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2. Consensus guidance for monitoring individuals with islet autoantibody-positive pre-stage 3 type 1 diabetes

Author

Phillip, Moshe, Achenbach, Peter, Addala, Ananta, Albanese-O’Neill, Anastasia, Battelino, Tadej, Bell, Kirstine J., Besser, Rachel E. J., Bonifacio, Ezio, Colhoun, Helen M., Couper, Jennifer J., Craig, Maria E., Danne, Thomas, de Beaufort, Carine, Dovc, Klemen, Driscoll, Kimberly A., Dutta, Sanjoy, Ebekozien, Osagie, Larsson, Helena Elding, Feiten, Daniel J., Frohnert, Brigitte I., Gabbay, Robert A., Gallagher, Mary P., Greenbaum, Carla J., Griffin, Kurt J., Hagopian, William, Haller, Michael J., Hendrieckx, Christel, Hendriks, Emile, Holt, Richard I. G., Hughes, Lucille, Ismail, Heba M., Jacobsen, Laura M., Johnson, Suzanne B., Kolb, Leslie E., Kordonouri, Olga, Lange, Karin, Lash, Robert W., Lernmark, Åke, Libman, Ingrid, Lundgren, Markus, Maahs, David M., Marcovecchio, M. Loredana, Mathieu, Chantal, Miller, Kellee M., O’Donnell, Holly K., Oron, Tal, Patil, Shivajirao P., Pop-Busui, Rodica, Rewers, Marian J., Rich, Stephen S., Schatz, Desmond A., Schulman-Rosenbaum, Rifka, Simmons, Kimber M., Sims, Emily K., Skyler, Jay S., Smith, Laura B., Speake, Cate, Steck, Andrea K., Thomas, Nicholas P. B., Tonyushkina, Ksenia N., Veijola, Riitta, Wentworth, John M., Wherrett, Diane K., Wood, Jamie R., Ziegler, Anette-Gabriele, and DiMeglio, Linda A.

Published
2024
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4. Correction to: Consensus guidance for monitoring individuals with islet autoantibody‑positive pre‑stage 3 type 1 diabetes

Author

Phillip, Moshe, Achenbach, Peter, Addala, Ananta, Albanese‑O’Neill, Anastasia, Battelino, Tadej, Bell, Kirstine J., Besser, Rachel E. J., Bonifacio, Ezio, Colhoun, Helen M., Couper, Jennifer J., Craig, Maria E., Danne, Thomas, de Beaufort, Carine, Dovc, Klemen, Driscoll, Kimberly A., Dutta, Sanjoy, Ebekozien, Osagie, Larsson, Helena Elding, Feiten, Daniel J., Frohnert, Brigitte I., Gabbay, Robert A., Gallagher, Mary P., Greenbaum, Carla J., Griffin, Kurt J., Hagopian, William, Haller, Michael J., Hendrieckx, Christel, Hendriks, Emile, Holt, Richard I. G., Hughes, Lucille, Ismail, Heba M., Jacobsen, Laura M., Johnson, Suzanne B., Kolb, Leslie E., Kordonouri, Olga, Lange, Karin, Lash, Robert W., Lernmark, Åke, Libman, Ingrid, Lundgren, Markus, Maahs, David M., Marcovecchio, M. Loredana, Mathieu, Chantal, Miller, Kellee M., O’Donnell, Holly K., Oron, Tal, Patil, Shivajirao P., Pop‑Busui, Rodica, Rewers, Marian J., Rich, Stephen S., Schatz, Desmond A., Schulman‑Rosenbaum, Rifka, Simmons, Kimber M., Sims, Emily K., Skyler, Jay S., Smith, Laura B., Speake, Cate, Steck, Andrea K., Thomas, Nicholas P. B., Tonyushkina, Ksenia N., Veijola, Riitta, Wentworth, John M., Wherrett, Diane K., Wood, Jamie R., Ziegler, Anette‑Gabriele, and DiMeglio, Linda A.

