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PubMed2026

Mapping the plasma proteomic architecture of systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is a heterogeneous systemic autoimmune disease, yet the molecular basis underlying this variability remains incompletely understood. We profiled the plasma proteome in 260 SLE patients and 86 healthy volunteers (HVs) using the SomaScan v4.1 platform, quantifying 7,288 analytes corresponding to 6,595 unique proteins. We identified 215 proteins that were robustly differentially abundant between SLE patients and HVs in both discovery (n = 207 SLE, n = 45 HVs) and validation sets (n = 53 SLE, n = 41 HVs). Within-cases analyses identified 421 proteins associated with disease activity. Network-based clustering delineated correlated protein modules, including an interferon-associated (IFN-associated) module and a kidney-associated module. Autoantibody-stratified analyses further uncovered distinct proteomic endotypes; positivity for antibodies targeting RNA-binding proteins (anti-Sm, anti-Ro-60, anti-RNP68, anti-RNP-A) was associated with increased IFN-stimulated protein levels (e.g., MX1, ISG15, and CXCL10), independent of disease activity. Anti-Sm, anti-RNP-A, and anti-Ro52 antibodies were associated with reduced plasma levels of their respective autoantigens. Anti-dsDNA antibodies were associated with elevated levels of CD40 ligand (CD40LG) and the neutrophil protease, proteinase-3. Moreover, we identified an association between CD40LG and disease activity specific to the anti-dsDNA-positive subgroup. Together, these data define plasma protein signatures of SLE and disease activity, highlight autoantibody-specific molecular phenotypes, and provide a basis for precision medicine.

Humans↗
PubMed2009

Multipotent genetic suppression of retrotransposon-induced mutations by Nxf1 through fine-tuning of alternative splicing.

Cellular gene expression machinery has coevolved with molecular parasites, such as viruses and transposons, which rely on host cells for their expression and reproduction. We previously reported that a wild-derived allele of mouse Nxf1 (Tap), a key component of the host mRNA nuclear export machinery, suppresses two endogenous retrovirus-induced mutations and shows suggestive evidence of positive selection. Here we show that Nxf1(CAST) suppresses a specific and frequent class of intracisternal A particle (IAP)-induced mutations, including Ap3d1(mh2J), a model for Hermansky-Pudlak syndrome, and Atcay(hes), an orthologous gene model for Cayman ataxia, among others. The molecular phenotype of suppression includes approximately two-fold increase in the level of correctly-spliced mRNA and a decrease in mutant-specific, alternatively-processed RNA accumulating from the inserted allele. Insertional mutations involving ETn and LINE elements are not suppressed, demonstrating a high degree of specificity to this suppression mechanism. These results implicate Nxf1 in some instances of pre-mRNA processing, demonstrate the useful range of Nxf1(CAST) alleles for manipulating existing mouse models of disease, and specifically imply a low functional threshold for therapeutic benefit in Cayman ataxia.

Alternative Splicing↗
PubMed2026

Comprehensive Somatic Profiling of Gastroenteropancreatic Neuroendocrine Neoplasms.

BACKGROUND: The incidence of gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) is rising, yet their biological heterogeneity and variable response to treatments remain poorly understood. Comprehensive genomic characterization may uncover somatic drivers and inform biomarker-driven therapeutic strategies. METHODS: We retrospectively analyzed clinically ordered next-generation sequencing (NGS) results from tumor samples of 111 patients with confirmed GEP-NENs treated at Johns Hopkins Hospital between 2020 and 2022. Pathogenic and likely pathogenic mutations were identified using OncoKB, CHASMplus, and COSMIC databases. Mutational patterns were correlated with clinical characteristics and overall survival using univariate and multivariate analyses. RESULTS: In this retrospective study of 111 patients with gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs), somatic pathogenic or likely pathogenic mutations were identified in 79% of cases. The most frequent alterations involved TP53 (19%), MEN1 (17%), and chromatin remodeling genes such as DAXX (9%) and ATRX (6%). Notably, we also identified a subset of patients (9%) patients with mutations typically associated with hematologic malignancies. Distinct co-mutation and mutual exclusivity patterns were observed between pancreatic and non-pancreatic NENs. Poorly differentiated or high-grade tumors correlated with mutations in TP53, KRAS, and CDKN2A. Mutations in KRAS, DAXX/ATRX, and hematologic malignancy-associated genes were independently associated with worse overall survival. CONCLUSIONS: This study reveals distinct somatic mutation patterns in GEP-NENs associated with tumor differentiation, grade, primary site, and survival. The identification of hematologic malignancy-associated mutations in a subset of GEP-NENs suggests possible shared molecular phenotypes with poor prognostic implications. The presence of KRAS mutations supports exploring pan-RAS inhibitors as potential therapies in select patients. These findings highlight the clinical utility of genomic profiling in GEP-NENs.

