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Results for “Variant Burden Testing”

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PubMed2026

Comprehensive analysis of de novo variants across 2,497 orofacial cleft trios reveals novel genetic drivers of disease.

BACKGROUND: Orofacial clefts (OFCs) and other palate abnormalities (PAs) are among the most common birth defects worldwide and are characterized by the abnormal formation of the lip and/or palate. Genetic studies have traditionally classified OFC cases as either syndromic, involving OFCs alongside other congenital anomalies, or nonsyndromic, which represent the majority of cases and occur in isolation. Emerging genomic evidence indicates that genes traditionally associated with syndromic forms of OFC can also harbor variants contributing to isolated cases, challenging the notion of a strict dichotomy between these categories and supporting their integration for gene discovery. METHODS: In this study, we applied multiple analytic approaches to characterize the genetic architecture of OFC and PAs by integrating genomic data from 2,497 trios with probands diagnosed with an OFC (n=2,080) or PA (n=417). We compared these findings across OFC subtypes and syndromic status with those from 5,515 control trios to identify enriched biological pathways and mechanisms and to prioritize candidate genes using variant burden testing. RESULTS: We observed a significant enrichment of de novo protein-truncating and damaging missense variants in cases compared to controls (OR = 2.17, p = 1.21×10-32), with particularly strong signals in biologically relevant gene sets involving OFC-associated, constrained, Mendelian disorder, and mouse candidate genes. Variant burden testing identified 39 OFC risk genes at FDR ≤ 0.05, which we then integrated with 593 established OFC genes to interrogate the functional underpinnings of OFC via network analysis. This analysis revealed 309 high-order interactor genes not previously associated with OFC. Notably, this OFC network clustered into ten distinct biological pathways, with nucleosome-associated genes showing significant enrichment among cases in our cohort (OR = 14.8, p = 8.1×10-4). In a final integrative step, we combined evidence across all analyses to nominate 231 candidate genes, 32 of which contained at least two deleterious de novo variants in our cohort. CONCLUSIONS: These findings underscore the value of integrating diverse OFC and PA subtypes, syndromic status, and variant classes to elucidate the genetic architecture of these disorders, highlighting both phenotypic expansion of known disease genes and the emergence of novel gene-phenotype associations.

De Novo Variant Enrichment↗

PubMed2026

Integrating multi-ancestry common and rare variant mapping accelerates therapeutic target discovery.

Integrating human genetics into therapeutic discovery accelerates drug development. However, ancestral biases in historical cohorts have left critical functional variation largely uncharted. Here, we leverage the diverse NIH All of Us Research Program to conduct comprehensive common- and rare-variant association analyses for 624 quantitative traits across 369,655 ancestrally diverse individuals. We identified 6,181 genome-wide significant locus-trait associations (526 novel) and 416 gene-trait associations (105 novel) via rare-variant burden testing. By integrating fine-mapping with computational variant-effect predictors, we systematically prioritized rare, likely causal variants driving these signals. Jointly modeling common and rare variation with protein-class annotations significantly improved the identification of known drug targets compared to common-variant analysis alone. Notably, we identified NRG4 as a high-confidence candidate therapeutic target for preserving kidney function. Our findings demonstrate that characterization of rare and common variation across diverse populations enhances causal gene discovery and identifies novel, actionable therapeutic targets.

Journal Article↗

PubMed2025

The impact of common and rare genetic variants on bradyarrhythmia development.

To broaden our understanding of bradyarrhythmias and conduction disease, we performed common variant genome-wide association analyses in up to 1.3 million individuals and rare variant burden testing in 460,000 individuals for sinus node dysfunction (SND), distal conduction disease (DCD) and pacemaker (PM) implantation. We identified 13, 31 and 21 common variant loci for SND, DCD and PM, respectively. Four well-known loci (SCN5A/SCN10A, CCDC141, TBX20 and CAMK2D) were shared for SND and DCD, while others were more specific for SND or DCD. SND and DCD showed a moderate genetic correlation (rg = 0.63). Cardiomyocyte-expressed genes were enriched for contributions to DCD heritability. Rare-variant analyses implicated LMNA for all bradyarrhythmia phenotypes, SMAD6 and SCN5A for DCD and TTN, MYBPC3 and SCN5A for PM. These results show that variation in multiple genetic pathways (for example, ion channel function, cardiac developmental programs, sarcomeric structure and cellular homeostasis) appear critical to the development of bradyarrhythmias.

