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PubMed2016

Gene co-expression analysis identifies brain regions and cell types involved in migraine pathophysiology: a GWAS-based study using the Allen Human Brain Atlas.

Migraine is a common disabling neurovascular brain disorder typically characterised by attacks of severe headache and associated with autonomic and neurological symptoms. Migraine is caused by an interplay of genetic and environmental factors. Genome-wide association studies (GWAS) have identified over a dozen genetic loci associated with migraine. Here, we integrated migraine GWAS data with high-resolution spatial gene expression data of normal adult brains from the Allen Human Brain Atlas to identify specific brain regions and molecular pathways that are possibly involved in migraine pathophysiology. To this end, we used two complementary methods. In GWAS data from 23,285 migraine cases and 95,425 controls, we first studied modules of co-expressed genes that were calculated based on human brain expression data for enrichment of genes that showed association with migraine. Enrichment of a migraine GWAS signal was found for five modules that suggest involvement in migraine pathophysiology of: (i) neurotransmission, protein catabolism and mitochondria in the cortex; (ii) transcription regulation in the cortex and cerebellum; and (iii) oligodendrocytes and mitochondria in subcortical areas. Second, we used the high-confidence genes from the migraine GWAS as a basis to construct local migraine-related co-expression gene networks. Signatures of all brain regions and pathways that were prominent in the first method also surfaced in the second method, thus providing support that these brain regions and pathways are indeed involved in migraine pathophysiology.

Atlases as Topic↗

PubMed2025

Brain dynamics reflecting an intra-network brain state is associated with increased posttraumatic stress symptoms in the early aftermath of trauma.

Post-traumatic stress (PTS) encompasses a range of psychological responses following trauma, which may lead to more severe outcomes such as post-traumatic stress disorder (PTSD). Identifying early neuroimaging biomarkers that link brain function to PTS outcomes is critical for understanding PTSD risk. This longitudinal study examines the association between brain dynamic functional network connectivity (dFNC) and current/future PTS symptom severity, and the impact of sex on this relationship. By analyzing 275 participants' dFNC data obtained ~2 weeks after trauma exposure, we noted that brain dynamics of an inter-network brain state link negatively with current (r=-0.197, p corrected = 0.0079) and future (r=-0.176, p corrected = 0.0176) PTS symptom severity. Also, dynamics of an intra-network brain state correlated with future symptom intensity (r = 0.205, p corrected = 0.0079). We additionally observed that the association between the network dynamics of the inter-network and intra-network brain state with symptom severity is more pronounced in female group. Our findings highlight a potential link between brain network dynamics in the aftermath of trauma with current and future PTSD outcomes, with a stronger effect in female group, underscoring the importance of sex differences.

Journal Article↗

PubMed2026

Understanding specificity in immune-brain pathways: A systematic review of differential associations between individual cytokines and brain structure and function measured through magnetic resonance imaging in humans.

Research shows that cytokines are associated with psychiatric disorders, including major depression, and multiple aspects of brain structure and function. Accumulating data suggest that different cytokines may have unique profiles of biological activity, particularly in their neuromodulatory roles, but it is currently unclear whether they have unique associations with specific neural circuits in humans. In this paper, we systematically review magnetic resonance imaging studies conducted with depressed or healthy control human participants under age 65 that examine associations between peripheral cytokines and brain structure and function, with the goal of evaluating evidence for the specificity of these cytokine-brain associations. We find that across multiple measures of brain structure and function, the majority of studies reviewed reported unique associations between individual cytokines and brain outcomes. A synthesis of findings across studies also suggests a preliminary hypothesis of specific associations of interleukin-6 levels in circulation with the default mode network and tumor necrosis factor-alpha with the salience network, which could be tested in future research. We conclude the review with future directions for research that can strengthen understanding of these associations.

Humans↗

PubMed2026

One brain, one mind: A joint EPA-EAN leadership perspective on brain health.

