Background The lung microbiome’s contribution to IPF pathogenesisis unknown. Using COMET-IPF (Correlating Outcomes with biochemical Markers to Estimate Time-progression in Idiopathic Pulmonary Fibrosis), the goal of this study was to determine whether unique microbial signatures would associate with disease progression. Methods IPF subjects within four years of diagnosis aged 35–80 were eligible for inclusion. Subjects were followed for up to a maximum of 80 weeks. This completed observational study is registered with ClinicalTrials.gov, number NCT01071707. Progression-free survival was defined as death, acute exacerbation, lung transplant, or decline in FVC of 10% or DLCO of 15%.DNA was isolated from 55 bronchoscopic alveolar lavage (BAL) samples. 454 pyrosequencing was used to assign operational taxonomic units (OTUs) based on a 3% sequence divergence. Adjusted Cox models identified OTUs significantly associated with progression-free survival at a p<0·10 level. These OTUs were then used in principal components (PC) analysis. The association between PCs and microbes with high factor loadings from the PC analysis and progression-free survival were examined via Cox regression analyses. Findings Mean FVC was 70·1% and mean DLCO 42·3 %predicted. Significant associations with disease progression were noted with increased % relative abundance of two OTUs identified by PC analysis, a Streptococcus OTU. (p<0·0009) and a Staphylococcus OTU(p=0·01). Strength of associations using PCs versus two OTUs alone was similar. Threshold analysis helped define a cut point for % relative abundance for each OTU associated with progression-free survival, >3·9% for the Streptococcus OTU, HR 10·19 (95% CI 2·94, 35·35; p=0·0002) and >1·8% for the Staphylococcus OTU, HR 5·06 (1·71, 14·93; p=0·003). Interpretation These preliminary data suggest IPF disease progression is associated with presence of specific members within the Staphylococcus and Streptococcus genera.
Idiopathic pulmonary fibrosis (IPF) is a progressive fibrotic lung disease without effective therapeutics. Periostin has been reported to be elevated in IPF patients relative to controls, but its sources and mechanisms of action remain unclear. We confirm excess periostin in lungs of IPF patients and show that IPF fibroblasts produce periostin. Blood was obtained from 54 IPF patients (all but 1 with 48 wk of follow-up). We show that periostin levels predict clinical progression at 48 wk (hazard ratio = 1.47, 95% confidence interval = 1.03–2.10, P < 0.05). Monocytes and fibrocytes are sources of periostin in circulation in IPF patients. Previous studies suggest that periostin may regulate the inflammatory phase of bleomycin-induced lung injury, but periostin effects during the fibroproliferative phase of the disease are unknown. Wild-type and periostin-deficient (periostin−/−) mice were anesthetized and challenged with bleomycin. Wild-type mice were injected with bleomycin and then treated with OC-20 Ab (which blocks periostin and integrin interactions) or control Ab during the fibroproliferative phase of disease, and fibrosis and survival were assessed. Periostin expression was upregulated quickly after treatment with bleomycin and remained elevated. Periostin−/− mice were protected from bleomycin-induced fibrosis. Instillation of OC-20 during the fibroproliferative phase improved survival and limited collagen deposition. Chimeric mouse studies suggest that hematopoietic and structural sources of periostin contribute to lung fibrogenesis. Periostin was upregulated by transforming growth factor-β in lung mesenchymal cells, and periostin promoted extracellular matrix deposition, mesenchymal cell proliferation, and wound closure. Thus periostin plays a vital role in late stages of pulmonary fibrosis and is a potential biomarker for disease progression and a target for therapeutic intervention.