Humans↗

PubMed2025

HAP-SAMPLE2: data-based resampling for association studies with admixture.

MOTIVATION: HAP-SAMPLE2 extends the functionality of the original HAP-SAMPLE tool for simulating genotype-phenotype data, now with features to handle population admixture and rare variant analysis. It allows users to define parameters such as disease prevalence and allele effect sizes for both common and rare variant simulations. RESULTS: HAP-SAMPLE2 provides an efficient means for simulating complex datasets, suitable for large-scale projects like the 1000 Genomes Project. Its capabilities for population admixture allow users to create admixed populations or preserve substructures while introducing novel variation through artificial recombination. Additionally, the tool supports burden testing for rare variants using fixed and Madsen-Browning weighting schemes. AVAILABILITY AND IMPLEMENTATION: The software, along with a detailed vignette, is available on GitHub: https://github.com/M3dical/HAPSAMPLE2.

Software↗

PubMed2025

Monogenic disorders associated with motor speech phenotypes in children and adolescents undergoing clinical exome sequencing.

PURPOSE: Prior studies investigating the genetic architecture of pediatric motor speech disorders (MSDs) have been limited by small sample sizes and an exclusive focus on apraxia. We aimed to identify pathogenic genomic variants associated with MSDs in a large pediatric population referred for exome sequencing (ES). METHODS: We identified pediatric patients with MSDs who had clinical ES between 2012 and 2022. The rate of pathogenic/likely pathogenic (P/LP) findings considered causative of the MSD phenotype was determined and delineated by sex and neurodevelopmental comorbidity. Gene-based burden testing compared the rate of P/LP variants in each gene in MSD cases with a comparison clinical ES cohort. RESULTS: Positive diagnostic results were detected in 527 of 2004 (26.3%) patients with MSDs, with higher diagnostic rates in females and individuals with neurodevelopmental comorbidities. P/LP sequence variants were detected in 262 genes. Gene-based case-referent burden analysis revealed that 30 genes were nominally associated with MSDs, 2 of which (SETBP1 and ADCY5) survived exome-wide correction. CONCLUSION: Over 25% of patients with MSDs were found to harbor P/LP variants in 262 genes, many of which have not previously been associated with MSDs. Potential clinical implications include early implementation of intensive speech therapy for children diagnosed with monogenic causes of MSDs.

Humans↗

PubMed2025

Rare damaging CCR2 variants are associated with lower lifetime cardiovascular risk.

BACKGROUND: Previous work has shown a role of CCL2, a key chemokine governing monocyte trafficking, in atherosclerosis. However, it remains unknown whether targeting CCR2, the cognate receptor of CCL2, provides protection against human atherosclerotic cardiovascular disease. METHODS: Computationally predicted damaging or loss-of-function (REVEL > 0.5) variants within CCR2 were detected in whole-exome-sequencing data from 454,775 UK Biobank participants and tested for association with cardiovascular endpoints in gene-burden tests. Given the key role of CCR2 in monocyte mobilization, variants associated with lower monocyte count were prioritized for experimental validation. The response to CCL2 of human cells transfected with these variants was tested in migration and cAMP assays. Validated damaging variants were tested for association with cardiovascular endpoints, atherosclerosis burden, and vascular risk factors. Significant associations were replicated in six independent datasets (n = 1,062,595). RESULTS: Carriers of 45 predicted damaging or loss-of-function CCR2 variants (n = 787 individuals) were at lower risk of myocardial infarction and coronary artery disease. One of these variants (M249K, n = 585, 0.15% of European ancestry individuals) was associated with lower monocyte count and with both decreased downstream signaling and chemoattraction in response to CCL2. While M249K showed no association with conventional vascular risk factors, it was consistently associated with a lower risk of myocardial infarction (odds ratio [OR]: 0.66, 95% confidence interval [CI]: 0.54-0.81, p = 6.1 × 10-5) and coronary artery disease (OR: 0.74, 95%CI: 0.63-0.87, p = 2.9 × 10-4) in the UK Biobank and in six replication cohorts. In a phenome-wide association study, there was no evidence of a higher risk of infections among M249K carriers. CONCLUSIONS: Carriers of an experimentally confirmed damaging CCR2 variant are at a lower lifetime risk of myocardial infarction and coronary artery disease without carrying a higher risk of infections. Our findings provide genetic support for the translational potential of CCR2-targeting as an atheroprotective approach.

