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2. Intake of B vitamins and the risk of developing islet autoimmunity and type 1 diabetes in the TEDDY study

Author

Hakola, Leena, Mramba, Lazarus K., Uusitalo, Ulla, Andrén Aronsson, Carin, Hummel, Sandra, Niinistö, Sari, Erlund, Iris, Yang, Jimin, Rewers, Marian J., Akolkar, Beena, McIndoe, Richard A., Rich, Stephen S., Hagopian, William A., Ziegler, Anette, Lernmark, Åke, Toppari, Jorma, Krischer, Jeffrey P., Norris, Jill M., and Virtanen, Suvi M.

Published
2024
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3. The Type 2 Diabetes Knowledge Portal: An open access genetic resource dedicated to type 2 diabetes and related traits

Author

Costanzo, Maria C, von Grotthuss, Marcin, Massung, Jeffrey, Jang, Dongkeun, Caulkins, Lizz, Koesterer, Ryan, Gilbert, Clint, Welch, Ryan P, Kudtarkar, Parul, Hoang, Quy, Boughton, Andrew P, Singh, Preeti, Sun, Ying, Duby, Marc, Moriondo, Annie, Nguyen, Trang, Smadbeck, Patrick, Alexander, Benjamin R, Brandes, MacKenzie, Carmichael, Mary, Dornbos, Peter, Green, Todd, Huellas-Bruskiewicz, Kenneth C, Ji, Yue, Kluge, Alexandria, McMahon, Aoife C, Mercader, Josep M, Ruebenacker, Oliver, Sengupta, Sebanti, Spalding, Dylan, Taliun, Daniel, Consortium, AMP-T2D, Abecasis, Gonçalo, Akolkar, Beena, Allred, Nicholette D, Altshuler, David, Below, Jennifer E, Bergman, Richard, Beulens, Joline WJ, Blangero, John, Boehnke, Michael, Bokvist, Krister, Bottinger, Erwin, Bowden, Donald, Brosnan, M Julia, Brown, Christopher, Bruskiewicz, Kenneth, Burtt, Noël P, Cebola, Inês, Chambers, John, Chen, Yii-Der Ida, Cherkas, Andriy, Chu, Audrey Y, Clark, Christopher, Claussnitzer, Melina, Cox, Nancy J, Hoed, Marcel den, Dong, Duc, Duggirala, Ravindranath, Dupuis, Josée, Elders, Petra JM, Engreitz, Jesse M, Fauman, Eric, Ferrer, Jorge, Flannick, Jason, Flicek, Paul, Flickinger, Matthew, Florez, Jose C, Fox, Caroline S, Frayling, Timothy M, Frazer, Kelly A, Gaulton, Kyle J, Gloyn, Anna L, Hanis, Craig L, Hanson, Robert, Hattersley, Andrew T, Im, Hae Kyung, Iqbal, Sidra, Jacobs, Suzanne BR, Jang, Dong-Keun, Jordan, Tad, Kamphaus, Tania, Karpe, Fredrik, Keane, Thomas M, Kim, Seung K, Lage, Kasper, Lange, Leslie A, and Lazar, Mitchell

Subjects
Genetics, Diabetes, Human Genome, Metabolic and endocrine, Good Health and Well Being, Humans, Diabetes Mellitus, Type 2, Access to Information, Prospective Studies, Genomics, Phenotype, AMP-T2D Consortium, CMDKP, GWAS, T2DKP, data sharing, diabetes, effector genes, genetic associations, genetic support, genomics, portal, Biochemistry and Cell Biology, Medical Biochemistry and Metabolomics, Endocrinology & Metabolism
Abstract

Associations between human genetic variation and clinical phenotypes have become a foundation of biomedical research. Most repositories of these data seek to be disease-agnostic and therefore lack disease-focused views. The Type 2 Diabetes Knowledge Portal (T2DKP) is a public resource of genetic datasets and genomic annotations dedicated to type 2 diabetes (T2D) and related traits. Here, we seek to make the T2DKP more accessible to prospective users and more useful to existing users. First, we evaluate the T2DKP's comprehensiveness by comparing its datasets with those of other repositories. Second, we describe how researchers unfamiliar with human genetic data can begin using and correctly interpreting them via the T2DKP. Third, we describe how existing users can extend their current workflows to use the full suite of tools offered by the T2DKP. We finally discuss the lessons offered by the T2DKP toward the goal of democratizing access to complex disease genetic results.

Published
2023

5. Associations of dietary patterns between age 9 and 24 months with risk of celiac disease autoimmunity and celiac disease among children at increased risk

Author

Hård af Segerstad, Elin M., Mramba, Lazarus K., Liu, Xiang, Uusitalo, Ulla, Yang, Jimin, Norris, Jill, Virtanen, Suvi M., Liu, Edwin, Kurppa, Kalle, Koletzko, Sibylle, Ziegler, Annette G., Toppari, Jorma, Rewers, Marian, Akolkar, Beena, Krischer, Jeffrey P., Aronsson, Carin Andrén, and Agardh, Daniel

Published
2023
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6. Plasma protein biomarkers predict the development of persistent autoantibodies and type 1 diabetes 6 months prior to the onset of autoimmunity

Author

Nakayasu, Ernesto S., Bramer, Lisa M., Ansong, Charles, Schepmoes, Athena A., Fillmore, Thomas L., Gritsenko, Marina A., Clauss, Therese R., Gao, Yuqian, Piehowski, Paul D., Stanfill, Bryan A., Engel, Dave W., Orton, Daniel J., Moore, Ronald J., Qian, Wei-Jun, Sechi, Salvatore, Frohnert, Brigitte I., Toppari, Jorma, Ziegler, Anette-G., Lernmark, Åke, Hagopian, William, Akolkar, Beena, Smith, Richard D., Rewers, Marian J., Webb-Robertson, Bobbie-Jo M., and Metz, Thomas O.

Published
2023
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7. The Type 2 Diabetes Knowledge Portal: An open access genetic resource dedicated to type 2 diabetes and related traits

Author

Abecasis, Gonçalo, Akolkar, Beena, Alexander, Benjamin R., Allred, Nicholette D., Altshuler, David, Below, Jennifer E., Bergman, Richard, Beulens, Joline W.J., Blangero, John, Boehnke, Michael, Bokvist, Krister, Bottinger, Erwin, Boughton, Andrew P., Bowden, Donald, Brosnan, M. Julia, Brown, Christopher, Bruskiewicz, Kenneth, Burtt, Noël P., Carmichael, Mary, Caulkins, Lizz, Cebola, Inês, Chambers, John, Ida Chen, Yii-Der, Cherkas, Andriy, Chu, Audrey Y., Clark, Christopher, Claussnitzer, Melina, Costanzo, Maria C., Cox, Nancy J., Hoed, Marcel den, Dong, Duc, Duby, Marc, Duggirala, Ravindranath, Dupuis, Josée, Elders, Petra J.M., Engreitz, Jesse M., Fauman, Eric, Ferrer, Jorge, Flannick, Jason, Flicek, Paul, Flickinger, Matthew, Florez, Jose C., Fox, Caroline S., Frayling, Timothy M., Frazer, Kelly A., Gaulton, Kyle J., Gilbert, Clint, Gloyn, Anna L., Green, Todd, Hanis, Craig L., Hanson, Robert, Hattersley, Andrew T., Hoang, Quy, Im, Hae Kyung, Iqbal, Sidra, Jacobs, Suzanne B.R., Jang, Dong-Keun, Jordan, Tad, Kamphaus, Tania, Karpe, Fredrik, Keane, Thomas M., Kim, Seung K., Kluge, Alexandria, Koesterer, Ryan, Kudtarkar, Parul, Lage, Kasper, Lange, Leslie A., Lazar, Mitchell, Lehman, Donna, Liu, Ching-Ti, Loos, Ruth J.F., Ma, Ronald Ching-wan, MacDonald, Patrick, Massung, Jeffrey, Maurano, Matthew T., McCarthy, Mark I., McVean, Gil, Meigs, James B., Mercader, Josep M., Miller, Melissa R., Mitchell, Braxton, Mohlke, Karen L., Morabito, Samuel, Morgan, Claire, Mullican, Shannon, Narendra, Sharvari, Ng, Maggie C.Y., Nguyen, Lynette, Palmer, Colin N.A., Parker, Stephen C.J., Parrado, Antonio, Parsa, Afshin, Pawlyk, Aaron C., Pearson, Ewan R., Plump, Andrew, Province, Michael, Quertermous, Thomas, Redline, Susan, Reilly, Dermot F., Ren, Bing, Rich, Stephen S., Richards, J. Brent, Rotter, Jerome I., Ruebenacker, Oliver, Ruetten, Hartmut, Salem, Rany M., Sander, Maike, Sanders, Michael, Sanghera, Dharambir, Scott, Laura J., Sengupta, Sebanti, Siedzik, David, Sim, Xueling, Singh, Preeti, Sladek, Robert, Small, Kerrin, Smith, Philip, Stein, Peter, Spalding, Dylan, Stringham, Heather M., Sun, Ying, Susztak, Katalin, ’t Hart, Leen M., Taliun, Daniel, Taylor, Kent, Thomas, Melissa K., Todd, Jennifer A., Udler, Miriam S., Voight, Benjamin, von Grotthuss, Marcin, Wan, Andre, Welch, Ryan P., Wholley, David, Yuksel, Kaan, Zaghloul, Norann A., Jang, Dongkeun, Moriondo, Annie, Nguyen, Trang, Smadbeck, Patrick, Brandes, MacKenzie, Dornbos, Peter, Huellas-Bruskiewicz, Kenneth C., Ji, Yue, McMahon, Aoife C., Fauman, Eric B., Kamphaus, Tania Nayak, and Abecasis, Gonçalo R.

