n=1 herbals case study
Daily PCR Ct’s of my omicron-wave case study while tracking interventions of an everyday food compound
Disclaimer: This is an opportunistic test of an herbal constituent previously under study. This post is not an encouragement to try similar on your own, it’s simply a source of data of use for the herbal antivirals clinical trialing community.
Following a Christmas weekend trip to the coast here in Kenya, I started coming down with cold/flu-like symptoms: a sore throat and proceeding to coughing. On return to Nairobi, I got tested at the garden-variety testing house, and turned out to be quite CoV+. So I re-engaged with the specialist PCR vendor we had tied up with for the prospective clinical trial we were ramping up toward earlier this year. A baseline example of viral load to compare against is from Kissler et al (2021).
which describes the Alpha variant. (I’ve yet to see viral load data on Delta/Omicron variants which are probably the more relevant comparisons here). In testing an antiviral candidate, the goal was to see if the Ct value could be made to increase faster than the average patient in the wild. I underwent PCR nasal swabs daily. Here are the results:
Remember that Ct, which stands for Cycle Threshold, is roughly an inverse logarithm of the viral RNA concentration in a sample. Generally the RdRp was remaining stable (frustratingly, in my view) through Jan 1st.
The first 2 days’ samples are unbuffered, which means the quantity of detectable viral RNA can degrade markedly in transit between home where the sample is collected and the laboratory where the PCR is run. Also, the 1st sample is the mainstream vendor, the 2nd is the specialty genomics vendor used for the rest of the study. They are called The Africa Genomics Centre & Consultancy (TAGCC). (We ran a couple baselines to determine that the unbuffered 1st vendor can be as much as 5 Ct less sensitive than the buffered results with the TAGCC. Also, the unbuffered sample can be 3 Ct less sensitive than a buffered sample with the TAGCC).
Concurrently, I was also consuming different preparations of the study compounds:
Of course, sparse-looking bar charts like this don’t remotely do justice to the nuance of serum tissue concentrations of Active Pharmaceutical Ingredient (API), a topic we go into some detail on in a manuscript we submitted at the end of 2021. As a reminder from previous posts, the APIs we study are the flavonoids hesperidin and diosmin. Mango Seed Kernel (MSK) is our go-to plant source (see ‘Table 2’) for hesperidin.
I’m going to try to keep this simple, as there’s a lot of nuance especially in the herbal preparations. In this chart, mango kernel preparations (based on hot water pressure decoctions) are in colored in brown and measured on the left axis. The pharmaceutical preparation Daflon is in blue, and a nutritional supplement consisting primarily of hesperidin is in yellow, as measured on the right axis. Although left & right axes are independent of each other, I’ve tried to maintain a ballpark sense of relative API quantity by scaling the left axis by the estimated (but unverified!) amount of hesperidin in mango seek kernels.
Anyway, through till the New Year’s weekend I was struggling to get the virus’ RdRp Ct value to budge. (Even while the N-gene was varying — more on N in the appendix):
When I got the weekend’s results back from TAGCC, however, an intriguing transition turned up:
That difference is about 3 Ct. On its own, a 3-Ct rise is nothing to write home about. But given the steadiness of the values prior and following, I looked back at my interventions prior to that transition:
As you can see, by Friday I had run out of the mango seed kernel extract (it’s kind of laborious to prepare) and had gone back to large doses of a combination of Daflon & the hesperidin nutritional supplement — easily 3,000–5,000 mg at a go (before you caution anything, remember I’ve studied and practiced safe dosages of these for my body mass ad nauseam, and importantly, I’m not taking prescription drugs concurrently). I had also run out of Daflon, but had lots of the nutritional supplement to spare. Also, as you can see on 29-Dec and 30-Dec, whether or not the Daflon could be having any effect on viral load, it wasn’t obvious (at least without a control to compare to). So in the twelve hours until my next sample, I was interested to see if I could get my serum hesperidin load from the nutritional supplement to be high enough to have any effect on viral replication. I did a bolus dose and employed middle-of-the-night wake-up alarms to take additional doses to keep my serum levels up. And here are the results:
Let’s look at that against the fresh intervention log:
Not a bad signal! — A 9-Ct and 6-Ct cycle threshold increase on N-gene & RdRp respectively 😃. It’s worth keeping in mind that a transition like this could be due to a sampling error, or that phenolic compounds like our study compounds are known to inhibit PCR when a sample is directly contaminated with them. We’ve controlled for this in the past, but given the large doses in play, it’s certainly worth controlling for this again with reagents that are designed to tolerate phenolic compounds. Let’s look at the rest of the run:
As you can see, despite my religiously maintaining the hesperidin dosage, the Ct value actually decreased slightly from its previous peak. This was interesting and I can only speculate with narratives (along the lines of Michaelis-Menten enzyme kinetics) that would need to be studied against the complicating factor of viral replication dynamics. But it did show that the previous high datapoint was likely not a total fluke. I’ve since ceased interventions and we’ll see how this continues. I’ll post updates into the same post.
