PHF2-mediated H3K9me balance orchestrates heterochromatin stability and neural progenitor proliferation.

Heterochromatin stability is crucial for progenitor proliferation during early neurogenesis. It relays on the maintenance of local hubs of H3K9me. However, understanding the formation of efficient localized levels of H3K9me remains limited. To address this question, we used neural stem cells to analyze the function of the H3K9me2 demethylase PHF2, which is crucial for progenitor proliferation. Through mass-spectroscopy and genome-wide assays, we show that PHF2 interacts with heterochromatin components and is enriched at pericentromeric heterochromatin (PcH) boundaries where it maintains transcriptional activity. This binding is essential for silencing the satellite repeats, preventing DNA damage and genome instability. PHF2's depletion increases the transcription of heterochromatic repeats, accompanied by a decrease in H3K9me3 levels and alterations in PcH organization. We further show that PHF2's PHD and catalytic domains are crucial for maintaining PcH stability, thereby safeguarding genome integrity. These results highlight the multifaceted nature of PHF2's functions in maintaining heterochromatin stability and regulating gene expression during neural development. Our study unravels the intricate relationship between heterochromatin stability and progenitor proliferation during mammalian neurogenesis.

QAFI: a novel method for quantitative estimation of missense variant impact using protein-specific predictors and ensemble learning.

Next-generation sequencing (NGS) has revolutionized genetic diagnostics, yet its application in precision medicine remains incomplete, despite significant advances in computational tools for variant annotation. Many variants remain unannotated, and existing tools often fail to accurately predict the range of impacts that variants have on protein function. This limitation restricts their utility in relevant applications such as predicting disease severity and onset age. In response to these challenges, a new generation of computational models is emerging, aimed at producing quantitative predictions of genetic variant impacts. However, the field is still in its early stages, and several issues need to be addressed, including improved performance and better interpretability. This study introduces QAFI, a novel methodology that integrates protein-specific regression models within an ensemble learning framework, utilizing conservation-based and structure-related features derived from AlphaFold models. Our findings indicate that QAFI significantly enhances the accuracy of quantitative predictions across various proteins. The approach has been rigorously validated through its application in the CAGI6 contest, focusing on ARSA protein variants, and further tested on a comprehensive set of clinically labeled variants, demonstrating its generalizability and robust predictive power. The straightforward nature of our models may also contribute to better interpretability of the results.

The histone demethylase PHF8 regulates astrocyte differentiation and function.

Epigenetic factors have been shown to play a crucial role in X-linked intellectual disability (XLID). Here, we investigate the contribution of the XLID-associated histone demethylase PHF8 to astrocyte differentiation and function. Using genome-wide analyses and biochemical assays in mouse astrocytic cultures, we reveal a regulatory crosstalk between PHF8 and the Notch signaling pathway that balances the expression of the master astrocytic gene Nfia. Moreover, PHF8 regulates key synaptic genes in astrocytes by maintaining low levels of H4K20me3. Accordingly, astrocytic-PHF8 depletion has a striking effect on neuronal synapse formation and maturation in vitro. These data reveal that PHF8 is crucial in astrocyte development to maintain chromatin homeostasis and limit heterochromatin formation at synaptogenic genes. Our studies provide insights into the involvement of epigenetics in intellectual disability.

Choosing Variant Interpretation Tools for Clinical Applications: Context Matters.

Pathogenicity predictors are computational tools that classify genetic variants as benign or pathogenic; this is currently a major challenge in genomic medicine. With more than fifty such predictors available, selecting the most suitable tool for clinical applications like genetic screening, molecular diagnostics, and companion diagnostics has become increasingly challenging. To address this issue, we have developed a cost-based framework that naturally considers the various components of the problem. This framework encodes clinical scenarios using a minimal set of parameters and treats pathogenicity predictors as rejection classifiers, a common practice in clinical applications where low-confidence predictions are routinely rejected. We illustrate our approach in four examples where we compare different numbers of pathogenicity predictors for missense variants. Our results show that no single predictor is optimal for all clinical scenarios and that considering rejection yields a different perspective on classifiers.