Humans↗

PubMed2025

Imprecision medicine: Systematic gaps in reporting variants of uncertain significance (VUS) and their reclassifications.

PURPOSE: Variants of uncertain significance (VUS) are frequently encountered during clinical genetic testing. To explore the clinical burden of VUS, we developed the Brotman Baty Institute Clinical Variant Database, which is an electronic health record (EHR)-linked database of clinical germline genetic variant information from patients with rare genetic disorders seen at 2 tertiary academic medical centers. METHODS: We retrospectively reviewed EHRs and genetic testing reports from 5158 patients seen across diverse adult genetics practices at these institutions from 2015 to 2024. We also compared these EHR-based variant classifications with those in ClinVar. RESULTS: The number of reported VUS relative to pathogenic or likely pathogenic variants can vary by over 14-fold depending on the primary indication for genetic testing and 3-fold depending on self-reported race. Furthermore, at least 1.6% of variant classifications used in the EHR for clinical care are outdated based on ClinVar variant classifications, including 26 instances in which the testing lab updated ClinVar, but the reclassification was never communicated to the patient. CONCLUSION: Our findings reveal that the clinical burden of VUS in adult medical genetics is unequally distributed across patients. We also highlight a deficiency in existing systems for communicating variant reclassifications to ClinVar, patients, and providers.

Humans↗

PubMed2026

Tackling non-canonical splicing in arrhythmogenic cardiomyopathy to reduce the uncertain significance variants burden.

BACKGROUND: Splice-altering variants (SAVs), particularly those outside canonical splice sites, are an underappreciated contributor to inherited cardiovascular diseases. In arrhythmogenic cardiomyopathy (ACM), these variants frequently remain classified as of uncertain significance (VUS) due to limited predictive power and lack of transcript-level evidence, constraining genetic yield and clinical management. Our study aimed to determine the functional impact of SAVs in ACM genes and refine their classification using ACMG/AMP and ClinGen SVI criteria. METHODS: SAVs identified in 200 ACM probands underwent SpliceAI prediction, GTEx cardiac exon-usage annotation, and functional assessment using pSPL3-based minigene assays. Aberrant transcripts were quantified using Percent Splicing Alteration (PSA). Segregation data and ACMG/AMP criteria refined by ClinGen SVI were applied to integrate functional and clinical evidence for classification. RESULTS: Aberrant splicing was confirmed in 9/20 variants (45%), including synonymous, missense, and non-canonical intronic changes. SpliceAI scores correlated strongly with PSA values (R²=0.86). Case-control burden testing revealed significant enrichment of splice-altering variants in DSP, DSG2, DSC2 and FLNC. Integrating predictive algorithms with experimental validation and segregation analysis markedly enhances reclassification of 16/20 variants (80%). CONCLUSION: Splicing defects beyond canonical sites significantly shape ACM genetic landscape. Integrating predictive models with experimental validation clarifies uncertain variants bridging the gap between genomic uncertainty and clinical decision-making.

Humans↗

PubMed2026

Large-scale admixture mapping in the All of Us Research Program improves the characterization of cross-population phenotypic differences.

Admixed individuals have been understudied in medical research largely due to their complex genetic ancestries. However, the consideration of admixture can identify ancestry-enriched genetic associations, delineating genetic underpinnings of cross-population phenotypic variation. Here, we performed admixture mapping in individuals with inferred admixture from African and European populations (N = 48,921). Across 22 traits, we identified 71 ancestry-trait associations, including loci where ancestral haplotypes explained phenotypic variation yet were missed by single-variant association testing due to their stricter multiple testing burden. One such locus where inferred local AFR ancestries are associated with increased hemoglobin A1c (HbA1c) was 12q14.3, highlighting its potential role in explaining differences between populations. Together, our results expand upon the phenotypic differences between populations and characterize loci where genetic ancestries play a critical role in the architecture of disease.

Humans↗

PubMed2024

Association analysis of mitochondrial DNA heteroplasmic variants: Methods and application.

