Brent Richter

Single nucleotide polymorphisms in innate immunity genes: abundant variation and potential role in complex human disease.

Summary: Under selective pressure from infectious microorganisms, multicellular organisms have evolved immunological defense mechanisms, broadly categorized as innate or adaptive. Recent insights into the complex mechanisms of human innate immunity suggest that genetic variability in genes encoding its components may play a role in the development of asthma and related diseases. As part of a systematic assessment of genetic variability in innate immunity genes, we have thus far have examined 16 genes by resequencing 93 unrelated subjects from three ethnic samples (European American, African American and Hispanic American) and a sample of European American asthmatics. Approaches to discovering and understanding variation and the subsequent implementation of disease association studies are described and illustrated. Although highly conserved across a wide range of species, the innate immune genes we have sequenced demonstrate substantial interindividual variability predominantly in the form of single nucleotide polymorphisms (SNPs). Genetic variation in these genes may play a role in determining susceptibility to a range of common, chronic human diseases which have an inflammatory component. Differences in population history have produced distinctive patterns of SNP allele frequencies, linkage disequilibrium and haplotypes when ethnic groups are compared. These and other factors must be taken into account in the design and analysis of disease association studies.

TBX21: A functional variant predicts improvement in asthma with the use of inhaled corticosteroids

TBX21 encodes for the transcription factor T-bet (T-box expressed in T cells), which influences naïve T lymphocyte development and has been implicated in asthma pathogenesis. Specifically, the T-bet knockout mouse spontaneously develops airway hyperresponsiveness and other changes consistent with asthma. Because airway responsiveness is moderated by the use of inhaled corticosteroids in asthma, it is conceivable that genetic variation in TBX21 may alter asthma phenotypes in a treatment-specific fashion. Here we demonstrate that the nonsynonymous variation in TBX21 coding for replacement of histidine 33 with glutamine is associated with significant improvement in the PC20 (a measure of airway responsiveness) of asthmatic children in a large clinical trial spanning 4 years. We note that this increase occurs only in the children randomized to inhaled corticosteroids and that it dramatically enhances the overall improvement in PC20 associated with inhaled corticosteroid usage. The average PC20 at trial end for subjects on inhaled corticosteroids possessing a variant allele was in the normal range for nonasthmatics. In cellular models, we show that the TBX21 variant increases T helper 1 and decreases T helper 2 cytokine expression comparably with wild type. TBX21 may thus be an important determinant pharmacogenetic response to the therapy of asthma with inhaled corticosteroids.

The IL12B Gene Is Associated with Asthma

The IL12B gene on chromosome 5q31-33 encodes the p40 subunit of interleukin 12, an immunomodulatory cytokine. To test the hypothesis that the IL12B gene contains polymorphisms associated with asthma, we genotyped six haplotype-tagging polymorphisms in the IL12B gene, both in 708 children enrolled in the Childhood Asthma Management Program (CAMP) and in their parents. Using the family-based association test (FBAT) program and its haplotype (HBAT) and phenotype (PBAT) options, we tested each polymorphism and haplotype for association with asthma and asthma-related phenotypes. We tested positive associations for replication in a case-control study comparing 177 adult moderate-to-severe asthmatics with 177 nonasthmatic controls. In whites in the CAMP cohort, the A allele of the IL12B G4237A polymorphism was undertransmitted to asthmatic children (P=.0008, recessive model), the global test for haplotypes for affection status was positive (P=.009, multiallelic chi (2)), and two polymorphisms were associated with different atopy phenotypes. In addition, we found a strong association between the IL12B_4237 and IL12B_6402 polymorphisms and an asthma-severity phenotype in whites, which we also found in the independent population of white adult asthmatics. IL12B may be an important asthma gene.

Managing and Analyzing Next-Generation Sequence Data

Centralized Bioinformatics Core Facilities provide shared resources for the computational and IT requirements of the investigators in their department or institution. As such, they must be able to effectively react to new types of experimental technology. Recently faced with an unprecedented flood of data generated by the next generation of DNA sequencers, these groups found it necessary to respond quickly and efficiently to the informatics and infrastructure demands. Centralized Facilities newly facing this challenge need to anticipate time and design considerations of necessary components, including infrastructure upgrades, staffing, and tools for data analyses and management. The evolution of the sequencing instrumentation is far from static. Sequence throughput from this new generation of instruments continues to increase exponentially at the same time that the cost of sequencing a genome continues to fall. These realities make the technology accessible to greater numbers of investigators while leading them to a greater usage of sequencing for a variety of experimental techniques, including variation discovery, whole transcriptome analysis, and DNA–protein interaction analysis. This places unique challenges upon the Bioinformatics Core Facility, whose mission could vary from the support of a single department or sequencing core to a Facility that supports many disparate and independent groups that run their own sequencers but rely on the Central Facility to host the informatics, research cyberinfrastructures, or both. It is worth noting that the initial investment in the instrument is accompanied by an almost equal investment in upgrading the informatics infrastructure of the institution, hiring staff to analyze the data produced by the instrument, and storing the data for future use. Many investigators do not realize that these extensive investments are necessary prior to purchasing the new technology. This is why it is advantageous to have a centralized Bioinformatics Core to put in place platforms that acquire, store, and analyze the very large datasets created by these instruments. A Bioinformatics Core, already familiar with data of this type and complexity, dedicated to investigators, and jointly working with IT personnel, can span multiple domains rather effortlessly. The large sequencing centers (e.g., Sanger, Broad Institute, and Washington University) have automated processes and architectures not generally replicable in medium and small sequencing groups. However, as these smaller groups obtain next-generation technology they can nevertheless learn lessons from the larger centers. Through collaboration and sharing best practices, small and medium-sized groups can prepare for the arrival of the technology and develop methods to manage and analyze the data. The Bioinfo-Core Special Interest Group [1], affiliated with the International Society for Computational Biology, has been actively collaborating to formulate best practices to assist small and medium-sized Cores in setting up platforms for next-generation sequencing. Here, we provide a Perspective for such a Core Facility in accomplishing this task, using collective experiences from Facilities that have solved many of these issues.

