What's in a name? Issues to consider when naming Mendelian disorders

Catalpol alleviates heat stroke-induced liver injury in mice by downregulating the JAK/STAT signaling pathway

BACKGROUND

Heat stroke (HS) generated liver injury is a lethal emergency that occurs when the body is exposed to temperatures up to 40 °C for a few hours.

PURPOSE

This study aimed to evaluate the therapeutic prospects of Catalpol (CA) from the blood-cooling herb Rehamanniae Radix on liver injury by HS.

STUDY DESIGN AND METHODS

A murine HS model (41 ± 0.5 °C, 60 ± 5 % relative humidity) and two cell lines (lipopolysaccharide + 42 °C) were used to assess the protective effects of CA on physiological, pathological, and biochemical features in silico, in vivo, and in vitro.

RESULTS

CA treatment significantly improved survival rates in vivo and cell viability in vitro over those of the untreated group. Additionally, CA treatment reduced core body temperature, enhanced survival time, and mitigated liver tissue damage. Furthermore, CA treatment also reduced the activities of AST and ALT enzymes in the serum samples of HS mice. Molecular docking analysis of the 28 overlapping targets between HS and CA revealed that CA has strong binding affinities for the top 15 targets. These targets are primarily involved in nine major signaling pathways, with the JAK-STAT pathway being highly associated with the other eight pathways. Our findings also indicate that CA treatment significantly downregulated the expression of proinflammatory cytokines both in vivo and in vitro while upregulating the expression of anti-inflammatory cytokines. Moreover, CA treatment reduced the levels of JAK2, phospho-STAT5, and phospho-STAT3 both in vivo and in vitro, which is consistent with its inhibition of the apoptotic markers p53, Bcl2, and Bax.

CONCLUSIONS

Heat stroke-induced liver injury was inhibited by CA through the downregulation of JAK/STAT signaling.

Resolving unsolved whole-genome sequencing data in paediatric neurological disorders: a cohort study

OBJECTIVE

To resolve unsolved whole-genome sequencing (WGS) data in individuals with paediatric neurological disorders.

DESIGN

A cohort study method using updated bioinformatic tools, new analysis targets, clinical information and literature databases was employed to reanalyse existing unsolved genome data.

PARTICIPANTS

From January 2016 to September 2023, a total of 615 individuals who aged under 18 years old, exhibited neurological disorders and received singleton WGS were recruited. 364 cases were unsolved during initial WGS analysis, in which 102 consented to reanalyse existing singleton WGS data.

RESULTS

Median duration for reanalysis after initial negative WGS results was 2 years and 4 months. The diagnostic yield was 29 of 102 individuals (28.4%) through reanalysis. New disease gene discovery and new target acquisitions contributed to 13 of 29 solved cases (44.8%). The reasons of non-detected causative variants during initial WGS analysis were variant reclassification in 9 individuals (31%), analytical issue in 9 (31%), new emerging disease-gene association in 8 (27.6%) and clinical update in 3 (10.3%). The 29 new diagnoses increased the cumulative diagnostic yield of clinical WGS in the entire study cohort to 45.5% after reanalysis.

CONCLUSIONS

Unsolved paediatric WGS individuals with neurological disorders could obtain molecular diagnoses through reanalysis within a timeframe of 2-2.5 years. New disease gene, structural variations and deep intronic splice variants make a significant contribution to diagnostic yield. This approach can provide precise genetic counselling to positive reanalysis results and end a diagnostic odyssey.

Elucidating the anti-hypertensive mechanisms of Uncaria rhynchophylla-Alisma plantago-aquatica L: an integrated network pharmacology, cluster analysis, and molecular docking approach

