Estimating the net contribution of interleukin-28B variation to spontaneous hepatitis C virus clearance

The identification of associations between interleukin-28B (IL-28B) variants and the spontaneous clearance of hepatitis C virus (HCV) raises the issues of causality and the net contribution of host genetics to the trait. To estimate more precisely the net effect of IL-28B genetic variation on HCV clearance, we optimized genotyping and compared the host contributions in multiple- and single-source cohorts to control for viral and demographic effects. The analysis included individuals with chronic or spontaneously cleared HCV infections from a multiple-source cohort (n = 389) and a single-source cohort (n = 71). We performed detailed genotyping in the coding region of IL-28B and searched for copy number variations to identify the genetic variant or haplotype carrying the strongest association with viral clearance. This analysis was used to compare the effects of IL-28B variation in the two cohorts. Haplotypes characterized by carriage of the major alleles at IL-28B single-nucleotide polymorphisms (SNPs) were highly overrepresented in individuals with spontaneous clearance versus those with chronic HCV infections (66.1% versus 38.6%, P = 6 × 10(-9) ). The odds ratios for clearance were 2.1 [95% confidence interval (CI) = 1.6-3.0] and 3.9 (95% CI = 1.5-10.2) in the multiple- and single-source cohorts, respectively. Protective haplotypes were in perfect linkage (r(2) = 1.0) with a nonsynonymous coding variant (rs8103142). Copy number variants were not detected. CONCLUSION: We identified IL-28B haplotypes highly predictive of spontaneous HCV clearance. The high linkage disequilibrium between IL-28B SNPs indicates that association studies need to be complemented by functional experiments to identify single causal variants. The point estimate for the genetic effect was higher in the single-source cohort, which was used to effectively control for viral diversity, sex, and coinfections and, therefore, offered a precise estimate of the net host genetic contribution.

SNPs in DNA repair genes associated to meningitis and host immune response

In vitro and in animal models, APE1, OGG1, and PARP-1 have been proposed as being involved with inflammatory response. In this work, we have investigated if the SNPs APE1 Asn148Glu, OGG1 Ser326Cys, and PARP-1 Val762Ala are associated to meningitis. The patient genotypes were investigated by PIRA-PCR or PCR-RFLP. DNA damages were detected in genomic DNA by Fpg treatment. IgG and IgA were measured from plasma and the cytokines and chemokines were measured from cerebrospinal fluid samples using Bio-Plex assays. A higher frequency (P<0.05) of APE1 Glu allele in bacterial meningitis (BM) and aseptic meningitis (AM) patients was observed. The genotypes Asn/Asn in control group and Asn/Glu in BM group was also higher. For the SNP OGG1 Ser326Cys, the genotype Cys/Cys was more frequent (P<0.05) in BM group. The frequency of PARP-1 Val/Val genotype was higher in control group (P<0.05). The occurrence of combined SNPs is significantly higher in BM patients, indicating that these SNPs may be associated to the disease. Increasing in sensitive sites to Fpg was observed in carriers of APE1 Glu allele or OGG1 Cys allele, suggesting that SNPs affect DNA repair activity. Alterations in IgG production were observed in the presence of SNPs APE1 Asn148Glu, OGG1 Ser326Cys or PARP-1 Val762Ala. Moreover, reduction in the levels of IL-6, IL-1Ra, MCP-1/CCL2 and IL-8/CXCL8 was observed in the presence of APE1 Glu allele in BM patients. In conclusion, we obtained indications of an effect of SNPs in DNA repair genes on the regulation of immune response in meningitis.

Associations between fluctuations in lung function and asthma control in two populations with differing asthma severity

Lung function is a major criterion used to assess asthma control. Fluctuation analyses can account for lung function history over time, and may provide an additional dimension to characterise control. The relationships between mean and fluctuations in lung function with asthma control, exacerbation and quality of life were studied in two independent data sets.

