Etiology Of Disease Research Articles

Polyploid superficial uroepithelial bladder barrier cells express features of cellular senescence across the lifespan and are insensitive to senolytics.

Lower urinary tract dysfunction (LUTD) increases with aging. Ensuing symptoms including incontinence greatly impact quality of life, isolation, depression, and nursing home admission. The aging bladder is hypothesized to be central to this decline, however, it remains difficult to pinpoint a singular strong driver of aging-related bladder dysfunction. Many molecular and cellular changes occur with aging, contributing to decreased resilience to internal and external stressors, affecting urinary control and exacerbating LUTD. In this study, we examined whether cellular senescence, a cell fate involved in the etiology of most aging diseases, contributes to LUTD. We found that umbrella cells (UCs), luminal barrier uroepithelial cells in the bladder, show senescence features over the mouse lifespan. These polyploid UCs exhibit high cyclin D1 staining, previously reported to mediate tetraploidy-induced senescence invitro. These senescent UCs were not eliminated by the senolytic combination of Dasatinib and Quercetin. We also tested the effect of a high-fat diet (HFD) and senescent cell transplantation on bladder function and showed that both models induce cystometric changes similar to natural aging in mice, with no effect of senolytics on HFD-induced changes. These findings illustrate the heterogeneity of cellular senescence in varied tissues, while also providing potential insights into the origin of urothelial cancer. We conclude that senescence of bladder uroepithelial cells plays a role in normal physiology, namely in their role as barrier cells, helping promote uroepithelial integrity and impermeability and maintaining the urine-blood barrier.

Bronchiectasis in African children: Prevalence, etiology, and clinical spectrum at a pediatric tertiary hospital in Cape Town, South Africa

Objectives: The objective of the study was to describe the disease burden, etiology, and clinical spectrum of bronchiectasis in children attending a tertiary hospital in Cape Town, South Africa. Materials and Methods: Data were collected by chart review of all patients aged 3 months to 15 years attending the respiratory clinic at Red Cross War Memorial Children’s Hospital between January 2019 and December 2019. We included children who had a diagnosis of bronchiectasis based on a history of a recurrent (>3 episodes/year) or persistent (>4 weeks) wet or productive cough and a clinical phenotype characterized by any of the following: Exertion dyspnea, recurrent chest infections, growth failure, finger clubbing, and chest deformity associated with radiographic features of bronchiectasis on chest radiograph or chest tomography reported by a pediatric radiologist. Patients with cystic fibrosis were excluded from the study. Results: Of 337 children seen at the respiratory clinic during the study period, 58 (17.2%) had bronchiectasis that was diagnosed at a mean age of 34 months (standard deviation 26), and 32 (55.0%) were female. The most common causes of bronchiectasis were post-infectious 25 (43.1%), and underlying immunodeficiencies 19 (32.8%), including 16/58 (27.6%) who were living with human immunodeficiency virus (HIV) and 3 (5.1%) with primary immunodeficiency. Other causes included aspiration syndrome 8 (13.8%) and anatomical abnormalities 4 (6.9%). Of the participants with post-infectious bronchiectasis, tuberculosis (TB) was the most common organism isolated 16 (64.0%), and most common in children living with HIV (11/16, 68.8%). Cough was common in 48 (82.8%), with wet cough being predominant in 41 (85.4%), course crepitations were found in 37 (63.8%), hyperinflation in 24 (41.4%), finger clubbing in 21 (36.2%), wheeze in 16 (29.3%), and exertional dyspnea in 7 (12.0%). Conclusion: Bronchiectasis is common in South African children, usually resulting from previous pneumonia episodes, with TB being the most common infective cause. The importance of early diagnosis and treatment of underlying causes, especially infectious diseases in low-middle-income settings, to prevent bronchiectasis is highlighted.

Unveiling the molecular and cellular links between obstructive sleep apnea-hypopnea syndrome and vascular aging.

