The Monarch Initiative in 2024: an analytic platform integrating phenotypes, genes and diseases across species.

Bridging the gap between genetic variations, environmental determinants, and phenotypic outcomes is critical for supporting clinical diagnosis and understanding mechanisms of diseases. It requires integrating open data at a global scale. The Monarch Initiative advances these goals by developing open ontologies, semantic data models, and knowledge graphs for translational research. The Monarch App is an integrated platform combining data about genes, phenotypes, and diseases across species. Monarch's APIs enable access to carefully curated datasets and advanced analysis tools that support the understanding and diagnosis of disease for diverse applications such as variant prioritization, deep phenotyping, and patient profile-matching. We have migrated our system into a scalable, cloud-based infrastructure; simplified Monarch's data ingestion and knowledge graph integration systems; enhanced data mapping and integration standards; and developed a new user interface with novel search and graph navigation features. Furthermore, we advanced Monarch's analytic tools by developing a customized plugin for OpenAI's ChatGPT to increase the reliability of its responses about phenotypic data, allowing us to interrogate the knowledge in the Monarch graph using state-of-the-art Large Language Models. The resources of the Monarch Initiative can be found at monarchinitiative.org and its corresponding code repository at github.com/monarch-initiative/monarch-app.

Bioinformatic Identification of Signaling Pathways and Hub Genes in Vascular Dementia

Background: Vascular dementia (VaD) is a prevalent neurodegenerative disease characterized by cognitive impairment due to cerebrovascular factors, affecting a significant portion of the aging population and highlighting the critical need to understand specific targets and mechanisms for effective prevention and treatment strategies. We aimed to identify pathways and crucial genes involved in the progression of VaD through bioinformatics analysis and subsequently validate these findings. Methods: We conducted differential expression analysis, Weighted Gene Co-expression Network Analysis (WGCNA), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and Protein-Protein Interaction (PPI) analysis. We utilized pheochromocytoma 12 (PC12) cells to create an in vitro oxygen-glucose deprivation (OGD) model. We investigated the impact of overexpression and interference of adrenoceptor alpha 1D (ADRA1D) on OGD PC12 cells using TdT-mediated dUTP nick-end labeling (TUNEL), reverse transcription-quantitative polymerase chain reaction (RT-qPCR), western blot (WB), and Fluo-3-pentaacetoxymethyl ester (Fluo-3 AM) analysis. Results: We found 187 differentially expressed genes (DEGs) in the red module that were strongly associated with VaD and were primarily enriched in vasoconstriction, G protein-coupled amine receptor activity, and neuroactive ligand-receptor interaction, mitogen-activated protein kinase (MAPK) signaling pathway, and cell adhesion. Among these pathways, we identified ADRA1D as a gene shared by vasoconstriction, G protein-coupled amine receptor activity, and neuroactive ligand-receptor interaction. The TUNEL assay revealed a significant decrease in PC12 cell apoptosis with ADRA1D overexpression (p < 0.01) and a significant increase in apoptosis upon silencing ADRA1D (p < 0.01). RT-qPCR and WB analysis revealed elevated ADRA1D expression (p < 0.001) ... (AU)

g:Profiler-interoperable web service for functional enrichment analysis and gene identifier mapping (2023 update).

g:Profiler is a reliable and up-to-date functional enrichment analysis tool that supports various evidence types, identifier types and organisms. The toolset integrates many databases, including Gene Ontology, KEGG and TRANSFAC, to provide a comprehensive and in-depth analysis of gene lists. It also provides interactive and intuitive user interfaces and supports ordered queries and custom statistical backgrounds, among other settings. g:Profiler provides multiple programmatic interfaces to access its functionality. These can be easily integrated into custom workflows and external tools, making them valuable resources for researchers who want to develop their own solutions. g:Profiler has been available since 2007 and is used to analyse millions of queries. Research reproducibility and transparency are achieved by maintaining working versions of all past database releases since 2015. g:Profiler supports 849 species, including vertebrates, plants, fungi, insects and parasites, and can analyse any organism through user-uploaded custom annotation files. In this update article, we introduce a novel filtering method highlighting Gene Ontology driver terms, accompanied by new graph visualizations providing a broader context for significant Gene Ontology terms. As a leading enrichment analysis and gene list interoperability service, g:Profiler offers a valuable resource for genetics, biology and medical researchers. It is freely accessible at https://biit.cs.ut.ee/gprofiler.

HGCA2.0: An RNA-Seq Based Webtool for Gene Coexpression Analysis in Homo sapiens.

