Correction: Investigation of common, low-frequency and rare genome-wide variation in anorexia nervosa.

The fortieth author's name was listed incorrectly. The correct presentation is A Keski-Rahkonen.

Investigation of common, low-frequency and rare genome-wide variation in anorexia nervosa.

Anorexia nervosa (AN) is a complex neuropsychiatric disorder presenting with dangerously low body weight, and a deep and persistent fear of gaining weight. To date, only one genome-wide significant locus associated with AN has been identified. We performed an exome-chip based genome-wide association studies (GWAS) in 2158 cases from nine populations of European origin and 15 485 ancestrally matched controls. Unlike previous studies, this GWAS also probed association in low-frequency and rare variants. Sixteen independent variants were taken forward for in silico and de novo replication (11 common and 5 rare). No findings reached genome-wide significance. Two notable common variants were identified: rs10791286, an intronic variant in OPCML (P=9.89 × 10-6), and rs7700147, an intergenic variant (P=2.93 × 10-5). No low-frequency variant associations were identified at genome-wide significance, although the study was well-powered to detect low-frequency variants with large effect sizes, suggesting that there may be no AN loci in this genomic search space with large effect sizes.

A novel interaction between the FLJ33534 locus and smoking in obesity: a genome-wide study of 14 131 Pakistani adults.

BACKGROUND: Obesity is a complex disease caused by the interplay of genetic and lifestyle factors, but identification of gene-lifestyle interactions in obesity has remained challenging. Few large-scale studies have reported use of genome-wide approaches to investigate gene-lifestyle interactions in obesity. METHODS: In the Pakistan Risk of Myocardial Infraction Study, a cross-sectional study based in Pakistan, we calculated body mass index (BMI) variance estimates (square of the residual of inverse-normal transformed BMI z-score) in 14 131 participants and conducted genome-wide heterogeneity of variance analyses (GWHVA) for this outcome. All analyses were adjusted for age, age(2), sex and genetic ancestry. RESULTS: The GWHVA analyses identified an intronic variant, rs140133294, in the FLJ33544 gene in association with BMI variance (P-value=3.1 × 10(-8)). In explicit tests of gene × lifestyle interaction, smoking was found to significantly modify the effect of rs140133294 on BMI (Pinteraction=0.0005), whereby the minor allele (T) was associated with lower BMI in current smokers, while positively associated with BMI in never smokers. Analyses of ENCODE data at the FLJ33534 locus revealed features indicative of open chromatin and high confidence DNA-binding motifs for several transcription factors, providing suggestive biological support for a mechanism of interaction. CONCLUSIONS: In summary, we have identified a novel interaction between smoking and variation at the FLJ33534 locus in relation to BMI in people from Pakistan.

Lifestyle may modify the glucose-raising effect of genetic loci. A study in the Greek population.

BACKGROUND AND AIMS: Lifestyle habits including dietary intake and physical activity are closely associated with multiple body processes including glucose metabolism and are known to affect human health. Recent genome-wide association studies have identified several single nucleotide polymorphisms (SNPs) associated with glucose levels. The hypothesis tested here is whether a healthy lifestyle assessed via a score is associated with glycaemic traits and whether there is an interaction between the lifestyle and known glucose-raising genetic variants in association with glycaemic traits. METHODS AND RESULTS: Participants of Greek descent from the THISEAS study were included in this analysis. We developed a glucose preventive score (GPS) including dietary and physical activity characteristics. We also modelled a weighted genetic risk score (wGRS), based on 20 known glucose-raising loci, in order to investigate the impact of lifestyle-gene interaction on glucose levels. The GPS was observed to be significantly associated with lower glucose concentrations (ß ± SE: -0.083 ± 0.021 mmol/L, P = 1.6 × 10(-04)) and the wGRS, as expected, with increased glucose levels (ß ± SE: 0.020 ± 0.007 mmol/L, P = 8.4 × 10(-3)). The association of the wGRS with glucose levels was attenuated after interaction with the GPS. A higher GPS indicated decreasing glucose levels in the presence of an increasing wGRS (ß interaction ± SE: -0.019 ± 0.007 mmol/L, P = 0.014). CONCLUSION: Our results indicate that lower glucose levels underlie a healthier lifestyle and also support an interaction between the wGRS for known glycaemic loci and GPS associated with lower glucose levels. These scores could be useful tools for monitoring glucose metabolism.

