GSTM5 Human, Active

What is GSTM5 and what is its primary biological function?

GSTM5 (Glutathione S-transferase Mu 5) is a member of the mu class of GSTs that plays a crucial role in cellular detoxification processes. Its primary biological function involves the conjugation of reduced glutathione to a wide range of exogenous and endogenous hydrophobic electrophiles . This conjugation reaction neutralizes toxic compounds and makes them more water-soluble, facilitating their elimination from cells. GSTM5 belongs to the larger GST superfamily, which collectively represents one of the major xenobiotic detoxification enzyme systems protecting cells from harmful effects of toxic drugs and environmental electrophilic agents .

Where is the GSTM5 gene located in the human genome and how is it organized?

The GSTM5 gene is located on human chromosome 1, specifically in or near the 1p13.3 region . It exists as part of a gene cluster that includes five closely related GSTM genes: GSTM1, GSTM2, GSTM3, GSTM4, and GSTM5 . This tight clustering of related genes has been confirmed through multiple mapping techniques, including locus-specific PCR primers spanning exon 6, intron 6, and exon 7, as well as through fluorescence in situ hybridization (FISH) using a yeast artificial chromosome clone (GSTM-YAC2) containing all five genes .

The genomic organization of GSTM5 follows the typical structure of GSTM genes, with multiple exons separated by introns. The close physical proximity of these genes and their high sequence homology (particularly between GSTM1 and GSTM2, which share 99% nucleotide sequence identity over 460 nucleotides of 3'-untranslated mRNA) suggests that they arose through gene duplication events . This genomic arrangement may also facilitate evolutionary events such as unequal crossing-over, which has been proposed as a mechanism for generating null alleles in the GSTM family.

What expression patterns does GSTM5 exhibit across human tissues?

GSTM5 demonstrates tissue-specific expression patterns that differ from other GSTM family members. Unlike some GSTs with broad tissue distribution, GSTM5 shows more restricted expression profiles. Based on the available research data, GSTM5 expression has been detected in various human tissues, though often at different levels.

In pathological contexts, GSTM5 expression appears to be altered in specific disease states. For instance, in diabetic foot ulcer (DFU) samples, GSTM5 has been found to be significantly downregulated compared to normal tissue controls . This downregulation has been consistently observed across multiple independent datasets (GSE68183, GSE80178, and validated in GSE134431), suggesting a potential role in the pathophysiology of DFU .

The tissue-specific expression pattern of GSTM5 suggests that its function may be particularly important in certain physiological contexts. Currently, research indicates that GSTM5 expression levels may have diagnostic and prognostic value in specific disease contexts, particularly those involving immune dysregulation or impaired detoxification processes.

How does GSTM5 relate to other members of the GST superfamily?

GSTM5 is one of five members of the mu-class GST family (along with GSTM1, GSTM2, GSTM3, and GSTM4), which in turn belongs to the larger GST superfamily . The relationship between GSTM5 and other GST family members can be examined at several levels:

The table below summarizes the predicted functional partners of GSTM5 based on STRING database analysis:

These interactions highlight the integration of GSTM5 within a network of detoxification and antioxidant defense systems .

What role does GSTM5 play in immune regulation and inflammatory processes?

Recent research has uncovered a significant role for GSTM5 in immune regulation and inflammatory processes. Analysis of DFU datasets has revealed that GSTM5 expression correlates with changes in immune cell populations and inflammatory pathways . Specifically, GSTM5 appears to have functional relationships with several key immune components:

• T cell populations: GSTM5 expression levels show associations with T cells regulatory (Tregs) and T cells follicular helper populations . In DFU samples where GSTM5 is downregulated, there are corresponding decreases in T cells CD4 memory resting, T cells regulatory (Tregs), and T cells follicular helper populations compared to control samples .

• B cells and cytolytic activity: Immune function analysis suggests that GSTM5 may have relationships with B cells and cytolytic activity . In DFU samples, B cells naive and activated dendritic cells are higher compared to control groups .

• Macrophage populations: GSTM5 expression correlates with changes in macrophage populations, with Macrophages M1 being lower in DFU samples compared to controls . Correlation analysis also revealed that Macrophages M1 and T cells CD4 memory resting show a strong positive correlation, while B cells naive and Macrophages M2 exhibit a strong negative correlation .

