Risk Prediction for Epithelial Ovarian Cancer in 11 United States-Based Case-Control Studies: Incorporation of Epidemiologic Risk Factors and 17 Confirmed Genetic Loci.

Previously developed models for predicting absolute risk of invasive epithelial ovarian cancer have included a limited number of risk factors and have had low discriminatory power (area under the receiver operating characteristic curve (AUC) < 0.60). Because of this, we developed and internally validated a relative risk prediction model that incorporates 17 established epidemiologic risk factors and 17 genome-wide significant single nucleotide polymorphisms (SNPs) using data from 11 case-control studies in the United States (5,793 cases; 9,512 controls) from the Ovarian Cancer Association Consortium (data accrued from 1992 to 2010). We developed a hierarchical logistic regression model for predicting case-control status that included imputation of missing data. We randomly divided the data into an 80% training sample and used the remaining 20% for model evaluation. The AUC for the full model was 0.664. A reduced model without SNPs performed similarly (AUC = 0.649). Both models performed better than a baseline model that included age and study site only (AUC = 0.563). The best predictive power was obtained in the full model among women younger than 50 years of age (AUC = 0.714); however, the addition of SNPs increased the AUC the most for women older than 50 years of age (AUC = 0.638 vs. 0.616). Adapting this improved model to estimate absolute risk and evaluating it in prospective data sets is warranted.

Functional annotation signatures of disease susceptibility loci improve SNP association analysis.

BACKGROUND: Genetic association studies are conducted to discover genetic loci that contribute to an inherited trait, identify the variants behind these associations and ascertain their functional role in determining the phenotype. To date, functional annotations of the genetic variants have rarely played more than an indirect role in assessing evidence for association. Here, we demonstrate how these data can be systematically integrated into an association study's analysis plan. RESULTS: We developed a Bayesian statistical model for the prior probability of phenotype-genotype association that incorporates data from past association studies and publicly available functional annotation data regarding the susceptibility variants under study. The model takes the form of a binary regression of association status on a set of annotation variables whose coefficients were estimated through an analysis of associated SNPs in the GWAS Catalog (GC). The functional predictors examined included measures that have been demonstrated to correlate with the association status of SNPs in the GC and some whose utility in this regard is speculative: summaries of the UCSC Human Genome Browser ENCODE super-track data, dbSNP function class, sequence conservation summaries, proximity to genomic variants in the Database of Genomic Variants and known regulatory elements in the Open Regulatory Annotation database, PolyPhen-2 probabilities and RegulomeDB categories. Because we expected that only a fraction of the annotations would contribute to predicting association, we employed a penalized likelihood method to reduce the impact of non-informative predictors and evaluated the model's ability to predict GC SNPs not used to construct the model. We show that the functional data alone are predictive of a SNP's presence in the GC. Further, using data from a genome-wide study of ovarian cancer, we demonstrate that their use as prior data when testing for association is practical at the genome-wide scale and improves power to detect associations. CONCLUSIONS: We show how diverse functional annotations can be efficiently combined to create 'functional signatures' that predict the a priori odds of a variant's association to a trait and how these signatures can be integrated into a standard genome-wide-scale association analysis, resulting in improved power to detect truly associated variants.

Genetic and Molecular Basis of Encapsulation and Capsule Diversity in Kingella kingae

Kingella kingae is a bacterial pathogen that is increasingly recognized as an etiology of septic arthritis, osteomyelitis, bacteremia, and endocarditis in young children. The pathogenesis of K. kingae disease starts with bacterial adherence to the respiratory epithelium of the posterior pharynx. Previous work has identified type IV pili and a trimeric autotransporter protein called Knh (Kingella NhhA homolog) as critical factors for adherence to human epithelial cells. Additional studies established that the presence of a polysaccharide capsule interferes with Knh-mediated adherence. Given the inhibitory role of capsule during adherence we sought to uncover the genes involved in capsule expression to understand how capsule is elaborated on the cell surface. Additionally, this work aimed to further characterize capsule diversity among K. kingae clinical isolates and to investigate the relationship between capsule type and site of isolation.

We first set out to identify the carbohydrates present in the K. kingae capsule present in the prototype strain 269-492. Glycosyl composition and NMR analysis of surface extractable polysaccharides demonstrated two distinct polysaccharides, one consisting of GalNAc and Kdo with the structure →3)-β-GalpNAc-(1→5)-β-Kdop-(2→ and the other containing galactose alone with the structure →5)-β-Galf-(1→.

