Genetic polymorphisms in molecules of innate immunity and susceptibility to infection with Wuchereria bancrofti in South India

A pilot study was conducted to determine if host genetic factors influence susceptibility and outcomes in human filariasis. Using the candidate gene approach, a well-characterized population in South India was studied using common polymorphisms in six genes (CHIT1, MPO, NRAMP, CYBA, NCF2, and MBL2). A total of 216 individuals from South India were genotyped; 67 normal (N), 63 asymptomatic microfilaria positive (MF+), 50 with chronic lymphatic dysfunction/elephantiasis (CP), and 36 tropical pulmonary eosinophilia (TPE). An association was observed between the HH variant CHIT1 genotype, which correlates with decreased activity and levels of chitotriosidase and susceptibility to filarial infection (MF+ and CP; P = 0.013). The heterozygosity of CHIT1 gene was over-represented in the normal individuals (P = 0.034). The XX genotype of the promoter region in MBL2 was associated with susceptibility to filariasis (P = 0.0093). Since analysis for MBL-sufficient vs insufficient haplotypes was not informative, it is possible the MBL2 promoter association results from linkage disequilibrium with neighboring loci. We have identified two polymorphisms, CHIT1 and MBL2 that are associated with susceptibility to human filarial infection, findings that merit further follow-up in a larger study

A two-stage genome-wide association study of sporadic amyotrophic lateral sclerosis

The cause of sporadic amyotrophic lateral sclerosis (ALS) is largely unknown, but genetic factors are thought to play a significant role in determining susceptibility to motor neuron degeneration. To identify genetic variants altering risk of ALS, we undertook a two-stage genome-wide association study (GWAS): we followed our initial GWAS of 545 066 SNPs in 553 individuals with ALS and 2338 controls by testing the 7600 most associated SNPs from the first stage in three independent cohorts consisting of 2160 cases and 3008 controls. None of the SNPs selected for replication exceeded the Bonferroni threshold for significance. The two most significantly associated SNPs, rs2708909 and rs2708851 [odds ratio (OR) = 1.17 and 1.18, and P-values = 6.98 x 10–7 and 1.16 x 10–6], were located on chromosome 7p13.3 within a 175 kb linkage disequilibrium block containing the SUNC1, HUS1 and C7orf57 genes. These associations did not achieve genome-wide significance in the original cohort and failed to replicate in an additional independent cohort of 989 US cases and 327 controls (OR = 1.18 and 1.19, P-values = 0.08 and 0.06, respectively). Thus, we chose to cautiously interpret our data as hypothesis-generating requiring additional confirmation, especially as all previously reported loci for ALS have failed to replicate successfully. Indeed, the three loci (FGGY, ITPR2 and DPP6) identified in previous GWAS of sporadic ALS were not significantly associated with disease in our study. Our findings suggest that ALS is more genetically and clinically heterogeneous than previously recognized. Genotype data from our study have been made available online to facilitate such future endeavors

SPOT: a web-based tool for using biological databases to prioritize SNPs after a genome-wide association study

SPOT (http://spot.cgsmd.isi.edu), the SNP prioritization online tool, is a web site for integrating biological databases into the prioritization of single nucleotide polymorphisms (SNPs) for further study after a genome-wide association study (GWAS). Typically, the next step after a GWAS is to genotype the top signals in an independent replication sample. Investigators will often incorporate information from biological databases so that biologically relevant SNPs, such as those in genes related to the phenotype or with potentially non-neutral effects on gene expression such as a splice sites, are given higher priority. We recently introduced the genomic information network (GIN) method for systematically implementing this kind of strategy. The SPOT web site allows users to upload a list of SNPs and GWAS P-values and returns a prioritized list of SNPs using the GIN method. Users can specify candidate genes or genomic regions with custom levels of prioritization. The results can be downloaded or viewed in the browser where users can interactively explore the details of each SNP, including graphical representations of the GIN method. For investigators interested in incorporating biological databases into a post-GWAS SNP selection strategy, the SPOT web tool is an easily implemented and flexible solution

Retinoic acid inducible gene I Activates innate antiviral response against human parainfluenza virus type 3

