Identification of multiple rare variants associated with a disease

Identifying rare variants that are responsible for complex disease has been promoted by advances in sequencing technologies. However, statistical methods that can handle the vast amount of data generated and that can interpret the complicated relationship between disease and these variants have lagged. We apply a zero-inflated Poisson regression model to take into account the excess of zeros caused by the extremely low frequency of the 24,487 exonic variants in the Genetic Analysis Workshop 17 data. We grouped the 697 subjects in the data set as Europeans, Asians, and Africans based on principal components analysis and found the total number of rare variants per gene for each individual. We then analyzed these collapsed variants based on the assumption that rare variants are enriched in a group of people affected by a disease compared to a group of unaffected people. We also tested the hypothesis with quantitative traits Q1, Q2, and Q4. Analyses performed on the combined 697 individuals and on each ethnic group yielded different results. For the combined population analysis, we found that UGT1A1, which was not part of the simulation model, was associated with disease liability and that FLT1, which was a causal locus in the simulation model, was associated with Q1. Of the causal loci in the simulation models, FLT1 and KDR were associated with Q1 and VNN1 was correlated with Q2. No significant genes were associated with Q4. These results show the feasibility and capability of our new statistical model to detect multiple rare variants influencing disease risk

The mass assembly of galaxy groups and the evolution of the magnitude gap

We investigate the assembly of groups and clusters of galaxies using the Millennium dark matter simulation and the associated gas simulations and semi-analytic catalogues of galaxies. In particular, in order to find an observable quantity that could be used to identify early-formed groups, we study the development of the difference in magnitude between their brightest galaxies to assess the use of magnitude gaps as possible indicators. We select galaxy groups and clusters at redshift z=1 with dark matter halo mass M(R200) > 1E13/h Msun, and trace their properties until the present time (z=0). We consider only the systems with X-ray luminosity L_X> 0.25E42/h^2 erg/s at z=0. While it is true that a large magnitude gap between the two brightest galaxies of a particular group often indicates that a large fraction of its mass was assembled at an early epoch, it is not a necessary condition. More than 90% of fossil groups defined on the basis of their magnitude gaps (at any epoch between 0<z<1) cease to be fossils within 4 Gyr, mostly because other massive galaxies are assembled within their cores, even though most of the mass in their haloes might have been assembled at early times. We show that, compared to the conventional definition of fossil galaxy groups based on the magnitude gap Delta m(12)> 2 (in the R-band, within 0.5R200 of the centre of the group), an alternative criterion Delta m(14)>2.5 (within the same radius) finds 50% more early-formed systems, and those that on average retain their fossil phase longer. However, the conventional criterion performs marginally better at finding early-formed groups at the high-mass end of groups. Nevertheless, both criteria fail to identify a majority of the early-formed systems.Comment: 16 pages, 11 figures, 2 tables. Accepted for publication in MNRA

A framework for interpreting genome-wide association studies of psychiatric disorders

Genome-wide association studies (GWAS) have yielded a plethora of new findings in the past 3 years. By early 2009, GWAS on 47 samples of subjects with attention-deficit hyperactivity disorder, autism, bipolar disorder, major depressive disorder and schizophrenia will be completed. Taken together, these GWAS constitute the largest biological experiment ever conducted in psychiatry (59 000 independent cases and controls, 7700 family trios and >40 billion genotypes). We know that GWAS can work, and the question now is whether it will work for psychiatric disorders. In this review, we describe these studies, the Psychiatric GWAS Consortium for meta-analyses of these data, and provide a logical framework for interpretation of some of the conceivable outcomes

Family- and population-based designs identify different rare causal variants

Both family- and population-based samples are used to identify genetic variants associated with phenotypes. Each strategy has demonstrated advantages, but their ability to identify rare variants and genes containing rare variants is unclear. To compare these two study designs in the identification of rare causal variants, we applied various methods to the population- and family-based data simulated by the Genetic Analysis Workshop 17 with knowledge of the simulated model. Our results suggest that different variants can be identified by different study designs. Family-based and population-based study designs can be complementary in the identification of rare causal variants and should be considered in future studies

