Insights into the Effects of Crack Abuse on the Human Metabolome Using a NMR Approach.

Approximately 255 million people consume illicit drugs every year, among which 18 million use cocaine. A portion of this drug is represented by crack, but it is difficult to estimate the number of users since most are marginalized. However, there are no recognized efficacious pharmacotherapies for crack-cocaine dependence. Inflammation and infection in cocaine users may be due to behavior adopted in conjunction with drug-related changes in the brain. To understand the metabolic changes associated with the drug abuse disorder and identify biomarkers, we performed a 1H NMR-based metabonomic analysis of 44 crack users' and 44 healthy volunteers' blood serum. The LDA model achieved 98% of accuracy. From the water suppressed 1H NMR spectra analyses, it was observed that the relative concentration of lactate was higher in the crack group, while long chain fatty acid acylated carnitines were decreased, which was associated with their nutritional behavior. Analyses of the aromatic region of CPMG 1H NMR spectra demonstrated histidine and tyrosine levels increased in the blood serum of crack users. The reduction of carnitine and acylcarnitines and the accumulation of histidine in the serum of the crack users suggest that histamine biosynthesis is compromised. The tyrosine level points to altered dopamine concentration.

Metabolomic Biomarkers in Mental Disorders: Bipolar Disorder and Schizophrenia.

Psychiatric disorders are some of the most impairing human diseases. Among them, bipolar disorder and schizophrenia are the most common. Both have complicated diagnostics due to their phenotypic, biological, and genetic heterogeneity, unknown etiology, and the underlying biological pathways, and molecular mechanisms are still not completely understood. Given the multifactorial complexity of these disorders, identification and implementation of metabolic biomarkers would assist in their early detection and diagnosis and facilitate disease monitoring and treatment responses. To date, numerous studies have utilized metabolomics to better understand psychiatric disorders, and findings from these studies have begun to converge. In this chapter, we briefly describe some of the metabolomic biomarkers found in these two disorders.

Lipidomics, Biomarkers, and Schizophrenia: A Current Perspective.

Lipidomics is a lipid-targeted metabolomics approach aiming at comprehensive analysis of lipids in biological systems. Recent technological progresses in mass spectrometry, nuclear magnetic resonance spectroscopy, and chromatography have significantly enhanced the developments and applications of metabolic profiling of lipids in more complex biological samples. As many diseases reveal a notable change in lipid profiles compared with that of healthy people, lipidomics have also been broadly introduced to scientific research on diseases. Exploration of lipid biochemistry by lipidomics approach will not only provide insights into specific roles of lipid molecular species in health and disease, but it will also support the identification of potential biomarkers for establishing preventive or therapeutic approaches for human health. This chapter aims to illustrate how lipidomics can contribute for understanding the biological mechanisms inherent to schizophrenia and why lipids are relevant biomarkers of schizophrenia. The application of lipidomics in clinical studies has the potential to provide new insights into lipid profiling and pathophysiological mechanisms underlying schizophrenia. The future perspectives of lipidomics in mental disorders are also discussed herein.

Peripheral biomarkers allow differential diagnosis between schizophrenia and bipolar disorder.

Schizophrenia (SCZ) and bipolar disorder (BD) are severe mental disorders that pose important challenges for diagnosis by sharing common symptoms, such as delusions and hallucinations. The underlying pathophysiology of both disorders remains largely unknown, and the identification of biomarkers with potential to support diagnosis is highly desirable. In a previous study, we successfully discriminated SCZ and BD patients from healthy control (HC) individuals by employing proton magnetic resonance spectroscopy (1H-NMR). In this study, 1H-NMR data treated by chemometrics, principal component analysis (PCA) and supervised partial least-squares discriminant analysis (PLS-DA), provided the identification of metabolites present only in BD (as for instance the 2,3-diphospho-D-glyceric acid, N-acetyl aspartyl-glutamic acid, monoethyl malonate) or only in SCZ (as isovaleryl carnitine, pantothenate, mannitol, glycine, GABA). This may represent a set of potential biomarkers to support the diagnosis of these mental disorders, enabling the discrimination between SCZ and BD, and among these psychiatric patients and HC (as 6-hydroxydopamine was present in BD and SCZ but not in HC). The presence or absence of these metabolites in blood allowed the categorization of 182 independent subjects into one of these three groups. In addition, the presented data suggest disturbances in metabolic pathways in SCZ and BD, which may provide new and important information to support the elucidation and/or new insights into the neurobiology underlying these mental disorders.

NMR insights on nano silver post-surgical treatment of superficial caseous lymphadenitis in small ruminants.

