A Two-Stage Random Forest-Based Pathway Analysis Method

Pathway analysis provides a powerful approach for identifying the joint effect of genes grouped into biologically-based pathways on disease. Pathway analysis is also an attractive approach for a secondary analysis of genome-wide association study (GWAS) data that may still yield new results from these valuable datasets. Most of the current pathway analysis methods focused on testing the cumulative main effects of genes in a pathway. However, for complex diseases, gene-gene interactions are expected to play a critical role in disease etiology. We extended a random forest-based method for pathway analysis by incorporating a two-stage design. We used simulations to verify that the proposed method has the correct type I error rates. We also used simulations to show that the method is more powerful than the original random forest-based pathway approach and the set-based test implemented in PLINK in the presence of gene-gene interactions. Finally, we applied the method to a breast cancer GWAS dataset and a lung cancer GWAS dataset and interesting pathways were identified that have implications for breast and lung cancers

Genetic and expression studies of SMN2 gene in Russian patients with spinal muscular atrophy type II and III

<p>Abstract</p> <p>Background</p> <p>Spinal muscular atrophy (SMA type I, II and III) is an autosomal recessive neuromuscular disorder caused by mutations in the survival motor neuron gene (<it>SMN1</it>). <it>SMN2 </it>is a centromeric copy gene that has been characterized as a major modifier of SMA severity. SMA type I patients have one or two <it>SMN2 </it>copies while most SMA type II patients carry three <it>SMN2 </it>copies and SMA III patients have three or four <it>SMN2 </it>copies. The <it>SMN1 </it>gene produces a full-length transcript (FL-SMN) while <it>SMN2 </it>is only able to produce a small portion of the FL-SMN because of a splice mutation which results in the production of abnormal SMNΔ7 mRNA.</p> <p>Methods</p> <p>In this study we performed quantification of the <it>SMN2 </it>gene copy number in Russian patients affected by SMA type II and III (42 and 19 patients, respectively) by means of real-time PCR. Moreover, we present two families consisting of asymptomatic carriers of a homozygous absence of the <it>SMN1 </it>gene. We also developed a novel RT-qPCR-based assay to determine the FL-SMN/SMNΔ7 mRNA ratio as SMA biomarker.</p> <p>Results</p> <p>Comparison of the <it>SMN2 </it>copy number and clinical features revealed a significant correlation between mild clinical phenotype (SMA type III) and presence of four copies of the <it>SMN2 </it>gene. In both asymptomatic cases we found an increased number of <it>SMN2 </it>copies in the healthy carriers and a biallelic <it>SMN1 </it>absence. Furthermore, the novel assay revealed a difference between SMA patients and healthy controls.</p> <p>Conclusions</p> <p>We suggest that the <it>SMN2 </it>gene copy quantification in SMA patients could be used as a prognostic tool for discrimination between the SMA type II and SMA type III diagnoses, whereas the FL-SMN/SMNΔ7 mRNA ratio could be a useful biomarker for detecting changes during SMA pharmacotherapy.</p

Repertoire of Intensive Care Unit Pneumonia Microbiota

Despite the considerable number of studies reported to date, the causative agents of pneumonia are not completely identified. We comprehensively applied modern and traditional laboratory diagnostic techniques to identify microbiota in patients who were admitted to or developed pneumonia in intensive care units (ICUs). During a three-year period, we tested the bronchoalveolar lavage (BAL) of patients with ventilator-associated pneumonia, community-acquired pneumonia, non-ventilator ICU pneumonia and aspiration pneumonia, and compared the results with those from patients without pneumonia (controls). Samples were tested by amplification of 16S rDNA, 18S rDNA genes followed by cloning and sequencing and by PCR to target specific pathogens. We also included culture, amoeba co-culture, detection of antibodies to selected agents and urinary antigen tests. Based on molecular testing, we identified a wide repertoire of 160 bacterial species of which 73 have not been previously reported in pneumonia. Moreover, we found 37 putative new bacterial phylotypes with a 16S rDNA gene divergence ≥98% from known phylotypes. We also identified 24 fungal species of which 6 have not been previously reported in pneumonia and 7 viruses. Patients can present up to 16 different microorganisms in a single BAL (mean ± SD; 3.77±2.93). Some pathogens considered to be typical for ICU pneumonia such as Pseudomonas aeruginosa and Streptococcus species can be detected as commonly in controls as in pneumonia patients which strikingly highlights the existence of a core pulmonary microbiota. Differences in the microbiota of different forms of pneumonia were documented

Validation of a high resolution NGS method for detecting spinal muscular atrophy carriers among phase 3 participants in the 1000 Genomes Project

BACKGROUND: Spinal muscular atrophy (SMA) is the most common pan-ethnic cause of early childhood death due to mutations in a single gene, SMN1. Most chromosome 5 homologs have a functional gene and dysfunctional copy, SMN2, with a single synonymous base substitution that results in faulty RNA splicing. However, the copy number of SMN1 and SMN2 is highly variable, and one in 60 adults worldwide are SMA carriers. Although population-wide screening is recommended, current SMA carrier tests have not been incorporated into targeted gene panels. METHODS: Here we describe a novel computational protocol for determining SMA carrier status based solely on individual exome data. Our method utilizes a Bayesian hierarchical model to quantify an individual’s carrier probability given only his or her SMN1 and SMN2 reads at six loci of interest. RESULTS: We find complete concordance with results obtained with the current qPCR-based testing standard in known SMA carriers and affecteds. We applied our protocol to the phase 3 cohort of the 1,000 Genomes Project and found carrier frequencies in multiple populations consistent with the present literature. CONCLUSION: Our process is a convenient, robust alternative to qPCR, which can easily be integrated into the analysis of large multi-gene NGS carrier screens. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12881-015-0246-2) contains supplementary material, which is available to authorized users