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1.  Characterization of reference genes for RT-qPCR in the desert moss Syntrichia caninervis in response to abiotic stress and desiccation/rehydration 
Syntrichia caninervis is the dominant bryophyte of the biological soil crusts found in the Gurbantunggut desert. The extreme desert environment is characterized by prolonged drought, temperature extremes, high radiation and frequent cycles of hydration and dehydration. S. caninervis is an ideal organism for the identification and characterization of genes related to abiotic stress tolerance. Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) expression analysis is a powerful analytical technique that requires the use of stable reference genes. Using available S. caninervis transcriptome data, we selected 15 candidate reference genes and analyzed their relative expression stabilities in S. caninervis gametophores exposed to a range of abiotic stresses or a hydration-desiccation-rehydration cycle. The programs geNorm, NormFinder, and RefFinder were used to assess and rank the expression stability of the 15 candidate genes. The stability ranking results of reference genes under each specific experimental condition showed high consistency using different algorithms. For abiotic stress treatments, the combination of two genes (α-TUB2 and CDPK) were sufficient for accurate normalization. For the hydration-desiccation-rehydration process, the combination of two genes (α-TUB1 and CDPK) were sufficient for accurate normalization. 18S was among the least stable genes in all of the experimental sets and was unsuitable as reference gene in S. caninervis. This is the first systematic investigation and comparison of reference gene selection for RT-qPCR work in S. caninervis. This research will facilitate gene expression studies in S. caninervis, related moss species from the Syntrichia complex and other mosses.
doi:10.3389/fpls.2015.00038
PMCID: PMC4318276
Syntrichia caninervis; quantitative real-time PCR; reference gene; geNorm; NormFinder; RefFinder
2.  Initial Testing (Stage 1) of the Antibody-Maytansinoid Conjugate, IMGN901 (Lorvotuzumab Mertansine), by the Pediatric Preclinical Testing Program 
Pediatric blood & cancer  2013;60(11):1860-1867.
Background
IMGN901 (lorvotuzumab mertansine) is an antibody-drug conjugate composed of a humanized antibody that specifically binds to CD56 (NCAM, neural cell adhesion molecule) and that is conjugated to the maytansinoid, DM1 (a microtubule targeting agent).
Procedures
IMGN901 and DM1-SMe (unconjugated DM1 as a mixed disulfide with thiomethane to cap its sulfhydryl group) were tested in vitro at concentrations ranging from 0.01 nM to 0.1 μM and 0.3 pM to 3 nM, respectively. IMGN901 was tested against a subset of PPTP solid tumor xenografts focusing on those with high CD56 expression.The combination of IMGN901 with topotecan was also evaluated.
Results
Neuroblastoma models expressed CD56 at or above the median expression level for all PPTP xenografts and cell lines. Neuroblastoma cell lines demonstrated relatively low sensitivity to DM1-SMe compared to other cell lines, but the sensitivity of neuroblastoma cell lines to IMGN901 was comparable to that of non-neuroblastoma cell lines. In vivo, objective responses were observed in 9 of 24 (38%) models including, 3 of 7 neuroblastoma xenografts, and 2 of 7 rhabdomyosarcoma xenografts. All xenografts with objective responses showed homogeneous high-level staining by IHC for CD56, but not all xenografts with homogenous high-level staining had objective responses. Combined with topotecan, IMGN901 demonstrated therapeutic enhancement against 2 of 4 neuroblastoma models.
Conclusions
IMGN901 has anti-tumor activity against some CD56 expressing pediatric cancer models. High expression of CD56 is a biomarker for in vivo response, but resistance mechanisms to IMGN901 in some high CD56 expressing lines need to be defined.
doi:10.1002/pbc.24647
PMCID: PMC4260400  PMID: 23798344
Preclinical Testing; Developmental Therapeutics; antibody-maytansinoid conjugate; microtubules
3.  Dual CDK4/CDK6 Inhibition Induces Cell Cycle Arrest and Senescence in Neuroblastoma 
Purpose
Neuroblastoma is a pediatric cancer that continues to exact significant morbidity and mortality. Recently, a number of cell cycle proteins, particularly those within the Cyclin D/CDK4/CDK6/RB network, have been shown to exert oncogenic roles in neuroblastoma, suggesting that their therapeutic exploitation might improve patient outcomes.
Experimental Procedures
We evaluated the effect of dual CDK4/CDK6 inhibition on neuroblastoma viability using LEE011, a highly specific CDK4/6 inhibitor.
Results
Treatment with LEE011 significantly reduced proliferation in 12 of 17 human neuroblastoma-derived cell lines by inducing cytostasis at nanomolar concentrations (mean IC50 = 307 ± 68 nM in sensitive lines). LEE011 caused cell cycle arrest and cellular senescence that was attributed to dose-dependent decreases in phosphorylated RB and FOXM1, respectively. In addition, responsiveness of neuroblastoma xenografts to LEE011 translated to the in vivo setting in that there was a direct correlation of in vitro IC50 values with degree of subcutaneous xenograft growth delay. While our data indicate that neuroblastomas sensitive to LEE011 were more likely to contain genomic amplification of MYCN (p = 0.01), the identification of additional clinically accessible biomarkers is of high importance.
Conclusions
Taken together, our data show that LEE011 is active in a large subset of neuroblastoma cell line and xenograft models, and supports the clinical development of this CDK4/6 inhibitor as a therapy for patients with this disease.
doi:10.1158/1078-0432.CCR-13-1675
PMCID: PMC3844928  PMID: 24045179
Neuroblastoma; CDK4; CDK6; LEE011; MYCN
4.  Quality control and conduct of genome-wide association meta-analyses 
Nature protocols  2014;9(5):1192-1212.
Rigorous organization and quality control (QC) are necessary to facilitate successful genome-wide association meta-analyses (GWAMAs) of statistics aggregated across multiple genome-wide association studies. This protocol provides guidelines for [1] organizational aspects of GWAMAs, and for [2] QC at the study file level, the meta-level across studies, and the meta-analysis output level. Real–world examples highlight issues experienced and solutions developed by the GIANT Consortium that has conducted meta-analyses including data from 125 studies comprising more than 330,000 individuals. We provide a general protocol for conducting GWAMAs and carrying out QC to minimize errors and to guarantee maximum use of the data. We also include details for use of a powerful and flexible software package called EasyQC. For consortia of comparable size to the GIANT consortium, the present protocol takes a minimum of about 10 months to complete.
doi:10.1038/nprot.2014.071
PMCID: PMC4083217  PMID: 24762786
5.  Quality control and conduct of genome-wide association meta-analyses 
Nature protocols  2014;9(5):1192-1212.
Rigorous organization and quality control (QC) are necessary to facilitate successful genome-wide association meta-analyses (GWAMAs) of statistics aggregated across multiple genome-wide association studies. This protocol provides guidelines for [1] organizational aspects of GWAMAs, and for [2] QC at the study file level, the meta-level across studies, and the meta-analysis output level. Real–world examples highlight issues experienced and solutions developed by the GIANT Consortium that has conducted meta-analyses including data from 125 studies comprising more than 330,000 individuals. We provide a general protocol for conducting GWAMAs and carrying out QC to minimize errors and to guarantee maximum use of the data. We also include details for use of a powerful and flexible software package called EasyQC. For consortia of comparable size to the GIANT consortium, the present protocol takes a minimum of about 10 months to complete.
doi:10.1038/nprot.2014.071
PMCID: PMC4083217  PMID: 24762786
6.  De novo assembly and characterization of the transcriptome in the desiccation-tolerant moss Syntrichia caninervis 
BMC Research Notes  2014;7:490.
Background
Syntrichia caninervis is a desiccation-tolerant moss and the dominant bryophyte of the Biological Soil Crusts (BSCs) found in the Mojave and Gurbantunggut deserts. Next generation high throughput sequencing technologies offer an efficient and economic choice for characterizing non-model organism transcriptomes with little or no prior molecular information available.
Results
In this study, we employed next generation, high-throughput, Illumina RNA-Seq to analyze the poly-(A) + mRNA from hydrated, dehydrating and desiccated S. caninervis gametophores. Approximately 58.0 million paired-end short reads were obtained and 92,240 unigenes were assembled with an average size of 493 bp, N50 value of 662 bp and a total size of 45.48 Mbp. Sequence similarity searches against five public databases (NR, Swiss-Prot, COSMOSS, KEGG and COG) found 54,125 unigenes (58.7%) with significant similarity to an existing sequence (E-value ≤ 1e-5) and could be annotated. Gene Ontology (GO) annotation assigned 24,183 unigenes to the three GO terms: Biological Process, Cellular Component or Molecular Function. GO comparison between P. patens and S. caninervis demonstrated similar sequence enrichment across all three GO categories. 29,370 deduced polypeptide sequences were assigned Pfam domain information and categorized into 4,212 Pfam domains/families. Using the PlantTFDB, 778 unigenes were predicted to be involved in the regulation of transcription and were classified into 49 transcription factor families. Annotated unigenes were mapped to the KEGG pathways and further annotated using MapMan. Comparative genomics revealed that 44% of protein families are shared in common by S. caninervis, P. patens and Arabidopsis thaliana and that 80% are shared by both moss species.
Conclusions
This study is one of the first comprehensive transcriptome analyses of the moss S. caninervis. Our data extends our knowledge of bryophyte transcriptomes, provides an insight to plants adapted to the arid regions of central Asia, and continues the development of S. caninervis as a model for understanding the molecular aspects of desiccation-tolerance.
doi:10.1186/1756-0500-7-490
PMCID: PMC4124477  PMID: 25086984
Biological soil crust; Desiccation; Physcomitrella; Stress; Syntrichia; Transcriptome
7.  Data for Genetic Analysis Workshop 18: human whole genome sequence, blood pressure, and simulated phenotypes in extended pedigrees 
BMC Proceedings  2014;8(Suppl 1):S2.