Published
2023
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8. Longitudinal Metabolome-Wide Signals Prior to the Appearance of a First Islet Autoantibody in Children Participating in the TEDDY Study

Author

Li, Qian, Parikh, Hemang, Butterworth, Martha D, Lernmark, Åke, Hagopian, William, Rewers, Marian, She, Jin-Xiong, Toppari, Jorma, Ziegler, Anette-G, Akolkar, Beena, Fiehn, Oliver, Fan, Sili, Krischer, Jeffrey P, Barbour, Aaron, Bautista, Kimberly, Baxter, Judith, Felipe-Morales, Daniel, Driscoll, Kimberly, Frohnert, Brigitte I, Stahl, Marisa, Gesualdo, Patricia, Hoffman, Michelle, Karban, Rachel, Liu, Edwin, Norris, Jill, Peacock, Stesha, Shorrosh, Hanan, Steck, Andrea, Stern, Megan, Villegas, Erica, Waugh, Kathleen, Simell, Olli G, Adamsson, Annika, Ahonen, Suvi, Åkerlund, Mari, Hakola, Leena, Hekkala, Anne, Holappa, Henna, Hyöty, Heikki, Ikonen, Anni, Ilonen, Jorma, Jäminki, Sinikka, Jokipuu, Sanna, Karlsson, Leena, Kero, Jukka, Kähönen, Miia, Knip, Mikael, Koivikko, Minna-Liisa, Koskinen, Merja, Koreasalo, Mirva, Kurppa, Kalle, Kytölä, Jarita, Latva-aho, Tiina, Lindfors, Katri, Lönnrot, Maria, Mäntymäki, Elina, Mattila, Markus, Miettinen, Maija, Multasuo, Katja, Mykkänen, Teija, Niininen, Tiina, Niinistö, Sari, Nyblom, Mia, Oikarinen, Sami, Ollikainen, Paula, Othmani, Zhian, Pohjola, Sirpa, Rajala, Petra, Rautanen, Jenna, Riikonen, Anne, Riski, Eija, Pekkola, Miia, Romo, Minna, Ruohonen, Satu, Simell, Satu, Sjöberg, Maija, Stenius, Aino, Tossavainen, Päivi, Vähä-Mäkilä, Mari, Vainionpää, Sini, Varjonen, Eeva, Veijola, Riitta, Viinikangas, Irene, Virtanen, Suvi M, Schatz, Desmond, Hopkins, Diane, Steed, Leigh, Bryant, Jennifer, Silvis, Katherine, Haller, Michael, Gardiner, Melissa, McIndoe, Richard, Sharma, Ashok, Anderson, Stephen W, Jacobsen, Laura, Marks, John, and Towe, PD

Subjects
Pediatric, Autoimmune Disease, Diabetes, Prevention, Nutrition, Metabolic and endocrine, Alanine, Amino Acids, Branched-Chain, Autoantibodies, Child, Preschool, Dehydroascorbic Acid, Diabetes Mellitus, Type 1, Fatty Acids, Female, Genetic Predisposition to Disease, Glutamate Decarboxylase, Humans, Infant, Infant, Newborn, Insulin Antibodies, Longitudinal Studies, Male, Metabolome, Methionine, Phosphatidylethanolamines, Prodromal Symptoms, Proline, Risk, Triglycerides, gamma-Aminobutyric Acid, TEDDY Study Group, Medical and Health Sciences, Endocrinology & Metabolism
Abstract

Children at increased genetic risk for type 1 diabetes (T1D) after environmental exposures may develop pancreatic islet autoantibodies (IA) at a very young age. Metabolic profile changes over time may imply responses to exposures and signal development of the first IA. Our present research in The Environmental Determinants of Diabetes in the Young (TEDDY) study aimed to identify metabolome-wide signals preceding the first IA against GAD (GADA-first) or against insulin (IAA-first). We profiled metabolomes by mass spectrometry from children's plasma at 3-month intervals after birth until appearance of the first IA. A trajectory analysis discovered each first IA preceded by reduced amino acid proline and branched-chain amino acids (BCAAs), respectively. With independent time point analysis following birth, we discovered dehydroascorbic acid (DHAA) contributing to the risk of each first IA, and γ-aminobutyric acid (GABAs) associated with the first autoantibody against insulin (IAA-first). Methionine and alanine, compounds produced in BCAA metabolism and fatty acids, also preceded IA at different time points. Unsaturated triglycerides and phosphatidylethanolamines decreased in abundance before appearance of either autoantibody. Our findings suggest that IAA-first and GADA-first are heralded by different patterns of DHAA, GABA, multiple amino acids, and fatty acids, which may be important to primary prevention of T1D.

Published
2020

9. Metabolite-related dietary patterns and the development of islet autoimmunity.

Author

Johnson, Randi K, Vanderlinden, Lauren, DeFelice, Brian C, Kechris, Katerina, Uusitalo, Ulla, Fiehn, Oliver, Sontag, Marci, Crume, Tessa, Beyerlein, Andreas, Lernmark, Åke, Toppari, Jorma, Ziegler, Anette-G, She, Jin-Xiong, Hagopian, William, Rewers, Marian, Akolkar, Beena, Krischer, Jeffrey, Virtanen, Suvi M, Norris, Jill M, and TEDDY Study Group

Subjects
TEDDY Study Group
Abstract

The role of diet in type 1 diabetes development is poorly understood. Metabolites, which reflect dietary response, may help elucidate this role. We explored metabolomics and lipidomics differences between 352 cases of islet autoimmunity (IA) and controls in the TEDDY (The Environmental Determinants of Diabetes in the Young) study. We created dietary patterns reflecting pre-IA metabolite differences between groups and examined their association with IA. Secondary outcomes included IA cases positive for multiple autoantibodies (mAb+). The association of 853 plasma metabolites with outcomes was tested at seroconversion to IA, just prior to seroconversion, and during infancy. Key compounds in enriched metabolite sets were used to create dietary patterns reflecting metabolite composition, which were then tested for association with outcomes in the nested case-control subset and the full TEDDY cohort. Unsaturated phosphatidylcholines, sphingomyelins, phosphatidylethanolamines, glucosylceramides, and phospholipid ethers in infancy were inversely associated with mAb+ risk, while dicarboxylic acids were associated with an increased risk. An infancy dietary pattern representing higher levels of unsaturated phosphatidylcholines and phospholipid ethers, and lower sphingomyelins was protective for mAb+ in the nested case-control study only. Characterization of this high-risk infant metabolomics profile may help shape the future of early diagnosis or prevention efforts.