• Inflammatory signaling pathways: GSTM5 appears to influence several key inflammatory signaling pathways, including the NF-κB signaling pathway, which is a central regulator of inflammatory responses . KEGG enrichment analysis indicates that differentially expressed genes related to GSTM5 are primarily involved in the NF-κB signaling pathway (hsa04064), Nitrogen metabolism (hsa00910), and GnRH signaling pathway (hsa04912) .

These findings suggest that GSTM5 may function beyond its classical role in detoxification to influence immune regulation and inflammatory processes, potentially through its effects on cellular redox status or through more direct interactions with immune signaling pathways.

How does GSTM5 contribute to the pathophysiology of diabetic foot ulcers?

GSTM5 has emerged as a critical biomarker in diabetic foot ulcer (DFU) pathophysiology, with multiple lines of evidence supporting its role in this condition:

• Consistent downregulation: GSTM5 is significantly downregulated in DFU tissue compared to normal control tissue, as demonstrated across multiple independent datasets (GSE68183, GSE80178, and validated in GSE134431) . This consistent pattern of reduced expression suggests a potential causal relationship rather than merely a coincidental finding.

• Diagnostic potential: ROC curve analysis demonstrates that GSTM5 has good diagnostic performance for identifying DFU, suggesting its potential utility as a biomarker . The consistent downregulation makes it a promising candidate for diagnostic applications.

• Pathway dysregulation: GSTM5 expression levels are associated with alterations in several key pathways relevant to DFU pathophysiology:

  • In samples with high GSTM5 expression, butanoate metabolism, complement and coagulation cascades, and drug metabolism cytochrome p450 pathways are more active .

  • In samples with low GSTM5 expression (as in DFU), insulin signaling pathway, MAPK signaling pathway, and neurotrophin signaling pathway are more active .

  • GSVA analysis indicates a close association between GSTM5 and terpenoid backbone biosynthesis and complement and coagulation cascades .

• Biological processes: Enrichment analysis indicates that genes differentially expressed in relation to GSTM5 are involved in cell-substrate adhesion (GO:0031589), epithelial cell proliferation (GO:0050673), and negative regulation of leukocyte apoptotic process (GO:2000107) . These processes are directly relevant to wound healing and tissue repair, which are impaired in DFU.

• Immune cell alterations: The altered immune cell profiles associated with GSTM5 downregulation in DFU (decreased T cells regulatory, T cells follicular helper, and Macrophages M1; increased B cells naive and Dendritic cells activated) may contribute to the chronic inflammation and impaired healing characteristic of DFU .

The mechanistic link between GSTM5 downregulation and DFU pathophysiology likely involves its influence on oxidative stress management, immune regulation, and inflammatory processes. Reduced GSTM5 expression may lead to impaired detoxification of harmful electrophiles, altered redox homeostasis, and dysregulated immune responses, all contributing to the chronic non-healing nature of diabetic foot ulcers.

What are the key signaling pathways influenced by GSTM5 expression levels?

GSTM5 expression levels appear to influence multiple signaling pathways that are crucial for cellular homeostasis, stress responses, and immune function. Based on the research data, several key pathways show differential activation depending on GSTM5 expression levels:

• NF-κB signaling pathway: KEGG enrichment analysis indicates that differentially expressed genes related to GSTM5 are primarily involved in the NF-κB signaling pathway (hsa04064) . This pathway is central to inflammatory responses, immune regulation, and cell survival, suggesting that GSTM5 may modulate inflammation through NF-κB-dependent mechanisms.

• MAPK signaling pathway: In the context of low GSTM5 expression (as observed in DFU), the MAPK signaling pathway shows increased activity . This pathway regulates various cellular processes including proliferation, differentiation, and stress responses, and its dysregulation in low-GSTM5 states may contribute to impaired wound healing.

• Insulin signaling pathway: Similarly, the insulin signaling pathway is more active in conditions of low GSTM5 expression . This finding is particularly relevant in the context of diabetic complications, suggesting potential cross-talk between GSTM5 function and insulin signaling.

• GnRH signaling pathway: KEGG enrichment analysis identified the GnRH signaling pathway (hsa04912) as one of the primary pathways involved with differentially expressed genes related to GSTM5 . While this pathway is traditionally associated with reproductive function, it also involves calcium signaling and MAPK activation, suggesting broader cellular effects.

