J. Matthew Mahoney’s research while affiliated with The Jackson Laboratory and other places

Epilepsy, affecting millions globally, often leads to significant cognitive and psychiatric comorbidities, particularly in children. Anxiety and depression are particularly prevalent, with roughly a quarter of pediatric epilepsy patients having a comorbid diagnosis. Current treatments inadequately address these issues. Adrenocorticotropic hormone (ACTH), a melanocortin peptide, has shown promise in mitigating deficits after early-life seizures (ELS), potentially through mechanisms beyond its canonical action on the melanocortin 2 receptor. This study explores the hypothesis that recurrent ELS is associated with long-term anxiety and that treatment with ACTH can prevent this anxiety through a mechanism that involves the melanocortin 4 receptor (MC4R) in the brain. Our findings reveal that ACTH ameliorates anxiety-like behavior associated with ELS, without altering seizure parameters, in wild-type but not in male and female MC4R knock-out mice. Our findings also show that knocking-in MC4R in either neurons or astrocytes was able to rescue the anxiety-like behavior after ACTH treatment. Furthermore, our results show that ACTH normalizes important astrocytic proteins like glial fibrillary acidic protein and aquaporin-4 after ELS. This suggests that ACTH's beneficial effects on anxiety are mediated through MC4R activation in both neuronal and astrocytic populations. This study underscores the therapeutic potential of targeting MC4R as a treatment, highlighting its role in mitigating anxiety-like behaviors associated with ELS.

Systemic sclerosis (SSc) remains a challenging and enigmatic systemic autoimmune disease, owing to its complex pathogenesis, clinical and molecular heterogeneity, and the lack of effective disease-modifying treatments. Despite a century of research in SSc, the interconnections among microvascular dysfunction, autoimmune phenomena and tissue fibrosis in SSc remain unclear. The absence of validated biomarkers and reliable animal models complicates diagnosis and treatment, contributing to high morbidity and mortality. Advances in the past 5 years, such as single-cell RNA sequencing, next-generation sequencing, spatial biology, transcriptomics, genomics, proteomics, metabolomics, microbiome profiling and artificial intelligence, offer new avenues for identifying the early pathogenetic events that, once treated, could change the clinical history of SSc. Collaborative global efforts to integrate these approaches are crucial to developing a comprehensive, mechanistic understanding and enabling personalized therapies. Challenges include disease classification, clinical heterogeneity and the establishment of robust biomarkers for disease activity and progression. Innovative clinical trial designs and patient-centred approaches are essential for developing effective treatments. Emerging therapies, including cell-based and fibroblast-targeting treatments, show promise. Global cooperation, standardized protocols and interdisciplinary research are vital for advancing SSc research and improving patient outcomes. The integration of advanced research techniques holds the potential for important breakthroughs in the diagnosis, treatment and care of individuals with SSc.

Genetic variation leads to phenotypic variability in pluripotent stem cells that presents challenges for regenerative medicine. Although recent studies have investigated the impact of genetic variation on pluripotency maintenance and differentiation capacity, less is known about how genetic variants affecting the pluripotent state influence gene regulation in later stages of development. Here, we characterized expression of more than 12,000 genes in 127 donor-matched Diversity Outbred (DO) mouse embryonic stem cell (mESC) and neural progenitor cell (mNPC) lines. Quantitative trait locus (QTL) mapping identified 2,947 expression QTL (eQTL) unique to DO mNPCs and 1,113 eQTL observed in both mNPCs and mESCs with highly concordant allele effects. We mapped three eQTL hotspots on Chromosomes (Chrs) 1, 10, and 11 that were unique to mNPCs. Target genes of the Chr 1 hotspot were overrepresented for those involved in mRNA processing, DNA repair, chromatin organization, protein degradation, and cell cycle. Mediation analysis of the Chr 1 hotspot identified Rnf152 as the best candidate mediator expressed in mNPCs, while cross-cell type mediation using mESC gene expression along with partial correlation analysis strongly implicated genetic variant(s) affecting Pign expression in the mESC state as regulating the mNPC Chr 1 eQTL hotspot. Together these findings highlight that many local eQTL confer similar effects on gene expression in multiple cell states; distant eQTL in DO mNPCs are numerous and largely unique to that cell state, with many co-localizing to mNPC-specific hotspots; and mediation analysis across cell types suggests that expression of Pign early in development (mESCs) shapes the transcriptome of the more specialized mNPC state.