Neurology and psychiatry have operated as separate disciplines for over a century, yet this division reflects historical and institutional developments rather than the underlying biology of the brain. Contemporary neuroscience shows that brain and mental health disorders share genetic susceptibilities, inflammatory and metabolic pathways, environmental and social risk factors, and clinical features that cross diagnostic boundaries. Cognitive, emotional, sensory, and motor symptoms regularly appear across both neurological and psychiatric populations, and conditions such as seizures, psychosis, mood disorders, cognitive disorders, and sleep disorders are common to both. A brain health framework addresses this reality by treating the brain as a single biological organ whose function emerges from the interplay between genome and exposome - including stress, trauma, social context, existential meaning, pollution, and physical health - and which underlies perception, behaviour, cognition, emotion, resilience, and vulnerability. Translating this perspective into practice requires coordinated action across domains. Clinically, collaborative models such as joint neurology-psychiatry consultations and shared outpatient pathways can be implemented within existing resources to improve diagnostic clarity and continuity of care. In training, a more harmonised curriculum with shared foundations in neurobiology, joint seminars, and cross-rotations would equip clinicians with a common language while preserving specialist depth, and support the emerging fields of preventive neurology and preventive psychiatry. In research, organising studies around shared mechanisms and symptom dimensions, and launching joint funding calls, would enhance translational relevance and reduce duplication. To realise this vision, sustained leadership from European professional bodies is essential to establish collaboration as a shared professional standard.

Humans↗

PubMed2025

Three-dimensional U-Net with transfer learning improves automated whole brain delineation from MRI brain scans of rats, mice, and monkeys.

BACKGROUND: Automated whole-brain delineation (WBD) techniques often struggle to generalize across pre-clinical studies due to variations in animal models, magnetic resonance imaging (MRI) scanners, and tissue contrasts. We developed a 3D U-Net neural network for WBD pre-trained on organophosphate intoxication (OPI) rat brain MRI scans. We used transfer learning (TL) to adapt this OPI-pretrained network to other animal models: rat model of Alzheimer's disease (AD), mouse model of tetramethylenedisulfotetramine (TETS) intoxication, and titi monkey model of social bonding. METHODS: We assessed an OPI-pretrained 3D U-Net across animal models under three conditions: (1) direct application to each dataset; (2) utilizing TL; and (3) training disease-specific U-Net models. For each condition, training dataset size (TDS) was optimized, and output WBDs were compared to manual segmentations for accuracy. RESULTS: The OPI-pretrained 3D U-Net (TDS = 100) achieved the best accuracy [median[min-max]] for the test OPI dataset with a Dice coefficient (DC) = [0.987 [0.977-0.992]] and Hausdorff distance (HD) = [0.86 [0.55-1.27]]mm. TL improved generalization across all models [AD (TDS = 40): DC = 0.987 [0.977-0.992] and HD = 0.72 [0.54-1.00]mm; TETS (TDS = 10): DC = 0.992 [0.984-0.993] and HD = 0.40 [0.31-0.50]mm; Monkey (TDS = 8): DC = 0.977 [0.968-0.979] and HD = 3.03 [2.19-3.91]mm], showing performance comparable to disease-specific networks. CONCLUSIONS: The OPI-pretrained 3D U-Net with TL achieved accuracy comparable to disease-specific networks with reduced training data (TDS ≤ 40 scans) across all models. Future work will focus on developing a multi-region delineation pipeline for pre-clinical MRI brain data, utilizing the proposed WBD as an initial step.

Animals↗

PubMed2025

Correlation of extracellular vesicle Alu RNA with brain aging and neuronal injury: a potential biomarker for brain aging.

