Citations

Key Points A recurring mutation in NDUFB11 causes congenital sideroblastic anemia. The NDUFB11 p.93del mutation impairs erythroid proliferation, but not differentiation.

SummaryBackgroundClostridium difficile infection (CDI) may not respond to initial therapy and frequently recurs, but predictors of response and recurrence are inconsistent. The impact of specific alterations in the gut microbiota determining treatment response and recurrence in patients with CDI is unknown.AimTo assess microbial signatures as predictors of treatment response and recurrence in CDI.MethodsPre‐treatment stool samples and clinical metadata including outcomes were collected prospectively from patients with their first CDI episode. Next generation 16s rRNA sequencing using MiSeq Illumina platform was performed and changes in microbial community structure were correlated with CDI outcomes.ResultsEighty‐eight patients (median age 52.7 years, 60.2% female) were included. Treatment failure occurred in 12.5% and recurrence after response in 28.5%. Patients who responded to treatment had an increase in Ruminococcaceae, Rikenellaceae, Clostridiaceae, Bacteroides, Faecalibacterium and Rothia compared to nonresponders. A risk‐index built from this panel of microbes differentiated responders (mean 0.07 ± 0.24) from nonresponders (0.52 ± 0.42; P = 0.0002). Receiver operating characteristic (ROC) curve demonstrated that risk‐index was a strong predictor of treatment response with an area under the curve (AUC) of 0.85. Among clinical parameters tested, only proton pump inhibitor use predicted recurrent CDI (OR 3.75, 95% CI 1.27–11.1, P = 0.01). Patients with recurrent CDI had statistically significant increases in Veillonella, Enterobacteriaceae, Streptococci, Parabacteroides and Lachnospiraceae compared to patients without recurrence and a risk index was able to predict recurrence (AUC = 0.78).ConclusionGut microbiota signatures predict treatment response and recurrence potentially, allowing identification of patients with Clostridium difficile infection that may benefit from early institution of alternate therapies.

ObjectiveThe Rituximab in ANCA‐Associated Vasculitis (RAVE) trial compared rituximab to cyclophosphamide as induction therapy for the treatment of antineutrophil cytoplasmic antibody (ANCA)–associated vasculitis. We undertook the current study to determine whether known single‐nucleotide polymorphisms (SNPs) for Fcγ receptors (FcγR) or cytochrome P450 (CYP) enzymes were associated with the response to treatment with rituximab and cyclophosphamide, respectively.MethodsFunctional SNPs for FcγR (FcγRIIa 519G>A, FcγRIIb 695T>C, FcγRIIIa 559T>G) and CYP enzymes (CYP2B6 1459C>T, CYP2C19 681G>A) were analyzed by direct sequencing of polymerase chain reaction–amplified genomic DNA. Each SNP was tested as a predictor of complete remission at 6 months or remission with continued prednisone administration using logistic regression and including the covariates of baseline Birmingham Vasculitis Activity Score for Wegener's Granulomatosis, ANCA type, and new versus relapsing disease. The associations of these SNPs with the secondary outcomes of time to complete remission, time to relapse, or time to B cell reconstitution were analyzed by Cox proportional hazard tests.ResultsNo significant associations were identified between complete remission and any FcγR genotype in the rituximab group or any CYP genotype in the cyclophosphamide group. However, when the treatment groups were combined, an association was found between the 519AA genotype of FcγRIIa and complete remission (P = 0.01). The 519AA genotype predicted complete remission (P = 0.006) and a shorter time to complete remission (P < 0.001).ConclusionThe finding that the homozygous FcγRIIa 519AA variant was associated with complete response and a shorter time to complete response in the RAVE trial, independent of treatment type, implies that FcγRIIa may be broadly involved in disease pathogenesis and response to therapy.

Quantitative computed tomography-based finite-element analysis (QCT/FEA) has become increasingly popular in an attempt to understand and possibly reduce vertebral fracture risk. It is known that scanning acquisition settings affect Hounsfield units (HU) of the CT voxels. Material properties assignments in QCT/FEA, relating HU to Young's modulus, are performed by applying empirical equations. The purpose of this study was to evaluate the effect of QCT scanning protocols on predicted stiffness values from finite-element models. One fresh frozen cadaveric torso and a QCT calibration phantom were scanned six times varying voltage and current and reconstructed to obtain a total of 12 sets of images. Five vertebrae from the torso were experimentally tested to obtain stiffness values. QCT/FEA models of the five vertebrae were developed for the 12 image data resulting in a total of 60 models. Predicted stiffness was compared to the experimental values. The highest percent difference in stiffness was approximately 480% (80 kVp, 110 mAs, U70), while the lowest outcome was ∼1% (80 kVp, 110 mAs, U30). There was a clear distinction between reconstruction kernels in predicted outcomes, whereas voltage did not present a clear influence on results. The potential of QCT/FEA as an improvement to conventional fracture risk prediction tools is well established. However, it is important to establish research protocols that can lead to results that can be translated to the clinical setting.

