Biology subjects

Giannoulatou, E.

Publications and source records attributed to Giannoulatou, E..

10 recordsLinked to original sources

bioRxiv2026

HeartVar: An LLM-Assisted Tool for Clinical Classification of Variants in Cardiovascular Disease Cohorts

Manual clinical DNA variant classification is the bottleneck of every clinical and research rare disease workflow. The process typically requires a curator to assemble evidence from numerous databases, weigh 28 criteria, reconcile competing evidence, and produce a defensible case for the final classification. Additionally, the framework used to assess variants is not static and successive addenda have revised individual criteria. The most complete and current evidence aggregators available are commercial platforms, which can limit researcher access. We present HeartVar, an open-source web tool that automates the evidence-gathering and interpretation steps of variant classification associated with cardiovascular disease. Given a gene, a variant, and clinical context, HeartVar queries 20 public databases in parallel and assigns ACMG/AMP criteria through a hybrid rule-based/large language model (LLM) approach. Criteria that can be resolved from structured data are computed programmatically, and only those requiring interpretation of unstructured evidence are passed to the LLM. HeartVar returns a classification, point score, per-criterion breakdown, clinical-narrative summary, and database annotations. Benchmarking of 106 expert-curated ClinGen variants showed HeartVar outperformed other curation tools, assigning the correct ACMG tier in 72% of cases. HeartVar demonstrates that an LLM constrained by a domain-specific prompt and grounded in structured evidence can produce variant interpretations of first-pass quality for a cardiovascular disease cohort; however, it is not intended to replace manual assessment by a qualified variant curator. The tool is freely available to use and hosted at www.heartvar.victorchang.edu.au.

bioinformatics↗

bioRxiv2025

Robotic Handling Preserves Induced Pluripotent Stem Cell Derived Vascular Smooth Muscle Cells Differentiation using a Weekend-free, Automatable, Low-variability, Low-cost (WALL) Protocol

Vascular disease modeling and tissue engineering require scalable, efficient, and reproducible methods for differentiating cells, however no studies have validated whether automation, essential for scale-up, preserves differentiation quality in cells. Here, we developed a differentiation protocol for induced pluripotent stem cell (iPSC)-derived vascular smooth muscle cells (iVSMCs) that is applicable to both manual, and automated robotic culture. iPSC lines generated from male and female donors across various ages were used to optimize the generation of iVSMCs. iVSMCs had consistent morphology and protein expression was largely similar to primary VSMCs, including expression of myosin heavy chain-11 (MYH11), -smooth muscle actin (-SMA), transgelin (TAGLN) and calponin (CNN1). Functionally, these iVSMCs could respond to the vasoconstrictor carbachol. Coupling this protocol with an automated Hamilton liquid-handling robotics system allowed the generation of iVSMCs in large quantities, morphologically similar to manually differentiated iVSMCs. Comparative proteomic analysis confirmed protein expression did not differ between automated and manual differentiation methods. Automation markedly reduced manual labor and facilitated increased production without sacrificing cell quality. This study demonstrates the feasibility of automating iVSMC differentiation, marking a significant step towards scalable VSMC manufacturing for three-dimensional applications, and for the ever-growing demands of organoid and tissue engineering applications. Statement of significanceThe rapidly expanding fields of tissue engineering and high-throughput disease modeling require large quantities of viable cells, making automation essential. Robotic liquid handling systems are increasingly employed for generating large quantities of induced pluripotent stem cell (iPSC)-derived cells, requiring the development of scalable protocols. No studies have yet evaluated whether the use of robotic liquid handling alters the differentiation of cells compared to traditional manual handling. Here, we report a scalable differentiation protocol that robustly generates iPSC-derived VSMCs (iVSMCs) from a cohort of female and male donors of varying age (n=5 lines). We demonstrate for the first time that iVSMCs, differentiated through an automated robotic pipeline, had no significant differences in morphological or proteomic phenotype compared to manual differentiation. The ability to automate this protocol facilitates robust and reproducible differentiation of large quantities of iVSMC, setting a precedent for the application of automation in generating iPSC-derived cells. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=57 SRC="FIGDIR/small/690512v1_ufig1.gif" ALT="Figure 1000"> View larger version (18K): org.highwire.dtl.DTLVardef@673d61org.highwire.dtl.DTLVardef@1eead89org.highwire.dtl.DTLVardef@c3089eorg.highwire.dtl.DTLVardef@6af2cd_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗

bioRxiv2025

Neural crest cell derived DKK1 modulates Wnt signalling in the second heart field to orchestrate cardiac outflow tract development

