ADHD May Associate With Reduced Tolerance to Acute Subconcussive Head Impacts: A Pilot Case-Control Intervention Study

Abstract

Objective:

To test our hypothesis that individuals with ADHD would exhibit reduced resiliency to subconcussive head impacts induced by ten soccer headings.

Method:

We conducted a case-control intervention study in 51 adults (20.6 ± 1.7 years old). Cognitive assessment, using ImPACT, and plasma levels of neurofilament-light (NF-L), Tau, glial-fibrillary-acidic protein (GFAP), and ubiquitin-C-terminal hydrolase-L1 (UCH-L1) were measured.

Results:

Ten controlled soccer headings demonstrated ADHD-specific transient declines in verbal memory function. Ten headings also blunted learning effects in visual memory function in the ADHD group while the non-ADHD counterparts improved both verbal and visual memory functions even after ten headings. Blood biomarker levels of the ADHD group were sensitive to the stress induced by ten headings, where plasma GFAP and UCH-L1 levels acutely increased after 10 headings. Variance in ADHD-specific verbal memory decline was correlated with increased levels of plasma GFAP in the ADHD group.

Conclusions:

These data suggest that ADHD may reduce brain tolerance to repetitive subconcussive head impacts.

Keywords

ADHD adult ADHD cognitive functioning head trauma case-control study concussion soccer football

Introduction

Attention-deficit/hyperactivity disorder (ADHD), which affects 6.4 million children (Visser et al., 2014) and nearly 2 million young adults in the United States (Kessler et al., 2006), is the most common neurodevelopmental disorder and is characterized by impulsivity, inattention, and hyperactivity (Centers for Disease & Prevention, 2005). ADHD has been shown to be an antecedent risk factor for concussion in high school and college athletes, with the concussion incidence increasing by 1.5- to 5-fold (Biederman et al., 2015; Iaccarino et al., 2018; Liou et al., 2018), accompanied by amplified concussion symptoms, prolonged recovery (Adeyemo et al., 2014), and impaired performance on working memory tasks (Biederman et al., 2015).

The current scientific literature primarily focuses on ADHD-specific neurophysiological and functional sequalae after a concussion. However, subconcussive head impacts in sports, which are defined as hits to the head that do not cause overt concussion symptoms, have emerged as a major public health concern (McCrory et al., 2017). Although asymptomatic, these subconcussive head impacts have shown to disrupt neural connections (Slobounov et al., 2017), increase axonal diffusion (Hirad et al., 2019; Lipton et al., 2013), impair ocular-motor function (Kawata, Rubin, et al., 2016; Zonner, Ejima, Fulgar, et al., 2019), and increase brain-derived blood biomarker levels (Joseph et al., 2018; Oliver et al., 2016; Zonner, Ejima, Bevilacqua, et al., 2019) in an impact-dependent manner. Approximately 6.5% to 10.1% of college athletes are diagnosed with and treated for ADHD (Poysophon & Rao, 2018), and the majority of these athletes engage in contact sports (e.g., soccer, football) (Manderino & Gunstad, 2018), where they can sustain several hundred to a thousand subconcussive head impacts per season (Bailes et al., 2013). However, it remains unknown whether, and to what extent, subconcussive head impact exposure influences neurocognitive function and blood biomarker expressions in ADHD.

Since ADHD and subconcussive head impacts can individually and collectively alter diverse aspects of brain function, it is of paramount importance to use a multimodal assessment approach to understand the influence of ADHD and subconcussion. The use of brain-derived blood biomarkers is a productive means to objectively study cellular structural, metabolic, and vascular integrity of the brain (Kawata, Liu, et al., 2016). In early 2018, The United States Food and Drug Administration (FDA) approved the use of blood levels of glial fibrillary acidic protein (GFAP) and Ubiquitin C-terminal hydrolase-L1 (UCH-L1) as referral tools for CT scans to test for the presence of intracranial bleeding (Bazarian et al., 2018). Neuronal axon-derived proteomes, neurofilament light (NF-L) and Tau, also have been studied extensively in athletes without ADHD. For example, as few as 10 acute soccer headings were sufficient to increase NF-L levels in plasma after 24 hours (Wallace et al., 2018; Wirsching et al., 2019), and season-long exposure to American football subconcussive head impacts resulted in gradual and lingering elevations in NF-L and Tau levels (Joseph et al., 2018; Oliver et al., 2016). However, there are no studies examining these blood biomarkers after acute subconcussive head impacts in athletes with ADHD, or the relationship between blood biomarkers and cognitive function.

