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Prasad RB, Kristensen K, Katsarou A, Shaat N. Association of single nucleotide polymorphisms with insulin secretion, insulin sensitivity, and diabetes in women with a history of gestational diabetes mellitus. BMC Med Genomics 2021; 14:274. [PMID: 34801028 PMCID: PMC8606068 DOI: 10.1186/s12920-021-01123-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Accepted: 11/10/2021] [Indexed: 12/23/2022] Open
Abstract
Background This study investigated whether single nucleotide polymorphisms (SNPs) reported by previous genome-wide association studies (GWAS) to be associated with impaired insulin secretion, insulin resistance, and/or type 2 diabetes are associated with disposition index, the homeostasis model assessment of insulin resistance (HOMA-IR), and/or development of diabetes following a pregnancy complicated by gestational diabetes mellitus (GDM). Methods Seventy-two SNPs were genotyped in 374 women with previous GDM from Southern Sweden. An oral glucose tolerance test was performed 1–2 years postpartum, although data on the diagnosis of diabetes were accessible up to 5 years postpartum. HOMA-IR and disposition index were used to measure insulin resistance and secretion, respectively. Results The risk A-allele in the rs11708067 polymorphism of the adenylate cyclase 5 gene (ADCY5) was associated with decreased disposition index (beta = − 0.90, SE 0.38, p = 0.019). This polymorphism was an expression quantitative trait loci (eQTL) in islets for both ADCY5 and its antisense transcript. The risk C-allele in the rs2943641 polymorphism, near the insulin receptor substrate 1 gene (IRS1), showed a trend towards association with increased HOMA-IR (beta = 0.36, SE 0.18, p = 0.050), and the T-allele of the rs4607103 polymorphism, near the ADAM metallopeptidase with thrombospondin type 1 motif 9 gene (ADAMTS9), was associated with postpartum diabetes (OR = 2.12, SE 0.22, p = 0.00055). The genetic risk score (GRS) of the top four SNPs tested for association with the disposition index using equal weights was associated with the disposition index (beta = − 0.31, SE = 0.29, p = 0.00096). In addition, the GRS of the four SNPs studied for association with HOMA-IR using equal weights showed an association with HOMA-IR (beta = 1.13, SE = 0.48, p = 9.72874e−11). All analyses were adjusted for age, body mass index, and ethnicity. Conclusions This study demonstrated the genetic susceptibility of women with a history of GDM to impaired insulin secretion and sensitivity and, ultimately, to diabetes development.
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Affiliation(s)
- Rashmi B Prasad
- Genomics, Diabetes and Endocrinology, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Karl Kristensen
- Genomics, Diabetes and Endocrinology, Department of Clinical Sciences, Lund University, Malmö, Sweden.,Department of Obstetrics and Gynaecology, Skåne University Hospital, Malmö, Sweden
| | - Anastasia Katsarou
- Genomics, Diabetes and Endocrinology, Department of Clinical Sciences, Lund University, Malmö, Sweden.,Department of Endocrinology, Skåne University Hospital, 205 02, Malmö, Sweden
| | - Nael Shaat
- Genomics, Diabetes and Endocrinology, Department of Clinical Sciences, Lund University, Malmö, Sweden. .,Department of Endocrinology, Skåne University Hospital, 205 02, Malmö, Sweden.
