. Association Between Childhood-Onset Epilepsy and Amyloid Burden 5 Decades Later. JAMA Neurol. 2017 May 1;74(5):583-590. PubMed.

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  1. This study focuses on the blurry borderland of epilepsy and brain amyloid deposition that emerged even before Alzheimer’s description of Auguste D. (Alzheimer 1907), since the plaques he described with great clarity in 1907 had been first noted by Blocq and Marinesco in so-called “essential epilepsy” patients over a decade earlier (Buda et al., 2009). Over the years, little significance was attached to the coincidence of seizures and amyloid plaques in human cases or mouse models of AD until the arrival of compelling epidemiological (Scarmeas et al., 2009) and experimental evidence (Palop et al., 2007). Now, a century later, Joutsa and colleagues logically ask whether a 50-year history of “uncomplicated” epilepsy actually favors amyloid plaque formation. The authors assembled a cohort of individuals with early onset idiopathic and cryptogenic epilepsy to image the distribution of PiB-positive amyloid plaques and compare the patterns to age-matched, neurologically unaffected controls. Their hypothesis was that individuals with long-standing epilepsy and positive APOE4 status would be more likely to show an elevated plaque burden. The hypothesis is important, but unfortunately, the study design and data set are insufficient for a clinically meaningful answer, and indeed, there may be no single answer.

    The authors themselves point out four critical limitations of their pilot study. The first is the small size of the cohort, and its clinical heterogeneity. The lack of a group representing a single etiology of epilepsy is a major confound, since within the category of idiopathic and cryptogenic epilepsy there are many monogenic pathways leading to vastly different intrinsic seizure networks and patterns of Aβ protein release and metabolism in different brain regions, as well as distinct molecular reasons for amyloid plaques to locally accumulate, and the authors found this heterogeneity in their imaging results. The second issue is epilepsy severity. The seizure history is undocumented in each of these individuals. They are described as uncomplicated cases, many in remission, and the types of seizures they presented with, their location in the brain, and their severity are not included in the analysis. A third issue is timing. Imaging was performed at only a single time point, thus the chronological age and plaque accumulation rate is not known. Both seizures and rate of plaque deposition are determined by complex cellular and synaptic interactions during aging, and both vary in the young and older brain. Finally, the time point chosen for determination of amyloid plaque load was made at a mean age that precedes most late-onset dementia, and there was a selection bias against cases with substantial cognitive impairment.

    Whether a history of abnormal synaptic activity drives the accumulation of amyloid plaques, when and where it begins, and how this process contributes to the progression of dementia remain fundamental relationships to explore. A few insights from the laboratory illustrate the complicated road ahead. Single experimentally induced seizures in mice release soluble Aβ from synapses (Cirrito et al., 2005), but this may not be sustained. In a monogenic mouse channelopathy model (Kv1.1 knockout) of early onset epilepsy, despite a history of intense early seizure activity, there is no elevation of Aβ aggregates in the first month of life (Holth et al., 2013). In a transgenic model of Aβ overexpression on a seizure-prone versus seizure-resistant genetic background, mice with the more severe seizure phenotype actually showed less Aβ accumulation (Jackson et al., 2015). For its part, overexpression of Aβ, which triggers epilepsy in most mouse models (Noebels et al., 2011), appears to do so more readily when expressed early rather than late in adulthood (Born et al., 2014). Finally, cortical hyperexcitability occurs at levels of Aβ below, and earlier than, those required for plaque deposition (Cummings et al., 2015), suggesting an earlier biomarker for cognitive impairment than simple plaque load. 

    References:

    . Über eine eigenartige Erkrankung der Hirnrinde. Allgemeine Zeitschrift fur Psychiatrie und Psychisch-gerichtliche Medizin. 1907 Jan;64:146-8.

    . Georges Marinesco and the early research in neuropathology. Neurology. 2009 Jan 6;72(1):88-91. PubMed.

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    . Aberrant excitatory neuronal activity and compensatory remodeling of inhibitory hippocampal circuits in mouse models of Alzheimer's disease. Neuron. 2007 Sep 6;55(5):697-711. PubMed.

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    . Tau loss attenuates neuronal network hyperexcitability in mouse and Drosophila genetic models of epilepsy. J Neurosci. 2013 Jan 23;33(4):1651-9. PubMed.

    . DBA/2J genetic background exacerbates spontaneous lethal seizures but lessens amyloid deposition in a mouse model of Alzheimer's disease. PLoS One. 2015;10(5):e0125897. Epub 2015 May 1 PubMed.

    . A perfect storm: Converging paths of epilepsy and Alzheimer's dementia intersect in the hippocampal formation. Epilepsia. 2011 Jan;52 Suppl 1:39-46. PubMed.

    . Genetic suppression of transgenic APP rescues Hypersynchronous network activity in a mouse model of Alzeimer's disease. J Neurosci. 2014 Mar 12;34(11):3826-40. PubMed.

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    View all comments by Jeffrey L. Noebels
  2. As recently reviewed in some depth (Palop and Mucke, 2016) and prospectively demonstrated in the clinic (Vossel et al., 2016), there clearly is an important link between Alzheimer’s disease and epilepsy, which may involve a vicious cycle between aberrant neural network activity and the accumulation of pathogenic proteins in brain. The interesting findings reported by Joutsa et al. provide additional support for this hypothesis. At least in my opinion, the results of this study also indirectly support the idea that the effective suppression of network hypersynchrony could have symptomatic as well as disease-modifying therapeutic benefits in people with AD or at high risk of developing the disease (Bakker et al., 2012; Sanchez et al., 2012; Palop and Mucke, 2016). Although many epilepsy patients included in the study by Joutsa et al. had not received any antiepileptic drugs for a long time before they received the PiB PET scan, it is worth noting that most of them appear to have never been treated with levetiracetam, an antiepileptic that had beneficial effects in AD-related mouse models (Sanchez et al., 2012) and in patients with amnestic mild cognitive impairment (Bakker et al., 2012; Bakker et al., 2015). Instead, many patients in this cohort received antiepileptic drugs that strongly block voltage-gated sodium channels and, thus, might be expected to promote rather than suppress AD-related network dysfunction (Verret et al., 2012; Palop and Mucke, 2016). 

    References:

    . Network abnormalities and interneuron dysfunction in Alzheimer disease. Nat Rev Neurosci. 2016 Dec;17(12):777-792. Epub 2016 Nov 10 PubMed.

    . Incidence and impact of subclinical epileptiform activity in Alzheimer's disease. Ann Neurol. 2016 Dec;80(6):858-870. Epub 2016 Nov 7 PubMed.

    . Reduction of hippocampal hyperactivity improves cognition in amnestic mild cognitive impairment. Neuron. 2012 May 10;74(3):467-74. PubMed.

    . Levetiracetam suppresses neuronal network dysfunction and reverses synaptic and cognitive deficits in an Alzheimer's disease model. Proc Natl Acad Sci U S A. 2012 Oct 16;109(42):E2895-903. PubMed.

    . Network abnormalities and interneuron dysfunction in Alzheimer disease. Nat Rev Neurosci. 2016 Dec;17(12):777-792. Epub 2016 Nov 10 PubMed.

    . Response of the medial temporal lobe network in amnestic mild cognitive impairment to therapeutic intervention assessed by fMRI and memory task performance. Neuroimage Clin. 2015;7:688-98. Epub 2015 Feb 21 PubMed.

    . Inhibitory interneuron deficit links altered network activity and cognitive dysfunction in Alzheimer model. Cell. 2012 Apr 27;149(3):708-21. PubMed.

    View all comments by Lennart Mucke

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