BACKGROUND: Clinical exome sequencing (CES) provides a comprehensive and effective analysis of relevant disease-associated genes in a cost-effective manner compared to whole exome sequencing. Although several studies have focused on the diagnostic yield of CES, no study has assessed predictors of CES utility among patients with various Mendelian phenotypes. We assessed the effectiveness of CES as a first-level genetic test for molecular diagnosis in patients with a Mendelian phenotype and explored independent predictors of the clinical utility of CES. RESULTS: Between January 2016 and December 2019, 603 patients (426 probands and 177 siblings) underwent CES at the Department of Molecular Medicine of the University Hospital of Nancy. The median age of the probands was 34 years (IQR, 12-48), and the proportion of males was 46.9% (200/426). Adults and children represented 64.8% (276/426) and 35.2% (150/426), respectively. The median test-to-report time was 5.6 months (IQR, 4.1-7.2). CES revealed 203 pathogenic or likely pathogenic variants in 160 patients, corresponding to a diagnostic yield of 37.6% (160/426). Independent predictors of CES utility were criteria strongly suggestive of an extreme phenotype, including pediatric presentation and patient phenotypes associated with an increased risk of a priori probability of a monogenic disorder, the inclusion of at least one family member in addition to the proband, and a CES prescription performed by an expert in the field of rare genetic disorders. CONCLUSIONS: Based on a large dataset of consecutive patients with various Mendelian phenotypes referred for CES as a first-tier genetic test, we report a diagnostic yield of ~ 40% and several independent predictors of CES utility that might improve CES diagnostic efficiency.

BACKGROUND: Genetic variability in the cytochrome P450 CYP2C9 constitutes an important predictor for efficacy and safety of various commonly prescribed drugs, including coumarin anticoagulants, phenytoin and multiple non-steroidal anti-inflammatory drugs (NSAIDs). A global map of CYP2C9 variability and its inferred functional consequences has been lacking. RESULTS: Frequencies of eight functionally relevant CYP2C9 alleles (*2, *3, *5, *6, *8, *11, *13 and *14) were analyzed. In total, 108 original articles were identified that included genotype data from a total of 81,662 unrelated individuals across 70 countries and 40 unique ethnic groups. The results revealed that CYP2C9*2 was most abundant in Europe and the Middle East, whereas CYP2C9*3 was the main reason for reduced CYP2C9 activity across South Asia. Our data show extensive variation within superpopulations with up to tenfold differences between geographically adjacent populations in Malaysia, Thailand and Vietnam. Translation of genetic CYP2C9 variability into functional consequences indicates that up to 40% of patients in Southern Europe and the Middle East might benefit from warfarin and phenytoin dose reductions, while 3% of patients in Southern Europe and Israel are recommended to reduce starting doses of NSAIDs. CONCLUSIONS: This study provides a comprehensive map of the genetic and functional variability of CYP2C9 with high ethnogeographic resolution. The presented data can serve as a useful resource for CYP2C9 allele and phenotype frequencies and might guide the optimization of genotyping strategies, particularly for indigenous and founder populations with distinct genetic profiles.

The SPATA5 gene encodes a 892 amino-acids long protein that has a putative mitochondrial targeting sequence and has been proposed to function in maintenance of mitochondrial function and integrity during mouse spermatogenesis. Several studies have associated homozygous or compound heterozygous mutations in SPATA5 gene to microcephaly, intellectual disability, seizures and hearing loss. This suggests a role of the SPATA5 gene also in neuronal development. Recently, our group presented results validating the use of blood cells for the assessment of mitochondrial function for diagnosis and follow-up of mitochondrial disease, minimizing the need for invasive procedures such as muscle biopsy. In this study, we were able to diagnose a patient with epileptogenic encephalopathy using next generation sequencing. We found two novel compound heterozygous variants in SPATA5 that are most likely causative. To analyze the impact of SPATA5 mutations on mitochondrial functional studies directly on the patients' mononuclear cells and platelets were undertaken. Oxygen consumption rates in platelets and PBMCs were impaired in the patient when compared to a healthy control. Also, a decrease in mitochondrial mass was observed in the patient monocytes with respect to the control. This suggests a true pathogenic effect of the mutations in mitochondrial function, especially in energy production and possibly biogenesis, leading to the observed phenotype.

