Search tips
Search criteria

Results 1-12 (12)

Clipboard (0)

Select a Filter Below

Year of Publication
Document Types
1.  Dilution of candidates: the case of iron-related genes in restless legs syndrome 
Restless legs syndrome (RLS) is a common multifactorial disease. Some genetic risk factors have been identified. RLS susceptibility also has been related to iron. We therefore asked whether known iron-related genes are candidates for association with RLS and, vice versa, whether known RLS-associated loci influence iron parameters in serum. RLS/control samples (n=954/1814 in the discovery step, 735/736 in replication 1, and 736/735 in replication 2) were tested for association with SNPs located within 4 Mb intervals surrounding each gene from a list of 111 iron-related genes using a discovery threshold of P=5 × 10−4. Two population cohorts (KORA F3 and F4 with together n=3447) were tested for association of six known RLS loci with iron, ferritin, transferrin, transferrin-saturation, and soluble transferrin receptor. Results were negative. None of the candidate SNPs at the iron-related gene loci was confirmed significantly. An intronic SNP, rs2576036, of KATNAL2 at 18q21.1 was significant in the first (P=0.00085) but not in the second replication step (joint nominal P-value=0.044). Especially, rs1800652 (C282Y) in the HFE gene did not associate with RLS. Moreover, SNPs at the known RLS loci did not significantly affect serum iron parameters in the KORA cohorts. In conclusion, the correlation between RLS and iron parameters in serum may be weaker than assumed. Moreover, in a general power analysis, we show that genetic effects are diluted if they are transmitted via an intermediate trait to an end-phenotype. Sample size formulas are provided for small effect sizes.
PMCID: PMC3598324  PMID: 22929029
restless legs syndrome; iron parameters; MEIS1 haplotype; power calculation; linear regression; logistic regression
2.  Development and Application of Genomic Control Methods for Genome-Wide Association Studies Using Non-Additive Models 
PLoS ONE  2013;8(12):e81431.
Genome-wide association studies (GWAS) comprise a powerful tool for mapping genes of complex traits. However, an inflation of the test statistic can occur because of population substructure or cryptic relatedness, which could cause spurious associations. If information on a large number of genetic markers is available, adjusting the analysis results by using the method of genomic control (GC) is possible. GC was originally proposed to correct the Cochran-Armitage additive trend test. For non-additive models, correction has been shown to depend on allele frequencies. Therefore, usage of GC is limited to situations where allele frequencies of null markers and candidate markers are matched.
In this work, we extended the capabilities of the GC method for non-additive models, which allows us to use null markers with arbitrary allele frequencies for GC. Analytical expressions for the inflation of a test statistic describing its dependency on allele frequency and several population parameters were obtained for recessive, dominant, and over-dominant models of inheritance. We proposed a method to estimate these required population parameters. Furthermore, we suggested a GC method based on approximation of the correction coefficient by a polynomial of allele frequency and described procedures to correct the genotypic (two degrees of freedom) test for cases when the model of inheritance is unknown. Statistical properties of the described methods were investigated using simulated and real data. We demonstrated that all considered methods were effective in controlling type 1 error in the presence of genetic substructure. The proposed GC methods can be applied to statistical tests for GWAS with various models of inheritance. All methods developed and tested in this work were implemented using R language as a part of the GenABEL package.
PMCID: PMC3864791  PMID: 24358113
3.  Human metabolic individuality in biomedical and pharmaceutical research 
Nature  2011;477(7362):10.1038/nature10354.
Genome-wide association studies (GWAS) have identified many risk loci for complex diseases, but effect sizes are typically small and information on the underlying biological processes is often lacking. Associations with metabolic traits as functional intermediates can overcome these problems and potentially inform individualized therapy. Here we report a comprehensive analysis of genotype-dependent metabolic phenotypes using a GWAS with non-targeted metabolomics. We identified 37 genetic loci associated with blood metabolite concentrations, of which 25 exhibit effect sizes that are unusually high for GWAS and account for 10-60% of metabolite levels per allele copy. Our associations provide new functional insights for many disease-related associations that have been reported in previous studies, including cardiovascular and kidney disorders, type 2 diabetes, cancer, gout, venous thromboembolism, and Crohn’s disease. Taken together our study advances our knowledge of the genetic basis of metabolic individuality in humans and generates many new hypotheses for biomedical and pharmaceutical research.
PMCID: PMC3832838  PMID: 21886157
4.  Causal and Synthetic Associations of Variants in the SERPINA Gene Cluster with Alpha1-antitrypsin Serum Levels 
PLoS Genetics  2013;9(8):e1003585.