Background: With the increasing global prevalence of hypertension, a condition that can severely affect multiple organs, there is a growing need for effective treatment options. Uncaria rhynchophylla-Alisma plantago-aquatica L. (UR-AP) is a traditional drug pair used for treating hypertension based on the liver-kidney synergy concept. However, the detailed molecular mechanisms underlying its efficacy remain unclear. Methods: This study utilized an integrative approach combining network pharmacology, cluster analysis, and molecular docking to uncover the bioactive components and targets of UR-AP in the treatment of hypertension. Initially, we extracted data from public databases to identify these components and targets. A Protein-Protein Interaction (PPI) network was constructed, followed by enrichment analysis to pinpoint the bioactive components, core targets, and pivotal pathways. Cluster analysis helped in identifying key sub-networks and hypothesizing primary targets. Furthermore, molecular docking was conducted to validate the interaction between the core targets and major bioactive components, thus confirming their potential efficacy in hypertension treatment. Results: Network pharmacological analysis identified 58 bioactive compounds in UR-AP, notably quercetin, kaempferol, beta-sitosterol (from Uncaria rhynchophylla), and Alisol B, alisol B 23-acetate (from Alisma plantago-aquatica L.), as pivotal bioactives. We pinpointed 143 targets common to both UR-AP and hypertension, highlighting MAPK1, IL6, AKT1, VEGFA, EGFR, and TP53 as central targets involved in key pathways like diastolic and endothelial function, anti-atherosclerosis, AGE-RAGE signaling, and calcium signaling. Cluster analysis emphasized IL6, TNF, AKT1, and VEGFA's roles in atherosclerosis and inflammation. Molecular docking confirmed strong interactions between these targets and UR-AP's main bioactives, underscoring their therapeutic potential. Conclusion: This research delineates UR-AP's pharmacological profile in hypertension treatment, linking traditional medicine with modern pharmacology. It highlights key bioactive components and their interactions with principal targets, suggesting UR-AP's potential as a novel therapeutic option for hypertension. The evidence from molecular docking studies supports these interactions, indicating the relevance of these components in affecting hypertension pathways. However, the study acknowledges its limitations, including the reliance on in silico analyses and the need for in vivo validation. These findings pave the way for future clinical research, aiming to integrate traditional medicine insights with contemporary scientific approaches for developing innovative hypertension therapies.

NCAD v1.0: a database for non-coding variant annotation and interpretation

The application of whole genome sequencing is expanding in clinical diagnostics across various genetic disorders, and the significance of non-coding variants in penetrant diseases is increasingly being demonstrated. Therefore, it is urgent to improve the diagnostic yield by exploring the pathogenic mechanisms of variants in non-coding regions. However, the interpretation of non-coding variants remains a significant challenge, due to the complex functional regulatory mechanisms of non-coding regions and the current limitations of available databases and tools. Hence, we develop the non-coding variant annotation database (NCAD, http://www.ncawdb.net/), encompassing comprehensive insights into 665,679,194 variants, regulatory elements, and element interaction details. Integrating data from 96 sources, spanning both GRCh37 and GRCh38 versions, NCAD v1.0 provides vital information to support the genetic diagnosis of non-coding variants, including allele frequencies of 12 diverse populations, with a particular focus on the population frequency information for 230,235,698 variants in 20,964 Chinese individuals. Moreover, it offers prediction scores for variant functionality, five categories of regulatory elements, and four types of non-coding RNAs. With its rich data and comprehensive coverage, NCAD serves as a valuable platform, empowering researchers and clinicians with profound insights into non-coding regulatory mechanisms while facilitating the interpretation of non-coding variants.

Efficacy of Danlou tablet on myocardial ischemia/ reperfusion injury assessed by network pharmacology and experimental verification

OBJECTIVE

To investigate the potential pharmacological mechanism of Danlou tablet (, DLT) with a long-term clinical application in the treatment of myocardial ischemia/reperfusion (I/R) injury through network pharmacology, molecular docking and experimental verification.

METHODS

The main chemical ingredients in DLT were retrieved from the Traditional Chinese Medicine (TCM) System Pharmacology Database, the TCM information database, the bioinformatics analysis tool for molecular mechanism of TCM, and HERB database. Disease targets of I/R were accessed from the databases of Online Mendelian Inheritance in Man, GeneCards, Therapeutic Target Database, and DisGeNET database. The overlaying genes of DLT and I/R were obtained from the Venny online platform. The core targets and protein-protein interaction network were constructed and analyzed via the Search Tool for the Retrieval of Interacting Genes Proteins database and Cytoscape software. Furthermore, Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed by the Metascape platform. Based on the results, the component-target-pathway network was constructed and drafted via the Cytoscape software and the platform of Bioinformatics. Furthermore, we performed molecular docking to predict the binding information between chemical molecules and target proteins. Finally, oxygen-glucose deprivation/recovery (OGD/R)-induced H9c2 cardiomyocytes were used to validate the results of network pharmacology in vitro.