PHF2 histone demethylase prevents DNA damage and genome instability by controlling cell cycle progression of neural progenitors.

Histone H3 lysine 9 methylation (H3K9me) is essential for cellular homeostasis; however, its contribution to development is not well established. Here, we demonstrate that the H3K9me2 demethylase PHF2 is essential for neural progenitor proliferation in vitro and for early neurogenesis in the chicken spinal cord. Using genome-wide analyses and biochemical assays we show that PHF2 controls the expression of critical cell cycle progression genes, particularly those related to DNA replication, by keeping low levels of H3K9me3 at promoters. Accordingly, PHF2 depletion induces R-loop accumulation that leads to extensive DNA damage and cell cycle arrest. These data reveal a role of PHF2 as a guarantor of genome stability that allows proper expansion of neural progenitors during development.

A Collaborative Effort to Define Classification Criteria for ATM Variants in Hereditary Cancer Patients.

BACKGROUND: Gene panel testing by massive parallel sequencing has increased the diagnostic yield but also the number of variants of uncertain significance. Clinical interpretation of genomic data requires expertise for each gene and disease. Heterozygous ATM pathogenic variants increase the risk of cancer, particularly breast cancer. For this reason, ATM is included in most hereditary cancer panels. It is a large gene, showing a high number of variants, most of them of uncertain significance. Hence, we initiated a collaborative effort to improve and standardize variant classification for the ATM gene. METHODS: Six independent laboratories collected information from 766 ATM variant carriers harboring 283 different variants. Data were submitted in a consensus template form, variant nomenclature and clinical information were curated, and monthly team conferences were established to review and adapt American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) criteria to ATM, which were used to classify 50 representative variants. RESULTS: Amid 283 different variants, 99 appeared more than once, 35 had differences in classification among laboratories. Refinement of ACMG/AMP criteria to ATM involved specification for twenty-one criteria and adjustment of strength for fourteen others. Afterwards, 50 variants carried by 254 index cases were classified with the established framework resulting in a consensus classification for all of them and a reduction in the number of variants of uncertain significance from 58% to 42%. CONCLUSIONS: Our results highlight the relevance of data sharing and data curation by multidisciplinary experts to achieve improved variant classification that will eventually improve clinical management.

Towards a New, Endophenotype-Based Strategy for Pathogenicity Prediction in BRCA1 and BRCA2: In Silico Modeling of the Outcome of HDR/SGE Assays for Missense Variants.

The present limitations in the pathogenicity prediction of BRCA1 and BRCA2 (BRCA1/2) missense variants constitute an important problem with negative consequences for the diagnosis of hereditary breast and ovarian cancer. However, it has been proposed that the use of endophenotype predictions, i.e., computational estimates of the outcomes of functional assays, can be a good option to address this bottleneck. The application of this idea to the BRCA1/2 variants in the CAGI 5-ENIGMA international challenge has shown promising results. Here, we developed this approach, exploring the predictive performances of the regression models applied to the BRCA1/2 variants for which the values of the homology-directed DNA repair and saturation genome editing assays are available. Our results first showed that we can generate endophenotype estimates using a few molecular-level properties. Second, we show that the accuracy of these estimates is enough to obtain pathogenicity predictions comparable to those of many standard tools. Third, endophenotype-based predictions are complementary to, but do not outperform, those of a Random Forest model trained using variant pathogenicity annotations instead of endophenotype values. In summary, our results confirmed the usefulness of the endophenotype approach for the pathogenicity prediction of the BRCA1/2 missense variants, suggesting different options for future improvements.

Increased dNTP pools rescue mtDNA depletion in human POLG-deficient fibroblasts.