We rigorously assessed a comprehensive association testing framework for heteroplasmy, employing both simulated and real-world data. This framework employed a variant allele fraction (VAF) threshold and harnessed multiple gene-based tests for robust identification and association testing of heteroplasmy. Our simulation studies demonstrated that gene-based tests maintained an appropriate type I error rate at α = 0.001. Notably, when 5 % or more heteroplasmic variants within a target region were linked to an outcome, burden-extension tests (including the adaptive burden test, variable threshold burden test, and z-score weighting burden test) outperformed the sequence kernel association test (SKAT) and the original burden test. Applying this framework, we conducted association analyses on whole-blood derived heteroplasmy in 17,507 individuals of African and European ancestries (31 % of African Ancestry, mean age of 62, with 58 % women) with whole genome sequencing data. We performed both cohort- and ancestry-specific association analyses, followed by meta-analysis on both pooled samples and within each ancestry group. Our results suggest that mtDNA-encoded genes/regions are likely to exhibit varying rates in somatic aging, with the notably strong associations observed between heteroplasmy in the RNR1 and RNR2 genes (p < 0.001) and advance aging by the Original Burden test. In contrast, SKAT identified significant associations (p < 0.001) between diabetes and the aggregated effects of heteroplasmy in several protein-coding genes. Further research is warranted to validate these findings. In summary, our proposed statistical framework represents a valuable tool for facilitating association testing of heteroplasmy with disease traits in large human populations.

Humans↗

PubMed2025

Gene dosage architecture across complex traits.

UNLABELLED: Copy number variants (CNVs) have large effects on complex traits, but they are rare and remain challenging to study. As a result, our understanding of biological functions linking gene dosage to complex traits remains limited, and whether these functions sensitive to gene dosage are similar to those underlying the effects of rare single nucleotide variants (SNVs) and common variants remains unknown. METHODS: We developed FunBurd, a functional burden analysis, to test the association of CNVs aggregated within functional gene sets. We applied this approach in 500,000 individuals from the UK Biobank to associate 43 complex traits with CNVs disrupting 172 gene sets across tissues and cell types. We compared CNV findings with those from common variants and LoF (Loss of Function) SNVs in the same cohort using the same functional gene sets. RESULTS: All 43 traits showed FDR significant associations with CNVs. Brain tissue and neuronal cell-types showed the highest levels of pleiotropy. Most of the functional gene set associations could, in part, be explained by genetic constraint, except for brain related processes. Shared genetic contributions between pairs of traits were concordant across types of variants, but on average 2-fold higher, for rare CNVs and SNVs compared to common variants.Functional enrichment across traits found limited overlap between CNVs and common variants. Moreover, the effects of deletions and duplications were negatively correlated for most traits.In conclusion, we present new methods to separate the contributions of genetic constraint and gene function to the associations of CNVs with complex traits. Overall, the functional convergence between different types of variants -even between deletions and duplications-remains limited.

Journal Article↗

PubMed2026

Determinants of functional burden pleiotropy and gene dosage responses across human traits.

Pleiotropic and monotonic effects of gene dosage are central to understanding comorbidities in developmental pediatric and psychiatric disorders, yet the underlying biological processes are not well characterized. Here we develop a functional burden analysis to investigate the association of all protein-coding copy-number variants, genome-wide, with 43 complex traits in approximately 500,000 UK Biobank participants. We test variant associations disrupting 172 tissue or cell-type gene sets, finding associations for all traits, which we replicate in the All of Us cohort. Functional burden pleiotropy, defined as the number of traits significantly associated with a gene set, correlates with genetic constraint and is higher for brain than non-brain functions, even after normalizing for genetic constraint. Levels of pleiotropy, measured by burden correlation, are similar in deletions and loss-of-function single-nucleotide variants, and higher than in common variants and duplications. Most gene dosage responses are non-monotonic, with deletions and duplications showing same-direction effects, and monotonic responses decrease with genetic constraint. We observe associations between functional gene sets and traits for either deletions or duplications, but rarely both, with negatively correlated effect sizes. Together, these results link genetic constraint and brain-specific mechanisms to the whole-body multimorbidity of neurodevelopmental and psychiatric conditions.

Humans↗

PubMed2026

[State Changes and Stability Grading of Driver Genes in Non-small Cell Lung Cancer Based on Repeated NGS Testing].