Published
2024
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5. 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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6. Assisting the implementation of screening for type 1 diabetes by using artificial intelligence on publicly available data

Author

Teixeira, Pedro F., Battelino, Tadej, Carlsson, Anneli, Gudbjörnsdottir, Soffia, Hannelius, Ulf, von Herrath, Matthias, Knip, Mikael, Korsgren, Olle, Elding Larsson, Helena, Lindqvist, Anton, Ludvigsson, Johnny, Lundgren, Markus, Nowak, Christoph, Pettersson, Paul, Pociot, Flemming, Sundberg, Frida, Åkesson, Karin, Lernmark, Åke, and Forsander, Gun

Published
2024
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7. Type 1 diabetes, celiac disease, and autoimmune thyroiditis autoantibodies in population-based type 2 diabetes patients

Author

Lind Alexander, Tsai Cheng-ting, Lernmark Åke, and Jendle Johan

Subjects
Type 1 diabetes, Type 2 diabetes, Celiac disease, Autoimmune thyroid disease, Autoantibodies, Diseases of the endocrine glands. Clinical endocrinology, RC648-665
Abstract

Aims: The study aims were to determine autoantibodies associated with type 1 diabetes (T1D), celiac disease (CD) and autoimmune thyroid disease (AITD) in individuals living with type 2 diabetes (T2D) compared to T1D and matched controls. Methods: Individuals with T1D and T2D were randomly identified in health-care registers. Blood was collected through home-capillary sampling and autoantibodies associated with either T1D against glutamic acid decarboxylase (GADA), insulin (IAA), insulinoma antigen-2 (IA-2A), and zinc transporter 8 (ZnT8A), CD against tissue transglutaminase (tTGA) or AITD against thyroid peroxidase (TPOA) were determined in an automated, multiplex Antibody Detection by Agglutination-PCR (ADAP) assay. Results: GADA were detected in 46 % (88/191) of T1D and increased to 6.2 % (23/372) in T2D compared to 2.6 % (7/259) of controls (p = 0.0367). tTGA was low (1.1–2.6 %) and not different in between the study cohorts, nonetheless, in T1D tTGA was associated to islet autoantibodies. TPOA was more frequent in T1D, 27.1 % (53/191), compared to either T2D, 14.8 % (55/372; p = 0.0002) or controls, 14.3 % (37/259) (p = 0.0004). Overall, TPOA was more frequent in GADA positive (34.8 %; 8/23) than negative (13.5 %; 47/349; p = 0.0053) T2D individuals. Conclusion: It’s suggested that analyzing GADA and TPOA may refine the autoimmune landscape in individuals clinically classified as T2D.

Published
2024
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8. Childhood screening for type 1 diabetes comparing automated multiplex Antibody Detection by Agglutination-PCR (ADAP) with single plex islet autoantibody radiobinding assays

Author

Persson, Martina, Forsander, Gun, Ludvigsson, Johnny, Samuelsson, Ulf, Marcus, Claude, Lind, Alexander, Freyhult, Eva, de Jesus Cortez, Felipe, Ramelius, Anita, Bennet, Rasmus, Robinson, Peter V., Seftel, David, Gebhart, David, Tandel, Devangkumar, Maziarz, Marlena, Larsson, Helena Elding, Lundgren, Markus, Carlsson, Annelie, Nilsson, Anna-Lena, Fex, Malin, Törn, Carina, Agardh, Daniel, Tsai, Cheng-ting, and Lernmark, Åke

Published
2024
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9. 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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11. Anxiety, depression and quality of life in relation to SARS-CoV-2 antibodies in individuals living with diabetes during the second wave of COVID-19

Author

Lind Alexander, Cao Yang, Hesser Hugo, Hårdstedt Maria, Jansson Stefan, Lernmark Åke, Sundqvist Martin, Tevell Staffan, Tsai Cheng-ting, Wahlberg Jeanette, and Jendle Johan