Therefore, we conducted a case-control intervention study to examine the neural response to subconcussive head impacts in individuals with and without ADHD diagnosis through cognitive testing using Immediate Post-concussion Assessment and Cognitive Testing (ImPACT) and four of the most well-studied proteomic blood biomarkers (NF-L, Tau, GFAP, and UCH-L1). We used our soccer heading paradigm (Bevilacqua et al., 2019) to induce 10 controlled subconcussive head impacts while eliminating extraneous influences that is inherent in field studies, such as bodily hits, fatigue, strenuous exercise, and perspiration/hydration. Since individuals with ADHD have shown to respond adversely to concussion compared to non-ADHD counterparts (Adeyemo et al., 2014; Biederman et al., 2015; Iaccarino et al., 2018; Liou et al., 2018), we hypothesized that individuals with ADHD would also have a reduced tolerance to subconcussive head impacts, by exhibiting significant declines in cognitive function and increases in blood biomarker levels after 10 soccer headings, as compared to their non-ADHD counterparts. In addition, we conducted a post-hoc analysis to examine whether the cognitive decline would correlate with elevations in blood biomarkers in individuals with ADHD.

Methods

Participants

From August 2018 through May 2019, we screened 70 potential participants, and 51 participants (ADHD-heading, n = 17; non-ADHD-heading, n = 17; and non-ADHD-kicking, n = 17) were included in the study (Figure 1). All potential participants filled out a health questionnaire pertaining to his/her current health status, sport participation history, and history of concussion. Inclusion criteria across all groups consisted of being between the ages of 18 and 26 years and to have at least 5 years of soccer heading experience. Participants were asked to recall and self-report his/her history of concussion. This retrospective recall method has potential to be influenced by recall bias; however, it is a commonly used method and has been implemented in our previous studies (Nowak et al., 2020; Wirsching et al., 2019). For exclusion, participants in all groups were excluded for a history of head injury including concussion during 1 year prior to the study or for a history of neurologic or learning disorders besides ADHD. Participants were blinded to the study aims and hypotheses.

Figure 1.

Study flow chart.

ADHD cohort

Additional inclusion criteria for ADHD participants consisted of documentation of a full ADHD diagnosis administrated by either a psychologist, psychiatrist, or neurologist, and administration of their prescribed ADHD medication at least 5 times a week. To validate their ADHD diagnosis, we administrated the symptom-checklist of the Diagnostic and Statistical Manual of Mental Disorders 5th Edition (DSM-5) (Biederman et al., 2015; Epstein & Loren, 2013) to quantify participants’ current inattention and hyperactivity/impulsivity-related symptoms. In compliance with the DMS-5, participants proceeded to the study if they reported at least five symptoms in either inattention or hyperactivity/impulsivity domains of the questionnaire and were free of symptoms unrelated to ADHD (i.e., schizophrenia, substance withdrawal) (Epstein & Loren, 2013).

Non-ADHD cohort

Participants in the non-ADHD-heading and non-ADHD-kicking groups were required to be free of current and previous diagnosis of ADHD and have no history of taking ADHD medication. As with the ADHD-heading group, participants in the non-ADHD groups completed the DSM-5 symptom-checklist, and those participants who scored below the threshold of the ADHD criteria proceeded to the study (Epstein & Loren, 2013).

Study Design

This single-center, case-control intervention study consisted of three groups: ADHD-heading, non-ADHD-heading, and non-ADHD-kicking. ADHD participants were directly assigned into the ADHD-heading group, whereas non-ADHD participants were randomly assigned to the non-ADHD-heading or non-ADHD-kicking group through a random coding derived from R that was corresponded to the order of interested participants. Each group underwent serial testing of cognitive function using ImPACT at 4 time points: [pre-intervention baseline, 0 hour- (or 15 minutes-), 2 hours-, and 24 hours-post intervention]. Plasma samples were also collected at all 4 time points, to assure consistency of the procedures, but were analyzed at the 3 selected time points. Our previous data informed us that brain-derived cellular factors require much longer than 15 minutes to overexpress and translocate into the peripheral circulation (Wirsching et al., 2019). Thus, we assessed NF-L, Tau, GFAP, and UCH-L1 levels at the pre, 2 hours-, and 24 hours-post time points. Between pre- and 0 hour-post intervention, the ADHD-heading and non-ADHD-heading groups performed 10 soccer headers, whereas the non-ADHD-kicking group performed 10 kicks (see the Subconcussion Intervention section). Participants in all groups remained in the laboratory until the 2 hours-post intervention time point without engaging in strenuous cognitive or physical activities and returned to the laboratory 24 hours later for the final data collection. All individuals were instructed to refrain from activities that may induce subconcussive head impacts, as well as alcohol and recreational drug use during the study period. Additionally, individuals in the ADHD group were instructed to take their prescribed ADHD medication during the days of the study period, which was verified at the beginning of each testing days. Please refer to the online-only supplemental document for the detailed procedure.

Protocol Approvals and Registration

The Indiana University Institutional Review Board approved the study protocol, and written informed consent was obtained from all participants. The randomized controlled trial protocol for the control groups was registered in ClinicalTrials.gov (ID: NCT03488381).

