PMCC PMCC

Search tips
Search criteria

Advanced
Results 1-25 (159)
 

Clipboard (0)
None

Select a Filter Below

Journals
more »
Year of Publication
author:("loukas, Panos")
1.  Allelic expression mapping across cellular lineages to establish impact of non-coding SNPs 
Molecular Systems Biology  2014;10(10):1-15.
Most complex disease-associated genetic variants are located in non-coding regions and are therefore thought to be regulatory in nature. Association mapping of differential allelic expression (AE) is a powerful method to identify SNPs with direct cis-regulatory impact (cis-rSNPs). We used AE mapping to identify cis-rSNPs regulating gene expression in 55 and 63 HapMap lymphoblastoid cell lines from a Caucasian and an African population, respectively, 70 fibroblast cell lines, and 188 purified monocyte samples and found 40–60% of these cis-rSNPs to be shared across cell types. We uncover a new class of cis-rSNPs, which disrupt footprint-derived de novo motifs that are predominantly bound by repressive factors and are implicated in disease susceptibility through overlaps with GWAS SNPs. Finally, we provide the proof-of-principle for a new approach for genome-wide functional validation of transcription factor–SNP interactions. By perturbing NFκB action in lymphoblasts, we identified 489 cis-regulated transcripts with altered AE after NFκB perturbation. Altogether, we perform a comprehensive analysis of cis-variation in four cell populations and provide new tools for the identification of functional variants associated to complex diseases.
doi:10.15252/msb.20145114
PMCID: PMC4299376  PMID: 25326100
allelic expression; cis-rSNPs; complex disease; NFκB; repressor
2.  Epigenome-Wide DNA Methylation in Hearing Ability: New Mechanisms for an Old Problem 
PLoS ONE  2014;9(9):e105729.
Epigenetic regulation of gene expression has been shown to change over time and may be associated with environmental exposures in common complex traits. Age-related hearing impairment is a complex disorder, known to be heritable, with heritability estimates of 57–70%. Epigenetic regulation might explain the observed difference in age of onset and magnitude of hearing impairment with age. Epigenetic epidemiology studies using unrelated samples can be limited in their ability to detect small effects, and recent epigenetic findings in twins underscore the power of this well matched study design. We investigated the association between venous blood DNA methylation epigenome-wide and hearing ability. Pure-tone audiometry (PTA) and Illumina HumanMethylation array data were obtained from female twin volunteers enrolled in the TwinsUK register. Two study groups were explored: first, an epigenome-wide association scan (EWAS) was performed in a discovery sample (n = 115 subjects, age range: 47–83 years, Illumina 27 k array), then replication of the top ten associated probes from the discovery EWAS was attempted in a second unrelated sample (n = 203, age range: 41–86 years, Illumina 450 k array). Finally, a set of monozygotic (MZ) twin pairs (n = 21 pairs) within the discovery sample (Illumina 27 k array) was investigated in more detail in an MZ discordance analysis. Hearing ability was strongly associated with DNA methylation levels in the promoter regions of several genes, including TCF25 (cg01161216, p = 6.6×10−6), FGFR1 (cg15791248, p = 5.7×10−5) and POLE (cg18877514, p = 6.3×10−5). Replication of these results in a second sample confirmed the presence of differential methylation at TCF25 (p(replication) = 6×10−5) and POLE (p(replication) = 0.016). In the MZ discordance analysis, twins' intrapair difference in hearing ability correlated with DNA methylation differences at ACP6 (cg01377755, r = −0.75, p = 1.2×10−4) and MEF2D (cg08156349, r = −0.75, p = 1.4×10−4). Examination of gene expression in skin, suggests an influence of differential methylation on expression, which may account for the variation in hearing ability with age.
doi:10.1371/journal.pone.0105729
PMCID: PMC4153547  PMID: 25184702
3.  Genetic variants associated with warfarin dose in African-American individuals: a genome-wide association study 
Lancet  2013;382(9894):790-796.
Summary
Background
VKORC1 and CYP2C9 are important contributors to warfarin dose variability, but explain less variability for individuals of African descent than for those of European or Asian descent. We aimed to identify additional variants contributing to warfarin dose requirements in African Americans.
Methods
We did a genome-wide association study of discovery and replication cohorts. Samples from African-American adults (aged ≥18 years) who were taking a stable maintenance dose of warfarin were obtained at International Warfarin Pharmacogenetics Consortium (IWPC) sites and the University of Alabama at Birmingham (Birmingham, AL, USA). Patients enrolled at IWPC sites but who were not used for discovery made up the independent replication cohort. All participants were genotyped. We did a stepwise conditional analysis, conditioning first for VKORC1 −1639G→A, followed by the composite genotype of CYP2C9*2 and CYP2C9*3. We prespecified a genome-wide significance threshold of p<5×10−8 in the discovery cohort and p<0·0038 in the replication cohort.
Findings
The discovery cohort contained 533 participants and the replication cohort 432 participants. After the prespecified conditioning in the discovery cohort, we identified an association between a novel single nucleotide polymorphism in the CYP2C cluster on chromosome 10 (rs12777823) and warfarin dose requirement that reached genome-wide significance (p=1·51×10−8). This association was confirmed in the replication cohort (p=5·04×10−5); analysis of the two cohorts together produced a p value of 4·5×10−12. Individuals heterozygous for the rs12777823 A allele need a dose reduction of 6·92 mg/week and those homozygous 9·34 mg/week. Regression analysis showed that the inclusion of rs12777823 significantly improves warfarin dose variability explained by the IWPC dosing algorithm (21% relative improvement).
Interpretation
A novel CYP2C single nucleotide polymorphism exerts a clinically relevant effect on warfarin dose in African Americans, independent of CYP2C9*2 and CYP2C9*3. Incorporation of this variant into pharmacogenetic dosing algorithms could improve warfarin dose prediction in this population.
Funding
National Institutes of Health, American Heart Association, Howard Hughes Medical Institute, Wisconsin Network for Health Research, and the Wellcome Trust.
doi:10.1016/S0140-6736(13)60681-9
PMCID: PMC3759580  PMID: 23755828
4.  Whole-exome sequencing in an extended family with myocardial infarction unmasks familial hypercholesterolemia 
Background
Familial hypercholesterolemia (FH) is an autosomal-dominant disease leading to markedly elevated low-density lipoprotein (LDL) cholesterol levels and increased risk for premature myocardial infarction (MI). Mutation carriers display variable LDL cholesterol levels, which may obscure the diagnosis. We examined by whole-exome sequencing a family in which multiple myocardial infarctions occurred at a young age with unclear etiology.
Methods
Whole-exome sequencing of three affected family members, validation of the identified variant with Sanger-sequencing, and subsequent co-segregation analysis in the family.
Results
The index patient (LDL cholesterol 188 mg/dL) was referred for molecular-genetic investigations. He had coronary artery bypass graft (CABG) at the age of 59 years; 12 out of 15 1st, 2nd and 3rd degree relatives were affected with coronary artery disease (CAD) and/or premature myocardial infarction (MI). We sequenced the whole-exome of the patient and two cousins with premature MI. After filtering, we were left with a potentially disease causing variant in the LDL receptor (LDLR) gene, which we validated by Sanger-sequencing (nucleotide substitution in the acceptor splice-site of exon 10, c.1359-1G > A). Sequencing of all family members available for genetic analysis revealed co-segregation of the variant with CAD (LOD 3.0) and increased LDLC (>190 mg/dL), following correction for statin treatment (LOD 4.3). Interestingly, mutation carriers presented with highly variable corrected (183–354 mg/dL) and on-treatment LDL levels (116–274 mg/dL) such that the diagnosis of FH in this family was made only after the molecular-genetic analysis.