Several infrequent genetic polymorphisms in the SERPINA1 gene are known to substantially reduce concentration of alpha1-antitrypsin (AAT) in the blood. Since low AAT serum levels fail to protect pulmonary tissue from enzymatic degradation, these polymorphisms also increase the risk for early onset chronic obstructive pulmonary disease (COPD). The role of more common SERPINA1 single nucleotide polymorphisms (SNPs) in respiratory health remains poorly understood.
We present here an agnostic investigation of genetic determinants of circulating AAT levels in a general population sample by performing a genome-wide association study (GWAS) in 1392 individuals of the SAPALDIA cohort.
Five common SNPs, defined by showing minor allele frequencies (MAFs) >5%, reached genome-wide significance, all located in the SERPINA gene cluster at 14q32.13. The top-ranking genotyped SNP rs4905179 was associated with an estimated effect of β = −0.068 g/L per minor allele (P = 1.20*10−12). But denser SERPINA1 locus genotyping in 5569 participants with subsequent stepwise conditional analysis, as well as exon-sequencing in a subsample (N = 410), suggested that AAT serum level is causally determined at this locus by rare (MAF<1%) and low-frequent (MAF 1–5%) variants only, in particular by the well-documented protein inhibitor S and Z (PI S, PI Z) variants. Replication of the association of rs4905179 with AAT serum levels in the Copenhagen City Heart Study (N = 8273) was successful (P<0.0001), as was the replication of its synthetic nature (the effect disappeared after adjusting for PI S and Z, P = 0.57). Extending the analysis to lung function revealed a more complex situation. Only in individuals with severely compromised pulmonary health (N = 397), associations of common SNPs at this locus with lung function were driven by rarer PI S or Z variants. Overall, our meta-analysis of lung function in ever-smokers does not support a functional role of common SNPs in the SERPINA gene cluster in the general population.
Author Summary
Low levels of alpha1-antitrypsin (AAT) in the blood are a well-established risk factor for accelerated loss in lung function and chronic obstructive pulmonary disease. While a few infrequent genetic polymorphisms are known to influence the serum levels of this enzyme, the role of common genetic variants has not been examined so far. The present genome-wide scan for associated variants in approximately 1400 Swiss inhabitants revealed a chromosomal locus containing the functionally established variants of AAT deficiency and variants previously associated with lung function and emphysema. We used dense genotyping of this genetic region in more than 5500 individuals and subsequent conditional analyses to unravel which of these associated variants contribute independently to the phenotype's variability. All associations of common variants could be attributed to the rarer functionally established variants, a result which was then replicated in an independent population-based Danish cohort. Hence, this locus represents a textbook example of how a large part of a trait's heritability can be hidden in infrequent genetic polymorphisms. The attempt to transfer these results to lung function furthermore suggests that effects of common variants in this genetic region in ever-smokers may also be explained by rarer variants, but only in individuals with hampered pulmonary health.
PMCID: PMC3749935  PMID: 23990791
5.  The Role of Adiposity in Cardiometabolic Traits: A Mendelian Randomization Analysis 
Fall, Tove | Hägg, Sara | Mägi, Reedik | Ploner, Alexander | Fischer, Krista | Horikoshi, Momoko | Sarin, Antti-Pekka | Thorleifsson, Gudmar | Ladenvall, Claes | Kals, Mart | Kuningas, Maris | Draisma, Harmen H. M. | Ried, Janina S. | van Zuydam, Natalie R. | Huikari, Ville | Mangino, Massimo | Sonestedt, Emily | Benyamin, Beben | Nelson, Christopher P. | Rivera, Natalia V. | Kristiansson, Kati | Shen, Huei-yi | Havulinna, Aki S. | Dehghan, Abbas | Donnelly, Louise A. | Kaakinen, Marika | Nuotio, Marja-Liisa | Robertson, Neil | de Bruijn, Renée F. A. G. | Ikram, M. Arfan | Amin, Najaf | Balmforth, Anthony J. | Braund, Peter S. | Doney, Alexander S. F. | Döring, Angela | Elliott, Paul | Esko, Tõnu | Franco, Oscar H. | Gretarsdottir, Solveig | Hartikainen, Anna-Liisa | Heikkilä, Kauko | Herzig, Karl-Heinz | Holm, Hilma | Hottenga, Jouke Jan | Hyppönen, Elina | Illig, Thomas | Isaacs, Aaron | Isomaa, Bo | Karssen, Lennart C. | Kettunen, Johannes | Koenig, Wolfgang | Kuulasmaa, Kari | Laatikainen, Tiina | Laitinen, Jaana | Lindgren, Cecilia | Lyssenko, Valeriya | Läärä, Esa | Rayner, Nigel W. | Männistö, Satu | Pouta, Anneli | Rathmann, Wolfgang | Rivadeneira, Fernando | Ruokonen, Aimo | Savolainen, Markku J. | Sijbrands, Eric