1
|
Long SA, Linsley PS. Integrating Omics into Functional Biomarkers of Type 1 Diabetes. Cold Spring Harb Perspect Med 2024; 14:a041602. [PMID: 38772709 PMCID: PMC11216170 DOI: 10.1101/cshperspect.a041602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/23/2024]
Abstract
Biomarkers are critical to the staging and diagnosis of type 1 diabetes (T1D). Functional biomarkers offer insights into T1D immunopathogenesis and are often revealed using "omics" approaches that integrate multiple measures to identify involved pathways and functions. Application of the omics biomarker discovery may enable personalized medicine approaches to circumvent the more recently appreciated heterogeneity of T1D progression and treatment. Use of omics to define functional biomarkers is still in its early years, yet findings to date emphasize the role of cytokine signaling and adaptive immunity in biomarkers of progression and response to therapy. Here, we share examples of the use of omics to define functional biomarkers focusing on two signatures, T-cell exhaustion and T-cell help, which have been associated with outcomes in both the natural history and treatment contexts.
Collapse
Affiliation(s)
- S Alice Long
- Center for Translational Immunology, Benaroya Research Institute, Seattle, Washington 98101, USA
| | - Peter S Linsley
- Center for Systems Immunology, Benaroya Research Institute, Seattle, Washington 98101, USA
| |
Collapse
|
2
|
Bhosale SD, Moulder R, Suomi T, Ruohtula T, Honkanen J, Virtanen SM, Ilonen J, Elo LL, Knip M, Lahesmaa R. Serum proteomics of mother-infant dyads carrying HLA-conferred type 1 diabetes risk. iScience 2024; 27:110048. [PMID: 38883825 PMCID: PMC11176638 DOI: 10.1016/j.isci.2024.110048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Revised: 03/22/2024] [Accepted: 05/17/2024] [Indexed: 06/18/2024] Open
Abstract
In-utero and dietary factors make important contributions toward health and development in early childhood. In this respect, serum proteomics of maturing infants can provide insights into studies of childhood diseases, which together with perinatal proteomes could reveal further biological perspectives. Accordingly, to determine differences between feeding groups and changes in infancy, serum proteomics analyses of mother-infant dyads with HLA-conferred susceptibility to type 1 diabetes (n = 22), weaned to either an extensively hydrolyzed or regular cow's milk formula, were made. The LC-MS/MS analyses included samples from the beginning of third trimester, the time of delivery, 3 months postpartum, cord blood, and samples from the infants at 3, 6, 9, and 12 months. Correlations between ranked protein intensities were detected within the dyads, together with perinatal and age-related changes. Comparison with intestinal permeability data revealed a number of significant correlations, which could merit further consideration in this context.
Collapse
Affiliation(s)
- Santosh D Bhosale
- Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland
| | - Robert Moulder
- Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland
- InFLAMES Research Flagship Center, University of Turku, Turku, Finland
| | - Tomi Suomi
- Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland
- InFLAMES Research Flagship Center, University of Turku, Turku, Finland
| | - Terhi Ruohtula
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Jarno Honkanen
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Suvi M Virtanen
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- Unit of Health Sciences, Faculty of Social Sciences, Tampere University, Tampere, Finland
- Center for Child Health Research and Research, Development and Innovation Center, Tampere University Hospital, Tampere, Finland
| | - Jorma Ilonen
- Immunogenetics Laboratory, Institute of Biomedicine, University of Turku, Turku, Finland
| | - Laura L Elo
- Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland
- InFLAMES Research Flagship Center, University of Turku, Turku, Finland
- Institute of Biomedicine, University of Turku, Turku, Finland
| | - Mikael Knip
- Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Center for Child Health Research and Research, Development and Innovation Center, Tampere University Hospital, Tampere, Finland
| | - Riitta Lahesmaa
- Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland
- InFLAMES Research Flagship Center, University of Turku, Turku, Finland