Subconcussion Intervention

A standardized and reliable soccer heading protocol was used as a means to induce subconcussive head impacts (Wirsching et al., 2019). See Bevilacqua et al. (2019) for a video version of the soccer heading protocol. A triaxial accelerometer (Triax Technologies, Inc.) was used to measure linear and rotational head acceleration. A JUGS soccer machine (JPS Sports, Tualatin, Oregon) was used to launch a size 5 soccer ball, with the ball traveling at a speed set at 25 mph (11.2 m/s), which is on the slower-scale end of rising balls kicked by adult soccer players (Babbs, 2001). Participants in all groups stood 40 feet away from the machine to perform the headers or kicks. Participants performed 10 headers or kicks with a 1-minute interval between each launch.

Neurocognitive Assessment using ImPACT

ImPACT is a well-established computer-based cognitive assessment frequently used in concussion diagnosis, with a reported sensitivity of 91.4% and specificity of 69.1% (Schatz & Sandel, 2013). The ImPACT was administered in a non-distracting environment at every time point and took approximately 25 minutes to complete. As part of our protocol, only one test variation was used at all timepoints for all participants. This allowed us to evaluate participants’ cognitive ability to learn and adapt to repeated testing (Peterson et al., 2003). Upon completion of the test, five composite scores were generated: verbal memory, visual memory, visual-motor speed, reaction time, and impulse control. Scoring range and normative score were listed in Supplemental Table 1. ImPACT also evaluated 22 concussion-related symptoms (e.g., headache, dizziness, disorientation) (McCrory et al., 2017) on a 7-point Likert scale (0, no symptom; 6, most severe).

Blood Biomarker Assessments

Blood samples collected pre- (30 minutes before), 2 hours-, and 24 hours-post intervention were used for biomarker assessments. Plasma levels of NF-L, Tau, GFAP, and UCH-L1 in the same sample aliquot were measured using the Human Neurology 4-Plex A assay (N4PA) on a HD-1 single molecule array (Simoa^TM, Quanterix). An experimental protocol was previously described in detail (Thelin et al., 2019). The analyses were performed by a board-certified laboratory technician blinded to the study design and subject characteristics. Limit of detection (LOD) was 0.104 pg/mL for NF-L, 0.024 pg/mL for Tau, 0.221 pg/mL for GFAP, and 1.74 pg/mL for UCH-L1. The average intra-assay coefficients of variation for the samples were 8.3 ± 6.0% for NF-L, 6.7 ± 5.2% for Tau, 3.7 ± 2.7% for GFAP, and 21.5 ± 20.8% for UCH-L1.

Primary and Secondary Interests

Since the ADHD and non-ADHD groups have fundamental difference in neurological conditions at baseline, our primary interest was set to the within-group changes in neurocognitive scores and biomarker levels over time compared to the baselines of each group. The data for the non-ADHD-kicking group was used to evaluate the participants’ ability to demonstrate a learning effect with repeated neurocognitive testing and to assess biomarker fluctuation due to soccer kicking. Our secondary interest was to test the changes in neurocognitive scores and biomarker levels over time between the ADHD-heading and non-ADHD-heading groups, which addressed whether ADHD could modify the heading effects on neurocognitive function and neuronal cellular damage.

Statistical Analysis

Multivariate mixed-effect regression models (MMRM) were used to examine our primary and secondary interests. The neurocognitive variables were scores for verbal memory, visual memory, visual-motor speed, reaction time, impulse control, and total symptom score. The blood biomarker variables were plasma levels of NF-L, Tau, GFAP, and UCH-L1. The primary predictors (fixed effect) were groups (ADHD-heading, non-ADHD-heading, non-ADHD-kicking), time of measurement (pre, 0 hour-, 2 hours-, and 24 hours-post intervention), and group by time interaction. Time was treated as a categorical variable by providing dummy variables for each time point. The model accounted for the repeated measures from the same participants, with participants treated as a random effect, and included potential covariates (sex, age, BMI, years of soccer heading experience, number of previous concussion). Relative to other analytic approaches (i.e., repeated measures ANOVA), MMRM accounts for missing data, and a single model is able to provide estimates (β) for all possible comparisons. Therefore, the correction for multiple comparison was not conducted.

Lastly, we conducted a post-hoc analysis to examine whether blood biomarker change correlates with head-impact induced cognitive change. Although there were numerous comparisons to explore, we focused on significant within-group declines in cognitive variables and elevations in blood biomarkers at the same time point after 10 headings. In a linear regression model, we treated changes in cognitive score from baseline as outcome and changes in biomarker levels from baseline as predictor. All analyses were conducted using statistical software R (version 3.4.1) with package “nlme.” Two identical MMRM to test ImPACT and biomarker data were used, thus significance level was corrected to 0.025. The analysis was summarized by providing a contrast estimate with its 95% CI and a p-value in the following format: [estimate (CI_low, CI_high); p-value].

