Multisite Evaluation and Validation of a Sensitive Diagnostic and Screening System for Spinal Muscular Atrophy that Reports SMN1 and SMN2 Copy Number, along with Disease Modifier and Gene Duplication Variants.

Spinal muscular atrophy is a severe autosomal recessive disease caused by disruptions in the SMN1 gene. The nearly identical SMN2 gene copy number is associated with disease severity. SMN1 duplication markers, such as c.∗3+80T>G and c.∗211_∗212del, can assess residual carrier risk. An SMN2 disease modifier (c.859G>C) can help inform prognostic outcomes. The emergence of multiple precision gene therapies for spinal muscular atrophy requires accurate and rapid detection of SMN1 and SMN2 copy numbers to enable early treatment and optimal patient outcomes. We developed and evaluated a single-tube PCR/capillary electrophoresis assay system that quantifies SMN1/2 copy numbers and genotypes three additional clinically relevant variants. Analytical validation was performed with human cell lines and whole blood representing varying SMN1/2 copies on four capillary electrophoresis instrument models. In addition, four independent laboratories used the assay to test 468 residual clinical genomic DNA samples. The results were ≥98.3% concordant with consensus SMN1/2 exon 7 copy numbers, determined using multiplex ligation-dependent probe amplification and droplet digital PCR, and were 100% concordant with Sanger sequencing for the three variants. Furthermore, copy number values were 98.6% (SMN1) and 97.1% (SMN2) concordant to each laboratory's own reference results.

Dry Beriberi Manifesting as Acute Inflammatory Demyelinating Polyneuropathy in a Patient With Decompensated Alcohol-Induced Cirrhosis.

Thiamine (vitamin B1) deficiency is uncommon in developed countries and is most commonly seen in patients with poor dietary intake, malabsorption syndromes, and alcoholism. With the increasing rates of alcohol use, thiamine deficiency is likely an under-recognized and potentially reversible cause of sensorimotor dysfunction called dry beriberi. We present a case of profound lower extremity weakness in a 28-year-old female from Nepal with decompensated alcohol-induced cirrhosis. Based on laboratory testing, it was determined that the cause of her neuropathy was dry beriberi. She was subsequently started on thiamine replacement therapy with slow improvement over the next six months.

Multilaboratory Assessment of a New Reference Material for Quality Assurance of Cell-Free Tumor DNA Measurements.

We conducted a multilaboratory assessment to determine the suitability of a new commercially available reference material with 40 cancer variants in a background of wild-type DNA at four different variant allele frequencies (VAFs): 2%, 0.50%, 0.125%, and 0%. The variants include single nucleotides, insertions, deletions, and two structural variations selected for their clinical importance and to challenge the performance of next-generation sequencing (NGS) methods. Fragmented DNA was formulated to simulate the size distribution of circulating wild-type and tumor DNA in a synthetic plasma matrix. DNA was extracted from these samples and characterized with different methods and multiple laboratories. The various extraction methods had differences in yield, perhaps because of differences in chemistry. Digital PCR assays were used to measure VAFs to compare results from different NGS methods. Comparable VAFs were observed across the different NGS methods. This multilaboratory assessment demonstrates that the new reference material is an appropriate tool to determine the analytical parameters of different measurement methods and to ensure their quality assurance.

Diverse Brain Myeloid Expression Profiles Reveal Distinct Microglial Activation States and Aspects of Alzheimer's Disease Not Evident in Mouse Models.

Microglia, the CNS-resident immune cells, play important roles in disease, but the spectrum of their possible activation states is not well understood. We derived co-regulated gene modules from transcriptional profiles of CNS myeloid cells of diverse mouse models, including new tauopathy model datasets. Using these modules to interpret single-cell data from an Alzheimer's disease (AD) model, we identified microglial subsets-distinct from previously reported "disease-associated microglia"-expressing interferon-related or proliferation modules. We then analyzed whole-tissue RNA profiles from human neurodegenerative diseases, including a new AD dataset. Correcting for altered cellular composition of AD tissue, we observed elevated expression of the neurodegeneration-related modules, but also modules not implicated using expression profiles from mouse models alone. We provide a searchable, interactive database for exploring gene expression in all these datasets (http://research-pub.gene.com/BrainMyeloidLandscape). Understanding the dimensions of CNS myeloid cell activation in human disease may reveal opportunities for therapeutic intervention.

