Hematopoietic Cell Transplantation in Patients With Primary Immune Regulatory Disorders (PIRD): A Primary Immune Deficiency Treatment Consortium (PIDTC) Survey.

Primary Immune Regulatory Disorders (PIRD) are an expanding group of diseases caused by gene defects in several different immune pathways, such as regulatory T cell function. Patients with PIRD develop clinical manifestations associated with diminished and exaggerated immune responses. Management of these patients is complicated; oftentimes immunosuppressive therapies are insufficient, and patients may require hematopoietic cell transplant (HCT) for treatment. Analysis of HCT data in PIRD patients have previously focused on a single gene defect. This study surveyed transplanted patients with a phenotypic clinical picture consistent with PIRD treated in 33 Primary Immune Deficiency Treatment Consortium centers and European centers. Our data showed that PIRD patients often had immunodeficient and autoimmune features affecting multiple organ systems. Transplantation resulted in resolution of disease manifestations in more than half of the patients with an overall 5-years survival of 67%. This study, the first to encompass disorders across the PIRD spectrum, highlights the need for further research in PIRD management

Comparative Treatment Outcomes for Patients With Idiopathic Subglottic Stenosis.

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked DownloadImportance: Surgical treatment comparisons in rare diseases are difficult secondary to the geographic distribution of patients. Fortunately, emerging technologies offer promise to reduce these barriers for research. Objective: To prospectively compare the outcomes of the 3 most common surgical approaches for idiopathic subglottic stenosis (iSGS), a rare airway disease. Design, setting, and participants: In this international, prospective, 3-year multicenter cohort study, 810 patients with untreated, newly diagnosed, or previously treated iSGS were enrolled after undergoing a surgical procedure (endoscopic dilation [ED], endoscopic resection with adjuvant medical therapy [ERMT], or cricotracheal resection [CTR]). Patients were recruited from clinician practices in the North American Airway Collaborative and an online iSGS community on Facebook. Main outcomes and measures: The primary end point was days from initial surgical procedure to recurrent surgical procedure. Secondary end points included quality of life using the Clinical COPD (chronic obstructive pulmonary disease) Questionnaire (CCQ), Voice Handicap Index-10 (VHI-10), Eating Assessment Test-10 (EAT-10), the 12-Item Short-Form Version 2 (SF-12v2), and postoperative complications. Results: Of 810 patients in this cohort, 798 (98.5%) were female and 787 (97.2%) were white, with a median age of 50 years (interquartile range, 43-58 years). Index surgical procedures were ED (n = 603; 74.4%), ERMT (n = 121; 14.9%), and CTR (n = 86; 10.6%). Overall, 185 patients (22.8%) had a recurrent surgical procedure during the 3-year study, but recurrence differed by modality (CTR, 1 patient [1.2%]; ERMT, 15 [12.4%]; and ED, 169 [28.0%]). Weighted, propensity score-matched, Cox proportional hazards regression models showed ED was inferior to ERMT (hazard ratio [HR], 3.16; 95% CI, 1.8-5.5). Among successfully treated patients without recurrence, those treated with CTR had the best CCQ (0.75 points) and SF-12v2 (54 points) scores and worst VHI-10 score (13 points) 360 days after enrollment as well as the greatest perioperative risk. Conclusions and relevance: In this cohort study of 810 patients with iSGS, endoscopic dilation, the most popular surgical approach for iSGS, was associated with a higher recurrence rate compared with other procedures. Cricotracheal resection offered the most durable results but showed the greatest perioperative risk and the worst long-term voice outcomes. Endoscopic resection with medical therapy was associated with better disease control compared with ED and had minimal association with vocal function. These results may be used to inform individual patient treatment decision-making.Patient-Centered Outcomes Research Institute - PCOR

