Biology subjects

Perez de Arce, K.

Publications and source records attributed to Perez de Arce, K..

4 recordsLinked to original sources

bioRxiv2026

Discovery of GluA3 preferring AMPA receptor positive allosteric modulator BRD3290

Schizophrenia is a debilitating neuropsychiatric disease that lacks effective treatments for many symptom domains including negative, cognitive and sleep disturbances. Lack of clear disease etiology has hampered the development of new, effective treatments for the unmet needs of people with schizophrenia. Large scale human genetics have identified rare loss of function mutations that substantially increase risk of developing schizophrenia, including in GRIA3, the gene that encodes the GluA3 receptor subunit of the AMPA receptor (AMPAR). Several drug discovery programs have been aimed at developing AMPAR positive allosteric modulators (PAMs) as a novel treatment for schizophrenia. Despite intense drug discovery efforts, there are no FDA approved AMPAR PAMs. We therefore hypothesized that selectively targeting GluA3, the AMPAR subunit implicated by human genetics, could yield a safer and more effective AMPAR PAM for the potential treatment of schizophrenia. Using a combination of medicinal chemistry, in vitro, and in vivo studies, we discovered BRD3290, a GluA3-preferring AMPAR PAM with reasonable potency in heterologous cells, as well as favorable tolerability and brain exposure. Peripheral administration of BRD3290 engaged an established AMPAR PAM target engagement biomarker but did not improve performance of wildtype mice in the novel object recognition task (NOR), in contrast to the nonselective AMPAR PAM PF-4778574, which improved mouse NOR. These findings suggest that the GluA3 selectivity profile of BRD3290 was insufficient to enhance cognitive function in this mouse NOR paradigm. This work highlights the challenges of AMPAR subtype-selective modulation and provides molecular insights into the ability to develop subtype-selective AMPAR PAMs. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/740780v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@1577f62org.highwire.dtl.DTLVardef@16c1750org.highwire.dtl.DTLVardef@16eaef3org.highwire.dtl.DTLVardef@19fdb6f_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2022

A survey of proteomic variation across two ethnic groups in Nigeria and its relationship to obesity risk

Proteomic variation between individuals has immense potential for identifying novel drug targets and disease mechanisms. However, with high-throughput proteomic technologies still in their infancy, they have largely been applied in large majority European ancestry cohorts (e.g. the UK Biobank). An open question is the degree to which proteomic signatures seen in European and other groups mirror those seen in diverse populations, such as cohorts from Africa. Coupled with genetic information, we can also gain a better understanding of the role of genetic variants in the regulation of the proteome and subsequent disease mechanisms. To address the gap in our understanding of proteomic variation in individuals of African ancestry, we collected proteomic data from 176 individuals across two ethnic groups (Igbo and Yoruba) in Nigeria. These individuals were also stratified into high BMI (BMI > 30 kg/m2) and normal BMI (20 kg/m2 < BMI < 30 kg/m2) categories. We characterized differences in plasma protein abundance using the Olink Explore 1536 panel between high and normal BMI individuals, finding strong associations consistent with previously known signals in individuals of European descent. We additionally found 73 sentinel cis-pQTL in this dataset, with 21 lead cis-pQTL not observed in catalogs of variation from European-ancestry individuals. In summary, our study highlights the value of leveraging proteomic data in cohorts of diverse ancestry for investigating trait-specific mechanisms and discovering novel genetic regulators of the plasma proteome.

genomics↗

bioRxiv2022

Perturbations of a causal synaptic molecular network in autism and schizophrenia revealed with multiplexed imaging

The complex functions of neuronal synapses in the central nervous system depend on their tightly interacting, compartmentalized molecular network of hundreds of proteins spanning the pre- and post-synaptic sites. This biochemical system is implicated in the pathogenesis of autism spectrum disorders and schizophrenia, with identified common synaptopathologies and numerous risk genes associated with synaptic function. However, it remains unclear how the synaptic molecular network is altered in these disorders, and whether effects are common to distinct genetic perturbations. Here, we applied PRISM, a quantitative single-synapse multiplexed imaging technique, to systematically probe the effects of RNAi knockdown of 16 autism- and schizophrenia-associated genes on the simultaneous distribution of 10 synaptic proteins. This enabled the identification of novel phenotypes in synapse compositions and distributions. We applied Bayesian network inference to construct and validate a predictive model of causal hierarchical dependencies among eight proteins of the excitatory synapse. The resulting conditional dependence relationships could only be accessed via measurement which is both single-synapse and multiprotein, unique to PRISM. Finally, we show that central features of the network are similarly affected across distinct gene knockdowns. These results offer insight into the convergent molecular etiology of these debilitating, hereditary and highly polygenic disorders, as well as offering a novel, general framework for probing subcellular molecular networks.

neuroscience↗

bioRxiv2020

Molecular diversity of glutamatergic and GABAergic synapses from multiplexed fluorescence imaging

Neuronal synapses contain hundreds of different protein species important for regulating signal transmission. Characterizing differential expression profiles of proteins within synapses in distinct regions of the brain has revealed a high degree of synaptic diversity defined by unique molecular organization. Multiplexed imaging of in vitro neuronal culture models at single synapse resolution offers new opportunities for exploring synaptic reorganization in response to chemical and genetic perturbations. Here, we combine 12-color multiplexed fluorescence imaging with quantitative image analysis and machine learning to identify novel synaptic subtypes within excitatory and inhibitory synapses based on the expression profiles of major synaptic components. We characterize differences in the correlated expression of proteins within these subtypes and we examine how the distribution of these synapses is modified following induction of synaptic plasticity. Under chronic suppression of neuronal activity, phenotypic characterization revealed coordinated increases in both excitatory and inhibitory protein levels without changes in the distribution of synaptic subtypes, suggesting concerted events targeting glutamatergic and GABAergic synapses. Our results offer molecular insight into the mechanisms of synaptic plasticity.

neuroscience↗