Published
2019

10. The influence of pubertal development on autoantibody appearance and progression to type 1 diabetes in the TEDDY study

Author

Warncke, Katharina, primary, Tamura, Roy, additional, Schatz, Desmond A, additional, Veijola, Riitta, additional, Steck, Andrea K, additional, Akolkar, Beena, additional, Hagopian, William, additional, Krischer, Jeffrey P, additional, Lernmark, Åke, additional, Rewers, Marian J, additional, Toppari, Jorma, additional, McIndoe, Richard, additional, Ziegler, Anette-G, additional, Vehik, Kendra, additional, Haller, Michael J, additional, and Elding Larsson, Helena, additional

Published
2024
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12. Telomere length is not a main factor for the development of islet autoimmunity and type 1 diabetes in the TEDDY study

Author

Törn, Carina, Liu, Xiang, Onengut-Gumuscu, Suna, Counts, Kevin M., Moreno, Jose Leonardo, Remedios, Cassandra L., Chen, Wei-Min, LeFaive, Jonathon, Butterworth, Martha D., Akolkar, Beena, Krischer, Jeffrey P., Lernmark, Åke, Rewers, Marian, She, Jin-Xiong, Toppari, Jorma, Ziegler, Anette-Gabriele, Ratan, Aakrosh, Smith, Albert V., Hagopian, William A., Rich, Stephen S., and Parikh, Hemang M.

Published
2022
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13. Evaluating the contribution of rare variants to type 2 diabetes and related traits using pedigrees

Author

Jun, Goo, Manning, Alisa, Almeida, Marcio, Zawistowski, Matthew, Wood, Andrew R, Teslovich, Tanya M, Fuchsberger, Christian, Feng, Shuang, Cingolani, Pablo, Gaulton, Kyle J, Dyer, Thomas, Blackwell, Thomas W, Chen, Han, Chines, Peter S, Choi, Sungkyoung, Churchhouse, Claire, Fontanillas, Pierre, King, Ryan, Lee, SungYoung, Lincoln, Stephen E, Trubetskoy, Vasily, DePristo, Mark, Fingerlin, Tasha, Grossman, Robert, Grundstad, Jason, Heath, Alison, Kim, Jayoun, Kim, Young Jin, Laramie, Jason, Lee, Jaehoon, Li, Heng, Liu, Xuanyao, Livne, Oren, Locke, Adam E, Maller, Julian, Mazur, Alexander, Morris, Andrew P, Pollin, Toni I, Ragona, Derek, Reich, David, Rivas, Manuel A, Scott, Laura J, Sim, Xueling, Tearle, Rick G, Teo, Yik Ying, Williams, Amy L, Zöllner, Sebastian, Curran, Joanne E, Peralta, Juan, Akolkar, Beena, Bell, Graeme I, Burtt, Noël P, Cox, Nancy J, Florez, Jose C, Hanis, Craig L, McKeon, Catherine, Mohlke, Karen L, Seielstad, Mark, Wilson, James G, Atzmon, Gil, Below, Jennifer E, Dupuis, Josée, Nicolae, Dan L, Lehman, Donna, Park, Taesung, Won, Sungho, Sladek, Robert, Altshuler, David, McCarthy, Mark I, Duggirala, Ravindranath, Boehnke, Michael, Frayling, Timothy M, Abecasis, Gonçalo R, and Blangero, John

Subjects
Diabetes, Genetics, Human Genome, Clinical Research, Obesity, Genetic Testing, 2.1 Biological and endogenous factors, Aetiology, Metabolic and endocrine, Diabetes Mellitus, Type 2, Family Health, Female, Gene Frequency, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Genotype, Humans, Male, Mexican Americans, Pedigree, Phenotype, Quantitative Trait Loci, Whole Genome Sequencing, genetics, sequencing, type 2 diabetes, eQTL, rare variants
Abstract

A major challenge in evaluating the contribution of rare variants to complex disease is identifying enough copies of the rare alleles to permit informative statistical analysis. To investigate the contribution of rare variants to the risk of type 2 diabetes (T2D) and related traits, we performed deep whole-genome analysis of 1,034 members of 20 large Mexican-American families with high prevalence of T2D. If rare variants of large effect accounted for much of the diabetes risk in these families, our experiment was powered to detect association. Using gene expression data on 21,677 transcripts for 643 pedigree members, we identified evidence for large-effect rare-variant cis-expression quantitative trait loci that could not be detected in population studies, validating our approach. However, we did not identify any rare variants of large effect associated with T2D, or the related traits of fasting glucose and insulin, suggesting that large-effect rare variants account for only a modest fraction of the genetic risk of these traits in this sample of families. Reliable identification of large-effect rare variants will require larger samples of extended pedigrees or different study designs that further enrich for such variants.

Published
2018

17. Biomarker discovery study design for type 1 diabetes in The Environmental Determinants of Diabetes in the Young (TEDDY) study

Author

Lee, Hye‐Seung, Burkhardt, Brant R, McLeod, Wendy, Smith, Susan, Eberhard, Chris, Lynch, Kristian, Hadley, David, Rewers, Marian, Simell, Olli, She, Jin‐Xiong, Hagopian, Bill, Lernmark, Ake, Akolkar, Beena, Ziegler, Anette G, Krischer, Jeffrey P, and group, The TEDDY study

Subjects
Autoimmune Disease, Diabetes, Nutrition, Pediatric, Metabolic and endocrine, Autoantibodies, Biomarkers, Case-Control Studies, Diabetes Mellitus, Type 1, Diet, Epidemiologic Methods, Gene Expression, Humans, Islets of Langerhans, Metabolomics, Metagenomics, Microbiota, TEDDY study group, TEDDY, batch effects, biomarker discovery, nested case-control design, type 1 diabetes, Clinical Sciences, Endocrinology & Metabolism
Abstract

AimsThe Environmental Determinants of Diabetes in the Young planned biomarker discovery studies on longitudinal samples for persistent confirmed islet cell autoantibodies and type 1 diabetes using dietary biomarkers, metabolomics, microbiome/viral metagenomics and gene expression.MethodsThis article describes the details of planning The Environmental Determinants of Diabetes in the Young biomarker discovery studies using a nested case-control design that was chosen as an alternative to the full cohort analysis. In the frame of a nested case-control design, it guides the choice of matching factors, selection of controls, preparation of external quality control samples and reduction of batch effects along with proper sample allocation.Results and conclusionOur design is to reduce potential bias and retain study power while reducing the costs by limiting the numbers of samples requiring laboratory analyses. It also covers two primary end points (the occurrence of diabetes-related autoantibodies and the diagnosis of type 1 diabetes). The resulting list of case-control matched samples for each laboratory was augmented with external quality control samples.

Published
2014

18. Gastrointestinal infections modulate the risk for insulin autoantibodies as the first-appearing autoantibody in the TEDDY Study

Author

Lönnrot, Maria, primary, F. Lynch, Kristian, primary, Rewers, Marian, primary, Lernmark, Åke, primary, Vehik, Kendra, primary, Akolkar, Beena, primary, Hagopian, William, primary, Krischer, Jeffrey, primary, A. McIndoe, Rickhard, primary, Toppari, Jorma, primary, Ziegler, Anette G., primary, Petrosino, Joseph F., primary, Lloyd, Richard, primary, and Hyöty, Heikki, primary

Published
2023
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19. HLA genotype and probiotics modify the association between timing of solid food introduction and islet autoimmunity in the TEDDY Study

Author

Hagopian, William, primary, Uusitalo, Ulla, primary, Mramba, Lazarus K., primary, Aronsson, Carin Andrén, primary, Vehik, Kendra, primary, Yang, Jimin, primary, Hummel, Sandra, primary, Lernmark, Åke, primary, Rewers, Marian, primary, McIndoe, Richard, primary, Toppari, Jorma, primary, Ziegler, Anette G., primary, Akolkar, Beena, primary, Krischer, Jeffrey P., primary, Virtanen, Suvi M., primary, and Norris, Jill M., primary

Published
2023
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22. The human gut microbiome in early-onset type 1 diabetes from the TEDDY study

Author

Vatanen, Tommi, Franzosa, Eric A., Schwager, Randall, Tripathi, Surya, Arthur, Timothy D., Vehik, Kendra, Lernmark, Åke, Hagopian, William A., Rewers, Marian J., She, Jin-Xiong, Toppari, Jorma, Ziegler, Anette-G., Akolkar, Beena, Krischer, Jeffrey P., Stewart, Christopher J., Ajami, Nadim J., Petrosino, Joseph F., Gevers, Dirk, Lähdesmäki, Harri, Vlamakis, Hera, Huttenhower, Curtis, and Xavier, Ramnik J.

