Diaphragm adaptations in patients with COPD

Inspiratory muscle weakness in patients with COPD is of major clinical relevance. For instance, maximum inspiratory pressure generation is an independent determinant of survival in severe COPD. Traditionally, inspiratory muscle weakness has been ascribed to hyperinflation-induced diaphragm shortening. However, more recently, invasive evaluation of diaphragm contractile function, structure, and biochemistry demonstrated that cellular and molecular alterations occur, of which several can be considered pathologic of nature. Whereas the fiber type shift towards oxidative type I fibers in COPD diaphragm is regarded beneficial, rendering the overloaded diaphragm more resistant to fatigue, the reduction of diaphragm fiber force generation in vitro likely contributes to diaphragm weakness. The reduced diaphragm force generation at single fiber level is associated with loss of myosin content in these fibers. Moreover, the diaphragm in COPD is exposed to oxidative stress and sarcomeric injury. This review postulates that the oxidative stress and sarcomeric injury activate proteolytic machinery, leading to contractile protein wasting and, consequently, loss of force generating capacity of diaphragm fibers in patients with COPD. Interestingly, several of these presumed pathologic alterations are already present early in the course of the disease (GOLD I/II), although these patients appear not limited in their daily life activities. Treatment of diaphragm dysfunction in COPD is complex since its etiology is unclear, but recent findings indicate the ubiquitin-proteasome pathway as a prime target to attenuate diaphragm wasting in COPD.     

Determining the quality and complexity of next-generation sequencing data without a reference genome

We describe an open-source kPAL package that facilitates an alignment-free assessment of the quality and comparability of sequencing datasets by analyzing k-mer frequencies. We show that kPAL can detect technical artefacts such as high duplication rates, library chimeras, contamination and differences in library preparation protocols. kPAL also successfully captures the complexity and diversity of microbiomes and provides a powerful means to study changes in microbial communities. Together, these features make kPAL an attractive and broadly applicable tool to determine the quality and comparability of sequence libraries even in the absence of a reference sequence. kPAL is freely available at https://github.com/LUMC/kPAL.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-014-0555-3) contains supplementary material, which is available to authorized users.     

Surprising negative association between IgG1 allotype disparity and anti-adalimumab formation: a cohort study

Introduction

The human monoclonal antibody adalimumab is known to induce an anti-globulin response in some adalimumab-treated patients. Antibodies against adalimumab (AAA) are associated with non-response to treatment. Immunoglobulins, such as adalimumab, carry allotypes which represent slight differences in the amino acid sequences of the constant chains of an IgG molecule. Immunoglobulins with particular IgG (Gm) allotypes are racially distributed and could be immunogenic for individuals who do not express these allotypes. Therefore, we investigated whether a mismatch in IgG allotypes between adalimumab and IgG in adalimumab-treated patients is associated with the development of AAA.

Methods

This cohort study consisted of 250 adalimumab-treated rheumatoid arthritis (RA) patients. IgG allotypes were determined for adalimumab and for all patients. Anti-idiotype antibodies against adalimumab were measured with a regular radio immunoassay (RIA), and a newly developed bridging enzyme linked immunosorbent assay (ELISA) was used to measure anti-allotype antibodies against adalimumab. The association between AAA and the G1m3 and the G1m17 allotypes was determined. For differences between groups we used the independent or paired samples t-test, Mann-Whitney test or Chi square/Fisher's exact test as appropriate. To investigate the influence of confounders on the presence or absence of AAA a multiple logistic regression-analysis was used.

Results

Adalimumab carries the G1m17 allotype. No anti-allotype antibodies against adalimumab were detected. Thirty-nine out of 249 patients had anti-idiotype antibodies against adalimumab (16%). IgG allotypes of RA patients were associated with the frequency of AAA: patients homozygous for G1m17 had the highest frequency of AAA (41%), patients homozygous for G1m3 the lowest frequency (10%), and heterozygous patients' AAA frequency was 14% (P = 0.0001).

Conclusions

An allotype mismatch between adalimumab and IgG in adalimumab-treated patients did not lead to a higher frequency of AAA. On the contrary, patients who carried the same IgG allotype as present on the adalimumab IgG molecule, had the highest frequency of anti-adalimumab antibodies compared to patients whose IgG allotype differed from adalimumab. This suggests that the allotype of adalimumab may not be highly immunogenic. Furthermore, patients carrying the G1m17-allotype might be more prone to antibody responses.     

