Preprint Mitochondrial Gene Signatures Illuminate Mitochondrial Function as an Important Contributor to Post-COVID Recovery and Long COVID Progression, 2024,..

[pooriepoor91]

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4950019

Authors: Ana R. Silverstein, Junxiang Wan, Kelvin Yen, Hemal H. Mehta, Hiroshi Kumagai, Melanie Flores, Jesse Goodrich, Howard Hu, Jeffrey D. Klausner, Omid Akbari, Igor Koralnik, Pinchas Cohen

Abstract
Long COVID, affecting an estimated 200 million individuals worldwide, is a poorly understood multisystem disorder following severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection, with unclear causative factors. However, given common symptoms such as brain fog and chronic fatigue, we suggest that long COVID is partially regulated by changes to mitochondrial genes and energy homeostasis. We explore this here by assessing the differences in acute mitochondrial signatures between retrospectively diagnosed COVID convalescent and long COVID patients using two cohorts.

For transcriptomic analyses, whole-blood RNA-seq results from publicly accessible data were extracted, assigned long-COVID or convalescent diagnosis retrospectively at 6-months post infection, and compared against non-symptomatic controls to assess for changes in mitochondrial specific gene signatures at 0-3 weeks post infection; revealing distinct mitochondrial gene expression patterns in those with and without long COVID manifestation.

For proteomic analyses, plasma samples from 20 long COVID and 20 age- and sex matched COVID-convalescent participants were selected from the Southern California Clinical and Translational Science Institute COVID biorepository, and correlations between levels of 37 inflammatory biomarkers and three mitochondrial-derived peptides (MDPs) were assessed, revealing unique biomarker clustering between patients with and without long COVID.

Combined, these findings suggest that successful COVID recovery is mediated in part by efficient mitochondrial repair and reduced oxidative stress, while mitochondrial dysfunction and continued dysregulation of mitochondrial gene expression contributes to chronic inflammation and long COVID onset.

 

[Hutan]

University of Southern California

Funding: This study was supported by NIA grants R01 AG069698, R01 AG068405, P30 AG068345, P30 ES007048, and grant UL1TR001855 from the National Center for Advancing Translational Science (NCATS) of the U.S. National Institutes of Health.

we aimed to identify profiles of mitochondrial gene dysregulation that are present in early stages of post-
COVID recovery which may contribute to long COVID manifestation.

In addition to exploring the underlying mitochondrial-specific mechanisms contributing to long COVID progression, we consider the role of mitochondrial-derived peptides (MDPs) as indicators of mitochondrial health. Mitochondrial-derived peptides, deriving from alternative short open reading frames (sORFs) in the mitochondrial genome, act as unique mitochondrial signaling molecules across various biological contexts [22]. Previously, a reduction in circulating levels of the MDP humanin and an increase in levels of the MDP MOTS-c were observed in COVID-19 patients during initial onset of infection [23]. Thus, we aimed to explore the role of MDPs in
modulating post-COVID recovery by assessing the relationship between selected MDPs and levels of pro-inflammatory biomarkers in patients with or without a later long COVID diagnosis.

 

[Hutan]

METHOD
A. Mitochondrial gene analysis

samples were selected from a pool of patients that were admitted to the Mount Sinai Health System
between April and June 2020.

Hospitalised - but this was in 2020 when maybe everyone who was positive may have been hospitalised

Between February and July of 2021, a questionnaire was administered to determine the presence of persistent long-COVID symptoms. RNA-seq samples from those that filled out the questionnaire were retrospectively defined as “Recovered” or “Not Recovered”, all who did not fill out the questionnaire were defined as “Unknown”.

For assessment of NEM differentially expressed genes (DEGs), a sample raw gene-count matrix of 1,392 prepared RNA-seq samples from 567 individuals (495 COVID-19 diagnosed and 72 non-infected controls) was loaded from Gene Expression Omnibus (GEO) into R (v4.3.1), and genes with at least two counts greater than ten were kept. 16 samples were removed for overall low read counts (< 10) across all genes. Samples were labeled based on time of sample collection, Long COVID status, and questionnaire
completion (determined by “Recovered”, “Not Recovered”, or “Unknown” definitions).

DEG analysis was then conducted using the DESeq2 R package and adjusted for age and sex, followed by NEM enrichment analysis using previously published methodology

​

B. Relationship between Mitochondrial derived peptides (MDPs) and inflammatory markers

Samples were provided from archived plasma taken from 40 patients, 20 convalescent and 20 long COVID

Samples were age-and sex-matched, and classification as “convalescent” or “Neuro-PASC” long COVID was based on a binned approach from
questionnaire answers related to cognition.

