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1. Discovery and Fine-Mapping of Glycaemic and Obesity-Related Trait Loci Using High-Density Imputation.

Author

Momoko Horikoshi, Reedik Mӓgi, Martijn van de Bunt, Ida Surakka, Antti-Pekka Sarin, Anubha Mahajan, Letizia Marullo, Gudmar Thorleifsson, Sara Hӓgg, Jouke-Jan Hottenga, Claes Ladenvall, Janina S Ried, Thomas W Winkler, Sara M Willems, Natalia Pervjakova, Tõnu Esko, Marian Beekman, Christopher P Nelson, Christina Willenborg, Steven Wiltshire, Teresa Ferreira, Juan Fernandez, Kyle J Gaulton, Valgerdur Steinthorsdottir, Anders Hamsten, Patrik K E Magnusson, Gonneke Willemsen, Yuri Milaneschi, Neil R Robertson, Christopher J Groves, Amanda J Bennett, Terho Lehtimӓki, Jorma S Viikari, Johan Rung, Valeriya Lyssenko, Markus Perola, Iris M Heid, Christian Herder, Harald Grallert, Martina Müller-Nurasyid, Michael Roden, Elina Hypponen, Aaron Isaacs, Elisabeth M van Leeuwen, Lennart C Karssen, Evelin Mihailov, Jeanine J Houwing-Duistermaat, Anton J M de Craen, Joris Deelen, Aki S Havulinna, Matthew Blades, Christian Hengstenberg, Jeanette Erdmann, Heribert Schunkert, Jaakko Kaprio, Martin D Tobin, Nilesh J Samani, Lars Lind, Veikko Salomaa, Cecilia M Lindgren, P Eline Slagboom, Andres Metspalu, Cornelia M van Duijn, Johan G Eriksson, Annette Peters, Christian Gieger, Antti Jula, Leif Groop, Olli T Raitakari, Chris Power, Brenda W J H Penninx, Eco de Geus, Johannes H Smit, Dorret I Boomsma, Nancy L Pedersen, Erik Ingelsson, Unnur Thorsteinsdottir, Kari Stefansson, Samuli Ripatti, Inga Prokopenko, Mark I McCarthy, Andrew P Morris, and ENGAGE Consortium

Subjects
Genetics, QH426-470
Abstract

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.

Published
2015
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2. The role of adiposity in cardiometabolic traits: a Mendelian randomization analysis.

Author

Tove Fall, Sara Hägg, Reedik Mägi, Alexander Ploner, Krista Fischer, Momoko Horikoshi, Antti-Pekka Sarin, Gudmar Thorleifsson, Claes Ladenvall, Mart Kals, Maris Kuningas, Harmen H M Draisma, Janina S Ried, Natalie R van Zuydam, Ville Huikari, Massimo Mangino, Emily Sonestedt, Beben Benyamin, Christopher P Nelson, Natalia V Rivera, Kati Kristiansson, Huei-Yi Shen, Aki S Havulinna, Abbas Dehghan, Louise A Donnelly, Marika Kaakinen, Marja-Liisa Nuotio, Neil Robertson, Renée F A G de Bruijn, M Arfan Ikram, Najaf Amin, Anthony J Balmforth, Peter S Braund, Alexander S F Doney, Angela Döring, Paul Elliott, Tõnu Esko, Oscar H Franco, Solveig Gretarsdottir, Anna-Liisa Hartikainen, Kauko Heikkilä, Karl-Heinz Herzig, Hilma Holm, Jouke Jan Hottenga, Elina Hyppönen, Thomas Illig, Aaron Isaacs, Bo Isomaa, Lennart C Karssen, Johannes Kettunen, Wolfgang Koenig, Kari Kuulasmaa, Tiina Laatikainen, Jaana Laitinen, Cecilia Lindgren, Valeriya Lyssenko, Esa Läärä, Nigel W Rayner, Satu Männistö, Anneli Pouta, Wolfgang Rathmann, Fernando Rivadeneira, Aimo Ruokonen, Markku J Savolainen, Eric J G Sijbrands, Kerrin S Small, Jan H Smit, Valgerdur Steinthorsdottir, Ann-Christine Syvänen, Anja Taanila, Martin D Tobin, Andre G Uitterlinden, Sara M Willems, Gonneke Willemsen, Jacqueline Witteman, Markus Perola, Alun Evans, Jean Ferrières, Jarmo Virtamo, Frank Kee, David-Alexandre Tregouet, Dominique Arveiler, Philippe Amouyel, Marco M Ferrario, Paolo Brambilla, Alistair S Hall, Andrew C Heath, Pamela A F Madden, Nicholas G Martin, Grant W Montgomery, John B Whitfield, Antti Jula, Paul Knekt, Ben Oostra, Cornelia M van Duijn, Brenda W J H Penninx, George Davey Smith, Jaakko Kaprio, Nilesh J Samani, Christian Gieger, Annette Peters, H Erich Wichmann, Dorret I Boomsma, Eco J C de Geus, TiinaMaija Tuomi, Chris Power, Christopher J Hammond, Tim D Spector, Lars Lind, Marju Orho-Melander, Colin Neil Alexander Palmer, Andrew D Morris, Leif Groop, Marjo-Riitta Järvelin, Veikko Salomaa, Erkki Vartiainen, Albert Hofman, Samuli Ripatti, Andres Metspalu, Unnur Thorsteinsdottir, Kari Stefansson, Nancy L Pedersen, Mark I McCarthy, Erik Ingelsson, Inga Prokopenko, and European Network for Genetic and Genomic Epidemiology (ENGAGE) consortium

Subjects
Medicine
Abstract

BackgroundThe association between adiposity and cardiometabolic traits is well known from epidemiological studies. Whilst the causal relationship is clear for some of these traits, for others it is not. We aimed to determine whether adiposity is causally related to various cardiometabolic traits using the Mendelian randomization approach.Methods and findingsWe used the adiposity-associated variant rs9939609 at the FTO locus as an instrumental variable (IV) for body mass index (BMI) in a Mendelian randomization design. Thirty-six population-based studies of individuals of European descent contributed to the analyses. Age- and sex-adjusted regression models were fitted to test for association between (i) rs9939609 and BMI (n = 198,502), (ii) rs9939609 and 24 traits, and (iii) BMI and 24 traits. The causal effect of BMI on the outcome measures was quantified by IV estimators. The estimators were compared to the BMI-trait associations derived from the same individuals. In the IV analysis, we demonstrated novel evidence for a causal relationship between adiposity and incident heart failure (hazard ratio, 1.19 per BMI-unit increase; 95% CI, 1.03-1.39) and replicated earlier reports of a causal association with type 2 diabetes, metabolic syndrome, dyslipidemia, and hypertension (odds ratio for IV estimator, 1.1-1.4; all p < 0.05). For quantitative traits, our results provide novel evidence for a causal effect of adiposity on the liver enzymes alanine aminotransferase and gamma-glutamyl transferase and confirm previous reports of a causal effect of adiposity on systolic and diastolic blood pressure, fasting insulin, 2-h post-load glucose from the oral glucose tolerance test, C-reactive protein, triglycerides, and high-density lipoprotein cholesterol levels (all p < 0.05). The estimated causal effects were in agreement with traditional observational measures in all instances except for type 2 diabetes, where the causal estimate was larger than the observational estimate (p = 0.001).ConclusionsWe provide novel evidence for a causal relationship between adiposity and heart failure as well as between adiposity and increased liver enzymes.

