A MULTILEVEL MODEL TO ADDRESS BATCH EFFECTS IN COPY NUMBER ESTIMATION USING SNP ARRAYS

Submicroscopic changes in chromosomal DNA copy number dosage are common and have been implicated in many heritable diseases and cancers. Recent high-throughput technologies have a resolution that permits the detection of segmental changes in DNA copy number that span thousands of basepairs across the genome. Genome-wide association studies (GWAS) may simultaneously screen for copy number-phenotype and SNP-phenotype associations as part of the analytic strategy. However, genome-wide array analyses are particularly susceptible to batch effects as the logistics of preparing DNA and processing thousands of arrays often involves multiple laboratories and technicians, or changes over calendar time to the reagents and laboratory equipment. Failure to adjust for batch effects can lead to incorrect inference and requires inefficient post-hoc quality control procedures that exclude regions that are associated with batch. Our work extends previous model-based approaches for copy number estimation by explicitly modeling batch effects and using shrinkage to improve locus-specific estimates of copy number uncertainty. Key features of this approach include the use of diallelic genotype calls from experimental data to estimate batch- and locus-specific parameters of background and signal without the requirement of training data. We illustrate these ideas using a study of bipolar disease and a study of chromosome 21 trisomy. The former has batch effects that dominate much of the observed variation in quantile-normalized intensities, while the latter illustrates the robustness of our approach to datasets where as many as 25% of the samples have altered copy number. Locus-specific estimates of copy number can be plotted on the copy-number scale to investigate mosaicism and guide the choice of appropriate downstream approaches for smoothing the copy number as a function of physical position. The software is open source and implemented in the R package CRLMM available at Bioconductor (http:www.bioconductor.org).

Identification and validation of copy number variants using SNP genotyping arrays from a large clinical cohort.

BACKGROUND: Genotypes obtained with commercial SNP arrays have been extensively used in many large case-control or population-based cohorts for SNP-based genome-wide association studies for a multitude of traits. Yet, these genotypes capture only a small fraction of the variance of the studied traits. Genomic structural variants (GSV) such as Copy Number Variation (CNV) may account for part of the missing heritability, but their comprehensive detection requires either next-generation arrays or sequencing. Sophisticated algorithms that infer CNVs by combining the intensities from SNP-probes for the two alleles can already be used to extract a partial view of such GSV from existing data sets. RESULTS: Here we present several advances to facilitate the latter approach. First, we introduce a novel CNV detection method based on a Gaussian Mixture Model. Second, we propose a new algorithm, PCA merge, for combining copy-number profiles from many individuals into consensus regions. We applied both our new methods as well as existing ones to data from 5612 individuals from the CoLaus study who were genotyped on Affymetrix 500K arrays. We developed a number of procedures in order to evaluate the performance of the different methods. This includes comparison with previously published CNVs as well as using a replication sample of 239 individuals, genotyped with Illumina 550K arrays. We also established a new evaluation procedure that employs the fact that related individuals are expected to share their CNVs more frequently than randomly selected individuals. The ability to detect both rare and common CNVs provides a valuable resource that will facilitate association studies exploring potential phenotypic associations with CNVs. CONCLUSION: Our new methodologies for CNV detection and their evaluation will help in extracting additional information from the large amount of SNP-genotyping data on various cohorts and use this to explore structural variants and their impact on complex traits.

A HIDDEN MARKOV MODEL FOR JOINT ESTIMATION OF GENOTYPE AND COPY NUMBER IN HIGH-THROUGHPUT SNP CHIPS

Amplifications and deletions of chromosomal DNA, as well as copy-neutral loss of heterozygosity have been associated with diseases processes. High-throughput single nucleotide polymorphism (SNP) arrays are useful for making genome-wide estimates of copy number and genotype calls. Because neighboring SNPs in high throughput SNP arrays are likely to have dependent copy number and genotype due to the underlying haplotype structure and linkage disequilibrium, hidden Markov models (HMM) may be useful for improving genotype calls and copy number estimates that do not incorporate information from nearby SNPs. We improve previous approaches that utilize a HMM framework for inference in high throughput SNP arrays by integrating copy number, genotype calls, and the corresponding confidence scores when available. Using simulated data, we demonstrate how confidence scores control smoothing in a probabilistic framework. Software for fitting HMMs to SNP array data is available in the R package ICE.

