title: Early signs of disease in type 1 diabetes.
abstract: As a severe chronic disease with long-term complications, type 1 diabetes (T1D) is a burden to the patients and their families as well as a challenge to the health care system. T1D is a heterogeneous disease with a variety of etiologies and a wide range in the rate of progression to the disease. In order to prevent and treat T1D it would be important to identify measures that could be used to predict and monitor disease progression, as well as to further understand the molecular mechanisms involved. During the past 20 yr since its initiation, the Finnish Diabetes Prediction and Prevention Project (DIPP) has collected longitudinal biological samples from children with a human leukocyte antigen gene-conferred risk of T1D. This large sample collection has provided detailed sample series that enable studies to map the progression from health to disease, as well as the healthy maturation of risk-matched children. The DIPP samples have been used in a large body of research to elucidate the factors involved in the development of T1D. Interestingly, results from recent studies exploiting omics platforms have revealed that signs of the disease process can be detected very early on, even prior to appearance of the first T1D-associated antibodies, which are currently considered the earliest indications of the emerging disease. Identification and validation of multi-modal molecular markers will we hope provide a means to subgroup the heterogeneous group of T1D patients and enable prediction, diagnosis, and monitoring of T1D. Discovery of such markers is important in the design and testing of prevention and therapies for T1D.
authors.affiliation: Turku Centre for Biotechnology, University of Turku and Åbo Akademi, Turku, Finland.
authors.forename: Robert
authors.initials: R
authors.lastname: Moulder
authors.affiliation: Turku Centre for Biotechnology, University of Turku and Åbo Akademi, Turku, Finland.
authors.forename: Riitta
authors.initials: R
authors.lastname: Lahesmaa
mesh_terms: D003922:Diabetes Mellitus, Type 1 / Q000097:blood / Q000175:diagnosis*; D006801:Humans; D055432:Metabolomics; D040901:Proteomics; D059467:Transcriptome
keywords: biological markers; longitudinal studies; metabolome; proteomics; transcriptome analysis