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Lamichhane, S., Ahonen, L., Dyrlund, T. S., Dickens, A. M., Siljander, H., Hyöty, H., . . . Oresic, M. (2019). Cord-Blood Lipidome in Progression to Islet Autoimmunity and Type 1 Diabetes. Biomolecules, 9(1), Article ID E33.
Open this publication in new window or tab >>Cord-Blood Lipidome in Progression to Islet Autoimmunity and Type 1 Diabetes
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2019 (English)In: Biomolecules, E-ISSN 2218-273X, Vol. 9, no 1, article id E33Article in journal (Refereed) Published
Abstract [en]

Previous studies suggest that children who progress to type 1 diabetes (T1D) later in life already have an altered serum lipid molecular profile at birth. Here, we compared cord blood lipidome across the three study groups: children who progressed to T1D (PT1D; n = 30), children who developed at least one islet autoantibody but did not progress to T1D during the follow-up (P1Ab; n = 33), and their age-matched controls (CTR; n = 38). We found that phospholipids, specifically sphingomyelins, were lower in T1D progressors when compared to P1Ab and the CTR. Cholesterol esters remained higher in PT1D when compared to other groups. A signature comprising five lipids was predictive of the risk of progression to T1D, with an area under the receiver operating characteristic curve (AUROC) of 0.83. Our findings provide further evidence that the lipidomic profiles of newborn infants who progress to T1D later in life are different from lipidomic profiles in P1Ab and CTR.

Place, publisher, year, edition, pages
MDPI, 2019
Keywords
Autoimmunity, cord blood, lipidomics, metabolomics, type 1 diabetes
National Category
Endocrinology and Diabetes
Identifiers
urn:nbn:se:oru:diva-71853 (URN)10.3390/biom9010033 (DOI)000458051700033 ()30669674 (PubMedID)2-s2.0-85060365305 (Scopus ID)
Note

Funding Agencies:

JDRF  4-1998-274  4-1999-731 4-2001-435 

Special research funds for Oulu, Tampere and Turku University Hospitals in Finland  

Juvenile Diabetes Research Foundation  2-SRA-2014-159-Q-R 

Academy of Finland (Centre of Excellence in Molecular Systems Immunology and Physiology Research-SyMMyS)  250114 

Available from: 2019-02-12 Created: 2019-02-12 Last updated: 2019-06-19Bibliographically approved
Hernández-Alvarez, M. I., Sebastián, D., Vives, S., Ivanova, S., Bartoccioni, P., Kakimoto, P., . . . Zorzano, A. (2019). Deficient Endoplasmic Reticulum-Mitochondrial Phosphatidylserine Transfer Causes Liver Disease. Cell, 177(4), 881-895.e17
Open this publication in new window or tab >>Deficient Endoplasmic Reticulum-Mitochondrial Phosphatidylserine Transfer Causes Liver Disease
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2019 (English)In: Cell, ISSN 0092-8674, E-ISSN 1097-4172, Vol. 177, no 4, p. 881-895.e17Article in journal (Refereed) Published
Abstract [en]

Non-alcoholic fatty liver is the most common liver disease worldwide. Here, we show that the mitochondrial protein mitofusin 2 (Mfn2) protects against liver disease. Reduced Mfn2 expression was detected in liver biopsies from patients with non-alcoholic steatohepatitis (NASH). Moreover, reduced Mfn2 levels were detected in mouse models of steatosis or NASH, and its re-expression in a NASH mouse model ameliorated the disease. Liver-specific ablation of Mfn2 in mice provoked inflammation, triglyceride accumulation, fibrosis, and liver cancer. We demonstrate that Mfn2 binds phosphatidylserine (PS) and can specifically extract PS into membrane domains, favoring PS transfer to mitochondria and mitochondrial phosphatidylethanolamine (PE) synthesis. Consequently, hepatic Mfn2 deficiency reduces PS transfer and phospholipid synthesis, leading to endoplasmic reticulum (ER) stress and the development of a NASH-like phenotype and liver cancer. Ablation of Mfn2 in liver reveals that disruption of ER-mitochondrial PS transfer is a new mechanism involved in the development of liver disease.

