The ExAC browser: displaying reference data information from over 60 000 exomes

LIMK1 variants are associated with divergent endocrinological phenotypes and altered exocytosis dynamics

LIM kinase 1 (LIMK1) plays a pivotal role in dynamic actin remodeling through phosphorylation of cofilin, thereby regulating exocytosis. We report two individuals harboring LIMK1 de novo variants with dissimilar phenotypes: one exhibited epileptic encephalopathy and developmental delay, while the other showed common variable immune deficiency and glucose dysregulation. We suspected that the divergent phenotypic features arose from opposing effects on LIMK1 activity. Indeed, actin polymerization was significantly decreased in individual 1, whereas it was increased in individual 2. Insulin-secreting cell lines expressing the LIMK1 variant of individual 1 exhibited significantly slower exocytosis, contrasting the rapid and uncontrolled exocytosis in individual 2. Intriguingly, both variants led to increased overall insulin secretion. This first report of two individuals with LIMK1 variants with divergent effects on cofilin phosphorylation and actin polymerization, reveals that LIMK1 has an important role in tuned insulin exocytosis. These distinct exocytosis defects may underlie the glucose dysregulation observed.

Genetic variations and recurrence in stage III Korean colorectal cancer: Insights from tumor-only mutation analysis

Colorectal cancer (CRC) has the second highest incidence rate among all cancers in Korea, with approximately 30% of patients with regional CRC experiencing recurrence. Understanding the genetic drivers of recurrence is essential for early detection and targeted treatment. Therefore, many studies have focused on genetic analysis using tumor-normal matched samples, as this approach provides more comprehensive insights. However, tumor-only samples are far more common in clinical practice because of the difficulty in obtaining normal tissues, making developing robust methods for analyzing tumor-only data a pressing need. This study aimed to investigate the genetic variations associated with CRC recurrence using tumor-only whole-exome sequencing data from 200 Korean patients with stage III CRC. By applying stringent filtering using public databases including Genome Aggregation Database (gnomAD), Exome Aggregation Consortium (ExAC), Single Nucleotide Polymorphism Database (dbSNP), 1000 Genomes Project (1000G), Korean Variant Archive 2 (KOVA2), and Korean Reference Genome Database (KRGDB), we identified 221 statistically significant mutations across 195 genes with distinct distributions between the recurrence and non-recurrence groups. Furthermore, statistical analysis of the clinical data revealed that the T-category, N-category, and preoperative carcinoembryonic antigen levels were correlated with CRC recurrence. Moreover, we identified nine networks through protein-protein interaction analysis and identified networks with high feature importance. We also developed a CRC recurrence prediction model using PyCaret, which achieved an area under the curve (AUC) of 0.77. Our findings highlight the importance of robust variant filtering in tumor-only sample analyses and provide insights into the genetic landscape of CRC recurrence in the Korean population.

Clinical Bioinformatician Body of Knowledge-Bioinformatics and Software Core: A Report of the Association for Molecular Pathology

With the evolution of next-generation sequencing-based testing in molecular diagnostics laboratories, the clinical role of bioinformaticians has also evolved. The Association for Molecular Pathology's Clinical Bioinformatician Body of Knowledge aims to define the various roles the clinical bioinformatician operates individually or within a clinical bioinformatics team, along with proficiencies and skill sets that may be required or desirable across these roles. One of the most common professional responsibilities of a clinical bioinformatician is to implement bioinformatics pipelines, either vendor supplied or custom built for the assays in the molecular diagnostics laboratory, along with analysis and quality control of clinical genomics data. This second article in the series describes the various stages in the life cycle of a clinical bioinformatics pipeline and the considerations, areas of expertise, and skill sets required in each stage. This information may help laboratory professionals to better work with clinical bioinformaticians and laboratory directors to hire the appropriate expertise based on the specific needs of the laboratory.

Effect of newborn genomic screening for lysosomal storage disorders: a cohort study in China

BACKGROUND

Lysosomal storage disorders (LSDs) have a relatively high incidence among rare diseases and can lead to severe consequences if not treated promptly. However, many countries and regions have not included these disorders in their newborn screening programs, resulting in missed early detection, underdiagnosis, and delayed treatment. Newborn genomic screening (NBGS) has shown good screening effectiveness for traditional biochemical screening diseases; however, its effectiveness for LSDs has not yet been evaluated in the general newborn population.

METHODS

To evaluate the outcome of NBGS for LSDs, a cohort study was conducted involving newborns recruited from Nanjing Women and Children's Healthcare Hospital in China from March 18, 2022, to September 21, 2023. All participants underwent NBGS of 15 LSDs (18 genes) via dried blood spots, followed by enzyme activity testing for NBGS-positive individuals. The study calculated the incidence and carrier rates for each LSD though NBGS, as well as the positive screening rate, the false positive rate and the positive predictive value of the screening process.

RESULTS

Among 22,687 newborns (11,996 males [52.88%]), 1344 (6.0%) were identified as carriers, and 30 (0.13%) were initially positive for LSDs. Of these, 4 were excluded, 15 were diagnosed as LSD-presymptomatic individuals based on enzyme deficiency and pathogenic variants conforming to inheritance patterns, and 11 remain under follow-up. The estimated combined birth incidence of LSDs in Nanjing was 1/1512, primarily including Fabry disease, Krabbe disease, glycogen storage disease type II, Niemann-Pick disease, and mucopolysaccharidosis type II. Rather than directly comparing NBGS and enzyme activity screening, this study evaluated two sequential screening strategies: (1) NBGS-first with reflex enzyme testing and (2) enzyme activity-first with reflex genomic testing. The NBGS-first strategy demonstrated higher sensitivity and specificity, with a significantly lower false positive rate and higher positive predictive values compared to the enzyme-first strategy (P < 0.05).

CONCLUSIONS

This study highlights the potential of NBGS to enhance early detection of presymptomatic LSD individuals, enabling timely interventions and improving newborn health outcomes. Integrating NBGS into routine newborn screening programs could provide an effective and proactive approach for LSD identification and management.

Reporting Criteria for Prenatally Identified Variants of Uncertain Significance Differs Among Cytogenetics Laboratories in North America

OBJECTIVE

Current technical standards for chromosomal microarray (CMA) interpretation are not prescriptive for reporting variants of uncertain significance (VUS) identified prenatally. We sought to compare prenatal CMA reporting among cytogenetic labs and identify potential drivers of practice variation.

METHODS

We conducted an electronic cross-sectional survey of cytogeneticists in the United States and Canada from July-December 2023. Participants were identified through the American Cytogenetics Forum List.

RESULTS

Labs reported differences in their size threshold used when reporting CNVs lacking OMIM annotated genes as a VUS, variable use of clinical data such as ultrasound or family history when deciding to report a VUS, and differences in opinion regarding the underlying pathogenicity of certain CNVs. Many cytogeneticists reported concerns about legal liability related to prenatal CMA reporting, and many shared concerns that a patient may terminate a pregnancy based on a VUS.

CONCLUSION

Reporting criteria for prenatally identified variants of uncertain significance differs among cytogenetic laboratories in North America. Many possible drivers of this practice variation were identified, including a lack of national guidelines that comprehensively address the unique considerations for prenatal CMA reporting.

Flores S, Esquivel E, Ding Y, Peitzsch M, Robles-Guirado JÁ, Regojo Zapata RM, Pozo-Kreilinger JJ, Iglesias C, Dwight T, Muir CA, Oleaga A, Garrido-Lestache Rodríguez-Monte ME, Del Cerro MJ, Martínez-Bendayán I, Álvarez-González E, Cubiella T, Lourenço DM, A. Pereira MA, Burnichon N, Buffet A, Broberg C, Dickson PV, Fraga MF, Llorente Pendás JL, Rueda Soriano J, Buendía Fuentes F, Toledo SP, Clifton-Bligh R, Dienstmann R, Villanueva J, Capdevila J, Gimenez-Roqueplo AP, Favier J, Nuciforo P, Young WF, Bechmann N, Opotowsky AR, Vaidya A, Bancos I, Weghorn D, Robledo M, Casteràs A, Dos-Subirà L, Adameyko I, Chiara MD, Dahia PL, Toledo RA. Convergent Genetic Adaptation in Human Tumors Developed Under Systemic Hypoxia and in Populations Living at High Altitudes

SIGNIFICANCE

This study reveals a broad convergence in genetic adaptation to hypoxia between natural populations and tumors, suggesting that insights from natural populations could enhance our understanding of cancer biology and identify novel therapeutic targets. See related commentary by Lee, p. 875.