Conclusion
Even in families with unusual clustering of CAD FH remains to be underdiagnosed, which underscores the need for implementation of systematic screening programs. Whole-exome sequencing may facilitate identification of disease-causing variants in families with unclear etiology of MI and enable preventive treatment of mutation carriers in a more timely fashion.
doi:10.1186/1471-2261-14-108
PMCID: PMC4243586  PMID: 25154303
Familial hypercholesterolemia; Myocardial infarction; Whole-exome sequencing
6.  Single Nucleotide Polymorphisms with Cis-Regulatory Effects on Long Non-Coding Transcripts in Human Primary Monocytes 
PLoS ONE  2014;9(7):e102612.
We applied genome-wide allele-specific expression analysis of monocytes from 188 samples. Monocytes were purified from white blood cells of healthy blood donors to detect cis-acting genetic variation that regulates the expression of long non-coding RNAs. We analysed 8929 regions harboring genes for potential long non-coding RNA that were retrieved from data from the ENCODE project. Of these regions, 60% were annotated as intergenic, which implies that they do not overlap with protein-coding genes. Focusing on the intergenic regions, and using stringent analysis of the allele-specific expression data, we detected robust cis-regulatory SNPs in 258 out of 489 informative intergenic regions included in the analysis. The cis-regulatory SNPs that were significantly associated with allele-specific expression of long non-coding RNAs were enriched to enhancer regions marked for active or bivalent, poised chromatin by histone modifications. Out of the lncRNA regions regulated by cis-acting regulatory SNPs, 20% (n = 52) were co-regulated with the closest protein coding gene. We compared the identified cis-regulatory SNPs with those in the catalog of SNPs identified by genome-wide association studies of human diseases and traits. This comparison identified 32 SNPs in loci from genome-wide association studies that displayed a strong association signal with allele-specific expression of non-coding RNAs in monocytes, with p-values ranging from 6.7×10−7 to 9.5×10−89. The identified cis-regulatory SNPs are associated with diseases of the immune system, like multiple sclerosis and rheumatoid arthritis.
doi:10.1371/journal.pone.0102612
PMCID: PMC4099216  PMID: 25025429
7.  Cis and Trans Effects of Human Genomic Variants on Gene Expression 
PLoS Genetics  2014;10(7):e1004461.
Gene expression is a heritable cellular phenotype that defines the function of a cell and can lead to diseases in case of misregulation. In order to detect genetic variations affecting gene expression, we performed association analysis of single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) with gene expression measured in 869 lymphoblastoid cell lines of the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort in cis and in trans. We discovered that 3,534 genes (false discovery rate (FDR) = 5%) are affected by an expression quantitative trait locus (eQTL) in cis and 48 genes are affected in trans. We observed that CNVs are more likely to be eQTLs than SNPs. In addition, we found that variants associated to complex traits and diseases are enriched for trans-eQTLs and that trans-eQTLs are enriched for cis-eQTLs. As a variant affecting both a gene in cis and in trans suggests that the cis gene is functionally linked to the trans gene expression, we looked specifically for trans effects of cis-eQTLs. We discovered that 26 cis-eQTLs are associated to 92 genes in trans with the cis-eQTLs of the transcriptions factors BATF3 and HMX2 affecting the most genes. We then explored if the variation of the level of expression of the cis genes were causally affecting the level of expression of the trans genes and discovered several causal relationships between variation in the level of expression of the cis gene and variation of the level of expression of the trans gene. This analysis shows that a large sample size allows the discovery of secondary effects of human variations on gene expression that can be used to construct short directed gene regulatory networks.
Author Summary
Humans differ in their genetic sequences at millions of positions but only a subset of these differences have a functional effect. In order to detect functional genetic differences, we assessed the impact of common genetic variants on gene expression in 869 individuals and discovered that the expression of many genes is affected by common variants in cis or in trans. We show that the effect of some variants on gene expression cannot be detected in other tissues, highlighting the tissue specificity of gene regulation. In addition, we show that variants associated to common diseases are more likely to affect gene expression in cis and in trans. Finally, we show that variants affecting gene expression in cis often affect gene expression in trans, which suggests that the trans effects are due to the cis genes expression. We tested this hypothesis and discovered several cases of genes regulated in trans by a cis regulated gene in a causal manner. This shows that a population-based strategy with a large number of individuals has the potential to detect secondary effects of common variants that can be used to construct short directed regulatory networks.
doi:10.1371/journal.pgen.1004461
PMCID: PMC4091791  PMID: 25010687
8.  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
9.  Gene-Lifestyle Interaction and Type 2 Diabetes: The EPIC InterAct Case-Cohort Study 
PLoS Medicine  2014;11(5):e1001647.
In this study, Wareham and colleagues quantified the combined effects of genetic and lifestyle factors on risk of T2D in order to inform strategies for prevention. The authors found that the relative effect of a type 2 diabetes genetic risk score is greater in younger and leaner participants, and the high absolute risk associated with obesity at any level of genetic risk highlights the importance of universal rather than targeted approaches to lifestyle intervention.
Please see later in the article for the Editors' Summary
Background
Understanding of the genetic basis of type 2 diabetes (T2D) has progressed rapidly, but the interactions between common genetic variants and lifestyle risk factors have not been systematically investigated in studies with adequate statistical power. Therefore, we aimed to quantify the combined effects of genetic and lifestyle factors on risk of T2D in order to inform strategies for prevention.
Methods and Findings
The InterAct study includes 12,403 incident T2D cases and a representative sub-cohort of 16,154 individuals from a cohort of 340,234 European participants with 3.99 million person-years of follow-up. We studied the combined effects of an additive genetic T2D risk score and modifiable and non-modifiable risk factors using Prentice-weighted Cox regression and random effects meta-analysis methods. The effect of the genetic score was significantly greater in younger individuals (p for interaction  = 1.20×10−4). Relative genetic risk (per standard deviation [4.4 risk alleles]) was also larger in participants who were leaner, both in terms of body mass index (p for interaction  = 1.50×10−3) and waist circumference (p for interaction  = 7.49×10−9). Examination of absolute risks by strata showed the importance of obesity for T2D risk. The 10-y cumulative incidence of T2D rose from 0.25% to 0.89% across extreme quartiles of the genetic score in normal weight individuals, compared to 4.22% to 7.99% in obese individuals. We detected no significant interactions between the genetic score and sex, diabetes family history, physical activity, or dietary habits assessed by a Mediterranean diet score.
