Distinct transcriptomic profiles in children prior to the appearance of type 1 diabetes-linked islet autoantibodies and following enterovirus infection

The TEDDY Study Group, Jake Lin, Elaheh Moradi, Karoliina Salenius, Suvi Lehtipuro, Tomi Häkkinen, Jutta E. Laiho, Sami Oikarinen, Sofia Randelin, Hemang M. Parikh, Jeffrey P. Krischer, Jorma Toppari, Åke Lernmark, Joseph F. Petrosino, Nadim J. Ajami, Jin-Xiong She, William A. Hagopian, Marian J. Rewers, Richard E. Lloyd, Kirsi J. RautajokiHeikki Hyöty, Matti Nykter

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Although the genetic basis and pathogenesis of type 1 diabetes have been studied extensively, how host responses to environmental factors might contribute to autoantibody development remains largely unknown. Here, we use longitudinal blood transcriptome sequencing data to characterize host responses in children within 12 months prior to the appearance of type 1 diabetes-linked islet autoantibodies, as well as matched control children. We report that children who present with insulin-specific autoantibodies first have distinct transcriptional profiles from those who develop GADA autoantibodies first. In particular, gene dosage-driven expression of GSTM1 is associated with GADA autoantibody positivity. Moreover, compared with controls, we observe increased monocyte and decreased B cell proportions 9-12 months prior to autoantibody positivity, especially in children who developed antibodies against insulin first. Lastly, we show that control children present transcriptional signatures consistent with robust immune responses to enterovirus infection, whereas children who later developed islet autoimmunity do not. These findings highlight distinct immune-related transcriptomic differences between case and control children prior to case progression to islet autoimmunity and uncover deficient antiviral response in children who later develop islet autoimmunity.

Original languageEnglish
Article number7630
JournalNature Communications
Volume14
Issue number1
Number of pages13
ISSN2041-1723
DOIs
Publication statusPublished - 22 Nov 2023
MoE publication typeA1 Journal article-refereed

Fields of Science

  • 318 Medical biotechnology
  • 112 Statistics and probability

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