PMCC PMCC

Search tips
Search criteria

Advanced
Results 1-24 (24)
 

Clipboard (0)
None

Select a Filter Below

Journals
more »
Year of Publication
Document Types
1.  No Association of nineteenCOX-2 gene variants to preclinical markers of atherosclerosis The Cardiovascular Risk in Young Finns Study 
BMC Medical Genetics  2012;13:32.
Backgroud
The role of cyclooxygenase-2 (COX-2) single nucleotide polymorphisms has mostly been studied in relation to advanced atherosclerosis, but little is known how they contribute to preclinical disease. In the present study we analyzed whether COX-2 gene variants associate independently with the early subclinical markers of atherosclerosis, carotid intima-media thickness and carotid artery distensibility in a population of young healthy Caucasian adults.
Methods
SNPs for association analysis were collected from the COX-2 gene and 5 kb up- and downstream of it. There were 19 SNPs available for analysis, four genotyped and fifteen imputed. Genotype data was available for 2442 individuals participating in the Cardiovascular Risk in Young Finns Study. Genotype imputation was performed using MACH 1.0 and HapMap II CEU (release 22) samples as reference. Association analysis was performed using linear regression with an additive model. PLINK was used for true genotyped SNPs and ProbABEL for imputed genotype dosages. False discovery rate was used to take into account multiple testing bias.
Results
Two of the COX-2 variants (rs689470, rs689462) associated with distensibility (p = 0.005) under the linear regression additive model. After adjustment with gender, age, body mass index and smoking status, association between these SNPs and distensibility remained significant (p = 0.031). Subjects carrying the minor alleles had higher value of carotid artery distensibility compared to the major allele homozygotes. However, after correcting p-values for multiple testing bias using false discovery rate, association was lost. Another COX-2 variant rs4648261 associated with mean carotid intima-media thickness (p = 0.046) and maximal carotid intima-media thickness (p = 0.048) in the linear regression model. Subjects carrying the minor allele of rs4648261 had lower values of mean and maximal carotid intima-media thickness compared to subjects homozygote for major allele. After adjustments the associations were lost with both mean and maximal carotid intima-media thickness. Thus, no statistically significant associations of the studied COX-2 variants with carotid artery distensibility or carotid intima-media thickness were found.
Conclusions
Our results suggest that in a Finnish population, there are no significant associations between COX-2 variants and early atherosclerotic changes in young adulthood.
doi:10.1186/1471-2350-13-32
PMCID: PMC3388005  PMID: 22551325
2.  Genetic association study of QT interval highlights role for calcium signaling pathways in myocardial repolarization 
Arking, Dan E. | Pulit, Sara L. | Crotti, Lia | van der Harst, Pim | Munroe, Patricia B. | Koopmann, Tamara T. | Sotoodehnia, Nona | Rossin, Elizabeth J. | Morley, Michael | Wang, Xinchen | Johnson, Andrew D. | Lundby, Alicia | Gudbjartsson, Daníel F. | Noseworthy, Peter A. | Eijgelsheim, Mark | Bradford, Yuki | Tarasov, Kirill V. | Dörr, Marcus | Müller-Nurasyid, Martina | Lahtinen, Annukka M. | Nolte, Ilja M. | Smith, Albert Vernon | Bis, Joshua C. | Isaacs, Aaron | Newhouse, Stephen J. | Evans, Daniel S. | Post, Wendy S. | Waggott, Daryl | Lyytikäinen, Leo-Pekka | Hicks, Andrew A. | Eisele, Lewin | Ellinghaus, David | Hayward, Caroline | Navarro, Pau | Ulivi, Sheila | Tanaka, Toshiko | Tester, David J. | Chatel, Stéphanie | Gustafsson, Stefan | Kumari, Meena | Morris, Richard W. | Naluai, Åsa T. | Padmanabhan, Sandosh | Kluttig, Alexander | Strohmer, Bernhard | Panayiotou, Andrie G. | Torres, Maria | Knoflach, Michael | Hubacek, Jaroslav A. | Slowikowski, Kamil | Raychaudhuri, Soumya | Kumar, Runjun D. | Harris, Tamara B. | Launer, Lenore J. | Shuldiner, Alan R. | Alonso, Alvaro | Bader, Joel S. | Ehret, Georg | Huang, Hailiang | Kao, W.H. Linda | Strait, James B. | Macfarlane, Peter W. | Brown, Morris | Caulfield, Mark J. | Samani, Nilesh J. | Kronenberg, Florian | Willeit, Johann | Smith, J. Gustav | Greiser, Karin H. | zu Schwabedissen, Henriette Meyer | Werdan, Karl | Carella, Massimo | Zelante, Leopoldo | Heckbert, Susan R. | Psaty, Bruce M. | Rotter, Jerome I. | Kolcic, Ivana | Polašek, Ozren | Wright, Alan F. | Griffin, Maura | Daly, Mark J. | Arnar, David O. | Hólm, Hilma | Thorsteinsdottir, Unnur | Denny, Joshua C. | Roden, Dan M. | Zuvich, Rebecca L. | Emilsson, Valur | Plump, Andrew S. | Larson, Martin G. | O'Donnell, Christopher J. | Yin, Xiaoyan | Bobbo, Marco | D'Adamo, Adamo P. | Iorio, Annamaria | Sinagra, Gianfranco | Carracedo, Angel | Cummings, Steven R. | Nalls, Michael A. | Jula, Antti | Kontula, Kimmo K. | Marjamaa, Annukka | Oikarinen, Lasse | Perola, Markus | Porthan, Kimmo | Erbel, Raimund | Hoffmann, Per | Jöckel, Karl-Heinz | Kälsch, Hagen | Nöthen, Markus M. | consortium, HRGEN | den Hoed, Marcel | Loos, Ruth J.F. | Thelle, Dag S. | Gieger, Christian | Meitinger, Thomas | Perz, Siegfried | Peters, Annette | Prucha, Hanna | Sinner, Moritz F. | Waldenberger, Melanie | de Boer, Rudolf A. | Franke, Lude | van der Vleuten, Pieter A. | Beckmann, Britt Maria | Martens, Eimo | Bardai, Abdennasser | Hofman, Nynke | Wilde, Arthur A.M. | Behr, Elijah R. | Dalageorgou, Chrysoula | Giudicessi, John R. | Medeiros-Domingo, Argelia | Barc, Julien | Kyndt, Florence | Probst, Vincent | Ghidoni, Alice | Insolia, Roberto | Hamilton, Robert M. | Scherer, Stephen W. | Brandimarto, Jeffrey | Margulies, Kenneth | Moravec, Christine E. | Fabiola Del, Greco M. | Fuchsberger, Christian | O'Connell, Jeffrey R. | Lee, Wai K. | Watt, Graham C.M. | Campbell, Harry | Wild, Sarah H. | El Mokhtari, Nour E. | Frey, Norbert | Asselbergs, Folkert W. | Leach, Irene Mateo | Navis, Gerjan | van den Berg, Maarten P. | van Veldhuisen, Dirk J. | Kellis, Manolis | Krijthe, Bouwe P. | Franco, Oscar H. | Hofman, Albert | Kors, Jan A. | Uitterlinden, André G. | Witteman, Jacqueline C.M. | Kedenko, Lyudmyla | Lamina, Claudia | Oostra, Ben A. | Abecasis, Gonçalo R. | Lakatta, Edward G. | Mulas, Antonella | Orrú, Marco | Schlessinger, David | Uda, Manuela | Markus, Marcello R.P. | Völker, Uwe | Snieder, Harold | Spector, Timothy D. | Ärnlöv, Johan | Lind, Lars | Sundström, Johan | Syvänen, Ann-Christine | Kivimaki, Mika | Kähönen, Mika | Mononen, Nina | Raitakari, Olli T. | Viikari, Jorma S. | Adamkova, Vera | Kiechl, Stefan | Brion, Maria | Nicolaides, Andrew N. | Paulweber, Bernhard | Haerting, Johannes | Dominiczak, Anna F. | Nyberg, Fredrik | Whincup, Peter H. | Hingorani, Aroon | Schott, Jean-Jacques | Bezzina, Connie R. | Ingelsson, Erik | Ferrucci, Luigi | Gasparini, Paolo | Wilson, James F. | Rudan, Igor | Franke, Andre | Mühleisen, Thomas W. | Pramstaller, Peter P. | Lehtimäki, Terho J. | Paterson, Andrew D. | Parsa, Afshin | Liu, Yongmei | van Duijn, Cornelia | Siscovick, David S. | Gudnason, Vilmundur | Jamshidi, Yalda | Salomaa, Veikko | Felix, Stephan B. | Sanna, Serena | Ritchie, Marylyn D. | Stricker, Bruno H. | Stefansson, Kari | Boyer, Laurie A. | Cappola, Thomas P. | Olsen, Jesper V. | Lage, Kasper | Schwartz, Peter J. | Kääb, Stefan | Chakravarti, Aravinda | Ackerman, Michael J. | Pfeufer, Arne | de Bakker, Paul I.W. | Newton-Cheh, Christopher
Nature genetics  2014;46(8):826-836.
The QT interval, an electrocardiographic measure reflecting myocardial repolarization, is a heritable trait. QT prolongation is a risk factor for ventricular arrhythmias and sudden cardiac death (SCD) and could indicate the presence of the potentially lethal Mendelian Long QT Syndrome (LQTS). Using a genome-wide association and replication study in up to 100,000 individuals we identified 35 common variant QT interval loci, that collectively explain ∼8-10% of QT variation and highlight the importance of calcium regulation in myocardial repolarization. Rare variant analysis of 6 novel QT loci in 298 unrelated LQTS probands identified coding variants not found in controls but of uncertain causality and therefore requiring validation. Several newly identified loci encode for proteins that physically interact with other recognized repolarization proteins. Our integration of common variant association, expression and orthogonal protein-protein interaction screens provides new insights into cardiac electrophysiology and identifies novel candidate genes for ventricular arrhythmias, LQTS,and SCD.
doi:10.1038/ng.3014
PMCID: PMC4124521  PMID: 24952745
genome-wide association study; QT interval; Long QT Syndrome; sudden cardiac death; myocardial repolarization; arrhythmias
3.  Mendelian Randomization Studies Do Not Support a Causal Role for Reduced Circulating Adiponectin Levels in Insulin Resistance and Type 2 Diabetes 
Yaghootkar, Hanieh | Lamina, Claudia | Scott, Robert A. | Dastani, Zari | Hivert, Marie-France | Warren, Liling L. | Stancáková, Alena | Buxbaum, Sarah G. | Lyytikäinen, Leo-Pekka | Henneman, Peter | Wu, Ying | Cheung, Chloe Y.Y. | Pankow, James S. | Jackson, Anne U. | Gustafsson, Stefan | Zhao, Jing Hua | Ballantyne, Christie M. | Xie, Weijia | Bergman, Richard N. | Boehnke, Michael | el Bouazzaoui, Fatiha | Collins, Francis S. | Dunn, Sandra H. | Dupuis, Josee | Forouhi, Nita G. | Gillson, Christopher | Hattersley, Andrew T. | Hong, Jaeyoung | Kähönen, Mika | Kuusisto, Johanna | Kedenko, Lyudmyla | Kronenberg, Florian | Doria, Alessandro | Assimes, Themistocles L. | Ferrannini, Ele | Hansen, Torben | Hao, Ke | Häring, Hans | Knowles, Joshua W. | Lindgren, Cecilia M. | Nolan, John J. | Paananen, Jussi | Pedersen, Oluf | Quertermous, Thomas | Smith, Ulf | Lehtimäki, Terho | Liu, Ching-Ti | Loos, Ruth J.F. | McCarthy, Mark I. | Morris, Andrew D. | Vasan, Ramachandran S. | Spector, Tim D. | Teslovich, Tanya M. | Tuomilehto, Jaakko | van Dijk, Ko Willems | Viikari, Jorma S. | Zhu, Na | Langenberg, Claudia | Ingelsson, Erik | Semple, Robert K. | Sinaiko, Alan R. | Palmer, Colin N.A. | Walker, Mark | Lam, Karen S.L. | Paulweber, Bernhard | Mohlke, Karen L. | van Duijn, Cornelia | Raitakari, Olli T. | Bidulescu, Aurelian | Wareham, Nick J. | Laakso, Markku | Waterworth, Dawn M. | Lawlor, Debbie A. | Meigs, James B. | Richards, J. Brent | Frayling, Timothy M.
Diabetes  2013;62(10):3589-3598.
