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      Interaction between plasma phospholipid odd-chain fatty acids and GAD65 autoantibodies on the incidence of adult-onset diabetes: the EPIC-InterAct case–cohort study

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          Abstract

          Aims/hypothesis

          Islet autoimmunity may progress to adult-onset diabetes. We investigated whether circulating odd-chain fatty acids (OCFA) 15:0 and 17:0, which are inversely associated with type 2 diabetes, interact with autoantibodies against GAD65 (GAD65Ab) on the incidence of adult-onset diabetes.

          Methods

          We used the European EPIC-InterAct case–cohort study including 11,124 incident adult-onset diabetes cases and a subcohort of 14,866 randomly selected individuals. Adjusted Prentice-weighted Cox regression estimated HRs and 95% CIs of diabetes in relation to 1 SD lower plasma phospholipid 15:0 and/or 17:0 concentrations or their main contributor, dairy intake, among GAD65Ab-negative and -positive individuals. Interactions between tertiles of OCFA and GAD65Ab status were estimated by proportion attributable to interaction (AP).

          Results

          Low concentrations of OCFA, particularly 17:0, were associated with a higher incidence of adult-onset diabetes in both GAD65Ab-negative (HR 1.55 [95% CI 1.48, 1.64]) and GAD65Ab-positive (HR 1.69 [95% CI 1.34, 2.13]) individuals. The combination of low 17:0 and high GAD65Ab positivity vs high 17:0 and GAD65Ab negativity conferred an HR of 7.51 (95% CI 4.83, 11.69), with evidence of additive interaction (AP 0.25 [95% CI 0.05, 0.45]). Low dairy intake was not associated with diabetes incidence in either GAD65Ab-negative (HR 0.98 [95% CI 0.94, 1.02]) or GAD65Ab-positive individuals (HR 0.97 [95% CI 0.79, 1.18]).

          Conclusions/interpretation

          Low plasma phospholipid 17:0 concentrations may promote the progression from GAD65Ab positivity to adult-onset diabetes.

          Graphical Abstract

          Supplementary Information

          The online version of this article (10.1007/s00125-023-05948-x) contains peer-reviewed but unedited supplementary material.

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          Most cited references38

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          Validity and repeatability of a simple index derived from the short physical activity questionnaire used in the European Prospective Investigation into Cancer and Nutrition (EPIC) study.

          To assess the validity and repeatability of a simple index designed to rank participants according to their energy expenditure estimated by self-report, by comparison with objectively measured energy expenditure assessed by heart-rate monitoring with individual calibration. Energy expenditure was assessed over one year by four separate episodes of 4-day heart-rate monitoring, a method previously validated against whole-body calorimetry and doubly labelled water. Cardio-respiratory fitness was assessed by four repeated measures of sub-maximum oxygen uptake. At the end of the 12-month period, participants completed a physical activity questionnaire that assessed past-year activity. A simple four-level physical activity index was derived by combining occupational physical activity together with time participating in cycling and other physical exercise (such as keep fit, aerobics, swimming and jogging). One hundred and seventy-three randomly selected men and women aged 40 to 65 years. The repeatability of the physical activity index was high (weighted kappa=0.6, ). There were positive associations between the physical activity index from the questionnaire and the objective measures of the ratio of daytime energy expenditure to resting metabolic rate and cardio-respiratory fitness As an indirect test of validity, there was a positive association between the physical activity index and the ratio of energy intake, assessed by 7-day food diaries, to predicted basal metabolic rate. The summary index of physical activity derived from the questions used in the European Prospective Investigation into Cancer and Nutrition (EPIC) study suggest it is useful for ranking participants in terms of their physical activity in large epidemiological studies. The index is simple and easy to comprehend, which may make it suitable for situations that require a concise, global index of activity.
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            Seroconversion to multiple islet autoantibodies and risk of progression to diabetes in children.