Exploring pharmacogenetic factors influencing hydroxyurea response in tanzanian sickle cell disease patients: a genomic medicine approach

In sub-Saharan Africa, sickle cell disease (SCD) remains a significant public health challenge. Despite the discovery of SCD over a century ago, progress in developing and accessing effective treatments has been limited. Hydroxyurea is the primary drug used for managing SCD and associated with improving clinical outcomes. However, up to 30% of patients do not respond to hydroxyurea, likely due to genetic factors. This study involved 148 individuals with SCD investigated the association of hydroxyurea response with genetic variants across 13 loci associated with HbF synthesis and drug metabolism, focusing on MYB, HBB, HBG1, HBG2, BCL11A, KLF10, HAO2, NOS1, ARG2, SAR1A, CYP2C9, and CYP2E1. Significant associations with hydroxyurea response were identified in CYP2C9, CYP2E1, KLF10, BCL11A, ARG2, HBG1, SAR1A, MYB, and NOS1 loci. Furthermore, pathway enrichment and gene-gene interaction analyses provide deeper insights into the genetic mechanisms underlying hydroxyurea treatment response, highlighting potential avenues for personalized therapy in SCD management.

Genomic Insights into Oral Cancer Highlight Mutant SIGMAR1 as a Critical Target to Overcome Chemoresistance

Oral cancer (OC) is a highly aggressive malignancy characterized by uncontrolled cell proliferation in the oral cavity. Recent studies have highlighted the role of Sigma-1 receptor (SIGMAR1) mutations in cancer progression, disrupting cellular homeostasis, altering gene and protein expression, and promoting drug resistance. However, its role in OC remains scarce. This study investigated SIGMAR1 mutations, expression profiles, and their potential link to drug resistance in OC. Using 2008 OC samples from the TCGA Pan-Cancer Atlas, we identified SIGMAR1 genetic alterations in 4% of cases, including missense mutations, deletions, and amplifications. In the HN13 OC cell line, Sanger sequencing revealed a novel heterozygous Asp-to-Gly (c.585C > G) missense mutation. Quantitative RT-PCR and Western blot analyses showed SIGMAR1 overexpression in HN13 cells compared to non-tumor oral keratinocytes (NOK-SI). Silencing SIGMAR1 increased HN13 cell sensitivity to cisplatin, indicating its role in drug resistance. This study is the first to report the c.585C > G mutation in SIGMAR1 and demonstrate its contribution to cisplatin resistance, a major chemotherapy challenge to OC treatment. These findings highlight SIGMAR1's critical role in OC pathogenesis and its potential as a therapeutic target to overcome chemoresistance. The results also pave the way for future research into RNA-based therapies and precision oncology interventions.

Structure of human MUTYH and functional profiling of cancer-associated variants reveal an allosteric network between its [4Fe-4S] cluster cofactor and active site required for DNA repair

MUTYH is a clinically important DNA glycosylase that thwarts mutations by initiating base-excision repair at 8-oxoguanine (OG):A lesions. The roles for its [4Fe-4S] cofactor in DNA repair remain enigmatic. Functional profiling of cancer-associated variants near the [4Fe-4S] cofactor reveals that most variations abrogate both retention of the cofactor and enzyme activity. Surprisingly, R241Q and N238S retained the metal cluster and bound substrate DNA tightly, but were completely inactive. We determine the crystal structure of human MUTYH bound to a transition state mimic and this shows that Arg241 and Asn238 build an H-bond network connecting the [4Fe-4S] cluster to the catalytic Asp236 that mediates base excision. The structure of the bacterial MutY variant R149Q, along with molecular dynamics simulations of the human enzyme, support a model in which the cofactor functions to position and activate the catalytic Asp. These results suggest that allosteric cross-talk between the DNA binding [4Fe-4S] cofactor and the base excision site of MUTYH regulate its DNA repair function.

A genetically informed brain atlas for enhancing brain imaging genomics

Brain imaging genomics has manifested considerable potential in illuminating the genetic determinants of human brain structure and function. This has propelled us to develop the GIANT (Genetically Informed brAiN aTlas) that accounts for genetic and neuroanatomical variations simultaneously. Integrating voxel-wise heritability and spatial proximity, GIANT clusters brain voxels into genetically informed regions, while retaining fundamental anatomical knowledge. Compared to conventional (non-genetics) brain atlases, GIANT exhibits smaller intra-region variations and larger inter-region variations in terms of voxel-wise heritability. As a result, GIANT yields increased regional SNP heritability, enhanced polygenicity, and its polygenic risk score explains more brain volumetric variation than traditional neuroanatomical brain atlases. We provide extensive validation to GIANT and demonstrate its neuroanatomical validity, confirming its generalizability across populations with diverse genetic ancestries and various brain conditions. Furthermore, we present a comprehensive genetic architecture of the GIANT regions, covering their functional annotation at the molecular levels, their associations with other complex traits/diseases, and the genetic and phenotypic correlations among GIANT-defined imaging endophenotypes. In summary, GIANT constitutes a brain atlas that captures the complexity of genetic and neuroanatomical heterogeneity, thereby enhancing the discovery power and applicability of imaging genomics investigations in biomedical science.

DTreePred: an online viewer based on machine learning for pathogenicity prediction of genomic variants

BACKGROUND

A significant challenge in precision medicine is confidently identifying mutations detected in sequencing processes that play roles in disease treatment or diagnosis. Furthermore, the lack of representativeness of single nucleotide variants in public databases and low sequencing rates in underrepresented populations pose defies, with many pathogenic mutations still awaiting discovery. Mutational pathogenicity predictors have gained relevance as supportive tools in medical decision-making. However, significant disagreement among different tools regarding pathogenicity identification is rooted, necessitating manual verification to confirm mutation effects accurately.

RESULTS

This article presents a cross-platform mobile application, DTreePred, an online visualization tool for assessing the pathogenicity of nucleotide variants. DTreePred utilizes a machine learning-based pathogenicity model, including a decision tree algorithm and 15 machine learning classifiers alongside classical predictors. Connecting public databases with diverse prediction algorithms streamlines variant analysis, whereas the decision tree algorithm enhances the accuracy and reliability of variant pathogenicity data. This integration of information from various sources and prediction techniques aims to serve as a functional guide for decision-making in clinical practice. In addition, we tested DTreePred in a case study involving a cohort from Rio Grande do Norte, Brazil. By categorizing nucleotide variants from the list of oncogenes and suppressor genes classified in ClinVar as inexact data, DTreePred successfully revealed the pathogenicity of more than 95% of the nucleotide variants. Furthermore, an integrity test with 200 known mutations yielded an accuracy of 97%, surpassing rates expected from previous models.

CONCLUSIONS

DTreePred offers a robust solution for reducing uncertainty in clinical decision-making regarding pathogenic variants. Improving the accuracy of pathogenicity assessments has the potential to significantly increase the precision of medical diagnoses and treatments, particularly for underrepresented populations.

Whole-genome sequencing reveals the impact of lipid pathway and APOE genotype on brain amyloidosis

Amyloid-PET imaging tracks the accumulation of amyloid beta (Aβ) deposits in the brain. Amyloid plaques accumulation may begin 10 to 20 years before the individual experiences clinical symptoms associated with Alzheimer's diseases (ad). Recent large-scale genome-wide association studies reported common risk factors associated with brain amyloidosis, suggesting that this endophenotype is driven by genetic variants. However, these loci pinpoint to large genomic regions and the functional variants remain to be identified. To identify new risk factors associated with brain amyloid deposition, we performed whole-genome sequencing on a large cohort of European descent individuals with amyloid PET imaging data (n = 1,888). Gene-based analysis for coding variants was performed using SKAT-O for amyloid PET as a quantitative endophenotype that identified genome-wide significant association for APOE (P = 2.45 × 10-10), and 26 new candidate genes with suggestive significance association (P < 5. 0 × 10-03) including SCN7A (P = 7.31 × 10-05), SH3GL1 (P = 7.56 × 10-04), and MFSD12 (P = 8.51 × 10-04). Enrichment analysis highlighted the lipid binding pathways as associated with Aβ deposition in brain driven by PITPNM3 (P = 4.27 × 10-03), APOE (P = 2.45 × 10-10), AP2A2 (P = 1.06 × 10-03), and SH3GL1 (P = 7.56 × 10-04). Overall, our data strongly support a connection between lipid metabolism and the deposition of Aβ in the brain. Our study illuminates promising avenues for therapeutic interventions targeting lipid metabolism to address brain amyloidosis.

