EXtremely Early-onset Type 1 Diabetes EXtremely Early-onset Type 1 Diabetes (A Musketeers' Memorandum Study)
NCT ID: NCT03369821
Last Updated: 2025-12-19
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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RECRUITING
300 participants
OBSERVATIONAL
2017-09-19
2028-11-30
Brief Summary
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Studying people with EET1D will enable us to look at exactly what goes wrong with the immune system because they have one of the most extreme forms of the disease. Much may be learned about the disease from a small number of rare individuals. The investigators aim to confirm that they have autoimmune type 1 diabetes and then try to understand how they have developed diabetes so young by studying their immune system genes, the function of their immune system, and environmental factors (such as maternal genetics) that may play a role in their development of the disease.
People with diabetes diagnosed under 12 months are very rare, live all over the world. and are usually referred to Exeter for genetic testing. Individuals will be contacted via their clinician to ask for more information about their diabetes and their family history. Samples will be collected to study whether they still make any of their own insulin and whether they make specific antibodies against their beta cells in the pancreas. Separately, their immune system will be studied in depth using immune cells isolated from a blood sample. These cells will undergo cutting edge techniques by Dr Tim Tree at King's College London, by Professor Bart Roep at Leiden University Medical Center, Netherlands, and Dr Cate Speake, Benaroya Research Institute, Seattle (USA). Some of these tests have never been used in people of young ages around the world, so an aim of this project will be to develop methods that can be used to study people even if they live far away.
Additional funding extended the study for a further 3 years (Phase 2) to include recruitment of infants without diabetes, aged 0-6 years, as controls to enable assessment of how the abnormalities found in autoimmune and non-autoimmune diabetes compare to normal early life development of the immune system.
An additional funding award extended the study (Phase 3) until November 2028, to advance the EXE-T1D program into its third phase, building on major discoveries from phases 1 and 2 to identify, validate, and target immune pathways that drive extremely early-onset type 1 diabetes (eeT1D) and are likely relevant to T1D across all ages. eeT1D cases, diagnosed within the first two years of life, represent particularly aggressive onset of beta-cell autoimmunity. They offer a unique lens to uncover mechanisms of immune dysregulation, informed by both polygenic and monogenic causes. The central aim is to move from pathway discovery to demonstration of novel druggable targets with potential to delay or prevent T1D onset across all ages.
Detailed Description
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In Exeter, a group of rare children who have developed T1D in the first year of life (Patel) is described as having Extremely Early-onset Type 1 Diabetes (EET1D). Studying these rare patients is important because they are presenting with autoimmunity at the beginning of life when the immune system is not yet fully developed and at a time when pancreatic autoimmunity first emerges (Krisher), so this study may give novel insights into the cause of T1D.
The Exeter Molecular Genetics Laboratory is a world referral centre (www.diabetesgenes.org) for Neonatal Diabetes (NDM). Most cases of diabetes diagnosed under 6 months do not have EET1D but have genetic mutations in beta cell genes that lead to impaired insulin production (NDM)(Ellard; De Franco). Exeter is able to identify the remaining \<20% without a mutation in a beta cell gene who actually have EET1D. Exeter uses a novel measure of T1D risk genes, called the T1D Genetic Risk Score (T1D GRS), showing that a proportion of the remaining patients have very high T1D risk and therefore EET1D(Patel). Understanding the mechanism for very early presentation could be highly important as immune strategies to intervene before or after people get T1D may differ by age of onset.
The results may focus the research community on events that occur before birth and may then inform new efforts to prevent or intervene in the underlying destruction of beta cells in T1D.
Additional funding extended the study to include recruitment of infants without diabetes, aged 0-6 years, as controls to enable assessment of how the abnormalities found in autoimmune and non-autoimmune diabetes compare to normal early life development of the immune system.
