Variation in European harbour seal immune response genes and susceptibility to phocine distemper virus (PDV)

Phocine distemper virus (PDV) has caused two mass mortalities of European harbour seals (Phoca vitulina) in recent decades. Levels of mortality varied considerably among European populations in both the 1988 and 2002 epidemics, with higher mortality in continental European populations in comparison to UK populations. High levels of genetic differentiation at neutral makers among seal populations allow for the possibility that there could be potential genetic differences at functional loci that may account for some of the variation in mortality. Recent genome sequencing of carnivore species and development of genomic tools have now made it possible to explore the possible contribution of variation in candidate genes from harbour seals in relation to the differential mortality patterns. We assessed variation in eight genes (CD46, IFNG, IL4, IL8, IL10, RARa, SLAM and TLR2) encoding key proteins involved in host cellular interactions with Morbilliviruses and the relationship of variants to disease status. This work constitutes the first genetic association study for Morbillivirus disease susceptibility in a non-model organism, and for a natural mortality event. We found no variation in harbour seals from across Europe in the protein coding domains of the viral receptors SLAM and CD46, but SNPs were present in SLAM intron 2. SNPs were also present in IL8 p2 and RARa exon 1. There was no significant association of SLAM or RARa polymorphisms with disease status implying no role of these genes in determining resistance to PDV induced mortality, that could be detected with the available samples and the small number of polymorphisms indentified. However there was significant differentiation of allele frequencies among populations. PDV and other morbilliviruses are important models for wildlife epidemiology, host switches and viral evolution. Despite a negative result in this case, full sequencing of pinniped and other ‘non-model’ carnivore genomes will help in refining understanding the role of host genetics in disease susceptibility for these viruses.     

On the utility of gene set methods in genomewide association studies of quantitative traits

In genomewide genetic association studies, prior biological knowledge may help distinguish variation that is truly associated with a quantitative trait from the vast majority of unassociated variation that may be significant in hypothesis testing due to chance. However, formal methods for integrating prior biological knowledge into association studies have only been proposed recently, and their potential utility has not been thoroughly evaluated. Herein, gene set methods from genomewide analysis of gene expression data are adapted for application to genomewide genetic analysis of quantitative traits. The proposed gene set method was tested in simulations with gene sets that included up to 500 total variants, among which up to 20 collectively explained 5% of the variance. In a population of 1,000 individuals, the gene set method was largely more efficient at detecting truly associated variants in these gene sets than a comparably calibrated conventional approach relying on P-values alone. While extremely strong associations remain best identified by conventional methods, the gene set approach may provide a complementary mode of analysis for revealing the full spectrum of genes that influence a quantitative trait.     

Trypanosoma brucei gambiense Type 1 populations from human patients are clonal and display geographical genetic differentiation

We have rigorously tested the hypothesis that Trypanosoma brucei gambiense Type 1 is composed of genetically homogenous populations by examining the parasite population present in Human African Trypanosomiasis (HAT) patients from the Democratic Republic of Congo (DRC) and Cameroon (CAM). We amplified eight microsatellite markers by PCR directly from blood spots on FTA filters, thereby avoiding the significant parasite selection inherent in the traditional isolation techniques of rodent inoculation or in vitro culture. All microsatellite markers were polymorphic, although for four markers there was only polymorphism between the DRC and CAM populations, not within populations, suggesting very limited genetic exchange. Within the largest population from the DRC, Hardy–Weinberg equilibrium is not evident at any loci. This evidence suggests a clonal population. However, there was significant sub-structuring between the DRC and CAM samples (F_ST = 0.32), indicating that Trypanosoma brucei gambiense Type 1 has genetically distinct clades. The data combine to indicate that genetic exchange plays a very limited role. The finding of distinct clades in different places suggests the possibility that samples from humans with clinical signs represent clonal expansions from an underlying population that requires identifying and characterising.     

Joint effects of density dependence and toxicant exposure on Drosophila melanogaster populations

Risk assessment of environmental contaminants is usually based on experiments on well-fed individuals held at low population densities. However, field populations are often subject to resource limitation. Individuals who are already stressed by crowding or food limitation may show greater susceptibility to toxicants. But density dependence could also reduce population-level impacts as toxicant-related mortalities may reduce competition for resources. This study examines the joint effects of toxicants and food availability on populations of Drosophila melanogaster. The interactions between the effects of food limitation and toxicant stress were dose dependent and strongly influenced by toxicity mechanisms. In food-limited conditions, a compensatory effect often occurred, with toxicant exposure having a lower proportional impact than at higher food levels. This provides further evidence that density-dependent population processes can produce an assimilative capacity for the effects of toxicants. But synergistic food–toxicant effects were also common and the interaction often switched between synergistic and compensatory at different toxicant concentrations and food supplies. There is no simple “less-than-additive”, “additive” or “more-than-additive” relationship between density and toxicant effects, even for a single toxicant.     

