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A Brain-Heart Biomarker for Epileptogenesis

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A Brain-Heart Biomarker for Epileptogenesis This Accepted Manuscript has not been copyedited and formatted. The final version may differ from this version. Research Articles: Neurobiology of Disease A Brain-Heart Biomarker for Epileptogenesis Fatemeh Bahari1,2, Paddy Ssentongo1,2, Steven J. Schiff1,2,3,5,6 and Bruce J. Gluckman1,2,3,4 1Center for Neural Engineering, Pennsylvania State University, University Park, PA 16802, USA. 2Department of Engineering Science and Mechanics, Pennsylvania State University, University Park, PA 16802, USA. 3Department of Neurosurgery, Pennsylvania State College of Medicine, Hershey, PA 16802, USA. 4Department of Bioengineering, Pennsylvania State University, University Park, PA 16802, USA. 5Department of Physics, Pennsylvania State University, University Park, PA 16802, USA. 6Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA 16802, USA. DOI: 10.1523/JNEUROSCI.1130-18.2018 Received: 1 May 2018 Revised: 17 July 2018 Accepted: 8 August 2018 Published: 27 August 2018 Author contributions: F.B., S.J.S., and B.J.G. designed research; F.B. and P.S. performed research; F.B. and B.J.G. analyzed data; F.B. wrote the first draft of the paper; F.B., S.J.S., and B.J.G. edited the paper; F.B. and B.J.G. wrote the paper. Conflict of Interest: The authors declare no competing financial interests. We thank Ali Nabi, Balaji Shanmugasundaram, and Myles W. Billard for assistance in development of the acquisition electronics and recording electrodes. This work was supported by Pennsylvania State Institute for the Neuroscience from Pennsylvania Department of Health Tobacco Funds, a Multidisciplinary grant from Citizens United for Research in Epilepsy (CURE), National Institute of Health grant R01EB019804, and a doctoral Academic Computing Fellowship from Pennsylvania State University to F.B. Corresponding authors email addresses: Fatemeh Bahari, [email protected], Bruce J. Gluckman, [email protected] Cite as: J. Neurosci ; 10.1523/JNEUROSCI.1130-18.2018 Alerts: Sign up at www.jneurosci.org/cgi/alerts to receive customized email alerts when the fully formatted version of this article is published. Accepted manuscripts are peer-reviewed but have not been through the copyediting, formatting, or proofreading process. Copyright © 2018 the authors 1 A Brain-Heart Biomarker for Epileptogenesis 2 3 Abbreviated title: Delayed brain-heart coincidences predict epilepsy 4 Authors: Fatemeh Bahari1,2*, Paddy Ssentongo1,2, Steven J. Schiff1,2,3,5,6, Bruce J. 5 Gluckman1,2,3,4* 6 Affiliations: 7 1Center for Neural Engineering, Pennsylvania State University, University Park, PA 16802, 8 USA. 9 2Department of Engineering Science and Mechanics, Pennsylvania State University, University 10 Park, PA 16802, USA. 11 3Department of Neurosurgery, Pennsylvania State College of Medicine, Hershey, PA 16802, 12 USA. 13 4Department of Bioengineering, Pennsylvania State University, University Park, PA 16802, 14 USA. 15 5Department of Physics, Pennsylvania State University, University Park, PA 16802, USA. 16 6Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA 17 16802, USA. 18 *Corresponding authors email addresses: Fatemeh Bahari, [email protected], Bruce J. Gluckman, 19 [email protected] 20 21 Number of figures and tables: 7 22 Number of words for Abstract, Introduction, and Discussion: [159, 435, 1327] 23 Financial interests or conflicts of interest: Fatemeh Bahari, Bruce J. Gluckman and Steven J. 24 Schiff are co-inventors on a U.S. provisional patent Ser. No. 62/663,213 25 Acknowledgements: 26 We thank Ali Nabi, Balaji Shanmugasundaram, and Myles W. Billard for assistance in 27 development of the acquisition electronics and recording electrodes. This work was supported by 28 Pennsylvania State Institute for the Neuroscience from Pennsylvania Department of Health 29 Tobacco Funds, a Multidisciplinary grant from Citizens United for Research in Epilepsy 30 (CURE), National Institute of Health grant R01EB019804, and a doctoral Academic Computing 31 Fellowship from Pennsylvania State University to F.B. 32 Author contributions: 33 F.B., B.J.G, S.J.S designed the research; P.S. performed surgeries and animal care; F.B. and 34 B.J.G. analyzed data; F.B., B.J.G., and S.J.S. wrote the manuscript. 35 Abstract 36 Post-injury epilepsy is an unpreventable sequela in as many as 20% of patients with brain insults. 37 For these cases biomarkers of epileptogenesis are critical to facilitate identification of patients at 38 high-risk of developing epilepsy and to introduce effective anti-epileptogenic interventions. 