Network hypersynchrony is emerging as an important system-level mechanism underlying seizures, as well as cognitive and behavioural impairments, in children with structural brain abnormalities. We investigated patterns of single neuron action potential behaviour in 206 neurons recorded from tubers, transmantle tails of tubers and normal looking cortex in 3 children with tuberous sclerosis. The patterns of neuronal firing on a neuron-by-neuron (autocorrelation) basis did not reveal any differences as a function of anatomy. However, at the level of functional networks (cross-correlation), there is a much larger propensity towards hypersynchrony of tuber-tuber neurons than in neurons from any other anatomical site. This suggests that tubers are the primary drivers of adverse outcomes in children with tuberous sclerosis. Supplementary Information The online version contains supplementary material available at 10.1038/s41598-024-80634-5.

Fragile X Syndrome (FXS) is associated with autism spectrum symptoms that are associated with cognitive, learning, and behavioral challenges. We investigated how known molecular disruptions in the Fmr1 knockout (FMR-KO) rat model of FXS negatively impact hippocampal-prefrontal cortex (H-PFC) neural network activity and consequent behavior. Methods: FMR-KO and control rats underwent a battery of behavioral tests assessing sociability, memory, and anxiety. Single-unit electrophysiology recordings were then conducted to measure patterns of neural activity in H-PFC circuit. Advanced mathematical models were used to characterize the patterns that were then compared between groups using generalized linear mixed models. Results: FMR-KO rats demonstrated significant behavioral deficits in sociability, spatial learning, and anxiety, aligning with symptoms of ASD. At the neural level, these rats exhibited abnormal firing patterns in the H-PFC circuit that is critical for learning, memory, and social behavior. The neural networks in FMR-KO rats were also less densely connected and more fragmented, particularly in hippocampal-PFC correlated firing. These findings suggest that disruptions in neural network dynamics underlie the observed behavioral impairments in FMR-KO rats. Conclusion: FMR-KO significantly disrupts several characteristics of action potential firing in the H-PFC network, leading to deficits in social behavior, memory, and anxiety, as seen in FXS. This disruption is characterized by less organized and less resilient hippocampal-PFC networks. These findings suggest that therapeutic strategies aimed at normalizing neural dynamics, such as with brain stimulation, could potentially improve behavior and cognitive functions in autistic individuals.

Epilepsy, affecting millions globally, often leads to significant cognitive and psychiatric comorbidities, particularly in children. Anxiety and depression are particularly prevalent, with roughly a quarter of pediatric epilepsy patients having a comorbid diagnosis. Current treatments inadequately address these issues. Adrenocorticotropic hormone (ACTH), a melanocortin peptide, has shown promise in mitigating cognitive deficits after early life seizures (ELS), potentially through mechanisms beyond its canonical action on melanocortin 2 receptor (MC2R). This study explores the hypothesis that recurrent ELS is associated with long-term anxiety, and that treatment with ACTH can prevent this anxiety through a mechanism that involves melanocortin 4 receptors (MC4R) in the brain. Our findings reveal that ACTH ameliorates anxiety-like behavior associated with ELS, without altering seizure parameters, in wildtype (WT) mice but not in MC4R knockout (KO) mice. Our findings also show that knocking-in MC4R in either neurons or astrocytes was able to rescue the anxiety-like behavior after ACTH treatment. Further, our results show that ACTH normalizes important astrocytic proteins like Glial Fibrillary Acidic Protein (GFAP) and Aquaporin-4 (AQP4) after ELS. This suggests that ACTH beneficial effects on anxiety are mediated through MC4R activation in both neuronal and astrocytic populations. This study underscores the therapeutic potential of targeting MC4R in epilepsy treatment, highlighting its role in mitigating cognitive impairments and anxiety-like behaviors associated with ELS.

