A Causal Link Between Epstein-Barr Virus and Multiple Sclerosis

Post by Negar Mazloum-Farzaghi

The takeaway

To investigate the cause of multiple sclerosis, researchers examined data from over 10 million US military recruits. Examination of blood samples provided strong evidence that Epstein-Barr virus is linked to multiple sclerosis.

What's the science?

Multiple sclerosis (MS) is a chronic neurodegenerative disease of the central nervous system that attacks the nerve fibers and myelin sheathing of the brain and spinal cord. While the cause of MS is currently unknown, previous evidence has pointed to viral infection with Epstein- Barr virus (EBV) as a potential trigger of MS. EBV is one of the most common human viruses that can give rise to infectious mononucleosis and can persist in latent form throughout the life of the host. Evidence of causality between EBV and MS remains to be investigated.

This week in Science, Bjornevik and colleagues examined a cohort of over 10 million young adults in the US military, 955 of whom were diagnosed with MS over a 20-year period, to test the hypothesis that there is a causal link between EBV and MS.

How did they do it?

In order to investigate the relationship between EBV and MS, the authors collaborated with the US military to examine blood samples of more than 10 million racially diverse individuals who were serving in the US military over the span of 20-years. The US military screens for HIV at the start of service and biennially thereafter, and residual serum from these tests are archived in a repository. Using the archived serum, the authors determined EBV status at the time of the first sample and the association between EBV infection and MS development during active military duty. They found that 5.3% of individuals were negative for the EBV virus at the time of first sample.

In total, 955 MS cases were documented among active-duty military personnel. For each MS case, evidence for EBV infection was assessed by examining three serum samples which were collected before the start of MS onset (the first collected sample, the last collected sample prior to disease onset, and one sample in between). Next, the MS cases were matched (for age, sex, and race) to two randomly selected individuals without MS. There were 801 individuals with MS and 1566 control individuals with samples available to assess EBV infection status. Most individuals in the study were 20 years of age or younger at the time of their first blood sample, and those who developed MS had a symptom onset of a median of 10 years after the time of their first sample.

What did they find?

To investigate the risk of MS from EBV infection, the authors identified 35 MS cases and 107 controls who were EBV-negative in their initial collected blood sample. All but one of these 35 EBV-negative MS cases eventually tested positive for EBV antibodies, indicating that almost all MS cases were infected with EBV prior to MS symptom onset. Importantly, there were no cases of MS among individuals who remained EBV-negative. To assess whether other viruses were also associated with the MS cases, the authors investigated cytomegalovirus, a similar virus to EBV. They found that cytomegalovirus infection was not associated with an increased risk of MS.

The authors also investigated serum concentrations of neurofilament light chain (sNfL), a biomarker of neuroaxonal degeneration in the samples of MS cases and controls who were EBV-negative at baseline. They found that sNfL levels in EBV-negative individuals at baseline who eventually went on to develop MS were similar to control levels before the time of EBV infection in those who went on to develop MS. However, sNfL levels increased after EBV infection. Thus, there was no indication of neuroaxonal degeneration before EBV infection in individuals who later developed MS, suggesting that EBV infection preceded MS pathological onset.

What's the impact?

This study provides the strongest evidence to date that EBV infection can lead to MS. Future research should investigate the underlying biological mechanisms involved in the relationship between EBV and MS, which could ultimately lead to the development of interventions, such as vaccination, to prevent MS before onset. 

Sensory-Motor Brain Networks are Coupled with the Stomach’s Rhythm

Post by Leanna Kalinowski

The takeaway

Natural electrical rhythms produced in the stomach are coupled with resting-state activity in sensory and motor brain regions, providing insights into how the brain and body communicate. 

What's the science?

The study of resting state brain networks (RSNs) – areas of the brain that work synchronously even during times of rest – has taught neuroscientists a lot about how brain activity is organized across distinct brain regions. Traditionally, these networks have been broadly categorized into groups of sensory-motor regions, which allow for interaction with the external environment, and groups of transmodal regions, which control cognitive processing. However, despite a growing interest in how the brain and body interact, little work has been done to identify potential relationships between RSNs and internal bodily rhythms outside of the brain.

Scientists have previously identified a connection between brain activity at rest and the gastric rhythm, which is a slow electrical rhythm that is continuously produced in the stomach. This week in the Journal of Neuroscience, Rebollo and Tallon-Baudry further characterized the connections between this gastric rhythm and RSNs.