Genome-wide functional annotation of variants: a systematic review of state-of-the-art tools, techniques and resources

The recent advancement of sequencing technologies marks a significant shift in the character and complexity of the digital genomic data universe, encompassing diverse types of molecular data, screened through manifold technological platforms. As a result, a plethora of fully assembled genomes are generated that span vertically the evolutionary scale. Notwithstanding the tsunami of thriving innovations that accomplish unprecedented, nucleotide-level, structural and functional annotation, an exhaustive, systemic, massive genome-wide functional annotation remains elusive, particularly when the criterion is automation and efficiency in data-agnostic interpretation. The latter is of paramount importance for the elaboration of strategies for sophisticated, data-driven genome-wide annotation, which aim to impart a sustainable and comprehensive systemic approach to addressing whole genome variation. Therefore, it is essential to develop methods and tools that promote systematic functional genomic annotation, with emphasis on mechanistic information exceeding the limits of coding regions, and exploiting the chunks of pertinent information residing in non-coding regions, including promoter and enhancer sequences, non-coding RNAs, DNA methylation sites, transcription factor binding sites, transposable elements and more. This review provides an overview of the current state-of-the-art in genome-wide functional annotation of genetic variation, including existing bioinformatic tools, resources, databases and platforms currently available or reported in the literature. Particular emphasis is placed on the functional annotation of variants that lie outside protein-coding genomic regions (intronic or intergenic), their potential co-localization with regulatory element areas, such as putative non-coding RNA regions, and the assessment of their functional impact on the investigated phenotype. In addition, state-of-the-art tools that leverage data obtained from WGS and GWAS-based analyses are discussed, along with future bioinformatics directions and developments. These future directions emphasize efficient, comprehensive, and largely automated functional annotation of both coding and non-coding genomic variants, as well as their optimal evaluation.

Generation of prostate cancer assembloids modeling the patient-specific tumor microenvironment

Prostate cancer (PC) is the most frequently diagnosed malignancy among men and contributes significantly to cancer-related mortality. While recent advances in in vitro PC modeling systems have been made, there remains a lack of robust preclinical models that faithfully recapitulate the genetic and phenotypic characteristics across various PC subtypes-from localized PC (LPC) to castration-resistant PC (CRPC)-along with associated stromal cells. Here, we established human PC assembloids from LPC and CRPC tissues by reconstituting tumor organoids with corresponding cancer-associated fibroblasts (CAFs), thereby incorporating aspects of the tumor microenvironment (TME). Established PC organoids exhibited high concordance in genomic landscape with parental tumors, and the tumor assembloids showed a higher degree of phenotypic similarity to parental tumors compared to tumor organoids without CAFs. PC assembloids displayed increased proliferation and reduced sensitivity to anti-cancer treatments, indicating that PC assembloids are potent tools for understanding PC biology, investigating the interaction between tumor and CAFs, and identifying personalized therapeutic targets.

PTEN mutations impair CSF dynamics and cortical networks by dysregulating periventricular neural progenitors

Enlargement of the cerebrospinal fluid (CSF)-filled brain ventricles (ventriculomegaly) is a defining feature of congenital hydrocephalus (CH) and an under-recognized concomitant of autism. Here, we show that de novo mutations in the autism risk gene PTEN are among the most frequent monogenic causes of CH and primary ventriculomegaly. Mouse Pten-mutant ventriculomegaly results from aqueductal stenosis due to hyperproliferation of periventricular Nkx2.1+ neural progenitor cells (NPCs) and increased CSF production from hyperplastic choroid plexus. Pten-mutant ventriculomegalic cortices exhibit network dysfunction from increased activity of Nkx2.1+ NPC-derived inhibitory interneurons. Raptor deletion or postnatal everolimus treatment corrects ventriculomegaly, rescues cortical deficits and increases survival by antagonizing mTORC1-dependent Nkx2.1+ NPC pathology. Thus, PTEN mutations concurrently alter CSF dynamics and cortical networks by dysregulating Nkx2.1+ NPCs. These results implicate a nonsurgical treatment for CH, demonstrate a genetic association of ventriculomegaly and ASD, and help explain neurodevelopmental phenotypes refractory to CSF shunting in select individuals with CH.

RAB32 Ser71Arg in Chinese patients with Parkinson's disease

BACKGROUND

The RAB32 Ser71Arg variant has been identified as a novel risk locus for Parkinson's disease (PD) in North American, European and North African populations. However, its pathogenicity in Asian populations remains unclear.

METHOD

To investigate this, we screened for the RAB32 c.213C > G (Ser71Arg) variant using Sanger sequencing in 1,099 PD patients and 1,549 controls. And we search for the RAB32 Ser71Arg variant in public databases to identified its mutant frequency.

RESULTS

Our results show that no individuals carrying the RAB32 Ser71Arg variant were identified in our cohort. Additionally, this variant rarely appears in Asian population databases.

CONCLUSION

Our findings suggest that the RAB32 Ser71Arg variant is unlikely to be a risk locus for PD in Chinese patients, which is potentially attributed to racial or ethnic differences.

Identification of a novel single nucleotide deletion in the NHS causing Nance-Horan syndrome

BACKGROUND

Nance-Horan syndrome (NHS) is a rare X-linked dominant disorder caused by pathogenic variants in the NHS gene on chromosome Xp22.2-Xp22.13. Clinical manifestations consist of congenital cataracts, along with dysmorphic facial features and dental anomalies and, in certain instances, intellectual disability. This study aimed to identify the genetic cause responsible for NHS in a Chinese family with four individuals primarily presenting with congenital cataracts.

METHODS

Genomic DNA was collected from six family members, including four affected individuals (three females and one male) from a two-generation family. The family history and clinical data were documented. Whole-exome sequencing was performed on the proband, and candidate pathogenic variants were filtered through a series of screening steps and validated by Sanger sequencing. Co-segregation analysis was conducted to confirm the pathogenicity of the identified variant.

RESULTS

Genetic analysis revealed a novel frameshift pathogenic variant in NHS gene (c.1735delA: p.R579Gfs*91) present in all four affected members. All affected members exhibited congenital cataracts, congenital ptosis, strabismus, high myopia as well as dental and facial anomalies, and more severe characteristic features observed in the male patient. These clinical manifestations were consistent with the phenotype of NHS.

CONCLUSION

This study identified a novel NHS pathogenic variant in a Chinese family, expanding the mutational spectrum of NHS. Contrary to previous reports of female carriers exhibiting mild symptoms, we demonstrated severe ocular phenotypes in three affected females. These findings will assist in providing genetic counseling for NHS patients.

DICER1 in pediatric and adult cancer predisposition populations: Prevalence, phenotypes, and mosaicism

PURPOSE

DICER1 tumor predisposition syndrome (DTPS) is a hereditary condition affecting children and young adults. Identification of DICER1 carriers is key for prevention and actionability in families. However, DTPS diagnosis is hindered by its incomplete penetrance and broad phenotypic spectrum.

METHODS

We performed an analysis of DICER1 sequencing data from 92 children and 6108 adults with suspected cancer predisposition syndrome. Clinical and DICER1 somatic data from selected carriers and public data sets were studied.

RESULTS

The prevalence of germline DICER1 pathogenic variants was 1:30 in children and 1:3054 in adults. No adult referral phenotype was a known DTPS-associated tumor, although 3 of 5 carriers developed thyroid alterations. We provide functional evidence supporting the pathogenicity of a novel in-frame deletion. A 56-year-old woman with ovarian carcinoma and toxic diffuse thyroid hyperplasia was found to have a postzygotic hotspot missense variant.

CONCLUSION

The prevalence of DICER1 pathogenic variants in cancer predisposition populations was 5 to 6 times that reported in the general population. Pediatric-onset DTPS is well characterized, whereas adult carriers mainly present with thyroid abnormalities in the absence of DICER1-related family history, thus requiring accurate criteria for its identification when in constellation with other tumor types. Postzygotic hotspot missense variants may exist without the expected severe phenotype.

Antisense oligonucleotide-mediated MSH3 suppression reduces somatic CAG repeat expansion in Huntington's disease iPSC-derived striatal neurons

Expanded CAG alleles in the huntingtin (HTT) gene that cause the neurodegenerative disorder Huntington's disease (HD) are genetically unstable and continue to expand somatically throughout life, driving HD onset and progression. MSH3, a DNA mismatch repair protein, modifies HD onset and progression by driving this somatic CAG repeat expansion process. MSH3 is relatively tolerant of loss-of-function variation in humans, making it a potential therapeutic target. Here, we show that an MSH3-targeting antisense oligonucleotide (ASO) effectively engaged with its RNA target in induced pluripotent stem cell (iPSC)-derived striatal neurons obtained from a patient with HD carrying 125 HTT CAG repeats (the 125 CAG iPSC line). ASO treatment led to a dose-dependent reduction of MSH3 and subsequent stalling of CAG repeat expansion in these striatal neurons. Bulk RNA sequencing revealed a safe profile for MSH3 reduction, even when reduced by >95%. Maximal knockdown of MSH3 also effectively slowed CAG repeat expansion in striatal neurons with an otherwise accelerated expansion rate, derived from the 125 CAG iPSC line where FAN1 was knocked out by CRISPR-Cas9 editing. Last, we created a knock-in mouse model expressing the human MSH3 gene and demonstrated effective in vivo reduction in human MSH3 after ASO treatment. Our study shows that ASO-mediated MSH3 reduction can prevent HTT CAG repeat expansion in HD 125 CAG iPSC-derived striatal neurons, highlighting the therapeutic potential of this approach.

