Associations between smoking behavior-related alleles and the risk of melanoma.

Several studies have reported that cigarette smoking is inversely associated with the risk of melanoma. This study further tested whether incorporating genetic factors will provide another level of evaluation of mechanisms underlying the association between smoking and risk of melanoma. We investigated the association between SNPs selected from genome-wide association studies (GWAS) on smoking behaviors and risk of melanoma using 2,298 melanoma cases and 6,654 controls. Among 16 SNPs, three (rs16969968 [A], rs1051730 [A] and rs2036534 [C] in the 15q25.1 region) reached significance for association with melanoma risk in men (0.01 < = P values < = 0.02; 0.85 < = Odds Ratios (ORs) <= 1.20). There was association between the genetic scores based on the number of smoking behavior-risk alleles and melanoma risk with P-trend = 0.005 among HPFS. Further association with smoking behaviors indicating those three SNPs (rs16969968 [A], rs1051730 [A] and rs2036534 [C]) significantly associated with number of cigarettes smoked per day, CPD, with P = 0.009, 0.011 and 0.001 respectively. The SNPs rs215605 in the PDE1C gene and rs6265 in the BDNF gene significantly interacted with smoking status on melanoma risk (interaction P = 0.005 and P = 0.003 respectively). Our study suggests that smoking behavior-related SNPs are likely to play a role in melanoma development and the potential public health importance of polymorphisms in the CHRNA5-A3-B4 gene cluster. Further larger studies are warranted to validate the findings.

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.

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.

Understanding Antenatal Genetics Services in Sri Lanka: Current Landscape of Screening and Diagnostic Services and Contextual Factors Influencing Their Availability and Uptake

Background: Too little information is available on Sri Lanka’s current capacity to provide community genetic services—antenatal genetic services in particular—to understand whether building that capacity could further improve and reduce disparity in maternal and child health. This qualitative research project seeks to gather information on congenital disorders, routine antenatal care, and the current state of antenatal screening testing services within that routine antenatal to assess the feasibility of and the need for scaling up antenatal genetics services in Sri Lanka. Methods: Nineteen key informant (KI) interviews were conducted with stakeholders in antenatal care and genetic services. Seven focus group discussions were held with a total of 56 Public Health Midwives (PHMs), the health workers responsible for antenatal care at the field level. Transcripts for all interviews and FGDs were analyzed for key themes, and themes were categorized to address the specific aims of the project. Results: Antenatal genetic services play a minor role in antenatal care, with screening and diagnostic procedures available in the private sector and paid for out-of-pocket. KIs and PHMs expect that demand for antenatal genetic services will increase as patients’ purchasing power and knowledge grow but note that prohibitive abortion laws limit the ability of patients to act on test results. Genetic services compete for limited financial and human resources in the free public health system, and inadequate information on the prevalence of congenital disorders limits the ability to understand whether funding for services related to those disorders should be increased. A number of alternatives to scaling up antenatal genetic services within the free health system might be better suited to the Sri Lankan structural and social context. Conclusions: Scaling up antenatal genetic services within the public health system is not feasible in the current financial, legal, and human resource context. Yet current availability and utilization patterns contribute to regional and economic disparities, suggesting that stasis will not bring continued improvements in maternal and child health. More information on the burden of congenital disorders is necessary to fully understand if and how antenatal genetic service availability should be increased in Sri Lanka, but even before that information is gathered, examination of policies for patient referral, termination of pregnancy, and government support for individuals with genetic disease are steps that might bring extend improvements and reduce disparity in maternal and child health.