Meta-analysis of genome-wide association data identifies a risk locus for major mood disorders on 3p21.1.

The major mood disorders, which include bipolar disorder and major depressive disorder (MDD), are considered heritable traits, although previous genetic association studies have had limited success in robustly identifying risk loci. We performed a meta-analysis of five case-control cohorts for major mood disorder, including over 13,600 individuals genotyped on high-density SNP arrays. We identified SNPs at 3p21.1 associated with major mood disorders (rs2251219, P = 3.63 x 10(-8); odds ratio = 0.87; 95% confidence interval, 0.83-0.92), with supportive evidence for association observed in two out of three independent replication cohorts. These results provide an example of a shared genetic susceptibility locus for bipolar disorder and MDD.

Loss-of-Function Mutations in PTPN11 Cause Metachondromatosis, but Not Ollier Disease or Maffucci Syndrome.

Metachondromatosis (MC) is a rare, autosomal dominant, incompletely penetrant combined exostosis and enchondromatosis tumor syndrome. MC is clinically distinct from other multiple exostosis or multiple enchondromatosis syndromes and is unlinked to EXT1 and EXT2, the genes responsible for autosomal dominant multiple osteochondromas (MO). To identify a gene for MC, we performed linkage analysis with high-density SNP arrays in a single family, used a targeted array to capture exons and promoter sequences from the linked interval in 16 participants from 11 MC families, and sequenced the captured DNA using high-throughput parallel sequencing technologies. DNA capture and parallel sequencing identified heterozygous putative loss-of-function mutations in PTPN11 in 4 of the 11 families. Sanger sequence analysis of PTPN11 coding regions in a total of 17 MC families identified mutations in 10 of them (5 frameshift, 2 nonsense, and 3 splice-site mutations). Copy number analysis of sequencing reads from a second targeted capture that included the entire PTPN11 gene identified an additional family with a 15 kb deletion spanning exon 7 of PTPN11. Microdissected MC lesions from two patients with PTPN11 mutations demonstrated loss-of-heterozygosity for the wild-type allele. We next sequenced PTPN11 in DNA samples from 54 patients with the multiple enchondromatosis disorders Ollier disease or Maffucci syndrome, but found no coding sequence PTPN11 mutations. We conclude that heterozygous loss-of-function mutations in PTPN11 are a frequent cause of MC, that lesions in patients with MC appear to arise following a "second hit," that MC may be locus heterogeneous since 1 familial and 5 sporadically occurring cases lacked obvious disease-causing PTPN11 mutations, and that PTPN11 mutations are not a common cause of Ollier disease or Maffucci syndrome.

Computational and statistical analysis of copy number variants in normal and cancer genomes