Mathematical modelling of CAD systems in Building Engineering

[EN] There exists a wide range of CAD systems devoted to model three-dimensional objects. Based on an intuitive creation and transformation of basic geometrical objects, the mathematical foundation of such systems is generally unknown to their users. The incorporation of this kind of software in Math classes is a fundamental key to get the attention of students of those degrees for which CAD systems are not only attractive, but also extremely important in the future professional career. The current paper deals with the experience carried out in this regard during the last five years by students of the Building Engineering Degree of the University of Seville. The methodological search of mathematical models that allow them to construct virtually real buildings has improved not only the process of teaching-learning, but also their interest in the subject and their academic efficiency. A virtual tour through their constructions is a perfect excuse to deal also with the mathematical foundation on which they are based on.[ES] Existe una amplia gama de sistemas CAD destinados a modelar objetos tridimensionales. Basados en una creación y transformación intuitiva de objetos geométricos básicos, el fundamento matemático de estas herramientas es generalmente desconocido por sus usuarios. La incorporación de las mismas en el aula de Matemáticas es una pieza clave para lograr captar la atención del alumnado de aquellas titulaciones universitarias en las que los sistemas CAD no sólo son atrayentes, sino que son además de suma importancia para la futura vida profesional. El presente artículo trata acerca de la experiencia docente llevada a cabo en este sentido durante los últimos cinco años en el Grado de Ingeniería de Edificación de la Universidad de Sevilla. La búsqueda metodológica de modelos matemáticos que les permita construir virtualmente edificios reales ha mejorado no sólo el proceso de enseñanza-aprendizaje, sino también su interés en la materia y su rendimiento académico. Un recorrido virtual a través de sus construcciones es una perfecta excusa para tratar también el fundamento matemático en los que se basan los mismosFalcón Ganfornina, RM. (2015). Modelización matemática de sistemas CAD en Edificación. Modelling in Science Education and Learning. 8(2):145-194. doi:10.4995/msel.2015.3258.SWORD1451948

A multi-stage genome-wide association study of bladder cancer identifies multiple susceptibility loci.

We conducted a multi-stage, genome-wide association study of bladder cancer with a primary scan of 591,637 SNPs in 3,532 affected individuals (cases) and 5,120 controls of European descent from five studies followed by a replication strategy, which included 8,382 cases and 48,275 controls from 16 studies. In a combined analysis, we identified three new regions associated with bladder cancer on chromosomes 22q13.1, 19q12 and 2q37.1: rs1014971, (P = 8 × 10⁻¹²) maps to a non-genic region of chromosome 22q13.1, rs8102137 (P = 2 × 10⁻¹¹) on 19q12 maps to CCNE1 and rs11892031 (P = 1 × 10⁻⁷) maps to the UGT1A cluster on 2q37.1. We confirmed four previously identified genome-wide associations on chromosomes 3q28, 4p16.3, 8q24.21 and 8q24.3, validated previous candidate associations for the GSTM1 deletion (P = 4 × 10⁻¹¹) and a tag SNP for NAT2 acetylation status (P = 4 × 10⁻¹¹), and found interactions with smoking in both regions. Our findings on common variants associated with bladder cancer risk should provide new insights into the mechanisms of carcinogenesis

Genome-wide association studies and genetic architecture of common human diseases

Genome-wide association scans provide the first successful method to identify genetic variation contributing to risk for common complex disease. Progress in identifying genes associated with melanoma show complex relationships between genes for pigmentation and the development of melanoma. Novel risk loci account for only a small fraction of the genetic variation contributing to this and many other diseases. Large meta-analyses find additional variants, but there is current debate about the contribution of common polymorphisms, rare polymorphisms or mutations to disease risk

Identifying Selected Regions from Heterozygosity and Divergence Using a Light-Coverage Genomic Dataset from Two Human Populations

When a selective sweep occurs in the chromosomal region around a target gene in two populations that have recently separated, it produces three dramatic genomic consequences: 1) decreased multi-locus heterozygosity in the region; 2) elevated or diminished genetic divergence (FST) of multiple polymorphic variants adjacent to the selected locus between the divergent populations, due to the alternative fixation of alleles; and 3) a consequent regional increase in the variance of FST (S2FST) for the same clustered variants, due to the increased alternative fixation of alleles in the loci surrounding the selection target. In the first part of our study, to search for potential targets of directional selection, we developed and validated a resampling-based computational approach; we then scanned an array of 31 different-sized moving windows of SNP variants (5–65 SNPs) across the human genome in a set of European and African American population samples with 183,997 SNP loci after correcting for the recombination rate variation. The analysis revealed 180 regions of recent selection with very strong evidence in either population or both. In the second part of our study, we compared the newly discovered putative regions to those sites previously postulated in the literature, using methods based on inspecting patterns of linkage disequilibrium, population divergence and other methodologies. The newly found regions were cross-validated with those found in nine other studies that have searched for selection signals. Our study was replicated especially well in those regions confirmed by three or more studies. These validated regions were independently verified, using a combination of different methods and different databases in other studies, and should include fewer false positives. The main strength of our analysis method compared to others is that it does not require dense genotyping and therefore can be used with data from population-based genome SNP scans from smaller studies of humans or other species