- Institute of Biomedicine, University of Turku, Turku, Finland
| |
Collapse
|
3
|
Zou M, Yang J. Novel Protein Biomarkers and Therapeutic Targets for Type 1 Diabetes and Its Complications: Insights from Summary-Data-Based Mendelian Randomization and Colocalization Analysis. Pharmaceuticals (Basel) 2024; 17:766. [PMID: 38931433 PMCID: PMC11206317 DOI: 10.3390/ph17060766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2024] [Revised: 06/06/2024] [Accepted: 06/08/2024] [Indexed: 06/28/2024] Open
Abstract
Millions of patients suffer from type 1 diabetes (T1D) and its associated complications. Nevertheless, the pursuit of a cure for T1D has encountered significant challenges, with a crucial impediment being the lack of biomarkers that can accurately predict the progression of T1D and reliable therapeutic targets for T1D. Hence, there is an urgent need to discover novel protein biomarkers and therapeutic targets, which holds promise for targeted therapy for T1D. In this study, we extracted summary-level data on 4907 plasma proteins from 35,559 Icelanders and 2923 plasma proteins from 54,219 UK participants as exposures. The genome-wide association study (GWAS) summary statistics on T1D and T1D with complications were obtained from the R9 release results from the FinnGen consortium. Summary-data-based Mendelian randomization (SMR) analysis was employed to evaluate the causal associations between the genetically predicted levels of plasma proteins and T1D-associated outcomes. Colocalization analysis was utilized to investigate the shared genetic variants between the exposure and outcome. Moreover, transcriptome analysis and a protein-protein interaction (PPI) network further illustrated the expression patterns of the identified protein targets and their interactions with the established targets of T1D. Finally, a Mendelian randomization phenome-wide association study evaluated the potential side effects of the identified core protein targets. In the primary SMR analysis, we identified 72 potential protein targets for T1D and its complications, and nine of them were considered crucial protein targets. Within the group were five risk targets and four protective targets. Backed by evidence from the colocalization analysis, the protein targets were classified into four tiers, with MANSC4, CTRB1, SIGLEC5 and MST1 being categorized as tier 1 targets. Delving into the DrugBank database, we retrieved 11 existing medications for T1D along with their therapeutic targets. The PPI network clarified the interactions among the identified potential protein targets and established ones. Finally, the Mendelian randomization phenome-wide association study corroborated MANSC4 as a reliable target capable of mitigating the risk of various forms of diabetes, and it revealed the absence of adverse effects linked to CTRB1, SIGLEC5 and MST1. This study unveiled many protein biomarkers and therapeutic targets for T1D and its complications. Such advancements hold great promise for the progression of drug development and targeted therapy for T1D.
Collapse
Affiliation(s)
- Mingrui Zou
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Key Laboratory of Molecular Cardiovascular Science of the Ministry of Education, Center for Non-Coding RNA Medicine, Peking University Health Science Center, Beijing 100191, China
- Peking University First School of Clinical Medicine, Peking University First Hospital, Beijing 100034, China;
| | - Jichun Yang
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Key Laboratory of Molecular Cardiovascular Science of the Ministry of Education, Center for Non-Coding RNA Medicine, Peking University Health Science Center, Beijing 100191, China
| |
Collapse
|
4
|
Teixeira PF, Battelino T, Carlsson A, Gudbjörnsdottir S, Hannelius U, von Herrath M, Knip M, Korsgren O, Elding Larsson H, Lindqvist A, Ludvigsson J, Lundgren M, Nowak C, Pettersson P, Pociot F, Sundberg F, Åkesson K, Lernmark Å, Forsander G. Assisting the implementation of screening for type 1 diabetes by using artificial intelligence on publicly available data. Diabetologia 2024; 67:985-994. [PMID: 38353727 PMCID: PMC11058797 DOI: 10.1007/s00125-024-06089-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 12/06/2023] [Indexed: 04/30/2024]
Abstract