Genetic Analysis Workshop 18 (GAW18) focused on identification of genes and functional variants that influence complex phenotypes in human sequence data. Data for the workshop were donated by the T2D-GENES Consortium and included whole genome sequences for odd-numbered autosomes in 464 key individuals selected from 20 Mexican American families, a dense set of single-nucleotide polymorphisms in 959 individuals in these families, and longitudinal data on systolic and diastolic blood pressure measured at 1-4 examinations over a period of 20 years. Simulated phenotypes were generated based on the real sequence data and pedigree structures. In the design of the simulation model, gene expression measures from the San Antonio Family Heart Study (not distributed as part of the GAW18 data) were used to identify genes whose mRNA levels were correlated with blood pressure. Observed variants within these genes were designated as functional in the GAW18 simulation if they were nonsynonymous and predicted to have deleterious effects on protein function or if they were noncoding and associated with mRNA levels. Two simulated longitudinal phenotypes were modeled to have the same trait distributions as the real systolic and diastolic blood pressure data, with effects of age, sex, and medication use, including a genotype-medication interaction. For each phenotype, more than 1000 sequence variants in more than 200 genes present on the odd-numbered autosomes individually explained less than 0.01-2.78% of phenotypic variance. Cumulatively, variants in the most influential gene explained 7.79% of trait variance. An additional simulated phenotype, Q1, was designed to be correlated among family members but to not be associated with any sequence variants. Two hundred replicates of the phenotypes were simulated, with each including data for 849 individuals.
doi:10.1186/1753-6561-8-S1-S2
PMCID: PMC4145406  PMID: 25519314
8.  Genetic Variants Associated With Glycine Metabolism and Their Role in Insulin Sensitivity and Type 2 Diabetes 
Diabetes  2013;62(6):2141-2150.
Circulating metabolites associated with insulin sensitivity may represent useful biomarkers, but their causal role in insulin sensitivity and diabetes is less certain. We previously identified novel metabolites correlated with insulin sensitivity measured by the hyperinsulinemic-euglycemic clamp. The top-ranking metabolites were in the glutathione and glycine biosynthesis pathways. We aimed to identify common genetic variants associated with metabolites in these pathways and test their role in insulin sensitivity and type 2 diabetes. With 1,004 nondiabetic individuals from the RISC study, we performed a genome-wide association study (GWAS) of 14 insulin sensitivity–related metabolites and one metabolite ratio. We replicated our results in the Botnia study (n = 342). We assessed the association of these variants with diabetes-related traits in GWAS meta-analyses (GENESIS [including RISC, EUGENE2, and Stanford], MAGIC, and DIAGRAM). We identified four associations with three metabolites—glycine (rs715 at CPS1), serine (rs478093 at PHGDH), and betaine (rs499368 at SLC6A12; rs17823642 at BHMT)—and one association signal with glycine-to-serine ratio (rs1107366 at ALDH1L1). There was no robust evidence for association between these variants and insulin resistance or diabetes. Genetic variants associated with genes in the glycine biosynthesis pathways do not provide consistent evidence for a role of glycine in diabetes-related traits.
doi:10.2337/db12-0876
PMCID: PMC3661655  PMID: 23378610
9.  Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture 
Berndt, Sonja I. | Gustafsson, Stefan | Mägi, Reedik | Ganna, Andrea | Wheeler, Eleanor | Feitosa, Mary F. | Justice, Anne E. | Monda, Keri L. | Croteau-Chonka, Damien C. | Day, Felix R. | Esko, Tõnu | Fall, Tove | Ferreira, Teresa | Gentilini, Davide | Jackson, Anne U. | Luan, Jian’an | Randall, Joshua C. | Vedantam, Sailaja | Willer, Cristen J. | Winkler, Thomas W. | Wood, Andrew R. | Workalemahu, Tsegaselassie | Hu, Yi-Juan | Lee, Sang Hong | Liang, Liming | Lin, Dan-Yu | Min, Josine L. | Neale, Benjamin M. | Thorleifsson, Gudmar | Yang, Jian | Albrecht, Eva | Amin, Najaf | Bragg-Gresham, Jennifer L. | Cadby, Gemma | den Heijer, Martin | Eklund, Niina | Fischer, Krista | Goel, Anuj | Hottenga, Jouke-Jan | Huffman, Jennifer E. | Jarick, Ivonne | Johansson, Åsa | Johnson, Toby | Kanoni, Stavroula | Kleber, Marcus E. | König, Inke R. | Kristiansson, Kati | Kutalik, Zoltán | Lamina, Claudia | Lecoeur, Cecile | Li, Guo | Mangino, Massimo | McArdle, Wendy L. | Medina-Gomez, Carolina | Müller-Nurasyid, Martina | Ngwa, Julius S. | Nolte, Ilja M. | Paternoster, Lavinia | Pechlivanis, Sonali | Perola, Markus | Peters, Marjolein J. | Preuss, Michael | Rose, Lynda M. | Shi, Jianxin | Shungin, Dmitry | Smith, Albert Vernon | Strawbridge, Rona J. | Surakka, Ida | Teumer, Alexander | Trip, Mieke D. | Tyrer, Jonathan | Van Vliet-Ostaptchouk, Jana V. | Vandenput, Liesbeth | Waite, Lindsay L. | Zhao, Jing Hua | Absher, Devin | Asselbergs, Folkert W. | Atalay, Mustafa | Attwood, Antony P. | Balmforth, Anthony J. | Basart, Hanneke | Beilby, John | Bonnycastle, Lori L. | Brambilla, Paolo | Bruinenberg, Marcel | Campbell, Harry | Chasman, Daniel I. | Chines, Peter S. | Collins, Francis S. | Connell, John M. | Cookson, William | de Faire, Ulf | de Vegt, Femmie | Dei, Mariano | Dimitriou, Maria | Edkins, Sarah | Estrada, Karol | Evans, David M. | Farrall, Martin | Ferrario, Marco M. | Ferrières, Jean | Franke, Lude | Frau, Francesca | Gejman, Pablo V. | Grallert, Harald | Grönberg, Henrik | Gudnason, Vilmundur | Hall, Alistair S. | Hall, Per | Hartikainen, Anna-Liisa | Hayward, Caroline | Heard-Costa, Nancy L. | Heath, Andrew C. | Hebebrand, Johannes | Homuth, Georg | Hu, Frank B. | Hunt, Sarah E. | Hyppönen, Elina | Iribarren, Carlos | Jacobs, Kevin B. | Jansson, John-Olov | Jula, Antti | Kähönen, Mika | Kathiresan, Sekar | Kee, Frank | Khaw, Kay-Tee | Kivimaki, Mika | Koenig, Wolfgang | Kraja, Aldi T. | Kumari, Meena | Kuulasmaa, Kari | Kuusisto, Johanna | Laitinen, Jaana H. | Lakka, Timo A. | Langenberg, Claudia | Launer, Lenore J. | Lind, Lars | Lindström, Jaana | Liu, Jianjun | Liuzzi, Antonio | Lokki, Marja-Liisa | Lorentzon, Mattias | Madden, Pamela A. | Magnusson, Patrik K. | Manunta, Paolo | Marek, Diana | März, Winfried | Mateo Leach, Irene | McKnight, Barbara | Medland, Sarah E. | Mihailov, Evelin | Milani, Lili | Montgomery, Grant W. | Mooser, Vincent | Mühleisen, Thomas W. | Munroe, Patricia B. | Musk, Arthur W. | Narisu, Narisu | Navis, Gerjan | Nicholson, George | Nohr, Ellen A. | Ong, Ken K. | Oostra, Ben A. | Palmer, Colin N.A. | Palotie, Aarno | Peden, John F. | Pedersen, Nancy | Peters, Annette | Polasek, Ozren | Pouta, Anneli | Pramstaller, Peter P. | Prokopenko, Inga | Pütter, Carolin | Radhakrishnan, Aparna | Raitakari, Olli | Rendon, Augusto | Rivadeneira, Fernando | Rudan, Igor | Saaristo, Timo E. | Sambrook, Jennifer G. | Sanders, Alan R. | Sanna, Serena | Saramies, Jouko | Schipf, Sabine | Schreiber, Stefan | Schunkert, Heribert | Shin, So-Youn | Signorini, Stefano | Sinisalo, Juha | Skrobek, Boris | Soranzo, Nicole | Stančáková, Alena | Stark, Klaus | Stephens, Jonathan C. | Stirrups, Kathleen | Stolk, Ronald P. | Stumvoll, Michael | Swift, Amy J. | Theodoraki, Eirini V. | Thorand, Barbara | Tregouet, David-Alexandre | Tremoli, Elena | Van der Klauw, Melanie M. | van Meurs, Joyce B.J. | Vermeulen, Sita H. | Viikari, Jorma | Virtamo, Jarmo | Vitart, Veronique | Waeber, Gérard | Wang, Zhaoming | Widén, Elisabeth | Wild, Sarah H. | Willemsen, Gonneke | Winkelmann, Bernhard R. | Witteman, Jacqueline C.M. | Wolffenbuttel, Bruce H.R. | Wong, Andrew | Wright, Alan F. | Zillikens, M. Carola | Amouyel, Philippe | Boehm, Bernhard O. | Boerwinkle, Eric | Boomsma, Dorret I. | Caulfield, Mark J. | Chanock, Stephen J. | Cupples, L. Adrienne | Cusi, Daniele | Dedoussis, George V. | Erdmann, Jeanette | Eriksson, Johan G. | Franks, Paul W. | Froguel, Philippe | Gieger, Christian | Gyllensten, Ulf | Hamsten, Anders | Harris, Tamara B. | Hengstenberg, Christian | Hicks, Andrew A. | Hingorani, Aroon | Hinney, Anke | Hofman, Albert | Hovingh, Kees G. | Hveem, Kristian | Illig, Thomas | Jarvelin, Marjo-Riitta | Jöckel, Karl-Heinz | Keinanen-Kiukaanniemi, Sirkka M. | Kiemeney, Lambertus A. | Kuh, Diana | Laakso, Markku | Lehtimäki, Terho | Levinson, Douglas F. | Martin, Nicholas G. | Metspalu, Andres | Morris, Andrew D. | Nieminen, Markku S. | Njølstad, Inger | Ohlsson, Claes | Oldehinkel, Albertine J. | Ouwehand, Willem H. | Palmer, Lyle J. | Penninx, Brenda | Power, Chris | Province, Michael A. | Psaty, Bruce M. | Qi, Lu | Rauramaa, Rainer | Ridker, Paul M. | Ripatti, Samuli | Salomaa, Veikko | Samani, Nilesh J. | Snieder, Harold | Sørensen, Thorkild I.A. | Spector, Timothy D. | Stefansson, Kari | Tönjes, Anke | Tuomilehto, Jaakko | Uitterlinden, André G. | Uusitupa, Matti | van der Harst, Pim | Vollenweider, Peter | Wallaschofski, Henri | Wareham, Nicholas J. | Watkins, Hugh | Wichmann, H.-Erich | Wilson, James F. | Abecasis, Goncalo R. | Assimes, Themistocles L. | Barroso, Inês | Boehnke, Michael | Borecki, Ingrid B. | Deloukas, Panos | Fox, Caroline S. | Frayling, Timothy | Groop, Leif C. | Haritunian, Talin | Heid, Iris M. | Hunter, David | Kaplan, Robert C. | Karpe, Fredrik | Moffatt, Miriam | Mohlke, Karen L. | O’Connell, Jeffrey R. | Pawitan, Yudi | Schadt, Eric E. | Schlessinger, David | Steinthorsdottir, Valgerdur | Strachan, David P. | Thorsteinsdottir, Unnur | van Duijn, Cornelia M. | Visscher, Peter M. | Di Blasio, Anna Maria | Hirschhorn, Joel N. | Lindgren, Cecilia M. | Morris, Andrew P. | Meyre, David | Scherag, André | McCarthy, Mark I. | Speliotes, Elizabeth K. | North, Kari E. | Loos, Ruth J.F. | Ingelsson, Erik
Nature genetics  2013;45(5):501-512.
