Introduction Repetitive head trauma may be a risk factor for Alzheimer's disease and is considered the primary cause of chronic traumatic encephalopathy (CTE),1–5 a pathologically characterised neurodegenerative condition with diverse presentations during life.6 The potential long-term effects of cumulative head trauma on the brain have come to public view with the recognition that athletes in contact sports including American football demonstrated postmortem findings associated with CTE; a few of these reported cases harbouring very focal lesions have occurred in individuals under 20 years of age.7 A fundamental question that needs more exploration is the relationship between the amount, or dose, of head trauma and alteration in brain structure and function. Previous studies in boxers have reported frequency and duration of fighting to be associated with cognitive or neurological problems.7 ,8 Moreover, postmortem studies of CTE have revealed changes in a number of subcortical and cortical regions (9–11). With advances in neuroimaging, segmentation of these structures can be completed with automated programmes which are widely available, reproducible, and thus, if these regions prove to be markers of decline with repetitive traumatic brain injury, they have the potential to become clinically useful and readily calculated biomarkers. The Professional Fighters Brain Health Study (PFBHS) is a longitudinal cohort study of boxers and mixed martial arts (MMA) fighters designed to better understand the effects of repeated blows to the head on brain structure and function over time. This cross-sectional analysis of participants’ baseline evaluation explores the relationship between exposure to repeated blows to the head and MRI measures of brain structure and function, along with cognitive performance.

Methods Participants in the PFBHS are athletes, age 18 and older, who have at least a fourth grade reading level and are licensed to fight professionally in one of the combat sports, boxing or MMA. In addition, we recruited a control group who were matched on age and education to the fighter group. The control participants had no reported history of head trauma in civilian or military life, nor could they have played a sport associated with head injuries (eg, football, rugby, hockey, boxing, MMA, wrestling, soccer, rodeo) at a high school level or beyond. Participants are seen for baseline evaluation and on an annual basis thereafter over the next 4 years. Methods of recruitment and study procedures have been described previously.9 Data for this study come from the baseline evaluations. At the baseline visit, participants answer questionnaires with the assistance of the study coordinator that collect information on demographics; educational attainment; previous head trauma, both related and unrelated to athletic activities; and prior involvement in other contacts sports. Before the study visit, the fighter's professional record was obtained from commonly cited websites (boxrec.com for boxers and mixed martial arts.com and sherdog.com for MMA fighters) to determine number of years of professional fighting, number and outcome of professional fights, and frequency of professional fighting. Cognitive function was assessed by a computer-based battery that consists of four subtests of the CNS Vital Signs (CNS Vital Signs, North Carolina) including verbal memory, symbol digit coding, Stroop and a finger tapping test. CNS Vital Signs offers robust and reliable measurements of cognition which are computerised but are supervised by a technician. Raw summary scores were used for all analyses. Results from these tests are used to make up scores in various clinical domains: verbal memory, processing speed, psychomotor speed and reaction time.10 A high resolution T1-weighted anatomical MRI was obtained on all fighters. Scans were performed using the same Siemens 3T Verio scanner with a 32 channel head coil (Siemens Medical Systems, Erlangen, Germany). Acquisition protocol details were TR/TE/TI=2300/2.98/900, flip angle=9, BW=240 H z/Px, 240×256 matrix, 160 slices, voxel size=1×1×1.2 mm, scan time: 9:14. Volumes of the hippocampus and amygdala and subcortical grey matter including thalamus, caudate and putamen were calculated using the automated full brain segmentation process in Freesurfer software.11 The volumes of each structure were measured in both hemispheres separately. Statistical analysis The primary goal of the current study was to test for an association between fight exposure and brain volumes. Repeated measures analysis of variance was performed to test the association between the outcome variables and fight exposure variables. Five pairs of dependent variables, left and right thalamus, left and right hippocampus, left and right caudate, left and right putamen, and left and right amygdala were evaluated in separate models. Fight exposure was characterised by the total number of professional fights and the number of years of professional fighting. In univariate analyses the associations of these two continuous variables with brain volume were assessed using linear and quadratic effects, as well as cubic splines. A Fight Exposure Score (FES) had previously been derived as a function of cumulative fights and intensity of exposure (ie, total number of professional fights and number of professional fights per year; see table 1) and was also evaluated in this study. The FES detailed here has been explained in previous publications.9 Scores on the FES ranged from 0 to 4 with 4 representing the greatest exposure. Though there was only one subject with a score of 3, this category was maintained to ensure symmetry with scores of 1 and 2. In each model we included the type of fighter (boxer or MMA); we tested the significance of the interaction term for the type of fighter with the other exposure variable. All analyses were adjusted for intracranial volume (ICV; treated as a continuous variable), age (treated as a continuous variable), education (defined as no college level vs some college level) and race (defined as: (1) Caucasian, (2) African-American and (3) other (Asian, Pacific Islander, American Indian and Alaskan Native)). A significance level of 0.05 was used to test the effect of the exposure variables on brain volumes. Table 1 Fight Exposure Score Models were also constructed to assess differences between the fighter groups and controls in brain volume. A comparison of estimated reduction in brain volume between boxers, MMA and control while controlling for age, years of education, race and number of professional fights was completed to assess the specificity of our findings to fighters. Dunnett's test was used for contrasting mean responses against controls and making adjustments for multiple comparisons within a particular measure. Secondary goals of the study were to test for associations between brain volume and cognitive test scores and between fight exposure and cognitive test scores. Generalised linear models were constructed with cognitive scores as the dependent variables and brain volume or fight exposure variables as the independent variables of interest; analyses were adjusted for ICV, age, race and education. Cognitive scores were compared against age-matched and education level-matched normative values (based on cutpoints at 1.5×SD below the mean) provided to our group by CNS Vital Signs to define presence/absence of impairment. Associations between types of impairment and the FES were evaluated using χ2 tests. All analyses were performed in SAS V.9.2.