BACKGROUND: Next-generation sequencing (NGS)-based driver gene testing has become a routine component of molecular subtyping and precision therapy for non-small cell lung cancer (NSCLC). Dynamic genomic monitoring facilitates early detection of resistance-related molecular alterations and informs timely therapeutic adjustments. However, standardized criteria for evaluating the stability of serial NGS testing are currently lacking, and the applicability of NGS using formalin-fixed paraffin-embedded (FFPE) specimens for dynamic monitoring remains poorly defined. This study aims to establish a stability grading system for driver gene status alterations based on repeated NGS testing, and to provide evidence-based support for clinical repeat biopsy strategies. METHODS: Data from 1232 patients with NSCLC who underwent two or more NGS tests on FFPE tissue specimens at Beijing Chest Hospital between June 2019 and April 2026 were collected retrospectively. Patients with an interval of ≥4 months between the initial and last tests were included to ensure the representativeness of temporal analysis, resulting in a main analysis cohort of 942 patients. The Kappa consistency test was used to evaluate the state stability of nine core driver genes [epidermal growth factor receptor (EGFR), Kirsten rat sarcoma viral oncogene homolog (KRAS), anaplastic lymphoma kinase (ALK), ROS proto-oncogene 1, receptor tyrosine kinase (ROS1), mesenchymal‑epithelial transition factor (MET), rearranged during transfection (RET), v-raf murine sarcoma viral oncogene homolog B1 (BRAF), erb‑b2 receptor tyrosine kinase 2 (ERBB2), and phosphatidylinositol‑4,5‑bisphosphate 3‑kinase catalytic subunit alpha (PIK3CA)] and to construct a five‑level grading system. Paired variant allele frequency (VAF) differences were compared using the Wilcoxon signed‑rank test. Independent influencing factors for mutation accumulation were identified by binary Logistic regression. RESULTS: The state stability of the nine genes was classified into five levels: EGFR showed high stability (Kappa=0.838), ROS1/ALK/KRAS good stability, BRAF/PIK3CA/RET moderate stability, and ERBB2 low stability, and MET showed high instability. MET exhibited the highest rate of state change (9.3%) with a raw observed agreement of 90.7%. Its Kappa value (0.172) was influenced by the low prevalence (3.7%) compression effect and should therefore be interpreted alongside the observed agreement (90.7%) and the prevalence-adjusted and bias-adjusted Kappa (PABAK). The VAF of PIK3CA increased significantly (P=0.005). T790M positivity increased from 5.8% to 10.8%, and 30 new C797S mutations were detected at the last test (13 with T790M, 17 without). The overall rate of new driver gene variants in the main cohort was 18.0%. Binary Logistic regression showed that a lower number of initial mutated genes was the only independent predictor of new variants [odds ratio (OR)=0.399, P<0.001], while sex and detection interval showed no independent association. CONCLUSIONS: A five level stability grading system for state changes of driver genes in NSCLC based on repeated NGS testing has been established. MET showed the most frequent state changes, which should be interpreted in conjunction with the prevalence effect. The VAF increase of PIK3CA is an observational finding, and its clinical significance requires further prospective validation. A lower initial mutation burden may reflect tumor clonal complexity and was associated with a higher likelihood of subsequent acquisition of new variants. FFPE based NGS is applicable for repeated testing at clinical treatment decision nodes.

Humans↗

PubMed2026

Paired Exome-Based Comprehensive Genomic Profiling and Germline Genetic Testing for Unselected Patients With Colorectal Cancer in a Multicenter Prospective Study.