Polymorphisms in signal transducer and activator of transcription 3 and lung function in asthma

BackgroundIdentifying genetic determinants for lung function is important in providing insight into the pathophysiology of asthma. Signal transducer and activator of transcription 3 is a transcription factor latent in the cytoplasm; the gene (STAT3) is activated by a wide range of cytokines, and may play a role in lung development and asthma pathogenesis.MethodsWe genotyped six single nucleotide polymorphisms (SNPs) in the STAT3 gene in a cohort of 401 Caucasian adult asthmatics. The associations between each SNP and forced expiratory volume in 1 second (FEV1), as a percent of predicted, at the baseline exam were tested using multiple linear regression models. Longitudinal analyses involving repeated measures of FEV1 were conducted with mixed linear models. Haplotype analyses were conducted using imputed haplotypes. We completed a second association study by genotyping the same six polymorphisms in a cohort of 652 Caucasian children with asthma.ResultsWe found that three polymorphisms were significantly associated with baseline FEV1: homozygotes for the minor alleles of each polymorphism had lower FEV1 than homozygotes for the major alleles. Moreover, these associations persisted when we performed an analysis on repeated measures of FEV1 over 8 weeks. A haplotypic analysis based on the six polymorphisms indicated that two haplotypes were associated with baseline FEV1. Among the childhood asthmatics, one polymorphism was associated with both baseline FEV1 and the repeated measures of FEV1 over 4 years.ConclusionOur results indicate that genetic variants in STAT3, independent of asthma treatment, are determinants of FEV1 in both adults and children with asthma, and suggest that STAT3 may participate in inflammatory pathways that have an impact on level of lung function.

Current state of information technologies for the clinical research enterprise across academic medical centers.

Information technology (IT) to support clinical research has steadily grown over the past 10 years. Many new applications at the enterprise level are available to assist with the numerous tasks necessary in performing clinical research. However, it is not clear how rapidly this technology is being adopted or whether it is making an impact upon how clinical research is being performed. The Clinical Research Forum’s IT Roundtable performed a survey of 17 representative academic medical centers (AMCs) to understand the adoption rate and implementation strategies within this field. The results were compared with similar surveys from 4 and 6 years ago. We found the adoption rate for four prominent areas of IT‐supported clinical research had increased remarkably, specifically regulatory compliance, electronic data capture for clinical trials, data repositories for secondary use of clinical data, and infrastructure for supporting collaboration. Adoption of other areas of clinical research IT was more irregular with wider differences between AMCs. These differences appeared to be partially due to a set of openly available applications that have emerged to occupy an important place in the landscape of clinical research enterprise‐level support at AMC’s. Clin Trans Sci 2012; Volume #: 1–4

The need for centralization of computational biology resources.

Biomedical research is benefiting from the wealth of new data generated in the laboratory through new instrumentation, greater computational resources, and massive repositories of public domain data. Using these data to make scientific discoveries is sometimes straightforward, but can be complicated by the number and breadth of public sources available to the researcher as well as by the plethora of tools from which to choose. Complex searches, analyses, or even storage needs require more computational expertise than that available within an individual laboratory. As biomedical researchers develop more computational skills, this may change over time. Having a centralized group of experts in computational biology can be of great value to the experimental biologist, and, recognizing this, many organizations have invested in building a team of computational biologists, bioinformaticists, and research IT services to address the needs of the investigators. This Editorial presents our views on the benefits and challenges of centralizing these activities. In order to benefit from expertise among existing teams of experts around the world, the “Bioinfo-Core” group was formed during the ISMB 2002 meeting in Edmonton, Canada, with approximately 25 initial members. Since then, the group has expanded in both organization and interest. Our worldwide membership now includes more than 150 people who administer centralized bioinformatics and research computing facilities within diverse organizations, including academia, independent research institutes, academic medical centers, and industry. Additionally, the group holds quarterly meetings via teleconference, continues an annual face-to-face meeting at ISMB (averaging 40–60 people), and hosts a mailing list and Wiki (http://www.bioinfo-core.org) to further communication.