Exploiting the full power of temporal gene expression profiling through a new statistical test: Application to the analysis of muscular dystrophy data

Background  

The identification of biologically interesting genes in a temporal expression profiling dataset is challenging and complicated by high levels of experimental noise. Most statistical methods used in the literature do not fully exploit the temporal ordering in the dataset and are not suited to the case where temporal profiles are measured for a number of different biological conditions. We present a statistical test that makes explicit use of the temporal order in the data by fitting polynomial functions to the temporal profile of each gene and for each biological condition. A Hotelling T ²-statistic is derived to detect the genes for which the parameters of these polynomials are significantly different from each other.     

Use of chromomycin A3 staining in bovine sperm cells for detection of protamine deficiency

Sperm chromatin integrity is essential for accurate transmission of male genetic information, and normal sperm chromatin structure is important for fertilization. Protamine is a nuclear protein that plays a key role in sperm DNA integrity, because it is responsible for sperm DNA stability and packing until the paternal genome is delivered into the oocyte during fertilization. Our aim was to investigate protamine deficiency in sperm cells of Bos indicus bulls (Nelore) using chromomycin A₃ (CMA₃) staining. Frozen semen from 14 bulls were thawed, then fixed in Carnoy's solution. Smears were prepared and analyzed by microscopy. As a positive control of CMA₃ staining, sperm from one bull was subjected to deprotamination of nuclei. The percentage of CMA₃-positive bovine sperm did not vary among batches. Only two bulls showed a higher percentage of CMA₃-positive sperm cells compared to the others. CMA₃ is a simple and useful tool for detecting sperm protamine deficiency in bulls.     

Monitoring of clinical signs in goats with transmissible spongiform encephalopathies

Background  

As there is limited information about the clinical signs of BSE and scrapie in goats, studies were conducted to describe the clinical progression of scrapie and BSE in goats and to evaluate a short clinical protocol for its use in detecting scrapie-affected goats in two herds with previously confirmed scrapie cases. Clinical assessments were carried out in five goats intracerebrally infected with the BSE agent as well as five reported scrapie suspects and 346 goats subject to cull from the two herds, 24 of which were retained for further monitoring. The brain and selected lymphoid tissue were examined by postmortem tests for disease confirmation.     

The interferon type I signature towards prediction of non-response to rituximab in rheumatoid arthritis patients

Introduction

B cell depletion therapy is efficacious in rheumatoid arthritis (RA) patients failing on tumor necrosis factor (TNF) blocking agents. However, approximately 40% to 50% of rituximab (RTX) treated RA patients have a poor response. We investigated whether baseline gene expression levels can discriminate between clinical non-responders and responders to RTX.

Methods

In 14 consecutive RA patients starting on RTX (test cohort), gene expression profiling on whole peripheral blood RNA was performed by Illumina^® HumanHT beadchip microarrays. Supervised cluster analysis was used to identify genes expressed differentially at baseline between responders and non-responders based on both a difference in 28 joints disease activity score (ΔDAS28 < 1.2) and European League against Rheumatism (EULAR) response criteria after six months RTX. Genes of interest were measured by quantitative real-time PCR and tested for their predictive value using receiver operating characteristics (ROC) curves in an independent validation cohort (n = 26).

Results

Genome-wide microarray analysis revealed a marked variation in the peripheral blood cells between RA patients before the start of RTX treatment. Here, we demonstrated that only a cluster consisting of interferon (IFN) type I network genes, represented by a set of IFN type I response genes (IRGs), that is, LY6E, HERC5, IFI44L, ISG15, MxA, MxB, EPSTI1 and RSAD2, was associated with ΔDAS28 and EULAR response outcome (P = 0.0074 and P = 0.0599, respectively). Based on the eight IRGs an IFN-score was calculated that reached an area under the curve (AUC) of 0.82 to separate non-responders from responders in an independent validation cohort of 26 patients using Receiver Operator Characteristics (ROC) curves analysis according to ΔDAS28 < 1.2 criteria. Advanced classifier analysis yielded a three IRG-set that reached an AUC of 87%. Comparable findings applied to EULAR non-response criteria.

Conclusions

This study demonstrates clinical utility for the use of baseline IRG expression levels as a predictive biomarker for non-response to RTX in RA.