Vascular aging (VA) is a common etiology of various chronic diseases and represents a major public health concern. Intermittent hypoxia (IH) associated with obstructive sleep apnea-hypopnea syndrome (OSAHS) is a primary pathological and physiological driver of OSAHS-induced systemic complications. A substantial proportion of OSAHS patients, estimated to be between 40% and 80%, have comorbidities such as hypertension, heart failure, coronary artery disease, pulmonary hypertension, atrial fibrillation, aneurysm, and stroke, all of which are closely associated with VA. This review examines the molecular and cellular features common to both OSAHS and VA, highlighting decreased melatonin secretion, impaired autophagy, increased apoptosis, increased inflammation and pyroptosis, increased oxidative stress, accelerated telomere shortening, accelerated stem cell depletion, metabolic disorders, imbalanced protein homeostasis, epigenetic alterations, and dysregulated neurohormonal signaling. The accumulation and combination of these features may underlie the pathophysiological link between OSAHS and VA, but the exact mechanisms by which OSAHS affects VA may require further investigation. Taken together, these findings suggest that OSAHS may serve as a novel risk factor for VA and related vascular disorders, and that targeting these features may offer therapeutic potential to mitigate the vascular risks associated with OSAHS.

Stat3 Induces IL-10 and SR-A/CD204 Expression in Silica Nanoparticle-Triggered Pulmonary Fibrosis through Transactivation.

Inhalation of silica dust in the workplace has been addressed as a serious occupational pulmonary disease subsequently leading to inflammation and fibrosis. Enhanced expression of IL-10 significantly contributes to the disease etiology, along with an elevated Th2-type paradigm. Previously, we showed that the exaggerated Th2-type response was also associated with consistent upregulation of Stat3 in mouse airways stimulated with silica microparticles. However, a precise understanding of silicosis in light of the IL-10/Stat3 immune axis is required. We, therefore, aimed to determine the regulatory role of IL-10 in nanosized silica (nSiO2)-induced pulmonary fibrosis in association with Stat3. Herein, we report that amorphous nSiO2 could induce pulmonary fibrosis with consistent and concomitant upregulation of IL-10, Stat3, and SR-A/CD204. Following exogenous administration of siStat3 and rIL-10, the study further confirmed that Stat3 mediates the regulation of IL-10 and SR-A/CD204 and that IL-10 could regulate its own expression in an autoregulatory loop. The ChIP assay highlighted the localization of Stat3 over two putative binding sites in the IL-10 promoter region, which subsequently resulted in the overexpression of SR-A/CD204. Conclusively, Stat3-mediated transregulation of IL-10 through an autoregulatory loop in silicosis could offer novel molecular targets for therapeutic interventions.

EVALUATION OF BLOOD GAS INSTRUMENTS WITH 6 SIGMA METHODOLOGY

Purpose : 6 sigma is one of the most effective quality tools for demonstrating laboratory analytical performance. 6 sigma tells us what level we are at and what rules to follow in case of poor performance. Blood gas analysis plays an important role in the assessment of critical illness, determining the aetiology and severity of disease. In our study, we aimed to evaluate the test performance of blood gas instruments in our hospital with 6 sigma methodology. Methods : The study included pH, pO2, pCO2, glucose, lactate, ionised Ca, Na, K and Cl parameters analysed on Siemens RAPIDpoint 500e blood gas instruments in the emergency laboratory. In the sigma metric calculation TEa (total permissible error) rates, the values determined by RiliBAK (German Guidelines for Quality) were used. The causes of errors of poorly performing tests were evaluated with the quality goal index (QGI). Results : At the results, PCO2 (Level 2) in Instrument I, Lactate (Level 1-2) in Instrument II and pCO2 (Level 1-2) in Instrument III are the tests with sigma values below 4. When we look at the low performance problems, precision in Instrument I pCO2 (Level 2), accuracy in Instrument II lactate (Level 1-2) and accuracy in Instrument III pCO2 (Level 1-2) were detected. Conclusion : This study has allowed us to monitor laboratory blood gas testing performance very closely. With the 6 sigma methodology we have captured underperforming tests and investigated the reasons behind them

Understanding genetic variants in context.