Hypotheses:
i) Extreme early-onset T1D (EET1D) is associated with classic biomarkers of T1D, such as islet specific autoantibodies, autoreactive islet specific CD8 T cells, and loss of beta cell function, whereas children with monogenic neonatal diabetes or without diabetes will not show abnormalities in these markers.
ii) EET1D will be associated with more rapid beta cell loss than T1D presenting at older ages.
iii) The mechanisms for EET1D will be due to rare changes in immune genes or due to a particularly potent, early response of the immune system to beta cells, as measured by autoreactive T cells or immune gene expression when compared to older onset T1D.
Study Aim: The EXE-T1D study will take people with T1D diagnosed before the age of 24 months and compare them to people with T1D diagnosed at more typical ages (1-20 years) and people diagnosed with non-autoimmune diabetes at a similar very young age (children with neonatal diabetes \[NDM\]), and infants without diabetes matched for age.
EXE-T1D is an observational study organised into two sub-studies:
Study 1: Cross-sectional study of existing patients with EET1D (n=100 v 100): Assess islet autoantibodies, islet T cell autoimmunity, C-peptide, RNAseq, genetics and clinical features of EET1D compared to T1D in selected patients of varying ages and durations of diabetes referred over the last 15 years to the Exeter genetics team/Prof Oram.
Study 2: Newly referred patients (n=20 v 20): Recruit newly diagnosed patients with EET1D who are referred to Exeter/Prof Oram for diagnostic testing to allow assessment of immune phenotype in patients close to diagnosis(Abreu; Unger; Velthuis). Assess immune function longitudinally by collecting a blood sample for serum and peripheral lymphocytes, islet autoantibodies and C-peptide assessment shortly after referral, and approximately 2 years later.
The investigators may also be approached by patients' GPs and by patients themselves. Recruitment to the study in this setting will be by the investigator's team who will provide information about the study and feedback inclusion of the participant in the study to the GP and diabetes clinician as appropriate.
UK participants will be recruited under UK wide ethics. Exeter will recruit patients from international centres in collaboration with local clinicians that have specific Institutional Review Board (IRB) approval.
The Exeter Clinical Laboratories encompass the Exeter Blood Sciences Laboratory and Exeter Molecular Genetics Laboratory at the Royal Devon and Exeter NHS Foundation Trust and will perform C-peptide, islet autoantibody and genetic tests.
Peripheral lymphocyte (PBMC) analysis for autoreactive CD4 and CD8 T cells will be performed by Tim Tree (King's College London). RNAseq will be performed by Cate Speake and the Benaroya Research Institute, Seattle (USA).
All participants (or their legal guardian) recruited to the study will be required to give written informed consent and will be informed of their right to withdraw from the study at any time without prejudice or jeopardy to any future clinical care.
Patients identified and screened as being suitable for this study will have a blood sample and optional urine sample collected by the clinical team at a time and location suitable for the patient, clinical and study teams.
Study 2: In addition to the first visit, a repeat blood sample for PBMC, C-peptide and Autoantibody analysis may be collected, approximately 2 years (+/-6 months) later.
Non-UK samples will be collected by collaborating international centres with their own IRB approval. The local team will spin and freeze the EDTA plasma sample and store it on site while the PBMCs are extracted as per Exeter's SOP. All tubes will then be couriered to Exeter. If no local team is available to extract PBMCs, all tubes will be couriered to Exeter for analysis. For some centres, it may be possible to arrange for the samples to be flown directly to the UK for PBMC extraction.
End of Study Definition: last participant's final study visit plus 6 months to enable follow-up data capture.
Safety, Definitions and Reporting Risks Blood samples will be collected by staff trained in venepuncture. Any potential discomfort or side-effects will be equivalent to that experienced in routine clinical care.
Benefits The C-peptide and autoantibody results may help to confirm a diagnosis of T1D so will be reported back to clinicians responsible for the patient's diabetes care. Decisions about ongoing clinical care and treatment will be made externally to the research study but treatment will be recorded.