• Complement and coagulation cascades: In high GSTM5 expression states, complement and coagulation cascades show increased activity . These pathways are involved in immune defense and hemostasis, which are crucial for proper wound healing.

• Metabolic pathways: Several metabolic pathways show differential activity based on GSTM5 expression levels:

  • Butanoate metabolism and drug metabolism cytochrome p450 are more active in high GSTM5 expression states

  • Nitrogen metabolism (hsa00910) is associated with differentially expressed genes related to GSTM5

  • Terpenoid backbone biosynthesis shows a close association with GSTM5 expression

The influence of GSTM5 on these diverse signaling pathways suggests that it functions as a regulatory node connecting detoxification processes with broader cellular signaling networks that control metabolism, immune function, and stress responses.

What genetic and epigenetic factors regulate GSTM5 expression?

While the search results don't provide comprehensive information on the genetic and epigenetic regulation of GSTM5, we can infer several important aspects of its regulation based on available information and general principles of gene regulation for the GST family:

• Genomic organization: The GSTM5 gene is part of a gene cluster on chromosome 1p13.3 that includes five GSTM genes (GSTM1-GSTM5) . This clustered organization suggests potential coordinated regulation of these genes through shared regulatory elements or chromatin domains.

• Promoter elements: Like other GST genes, GSTM5 likely contains promoter elements responsive to oxidative stress and xenobiotic exposure. These may include antioxidant response elements (AREs) that bind transcription factors such as Nrf2 (Nuclear factor erythroid 2-related factor 2), which is a master regulator of cellular responses to oxidative stress.

• Disease-specific regulation: In the context of diabetic foot ulcers, GSTM5 is consistently downregulated . This suggests that pathological conditions associated with diabetes, such as chronic hyperglycemia, oxidative stress, or inflammatory signals, may influence GSTM5 expression through specific regulatory mechanisms.

• Potential epigenetic regulation: The consistent downregulation of GSTM5 in disease states like DFU raises the possibility of epigenetic silencing mechanisms. These might include:

  • DNA methylation of the GSTM5 promoter region

  • Histone modifications affecting chromatin accessibility

  • Regulation by non-coding RNAs, including microRNAs that target GSTM5 mRNA

• Genetic polymorphisms: While the search results don't specifically mention GSTM5 polymorphisms, it's worth noting that other GSTM family members (particularly GSTM1) exhibit well-characterized polymorphisms, including null alleles resulting from gene deletion . The close physical proximity of GSTM genes and their high sequence homology suggests that GSTM5 might also be subject to similar genetic variation, potentially affecting its expression or function.

• Environmental factors: Given the role of GSTs in detoxification and response to environmental stressors, GSTM5 expression is likely influenced by environmental factors such as exposure to toxins, pollutants, drugs, or dietary compounds that induce detoxification pathways.

Understanding the specific regulatory mechanisms controlling GSTM5 expression would be valuable for developing therapeutic strategies aimed at modulating its levels in disease contexts.

What are the optimal approaches for detecting and quantifying GSTM5 expression in human tissue samples?

Researchers have employed several methodological approaches to detect and quantify GSTM5 expression in human tissue samples, each with specific advantages and applications:

• Microarray analysis: The studies referenced in the search results utilized microarray data from the Gene Expression Omnibus (GEO) database to analyze GSTM5 expression . Specifically, datasets GSE68183, GSE80178, and GSE134431 were used to examine expression patterns in DFU compared to control tissues. For microarray data processing:

  • Probe matrices were transformed into gene expression matrices using probe annotation files

  • For genes corresponding to multiple probes, mean values were calculated to represent expression levels

  • Standardization and batch effect correction (using the SVA package) were performed to ensure comparability across datasets

  • Principal component analysis (PCA) was used to evaluate the removal of batch effects

• Differential expression analysis: For identifying significant changes in GSTM5 expression:

  • The limma package was used to analyze differential expression between control and disease groups

  • Thresholds of |log FC| > 1 and adjusted p-value < 0.05 were applied to identify statistically significant changes

  • Visualization methods included violin plots to show expression distribution differences between groups and line graphs to illustrate expression profiles across samples

• Immunohistochemistry (IHC): For protein-level validation of GSTM5 expression:

  • IHC was used to confirm the differential expression of GSTM5 in tissue samples

  • This technique allows for visualization of protein expression patterns within the tissue context and can reveal cell type-specific expression

• PCR-based methods: For gene-specific detection:

  • Locus-specific PCR primer pairs spanning exon 6, intron 6, and exon 7 have been used for GSTM gene detection

  • These primer pairs can be adapted for quantitative PCR (qPCR) applications to quantify GSTM5 expression levels

• Southern blot hybridization: This technique has been used for confirming gene identity and structure, as demonstrated for GSTM1 with hybridization to a pair of 12.5/2.4-kb HindIII fragments . Similar approaches could be applied to GSTM5.