Over the last three decades, human genetics has gone from dissecting high-penetrance Mendelian diseases to discovering the vast and complex genetic etiology of common human diseases. In tackling this complexity, scientists have discovered the importance of numerous genetic processes - most notably functional regulatory elements - in the development and progression of these diseases. Simultaneously, scientists have increasingly used multiplex assays of variant effect to systematically phenotype the cellular consequences of millions of genetic variants. In this article, we argue that the context of genetic variants - at all scales, from other genetic variants and gene regulation to cell biology to organismal environment - are critical components of how we can employ genomics to interpret these variants, and ultimately treat these diseases. We describe approaches to extend existing experimental assays and computational approaches to examine and quantify the importance of this context, including through causal analytic approaches. Having a unified understanding of the molecular, physiological, and environmental processes governing the interpretation of genetic variants is sorely needed for the field, and this perspective argues for feasible approaches by which the combined interpretation of cellular, animal, and epidemiological data can yield that knowledge.

Morphological and molecular identification of Schizophyllum commune causing storage bulb rot disease of Lanzhou edible lily in China and its biological characteristics

Lily bulb rot disease has harmed edible lily in recent years, resulting in yield losses in China. As a results, both morphological and molecular techniques must be used to confirm the etiology of storage bulb rot disease on lily bulbs. Lily bulbs with indications of rot symptoms during storage were gathered in Lanzhou, Gansu Province, China. A strain was isolated and its morphologically characterized as a Schizophyllum commune specie. Pathogenicity tests further confirmed that the strain caused apparent S. commune symptoms on lily bulbs which were consistent with those seen in the field. The pathogenicity of S. commune to lily bulb was 100%, and morphological identification showed that the mycelia of the pathogen were white and villous, with septate, branched, and acicular bodies and obvious lock-shaped joints. The mycelia had uneven thickness, ranging from 1.03 to 3.06 μm, and turned gray-white at the later growth stage. Moreover, the pathogen formed a mycelial column on potato dextrose agar (PDA) medium, which formed a coral-like fruiting body primordium, which split, forming pileus for spore production. The spores were colorless and cylindrical, with an oblique tip and a size of 4.6–7.2 μm × 2.2–2.7 μm. The isolate was deduced as based on phylogenetic analysis with 2 genes (ribosomal DNA-ITS and LSU) as well as morphological characteristics and cultural features, the isolate was identified S. commune. Soluble starch, yeast extract, temperature of 30°C, pH 7, relative humidity of 100%, and complete dark were shown to be the optimum culture conditions for surface mycelium growth. In conclusion, this is the first report of S. commune causing bulb rot of edible lilies in China. The study provides a basis for more effective control strategies for lily bulb rot disease.

Harnessing network pharmacology in drug discovery: an integrated approach.

Traditional drug discovery approach is based on one drug-one target, that is associated with very lengthy timelines, high costs and very low success rates. Network pharmacology (NP) is a novel method of drug designing, that is based on a multiple-target approach. NP integrates systems such as biology, pharmacology and computational techniques to address the limitations of traditional methods of drug discovery. With help of mapping biological networks, it provides deep insights into biological molecules' interactions and enhances our understanding to the mechanism of drugs, polypharmacology and disease etiology. This review explores the theoretical framework of network pharmacology, discussing the principles and methodologies that enable the construction of drug-target and disease-gene networks. It highlights how data mining, bioinformatics tools and computational models are utilised to predict drug behaviour, repurpose existing drugs and identify novel therapeutic targets. Applications of network pharmacology in the treatment of complex diseases-such as cancer, neurodegenerative disorders, cardiovascular diseases and infectious diseases-are extensively covered, demonstrating its potential to identify multi-target drugs for multifaceted disease mechanisms. Despite the promising results, NP faces challenges due to incomplete and quality of biological data, computational complexities and biological system redundancy. It also faces regulatory challenges in drug approval, demanding revision in regulatory guidelines towards multi-target therapies. Advancements in AI and machine learning, dynamic network modelling and global collaboration can further enhance the efficacy of network pharmacology. This integrative approach has the potential to revolutionise drug discovery, offering new solutions for personalised medicine, drug repurposing and tackling the complexities of modern diseases.

