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Biology subjects

Carrillo, F.

Publications and source records attributed to Carrillo, F..

6 recordsLinked to original sources

Rare variants alter mitochondrial lipid homeostasis and neuronal excitability in PD patient-derived dopaminergic neurons

Parkinsons disease (PD) exhibits substantial genetic heterogeneity, yet how combinations of rare variants converge on disease-relevant cellular mechanisms remains unclear. Here, we generated human induced pluripotent stem cell-derived dopaminergic neurons from PD patients carrying rare variants in recently implicated genes and performed integrated electrophysiological, proteomic, lipidomic, and genetic analyses. Patient-derived neurons showed reduced membrane capacitance and altered action potential firing, indicating impaired intrinsic excitability and synaptic dysfunction, with marked variability across genetic backgrounds. Multi-omics profiling revealed dysregulation of mitochondrial function, glycolysis, and oxidative phosphorylation, accompanied by extensive lipid remodeling, including increased fatty acids, acylcarnitines, and sphingolipids, and reduced gangliosides. These alterations were more pronounced in neurons harboring specific variant combinations in KIF21B, SLC6A3, HMOX2, TMEM175, and AIMP2. Integrative analyses uncovered coordinated protein-lipid changes linking mitochondrial dysfunction and membrane homeostasis. Notably, Calpastatin and CXCR4 were consistently dysregulated across PD neurons. Genetic association analyses in independent cohorts identified PD-associated variants in genes encoding dysregulated proteins, supporting the functional relevance of these pathways. Overall, our results define convergent and variant-specific mechanisms underlying PD and highlight candidate biomarkers and therapeutic targets.

neuroscience↗

Deep Brain Stimulation rescues the homeostasis disruption of circulating D- and L-amino acids level in men with Parkinson's Disease.

Recent evidence indicates a marked downregulation of circulating D- and L-amino acids involved in regulating glutamatergic NMDAR function in Parkinsons disease (PD) patients compared with matched controls. However, the extent to which disease progression and antiparkinsonian therapies contribute to this dysregulation remains unclear. To address these issues, in the present study we measured by High Performance Liquid Chromatography the concentrations of glutamatergic system-related D- and L-amino acids and their precursors in the plasma of male and female healthy controls (HC) and PD patients across three distinct clinical stages and treatment conditions: (1) early stage L-DOPA naive patients treated with MAO-B inhibitors; (2) mid-stage patients treated with L-DOPA; and (3) advanced stage patients receiving Deep Brain Stimulation in the subthalamic nucleus (STN-DBS) plus L-DOPA. Our results reveal notable reduction of circulating neuroactive D- and L-amino acids exclusively in male PD patients, while female patients exhibit a similar directional trend. In male patients, this dysregulation manifests early, with L-DOPA-naive individuals showing decreased plasma levels of L-glutamate and L-aspartate. In mid-stage L-DOPA-treated PD patients, amino acid reductions extend to L-alanine, L-serine, L-glutamine, L-asparagine, and L-threonine. Remarkably, in advanced PD patients, with a median disease duration of [~] 23 years, STN-DBS normalizes the blood concentrations of these amino acids to those observed in HC. In conclusion, our study highlights the potential of circulating D- and L-amino acid dysregulation as an early biomarker of PD and demonstrates that, in contrast to L-DOPA therapy, the STN-DBS confers systemic metabolic benefits even at advanced stages of the disease.

neuroscience↗

Tandem Mass Tag-Based High-Resolution LC-MS/MS identifies free D-aspartate-induced expression of proteins linked to schizophrenia and autism spectrum disorder

D-aspartate is an endogenous agonist of NMDA and mGlu5 receptors, with a distinctive spatiotemporal expression profile that peaks in the prenatal and early postnatal brain. This suggests a critical role for D-aspartate metabolism in modulating neurodevelopmental processes linked to glutamatergic neurotransmission. However, the precise mechanisms through which D-aspartate exerts its effects remain unclear. To elucidate the molecular pathways orchestrated by early D-aspartate signalling, we employed a knockin mouse model characterized by constitutive D-aspartate depletion due to the prenatal expression of its degradative enzyme, D-aspartate oxidase. Using an advanced quantitative proteomic approach based on Tandem Mass Tag isobaric labelling and nano-liquid chromatography coupled with high-resolution tandem mass spectrometry, we investigated the proteomic variations induced by D-aspartate depletion during postnatal brain development comparing Ddo knockin mice with their wild-type littermates. Our findings reveal that D-aspartate modulates the neonatal expression of proteins involved in glutamatergic neurotransmission, nervous system development, and cytoskeleton organization. Moreover, proteomic analysis identified a subset of D-aspartate-regulated proteins mapping molecular pathways associated with autism spectrum disorder and schizophrenia. These findings offer new perspectives on the complex protein networks influenced by D-aspartate metabolism in the developing brain and highlight its potential impact on cerebral function in health and psychiatric disorders.