Adiponectin is strongly inversely associated with insulin resistance and type 2 diabetes, but its causal role remains controversial. We used a Mendelian randomization approach to test the hypothesis that adiponectin causally influences insulin resistance and type 2 diabetes. We used genetic variants at the ADIPOQ gene as instruments to calculate a regression slope between adiponectin levels and metabolic traits (up to 31,000 individuals) and a combination of instrumental variables and summary statistics–based genetic risk scores to test the associations with gold-standard measures of insulin sensitivity (2,969 individuals) and type 2 diabetes (15,960 case subjects and 64,731 control subjects). In conventional regression analyses, a 1-SD decrease in adiponectin levels was correlated with a 0.31-SD (95% CI 0.26–0.35) increase in fasting insulin, a 0.34-SD (0.30–0.38) decrease in insulin sensitivity, and a type 2 diabetes odds ratio (OR) of 1.75 (1.47–2.13). The instrumental variable analysis revealed no evidence of a causal association between genetically lower circulating adiponectin and higher fasting insulin (0.02 SD; 95% CI −0.07 to 0.11; N = 29,771), nominal evidence of a causal relationship with lower insulin sensitivity (−0.20 SD; 95% CI −0.38 to −0.02; N = 1,860), and no evidence of a relationship with type 2 diabetes (OR 0.94; 95% CI 0.75–1.19; N = 2,777 case subjects and 13,011 control subjects). Using the ADIPOQ summary statistics genetic risk scores, we found no evidence of an association between adiponectin-lowering alleles and insulin sensitivity (effect per weighted adiponectin-lowering allele: −0.03 SD; 95% CI −0.07 to 0.01; N = 2,969) or type 2 diabetes (OR per weighted adiponectin-lowering allele: 0.99; 95% CI 0.95–1.04; 15,960 case subjects vs. 64,731 control subjects). These results do not provide any consistent evidence that interventions aimed at increasing adiponectin levels will improve insulin sensitivity or risk of type 2 diabetes.
doi:10.2337/db13-0128
PMCID: PMC3781444  PMID: 23835345
4.  Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake1234 
Background: Macronutrient intake varies substantially between individuals, and there is evidence that this variation is partly accounted for by genetic variants.
Objective: The objective of the study was to identify common genetic variants that are associated with macronutrient intake.
Design: We performed 2-stage genome-wide association (GWA) meta-analysis of macronutrient intake in populations of European descent. Macronutrients were assessed by using food-frequency questionnaires and analyzed as percentages of total energy consumption from total fat, protein, and carbohydrate. From the discovery GWA (n = 38,360), 35 independent loci associated with macronutrient intake at P < 5 × 10−6 were identified and taken forward to replication in 3 additional cohorts (n = 33,533) from the DietGen Consortium. For one locus, fat mass obesity-associated protein (FTO), cohorts with Illumina MetaboChip genotype data (n = 7724) provided additional replication data.
Results: A variant in the chromosome 19 locus (rs838145) was associated with higher carbohydrate (β ± SE: 0.25 ± 0.04%; P = 1.68 × 10−8) and lower fat (β ± SE: −0.21 ± 0.04%; P = 1.57 × 10−9) consumption. A candidate gene in this region, fibroblast growth factor 21 (FGF21), encodes a fibroblast growth factor involved in glucose and lipid metabolism. The variants in this locus were associated with circulating FGF21 protein concentrations (P < 0.05) but not mRNA concentrations in blood or brain. The body mass index (BMI)–increasing allele of the FTO variant (rs1421085) was associated with higher protein intake (β ± SE: 0.10 ± 0.02%; P = 9.96 × 10−10), independent of BMI (after adjustment for BMI, β ± SE: 0.08 ± 0.02%; P = 3.15 × 10−7).
Conclusion: Our results indicate that variants in genes involved in nutrient metabolism and obesity are associated with macronutrient consumption in humans. Trials related to this study were registered at clinicaltrials.gov as NCT00005131 (Atherosclerosis Risk in Communities), NCT00005133 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetic and Environmental Determinants of Triglycerides), NCT01331512 (InCHIANTI Study), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis).
doi:10.3945/ajcn.112.052183
PMCID: PMC3652928  PMID: 23636237
5.  Discovery and Refinement of Loci Associated with Lipid Levels 
Willer, Cristen J. | Schmidt, Ellen M. | Sengupta, Sebanti | Peloso, Gina M. | Gustafsson, Stefan | Kanoni, Stavroula | Ganna, Andrea | Chen, Jin | Buchkovich, Martin L. | Mora, Samia | Beckmann, Jacques S. | Bragg-Gresham, Jennifer L. | Chang, Hsing-Yi | Demirkan, Ayşe | Den Hertog, Heleen M. | Do, Ron | Donnelly, Louise A. | Ehret, Georg B. | Esko, Tõnu | Feitosa, Mary F. | Ferreira, Teresa | Fischer, Krista | Fontanillas, Pierre | Fraser, Ross M. | Freitag, Daniel F. | Gurdasani, Deepti | Heikkilä, Kauko | Hyppönen, Elina | Isaacs, Aaron | Jackson, Anne U. | Johansson, Åsa | Johnson, Toby | Kaakinen, Marika | Kettunen, Johannes | Kleber, Marcus E. | Li, Xiaohui | Luan, Jian’an | Lyytikäinen, Leo-Pekka | Magnusson, Patrik K.E. | Mangino, Massimo | Mihailov, Evelin | Montasser, May E. | Müller-Nurasyid, Martina | Nolte, Ilja M. | O’Connell, Jeffrey R. | Palmer, Cameron D. | Perola, Markus | Petersen, Ann-Kristin | Sanna, Serena | Saxena, Richa | Service, Susan K. | Shah, Sonia | Shungin, Dmitry | Sidore, Carlo | Song, Ci | Strawbridge, Rona J. | Surakka, Ida | Tanaka, Toshiko | Teslovich, Tanya M. | Thorleifsson, Gudmar | Van den Herik, Evita G. | Voight, Benjamin F. | Volcik, Kelly A. | Waite, Lindsay L. | Wong, Andrew | Wu, Ying | Zhang, Weihua | Absher, Devin | Asiki, Gershim | Barroso, Inês | Been, Latonya F. | Bolton, Jennifer L. | Bonnycastle, Lori L | Brambilla, Paolo | Burnett, Mary S. | Cesana, Giancarlo | Dimitriou, Maria | Doney, Alex S.F. | Döring, Angela | Elliott, Paul | Epstein, Stephen E. | Ingi Eyjolfsson, Gudmundur | Gigante, Bruna | Goodarzi, Mark O. | Grallert, Harald | Gravito, Martha L. | Groves, Christopher J. | Hallmans, Göran | Hartikainen, Anna-Liisa | Hayward, Caroline | Hernandez, Dena | Hicks, Andrew A. | Holm, Hilma | Hung, Yi-Jen | Illig, Thomas | Jones, Michelle R. | Kaleebu, Pontiano | Kastelein, John J.P. | Khaw, Kay-Tee | Kim, Eric | Klopp, Norman | Komulainen, Pirjo | Kumari, Meena | Langenberg, Claudia | Lehtimäki, Terho | Lin, Shih-Yi | Lindström, Jaana | Loos, Ruth J.F. | Mach, François | McArdle, Wendy L | Meisinger, Christa | Mitchell, Braxton D. | Müller, Gabrielle | Nagaraja, Ramaiah | Narisu, Narisu | Nieminen, Tuomo V.M. | Nsubuga, Rebecca N. | Olafsson, Isleifur | Ong, Ken K. | Palotie, Aarno | Papamarkou, Theodore | Pomilla, Cristina | Pouta, Anneli | Rader, Daniel J. | Reilly, Muredach P. | Ridker, Paul M. | Rivadeneira, Fernando | Rudan, Igor | Ruokonen, Aimo | Samani, Nilesh | Scharnagl, Hubert | Seeley, Janet | Silander, Kaisa | Stančáková, Alena | Stirrups, Kathleen | Swift, Amy J. | Tiret, Laurence | Uitterlinden, Andre G. | van Pelt, L. Joost | Vedantam, Sailaja | Wainwright, Nicholas | Wijmenga, Cisca | Wild, Sarah H. | Willemsen, Gonneke | Wilsgaard, Tom | Wilson, James F. | Young, Elizabeth H. | Zhao, Jing Hua | Adair, Linda S. | Arveiler, Dominique | Assimes, Themistocles L. | Bandinelli, Stefania | Bennett, Franklyn | Bochud, Murielle | Boehm, Bernhard O. | Boomsma, Dorret I. | Borecki, Ingrid B. | Bornstein, Stefan R. | Bovet, Pascal | Burnier, Michel | Campbell, Harry | Chakravarti, Aravinda | Chambers, John C. | Chen, Yii-Der Ida | Collins, Francis S. | Cooper, Richard S. | Danesh, John | Dedoussis, George | de Faire, Ulf | Feranil, Alan B. | Ferrières, Jean | Ferrucci, Luigi | Freimer, Nelson B. | Gieger, Christian | Groop, Leif C. | Gudnason, Vilmundur | Gyllensten, Ulf | Hamsten, Anders | Harris, Tamara B. | Hingorani, Aroon | Hirschhorn, Joel N. | Hofman, Albert | Hovingh, G. Kees | Hsiung, Chao Agnes | Humphries, Steve E. | Hunt, Steven C. | Hveem, Kristian | Iribarren, Carlos | Järvelin, Marjo-Riitta | Jula, Antti | Kähönen, Mika | Kaprio, Jaakko | Kesäniemi, Antero | Kivimaki, Mika | Kooner, Jaspal S. | Koudstaal, Peter J. | Krauss, Ronald M. | Kuh, Diana | Kuusisto, Johanna | Kyvik, Kirsten O. | Laakso, Markku | Lakka, Timo A. | Lind, Lars | Lindgren, Cecilia M. | Martin, Nicholas G. | März, Winfried | McCarthy, Mark I. | McKenzie, Colin A. | Meneton, Pierre | Metspalu, Andres | Moilanen, Leena | Morris, Andrew D. | Munroe, Patricia B. | Njølstad, Inger | Pedersen, Nancy L. | Power, Chris | Pramstaller, Peter P. | Price, Jackie F. | Psaty, Bruce M. | Quertermous, Thomas | Rauramaa, Rainer | Saleheen, Danish | Salomaa, Veikko | Sanghera, Dharambir K. | Saramies, Jouko | Schwarz, Peter E.H. | Sheu, Wayne H-H | Shuldiner, Alan R. | Siegbahn, Agneta | Spector, Tim D. | Stefansson, Kari | Strachan, David P. | Tayo, Bamidele O. | Tremoli, Elena | Tuomilehto, Jaakko | Uusitupa, Matti | van Duijn, Cornelia M. | Vollenweider, Peter | Wallentin, Lars | Wareham, Nicholas J. | Whitfield, John B. | Wolffenbuttel, Bruce H.R. | Ordovas, Jose M. | Boerwinkle, Eric | Palmer, Colin N.A. | Thorsteinsdottir, Unnur | Chasman, Daniel I. | Rotter, Jerome I. | Franks, Paul W. | Ripatti, Samuli | Cupples, L. Adrienne | Sandhu, Manjinder S. | Rich, Stephen S. | Boehnke, Michael | Deloukas, Panos | Kathiresan, Sekar | Mohlke, Karen L. | Ingelsson, Erik | Abecasis, Gonçalo R.
Nature genetics  2013;45(11):10.1038/ng.2797.