Subjects
Diabetes, SARS-CoV-2, COVID-19, Anxiety, Depression, Quality of life, Diseases of the endocrine glands. Clinical endocrinology, RC648-665
Abstract

Aims: The objective was to compare anxiety, depression, and quality of life (QoL) in individuals living with type 1 (T1D) and type 2 (T2D) diabetes with matched controls during the second wave of the COVID-19 pandemic. Methods: Via randomization, individuals living with diabetes T1D (n = 203) and T2D (n = 413), were identified during February-July 2021 through health-care registers. Population controls (n = 282) were matched for age, gender, and residential area. Questionnaires included self-assessment of anxiety, depression, QoL, and demographics in relation to SARS-CoV-2 exposure. Blood was collected through home-capillary sampling, and SARS-CoV-2 Nucleocapsid (NCP) and Spike antibodies (SC2_S1) were determined by multiplex Antibody Detection by Agglutination-PCR (ADAP) assays. Results: Younger age and health issues were related to anxiety, depression, and QoL, with no differences between the study groups. Female gender was associated with anxiety, while obesity was associated with lower QoL. The SARS‑CoV‑2 NCP seroprevalence was higher in T1D (8.9 %) compared to T2D (3.9 %) and controls (4.0 %), while the SARS‑CoV‑2 SC2_S1 seroprevalence was higher for controls (25.5 %) compared to T1D (16.8 %) and T2D (14.0 %). Conclusions: A higher SARS‑CoV‑2 infection rate in T1D may be explained by younger age and higher employment rate, and the associated increased risk for viral exposure.

Published
2024
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12. 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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13. 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

14. Childhood screening for type 1 diabetes comparing automated multiplex Antibody Detection by Agglutination-PCR (ADAP) with single plex islet autoantibody radiobinding assays

Author

Lind, Alexander, primary, Freyhult, Eva, additional, de Jesus Cortez, Felipe, additional, Ramelius, Anita, additional, Bennet, Rasmus, additional, Robinson, Peter V., additional, Seftel, David, additional, Gebhart, David, additional, Tandel, Devangkumar, additional, Maziarz, Marlena, additional, Larsson, Helena Elding, additional, Lundgren, Markus, additional, Carlsson, Annelie, additional, Nilsson, Anna-Lena, additional, Fex, Malin, additional, Törn, Carina, additional, Agardh, Daniel, additional, Tsai, Cheng-ting, additional, Lernmark, Åke, additional, Persson, Martina, additional, Forsander, Gun, additional, Ludvigsson, Johnny, additional, Samuelsson, Ulf, additional, and Marcus, Claude, additional

Published
2024
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15. 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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16. 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

19. 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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20. Oral Insulin Delay of Stage 3 Type 1 Diabetes Revisited in HLA DR4-DQ8 Participants in the TrialNet Oral Insulin Prevention Trial (TN07).

Author

Zhao, Lue Ping, Papadopoulos, George K., Skyler, Jay S., Parikh, Hemang M., Kwok, William W., Bondinas, George P., Moustakas, Antonis K., Wang, Ruihan, Pyo, Chul-Woo, Nelson, Wyatt C., Geraghty, Daniel E., and Lernmark, Åke

Subjects
TYPE 1 diabetes, HAPLOTYPES, REGRESSION analysis, INSULIN, AUTOANTIBODIES
Abstract

