Changes in lipid metabolism track with the progression of neurofibrillary pathology in tauopathies.

BACKGROUND: Accumulation of tau leads to neuroinflammation and neuronal cell death in tauopathies, including Alzheimer's disease. As the disease progresses, there is a decline in brain energy metabolism. However, the role of tau protein in regulating lipid metabolism remains less characterized and poorly understood. METHODS: We used a transgenic rat model for tauopathy to reveal metabolic alterations induced by neurofibrillary pathology. Transgenic rats express a tau fragment truncated at the N- and C-terminals. For phenotypic profiling, we performed targeted metabolomic and lipidomic analysis of brain tissue, CSF, and plasma, based on the LC-MS platform. To monitor disease progression, we employed samples from transgenic and control rats aged 4, 6, 8, 10, 12, and 14 months. To study neuron-glia interplay in lipidome changes induced by pathological tau we used well well-established multicomponent cell model system. Univariate and multivariate statistical approaches were used for data evaluation. RESULTS: We showed that tau has an important role in the deregulation of lipid metabolism. In the lipidomic study, pathological tau was associated with higher production of lipids participating in protein fibrillization, membrane reorganization, and inflammation. Interestingly, significant changes have been found in the early stages of tauopathy before the formation of high-molecular-weight tau aggregates and neurofibrillary pathology. Increased secretion of pathological tau protein in vivo and in vitro induced upregulated production of phospholipids and sphingolipids and accumulation of lipid droplets in microglia. We also found that this process depended on the amount of extracellular tau. During the later stages of tauopathy, we found a connection between the transition of tau into an insoluble fraction and changes in brain metabolism. CONCLUSION: Our results revealed that lipid metabolism is significantly affected during different stages of tau pathology. Thus, our results demonstrate that the dysregulation of lipid composition by pathological tau disrupts the microenvironment, further contributing to the propagation of pathology.

Assessing HCH isomer uptake in Alnus glutinosa: implications for phytoremediation and microbial response.

Although the pesticide hexachlorocyclohexane (HCH) and its isomers have long been banned, their presence in the environment is still reported worldwide. In this study, we investigated the bioaccumulation potential of α, ß, and δ hexachlorocyclohexane (HCH) isomers in black alder saplings (Alnus glutinosa) to assess their environmental impact. Each isomer, at a concentration of 50 mg/kg, was individually mixed with soil, and triplicate setups, including a control without HCH, were monitored for three months with access to water. Gas chromatography-mass spectrometry revealed the highest concentrations of HCH isomers in roots, decreasing towards branches and leaves, with δ-HCH exhibiting the highest uptake (roots-14.7 µg/g, trunk-7.2 µg/g, branches-1.53 µg/g, leaves-1.88 µg/g). Interestingly, α-HCH was detected in high concentrations in ß-HCH polluted soil. Phytohormone analysis indicated altered cytokinin, jasmonate, abscisate, and gibberellin levels in A. glutinosa in response to HCH contamination. In addition, amplicon 16S rRNA sequencing was used to study the rhizosphere and soil microbial community. While rhizosphere microbial populations were generally similar in all HCH isomer samples, Pseudomonas spp. decreased across all HCH-amended samples, and Tomentella dominated in ß-HCH and control rhizosphere samples but was lowest in δ-HCH samples.

Parallel Metabolomics and Lipidomics of a PSMA/GCPII Deficient Mouse Model Reveal Alteration of NAAG Levels and Brain Lipid Composition.

Glutamate carboxypeptidase II (GCPII, also known as PSMA or FOLH1) is responsible for the cleavage of N-acetyl-aspartyl-glutamate (NAAG) to N-acetyl-aspartate and glutamate in the central nervous system and facilitates the intestinal absorption of folate by processing dietary folyl-poly-γ-glutamate in the small intestine. The physiological function of GCPII in other organs like kidneys is still not known. GCPII inhibitors are neuroprotective in various conditions (e.g., ischemic brain injury) in vivo; however, their utilization as potential drug candidates has not been investigated in regard to not yet known GCPII activities. To explore the GCPII role and possible side effects of GCPII inhibitors, we performed parallel metabolomic and lipidomic analysis of the cerebrospinal fluid (CSF), urine, plasma, and brain tissue of mice with varying degrees of GCPII deficiency (fully deficient in Folh1, -/-; one allele deficient in Folh1, +/-; and wild type, +/+). Multivariate analysis of metabolites showed no significant differences between wild-type and GCPII-deficient mice (except for NAAG), although changes were observed between the sex and age. NAAG levels were statistically significantly increased in the CSF, urine, and plasma of GCPII-deficient mice. However, no difference in NAAG concentrations was found in the whole brain lysate likely because GCPII, as an extracellular enzyme, can affect only extracellular and not intracellular NAAG concentrations. Regarding the lipidome, the most pronounced genotype-linked changes were found in the brain tissue. In brains of GCPII-deficient mice, we observed statistically significant enrichment in phosphatidylcholine-based lipids and reduction of sphingolipids and phosphatidylethanolamine plasmalogens. We hypothesize that the alteration of the NAA-NAAG axis by absent GCPII activity affected myelin composition. In summary, the absence of GCPII and thus similarly its inhibition do not have detrimental effects on metabolism, with just minor changes in the brain lipidome.