J. G. | Small, Kerrin S. | Smit, Jan H. | Steinthorsdottir, Valgerdur | Syvänen, Ann-Christine | Taanila, Anja | Tobin, Martin D. | Uitterlinden, Andre G. | Willems, Sara M. | Willemsen, Gonneke | Witteman, Jacqueline | Perola, Markus | Evans, Alun | Ferrières, Jean | Virtamo, Jarmo | Kee, Frank | Tregouet, David-Alexandre | Arveiler, Dominique | Amouyel, Philippe | Ferrario, Marco M. | Brambilla, Paolo | Hall, Alistair S. | Heath, Andrew C. | Madden, Pamela A. F. | Martin, Nicholas G. | Montgomery, Grant W. | Whitfield, John B. | Jula, Antti | Knekt, Paul | Oostra, Ben | van Duijn, Cornelia M. | Penninx, Brenda W. J. H. | Davey Smith, George | Kaprio, Jaakko | Samani, Nilesh J. | Gieger, Christian | Peters, Annette | Wichmann, H.-Erich | Boomsma, Dorret I. | de Geus, Eco J. C. | Tuomi, TiinaMaija | Power, Chris | Hammond, Christopher J. | Spector, Tim D. | Lind, Lars | Orho-Melander, Marju | Palmer, Colin Neil Alexander | Morris, Andrew D. | Groop, Leif | Järvelin, Marjo-Riitta | Salomaa, Veikko | Vartiainen, Erkki | Hofman, Albert | Ripatti, Samuli | Metspalu, Andres | Thorsteinsdottir, Unnur | Stefansson, Kari | Pedersen, Nancy L. | McCarthy, Mark I. | Ingelsson, Erik | Prokopenko, Inga
PLoS Medicine  2013;10(6):e1001474.
In this study, Prokopenko and colleagues provide novel evidence for causal relationship between adiposity and heart failure and increased liver enzymes using a Mendelian randomization study design.
Please see later in the article for the Editors' Summary
The association between adiposity and cardiometabolic traits is well known from epidemiological studies. Whilst the causal relationship is clear for some of these traits, for others it is not. We aimed to determine whether adiposity is causally related to various cardiometabolic traits using the Mendelian randomization approach.
Methods and Findings
We used the adiposity-associated variant rs9939609 at the FTO locus as an instrumental variable (IV) for body mass index (BMI) in a Mendelian randomization design. Thirty-six population-based studies of individuals of European descent contributed to the analyses.
Age- and sex-adjusted regression models were fitted to test for association between (i) rs9939609 and BMI (n = 198,502), (ii) rs9939609 and 24 traits, and (iii) BMI and 24 traits. The causal effect of BMI on the outcome measures was quantified by IV estimators. The estimators were compared to the BMI–trait associations derived from the same individuals. In the IV analysis, we demonstrated novel evidence for a causal relationship between adiposity and incident heart failure (hazard ratio, 1.19 per BMI-unit increase; 95% CI, 1.03–1.39) and replicated earlier reports of a causal association with type 2 diabetes, metabolic syndrome, dyslipidemia, and hypertension (odds ratio for IV estimator, 1.1–1.4; all p<0.05). For quantitative traits, our results provide novel evidence for a causal effect of adiposity on the liver enzymes alanine aminotransferase and gamma-glutamyl transferase and confirm previous reports of a causal effect of adiposity on systolic and diastolic blood pressure, fasting insulin, 2-h post-load glucose from the oral glucose tolerance test, C-reactive protein, triglycerides, and high-density lipoprotein cholesterol levels (all p<0.05). The estimated causal effects were in agreement with traditional observational measures in all instances except for type 2 diabetes, where the causal estimate was larger than the observational estimate (p = 0.001).
We provide novel evidence for a causal relationship between adiposity and heart failure as well as between adiposity and increased liver enzymes.
Please see later in the article for the Editors' Summary
Editors' Summary
Cardiovascular disease (CVD)—disease that affects the heart and/or the blood vessels—is a major cause of illness and death worldwide. In the US, for example, coronary heart disease—a CVD in which narrowing of the heart's blood vessels by fatty deposits slows the blood supply to the heart and may eventually cause a heart attack—is the leading cause of death, and stroke—a CVD in which the brain's blood supply is interrupted—is the fourth leading cause of death. Globally, both the incidence of CVD (the number of new cases in a population every year) and its prevalence (the proportion of the population with CVD) are increasing, particularly in low- and middle-income countries. This increasing burden of CVD is occurring in parallel with a global increase in the incidence and prevalence of obesity—having an unhealthy amount of body fat (adiposity)—and of metabolic diseases—conditions such as diabetes in which metabolism (the processes that the body uses to make energy from food) is disrupted, with resulting high blood sugar and damage to the blood vessels.