OBJECTIVE: To explore if oral insulin could delay onset of stage 3 type 1 diabetes (T1D) among patients with stage 1/2 who carry HLA DR4-DQ8 and/or have elevated levels of IA-2 autoantibodies (IA-2As). RESEARCH AND METHODS: Next-generation targeted sequencing technology was used to genotype eight HLA class II genes (DQA1 , DQB1 , DRB1 , DRB3 , DRB4 , DRB5 , DPA1 , and DPB1) in 546 participants in the TrialNet oral insulin preventative trial (TN07). Baseline levels of autoantibodies against insulin (IAA), GAD65 (GADA), and IA-2A were determined prior to treatment assignment. Available clinical and demographic covariables from TN07 were used in this post hoc analysis with the Cox regression model to quantify the preventive efficacy of oral insulin. RESULTS: Oral insulin reduced the frequency of T1D onset among participants with elevated IA-2A levels (HR 0.62; P = 0.012) but had no preventive effect among those with low IA-2A levels (HR 1.03; P = 0.91). High IA-2A levels were positively associated with the HLA DR4-DQ8 haplotype (OR 1.63; P = 6.37 × 10−6) and negatively associated with the HLA DR7– containing DRB1*07:01-DRB4*01:01-DQA1*02:01-DQB1*02:02 extended haplotype (OR 0.49; P = 0.037). Among DR4-DQ8 carriers, oral insulin delayed the progression toward stage 3 T1D onset (HR 0.59; P = 0.027), especially if participants also had high IA-2A level (HR 0.50; P = 0.028). CONCLUSIONS: These results suggest the presence of a T1D endotype characterized by HLA DR4-DQ8 and/or elevated IA-2A levels; for those patients with stage 1/2 disease with such an endotype, oral insulin delays the clinical T1D onset. [ABSTRACT FROM AUTHOR]

Published
2024
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21. Understanding and preventing type 1 diabetes through the unique working model of TrialNet

Author

Battaglia, Manuela, Anderson, Mark S, Buckner, Jane H, Geyer, Susan M, Gottlieb, Peter A, Kay, Thomas WH, Lernmark, Åke, Muller, Sarah, Pugliese, Alberto, Roep, Bart O, Greenbaum, Carla J, and Peakman, Mark

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Clinical Research, Pediatric, Prevention, Autoimmune Disease, Diabetes, Metabolic and endocrine, Autoimmune Diseases, Autoimmunity, Diabetes Mellitus, Type 1, Humans, Mechanistic studies, Review, Type 1 diabetes, Paediatrics and Reproductive Medicine, Public Health and Health Services, Endocrinology & Metabolism, Clinical sciences, Public health
Abstract

Type 1 diabetes is an autoimmune disease arising from the destruction of pancreatic insulin-producing beta cells. The disease represents a continuum, progressing sequentially at variable rates through identifiable stages prior to the onset of symptoms, through diagnosis and into the critical periods that follow, culminating in a variable depth of beta cell depletion. The ability to identify the very earliest of these presymptomatic stages has provided a setting in which prevention strategies can be trialled, as well as furnishing an unprecedented opportunity to study disease evolution, including intrinsic and extrinsic initiators and drivers. This niche opportunity is occupied by Type 1 Diabetes TrialNet, an international consortium of clinical trial centres that leads the field in intervention and prevention studies, accompanied by deep longitudinal bio-sampling. In this review, we focus on discoveries arising from this unique bioresource, comprising more than 70,000 samples, and outline the processes and science that have led to new biomarkers and mechanistic insights, as well as identifying new challenges and opportunities. We conclude that via integration of clinical trials and mechanistic studies, drawing in clinicians and scientists and developing partnership with industry, TrialNet embodies an enviable and unique working model for understanding a disease that to date has no cure and for designing new therapeutic approaches.

Published
2017

22. HLA Class II (DR, DQ, DP) genes were separately associated with the progression from seroconversion to onset of type 1 diabetes among participants in two diabetes prevention trials (DPT-1 and TN07)

Author

Ping Zhao, Lue, primary, K. Papadopoulos, George, primary, S. Skyler, Jay, primary, Pugliese, Alberto, primary, M. Parikh, Hemang, primary, Kwok, Bill, primary, P. Lybrand, Terry, primary, P. Bondinas, George, primary, K. Moustakas, Antonis, primary, Wang, Ruihan, primary, Pyo, Chul-Woo, primary, C. Nelson, Wyatt, primary, E. Geraghty, Daniel, primary, and Lernmark, Åke, primary

