Fine mapping of chromosome 15q25 implicates ZNF592 in neurosarcoidosis patients

Neurosarcoidosis is a clinical subtype of sarcoidosis characterized by the presence of granulomas in the nervous system. Here, we report a highly significant association with a variant (rs75652600, P = 3.12 × 10(-8), odds ratios = 4.34) within a zinc finger gene, ZNF592, from an imputation-based fine-mapping study of the chromosomal region 15q25 in African-Americans with neurosarcoidosis. We validate the association with ZNF592, a gene previously shown to cause cerebellar ataxia, in a cohort of European-Americans with neurosarcoidosis by uncovering low-frequency variants with a similar risk effect size (chr15:85309284, P = 0.0021, odds ratios = 5.36)

Extent and distribution of linkage disequilibrium in the Old Order Amish

Knowledge of the extent and distribution of linkage disequilibrium (LD) is critical to the design and interpretation of gene mapping studies. Because the demographic history of each population varies and is often not accurately known, it is necessary to empirically evaluate LD on a population-specific basis. Here we present the first genome-wide survey of LD in the Old Order Amish (OOA) of Lancaster County Pennsylvania, a closed population derived from a modest number of founders. Specifically, we present a comparison of LD between OOA individuals and US Utah participants in the International HapMap project (abbreviated CEU) using a high-density single nucleotide polymorphism (SNP) map. Overall, the allele (and haplotype) frequency distributions and LD profiles were remarkably similar between these two populations. For example, the median absolute allele frequency difference for autosomal SNPs was 0.05, with an inter-quartile range of 0.02–0.09, and for autosomal SNPs 10–20 kb apart with common alleles (minor allele frequency≥0.05), the LD measure r 2 was at least 0.8 for 15 and 14% of SNP pairs in the OOA and CEU, respectively. Moreover, tag SNPs selected from the HapMap CEU sample captured a substantial portion of the common variation in the OOA (∼88%) at r 2 ≥0.8. These results suggest that the OOA and CEU may share similar LD profiles for other common but untyped SNPs. Thus, in the context of the common variant-common disease hypothesis, genetic variants discovered in gene mapping studies in the OOA may generalize to other populations. Genet. Epidemiol . 34: 146–150, 2010. © 2009 Wiley-Liss, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/64895/1/20444_ftp.pd

Common Variation in the BRCA1 Gene and Prostate Cancer Risk

Rare, inactivating mutations in the BRCA1 gene appear to play a limited role in prostate cancer. To our knowledge, however, no study has comprehensively assessed the role of other BRCA1 sequence variations, e.g., missense mutations, in prostate cancer. In a study of 817 men with and without prostate cancer from 323 familial and early-onset prostate cancer families, we used family-based association tests and conditional logistic regression to investigate the association between prostate cancer and single nucleotide polymorphisms (SNPs) tagging common haplotype variation in a 200 kb-region surrounding (and including) the BRCA1 gene. We also used the Genotype-IBD Sharing Test (GIST) to determine whether our most strongly associated SNP could account for prostate cancer linkage to chromosome 17q21 in a sample of 154 families from our previous genome-wide linkage study. The strongest evidence for prostate cancer association was for a glutamine-to-arginine substitution at codon 356 (Gln356Arg) in exon 11 of the BRCA1 gene. The minor (Arg) allele was preferentially transmitted to affected men (p=0.005 for a dominant model), with an estimated odds ratio of 2.25 (95% confidence interval = 1.21 to 4.20). Notably, BRCA1 Gln356Arg is not in strong linkage disequilibrium with other BRCA1 coding SNPs or any known HapMap SNP on chromosome 17. In addition, GIST results suggest that Gln356Arg accounts (in part) for our prior evidence of prostate cancer linkage to chromosome 17q21 (p=0.022). Thus, we have identified a common, non-synonymous substitution in the BRCA1 gene that is associated with and linked to prostate cancer

Efficient Generalized Least Squares Method for Mixed Population and Family‐based Samples in Genome‐wide Association Studies

Genome‐wide association studies (GWAS) that draw samples from multiple studies with a mixture of relationship structures are becoming more common. Analytical methods exist for using mixed‐sample data, but few methods have been proposed for the analysis of genotype‐by‐environment (G×E) interactions. Using GWAS data from a study of sarcoidosis susceptibility genes in related and unrelated African Americans, we explored the current analytic options for genotype association testing in studies using both unrelated and family‐based designs. We propose a novel method—generalized least squares (GLX)—to estimate both SNP and G×E interaction effects for categorical environmental covariates and compared this method to generalized estimating equations (GEE), logistic regression, the Cochran–Armitage trend test, and the W QLS and M QLS methods. We used simulation to demonstrate that the GLX method reduces type I error under a variety of pedigree structures. We also demonstrate its superior power to detect SNP effects while offering computational advantages and comparable power to detect G×E interactions versus GEE. Using this method, we found two novel SNPs that demonstrate a significant genome‐wide interaction with insecticide exposure—rs10499003 and rs7745248, located in the intronic and 3' UTR regions of the FUT9 gene on chromosome 6q16.1.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/107571/1/gepi21811.pd

