical Immunology & Microbiology, National Institute of Allergy and Infectious Diseases, Bethesda, Md. 17. Harvard Medical School, Boston, Mass; Division of Hematology-Oncology, Boston Children's Hospital, Harvard Medical School, Boston, Mass; Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, Mass. Electronic address: sung-yun.pai@nih.gov. 18. New England Newborn Screening Program, Commonwealth Medicine, University of Massachusetts Medical School, Worcester, Mass; Department of Pediatrics, University of Massachusetts Medical School, Worcester, Mass. Electronic address: anne.comeau@umassmed.edu.
Abstract
BACKGROUND: Massachusetts began newborn screening (NBS) for severe combined immunodeficiency (SCID) using measurement of T-cell receptor excision circles (TRECs) from dried blood spots. OBJECTIVE: We describe developments and outcomes from the first 10 years of this program (February 1, 2009, to January 31, 2019). METHODS: TREC values, diagnostic, and outcome data from all patients screened for SCID were evaluated. RESULTS: NBS of 720,038 infants prompted immunologic evaluation of 237 (0.03%). Of 237, 9 were diagnosed with SCID/leaky SCID (4% of referrals vs 0.001% general population). Another 7 were diagnosed with other combined immunodeficiencies, and 3 with athymia. SCID/leaky SCID incidence was approximately 1 in 80,000, whereas approximately 1 in 51,000 had severe T-cell lymphopenia for which definitive treatment was indicated. All patients with SCID/leaky SCID underwent hematopoietic cell transplant or gene therapy with 100% survival. One patient with athymia underwent successful thymus transplant. No known cases of SCID were missed. Compared with outcomes from the 10 years before SCID NBS, survival trended higher (9 of 9 vs 4 of 7), likely due to a lower rate of infection before treatment. CONCLUSIONS: Our data support a single NBS testing-and-referral algorithm for all gestational ages. Despite lower median TREC values in premature infants, the majority for all ages are well above the TREC cutoff and the algorithm, which selects urgent (undetectable TREC) and repeatedly abnormal TREC values, minimizes referral. We also found that low naïve T-cell percentage is associated with a higher risk of SCID/CID, demonstrating the utility of memory/naïve T-cell phenotyping as part of follow-up flow cytometry.
BACKGROUND: Massachusetts began newborn screening (NBS) for severe combined immunodeficiency (SCID) using measurement of T-cell receptor excision circles (TRECs) from dried blood spots. OBJECTIVE: We describe developments and outcomes from the first 10 years of this program (February 1, 2009, to January 31, 2019). METHODS: TREC values, diagnostic, and outcome data from all patients screened for SCID were evaluated. RESULTS: NBS of 720,038 infants prompted immunologic evaluation of 237 (0.03%). Of 237, 9 were diagnosed with SCID/leaky SCID (4% of referrals vs 0.001% general population). Another 7 were diagnosed with other combined immunodeficiencies, and 3 with athymia. SCID/leaky SCID incidence was approximately 1 in 80,000, whereas approximately 1 in 51,000 had severe T-cell lymphopenia for which definitive treatment was indicated. All patients with SCID/leaky SCID underwent hematopoietic cell transplant or gene therapy with 100% survival. One patient with athymia underwent successful thymus transplant. No known cases of SCID were missed. Compared with outcomes from the 10 years before SCID NBS, survival trended higher (9 of 9 vs 4 of 7), likely due to a lower rate of infection before treatment. CONCLUSIONS: Our data support a single NBS testing-and-referral algorithm for all gestational ages. Despite lower median TREC values in premature infants, the majority for all ages are well above the TREC cutoff and the algorithm, which selects urgent (undetectable TREC) and repeatedly abnormal TREC values, minimizes referral. We also found that low naïve T-cell percentage is associated with a higher risk of SCID/CID, demonstrating the utility of memory/naïve T-cell phenotyping as part of follow-up flow cytometry.
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