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1.  DNA methylation signatures of chronic low-grade inflammation are associated with complex diseases 
Ligthart, Symen | Marzi, Carola | Aslibekyan, Stella | Mendelson, Michael M. | Conneely, Karen N. | Tanaka, Toshiko | Colicino, Elena | Waite, Lindsay L. | Joehanes, Roby | Guan, Weihua | Brody, Jennifer A. | Elks, Cathy | Marioni, Riccardo | Jhun, Min A. | Agha, Golareh | Bressler, Jan | Ward-Caviness, Cavin K. | Chen, Brian H. | Huan, Tianxiao | Bakulski, Kelly | Salfati, Elias L. | Fiorito, Giovanni | Wahl, Simone | Schramm, Katharina | Sha, Jin | Hernandez, Dena G. | Just, Allan C. | Smith, Jennifer A. | Sotoodehnia, Nona | Pilling, Luke C. | Pankow, James S. | Tsao, Phil S. | Liu, Chunyu | Zhao, Wei | Guarrera, Simonetta | Michopoulos, Vasiliki J. | Smith, Alicia K. | Peters, Marjolein J. | Melzer, David | Vokonas, Pantel | Fornage, Myriam | Prokisch, Holger | Bis, Joshua C. | Chu, Audrey Y. | Herder, Christian | Grallert, Harald | Yao, Chen | Shah, Sonia | McRae, Allan F. | Lin, Honghuang | Horvath, Steve | Fallin, Daniele | Hofman, Albert | Wareham, Nicholas J. | Wiggins, Kerri L. | Feinberg, Andrew P. | Starr, John M. | Visscher, Peter M. | Murabito, Joanne M. | Kardia, Sharon L. R. | Absher, Devin M. | Binder, Elisabeth B. | Singleton, Andrew B. | Bandinelli, Stefania | Peters, Annette | Waldenberger, Melanie | Matullo, Giuseppe | Schwartz, Joel D. | Demerath, Ellen W. | Uitterlinden, André G. | van Meurs, Joyce B. J. | Franco, Oscar H. | Chen, Yii-Der Ida | Levy, Daniel | Turner, Stephen T. | Deary, Ian J. | Ressler, Kerry J. | Dupuis, Josée | Ferrucci, Luigi | Ong, Ken K. | Assimes, Themistocles L. | Boerwinkle, Eric | Koenig, Wolfgang | Arnett, Donna K. | Baccarelli, Andrea A. | Benjamin, Emelia J. | Dehghan, Abbas
Genome Biology  2016;17:255.
Background
Chronic low-grade inflammation reflects a subclinical immune response implicated in the pathogenesis of complex diseases. Identifying genetic loci where DNA methylation is associated with chronic low-grade inflammation may reveal novel pathways or therapeutic targets for inflammation.
Results
We performed a meta-analysis of epigenome-wide association studies (EWAS) of serum C-reactive protein (CRP), which is a sensitive marker of low-grade inflammation, in a large European population (n = 8863) and trans-ethnic replication in African Americans (n = 4111). We found differential methylation at 218 CpG sites to be associated with CRP (P < 1.15 × 10–7) in the discovery panel of European ancestry and replicated (P < 2.29 × 10–4) 58 CpG sites (45 unique loci) among African Americans. To further characterize the molecular and clinical relevance of the findings, we examined the association with gene expression, genetic sequence variants, and clinical outcomes. DNA methylation at nine (16%) CpG sites was associated with whole blood gene expression in cis (P < 8.47 × 10–5), ten (17%) CpG sites were associated with a nearby genetic variant (P < 2.50 × 10–3), and 51 (88%) were also associated with at least one related cardiometabolic entity (P < 9.58 × 10–5). An additive weighted score of replicated CpG sites accounted for up to 6% inter-individual variation (R2) of age-adjusted and sex-adjusted CRP, independent of known CRP-related genetic variants.
Conclusion
We have completed an EWAS of chronic low-grade inflammation and identified many novel genetic loci underlying inflammation that may serve as targets for the development of novel therapeutic interventions for inflammation.
Electronic supplementary material
The online version of this article (doi:10.1186/s13059-016-1119-5) contains supplementary material, which is available to authorized users.
doi:10.1186/s13059-016-1119-5
PMCID: PMC5151130  PMID: 27955697
Inflammation; DNA methylation; Epigenome-wide association study; C-reactive protein; Body mass index; Diabetes; Coronary heart disease
2.  Relevance of Morning and Evening Energy and Macronutrient Intake during Childhood for Body Composition in Early Adolescence 
Nutrients  2016;8(11):716.
(1) Background: This study investigated the relevance of morning and evening energy and macronutrient intake during childhood for body composition in early adolescence; (2) Methods: Analyses were based on data from 372 DONALD (DOrtmund Nutritional and Anthropometric Longitudinally Designed study) participants. Explorative life-course plots were performed to examine whether morning or evening energy and macronutrient intake at 3/4 years, 5/6 years, or 7/8 years is critical for fat mass index (FMI [kg/m2]) and fat free mass index (FFMI [kg/m2]) in early adolescence (10/11 years). Subsequently, exposures in periods identified as consistently critical were examined in depth using adjusted regression models; (3) Results: Life-course plots identified morning fat and carbohydrate (CHO) intake at 3/4 years and 7/8 years as well as changes in these intakes between 3/4 years and 7/8 years as potentially critical for FMI at 10/11 years. Adjusted regression models corroborated higher FMI values at 10/11 years among those who had consumed less fat (p = 0.01) and more CHO (p = 0.01) in the morning at 7/8 years as well as among those who had decreased their morning fat intake (p = 0.02) and increased their morning CHO intake (p = 0.05) between 3/4 years and 7/8 years; (4) Conclusion: During childhood, adherence to a low fat, high CHO intake in the morning may have unfavorable consequences for FMI in early adolescence.
doi:10.3390/nu8110716
PMCID: PMC5133102  PMID: 27834901
childhood; adolescence; morning intake; evening intake; macronutrient intake; fat mass
3.  Molecular Characterization of the NLRC4 Expression in Relation to Interleukin-18 Levels 
Background
Interleukin-18 (IL-18) is a pleiotropic cytokine centrally involved in the cytokine cascade with complex immunomodulatory functions in innate and acquired immunity. Circulating IL-18 concentrations are associated with type 2 diabetes, cardiovascular events and diverse inflammatory and autoimmune disorders.
Methods and Results
To identify causal variants affecting circulating IL-18 concentrations, we applied various omics and molecular biology approaches. By GWAS, we confirmed association of IL-18 levels with a SNP in the untranslated exon 2 of the inflammasome component NLRC4 (NLR family, CARD domain containing 4) gene on chromosome 2 (rs385076, P=2.4×10−45). Subsequent molecular analyses by gene expression analysis and reporter gene assays indicated an effect of rs385076 on NLRC4 expression and differential isoform usage by modulating binding of the transcription factor PU.1.
Conclusions
Our study provides evidence for the functional causality of SNP rs385076 within the NLRC4 gene in relation to IL-18 activation.
doi:10.1161/CIRCGENETICS.115.001079
PMCID: PMC4618032  PMID: 26362438
gene expression; transcription factors; gene regulation; genetic variation; Interleukin 18; Inflammasome; PU.1; NLRC4
4.  DNA Methylation of Lipid-Related Genes Affects Blood Lipid Levels 
Background
Epigenetic mechanisms might be involved in the regulation of interindividual lipid level variability and thus may contribute to the cardiovascular risk profile. The aim of this study was to investigate the association between genome-wide DNA methylation and blood lipid levels high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides, and total cholesterol. Observed DNA methylation changes were also further analyzed to examine their relationship with previous hospitalized myocardial infarction.
Methods and Results
Genome-wide DNA methylation patterns were determined in whole blood samples of 1776 subjects of the Cooperative Health Research in the Region of Augsburg F4 cohort using the Infinium HumanMethylation450 BeadChip (Illumina). Ten novel lipid-related CpG sites annotated to various genes including ABCG1, MIR33B/SREBF1, and TNIP1 were identified. CpG cg06500161, located in ABCG1, was associated in opposite directions with both high-density lipoprotein cholesterol (β coefficient=−0.049; P=8.26E-17) and triglyceride levels (β=0.070; P=1.21E-27). Eight associations were confirmed by replication in the Cooperative Health Research in the Region of Augsburg F3 study (n=499) and in the Invecchiare in Chianti, Aging in the Chianti Area study (n=472). Associations between triglyceride levels and SREBF1 and ABCG1 were also found in adipose tissue of the Multiple Tissue Human Expression Resource cohort (n=634). Expression analysis revealed an association between ABCG1 methylation and lipid levels that might be partly mediated by ABCG1 expression. DNA methylation of ABCG1 might also play a role in previous hospitalized myocardial infarction (odds ratio, 1.15; 95% confidence interval=1.06–1.25).