Why Was This Study Done?
Epidemiological studies—investigations that record the patterns and causes of disease in populations—have reported an association between adiposity (indicated by an increased body mass index [BMI], which is calculated by dividing body weight in kilograms by height in meters squared) and cardiometabolic traits such as coronary heart disease, stroke, heart failure (a condition in which the heart is incapable of pumping sufficient amounts of blood around the body), diabetes, high blood pressure (hypertension), and high blood cholesterol (dyslipidemia). However, observational studies cannot prove that adiposity causes any particular cardiometabolic trait because overweight individuals may share other characteristics (confounding factors) that are the real causes of both obesity and the cardiometabolic disease. Moreover, it is possible that having CVD or a metabolic disease causes obesity (reverse causation). For example, individuals with heart failure cannot do much exercise, so heart failure may cause obesity rather than vice versa. Here, the researchers use “Mendelian randomization” to examine whether adiposity is causally related to various cardiometabolic traits. Because gene variants are inherited randomly, they are not prone to confounding and are free from reverse causation. It is known that a genetic variant (rs9939609) within the genome region that encodes the fat-mass- and obesity-associated gene (FTO) is associated with increased BMI. Thus, an investigation of the associations between rs9939609 and cardiometabolic traits can indicate whether obesity is causally related to these traits.
What Did the Researchers Do and Find?
The researchers analyzed the association between rs9939609 (the “instrumental variable,” or IV) and BMI, between rs9939609 and 24 cardiometabolic traits, and between BMI and the same traits using genetic and health data collected in 36 population-based studies of nearly 200,000 individuals of European descent. They then quantified the strength of the causal association between BMI and the cardiometabolic traits by calculating “IV estimators.” Higher BMI showed a causal relationship with heart failure, metabolic syndrome (a combination of medical disorders that increases the risk of developing CVD), type 2 diabetes, dyslipidemia, hypertension, increased blood levels of liver enzymes (an indicator of liver damage; some metabolic disorders involve liver damage), and several other cardiometabolic traits. All the IV estimators were similar to the BMI–cardiovascular trait associations (observational estimates) derived from the same individuals, with the exception of diabetes, where the causal estimate was higher than the observational estimate, probably because the observational estimate is based on a single BMI measurement, whereas the causal estimate considers lifetime changes in BMI.
What Do These Findings Mean?
Like all Mendelian randomization studies, the reliability of the causal associations reported here depends on several assumptions made by the researchers. Nevertheless, these findings provide support for many previously suspected and biologically plausible causal relationships, such as that between adiposity and hypertension. They also provide new insights into the causal effect of obesity on liver enzyme levels and on heart failure. In the latter case, these findings suggest that a one-unit increase in BMI might increase the incidence of heart failure by 17%. In the US, this corresponds to 113,000 additional cases of heart failure for every unit increase in BMI at the population level. Although additional studies are needed to confirm and extend these findings, these results suggest that global efforts to reduce the burden of obesity will likely also reduce the occurrence of CVD and metabolic disorders.
Additional Information
Please access these websites via the online version of this summary at
The American Heart Association provides information on all aspects of cardiovascular disease and tips on keeping the heart healthy, including weight management (in several languages); its website includes personal stories about stroke and heart attacks
The US Centers for Disease Control and Prevention has information on heart disease, stroke, and all aspects of overweight and obesity (in English and Spanish)
The UK National Health Service Choices website provides information about cardiovascular disease and obesity, including a personal story about losing weight
The World Health Organization provides information on obesity (in several languages)
The International Obesity Taskforce provides information about the global obesity epidemic
Wikipedia has a page on Mendelian randomization (note: Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
MedlinePlus provides links to other sources of information on heart disease, on vascular disease, on obesity, and on metabolic disorders (in English and Spanish)
The International Association for the Study of Obesity provides maps and information about obesity worldwide
The International Diabetes Federation has a web page that describes types, complications, and risk factors of diabetes
PMCID: PMC3692470  PMID: 23824655
6.  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.
PMCID: PMC3623669  PMID: 23222517
7.  Novel association to the proprotein convertase PCSK7 gene locus revealed by analysing soluble transferrin receptor (sTfR) levels 
Human Molecular Genetics  2010;20(5):1042-1047.