BACKGROUND AND AIMS: Comprehensive genomic profiling (CGP) for tumors and germline genetic testing (GGT) inform precision therapy and clinical management of patients with colorectal cancer (CRC), and evidence is growing in support of universal paired CGP-GGT patient testing. However, the utility of combining CGP and GGT for early-stage CRC (ESC) and early-onset CRC (EOC) is unclear. METHODS: We performed a prospective, multisite study featuring GGT using an 80+ gene next-generation sequencing platform and exome-based CGP among CRC patients (unselected for age, stage, family history) receiving care at Mayo Clinic Cancer Centers between April 1, 2018, and March 31, 2020. RESULTS: A total of 150 CRC patients had GGT and exome-based CGP performed. ESC patients had an enrichment of high microsatellite instability and high tumor mutation burden. High microsatellite instability was also enriched in those with smoking history, and in tumors with mutated BRAF, homologous recombination deficiency, or at least 1 variant in the rat sarcoma virus pathway. Moreover, patients with smoking history were enriched in BRAF and other Tier 1 or 2 variants overall. Sixteen percent of patients harbored a pathogenic germline variant, most frequent being in Lynch syndrome genes. Paired GGT and CGP testing had high rates of clinically significant findings (≈70%) with the most frequent being high tumor mutation burden status. Pathway and mutational signature analysis revealed frequent CGP mutations in DNA repair and cell cycle pathways. CONCLUSION: These data suggest that universal, combined GGT-CGP increases clinical utility for EOC and ESC patients. This is key for EOC patients who tend to experience poorer outcomes. CGP-GGT expedites germline resolution for tumor mutations in hereditary cancer genes, reducing delays and facilitating identification of relevant therapies, clinical trials, and management recommendations.

Colorectal Cancer↗

PubMed2025

Meta-evolutionary exome analysis identifies novel type 2 diabetes mellitus genes in the UK Biobank and all of us.

Type 2 diabetes mellitus (T2DM) risk is heavily influenced by genetics, yet current association tests have explained only parts of its heritability. We developed MEVA (Meta-Evolutionary Action), a meta-analytic framework that integrates three complementary methods-EAML, Sigma-Diff, and GeneEMBED-to assess the functional burden of protein-coding variants using evolutionary data. MEVA was applied to exome data from 28,115 T2DM cases and 28,115 controls in the UK Biobank (UKB), identifying 101 genes (p < 1e-5). MEVA outperformed its component methods, each of which substantially outperformed a conventional burden test (MAGMA), in recovering known T2DM genes (AUROC = 0.925) and maintaining robustness in progressively smaller cohorts (AUROC = 0.917). MEVA showed significant enrichment for T2DM-related loci (p = 6.8e-10, p = 2.0e-34), protein interactions (z = 4.6, z = 4.2), pathways (p = 1.3e-6, z = 2.0), phenotypes (p = 1.3e-21, z = 9.1), and literature mentions (z = 7.2). Replication in 16,915 T2DM cases and 16,915 controls from All of Us (AoU) yielded 99 genes (p < 1e-5), 23 of which were also recovered in the UKB cohort - far exceeding random chance. These included established genes (SLC30A8, WFS1, HNF1A) and less-characterized candidates (NRIP1, ADAM30, CALCOCO2, TUBB1, ZFP36L2, WDR90). Notably, NRIP1 loss-of-function variants were associated with increased T2DM risk in both the UKB (OR = 1.09, FDR = 5.4e-4) and AoU (OR = 1.09, FDR = 0.046), and TUBB1 and CALCOCO2 gain-of-function variants showed consistent risk effects (FDR < 0.05). Pathway analyses revealed convergence on endoplasmic reticulum chaperone complexes (FDR = 0.02) and Hippo signaling (FDR = 8.5e-4). Finally, all 177 candidate genes were functionally prioritized using ten orthogonal criteria to guide experimental follow-up. These results demonstrate that combining complementary, impact-aware association tests increases sensitivity, improves replication, and expands the catalog of genetic risk factors for T2DM.

Humans↗

PubMed2025

Multiple Psychiatric Traits Enriched for Brain Tissues in the Early Postpartum Period.

BACKGROUND: The perinatal period is a high-risk time for onset of various psychiatric disorders. However, it is unclear how genetic risk factors for these disorders interact with biological changes associated with pregnancy and postpartum. This study evaluates whether psychiatric genome-wide association study (GWAS) results are enriched within various brain regions across the perinatal period. METHODS: Tissue-specific enrichment analyses were conducted to estimate the potential impact of GWAS loci on transcriptional changes in the brain across the perinatal period. GWAS summary statistics were obtained for 26 psychiatric phenotypes. RNA-sequencing data was acquired from four brain regions (hypothalamus, hippocampus, cerebellum, and neocortex) in mice at six timepoints (virgin, 14- and 16-days post-conception, and 1-, 3- and 10-days postpartum). RESULTS: Hippocampus and neocortex in the early postpartum period are significantly enriched (q-value < 0.05) for genetic variants associated with schizophrenia (SCZ), bipolar disorder (BD), depressive symptoms, and major depressive disorder with suicidal features. The most significant enrichment occurred in the neocortex for SCZ and BD, peaking at postpartum day 1 (SCZ p-value = 3.85 × 10-8; BD p-value = 6.65 × 10-5). In the hippocampus, BD and SCZ were enriched at postpartum day 1 (SCZ p-value = 3.27 × 10-3; BD p-value = 4.33 × 10-3). No enrichment was observed in cerebellum or hypothalamus for any of the psychiatric traits tested. CONCLUSIONS: The results accord with previous epidemiological studies and provide context in which to interpret GWAS results. Understanding the burden of genetic variants across the perinatal period may help prioritise pathways underlying onset of psychiatric disorders outside of pregnancy and postpartum periods.