The type 1 diabetes community is coalescing around the benefits and advantages of early screening for disease risk. To be accepted by healthcare providers, regulatory authorities and payers, screening programmes need to show that the testing variables allow accurate risk prediction and that individualised risk-informed monitoring plans are established, as well as operational feasibility, cost-effectiveness and acceptance at population level. Artificial intelligence (AI) has the potential to contribute to solving these issues, starting with the identification and stratification of at-risk individuals. ASSET (AI for Sustainable Prevention of Autoimmunity in the Society; www.asset.healthcare ) is a public/private consortium that was established to contribute to research around screening for type 1 diabetes and particularly to how AI can drive the implementation of a precision medicine approach to disease prevention. ASSET will additionally focus on issues pertaining to operational implementation of screening. The authors of this article, researchers and clinicians active in the field of type 1 diabetes, met in an open forum to independently debate key issues around screening for type 1 diabetes and to advise ASSET. The potential use of AI in the analysis of longitudinal data from observational cohort studies to inform the design of improved, more individualised screening programmes was also discussed. A key issue was whether AI would allow the research community and industry to capitalise on large publicly available data repositories to design screening programmes that allow the early detection of individuals at high risk and enable clinical evaluation of preventive therapies. Overall, AI has the potential to revolutionise type 1 diabetes screening, in particular to help identify individuals who are at increased risk of disease and aid in the design of appropriate follow-up plans. We hope that this initiative will stimulate further research on this very timely topic.
Collapse
Affiliation(s)
| | - Tadej Battelino
- University Medical Center Ljubljana, University of Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Anneli Carlsson
- Department of Clinical Sciences, Lund University/CRC, Skåne University Hospital, Malmö, Sweden
| | - Soffia Gudbjörnsdottir
- Swedish National Diabetes Register, Centre of Registers, Gothenburg, Sweden
- Department of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden
| | | | - Matthias von Herrath
- Global Chief Medical Office, Novo Nordisk, A/S, Søborg, Denmark
- Diabetes Research Institute, University of Miami, Miami, FL, USA
| | - Mikael Knip
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Center for Child Health Research, Tampere University Hospital, Tampere, Finland
| | - Olle Korsgren
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
- Department of Clinical Chemistry and Transfusion Medicine, Institute of Biomedicine, University of Gothenburg, Gothenburg, Sweden
| | - Helena Elding Larsson
- Department of Clinical Sciences, Lund University/CRC, Skåne University Hospital, Malmö, Sweden
- Department of Pediatrics, Skåne University Hospital, Malmö, Sweden
| | | | - Johnny Ludvigsson
- Crown Princess Victoria Children's Hospital and Division of Pediatrics, Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
| | - Markus Lundgren
- Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
- Department of Paediatrics, Kristianstad Hospital, Kristianstad, Sweden
| | | | - Paul Pettersson
- Division of Networked and Embedded Systems, Mälardalen University, Västerås, Sweden
- MainlyAI AB, Stockholm, Sweden
| | - Flemming Pociot
- Steno Diabetes Center Copenhagen, Herlev, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Frida Sundberg
- Department of Paediatrics, Institute for Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Queen Silvia Children's Hospital, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Karin Åkesson
- Department of Clinical and Experimental Medicine, Division of Pediatrics and Diabetes Research Center, Linköping University, Linköping, Sweden
- Department of Pediatrics, Ryhov County Hospital, Jönköping, Sweden
| | - Åke Lernmark
- Department of Clinical Sciences, Lund University/CRC, Skåne University Hospital, Malmö, Sweden.
| | - Gun Forsander
- Department of Paediatrics, Institute for Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
- Queen Silvia Children's Hospital, Sahlgrenska University Hospital, Gothenburg, Sweden.