Conclusions
Epigenetic modifications of the newly identified loci might regulate disturbed blood lipid levels and thus contribute to the development of complex lipid-related diseases.
doi:10.1161/CIRCGENETICS.114.000804
PMCID: PMC5012424  PMID: 25583993
ABCG1; DNA methylatio; epidemiology; gene expression; myocardial infarction
5.  Meta-analysis of genome-wide association studies identifies 10 loci influencing allergic sensitization 
Nature genetics  2013;45(8):902-906.
Allergen-specific IgE (allergic sensitization) plays a central role in the pathogenesis of allergic disease. We performed the first large-scale genome wide association study (GWAS) of allergic sensitization in 5,789 affected individuals and 10,056 controls and followed up the top SNP from 26 loci in 6,114 affected individuals and 9,920 controls. We increased the number of susceptibility loci with genome-wide significant association to allergic sensitization from three to 10, including SNPs in or near TLR6, C11orf30, STAT6, SLC25A46, HLA-DQB1, IL1RL1, LPP, MYC, IL2 and HLA-B. All the top-SNPs were associated with allergic symptoms in an independent study. Risk variants at these 10 loci were estimated to account for at least 25% of allergic sensitization and allergic rhinitis. Understanding the molecular mechanisms underlying these associations may provide novel insight into the etiology of allergic disease.
doi:10.1038/ng.2694
PMCID: PMC4922420  PMID: 23817571
6.  Genetic fine-mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci 
Gaulton, Kyle J | Ferreira, Teresa | Lee, Yeji | Raimondo, Anne | Mägi, Reedik | Reschen, Michael E | Mahajan, Anubha | Locke, Adam | Rayner, N William | Robertson, Neil | Scott, Robert A | Prokopenko, Inga | Scott, Laura J | Green, Todd | Sparso, Thomas | Thuillier, Dorothee | Yengo, Loic | Grallert, Harald | Wahl, Simone | Frånberg, Mattias | Strawbridge, Rona J | Kestler, Hans | Chheda, Himanshu | Eisele, Lewin | Gustafsson, Stefan | Steinthorsdottir, Valgerdur | Thorleifsson, Gudmar | Qi, Lu | Karssen, Lennart C | van Leeuwen, Elisabeth M | Willems, Sara M | Li, Man | Chen, Han | Fuchsberger, Christian | Kwan, Phoenix | Ma, Clement | Linderman, Michael | Lu, Yingchang | Thomsen, Soren K | Rundle, Jana K | Beer, Nicola L | van de Bunt, Martijn | Chalisey, Anil | Kang, Hyun Min | Voight, Benjamin F | Abecasis, Goncalo R | Almgren, Peter | Baldassarre, Damiano | Balkau, Beverley | Benediktsson, Rafn | Blüher, Matthias | Boeing, Heiner | Bonnycastle, Lori L | Borringer, Erwin P | Burtt, Noël P | Carey, Jason | Charpentier, Guillaume | Chines, Peter S | Cornelis, Marilyn C | Couper, David J | Crenshaw, Andrew T | van Dam, Rob M | Doney, Alex SF | Dorkhan, Mozhgan | Edkins, Sarah | Eriksson, Johan G | Esko, Tonu | Eury, Elodie | Fadista, João | Flannick, Jason | Fontanillas, Pierre | Fox, Caroline | Franks, Paul W | Gertow, Karl | Gieger, Christian | Gigante, Bruna | Gottesman, Omri | Grant, George B | Grarup, Niels | Groves, Christopher J | Hassinen, Maija | Have, Christian T | Herder, Christian | Holmen, Oddgeir L | Hreidarsson, Astradur B | Humphries, Steve E | Hunter, David J | Jackson, Anne U | Jonsson, Anna | Jørgensen, Marit E | Jørgensen, Torben | Kao, Wen-Hong L | Kerrison, Nicola D | Kinnunen, Leena | Klopp, Norman | Kong, Augustine | Kovacs, Peter | Kraft, Peter | Kravic, Jasmina | Langford, Cordelia | Leander, Karin | Liang, Liming | Lichtner, Peter | Lindgren, Cecilia M | Lindholm, Eero | Linneberg, Allan | Liu, Ching-Ti | Lobbens, Stéphane | Luan, Jian’an | Lyssenko, Valeriya | Mӓnnistö, Satu | McLeod, Olga | Meyer, Julia | Mihailov, Evelin | Mirza, Ghazala | Mühleisen, Thomas W | Müller-Nurasyid, Martina | Navarro, Carmen | Nöthen, Markus M | Oskolkov, Nikolay N | Owen, Katharine R | Palli, Domenico | Pechlivanis, Sonali | Peltonen, Leena | Perry, John RB | Platou, Carl GP | Roden, Michael | Ruderfer, Douglas | Rybin, Denis | van der Schouw, Yvonne T | Sennblad, Bengt | Sigurđsson, Gunnar | Stančáková, Alena | Steinbach, Gerald | Storm, Petter | Strauch, Konstantin | Stringham, Heather M | Sun, Qi | Thorand, Barbara | Tikkanen, Emmi | Tonjes, Anke | Trakalo, Joseph | Tremoli, Elena | Tuomi, Tiinamaija | Wennauer, Roman | Wiltshire, Steven | Wood, Andrew R | Zeggini, Eleftheria | Dunham, Ian | Birney, Ewan | Pasquali, Lorenzo | Ferrer, Jorge | Loos, Ruth JF | Dupuis, Josée | Florez, Jose C | Boerwinkle, Eric | Pankow, James S | van Duijn, Cornelia | Sijbrands, Eric | Meigs, James B | Hu, Frank B | Thorsteinsdottir, Unnur | Stefansson, Kari | Lakka, Timo A | Rauramaa, Rainer | Stumvoll, Michael | Pedersen, Nancy L | Lind, Lars | Keinanen-Kiukaanniemi, Sirkka M | Korpi-Hyövӓlti, Eeva | Saaristo, Timo E | Saltevo, Juha | Kuusisto, Johanna | Laakso, Markku | Metspalu, Andres | Erbel, Raimund | Jöckel, Karl-Heinz | Moebus, Susanne | Ripatti, Samuli | Salomaa, Veikko | Ingelsson, Erik | Boehm, Bernhard O | Bergman, Richard N | Collins, Francis S | Mohlke, Karen L | Koistinen, Heikki | Tuomilehto, Jaakko | Hveem, Kristian | Njølstad, Inger | Deloukas, Panagiotis | Donnelly, Peter J | Frayling, Timothy M | Hattersley, Andrew T | de Faire, Ulf | Hamsten, Anders | Illig, Thomas | Peters, Annette | Cauchi, Stephane | Sladek, Rob | Froguel, Philippe | Hansen, Torben | Pedersen, Oluf | Morris, Andrew D | Palmer, Collin NA | Kathiresan, Sekar | Melander, Olle | Nilsson, Peter M | Groop, Leif C | Barroso, Inês | Langenberg, Claudia | Wareham, Nicholas J | O’Callaghan, Christopher A | Gloyn, Anna L | Altshuler, David | Boehnke, Michael | Teslovich, Tanya M | McCarthy, Mark I | Morris, Andrew P
Nature genetics  2015;47(12):1415-1425.
We performed fine-mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in/near KCNQ1. “Credible sets” of variants most likely to drive each distinct signal mapped predominantly to non-coding sequence, implying that T2D association is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine-mapping implicated rs10830963 as driving T2D association. We confirmed that this T2D-risk allele increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D-risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease.