AbstractAlthough the genomes from any two human individuals are more than 99.99% identical at the sequence level, some structural variation can be observed. Differences between genomes include single nucleotide polymorphism (SNP), inversion and copy number changes (gain or loss of DNA). The latter can range from submicroscopic events (CNVs, at least 1kb in size) to complete chromosomal aneuploidies. Small copy number variations have often no (lethal) consequences to the cell, but a few were associated to disease susceptibility and phenotypic variations. Larger re-arrangements (i.e. complete chromosome gain) are frequently associated with more severe consequences on health such as genomic disorders and cancer. High-throughput technologies like DNA microarrays enable the detection of CNVs in a genome-wide fashion. Since the initial catalogue of CNVs in the human genome in 2006, there has been tremendous interest in CNVs both in the context of population and medical genetics. Understanding CNV patterns within and between human populations is essential to elucidate their possible contribution to disease. But genome analysis is a challenging task; the technology evolves rapidly creating needs for novel, efficient and robust analytical tools which need to be compared with existing ones. Also, while the link between CNV and disease has been established, the relative CNV contribution is not fully understood and the predisposition to disease from CNVs of the general population has not been yet investigated.During my PhD thesis, I worked on several aspects related to CNVs. As l will report in chapter 3, ! was interested in computational methods to detect CNVs from the general population. I had access to the CoLaus dataset, a population-based study with more than 6,000 participants from the Lausanne area. All these individuals were analysed on SNP arrays and extensive clinical information were available. My work explored existing CNV detection methods and I developed a variety of metrics to compare their performance. Since these methods were not producing entirely satisfactory results, I implemented my own method which outperformed two existing methods. I also devised strategies to combine CNVs from different individuals into CNV regions.I was also interested in the clinical impact of CNVs in common disease (chapter 4). Through an international collaboration led by the Centre Hospitalier Universitaire Vaudois (CHUV) and the Imperial College London I was involved as a main data analyst in the investigation of a rare deletion at chromosome 16p11 detected in obese patients. Specifically, we compared 8,456 obese patients and 11,856 individuals from the general population and we found that the deletion was accounting for 0.7% of the morbid obesity cases and was absent in healthy non- obese controls. This highlights the importance of rare variants with strong impact and provides new insights in the design of clinical studies to identify the missing heritability in common disease.Furthermore, I was interested in the detection of somatic copy number alterations (SCNA) and their consequences in cancer (chapter 5). This project was a collaboration initiated by the Ludwig Institute for Cancer Research and involved other groups from the Swiss Institute of Bioinformatics, the CHUV and Universities of Lausanne and Geneva. The focus of my work was to identify genes with altered expression levels within somatic copy number alterations (SCNA) in seven metastatic melanoma ceil lines, using CGH and SNP arrays, RNA-seq, and karyotyping. Very few SCNA genes were shared by even two melanoma samples making it difficult to draw any conclusions at the individual gene level. To overcome this limitation, I used a network-guided analysis to determine whether any pathways, defined by amplified or deleted genes, were common among the samples. Six of the melanoma samples were potentially altered in four pathways and five samples harboured copy-number and expression changes in components of six pathways. In total, this approach identified 28 pathways. Validation with two external, large melanoma datasets confirmed all but three of the detected pathways and demonstrated the utility of network-guided approaches for both large and small datasets analysis.RésuméBien que le génome de deux individus soit similaire à plus de 99.99%, des différences de structure peuvent être observées. Ces différences incluent les polymorphismes simples de nucléotides, les inversions et les changements en nombre de copies (gain ou perte d'ADN). Ces derniers varient de petits événements dits sous-microscopiques (moins de 1kb en taille), appelés CNVs (copy number variants) jusqu'à des événements plus large pouvant affecter des chromosomes entiers. Les petites variations sont généralement sans conséquence pour la cellule, toutefois certaines ont été impliquées dans la prédisposition à certaines maladies, et à des variations phénotypiques dans la population générale. Les réarrangements plus grands (par exemple, une copie additionnelle d'un chromosome appelée communément trisomie) ont des répercutions plus grave pour la santé, comme par exemple dans certains syndromes génomiques et dans le cancer. Les technologies à haut-débit telle les puces à ADN permettent la détection de CNVs à l'échelle du génome humain. La cartographie en 2006 des CNV du génome humain, a suscité un fort intérêt en génétique des populations et en génétique médicale. La détection de différences au sein et entre plusieurs populations est un élément clef pour élucider la contribution possible des CNVs dans les maladies. Toutefois l'analyse du génome reste une tâche difficile, la technologie évolue très rapidement créant de nouveaux besoins pour le développement d'outils, l'amélioration des précédents, et la comparaison des différentes méthodes. De plus, si le lien entre CNV et maladie a été établit, leur contribution précise n'est pas encore comprise. De même que les études sur la prédisposition aux maladies par des CNVs détectés dans la population générale n'ont pas encore été réalisées.Pendant mon doctorat, je me suis concentré sur trois axes principaux ayant attrait aux CNV. Dans le chapitre 3, je détaille mes travaux sur les méthodes d'analyses des puces à ADN. J'ai eu accès aux données du projet CoLaus, une étude de la population de Lausanne. Dans cette étude, le génome de plus de 6000 individus a été analysé avec des puces SNP et de nombreuses informations cliniques ont été récoltées. Pendant mes travaux, j'ai utilisé et comparé plusieurs méthodes