Dataset Information

Serum APOC1 levels are decreased in seroconverted children who progress to type 1 diabetes at a young age

ABSTRACT: Biomarkers are needed to accurately predict and monitor type 1 diabetes progression during the substantially heterogeneous presymptomatic period of the disease development. To address this concern, we studied temporal changes in the plasma and serum proteomes of < 5-year-old children with HLA-conferred risk for type 1 diabetes by analysing longitudinal sample series that were collected at regular intervals between birth and diagnosis. Using mass spectrometry-based discovery proteomics, longitudinal plasma sample series from multiple autoantibody positive children who had rapidly progressed to type 1 diabetes before 4 years of age were analysed and compared with similar measurements from age and gender matched children who were either single autoantibody positive or autoantibody negative. Following analysis of the data with an additive Gaussian process regression model (LonGP), targeted proteomics was used to verify 11 biomarker candidates in a larger independent yet similar cohort of children with more frequent sampling points. The data reiterated extensive age related trends for protein levels in young children. Further, by combining the utility of LonGP together with the targeted analysis in an extended cohort, these analyses demonstrated that the serum levels of two peptides unique for apolipoprotein C1 (APOC1) were decreased after the appearance of the first autoantibody and remained relatively less abundant in children who progressed to type 1 diabetes in comparison to autoantibody negative children.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Plasma

DISEASE(S): Type 1 Diabetes Mellitus

SUBMITTER: Maria Karoliina Hirvonen

LAB HEAD: Riitta Lahesmaa

PROVIDER: PXD033744 | Pride | 2023-09-26

REPOSITORIES: Pride

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Serum APOC1 levels are decreased in young autoantibody positive children who rapidly progress to type 1 diabetes.

Hirvonen M Karoliina MK Lietzén Niina N Moulder Robert R Bhosale Santosh D SD Koskenniemi Jaakko J Vähä-Mäkilä Mari M Nurmio Mirja M Orešič Matej M Ilonen Jorma J Toppari Jorma J Veijola Riitta R Hyöty Heikki H Lähdesmäki Harri H Knip Mikael M Cheng Lu L Lahesmaa Riitta R

Scientific reports 20230924 1

Better understanding of the early events in the development of type 1 diabetes is needed to improve prediction and monitoring of the disease progression during the substantially heterogeneous presymptomatic period of the beta cell damaging process. To address this concern, we used mass spectrometry-based proteomics to analyse longitudinal pre-onset plasma sample series from children positive for multiple islet autoantibodies who had rapidly progressed to type 1 diabetes before 4 years of age (n ...[more]

PMID: 37743383

Similar Datasets

Project description:Aims/hypothesis: Biomarkers are needed to accurately predict and monitor type 1 diabetes progression during the substantially heterogeneous presymptomatic period of the disease development. To address this concern, we studied temporal changes in the plasma and serum proteomes of < 5-year-old children with HLA-conferred risk for type 1 diabetes, by analysing longitudinal sample series that were collected at regular intervals between birth and diagnosis. Methods: Using mass spectrometry-based discovery proteomics, longitudinal sample series from children positive for multiple autoantibodies who had rapidly progressed to type 1 diabetes before 4 years of age (n=10) were analysed and compared with similar measurements from children, matched from age and gender who were either positive for single autoantibody (n=10) or autoantibody negative (n=10). Following analysis of the data with an additive Gaussian process regression model (LonGP), targeted proteomics was used to verify 11 biomarker candidates in a similar yet independent cohort of children who progressed to the disease within 5 years of age (n=31) and matched autoantibody negative children (n=31). Results: These data reiterated extensive age related trends for protein levels in young children. Further, by combining the utility of LonGP together with the targeted analysis in an extended cohort with more frequent sampling points, these analysis demonstrated that the serum levels of two peptides unique for apolipoprotein C1 (APOC1) were decreased after the appearance of the first islet autoantibody and remained relatively less abundant in children who later progressed to type 1 diabetes, in comparison to autoantibody negative children. Conclusions/interpretation: Through the comparative analysis of prospectively collected samples, our data indicate that the serum/plasma levels of APOC1 are decreased in islet autoantibody positive children who develop type 1 diabetes at a young age. In future studies, APOC1 could be used as an additional measurement to improve early prediction of type 1 diabetes and selection of subjects for intervention studies.

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