Adverse effects Should any unforeseen adverse events arise that are possibly, probably, or definitely related to a study procedure, they will be reported to the Sponsor and CI/central coordinating team within 24 hours of the CI or PI or co-investigators becoming aware of the event.
Confidentiality All information related to study participants will be kept confidential and managed in accordance with the Data Protection Act, NHS Caldicott Guardian, The Research Governance Framework for Health and Social Care and Research Ethics Committee Approval.
Participant data will be held in a link-anonymised format, with personal identifiable data only accessible to personnel with training in data protection who require this information to perform their study role.
Record Retention and Archiving When the research study is complete, it is a requirement of the Research Governance Framework and Sponsor Trust Policy that the records are kept for a further 15 years.
Local investigator site files must be archived at the external site according to local R\&D requirements. They will not be stored at the coordinating centre's archiving facility.
Statistical Considerations Sample Size Total recruitment target is at least 240: Study 1: 100 with EET1D plus 100 controls (N=200); Study 2: EET1D v Monogenic / NDM controls (N=30+); Non-diabetic controls: (N=20+) Feasibility: The sample size has been selected to assess feasibility rather than on the basis of statistical power. In reality with these extremely rare but potentially very interesting patients, every single patient recruited could contribute on their own to a novel discovery. The immune, beta cell or autoantibody differences the study may reveal are unknown but a group of 20 v 20 gives an 80% power (alpha 0.05) to detect a difference of 10% v 50% in a proportion between the two groups and a power of 85% (alpha 0.05) to detect a 1 SD difference in a continuous variable.
Statistical analysis: The EET1D as described are unique and findings in the various studies are difficult to predict given the novel nature of this study. The study using 100 EET1D v 100 controls gives a 90% power (alpha 0.05) to detect a difference in proportions of a binary variable of 50% v 30% and a 0.6SD difference in a continuous variable, and similarly a group of 20 v 20 gives an 80% power (alpha 0.05) to detect a difference of 10% v 50% in the two groups and a power of 85% (alpha 0.05) to detect a 1 SD difference in a continuous variable.
Monitoring ensure compliance with Good Clinical Practice. The Investigators will permit monitoring, audits, REC review, and regulatory inspections by providing the Sponsor(s), Regulators and REC direct access to source data and other documents.
No financial and other competing interests to disclose for the Chief Investigator, PIs at each site and committee members for the overall study management.
NHS Indemnity will apply to UK participants and UK public liability insurance is provided by the University of Exeter.
Accidental protocol deviations must be adequately documented and reported to the Chief Investigator and Sponsor immediately.
Access to the final study dataset The Exeter study team will have access to the final dataset. Of the multiple analyses done during the study, relevant co-investigators for each analysis (e.g. RNAseq for Cate Speake) will have access to the datasets they have contributed to.
Public and Patient Involvement The CI's direct contact with patients with a diagnosis of diabetes in the first 12 months of life led to the study design. Patients, relatives and clinicians agree there would be significant benefit to knowing why and how T1D can present so young and whether understanding this could help with treatment or prevention.
Funders: Diabetes UK; The Leona M. and Harry B. Helmsley Charitable Trust. Publication Policy: On completion of the study, the data will be analysed and a Final Study Report will be prepared and submitted to the Funders, Sponsor and REC.
Conditions
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Keywords
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Study Design
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CASE_CONTROL
CROSS_SECTIONAL
Study Groups
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Study 1: Existing EET1D (Case)
* Aged 0 to 70 years
* Clinical diagnosis of diabetes \<24 months (+ evidence of WHO diabetes criteria)
* Negative genetic test for mutations causing non-autoimmune neonatal diabetes if diagnosed \<12 months
* Type 1 diabetes genetic risk score \>50th centile of T1D reference group, or monogenic cause of T1D (e.g. STAT3 or FOXP3 mutation).