The link between family history and risk of type 2 diabetes is not explained by anthropometric, lifestyle or genetic risk factors: the EPIC-InterAct study.

AIMS/HYPOTHESIS: Although a family history of type 2 diabetes is a strong risk factor for the disease, the factors mediating this excess risk are poorly understood. In the InterAct case-cohort study, we investigated the association between a family history of diabetes among different family members and the incidence of type 2 diabetes, as well as the extent to which genetic, anthropometric and lifestyle risk factors mediated this association. METHODS: A total of 13,869 individuals (including 6,168 incident cases of type 2 diabetes) had family history data available, and 6,887 individuals had complete data on all mediators. Country-specific Prentice-weighted Cox models were fitted within country, and HRs were combined using random effects meta-analysis. Lifestyle and anthropometric measurements were performed at baseline, and a genetic risk score comprising 35 polymorphisms associated with type 2 diabetes was created. RESULTS: A family history of type 2 diabetes was associated with a higher incidence of the condition (HR 2.72, 95% CI 2.48, 2.99). Adjustment for established risk factors including BMI and waist circumference only modestly attenuated this association (HR 2.44, 95% CI 2.03, 2.95); the genetic score alone explained only 2% of the family history-associated risk of type 2 diabetes. The greatest risk of type 2 diabetes was observed in those with a biparental history of type 2 diabetes (HR 5.14, 95% CI 3.74, 7.07) and those whose parents had been diagnosed with diabetes at a younger age (<50 years; HR 4.69, 95% CI 3.35, 6.58), an effect largely confined to a maternal family history. CONCLUSIONS/INTERPRETATION: Prominent lifestyle, anthropometric and genetic risk factors explained only a marginal proportion of the excess risk associated with family history, highlighting the fact that family history remains a strong, independent and easily assessed risk factor for type 2 diabetes. Discovering factors that will explain the association of family history with type 2 diabetes risk will provide important insight into the aetiology of type 2 diabetes.

Design and cohort description of the InterAct Project: an examination of the interaction of genetic and lifestyle factors on the incidence of type 2 diabetes in the EPIC Study.

AIMS/HYPOTHESIS: Studying gene-lifestyle interaction may help to identify lifestyle factors that modify genetic susceptibility and uncover genetic loci exerting important subgroup effects. Adequately powered studies with prospective, unbiased, standardised assessment of key behavioural factors for gene-lifestyle studies are lacking. This case-cohort study aims to investigate how genetic and potentially modifiable lifestyle and behavioural factors, particularly diet and physical activity, interact in their influence on the risk of developing type 2 diabetes. METHODS: Incident cases of type 2 diabetes occurring in European Prospective Investigation into Cancer and Nutrition (EPIC) cohorts between 1991 and 2007 from eight of the ten EPIC countries were ascertained and verified. Prentice-weighted Cox regression and random-effects meta-analyses were used to investigate differences in diabetes incidence by age and sex. RESULTS: A total of 12,403 verified incident cases of type 2 diabetes occurred during 3.99 million person-years of follow-up of 340,234 EPIC participants eligible for InterAct. We defined a centre-stratified subcohort of 16,154 individuals for comparative analyses. Individuals with incident diabetes who were randomly selected into the subcohort (n = 778) were included as cases in the analyses. All prevalent diabetes cases were excluded from the study. InterAct cases were followed-up for an average of 6.9 years; 49.7% were men. Mean baseline age and age at diagnosis were 55.6 and 62.5 years, mean BMI and waist circumference values were 29.4 kg/m(2) and 102.7 cm in men, and 30.1 kg/m(2) and 92.8 cm in women, respectively. Risk of type 2 diabetes increased linearly with age, with an overall HR of 1.56 (95% CI 1.48-1.64) for a 10 year age difference, adjusted for sex. A male excess in the risk of incident diabetes was consistently observed across all countries, with a pooled HR of 1.51 (95% CI 1.39-1.64), adjusted for age. CONCLUSIONS/INTERPRETATION: InterAct is a large, well-powered, prospective study that will inform our understanding of the interplay between genes and lifestyle factors on the risk of type 2 diabetes development.