RESULTS

A total of 189 active chemical components in DLT and 849 correlative targets of I/R were screened. Of note, 133 overlaying genes found from the Venny online platform were concentrated into 28 core genes. Furthermore, the GO and KEGG pathway enrichment analysis presented that DLT might participate in 42 types of GO molecular functions, 747 types of GO biological processes, 19 types of GO cellular components, and 140 kinds of pathways to treat I/R. In the component-target-pathway network, the indirect relationship between herbs and their possible effective pathways was clarified. Based on the molecular docking, we speculated that Baicalein-prostaglandin G/H synthase 2 (PTGS2) with -3.24 kcal/mol, Luteolin-heat shock protein 90 alpha family class A member 1 (HSP90AA1) with -3.22 kcal/mol, Baicalein-HSP90AA1 with -3.13 kcal/mol, and Quercetin-HSP90AA1 with -3.05 kcal/mol possessed the strongest binding force of less than -3 kcal/mol, sequentially. Experimental verification showed that Quercetin, Luteolin, and Baicalein could increase the relative cell viability of OGD/R-stimulated cardiomyocytes, probably by suppressing PTGS2, and activating HSP90AA1 and estrogen receptor 1 expression.

CONCLUSIONS

We predicted the potential active compounds as the material basis of DLT that may provide a new approach to elucidate the novel pharmacological mechanism underlying the treatment of cardiac I/R damage.

Research into the anti-pulmonary fibrosis mechanism of Renshen Pingfei formula based on network pharmacology, metabolomics, and verification of AMPK/PPAR-γ pathway of active ingredients

ETHNOPHARMACOLOGICAL RELEVANCE

Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive disease with limited therapy. Renshen Pingfei Formula (RPFF), a classic Chinese medicine derivative formula, has been shown to exert therapeutic effects on IPF.

AIM OF THE STUDY

The study aimed to explore the anti-pulmonary fibrosis mechanism of RPFF through network pharmacology, clinical plasma metabolomics, and in vitro experiment.

METHODS

Network pharmacology was used to study the holistic pharmacological mechanism of RPFF in the treatment of IPF. The differential plasma metabolites for RPFF in the treatment of IPF were identified by untargeted metabolomics analysis. By integrated analysis of metabolomics and network pharmacology, the therapeutic target of RPFF for IPF and the corresponding herbal ingredients were identified. In addition, the effects of the main components of the formula, kaempferol and luteolin, which regulate the adenosine monophosphate (AMP)-activated protein kinase (AMPK)/peroxisome proliferator-activated receptor γ (PPAR-γ) pathway were observed in vitro according to the orthogonal design.

RESULTS

A total of 92 potential targets for RPFF in the treatment of IPF were obtained. The Drug-Ingredients-Disease Target network showed that PTGS2, ESR1, SCN5A, PPAR-γ, and PRSS1 were associated with more herbal ingredients. The protein-protein interaction (PPI) network identified the key targets of RPFF in IPF treatment, including IL6, VEGFA, PTGS2, PPAR-γ, and STAT3. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis acquired the main enriched pathways, and PPAR-γ involved in multiple signaling pathways, including the AMPK signaling pathway. Untargeted clinical metabolomics analysis revealed plasma metabolite variations in patients with IPF versus controls and before versus after RPFF treatment for patients with IPF. Six differential metabolites were explored as differential plasma metabolites for RPFF in IPF treatment. Combined with network pharmacology, a therapeutic target PPAR-γ of RPFF in IPF treatment and the corresponding herbal components were identified. Based on the orthogonal experimental design, the experiments showed that kaempferol and luteolin can decrease the mRNA and protein expression of α-smooth muscle actin (α-SMA), and the combination of lower dose can inhibit α-SMA mRNA and protein expression by promoting the AMPK/PPAR-γ pathway in transforming growth factor beta 1 (TGF-β1)-treated MRC-5 cells.

CONCLUSIONS

This study revealed that the therapeutic effects of RPFF are due to multiple ingredients and have multiple targets and pathways, and PPAR-γ is one of therapeutic targets for RPPF in IPF and involved in the AMPK signaling pathway. Two ingredients of RPFF, kaempferol and luteolin, can inhibit fibroblast proliferation and the myofibroblast differentiation of TGF-β1, and exert a synergistic effect through AMPK/PPAR-γ pathway activation.

Coding long COVID: characterizing a new disease through an ICD-10 lens

BACKGROUND

Naming a newly discovered disease is a difficult process; in the context of the COVID-19 pandemic and the existence of post-acute sequelae of SARS-CoV-2 infection (PASC), which includes long COVID, it has proven especially challenging. Disease definitions and assignment of a diagnosis code are often asynchronous and iterative. The clinical definition and our understanding of the underlying mechanisms of long COVID are still in flux, and the deployment of an ICD-10-CM code for long COVID in the USA took nearly 2 years after patients had begun to describe their condition. Here, we leverage the largest publicly available HIPAA-limited dataset about patients with COVID-19 in the US to examine the heterogeneity of adoption and use of U09.9, the ICD-10-CM code for "Post COVID-19 condition, unspecified."