A novel frameshift mutation in the DIAPH1 gene causes a Chinese family autosomal dominant nonsyndromic hearing loss: Mutation in DIAPH1 causes hearing loss

OBJECTIVE

This study reports a novel heterozygous, likely truncating mutation in the diaphanous homolog 1 (DIAPH1) gene associated with non-syndromic hearing loss.

METHODS

Family members underwent audiological and imaging assessments, whole-exome sequencing (WES), and Sanger sequencing.

RESULTS

Sensorineural hearing loss was observed in all five individuals, with severity ranging from mild to severe. None of the affected patients reported vestibular complaints, and routine blood tests showed normal platelet counts. Whole-exome sequencing (WES) revealed a novel frameshift variation, c.3555delA (p.Gln1185Hisfs*3), in exon 26 of the DIAPH1 gene. This variation co-segregated with the hearing-impaired phenotype in the family. The data collected support the classification of c.3555delA as a genetic etiology of hereditary hearing loss according to the American College of Medical Genetics and Genomics guidelines.

CONCLUSION

We identified a novel pathogenic mutation in the DIAPH1 gene, thereby expanding the mutation spectrum associated with hearing loss.

Rare variants in cardiomyopathy genes predispose to cardiac injury in severe COVID-19 patients of African or Hispanic ancestry

In one of the earliest reports from China during COVID-19, it was noted that over 20% of patients hospitalized with the disease had significant elevations of troponin, a marker of myocardial tissue damage, that put them at a higher risk. In a hypothesis-independent whole exome sequencing (WES) study in hospitalized COVID-19 patients of diverse ancestry, we observed putative enrichment in pathogenic variants in genes known to be involved in the pathogenesis of cardiomyopathy. This observation led us to hypothesize that the observed high morbidity and mortality in these patients might be due to the presence of rare genetic factors that had previously been silent but became relevant as a consequence of the severe stress inflicted by an infection with SARS-CoV-2. To test this hypothesis, we analyzed our WES data generated from a cohort of 325 patients sequentially admitted for COVID-19 infection. In this predominantly minority population (53.9% African ancestry and 37.9% Hispanic/Latin ancestry), our initial analysis screen identified 263 variants that were identified as highly deleterious (HD) from a total of 26,661 variants of interest that represented 215 genes. Of those, we identified 46 genes (in 58 patients) harboring rare HD coding variants that were previously implicated in dilated cardiomyopathy and were considered as disease initiators for the severe COVID-19 in this study. These findings offer valuable insights into the molecular mechanisms and genetic susceptibility to heart injury in severe COVID-19. KEY MESSAGES: COVID-19 may cause cardiac damage in some affected patients without a plausible biological explanation. Our study reveals an enrichment of highly deleterious variants linked to cardiomyopathy in severe COVID-19 patients. Genetic profiling unveils the molecular basis of severe COVID-19-related heart injury, potentially aiding in patient stratification.

GoFCards: an integrated database and analytic platform for gain of function variants in humans

Gain-of-function (GOF) variants, which introduce new or amplify protein functions, are essential for understanding disease mechanisms. Despite advances in genomics and functional research, identifying and analyzing pathogenic GOF variants remains challenging owing to fragmented data and database limitations, underscoring the difficulty in accessing critical genetic information. To address this challenge, we manually reviewed the literature, pinpointing 3089 single-nucleotide variants and 72 insertions and deletions in 579 genes associated with 1299 diseases from 2069 studies, and integrated these with the 3.5 million predicted GOF variants. Our approach is complemented by a proprietary scoring system that prioritizes GOF variants on the basis of the evidence supporting their GOF effects and provides predictive scores for variants that lack existing documentation. We then developed a database named GoFCards for general geneticists and clinicians to easily obtain GOF variants in humans (http://www.genemed.tech/gofcards). This database also contains data from >150 sources and offers comprehensive variant-level and gene-level annotations, with the aim of providing users with convenient access to detailed and relevant genetic information. Furthermore, GoFCards empowers users with limited bioinformatic skills to analyze and annotate genetic data, and prioritize GOF variants. GoFCards offers an efficient platform for interpreting GOF variants and thereby advancing genetic research.

Machine learning based on multiplatform tests assists in subtype classification of mature B-cell neoplasms

Mature B-cell neoplasms (MBNs) are clonal proliferative diseases encompassing over 40 subtypes. The WHO classification (morphology, immunology, cytogenetics and molecular biology) provides comprehensive diagnostic understandings. However, MBN subtyping relies heavily on the expertise of clinicians and pathologists, and differences in clinical experience can lead to variations in subtyping efficiency and consistency. Additionally, due to the diversity in genetic backgrounds, machine learning (ML) models constructed based on Western populations may not be suitable for Chinese MBN patients. To construct a highly accurate classification model suitable for Chinese MBN patients, we first developed an ML model based on next-generation sequencing (NGS) from Chinese MBN patients, with an accuracy of 0.719, which decreased to 0.707 after model feature selection. Another ML model based on NGS and tumour cell size had an accuracy of 0.715, which increased to 0.763 after model feature selection. Both models were more accurate than models constructed using Western MBN patient databases. Furthermore, by adding flow cytometry for CD5 and CD10, the accuracy reached 0.864, which further improved to 0.872 after model feature selection. These models are accessible via an open-access website. Overall, ML models incorporating multiplatform tests can serve as practical auxiliary tools for MBN subtype classification.

Pharmacogenomic landscape of the Thai population from genome sequencing of 949 individuals

Inter-individual variability in drug responses is significantly influenced by genetic factors, underscoring the importance of population-specific pharmacogenomic studies to optimize clinical outcomes. In this study, we analyzed whole genome sequencing data from 949 unrelated Thai individuals and conducted an in-depth analysis of 3239 genes involved in drug pharmacokinetics, pharmacodynamics, or immune-mediated adverse drug reactions. We identified 43 single nucleotide polymorphisms (SNPs), 134 diplotypes, and 15 human leukocyte antigen (HLA) alleles, all with moderate to high clinical significance. On average, each Thai individual carried 14 SNPs, one to two HLA alleles, and six diplotypes with actionable phenotypic associations. Clinically important diplotypes were present in over 20% of individuals for seven genes (CYP2A6, CYP2B6, CYP2C19, CYP3A5, NAT2, SLCO1B1, and VKORC1). In addition, clinically significant SNPs with allele frequencies exceeding 20% were identified among 15 genes, including VKORC1, CYP4F2, and ABCG2. We also identified 21,211 potentially deleterious variants among 3239 genes. Of these variants, 3746 were novel. The comprehensive dataset from this study serves as a valuable resource of pharmacogenomic variants in the Thai population, which will facilitate the development of personalized drug therapies and enhance patient care in Thailand.

EpiGePT: a pretrained transformer-based language model for context-specific human epigenomics

The inherent similarities between natural language and biological sequences have inspired the use of large language models in genomics, but current models struggle to incorporate chromatin interactions or predict in unseen cellular contexts. To address this, we propose EpiGePT, a transformer-based model designed for predicting context-specific human epigenomic signals. By incorporating transcription factor activities and 3D genome interactions, EpiGePT outperforms existing methods in epigenomic signal prediction tasks, especially in cell-type-specific long-range interaction predictions and genetic variant impacts, advancing our understanding of gene regulation. A free online prediction service is available at http://health.tsinghua.edu.cn/epigept .

The genetic landscape of autism spectrum disorder in an ancestrally diverse cohort

Autism spectrum disorder (ASD) comprises neurodevelopmental disorders with wide variability in genetic causes and phenotypes, making it challenging to pinpoint causal genes. We performed whole exome sequencing on a modest, ancestrally diverse cohort of 195 families, including 754 individuals (222 with ASD), and identified 38,834 novel private variants. In 68 individuals with ASD (~30%), we identified 92 potentially pathogenic variants in 73 known genes, including BCORL1, CDKL5, CHAMP1, KAT6A, MECP2, and SETD1B. Additionally, we identified 158 potentially pathogenic variants in 120 candidate genes, including DLG3, GABRQ, KALRN, KCTD16, and SLC8A3. We also found 34 copy number variants in 31 individuals overlapping known ASD loci. Our work expands the catalog of ASD genetics by identifying hundreds of variants across diverse ancestral backgrounds, highlighting convergence on nervous system development and signal transduction. These findings provide insights into the genetic underpinnings of ASD and inform molecular diagnosis and potential therapeutic targets.

