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Lasseigne, B. N.

Publications and source records attributed to Lasseigne, B. N..

17 recordsLinked to original sources

Intersection of Regulatory Analysis and Signature Reversion Uncovers Therapeutic Drugs and Targets for SETBP1-HD

BackgroundSETBP1 haploinsufficiency disorder (SETBP1-HD) is a neurodevelopmental condition characterized by developmental delay, speech apraxia, motor deficits, and autism spectrum disorder (ASD), caused by deficiency of the transcription factor (TF) SETBP1. Since current management is limited to symptomatic relief, we defined a robust consensus molecular signature for SETBP1-HD and prioritized drugs that converge with SETBP1 regulatory targets. MethodsWe performed a meta-analysis of three independent transcriptomic datasets derived from in vitro models of SETBP1 deficiency. Using Robust Rank Aggregation (RRA), we overcame transcriptomic heterogeneity to establish a SETBP1-HD consensus signature. We integrated this signature with known and spatio-temporal-aware SETBP1 interactions to prioritize key regulatory and drug targets. Finally, we screened the LINCS L1000 drug perturbation database for compounds capable of reversing the consensus SETBP1-HD gene signature. ResultsOur regulatory analysis yielded potential, critical therapeutic windows, while our consensus analysis identified LIN28A (a key regulator of developmental timing) and SPON1 ( F-spondin) as novel, robustly upregulated targets across models. LIN28A provides a potential mechanism for the dysregulated neurogenesis and progenitor proliferation observed in patient-derived cells, while SPON1 links molecular dysfunction to motor and connectivity deficits seen in patients. Our in silico drug repurposing screens prioritized celecoxib and buspirone as top therapeutic candidates. Mechanistically, celecoxib targets the prioritized SETBP1 regulatory target COX-2 (PTGS2) to mitigate neuroinflammation, while the potent neuromodulator buspirone chemically stabilizes vulnerable circuits to correct the underlying neurotransmitter imbalance driven by SETBP1 loss. LimitationsThis study relies on in silico consensus modeling derived from cell culture and animal models. While robust statistical thresholds were applied, the therapeutic efficacy of the identified candidates on behavioral phenotypes--specifically motor deficits and speech apraxia--requires in vivo validation. Additionally, the specific contribution of LIN28A to the ASD phenotype warrants further functional characterization. ConclusionsWe defined a unified molecular mechanism for SETBP1-HD, in which dosage deficiency leads to a delayed neurogenic state driven by LIN28A, coupled with connectivity defects driven by SPON1, ultimately resulting in a destabilized excitation/inhibition balance. We identify celecoxib and buspirone as top therapeutic candidates, offering an immediate translational pathway to address the core neurodevelopmental, circuitry, and motor challenges associated with SETBP1-HD variants.

genomics↗

Cell-type-specific alternative splicing in the cerebral cortex of a Schinzel-Giedion Syndrome patient variant mouse model

Schinzel-Giedion Syndrome (SGS) is an ultra-rare Mendelian disorder caused by gain-of-function mutations in the SETBP1 gene. While previous studies determined multiple roles for how SETBP1 and associated pathways may cause disease manifestation, they have not assessed whether cell-type-specific alternative splicing (AS) plays a role in SGS. We quantified gene and splice junction (SJ) expression from snRNA-seq data we previously generated from the cerebral cortex and the kidney of an atypical Setbp1S858R SGS patient variant (n = 3) and wild-type (n = 3) mice. We performed pseudobulk differential gene expression and SJ usage (SJU) analyses across cell types and conditions. We identified 33 and 62 genes with statistically significant alterations in SJU in the brain and the kidney, respectively. Astrocytes and T cells had the most genes with cell-type-specific changes in SJU (n = 6 each) in the brain and kidney, respectively. We identified significant SJU in a member of the heterogeneous nuclear ribonucleoprotein family, Hnrnpa2b1. These findings were cell-type-specific for inhibitory neurons in the cerebral cortex and cell-type-agnostic in the kidney, suggesting tissue-specificity of AS in Setbp1S858R mice. To broaden the impact of our results for the rare disease community, we developed a point-and-click web application as a resource for users to explore single-cell resolution changes in the presence of Setbp1S858R at the gene and splice junction level. Overall, we find that AS may be implicated in a tissue- and cell-type-specific manner in the cerebral cortex and kidney of Setbp1S858R mice.

