Aresatz Usobiaga’s research while affiliated with University of the Basque Country and other places

Cannabis use disorder affects up to 42% of individuals with schizophrenia, correlating with earlier onset, increased positive symptoms, and more frequent hospitalizations. This study employed an untargeted lipidomics approach to identify biomarkers in plasma samples from subjects with schizophrenia, cannabis use disorder, or both (dual diagnosis), aiming to elucidate the metabolic underpinnings of cannabis abuse and schizophrenia development. The use of liquid chromatography-high resolution mass spectrometry enabled the annotation of 119 metabolites, with the highest identification confidence level achieved for 16 compounds. Notably, a marked reduction in acylcarnitines, including octanoylcarnitine and decanoylcarnitine, was observed across all patient groups compared to controls. In cannabis use disorder patients, N-acyl amino acids (NAAAs), particularly N-palmitoyl threonine and N-palmitoyl serine, showed a strong downregulation, a pattern also seen in schizophrenia and dual diagnosis patients. Conversely, elevated levels of 7-dehydrodesmosterol were detected in schizophrenia and dual diagnosis patients relative to controls. These findings suggest a potential link between metabolic disruptions and the pathophysiology of both disorders. The untargeted lipidomics approach offers a powerful tool to identify novel biomarkers, enhancing our understanding of the biological relationship between cannabis abuse and schizophrenia, and paving the way for future therapeutic strategies targeting metabolic pathways in these conditions.

Cannabinoids, such as ∆ ⁹ -tetrahydrocannabinol (THC) and cannabidiol (CBD), are effective bioactive compounds that improve the quality of life of patients with certain chronic conditions. The copolymer poly(lactic-co-glycolic acid) (PLGA) has been used to encapsulate such compounds separately, providing pharmaceutical grade edible products with unique features. In this work, a variety of PLGA based nanoformulations that maintain the natural cannabinoid profile found in the plant (known as full-spectrum) are proposed and evaluated. Three different cannabis sources were used, representing the three most relevant cannabis chemotypes. PLGA nanocapsules loaded with different amounts of cannabinoids were prepared by nanoemulsion, and were then functionalized with three of the most common coating polymers: pectin, alginate and chitosan. In order to evaluate the suitability of the proposed formulations, all the synthesized nanocapsules were characterized, and their cannabinoid content, size, zeta-potential, morphology and in vitro bioaccessibility was determined. Regardless of the employed cannabis source, its load and the functionalization, high cannabinoid content PLGA nanocapsules with suitable particle size and zeta-potential were obtained. Study of nanocapsules’ morphology and in vitro release assays in gastro-intestinal media suggested that high cannabis source load may compromise the structure of nanocapsules and their release properties, and hence, the use of lower content of cannabis source is recommended. Graphical Abstract

Cannabis use disorder occurs in up to 42% of subjects with schizophrenia. It has been associated with a lower age of onset of schizophrenia, more positive symptoms and a higher frequency of hospitalizations. A number of metabolomic-based studies have shown that levels of several amino acids and lipids are altered in plasma of schizophrenia patients. Similarly, different levels of various lipids, amino acids, sugars, proteins and other metabolites have been quantified in plasma of cannabis consumers, suggesting that consumption of cannabis does interfere in the regulation of further metabolic pathways. In the present study, we performed a non-targeted metabolomic approach in plasma samples of subjects with a diagnosis of schizophrenia, cannabis use disorder or dual diagnosis. The aim was to find potential biomarkers of the diseases and to gain a better understanding of the relation between cannabis abuse and the development of schizophrenia. The liquid chromatography-high resolution mass spectrometry outcomes allowed the annotation of 121 metabolites. The analysis between each group and the corresponding control samples showed a clearer clustering of the samples. The two-way ANOVA and linear analysis of the whole dataset showed that most of the analytes were differently present between the groups, but none of them seems to correlate to gender or age. It can be highlighted the presence of two endocannabinoids (palmitylethanolamide (PEA) and oleoylethanolamide (OEA)), nicotine and cotinine as biomarkers of tobacco consumption, and nor-9- carboxy-Δ ⁹ -THC as biomarker of the consumption of cannabis. Moreover, some medium chain acylcarnitines (C8/C10) share a common pattern in the three comparison groups whereas some N-acyl serines were also highlighted in some of the group comparisons. The use of this non-targeted metabolomic approach provided us a deep insight to evaluate the metabolomics profile and to uncover putative biomarkers in schizophrenia and cannabis use disorder.

The determination of the concentration of endocannabinoids and related compounds in human plasma has become a matter of interest due to their implication in physiological processes and, thus, their possible relation with physiological conditions or illnesses. The analysis of these compounds though has to be carefully designed as they are found in very low concentrations, and some of them degrade easily once blood is collected. In this chapter, a simple method based on a liquid-liquid extraction and analysis by liquid chromatography tandem mass spectrometry (LC-MS/MS) is described to determine the concentration of eight of the most relevant endocannabinoids in plasma.

Cannabinoids present in Cannabis sativa are increasingly used in medicine due to their therapeutic potential. Moreover, the synergistic interaction between different cannabinoids and other plant constituents has led to the development of full-spectrum formulations for therapeutic treatments. In this work, the microencapsulation of a full-spectrum extract via vibration microencapsulation nozzle technique using chitosan-coated alginate is proposed to obtain an edible pharmaceutical-grade product. The suitability of microcapsules was assessed by their physicochemical characterization, long-term stability in three different storage conditions and in vitro gastrointestinal release. The synthetized microcapsules contained mainly ∆9-tetrahydrocannabinol (THC)-type and cannabinol (CBN)-type cannabinoids and had a mean size of 460 ± 260 µm and a mean sphericity of 0.5 ± 0.3. The stability assays revealed that capsules should be stored only at 4 °C in darkness to maintain their cannabinoid profile. In addition, based on the in vitro experiments, a fast intestinal release of cannabinoids ensures a medium–high bioaccessibility (57–77%) of therapeutically relevant compounds. The full characterization of microcapsules indicates that they could be used for the design of further full-spectrum cannabis oral formulations.

Metabolomics as a diagnosis tool for plant performance has shown good features for breeding and crop improvement. Additionally, due to limitations in land area and the increasing climate changes, breeding projects focusing on abiotic stress tolerance are becoming essential. Nowadays no universal method is available to identify predictive metabolic markers. As a result, research aims must dictate the best method or combination of methods. To this end, we will introduce the key aspects to consider regarding growth scenarios and sampling strategies and discuss major analytical and data treatment approaches that are available to find metabolic markers of plant performance.