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Inconsistent findings between laboratories are hampering scientific progress and are of increasing public concern. Differences in laboratory environment is a known factor contributing to poor reproducibility of findings between research sites, and well-controlled multisite efforts are an important next step to identify the relevant factors needed to reduce variation in study outcome between laboratories. Through harmonization of apparatus, test protocol, and aligned and non-aligned environmental variables, the present study shows that behavioral pharmacological responses in Shank2 knockout (KO) rats, a model of synaptic dysfunction relevant to autism spectrum disorders, were highly replicable across three research centers. All three sites reliably observed a hyperactive and repetitive behavioral phenotype in KO rats compared to their wild-type littermates as well as a dose-dependent phenotype attenuation following acute injections of a selective mGluR1 antagonist. These results show that reproducibility in preclinical studies can be obtained and emphasizes the need for high quality and rigorous methodologies in scientific research. Considering the observed external validity, the present study also suggests mGluR1 as potential target for the treatment of autism spectrum disorders.

Background Alzheimer's Disease (AD) and traumatic brain injuries (TBI) are frequently associated in medical literature, with a significant prevalence of TBI history observed among individuals diagnosed with AD. Our investigation focuses on this intersection, explicitly examining the risk of AD in individuals with a history of TBI. While current targets in cerebrospinal fluid and plasma can effectively detect acute TBI, the challenge lies in identifying biosignatures associated with TBI long after injury. Neuron‐derived small extracellular vesicles (NEVs) from plasma offer potential biomarkers linked to neuronal dysfunction. Prior research has demonstrated that the AD‐associated protein amyloid‐beta (Aβ) is sequestered in NEVs, making them more sensitive biomarkers than free proteins in native plasma. To evaluate the effectiveness of NEV cargo proteins in predicting TBI exposure, we used plasma samples from the third wave of the Vietnam Era Twin Study of Aging (VETSA3). We hypothesized that previous exposure to TBI is associated with abnormalities in AD‐related proteins in circulating NEVs. Method Participants in the VETSA3 study, comprising a community‐based sample of male twins aged 61‐73 (average 68), self‐reported a 40% history of mild to moderate TBI. We precipitated NEVs from biobanked VETSA3 plasma samples and enriched them for the neuronal‐specific protein L1CAM using magnetic immunocapture and fluorescence‐activated cell sorting. Following the International Society of Extracellular Vesicles’ guidelines, we characterized NEVs for size, integrity, and homogeneity using NanoSight and ELISA. We quantified AD neuropathogenic proteins Aβ40–42, tau, p‐tau, and Nf‐L in NEVs using SIMOA assays. Our analyses explored the influence of TBI characteristics (number, age at occurrence, severity) on NEV cargo compared to non‐TBI individuals, assessing their utility as potential biomarkers. Result NEVs derived from VETSA3 plasma demonstrated similar size distributions and shape characteristics required for cargo analysis. The outcomes of the ELISA validated the presence of the NEV marker protein Flotillin‐1. A significant variation was observed in several neuropathogenic proteins, demonstrating the relationship between TBI exposure and AD. Conclusion Our findings give insight into TBI as a risk factor for AD and the role of NEV cargo proteins as potential clinical biomarkers of neurodegeneration.

Traumatic brain injury (TBI) is a significant risk factor for Alzheimer's disease (AD) and cognitive decline, yet biomarkers identifying persistent neuroinflammation following TBI remain underexplored. Astrocyte-derived small extracellular vesicles (AEVs) from plasma encapsulate inflammatory cytokines and complement proteins, offering a window into chronic neuroinflammatory processes linked to TBI and cognitive dysfunction. Previous studies demonstrate that complement proteins within AEVs predict mild cognitive impairment (MCI) conversion and are elevated in TBI patients years post-injury. This study examines AEV cargo to determine whether inflammatory cytokines and complement proteins serve as biomarkers for cognitive decline in aging veterans with a history of TBI. Participants of the Vietnam Era Twin Study of Aging (VETSA), a longitudinal cohort of male twins (mean age = 68), have extensive cognitive, laboratory, and genetic assessments. Plasma AEVs from biobanked VETSA3 samples were isolated using immunocapture of astrocyte-specific marker GLAST (ACSA-1) and characterized using nanoimaging. We quantified key inflammatory cytokines (IL-1β, IL-6, TNF-α, IL-10) and complement proteins (C4b and C3b) within AEV cargo using ultra-sensitive SIMOA assays. Group differences between TBI-exposed (N≈320) and non-TBI (N≈680) participants were assessed using linear mixed-effects models, accounting for twin clustering. Longitudinal mixed models were applied to evaluate the association of AEV protein cargo with cognitive decline, with MCI classification used as a secondary outcome. ROC analyses examined the predictive utility of AEV biomarkers for MCI diagnosis. AEVs were successfully isolated and characterized, confirming the EV size, shape, and enrichment of astrocyte markers. Preliminary findings suggest significant elevations in C3b and IL-6 in TBI-exposed individuals compared to controls, with higher levels correlating with accelerated cognitive decline. ROC analyses indicate that a combined biomarker panel (IL-6, TNF-α, and C4b) improves the classification of MCI status (AUC > 0.7). These findings highlight the potential of AEV-derived inflammatory and complement proteins as biomarkers of neuroinflammation and cognitive decline in TBI-exposed aging populations. The persistence of inflammatory abnormalities in AEVs years after TBI suggests a chronic neuroinflammatory response that may underlie increased AD risk. Future work will examine interactions between inflammatory and neurodegenerative AEV biomarkers to refine risk prediction models for cognitive impairment in TBI populations.