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Huvinen E, Eriksson JG, Stach-Lempinen B, Tiitinen A, Koivusalo SB. Heterogeneity of gestational diabetes (GDM) and challenges in developing a GDM risk score. Acta Diabetol 2018; 55:1251-1259. [PMID: 30221319 DOI: 10.1007/s00592-018-1224-x] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/14/2018] [Accepted: 09/03/2018] [Indexed: 02/07/2023]
Abstract
AIMS Gestational diabetes (GDM) affects a growing number of women and identification of individuals at risk, e.g., with risk prediction models, would be important. However, the performance of GDM risk scores has not been optimal. Here, we assess the impact of GDM heterogeneity on the performance of two top-rated GDM risk scores. METHODS This is a substudy of the RADIEL trial-a lifestyle intervention study including women at high GDM risk. We assessed the GDM risk score by Teede and that developed by Van Leeuwen in our high-risk cohort of 510 women. To investigate the heterogeneity of GDM, we further divided the women according to GDM history, BMI, and parity. With the goal of identifying novel predictors of GDM, we further analyzed 319 women with normal glucose tolerance in the first trimester. RESULTS Both risk scores underestimated GDM incidence in our high-risk cohort. Among women with a BMI ≥ 30 kg/m2 and/or previous GDM, 49.4% developed GDM and 37.4% received the diagnosis already in the first trimester. Van Leeuwen score estimated a 19% probability of GDM and Teede succeeded in risk identification in 61%. The lowest performance of the risk scores was seen among the non-obese women. Fasting plasma glucose, HbA1c, and family history of diabetes were predictors of GDM in the total study population. Analysis of subgroups did not provide any further information. CONCLUSIONS Our findings suggest that the marked heterogeneity of GDM challenges the development of risk scores for detection of GDM.
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Affiliation(s)
- Emilia Huvinen
- Department of Obstetrics and Gynaecology, Helsinki University Hospital, University of Helsinki, Helsinki, Finland.
- Unit of General Practice and Primary Health Care, University of Helsinki, Tukholmankatu 8 B, P.O. Box 20, 00014, Helsinki, Finland.
| | - Johan G Eriksson
- Unit of General Practice and Primary Health Care, University of Helsinki, Tukholmankatu 8 B, P.O. Box 20, 00014, Helsinki, Finland
- Folkhälsan Research Centre, Helsinki, Finland
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
| | - Beata Stach-Lempinen
- Department of Obstetrics and Gynaecology, South-Karelia Central Hospital, Lappeenranta, Finland
| | - Aila Tiitinen
- Department of Obstetrics and Gynaecology, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
| | - Saila B Koivusalo
- Department of Obstetrics and Gynaecology, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
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Molnos S, Wahl S, Haid M, Eekhoff EMW, Pool R, Floegel A, Deelen J, Much D, Prehn C, Breier M, Draisma HH, van Leeuwen N, Simonis-Bik AMC, Jonsson A, Willemsen G, Bernigau W, Wang-Sattler R, Suhre K, Peters A, Thorand B, Herder C, Rathmann W, Roden M, Gieger C, Kramer MHH, van Heemst D, Pedersen HK, Gudmundsdottir V, Schulze MB, Pischon T, de Geus EJC, Boeing H, Boomsma DI, Ziegler AG, Slagboom PE, Hummel S, Beekman M, Grallert H, Brunak S, McCarthy MI, Gupta R, Pearson ER, Adamski J, 't Hart LM. Metabolite ratios as potential biomarkers for type 2 diabetes: a DIRECT study. Diabetologia 2018; 61:117-129. [PMID: 28936587 PMCID: PMC6448944 DOI: 10.1007/s00125-017-4436-7] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2017] [Accepted: 07/28/2017] [Indexed: 01/13/2023]
Abstract
AIMS/HYPOTHESIS Circulating metabolites have been shown to reflect metabolic changes during the development of type 2 diabetes. In this study we examined the association of metabolite levels and pairwise metabolite ratios with insulin responses after glucose, glucagon-like peptide-1 (GLP-1) and arginine stimulation. We then investigated if the identified metabolite ratios were associated with measures of OGTT-derived beta cell function and with prevalent and incident type 2 diabetes. METHODS We measured the levels of 188 metabolites in plasma samples from 130 healthy members of twin families (from the Netherlands Twin Register) at five time points during a modified 3 h hyperglycaemic clamp with glucose, GLP-1 and arginine stimulation. We validated our results in cohorts with OGTT data (n = 340) and epidemiological case-control studies of prevalent (n = 4925) and incident (n = 4277) diabetes. The data were analysed using regression models with adjustment for potential confounders. RESULTS There were dynamic changes in metabolite levels in response to the different secretagogues. Furthermore, several fasting pairwise metabolite ratios were associated with one or multiple clamp-derived measures of insulin secretion (all p < 9.2 × 10-7). These associations were significantly stronger compared with the individual metabolite components. One of the ratios, valine to phosphatidylcholine acyl-alkyl C32:2 (PC ae C32:2), in addition showed a directionally consistent positive association with OGTT-derived measures of insulin secretion and resistance (p ≤ 5.4 × 10-3) and prevalent type 2 diabetes (ORVal_PC ae C32:2 2.64 [β 0.97 ± 0.09], p = 1.0 × 