BACKGROUND: Extracellular vesicles (EVs) are promising biomarkers for neurodegeneration. Alu elements are retrotransposons increasingly expressed with age and may be involved in aging-related diseases. OBJECTIVE: To determine the potential of Alu RNA in plasma-derived EVs as a biomarker for brain aging and neuronal injury. METHODS: EVs were isolated from plasma samples across different age groups. EV Alu RNA levels were measured and their associations with biomarkers of brain aging, including plasma neurofilament light chain (NfL), plasma amyloid-beta (Aβ42 and Aβ40), and plasma phosphorylated tau (p-Tau181), were analyzed. RESULTS: EV Alu RNA levels were increased significantly with age and were strongly correlated with plasma NfL, suggesting a strong association between EV Alu RNA and neuronal injury. Significant correlations were also found between EV Alu RNA and plasma amyloid-beta levels, while no significant association was observed with tau pathology. CONCLUSIONS: EV Alu RNA levels are elevated with age and associated with neuronal injury, highlighting their potential as a novel, non-invasive biomarker for brain aging and neurodegeneration.

Humans↗

PubMed2026

The role of artificial intelligence in the diagnosis and prognosis of traumatic brain injury based on brain CT scans: a systematic review.

Traumatic brain injury (TBI) is a leading cause of emergency department visits and a major contributor to injury-related mortality and long-term neurological disability. Non-contrast computed tomography (CT) is the gold-standard imaging modality for the rapid diagnosis of TBI. Clinical outcomes depend strongly on early detection and prompt acute management. Artificial intelligence (AI)-based models may support faster automated identification of traumatic findings and early prediction of patient prognosis. A systematic literature search was conducted in PubMed/MEDLINE, Scopus, IEEE Xplore, ACM Digital Library, and the Cochrane Library in accordance with PRISMA 2020 guidelines to evaluate AI-based models for automated detection of TBI-related findings on CT and for prediction of clinical outcomes. Risk of bias and applicability were assessed using QUADAS-2 for diagnostic accuracy studies and PROBAST + AI for prediction model studies. Twenty-two studies were included. Sixteen studies evaluated diagnostic tasks and 10 evaluated prognostic outcomes, with four studies contributing to both categories. Diagnostic performance was generally high, with many studies reporting AUC values approaching or exceeding 0.90, particularly for larger lesion volumes.Prognostic performance was more variable, with moderate to high discrimination and substantial heterogeneity. Only 9 studies incorporated independent external validation, and performance was frequently lower in external cohorts. All prognostic model studies were judged to be at high overall risk of bias using PROBAST + AI, and most diagnostic accuracy studies also demonstrated high or unclear risk of bias in at least one QUADAS-2 domain, most frequently in patient selection. AI-based models applied to brain CT demonstrate strong technical performance for both diagnostic and prognostic tasks in TBI. However, most studies relied on retrospective designs and lacked independent external validation which limits models generalizability and raises concern for potential overfitting. Prospective, multicenter studies with standardized methodologies and rigorous external validation are required before widespread clinical implementation.

Humans↗

PubMed2025

Trastuzumab Deruxtecan for ERBB2-Mutant Metastatic Non-Small Cell Lung Cancer With or Without Brain Metastases: A Secondary Analysis of Randomized Clinical Trials.