Low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides, and total cholesterol are heritable, modifiable, risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,578 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5×10−8, including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian, and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipids are often associated with cardiovascular and metabolic traits including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio, and body mass index. Our results illustrate the value of genetic data from individuals of diverse ancestries and provide insights into biological mechanisms regulating blood lipids to guide future genetic, biological, and therapeutic research.
doi:10.1038/ng.2797
PMCID: PMC3838666  PMID: 24097068
6.  Common variants associated with plasma triglycerides and risk for coronary artery disease 
Do, Ron | Willer, Cristen J. | Schmidt, Ellen M. | Sengupta, Sebanti | Gao, Chi | Peloso, Gina M. | Gustafsson, Stefan | Kanoni, Stavroula | Ganna, Andrea | Chen, Jin | Buchkovich, Martin L. | Mora, Samia | Beckmann, Jacques S. | Bragg-Gresham, Jennifer L. | Chang, Hsing-Yi | Demirkan, Ayşe | Den Hertog, Heleen M. | Donnelly, Louise A. | Ehret, Georg B. | Esko, Tõnu | Feitosa, Mary F. | Ferreira, Teresa | Fischer, Krista | Fontanillas, Pierre | Fraser, Ross M. | Freitag, Daniel F. | Gurdasani, Deepti | Heikkilä, Kauko | Hyppönen, Elina | Isaacs, Aaron | Jackson, Anne U. | Johansson, Åsa | Johnson, Toby | Kaakinen, Marika | Kettunen, Johannes | Kleber, Marcus E. | Li, Xiaohui | Luan, Jian'an | Lyytikäinen, Leo-Pekka | Magnusson, Patrik K.E. | Mangino, Massimo | Mihailov, Evelin | Montasser, May E. | Müller-Nurasyid, Martina | Nolte, Ilja M. | O'Connell, Jeffrey R. | Palmer, Cameron D. | Perola, Markus | Petersen, Ann-Kristin | Sanna, Serena | Saxena, Richa | Service, Susan K. | Shah, Sonia | Shungin, Dmitry | Sidore, Carlo | Song, Ci | Strawbridge, Rona J. | Surakka, Ida | Tanaka, Toshiko | Teslovich, Tanya M. | Thorleifsson, Gudmar | Van den Herik, Evita G. | Voight, Benjamin F. | Volcik, Kelly A. | Waite, Lindsay L. | Wong, Andrew | Wu, Ying | Zhang, Weihua | Absher, Devin | Asiki, Gershim | Barroso, Inês | Been, Latonya F. | Bolton, Jennifer L. | Bonnycastle, Lori L | Brambilla, Paolo | Burnett, Mary S. | Cesana, Giancarlo | Dimitriou, Maria | Doney, Alex S.F. | Döring, Angela | Elliott, Paul | Epstein, Stephen E. | Eyjolfsson, Gudmundur Ingi | Gigante, Bruna | Goodarzi, Mark O. | Grallert, Harald | Gravito, Martha L. | Groves, Christopher J. | Hallmans, Göran | Hartikainen, Anna-Liisa | Hayward, Caroline | Hernandez, Dena | Hicks, Andrew A. | Holm, Hilma | Hung, Yi-Jen | Illig, Thomas | Jones, Michelle R. | Kaleebu, Pontiano | Kastelein, John J.P. | Khaw, Kay-Tee | Kim, Eric | Klopp, Norman | Komulainen, Pirjo | Kumari, Meena | Langenberg, Claudia | Lehtimäki, Terho | Lin, Shih-Yi | Lindström, Jaana | Loos, Ruth J.F. | Mach, François | McArdle, Wendy L | Meisinger, Christa | Mitchell, Braxton D. | Müller, Gabrielle | Nagaraja, Ramaiah | Narisu, Narisu | Nieminen, Tuomo V.M. | Nsubuga, Rebecca N. | Olafsson, Isleifur | Ong, Ken K. | Palotie, Aarno | Papamarkou, Theodore | Pomilla, Cristina | Pouta, Anneli | Rader, Daniel J. | Reilly, Muredach P. | Ridker, Paul M. | Rivadeneira, Fernando | Rudan, Igor | Ruokonen, Aimo | Samani, Nilesh | Scharnagl, Hubert | Seeley, Janet | Silander, Kaisa | Stančáková, Alena | Stirrups, Kathleen | Swift, Amy J. | Tiret, Laurence | Uitterlinden, Andre G. | van Pelt, L. Joost | Vedantam, Sailaja | Wainwright, Nicholas | Wijmenga, Cisca | Wild, Sarah H. | Willemsen, Gonneke | Wilsgaard, Tom | Wilson, James F. | Young, Elizabeth H. | Zhao, Jing Hua | Adair, Linda S. | Arveiler, Dominique | Assimes, Themistocles L. | Bandinelli, Stefania | Bennett, Franklyn | Bochud, Murielle | Boehm, Bernhard O. | Boomsma, Dorret I. | Borecki, Ingrid B. | Bornstein, Stefan R. | Bovet, Pascal | Burnier, Michel | Campbell, Harry | Chakravarti, Aravinda | Chambers, John C. | Chen, Yii-Der Ida | Collins, Francis S. | Cooper, Richard S. | Danesh, John | Dedoussis, George | de Faire, Ulf | Feranil, Alan B. | Ferrières, Jean | Ferrucci, Luigi | Freimer, Nelson B. | Gieger, Christian | Groop, Leif C. | Gudnason, Vilmundur | Gyllensten, Ulf | Hamsten, Anders | Harris, Tamara B. | Hingorani, Aroon | Hirschhorn, Joel N. | Hofman, Albert | Hovingh, G. Kees | Hsiung, Chao Agnes | Humphries, Steve E. | Hunt, Steven C. | Hveem, Kristian | Iribarren, Carlos | Järvelin, Marjo-Riitta | Jula, Antti | Kähönen, Mika | Kaprio, Jaakko | Kesäniemi, Antero | Kivimaki, Mika | Kooner, Jaspal S. | Koudstaal, Peter J. | Krauss, Ronald M. | Kuh, Diana | Kuusisto, Johanna | Kyvik, Kirsten O. | Laakso, Markku | Lakka, Timo A. | Lind, Lars | Lindgren, Cecilia M. | Martin, Nicholas G. | März, Winfried | McCarthy, Mark I. | McKenzie, Colin A. | Meneton, Pierre | Metspalu, Andres | Moilanen, Leena | Morris, Andrew D. | Munroe, Patricia B. | Njølstad, Inger | Pedersen, Nancy L. | Power, Chris | Pramstaller, Peter P. | Price, Jackie F. | Psaty, Bruce M. | Quertermous, Thomas | Rauramaa, Rainer | Saleheen, Danish | Salomaa, Veikko | Sanghera, Dharambir K. | Saramies, Jouko | Schwarz, Peter E.H. | Sheu, Wayne H-H | Shuldiner, Alan R. | Siegbahn, Agneta | Spector, Tim D. | Stefansson, Kari | Strachan, David P. | Tayo, Bamidele O. | Tremoli, Elena | Tuomilehto, Jaakko | Uusitupa, Matti | van Duijn, Cornelia M. | Vollenweider, Peter | Wallentin, Lars | Wareham, Nicholas J. | Whitfield, John B. | Wolffenbuttel, Bruce H.R. | Altshuler, David | Ordovas, Jose M. | Boerwinkle, Eric | Palmer, Colin N.A. | Thorsteinsdottir, Unnur | Chasman, Daniel I. | Rotter, Jerome I. | Franks, Paul W. | Ripatti, Samuli | Cupples, L. Adrienne | Sandhu, Manjinder S. | Rich, Stephen S. | Boehnke, Michael | Deloukas, Panos | Mohlke, Karen L. | Ingelsson, Erik | Abecasis, Goncalo R. | Daly, Mark J. | Neale, Benjamin M. | Kathiresan, Sekar
Nature genetics  2013;45(11):1345-1352.
Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiologic studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids (P<5×10−8 for each) to examine the role of triglycerides on risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglycerides, and show that the direction and magnitude of both are factors in determining CAD risk. Second, we consider loci with only a strong magnitude of association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol, a polymorphism's strength of effect on triglycerides is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD.
doi:10.1038/ng.2795
PMCID: PMC3904346  PMID: 24097064
7.  Upstream Transcription Factor 1 (USF1) allelic variants regulate lipoprotein metabolism in women and USF1 expression in atherosclerotic plaque 
Scientific Reports  2014;4:4650.
Upstream transcription factor 1 (USF1) allelic variants significantly influence future risk of cardiovascular disease and overall mortality in females. We investigated sex-specific effects of USF1 gene allelic variants on serum indices of lipoprotein metabolism, early markers of asymptomatic atherosclerosis and their changes during six years of follow-up. In addition, we investigated the cis-regulatory role of these USF1 variants in artery wall tissues in Caucasians. In the Cardiovascular Risk in Young Finns Study, 1,608 participants (56% women, aged 31.9 ± 4.9) with lipids and cIMT data were included. For functional study, whole genome mRNA expression profiling was performed in 91 histologically classified atherosclerotic samples. In females, serum total, LDL cholesterol and apoB levels increased gradually according to USF1 rs2516839 genotypes TT < CT < CC and rs1556259 AA < AG < GG as well as according to USF1 H3 (GCCCGG) copy number 0 < 1 < 2. Furthermore, the carriers of minor alleles of rs2516839 (C) and rs1556259 (G) of USF1 gene had decreased USF1 expression in atherosclerotic plaques (P = 0.028 and 0.08, respectively) as compared to non-carriers. The genetic variation in USF1 influence USF1 transcript expression in advanced atherosclerosis and regulates levels and metabolism of circulating apoB and apoB-containing lipoprotein particles in sex-dependent manner, but is not a major determinant of early markers of atherosclerosis.
doi:10.1038/srep04650
PMCID: PMC3983598  PMID: 24722012
8.  Distinct Loci in the CHRNA5/CHRNA3/CHRNB4 Gene Cluster Are Associated With Onset of Regular Smoking 
Stephens, Sarah H. | Hartz, Sarah M. | Hoft, Nicole R. | Saccone, Nancy L. | Corley, Robin C. | Hewitt, John K. | Hopfer, Christian J. | Breslau, Naomi | Coon, Hilary | Chen, Xiangning | Ducci, Francesca | Dueker, Nicole | Franceschini, Nora | Frank, Josef | Han, Younghun | Hansel, Nadia N. | Jiang, Chenhui | Korhonen, Tellervo | Lind, Penelope A. | Liu, Jason | Lyytikäinen, Leo-Pekka | Michel, Martha | Shaffer, John R. | Short, Susan E. | Sun, Juzhong | Teumer, Alexander | Thompson, John R. | Vogelzangs, Nicole | Vink, Jacqueline M. | Wenzlaff, Angela | Wheeler, William | Yang, Bao-Zhu | Aggen, Steven H. | Balmforth, Anthony J. | Baumeister, Sebastian E. | Beaty, Terri H. | Benjamin, Daniel J. | Bergen, Andrew W. | Broms, Ulla | Cesarini, David | Chatterjee, Nilanjan | Chen, Jingchun | Cheng, Yu-Ching | Cichon, Sven | Couper, David | Cucca, Francesco | Dick, Danielle | Foroud, Tatiana | Furberg, Helena | Giegling, Ina | Gillespie, Nathan A. | Gu, Fangyi | Hall, Alistair S. | Hällfors, Jenni | Han, Shizhong | Hartmann, Annette M. | Heikkilä, Kauko | Hickie, Ian B. | Hottenga, Jouke Jan | Jousilahti, Pekka | Kaakinen, Marika | Kähönen, Mika | Koellinger, Philipp D. | Kittner, Stephen | Konte, Bettina | Landi, Maria-Teresa | Laatikainen, Tiina | Leppert, Mark | Levy, Steven M. | Mathias, Rasika A. | McNeil, Daniel W. | Medland, Sarah E. | Montgomery, Grant W. | Murray, Tanda | Nauck, Matthias | North, Kari E. | Paré, Peter D. | Pergadia, Michele | Ruczinski, Ingo | Salomaa, Veikko | Viikari, Jorma | Willemsen, Gonneke | Barnes, Kathleen C. | Boerwinkle, Eric | Boomsma, Dorret I. | Caporaso, Neil | Edenberg, Howard J. | Francks, Clyde | Gelernter, Joel | Grabe, Hans Jörgen | Hops, Hyman | Jarvelin, Marjo-Riitta | Johannesson, Magnus | Kendler, Kenneth S. | Lehtimäki, Terho | Magnusson, Patrik K.E. | Marazita, Mary L. | Marchini, Jonathan | Mitchell, Braxton D. | Nöthen, Markus M. | Penninx, Brenda W. | Raitakari, Olli | Rietschel, Marcella | Rujescu, Dan | Samani, Nilesh J. | Schwartz, Ann G. | Shete, Sanjay | Spitz, Margaret | Swan, Gary E. | Völzke, Henry | Veijola, Juha | Wei, Qingyi | Amos, Chris | Cannon, Dale S. | Grucza, Richard | Hatsukami, Dorothy | Heath, Andrew | Johnson, Eric O. | Kaprio, Jaakko | Madden, Pamela | Martin, Nicholas G. | Stevens, Victoria L. | Weiss, Robert B. | Kraft, Peter | Bierut, Laura J. | Ehringer, Marissa A.
Genetic epidemiology  2013;37(8):846-859.
Neuronal nicotinic acetylcholine receptor (nAChR) genes (CHRNA5/CHRNA3/CHRNB4) have been reproducibly associated with nicotine dependence, smoking behaviors, and lung cancer risk. Of the few reports that have focused on early smoking behaviors, association results have been mixed. This meta-analysis examines early smoking phenotypes and SNPs in the gene cluster to determine: (1) whether the most robust association signal in this region (rs16969968) for other smoking behaviors is also associated with early behaviors, and/or (2) if additional statistically independent signals are important in early smoking. We focused on two phenotypes: age of tobacco initiation (AOI) and age of first regular tobacco use (AOS). This study included 56,034 subjects (41 groups) spanning nine countries and evaluated five SNPs including rs1948, rs16969968, rs578776, rs588765, and rs684513. Each dataset was analyzed using a centrally generated script. Meta-analyses were conducted from summary statistics. AOS yielded significant associations with SNPs rs578776 (beta = 0.02, P = 0.004), rs1948 (beta = 0.023, P = 0.018), and rs684513 (beta = 0.032, P = 0.017), indicating protective effects. There were no significant associations for the AOI phenotype. Importantly, rs16969968, the most replicated signal in this region for nicotine dependence, cigarettes per day, and cotinine levels, was not associated with AOI (P = 0.59) or AOS (P = 0.92). These results provide important insight into the complexity of smoking behavior phenotypes, and suggest that association signals in the CHRNA5/A3/B4 gene cluster affecting early smoking behaviors may be different from those affecting the mature nicotine dependence phenotype.
doi:10.1002/gepi.21760
PMCID: PMC3947535  PMID: 24186853
CHRNA5; CHRNA3; CHRNB4; meta-analysis; nicotine; smoke
9.  A Meta-Analysis of Genome-Wide Association Studies of the Electrocardiographic Early Repolarization Pattern 
Background
The early repolarization pattern (ERP) is common and associated with risk of sudden cardiac death. ERP is heritable and mutations have been described in syndromatic cases.