Published
2018
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23. Temporal development of the gut microbiome in early childhood from the TEDDY study

Author

Stewart, Christopher J., Ajami, Nadim J., O’Brien, Jacqueline L., Hutchinson, Diane S., Smith, Daniel P., Wong, Matthew C., Ross, Matthew C., Lloyd, Richard E., Doddapaneni, HarshaVardhan, Metcalf, Ginger A., Muzny, Donna, Gibbs, Richard A., Vatanen, Tommi, Huttenhower, Curtis, Xavier, Ramnik J., Rewers, Marian, Hagopian, William, Toppari, Jorma, Ziegler, Anette-G., She, Jin-Xiong, Akolkar, Beena, Lernmark, Ake, Hyoty, Heikki, Vehik, Kendra, Krischer, Jeffrey P., and Petrosino, Joseph F.

Published
2018
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25. Physical Activity and the Development of Islet Autoimmunity and Type 1 Diabetes in 5-15 Year Old Children Followed in the TEDDY Study

Author

Liu, Xiang, primary, Bennett Johnson, Suzanne, primary, F. Lynch, Kristian, primary, Cordan, Kerry, primary, Pate, Russell, primary, D. Butterworth, Martha, primary, Lernmark, Åke, primary, A. Hagopian, William, primary, J. Rewers, Marian, primary, A. McIndoe, Richard, primary, Toppari, Jorma, primary, Ziegler, Anette-G., primary, Akolkar, Beena, primary, P. Krischer, Jeffrey, primary, Yang, Jimin, primary, and TEDDY Study Group, the, primary

Published
2023
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27. Gastrointestinal Infections Modulate the Risk for Insulin Autoantibodies as the First-Appearing Autoantibody in the TEDDY Study.

Author

Lönnrot, Maria, Lynch, Kristian F., Rewers, Marian, Lernmark, Åke, Vehik, Kendra, Akolkar, Beena, Hagopian, William, Krischer, Jeffrey, McIndoe, Rickhard A., Toppari, Jorma, Ziegler, Anette-G., Petrosino, Joseph F., Lloyd, Richard, Hyöty, Heikki, TEDDY Study Group, Bautista, Kimberly, Baxter, Judith, Felipe-Morales, Daniel, Frohnert, Brigitte I., and Stahl, Marisa

Abstract

OBJECTIVE: To investigate gastrointestinal infection episodes (GIEs) in relation to the appearance of islet autoantibodies in The Environmental Determinants of Diabetes in the Young (TEDDY) cohort. RESEARCH DESIGN AND METHODS: GIEs on risk of autoantibodies against either insulin (IAA) or GAD (GADA) as the first-appearing autoantibody were assessed in a 10-year follow-up of 7,867 children. Stool virome was characterized in a nested case-control study. RESULTS: GIE reports (odds ratio [OR] 2.17 [95% CI 1.39–3.39]) as well as Norwalk viruses found in stool (OR 5.69 [1.36–23.7]) at <1 year of age were associated with an increased IAA risk at 2–4 years of age. GIEs reported at age 1 to <2 years correlated with a lower risk of IAA up to 10 years of age (OR 0.48 [0.35–0.68]). GIE reports at any other age were associated with an increase in IAA risk (OR 2.04 for IAA when GIE was observed 12–23 months prior [1.41–2.96]). Impacts on GADA risk were limited to GIEs <6 months prior to autoantibody development in children <4 years of age (OR 2.16 [1.54–3.02]). CONCLUSIONS: Bidirectional associations were observed. GIEs were associated with increased IAA risk when reported before 1 year of age or 12–23 months prior to IAA. Norwalk virus was identified as one possible candidate factor. GIEs reported during the 2nd year of life were associated with a decreased IAA risk. [ABSTRACT FROM AUTHOR]

Published
2023
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28. HLA Genotype and Probiotics Modify the Association Between Timing of Solid Food Introduction and Islet Autoimmunity in the TEDDY Study.

Author

Uusitalo, Ulla, Mramba, Lazarus K., Aronsson, Carin Andrén, Vehik, Kendra, Yang, Jimin, Hummel, Sandra, Lernmark, Åke, Rewers, Marian, Hagopian, William, McIndoe, Richard, Toppari, Jorma, Ziegler, Anette-G., Akolkar, Beena, Krischer, Jeffrey P., Virtanen, Suvi M., and Norris, Jill M.

Subjects
BABY foods, PROPORTIONAL hazards models, TYPE 1 diabetes, GENOTYPES, PROBIOTICS, AUTOIMMUNITY, JUNK food
Abstract

OBJECTIVE: To study the interaction among HLA genotype, early probiotic exposure, and timing of complementary foods in relation to risk of islet autoimmunity (IA). RESEARCH DESIGN AND METHODS: The Environmental Determinants of Diabetes in the Young (TEDDY) study prospectively follows 8,676 children with increased genetic risk of type 1 diabetes. We used a Cox proportional hazards regression model adjusting for potential confounders to study early feeding and the risk of IA in a sample of 7,770 children. RESULTS: Any solid food introduced early (<6 months) was associated with increased risk of IA if the child had the HLA DR3/4 genotype and no probiotic exposure during the 1st year of life. Rice introduced at 4–5.9 months compared with later in the U.S. was associated with an increased risk of IA. CONCLUSIONS: Timing of solid food introduction, including rice, may be associated with IA in children with the HLA DR3/4 genotype not exposed to probiotics. The microbiome composition under these exposure combinations requires further study. [ABSTRACT FROM AUTHOR]

Published
2023
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29. Joint modeling of longitudinal autoantibody patterns and progression to type 1 diabetes: results from the TEDDY study