<Emphasis Type="Italic">Chlamydia pneumoniae</Emphasis> seropositivity and risk of ischemic stroke:

Chlamydia pneumoniae has been linked with increased risk of cardiovascular disease, but data on stroke are sparse. We examined whether seropositivity to Chlamydia pneumoniae was associated with the risk of ischemic stroke in a nested case–control study. Data on Chlamydia pneumoniae serology, lifestyle factors, and medical history were obtained at baseline. Verified cases (n = 254) were compared with gender- and age-matched controls (n = 254). Positive IgA ( 1:16) or IgG ( 1:64) titers were associated with an increased risk of acute ischemic stroke, i.e. adjusted odds ratios (ORs) were 1.54 (95% confidence interval, CI: 0.96–2.47) and 1.28 (95% CI: 0.83–1.95). The adjusted OR was 1.77 (95% CI: 1.04–3.00) when both titers were elevated. The highest point estimates were seen for ischemic stroke due to large-artery atherosclerosis, adjusted OR: 6.32 (95% CI: 0.76–52.61) (IgG ( 1:64)). No clear associations were found for other types of ischemic stroke. The strength of the association varied depending on gender and the chosen cut-off values for the antibody titers. These results partly support the hypothesis that serologic evidence of Chlamydia pneumoniae infection may be associated with an increased risk of ischemic stroke. However, the risk may differ according to gender, subtype of ischemic stroke, and cut-off value of antibody titers.     

Transethnic meta-analysis of genomewide association studies

The detection of loci contributing effects to complex human traits, and their subsequent fine-mapping for the location of causal variants, remains a considerable challenge for the genetics research community. Meta-analyses of genomewide association studies, primarily ascertained from European-descent populations, have made considerable advances in our understanding of complex trait genetics, although much of their heritability is still unexplained. With the increasing availability of genomewide association data from diverse populations, transethnic meta-analysis may offer an exciting opportunity to increase the power to detect novel complex trait loci and to improve the resolution of fine-mapping of causal variants by leveraging differences in local linkage disequilibrium structure between ethnic groups. However, we might also expect there to be substantial genetic heterogeneity between diverse populations, both in terms of the spectrum of causal variants and their allelic effects, which cannot easily be accommodated through traditional approaches to meta-analysis. In order to address this challenge, I propose novel transethnic meta-analysis methodology that takes account of the expected similarity in allelic effects between the most closely related populations, while allowing for heterogeneity between more diverse ethnic groups. This approach yields substantial improvements in performance, compared to fixed-effects meta-analysis, both in terms of power to detect association, and localization of the causal variant, over a range of models of heterogeneity between ethnic groups. Furthermore, when the similarity in allelic effects between populations is well captured by their relatedness, this approach has increased power and mapping resolution over random-effects meta-analysis.     

Genetic structure of Plasmodium falciparum populations between lowland and highland sites and antimalarial drug resistance in Western Kenya

Human travel to malaria endemic lowlands from epidemic highlands has been shown to increase the risk of malaria infections in the highlands. In order to gain insight on the impact of human travel, we examined prevalence, genetic variability and population genetic structure of Plasmodium falciparum in asymptomatic children from one highland site and three surrounding malaria endemic lowland sites in Western Kenya, using multilocus microsatellite genotyping. We further analyzed the frequencies of mutations at the genes conferring resistance to chloroquine and sulfadoxine–pyrimethamine. We found a significant decrease in malaria prevalence in the highland site from 2006 to 2007, 1 year after the introduction of the artemisinin-based combination therapy as first-line treatment for uncomplicated malaria and the scale-up of insecticide-treated bed nets. Population genetic diversity, measured by the number of observed and effective microsatellite alleles and Nei's unbiased genetic diversity, was high and comparable for both highland and lowland populations. Analysis of molecular variance did not detect a significant genetic structure across highland and lowland regions. Similarly, mutations at key antimalarial-resistance codons of the pfcrt, pfmdr1, pfdhfr and pfdhps genes were found at comparable high frequencies in all four sites. High level of gene flow and lack of significant genetic structure in malaria parasites between highland and lowland areas suggest the importance of human travel in shaping parasite population structure.     