IMPORTANCE: Brain metastases reduce overall survival rates of patients with non-small cell lung cancer (NSCLC); patients with epidermal growth factor receptor 2 (ERBB2 [formerly HER2])-mutant NSCLC are more likely to have baseline brain metastases. Trastuzumab deruxtecan (T-DXd) is an approved ERBB2-directed treatment for previously treated unresectable or metastatic ERBB2-mutant NSCLC. OBJECTIVE: To assess the clinical effectiveness and safety of T-DXd 5.4 mg/kg and 6.4 mg/kg doses in patients with previously treated ERBB2-mutant metastatic NSCLC with or without untreated or previously treated stable brain metastases. DESIGN, SETTING, AND PARTICIPANTS: This post hoc secondary analysis pooled patients from the DESTINY-Lung01 (data cutoff date: December 3, 2021) and DESTINY-Lung02 (data cutoff date: December 23, 2022) clinical trials by T-DXd dose (5.4 mg/kg and 6.4 mg/kg). DESTINY-Lung01 was a multicenter, open-label, 2-cohort, nonrandomized phase 2 study, while DESTINY-Lung02 was a dose-blinded, multicenter, 2-cohort, randomized phase 2 study. Participants had a previously treated ERBB2-mutant metastatic NSCLC with or without untreated or previously treated stable brain metastases at baseline. All statistical analyses were performed from April 2023 to October 2024. INTERVENTION: Patients received a T-DXd dose of either 5.4 mg/kg or 6.4 mg/kg intravenously every 3 weeks. MAIN OUTCOME AND MEASURE: Systemic and intracranial effectiveness by blinded independent central review using RECIST (Response Evaluation Criteria in Solid Tumors) version 1.1, sites of progression, and safety. RESULTS: This analysis included 102 patients in the T-DXd 5.4-mg/kg dose group (65 females [64%]; median [range] age, 57.5 [37.0-83.0] years and 59.5 [30.0-79.0] years in patients with and without brain metastases, respectively) and 141 patients in the T-DXd 6.4-mg/kg dose group (94 females [67%]; median [range] age, 62.5 [29.0-88.0] years and 59.0 [27.0-83.0] years in patients with and without brain metastases, respectively). In each group, 31% (32 of 102) and 38% (54 of 141) of patients, respectively, had baseline brain metastases and 53% (17 of 32) and 44% (24 of 54), respectively, received prior brain metastasis treatment. In patients with and without brain metastases, systemic confirmed objective response rates (ORRs) were 47% (15 of 32; 95% CI, 29%-65%) and 50% (35 of 70; 95% CI, 38%-62%), respectively, with the T-DXd 5.4-mg/kg dose, and 50% (27 of 54; 95% CI, 36%-64%) and 59% (51 of 87; 95% CI, 48%-69%) with the T-DXd 6.4-mg/kg dose. Median progression-free survival was 7.1 (95% CI, 5.5-9.7) months in the T-DXd 5.4-mg/kg dose group and 7.1 (95% CI, 4.5-9.6) months in the T-DXd 6.4-mg/kg dose group of patients with baseline brain metastases. Among patients with measurable baseline brain metastases, intracranial confirmed ORRs were 50% (7 of 14; 95% CI, 23%-77%) with the T-DXd 5.4-mg/kg dose and 30% (9 of 30; 95% CI, 15%-49%) with the T-DXd 6.4-mg/kg dose. At both doses, the safety profile of T-DXd was generally manageable, regardless of baseline brain metastases, favoring the T-DXd 5.4 mg/kg dose. CONCLUSIONS AND RELEVANCE: In this secondary analysis, T-DXd at the approved dose of 5.4 mg/kg showed antitumor activity in patients with previously treated ERBB2-mutant metastatic NSCLC with or without brain metastases. This finding supports T-DXd 5.4 mg/kg use in this population.

Adult↗

PubMed2026

Genetic evidence that advanced COVID-19 accelerates longitudinal brain atrophy: A Mendelian randomization study.

