Integrative genomic and transcriptomic analysis of genetic markers in Dupuytren's disease

Molecular genetics of Dupuytren's contracture

Dupuytren's contracture (DC) is a fibroproliferative disorder of the palmar fascia characterised by the digits' flexion contractures and is associated with abnormal build-up of type III collagen. The prevalence of the disease is reported to be highest among Northern European descendants. However, the disease is widespread globally with varying prevalence. DC is a multifactorial disease, having both genetic and environmental factors contributing to the causality of the disease. Over the years, various studies have been conducted to understand the molecular mechanism and genetic aspects of DC but there is a lack of reports on the variants found in the exonic regions. Most reports are backdated making it necessary to re-evaluate the variants to further understand the genetic aetiology of DC. In this review, we first highlight the genetic aspects and previous genetic studies on DC. The report is followed by a discussion on the molecular pathways suggested to be associated with DC and a summary of the genetic variants in the exonic regions found in DC and their connections with the molecular pathways. A total of nine variants were reported originating from six genes comprising three pathways. Most variants reported are involved in the Wnt signalling pathway. Moreover, all variants identified are in European/Caucasian subjects and the variants found in the exonic regions are missense variants. A comparison of these findings with variants from populations of other regions can be conducted to identify the variants with the most occurrence to act as biomarkers or therapeutic targets for DC.

Large-scale integrative analysis of juvenile idiopathic arthritis for new insight into its pathogenesis

BACKGROUND

Juvenile idiopathic arthritis (JIA) is one of the most prevalent rheumatic disorders in children and is classified as an autoimmune disease (AID). While a robust genetic contribution to JIA etiology has been established, the exact pathogenesis remains unclear.

METHODS

To prioritize biologically interpretable susceptibility genes and proteins for JIA, we conducted transcriptome-wide and proteome-wide association studies (TWAS/PWAS). Then, to understand the genetic architecture of JIA, we systematically analyzed single-nucleotide polymorphism (SNP)-based heritability, a signature of natural selection, and polygenicity. Next, we conducted HLA typing using multi-ethnicity RNA sequencing data. Additionally, we examined the T cell receptor (TCR) repertoire at a single-cell level to explore the potential links between immunity and JIA risk.

RESULTS

We have identified 19 TWAS genes and two PWAS proteins associated with JIA risks. Furthermore, we observe that the heritability and cell type enrichment analysis of JIA are enriched in T lymphocytes and HLA regions and that JIA shows higher polygenicity compared to other AIDs. In multi-ancestry HLA typing, B*45:01 is more prevalent in African JIA patients than in European JIA patients, whereas DQA1*01:01, DQA1*03:01, and DRB1*04:01 exhibit a higher frequency in European JIA patients. Using single-cell immune repertoire analysis, we identify clonally expanded T cell subpopulations in JIA patients, including CXCL13+BHLHE40+ TH cells which are significantly associated with JIA risks.

CONCLUSION

Our findings shed new light on the pathogenesis of JIA and provide a strong foundation for future mechanistic studies aimed at uncovering the molecular drivers of JIA.

RNA-seq unravels distinct expression profiles of keloids and Dupuytren's disease

Keloid scars and Dupuytren's disease are two common, chronic, and incurable fibroproliferative disorders that, among other shared clinical features, may induce joint contractures. We employed bulk RNA sequencing to discern potential shared gene expression patterns and underlying pathological pathways between these two conditions. Our aim was to uncover potential molecular targets that could pave the way for novel therapeutic strategies. Differentially expressed genes (DEGs) were functionally annotated using Gene Ontology (GO) terms and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways with the Database for Annotation, Visualization, and Integrated Discovery (DAVID). The protein-protein-interaction (PPI) networks were constructed by using the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape. The Molecular Complex Detection (MCODE) plugin was used for downstream analysis of the PPI networks. A total of 1922 DEGs were identified within Dupuytren's and keloid samples, yet no overlapping gene expression profiles were detected. Significantly enriched GO terms were related to skin development and tendon formation in keloid scars and Dupuytren's disease, respectively. The PPI network analysis revealed 10 genes and the module analysis provided six protein networks, which might play an integral part in disease development. These genes, including CDH1, ERBB2, CASP3 and RPS27A, may serve as new targets for future research to develop biomarkers and/or therapeutic agents.