doi:10.1038/ng.3437
PMCID: PMC4666734  PMID: 26551672
7.  Genetic fine-mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci 
Gaulton, Kyle J | Ferreira, Teresa | Lee, Yeji | Raimondo, Anne | Mägi, Reedik | Reschen, Michael E | Mahajan, Anubha | Locke, Adam | Rayner, N William | Robertson, Neil | Scott, Robert A | Prokopenko, Inga | Scott, Laura J | Green, Todd | Sparso, Thomas | Thuillier, Dorothee | Yengo, Loic | Grallert, Harald | Wahl, Simone | Frånberg, Mattias | Strawbridge, Rona J | Kestler, Hans | Chheda, Himanshu | Eisele, Lewin | Gustafsson, Stefan | Steinthorsdottir, Valgerdur | Thorleifsson, Gudmar | Qi, Lu | Karssen, Lennart C | van Leeuwen, Elisabeth M | Willems, Sara M | Li, Man | Chen, Han | Fuchsberger, Christian | Kwan, Phoenix | Ma, Clement | Linderman, Michael | Lu, Yingchang | Thomsen, Soren K | Rundle, Jana K | Beer, Nicola L | van de Bunt, Martijn | Chalisey, Anil | Kang, Hyun Min | Voight, Benjamin F | Abecasis, Goncalo R | Almgren, Peter | Baldassarre, Damiano | Balkau, Beverley | Benediktsson, Rafn | Blüher, Matthias | Boeing, Heiner | Bonnycastle, Lori L | Borringer, Erwin P | Burtt, Noël P | Carey, Jason | Charpentier, Guillaume | Chines, Peter S | Cornelis, Marilyn C | Couper, David J | Crenshaw, Andrew T | van Dam, Rob M | Doney, Alex SF | Dorkhan, Mozhgan | Edkins, Sarah | Eriksson, Johan G | Esko, Tonu | Eury, Elodie | Fadista, João | Flannick, Jason | Fontanillas, Pierre | Fox, Caroline | Franks, Paul W | Gertow, Karl | Gieger, Christian | Gigante, Bruna | Gottesman, Omri | Grant, George B | Grarup, Niels | Groves, Christopher J | Hassinen, Maija | Have, Christian T | Herder, Christian | Holmen, Oddgeir L | Hreidarsson, Astradur B | Humphries, Steve E | Hunter, David J | Jackson, Anne U | Jonsson, Anna | Jørgensen, Marit E | Jørgensen, Torben | Kao, Wen-Hong L | Kerrison, Nicola D | Kinnunen, Leena | Klopp, Norman | Kong, Augustine | Kovacs, Peter | Kraft, Peter | Kravic, Jasmina | Langford, Cordelia | Leander, Karin | Liang, Liming | Lichtner, Peter | Lindgren, Cecilia M | Lindholm, Eero | Linneberg, Allan | Liu, Ching-Ti | Lobbens, Stéphane | Luan, Jian’an | Lyssenko, Valeriya | Männistö, Satu | McLeod, Olga | Meyer, Julia | Mihailov, Evelin | Mirza, Ghazala | Mühleisen, Thomas W | Müller-Nurasyid, Martina | Navarro, Carmen | Nöthen, Markus M | Oskolkov, Nikolay N | Owen, Katharine R | Palli, Domenico | Pechlivanis, Sonali | Peltonen, Leena | Perry, John RB | Platou, Carl GP | Roden, Michael | Ruderfer, Douglas | Rybin, Denis | van der Schouw, Yvonne T | Sennblad, Bengt | Sigurðsson, Gunnar | Stančáková, Alena | Steinbach, Gerald | Storm, Petter | Strauch, Konstantin | Stringham, Heather M | Sun, Qi | Thorand, Barbara | Tikkanen, Emmi | Tonjes, Anke | Trakalo, Joseph | Tremoli, Elena | Tuomi, Tiinamaija | Wennauer, Roman | Wiltshire, Steven | Wood, Andrew R | Zeggini, Eleftheria | Dunham, Ian | Birney, Ewan | Pasquali, Lorenzo | Ferrer, Jorge | Loos, Ruth JF | Dupuis, Josée | Florez, Jose C | Boerwinkle, Eric | Pankow, James S | van Duijn, Cornelia | Sijbrands, Eric | Meigs, James B | Hu, Frank B | Thorsteinsdottir, Unnur | Stefansson, Kari | Lakka, Timo A | Rauramaa, Rainer | Stumvoll, Michael | Pedersen, Nancy L | Lind, Lars | Keinanen-Kiukaanniemi, Sirkka M | Korpi-Hyövälti, Eeva | Saaristo, Timo E | Saltevo, Juha | Kuusisto, Johanna | Laakso, Markku | Metspalu, Andres | Erbel, Raimund | Jöckel, Karl-Heinz | Moebus, Susanne | Ripatti, Samuli | Salomaa, Veikko | Ingelsson, Erik | Boehm, Bernhard O | Bergman, Richard N | Collins, Francis S | Mohlke, Karen L | Koistinen, Heikki | Tuomilehto, Jaakko | Hveem, Kristian | Njølstad, Inger | Deloukas, Panagiotis | Donnelly, Peter J | Frayling, Timothy M | Hattersley, Andrew T | de Faire, Ulf | Hamsten, Anders | Illig, Thomas | Peters, Annette | Cauchi, Stephane | Sladek, Rob | Froguel, Philippe | Hansen, Torben | Pedersen, Oluf | Morris, Andrew D | Palmer, Collin NA | Kathiresan, Sekar | Melander, Olle | Nilsson, Peter M | Groop, Leif C | Barroso, Inês | Langenberg, Claudia | Wareham, Nicholas J | O’Callaghan, Christopher A | Gloyn, Anna L | Altshuler, David | Boehnke, Michael | Teslovich, Tanya M | McCarthy, Mark I | Morris, Andrew P
Nature genetics  2015;47(12):1415-1425.
We performed fine-mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in/near KCNQ1. “Credible sets” of variants most likely to drive each distinct signal mapped predominantly to non-coding sequence, implying that T2D association is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine-mapping implicated rs10830963 as driving T2D association. We confirmed that this T2D-risk allele increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D-risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease.
doi:10.1038/ng.3437
PMCID: PMC4666734  PMID: 26551672
8.  Age- and Sex-Specific Causal Effects of Adiposity on Cardiovascular Risk Factors 
Fall, Tove | Hägg, Sara | Ploner, Alexander | Mägi, Reedik | Fischer, Krista | Draisma, Harmen H.M. | Sarin, Antti-Pekka | Benyamin, Beben | Ladenvall, Claes | Åkerlund, Mikael | Kals, Mart | Esko, Tõnu | Nelson, Christopher P. | Kaakinen, Marika | Huikari, Ville | Mangino, Massimo | Meirhaeghe, Aline | Kristiansson, Kati | Nuotio, Marja-Liisa | Kobl, Michael | Grallert, Harald | Dehghan, Abbas | Kuningas, Maris | de Vries, Paul S. | de Bruijn, Renée F.A.G. | Willems, Sara M. | Heikkilä, Kauko | Silventoinen, Karri | Pietiläinen, Kirsi H. | Legry, Vanessa | Giedraitis, Vilmantas | Goumidi, Louisa | Syvänen, Ann-Christine | Strauch, Konstantin | Koenig, Wolfgang | Lichtner, Peter | Herder, Christian | Palotie, Aarno | Menni, Cristina | Uitterlinden, André G. | Kuulasmaa, Kari | Havulinna, Aki S. | Moreno, Luis A. | Gonzalez-Gross, Marcela | Evans, Alun | Tregouet, David-Alexandre | Yarnell, John W.G. | Virtamo, Jarmo | Ferrières, Jean | Veronesi, Giovanni | Perola, Markus | Arveiler, Dominique | Brambilla, Paolo | Lind, Lars | Kaprio, Jaakko | Hofman, Albert | Stricker, Bruno H. | van Duijn, Cornelia M. | Ikram, M. Arfan | Franco, Oscar H. | Cottel, Dominique | Dallongeville, Jean | Hall, Alistair S. | Jula, Antti | Tobin, Martin D. | Penninx, Brenda W. | Peters, Annette | Gieger, Christian | Samani, Nilesh J. | Montgomery, Grant W. | Whitfield, John B. | Martin, Nicholas G. | Groop, Leif | Spector, Tim D. | Magnusson, Patrik K. | Amouyel, Philippe | Boomsma, Dorret I. | Nilsson, Peter M. | Järvelin, Marjo-Riitta | Lyssenko, Valeriya | Metspalu, Andres | Strachan, David P. | Salomaa, Veikko | Ripatti, Samuli | Pedersen, Nancy L. | Prokopenko, Inga | McCarthy, Mark I. | Ingelsson, Erik
Diabetes  2015;64(5):1841-1852.
Observational studies have reported different effects of adiposity on cardiovascular risk factors across age and sex. Since cardiovascular risk factors are enriched in obese individuals, it has not been easy to dissect the effects of adiposity from those of other risk factors. We used a Mendelian randomization approach, applying a set of 32 genetic markers to estimate the causal effect of adiposity on blood pressure, glycemic indices, circulating lipid levels, and markers of inflammation and liver disease in up to 67,553 individuals. All analyses were stratified by age (cutoff 55 years of age) and sex. The genetic score was associated with BMI in both nonstratified analysis (P = 2.8 × 10−107) and stratified analyses (all P < 3.3 × 10−30). We found evidence of a causal effect of adiposity on blood pressure, fasting levels of insulin, C-reactive protein, interleukin-6, HDL cholesterol, and triglycerides in a nonstratified analysis and in the <55-year stratum. Further, we found evidence of a smaller causal effect on total cholesterol (P for difference = 0.015) in the ≥55-year stratum than in the <55-year stratum, a finding that could be explained by biology, survival bias, or differential medication. In conclusion, this study extends previous knowledge of the effects of adiposity by providing sex- and age-specific causal estimates on cardiovascular risk factors.
doi:10.2337/db14-0988
PMCID: PMC4407863  PMID: 25712996
9.  Cohort profile: the German Diabetes Study (GDS) 
Background
The German Diabetes Study (GDS) is a prospective longitudinal cohort study describing the impact of subphenotypes on the course of the disease. GDS aims at identifying prognostic factors and mechanisms underlying the development of related comorbidities.
