Saturday, April 27, 2024

Clues toward the Cause of Long COVID

I previously shared some of the amazing data from the paper "Muscle abnormalities worsen after post-exertional malaise in long COVID" by Appelman et al. 

The paper will undoubtable become a classic in the field of Long COVID, providing a fascinating series of clues that the researchers followed past several dead-ends to their interesting implications. 

First, and most importantly, the researchers confirmed beyond a shadow of doubt that Post-Exertional Malaise (PEM) is a real disease, with myriad muscle and metabolic abnormalities in the Long COVID patients following intense exercise.  Metabolomics provided additional key findings, including the first clue: a possible blockage of glycolysis in Long COVID (see diagrams in previous post).  

A Clue: Glycolysis Blockage

In the glycolysis pathway, the phosphoenolpyruvate (PEP) levels of Long COVID patients were increased, while pyruvate levels were decreased, indicating a disruption or imbalance in enzyme activities within the pathway.   This could be due to a decreased activity of the enzyme pyruvate kinase (PK), which converts PEP to pyruvate in the final step of glycolysis.  Reduced PK activity would result in a buildup of PEP.  With less PEP being converted to pyruvate, the downstream levels of pyruvate would be lower.  

There are several interconnected regulatory pathways that can reduce the activity of pyruvate kinase (PK), the two most relevant being Oxidative Stress and Hypoxia.  Increased levels of reactive oxygen species (ROS) or oxidative stress can lead to the oxidation and inactivation of PK.  Under hypoxic conditions (low oxygen levels), the transcription factor HIF-1 (Hypoxia-Inducible Factor 1) can be activated, which can lead to the downregulation of PK expression and activity.  This is part of the cellular adaptation to hypoxia, where glycolysis is regulated to favor the production of metabolic intermediates for other pathways.

Hypoxia?

In the context of Long Covid and post-exertional malaise (PEM), hypoxia from microclots has been suggested to increase lactic acid production. However, in this study the metabolomics showed decreased* lactic acid, because glycolysis was shut down at PEP by loss of PK activity, not at pyruvate by loss of pyruvate dehydrogenase (PDH).  

The researchers looked for but did not find decreased muscle oxygen perfusion or any differences in microvasculature.  The researchers noted decreased oxygen utilization, but this could be due to anything that disrupts metabolism and does not indicate hypoxia as a specific issue.  

They noted amyloid plaques in the extracellular matrix; the plaques were not blocking the microcapillaries and it is unclear what role they play in the pathophysiology of Long COVID: are they a cause of PEM, or a consequence?  

Their observation that Long COVID patients' muscle force was not dependent on The Citric Acid (TCA) cycle enzyme succinate dehydrogenase (SDH) can also be explained by impaired metabolism upstream of TCA Cycle, i.e. in glycolysis.

Oxidative Stress

Therefore, it seems likely that the regulatory pathway most likely to contribute to reduced pyruvate kinase (PK) expression and activity is the oxidative stress pathway.  

Long Covid patients have been reported to exhibit higher levels of oxidative stress markers, such as lipid peroxidation products and decreased antioxidant levels, compared to healthy individuals or those who have recovered from acute COVID-19 infection.  Physical exertion and exercise can lead to an acute increase in reactive oxygen species (ROS) production, potentially exacerbating oxidative stress in individuals with Long Covid and triggering PEM symptoms.

Some studies have suggested that Long Covid patients may experience mitochondrial dysfunction, which can further contribute to increased ROS generation and oxidative stress.

Next Steps

The paper concluded with these results, but the logical next step would be to use metabolomics to assess free radical concentrations.  One theory is that COVID spike proteins form "pores", or holes in the mitochondrial membranes, disrupting the mitochondria and releasing free radicals into the cell.  

The researchers did look at COVID nucleocapsid protein, but found it in both the control and Long COVID groups in equal concentrations, suggesting that remnant viral protein doesn't explain the pathophysiology of Long COVID.  But maybe remnant virus affects the Long COVID patients differently?  

The researchers noted immune cell infiltration into muscle tissue, which could be in response to a signal from excess free radicals, or could be due to some other reason like persistent COVID infection/expression.  

Lactate?

This study seems to indicate the lactate is not an important variable for the pathophysiology of Long COVID.  However, the details about how lactate was measured limit these conclusions. The researchers measured lactate from three different sources:  metabolomic blood (venous) and muscle lactate measured before and after PEM, and capillary (i.e. finger prick) lactate measured during exercise.  Venous lactate measured one week after PEM induction showed a slightly increased level in Long COVID patients, but none of the other metabolomic lactate measurements showed any difference.  The capillary lactate also showed a slightly elevated blood lactate level before exercise in the Long COVID patients, but the difference was not significantly different.  

However, the baseline measurements were not taken in a fasted condition, and because eating normally raises resting lactate it cannot be determined from this study if fasted lactate might show other differences that are important to Long COVID.