To discern the two polysaccharides we disrupted the ctrA gene required for surface localization of the K. kingae polysaccharide capsule and observed a loss of GalNAc and Kdo but no effect on the presence of Gal in bacterial surface extracts. In contrast, deletion of the pamABCDE locus involved in production of a reported galactan exopolysaccharide eliminated Gal but had no effect on the presence of GalNAc and Kdo in surface extracts. These results established that K. kingae strain KK01 produces a polysaccharide capsule with the structure →3)-β-GalpNAc-(1→5)-β-Kdop-(2→ and a separate exopolysaccharide with the structure →5)-β-Galf-(1→.

Having established that K. kingae produces a capsule comprised of GalNAc and Kdo, we next set out to identify the genetic determinants of capsule through a transposon mutagenesis screen. In addition to the previously identified ctrABCD operon, lipA, lipB, and a putative glycosyltransferase termed csaA (capsule synthesis region A gene A) were found to be essential for the production of surface-localized capsule. The ctr operon, lipA, lipB, and csaA were found to be present at unlinked locations throughout the genome, which is atypical for gram-negative organisms that elaborate a capsule dependent on an ABC-type transporter for surface localization. Through examining capsule localization in the ctrA, lipA, lipB, and csaA mutant strains, we determined that the ctrABCD, lipA/lipB, and csaA gene products respectively function in capsule export, assembly, and synthesis, respectively. The GalNAc transferase and Kdo transferase domains found in CsaA further support its role in catalyzing the synthesis of the GalNAc-Kdo capsule in the K. kingae prototype strain.

To investigate the capsule diversity that exists in K. kingae we screened a panel of strains isolated from patients with invasive disease or healthy carriers for the csaA capsule synthesis locus. We discovered that Kingella kingae expresses one of 4 capsule synthesis loci (csa, csb, csc, or csd) associated with a capsule consisting of Kdo and GalNAc (type a), Kdo and GlcNAc (type b), Kdo and ribose (type c), and GlcNAc and galactose (type d), respectively. Cloning of the csa, csb, csc, or csd locus into the empty flanking gene region in a non-encapsulated mutant (creation of an isogenic capsule swap) was sufficient to produce either the type a, type b, or type c capsule, respectively, further supporting the role of these loci in expression of a specific polysaccharide linkage. Capsule type a and capsule type b accounted for 96% of invasive strains. Conversely, capsule type c and capsule type d were found disproportionately among carrier isolates, suggesting that capsule type is important in promoting invasion and dissemination.

In conclusion, we discovered that Kingella kingae expresses a polysaccharide capsule and an exopolysaccharide on its surface that require distinct genetic loci for surface localization. Further investigation into genetic determinants of encapsulation revealed the loci ctrABCD, lipA/lipB, and a putative glycosyltransferase are required for capsule expression, with the gene products having roles in capsule export, assembly, and synthesis, respectively. The putative glycosyltransferase CsaA was determined to be a bifunctional enzyme with both GalNAc-transferase and Kdo-transferase activity. Furthermore, we discovered a total of 4 capsule types expressed in clinical isolates of K. kingae, each with a distinct capsule synthesis locus. The variation in the proportion of capsule types found between invasive strains and carriage strains suggest that capsule type is important in promoting invasion and dissemination. Taken together, this work expands our knowledge of the capsule types expressed among K. kingae carrier and invasive isolates and provides insights into the common genetic determinants of capsule expression. These contributions may lead to selecting clinically relevant capsule types to develop into a capsule based vaccine to prevent K. kingae colonization.

A genome-wide association study identifies susceptibility variants for type 2 diabetes in Han Chinese.