Approaches exploiting extremes of the trait distribution may reveal novel loci for common traits, but it is unknown whether such loci are generalizable to the general population. In a genome-wide search for loci associated with upper vs. lower 5th percentiles of body mass index, height and waist-hip ratio, as well as clinical classes of obesity including up to 263,407 European individuals, we identified four new loci (IGFBP4, H6PD, RSRC1, PPP2R2A) influencing height detected in the tails and seven new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3, ZZZ3) for clinical classes of obesity. Further, we show that there is large overlap in terms of genetic structure and distribution of variants between traits based on extremes and the general population and little etiologic heterogeneity between obesity subgroups.
doi:10.1038/ng.2606
PMCID: PMC3973018  PMID: 23563607
10.  EsDREB2B, a novel truncated DREB2-type transcription factor in the desert legume Eremosparton songoricum, enhances tolerance to multiple abiotic stresses in yeast and transgenic tobacco 
BMC Plant Biology  2014;14:44.
Background
Dehydration-Responsive Element-Binding Protein2 (DREB2) is a transcriptional factor which regulates the expression of several stress-inducible genes. DREB2-type proteins are particularly important in plant responses to drought, salt and heat. DREB2 genes have been identified and characterized in a variety of plants, and DREB2 genes are promising candidate genes for the improvement of stress tolerance in plants. However, little is known about these genes in plants adapted to water-limiting environments.
Results
In this study, we describe the characterization of EsDREB2B, a novel DREB2B gene identified from the desert plant Eremosparton songoricum. Phylogenetic analysis and motif prediction indicate that EsDREB2B encodes a truncated DREB2 polypeptide that belongs to a legume-specific DREB2 group. In E. songoricum, EsDREB2B transcript accumulation was induced by a variety of abiotic stresses, including drought, salinity, cold, heat, heavy metal, mechanical wounding, oxidative stress and exogenous abscisic acid (ABA) treatment. Consistent with the predicted role as a transcription factor, EsDREB2B was targeted to the nucleus of onion epidermal cells and exhibited transactivation activity of a GAL4-containing reporter gene in yeast. In transgenic yeast, overexpression of EsDREB2B increased tolerance to multiple abiotic stresses. Our findings indicate that EsDREB2B can enhance stress tolerance in other plant species. Heterologous expression of EsDREB2B in tobacco showed improved tolerance to multiple abiotic stresses, and the transgenic plants exhibited no reduction in foliar growth. We observed that EsDREB2B is a functional DREB2-orthologue able to influence the physiological and biochemical response of transgenic tobacco to stress.
Conclusions
Based upon these findings, EsDREB2B encodes an abiotic stress-inducible, transcription factor which confers abiotic stress-tolerance in yeast and transgenic tobacco.
doi:10.1186/1471-2229-14-44
PMCID: PMC3940028  PMID: 24506952
Cold; DREB; Drought; Heat; Proline; Salt; Stress; Transcript accumulation; Transgenic tobacco
11.  Aldehyde dehydrogenase (ALDH) superfamily in plants: gene nomenclature and comparative genomics 
Planta  2012;237(1):189-210.
In recent years, there has been a significant increase in the number of completely sequenced plant genomes. The comparison of fully sequenced genomes allows for identification of new gene family members, as well as comprehensive analysis of gene family evolution. The aldehyde dehydrogenase (ALDH) gene superfamily comprises a group of enzymes involved in the NAD+- or NADP+-dependent conversion of various aldehydes to their corresponding carboxylic acids. ALDH enzymes are involved in processing many aldehydes that serve as biogenic intermediates in a wide range of metabolic pathways. In addition, many of these enzymes function as ‘aldehyde scavengers’ by removing reactive aldehydes generated during the oxidative degradation of lipid membranes, also known as lipid peroxidation. Plants and animals share many ALDH families, and many genes are highly conserved between these two evolutionarily distinct groups. Conversely, both plants and animals also contain unique ALDH genes and families. Herein we carried outgenome-wide identification of ALDH genes in a number of plant species—including Arabidopsis thaliana (thale crest), Chlamydomonas reinhardtii (unicellular algae), Oryza sativa (rice), Physcomitrella patens (moss), Vitis vinifera (grapevine) and Zea mays (maize). These data were then combined with previous analysis of Populus trichocarpa (poplar tree), Selaginella moellindorffii (gemmiferous spikemoss), Sorghum bicolor (sorghum) and Volvox carteri (colonial algae) for a comprehensive evolutionary comparison of the plant ALDH superfamily. As a result, newly identified genes can be more easily analyzed and gene names can be assigned according to current nomenclature guidelines; our goal is to clarify previously confusing and conflicting names and classifications that might confound results and prevent accurate comparisons between studies.
doi:10.1007/s00425-012-1749-0
PMCID: PMC3536936  PMID: 23007552
ALDH; Aldehyde dehydrogenase; Stress response; Gene family; Nomenclature
12.  The splice site variant rs11078928 may be associated with a genotype-dependent alteration in expression of GSDMB transcripts 
BMC Genomics  2013;14:627.
Background
Many genetic variants have been associated with susceptibility to complex traits by genome wide association studies (GWAS), but for most, causal genes and mechanisms of action have yet to be elucidated. Using bioinformatics, we identified index and proxy variants associated with autoimmune disease susceptibility, with the potential to affect splicing of candidate genes. PCR and sequence analysis of whole blood RNA samples from population controls was then carried out for the 8 most promising variants to determine the effect of genetic variation on splicing of target genes.
Results
We identified 31 splice site SNPs with the potential to affect splicing, and prioritised 8 to determine the effect of genotype on candidate gene splicing. We identified that variants rs11078928 and rs2014886 were associated with altered splicing of the GSDMB and TSFM genes respectively. rs11078928, present in the asthma and autoimmune disease susceptibility locus on chromosome 17q12-21, was associated with the production of a novel Δ exon5-8 transcript of the GSDMB gene, and a separate decrease in the percentage of transcripts with inclusion of exon 6, whereas the multiple sclerosis susceptibility variant rs2014886, was associated with an alternative TFSM transcript encompassing a short cryptic exon within intron 2.
Conclusions
Our findings demonstrate the utility of a bioinformatic approach in identification and prioritisation of genetic variants effecting splicing of their host genes, and suggest that rs11078928 and rs2014886 may affect the splicing of the GSDMB and TSFM genes respectively.
doi:10.1186/1471-2164-14-627
PMCID: PMC3848490  PMID: 24044605
GSDMB; Rs11078928; Asthma; Autoimmune disease; GWAS; SNP; Alternative mRNA splicing
13.  The genetic landscape of high-risk neuroblastoma 
Nature genetics  2013;45(3):279-284.
Neuroblastoma is a malignancy of the developing sympathetic nervous system that often presents with widespread metastatic disease, resulting in survival rates of less than 50%1. To determine the spectrum of somatic mutation in high-risk neuroblastoma, we studied 240 cases using a combination of whole exome, genome and transcriptome sequencing as part of the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) initiative. Here we report a low median exonic mutation frequency of 0.60 per megabase (0.48 non-silent), and remarkably few recurrently mutated genes in these tumors. Genes with significant somatic mutation frequencies included ALK (9.2% of cases), PTPN11 (2.9%), ATRX (2.5%, an additional 7.1% had focal deletions), MYCN (1.7%, a recurrent p.Pro44Leu alteration), and NRAS (0.83%). Rare, potentially pathogenic germline variants were significantly enriched in ALK, CHEK2, PINK1, and BARD1. The relative paucity of recurrent somatic mutations in neuroblastoma challenges current therapeutic strategies reliant upon frequently altered oncogenic drivers.
doi:10.1038/ng.2529
PMCID: PMC3682833  PMID: 23334666
14.  A Benign Renal Cyst Containing Liesegang Rings Mimicking a Renal Cell Carcinoma: A Case Report 
Current Urology  2013;7(1):37-39.