Results

Demographics

Seventy individuals were assessed for eligibility, and 63 individuals who met the inclusion criteria and were free of exclusion criteria proceeded to the study. Twelve individuals withdrew voluntarily before the pre-intervention time point due to lost interest or schedule conflict. As a result, data from 51 participants were valid for neurocognitive function analysis: ADHD-heading, n = 17; non-ADHD-heading, n = 17; and non-ADHD-kicking, n = 17. Three individuals were not valid for blood biomarker analysis due to phlebotomy issues, yielding: ADHD-heading, n = 16; non-ADHD-heading, n = 17; and non-ADHD-kicking, n = 15. All subjects in the ADHD-heading group reported to take their prescribed ADHD medications during the study period, except for one individual who did not take his/her medication on day two of the study; therefore, his/her data from 24 hours-post time point was excluded from analysis (Figure 1). Demographics and head impact kinematics are detailed in Table 1.

Table 1.

Demographics and Impact Kinematics by Group.

Variables	ADHD heading	Non-ADHD heading	Non-ADHD kicking
n	17	17	17
Sex	6 M 11 F	10 M 7 F	7 M 10 F
Age, y	20.2 ± 0.15	21.1 ± 0.10	20.5 ± 0.08
BMI, kg/m²	24.4 ± 0.37	24.1 ± 0.15	24.9 ± 0.24
No. of previous concussion
0, n (%)	6 (35.3)	13 (76.5)	11 (64.7)
1, n (%)	6 (35.3)	2 (11.8)	5 (29.4)
2, n (%)	4 (23.5)	1 (5.9)	1 (5.9)
3, n (%)	1 (5.9)	1 (5.9)	0 (0.0)
Soccer heading experience, y	9.4 ± 0.21	9.1 ± 0.23	9.5 ± 0.23
Race, n (%)
White	16 (94)	15 (88)	15 (88)
Black/African American	1 (6)	2 (12)	2 (12)
Ethnicity, n (%)
Not Latino/Hispanic	17 (100)	12 (71)	15 (88)
Latino/Hispanic	0 (0)	5 (29)	2 (12)
ADHD Medication, avg. days per week	6.8 ± 0.03	-^a	-^a
DSM-5 Criteria, No. of symptoms
Inattention	6.1 ± 0.14	0.35 ± 0.04	0.29 ± 0.03
Hyperactivity-Impulsivity	4.0 ± 0.12	0.65 ± 0.05	0.59 ± 0.06
Head impact kinematics per header
PLA, g	30.9 ± 2.1	31.2 ± 3.91	- ^b
PRA, krad/s²	3.5 ± 1.1	3.2 ± 0.7	- ^b

Note. BMI = body mass index; DSM-5 = diagnostic and statistical manual of mental disorders 5th edition; PLA = peak linear acceleration; PRA = peak rotational acceleration. krad, kiloradian.

Individuals who were not diagnosed with ADHD and had no history of taking ADHD medication. ^bSoccer kicking did not cause a detectable level of head acceleration.

ADHD-Specific Alteration in Verbal and Visual Memory Function After 10 Headings

ADHD-heading group showed significant declines in verbal memory function at 0 hour-post and 2 hours-post heading compared to baseline, and then return to their baseline level at 24 hours-post heading. Conversely, verbal memory function of the non-ADHD-heading group did not change after 10 soccer headings. Significant group by time interactions between the ADHD-heading and non-ADHD-heading groups emerged at 0 hour- and 2 hours-post heading [0 hour-post, –7.65 (–12.58, –2.71), p = .003; 2 hours-post, –9.41 (–14.35, –4.48), p < .001] and disappeared at 24 hours-post heading [–4.01 (–9.00, 0.97), p = 0.117] (Figure 2a). These groups did not differ at baseline [0.59 (–5.49, 6.68), p = 0.849]. The non-ADHD-kicking group demonstrated a significant improvement in verbal memory function at all post-kicking time points compared with baseline. Please refer to Supplemental Figure 2 for individual changes from baseline.

Figure 2.

Subconcussive effects on (a) verbal memory and (b) visual memory. Our primary comparison was of the ADHD-heading versus non-ADHD-heading groups. The ADHD-heading group showed significant impairment in verbal and visual memory function after 10 headings. Values graphed represent group means at each timepoint and the standard error of the mean (SEM).

Despite sustaining 10 headings, the non-ADHD-heading group showed significant improvements in visual memory function at 24 hours-post heading compared with baseline. Contrarily, 10 headings blunted improvements of visual memory function in the ADHD-heading group. Improvements were also seen in the non-ADHD-kicking group at 0 hour-post and at 24 hours-post kicking compared with baseline (Supplemental Table 2). A significant group by time interaction between the ADHD-heading and non-ADHD-heading groups appeared at 24 hours-post heading [–9.83 (–16.84, –2.83), p = .007], where the ADHD-heading group performed substantially poorer visual memory function than the non-ADHD heading group (Figure 2b). These groups did not differ at baseline [–1.64 (–9.68, 6.40), p = .691].