Conclusions
The relative effect of a T2D genetic risk score is greater in younger and leaner participants. However, this sub-group is at low absolute risk and would not be a logical target for preventive interventions. The high absolute risk associated with obesity at any level of genetic risk highlights the importance of universal rather than targeted approaches to lifestyle intervention.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Worldwide, more than 380 million people currently have diabetes, and the condition is becoming increasingly common. Diabetes is characterized by high levels of glucose (sugar) in the blood. Blood sugar levels are usually controlled by insulin, a hormone released by the pancreas after meals (digestion of food produces glucose). In people with type 2 diabetes (the commonest type of diabetes), blood sugar control fails because the fat and muscle cells that normally respond to insulin by removing excess sugar from the blood become less responsive to insulin. Type 2 diabetes can often initially be controlled with diet and exercise (lifestyle changes) and with antidiabetic drugs such as metformin and sulfonylureas, but patients may eventually need insulin injections to control their blood sugar levels. Long-term complications of diabetes, which include an increased risk of heart disease and stroke, reduce the life expectancy of people with diabetes by about ten years compared to people without diabetes.
Why Was This Study Done?
Type 2 diabetes is thought to originate from the interplay between genetic and lifestyle factors. But although rapid progress is being made in understanding the genetic basis of type 2 diabetes, it is not known whether the consequences of adverse lifestyles (for example, being overweight and/or physically inactive) differ according to an individual's underlying genetic risk of diabetes. It is important to investigate this question to inform strategies for prevention. If, for example, obese individuals with a high level of genetic risk have a higher risk of developing diabetes than obese individuals with a low level of genetic risk, then preventative strategies that target lifestyle interventions to obese individuals with a high genetic risk would be more effective than strategies that target all obese individuals. In this case-cohort study, researchers from the InterAct consortium quantify the combined effects of genetic and lifestyle factors on the risk of type 2 diabetes. A case-cohort study measures exposure to potential risk factors in a group (cohort) of people and compares the occurrence of these risk factors in people who later develop the disease with those who remain disease free.
What Did the Researchers Do and Find?
The InterAct study involves 12,403 middle-aged individuals who developed type 2 diabetes after enrollment (incident cases) into the European Prospective Investigation into Cancer and Nutrition (EPIC) and a sub-cohort of 16,154 EPIC participants. The researchers calculated a genetic type 2 diabetes risk score for most of these individuals by determining which of 49 gene variants associated with type 2 diabetes each person carried, and collected baseline information about exposure to lifestyle risk factors for type 2 diabetes. They then used various statistical approaches to examine the combined effects of the genetic risk score and lifestyle factors on diabetes development. The effect of the genetic score was greater in younger individuals than in older individuals and greater in leaner participants than in participants with larger amounts of body fat. The absolute risk of type 2 diabetes, expressed as the ten-year cumulative incidence of type 2 diabetes (the percentage of participants who developed diabetes over a ten-year period) increased with increasing genetic score in normal weight individuals from 0.25% in people with the lowest genetic risk scores to 0.89% in those with the highest scores; in obese people, the ten-year cumulative incidence rose from 4.22% to 7.99% with increasing genetic risk score.
What Do These Findings Mean?
These findings show that in this middle-aged cohort, the relative association with type 2 diabetes of a genetic risk score comprised of a large number of gene variants is greatest in individuals who are younger and leaner at baseline. This finding may in part reflect the methods used to originally identify gene variants associated with type 2 diabetes, and future investigations that include other genetic variants, other lifestyle factors, and individuals living in other settings should be undertaken to confirm this finding. Importantly, however, this study shows that young, lean individuals with a high genetic risk score have a low absolute risk of developing type 2 diabetes. Thus, this sub-group of individuals is not a logical target for preventative interventions. Rather, suggest the researchers, the high absolute risk of type 2 diabetes associated with obesity at any level of genetic risk highlights the importance of universal rather than targeted approaches to lifestyle intervention.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001647.
The US National Diabetes Information Clearinghouse provides information about diabetes for patients, health-care professionals and the general public, including detailed information on diabetes prevention (in English and Spanish)
The UK National Health Service Choices website provides information for patients and carers about type 2 diabetes and about living with diabetes; it also provides people's stories about diabetes
The charity Diabetes UK provides detailed information for patients and carers in several languages, including information on healthy lifestyles for people with diabetes
The UK-based non-profit organization Healthtalkonline has interviews with people about their experiences of diabetes
The Genetic Landscape of Diabetes is published by the US National Center for Biotechnology Information
More information on the InterAct study is available
MedlinePlus provides links to further resources and advice about diabetes and diabetes prevention (in English and Spanish)
doi:10.1371/journal.pmed.1001647
PMCID: PMC4028183  PMID: 24845081
10.  Analysis of immune-related loci identifies 48 new susceptibility variants for multiple sclerosis 
Beecham, Ashley H | Patsopoulos, Nikolaos A | Xifara, Dionysia K | Davis, Mary F | Kemppinen, Anu | Cotsapas, Chris | Shahi, Tejas S | Spencer, Chris | Booth, David | Goris, An | Oturai, Annette | Saarela, Janna | Fontaine, Bertrand | Hemmer, Bernhard | Martin, Claes | Zipp, Frauke | D’alfonso, Sandra | Martinelli-Boneschi, Filippo | Taylor, Bruce | Harbo, Hanne F | Kockum, Ingrid | Hillert, Jan | Olsson, Tomas | Ban, Maria | Oksenberg, Jorge R | Hintzen, Rogier | Barcellos, Lisa F | Agliardi, Cristina | Alfredsson, Lars | Alizadeh, Mehdi | Anderson, Carl | Andrews, Robert | Søndergaard, Helle Bach | Baker, Amie | Band, Gavin | Baranzini, Sergio E | Barizzone, Nadia | Barrett, Jeffrey | Bellenguez, Céline | Bergamaschi, Laura | Bernardinelli, Luisa | Berthele, Achim | Biberacher, Viola | Binder, Thomas M C | Blackburn, Hannah | Bomfim, Izaura L | Brambilla, Paola | Broadley, Simon | Brochet, Bruno | Brundin, Lou | Buck, Dorothea | Butzkueven, Helmut | Caillier, Stacy J | Camu, William | Carpentier, Wassila | Cavalla, Paola | Celius, Elisabeth G | Coman, Irène | Comi, Giancarlo | Corrado, Lucia | Cosemans, Leentje | Cournu-Rebeix, Isabelle | Cree, Bruce A C | Cusi, Daniele | Damotte, Vincent | Defer, Gilles | Delgado, Silvia R | Deloukas, Panos | di Sapio, Alessia | Dilthey, Alexander T | Donnelly, Peter | Dubois, Bénédicte | Duddy, Martin | Edkins, Sarah | Elovaara, Irina | Esposito, Federica | Evangelou, Nikos | Fiddes, Barnaby | Field, Judith | Franke, Andre | Freeman, Colin | Frohlich, Irene Y | Galimberti, Daniela | Gieger, Christian | Gourraud, Pierre-Antoine | Graetz, Christiane | Graham, Andrew | Grummel, Verena | Guaschino, Clara | Hadjixenofontos, Athena | Hakonarson, Hakon | Halfpenny, Christopher | Hall, Gillian | Hall, Per | Hamsten, Anders | Harley, James | Harrower, Timothy | Hawkins, Clive | Hellenthal, Garrett | Hillier, Charles | Hobart, Jeremy | Hoshi, Muni | Hunt, Sarah E | Jagodic, Maja | Jelčić, Ilijas | Jochim, Angela | Kendall, Brian | Kermode, Allan | Kilpatrick, Trevor | Koivisto, Keijo | Konidari, Ioanna | Korn, Thomas | Kronsbein, Helena | Langford, Cordelia | Larsson, Malin | Lathrop, Mark | Lebrun-Frenay, Christine | Lechner-Scott, Jeannette | Lee, Michelle H | Leone, Maurizio A | Leppä, Virpi | Liberatore, Giuseppe | Lie, Benedicte A | Lill, Christina M | Lindén, Magdalena | Link, Jenny | Luessi, Felix | Lycke, Jan | Macciardi, Fabio | Männistö, Satu | Manrique, Clara P | Martin, Roland | Martinelli, Vittorio | Mason, Deborah | Mazibrada, Gordon | McCabe, Cristin | Mero, Inger-Lise | Mescheriakova, Julia | Moutsianas, Loukas | Myhr, Kjell-Morten | Nagels, Guy | Nicholas, Richard | Nilsson, Petra | Piehl, Fredrik | Pirinen, Matti | Price, Siân E | Quach, Hong | Reunanen, Mauri | Robberecht, Wim | Robertson, Neil P | Rodegher, Mariaemma | Rog, David | Salvetti, Marco | Schnetz-Boutaud, Nathalie C | Sellebjerg, Finn | Selter, Rebecca C | Schaefer, Catherine | Shaunak, Sandip | Shen, Ling | Shields, Simon | Siffrin, Volker | Slee, Mark | Sorensen, Per Soelberg | Sorosina, Melissa | Sospedra, Mireia | Spurkland, Anne | Strange, Amy | Sundqvist, Emilie | Thijs, Vincent | Thorpe, John | Ticca, Anna | Tienari, Pentti | van Duijn, Cornelia | Visser, Elizabeth M | Vucic, Steve | Westerlind, Helga | Wiley, James S | Wilkins, Alastair | Wilson, James F | Winkelmann, Juliane | Zajicek, John | Zindler, Eva | Haines, Jonathan L | Pericak-Vance, Margaret A | Ivinson, Adrian J | Stewart, Graeme | Hafler, David | Hauser, Stephen L | Compston, Alastair | McVean, Gil | De Jager, Philip | Sawcer, Stephen | McCauley, Jacob L
Nature genetics  2013;45(11):10.1038/ng.2770.