Published
2013
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3. Development and application of genomic control methods for genome-wide association studies using non-additive models.

Author

Yakov A Tsepilov, Janina S Ried, Konstantin Strauch, Harald Grallert, Cornelia M van Duijn, Tatiana I Axenovich, and Yurii S Aulchenko

Subjects
Medicine, Science
Abstract

Genome-wide association studies (GWAS) comprise a powerful tool for mapping genes of complex traits. However, an inflation of the test statistic can occur because of population substructure or cryptic relatedness, which could cause spurious associations. If information on a large number of genetic markers is available, adjusting the analysis results by using the method of genomic control (GC) is possible. GC was originally proposed to correct the Cochran-Armitage additive trend test. For non-additive models, correction has been shown to depend on allele frequencies. Therefore, usage of GC is limited to situations where allele frequencies of null markers and candidate markers are matched. In this work, we extended the capabilities of the GC method for non-additive models, which allows us to use null markers with arbitrary allele frequencies for GC. Analytical expressions for the inflation of a test statistic describing its dependency on allele frequency and several population parameters were obtained for recessive, dominant, and over-dominant models of inheritance. We proposed a method to estimate these required population parameters. Furthermore, we suggested a GC method based on approximation of the correction coefficient by a polynomial of allele frequency and described procedures to correct the genotypic (two degrees of freedom) test for cases when the model of inheritance is unknown. Statistical properties of the described methods were investigated using simulated and real data. We demonstrated that all considered methods were effective in controlling type 1 error in the presence of genetic substructure. The proposed GC methods can be applied to statistical tests for GWAS with various models of inheritance. All methods developed and tested in this work were implemented using R language as a part of the GenABEL package.

Published
2013
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4. Causal and synthetic associations of variants in the SERPINA gene cluster with alpha1-antitrypsin serum levels.

Author

Gian Andri Thun, Medea Imboden, Ilaria Ferrarotti, Ashish Kumar, Ma'en Obeidat, Michele Zorzetto, Margot Haun, Ivan Curjuric, Alexessander Couto Alves, Victoria E Jackson, Eva Albrecht, Janina S Ried, Alexander Teumer, Lorna M Lopez, Jennifer E Huffman, Stefan Enroth, Yohan Bossé, Ke Hao, Wim Timens, Ulf Gyllensten, Ozren Polasek, James F Wilson, Igor Rudan, Caroline Hayward, Andrew J Sandford, Ian J Deary, Beate Koch, Eva Reischl, Holger Schulz, Jennie Hui, Alan L James, Thierry Rochat, Erich W Russi, Marjo-Riitta Jarvelin, David P Strachan, Ian P Hall, Martin D Tobin, Morten Dahl, Sune Fallgaard Nielsen, Børge G Nordestgaard, Florian Kronenberg, Maurizio Luisetti, and Nicole M Probst-Hensch

Subjects
Genetics, QH426-470
Abstract

Several infrequent genetic polymorphisms in the SERPINA1 gene are known to substantially reduce concentration of alpha1-antitrypsin (AAT) in the blood. Since low AAT serum levels fail to protect pulmonary tissue from enzymatic degradation, these polymorphisms also increase the risk for early onset chronic obstructive pulmonary disease (COPD). The role of more common SERPINA1 single nucleotide polymorphisms (SNPs) in respiratory health remains poorly understood. We present here an agnostic investigation of genetic determinants of circulating AAT levels in a general population sample by performing a genome-wide association study (GWAS) in 1392 individuals of the SAPALDIA cohort. Five common SNPs, defined by showing minor allele frequencies (MAFs) >5%, reached genome-wide significance, all located in the SERPINA gene cluster at 14q32.13. The top-ranking genotyped SNP rs4905179 was associated with an estimated effect of β = -0.068 g/L per minor allele (P = 1.20*10(-12)). But denser SERPINA1 locus genotyping in 5569 participants with subsequent stepwise conditional analysis, as well as exon-sequencing in a subsample (N = 410), suggested that AAT serum level is causally determined at this locus by rare (MAF

Published
2013
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5. A genome-wide screen for interactions reveals a new locus on 4p15 modifying the effect of waist-to-hip ratio on total cholesterol.

Author

Ida Surakka, Aaron Isaacs, Lennart C Karssen, Pirkka-Pekka P Laurila, Rita P S Middelberg, Emmi Tikkanen, Janina S Ried, Claudia Lamina, Massimo Mangino, Wilmar Igl, Jouke-Jan Hottenga, Vasiliki Lagou, Pim van der Harst, Irene Mateo Leach, Tõnu Esko, Zoltán Kutalik, Nicholas W Wainwright, Maksim V Struchalin, Antti-Pekka Sarin, Antti J Kangas, Jorma S Viikari, Markus Perola, Taina Rantanen, Ann-Kristin Petersen, Pasi Soininen, Asa Johansson, Nicole Soranzo, Andrew C Heath, Theodore Papamarkou, Inga Prokopenko, Anke Tönjes, Florian Kronenberg, Angela Döring, Fernando Rivadeneira, Grant W Montgomery, John B Whitfield, Mika Kähönen, Terho Lehtimäki, Nelson B Freimer, Gonneke Willemsen, Eco J C de Geus, Aarno Palotie, Manj S Sandhu, Dawn M Waterworth, Andres Metspalu, Michael Stumvoll, André G Uitterlinden, Antti Jula, Gerjan Navis, Cisca Wijmenga, Bruce H R Wolffenbuttel, Marja-Riitta Taskinen, Mika Ala-Korpela, Jaakko Kaprio, Kirsten O Kyvik, Dorret I Boomsma, Nancy L Pedersen, Ulf Gyllensten, James F Wilson, Igor Rudan, Harry Campbell, Peter P Pramstaller, Tim D Spector, Jacqueline C M Witteman, Johan G Eriksson, Veikko Salomaa, Ben A Oostra, Olli T Raitakari, H-Erich Wichmann, Christian Gieger, Marjo-Riitta Järvelin, Nicholas G Martin, Albert Hofman, Mark I McCarthy, Leena Peltonen, Cornelia M van Duijn, Yurii S Aulchenko, Samuli Ripatti, and ENGAGE Consortium

Subjects
Genetics, QH426-470
Abstract

Recent genome-wide association (GWA) studies described 95 loci controlling serum lipid levels. These common variants explain ∼25% of the heritability of the phenotypes. To date, no unbiased screen for gene-environment interactions for circulating lipids has been reported. We screened for variants that modify the relationship between known epidemiological risk factors and circulating lipid levels in a meta-analysis of genome-wide association (GWA) data from 18 population-based cohorts with European ancestry (maximum N = 32,225). We collected 8 further cohorts (N = 17,102) for replication, and rs6448771 on 4p15 demonstrated genome-wide significant interaction with waist-to-hip-ratio (WHR) on total cholesterol (TC) with a combined P-value of 4.79×10(-9). There were two potential candidate genes in the region, PCDH7 and CCKAR, with differential expression levels for rs6448771 genotypes in adipose tissue. The effect of WHR on TC was strongest for individuals carrying two copies of G allele, for whom a one standard deviation (sd) difference in WHR corresponds to 0.19 sd difference in TC concentration, while for A allele homozygous the difference was 0.12 sd. Our findings may open up possibilities for targeted intervention strategies for people characterized by specific genomic profiles. However, more refined measures of both body-fat distribution and metabolic measures are needed to understand how their joint dynamics are modified by the newly found locus.