Cognitive Domains that are Resilient to Acute Subconcussive Head Impacts

There were minimal to no negative influence from soccer heading and kicking on visual-motor speed, impulse control, reaction time, and symptom scores in all three groups. Please refer to Figure 3a−d for the group trend and Supplemental Table 2 for the within-group changes from baseline.

Figure 3.

Subconcussive effects on (a) visual-motor speed, (b) impulse control, (c) reaction time, and (d) total symptom score. Our primary comparison was of the ADHD-heading versus non-ADHD-heading groups, and there was no significant group by time interaction. Values graphed represent group means at each timepoint and the standard error of the mean (SEM).

ADHD and Subconcussive Effects on Brain-Derived Blood Biomarker Profile

ADHD’s unique response to 10 soccer headings was observed in GFAP and UCH-L1. Specifically, 10 soccer headings led to a significant increase in GFAP at 2 hours-post heading [13.48 pg/mL (6.30, 20.65), p < .001] and 24 hours-post heading [8.51 pg/mL (1.52, 15.50), p = .019] in the ADHD-heading group, compared with baseline. Conversely, GFAP levels in both non-ADHD groups remained unchanged at all time points (Figure 4a). We failed to detect a group by time interaction in GFAP between the ADHD-heading and non-ADHD-heading groups [2 hours-post, 10.03 pg/mL (–0.12, 20.17), p = .056; 24 hours-post, 5.19 (–4.59, 14.96), p = .301]. Plasma UCH-L1 gradually increased after headings in the ADHD-heading group, and a significant time effect emerged at 24 hours-post heading as compared to baseline [6.26 pg/mL (1.42, 11.10), p = .013]. Conversely, both non-ADHD groups remained unchanged at all time points, resulting in a significant group by time interaction in plasma UCH-L1 levels between the ADHD-heading and non-ADHD-heading groups at 24 hours-post heading [7.60 pg/mL (0.92, 14.29), p = .029] (Figure 4b). Please refer to Supplemental Figures 3 (GFAP) and 4 (UCH-L1) for individual changes from baseline. There were minimum within-group fluctuations in Tau and NF-L levels in all groups (Figure 4c and D), except for a significant elevation in NF-L levels in the non-ADHD-heading group at 24 hours-post heading. See Supplemental Table 3 for the within-group changes from baseline.

Figure 4.

Subconcussive effects on plasma levels of (a) GFAP, (b) UCH-L1, (c) Tau, and (d) NF-L. ADHD specific elevation was observed in GFAP and UCH-L1, whereas NF-L was elevated only in the non-ADHD-heading group.

Relationships Between Impact-Induced Cognitive Declines and Biomarker Elevations

As shown above, a concomitant cognitive decline with biomarker elevation was observed only in the ADHD-heading group. Specifically, a significant decrease in verbal memory score and an increase in GFAP levels occurred at 2 hours-post heading. Our post-hoc regression analysis revealed an inverse correlation between verbal memory and GFAP level at 2 hours-post heading in the ADHD-heading group (Figure 5a). These data indicate that each unit increase (1 pg/mL) in plasma GFAP level after 10 soccer headings is associated with a 0.423 decrease in their verbal memory score (p = .008). The GFAP-verbal memory association was specific to 2 hours-post heading (Figure 5b−d).

Figure 5.

Association between cognitive declines and blood biomarker elevations. A significant association was specific to the 2 hours-post heading time point in the ADHD-heading group (a). Our finding was reinforced by non-significant association in three other combinations in the ADHD-heading group (b−d).

Discussion

This case-control intervention study provides initial evidence that ADHD may associate with reduced neurologic tolerance to acute subconcussive head impacts. The data confirmed some previous findings, generated critical knowledge about subconcussive effects on cognition and blood biomarkers, and might introduce an entirely new concept to the neurology, psychiatry, and neurotrauma research communities. First, varied degrees of acute and transient impairments in verbal memory function were observed in participants with ADHD following 10 soccer headings. Second, 10 soccer headings seemed to blunt a learning effect on visual memory function in ADHD participants, whereas non-ADHD counterparts showed significant improvements. Third, all domains of cognitive functions in individuals without ADHD were able to tolerate 10 soccer headings. Fourth, plasma GFAP and UCH-L1 levels were acutely elevated after soccer headings in participants with ADHD only. Plasma Tau did not change after 10 soccer headings regardless of ADHD status. Fifth, acute elevations of GFAP after headings were correlated to acute verbal memory declines in the ADHD group. These data suggest that there may be a connection between ADHD and reduced neurologic resiliency to subconcussive head impacts, especially in memory functions, astrocyte activation through GFAP elevations, and neuronal enzymatic alteration through UCH-L1 elevations.