Objective
To conduct a meta-analysis of genome-wide association studies (GWAS) to identify common genetic variants influencing ERP.
Methods
We ascertained ERP based on electrocardiograms in three large community-based cohorts from Europe and the US: the Framingham Heart Study, the Health 2000 Study, and the KORA F4 Study. We analyzed GWAS in participants with and without ERP by logistic regression assuming an additive genetic model and meta-analyzed individual cohort results. We then sought to strengthen support for findings that reached p≤1×10−5 in independent individuals by direct genotyping or in-silico analysis of genome-wide data. We meta-analyzed the results from both stages.
Results
Of 7482 individuals in the discovery stage, 452 showed ERP (ERP positive: mean age 46.9±8.9 years, 30.3% women; ERP negative: 47.5±9.4 years, 54.2% women). After meta-analysis, eight single nucleotide polymorphisms reached p≤1×10−5: The most significant finding was intergenic rs11653989 (odds ratio 0.47; 95% confidence interval 0.36–0.61; p=6.9×10−9). The most biologically relevant finding was intronic to KCND3: rs17029069 (odds ratio 1.46; 95% confidence interval 1.25–1.69; p=8.5×10−7). In the replication step (7151 individuals), none of the eight variants replicated, and combined meta-analysis results failed to reach genome-wide significance.
Conclusions
In a GWAS, we were not able to reliably identify genetic variants predisposing to ERP, presumably due to insufficient statistical power and phenotype heterogeneity. The reported heritability of ERP warrants continued investigation in larger well-phenotyped populations.
doi:10.1016/j.hrthm.2012.06.008
PMCID: PMC3459269  PMID: 22683750
Early repolarization; Sudden cardiac death; Arrhythmia; GWAS; Meta-analysis; Electrocardiogram
10.  Increased Genetic Vulnerability to Smoking at CHRNA5 in Early-Onset Smokers 
Hartz, Sarah M. | Short, Susan E. | Saccone, Nancy L. | Culverhouse, Robert | Chen, LiShiun | Schwantes-An, Tae-Hwi | Coon, Hilary | Han, Younghun | Stephens, Sarah H. | Sun, Juzhong | Chen, Xiangning | Ducci, Francesca | Dueker, Nicole | Franceschini, Nora | Frank, Josef | Geller, Frank | Guđbjartsson, Daniel | Hansel, Nadia N. | Jiang, Chenhui | Keskitalo-Vuokko, Kaisu | Liu, Zhen | Lyytikäinen, Leo-Pekka | Michel, Martha | Rawal, Rajesh | Hum, Sc | Rosenberger, Albert | Scheet, Paul | Shaffer, John R. | Teumer, Alexander | Thompson, John R. | Vink, Jacqueline M. | Vogelzangs, Nicole | Wenzlaff, Angela S. | Wheeler, William | Xiao, Xiangjun | Yang, Bao-Zhu | Aggen, Steven H. | Balmforth, Anthony J. | Baumeister, Sebastian E. | Beaty, Terri | Bennett, Siiri | Bergen, Andrew W. | Boyd, Heather A. | Broms, Ulla | Campbell, Harry | Chatterjee, Nilanjan | Chen, Jingchun | Cheng, Yu-Ching | Cichon, Sven | Couper, David | Cucca, Francesco | Dick, Danielle M. | Foroud, Tatiana | Furberg, Helena | Giegling, Ina | Gu, Fangyi | Hall, Alistair S. | Hällfors, Jenni | Han, Shizhong | Hartmann, Annette M. | Hayward, Caroline | Heikkilä, Kauko | Lic, Phil | Hewitt, John K. | Hottenga, Jouke Jan | Jensen, Majken K. | Jousilahti, Pekka | Kaakinen, Marika | Kittner, Steven J. | Konte, Bettina | Korhonen, Tellervo | Landi, Maria-Teresa | Laatikainen, Tiina | Leppert, Mark | Levy, Steven M. | Mathias, Rasika A. | McNeil, Daniel W. | Medland, Sarah E. | Montgomery, Grant W. | Muley, Thomas | Murray, Tanda | Nauck, Matthias | North, Kari | Pergadia, Michele | Polasek, Ozren | Ramos, Erin M. | Ripatti, Samuli | Risch, Angela | Ruczinski, Ingo | Rudan, Igor | Salomaa, Veikko | Schlessinger, David | Styrkársdóttir, Unnur | Terracciano, Antonio | Uda, Manuela | Willemsen, Gonneke | Wu, Xifeng | Abecasis, Goncalo | Barnes, Kathleen | Bickeböller, Heike | Boerwinkle, Eric | Boomsma, Dorret I. | Caporaso, Neil | Duan, Jubao | Edenberg, Howard J. | Francks, Clyde | Gejman, Pablo V. | Gelernter, Joel | Grabe, Hans Jörgen | Hops, Hyman | Jarvelin, Marjo-Riitta | Viikari, Jorma | Kähönen, Mika | Kendler, Kenneth S. | Lehtimäki, Terho | Levinson, Douglas F. | Marazita, Mary L. | Marchini, Jonathan | Melbye, Mads | Mitchell, Braxton D. | Murray, Jeffrey C. | Nöthen, Markus M. | Penninx, Brenda W. | Raitakari, Olli | Rietschel, Marcella | Rujescu, Dan | Samani, Nilesh J. | Sanders, Alan R. | Schwartz, Ann G. | Shete, Sanjay | Shi, Jianxin | Spitz, Margaret | Stefansson, Kari | Swan, Gary E. | Thorgeirsson, Thorgeir | Völzke, Henry | Wei, Qingyi | Wichmann, H.-Erich | Amos, Christopher I. | Breslau, Naomi | Cannon, Dale S. | Ehringer, Marissa | Grucza, Richard | Hatsukami, Dorothy | Heath, Andrew | Johnson, Eric O. | Kaprio, Jaakko | Madden, Pamela | Martin, Nicholas G. | Stevens, Victoria L. | Stitzel, Jerry A. | Weiss, Robert B. | Kraft, Peter | Bierut, Laura J.
Archives of general psychiatry  2012;69(8):854-860.
Context
Recent studies have shown an association between cigarettes per day (CPD) and a nonsynonymous single-nucleotide polymorphism in CHRNA5, rs16969968.
Objective
To determine whether the association between rs16969968 and smoking is modified by age at onset of regular smoking.
Data Sources
Primary data.
Study Selection
Available genetic studies containing measures of CPD and the genotype of rs16969968 or its proxy.
Data Extraction
Uniform statistical analysis scripts were run locally. Starting with 94 050 ever-smokers from 43 studies, we extracted the heavy smokers (CPD >20) and light smokers (CPD ≤10) with age-at-onset information, reducing the sample size to 33 348. Each study was stratified into early-onset smokers (age at onset ≤16 years) and late-onset smokers (age at onset >16 years), and a logistic regression of heavy vs light smoking with the rs16969968 genotype was computed for each stratum. Meta-analysis was performed within each age-at-onset stratum.
Data Synthesis
Individuals with 1 risk allele at rs16969968 who were early-onset smokers were significantly more likely to be heavy smokers in adulthood (odds ratio [OR]=1.45; 95% CI, 1.36–1.55; n=13 843) than were carriers of the risk allele who were late-onset smokers (OR = 1.27; 95% CI, 1.21–1.33, n = 19 505) (P = .01).
Conclusion
These results highlight an increased genetic vulnerability to smoking in early-onset smokers.
doi:10.1001/archgenpsychiatry.2012.124
PMCID: PMC3482121  PMID: 22868939
11.  Seventy-five genetic loci influencing the human red blood cell 
van der Harst, Pim | Zhang, Weihua | Leach, Irene Mateo | Rendon, Augusto | Verweij, Niek | Sehmi, Joban | Paul, Dirk S. | Elling, Ulrich | Allayee, Hooman | Li, Xinzhong | Radhakrishnan, Aparna | Tan, Sian-Tsung | Voss, Katrin | Weichenberger, Christian X. | Albers, Cornelis A. | Al-Hussani, Abtehale | Asselbergs, Folkert W. | Ciullo, Marina | Danjou, Fabrice | Dina, Christian | Esko, Tõnu | Evans, David M. | Franke, Lude | Gögele, Martin | Hartiala, Jaana | Hersch, Micha | Holm, Hilma | Hottenga, Jouke-Jan | Kanoni, Stavroula | Kleber, Marcus E. | Lagou, Vasiliki | Langenberg, Claudia | Lopez, Lorna M. | Lyytikäinen, Leo-Pekka | Melander, Olle | Murgia, Federico | Nolte, Ilja M. | O’Reilly, Paul F. | Padmanabhan, Sandosh | Parsa, Afshin | Pirastu, Nicola | Porcu, Eleonora | Portas, Laura | Prokopenko, Inga | Ried, Janina S. | Shin, So-Youn | Tang, Clara S. | Teumer, Alexander | Traglia, Michela | Ulivi, Sheila | Westra, Harm-Jan | Yang, Jian | Zhao, Jing Hua | Anni, Franco | Abdellaoui, Abdel | Attwood, Antony | Balkau, Beverley | Bandinelli, Stefania | Bastardot, François | Benyamin, Beben | Boehm, Bernhard O. | Cookson, William O. | Das, Debashish | de Bakker, Paul I. W. | de Boer, Rudolf A. | de Geus, Eco J. C. | de Moor, Marleen H. | Dimitriou, Maria | Domingues, Francisco S. | Döring, Angela | Engström, Gunnar | Eyjolfsson, Gudmundur Ingi | Ferrucci, Luigi | Fischer, Krista | Galanello, Renzo | Garner, Stephen F. | Genser, Bernd | Gibson, Quince D. | Girotto, Giorgia | Gudbjartsson, Daniel Fannar | Harris, Sarah E. | Hartikainen, Anna-Liisa | Hastie, Claire E. | Hedblad, Bo | Illig, Thomas | Jolley, Jennifer | Kähönen, Mika | Kema, Ido P. | Kemp, John P. | Liang, Liming | Lloyd-Jones, Heather | Loos, Ruth J. F. | Meacham, Stuart | Medland, Sarah E. | Meisinger, Christa | Memari, Yasin | Mihailov, Evelin | Miller, Kathy | Moffatt, Miriam F. | Nauck, Matthias | Novatchkova, Maria | Nutile, Teresa | Olafsson, Isleifur | Onundarson, Pall T. | Parracciani, Debora | Penninx, Brenda W. | Perseu, Lucia | Piga, Antonio | Pistis, Giorgio | Pouta, Anneli | Puc, Ursula | Raitakari, Olli | Ring, Susan M. | Robino, Antonietta | Ruggiero, Daniela | Ruokonen, Aimo | Saint-Pierre, Aude | Sala, Cinzia | Salumets, Andres | Sambrook, Jennifer | Schepers, Hein | Schmidt, Carsten Oliver | Silljé, Herman H. W. | Sladek, Rob | Smit, Johannes H. | Starr, John M. | Stephens, Jonathan | Sulem, Patrick | Tanaka, Toshiko | Thorsteinsdottir, Unnur | Tragante, Vinicius | van Gilst, Wiek H. | van Pelt, L. Joost | van Veldhuisen, Dirk J. | Völker, Uwe | Whitfield, John B. | Willemsen, Gonneke | Winkelmann, Bernhard R. | Wirnsberger, Gerald | Algra, Ale | Cucca, Francesco | d’Adamo, Adamo Pio | Danesh, John | Deary, Ian J. | Dominiczak, Anna F. | Elliott, Paul | Fortina, Paolo | Froguel, Philippe | Gasparini, Paolo | Greinacher, Andreas | Hazen, Stanley L. | Jarvelin, Marjo-Riitta | Khaw, Kay Tee | Lehtimäki, Terho | Maerz, Winfried | Martin, Nicholas G. | Metspalu, Andres | Mitchell, Braxton D. | Montgomery, Grant W. | Moore, Carmel | Navis, Gerjan | Pirastu, Mario | Pramstaller, Peter P. | Ramirez-Solis, Ramiro | Schadt, Eric | Scott, James | Shuldiner, Alan R. | Smith, George Davey | Smith, J. Gustav | Snieder, Harold | Sorice, Rossella | Spector, Tim D. | Stefansson, Kari | Stumvoll, Michael | Wilson Tang, W. H. | Toniolo, Daniela | Tönjes, Anke | Visscher, Peter M. | Vollenweider, Peter | Wareham, Nicholas J. | Wolffenbuttel, Bruce H. R. | Boomsma, Dorret I. | Beckmann, Jacques S. | Dedoussis, George V. | Deloukas, Panos | Ferreira, Manuel A. | Sanna, Serena | Uda, Manuela | Hicks, Andrew A. | Penninger, Josef Martin | Gieger, Christian | Kooner, Jaspal S. | Ouwehand, Willem H. | Soranzo, Nicole | Chambers, John C
Nature  2012;492(7429):369-375.
