Expression Profiling in the Muscular Dystrophies: Identification of Novel Aspects of Molecular Pathophysiology

We used expression profiling to define the pathophysiological cascades involved in the progression of two muscular dystrophies with known primary biochemical defects, dystrophin deficiency (Duchenne muscular dystrophy) and α-sarcoglycan deficiency (a dystrophin-associated protein). We employed a novel protocol for expression profiling in human tissues using mixed samples of multiple patients and iterative comparisons of duplicate datasets. We found evidence for both incomplete differentiation of patient muscle, and for dedifferentiation of myofibers to alternative lineages with advancing age. One developmentally regulated gene characterized in detail, α-cardiac actin, showed abnormal persistent expression after birth in 60% of Duchenne dystrophy myofibers. The majority of myofibers (∼80%) remained strongly positive for this protein throughout the course of the disease. Other developmentally regulated genes that showed widespread overexpression in these muscular dystrophies included embryonic myosin heavy chain, versican, acetylcholine receptor α-1, secreted protein, acidic and rich in cysteine/osteonectin, and thrombospondin 4. We hypothesize that the abnormal Ca2+ influx in dystrophin- and α-sarcoglycan–deficient myofibers leads to altered developmental programming of developing and regenerating myofibers. The finding of upregulation of HLA-DR and factor XIIIa led to the novel identification of activated dendritic cell infiltration in dystrophic muscle; these cells mediate immune responses and likely induce microenvironmental changes in muscle. We also document a general metabolic crisis in dystrophic muscle, with large scale downregulation of nuclear-encoded mitochondrial gene expression. Finally, our expression profiling results show that primary genetic defects can be identified by a reduction in the corresponding RNA

Sources of variability and effect of experimental approach on expression profiling data interpretation

BACKGROUND: We provide a systematic study of the sources of variability in expression profiling data using 56 RNAs isolated from human muscle biopsies (34 Affymetrix MuscleChip arrays), and 36 murine cell culture and tissue RNAs (42 Affymetrix U74Av2 arrays). RESULTS: We studied muscle biopsies from 28 human subjects as well as murine myogenic cell cultures, muscle, and spleens. Human MuscleChip arrays (4,601 probe sets) and murine U74Av2 Affymetrix microarrays were used for expression profiling. RNAs were profiled both singly, and as mixed groups. Variables studied included tissue heterogeneity, cRNA probe production, patient diagnosis, and GeneChip hybridizations. We found that the greatest source of variability was often different regions of the same patient muscle biopsy, reflecting variation in cell type content even in a relatively homogeneous tissue such as muscle. Inter-patient variation was also very high (SNP noise). Experimental variation (RNA, cDNA, cRNA, or GeneChip) was minor. Pre-profile mixing of patient cRNA samples effectively normalized both intra- and inter-patient sources of variation, while retaining a high degree of specificity of the individual profiles (86% of statistically significant differences detected by absolute analysis; and 85% by a 4-pairwise comparison survival method). CONCLUSIONS: Using unsupervised cluster analysis and correlation coefficients of 92 RNA samples on 76 oligonucleotide microarrays, we found that experimental error was not a significant source of unwanted variability in expression profiling experiments. Major sources of variability were from use of small tissue biopsies, particularly in humans where there is substantial inter-patient variability (SNP noise)

Motif-directed network component analysis for regulatory network inference

<p>Abstract</p> <p>Background</p> <p>Network Component Analysis (NCA) has shown its effectiveness in discovering regulators and inferring transcription factor activities (TFAs) when both microarray data and ChIP-on-chip data are available. However, a NCA scheme is not applicable to many biological studies due to limited topology information available, such as lack of ChIP-on-chip data. We propose a new approach, motif-directed NCA (mNCA), to integrate motif information and gene expression data to infer regulatory networks.</p> <p>Results</p> <p>We develop motif-directed NCA (mNCA) to incorporate motif information into NCA for regulatory network inference. While motif information is readily available from knowledge databases, it is a "noisy" source of network topology information consisting of many false positives. To overcome this problem, we develop a stability analysis procedure embedded in mNCA to resolve the inconsistency between motif information and gene expression data, and to enable the identification of stable TFAs. The mNCA approach has been applied to a time course microarray data set of muscle regeneration. The experimental results show that the inferred TFAs are not only numerically stable but also biologically relevant to muscle differentiation process. In particular, several inferred TFAs like those of MyoD, myogenin and YY1 are well supported by biological experiments.</p> <p>Conclusion</p> <p>A novel computational approach, mNCA, has been developed to integrate motif information and gene expression data for regulatory network reconstruction. Specifically, motif analysis is used to obtain initial network topology, and stability analysis is developed and applied with mNCA to extract stable TFAs. Experimental results on muscle regeneration microarray data have demonstrated that mNCA is a practical and reliable computational method for regulatory network inference and pathway discovery.</p