de détection des CNVs. Les résultats n'étant pas complètement satisfaisant, j'ai implémenté ma propre méthode qui donne de meilleures performances que deux des trois autres méthodes utilisées. Je me suis aussi intéressé aux stratégies pour combiner les CNVs de différents individus en régions.Je me suis aussi intéressé à l'impact clinique des CNVs dans le cas des maladies génétiques communes (chapitre 4). Ce projet fut possible grâce à une étroite collaboration avec le Centre Hospitalier Universitaire Vaudois (CHUV) et l'Impérial College à Londres. Dans ce projet, j'ai été l'un des analystes principaux et j'ai travaillé sur l'impact clinique d'une délétion rare du chromosome 16p11 présente chez des patients atteints d'obésité. Dans cette collaboration multidisciplinaire, nous avons comparés 8'456 patients atteint d'obésité et 11 '856 individus de la population générale. Nous avons trouvés que la délétion était impliquée dans 0.7% des cas d'obésité morbide et était absente chez les contrôles sains (non-atteint d'obésité). Notre étude illustre l'importance des CNVs rares qui peuvent avoir un impact clinique très important. De plus, ceci permet d'envisager une alternative aux études d'associations pour améliorer notre compréhension de l'étiologie des maladies génétiques communes.Egalement, j'ai travaillé sur la détection d'altérations somatiques en nombres de copies (SCNA) et de leurs conséquences pour le cancer (chapitre 5). Ce projet fut une collaboration initiée par l'Institut Ludwig de Recherche contre le Cancer et impliquant l'Institut Suisse de Bioinformatique, le CHUV et les Universités de Lausanne et Genève. Je me suis concentré sur l'identification de gènes affectés par des SCNAs et avec une sur- ou sous-expression dans des lignées cellulaires dérivées de mélanomes métastatiques. Les données utilisées ont été générées par des puces ADN (CGH et SNP) et du séquençage à haut débit du transcriptome. Mes recherches ont montrées que peu de gènes sont récurrents entre les mélanomes, ce qui rend difficile l'interprétation des résultats. Pour contourner ces limitations, j'ai utilisé une analyse de réseaux pour définir si des réseaux de signalisations enrichis en gènes amplifiés ou perdus, étaient communs aux différents échantillons. En fait, parmi les 28 réseaux détectés, quatre réseaux sont potentiellement dérégulés chez six mélanomes, et six réseaux supplémentaires sont affectés chez cinq mélanomes. La validation de ces résultats avec deux larges jeux de données publiques, a confirmée tous ces réseaux sauf trois. Ceci démontre l'utilité de cette approche pour l'analyse de petits et de larges jeux de données.Résumé grand publicL'avènement de la biologie moléculaire, en particulier ces dix dernières années, a révolutionné la recherche en génétique médicale. Grâce à la disponibilité du génome humain de référence dès 2001, de nouvelles technologies telles que les puces à ADN sont apparues et ont permis d'étudier le génome dans son ensemble avec une résolution dite sous-microscopique jusque-là impossible par les techniques traditionnelles de cytogénétique. Un des exemples les plus importants est l'étude des variations structurales du génome, en particulier l'étude du nombre de copies des gènes. Il était établi dès 1959 avec l'identification de la trisomie 21 par le professeur Jérôme Lejeune que le gain d'un chromosome supplémentaire était à l'origine de syndrome génétique avec des répercussions graves pour la santé du patient. Ces observations ont également été réalisées en oncologie sur les cellules cancéreuses qui accumulent fréquemment des aberrations en nombre de copies (telles que la perte ou le gain d'un ou plusieurs chromosomes). Dès 2004, plusieurs groupes de recherches ont répertorié des changements en nombre de copies dans des individus provenant de la population générale (c'est-à-dire sans symptômes cliniques visibles). En 2006, le Dr. Richard Redon a établi la première carte de variation en nombre de copies dans la population générale. Ces découvertes ont démontrées que les variations dans le génome était fréquentes et que la plupart d'entre elles étaient bénignes, c'est-à-dire sans conséquence clinique pour la santé de l'individu. Ceci a suscité un très grand intérêt pour comprendre les variations naturelles entre individus mais aussi pour mieux appréhender la prédisposition génétique à certaines maladies.Lors de ma thèse, j'ai développé de nouveaux outils informatiques pour l'analyse de puces à ADN dans le but de cartographier ces variations à l'échelle génomique. J'ai utilisé ces outils pour établir les variations dans la population suisse et je me suis consacré par la suite à l'étude de facteurs pouvant expliquer la prédisposition aux maladies telles que l'obésité. Cette étude en collaboration avec le Centre Hospitalier Universitaire Vaudois a permis l'identification d'une délétion sur le chromosome 16 expliquant 0.7% des cas d'obésité morbide. Cette étude a plusieurs répercussions. Tout d'abord elle permet d'effectuer le diagnostique chez les enfants à naître afin de déterminer leur prédisposition à l'obésité. Ensuite ce locus implique une vingtaine de gènes. Ceci permet de formuler de nouvelles hypothèses de travail et d'orienter la recherche afin d'améliorer notre compréhension de la maladie et l'espoir de découvrir un nouveau traitement Enfin notre étude fournit une alternative aux études d'association génétique qui n'ont eu jusqu'à présent qu'un succès mitigé.Dans la dernière partie de ma thèse, je me suis intéressé à l'analyse des aberrations en nombre de copies dans le cancer. Mon choix s'est porté sur l'étude de mélanomes, impliqués dans le cancer de la peau. Le mélanome est une tumeur très agressive, elle est responsable de 80% des décès des cancers de la peau et est souvent résistante aux traitements utilisés en oncologie (chimiothérapie, radiothérapie). Dans le cadre d'une collaboration entre l'Institut Ludwig de Recherche contre le Cancer, l'Institut Suisse de Bioinformatique, le CHUV et les universités de Lausanne et Genève, nous avons séquencés l'exome (les gènes) et le transcriptome (l'expression des gènes) de sept mélanomes métastatiques, effectués des analyses du nombre de copies par des puces à ADN et des caryotypes. Mes travaux ont permis le développement de nouvelles méthodes d'analyses adaptées au cancer, d'établir la liste des réseaux de signalisation cellulaire affectés de façon récurrente chez le mélanome et d'identifier deux cibles thérapeutiques potentielles jusqu'alors ignorées dans les cancers de la peau.