Anaemia is a chief determinant of globalill health, contributing to cognitive impairment, growth retardation and impaired physical capacity. To understand further the genetic factors influencing red blood cells, we carried out a genome-wide association study of haemoglobin concentration and related parameters in up to 135,367 individuals. Here we identify 75 independent genetic loci associated with one or more red blood cell phenotypes at P <10−8, which together explain 4–9% of the phenotypic variance per trait. Using expression quantitative trait loci and bioinformatic strategies, we identify 121 candidate genes enriched in functions relevant to red blood cell biology. The candidate genes are expressed preferentially in red blood cell precursors, and 43 have haematopoietic phenotypes in Mus musculus or Drosophila melanogaster. Through open-chromatin and coding-variant analyses we identify potential causal genetic variants at 41 loci. Our findings provide extensive new insights into genetic mechanisms and biological pathways controlling red blood cell formation and function.
doi:10.1038/nature11677
PMCID: PMC3623669  PMID: 23222517
12.  Genome-wide association study identifies multiple loci influencing human serum metabolite levels 
Nature genetics  2012;44(3):269-276.
Nuclear magnetic resonance assays allow for measurement of a wide range of metabolic phenotypes. We report here the results of a GWAS on 8,330 Finnish individuals genotyped and imputed at 7.7 million SNPs for a range of 216 serum metabolic phenotypes assessed by NMR of serum samples. We identified significant associations (P < 2.31 × 10−10) at 31 loci, including 11 for which there have not been previous reports of associations to a metabolic trait or disorder. Analyses of Finnish twin pairs suggested that the metabolic measures reported here show higher heritability than comparable conventional metabolic phenotypes. In accordance with our expectations, SNPs at the 31 loci associated with individual metabolites account for a greater proportion of the genetic component of trait variance (up to 40%) than is typically observed for conventional serum metabolic phenotypes. The identification of such associations may provide substantial insight into cardiometabolic disorders.
doi:10.1038/ng.1073
PMCID: PMC3605033  PMID: 22286219
13.  Genetic Determinants of Trabecular and Cortical Volumetric Bone Mineral Densities and Bone Microstructure 
PLoS Genetics  2013;9(2):e1003247.
Most previous genetic epidemiology studies within the field of osteoporosis have focused on the genetics of the complex trait areal bone mineral density (aBMD), not being able to differentiate genetic determinants of cortical volumetric BMD (vBMD), trabecular vBMD, and bone microstructural traits. The objective of this study was to separately identify genetic determinants of these bone traits as analysed by peripheral quantitative computed tomography (pQCT). Separate GWA meta-analyses for cortical and trabecular vBMDs were performed. The cortical vBMD GWA meta-analysis (n = 5,878) followed by replication (n = 1,052) identified genetic variants in four separate loci reaching genome-wide significance (RANKL, rs1021188, p = 3.6×10−14; LOC285735, rs271170, p = 2.7×10−12; OPG, rs7839059, p = 1.2×10−10; and ESR1/C6orf97, rs6909279, p = 1.1×10−9). The trabecular vBMD GWA meta-analysis (n = 2,500) followed by replication (n = 1,022) identified one locus reaching genome-wide significance (FMN2/GREM2, rs9287237, p = 1.9×10−9). High-resolution pQCT analyses, giving information about bone microstructure, were available in a subset of the GOOD cohort (n = 729). rs1021188 was significantly associated with cortical porosity while rs9287237 was significantly associated with trabecular bone fraction. The genetic variant in the FMN2/GREM2 locus was associated with fracture risk in the MrOS Sweden cohort (HR per extra T allele 0.75, 95% confidence interval 0.60–0.93) and GREM2 expression in human osteoblasts. In conclusion, five genetic loci associated with trabecular or cortical vBMD were identified. Two of these (FMN2/GREM2 and LOC285735) are novel bone-related loci, while the other three have previously been reported to be associated with aBMD. The genetic variants associated with cortical and trabecular bone parameters differed, underscoring the complexity of the genetics of bone parameters. We propose that a genetic variant in the RANKL locus influences cortical vBMD, at least partly, via effects on cortical porosity, and that a genetic variant in the FMN2/GREM2 locus influences GREM2 expression in osteoblasts and thereby trabecular number and thickness as well as fracture risk.
Author Summary
Osteoporosis is a common highly heritable skeletal disease characterized by reduced bone mineral density (BMD) and deteriorated bone microstructure, resulting in an increased risk of fracture. Most previous genetic epidemiology studies have focused on the genetics of the complex trait BMD, not being able to separate genetic determinants of the trabecular and cortical bone compartments and bone microstructure. The trabecular and cortical BMDs can be analysed separately by computed tomography. Therefore, we performed separate genome-wide association studies for trabecular and cortical BMDs, demonstrating that the genetic determinants of cortical and trabecular BMDs differ. Genetic variants in the RANKL, LOC285735, OPG, and ESR1 loci were associated with cortical BMD, while a genetic variant in the FMN2/GREM2 locus was associated with trabecular BMD. Two of these are novel bone-related loci. Follow-up analyses of bone microstructure demonstrated that a genetic variant in the RANKL locus is associated with cortical porosity and that the FMN2/GREM2 locus is associated with trabecular number and thickness. We propose that a genetic variant in the RANKL locus influences cortical BMD via effects on cortical porosity, and that a genetic variant in the FMN2/GREM2 locus influences trabecular BMD and fracture risk via effects on both trabecular number and thickness.
doi:10.1371/journal.pgen.1003247
PMCID: PMC3578773  PMID: 23437003
14.  Novel Loci for Metabolic Networks and Multi-Tissue Expression Studies Reveal Genes for Atherosclerosis 
PLoS Genetics  2012;8(8):e1002907.
Association testing of multiple correlated phenotypes offers better power than univariate analysis of single traits. We analyzed 6,600 individuals from two population-based cohorts with both genome-wide SNP data and serum metabolomic profiles. From the observed correlation structure of 130 metabolites measured by nuclear magnetic resonance, we identified 11 metabolic networks and performed a multivariate genome-wide association analysis. We identified 34 genomic loci at genome-wide significance, of which 7 are novel. In comparison to univariate tests, multivariate association analysis identified nearly twice as many significant associations in total. Multi-tissue gene expression studies identified variants in our top loci, SERPINA1 and AQP9, as eQTLs and showed that SERPINA1 and AQP9 expression in human blood was associated with metabolites from their corresponding metabolic networks. Finally, liver expression of AQP9 was associated with atherosclerotic lesion area in mice, and in human arterial tissue both SERPINA1 and AQP9 were shown to be upregulated (6.3-fold and 4.6-fold, respectively) in atherosclerotic plaques. Our study illustrates the power of multi-phenotype GWAS and highlights candidate genes for atherosclerosis.
Author Summary
In this study, we aim to identify novel genetic variants for metabolism, characterize their effects on nearby genes, and show that the nearby genes are associated with metabolism and atherosclerosis. To discover new genetic variants, we use an alternative approach to traditional genome-wide association studies: we leverage the information in phenotype covariance to increase our statistical power. We identify variants at seven novel loci and then show that our top signals drive expression of nearby genes AQP9 and SERPINA1 in multiple tissues. We demonstrate that AQP9 and SERPINA1 gene expression, in turn, is associated with metabolite levels. Finally, we show that the genes are associated with atherosclerosis using mouse atherosclerotic lesion size (AQP9) as well as tissue from healthy human arteries and atherosclerotic plaques (AQP9 and SERPINA1). This study illustrates that multivariate analysis of correlated metabolites can boost power for gene discovery substantially. Further functional work will need to be performed to elucidate the biological role of SERPINA1 and AQP9 in atherosclerosis.
doi:10.1371/journal.pgen.1002907
PMCID: PMC3420921  PMID: 22916037
15.  Evidence of Inbreeding Depression on Human Height 
McQuillan, Ruth | Eklund, Niina | Pirastu, Nicola | Kuningas, Maris | McEvoy, Brian P. | Esko, Tõnu | Corre, Tanguy | Davies, Gail | Kaakinen, Marika | Lyytikäinen, Leo-Pekka | Kristiansson, Kati | Havulinna, Aki S. | Gögele, Martin | Vitart, Veronique | Tenesa, Albert | Aulchenko, Yurii | Hayward, Caroline | Johansson, Åsa | Boban, Mladen | Ulivi, Sheila | Robino, Antonietta | Boraska, Vesna | Igl, Wilmar | Wild, Sarah H. | Zgaga, Lina | Amin, Najaf | Theodoratou, Evropi | Polašek, Ozren | Girotto, Giorgia | Lopez, Lorna M. | Sala, Cinzia | Lahti, Jari | Laatikainen, Tiina | Prokopenko, Inga | Kals, Mart | Viikari, Jorma | Yang, Jian | Pouta, Anneli | Estrada, Karol | Hofman, Albert | Freimer, Nelson | Martin, Nicholas G. | Kähönen, Mika | Milani, Lili | Heliövaara, Markku | Vartiainen, Erkki | Räikkönen, Katri | Masciullo, Corrado | Starr, John M. | Hicks, Andrew A. | Esposito, Laura | Kolčić, Ivana | Farrington, Susan M. | Oostra, Ben | Zemunik, Tatijana | Campbell, Harry | Kirin, Mirna | Pehlic, Marina | Faletra, Flavio | Porteous, David | Pistis, Giorgio | Widén, Elisabeth | Salomaa, Veikko | Koskinen, Seppo | Fischer, Krista | Lehtimäki, Terho | Heath, Andrew | McCarthy, Mark I. | Rivadeneira, Fernando | Montgomery, Grant W. | Tiemeier, Henning | Hartikainen, Anna-Liisa | Madden, Pamela A. F. | d'Adamo, Pio | Hastie, Nicholas D. | Gyllensten, Ulf | Wright, Alan F. | van Duijn, Cornelia M. | Dunlop, Malcolm | Rudan, Igor | Gasparini, Paolo | Pramstaller, Peter P. | Deary, Ian J. | Toniolo, Daniela | Eriksson, Johan G. | Jula, Antti | Raitakari, Olli T. | Metspalu, Andres | Perola, Markus | Järvelin, Marjo-Riitta | Uitterlinden, André | Visscher, Peter M. | Wilson, James F.
PLoS Genetics  2012;8(7):e1002655.
Stature is a classical and highly heritable complex trait, with 80%–90% of variation explained by genetic factors. In recent years, genome-wide association studies (GWAS) have successfully identified many common additive variants influencing human height; however, little attention has been given to the potential role of recessive genetic effects. Here, we investigated genome-wide recessive effects by an analysis of inbreeding depression on adult height in over 35,000 people from 21 different population samples. We found a highly significant inverse association between height and genome-wide homozygosity, equivalent to a height reduction of up to 3 cm in the offspring of first cousins compared with the offspring of unrelated individuals, an effect which remained after controlling for the effects of socio-economic status, an important confounder (χ2 = 83.89, df = 1; p = 5.2×10−20). There was, however, a high degree of heterogeneity among populations: whereas the direction of the effect was consistent across most population samples, the effect size differed significantly among populations. It is likely that this reflects true biological heterogeneity: whether or not an effect can be observed will depend on both the variance in homozygosity in the population and the chance inheritance of individual recessive genotypes. These results predict that multiple, rare, recessive variants influence human height. Although this exploratory work focuses on height alone, the methodology developed is generally applicable to heritable quantitative traits (QT), paving the way for an investigation into inbreeding effects, and therefore genetic architecture, on a range of QT of biomedical importance.