Genes with similar expression patterns in a set of diverse samples may be considered coexpressed. Human Gene Coexpression Analysis 2.0 (HGCA2.0) is a webtool which studies the global coexpression landscape of human genes. The website is based on the hierarchical clustering of 55,431 Homo sapiens genes based on a large-scale coexpression analysis of 3500 GTEx bulk RNA-Seq samples of healthy individuals, which were selected as the best representative samples of each tissue type. HGCA2.0 presents subclades of coexpressed genes to a gene of interest, and performs various built-in gene term enrichment analyses on the coexpressed genes, including gene ontologies, biological pathways, protein families, and diseases, while also being unique in revealing enriched transcription factors driving coexpression. HGCA2.0 has been successful in identifying not only genes with ubiquitous expression patterns, but also tissue-specific genes. Benchmarking showed that HGCA2.0 belongs to the top performing coexpression webtools, as shown by STRING analysis. HGCA2.0 creates working hypotheses for the discovery of gene partners or common biological processes that can be experimentally validated. It offers a simple and intuitive website design and user interface, as well as an API endpoint.

The Human Host Defense Peptide LL-37 Overexpressed in Lung Cell Lines by Methanolic Extract of Valeriana officinalis

Abstract The present study investigated the effects of valerian methanolic extract and valerenic acid on the expression of LL-37 gene and protein in A549 and MRC5 line cells. After preparing Valerian seeds, sowing them in March 2020, and harvesting the rhizome in October 2020, the extract was prepared from the valerian rhizome by maceration method. Valerian acid content was determined using high performance liquid chromatography (HPLC). Two cell lines (A549 and MRC-5) were used to study the effects of valerian extract, and the MTT test was used to evaluate cell viability. The expression of LL-37 mRNA and protein was assessed by Real-Time PCR and western blot, respectively. In vivo safety assessments and histopathological analysis were also conducted. Data was analyzed by Graphpad Prism 8 software. Valerian methanolic extract and valerenic acid upregulated the LL-37 mRNA and protein expression in both treated cell lines. Valerenic acid showed a greater effect on upregulating LL-37 expression than valerian methanolic extract. A549 cells were more sensitive to valerian methanolic extract compared to MRC5 cells, and its cell viability was reduced. Furthermore, liver and kidney-related safety assessments showed that valerian methanolic extract had no toxic effects. In general, it was concluded that the methanolic extract of valerian as well as the resulting valerenic acid as the most important component of the extract has the ability to upregulate LL-37expression. Therefore, methanolic extract of valerian and valerenic acid can be considered for improving the immune system.

Obesidade genética não sindrômica: histórico, fisiopatologia e principais genes / Non-syndromic genetic obesity: history, pathophysiology and key genes

A obesidade é definida pelo excesso de gordura corporal acumulada no tecido adiposo quando o indivíduo atinge valores de IMC igual ou superior a 30 Kg/m2. Constitui um dos principais fatores de risco para várias doenças não transmissíveis (DNTs) como por exemplo, diabetes mellitus tipo 2 (DM2), doenças cardiovasculares, hipertensão arterial, acidente vascular cerebral e até mesmo o câncer. Embora a obesidade esteja diretamente relacionada com o consumo calórico excessivo em relação ao gasto energético diário, sua etiologia pode estar associada aos baixos níveis de atividade física, às alterações neuroendócrinas e aos fatores genéticos. Considerando o componente genético, esta pode ser classificada como sindrômicas e estar associada às alterações cromossômicas estruturais ou numéricas, ou como não sindrômica, quando relacionada, principalmente, com os polimorfismos de nucleotídeos simples (SNPs) em alelos que atuam como herança monogênica, ou ainda com a interação vários genes (poligênica multifatorial). Apesar de existirem muitas etiologias diferentes, normalmente a obesidade é tratada a partir da mesma abordagem, desconsiderando a fisiologia que a desencadeou. Dessa forma, o objetivo do presente trabalho foi abordar a obesidade genética não sindrômica por meio a) da descrição breve de perspectiva histórica sobre seu entendimento; b) da exposição dos principais mecanismos moleculares envolvidos com o controle de peso; c) da compilação dos principais genes e SNPs relacionados; d) da definição dos principais genes; e e) da abordagem das principais perspectivas de intervenção.