Abstract Background Irritable bowel syndrome (IBS) is a complex condition with multiple factors contributing to its aetiology and pathophysiology. Aetiologically these include genetics, life‐time events and environment, and physiologically, changes in motility, central processing, visceral sensitivity, immunity, epithelial permeability and gastrointestinal microflora. Such complexity means there is currently no specific reliable biomarker for IBS, and thus IBS continues to be diagnosed and classified according to symptom based criteria, the Rome Criteria. Carefully phenotyping and characterisation of a ‘large’ pool of IBS patients across Europe and even the world however, might help identify sub‐populations with accuracy and consistency. This will not only aid future research but improve tailoring of treatment and health care of IBS patients. Purpose The aim of this position paper is to discuss the requirements necessary to standardize the process of selecting and phenotyping IBS patients and how to organise the collection and storage of patient information/samples in such a large multi‐centre pan European/global study. We include information on general demographics, gastrointestinal symptom assessment, psychological factors, quality of life, physiological evaluation, genetic/epigenetic and microbiota analysis, biopsy/blood sampling, together with discussion on the organisational, ethical and language issues associated with implementing such a study. The proposed approach and documents selected to be used in such a study was the result of a thoughtful and thorough four‐year dialogue amongst experts associated with the European COST action BM1106 GENIEUR ( www.GENIEUR.eu ).

BACKGROUNDPatients with FMS like tyrosine kinase 3 (FLT3)‐mutated acute myeloid leukemia (AML) have a poor prognosis and are referred for early allogeneic hematopoietic stem cell transplantation (HCT).METHODSData from the Center for International Blood and Marrow Transplant Research (CIBMTR) were used to evaluate 511 adult patients with de novo AML who underwent HCT during 2008 through 2011 to determine whether FLT3 mutations had an impact on HCT outcomes.RESULTSIn total, 158 patients (31%) had FLT3 mutations. Univariate and multivariate analyses revealed an increased risk of relapse at 3 years in the FLT3 mutated group compared with the wild‐type (WT) group (38% [95% confidence interval (CI), 30%‐45%] vs 28% [95% CI, 24%‐33%]; P = .04; relative risk, 1.60 [95% CI, 1.15‐2.22]; P = .0048). However, FLT3 mutation status was not significantly associated with nonrelapse mortality, leukemia‐free survival, or overall survival. Although more patients in the FLT3 mutated group died from relapsed primary disease compared with those in the WT group (60% vs 46%), the 3‐year overall survival rate was comparable for the 2 groups (mutated group: 49%; 95% CI, 40%‐57%; WT group: 55%, 95% CI, 50%‐60%; P = .20).CONCLUSIONSThe current data indicate that FLT3 mutation status did not adversely impact overall survival after HCT, and about 50% of patients with this mutation who underwent HCT were long‐term survivors. Cancer 2016;122:3005‐3014. © 2016 American Cancer Society.

Objectives: The primary objective of NRG Oncology Radiation Therapy Oncology Group 0123 was to test the ability of the angiotensin-converting enzyme inhibitor captopril to alter the incidence of pulmonary damage after radiation therapy for lung cancer; secondary objectives included analyzing pulmonary cytokine expression, quality of life, and the long-term effects of captopril. Materials and Methods: Eligible patients included stage II-IIIB non–small cell lung cancer, stage I central non–small cell lung cancer, or limited-stage small cell. Patients who met eligibility for randomization at the end of radiotherapy received either captopril or standard care for 1 year. The captopril was to be escalated to 50 mg three times a day. Primary endpoint was incidence of grade 2+ radiation-induced pulmonary toxicity in the first year. Results: Eighty-one patients were accrued between June 2003 and August 2007. Given the low accrual rate, the study was closed early. No significant safety issues were encountered. Eight patients were ineligible for registration or withdrew consent before randomization and 40 patients were not randomized postradiation. Major reasons for nonrandomization included patients’ refusal and physician preference. Of the 33 randomized patients, 20 were analyzable (13 observation, 7 captopril). The incidence of grade 2+ pulmonary toxicity attributable to radiation therapy was 23% (3/13) in the observation arm and 14% (1/7) in the captopril arm. Conclusions: Despite significant resources and multiple amendments, NRG Oncology Radiation Therapy Oncology Group 0123 was unable to test the hypothesis that captopril mitigates radiation-induced pulmonary toxicity. It did show the safety of such an approach and the use of newer angiotensin-converting enzyme inhibitors started during radiotherapy may solve the accrual problems.

Abstract Objective Health care generated data have become an important source for clinical and genomic research. Often, investigators create and iteratively refine phenotype algorithms to achieve high positive predictive values (PPVs) or sensitivity, thereby identifying valid cases and controls. These algorithms achieve the greatest utility when validated and shared by multiple health care systems. Materials and Methods We report the current status and impact of the Phenotype KnowledgeBase (PheKB, http://phekb.org ), an online environment supporting the workflow of building, sharing, and validating electronic phenotype algorithms. We analyze the most frequent components used in algorithms and their performance at authoring institutions and secondary implementation sites. Results As of June 2015, PheKB contained 30 finalized phenotype algorithms and 62 algorithms in development spanning a range of traits and diseases. Phenotypes have had over 3500 unique views in a 6-month period and have been reused by other institutions. International Classification of Disease codes were the most frequently used component, followed by medications and natural language processing. Among algorithms with published performance data, the median PPV was nearly identical when evaluated at the authoring institutions (n = 44; case 96.0%, control 100%) compared to implementation sites (n = 40; case 97.5%, control 100%). Discussion These results demonstrate that a broad range of algorithms to mine electronic health record data from different health systems can be developed with high PPV, and algorithms developed at one site are generally transportable to others. Conclusion By providing a central repository, PheKB enables improved development, transportability, and validity of algorithms for research-grade phenotypes using health care generated data.