Exome Sequencing and the Management of Neurometabolic Disorders

BACKGROUND: Whole-exome sequencing has transformed gene discovery and diagnosis in rare diseases. Translation into disease-modifying treatments is challenging, particularly for intellectual developmental disorder. However, the exception is inborn errors of metabolism, since many of these disorders are responsive to therapy that targets pathophysiological features at the molecular or cellular level. METHODS: To uncover the genetic basis of potentially treatable inborn errors of metabolism, we combined deep clinical phenotyping (the comprehensive characterization of the discrete components of a patient's clinical and biochemical phenotype) with whole-exome sequencing analysis through a semiautomated bioinformatics pipeline in consecutively enrolled patients with intellectual developmental disorder and unexplained metabolic phenotypes. RESULTS: We performed whole-exome sequencing on samples obtained from 47 probands. Of these patients, 6 were excluded, including 1 who withdrew from the study. The remaining 41 probands had been born to predominantly nonconsanguineous parents of European descent. In 37 probands, we identified variants in 2 genes newly implicated in disease, 9 candidate genes, 22 known genes with newly identified phenotypes, and 9 genes with expected phenotypes; in most of the genes, the variants were classified as either pathogenic or probably pathogenic. Complex phenotypes of patients in five families were explained by coexisting monogenic conditions. We obtained a diagnosis in 28 of 41 probands (68%) who were evaluated. A test of a targeted intervention was performed in 18 patients (44%). CONCLUSIONS: Deep phenotyping and whole-exome sequencing in 41 probands with intellectual developmental disorder and unexplained metabolic abnormalities led to a diagnosis in 68%, the identification of 11 candidate genes newly implicated in neurometabolic disease, and a change in treatment beyond genetic counseling in 44%. (Funded by BC Children's Hospital Foundation and others.)

The discrepancy among single nucleotide variants detected by DNA and RNA high throughput sequencing data

Abstract Background High throughput sequencing technology enables the both the human genome and transcriptome to be screened at the single nucleotide resolution. Tools have been developed to infer single nucleotide variants (SNVs) from both DNA and RNA sequencing data. To evaluate how much difference can be expected between DNA and RNA sequencing data, and among tissue sources, we designed a study to examine the single nucleotide difference among five sources of high throughput sequencing data generated from the same individual, including exome sequencing from blood, tumor and adjacent normal tissue, and RNAseq from tumor and adjacent normal tissue. Results Through careful quality control and analysis of the SNVs, we found little difference between DNA-DNA pairs (1%–2%). However, between DNA-RNA pairs, SNV differences ranged anywhere from 10% to 20%. Conclusions Only a small portion of these differences can be explained by RNA editing. Instead, the majority of the DNA-RNA differences should be attributed to technical errors from sequencing and post-processing of RNAseq data. Our analysis results suggest that SNV detection using RNAseq is subject to high false positive rates

Evaluation of Allele Frequency Estimation Using Pooled Sequencing Data Simulation

Next-generation sequencing (NGS) technology has provided researchers with opportunities to study the genome in unprecedented detail. In particular, NGS is applied to disease association studies. Unlike genotyping chips, NGS is not limited to a fixed set of SNPs. Prices for NGS are now comparable to the SNP chip, although for large studies the cost can be substantial. Pooling techniques are often used to reduce the overall cost of large-scale studies. In this study, we designed a rigorous simulation model to test the practicability of estimating allele frequency from pooled sequencing data. We took crucial factors into consideration, including pool size, overall depth, average depth per sample, pooling variation, and sampling variation. We used real data to demonstrate and measure reference allele preference in DNAseq data and implemented this bias in our simulation model. We found that pooled sequencing data can introduce high levels of relative error rate (defined as error rate divided by targeted allele frequency) and that the error rate is more severe for low minor allele frequency SNPs than for high minor allele frequency SNPs. In order to overcome the error introduced by pooling, we recommend a large pool size and high average depth per sample

Comparative Study of Exome Copy Number Variation Estimation Tools Using Array Comparative Genomic Hybridization as Control

Exome sequencing using next-generation sequencing technologies is a cost-efficient approach to selectively sequencing coding regions of the human genome for detection of disease variants. One of the lesser known yet important applications of exome sequencing data is to identify copy number variation (CNV). There have been many exome CNV tools developed over the last few years, but the performance and accuracy of these programs have not been thoroughly evaluated. In this study, we systematically compared four popular exome CNV tools (CoNIFER, cn.MOPS, exomeCopy, and ExomeDepth) and evaluated their effectiveness against array comparative genome hybridization (array CGH) platforms. We found that exome CNV tools are capable of identifying CNVs, but they can have problems such as high false positives, low sensitivity, and duplication bias when compared to array CGH platforms. While exome CNV tools do serve their purpose for data mining, careful evaluation and additional validation is highly recommended. Based on all these results, we recommend CoNIFER and cn.MOPs for nonpaired exome CNV detection over the other two tools due to a low false-positive rate, although none of the four exome CNV tools performed at an outstanding level when compared to array CGH