Blood co-expression modules identify potential modifier genes of diabetes and lung function in cystic fibrosis

Unlocking the genetic tapestry of autoimmune diseases: Unveiling common genes across multiple conditions

OBJECTIVES

This study aimed to unravel the complexities of autoimmune diseases by conducting a comprehensive analysis of gene expression data across 10 conditions, including systemic lupus erythematosus (SLE), psoriasis, Sjögren's syndrome, sclerosis, immune-associated diseases, osteoarthritis, cystic fibrosis, inflammatory bowel disease (IBD), type 1 diabetes, and Guillain-Barré syndrome.

METHODS

Gene expression profiles were rigorously examined to identify both upregulated and downregulated genes specific to each autoimmune disease. The study employed visual representation techniques such as heatmaps, volcano plots, and contour-MA plots to provide an intuitive understanding of the complex gene expression patterns in these conditions.

RESULTS

Distinct gene expression profiles for each autoimmune condition were uncovered, with psoriasis and osteoarthritis standing out due to a multitude of both upregulated and downregulated genes, indicating intricate molecular interplays in these disorders. Notably, common upregulated and downregulated genes were identified across various autoimmune conditions, with genes like SELENBP1, MMP9, BNC1, and COL1A1 emerging as pivotal players.

CONCLUSION

This research contributes valuable insights into the molecular signatures of autoimmune diseases, highlighting the unique gene expression patterns characterizing each condition. The identification of common genes shared among different autoimmune conditions, and their potential role in mitigating the risk of rare diseases in patients with more prevalent conditions, underscores the growing significance of genetics in healthcare and the promising future of personalized medicine.

Lack of association between leptin concentrations and cystic fibrosis: A meta-analysis and regression

BACKGROUND

Leptin (LEP) acts as a proinflammatory cytokine and may play an important role in the pathophysiology of cystic fibrosis (CF). This review aimed to assess the quantitative difference in leptin status between CF patients and non-CF controls.

METHODS

In this study, the researchers conducted systematic searches of various databases, such as PubMed, Excerpta Medica Database, Google Scholar, Web of Science, and the China National Knowledge Infrastructure. The data collected from the above databases were assessed using the Stata 11.0 and R 4.1.3 software. The correlation coefficients and the Standardized Mean Differences (SMD) were employed to assess the effect size. A combination analysis was also carried out with the help of either a fixed-effects or random-effects model. In addition, the single-cell sequencing GSE193782 dataset was obtained to determine the mRNA expression levels of LEP and leptin receptor (LEPR) in the bronchoalveolar lavage fluid, to verify the different leptin expression between the CF patients and healthy controls.

RESULTS

A total of 919 CF patients and 397 controls from 14 articles were included in this study. CF patients and non-CF controls showed similar serum/plasma leptin levels. Gender, specimen testing, age, and study design were all taken into account for carrying out subgroup analyses. The results revealed no variations in serum/plasma leptin levels between the controls and CF patients in the various subgroups. Female CF patients exhibited higher leptin concentrations compared to male CF patients, and male healthy individuals showed lower leptin levels than female healthy participants. Aside from the fact that serum/plasma leptin appeared to be favorably linked to fat mass and BMI, the findings in this study also indicated that serum/plasma concentrations were not associated with Forced Expiratory Volume in the first second (FEV1). No statistically significant differences were observed in the leptin and leptin receptor mRNA expression levels between the healthy controls and CF patients. The leptin receptor and leptin expression levels in alveolar lavage fluid were low in various cells, without any distinctive distribution patterns.

CONCLUSIONS

The current meta-analysis indicated the absence of significant differences in leptin levels between CF patients and healthy individuals. Gender, fat mass, and BMI may all be correlated with leptin concentrations.

SYSTEMATIC REVIEW REGISTRATION

https://www.crd.york.ac.uk/prospero/, identifier CRD42022380118.

Identification of human mitochondrial RNA cleavage sites and candidate RNA processing factors

BACKGROUND

The human mitochondrial genome is transcribed as long strands of RNA containing multiple genes, which require post-transcriptional cleavage and processing to release functional gene products that play vital roles in cellular energy production. Despite knowledge implicating mitochondrial post-transcriptional processes in pathologies such as cancer, cardiovascular disease and diabetes, very little is known about the way their function varies on a human population level and what drives changes in these processes to ultimately influence disease risk. Here, we develop a method to detect and quantify mitochondrial RNA cleavage events from standard RNA sequencing data and apply this approach to human whole blood data from > 1000 samples across independent cohorts.