Heart morphogenesis is highly complex, and depends on the generation of diverse cell types which interact with each other in an orchestrated manner to remodel the primitive heart tube into a functional organ. Cardiac outflow tract formation critically depends on continued contribution of cardiac progenitor cells from the anterior second heart field to ensure proper growth of the outflow tract. Prior to entering the outflow tract, neural crest cells migrate in close apposition to the second heart field and may play important roles in regulating second heart field growth dynamics, however the molecular mechanisms by which neural crest cells interact with the second heart field have remained elusive. Here, we discover that neural crest cells are a primary source of Dickkopf1 (DKK1), a secreted Wnt signalling inhibitor, which modulates Wnt signalling activity in the second heart field to impose a balance between progenitor maintenance and differentiation. Further, we identify the ubiquitin ligase NEDD4 as a critical regulator of DKK1 levels, with disruption of Nedd4 activity leading to outflow tract defects. In the context of disease pathogenicity, we show a novel human congenital heart disease variant of NEDD4 has lost the ability to ubiquitinate DKK1, and is associated with heart defects in a mouse model of the genetic variant. Our findings point to an unexpected role for neural crest cells acting as a rheostat of Wnt signalling activity in cardiac progenitors, identifying a new molecular pathway underpinning correct outflow tract morphogenesis, and a new causative factor of congenital heart disease.

developmental biology↗

bioRxiv2025

Benchmarking of variant pathogenicity prediction methods using a population genetics approach

MotivationVariant pathogenicity predictors are essential for identifying new associations between genetic variants and rare diseases. However, despite the availability of numerous predictors, there is no clear consensus on which methods provide the most reliable results. The common practice of training, testing, and benchmarking these predictors using known variant sets from disease or mutagenesis studies raises concerns about ascertainment bias and data circularity. ResultsWe benchmarked commonly used pathogenicity predictors using an orthogonal approach that does not rely on predefined "ground truth" datasets. By leveraging population-level genomic data from gnomAD and the Context-Adjusted Proportion of Singletons (CAPS) metric, we identified CADD and REVEL as the best-performing predictors for distinguishing extremely deleterious variants from moderately deleterious ones. REVEL demonstrated superior calibration. Additionally, we show that CAPS can serve as a meta-analysis tool for interpreting variant annotations and highlight biases in ClinVar-based predictor training. Availability and ImplementationCAPS analysis and benchmarking results are available at https://github.com/mgudVCCRI/PopGenVariantFiltering Contacte.giannoulatou@victorchang.edu.au

genomics↗

bioRxiv2024

Systematic evaluation of de novo mutation calling tools using whole genome sequencing data

De novo mutations (DNMs) are genetic alterations that occur for the first time in an offspring. DNMs have been found to be a significant cause of severe developmental disorders. With the widespread use of next-generation sequencing (NGS) technologies, accurate detection of DNMs is crucial. Several bioinformatics tools have been developed to call DNMs from NGS data, but no study to date has systematically compared these tools. We used both real whole genome sequencing (WGS) data from a trio from the 1000 Genomes Project (1000G) and an in-house simulated trio dataset to evaluate five DNM calling tools: DeNovoGear, TrioDeNovo, PhaseByTransmission, VarScan2, and DeNovoCNN. For DNMs called in the real dataset, we observed 8.4% concordance of variants between all tools, while 83.8% of DNMs variants were identified by only one caller. For simulated trio WGS dataset spiked with 100 DNMs, the concordance rate was also low at 3.9%. DeNovoGear achieved the highest F1 score on the real 1000G dataset, while DeNovoCNN had the highest F1 score on the simulated data. Our study provides valuable recommendations for the selection and application of DNM callers on WGS trio data.