Insights into the genetic architecture of osteoarthritis from stage 1 of the arcOGEN study.

OBJECTIVES: The genetic aetiology of osteoarthritis has not yet been elucidated. To enable a well-powered genome-wide association study (GWAS) for osteoarthritis, the authors have formed the arcOGEN Consortium, a UK-wide collaborative effort aiming to scan genome-wide over 7500 osteoarthritis cases in a two-stage genome-wide association scan. Here the authors report the findings of the stage 1 interim analysis. METHODS: The authors have performed a genome-wide association scan for knee and hip osteoarthritis in 3177 cases and 4894 population-based controls from the UK. Replication of promising signals was carried out in silico in five further scans (44,449 individuals), and de novo in 14 534 independent samples, all of European descent. RESULTS: None of the association signals the authors identified reach genome-wide levels of statistical significance, therefore stressing the need for corroboration in sample sets of a larger size. Application of analytical approaches to examine the allelic architecture of disease to the stage 1 genome-wide association scan data suggests that osteoarthritis is a highly polygenic disease with multiple risk variants conferring small effects. CONCLUSIONS: Identifying loci conferring susceptibility to osteoarthritis will require large-scale sample sizes and well-defined phenotypes to minimise heterogeneity.

Large scale association analysis of novel genetic loci for coronary artery disease.

BACKGROUND: Combined analysis of 2 genome-wide association studies in cases enriched for family history recently identified 7 loci (on 1p13.3, 1q41, 2q36.3, 6q25.1, 9p21, 10q11.21, and 15q22.33) that may affect risk of coronary artery disease (CAD). Apart from the 9p21 locus, the other loci await substantive replication. Furthermore, the effect of these loci on CAD risk in a broader range of individuals remains to be determined. METHODS AND RESULTS: We undertook association analysis of single nucleotide polymorphisms at each locus with CAD risk in 11,550 cases and 11,205 controls from 9 European studies. The 9p21.3 locus showed unequivocal association (rs1333049, combined odds ratio [OR]=1.20, 95% CI [1.16 to 1.25], probability value=2.81 x 10(-21)). We also confirmed association signals at 1p13.3 (rs599839, OR=1.13 [1.08 to 1.19], P=1.44 x 10(-7)), 1q41 (rs3008621, OR=1.10 [1.04 to 1.17], P=1.02 x 10(-3)), and 10q11.21 (rs501120, OR=1.11 [1.05 to 1.18], P=4.34 x 10(-4)). The associations with 6q25.1 (rs6922269, P=0.020) and 2q36.3 (rs2943634, P=0.032) were borderline and not statistically significant after correction for multiple testing. The 15q22.33 locus did not replicate. The 10q11.21 locus showed a possible sex interaction (P=0.015), with a significant effect in women (OR=1.29 [1.15 to 1.45], P=1.86 x 10(-5)) but not men (OR=1.03 [0.96 to 1.11], P=0.387). There were no other strong interactions of any of the loci with other traditional risk factors. The loci at 9p21, 1p13.3, 2q36.3, and 10q11.21 acted independently and cumulatively increased CAD risk by 15% (12% to 18%), per additional risk allele. CONCLUSIONS: The findings provide strong evidence for association between at least 4 genetic loci and CAD risk. Cumulatively, these novel loci have a significant impact on risk of CAD at least in European populations.

The DNA sequence and comparative analysis of human chromosome 10.

The finished sequence of human chromosome 10 comprises a total of 131,666,441 base pairs. It represents 99.4% of the euchromatic DNA and includes one megabase of heterochromatic sequence within the pericentromeric region of the short and long arm of the chromosome. Sequence annotation revealed 1,357 genes, of which 816 are protein coding, and 430 are pseudogenes. We observed widespread occurrence of overlapping coding genes (either strand) and identified 67 antisense transcripts. Our analysis suggests that both inter- and intrachromosomal segmental duplications have impacted on the gene count on chromosome 10. Multispecies comparative analysis indicated that we can readily annotate the protein-coding genes with current resources. We estimate that over 95% of all coding exons were identified in this study. Assessment of single base changes between the human chromosome 10 and chimpanzee sequence revealed nonsense mutations in only 21 coding genes with respect to the human sequence.

The DNA sequence and analysis of human chromosome 13.

