School of Medicine

Glycation is a class of modifications arising from non-enzymatic reactions of reducing sugars with proteins, lipids, and/or DNA, generating advanced glycation end-products (AGEs). AGEs are linked to many age-related comorbidities. In response to HIV-1 infection, activated T-cells and macrophages shift their predominate metabolism from oxidative phosphorylation to glycolysis. Increased glycolytic flux enhances AGE formation, which may increase age-related comorbidities. In this prospective, multicenter cohort study of antiretroviral therapy treated people with HIV, we explored predictive associations by baseline plasma AGE concentrations and their corresponding detoxification metabolites, with incident comorbidities and mortality. AGEs included dicarbonyl sugars: 3-deoxyglucosone, glyoxal, and methylglyoxal. Methylglyoxal-derived metabolites included carboxyethyl-arginine, carboxyethyl-lysine, and methylglyoxal hydroimidazolone-1. Detoxification metabolites included reduced and oxidized glutathione, and the glyoxalase cycle products lactoyl-glutathione and lactoyl-Lysine modified proteins. Plasma was collected at study entry, in the fasting state, and assayed by liquid chromatography-mass spectroscopy. Incident clinical outcomes included diabetes, chronic kidney disease, hypertension, neurocognitive impairment, peripheral neuropathy, frailty, fractures, recurrent falls, and all-cause mortality. Among 376 participants, higher baseline plasma concentrations of methylglyoxal derived AGEs predicted increased risks of diabetes, chronic kidney disease, and recurrent falls, while higher 3-deoxyglucosone predicted an increased risk of peripheral neuropathy. By contrast, higher baseline concentrations of reduced or oxidized glutathione, lactoyl-glutathione, and/or lactoyl-Lysine modified proteins predicted lower risks of diabetes, neurocognitive impairment, frailty, fractures, recurrent falls, and all-cause mortality. These findings support growing experimental evidence of the potential to mitigate age-related declines by interventions that reduce glycation or increase glutathione.

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MEF2C is a critical transcription factor in neurodevelopment, whose loss-of-function mutation in humans results in MEF2C haploinsufficiency syndrome (MHS), a severe form of autism spectrum disorder (ASD)/intellectual disability (ID). Despite prior animal studies of MEF2C heterozygosity to mimic MHS, MHS-specific mutations have not been investigated previously, particularly in a human context as hiPSCs afford. Here, for the first time, we use patient hiPSC-derived cerebrocortical neurons and cerebral organoids to characterize MHS deficits. Unexpectedly, we found that decreased neurogenesis was accompanied by activation of a micro-(mi)RNA-mediated gliogenesis pathway. We also demonstrate network-level hyperexcitability in MHS neurons, as evidenced by excessive synaptic and extrasynaptic activity contributing to excitatory/inhibitory (E/I) imbalance. Notably, the predominantly extrasynaptic (e)NMDA receptor antagonist, NitroSynapsin, corrects this aberrant electrical activity associated with abnormal phenotypes. During neurodevelopment, MEF2C regulates many ASD-associated gene networks, suggesting that treatment of MHS deficits may possibly help other forms of ASD as well.

