Indiana University
Indianapolis, Indiana, 46202, United States
NCT Number: NCT04362917
Despite the valuable information derived from older studies evaluating type 1 diabetes, the diabetes research community has, in large part, overlooked potential contributions of baseline abnormalities in β cell function to T1D development. Newer studies focusing on higher risk individuals often exclude family members without evidence of positive islet autoantibodies. New technologies to assay alternative biomarkers of β cell stress and death remain incompletely explored in both Ab negative and Ab positive family members of T1D patients. Specifically, modern biomarkers of β cell dysfunction have not been rigorously tested in combination with metabolic testing to fully understand their association with insulin secretion.
The investigator's working hypothesis is that individuals at genetic risk for T1D exhibit baseline β cell dysfunction, even before development of detectable islet autoimmunity (seropositivity for islet Abs).
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Notify Me12 year–55 year
All sexes
Observational
Indianapolis, Indiana, 46202, United States
Healthy volunteers accepted: Yes
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
for each subject group* note age limits different for each group*:
Criteria for all subjects:
Exclusion criteria
for all participants:
There is no intervention
Time frame: The data for this analysis will come from cross-sectional samples collected through study completion, study completion will be on average 13-16 weeks from visit 1.
Our primary outcome is to assess if there is a difference in first phase beta call function in those genetically at risk for developing type 1 diabetes (first degree relatives) but who are islet autoantibody negative versus healthy controls with no family history of type 1 diabetes.
We will calculate the first phase beta cell function by multiplying the acute c-peptide response to glucose (ACPRg) (nmol/L) by the insulin sensitivity (M/I) (x10-5 mmol/kg/min per pmol/L)
Time frame: The data for this analysis will come from cross-sectional samples collected through study completion, study completion will be on average 13-16 weeks from visit 1.
Our secondary outcome is to assess if there is a difference in second phase beta cell function in those genetically at risk for developing type 1 diabetes (first degree relatives) but who are islet autoantibody negative versus healthy controls with no family history of type 1 diabetes.
We will calculate the second phase beta cell function by averaging the C-peptide values collected during the steady state of the clamp (nmol*L) and multiplying by the insulin sensitivity (M/I) (x10-5 mmol/kg/min per pmol/L)
Time frame: The data for this analysis will come from cross-sectional samples collected through study completion, study completion will be on average 13-16 weeks from visit 1.
Another prespecified outcome measure is to see if there is a difference in unmethylated/methylated INS DNA (which is a biomarker of beta cell death) in those genetically at risk for developing type 1 diabetes (first degree relatives) but who are islet autoantibody negative versus healthy controls with no family history of type 1 diabetes.
Time frame: The data for this analysis will come from cross-sectional samples collected through study completion, study completion will be on average 13-16 weeks from visit 1.
Another prespecified outcome measure is to see if there is a difference in the Proinsulin/C-peptide ratio (PI:C) in those genetically at risk for developing type 1 diabetes (first degree relatives) but who are islet autoantibody negative versus healthy controls with no family history of type 1 diabetes.
Time frame: The data for this analysis will come from cross-sectional samples collected through study completion, study completion will be on average 13-16 weeks from visit 1.
We will calculate the test-retest variability of the above mentioned variables (first phase, second phase, unmethylated/methylated DNA, fasting proinsulin/c-peptide), by looking at the between-visit coefficients of variation and intraclass correlations.
Indiana University
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