Beta Cell Loss and Immune Function
Beta cell loss (measured by serum/urine C-peptide), islet-specific autoantibodies, T1D risk genes and autoreactive CD8 T cells.
Immune Function with RNAseq
Immune function (measuring autoantibodies, autoreactive CD8 T cells and RNAseq of immune genes).
Study 1: T1D (Control)
* Age 0-70 years (matched to above)
* Clinical diagnosis of T1D (diagnosed age 1-20 years)
* Insulin treated from diagnosis.
Beta Cell Loss and Immune Function
Beta cell loss (measured by serum/urine C-peptide), islet-specific autoantibodies, T1D risk genes and autoreactive CD8 T cells.
Immune Function with RNAseq
Immune function (measuring autoantibodies, autoreactive CD8 T cells and RNAseq of immune genes).
Study 2: Newly diagnosed EET1D (Case)
* Aged 0 to 24 months at recruitment
* Clinical diagnosis of diabetes \<24 months (+ evidence of WHO diabetes criteria)
* Negative genetic test for mutations causing non-autoimmune neonatal diabetes
* Type 1 diabetes genetic risk score \>50th centile of T1D reference group, or monogenic cause of T1D (e.g. STAT3 or FOXP3 mutation)
Beta Cell Loss and Immune Function
Beta cell loss (measured by serum/urine C-peptide), islet-specific autoantibodies, T1D risk genes and autoreactive CD8 T cells.
Immune Function with RNAseq
Immune function (measuring autoantibodies, autoreactive CD8 T cells and RNAseq of immune genes).
Monogenic / NDM (Control)
* Diagnosis of diabetes \<24 months
* Age 0 to 24 months at recruitment
* Diagnosis of Monogenic / NDM (confirmed by Exeter Molecular Genetics Laboratory).
Beta Cell Loss and Immune Function
Beta cell loss (measured by serum/urine C-peptide), islet-specific autoantibodies, T1D risk genes and autoreactive CD8 T cells.
Immune Function with RNAseq
Immune function (measuring autoantibodies, autoreactive CD8 T cells and RNAseq of immune genes).
Without diabetes (Control)
* Aged 0-6 years
* Attending specified participating hospital sites for elective surgery, including but not limited to: inguinal hernia repair, umbilical/midline hernia repair, orchidopexy, gastrostomy insertion/change, hypospadias repair, cleft palate repair, excision of accessory digit, laryngoscopy, adenoidectomy, tonsillectomy, MRI under general anaesthesia, eye surgery.
Should recruitment be slower than anticipated, we would recruit children with congenital non-immune thyroid disease when they attend paediatric clinic for blood draw.
Beta Cell Loss and Immune Function
Beta cell loss (measured by serum/urine C-peptide), islet-specific autoantibodies, T1D risk genes and autoreactive CD8 T cells.
Immune Function with RNAseq
Immune function (measuring autoantibodies, autoreactive CD8 T cells and RNAseq of immune genes).
Interventions
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Beta Cell Loss and Immune Function
Beta cell loss (measured by serum/urine C-peptide), islet-specific autoantibodies, T1D risk genes and autoreactive CD8 T cells.
Immune Function with RNAseq
Immune function (measuring autoantibodies, autoreactive CD8 T cells and RNAseq of immune genes).
Eligibility Criteria
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Inclusion Criteria
EET1D
* Aged 0 to 70 years
* Clinical diagnosis of diabetes \<24 months (+ evidence of WHO diabetes criteria)
* Negative genetic test for mutations causing non-autoimmune neonatal diabetes if diagnosed \<12 months
* Type 1 diabetes genetic risk score \>50th centile of T1D reference group, or monogenic cause of T1D.
T1D Controls
* Age 0-70 years (matched to above)
* Clinical diagnosis of T1D (diagnosed age 1-20 years)
* Insulin treated from diagnosis.
Monogenic / NDM controls
* Diagnosis of diabetes \<12 months
* Diagnosis of monogenic / NDM (confirmed by Exeter Molecular Genetics Laboratory).