genomics↗

Evaluation of altered cell-cell communication between glia and neurons in the hippocampus of 3xTg-AD mice at two time points

Alzheimers disease (AD) is the most common form of dementia and is characterized by progressive memory loss and cognitive decline, affecting behavior, speech, and motor abilities. The neuropathology of AD includes the formation of extracellular amyloid-{beta} plaque and intracellular neurofibrillary tangles of phosphorylated tau, along with neuronal loss. While neuronal loss is an AD hallmark, cell-cell communication between neuronal and non-neuronal cell populations maintains neuronal health and brain homeostasis. To study changes in cellcell communication during disease progression, we performed snRNA-sequencing of the hippocampus from female 3xTg-AD and wild-type littermates at 6 and 12 months. We inferred differential cell-cell communication between 3xTg-AD and wild-type mice across time points and between senders (astrocytes, microglia, oligodendrocytes, and OPCs) and receivers (excitatory and inhibitory neurons) of interest. We also assessed the downstream effects of altered glia-neuron communication using pseudobulk differential gene expression, functional enrichment, and gene regulatory analyses. We found that glia-neuron communication is increasingly dysregulated in 12-month 3xTg-AD mice. We also identified 23 AD-associated ligand-receptor pairs that are upregulated in the 12-month-old 3xTg-AD hippocampus. Our results suggest increased AD association of interactions originating from microglia. Signaling mediators were not significantly differentially expressed but showed altered gene regulation and TF activity. Our findings indicate that altered glia-neuron communication is increasingly dysregulated and affects the gene regulatory mechanisms in neurons of 12-month-old 3xTg-AD mice.

genomics↗

Long-read RNA sequencing identifies region- and sex-specific C57BL/6J mouse brain mRNA isoform expression and usage

Alternative splicing (AS) contributes to the biological heterogeneity between species, sexes, tissues, and cell types. Many diseases are either caused by alterations in AS or by alterations to AS. Therefore, measuring AS accurately and efficiently is critical for assessing molecular phenotypes, including those associated with disease. Long-read sequencing enables more accurate quantification of differentially spliced isoform expression than short-read sequencing approaches, and third-generation platforms facilitate high-throughput experiments. To assess differences in AS across the cerebellum, cortex, hippocampus, and striatum by sex, we generated and analyzed Oxford Nanopore Technologies (ONT) long-read RNA sequencing (lrRNA-Seq) C57BL/6J mouse brain cDNA libraries. From >85 million reads that passed quality control metrics, we calculated differential gene expression (DGE), differential transcript expression (DTE), and differential transcript usage (DTU) across brain regions and by sex. We found significant DGE, DTE, and DTU across brain regions and that the cerebellum had the most differences compared to the other three regions. Additionally, we found region-specific differential splicing between sexes, with the most sex differences in DTU in the cortex and no DTU in the hippocampus. We also report on two distinct patterns of sex DTU we observed, sex-divergent and sex-specific, that could potentially help explain sex differences in the prevalence and prognosis of various neurological and psychiatric disorders in future studies. Finally, we built a Shiny web application for researchers to explore the data further. Our study provides a resource for the community; it underscores the importance of AS in biological heterogeneity and the utility of long-read sequencing to better understand AS in the brain.

genomics↗

Altered Glia-Neuron Communication in Alzheimer's Disease Affects WNT, p53, and NFkB Signaling Determined by snRNA-seq