Journal Article↗

PubMed2026

Analysis of structure and conservation for supporting functional evaluation of PMS2 missense variants.

Germline defects in mismatch repair (MMR) genes are known to significantly increase the risk of developing certain types of cancers, notably colorectal and endometrial cancers. These conditions are characterized under Lynch syndrome. Accurate diagnosis of this predisposition, along with meaningful predictive testing for family members, necessitates the identification of pathogenic variants. However, classifying small coding genetic variants identified in cancer patients is very challenging, specifically in the case of PMS2 variants, since PMS2 pathogenic variants display a lower penetrance and less severe phenotype and therefore a lower tumor burden in affected families. We have assembled clinical data on four PMS2 missense variants of uncertain significance (VUS) identified in 23 patients (p.(Asp286Gly), p.(Asn335Ser), p.(Ile679Thr) and p.(Arg799Trp)). For these variants, functional testing was performed (RNA splicing, protein stability and catalytic activity). Since many protein ortholog sequences and accurate predictive models from AlphaFold2 are available, we also included a systematic analysis of residue conservation and structural role (ConStruct assessment). Overall, our findings indicate that p.(Asp286Gly) and p.(Arg799Trp) behave similarly to wild-type PMS2 and are thus probably neutral. In contrast, p.(Asn335Ser) and p.(Ile679Thr) conferred defects in protein expression or MMR activity. These could be explained by the relevant roles of these amino acids in MLH1-PMS2-N-terminal dimerization (p.Asn335) and C-terminal dimerization (p.Ile679). Our data thus suggest that p.(Asp286Gly) and p.(Arg799Trp) are benign, while the tumor risk in the other two variants remains to be established. Taken together, we suggest roadmaps for the individualized evaluation of difficult uncertain variants by comprising information from all available sources.

Humans↗

PubMed2025

Multiple features of cell-free mtDNA for predicting transarterial chemoembolization response in hepatocellular carcinoma.

BACKGROUND: Transarterial chemoembolization (TACE) is the primary treatment modality for advanced HCC, yet its efficacy assessment and prognosis prediction largely depend on imaging and serological markers that possess inherent limitations in terms of real-time capability, sensitivity, and specificity. Here, we explored whether multiple features of cell-free mitochondrial DNA (cf-mtDNA), including copy number, mutations, and fragmentomics, could be used to predict the response and prognosis of patients with HCC undergoing TACE treatment. METHODS: A total of 60 plasma cell-free DNA samples were collected from 30 patients with HCC before and after the first TACE treatment and then subjected to capture-based mtDNA sequencing and whole-genome sequencing. RESULTS: Comprehensive analyses revealed a clear association between cf-mtDNA multiple features and tumor characteristics. Based on cf-mtDNA multiple features, we also developed HCC death and progression risk prediction models. Kaplan-Meier curve analyses revealed that the high-death risk or high-progression-risk group had significantly shorter median overall survival (OS) and progression-free survival than the low-death risk or low-progression-risk group (all p<0.05). Moreover, the change in cf-mtDNA multiple features before and after TACE treatment exhibited an exceptional ability to predict the risk of death and progression in patients with HCC (log-rank test, all p<0.01; HRs: 0.36 and 0.33, respectively). Furthermore, we observed the consistency of change between the cf-mtDNA multiple features and copy number variant burden before and after TACE treatment in 40.00% (12/30) patients with HCC. CONCLUSIONS: Altogether, we developed a novel strategy based on profiling of cf-mtDNA multiple features for prognosis prediction and efficacy evaluation in patients with HCC undergoing TACE treatment.

Humans↗