Author Summary
Studies investigating the extent to which genetics influences human characteristics such as height have concentrated mainly on common variants of genes, where having one or two copies of a given variant influences the trait or risk of disease. This study explores whether a different type of genetic variant might also be important. We investigate the role of recessive genetic variants, where two identical copies of a variant are required to have an effect. By measuring genome-wide homozygosity—the phenomenon of inheriting two identical copies at a given point of the genome—in 35,000 individuals from 21 European populations, and by comparing this to individual height, we found that the more homozygous the genome, the shorter the individual. The offspring of first cousins (who have increased homozygosity) were predicted to be up to 3 cm shorter on average than the offspring of unrelated parents. Height is influenced by the combined effect of many recessive variants dispersed across the genome. This may also be true for other human characteristics and diseases, opening up a new way to understand how genetic variation influences our health.
doi:10.1371/journal.pgen.1002655
PMCID: PMC3400549  PMID: 22829771
16.  A Genome-Wide Association Meta-Analysis of Circulating Sex Hormone–Binding Globulin Reveals Multiple Loci Implicated in Sex Steroid Hormone Regulation 
Coviello, Andrea D. | Haring, Robin | Wellons, Melissa | Vaidya, Dhananjay | Lehtimäki, Terho | Keildson, Sarah | Lunetta, Kathryn L. | He, Chunyan | Fornage, Myriam | Lagou, Vasiliki | Mangino, Massimo | Onland-Moret, N. Charlotte | Chen, Brian | Eriksson, Joel | Garcia, Melissa | Liu, Yong Mei | Koster, Annemarie | Lohman, Kurt | Lyytikäinen, Leo-Pekka | Petersen, Ann-Kristin | Prescott, Jennifer | Stolk, Lisette | Vandenput, Liesbeth | Wood, Andrew R. | Zhuang, Wei Vivian | Ruokonen, Aimo | Hartikainen, Anna-Liisa | Pouta, Anneli | Bandinelli, Stefania | Biffar, Reiner | Brabant, Georg | Cox, David G. | Chen, Yuhui | Cummings, Steven | Ferrucci, Luigi | Gunter, Marc J. | Hankinson, Susan E. | Martikainen, Hannu | Hofman, Albert | Homuth, Georg | Illig, Thomas | Jansson, John-Olov | Johnson, Andrew D. | Karasik, David | Karlsson, Magnus | Kettunen, Johannes | Kiel, Douglas P. | Kraft, Peter | Liu, Jingmin | Ljunggren, Östen | Lorentzon, Mattias | Maggio, Marcello | Markus, Marcello R. P. | Mellström, Dan | Miljkovic, Iva | Mirel, Daniel | Nelson, Sarah | Morin Papunen, Laure | Peeters, Petra H. M. | Prokopenko, Inga | Raffel, Leslie | Reincke, Martin | Reiner, Alex P. | Rexrode, Kathryn | Rivadeneira, Fernando | Schwartz, Stephen M. | Siscovick, David | Soranzo, Nicole | Stöckl, Doris | Tworoger, Shelley | Uitterlinden, André G. | van Gils, Carla H. | Vasan, Ramachandran S. | Wichmann, H.-Erich | Zhai, Guangju | Bhasin, Shalender | Bidlingmaier, Martin | Chanock, Stephen J. | De Vivo, Immaculata | Harris, Tamara B. | Hunter, David J. | Kähönen, Mika | Liu, Simin | Ouyang, Pamela | Spector, Tim D. | van der Schouw, Yvonne T. | Viikari, Jorma | Wallaschofski, Henri | McCarthy, Mark I. | Frayling, Timothy M. | Murray, Anna | Franks, Steve | Järvelin, Marjo-Riitta | de Jong, Frank H. | Raitakari, Olli | Teumer, Alexander | Ohlsson, Claes | Murabito, Joanne M. | Perry, John R. B.
PLoS Genetics  2012;8(7):e1002805.
Sex hormone-binding globulin (SHBG) is a glycoprotein responsible for the transport and biologic availability of sex steroid hormones, primarily testosterone and estradiol. SHBG has been associated with chronic diseases including type 2 diabetes (T2D) and with hormone-sensitive cancers such as breast and prostate cancer. We performed a genome-wide association study (GWAS) meta-analysis of 21,791 individuals from 10 epidemiologic studies and validated these findings in 7,046 individuals in an additional six studies. We identified twelve genomic regions (SNPs) associated with circulating SHBG concentrations. Loci near the identified SNPs included SHBG (rs12150660, 17p13.1, p = 1.8×10−106), PRMT6 (rs17496332, 1p13.3, p = 1.4×10−11), GCKR (rs780093, 2p23.3, p = 2.2×10−16), ZBTB10 (rs440837, 8q21.13, p = 3.4×10−09), JMJD1C (rs7910927, 10q21.3, p = 6.1×10−35), SLCO1B1 (rs4149056, 12p12.1, p = 1.9×10−08), NR2F2 (rs8023580, 15q26.2, p = 8.3×10−12), ZNF652 (rs2411984, 17q21.32, p = 3.5×10−14), TDGF3 (rs1573036, Xq22.3, p = 4.1×10−14), LHCGR (rs10454142, 2p16.3, p = 1.3×10−07), BAIAP2L1 (rs3779195, 7q21.3, p = 2.7×10−08), and UGT2B15 (rs293428, 4q13.2, p = 5.5×10−06). These genes encompass multiple biologic pathways, including hepatic function, lipid metabolism, carbohydrate metabolism and T2D, androgen and estrogen receptor function, epigenetic effects, and the biology of sex steroid hormone-responsive cancers including breast and prostate cancer. We found evidence of sex-differentiated genetic influences on SHBG. In a sex-specific GWAS, the loci 4q13.2-UGT2B15 was significant in men only (men p = 2.5×10−08, women p = 0.66, heterogeneity p = 0.003). Additionally, three loci showed strong sex-differentiated effects: 17p13.1-SHBG and Xq22.3-TDGF3 were stronger in men, whereas 8q21.12-ZBTB10 was stronger in women. Conditional analyses identified additional signals at the SHBG gene that together almost double the proportion of variance explained at the locus. Using an independent study of 1,129 individuals, all SNPs identified in the overall or sex-differentiated or conditional analyses explained ∼15.6% and ∼8.4% of the genetic variation of SHBG concentrations in men and women, respectively. The evidence for sex-differentiated effects and allelic heterogeneity highlight the importance of considering these features when estimating complex trait variance.
Author Summary
Sex hormone-binding globulin (SHBG) is the key protein responsible for binding and transporting the sex steroid hormones, testosterone and estradiol, in the circulatory system. SHBG regulates their bioavailability and therefore their effects in the body. SHBG has been linked to chronic diseases including type 2 diabetes and to hormone-sensitive cancers such as breast and prostate cancer. SHBG concentrations are approximately 50% heritable in family studies, suggesting SHBG concentrations are under significant genetic control; yet, little is known about the specific genes that influence SHBG. We conducted a large study of the association of SHBG concentrations with markers in the human genome in ∼22,000 white men and women to determine which loci influence SHBG concentrations. Genes near the identified genomic markers in addition to the SHBG protein coding gene included PRMT6, GCKR, ZBTB10, JMJD1C, SLCO1B1, NR2F2, ZNF652, TDGF3, LHCGR, BAIAP2L1, and UGT2B15. These genes represent a wide range of biologic pathways that may relate to SHBG function and sex steroid hormone biology, including liver function, lipid metabolism, carbohydrate metabolism and type 2 diabetes, and the development and progression of sex steroid hormone-responsive cancers.
doi:10.1371/journal.pgen.1002805
PMCID: PMC3400553  PMID: 22829776
17.  WNT16 Influences Bone Mineral Density, Cortical Bone Thickness, Bone Strength, and Osteoporotic Fracture Risk 
PLoS Genetics  2012;8(7):e1002745.
We aimed to identify genetic variants associated with cortical bone thickness (CBT) and bone mineral density (BMD) by performing two separate genome-wide association study (GWAS) meta-analyses for CBT in 3 cohorts comprising 5,878 European subjects and for BMD in 5 cohorts comprising 5,672 individuals. We then assessed selected single-nucleotide polymorphisms (SNPs) for osteoporotic fracture in 2,023 cases and 3,740 controls. Association with CBT and forearm BMD was tested for ∼2.5 million SNPs in each cohort separately, and results were meta-analyzed using fixed effect meta-analysis. We identified a missense SNP (Thr>Ile; rs2707466) located in the WNT16 gene (7q31), associated with CBT (effect size of −0.11 standard deviations [SD] per C allele, P = 6.2×10−9). This SNP, as well as another nonsynonymous SNP rs2908004 (Gly>Arg), also had genome-wide significant association with forearm BMD (−0.14 SD per C allele, P = 2.3×10−12, and −0.16 SD per G allele, P = 1.2×10−15, respectively). Four genome-wide significant SNPs arising from BMD meta-analysis were tested for association with forearm fracture. SNP rs7776725 in FAM3C, a gene adjacent to WNT16, was associated with a genome-wide significant increased risk of forearm fracture (OR = 1.33, P = 7.3×10−9), with genome-wide suggestive signals from the two missense variants in WNT16 (rs2908004: OR = 1.22, P = 4.9×10−6 and rs2707466: OR = 1.22, P = 7.2×10−6). We next generated a homozygous mouse with targeted disruption of Wnt16. Female Wnt16−/− mice had 27% (P<0.001) thinner cortical bones at the femur midshaft, and bone strength measures were reduced between 43%–61% (6.5×10−13
Author Summary
Bone traits are highly dependent on genetic factors. To date, numerous genetic loci for bone mineral density (BMD) and only one locus for osteoporotic fracture have been previously identified to be genome-wide significant. Cortical bone has been reported to be an important determinant of bone strength; so far, no genome-wide association studies (GWAS) have been performed for cortical bone thickness (CBT) of the tibial and radial diaphysis or BMD at forearm, a skeletal site rich in cortical bone. Therefore, we performed two separated meta-analyses of GWAS for cortical thickness of the tibia in 3 independent cohorts of 5,878 men and women, and for forearm BMD in 5 cohorts of 5,672 individuals. We identified the 7q31 locus, which contains WNT16, to be associated with CBT and BMD. Four SNPs from this locus were then tested in 2,023 osteoporotic fracture cases and 3,740 controls. One of these SNPs was genome-wide significant, and two were genome-wide suggestive, for forearm fracture. Generating a mouse with targeted disruption of Wnt16, we also demonstrated that mice lacking this protein had substantially thinner bone cortices and reduced bone strength than their wild-type littermates. These findings highlight WNT16 as a clinically relevant member of the Wnt signaling pathway and increase our understanding of the etiology of osteoporosis-related phenotypes and fracture.
doi:10.1371/journal.pgen.1002745
PMCID: PMC3390364  PMID: 22792071
PLoS ONE  2012;7(4):e35426.
Introduction
Circulating cell-free DNA (cf-DNA) is a useful indicator of cell death, and it can also be used to predict outcomes in various clinical disorders. Several innate immune mechanisms are known to be involved in eliminating DNA and chromatin-related material as part of the inhibition of potentially harmful autoimmune responses. However, the exact molecular mechanism underlying the clearance of circulating cf-DNA is currently unclear.
Methods
To examine the mechanisms controlling serum levels of cf-DNA, we carried out a genome-wide association analysis (GWA) in a cohort of young adults (aged 24–39 years; n = 1841; 1018 women and 823 men) participating in the Cardiovascular Risk in Young Finns Study. Genotyping was performed with a custom-built Illumina Human 670 k BeadChip. The Quant-iTTM high sensitivity DNA assay was used to measure cf-DNA directly from serum.
Results
The results revealed that 110 single nucleotide polymorphisms (SNPs) were associated with serum cf-DNA with genome-wide significance (p<5×10−8). All of these significant SNPs were localised to chromosome 2q37, near the UDP-glucuronosyltransferase 1 (UGT1) family locus, and the most significant SNPs localised within the UGT1 polypeptide A1 (UGT1A1) gene region.