Place, publisher, year, edition, pages
Cell Press, 2019
Keywords
MAMs, Mfn2, NASH, mitochondria, phosphatidylserine, phospholipid transfer
National Category
Gastroenterology and Hepatology Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Identifiers
urn:nbn:se:oru:diva-74195 (URN)10.1016/j.cell.2019.04.010 (DOI)000466843000010 ()31051106 (PubMedID)2-s2.0-85064698279 (Scopus ID)
Note

Funding Agencies:

CONACYT, Mexico  

MICINN Spain  

Coordenacao de Aperfeicoamento do Pessoal de Nivel Superior (CAPES)  

MINECO  SAF201675246R 

Generalitat de Catalunya (ICREA Academia)  2014SGR48  2017SGR696 

INFLAMES (ISCIII) PIE-14/00045 

CIBERDEM, ISCIII, INTERREG IV-B-SUDOE-FEDER (DIOMED)  SOE1/P1/E178 

"la Caixa'' Foundation  

Miguel Servet tenure-track program from the Fondo de Investigacion Sanitaria  CP10/00438  CPII16/00008 

ERD  

MINECO through the Centres of Excellence Severo Ochoa Award  

CERCA Programme of the Generalitat de Catalunya 

Available from: 2019-05-13 Created: 2019-05-13 Last updated: 2019-06-19Bibliographically approved
Geng, D., Musse, A. A., Wigh, V., Carlsson, C., Engwall, M., Oresic, M., . . . Hyötyläinen, T. (2019). Effect of perfluorooctanesulfonic acid (PFOS) on the liver lipid metabolism of the developing chicken embryo. Ecotoxicology and Environmental Safety, 170, 691-698
Open this publication in new window or tab >>Effect of perfluorooctanesulfonic acid (PFOS) on the liver lipid metabolism of the developing chicken embryo
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2019 (English)In: Ecotoxicology and Environmental Safety, ISSN 0147-6513, E-ISSN 1090-2414, Vol. 170, p. 691-698Article in journal (Refereed) Published
Abstract [en]

Perfluorooctanesulfonate (PFOS) is a well-known contaminant in the environment and it has shown to disrupt multiple biological pathways, particularly those related with lipid metabolism. In this study, we have studied the impact of in ovo exposure to PFOS on lipid metabolism in livers in developing chicken embryos using lipidomics for detailed characterization of the liver lipidome. We used an avian model (Gallus gallus domesticus) for in ovo treatment at two levels of PFOS. The lipid profile of the liver of the embryo was investigated by ultra-high performance liquid chromatography combined with quadrupole-time-of-flight mass spectrometry and by gas chromatography mass spectrometry. Over 170 lipids were identified, covering phospholipids, ceramides, di- and triacylglycerols, cholesterol esters and fatty acid composition of the lipids. The PFOS exposure caused dose dependent changes in the lipid levels, which included upregulation of specific phospholipids associated with the phosphatidylethanolamine N-methyltransferase (PEMT) pathway, triacylglycerols with low carbon number and double bond count as well as of lipotoxic ceramides and diacylglycerols. Our data suggest that at lower levels of exposure, mitochondrial fatty acid β-oxidation is suppressed while the peroxisomal fatty acid β -oxidation is increased. At higher doses, however, both β -oxidation pathways are upregulated.

Place, publisher, year, edition, pages
Elsevier, 2019
Keywords
Avian model, Lipidomics, Liver metabolism, Mass spectrometry, Perfluorooctanesulfonate
National Category
Pharmaceutical Sciences
Identifiers
urn:nbn:se:oru:diva-71192 (URN)10.1016/j.ecoenv.2018.12.040 (DOI)000456890700083 ()30580163 (PubMedID)2-s2.0-85058940877 (Scopus ID)
Funder
Swedish Research Council, 2016-05176Swedish Research Council FormasKnowledge Foundation
Available from: 2019-01-08 Created: 2019-01-08 Last updated: 2019-03-04Bibliographically approved
Madrid-Gambin, F., Focking, M., Sabherwal, S., Heurich, M., English, J. A., O'Gorman, A., . . . Brennan, L. (2019). Integrated Lipidomics and Proteomics Point to Early Blood-Based Changes in Childhood Preceding Later Development of Psychotic Experiences: Evidence From the Avon Longitudinal Study of Parents and Children. Biological Psychiatry, 86(1), 25-34
Open this publication in new window or tab >>Integrated Lipidomics and Proteomics Point to Early Blood-Based Changes in Childhood Preceding Later Development of Psychotic Experiences: Evidence From the Avon Longitudinal Study of Parents and Children
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2019 (English)In: Biological Psychiatry, ISSN 0006-3223, E-ISSN 1873-2402, Vol. 86, no 1, p. 25-34Article in journal (Refereed) Published
Abstract [en]