• Machine learning approaches: Advanced computational methods have been employed to analyze GSTM5 expression patterns:

  • LASSO and SVM-RFE machine learning models were constructed to identify genes of interest, including GSTM5

  • ROC curve analysis was used to evaluate the diagnostic performance of GSTM5 expression levels

For optimal detection and quantification of GSTM5, researchers should consider combining multiple approaches. For example, initial screening might employ high-throughput methods like microarray or RNA-seq, followed by validation with qPCR and protein-level confirmation using immunohistochemistry or Western blotting. The choice of method should be guided by the specific research question, sample availability, and required sensitivity and specificity.

How can GSTM5 activity be measured in vitro and in vivo?

Measuring GSTM5 activity, as opposed to simply its expression levels, requires assays that specifically detect its enzymatic function. Below are methodological approaches for measuring GSTM5 activity in both in vitro and in vivo contexts:

In Vitro Activity Measurement:

• Spectrophotometric enzyme assays: These assays measure the conjugation of glutathione to model substrates:

  • 1-chloro-2,4-dinitrobenzene (CDNB) is a common substrate for many GSTs, including GSTM5

  • The formation of the glutathione-substrate conjugate can be monitored by the change in absorbance at specific wavelengths

  • For GSTM5 specificity, researchers can use substrates with preferential reactivity toward mu-class GSTs

• Recombinant protein assays: Using purified recombinant GSTM5:

  • Express and purify recombinant human GSTM5 protein using bacterial, yeast, or mammalian expression systems

  • Measure enzymatic activity with various substrates to determine kinetic parameters (Km, Vmax)

  • Compare activity with other GSTM family members to identify substrate specificities

• Cell-based activity assays:

  • Transfect cells with GSTM5 expression constructs or modulate endogenous GSTM5 expression using siRNA/shRNA

  • Challenge cells with GST substrates or electrophilic compounds

  • Measure glutathione conjugation, cell viability, or oxidative stress markers as indicators of GSTM5 activity

In Vivo Activity Measurement:

• Animal models:

  • The search results mention animal experiments conducted for validation of GSTM5 findings

  • Transgenic or knockout mouse models could be developed to study GSTM5 function

  • Challenge animals with compounds metabolized by GSTM5 and measure metabolite formation in tissues or biofluids

• Biomarker approaches:

  • Measure glutathione conjugates of endogenous or xenobiotic compounds in biofluids (urine, plasma) as indicators of GSTM5 activity

  • Use mass spectrometry to identify and quantify specific GSTM5-dependent metabolites

• Ex vivo tissue assays:

  • Collect tissue samples from subjects or animal models

  • Prepare tissue homogenates or microsomes

  • Measure GSTM5-specific enzymatic activity using selective substrates

Considerations for GSTM5-Specific Activity Measurement:

• Selectivity challenges: Due to overlapping substrate specificities among GST family members, achieving GSTM5-specific activity measurement can be challenging. Approaches to address this include:

  • Using immunoprecipitation to isolate GSTM5 before activity measurement

  • Developing GSTM5-selective substrates or inhibitors

  • Comparing activity profiles in samples with known GSTM5 expression levels

• Integration with expression data: Correlating activity measurements with expression data (mRNA and protein levels) provides a more comprehensive understanding of GSTM5 regulation and function.

• Physiological relevance: When possible, activity measurements should incorporate physiologically relevant substrates or conditions to better reflect GSTM5's role in vivo.

These methodological approaches provide researchers with a toolkit for investigating GSTM5 activity in various experimental contexts, from basic biochemical characterization to physiological function in disease models.

What bioinformatics and machine learning approaches are most effective for studying GSTM5 in disease contexts?

