Pro Soccer Players Have Unique Cognitive Abilities and Personalities

Post by Anastasia Sares

The takeaway

This study looked at professional soccer players’ cognitive abilities and personalities, finding that they differ significantly from the general population. This shows that it takes more than physical attributes to make it at the highest levels of play.

What's the science?

Professional athletes are often praised for their physical prowess, including their stamina and strength. Yet, in sports such as soccer, there are other important abilities, like keeping track of players’ positions, knowing when and where to pass, and quickly reacting to changes on the field. Not only that but becoming a competitive player involves dedication to hours of practice, as well as confidence and a healthy mentality. Previous studies have begun to quantify these traits, showing that successful soccer players perform better on some cognitive tests than the general population. Still, these studies often have small samples of professional players, or study non-professional athletes, since it’s very hard to get access to top players.

This week in the Proceedings of the National Academy of Sciences, Leonardo Bonetti and colleagues conducted one of the largest studies to date on the cognitive and personality traits of professional soccer players, showing that these traits are distinct from the general population.

How did they do it?

The authors gathered a large group of professional soccer players (over 200) and a matched comparison group from the general population. The comparison group was matched on socio-economic status and age, which are important to consider when it comes to cognitive ability. The authors administered cognitive and personality tests to the participants so that they could compare the two groups. This sample included both men and women players, as well as players from two different countries (Brazil and Sweden), so they could ensure their results were replicated across cultures.

The cognitive tests (taken from the D-KEFS and WAIS IV) were measures of what is sometimes called “fluid intelligence”—cognitive abilities that are less dependent on education. For example, digit span, a simple test of working memory, involves the participant hearing a string of numbers and then reporting back as many as they can remember. Another example is the 5-point test, which evaluates a skill called nonverbal fluency, where participants had to generate as many ways as possible to connect a set of 5 dots in a limited amount of time. A third example is the Tower of Hanoi, where participants must move a series of stacked objects to get from one configuration to another in as few moves as possible. The personality measure used in the study was the Big Five, a science-backed personality system consisting of five traits: Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism (often known by the acronym OCEAN or CANOE).

What did they find?

The soccer players performed better than the general population on the cognitive tests: this superior performance included planning, problem-solving, and memory capacities. In the working memory test, the soccer players remembered 6 digits on average, whereas the control group could only remember just above 4 on average. The soccer players also showed higher levels of the personality traits Conscientiousness, Extraversion, and Openness to experience, along with lower levels of Neuroticism and Agreeableness.

The number of goals scored by a player was related to a high score on the 5-point test (nonverbal fluency), high Openness to experience, and low Conscientiousness. On the other hand, attempted and successful dribbles were predicted by a high digit span (working memory), a high Tower of Hanoi score (visuospatial reasoning), and high Openness to experience.

What's the impact?

This study shows that professional soccer players outperform the general population cognitively, not just physically, and that they have a specific pattern of personality traits. The authors think this could be helpful for recruiters looking for the next generation of stars. But it is unclear how these traits come about—are they the result of high-level training, or are they present before any training has begun?

An Atlas of Microglia in Neurodegenerative Disease

Post by Laura Maile

The takeaway

Microglia, the immune cells of the brain, play important roles in both brain homeostasis and disease. Several human datasets have now been compiled to create a human microglia atlas that characterizes microglia across multiple neurodegenerative diseases.

What's the science?

Microglia, the brain's resident immune cells, help maintain homeostasis and normal function of the CNS environment, including modulating synaptic connections between neurons. In cases of injury or infection, microglia convert to an activated state, where they take on an amoeboid shape and work to return the brain to homeostasis. In neurological disease, however, they can become abnormally activated and contribute to disease. Historically, activated microglia were divided into two categories: M1, a pro-inflammatory type, and M2, a neuroprotective type. Since this initial categorization, gene expression analysis led to a distinct class designated “disease-associated microglia” (DAM). DAM gene expression patterns, or signatures, have been commonly used to identify activated microglia in tissue responding to injury or other pathologies. Though the evolution of this field has proposed that these categories are too simplified to describe the range of microglia observed in disease, a comprehensive classification of microglia across different disease states has not yet been achieved. This week in Nature Communications, Martins-Ferreira and colleagues used 19 human datasets to create an atlas describing nine subpopulations of microglia in neurodegenerative disease.

How did they do it?

The authors integrated data from 19 single-cell RNA sequencing datasets from human brain tissue from patients with a variety of neurodegenerative disorders, including autism spectrum disorder (ASD), Alzheimer’s Disease, multiple sclerosis, epilepsy, Lewy Body Disease, and severe COVID-19. The integrated Human Microglia Atlas (HuMicA) accounts for 90,716 cells from 241 patient samples. They completed a cluster analysis to identify natural groupings of the sorted cells based on their gene expression and nine subpopulations were identified. The authors calculated the upregulated gene markers for each subpopulation and compared these markers with other available gene datasets that describe patterns of transcriptomic signatures in microglia populations. They identified specific patterns in each subpopulation and compared the prevalence of each subpopulation across each pathology to understand how microglial changes are associated with specific neurodegenerative diseases. Finally, the authors used the HuMicA to analyze differentially expressed genes (DEGs) in disease and healthy populations, allowing them to detect specific patterns of gene expression associated with individual pathologies.