BACKGROUND: The identification of early biomarkers of psychotic experiences (PEs) is of interest because early diagnosis and treatment of those at risk of future disorder is associated with improved outcomes. The current study investigated early lipidomic and coagulation pathway protein signatures of later PEs in subjects from the Avon Longitudinal Study of Parents and Children cohort.

METHODS: Plasma of 115 children (12 years of age) who were first identified as experiencing PEs at 18 years of age (48 cases and 67 controls) were assessed through integrated and targeted lipidomics and semitargeted proteomics approaches. We assessed the lipids, lysophosphatidylcholines (n = 11) and phosphatidylcholines (n = 61), and the protein members of the coagulation pathway (n = 22) and integrated these data with complement pathway protein data already available on these subjects.

RESULTS: Twelve phosphatidylcholines, four lysophosphatidylcholines, and the coagulation protein plasminogen were altered between the control and PEs groups after correction for multiple comparisons. Lipidomic and proteomic datasets were integrated into a multivariate network displaying a strong relationship between most lipids that were significantly associated with PEs and plasminogen. Finally, an unsupervised clustering approach identified four different clusters, with one of the clusters presenting the highest case-control ratio (p < .01) and associated with a higher concentration of smaller low-density lipoprotein cholesterol particles.

CONCLUSIONS: Our findings indicate that the lipidome and proteome of subjects who report PEs at 18 years of age are already altered at 12 years of age, indicating that metabolic dysregulation may contribute to an early vulnerability to PEs and suggesting crosstalk between these lysophosphatidylcholines, phosphatidylcholines, and coagulation and complement proteins.

Place, publisher, year, edition, pages
Elsevier, 2019
Keywords
ALSPAC, Early life, Integration, Lipidomics, Proteomics, Psychotic episode
National Category
Neurology Psychiatry
Identifiers
urn:nbn:se:oru:diva-75212 (URN)10.1016/j.biopsych.2019.01.018 (DOI)000472860900007 ()30878195 (PubMedID)2-s2.0-85062721715 (Scopus ID)
Funder
Wellcome trust, 102215/2/13/2
Note

Funding Agencies:Health Research Board  HRA-POR-2013-282  HRBCSA2012/8 

European Research Council  647783  724809 

European Union FP7 collaborative project METSY  602478 

National Institute for Health Research Biomedical Research Centre at University Hospitals Bristol NHS Foundation Trust and the University of Bristol  

Irish Health Research Board Clinician Scientist Award  

UK Medical Research Council  102215/2/13/2 

Available from: 2019-07-26 Created: 2019-07-26 Last updated: 2019-07-26Bibliographically approved
Sen, P. & Oresic, M. (2019). Metabolic Modeling of Human Gut Microbiota on a Genome Scale: An Overview. Metabolites, 9(2), Article ID E22.
Open this publication in new window or tab >>Metabolic Modeling of Human Gut Microbiota on a Genome Scale: An Overview
2019 (English)In: Metabolites, ISSN 2218-1989, E-ISSN 2218-1989, Vol. 9, no 2, article id E22Article, review/survey (Refereed) Published
Abstract [en]

There is growing interest in the metabolic interplay between the gut microbiome and host metabolism. Taxonomic and functional profiling of the gut microbiome by next-generation sequencing (NGS) has unveiled substantial richness and diversity. However, the mechanisms underlying interactions between diet, gut microbiome and host metabolism are still poorly understood. Genome-scale metabolic modeling (GSMM) is an emerging approach that has been increasingly applied to infer diet⁻microbiome, microbe⁻microbe and host⁻microbe interactions under physiological conditions. GSMM can, for example, be applied to estimate the metabolic capabilities of microbes in the gut. Here, we discuss how meta-omics datasets such as shotgun metagenomics, can be processed and integrated to develop large-scale, condition-specific, personalized microbiota models in healthy and disease states. Furthermore, we summarize various tools and resources available for metagenomic data processing and GSMM, highlighting the experimental approaches needed to validate the model predictions.