Two new rapid SNP-typing methods for classifying Mycobacterium tuberculosis complex into the main phylogenetic lineages

There is increasing evidence that strain variation in Mycobacterium tuberculosis complex (MTBC) might influence the outcome of tuberculosis infection and disease. To assess genotype-phenotype associations, phylogenetically robust molecular markers and appropriate genotyping tools are required. Most current genotyping methods for MTBC are based on mobile or repetitive DNA elements. Because these elements are prone to convergent evolution, the corresponding genotyping techniques are suboptimal for phylogenetic studies and strain classification. By contrast, single nucleotide polymorphisms (SNP) are ideal markers for classifying MTBC into phylogenetic lineages, as they exhibit very low degrees of homoplasy. In this study, we developed two complementary SNP-based genotyping methods to classify strains into the six main human-associated lineages of MTBC, the "Beijing" sublineage, and the clade comprising Mycobacterium bovis and Mycobacterium caprae. Phylogenetically informative SNPs were obtained from 22 MTBC whole-genome sequences. The first assay, referred to as MOL-PCR, is a ligation-dependent PCR with signal detection by fluorescent microspheres and a Luminex flow cytometer, which simultaneously interrogates eight SNPs. The second assay is based on six individual TaqMan real-time PCR assays for singleplex SNP-typing. We compared MOL-PCR and TaqMan results in two panels of clinical MTBC isolates. Both methods agreed fully when assigning 36 well-characterized strains into the main phylogenetic lineages. The sensitivity in allele-calling was 98.6% and 98.8% for MOL-PCR and TaqMan, respectively. Typing of an additional panel of 78 unknown clinical isolates revealed 99.2% and 100% sensitivity in allele-calling, respectively, and 100% agreement in lineage assignment between both methods. While MOL-PCR and TaqMan are both highly sensitive and specific, MOL-PCR is ideal for classification of isolates with no previous information, whereas TaqMan is faster for confirmation. Furthermore, both methods are rapid, flexible and comparably inexpensive.

Mapping genetic variants associated with beta-adrenergic responses in inbred mice

β-blockers and β-agonists are primarily used to treat cardiovascular diseases. Inter-individual variability in response to both drug classes is well recognized, yet the identity and relative contribution of the genetic players involved are poorly understood. This work is the first genome-wide association study (GWAS) addressing the values and susceptibility of cardiovascular-related traits to a selective β(1)-blocker, Atenolol (ate), and a β-agonist, Isoproterenol (iso). The phenotypic dataset consisted of 27 highly heritable traits, each measured across 22 inbred mouse strains and four pharmacological conditions. The genotypic panel comprised 79922 informative SNPs of the mouse HapMap resource. Associations were mapped by Efficient Mixed Model Association (EMMA), a method that corrects for the population structure and genetic relatedness of the various strains. A total of 205 separate genome-wide scans were analyzed. The most significant hits include three candidate loci related to cardiac and body weight, three loci for electrocardiographic (ECG) values, two loci for the susceptibility of atrial weight index to iso, four loci for the susceptibility of systolic blood pressure (SBP) to perturbations of the β-adrenergic system, and one locus for the responsiveness of QTc (p<10(-8)). An additional 60 loci were suggestive for one or the other of the 27 traits, while 46 others were suggestive for one or the other drug effects (p<10(-6)). Most hits tagged unexpected regions, yet at least two loci for the susceptibility of SBP to β-adrenergic drugs pointed at members of the hypothalamic-pituitary-thyroid axis. Loci for cardiac-related traits were preferentially enriched in genes expressed in the heart, while 23% of the testable loci were replicated with datasets of the Mouse Phenome Database (MPD). Altogether these data and validation tests indicate that the mapped loci are relevant to the traits and responses studied.