Single Cell Transcriptomics Implicate Novel Monocyte and T Cell Immune Dysregulation in Sarcoidosis

Sarcoidosis is a systemic inflammatory disease characterized by infiltration of immune cells into granulomas. Previous gene expression studies using heterogeneous cell mixtures lack insight into cell-type-specific immune dysregulation. We performed the first single-cell RNA-sequencing study of sarcoidosis in peripheral immune cells in 48 patients and controls. Following unbiased clustering, differentially expressed genes were identified for 18 cell types and bioinformatically assessed for function and pathway enrichment. Our results reveal persistent activation of circulating classical monocytes with subsequent upregulation of trafficking molecules. Specifically, classical monocytes upregulated distinct markers of activation including adhesion molecules, pattern recognition receptors, and chemokine receptors, as well as enrichment of immunoregulatory pathways HMGB1, mTOR, and ephrin receptor signaling. Predictive modeling implicated TGFβ and mTOR signaling as drivers of persistent monocyte activation. Additionally, sarcoidosis T cell subsets displayed patterns of dysregulation. CD4 naïve T cells were enriched for markers of apoptosis and Th17/T(reg) differentiation, while effector T cells showed enrichment of anergy-related pathways. Differentially expressed genes in regulatory T cells suggested dysfunctional p53, cell death, and TNFR2 signaling. Using more sensitive technology and more precise units of measure, we identify cell-type specific, novel inflammatory and regulatory pathways. Based on our findings, we suggest a novel model involving four convergent arms of dysregulation: persistent hyperactivation of innate and adaptive immunity via classical monocytes and CD4 naïve T cells, regulatory T cell dysfunction, and effector T cell anergy. We further our understanding of the immunopathology of sarcoidosis and point to novel therapeutic targets

Polygenic Risk Assessment Reveals Pleiotropy between Sarcoidosis and Inflammatory Disorders in the Context of Genetic Ancestry

Sarcoidosis is a complex disease of unknown etiology characterized by the presence of granulomatous inflammation. Though various immune system pathways have been implicated in disease, the relationship between the genetic determinants of sarcoidosis and other inflammatory disorders has not been characterized. Herein, we examined the degree of genetic pleiotropy common to sarcoidosis and other inflammatory disorders to identify shared pathways and disease systems pertinent to sarcoidosis onset. To achieve this, we quantify the association of common variant polygenic risk scores from nine complex inflammatory disorders with sarcoidosis risk. Enrichment analyses of genes implicated in pleiotropic associations were further used to elucidate candidate pathways. In European-Americans, we identify significant pleiotropy between risk of sarcoidosis and risk of asthma (R2=2.03%; p=8.89×10−9), celiac disease (R2=2.03%; p=8.21×10−9), primary biliary cirrhosis (R2=2.43%; p=2.01×10−10), and rheumatoid arthritis (R2=4.32%; p=2.50×10−17). These associations validate in African Americans only after accounting for the proportion of genome-wide European ancestry, where we demonstrate similar effects of polygenic risk for African-Americans with the highest levels of European ancestry. Variants and genes implicated in European-American pleiotropic associations were enriched for pathways involving interleukin-12, interleukin-27, and cell adhesion molecules, corroborating the hypothesized immunopathogenesis of disease

Lung cancer risk test trial: study design, participant baseline characteristics, bronchoscopy safety, and establishment of a biospecimen repository