Published
2011
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6. Discovery of sexual dimorphisms in metabolic and genetic biomarkers.

Author

Kirstin Mittelstrass, Janina S Ried, Zhonghao Yu, Jan Krumsiek, Christian Gieger, Cornelia Prehn, Werner Roemisch-Margl, Alexey Polonikov, Annette Peters, Fabian J Theis, Thomas Meitinger, Florian Kronenberg, Stephan Weidinger, Heinz Erich Wichmann, Karsten Suhre, Rui Wang-Sattler, Jerzy Adamski, and Thomas Illig

Subjects
Genetics, QH426-470
Abstract

Metabolomic profiling and the integration of whole-genome genetic association data has proven to be a powerful tool to comprehensively explore gene regulatory networks and to investigate the effects of genetic variation at the molecular level. Serum metabolite concentrations allow a direct readout of biological processes, and association of specific metabolomic signatures with complex diseases such as Alzheimer's disease and cardiovascular and metabolic disorders has been shown. There are well-known correlations between sex and the incidence, prevalence, age of onset, symptoms, and severity of a disease, as well as the reaction to drugs. However, most of the studies published so far did not consider the role of sexual dimorphism and did not analyse their data stratified by gender. This study investigated sex-specific differences of serum metabolite concentrations and their underlying genetic determination. For discovery and replication we used more than 3,300 independent individuals from KORA F3 and F4 with metabolite measurements of 131 metabolites, including amino acids, phosphatidylcholines, sphingomyelins, acylcarnitines, and C6-sugars. A linear regression approach revealed significant concentration differences between males and females for 102 out of 131 metabolites (p-values

Published
2011
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7. Genome-wide association study identifies two novel regions at 11p15.5-p13 and 1p31 with major impact on acute-phase serum amyloid A.

Author

Carola Marzi, Eva Albrecht, Pirro G Hysi, Vasiliki Lagou, Melanie Waldenberger, Anke Tönjes, Inga Prokopenko, Katharina Heim, Hannah Blackburn, Janina S Ried, Marcus E Kleber, Massimo Mangino, Barbara Thorand, Annette Peters, Christopher J Hammond, Harald Grallert, Bernhard O Boehm, Peter Kovacs, Ludwig Geistlinger, Holger Prokisch, Bernhard R Winkelmann, Tim D Spector, H-Erich Wichmann, Michael Stumvoll, Nicole Soranzo, Winfried März, Wolfgang Koenig, Thomas Illig, and Christian Gieger

Subjects
Genetics, QH426-470
Abstract

Elevated levels of acute-phase serum amyloid A (A-SAA) cause amyloidosis and are a risk factor for atherosclerosis and its clinical complications, type 2 diabetes, as well as various malignancies. To investigate the genetic basis of A-SAA levels, we conducted the first genome-wide association study on baseline A-SAA concentrations in three population-based studies (KORA, TwinsUK, Sorbs) and one prospective case cohort study (LURIC), including a total of 4,212 participants of European descent, and identified two novel genetic susceptibility regions at 11p15.5-p13 and 1p31. The region at 11p15.5-p13 (rs4150642; p = 3.20×10(-111)) contains serum amyloid A1 (SAA1) and the adjacent general transcription factor 2 H1 (GTF2H1), Hermansky-Pudlak Syndrome 5 (HPS5), lactate dehydrogenase A (LDHA), and lactate dehydrogenase C (LDHC). This region explains 10.84% of the total variation of A-SAA levels in our data, which makes up 18.37% of the total estimated heritability. The second region encloses the leptin receptor (LEPR) gene at 1p31 (rs12753193; p = 1.22×10(-11)) and has been found to be associated with CRP and fibrinogen in previous studies. Our findings demonstrate a key role of the 11p15.5-p13 region in the regulation of baseline A-SAA levels and provide confirmative evidence of the importance of the 1p31 region for inflammatory processes and the close interplay between A-SAA, leptin, and other acute-phase proteins.

Published
2010
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8. Genome-wide association studies of serum magnesium, potassium, and sodium concentrations identify six Loci influencing serum magnesium levels.

Author

Tamra E Meyer, Germaine C Verwoert, Shih-Jen Hwang, Nicole L Glazer, Albert V Smith, Frank J A van Rooij, Georg B Ehret, Eric Boerwinkle, Janine F Felix, Tennille S Leak, Tamara B Harris, Qiong Yang, Abbas Dehghan, Thor Aspelund, Ronit Katz, Georg Homuth, Thomas Kocher, Rainer Rettig, Janina S Ried, Christian Gieger, Hanna Prucha, Arne Pfeufer, Thomas Meitinger, Josef Coresh, Albert Hofman, Mark J Sarnak, Yii-Der Ida Chen, André G Uitterlinden, Aravinda Chakravarti, Bruce M Psaty, Cornelia M van Duijn, W H Linda Kao, Jacqueline C M Witteman, Vilmundur Gudnason, David S Siscovick, Caroline S Fox, Anna Köttgen, Genetic Factors for Osteoporosis Consortium, and Meta Analysis of Glucose and Insulin Related Traits Consortium

Subjects
Genetics, QH426-470
Abstract

Magnesium, potassium, and sodium, cations commonly measured in serum, are involved in many physiological processes including energy metabolism, nerve and muscle function, signal transduction, and fluid and blood pressure regulation. To evaluate the contribution of common genetic variation to normal physiologic variation in serum concentrations of these cations, we conducted genome-wide association studies of serum magnesium, potassium, and sodium concentrations using approximately 2.5 million genotyped and imputed common single nucleotide polymorphisms (SNPs) in 15,366 participants of European descent from the international CHARGE Consortium. Study-specific results were combined using fixed-effects inverse-variance weighted meta-analysis. SNPs demonstrating genome-wide significant (p

Published
2010
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9. Establishment of a high-content imaging assay for tau aggregation in hiPSC-derived neurons differentiated from two protocols to routinely evaluate compounds and genetic perturbations

Author

Lamiaa Bahnassawy, Nathalie Nicolaisen, Christopher Untucht, Benjamin Mielich-Süss, Lydia Reinhardt, Janina S. Ried, Martina P. Morawe, Daniela Geist, Anja Finck, Elke Käfer, Jürgen Korffmann, Matthew Townsend, Brinda Ravikumar, Viktor Lakics, Miroslav Cik, and Peter Reinhardt

Subjects
Neurodegenerative diseases, In vitro screening, Human pluripotent stem cells, High content screening, Small molecule screening, Gene knockdown screening, Medicine (General), R5-920, Biotechnology, TP248.13-248.65
Abstract

