{"doi":"10.1101/2025.09.16.676387","title":"Fast Ripple-Delta Coupling as Early Biomarker for Post-Traumatic Epileptogenesis in Repetitive Brain Injury","abstract":"Abstract Traumatic brain injury (TBI) can induce post-traumatic epilepsy (PTE), but early biomarkers for epileptogenesis are lacking. We used a repetitive diffuse TBI (rdTBI) model in mice with continuous video-EEG monitoring up to 4½ months post-injury to investigate electrographic biomarkers before and during post-traumatic seizure development. 25% of mice developed post-traumatic seizures with highly variable latency (5-126 days post-injury). Most significantly, we identified fast ripple-delta DOWN state coupling as an early biomarker that was detectable at 4 days post-TBI and appeared before seizure onset in all seizure-experiencing mice. This EEG signature distinguished seizure-experiencing from seizure-free TBI mice with high specificity. Power spectrum analysis revealed elevated delta and theta power, reduced physiological fast oscillations (alpha, beta, gamma) and increased pathological high-frequency oscillations (fast ripples) in seizure-experiencing animals, indicating network hyperexcitability. Spike analysis showed that while TBI itself increased cortical excitability, seizure onset triggered a dramatic further escalation in interictal activity. These electrographic signatures were remarkably consistent across all seizure-experiencing animals regardless of single or recurrent seizure pattern. Our results demonstrate that fast ripple-delta coupling represents a promising early biomarker detectable at 4 days post-TBI, before seizure onset, offering potential for early identification of post-traumatic seizure susceptibility. Importantly, this biomarker identified all seizure-prone animals regardless of whether they developed single or recurrent seizures, suggesting shared underlying mechanisms and clinical relevance for any post-traumatic seizure occurrence. These findings emphasize the utility of temporal EEG analysis for detecting early electrographic changes in post-traumatic epileptogenesis and may inform future intervention strategies. Key Points Fast ripple-delta DOWN state coupling was detectable as early as 4 days post-TBI and appeared before seizure onset in seizure-experiencing mice, representing the first early biomarker that can stratify animals for epileptogenesis risk during the critical latent period. Delta and theta power increased while alpha, beta and gamma power decreased in all seizure-experiencing mice post-TBI, creating a consistent electrographic signature regardless of whether animals developed single or recurrent seizures. Fast ripples were elevated and gamma-to-HFO ratios were reduced in seizure-experiencing mice, reflecting network hyperexcitability shift and potential inhibitory dysfunction that preceded seizure onset. Seizure onset triggered a 3-fold escalation in spike activity, while baseline spike differences between TBI and pre-seizure mice were not significant, highlighting the limitation of spike counts alone as predictive biomarkers during the latent period. Electrographic signatures were almost similar across all seizure patterns (single and recurrent), suggesting shared underlying mechanisms of network dysfunction, though larger studies are needed to determine if biomarkers can predict seizure frequency in addition to seizure susceptibility.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2025,"id":575062,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.96,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":900656,"name":"Dzenis Mahmutovic","orcid":"0000-0002-2180-2147","position":1,"is_corresponding":false},{"id":436367,"name":"Biswajit Maharathi","orcid":"0000-0002-9869-1801","position":2,"is_corresponding":false},{"id":1482639,"name":"Md. Safayet Hosen Talukder Arman","orcid":"0009-0002-5937-8027","position":3,"is_corresponding":false},{"id":535009,"name":"Michael J. Benko","orcid":"0000-0002-0741-0788","position":4,"is_corresponding":false},{"id":915123,"name":"Owen Leitzel","orcid":"0000-0002-2924-9366","position":5,"is_corresponding":false},{"id":1482640,"name":"Pritom Kumar Saha","orcid":"0009-0003-7211-826X","position":6,"is_corresponding":false},{"id":238189,"name":"Stefanie Robel","orcid":"0000-0001-6716-3670","position":7,"is_corresponding":false},{"id":613904,"name":"Oleksii Shandra","orcid":"0000-0003-4447-3312","position":0,"is_corresponding":true}],"reference_count":36,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T02:57:44.572630Z","pmid":"41000921","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}