Place, publisher, year, edition, pages
MDPI, 2019
Keywords
Constraint-based modeling, flux balance, genome-scale metabolic modeling, gut microbiome, host–microbiome, meta-omics, metabolic reconstructions, metabolism, metabolomics, metagenomics
National Category
Bioinformatics (Computational Biology)
Identifiers
urn:nbn:se:oru:diva-72041 (URN)10.3390/metabo9020022 (DOI)000460288400006 ()30695998 (PubMedID)
Note

Funding Agencies:

Academy of Finland (Centre of Excellence in Molecular Systems Immunology and Physiology Research)  250114 

Juvenile Diabetes Research Foundation  2-SRA-2014-159-Q-R 

European Union  634413 

Available from: 2019-02-12 Created: 2019-02-12 Last updated: 2019-06-18Bibliographically approved
Playdon, M. C., Joshi, A. D., Tabung, F. K., Cheng, S., Henglin, M., Kim, A., . . . Zeleznik, O. A. (2019). Metabolomics Analytics Workflow for Epidemiological Research: Perspectives from the Consortium of Metabolomics Studies (COMETS). Metabolites, 9(7), Article ID E145.
Open this publication in new window or tab >>Metabolomics Analytics Workflow for Epidemiological Research: Perspectives from the Consortium of Metabolomics Studies (COMETS)
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2019 (English)In: Metabolites, ISSN 2218-1989, E-ISSN 2218-1989, Vol. 9, no 7, article id E145Article in journal (Refereed) Published
Abstract [en]

The application of metabolomics technology to epidemiological studies is emerging as a new approach to elucidate disease etiology and for biomarker discovery. However, analysis of metabolomics data is complex and there is an urgent need for the standardization of analysis workflow and reporting of study findings. To inform the development of such guidelines, we conducted a survey of 47 cohort representatives from the Consortium of Metabolomics Studies (COMETS) to gain insights into the current strategies and procedures used for analyzing metabolomics data in epidemiological studies worldwide. The results indicated a variety of applied analytical strategies, from biospecimen and data pre-processing and quality control to statistical analysis and reporting of study findings. These strategies included methods commonly used within the metabolomics community and applied in epidemiological research, as well as novel approaches to pre-processing pipelines and data analysis. To help with these discrepancies, we propose use of open-source initiatives such as the online web-based tool COMETS Analytics, which includes helpful tools to guide analytical workflow and the standardized reporting of findings from metabolomics analyses within epidemiological studies. Ultimately, this will improve the quality of statistical analyses, research findings, and study reproducibility.

Place, publisher, year, edition, pages
MDPI, 2019
Keywords
Analytical methods, data analysis, epidemiology, metabolomics, pre-processing, reporting, statistical analysis
National Category
Public Health, Global Health, Social Medicine and Epidemiology Information Systems
Identifiers
urn:nbn:se:oru:diva-75584 (URN)10.3390/metabo9070145 (DOI)31319517 (PubMedID)
Available from: 2019-08-16 Created: 2019-08-16 Last updated: 2019-08-16Bibliographically approved
Sen, P., Carlsson, C., Virtanen, S. M., Simell, S., Hyöty, H., Ilonen, J., . . . Oresic, M. (2019). Persistent Alterations in Plasma Lipid Profiles Before Introduction of Gluten in the Diet Associated With Progression to Celiac Disease. Clinical and Translational Gastroenterology, 10, Article ID e-00044.
Open this publication in new window or tab >>Persistent Alterations in Plasma Lipid Profiles Before Introduction of Gluten in the Diet Associated With Progression to Celiac Disease
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2019 (English)In: Clinical and Translational Gastroenterology, ISSN 2155-384X, E-ISSN 2155-384X, Vol. 10, article id e-00044Article in journal (Refereed) Published
Abstract [en]

OBJECTIVES: Celiac disease (CD) is a chronic enteropathy characterized by an autoimmune reaction in the small intestine of genetically susceptible individuals. The underlying causes of autoimmune reaction and its effect on host metabolism remain largely unknown. Herein, we apply lipidomics to elucidate the early events preceding clinical CD in a cohort of Finnish children, followed up in the Type 1 Diabetes Prediction and Prevention study.

