Ezequiel Gleichgerrcht, Erik Kaestner, Reihaneh Hassanzadeh, Rebecca W Roth, Alexandra Parashos, Kathryn A Davis, Anto Bagić, Simon S Keller, Theodor Rüber, Travis Stoub, Heath R Pardoe, Patricia Dugan, Daniel L Drane, Anees Abrol, Vince Calhoun, Ruben I Kuzniecky, Carrie R McDonald, Leonardo Bonilha
Despite decades of advancements in diagnostic MRI, 30-50% of temporal lobe epilepsy (TLE) patients remain categorized as “non-lesional” (i.e., MRI negative or MRI–) based on visual assessment by human experts. MRI– patients face diagnostic uncertainty and significant delays in treatment planning. Quantitative MRI studies have demonstrated that MRI– patients often exhibit a TLE-specific pattern of temporal and limbic atrophy that may be too subtle for the human eye to detect. This signature pattern could be successfully translated into clinical use via artificial intelligence (AI) advances in computer-aided MRI interpretation, thereby improving the detection of brain “lesional” patterns associated with TLE. Here, we tested this hypothesis by employing a three-dimensional convolutional neural network (3D CNN) applied to a dataset of 1,178 scans from 12 different centers. 3D CNN was able to differentiate TLE from healthy controls with high accuracy (85.9% ± 2.8), significantly outperforming support vector machines based on hippocampal (74.4% ± 2.6) and whole-brain (78.3% ± 3.3) volumes. Our analysis subsequently focused on a subset of patients who achieved sustained seizure freedom post-surgery as a gold standard for confirming TLE. Importantly, MRI– patients from this cohort were accurately identified as TLE 82.7% ± 0.9 of the time, an encouraging finding since clinically these were all patients considered to be MRI– (i.e., not radiographically different than controls). The saliency maps from the CNN revealed that limbic structures, particularly medial temporal, cingulate, and orbitofrontal areas, were most influential in classification, confirming the importance of the well-established TLE signature atrophy pattern for diagnosis. Indeed, the saliency maps were similar in MRI+ and MRI– TLE groups, suggesting that even when humans cannot distinguish more subtle levels of atrophy, these MRI– patients are on the same continuum common across all TLE patients. As such, AI can identify TLE lesional patterns and AI-aided diagnosis has the potential to greatly enhance the neuroimaging diagnosis of TLE and redefine the concept of “lesional” TLE.
{"title":"Redefining diagnostic lesional status in temporal lobe epilepsy with artificial intelligence","authors":"Ezequiel Gleichgerrcht, Erik Kaestner, Reihaneh Hassanzadeh, Rebecca W Roth, Alexandra Parashos, Kathryn A Davis, Anto Bagić, Simon S Keller, Theodor Rüber, Travis Stoub, Heath R Pardoe, Patricia Dugan, Daniel L Drane, Anees Abrol, Vince Calhoun, Ruben I Kuzniecky, Carrie R McDonald, Leonardo Bonilha","doi":"10.1093/brain/awaf020","DOIUrl":"https://doi.org/10.1093/brain/awaf020","url":null,"abstract":"Despite decades of advancements in diagnostic MRI, 30-50% of temporal lobe epilepsy (TLE) patients remain categorized as “non-lesional” (i.e., MRI negative or MRI–) based on visual assessment by human experts. MRI– patients face diagnostic uncertainty and significant delays in treatment planning. Quantitative MRI studies have demonstrated that MRI– patients often exhibit a TLE-specific pattern of temporal and limbic atrophy that may be too subtle for the human eye to detect. This signature pattern could be successfully translated into clinical use via artificial intelligence (AI) advances in computer-aided MRI interpretation, thereby improving the detection of brain “lesional” patterns associated with TLE. Here, we tested this hypothesis by employing a three-dimensional convolutional neural network (3D CNN) applied to a dataset of 1,178 scans from 12 different centers. 3D CNN was able to differentiate TLE from healthy controls with high accuracy (85.9% ± 2.8), significantly outperforming support vector machines based on hippocampal (74.4% ± 2.6) and whole-brain (78.3% ± 3.3) volumes. Our analysis subsequently focused on a subset of patients who achieved sustained seizure freedom post-surgery as a gold standard for confirming TLE. Importantly, MRI– patients from this cohort were accurately identified as TLE 82.7% ± 0.9 of the time, an encouraging finding since clinically these were all patients considered to be MRI– (i.e., not radiographically different than controls). The saliency maps from the CNN revealed that limbic structures, particularly medial temporal, cingulate, and orbitofrontal areas, were most influential in classification, confirming the importance of the well-established TLE signature atrophy pattern for diagnosis. Indeed, the saliency maps were similar in MRI+ and MRI– TLE groups, suggesting that even when humans cannot distinguish more subtle levels of atrophy, these MRI– patients are on the same continuum common across all TLE patients. As such, AI can identify TLE lesional patterns and AI-aided diagnosis has the potential to greatly enhance the neuroimaging diagnosis of TLE and redefine the concept of “lesional” TLE.","PeriodicalId":9063,"journal":{"name":"Brain","volume":"14 1","pages":""},"PeriodicalIF":14.5,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143020652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Epilepsy is a network disorder, involving neural circuits at both the micro- and macroscale. While local excitatory-inhibitory imbalances are recognized as a hallmark at the microscale, the