Search

Hailey-Hailey disease (OMIM#169600) is an autosomal dominantly inherited genodermatosis characterized by erosions in the flexural areas of the body. Hailey-Hailey disease is caused by variants in ATP2C1, but for ~10% of the patients, no causative variant is found in the coding region of ATP2C1. We aimed to determine the genetic cause of Hailey-Hailey disease in a family without a variant in the coding areas of ATP2C1. By genome sequencing and analysis of all exon and intron sequences of ATP2C1, we identified the variant c.532-560 T>G (NM_014382.5) in intron 7 of ATP2C1. The variant is predicted by in silico tools to create a new deep intronic donor splice site. Segregation analysis detected the variant in the three affected family members. RNA sequencing confirmed that the variant creates a new deep intronic donor splice site that gives rise to an alternative exon. The identified deep-intronic variant in ATP2C1 is the likely cause of Hailey-Hailey disease. This is to our knowledge the first report of a deep-intronic variant as the cause of Hailey-Hailey disease, which shows that the analysis of the intronic sequences of ATP2C1 could increase the genetic diagnostic yield for Hailey-Hailey disease patients., (© 2024 The Author(s). American Journal of Medical Genetics Part A published by Wiley Periodicals LLC.)

Structural variations (SVs) play important roles in genetic diversity, evolution, and carcinogenesis and are, as such, important for human health. However, it remains unclear how spatial proximity of double-strand breaks (DSBs) affects the formation of SVs. To investigate if spatial proximity between two DSBs affects DNA repair, we used data from 3C experiments (Hi-C, ChIA-PET, and ChIP-seq) to identify highly interacting loci on six different chromosomes. The target regions correlate with the borders of megabase-sized topologically associated domains (TADs), and we used CRISPR-Cas9 nuclease and pairs of single guide RNAs (sgRNAs) against these targets to generate DSBs in both K562 cells and H9 human embryonic stem cells (hESCs). Droplet digital PCR (ddPCR) was used to quantify the resulting recombination events, and high-throughput sequencing was used to analyze the chimeric junctions created between the two DSBs. We observe a significantly higher formation frequency of deletions and inversions with DSBs in proximity compared with deletions and inversions with DSBs not in proximity in K562 cells. Additionally, our results suggest that DSB proximity may affect the ligation of chimeric deletion junctions. Taken together, spatial proximity between DSBs is a significant predictor of large-scale deletion and inversion frequency induced by CRISPR-Cas9 in K562 cells. This finding has implications for understanding SVs in the human genome and for the future application of CRISPR-Cas9 in gene editing and the modeling of rare SVs., (© 2025 Dahl-Jessen et al.; Published by Cold Spring Harbor Laboratory Press.)

The growth and development of the skeleton is regulated by bone morphogenetic proteins of which several are linked to genetic skeletal disorders. So far, no human skeletal malformations have been associated with variants in BMP5. Here, we report a patient with biallelic loss of function variants in BMP5 and a syndromic phenotype including skeletal dysostosis, dysmorphic features, hypermobility, laryngo-tracheo-bronchomalacia and atrioventricular septal defect. We discuss the phenotype in relation to the known tissue-specific expression of Bmp5 and similar morphological abnormalities previously reported in experimental animal models. Our findings suggest a new association between BMP5 variants and a range of developmental anomalies, involving ears, heart and skeleton, thereby increasing understanding of BMP5's role in human development., (© 2024 The Author(s). Clinical Genetics published by John Wiley & Sons Ltd.)