DRED: A Comprehensive Database of Genes Related to Repeat Expansion Diseases

Expansion of tandem repeats in genes often causes severe diseases, such as fragile X syndrome, Huntington's disease, and spinocerebellar ataxia. However, information on genes associated with repeat expansion diseases is scattered throughout the literature, systematic prediction of potential genes that may cause diseases via repeat expansion is also lacking. Here, we develop DRED, a Database of genes related to Repeat Expansion Diseases, as a manually-curated database that covers all known 61 genes related to repeat expansion diseases reported in PubMed and OMIM, along with the detailed repeat information for each gene. DRED also includes 516 genes with the potential to cause diseases via repeat expansion, which were predicted based on their repeat composition, genetic variations, genomic features, and disease associations. Various types of information on repeat expansion diseases and their corresponding genes/repeats are presented in DRED, together with links to external resources, such as NCBI and ClinVar. DRED provides user-friendly interfaces with comprehensive functions, and can serve as a central data resource for basic research and repeat expansion disease-related medical diagnosis. DRED is freely accessible at http://omicslab.genetics.ac.cn/dred, and will be frequently updated to include newly reported genes related to repeat expansion diseases.

Genetic variant classification by predicted protein structure: A case study on IRF6

Next-generation genome sequencing has revolutionized genetic testing, identifying numerous rare disease-associated gene variants. However, to impute pathogenicity, computational approaches remain inadequate and functional testing of gene variant is required to provide the highest level of evidence. The emergence of AlphaFold2 has transformed the field of protein structure determination, and here we outline a strategy that leverages predicted protein structure to enhance genetic variant classification. We used the gene IRF6 as a case study due to its clinical relevance, its critical role in cleft lip/palate malformation, and the availability of experimental data on the pathogenicity of IRF6 gene variants through phenotype rescue experiments in irf6-/- zebrafish. We compared results from over 30 pathogenicity prediction tools on 37 IRF6 missense variants. IRF6 lacks an experimentally derived structure, so we used predicted structures to explore associations between mutational clustering and pathogenicity. We found that among these variants, 19 of 37 were unanimously predicted as deleterious by computational tools. Comparing in silico predictions with experimental findings, 12 variants predicted as pathogenic were experimentally determined as benign. Even with the recently published AlphaMissense model, 15/18 (83%) of the predicted pathogenic variants were experimentally determined as benign. In comparison, mapping variants to the protein revealed deleterious mutation clusters around the protein binding domain, whereas N-terminal variants tend to be benign, suggesting the importance of structural information in determining pathogenicity of mutations in this gene. In conclusion, incorporating gene-specific structural features of known pathogenic/benign mutations may provide meaningful insights into pathogenicity predictions in a gene-specific manner and facilitate the interpretation of variant pathogenicity.

G protein-coupled receptor (GPCR) pharmacogenomics

The field of pharmacogenetics, the investigation of the influence of one or more sequence variants on drug response phenotypes, is a special case of pharmacogenomics, a discipline that takes a genome-wide approach. Massively parallel, next generation sequencing (NGS), has allowed pharmacogenetics to be subsumed by pharmacogenomics with respect to the identification of variants associated with responders and non-responders, optimal drug response, and adverse drug reactions. A plethora of rare and common naturally-occurring GPCR variants must be considered in the context of signals from across the genome. Many fundamentals of pharmacogenetics were established for G protein-coupled receptor (GPCR) genes because they are primary targets for a large number of therapeutic drugs. Functional studies, demonstrating likely-pathogenic and pathogenic GPCR variants, have been integral to establishing models used for in silico analysis. Variants in GPCR genes include both coding and non-coding single nucleotide variants and insertion or deletions (indels) that affect cell surface expression (trafficking, dimerization, and desensitization/downregulation), ligand binding and G protein coupling, and variants that result in alternate splicing encoding isoforms/variable expression. As the breadth of data on the GPCR genome increases, we may expect an increase in the use of drug labels that note variants that significantly impact the clinical use of GPCR-targeting agents. We discuss the implications of GPCR pharmacogenomic data derived from the genomes available from individuals who have been well-phenotyped for receptor structure and function and receptor-ligand interactions, and the potential benefits to patients of optimized drug selection. Examples discussed include the renin-angiotensin system in SARS-CoV-2 (COVID-19) infection, the probable role of chemokine receptors in the cytokine storm, and potential protease activating receptor (PAR) interventions. Resources dedicated to GPCRs, including publicly available computational tools, are also discussed.

Identification of molecular biomarkers associated with non-small-cell lung carcinoma (NSCLC) using whole-exome sequencing

ObjectivesSignificant progress has been made in the treatment of patients with pulmonary adenocarcinoma (ADCA) based on molecular profiling. However, no such molecular target exists for squamous cell carcinoma (SQCC). An exome sequence may provide new markers for personalized medicine for lung cancer patients of all subtypes. The current study aims to discover new genetic markers that can be used as universal biomarkers for non-small cell lung cancer (NSCLC).MethodsWES of 19 advanced NSCLC patients (10 ADCA and 9 SQCC) was performed using Illumina HiSeq 2000. Variant calling was performed using GATK HaplotypeCaller and then the impacts of variants on protein structure or function were predicted using SnpEff and ANNOVAR. The clinical impact of somatic variants in cancer was assessed using cancer archives. Somatic variants were further prioritized using a knowledge-driven variant interpretation approach. Sanger sequencing was used to validate functionally important variants.ResultsWe identified 24 rare single-nucleotide variants (SNVs) including 17 non-synonymous SNVs, and 7 INDELs in 18 genes possibly linked to lung carcinoma. Variants were classified as known somatic (n = 10), deleterious (n = 8), and variant of uncertain significance (n = 6). We found TBP and MPRIP genes exclusively associated with ADCA subtypes, FBOX6 with SQCC subtypes and GPRIN2, KCNJ18 and TEKT4 genes mutated in all the patients. The Sanger sequencing of 10 high-confidence somatic SNVs showed 100% concordance in 7 genes, and 80% concordance in the remaining 3 genes.ConclusionsOur bioinformatics analysis identified KCNJ18, GPRIN2, TEKT4, HRNR, FOLR3, ESSRA, CTBP2, MPRIP, TBP, and FBXO6 may contribute to progression in NSCLC and could be used as new biomarkers for the treatment. The mechanism by which GPRIN2, KCNJ12, and TEKT4 contribute to tumorigenesis is unclear, but our results suggest they may play an important role in NSCLC and it is worth investigating in future.

Bronchial washing fluid sequencing is useful in the diagnosis of lung cancer with necrotic tumor

BACKGROUND

Early-stage lung cancers detected by low-dose computed tomography (CT) often require confirmation through invasive procedures due to the absence of endobronchial lesions. This study assesses the diagnostic utility of bronchial washing fluid (BW) sequencing, a less invasive alternative, aiming to identify patient characteristics most suited for this approach.

METHODS

From June 2017 to March 2018, we conducted a prospective cohort study by enrolling patients with incidental lung lesions suspected of early-stage lung cancer at two independent hospitals, and 114 were diagnosed with lung cancer while 50 were diagnosed with benign lesions. BW sequencing was performed using a targeted gene panel, and the clinical characteristics of patients detected with cancer through sequencing were identified.

RESULTS

Malignant cells were detected in 33 patients (28.9 %) through BW cytology. By applying specificity-focused mutation criteria, BW sequencing classified 42 patients (36.8 %) as having cancer. Among the cancer patients who were BW sequencing positive and BW cytology negative, 15 patients (75.0 %) showed necrosis on CT. The sensitivity of BW sequencing was particularly enhanced in patients with necrotic tumors, reaching 75 %.

CONCLUSIONS

BW sequencing presents a viable, non-invasive diagnostic option for early-stage lung cancer, especially valuable in patients with necrotic lesions. By potentially reducing the reliance on more invasive diagnostic procedures, this method could streamline clinical workflows, decrease patient burden, and improve overall diagnostic efficiency.

Clinical exome sequencing data from patients with inborn errors of immunity: Cohort level diagnostic yield and the benefit of systematic reanalysis

While next generation sequencing has expanded the scientific understanding of Inborn Errors of Immunity (IEI), the clinical use and re-use of exome sequencing is still emerging. We revisited clinical exome data from 1300 IEI patients using an updated in silico IEI gene panel. Variants were classified and curated through expert review. The molecular diagnostic yield after standard exome analysis was 11.8 %. Through systematic reanalysis, we identified variants of interest in 5.2 % of undiagnosed patients, with 76.7 % being (candidate) disease-causing, providing a (candidate) diagnosis in 15.2 % of our cohort. We find a 1.7 percentage point increase in conclusive molecular diagnoses. We find a high degree of actionability in patients with a genetic diagnosis (76.4 %). Despite the modest absolute diagnostic gain, these data support the benefit of iterative exome reanalysis in IEI patients, conveying the notion that our current understanding of genes and variants involved in IEI is by far not saturated.