ADHD-Specific Transient Memory Decline After Acute Subconcussive Head Impacts

Our findings are translatable to naturalistic field environment, where adult soccer players head the ball an average of 6 to 12 times per game and up to 30 times during practice (Spiotta et al., 2012). Furthermore, American football players can experience on average 7 to 10 head impacts (29–32 g per impact) during practice (Duma et al., 2005; Kawata, Rubin, et al., 2016; Reynolds et al., 2015), which are similar to our intervention consisting of 10 headers with 31 g per header. Participants without ADHD revealed minimal cognitive effects after completing 10 headings amounting to approximately 300 g and 30 krad/s². In fact, various studies indicate that soccer headings and football tackles from a single season do not necessarily contribute to a decline in overall cognitive function (Broglio et al., 2018; Kaminski et al., 2007; Kontos et al., 2011). The subconcussive effect, however, begins to accumulate with chronicity. For example, professional soccer players exhibit a significant impairment in memory, planning, and visual processing compared with a control group consisting of elite noncontact sport athletes that is correlated with the cumulative frequency of soccer heading (Matser et al., 1998).

Only one study to date has examined the concussion effects on cognitive functioning in individuals with ADHD. Iaccarino et al. (2018) reported that athletes with concussion who also had ADHD diagnosis showed significant impairments in executive functioning (e.g., inhibition, working memory, plan/organization) as compared to concussed athletes without ADHD. However, in the same study, the authors were unable to differentiate two concussed groups with and without ADHD using ImPACT. This is partly due to the insensitivity nature of ImPACT to discern previous concussion effects, owing to their loose inclusion criterion (concussion occurred in the past 10 years). On the contrary, our study using tight inclusion criteria and a precise timeline shed new light on the interaction between ADHD and subconcussive head impacts. When the ADHD participants experienced 10 headings, their verbal memory function was transiently impaired (7.9% at 0 hour post and 9.2% at 2 hours post) but 24 hours of rest was sufficient to restore baseline function. For visual memory, while non-ADHD groups showed significant improvement (7–15% increase at 24 hours post), 10 soccer headings impaired a learning effect among the ADHD participants (4% decline at 24 hours post). To further strengthen this relationship, we conducted a pilot study where we recruited individuals with ADHD to perform the kicking intervention. This ADHD-kicking group served as a control group for our ADHD-heading group. Our data indicate that individuals with ADHD can improve verbal and visual memory functions over time if they are free of head trauma (Supplemental Figure 1). This eliminates the possibility that the blunted memory functions simply attribute to ADHD diagnosis alone (e.g., lack of attention and motivation to the repeated cognitive testing). These data reinforce our finding that the memory impairment observed in the ADHD-heading group was due to the interactive effects between ADHD and subconcussive head impacts.

Association Between Verbal Memory Decline and Plasma GFAP Elevation in the ADHD Population

Our findings indicate that after experiencing just 10 soccer headings, acute astrocytic activation is present in the ADHD population, as illustrated by elevations in plasma GFAP levels. Furthermore, ADHD-specific increase in GFAP was related to the degree of verbal memory decline at 2 hours-post heading. A number of groups synchronously advocate for the use of GFAP in differentiating the severity of brain damage. For instance, Bazarian et al. (2018) determined the use of acute serum GFAP concentrations for identifying intracranial bleeding detected by head CT scan, with a reported sensitivity of 0.976 in 1,959 adult patients with mild to moderate traumatic brain injury. This result was successfully corroborated in concussion patients (Metting et al., 2012). In a large prospective cohort study of 712 patients, Papa et al. (2019) demonstrated lower GFAP levels in patients with subconcussive injury than seen in the patients with concussion. The authors were able to identify small, but statistically significant, increases in GFAP levels in patients with subconcussive injury as compared to ones with body trauma.

However, there is virtually no research documenting the multimodal relationship between GFAP levels and cognitive function after brain trauma, nor the ADHD contribution to such a relationship. Kashon et al. (2004) recruited 204 elderly patients with dementia and longitudinally tracked their cognitive function, and GFAP expressions in brain tissue were assessed after deceased. The authors found that GFAP levels in the occipital, parietal, and temporal lobes, were negatively correlated with the patients’ overall cognitive functions. Using a mouse model, Wilhelmsson et al. (2019) showed a new mechanistic link between GFAP and memory function, by demonstrating a pronounced memory deficit in GFAP and vimentin (both intermediate filament protein of astrocyte) double-knockout mice, as compared to wildtype mice. Neither our data nor available literature can address why plasma GFAP and verbal memory decline were linked only in the ADHD population. Therefore, future studies focusing on the neuropathology and structural integrity of the ADHD population are needed to link cellular and functional responses to subconcussive head impacts.