Genetic variants that affect mRNA splicing are a major cause of hereditary disorders, but the spliceogenicity of variants is challenging to predict. RNA diagnostics of clinically accessible tissues enable rapid functional characterization of splice-altering variants within their natural genetic context. However, this analysis cannot be offered to all individuals as one in five human disease genes are not expressed in easily accessible cell types. To overcome this problem, we have used CRISPR activation (CRISPRa) based on a dCas9-VPR mRNA-based delivery platform to induce expression of the gene of interest in skin fibroblasts from individuals with suspected monogenic disorders. Using this ex vivo splicing assay, we characterized the splicing patterns associated with germline variants in the myelin protein zero gene (MPZ), which is exclusively expressed in Schwann cells of the peripheral nerves, and the spastin gene (SPAST), which is predominantly expressed in the central nervous system. After overnight incubation, CRISPRa strongly upregulated MPZ and SPAST transcription in skin fibroblasts, which enabled splice variant profiling using reverse transcription polymerase chain reaction, next-generation sequencing, and long-read sequencing. Our investigations show proof of principle of a promising genetic diagnostic tool that involves CRISPRa to activate gene expression in easily accessible cells to study the functional impact of genetic variants. The procedure is easy to perform in a diagnostic laboratory with equipment and reagents all readily available., Competing Interests: Declaration of interests R.O.B. holds equity in Graphite Bio and UNIKUM Tx and is a paid consultant of UNIKUM Therapeutics., (Copyright © 2023 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Extensive research has explored the role of gut microbiota in colorectal cancer (CRC). Nonetheless, metatranscriptomic studies investigating the in situ functional implications of host-microbe interactions in CRC are scarce. Therefore, we characterized the influence of CRC core pathogens and biofilms on the tumor microenvironment (TME) in 40 CRC, paired normal, and healthy tissue biopsies using fluorescence in situ hybridization (FISH) and dual-RNA sequencing. FISH revealed that Fusobacterium spp . was associated with increased bacterial biomass and inflammatory response in CRC samples. Dual-RNA sequencing demonstrated increased expression of pro-inflammatory cytokines, defensins, matrix-metalloproteases, and immunomodulatory factors in CRC samples with high bacterial activity. In addition, bacterial activity correlated with the infiltration of several immune cell subtypes, including M2 macrophages and regulatory T-cells in CRC samples. Specifically, Bacteroides fragilis and Fusobacterium nucleatum correlated with the infiltration of neutrophils and CD4 + T-cells, respectively. The collective bacterial activity/biomass appeared to exert a more significant influence on the TME than core pathogens, underscoring the intricate interplay between gut microbiota and CRC. These results emphasize how biofilms and core pathogens shape the immune phenotype and TME in CRC while highlighting the need to extend the bacterial scope beyond CRC pathogens to advance our understanding and identify treatment targets.

Differential analysis of bulk RNA-seq data often suffers from lack of good controls. Here, we present a generative model that replaces controls, trained solely on healthy tissues. The unsupervised model learns a low-dimensional representation and can identify the closest normal representation for a given disease sample. This enables control-free, single-sample differential expression analysis. In breast cancer, we demonstrate how our approach selects marker genes and outperforms a state-of-the-art method. Furthermore, significant genes identified by the model are enriched in driver genes across cancers. Our results show that the in silico closest normal provides a more favorable comparison than control samples., (© 2023. The Author(s).)

KPTN-related disorder is an autosomal recessive disorder associated with germline variants in KPTN (previously known as kaptin), a component of the mTOR regulatory complex KICSTOR. To gain further insights into the pathogenesis of KPTN-related disorder, we analysed mouse knockout and human stem cell KPTN loss-of-function models. Kptn -/- mice display many of the key KPTN-related disorder phenotypes, including brain overgrowth, behavioural abnormalities, and cognitive deficits. By assessment of affected individuals, we have identified widespread cognitive deficits (n = 6) and postnatal onset of brain overgrowth (n = 19). By analysing head size data from their parents (n = 24), we have identified a previously unrecognized KPTN dosage-sensitivity, resulting in increased head circumference in heterozygous carriers of pathogenic KPTN variants. Molecular and structural analysis of Kptn-/- mice revealed pathological changes, including differences in brain size, shape and cell numbers primarily due to abnormal postnatal brain development. Both the mouse and differentiated induced pluripotent stem cell models of the disorder display transcriptional and biochemical evidence for altered mTOR pathway signalling, supporting the role of KPTN in regulating mTORC1. By treatment in our KPTN mouse model, we found that the increased mTOR signalling downstream of KPTN is rapamycin sensitive, highlighting possible therapeutic avenues with currently available mTOR inhibitors. These findings place KPTN-related disorder in the broader group of mTORC1-related disorders affecting brain structure, cognitive function and network integrity., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Polygenic risk scores (PRS) identify at-risk individuals for many common diseases. A discussion of strengths and limitations is carried out in this review. PRS complement traditional genetic testing and have shown utility in establishing a proper diagnosis and guiding primary and secondary prevention. Some individuals with high PRS have risks similar to those with monogenic predisposition. Limitations include potential misinterpretations, problems with application across ancestries, and limited usefulness in low-heritability traits. Despite its shortcomings PRS are predicted to play major roles in the future of personal medicine and genetic testing., (Published under Open Access CC-BY-NC-BD 4.0. https://creativecommons.org/licenses/by-nc-nd/4.0/.)