Caseous lymphadenitis (CL), caused by a pathogen of the second class of biosafety - Corynebacterium pseudotuberculosis, is a chronic and severe infectious disease that affects small ruminants and requires long, ineffective treatment which generally leads to animal sacrifice so as to stop the disease spreading. The infected animals suffer the excision of affected superficial lymph nodes and post-surgical treatment with iodine (10% solution in ethanol) and, sometimes, prolonged antibiotic use, but only if the sick animals are of great importance to breeding. Herein, we propose a cheap and easy to apply treatment of CL with excellent results using biogenic silver nanoparticles (AgNP) based technology. AgNP antibacterial properties were investigated in vitro against Corynebacterium pseudotuberculosis cells and in vivo on small ruminants with CL. Treatment of surgical wounds resulting from the excision of superficial CL lesions with a AgNP-based cream was compared to the standard post-surgical treatment method by iodine. Also, the effects of AgNP-based cream treatment were evaluated and compared with the effects of the iodine CL treatment by serum NMR-based metabolomics. Serum samples were collected from 29 animals, 9 sheep and 20 goats, during the treatments and analyzed. All animals showed stable serum metabolomes when iodine or AgNP-based cream effects were compared. The AgNP-based cream treatment showed excellent results, especially in accelerating the healing of wounds, which occurred two to three times faster in comparison with the iodine treatment. AgNP-based cream treatment also prevented CL reappearance and did not cause any side effects on animals. This is the first report on very effective post-surgical treatment of superficial CL in small ruminants based on biogenic silver nanoparticles, which might open up the possibility for a safe veterinary application of AgNP-based cream.

1H NMR Metabolomic Profiling of Human and Animal Blood Serum Samples.

Nuclear magnetic resonance (NMR) spectroscopy techniques allow the acquisition of a large amount of data and when combined with multivariate statistical analysis, it is possible to process and interpret the obtained NMR data in accordance with the biological problem being investigated. In this chapter, the search for biologically relevant biomarkers is addressed using NMR spectroscopy-based metabolomics, due to their clinical relevance for either diagnosis or monitoring of diseases and disorders.

1H-NMR, 1H-NMR T2-edited, and 2D-NMR in bipolar disorder metabolic profiling.

BACKGROUND: The objective of this study was to identify molecular alterations in the human blood serum related to bipolar disorder, using nuclear magnetic resonance (NMR) spectroscopy and chemometrics. METHODS: Metabolomic profiling, employing 1H-NMR, 1H-NMR T2-edited, and 2D-NMR spectroscopy and chemometrics of human blood serum samples from patients with bipolar disorder (n = 26) compared with healthy volunteers (n = 50) was performed. RESULTS: The investigated groups presented distinct metabolic profiles, in which the main differential metabolites found in the serum sample of bipolar disorder patients compared with those from controls were lipids, lipid metabolism-related molecules (choline, myo-inositol), and some amino acids (N-acetyl-L-phenyl alanine, N-acetyl-L-aspartyl-L-glutamic acid, L-glutamine). In addition, amygdalin, α-ketoglutaric acid, and lipoamide, among other compounds, were also present or were significantly altered in the serum of bipolar disorder patients. The data presented herein suggest that some of these metabolites differentially distributed between the groups studied may be directly related to the bipolar disorder pathophysiology. CONCLUSIONS: The strategy employed here showed significant potential for exploring pathophysiological features and molecular pathways involved in bipolar disorder. Thus, our findings may contribute to pave the way for future studies aiming at identifying important potential biomarkers for bipolar disorder diagnosis or progression follow-up.

Metabolomics and lipidomics analyses by 1H nuclear magnetic resonance of schizophrenia patient serum reveal potential peripheral biomarkers for diagnosis.

Using 1H NMR-based metabolomics in association to chemometrics analysis, we analyzed here the metabolic differences between schizophrenia patients (SCZ) compared to healthy controls (HCs). HCs and SCZ patients underwent clinical interview using the Structured Clinical Interview for DSM Disorders (SCID). SCZ patients were further assessed by Positive and Negative Syndrome Scale (PANSS), Calgary Depression Scale, Global Assessment of Functioning Scale (GAF), and Clinical Global Impressions Scale (CGI). Using the principal component analysis (PCA) and supervised partial least-squares discriminate analysis (PLS-DA) in obtained NMR data, a clear group separation between HCs and SCZ patients was achieved. Interestingly, all metabolite compounds identified as exclusively present in the SCZ group, except for the gamma-aminobutyric acid (GABA), were never previously associated with mental disorders. Although the initial perception of an absence of obvious biological link among the different key molecules exclusively observed in each group, and no identification of any specific pathway yet, the present work represents an important contribution for the identification of potential biomarkers to inform diagnosis, as it was possible to completely separate the affected SCZ patients from HCs, with no outliers or exceptions. In addition, the data presented here reinforced the role of the modulation of glycolysis pathway and the loss of GABA interneuron/hyperglutamate hypothesis in SCZ.