Sexual dimorphism in immune response genes as a function of puberty

BACKGROUND: Autoimmune diseases are more prevalent in females than in males, whereas males have higher mortality associated with infectious diseases. To increase our understanding of this sexual dimorphism in the immune system, we sought to identify and characterize inherent differences in immune response programs in the spleens of male and female mice before, during and after puberty. RESULTS: After the onset of puberty, female mice showed a higher expression of adaptive immune response genes, while males had a higher expression of innate immune genes. This result suggested a requirement for sex hormones. Using in vivo and in vitro assays in normal and mutant mouse strains, we found that reverse signaling through FasL was directly influenced by estrogen, with downstream consequences of increased CD8(+ )T cell-derived B cell help (via cytokines) and enhanced immunoglobulin production. CONCLUSION: These results demonstrate that sexual dimorphism in innate and adaptive immune genes is dependent on puberty. This study also revealed that estrogen influences immunoglobulin levels in post-pubertal female mice via the Fas-FasL pathway

In vivo filtering of in vitro MyoD target data: An approach for identification of biologically relevant novel downstream targets of transcription factors (2003)

We report a novel approach to identification of downstream targets of MyoD, where a published set of candidate targets from a well-controlled in vitro experiment [1] is filtered for relevance to muscle regeneration using a 27 time point in vivo murine regeneration series. Using both interactive hierarchical clustering (HCE) [2], and Bayes soft clustering (VISDA) [3,4]. We show that only a minority of in vitroefined candidates can be confirmed in vivo (~50% of induced transcripts, and none of repressed transcripts). The concordance of the in vitro, in vivo datasets, and both HCE and VISDA analytical techniques showed strong support for 18 targets (13 no vel) of MyoD that are biologically relevant during myoblast differentiation, including Cdh15, L-myc, Hes6, Stam, Tnnt2, Fyn, Rapsn, Nestin, Osp94, Pep4, Mef2a, Sh3glb1 and Rb1

Interactive Color Mosaic and Dendogram Displays for Signal/Noise Optimization in Microarray Data Analysis (2003)

Data analysis and visualization is strongly influenced by noise and noise filters. There are multiple sources of oisein microarray data analysis, but signal/noise ratios are rarely optimized, or even considered. Here, we report a noise analysis of a novel 13 million oligonucleotide dataset - 25 human U133A (~500,000 features) profiles of patient muscle biposies. We use our recently described interactive visualization tool, the Hierarchical Clustering Explorer (HCE) to systemically address the effect of different noise filters on resolution of arrays into orrectbiological groups (unsupervised clustering into three patient groups of known diagnosis). We varied probe set interpretation methods (MAS 5.0, RMA), resent callfilters, and clustering linkage methods, and investigated the results in HCE. HCE interactive features enabled us to quickly see the impact of these three variables. Dendrogram displays showed the clustering results systematically, and color mosaic displays provided a visual support for the results. We show that each of these three variables has a strong effect on unsupervised clustering. For this dataset, the strength of the biological variable was maximized, and noise minimized, using MAS 5.0, 10% present call filter, and Average Group Linkage. We propose a general method of using interactive tools to identify the optimal signal/noise balance or the optimal combination of these three variables to maximize the effect of the desired biological variable on data interpretation

Increasing confidence and changing behaviors in primary care providers engaged in genetic counselling.