METHODS: Mass spectrometry-based lipidomics profiling was applied to a longitudinal/prospective series of 233 plasma samples obtained from CD progressors (n = 23) and healthy controls (n = 23), matched for human leukocyte antigen (HLA) risk, sex, and age. The children were followed from birth until diagnosis of clinical CD and subsequent introduction of a gluten-free diet.

RESULTS: Twenty-three children progressed to CD at a mean age of 4.8 years. They showed increased amounts of triacylglycerols (TGs) of low carbon number and double bond count and a decreased level of phosphatidylcholines by age 3 months as compared to controls. These differences were exacerbated with age but were not observed at birth (cord blood). No significant differences were observed in the essential TGs.

DISCUSSION: Our preliminary findings suggest that abnormal lipid metabolism associates with the development of clinical CD and occurs already before the first introduction of gluten to the diet. Moreover, our data suggest that the specific TGs found elevated in CD progressors may be due to a host response to compromised intake of essential lipids in the small intestine, requiring de novo lipogenesis.

Place, publisher, year, edition, pages
Nature Publishing Group, 2019
National Category
Pediatrics Gastroenterology and Hepatology
Identifiers
urn:nbn:se:oru:diva-74371 (URN)10.14309/ctg.0000000000000044 (DOI)000468998400001 ()31082858 (PubMedID)
Note

Funding Agency:

Academy of Finland (Centre of Excellence in Molecular Systems Immunology and Physiology Research-SyMMyS)  250114  292568

Available from: 2019-05-23 Created: 2019-05-23 Last updated: 2019-06-19Bibliographically approved
Yu, B., Oresic, M. & Moore, S. C. (2019). The Consortium of Metabolomics Studies (COMETS): Metabolomics in 47 Prospective Cohort Studies. American Journal of Epidemiology, 188(6), 991-1012
Open this publication in new window or tab >>The Consortium of Metabolomics Studies (COMETS): Metabolomics in 47 Prospective Cohort Studies
2019 (English)In: American Journal of Epidemiology, ISSN 0002-9262, E-ISSN 1476-6256, Vol. 188, no 6, p. 991-1012Article in journal (Refereed) Published
Abstract [en]

The Consortium of Metabolomics Studies (COMETS) was established in 2014 to facilitate large-scale collaborative research on the human metabolome and its relationship with disease etiology, diagnosis, and prognosis. COMETS comprises 47 cohorts from Asia, Europe, North America, and South America that together include more than 136,000 participants with blood metabolomics data on samples collected from 1985 to 2017. Metabolomics data were provided by 17 different platforms, with the most frequently used labs being Metabolon, Inc. (14 cohorts), the Broad Institute (15 cohorts), and Nightingale Health (11 cohorts). Participants have been followed for a median of 23 years for health outcomes including death, cancer, cardiovascular disease, diabetes, and others; many of the studies are ongoing. Available exposure-related data include common clinical measurements and behavioral factors, as well as genome-wide genotype data. Two feasibility studies were conducted to evaluate the comparability of metabolomics platforms used by COMETS cohorts. The first study showed that the overlap between any 2 different laboratories ranged from 6 to 121 metabolites at 5 leading laboratories. The second study showed that the median Spearman correlation comparing 111 overlapping metabolites captured by Metabolon and the Broad Institute was 0.79 (interquartile range, 0.56-0.89).