dynamic role of distinct neuron types during seizures remain poorly understood. At the macroscale, interactions between key nodes within the epileptic network, such as the central median thalamic nucleus (CMT), are critical to the, hippocampal epileptic process. However, precise mechanisms underlying these interactions remain unclear. In this study, we investigated the microcircuit dynamics within the seizure onset zone and secondary spreading regions, as well as the network connectivity between the hippocampus and the CMT, using a 4-aminopyridine (4-AP) induced hippocampal seizure model. Rats were allocated into three experimental groups. The first group used a 3D tetrode array to monitor hippocampal seizure activity and microcircuit dynamics, including seizure propagation across the macroscale network. In the second group, a chemical lesion was induced in the CMT to assess its impact on hippocampal seizures. In the third group, chemogenetic techniques were used to selectively suppress pyramidal neurons in the CMT and observe changes in neural network connectivity between the CMT and hippocampus during seizures. Offline single-unit sorting was performed using KlustaKwik and further analysis was conducted with CellExplorer. At seizure onset, the narrow interneurons exhibited increased firing rates, initiating recruitment of other neurons, followed by increased activity in pyramidal neuron. Wide interneurons also showed heightened activity subsequent to pyramidal neurons. Interneurons played a more prominent role in the microcircuit during seizures compared to baseline. The CMT exhibited characteristic seizure activity and a decrease in narrow interneuron activity, whereas the cortex did not display seizure activity during hippocampal seizures. Lesioning the CMT resulted in the loss of the tonic component of hippocampal seizures and reduced overall neuronal activity in the hippocampal. Selective suppression of CMT pyramidal neurons resulted in shortened hippocampal seizures while preserving the tonic component. Narrow interneuron activity remained unchanged, while pyramidal neuron and wide interneuron activity significantly decreased. Our findings underscore the critical role of interneurons in the micronetwork of the seizure onset zone and secondary spreading region. Narrow interneurons were particularly vital in seizure initiation, whereas wide interneurons may contribute to seizure termination within the onset zone but not in the secondary spreading region. Pyramidal neurons in the CMT influence hippocampal seizures by modulating of both hippocampal pyramidal neurons and wide interneurons.
{"title":"Cell-type-specific networks during hippocampal seizures at the micro- and macroscale","authors":"Jiaoyang Wang, Jiaqing Yan, Donghong Li, Shipei He, Xiaonan Li, Yue Xing, Huanling Lai, Yue Gui, Nannan Zhang, Wenyao Huang, Xiaofeng Yang","doi":"10.1093/brain/awaf024","DOIUrl":"https://doi.org/10.1093/brain/awaf024","url":null,"abstract":"Epilepsy is a network disorder, involving neural circuits at both the micro- and macroscale. While local excitatory-inhibitory imbalances are recognized as a hallmark at the microscale, the dynamic role of distinct neuron types during seizures remain poorly understood. At the macroscale, interactions between key nodes within the epileptic network, such as the central median thalamic nucleus (CMT), are critical to the, hippocampal epileptic process. However, precise mechanisms underlying these interactions remain unclear. In this study, we investigated the microcircuit dynamics within the seizure onset zone and secondary spreading regions, as well as the network connectivity between the hippocampus and the CMT, using a 4-aminopyridine (4-AP) induced hippocampal seizure model. Rats were allocated into three experimental groups. The first group used a 3D tetrode array to monitor hippocampal seizure activity and microcircuit dynamics, including seizure propagation across the macroscale network. In the second group, a chemical lesion was induced in the CMT to assess its impact on hippocampal seizures. In the third group, chemogenetic techniques were used to selectively suppress pyramidal neurons in the CMT and observe changes in neural network connectivity between the CMT and hippocampus during seizures. Offline single-unit sorting was performed using KlustaKwik and further analysis was conducted with CellExplorer. At seizure onset, the narrow interneurons exhibited increased firing rates, initiating recruitment of other neurons, followed by increased activity in pyramidal neuron. Wide interneurons also showed heightened activity subsequent to pyramidal neurons. Interneurons played a more prominent role in the microcircuit during seizures compared to baseline. The CMT exhibited characteristic seizure activity and a decrease in narrow interneuron activity, whereas the cortex did not display seizure activity during hippocampal seizures. Lesioning the CMT resulted in the loss of the tonic component of hippocampal seizures and reduced overall neuronal activity in the hippocampal. Selective suppression of CMT pyramidal neurons resulted in shortened hippocampal seizures while preserving the tonic component. Narrow interneuron activity remained unchanged, while pyramidal neuron and wide interneuron activity significantly decreased. Our findings underscore the critical role of interneurons in the micronetwork of the seizure onset zone and secondary spreading region. Narrow interneurons were particularly vital in seizure initiation, whereas