Using the ImmunoChip custom genotyping array, we analysed 14,498 multiple sclerosis subjects and 24,091 healthy controls for 161,311 autosomal variants and identified 135 potentially associated regions (p-value < 1.0 × 10-4). In a replication phase, we combined these data with previous genome-wide association study (GWAS) data from an independent 14,802 multiple sclerosis subjects and 26,703 healthy controls. In these 80,094 individuals of European ancestry we identified 48 new susceptibility variants (p-value < 5.0 × 10-8); three found after conditioning on previously identified variants. Thus, there are now 110 established multiple sclerosis risk variants in 103 discrete loci outside of the Major Histocompatibility Complex. With high resolution Bayesian fine-mapping, we identified five regions where one variant accounted for more than 50% of the posterior probability of association. This study enhances the catalogue of multiple sclerosis risk variants and illustrates the value of fine-mapping in the resolution of GWAS signals.
doi:10.1038/ng.2770
PMCID: PMC3832895  PMID: 24076602
11.  Genome-Wide Association Study Identifies a Novel Locus Contributing to Type 2 Diabetes Susceptibility in Sikhs of Punjabi Origin From India 
Diabetes  2013;62(5):1746-1755.
We performed a genome-wide association study (GWAS) and a multistage meta-analysis of type 2 diabetes (T2D) in Punjabi Sikhs from India. Our discovery GWAS in 1,616 individuals (842 case subjects) was followed by in silico replication of the top 513 independent single nucleotide polymorphisms (SNPs) (P < 10−3) in Punjabi Sikhs (n = 2,819; 801 case subjects). We further replicated 66 SNPs (P < 10−4) through genotyping in a Punjabi Sikh sample (n = 2,894; 1,711 case subjects). On combined meta-analysis in Sikh populations (n = 7,329; 3,354 case subjects), we identified a novel locus in association with T2D at 13q12 represented by a directly genotyped intronic SNP (rs9552911, P = 1.82 × 10−8) in the SGCG gene. Next, we undertook in silico replication (stage 2b) of the top 513 signals (P < 10−3) in 29,157 non-Sikh South Asians (10,971 case subjects) and de novo genotyping of up to 31 top signals (P < 10−4) in 10,817 South Asians (5,157 case subjects) (stage 3b). In combined South Asian meta-analysis, we observed six suggestive associations (P < 10−5 to < 10−7), including SNPs at HMG1L1/CTCFL, PLXNA4, SCAP, and chr5p11. Further evaluation of 31 top SNPs in 33,707 East Asians (16,746 case subjects) (stage 3c) and 47,117 Europeans (8,130 case subjects) (stage 3d), and joint meta-analysis of 128,127 individuals (44,358 case subjects) from 27 multiethnic studies, did not reveal any additional loci nor was there any evidence of replication for the new variant. Our findings provide new evidence on the presence of a population-specific signal in relation to T2D, which may provide additional insights into T2D pathogenesis.
doi:10.2337/db12-1077
PMCID: PMC3636649  PMID: 23300278
12.  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
13.  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
14.  Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture 
Berndt, Sonja I. | Gustafsson, Stefan | Mägi, Reedik | Ganna, Andrea | Wheeler, Eleanor | Feitosa, Mary F. | Justice, Anne E. | Monda, Keri L. | Croteau-Chonka, Damien C. | Day, Felix R. | Esko, Tõnu | Fall, Tove | Ferreira, Teresa | Gentilini, Davide | Jackson, Anne U. | Luan, Jian’an | Randall, Joshua C. | Vedantam, Sailaja | Willer, Cristen J. | Winkler, Thomas W. | Wood, Andrew R. | Workalemahu, Tsegaselassie | Hu, Yi-Juan | Lee, Sang Hong | Liang, Liming | Lin, Dan-Yu | Min, Josine L. | Neale, Benjamin M. | Thorleifsson, Gudmar | Yang, Jian | Albrecht, Eva | Amin, Najaf | Bragg-Gresham, Jennifer L. | Cadby, Gemma | den Heijer, Martin | Eklund, Niina | Fischer, Krista | Goel, Anuj | Hottenga, Jouke-Jan | Huffman, Jennifer E. | Jarick, Ivonne | Johansson, Åsa | Johnson, Toby | Kanoni, Stavroula | Kleber, Marcus E. | König, Inke R. | Kristiansson, Kati | Kutalik, Zoltán | Lamina, Claudia | Lecoeur, Cecile | Li, Guo | Mangino, Massimo | McArdle, Wendy L. | Medina-Gomez, Carolina | Müller-Nurasyid, Martina | Ngwa, Julius S. | Nolte, Ilja M. | Paternoster, Lavinia | Pechlivanis, Sonali | Perola, Markus | Peters, Marjolein J. | Preuss, Michael | Rose, Lynda M. | Shi, Jianxin | Shungin, Dmitry | Smith, Albert Vernon | Strawbridge, Rona J. | Surakka, Ida | Teumer, Alexander | Trip, Mieke D. | Tyrer, Jonathan | Van Vliet-Ostaptchouk, Jana V. | Vandenput, Liesbeth | Waite, Lindsay L. | Zhao, Jing Hua | Absher, Devin | Asselbergs, Folkert W. | Atalay, Mustafa | Attwood, Antony P. | Balmforth, Anthony J. | Basart, Hanneke | Beilby, John | Bonnycastle, Lori L. | Brambilla, Paolo | Bruinenberg, Marcel | Campbell, Harry | Chasman, Daniel I. | Chines, Peter S. | Collins, Francis S. | Connell, John M. | Cookson, William | de Faire, Ulf | de Vegt, Femmie | Dei, Mariano | Dimitriou, Maria | Edkins, Sarah | Estrada, Karol | Evans, David M. | Farrall, Martin | Ferrario, Marco M. | Ferrières, Jean | Franke, Lude | Frau, Francesca | Gejman, Pablo V. | Grallert, Harald | Grönberg, Henrik | Gudnason, Vilmundur | Hall, Alistair S. | Hall, Per | Hartikainen, Anna-Liisa | Hayward, Caroline | Heard-Costa, Nancy L. | Heath, Andrew C. | Hebebrand, Johannes | Homuth, Georg | Hu, Frank B. | Hunt, Sarah E. | Hyppönen, Elina | Iribarren, Carlos | Jacobs, Kevin B. | Jansson, John-Olov | Jula, Antti | Kähönen, Mika | Kathiresan, Sekar | Kee, Frank | Khaw, Kay-Tee | Kivimaki, Mika | Koenig, Wolfgang | Kraja, Aldi T. | Kumari, Meena | Kuulasmaa, Kari | Kuusisto, Johanna | Laitinen, Jaana H. | Lakka, Timo A. | Langenberg, Claudia | Launer, Lenore J. | Lind, Lars | Lindström, Jaana | Liu, Jianjun | Liuzzi, Antonio | Lokki, Marja-Liisa | Lorentzon, Mattias | Madden, Pamela A. | Magnusson, Patrik K. | Manunta, Paolo | Marek, Diana | März, Winfried | Mateo Leach, Irene | McKnight, Barbara | Medland, Sarah E. | Mihailov, Evelin | Milani, Lili | Montgomery, Grant W. | Mooser, Vincent | Mühleisen, Thomas W. | Munroe, Patricia B. | Musk, Arthur W. | Narisu, Narisu | Navis, Gerjan | Nicholson, George | Nohr, Ellen A. | Ong, Ken K. | Oostra, Ben A. | Palmer, Colin N.A. | Palotie, Aarno | Peden, John F. | Pedersen, Nancy | Peters, Annette | Polasek, Ozren | Pouta, Anneli | Pramstaller, Peter P. | Prokopenko, Inga | Pütter, Carolin | Radhakrishnan, Aparna | Raitakari, Olli | Rendon, Augusto | Rivadeneira, Fernando | Rudan, Igor | Saaristo, Timo E. | Sambrook, Jennifer G. | Sanders, Alan R. | Sanna, Serena | Saramies, Jouko | Schipf, Sabine | Schreiber, Stefan | Schunkert, Heribert | Shin, So-Youn | Signorini, Stefano | Sinisalo, Juha | Skrobek, Boris | Soranzo, Nicole | Stančáková, Alena | Stark, Klaus | Stephens, Jonathan C. | Stirrups, Kathleen | Stolk, Ronald P. | Stumvoll, Michael | Swift, Amy J. | Theodoraki, Eirini V. | Thorand, Barbara | Tregouet, David-Alexandre | Tremoli, Elena | Van der Klauw, Melanie M. | van Meurs, Joyce B.J. | Vermeulen, Sita H. | Viikari, Jorma | Virtamo, Jarmo | Vitart, Veronique | Waeber, Gérard | Wang, Zhaoming | Widén, Elisabeth | Wild, Sarah H. | Willemsen, Gonneke | Winkelmann, Bernhard R. | Witteman, Jacqueline C.M. | Wolffenbuttel, Bruce H.R. | Wong, Andrew | Wright, Alan F. | Zillikens, M. Carola | Amouyel, Philippe | Boehm, Bernhard O. | Boerwinkle, Eric | Boomsma, Dorret I. | Caulfield, Mark J. | Chanock, Stephen J. | Cupples, L. Adrienne | Cusi, Daniele | Dedoussis, George V. | Erdmann, Jeanette | Eriksson, Johan G. | Franks, Paul W. | Froguel, Philippe | Gieger, Christian | Gyllensten, Ulf | Hamsten, Anders | Harris, Tamara B. | Hengstenberg, Christian | Hicks, Andrew A. | Hingorani, Aroon | Hinney, Anke | Hofman, Albert | Hovingh, Kees G. | Hveem, Kristian | Illig, Thomas | Jarvelin, Marjo-Riitta | Jöckel, Karl-Heinz | Keinanen-Kiukaanniemi, Sirkka M. | Kiemeney, Lambertus A. | Kuh, Diana | Laakso, Markku | Lehtimäki, Terho | Levinson, Douglas F. | Martin, Nicholas G. | Metspalu, Andres | Morris, Andrew D. | Nieminen, Markku S. | Njølstad, Inger | Ohlsson, Claes | Oldehinkel, Albertine J. | Ouwehand, Willem H. | Palmer, Lyle J. | Penninx, Brenda | Power, Chris | Province, Michael A. | Psaty, Bruce M. | Qi, Lu | Rauramaa, Rainer | Ridker, Paul M. | Ripatti, Samuli | Salomaa, Veikko | Samani, Nilesh J. | Snieder, Harold | Sørensen, Thorkild I.A. | Spector, Timothy D. | Stefansson, Kari | Tönjes, Anke | Tuomilehto, Jaakko | Uitterlinden, André G. | Uusitupa, Matti | van der Harst, Pim | Vollenweider, Peter | Wallaschofski, Henri | Wareham, Nicholas J. | Watkins, Hugh | Wichmann, H.-Erich | Wilson, James F. | Abecasis, Goncalo R. | Assimes, Themistocles L. | Barroso, Inês | Boehnke, Michael | Borecki, Ingrid B. | Deloukas, Panos | Fox, Caroline S. | Frayling, Timothy | Groop, Leif C. | Haritunian, Talin | Heid, Iris M. | Hunter, David | Kaplan, Robert C. | Karpe, Fredrik | Moffatt, Miriam | Mohlke, Karen L. | O’Connell, Jeffrey R. | Pawitan, Yudi | Schadt, Eric E. | Schlessinger, David | Steinthorsdottir, Valgerdur | Strachan, David P. | Thorsteinsdottir, Unnur | van Duijn, Cornelia M. | Visscher, Peter M. | Di Blasio, Anna Maria | Hirschhorn, Joel N. | Lindgren, Cecilia M. | Morris, Andrew P. | Meyre, David | Scherag, André | McCarthy, Mark I. | Speliotes, Elizabeth K. | North, Kari E. | Loos, Ruth J.F. | Ingelsson, Erik
Nature genetics  2013;45(5):501-512.