Liesegang rings are uncommon pathological findings which may cause diagnostic dilemmas for pathologists. Awareness of their appearance is important to avoid over diagnosis of parasitic infection, algal contamination and psammoma bodies. Liesegang rings are benign, lamellar structures with radial striations and a central amorphous core. They are found in a variety of tissues and fluids in both an intra- and extra-cellular sites. We present here a case of a cystic renal lesion containing Liesegang rings mimicking a renal cell carcinoma.
doi:10.1159/000343551
PMCID: PMC3783286  PMID: 24917755
Liesegang rings; Kidney; Pseudotumor
15.  Sex-stratified Genome-wide Association Studies Including 270,000 Individuals Show Sexual Dimorphism in Genetic Loci for Anthropometric Traits 
Randall, Joshua C. | Winkler, Thomas W. | Kutalik, Zoltán | Berndt, Sonja I. | Jackson, Anne U. | Monda, Keri L. | Kilpeläinen, Tuomas O. | Esko, Tõnu | Mägi, Reedik | Li, Shengxu | Workalemahu, Tsegaselassie | Feitosa, Mary F. | Croteau-Chonka, Damien C. | Day, Felix R. | Fall, Tove | Ferreira, Teresa | Gustafsson, Stefan | Locke, Adam E. | Mathieson, Iain | Scherag, Andre | Vedantam, Sailaja | Wood, Andrew R. | Liang, Liming | Steinthorsdottir, Valgerdur | Thorleifsson, Gudmar | Dermitzakis, Emmanouil T. | Dimas, Antigone S. | Karpe, Fredrik | Min, Josine L. | Nicholson, George | Clegg, Deborah J. | Person, Thomas | Krohn, Jon P. | Bauer, Sabrina | Buechler, Christa | Eisinger, Kristina | Bonnefond, Amélie | Froguel, Philippe | Hottenga, Jouke-Jan | Prokopenko, Inga | Waite, Lindsay L. | Harris, Tamara B. | Smith, Albert Vernon | Shuldiner, Alan R. | McArdle, Wendy L. | Caulfield, Mark J. | Munroe, Patricia B. | Grönberg, Henrik | Chen, Yii-Der Ida | Li, Guo | Beckmann, Jacques S. | Johnson, Toby | Thorsteinsdottir, Unnur | Teder-Laving, Maris | Khaw, Kay-Tee | Wareham, Nicholas J. | Zhao, Jing Hua | Amin, Najaf | Oostra, Ben A. | Kraja, Aldi T. | Province, Michael A. | Cupples, L. Adrienne | Heard-Costa, Nancy L. | Kaprio, Jaakko | Ripatti, Samuli | Surakka, Ida | Collins, Francis S. | Saramies, Jouko | Tuomilehto, Jaakko | Jula, Antti | Salomaa, Veikko | Erdmann, Jeanette | Hengstenberg, Christian | Loley, Christina | Schunkert, Heribert | Lamina, Claudia | Wichmann, H. Erich | Albrecht, Eva | Gieger, Christian | Hicks, Andrew A. | Johansson, Åsa | Pramstaller, Peter P. | Kathiresan, Sekar | Speliotes, Elizabeth K. | Penninx, Brenda | Hartikainen, Anna-Liisa | Jarvelin, Marjo-Riitta | Gyllensten, Ulf | Boomsma, Dorret I. | Campbell, Harry | Wilson, James F. | Chanock, Stephen J. | Farrall, Martin | Goel, Anuj | Medina-Gomez, Carolina | Rivadeneira, Fernando | Estrada, Karol | Uitterlinden, André G. | Hofman, Albert | Zillikens, M. Carola | den Heijer, Martin | Kiemeney, Lambertus A. | Maschio, Andrea | Hall, Per | Tyrer, Jonathan | Teumer, Alexander | Völzke, Henry | Kovacs, Peter | Tönjes, Anke | Mangino, Massimo | Spector, Tim D. | Hayward, Caroline | Rudan, Igor | Hall, Alistair S. | Samani, Nilesh J. | Attwood, Antony Paul | Sambrook, Jennifer G. | Hung, Joseph | Palmer, Lyle J. | Lokki, Marja-Liisa | Sinisalo, Juha | Boucher, Gabrielle | Huikuri, Heikki | Lorentzon, Mattias | Ohlsson, Claes | Eklund, Niina | Eriksson, Johan G. | Barlassina, Cristina | Rivolta, Carlo | Nolte, Ilja M. | Snieder, Harold | Van der Klauw, Melanie M. | Van Vliet-Ostaptchouk, Jana V. | Gejman, Pablo V. | Shi, Jianxin | Jacobs, Kevin B. | Wang, Zhaoming | Bakker, Stephan J. L. | Mateo Leach, Irene | Navis, Gerjan | van der Harst, Pim | Martin, Nicholas G. | Medland, Sarah E. | Montgomery, Grant W. | Yang, Jian | Chasman, Daniel I. | Ridker, Paul M. | Rose, Lynda M. | Lehtimäki, Terho | Raitakari, Olli | Absher, Devin | Iribarren, Carlos | Basart, Hanneke | Hovingh, Kees G. | Hyppönen, Elina | Power, Chris | Anderson, Denise | Beilby, John P. | Hui, Jennie | Jolley, Jennifer | Sager, Hendrik | Bornstein, Stefan R. | Schwarz, Peter E. H. | Kristiansson, Kati | Perola, Markus | Lindström, Jaana | Swift, Amy J. | Uusitupa, Matti | Atalay, Mustafa | Lakka, Timo A. | Rauramaa, Rainer | Bolton, Jennifer L. | Fowkes, Gerry | Fraser, Ross M. | Price, Jackie F. | Fischer, Krista | KrjutÅ¡kov, Kaarel | Metspalu, Andres | Mihailov, Evelin | Langenberg, Claudia | Luan, Jian'an | Ong, Ken K. | Chines, Peter S. | Keinanen-Kiukaanniemi, Sirkka M. | Saaristo, Timo E. | Edkins, Sarah | Franks, Paul W. | Hallmans, Göran | Shungin, Dmitry | Morris, Andrew David | Palmer, Colin N. A. | Erbel, Raimund | Moebus, Susanne | Nöthen, Markus M. | Pechlivanis, Sonali | Hveem, Kristian | Narisu, Narisu | Hamsten, Anders | Humphries, Steve E. | Strawbridge, Rona J. | Tremoli, Elena | Grallert, Harald | Thorand, Barbara | Illig, Thomas | Koenig, Wolfgang | Müller-Nurasyid, Martina | Peters, Annette | Boehm, Bernhard O. | Kleber, Marcus E. | März, Winfried | Winkelmann, Bernhard R. | Kuusisto, Johanna | Laakso, Markku | Arveiler, Dominique | Cesana, Giancarlo | Kuulasmaa, Kari | Virtamo, Jarmo | Yarnell, John W. G. | Kuh, Diana | Wong, Andrew | Lind, Lars | de Faire, Ulf | Gigante, Bruna | Magnusson, Patrik K. E. | Pedersen, Nancy L. | Dedoussis, George | Dimitriou, Maria | Kolovou, Genovefa | Kanoni, Stavroula | Stirrups, Kathleen | Bonnycastle, Lori L. | Njølstad, Inger | Wilsgaard, Tom | Ganna, Andrea | Rehnberg, Emil | Hingorani, Aroon | Kivimaki, Mika | Kumari, Meena | Assimes, Themistocles L. | Barroso, Inês | Boehnke, Michael | Borecki, Ingrid B. | Deloukas, Panos | Fox, Caroline S. | Frayling, Timothy | Groop, Leif C. | Haritunians, Talin | Hunter, David | Ingelsson, Erik | Kaplan, Robert | Mohlke, Karen L. | O'Connell, Jeffrey R. | Schlessinger, David | Strachan, David P. | Stefansson, Kari | van Duijn, Cornelia M. | Abecasis, Gonçalo R. | McCarthy, Mark I. | Hirschhorn, Joel N. | Qi, Lu | Loos, Ruth J. F. | Lindgren, Cecilia M. | North, Kari E. | Heid, Iris M.
PLoS Genetics  2013;9(6):e1003500.
Given the anthropometric differences between men and women and previous evidence of sex-difference in genetic effects, we conducted a genome-wide search for sexually dimorphic associations with height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip-ratio (133,723 individuals) and took forward 348 SNPs into follow-up (additional 137,052 individuals) in a total of 94 studies. Seven loci displayed significant sex-difference (FDR<5%), including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were genome-wide significant in women (P<5×10−8), but not in men. Sex-differences were apparent only for waist phenotypes, not for height, weight, BMI, or hip circumference. Moreover, we found no evidence for genetic effects with opposite directions in men versus women. The PPARG locus is of specific interest due to its role in diabetes genetics and therapy. Our results demonstrate the value of sex-specific GWAS to unravel the sexually dimorphic genetic underpinning of complex traits.
Author Summary
Men and women differ substantially regarding height, weight, and body fat. Interestingly, previous work detecting genetic effects for waist-to-hip ratio, to assess body fat distribution, has found that many of these showed sex-differences. However, systematic searches for sex-differences in genetic effects have not yet been conducted. Therefore, we undertook a genome-wide search for sexually dimorphic genetic effects for anthropometric traits including 133,723 individuals in a large meta-analysis and followed promising variants in further 137,052 individuals, including a total of 94 studies. We identified seven loci with significant sex-difference including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were significant in women, but not in men. Of interest is that sex-difference was only observed for waist phenotypes, but not for height or body-mass-index. We found no evidence for sex-differences with opposite effect direction for men and women. The PPARG locus is of specific interest due to its link to diabetes genetics and therapy. Our findings demonstrate the importance of investigating sex differences, which may lead to a better understanding of disease mechanisms with a potential relevance to treatment options.
doi:10.1371/journal.pgen.1003500
PMCID: PMC3674993  PMID: 23754948
16.  Imputation of Variants from the 1000 Genomes Project Modestly Improves Known Associations and Can Identify Low-frequency Variant - Phenotype Associations Undetected by HapMap Based Imputation 
PLoS ONE  2013;8(5):e64343.