bioinformatics↗

bioRxiv2024

Improving estimates of negative selection in human genome using CAPS

Despite ongoing efforts, variant interpretation in disease sequencing studies is often hindered by the lack of well-established ways of determining the potential pathogenicity of genetic variation, especially for understudied classes of single-nucleotide variants (SNVs). Population genetics methods offer an attractive solution to this problem by enabling the assessment of the effects of SNVs through their distributions in human populations. For instance, negative selection is known to shift site-frequency spectra of genetic variation, thus affecting the ratio of singleton variants. It has been shown that the extent of negative selection can serve as a proxy for deleteriousness. An example of this approach is the Mutability-Adjusted Proportion of Singletons (MAPS) metric. Although MAPS proves a useful instrument for the assessment of selection-based deleteriousness in SNVs, it is highly sensitive to the calibration of the singletons-by-mutability model, which results in potentially biased estimates for some classes of variants. Building up on the methodology used in MAPS, we developed a novel metric of negative selection in the human genome -- CAPS, or Context-Adjusted Proportion of Singletons. Compared to its predecessor, CAPS provides estimates of negative selection that are less biased and have more accurate confidence intervals. CAPS inherits some of the same features that make MAPS useful for studying SNVs, yet the key difference of our method is the complete elimination of the mutability layer in the model, which makes the metric more robust and reliable. We believe that CAPS holds promise for improving the discovery of new disease-variant associations in clinical and research settings.

genomics↗

bioRxiv2023

Single cell sequencing data identify distinct B cell and fibroblast populations in stricturing Crohns disease

We used human full thickness Crohns disease (CD) small bowel resection specimens and single cell RNA sequencing to identify potential therapeutic targets for stricturing (S)CD. Using an unbiased approach, 16 cell lineages were assigned within 14,539 sequenced cells from patient-matched SCD and non-stricturing (NSCD) preparations. SCD and NSCD contained identical cell types. Amongst immune cells, B cells and plasma cells were selectively increased in SCD samples. B cell subsets suggested formation of tertiary lymphoid tissue in SCD and compared with NSCD there was an increase in IgG, and a decrease in IgA plasma cells, consistent with their potential role in CD fibrosis. Two Lumican-positive fibroblast subtypes were identified and subclassified based on expression of selectively enriched genes as fibroblast clusters (C)12 and C9. Cells within these clusters expressed the profibrotic genes Decorin (C12) and JUN (C9). C9 cells expressed ACTA2; ECM genes COL4A1, COL4A2, COL15A1, COL6A3, COL18A1 and ADAMDEC1; LAMB1 and GREM1. GO and KEGG Biological terms showed extracellular matrix, stricture organisation and regulation of WNT pathway genes are associated with the C12 and C9 gene sets. Trajectory and differential gene analysis of C12 and C9 identified four sub-clusters. Intra sub-cluster gene analysis detected co-regulated gene modules that aligned along predicted pseudotime trajectories and identified CXCL14 and ADAMDEC1 as key module markers. Our findings support further investigation of fibroblast heterogeneity and interactions with local and circulating immune cells at earlier time points in fibrosis progression. Breaking these interactions by targeting one or other population may improve therapeutic management for SCD.

genomics↗

bioRxiv2022

The PREGCARE study: Personalized recurrence risk assessment following the birth of a child with a pathogenic de novo mutation