Approaches exploiting extremes of the trait distribution may reveal novel loci for common traits, but it is unknown whether such loci are generalizable to the general population. In a genome-wide search for loci associated with upper vs. lower 5th percentiles of body mass index, height and waist-hip ratio, as well as clinical classes of obesity including up to 263,407 European individuals, we identified four new loci (IGFBP4, H6PD, RSRC1, PPP2R2A) influencing height detected in the tails and seven new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3, ZZZ3) for clinical classes of obesity. Further, we show that there is large overlap in terms of genetic structure and distribution of variants between traits based on extremes and the general population and little etiologic heterogeneity between obesity subgroups.
doi:10.1038/ng.2606
PMCID: PMC3973018  PMID: 23563607
15.  Interrogating causal pathways linking genetic variants, small molecule metabolites, and circulating lipids 
Genome Medicine  2014;6(3):25.
Background
Emerging technologies based on mass spectrometry or nuclear magnetic resonance enable the monitoring of hundreds of small metabolites from tissues or body fluids. Profiling of metabolites can help elucidate causal pathways linking established genetic variants to known disease risk factors such as blood lipid traits.
Methods
We applied statistical methodology to dissect causal relationships between single nucleotide polymorphisms, metabolite concentrations, and serum lipid traits, focusing on 95 genetic loci reproducibly associated with the four main serum lipids (total-, low-density lipoprotein-, and high-density lipoprotein- cholesterol and triglycerides). The dataset used included 2,973 individuals from two independent population-based cohorts with data for 151 small molecule metabolites and four main serum lipids. Three statistical approaches, namely conditional analysis, Mendelian randomization, and structural equation modeling, were compared to investigate causal relationship at sets of a single nucleotide polymorphism, a metabolite, and a lipid trait associated with one another.
Results
A subset of three lipid-associated loci (FADS1, GCKR, and LPA) have a statistically significant association with at least one main lipid and one metabolite concentration in our data, defining a total of 38 cross-associated sets of a single nucleotide polymorphism, a metabolite and a lipid trait. Structural equation modeling provided sufficient discrimination to indicate that the association of a single nucleotide polymorphism with a lipid trait was mediated through a metabolite at 15 of the 38 sets, and involving variants at the FADS1 and GCKR loci.
Conclusions
These data provide a framework for evaluating the causal role of components of the metabolome (or other intermediate factors) in mediating the association between established genetic variants and diseases or traits.
doi:10.1186/gm542
PMCID: PMC4062056  PMID: 24678845
16.  Meta-Analysis Investigating Associations Between Healthy Diet and Fasting Glucose and Insulin Levels and Modification by Loci Associated With Glucose Homeostasis in Data From 15 Cohorts 
American Journal of Epidemiology  2012;177(2):103-115.
Whether loci that influence fasting glucose (FG) and fasting insulin (FI) levels, as identified by genome-wide association studies, modify associations of diet with FG or FI is unknown. We utilized data from 15 US and European cohort studies comprising 51,289 persons without diabetes to test whether genotype and diet interact to influence FG or FI concentration. We constructed a diet score using study-specific quartile rankings for intakes of whole grains, fish, fruits, vegetables, and nuts/seeds (favorable) and red/processed meats, sweets, sugared beverages, and fried potatoes (unfavorable). We used linear regression within studies, followed by inverse-variance-weighted meta-analysis, to quantify 1) associations of diet score with FG and FI levels and 2) interactions of diet score with 16 FG-associated loci and 2 FI-associated loci. Diet score (per unit increase) was inversely associated with FG (β = −0.004 mmol/L, 95% confidence interval: −0.005, −0.003) and FI (β = −0.008 ln-pmol/L, 95% confidence interval: −0.009, −0.007) levels after adjustment for demographic factors, lifestyle, and body mass index. Genotype variation at the studied loci did not modify these associations. Healthier diets were associated with lower FG and FI concentrations regardless of genotype at previously replicated FG- and FI-associated loci. Studies focusing on genomic regions that do not yield highly statistically significant associations from main-effect genome-wide association studies may be more fruitful in identifying diet-gene interactions.
doi:10.1093/aje/kws297
PMCID: PMC3707424  PMID: 23255780
diabetes; dietary pattern; gene-environment interaction; glucose; insulin
17.  Dense genotyping of immune-related disease regions identifies 14 new susceptibility loci for juvenile idiopathic arthritis 
Nature genetics  2013;45(6):664-669.
Analysis of the ImmunoChip single nucleotide polymorphism (SNP) array in 2816 individuals, comprising the most common subtypes (oligoarticular and RF negative polyarticular) of juvenile idiopathic arthritis (JIA) and 13056 controls strengthens the evidence for association to three known JIA-risk loci (HLA, PTPN22 and PTPN2) and has identified fourteen risk loci reaching genome-wide significance (p < 5 × 10-8) for the first time. Eleven additional novel regions showed suggestive evidence for association with JIA (p < 1 × 10-6). Dense-mapping of loci along with bioinformatic analysis has refined the association to one gene for eight regions, highlighting crucial pathways, including the IL-2 pathway, in JIA disease pathogenesis. The entire ImmunoChip loci, HLA region and the top 27 loci (p < 1 × 10-6) explain an estimated 18%, 13% and 6% risk of JIA, respectively. Analysis of the ImmunoChip dataset, the largest cohort of JIA cases investigated to date, provides new insight in understanding the genetic basis for this childhood autoimmune disease.
doi:10.1038/ng.2614
PMCID: PMC3673707  PMID: 23603761
18.  Human metabolic individuality in biomedical and pharmaceutical research 
Nature  2011;477(7362):10.1038/nature10354.
SUMMARY
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.
doi:10.1038/nature10354
PMCID: PMC3832838  PMID: 21886157
19.  Mapping cis- and trans-regulatory effects across multiple tissues in twins 
Nature genetics  2012;44(10):1084-1089.
Sequence-based variation in gene expression is a key driver of disease risk. Common variants regulating expression in cis have been mapped in many eQTL studies typically in single tissues from unrelated individuals. Here, we present a comprehensive analysis of gene expression across multiple tissues conducted in a large set of mono- and dizygotic twins that allows systematic dissection of genetic (cis and trans) and non-genetic effects on gene expression. Using identity-by-descent estimates, we show that at least 40% of the total heritable cis-effect on expression cannot be accounted for by common cis-variants, a finding which exposes the contribution of low frequency and rare regulatory variants with respect to both transcriptional regulation and complex trait susceptibility. We show that a substantial proportion of gene expression heritability is trans to the structural gene and identify several replicating trans-variants which act predominantly in a tissue-restricted manner and may regulate the transcription of many genes.
doi:10.1038/ng.2394
PMCID: PMC3784328  PMID: 22941192
20.  Genetically Distinct Subsets within ANCA-Associated Vasculitis 
The New England journal of medicine  2012;367(3):214-223.
BACKGROUND
Antineutrophil cytoplasmic antibody (ANCA)–associated vasculitis is a severe condition encompassing two major syndromes: granulomatosis with polyangiitis (formerly known as Wegener’s granulomatosis) and microscopic polyangiitis. Its cause is unknown, and there is debate about whether it is a single disease entity and what role ANCA plays in its pathogenesis. We investigated its genetic basis.
METHODS
A genomewide association study was performed in a discovery cohort of 1233 U.K. patients with ANCA-associated vasculitis and 5884 controls and was replicated in 1454 Northern European case patients and 1666 controls. Quality control, population stratification, and statistical analyses were performed according to standard criteria.