Author

Köhler, Meike, Beyerlein, Andreas, Vehik, Kendra, Greven, Sonja, Umlauf, Nikolaus, Lernmark, Åke, Hagopian, William A., Rewers, Marian, She, Jin-Xiong, Toppari, Jorma, Akolkar, Beena, Krischer, Jeffrey P., Bonifacio, Ezio, Ziegler, Anette-G., Rewers, Marian, Bautista, Kimberly, Baxter, Judith, Bedoy, Ruth, Felipe-Morales, Daniel, Driscoll, Kimberly, Frohnert, Brigitte I., Gesualdo, Patricia, Hoffman, Michelle, Karban, Rachel, Liu, Edwin, Norris, Jill, Samper-Imaz, Adela, Steck, Andrea, Waugh, Kathleen, Wright, Hali, Toppari, Jorma, Simell, Olli G., Adamsson, Annika, Ahonen, Suvi, Hyöty, Heikki, Ilonen, Jorma, Jokipuu, Sanna, Kallio, Tiina, Karlsson, Leena, Kähönen, Miia, Knip, Mikael, Kovanen, Lea, Koreasalo, Mirva, Kurppa, Kalle, Latva-aho, Tiina, Lönnrot, Maria, Mäntymäki, Elina, Multasuo, Katja, Mykkänen, Juha, Niininen, Tiina, Niinistö, Sari, Nyblom, Mia, Rajala, Petra, Rautanen, Jenna, Riikonen, Anne, Riikonen, Mika, Rouhiainen, Jenni, Romo, Minna, Simell, Tuula, Simell, Ville, Sjöberg, Maija, Stenius, Aino, Leppänen, Maria, Vainionpää, Sini, Varjonen, Eeva, Veijola, Riitta, Virtanen, Suvi M., Vähä-Mäkilä, Mari, Åkerlund, Mari, Lindfors, Katri, She, Jin-Xiong, Schatz, Desmond, Hopkins, Diane, Steed, Leigh, Thomas, Jamie, Adams, Janey, Silvis, Katherine, Haller, Michael, Gardiner, Melissa, McIndoe, Richard, Sharma, Ashok, Williams, Joshua, Young, Gabriela, Anderson, Stephen W., Jacobsen, Laura, Ziegler, Anette G., Beyerlein, Andreas, Bonifacio, Ezio, Hummel, Michael, Hummel, Sandra, Foterek, Kristina, Janz, Nicole, Kersting, Mathilde, Knopff, Annette, Koletzko, Sibylle, Peplow, Claudia, Roth, Roswith, Scholz, Marlon, Stock, Joanna, Warncke, Katharina, Wendel, Lorena, Winkler, Christiane, Lernmark, Åke, Agardh, Daniel, Aronsson, Carin Andrén, Ask, Maria, Bremer, Jenny, Carlsson, Ulla-Marie, Cilio, Corrado, Ericson-Hallström, Emelie, Fransson, Lina, Gard, Thomas, Gerardsson, Joanna, Bennet, Rasmus, Hansen, Monica, Hansson, Gertie, Hyberg, Susanne, Johansen, Fredrik, Jonsdottir, Berglind, Larsson, Helena Elding, Lindström, Marielle, Lundgren, Markus, Månsson-Martinez, Maria, Markan, Maria, Melin, Jessica, Mestan, Zeliha, Ottosson, Karin, Rahmati, Kobra, Ramelius, Anita, Salami, Falastin, Sibthorpe, Sara, Sjöberg, Birgitta, Swartling, Ulrica, Amboh, Evelyn Tekum, Törn, Carina, Wallin, Anne, Wimar, Åsa, Åberg, Sofie, Hagopian, William A., Killian, Michael, Crouch, Claire Cowen, Skidmore, Jennifer, Carson, Josephine, Dalzell, Maria, Dunson, Kayleen, Hervey, Rachel, Johnson, Corbin, Lyons, Rachel, Meyer, Arlene, Mulenga, Denise, Tarr, Alexander, Uland, Morgan, Willis, John, Becker, Dorothy, Franciscus, Margaret, Smith, MaryEllen Dalmagro-Elias, Daftary, Ashi, Klein, Mary Beth, Yates, Chrystal, Krischer, Jeffrey P., Abbondondolo, Michael, Austin-Gonzalez, Sarah, Avendano, Maryouri, Baethke, Sandra, Brown, Rasheedah, Burkhardt, Brant, Butterworth, Martha, Clasen, Joanna, Cuthbertson, David, Eberhard, Christopher, Fiske, Steven, Garcia, Dena, Garmeson, Jennifer, Gowda, Veena, Heyman, Kathleen, PerezLaras, Francisco, Lee, Hye-Seung, Liu, Shu, Liu, Xiang, Lynch, Kristian, Malloy, Jamie, McCarthy, Cristina, Meulemans, Steven, Parikh, Hemang, Shaffer, Chris, Smith, Laura, Smith, Susan, Sulman, Noah, Tamura, Roy, Uusitalo, Ulla, Vehik, Kendra, Vijayakandipan, Ponni, Wood, Keith, Yang, Jimin, Ballard, Lori, Hadley, David, McLeod, Wendy, Akolkar, Beena, Yu, Liping, Miao, Dongmei, Bingley, Polly, Williams, Alistair, Chandler, Kyla, Rokni, Saba, Williams, Claire, Wyatt, Rebecca, George, Gifty, Grace, Sian, Erlich, Henry, Mack, Steven J., Ke, Sandra, Mulholland, Niveen, Bourcier, Kasia, Briese, Thomas, Johnson, Suzanne Bennett, Triplett, Eric, TEDDY study group, Ancillary Studies, Diet, Genetics, Human Subjects/Publicity/Publications, Immune Markers, Infectious Agents, Laboratory Implementation, Maternal Studies, Psychosocial, Quality Assurance, Steering, Study Coordinators, Celiac Disease, Clinical Implementation, and Quality Assurance Subcommittee on Data Quality

Published
2017
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30. Interaction between dietary iron intake and genetically determined iron overload: risk of islet autoimmunity and progression to type 1 diabetes in the TEDDY study

Author

Thorsen, Steffen U., primary, Liu, Xiang, primary, Kataria, Yachana, primary, Mandrup-Poulsen, Thomas, primary, Kaur, Simranjeet, primary, Uusitalo, Ulla, primary, Virtanen, Suvi M., primary, M. Norris, Jill, primary, Rewers, Marian, primary, Hagopian, William, primary, Yang, Jimin, primary, She, Jin-Xiong, primary, Akolkar, Beena, primary, Rich, Stephen, primary, Aronsson, Carin Andrén, primary, Lernmark, Åke, primary, Ziegler, Anette-Gabriele, primary, Toppari, Jorma, primary, Krischer, Jeffrey, primary, Parikh, Hemang M., primary, Ellervik, Christina, primary, Svensson, Jannet, primary, and Group, the TEDDY Study, primary

Published
2023
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31. Dietary Intake and Body Mass Index Influence the Risk of Islet Autoimmunity in Genetically At-Risk Children: A Mediation Analysis Using the TEDDY Cohort

Author

Andrén Aronsson, Carin, primary, Tamura, Roy, additional, Vehik, Kendra, additional, Uusitalo, Ulla, additional, Yang, Jimin, additional, Haller, Michael J., additional, Toppari, Jorma, additional, Hagopian, William, additional, McIndoe, Richard A., additional, Rewers, Marian J., additional, Ziegler, Anette-G., additional, Akolkar, Beena, additional, Krischer, Jeffrey P., additional, Norris, Jill M., additional, Virtanen, Suvi M., additional, and Elding Larsson, Helena, additional

Published
2023
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33. Respiratory infections are temporally associated with initiation of type 1 diabetes autoimmunity: the TEDDY study

Author

Lönnrot, Maria, Lynch, Kristian F., Elding Larsson, Helena, Lernmark, Åke, Rewers, Marian J., Törn, Carina, Burkhardt, Brant R., Briese, Thomas, Hagopian, William A., She, Jin-Xiong, Simell, Olli G., Toppari, Jorma, Ziegler, Anette-G., Akolkar, Beena, Krischer, Jeffrey P., Hyöty, Heikki, and on behalf of the TEDDY Study Group

Published
2017
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34. Effects of Gluten Intake on Risk of Celiac Disease: A Case-Control Study on a Swedish Birth Cohort