wide interneurons may contribute to seizure termination within the onset zone but not in the secondary spreading region. Pyramidal neurons in the CMT influence hippocampal seizures by modulating of both hippocampal pyramidal neurons and wide interneurons.","PeriodicalId":9063,"journal":{"name":"Brain","volume":"25 1","pages":""},"PeriodicalIF":14.5,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143027168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Distinct roles of mTORC2 in excitatory and inhibitory neurons in inflammatory and neuropathic pain.","authors":"Wei He,Xin Ge,Ru-Rong Ji","doi":"10.1093/brain/awaf004","DOIUrl":"https://doi.org/10.1093/brain/awaf004","url":null,"abstract":"","PeriodicalId":9063,"journal":{"name":"Brain","volume":"28 1","pages":""},"PeriodicalIF":14.5,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142991834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Marie-Sophie von Braun, Kristin Starke, Lucas Peter, Daniel Kürsten, Florian Welle, Hans Ralf Schneider, Max Wawrzyniak, Daniel P O Kaiser, Gordian Prasse, Cindy Richter, Elias Kellner, Marco Reisert, Julian Klingbeil, Anika Stockert, Karl-Titus Hoffmann, Gerik Scheuermann, Christina Gillmann, Dorothee Saur
The advent of endovascular thrombectomy has significantly improved outcomes for stroke patients with intracranial large vessel occlusion, yet individual benefits can vary widely. As demand for thrombectomy rises and geographic disparities in stroke care access persist, there is a growing need for predictive models that quantify individual benefits. However, current imaging methods for estimating outcomes may not fully capture the dynamic nature of cerebral ischemia and lack a patient-specific assessment of thrombectomy benefits. Our study introduces a deep learning approach to predict individual responses to thrombectomy in acute ischemic stroke patients. The proposed models provide predictions for both tissue and clinical outcomes under two scenarios: one assuming successful reperfusion and another assuming unsuccessful reperfusion. The resulting simulations of penumbral salvage and difference in NIHSS at discharge quantify the potential individual benefits of the intervention. Our models were developed on an extensive dataset from routine stroke care, which included 405 ischemic stroke patients who underwent thrombectomy. We used acute data for training (n = 304), including multimodal CT imaging and clinical characteristics, along with post hoc markers like thrombectomy success, final infarct localization, and NIHSS at discharge. We benchmarked our tissue outcome predictions under the observed reperfusion scenario against a thresholding-based clinical method and a generalised linear model. Our deep-learning model showed significant superiority, with a mean Dice score of 0.48 on internal (n = 50) and 0.52 on external (n = 51) test data, versus 0.26/0.36 and 0.34/0.35 for the baselines, respectively. The NIHSS sum score prediction achieved median absolute errors of 1.5 NIHSS points on the internal test dataset and 3.0 NIHSS points on the external test dataset, outperforming other machine learning models. By predicting the patient-specific response to thrombectomy for both tissue and clinical outcomes, our approach offers an innovative biomarker that captures the dynamics of cerebral ischemia. We believe this method holds significant potential to enhance personalised therapeutic strategies and to facilitate efficient resource allocation in acute stroke care.
{"title":"Prediction of tissue and clinical thrombectomy outcome in acute ischaemic stroke using deep learning","authors":"Marie-Sophie von Braun, Kristin Starke, Lucas Peter, Daniel Kürsten, Florian Welle, Hans Ralf Schneider, Max Wawrzyniak, Daniel P O Kaiser, Gordian Prasse, Cindy Richter, Elias Kellner, Marco Reisert, Julian Klingbeil, Anika Stockert, Karl-Titus Hoffmann, Gerik Scheuermann, Christina Gillmann, Dorothee Saur","doi":"10.1093/brain/awaf013","DOIUrl":"https://doi.org/10.1093/brain/awaf013","url":null,"abstract":"The advent of endovascular thrombectomy has significantly improved outcomes for stroke patients with intracranial large vessel occlusion, yet individual benefits can vary widely. As demand for thrombectomy rises and geographic disparities in stroke care access persist, there is a growing need for predictive models that quantify individual benefits. However, current imaging methods for estimating outcomes may not fully capture the dynamic nature of cerebral ischemia and lack a patient-specific assessment of thrombectomy benefits. Our study introduces a deep learning approach to predict individual responses to thrombectomy in acute ischemic stroke patients. The proposed models provide predictions for both tissue and clinical outcomes under two scenarios: one assuming successful reperfusion and another assuming unsuccessful reperfusion. The resulting simulations of penumbral salvage and difference in NIHSS at discharge quantify the potential individual benefits of the intervention. Our models were developed on an extensive dataset from routine stroke care, which included 405 ischemic stroke patients who underwent thrombectomy. We used acute data for training (n = 304), including multimodal CT imaging and clinical characteristics, along with post hoc markers like thrombectomy success, final infarct localization, and NIHSS at discharge. We benchmarked our tissue outcome predictions under the observed reperfusion scenario against a thresholding-based clinical method and a generalised