The prevalence of Dupuytren's disease in patients with diabetes mellitus

BACKGROUND

Dupuytren's disease (DD) is a fibroproliferative hand disorder associated with various medical conditions, including diabetes mellitus (DM). The reported prevalence of DM among DD patients varies widely, primarily due to small sample sizes in previous studies.

METHODS

This was a retrospective cohort study using data from the TriNetX Research Database. We analyzed the overall prevalence of DD between 2010 and 2020, comparing the DM, type 1 diabetes mellitus (T1DM), and type 2 diabetes mellitus (T2DM) cohorts. Within the DM group, patients were further categorized based on hemoglobin A1c (HbA1c) values and prescribed anti-diabetic agents (insulin or metformin). We compared the prevalence of DD diagnosis in each group using prevalence ratios and differences.

RESULTS

There is a higher prevalence of DD in patients with T2DM than in patients with T1DM (relative risk [RR]: 1.641; 95% confidence interval [CI]: [1.356, 1.986]). Among patients with diabetes, there is a higher prevalence of DD in those taking insulin compared to those taking metformin (RR: 0.801, 95% CI: [0.774, 0.83]). The prevalence of DD varies depending on HbA1c levels, with a prevalence of 0.463% in patients having levels within the diabetic range, while lower prevalences of 0.392% and 0.416% are found in patients with prediabetes or uncontrolled diabetes, respectively.

CONCLUSIONS

This study provides further insight into the relationship between DM and DD. These findings may be attributed to the increased accumulation of advanced glycosylated end products (AGEs) in patients with diabetes. Future research exploring the connection between AGE accumulation and DD development may enhance our understanding of the relationship between DD and DM.

An in-silico approach to studying a very rare neurodegenerative disease using a disease with higher prevalence with shared pathways and genes: Cerebral adrenoleukodystrophy and Alzheimer’s disease

Cerebral adrenoleukodystrophy (cALD) is a rare neurodegenerative disease characterized by inflammatory demyelination in the central nervous system. Another neurodegenerative disease with a high prevalence, Alzheimer’s disease (AD), shares many common features with cALD such as cognitive impairment and the alleviation of symptoms by erucic acid. We investigated cALD and AD in parallel to study the shared pathological pathways between a rare disease and a more common disease. The approach may expand the biological understandings and reveal novel therapeutic targets. Gene set enrichment analysis (GSEA) and weighted gene correlation network analysis (WGCNA) were conducted to identify both the resemblance in gene expression patterns and genes that are pathologically relevant in the two diseases. Within differentially expressed genes (DEGs), GSEA identified 266 common genes with similar up- or down-regulation patterns in cALD and AD. Among the interconnected genes in AD data, two gene sets containing 1,486 genes preserved in cALD data were selected by WGCNA that may significantly affect the development and progression of cALD. WGCNA results filtered by functional correlation via protein–protein interaction analysis overlapping with GSEA revealed four genes (annexin A5, beta-2-microglobulin, CD44 molecule, and fibroblast growth factor 2) that showed robust associations with the pathogeneses of cALD and AD, where they were highly involved in inflammation, apoptosis, and the mitogen-activated protein kinase pathway. This study provided an integrated strategy to provide new insights into a rare disease with scant publicly available data (cALD) using a more prevalent disorder with some pathological association (AD), which suggests novel druggable targets and drug candidates.