Pathogenesis of rickettsial infections emphasis on Q fever

The underlying mechanisms at the organismic, cellular and molecular levels that account for rickettsial pathogenesis are beginning to be revealed. In the case of Coxiella burnetii infection, relatively recent genetic and biochemical data, as well as drug susceptibility studies, indicate a correlation between isolate type and clinical disease — chronic or short-term acute. The use of cultured cells as model host systems has revealed that, indeed, different isolates from the major classified strains of C. burnetii cause different host cell responses. Use of this and other models (guinea pigs, mice) have revealed other characteristics and properties of the rickettsiae and the infected hosts and host cells that may account, in part, for acute disease and persistent infection culminating in chronic disease. The virulence factors involved apparently include the agent's surface lipopolysaccharide; other unidentified factors have not been excluded. Molecular cloning will play a major role in elucidating the roles of these factors and in identifying other virulence determinants.Presented at the 4th International Symposium on Riskettsial and Rickettsial Diseases, Pietany, C.S.F.R., 1–6 October, 1990.     

Relationship among metabolizing genes,smoking and alcohol used as modifier factors on prostate cancer risk: Exploring some gene–gene and gene–environment interactions

Background: Prostate cancer (PCa) is one of the most common male cancers, but the burden of this disease shows remarkable worldwide variation. The role of susceptibility low penetrance genes and environmental factors in the etiology of (PCa) is unclear, but may involve, in some cases, multiple alleles at multiple loci and environmental factors. Study Objectives: To assess whether CYP1A1, GSTM1, GSTT1 susceptibility genotypes, smoking status and alcohol consumption factors contribute to PCa risk, gene–gene and gene–environment interactions were analyzed. Design and Participants: We explored interactions on a multiplicative scale conducting a population-based case–control and a case–only study on 103 incident PCa patients and 132 unrelated controls. Main Results: The interaction odds ratios (IOR) for PCa risk were increased in men who had both susceptibility genotypes GST (M1; T1) null and CYP1A1-M1* in a case–control and case-only design (IOR_cc: 1.11; 95% CI: 0.12–10.02; IOR_cc: 6.23; 95%, CI: 0.51–75.89; IOR_co: 2.80; 95% CI: 0.44–17.45 and IOR_co: 2.65; 95%, CI: 0.30–25.40). No clear evidence for interaction on a multiplicative scale between smoking status, alcohol consumption and genetic polymorphisms in PCa risk was observed. Conclusions: Our findings suggest that the interaction between genetic polymorphisms in GST (T1; M1) and CYP1A1-M1* would play a significant role as a modifying factor on PCa risk in Chilean people. However, these preliminary exploratory results should be confirmed in a larger study.     

A Robust Method for Genome‐Wide Association Meta‐Analysis With the Application to Circulating Insulin‐Like Growth Factor I Concentrations

Genome‐wide association studies (GWAS) offer an excellent opportunity to identify the genetic variants underlying complex human diseases. Successful utilization of this approach requires a large sample size to identify single nucleotide polymorphisms (SNPs) with subtle effects. Meta‐analysis is a cost‐efficient means to achieve large sample size by combining data from multiple independent GWAS; however, results from studies performed on different populations can be variable due to various reasons, including varied linkage equilibrium structures as well as gene‐gene and gene‐environment interactions. Nevertheless, one should expect effects of the SNP are more similar between similar populations than those between populations with quite different genetic and environmental backgrounds. Prior information on populations of GWAS is often not considered in current meta‐analysis methods, rendering such analyses less optimal for the detecting association. This article describes a test that improves meta‐analysis to incorporate variable heterogeneity among populations. The proposed method is remarkably simple in computation and hence can be performed in a rapid fashion in the setting of GWAS. Simulation results demonstrate the validity and higher power of the proposed method over conventional methods in the presence of heterogeneity. As a demonstration, we applied the test to real GWAS data to identify SNPs associated with circulating insulin‐like growth factor I concentrations.     

Fluorescence analysis detects gp60 subtype diversity in Cryptosporidium infections

Ninety percent of human cryptosporidiosis infections are attributed to two species; the anthroponotic Cryptosporidium hominis and the zoonotic Cryptosporidium parvum. Sequence analysis of the hypervariable gp60 gene, which is used to classify Cryptosporidium to the subtype level, has highlighted extensive intra-species diversity within both C. hominis and C. parvum. The gp60 has also facilitated contamination source tracking and increased understanding of the epidemiology of cryptosporidiosis. Two surface glycoproteins, the gp40 and gp15 are encoded in the gp60 gene; both are exposed to the hosts’ immune system and play a pivotal role in the disease initiation process. The extent of genetic diversity observed within the gp60 would support the hypotheses of significant selection pressure placed on the gp40 and gp15. This study used a dual fluorescent terminal-restriction fragment length polymorphism (T-RFLP) analysis to investigate the genetic diversity of Cryptosporidium subtype populations in a single host infection. Terminal-RFLP showed subtype variation within one human Cryptosporidium sample and mouse samples from seven consecutive passages with C. parvum. Furthermore, this was the first study to show that differences in the ratio of subtype populations occur between infections. T-RFLP has provided a novel platform to study infection populations and to begin to investigate the impact of the hosts’ immune system on the gp60 gene.     

