Anne C. Ritter

IL‐1β associations with posttraumatic epilepsy development: A genetics and biomarker cohort study

Posttraumatic epilepsy (PTE) is a significant complication following traumatic brain injury (TBI), yet the role of genetic variation in modulating PTE onset is unclear. We hypothesized that TBI‐induced inflammation likely contributes to seizure development. We assessed whether genetic variation in the interleukin‐1beta (IL‐1β) gene, IL‐1β levels in cerebrospinal fluid (CSF) and serum, and CSF/serum IL‐1β ratios would predict PTE development post‐TBI.

Genetic variation in the adenosine regulatory cycle is associated with posttraumatic epilepsy development

Determine if genetic variation in enzymes/transporters influencing extracellular adenosine homeostasis, including adenosine kinase (ADK), [ecto‐5′‐nucleotidase (NT5E), cluster of differentiation 73 (CD73)], and equilibrative nucleoside transporter type‐1 (ENT‐1), is significantly associated with epileptogenesis and posttraumatic epilepsy (PTE) risk, as indicated by time to first seizure analyses.

Incidence and risk factors of posttraumatic seizures following traumatic brain injury: A Traumatic Brain Injury Model Systems Study

Determine incidence of posttraumatic seizure (PTS) following traumatic brain injury (TBI) among individuals with moderate‐to‐severe TBI requiring rehabilitation and surviving at least 5 years.

Genetic variation in neuronal glutamate transport genes and associations with posttraumatic seizure

Posttraumatic seizures (PTS) commonly occur following severe traumatic brain injury (sTBI). Risk factors for PTS have been identified, but variability in who develops PTS remains. Excitotoxicity may influence epileptogenesis following sTBI. Glutamate transporters manage glutamate levels and excitatory neurotransmission, and they have been associated with both epilepsy and TBI. Therefore, we aimed to determine if genetic variation in neuronal glutamate transporter genes is associated with accelerated epileptogenesis and increased PTS risk after sTBI.

Brain venular pattern by 7T MRI correlates with memory and haemoglobin in sickle cell anaemia

Sickle cell anaemia (SCA) is a hereditary hemoglobinopathy characterised by extensive vascular dysfunction that stems from inflammation, thrombosis and occlusion of post-capillary venules. Cognitive impairment is a neurological complication of SCA whose pathogenesis is unknown. We hypothesised that cerebral venular abnormalities are linked to cognitive impairment in SCA. Thus, we employed 7T magnetic resonance imaging (MRI) to examine the association between venular density and cognitive function in homozygous SCA. We quantified the density of total, long, and short venules in pre-defined regions of interest between the frontal and occipital cornu on each hemisphere. Cognitive function was assessed using the Hopkins Verbal Learning Test - Revised (HVLT-R) test of learning and memory. Patients (n=11) were compared with race, age and gender-equated controls (n=7). Compared to controls, patients had an overall venular rarefaction, with significantly lower density of long venules and greater density of short venules which was inversely related to HVLT-R performance and haemoglobin. To our knowledge, this is the first 7T MRI study in SCA and first report of associations between cerebral venular patterns and cognitive performance and haemoglobin. Future studies should examine whether these novel neuroimaging markers predict cognitive impairment longitudinally and are mechanistically linked to severity of anaemia.

Genetic Variation in the Vesicular Monoamine Transporter: Preliminary Associations With Cognitive Outcomes After Severe Traumatic Brain Injury.

Introduction: Traumatic brain injury (TBI) frequently results in impaired cognition, a function that can be modulated by monoaminergic signaling. Genetic variation among monoaminergic genes may affect post-TBI cognitive performance. The vesicular monoamine transporter-2 (VMAT2) gene may be a novel source of genetic variation important for cognitive outcomes post-TBI given VMAT2s role in monoaminergic neurotransmission. Objective: To evaluate associations between VMAT2 variability and cognitive outcomes post-TBI. Methods: We evaluated 136 white adults with severe TBI for variation in VMAT2 using a tagging single nucleotide polymorphism (tSNP) approach (rs363223, rs363226, rs363251, and rs363341). We show genetic variation interacts with assessed cognitive impairment (cognitive composite [Comp-Cog] T-scores) to influence functional cognition (functional independence measure cognitive [FIM-Cog] subscale] 6 and 12 months postinjury. Results: Multivariate analyses at 6 months postinjury showed rs363226 genotype was associated with Comp-Cog (P = .040) and interacted with Comp-Cog to influence functional cognition (P < .001). G-homozygotes had the largest cognitive impairment, and their cognitive impairment had the greatest adverse effect on functional cognition. Discussion: We provide the first evidence that genetic variation within VMAT2 is associated with cognitive outcomes after TBI. Further work is needed to validate this finding and elucidate mechanisms by which genetic variation affects monoaminergic signaling, mediating differences in cognitive outcomes.

Prognostic models for predicting posttraumatic seizures during acute hospitalization, and at 1 and 2 years following traumatic brain injury.