Deciphering proteins in Alzheimer's disease: A new Mendelian randomization method integrated with AlphaFold3 for 3D structure prediction.

Hidden confounding biases hinder identifying causal protein biomarkers for Alzheimer's disease in non-randomized studies. While Mendelian randomization (MR) can mitigate these biases using protein quantitative trait loci (pQTLs) as instrumental variables, some pQTLs violate core assumptions, leading to biased conclusions. To address this, we propose MR-SPI, a novel MR method that selects valid pQTL instruments using Leo Tolstoy's Anna Karenina principle and performs robust post-selection inference. Integrating MR-SPI with AlphaFold3, we developed a computational pipeline to identify causal protein biomarkers and predict 3D structural changes. Applied to genome-wide proteomics data from 54,306UK Biobank participants and 455,258 subjects (71,880 cases and 383,378 controls) for a genome-wide association study of Alzheimer's disease, we identified seven proteins (TREM2, PILRB, PILRA, EPHA1, CD33, RET, and CD55) with structural alterations due to missense mutations. These findings offer insights into the etiology and potential drug targets for Alzheimer's disease.

Leveraging a Vision Transformer Model to Improve Diagnostic Accuracy of Cardiac Amyloidosis With Cardiac Magnetic Resonance.

Cardiac magnetic resonance (CMR) imaging is an important diagnostic tool for diagnosis of cardiac amyloidosis (CA). However, discrimination of CA from other etiologies of myocardial disease can be challenging. The aim of this study was to develop and rigorously validate a deep learning (DL) algorithm to aid in the discrimination of CA using cine and late gadolinium enhancement CMR imaging. A DL model using a retrospective cohort of 807 patients who were referred for CMR for suspicion of infiltrative disease or hypertrophic cardiomyopathy (HCM) was developed. Confirmed definitive diagnosis was as follows: 252 patients with CA, 290 patients with HCM, and 265 with neither CA or HCM (other). This cohort was split 70/30 into training and test sets. A vision transformer (ViT) model was trained primarily to identify CA. The model was validated in an external cohort of 157 patients also referred for CMR for suspicion of infiltrative disease or HCM (51 CA, 49 HCM, 57 other). The ViT model achieved a diagnostic accuracy (84.1%) and an area under the curve of 0.954 in the internal testing data set. The ViT model further demonstrated an accuracy of 82.8% and an area under the curve of 0.957 in the external testing set. The ViT model achieved an accuracy of 90% (n=55 of 61), among studies with clinical reports with moderate/high confidence diagnosis of CA, and 61.1% (n=22 of 36) among studies with reported uncertain, missing, or incorrect diagnosis of CA in the internal cohort. DL accuracy of this cohort increased to 79.1% when studies with poor image quality, dual pathologies, or ambiguity of clinically significant CA diagnosis were removed. A ViT model using only cine and late gadolinium enhancement CMR images can achieve high accuracy in differentiating CA from other underlying etiologies of suspected cardiomyopathy, especially in cases when reported human diagnostic confidence was uncertain in both a large single state health system and in an external CA cohort.

Sex Differences in Gut Microbiota, Hypertension, and Cardiovascular Risk.