GEE‐Based SNP Set Association Test for Continuous and Discrete Traits in Family‐Based Association Studies

Family‐based genetic association studies of related individuals provide opportunities to detect genetic variants that complement studies of unrelated individuals. Most statistical methods for family association studies for common variants are single marker based, which test one SNP a time. In this paper, we consider testing the effect of an SNP set, e.g., SNPs in a gene, in family studies, for both continuous and discrete traits. Specifically, we propose a generalized estimating equations (GEEs) based kernel association test, a variance component based testing method, to test for the association between a phenotype and multiple variants in an SNP set jointly using family samples. The proposed approach allows for both continuous and discrete traits, where the correlation among family members is taken into account through the use of an empirical covariance estimator. We derive the theoretical distribution of the proposed statistic under the null and develop analytical methods to calculate the P‐values. We also propose an efficient resampling method for correcting for small sample size bias in family studies. The proposed method allows for easily incorporating covariates and SNP‐SNP interactions. Simulation studies show that the proposed method properly controls for type I error rates under both random and ascertained sampling schemes in family studies. We demonstrate through simulation studies that our approach has superior performance for association mapping compared to the single marker based minimum P‐value GEE test for an SNP‐set effect over a range of scenarios. We illustrate the application of the proposed method using data from the Cleveland Family GWAS Study.     

Boosting for detection of gene–environment interactions

In genetic association studies, it is typically thought that genetic variants and environmental variables jointly will explain more of the inheritance of a phenotype than either of these two components separately. Traditional methods to identify gene–environment interactions typically consider only one measured environmental variable at a time. However, in practice, multiple environmental factors may each be imprecise surrogates for the underlying physiological process that actually interacts with the genetic factors. In this paper, we develop a variant of L₂ boosting that is specifically designed to identify combinations of environmental variables that jointly modify the effect of a gene on a phenotype. Because the effect modifiers might have a small signal compared with the main effects, working in a space that is orthogonal to the main predictors allows us to focus on the interaction space. In a simulation study that investigates some plausible underlying model assumptions, our method outperforms the least absolute shrinkage and selection and Akaike Information Criterion and Bayesian Information Criterion model selection procedures as having the lowest test error. In an example for the Women's Health Initiative‐Population Architecture using Genomics and Epidemiology study, the dedicated boosting method was able to pick out two single‐nucleotide polymorphisms for which effect modification appears present. The performance was evaluated on an independent test set, and the results are promising. Copyright © 2012 John Wiley & Sons, Ltd.     

Genetic structure of Triatoma infestans populations in rural communities of Santiago del Estero, northern Argentina

To gain an understanding of the genetic structure and dispersal dynamics of Triatoma infestans populations, we analyzed the multilocus genotype of 10 microsatellite loci for 352 T. infestans collected in 21 houses of 11 rural communities in October 2002. Genetic structure was analyzed at the community and house compound levels. Analysis revealed that vector control actions affected the genetic structure of T. infestans populations. Bug populations from communities under sustained vector control (core area) were highly structured and genetic differentiation between neighboring house compounds was significant. In contrast, bug populations from communities with sporadic vector control actions were more homogeneous and lacked defined genetic clusters. Genetic differentiation between population pairs did not fit a model of isolation by distance at the microgeographical level. Evidence consistent with flight or walking bug dispersal was detected within and among communities, dispersal was more female-biased in the core area and results suggested that houses received immigrants from more than one source. Putative sources and mechanisms of re-infestation are described. These data may be use to design improved vector control strategies.     

Antigens of the Mycobacterium avium,Micobacterium intracellulare complex

In the past decade, the clinical significance of the Mycobacterium avium, Mycobacterium intracellulare complex (MAC) has increased dramatically primarily because of the association between the MAC and the acquired immunodeficiency syndrome (AIDS). Recent hospital reports have suggested that about one-half of AIDS patients in the United States are infected with the MAC. The resulting mycobacteremia is a primary cause of mortality in 5–10% of these patients. This increased clinical importance of the MAC has generated renewed interest in MAC immunobiology. In this review, recent immunological and biochemical characterizations of four classes of dominant mycobacterial antigens — glycopeptidolipids, arabinogalactan, lipoarabinomannan and MAC proteins — is examined. In addition, future prospects for improved diagnosis of MAC disease using defined monospecific antigens is discussed.     