Author

Rewers, Marian, Bautista, Kimberly, Baxter, Judith, Bedoy, Ruth, Felipe-Morales, Daniel, Frohnert, Brigitte I., Gesualdo, Patricia, Hoffman, Michelle, Karban, Rachel, Liu, Edwin, Norris, Jill, Samper-Imaz, Adela, Steck, Andrea, Waugh, Kathleen, Wright, Hali, She, Jin-Xiong, Schatz, Desmond, Hopkins, Diane, Steed, Leigh, Thomas, Jamie, Adams, Janey, Silvis, Katherine, Haller, Michael, Gardiner, Melissa, McIndoe, Richard, Sharma, Ashok, Williams, Joshua, Foghis, Gabriela, Anderson, Stephen W., Robinson, Richard, Ziegler, Anette G., Beyerlein, Andreas, Bonifacio, Ezio, Hummel, Michael, Hummel, Sandra, Foterek, Kristina, Kersting, Mathilde, Knopff, Annette, Koletzko, Sibylle, Peplow, Claudia, Roth, Roswith, Stock, Joanna, Strauss, Elisabeth, Warncke, Katharina, Winkler, Christiane, Toppari, Jorma, Simell, Olli G., Adamsson, Annika, Hyöty, Heikki, Ilonen, Jorma, Jokipuu, Sanna, Kallio, Tiina, Kähönen, Miia, Knip, Mikael, Koivu, Annika, Koreasalo, Mirva, Kurppa, Kalle, Lönnrot, Maria, Mäntymäki, Elina, Multasuo, Katja, Mykkänen, Juha, Niininen, Tiina, Nyblom, Mia, Rajala, Petra, Rautanen, Jenna, Riikonen, Anne, Romo, Minna, Simell, Satu, Simell, Tuula, Simell, Ville, Sjöberg, Maija, Stenius, Aino, Särmä, Maria, Vainionpää, Sini, Varjonen, Eeva, Veijola, Riitta, Virtanen, Suvi M., Vähä-Mäkilä, Mari, Åkerlund, Mari, Lernmark, Åke, Agardh, Daniel, Aronsson, Carin Andrén, Ask, Maria, Bremer, Jenny, Carlsson, Ulla-Marie, Cilio, Corrado, Ericson-Hallström, Emelie, Fransson, Lina, Gard, Thomas, Gerardsson, Joanna, Bennet, Rasmus, Hansen, Monica, Hansson, Gertie, Harmby, Cecilia, Hyberg, Susanne, Johansen, Fredrik, Jonasdottir, Berglind, Larsson, Helena Elding, Forss, Sigrid Lenrick, Lundgren, Markus, Månsson-Martinez, Maria, Markan, Maria, Melin, Jessica, Mestan, Zeliha, Rahmati, Kobra, Ramelius, Anita, Rosenquist, Anna, Salami, Falastin, Sibthorpe, Sara, Sjöberg, Birgitta, Swartling, Ulrica, Amboh, Evelyn Tekum, Trulsson, Erika, Törn, Carina, Wallin, Anne, Wimar, Åsa, Åberg, Sofie, Hagopian, William A., Killian, Michael, Crouch, Claire Cowen, Skidmore, Jennifer, Ayres, Stephen, Dunson, Kayleen, Hervey, Rachel, Johnson, Corbin, Lyons, Rachel, Meyer, Arlene, Mulenga, Denise, Scott, Elizabeth, Stabbert, Joshua, Tarr, Alexander, Uland, Morgan, Willis, John, Becker, Dorothy, Franciscus, Margaret, Smith, MaryEllen Dalmagro-Elias, Daftary, Ashi, Klein, Mary Beth, Yates, Chrystal, Krischer, Jeffrey P., Abbondondolo, Michael, Austin-Gonzalez, Sarah, Baethke, Sandra, Brown, Rasheedah, Burkhardt, Brant, Butterworth, Martha, Clasen, Joanna, Cuthbertson, David, Eberhard, Christopher, Fiske, Steven, Garcia, Dena, Garmeson, Jennifer, Gowda, Veena, Heyman, Kathleen, Laras, Francisco Perez, Lee, Hye-Seung, Liu, Shu, Liu, Xiang, Lynch, Kristian, Malloy, Jamie, McCarthy, Cristina, McLeod, Wendy, Meulemans, Steven, Shaffer, Chris, Smith, Laura, Smith, Susan, Sulman, Noah, Tamura, Roy, Uusitalo, Ulla, Vehik, Kendra, Vijayakandipan, Ponni, Wood, Keith, Yang, Jimin, Ballard, Lori, Hadley, David, Akolkar, Beena, Bourcier, Kasia, Briese, Thomas, Johnson, Suzanne Bennett, Triplett, Eric, Andrén Aronsson, Carin, and Norris, Jill M.

Published
2016
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35. Gluten-free diet adherence in children with screening-detected celiac disease using a prospective birth cohort study

Author

TEDDY Study Group, Mehta, Pooja, Li, Qian, Stahl, Marisa, Uusitalo, Ulla, Lindfors, Katri, Butterworth, Martha D., Kurppa, Kalle, Virtanen, Suvi, Koletzko, Sibylle, Aronsson, Carin, Hagopian, William A., Rewers, Marian J., Toppari, Jorma, Ziegler, Anette G., Akolkar, Beena, Krischer, Jeffrey P., Agardh, Daniel, Liu, Edwin, Tampere University, BioMediTech, Department of Paediatrics, Clinical Medicine, Seinäjoen keskussairaala VA, and Health Sciences

Subjects
Multidisciplinary, 3123 Gynaecology and paediatrics, 3121 Internal medicine, 3142 Public health care science, environmental and occupational health
Abstract

Background Celiac disease has an increasing incidence worldwide and is treated with lifelong adherence to a gluten-free diet. We aimed to describe gluten-free diet adherence rates in children with screening-identified celiac disease, determine adherence-related factors, and compare adherence to food records in a multinational prospective birth cohort study. Methods Children in The Environmental Determinants of Diabetes in the Young study with celiac disease were included. Subjects had at least annual measurement of adherence (parent-report) and completed 3-day food records. Descriptive statistics, t-tests, Kruskal-Wallis tests and multivariable logistic and linear regression were employed. Results Two hundred ninety (73%) and 199 (67%) of subjects were always adherent to a gluten-free diet at 2 and 5 years post celiac disease diagnosis respectively. The percentage of children with variable adherence increased from 1% at 2 years to 15% at 5 years. Children with a first-degree relative with celiac disease were more likely to be adherent to the gluten-free diet. Gluten intake on food records could not differentiate adherent from nonadherent subjects. Adherent children from the United States had more gluten intake based on food records than European children (P < .001 and P = .007 at 2 and 5 years respectively). Conclusion Approximately three-quarters of children with screening-identified celiac disease remain strictly adherent to a gluten-free diet over time. There are no identifiable features associated with adherence aside from having a first-degree relative with celiac disease. Despite good parent-reported adherence, children from the United States have more gluten intake when assessed by food records. Studies on markers of gluten-free diet adherence, sources of gluten exposure (particularly in the United States), and effects of adherence on mucosal healing are needed.

Published
2023

36. Physical Activity and the Development of Islet Autoimmunity and Type 1 Diabetes in 5- to 15-Year-Old Children Followed in the TEDDY Study.

Author

Liu, Xiang, Johnson, Suzanne Bennett, Lynch, Kristian F., Cordan, Kerry, Pate, Russell, Butterworth, Martha D., Lernmark, Åke, Hagopian, William A., Rewers, Marian J., McIndoe, Richard A., Toppari, Jorma, Ziegler, Anette-G., Akolkar, Beena, Krischer, Jeffrey P., Yang, Jimin, The TEDDY Study Group, Rewers, Marian, Bautista, Kimberly, Baxter, Judith, and Felipe-Morales, Daniel

Abstract

OBJECTIVE: This study investigated physical activity and its association with the development of islet autoimmunity and type 1 diabetes in genetically at-risk children aged 5–15 years. RESEARCH DESIGN AND METHODS: As part of the longitudinal Environmental Determinants of Diabetes in the Young (TEDDY) study, annual assessment of activity using accelerometry was conducted from age 5 years. Time-to-event analyses using Cox proportional hazard models were used to assess the association between time spent in moderate to vigorous physical activity per day and the appearance of one or several autoantibodies and progression to type 1 diabetes in three risk groups: 1) 3,869 islet autoantibody (IA)-negative children, of whom 157 became single IA positive; 2) 302 single IA–positive children, of whom 73 became multiple IA positive; and 3) 294 multiple IA–positive children, of whom 148 developed type 1 diabetes. RESULTS: No significant association was found in risk group 1 or risk group 2. A significant association was seen in risk group 3 (hazard ratio 0.920 [95% CI 0.856, 0.988] per 10-min increase; P = 0.021), particularly when glutamate decarboxylase autoantibody was the first autoantibody (hazard ratio 0.883 [95% CI 0.783, 0.996] per 10-min increase; P = 0.043). CONCLUSIONS: More daily minutes spent in moderate to vigorous physical activity was associated with a reduced risk of progression to type 1 diabetes in children aged 5–15 years who had developed multiple IAs. [ABSTRACT FROM AUTHOR]

Published
2023
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39. Plasma protein biomarkers predict both the development of persistent autoantibodies and type 1 diabetes 6 months prior to the onset of autoimmunity: the TEDDY Study