How did they do it?

To measure brain activity at rest, 72 participants underwent functional magnetic resonance imaging (fMRI) scans while resting; they were instructed to lay still and fixate on a bull’s eye on a grey screen. To measure gastric rhythm, the participants simultaneously underwent electrogastrogram (EGG) recordings in which non-invasive electrodes were placed over their abdomen. The researchers then filtered the fMRI signals to match the slow electrical rhythm of the stomach; a technique called phase synchronization. This way, they were able to measure how stable the lag between the two signals was over time.

What did they find?

The researchers found that rhythms in all sensory and motor cortices are coupled with the gastric rhythm, including brain regions that respond to touch, vision, audition, and interoception. In contrast, very few brain regions associated with cognitive processing (i.e., transmodal RSNs) are coupled with the gastric rhythm. Taken together, these results suggest that gastric rhythm and sensory-motor processes likely interact while bypassing cognitive processes.

What's the impact?

The results from this study transform what we previously knew about how brain activity is organized. Notably, fluctuations in the activity of brain regions that have been largely considered to be independent are in fact coupled with gastric activity. Future research should be conducted to further characterize connections between the brain and body.  


Access the original scientific publication here.

Using EEG to Assess the Impact of a Poverty Reduction Intervention On Brain Development

Post by Lani Cupo

The takeaway

While poverty can impact brain activity in children, this study shows predictable, unconditional, monthly money transfers to low-income homes can serve as a positive intervention in altering the brain activity of low-income children.

What's the science?

The first year of infants’ lives represents a period of great plasticity and sensitivity. In humans, it is difficult to assess the causality of variables such as income, as they often covary with other salient variables, like education or urbanicity. Previous evidence suggests early life poverty is associated with certain patterns in brain activity as measured with electroencephalograms (EEG). This week in PNAS, Troller-Renfree and colleagues seek to experimentally investigate whether financial intervention can alter brain activity associated with the development of cognitive skills.

How did they do it?

EEG provides researchers with noninvasive measures of two main variables: frequency (the waves of brain activity that occur at different rates) and power (the amount of activity at a specific frequency per region). From infancy to middle childhood, children show characteristic changes in EEG signals, with decreasing power in low frequency bands (slow oscillations called theta) and increasing power in high frequency bands (higher oscillations, alpha, beta, and gamma). Differences in this changing pattern are associated with poorer cognitive outcomes, often correlated with poverty during the first years of life. To assess whether poverty reduction strategies could alter brain activity in infants, 1000 low-income women from 4 urban areas in the United States were randomized to receive a gift of either $20 per month (low-cash gift) or $333 (high-cash gift) per month, to be used as they chose. When the infants were one-year old and the mothers had received the gifts for one year, surveys and EEG recordings were completed in 435 infants. The authors examined both absolute and relative power, where absolute power refers to the amount of power measured at a specific frequency band and relative power refers to the fraction of absolute power over total power. For example, absolute power would reflect the power measured in the low-frequency theta band, and the relative power would reflect the theta power over the combined alpha, beta, and gamma power.

What did they find?

Compared to the low-cash group, children in the high-cash group had higher absolute power in the mid-high frequency ranges (alpha, beta, and gamma), as hypothesized. Higher power in mid-to-high-frequency bands has been associated with better cognitive and language outcomes. Of the three frequency ranges, the greatest effect size was observed in the beta range, indicating it was the most impacted. Of note, beta frequencies have been associated with eye movement artifacts, and potentially with concentrated activity.

The same patterns were reflected in relative power, although the effects were smaller. The high-cash group showed increased frontal beta and gamma power, as well as more central beta power, indicating regions consistent with previous work linking income, brain activity, and cognitive outcomes. There was no impact on theta-power, contrary to hypotheses. Previous work in children indicates high theta power is associated with poorer behavioral outcomes, and the authors expected to see reduced theta power in the high-cash group.

What's the impact?

This study is the first to report a causal relationship between income level and brain activity in young children by implementing a poverty-reduction intervention for low-income mothers. They found an unconditional payment of $333 per month was sufficient to increase mid-high frequency power in EEG recordings at age 1. This work provides important experimental evidence that could impact public policy to reduce inequality and ensure better outcomes for low-income children.