linear model. Our deep-learning model showed significant superiority, with a mean Dice score of 0.48 on internal (n = 50) and 0.52 on external (n = 51) test data, versus 0.26/0.36 and 0.34/0.35 for the baselines, respectively. The NIHSS sum score prediction achieved median absolute errors of 1.5 NIHSS points on the internal test dataset and 3.0 NIHSS points on the external test dataset, outperforming other machine learning models. By predicting the patient-specific response to thrombectomy for both tissue and clinical outcomes, our approach offers an innovative biomarker that captures the dynamics of cerebral ischemia. We believe this method holds significant potential to enhance personalised therapeutic strategies and to facilitate efficient resource allocation in acute stroke care.","PeriodicalId":9063,"journal":{"name":"Brain","volume":"52 1","pages":""},"PeriodicalIF":14.5,"publicationDate":"2025-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142989763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shih-Pin Chen, Ya-Hsuan Chang, Yen-Feng Wang, Hsuan-Yu Chen, Shuu-Jiun Wang
The neurobiological mechanisms driving the ictal-interictal fluctuations and the chronification of migraine remain elusive. We aimed to construct a composite genetic-microRNA model that could reflect the dynamic perturbations of the disease course and inform the pathogenesis of migraine. We prospectively recruited four groups of participants, including interictal episodic migraine (i.e., headache-free for > 72 hrs apart from prior and subsequent attacks), ictal episodic migraine (i.e., during moderate to severe migraine attacks), chronic migraine, and controls in the discovery cohort. Next-generation sequencing (NGS) was used for microRNA profiling. The candidate microRNAs were validated with quantitative PCR (qPCR) in an independent validation cohort. Biological pathways associated with the microRNA regulome and interaction networks were explored. In addition, all participants received genotyping with the Axiom Genome-Wide Array TWB chip. A composite model was established, combining disease-associated microRNAs and genetic risk scores (GRS) indicative of genetic susceptibility, with the objective of differentiating migraine from controls using a binary outcome. From a total of 120 participants in the discovery cohort and 197 participants in the validation cohort, we identified disease-state microRNA signatures (including miR-183, miR-25, and miR-320) that were ubiquitously higher or lower in patients with migraine compared to controls. We have also validated four disease-activity miRNA signatures (miR-1307-5p, miR-6810-5p, let-7e, and miR-140-3p) that were differentially expressed only during the ictal stage of episodic migraine. Functional analysis suggested that prolactin and estrogen signaling pathways might play important roles in the pathogenesis. Moreover, the composite microRNA-GRS model differentiated patients from controls, achieving a positive predictive value of over 90%. To conclude, we developed a composite microRNA-genetic risk score model, which may serve as a predictive tool for identifying high-risk individuals. Our findings may help illuminate potential pathogenic mechanisms underlying the dysfunctional allostasis of migraine and pave the way for future precision medicine.
{"title":"Composite microRNA-genetic risk score model links to migraine and implicates its pathogenesis","authors":"Shih-Pin Chen, Ya-Hsuan Chang, Yen-Feng Wang, Hsuan-Yu Chen, Shuu-Jiun Wang","doi":"10.1093/brain/awaf005","DOIUrl":"https://doi.org/10.1093/brain/awaf005","url":null,"abstract":"The neurobiological mechanisms driving the ictal-interictal fluctuations and the chronification of migraine remain elusive. We aimed to construct a composite genetic-microRNA model that could reflect the dynamic perturbations of the disease course and inform the pathogenesis of migraine. We prospectively recruited four groups of participants, including interictal episodic migraine (i.e., headache-free for > 72 hrs apart from prior and subsequent attacks), ictal episodic migraine (i.e., during moderate to severe migraine attacks), chronic migraine, and controls in the discovery cohort. Next-generation sequencing (NGS) was used for microRNA profiling. The candidate microRNAs were validated with quantitative PCR (qPCR) in an independent validation cohort. Biological pathways associated with the microRNA regulome and interaction networks were explored. In addition, all participants received genotyping with the Axiom Genome-Wide Array TWB chip. A composite model was established, combining disease-associated microRNAs and genetic risk scores (GRS) indicative of genetic susceptibility, with the objective of differentiating migraine from controls using a binary outcome. From a total of 120 participants in the discovery cohort and 197 participants in the validation cohort, we identified disease-state microRNA signatures (including miR-183, miR-25, and miR-320) that were ubiquitously higher or lower in patients with migraine compared to controls. We have also validated four disease-activity miRNA signatures (miR-1307-5p, miR-6810-5p, let-7e, and miR-140-3p) that were differentially expressed only during the ictal stage of episodic migraine. Functional analysis suggested that prolactin and estrogen signaling pathways might play important roles in the pathogenesis. Moreover, the composite microRNA-GRS model differentiated patients from controls, achieving a positive predictive value of over 90%. To conclude, we developed a composite microRNA-genetic risk score model, which may serve as a predictive tool for identifying high-risk individuals. Our findings may help illuminate potential pathogenic mechanisms underlying the dysfunctional allostasis of migraine and pave the way for future precision medicine.","PeriodicalId":9063,"journal":{"name":"Brain","volume":"30 1","pages":""},"PeriodicalIF":14.5,"publicationDate":"2025-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142988843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zeynep Kaya, Nevin Belder, Melike Sever-Bahçekapılı, Şefik Evren Erdener, Buket Dönmez-Demir, Canan Bağcı, Merve Nur Köroğlu, Kaya Bilguvar, Turgay Dalkara