| |
Collapse
|
5
|
Webb-Robertson BJM, Nakayasu ES, Dong F, Waugh KC, Flores JE, Bramer LM, Schepmoes AA, Gao Y, Fillmore TL, Onengut-Gumuscu S, Frazer-Abel A, Rich SS, Holers VM, Metz TO, Rewers MJ. Decrease in multiple complement proteins associated with development of islet autoimmunity and type 1 diabetes. iScience 2024; 27:108769. [PMID: 38303689 PMCID: PMC10831269 DOI: 10.1016/j.isci.2023.108769] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 10/16/2023] [Accepted: 12/18/2023] [Indexed: 02/03/2024] Open
Abstract
Type 1 diabetes (T1D) is a chronic condition caused by autoimmune destruction of the insulin-producing pancreatic β cells. While it is known that gene-environment interactions play a key role in triggering the autoimmune process leading to T1D, the pathogenic mechanism leading to the appearance of islet autoantibodies-biomarkers of autoimmunity-is poorly understood. Here we show that disruption of the complement system precedes the detection of islet autoantibodies and persists through disease onset. Our results suggest that children who exhibit islet autoimmunity and progress to clinical T1D have lower complement protein levels relative to those who do not progress within a similar time frame. Thus, the complement pathway, an understudied mechanistic and therapeutic target in T1D, merits increased attention for use as protein biomarkers of prediction and potentially prevention of T1D.
Collapse
Affiliation(s)
- Bobbie-Jo M. Webb-Robertson
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
- Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Gainesville, FL, USA
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
| | - Ernesto S. Nakayasu
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Fran Dong
- Barbara Davis Center for Diabetes, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Kathy C. Waugh
- Barbara Davis Center for Diabetes, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Javier E. Flores
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Lisa M. Bramer
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Athena A. Schepmoes
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Yuqian Gao
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Thomas L. Fillmore
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Suna Onengut-Gumuscu
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Ashley Frazer-Abel
- Divison of Rheumatology, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - V. Michael Holers
- Divison of Rheumatology, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Thomas O. Metz
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Marian J. Rewers
- Barbara Davis Center for Diabetes, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| |
Collapse
|
6
|
Alcazar O, Chuang ST, Ren G, Ogihara M, Webb-Robertson BJM, Nakayasu ES, Buchwald P, Abdulreda MH. A Composite Biomarker Signature of Type 1 Diabetes Risk Identified via Augmentation of Parallel Multi-Omics Data from a Small Cohort. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.09.579673. [PMID: 38405796 PMCID: PMC10888829 DOI: 10.1101/2024.02.09.579673] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Background Biomarkers of early pathogenesis of type 1 diabetes (T1D) are crucial to enable effective prevention measures in at-risk populations before significant damage occurs to their insulin producing beta-cell mass. We recently introduced the concept of integrated parallel multi-omics and employed a novel data augmentation approach which identified promising candidate biomarkers from a small cohort of high-risk T1D subjects. We now validate selected biomarkers to generate a potential composite signature of T1D risk. Methods Twelve candidate biomarkers, which were identified in the augmented data and selected based on their fold-change relative to healthy controls and cross-reference to proteomics data previously obtained in the expansive TEDDY and DAISY cohorts, were measured in the original samples by ELISA. Results All 12 biomarkers had established connections with lipid/lipoprotein metabolism, immune function, inflammation, and diabetes, but only 7 were found to be markedly changed in the high-risk subjects compared to the healthy controls: ApoC1 and PON1 were reduced while CETP, CD36, FGFR1, IGHM, PCSK9, SOD1, and VCAM1 were elevated. Conclusions Results further highlight the promise of our data augmentation approach in unmasking important patterns and pathologically significant features in parallel multi-omics datasets obtained from small sample cohorts to facilitate the identification of promising candidate T1D biomarkers for downstream validation. They also support the potential utility of a composite biomarker signature of T1D risk characterized by the changes in the above markers.