RESULTS

We detect 54 putative mitochondrial RNA cleavage sites that not only map to known gene boundaries, short RNA ends and RNA modification sites, but also occur at internal gene positions, suggesting novel mitochondrial RNA cleavage junctions. Inferred RNA cleavage rates correlate with mitochondrial-encoded gene expression across individuals, suggesting an impact on downstream processes. Furthermore, by comparing inferred cleavage rates to nuclear genetic variation and gene expression, we implicate multiple genes in modulating mitochondrial RNA cleavage (e.g. MRPP3, TBRG4 and FASTKD5), including a potentially novel role for RPS19 in influencing cleavage rates at a site near to the MTATP6-COX3 junction that we validate using shRNA knock down data.

CONCLUSIONS

We identify novel cleavage junctions associated with mitochondrial RNA processing, as well as genes newly implicated in these processes, and detect the potential impact of variation in cleavage rates on downstream phenotypes and disease processes. These results highlight the complexity of the mitochondrial transcriptome and point to novel mechanisms through which nuclear-encoded genes can potentially influence key mitochondrial processes.

Cystic Fibrosis: Systems Biology Analysis from Homozygous p.Phe508del Variant Patients' Samples Reveals Perturbations in Tissue-Specific Pathways

Cystic fibrosis (CF) is an autosomal recessive disorder, caused by diverse genetic variants for the CF transmembrane conductance regulator (CFTR) protein. Among these, p.Phe508del is the most prevalent variant. The effects of this variant on the physiology of each tissue remains unknown. This study is aimed at predicting cell signaling pathways present in different tissues of fibrocystic patients, homozygous for p.Phe508del. The study involved analysis of two microarray datasets, E-GEOD-15568 and E-MTAB-360 corresponding to the rectal and bronchial epithelium, respectively, obtained from the ArrayExpress repository. Particularly, differentially expressed genes (DEGs) were predicted, protein-protein interaction (PPI) networks were designed, and centrality and functional interaction networks were analyzed. The study reported that p.Phe508del-mutated CFTR-allele in homozygous state influenced the whole gene expression in each tissue differently. Interestingly, gene ontology (GO) term enrichment analysis revealed that only “neutrophil activation” was shared between both tissues; however, nonshared DEGs were grouped into the same GO term. For further verification, functional interaction networks were generated, wherein no shared nodes were reported between these tissues. These results suggested that the p.Phe508del-mutated CFTR-allele in homozygous state promoted tissue-specific pathways in fibrocystic patients. The generated data might further assist in prediction diagnosis to define biomarkers or devising therapeutic strategies.

Cystic Fibrosis-Related Diabetes (CFRD): Overview of Associated Genetic Factors

Cystic fibrosis (CF) is the most common autosomal recessive disease in the Caucasian population and is caused by mutations in the CF transmembrane conductance regulator (CFTR) gene that encodes for a chloride/bicarbonate channel expressed on the membrane of epithelial cells of the airways and of the intestine, as well as in cells with exocrine and endocrine functions. A common nonpulmonary complication of CF is cystic fibrosis-related diabetes (CFRD), a distinct form of diabetes due to insulin insufficiency or malfunction secondary to destruction/derangement of pancreatic betacells, as well as to other factors that affect their function. The prevalence of CFRD increases with age, and 40–50% of CF adults develop the disease. Several proposed hypotheses on how CFRD develops have emerged, including exocrine-driven fibrosis and destruction of the entire pancreas, as well as contrasting theories on the direct or indirect impact of CFTR mutation on islet function. Among contributors to the development of CFRD, in addition to CFTR genotype, there are other genetic factors related and not related to type 2 diabetes. This review presents an overview of the current understanding on genetic factors associated with glucose metabolism abnormalities in CF.

DNA Methylation at ATP11A cg11702988 Is a Biomarker of Lung Disease Severity in Cystic Fibrosis: A Longitudinal Study

Cystic fibrosis (CF) is a chronic genetic disease that mainly affects the respiratory and gastrointestinal systems. No curative treatments are available, but the follow-up in specialized centers has greatly improved the patient life expectancy. Robust biomarkers are required to monitor the disease, guide treatments, stratify patients, and provide outcome measures in clinical trials. In the present study, we outline a strategy to select putative DNA methylation biomarkers of lung disease severity in cystic fibrosis patients. In the discovery step, we selected seven potential biomarkers using a genome-wide DNA methylation dataset that we generated in nasal epithelial samples from the MethylCF cohort. In the replication step, we assessed the same biomarkers using sputum cell samples from the MethylBiomark cohort. Of interest, DNA methylation at the cg11702988 site (ATP11A gene) positively correlated with lung function and BMI, and negatively correlated with lung disease severity, P. aeruginosa chronic infection, and the number of exacerbations. These results were replicated in prospective sputum samples collected at four time points within an 18-month period and longitudinally. To conclude, (i) we identified a DNA methylation biomarker that correlates with CF severity, (ii) we provided a method to easily assess this biomarker, and (iii) we carried out the first longitudinal analysis of DNA methylation in CF patients. This new epigenetic biomarker could be used to stratify CF patients in clinical trials.