Cortical spreading depolarization (CSD), the neurophysiological event believed to underlie aura, may trigger migraine headaches through inflammatory signaling that originates in neurons and spreads to the meninges via astrocytes. Increasing evidence from studies on rodents and migraine patients supports this hypothesis. The transition from pro-inflammatory to anti-inflammatory mechanisms is crucial for resolving inflammation. However, the resolution of inflammation in the context of CSD and migraine headaches remains poorly understood. This study aims to elucidate the progression of post-CSD inflammatory signaling and its resolution in neurons, astrocytes, and microglia in mouse brains. CSD was triggered optogenetically or by pinprick. HMGB1 release, caspase-1 activation, and cell-specific activation of NF-κB pairs, along with ensuing transcriptomic changes, were evaluated using immunofluorescence, Western blotting, co-immunoprecipitation, FRET analysis, and cell-specific transcriptomics. Our findings indicate that after the initial burst, HMGB1 release from neurons ceased, and caspase-1 activation, which peaked 1-hour post-CSD, diminished within 3-5 hours. This suggests that pro-inflammatory stimuli driving inflammatory signaling decreased within hours after CSD. Pro-inflammatory NF-κB p65:p50 pairs, along with anti-inflammatory cRel:p65 pairs, were detected in astrocyte nuclei shortly after CSD. However, 24 hours post-CSD, the former had disappeared while the latter persisted, indicating a shift from pro-inflammatory to anti-inflammatory activity in astrocytes. Pathway analysis of cell-specific transcriptomic data confirmed NF-κB-related pro-inflammatory transcription in astrocytes 1-hour post-CSD, while no such activity was observed in neurons. Detailed transcriptomic analysis with Bayesian cell proportion reconstruction revealed that microglia exhibited transcriptional changes trending towards an anti-inflammatory profile, along with upregulation of several chemokines and cytokines (e.g., TNF). This suggests that microglia may play a role in supporting the inflammatory responses in astrocytes through the release of these mediators. The upregulation of genes involved in chemotaxis (e.g., Ccl3) and spine pruning (e.g., C1q) in microglia implies that microglia may contribute to synaptic repair, while inflammatory signaling in astrocytes could potentially modulate meningeal nociceptor activity through an extensive astrocyte endfeet syncytium abutting subarachnoid and perivascular spaces although direct evidence remains incomplete. This nuanced understanding of the inflammatory response in CNS cell types highlights the intricate cellular interactions and responses to CSD. Following a single CSD, distinct transcriptomic responses occur in neurons, astrocytes, and microglia, driving inflammatory and anti-inflammatory responses, potentially contributing to headache initiation and resolution.
{"title":"Spreading depolarization triggers pro- and anti-inflammatory signalling: a potential link to headache","authors":"Zeynep Kaya, Nevin Belder, Melike Sever-Bahçekapılı, Şefik Evren Erdener, Buket Dönmez-Demir, Canan Bağcı, Merve Nur Köroğlu, Kaya Bilguvar, Turgay Dalkara","doi":"10.1093/brain/awaf015","DOIUrl":"https://doi.org/10.1093/brain/awaf015","url":null,"abstract":"Cortical spreading depolarization (CSD), the neurophysiological event believed to underlie aura, may trigger migraine headaches through inflammatory signaling that originates in neurons and spreads to the meninges via astrocytes. Increasing evidence from studies on rodents and migraine patients supports this hypothesis. The transition from pro-inflammatory to anti-inflammatory mechanisms is crucial for resolving inflammation. However, the resolution of inflammation in the context of CSD and migraine headaches remains poorly understood. This study aims to elucidate the progression of post-CSD inflammatory signaling and its resolution in neurons, astrocytes, and microglia in mouse brains. CSD was triggered optogenetically or by pinprick. HMGB1 release, caspase-1 activation, and cell-specific activation of NF-κB pairs, along with ensuing transcriptomic changes, were evaluated using immunofluorescence, Western blotting, co-immunoprecipitation, FRET analysis, and cell-specific transcriptomics. Our findings indicate that after the initial burst, HMGB1 release from neurons ceased, and caspase-1 activation, which peaked 1-hour post-CSD, diminished within 3-5 hours. This suggests that pro-inflammatory stimuli driving inflammatory signaling decreased within hours after CSD. Pro-inflammatory NF-κB p65:p50 pairs, along with anti-inflammatory cRel:p65 pairs, were detected in astrocyte nuclei shortly after CSD. However, 24 hours post-CSD, the former had disappeared while the latter persisted, indicating a shift from pro-inflammatory to