Author

Nakayasu, Ernesto S, primary, Bramer, Lisa, additional, Ansong, Charles, additional, Schepmoes, Athena, additional, Fillmore, Thomas, additional, Gritsenko, Marina, additional, Clauss, Therese, additional, Gao, Yuqian, additional, Piehowski, Paul, additional, Stafill, Bryan, additional, Engel, David, additional, Orton, Daniel, additional, Moore, Ronald, additional, Qian, Wei-Jun, additional, Sechi, Salvatore, additional, Frohnert, Brigitte, additional, Toppari, Jorma, additional, Ziegler, Anette, additional, Lernmark, Ake, additional, Hagopian, William, additional, Akolkar, Beena, additional, Smith, Richard D, additional, Rewers, Marian, additional, Webb-Robertson, Bobbie-Jo, additional, and Metz, Thomas O, additional

Published
2022
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41. Rising Hemoglobin A1c in the Non-Diabetic Range Predicts Progression of Type 1 Diabetes As Well As Oral Glucose Tolerance Tests

Author

Vehik, Kendra, primary, Boulware, David, primary, Killian, Michael, primary, Rewers, Marian, primary, McIndoe, Richard, primary, Toppari, Jorma, primary, Lernmark, Ake, primary, Akolkar, Beena, primary, Ziegler, Anette-Gabriele, primary, Rodriguez, Henry, primary, Schatz, Desmond A, primary, P. Krischer, Jeffrey, primary, Hagopian, William A., primary, Group, TrialNet Study, primary, and Group, TEDDY Study, primary

Published
2022
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43. Interaction Between Dietary Iron Intake and Genetically Determined Iron Overload: Risk of Islet Autoimmunity and Progression to Type 1 Diabetes in the TEDDY Study.

Author

Thorsen, Steffen U., Liu, Xiang, Kataria, Yachana, Mandrup-Poulsen, Thomas, Kaur, Simranjeet, Uusitalo, Ulla, Virtanen, Suvi M., Norris, Jill M., Rewers, Marian, Hagopian, William, Yang, Jimin, She, Jin-Xiong, Akolkar, Beena, Rich, Stephen, Aronsson, Carin Andrén, Lernmark, Åke, Ziegler, Anette-Gabriele, Toppari, Jorma, Krischer, Jeffrey, and Parikh, Hemang M.

Subjects
TYPE 1 diabetes, IRON overload, FOOD consumption, IRON, DISEASE risk factors
Abstract

OBJECTIVE: To examine whether iron intake and genetically determined iron overload interact in predisposing to the development of childhood islet autoimmunity (IA) and type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS: In The Environmental Determinants of Diabetes in the Young (TEDDY) study, 7,770 genetically high-risk children were followed from birth until the development of IA and progression to T1D. Exposures included energy-adjusted iron intake in the first 3 years of life and a genetic risk score (GRS) for increased circulating iron. RESULTS: We found a U-shaped association between iron intake and risk of GAD antibody as the first autoantibody. In children with GRS ≥2 iron risk alleles, high iron intake was associated with an increased risk of IA, with insulin as first autoantibody (adjusted hazard ratio 1.71 [95% CI 1.14; 2.58]) compared with moderate iron intake. CONCLUSIONS: Iron intake may alter the risk of IA in children with high-risk HLA haplogenotypes. [ABSTRACT FROM AUTHOR]

Published
2023
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44. Gluten-free diet adherence in children with screening-detected celiac disease using a prospective birth cohort study.

Author

Mehta, Pooja, Li, Qian, Stahl, Marisa, Uusitalo, Ulla, Lindfors, Katri, Butterworth, Martha D., Kurppa, Kalle, Virtanen, Suvi, Koletzko, Sibylle, Aronsson, Carin, Hagopian, William A., Rewers, Marian J., Toppari, Jorma, Ziegler, Anette-G., Akolkar, Beena, Krischer, Jeffrey P., Agardh, Daniel, and Liu, Edwin

Subjects
CELIAC disease, GLUTEN-free diet, COHORT analysis, FOOD consumption, KRUSKAL-Wallis Test, MULTIVARIABLE testing
Abstract

Background: Celiac disease has an increasing incidence worldwide and is treated with lifelong adherence to a gluten-free diet. We aimed to describe gluten-free diet adherence rates in children with screening-identified celiac disease, determine adherence-related factors, and compare adherence to food records in a multinational prospective birth cohort study. Methods: Children in The Environmental Determinants of Diabetes in the Young study with celiac disease were included. Subjects had at least annual measurement of adherence (parent-report) and completed 3-day food records. Descriptive statistics, t-tests, Kruskal-Wallis tests and multivariable logistic and linear regression were employed. Results: Two hundred ninety (73%) and 199 (67%) of subjects were always adherent to a gluten-free diet at 2 and 5 years post celiac disease diagnosis respectively. The percentage of children with variable adherence increased from 1% at 2 years to 15% at 5 years. Children with a first-degree relative with celiac disease were more likely to be adherent to the gluten-free diet. Gluten intake on food records could not differentiate adherent from nonadherent subjects. Adherent children from the United States had more gluten intake based on food records than European children (P <.001 and P =.007 at 2 and 5 years respectively). Conclusion: Approximately three-quarters of children with screening-identified celiac disease remain strictly adherent to a gluten-free diet over time. There are no identifiable features associated with adherence aside from having a first-degree relative with celiac disease. Despite good parent-reported adherence, children from the United States have more gluten intake when assessed by food records. Studies on markers of gluten-free diet adherence, sources of gluten exposure (particularly in the United States), and effects of adherence on mucosal healing are needed. [ABSTRACT FROM AUTHOR]

Published
2023
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46. Heterogeneity of DKA Incidence and Age-Specific Clinical Characteristics in Children Diagnosed With Type 1 Diabetes in the TEDDY Study

Author

Jacobsen, Laura M., primary, Vehik, Kendra, primary, Veijola, Riitta, primary, Warncke, Katharina, primary, Toppari, Jorma, primary, Steck, Andrea K., primary, Gesualdo, Patricia, primary, Akolkar, Beena, primary, Lundgren, Markus, primary, Hagopian, William A., primary, She, Jin-Xiong, primary, Rewers, Marian, primary, Ziegler, Anette G., primary, Krischer, Jeffrey P., primary, Larsson, Helena Elding, primary, Haller, Michael J., primary, and Group, the TEDDY Study, primary

Published
2022
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47. Transcriptional networks in at-risk individuals identify signatures of type 1 diabetes progression

Author

Xhonneux, Louis-Pascal, Knight, Oliver, Lernmark, Åke, Bonifacio, Ezio, Hagopian, William A, Rewers, Marian J, She, Jin-Xiong, Toppari, Jorma, Parikh, Hemang, Smith, Kenneth GC, Ziegler, Anette-G, Akolkar, Beena, Krischer, Jeffrey P, McKinney, Eoin F, Xhonneux, Louis-Pascal [0000-0003-1990-4475], Knight, Oliver [0000-0002-0424-2379], Lernmark, Åke [0000-0003-1735-0499], Bonifacio, Ezio [0000-0002-8704-4713], Hagopian, William A [0000-0003-2979-0475], Rewers, Marian J [0000-0003-3829-9207], She, Jin-Xiong [0000-0002-0966-6381], Toppari, Jorma [0000-0003-2228-334X], Parikh, Hemang [0000-0002-9076-6709], Smith, Kenneth GC [0000-0003-3829-4326], Ziegler, Anette-G [0000-0002-6290-5548], Akolkar, Beena [0000-0002-2351-5942], McKinney, Eoin F [0000-0003-3516-3072], and Apollo - University of Cambridge Repository

Subjects
endocrine system, Islets of Langerhans, Diabetes Mellitus, Type 1, endocrine system diseases, Disease Progression, Humans, Autoimmunity, Bayes Theorem, Gene Regulatory Networks, Genetic Predisposition to Disease, Prospective Studies, Autoantibodies
Abstract

