Richard Duerr and colleagues present a genome-wide association study of ulcerative colitis. They identify new risk loci on chromosomes 1p36 and 12q15. Ulcerative colitis is a chronic inflammatory disease of the colon that presents as diarrhea and gastrointestinal bleeding. We performed a genome-wide association study using DNA samples from 1,052 individuals with ulcerative colitis and preexisting data from 2,571 controls, all of European ancestry. In an analysis that controlled for gender and population structure, ulcerative colitis loci attaining genome-wide significance and subsequent replication in two independent populations were identified on chromosomes 1p36 (rs6426833, combined P = 5.1 × 10−13, combined odds ratio OR = 0.73) and 12q15 (rs1558744, combined P = 2.5 × 10−12, combined OR = 1.35). In addition, combined genome-wide significant evidence for association was found in a region spanning BTNL2 to HLA-DQB1 on chromosome 6p21 (rs2395185, combined P = 1.0 × 10−16, combined OR = 0.66) and at the IL23R locus on chromosome 1p31 (rs11209026, combined P = 1.3 × 10−8, combined OR = 0.56; rs10889677, combined P = 1.3 × 10−8, combined OR = 1.29).

Background: A recently developed probe-based technology, the NanoString nCounter™ gene expression system, has been shown to allow accurate mRNA transcript quantification using low amounts of total RNA. We assessed the ability of this technology for mRNA expression quantification in archived formalin-fixed, paraffin-embedded (FFPE) oral carcinoma samples. Results: We measured the mRNA transcript abundance of 20 genes (COL3A1, COL4A1, COL5A1, COL5A2, CTHRC1, CXCL1, CXCL13, MMP1, P4HA2, PDPN, PLOD2, POSTN, SDHA, SERPINE1, SERPINE2, SERPINH1, THBS2, TNC, GAPDH, RPS18) in 38 samples (19 paired fresh-frozen and FFPE oral carcinoma tissues, archived from 1997-2008) by both NanoString and SYBR Green I fluorescent dye-based quantitative real-time PCR (RQ-PCR). We compared gene expression data obtained by NanoString vs. RQ-PCR in both fresh-frozen and FFPE samples. Fresh-frozen samples showed a good overall Pearson correlation of 0.78, and FFPE samples showed a lower overall correlation coefficient of 0.59, which is likely due to sample quality. We found a higher correlation coefficient between fresh-frozen and FFPE samples analyzed by NanoString (r = 0.90) compared to fresh-frozen and FFPE samples analyzed by RQ-PCR (r = 0.50). In addition, NanoString data showed a higher mean correlation (r = 0.94) between individual fresh-frozen and FFPE sample pairs compared to RQ-PCR (r = 0.53). Conclusions: Based on our results, we conclude that both technologies are useful for gene expression quantification in fresh-frozen or FFPE tissues; however, the probe-based NanoString method achieved superior gene expression quantification results when compared to RQ-PCR in archived FFPE samples. We believe that this newly developed technique is optimal for large-scale validation studies using total RNA isolated from archived, FFPE samples.

Typical data in a microbiome study consist of the operational taxonomic unit (OTU) counts that have the characteristic of excess zeros, which are often ignored by investigators. In this paper, we compare the performance of different competing methods to model data with zero inflated features through extensive simulations and application to a microbiome study. These methods include standard parametric and non-parametric models, hurdle models, and zero inflated models. We examine varying degrees of zero inflation, with or without dispersion in the count component, as well as different magnitude and direction of the covariate effect on structural zeros and the count components. We focus on the assessment of type I error, power to detect the overall covariate effect, measures of model fit, and bias and effectiveness of parameter estimations. We also evaluate the abilities of model selection strategies using Akaike information criterion (AIC) or Vuong test to identify the correct model. The simulation studies show that hurdle and zero inflated models have well controlled type I errors, higher power, better goodness of fit measures, and are more accurate and efficient in the parameter estimation. Besides that, the hurdle models have similar goodness of fit and parameter estimation for the count component as their corresponding zero inflated models. However, the estimation and interpretation of the parameters for the zero components differs, and hurdle models are more stable when structural zeros are absent. We then discuss the model selection strategy for zero inflated data and implement it in a gut microbiome study of > 400 independent subjects.