Neuroendocrine neoplasms↗
PubMed2026

Disruption of Polycystin Ciliary Localization and Channel Function by Autosomal Dominant Polycystic Kidney Disease-Causing Polycystin-1 Variants.

KEY POINTS: We developed assays to measure genetic variant effects on polycystin-1, the protein mutated in most autosomal dominant polycystic kidney disease. All tested pathogenic variants disrupted either polycystin-1 ciliary trafficking or channel function. Trafficking and channel function of some pathogenic variants was restored by low temperature culture to promote polycystin folding. BACKGROUND: Autosomal dominant polycystic kidney disease (ADPKD) is the leading monogenic cause of kidney failure and affects millions of people worldwide. Despite the prevalence of ADPKD, limited mechanistic understanding has hindered therapeutic development. Most ADPKD is caused by loss-of-function variants in polycystin-1 (PC1). METHODS: We developed assays that quantify the effect of nontruncating variants on PC1 ciliary localization, membrane trafficking, and polycystin channel function. RESULTS: We evaluated 29 nontruncating variants in PC1 and found that pathogenic variants disrupt two molecular phenotypes: ( 1 ) localization of PC1 at the primary cilium or ( 2 ) polycystin ion channel activity. Ciliary localization of a subset of polycystin variants was restored when cells were cultured at low temperature. A subset of variants with localization restored by low temperature formed functional channels. CONCLUSIONS: This study demonstrated that disruptions in polycystin ciliary trafficking and channel function are common causes of ADPKD. Defects in ciliary trafficking and channel function can be rescued for a subset of pathogenic variants, establishing a foundation for polycystin-targeted therapies in ADPKD.

Polycystic Kidney, Autosomal Dominant↗
PubMed2026

Invasive mucinous adenocarcinoma of the lung: integrating molecular landscape, imaging phenotypes, and translational therapeutic strategies.

Invasive mucinous adenocarcinoma (IMA) of the lung is an uncommon but clinically important subtype of lung adenocarcinoma with distinctive radiologic, histopathologic, and molecular features. Its indolent symptoms, mucin-rich growth pattern, and frequent pneumonia-like or multifocal presentation can obscure early diagnosis and complicate distinction from infection, synchronous primary tumors, and intrapulmonary spread. This review integrates current evidence on the clinical course, imaging phenotypes, diagnostic workflow, histopathologic features, molecular alterations, tumor immune microenvironment, and treatment response patterns of IMA. Emphasis is placed on the relationship between radiologic appearance and underlying mucinous pathology, the clinical significance of spread through air spaces (STAS), and the need for adequate tissue sampling and comprehensive molecular profiling. Compared with non-mucinous lung adenocarcinoma, IMA is enriched for KRAS mutations and selected fusion or receptor alterations, whereas canonical EGFR mutations are less frequent. These biological differences help explain why treatment strategies extrapolated from broader non-small cell lung cancer (NSCLC) populations may be insufficient, particularly for multifocal, pneumonic-type, or advanced disease. Although surgery can provide favorable outcomes in localized disease, systemic therapy remains challenging, and the role of immunotherapy requires further clarification. Future progress will depend on integrated imaging-pathology-genomic models, prospective IMA-specific cohorts, and translational studies aimed at refining classification and developing individualized therapeutic strategies.

Invasive mucinous adenocarcinoma (IMA)↗
PubMed2025

Molecular characterization, clinical phenotype, and neurological outcome of twelve Palestinian children with beta-ketothiolase deficiency: report of two novel variants in the ACAT1 gene.