Background Traumatic brain injury (TBI) is a significant risk factor for Alzheimer's disease (AD) and cognitive decline, yet biomarkers identifying persistent neuroinflammation following TBI remain underexplored. Astrocyte‐derived small extracellular vesicles (AEVs) from plasma encapsulate inflammatory cytokines and complement proteins, offering a window into chronic neuroinflammatory processes linked to TBI and cognitive dysfunction. Previous studies demonstrate that complement proteins within AEVs predict mild cognitive impairment (MCI) conversion and are elevated in TBI patients years post‐injury. This study examines AEV cargo to determine whether inflammatory cytokines and complement proteins serve as biomarkers for cognitive decline in aging veterans with a history of TBI. Method Participants of the Vietnam Era Twin Study of Aging (VETSA), a longitudinal cohort of male twins (mean age = 68), have extensive cognitive, laboratory, and genetic assessments. Plasma AEVs from biobanked VETSA3 samples were isolated using immunocapture of astrocyte‐specific marker GLAST (ACSA‐1) and characterized using nanoimaging. We quantified key inflammatory cytokines (IL‐1β, IL‐6, TNF‐α, IL‐10) and complement proteins (C4b and C3b) within AEV cargo using ultra‐sensitive SIMOA assays. Group differences between TBI‐exposed (N≈320) and non‐TBI (N≈680) participants were assessed using linear mixed‐effects models, accounting for twin clustering. Longitudinal mixed models were applied to evaluate the association of AEV protein cargo with cognitive decline, with MCI classification used as a secondary outcome. ROC analyses examined the predictive utility of AEV biomarkers for MCI diagnosis. Result AEVs were successfully isolated and characterized, confirming the EV size, shape, and enrichment of astrocyte markers. Preliminary findings suggest significant elevations in C3b and IL‐6 in TBI‐exposed individuals compared to controls, with higher levels correlating with accelerated cognitive decline. ROC analyses indicate that a combined biomarker panel (IL‐6, TNF‐α, and C4b) improves the classification of MCI status (AUC > 0.7). Conclusion These findings highlight the potential of AEV‐derived inflammatory and complement proteins as biomarkers of neuroinflammation and cognitive decline in TBI‐exposed aging populations. The persistence of inflammatory abnormalities in AEVs years after TBI suggests a chronic neuroinflammatory response that may underlie increased AD risk. Future work will examine interactions between inflammatory and neurodegenerative AEV biomarkers to refine risk prediction models for cognitive impairment in TBI populations.

Inconsistent findings between laboratories are hampering scientific progress and are of increasing public concern. Differences in laboratory environment is a known factor contributing to poor reproducibility of findings between research sites, and well-controlled multisite efforts are an important next step to identify the relevant factors needed to reduce variation in study outcome between laboratories. Through harmonization of apparatus, test protocol, and aligned and non-aligned environmental variables, the present study shows that behavioral pharmacological responses in Shank2 knockout (KO) rats, a model of synaptic dysfunction relevant to autism spectrum disorders, were highly replicable across three research centers. All three sites reliably observed a hyperactive and repetitive behavioral phenotype in KO rats compared to their wild-type littermates as well as a dose-dependent phenotype attenuation following acute injections of a selective mGluR1 antagonist. These results show that reproducibility in preclinical studies can be obtained and emphasizes the need for high quality and rigorous methodologies in scientific research. Considering the observed external validity, the present study also suggests mGluR1 as potential target for the treatment of autism spectrum disorders.