Study 2:
EET1D
* Aged 0 to 24 months at recruitment
* Clinical diagnosis of diabetes \<24 months (+ evidence of WHO diabetes criteria)
* Negative genetic test for mutations causing non-autoimmune neonatal diabetes
* Type 1 diabetes genetic risk score \>50th centile of T1D reference group, or monogenic cause of T1D.
Monogenic/NDM controls
* Diagnosis of diabetes \<24 months
* Age 0 to 18 months at recruitment
* Diagnosis of monogenic/NDM (confirmed by Exeter Molecular Genetics Laboratory).
Non-diabetic controls
* Aged 0-6 years
* Attending specified participating hospital sites for elective surgery, including but not limited to: inguinal hernia repair, umbilical/midline hernia repair, orchidopexy, gastrostomy insertion/change, hypospadias repair, cleft palate repair, excision of accessory digit, laryngoscopy, adenoidectomy, tonsillectomy, MRI under general anaesthesia, eye surgery.
Exclusion Criteria
* Aged \>70 years
* No diagnosis of diabetes
* MODY (e.g. caused by HNF1A/HNF4A/HNF1B/GCK mutations), type 2 diabetes or diabetes related to pancreatic insufficiency or syndromic diabetes
* Intercurrent illness at time of sampling for PBMCs (see below).
Study 2:
* Aged \>24 months
* Clinical diagnosis of diabetes \>24 months
* Intercurrent illness at time of sampling for PBMCs or RNA (see below).
Non-diabetic controls:
* Aged \>6 years
* Diagnosis of diabetes or other autoimmune condition
* Known immunological disorder
* On immunosuppressive medication
* Ongoing infections/sepsis
* Major congenital abnormality or significant systemic illness that may affect the immune system, e.g. metabolic disease, 22q deletion syndrome
* Recent (within two weeks) febrile illness
* Renal failure.
For PBMC and RNA sampling: Exclusion for factors that may alter T cell function and RNAseq
* Recreational drug use (excluding cannabis use more than 1 week prior to blood sampling) - drug abuse may alter T cell function
* Alcohol related illness (excessive alcohol consumption may alter T cell function)
* Renal failure: Creatinine \>200 (as may alter T cell function)
* Any other medical condition which, in the opinion of the investigator, would affect the safety of the subject's participation.
Factors that if temporary would lead to rearrangement of study visit but if long duration, may lead to exclusion subject to the CI's discretion:
* Pregnant or lactating (as this may limit blood sampling and affect T cell function)
* Any infectious illness within the last 2 weeks if it was a febrile illness, or within 2-3 days if it was non-febrile (as this may activate T cells non-specifically)
* Taking steroids or other immunosuppressive medications (as these may alter T cell function)
* Received any immunoglobulin treatments or blood products in the last 3 months (as these may alter T cell function).
70 Years
ALL
No
Sponsors
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Royal Devon and Exeter NHS Foundation Trust
OTHER
King's College London
OTHER
Benaroya Research Institute
OTHER
University of Exeter
OTHER
Responsible Party
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Principal Investigators
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Richard Oram
Role: PRINCIPAL_INVESTIGATOR
University of Exeter
Locations
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Benaroya Research Institute
Seattle, Washington, United States
Leiden University Medical Center
Leiden, Leiden, Netherlands
Royal Devon & Exeter NHS Foundation Trust
Exeter, Devon, United Kingdom
King's College London
London, , United Kingdom
Countries
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Central Contacts
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Facility Contacts
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Cate Speake
Role: primary
Bart Roep
Role: primary
Richard Oram
Role: primary
Michelle Hudson
Role: backup
References
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Oram RA, Patel K, Hill A, Shields B, McDonald TJ, Jones A, Hattersley AT, Weedon MN. A Type 1 Diabetes Genetic Risk Score Can Aid Discrimination Between Type 1 and Type 2 Diabetes in Young Adults. Diabetes Care. 2016 Mar;39(3):337-44. doi: 10.2337/dc15-1111. Epub 2015 Nov 17.