Homozygosity mapping reveals novel and known mutations in Pakistani families with inherited retinal dystrophies.

Inherited retinal dystrophies are phenotypically and genetically heterogeneous. This extensive heterogeneity poses a challenge when performing molecular diagnosis of patients, especially in developing countries. In this study, we applied homozygosity mapping as a tool to reduce the complexity given by genetic heterogeneity and identify disease-causing variants in consanguineous Pakistani pedigrees. DNA samples from eight families with autosomal recessive retinal dystrophies were subjected to genome wide homozygosity mapping (seven by SNP arrays and one by STR markers) and genes comprised within the detected homozygous regions were analyzed by Sanger sequencing. All families displayed consistent autozygous genomic regions. Sequence analysis of candidate genes identified four previously-reported mutations in CNGB3, CNGA3, RHO, and PDE6A, as well as three novel mutations: c.2656C > T (p.L886F) in RPGRIP1, c.991G > C (p.G331R) in CNGA3, and c.413-1G > A (IVS6-1G > A) in CNGB1. This latter mutation impacted pre-mRNA splicing of CNGB1 by creating a -1 frameshift leading to a premature termination codon. In addition to better delineating the genetic landscape of inherited retinal dystrophies in Pakistan, our data confirm that combining homozygosity mapping and candidate gene sequencing is a powerful approach for mutation identification in populations where consanguineous unions are common.