Obesity is defined as excess body fat accumulated in the adipose tissue when the individual reaches BMI values equal to or greater than 30 kg/m2. It is one of the main risk factors for several non-communicable diseases (NCDs), such as Type 2 Diabetes mellitus (T2D), cardiovascular diseases, high blood pressure, stroke and even cancer. Although obesity is directly related to excessive calorie intake in relation to daily energy expenditure, its etiology may be associated with low levels of physical activity, neuroendocrine changes, and genetic factors. Considering the genetic component, it can be classified as syndromic and be associated with chromosomal or numerical changes, or as non-syndromic and being related mainly to single nucleotide polymorphisms (SNPs) in alleles that act as monogenic inheritance, or with an interaction of several genes (multifactorial polygenic). Although there are many different etiologies, obesity is usually treated using the same approach, disregarding the physiology that triggered it. Thus, the aim of this study was to address non-syndromic genetic obesity through a) a brief description of a historical perspective on its understanding; b) the exposure of the main molecular mechanisms involved in weight control, c) the compilation of the key genes and related SNPs, d) the definition of the key genes and e) the approach of the main intervention representations.

Mutational Landscape Screening Through Comprehensive In Silico Analysis for Polycystic Ovarian Syndrome-Related Genes.

Polycystic ovary syndrome (PCOS) is a multifactorial endocrinopathy of indistinguishable etiopathogenesis that is liable to entail genetic and environmental machinery synergistically interacting with its phenotypic expression. It has been hypothesized that the environment secondarily interacts with genes to define the quantifiable phenotype in a primary, genetically determined, hyper-androgenic ovarian defect. The severity and prevalence of the disease are escalating due to uncontrolled diet and lifestyle, the influence of multiple environmental factors as well as genetic disorders. Many candidate genes have been identified to be one of the causes of PCOS. Different studies have been carried out to find the genetic correlation of PCOS. The mutational landscape analysis scans the entire genes for SNPs which usually occurs more frequently in patients and not in healthy individuals. In this study, an extensive computational analysis of all reported nsSNPs of the 27 selected PCOS-related genes was performed to infer the most pathogenic forms associated with PCOS. As a result, 28 genetic variants from 11 genes were predicted to be most harmful. Results of the present study can be useful for building an integrative genotype-phenotype database for further studies.

A Novel Noncanonical Splicing Mutation of ANOS1 Gene in Siblings with Kallmann Syndrome Identified by Whole-Exome Sequencing.

Kallmann syndrome (KS) is a rare genetic disorder that is characterized by idiopathic hypogonadotropic hypogonadism associated with anosmia. Genetic variants in ANOS1 gene are the most common mutations associated with X-linked recessive form of KS. Canonical ± 1 or 2 splice site variants in ANOS1 have been described to be responsible for KS. Here, we identified a novel noncanonical splice site variant (c.1062+4T>C) in ANOS1 gene in two siblings with KS by whole-exome sequencing (WES). Sanger sequencing showed this mutation was inherited from their mother, whose brother was a KS patient as well. Through the functional assay in vitro, we found that this mutation resulted in a 50-bp deletion of exon 7, which caused frameshift mutation leading to a premature termination of translation and a truncated anosmin-1 protein. Our results revealed that this noncanonical splice site variant is involved in KS. Thus, it is suggested that we should pay attention to the noncanonical splice site variants when using molecular genetic diagnostics of KS.

Extracting multi-way chromatin contacts from Hi-C data.

There is a growing realization that multi-way chromatin contacts formed in chromosome structures are fundamental units of gene regulation. However, due to the paucity and complexity of such contacts, it is challenging to detect and identify them using experiments. Based on an assumption that chromosome structures can be mapped onto a network of Gaussian polymer, here we derive analytic expressions for n-body contact probabilities (n > 2) among chromatin loci based on pairwise genomic contact frequencies available in Hi-C, and show that multi-way contact probability maps can in principle be extracted from Hi-C. The three-body (triplet) contact probabilities, calculated from our theory, are in good correlation with those from measurements including Tri-C, MC-4C and SPRITE. Maps of multi-way chromatin contacts calculated from our analytic expressions can not only complement experimental measurements, but also can offer better understanding of the related issues, such as cell-line dependent assemblies of multiple genes and enhancers to chromatin hubs, competition between long-range and short-range multi-way contacts, and condensates of multiple CTCF anchors.

Identification of Feature Autophagy-Related Genes and DNA Methylation Profiles in Systemic Lupus Erythematosus Patients.

