New study IDs 4 copper metabolism genes as possible biomarkers for PAH
Use of computer software tools may help improve diagnostic tests
Four genes associated with the metabolism of copper in the body have been identified as potential diagnostic biomarkers of pulmonary arterial hypertension (PAH), a new study reports.
Researchers used computer software tools to look for specific genes tied to copper metabolism that may serve as less-invasive markers for diagnosing PAH, by testing bloodwork.
“The results of this study may have significant implications for the development of new diagnostic biomarkers and actionable targets to expand treatment options for PAH patients,” the researchers wrote.
The study, “Identification of biomarkers related to copper metabolism in patients with pulmonary arterial hypertension,” was published in the journal BMC Pulmonary Medicine.
Investigating genes related to copper metabolism
PAH is caused by the narrowing of the pulmonary arteries, the blood vessels that transport blood from the heart to the lungs. This restricts blood flow and causes high blood pressure, or hypertension.
Right heart catheterization is the gold standard test to confirm PAH. However, this is an invasive test that requires the use of a catheter inserted into a vein in the neck or groin to measure the pressure in the heart and lungs.
Bloodwork to detect changes in the levels of certain proteins — suggested as biomarkers for PAH — could be a less invasive method of diagnosis. But no single blood biomarker has shown enough accuracy for the diagnosis of PH.
Growing evidence suggests that PAH is linked with metabolic alterations in the pulmonary arteries, including in the metabolism of copper. In fact, copper has been proposed as a biomarker for PAH. However, the genes related to copper metabolism that are implicated in PAH are still unclear.
“Copper participates in PAH development, but the role of specific genes related to copper metabolism in pathogenesis [disease processes] of PAH remain to be determined,” the scientists wrote, noting that doing so “would help to identify potential treatment targets and biomarkers.”
The team, from Xi’an, in China, sought to address this knowledge gap by conducting a computational analysis. To that end, the researchers obtained PAH-related genes from two datasets of the Gene Expression Omnibus (GEO), a public database of functional genomic data submitted by the scientific community, and the copper metabolism-related genes from the GeneCards database.
When compared with control samples without PAH, a total of 814 genes had different levels of activity in the PAH group. In all, 85 genes were associated with copper metabolism.
Further analysis, namely the weighted gene coexpression network analysis (WGCNA), was used to assess the relationships between different gene sets (modules) and PAH. That assessment identified 10 candidate key genes of copper metabolism with potential diagnostic value for PAH.
The researchers then conducted two additional computational analyses, called support vector machine and least absolute shrinkage and selection operator regression, that identified four copper metabolism-related genes — called DDIT3, NFKBIA, OSM, and PTGER4 — as biomarkers for PAH diagnosis.
Training and testing sets were built using 30 PAH and 41 control samples, and further supported the “high predictive effectiveness of the [diagnostic] model.”
Overall, the expression (activity) of the four genes was reduced in PAH. The team then assessed gene expression in eight new PAH and control clinical samples. They were able to confirm the reduced expression of the NFKBIA and OSM genes, but not of DDIT3 and PTGER4. This likely was linked to “sample heterogeneity or limited sample size,” the scientists wrote.
Copper metabolism has potential as a new diagnostic biomarker as well as a targeted therapy for PAH.
In agreement with the role of inflammation in PAH, and as previously reported, the profile of immune cells was markedly different between PAH and control samples.
Activity levels of the OSM gene showed the most significant positive correlation — meaning the greater one, the greater the other — with resting memory CD4 T cells. These T cells are a type of immune cells that serve as a memory of sorts from past infections, and can mount a response more quickly upon another exposure.
Meanwhile, with neutrophils — immune cells involved in inflammation — DDIT3 had the most significant negative correlation, meaning the greater one, the lower the other.
Finally, the investigators developed a gene-drug network and found that the activity of 27 therapies was predicted by DDIT3, and 21 therapies by PTGER4. Another nine were predicted by NFKBIA, while one, the anti-inflammatory interleukin-10, was predicted by OSM.
The therapies linked with both DDIT3 and PTGER4 were the anti-inflammatories ibuprofen and celecoxib, and the cancer treatment streptozocin.
“In summary, this study identified four copper metabolism-related biomarkers (DDIT3, NFKBIA, OSM, and PTGER4) with considerable diagnostic values based on bioinformatics analyses, and further constructed a gene- drug network,” the researchers wrote.
“Copper metabolism has potential as a new diagnostic biomarker as well as a targeted therapy for PAH, while the underlying mechanisms need to be clarified further in future studies,” the team concluded.
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