Collapse
|
7
|
Lin J, Moradi E, Salenius K, Lehtipuro S, Häkkinen T, Laiho JE, Oikarinen S, Randelin S, Parikh HM, Krischer JP, Toppari J, Lernmark Å, Petrosino JF, Ajami NJ, She JX, Hagopian WA, Rewers MJ, Lloyd RE, Rautajoki KJ, Hyöty H, Nykter M. Distinct transcriptomic profiles in children prior to the appearance of type 1 diabetes-linked islet autoantibodies and following enterovirus infection. Nat Commun 2023; 14:7630. [PMID: 37993433 PMCID: PMC10665402 DOI: 10.1038/s41467-023-42763-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 10/17/2023] [Indexed: 11/24/2023] Open
Abstract
Although the genetic basis and pathogenesis of type 1 diabetes have been studied extensively, how host responses to environmental factors might contribute to autoantibody development remains largely unknown. Here, we use longitudinal blood transcriptome sequencing data to characterize host responses in children within 12 months prior to the appearance of type 1 diabetes-linked islet autoantibodies, as well as matched control children. We report that children who present with insulin-specific autoantibodies first have distinct transcriptional profiles from those who develop GADA autoantibodies first. In particular, gene dosage-driven expression of GSTM1 is associated with GADA autoantibody positivity. Moreover, compared with controls, we observe increased monocyte and decreased B cell proportions 9-12 months prior to autoantibody positivity, especially in children who developed antibodies against insulin first. Lastly, we show that control children present transcriptional signatures consistent with robust immune responses to enterovirus infection, whereas children who later developed islet autoimmunity do not. These findings highlight distinct immune-related transcriptomic differences between case and control children prior to case progression to islet autoimmunity and uncover deficient antiviral response in children who later develop islet autoimmunity.
Collapse
Grants
- U01 DK063821 NIDDK NIH HHS
- UC4 DK063863 NIDDK NIH HHS
- UL1 TR002535 NCATS NIH HHS
- U01 DK128847 NIDDK NIH HHS
- U01 DK063790 NIDDK NIH HHS
- UL1 TR000064 NCATS NIH HHS
- HHSN267200700014C NLM NIH HHS
- U01 DK063836 NIDDK NIH HHS
- U01 DK063829 NIDDK NIH HHS
- U01 DK063865 NIDDK NIH HHS
- UC4 DK095300 NIDDK NIH HHS
- UC4 DK063861 NIDDK NIH HHS
- UC4 DK063829 NIDDK NIH HHS
- UC4 DK063821 NIDDK NIH HHS
- UC4 DK117483 NIDDK NIH HHS
- UC4 DK063836 NIDDK NIH HHS
- UC4 DK112243 NIDDK NIH HHS
- U01 DK124166 NIDDK NIH HHS
- U01 DK063861 NIDDK NIH HHS
- UC4 DK063865 NIDDK NIH HHS
- U01 DK063863 NIDDK NIH HHS
- UC4 DK106955 NIDDK NIH HHS
- UC4 DK100238 NIDDK NIH HHS
- Academy of Finland (Suomen Akatemia)
- Sigrid Juséliuksen Säätiö (Sigrid Jusélius Foundation)
- U.S. Department of Health & Human Services | NIH | National Institute of Diabetes and Digestive and Kidney Diseases (National Institute of Diabetes & Digestive & Kidney Diseases)
- EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020)
- The TEDDY Study is funded by U01 DK63829, U01 DK63861, U01 DK63821, U01 DK63865, U01 DK63863, U01 DK63836, U01 DK63790, UC4 DK63829, UC4 DK63861, UC4 DK63821, UC4 DK63865, UC4 DK63863, UC4 DK63836, UC4 DK95300, UC4 DK100238, UC4 DK106955, UC4 DK112243, UC4 DK117483, U01 DK124166, U01 DK128847, and Contract No. HHSN267200700014C from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institute of Allergy and Infectious Diseases (NIAID), Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institute of Environmental Health Sciences (NIEHS), Centers for Disease Control and Prevention (CDC), and JDRF. This work is supported in part by the NIH/NCATS Clinical and Translational Science Awards to the University of Florida (UL1 TR000064) and the University of Colorado (UL1 TR002535).
