Whole Genome Sequence Data From Captive Baboons Implicate RBFOX1 in Epileptic Seizure Risk

Are we there yet? A critical evaluation of sudden and unexpected death in epilepsy models

Although animal models have helped to elaborate meaningful hypotheses about the pathophysiology of sudden and unexpected death in epilepsy (SUDEP), specific prevention strategies are still lacking, potentially reflecting the limitations of these models and the intrinsic difficulties of investigating SUDEP. The interpretation of preclinical data and their translation to diagnostic and therapeutic developments in patients thus require a high level of confidence in their relevance to model the human situation. Preclinical models of SUDEP are heterogeneous and include rodent and nonrodent species. A critical aspect is whether the animals have isolated seizures exclusively induced by a specific trigger, such as models where seizures are elicited by electrical stimulation, pharmacological intervention, or DBA mouse strains, or whether they suffer from epilepsy with spontaneous seizures, with or without spontaneous SUDEP, either of nongenetic epilepsy etiology or from genetically based developmental and epileptic encephalopathies. All these models have advantages and potential disadvantages, but it is important to be aware of these limitations to interpret data appropriately in a translational perspective. The majority of models with spontaneous seizures are of a genetic basis, whereas SUDEP cases with a genetic basis represent only a small proportion of the total number. In almost all models, cardiorespiratory arrest occurs during the course of the seizure, contrary to that in patients observed at the time of death, potentially raising the issue of whether we are studying models of SUDEP or models of periseizure death. However, some of these limitations are impossible to avoid and can in part be dependent on specific features of SUDEP, which may be difficult to model. Several preclinical tools are available to address certain gaps in SUDEP pathophysiology, which can be used to further validate current preclinical models.

Population genetics of marmosets in Asian primate research centers and loci associated with epileptic risk revealed by whole-genome sequencing

The common marmoset ( Callithrix jacchus) has emerged as a valuable nonhuman primate model in biomedical research with the recent release of high-quality reference genome assemblies. Epileptic marmosets have been independently reported in two Asian primate research centers. Nevertheless, the population genetics within these primate centers and the specific genetic variants associated with epilepsy in marmosets have not yet been elucidated. Here, we characterized the genetic relationships and risk variants for epilepsy in 41 samples from two epileptic marmoset pedigrees using whole-genome sequencing. We identified 14 558 184 single nucleotide polymorphisms (SNPs) from the 41 samples and found higher chimerism levels in blood samples than in fingernail samples. Genetic analysis showed fourth-degree of relatedness among marmosets at the primate centers. In addition, SNP and copy number variation (CNV) analyses suggested that the WW domain-containing oxidoreductase ( WWOX) and Tyrosine-protein phosphatase nonreceptor type 21 ( PTPN21) genes may be associated with epilepsy in marmosets. Notably, KCTD18-like gene deletion was more common in epileptic marmosets than control marmosets. This study provides valuable population genomic resources for marmosets in two Asian primate centers. Genetic analyses identified a reasonable breeding strategy for genetic diversity maintenance in the two centers, while the case-control study revealed potential risk genes/variants associated with epilepsy in marmosets.

Genome-wide association studies of human and rat BMI converge on synapse, epigenome, and hormone signaling networks

A vexing observation in genome-wide association studies (GWASs) is that parallel analyses in different species may not identify orthologous genes. Here, we demonstrate that cross-species translation of GWASs can be greatly improved by an analysis of co-localization within molecular networks. Using body mass index (BMI) as an example, we show that the genes associated with BMI in humans lack significant agreement with those identified in rats. However, the networks interconnecting these genes show substantial overlap, highlighting common mechanisms including synaptic signaling, epigenetic modification, and hormonal regulation. Genetic perturbations within these networks cause abnormal BMI phenotypes in mice, too, supporting their broad conservation across mammals. Other mechanisms appear species specific, including carbohydrate biosynthesis (humans) and glycerolipid metabolism (rodents). Finally, network co-localization also identifies cross-species convergence for height/body length. This study advances a general paradigm for determining whether and how phenotypes measured in model species recapitulate human biology.

Development and validation of a copper-related gene prognostic signature in hepatocellular carcinoma

Introduction: Reliable biomarkers are in need to predict the prognosis of hepatocellular carcinoma (HCC). Whilst recent evidence has established the critical role of copper homeostasis in tumor growth and progression, no previous studies have dealt with the copper-related genes (CRGs) signature with prognostic potential in HCC. Methods: To develop and validate a CRGs prognostic signature for HCC, we retrospectively included 353 and 142 patients as the development and validation cohort, respectively. Copper-related Prognostic Signature (Copper-PSHC) was developed using differentially expressed CRGs with prognostic value. The hazard ratio (HR) and the area under the time-dependent receiver operating characteristic curve (AUC) during 3-year follow-up were utilized to evaluate the performance. Additionally, the Copper-PSHC was combined with age, sex, and cancer stage to construct a Copper-clinical-related Prognostic Signature (Copper-CPSHC), by multivariate Cox regression. We further explored the underlying mechanism of Copper-PSHC by analyzing the somatic mutation, functional enrichment, and tumor microenvironment. Potential drugs for the high-risk group were screened. Results: The Copper-PSHC was constructed with nine CRGs. Patients in the high-risk group demonstrated a significantly reduced overall survival (OS) (adjusted HR, 2.65 [95% CI, 1.83-3.84] and 3.30, [95% CI, 1.27-8.60] in the development and validation cohort, respectively). The Copper-PSHC achieved a 3-year AUC of 0.74 [95% CI, 0.67-0.82] and 0.71 [95% CI, 0.56-0.86] for OS in the development and validation cohort, respectively. Copper-CPSHC yield a 3-year AUC of 0.73 [95% CI, 0.66-0.80] and 0.72 [95% CI, 0.56-0.87] for OS in the development and validation cohort, respectively. Higher tumor mutation burden, downregulated metabolic processes, hypoxia status and infiltrated stroma cells were found for the high-risk group. Six small molecular drugs were screened for the treatment of the high-risk group. Conclusion: Copper-PSHC services as a promising tool to identify HCC with poor prognosis and to improve disease outcomes by providing potential clinical decision support in treatment.

Neuroimaging in the Epileptic Baboon

Characterization of baboon model of genetic generalized epilepsy (GGE) is driven both electroclinically and by successful adoption of neuroimaging platforms, such as magnetic resonance imaging (MRI) and positron emission tomography (PET). Based upon its phylogenetic proximity and similar brain anatomy to humans, the epileptic baboon provides an excellent translational model. Its relatively large brain size compared to smaller nonhuman primates or rodents, a gyrencephalic structure compared to lissencephalic organization of rodent brains, and the availability of a large pedigreed colony allows exploration of neuroimaging markers of diseases. Similar to human idiopathic generalized epilepsy (IGE), structural imaging in the baboon is usually normal in individual subjects, but gray matter volume/concentration (GMV/GMC) changes are reported by statistical parametric mapping (SPM) analyses. Functional neuroimaging has been effective for mapping the photoepileptic responses, the epileptic network, altered functional connectivity of physiological networks, and the effects of anti-seizure therapies. This review will provide insights into our current understanding the baboon model of GGE through functional and structural imaging.