Polymerase γ catalytic subunit (POLG) gene encodes the enzyme responsible for mitochondrial DNA (mtDNA) synthesis. Mutations affecting POLG are the most prevalent cause of mitochondrial disease because of defective mtDNA replication and lead to a wide spectrum of clinical phenotypes characterized by mtDNA deletions or depletion. Enhancing mitochondrial deoxyribonucleoside triphosphate (dNTP) synthesis effectively rescues mtDNA depletion in different models of defective mtDNA maintenance due to dNTP insufficiency. In this study, we studied mtDNA copy number recovery rates following ethidium bromide-forced depletion in quiescent fibroblasts from patients harboring mutations in different domains of POLG. Whereas control cells spontaneously recovered initial mtDNA levels, POLG-deficient cells experienced a more severe depletion and could not repopulate mtDNA. However, activation of deoxyribonucleoside (dN) salvage by supplementation with dNs plus erythro-9-(2-hydroxy-3-nonyl) adenine (inhibitor of deoxyadenosine degradation) led to increased mitochondrial dNTP pools and promoted mtDNA repopulation in all tested POLG-mutant cells independently of their specific genetic defect. The treatment did not compromise POLG fidelity because no increase in multiple deletions or point mutations was detected. Our study suggests that physiologic dNTP concentration limits the mtDNA replication rate. We thus propose that increasing mitochondrial dNTP availability could be of therapeutic interest for POLG deficiency and other conditions in which mtDNA maintenance is challenged.-Blázquez-Bermejo, C., Carreño-Gago, L., Molina-Granada, D., Aguirre, J., Ramón, J., Torres-Torronteras, J., Cabrera-Pérez, R., Martín, M. Á., Domínguez-González, C., de la Cruz, X., Lombès, A., García-Arumí, E., Martí, R., Cámara, Y. Increased dNTP pools rescue mtDNA depletion in human POLG-deficient fibroblasts.

Lineage specific transcription factors and epigenetic regulators mediate TGFß-dependent enhancer activation.

During neurogenesis, dynamic developmental cues, transcription factors and histone modifying enzymes regulate the gene expression programs by modulating the activity of neural-specific enhancers. How transient developmental signals coordinate transcription factor recruitment to enhancers and to which extent chromatin modifiers contribute to enhancer activity is starting to be uncovered. Here, we take advantage of neural stem cells as a model to unravel the mechanisms underlying neural enhancer activation in response to the TGFß signaling. Genome-wide experiments demonstrate that the proneural factor ASCL1 assists SMAD3 in the binding to a subset of enhancers. Once located at the enhancers, SMAD3 recruits the histone demethylase JMJD3 and the remodeling factor CHD8, creating the appropriate chromatin landscape to allow enhancer transcription and posterior gene activation. Finally, to analyze the phenotypical traits owed to cis-regulatory regions, we use CRISPR-Cas9 technology to demonstrate that the TGFß-responsive Neurog2 enhancer is essential for proper neuronal polarization.

BRCA1- and BRCA2-specific in silico tools for variant interpretation in the CAGI 5 ENIGMA challenge.

BRCA1 and BRCA2 (BRCA1/2) germline variants disrupting the DNA protective role of these genes increase the risk of hereditary breast and ovarian cancers. Correct identification of these variants then becomes clinically relevant, because it may increase the survival rates of the carriers. Unfortunately, we are still unable to systematically predict the impact of BRCA1/2 variants. In this article, we present a family of in silico predictors that address this problem, using a gene-specific approach. For each protein, we have developed two tools, aimed at predicting the impact of a variant at two different levels: Functional and clinical. Testing their performance in different datasets shows that specific information compensates the small number of predictive features and the reduced training sets employed to develop our models. When applied to the variants of the BRCA1/2 (ENIGMA) challenge in the fifth Critical Assessment of Genome Interpretation (CAGI 5) we find that these methods, particularly those predicting the functional impact of variants, have a good performance, identifying the large compositional bias towards neutral variants in the CAGI sample. This performance is further improved when incorporating to our prediction protocol estimates of the impact on splicing of the target variant.

Assessment of blind predictions of the clinical significance of BRCA1 and BRCA2 variants.