- Päivikki and Sakari Sohlberg's Foundation
Collapse
Affiliation(s)
- Jake Lin
- Prostate Cancer Research Center, Faculty of Medicine and Health Technology, Tampere University and Tays Cancer Centre, Tampere, Finland
- Biostatistics, Health Sciences, Faculty of Social Sciences, Tampere University, Tampere, Finland
- Finnish Institute of Molecular Medicine, FIMM, University of Helsinki, 00290, Helsinki, Finland
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Elaheh Moradi
- Prostate Cancer Research Center, Faculty of Medicine and Health Technology, Tampere University and Tays Cancer Centre, Tampere, Finland
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, 70150, Finland
| | - Karoliina Salenius
- Prostate Cancer Research Center, Faculty of Medicine and Health Technology, Tampere University and Tays Cancer Centre, Tampere, Finland
| | - Suvi Lehtipuro
- Prostate Cancer Research Center, Faculty of Medicine and Health Technology, Tampere University and Tays Cancer Centre, Tampere, Finland
| | - Tomi Häkkinen
- Prostate Cancer Research Center, Faculty of Medicine and Health Technology, Tampere University and Tays Cancer Centre, Tampere, Finland
| | - Jutta E Laiho
- Department of Virology, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Sami Oikarinen
- Department of Virology, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Sofia Randelin
- Prostate Cancer Research Center, Faculty of Medicine and Health Technology, Tampere University and Tays Cancer Centre, Tampere, Finland
| | - Hemang M Parikh
- Health Informatics Institute, Morsani College of Medicine, University of South Florida, Tampa, FL, USA
| | - Jeffrey P Krischer
- Health Informatics Institute, Morsani College of Medicine, University of South Florida, Tampa, FL, USA
| | - Jorma Toppari
- Research Centre for Integrative Physiology and Pharmacology, Institute of Biomedicine, and Centre for Population Health Research, University of Turku, Turku, Finland
- Department of Pediatrics, Turku University Hospital, Turku, Finland
| | - Åke Lernmark
- Department of Clinical Sciences, Lund University CRC, Skåne University Hospital, Malmö, Sweden
| | - Joseph F Petrosino
- Alkek Center for Metagenomics and Microbiome Research, Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA
| | - Nadim J Ajami
- Alkek Center for Metagenomics and Microbiome Research, Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA
- Platform for Innovative Microbiome & Translational Research (PRIME-TR), Moon Shots™ Program, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jin-Xiong She
- Jinfiniti Precision Medicine, Inc., Augusta, GA, USA
| | - William A Hagopian
- Pacific Northwest Research Institute, Seattle, WA, USA
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Marian J Rewers
- Barbara Davis Center for Childhood Diabetes, University of Colorado, Aurora, CO, USA
| | - Richard E Lloyd
- Alkek Center for Metagenomics and Microbiome Research, Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA
| | - Kirsi J Rautajoki
- Prostate Cancer Research Center, Faculty of Medicine and Health Technology, Tampere University and Tays Cancer Centre, Tampere, Finland.
| | - Heikki Hyöty
- Department of Virology, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
- Fimlab Laboratories, Tampere, Finland.
| | - Matti Nykter
- Prostate Cancer Research Center, Faculty of Medicine and Health Technology, Tampere University and Tays Cancer Centre, Tampere, Finland.