Next-generation sequencing has led to a dramatic improvement in molecular diagnoses of serious pediatric disorders caused by apparently de novo mutations (DNMs); by contrast, clinicians ability to counsel the parents about the risk of recurrence in a future child has lagged behind. Owing to the possibility that one of the parents could be mosaic in their germline, a recurrence risk of 1-2% is frequently quoted, but for any specific couple, this figure is usually incorrect. We present a systematic approach to providing individualized recurrence risk stratification, by combining deep-sequencing of multiple tissues in the mother-father-child trio with haplotyping to determine the parental origin of the DNM. In the first 58 couples analysed (total of 59 DNMs in 49 different genes), the risk for 35 (59%) DNMs was decreased below 0.1% but for 6 (10%) couples it was increased owing to parental mosaicism - that could be quantified in semen (recurrence risks of 5.6-12.1%) for the paternal cases. Deep-sequencing of the DNM efficiently identifies couples at greatest risk for recurrence and may qualify them for additional reproductive technologies. Haplotyping can further reassure many other couples that their recurrence risk is very low, but its implementation is more technically challenging and will require better understanding of how couples respond to information that reduces their risks.

genetics↗

bioRxiv2020

Maternal iron deficiency perturbs embryonic cardiovascular development

Congenital heart disease (CHD) is the most common type of birth defect, with a global prevalence of 0.9% of live births1. Most research in the last 30 years has focused on finding genetic causes of CHD. However, despite the association of over 100 genes with CHD, mutations in these genes only explain ~30% of cases2. Many of the remaining cases of CHD are caused by in utero exposure to environmental factors3. Here we have identified a completely new environmental teratogen causing CHD: maternal iron deficiency. In humans, iron deficiency anaemia is a major global health problem. 38% of pregnant women worldwide are anaemic4, and at least half of these are due to iron deficiency, the most prevalent micronutrient deficiency. We describe a mouse model of maternal iron deficiency anaemia that causes severe cardiovascular defects in her offspring. We show that these defects likely arise from increased retinoic acid signalling in iron deficient embryos, probably due to reduced activity of the iron-dependent retinoic acid catabolic CYP26 enzymes. The defects can be prevented by maternal iron administration early in pregnancy, and are also greatly reduced in offspring of mothers deficient in both iron and the retinoic acid precursor vitamin A. Finally, one puzzling feature of many genetic forms of CHD in humans is the considerable variation in penetrance and severity of defects. We show that maternal iron deficiency acts as a significant modifier of heart and craniofacial phenotype in a mouse model of Down syndrome. Given the high incidence of maternal iron deficiency, peri-conceptional iron monitoring and supplementation could be a viable strategy to reduce the prevalence and severity of CHD in human populations worldwide.

developmental biology↗

bioRxiv2018

Selfish mutations dysregulating RAS-MAPK signaling are pervasive in aged human testes

Mosaic mutations present in the germline have important implications for reproductive risk and disease transmission. We previously demonstrated a phenomenon occurring in the male germline, whereby specific mutations arising spontaneously in stem cells (spermatogonia) lead to clonal expansion, resulting in elevated mutation levels in sperm over time. This process, termed selfish spermatogonial selection, explains the high spontaneous birth prevalence and strong paternal age-effect of disorders such as achondroplasia, Apert, Noonan and Costello syndromes, with direct experimental evidence currently available for specific positions of six genes (FGFR2, FGFR3, RET, PTPN11, HRAS and KRAS). We present a discovery screen to identify novel mutations and genes showing evidence of positive selection in the male germline, by performing massively parallel simplex PCR using RainDance technology to interrogate mutational hotspots in 67 genes (51.5 kb in total) in 276 biopsies of testes from 5 men (median age: 83 years). Following ultra-deep sequencing (~16,000x), development of a low-frequency variant prioritization strategy and targeted validation, we identified 61 distinct variants present at frequencies as low as 0.06%, including 54 variants not previously directly associated with selfish selection. The majority (80%) of variants identified have previously been implicated in developmental disorders and/or oncogenesis and include mutations in six newly associated genes (BRAF, CBL, MAP2K1, MAP2K2, RAF1 and SOS1), all of which encode components of RAS-MAPK pathway and activate signaling. Our findings extend the link between mutations dysregulating the RAS-MAPK pathway and selfish selection, and show that the ageing male germline is a repository for such deleterious mutations.

genetics↗