Association tests for rare and common variants based on genotypic and phenotypic measures of similarity between individuals

Genome-wide association studies have helped us identify thousands of common variants associated with several widespread complex diseases. However, for most traits, these variants account for only a small fraction of phenotypic variance or heritability. Next-generation sequencing technologies are being used to identify additional rare variants hypothesized to have higher effect sizes than the already identified common variants, and to contribute significantly to the fraction of heritability that is still unexplained. Several pooling strategies have been proposed to test the joint association of multiple rare variants, because testing them individually may not be optimal. Within a gene or genomic region, if there are both rare and common variants, testing their joint association may be desirable to determine their synergistic effects. We propose new methods to test the joint association of several rare and common variants with binary and quantitative traits. Our association test for quantitative traits is based on genotypic and phenotypic measures of similarity between pairs of individuals. For the binary trait or case-control samples, we recently proposed an association test based on the genotypic similarity between individuals. Here, we develop a modified version of this test for rare variants. Our tests can be used for samples taken from multiple subpopulations. The power of our test statistics for case-control samples and quantitative traits was evaluated using the GAW17 simulated data sets. Type I error rates for the proposed tests are well controlled. Our tests are able to identify some of the important causal genes in the GAW17 simulated data sets

Clinical and genetic characterisation of dystrophin-deficient muscular dystrophy in a family of Miniature Poodle dogs

Four full-sibling intact male Miniature Poodles were evaluated at 4–19 months of age. One was clinically normal and three were affected. All affected dogs were reluctant to exercise and had generalised muscle atrophy, a stiff gait and a markedly elevated serum creatine kinase activity. Two affected dogs also showed poor development, learning difficulties and episodes of abnormal behaviour. In these two dogs, investigations into forebrain structural and metabolic diseases were unremarkable; electromyography demonstrated fibrillation potentials and complex repetitive discharges in the infraspinatus, supraspinatus and epaxial muscles. Histopathological, immunohistochemical and immunoblotting analyses of muscle biopsies were consistent with dystrophin-deficient muscular dystrophy. DNA samples were obtained from all four full-sibling male Poodles, a healthy female littermate and the dam, which was clinically normal. Whole genome sequencing of one affected dog revealed a >5 Mb deletion on the X chromosome, encompassing the entire DMD gene. The exact deletion breakpoints could not be experimentally ascertained, but we confirmed that this region was deleted in all affected males, but not in the unaffected dogs. Quantitative polymerase chain reaction confirmed all three affected males were hemizygous for the mutant X chromosome, while the wildtype chromosome was observed in the unaffected male littermate. The female littermate and the dam were both heterozygous for the mutant chromosome. Forty-four Miniature Poodles from the general population were screened for the mutation and were homozygous for the wildtype chromosome. The finding represents a naturally-occurring mutation causing dystrophin-deficient muscular dystrophy in the dog

Digging into the extremes: a useful approach for the analysis of rare variants with continuous traits?

The common disease/rare variant hypothesis predicts that rare variants with large effects will have a strong impact on corresponding phenotypes. Therefore it is assumed that rare functional variants are enriched in the extremes of the phenotype distribution. In this analysis of the Genetic Analysis Workshop 17 data set, my aim is to detect genes with rare variants that are associated with quantitative traits using two general approaches: analyzing the association with the complete distribution of values by means of linear regression and using statistical tests based on the tails of the distribution (bottom 10% of values versus top 10%). Three methods are used for this extreme phenotype approach: Fisher’s exact test, weighted-sum method, and beta method. Rare variants were collapsed on the gene level. Linear regression including all values provided the highest power to detect rare variants. Of the three methods used in the extreme phenotype approach, the beta method performed best. Furthermore, the sample size was enriched in this approach by adding additional samples with extreme phenotype values. Doubling the sample size using this approach, which corresponds to only 40% of sample size of the original continuous trait, yielded a comparable or even higher power than linear regression. If samples are selected primarily for sequencing, enriching the analysis by gathering a greater proportion of individuals with extreme values in the phenotype of interest rather than in the general population leads to a higher power to detect rare variants compared to analyzing a population-based sample with equivalent sample size

Supersymmetric Charged Clouds in AdS_5

We consider supersymmetric holographic flows that involve background gauge fields dual to chemical potentials in the boundary field theory. We use a consistent truncation of gauged N=8 supergravity in five dimensions and we give a complete analysis of the supersymmetry conditions for a large family of flows. We examine how the well-known supersymmetric flow between two fixed points is modified by the presence of the chemical potentials and this yields a new, completely smooth, solution that interpolates between two global AdS spaces of different radii and with different values of the chemical potential. We also examine some black-hole-like singular flows and a new non-supersymmetric black hole solution. We comment on the interpretation of our new solutions in terms of giant gravitons and discuss the implications of our work for finding black-hole solutions in AdS geometries.Comment: 31 pages, 6 figures; minor corrections, updated reference

Theory and practice of social norms interventions: eight common pitfalls.