- Foundation for the Finnish Cancer Institute, Helsinki, Finland.
| |
Collapse
|
8
|
Sarkar S, Elliott EC, Henry HR, Ludovico ID, Melchior JT, Frazer-Abel A, Webb-Robertson BJ, Davidson WS, Holers VM, Rewers MJ, Metz TO, Nakayasu ES. Systematic review of type 1 diabetes biomarkers reveals regulation in circulating proteins related to complement, lipid metabolism, and immune response. Clin Proteomics 2023; 20:38. [PMID: 37735622 PMCID: PMC10512508 DOI: 10.1186/s12014-023-09429-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 08/25/2023] [Indexed: 09/23/2023] Open
Abstract
BACKGROUND Type 1 diabetes (T1D) results from an autoimmune attack of the pancreatic β cells that progresses to dysglycemia and symptomatic hyperglycemia. Current biomarkers to track this evolution are limited, with development of islet autoantibodies marking the onset of autoimmunity and metabolic tests used to detect dysglycemia. Therefore, additional biomarkers are needed to better track disease initiation and progression. Multiple clinical studies have used proteomics to identify biomarker candidates. However, most of the studies were limited to the initial candidate identification, which needs to be further validated and have assays developed for clinical use. Here we curate these studies to help prioritize biomarker candidates for validation studies and to obtain a broader view of processes regulated during disease development. METHODS This systematic review was registered with Open Science Framework ( https://doi.org/10.17605/OSF.IO/N8TSA ). Using PRISMA guidelines, we conducted a systematic search of proteomics studies of T1D in the PubMed to identify putative protein biomarkers of the disease. Studies that performed mass spectrometry-based untargeted/targeted proteomic analysis of human serum/plasma of control, pre-seroconversion, post-seroconversion, and/or T1D-diagnosed subjects were included. For unbiased screening, 3 reviewers screened all the articles independently using the pre-determined criteria. RESULTS A total of 13 studies met our inclusion criteria, resulting in the identification of 266 unique proteins, with 31 (11.6%) being identified across 3 or more studies. The circulating protein biomarkers were found to be enriched in complement, lipid metabolism, and immune response pathways, all of which are found to be dysregulated in different phases of T1D development. We found 2 subsets: 17 proteins (C3, C1R, C8G, C4B, IBP2, IBP3, ITIH1, ITIH2, BTD, APOE, TETN, C1S, C6A3, SAA4, ALS, SEPP1 and PI16) and 3 proteins (C3, CLUS and C4A) have consistent regulation in at least 2 independent studies at post-seroconversion and post-diagnosis compared to controls, respectively, making them strong candidates for clinical assay development. CONCLUSIONS Biomarkers analyzed in this systematic review highlight alterations in specific biological processes in T1D, including complement, lipid metabolism, and immune response pathways, and may have potential for further use in the clinic as prognostic or diagnostic assays.
Collapse
Affiliation(s)
- Soumyadeep Sarkar
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Emily C Elliott
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Hayden R Henry
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Ivo Díaz Ludovico
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - John T Melchior
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
- Department of Pathology and Laboratory Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Ashley Frazer-Abel
- Division of Rheumatology, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | | | - W Sean Davidson
- Department of Pathology and Laboratory Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - V Michael Holers
- Division of Rheumatology, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Marian J Rewers
- Barbara Davis Center for Diabetes, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Thomas O Metz
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Ernesto S Nakayasu
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA.
| |
Collapse
|
9
|
Jia X, Wang S, Lu J. Plasma protein biomarkers trailblaze as early predictors of type 1 diabetes. Cell Rep Med 2023; 4:101116. [PMID: 37467728 PMCID: PMC10394253 DOI: 10.1016/j.xcrm.2023.101116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 06/19/2023] [Accepted: 06/20/2023] [Indexed: 07/21/2023]
Abstract
Nakayasu et al.'s investigation1 on children from TEDDY study revealed robust predictive value of plasma protein biomarkers in identifying the emergence of persistent autoantibodies and type 1 diabetes. Remarkably, this predictive accuracy was observed six months prior to autoimmunity initiation.
Collapse
Affiliation(s)
- Xiaojing Jia
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shuangyuan Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jieli Lu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| |
Collapse
|