Samples taken 4 weeks after infection.
20 Neurological-PASC (10 male, 10 female)
20 Convalescent (less than 3 NeuroPASC symptoms)
(I don't think number of symptoms is a very good measure. Fatigue is not a possible symptom, although malaise is.)

measuring the levels of 37 inflammation-associated biomarkers as well as three previously published MDPs; humanin, MOTS-c, and SHMOOSE.

 

[Hutan]

RESULTS
Part A

495 hospitalized COVID-19 patients at approximate timepoints of 0-3 weeks post infection

a retrospective assessment of long COVID diagnosis was conducted in 165 patients with RNA-seq, defining a subset of previouslyinfected patients as having long-COVID, and a subset as being COVID convalescent (or fully
recovered)

I can't see how many of the 165 patients were labelled as having long COVID for the Part A analysis - can anyone find that?

Of interest, long COVID diagnosis was not significantly associated with demographics such as age, sex, or COVID-19 severity [24]. Prior comorbidities, acute laboratory values, and medications, also showed no consistent associations across long COVID symptoms.

That's interesting, no sex bias in the development of long COVID, although perhaps the sample was too small and Long Covid is defined loosely.

So, they looked at mitochondrial genes differentially expressed at 3 weeks after acute illness:

convalescent patients showed specific enrichment of pathways related to ATP synthesis and electron transport, with strong upregulation of CDK1 and ND3, as well as the cytochrome c
oxidase subunit gene COX1 (Fig. 1b,c). In contrast, long-COVID patients were characterized by pathway enrichment of mitochondrial membrane organization, mitochondrial complex assembly, and protein transport, with upregulation of multiple related genes including CHCHD6, IMMP2L and ME3 (Fig. 1d, e).

Supplementary Table 2 lists expressed mitochondrial genes by group.

 

[Hutan]

RESULTS
Part B

Building on previous findings that MDPs such as humanin activate inflammatory signaling pathways [26], we predict interactions between MDPs and inflammatory biomarkers play a role in early COVID recovery that contributes to the progression of long COVID.

Convalescent samples:

humanin was found to be significantly negatively correlated with multiple biomarkers, including TNFSF10, CCL13, CXCL8, and CSF1, while MOTS-c was found to be negatively correlated with TNFSF10 and IL17C (Fig. 2c). SHMOOSE however, showed a significant positive correlation only with levels of IL15 in the convalescent group.

NeuroPASC samples:

negative correlations between SHMOOSE and biomarker levels, and positive correlations between humanin, MOTS-c and biomarker levels (Fig. 3b). Specifically, humanin was found to be significantly positively correlated with levels of OSM, TGFA, TNF, FLT3LG, and IL18, while SHMOOSE was found to be significantly negatively correlated with levels of OLR1, OSM,
TGFA, CCL4, and IL18. Finally, MOTS-c was highly positively correlated with a large number of inflammatory biomarkers, including all found to be correlated with humanin as well as HGF, CCL3, CCL2, CSF1, CCL7, CCL8, CCL4, IL-1B, VEGFA, CXCL11, CCL13, EGF, TNFSF12, CXCL8, IL7, CXCL12, MMP1, and IL18 (Fig. 2d).

I'm not sure that we should be too excited by these results. The sample size at 20 in each group is small. Not a single MDP or cytokine was significantly different between the two groups (see Table 2). So, they have turned to ratios between the biomarkers in order to find something. I'm not sure how stable the various cytokines are. And I'm not sure how good the classification of the people in the two groups is.


But, if you look at Figure 3, the direction of correlations between many of the biomarkers does seem to be quite different in the two groups. So, perhaps that is evidence of a dysregulated system, perhaps, as is suggested in the introduction, a sign of immune systems being subverted by pathogens.

Figure 3 - Heatmap shows specific clustering between Mitochondrial-Derived Peptides and selected biomarkers in long COVID patients. The strength of the correlation between variables is represented by the color at the intersection of those variables, with colors ranging from red (r-squared = 1) to blue (r-squared = -1). a) heatmap showing correlations between MDPs (x-axis) and biomarkers (y-axis) in COVID convalescent group. b) heatmap showing correlations between MDPs (x-axis) and biomarkers (y-axis) in long COVID group.

a. Convalescent; b. NeuroPASC
3 mitochondrial-derived peptides on the x axis; the 37 inflammatory markers on the y axis