Introduction

Studies have shown that both active and retired athletes with repeated head trauma are more likely to suffer from cognitive decline and loss of executive and attention functions when compared to age-matched healthy controls^1,2. However, to the best of our knowledge, it is still unclear: (a) whether there are changes in cortical thickness between cognitively impaired and nonimpaired active professional fighters, and whether or not there is an association between cortical thickness and exposure to fighting; (b) whether there is a differentiable coordinated pattern of large-scale structural networks between the cognitively impaired and nonimpaired active professional fighters; and (c) whether the differences in regional cortical thickness can be exploited to predict cognitive decline in active professional fighters. Hence, in this study we utilized data from the professional fighters brain health study (PFBHS)³ which is a longitudinal study of active professional fighters, to compare cortical thickness of the brain regions between cognitively impaired and nonimpaired active fighters

Methods

Subjects: A total of 252 active professional fighters (18 females (F)) were recruited at our centre. Each subject went through a battery of neuropsychological assessment tests to measure psychomotor speed (PSY) and processing speed (P). The fighters were classified as cognitively impaired if the standardized PSY and P scores were 1.5 standard deviations below the mean⁴. Data Acquisition: All subjects were scanned at our center with a 3T Siemens Verio scanner with a 32 channel head coil. Sagittal-MPRAGE T1-weighted images were also acquired for every subject within the same session with TR/TE/FA/Resolution= 2300ms/2.98ms/9^o/1mm. Network construction: Cortical thickness from 34 regions in Collin’s atlas in each hemisphere were extracted for every subject using Freesurfer v5.3.05. Interregional correlation matrix of each group was computed by calculating partial correlations between the cortical thicknesses of every pair of regions across individuals⁶. A linear regression analysis was performed to remove the effect of the confounding factors (age, gender, YOE, and race) and the residuals were used in the following analysis. Graph-theoretical properties: Various local and global graph-theoretical properties were computed for each group using GRETNA⁷. The graph-theoretical properties were evaluated at various sparsity thresholds (5%-40%, step=1%). At each sparsity threshold, all the entries of the correlation matrix were binarized and the computation was done on this binary matrix. Predictive analysis: A predictive analysis was conducted to understand whether changes in the topological network of cortical thickness could predict cognitive impairment in active professional fighters using our LASSO and RBFN⁸. Statistical analysis: Vertex-wise analysis was conducted in FreeSurfer with permutation testing to test for any group differences in cortical thickness between groups after controlling for confounds. To test the differences in the interregional cortical thickness between the fighters group, every internode correlation value was converted to z-score and a Z-statistic was performed to compare the transformed z-values with false discovery rate correction at p<0.05⁶. Nonparametric permutation testing was applied to compare the various graph-theoretical properties⁶. All statistical comparisons were corrected for family-wise error at p<0.05.

Results

Vertex-wise analysis revealed no region with significant differences in cortical thickness between groups. Regions from Colin’s atlas used to build the connectivity matrix are shown in the left-panel of Fig.1 (a). The regions with the same name are coded with the same color between the hemispheres. Partial correlation matrix, both weighted (Fig.1b) and binarized (Fig.1c) show that there is a discernible qualitative difference in the correlation between the two groups. As shown in Fig.2a, both higher and lower correlation strength was observed for impaired fighters. However, most of the correlations where impaired fighters had a higher correlation as compared to nonimpaired fighters were driven by short-distance connections (Fig.2b). Significantly impaired graph-theoretical measures were obtained in cognitively impaired fighters (Fig.3). The cortical thickness of just two regions, rostral anterior cingulate cortex, and transverse temporal cortex, derived using the connectivity pattern shift between the groups was able to predict cognitive decline with 61% accuracy.

Discussion and Conclusion

This study shows that repeated head trauma is associated with altered coordination of large-scale structural brain networks, especially in the long-range connections. Furthermore, the cortical thickness of regions identified as hubs has the potential of developing into a predictive biomarker for identifying the fighters that will develop cognitive decline due to repeated head trauma.

Acknowledgements

This work was supported by an Institutional Development Award (IDeA) from the National Institute of General Medical Sciences of the National Institutes of Health under grant number 5P20GM109025, and private grant funds from the Lincy Foundation, the Peter and Angela Dal Pezzo funds, and the young scientist award.