Rare RNF213 variants is related to early-onset intracranial atherosclerosis: A Chinese community-based study

BACKGROUND

The relationship between rare variants in Ring finger protein 213 (RNF213) and intracranial atherosclerosis (ICAS) remained unelucidated. Using whole-exome sequencing (WES) and high-resolution magnetic resonance imaging (HR-MRI), this study aimed at investigating the association between rare RNF213 variants and ICAS within a Chinese community-dwelling population.

METHODS

The present study included 821 participants from Shunyi cohort. Genetic data of rare RNF213 variants were acquired by WES and were categorized by functional domains. Intracranial and extracranial atherosclerosis were assessed by brain HR-MRI and carotid ultrasound, respectively. Logistic regression and generalized linear regression were applied to evaluate the effects of rare RNF213 variants on atherosclerosis. Stratification by age were conducted with 50 years old set as the cutoff value.

RESULTS

Ninety-five participants were identified as carriers of rare RNF213 variants. Carotid plaques were observed in 367 (44.7 %) participants, while ICAS was identified in 306 (37.3 %). Rare variants of RNF213 was not associated with ECAS. Employing HR-MRI, both the presence of rare variants (β = 0.150, P = 0.025) and numerical count of variants (β = 0.182, P = 0.003) were significantly correlated with ICAS within the group of age ≤50 years. Both variant existence (β = 0.154, P = 0.014) and variant count (β = 0.188, P = 0.003) were significantly associated with plaques in middle cerebral arteries within younger subgroup, rather than basilar arteries. Furthermore, a significant association was observed between variants that located outside the N-arm domain and ICAS in the younger subgroup (OR = 2.522, P = 0.030). Statistical results remained robust after adjusted for age, gender, and cardiovascular risk factors.

CONCLUSIONS

Rare variants of RNF213 is associated with age-related ICAS in general Chinese population, highlighting the potential role of RNF213 as a genetic contributor to early-onset ICAS.

The discrepancy of somatic BRCA1/2 pathogenic variants from two different platforms in epithelial ovarian, fallopian tube, and peritoneal cancer

The somatic BRCA1 or BRCA2 Pathogenic Variant (PV)/Likely PV (LPV) from Next Generation Sequencing (NGS) is the most important biomarker for PARP inhibitor use and maintenance-targeted therapies. A discrepancy in the detection rates of BRCA1 and BRCA2 PV/LPV was identified among the NGS platforms. The objective of this study was to compare the somatic BRCA results from two distinct platforms using the same cohort and to identify the causes of these differences. Patients with epithelial ovarian cancer who concurrently underwent tumor NGS using two different platforms between January 2022 and June 2023 were included in this study. The two platforms used were in-house tumor NGS (Illumina NextSeq 550Dx, SureSelectXT library kit, and datasets from 1000 Genomes, ESP6500, ExAC, and ClinVar) and GreenPlan homologous recombination deficiency (HRD) test (Illumina NextSeq 550Dx, customized Twist Bioscience library kit, and datasets from COSMIC and OncoKB). The results of somatic mutations in BRCA1 and BRCA2 were compared between the two platforms. Of the 118 patients, 11.9% (n = 14) exhibited a discordant interpretation of BRCA1 or BRCA2 between the two platforms. Eleven patients (9.3%) exhibited negative results in the in-house platform but positive results (eight seven as PV of BRCA1, one as PV of BRCA2, one as LPV of BRCA1, and two as LPV of BRCA2) in the GreenPlan HRD test, while three patients (2.6%) had positive BRCA pathogenic variants (two as PV of BRCA1 [c.3340G > T, c.5152 + 3 A > C], one as LPV of BRCA2 [c.8174G > T], and one as LPV of BRCA1 [c.5017_5019delCAC]) in the in-house platform but a negative result in the GreenPlan HRD test. The discordance rate of somatic BRCA1 or BRCA2 mutations from different platforms was approximately 12%. In the case of the strong implication of BRCA PV/LPV with a negative result with one genetic test, different platforms could be considered in limited cases. Careful interpretation and further studies for the cross-validation of gene analysis platforms are needed.

Treatment with novel topoisomerase inhibitors in Ewing sarcoma models reveals heterogeneity of tumor response

Introduction

The topoisomerase 1 (TOP1) inhibitor irinotecan is a standard-of-care agent for relapsed Ewing sarcoma (EWS), but its efficacy is limited by chemical instability, rapid clearance and reversibility, and dose-limiting toxicities, such as diarrhea. Indenoisoquinolines (IIQs) represent a new class of clinical TOP1 inhibitors designed to address these limitations.

Methods

In this study, we evaluated the preclinical efficacy of three IIQs (LMP400, LMP744, and LMP776) in relevant models of EWS. We characterized the pharmacokinetics of IIQs in orthotopic xenograft models of EWS, optimized the dosing regimen through tolerability studies, and tested the efficacy of IIQs in a panel of six molecularly heterogeneous EWS patient-derived xenograft (PDX) models. For each PDX, we conducted whole genome and RNA sequencing, and methylation analysis.

Results

We show that IIQs potently inhibit the proliferation of EWS cells in vitro, inducing complete cell growth inhibition at nanomolar concentrations via induction of DNA damage and apoptotic cell death. LMP400 treatment induced ≥30% tumor regression in two of six PDX models, with more durable regression compared to irinotecan treatment in one of these models. RNA sequencing of PDX models identified a candidate predictive biomarker gene signature for LMP400 response. These data, along with pharmacogenomic data on IIQs in sarcoma cell lines, are available at a new interactive public website: https://discover.nci.nih.gov/rsconnect/EwingSarcomaMinerCDB/.

Discussion

Our findings suggest that IIQs may be promising new agents for a subset of EWS patients.

CardioGraph: a platform to study variations associated with familiar cardiopathies

BACKGROUND

Familiar cardiopathies are genetic disorders that affect the heart. Cardiologists face a significant problem when treating patients suffering from these disorders: most DNA variations are novel (i.e., they have not been classified before). To facilitate the analysis of novel variations, we present CardioGraph, a platform specially designed to support the analysis of novel variations and help determine whether they are relevant for diagnosis. To do this, CardioGraph identifies and annotates the consequence of variations and provides contextual information regarding which heart structures, pathways, and biological processes are potentially affected by those variations.

METHODS

We conducted our work through three steps. First, we define a data model to support the representation of the heterogeneous information. Second, we instantiate this data model to integrate and represent all the genomics knowledge available for familiar cardiopathies. In this step, we consider genomic data sources and the scientific literature. Third, the design and implementation of the CardioGraph platform. A three-tier structure was used: the database, the backend, and the frontend.

RESULTS

Three main results were obtained: the data model, the knowledge base generated with the instantiation of the data model, and the platform itself. The platform code has been included as supplemental material in this manuscript. Besides, an instance is publicly available in the following link: https://genomics-hub.pros.dsic.upv.es:3090 .

CONCLUSION

CardioGraph is a platform that supports the analysis of novel variations. Future work will expand the body of knowledge about familiar cardiopathies and include new information about hotspots, functional studies, and previously reported variations.

Proteogenomic Characterization of Early Intrahepatic Recurrence after Curative-Intent Treatment of Colorectal Liver Metastases

Clinical and pathological factors are insufficient to accurately identify patients at risk of early recurrence after curative-intent treatment of colorectal liver metastases (CRLM). This study aimed to identify candidate prognostic proteogenomic biomarkers for early intrahepatic recurrence after curative-intent resection of CRLM. Patients diagnosed with intrahepatic recurrence within 6 months of liver resection were categorized as the "early recurrence" group, while those who achieved a recurrence-free status for 10 years were designated as "durable remission". Comprehensive genomic and proteomic profiling of fresh frozen samples from these prognostically distinct groups was performed using the TruSight Oncology 500 assay and label-free data-dependent acquisition liquid chromatography-mass spectrometry. Genetic alterations were identified in 117 of the 523 profiled genes in patients with early recurrence. The most common somatic mutations linked to early recurrence were TP53 (88%), APC (71%), KRAS (38%), and SMAD4 (21%). SMAD4 alterations were absent in samples from patients with a durable remission. Calponin-2, versican core protein, glutathione peroxidase 3, fibulin-5, and amyloid-β precursor protein were upregulated more than 2-fold in early recurrence. Exploratory analysis of these proteogenomic biomarkers suggests that SMAD4, calponin-2, and glutathione peroxidase 3 may have the potential to predict early recurrence, enabling improved prognostication and precision oncology in CRLM.

