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. 2024 Feb 5;7(2):e2354235.
doi: 10.1001/jamanetworkopen.2023.54235.

Cerebral Cortical Surface Structure and Neural Activation Pattern Among Adolescent Football Players

Taylor R Zuidema  1   2 , Jiancheng Hou  1   3 , Kyle A Kercher  1 , Grace O Recht  1 , Sage H Sweeney  1 , Nishant Chenchaiah  1 , Hu Cheng  2   4 , Jesse A Steinfeldt  5 , Keisuke Kawata  1   2   6
Affiliations

Cerebral Cortical Surface Structure and Neural Activation Pattern Among Adolescent Football Players

Taylor R Zuidema et al. JAMA Netw Open. .

Abstract

Importance: Recurring exposure to head impacts in American football has garnered public and scientific attention, yet neurobiological associations in adolescent football players remain unclear.

Objective: To examine cortical structure and neurophysiological characteristics in adolescent football players.

Design, setting, and participants: This cohort study included adolescent football players and control athletes (swimming, cross country, and tennis) from 5 high school athletic programs, who were matched with age, sex (male), and school. Neuroimaging assessments were conducted May to July of the 2021 and 2022 seasons. Data were analyzed from February to November 2023.

Exposure: Playing tackle football or noncontact sports.

Main outcomes and measures: Structural magnetic resonance imaging (MRI) data were analyzed for cortical thickness, sulcal depth, and gyrification, and cortical surface-based resting state (RS)-functional MRI analyses examined the amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and RS-functional connectivity (RS-FC).

Results: Two-hundred seventy-five male participants (205 football players; mean [SD] age, 15.8 [1.2] years; 5 Asian [2.4%], 8 Black or African American [3.9%], and 189 White [92.2%]; 70 control participants; mean [SD] age 15.8 [1.2] years, 4 Asian [5.7], 1 Black or African American [1.4%], and 64 White [91.5%]) were included in this study. Relative to the control group, the football group showed significant cortical thinning, especially in fronto-occipital regions (eg, right precentral gyrus: t = -2.24; P = .01; left superior frontal gyrus: -2.42; P = .002). Elevated cortical thickness in football players was observed in the anterior and posterior cingulate cortex (eg, left posterior cingulate cortex: t = 2.28; P = .01; right caudal anterior cingulate cortex 3.01; P = .001). The football group had greater and deeper sulcal depth than the control groups in the cingulate cortex, precuneus, and precentral gyrus (eg, right inferior parietal lobule: t = 2.20; P = .004; right caudal anterior cingulate cortex: 4.30; P < .001). Significantly lower ALFF was detected in the frontal lobe and cingulate cortex of the football group (t = -3.66 to -4.92; P < .01), whereas elevated ALFF was observed in the occipital regions (calcarine and lingual gyrus, t = 3.20; P < .01). Similar to ALFF, football players exhibited lower ReHo in the precentral gyrus and medial aspects of the brain, such as precuneus, insula, and cingulum, whereas elevated ReHo was clustered in the occipitotemporal regions (t = 3.17; P < .001; to 4.32; P < .01). There was no group difference in RS-FC measures.

Conclusions and relevance: In this study of adolescent athletes, there was evidence of discernible structural and physiological differences in the brains of adolescent football players compared with their noncontact controls. Many of the affected brain regions were associated with mental health well-being.

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Conflict of interest statement

Conflict of Interest Disclosures: Dr Kercher reported receiving grants from the National Institutes of Health (NIH) during the conduct of the study. Dr Kawata reported receiving grants from the NIH and Indiana State Department of Health during the conduct of the study. No other disclosures were reported.

Figures

Figure 1.
Figure 1.. Cortical Morphological Differences Between the Adolescent Football Players and Control Athletes
Group difference was assessed for cortical thickness (A), sulcal depth (B), and gyrification (C). The multiple comparison correction was used with nonparametric permutations (5000 permutations) and the threshold-free cluster enhancement correction after 5000 permutations. Red indicates that the football group is higher compared with the control group. Blue indicates that the football group is lower compared with the control group.
Figure 2.
Figure 2.. Regional Differences in Neurophysiology Between the Football and Control Groups
The surface-based resting state–functional magnetic resonance imaging technique was used to test the group differences in amplitude of low-frequency fluctuation (A and B) and regional homogeneity (C and D). The multiple comparison correction was used with nonparametric permutations (5000 permutations) and the threshold-free cluster enhancement correction after 5000 permutations.
See this image and copyright information in PMC

Comment in

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