10-27). Furthermore, Val_PC ae C32:2 predicted incident diabetes independent of established risk factors in two epidemiological cohort studies (HRVal_PC ae C32:2 1.57 [β 0.45 ± 0.06]; p = 1.3 × 10-15), leading to modest improvements in the receiver operating characteristics when added to a model containing a set of established risk factors in both cohorts (increases from 0.780 to 0.801 and from 0.862 to 0.865 respectively, when added to the model containing traditional risk factors + glucose). CONCLUSIONS/INTERPRETATION In this study we have shown that the Val_PC ae C32:2 metabolite ratio is associated with an increased risk of type 2 diabetes and measures of insulin secretion and resistance. The observed effects were stronger than that of the individual metabolites and independent of known risk factors.
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Affiliation(s)
- Sophie Molnos
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Simone Wahl
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Mark Haid
- Institute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - E Marelise W Eekhoff
- Department of Internal Medicine-Diabetes Center, VU University Medical Center, Amsterdam, the Netherlands
| | - René Pool
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
| | - Anna Floegel
- Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
| | - Joris Deelen
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
- Max Planck Institute for Biology of Ageing, Cologne, Germany
| | - Daniela Much
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
- Institute of Diabetes Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Forschergruppe Diabetes, Klinikum rechts der Isar, Technische Universität München, Neuherberg, Germany
| | - Cornelia Prehn
- Institute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Michaela Breier
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Harmen H Draisma
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
| | - Nienke van Leeuwen
- Department of Molecular Cell Biology, Leiden University Medical Center, Albinusdreef 2, 2333ZA, Leiden, the Netherlands
| | - Annemarie M C Simonis-Bik
- Department of Internal Medicine-Diabetes Center, VU University Medical Center, Amsterdam, the Netherlands
| | - Anna Jonsson
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
| | - Wolfgang Bernigau
- Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
| | - Rui Wang-Sattler
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Karsten Suhre
- Department of Biophysics and Physiology, Weill Cornell Medical College in Qatar, Doha, Qatar
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Annette Peters
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Barbara Thorand
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Christian Herder
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Wolfgang Rathmann
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Michael Roden
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Department of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Mark H H Kramer
- Department of Internal Medicine-Diabetes Center, VU University Medical Center, Amsterdam, the Netherlands
| | - Diana van Heemst
- Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Helle K Pedersen
- Department of Bio and Health Informatics, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Valborg Gudmundsdottir
- Department of Bio and Health Informatics, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Matthias B Schulze
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
| | - Tobias Pischon
- Molecular Epidemiology Research Group, Max Delbrück Center for Molecular Medicine, Berlin Buch, Germany
| | - Eco J C de Geus
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
| | - Heiner Boeing
- Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
| | - Anette G Ziegler
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
- Institute of Diabetes Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Forschergruppe Diabetes, Klinikum rechts der Isar, Technische Universität München, Neuherberg, Germany
| | - P Eline Slagboom
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Sandra Hummel
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
- Institute of Diabetes Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Forschergruppe Diabetes, Klinikum rechts der Isar, Technische Universität München, Neuherberg, Germany
| | - Marian Beekman
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Harald Grallert
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Søren Brunak
- Department of Bio and Health Informatics, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Mark I McCarthy
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Headington, Oxford, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Churchill Hospital, Headington, Oxford, UK
| | - Ramneek Gupta
- Department of Bio and Health Informatics, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Ewan R Pearson
- Division of Molecular and Clinical Medicine, School of Medicine, University of Dundee, Dundee, UK
| | - Jerzy Adamski
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
- Institute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Experimental Genetics, Technical University of Munich, Freising-Weihenstephan, Germany
| | - Leen M 't Hart
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.