Chromosome 13 is the largest acrocentric human chromosome. It carries genes involved in cancer including the breast cancer type 2 (BRCA2) and retinoblastoma (RB1) genes, is frequently rearranged in B-cell chronic lymphocytic leukaemia, and contains the DAOA locus associated with bipolar disorder and schizophrenia. We describe completion and analysis of 95.5 megabases (Mb) of sequence from chromosome 13, which contains 633 genes and 296 pseudogenes. We estimate that more than 95.4% of the protein-coding genes of this chromosome have been identified, on the basis of comparison with other vertebrate genome sequences. Additionally, 105 putative non-coding RNA genes were found. Chromosome 13 has one of the lowest gene densities (6.5 genes per Mb) among human chromosomes, and contains a central region of 38 Mb where the gene density drops to only 3.1 genes per Mb.

A genome-wide association study identifies a novel locus on chromosome 18q12.2 influencing white cell telomere length.

BACKGROUND: Telomere length is a predictor for a number of common age related diseases and is a heritable trait. METHODS AND RESULTS: To identify new loci associated with mean leukocyte telomere length we conducted a genome wide association study of 314,075 single nucleotide polymorphisms (SNPs) and validated the results in a second cohort (n for both cohorts combined = 2790). We identified two novel associated variants (rs2162440, p = 2.6 x 10(-6); and rs7235755, p = 5.5 x 10(-6)) on chromosome 18q12.2 in the same region as the VPS34/PIKC3C gene, which has been directly implicated in the pathway controlling telomere length variation in yeast. CONCLUSION: These results provide new insights into the pathways regulating telomere homeostasis in humans.

A genome-wide association study suggests that a locus within the ataxin 2 binding protein 1 gene is associated with hand osteoarthritis: the Treat-OA consortium.

To identify the susceptibility gene in hand osteoarthritis (OA) the authors used a two-stage approach genome-wide association study using two discovery samples (the TwinsUK cohort and the Rotterdam discovery subset; a total of 1804 subjects) and four replication samples (the Chingford Study, the Chuvasha Skeletal Aging Study, the Rotterdam replication subset and the Genetics, Arthrosis, and Progression (GARP) Study; a total of 3266 people). Five single-nucleotide polymorphisms (SNPs) had a likelihood of association with hand OA in the discovery stage and one of them (rs716508), was successfully confirmed in the replication stage (meta-analysis p = 1.81x10(-5)). The C allele conferred a reduced risk of 33% to 41% using a case-control definition. The SNP is located in intron 1 of the A2BP1 gene. This study also found that the same allele of the SNP significantly reduced bone density at both the hip and spine (p<0.01), suggesting the potential mechanism of the gene in hand OA might be via effects on subchondral bone. The authors' findings provide a potential new insight into genetic mechanisms in the development of hand OA.

Bone mineral density, osteoporosis, and osteoporotic fractures: a genome-wide association study.

BACKGROUND: Osteoporosis is diagnosed by the measurement of bone mineral density, which is a highly heritable and multifactorial trait. We aimed to identify genetic loci that are associated with bone mineral density. METHODS: In this genome-wide association study, we identified the most promising of 314 075 single nucleotide polymorphisms (SNPs) in 2094 women in a UK study. We then tested these SNPs for replication in 6463 people from three other cohorts in western Europe. We also investigated allelic expression in lymphoblast cell lines. We tested the association between the replicated SNPs and osteoporotic fractures with data from two studies. FINDINGS: We identified genome-wide evidence for an association between bone mineral density and two SNPs (p<5x10(-8)). The SNPs were rs4355801, on chromosome 8, near to the TNFRSF11B (osteoprotegerin) gene, and rs3736228, on chromosome 11 in the LRP5 (lipoprotein-receptor-related protein) gene. A non-synonymous SNP in the LRP5 gene was associated with decreased bone mineral density (rs3736228, p=6.3x10(-12) for lumbar spine and p=1.9x10(-4) for femoral neck) and an increased risk of both osteoporotic fractures (odds ratio [OR] 1.3, 95% CI 1.09-1.52, p=0.002) and osteoporosis (OR 1.3, 1.08-1.63, p=0.008). Three SNPs near the TNFRSF11B gene were associated with decreased bone mineral density (top SNP, rs4355801: p=7.6x10(-10) for lumbar spine and p=3.3x10(-8) for femoral neck) and increased risk of osteoporosis (OR 1.2, 95% CI 1.01-1.42, p=0.038). For carriers of the risk allele at rs4355801, expression of TNFRSF11B in lymphoblast cell lines was halved (p=3.0x10(-6)). 1883 (22%) of 8557 people were at least heterozygous for these risk alleles, and these alleles had a cumulative association with bone mineral density (trend p=2.3x10(-17)). The presence of both risk alleles increased the risk of osteoporotic fractures (OR 1.3, 1.08-1.63, p=0.006) and this effect was independent of bone mineral density. INTERPRETATION: Two gene variants of key biological proteins increase the risk of osteoporosis and osteoporotic fracture. The combined effect of these risk alleles on fractures is similar to that of most well-replicated environmental risk factors, and they are present in more than one in five white people, suggesting a potential role in screening.