Évaluation du caryotype moléculaire en tant qu’outil diagnostique chez les enfants avec déficience intellectuelle et/ou malformations congénitales

Le caryotype moléculaire permet d’identifier un CNV chez 10-14% des individus atteints de déficience intellectuelle et/ou de malformations congénitales. C’est pourquoi il s’agit maintenant de l’analyse de première intention chez ces patients. Toutefois, le rendement diagnostique n’est pas aussi bien défini en contexte prénatal et l’identification de CNVs de signification clinique incertaine y est particulièrement problématique à cause du risque d’interruption de grossesse. Nous avons donc testé 49 fœtus avec malformations majeures et un caryotype conventionnel normal avec une micropuce CGH pangénomique, et obtenu un diagnostic dans 8,2% des cas. Par ailleurs, des micropuces à très haute résolution combinant le caryotype moléculaire et le génotypage de SNPs ont récemment été introduites sur le marché. En plus d’identifier les CNVs, ces plateformes détectent les LOHs, qui peuvent indiquer la présence d’une mutation homozygote ou de disomie uniparentale. Ces anomalies pouvant être associées à la déficience intellectuelle ou à des malformations, leur détection est particulièrement intéressante pour les patients dont le phénotype reste inexpliqué. Cependant, le rendement diagnostique de ces plateformes n’est pas confirmé, et l’utilité clinique réelle des LOHs n’est toujours pas établie. Nous avons donc testé 21 enfants atteints de déficience intellectuelle pour qui les méthodes standards d’analyse génétique n’avaient pas résulté en un diagnostic, et avons pu faire passer le rendement diagnostique de 14,3% à 28,6% grâce à l’information fournie par les LOHs. Cette étude démontre l’utilité clinique d’une micropuce CGH pangénomique chez des fœtus avec malformations, de même que celle d’une micropuce SNP chez des enfants avec déficience intellectuelle.

Stratégie de détection des anomalies chromosomiques dans les leucémies aiguës pédiatriques

L’analyse des anomalies génomiques récurrentes est importante pour établir le diagnostic, le pronostic et pour orienter la thérapie des leucémies aiguës pédiatriques. L’objectif de notre étude est d’élaborer une stratégie optimale pour détecter les anomalies chromosomiques dans les leucémies aiguës lymphoblastiques (LAL) et myéloïdes (LAM) des enfants. Pour ce faire, nous avons caractérisé au caryotype, avec des panels d’hybridation in situ en fluorescence (FISH), par RT-PCR et par l’index d’ADN 253 leucémies de novo reçues au CHU Sainte-Justine entre 2005 et 2011 (186 LAL-B, 27 LAL-T et 40 LAM). Nous avons réussi à optimiser la détection des anomalies chromosomiques dans les trois types de leucémies, avec des fréquences de 93,5% dans les LAL-B (174/186), 66,7% dans les LAL-T (18/27) et 90% dans les LAM (36/40). Nos résultats suggèrent d’utiliser plusieurs tests génétiques concomitants afin d’optimiser la détection des anomalies génomiques dans les LAL et les LAM de novo pédiatriques.

Search for Genomic Alterations in Monozygotic Twins Discordant for Cleft Lip and/or Palate

Phenotypically discordant monozygotic twins offer the possibility of gene discovery through delineation of molecular abnormalities in one member of the twin pair. One proposed mechanism of discordance is postzygotically occurring genomic alterations resulting from mitotic recombination and other somatic changes. Detection of altered genomic fragments can reveal candidate gene loci that can be verified through additional analyses. We investigated this hypothesis using array comparative genomic hybridization; the 50K and 250K Affymetrix GeneChip (R) SNP arrays and an Illumina custom array consisting of 1,536 SNPs, to scan for genomic alterations in a sample of monozygotic twin pairs with discordant cleft lip and/or palate phenotypes. Paired analysis for deletions, amplifications and loss of heterozygosity, along with sequence verification of SNPs with discordant genotype calls did not reveal any genomic discordance between twin pairs in lymphocyte DNA samples. Our results demonstrate that postzygotic genomic alterations are not a common cause of monozygotic twin discordance for isolated cleft lip and/or palate. However, rare or balanced genomic alterations, tissue-specific events and small aberrations beyond the detection level of our experimental approach cannot be ruled out. The stability of genomes we observed in our study samples also suggests that detection of discordant events in other monozygotic twin pairs would be remarkable and of potential disease significance.

