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Longitudinal Metabolome-Wide Signals Prior to the Appearance of a First Islet Autoantibody in Children Participating in the TEDDY Study

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Longitudinal Metabolome-Wide Signals Prior to the Appearance of a First Islet Autoantibody in Children Participating in the TEDDY Study Diabetes 1 Longitudinal Metabolome-Wide Signals Prior to the Appearance of a First Islet Autoantibody in Children Participating in the TEDDY Study Qian Li,1 Hemang Parikh,1 Martha D. Butterworth,1 Åke Lernmark,2 William Hagopian,3 Marian Rewers,4 Jin-Xiong She,5 Jorma Toppari,6,7 Anette-G. Ziegler,8,9,10 Beena Akolkar,11 Oliver Fiehn,12 Sili Fan,12 and Jeffrey P. Krischer,1 the TEDDY Study Group* https://doi.org/10.2337/db19-0756 GENETICS/GENOMES/PROTEOMICS/METABOLOMICS Children at increased genetic risk for type 1 diabetes suggest that IAA-first and GADA-first are heralded by (T1D) after environmental exposures may develop pan- different patterns of DHAA, GABA, multiple amino acids, creatic islet autoantibodies (IA) at a very young age. and fatty acids, which may be important to primary pre- Metabolic profile changes over time may imply responses vention of T1D. to exposures and signal development of the first IA. Our present research in The Environmental Determinants of Diabetes in the Young (TEDDY) study aimed to identify Primary metabolites and complex lipid concentrations in fi metabolome-wide signals preceding the rst IA against children’s blood may reflect genetic and environmental GAD (GADA-first) or against insulin (IAA-first). We profiled exposure variations that contribute to the development of metabolomes by mass spectrometry from children’s diseases. Research of the prodrome to type 1 diabetes plasma at 3-month intervals after birth until appear- (T1D) has indicated a strong association of the metabo- ance of the first IA. A trajectory analysis discovered each first IA preceded by reduced amino acid proline and lome or lipidome in healthy infants who later developed branched-chain amino acids (BCAAs), respectively. With pancreatic islet autoantibodies (IA) as markers of islet – fi independent time point analysis following birth, we dis- autoimmunity and progressed to T1D (1 3). In a rst covered dehydroascorbic acid (DHAA) contributing to investigation, the appearance of autoantibodies against the risk of each first IA, and g-aminobutyric acid (GABAs) insulin (IAA) and GAD (GADA) was preceded by dimin- associated with the first autoantibody against insulin ished ketoleucine and elevated glutamic acid (4). Subse- (IAA-first). Methionine and alanine, compounds pro- quently, it was reported that, in children born to a father duced in BCAA metabolism and fatty acids, also pre- or a mother with T1D, autoantibody-positive children had ceded IA at different time points. Unsaturated triglycerides higher levels of odd-chain triglycerides (TGs) and poly- and phosphatidylethanolamines decreased in abundance unsaturated fatty acid–containing phospholipids at first before appearance of either autoantibody. Our findings autoantibody appearance than autoantibody-negative children 1Health Informatics Institute, Morsani College of Medicine, University of South 11National Institute of Diabetes and Digestive and Kidney Diseases, National Florida, Tampa, FL Institutes of Health, Bethesda, MD 2Department of Clinical Sciences, Lund University/CRC, Skåne University Hospital 12Genome Center, University of California, Davis, Davis, CA SUS, Malmo, Sweden Corresponding authors: Qian Li, [email protected], and Jeffrey P. Krischer, 3 fi Paci c Northwest Diabetes Research Institute, Seattle, WA [email protected] 4Barbara Davis Center for Childhood Diabetes, University of Colorado Denver, Received 7 August 2019 and accepted 5 December 2019 Aurora, CO 5Center for Biotechnology and Genomic Medicine, Medical College of Georgia, This article contains Supplementary Data online at http://diabetes Augusta University, Augusta, GA .diabetesjournals.org/lookup/suppl/doi:10.2337/db19-0756/-/DC1. 6 Department of Pediatrics, Turku University Hospital, Turku, Finland *Members of the TEDDY Study Group are listed in the APPENDIX. 7Research Centre for Integrative Physiology and Pharmacology, Institute of Bio- © 2020 by the American Diabetes Association. Readers may use this article as medicine, University of Turku, Turku, Finland long as the work is properly cited, the use is educational and not for profit, and the 8Institute of Diabetes Research, Helmholtz Zentrum München, Munich, Germany work is not altered. More information is available at http://www.diabetesjournals 9Forschergruppe Diabetes, Technical University of Munich, Klinikum Rechts der .org/content/license. Isar, Munich, Germany 10Forschergruppe Diabetes e.V. at Helmholtz Zentrum München, Munich, Germany Diabetes Publish Ahead of Print, published online February 6, 2020 2 Metabolome-Wide Signals for Islet Autoimmunity Diabetes (5). Children who