BackgroundAlzheimers disease is the most common cause of dementia and is characterized by amyloid-{beta} plaques, tau neurofibrillary tangles, and neuronal loss. Although neuronal loss is a primary hallmark of Alzheimers disease, it is known that non-neuronal cell populations are ultimately responsible for maintaining brain homeostasis and neuronal health through neuron-glia and glial cell crosstalk. Many signaling pathways have been proposed to be dysregulated in Alzheimers disease, including WNT, TGF{beta}, p53, mTOR, NFkB, and Pi3k/Akt signaling. Here, we predict altered cell-cell communication between glia and neurons. MethodsUsing public snRNA-sequencing data generated from postmortem human prefrontal cortex, we predicted altered cell-cell communication between glia (astrocytes, microglia, oligodendrocytes, and oligodendrocyte progenitor cells) and neurons (excitatory and inhibitory). We confirmed interactions in a second and third independent orthogonal dataset. We determined cell-type-specificity using Jaccard Similarity Index and investigated the downstream effects of altered interactions in inhibitory neurons through gene expression and transcription factor activity analyses of signaling mediators. Finally, we determined changes in pathway activity in inhibitory neurons. ResultsCell-cell communication between glia and neurons is altered in Alzheimers disease in a cell-type-specific manner. As expected, ligands are more cell-type-specific than receptors and targets. We identified ligand-receptor pairs in three independent datasets and found involvement of the Alzheimers disease risk genes APP and APOE across datasets. Most of the signaling mediators of these interactions were not differentially expressed, however, the mediators that are also transcription factors had differential activity between AD and control. Namely, MYC and TP53, which are associated with WNT and p53 signaling, respectively, had decreased TF activity in Alzheimers disease, along with decreased WNT and p53 pathway activity in inhibitory neurons. Additionally, inhibitory neurons had both increased NFkB signaling pathway activity and increased TF activity of NFIL3, an NFkB signaling-associated transcription factor. ConclusionsCell-cell communication between glia and neurons in Alzheimers disease is altered in a cell-type-specific manner involving Alzheimers disease risk genes. Signaling mediators had altered transcription factor activity suggesting altered glia-neuron interactions may dysregulate signaling pathways including WNT, p53, and NFkB in inhibitory neurons.

genomics↗

The landscape of SETBP1 gene expression and transcription factor activity across human tissues

BackgroundThe SET binding protein 1 (SETBP1) gene encodes a transcription factor (TF) involved in various cellular processes. Distinct SETBP1 variants have been linked to three different diseases. Germline variants cause the ultra-rare pediatric Schinzel Giedion Syndrome (SGS) and SETBP1 haploinsufficiency disorder (SETBP1-HD), characterized by severe multisystemic abnormalities with neurodegeneration or a less severe brain phenotype accompanied by hypotonia and strabismus, respectively. Somatic variants in SETBP1 are associated with hematological malignancies and cancer development in other tissues in adults. ResultsTo better understand the tissue-specific mechanisms involving SETBP1, we analyzed publicly available RNA-sequencing data from the Genotype-Tissue Expression (GTEx) project. We found SETBP1, and its known target genes were widely expressed across 31 adult human tissues. K-means clustering identified three distinct expression patterns of SETBP1 targets across tissues. Functional enrichment analysis (FEA) of each cluster revealed gene sets related to transcription regulation, DNA binding, and mitochondrial function. TF activity analysis of SETBP1 and its target TFs revealed tissue-specific TF activity, underscoring the role of tissue context-driven regulation and suggesting its impact in SETBP1-associated disease. In addition to uncovering tissue-specific molecular signatures of SETBP1 expression and TF activity, we provide a Shiny web application to facilitate exploring TF activity across human tissues for 758 TFs. ConclusionsThis study provides insight into the landscape of SETBP1 expression and TF activity across 31 non-diseased human tissues and reveals tissue-specific expression and activity of SETBP1 and its targets. In conjunction with the web application we constructed, our framework enables researchers to generate hypotheses related to the role tissue backgrounds play with respect to gene expression and TF activity in different disease contexts.

genomics↗

Cell-type-specific gene expression and regulation in the cerebral cortex and kidney of atypical Setbp1S858R Schinzel Giedion Syndrome mice