BACKGROUND: Beta-ketothiolase deficiency (mitochondrial acetoacetyl-CoA thiolase, T2) deficiency (OMIM #203750, *607809) is an autosomal recessive disorder of isoleucine catabolism and ketone body utilization. It is caused by mutations in the ACAT1 gene and characterized by intermittent ketoacidosis episodes triggered by ketogenic stresses, with no clinical symptoms between the episodes. Neurological complications, particularly extrapyramidal signs may occur as sequelae of the ketoacidosis episodes but may also occur without or before any apparent metabolic crisis. T2 deficiency is characterized by the accumulation of isoleucine metabolites, 2methylacetoacetate, 2-methyl-3-hydroxybutyrate, and tiglylglycine, detected in urine organic acids and blood acylcarnitines with or without hypoglycemia. METHODS: This study presents data from twelve patients with T2 deficiency, diagnosed between 7 months and 22 months of age at two tertiary care centers in Palestine. The clinical, biochemical, molecular genetic data, and neurological outcomes are reviewed. RESULTS: We report on twelve patients (6 females and 6 males) from eight families in four different regions of the West Bank and Gaza Strip. All patients were offspring of consanguineous marriages. Ketoacidotic episodes were the predominant manifestations in all patients, and each episode was triggered by either acute gastroenteritis or upper respiratory infections. One patient initially presented with hypotonia and psychomotor delay, later developing a ketoacidotic episode a few months afterward. The characteristic laboratory finding in all patients was the increased urinary excretion of 2-methyl-3-hydroxybutyrate and tiglylglycine. Ten of the twelve patients had favorable outcomes, while two unfortunately passed away at the time of the study. Molecular genetic analysis of the ACAT1 gene was conducted on nine patients from six families, revealing four different variants, two of which were novel. Additionally, a founder mutation was identified in six patients from three families. CONCLUSIONS: The study underscores the critical role of genetic research in unraveling the complexities of beta-ketothiolase deficiency and related disorders. By identifying haplotype blocks, founder mutations, and novel pathogenic variants, researchers can significantly improve diagnostic precision, enhance genetic counseling, and lay the groundwork for developing targeted therapies. We identified two novel variants and a founder mutation, thereby broadening the genetic spectrum of this rare disease.

Humans↗
PubMed1975

A genetic determinant of the phenotypic variance of the molecular weight of low density lipoprotein.

The molecular weight of monodisperse human plasma low densitylipoprotein has been measured in 69 individuals and found to vary over the range of 2.4 to 3.9 X 10-6. By contrast, the molecular weight of low density lipoprotein measured on two separate occasions for specific individuals shows a mean difference of 0.07 X 10-6 and a standard deviation of 0.08 X 10-6; hence low density lipoprotein differing in molecular weight by greater than 0.2 X 10-6 may be considered different macomolecules. The distribution of the molecular weight of low density lipoprotein does not differ as a function of age or sex. Hyperlipemic subjects having monodisperse low density lipoprotein show similar molecular weight distribution to normal subjects, as do subjects with premature coronary artery disease. Family studies reveal a correlation coefficient of 0.82 between average molecular weights of parents and offspring, with significance at 0.01. In order to assess the influence of environment on molecular weight of low density lipoprotein, the correlation coefficient between the fathers' and mothers' low density lipoprotein was measured and no statistically significant correlation was found. These data are interpreted as strong evidence for a genetic determination of molecular weight of low density lipoprotein. A study of individuals in five families yields molecular weight data consistent with a single gene locus genetic mode of inheritance without dominance. The regression coefficient of the mean low denisty lipoprotein parental molecular weight on the offspring molecular weight is 0.30. If the variability of molecular weight is considered as an expression of phenotypic variance, then the regression analysis identified 30% of this phenotypic variance as arising from additive gene action presumably at a single locus. Segregation in the family data is consistent. Since the differences in molecular weight of low density lipoprotein arise from differences in the amount of lipid bound to the apoprotein, it is likely that an additional portion of the phenotypic variance of the molecular weight results from individual variations in the metabolism of low density lipoprotein, which yield differences in lipid content. The individual variation in molecular weight is only approximately 5%; hence those metabolic sequences that influence molecular weight of low density lipoproteins must be precisely controlled.

Adolescent↗
PubMed2026

[Genetic diversity analysis of Forsythia suspensa germplasm resources in Shanxi based on phenotypic traits and SNP molecular markers].