Background & Aims Lynch Syndrome is the most common hereditary colorectal cancer (CRC) syndrome. Previous estimates of lifetime risk for CRC and endometrial cancer (EC) did not control for ascertainment and were susceptible to bias towards overestimated risk. Methods We studied 147 families with mismatch repair (MMR) gene mutations (55 MLH1, 81 MSH2, and 11 MSH6) identified at 2 U.S. cancer genetics clinics. Age-specific cumulative risks (penetrance) and hazard ratio (HR) estimates of CRC and EC risks were calculated and compared to the general population using modified segregation analysis. The likelihood for each pedigree was conditioned on the proband and first-degree relatives affected with CRC to reduce ascertainment bias and overestimation of penetrance. Results We analyzed 628 cases of CRC, diagnosed at median ages of 42 and 47 years for men and women, respectively. Cumulative risk of CRC was 66.08% (95% confidence interval [CI 59.47%–76.17%) for men and 42.71% (95% CI 36.57%–52.83%) for women, with overall HRs of 148.4 and 51.1, respectively. CRC risk was highest for males with mutations in MLH1. There were 155 cases of EC, diagnosed at median age of 47.5 years. Cumulative risk of EC was 39.39% (95% CI 30.78%–46.94%) with overall HR of 39.0% (95% CI 30.4%–50.2%). For women, the cumulative risk of CRC or EC was 73.42% (95% CI 63.76%–80.54%). Conclusions Lifetime risks of CRC and EC in MMR gene mutation carriers are high even after adjusting for ascertainment. These estimates are valuable for patients and providers; specialized cancer surveillance is necessary.
The composite physiologic index(CPI) was derived to represent the extent of fibrosis on high resolution computed tomography, adjusting for emphysema in patients with idiopathic pulmonary fibrosis(IPF). We hypothesized longitudinal change in CPI would better predict mortality than forced expiratory volume in 1 second(FEV1), forced vital capacity(FVC), or diffusing capacity for carbon monoxide(DLCO) in all patients with IPF, and especially in those with combined pulmonary fibrosis and emphysema(CPFE). Cox proportional hazard models were performed on pulmonary function data from IPF patients at baseline (n=321), 6 months (n=211) and 12 months (n=144). Presence of CPFE was determined by high resolution computed tomography. A 5 point increase in CPI over 12 months predicted subsequent mortality (HR 2.1, p=0.004). At 12 months, a 10% relative decline in FVC, a 15% relative decline in DLCO or an absolute increase in CPI of 5 points all discriminated median survival by 2.1 to 2.2 years versus patients with lesser change. Half our cohort had CPFE. In patients with moderate/severe emphysema, only a 10% decline in FEV1 predicted mortality (HR 3.7, p=0.046). In IPF, a 5 point increase in CPI over 12 months predicts mortality similarly to relative declines of 10% in FVC or 15% in DLCO. For CPFE patients, change in FEV1 was the best predictor of mortality.
BackgroundHepatocellular carcinoma (HCC) has limited treatment options in patients with advanced stage disease and early detection of HCC through surveillance programs is a key component towards reducing mortality. The current practice guidelines recommend that high-risk cirrhosis patients are screened every six months with ultrasonography but these are done in local hospitals with variable quality leading to disagreement about the benefit of HCC surveillance. The well-established diagnostic biomarker α-Fetoprotein (AFP) is used widely in screening but the reported performance varies widely across studies. We evaluate two biomarker screening approaches, a six-month risk prediction model and a parametric empirical Bayes (PEB) algorithm, in terms of their ability to improve the likelihood of early detection of HCC compared to current AFP alone when applied prospectively in a future study.MethodsWe used electronic medical records from the Department of Veterans Affairs Hepatitis C Clinical Case Registry to construct our analysis cohort, which consists of serial AFP tests in 11,222 cirrhosis control patients and 902 HCC cases prior to their HCC diagnosis. The six-month risk prediction model incorporates routinely measured laboratory tests, age, the rate of change in AFP over the past year with the current AFP. The PEB algorithm incorporates prior AFP screening values to identify patients with a significant elevated level of AFP at their current screen. We split the analysis cohort into independent training and validation datasets. All model fitting and parameter estimation was performed using the training data and the algorithm performance was assessed by applying each approach to patients in the validation dataset.ResultsWhen the screening-level false positive rate was set at 10%, the patient-level true positive rate using current AFP alone was 53.88% while the patient-level true positive rate for the six-month risk prediction model was 58.09% (4.21% increase) and PEB approach was 63.64% (9.76% increase). Both screening approaches identify a greater proportion of HCC cases earlier than using AFP alone.ConclusionsThe two approaches show greater potential to improve early detection of HCC compared to using the current AFP only and are worthy of further study.Electronic supplementary materialThe online version of this article (10.1186/s12874-017-0458-6) contains supplementary material, which is available to authorized users.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.