The intricate ecosystem of the gut microbiome exhibits sex-specific differences, influencing the susceptibility to cardiovascular diseases (CVD). Imbalance within the gut microbiome compromises the gut barrier, activates inflammatory pathways, and alters the production of metabolites, all of which initiate chronic diseases including CVD. In particular, the interplay between lifestyle choices, hormonal changes, and metabolic byproducts uniquely affects sex-specific gut microbiomes, potentially shaping the risk profiles for hypertension and CVD differently in men and women. Understanding the gut microbiome's role in CVD risk offers informative reasoning behind the importance of developing tailored preventative strategies based on sex-specific differences in CVD risk. Furthermore, insight into the differential impact of social determinants and biological factors on CVD susceptibility emphasizes the necessity for more nuanced approaches. This review also outlines specific dietary interventions that may enhance gut microbiome health, offering a glimpse into potential therapeutic avenues for reducing CVD risk that require greater awareness. Imbalance in natural gut microbiomes may explain etiologies of chronic diseases; we advocate for future application to alter the gut microbiome as possible treatment of the aforementioned diseases. This review mentions the idea of altering the gut microbiome through interventions such as fecal microbiota transplantation (FMT), a major application of microbiome-based therapy that is first-line for Clostridium difficile infections and patient-specific probiotics highlights more innovative approaches to hypertension and CVD prevention. Through increased analysis of gut microbiota compositions along with patient-centric probiotics and microbiome transfers, this review advocates for future preventative strategies for hypertension.

Impact of exposure to extreme heat events during pregnancy on the incidence of congenital heart disease in offspring: a meta-analysis

BackgroundThe aetiology of congenital heart disease (CHD) is multifactorial. Environmental risk factors have emerged as an important modifiable determinant of several congenital cardiac conditions. Previous studies have shown a strong...

Deciphering the Molecular Landscape of Dengue Infection: Insights from gene expression profiling and Protein Interactions

Dengue fever (DF) is a viral infection recognized as one of the most rapidly spreading vector-borne diseases among humans. However, the molecular mechanisms underlying disease aetiology and potential therapeutic targets remain unclear. This study presents a thorough examination of differentially expressed genes (DEGs) throughout the spectrum of Dengue infection stages, offering insights into disease mechanisms and therapeutic targets. Through meticulous analysis of DEGs within each infection stage, key genes pertinent to disease progression are identified, highlighting their roles in host-virus interactions. Noteworthy discoveries include the upregulation of IFI27 and USP18 in mild infection, suggesting involvement in viral replication inhibition and host defence, alongside the downregulation of CMTM2, indicating alterations in immune-related functions. Similarly, in severe infection, upregulated genes like IGHV1-69 are linked to illness severity, while downregulated IL-13RA1 signifies disruptions in cytokine signaling. Overlapping DEGs between infection groups unveil shared biological processes, further elucidated through functional enrichment analysis, showcasing coordinated regulation of cellular processes and pathways. Integration of Dengue virus and human interaction network analysis reveals crucial insights into the mechanisms by which the virus mediates the disease progression and offers potential therapeutic opportunities for disease management.

Research Progress of Chinese Medicine in Treating Chronic Liver Disease by Regulating Autophagy.

In recent years, rising living standards and an accelerated lifestyle have led to an increase in the incidence of chronic liver disease. Modern medicine has yet to fully develop effective methods for preventing and treating these conditions due to their complex pathogenesis. Autophagy, a cellular process that maintains homeostasis by removing abnormal proteins, has emerged as a promising therapeutic target for chronic liver diseases. These diseases include liver fibrosis, liver cirrhosis, non-alcoholic steatohepatitis, chronic hepatitis B, and hepatocellular carcinoma. Chinese medicine, with its multi-component, multi-target, and multi-pathway approach, offers unique advantages in treating these conditions, especially given the unclear etiology of chronic liver diseases. Recent research demonstrates that Chinese medicine - comprising single herbs, herbal combinations, and proprietary formulas - can effectively regulate autophagy, thereby providing therapeutic and preventive benefits for chronic liver diseases. This paper reviews recent studies, categorizes various chronic liver diseases, and examines the impact of active ingredients and compound formulas from Chinese medicine on autophagy. These insights are crucial for slowing the progression of chronic liver diseases and pave the way for the future application of Chinese medicine in preventing and managing these conditions through autophagy modulation.

Diacylglycerol metabolism and homeostasis in fungal physiology.