Testing for variation in BRCA1 and BRCA2 (commonly referred to as BRCA1/2), has emerged as a standard clinical practice and is helping countless women better understand and manage their heritable risk of breast and ovarian cancer. Yet the increased rate of BRCA1/2 testing has led to an increasing number of Variants of Uncertain Significance (VUS), and the rate of VUS discovery currently outpaces the rate of clinical variant interpretation. Computational prediction is a key component of the variant interpretation pipeline. In the CAGI5 ENIGMA Challenge, six prediction teams submitted predictions on 326 newly-interpreted variants from the ENIGMA Consortium. By evaluating these predictions against the new interpretations, we have gained a number of insights on the state of the art of variant prediction and specific steps to further advance this state of the art.

PMut: a web-based tool for the annotation of pathological variants on proteins, 2017 update.

We present here a full update of the PMut predictor, active since 2005 and with a large acceptance in the field of predicting Mendelian pathological mutations. PMut internal engine has been renewed, and converted into a fully featured standalone training and prediction engine that not only powers PMut web portal, but that can generate custom predictors with alternative training sets or validation schemas. PMut Web portal allows the user to perform pathology predictions, to access a complete repository of pre-calculated predictions, and to generate and validate new predictors. The default predictor performs with good quality scores (MCC values of 0.61 on 10-fold cross validation, and 0.42 on a blind test with SwissVar 2016 mutations). The PMut portal is freely accessible at http://mmb.irbbarcelona.org/PMut. A complete help and tutorial is available at http://mmb.irbbarcelona.org/PMut/help.

The histone demethylase PHF8 is a molecular safeguard of the IFNγ response.

A precise immune response is essential for cellular homeostasis and animal survival. The paramount importance of its control is reflected by the fact that its non-specific activation leads to inflammatory events that ultimately contribute to the appearance of many chronic diseases. However, the molecular mechanisms preventing non-specific activation and allowing a quick response upon signal activation are not yet fully understood. In this paper we uncover a new function of PHF8 blocking signal independent activation of immune gene promoters. Affinity purifications coupled with mass spectrometry analysis identified SIN3A and HDAC1 corepressors as new PHF8 interacting partners. Further molecular analysis demonstrated that prior to interferon gamma (IFNγ) stimulation, PHF8 is bound to a subset of IFNγ-responsive promoters. Through the association with HDAC1 and SIN3A, PHF8 keeps the promoters in a silent state, maintaining low levels of H4K20me1. Upon IFNγ treatment, PHF8 is phosphorylated by ERK2 and evicted from the promoters, correlating with an increase in H4K20me1 and transcriptional activation. Our data strongly indicate that in addition to its well-characterized function as a coactivator, PHF8 safeguards transcription to allow an accurate immune response.

Structural and Computational Characterization of Disease-Related Mutations Involved in Protein-Protein Interfaces.

One of the known potential effects of disease-causing amino acid substitutions in proteins is to modulate protein-protein interactions (PPIs). To interpret such variants at the molecular level and to obtain useful information for prediction purposes, it is important to determine whether they are located at protein-protein interfaces, which are composed of two main regions, core and rim, with different evolutionary conservation and physicochemical properties. Here we have performed a structural, energetics and computational analysis of interactions between proteins hosting mutations related to diseases detected in newborn screening. Interface residues were classified as core or rim, showing that the core residues contribute the most to the binding free energy of the PPI. Disease-causing variants are more likely to occur at the interface core region rather than at the interface rim (p < 0.0001). In contrast, neutral variants are more often found at the interface rim or at the non-interacting surface rather than at the interface core region. We also found that arginine, tryptophan, and tyrosine are over-represented among mutated residues leading to disease. These results can enhance our understanding of disease at molecular level and thus contribute towards personalized medicine by helping clinicians to provide adequate diagnosis and treatments.

Development of pathogenicity predictors specific for variants that do not comply with clinical guidelines for the use of computational evidence.