The search results highlight several sophisticated bioinformatics and machine learning approaches that have proven effective for studying GSTM5 in disease contexts, particularly in identifying it as a biomarker for diabetic foot ulcers:

• Differential gene expression analysis:

  • The limma package was used to analyze differential expression between control and disease groups

  • Thresholds of |log FC| > 1 and adjusted p-value < 0.05 were applied to identify statistically significant changes

  • This approach effectively identified GSTM5 as being significantly downregulated in DFU samples

• Machine learning algorithms for biomarker identification:

  • LASSO (Least Absolute Shrinkage and Selection Operator): Package glmnet was used to construct a LASSO model, which is effective for feature selection and handling high-dimensional data

  • SVM-RFE (Support Vector Machine-Recursive Feature Elimination): Package e1071 was used to implement this algorithm, which iteratively removes features to identify the most discriminative genes

  • These approaches successfully identified GSTM5 as a key gene associated with DFU

• Model validation strategies:

  • Training and validation datasets: GSE68183 and GSE80178 were used as training datasets, while GSE134431 served as an independent validation set

  • This cross-dataset validation approach strengthens the reliability of findings by demonstrating consistency across different patient cohorts

• Batch effect correction and data integration:

  • The SVA package was used to address batch effects between different datasets

  • Principal Component Analysis (PCA) was employed to evaluate the effectiveness of batch effect removal

  • These techniques are crucial for integrating data from different sources or platforms

• Pathway and functional enrichment analysis:

  • Gene Ontology (GO) enrichment: Identified biological processes associated with GSTM5, such as cell-substrate adhesion and epithelial cell proliferation

  • KEGG pathway analysis: Revealed signaling pathways influenced by GSTM5, including NF-κB, GnRH, and MAPK pathways

  • Gene Set Enrichment Analysis (GSEA): Identified pathways active in high vs. low GSTM5 expression states

  • Gene Set Variation Analysis (GSVA): Assessed pathway activity changes in individual samples

  • The clusterProfiler R package was used for many of these analyses

• Immune cell infiltration analysis:

  • The CIBERSORT algorithm and LM22 gene set were used to calculate the relative abundance of 22 lymphocyte subtypes in samples

  • This approach revealed associations between GSTM5 expression and specific immune cell populations

• Diagnostic performance evaluation:

  • ROC curve analysis demonstrated the diagnostic utility of GSTM5 for identifying DFU

  • This statistical approach quantifies the potential clinical value of GSTM5 as a biomarker

• Correlation analysis and visualization:

  • Correlation heatmaps showed relationships between GSTM5 and other genes

  • Visualization of immune cell distributions and their correlations with GSTM5 expression helped elucidate its role in immune regulation

For researchers studying GSTM5 in other disease contexts, these approaches provide a methodological framework that can be adapted to different research questions. The combination of differential expression analysis, machine learning for feature selection, pathway enrichment, immune cell profiling, and rigorous validation represents a comprehensive strategy for investigating the role of GSTM5 in disease processes.

What experimental models are most appropriate for studying GSTM5 function in immune regulation?

Based on the search results and the emerging understanding of GSTM5's role in immune regulation, several experimental models would be appropriate for investigating its function:

• Cell Culture Models:

  • Immune cell lines: Given GSTM5's associations with T cells (regulatory and follicular helper) and B cells , cell lines representing these lineages would be valuable for studying its function

  • Co-culture systems: Models incorporating multiple cell types (e.g., T cells, B cells, macrophages, and dendritic cells) would allow investigation of GSTM5's role in immune cell interactions

  • Primary human immune cells: Isolation of specific immune cell populations from blood samples of healthy donors and patients with relevant conditions

• Animal Models:

  • GSTM5 knockout or transgenic mice: Although not specifically mentioned in the search results, targeted manipulation of GSTM5 expression in mice would provide insights into its physiological role

  • Diabetic mouse models: Since GSTM5 has been identified as a biomarker in diabetic foot ulcers, diabetic mouse models (e.g., streptozotocin-induced, db/db, or high-fat diet models) with subsequent wound healing studies would be relevant

  • Immune challenge models: Exposing animals to inflammatory stimuli or pathogens to assess how GSTM5 modulates immune responses

• Ex Vivo Tissue Models:

  • Human skin explants: For studying GSTM5's role in wound healing and immune cell infiltration in a complex tissue environment