A Common Variant of IL-6R is Associated with Elevated IL-6 Pathway Activity in Alzheimer's Disease Brains.

The common p.D358A variant (rs2228145) in IL-6R is associated with risk for multiple diseases and with increased levels of soluble IL-6R in the periphery and central nervous system (CNS). Here, we show that the p.D358A allele leads to increased proteolysis of membrane bound IL-6R and demonstrate that IL-6R peptides with A358 are more susceptible to cleavage by ADAM10 and ADAM17. IL-6 responsive genes were identified in primary astrocytes and microglia and an IL-6 gene signature was increased in the CNS of late onset Alzheimer's disease subjects in an IL6R allele dependent manner. We conducted a screen to identify variants associated with the age of onset of Alzheimer's disease in APOE ɛ4 carriers. Across five datasets, p.D358A had a meta P = 3 ×10-4 and an odds ratio = 1.3, 95% confidence interval 1.12 -1.48. Our study suggests that a common coding region variant of the IL-6 receptor results in neuroinflammatory changes that may influence the age of onset of Alzheimer's disease in APOE ɛ4 carriers.

Carrier Screening is a Deficient Strategy for Determining Sperm Donor Eligibility and Reducing Risk of Disease in Recipient Children.

AIMS: DNA-based carrier screening is a standard component of donor eligibility protocols practiced by U.S. sperm banks. Applicants who test positive for carrying a recessive disease mutation are typically disqualified. The aim of our study was to examine the utility of a range of screening panels adopted by the industry and the effectiveness of the screening paradigm in reducing a future child's risk of inheriting disease. METHODS: A cohort of 27 donor applicants, who tested negative on an initial cystic fibrosis carrier test, was further screened with three expanded commercial carrier testing panels. These results were then compared to a systematic analysis of the applicants' DNA using next-generation sequencing (NGS) data. RESULTS: The carrier panels detected serious pediatric disease mutations in one, four, or six donor applicants. Because each panel screens distinct regions of the genome, no single donor was uniformly identified as carrier positive by all three panels. In contrast, systematic NGS analysis identified all donors as carriers of one or more mutations associated with severe monogenic pediatric disease. These included 30 variants classified as "pathogenic" based on clinical observation and 66 with a high likelihood of causing gene dysfunction. CONCLUSION: Despite tremendous advances in variant identification, understanding, and analysis, the vast majority of disease-causing mutation combinations remain undetected by commercial carrier screening panels, which cover a narrow, and often distinct, subset of genes and mutations. The biological reality is that all donors and recipients carry serious recessive disease mutations. This challenges the utility of any screening protocol that anchors donor eligibility to carrier status. A more effective approach to reducing recessive disease risk would consider joint comprehensive analysis of both donor and recipient disease mutations. This type of high-resolution recessive disease risk analysis is now available and affordable, but industry practice must be modified to incorporate its use.

Untangling the brain's neuroinflammatory and neurodegenerative transcriptional responses.

A common approach to understanding neurodegenerative disease is comparing gene expression in diseased versus healthy tissues. We illustrate that expression profiles derived from whole tissue RNA highly reflect the degenerating tissues' altered cellular composition, not necessarily transcriptional regulation. To accurately understand transcriptional changes that accompany neuropathology, we acutely purify neurons, astrocytes and microglia from single adult mouse brains and analyse their transcriptomes by RNA sequencing. Using peripheral endotoxemia to establish the method, we reveal highly specific transcriptional responses and altered RNA processing in each cell type, with Tnfr1 required for the astrocytic response. Extending the method to an Alzheimer's disease model, we confirm that transcriptomic changes observed in whole tissue are driven primarily by cell type composition, not transcriptional regulation, and identify hundreds of cell type-specific changes undetected in whole tissue RNA. Applying similar methods to additional models and patient tissues will transform our understanding of aberrant gene expression in neurological disease.

Targeted mutation screening panels expose systematic population bias in detection of cystic fibrosis risk.

