University of Oulu

Lamichhane, S. et al. A longitudinal plasma lipidomics dataset from children who developed islet autoimmunity and type 1 diabetes. Sci. Data. 5:180250 doi: 10.1038/sdata.2018.250 (2018).

A longitudinal plasma lipidomics dataset from children who developed islet autoimmunity and type 1 diabetes

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Author: Lamichhane, Santosh1; Ahonen, Linda2; Dyrlund, Thomas Sparholt2;
Organizations: 1Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Turku 20520, Finland
2Steno Diabetes Center Copenhagen, 2820 Gentofte, Denmark
3Children’s Hospital, University of Helsinki and Helsinki University Hospital, 00290 Helsinki, Finland
4Research Program Unit, Diabetes and Obesity, University of Helsinki, 00290 Helsinki, Finland
55Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
6Fimlab Laboratories, Pirkanmaa Hospital District, Tampere, Finland.
7Immunogenetics Laboratory, Institute of Biomedicine, University of Turku, Turku, Finland
8Clinical Microbiology, Turku University Hospital, Turku, Finland
9Institute of Biomedicine, Centre for Integrative Physiology and Pharmacology, University of Turku, Turku, Finland
10Department of Pediatrics, Turku University Hospital, Turku, Finland
11Department of Paediatrics, PEDEGO Research Unit, Medical Research Centre, University of Oulu, Oulu, Finland
12Department of Children and Adolescents, Oulu University Hospital, Oulu, Finland
13Department of Women’s and Children’s Health, Karolinska Institutet, Stockholm, Sweden
14Department of Chemistry, Örebro University, 702 81 Örebro, Sweden
15Tampere Center for Child Health Research, Tampere University Hospital, Tampere, Finland
16Folkhälsan Research Center, Helsinki, Finland
17School of Medical Sciences, Örebro University, 702 81 Örebro, Sweden
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 0.8 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2019062621969
Language: English
Published: Springer Nature, 2018
Publish Date: 2019-06-26
Description:

Abstract

Early prediction and prevention of type 1 diabetes (T1D) are currently unmet medical needs. Previous metabolomics studies suggest that children who develop T1D are characterised by a distinct metabolic profile already detectable during infancy, prior to the onset of islet autoimmunity. However, the specificity of persistent metabolic disturbances in relation T1D development has not yet been established. Here, we report a longitudinal plasma lipidomics dataset from (1) 40 children who progressed to T1D during follow-up, (2) 40 children who developed single islet autoantibody but did not develop T1D and (3) 40 matched controls (6 time points: 3, 6, 12, 18, 24 and 36 months of age). This dataset may help other researchers in studying age-dependent progression of islet autoimmunity and T1D as well as of the age-dependence of lipidomic profiles in general. Alternatively, this dataset could more broadly used for the development of methods for the analysis of longitudinal multivariate data.

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Series: Scientific data
ISSN: 2052-4463
ISSN-E: 2052-4463
ISSN-L: 2052-4463
Volume: 5
Article number: 180250
DOI: 10.1038/sdata.2018.250
OADOI: https://oadoi.org/10.1038/sdata.2018.250
Type of Publication: A1 Journal article – refereed
Field of Science: 3121 General medicine, internal medicine and other clinical medicine
Subjects:
Funding: This work was supported by the JDRF grants 4-1998-274, 4-1999-731 4-2001-435 and special research funds for Oulu, Tampere and Turku University Hospitals in Finland. This work was supported by the Juvenile Diabetes Research Foundation (2-SRA-2014-159-Q-R to M.O.) and the Academy of Finland (Centre of Excellence in Molecular Systems Immunology and Physiology Research – SyMMyS, Decision No. 250114, to M.O. and M.K.).
Copyright information: © The Author(s) 2018. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
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