Genome-wide DNA profiling of marginal zone lymphomas identifies subtype-specific lesions with an impact on the clinical outcome

Marginal zone B-cell lymphomas (MZLs) have been divided into 3 distinct subtypes (extranodal MZLs of mucosa-associated lymphoid tissue [MALT] type, nodal MZLs, and splenic MZLs). Nevertheless, the relationship between the subtypes is still unclear. We performed a comprehensive analysis of genomic DNA copy number changes in a very large series of MZL cases with the aim of addressing this question. Samples from 218 MZL patients (25 nodal, 57 MALT, 134 splenic, and 2 not better specified MZLs) were analyzed with the Affymetrix Human Mapping 250K SNP arrays, and the data combined with matched gene expression in 33 of 218 cases. MALT lymphoma presented significantly more frequently gains at 3p, 6p, 18p, and del(6q23) (TNFAIP3/A20), whereas splenic MZLs was associated with del(7q31), del(8p). Nodal MZLs did not show statistically significant differences compared with MALT lymphoma while lacking the splenic MZLs-related 7q losses. Gains of 3q and 18q were common to all 3 subtypes. del(8p) was often present together with del(17p) (TP53). Although del(17p) did not determine a worse outcome and del(8p) was only of borderline significance, the presence of both deletions had a highly significant negative impact on the outcome of splenic MZLs.

ASSOCIATON TESTS THAT ACCOMMODATE GENOTYPING ERRORS

High-throughput SNP arrays provide estimates of genotypes for up to one million loci, often used in genome-wide association studies. While these estimates are typically very accurate, genotyping errors do occur, which can influence in particular the most extreme test statistics and p-values. Estimates for the genotype uncertainties are also available, although typically ignored. In this manuscript, we develop a framework to incorporate these genotype uncertainties in case-control studies for any genetic model. We verify that using the assumption of a “local alternative” in the score test is very reasonable for effect sizes typically seen in SNP association studies, and show that the power of the score test is simply a function of the correlation of the genotype probabilities with the true genotypes. We demonstrate that the power to detect a true association can be substantially increased for difficult to call genotypes, resulting in improved inference in association studies.

The NF-{kappa}B negative regulator TNFAIP3 (A20) is inactivated by somatic mutations and genomic deletions in marginal zone lymphomas

Unique and shared cytogenetic abnormalities have been documented for marginal zone lymphomas (MZLs) arising at different sites. Recently, homozygous deletions of the chromosomal band 6q23, involving the tumor necrosis factor alpha-induced protein 3 (TNFAIP3, A20) gene, a negative regulator of NF-kappaB, were described in ocular adnexal MZL, suggesting a role for A20 as a tumor suppressor in this disease. Here, we investigated inactivation of A20 by DNA mutations or deletions in a panel of extranodal MZL (EMZL), nodal MZL (NMZL), and splenic MZL (SMZL). Inactivating mutations encoding truncated A20 proteins were identified in 6 (19%) of 32 MZLs, including 2 (18%) of 11 EMZLs, 3 (33%) of 9 NMZLs, and 1 (8%) of 12 SMZLs. Two additional unmutated nonsplenic MZLs also showed monoallelic or biallelic A20 deletions by fluorescent in situ hybridization (FISH) and/or SNP-arrays. Thus, A20 inactivation by either somatic mutation and/or deletion represents a common genetic aberration across all MZL subtypes, which may contribute to lymphomagenesis by inducing constitutive NF-kappaB activation.