Subconcussive Head Impact Effects on Brain-Derived Blood Biomarkers

As with acute American football subconcussive head impacts (Kawata et al., 2018), 10 soccer headings did not induce changes in plasma Tau levels. Despite sharing the same cellular origin, NF-L levels were significantly elevated after headings in the non-ADHD population, which is similar to the previous soccer studies (Wallace et al., 2018; Wirsching et al., 2019). The ADHD counterparts, however, did not show changes in NF-L levels, although research underpins ADHD-specific delayed myelination processes up to 5 years in the prefrontal neuronal network (Shaw et al., 2006). This premature neuronal development has been postulated to contribute to individuals with ADHD having heightened risk for concussion and development of severe concussion symptoms. The perplexing results in NF-L require further investigation. Conversely, GFAP and UCH-L1 reflected ADHD’s unique response to subconcussive head impacts.

The current consensus is that GFAP and UCH-L1 are useful for more severe forms of brain injury (e.g., concussion, moderate-severe TBI) than subconcussive head impacts, although one recent report suggests small increases in GFAP due to subconcussion (Papa et al., 2019). In longitudinal time-course studies, concussion induced gradual increase in GFAP up to 4-fold and peaked at 20 hours-post concussion, whereas UCH-L1 was a fast-acting biomarker with the highest expression level being observed immediately after concussion and declined thereafter (Papa et al., 2016, 2019). The non-ADHD-heading group in our study showed no change in GFAP and UCH-L1, indicating that 10 soccer headings are below the threshold to induce astrocyte activation and neuronal injury. However, the ADHD-heading group showed 25% increase in GFAP at 2 hours-post heading and 29% increase in UCH-L1 at 24 hours-post heading. These results collectively highlight the subtle, but detectable levels of ADHD-specific hyper-sensitivity to acute subconcussive head impacts.

ADHD-Related Elevated Baseline Symptoms

None of the three groups showed an increase in symptom levels after heading or kicking, assuring that the 10 headings were in fact “subconcussive” head impacts. However, the participants with ADHD reported substantially higher symptoms at baseline than non-ADHD counterparts, which agrees with the preexisting literature (Elbin et al., 2013), despite controlling for administration of ADHD medication. Collectively, our investigation brought forward that ADHD regularly elevates symptoms in athletes without head trauma and is associated with reduced cognitive resiliency to subconcussive head impacts as displayed in the verbal and visual memory deficits, even in individuals taking ADHD medication. These ideas pose a question to 2 systematic reviews concluding that athletes with ADHD are at increased risk for sustaining a concussion (Adeyemo et al., 2014; Poysophon & Rao, 2018). Since many athletes in contact sports frequently incur subconcussive head impacts prior to concussion (Beckwith et al., 2013), these head impacts may decrease the cognitive resiliency of athletes with ADHD to a concussive blow. Thus, athletes with ADHD may become more likely to sustain later concussions. Moreover, elevated baseline psychiatric symptoms in athletes with ADHD may contaminate commonly used concussion symptom scales and may produce a false-positive diagnosis of concussion, since clinicians still rely heavily on symptom reporting to diagnose a concussion (McCrory et al., 2017).

Clinical Implications

It is important to emphasize that exercise and physical activity have tremendous positive effects on cognitive, cardiovascular, and behavioral health in individuals with ADHD (Den Heijer et al., 2017; Halperin & Healey, 2011), and soccer is an excellent platform to provide such benefits. A recent study suggests that participating in soccer is associated with increased axonal microstructural integrity and better performance on attention, processing speed, and memory compared to non-athletes. However, these beneficial effects were absent in soccer players who incurred high exposure to soccer headings (Strauss et al., 2020). Our data provide an additional layer to the current knowledge that if soccer players with ADHD sustain high exposure, there is a potential to observe an amplified negative response compared to soccer players without ADHD. Growing awareness and evolution of rule changes to minimize soccer headings has improved the safety of soccer participation. One line of research indicates that on average, soccer players do not show cognitive declines after a soccer season (Guskiewicz et al., 2002; Kontos et al., 2011; Rodrigues et al., 2019), but these evidence are possibly confounded due to players’ learning effects by taking the cognitive testing multiple times. Nonetheless, our data provide an important initial step to establish an ADHD patient-specific guideline to participate in contact-prone sports.

Pending confirmation in larger-scale field studies, these results may have important implications for the clinical management of athletes with ADHD participating in contact sports. If athletes with ADHD are indeed more susceptible to the adverse effects of subconcussive head impacts, strategies to minimize these effects would be a logical next step. One option would be to limit head impact exposures during the course of a single sporting contest while periodically monitoring players’ cognitive functions.

Limitations

There are several limitations to this study. First, due to our study design monitoring the participants up to 24 hours, we were unable to determine how long the impairment in visual memory lasted. Second, our controlled framework of 10 soccer headings in 10 minutes has limited ecological validity, given that soccer players typically do not perform headings within 1-minute intervals during a game, which limits generalizability of our findings. Third, cognitive changes we observed in the ADHD-heading group were below the threshold of reliable changes of ImPACT composite score (>9 for verbal memory; >14 for visual memory) (Iverson et al., 2003). These cut-off points are important when clinicians face an individual patient to aid their diagnosis. Instead of individual evaluation, our approach was to statistically compare group means after controlled heading intervention. Therefore, our study is not to make any diagnostic claim of concussive or subconcussive injury after 10 soccer headings. Fourth, the sample size was limited to 17 per group, yet this sample size tested in a repeated-measures design provides sufficient statistical power with large effect sizes for verbal (d = 0.983 at 2 hours-post) and visual (d = 0.970 at 24 hours-post) memory functions between the ADHD-heading and non-ADHD-heading groups. Lastly, we encourage a follow-up longitudinal field study tracking the association of ADHD athletes’ exposure to head impact with neurologic outcomes.