            Type 1 diabetes usually has a preclinical phase identified by circulating islet autoantibodies, but the rate of progression to diabetes after seroconversion to islet autoantibodies is uncertain. To determine the rate of progression to diabetes after islet autoantibody seroconversion. Data were pooled from prospective cohort studies performed in Colorado (recruitment, 1993-2006), Finland (recruitment, 1994-2009), and Germany (recruitment, 1989-2006) examining children genetically at risk for type 1 diabetes for the development of insulin autoantibodies, glutamic acid decarboxylase 65 (GAD65) autoantibodies, insulinoma antigen 2 (IA2) autoantibodies, and diabetes. Participants were all children recruited and followed up in the 3 studies (Colorado, 1962; Finland, 8597; Germany, 2818). Follow-up assessment in each study was concluded by July 2012. The primary analysis was the diagnosis of type 1 diabetes in children with 2 or more autoantibodies. The secondary analysis was the diagnosis of type 1 diabetes in children with 1 autoantibody or no autoantibodies. Progression to type 1 diabetes at 10-year follow-up after islet autoantibody seroconversion in 585 children with multiple islet autoantibodies was 69.7% (95% CI, 65.1%-74.3%), and in 474 children with a single islet autoantibody was 14.5% (95% CI, 10.3%-18.7%). Risk of diabetes in children who had no islet autoantibodies was 0.4% (95% CI, 0.2%-0.6%) by the age of 15 years. Progression to type 1 diabetes in the children with multiple islet autoantibodies was faster for children who had islet autoantibody seroconversion younger than age 3 years (hazard ratio [HR], 1.65 [95% CI, 1.30-2.09; P < .001]; 10-year risk, 74.9% [95% CI, 69.7%-80.1%]) vs children 3 years or older (60.9% [95% CI, 51.5%-70.3%]); for children with the human leukocyte antigen (HLA) genotype DR3/DR4-DQ8 (HR, 1.35 [95% CI, 1.09-1.68; P = .007]; 10-year risk, 76.6% [95% CI, 69.2%-84%]) vs other HLA genotypes (66.2% [95% CI, 60.2%-72.2%]); and for girls (HR, 1.28 [95% CI, 1.04-1.58; P = .02];10-year risk, 74.8% [95% CI, 68.0%-81.6%]) vs boys (65.7% [95% CI, 59.3%-72.1%]). The majority of children at risk of type 1 diabetes who had multiple islet autoantibody seroconversion progressed to diabetes over the next 15 years. Future prevention studies should focus on this high-risk population.
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              A Tutorial on Interaction

              In this tutorial, we provide a broad introduction to the topic of interaction between the effects of exposures. We discuss interaction on both additive and multiplicative scales using risks, and we discuss their relation to statistical models (e.g. linear, log-linear, and logistic models). We discuss and evaluate arguments that have been made for using additive or multiplicative scales to assess interaction. We further discuss approaches to presenting interaction analyses, different mechanistic forms of interaction, when interaction is robust to unmeasured confounding, interaction for continuous outcomes, qualitative or “crossover” interactions, methods for attributing effects to interactions, case-only estimators of interaction, and power and sample size calculations for additive and multiplicative interaction.
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                Author and article information