anti-inflammatory activity in astrocytes. Pathway analysis of cell-specific transcriptomic data confirmed NF-κB-related pro-inflammatory transcription in astrocytes 1-hour post-CSD, while no such activity was observed in neurons. Detailed transcriptomic analysis with Bayesian cell proportion reconstruction revealed that microglia exhibited transcriptional changes trending towards an anti-inflammatory profile, along with upregulation of several chemokines and cytokines (e.g., TNF). This suggests that microglia may play a role in supporting the inflammatory responses in astrocytes through the release of these mediators. The upregulation of genes involved in chemotaxis (e.g., Ccl3) and spine pruning (e.g., C1q) in microglia implies that microglia may contribute to synaptic repair, while inflammatory signaling in astrocytes could potentially modulate meningeal nociceptor activity through an extensive astrocyte endfeet syncytium abutting subarachnoid and perivascular spaces although direct evidence remains incomplete. This nuanced understanding of the inflammatory response in CNS cell types highlights the intricate cellular interactions and responses to CSD. Following a single CSD, distinct transcriptomic responses occur in neurons, astrocytes, and microglia, driving inflammatory and anti-inflammatory responses, potentially contributing to headache initiation and resolution.","PeriodicalId":9063,"journal":{"name":"Brain","volume":"119 1","pages":""},"PeriodicalIF":14.5,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142988847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ifrah Zawar, Aleksander Luniewski, Rithvik Gundlapalli, Carol Manning, Prachi Parikh, Jaideep Kapur, Mark Quigg
Seizures in people with dementia (PWD) are associated with faster cognitive decline and worse clinical outcomes. However, the relationship between ongoing seizure activity and postmortem neuropathology in PWD remains unexplored. We compared post-mortem findings in PWD with active, remote, and no seizures using multicentre data from 39 Alzheimer’s Disease Centres from 2005 to 2021. PWD were grouped by seizure status into active (seizures over the preceding one year), remote (prior seizures but none in the preceding year), and no seizures (controls). Baseline demographics, cognition, mortality, and postmortem findings of primary and contributing(co-pathologies) Alzheimer’s Disease(AD), Frontotemporal lobar degeneration(FTD), Lewy body, vascular pathologies and neurodegeneration were compared among the groups using Pearson’s Chi-squared test, fisher’s exact test, t-test, and ANOVA tests. Of 10,474 deceased PWD, active seizure participants suffered the highest mortality among the groups(proportion deceased among the groups: active=56%remote=35%, controls=34%, p<0.001). Among 6085 (58.1% of deceased) who underwent autopsy, 294 had active, 151 had remote, and 5640 had no seizures. PWD and active seizures died at a younger age (Active=75.8, remote=77.9, controls: 80.8 years, p <0.001) and had more severe dementia (CDR-Global: active=2.36, remote=1.90, controls=1.69, p<0.001). In post hoc analyses, those with primary postmortem diagnosis of AD with active seizures had more severe and later stages of AD pathology and ATN (amyloid, tau, and neurodegeneration) as evidenced by Braak stage for neurofibrillary(tau) degeneration and CERAD score density of neuritic(amyloid) plaques than remote seizure participants and controls. Active seizure participants had more neurodegeneration, evidenced by cerebral atrophy, hippocampal atrophy, and locus coeruleus hypopigmentation than controls. Among participants with primary postmortem diagnosis of non-AD, in posthoc analyses, active seizure participants had worse AD co-pathology evidenced by higher Braak stages than remote seizures and controls and a higher thal phase of beta-amyloid plaques than controls. Neurodegeneration (cerebral/hippocampal atrophy) and LC hypopigmentation were comparable among the groups. In both primary postmortem AD and non-AD diagnoses, FTD (co)pathology was less prevalent among active seizure participants than controls, while vascular pathology, Circle of Willis atherosclerosis, Lewy body pathology, lobar atrophy, and substantia nigra hypopigmentation were comparable among the three groups. This study shows that active, compared to remote seizures, are associated with earlier death and postmortem evidence of more severe ATN pathology. Active seizures are associated with more advanced AD pathology in AD and worse AD co-pathology in non-AD dementias. Therefore, clinicians should be vigilant in detecting ongoing seizures as this could reflect a worse prognosis in PWD.
{"title":"The association of seizure control with neuropathology in dementia","authors":"Ifrah Zawar, Aleksander Luniewski, Rithvik Gundlapalli, Carol Manning, Prachi Parikh, Jaideep Kapur, Mark Quigg","doi":"10.1093/brain/awaf017","DOIUrl":"https://doi.org/10.1093/brain/awaf017","url":null,"abstract":"Seizures in people with dementia (PWD) are associated with faster cognitive decline and worse clinical outcomes. However, the relationship between ongoing seizure activity and postmortem neuropathology in PWD remains unexplored. We compared post-mortem findings in PWD with active, remote, and no seizures using multicentre data from 39 Alzheimer’s Disease Centres from 2005 to 2021. PWD were grouped by seizure status into active (seizures over the preceding one year), remote (prior seizures but none in the preceding year), and no seizures (controls). Baseline