Schinzel Giedion Syndrome (SGS) is an ultra-rare autosomal dominant Mendelian disease presenting with abnormalities spanning multiple organ systems. The most notable phenotypes involve severe developmental delay, progressive brain atrophy, and drug-resistant seizures. SGS is caused by spontaneous variants in SETBP1, which encodes for the epigenetic hub SETBP1 transcription factor (TF). SETBP1 variants causing classical SGS cluster at the degron, disrupting SETBP1 protein degradation resulting in toxic accumulation, while those located outside cause milder atypical SGS. Due to the multi-system phenotype, we evaluated gene expression and regulatory programs altered in atypical SGS by snRNA-seq of cerebral cortex and kidney of Setbp1S858R heterozygous mice (corresponds to the human likely pathogenic SETBP1S867R variant) compared to matched wild-type mice by constructing cell-type-specific regulatory networks. Setbp1 was differentially expressed in excitatory neurons, but known SETBP1 targets were differentially expressed and regulated in many cell types. Our findings suggest molecular drivers underlying neurodevelopmental phenotypes in classical SGS also drive atypical SGS, persist after birth, and are present in the kidney. Our results indicate SETBP1s role as an epigenetic hub leads to cell-type-specific differences in TF activity, gene targeting, and regulatory rewiring. This research provides a framework for investigating cell-type-specific variant impact on gene expression and regulation.

genomics↗

Sex-biased gene expression and gene-regulatory networks of sex-biased adverse event drug targets and drug metabolism genes

BackgroundPrevious pharmacovigilance studies and a retroactive review of cancer clinical trial studies identified that women were more likely to experience drug adverse events (i.e., any unintended effects of medication), and men were more likely to experience adverse events that resulted in hospitalization or death. These sex-biased adverse events (SBAEs) are due to many factors not entirely understood, including differences in body mass, hormones, pharmacokinetics, and liver drug metabolism enzymes and transporters. MethodsWe first identified drugs associated with SBAEs from the FDA Adverse Event Reporting System (FAERS) database. Next, we evaluated sex-specific gene expression of the known drug targets and metabolism enzymes for those SBAE-associated drugs. We also constructed sex-specific tissue gene-regulatory networks to determine if these known drug targets and metabolism enzymes from the SBAE-associated drugs had sex-specific gene-regulatory network properties and predicted regulatory relationships. ResultsWe identified liver-specific gene-regulatory differences for drug metabolism genes between males and females, which could explain observed sex differences in pharmacokinetics and pharmacodynamics. In addition, we found that [~]85% of SBAE-associated drug targets had sex-biased gene expression or were core genes of sex- and tissue-specific network communities, significantly higher than randomly selected drug targets. Lastly, we provide the sex-biased drug-adverse event pairs, drug targets, and drug metabolism enzymes as a resource for the research community. ConclusionsOverall, we provide evidence that many SBAEs are associated with drug targets and drug metabolism genes that are differentially expressed and regulated between males and females. These SBAE-associated drug metabolism enzymes and drug targets may be useful for future studies seeking to explain or predict SBAEs.

genomics↗

Inferring chromosomal instability from copy number aberrations as a measure of chromosomal instability across human cancers

BackgroundCancer is a complex disease that is the second leading cause of death in the United States. Despite research efforts, the ability to manage cancer and select optimal therapeutic responses for each patient remains elusive. Chromosomal instability (CIN) is primarily a product of segregation errors wherein one or many chromosomes, in part or whole, vary in number. CIN is an enabling characteristic of cancer, contributes to tumor-cell heterogeneity, and plays a crucial role in the multistep tumorigenesis process, especially in tumor growth and initiation and in response to treatment. AimsMultiple studies have reported different metrics for analyzing copy number aberrations as surrogates of CIN from DNA copy number variation data. However, these metrics differ in how they are calculated with respect to the type of variation, the magnitude of change, and the inclusion of breakpoints. Here we compared metrics capturing CIN as either numerical aberrations, structural aberrations, or a combination of the two across 33 cancer data sets from The Cancer Genome Atlas (TCGA). Methods and resultsUsing CIN inferred by methods in the CINmetrics R package, we evaluated how six copy number CIN surrogates compared across TCGA cohorts by assessing each across tumor types, as well as how they associate with tumor stage, metastasis, and nodal involvement, and with respect to patient sex. ConclusionsWe found that the tumor type impacts how well any two given CIN metrics correlate. While we also identified overlap between metrics regarding their association with clinical characteristics and patient sex, there was not complete agreement between metrics. We identified several cases where only one CIN metric was significantly associated with a clinical characteristic or patient sex for a given tumor type. Therefore, caution should be used when describing CIN based on a given metric or comparing it to other studies.