To investigate the underlying mechanisms of T2D pathogenesis, we looked for diabetes susceptibility genes that increase the risk of type 2 diabetes (T2D) in a Han Chinese population. A two-stage genome-wide association (GWA) study was conducted, in which 995 patients and 894 controls were genotyped using the Illumina HumanHap550-Duo BeadChip for the first genome scan stage. This was further replicated in 1,803 patients and 1,473 controls in stage 2. We found two loci not previously associated with diabetes susceptibility in and around the genes protein tyrosine phosphatase receptor type D (PTPRD) (P = 8.54x10(-10); odds ratio [OR] = 1.57; 95% confidence interval [CI] = 1.36-1.82), and serine racemase (SRR) (P = 3.06x10(-9); OR = 1.28; 95% CI = 1.18-1.39). We also confirmed that variants in KCNQ1 were associated with T2D risk, with the strongest signal at rs2237895 (P = 9.65x10(-10); OR = 1.29, 95% CI = 1.19-1.40). By identifying two novel genetic susceptibility loci in a Han Chinese population and confirming the involvement of KCNQ1, which was previously reported to be associated with T2D in Japanese and European descent populations, our results may lead to a better understanding of differences in the molecular pathogenesis of T2D among various populations.

Evolution of the sex-related locus and genomic features shared in microsporidia and fungi.

BACKGROUND: Microsporidia are obligate intracellular, eukaryotic pathogens that infect a wide range of animals from nematodes to humans, and in some cases, protists. The preponderance of evidence as to the origin of the microsporidia reveals a close relationship with the fungi, either within the kingdom or as a sister group to it. Recent phylogenetic studies and gene order analysis suggest that microsporidia share a particularly close evolutionary relationship with the zygomycetes. METHODOLOGY/PRINCIPAL FINDINGS: Here we expanded this analysis and also examined a putative sex-locus for variability between microsporidian populations. Whole genome inspection reveals a unique syntenic gene pair (RPS9-RPL21) present in the vast majority of fungi and the microsporidians but not in other eukaryotic lineages. Two other unique gene fusions (glutamyl-prolyl tRNA synthetase and ubiquitin-ribosomal subunit S30) that are present in metazoans, choanoflagellates, and filasterean opisthokonts are unfused in the fungi and microsporidians. One locus previously found to be conserved in many microsporidian genomes is similar to the sex locus of zygomycetes in gene order and architecture. Both sex-related and sex loci harbor TPT, HMG, and RNA helicase genes forming a syntenic gene cluster. We sequenced and analyzed the sex-related locus in 11 different Encephalitozoon cuniculi isolates and the sibling species E. intestinalis (3 isolates) and E. hellem (1 isolate). There was no evidence for an idiomorphic sex-related locus in this Encephalitozoon species sample. According to sequence-based phylogenetic analyses, the TPT and RNA helicase genes flanking the HMG genes are paralogous rather than orthologous between zygomycetes and microsporidians. CONCLUSION/SIGNIFICANCE: The unique genomic hallmarks between microsporidia and fungi are independent of sequence based phylogenetic comparisons and further contribute to define the borders of the fungal kingdom and support the classification of microsporidia as unusual derived fungi. And the sex/sex-related loci appear to have been subject to frequent gene conversion and translocations in microsporidia and zygomycetes.

The evolutionary history of ferns inferred from 25 low-copy nuclear genes.

UNLABELLED: • PREMISE OF THE STUDY: Understanding fern (monilophyte) phylogeny and its evolutionary timescale is critical for broad investigations of the evolution of land plants, and for providing the point of comparison necessary for studying the evolution of the fern sister group, seed plants. Molecular phylogenetic investigations have revolutionized our understanding of fern phylogeny, however, to date, these studies have relied almost exclusively on plastid data.• METHODS: Here we take a curated phylogenomics approach to infer the first broad fern phylogeny from multiple nuclear loci, by combining broad taxon sampling (73 ferns and 12 outgroup species) with focused character sampling (25 loci comprising 35877 bp), along with rigorous alignment, orthology inference and model selection.• KEY RESULTS: Our phylogeny corroborates some earlier inferences and provides novel insights; in particular, we find strong support for Equisetales as sister to the rest of ferns, Marattiales as sister to leptosporangiate ferns, and Dennstaedtiaceae as sister to the eupolypods. Our divergence-time analyses reveal that divergences among the extant fern orders all occurred prior to ∼200 MYA. Finally, our species-tree inferences are congruent with analyses of concatenated data, but generally with lower support. Those cases where species-tree support values are higher than expected involve relationships that have been supported by smaller plastid datasets, suggesting that deep coalescence may be reducing support from the concatenated nuclear data.• CONCLUSIONS: Our study demonstrates the utility of a curated phylogenomics approach to inferring fern phylogeny, and highlights the need to consider underlying data characteristics, along with data quantity, in phylogenetic studies.