Friday, April 26, 2024

Rangeland Analysis Platform

New data source for In-Season NDVI:  Rangeland Analysis Platform. (RAP) https://rangelands.app/rap/ 

RAP allows mapping of Cover and Biomass, and generates reports for an Area of Interest for Cover, Annual biomass, and 16-day biomass.  I'm hopeful they will upgrade the map to include 16-day biomass.  If they did, I could add it to the comparisons of the other NDVI sources.  Mapping would allow in-season management decisions based on forage production.



Case Example: Dugas, AZ

This series of years from 2018-2023 shows the variability in biomass production by season in a desert grassland at mid-elevation (4,000 ft) in AZ:


2018 shows a drought year, when there was little to no spring green-up due to a lack of winter precipitation, and a low green-up in response to summer monsoons.

2019 and 2020 were the "nonsoon" years, when the summer monsoons failed to materialize.  However, because the winter rains were good in 2019 and exceptional in 2020, total production was high.

2021 and 2022 show the potential for growth in years of good monsoon rains.  2023 shows a "normal" year with bimodal peaks in production corresponding to the spring green-up peaking in late March, and the summer monsoons peaking in mid-August.  However, for some reason this year had almost no annual biomass production associated with the monsoon.  Each year is different!

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Case Example: Congress, AZ

This series from around Congress, AZ shows the extreme variability of plant growth in the Sonoran desert (2,500 ft).

In drought years like 2018 and 2022, there is almost no plant growth, whereas the extreme winter precipitation year of 2020 annuals produced almost 130 pounds/acre of spring growth.  None of the years hadmuch perennial herbaceous production, and monsoons inconsistently produce up to 40 pound/acre of growth in good years.  


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Case Example:  Grand Canyon Junction 

SR-64 and SR 180 intersection, just south of Grand Canyon high-elevation grassland (6,000 ft).



Maximum production compared to the lower elevation sites is lower, only reaching 50 pounds/acre in good years.   However, total annual production is usually more consistent.  There is still the potential for bimodal production peaking in the late spring (early June) (2023 and 2017, not shown) and in the monsoons.  The monsoon peak seems to be most consistent, except in 2019 and 2020 when the monsoons failed - luckily those years had relatively good spring growth.   

In contrast to the low desert site, annual production (red) is usually less important than perennial production (green) at this site:



Thursday, April 18, 2024

Spring Update: NDVI Differences

Last September, I wrote about Finding the Greenest Place in AZ.  This Spring, we have continued to compare and evaluate the different NDVI difference mapping applications and compare them to the actual growth of wildflowers and grasses we see when we go out hiking.  

Methods

I conduct pre-field research to identify predicted greenness/moisture from UA's Droughtview, USGS VegDRI, and NWS Accumulated Precipitation.  I take a screenshot of each product and assign the proposed site a scale from 1 (driest) to 10 (greenest).  We then visit the area and evaluate the plant production, recording example photos of overall landscape greenness, as well as assigning a score.  The data are organized in a OneNote table.  I then compare the numerical scores in an excel table, adding up the differences between each model and the observations.  


Results

So far, the UA model seems to slightly overestimate greenness, the USGS model greatly underestimates greenness, and the NWS precipitation record comes out closest to observation.

For the UA model, I think it might be helpful to have a difference from maximum, instead of the difference from period. The latter overestimates early spring greenness when the denominator NDVI is very small, so any amount of NDVI in the numerator saturates the index.  Using the maximum NDVI for that pixel could help with this phenology issue.  Plus, % of maximum NDVI may be more intuitive than “difference from average”.

The USGS VegDRI index consistently estimates pre-drought to severe drought in areas that have above average precipitation this water year and have an NDVI above average.  This leads me to think that VegDRI 7-Day eVIIRS is either not well calibrated to the desert southwest, or perhaps that it is better used as a predictive index – perhaps these areas are drying out even though they currently appear green?  However, SWCC does not show significant vegetation drying yet in the areas I assessed.  


Examples

Wingfield Mesa:  UA Droughtview shows this area at maximum NDVI (for this time of year)(=10/10), USGS showed it as pre-drought to moderate drought (4/10) , and NWS shows 125-200% of normal year to date precipitation (9/10).  It is quite green, but it is still early in the growing season and the mesquite have not leafed out yet.  We rated it 6 out of 10.  


Dugas Rd:  UA shows above average (8/10), while USGS showed Moderate drought (3.5/10) and NWS showed slightly below average precipitation (75-90%) (3.5/10).  It is quite green right now, but again not quite at maximum greenness production.  We rated it 8 out of 10.   

Post Exertional Malaise in Long Covid

 Severe exercise-induced myopathy has been found in long COVID post-exertional malaise (PEM).  


Just look at these long COVID patients (in red) pushing close to 20 mmol/L lactate on the exercise bike!  That is serious dedication for a group of patients who know what the consequences will be.



After the exercise test, blood metabolomics show elevated glycolysis, but decreased pyruvate and TCA cycle metabolites.



Muscle biopsy metabolomics show decreased purine synthesis and TCA cycle.



Key:





Appelman, B., Charlton, B.T., Goulding, R.P. et al. Muscle abnormalities worsen after post-exertional malaise in long COVID. Nat Commun 15, 17 (2024). https://doi.org/10.1038/s41467-023-44432-3