Heterozygous Variants in KCNJ10 Cause Paroxysmal Kinesigenic Dyskinesia Via Haploinsufficiency

OBJECTIVE

Most paroxysmal kinesigenic dyskinesia (PKD) cases are hereditary, yet approximately 60% of patients remain genetically undiagnosed. We undertook the present study to uncover the genetic basis for undiagnosed PKD patients.

METHODS

Whole-exome sequencing was performed for 106 PRRT2-negative PKD probands. The functional impact of the genetic variants was investigated in HEK293T cells and Drosophila.

RESULTS

Heterozygous variants in KCNJ10 were identified in 11 individuals from 8 unrelated families, which accounted for 7.5% (8/106) of the PRRT2-negative probands. Both co-segregation of the identified variants and the significantly higher frequency of rare KCNJ10 variants in PKD cases supported impacts from the detected KCNJ10 heterozygous variants on PKD pathogenesis. Moreover, a KCNJ10 mutation-carrying father from a typical EAST/SeSAME family was identified as a PKD patient. All patients manifested dystonia attacks triggered by sudden movement with a short episodic duration. Patch-clamp recordings in HEK293T cells revealed apparent reductions in K+ currents of the patient-derived variants, indicating a loss-of-function. In Drosophila, milder hyperexcitability phenotypes were observed in heterozygous Irk2 knock-in flies compared to homozygotes, supporting haploinsufficiency as the mechanism for the detected heterozygous variants. Electrophysiological recordings showed that excitatory neurons in Irk2 haploinsufficiency flies exhibited increased excitability, and glia-specific complementation with human Kir4.1 rescued the Irk2 mutant phenotypes.

INTERPRETATION

Our study established haploinsufficiency resulting from heterozygous variants in KCNJ10 can be understood as a previously unrecognized genetic cause for PKD and provided evidence of glial involvement in the pathophysiology of PKD. ANN NEUROL 2024;96:758-773.

Next generation sequencing identifies WNT signalling as a significant pathway in Autosomal Recessive Polycystic Kidney Disease (ARPKD) manifestation and may be linked to disease severity

INTRODUCTION

Autosomal Recessive Polycystic Kidney Disease (ARPKD) is a rare paediatric disease primarily caused by sequence variants in PKHD1. ARPKD presents with considerable clinical variability relating to the type of PKHD1 sequence variant, but not its position. Animal models of Polycystic Kidney Disease (PKD) suggest a complex genetic landscape, with genetic modifiers as a potential cause of disease variability.

METHODS

To investigate in an unbiased manner the molecular mechanisms of ARPKD and identify potential indicators of disease severity, Whole Exome Sequencing (WES) and RNA-Sequencing (RNA-Seq) were employed on human ARPKD kidneys and age-matched healthy controls.

RESULTS

WES confirmed the clinical diagnosis of ARPKD in our patient cohort consisting of ten ARPKD kidneys. Sequence variant type, nor position of PKHD1 sequence variants, was linked to disease severity. Sequence variants in genes associated with other ciliopathies were detected in the ARPKD cohort, but only PKD1 could be linked to disease severity. Transcriptomic analysis on a subset of four ARPKD kidneys representing severe and moderate ARPKD, identified a significant number of genes relating to WNT signalling, cellular metabolism and development. Increased expression of WNT signalling-related genes was validated by RT-qPCR in severe and moderate ARPKD kidneys. Two individuals in our cohort with the same PKHD1 sequence variants but different rates of kidney disease progression, with displayed transcriptomic differences in the expression of WNT signalling genes.

CONCLUSION

ARPKD kidney transcriptomics highlights changes in WNT signalling as potentially significant in ARPKD manifestation and severity, providing indicators for slowing down the progression of ARPKD.

Unveiling the role of IGF1R in autism spectrum disorder: a multi-omics approach to decipher common pathogenic mechanisms in the IGF signaling pathway

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition marked by impairments in social interaction, communication, and repetitive behaviors. Emerging evidence suggests that the insulin-like growth factor (IGF) signaling pathway plays a critical role in ASD pathogenesis; however, the precise pathogenic mechanisms remain elusive. This study utilizes multi-omics approaches to investigate the pathogenic mechanisms of ASD susceptibility genes within the IGF pathway. Whole-exome sequencing (WES) revealed a significant enrichment of rare variants in key IGF signaling components, particularly the IGF receptor 1 (IGF1R), in a cohort of Chinese Han individuals diagnosed with ASD, as well as in ASD patients from the SFARI SPARK WES database. Subsequent single-cell RNA sequencing (scRNA-seq) of cortical tissues from children with ASD demonstrated elevated expression of IGF receptors in parvalbumin (PV) interneurons, suggesting a substantial impact on their development. Notably, IGF1R appears to mediate the effects of IGF2R on these neurons. Additionally, transcriptomic analysis of brain organoids derived from ASD patients indicated a significant association between IGF1R and ASD. Protein-protein interaction (PPI) and gene regulatory network (GRN) analyses further identified ASD susceptibility genes that interact with and regulate IGF1R expression. In conclusion, IGF1R emerges as a central node within the IGF signaling pathway, representing a potential common pathogenic mechanism and therapeutic target for ASD. These findings highlight the need for further investigation into the modulation of this pathway as a strategy for ASD intervention.

Frequent CHD1 deletions in prostate cancers of African American men is associated with rapid disease progression

We analyzed genomic data from the prostate cancer of African- and European American men to identify differences contributing to racial disparity of outcome. We also performed FISH-based studies of Chromodomain helicase DNA-binding protein 1 (CHD1) loss on prostate cancer tissue microarrays. We created CHD1-deficient prostate cancer cell lines for genomic, drug sensitivity and functional homologous recombination (HR) activity analysis. Subclonal deletion of CHD1 was nearly three times as frequent in prostate tumors of African American than in European American men and it associates with rapid disease progression. CHD1 deletion was not associated with HR deficiency associated mutational signatures or HR deficiency as detected by RAD51 foci formation. This was consistent with the moderate increase of olaparib and talazoparib sensitivity with several CHD1 deficient cell lines showing talazoparib sensitivity in the clinically relevant concentration range. CHD1 loss may contribute to worse disease outcome in African American men.

Variants in NLRP2 and ZFP36L2, non-core components of the human subcortical maternal complex, cause female infertility with embryonic development arrest

The subcortical maternal complex (SCMC), which is vital in oocyte maturation and embryogenesis, consists of core proteins (NLRP5, TLE6, OOEP), non-core proteins (PADI6, KHDC3L, NLRP2, NLRP7), and other unknown proteins that are encoded by maternal effect genes. Some variants of SCMC genes have been linked to female infertility characterized by embryonic development arrest. However, so far, the candidate non-core SCMC components associated with embryonic development need further exploration and the pathogenic variants that have been identified are still limited. In this study, we discovered two novel variants [p.(Ala131Val) and p.(Met326Val)] of NLRP2 in patients with primary infertility displaying embryonic development arrest from large families. In vitro studies using 293T cells and mouse oocytes, respectively, showed that these variants significantly decreased protein expression and caused the phenotype of embryonic development arrest. Additionally, we combined the 'DevOmics' database with the whole exome sequence data of our cohort and screened out a new candidate non-core SCMC gene ZFP36L2. Its variants [p.(Ala241Pro) and p.(Pro291dup)] were found to be responsible for embryonic development arrest. Co-immunoprecipitation experiments in 293T cells, used to demonstrate the interaction between proteins, verified that ZFP36L2 is one of the human SCMC components, and microinjection of ZFP36L2 complementary RNA variants into mouse oocytes affected embryonic development. Furthermore, the ZFP36L2 variants were associated with disrupted stability of its target mRNAs, which resulted in aberrant H3K4me3 and H3K9me3 levels. These disruptions decreased oocyte quality and further developmental potential. Overall, this is the first report of ZFP36L2 as a non-core component of the human SCMC and we found four novel pathogenic variants in the NLRP2 and ZFP36L2 genes in 4 of 161 patients that caused human embryonic development arrest. These findings contribute to the genetic diagnosis of female infertility and provide new insights into the physiological function of SCMC in female reproduction.

Case report: Unveiling genetic and phenotypic variability in Nonketotic hyperglycinemia: an atypical early onset case associated with a novel GLRX5 variant

Nonketotic hyperglycinemia (NKH) is a rare, autosomal recessive metabolic disorder usually associated with mutations in genes AMT, GLDC or GCSH involved in the glycine cleavage complex. Other genes have been linked with less severe NKH, associated with deficiency of lipoate cofactor such as GLRX5, LIAS, BOLA3. We identified a new case of GLRX5-mediated NKH who presented at 2-month with severe developmental delay and seizures. The initial suspicion was raised by the MRI and then confirmed by glycine measurements in cerebrospinal fluid and blood. Genetic analysis revealed a previously undescribed homozygous variant in the GLRX5 gene [NM_016417.3:c.367G>C; p. (Asp123His)]. Despite medication and supportive care, he died at the age of 4 months after a sudden neurological deterioration. It was decided to limit therapeutic interventions due to the severity of the prognosis. The case was more severe than the previous GLRX5-mediated NKH described, regarding the early age at onset and the severity. Moreover, the genetic variant was located at a potentially crucial site for glutathione binding in the GLRX5 protein. This report, thereby, expands our understanding of NKH's genetic underpinnings and phenotypic variability, highlighting the crucial role of GLRX5 and other related genes in variant NKH.