Examining The Genetic, Social-Cognitive, And Neural Correlates Of Autism Spectrum Disorder Behaviors In Typically Developing Chi

Autism spectrum disorders (ASD) are pervasive developmental disorders that affect approximately 1 in 50 children (Blumberg et al., 2013). Due to the social nature of the deficits that characterize the disorders, many have classified them as disorders of social cognition, which is the process that individuals use in order to successfully interact with members of their own species (Frith & Frith, 2007). Previous research has typically neglected the spectrum nature of ASD in favor of a more categorical approach of ¿autistic¿ versus ¿non-autistic,¿ but the spectrum requires a more continuous approach. Thus, the present study sought to examine the genetic, social-cognitive, and neural correlates of ASD-like traits as well as the relationship between these dimensions in typically developing children. Parents and children completed several quantitative measures examining several areas of social-cognitive functioning, including theory of mind and social functioning, restricted/repetitive behaviors and interests, and adaptive/maladaptive functioning. Children were also asked to undergo an EEG and both parents and children contributed a saliva sample that was used to sequence four single nucleotide polymorphisms (SNPs) of the OXTR gene, rs1042778, rs53576, rs2254298, and rs237897. We successfully demonstrated a significant relationship between behavioral measures of social-cognition and differences in face perception via the N170. However, the directionality of these relationships varied based on the behavioral measure and particular N170 difference scores. We also found support for the associations between the G_G allelic combination of rs1042778 and the A_A and A_G allelic combinations of rs2254298 and increased ASD-like behavior with decreased social-cognitive functioning. In contrast, our results contradict previous findings with rs237897 and imply that individuals with the A_A and A_G genotypes are less similar to those with ASD and have higher social cognitive functioning than those with the G_G genotype. In conclusion, we have demonstrated the existence of ASD-like traits in typically developing children and have shown a link between behavioral, genetic, and neural correlates of social-cognition. These findings demonstrate the importance of considering autism as a spectrum disorder and provide support for the move to a more continuous approach to neurodevelopmental disorders.

Associations between prion protein genotype and type traits in East Friesian milk sheep

Linear models were used to analyse the relationships between the prion protein genotypes and the height at the withers and rump, the heart girth and the length of the trunk of 440 East Friesian milk sheep. Significant associations were found between the ARR allele and the height of the withers and rump, and heart girth. The average height at the withers of the homozygous ARR/ARR sheep was 1.9 cm less than that of ARQ/ARQ sheep and 1.6 cm less than in sheep heterozygous for ARR; the height at the rump, length of the trunk and heart girth were similarly smaller. In the ARR/ARR ewes, the average height at the withers was 2.6 cm less and the height at the rump was 1.9 cm less than in the ARQ/ARQ ewes.

Assessment of population structure by single nucleotide polymorphisms (SNPs) in goat breeds

Single nucleotide polymorphisms (SNPs) may be used in biodiversity studies and commercial tasks like traceability, paternity testing and selection for suitable genotypes. Twenty-seven SNPs were characterized and genotyped on 250 individuals belonging to eight Italian goat breeds. Multilocus genotype data were used to infer population structure and assign individuals to populations. To estimate the number of groups (K) to test in population structure analysis we used likelihood values and variance of the bootstrap samples, deriving optimal K from a drop in the likelihood and a rise in the variance plots against K.

A graph theoretic approach to testing associations between disparate sources of functional genomic data

The last few years have seen the advent of high-throughput technologies to analyze various properties of the transcriptome and proteome of several organisms. The congruency of these different data sources, or lack thereof, can shed light on the mechanisms that govern cellular function. A central challenge for bioinformatics research is to develop a unified framework for combining the multiple sources of functional genomics information and testing associations between them, thus obtaining a robust and integrated view of the underlying biology. We present a graph theoretic approach to test the significance of the association between multiple disparate sources of functional genomics data by proposing two statistical tests, namely edge permutation and node label permutation tests. We demonstrate the use of the proposed tests by finding significant association between a Gene Ontology-derived "predictome" and data obtained from mRNA expression and phenotypic experiments for Saccharomyces cerevisiae. Moreover, we employ the graph theoretic framework to recast a surprising discrepancy presented in Giaever et al. (2002) between gene expression and knockout phenotype, using expression data from a different set of experiments.