Published
2024
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23. HLA Class II (DR, DQ, DP) Genes Were Separately Associated With the Progression From Seroconversion to Onset of Type 1 Diabetes Among Participants in Two Diabetes Prevention Trials (DPT-1 and TN07)

Author

Zhao, Lue Ping, primary, Papadopoulos, George K., additional, Skyler, Jay S., additional, Pugliese, Alberto, additional, Parikh, Hemang M., additional, Kwok, William W., additional, Lybrand, Terry P., additional, Bondinas, George P., additional, Moustakas, Antonis K., additional, Wang, Ruihan, additional, Pyo, Chul-Woo, additional, Nelson, Wyatt C., additional, Geraghty, Daniel E., additional, and Lernmark, Åke, additional

Published
2024
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24. Anxiety, depression and quality of life in relation to SARS-CoV-2 antibodies in individuals living with diabetes during the second wave of COVID-19

Author

Lind, Alexander, Cao, Yang, Hesser, Hugo, Hårdstedt, Maria, Jansson, Stefan P. O., Lernmark, Åke, Sundqvist, Martin, Tevell, Staffan, Tsai, Cheng-ting, Wahlberg, Jeanette, Jendle, Johan, Lind, Alexander, Cao, Yang, Hesser, Hugo, Hårdstedt, Maria, Jansson, Stefan P. O., Lernmark, Åke, Sundqvist, Martin, Tevell, Staffan, Tsai, Cheng-ting, Wahlberg, Jeanette, and Jendle, Johan

Abstract

Aims: The objective was to compare anxiety, depression, and quality of life (QoL) in individuals living with type 1 (T1D) and type 2 (T2D) diabetes with matched controls during the second wave of the COVID-19 pandemic. Methods: Via randomization, individuals living with diabetes T1D (n = 203) and T2D (n = 413), were identified during February-July 2021 through health-care registers. Population controls (n = 282) were matched for age, gender, and residential area. Questionnaires included self-assessment of anxiety, depression, QoL, and demographics in relation to SARS-CoV-2 exposure. Blood was collected through home-capillary sampling, and SARS-CoV-2 Nucleocapsid (NCP) and Spike antibodies (SC2_S1) were determined by multiplex Antibody Detection by Agglutination-PCR (ADAP) assays. Results: Younger age and health issues were related to anxiety, depression, and QoL, with no differences between the study groups. Female gender was associated with anxiety, while obesity was associated with lower QoL. The SARS-CoV-2 NCP seroprevalence was higher in T1D (8.9 %) compared to T2D (3.9 %) and controls (4.0 %), while the SARS-CoV-2 SC2_S1 seroprevalence was higher for controls (25.5 %) compared to T1D (16.8 %) and T2D (14.0 %). Conclusions: A higher SARS-CoV-2 infection rate in T1D may be explained by younger age and higher employment rate, and the associated increased risk for viral exposure., This work was supported by NIH SBIR 2R44DK110005-02, Strategic Research Area Exodiab Dnr 2009-1039, and the Swedish Foundation for Strategic Research Dnr IRC15-0067.

Published
2024
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28. 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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30. 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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31. 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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33. List of Contributors