Update 6-Jan-22 8:30pm:
Today’s sample is in, as well as an interesting result from a recently banked sample. First the general update:
As nasopharyngeal swabs go, this infection is clearly on the way out. And that’s without having had any further intervention since 5-Jan morning:
My final sample today did indeed come back as completely undetectable (i.e. negative). Nothing to add to the chart, they would just look like >40 Ct bars.
An n=1 case study is of course no basis on which to inform anyone’s therapy. But if you’re designing a Ph-II clinical trial of flavonoids for antivirals, I think there’s a strong case here that hesperidin should be considered as an important component of that, by the straightforward mechanism of promiscuous binding and deglucuronidation which I helped produced a manuscript for in late 2021. Dosage is key and I think the data here shines a light forward on that too.
Since this article came out, the Kissler et al group came out with Omicron Ct profiles. Their study group for their past 3 studies has been the American NBA basketball association athletes and associated individuals. I began comparing my results with theirs before realizing that by the time of the Omicron study, the NBA study participants (including well-connected athletes) likely have had access to the newly approved prescription antivirals paxlovid and molnupiravir, and therefore don’t make for an adequate baseline comparison. The Kissler group however does have similar data posted from the Delta and Alpha variant waves. I compared against these.
In both cases, the “wow-emoji” transition is showing these percentiles against transitions taken from those of the study populations as they crossed the 24.5–28.5 interval:
So this should provide some perspective on the uniqueness of that transition against the general population.
As highlighted at the beginning of the article, this post is not an encouragement to try similar on your own, it’s simply a source of data of use for the herbal antivirals clinical trialing community such as the WHO-convened African traditional medicine groups we maintain relationships with. CoV+ readers should review NIH Treatment Guidelines and consult with one’s own primary healthcare provider.
The tests were performed on the Viasure Real Time PCR Detection Kit for SARS-CoV-2 by CertTest.
Underlying data & logs from which these charts are drawn can be found here in Google Sheet form. Our PCR vendor, TAGCC, maintains records that can be independently referenced.
- Special shout-out to the TAGCC — if anyone needs top-notch PCR support in Kenya or genomics expertise from abroad, these are the experts for whom I am very happy to provide reference 🙂. Their travel-related & diagnostic assays are under the name Nextgen Molecule Lab.
- I’d like to appreciate our collector who always provided consistently deep (not to mention painful!) swabs.
- I’d like to recognize Strathmore University’s CREATES lab which had earlier generated the above LC-MS results on our candidate therapeutics, which turned out to be crucial to deciding to try both of them.
Addendum for herbals geeks:
Here is some of that nuance in the dosages described.
The mango seed kernel extract through the end of Thursday, Dec 30th was a pressurized hot water decoction in liquid form. The earlier doses have cut plant material, the later doses see the plant material in the same extract pulverized. The preparations on Jan 2nd and Jan 3rd are solid starches of the extract in an attempt to improve bioavailability (by reducing exposure to gastric juice, and extending time in the intestine)
The nutritional supplement is from a US vendor. I don’t disclose them primarily because I had taken their product in for LC-MS analysis, and found their active ingredients looked to be the reverse in prevalence as labeled. So. I didn’t want others’ efforts confused by what’s likely a batch-specific compounding error:
Compare with Daflon as gold-standard:
Finally, I did have a couple minor interventions I haven’t shown in the charts for simplicity:
- 31-Dec: 2 cups of artemisia afra tea which could reasonably affect results. 5-Jan: 1 cup of artemisia afra tea
- 30-Dec: 50 micrograms of vitamin D3, which I take generally yet ceased for the most part during this study.
Addendum for virology geeks:
The N-gene, being the nucleocapsid, was obviously varying more, and I wasn’t sure what to make of it. The vendor, possessing much more expertise on these topics than me, says that each gene’s amplification results are subject to gene-specific primer efficiency, and so should only be considered in reference to the same gene’s previous results. That said, welcome comments on the topic.