BACKGROUND: Strict guidelines delimit the use of computational information in the clinical setting, due to the still moderate accuracy of in silico tools. These guidelines indicate that several tools should always be used and that full coincidence between them is required if we want to consider their results as supporting evidence in medical decision processes. Application of this simple rule certainly decreases the error rate of in silico pathogenicity assignments. However, when predictors disagree this rule results in the rejection of potentially valuable information for a number of variants. In this work, we focus on these variants of the protein sequence and develop specific predictors to help improve the success rate of their annotation. RESULTS: We have used a set of 59,442 protein sequence variants (15,723 pathological and 43,719 neutral) from 228 proteins to identify those cases for which pathogenicity predictors disagree. We have repeated this process for all the possible combinations of five known methods (SIFT, PolyPhen-2, PON-P2, CADD and MutationTaster2). For each resulting subset we have trained a specific pathogenicity predictor. We find that these specific predictors are able to discriminate between neutral and pathogenic variants, with a success rate different from random. They tend to outperform the constitutive methods but this trend decreases as the performance of the constitutive predictor improves (e.g. with PON-P2 and PolyPhen-2). We also find that specific methods outperform standard consensus methods (Condel and CAROL). CONCLUSION: Focusing development efforts on the case of variants for which known methods disagree we may obtain pathogenicity predictors with improved performances. Although we have not yet reached the success rate that allows the use of this computational evidence in a clinical setting, the simplicity of the approach indicates that more advanced methods may reach this goal in a close future.

Elucidating the molecular basis of MSH2-deficient tumors by combined germline and somatic analysis.

In a proportion of patients presenting mismatch repair (MMR)-deficient tumors, no germline MMR mutations are identified, the so-called Lynch-like syndrome (LLS). Recently, MMR-deficient tumors have been associated with germline mutations in POLE and MUTYH or double somatic MMR events. Our aim was to elucidate the molecular basis of MSH2-deficient LS-suspected cases using a comprehensive analysis of colorectal cancer (CRC)-associated genes at germline and somatic level. Fifty-eight probands harboring MSH2-deficient tumors were included. Germline mutational analysis of MSH2 (including EPCAM deletions) and MSH6 was performed. Pathogenicity of MSH2 variants was assessed by RNA analysis and multifactorial likelihood calculations. MSH2 cDNA and methylation of MSH2 and MSH6 promoters were studied. Matched blood and tumor DNA were analyzed using a customized next generation sequencing panel. Thirty-five individuals were carriers of pathogenic or probably pathogenic variants in MSH2 and EPCAM. Five patients harbored 4 different MSH2 variants of unknown significance (VUS) and one had 2 novel MSH6 promoter VUS. Pathogenicity assessment allowed the reclassification of the 4 MSH2 VUS and 6 probably pathogenic variants as pathogenic mutations, enabling a total of 40 LS diagnostics. Predicted pathogenic germline variants in BUB1, SETD2, FAN1 and MUTYH were identified in 5 cases. Three patients had double somatic hits in MSH2 or MSH6, and another 2 had somatic alterations in other MMR genes and/or proofreading polymerases. In conclusion, our comprehensive strategy combining germline and somatic mutational status of CRC-associated genes by means of a subexome panel allows the elucidation of up to 86% of MSH2-deficient suspected LS tumors.

Early Versus Late Diagnosis of Complement Factor I Deficiency: Clinical Consequences Illustrated in Two Families with Novel Homozygous CFI Mutations.

The complement system is an important effector arm of innate immunity and plays a crucial role in the defense against common pathogens. But effective defense and maintenance of homeostasis requires a careful balance between complement activation and regulation. Factor I (FI) is one of the most important regulators of the complement system. Complete FI deficiency is a rare autosomal recessive disorder typically resulting in severe, recurrent infection by encapsulated bacteria. In the present study, we describe two patients from unrelated families with complete FI deficiency diagnosed at very different ages: Patient 1 is a 60-year-old man who had experienced several severe infections (pneumonia, meningitis, sepsis) since childhood, one of which caused significant and permanent neurologic sequelae. In contrast, patient 2 was diagnosed at the age of 4 years after a single infectious episode (otitis media) and through detection of a flat beta2 peak on serum protein electrophoresis. This early diagnosis of FI deficiency enabled prompt implementation of a therapeutic intervention consisting of vaccination with encapsulated bacteria and prophylactic antibiotics. The two patients had novel homozygous mutations in the CFI gene (p.Gly162Asp and p.His380Arg) that disrupted protein function. Interestingly, p.His380Arg is the first mutation described affecting a residue of the highly conserved FI catalytic triad (His380, Asp429, and Ser525). This study illustrates the importance of early versus late diagnosis of FI deficiency and, in general, highlights the clinical relevance of prompt detection of complement system deficiencies.