Type 1 diabetes (T1D) is a disease of insulin deficiency that results from autoimmune destruction of pancreatic islet β cells. The exact cause of T1D remains unknown, although asymptomatic islet autoimmunity lasting from weeks to years before diagnosis raises the possibility of intervention before the onset of clinical disease. The number, type, and titer of islet autoantibodies are associated with long-term disease risk but do not cause disease, and robust early predictors of individual progression to T1D onset remain elusive. The Environmental Determinants of Diabetes in the Young (TEDDY) consortium is a prospective cohort study aiming to determine genetic and environmental interactions causing T1D. Here, we analyzed longitudinal blood transcriptomes of 2013 samples from 400 individuals in the TEDDY study before both T1D and islet autoimmunity. We identified and interpreted age-associated gene expression changes in healthy infancy and age-independent changes tracking with progression to both T1D and islet autoimmunity, beginning before other evidence of islet autoimmunity was present. We combined multivariate longitudinal data in a Bayesian joint model to predict individual risk of T1D onset and validated the association of a natural killer cell signature with progression and the model's predictive performance on an additional 356 samples from 56 individuals in the independent Type 1 Diabetes Prediction and Prevention study. Together, our results indicate that T1D is characterized by early and longitudinal changes in gene expression, informing the immunopathology of disease progression and facilitating prediction of its course.

Published
2021

48. Telomere Length is Not a Main factor for the Development of Islet Autoimmunity and Type 1 Diabetes in the TEDDY Study

Author

Parikh, Hemang, primary, Törn, Carina, additional, Liu, Xiang, additional, Onengut-Gumuscu, Suna, additional, Counts, Kevin, additional, Moreno, Jose, additional, Remedios, Cassandra, additional, Chen, Wei-Min, additional, LeFaive, Jonathon, additional, Butterworth, Martha, additional, Akolkar, Beena, additional, Krischer, Jeffrey, additional, Lernmark, Åke, additional, Rewers, Marian, additional, She, Jin-Xiong, additional, Toppari, Jorma, additional, Ziegler, Anette-Gabriele, additional, Ratan, Aakrosh, additional, Smith, Albert, additional, Hagopian, William, additional, and Rich, Stephen, additional

Published
2021
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49. HbA1c as a time predictive biomarker for an additional islet autoantibody and type 1 diabetes in seroconverted TEDDY children.

Author

Salami, Falastin, Tamura, Roy, You, Lu, Lernmark, Åke, Larsson, Helena Elding, Lundgren, Markus, Krischer, Jeffrey, Ziegler, Anette‐Gabriele, Toppari, Jorma, Veijola, Riitta, Rewers, Marian, Haller, Michael J., Hagopian, William, Akolkar, Beena, and Törn, Carina

Subjects
GLYCOSYLATED hemoglobin, BIOMARKERS, AUTOANTIBODIES, DISEASE progression, SOCIAL determinants of health, CONFIDENCE intervals, TYPE 1 diabetes, SEROCONVERSION, RISK assessment, DESCRIPTIVE statistics, LONGITUDINAL method, DISEASE risk factors
Abstract

Objective: Increased level of glycated hemoglobin (HbA1c) is associated with type 1 diabetes onset that in turn is preceded by one to several autoantibodies against the pancreatic islet beta cell autoantigens; insulin (IA), glutamic acid decarboxylase (GAD), islet antigen‐2 (IA‐2) and zinc transporter 8 (ZnT8). The risk for type 1 diabetes diagnosis increases by autoantibody number. Biomarkers predicting the development of a second or a subsequent autoantibody and type 1 diabetes are needed to predict disease stages and improve secondary prevention trials. This study aimed to investigate whether HbA1c possibly predicts the progression from first to a subsequent autoantibody or type 1 diabetes in healthy children participating in the Environmental Determinants of Diabetes in the Young (TEDDY) study. Research Design and Methods: A joint model was designed to assess the association of longitudinal HbA1c levels with the development of first (insulin or GAD autoantibodies) to a second, second to third, third to fourth autoantibody or type 1 diabetes in healthy children prospectively followed from birth until 15 years of age. Results: It was found that increased levels of HbA1c were associated with a higher risk of type 1 diabetes (HR 1.82, 95% CI [1.57–2.10], p < 0.001) regardless of first appearing autoantibody, autoantibody number or type. A decrease in HbA1c levels was associated with the development of IA‐2A as a second autoantibody following GADA (HR 0.85, 95% CI [0.75, 0.97], p = 0.017) and a fourth autoantibody following GADA, IAA and ZnT8A (HR 0.90, 95% CI [0.82, 0.99], p = 0.036). HbA1c trajectory analyses showed a significant increase of HbA1c over time (p < 0.001) and that the increase is more rapid as the number of autoantibodies increased from one to three (p < 0.001). Conclusion: In conclusion, increased HbA1c is a reliable time predictive marker for type 1 diabetes onset. The increased rate of increase of HbA1c from first to third autoantibody and the decrease in HbA1c predicting the development of IA‐2A are novel findings proving the link between HbA1c and the appearance of autoantibodies. [ABSTRACT FROM AUTHOR]

Published
2022
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50. Rising Hemoglobin A1c in the Nondiabetic Range Predicts Progression of Type 1 Diabetes As Well As Oral Glucose Tolerance Tests.

Author

Vehik, Kendra, Boulware, David, Killian, Michael, Rewers, Marian, McIndoe, Richard, Toppari, Jorma, Lernmark, Åke, Akolkar, Beena, Ziegler, Anette-G., Rodriguez, Henry, Schatz, Desmond A., Krischer, Jeffrey P., Hagopian, William, The TEDDY Study Group Colorado Clinical Center, Barbour, Aaron, Bautista, Kimberly, Baxter, Judith, Felipe-Morales, Daniel, Frohnert, Brigitte I., and Stahl, Marisa

Subjects
BLOOD sugar analysis, AUTOANTIBODIES, RESEARCH, RESEARCH methodology, TYPE 1 diabetes, EVALUATION research, COMPARATIVE studies, GLUCOSE tolerance tests, LONGITUDINAL method
Abstract

Objective: Biomarkers predicting risk of type 1 diabetes (stage 3) among children with islet autoantibodies are greatly needed to prevent diabetic ketoacidosis and facilitate prevention therapies.Research Design and Methods: Children in the prospective The Environmental Determinants of Diabetes in the Young (TEDDY) study (n = 707) with confirmed diabetes-associated autoantibodies (GAD antibody, IA-2A, and/or insulin autoantibody) and two or more HbA1c measurements were followed to diabetes or median age 11.1 years. Once confirmed autoantibody positive, HbA1c was measured quarterly. Cox models and receiver operative characteristic curve analyses revealed the prognostic utility for risk of stage 3 on a relative HbA1c increase from the baseline visit or an oral glucose tolerance test (OGTT) 2-h plasma glucose (2-hPG). This HbA1c approach was then validated in the Type 1 Diabetes TrialNet Pathway to Prevention Study (TrialNet) (n = 1,190).Results: A 10% relative HbA1c increase from baseline best marked the increased risk of stage 3 in TEDDY (74% sensitive; 88% specific). Significant predictors of risk for HbA1c change were age and HbA1c at the baseline test, genetic sex, maximum number of autoantibodies, and maximum rate of HbA1c increase by time of change. The multivariable model featuring a HbA1c ≥10% increase and these additional factors revealed increased risk of stage 3 in TEDDY (hazard ratio [HR] 12.74, 95% CI 8.7-18.6, P < 0.0001) and TrialNet (HR 5.09, 95% CI 3.3-7.9, P < 0.0001). Furthermore, the composite model using HbA1c ≥10% increase performed similarly to an OGTT 2-hPG composite model (TEDDY area under the curve [AUC] 0.88 and 0.85, respectively) and to the HbA1c model in TrialNet (AUC 0.82).Conclusions: An increase of ≥10% in HbA1c from baseline is as informative as OGTT 2-hPG in predicting risk of stage 3 in youth with genetic risk and diabetes-associated autoantibodies. [ABSTRACT FROM AUTHOR]

Published
2022
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