Conclusion
The UGT1A1 enzyme catalyses the detoxification of several drugs and the turnover of many xenobiotic and endogenous compounds by glucuronidating its substrates. These data indicate that UGT1A1-associated processes are also involved in the regulation of serum cf-DNA concentrations.
doi:10.1371/journal.pone.0035426
PMCID: PMC3325226  PMID: 22511988
Dastani, Zari | Hivert, Marie-France | Timpson, Nicholas | Perry, John R. B. | Yuan, Xin | Scott, Robert A. | Henneman, Peter | Heid, Iris M. | Kizer, Jorge R. | Lyytikäinen, Leo-Pekka | Fuchsberger, Christian | Tanaka, Toshiko | Morris, Andrew P. | Small, Kerrin | Isaacs, Aaron | Beekman, Marian | Coassin, Stefan | Lohman, Kurt | Qi, Lu | Kanoni, Stavroula | Pankow, James S. | Uh, Hae-Won | Wu, Ying | Bidulescu, Aurelian | Rasmussen-Torvik, Laura J. | Greenwood, Celia M. T. | Ladouceur, Martin | Grimsby, Jonna | Manning, Alisa K. | Liu, Ching-Ti | Kooner, Jaspal | Mooser, Vincent E. | Vollenweider, Peter | Kapur, Karen A. | Chambers, John | Wareham, Nicholas J. | Langenberg, Claudia | Frants, Rune | Willems-vanDijk, Ko | Oostra, Ben A. | Willems, Sara M. | Lamina, Claudia | Winkler, Thomas W. | Psaty, Bruce M. | Tracy, Russell P. | Brody, Jennifer | Chen, Ida | Viikari, Jorma | Kähönen, Mika | Pramstaller, Peter P. | Evans, David M. | St. Pourcain, Beate | Sattar, Naveed | Wood, Andrew R. | Bandinelli, Stefania | Carlson, Olga D. | Egan, Josephine M. | Böhringer, Stefan | van Heemst, Diana | Kedenko, Lyudmyla | Kristiansson, Kati | Nuotio, Marja-Liisa | Loo, Britt-Marie | Harris, Tamara | Garcia, Melissa | Kanaya, Alka | Haun, Margot | Klopp, Norman | Wichmann, H.-Erich | Deloukas, Panos | Katsareli, Efi | Couper, David J. | Duncan, Bruce B. | Kloppenburg, Margreet | Adair, Linda S. | Borja, Judith B. | Wilson, James G. | Musani, Solomon | Guo, Xiuqing | Johnson, Toby | Semple, Robert | Teslovich, Tanya M. | Allison, Matthew A. | Redline, Susan | Buxbaum, Sarah G. | Mohlke, Karen L. | Meulenbelt, Ingrid | Ballantyne, Christie M. | Dedoussis, George V. | Hu, Frank B. | Liu, Yongmei | Paulweber, Bernhard | Spector, Timothy D. | Slagboom, P. Eline | Ferrucci, Luigi | Jula, Antti | Perola, Markus | Raitakari, Olli | Florez, Jose C. | Salomaa, Veikko | Eriksson, Johan G. | Frayling, Timothy M. | Hicks, Andrew A. | Lehtimäki, Terho | Smith, George Davey | Siscovick, David S. | Kronenberg, Florian | van Duijn, Cornelia | Loos, Ruth J. F. | Waterworth, Dawn M. | Meigs, James B. | Dupuis, Josee | Richards, J. Brent
PLoS Genetics  2012;8(3):e1002607.
Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10−8–1.2×10−43). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p<3×10−4). We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p = 4.3×10−3, n = 22,044), increased triglycerides (p = 2.6×10−14, n = 93,440), increased waist-to-hip ratio (p = 1.8×10−5, n = 77,167), increased glucose two hours post oral glucose tolerance testing (p = 4.4×10−3, n = 15,234), increased fasting insulin (p = 0.015, n = 48,238), but with lower in HDL-cholesterol concentrations (p = 4.5×10−13, n = 96,748) and decreased BMI (p = 1.4×10−4, n = 121,335). These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.
Author Summary
Serum adiponectin levels are highly heritable and are inversely correlated with the risk of type 2 diabetes (T2D), coronary artery disease, stroke, and several metabolic traits. To identify common genetic variants associated with adiponectin levels and risk of T2D and metabolic traits, we conducted a meta-analysis of genome-wide association studies of 45,891 multi-ethnic individuals. In addition to confirming that variants at the ADIPOQ and CDH13 loci influence adiponectin levels, our analyses revealed that 10 new loci also affecting circulating adiponectin levels. We demonstrated that expression levels of several genes in these candidate regions are associated with serum adiponectin levels. Using a powerful novel method to assess the contribution of the identified variants with other traits using summary-level results from large-scale GWAS consortia, we provide evidence that the risk alleles for adiponectin are associated with deleterious changes in T2D risk and metabolic syndrome traits (triglycerides, HDL, post-prandial glucose, insulin, and waist-to-hip ratio), demonstrating that the identified loci, taken together, impact upon metabolic disease.
doi:10.1371/journal.pgen.1002607
PMCID: PMC3315470  PMID: 22479202
PLoS ONE  2012;7(1):e28931.
Background
Genome-wide association studies (GWASs) have identified a large number of variants (SNPs) associating with an increased risk of coronary artery disease (CAD). Recently, the CARDIoGRAM consortium published a GWAS based on the largest study population so far. They successfully replicated twelve already known associations and discovered thirteen new SNPs associating with CAD. We examined whether the genetic profiling of these variants improves prediction of subclinical atherosclerosis – i.e., carotid intima-media thickness (CIMT) and carotid artery elasticity (CAE) – beyond classical risk factors.
Subjects and Methods
We genotyped 24 variants found in a population of European ancestry and measured CIMT and CAE in 2001 and 2007 from 2,081, and 2,015 subjects (aged 30–45 years in 2007) respectively, participating in the Cardiovascular Risk in Young Finns Study (YFS). The Bogalusa Heart Study (BHS; n = 1179) was used as a replication cohort (mean age of 37.5). For additional replication, a sub-sample of 5 SNPs was genotyped for 1,291 individuals aged 46–76 years participating in the Health 2000 population survey. We tested the impact of genetic risk score (GRS24SNP/CAD) calculated as a weighted (by allelic odds ratios for CAD) sum of CAD risk alleles from the studied 24 variants on CIMT, CAE, the incidence of carotid atherosclerosis and the progression of CIMT and CAE during a 6-year follow-up.
Results
CIMT or CAE did not significantly associate with GRS24SNP/CAD before or after adjusting for classical CAD risk factors (p>0.05 for all) in YFS or in the BHS. CIMT and CAE associated with only one SNP each in the YFS. The findings were not replicated in the replication cohorts. In the meta-analysis CIMT or CAE did not associate with any of the SNPs.
Conclusion
Genetic profiling, by using known CAD risk variants, should not improve risk stratification for subclinical atherosclerosis beyond conventional risk factors among healthy young adults.
doi:10.1371/journal.pone.0028931
PMCID: PMC3266236  PMID: 22295058
PLoS Genetics  2011;7(10):e1002313.
Testosterone concentrations in men are associated with cardiovascular morbidity, osteoporosis, and mortality and are affected by age, smoking, and obesity. Because of serum testosterone's high heritability, we performed a meta-analysis of genome-wide association data in 8,938 men from seven cohorts and followed up the genome-wide significant findings in one in silico (n = 871) and two de novo replication cohorts (n = 4,620) to identify genetic loci significantly associated with serum testosterone concentration in men. All these loci were also associated with low serum testosterone concentration defined as <300 ng/dl. Two single-nucleotide polymorphisms at the sex hormone-binding globulin (SHBG) locus (17p13-p12) were identified as independently associated with serum testosterone concentration (rs12150660, p = 1.2×10−41 and rs6258, p = 2.3×10−22). Subjects with ≥3 risk alleles of these variants had 6.5-fold higher risk of having low serum testosterone than subjects with no risk allele. The rs5934505 polymorphism near FAM9B on the X chromosome was also associated with testosterone concentrations (p = 5.6×10−16). The rs6258 polymorphism in exon 4 of SHBG affected SHBG's affinity for binding testosterone and the measured free testosterone fraction (p<0.01). Genetic variants in the SHBG locus and on the X chromosome are associated with a substantial variation in testosterone concentrations and increased risk of low testosterone. rs6258 is the first reported SHBG polymorphism, which affects testosterone binding to SHBG and the free testosterone fraction and could therefore influence the calculation of free testosterone using law-of-mass-action equation.
Author Summary
Testosterone is the most important testicular androgen in men. Low serum testosterone concentrations are associated with cardiovascular morbidity, metabolic syndrome, type 2 diabetes mellitus, atherosclerosis, osteoporosis, sarcopenia, and increased mortality risk. Thus, there is growing evidence that serum testosterone is a valuable biomarker of men's overall health status. Studies in male twins indicate that there is a strong heritability of serum testosterone. Here we perform a large-scale genome-wide association study to examine the effects of common genetic variants on serum testosterone concentrations. By examining 14,429 men, we show that genetic variants in the sex hormone-binding globulin (SHBG) locus and on the X chromosome are associated with a substantial variation in serum testosterone concentrations and increased risk of low testosterone. The reported associations may now be used in order to better understand the functional background of recently identified disease associations related to low testosterone. Importantly, we identified the first known genetic variant, which affects SHBG's affinity for binding testosterone and the free testosterone fraction and could therefore influence the calculation of free testosterone. This finding suggests that individual-based SHBG-testosterone affinity constants are required depending on the genotype of this single-nucleotide polymorphism.
doi:10.1371/journal.pgen.1002313
PMCID: PMC3188559  PMID: 21998597
Fox, Ervin R. | Young, J. Hunter | Li, Yali | Dreisbach, Albert W. | Keating, Brendan J. | Musani, Solomon K. | Liu, Kiang | Morrison, Alanna C. | Ganesh, Santhi | Kutlar, Abdullah | Ramachandran, Vasan S. | Polak, Josef F. | Fabsitz, Richard R. | Dries, Daniel L. | Farlow, Deborah N. | Redline, Susan | Adeyemo, Adebowale | Hirschorn, Joel N. | Sun, Yan V. | Wyatt, Sharon B. | Penman, Alan D. | Palmas, Walter | Rotter, Jerome I. | Townsend, Raymond R. | Doumatey, Ayo P. | Tayo, Bamidele O. | Mosley, Thomas H. | Lyon, Helen N. | Kang, Sun J. | Rotimi, Charles N. | Cooper, Richard S. | Franceschini, Nora | Curb, J. David | Martin, Lisa W. | Eaton, Charles B. | Kardia, Sharon L.R. | Taylor, Herman A. | Caulfield, Mark J. | Ehret, Georg B. | Johnson, Toby | Chakravarti, Aravinda | Zhu, Xiaofeng | Levy, Daniel | Munroe, Patricia B. | Rice, Kenneth M. | Bochud, Murielle | Johnson, Andrew D. | Chasman, Daniel I. | Smith, Albert V. | Tobin, Martin D. | Verwoert, Germaine C. | Hwang, Shih-Jen | Pihur, Vasyl | Vollenweider, Peter | O'Reilly, Paul F. | Amin, Najaf | Bragg-Gresham, Jennifer L. | Teumer, Alexander | Glazer, Nicole L. | Launer, Lenore | Zhao, Jing Hua | Aulchenko, Yurii | Heath, Simon | Sõber, Siim | Parsa, Afshin | Luan, Jian'an | Arora, Pankaj | Dehghan, Abbas | Zhang, Feng | Lucas, Gavin | Hicks, Andrew A. | Jackson, Anne U. | Peden, John F. | Tanaka, Toshiko | Wild, Sarah H. | Rudan, Igor | Igl, Wilmar | Milaneschi, Yuri | Parker, Alex N. | Fava, Cristiano | Chambers, John C. | Kumari, Meena | JinGo, Min | van der Harst, Pim | Kao, Wen Hong Linda | Sjögren, Marketa | Vinay, D.G. | Alexander, Myriam | Tabara, Yasuharu | Shaw-Hawkins, Sue | Whincup, Peter H. | Liu, Yongmei | Shi, Gang | Kuusisto, Johanna | Seielstad, Mark | Sim, Xueling | Nguyen, Khanh-Dung Hoang | Lehtimäki, Terho | Matullo, Giuseppe | Wu, Ying | Gaunt, Tom R. | Charlotte Onland-Moret, N. | Cooper, Matthew N. | Platou, Carl G.P. | Org, Elin | Hardy, Rebecca | Dahgam, Santosh | Palmen, Jutta | Vitart, Veronique | Braund, Peter S. | Kuznetsova, Tatiana | Uiterwaal, Cuno S.P.M. | Campbell, Harry | Ludwig, Barbara | Tomaszewski, Maciej | Tzoulaki, Ioanna | Palmer, Nicholette D. | Aspelund, Thor | Garcia, Melissa | Chang, Yen-Pei C. | O'Connell, Jeffrey R. | Steinle, Nanette I. | Grobbee, Diederick E. | Arking, Dan E. | Hernandez, Dena | Najjar, Samer | McArdle, Wendy L. | Hadley, David | Brown, Morris J. | Connell, John M. | Hingorani, Aroon D. | Day, Ian N.M. | Lawlor, Debbie A. | Beilby, John P. | Lawrence, Robert W. | Clarke, Robert | Collins, Rory | Hopewell, Jemma C. | Ongen, Halit | Bis, Joshua C. | Kähönen, Mika | Viikari, Jorma | Adair, Linda S. | Lee, Nanette R. | Chen, Ming-Huei | Olden, Matthias | Pattaro, Cristian | Hoffman Bolton, Judith A. | Köttgen, Anna | Bergmann, Sven | Mooser, Vincent | Chaturvedi, Nish | Frayling, Timothy M. | Islam, Muhammad | Jafar, Tazeen H. | Erdmann, Jeanette | Kulkarni, Smita R. | Bornstein, Stefan R. | Grässler, Jürgen | Groop, Leif | Voight, Benjamin F. | Kettunen, Johannes | Howard, Philip | Taylor, Andrew | Guarrera, Simonetta | Ricceri, Fulvio | Emilsson, Valur | Plump, Andrew | Barroso, Inês | Khaw, Kay-Tee | Weder, Alan B. | Hunt, Steven C. | Bergman, Richard N. | Collins, Francis S. | Bonnycastle, Lori L. | Scott, Laura J. | Stringham, Heather M. | Peltonen, Leena | Perola, Markus | Vartiainen, Erkki | Brand, Stefan-Martin | Staessen, Jan A. | Wang, Thomas J. | Burton, Paul R. | SolerArtigas, Maria | Dong, Yanbin | Snieder, Harold | Wang, Xiaoling | Zhu, Haidong | Lohman, Kurt K. | Rudock, Megan E. | Heckbert, Susan R. | Smith, Nicholas L. | Wiggins, Kerri L. | Shriner, Daniel | Veldre, Gudrun | Viigimaa, Margus | Kinra, Sanjay | Prabhakaran, Dorairajan | Tripathy, Vikal | Langefeld, Carl D. | Rosengren, Annika | Thelle, Dag S. | MariaCorsi, Anna | Singleton, Andrew | Forrester, Terrence | Hilton, Gina | McKenzie, Colin A. | Salako, Tunde | Iwai, Naoharu | Kita, Yoshikuni | Ogihara, Toshio | Ohkubo, Takayoshi | Okamura, Tomonori | Ueshima, Hirotsugu | Umemura, Satoshi | Eyheramendy, Susana | Meitinger, Thomas | Wichmann, H.