ENIGMA and the individual: Predicting factors that affect the brain in 35 countries worldwide.

In this review, we discuss recent work by the ENIGMA Consortium (http://enigma.ini.usc.edu) - a global alliance of over 500 scientists spread across 200 institutions in 35 countries collectively analyzing brain imaging, clinical, and genetic data. Initially formed to detect genetic influences on brain measures, ENIGMA has grown to over 30 working groups studying 12 major brain diseases by pooling and comparing brain data. In some of the largest neuroimaging studies to date - of schizophrenia and major depression - ENIGMA has found replicable disease effects on the brain that are consistent worldwide, as well as factors that modulate disease effects. In partnership with other consortia including ADNI, CHARGE, IMAGEN and others(1), ENIGMA's genomic screens - now numbering over 30,000 MRI scans - have revealed at least 8 genetic loci that affect brain volumes. Downstream of gene findings, ENIGMA has revealed how these individual variants - and genetic variants in general - may affect both the brain and risk for a range of diseases. The ENIGMA consortium is discovering factors that consistently affect brain structure and function that will serve as future predictors linking individual brain scans and genomic data. It is generating vast pools of normative data on brain measures - from tens of thousands of people - that may help detect deviations from normal development or aging in specific groups of subjects. We discuss challenges and opportunities in applying these predictors to individual subjects and new cohorts, as well as lessons we have learned in ENIGMA's efforts so far.

Integrated pathway and epistasis analysis reveals interactive effect of genetic variants at TERF1 and AFAP1L2 loci on melanoma risk.

Genome-wide association studies (GWASs) have characterized 13 loci associated with melanoma, which only account for a small part of melanoma risk. To identify new genes with too small an effect to be detected individually but which collectively influence melanoma risk and/or show interactive effects, we used a two-step analysis strategy including pathway analysis of genome-wide SNP data, in a first step, and epistasis analysis within significant pathways, in a second step. Pathway analysis, using the gene-set enrichment analysis (GSEA) approach and the gene ontology (GO) database, was applied to the outcomes of MELARISK (3,976 subjects) and MDACC (2,827 subjects) GWASs. Cross-gene SNP-SNP interaction analysis within melanoma-associated GOs was performed using the INTERSNP software. Five GO categories were significantly enriched in genes associated with melanoma (false discovery rate ≤ 5% in both studies): response to light stimulus, regulation of mitotic cell cycle, induction of programmed cell death, cytokine activity and oxidative phosphorylation. Epistasis analysis, within each of the five significant GOs, showed significant evidence for interaction for one SNP pair at TERF1 and AFAP1L2 loci (pmeta-int  = 2.0 × 10(-7) , which met both the pathway and overall multiple-testing corrected thresholds that are equal to 9.8 × 10(-7) and 2.0 × 10(-7) , respectively) and suggestive evidence for another pair involving correlated SNPs at the same loci (pmeta-int  = 3.6 × 10(-6) ). This interaction has important biological relevance given the key role of TERF1 in telomere biology and the reported physical interaction between TERF1 and AFAP1L2 proteins. This finding brings a novel piece of evidence for the emerging role of telomere dysfunction into melanoma development.

Are the native giant tortoises from the Seychelles really extinct? A genetic perspective based on mtDNA and microsatellite data.

The extinction of the giant tortoises of the Seychelles Archipelago has long been suspected but is not beyond doubt. A recent morphological study of the giant tortoises of the western Indian Ocean concluded that specimens of two native Seychelles species survive in captivity today alongside giant tortoises of Aldabra, which are numerous in zoos as well as in the wild. This claim has been controversial because some of the morphological characters used to identify these species, several measures of carapace morphology, are reputed to be quite sensitive to captive conditions. Nonetheless, the potential survival of giant tortoise species previously thought extinct presents an exciting scenario for conservation. We used mitochondrial DNA sequences and nuclear microsatellites to examine the validity of the rediscovered species of Seychelles giant tortoises. Our results indicate that the morphotypes suspected to represent Seychelles species do not show levels of variation and genetic structuring consistent with long periods of reproductive isolation. We found no variation in the mitochondrial control region among 55 individuals examined and no genetic structuring in eight microsatellite loci, pointing to the survival of just a single lineage of Indian Ocean tortoises.