The level of body iron storage and the erythropoietic need for iron are indicated by the serum levels of ferritin and soluble transferrin receptor (sTfR), respectively. A meta-analysis of five genome-wide association studies on sTfR and ferritin revealed novel association to the PCSK7 and TMPRSS6 loci for sTfR and the HFE locus for both parameters. The PCSK7 association was the most significant (rs236918, P = 1.1 × 10E−27) suggesting that proprotein convertase 7, the gene product of PCSK7, may be involved in sTfR generation and/or iron homeostasis. Conditioning the sTfR analyses on transferrin saturation abolished the HFE signal and substantially diminished the TMPRSS6 signal while the PCSK7 association was unaffected, suggesting that the former may be mediated by transferrin saturation whereas the PCSK7-associated effect on sTfR generation appears to be more direct.
PMCID: PMC3033185  PMID: 21149283
8.  Genetic variation near IRS1 associates with reduced adiposity and an impaired metabolic profile 
Kilpeläinen, Tuomas O | Zillikens, M Carola | Stančáková, Alena | Finucane, Francis M | Ried, Janina S | Langenberg, Claudia | Zhang, Weihua | Beckmann, Jacques S | Luan, Jian’an | Vandenput, Liesbeth | Styrkarsdottir, Unnur | Zhou, Yanhua | Smith, Albert Vernon | Zhao, Jing-Hua | Amin, Najaf | Vedantam, Sailaja | Shin, So Youn | Haritunians, Talin | Fu, Mao | Feitosa, Mary F | Kumari, Meena | Halldorsson, Bjarni V | Tikkanen, Emmi | Mangino, Massimo | Hayward, Caroline | Song, Ci | Arnold, Alice M | Aulchenko, Yurii S | Oostra, Ben A | Campbell, Harry | Cupples, L Adrienne | Davis, Kathryn E | Döring, Angela | Eiriksdottir, Gudny | Estrada, Karol | Fernández-Real, José Manuel | Garcia, Melissa | Gieger, Christian | Glazer, Nicole L | Guiducci, Candace | Hofman, Albert | Humphries, Steve E | Isomaa, Bo | Jacobs, Leonie C | Jula, Antti | Karasik, David | Karlsson, Magnus K | Khaw, Kay-Tee | Kim, Lauren J | Kivimäki, Mika | Klopp, Norman | Kühnel, Brigitte | Kuusisto, Johanna | Liu, Yongmei | Ljunggren, Östen | Lorentzon, Mattias | Luben, Robert N | McKnight, Barbara | Mellström, Dan | Mitchell, Braxton D | Mooser, Vincent | Moreno, José Maria | Männistö, Satu | O’Connell, Jeffery R | Pascoe, Laura | Peltonen, Leena | Peral, Belén | Perola, Markus | Psaty, Bruce M | Salomaa, Veikko | Savage, David B | Semple, Robert K | Skaric-Juric, Tatjana | Sigurdsson, Gunnar | Song, Kijoung S | Spector, Timothy D | Syvänen, Ann-Christine | Talmud, Philippa J | Thorleifsson, Gudmar | Thorsteinsdottir, Unnur | Uitterlinden, André G | van Duijn, Cornelia M | Vidal-Puig, Antonio | Wild, Sarah H | Wright, Alan F | Clegg, Deborah J | Schadt, Eric | Wilson, James F | Rudan, Igor | Ripatti, Samuli | Borecki, Ingrid B | Shuldiner, Alan R | Ingelsson, Erik | Jansson, John-Olov | Kaplan, Robert C | Gudnason, Vilmundur | Harris, Tamara B | Groop, Leif | Kiel, Douglas P | Rivadeneira, Fernando | Walker, Mark | Barroso, Inês | Vollenweider, Peter | Waeber, Gérard | Chambers, John C | Kooner, Jaspal S | Soranzo, Nicole | Hirschhorn, Joel N | Stefansson, Kari | Wichmann, H-Erich | Ohlsson, Claes | O’Rahilly, Stephen | Wareham, Nicholas J | Speliotes, Elizabeth K | Fox, Caroline S | Laakso, Markku | Loos, Ruth J F
Nature Genetics  2011;43(8):753-760.