Although many genes are subject to local regulation, recent evidence suggests that complex distal regulation may be more important in mediating phenotypic variability. To assess the role of distal gene regulation in complex traits, we combined multi-tissue transcriptomes with physiological outcomes to model diet-induced obesity and metabolic disease in a population of 371 Diversity Outbred mice. Using a novel high-dimensional mediation analysis, we identified a composite transcriptome signature that summarized genetic effects on gene expression and explained 30% of the variation across all metabolic traits. The signature was heritable, interpretable in biological terms, and predicted obesity status from gene expression in an independently derived mouse cohort and multiple human studies. Transcripts contributing most strongly to this composite mediator frequently had complex, distal regulation distributed throughout the genome. These results suggest that trait-relevant variation in transcription is largely distally regulated, but is nonetheless identifiable, interpretable, and translatable across species.

Multiple sclerosis (MS) is a complex disease with significant heterogeneity in disease course and progression. Genetic studies have identified numerous loci associated with MS risk, but the genetic basis of disease progression remains elusive. To address this, we leveraged the Collaborative Cross (CC), a genetically diverse mouse strain panel, and experimental autoimmune encephalomyelitis (EAE). The thirty-two CC strains studied captured a wide spectrum of EAE severity, trajectory, and presentation, including severe-progressive, monophasic, relapsing remitting, and axial rotary (AR)-EAE, accompanied by distinct immunopathology. Sex differences in EAE severity were observed in six strains. Quantitative trait locus analysis revealed distinct genetic linkage patterns for different EAE phenotypes, including EAE severity and incidence of AR-EAE. Machine learning-based approaches prioritized candidate genes for loci underlying EAE severity (Abcc4 and Gpc6) and AR-EAE (Yap1 and Dync2h1). This work expands the EAE phenotypic repertoire and identifies novel loci controlling unique EAE phenotypes, supporting the hypothesis that heterogeneity in MS disease course is driven by genetic variation.

Background The modified Rodnan skin score (mRSS), used to measure dermal thickness in patients with systemic sclerosis (SSc), is agnostic to inflammation and vasculopathy. Previously, we demonstrated the potential of neural network-based digital pathology applied to stained skin biopsies from SSc patients as a quantitative outcome. We leveraged deep learning and histologic analyses of clinical trial biopsies to decipher SSc skin features ‘seen’ by artificial intelligence (AI). Methods Adults with diffuse cutaneous SSc (disease duration ≤ 6 years) enrolled in an open-label trial evaluating belumosudil underwent serial mRSS assessment and dorsal arm biopsies at week 0, 24 and 52/end of trial. Two blinded dermatopathologists independently scored stained sections [Masson’s trichrome, hematoxylin and eosin (H&E), CD3, CD34, CD8, α smooth muscle actin (αSMA)] for 16 published SSc dermal pathological parameters. We applied our previously published deep learning model to generate QIF signatures/biopsy and generated Fibrosis Scores. Associations between Fibrosis Score and mRSS (Spearman correlation); and between Fibrosis Score mRSS versus histologic parameters [odds ratios (OR)] were determined. Results Only ten patients were enrolled because the sponsor terminated the trial early. Median, interquartile range (IQR) for mRSS change (0–52 weeks) for the five participants with paired biopsies was − 2.5 (-11—7.5), and for the ten participants was − 2 (-9—7.5). The correlation between Fibrosis Score and mRSS was R = 0.3; p = 0.674. Per 1-unit mRSS change (0-52W), histologic parameters with the greatest associated changes were (OR, p-value): telangiectasia (2.01, 0.001), perivascular CD3+ (1.03, 0.015), and % of CD8 + among CD3+ (1.08, 0.031). Likewise, per 1-unit Fibrosis Score change, parameters with greatest changes were (OR, p-value): hyalinized collagen (1.1, < 0.001), subcutaneous (SC) fat loss (1.47, < 0.001), thickened intima (1.21, 0.005), and eccrine entrapment (1.14, 0.046). Conclusions Belumosudil was associated with a non-clinically meaningful improvement in mRSS. Fibrosis Score changes correlated with histologic feature changes (e.g., hyalinized collagen, SC fat loss) that were distinct from those associated with mRSS changes (e.g., telangiectasia, perivascular CD3+, and % of CD8 + among CD3+). These data suggest that AI applied to SSc biopsies may be useful for quantifying pathologic features of SSc beyond skin thickness.