                Contributors
                annamaria.lampousi@ki.se
                Journal
                Diabetologia
                Diabetologia
                Diabetologia
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                0012-186X
                1432-0428
                10 June 2023
                10 June 2023
                2023
                : 66
                : 8
                : 1460-1471
                Affiliations
                [1 ]GRID grid.4714.6, ISNI 0000 0004 1937 0626, Institute of Environmental Medicine, Karolinska Institutet, ; Stockholm, Sweden
                [2 ]Department of Risk and Benefit Assessment, Swedish Food Agency, Uppsala, Sweden
                [3 ]GRID grid.452553.0, ISNI 0000 0004 8504 7077, Department of Epidemiology, , Regional Health Council, IMIB-Arrixaca, ; Murcia, Spain
                [4 ]GRID grid.466571.7, ISNI 0000 0004 1756 6246, Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), ; Madrid, Spain
                [5 ]GRID grid.10586.3a, ISNI 0000 0001 2287 8496, Department of Health and Social Sciences, , Murcia University, ; Murcia, Spain
                [6 ]GRID grid.451012.3, ISNI 0000 0004 0621 531X, Deep Digital Phenotyping Research Unit, Department of Precision Health, , Luxembourg Institute of Health, ; Strassen, Luxembourg
                [7 ]GRID grid.411843.b, ISNI 0000 0004 0623 9987, Department of Clinical Sciences, Clinical Research Center, , Skåne University Hospital, Lund University, ; Malmö, Sweden
                [8 ]GRID grid.12650.30, ISNI 0000 0001 1034 3451, Department of Public Health and Clinical Medicine, Family Medicine, , Umeå University, ; Umeå, Sweden
                [9 ]GRID grid.34477.33, ISNI 0000000122986657, Department of Medicine, , University of Washington School of Medicine, ; Seattle, WA USA
                [10 ]GRID grid.418701.b, ISNI 0000 0001 2097 8389, Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, , Catalan Institute of Oncology (ICO-IDIBELL), ; Barcelona, Spain
                [11 ]GRID grid.6162.3, ISNI 0000 0001 2174 6723, Blanquerna School of Health Sciences, , Ramon Llull University, ; Barcelona, Spain
                [12 ]GRID grid.5335.0, ISNI 0000000121885934, Medical Research Council Epidemiology Unit, Institute of Metabolic Science, , University of Cambridge School of Clinical Medicine, ; Cambridge, UK
                [13 ]GRID grid.5335.0, ISNI 0000000121885934, National Institute for Health Research Biomedical Research Centre Core Nutritional Biomarker Laboratory, , University of Cambridge School of Clinical Medicine, ; Cambridge, UK
                [14 ]GRID grid.417390.8, ISNI 0000 0001 2175 6024, Danish Cancer Society Research Center, ; Copenhagen, Denmark
                [15 ]GRID grid.419126.9, ISNI 0000 0004 0375 9231, Navarra Public Health Institute, ; Pamplona, Spain
                [16 ]GRID grid.508840.1, ISNI 0000 0004 7662 6114, Navarra Institute for Health Research (IdiSNA), ; Pamplona, Spain
                [17 ]GRID grid.4691.a, ISNI 0000 0001 0790 385X, Dipartimento di Medicina Clinica e Chirurgia, , Federico II University, ; Naples, Italy
                [18 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, Cancer Epidemiology Unit, Nuffield Department of Population Health, , University of Oxford, ; Oxford, UK
                [19 ]GRID grid.5477.1, ISNI 0000000120346234, Julius Center for Health Sciences and Primary Care, , University Medical Center Utrecht, Utrecht University, ; Utrecht, the Netherlands
                [20 ]GRID grid.418213.d, ISNI 0000 0004 0390 0098, Department of Molecular Epidemiology, , German Institute of Human Nutrition Potsdam-Rehbruecke, ; Nuthetal, Germany
                [21 ]GRID grid.452622.5, German Center for Diabetes Research (DZD), ; Neuherberg, Germany
                [22 ]GRID grid.11348.3f, ISNI 0000 0001 0942 1117, Institute of Nutritional Science, , University of Potsdam, ; Nuthetal, Germany
                [23 ]GRID grid.17703.32, ISNI 0000000405980095, International Agency for Research on Cancer, World Health Organization, ; Lyon, France
                Author information
                http://orcid.org/0000-0002-3640-3827
                http://orcid.org/0000-0002-9497-2331
                http://orcid.org/0000-0002-0099-969X
                http://orcid.org/0000-0001-9242-3040
                http://orcid.org/0000-0001-5033-5966
                http://orcid.org/0000-0002-0520-7604
                http://orcid.org/0000-0001-9111-6671
                http://orcid.org/0000-0003-0672-8847
                http://orcid.org/0000-0001-9998-051X
                http://orcid.org/0000-0002-9083-8960
                http://orcid.org/0000-0001-6537-0131
                http://orcid.org/0000-0002-5652-8459
                http://orcid.org/0000-0002-5498-8312
                http://orcid.org/0000-0002-4102-6835
                http://orcid.org/0000-0002-4605-435X
                http://orcid.org/0000-0002-0830-5277
                http://orcid.org/0000-0003-2237-0128
                http://orcid.org/0000-0002-6236-6804
                http://orcid.org/0000-0002-5041-248X
                http://orcid.org/0000-0003-2375-1440
                http://orcid.org/0000-0002-1341-6828
                http://orcid.org/0000-0003-1422-2993
                Article
                5948
                10.1007/s00125-023-05948-x
                10317878
                37301794
                d361d369-18ff-4dca-99f7-daaa22c7f738
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 9 March 2023
                : 25 April 2023
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000009, Foundation for the National Institutes of Health;
                Award ID: DK-26190
                Funded by: MRC Epidemiology Unit
                Award ID: MC_UU_00006/1
                Award ID: MC_UU_00006/3
                Funded by: FundRef http://dx.doi.org/10.13039/501100018956, NIHR Cambridge Biomedical Research Centre;
                Award ID: NIHR203312
                Funded by: FundRef http://dx.doi.org/10.13039/501100002960, Västerbotten Läns Landsting;
                Funded by: FundRef http://dx.doi.org/10.13039/501100006636, Forskningsrådet om Hälsa, Arbetsliv och Välfärd;
                Award ID: 2018-00337
                Funded by: FundRef http://dx.doi.org/10.13039/501100008546, Diabetesförbundet;
                Award ID: DIA2022-735
                Funded by: FundRef http://dx.doi.org/10.13039/501100004359, Vetenskapsrådet;
                Award ID: 2018-03035
                Funded by: FundRef http://dx.doi.org/10.13039/501100004895, European Social Fund;
                Funded by: FundRef http://dx.doi.org/10.13039/501100000265, Medical Research Council;
                Award ID: MC_UU_12015/1
                Funded by: German Federal Ministry of Education and Research and the State of Brandenburg
                Award ID: 82DZD03D03
                Funded by: FundRef http://dx.doi.org/10.13039/501100009708, Novo Nordisk Fonden;
                Award ID: NNF19OC0057274
                Funded by: FundRef http://dx.doi.org/10.13039/501100004587, Instituto de Salud Carlos III;
                Award ID: CPII20/00009
                Funded by: European Union FP6 programme
                Award ID: LSHM_CT_2006_037197
                Funded by: FundRef http://dx.doi.org/10.13039/501100004885, Umeå Universitet;
                Funded by: Karolinska Institute
                Categories
                Article
                Custom metadata
                © Springer-Verlag GmbH Germany, part of Springer Nature 2023

                Endocrinology & Diabetes
                diabetes,gad65ab,heptadecanoic,islet autoimmunity,ocfa,pentadecanoic
                Endocrinology & Diabetes
                diabetes, gad65ab, heptadecanoic, islet autoimmunity, ocfa, pentadecanoic

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