A physical map of 30,000 human genes.

A map of 30,181 human gene-based markers was assembled and integrated with the current genetic map by radiation hybrid mapping. The new gene map contains nearly twice as many genes as the previous release, includes most genes that encode proteins of known function, and is twofold to threefold more accurate than the previous version. A redesigned, more informative and functional World Wide Web site (www.ncbi.nlm.nih.gov/genemap) provides the mapping information and associated data and annotations. This resource constitutes an important infrastructure and tool for the study of complex genetic traits, the positional cloning of disease genes, the cross-referencing of mammalian genomes, and validated human transcribed sequences for large-scale studies of gene expression.

Haplotype-based search for SNPs associated with differential type 1 diabetes risk among chromosomes carrying a specific HLA DRB1-DQA1-DQB1 haplotype.

AIM: The aim of this study was to test chromosomes carrying the same DRB1-DQA1-DQB1 haplotype for single nucleotide polymorphisms (SNPs) in the major histocompatibility complex (MHC) that might mark subgroups of the haplotype with different risks for type 1 diabetes (T1D). METHODS: Chromosomes from T1D children, their parents and non-diabetic siblings in families of the Type 1 Diabetes Genetics Consortium (T1DGC) were analysed by two haplotype-based methods: (i) logistic regression analysis restricted to phased chromosomes carrying the same DRB1-DQA1-DQB1 haplotype but differentiated by the two alleles at MHC SNPs, which were individually tested for association with T1D and (ii) homozygous parent transmission disequilibrium test (TDT) for biased transmission of a SNP allele to diabetic children from parents who are heterozygous at the SNP but homozygous for the specific DRB1-DQA1-DQB1 haplotype being evaluated. RESULTS: A number of SNPs gave nominally significant (p < 0.05) evidence of marking two subsets of the 301-501-201 haplotype that might differ with respect to their diabetogenic potency. However, none of the SNPs achieved experiment-wide significance and hence may be false-positive associations. CONCLUSIONS: We discuss limitations and possible deficiencies of our study suggesting further work that might yield more robust SNP associations marking two subgroups of a DRB1-DQA1-DQB1 haplotype with different T1D risks.

Overview of the MHC fine mapping data.

AIM: The aim of this study was to perform quality control (QC) and initial family-based association analyses on the major histocompatibility complex (MHC) single nucleotide polymorphism (SNP) and microsatellite marker data for the MHC Fine Mapping Workshop through the Type 1 Diabetes Genetics Consortium (T1DGC). METHODS: A random sample of blind duplicates was sent for analysis of QC. DNA samples collected from participants were shipped to the genotyping laboratory from several T1DGC DNA Repository sites. Quality checks including examination of plate-panel yield, marker yield, Hardy-Weinberg equilibrium, mismatch error rate, Mendelian error rate and allele distribution across plates were performed. RESULTS: Genotypes from 2325 families within nine cohorts were obtained and subjected to QC procedures. The MHC project consisted of three marker panels - two 1536 SNP sets (Illumina Golden Gate platform performed at the Wellcome Trust Sanger Institute, Cambridge, UK) and one 66 microsatellite marker panel (performed at deCODE). In the raw SNP data, the overall concordance rate was 99.1% (+/-0.02). CONCLUSIONS: The T1DGC MHC Fine Mapping project resulted in a 2300 family, 9992 genotyped individuals database comprising of two 1536 SNP panels and a 66 microsatellite panel to densely cover the 4 Mb MHC core region for use in statistical genetic analyses.