had a first-degree relative with T1D and In addition to identifying predictive trajectories and bio- developed autoantibodies by 2 years of age also had two- markers, we performed metabolite set enrichment analysis fold lower levels of methionine compared with those who based on time points at infancy to show metabolites and developed autoantibodies in later childhood or remained lipid clusters enriched for the compounds potentially autoantibody negative (1,5,6). However, the studies ref- associated with IA risk. erenced above mostly identified biomarkers for IA and T1D based either on longitudinal blood samples at and after RESEARCH DESIGN AND METHODS seroconversion (5) or on samples at only one time point Mass Spectrum Profiling of Longitudinal Plasma prior to seroconversion (4). The study in 3 used longitu- Samples dinal metabolome in plasma prior to IA only for the The TEDDY study enrolled 8,676 children based on HLA- children with two or three autoantibodies, without con- DR-DQ haplogenotypes for the risk of T1D in a prospective sidering the subtypes of first-appearing IA. For prediction cohort. Blood sample collection for participants in TEDDY of IA for the use of primary prevention therapy, it is critical began at the 3 months of age visit and continued at a 3-month to analyze the preseroconversion metabolome in longitu- interval up to development of IA before 4 years of age dinal samples after birth, as well as to compare metabolic (7,18), although most subjects have randomly missing patterns preceding IA between different first-appearing visits. If a subject develops persistent IA, they continue autoantibodies. on the 3-month interval schedule up to the age of 15 years; The Environmental Determinants of Diabetes in the otherwise, they switch to a 6-month interval schedule. The Young (TEDDY) is a multicenter prospective cohort study metabolomes of the TEDDY first nested case-control to identify environmental factors that trigger or protect (NCC) cohort (19,20) subjects for IA were profiled from against the development of islet autoimmunity and T1D. 10,522 plasma samples. Characteristics of the study pop- The first end point is the appearance of a first IA such as ulation and distribution of plasma samples in the TEDDY IAA, GADA, IA-2A, or zinc transporter 8 (ZnT8)A. The NCC cohort have previously been described (9). second end point is the clinical onset of diabetes (7,8). The The primary metabolite assay in TEDDY was profiled by end point for IA is the first persistent confirmed autoan- GC-TOF MS on a LECO Pegasus III instrument, annotated tibody, defined as one autoantibody confirmed on two or by BinBase (21). The complex lipid assay was analyzed by more consecutive samples (9). The first persistent con- charged-surface hybrid column with electrospray ioniza- firmed, i.e., first-appearing autoantibodies, can be one or tion (CSH-ESI) on Agilent ultrahigh-pressure LC-QTOF MS a combination of GADA, IAA, and IA-2A. IAA as the first- instruments, annotated with LipidBlast (22). Peaks from appearing autoantibody (IAA-first) was associated with GC-TOF MS platform were automatically detected HLA DR4-DQ8 and a peak of IAA incidence rate at 1–2 and deconvoluted from coeluting peaks by the LECO years of age, while GADA as the first-appearing IA (GADA- ChromaTOF (23) software (v3.0). Raw data output from first) tended to occur in children with DR3-DQ2 and CSH-ESI-QTOF instruments were processed in an untar- displayed a later incidence peak (10). Furthermore, IAA- geted (qualitative) manner by Agilent software (24) Mass- first was related to the INS gene polymorphism, while Hunter Qual (v. B.05.00) to find peaks. Peak features are GADA-first was related to polymorphisms in the ERBB3, then imported into Mass Profiler Professional for peak SH2B3, and BACH2 gene polymorphisms (10). Probiotics alignments to seek which peaks are present in multiple before 28 days of age reduced the risk for IAA-first but not chromatograms. These peaks are then collated and con- GADA-first (11). Hence, we aimed to investigate whether strained within the MassHunter quantification software longitudinal metabolome profiles of TEDDY subjects show (v. B.05.01) on the accurate mass precursor ion level, using similar patterns associated with the risk of different first- the MS information and the LipidBlast library. The TEDDY appearing autoantibodies. The current study used mass Data Coordinating Center applied a comprehensive nor- spectrometry (MS) with gas chromatography time-of-flight malization pipeline, systematic error removal using ran- (GC-TOF MS) and liquid chromatography quadrupole time dom forest (SERRF) (25), to the raw quantified intensity of of flight (LC-QTOF MS) to analyze nested case-control primary metabolites and complex lipids and successfully TEDDY plasma samples at the West Coast Metabolomics removed laboratory running order effects. The GC-TOF Center, University of California, Davis. normalized data
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