Aberrant protein aggregation is a pathological cellular hallmark of many neurodegenerative diseases, such as Alzheimer's disease (AD) and frontotemporal dementia (FTD), where the tau protein is aggregating, forming neurofibrillary tangles (NFTs), and propagating from neuron to neuron. These processes have been linked to disease progression and a decline in cognitive function. Various therapeutic approaches aim at the prevention or reduction of tau aggregates in neurons. Human induced pluripotent stem cells (hiPSCs) are a very valuable tool in neuroscience discovery, as they offer access to potentially unlimited amounts of cell types that are affected in disease, including cortical neurons, for in vitro studies. We have generated an in vitro model for tau aggregation that uses hiPSC – derived neurons expressing an aggregation prone, fluorescently tagged version of the human tau protein after lentiviral transduction. Upon addition of tau seeds in the form of recombinant sonicated paired helical filaments (sPHFs), the neurons show robust, disease-like aggregation of the tau protein. The model was developed as a plate-based high content screening assay coupled with an image analysis algorithm to evaluate the impact of small molecules or genetic perturbations on tau. We show that the assay can be used to evaluate small molecules or screen targeted compound libraries. Using siRNA-based gene knockdown, genes of interest can be evaluated, and we could show that a targeted gene library can be screened, by screening nearly 100 deubiquitinating enzymes (DUBs) in that assay. The assay uses an imaging-based readout, a relatively short timeline, quantifies the extent of tau aggregation, and also allows the assessment of cell viability. Furthermore, it can be easily adapted to different hiPSC lines or neuronal subtypes. Taken together, this complex and highly relevant approach can be routinely applied on a weekly basis in the screening funnels of several projects and generates data with a turnaround time of approximately five weeks.

Published
2024
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10. SETD7-mediated monomethylation is enriched on soluble Tau in Alzheimer’s disease

Author

Maria Bichmann, Nuria Prat Oriol, Ebru Ercan-Herbst, David C. Schöndorf, Borja Gomez Ramos, Vera Schwärzler, Marie Neu, Annabelle Schlüter, Xue Wang, Liang Jin, Chenqi Hu, Yu Tian, Janina S. Ried, Per Haberkant, Laura Gasparini, and Dagmar E. Ehrnhoefer

Subjects
Lysine methylation, Protein methyl transferase, Nuclear tau, Posttranslational modification, Neurology. Diseases of the nervous system, RC346-429, Geriatrics, RC952-954.6
Abstract

Abstract Background Human tauopathies including Alzheimer’s disease (AD) are characterized by alterations in the post-translational modification (PTM) pattern of Tau, which parallel the formation of insoluble Tau aggregates, neuronal dysfunction and degeneration. While PTMs on aggregated Tau have been studied in detail, much less is known about the modification patterns of soluble Tau. Furthermore, PTMs other than phosphorylation have only come into focus recently and are still understudied. Soluble Tau species are likely responsible for the spreading of pathology during disease progression and are currently being investigated as targets for immunotherapies. A better understanding of their biochemical properties is thus of high importance. Methods We used a mass spectrometry approach to characterize Tau PTMs on a detergent-soluble fraction of human AD and control brain tissue, which led to the discovery of novel lysine methylation events. We developed specific antibodies against Tau methylated at these sites and biochemically characterized methylated Tau species in extracts from human brain, the rTg4510 mouse model and in hiPSC-derived neurons. Results Our study demonstrates that methylated Tau levels increase with Tau pathology stage in human AD samples as well as in a mouse model of Tauopathy. Methylated Tau is enriched in soluble brain extracts and is not associated with hyperphosphorylated, high molecular weight Tau species. We also show that in hiPSC-derived neurons and mouse brain, methylated Tau preferentially localizes to the cell soma and nuclear fractions and is absent from neurites. Knock down and inhibitor studies supported by proteomics data led to the identification of SETD7 as a novel lysine methyltransferase for Tau. SETD7 specifically methylates Tau at K132, an event that facilitates subsequent methylation at K130. Conclusions Our findings indicate that methylated Tau has a specific somatic and nuclear localization, suggesting that the methylation of soluble Tau species may provide a signal for their translocation to different subcellular compartments. Since the mislocalization and depletion of Tau from axons is associated with tauopathies, our findings may shed light onto this disease-associated phenomenon.

Published
2021
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11. A genome-wide association meta-analysis on lipoprotein (a) concentrations adjusted for apolipoprotein (a) isoforms[S]

Author

Salome Mack, Stefan Coassin, Rico Rueedi, Noha A. Yousri, Ilkka Seppälä, Christian Gieger, Sebastian Schönherr, Lukas Forer, Gertraud Erhart, Pedro Marques-Vidal, Janina S. Ried, Gerard Waeber, Sven Bergmann, Doreen Dähnhardt, Andrea Stöckl, Olli T. Raitakari, Mika Kähönen, Annette Peters, Thomas Meitinger, Konstantin Strauch, Ludmilla Kedenko, Bernhard Paulweber, Terho Lehtimäki, Steven C. Hunt, Peter Vollenweider, Claudia Lamina, and Florian Kronenberg

Subjects
genetics, epidemiology, coronary artery disease, Biochemistry, QD415-436
Abstract

High lipoprotein (a) [Lp(a)] concentrations are an independent risk factor for cardiovascular outcomes. Concentrations are strongly influenced by apo(a) kringle IV repeat isoforms. We aimed to identify genetic loci associated with Lp(a) concentrations using data from five genome-wide association studies (n = 13,781). We identified 48 independent SNPs in the LPA and 1 SNP in the APOE gene region to be significantly associated with Lp(a) concentrations. We also adjusted for apo(a) isoforms to identify loci affecting Lp(a) levels independently from them, which resulted in 31 SNPs (30 in the LPA, 1 in the APOE gene region). Seven SNPs showed a genome-wide significant association with coronary artery disease (CAD) risk. A rare SNP (rs186696265; MAF ∼1%) showed the highest effect on Lp(a) and was also associated with increased risk of CAD (odds ratio = 1.73, P = 3.35 × 10−30). Median Lp(a) values increased from 2.1 to 91.1 mg/dl with increasing number of Lp(a)-increasing alleles. We found the APOE2-determining allele of rs7412 to be significantly associated with Lp(a) concentrations (P = 3.47 × 10−10). Each APOE2 allele decreased Lp(a) by 3.34 mg/dl corresponding to ∼15% of the populationʼns mean values. Performing a gene-based test of association, including suspected Lp(a) receptors and regulators, resulted in one significant association of the TLR2 gene with Lp(a) (P = 3.4 × 10−4). In summary, we identified a large number of independent SNPs in the LPA gene region, as well as the APOE2 allele, to be significantly associated with Lp(a) concentrations.