Study design and methods
The study comprises intensive phenotyping within 12 months after clinical diagnosis, at 5-year intervals for 20 years and annual telephone interviews in between. Dynamic tests, including glucagon, mixed meal, intravenous glucose tolerance and hyperinsulinemic clamp tests, serve to assess beta-cell function and tissue-specific insulin sensitivity. Magnetic resonance imaging and multinuclei spectroscopy allow quantifying whole-body fat distribution, tissue-specific lipid deposition and energy metabolism. Comprehensive analyses of microvascular (nerve, eye, kidney) and macrovascular (endothelial, cardiorespiratory) morphology and function enable identification and monitoring of comorbidities. The GDS biobank stores specimens from blood, stool, skeletal muscle, subcutaneous adipose tissue and skin for future analyses including multiomics, expression profiles and histology. Repeated questionnaires on socioeconomic conditions, patient-reported outcomes as quality of life, health-related behavior as physical activity and nutritional habits are a specific asset of GDS. This study will recruit 3000 patients and a group of humans without familiy history of diabetes. 237 type 1 and 456 type 2 diabetes patients have been already included.
Electronic supplementary material
The online version of this article (doi:10.1186/s12933-016-0374-9) contains supplementary material, which is available to authorized users.
doi:10.1186/s12933-016-0374-9
PMCID: PMC4823856  PMID: 27053136
Insulin resistance; Magnetic resonance spectroscopy; Beta cell function; Metabolic phenotyping; Diabetes comorbidities
10.  Association between DNA Methylation in Whole Blood and Measures of Glucose Metabolism: KORA F4 Study 
PLoS ONE  2016;11(3):e0152314.
Epigenetic regulation has been postulated to affect glucose metabolism, insulin sensitivity and the risk of type 2 diabetes. Therefore, we performed an epigenome-wide association study for measures of glucose metabolism in whole blood samples of the population-based Cooperative Health Research in the Region of Augsburg F4 study using the Illumina HumanMethylation 450 BeadChip. We identified a total of 31 CpG sites where methylation level was associated with measures of glucose metabolism after adjustment for age, sex, smoking, and estimated white blood cell proportions and correction for multiple testing using the Benjamini-Hochberg (B-H) method (four for fasting glucose, seven for fasting insulin, 25 for homeostasis model assessment-insulin resistance [HOMA-IR]; B-H-adjusted p-values between 9.2x10-5 and 0.047). In addition, DNA methylation at cg06500161 (annotated to ABCG1) was associated with all the aforementioned phenotypes and 2-hour glucose (B-H-adjusted p-values between 9.2x10-5 and 3.0x10-3). Methylation status of additional three CpG sites showed an association with fasting insulin only after additional adjustment for body mass index (BMI) (B-H-adjusted p-values = 0.047). Overall, effect strengths were reduced by around 30% after additional adjustment for BMI, suggesting that this variable has an influence on the investigated phenotypes. Furthermore, we found significant associations between methylation status of 21 of the aforementioned CpG sites and 2-hour insulin in a subset of samples with seven significant associations persisting after additional adjustment for BMI. In a subset of 533 participants, methylation of the CpG site cg06500161 (ABCG1) was inversely associated with ABCG1 gene expression (B-H-adjusted p-value = 1.5x10-9). Additionally, we observed an enrichment of the top 1,000 CpG sites for diabetes-related canonical pathways using Ingenuity Pathway Analysis. In conclusion, our study indicates that DNA methylation and diabetes-related traits are associated and that these associations are partially BMI-dependent. Furthermore, the interaction of ABCG1 with glucose metabolism is modulated by epigenetic processes.
doi:10.1371/journal.pone.0152314
PMCID: PMC4809492  PMID: 27019061
11.  Influence of Acute and Chronic Exercise on Glucose Uptake 
Journal of Diabetes Research  2016;2016:2868652.
Insulin resistance plays a key role in the development of type 2 diabetes. It arises from a combination of genetic predisposition and environmental and lifestyle factors including lack of physical exercise and poor nutrition habits. The increased risk of type 2 diabetes is molecularly based on defects in insulin signaling, insulin secretion, and inflammation. The present review aims to give an overview on the molecular mechanisms underlying the uptake of glucose and related signaling pathways after acute and chronic exercise. Physical exercise, as crucial part in the prevention and treatment of diabetes, has marked acute and chronic effects on glucose disposal and related inflammatory signaling pathways. Exercise can stimulate molecular signaling pathways leading to glucose transport into the cell. Furthermore, physical exercise has the potential to modulate inflammatory processes by affecting specific inflammatory signaling pathways which can interfere with signaling pathways of the glucose uptake. The intensity of physical training appears to be the primary determinant of the degree of metabolic improvement modulating the molecular signaling pathways in a dose-response pattern, whereas training modality seems to have a secondary role.
doi:10.1155/2016/2868652
PMCID: PMC4812462  PMID: 27069930
12.  Genome-wide meta-analysis uncovers novel loci influencing circulating leptin levels 
Kilpeläinen, Tuomas O. | Carli, Jayne F. Martin | Skowronski, Alicja A. | Sun, Qi | Kriebel, Jennifer | Feitosa, Mary F | Hedman, Åsa K. | Drong, Alexander W. | Hayes, James E. | Zhao, Jinghua | Pers, Tune H. | Schick, Ursula | Grarup, Niels | Kutalik, Zoltán | Trompet, Stella | Mangino, Massimo | Kristiansson, Kati | Beekman, Marian | Lyytikäinen, Leo-Pekka | Eriksson, Joel | Henneman, Peter | Lahti, Jari | Tanaka, Toshiko | Luan, Jian'an | Greco M, Fabiola Del | Pasko, Dorota | Renström, Frida | Willems, Sara M. | Mahajan, Anubha | Rose, Lynda M. | Guo, Xiuqing | Liu, Yongmei | Kleber, Marcus E. | Pérusse, Louis | Gaunt, Tom | Ahluwalia, Tarunveer S. | Ju Sung, Yun | Ramos, Yolande F. | Amin, Najaf | Amuzu, Antoinette | Barroso, Inês | Bellis, Claire | Blangero, John | Buckley, Brendan M. | Böhringer, Stefan | I Chen, Yii-Der | de Craen, Anton J. N. | Crosslin, David R. | Dale, Caroline E. | Dastani, Zari | Day, Felix R. | Deelen, Joris | Delgado, Graciela E. | Demirkan, Ayse | Finucane, Francis M. | Ford, Ian | Garcia, Melissa E. | Gieger, Christian | Gustafsson, Stefan | Hallmans, Göran | Hankinson, Susan E. | Havulinna, Aki S | Herder, Christian | Hernandez, Dena | Hicks, Andrew A. | Hunter, David J. | Illig, Thomas | Ingelsson, Erik | Ioan-Facsinay, Andreea | Jansson, John-Olov | Jenny, Nancy S. | Jørgensen, Marit E. | Jørgensen, Torben | Karlsson, Magnus | Koenig, Wolfgang | Kraft, Peter | Kwekkeboom, Joanneke | Laatikainen, Tiina | Ladwig, Karl-Heinz | LeDuc, Charles A. | Lowe, Gordon | Lu, Yingchang | Marques-Vidal, Pedro | Meisinger, Christa | Menni, Cristina | Morris, Andrew P. | Myers, Richard H. | Männistö, Satu | Nalls, Mike A. | Paternoster, Lavinia | Peters, Annette | Pradhan, Aruna D. | Rankinen, Tuomo | Rasmussen-Torvik, Laura J. | Rathmann, Wolfgang | Rice, Treva K. | Brent Richards, J | Ridker, Paul M. | Sattar, Naveed | Savage, David B. | Söderberg, Stefan | Timpson, Nicholas J. | Vandenput, Liesbeth | van Heemst, Diana | Uh, Hae-Won | Vohl, Marie-Claude | Walker, Mark | Wichmann, Heinz-Erich | Widén, Elisabeth | Wood, Andrew R. | Yao, Jie | Zeller, Tanja | Zhang, Yiying | Meulenbelt, Ingrid | Kloppenburg, Margreet | Astrup, Arne | Sørensen, Thorkild I. A. | Sarzynski, Mark A. | Rao, D. C. | Jousilahti, Pekka | Vartiainen, Erkki | Hofman, Albert | Rivadeneira, Fernando | Uitterlinden, André G. | Kajantie, Eero | Osmond, Clive | Palotie, Aarno | Eriksson, Johan G. | Heliövaara, Markku | Knekt, Paul B. | Koskinen, Seppo | Jula, Antti | Perola, Markus | Huupponen, Risto K. | Viikari, Jorma S. | Kähönen, Mika | Lehtimäki, Terho | Raitakari, Olli T. | Mellström, Dan | Lorentzon, Mattias | Casas, Juan P. | Bandinelli, Stefanie | März, Winfried | Isaacs, Aaron | van Dijk, Ko W. | van Duijn, Cornelia M. | Harris, Tamara B. | Bouchard, Claude | Allison, Matthew A. | Chasman, Daniel I. | Ohlsson, Claes | Lind, Lars | Scott, Robert A. | Langenberg, Claudia | Wareham, Nicholas J. | Ferrucci, Luigi | Frayling, Timothy M. | Pramstaller, Peter P. | Borecki, Ingrid B. | Waterworth, Dawn M. | Bergmann, Sven | Waeber, Gérard | Vollenweider, Peter | Vestergaard, Henrik | Hansen, Torben | Pedersen, Oluf | Hu, Frank B. | Eline Slagboom, P | Grallert, Harald | Spector, Tim D. | Jukema, J.W. | Klein, Robert J. | Schadt, Erik E | Franks, Paul W. | Lindgren, Cecilia M. | Leibel, Rudolph L. | Loos, Ruth J. F.