Contribution of Genetic Background and Clinical Risk Factors to Low-Trauma Fractures in Human Immunodeficiency Virus (HIV)-Positive Persons: The Swiss HIV Cohort Study.

Background.  The impact of human genetic background on low-trauma fracture (LTF) risk has not been evaluated in the context of human immunodeficiency virus (HIV) and clinical LTF risk factors. Methods.  In the general population, 6 common single-nucleotide polymorphisms (SNPs) associate with LTF through genome-wide association study. Using genome-wide SNP arrays and imputation, we genotyped these SNPs in HIV-positive, white Swiss HIV Cohort Study participants. We included 103 individuals with a first, physician-validated LTF and 206 controls matched on gender, whose duration of observation and whose antiretroviral therapy start dates were similar using incidence density sampling. Analyses of nongenetic LTF risk factors were based on 158 cases and 788 controls. Results.  A genetic risk score built from the 6 LTF-associated SNPs did not associate with LTF risk, in both models including and not including parental hip fracture history. The contribution of clinical LTF risk factors was limited in our dataset. Conclusions.  Genetic LTF markers with a modest effect size in the general population do not improve fracture prediction in persons with HIV, in whom clinical LTF risk factors are prevalent in both cases and controls.

Genome-wide association studies in oesophageal adenocarcinoma and Barrett's oesophagus: a large-scale meta-analysis

Background: Esophageal adenocarcinoma (EA) is one of the fastest rising cancers in western countries. Barrett’s Esophagus (BE) is the premalignant precursor of EA. However, only a subset of BE patients develop EA, which complicates the clinical management in the absence of valid predictors. Genetic risk factors for BE and EA are incompletely understood. This study aimed to identify novel genetic risk factors for BE and EA.Methods: Within an international consortium of groups involved in the genetics of BE/EA, we performed the first meta-analysis of all genome-wide association studies (GWAS) available, involving 6,167 BE patients, 4,112 EA patients, and 17,159 representative controls, all of European ancestry, genotyped on Illumina high-density SNP-arrays, collected from four separate studies within North America, Europe, and Australia. Meta-analysis was conducted using the fixed-effects inverse variance-weighting approach. We used the standard genome-wide significant threshold of 5×10-8 for this study. We also conducted an association analysis following reweighting of loci using an approach that investigates annotation enrichment among the genome-wide significant loci. The entire GWAS-data set was also analyzed using bioinformatics approaches including functional annotation databases as well as gene-based and pathway-based methods in order to identify pathophysiologically relevant cellular pathways.Findings: We identified eight new associated risk loci for BE and EA, within or near the CFTR (rs17451754, P=4·8×10-10), MSRA (rs17749155, P=5·2×10-10), BLK (rs10108511, P=2·1×10-9), KHDRBS2 (rs62423175, P=3·0×10-9), TPPP/CEP72 (rs9918259, P=3·2×10-9), TMOD1 (rs7852462, P=1·5×10-8), SATB2 (rs139606545, P=2·0×10-8), and HTR3C/ABCC5 genes (rs9823696, P=1·6×10-8). A further novel risk locus at LPA (rs12207195, posteriori probability=0·925) was identified after re-weighting using significantly enriched annotations. This study thereby doubled the number of known risk loci. The strongest disease pathways identified (P<10-6) belong to muscle cell differentiation and to mesenchyme development/differentiation, which fit with current pathophysiological BE/EA concepts. To our knowledge, this study identified for the first time an EA-specific association (rs9823696, P=1·6×10-8) near HTR3C/ABCC5 which is independent of BE development (P=0·45).Interpretation: The identified disease loci and pathways reveal new insights into the etiology of BE and EA. Furthermore, the EA-specific association at HTR3C/ABCC5 may constitute a novel genetic marker for the prediction of transition from BE to EA. Mutations in CFTR, one of the new risk loci identified in this study, cause cystic fibrosis (CF), the most common recessive disorder in Europeans. Gastroesophageal reflux (GER) belongs to the phenotypic CF-spectrum and represents the main risk factor for BE/EA. Thus, the CFTR locus may trigger a common GER-mediated pathophysiology.