BACKGROUND: Recently, Global Health practitioners, scholars, and donors have expressed increased interest in "changing social norms" as a strategy to promote health and well-being in low and mid-income countries (LMIC). Despite this burgeoning interest, the ability of practitioners to use social norm theory to inform health interventions varies widely. MAIN BODY: Here, we identify eight pitfalls that practitioners must avoid as they plan to integrate a social norms perspective in their interventions, as well as eight learnings. These learnings are: 1) Social norms and attitudes are different; 2) Social norms and attitudes can coincide; 3) Protective norms can offer important resources for achieving effective social improvement in people's health-related practices; 4) Harmful practices are sustained by a matrix of factors that need to be understood in their interactions; 5) The prevalence of a norm is not necessarily a sign of its strength; 6) Social norms can exert both direct and indirect influence; 7) Publicising the prevalence of a harmful practice can make things worse; 8) People-led social norm change is both the right and the smart thing to do. CONCLUSIONS: As the understanding of how norms evolve in LMIC advances, practitioners will develop greater understanding of what works to help people lead change in harmful norms within their contexts. Awareness of these pitfalls has helped several of them increase the effectiveness of their interventions addressing social norms in the field. We are confident that others will benefit from these reflections as well

The Effects of Biogeography on Ant Diversity and Activity on the Boston Harbor Islands, Massachusetts, U.S.A

Many studies have examined how island biogeography affects diversity on the scale of island systems. In this study, we address how diversity varies over very short periods of time on individual islands. To do this, we compile an inventory of the ants living in the Boston Harbor Islands National Recreation Area, Boston, Massachusetts, USA using data from a five-year All Taxa Biodiversity Inventory of the region's arthropods. Consistent with the classical theory of island biogeography, species richness increased with island size, decreased with island isolation, and remained relatively constant over time. Additionally, our inventory finds that almost half of the known Massachusetts ant fauna can be collected in the BHI, and identifies four new species records for Massachusetts, including one new to the United States, Myrmica scabrinodis. We find that the number of species actually active on islands depended greatly on the timescale under consideration. The species that could be detected during any given week of sampling could by no means account for total island species richness, even when correcting for sampling effort. Though we consistently collected the same number of species over any given week of sampling, the identities of those species varied greatly between weeks. This variation does not result from local immigration and extinction of species, nor from seasonally-driven changes in the abundance of individual species, but rather from weekly changes in the distribution and activity of foraging ants. This variation can be upwards of 50% of ant species per week. This suggests that numerous ant species on the BHI share the same physical space at different times. This temporal partitioning could well explain such unexpectedly high ant diversity in an isolated, urban site

Large Differences in Publicly Visible Health Behaviours across Two Neighbourhoods of the Same City

Background: There are socioeconomic disparities in the likelihood of adopting unhealthy behaviours, and success at giving them up. This may be in part because people living in deprived areas are exposed to greater rates of unhealthy behaviour amongst those living around them. Conventional self-report surveys do not capture these differences in exposure, and more ethological methods are required in order to do so. Methodology/Principal Findings: We performed 12 hours of direct behavioural observation in the streets of two neighbourhoods of the same city which were similar in most regards, except that one was much more socioeconomically deprived than the other. There were large differences in the publicly visible health behaviours observed. In the deprived neighbourhood, we observed 266 more adults smoking (rate ratio 3.44), 53 more adults drinking alcohol (rate ratio not calculable), and 38 fewer adults running (rate ratio 0.23), than in the affluent neighbourhood. We used data from the Health Survey for England to calculate the differences we ought to expect to have seen given the individual-level socioeconomic characteristics of the residents. The observed disparities between the two neighbourhoods were considerably greater than this null model predicted. There were also different patterns of smoking in proximity to children in the two neighbourhoods. Conclusions/Significance: The differences in observed smoking, drinking alcohol, and physical activity between these tw

Study of Transcriptional Effects in Cis at the IFIH1 Locus

Background: The Thr allele at the non-synonymous single-nucleotide polymorphism (nsSNP) Thr946Ala in the IFIH1 gene confers risk for Type 1 diabetes (T1D). The SNP is embedded in a 236 kb linkage disequilibrium (LD) block that includes four genes: IFIH1, GCA, FAP and KCNH7. The absence of common nsSNPs in the other genes makes the IFIH1 SNP the strongest functional candidate, but it could be merely a marker of association, due to LD with a variant regulating expression levels of IFIH1 or neighboring genes. Methodology/Principal Findings: We investigated the effect of the T1D-associated variation on mRNA transcript expression of these genes. Heterozygous mRNA from lymphoblastoid cell lines (LCLs), pancreas and thymus was examined by allelic expression imbalance, to detect effects in cis on mRNA expression. Using single-nucleotide primer extension, we found no difference between mRNA transcripts in 9 LCLs, 6 pancreas and 13 thymus samples, suggesting that GCA and FAP are not involved. On the other hand, KCNH7 was not expressed at a detectable level in all tissues examined. Moreover, the association of the Thr946Ala SNP with T1D is not due to modulation of IFIH1 expression in organs involved in the disease, pointing to the IFIH1 nsSNP as the causal variant. Conclusions/Significance: The mechanism of the association of the nsSNP with T1D remains to be determined, but does not involve mRNA modulation. It becomes necessary to study differential function of the IFIH1 protein alleles at Thr946Al