  • Precision-cut tissue slices: Maintaining the tissue architecture while allowing experimental manipulation

• Disease-Specific Models:

  • Diabetic foot ulcer models: The search results specifically identify GSTM5 as a biomarker in DFU , making this a highly relevant disease context for investigation

  • Inflammatory disease models: Given GSTM5's associations with NF-κB signaling and immune cell populations , models of inflammatory conditions would be appropriate

• Molecular and Functional Assays:

  • CRISPR-Cas9 gene editing: For precise manipulation of GSTM5 expression or function

  • RNA interference: siRNA or shRNA approaches for transient or stable knockdown of GSTM5

  • Overexpression systems: To study the effects of increased GSTM5 activity

  • Reporter assays: To investigate GSTM5's influence on signaling pathways such as NF-κB

• Immunological Functional Assays:

  • T cell differentiation assays: To examine how GSTM5 affects the development of specific T cell subsets, particularly Tregs and T follicular helper cells

  • Cytokine production assays: To measure how GSTM5 modulation affects immune cell activation and cytokine secretion

  • Migration and adhesion assays: Given GSTM5's association with cell-substrate adhesion , these assays would be relevant

  • Phagocytosis and antigen presentation assays: To investigate GSTM5's role in innate immune functions

• Omics Approaches:

  • Transcriptomics: RNA-seq to identify genes and pathways affected by GSTM5 modulation

  • Proteomics: To identify GSTM5 interacting partners and affected proteins

  • Metabolomics: To assess changes in metabolic profiles, particularly those related to glutathione metabolism and oxidative stress

  • Single-cell sequencing: To examine cell type-specific effects of GSTM5 in heterogeneous immune cell populations

When designing experiments with these models, researchers should carefully consider the specific aspects of GSTM5 function they aim to investigate (e.g., enzymatic activity, signaling pathway regulation, or immune cell interactions) and select the most appropriate model accordingly. Combining multiple complementary approaches would provide the most comprehensive understanding of GSTM5's role in immune regulation.

What is the potential of GSTM5 as a biomarker for diabetic foot ulcers and other conditions?

GSTM5 demonstrates considerable promise as a biomarker, particularly for diabetic foot ulcers, based on several lines of evidence:

• Consistent differential expression: GSTM5 is consistently downregulated in DFU tissue compared to normal control tissue across multiple independent datasets (GSE68183, GSE80178, and validated in GSE134431) . This reproducibility across different patient cohorts strengthens its potential as a reliable biomarker.

• Strong diagnostic performance: ROC curve analysis demonstrates that GSTM5 has good diagnostic performance for identifying DFU . The downregulation pattern makes it a potentially useful negative biomarker (where decreased levels indicate disease).

• Machine learning validation: Two independent machine learning approaches (LASSO and SVM-RFE) identified GSTM5 as a key gene associated with DFU, further supporting its biomarker potential .

• Biological relevance: GSTM5's involvement in detoxification, immune regulation, and inflammatory processes provides a mechanistic basis for its role in DFU pathophysiology , making it a biologically plausible biomarker rather than merely a statistical association.

• Relationship to immune infiltration: GSTM5 expression correlates with specific patterns of immune cell infiltration in tissues , suggesting it might serve as a biomarker not only for disease presence but also for specific immunological phenotypes.

The diagnostic performance metrics for GSTM5 as a DFU biomarker, based on the available data, can be summarized as follows:

• Other chronic wounds: Similar pathophysiological mechanisms may be involved in different types of non-healing wounds

• Inflammatory conditions: Given its association with NF-κB signaling and immune cell populations

• Conditions involving oxidative stress: Due to its role in detoxification and antioxidant defense

For clinical application as a biomarker, several practical considerations would need to be addressed:

• Tissue vs. circulating biomarker: The current evidence is based on tissue expression , but blood-based biomarkers would be more practical for routine clinical use

• Standardization of measurement methods: Establishing standardized protocols for GSTM5 quantification

• Determination of reference ranges and cutoff values: For distinguishing normal from pathological states

• Combination with other biomarkers: GSTM5 might be most valuable as part of a multi-marker panel for improved diagnostic accuracy

The growing evidence for GSTM5 as a biomarker justifies further investigation in larger clinical cohorts and exploration of its utility in additional disease contexts.