Coronavirus disease 2019 (COVID-19) was reported to persist long-term in the brain and leave several long-term neurologic sequelae. However, the causal relationship between COVID-19 and brain aging is still unknown. The genome-wide association study (GWAS) data on COVID-19 phenotypes (susceptibility, hospitalization, and severity), involving a total of 5,779,391 participants, were collected from the COVID-19 Host Genetics Initiative. In addition, GWAS data on longitudinal changes in 15 brain structures, assessed via magnetic resonance imaging across the lifespan, were sourced from the ENIGMA Consortium and involved 15,640 participants. Two-sample Mendelian randomization was conducted to infer the causal relationship between COVID-19 and longitudinal brain changes. Multi-trait GWAS meta-analysis, colocalization, and fine-mapping analyses were performed to identify shared genetic etiologies. H3K27me3 ChIP-seq was used to evaluate the regulatory effect of colocalized loci. Two-step Mendelian randomization was applied to explore potential mediating mechanisms across multi-omics layers, including proteomics, metabolomics, and immunomics. Our results showed that COVID-19 hospitalization (β = -262.405, P = .041) and severity (β = -177.676, P = .049) were genetically associated with atrophied volume of total brain during longitudinal change. This suggests that individuals with advanced COVID-19 may be more susceptible to accelerated global brain aging. Caudate was genetically affected by all COVID-19 phenotypes. Seven variants were shared between advanced COVID-19 and global brain aging. rs117169628 was colocalized between advanced COVID-19 and global brain aging, and exerted an inhibitory effect on CDH15 expression, further strengthening the causality. Six metabolites, 1 protein, and 1 immune trait were identified as potential mediators. Our study indicates that advanced COVID-19 might be genetically associated with accelerated brain aging. Brain health should be paid more attention in long COVID-19.

Humans↗

PubMed2025

Brain Health Loss Mediates the Effect of Infarct Volume on Functional Outcome in Ischemic Stroke.

IMPORTANCE: Brain health may facilitate resilience to detrimental consequences from neurological diseases. Infarct volume is associated with poor functional outcome after acute ischemic stroke (AIS), but potential mediating effects through stroke-related brain health loss have not been investigated. OBJECTIVE: To determine whether stroke-related brain health loss, quantified by change in MRI derived effective Reserve (eR), mediates the effect of acute infarct volume on functional outcome after AIS. DESIGN: Observational multicenter cohort study. SETTING: We analyzed data from the GASROS (n=488) and MRI-GENIE (n=560) cohorts, collected 2003-2011. PARTICIPANTS: Adult patients consecutively diagnosed with AIS, with available admission MRI. EXPOSURE: At admission, white matter hyperintensity (WMH) and normal-appearing brain volumes were assessed on T2-FLAIR, and acute infarct volume on diffusion weighted imaging. WMH was normalized by brain volume, creating WMH load. We quantified brain health using eR, a latent variable incorporating age, WMH load, and normal-appearing brain volume. ΔeR reflected the change in eR when acute infarct volume was included, representing stroke-related brain health decline. Mediation analysis was used to determine if ΔeR mediates the effect of infarct volume on functional outcome (modified Rankin Scale [mRS] at 90 days). MAIN OUTCOME MEASURE: Proportion of mediating effect. RESULTS: We included 1,048 patients (median age 67y, 38% females). At baseline, median NIHSS score was 3 (IQR 1-7), median infarct volume 3.1mL (IQR 0.9-15.5). At 90 days, median mRS score was 1 (IQR 1-3) and 51 (5%) patients had died. In mediation analysis, ΔeR significantly mediated 36% (95% CI 16-56%) of the total effect of infarct volume on functional outcome (direct effect (ß=0.15 [95% CI 0.09-0.22], p<0.001; indirect effect mediated through ΔeR: ß=0.09 [95% CI 0.04 to 0.14], p=0.001). In subgroup-analyses, the mediative effect was apparent among female but not male, and among patients aged >67y but not ≤67y. CONCLUSIONS AND RELEVANCE: Stroke-related structural brain health loss mediates about one third of the effect of acute infarct volume on functional outcome after ischemic stroke, with important sex and age differences. Brain health significantly influences outcome and recovery potential, and may be considered a key biomarker when modeling outcome after AIS.

acute ischemic stroke↗

PubMed2026

A systematic review of macaque brain stimulation: Trends and future directions.