Posttraumatic seizures (PTS) are well‐recognized acute and chronic complications of traumatic brain injury (TBI). Risk factors have been identified, but considerable variability in who develops PTS remains. Existing PTS prognostic models are not widely adopted for clinical use and do not reflect current trends in injury, diagnosis, or care. We aimed to develop and internally validate preliminary prognostic regression models to predict PTS during acute care hospitalization, and at year 1 and year 2 postinjury.

In response to comments on IL-1β associations with posttraumatic epilepsy development: a genetics and biomarker cohort study.

To the Editors: We have read with great interest the recent article in Epilepsia from Diamond et al. Although the role of interleukin (IL)-1b in epileptogenesis is a topic of importance, the article fails to address several key issues. First, although the authors mention the importance of the blood–brain barrier (BBB) and the potential role of type II IL-1 transporters in moving IL-1b across the endothelial barrier, they fail to investigate any markers of BBB integrity in their study. A simple analysis of the cerebrospinal fluid (CSF)/serum albumin ratio may have clarified the role of BBB dysfunction versus intrinsic central nervous system (CNS) IL-1b production in determining the CSF/serum IL-1b ratio. Furthermore, the authors primary variable of interest was time to first seizure, whereas seizure recurrence was not investigated. Although late posttraumatic seizures are an important risk factor for developing epilepsy, it is incorrect to assume these patients truly developed epilepsy without any data concerning further seizure activity over time. Although this study provides some evidence of a genetic component to risk of posttraumatic epilepsy (PTE), controversy remains over the functional difference of the rs1143634 single nucleotide polymorphism (SNP) and the unclear role of peripheral production of IL-1b and their role in epileptogenesis following traumatic brain injury (TBI). It is important to realize that a much more nuanced understanding of the role of IL-1b and its genetic variants in PTE is necessary before any firm conclusions regarding genetic susceptibility to PTE can be made.

Post-traumatic epilepsy associations with mental health outcomes in the first two years after moderate to severe TBI: A TBI Model Systems analysis

PURPOSE Research suggests that there are reciprocal relationships between mental health (MH) disorders and epilepsy risk. However, MH relationships to post-traumatic epilepsy (PTE) have not been explored. Thus, the objective of this study was to assess associations between PTE and frequency of depression and/or anxiety in a cohort of individuals with moderate-to-severe TBI who received acute inpatient rehabilitation. METHODS Multivariate regression models were developed using a recent (2010-2012) cohort (n=867 unique participants) from the TBI Model Systems (TBIMS) National Database, a time frame during which self-reported seizures, depression [Patient Health Questionnaire (PHQ)-9], and anxiety [Generalized Anxiety Disorder (GAD-7)] follow-up measures were concurrently collected at year-1 and year-2 after injury. RESULTS PTE did not significantly contribute to depression status in either the year-1 or year-2 cohort, nor did it contribute significantly to anxiety status in the year-1 cohort, after controlling for other known depression and anxiety predictors. However, those with PTE in year-2 had 3.34 times the odds (p=.002) of having clinically significant anxiety, even after accounting for other relevant predictors. In this model, participants who self-identified as Black were also more likely to report clinical symptoms of anxiety than those who identified as White. PTE was the only significant predictor of comorbid depression and anxiety at year-2 (Odds Ratio 2.71; p=0.049). CONCLUSIONS Our data suggest that PTE is associated with MH outcomes 2years after TBI, findings whose significance may reflect reciprocal, biological, psychological, and/or experiential factors contributing to and resulting from both PTE and MH status post-TBI. Future work should consider temporal and reciprocal relationships between PTE and MH as well as if/how treatment of each condition influences biosusceptibility to the other condition.

Probabilistic matching approach to link deidentified data from a trauma registry and a Traumatic Brain Injury Model System center

Objective There is no civilian traumatic brain injury database that captures patients in all settings of the care continuum. The linkage of such databases would yield valuable insight into possible care interventions. Thus, the objective of this article is to describe the creation of an algorithm used to link the Traumatic Brain Injury Model System (TBIMS) to trauma data in state and national trauma databases. Design The TBIMS data from a single center was randomly divided into two sets. One subset was used to generate a probabilistic linking algorithm to link the TBIMS data to the centers trauma registry. The other subset was used to validate the algorithm. Medical record numbers were obtained and used as unique identifiers to measure the quality of the linkage. Novel methods were used to maximize the positive predictive value. Results The algorithm generation subset had 121 patients. It had a sensitivity of 88% and a positive predictive value of 99%. The validation subset consisted of 120 patients and had a sensitivity of 83% and a positive predictive value of 99%. Conclusions The probabilistic linkage algorithm can accurately link TBIMS data across systems of trauma care. Future studies can use this database to answer meaningful research questions regarding the long-term impact of the acute trauma complex on health care utilization and recovery across the care continuum in traumatic brain injury populations.