A reader asked for a comparison between various labs (apart from ubiome).

The table is below (also available here as a PDF file)
CompareLabs

A reader forwarded a copy of their Viome report and I have created an entry form for it. It is at: http://microbiomeprescription.com/Kyber/Viome

• Assume Normal is not 1.5 x higher than “healthy” or 2/3 of healthy

The report looks like this:

I assume that “Activity” is what the person has.

The report also recommends some food (without providing studies backing them 😦 )

The top recommendation from our site is below. Note that only certain lactobacillus are recommended.

Their Food List

which goes on for several pages. Several items were listed which my analysis suggest should be avoided (barley, almonds, etc) My general impression is their customized for the individual food list is a general healthy living list with perhaps a few minor changes.

Bottom Line

I will be researching papaya, cauliflower, orange and bone broth on PubMed to see if there are studies. If they are, I will add them to our database.

Both the other Labs Analysis and Ubiome recommendations have had the revised algorithm applied.

The Values are not how strong it works, but the probability that it will have impact (works)

A higher number means more and more studies have found that it has modified the bacteria.

Ubiome Example

The default recommendations look at:

• High counts > 150%
• Items with moderate impacts
• No antibiotics or prescription drugs
• Aggregated items

If there are too many items, you may wish to change it to High Impact

If you are concerned about UNDER GROWTH..

Note that there can be some agreements between the High and Low. For example: avoid coconut products and saccharomyces are on both lists.

If you are interested in an item like ‘beta-glucan foods’, just click on it to see the break down.

Bottom Line

This revision should produce better recommendations and be easier to understand. It also provides a tool for those who are concerned about under growths. It also allows people to explore different approaches.

This is an education post to facilitate discussing this approach with your medical professionals. It is not medical advice for the treatment of any medical condition. Always consult with your medical professional before doing any  changes of diet, supplements or activity. Some items cites may interfere with prescription medicines.

Another portion of the revision has been completed.  This consists of two parts:

• Displaying the percentage of gut samples that have a specific bacteria level
• Refactor of information on each bacteria level

I have expanded the reference to every level of the hierarchy

Bacteria Level

An example is shown below

Bacteria Species_group

Click the appropriate link if you have an overgrowth or undergrowth

The literature link takes you to the National Institute of Health site, where you have many additional links of a technical nature.

And DataPunk for the other

Hierarchy Tree

If you go to Bacteria Hierarchy or  Bacteria Hierarchy Down To Species you will see the percentage of gut samples that have a specific bacteria.

This is important because my long standing question is which low or no count bacteria should we be concerned about to increase. A low Olsenella level is likely not a concern, because most people have none of it. A low Coriobacteriaceae level may be a concern.

If you have a very high level of Olsenella, then this may be a concern. The pending refactor of recommendations will allow have a default (my own assumptions) filtering and the ability for readers to modify it to suit their own assumptions.

Bottom Line

These enhancements allow easy access to additional technical information and also allow us to see which bacteria we expect to see normally. This means we can include bacteria that should be there but which are at an abnormally low level in the revised recommendations.