Neurostimulation techniques can powerfully modulate neural circuit activity and provide causal insights into the relationship between brain function and behavior. Macaque monkeys have long been a key animal model for brain stimulation studies. While stimulating the macaque brain with one or a few electrodes has already taught us much about brain function and dysfunction, recent technological advances promise a future with more precise stimulation using many more electrodes. However, such possibilities also increase the number of choices an experimenter has when designing their study. We can learn from a rich past, but a comprehensive overview of which brain regions have been studied and with what stimulation parameters is lacking. Here, we present a PRISMA-compliant systematic review of 734 macaque brain stimulation studies using electrical and/or optogenetic stimulation. We find a striking bias in which brain areas have traditionally been stimulated: a mere 10 brain regions account for half of all studies, with the remainder of studies investigating approximately 150 other areas. Across studies, stimulation frequency robustly predicted direct behavioral effects independent of brain region, while amplitude did not. Future studies could more systematically explore less studied regions through lower stimulation frequencies (e.g., 20-50 Hz) alongside established ranges (∼200 Hz). Tools such as fMRI or optical imaging can capture neural circuit engagement evoked by these frequencies, even when behavioral effects are absent or remain subtle. Our synthesis offers a guide towards the next steps in high-channel-count, high-precision stimulation approaches.

Animals↗

PubMed2026

Predicted brain-regional gene expression patterns in individuals living with Alzheimer's disease.

Studying brain gene expression in Alzheimer's Disease (AD) remains difficult as postmortem brain is difficult to access, cannot be used to guide donor treatment, may be confounded by environmental factors before and after death, and is difficult to link to early AD states or disease progression. To circumvent these limitations, several studies have tested blood transcriptome biomarkers for AD. However, gene-expression levels in the blood have limited correlation with those in the brain. To evaluate the potential of monitoring Alzheimer's progression with peripheral data, we used transcriptome-imputation to identify brain-region-specific AD-associated gene-expression differences in cohorts with blood-based transcriptome data. This approach provides a high-resolution image of AD-associated molecular differences in the brains of individuals actively living with disease. We analyzed eight AD studies (777 AD cases, 779 cognitively unimpaired controls), imputing transcriptomes in 10 brain regions via the Brain Gene Expression and Network Imputation Engine (BrainGENIE). Hundreds of differentially expressed genes (DEGs) associated with AD were identified in nine brain regions, with anterior cingulate cortex and amygdala showing the most differential expression. AD-associated genes were enriched in pathways such as proteostasis, mitochondrial dysfunction, and immune activation. We observed significant yet moderate concordance between imputed AD-associated changes and those directly measured in the dorsolateral prefrontal cortex and cerebellum. These transcriptomic changes can guide future in vitro studies focused on pathogenesis or be targets of novel therapeutic development. In conclusion, we demonstrated the scope and utility of brain expression imputation from the peripheral transcriptome, laying the groundwork for biomarker discovery and prospective AD studies.

Alzheimer Disease↗

PubMed2026

Loss of ovarian function and estrogen therapy remodel the brain's synaptic and metabolic proteome.

Menopause is linked to cognitive decline and reduced brain metabolism, whereas estrogen (E2) therapy has been shown to mitigate these effects. Understanding the molecular mechanisms by which ovarian hormones and E2 influence neuroprotection is essential for developing strategies to maintain brain health in women. In this study, we examined how the loss of ovarian hormones, with or without E2 treatment, affects the brain proteome and mitochondrial energy production in aged female C57BL/6J mice (36-40 wk). The mice underwent sham or ovariectomy (OVX) surgery and were fed a high-fat diet for 10 wk; 6 wk after surgery, OVX mice received either sesame oil or E2 treatment for 4 wk. Proteomic analysis of brain homogenates revealed 4,992 proteins regulated by E2, with pathway analysis showing increased signaling proteins related to synaptogenesis. OVX reduced proteins involved in synaptic function, branched-chain amino acid and ketone metabolism, the tricarboxylic acid cycle, and oxidative phosphorylation (Complexes I, IV, and V), whereas E2 restored protein expression within these pathways. Despite alterations in OxPhos proteins, basal and state 3 mitochondrial respiration remained unchanged, although notable impairments in Complex IV enzymatic activity were apparent in OVX, which were partially reversed by E2 treatment. Overall, these results indicate that E2 supports brain health by maintaining proteins crucial for synaptic integrity and metabolism, while partially offsetting the functional decline in mitochondrial bioenergetics associated with menopause.NEW & NOTEWORTHY The menopausal transition, marked by declining estrogen levels, alters cognition, neuroplasticity, and brain metabolism. Although hormone therapy benefits cognition, its molecular effects on the brain remain unclear. Using whole-brain proteomics in aged ovariectomized (OVX) mice with or without estrogen treatment, we found that OVX reduced proteins linked to synaptogenesis and mitochondrial metabolism. Estrogen reversed these declines, restoring pathways supporting neuronal signaling and energy balance, identifying estrogen-regulated proteins critical for maintaining brain health during menopause.