genomics↗

CoSIA: an R Bioconductor package for CrOss Species Investigation and Analysis

SummaryHigh throughput sequencing technologies have enabled cross-species comparative transcriptomic studies; however, there are numerous challenges for these studies due to biological and technical factors. We developed CoSIA (Cross-Species Investigation and Analysis), an Bioconductor R package and Shiny app that provides an alternative framework for cross-species transcriptomic comparison of non-diseased wild-type RNA sequencing gene expression data from Bgee across tissues and species (human, mouse, rat, zebrafish, fly, and nematode) through visualization of variability, diversity, and specificity metrics. Availability and Implementationhttps://github.com/lasseignelab/CoSIA ContactBrittany Lasseigne (bnp0001@uab.edu) Supplementary informationSee Supplementary Files

bioinformatics↗

Evaluating cancer cell line and patient-derived xenograft recapitulation of tumor and non-diseased tissue gene expression profiles

Preclinical models like cancer cell lines and patient-derived xenografts (PDXs) are vital for studying disease mechanisms and evaluating treatment options. It is essential that they accurately recapitulate the disease state of interest to generate results that will translate in the clinic. Prior studies have demonstrated that preclinical models do not recapitulate all biological aspects of human tissues, particularly with respect to the tissue of origin gene expression signatures. Therefore, it is critical to assess how well preclinical model gene expression profiles correlate with human cancer tissues to inform preclinical model selection and data analysis decisions. Here we evaluated how well preclinical models recapitulate human cancer and non-diseased tissue gene expression patterns in silico with respect to the full gene expression profile as well as subsetting by the most variable genes, genes significantly correlated with tumor purity, and tissue-specific genes by using publicly available gene expression profiles across multiple sources. We found that using the full gene set improves correlations between preclinical model and tissue global gene expression profiles, confirmed that GBM PDX global gene expression correlation to GBM tumor global gene expression outperforms GBM cell line to GBM tumor global gene expression correlations, and demonstrated that preclinical models in our study often failed to reproduce tissue-specific expression. While including additional genes for global gene expression comparison between cell lines and tissues decreases the overall correlation, it improves the relative rank between a cell line and its tissue of origin compared to other tissues. Our findings underscore the importance of using the full gene expression set measured when comparing preclinical models and tissues and confirm that tissue-specific patterns are better preserved in GBM PDX models than in GBM cell lines. Future studies can build on these findings to determine the specific pathways and gene sets recapitulated by particular preclinical models to facilitate model selection for a given study design or goal.

genomics↗

Signature reversion of three disease-associated gene signatures prioritizes cancer drug repurposing candidates

Drug repurposing is promising because approving a drug for a new indication requires fewer resources than approving a new drug. Signature reversion detects drug perturbations most inversely related to the disease-associated gene signature to identify drugs that may reverse that signature. We assessed the performance and biological relevance of three approaches for constructing disease-associated gene signatures (i.e, limma, DESeq2, and MultiPLIER) and prioritized the resulting drug repurposing candidates for four low-survival human cancers. Our results were enriched for candidates that had been used in clinical trials or performed well in the PRISM drug screen. Additionally, we found that pamidronate and nimodipine, drugs predicted to be efficacious against the brain tumor glioblastoma (GBM), inhibited the growth of a GBM cell line and cells isolated from a patient derived xenograft (PDX). Our results demonstrate that by applying multiple disease-associated gene signature methods, we prioritized several drug repurposing candidates for low-survival cancers. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=155 HEIGHT=200 SRC="FIGDIR/small/532074v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@1c5d402org.highwire.dtl.DTLVardef@e1dc86org.highwire.dtl.DTLVardef@54e6feorg.highwire.dtl.DTLVardef@96856_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