BACKGROUND The aim of this study was to identify feature autophagy-related genes (ARGs) in systemic lupus erythematosus (SLE), evaluate their diagnostic value, and further explore DNA methylation and expression levels in the pathogenesis of SLE. MATERIAL AND METHODS WGCNA was used to construct network and selected hub genes based on gene expression dataset GSE81622. ARGS were overlapped with hub genes, and feature ARGs were identified. A diagnostic model was established by these feature ARGs using LASSO. GSE96879 was used to analyze the methylation levels of feature ARGs. The expression and methylation levels of feature ARGs were verified using RT-PCR and methylation-specific PCR. RESULTS We found that 55 hub genes were highly connected to the red module of WGCNA, and ARGs were extracted from the Human Autophagy Database and the GO_AUTOPHAGY gene set. Overlapping of 55 hub gene with ARGs resulted in 18 feature ARGs. S100A8, MyD88, and NCR3 from the 18 feature ARGs showed higher good diagnostic value for SLE. Five differentially methylated positions locating to S100A8, MyD88, and NCR3 genes were identified from GSE96879. After validation tests, RT-PCR showed that gene expressions of MyD88 and S100A8 were increased in the PBMCs samples of SLE patients compared with healthy controls, whereas NCR3 was the opposite. MSP found that cg24898863 (S100A8) was hypomethylated, while cg27490128 (NCR3) was hypermethylated in the SLE group, and S100A8 and NCR3 methylation were positively correlated with their expressions. CONCLUSIONS Our present study identified the potential roles of feature ARGs in SLE diagnosis, and shows correlation among DNA methylation and gene expressions of these feature ARGs in SLE.

The risks of using unapproved gene symbols.

The use of approved nomenclature in publications is vital to enable effective scientific communication and is particularly crucial when discussing genes of clinical relevance. Here, we discuss several examples of cases where the failure of researchers to use a HUGO Gene Nomenclature Committee (HGNC)-approved symbol in publications has led to confusion between unrelated human genes in the literature. We also inform authors of the steps they can take to ensure that they use approved nomenclature in their manuscripts and discuss how referencing HGNC IDs can remove ambiguity when referring to genes that have previously been published with confusing alias symbols.

Changes in DNA methylation in APOE and ACKR3 genes in multiple sclerosis patients and the relationship with their heavy metal blood levels.

Multiple sclerosis (MS) is a chronic inflammatory disease with demyelinated lesions in the central nervous system caused by genetic and environmental factors. DNA methylation as an epigenetic change influenced by environmental factors, including heavy metals has been implemented in MS disease. We investigated the correlation of DNA methylation changes in APOE and ACKR3 genes in MS patients and the possible association with blood concentration of arsenic (As), cadmium (Cd) and lead (Pb) as major heavy metal pollutants. This study included 69 relapsing-remitting multiple sclerosis (RR-MS) patients and 69 age/gender-matched healthy subjects. The HRM real-time PCR method was used to investigate the changes in DNA methylation and heavy metal concentrations were measured by electrothermal atomic absorption spectrometry. Our results showed that the methylation pattern in the ACKR3 gene of the patient group was more hypomethylated, while in the case of the APOE gene, this pattern was more towards hypermethylation compared to healthy subjects. Moreover, the blood levels of As and Cd metals, but not Pb, were significantly higher in the patient group compare to the control group (p ≤ 0.05). The data indicate that the increase in expression of ACKR3 gene by hypomethylation and the decrease in expression of APOE gene via hypermethylation are possibly involved in the onset and progression of inflammatory processes in MS patients. The level of As can also lead to hypomethylation by disrupting the methylation patterns of the ACKR3 gene, resulting in increased expression in MS patients. Finally, we have shown that epigenetic changes can be an important factor in increasing and decreasing the expression of genes involved in the onset and/or progression of inflammatory processes in MS. Furthermore, exposure to heavy metals, especially As, by changing the natural patterns of DNA methylation can be effective in this disease.

Association study of six candidate genes with major depressive disorder in the North-Western population of Pakistan.

People around the world are currently affected by Major Depressive Disorder (MDD). Despite its many aspects, symptoms, manifestations and impacts, efforts have been made to identify the root causes of the disorder. In particular, genetic studies have concentrated on identifying candidate genes for MDD and exploring associations between these genes and some specific group of individuals. The aim of this research was to find out the association between single nucleotide polymorphisms in 6 candidate genes linked to the neurobiology of major depressive disorder in the North-Western population of Pakistan. We performed a case-control analysis, with 400 MDD and 232 controls. A trained psychiatrist or clinical psychologists evaluated the patients. Six polymorphisms were genotyped and tested for allele and genotype association with MDD. There were no statistical variations between MDD patients and healthy controls for genotypic and allelic distribution of all the polymorphisms observed. Thus, our analysis does not support the major role of these polymorphisms in contributing to MDD susceptibility, although it does not preclude minor impact. The statistically significant correlation between six polymorphisms and major depressive disorder in the studied population was not observed. There are inconsistencies in investigations around the world. Future research, including GWAS and association analysis on larger scale should be addressed for further validation and replication of the present findings.