The Importance of Copy Number Variant Analysis in Patients with Monogenic Kidney Disease

Introduction

Genetic testing can reveal monogenic causes of kidney diseases, offering diagnostic, therapeutic, and prognostic benefits. Although single nucleotide variants (SNVs) and copy number variants (CNVs) can result in kidney disease, CNV analysis is not always included in genetic testing.

Methods

We investigated the diagnostic value of CNV analysis in 2432 patients with kidney disease genetically tested at the University Medical Centre Utrecht between 2014 and May 2022. We combined previous diagnostic testing results, encompassing SNVs and CNVs, with newly acquired results based on retrospective CNV analysis. The reported yield considers both the American College of Medical Genetics and Genomics (ACMG) classification and whether the genotype actually results in disease.

Results

We report a diagnostic yield of at least 23% for our complete diagnostic cohort. The total diagnostic yield based solely on CNVs was 2.4%. The overall contribution of CNV analysis, defined as the proportion of positive genetic tests requiring CNV analysis, was 10.5% and varied among different disease subcategories, with the highest impact seen in congenital anomalies of the kidney and urinary tract (CAKUT) and chronic kidney disease at a young age. We highlight the efficiency of exome-based CNV calling, which reduces the need for additional diagnostic tests. Furthermore, a complex structural variant, likely a COL4A4 founder variant, was identified. Additional findings unrelated to kidney diseases were reported in a small percentage of cases.

Conclusion

In summary, this study demonstrates the substantial diagnostic value of CNV analysis, providing insights into its contribution to the diagnostic yield and advocating for its routine inclusion in genetic testing of patients with kidney disease.

Viral hepatitis moderates the impact of TGFB1 on neurocognitive impairment

Recent studies have identified a correlation between chronic viral hepatitis and cognitive impairment, yet the underlying mechanisms remain unclear. This study investigated the influence of TGFB1 genetic polymorphisms on cognitive function in individuals with and without hepatitis infections, hypothesizing that these polymorphisms and the viral hepatitis-induced inflammatory environment interact to affect cognitive abilities. Participants (173 with viral hepatitis and 258 healthy controls) were recruited. Genotyping of TGFB1 SNPs was performed using the C2-58 Axiom Genome-Wide TWB 2.0 Array Plate. Cognitive function was assessed using the MMSE and MoCA tests. Our results showed that healthy individuals carrying the C allele of rs2241715 displayed better performance in sentence writing (p = 0.020) and language tasks (p = 0.022). Notably, viral hepatitis was found to moderate the impact of the rs2241715 genotype on language function (p = 0.002). Similarly, those carrying the T allele of rs10417924 demonstrated superior orientation to time (p = 0.002), with viral hepatitis modifying the influence of the SNP on this particular cognitive function (p = 0.010). Our findings underscore the significant role of TGFβ1 in cognitive function and the moderating impact of viral hepatitis on TGFB1 SNP effects. These findings illuminate the potential of TGFB1 as a therapeutic target for cognitive impairment induced by viral hepatitis, thus broadening our understanding of TGFβ1 functionality in the pathogenesis of neurodegeneration.

Comparative genomic landscape of lower-grade glioma and glioblastoma

Biomarkers for classifying and grading gliomas have been extensively explored, whereas populations in public databases were mostly Western/European. Based on public databases cannot accurately represent Chinese population. To identify molecular characteristics associated with clinical outcomes of lower-grade glioma (LGG) and glioblastoma (GBM) in the Chinese population, we performed whole-exome sequencing (WES) in 16 LGG and 35 GBM tumor tissues. TP53 (36/51), TERT (31/51), ATRX (16/51), EFGLAM (14/51), and IDH1 (13/51) were the most common genes harboring mutations. IDH1 mutation (c.G395A; p.R132H) was significantly enriched in LGG, whereas PCDHGA10 mutation (c.A265G; p.I89V) in GBM. IDH1-wildtype and PCDHGA10 mutation were significantly related to poor prognosis. IDH1 is an important biomarker in gliomas, whereas PCDHGA10 mutation has not been reported to correlate with gliomas. Different copy number variations (CNVs) and oncogenic signaling pathways were identified between LGG and GBM. Differential genomic landscapes between LGG and GBM were revealed in the Chinese population, and PCDHGA10, for the first time, was identified as the prognostic factor of gliomas. Our results might provide a basis for molecular classification and identification of diagnostic biomarkers and even potential therapeutic targets for gliomas.

ECEL1 related distal arthrogryposis 5D in an Indian cohort-Report of recognizable musculoskeletal phenotype and a possible founder variant

Distal arthrogryposis type 5D (DA5D) is clinically characterized by knee extension contractures, distal joint contractures, clubfoot, micrognathia, ptosis, and scoliosis. We report nine affected individuals from eight unrelated Indian families with DA5D. Although the overall musculoskeletal phenotype is not very distinct from other distal arthrogryposis, the presence of fixed knee extension contractures with or without scoliosis could be an important early pointer to DA5D. We also report a possible founder variant in ECEL1 along with four novel variants and further expand the genotypic spectrum of DA5D.

Landscape of genomic structural variations in Indian population-based cohorts: Deeper insights into their prevalence and clinical relevance

Structural variations (SV) are large (>50 base pairs) genomic rearrangements comprising deletions, duplications, insertions, inversions, and translocations. Studying SVs is important because they play active and critical roles in regulating gene expression, determining disease predispositions, and identifying population-specific differences among individuals of diverse ancestries. However, SV discoveries in the Indian population using whole-genome sequencing (WGS) have been limited. In this study, using short-read WGS having an average 42X depth of coverage, we identify and characterize 36,210 SVs from 529 individuals enrolled in population-based cohorts in India. These SVs include 24,574 deletions, 2,913 duplications, 8,710 insertions, and 13 inversions; 1.26% (456 out of 36,210) of the identified SVs can potentially impact the coding regions of genes. Furthermore, 56 of these SVs are highly intolerant to loss-of-function changes to the mapped genes, and five SVs impacting ADAMTS17, CCDC40, and RHCE are common in our study individuals. Seven rare SVs significantly impact dosage sensitivity of genes known to be associated with various clinical phenotypes. Most of the SVs in our study are rare and heterozygous. This fine-scale SV discovery in the underrepresented Indian population provides valuable insights that extend beyond Eurocentric human genetic studies.

ProtVar: mapping and contextualizing human missense variation

Genomic variation can impact normal biological function in complex ways and so understanding variant effects requires a broad range of data to be coherently assimilated. Whilst the volume of human variant data and relevant annotations has increased, the corresponding increase in the breadth of participating fields, standards and versioning mean that moving between genomic, coding, protein and structure positions is increasingly complex. In turn this makes investigating variants in diverse formats and assimilating annotations from different resources challenging. ProtVar addresses these issues to facilitate the contextualization and interpretation of human missense variation with unparalleled flexibility and ease of accessibility for use by the broadest range of researchers. By precalculating all possible variants in the human proteome it offers near instantaneous mapping between all relevant data types. It also combines data and analyses from a plethora of resources to bring together genomic, protein sequence and function annotations as well as structural insights and predictions to better understand the likely effect of missense variation in humans. It is offered as an intuitive web server https://www.ebi.ac.uk/protvar where data can be explored and downloaded, and can be accessed programmatically via an API.

Genetic diversity of 1,845 rhesus macaques improves genetic variation interpretation and identifies disease models

Understanding and treating human diseases require valid animal models. Leveraging the genetic diversity in rhesus macaque populations across eight primate centers in the United States, we conduct targeted-sequencing on 1845 individuals for 374 genes linked to inherited human retinal and neurodevelopmental diseases. We identify over 47,000 single nucleotide variants, a substantial proportion of which are shared with human populations. By combining rhesus and human allele frequencies with established variant prediction methods, we develop a machine learning-based score that outperforms established methods in predicting missense variant pathogenicity. Remarkably, we find a marked number of loss-of-function variants and putative deleterious variants, which may lead to the development of rhesus disease models. Through phenotyping of macaques carrying a pathogenic OPA1:p.A8S variant, we identify a genetic model of autosomal dominant optic atrophy. Finally, we present a public website housing variant and genotype data from over two thousand rhesus macaques.