This study aimed to clarify the degree of fruit phenotypic variation and the characteristics of genetic diversity, population structure, and genetic differentiation of Forsythia suspensa resources in Shanxi, providing an important basis for germplasm conservation and breeding of superior varieties. A total of 46 F. suspensa fruits were collected, and 12 agronomic traits were measured and analyzed. The population genetic structure and genetic diversity of F. suspensa germplasm were evaluated using simplified genome sequencing technology. For the five quality traits of the 46 fruits, the Shannon-Wiener index ranged from 0.631 to 1.074, and the Simpson index ranged from 0.379 to 0.560. The seven quantitative traits exhibited abundant genetic variation, with coefficients of variation ranging from 9.764%(fruit shape index) to 45.494%(forsythin content). Principal component analysis reduced the 12 phenotypic traits to four factors, with a cumulative variance contribution of 74.547%. Sequencing data showed mean Q20 and Q30 values of 98.13% and 94.33%, respectively, with an average GC content of 35.95%. After filtering, a total of 12 347 327 high-quality single nucleotide polymorphism(SNP) loci were obtained. Based on these high-quality SNPs, principal component analysis, population structure analysis, and phylogenetic tree construction were carried out. The 46 germplasm resources were divided into four groups; however, grouping showed little relationship with geographic origin, and intermixing occurred among regions. Mantel test revealed a significant but weak positive correlation between phenotypic and genetic distances(r=0.159, P=0.001). At the molecular level, the four groups exhibited moderate genetic diversity overall, and the genetic differentiation index among populations ranged from 0.027 to 0.084, indicating low to moderate differentiation. The rich genetic diversity of the main phenotypic traits provides a solid material basis for screening superior germplasm and genetic breeding of F. suspensa.

Forsythia↗
PubMed2025

Reconstructing the 3D genome organization of Neanderthals reveals that chromatin folding shaped phenotypic and sequence divergence.

Changes in gene regulation were a major driver of the divergence of archaic hominins (AHs)-Neanderthals and Denisovans-and modern humans (MHs). The three-dimensional (3D) folding of the genome is critical for regulating gene expression; however, its role in recent human evolution has not been explored because the degradation of ancient samples does not permit experimental determination of AH 3D genome folding. To fill this gap, we apply novel deep learning methods for inferring 3D genome organization from DNA sequence to Neanderthal, Denisovan, and diverse MH genomes. Using the resulting 3D contact maps across the genome, we identify 167 distinct regions with diverged 3D genome organization between AHs and MHs. We show that these 3D-diverged loci are enriched for genes related to the function and morphology of the eye, supra-orbital ridges, hair, lungs, immune response, and cognition. Despite these specific diverged loci, the 3D genome of AHs and MHs is more similar than expected based on sequence divergence, suggesting that the pressure to maintain 3D genome organization constrained hominin sequence evolution. We also find that 3D genome organization constrained the landscape of AH ancestry in MHs today: regions more tolerant of 3D variation are enriched for introgression in modern Eurasians. Finally, we identify loci where modern Eurasians have inherited novel 3D genome folding patterns from AH ancestors and validate folding differences in a high-frequency locus using Hi-C, revealing a putative molecular mechanism for phenotypes associated with archaic introgression. In summary, our application of deep learning to predict archaic 3D genome organization illustrates the potential of inferring molecular phenotypes from ancient DNA to reveal previously unobservable biological differences.

Journal Article↗
PubMed2026

PathMED: an R toolkit for single-sample molecular scoring and machine learning with omics data.

MOTIVATION: Molecular scoring is a popular approach for studying pathway-level functional alterations with omics data. Using molecular scores for tasks such as single-sample molecular characterisation, phenotype prediction or disease stratification has several advantages compared to using omics data directly. Molecular scores provide biological interpretability and are more generalisable across datasets, facilitating data integration and machine learning applications. However, numerous scoring methods are available through different software packages, and currently there is a lack of tools to easily use these scores for model training and prediction. RESULTS: We developed pathMED, an R/Bioconductor package that unifies various scoring methods in a simple framework. Furthermore, pathMED also contains a machine learning module to train and test models that use the calculated molecular scores to predict clinical outcomes. We demonstrate some of its potential applications in three use cases using public omics data. We showed the generalisability of machine learning models trained on transcriptomic scores in predicting clinical outcomes when deploying on proteomic scores. We also demonstrated the application of transcriptomics scores in predicting breast cancer treatment response and identifying pathways strongly associated to tumour biology and treatment response. Finally, we demonstrated the benefit of integrating a novel gene set dissection step into the analysis pipeline to resolve disease heterogeneity at the pathway level. AVAILABILITY: PathMED is freely available in the Bioconductor repository (https://bioconductor.org/packages/release/bioc/html/pathMED.html). Code to reproduce the analyses is publicly available at https://github.com/GENyO-BioInformatics/pathMED_article.