Animals↗

PubMed2025

Human development, inequality, and their associations with brain structure across 29 countries.

BACKGROUND: The macro-social and environmental conditions in which people live, such as the level of a country's development or inequality, are associated with brain-related disorders. However, the relationship between these systemic environmental factors and the brain remains unclear. We aimed to determine the association between the level of development and inequality of a country and the brain structure of healthy adults. METHODS: We conducted a cross-sectional study pooling brain imaging (T1-based) data from 145 magnetic resonance imaging (MRI) studies in 7,962 healthy adults (4,110 women) in 29 different countries. We used a meta-regression approach to relate the brain structure to the country's level of development and inequality. RESULTS: Higher human development was consistently associated with larger hippocampi and more expanded global cortical surface area, particularly in frontal areas. Increased inequality was most consistently associated with smaller hippocampal volume and thinner cortical thickness across the brain. CONCLUSIONS: Our results suggest that the macro-economic conditions of a country are reflected in its inhabitants' brains and may explain the different incidence of brain disorders across the world. The observed variability of brain structure in health across countries should be considered when developing tools in the field of personalized or precision medicine that are intended to be used across the world.

Humans↗

PubMed2026

Unraveling the Enigma of Melanoma Brain Metastasis: New Molecular Insights and Therapeutic Directions.

Melanoma, a highly aggressive and metastatic cancer, poses significant challenges due to its propensity to spread to distant organs, with brain metastasis representing a particularly devastating complication. This review synthesizes preclinical and clinical evidence on the molecular, cellular, and microenvironmental mechanisms driving melanoma metastasis, emphasizing mechanisms of blood-brain barrier traversal, tumor-stroma co-option, and brain-specific genomic and transcriptional programs. We summarize advances in therapeutic strategies to combat melanoma brain metastasis including novel small molecules, immunotherapies, and combination approaches tailored for brain metastases. The review also highlights the immunological landscape of the brain, translational models, and multidisciplinary clinical management strategies. Finally, we identify critical research gaps, including the need for brain metastasis-specific clinical trials, AI-driven predictive models, and preventive strategies, to guide future efforts in improving outcomes for patients with melanoma brain metastasis.

Humans↗

PubMed2026

Accurate quantification of canine mitochondrial DNA copy number from canine blood and brain samples.