Published
2017
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12. Reproducibility of Molecular Phenotypes after Long-Term Differentiation to Human iPSC-Derived Neurons: A Multi-Site Omics Study

Author

Viola Volpato, James Smith, Cynthia Sandor, Janina S. Ried, Anna Baud, Adam Handel, Sarah E. Newey, Frank Wessely, Moustafa Attar, Emma Whiteley, Satyan Chintawar, An Verheyen, Thomas Barta, Majlinda Lako, Lyle Armstrong, Caroline Muschet, Anna Artati, Carlo Cusulin, Klaus Christensen, Christoph Patsch, Eshita Sharma, Jerome Nicod, Philip Brownjohn, Victoria Stubbs, Wendy E. Heywood, Paul Gissen, Roberta De Filippis, Katharina Janssen, Peter Reinhardt, Jerzy Adamski, Ines Royaux, Pieter J. Peeters, Georg C. Terstappen, Martin Graf, Frederick J. Livesey, Colin J. Akerman, Kevin Mills, Rory Bowden, George Nicholson, Caleb Webber, M. Zameel Cader, and Viktor Lakics

Subjects
Medicine (General), R5-920, Biology (General), QH301-705.5
Abstract

Summary: Reproducibility in molecular and cellular studies is fundamental to scientific discovery. To establish the reproducibility of a well-defined long-term neuronal differentiation protocol, we repeated the cellular and molecular comparison of the same two iPSC lines across five distinct laboratories. Despite uncovering acceptable variability within individual laboratories, we detect poor cross-site reproducibility of the differential gene expression signature between these two lines. Factor analysis identifies the laboratory as the largest source of variation along with several variation-inflating confounders such as passaging effects and progenitor storage. Single-cell transcriptomics shows substantial cellular heterogeneity underlying inter-laboratory variability and being responsible for biases in differential gene expression inference. Factor analysis-based normalization of the combined dataset can remove the nuisance technical effects, enabling the execution of robust hypothesis-generating studies. Our study shows that multi-center collaborations can expose systematic biases and identify critical factors to be standardized when publishing novel protocols, contributing to increased cross-site reproducibility. : In this article, Lakics and colleagues show that, while individual laboratories are able to identify consistent molecular and seemingly statistically robust differences between iPSC neuronal models, cross-site reproducibility is poor. Their findings support multi-center collaborations to expose systematic biases and identify critical factors to be standardized to improve reproducibility in iPSC-based molecular experiments. Keywords: induced pluripotent stem cell, reproducibility, cross-site experimental variation, cortical neurons, gene expression profile, proteomic profiles, single-cell sequencing, molecular profiling, stembancc, public-private partnership

Published
2018
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13. Erratum: Large meta-analysis of genome-wide association studies identifies five loci for lean body mass

Author

M. Carola Zillikens, Serkalem Demissie, Yi-Hsiang Hsu, Laura M. Yerges-Armstrong, Wen-Chi Chou, Lisette Stolk, Gregory Livshits, Linda Broer, Toby Johnson, Daniel L. Koller, Zoltán Kutalik, Jian’an Luan, Ida Malkin, Janina S. Ried, Albert V. Smith, Gudmar Thorleifsson, Liesbeth Vandenput, Jing Hua Zhao, Weihua Zhang, Ali Aghdassi, Kristina Åkesson, Najaf Amin, Leslie J. Baier, Inês Barroso, David A. Bennett, Lars Bertram, Rainer Biffar, Murielle Bochud, Michael Boehnke, Ingrid B. Borecki, Aron S. Buchman, Liisa Byberg, Harry Campbell, Natalia Campos Obanda, Jane A. Cauley, Peggy M. Cawthon, Henna Cederberg, Zhao Chen, Nam H. Cho, Hyung Jin Choi, Melina Claussnitzer, Francis Collins, Steven R. Cummings, Philip L. De Jager, Ilja Demuth, Rosalie A. M. Dhonukshe-Rutten, Luda Diatchenko, Gudny Eiriksdottir, Anke W. Enneman, Mike Erdos, Johan G. Eriksson, Joel Eriksson, Karol Estrada, Daniel S. Evans, Mary F. Feitosa, Mao Fu, Melissa Garcia, Christian Gieger, Thomas Girke, Nicole L. Glazer, Harald Grallert, Jagvir Grewal, Bok-Ghee Han, Robert L. Hanson, Caroline Hayward, Albert Hofman, Eric P. Hoffman, Georg Homuth, Wen-Chi Hsueh, Monica J. Hubal, Alan Hubbard, Kim M. Huffman, Lise B. Husted, Thomas Illig, Erik Ingelsson, Till Ittermann, John-Olov Jansson, Joanne M. Jordan, Antti Jula, Magnus Karlsson, Kay-Tee Khaw, Tuomas O. Kilpeläinen, Norman Klopp, Jacqueline S. L. Kloth, Heikki A. Koistinen, William E. Kraus, Stephen Kritchevsky, Teemu Kuulasmaa, Johanna Kuusisto, Markku Laakso, Jari Lahti, Thomas Lang, Bente L. Langdahl, Lenore J. Launer, Jong-Young Lee, Markus M. Lerch, Joshua R. Lewis, Lars Lind, Cecilia Lindgren, Yongmei Liu, Tian Liu, Youfang Liu, Östen Ljunggren, Mattias Lorentzon, Robert N. Luben, William Maixner, Fiona E. McGuigan, Carolina Medina-Gomez, Thomas Meitinger, Håkan Melhus, Dan Mellström, Simon Melov, Karl Michaëlsson, Braxton D. Mitchell, Andrew P. Morris, Leif Mosekilde, Anne Newman, Carrie M. Nielson, Jeffrey R. O’Connell, Ben A. Oostra, Eric S. Orwoll, Aarno Palotie, Stephen C. J. Parker, Munro Peacock, Markus Perola, Annette Peters, Ozren Polasek, Richard L. Prince, Katri Räikkönen, Stuart H. Ralston, Samuli Ripatti, John A. Robbins, Jerome I. Rotter, Igor Rudan, Veikko Salomaa, Suzanne Satterfield, Eric E. Schadt, Sabine Schipf, Laura Scott, Joban Sehmi, Jian Shen, Chan Soo Shin, Gunnar Sigurdsson, Shad Smith, Nicole Soranzo, Alena Stančáková, Elisabeth Steinhagen-Thiessen, Elizabeth A. Streeten, Unnur Styrkarsdottir, Karin M. A. Swart, Sian-Tsung Tan, Mark A. Tarnopolsky, Patricia Thompson, Cynthia A. Thomson, Unnur Thorsteinsdottir, Emmi Tikkanen, Gregory J. Tranah, Jaakko Tuomilehto, Natasja M. van Schoor, Arjun Verma, Peter Vollenweider, Henry Völzke, Jean Wactawski-Wende, Mark Walker, Michael N. Weedon, Ryan Welch, H.-Erich Wichmann, Elisabeth Widen, Frances M. K. Williams, James F. Wilson, Nicole C. Wright, Weijia Xie, Lei Yu, Yanhua Zhou, John C. Chambers, Angela Döring, Cornelia M. van Duijn, Michael J. Econs, Vilmundur Gudnason, Jaspal S. Kooner, Bruce M. Psaty, Timothy D. Spector, Kari Stefansson, Fernando Rivadeneira, André G. Uitterlinden, Nicholas J. Wareham, Vicky Ossowski, Dawn Waterworth, Ruth J. F. Loos, David Karasik, Tamara B. Harris, Claes Ohlsson, and Douglas P. Kiel

Subjects
Science
Abstract

A correction to this article has been published and is linked from the HTML version of this article.