Place, publisher, year, edition, pages
Oxford University Press, 2019
Keywords
cancer, cohort, diabetes, genetics, heart disease, metabolomics, prospective
National Category
Public Health, Global Health, Social Medicine and Epidemiology
Identifiers
urn:nbn:se:oru:diva-75235 (URN)10.1093/aje/kwz028 (DOI)000473760200003 ()31155658 (PubMedID)2-s2.0-85066237094 (Scopus ID)
Note

Funding Agencies:

Roche Diagnostics  

Medtronic 

Available from: 2019-07-25 Created: 2019-07-25 Last updated: 2019-07-25Bibliographically approved
Pedersen, H. K., Forslund, S. K., Gudmundsdottir, V., Østergaard Petersen, A., Hildebrand, F., Hyötyläinen, T., . . . Nielsen, H. B. (2018). A computational framework to integrate high-throughput '-omics' datasets for the identification of potential mechanistic links. Nature Protocols, 13(12), 2781-2800
Open this publication in new window or tab >>A computational framework to integrate high-throughput '-omics' datasets for the identification of potential mechanistic links
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2018 (English)In: Nature Protocols, ISSN 1754-2189, E-ISSN 1750-2799, Vol. 13, no 12, p. 2781-2800Article in journal (Refereed) Published
Abstract [en]

We recently presented a three-pronged association study that integrated human intestinal microbiome data derived from shotgun-based sequencing with untargeted serum metabolome data and measures of host physiology. Metabolome and microbiome data are high dimensional, posing a major challenge for data integration. Here, we present a step-by-step computational protocol that details and discusses the dimensionality-reduction techniques used and methods for subsequent integration and interpretation of such heterogeneous types of data. Dimensionality reduction was achieved through a combination of data normalization approaches, binning of co-abundant genes and metabolites, and integration of prior biological knowledge. The use of prior knowledge to overcome functional redundancy across microbiome species is one central advance of our method over available alternative approaches. Applying this framework, other investigators can integrate various '-omics' readouts with variables of host physiology or any other phenotype of interest (e.g., connecting host and microbiome readouts to disease severity or treatment outcome in a clinical cohort) in a three-pronged association analysis to identify potential mechanistic links to be tested in experimental settings. Although we originally developed the framework for a human metabolome-microbiome study, it is generalizable to other organisms and environmental metagenomes, as well as to studies including other -omics domains such as transcriptomics and proteomics. The provided R code runs in ~1 h on a standard PC.

Place, publisher, year, edition, pages
Nature Publishing Group, 2018
National Category
Bioinformatics and Systems Biology Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Identifiers
urn:nbn:se:oru:diva-69996 (URN)10.1038/s41596-018-0064-z (DOI)000451343400004 ()30382244 (PubMedID)2-s2.0-85055979835 (Scopus ID)
Funder
Novo Nordisk, NNF14CC0001
Note

Funding Agencies:

European Community  HEALTH-F4-2007-201052 

MetaCardis  HEALTH-2012-305312 

Innovative Medicines Initiative Joint Undertaking  115317 

Agence Nationale de la Recherche MetaGenoPolis grant 'Investissements d'avenir'  ANR-11-DPBS-0001 

Lundbeck Foundation  R218-2016-1367 

European Union  

EFPIA 

Available from: 2018-11-07 Created: 2018-11-07 Last updated: 2019-03-04Bibliographically approved
Lamichhane, S., Ahonen, L., Dyrlund, T. S., Siljander, H., Hyöty, H., Ilonen, J., . . . Oresic, M. (2018). A longitudinal plasma lipidomics dataset from children who developed islet autoimmunity and type 1 diabetes. Scientific Data, 5, Article ID 180250.
Open this publication in new window or tab >>A longitudinal plasma lipidomics dataset from children who developed islet autoimmunity and type 1 diabetes
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2018 (English)In: Scientific Data, E-ISSN 2052-4463, Vol. 5, article id 180250Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Springer Nature, 2018
National Category
Endocrinology and Diabetes
Identifiers
urn:nbn:se:oru:diva-70175 (URN)10.1038/sdata.2018.250 (DOI)000449924000001 ()30422126 (PubMedID)2-s2.0-85056307525 (Scopus ID)
Note

Funding agencies:

JDRF (grants 4-1998-274, 4-1999-731 4-2001-435)

Oulu, Tampere and Turku University Hospitals

Juvenile Diabetes Research Foundation (2-SRA-2014-159-Q-R)

Academy of Finland (Centre of Excellence in Molecular Systems Immunology and Physiology Research – SyMMyS, Decision No. 250114)

Available from: 2018-11-15 Created: 2018-11-15 Last updated: 2019-03-04Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0002-2856-9165

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