Acute brain injury is difficult to evaluate in veterinary medicine and tools to investigate the potential involvement of mitochondrial involvement are limited. The brain is highly enriched in mitochondria and contains thousands of copies of mitochondrial DNA (mtDNA) per cell, but robust methods for quantifying mitochondrial DNA copy number (mtDNA-CN) in canine tissues are lacking. We describe the development of a quantitative real-time PCR assay for absolute measurement of mtDNA-CN which was validated in canine blood and brain tissue. To minimize amplification of nuclear mitochondrial insertion sequences (NumtS) and repetitive regions, species-specific oligonucleotide primers were designed following in silico genomic filtering. The assay was applied to a small pilot cohort comprising blood samples from dogs with and without acute brain injury (n = 4-6 per group) and cerebral cortex samples (n = 1 per group) to assess feasibility and biological plausibility. In non-brain injury dogs, blood mtDNA-CN ranged from 98 to 288 copies per nuclear genome (mean 193 ± 72), while values in brain-injured cases ranged from 163 to 228 copies per genome (mean 200 ± 33). Cerebral cortex samples exhibited higher mtDNA-CN than blood, consistent with known tissue-specific mitochondrial enrichment. In a single brain-injured case with serial sampling, mtDNA-CN increased over five days. This study presents a validated assay and pilot data for mtDNA-CN quantification in canine samples. While not powered for biomarker evaluation, this method may enable future studies of mitochondrial dynamics in canine brain injury and metabolic disease.

Animals↗

PubMed2026

SIRT1 in brain aging: molecular mechanisms and therapeutic potential of pharmacological and natural modulators.

Aging is a multifactorial process affects different tissues and organs and is modulated by genetic and environmental factors. In aging, the frequency of DNA repair errors and genomic instability are augmented. Depletion of endogenous antioxidant capacity during aging promotes the development of oxidative stress which triggers oxidative stress-induced DNA injury. Brain aging is manifested by cognitive impairment and memory disorders. Development of neuronal senescence is the major pathway in the progression of brain aging. Silent information regulator sirtuin 1 (SIRT1) is a class III histone deacetylase plays a critical role in genomic stability during aging. SIRT1 is highly expressed in specific brain regions involved in energy expenditure and metabolic activity that is necessary for brain development and control of brain senescence. Therefore, SIRT1 may have neuroprotective effects against brain aging and related neurodegenerative diseases. This narrative review aims to critically evaluate the role of SIRT1 in brain aging and to summarize current evidence on compounds that directly or indirectly modulate SIRT1 activity, with a focus on their mechanistic pathways and potential therapeutic implications. Findings of the present review highlighted that SIRT1 activators such as resveratrol, metformin and statins have neuroprotective effects against brain aging by regulating inflammatory and oxidative stress disorders through modulation of downstream signaling pathways.

Humans↗

PubMed2026

Epigenetic regulation of fatty acid chain elongation in MAFLD and its implications in the liver-brain axis dysfunction.

Lipid metabolism plays a crucial role in cellular health and physiology by acting as an energy storehouse, cell membrane component, brain development and signaling molecules. Crucial steps to metabolize dietary fat take place within the hepatic tissue. Any abnormalities in the hepatic fatty metabolic pathways cause abnormal accumulation of lipid inside the liver, causing MAFLD, ranging from simple steatosis to more complex steatohepatitis and fibrosis. During high-fat-diet-induced hepatic inflammation, systemic proinflammatory cytokines disrupt the blood-brain barrier, resulting in neuroinflammation, cognitive impairment, brain damage and even neurodegeneration. Further, during this altered metabolic scenario, circulating metabolites pass through the impaired BBR and deregulate the epigenetic landscape of the central nervous system. Thus, it becomes crucial to understand the epi-metabolic crosstalk between two crucial organs of our body: the liver and the brain. Here in this chapter, we demonstrate the approach that we are using in our laboratory to study the epigenetic reprogramming in the context of metabolic gene expression in the liver, which is the causal for life style disorders like MAFLD. Remarkably, we intend to understand how liver dysfunction can have an implication in the brain function. Here, we discuss the concept of developing a diet-induced steatosis and steatohepatitis mouse model to understand the disease progression and its interconnection with brain physiology. Further, we also demonstrate 2D and 3D cell culture models to study the liver-brain cross-talk in greater molecular detail. Collectively, these approaches can provide a template for studying the role of epi-metabolic cross-talk in liver-guided brain dysfunction upon MAFLD.

Animals↗