Published
2017
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14. Large meta-analysis of genome-wide association studies identifies five loci for lean body mass

Author

M. Carola Zillikens, Serkalem Demissie, Yi-Hsiang Hsu, Laura M. Yerges-Armstrong, Wen-Chi Chou, Lisette Stolk, Gregory Livshits, Linda Broer, Toby Johnson, Daniel L. Koller, Zoltán Kutalik, Jian’an Luan, Ida Malkin, Janina S. Ried, Albert V. Smith, Gudmar Thorleifsson, Liesbeth Vandenput, Jing Hua Zhao, Weihua Zhang, Ali Aghdassi, Kristina Åkesson, Najaf Amin, Leslie J. Baier, Inês Barroso, David A. Bennett, Lars Bertram, Rainer Biffar, Murielle Bochud, Michael Boehnke, Ingrid B. Borecki, Aron S. Buchman, Liisa Byberg, Harry Campbell, Natalia Campos Obanda, Jane A. Cauley, Peggy M. Cawthon, Henna Cederberg, Zhao Chen, Nam H. Cho, Hyung Jin Choi, Melina Claussnitzer, Francis Collins, Steven R. Cummings, Philip L. De Jager, Ilja Demuth, Rosalie A. M. Dhonukshe-Rutten, Luda Diatchenko, Gudny Eiriksdottir, Anke W. Enneman, Mike Erdos, Johan G. Eriksson, Joel Eriksson, Karol Estrada, Daniel S. Evans, Mary F. Feitosa, Mao Fu, Melissa Garcia, Christian Gieger, Thomas Girke, Nicole L. Glazer, Harald Grallert, Jagvir Grewal, Bok-Ghee Han, Robert L. Hanson, Caroline Hayward, Albert Hofman, Eric P. Hoffman, Georg Homuth, Wen-Chi Hsueh, Monica J. Hubal, Alan Hubbard, Kim M. Huffman, Lise B. Husted, Thomas Illig, Erik Ingelsson, Till Ittermann, John-Olov Jansson, Joanne M. Jordan, Antti Jula, Magnus Karlsson, Kay-Tee Khaw, Tuomas O. Kilpeläinen, Norman Klopp, Jacqueline S. L. Kloth, Heikki A. Koistinen, William E. Kraus, Stephen Kritchevsky, Teemu Kuulasmaa, Johanna Kuusisto, Markku Laakso, Jari Lahti, Thomas Lang, Bente L. Langdahl, Lenore J. Launer, Jong-Young Lee, Markus M. Lerch, Joshua R. Lewis, Lars Lind, Cecilia Lindgren, Yongmei Liu, Tian Liu, Youfang Liu, Östen Ljunggren, Mattias Lorentzon, Robert N. Luben, William Maixner, Fiona E. McGuigan, Carolina Medina-Gomez, Thomas Meitinger, Håkan Melhus, Dan Mellström, Simon Melov, Karl Michaëlsson, Braxton D. Mitchell, Andrew P. Morris, Leif Mosekilde, Anne Newman, Carrie M. Nielson, Jeffrey R. O’Connell, Ben A. Oostra, Eric S. Orwoll, Aarno Palotie, Stephen C. J. Parker, Munro Peacock, Markus Perola, Annette Peters, Ozren Polasek, Richard L. Prince, Katri Räikkönen, Stuart H. Ralston, Samuli Ripatti, John A. Robbins, Jerome I. Rotter, Igor Rudan, Veikko Salomaa, Suzanne Satterfield, Eric E. Schadt, Sabine Schipf, Laura Scott, Joban Sehmi, Jian Shen, Chan Soo Shin, Gunnar Sigurdsson, Shad Smith, Nicole Soranzo, Alena Stančáková, Elisabeth Steinhagen-Thiessen, Elizabeth A. Streeten, Unnur Styrkarsdottir, Karin M. A. Swart, Sian-Tsung Tan, Mark A. Tarnopolsky, Patricia Thompson, Cynthia A. Thomson, Unnur Thorsteinsdottir, Emmi Tikkanen, Gregory J. Tranah, Jaakko Tuomilehto, Natasja M. van Schoor, Arjun Verma, Peter Vollenweider, Henry Völzke, Jean Wactawski-Wende, Mark Walker, Michael N. Weedon, Ryan Welch, H.-Erich Wichmann, Elisabeth Widen, Frances M. K. Williams, James F. Wilson, Nicole C. Wright, Weijia Xie, Lei Yu, Yanhua Zhou, John C. Chambers, Angela Döring, Cornelia M. van Duijn, Michael J. Econs, Vilmundur Gudnason, Jaspal S. Kooner, Bruce M. Psaty, Timothy D. Spector, Kari Stefansson, Fernando Rivadeneira, André G. Uitterlinden, Nicholas J. Wareham, Vicky Ossowski, Dawn Waterworth, Ruth J. F. Loos, David Karasik, Tamara B. Harris, Claes Ohlsson, and Douglas P. Kiel

Subjects
Science
Abstract

Lean body mass is a highly heritable trait and is associated with various health conditions. Here, Kiel and colleagues perform a meta-analysis of genome-wide association studies for whole body lean body mass and find five novel genetic loci to be significantly associated.

Published
2017
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15. A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape

Author

Janina S. Ried, Janina Jeff M., Audrey Y. Chu, Jennifer L. Bragg-Gresham, Jenny van Dongen, Jennifer E. Huffman, Tarunveer S. Ahluwalia, Gemma Cadby, Niina Eklund, Joel Eriksson, Tõnu Esko, Mary F. Feitosa, Anuj Goel, Mathias Gorski, Caroline Hayward, Nancy L. Heard-Costa, Anne U. Jackson, Eero Jokinen, Stavroula Kanoni, Kati Kristiansson, Zoltán Kutalik, Jari Lahti, Jian'an Luan, Reedik Mägi, Anubha Mahajan, Massimo Mangino, Carolina Medina-Gomez, Keri L. Monda, Ilja M. Nolte, Louis Pérusse, Inga Prokopenko, Lu Qi, Lynda M. Rose, Erika Salvi, Megan T. Smith, Harold Snieder, Alena Stančáková, Yun Ju Sung, Ioanna Tachmazidou, Alexander Teumer, Gudmar Thorleifsson, Pim van der Harst, Ryan W. Walker, Sophie R. Wang, Sarah H. Wild, Sara M. Willems, Andrew Wong, Weihua Zhang, Eva Albrecht, Alexessander Couto Alves, Stephan J. L. Bakker, Cristina Barlassina, Traci M. Bartz, John Beilby, Claire Bellis, Richard N. Bergman, Sven Bergmann, John Blangero, Matthias Blüher, Eric Boerwinkle, Lori L. Bonnycastle, Stefan R. Bornstein, Marcel Bruinenberg, Harry Campbell, Yii-Der Ida Chen, Charleston W. K. Chiang, Peter S. Chines, Francis S Collins, Fracensco Cucca, L Adrienne Cupples, Francesca D’Avila, Eco J .C. de Geus, George Dedoussis, Maria Dimitriou, Angela Döring, Johan G. Eriksson, Aliki-Eleni Farmaki, Martin Farrall, Teresa Ferreira, Krista Fischer, Nita G. Forouhi, Nele Friedrich, Anette Prior Gjesing, Nicola Glorioso, Mariaelisa Graff, Harald Grallert, Niels Grarup, Jürgen Gräßler, Jagvir Grewal, Anders Hamsten, Marie Neergaard Harder, Catharina A. Hartman, Maija Hassinen, Nicholas Hastie, Andrew Tym Hattersley, Aki S. Havulinna, Markku Heliövaara, Hans Hillege, Albert Hofman, Oddgeir Holmen, Georg Homuth, Jouke-Jan Hottenga, Jennie Hui, Lise Lotte Husemoen, Pirro G. Hysi, Aaron Isaacs, Till Ittermann, Shapour Jalilzadeh, Alan L. James, Torben Jørgensen, Pekka Jousilahti, Antti Jula, Johanne Marie Justesen, Anne E. Justice, Mika Kähönen, Maria Karaleftheri, Kay Tee Khaw, Sirkka M. Keinanen-Kiukaanniemi, Leena Kinnunen, Paul B. Knekt, Heikki A. Koistinen, Ivana Kolcic, Ishminder K. Kooner, Seppo Koskinen, Peter Kovacs, Theodosios Kyriakou, Tomi Laitinen, Claudia Langenberg, Alexandra M. Lewin, Peter Lichtner, Cecilia M. Lindgren, Jaana Lindström, Allan Linneberg, Roberto Lorbeer, Mattias Lorentzon, Robert Luben, Valeriya Lyssenko, Satu Männistö, Paolo Manunta, Irene Mateo Leach, Wendy L. McArdle, Barbara Mcknight, Karen L. Mohlke, Evelin Mihailov, Lili Milani, Rebecca Mills, May E. Montasser, Andrew P. Morris, Gabriele Müller, Arthur W. Musk, Narisu Narisu, Ken K. Ong, Ben A. Oostra, Clive Osmond, Aarno Palotie, James S. Pankow, Lavinia Paternoster, Brenda W. Penninx, Irene Pichler, Maria G. Pilia, Ozren Polašek, Peter P. Pramstaller, Olli T Raitakari, Tuomo Rankinen, D. C. Rao, Nigel W. Rayner, Rasmus Ribel-Madsen, Treva K. Rice, Marcus Richards, Paul M. Ridker, Fernando Rivadeneira, Kathy A. Ryan, Serena Sanna, Mark A. Sarzynski, Salome Scholtens, Robert A. Scott, Sylvain Sebert, Lorraine Southam, Thomas Hempel Sparsø, Valgerdur Steinthorsdottir, Kathleen Stirrups, Ronald P. Stolk, Konstantin Strauch, Heather M. Stringham, Morris A. Swertz, Amy J. Swift, Anke Tönjes, Emmanouil Tsafantakis, Peter J. van der Most, Jana V. Van Vliet-Ostaptchouk, Liesbeth Vandenput, Erkki Vartiainen, Cristina Venturini, Niek Verweij, Jorma S. Viikari, Veronique Vitart, Marie-Claude Vohl, Judith M. Vonk, Gérard Waeber, Elisabeth Widén, Gonneke Willemsen, Tom Wilsgaard, Thomas W. Winkler, Alan F. Wright, Laura M. Yerges-Armstrong, Jing Hua Zhao, M. Carola Zillikens, Dorret I. Boomsma, Claude Bouchard, John C. Chambers, Daniel I. Chasman, Daniele Cusi, Ron T. Gansevoort, Christian Gieger, Torben Hansen, Andrew A. Hicks, Frank Hu, Kristian Hveem, Marjo-Riitta Jarvelin, Eero Kajantie, Jaspal S. Kooner, Diana Kuh, Johanna Kuusisto, Markku Laakso, Timo A. Lakka, Terho Lehtimäki, Andres Metspalu, Inger Njølstad, Claes Ohlsson, Albertine J. Oldehinkel, Lyle J. Palmer, Oluf Pedersen, Markus Perola, Annette Peters, Bruce M. Psaty, Hannu Puolijoki, Rainer Rauramaa, Igor Rudan, Veikko Salomaa, Peter E. H. Schwarz, Alan R. Shudiner, Jan H. Smit, Thorkild I. A. Sørensen, Timothy D. Spector, Kari Stefansson, Michael Stumvoll, Angelo Tremblay, Jaakko Tuomilehto, André G. Uitterlinden, Matti Uusitupa, Uwe Völker, Peter Vollenweider, Nicholas J. Wareham, Hugh Watkins, James F. Wilson, Eleftheria Zeggini, Goncalo R. Abecasis, Michael Boehnke, Ingrid B. Borecki, Panos Deloukas, Cornelia M. van Duijn, Caroline Fox, Leif C. Groop, Iris M. Heid, David J. Hunter, Robert C. Kaplan, Mark I. McCarthy, Kari E. North, Jeffrey R. O'Connell, David Schlessinger, Unnur Thorsteinsdottir, David P. Strachan, Timothy Frayling, Joel N. Hirschhorn, Martina Müller-Nurasyid, and Ruth J. F. Loos

Subjects
Science
Abstract

Past genome-wide associate studies have identified hundreds of genetic loci that influence body size and shape when examined one trait at a time. Here, Jeff and colleagues develop an aggregate score of various body traits, and use meta-analysis to find new loci linked to body shape.

Published
2016
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16. Meta-analysis of gene–environment-wide association scans accounting for education level identifies additional loci for refractive error

Author

Qiao Fan, Virginie J. M. Verhoeven, Robert Wojciechowski, Veluchamy A. Barathi, Pirro G. Hysi, Jeremy A. Guggenheim, René Höhn, Veronique Vitart, Anthony P. Khawaja, Kenji Yamashiro, S Mohsen Hosseini, Terho Lehtimäki, Yi Lu, Toomas Haller, Jing Xie, Cécile Delcourt, Mario Pirastu, Juho Wedenoja, Puya Gharahkhani, Cristina Venturini, Masahiro Miyake, Alex W. Hewitt, Xiaobo Guo, Johanna Mazur, Jenifer E. Huffman, Katie M. Williams, Ozren Polasek, Harry Campbell, Igor Rudan, Zoran Vatavuk, James F. Wilson, Peter K. Joshi, George McMahon, Beate St Pourcain, David M. Evans, Claire L. Simpson, Tae-Hwi Schwantes-An, Robert P. Igo, Alireza Mirshahi, Audrey Cougnard-Gregoire, Céline Bellenguez, Maria Blettner, Olli Raitakari, Mika Kähönen, Ilkka Seppälä, Tanja Zeller, Thomas Meitinger, Janina S. Ried, Christian Gieger, Laura Portas, Elisabeth M. van Leeuwen, Najaf Amin, André G. Uitterlinden, Fernando Rivadeneira, Albert Hofman, Johannes R. Vingerling, Ya Xing Wang, Xu Wang, Eileen Tai-Hui Boh, M. Kamran Ikram, Charumathi Sabanayagam, Preeti Gupta, Vincent Tan, Lei Zhou, Candice E. H. Ho, Wan’e Lim, Roger W. Beuerman, Rosalynn Siantar, E-Shyong Tai, Eranga Vithana, Evelin Mihailov, Chiea-Chuen Khor, Caroline Hayward, Robert N. Luben, Paul J. Foster, Barbara E. K. Klein, Ronald Klein, Hoi-Suen Wong, Paul Mitchell, Andres Metspalu, Tin Aung, Terri L. Young, Mingguang He, Olavi Pärssinen, Cornelia M. van Duijn, Jie Jin Wang, Cathy Williams, Jost B. Jonas, Yik-Ying Teo, David A. Mackey, Konrad Oexle, Nagahisa Yoshimura, Andrew D. Paterson, Norbert Pfeiffer, Tien-Yin Wong, Paul N. Baird, Dwight Stambolian, Joan E. Bailey Wilson, Ching-Yu Cheng, Christopher J. Hammond, Caroline C. W. Klaver, Seang-Mei Saw, and Consortium for Refractive Error and Myopia (CREAM)

Subjects
Science
Abstract

This report by the Consortium for Refractive Error and Myopia uses gene-environment-wide interaction study (GEWIS) to identify genetic loci that affect environmental influence in myopia development, and identifies ethnic specific genetic loci that attribute to eye refractive errors.