Genome-wide association studies have identified 32 loci associated with body mass index (BMI), a measure that does not allow distinguishing lean from fat mass. To identify adiposity loci, we meta-analyzed associations between ~2.5 million SNPs and body fat percentage from 36,626 individuals, and followed up the 14 most significant (P<10−6) independent loci in 39,576 individuals. We confirmed the previously established adiposity locus in FTO (P=3×10−26), and identified two new loci associated with body fat percentage, one near IRS1 (P=4×10−11) and one near SPRY2 (P=3×10−8). Both loci harbour genes with a potential link to adipocyte physiology, of which the locus near IRS1 shows an intriguing association pattern. The body-fat-decreasing allele associates with decreased IRS1 expression and with an impaired metabolic profile, including decreased subcutaneous-to-visceral fat ratio, increased insulin resistance, dyslipidemia, risk of diabetes and coronary artery disease, and decreased adiponectin levels. Our findings provide new insights into adiposity and insulin resistance.
PMCID: PMC3262230  PMID: 21706003
9.  A Genome-Wide Screen for Interactions Reveals a New Locus on 4p15 Modifying the Effect of Waist-to-Hip Ratio on Total Cholesterol 
Surakka, Ida | Isaacs, Aaron | Karssen, Lennart C. | Laurila, Pirkka-Pekka P. | Middelberg, Rita P. S. | Tikkanen, Emmi | Ried, Janina S. | Lamina, Claudia | Mangino, Massimo | Igl, Wilmar | Hottenga, Jouke-Jan | Lagou, Vasiliki | van der Harst, Pim | Mateo Leach, Irene | Esko, Tõnu | Kutalik, Zoltán | Wainwright, Nicholas W. | Struchalin, Maksim V. | Sarin, Antti-Pekka | Kangas, Antti J. | Viikari, Jorma S. | Perola, Markus | Rantanen, Taina | Petersen, Ann-Kristin | Soininen, Pasi | Johansson, Åsa | Soranzo, Nicole | Heath, Andrew C. | Papamarkou, Theodore | Prokopenko, Inga | Tönjes, Anke | Kronenberg, Florian | Döring, Angela | Rivadeneira, Fernando | Montgomery, Grant W. | Whitfield, John B. | Kähönen, Mika | Lehtimäki, Terho | Freimer, Nelson B. | Willemsen, Gonneke | de Geus, Eco J. C. | Palotie, Aarno | Sandhu, Manj S. | Waterworth, Dawn M. | Metspalu, Andres | Stumvoll, Michael | Uitterlinden, André G. | Jula, Antti | Navis, Gerjan | Wijmenga, Cisca | Wolffenbuttel, Bruce H. R. | Taskinen, Marja-Riitta | Ala-Korpela, Mika | Kaprio, Jaakko | Kyvik, Kirsten O. | Boomsma, Dorret I. | Pedersen, Nancy L. | Gyllensten, Ulf | Wilson, James F. | Rudan, Igor | Campbell, Harry | Pramstaller, Peter P. | Spector, Tim D. | Witteman, Jacqueline C. M. | Eriksson, Johan G. | Salomaa, Veikko | Oostra, Ben A. | Raitakari, Olli T. | Wichmann, H.-Erich | Gieger, Christian | Järvelin, Marjo-Riitta | Martin, Nicholas G. | Hofman, Albert | McCarthy, Mark I. | Peltonen, Leena | van Duijn, Cornelia M. | Aulchenko, Yurii S. | Ripatti, Samuli
PLoS Genetics  2011;7(10):e1002333.
Recent genome-wide association (GWA) studies described 95 loci controlling serum lipid levels. These common variants explain ∼25% of the heritability of the phenotypes. To date, no unbiased screen for gene–environment interactions for circulating lipids has been reported. We screened for variants that modify the relationship between known epidemiological risk factors and circulating lipid levels in a meta-analysis of genome-wide association (GWA) data from 18 population-based cohorts with European ancestry (maximum N = 32,225). We collected 8 further cohorts (N = 17,102) for replication, and rs6448771 on 4p15 demonstrated genome-wide significant interaction with waist-to-hip-ratio (WHR) on total cholesterol (TC) with a combined P-value of 4.79×10−9. There were two potential candidate genes in the region, PCDH7 and CCKAR, with differential expression levels for rs6448771 genotypes in adipose tissue. The effect of WHR on TC was strongest for individuals carrying two copies of G allele, for whom a one standard deviation (sd) difference in WHR corresponds to 0.19 sd difference in TC concentration, while for A allele homozygous the difference was 0.12 sd. Our findings may open up possibilities for targeted intervention strategies for people characterized by specific genomic profiles. However, more refined measures of both body-fat distribution and metabolic measures are needed to understand how their joint dynamics are modified by the newly found locus.
