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Previously, we reported germline DNA variants associated with risk of urinary bladder cancer (UBC) in Dutch and Icelandic subjects. Here we expanded the Icelandic sample set and tested the top 20 markers from the combined analysis in several European case-control sample sets, with a total of 4,739 cases and 45,549 controls. The T allele of rs798766 on 4p16.3 was found to associate with UBC (odds ratio = 1.24, P = 9.9 × 10 12). rs798766 is located in an intron of TACC3, 70 kb from FGFR3, which often harbors activating somatic mutations in low-grade, noninvasive UBC. Notably, rs798766[T] shows stronger association with low-grade and low-stage UBC than with more aggressive forms of the disease and is associated with higher risk of recurrence in low-grade stage Ta tumors. The frequency of rs798766[T] is higher in Ta tumors that carry an activating mutation in FGFR3 than in Ta tumors with wild-type FGFR3. Our results show a link between germline variants, somatic mutations of FGFR3 and risk of UBC. © 2010 Nature America, Inc. All rights reserved., Vlaamse regering 513943 Compagnia di San Paolo Yorkshire Cancer Research Adessium Foundation European Commission: LSHC-CT-2005 218071 Associazione Italiana per la Ricerca sul Cancro Prinses Beatrix Spierfonds, We thank the individuals who participated in the study and whose contribution made this work possible. We also thank the nurses at deCODE’s recruitment center and the personnel at the deCODE core facilities. We acknowledge the Icelandic Cancer Registry for assistance in the ascertainment of the Icelandic UBC cases. C.Z. and S.B. are funded by a FP7-MC-IAPP Grant agreement no. 218071 (CancerGene). Collection of samples and data in Iceland and The Netherlands was funded in part by the European Commission (POLYGENE: LSHC-CT-2005) and a research investment grant of the Radboud University Nijmegen Medical Centre. Control samples for the Dutch follow-up group were genotyped with generous support from the ‘Prinses Beatrix Fonds’, VSB Fonds, H. Kersten and M. Kersten (Kersten Foundation), The Netherlands ALS Foundation, J.R. van Dijk and the Adessium foundation. The controls from the Dutch Schizophrenia GWA study were genotyped with the support of the US National Institute of Mental Health (R.A.O.). The Leeds Bladder Cancer Study was funded by Cancer Research UK and Yorkshire Cancer Research. The Torino Bladder Cancer Case Control Study was supported by a grant to ECNIS (Environmental Cancer Risk, Nutrition and Individual Susceptibility), a network of excellence operating within the European Union Sixth Framework Program, Priority 5:‘Food Quality and Safety’ (Contract No. 513943), and by grants of the Compagnia di San Paolo, of the Italian Association for Cancer Research and of the Piedmont Region Progetti de Ricerca Sanitaria Finalizzata, Italy. The Belgian case-control study on bladder cancer risk was supported by a grant of the Flemish government, the government of the Belgian province of Limburg and the Limburg Cancer Fund., 1Department of Epidemiology, Biostatistics and Health Technology Assessment and 2Department of Urology, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands. 3Comprehensive Cancer Center East, Nijmegen, The Netherlands. 4deCODE Genetics, Reykjavik, Iceland. 5Section of Epidemiology and Biostatistics and 6Section of Experimental Oncology, Leeds Institute of Molecular Medicine, St. James’s University Hospital, Leeds, UK. 7Christie Hospital National Health Service Foundation Trust, Manchester, UK. 8Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden. 9National Institute of Environmental Health, Budapest, Hungary. 10Environmental Health Centre, Cluj-Napoca, Romania. 11State Health Institute, Banska Bystrica, Slovakia. 12Institute for Scientific Interchange (ISI) Foundation, Torino, Italy. 13Department of Epidemiology and Public Health, Imperial College, London, UK. 14Department of Genetics, Biology and Biochemistry, University of Torino, Torino, Italy. 15Unit of Cancer Epidemiology, University of Torino, Torino, Italy. 16Centre for Cancer Epidemiology and Prevention (CPO Piemonte), Torino, Italy. 17Department of Experimental and Applied Medicine, Section of Occupational Medicine and Industrial Hygiene, University of Brescia, Brescia, Italy. 18Unit of Genetic Epidemiology, Department of Public Health and Epidemiology, University of Birmingham, Birmingham, UK. 19Department of Complex Genetics, Cluster of Genetics and Cell Biology, Nutrition and Toxicology Research Institute, Maastricht University, Maastricht, The Netherlands. 20Leuven University Centre for Cancer Prevention (LUCK), Leuven, Belgium. 21Department of Medicine, University of Zaragoza, Zaragoza, Spain. 22Division of Urology, San Jorge Hospital, Huesca, Spain. 23Division of Urology, Hospital Clinico, Zaragoza, Spain. 24Department of Urology, University of Zaragoza School of Medicine, Zaragoza, Spain. 25Division of Surgical Pathology, San Jorge Hospital, Huesca, Spain. 26Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany. 27Department of Urology, Paul Gerhardt Foundation, Lutherstadt Wittenberg, Germany. 28Department of Medical Genetics, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, The Netherlands. 29University of California Los Angeles Center for Neurobehavioral Genetics, Los Angeles, USA. 30Department of Neurology, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, The Netherlands. 31Department of Medical Oncology, 32Department of Urology and 33Department of Pathology, Landspitali–University Hospital, Reykjavik, Iceland. 34Department of Urology, Zonguldak Karaelmas University, Zonguldak, Turkey. 35Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden. 36Department of General Practice, Catholic University of Leuven, Leuven, Belgium. 37Department of General Practice, Maastricht University, Maastricht, The Netherlands. 38Division of Medical Oncology, University of Zaragoza, Zaragoza, Spain. 39Division of Molecular Genetic Epidemiology, German Cancer Research Centre, Heidelberg, Germany. 40Section of Clinical Cancer Epidemiology, Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden. 41Division of Clinical Cancer Epidemiology, Department of Oncology, Institute of Clinical Sciences, The Sahlgrenska Academy, Gothenburg, Sweden. 42Gray Institute for Radiation Oncology and Biology, University of Oxford, Oxford, UK. 43Faculty of Medicine, University of Iceland, Reykjavik, Iceland. 44These authors contributed equally to this work. Correspondence should be addressed to L.A.K. (b.kiemeney@ebh.umcn.nl) or K.S. (kstefans@decode.is).