Results Complete data were collected on 224 male fighters: 93 boxers and 131 MMAs, and 22 controls. The fighters’ age ranged from 18 to 44 with median of 27 years. There were 89 (39.7%) Caucasians, 59 (26.3%) African-Americans and 76 (33.9%) others. Fifty-four per cent of the participants had less than or equal to a high school education; 46% had at least some college-level education. The total number of years of professional fighting ranged from 0 to 24, with a mean of 4 years. The total number of professional fights ranged from 0 to 101, with a mean of 10 fights. Table 2 summarises the amateur and professional years of fighting, number of fights and knock-outs by the type of fighting. Table 2 Fight exposure by type of fighting* A summary table of the results of various measures of exposure and brain volumes is given in table 3. Type of fighting was correlated with thalamic and hippocampal volumes with boxers having lower volumes than MMA fighters. In general, increasing exposure either as measured by the number of professional fights or years of professional fighting is associated with lower brain structure volumes, particularly with subcortical structures. The most consistent relationship between exposure variables and brain volume was seen in the thalamus and caudate. Table 3 Summary of correlations between exposure measures and brain volumes Utilising the FES, each increase in the score was associated with reductions of 0.8%, 0.9% and 0.8% in volumes of the caudate, amygdala and thalamus (see figure 1), respectively. There was no specific threshold of number of professional fights or FES where the relationship between number of professional fights or FES and brain volumes was seen. Figure 1 Illustration of association between thalamus volume and the number of professional fights for boxers and mixed martial arts (MMA) fighters. The estimated mean volumes are standardised relative to a MMA fighter with zero professional fights. When comparing brain volumes by type of fighter and controls, significant differences were seen between boxer and MMA fighters for all right and left brain measures and for several right and left brain measures for boxers and controls (table 4). Table 4 Summary of difference in volume between fighter groups and controls on the various brain measures Among the various cognitive domains, only speed of processing was significantly related to volume and exposure. Smaller volumes of the thalamus, amygdala and left hippocampus were associated with lower scores on speed of processing measures (figure 2). Boxers had significantly lower scores than MMA fighters (p<0.001). Figure 2 Association between brain volume (in one-unit SD increments below and above the mean) and processing speed scores. Scores decrease 2–3% per one SD decrease in brain volume. There was a significant relationship between the number of professional fights and speed of processing (p=0.041), with an estimated 0.19% reduction in processing speed per fight. Similarly, there was a significant relationship between the FES and speed of processing (p=0.023), with an estimated 2.1% reduction in processing speed scores for each increase in FES. The effect was most evident at the extremes of the FES, where fighters with a score of 4 have an 8.8% age-adjusted, race-adjusted and education-adjusted reduction in scores relative to fighters with a FES of 0. In models constructed to compare the three participant groups on the four cognitive measures (and including age, education and race in the model), no differences were seen for verbal memory. Processing speed was related to fighter type (adjusting for years of education) with both fighter groups scoring worse than controls, but boxers being overall slower than MMA fighters. Figure 3 illustrates the proportion of participants impaired, defined as 1.5 SD below age-matched and education level-matched normative values, for the various cognitive domains as a function of the participants’ FES. The proportions of participants with verbal memory impairment and with psychomotor speed impairment increased significantly with the magnitude of the FES (p=0.036 and p=0.046, respectively). Note that although we saw a significant association between the FES and speed of processing scores, this correlation was not seen when the analysis was limited to the proportion of those who were in an impaired range (p=0.244). Figure 3 Illustration of the proportion of impaired fighters for the four cognitive domains as a function of the Fight Exposure Score (FES). Values above bars indicate the number of impaired participants with the given FES. There were 49 participants with a FES of 0, 114 participants with scores of 1 or 2 and 11 participants with scores of 3 or 4.