- Department of Molecular Cell Biology, Leiden University Medical Center, Albinusdreef 2, 2333ZA, Leiden, the Netherlands.
- Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, the Netherlands.
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Krabbe CEM, Schipf S, Ittermann T, Dörr M, Nauck M, Chenot JF, Markus MRP, Völzke H. Comparison of traditional diabetes risk scores and HbA1c to predict type 2 diabetes mellitus in a population based cohort study. J Diabetes Complications 2017; 31:1602-1607. [PMID: 28886990 DOI: 10.1016/j.jdiacomp.2017.07.016] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2017] [Revised: 07/24/2017] [Accepted: 07/27/2017] [Indexed: 12/18/2022]
Abstract
AIMS Compare performances of diabetes risk scores and glycated hemoglobin (HbA1c) to estimate the risk of incident type 2 diabetes mellitus (T2DM) in Northeast Germany. METHODS We studied 2916 subjects (20 to 81years) from the Study of Health in Pomerania (SHIP) in a 5-year follow-up period. Diabetes risk scores included the Cooperative Health Research in the Region of Augsburg (KORA) base model, the Danish diabetes risk score and the Data from the Epidemiological Study on the Insulin Resistance syndrome (D.E.S.I.R) clinical risk score. We assessed the performance of each of the diabetes risk scores and the HbA1c for 5-year risk of T2DM by the area under the receiver-operating characteristic curve (AUC) and calibration plots. RESULTS In SHIP, the incidence of T2DM was 5.4% (n=157) in the 5-year follow-up period. Diabetes risk scores and HbA1c achieved AUCs ranging from 0.76 for the D.E.S.I.R. clinical risk score to 0.82 for the KORA base model. For diabetes risk scores, the discriminative ability was lower for the age group 55 to 74years. For HbA1c, the discriminative ability also decreased for the group 55 to 74years while it was stable in the age group 30 to 64years old. CONCLUSIONS All diabetes risk scores and the HbA1c showed a good prediction for the risk of T2DM in SHIP. Which model or biomarker should be used is driven by its context of use, e.g. the practicability, implementation of interventions and availability of measurement.
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Affiliation(s)
- Christine Emma Maria Krabbe
- Department of Study of Health in Pomerania/Clinical-Epidemiological Research, Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Sabine Schipf
- Department of Study of Health in Pomerania/Clinical-Epidemiological Research, Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany; German Center for Diabetes Research (DZD), partner site Greifswald, Greifswald, Germany
| | - Till Ittermann
- Department of Study of Health in Pomerania/Clinical-Epidemiological Research, Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Marcus Dörr
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany; German Centre for Cardiovascular Research (DZHK), partner site Greifswald, Greifswald, Germany
| | - Matthias Nauck
- German Centre for Cardiovascular Research (DZHK), partner site Greifswald, Greifswald, Germany; Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Jean-François Chenot
- Department of General Practice, Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Marcello Ricardo Paulista Markus
- Department of Study of Health in Pomerania/Clinical-Epidemiological Research, Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany; German Center for Diabetes Research (DZD), partner site Greifswald, Greifswald, Germany; Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany; German Centre for Cardiovascular Research (DZHK), partner site Greifswald, Greifswald, Germany.
| | - Henry Völzke
- Department of Study of Health in Pomerania/Clinical-Epidemiological Research, Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany; German Centre for Cardiovascular Research (DZHK), partner site Greifswald, Greifswald, Germany
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