A Genome‐Wide Association Study for Serum Bilirubin Levels and Gene‐Environment Interaction in a Chinese Population

Bilirubin is an effective antioxidant and is influenced by both genetic and environmental factors. Recent genome‐wide association studies (GWAS) have identified multiple loci affecting serum total bilirubin levels. However, most of the studies were conducted in European populations and little attention has been devoted either to genetic variants associated with direct and indirect bilirubin levels or to the gene‐environment interactions on bilirubin levels. In this study, a two‐stage GWAS was performed to identify genetic variants associated with all types of bilirubin levels in 10,282 Han Chinese individuals. Gene‐environment interactions were further examined. Briefly, two previously reported loci, UGT1A1 on 2q37 (rs6742078 and rs4148323, combined P = 1.44 × 10^?89 and P = 5.05 × 10^?69, respectively) and SLCO1B3 on 12p12 (rs2417940, combined P = 6.93 × 10^?19) were successfully replicated. The two loci explained 9.2% and 0.9% of the total variations of total bilirubin levels, respectively. Ethnic genetic differences were observed between Chinese and European populations. More importantly, a significant interaction was found between rs2417940 in SLCO1B3 gene and smoking on total bilirubin levels (P = 1.99 × 10^?3). Single nucleotide polymorphism (SNP) rs2417940 had stronger effects on total bilirubin levels in nonsmokers than in smokers, suggesting that the effects of SLCO1B3 genotype on bilirubin levels were partly dependent on smoking status. Consistent associations and interactions were observed for serum direct and indirect bilirubin levels.     

Experimental studies on the protective efficacy of a Pseudomonas aeruginosa vaccine

Pseudomonas aeruginosa vaccine (PV) containing cell proteins with molecular weight (M_r) 20 000–100 000 and up to 0.08% ( ) admixture of lipopolysaccharide was obtained by water—salt extraction and subsequent ultrafiltration. PV protects mice against experimental P. aeruginosa infection, stimulates production of specific protective antibodies in rabbit and does not provoke obvious toxicity in laboratory animals.     

Incorporating multiple sets of eQTL weights into gene-by-environment interaction analysis identifies novel susceptibility loci for pancreatic cancer

It is of great scientific interest to identify interactions between genetic variants and environmental exposures that may modify the risk of complex diseases. However, larger sample sizes are usually required to detect gene-by-environment interaction (G × E) than required to detect genetic main association effects. To boost the statistical power and improve the understanding of the underlying molecular mechanisms, we incorporate functional genomics information, specifically, expression quantitative trait loci (eQTLs), into a data-adaptive G × E test, called aGEw. This test adaptively chooses the best eQTL weights from multiple tissues and provides an extra layer of weighting at the genetic variant level. Extensive simulations show that the aGEw test can control the Type 1 error rate, and the power is resilient to the inclusion of neutral variants and noninformative external weights. We applied the proposed aGEw test to the Pancreatic Cancer Case–Control Consortium (discovery cohort of 3,585 cases and 3,482 controls) and the PanScan II genome-wide association study data (replication cohort of 2,021 cases and 2,105 controls) with smoking as the exposure of interest. Two novel putative smoking-related pancreatic cancer susceptibility genes, TRIP10 and KDM3A, were identified. The aGEw test is implemented in an R package aGE.     

Approaches to the molecular epidemiology of rickettsioses

This review deals with the developments of molecular approaches to the investigation of rickettsial disease epidemiology. The data presented include changes in the incidence and geographic distribution of endemic rickettsioses.Use of the DNA restriction enzyme technique, in combination with DNA probe analysis, for the molecular genetic differentiation of tick spotted fever — and typhus fever — group rickettsiae and correlation between with the analysis of polypeptide composition of the above group of rickettsiae are discussed.The data are presented on progress in the identification of various Coxiella burnetii strains as a result of restriction analysis of plasmid DNA as well as chromosomal DNA in combination with DNA probe.New and detailed characteristics of classified and newly isolated strains of rickettsiae and Coxiella burnettii revealed by molecular genetic differentiation techniques are discussed.New identification techniques using DNA probes in combination with restriction analysis of chromosomal from rickettsiae and both plasmid and chromosomal DNA from Coxiella burnettii are considered to have good prospects for future use in epidemiological assesment. The establishment of reference file banks containing restriction endonuclease data on the available typical and atypical strains of rickettsiae and Coxiella burnettii is suggested.Presented at the 4th European Congress of Clinical Microbiology, Nice, 17–20 April, 1989.