RESULTS
We found both major-histocompatibility-complex (MHC) and non-MHC associations with ANCA-associated vasculitis and also that granulomatosis with polyangiitis and microscopic polyangiitis were genetically distinct. The strongest genetic associations were with the antigenic specificity of ANCA, not with the clinical syndrome. Anti–proteinase 3 ANCA was associated with HLA-DP and the genes encoding α1-antitrypsin (SERPINA1) and proteinase 3 (PRTN3) (P = 6.2×10−89, P = 5.6×10−12, and P = 2.6×10−7, respectively). Anti–myeloperoxidase ANCA was associated with HLA-DQ (P = 2.1×10−8).
CONCLUSIONS
This study confirms that the pathogenesis of ANCA-associated vasculitis has a genetic component, shows genetic distinctions between granulomatosis with polyangiitis and microscopic polyangiitis that are associated with ANCA specificity, and suggests that the response against the autoantigen proteinase 3 is a central pathogenic feature of proteinase 3 ANCA–associated vasculitis. These data provide preliminary support for the concept that proteinase 3 ANCA–associated vasculitis and myeloperoxidase ANCA–associated vasculitis are distinct autoimmune syndromes. (Funded by the British Heart Foundation and others.)
doi:10.1056/NEJMoa1108735
PMCID: PMC3773907  PMID: 22808956
21.  Genome-wide association study in people of South Asian ancestry identifies six novel susceptibility loci for type 2 diabetes 
Nature genetics  2011;43(10):984-989.
We carried out a genome wide association study of type-2 diabetes (T2D) amongst 20,119 people of South Asian ancestry (5,561 with T2D); we identified 20 independent SNPs associated with T2D at P<10−4 for testing amongst a further 38,568 South Asians (13,170 with T2D). In combined analysis, common genetic variants at six novel loci (GRB14, ST6GAL1, VPS26A, HMG20A, AP3S2 and HNF4A) were associated with T2D (P=4.1×10−8 to P=1.9×10−11); SNPs at GRB14 were also associated with insulin sensitivity, and at ST6GAL1 and HNF4A with pancreatic beta-cell function respectively. Our findings provide additional insight into mechanisms underlying T2D, and demonstrate the potential for new discovery from genetic association studies in South Asians who have increased susceptibility to T2D.
doi:10.1038/ng.921
PMCID: PMC3773920  PMID: 21874001
22.  Genetic variants associated with warfarin dose in African-American individuals: a genome-wide association study 
Lancet  2013;382(9894):790-796.
Summary
Background
VKORC1 and CYP2C9 are important contributors to warfarin dose variability, but explain less variability for individuals of African descent than for those of European or Asian descent. We aimed to identify additional variants contributing to warfarin dose requirements in African Americans.
Methods
We did a genome-wide association study of discovery and replication cohorts. Samples from African-American adults (aged ≥18 years) who were taking a stable maintenance dose of warfarin were obtained at International Warfarin Pharmacogenetics Consortium (IWPC) sites and the University of Alabama at Birmingham (Birmingham, AL, USA). Patients enrolled at IWPC sites but who were not used for discovery made up the independent replication cohort. All participants were genotyped. We did a stepwise conditional analysis, conditioning first for VKORC1 −1639G→A, followed by the composite genotype of CYP2C9*2 and CYP2C9*3. We prespecified a genome-wide significance threshold of p<5×10−8 in the discovery cohort and p<0·0038 in the replication cohort.
Findings
The discovery cohort contained 533 participants and the replication cohort 432 participants. After the prespecified conditioning in the discovery cohort, we identified an association between a novel single nucleotide polymorphism in the CYP2C cluster on chromosome 10 (rs12777823) and warfarin dose requirement that reached genome-wide significance (p=1·51×10−8). This association was confirmed in the replication cohort (p=5·04×10−5); analysis of the two cohorts together produced a p value of 4·5×10−12. Individuals heterozygous for the rs12777823 A allele need a dose reduction of 6·92 mg/week and those homozygous 9·34 mg/week. Regression analysis showed that the inclusion of rs12777823 significantly improves warfarin dose variability explained by the IWPC dosing algorithm (21% relative improvement).
Interpretation
A novel CYP2C single nucleotide polymorphism exerts a clinically relevant effect on warfarin dose in African Americans, independent of CYP2C9*2 and CYP2C9*3. Incorporation of this variant into pharmacogenetic dosing algorithms could improve warfarin dose prediction in this population.
Funding
National Institutes of Health, American Heart Association, Howard Hughes Medical Institute, Wisconsin Network for Health Research, and the Wellcome Trust.
doi:10.1016/S0140-6736(13)60681-9
PMCID: PMC3759580  PMID: 23755828
23.  Identification of multiple risk variants for ankylosing spondylitis through high-density genotyping of immune-related loci 
Nature genetics  2013;45(7):730-738.
Ankylosing spondylitis is a common, highly heritable inflammatory arthritis affecting primarily the spine and pelvis. In addition to HLA-B*27 alleles, 12 loci have previously been identified that are associated with ankylosing spondylitis in populations of European ancestry, and 2 associated loci have been identified in Asians. In this study, we used the Illumina Immunochip microarray to perform a case-control association study involving 10,619 individuals with ankylosing spondylitis (cases) and 15,145 controls. We identified 13 new risk loci and 12 additional ankylosing spondylitis–associated haplotypes at 11 loci. Two ankylosing spondylitis–associated regions have now been identified encoding four aminopeptidases that are involved in peptide processing before major histocompatibility complex (MHC) class I presentation. Protective variants at two of these loci are associated both with reduced aminopeptidase function and with MHC class I cell surface expression.