PURPOSE: Carrier screening for mutations contributing to cystic fibrosis (CF) is typically accomplished with panels composed of variants that are clinically validated primarily in patients of European descent. This approach has created a static genetic and phenotypic profile for CF. An opportunity now exists to reevaluate the disease profile of CFTR at a global population level. METHODS: CFTR allele and genotype frequencies were obtained from a nonpatient cohort with more than 60,000 unrelated personal genomes collected by the Exome Aggregation Consortium. Likely disease-contributing mutations were identified with the use of public database annotations and computational tools. RESULTS: We identified 131 previously described and likely pathogenic variants and another 210 untested variants with a high probability of causing protein damage. None of the current genetic screening panels or existing CFTR mutation databases covered a majority of deleterious variants in any geographical population outside of Europe. CONCLUSIONS: Both clinical annotation and mutation coverage by commercially available targeted screening panels for CF are strongly biased toward detection of reproductive risk in persons of European descent. South and East Asian populations are severely underrepresented, in part because of a definition of disease that preferences the phenotype associated with European-typical CFTR alleles.

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.

Moment based gene set tests.

BACKGROUND: Permutation-based gene set tests are standard approaches for testing relationships between collections of related genes and an outcome of interest in high throughput expression analyses. Using M random permutations, one can attain p-values as small as 1/(M+1). When many gene sets are tested, we need smaller p-values, hence larger M, to achieve significance while accounting for the number of simultaneous tests being made. As a result, the number of permutations to be done rises along with the cost per permutation. To reduce this cost, we seek parametric approximations to the permutation distributions for gene set tests. RESULTS: We study two gene set methods based on sums and sums of squared correlations. The statistics we study are among the best performers in the extensive simulation of 261 gene set methods by Ackermann and Strimmer in 2009. Our approach calculates exact relevant moments of these statistics and uses them to fit parametric distributions. The computational cost of our algorithm for the linear case is on the order of doing |G| permutations, where |G| is the number of genes in set G. For the quadratic statistics, the cost is on the order of |G|(2) permutations which can still be orders of magnitude faster than plain permutation sampling. We applied the permutation approximation method to three public Parkinson's Disease expression datasets and discovered enriched gene sets not previously discussed. We found that the moment-based gene set enrichment p-values closely approximate the permutation method p-values at a tiny fraction of their cost. They also gave nearly identical rankings to the gene sets being compared. CONCLUSIONS: We have developed a moment based approximation to linear and quadratic gene set test statistics' permutation distribution. This allows approximate testing to be done orders of magnitude faster than one could do by sampling permutations. We have implemented our method as a publicly available Bioconductor package, npGSEA (www.bioconductor.org) .

Caspase-3 deficiency results in disrupted synaptic homeostasis and impaired attention control.

The ability to attend to relevant stimuli and to adapt dynamically as demands change is a core aspect of cognition, and one that is impaired in several neuropsychiatric diseases, including attention deficit/hyperactivity disorder. However, the cellular and molecular mechanisms underlying such cognitive adaptability are poorly understood. We found that deletion of the caspase-3 gene, encoding an apoptosis protease with newly discovered roles in neural plasticity, disrupts attention in mice while preserving multiple learning and memory capabilities. Attention-related deficits include distractibility, impulsivity, behavioral rigidity, and reduced habituation to novel stimuli. Excess exploratory activity in Casp3(-/-) mice was correlated with enhanced novelty-induced activity in the dentate gyrus, which may be related to our findings that caspase-3 is required for homeostatic synaptic plasticity in vitro and homeostatic expression of AMPA receptors in vivo in response to chronic or repeated stimuli. These results suggest an important role for caspase-3 in synaptic suppression of irrelevant stimuli.

ReportingTools: an automated result processing and presentation toolkit for high-throughput genomic analyses.

UNLABELLED: It is common for computational analyses to generate large amounts of complex data that are difficult to process and share with collaborators. Standard methods are needed to transform such data into a more useful and intuitive format. We present ReportingTools, a Bioconductor package, that automatically recognizes and transforms the output of many common Bioconductor packages into rich, interactive, HTML-based reports. Reports are not generic, but have been individually designed to reflect content specific to the result type detected. Tabular output included in reports is sortable, filterable and searchable and contains context-relevant hyperlinks to external databases. Additionally, in-line graphics have been developed for specific analysis types and are embedded by default within table rows, providing a useful visual summary of underlying raw data. ReportingTools is highly flexible and reports can be easily customized for specific applications using the well-defined API. AVAILABILITY: The ReportingTools package is implemented in R and available from Bioconductor (version ≥ 2.11) at the URL: http://bioconductor.org/packages/release/bioc/html/ReportingTools.html. Installation instructions and usage documentation can also be found at the above URL.

