[18F]FDG PET metabolic patterns in mesial temporal lobe epilepsy with different pathological types

Decomposed FDG PET-based phenotypic heterogeneity predicting clinical prognosis and decision-making in temporal lobe epilepsy patients

OBJECTIVE

This study utilized a data-driven Bayesian model to automatically identify distinct latent disease factors represented by overlapping glucose metabolism patterns from 18F-Fluorodeoxyglucose PET (18F-FDG PET) to analyze heterogeneity among patients with TLE.

METHODS

We employed unsupervised machine learning to estimate latent disease factors from 18F-FDG PET scans, representing whole-brain glucose metabolism patterns in seventy patients with TLE. We estimated the extent to which multiple distinct factors were expressed within each participant and analyzed their relevance to epilepsy burden, including seizure onset, duration, and frequency. Additionally, we established a predictive model for clinical prognosis and decision-making.

RESULTS

We identified three latent disease factors: hypometabolism in the unilateral temporal lobe and hippocampus (factor 1), hypometabolism in bilateral prefrontal lobes (factor 2), and hypometabolism in bilateral temporal lobes (factor 3), variably co-expressed within each patient. Factor 3 demonstrated the strongest negative correlation with the age of onset and duration (r =  - 0.33, - 0.38 respectively, P < 0.05). The supervised classifier, trained on latent disease factors for predicting patient-specific antiepileptic drug (AED) responses, achieved an area under the curve (AUC) of 0.655. For post-surgical seizure outcomes, the AUC was 0.857, and for clinical decision-making, it was 0.965.

CONCLUSIONS

Decomposing 18F-FDG PET-based phenotypic heterogeneity facilitates individual-level predictions relevant to disease monitoring and personalized therapeutic strategies.

Individual cerebellar metabolic connectome in patients with MTLE and NTLE associated with surgical prognosis

PURPOSE

This study aimed to comprehensively explore the different metabolic connectivity topological changes in MTLE and NTLE, as well as their association with surgical outcomes.

METHODS

This study enrolled a cohort of patients with intractable MTLE and NTLE. Each individual's metabolic connectome, as determined by Kullback-Leibler divergence similarity estimation for the [18F]FDG PET image, was employed to conduct a comprehensive analysis of the cerebral metabolic network. Alterations in network connectivity were assessed by extracting and evaluating the strength of edge and weighted connectivity. By utilizing these two connectivity strength metrics with the cerebellum, we explored the network properties of connectivity and its association with prognosis in surgical patients.

RESULTS

Both MTLE and NTLE patients exhibited substantial alterations in the connectivity of the metabolic network at the edge and nodal levels (p < 0.01, FDR corrected). The key disparity between MTLE and NTLE was observed in the cerebellum. In MTLE, there was a predominance of increased connectivity strength in the cerebellum. Whereas, a decrease in cerebellar connectivity was identified in NTLE. It was found that in MTLE, higher edge connectivity and weighted connectivity strength in the contralateral cerebellar hemisphere correlated with improved surgical outcomes. Conversely, in NTLE, a higher edge metabolic connectivity strength in the ipsilateral cerebellar hemisphere suggested a worse surgical prognosis.

CONCLUSION

The cerebellum exhibits distinct topological characteristics in the metabolic networks between MTLE and NTLE. The hyper- or hypo-metabolic connectivity in the cerebellum may be a prognostic biomarker of surgical prognosis, which might aid in therapeutic decision-making for TLE individuals.

Is there a biochemical basis for purinergic P2X3 and P2X4 receptor antagonists to be considered as anti-seizure medications?

Patients with epilepsy require improved medications. Purinergic receptors were identified as late as 1976 and are slowly emerging as potential drug targets for the discovery of antiseizure medications. While compounds interacting with these receptors have been approved for use as medicines (e.g., gefapixant for cough) and continue to be explored for a number of diseases (e.g., pain, cancer), there have been no purinergic receptor antagonists that have been advanced for epilepsy. There are very few studies on the channel conducting receptors, P2X3 and P2X4, that suggest their possible role in seizure generation or control. However, the limited data available provides some compelling reasons to believe that they could be valuable antiseizure medication drug targets. The data implicating P2X3 and P2X4 receptors in epilepsy includes the role played by ATP in neuronal excitability and seizures, receptor localization, increased receptor expression in epileptic brain, the involvement of these receptors in seizure-associated inflammation, crosstalk between these purinergic receptors and neuronal processes involved in seizures (GABAergic and glutamatergic neurotransmission), and the significant attenuation of seizures and seizure-like activity with P2X receptor blockade. The discovery of new and selective antagonists for P2X3 and P2X4 receptors is ongoing, armed with new structural data to guide rational design. The availability of safe, brain-penetrant compounds will likely encourage the clinical exploration of epilepsy as a disease entity.

In severe ADNC, hippocampi with comorbid LATE-NC and hippocampal sclerosis have substantially more astrocytosis than those with LATE-NC or hippocampal sclerosis alone

Limbic-predominant age-related TDP-43 encephalopathy neuropathologic change (LATE-NC) and hippocampal sclerosis of aging (HS-A) pathologies are found together at autopsy in ∼20% of elderly demented persons. Although astrocytosis is known to occur in neurodegenerative diseases, it is currently unknown how the severity of astrocytosis is correlated with the common combinations of pathologies in aging brains. To address this knowledge gap, we analyzed a convenience sample of autopsied subjects from the University of Kentucky Alzheimer's Disease Research Center community-based autopsy cohort. The subjects were stratified into 5 groups (n = 51 total): pure ADNC, ADNC + LATE-NC, ADNC + HS-A, ADNC + LATE-NC + HS-A, and low-pathology controls. Following GFAP immunostaining and digital slide scanning with a ScanScope, we measured GFAP-immunoreactive astrocytosis. The severities of GFAP-immunoreactive astrocytosis in hippocampal subfield CA1 and subiculum were compared between groups. The group with ADNC + LATE-NC + HS-A had the most astrocytosis as operationalized by either any GFAP+ or strong GFAP+ immunoreactivity in both CA1 and subiculum. In comparison to that pathologic combination, ADNC + HS or ADNC + LATE-NC alone showed lower astrocytosis. Pure ADNC had only marginally increased astrocytosis in CA1 and subiculum, in comparison to low-pathology controls. We conclude that there appeared to be pathogenetic synergy such that ADNC + LATE-NC + HS-A cases had relatively high levels of astrocytosis in the hippocampal formation.