The genome-wide recombination rate varies between individuals, but the mechanism controlling this variation in humans has remained elusive. A genome-wide search identified sequence variants in the 4p16.3 region correlated with recombination rate in both males and females. These variants are located in the RNF212 gene, a putative ortholog of the ZHP-3 gene that is essential for recombinations and chiasma formation in Caenorhabditis elegans . It is noteworthy that the haplotype formed by two single-nucleotide polymorphisms (SNPs) associated with the highest recombination rate in males is associated with a low recombination rate in females. Consequently, if the frequency of the haplotype changes, the average recombination rate will increase for one sex and decrease for the other, but the sex-averaged recombination rate of the population can stay relatively constant.

The restless legs syndrome (RLS) is a common neurologic disorder characterized by an irresistible urge to move the legs. It is a major cause of sleep disruption. Periodic limb movements in sleep are detectable in most patients with RLS and represent an objective physiological metric.To search for sequence variants contributing to RLS, we performed a genomewide association study and two replication studies. To minimize phenotypic heterogeneity, we focused on patients with RLS who had objectively documented periodic limb movements in sleep. We measured serum ferritin levels, since iron depletion has been associated with the pathogenesis of RLS.In an Icelandic discovery sample of patients with RLS and periodic limb movements in sleep, we observed a genomewide significant association with a common variant in an intron of BTBD9 on chromosome 6p21.2 (odds ratio, 1.8; P=2x10(-9)). This association was replicated in a second Icelandic sample (odds ratio, 1.8; P=4x10(-4)) and a U.S. sample (odds ratio, 1.5; P=4x10(-3)). With this variant, the population attributable risk of RLS with periodic limb movements was approximately 50%. An association between the variant and periodic limb movements in sleep without RLS (and the absence of such an association for RLS without periodic limb movements) suggests that we have identified a genetic determinant of periodic limb movements in sleep (odds ratio, 1.9; P=1x10(-17)). Serum ferritin levels were decreased by 13% per allele of the at-risk variant (95% confidence interval, 5 to 20; P=0.002).We have discovered a variant associated with susceptibility to periodic limb movements in sleep. The inverse correlation of the variant with iron stores is consistent with the suspected involvement of iron depletion in the pathogenesis of the disease.

We identified a marker in LINGO1 showing genome-wide significant association (P = 1.2 × 10−9, odds ratio = 1.55) with essential tremor. LINGO1 has potent, negative regulatory influences on neuronal survival and is also important in regulating both central-nervous-system axon regeneration and oligodendrocyte maturation. An increase in the number of fusiform swellings of Purkinje cell axons in LINGO1 knockout models highlights the potential role of LINGO1 in essential tremor pathophysiology.