Nature Communications  2016;7:10494.
Leptin is an adipocyte-secreted hormone, the circulating levels of which correlate closely with overall adiposity. Although rare mutations in the leptin (LEP) gene are well known to cause leptin deficiency and severe obesity, no common loci regulating circulating leptin levels have been uncovered. Therefore, we performed a genome-wide association study (GWAS) of circulating leptin levels from 32,161 individuals and followed up loci reaching P<10−6 in 19,979 additional individuals. We identify five loci robustly associated (P<5 × 10−8) with leptin levels in/near LEP, SLC32A1, GCKR, CCNL1 and FTO. Although the association of the FTO obesity locus with leptin levels is abolished by adjustment for BMI, associations of the four other loci are independent of adiposity. The GCKR locus was found associated with multiple metabolic traits in previous GWAS and the CCNL1 locus with birth weight. Knockdown experiments in mouse adipose tissue explants show convincing evidence for adipogenin, a regulator of adipocyte differentiation, as the novel causal gene in the SLC32A1 locus influencing leptin levels. Our findings provide novel insights into the regulation of leptin production by adipose tissue and open new avenues for examining the influence of variation in leptin levels on adiposity and metabolic health.
This meta-analysis of genome-wide association studies identifies four genetic loci associated with circulating leptin levels independent of adiposity. Examination in mouse adipose tissue explants provides functional support for the leptin-associated loci.
doi:10.1038/ncomms10494
PMCID: PMC4740377  PMID: 26833098
13.  Epigenome-wide association of DNA methylation markers in peripheral blood from Indian Asians and Europeans with incident type 2 diabetes: a nested case-control study 
Summary
Background
Indian Asians, who make up a quarter of the world’s population, are at high risk of developing type 2 diabetes. We investigated whether DNA methylation is associated with future type 2 diabetes incidence in Indian Asians and whether differences in methylation patterns between Indian Asians and Europeans are associated with, and could be used to predict, differences in the magnitude of risk of developing type 2 diabetes.
Methods
We did a nested case-control study of DNA methylation in Indian Asians and Europeans with incident type 2 diabetes who were identified from the 8-year follow-up of 25 372 participants in the London Life Sciences Prospective Population (LOLIPOP) study. Patients were recruited between May 1, 2002, and Sept 12, 2008. We did epigenome-wide association analysis using samples from Indian Asians with incident type 2 diabetes and age-matched and sex-matched Indian Asian controls, followed by replication testing of top-ranking signals in Europeans. For both discovery and replication, DNA methylation was measured in the baseline blood sample, which was collected before the onset of type 2 diabetes. Epigenome-wide significance was set at p<1 × 10−7. We compared methylation levels between Indian Asian and European controls without type 2 diabetes at baseline to estimate the potential contribution of DNA methylation to increased risk of future type 2 diabetes incidence among Indian Asians.
Findings
1608 (11·9%) of 13 535 Indian Asians and 306 (4·3%) of 7066 Europeans developed type 2 diabetes over a mean of 8·5 years (SD 1·8) of follow-up. The age-adjusted and sex-adjusted incidence of type 2 diabetes was 3·1 times (95% CI 2·8–3·6; p<0·0001) higher among Indian Asians than among Europeans, and remained 2·5 times (2·1–2·9; p<0·0001) higher after adjustment for adiposity, physical activity, family history of type 2 diabetes, and baseline glycaemic measures. The mean absolute difference in methylation level between type 2 diabetes cases and controls ranged from 0·5% (SD 0·1) to 1·1% (0·2). Methylation markers at five loci were associated with future type 2 diabetes incidence; the relative risk per 1% increase in methylation was 1·09 (95% CI 1·07–1·11; p=1·3 × 10−17) for ABCG1, 0·94 (0·92–0·95; p=4·2 × 10−11) for PHOSPHO1, 0·94 (0·92–0·96; p=1·4 × 10−9) for SOCS3, 1·07 (1·04–1·09; p=2·1 × 10−10) for SREBF1, and 0·92 (0·90–0·94; p=1·2 × 10−17) for TXNIP. A methylation score combining results for the five loci was associated with future type 2 diabetes incidence (relative risk quartile 4 vs quartile 1 3·51, 95% CI 2·79–4·42; p=1·3 × 10−26), and was independent of established risk factors. Methylation score was higher among Indian Asians than Europeans (p=1 × 10−34).
Interpretation
DNA methylation might provide new insights into the pathways underlying type 2 diabetes and offer new opportunities for risk stratification and prevention of type 2 diabetes among Indian Asians.
Funding
The European Union, the UK National Institute for Health Research, the Wellcome Trust, the UK Medical Research Council, Action on Hearing Loss, the UK Biotechnology and Biological Sciences Research Council, the Oak Foundation, the Economic and Social Research Council, Helmholtz Zentrum Munchen, the German Research Center for Environmental Health, the German Federal Ministry of Education and Research, the German Center for Diabetes Research, the Munich Center for Health Sciences, the Ministry of Science and Research of the State of North Rhine-Westphalia, and the German Federal Ministry of Health.
doi:10.1016/S2213-8587(15)00127-8
PMCID: PMC4724884  PMID: 26095709
14.  Genetic Determinants of Circulating Interleukin-1 Receptor Antagonist Levels and Their Association With Glycemic Traits 
Diabetes  2014;63(12):4343-4359.
The proinflammatory cytokine interleukin (IL)-1β is implicated in the development of insulin resistance and β-cell dysfunction, whereas higher circulating levels of IL-1 receptor antagonist (IL-1RA), an endogenous inhibitor of IL-1β, has been suggested to improve glycemia and β-cell function in patients with type 2 diabetes. To elucidate the protective role of IL-1RA, this study aimed to identify genetic determinants of circulating IL-1RA concentration and to investigate their associations with immunological and metabolic variables related to cardiometabolic risk. In the analysis of seven discovery and four replication cohort studies, two single nucleotide polymorphisms (SNPs) were independently associated with circulating IL-1RA concentration (rs4251961 at the IL1RN locus [n = 13,955, P = 2.76 × 10−21] and rs6759676, closest gene locus IL1F10 [n = 13,994, P = 1.73 × 10−17]). The proportion of the variance in IL-1RA explained by both SNPs combined was 2.0%. IL-1RA–raising alleles of both SNPs were associated with lower circulating C-reactive protein concentration. The IL-1RA–raising allele of rs6759676 was also associated with lower fasting insulin levels and lower HOMA insulin resistance. In conclusion, we show that circulating IL-1RA levels are predicted by two independent SNPs at the IL1RN and IL1F10 loci and that genetically raised IL-1RA may be protective against the development of insulin resistance.
doi:10.2337/db14-0731
PMCID: PMC4237993  PMID: 24969107
15.  The transcriptional landscape of age in human peripheral blood 
Peters, Marjolein J. | Joehanes, Roby | Pilling, Luke C. | Schurmann, Claudia | Conneely, Karen N. | Powell, Joseph | Reinmaa, Eva | Sutphin, George L. | Zhernakova, Alexandra | Schramm, Katharina | Wilson, Yana A. | Kobes, Sayuko | Tukiainen, Taru | Ramos, Yolande F. | Göring, Harald H. H. | Fornage, Myriam | Liu, Yongmei | Gharib, Sina A. | Stranger, Barbara E. | De Jager, Philip L. | Aviv, Abraham | Levy, Daniel | Murabito, Joanne M. | Munson, Peter J. | Huan, Tianxiao | Hofman, Albert | Uitterlinden, André G. | Rivadeneira, Fernando | van Rooij, Jeroen | Stolk, Lisette | Broer, Linda | Verbiest, Michael M. P. J. | Jhamai, Mila | Arp, Pascal | Metspalu, Andres | Tserel, Liina | Milani, Lili | Samani, Nilesh J. | Peterson, Pärt | Kasela, Silva | Codd, Veryan | Peters, Annette | Ward-Caviness, Cavin K. | Herder, Christian | Waldenberger, Melanie | Roden, Michael | Singmann, Paula | Zeilinger, Sonja | Illig, Thomas | Homuth, Georg | Grabe, Hans-Jörgen | Völzke, Henry | Steil, Leif | Kocher, Thomas | Murray, Anna | Melzer, David | Yaghootkar, Hanieh | Bandinelli, Stefania | Moses, Eric K. | Kent, Jack W. | Curran, Joanne E. | Johnson, Matthew P. | Williams-Blangero, Sarah | Westra, Harm-Jan | McRae, Allan F. | Smith, Jennifer A. | Kardia, Sharon L. R. | Hovatta, Iiris | Perola, Markus | Ripatti, Samuli | Salomaa, Veikko | Henders, Anjali K. | Martin, Nicholas G. | Smith, Alicia K. | Mehta, Divya | Binder, Elisabeth B. | Nylocks, K Maria | Kennedy, Elizabeth M. | Klengel, Torsten | Ding, Jingzhong | Suchy-Dicey, Astrid M. | Enquobahrie, Daniel A. | Brody, Jennifer | Rotter, Jerome I. | Chen, Yii-Der I. | Houwing-Duistermaat, Jeanine | Kloppenburg, Margreet | Slagboom, P. Eline | Helmer, Quinta | den Hollander, Wouter | Bean, Shannon | Raj, Towfique | Bakhshi, Noman | Wang, Qiao Ping | Oyston, Lisa J. | Psaty, Bruce M. | Tracy, Russell P. | Montgomery, Grant W. | Turner, Stephen T. | Blangero, John | Meulenbelt, Ingrid | Ressler, Kerry J. | Yang, Jian | Franke, Lude | Kettunen, Johannes | Visscher, Peter M. | Neely, G. Gregory | Korstanje, Ron | Hanson, Robert L. | Prokisch, Holger | Ferrucci, Luigi | Esko, Tonu | Teumer, Alexander | van Meurs, Joyce B. J. | Johnson, Andrew D.