Genome-wide association (GWA) studies have been limited by the reliance on common variants present on microarrays or imputable from the HapMap Project data. More recently, the completion of the 1000 Genomes Project has provided variant and haplotype information for several million variants derived from sequencing over 1,000 individuals. To help understand the extent to which more variants (including low frequency (1% ≤ MAF <5%) and rare variants (<1%)) can enhance previously identified associations and identify novel loci, we selected 93 quantitative circulating factors where data was available from the InCHIANTI population study. These phenotypes included cytokines, binding proteins, hormones, vitamins and ions. We selected these phenotypes because many have known strong genetic associations and are potentially important to help understand disease processes. We performed a genome-wide scan for these 93 phenotypes in InCHIANTI. We identified 21 signals and 33 signals that reached P<5×10−8 based on HapMap and 1000 Genomes imputation, respectively, and 9 and 11 that reached a stricter, likely conservative, threshold of P<5×10−11 respectively. Imputation of 1000 Genomes genotype data modestly improved the strength of known associations. Of 20 associations detected at P<5×10−8 in both analyses (17 of which represent well replicated signals in the NHGRI catalogue), six were captured by the same index SNP, five were nominally more strongly associated in 1000 Genomes imputed data and one was nominally more strongly associated in HapMap imputed data. We also detected an association between a low frequency variant and phenotype that was previously missed by HapMap based imputation approaches. An association between rs112635299 and alpha-1 globulin near the SERPINA gene represented the known association between rs28929474 (MAF = 0.007) and alpha1-antitrypsin that predisposes to emphysema (P = 2.5×10−12). Our data provide important proof of principle that 1000 Genomes imputation will detect novel, low frequency-large effect associations.
doi:10.1371/journal.pone.0064343
PMCID: PMC3655956  PMID: 23696881
17.  No Interactions Between Previously Associated 2-Hour Glucose Gene Variants and Physical Activity or BMI on 2-Hour Glucose Levels 
Scott, Robert A. | Chu, Audrey Y. | Grarup, Niels | Manning, Alisa K. | Hivert, Marie-France | Shungin, Dmitry | Tönjes, Anke | Yesupriya, Ajay | Barnes, Daniel | Bouatia-Naji, Nabila | Glazer, Nicole L. | Jackson, Anne U. | Kutalik, Zoltán | Lagou, Vasiliki | Marek, Diana | Rasmussen-Torvik, Laura J. | Stringham, Heather M. | Tanaka, Toshiko | Aadahl, Mette | Arking, Dan E. | Bergmann, Sven | Boerwinkle, Eric | Bonnycastle, Lori L. | Bornstein, Stefan R. | Brunner, Eric | Bumpstead, Suzannah J. | Brage, Soren | Carlson, Olga D. | Chen, Han | Chen, Yii-Der Ida | Chines, Peter S. | Collins, Francis S. | Couper, David J. | Dennison, Elaine M. | Dowling, Nicole F. | Egan, Josephine S. | Ekelund, Ulf | Erdos, Michael R. | Forouhi, Nita G. | Fox, Caroline S. | Goodarzi, Mark O. | Grässler, Jürgen | Gustafsson, Stefan | Hallmans, Göran | Hansen, Torben | Hingorani, Aroon | Holloway, John W. | Hu, Frank B. | Isomaa, Bo | Jameson, Karen A. | Johansson, Ingegerd | Jonsson, Anna | Jørgensen, Torben | Kivimaki, Mika | Kovacs, Peter | Kumari, Meena | Kuusisto, Johanna | Laakso, Markku | Lecoeur, Cécile | Lévy-Marchal, Claire | Li, Guo | Loos, Ruth J.F. | Lyssenko, Valeri | Marmot, Michael | Marques-Vidal, Pedro | Morken, Mario A. | Müller, Gabriele | North, Kari E. | Pankow, James S. | Payne, Felicity | Prokopenko, Inga | Psaty, Bruce M. | Renström, Frida | Rice, Ken | Rotter, Jerome I. | Rybin, Denis | Sandholt, Camilla H. | Sayer, Avan A. | Shrader, Peter | Schwarz, Peter E.H. | Siscovick, David S. | Stančáková, Alena | Stumvoll, Michael | Teslovich, Tanya M. | Waeber, Gérard | Williams, Gordon H. | Witte, Daniel R. | Wood, Andrew R. | Xie, Weijia | Boehnke, Michael | Cooper, Cyrus | Ferrucci, Luigi | Froguel, Philippe | Groop, Leif | Kao, W.H. Linda | Vollenweider, Peter | Walker, Mark | Watanabe, Richard M. | Pedersen, Oluf | Meigs, James B. | Ingelsson, Erik | Barroso, Inês | Florez, Jose C. | Franks, Paul W. | Dupuis, Josée | Wareham, Nicholas J. | Langenberg, Claudia
Diabetes  2012;61(5):1291-1296.
Gene–lifestyle interactions have been suggested to contribute to the development of type 2 diabetes. Glucose levels 2 h after a standard 75-g glucose challenge are used to diagnose diabetes and are associated with both genetic and lifestyle factors. However, whether these factors interact to determine 2-h glucose levels is unknown. We meta-analyzed single nucleotide polymorphism (SNP) × BMI and SNP × physical activity (PA) interaction regression models for five SNPs previously associated with 2-h glucose levels from up to 22 studies comprising 54,884 individuals without diabetes. PA levels were dichotomized, with individuals below the first quintile classified as inactive (20%) and the remainder as active (80%). BMI was considered a continuous trait. Inactive individuals had higher 2-h glucose levels than active individuals (β = 0.22 mmol/L [95% CI 0.13–0.31], P = 1.63 × 10−6). All SNPs were associated with 2-h glucose (β = 0.06–0.12 mmol/allele, P ≤ 1.53 × 10−7), but no significant interactions were found with PA (P > 0.18) or BMI (P ≥ 0.04). In this large study of gene–lifestyle interaction, we observed no interactions between genetic and lifestyle factors, both of which were associated with 2-h glucose. It is perhaps unlikely that top loci from genome-wide association studies will exhibit strong subgroup-specific effects, and may not, therefore, make the best candidates for the study of interactions.
doi:10.2337/db11-0973
PMCID: PMC3331745  PMID: 22415877
18.  Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes 
Morris, Andrew P | Voight, Benjamin F | Teslovich, Tanya M | Ferreira, Teresa | Segrè, Ayellet V | Steinthorsdottir, Valgerdur | Strawbridge, Rona J | Khan, Hassan | Grallert, Harald | Mahajan, Anubha | Prokopenko, Inga | Kang, Hyun Min | Dina, Christian | Esko, Tonu | Fraser, Ross M | Kanoni, Stavroula | Kumar, Ashish | Lagou, Vasiliki | Langenberg, Claudia | Luan, Jian'an | Lindgren, Cecilia M | Müller-Nurasyid, Martina | Pechlivanis, Sonali | Rayner, N William | Scott, Laura J | Wiltshire, Steven | Yengo, Loic | Kinnunen, Leena | Rossin, Elizabeth J | Raychaudhuri, Soumya | Johnson, Andrew D | Dimas, Antigone S | Loos, Ruth J F | Vedantam, Sailaja | Chen, Han | Florez, Jose C | Fox, Caroline | Liu, Ching-Ti | Rybin, Denis | Couper, David J | Kao, Wen Hong L | Li, Man | Cornelis, Marilyn C | Kraft, Peter | Sun, Qi | van Dam, Rob M | Stringham, Heather M | Chines, Peter S | Fischer, Krista | Fontanillas, Pierre | Holmen, Oddgeir L | Hunt, Sarah E | Jackson, Anne U | Kong, Augustine | Lawrence, Robert | Meyer, Julia | Perry, John RB | Platou, Carl GP | Potter, Simon | Rehnberg, Emil | Robertson, Neil | Sivapalaratnam, Suthesh | Stančáková, Alena | Stirrups, Kathleen | Thorleifsson, Gudmar | Tikkanen, Emmi | Wood, Andrew R | Almgren, Peter | Atalay, Mustafa | Benediktsson, Rafn | Bonnycastle, Lori L | Burtt, Noël | Carey, Jason | Charpentier, Guillaume | Crenshaw, Andrew T | Doney, Alex S F | Dorkhan, Mozhgan | Edkins, Sarah | Emilsson, Valur | Eury, Elodie | Forsen, Tom | Gertow, Karl | Gigante, Bruna | Grant, George B | Groves, Christopher J | Guiducci, Candace | Herder, Christian | Hreidarsson, Astradur B | Hui, Jennie | James, Alan | Jonsson, Anna | Rathmann, Wolfgang | Klopp, Norman | Kravic, Jasmina | Krjutškov, Kaarel | Langford, Cordelia | Leander, Karin | Lindholm, Eero | Lobbens, Stéphane | Männistö, Satu | Mirza, Ghazala | Mühleisen, Thomas W | Musk, Bill | Parkin, Melissa | Rallidis, Loukianos | Saramies, Jouko | Sennblad, Bengt | Shah, Sonia | Sigurðsson, Gunnar | Silveira, Angela | Steinbach, Gerald | Thorand, Barbara | Trakalo, Joseph | Veglia, Fabrizio | Wennauer, Roman | Winckler, Wendy | Zabaneh, Delilah | Campbell, Harry | van Duijn, Cornelia | Uitterlinden89-, Andre G | Hofman, Albert | Sijbrands, Eric | Abecasis, Goncalo R | Owen, Katharine R | Zeggini, Eleftheria | Trip, Mieke D | Forouhi, Nita G | Syvänen, Ann-Christine | Eriksson, Johan G | Peltonen, Leena | Nöthen, Markus M | Balkau, Beverley | Palmer, Colin N A | Lyssenko, Valeriya | Tuomi, Tiinamaija | Isomaa, Bo | Hunter, David J | Qi, Lu | Shuldiner, Alan R | Roden, Michael | Barroso, Ines | Wilsgaard, Tom | Beilby, John | Hovingh, Kees | Price, Jackie F | Wilson, James F | Rauramaa, Rainer | Lakka, Timo A | Lind, Lars | Dedoussis, George | Njølstad, Inger | Pedersen, Nancy L | Khaw, Kay-Tee | Wareham, Nicholas J | Keinanen-Kiukaanniemi, Sirkka M | Saaristo, Timo E | Korpi-Hyövälti, Eeva | Saltevo, Juha | Laakso, Markku | Kuusisto, Johanna | Metspalu, Andres | Collins, Francis S | Mohlke, Karen L | Bergman, Richard N | Tuomilehto, Jaakko | Boehm, Bernhard O | Gieger, Christian | Hveem, Kristian | Cauchi, Stephane | Froguel, Philippe | Baldassarre, Damiano | Tremoli, Elena | Humphries, Steve E | Saleheen, Danish | Danesh, John | Ingelsson, Erik | Ripatti, Samuli | Salomaa, Veikko | Erbel, Raimund | Jöckel, Karl-Heinz | Moebus, Susanne | Peters, Annette | Illig, Thomas | de Faire, Ulf | Hamsten, Anders | Morris, Andrew D | Donnelly, Peter J | Frayling, Timothy M | Hattersley, Andrew T | Boerwinkle, Eric | Melander, Olle | Kathiresan, Sekar | Nilsson, Peter M | Deloukas, Panos | Thorsteinsdottir, Unnur | Groop, Leif C | Stefansson, Kari | Hu, Frank | Pankow, James S | Dupuis, Josée | Meigs, James B | Altshuler, David | Boehnke, Michael | McCarthy, Mark I
Nature genetics  2012;44(9):981-990.