METHODS

We undertook a number of analyses to characterize the N3C population with a U09.9 diagnosis code (n = 33,782), including assessing person-level demographics and a number of area-level social determinants of health; diagnoses commonly co-occurring with U09.9, clustered using the Louvain algorithm; and quantifying medications and procedures recorded within 60 days of U09.9 diagnosis. We stratified all analyses by age group in order to discern differing patterns of care across the lifespan.

RESULTS

We established the diagnoses most commonly co-occurring with U09.9 and algorithmically clustered them into four major categories: cardiopulmonary, neurological, gastrointestinal, and comorbid conditions. Importantly, we discovered that the population of patients diagnosed with U09.9 is demographically skewed toward female, White, non-Hispanic individuals, as well as individuals living in areas with low poverty and low unemployment. Our results also include a characterization of common procedures and medications associated with U09.9-coded patients.

CONCLUSIONS

This work offers insight into potential subtypes and current practice patterns around long COVID and speaks to the existence of disparities in the diagnosis of patients with long COVID. This latter finding in particular requires further research and urgent remediation.

Coding Long COVID: Characterizing a new disease through an ICD-10 lens

Background

Naming a newly discovered disease is a difficult process; in the context of the COVID-19 pandemic and the existence of post-acute sequelae of SARS-CoV-2 infection (PASC), which includes Long COVID, it has proven especially challenging. Disease definitions and assignment of a diagnosis code are often asynchronous and iterative. The clinical definition and our understanding of the underlying mechanisms of Long COVID are still in flux, and the deployment of an ICD-10-CM code for Long COVID in the US took nearly two years after patients had begun to describe their condition. Here we leverage the largest publicly available HIPAA-limited dataset about patients with COVID-19 in the US to examine the heterogeneity of adoption and use of U09.9, the ICD-10-CM code for "Post COVID-19 condition, unspecified."

Methods

We undertook a number of analyses to characterize the N3C population with a U09.9 diagnosis code ( n = 21,072), including assessing person-level demographics and a number of area-level social determinants of health; diagnoses commonly co-occurring with U09.9, clustered using the Louvain algorithm; and quantifying medications and procedures recorded within 60 days of U09.9 diagnosis. We stratified all analyses by age group in order to discern differing patterns of care across the lifespan.

Results

We established the diagnoses most commonly co-occurring with U09.9, and algorithmically clustered them into four major categories: cardiopulmonary, neurological, gastrointestinal, and comorbid conditions. Importantly, we discovered that the population of patients diagnosed with U09.9 is demographically skewed toward female, White, non-Hispanic individuals, as well as individuals living in areas with low poverty, high education, and high access to medical care. Our results also include a characterization of common procedures and medications associated with U09.9-coded patients.

Conclusions

This work offers insight into potential subtypes and current practice patterns around Long COVID, and speaks to the existence of disparities in the diagnosis of patients with Long COVID. This latter finding in particular requires further research and urgent remediation.

On Terms: What's in a Name? Intellectual Disability and "Condition," "Disorder," "Syndrome," "Disease," and "Disability"

Individuals living with intellectual disability can have multiple co-occurring medical conditions including associated genetic diagnoses. The number of genetic etiologies associated with ID is growing, with some quite new and rare, and others more common and associated with what is often considered a syndrome. In the context of genetic etiologies and associated medical comorbidities, appropriate use of descriptive terminology warrants clarification. Using accurate nomenclature is essential for descriptions, especially as terms are used across both research and clinical reports. Here we discuss several terms that may be confused with each other, including "condition," "disorder," "syndrome," "disease," and "disability." Our goal is to shed light on the meanings of the five descriptors and their appropriate use in the ID population, especially in relation to those who have a genetic diagnosis.

A dyadic approach to the delineation of diagnostic entities in clinical genomics

The delineation of disease entities is complex, yet recent advances in the molecular characterization of diseases provide opportunities to designate diseases in a biologically valid manner. Here, we have formalized an approach to the delineation of Mendelian genetic disorders that encompasses two distinct but inter-related concepts: (1) the gene that is mutated and (2) the phenotypic descriptor, preferably a recognizably distinct phenotype. We assert that only by a combinatorial or dyadic approach taking both of these attributes into account can a unitary, distinct genetic disorder be designated. We propose that all Mendelian disorders should be designated as "GENE-related phenotype descriptor" (e.g., "CFTR-related cystic fibrosis"). This approach to delineating and naming disorders reconciles the complexity of gene-to-phenotype relationships in a simple and clear manner yet communicates the complexity and nuance of these relationships.