Dual leucine zipper kinase is required for excitotoxicity-induced neuronal degeneration.

Excessive glutamate signaling is thought to underlie neurodegeneration in multiple contexts, yet the pro-degenerative signaling pathways downstream of glutamate receptor activation are not well defined. We show that dual leucine zipper kinase (DLK) is essential for excitotoxicity-induced degeneration of neurons in vivo. In mature neurons, DLK is present in the synapse and interacts with multiple known postsynaptic density proteins including the scaffolding protein PSD-95. To examine DLK function in the adult, DLK-inducible knockout mice were generated through Tamoxifen-induced activation of Cre-ERT in mice containing a floxed DLK allele, which circumvents the neonatal lethality associated with germline deletion. DLK-inducible knockouts displayed a modest increase in basal synaptic transmission but had an attenuation of the JNK/c-Jun stress response pathway activation and significantly reduced neuronal degeneration after kainic acid-induced seizures. Together, these data demonstrate that DLK is a critical upstream regulator of JNK-mediated neurodegeneration downstream of glutamate receptor hyper-activation and represents an attractive target for the treatment of indications where excitotoxicity is a primary driver of neuronal loss.

A tiered hidden Markov model characterizes multi-scale chromatin states.

Precise characterization of chromatin states is an important but difficult task for understanding the regulatory role of chromatin. A number of computational methods have been developed with varying levels of success. However, a remaining challenge is to model epigenomic patterns over multi-scales, as each histone mark is distributed with its own characteristic length scale. We developed a tiered hidden Markov model and applied it to analyze a ChIP-seq dataset in human embryonic stem cells. We identified a two-tier structure containing 15 distinct bin-level chromatin states grouped into three domain-level states. Whereas the bin-level states capture the local variation of histone marks, the domain-level states detect large-scale variations. Compared to bin-level states, the domain-level states are more robust and coherent. We also found active regions in intergenic regions that upon closer examination were expressed non-coding RNAs and pseudogenes. These results provide insights into an additional layer of complexity in chromatin organization.

Chromatin states accurately classify cell differentiation stages.

Gene expression is controlled by the concerted interactions between transcription factors and chromatin regulators. While recent studies have identified global chromatin state changes across cell-types, it remains unclear to what extent these changes are co-regulated during cell-differentiation. Here we present a comprehensive computational analysis by assembling a large dataset containing genome-wide occupancy information of 5 histone modifications in 27 human cell lines (including 24 normal and 3 cancer cell lines) obtained from the public domain, followed by independent analysis at three different representations. We classified the differentiation stage of a cell-type based on its genome-wide pattern of chromatin states, and found that our method was able to identify normal cell lines with nearly 100% accuracy. We then applied our model to classify the cancer cell lines and found that each can be unequivocally classified as differentiated cells. The differences can be in part explained by the differential activities of three regulatory modules associated with embryonic stem cells. We also found that the "hotspot" genes, whose chromatin states change dynamically in accordance to the differentiation stage, are not randomly distributed across the genome but tend to be embedded in multi-gene chromatin domains, and that specialized gene clusters tend to be embedded in stably occupied domains.

Epigenetic domains found in mouse embryonic stem cells via a hidden Markov model.

BACKGROUND: Epigenetics is an important layer of transcriptional control necessary for cell-type specific gene regulation. Recent studies have shown significant epigenetic patterns associated with developmental stages and diseases. However, previous studies have been mostly limited to focal epigenetic patterns, whereas methods for analyzing large-scale organizations are still lacking. RESULTS: We developed a hidden Markov model (HMM) approach for detecting the types and locations of epigenetic domains from multiple histone modifications. We used this method to analyze a published ChIP-seq dataset of five histone modification marks (H3K4me2, H3K4me3, H3K27me3, H3K9me3, and H3K36me3) in mouse embryonic stem (ES) cells. We identified three types of domains, corresponding to active, non-active, and null states. In total, our three-state HMM identified 258 domains in the mouse genome containing 9.6 genes on average. These domains were validated by a number of criteria. The largest domains correspond to olfactory receptor (OR) gene clusters. Each Hox gene cluster also forms a separate epigenetic domain. We found that each type of domain is associated with distinct biological functions and structural changes during early cell differentiation. CONCLUSIONS: The HMM approach successfully detects domains of consistent epigenetic patterns from ChIP-seq data, providing new insights into the role of epigenetics in long-range gene regulation.