Diacylglycerol (DAG) is a relatively simple and primitive form of lipid, which does not possess a phospholipid headgroup. Being a central metabolite of the lipid metabolism network, DAGs are omnipresent in all life forms. While the role of DAG has been established in membrane and storage lipid biogenesis, it can impart crucial physiological functions including membrane shapeshifting, regulation of membrane protein activity and transduction of cellular signalling as a lipid-based secondary messenger. Besides, the chemical diversity of DAGs, due to fatty acyl chain composition, has been proposed to be the basis of its functional diversity. Therefore, cells must regulate DAG level at a spatio-temporal scale for homeostasis and adaptation. The vast network of eukaryotic lipid metabolism has been unravelled majorly by studying yeast models. Here, we review the current understanding and the emerging concepts in metabolic and functional aspects of DAG regulation in yeast. The implications can be extended to understand pathogenic fungi and mammalian counterparts as well as disease aetiology.

Autoimmune Disease is Increased in Women with Primary Ovarian Insufficiency.

Autoimmune disease is common in women with primary ovarian insufficiency (POI) and the genetic etiology of autoimmune disease suggests that it could be hereditary in families of women with POI. We hypothesized that a subset of women with POI and their family members would have increased risk for autoimmune disorders. Population-based study using electronic health records from 1995-2022. Two major Utah healthcare systems serving 85% of the state. Women with POI (n=610) were identified using ICD codes and chart reviewed for accuracy. First-, second-, and third-degree relatives were identified using genealogy data in the Utah Population Database. Autoimmune diagnoses were identified using ICD codes. The relative risk of autoimmune disease in women with POI and relatives was estimated by comparison to population rates. At least one autoimmune disease was identified in 25% of women with POI. The relative risk of autoimmune hypothyroidism (OR [95%CI] 6.88 [5.71, 8.22]; p<0.001), adrenal insufficiency (4.72 [1.73, 10.28]; p=0.0020), type 1 diabetes (4.13 [2.14, 7.22]; p=5.25X10-5), rheumatoid arthritis (5.66 [3.10, 9.50]; p=3.70X10-7), vitiligo (15.33 [6.16, 31.58]; p=5.25X10-7), celiac disease (7.58 [3.47, 14.39]; p=4.47X10-6), psoriasis (3.90 [2.01, 6.81]; p=9.04X10-5) and systemic lupus erythematosus (4.43 [1.63, 9.64]; p=0.0027) were increased in women with POI compared to population rates. There was no increased risk of autoimmune disease in family members. Data confirm increased autoimmune disease in women with POI. The increased risk is largely related to autoimmune polyglandular syndrome types 1 through 4 and autoimmune hypothyroidism. The absence of risk in family members may result from differences in environmental influences or hormone milieu.

Biliary Complications after Liver Transplant: Timeline, Spectrum, Management Algorithm, and Prevention

AbstractBiliary complications are the most common complications seen after liver transplantation (LT) with an incidence ranging between 10 and 15% and increasing in the setting of increased access to living donor liver transplant and utilization of marginal grafts. Among the biliary complications, the most common are anastomotic strictures, nonanastomotic strictures, and biliary leaks, which have a variable time of presentation posttransplant. The risk factors for the development of biliary complications include surgical techniques, type of grafts, prolonged ischemia, primary disease etiology, and associated post-LT complications. The approach to a diagnosis in an appropriate clinical setting involves a stepwise approach involving clinical history, assessment of risk factors, biochemical abnormalities, and appropriate imaging. Therapeutic options revolve around endoscopic retrograde cholangiopancreatography and percutaneous transhepatic biliary drainage, with surgical intervention being reserved in case of failure of these modalities. Preventive strategies with machine perfusion techniques are promising, while use of T-tubes for prevention of complications remains controversial.

