National Library of Medicine Citations for neuropsychiatric disorders (PANDAS, PANS)

The following have had published studies. These are report on the averages of a group of patients; they do not apply to all patients and are not necessary predictive.

Some studies were done on people with specific conditions, ethnic origin or diet style (i.e. traditional Chinese Diet versus Western Diet), which may be why some shifts are in opposite directions.

See this post about overlapping bacteria/taxa and possible progression of conditions.

AI Engines For more Details: Perplexity  Kagi Labs  You 

Note these are associations and not causation. Items being high or low may be part of the immune response.

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A percentile below 20% can be deemed to be low, and above 80% as high. These are arbitrary values.

Tax Rank Tax Name Shift Percentile Distribution Citation Link
family Bacteroidaceae (NCBI:815 ) High Distribution    📚 PubMed
family Carnobacteriaceae (NCBI:186828 ) Low Distribution    📚 PubMed
family Corynebacteriaceae (NCBI:1653 ) Low Distribution    📚 PubMed
family Erysipelotrichaceae (NCBI:128827 ) Low Distribution    📚 PubMed
family Lachnospiraceae (NCBI:186803 ) Low Distribution    📚 PubMed
family Rikenellaceae (NCBI:171550 ) High Distribution    📚 PubMed
family Ruminococcaceae (NCBI:541000 ) Low Distribution    📚 PubMed
family Tissierellaceae (NCBI:1737406 ) Low Distribution    📚 PubMed
genus Faecalibacterium (NCBI:216851 ) Low Distribution    📚 PubMed
genus Gemella (NCBI:1378 ) Low Distribution    📚 PubMed
genus Odoribacter (NCBI:283168 ) High Distribution    📚 PubMed
genus Turicibacter (NCBI:191303 ) Low Distribution    📚 PubMed
phylum Bacteroidetes (NCBI:976 ) High Distribution    📚 PubMed
phylum Firmicutes (NCBI:1239 ) Low Distribution    📚 PubMed
species Escherichia coli (NCBI:562 ) High Distribution    📚 PubMed

All suggestions are computed solely on their predicted microbiome impact. Safety, side-effects etc must be evaluated by your medical professionals before starting. Some items suggests have significant risk of adverse consequences for some people.

Special thanks to David F Morrison and Geert Van Houcke for doing Quality Assurance. Special thanks to Oliver Luk, B.Sc. (Biology) from BiomeSight for spot checking the coding of data from the US National Library of Medicine

This is an Academic site. It generates theoretical models of what may benefit a specific microbiome results.

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