Software↗
PubMed2026

Spectral-Proteomic Integration Analysis (SPIA) Deciphers Molecular Trajectories of Breast Cancer and Enables Multitarget Therapeutic Assessment.

Raman spectroscopy and mass spectrometry-based proteomics offer deeply complementary yet largely disconnected views of cancer biology: the former provides a label-free, real-time biochemical phenotype, while the latter delivers a quantitative inventory of specific protein effectors. Bridging this gap remains a fundamental challenge in analytical biomedicine. Here, we introduce Spectral-Proteomic Integration Analysis (SPIA)─a novel, data-driven integrative framework that systematically links Raman spectroscopic phenotypes with quantitative proteomic profiles through machine learning and statistical correlation. Using a DMBA-induced rat breast cancer model with and without Toremifene (TOR) intervention, SPIA dynamically maps tumor microenvironment remodeling, capturing progressive collagen deposition and lipid metabolic reprogramming. An SVM classifier trained on Raman spectra achieves exceptional diagnostic accuracy (AUC ≥ 99.0%) and successfully predicts TOR therapeutic response. Proteomic analysis identifies 1,350 differentially expressed proteins, with convergent machine learning feature selection (LASSO, Random Forest, XGBoost) pinpointing core regulators including Luc7l2, Nucb1, Cbx3, and Csnk2a1. Crucially, Spearman correlation analysis between key Raman bands and core DEPs reveals strong, statistically robust associations (median ρ ∼ 0.75 in the 1533-1669 cm-1 region), empirically validating SPIA's core integrative logic. Leveraging this multimodal map, we elucidate a multitarget mechanism for TOR involving concurrent suppression of collagen deposition and correction of aberrant lipid metabolism. SPIA establishes a powerful, generalizable paradigm for integrating phenotypic and molecular data, with broad implications for biomarker discovery, drug mechanism elucidation, and precision oncology.

Animals↗
PubMed1976

A molecular analysis of transductional marker rescue involving P-group plasmids in Pseudomonas aeruginosa.

The molecular properties of the P-group plasmids R26, R527 and R18-18- (a carbenicillin-sensitive derivative of R18) have been compared with those of RP1. R18-18 and RPI have a MW about 38 X 10(6) daltons, and R26 and R527 of 52 X 10(6) daltons (determined from contour lengths). All three plasmids have a bouyant density similar to that of RPI (1.719 g/cm3, 60% GN. From their molecular and phenotypic similarities, these plasmids probably represent two pairs of identical or closely similar elements. Resistant bacteria are not recovered following F116L-mediated transduction of R26 (or R527), and this correlates with the plasmids' larger size (phage genome=40 X 10(6) daltons). Fragments of R26 are, however, transduced and their resistance determinants may be "rescued" by recombination if the recipient harbours R1818. Such events are accompanied by an increase in the size of the recipient plasmid from 38 X 10(6) to 52 X 10(6) daltons following inheritance of the resistance determinants Sm Su Gm Hg, but not Cb. Thus, Sm Su Gm Hg are encoded in a DNA segment of MW about 14 X 10(6) daltons which apparently has no homologous region on R18-18. Since a piece of DNA of this MW also corresponds to the difference in size between R26 and R18-18, it is possible that the former is derived from an RPI-like element which has acquired these additional resistance determinants.

Carbenicillin↗
PubMed2024

Sparse spectral graph analysis and its application to gastric cancer drug resistance-specific molecular interplays identification.