Nature Communications  2015;6:8570.
Disease incidences increase with age, but the molecular characteristics of ageing that lead to increased disease susceptibility remain inadequately understood. Here we perform a whole-blood gene expression meta-analysis in 14,983 individuals of European ancestry (including replication) and identify 1,497 genes that are differentially expressed with chronological age. The age-associated genes do not harbor more age-associated CpG-methylation sites than other genes, but are instead enriched for the presence of potentially functional CpG-methylation sites in enhancer and insulator regions that associate with both chronological age and gene expression levels. We further used the gene expression profiles to calculate the ‘transcriptomic age' of an individual, and show that differences between transcriptomic age and chronological age are associated with biological features linked to ageing, such as blood pressure, cholesterol levels, fasting glucose, and body mass index. The transcriptomic prediction model adds biological relevance and complements existing epigenetic prediction models, and can be used by others to calculate transcriptomic age in external cohorts.
Ageing increases the risk of many diseases. Here the authors compare blood cell transcriptomes of over 14,000 individuals and identify a set of about 1,500 genes that are differently expressed with age, shedding light on transcriptional programs linked to the ageing process and age-associated diseases.
doi:10.1038/ncomms9570
PMCID: PMC4639797  PMID: 26490707
16.  Extensive alterations of the whole-blood transcriptome are associated with body mass index: results of an mRNA profiling study involving two large population-based cohorts 
BMC Medical Genomics  2015;8:65.
Background
Obesity, defined as pathologically increased body mass index (BMI), is strongly related to an increased risk for numerous common cardiovascular and metabolic diseases. It is particularly associated with insulin resistance, hyperglycemia, and systemic oxidative stress and represents the most important risk factor for type 2 diabetes (T2D). However, the pathophysiological mechanisms underlying these associations are still not completely understood. Therefore, in order to identify potentially disease-relevant BMI-associated gene expression signatures, a transcriptome-wide association study (TWAS) on BMI was performed.
Methods
Whole-blood mRNA levels determined by array-based transcriptional profiling were correlated with BMI in two large independent population-based cohort studies (KORA F4 and SHIP-TREND) comprising a total of 1977 individuals.
Results
Extensive alterations of the whole-blood transcriptome were associated with BMI: More than 3500 transcripts exhibited significant positive or negative BMI-correlation. Three major whole-blood gene expression signatures associated with increased BMI were identified. The three signatures suggested: i) a ratio shift from mature erythrocytes towards reticulocytes, ii) decreased expression of several genes essentially involved in the transmission and amplification of the insulin signal, and iii) reduced expression of several key genes involved in the defence against reactive oxygen species (ROS).
Conclusions
Whereas the first signature confirms published results, the other two provide possible mechanistic explanations for well-known epidemiological findings under conditions of increased BMI, namely attenuated insulin signaling and increased oxidative stress. The putatively causative BMI-dependent down-regulation of the expression of numerous genes on the mRNA level represents a novel finding. BMI-associated negative transcriptional regulation of insulin signaling and oxidative stress management provide new insights into the pathogenesis of metabolic syndrome and T2D.
Electronic supplementary material
The online version of this article (doi:10.1186/s12920-015-0141-x) contains supplementary material, which is available to authorized users.
doi:10.1186/s12920-015-0141-x
PMCID: PMC4608219  PMID: 26470795
Transcriptomics; Transcriptome-wide association study (TWAS); BMI; Obesity; Insulin resistance; Type 2 diabetes; Oxidative stress; Insulin signaling
17.  Discovery and Fine-Mapping of Glycaemic and Obesity-Related Trait Loci Using High-Density Imputation 
Horikoshi, Momoko | Mӓgi, Reedik | van de Bunt, Martijn | Surakka, Ida | Sarin, Antti-Pekka | Mahajan, Anubha | Marullo, Letizia | Thorleifsson, Gudmar | Hӓgg, Sara | Hottenga, Jouke-Jan | Ladenvall, Claes | Ried, Janina S. | Winkler, Thomas W. | Willems, Sara M. | Pervjakova, Natalia | Esko, Tõnu | Beekman, Marian | Nelson, Christopher P. | Willenborg, Christina | Wiltshire, Steven | Ferreira, Teresa | Fernandez, Juan | Gaulton, Kyle J. | Steinthorsdottir, Valgerdur | Hamsten, Anders | Magnusson, Patrik K. E. | Willemsen, Gonneke | Milaneschi, Yuri | Robertson, Neil R. | Groves, Christopher J. | Bennett, Amanda J. | Lehtimӓki, Terho | Viikari, Jorma S. | Rung, Johan | Lyssenko, Valeriya | Perola, Markus | Heid, Iris M. | Herder, Christian | Grallert, Harald | Müller-Nurasyid, Martina | Roden, Michael | Hypponen, Elina | Isaacs, Aaron | van Leeuwen, Elisabeth M. | Karssen, Lennart C. | Mihailov, Evelin | Houwing-Duistermaat, Jeanine J. | de Craen, Anton J. M. | Deelen, Joris | Havulinna, Aki S. | Blades, Matthew | Hengstenberg, Christian | Erdmann, Jeanette | Schunkert, Heribert | Kaprio, Jaakko | Tobin, Martin D. | Samani, Nilesh J. | Lind, Lars | Salomaa, Veikko | Lindgren, Cecilia M. | Slagboom, P. Eline | Metspalu, Andres | van Duijn, Cornelia M. | Eriksson, Johan G. | Peters, Annette | Gieger, Christian | Jula, Antti | Groop, Leif | Raitakari, Olli T. | Power, Chris | Penninx, Brenda W. J. H. | de Geus, Eco | Smit, Johannes H. | Boomsma, Dorret I. | Pedersen, Nancy L. | Ingelsson, Erik | Thorsteinsdottir, Unnur | Stefansson, Kari | Ripatti, Samuli | Prokopenko, Inga | McCarthy, Mark I. | Morris, Andrew P.
PLoS Genetics  2015;11(7):e1005230.
Reference panels from the 1000 Genomes (1000G) Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency ≥0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE) Consortium, we have undertaken the first large-scale meta-analysis of genome-wide association studies (GWAS), supplemented by 1000G imputation, for four quantitative glycaemic and obesity-related traits, in up to 87,048 individuals of European ancestry. We identified two loci for body mass index (BMI) at genome-wide significance, and two for fasting glucose (FG), none of which has been previously reported in larger meta-analysis efforts to combine GWAS of European ancestry. Through conditional analysis, we also detected multiple distinct signals of association mapping to established loci for waist-hip ratio adjusted for BMI (RSPO3) and FG (GCK and G6PC2). The index variant for one association signal at the G6PC2 locus is a low-frequency coding allele, H177Y, which has recently been demonstrated to have a functional role in glucose regulation. Fine-mapping analyses revealed that the non-coding variants most likely to drive association signals at established and novel loci were enriched for overlap with enhancer elements, which for FG mapped to promoter and transcription factor binding sites in pancreatic islets, in particular. Our study demonstrates that 1000G imputation and genetic fine-mapping of common and low-frequency variant association signals at GWAS loci, integrated with genomic annotation in relevant tissues, can provide insight into the functional and regulatory mechanisms through which their effects on glycaemic and obesity-related traits are mediated.