BACKGROUND: Therapy-related myeloid neoplasm (T-MN) rarely occurs among cancer survivors, and was characterized by poor prognosis. T-MN has germline predisposition in a considerable proportion. Here, clinical characteristics and germline/somatic variant profiles in T-MN patients were investigated, and the findings were compared with those of previous studies. METHODS: A review of medical records, cytogenetic study, targeted sequencing by next-generation sequencing, and survival analysis were performed on 53 patients with T-MN at a single institution in Korea. RESULTS: The patients were relatively younger compared to T-MN patients in other studies. Our T-MN patients showed a high frequency of complex karyotypes, -5/del(5q), and -7/del(7q), which was similar to the Japanese study group but higher than the Australian study group. The most common primary disease was non-Hodgkin lymphoma, followed by breast cancer. The detailed distributions of primary diseases were different across study groups. Seven patients (13.2%) harbored deleterious presumed/potential germline variants in cancer predisposition genes (CPG) such as BRIP1, CEBPA, DDX41, FANCM, NBN, NF1, and RUNX1. In the somatic variant profile, TP53 was the most frequently mutated gene, which was consistent with the previous studies about T-MN. However, the somatic variant frequency in our study group was lower than in other studies. Adverse factors for overall survival were male sex, older age, history of previous radiotherapy, previous longer cytotoxic therapy, and -5/del(5q). CONCLUSION: The findings of our study corroborate important information about T-MN patients. As well as a considerable predisposition to CPG, the clinical characteristics and somatic variant profile showed distinctive patterns. Germline variant testing should be recommended for T-MN patients. If the T-MN patients harbor pathogenic germline variants, the family members for stem cell donation should be screened for carrier status through germline variant testing to avoid donor-derived myeloid neoplasm. For the prediction of the prognosis in T-MN patients, sex, age, past treatment history, and cytogenetic findings can be considered.

BACKGROUND: Mutations in NF1 gene could cause allelic disorders with clinical spectrum of Neurofibromatosis type 1 to Noonan syndrome. Here, a 7-year-old Iranian girl is described with Neurofibromatosis-Noonan syndrome due to a pathogenic variant in NF1 gene. METHODS: Clinical evaluations were performed along with genetic testing using whole exome sequencing (WES). The variant analysis including pathogenicity prediction was also done using bioinformatics tools. RESULTS: The chief compliant of the patient was short stature and lack of proper weight gain. Other symptoms were developmental delay, learning disability, inadequate speech skill, broad forehead, hypertelorism, and epicanthal folds, low set ears and webbed neck. A small deletion, c.4375-4377delGAA, was found in NF1 gene using WES. This variant was classified as pathogenic according to ACMG. CONCLUSIONS: NF1 variants may show variable phenotypes among the patients; identifying such variants is helpful in therapeutic management of the disease. WES is considered as an appropriate test to diagnose Neurofibromatosis-Noonan syndrome.

BACKGROUND: Tuberous sclerosis complex (TSC) is an autosomal dominant disorder that is associated with neurological symptoms, including autism spectrum disorder. Tuberous sclerosis complex is caused by pathogenic germline mutations of either the TSC1 or TSC2 gene, but somatic mutations were identified in both genes, and the combined effects of TSC1 and TSC2 mutations have been unknown. METHODS: The present study investigated social behaviors by the social interaction test and three-chambered sociability tests, effects of rapamycin treatment, and gene expression profiles with a gene expression microarray in Tsc1 and Tsc2 double heterozygous mutant (TscD+/-) mice. RESULTS: TscD+/- mice exhibited impairments in social behaviors, and the severity of impairments was similar to Tsc2+/- mice rather than Tsc1+/- mice. Impairments in social behaviors were rescued by rapamycin treatment in all mutant mice. Gene expression profiles in the brain were greatly altered in TscD+/- mice more than in Tsc1+/- and Tsc2+/- mice. The gene expression changes compared with wild type (WT) mice were similar between TscD+/- and Tsc2+/- mice, and the overlapping genes whose expression was altered in mutant mice compared with WT mice were enriched in the neoplasm- and inflammation-related canonical pathways. The "signal transducer and activator of transcription 3, interferon regulatory factor 1, interferon regulatory factor 4, interleukin-2R α chain, and interferon-γ" signaling pathway, which is initiated from signal transducer and activator of transcription 4 and PDZ and LIM domain protein 2, was associated with impairments in social behaviors in all mutant mice. LIMITATIONS: It is unclear whether the signaling pathway also plays a critical role in autism spectrum disorders not caused by Tsc1 and Tsc2 mutations. CONCLUSIONS: These findings suggest that TSC1 and TSC2 double mutations cause autistic behaviors similarly to TSC2 mutations, although significant changes in gene expression were attributable to the double mutations. These findings contribute to the knowledge of genotype-phenotype correlations in TSC and suggest that mutations in both the TSC1 and TSC2 genes act in concert to cause neurological symptoms, including autism spectrum disorder.