Prioritized polycystic kidney disease drug targets and repurposing candidates from pre-cystic and cystic mouse model gene expression reversion

Autosomal dominant polycystic kidney disease (ADPKD) is one of the most prevalent monogenic human diseases. It is mostly caused by pathogenic variants in PKD1 or PKD2 genes that encode interacting transmembrane proteins polycystin-1 (PC1) and polycystin-2 (PC2). Among many pathogenic processes described in ADPKD, those associated with cAMP signaling, inflammation, and metabolic reprogramming appear to regulate the disease manifestations. Tolvaptan, a vasopressin receptor-2 antagonist that regulates cAMP pathway, is the only FDA-approved ADPKD therapeutic. Tolvaptan reduces renal cyst growth and kidney function loss, but it is not tolerated by many patients and is associated with idiosyncratic liver toxicity. Therefore, additional therapeutic options for ADPKD treatment are needed. As drug repurposing of FDA-approved drug candidates can significantly decrease the time and cost associated with traditional drug discovery, we used the computational approach signature reversion to detect inversely related drug response gene expression signatures from the Library of Integrated Network-Based Cellular Signatures (LINCS) database and identified compounds predicted to reverse disease-associated transcriptomic signatures in three publicly available Pkd2 kidney transcriptomic data sets of mouse ADPKD models. We focused on a pre-cystic model for signature reversion, as it was less impacted by confounding secondary disease mechanisms in ADPKD, and then compared the resulting candidates target differential expression in the two cystic mouse models. We further prioritized these drug candidates based on their known mechanism of action, FDA status, targets, and by functional enrichment analysis. With this in-silico approach, we prioritized 29 unique drug targets differentially expressed in Pkd2 ADPKD cystic models and 16 prioritized drug repurposing candidates that target them, including bromocriptine and mirtazapine, which can be further tested in-vitro and in-vivo. Collectively, these indicate drug targets and repurposing candidates that may effectively treat pre-cystic as well as cystic ADPKD. O_FIG O_LINKSMALLFIG WIDTH=110 HEIGHT=200 SRC="FIGDIR/small/518863v2_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@18af02org.highwire.dtl.DTLVardef@89d45corg.highwire.dtl.DTLVardef@d4fffdorg.highwire.dtl.DTLVardef@1f244b3_HPS_FORMAT_FIGEXP M_FIG Graphical abstract of the study created with Biorender.com. C_FIG

genomics↗

CINmetrics: An R package for chromosomal instability analysis

Genomic instability is an important hallmark of cancer and more recently has been identified in others like neurodegenrative diseases. Chromosomal instability, as a measure of genomic instability, has been used to characterize clinical and biological phenotypes associated with these diseases by measuring structural and numerical chromosomal alterations. There have been multiple chromosomal instability scores developed across many studies in the literature; however, these scores have not been compared because of the lack of a single tool available to calculate and facilitate these various metrics. Here, we provide an R package CINmetrics, that calculates six different chromosomal instability scores and allows direct comparison between them. We also demonstrate how these scores differ by applying CINmetrics to breast cancer data from The Cancer Genome Atlas (TCGA). The package is available on CRAN at https://cran.r-project.org/package=CINmetrics and on github at https://github.com/lasseignelab/CINmetrics.

cancer biology↗

Non-Coding and Loss-of-Function Coding Variants in TET2 are Associated with Multiple Neurodegenerative Diseases

