In 2013, we introduced our 4 stage color-coded Microbial Clock (MC), CHRONIC DISEASE CENTRIC, a means of expressing relationships to age and chronic diseases; this subsequently addressed published microbial phylotype changes to 2 parallel diseases (2015): 1) young ( Asthma and Autism )(Green Code) and old ( VAP and AD ) (Red Code). This was followed (2016) by tracking oral microbiota changes in patients with cognitive impairment, reporting 3) missing microbiota, all highlighted by 4) potential intervention of Restorative Microbiology (Replacement Therapy using probiotics), grouped in our educational, Searchable Data Base for Decision Support . (2016) (Probiotic Solutions, Bac-2-Health) (www.globalbugs.com.)
Here, we wanted 1) to expand our Decision Tree Probiotic data base as an AGING educational adjunct to interventional studies for dementia, age and age related co-morbidities, recognizing the emergence of the Hologenomic Theory of Co-Evolution (“Dual Citizenship”) as a complement to our MC and our New Center for Hologenomic Clinical Studies (www.globalbugs.com), launched in 2017. The recent NIH proposal that Aging should be classified as a disease amplified our position.
METHODS. Here, we have expanded our 7 layer decision tree (Bac-2-Health) based on initial review of 310 manuscripts to include 67 new AGING manuscripts addressing 1) aging and probiotics, 35 selected, highlighting 2) the growing awareness of a declining microbiota with age and the 3) unrecognized presence of the Mycobiota. Reviewed Manuscripts are Grouped into 2 basic categories reflecting the burgeoning, young information data sets: 1)Aging Theory and 2) Aging and Probiotic Intervention. 5 criteria are used , mimicking the original outline of Bac-2-Health, now evolving into Partners-4-Life including: Aging Condition, Study Type, Strength, Microbes and Probiotics.
Illuminating the declining microbiota/mycobiota and its impact on aging, may unmask the benefits of therapeutic bacteria as “Restorative Microbiology” enforcing the Hologneomic Theory of Co-Evolution and “Dual Citizenship”, while highlighting the educational benefits of our Decision Tree Data Base when designing new aging studies (Partners-4-Life). This is new in the age-old discussions of aging, and 1) what it is and 2) what mechanisms are involved, opening the way for a fresh approach, The Ying Yang Hypothesis.
The impact of the NIH in considering Aging as a disease, reinforces the use of our Microbial Clock, expressing the continuing relationship of diseases to age, enforced by a common pathway linking disparate diseases, including aging. It also highlights the role of microbes in rapidly providing genetic information, in contrast to the environment and the potential linking of data bases in Artificial Intelligence (AI). We envision probiotics/therapeutic bacteria and fungi as key elements in computerized human medical treatment, expanding the roles of existing AI Programs such as BUOY health. (www.BUOYhealth.com)
Finally, it now appears that the traditional, potential role of pathogens in aging linked to 1) immunosenescence and 2) lost tissue junctions, should be complement by the Brain GUT axial pathway ( direct interspecies signaling) and microbial burden, where the changing microbiota, particularly lost microbial fungal partners, is key to a balanced aged health. This targets our Replacement Therapy Strategy, emphasizing ‘Gene Theory to Gene Therapy’, a DISEASE CENTRIC approach, incorporating our 2 Themes: “Microbes Matter” and ”Don’t Trash your Microbiota”.
These beneficial microbes listed below are referenced in the Aging Theories Cross Section of Published Articles table:
A-2. Lustgarten, Michael S. 2016. Classifying aging as a disease: The role of microbes. Frontiers in Genetics. 7: 212 -219.
A-5. Bagie, E et al. 2012. Aging of the human meta-organism: The microbial counterpart. Age 34:247-267.
A-6. Carolyn Heintz and William Mair. 2014. You are what you host: Microbiome modulation of the aging process. Cell 156: (Jan 30): 408-411.
A-7. Gray, N. 2014. Understanding the Aging GUT: Microbiome Modifications may be Linked to Health and Lifespan. Www.neutraingredaints.com
A-11. Sitaraman Saraswati and Ranakrishnan Sitaraman. 2014. Aging and the human gut microbiota from correlation to causality. Frontiers in Microbiology. 5:764
A-23. Khatami M. 2009. Inflammation, aging and cancer: Tumoricidal versus Tumorigenesis of immunity (a common denominator mapping chronic diseases.) Cell biochemistry and biophysics. 55:55- 79.
A-X. Niv, Z. et al. 2016. Taking It Personally: Personalized Utilization of the Human Microbiome in Health and Disease. Cell Host and Microbe.19: (Jan 13):12-20.
A-Y. Thevaranjan, N.et al. 2017. Age-Associated Microbial Dysbiosis Promotes Intestinal Permeability, Systemic Inflammation, and Macrophage Dysfunction. Cell Host and Microbe. 21: (April 12):455-466.
These beneficial microbes are listed below are referenced in the corresponding Aging and Probiotics Cross Section of Published Articles table:
A-21. Tiihonen, K. 2010. Human Intestinal Microbiota and Healthy Aging. Aging Research Reviews. 9: 107-116.
A-24. Perez, M. 2014 Understanding GUT Microbiota in Elderly Health will enable intervention through Probiotics. Beneficial Microbes. 5(3):235-246.
A-26. Geoffrey A. Preidis and James Versalovic. 2009. Targeting the Human microbiome with antibiotics, probiotics and prebiotics: Gastroenterology enters the Metagenomic era. Gastroenterology. 136:2015-2033.
A-27. Probiotics Aid Memory in People with Alzheimer’s Disease. 2016. National Library of Medicine, PubMed Health. www.ncbi.nlm.nih.gov/pubmedhealth
A-28. Perlmutter, D. 2016. Reversing Alzheimer’s with Probiotics. Frontiers in Aging: Neuroscience. www.drperlmutter.com/reversing_alzheimer’s_with_probiotics
A-30. Maria G. Dominguez-Bello and Martin J. Blaser. 2008. Do You have a Probiotic in your Future? Microbes and Infection. 10:1072-1076.
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