BackgroundScreening and counseling for genetic conditions is an increasingly important part of primary care practice, particularly given the paucity of genetic counselors in the United States. However, primary care physicians (PCPs) often have an inadequate understanding of evidence-based screening; communication approaches that encourage shared decision-making; ethical, legal, and social implication (ELSI) issues related to screening for genetic mutations; and the basics of clinical genetics. This study explored whether an interactive, web-based genetics curriculum directed at PCPs in non-academic primary care settings was superior at changing practice knowledge, attitudes, and behaviors when compared to a traditional educational approach, particularly when discussing common genetic conditions.MethodsOne hundred twenty one PCPs in California and Pennsylvania physician practices were randomized to either an Intervention Group (IG) or Control Group (CG). IG physicians completed a 6 h interactive web-based curriculum covering communication skills, basics of genetic testing, risk assessment, ELSI issues and practice behaviors. CG physicians were provided with a traditional approach to Continuing Medical Education (CME) (clinical review articles) offering equivalent information.ResultsPCPs in the Intervention Group showed greater increases in knowledge compared to the Control Group. Intervention PCPs were also more satisfied with the educational materials, and more confident in their genetics knowledge and skills compared to those receiving traditional CME materials. Intervention PCPs felt that the web-based curriculum covered medical management, genetics, and ELSI issues significantly better than did the Control Group, and in comparison with traditional curricula. The Intervention Group felt the online tools offered several advantages, and engaged in better shared decision making with standardized patients, however, there was no difference in behavior change between groups with regard to increases in ELSI discussions between PCPs and patients.ConclusionWhile our intervention was deemed more enjoyable, demonstrated significant factual learning and retention, and increased shared decision making practices, there were few differences in behavior changes around ELSI discussions. Unfortunately, barriers to implementing behavior change in clinical genetics is not unique to our intervention. Perhaps the missing element is that busy physicians need systems-level support to engage in meaningful discussions around genetics issues. The next step in promoting active engagement between doctors and patients may be to put into place the tools needed for PCPs to easily access the materials they need at the point-of-care to engage in joint discussions around clinical genetics

Preparation of silk fibroin–poly(ethylene glycol) conjugate films through click chemistry

Azide silk fibroin (azido SF) and alkyne terminal poly(ethylene glycol) (PEG) 2000 (acetylene-terminal PEG 2000) were synthesized. Azido SF was reacted with acetylene-terminal PEG 2000 to produce films via a copper-mediated 1,3-cycloaddition (‘click’ chemistry) generating a triazole linkage as the networking forming reaction. Through click chemistry, novel silk-based films with various weight ratios were prepared and investigated. Fourier transform infrared, X-ray diffraction and differential scanning calorimetry analyses showed that the ordered association of the PEG molecules is strongly constrained by the presence of the SF molecules and crosslinking and that the presence of acetylene-terminal PEG 2000 in the films induced crystallization to a β-sheet of SF chains.Water content and contact angle measurements indicated that the hydrophilicity of the films increased compared with SF. SF–PEG films exhibited smooth and rough structures, depending on degree of crosslinking and on the weight ratio of SF and PEG, as shown by scanning electron microscopy

Experience and Challenges from Clinical Trials with Malaria Vaccines in Africa.

Malaria vaccines are considered amongst the most important modalities for potential elimination of malaria disease and transmission. Research and development in this field has been an area of intense effort by many groups over the last few decades. Despite this, there is currently no licensed malaria vaccine. Researchers, clinical trialists and vaccine developers have been working on many approached to make malaria vaccine available.African research institutions have developed and demonstrated a great capacity to undertake clinical trials in accordance to the International Conference on Harmonization-Good Clinical Practice (ICH-GCP) standards in the last decade; particularly in the field of malaria vaccines and anti-malarial drugs. This capacity is a result of networking among African scientists in collaboration with other partners; this has traversed both clinical trials and malaria control programmes as part of the Global Malaria Action Plan (GMAP). GMAP outlined and support global strategies toward the elimination and eradication of malaria in many areas, translating in reduction in public health burden, especially for African children. In the sub-Saharan region the capacity to undertake more clinical trials remains small in comparison to the actual need.However, sustainability of the already developed capacity is essential and crucial for the evaluation of different interventions and diagnostic tools/strategies for other diseases like TB, HIV, neglected tropical diseases and non-communicable diseases. There is urgent need for innovative mechanisms for the sustainability and expansion of the capacity in clinical trials in sub-Saharan Africa as the catalyst for health improvement and maintained