Published
2016
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17. New loci for body fat percentage reveal link between adiposity and cardiometabolic disease risk

Author

Yingchang Lu, Felix R. Day, Stefan Gustafsson, Martin L. Buchkovich, Jianbo Na, Veronique Bataille, Diana L. Cousminer, Zari Dastani, Alexander W. Drong, Tõnu Esko, David M. Evans, Mario Falchi, Mary F. Feitosa, Teresa Ferreira, Åsa K. Hedman, Robin Haring, Pirro G. Hysi, Mark M. Iles, Anne E. Justice, Stavroula Kanoni, Vasiliki Lagou, Rui Li, Xin Li, Adam Locke, Chen Lu, Reedik Mägi, John R. B. Perry, Tune H. Pers, Qibin Qi, Marianna Sanna, Ellen M. Schmidt, William R. Scott, Dmitry Shungin, Alexander Teumer, Anna A. E. Vinkhuyzen, Ryan W. Walker, Harm-Jan Westra, Mingfeng Zhang, Weihua Zhang, Jing Hua Zhao, Zhihong Zhu, Uzma Afzal, Tarunveer Singh Ahluwalia, Stephan J. L. Bakker, Claire Bellis, Amélie Bonnefond, Katja Borodulin, Aron S. Buchman, Tommy Cederholm, Audrey C. Choh, Hyung Jin Choi, Joanne E. Curran, Lisette C. P. G. M. de Groot, Philip L. De Jager, Rosalie A. M. Dhonukshe-Rutten, Anke W. Enneman, Elodie Eury, Daniel S. Evans, Tom Forsen, Nele Friedrich, Frédéric Fumeron, Melissa E. Garcia, Simone Gärtner, Bok-Ghee Han, Aki S. Havulinna, Caroline Hayward, Dena Hernandez, Hans Hillege, Till Ittermann, Jack W. Kent, Ivana Kolcic, Tiina Laatikainen, Jari Lahti, Irene Mateo Leach, Christine G. Lee, Jong-Young Lee, Tian Liu, Youfang Liu, Stéphane Lobbens, Marie Loh, Leo-Pekka Lyytikäinen, Carolina Medina-Gomez, Karl Michaëlsson, Mike A. Nalls, Carrie M. Nielson, Laticia Oozageer, Laura Pascoe, Lavinia Paternoster, Ozren Polašek, Samuli Ripatti, Mark A. Sarzynski, Chan Soo Shin, Nina Smolej Narančić, Dominik Spira, Priya Srikanth, Elisabeth Steinhagen-Thiessen, Yun Ju Sung, Karin M. A. Swart, Leena Taittonen, Toshiko Tanaka, Emmi Tikkanen, Nathalie van der Velde, Natasja M. van Schoor, Niek Verweij, Alan F. Wright, Lei Yu, Joseph M. Zmuda, Niina Eklund, Terrence Forrester, Niels Grarup, Anne U. Jackson, Kati Kristiansson, Teemu Kuulasmaa, Johanna Kuusisto, Peter Lichtner, Jian'an Luan, Anubha Mahajan, Satu Männistö, Cameron D. Palmer, Janina S. Ried, Robert A. Scott, Alena Stancáková, Peter J. Wagner, Ayse Demirkan, Angela Döring, Vilmundur Gudnason, Douglas P. Kiel, Brigitte Kühnel, Massimo Mangino, Barbara Mcknight, Cristina Menni, Jeffrey R. O'Connell, Ben A. Oostra, Alan R. Shuldiner, Kijoung Song, Liesbeth Vandenput, Cornelia M. van Duijn, Peter Vollenweider, Charles C. White, Michael Boehnke, Yvonne Boettcher, Richard S. Cooper, Nita G. Forouhi, Christian Gieger, Harald Grallert, Aroon Hingorani, Torben Jørgensen, Pekka Jousilahti, Mika Kivimaki, Meena Kumari, Markku Laakso, Claudia Langenberg, Allan Linneberg, Amy Luke, Colin A. Mckenzie, Aarno Palotie, Oluf Pedersen, Annette Peters, Konstantin Strauch, Bamidele O. Tayo, Nicholas J. Wareham, David A. Bennett, Lars Bertram, John Blangero, Matthias Blüher, Claude Bouchard, Harry Campbell, Nam H. Cho, Steven R. Cummings, Stefan A. Czerwinski, Ilja Demuth, Rahel Eckardt, Johan G. Eriksson, Luigi Ferrucci, Oscar H. Franco, Philippe Froguel, Ron T. Gansevoort, Torben Hansen, Tamara B. Harris, Nicholas Hastie, Markku Heliövaara, Albert Hofman, Joanne M. Jordan, Antti Jula, Mika Kähönen, Eero Kajantie, Paul B. Knekt, Seppo Koskinen, Peter Kovacs, Terho Lehtimäki, Lars Lind, Yongmei Liu, Eric S. Orwoll, Clive Osmond, Markus Perola, Louis Pérusse, Olli T. Raitakari, Tuomo Rankinen, D. C. Rao, Treva K. Rice, Fernando Rivadeneira, Igor Rudan, Veikko Salomaa, Thorkild I. A. Sørensen, Michael Stumvoll, Anke Tönjes, Bradford Towne, Gregory J. Tranah, Angelo Tremblay, André G. Uitterlinden, Pim van der Harst, Erkki Vartiainen, Jorma S. Viikari, Veronique Vitart, Marie-Claude Vohl, Henry Völzke, Mark Walker, Henri Wallaschofski, Sarah Wild, James F. Wilson, Loïc Yengo, D. Timothy Bishop, Ingrid B. Borecki, John C. Chambers, L. Adrienne Cupples, Abbas Dehghan, Panos Deloukas, Ghazaleh Fatemifar, Caroline Fox, Terrence S. Furey, Lude Franke, Jiali Han, David J. Hunter, Juha Karjalainen, Fredrik Karpe, Robert C. Kaplan, Jaspal S. Kooner, Mark I. McCarthy, Joanne M. Murabito, Andrew P. Morris, Julia A. N. Bishop, Kari E. North, Claes Ohlsson, Ken K. Ong, Inga Prokopenko, J. Brent Richards, Eric E. Schadt, Tim D. Spector, Elisabeth Widén, Cristen J. Willer, Jian Yang, Erik Ingelsson, Karen L. Mohlke, Joel N. Hirschhorn, John Andrew Pospisilik, M. Carola Zillikens, Cecilia Lindgren, Tuomas Oskari Kilpeläinen, and Ruth J. F. Loos

Subjects
Science
Abstract

A genome-wide association meta-analysis study here shows novel genetic loci to be associated to body fat percentage, and describes cross-phenotype association that further demonstrate a close relationship between adiposity and cardiovascular disease risk.

Published
2016
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