Non-syndromic inherited retinal diseases in Poland: Genes, mutations, and phenotypes.

Purpose: Inherited retinal diseases (IRDs), encompassing many clinical entities affecting the retina, are classified as rare disorders. Their extreme heterogeneity made molecular screening in the era before next-generation sequencing (NGS) expensive and time-consuming. Since then, many NGS studies of IRD molecular background have been conducted in Western populations; however, knowledge of the IRD mutational spectrum in Poland is still limited. Until now, there has been almost no comprehensive analysis of this particular population regarding the molecular basis and inheritance of IRDs. Therefore, the purpose of this study was to gain knowledge about the type and prevalence of causative variants in the Polish population. Methods: We recruited 190 Polish families with non-syndromic IRDs, including Stargardt disease (STGD), retinitis pigmentosa (RP), cone- and cone-rod dystrophy (CD/CRD), achromatopsia, and congenital stationary night blindness. A pool of molecular inversion probes was used, which targeted 108 genes associated with non-syndromic IRDs known in 2013. We applied filtering for known variants occurring with an allele frequency >0.5% in public and in-house databases, with the exception of variants in ABCA4, when the frequency filter was set to 3.0%. Hypomorphic p.(Asn1868Ile) was added manually. In the case of novel missense or splicing variants, we used in silico prediction software to assess mutation causality. Results: We detected causative mutations in 115 of the 190 families with non-syndromic IRD (60.2%). Fifty-nine individuals with STGD, RP, and CD/CRD carried causal variants in ABCA4. Novel single nucleotide variants were found in ABCA4, CEP290, EYS, MAK, and CNGA3. The complex allele c.[1622T>C;3113C>T], p.[Leu541Pro;Ala1038Val] was found in 33 individuals with ABCA4-associated disorders, which makes it the most prevalent allele in the Polish population (17% of all solved cases). Diagnosis was reevaluated in 16 cases. Conclusions: Previously, there were no comprehensive reports of IRDs in the Polish population. This study is the first to indicate that the most common IRDs in Poland are ABCA4-associated diseases, regardless of the phenotype. In Polish patients with RP, the second most prevalent causal gene was RHO and the third RPGR, while there were not as many mutations in EYS as in Western populations. The number of initial erroneous diagnoses may be the result of limited access to diagnostics with advanced tools, such as electroretinography; however, it is necessary to raise awareness among Polish ophthalmologists of rare IRDs. Additionally, it must be emphasized that in some cases genetic analysis of the patient is necessary to achieve an accurate diagnosis.

AHR-dependent genes and response to MTX therapy in rheumatoid arthritis patients.

Methotrexate (MTX) is the first-line therapy for rheumatoid arthritis. Nevertheless, MTX resistance is quite a common issue in clinical practice. There are some premises that aryl hydrocarbon receptor (AhR) gene battery may take part in MTX metabolism. In the present retrospective study, we analyzed genes expression of AHR genes battery associated with MTX metabolism in whole blood of RA patients with good and poor response to MTX treatment. Additionally, sequencing, genotyping and bioinformatics analysis of AHR repressor gene (AHRR) c.565C > G (rs2292596) and c.1933G > C (rs34453673) have been performed. Theoretically, both changes may have an impact on H3K36me3 and H3K27me3. Evolutionary analysis revealed that rs2292596 may be possibly damaging. Allele G in rs2292596 and DAS28 seems to be associated with a higher risk of poor response to MTX treatment in RA. RA patients with poor response to MTX treatment revealed upregulated AhR and SLC19A1 mRNA level. Treatment with IL-6 inhibitor may be helpful to overcome the low-dose MTX resistance. Analysis of gene expression revealed possible another cause of poor response to MTX treatment which is different from that observed in the case of acute lymphoblastic leukemia.

Gene name errors: Lessons not learned.

