Beyond COVID-19 in people with HIV: Specific miRNA expression profile persist after SARS-CoV-2 clearance, 2026, Grande-García et al.

[SNT Gatchaman]

Beyond COVID-19 in people with HIV: Specific miRNA expression profile persist after SARS-CoV-2 clearance

Spoiler: Authors

Grande-García; Llamas-Adán; Crespo-Bermejo; Lara-Aguilar; Arca-Lafuente; Martín-Carbonero; Ryan; Santos; de Lagarde; Mican-Rivera; Moreno; Resino; Berenguer; Briz; Fernández-Rodríguez

BACKGROUND
The impact of SARS-CoV-2 on epigenetic regulation in people with HIV (PWHIV) is not well understood. MicroRNAs, key post-transcriptional regulators, may serve as biomarkers of disease. This study aimed to identify plasma miRNAs reflecting epigenetic changes in PWHIV after SARS-CoV-2 resolution.

METHODS
We sequenced plasma smallRNA from 20 PWHIV at a median of 10 weeks after SARS-CoV-2 infection, and 18 SARS-CoV-2 uninfected and unvaccinated PWHIV. MirDeep2 was used for miRNA identification, and significant differential expression (SDE) and classification performance were calculated using GLMs and PLS-DA. Correlations were performed using spearman test. Target enrichment was analyzed using miRTarbase, RNAInter, and KEGG databases, and tissue expression was analysed using the IMOTA database.

RESULTS
Thirty-five microRNAs were SDE between groups. Hsa-mir-181a-2–3p was correlated to time elapsed since SARS-CoV-2 infection and sampling. Functional enrichment analysis predicted 410 target genes, which in turn overrepresented 52 cellular pathways, mainly related to neurodegeneration, major signaling cascades, and oncologic and cardiovascular diseases. The most significant pathways were Huntingtons disease and PI3K-Akt signalling pathway, while those with the highest number of targeted genes were Pathways of neurodegeneration and Alzheimers disease. The hsa-miR-374b-5p showed excellent predictive ability in classifying the SARS-CoV-2 infection status in more than 93% of all instances.

CONCLUSION
SARS-CoV-2 infection in PWHIV leaves an epigenetic signature of 35 SDE microRNAs, with hsa-miR-374b-5p as a strong post-infection marker. These microRNAs regulate genes mainly involved in neurodegenerative, cardiovascular, and oncologic processes, potentially underlying post-COVID symptomatology.

Web | DOI | Journal of Infection and Public Health | Open Access

 

[SNT Gatchaman]

if we rank the overrepresented pathways according to their p-value, the most significant were Huntington’s disease, PI3K-Akt signalling pathway and Parkinson’s disease.

Potentially of relevance to The genetic architecture of fibromyalgia across 2.5 million individuals (2025) —

The most significant association in the combined ancestry analysis was with rs149109767-A (OR = 1.09, p = 2.2 × 10-12), an inframe glutamic acid deletion in the Huntingtin (HTT) gene.

 

[hotblack]

Those 3 also looks like they have the highest FDRs and visually are above 0.05 although I think they mention using that as the cutoff? Am I reading that right? Just wondering if it’s relevant, only recently started learning about false discovery rates!

 

[forestglip]

Hmm, that's confusing. The paper points to Supplementary Table 7:

In total, 52 cellular pathways, according to the KEGG database, were overrepresented, with the most genes involved in neurodegenerative diseases, cancer and multiple infectious diseases (Fig. 2B; Supplementary Data 7). Specifically, if we rank the overrepresented pathways according to their p-value, the most significant were Huntington's disease, PI3K-Akt signalling pathway and Parkinson's disease.

But the table doesn't include any of these three that they say are most significant:

Supplementary Data 7: Functional enrichment analysis of KEGG overrepresented pathways associated with differentially expressed miRNAs. Only FDR adjusted -p-value significantly enriched KEGG pathways are shown, indicating the description of the pathway, the GeneRatio (proportion of genes associated with the pathway among the genes analysed), the BgRatio (proportion of genes associated in the reference genome), the adjusted significance value (p.adjust) and the total number of genes involved (Count).

Colorectal cancer is most significant, as suggested by the plot above. So I think they looked at the top three terms in their plot above instead of the bottom three by accident when writing the text.

But even so, the FDR values don't match up with the supplementary data, and the order of significance is different. For colorectal cancer, the plot shows somewhere around FDR=.01, but the table shows p=2.3304E-06.

 

[hotblack]

Hmm, that's confusing

Thanks for digging in to this. Something seemed off but I wasn’t sure if it was me or the paper! Great to have an explanation.