Autism is a multi-factorial disorder associated with a series of complex behavioral symptoms largely attributed to inflammation in different regions of the brain.

Autopsies performed on Autism patients revealed active neuroinflammatory processes in the cerebral cortex and the cerebellum, which are areas responsible for motor control, cognitive functions, emotional regulation, perception, and for the production and reception of language.

Although the underlying cause of this neuroinflammatory process is still unknown, several lines of research support the view that both genetic and environmental factors underlies Autistic cognitive processes and behaviors.

Specifically, the gut microbiome represents an important environmental factor that has been thought to exert significant influence on symptoms associated with Autism Spectrum Disorder (ASD). In fact, multiple research groups have observed a genetic predisposition in ASD children to develop significantly different microbiomes compared to those of neurotypical children, which has been confirmed when comparing the microbiomes of ASD and neurotypical siblings.

How can microbiome disruption lead to brain injury?

As discussed in a previous article, Autistic behaviors may be understood as the ultimate manifestation of a series of genetic “combinations of risk” that may either trigger or inhibit key enzymatic pathways for the production and metabolism of important neurotransmitters that are fundamental for brain activity.

Although studies on neurotransmitters have usually centered around their role in the “fight or flight” response and the transmission of signals across chemical synapses, recent research has shown that neurotransmitters (such as dopamine, serotonin, norepinephrine and epinephrine) can also play a significant role in gastrointestinal physiology and are able to affect gut motility, nutrient absorption, the gastrointestinal innate immune system and the microbiome.

Notably, although known as an important brain neurotransmitter, it is estimated that over 90% of the body’s serotonin is produced and regulated by colony-forming intestinal bacteria. Hence, bacterial imbalance in the gut could potentially lead to important disruptions in the creation and metabolism of serotonin, responsible for emotional behavior, sleep-wake cycles, sensitivity to pain, hormone release, the formation of synapses and overall neurodevelopment.

Microbiota Transfer Therapy: Clinical research

With this in mind, Dr. James B. Adams and his team at the Arizona State University (ASU) conducted a prospective open-label clinical trial with 18 ASD children using Fecal Microbiota Transplant (FMT), a.k.a. Microbiota Transfer Therapy (MTT).

The MTT involved a 2-week antibiotic treatment, a bowel cleanse, and the transfer of gut bacteria collected from healthy donors into the study participants, using a high initial dose and lower daily maintenance doses for 8 weeks.

At the end of the 8-week period, clinical assessments showed that behavioral ASD symptoms had “significantly improved” and were sustained 8 weeks after the treatment ended.

The ASU team then conducted a 2-year follow-up on the 18 study participants and found that Autism symptoms were reduced by nearly 50% compared to baseline. Professional evaluations further revealed an average 45% decrease in ASD symptoms across all participants, 83% of which had been rated as “severe” at the beginning of the study.

By the end of the 2-year follow-up only 17% were rated as “severe”, 39% were “mild/moderate” and 44% were “below the cutoff for mild ASD”, i.e. they didn’t meet the criteria for an ASD diagnosis!

The ASU team compared the differences between the microbiome of children with Autism to those of typically developing children. At the beginning of the study, children with Autism were found to have lower diversity in their respective gut microbes and were depleted of certain strains of helpful bacteria, such as Bifidobacteria and Bacteroides-Prevotella.

After the 8-week trial period, the team observed that the FMT had substantially increased the microbial diversity of the trial subjects and by the 2-year follow-up, the microbial diversity was found to be even higher and the presence of the beneficial bacteria remained.

Gastrointestinal Symptom Scale ratings also revealed an 80% reduction of GI symptoms, including significant improvements in constipation, diarrhea, indigestion and abdominal pain, which persisted 8 weeks after treatment, and at the 2-year follow-up.

Predictive Model: Gut Bacteria on Autism Severity

Although many reputable institutes have used behavioral, socialization, cognitive and communication metrics to assess effectiveness in clinical trial settings, objective biomarkers remain still largely unidentified to assess the relative benefits of ASD treatments.

According to the ASU-MTT study, gut bacteria counts could provide a promising set of biomarkers to objectively evaluate Autism severity and (as shown in their research) alleviate ASD symptoms by increasing the diversity and amount of key colony-forming bacterial units.

To confirm this hypothesis, the Author of this article collected Comprehensive Stool Profiles from 10 parents located in the United States and Spain that voluntarily submitted stool tests for a total of 11 children diagnosed with ASD along with their ATEC (Autism Treatment Evaluation Checklist) scores as a measure of severity at the time of the stool test.

The lab tests were performed by the company Genova Diagnostics in the United States and by the Instituto de Microecología based in Madrid, Spain. Both labs provided colony-forming units per gram (CFU/g) of stool for multiple bacteria species/genus/phylum, of which the most highly correlated with ATEC were the following,

Species/Genus	Correlations
Akkermansia muciniphila	-0.61
Lactobacillus	-0.58
Escherichia coli	-0.50
Faecalibacterium prausnitzii	-0.48
Bifidobacterium	-0.47
Clostridium	-0.39
Bacterioides	-0.25

Both the magnitude and the sign of the correlation coefficients is meaningful. Negative correlations indicate an inversely proportional relation between gut bacteria counts and ATEC, i.e. the lower the bacterial counts the higher the ATEC and the more severe the condition.