demographics, cognition, mortality, and postmortem findings of primary and contributing(co-pathologies) Alzheimer’s Disease(AD), Frontotemporal lobar degeneration(FTD), Lewy body, vascular pathologies and neurodegeneration were compared among the groups using Pearson’s Chi-squared test, fisher’s exact test, t-test, and ANOVA tests. Of 10,474 deceased PWD, active seizure participants suffered the highest mortality among the groups(proportion deceased among the groups: active=56%remote=35%, controls=34%, p&lt;0.001). Among 6085 (58.1% of deceased) who underwent autopsy, 294 had active, 151 had remote, and 5640 had no seizures. PWD and active seizures died at a younger age (Active=75.8, remote=77.9, controls: 80.8 years, p &lt;0.001) and had more severe dementia (CDR-Global: active=2.36, remote=1.90, controls=1.69, p&lt;0.001). In post hoc analyses, those with primary postmortem diagnosis of AD with active seizures had more severe and later stages of AD pathology and ATN (amyloid, tau, and neurodegeneration) as evidenced by Braak stage for neurofibrillary(tau) degeneration and CERAD score density of neuritic(amyloid) plaques than remote seizure participants and controls. Active seizure participants had more neurodegeneration, evidenced by cerebral atrophy, hippocampal atrophy, and locus coeruleus hypopigmentation than controls. Among participants with primary postmortem diagnosis of non-AD, in posthoc analyses, active seizure participants had worse AD co-pathology evidenced by higher Braak stages than remote seizures and controls and a higher thal phase of beta-amyloid plaques than controls. Neurodegeneration (cerebral/hippocampal atrophy) and LC hypopigmentation were comparable among the groups. In both primary postmortem AD and non-AD diagnoses, FTD (co)pathology was less prevalent among active seizure participants than controls, while vascular pathology, Circle of Willis atherosclerosis, Lewy body pathology, lobar atrophy, and substantia nigra hypopigmentation were comparable among the three groups. This study shows that active, compared to remote seizures, are associated with earlier death and postmortem evidence of more severe ATN pathology. Active seizures are associated with more advanced AD pathology in AD and worse AD co-pathology in non-AD dementias. Therefore, clinicians should be vigilant in detecting ongoing seizures as this could reflect a worse prognosis in PWD.","PeriodicalId":9063,"journal":{"name":"Brain","volume":"131 1","pages":""},"PeriodicalIF":14.5,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142987672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Claudia Cicognola, Gemma Salvadó, Ruben Smith, Sebastian Palmqvist, Erik Stomrud, Tobey Betthauser, Sterling Johnson, Shorena Janelidze, Niklas Mattsson-Carlgren, Oskar Hansson, Alexa Pichet Binette
The APOE4 allele is the strongest genetic risk factor for sporadic Alzheimer’s disease (AD). While APOE4 is strongly associated with amyloid-beta (Aβ), its relationship with tau accumulation is less understood. Studies evaluating the role of APOE4 on tau accumulation showed conflicting results, particularly regarding the independence of these associations from Aβ load. In this study, we examined three independent longitudinal cohorts (BioFINDER-1, BioFINDER-2 and WRAP) in which participants had cross-sectional and longitudinal measures of tau tangles (tau-PET; temporal meta-ROI and entorhinal) or soluble p-tau (p-tau217), Aβ-PET and APOE genotype. The study included a total of 1370 cognitively unimpaired (CU) and 449 mild cognitive impairment (MCI) subjects, followed longitudinally with tau-PET and p-tau217. APOE4 carriers accounted for 40.2-50% of the cohorts. Different linear regressions (cross-sectional) and linear mixed-effect models (longitudinal) with tau measures as outcomes were fitted to test the effect of APOE4 as independent predictor, as well as in combination with baseline Aβ load (including interaction). All models included age, sex and cognitive status as covariates. We found no independent effects of the APOE4 carriership on insoluble tau in either cohort (BioFINDER-2 or WRAP), both on cross-sectional and longitudinal tau-PET in the temporal meta-ROI, when Aβ was present in the model (p=0.531-0.949). Aβ alone was the best predictor of insoluble tau accumulation, with no interaction between APOE4 and Aβ on tau-PET. In BioFINDER-2, there was a significant interaction between APOE4 and Aβ (b=0.166, p<0.001) in the entorhinal cortex at baseline. However, the interaction was not present in WRAP PET. No independent effects of the APOE4 carriership on baseline (p=0.683-0.708) and longitudinal (p=0.188-0.570) soluble p-tau217 were observed when Aβ was included in the model in BioFINDER-1 and WRAP. Similarly, no interaction between APOE4 and Aβ on soluble p-tau217 was observed. Mediation analysis revealed that Aβ load fully mediated most associations between APOE4 and tau (46-112%, either cross-sectional or longitudinal tau-PET or soluble p-tau217). In the largest cohort (BioFINDER-2), looking at APOE4 groups by number of ε4 alleles, we found an interaction between APOE4 homozygotes and Aβ on tau-PET levels at baseline and over time in the temporal meta-ROI, while in the entorhinal cortex this effect was observed only at baseline. In conclusion, although APOE4 is strongly associated with Aβ aggregation, it seems to be minimally associated with longitudinal changes in soluble or insoluble p-tau levels at a given level of Aβ pathology, confirming the primacy of Aβ in driving tau pathology.