doi:10.1038/ng.2667
PMCID: PMC3757343  PMID: 23749187
24.  GWAS of 126,559 Individuals Identifies Genetic Variants Associated with Educational Attainment 
Rietveld, Cornelius A. | Medland, Sarah E. | Derringer, Jaime | Yang, Jian | Esko, Tõnu | Martin, Nicolas W. | Westra, Harm-Jan | Shakhbazov, Konstantin | Abdellaoui, Abdel | Agrawal, Arpana | Albrecht, Eva | Alizadeh, Behrooz Z. | Amin, Najaf | Barnard, John | Baumeister, Sebastian E. | Benke, Kelly S. | Bielak, Lawrence F. | Boatman, Jeffrey A. | Boyle, Patricia A. | Davies, Gail | de Leeuw, Christiaan | Eklund, Niina | Evans, Daniel S. | Ferhmann, Rudolf | Fischer, Krista | Gieger, Christian | Gjessing, Håkon K. | Hägg, Sara | Harris, Jennifer R. | Hayward, Caroline | Holzapfel, Christina | Ibrahim-Verbaas, Carla A. | Ingelsson, Erik | Jacobsson, Bo | Joshi, Peter K. | Jugessur, Astanand | Kaakinen, Marika | Kanoni, Stavroula | Karjalainen, Juha | Kolcic, Ivana | Kristiansson, Kati | Kutalik, Zoltán | Lahti, Jari | Lee, Sang H. | Lin, Peng | Lind, Penelope A. | Liu, Yongmei | Lohman, Kurt | Loitfelder, Marisa | McMahon, George | Vidal, Pedro Marques | Meirelles, Osorio | Milani, Lili | Myhre, Ronny | Nuotio, Marja-Liisa | Oldmeadow, Christopher J. | Petrovic, Katja E. | Peyrot, Wouter J. | Polašek, Ozren | Quaye, Lydia | Reinmaa, Eva | Rice, John P. | Rizzi, Thais S. | Schmidt, Helena | Schmidt, Reinhold | Smith, Albert V. | Smith, Jennifer A. | Tanaka, Toshiko | Terracciano, Antonio | van der Loos, Matthijs J.H.M. | Vitart, Veronique | Völzke, Henry | Wellmann, Jürgen | Yu, Lei | Zhao, Wei | Allik, Jüri | Attia, John R. | Bandinelli, Stefania | Bastardot, François | Beauchamp, Jonathan | Bennett, David A. | Berger, Klaus | Bierut, Laura J. | Boomsma, Dorret I. | Bültmann, Ute | Campbell, Harry | Chabris, Christopher F. | Cherkas, Lynn | Chung, Mina K. | Cucca, Francesco | de Andrade, Mariza | De Jager, Philip L. | De Neve, Jan-Emmanuel | Deary, Ian J. | Dedoussis, George V. | Deloukas, Panos | Dimitriou, Maria | Eiriksdottir, Gudny | Elderson, Martin F. | Eriksson, Johan G. | Evans, David M. | Faul, Jessica D. | Ferrucci, Luigi | Garcia, Melissa E. | Grönberg, Henrik | Gudnason, Vilmundur | Hall, Per | Harris, Juliette M. | Harris, Tamara B. | Hastie, Nicholas D. | Heath, Andrew C. | Hernandez, Dena G. | Hoffmann, Wolfgang | Hofman, Adriaan | Holle, Rolf | Holliday, Elizabeth G. | Hottenga, Jouke-Jan | Iacono, William G. | Illig, Thomas | Järvelin, Marjo-Riitta | Kähönen, Mika | Kaprio, Jaakko | Kirkpatrick, Robert M. | Kowgier, Matthew | Latvala, Antti | Launer, Lenore J. | Lawlor, Debbie A. | Lehtimäki, Terho | Li, Jingmei | Lichtenstein, Paul | Lichtner, Peter | Liewald, David C. | Madden, Pamela A. | Magnusson, Patrik K. E. | Mäkinen, Tomi E. | Masala, Marco | McGue, Matt | Metspalu, Andres | Mielck, Andreas | Miller, Michael B. | Montgomery, Grant W. | Mukherjee, Sutapa | Nyholt, Dale R. | Oostra, Ben A. | Palmer, Lyle J. | Palotie, Aarno | Penninx, Brenda | Perola, Markus | Peyser, Patricia A. | Preisig, Martin | Räikkönen, Katri | Raitakari, Olli T. | Realo, Anu | Ring, Susan M. | Ripatti, Samuli | Rivadeneira, Fernando | Rudan, Igor | Rustichini, Aldo | Salomaa, Veikko | Sarin, Antti-Pekka | Schlessinger, David | Scott, Rodney J. | Snieder, Harold | Pourcain, Beate St | Starr, John M. | Sul, Jae Hoon | Surakka, Ida | Svento, Rauli | Teumer, Alexander | Tiemeier, Henning | Rooij, Frank JAan | Van Wagoner, David R. | Vartiainen, Erkki | Viikari, Jorma | Vollenweider, Peter | Vonk, Judith M. | Waeber, Gérard | Weir, David R. | Wichmann, H.-Erich | Widen, Elisabeth | Willemsen, Gonneke | Wilson, James F. | Wright, Alan F. | Conley, Dalton | Davey-Smith, George | Franke, Lude | Groenen, Patrick J. F. | Hofman, Albert | Johannesson, Magnus | Kardia, Sharon L.R. | Krueger, Robert F. | Laibson, David | Martin, Nicholas G. | Meyer, Michelle N. | Posthuma, Danielle | Thurik, A. Roy | Timpson, Nicholas J. | Uitterlinden, André G. | van Duijn, Cornelia M. | Visscher, Peter M. | Benjamin, Daniel J. | Cesarini, David | Koellinger, Philipp D.
Science (New York, N.Y.)  2013;340(6139):1467-1471.
A genome-wide association study of educational attainment was conducted in a discovery sample of 101,069 individuals and a replication sample of 25,490. Three independent SNPs are genome-wide significant (rs9320913, rs11584700, rs4851266), and all three replicate. Estimated effects sizes are small (R2 ≈ 0.02%), approximately 1 month of schooling per allele. A linear polygenic score from all measured SNPs accounts for ≈ 2% of the variance in both educational attainment and cognitive function. Genes in the region of the loci have previously been associated with health, cognitive, and central nervous system phenotypes, and bioinformatics analyses suggest the involvement of the anterior caudate nucleus. These findings provide promising candidate SNPs for follow-up work, and our effect size estimates can anchor power analyses in social-science genetics.
doi:10.1126/science.1235488
PMCID: PMC3751588  PMID: 23722424
25.  Genome-wide association study identifies new psoriasis susceptibility loci and an interaction between HLA-C and ERAP1 
Strange, Amy | Capon, Francesca | Spencer, Chris CA | Knight, Jo | Weale, Michael E | Allen, Michael H | Barton, Anne | Band, Gavin | Bellenguez, Céline | Bergboer, Judith GM | Blackwell, Jenefer M | Bramon, Elvira | Bumpstead, Suzannah J | Casas, Juan P | Cork, Michael J | Corvin, Aiden | Deloukas, Panos | Dilthey, Alexander | Duncanson, Audrey | Edkins, Sarah | Estivill, Xavier | Fitzgerald, Oliver | Freeman, Colin | Giardina, Emiliano | Gray, Emma | Hofer, Angelika | Hüffmeier, Ulrike | Hunt, Sarah E | Irvine, Alan D | Jankowski, Janusz | Kirby, Brian | Langford, Cordelia | Lascorz, Jesús | Leman, Joyce | Leslie, Stephen | Mallbris, Lotus | Markus, Hugh S | Mathew, Christopher G | McLean, WH Irwin | McManus, Ross | Mössner, Rotraut | Moutsianas, Loukas | Naluai, Åsa T | Nestle, Frank O | Novelli, Giuseppe | Onoufriadis, Alexandros | Palmer, Colin NA | Perricone, Carlo | Pirinen, Matti | Plomin, Robert | Potter, Simon C | Pujol, Ramon M | Rautanen, Anna | Riveira-Munoz, Eva | Ryan, Anthony W | Salmhofer, Wolfgang | Samuelsson, Lena | Sawcer, Stephen J | Schalkwijk, Joost | Smith, Catherine H | Ståhle, Mona | Su, Zhan | Tazi-Ahnini, Rachid | Traupe, Heiko | Viswanathan, Ananth C | Warren, Richard B | Weger, Wolfgang | Wolk, Katarina | Wood, Nicholas | Worthington, Jane | Young, Helen S | Zeeuwen, Patrick LJM | Hayday, Adrian | Burden, A David | Griffiths, Christopher EM | Kere, Juha | Reis, André | McVean, Gilean | Evans, David M | Brown, Matthew A | Barker, Jonathan N | Peltonen, Leena | Donnelly, Peter | Trembath, Richard C
Nature genetics  2010;42(11):985-990.
doi:10.1038/ng.694
PMCID: PMC3749730  PMID: 20953190

Results 1-25 (159)