Author Summary
Human genetic studies have demonstrated that quantitative human anthropometric and metabolic traits, including body mass index, waist-hip ratio, and plasma concentrations of glucose and insulin, are highly heritable, and are established risk factors for type 2 diabetes and cardiovascular diseases. Although many regions of the genome have been associated with these traits, the specific genes responsible have not yet been identified. By making use of advanced statistical “imputation” techniques applied to more than 87,000 individuals of European ancestry, and publicly available “reference panels” of more than 37 million genetic variants, we have been able to identify novel regions of the genome associated with these glycaemic and obesity-related traits and localise genes within these regions that are most likely to be causal. This improved understanding of the biological mechanisms underlying glycaemic and obesity-related traits is extremely important because it may advance drug development for downstream disease endpoints, ultimately leading to public health benefits.
doi:10.1371/journal.pgen.1005230
PMCID: PMC4488845  PMID: 26132169
18.  The Human Blood Metabolome-Transcriptome Interface 
PLoS Genetics  2015;11(6):e1005274.
Biological systems consist of multiple organizational levels all densely interacting with each other to ensure function and flexibility of the system. Simultaneous analysis of cross-sectional multi-omics data from large population studies is a powerful tool to comprehensively characterize the underlying molecular mechanisms on a physiological scale. In this study, we systematically analyzed the relationship between fasting serum metabolomics and whole blood transcriptomics data from 712 individuals of the German KORA F4 cohort. Correlation-based analysis identified 1,109 significant associations between 522 transcripts and 114 metabolites summarized in an integrated network, the ‘human blood metabolome-transcriptome interface’ (BMTI). Bidirectional causality analysis using Mendelian randomization did not yield any statistically significant causal associations between transcripts and metabolites. A knowledge-based interpretation and integration with a genome-scale human metabolic reconstruction revealed systematic signatures of signaling, transport and metabolic processes, i.e. metabolic reactions mainly belonging to lipid, energy and amino acid metabolism. Moreover, the construction of a network based on functional categories illustrated the cross-talk between the biological layers at a pathway level. Using a transcription factor binding site enrichment analysis, this pathway cross-talk was further confirmed at a regulatory level. Finally, we demonstrated how the constructed networks can be used to gain novel insights into molecular mechanisms associated to intermediate clinical traits. Overall, our results demonstrate the utility of a multi-omics integrative approach to understand the molecular mechanisms underlying both normal physiology and disease.
Author Summary
Biological systems operate on multiple, intertwined organizational layers that can nowadays be accesses by high-throughput measurement methods, the so-called ‘omics’ technologies. A major aim in the field of systems biology is to understand the flow of biological information between the different layers at a systems level in both health and disease. To unravel the complex mechanisms underlying those molecular processes and to understand how the different functional levels interact with each other, an integrated analysis of multiple layers, i.e. a ‘multi-omics‘ approach is required. In our present study, we investigate the relationship between circulating metabolites in serum and whole-blood gene expression measured in the blood of individuals from a population-based cohort. To this end, we constructed a correlation network that displays which transcript and metabolite show the same trend of up- and down-regulation. We derived a functional characterization of the network by developing a novel computational analysis. The analysis revealed systematic signatures of signaling, transport and metabolic processes on both a regulatory and a pathway level. Moreover, integrating the network with associations to clinical markers such as HDL-cholesterol, LDL-cholesterol and TG identified coordinately activated pathways or modules which might help to assess the molecular machinery behind such an intermediate phenotype.
doi:10.1371/journal.pgen.1005274
PMCID: PMC4473262  PMID: 26086077
19.  Association between Advanced Glycation End Products and Impaired Fasting Glucose: Results from the SALIA Study 
PLoS ONE  2015;10(5):e0128293.
Advanced glycation end products (AGEs) may contribute to the development of type 2 diabetes and related complications, whereas their role in the early deterioration of glycaemia is unknown. While previous studies used antibody-based methods to quantify AGEs, data from tandem mass spectrometry coupled liquid chromatography (LC-MS/MS)-based measurements are limited to patients with known diabetes. Here, we used the LC-MS/MS method to test the hypothesis that plasma AGE levels are higher in individuals with impaired fasting glucose (IFG) than in those with normal fasting glucose (NFG). Secondary aims were to assess correlations of plasma AGEs with quantitative markers of glucose metabolism and biomarkers of subclinical inflammation. This study included on 60 women with NFG or IFG (n = 30 each, mean age 74 years) from the German SALIA cohort. Plasma levels of free metabolites (3-deoxyfructose, 3-deoxypentosone, 3-deoxypentulose), two hydroimidazolones, oxidised adducts (carboxymethyllysine, carboxyethyllysine, methionine sulfoxide) and Nε-fructosyllysine were measured using LC-MS/MS. Plasma concentrations of all tested AGEs did not differ between the NFG and IFG groups (all p>0.05). Associations between plasma levels of AGEs and fasting glucose, insulin and HOMA-IR as a measure of insulin resistance were weak (r between -0.2 and 0.2, all p>0.05). The association between 3-deoxyglucosone-derived hydroimidazolone with several proinflammatory biomarkers disappeared upon adjustment for multiple testing. In conclusion, plasma AGEs assessed by LC-MS/MS were neither increased in IFG nor associated with parameters of glucose metabolism and subclinical inflammation in our study. Thus, these data argue against strong effects of AGEs in the early stages of deterioration of glucose metabolism.
doi:10.1371/journal.pone.0128293
PMCID: PMC4446029  PMID: 26018950
20.  Cell Specific eQTL Analysis without Sorting Cells 
PLoS Genetics  2015;11(5):e1005223.
The functional consequences of trait associated SNPs are often investigated using expression quantitative trait locus (eQTL) mapping. While trait-associated variants may operate in a cell-type specific manner, eQTL datasets for such cell-types may not always be available. We performed a genome-environment interaction (GxE) meta-analysis on data from 5,683 samples to infer the cell type specificity of whole blood cis-eQTLs. We demonstrate that this method is able to predict neutrophil and lymphocyte specific cis-eQTLs and replicate these predictions in independent cell-type specific datasets. Finally, we show that SNPs associated with Crohn’s disease preferentially affect gene expression within neutrophils, including the archetypal NOD2 locus.
Author Summary
Many variants in the genome, including variants associated with disease, affect the expression of genes. These so-called expression quantitative trait loci (eQTL) can be used to gain insight in the downstream consequences of disease. While it has been shown that many disease-associated variants alter gene expression in a cell-type dependent manner, eQTL datasets for specific cell types may not always be available and their sample size is often limited. We present a method that is able to detect cell type specific effects within eQTL datasets that have been generated from whole tissues (which may be composed of many cell types), in our case whole blood. By combining numerous whole blood datasets through meta-analysis, we show that we are able to detect eQTL effects that are specific for neutrophils and lymphocytes (two blood cell types). Additionally, we show that the variants associated with some diseases may preferentially alter the gene expression in one of these cell types. We conclude that our method is an alternative method to detect cell type specific eQTL effects, that may complement generating cell type specific eQTL datasets and that may be applied on other cell types and tissues as well.
doi:10.1371/journal.pgen.1005223
PMCID: PMC4425538  PMID: 25955312
21.  Serum Chemerin Concentrations Associate with Beta-Cell Function, but Not with Insulin Resistance in Individuals with Non-Alcoholic Fatty Liver Disease (NAFLD) 
PLoS ONE  2015;10(5):e0124935.
The novel adipokine chemerin has been related to insulin-resistant states such as obesity and non alcoholic fatty liver disease (NAFLD). However, its association with insulin resistance and beta cell function remains controversial. The main objective was to examine whether serum chemerin levels associate with insulin sensitivity and beta cell function independently of body mass index (BMI), by studying consecutive outpatients of the hepatology clinics of a European university hospital. Individuals (n=196) with NAFLD were stratified into persons with normal glucose tolerance (NGT; n=110), impaired glucose tolerance (IGT; n=51) and type 2 diabetes (T2D; n=35) and the association between serum chemerin and measures of insulin sensitivity and beta cell function as assessed during fasting and during oral glucose tolerance test (OGTT) was measured. Our results showed that serum chemerin positively associated with BMI (P=0.0007) and C peptide during OGTT (P<0.004), but not with circulating glucose, insulin, lipids or liver enzymes (all P>0.18). No BMI independent relationships of chemerin with fasting and OGTT derived measures of insulin sensitivity were found (P>0.5). Chemerin associated positively with fasting beta cell function as well as the OGTT derived insulinogenic index IGI_cp and the adaptation index after adjustment for age, sex and BMI (P=0.002-0.007), and inversely with the insulin/C peptide ratio (P=0.007). Serum chemerin neither related to the insulinogenic index IGI_ins nor the disposition index. In conclusion, circulating chemerin is likely linked to enhanced beta cell function but not to insulin sensitivity in patients with NAFLD.
doi:10.1371/journal.pone.0124935
PMCID: PMC4416815  PMID: 25933030
22.  Differential Patterns and Determinants of Cardiac Autonomic Nerve Dysfunction during Endotoxemia and Oral Fat Load in Humans 
PLoS ONE  2015;10(4):e0124242.