The investigators, recognizing that coronary artery disease (CAD), including acute myocardial infarction (MI), is the leading cause of death worldwide, carried out a genome-wide associational study on Icelandic patients with MI. Initially more than 300,000 single nucleotide polymorphisms (SNPs) were examined for any association with MI. Ultimately, the study enrolled 4587 cases and 12,769 controls. The strongest association with MI was noted with 3 correlated SNPs, all located within a 190-kb linkage disequilibrium block on chromosome 9p21. The association with MI was replicated in case-control sample sets of persons of European descent from 3 US cities. The identified variant was adjacent to the tumor suppressor genes CDKN2A and CDKN2B. It was associated with MI at a high level of significance (P = 1.2 × 10−20). The proteins encoded by these genes have a key role in regulating cell proliferation, cell senescence, and apoptosis—all important features of atherogenesis. Approximately 21% of individuals in the study population are homozygous for the variant, and it is estimated that their risk of having MI is 1.64-fold greater than for noncarriers. The risk is 2.02-fold greater for early-onset cases. The population-attributable risk was estimated as 21% for MI in general and 31% for early-onset cases. This is the first common variant found to consistently confer a substantial risk of MI, defined as an odds ratio exceeding 1.20, in multiple case-control groups of European descent. The variant poses a substantial risk from a public health viewpoint, but it explains only a small part of familial clustering of the disease and would not yield high linkage scores. The implication is that other susceptibility variants are as yet unidentified. In addition to MI, there is reason to believe that the present variant might increase the risk of CAD in general. Just how genetic variants influence the pathogenesis of MI remains to be clarified.

Bone mineral density (BMD) is the most widely used predictor of fracture risk. We performed the largest meta-analysis to date on lumbar spine and femoral neck BMD, including 17 genome-wide association studies and 32,961 individuals of European and east Asian ancestry. We tested the top BMD-associated markers for replication in 50,933 independent subjects and for association with risk of low-trauma fracture in 31,016 individuals with a history of fracture (cases) and 102,444 controls. We identified 56 loci (32 new) associated with BMD at genome-wide significance (P < 5 × 10 -8). Several of these factors cluster within the RANK-RANKL-OPG, mesenchymal stem cell differentiation, endochondral ossification and Wnt signaling pathways. However, we also discovered loci that were localized to genes not known to have a role in bone biology. Fourteen BMD-associated loci were also associated with fracture risk (P < 5 × 10 -4, Bonferroni corrected), of which six reached P < 5 × 10 -8, including at 18p11.21 (FAM210A), 7q21.3 (SLC25A13), 11q13.2 (LRP5), 4q22.1 (MEPE), 2p16.2 (SPTBN1) and 10q21.1 (DKK1). These findings shed light on the genetic architecture and pathophysiological mechanisms underlying BMD variation and fracture susceptibility. © 2012 Nature America, Inc. All rights reserved.

Most genome-wide association (GWA) studies have focused on populations of European ancestry with limited assessment of the influence of the sequence variants on populations of other ethnicities. To determine whether markers that we have recently shown to associate with Bone Mineral Density (BMD) in Europeans also associate with BMD in East-Asians we analysed 50 markers from 23 genomic loci in samples from Korea (n = 1,397) and two Chinese Hong Kong sample sets (n = 3,869 and n = 785). Through this effort we identified fourteen loci that associated with BMD in East-Asian samples using a false discovery rate (FDR) of 0.05; 1p36 (ZBTB40, P = 4.3×10 -9), 1p31 (GPR177, P = 0.00012), 3p22 (CTNNB1, P = 0.00013), 4q22 (MEPE, P = 0.0026), 5q14 (MEF2C, P = 1.3×10 -5), 6q25 (ESR1, P = 0.0011), 7p14 (STARD3NL, P = 0.00025), 7q21 (FLJ42280, P = 0.00017), 8q24 (TNFRSF11B, P = 3.4×10 -5), 11p15 (SOX6, P = 0.00033), 11q13 (LRP5, P = 0.0033), 13q14 (TNFSF11, P = 7.5×10 -5), 16q24 (FOXL1, P = 0.0010) and 17q21 (SOST, P = 0.015). Our study marks an early effort towards the challenge of cataloguing bone density variants shared by many ethnicities by testing BMD variants that have been established in Europeans, in East-Asians. © 2010 Styrkarsdottir et al., published_or_final_version

Determination of recombination rates across the human genome has been constrained by the limited resolution and accuracy of existing genetic maps and the draft genome sequence. We have genotyped 5,136 microsatellite markers for 146 families, with a total of 1,257 meiotic events, to build a high-resolution genetic map meant to: (i) improve the genetic order of polymorphic markers; (ii) improve the precision of estimates of genetic distances; (iii) correct portions of the sequence assembly and SNP map of the human genome; and (iv) build a map of recombination rates. Recombination rates are significantly correlated with both cytogenetic structures (staining intensity of G bands) and sequence (GC content, CpG motifs and poly(A)/poly(T) stretches). Maternal and paternal chromosomes show many differences in locations of recombination maxima. We detected systematic differences in recombination rates between mothers and between gametes from the same mother, suggesting that there is some underlying component determined by both genetic and environmental factors that affects maternal recombination rates.

Nat. Genet, 41, 277–279 (2009), published online 1 February 2009; corrected after print 24 March 2009 In the version of this article initially published, one sentence in the abstract and two sentences in the final paragraph of the paper were in error and have been modified. The final sentence in theabstract should read