An Open Access Database of Genome-wide Association Results

<p>Abstract</p> <p>Background</p> <p>The number of genome-wide association studies (GWAS) is growing rapidly leading to the discovery and replication of many new disease loci. Combining results from multiple GWAS datasets may potentially strengthen previous conclusions and suggest new disease loci, pathways or pleiotropic genes. However, no database or centralized resource currently exists that contains anywhere near the full scope of GWAS results.</p> <p>Methods</p> <p>We collected available results from 118 GWAS articles into a database of 56,411 significant SNP-phenotype associations and accompanying information, making this database freely available here. In doing so, we met and describe here a number of challenges to creating an open access database of GWAS results. Through preliminary analyses and characterization of available GWAS, we demonstrate the potential to gain new insights by querying a database across GWAS.</p> <p>Results</p> <p>Using a genomic bin-based density analysis to search for highly associated regions of the genome, positive control loci (e.g., MHC loci) were detected with high sensitivity. Likewise, an analysis of highly repeated SNPs across GWAS identified replicated loci (e.g., <it>APOE</it>, <it>LPL</it>). At the same time we identified novel, highly suggestive loci for a variety of traits that did not meet genome-wide significant thresholds in prior analyses, in some cases with strong support from the primary medical genetics literature (<it>SLC16A7, CSMD1, OAS1</it>), suggesting these genes merit further study. Additional adjustment for linkage disequilibrium within most regions with a high density of GWAS associations did not materially alter our findings. Having a centralized database with standardized gene annotation also allowed us to examine the representation of functional gene categories (gene ontologies) containing one or more associations among top GWAS results. Genes relating to cell adhesion functions were highly over-represented among significant associations (p < 4.6 × 10^-14), a finding which was not perturbed by a sensitivity analysis.</p> <p>Conclusion</p> <p>We provide access to a full gene-annotated GWAS database which could be used for further querying, analyses or integration with other genomic information. We make a number of general observations. Of reported associated SNPs, 40% lie within the boundaries of a RefSeq gene and 68% are within 60 kb of one, indicating a bias toward gene-centricity in the findings. We found considerable heterogeneity in information available from GWAS suggesting the wider community could benefit from standardization and centralization of results reporting.</p

Genomic Runs of Homozygosity Record Population History and Consanguinity

The human genome is characterised by many runs of homozygous genotypes, where identical haplotypes were inherited from each parent. The length of each run is determined partly by the number of generations since the common ancestor: offspring of cousin marriages have long runs of homozygosity (ROH), while the numerous shorter tracts relate to shared ancestry tens and hundreds of generations ago. Human populations have experienced a wide range of demographic histories and hold diverse cultural attitudes to consanguinity. In a global population dataset, genome-wide analysis of long and shorter ROH allows categorisation of the mainly indigenous populations sampled here into four major groups in which the majority of the population are inferred to have: (a) recent parental relatedness (south and west Asians); (b) shared parental ancestry arising hundreds to thousands of years ago through long term isolation and restricted effective population size (N(e)), but little recent inbreeding (Oceanians); (c) both ancient and recent parental relatedness (Native Americans); and (d) only the background level of shared ancestry relating to continental N(e) (predominantly urban Europeans and East Asians; lowest of all in sub-Saharan African agriculturalists), and the occasional cryptically inbred individual. Moreover, individuals can be positioned along axes representing this demographic historic space. Long runs of homozygosity are therefore a globally widespread and under-appreciated characteristic of our genomes, which record past consanguinity and population isolation and provide a distinctive record of the demographic history of an individual's ancestors. Individual ROH measures will also allow quantification of the disease risk arising from polygenic recessive effects