BACKGROUND: While transcription factor (TF) regulation is known to play an important role in osteoblast development, differentiation, and bone metabolism, the molecular features of TFs in human osteoblasts at the single-cell resolution level have not yet been characterized. Here, we identified modules (regulons) of co-regulated genes by applying single-cell regulatory network inference and clustering to the single-cell RNA sequencing profiles of human osteoblasts. We also performed cell-specific network (CSN) analysis, reconstructed regulon activity-based osteoblast development trajectories, and validated the functions of important regulons both in vivo and in vitro. RESULTS: We identified four cell clusters: preosteoblast-S1, preosteoblast-S2, intermediate osteoblasts, and mature osteoblasts. CSN analysis results and regulon activity-based osteoblast development trajectories revealed cell development and functional state changes of osteoblasts. CREM and FOSL2 regulons were mainly active in preosteoblast-S1, FOXC2 regulons were mainly active in intermediate osteoblast, and RUNX2 and CREB3L1 regulons were most active in mature osteoblasts. CONCLUSIONS: This is the first study to describe the unique features of human osteoblasts in vivo based on cellular regulon active landscapes. Functional state changes of CREM, FOSL2, FOXC2, RUNX2, and CREB3L1 regulons regarding immunity, cell proliferation, and differentiation identified the important cell stages or subtypes that may be predominantly affected by bone metabolism disorders. These findings may lead to a deeper understanding of the mechanisms underlying bone metabolism and associated diseases.

BACKGROUND: Protein kinase C delta (PRKCD) and caspase recruitment domain family member 9 (CARD9) are genes involved in B and T cell activation, and cytokine production, which are vital mechanisms underlying autoimmune disease development. This study aimed to explore the association of the PRKCD and CARD9 genes with Vogt-Koyanagi-Harada disease (VKH) disease. The case-control study was performed to in 912 patients with VKH and 878 normal controls. MassARRAY system, SHEsis online platform, real-time PCR, and enzyme-linked immunosorbent assay were used to detect genotyping, haplotyping, mRNA expression, and cytokine levels, respectively. RESULTS: We found that rs74437127 C allele of PRKCD, rs3812555 CC genotype, and C allele of CARD9 were associated with increased susceptibility of VKH (Pc = 0.020, OR = 1.624; Pc = 2.04 × 10-5, OR = 1.810; Pc = 2.76 × 10-5, OR = 1.698, respectively). However, the rs74437127 T allele, and rs3812555 TC genotype and T allele were linked with decreased susceptibility to VKH (Pc = 0.020, OR = 0.616; Pc = 7.85 × 10-5, OR = 0.559; Pc = 2.76 × 10-5, OR = 0.589, respectively). PRKCD ATG and CARD9 GCTTA haplotypes decreased susceptibility to VKH (Pc = 3.11 × 10-3, OR = 0.594; Pc = 5.00 × 10-3, OR = 0.639, respectively). Functional studies on rs3812555 genotyped individuals revealed that CC carriers had significantly higher CARD9 mRNA expression and tumour necrosis factor-α production than TC/TT carriers (P = 1.00 × 10-4; P = 2.00 × 10-3, respectively). CONCLUSIONS: We found an association between PRKCD rs74437127 and CARD9 rs3812555 polymorphisms and VKH susceptibility and revealed that the increased susceptibility of rs3812555 for VKH may be mediated by regulating CARD9 gene expression and the production of pro-inflammatory cytokines, such as TNF-α.

PURPOSE: Inherited kidney diseases are among the leading causes of kidney failure in children, resulting in increased mortality, high healthcare costs and need for organ transplantation. Next-generation sequencing technologies can help in the diagnosis of rare monogenic conditions, allowing for optimized medical management and therapeutic choices. METHODS: Clinical exome sequencing (CES) was performed on a cohort of 191 pediatric patients from a single institution, followed by Sanger sequencing to confirm identified variants and for family segregation studies. RESULTS: All patients had a clinical diagnosis of kidney disease: the main disease categories were glomerular diseases (32.5%), ciliopathies (20.4%), CAKUT (17.8%), nephrolithiasis (11.5%) and tubular disease (10.5%). 7.3% of patients presented with other conditions. A conclusive genetic test, based on CES and Sanger validation, was obtained in 37.1% of patients. The highest detection rate was obtained for ciliopathies (74.4%), followed by nephrolithiasis (45.5%), tubular diseases (45%), while most glomerular diseases and CAKUT remained undiagnosed. CONCLUSIONS: Results indicate that genetic testing consistently used in the diagnostic workflow of children with chronic kidney disease can (i) confirm clinical diagnosis, (ii) provide early diagnosis in the case of inherited conditions, (iii) find the genetic cause of previously unrecognized diseases and (iv) tailor transplantation programs.