Patel KA, Oram RA, Flanagan SE, De Franco E, Colclough K, Shepherd M, Ellard S, Weedon MN, Hattersley AT. Type 1 Diabetes Genetic Risk Score: A Novel Tool to Discriminate Monogenic and Type 1 Diabetes. Diabetes. 2016 Jul;65(7):2094-2099. doi: 10.2337/db15-1690. Epub 2016 Apr 5.
Krischer JP, Lynch KF, Schatz DA, Ilonen J, Lernmark A, Hagopian WA, Rewers MJ, She JX, Simell OG, Toppari J, Ziegler AG, Akolkar B, Bonifacio E; TEDDY Study Group. The 6 year incidence of diabetes-associated autoantibodies in genetically at-risk children: the TEDDY study. Diabetologia. 2015 May;58(5):980-7. doi: 10.1007/s00125-015-3514-y. Epub 2015 Feb 10.
Ellard S, Lango Allen H, De Franco E, Flanagan SE, Hysenaj G, Colclough K, Houghton JA, Shepherd M, Hattersley AT, Weedon MN, Caswell R. Improved genetic testing for monogenic diabetes using targeted next-generation sequencing. Diabetologia. 2013 Sep;56(9):1958-63. doi: 10.1007/s00125-013-2962-5. Epub 2013 Jun 15.
De Franco E, Flanagan SE, Houghton JA, Lango Allen H, Mackay DJ, Temple IK, Ellard S, Hattersley AT. The effect of early, comprehensive genomic testing on clinical care in neonatal diabetes: an international cohort study. Lancet. 2015 Sep 5;386(9997):957-63. doi: 10.1016/S0140-6736(15)60098-8. Epub 2015 Jul 28.
Abreu JR, Martina S, Verrijn Stuart AA, Fillie YE, Franken KL, Drijfhout JW, Roep BO. CD8 T cell autoreactivity to preproinsulin epitopes with very low human leucocyte antigen class I binding affinity. Clin Exp Immunol. 2012 Oct;170(1):57-65. doi: 10.1111/j.1365-2249.2012.04635.x.
Unger WW, Velthuis J, Abreu JR, Laban S, Quinten E, Kester MG, Reker-Hadrup S, Bakker AH, Duinkerken G, Mulder A, Franken KL, Hilbrands R, Keymeulen B, Peakman M, Ossendorp F, Drijfhout JW, Schumacher TN, Roep BO. Discovery of low-affinity preproinsulin epitopes and detection of autoreactive CD8 T-cells using combinatorial MHC multimers. J Autoimmun. 2011 Nov;37(3):151-9. doi: 10.1016/j.jaut.2011.05.012. Epub 2011 Jun 1.
Velthuis JH, Unger WW, Abreu JR, Duinkerken G, Franken K, Peakman M, Bakker AH, Reker-Hadrup S, Keymeulen B, Drijfhout JW, Schumacher TN, Roep BO. Simultaneous detection of circulating autoreactive CD8+ T-cells specific for different islet cell-associated epitopes using combinatorial MHC multimers. Diabetes. 2010 Jul;59(7):1721-30. doi: 10.2337/db09-1486. Epub 2010 Mar 31.
Speake C, Whalen E, Gersuk VH, Chaussabel D, Odegard JM, Greenbaum CJ. Longitudinal monitoring of gene expression in ultra-low-volume blood samples self-collected at home. Clin Exp Immunol. 2017 May;188(2):226-233. doi: 10.1111/cei.12916. Epub 2017 Mar 2.