39 Here, we demonstrate that delayed brain-heart coincidences serve as a reliable biomarker. In a 40 murine model of post-infection acquired epilepsy, we utilized long-term simultaneous 41 measurements of the brain activity via electroencephalography (EEG) and autonomic cardiac 42 activity via electrocardiography (ECG) to quantitatively track brain-heart interactions during 43 epileptogenesis. We find that abnormal cortical discharges precede abnormal fluctuations in the 44 cardiac rhythm at the resolution of single beat-to-beat intervals. The delayed brain-heart 45 coincidence is detectable as early as the onset of chronic measurements – 2 to 14 weeks prior to 46 the first seizure – only in animals that become epileptic, and increases during epileptogenesis. 47 Therefore, delayed brain-heart coincidence serves as a biomarker of epileptogenesis and could be 48 used for phenotyping, diagnostic, and therapeutic purposes. 49 Keywords: Epilepsy, Epileptogenesis, Brain-Heart coincidence, Acquired epilepsy 50 51 1 52 Significance Statement: 53 No biomarker that readily predicts and tracks epileptogenesis currently exists for the wide range 54 of human acquired epilepsies. Here, we utilized long-term measurements of brain and heart 55 activity in a mouse model of post-infection acquired epilepsy to investigate the potential of 56 brain-heart interaction as a biomarker of epileptogenesis. We found that delayed coincidences 57 from brain to heart can clearly separate the mice that became epileptic from those that did not 58 weeks before development of epilepsy. Our findings allow for phenotyping and tracking of 59 epileptogenesis in this and likely other models of acquired epilepsy. Such capability is critical for 60 efficient adjunctive treatment development and for tracking the efficacy of such treatments. 61 62 2 63 Introduction 64 No biomarker that readily predicts and tracks epileptogenesis (Gowers, 1881) currently exists for 65 the wide range of human acquired epilepsies – developed after brain insults such as traumatic 66 brain injuries, stroke, and infections (Engel et al., 2013; Pitkänen et al., 2016a, 2016b). These 67 biomarkers are critical to identify patients at risk of epilepsy, introduce early and effective 68 interventions to prevent establishment of epilepsy, and evaluate therapeutic efficacy of such 69 treatments. 70 Many investigators have focused on chronic cardiac alterations and autonomic dysfunction as 71 biomarkers for epileptogenesis (Kheiri et al., 2012) as well as features for seizure prediction 72 (Massé et al., 2013; Kolsal et al., 2014; Moridani and Farhadi, 2017; Pavei et al., 2017) with 73 limited success. However, the underlying coupled brain-heart dynamics and the alterations in 74 those dynamics during epileptogenesis are not fully investigated. 75 According to the lockstep phenomenon (LSP) (Lathers et al., 1987), epileptiform discharges can 76 induce intermittent synchronized cardiac sympathetic and vagal neural discharges. LSP is 77 therefore a representation of seizure-induced deficits in the brain circuitry of the cardiovascular 78 system (Goodman et al., 2008) that may alter, although not fully impair, the system’s function. 79 We hypothesized that these events are the extreme end of smaller, potentially abnormal, 80 fluctuations in brain activity that are likely to subtly modify cardiac function long before the 81 microscale instability propagates and results into an overwhelming seizure (Bragin et al., 2000; 82 Schevon et al., 2008; Stead et al., 2010). Our aim was therefore to investigate the frequency and 83 strength of the signals from brain affecting heart as a function of progression of epileptogenesis. 84 Once detected and quantified the coupled brain-heart dynamic could potentially serve as a 85 prognostic and diagnostic biomarker of epileptogenesis. 3 86 Previously, we developed a murine model of post-cerebral malaria epilepsy that duplicates 87 elements of the human post-infection acquired epilepsy. As with the human condition, the animal 88 model presents with long and highly variable epileptogenesis periods (Ssentongo et al., 2017) 89 thus provides a platform to investigate the potential of brain-heart interaction as a relevant 90 biomarker for epileptogenesis. 91 Here, we continuously track brain-heart dynamics during epileptogenesis. To achieve this, we 92 developed a new metric of cardiac rhythmicity whose statistics are independent of behavior and 93 state of vigilance (SOV). We report that in animals that survive the malarial infection and 94 become epileptic, extrema of the cardiac metric are preceded by potentially abnormal 95 fluctuations in brain activity. The causal transmission of activity along the brain-heart axis starts 96 early and progresses during epileptogenesis. These findings can thus be utilized to identify 97 potential patients at risk of developing epilepsy, track the progression of epileptogenesis as well 98 as anti-epileptogenic treatments,
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