biochemistry↗

Natural language signatures of psilocybin microdosing

Serotonergic psychedelics are being studied as novel treatments for mental health disorders and as facilitators of improved well-being, mental function and creativity. Recent studies have found mixed results concerning the effects of low doses of psychedelics ("microdosing") on these domains. However, microdosing is generally investigated using instruments designed to assess larger doses of psychedelics, which might lack sensitivity and specificity for this purpose. Following a double-blind and placebo-controlled experimental design, we explored natural language as a resource to identify speech produced under the acute effects of psilocybin microdoses, focusing on variables known to be affected by higher doses: verbosity, semantic variability and sentiment scores. Except for semantic variability, these metrics presented significant differences between a typical active microdose of 0.5 g of psilocybin mushrooms and an inactive placebo condition. Moreover, machine learning classifiers trained using these metrics were capable of distinguishing between conditions with high accuracy (AUC{approx}0.8). Our results constitute first proof that low doses of serotonergic psychedelics can be identified from unconstrained natural speech, with potential for widely applicable, affordable, and ecologically valid monitoring of microdosing schedules.

pharmacology and toxicology↗

Over eight hundred cannabis strains characterized by the relationship between their psychoactive effects, perceptual profiles, and chemical compositions

BackgroundCommercially available cannabis strains have multiplied in recent years as a consequence of regional changes in legislation for medicinal and recreational use. Lack of a standardized system to label plants and seeds hinders the consistent identification of particular strains with their elicited psychoactive effects. The objective of this work was to leverage information extracted from large databases to improve the identification and characterization of cannabis strains.\n\nMethodsWe analyzed a large publicly available dataset where users freely reported their experiences with cannabis strains, including different subjective effects and flavour associations. This analysis was complemented with information on the chemical composition of a subset of the strains. Both supervised and unsupervised machine learning algorithms were applied to classify strains based on self-reported and objective features.\n\nResultsMetrics of strain similarity based on self-reported effect and flavour tags allowed machine learning classification into three major clusters corresponding to Cannabis sativa, Cannabis indica, and hybrids. Synergy between terpene and cannabinoid content was suggested by significative correlations between psychoactive effect and flavour tags. The use of predefined tags was validated by applying semantic analysis tools to unstructured written reviews, also providing breed-specific topics consistent with their purported medicinal and subjective effects. While cannabinoid content was variable even within individual strains, terpene profiles matched the perceptual characterizations made by the users and could be used to predict associations between different psychoactive effects.\n\nConclusionsOur work represents the first data-driven synthesis of self-reported and chemical information in a large number of cannabis strains. Since terpene content is robustly inherited and less influenced by environmental factors, flavour perception could represent a reliable marker to predict the psychoactive effects of cannabis. Our novel methodology contributes to meet the demands for reliable strain classification and characterization in the context of an ever-growing market for medicinal and recreational cannabis.

neuroscience↗

The genetic architecture of Parkinson disease in Spain: characterizing population-specific risk, differential haplotype structures, and providing etiologic insight

BackgroundThe Iberian Peninsula stands out as having variable levels of population admixture and isolation, making Spain an interesting setting for studying the genetic architecture of neurodegenerative diseases.\n\nObjectivesTo perform the largest Parkinson disease (PD) genome-wide association study (GWAS) restricted to a single country.\n\nMethodsWe performed a GWAS for both risk of PD and age-at-onset (AAO) in 7,849 Spanish individuals. Further analyses included population-specific risk haplotype assessments, polygenic risk scoring through machine learning, Mendelian randomization of expression and methylation data to gain insight into disease-associated loci, heritability estimates, genetic correlations and burden analyses.\n\nResultsWe identified a novel population-specific GWAS signal at PARK2 associated with AAO. We replicated four genome-wide independent signals associated with PD risk, including SNCA, LRRK2, KANSL1/MAPT and HLA-DQB1. A significant trend for smaller risk haplotypes at known loci was found compared to similar studies of non-Spanish origin. Seventeen PD-related genes showed functional consequence via two-sample Mendelian randomization in expression and methylation datasets. Long runs of homozygosity at 28 known genes/loci were found to be enriched in cases versus controls.\n\nConclusionsOur data demonstrate the utility of the Spanish risk haplotype substructure for future fine-mapping efforts, showing how leveraging unique and diverse population histories can benefit genetic studies of complex diseases. The present study points to PARK2 as a major hallmark of PD etiology in Spain.

neuroscience↗