To extend understanding of the genetic architecture and molecular basis of type 2 diabetes (T2D), we conducted a meta-analysis of genetic variants on the Metabochip involving 34,840 cases and 114,981 controls, overwhelmingly of European descent. We identified ten previously unreported T2D susceptibility loci, including two demonstrating sex-differentiated association. Genome-wide analyses of these data are consistent with a long tail of further common variant loci explaining much of the variation in susceptibility to T2D. Exploration of the enlarged set of susceptibility loci implicates several processes, including CREBBP-related transcription, adipocytokine signalling and cell cycle regulation, in diabetes pathogenesis.
doi:10.1038/ng.2383
PMCID: PMC3442244  PMID: 22885922
19.  Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes 
Morris, Andrew P | Voight, Benjamin F | Teslovich, Tanya M | Ferreira, Teresa | Segré, Ayellet V | Steinthorsdottir, Valgerdur | Strawbridge, Rona J | Khan, Hassan | Grallert, Harald | Mahajan, Anubha | Prokopenko, Inga | Kang, Hyun Min | Dina, Christian | Esko, Tonu | Fraser, Ross M | Kanoni, Stavroula | Kumar, Ashish | Lagou, Vasiliki | Langenberg, Claudia | Luan, Jian’an | Lindgren, Cecilia M | Müller-Nurasyid, Martina | Pechlivanis, Sonali | Rayner, N William | Scott, Laura J | Wiltshire, Steven | Yengo, Loic | Kinnunen, Leena | Rossin, Elizabeth J | Raychaudhuri, Soumya | Johnson, Andrew D | Dimas, Antigone S | Loos, Ruth J F | Vedantam, Sailaja | Chen, Han | Florez, Jose C | Fox, Caroline | Liu, Ching-Ti | Rybin, Denis | Couper, David J | Kao, Wen Hong L | Li, Man | Cornelis, Marilyn C | Kraft, Peter | Sun, Qi | van Dam, Rob M | Stringham, Heather M | Chines, Peter S | Fischer, Krista | Fontanillas, Pierre | Holmen, Oddgeir L | Hunt, Sarah E | Jackson, Anne U | Kong, Augustine | Lawrence, Robert | Meyer, Julia | Perry, John R B | Platou, Carl G P | Potter, Simon | Rehnberg, Emil | Robertson, Neil | Sivapalaratnam, Suthesh | Stančáková, Alena | Stirrups, Kathleen | Thorleifsson, Gudmar | Tikkanen, Emmi | Wood, Andrew R | Almgren, Peter | Atalay, Mustafa | Benediktsson, Rafn | Bonnycastle, Lori L | Burtt, Noël | Carey, Jason | Charpentier, Guillaume | Crenshaw, Andrew T | Doney, Alex S F | Dorkhan, Mozhgan | Edkins, Sarah | Emilsson, Valur | Eury, Elodie | Forsen, Tom | Gertow, Karl | Gigante, Bruna | Grant, George B | Groves, Christopher J | Guiducci, Candace | Herder, Christian | Hreidarsson, Astradur B | Hui, Jennie | James, Alan | Jonsson, Anna | Rathmann, Wolfgang | Klopp, Norman | Kravic, Jasmina | Krjutškov, Kaarel | Langford, Cordelia | Leander, Karin | Lindholm, Eero | Lobbens, Stéphane | Männistö, Satu | Mirza, Ghazala | Mühleisen, Thomas W | Musk, Bill | Parkin, Melissa | Rallidis, Loukianos | Saramies, Jouko | Sennblad, Bengt | Shah, Sonia | Sigurðsson, Gunnar | Silveira, Angela | Steinbach, Gerald | Thorand, Barbara | Trakalo, Joseph | Veglia, Fabrizio | Wennauer, Roman | Winckler, Wendy | Zabaneh, Delilah | Campbell, Harry | van Duijn, Cornelia | Uitterlinden, Andre G | Hofman, Albert | Sijbrands, Eric | Abecasis, Goncalo R | Owen, Katharine R | Zeggini, Eleftheria | Trip, Mieke D | Forouhi, Nita G | Syvänen, Ann-Christine | Eriksson, Johan G | Peltonen, Leena | Nöthen, Markus M | Balkau, Beverley | Palmer, Colin N A | Lyssenko, Valeriya | Tuomi, Tiinamaija | Isomaa, Bo | Hunter, David J | Qi, Lu | Shuldiner, Alan R | Roden, Michael | Barroso, Ines | Wilsgaard, Tom | Beilby, John | Hovingh, Kees | Price, Jackie F | Wilson, James F | Rauramaa, Rainer | Lakka, Timo A | Lind, Lars | Dedoussis, George | Njølstad, Inger | Pedersen, Nancy L | Khaw, Kay-Tee | Wareham, Nicholas J | Keinanen-Kiukaanniemi, Sirkka M | Saaristo, Timo E | Korpi-Hyövälti, Eeva | Saltevo, Juha | Laakso, Markku | Kuusisto, Johanna | Metspalu, Andres | Collins, Francis S | Mohlke, Karen L | Bergman, Richard N | Tuomilehto, Jaakko | Boehm, Bernhard O | Gieger, Christian | Hveem, Kristian | Cauchi, Stephane | Froguel, Philippe | Baldassarre, Damiano | Tremoli, Elena | Humphries, Steve E | Saleheen, Danish | Danesh, John | Ingelsson, Erik | Ripatti, Samuli | Salomaa, Veikko | Erbel, Raimund | Jöckel, Karl-Heinz | Moebus, Susanne | Peters, Annette | Illig, Thomas | de Faire, Ulf | Hamsten, Anders | Morris, Andrew D | Donnelly, Peter J | Frayling, Timothy M | Hattersley, Andrew T | Boerwinkle, Eric | Melander, Olle | Kathiresan, Sekar | Nilsson, Peter M | Deloukas, Panos | Thorsteinsdottir, Unnur | Groop, Leif C | Stefansson, Kari | Hu, Frank | Pankow, James S | Dupuis, Josée | Meigs, James B | Altshuler, David | Boehnke, Michael | McCarthy, Mark I
Nature genetics  2012;44(9):981-990.
To extend understanding of the genetic architecture and molecular basis of type 2 diabetes (T2D), we conducted a meta-analysis of genetic variants on the Metabochip involving 34,840 cases and 114,981 controls, overwhelmingly of European descent. We identified ten previously unreported T2D susceptibility loci, including two demonstrating sex-differentiated association. Genome-wide analyses of these data are consistent with a long tail of further common variant loci explaining much of the variation in susceptibility to T2D. Exploration of the enlarged set of susceptibility loci implicates several processes, including CREBBP-related transcription, adipocytokine signalling and cell cycle regulation, in diabetes pathogenesis.
doi:10.1038/ng.2383
PMCID: PMC3442244  PMID: 22885922
20.  Causal Relationship between Obesity and Vitamin D Status: Bi-Directional Mendelian Randomization Analysis of Multiple Cohorts 
PLoS Medicine  2013;10(2):e1001383.
A mendelian randomization study based on data from multiple cohorts conducted by Karani Santhanakrishnan Vimaleswaran and colleagues re-examines the causal nature of the relationship between vitamin D levels and obesity.
Background
Obesity is associated with vitamin D deficiency, and both are areas of active public health concern. We explored the causality and direction of the relationship between body mass index (BMI) and 25-hydroxyvitamin D [25(OH)D] using genetic markers as instrumental variables (IVs) in bi-directional Mendelian randomization (MR) analysis.
Methods and Findings
We used information from 21 adult cohorts (up to 42,024 participants) with 12 BMI-related SNPs (combined in an allelic score) to produce an instrument for BMI and four SNPs associated with 25(OH)D (combined in two allelic scores, separately for genes encoding its synthesis or metabolism) as an instrument for vitamin D. Regression estimates for the IVs (allele scores) were generated within-study and pooled by meta-analysis to generate summary effects.
