Autism: Balancing excitation and inhibition in the autistic brain
Balance and stability are important for the human body. This is clearly true for some physical tasks, such as walking or running without falling over, but it is also true inside the brain. Neurons receive both excitatory and inhibitory inputs, and maintaining a balance between the two – that is, maintaining what is known as the excitation-inhibition or E:I balance – is crucial for the brain to work properly (Yizhar et al., 2011).
Disruptions to the E:I balance, such as increased levels of excitatory inputs, have been linked to autism and a number of other neurological conditions, and can affect brain function and social behavior (Rubenstein and Merzenich, 2003). It has also been shown that the E:I balance can depend on sex, especially in regions of the brain that support social behavior, such as the ventromedial prefrontal cortex (Lai et al., 2019). However, research into the relationships between autism, sex and social behavior have been hampered by a lack of non-invasive tools. Now, in eLife, Michael Lombardo (Istituto Italiano di Tecnologia and University of Cambridge) and colleagues – including Stavros Trakoshis and Pablo Martínez-Cañada as joint first authors – report how it may be possible to measure the E:I balance without causing damage to the brain (Trakoshis et al., 2020).
The researchers – who are based in Italy, Cyprus, South Korea, the United Kingdom, Switzerland, and Canada – first created a computational model of the brain and used data from this model to calculate a metric called the Hurst exponent. This metric is a measure of the long-term memory of a time series of data. The model was then tweaked to simulate the effect of a ligand called CNO (which is short for clozapine-N-oxide) on two receptors hM3Dq and hM4Di, which are synthetic proteins designed to bind synthetic drugs. When CNO binds to hM3Dq it increases excitation, and when it binds to hM4Di it reduces both excitation and inhibition. Trakoshis et al. found that the change in the E:I balance caused by CNO also changed the Hurst exponent: specifically, an increase in excitation decreased the Hurst exponent (Figure 1).
Second, the researchers tested if they could replicate these computational results in mice that had undergone chemogenetic manipulation to express hM3Dq and hM4Di. This involved measuring electrical activity in the prefrontal cortex of the mice before, during and after the administration of CNO, and then computing the Hurst exponent. They found that the in vivo results in mice confirmed the predictions of their computational model. Specifically, a drug-induced increase in excitation led to a decrease in the Hurst exponent.
Third, Trakoshis et al. wanted to find out why E:I processes may differ between males and females. They found that genes associated with autism that also affect the E:I balance (especially excitation) overlapped with genes that are sensitive to male-specific hormones. A comparison of these results with a gene expression map called the Allan Human Brain Atlas (Hawrylycz et al., 2012) further revealed that these genes are expressed in many regions of the brain, including the ventromedial prefrontal cortex.
To investigate how the E:I balance may differ between autistic men and women, and how those differences may relate to social behavior, Trakoshis et al. collected neural time series data and computed the Hurst exponent in individuals with and without autism (who were similar in age and IQ). In the ventromedial prefrontal cortex, the Hurst exponent of individuals with autism was lower than that of typically developing individuals, with the difference between the two being larger in males than in females. Moreover, in women with autism, the Hurst exponent was linked with social behavior: a higher (i.e., more typical) value was accompanied by a better ability to 'socially camouflage' – that is, the ability to compensate for social-communicative difficulties.
Taken together, these results suggest that the Hurst exponent may be a useful biomarker to examine the E:I balance and its relationship with sex and social behavior across the autism spectrum. More research is needed to investigate if shifting the E:I balance in the ventromedial prefrontal cortex could alter social behavior in people with autism. In the future, this approach could be extended into other conditions linked to E:I balance and sex-differences, such as attention deficit hyperactivity disorder.