{"title":"APOE4 impact on soluble and insoluble tau pathology is mostly influenced by amyloid-beta","authors":"Claudia Cicognola, Gemma Salvadó, Ruben Smith, Sebastian Palmqvist, Erik Stomrud, Tobey Betthauser, Sterling Johnson, Shorena Janelidze, Niklas Mattsson-Carlgren, Oskar Hansson, Alexa Pichet Binette","doi":"10.1093/brain/awaf016","DOIUrl":"https://doi.org/10.1093/brain/awaf016","url":null,"abstract":"The APOE4 allele is the strongest genetic risk factor for sporadic Alzheimer’s disease (AD). While APOE4 is strongly associated with amyloid-beta (Aβ), its relationship with tau accumulation is less understood. Studies evaluating the role of APOE4 on tau accumulation showed conflicting results, particularly regarding the independence of these associations from Aβ load. In this study, we examined three independent longitudinal cohorts (BioFINDER-1, BioFINDER-2 and WRAP) in which participants had cross-sectional and longitudinal measures of tau tangles (tau-PET; temporal meta-ROI and entorhinal) or soluble p-tau (p-tau217), Aβ-PET and APOE genotype. The study included a total of 1370 cognitively unimpaired (CU) and 449 mild cognitive impairment (MCI) subjects, followed longitudinally with tau-PET and p-tau217. APOE4 carriers accounted for 40.2-50% of the cohorts. Different linear regressions (cross-sectional) and linear mixed-effect models (longitudinal) with tau measures as outcomes were fitted to test the effect of APOE4 as independent predictor, as well as in combination with baseline Aβ load (including interaction). All models included age, sex and cognitive status as covariates. We found no independent effects of the APOE4 carriership on insoluble tau in either cohort (BioFINDER-2 or WRAP), both on cross-sectional and longitudinal tau-PET in the temporal meta-ROI, when Aβ was present in the model (p=0.531-0.949). Aβ alone was the best predictor of insoluble tau accumulation, with no interaction between APOE4 and Aβ on tau-PET. In BioFINDER-2, there was a significant interaction between APOE4 and Aβ (b=0.166, p&lt;0.001) in the entorhinal cortex at baseline. However, the interaction was not present in WRAP PET. No independent effects of the APOE4 carriership on baseline (p=0.683-0.708) and longitudinal (p=0.188-0.570) soluble p-tau217 were observed when Aβ was included in the model in BioFINDER-1 and WRAP. Similarly, no interaction between APOE4 and Aβ on soluble p-tau217 was observed. Mediation analysis revealed that Aβ load fully mediated most associations between APOE4 and tau (46-112%, either cross-sectional or longitudinal tau-PET or soluble p-tau217). In the largest cohort (BioFINDER-2), looking at APOE4 groups by number of ε4 alleles, we found an interaction between APOE4 homozygotes and Aβ on tau-PET levels at baseline and over time in the temporal meta-ROI, while in the entorhinal cortex this effect was observed only at baseline. In conclusion, although APOE4 is strongly associated with Aβ aggregation, it seems to be minimally associated with longitudinal changes in soluble or insoluble p-tau levels at a given level of Aβ pathology, confirming the primacy of Aβ in driving tau pathology.","PeriodicalId":9063,"journal":{"name":"Brain","volume":"23 1","pages":""},"PeriodicalIF":14.5,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142986803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Veith Weilnhammer, Marcus Rothkirch, Deniz Yilmaz, Merve Fritsch, Lena Esther Ptasczynski, Katrin Reichenbach, Lukas Rödiger, Philip Corlett, Philipp Sterzer
Perception integrates external sensory signals with internal predictions that reflect prior knowledge about the world. Previous research suggests that this integration is governed by slow alternations between an external mode, driven by sensory signals, and an internal mode, shaped by prior knowledge. Using a double-blind, placebo-controlled, cross-over experiment in healthy human participants, we investigated the effects of the N-Methyl-D-aspartate receptor (NMDAR) antagonist S-ketamine on the balance between external and internal modes. We found that S-ketamine causes a shift of perception toward the external mode. A case-control study revealed that individuals with paranoid Scz, a disorder repeatedly associated with NMDAR hypofunction, spend more time in the external mode. This NMDAR-dependent increase in the external mode suggests that the symptoms of schizophrenia are caused by recurring dissociations of perception from prior knowledge about the world.
感知将外部感官信号与反映对世界先验知识的内部预测结合起来。先前的研究表明，这种整合是由由感官信号驱动的外部模式和由先验知识形成的内部模式之间的缓慢交替控制的。采用双盲、安慰剂对照、交叉实验，研究了n -甲基- d -天冬氨酸受体（NMDAR）拮抗剂s-氯胺酮对内外部模式平衡的影响。我们发现s -氯胺酮导致感知转向外部模式。一项病例对照研究显示，患有偏执型Scz（一种反复与NMDAR功能减退相关的疾病）的个体在外部模式下花费的时间更多。这种依赖于nmdar的外部模式的增加表明，精神分裂症的症状是由对世界的先验知识的感知反复分离引起的。
{"title":"N-methyl-d-aspartate receptor hypofunction causes recurrent and transient failures of perceptual inference","authors":"Veith Weilnhammer, Marcus Rothkirch, Deniz Yilmaz, Merve Fritsch, Lena Esther Ptasczynski, Katrin Reichenbach, Lukas Rödiger, Philip Corlett, Philipp Sterzer","doi":"10.1093/brain/awaf011","DOIUrl":"https://doi.org/10.1093/brain/awaf011","url":null,"abstract":"Perception integrates external sensory signals with internal predictions that reflect prior knowledge about the world. Previous research suggests that this integration is governed by slow alternations between an external mode, driven by sensory signals, and an internal mode, shaped by prior knowledge. Using a double-blind, placebo-controlled, cross-over experiment in healthy human participants, we investigated the effects of the N-Methyl-D-aspartate receptor (NMDAR) antagonist S-ketamine on the balance between external and internal modes. We found that S-ketamine causes a shift of perception toward the external mode. A case-control study revealed that individuals with paranoid Scz, a disorder repeatedly associated with NMDAR hypofunction, spend more time in the external mode. This NMDAR-dependent increase in the external mode suggests that the symptoms of schizophrenia are caused by recurring dissociations of perception from prior knowledge about the world.","PeriodicalId":9063,"journal":{"name":"Brain","volume":"54 1","pages":""},"PeriodicalIF":14.5,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142987674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Intrinsic neuronal resilience as a tool for therapeutic discovery.","authors":"Stefania Corti,Eva Hedlund","doi":"10.1093/brain/awaf010","DOIUrl":"https://doi.org/10.1093/brain/awaf010","url":null,"abstract":"","PeriodicalId":9063,"journal":{"name":"Brain","volume":"142 1","pages":""},"PeriodicalIF":14.5,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142988901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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