The autonomic nervous system (ANS) plays an important role in regulating the metabolic homeostasis and controlling immune function. ANS alterations can be detected by reduced heart rate variability (HRV) in conditions like diabetes and sepsis. We determined the effects of experimental conditions mimicking inflammation and hyperlipidemia on HRV and heart rate (HR) in relation to the immune, metabolic, and hormonal responses resulting from these interventions. Sixteen lean healthy subjects received intravenous (i.v.) low-dose endotoxin (lipopolysaccharide [LPS]), i.v. fat, oral fat, and i.v. glycerol (control) for 6 hours, during which immune, metabolic, hormonal, and five HRV parameters (pNN50, RMSSD, low-frequency (LF) and high-frequency (HF) power, and LF/HF ratio) were monitored and energy metabolism and insulin sensitivity (M-value) were assessed. LPS infusion induced an increase (AUC) in HR and LF/HF ratio and decline in pNN50 and RMSSD, while oral fat resulted in elevated HR and a transient (hours 1-2) decrease in pNN50, RMSSD, and HF power. During LPS infusion, ΔIL-1ra levels and ΔIL-1ra and ΔIL-1ß gene expression correlated positively with ΔLF/HF ratio and inversely with ΔRMSSD. During oral fat intake, ΔGLP-1 tended to correlate positively with ΔHR and inversely with ΔpNN50 and ΔRMSSD. Following LPS infusion, lipid oxidation correlated positively with HR and inversely with pNN50 and RMSSD, whereas HRV was not related to M-value. In conclusion, suppression of vagal tone and sympathetic predominance during endotoxemia are linked to anti-inflammatory processes and lipid oxidation but not to insulin resistance, while weaker HRV changes in relation to the GLP-1 response are noted during oral fat load.
Trial Registration
ClinicalTrials.gov NCT01054989
doi:10.1371/journal.pone.0124242
PMCID: PMC4403853  PMID: 25893426
23.  A Meta-analysis of Gene Expression Signatures of Blood Pressure and Hypertension 
PLoS Genetics  2015;11(3):e1005035.
Genome-wide association studies (GWAS) have uncovered numerous genetic variants (SNPs) that are associated with blood pressure (BP). Genetic variants may lead to BP changes by acting on intermediate molecular phenotypes such as coded protein sequence or gene expression, which in turn affect BP variability. Therefore, characterizing genes whose expression is associated with BP may reveal cellular processes involved in BP regulation and uncover how transcripts mediate genetic and environmental effects on BP variability. A meta-analysis of results from six studies of global gene expression profiles of BP and hypertension in whole blood was performed in 7017 individuals who were not receiving antihypertensive drug treatment. We identified 34 genes that were differentially expressed in relation to BP (Bonferroni-corrected p<0.05). Among these genes, FOS and PTGS2 have been previously reported to be involved in BP-related processes; the others are novel. The top BP signature genes in aggregate explain 5%–9% of inter-individual variance in BP. Of note, rs3184504 in SH2B3, which was also reported in GWAS to be associated with BP, was found to be a trans regulator of the expression of 6 of the transcripts we found to be associated with BP (FOS, MYADM, PP1R15A, TAGAP, S100A10, and FGBP2). Gene set enrichment analysis suggested that the BP-related global gene expression changes include genes involved in inflammatory response and apoptosis pathways. Our study provides new insights into molecular mechanisms underlying BP regulation, and suggests novel transcriptomic markers for the treatment and prevention of hypertension.
Author Summary
The focus of blood pressure (BP) GWAS has been the identification of common DNA sequence variants associated with the phenotype; this approach provides only one dimension of molecular information about BP. While it is a critical dimension, analyzing DNA variation alone is not sufficient for achieving an understanding of the multidimensional complexity of BP physiology. The top loci identified by GWAS explain only about 1 percent of inter-individual BP variability. In this study, we performed a meta-analysis of gene expression profiles in relation to BP and hypertension in 7017 individuals from six studies. We identified 34 differentially expressed genes for BP, and discovered that the top BP signature genes explain 5%–9% of BP variability. We further linked BP gene expression signature genes with BP GWAS results by integrating expression associated SNPs (eSNPs) and discovered that one of the top BP loci from GWAS, rs3184504 in SH2B3, is a trans regulator of expression of 6 of the top 34 BP signature genes. Our study, in conjunction with prior GWAS, provides a deeper understanding of the molecular and genetic basis of BP regulation, and identifies several potential targets and pathways for the treatment and prevention of hypertension and its sequelae.
doi:10.1371/journal.pgen.1005035
PMCID: PMC4365001  PMID: 25785607
24.  Multi-omic signature of body weight change: results from a population-based cohort study 
BMC Medicine  2015;13:48.
Background
Excess body weight is a major risk factor for cardiometabolic diseases. The complex molecular mechanisms of body weight change-induced metabolic perturbations are not fully understood. Specifically, in-depth molecular characterization of long-term body weight change in the general population is lacking. Here, we pursued a multi-omic approach to comprehensively study metabolic consequences of body weight change during a seven-year follow-up in a large prospective study.
Methods
We used data from the population-based Cooperative Health Research in the Region of Augsburg (KORA) S4/F4 cohort. At follow-up (F4), two-platform serum metabolomics and whole blood gene expression measurements were obtained for 1,631 and 689 participants, respectively. Using weighted correlation network analysis, omics data were clustered into modules of closely connected molecules, followed by the formation of a partial correlation network from the modules. Association of the omics modules with previous annual percentage weight change was then determined using linear models. In addition, we performed pathway enrichment analyses, stability analyses, and assessed the relation of the omics modules with clinical traits.
Results
Four metabolite and two gene expression modules were significantly and stably associated with body weight change (P-values ranging from 1.9 × 10−4 to 1.2 × 10−24). The four metabolite modules covered major branches of metabolism, with VLDL, LDL and large HDL subclasses, triglycerides, branched-chain amino acids and markers of energy metabolism among the main representative molecules. One gene expression module suggests a role of weight change in red blood cell development. The other gene expression module largely overlaps with the lipid-leukocyte (LL) module previously reported to interact with serum metabolites, for which we identify additional co-expressed genes. The omics modules were interrelated and showed cross-sectional associations with clinical traits. Moreover, weight gain and weight loss showed largely opposing associations with the omics modules.
Conclusions
Long-term weight change in the general population globally associates with serum metabolite concentrations. An integrated metabolomics and transcriptomics approach improved the understanding of molecular mechanisms underlying the association of weight gain with changes in lipid and amino acid metabolism, insulin sensitivity, mitochondrial function as well as blood cell development and function.
Electronic supplementary material
The online version of this article (doi:10.1186/s12916-015-0282-y) contains supplementary material, which is available to authorized users.
doi:10.1186/s12916-015-0282-y
PMCID: PMC4367822  PMID: 25857605
Metabolomics; Transcriptomics; Weight change; Obesity; Molecular epidemiology; Bioinformatics
25.  Regional Differences of Undiagnosed Type 2 Diabetes and Prediabetes Prevalence Are Not Explained by Known Risk Factors 
PLoS ONE  2014;9(11):e113154.
Background
We have previously found regional differences in the prevalence of known type 2 diabetes between northeastern and southern Germany. We aim to also provide prevalence estimates for prediabetes (isolated impaired fasting glucose (i-IFG), isolated glucose intolerance (i-IGT), combined IFG and IGT) and unknown type 2 diabetes for both regions.
Methods
Prevalence (95%CI) of prediabetes (i-IFG: fasting glucose 5.6–6.9 mmol/l; i-IGT: 2 h postchallenge gluose 7.8–11.0 mmol/l, oral glucose tolerance test (OGTT), ≥8 h overnight fasting) and unknown diabetes were analyzed in two regional population-based surveys (age group 35–79 years): SHIP-TREND (Study of Health in Pomerania (northeast), 2008–2012) and KORA F4 (Cooperative Health Research in the region of Augsburg (south), 2006–2008). Both studies used similar methods, questionnaires, and identical protocols for OGTT. Overall, 1,980 participants from SHIP-TREND and 2,617 participants from KORA F4 were included.
Results
Age-sex-standardized prevalence estimates (95%CI) of prediabetes and unknown diabetes were considerably higher in the northeast (SHIP-TREND: 43.1%; 40.9–45.3% and 7.1%; 5.9–8.2%) than in the south of Germany (KORA F4: 30.1%; 28.4–31.7% and 3.9%; 3.2–4.6%), respectively. In particular, i-IFG (26.4%; 24.5–28.3% vs. 17.2%; 15.7–18.6%) and IFG+IGT (11.2%; 9.8–12.6% vs. 6.6%; 5.7–7.5%) were more frequent in SHIP-TREND than in KORA. In comparison to normal glucose tolerance, the odds of having unknown diabetes (OR, 95%CI: 2.59; 1.84–3.65) or prediabetes (1.98; 1.70–2.31) was higher in the northeast than in the south after adjustment for known risk factors (obesity, lifestyle).
Conclusions
The regional differences of prediabetes and unknown diabetes are in line with the geographical pattern of known diabetes in Germany. The higher prevalences in the northeast were not explained by traditional risk factors.
doi:10.1371/journal.pone.0113154
PMCID: PMC4234669  PMID: 25402347

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