Author

Abramson, Jakub, primary, Ahmed, S. Sohail, additional, Alba, Marco A., additional, Ali, Youssif M., additional, Ambrus, Julian L., additional, Andersson Svärd, Agnes, additional, Aringer, Martin, additional, Assassi, Shervin, additional, Aung, Thanda, additional, Ayzenberg, Ilya, additional, Barker, Robert N., additional, Baxter, Alan G., additional, Betterle, Corrado, additional, Birlea, Stanca A., additional, Björkström, Niklas K., additional, Blair, Paul A., additional, Blüml, Stephan, additional, Bosch, Xavier, additional, Brodsky, Robert A., additional, Bryceson, Yenan T., additional, Burkett, Patrick R., additional, Bussel, James B., additional, Caricchio, Roberto, additional, Casciola-Rosen, Livia, additional, Caturegli, Patrizio, additional, Chaigne-Delalande, Benjamin, additional, Chalan, Paulina, additional, Chatenoud, Lucienne, additional, Cohen, Philip L., additional, Cooper, Megan A., additional, Coppieters, Ken, additional, Crystal, Ronald G., additional, Culton, Donna A., additional, Damato, Valentina, additional, Davidson, Anne, additional, Delfino, Lorenzo, additional, Delves, Peter J., additional, Di Dalmazi, Giulia, additional, Diamond, Betty, additional, Diaz, Luis A., additional, Falk, Ronald J., additional, Fritzler, Marvin J., additional, Gallucci, Stefania, additional, Gangaputra, Sapna, additional, Gelbman, Brian, additional, Gershwin, M. Eric, additional, Gery, Igal, additional, Getts, Daniel R., additional, Gold, Ralf, additional, Goldfarb, Yael, additional, Gong, Jing, additional, Gordon, Siamon, additional, Goronzy, Jörg J., additional, Greer, Judith M., additional, Guazzone, Vanesa A., additional, Guilherme, Luiza, additional, Hafler, David A., additional, Hahn, Bevra H., additional, Hamad, Abdel Rahim A., additional, Hamano, Hideaki, additional, Harrison, Leonard C., additional, Homann, Dirk, additional, Husebye, Eystein S., additional, Jennette, J. Charles, additional, Jones, Richard J., additional, Jordan, Margaret A., additional, Kalil, Jorge, additional, Kawa, Shigeyuki, additional, Kaya, Ziya, additional, Keller, Christian W., additional, King, Nicholas J.C., additional, Kitcharoensakkul, Maleewan, additional, Kiyosawa, Kendo, additional, Königs, Christoph, additional, Kronenberg, Mitchell, additional, Kuchroo, Vijay K., additional, Laurence, Arian, additional, Lee, Eun-Ju, additional, Lehmann, Helmar C., additional, Lernmark, Åke, additional, Lindbladh, Ida, additional, Liu, Zhi, additional, Ljunggren, Hans-Gustaf, additional, Lunardi, Claudio, additional, Lundin, Knut E.A., additional, Lünemann, Jan D., additional, Lunn, Michael P.T., additional, Lustig, Livia, additional, Mackay, Charles R., additional, Mackay, Ian R., additional, Malattia, Clara, additional, Martinez-Pomares, Luisa, additional, Martini, Alberto, additional, Mauri, Claudia, additional, McCombe, Pamela A., additional, Melchers, Fritz, additional, Mieli-Vergani, Giorgina, additional, Miller, Frederick W., additional, Miller, Stephen D., additional, Mizui, Masayuki, additional, Mjösberg, Jenny, additional, Münz, Christian, additional, Nijjar, Jagtar Singh, additional, Norris, David A., additional, Oleinika, Kristine, additional, Oppenheim, Joost J., additional, Pawlak, Mathias, additional, Peligero-Cruz, Cristina, additional, Peters, Anneli, additional, Peterson, Pärt, additional, Pitarokoili, Kalliopi, additional, Presotto, Fabio, additional, Puccetti, Antonio, additional, Rabb, Hamid, additional, Raczek, Patricia, additional, Rahman, M. Jubayer, additional, Ramos-Casals, Manuel, additional, Rose, Noel R., additional, Rosen, Antony, additional, Sadasivam, Mohanraj, additional, Schiffenbauer, Adam, additional, Schwaeble, Wilhelm J., additional, Sen, H. Nida, additional, Serota, Marc, additional, Sheikh, Kazim A., additional, Shoenfeld, Yehuda, additional, Shovman, Ora, additional, Sieper, Joachim, additional, Silverstein, Arthur M., additional, Sim, Robert B., additional, Smith, Kenneth G C, additional, Smolen, Josef S., additional, Sollid, Ludvig M., additional, Spiteri, Alanna, additional, Steinman, Lawrence, additional, Stone, John H., additional, Syrbe, Uta, additional, Tamhaney, Ami, additional, Tanaka, Atsushi, additional, Taneja, Veena, additional, Tarbell, Kristin V., additional, Tinazzi, Elisa, additional, Tiong, Benedict K., additional, Toh, Ban-Hock, additional, Tsokos, George C., additional, Tung, Kenneth S.K., additional, Varga, John, additional, Vergani, Diego, additional, Vickers, Mark A., additional, Viegas, Stuart, additional, Vincent, Angela, additional, von Herrath, Matthias, additional, Weetman, Anthony P., additional, Weinstock, Joel V., additional, Wentworth, John M., additional, Wesley, Sarah, additional, Weyand, Cornelia M., additional, Wingender, Gerhard, additional, Winter, Michael W., additional, Zanchetta, Renato, additional, and Zouali, Moncef, additional