Nelson JL, Gillespie KM, Lambert NC, Stevens AM, Loubiere LS, Rutledge JC, Leisenring WM, Erickson TD, Yan Z, Mullarkey ME, Boespflug ND, Bingley PJ, Gale EA. Maternal microchimerism in peripheral blood in type 1 diabetes and pancreatic islet beta cell microchimerism. Proc Natl Acad Sci U S A. 2007 Jan 30;104(5):1637-42. doi: 10.1073/pnas.0606169104. Epub 2007 Jan 23.
Gloyn AL, Pearson ER, Antcliff JF, Proks P, Bruining GJ, Slingerland AS, Howard N, Srinivasan S, Silva JM, Molnes J, Edghill EL, Frayling TM, Temple IK, Mackay D, Shield JP, Sumnik Z, van Rhijn A, Wales JK, Clark P, Gorman S, Aisenberg J, Ellard S, Njolstad PR, Ashcroft FM, Hattersley AT. Activating mutations in the gene encoding the ATP-sensitive potassium-channel subunit Kir6.2 and permanent neonatal diabetes. N Engl J Med. 2004 Apr 29;350(18):1838-49. doi: 10.1056/NEJMoa032922.
McDonald TJ, Perry MH, Peake RW, Pullan NJ, O'Connor J, Shields BM, Knight BA, Hattersley AT. EDTA improves stability of whole blood C-peptide and insulin to over 24 hours at room temperature. PLoS One. 2012;7(7):e42084. doi: 10.1371/journal.pone.0042084. Epub 2012 Jul 30.
McDonald TJ, Colclough K, Brown R, Shields B, Shepherd M, Bingley P, Williams A, Hattersley AT, Ellard S. Islet autoantibodies can discriminate maturity-onset diabetes of the young (MODY) from Type 1 diabetes. Diabet Med. 2011 Sep;28(9):1028-33. doi: 10.1111/j.1464-5491.2011.03287.x.
Abu-Id MH. Correspondence (letter to the editor): Incidence of jaw necrosis is markedly higher. Dtsch Arztebl Int. 2011 May;108(20):356. doi: 10.3238/arztebl.2011.0356b. Epub 2011 May 20. No abstract available.
Roep BO, Kleijwegt FS, van Halteren AG, Bonato V, Boggi U, Vendrame F, Marchetti P, Dotta F. Islet inflammation and CXCL10 in recent-onset type 1 diabetes. Clin Exp Immunol. 2010 Mar;159(3):338-43. doi: 10.1111/j.1365-2249.2009.04087.x. Epub 2010 Jan 5.
Hope SV, Knight BA, Shields BM, Hattersley AT, McDonald TJ, Jones AG. Random non-fasting C-peptide: bringing robust assessment of endogenous insulin secretion to the clinic. Diabet Med. 2016 Nov;33(11):1554-1558. doi: 10.1111/dme.13142. Epub 2016 May 26.
Day K, Song J, Absher D. Targeted sequencing of large genomic regions with CATCH-Seq. PLoS One. 2014 Oct 30;9(10):e111756. doi: 10.1371/journal.pone.0111756. eCollection 2014.
Akesson K, Carlsson A, Ivarsson SA, Johansson C, Weidby BM, Ludvigsson J, Gustavsson B, Lernmark A, Kockum I. The non-inherited maternal HLA haplotype affects the risk for type 1 diabetes. Int J Immunogenet. 2009 Feb;36(1):1-8. doi: 10.1111/j.1744-313X.2008.00802.x. Epub 2008 Nov 25.
Related Links
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Exeter Molecular Genetics Laboratory website
EXE-T1D study website
Other Identifiers
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17/EM/0255
Identifier Type: OTHER
Identifier Source: secondary_id
1617/023
Identifier Type: OTHER
Identifier Source: secondary_id
1706443
Identifier Type: OTHER
Identifier Source: secondary_id
228082
Identifier Type: OTHER
Identifier Source: secondary_id
50793
Identifier Type: OTHER_GRANT
Identifier Source: secondary_id
CRF 228
Identifier Type: -
Identifier Source: org_study_id