Uncovering acquired drug resistance mechanisms has garnered considerable attention as drug resistance leads to treatment failure and death in patients with cancer. Although several bioinformatics studies developed various computational methodologies to uncover the drug resistance mechanisms in cancer chemotherapy, most studies were based on individual or differential gene expression analysis. However the single gene-based analysis is not enough, because perturbations in complex molecular networks are involved in anti-cancer drug resistance mechanisms. The main goal of this study is to reveal crucial molecular interplay that plays key roles in mechanism underlying acquired gastric cancer drug resistance. To uncover the mechanism and molecular characteristics of drug resistance, we propose a novel computational strategy that identified the differentially regulated gene networks. Our method measures dissimilarity of networks based on the eigenvalues of the Laplacian matrix. Especially, our strategy determined the networks' eigenstructure based on sparse eigen loadings, thus, the only crucial features to describe the graph structure are involved in the eigenanalysis without noise disturbance. We incorporated the network biology knowledge into eigenanalysis based on the network-constrained regularization. Therefore, we can achieve a biologically reliable interpretation of the differentially regulated gene network identification. Monte Carlo simulations show the outstanding performances of the proposed methodology for differentially regulated gene network identification. We applied our strategy to gastric cancer drug-resistant-specific molecular interplays and related markers. The identified drug resistance markers are verified through the literature. Our results suggest that the suppression and/or induction of COL4A1, PXDN and TGFBI and their molecular interplays enriched in the Extracellular-related pathways may provide crucial clues to enhance the chemosensitivity of gastric cancer. The developed strategy will be a useful tool to identify phenotype-specific molecular characteristics that can provide essential clues to uncover the complex cancer mechanism.

Stomach Neoplasms↗
PubMed2024

Quantitative natural history modeling of HPDL-related disease based on cross-sectional data reveals genotype-phenotype correlations.

PURPOSE: Biallelic HPDL variants have been identified as the cause of a progressive childhood-onset movement disorder, with a broad clinical spectrum from severe neurodevelopmental disorder to juvenile-onset pure hereditary spastic paraplegia type 83. This study aims at delineating the geno- and phenotypic spectra of patients with HPDL-related disease, quantitatively modeling the natural history, and uncovering genotype-phenotype associations. METHODS: A cross-sectional analysis of 90 published and 1 novel case was performed, using a Human-Phenotype-Ontology-based approach. Unsupervised phenotypic clustering was used alongside in silico analyses to identify distinct patient subgroups. RESULTS: The study models the natural history of the HPDL-related disease in a global cohort, clarifying the molecular and phenotypic spectrum and identifying 3 distinct subgroups characterized by differences in onset, clinical trajectories, and survival. It establishes genotype-phenotype associations, showing that the presence of moderately pathogenic missense variants in 1 allele leads to a milder, spastic paraplegic phenotype with later disease onset, whereas biallelic, highly pathogenic missense or truncating variants are associated with a more severe phenotype and reduced life span. CONCLUSION: Quantitative and unbiased natural history modeling in HPDL-related disease reveals significant genotype-phenotype associations, providing a foundation for variant interpretation, anticipatory guidance, and choice of outcome measures in future prospective and functional studies.

Humans↗
PubMed2026

A Novel De Novo STAG1 Variant at the RAD21 Binding Interface Is Associated With Hypoglycemia, Recurrent Fever, Immunodeficiency and Features of Classical Cohesinopathies.

The cohesin complex, composed of SMC1, SMC3, RAD21, and STAG1/STAG2, is essential for chromosome cohesion, DNA repair, and transcriptional regulation. Pathogenic variants in cohesin components cause cohesinopathies. The classical characteristics of cohesinopathies include developmental delay (DD), intellectual disability (ID), feeding difficulties, hypotonia, short stature, hearing loss, and dysmorphic features. Here, we present a 5-year-old boy with classical cohesinopathy features, including DD/ID and feeding difficulties, along with non-classical features such as hypoglycemia, recurrent fever, and immunodeficiency. Trio exome sequencing identified a novel de novo missense variant of uncertain significance (NM_005862.3:c.643G>A(p.Val215Ile)) in the STAG1 gene. The variant localizes to the RAD21 interaction interface, and molecular dynamics (MD) simulations revealed conformational changes comparable to other STAG1 variants reported as likely pathogenic in patients, supporting a deleterious effect which may disrupt the STAG1-RAD21 interaction interface. This case expands the phenotypic and molecular spectrum of STAG1-related cohesinopathy and advances our understanding of the disease mechanism.

STAG1↗
PubMed2022

TTC5 syndrome: Clinical and molecular spectrum of a severe and recognizable condition.