Background & Aims: Colonic adenomatous polyps, or adenomas, are frequent precancerous lesions and the origin of most cases of colorectal adenocarcinoma. However, we know from epidemiologic studies that although most colorectal cancers (CRCs) originate from adenomas, only a small fraction of adenomas (3%-5%) ever progress to cancer. At present, there are no molecular markers to guide follow-up surveillance programs., Methods: We profiled, by mass spectrometry-based proteomics combined with machine learning analysis, a selected cohort of formalin-fixed, paraffin-embedded high-grade (HG) adenomas with long clinical follow-up, collected as part of the Danish national screening program. We grouped subjects in the cohort according to their subsequent history of findings: a nonmetachronous advanced neoplasia group (G0), with no new HG adenomas or CRCs up to 10 years after polypectomy, and a metachronous advanced neoplasia group (G1) where individuals developed a new HG adenoma or CRC within 5 years of diagnosis., Results: We generated a proteome dataset from 98 selected HG adenoma samples, including 20 technical replicates, of which 45 samples belonged to the nonmetachronous advanced neoplasia group and 53 to the metachronous advanced neoplasia group. The clear distinction of these 2 groups seen in a uniform manifold approximation and projection plot indicated that the information contained within the abundance of the ∼5000 proteins was sufficient to predict the future occurrence of HG adenomas or development of CRC., Conclusions: We performed an in-depth analysis of quantitative proteomic data from 98 resected adenoma samples using various novel algorithms and statistical packages and found that their proteome can predict development of metachronous advanced lesions and progression several years in advance., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

BOADICEA is a comprehensive risk prediction model for breast and/or ovarian cancer (BC/OC) and for carrying pathogenic variants (PVs) in cancer susceptibility genes. In addition to BRCA1 and BRCA2, BOADICEA version 6 includes PALB2, CHEK2, ATM, BARD1, RAD51C and RAD51D. To validate its predictions for these genes, we conducted a retrospective study including 2033 individuals counselled at clinical genetics departments in Denmark. All counselees underwent comprehensive genetic testing by next generation sequencing on suspicion of hereditary susceptibility to BC/OC. Likelihoods of PVs were predicted from information about diagnosis, family history and tumour pathology. Calibration was examined using the observed-to-expected ratio (O/E) and discrimination using the area under the receiver operating characteristics curve (AUC). The O/E was 1.11 (95% CI 0.97-1.26) for all genes combined. At sub-categories of predicted likelihood, the model performed well with limited misestimation at the extremes of predicted likelihood. Discrimination was acceptable with an AUC of 0.70 (95% CI 0.66-0.74), although discrimination was better for BRCA1 and BRCA2 than for the other genes in the model. This suggests that BOADICEA remains a valid decision-making aid for determining which individuals to offer comprehensive genetic testing for hereditary susceptibility to BC/OC despite suboptimal calibration for individual genes in this population., (© 2023. The Author(s).)

Mutations, which result in amino acid substitutions, influence the stability of proteins and their binding to biomolecules. A molecular understanding of the effects of protein mutations is both of biotechnological and medical relevance. Empirical free energy functions that quickly estimate the free energy change upon mutation (ΔΔG) can be exploited for systematic screenings of proteins and protein complexes. In silico saturation mutagenesis can guide the design of new experiments or rationalize the consequences of known mutations. Often software such as FoldX, while fast and reliable, lack the necessary automation features to apply them in a high-throughput manner. We introduce MutateX, a software to automate the prediction of ΔΔGs associated with the systematic mutation of each residue within a protein, or protein complex to all other possible residue types, using the FoldX energy function. MutateX also supports ΔΔG calculations over protein ensembles, upon post-translational modifications and in multimeric assemblies. At the heart of MutateX lies an automated pipeline engine that handles input preparation, parallelization and outputs publication-ready figures. We illustrate the MutateX protocol applied to different case studies. The results of the high-throughput scan provided by our tools can help in different applications, such as the analysis of disease-associated mutations, to complement experimental deep mutational scans, or assist the design of variants for industrial applications. MutateX is a collection of Python tools that relies on open-source libraries. It is available free of charge under the GNU General Public License from https://github.com/ELELAB/mutatex., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)