BACKGROUND: The Lung Cancer Risk Test (LCRT) trial is a prospective cohort study comparing lung cancer incidence among persons with a positive or negative value for the LCRT, a 15 gene test measured in normal bronchial epithelial cells (NBEC). The purpose of this article is to describe the study design, primary endpoint, and safety; baseline characteristics of enrolled individuals; and establishment of a bio-specimen repository. METHODS/DESIGN: Eligible participants were aged 50-90 years, current or former smokers with 20 pack-years or more cigarette smoking history, free of lung cancer, and willing to undergo bronchoscopic brush biopsy for NBEC sample collection. NBEC, peripheral blood samples, baseline CT, and medical and demographic data were collected from each subject. DISCUSSION: Over a two-year span (2010-2012), 403 subjects were enrolled at 12 sites. At baseline 384 subjects remained in study and mean age and smoking history were 62.9 years and 50.4 pack-years respectively, with 34% current smokers. Obstructive lung disease (FEV1/FVC \u3c0.7) was present in 157 (54%). No severe adverse events were associated with bronchoscopic brushing. An NBEC and matched peripheral blood bio-specimen repository was established. The demographic composition of the enrolled group is representative of the population for which the LCRT is intended. Specifically, based on baseline population characteristics we expect lung cancer incidence in this cohort to be representative of the population eligible for low-dose Computed Tomography (LDCT) lung cancer screening. Collection of NBEC by bronchial brush biopsy/bronchoscopy was safe and well-tolerated in this population. These findings support the feasibility of testing LCRT clinical utility in this prospective study. If validated, the LCRT has the potential to significantly narrow the population of individuals requiring annual low-dose helical CT screening for early detection of lung cancer and delay the onset of screening for individuals with results indicating low lung cancer risk. For these individuals, the small risk incurred by undergoing once in a lifetime bronchoscopic sample collection for LCRT may be offset by a reduction in their CT-related risks. The LCRT biospecimen repository will enable additional studies of genetic basis for COPD and/or lung cancer risk. TRIAL REGISTRATION: The LCRT Study, NCT 01130285, was registered with Clinicaltrials.gov on May 24, 2010

Overview of mathematical approaches used to model bacterial chemotaxis I: the single cell

Mathematical modeling of bacterial chemotaxis systems has been influential and insightful in helping to understand experimental observations. We provide here a comprehensive overview of the range of mathematical approaches used for modeling, within a single bacterium, chemotactic processes caused by changes to external gradients in its environment. Specific areas of the bacterial system which have been studied and modeled are discussed in detail, including the modeling of adaptation in response to attractant gradients, the intracellular phosphorylation cascade, membrane receptor clustering, and spatial modeling of intracellular protein signal transduction. The importance of producing robust models that address adaptation, gain, and sensitivity are also discussed. This review highlights that while mathematical modeling has aided in understanding bacterial chemotaxis on the individual cell scale and guiding experimental design, no single model succeeds in robustly describing all of the basic elements of the cell. We conclude by discussing the importance of this and the future of modeling in this area

Performance of HLA allele prediction methods in African Americans for class II genes HLA-DRB1, -DQB1, and -DPB1

BACKGROUND: The expense of human leukocyte antigen (HLA) allele genotyping has motivated the development of imputation methods that use dense single nucleotide polymorphism (SNP) genotype data and the region’s haplotype structure, but the performance of these methods in admixed populations (such as African Americans) has not been adequately evaluated. We compared genotype-based—derived from both genome-wide genotyping and targeted sequencing—imputation results to existing allele data for HLA–DRB1, −DQB1, and –DPB1. RESULTS: In European Americans, the newly-developed HLA Genotype Imputation with Attribute Bagging (HIBAG) method outperformed HLA*IMP:02. In African Americans, HLA*IMP:02 performed marginally better than HIBAG pre-built models, but HIBAG models constructed using a portion of our African American sample with both SNP genotyping and four-digit HLA class II allele typing had consistently higher accuracy than HLA*IMP:02. However, HIBAG was significantly less accurate in individuals heterozygous for local ancestry (p ≤0.04). Accuracy improved in models with equal numbers of African and European chromosomes. Variants added by targeted sequencing and SNP imputation further improved both imputation accuracy and the proportion of high quality calls. CONCLUSION: Combining the HIBAG approach with local ancestry and dense variant data can produce highly-accurate HLA class II allele imputation in African Americans

Single hadron response measurement and calorimeter jet energy scale uncertainty with the ATLAS detector at the LHC

The uncertainty on the calorimeter energy response to jets of particles is derived for the ATLAS experiment at the Large Hadron Collider (LHC). First, the calorimeter response to single isolated charged hadrons is measured and compared to the Monte Carlo simulation using proton-proton collisions at centre-of-mass energies of sqrt(s) = 900 GeV and 7 TeV collected during 2009 and 2010. Then, using the decay of K_s and Lambda particles, the calorimeter response to specific types of particles (positively and negatively charged pions, protons, and anti-protons) is measured and compared to the Monte Carlo predictions. Finally, the jet energy scale uncertainty is determined by propagating the response uncertainty for single charged and neutral particles to jets. The response uncertainty is 2-5% for central isolated hadrons and 1-3% for the final calorimeter jet energy scale.Comment: 24 pages plus author list (36 pages total), 23 figures, 1 table, submitted to European Physical Journal