Author Summary
Circulating serum lipids contribute greatly to the global health by affecting the risk for cardiovascular diseases. Serum lipid levels are partly inherited, and already 95 loci affecting high- and low-density lipoprotein cholesterol, total cholesterol, and triglycerides have been found. Serum lipids are also known to be affected by multiple epidemiological risk factors like body composition, lifestyle, and sex. It has been hypothesized that there are loci modifying the effects between risk factors and serum lipids, but to date only candidate gene studies for interactions have been reported. We conducted a genome-wide screen with meta-analysis approach to identify loci having interactions with epidemiological risk factors on serum lipids with over 30,000 population-based samples. When combining results from our initial datasets and 8 additional replication cohorts (maximum N = 17,102), we found a genome-wide significant locus in chromosome 4p15 with a joint P-value of 4.79×10−9 modifying the effect of waist-to-hip ratio on total cholesterol. In the area surrounding this genetic variant, there were two genes having association between the genotypes and the gene expression in adipose tissue, and we also found enrichment of association in genes belonging to lipid metabolism related functions.
PMCID: PMC3197672  PMID: 22028671
10.  Discovery of Sexual Dimorphisms in Metabolic and Genetic Biomarkers 
PLoS Genetics  2011;7(8):e1002215.
Metabolomic profiling and the integration of whole-genome genetic association data has proven to be a powerful tool to comprehensively explore gene regulatory networks and to investigate the effects of genetic variation at the molecular level. Serum metabolite concentrations allow a direct readout of biological processes, and association of specific metabolomic signatures with complex diseases such as Alzheimer's disease and cardiovascular and metabolic disorders has been shown. There are well-known correlations between sex and the incidence, prevalence, age of onset, symptoms, and severity of a disease, as well as the reaction to drugs. However, most of the studies published so far did not consider the role of sexual dimorphism and did not analyse their data stratified by gender. This study investigated sex-specific differences of serum metabolite concentrations and their underlying genetic determination. For discovery and replication we used more than 3,300 independent individuals from KORA F3 and F4 with metabolite measurements of 131 metabolites, including amino acids, phosphatidylcholines, sphingomyelins, acylcarnitines, and C6-sugars. A linear regression approach revealed significant concentration differences between males and females for 102 out of 131 metabolites (p-values<3.8×10−4; Bonferroni-corrected threshold). Sex-specific genome-wide association studies (GWAS) showed genome-wide significant differences in beta-estimates for SNPs in the CPS1 locus (carbamoyl-phosphate synthase 1, significance level: p<3.8×10−10; Bonferroni-corrected threshold) for glycine. We showed that the metabolite profiles of males and females are significantly different and, furthermore, that specific genetic variants in metabolism-related genes depict sexual dimorphism. Our study provides new important insights into sex-specific differences of cell regulatory processes and underscores that studies should consider sex-specific effects in design and interpretation.
Author Summary
The combination of genomic and metabolic studies during the last years has provided astonishing results. However, most of the studies published so far did not consider the role of sexual dimorphism and did not analyse their data stratified by sex. The investigation of 131 serum metabolite concentrations of >3,300 population-based samples (KORA F3/F4) revealed significant differences in the metabolite profile of males and females. Furthermore, a genome-wide picture of sex-specific genetic variations in human metabolism (>2,000 subjects from KORA F3/F4 cohorts) was investigated. Sex-specific genome-wide association studies (GWAS) showed differences in the effect of genetic variations on metabolites in men and women. SNPs in the CPS1 (carbamoyl-phosphate synthase 1) locus showed genome-wide significant differences in beta-estimates of sex-specific association analysis (significance level: 3.8×10−10) for glycine. As global metabolomic techniques are more and more refined to identify more compounds in single biological samples, the predictive power of this new technology will greatly increase. This suggests that metabolites, which may be used as predictive biomarkers to indicate the presence or severity of a disease, have to be used selectively depending on sex.
PMCID: PMC3154959  PMID: 21852955
11.  Genome-Wide Association Study Identifies Two Novel Regions at 11p15.5-p13 and 1p31 with Major Impact on Acute-Phase Serum Amyloid A 
PLoS Genetics  2010;6(11):e1001213.
Elevated levels of acute-phase serum amyloid A (A-SAA) cause amyloidosis and are a risk factor for atherosclerosis and its clinical complications, type 2 diabetes, as well as various malignancies. To investigate the genetic basis of A-SAA levels, we conducted the first genome-wide association study on baseline A-SAA concentrations in three population-based studies (KORA, TwinsUK, Sorbs) and one prospective case cohort study (LURIC), including a total of 4,212 participants of European descent, and identified two novel genetic susceptibility regions at 11p15.5-p13 and 1p31. The region at 11p15.5-p13 (rs4150642; p = 3.20×10−111) contains serum amyloid A1 (SAA1) and the adjacent general transcription factor 2 H1 (GTF2H1), Hermansky-Pudlak Syndrome 5 (HPS5), lactate dehydrogenase A (LDHA), and lactate dehydrogenase C (LDHC). This region explains 10.84% of the total variation of A-SAA levels in our data, which makes up 18.37% of the total estimated heritability. The second region encloses the leptin receptor (LEPR) gene at 1p31 (rs12753193; p = 1.22×10−11) and has been found to be associated with CRP and fibrinogen in previous studies. Our findings demonstrate a key role of the 11p15.5-p13 region in the regulation of baseline A-SAA levels and provide confirmative evidence of the importance of the 1p31 region for inflammatory processes and the close interplay between A-SAA, leptin, and other acute-phase proteins.