-Erich | Cho, Yoon Shin | Kim, Hyung-Lae | Lee, Jong-Young | Scott, James | Sehmi, Joban S. | Zhang, Weihua | Hedblad, Bo | Nilsson, Peter | Smith, George Davey | Wong, Andrew | Narisu, Narisu | Stančáková, Alena | Raffel, Leslie J. | Yao, Jie | Kathiresan, Sekar | O'Donnell, Chris | Schwartz, Steven M. | Arfan Ikram, M. | Longstreth, Will T. | Seshadri, Sudha | Shrine, Nick R.G. | Wain, Louise V. | Morken, Mario A. | Swift, Amy J. | Laitinen, Jaana | Prokopenko, Inga | Zitting, Paavo | Cooper, Jackie A. | Humphries, Steve E. | Danesh, John | Rasheed, Asif | Goel, Anuj | Hamsten, Anders | Watkins, Hugh | Bakker, Stephan J.L. | van Gilst, Wiek H. | Janipalli, Charles S. | Radha Mani, K. | Yajnik, Chittaranjan S. | Hofman, Albert | Mattace-Raso, Francesco U.S. | Oostra, Ben A. | Demirkan, Ayse | Isaacs, Aaron | Rivadeneira, Fernando | Lakatta, Edward G. | Orru, Marco | Scuteri, Angelo | Ala-Korpela, Mika | Kangas, Antti J. | Lyytikäinen, Leo-Pekka | Soininen, Pasi | Tukiainen, Taru | Würz, Peter | Twee-Hee Ong, Rick | Dörr, Marcus | Kroemer, Heyo K. | Völker, Uwe | Völzke, Henry | Galan, Pilar | Hercberg, Serge | Lathrop, Mark | Zelenika, Diana | Deloukas, Panos | Mangino, Massimo | Spector, Tim D. | Zhai, Guangju | Meschia, James F. | Nalls, Michael A. | Sharma, Pankaj | Terzic, Janos | Kranthi Kumar, M.J. | Denniff, Matthew | Zukowska-Szczechowska, Ewa | Wagenknecht, Lynne E. | Fowkes, Gerald R. | Charchar, Fadi J. | Schwarz, Peter E.H. | Hayward, Caroline | Guo, Xiuqing | Bots, Michiel L. | Brand, Eva | Samani, Nilesh J. | Polasek, Ozren | Talmud, Philippa J. | Nyberg, Fredrik | Kuh, Diana | Laan, Maris | Hveem, Kristian | Palmer, Lyle J. | van der Schouw, Yvonne T. | Casas, Juan P. | Mohlke, Karen L. | Vineis, Paolo | Raitakari, Olli | Wong, Tien Y. | Shyong Tai, E. | Laakso, Markku | Rao, Dabeeru C. | Harris, Tamara B. | Morris, Richard W. | Dominiczak, Anna F. | Kivimaki, Mika | Marmot, Michael G. | Miki, Tetsuro | Saleheen, Danish | Chandak, Giriraj R. | Coresh, Josef | Navis, Gerjan | Salomaa, Veikko | Han, Bok-Ghee | Kooner, Jaspal S. | Melander, Olle | Ridker, Paul M. | Bandinelli, Stefania | Gyllensten, Ulf B. | Wright, Alan F. | Wilson, James F. | Ferrucci, Luigi | Farrall, Martin | Tuomilehto, Jaakko | Pramstaller, Peter P. | Elosua, Roberto | Soranzo, Nicole | Sijbrands, Eric J.G. | Altshuler, David | Loos, Ruth J.F. | Shuldiner, Alan R. | Gieger, Christian | Meneton, Pierre | Uitterlinden, Andre G. | Wareham, Nicholas J. | Gudnason, Vilmundur | Rettig, Rainer | Uda, Manuela | Strachan, David P. | Witteman, Jacqueline C.M. | Hartikainen, Anna-Liisa | Beckmann, Jacques S. | Boerwinkle, Eric | Boehnke, Michael | Larson, Martin G. | Järvelin, Marjo-Riitta | Psaty, Bruce M. | Abecasis, Gonçalo R. | Elliott, Paul | van Duijn , Cornelia M. | Newton-Cheh, Christopher
Human Molecular Genetics  2011;20(11):2273-2284.
The prevalence of hypertension in African Americans (AAs) is higher than in other US groups; yet, few have performed genome-wide association studies (GWASs) in AA. Among people of European descent, GWASs have identified genetic variants at 13 loci that are associated with blood pressure. It is unknown if these variants confer susceptibility in people of African ancestry. Here, we examined genome-wide and candidate gene associations with systolic blood pressure (SBP) and diastolic blood pressure (DBP) using the Candidate Gene Association Resource (CARe) consortium consisting of 8591 AAs. Genotypes included genome-wide single-nucleotide polymorphism (SNP) data utilizing the Affymetrix 6.0 array with imputation to 2.5 million HapMap SNPs and candidate gene SNP data utilizing a 50K cardiovascular gene-centric array (ITMAT-Broad-CARe [IBC] array). For Affymetrix data, the strongest signal for DBP was rs10474346 (P= 3.6 × 10−8) located near GPR98 and ARRDC3. For SBP, the strongest signal was rs2258119 in C21orf91 (P= 4.7 × 10−8). The top IBC association for SBP was rs2012318 (P= 6.4 × 10−6) near SLC25A42 and for DBP was rs2523586 (P= 1.3 × 10−6) near HLA-B. None of the top variants replicated in additional AA (n = 11 882) or European-American (n = 69 899) cohorts. We replicated previously reported European-American blood pressure SNPs in our AA samples (SH2B3, P= 0.009; TBX3-TBX5, P= 0.03; and CSK-ULK3, P= 0.0004). These genetic loci represent the best evidence of genetic influences on SBP and DBP in AAs to date. More broadly, this work supports that notion that blood pressure among AAs is a trait with genetic underpinnings but also with significant complexity.
doi:10.1093/hmg/ddr092
PMCID: PMC3090190  PMID: 21378095
PLoS Genetics  2010;6(9):e1001146.
The relative contribution of genetic risk factors to the progression of subclinical atherosclerosis is poorly understood. It is likely that multiple variants are implicated in the development of atherosclerosis, but the subtle genotypic and phenotypic differences are beyond the reach of the conventional case-control designs and the statistical significance testing procedures being used in most association studies. Our objective here was to investigate whether an alternative approach—in which common disorders are treated as quantitative phenotypes that are continuously distributed over a population—can reveal predictive insights into the early atherosclerosis, as assessed using ultrasound imaging-based quantitative measurement of carotid artery intima-media thickness (IMT). Using our population-based follow-up study of atherosclerosis precursors as a basis for sampling subjects with gradually increasing IMT levels, we searched for such subsets of genetic variants and their interactions that are the most predictive of the various risk classes, rather than using exclusively those variants meeting a stringent level of statistical significance. The area under the receiver operating characteristic curve (AUC) was used to evaluate the predictive value of the variants, and cross-validation was used to assess how well the predictive models will generalize to other subsets of subjects. By means of our predictive modeling framework with machine learning-based SNP selection, we could improve the prediction of the extreme classes of atherosclerosis risk and progression over a 6-year period (average AUC 0.844 and 0.761), compared to that of using conventional cardiovascular risk factors alone (average AUC 0.741 and 0.629), or when combined with the statistically significant variants (average AUC 0.762 and 0.651). The predictive accuracy remained relatively high in an independent validation set of subjects (average decrease of 0.043). These results demonstrate that the modeling framework can utilize the “gray zone” of genetic variation in the classification of subjects with different degrees of risk of developing atherosclerosis.
Author Summary
Although cardiovascular events, such as myocardial infarction and stroke, usually occur at later ages, it is known that the atherogenic process begins much earlier in life. Detection of subclinical atherosclerosis would therefore offer the means to identify individuals who are at increased risk of developing cardiovascular events. What remains unclear is the relative contribution of genetic variation to the development of the early stages of atherosclerosis. To address this question, we searched for combinations of both genetic and clinical determinants that are the most predictive of the progression of subclinical carotid atherosclerosis in a sample of 1,027 young adults, aged between 24–39 years, from the Finnish general population (The Cardiovascular Risk in Young Finns Study). We demonstrate here, for the first time in a population-based follow-up study, a predictive relationship between individual's genotypic variation and early signs of atherosclerosis, which cannot be explained by conventional cardiovascular risk factors, such as obesity and elevated blood pressure levels. The predictive modeling framework facilitates the usability of genetic information by identifying informative panels of variants, along with conventional risk factors, which may prove to be useful in early detection and management of atherosclerosis. The clinical implications of these findings remain to be studied.
doi:10.1371/journal.pgen.1001146
PMCID: PMC2947986  PMID: 20941391
Journal of Bone and Mineral Research  2014;29(4):1015-1024.
ABSTRACT
We hypothesized that bone resorption acts to increase bone strength through stimulation of periosteal expansion. Hence, we examined whether bone resorption, as reflected by serum β‐C‐telopeptides of type I collagen (CTX), is positively associated with periosteal circumference (PC), in contrast to inverse associations with parameters related to bone remodeling such as cortical bone mineral density (BMDC). CTX and mid‐tibial peripheral quantitative computed tomography (pQCT) scans were available in 1130 adolescents (mean age 15.5 years) from the Avon Longitudinal Study of Parents and Children (ALSPAC). Analyses were adjusted for age, gender, time of sampling, tanner stage, lean mass, fat mass, and height. CTX was positively related to PC (β = 0.19 [0.13, 0.24]) (coefficient = SD change per SD increase in CTX, 95% confidence interval)] but inversely associated with BMDC (β = –0.46 [–0.52,–0.40]) and cortical thickness [β = –0.11 (–0.18, –0.03)]. CTX was positively related to bone strength as reflected by the strength‐strain index (SSI) (β = 0.09 [0.03, 0.14]). To examine the causal nature of this relationship, we then analyzed whether single‐nucleotide polymorphisms (SNPs) within key osteoclast regulatory genes, known to reduce areal/cortical BMD, conversely increase PC. Fifteen such genetic variants within or proximal to genes encoding receptor activator of NF‐κB (RANK), RANK ligand (RANKL), and osteoprotegerin (OPG) were identified by literature search. Six of the 15 alleles that were inversely related to BMD were positively related to CTX (p < 0.05 cut‐off) (n = 2379). Subsequently, we performed a meta‐analysis of associations between these SNPs and PC in ALSPAC (n = 3382), Gothenburg Osteoporosis and Obesity Determinants (GOOD) (n = 938), and the Young Finns Study (YFS) (n = 1558). Five of the 15 alleles that were inversely related to BMD were positively related to PC (p < 0.05 cut‐off). We conclude that despite having lower BMD, individuals with a genetic predisposition to higher bone resorption have greater bone size, suggesting that higher bone resorption is permissive for greater periosteal expansion. © 2014 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals, Inc. on behalf of the American Society for Bone and Mineral Research. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
doi:10.1002/jbmr.2093
PMCID: PMC4138988  PMID: 24014423
CTX; BONE RESORPTION; PERIOSTEAL EXPANSION; pQCT

Results 1-24 (24)