Conclusion

The data from the current study provide initial evidence that ADHD may potentially reduce brain resiliency to repetitive soccer headings in a short interval, which can trigger transient impairment in verbal and visual memory functions. ADHD might also have heightened cellular response to soccer headings as reflected in increased plasma levels of GFAP and UCH-L1. Furthermore, in participants with ADHD, GFAP levels in acute time frame were reflective of their verbal memory function. Conversely, individuals without ADHD were resilient to 10 acute headings. Although these data have some implications for clinical practice, a larger-scale longitudinal study is needed to confirm our findings and advance our knowledge regarding the response of ADHD to subconcussive head impacts.

Supplemental Material

Supplemental_Material – Supplemental material for ADHD May Associate With Reduced Tolerance to Acute Subconcussive Head Impacts: A Pilot Case-Control Intervention Study

Supplemental material, Supplemental_Material for ADHD May Associate With Reduced Tolerance to Acute Subconcussive Head Impacts: A Pilot Case-Control Intervention Study by Madeleine K. Nowak, Keisuke Ejima, Patrick D. Quinn, Jeffrey J. Bazarian, Timothy D. Mickleborough, Jaroslaw Harezlak, Sharlene D. Newman and Keisuke Kawata in Journal of Attention Disorders

Footnotes

Acknowledgements

The authors would like to thank Ms. Rachel Kalbfell, Ms. Alekhya Koppineni, Mr. Joseph Kim, and Mr. Aditya Belamkar for their assistance in data collection. The authors would also like to thank Ms. Jennifer Holmes, ELS., for medical language editing.

Authors’ Note

Sharlene D. Newman is also affiliated with Alabama Life Research Institute, University of Alabama-Tuscaloosa, USA

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported from a Spinal Cord & Brain Injury Research Fund from the Indiana State Department of Health (to K Kawata: ISCBIRF 0019939) and the National Institute of Neurological Disorders and Stroke (to K Kawata and S Newman: 1R21NS116548). P. Quinn is supported by the National Institute on Drug Abuse of the National Institutes of Health under Award Number R00DA040727.

ORCID iD

Keisuke Kawata

Supplemental Material

Supplemental material for this article is available online.

Author Biographies

Madeleine K. Nowak, BS, is a PhD candidate at the Indiana University School of Public Health where she studies exercise physiology and neuroscience. Her research interests include the investigation of mental disorders as significant influencers for subconcussive brain injury.

Keisuke Ejima, PhD, is an assistant research scientist of Biostatistics and Epidemiology at the Indiana University School of Public Health. His research focuses on the development of mathematical model and statistical methodology and their application in public health domain.

Patrick D. Quinn, PhD, is an assistant professor of Applied Health Sciences at the Indiana University School of Public Health. He is licensed psychologist with training and experience in clinical application of evidence-based practices for ADHD. His research uses epidemiologic and behavioral genetic methods to understand public health problems related to the use and misuse of psychoactive drugs.

Jeffrey J. Bazarian, MD, MPH, is an emergency physician and a professor of Emergency Medicine and Neurology at the University of Rochester. His research incorporates blood biomarkers, neuroimaging, and cognitive and behavioral measures to inspect neurological sequalae in athletes and military service members. His research aims to understand the pathophysiologic mechanisms of neurodegeneration associated with repetitive head hits.

Timothy D. Mickleborough, PhD, is a professor of Exercise Physiology at the Indiana University School of Public Health. His main research focus is integrative human exercise physiology, with additional training in cardiopulmonary physiology and biochemistry.

Jaroslaw Harezlak, PhD, is a professor of Epidemiology and Biostatistics at the Indiana University School of Public Health. His research interests incorporate statistics, medicine, and epidemiology. His applied research includes structural and functional brain imaging, accelerometry and intensively collected longitudinal studies.

Sharlene D. Newman, PhD, is a professor of Psychology and director of Alabama Life Research Institute at University of Alabama. Her research focuses on understanding human neurocognitive functioning with the use of MRI.

Keisuke Kawata, PhD, is an assistant professor of Clinical Neuroscience at Indiana University School of Public Health. His clinical and research interests incorporate blood biomarkers, sensorimotor testing, head impact kinematics, and cognitive and behavioral measures to inspect the consequence of subconcussion brain injury. His research aims to establish brain injury specific objective markers.

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