We conducted genome sequencing to search for rare variation contributing to early onset Alzheimers disease (EOAD) and frontotemporal dementia (FTD). Discovery analysis was conducted on 493 cases and 671 controls of European ancestry. Burden testing for rare variation associated with disease was conducted using filters based on variant rarity (less than 1 in 10,000 or private), computational prediction of deleteriousness (CADD 10 or 15 thresholds), and molecular function (protein loss-of-function only, coding alteration only, or coding plus non-coding variants in experimentally predicted regulatory regions).\n\nReplication analysis was conducted on 16,871 independent cases and 15,941 independent controls. Rare variants in TET2 were enriched in the discovery combined EOAD and FTD cohort (p=6.5x10-8, genome-wide corrected p=0.0037). Most of these variants were canonical loss-of-function or non-coding in predicted regulatory regions. This enrichment replicated across several cohorts of AD and FTD (replication only p=0.0071). The combined analysis odds ratio was 2.2 (95% CI 1.5-3.2) for AD and FTD. The odds ratio for qualifying non-coding variants considered independently from coding variants was 2.1 (95% CI 1.2-3.9). For loss-of-function variants, the combined odds ratio (for AD, FTD, and amyotrophic lateral sclerosis, which shares clinicopathological overlap with FTD) was 3.2 (95% CI 2.0-5.3). TET2 catalyzes DNA demethylation. Given well-defined changes in DNA methylation that occur during aging, rare variation in TET2 may confer risk for neurodegeneration by altering the homeostasis of key aging-related processes. Additionally, our study emphasizes the relevance of non-coding variation in genetic studies of complex disease.

neuroscience↗

Genome sequencing for early-onset dementia: high diagnostic yield and frequent observation of multiple contributory alleles

We assessed the utility of genome sequencing for early-onset dementia. Participants were selected from a memory disorders clinic. Genome sequencing was performed along with C9orf72 repeat expansion testing. All returned sequencing results were Sanger validated clinically. Prior clinical diagnoses included Alzheimers disease, frontotemporal dementia, and unspecified dementia. The mean age-of-onset was 54 (41-76). 50% of patients had a strong family history, 37.5% had some, and 12.5% had no known family history. Nine of 32 patients (28%) had a variant defined as pathogenic or likely pathogenic (P/LP) by American College of Medical Genetics standards, including variants in APP, C9orf72, CSF1R, and MAPT. Nine patients (including three with P/LP variants) harbored established risk alleles with moderate penetrance (odds ratios of about 2-5) in ABCA7, AKAP9, GBA, PLD3, SORL1, and TREM2. All six patients harboring these moderate penetrance variants but not P/LP variants also had one or two APOE {varepsilon}4 alleles. One patient had two APOE {varepsilon}4 alleles with no other established contributors. In total, 16 patients (50%) harbored one or more genetic variants likely to explain symptoms. We identified variants of uncertain significance (VUSs) in ABI3, ADAM10, ARSA, GRID2IP, MME, NOTCH3, PLCD1, PSEN1, TM2D3, TNK1, TTC3, and VPS13C, also often along with other variants. In summary, genome sequencing for early-onset dementia demonstrated high utility, with particular advantages where targeted testing may fail such as atypical variant-disease associations or presence of multiple moderate impact alleles. One or more established contributory alleles is often present in early-onset dementia, supporting an oligogenic model.

neuroscience↗

Regional collapsing of rare variation implicates specific genic regions in ALS

Large-scale sequencing efforts in amyotrophic lateral sclerosis (ALS) have implicated novel genes using gene-based collapsing methods. However, pathogenic mutations may be concentrated in specific genic regions. To address this, we developed two collapsing strategies, one focuses rare variation collapsing on homology-based protein domains as the unit for collapsing and another gene-level approach that, unlike standard methods, leverages existing evidence of purifying selection against missense variation on said domains. The application of these two collapsing methods to 3,093 ALS cases and 8,186 controls of European ancestry, and also 3,239 cases and 11,808 controls of diversified populations, pinpoints risk regions of ALS genes including SOD1, NEK1, TARDBP and FUS. While not clearly implicating novel ALS genes, the new analyses not only pinpoint risk regions in known genes but also highlight candidate genes as well.

genetics↗