Model of autism: increased ratio of excitation/inhibition in key neural systemsGenes, Brain and Behavior 2:255–267.https://doi.org/10.1034/j.1601-183X.2003.00037.x
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- Version of Record published: August 4, 2020 (version 1)
© 2020, Pretzsch and Floris
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Plasma cell mastitis (PCM) is a nonbacterial breast inflammation with severe and intense clinical manifestation, yet treatment methods for PCM are still rather limited. Although the mechanism of PCM remains unclear, mounting evidence suggests that the dysregulation of immune system is closely associated with the pathogenesis of PCM. Drug combinations or combination therapy could exert improved efficacy and reduced toxicity by hitting multiple discrete cellular targets.
We have developed a knowledge graph architecture toward immunotherapy and systematic immunity that consists of herbal drug–target interactions with a novel scoring system to select drug combinations based on target-hitting rates and phenotype relativeness. To this end, we employed this knowledge graph to identify an herbal drug combination for PCM and we subsequently evaluated the efficacy of the herbal drug combination in clinical trial.
Our clinical data suggests that the herbal drug combination could significantly reduce the serum level of various inflammatory cytokines, downregulate serum IgA and IgG level, reduce the recurrence rate, and reverse the clinical symptoms of PCM patients with improvements in general health status.
In summary, we reported that an herbal drug combination identified by knowledge graph can alleviate the clinical symptoms of PCM patients. We demonstrated that the herbal drug combination holds great promise as an effective remedy for PCM, acting through the regulation of immunoinflammatory pathways and improvement of systematic immune level. In particular, the herbal drug combination could significantly reduce the recurrence rate of PCM, a major obstacle to PCM treatment. Our data suggests that the herbal drug combination is expected to feature prominently in future PCM treatment.
C. Liu’s lab was supported by grants from the Public Health Science and Technology Project of Shenyang (grant: 22-321-32-18); Y. Yang’s laboratory was supported by the National Natural Science Foundation of China (grant: 81874301), the Fundamental Research Funds for Central University (grant: DUT22YG122), and the Key Research project of ‘be Recruited and be in Command’ in Liaoning Province (2021JH1/10400050).
Clinical trial number:
- Genetics and Genomics
Background: Causality between plasma triglyceride (TG) levels and atherosclerotic cardiovascular disease (ASCVD) risk remains controversial despite more than four decades of study and two recent landmark trials, STRENGTH and REDUCE-IT. Further unclear is the association between TG levels and non-atherosclerotic diseases across organ systems.
Methods: Here, we conducted a phenome-wide, two-sample Mendelian randomization (MR) analysis using inverse-variance weighted (IVW) regression to systematically infer the causal effects of plasma TG levels on 2,600 disease traits in the European ancestry population of UK Biobank. For replication, we externally tested 221 nominally significant associations (p < 0.05) in an independent cohort from FinnGen. To account for potential horizontal pleiotropy and the influence of invalid instrumental variables, we performed sensitivity analyses using MR-Egger regression, weighted median estimator, and MR-PRESSO. Finally, we used multivariable MR controlling for correlated lipid fractions to distinguish the independent effect of plasma TG levels.
Results: Our results identified 7 disease traits reaching Bonferroni-corrected significance in both the discovery (p < 1.92 × 10-5) and replication analyses (p < 2.26 × 10-4), suggesting a causal relationship between plasma TG levels and ASCVDs, including coronary artery disease (OR 1.33, 95% CI 1.24-1.43, p = 2.47 × 10-13). We also identified 12 disease traits that were Bonferroni-significant in the discovery or replication analysis and at least nominally significant in the other analysis (p < 0.05), identifying plasma TG levels as a novel potential risk factor for 9 non-ASCVD diseases, including uterine leiomyoma (OR 1.19, 95% CI 1.10-1.29, p = 1.17 × 10-5).
Conclusions: Taking a phenome-wide, two-sample MR approach, we identified causal associations between plasma TG levels and 19 disease traits across organ systems. Our findings suggest unrealized drug repurposing opportunities or adverse effects related to approved and emerging TG-lowering agents, as well as mechanistic insights for future studies.
Funding: RD is supported by the National Institute of General Medical Sciences of the National Institutes of Health (NIH) (R35-GM124836) and the National Heart, Lung, and Blood Institute of the NIH (R01-HL139865 and R01-HL155915).