What did they find?

They identified three homeostatic clusters, representing relatively healthy, inactivated microglia. They noted these clusters shared patterns of upregulated genes that normally identify homeostatic microglia, though each cluster also had its own signature of upregulated genes.

The DAM signature was broken down into four subpopulations, each with its own transcriptional patterns, including pro-inflammatory pathways, phagocytosis, lipid metabolism, or leukocyte activation  In addition, a group of monocyte-derived microglia-like cells previously described in mice are shown here to be prevalent in human brain as well, showed increases in gene expression cytokine production. Though all the clusters were observed across all analyzed human samples and disease profiles, they discovered patterns of expansion or depletion of specific clusters associated with individual neurodegenerative disorders. For example, they found expansion of a subpopulation expressing genes involved in lipid metabolism in AD and MS. After analyzing DEGs, the authors found some general pathology-related patterns of gene expression that were shared across diseases and others that were more specific to an individual disease or group of diseases. 

What's the impact?

This study was the first to create a comprehensive human microglia atlas, which identified subpopulations of microglia associated with neurodegenerative disorders. With this atlas, the authors demonstrated that microglia are complex and exist in many different states in the diseased brain. This data will advance our understanding of microglia in neurodegenerative diseases, and provide a useful tool in the study of microglia and disease.

The Relationship Between Fluoride Exposure and Child IQ

Post by Lila Metko 

The takeaway

Researchers have yet to determine to what extent fluoride exposure could cause neurotoxic effects. The authors examined multiple studies that measured the relationship between prenatal and child fluoride exposure and child IQ scores. They reported an inverse association between fluoride exposure and child IQ, meaning that IQ went down as fluoride exposure levels went up. 

What's the science?

It is estimated that on average the largest percentage of an American’s fluoride consumption comes from fluoridated drinking water. In 2006, the National Research Council issued a report outlining the possible neurotoxic effects of high fluoride exposure from drinking water. Multiple meta-analyses in the past decade have suggested an inverse relationship between fluoride exposure and child IQ. This week in JAMA Pediatrics, Taylor and colleagues conducted a meta-analysis of 74 studies on this topic, including a study quality assessment (also called risk of bias). 

How did they do it?

The authors systematically searched eight large network databases including PubMed, Scopus, and PsycINFO. The criterion for inclusion in the meta-analysis necessitated that the study “estimated the association between exposure to fluoride…and a quantitative measure of children’s intelligence.” Each study in the meta-analysis was evaluated with the OHAT risk of bias tool, a method developed by the National Toxicology Program. The OHAT risk of bias tool is an 11-question assessment including key questions that evaluate how well individual studies address potential confounding, exposure characterization, and outcome assessment. The majority of studies included reported group averages but 19 reported individual-level exposure, typically determined through fluoride content in drinking water or fluoride concentration in urine. The authors did a mean effects meta-analysis and a regression slopes meta-analysis that evaluated group-level and individual-level fluoride exposures respectively. A mean effects meta-analysis estimates standardized mean differences, a summary statistic that calculates the difference in IQ between children living in areas with high fluoride exposure and children living in areas with low fluoride exposure. A regression slopes meta-analysis uses regression coefficients from individual studies to estimate the change in IQ per a 1 mg/L increase in fluoride exposure. Some studies were excluded from these primary analyses because of factors such as a lack of reported mean IQ scores for outcome measures and overlapping populations. 

What did they find?

The authors found an inverse relationship between fluoride exposure and IQ in both the mean effects and regression slopes meta-analyses. Findings were consistent across high-risk of bias and low-risk of bias studies. Associations remained inverse when the exposure groups were exposed to less than 4 mg/L and less than 2 mg/L in drinking water. In the regression slopes meta-analysis the authors found that for every 1 mg/L increase in urinary fluoride concentration, there is a decrease of 1.63 points in a child’s IQ. While this study only assesses associations, it is significant to note that the inverse relationship between fluoride level exposure and child IQ was intact across different study designs, methods of assessing fluoride exposure, and IQ assessments. 

What's the impact?

This study is one of several in the past decade to find an inverse relationship between fluoride exposure and child IQ. This meta-analysis is notable because it used a rigorous and transparent process to identify all studies relevant to the specific research question, extract data from each study, and assess each of the 74 studies for risk of bias based on pre-specified criteria. Interestingly, associations remained inverse even when the exposure groups were exposed to less than 4 mg/L and less than 2 mg/L in drinking water. The EPA enforces that drinking water cannot have more than 4 mg/L fluoride and recommends that drinking water should have less than 2 mg/L fluoride.