Associations between vitamin D scores and BMI were confirmed in the Genetic Investigation of Anthropometric Traits (GIANT) consortium (n = 123,864). Each 1 kg/m2 higher BMI was associated with 1.15% lower 25(OH)D (p = 6.52×10−27). The BMI allele score was associated both with BMI (p = 6.30×10−62) and 25(OH)D (−0.06% [95% CI −0.10 to −0.02], p = 0.004) in the cohorts that underwent meta-analysis. The two vitamin D allele scores were strongly associated with 25(OH)D (p≤8.07×10−57 for both scores) but not with BMI (synthesis score, p = 0.88; metabolism score, p = 0.08) in the meta-analysis. A 10% higher genetically instrumented BMI was associated with 4.2% lower 25(OH)D concentrations (IV ratio: −4.2 [95% CI −7.1 to −1.3], p = 0.005). No association was seen for genetically instrumented 25(OH)D with BMI, a finding that was confirmed using data from the GIANT consortium (p≥0.57 for both vitamin D scores).
Conclusions
On the basis of a bi-directional genetic approach that limits confounding, our study suggests that a higher BMI leads to lower 25(OH)D, while any effects of lower 25(OH)D increasing BMI are likely to be small. Population level interventions to reduce BMI are expected to decrease the prevalence of vitamin D deficiency.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Obesity—having an unhealthy amount of body fat—is increasing worldwide. In the US, for example, a third of the adult population is now obese. Obesity is defined as having a body mass index (BMI, an indicator of body fat calculated by dividing a person's weight in kilograms by their height in meters squared) of more than 30.0 kg/m2. Although there is a genetic contribution to obesity, people generally become obese by consuming food and drink that contains more energy than they need for their daily activities. Thus, obesity can be prevented by having a healthy diet and exercising regularly. Compared to people with a healthy weight, obese individuals have an increased risk of developing diabetes, heart disease and stroke, and tend to die younger. They also have a higher risk of vitamin D deficiency, another increasingly common public health concern. Vitamin D, which is essential for healthy bones as well as other functions, is made in the skin after exposure to sunlight but can also be obtained through the diet and through supplements.
Why Was This Study Done?
Observational studies cannot prove that obesity causes vitamin D deficiency because obese individuals may share other characteristics that reduce their circulating 25-hydroxy vitamin D [25(OH)D] levels (referred to as confounding). Moreover, observational studies cannot indicate whether the larger vitamin D storage capacity of obese individuals (vitamin D is stored in fatty tissues) lowers their 25(OH)D levels or whether 25(OH)D levels influence fat accumulation (reverse causation). If obesity causes vitamin D deficiency, monitoring and treating vitamin D deficiency might alleviate some of the adverse health effects of obesity. Conversely, if low vitamin D levels cause obesity, encouraging people to take vitamin D supplements might help to control the obesity epidemic. Here, the researchers use bi-directional “Mendelian randomization” to examine the direction and causality of the relationship between BMI and 25(OH)D. In Mendelian randomization, causality is inferred from associations between genetic variants that mimic the influence of a modifiable environmental exposure and the outcome of interest. Because gene variants do not change over time and are inherited randomly, they are not prone to confounding and are free from reverse causation. Thus, if a lower vitamin D status leads to obesity, genetic variants associated with lower 25(OH)D concentrations should be associated with higher BMI, and if obesity leads to a lower vitamin D status, then genetic variants associated with higher BMI should be associated with lower 25(OH)D concentrations.
What Did the Researchers Do and Find?
The researchers created a “BMI allele score” based on 12 BMI-related gene variants and two “25(OH)D allele scores,” which are based on gene variants that affect either 25(OH)D synthesis or breakdown. Using information on up to 42,024 participants from 21 studies, the researchers showed that the BMI allele score was associated with both BMI and with 25(OH)D levels among the study participants. Based on this information, they calculated that each 10% increase in BMI will lead to a 4.2% decrease in 25(OH)D concentrations. By contrast, although both 25(OH)D allele scores were strongly associated with 25(OH)D levels, neither score was associated with BMI. This lack of an association between 25(OH)D allele scores and obesity was confirmed using data from more than 100,000 individuals involved in 46 studies that has been collected by the GIANT (Genetic Investigation of Anthropometric Traits) consortium.
What Do These Findings Mean?
These findings suggest that a higher BMI leads to a lower vitamin D status whereas any effects of low vitamin D status on BMI are likely to be small. That is, these findings provide evidence for obesity as a causal factor in the development of vitamin D deficiency but not for vitamin D deficiency as a causal factor in the development of obesity. These findings suggest that population-level interventions to reduce obesity should lead to a reduction in the prevalence of vitamin D deficiency and highlight the importance of monitoring and treating vitamin D deficiency as a means of alleviating the adverse influences of obesity on health.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001383.
The US Centers for Disease Control and Prevention provides information on all aspects of overweight and obesity (in English and Spanish); a data brief provides information about the vitamin D status of the US population
The World Health Organization provides information on obesity (in several languages)
The UK National Health Service Choices website provides detailed information about obesity and a link to a personal story about losing weight; it also provides information about vitamin D
The International Obesity Taskforce provides information about the global obesity epidemic
The US Department of Agriculture's ChooseMyPlate.gov website provides a personal healthy eating plan; the Weight-control Information Network is an information service provided for the general public and health professionals by the US National Institute of Diabetes and Digestive and Kidney Diseases (in English and Spanish)
The US Office of Dietary Supplements provides information about vitamin D (in English and Spanish)
MedlinePlus has links to further information about obesity and about vitamin D (in English and Spanish)
Wikipedia has a page on Mendelian randomization (note: Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
Overview and details of the collaborative large-scale genetic association study (D-CarDia) provide information about vitamin D and the risk of cardiovascular disease, diabetes and related traits
doi:10.1371/journal.pmed.1001383
PMCID: PMC3564800  PMID: 23393431
21.  Association Between Chromosome 9p21 Variants and the Ankle-Brachial Index Identified by a Meta-Analysis of 21 Genome-Wide Association Studies 
Murabito, Joanne M. | White, Charles C. | Kavousi, Maryam | Sun, Yan V. | Feitosa, Mary F. | Nambi, Vijay | Lamina, Claudia | Schillert, Arne | Coassin, Stefan | Bis, Joshua C. | Broer, Linda | Crawford, Dana C. | Franceschini, Nora | Frikke-Schmidt, Ruth | Haun, Margot | Holewijn, Suzanne | Huffman, Jennifer E. | Hwang, Shih-Jen | Kiechl, Stefan | Kollerits, Barbara | Montasser, May E. | Nolte, Ilja M. | Rudock, Megan E. | Senft, Andrea | Teumer, Alexander | van der Harst, Pim | Vitart, Veronique | Waite, Lindsay L. | Wood, Andrew R. | Wassel, Christina L. | Absher, Devin M. | Allison, Matthew A. | Amin, Najaf | Arnold, Alice | Asselbergs, Folkert W. | Aulchenko, Yurii | Bandinelli, Stefania | Barbalic, Maja | Boban, Mladen | Brown-Gentry, Kristin | Couper, David J. | Criqui, Michael H. | Dehghan, Abbas | Heijer, Martin den | Dieplinger, Benjamin | Ding, Jingzhong | Dörr, Marcus | Espinola-Klein, Christine | Felix, Stephan B. | Ferrucci, Luigi | Folsom, Aaron R. | Fraedrich, Gustav | Gibson, Quince | Goodloe, Robert | Gunjaca, Grgo | Haltmayer, Meinhard | Heiss, Gerardo | Hofman, Albert | Kieback, Arne | Kiemeney, Lambertus A. | Kolcic, Ivana | Kullo, Iftikhar J. | Kritchevsky, Stephen B. | Lackner, Karl J. | Li, Xiaohui | Lieb, Wolfgang | Lohman, Kurt | Meisinger, Christa | Melzer, David | Mohler, Emile R | Mudnic, Ivana | Mueller, Thomas | Navis, Gerjan | Oberhollenzer, Friedrich | Olin, Jeffrey W. | O’Connell, Jeff | O’Donnell, Christopher J. | Palmas, Walter | Penninx, Brenda W. | Petersmann, Astrid | Polasek, Ozren | Psaty, Bruce M. | Rantner, Barbara | Rice, Ken | Rivadeneira, Fernando | Rotter, Jerome I. | Seldenrijk, Adrie | Stadler, Marietta | Summerer, Monika | Tanaka, Toshiko | Tybjaerg-Hansen, Anne | Uitterlinden, Andre G. | van Gilst, Wiek H. | Vermeulen, Sita H. | Wild, Sarah H. | Wild, Philipp S. | Willeit, Johann | Zeller, Tanja | Zemunik, Tatijana | Zgaga, Lina | Assimes, Themistocles L. | Blankenberg, Stefan | Boerwinkle, Eric | Campbell, Harry | Cooke, John P. | de Graaf, Jacqueline | Herrington, David | Kardia, Sharon L. R. | Mitchell, Braxton D. | Murray, Anna | Münzel, Thomas | Newman, Anne | Oostra, Ben A. | Rudan, Igor | Shuldiner, Alan R. | Snieder, Harold | van Duijn, Cornelia M. | Völker, Uwe | Wright, Alan F. | Wichmann, H.-Erich | Wilson, James F. | Witteman, Jacqueline C.M. | Liu, Yongmei | Hayward, Caroline | Borecki, Ingrid B. | Ziegler, Andreas | North, Kari E. | Cupples, L. Adrienne | Kronenberg, Florian
Background
Genetic determinants of peripheral arterial disease (PAD) remain largely unknown. To identify genetic variants associated with the ankle-brachial index (ABI), a noninvasive measure of PAD, we conducted a meta-analysis of genome-wide association study data from 21 population-based cohorts.