Erroneous conversion of gene names into other dates and other data types has been a frustration for computational biologists for years. We hypothesized that such errors in supplementary files might diminish after a report in 2016 highlighting the extent of the problem. To assess this, we performed a scan of supplementary files published in PubMed Central from 2014 to 2020. Overall, gene name errors continued to accumulate unabated in the period after 2016. An improved scanning software we developed identified gene name errors in 30.9% (3,436/11,117) of articles with supplementary Excel gene lists; a figure significantly higher than previously estimated. This is due to gene names being converted not just to dates and floating-point numbers, but also to internal date format (five-digit numbers). These findings further reinforce that spreadsheets are ill-suited to use with large genomic data.

Proangiogenic Effect of 2A-Peptide Based Multicistronic Recombinant Constructs Encoding VEGF and FGF2 Growth Factors.

Coronary artery disease remains one of the primary healthcare problems due to the high cost of treatment, increased number of patients, poor clinical outcomes, and lack of effective therapy. Though pharmacological and surgical treatments positively affect symptoms and arrest the disease progression, they generally exhibit a limited effect on the disease outcome. The development of alternative therapeutic approaches towards ischemic disease treatment, especially of decompensated forms, is therefore relevant. Therapeutic angiogenesis, stimulated by various cytokines, chemokines, and growth factors, provides the possibility of restoring functional blood flow in ischemic tissues, thereby ensuring the regeneration of the damaged area. In the current study, based on the clinically approved plasmid vector pVax1, multigenic constructs were developed encoding vascular endothelial growth factor (VEGF), fibroblast growth factors (FGF2), and the DsRed fluorescent protein, integrated via picornaviruses' furin-2A peptide sequences. In vitro experiments demonstrated that genetically modified cells with engineered plasmid constructs expressed the target proteins. Overexpression of VEGF and FGF2 resulted in increased levels of the recombinant proteins. Concomitantly, these did not lead to a significant shift in the general secretory profile of modified HEK293T cells. Simultaneously, the secretome of genetically modified cells showed significant stimulating effects on the formation of capillary-like structures by HUVEC (endothelial cells) in vitro. Our results revealed that when the multicistronic multigene vectors encoding 2A peptide sequences are created, transient transgene co-expression is ensured. The results obtained indicated the mutual synergistic effects of the growth factors VEGF and FGF2 on the proliferation of endothelial cells in vitro. Thus, recombinant multicistronic multigenic constructs might serve as a promising approach for establishing safe and effective systems to treat ischemic diseases.

Special Issue: A Tale of Genes and Genomes.

Variability is the source on which selective pressure acts, allowing genome evolution and adaptation [...].

The genetic architecture of age-related hearing impairment revealed by genome-wide association analysis.

Age-related hearing impairment (ARHI) is the most common sensory disorder in older adults. We conducted a genome-wide association meta-analysis of 121,934 ARHI cases and 591,699 controls from Iceland and the UK. We identified 21 novel sequence variants, of which 13 are rare, under either additive or recessive models. Of special interest are a missense variant in LOXHD1 (MAF = 1.96%) and a tandem duplication in FBF1 covering 4 exons (MAF = 0.22%) associating with ARHI (OR = 3.7 for homozygotes, P = 1.7 × 10-22 and OR = 4.2 for heterozygotes, P = 5.7 × 10-27, respectively). We constructed an ARHI genetic risk score (GRS) using common variants and showed that a common variant GRS can identify individuals at risk comparable to carriers of rare high penetrance variants. Furthermore, we found that ARHI and tinnitus share genetic causes. This study sheds a new light on the genetic architecture of ARHI, through several rare variants in both Mendelian deafness genes and genes not previously linked to hearing.

Genome-wide CRISPR screen identifies protein pathways modulating tau protein levels in neurons.

Aggregates of hyperphosphorylated tau protein are a pathological hallmark of more than 20 distinct neurodegenerative diseases, including Alzheimer's disease, progressive supranuclear palsy, and frontotemporal dementia. While the exact mechanism of tau aggregation is unknown, the accumulation of aggregates correlates with disease progression. Here we report a genome-wide CRISPR screen to identify modulators of endogenous tau protein for the first time. Primary screens performed in SH-SY5Y cells, identified positive and negative regulators of tau protein levels. Hit validation of the top 43 candidate genes was performed using Ngn2-induced human cortical excitatory neurons. Using this approach, genes and pathways involved in modulation of endogenous tau levels were identified, including chromatin modifying enzymes, neddylation and ubiquitin pathway members, and components of the mTOR pathway. TSC1, a critical component of the mTOR pathway, was further validated in vivo, demonstrating the relevance of this screening strategy. These findings may have implications for treating neurodegenerative diseases in the future.