Evaluation of WNT Signaling Pathway Gene Variants WNT7B rs6519955, SFRP4 rs17171229 and RSPO2 rs611744 in Patients with Dupuytren's Contracture

Dupuytren’s contracture (DC) represents a chronic fibroproliferative pathology of the palmar aponeurosis, which leads to flexion contractures of finger joints and hand disability. In recent decades, the WNT signaling pathway has been revealed to play a significant role in the manifestation and pathogenesis of DC. Our study aimed to evaluate the associations between Dupuytren’s contracture and WNT-related single-nucleotide polymorphisms: Wnt Family Member 7B (WNT7B) rs6519955 (G/T), Secreted Frizzled Related Protein 4 (SFRP4) rs17171229 (C/T) and R-spondin 2 (RSPO2) rs611744 (A/G). We enrolled 216 patients (113 DC cases and 103 healthy controls), and DNA samples were extracted from the peripheral blood. Genotyping of WNT7B rs6519955, SFRP4 rs17171229 and RSPO2 rs611744 was performed using the Real-Time PCR System 7900HT from Applied Biosystems. WNT7B rs6519955 genotype TT carriers were found to possess a higher prevalence of DC (OR = 3.516; CI = 1.624–7.610; p = 0.001), whereas RSPO2 rs611744 genotype GG appears to reduce the likelihood of the manifestation of DC nearly twofold (OR = 0.484, CI = 0.258–0.908, p = 0.024). In conclusion, SNPs WNT7B rs6519955 and RSPO2 rs611744 are associated with the development of Dupuytren’s contracture: WNT7B rs6519955 TT genotype increases the chances by 3.5-fold, and RSPO2 rs611744 genotype GG appears to attenuate the likelihood of the manifestation of DC nearly twofold. Findings of genotype distributions among DC patients and control groups suggest that SFRP4 rs17171229 is not significantly associated with development of the disease.

An Integrative Transcriptomic Analysis of Systemic Juvenile Idiopathic Arthritis for Identifying Potential Genetic Markers and Drug Candidates

Systemic juvenile idiopathic arthritis (sJIA) is a rare subtype of juvenile idiopathic arthritis, whose clinical features are systemic fever and rash accompanied by painful joints and inflammation. Even though sJIA has been reported to be an autoinflammatory disorder, its exact pathogenesis remains unclear. In this study, we integrated a meta-analysis with a weighted gene co-expression network analysis (WGCNA) using 5 microarray datasets and an RNA sequencing dataset to understand the interconnection of susceptibility genes for sJIA. Using the integrative analysis, we identified a robust sJIA signature that consisted of 2 co-expressed gene sets comprising 103 up-regulated genes and 25 down-regulated genes in sJIA patients compared with healthy controls. Among the 128 sJIA signature genes, we identified an up-regulated cluster of 11 genes and a down-regulated cluster of 4 genes, which may play key roles in the pathogenesis of sJIA. We then detected 10 bioactive molecules targeting the significant gene clusters as potential novel drug candidates for sJIA using an in silico drug repositioning analysis. These findings suggest that the gene clusters may be potential genetic markers of sJIA and 10 drug candidates can contribute to the development of new therapeutic options for sJIA.

Meta-Analysis of Polymyositis and Dermatomyositis Microarray Data Reveals Novel Genetic Biomarkers

Polymyositis (PM) and dermatomyositis (DM) are both classified as idiopathic inflammatory myopathies. They share a few common characteristics such as inflammation and muscle weakness. Previous studies have indicated that these diseases present aspects of an auto-immune disorder; however, their exact pathogenesis is still unclear. In this study, three gene expression datasets (PM: 7, DM: 50, Control: 13) available in public databases were used to conduct meta-analysis. We then conducted expression quantitative trait loci analysis to detect the variant sites that may contribute to the pathogenesis of PM and DM. Six-hundred differentially expressed genes were identified in the meta-analysis (false discovery rate (FDR) < 0.01), among which 317 genes were up-regulated and 283 were down-regulated in the disease group compared with those in the healthy control group. The up-regulated genes were significantly enriched in interferon-signaling pathways in protein secretion, and/or in unfolded-protein response. We detected 10 single nucleotide polymorphisms (SNPs) which could potentially play key roles in driving the PM and DM. Along with previously reported genes, we identified 4 novel genes and 10 SNP-variant regions which could be used as candidates for potential drug targets or biomarkers for PM and DM.