Methods and Results
Continuous ABI and PAD (ABI≤0.9) phenotypes adjusted for age and sex were examined. Each study conducted genotyping and imputed data to the ~2.5 million SNPs in HapMap. Linear and logistic regression models were used to test each SNP for association with ABI and PAD using additive genetic models. Study-specific data were combined using fixed-effects inverse variance weighted meta-analyses. There were a total of 41,692 participants of European ancestry (~60% women, mean ABI 1.02 to 1.19), including 3,409 participants with PAD and with GWAS data available. In the discovery meta-analysis, rs10757269 on chromosome 9 near CDKN2B had the strongest association with ABI (β= −0.006, p=2.46x10−8). We sought replication of the 6 strongest SNP associations in 5 population-based studies and 3 clinical samples (n=16,717). The association for rs10757269 strengthened in the combined discovery and replication analysis (p=2.65x10−9). No other SNP associations for ABI or PAD achieved genome-wide significance. However, two previously reported candidate genes for PAD and one SNP associated with coronary artery disease (CAD) were associated with ABI : DAB21P (rs13290547, p=3.6x10−5); CYBA (rs3794624, p=6.3x10−5); and rs1122608 (LDLR, p=0.0026).
Conclusions
GWAS in more than 40,000 individuals identified one genome-wide significant association on chromosome 9p21 with ABI. Two candidate genes for PAD and 1 SNP for CAD are associated with ABI.
doi:10.1161/CIRCGENETICS.111.961292
PMCID: PMC3303225  PMID: 22199011
cohort study; genetic association; genome-wide association study; meta-analysis; peripheral vascular disease
22.  Condensin and cohesin complexity: the expanding repertoire of functions 
Nature reviews. Genetics  2010;11(6):391-404.
Condensin and cohesin complexes act in diverse nuclear processes in addition to their widely known roles in chromosome compaction and sister chromatid cohesion. Recent work has elucidated the contribution of condensin and cohesin to interphase genome organization, control of gene expression, metazoan development and meiosis. Despite these wide-ranging functions, several themes have come to light: both complexes establish higher-order chromosome structure by inhibiting or promoting interactions between distant genomic regions, both complexes influence the chromosomal association of other proteins, and both complexes achieve functional specialization by swapping homologous subunits. Emerging data are expanding the range of processes in which condensin and cohesin are known to participate and are enhancing our knowledge of how chromosome architecture is regulated to influence numerous cellular functions.
doi:10.1038/nrg2794
PMCID: PMC3491780  PMID: 20442714
24.  NgR1 and NgR3 are Receptors for Chondroitin Sulfate Proteoglycans 
Nature neuroscience  2012;15(5):703-712.
In the adult mammalian CNS, chondroitin sulfate proteoglycans (CSPGs) and myelin–associated inhibitors (MAIs) stabilize neuronal structure and restrict compensatory sprouting following injury. The Nogo receptor family members NgR1 and NgR2 bind to MAIs and have been implicated in neuronal inhibition. Here we show that NgR1 and NgR3 bind with high–affinity to the glycosaminoglycan moiety of proteoglycans and participate in CSPG inhibition in cultured neurons. Nogo receptor triple mutants (NgR123−/−), but not single mutants, show enhanced axonal regeneration following retro–orbital optic nerve crush injury. The combined loss of NgR1 and NgR3 (NgR13−/−), but not NgR1 and NgR2 (NgR12−/−), is sufficient to mimic the NgR123−/− regeneration phenotype. Regeneration in NgR13−/− mice is further enhanced by simultaneous ablation of RPTPσ, a known CSPG receptor. Collectively, these results identify NgR1 and NgR3 as novel CSPG receptors, demonstrate functional redundancy among CSPG receptors, and provide unexpected evidence for shared mechanisms of MAI and CSPG inhibition.
doi:10.1038/nn.3070
PMCID: PMC3337880  PMID: 22406547
25.  Genome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture 
Estrada, Karol | Styrkarsdottir, Unnur | Evangelou, Evangelos | Hsu, Yi-Hsiang | Duncan, Emma L | Ntzani, Evangelia E | Oei, Ling | Albagha, Omar M E | Amin, Najaf | Kemp, John P | Koller, Daniel L | Li, Guo | Liu, Ching-Ti | Minster, Ryan L | Moayyeri, Alireza | Vandenput, Liesbeth | Willner, Dana | Xiao, Su-Mei | Yerges-Armstrong, Laura M | Zheng, Hou-Feng | Alonso, Nerea | Eriksson, Joel | Kammerer, Candace M | Kaptoge, Stephen K | Leo, Paul J | Thorleifsson, Gudmar | Wilson, Scott G | Wilson, James F | Aalto, Ville | Alen, Markku | Aragaki, Aaron K | Aspelund, Thor | Center, Jacqueline R | Dailiana, Zoe | Duggan, David J | Garcia, Melissa | Garcia-Giralt, Natàlia | Giroux, Sylvie | Hallmans, Göran | Hocking, Lynne J | Husted, Lise Bjerre | Jameson, Karen A | Khusainova, Rita | Kim, Ghi Su | Kooperberg, Charles | Koromila, Theodora | Kruk, Marcin | Laaksonen, Marika | Lacroix, Andrea Z | Lee, Seung Hun | Leung, Ping C | Lewis, Joshua R | Masi, Laura | Mencej-Bedrac, Simona | Nguyen, Tuan V | Nogues, Xavier | Patel, Millan S | Prezelj, Janez | Rose, Lynda M | Scollen, Serena | Siggeirsdottir, Kristin | Smith, Albert V | Svensson, Olle | Trompet, Stella | Trummer, Olivia | van Schoor, Natasja M | Woo, Jean | Zhu, Kun | Balcells, Susana | Brandi, Maria Luisa | Buckley, Brendan M | Cheng, Sulin | Christiansen, Claus | Cooper, Cyrus | Dedoussis, George | Ford, Ian | Frost, Morten | Goltzman, David | González-Macías, Jesús | Kähönen, Mika | Karlsson, Magnus | Khusnutdinova, Elza | Koh, Jung-Min | Kollia, Panagoula | Langdahl, Bente Lomholt | Leslie, William D | Lips, Paul | Ljunggren, Östen | Lorenc, Roman S | Marc, Janja | Mellström, Dan | Obermayer-Pietsch, Barbara | Olmos, José M | Pettersson-Kymmer, Ulrika | Reid, David M | Riancho, José A | Ridker, Paul M | Rousseau, François | Slagboom, P Eline | Tang, Nelson LS | Urreizti, Roser | Van Hul, Wim | Viikari, Jorma | Zarrabeitia, María T | Aulchenko, Yurii S | Castano-Betancourt, Martha | Grundberg, Elin | Herrera, Lizbeth | Ingvarsson, Thorvaldur | Johannsdottir, Hrefna | Kwan, Tony | Li, Rui | Luben, Robert | Medina-Gómez, Carolina | Palsson, Stefan Th | Reppe, Sjur | Rotter, Jerome I | Sigurdsson, Gunnar | van Meurs, Joyce B J | Verlaan, Dominique | Williams, Frances MK | Wood, Andrew R | Zhou, Yanhua | Gautvik, Kaare M | Pastinen, Tomi | Raychaudhuri, Soumya | Cauley, Jane A | Chasman, Daniel I | Clark, Graeme R | Cummings, Steven R | Danoy, Patrick | Dennison, Elaine M | Eastell, Richard | Eisman, John A | Gudnason, Vilmundur | Hofman, Albert | Jackson, Rebecca D | Jones, Graeme | Jukema, J Wouter | Khaw, Kay-Tee | Lehtimäki, Terho | Liu, Yongmei | Lorentzon, Mattias | McCloskey, Eugene | Mitchell, Braxton D | Nandakumar, Kannabiran | Nicholson, Geoffrey C | Oostra, Ben A | Peacock, Munro | Pols, Huibert A P | Prince, Richard L | Raitakari, Olli | Reid, Ian R | Robbins, John | Sambrook, Philip N | Sham, Pak Chung | Shuldiner, Alan R | Tylavsky, Frances A | van Duijn, Cornelia M | Wareham, Nick J | Cupples, L Adrienne | Econs, Michael J | Evans, David M | Harris, Tamara B | Kung, Annie Wai Chee | Psaty, Bruce M | Reeve, Jonathan | Spector, Timothy D | Streeten, Elizabeth A | Zillikens, M Carola | Thorsteinsdottir, Unnur | Ohlsson, Claes | Karasik, David | Richards, J Brent | Brown, Matthew A | Stefansson, Kari | Uitterlinden, André G | Ralston, Stuart H | Ioannidis, John P A | Kiel, Douglas P | Rivadeneira, Fernando
Nature genetics  2012;44(5):491-501.
Bone mineral density (BMD) is the most important predictor of fracture risk. We performed the largest meta-analysis to date on lumbar spine and femoral neck BMD, including 17 genome-wide association studies and 32,961 individuals of European and East Asian ancestry. We tested the top-associated BMD markers for replication in 50,933 independent subjects and for risk of low-trauma fracture in 31,016 cases and 102,444 controls. We identified 56 loci (32 novel)associated with BMD atgenome-wide significant level (P<5×10−8). Several of these factors cluster within the RANK-RANKL-OPG, mesenchymal-stem-cell differentiation, endochondral ossification and the Wnt signalling pathways. However, we also discovered loci containing genes not known to play a role in bone biology. Fourteen BMD loci were also associated with fracture risk (P<5×10−4, Bonferroni corrected), of which six reached P<5×10−8 including: 18p11.21 (C18orf19), 7q21.3 (SLC25A13), 11q13.2 (LRP5), 4q22.1 (MEPE), 2p16.2 (SPTBN1) and 10q21.1 (DKK1). These findings shed light on the genetic architecture and pathophysiological mechanisms underlying BMD variation and fracture susceptibility.
doi:10.1038/ng.2249
PMCID: PMC3338864  PMID: 22504420

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