Genetic analysis of the LGI/Epitempin gene family in sporadic and familial lateral temporal lobe epilepsy.

Mutations in the LGI1/Epitempin gene cause autosomal dominant lateral temporal lobe epilepsy (ADLTE), a partial epilepsy characterized by the presence of auditory seizures. However, not all the pedigrees with a phenotype consistent with ADLTE show mutations in LGI1/Epitempin, or evidence for linkage to the 10q24 locus. Other authors as well as ourselves have found an internal repeat (EPTP, pfam# PF03736) that allowed the identification of three other genes sharing a sequence and structural similarity with LGI1/Epitempin. In this work, we present the sequencing of these genes in a set of ADLTE families without mutations in both LGI1/Epitempin and sporadic cases. No analyzed polymorphisms modified susceptibility in either the familial or sporadic forms of this partial epilepsy.

Chromosome 20 deletions in myeloid malignancies: reduction of the common deleted region, generation of a PAC/BAC contig and identification of candidate genes. UK Cancer Cytogenetics Group (UKCCG).

Deletion of the long arm of chromosome 20 represents the most common chromosomal abnormality associated with the myeloproliferative disorders (MPDs) and is also found in other myeloid malignancies including myelodysplastic syndromes (MDS) and acute myeloid leukaemia (AML). Previous studies have identified a common deleted region (CDR) spanning approximately 8 Mb. We have now used G-banding, FISH or microsatellite PCR to analyse 113 patients with a 20q deletion associated with a myeloid malignancy. Our results define a new MPD CDR of 2.7 Mb, an MDS/AML CDR of 2.6 Mb and a combined 'myeloid' CDR of 1.7 Mb. We have also constructed the most detailed physical map of this region to date--a bacterial clone map spanning 5 Mb of the chromosome which contains 456 bacterial clones and 202 DNA markers. Fifty-one expressed sequences were localized within this contig of which 37 lie within the MPD CDR and 20 within the MDS/AML CDR. Of the 16 expressed sequences (six genes and 10 unique ESTs) within the 'myeloid' CDR, five were expressed in both normal bone marrow and purified CD34 positive cells. These data identify a set of genes which are both positional and expression candidates for the target gene(s) on 20q.

Construction of yeast artificial chromosome (YAC) clone banks covering three genome equivalents and isolation of YACs containing the human gene encoding tumor necrosis factor receptor beta.

Yeast artificial chromosome (YAC) banks covering in total about three haploid genome equivalents were constructed using a human Epstein-Barr-virus-transformed B lymphocytic cell line. Two clone banks were made: 20,000 clones with average inserts of 350 kb in the pYAC4 vector and 9850 clones with average inserts of 180 kb using vectors pJS89 and pJS91. Direct comparison of pYAC4 with pJS89 and pJS91 showed pYAC4 to be the most suitable cloning vector. Two partial banks with average insert sizes of 220 kb for human endothelial cell DNA and epithelial HEp2 cell DNA were also constructed, each covering 10% of the haploid genome. A rapid, three-step PCR screening procedure for isolation of individual YAC clones was developed and used to identify two clones encoding TNF-R beta. These clones cover about 200 kb and have 170 kb in common. TNF-R beta is 9.3 kb long and contains two introns within the protein-coding sequence.

Identification and characterization of a novel human brain-specific gene, homologous to S. scrofa tmp83.5, in the chromosome 10q24 critical region for temporal lobe epilepsy and spastic paraplegia.

We describe the structure, genomic organization, and some transcription features of a human brain-specific gene previously localized to the genomic region involved in temporal lobe epilepsy and spastic paraplegia on chromosome 10q24. The gene, which consists of six exons disseminated over 16 kb of genomic DNA, is highly homologous to the porcine tmp83.5 gene and encodes a putative transmembrane protein of 141 amino acids. Unlike its porcine homolog, from which two mRNAs with different 5'-sequences are transcribed, the human gene apparently encodes three mRNA species with 3'-untranslated regions of different sizes. Mutation analysis of its coding sequence in families affected with temporal lobe epilepsy or spastic paraplegia linked to 10q24 do not support the involvement of this gene in either diseases.