Identification and characterization of the novel point mutation m.3634A>G in the mitochondrial MT-ND1 gene associated with LHON syndrome.

Leber's hereditary optic neuropathy (LHON) is a mitochondrial genetic disease characterized by bilateral acute or subacute progressive central visual loss. Most cases of LHON syndrome are caused by point mutations in the MT-ND1, MT-ND4, and MT-ND6 genes. Here, we report a novel homoplasmic mutation in the MT-ND1 gene (m.3634A>G, p.Ser110Gly) in a patient with the classical clinical features of LHON syndrome. Several observations support the idea that the mutation is pathogenic and involved in the clinical phenotype of the patient: 1) The mutation affected a highly conserved amino acid, 2) A pathogenic mutation in the same amino acid (m.3635G>A, p.Ser110Asn) was previously reported in a patient with LHON syndrome, 3) The mutation is not recorded in the Mitomap or Human Mitochondrial Genome Database, 4) In silico predictors classified the mutation as "probably damaging", and 5) Cybrids carrying the mutation showed decreased Complex I enzyme activity, lower cell proliferation, and decreased mitochondrial membrane potential relative to control cybrids.

The Complementarity Between Protein-Specific and General Pathogenicity Predictors for Amino Acid Substitutions.

The usage of next-generation sequencing with biomedical/clinical purposes has fuelled the demand for tools that assess the functional impact of sequence variants. For single amino acid variants, general methods (GM), based on biophysics/evolutionary principles and trained by pooling variants from many proteins, are already available. Until now, their accuracy range (∼80%) has limited their usage in clinical applications. In parallel, a series of studies indicate that protein-specific predictors (PSP), using only information from the protein of interest, could frequently surpass the performance of GM. However, two reasons suggest that this may not always be the case: the existence of a performance threshold affecting both GM and PSP, and the effect of training data scarcity. Here, we characterize the relationship between the two approaches deriving 82 PSP and comparing them with several GM (PolyPhen-2, SIFT, PON-P2, MutationTaster2, CADD). We find a complementary relationship between PSP and GM, with no approach always outperforming the other. However, the relationship varies between two limiting situations, for example, PSP are frequently outperformed by PON-P2, the best GM; however, the opposite happens when we compare PSP and SIFT. Finally, we explore how the observed complementarity could lead to increased success rates in pathogenicity prediction.

Clinical and structural impact of mutations affecting the residue Phe367 of FOXP3 in patients with IPEX syndrome.

Immune dysregulation, polyendocrinopathy, enteropathy, X-linked (IPEX) syndrome is a monogenic autoimmune disease characterized by early-onset life-threatening multisystemic autoimmunity. This rare hereditary disorder is caused by loss-of-function mutations in the gene encoding the forkhead box P3 (FOXP3) transcription factor, which plays a key role in the differentiation and function of CD4(+)CD25(+) natural regulatory T cells (Tregs), essential for the establishment and maintenance of natural tolerance. We identified a novel mutation in the FOXP3 gene affecting the Phe367 residue of the protein (F367V) in a family with three male siblings affected by IPEX. Two other mutations affecting the FOXP3 Phe367 residue (F367L and F367C) have been described previously. This unique situation of three mutations affecting the same residue in FOXP3 led us to study the molecular impact of these mutations on the structure of FOXP3 protein. Structure analysis showed that Phe367 is involved in a rich interaction network related to both monomer and dimer structure stabilization, and is crucial for FOXP3 regulatory activity. The relevance of this location is confirmed by the results of SIFT and PolyPhen-2 pathogenicity predictions for F367V mutation. In summary, as assessment of the pathogenicity of a novel mutation is crucial to achieve a proper molecular diagnosis, we analysed the impact of mutations affecting the Phe367 residue using a combined approach that provides a mechanistic view of their pathogenic effect.