Correlation coefficients range between −1 and +1 and represent the extent in which one variable could be explained by the presence of another.

Although the magnitude of the coefficients is strong, correlations are bivariate metrics where the impact of a given bacteria species/genus is compared to ATEC, one at a time. A multivariate method OTOH allows for the prediction of ATEC scores using all bacterial counts across species simultaneously. Although there are many statistical methods to achieve this, a simple method to assess the extent in which ATEC could be explained by the collective bacteria counts is ordinary least squares (OLS) regression analysis.

Remarkably, the OLS regression showed a 82.7% prediction rate of the 7 bacterial species on ATEC. The table above shows a “forward stepwise” process showing that the model was built by determining the strength of the relations one at a time, starting (as confirmed by the correlation coefficients) with Akkermansia muciniphila and continuing the process by identifying the type of bacteria that most explained ATEC given the variables already entered into the model.

The appropriateness of the regression technique is not only given by its predictive power but by meeting its underlying assumptions of normality and homoscedasticity. A visual examination at these assumptions confirms that OLS is a valid and appropriate method.

Although generally regarded as a highly subjective metric, ATEC is perceived as a useful tool to gauge the overall severity of the Autism disorder. The following table shows the parental assessments vs. the predicted ATEC values as per the OLS model,

id	ATEC	Predicted ATEC
1	65	39
2	40	45
3	45	51
4	20	20
5	85	81
6	40	41
7	44	53
8	95	90
9	62	67
10	40	55
11	10	9

Remarkably, 9 out of the 11 cases included in the analysis were predicted within a +/- 10-point range of the ATEC scores originally provided by the parents, which may be in part attributed to the subjectivity of the scale.

Also, it should be noted that the lab reports used rounded all CFU/g figures to the nearest thousand, million, billion, etc. Given that the average figure across all species and subjects was 1 billion (1E+09) CFU/g, it is clear that some “noise” in the prediction rates could be attributed to the numerical rounding of the (very large) figures used to report bacterial counts.

Conclusions

Although applied to a very limited sample, the high predictive power of the OLS regression methodology supports the findings of the MTT-ASU phase-I clinical trial. Higher bacteria counts and more diverse microbiomes were in fact strongly associated with lower ATEC scores and vice versa, lower counts and less diverse microbiomes were strongly associated with higher ATEC scores.

Consistent with the MTT-ASU report, Bifidobacterium and Bacteroides-Prevotella were found to be particularly important in determining Autism severity. However, the species Akkermansia muciniphila and Faecalibacterium prausnitzii were also found to play a significant role in explaining ATEC variability when considering all species simultaneously.

Given the popularity of stem cell therapies, the Author of this article also explored the relation between bacterial counts on the relative improvements observed on the subset of ASD children whose parents reported receiving stem cell therapy (SCT).

Of the 11 children in the sample, 6 of them received some form of SCT, including both autologous (bone-marrow) and allogeneic (cord-blood and cord-tissue) sources. Parents reported the relative “gains” that could be attributed exclusively to the SCTs, defined as the point-drop in ATEC score post-SCTs compared to baseline, e.g. a child with an ATEC of 70 pre-SCT and 20 post-SCT would have a 71.4% improvement, i.e. (70-20)/70 = 0.714.

Although based on a sample of only 6 children, the bivariate correlation coefficients provided some perspective into the species/genus that might be linked to the potential success of SCTs. Generally speaking, the higher the bacteria counts the higher the % improvement in ATEC with respect to baseline,

Species/Genus	Correlations on SCT % Gain
Akkermansia muciniphila	0.80
Lactobacillus	0.63
Escherichia coli	0.99
Faecalibacterium prausnitzii	0.93
Bifidobacterium	0.99
Clostridium	0.99
Bacterioides	-0.01

MTT-ASU Clinical Research: Phase-II

Microbiota Transfer Therapy holds a great potential for ASD families to alleviate Autism symptoms. Phase-I of the ASU trial proved MTT to be safe and showed promising results. The MTT-ASU team is currently seeking to fund phase-II in order to further demonstrate the efficacy of the treatment at a larger scale. Phase-II will consist of a larger randomized, double-blind, placebo-controlled clinical trial with children and young adults with an ASD diagnosis, ages 7 to 17 .

Another MTT clinical trial for adults is currently in recruiting stages for ASD patients with gastrointestinal disorders, ages 18 to 60. For more information about this phase-II trial with adults, click here.

Disclosure

The Author of this article has no financial interest in neither Genova Diagnostics or Instituto de Microecología labs or in any other lab performing stool testing, is not involved in any way with the MTT-ASU research team, and worked pro bono in the collection of the data, analysis, and writing of this article.

Acknowledgements

A very big “Thank you!” to all the parents that provided their children’s stool reports, ATEC scores, and observed % gains in ATEC from SCTs. Special thanks to Natalia Marmol and Monica Cuenca who were instrumental in the data collection efforts for this research.