Biallelic mutations in the TTC5 gene have been associated with autosomal recessive intellectual disability (ARID) and subsequently with an ID syndrome including severe speech impairment, cerebral atrophy, and hypotonia as clinical cornerstones. A TTC5 role in IDs has been proposed based on the physical interaction of TTC5 with p300, and possibly reducing p300 co-activator complex activity, similarly to what was observed in Menke-Hennekam 1 and 2 patients (MKHK1 and 2) carrying, respectively, mutations in exon 30 and 31 of CREBBP and EP300, which code for the TTC5-binding region. Recently, TTC5-related brain malformation has been linked to tubulinopathies due to the function of TTC5 in tubulins' dynamics. We reported seven new patients with novel or recurrent TTC5 variants. The deep characterization of the molecular and phenotypic spectrum confirmed TTC5-related disorder as a recognizable, very severe neurodevelopmental syndrome. In addition, other relevant clinical aspects, including a severe pre- and postnatal growth retardation, cryptorchidism, and epilepsy, have emerged from the reversal phenotype approach and the review of already published TTC5 cases. Microcephaly and facial dysmorphism resulted in being less variable than that documented before. The TTC5 clinical features have been compared with MKHK1 published cases in the hypothesis that clinical overlap in some characteristics of the two conditions was related to the common p300 molecular pathway.

Exons↗
PubMed2026

Whole genome and exome sequencing of pancreatic neuroendocrine tumour to investigate PRRT response.

Patients with pancreatic neuroendocrine tumours (PNETs) often have similar baseline clinical characteristics, including grade and molecular imaging phenotype, yet have highly variable responses to peptide receptor radionuclide therapy (PRRT). To identify genomic alterations and mutational patterns associated with PRRT treatment response and acquired somatic changes following PRRT exposure, whole genome or exome sequencing was applied to 40 PNET samples from 32 patients, including eight paired pre- or post-PRRT samples. The genomic profile of tumours reflected the known mutational landscape of PNET with MEN1 (34%), ATRX/DAXX (47%) alterations and a recurrent pattern of aneuploidy (38%) detected. A recurrent PSIP1::TBL1X fusion of unknown function was also identified in four tumours. The disease control rate following PRRT using RECIST1.1 and molecular imaging criteria was 88% (28/32). No mutational features were found to be statistically associated with progression-free survival. There was no significant increase in tumour mutational burden in the post-PRRT tumours, nor recurrent emergent mutational changes in cancer driver genes to explain progression to higher-grade disease, when observed. However, a small indel signature (ID8) previously associated with DNA damage repair by non-homologous end joining (NHEJ) was higher in PRRT-exposed compared with PRRT-naive samples (23.8 vs 4.8%, respectively; P < 0.001). Thus, comprehensive DNA analysis of pancreatic NETs did not identify biomarkers predictive of PRRT response nor evidence for high-level PRRT-induced genomic instability or hypermutation, yet mutation signature analysis supports NHEJ as being important for DNA repair and survival of neuroendocrine cells following exposure to beta-particle radiation.

Humans↗
PubMed2026

Biallelic VPS41 Variants in Autosomal Recessive Spinocerebellar Ataxia 29 Resolved by Long-Read Sequencing and RNA Analysis.

BACKGROUND: Biallelic variants in VPS41, encoding a subunit of the HOPS complex, cause autosomal recessive spinocerebellar ataxia 29 (SCAR29), a rare neurodevelopmental disorder with an incompletely defined phenotypic and molecular spectrum. METHODS: We investigated a 24-year-old man with cerebellar ataxia, hypotonia, and intellectual disability. Exome sequencing identified four candidate VPS41 variants. Because maternal DNA was unavailable, long-read genome sequencing was performed to determine allelic configuration, followed by RNA and protein analyses. RESULTS: In addition to typical SCAR29 features, the patient showed previously unreported findings, including swan-neck deformities and pes cavus. Long-read genome sequencing demonstrated that two VPS41 variants were in trans. RNA analysis revealed distinct splicing consequences: one allele produced an out-of-frame transcript predicted to undergo nonsense-mediated decay, whereas the other generated an in-frame exon-skipped transcript. These complementary defects reduced VPS41 expression at both transcript and protein levels, supporting pathogenicity and variant reclassification. CONCLUSION: Our findings expand the phenotypic spectrum of VPS41-related disease and highlight the value of long-read allelic resolution in clarifying pathogenic mechanisms in rare genetic disorders.

Humans↗