Published
2020
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36. Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables

Author

Ahlqvist, Emma, Storm, Petter, Käräjämäki, Annemari, Martinell, Mats, Dorkhan, Mozhgan, Carlsson, Annelie, Vikman, Petter, Prasad, Rashmi B, Aly, Dina Mansour, Almgren, Peter, Wessman, Ylva, Shaat, Nael, Spégel, Peter, Mulder, Hindrik, Lindholm, Eero, Melander, Olle, Hansson, Ola, Malmqvist, Ulf, Lernmark, Åke, Lahti, Kaj, Forsén, Tom, Tuomi, Tiinamaija, Rosengren, Anders H, and Groop, Leif

Published
2018
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38. Meta-Immunological Profiling of Children With Type 1 Diabetes Identifies New Biomarkers to Monitor Disease Progression

Author

Galgani, Mario, Nugnes, Rosa, Bruzzese, Dario, Perna, Francesco, De Rosa, Veronica, Procaccini, Claudio, Mozzillo, Enza, Cilio, Corrado M, Larsson, Helena Elding, Lernmark, Åke, La Cava, Antonio, Franzese, Adriana, and Matarese, Giuseppe

Subjects
Diabetes, Autoimmune Disease, Nutrition, Clinical Research, Pediatric, Detection, screening and diagnosis, 2.1 Biological and endogenous factors, 4.1 Discovery and preclinical testing of markers and technologies, Aetiology, Metabolic and endocrine, Autoimmunity, Biomarkers, Child, Diabetes Mellitus, Type 1, Disease Progression, Flow Cytometry, Humans, Insulin-Secreting Cells, Monitoring, Immunologic, Prognosis, T-Lymphocytes, Medical and Health Sciences, Endocrinology & Metabolism
Abstract

Type 1 diabetes is characterized by autoimmune destruction of pancreatic β-cells in genetically susceptible individuals. Triggers of islet autoimmunity, time course, and the precise mechanisms responsible for the progressive β-cell failure are not completely understood. The recent escalation of obesity in affluent countries has been suggested to contribute to the increased incidence of type 1 diabetes. Understanding the link between metabolism and immune tolerance could lead to the identification of new markers for the monitoring of disease onset and progression. We studied several immune cell subsets and factors with high metabolic impact as markers associated with disease progression in high-risk subjects and type 1 diabetic patients at onset and at 12 and 24 months after diagnosis. A multiple correlation matrix among different parameters was evaluated statistically and assessed visually on two-dimensional graphs. Markers to predict residual β-cell function up to 1 year after diagnosis were identified in multivariate logistic regression models. The meta-immunological profile changed significantly over time in patients, and a specific signature that was associated with worsening disease was identified. A multivariate logistic regression model measuring age, BMI, fasting C-peptide, number of circulating CD3(+)CD16(+)CD56(+) cells, and the percentage of CD1c(+)CD19(-)CD14(-)CD303(-) type 1 myeloid dendritic cells at disease onset had a significant predictive value. The identification of a specific meta-immunological profile associated with disease status may contribute to our understanding of the basis of diabetes progression.

Published
2013

46. 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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48. 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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49. 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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