Background: Increasing evidence shows that Human Papillomavirus (HPV) is preferentially associated with some head and neck squamous cell carcinomas (HNSCCs), with variable infection rates reported. Methods: We assessed HPV involvement in HNSCC using the Roche Linear Array HPV Genotyping Test, which can detect 37 different HPV types. We examined the prevalence of HPV infection in 92 HNSCCs (oropharynx, oral cavity, and other HNSCC sites). Results: HPV was frequently detected in oropharyngeal cancers (OPCs) (16/22, 73%), but was uncommon in oral cavity cancers (2/53, 4%), and in other HNSCC subsites (1/17, 6%). HPV positive tumors were associated with patients that were 40-60 years old (p = 0.02), and node positive (p = < 0.0001). HPV 16 was the most prevalent type, but other types detected included 6, 18, 33, 35, 45, and 52/58. Conclusion: Our results show that in contrast to oropharyngeal cancers, oral cancers and other HNSCCs infrequently harbor HPV.

Unknown primary malignancy in the head and neck is not an infrequent diagnosis for patients with metastatic cervical lymph nodes. Although linked with a relatively good prognosis following radiation treatment, widespread radiation is coupled with significant morbidity. Altered microRNA (miRNA) expression has been associated with both cancer progression and metastasis. We sought to determine whether miRNA expression analysis could be used as a diagnostic tool to discover the primary site of malignancy, within the head and neck. We used quantitative real-time PCR to identify miRNA expression profiles of squamous cell carcinoma of the tonsil, base of tongue and post-nasal space, as well as their corresponding metastatic lymph nodes, from 6 patients. Our results revealed that each cancer maintained its expression profile between the primary site and the nodal metastasis (r = 0.82, p < 0.0001). In addition, each anatomical sub-site maintained a distinct miRNA profile between individual patients (r = 0.79, p < 0.0001). Finally, between sub-sites, the miRNA profiles were distinct (p < 0.0001). As proof of principle, our study provides an indication that miRNA expression analysis may be useful to compare the primary lesion and local metastatic disease. This may be clinically relevant to predict the primary site of origin of metastatic disease, when the primary site remains obscure.

Background: MicroRNAs (miRs) are non-coding RNA molecules involved in post-transcriptional regulation, with diverse functions in tissue development, differentiation, cell proliferation and apoptosis. miRs may be less prone to degradation during formalin fixation, facilitating miR expression studies in formalin-fixed paraffin-embedded (FFPE) tissue. Results: Our study demonstrates that the TaqMan Human MicroRNA Array v1.0 (Early Access) platform is suitable for miR expression analysis in FFPE tissue with a high reproducibility (correlation coefficients of 0.95 between duplicates, p < 0.00001) and outlines the optimal performance conditions of this platform using clinical FFPE samples. We also outline a method of data analysis looking at differences in miR abundance between FFPE and fresh-frozen samples. By dividing the profiled miR into abundance strata of high (Ct35), we show that reproducibility between technical replicates, equivalent dilutions, and FFPE vs. frozen samples is best in the high abundance stratum. We also demonstrate that the miR expression profiles of FFPE samples are comparable to those of fresh-frozen samples, with a correlation of up to 0.87 (p < 0.001), when examining all miRs, regardless of RNA extraction method used. Examining correlation coefficients between FFPE and fresh-frozen samples in terms of miR abundance reveals correlation coefficients of up to 0.32 (low abundance), 0.70 (medium abundance) and up to 0.97 (high abundance). Conclusion: Our study thus demonstrates the utility, reproducibility, and optimization steps needed in miR expression studies using FFPE samples on a high-throughput quantitative PCR-based miR platform, opening up a realm of research possibilities for retrospective studies.