The Who’s, What’s, and “Y”s: Y Sex Chromosome Loss and Methylation for Analysis in Male Aging and Mortality and Forensic Science Applications

The Y chromosome plays a crucial role in understanding the overall landscape of male health. Incorporating the Y chromosome into genomic and epigenomic research may elucidate the male-specific mechanisms behind aging and the pathogenesis of certain conditions, both acute and chronic. Present epigenetic research focuses on the effects of modifications like methylation on autosomal chromosomes. However, little research has been conducted to further these investigations in sex chromosomes, especially the Y chromosome. Epigenetic analyses can identify age-associated CpG sites that may offer potential biomarkers for age estimation and disease risk assessment, among others. This review emphasizes interdisciplinary efforts that have been made in the construction of an assembly and the application of “epigenetic clocks” to the Y chromosome. The studies reviewed here examined the effects of aging on genes such as NLGN4Y, DDX3Y, and TBL1Y, and on male-specific health disparities and disease etiologies, as well as the potential for the use of these genes to assess the diagnostic and age algorithmic potential of Y-specific genes.

CNV-Finder: Streamlining Copy Number Variation Discovery.

Copy Number Variations (CNVs) play pivotal roles in the etiology of complex diseases and are variable across diverse populations. Understanding the association between CNVs and disease susceptibility is of significant importance in disease genetics research and often requires analysis of large sample sizes. One of the most cost-effective and scalable methods for detecting CNVs is based on normalized signal intensity values, such as Log R Ratio (LRR) and B Allele Frequency (BAF), from Illumina genotyping arrays. In this study, we present CNV-Finder, a novel pipeline integrating deep learning techniques on array data, specifically a Long Short-Term Memory (LSTM) network, to expedite the large-scale identification of CNVs within predefined genomic regions. This facilitates the efficient prioritization of samples for subsequent, costly analyses such as short-read and long-read whole genome sequencing. We focus on five genes-Parkin (PRKN), Leucine Rich Repeat And Ig Domain Containing 2 (LINGO2), Microtubule Associated Protein Tau (MAPT), alpha-Synuclein (SNCA), and Amyloid Beta Precursor Protein (APP)-which may be relevant to neurological diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), or related disorders such as essential tremor (ET). By training our models on expert-annotated samples and validating them across diverse cohorts, including those from the Global Parkinson's Genetics Program (GP2) and additional dementia-specific databases, we demonstrate the efficacy of CNV-Finder in accurately detecting deletions and duplications. Our pipeline outputs app-compatible files for visualization within CNV-Finder's interactive web application. This interface enables researchers to review predictions and filter displayed samples by model prediction values, LRR range, and variant count in order to explore or confirm results. Our pipeline integrates this human feedback to enhance model performance and reduce false positive rates. Through a series of comprehensive analyses and validations using both short-read and long-read sequencing data, we demonstrate the robustness and adaptability of CNV-Finder in identifying CNVs with regions of varied sparsity, noise, and size. Our findings highlight the significance of contextual understanding and human expertise in enhancing the precision of CNV identification, particularly in complex genomic regions like 17q21.31. The CNV-Finder pipeline is a scalable, publicly available resource for the scientific community, available on GitHub (https://github.com/GP2code/CNV-Finder; DOI 10.5281/zenodo.14182563). CNV-Finder not only expedites accurate candidate identification but also significantly reduces the manual workload for researchers, enabling future targeted validation and downstream analyses in regions or phenotypes of interest.

RASopathies in Cardiac Disease.

RASopathies are a group of clinically overlapping autosomal dominant disorders caused primarily by mutations in genes that reside along the canonical Ras-mitogen-activated protein kinase signaling cascade. Though individually rare, collectively, these disorders constitute one of the largest families of congenital disorders worldwide, particularly for infantile hypertrophic cardiomyopathy. Significantly, despite almost five decades of RASopathy research, therapeutic options remain limited and focused primarily on treating symptoms rather than disease etiology. Targeting the genes causal to these disorders, and the nodal pathways critical for their regulation, however, has been challenging. In this review, we highlight these challenges, particularly with respect to congenital heart defects and cardiac diseases and discuss limitations and future directions for approaches to new therapeutic strategies.