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Title: DAISY Complement Protein ML-Ready Data

Abstract

A total of 172 children from the DAISY study with multiple plasma samples collected over time, with up to 23 years of follow-up, were characterized via proteomics analysis. Of the children there were 40 controls and 132 cases. All 132 cases had measurements across time relative to IA. Sampling was not consistent for all children. There were 47 of the children who had samples taken and evaluated prior to IA (Pre-IA), and 131 children had measurements at or after IA, but prior to diagnosis of clinical T1D (Post-IA). The control children were frequency matched on HLA genotypes and age and sex with an observed lower frequency of first degree relatives within the control group versus the cases For machine learning the children that will develop islet autoantibodies the 40 control and 47 Pre-IA children were down-selected to a single sample time point. For the 40 control children this was the earliest sample collected and for the 47 Pre-IA children it was a random selection of the first or second time point prior to the detection of autoantibodies to assure the age distributions were not significantly different.


Citation Formats

Webb-Robertson, Bobbie-Jo M, Flores, Javier E, Bramer, Lisa M, Nakayasu, Ernesto S, Dong, Fran, Waugh, Kathleen, Schepmoes, Athena A, Gao, Yuqian, Fillmore, Thomas L, Onengut-Gumuscu, Suna, Frazer-Abel, Ashley, Rich, Stephen S, Holers, Michael, Metz, Thomas O, and Rewers, Marian. DAISY Complement Protein ML-Ready Data. United States: N. p., 2023. Web. doi:10.25584/2371917.
Webb-Robertson, Bobbie-Jo M, Flores, Javier E, Bramer, Lisa M, Nakayasu, Ernesto S, Dong, Fran, Waugh, Kathleen, Schepmoes, Athena A, Gao, Yuqian, Fillmore, Thomas L, Onengut-Gumuscu, Suna, Frazer-Abel, Ashley, Rich, Stephen S, Holers, Michael, Metz, Thomas O, & Rewers, Marian. DAISY Complement Protein ML-Ready Data. United States. doi:https://doi.org/10.25584/2371917
Webb-Robertson, Bobbie-Jo M, Flores, Javier E, Bramer, Lisa M, Nakayasu, Ernesto S, Dong, Fran, Waugh, Kathleen, Schepmoes, Athena A, Gao, Yuqian, Fillmore, Thomas L, Onengut-Gumuscu, Suna, Frazer-Abel, Ashley, Rich, Stephen S, Holers, Michael, Metz, Thomas O, and Rewers, Marian. 2023. "DAISY Complement Protein ML-Ready Data". United States. doi:https://doi.org/10.25584/2371917. https://www.osti.gov/servlets/purl/2371917. Pub date:Wed Jul 12 04:00:00 UTC 2023
@article{osti_2371917,
title = {DAISY Complement Protein ML-Ready Data},
author = {Webb-Robertson, Bobbie-Jo M and Flores, Javier E and Bramer, Lisa M and Nakayasu, Ernesto S and Dong, Fran and Waugh, Kathleen and Schepmoes, Athena A and Gao, Yuqian and Fillmore, Thomas L and Onengut-Gumuscu, Suna and Frazer-Abel, Ashley and Rich, Stephen S and Holers, Michael and Metz, Thomas O and Rewers, Marian},
abstractNote = {A total of 172 children from the DAISY study with multiple plasma samples collected over time, with up to 23 years of follow-up, were characterized via proteomics analysis. Of the children there were 40 controls and 132 cases. All 132 cases had measurements across time relative to IA. Sampling was not consistent for all children. There were 47 of the children who had samples taken and evaluated prior to IA (Pre-IA), and 131 children had measurements at or after IA, but prior to diagnosis of clinical T1D (Post-IA). The control children were frequency matched on HLA genotypes and age and sex with an observed lower frequency of first degree relatives within the control group versus the cases For machine learning the children that will develop islet autoantibodies the 40 control and 47 Pre-IA children were down-selected to a single sample time point. For the 40 control children this was the earliest sample collected and for the 47 Pre-IA children it was a random selection of the first or second time point prior to the detection of autoantibodies to assure the age distributions were not significantly different.},
doi = {10.25584/2371917},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed Jul 12 04:00:00 UTC 2023},
month = {Wed Jul 12 04:00:00 UTC 2023}
}