BACKGROUND: Aging affects the incidence of diseases such as cancer and dementia, so the development of biomarkers for aging is an important research topic in medical science. While such biomarkers have been mainly identified based on the assumption of a linear relationship between phenotypic parameters, including molecular markers, and chronological age, numerous nonlinear changes between markers and aging have been identified. However, the overall landscape of the patterns in nonlinear changes that exist in aging is unknown. RESULT: We propose a novel computational method, Data-driven Identification and Classification of Nonlinear Aging Patterns (DICNAP), that is based on functional data analysis to identify biomarkers for aging and potential patterns of change during aging in a data-driven manner. We applied the proposed method to large-scale, public DNA methylation data to explore the potential patterns of age-related changes in methylation intensity. The results showed that not only linear, but also nonlinear changes in DNA methylation patterns exist. A monotonous demethylation pattern during aging, with its rate decreasing at around age 60, was identified as the candidate stable nonlinear pattern. We also analyzed the age-related changes in methylation variability. The results showed that the variability of methylation intensity tends to increase with age at age-associated sites. The representative variability pattern is a monotonically increasing pattern that accelerates after middle age. CONCLUSION: DICNAP was able to identify the potential patterns of the changes in the landscape of DNA methylation during aging. It contributes to an improvement in our theoretical understanding of the aging process.

SpliceAI is an open-source deep learning splicing prediction algorithm that has demonstrated in the past few years its high ability to predict splicing defects caused by DNA variations. However, its outputs present several drawbacks: (1) although the numerical values are very convenient for batch filtering, their precise interpretation can be difficult, (2) the outputs are delta scores which can sometimes mask a severe consequence, and (3) complex delins are most often not handled. We present here SpliceAI-visual, a free online tool based on the SpliceAI algorithm, and show how it complements the traditional SpliceAI analysis. First, SpliceAI-visual manipulates raw scores and not delta scores, as the latter can be misleading in certain circumstances. Second, the outcome of SpliceAI-visual is user-friendly thanks to the graphical presentation. Third, SpliceAI-visual is currently one of the only SpliceAI-derived implementations able to annotate complex variants (e.g., complex delins). We report here the benefits of using SpliceAI-visual and demonstrate its relevance in the assessment/modulation of the PVS1 classification criteria. We also show how SpliceAI-visual can elucidate several complex splicing defects taken from the literature but also from unpublished cases. SpliceAI-visual is available as a Google Colab notebook and has also been fully integrated in a free online variant interpretation tool, MobiDetails ( https://mobidetails.iurc.montp.inserm.fr/MD ).

BACKGROUND: RNA methylation is a widely known post-transcriptional regulation which exists in many cancer and immune system diseases. However, the potential role and crosstalk of five types RNA methylation regulators in diabetic nephropathy (DN) and immune microenvironment remain unclear. METHODS: The mRNA expression of 37 RNA modification regulators and RNA modification regulators related genes were identified in 112 samples from 5 Gene Expression Omnibus datasets. Nonnegative Matrix Factorization clustering method was performed to determine RNA modification patterns. The ssGSEA algorithms and the expression of human leukocyte antigen were employed to assess the immune microenvironment characteristics. Risk model based on differentially expression genes responsible for the modification regulators was constructed to evaluate its predictive capability in DN patients. Furthermore, the results were validated by using immunofluorescence co-localizations and protein experiments in vitro. RESULTS: We found 24 RNA methylation regulators were significant differently expressed in glomeruli in DN group compared with control group. Four methylation-related genes and six RNA regulators were introduced into riskScore model using univariate Logistic regression and integrated LASSO regression, which could precisely distinguish the DN and healthy individuals. Group with high-risk score was associated with high immune infiltration. Three distinct RNA modification patterns were identified, which has significant differences in immune microenvironment, biological pathway and eGFR. Validation analyses showed the METTL3, ADAR1, DNMT1 were upregulated whereas YTHDC1 was downregulated in DN podocyte cell lines comparing with cells cultured by the normal glucose. CONCLUSION: Our study reveals that RNA methylation regulators and immune infiltration regulation play critical roles in the pathogenesis of DN. The bioinformatic analyses combine with verification in vitro could provide robust evidence for identification of predictive RNA methylation regulators in DN.