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2. Distinct transcriptomic profiles in children prior to the appearance of type 1 diabetes-linked islet autoantibodies and following enterovirus infection

Author

Lin, Jake, Moradi, Elaheh, Salenius, Karoliina, Lehtipuro, Suvi, Häkkinen, Tomi, Laiho, Jutta E., Oikarinen, Sami, Randelin, Sofia, Parikh, Hemang M., Krischer, Jeffrey P., Toppari, Jorma, Lernmark, Åke, Petrosino, Joseph F., Ajami, Nadim J., She, Jin-Xiong, Hagopian, William A., Rewers, Marian J., Lloyd, Richard E., Rautajoki, Kirsi J., Hyöty, Heikki, and Nykter, Matti

Published
2023
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3. 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

4. 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

6. 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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8. Associations of breastfeeding with childhood autoimmunity, allergies, and overweight: The Environmental Determinants of Diabetes in the Young (TEDDY) study

Author

Hummel, Sandra, Weiß, Andreas, Bonifacio, Ezio, Agardh, Daniel, Akolkar, Beena, Aronsson, Carin A, Hagopian, William A, Koletzko, Sibylle, Krischer, Jeffrey P, Lernmark, Åke, Lynch, Kristian, Norris, Jill M, Rewers, Marian J, She, Jin-Xiong, Toppari, Jorma, Uusitalo, Ulla, Vehik, Kendra, Virtanen, Suvi M, Beyerlein, Andreas, and Ziegler, Anette-G

Published
2021
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16. A combined risk score enhances prediction of type 1 diabetes among susceptible children

Author

Ferrat, Lauric A., Vehik, Kendra, Sharp, Seth A., Lernmark, Åke, Rewers, Marian J., She, Jin-Xiong, and Ziegler, Anette-G.

Subjects
Type 1 diabetes -- Diagnosis -- Risk factors, Genetic susceptibility -- Identification and classification -- Health aspects -- Measurement, Islet cell stimulating antibodies -- Health aspects -- Measurement, Biological sciences, Health
Abstract

Type 1 diabetes (T1D)--an autoimmune disease that destroys the pancreatic islets, resulting in insulin deficiency--often begins early in life when islet autoantibody appearance signals high risk.sup.1. However, clinical diabetes can follow in weeks or only after decades, and is very difficult to predict. Ketoacidosis at onset remains common.sup.2,3 and is most severe in the very young.sup.4,5, in whom it can be life threatening and difficult to treat.sup.6-9. Autoantibody surveillance programs effectively prevent most ketoacidosis.sup.10-12 but require frequent evaluations whose expense limits public health adoption.sup.13. Prevention therapies applied before onset, when greater islet mass remains, have rarely been feasible.sup.14 because individuals at greatest risk of impending T1D are difficult to identify. To remedy this, we sought accurate, cost-effective estimation of future T1D risk by developing a combined risk score incorporating both fixed and variable factors (genetic, clinical and immunological) in 7,798 high-risk children followed closely from birth for 9.3 years. Compared with autoantibodies alone, the combined model dramatically improves T1D prediction at [greater than or equal to]2 years of age over horizons up to 8 years of age (area under the receiver operating characteristic curve [greater than or equal to] 0.9), doubles the estimated efficiency of population-based newborn screening to prevent ketoacidosis, and enables individualized risk estimates for better prevention trial selection. In a study of children with high genetic risk aged 2 years or older, a risk score integrating pancreatic islet autoantibodies, genetic factors and family history is highly predictive of type 1 diabetes in the subsequent 8 years., Author(s): Lauric A. Ferrat [sup.1] , Kendra Vehik [sup.2] , Seth A. Sharp [sup.1] , Åke Lernmark [sup.3] , Marian J. Rewers [sup.4] , Jin-Xiong She [sup.5] , Anette-G. Ziegler [...]

Published
2020
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19. 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

25. 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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27. 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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28. 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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29. 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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31. 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

Ullitz Thorsen, Steffen, Liu, Xiang, Kataria, Yachana, Mandrup-poulsen, Thomas, Kaur, Simranjeet, Uusitalo, Ulla, Virtanen, Suvi M., Norris, Jill, Rewers, Marian, Hagopian, William, Yang, Jimin, She, Jin-xiong, Akolkar, Beena, Rich, Stephen S., Aronsson, Carin Andrén, Lernmark, Åke, Ziegler, Anette-gabriele, Toppari, Jorma, Krischer, Jeffrey P., Parikh, Hemang M., Ellervik, Christina, Svensson, Jannet, Barbour, Aaron, Bautista, Kimberly, Baxter, Judith, Felipe-morales, Daniel, Frohnert, Brigitte I., Stahl, Marisa, Gesualdo, Patricia, Hoffman, Michelle, Karban, Rachel, Liu, Edwin, Munoz, Alondra, O’donnell, Holly, Peacock, Stesha, Shorrosh, Hanan, Steck, Andrea, Stern, Megan, Waugh, Kathleen, Simell, Olli G., Adamsson, Annika, Ahonen, Suvi, Åkerlund, Mari, Anttila, Sirpa, Hakola, Leena, Hekkala, Anne, Agardh, Daniel, Ullitz Thorsen, Steffen, Liu, Xiang, Kataria, Yachana, Mandrup-poulsen, Thomas, Kaur, Simranjeet, Uusitalo, Ulla, Virtanen, Suvi M., Norris, Jill, Rewers, Marian, Hagopian, William, Yang, Jimin, She, Jin-xiong, Akolkar, Beena, Rich, Stephen S., Aronsson, Carin Andrén, Lernmark, Åke, Ziegler, Anette-gabriele, Toppari, Jorma, Krischer, Jeffrey P., Parikh, Hemang M., Ellervik, Christina, Svensson, Jannet, Barbour, Aaron, Bautista, Kimberly, Baxter, Judith, Felipe-morales, Daniel, Frohnert, Brigitte I., Stahl, Marisa, Gesualdo, Patricia, Hoffman, Michelle, Karban, Rachel, Liu, Edwin, Munoz, Alondra, O’donnell, Holly, Peacock, Stesha, Shorrosh, Hanan, Steck, Andrea, Stern, Megan, Waugh, Kathleen, Simell, Olli G., Adamsson, Annika, Ahonen, Suvi, Åkerlund, Mari, Anttila, Sirpa, Hakola, Leena, Hekkala, Anne, and Agardh, Daniel

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.

Published
2023

32. 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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35. 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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42. 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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46. 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. The Anti-carbohydrate antibody repertoire in type 1 diabetes

Author

Tran, Paul, primary, Dong, Fran, additional, Kin, Eileen, additional, Richardson, Katherine, additional, Tran, Lynn, additional, Waugh, Kathleen, additional, Hopkins, Diane, additional, Cummings, Richard, additional, Wang, Peng George, additional, Rewers, Marian, additional, She, Jin-Xiong, additional, and Purohit, Sharad, additional

Published
2022
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