The catecholamine neurotransmitter dopamine is classically known for regulation of central nervous system (CNS) functions such as reward, movement, and cognition. Increasing evidence also indicates that dopamine regulates critical functions in peripheral organs and is an important immunoregulatory factor. We have previously shown that dopamine increases NF-κB activity, inflammasome activation, and the production of inflammatory cytokines such as IL-1β in human macrophages. As myeloid lineage cells are central to the initiation and resolution of acute inflammatory responses, dopamine-mediated dysregulation of these functions could both impair the innate immune response and exacerbate chronic inflammation. However, the exact pathways by which dopamine drives myeloid inflammation are not well defined, and studies in both rodent and human systems indicate that dopamine can impact the production of inflammatory mediators through both D1-like dopamine receptors (DRD1, DRD5) and D2-like dopamine receptors (DRD2, DRD3, and DRD4). Therefore, we hypothesized that dopamine-mediated production of IL-1β in myeloid cells is regulated by the ratio of different dopamine receptors that are activated. Our data in primary human monocyte-derived macrophages (hMDM) indicate that DRD1 expression is necessary for dopamine-mediated increases in IL-1β, and that changes in the expression of DRD2 and other dopamine receptors can alter the magnitude of the dopamine-mediated increase in IL-1β. Mature hMDM have a high D1-like to D2-like receptor ratio, which is different relative to monocytes and peripheral blood mononuclear cells (PBMCs). We further confirm in human microglia cell lines that a high ratio of D1-like to D2-like receptors promotes dopamine-induced increases in IL-1β gene and protein expression using pharmacological inhibition or overexpression of dopamine receptors. RNA-sequencing of dopamine-treated microglia shows that genes encoding functions in IL-1β signaling pathways, microglia activation, and neurotransmission increased with dopamine treatment. Finally, using HIV as an example of a chronic inflammatory disease that is substantively worsened by comorbid substance use disorders (SUDs) that impact dopaminergic signaling, we show increased effects of dopamine on inflammasome activation and IL-1β in the presence of HIV in both human macrophages and microglia. These data suggest that use of addictive substances and dopamine-modulating therapeutics could dysregulate the innate inflammatory response and exacerbate chronic neuroimmunological conditions like HIV. Thus, a detailed understanding of dopamine-mediated changes in inflammation, in particular pathways regulating IL-1β, will be critical to effectively tailor medication regimens.

OBJECTIVES: Tools are needed to evaluate the risk of developing Parkinson disease (PD) in at-risk populations. In this study, we examine differences in alpha-synuclein seed amplification assay (αSyn-SAA) qualitative results and amplification parameters between nonmanifesting carriers (NMCs) of PD-related pathogenic variants, prodromal PD, and PD and the risk of developing a synucleinopathy in participants with prodromal PD. METHODS: Cross-sectional and longitudinal CSF αSyn-SAA results from participants in the Parkinsons Progression Markers Initiative were analyzed. αSyn-SAA positivity and amplification parameters (maximum fluorescence [Fmax], time-to-threshold [TTT], time-to-50% Fmax [T50], and area under the curve [AUC]) were compared between NMCs, participants with prodromal PD, and participants with PD, and their relationship with the likelihood of phenoconversion in participants with prodromal PD was investigated. RESULTS: Samples from 1,027 participants were analyzed (159 healthy controls [HCs], 247 NMCs, 96 participants with prodromal PD, and 525 participants with PD). TTT and T50 were faster, and AUC was higher in αSyn-SAA+ participants with prodromal PD and PD than αSyn-SAA+ NMCs and HC participants (Kruskal-Wallis χ2 = 4.15-13.96, p < 0.0002-0.04). Participants with prodromal PD with positive αSyn-SAA tests and faster TTT had higher rates of phenoconversion (log-rank p = 0.001 and log-rank test-for-trend p < 0.0001). There were no changes in 48 participants with prodromal PD with longitudinal assays. DISCUSSION: αSyn-SAA positivity and faster seed amplification are associated with a greater risk of developing PD in at-risk individuals and may aid in predicting phenoconversion.