Human parainfluenza virus type 3 (HPIV3) is a respiratory paramyxovirus that infects lung epithelial cells to cause high morbidity among infants and children. To date, no effective vaccine or antiviral therapy exists for HPIV3 and therefore, it is important to study innate immune antiviral response induced by this virus in infected cells. Type-I interferons (IFN, interferon-α/β) and tumor necrosis factor-α (TNFα activated by NFκB) are potent antiviral cytokines that play an important role during innate immune antiviral response. A wide-spectrum of viruses utilizes pattern recognition receptors (PRRs) like toll-like receptors (TLRs) and RLH (RIG like helicases) receptors such as RIGI (retinoic acid inducible gene -I) and Mda5 to induce innate antiviral response. Previously it was shown that both TNFα and IFNβ are produced from HPIV3 infected cells. However, the mechanism by which infected cells activated innate response following HPIV3 infection was not known. In the current study, we demonstrated that RIGI serves as a PRR in HPIV3 infected cells to induce innate antiviral response by expressing IFNβ (via activation of interferon regulatory factor-3 or IRF3) and TNFα (via activation of NF-κB)

Predicting cell types and genetic variations contributing to disease by combining GWAS and epigenetic data

Genome-wide association studies (GWASs) identify single nucleotide polymorphisms (SNPs) that are enriched in individuals suffering from a given disease. Most disease-associated SNPs fall into non-coding regions, so that it is not straightforward to infer phenotype or function; moreover, many SNPs are in tight genetic linkage, so that a SNP identified as associated with a particular disease may not itself be causal, but rather signify the presence of a linked SNP that is functionally relevant to disease pathogenesis. Here, we present an analysis method that takes advantage of the recent rapid accumulation of epigenomics data to address these problems for some SNPs. Using asthma as a prototypic example; we show that non-coding disease-associated SNPs are enriched in genomic regions that function as regulators of transcription, such as enhancers and promoters. Identifying enhancers based on the presence of the histone modification marks such as H3K4me1 in different cell types, we show that the location of enhancers is highly cell-type specific. We use these findings to predict which SNPs are likely to be directly contributing to disease based on their presence in regulatory regions, and in which cell types their effect is expected to be detectable. Moreover, we can also predict which cell types contribute to a disease based on overlap of the disease-associated SNPs with the locations of enhancers present in a given cell type. Finally, we suggest that it will be possible to re-analyze GWAS studies with much higher power by limiting the SNPs considered to those in coding or regulatory regions of cell types relevant to a given disease

Leveraging population admixture to characterize the heritability of complex traits.

Despite recent progress on estimating the heritability explained by genotyped SNPs (h(2)g), a large gap between h(2)g and estimates of total narrow-sense heritability (h(2)) remains. Explanations for this gap include rare variants or upward bias in family-based estimates of h(2) due to shared environment or epistasis. We estimate h(2) from unrelated individuals in admixed populations by first estimating the heritability explained by local ancestry (h(2)γ). We show that h(2)γ = 2FSTCθ(1 - θ)h(2), where FSTC measures frequency differences between populations at causal loci and θ is the genome-wide ancestry proportion. Our approach is not susceptible to biases caused by epistasis or shared environment. We applied this approach to the analysis of 13 phenotypes in 21,497 African-American individuals from 3 cohorts. For height and body mass index (BMI), we obtained h(2) estimates of 0.55 ± 0.09 and 0.23 ± 0.06, respectively, which are larger than estimates of h(2)g in these and other data but smaller than family-based estimates of h(2)

Making connections: technological interventions to support students in using, and tutors in creating, assessment feedback

This paper explores the potential of technology to enhance the assessment and feedback process for both staff and students. The ‘Making Connections’ project aimed to better understand the connections that students make between the feedback that they receive and future assignments, and explored whether technology can help them in this activity. The project interviewed 10 tutors and 20 students, using a semi-structured approach. Data were analysed using a thematic approach, and the findings have identified a number of areas in which improvements could be made to the assessment and feedback process through the use of technology. The findings of the study cover each stage of the assessment process from the perspective of both staff and students. The findings are discussed in the context of current literature, and special attention is given to projects from the UK higher education sector intended to address the same issues. Keywords: feed-forward; assessment; practices; technology; technology-enhanced learnin