Author Summary
An elevated level of acute-phase serum amyloid A (A-SAA), a sensitive marker of the acute inflammatory state with high heritability estimates, causes amyloidosis and is a risk factor for atherosclerosis and its clinical complications, type 2 diabetes, as well as various malignancies. This study describes the first genome-wide association study on baseline A-SAA concentrations. In a meta-analysis of four genome-wide scans totalling 4,212 participants of European descent, we identified two novel genetic susceptibility regions on chromosomes 11 and 1 to be associated with baseline A-SAA concentrations. The chromosome 11 region contains the serum amyloid A1 gene and the adjacent genes and explains a high percentage of the total estimated heritability. The chromosome 1 region is a known genetic susceptibility region for inflammation. Taken together, we identified one region, which seems to be of key importance in the regulation of A-SAA levels and represents a novel potential target for the investigation of related clinical entities. In addition, our findings indicate a close interplay between A-SAA and other inflammatory proteins, as well as a larger role of a known genetic susceptibility region for inflammatory processes as it has been assumed in the past.
PMCID: PMC2987930  PMID: 21124955
12.  Genome-Wide Association Studies of Serum Magnesium, Potassium, and Sodium Concentrations Identify Six Loci Influencing Serum Magnesium Levels 
PLoS Genetics  2010;6(8):e1001045.
Magnesium, potassium, and sodium, cations commonly measured in serum, are involved in many physiological processes including energy metabolism, nerve and muscle function, signal transduction, and fluid and blood pressure regulation. To evaluate the contribution of common genetic variation to normal physiologic variation in serum concentrations of these cations, we conducted genome-wide association studies of serum magnesium, potassium, and sodium concentrations using ∼2.5 million genotyped and imputed common single nucleotide polymorphisms (SNPs) in 15,366 participants of European descent from the international CHARGE Consortium. Study-specific results were combined using fixed-effects inverse-variance weighted meta-analysis. SNPs demonstrating genome-wide significant (p<5×10−8) or suggestive associations (p<4×10−7) were evaluated for replication in an additional 8,463 subjects of European descent. The association of common variants at six genomic regions (in or near MUC1, ATP2B1, DCDC5, TRPM6, SHROOM3, and MDS1) with serum magnesium levels was genome-wide significant when meta-analyzed with the replication dataset. All initially significant SNPs from the CHARGE Consortium showed nominal association with clinically defined hypomagnesemia, two showed association with kidney function, two with bone mineral density, and one of these also associated with fasting glucose levels. Common variants in CNNM2, a magnesium transporter studied only in model systems to date, as well as in CNNM3 and CNNM4, were also associated with magnesium concentrations in this study. We observed no associations with serum sodium or potassium levels exceeding p<4×10−7. Follow-up studies of newly implicated genomic loci may provide additional insights into the regulation and homeostasis of human serum magnesium levels.
Author Summary
Magnesium, potassium, and sodium are involved in important physiological processes. To better understand how common genetic variation may contribute to inter-individual differences in serum concentrations of these electrolytes, we evaluated single nucleotide polymorphisms (SNPs) across the genome in association with serum magnesium, potassium, and sodium levels in 15,366 participants of European descent from the CHARGE Consortium. We then verified the associations in an additional 8,463 study participants. Six different genomic regions contain variants that are reproducibly associated with serum magnesium levels, and only one of the regions had been previously known to influence serum magnesium concentrations in humans. The identified SNPs also show association with clinically defined hypomagnesemia, and some of them with traits that have been linked to serum magnesium levels, including kidney function, fasting glucose, and bone mineral density. We further provide evidence for a physiological role of magnesium transporters in humans which have previously only been studied in model systems. None of the SNPs evaluated in our study are significantly associated with serum levels of sodium or potassium. Additional studies are needed to investigate the underlying molecular mechanisms in order to help us understand the contribution of these newly identified regions to magnesium homeostasis.
PMCID: PMC2916845  PMID: 20700443

Results 1-12 (12)