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Although the corticobasal syndrome was originally most closely linked with the pathology of corticobasal degeneration, the 2013 Armstrong clinical diagnostic criteria, without the addition of aetiology-specific biomarkers, have limited positive predictive value for identifying corticobasal degeneration pathology in life. Autopsy studies demonstrate considerable pathological heterogeneity in corticobasal syndrome, with corticobasal degeneration pathology accounting for only ∼50% of clinically diagnosed individuals. Individualized disease stage and progression modelling of brain changes in corticobasal syndrome may have utility in predicting this underlying pathological heterogeneity, and in turn improve the design of clinical trials for emerging disease-modifying therapies. The aim of this study was to jointly model the phenotypic and temporal heterogeneity of corticobasal syndrome, to identify unique imaging subtypes based solely on a data-driven assessment of MRI atrophy patterns and then investigate whether these subtypes provide information on the underlying pathology. We applied Subtype and Stage Inference, a machine learning algorithm that identifies groups of individuals with distinct biomarker progression patterns, to a large cohort of 135 individuals with corticobasal syndrome (52 had a pathological or biomarker defined diagnosis) and 252 controls. The model was fit using volumetric features extracted from baseline T1-weighted MRI scans and then used to subtype and stage follow-up scans. The subtypes and stages at follow-up were used to validate the longitudinal consistency of the baseline subtype and stage assignments. We then investigated whether there were differences in associated pathology and clinical phenotype between the subtypes. Subtype and Stage Inference identified at least two distinct and longitudinally stable spatiotemporal subtypes of atrophy progression in corticobasal syndrome; four-repeat-tauopathy confirmed cases were most commonly assigned to the Subcortical subtype (83% of individuals with progressive supranuclear palsy pathology and 75% of individuals with corticobasal-degeneration pathology), whilst those with Alzheimer's pathology were most commonly assigned to the Fronto-parieto-occipital subtype (81% of individuals). Subtype assignment was stable at follow-up (98% of cases), and individuals consistently progressed to higher stages (100% stayed at the same stage or progressed), supporting the model's ability to stage progression. By jointly modelling disease stage and subtype, we provide data-driven evidence for at least two distinct and longitudinally stable spatiotemporal subtypes of atrophy in corticobasal syndrome that are associated with different underlying pathologies. In the absence of sensitive and specific biomarkers, accurately subtyping and staging individuals with corticobasal syndrome at baseline has important implications for screening on entry into clinical trials, as well as for tracking disease progression.

GGGGCC repeat expansions in C9orf72 are a common genetic cause of amyotrophic lateral sclerosis in people of European ancestry; however, substantial variability in the penetrance of the mutation, age at disease onset, and clinical presentation can complicate diagnosis and prognosis. The repeat expansion is bidirectionally transcribed in the sense and antisense directions into repetitive RNAs and translated into dipeptide repeat proteins, and both accumulate in the cortex, cerebellum, and the spinal cord. Furthermore, neuropathological aggregates of phosphorylated TDP-43 are observed in motor cortex and other cortical regions, and in the spinal cord of patients at autopsy. C9orf72 repeat expansions can also cause frontotemporal dementia. The GGGGCC repeat induces a complex interplay of loss-of-function and gain-of-function pathological mechanisms. Clinical trials using antisense oligonucleotides to target the GGGGCC repeat RNA have not been successful, potentially because they only target a single gain-of-function mechanism. Novel therapeutic approaches targeting the DNA repeat expansion, multiple repeat-derived RNA species, or downstream targets of TDP-43 dysfunction are, however, on the horizon, together with the development of diagnostic and prognostic biomarkers.

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Episodic memory relies on the formation and retrieval of content-specific memory traces. In addition to their veridical reactivation, previous studies have indicated that traces may undergo substantial transformations. However, the exact time course and regional distribution of reinstatement and transformation during recognition memory have remained unclear. We applied representational similarity analysis to human intracranial electroencephalography to track the spatiotemporal dynamics underlying the reinstatement and transformation of memory traces. Specifically, we examined how reinstatement and transformation of item-specific representations across occipital, ventral visual, and lateral parietal cortices contribute to successful memory formation and recognition. Our findings suggest that reinstatement in temporal cortex and transformation in parietal cortex coexist and provide complementary strategies for recognition. Further, we find that generalization and differentiation of neural representations contribute to memory and probe memory-specific correspondence with deep neural network (DNN) model features. Our results suggest that memory formation is particularly supported by generalized and mnemonic representational formats beyond the visual features of a DNN.