Patients with Neurodegenerative Proteinopathies Exhibit Altered Tryptophan Metabolism in the Serum and Cerebrospinal Fluid.

Some pathological conditions affecting the human body can also disrupt metabolic pathways and thus alter the overall metabolic profile. Knowledge of metabolic disturbances in specific diseases could thus enable the differential diagnosis of otherwise similar conditions. This work therefore aimed to comprehensively characterize changes in tryptophan metabolism in selected neurodegenerative diseases. Levels of 18 tryptophan-related neuroactive substances were determined by high throughput and sensitive ultrahigh-performance liquid chromatography-tandem mass spectrometry in time-linked blood serum and cerebrospinal fluid samples from 100 age-matched participants belonging to five cohorts: healthy volunteers (n = 21) and patients with Lewy body disease (Parkinson's disease and dementia with Lewy bodies; n = 31), four-repeat tauopathy (progressive supranuclear palsy and corticobasal syndrome; n = 10), multiple system atrophy (n = 13), and Alzheimer's disease (n = 25). Although these conditions have different pathologies and clinical symptoms, the discovery of new biomarkers is still important. The most statistically significant differences (with p-values of ≤0.05 to ≤0.0001) between the study cohorts were observed for three tryptophan metabolites: l-kynurenine in cerebrospinal fluid and 3-hydroxy-l-kynurenine and 5-hydroxy-l-tryptophan in blood serum. This led to the discovery of distinctive correlation patterns between the profiled cerebrospinal fluid and serum metabolites that could provide a basis for the differential diagnosis of neurodegenerative tauopathies and synucleinopathies. However, further large-scale studies are needed to determine the direct involvement of these metabolites in the studied neuropathologies, their response to medication, and their potential therapeutic relevance.

Aminoacylase 1 deficiency: case report on three affected siblings.

Background: Aminoacylase 1 (ACY1, EC 3.5.1.14) deficiency (ACY1D) is a very rare inherited metabolic disease (IMD) with autosomal recessive inheritance (OMIM #609924). Up to date, only 15 cases have been reported in the literature. It is diagnosed by detecting acetylated amino acids among the patient's urine organic acids by gas chromatography-mass spectrometry. Its clinical manifestations are highly variable, ranging from severe neurological symptoms to being asymptomatic. Case Description: We present a 14-year-old boy with mild intellectual disability, speech sound disorder and non-alcoholic fatty liver disease who exhibited increased urinary excretion of N-acetylalanine, N-acetylmethionine and N-acetylglutamine during testing for inherited metabolic disorders. A suspected ACY1D was subsequently confirmed by targeted next generation sequencing, which revealed the presence of a homozygous pathogenic missense mutation in the ACY1 gene, c.1057C>T (p.Arg353Cys). The proband underwent speech education with good outcome. The same homozygous mutation in ACY1 gene was found in the boy's two brothers, who exhibited slightly varied intellectual abilities. Follow-up examinations of the siblings revealed no deterioration in their mental skills. Conclusions: These results suggest that uneven mental abilities in pediatric patients with various disorders including autism spectrum disorder may be sufficient grounds to warrant metabolic testing for ACY1D. The acylglycines urine excretion could be a promising novel metabolic marker for ACY1D testing.

Wide metabolite coverage LC-MS/MS assay for the diagnosis of inherited metabolic disorders in urine.

OBJECTIVE: The laboratory diagnosis of inherited metabolic disorders (IMD) has undergone significant development in recent decades, mainly due to the use of mass spectrometry, which allows rapid multicomponent analysis of a wide range of metabolites. Combined with advanced software tools, the diagnosis becomes more efficient as a benefit for both physicians and patients. METHODS: A hydrophilic interaction liquid chromatography coupled with tandem mass spectrometry assay for determination of urinary purines, pyrimidines, N-acylglycines, N-acetylated amino acids, sugars, sugar alcohols and other diagnostically important biomarkers was developed and validated. Evaluation of the results consisting of utilisation of robust scaling and advanced visualization tools is simple and even suitable for urgent requirements. RESULTS: The developed method, covering 65 biomarkers, provides a comprehensive diagnostic platform for 51 IMD. For most analytes, linearity with R2 > 0.99, intra and inter-day accuracy between 80 and 120 % and precision lower than 20 % were achieved. Diagnostic workflow was evaluated on 47 patients and External Quality Assurance samples involving a total of 24 different IMD. Over seven years, more than 2300 urine samples from patients suspected for IMD have been routinely analysed. CONCLUSIONS: This method offers the advantage of a broad coverage of intermediate metabolites of interest and therefore may be a potential alternative and simplification for clinical laboratories that use multiple methods for screening these markers.

Utilizing neurodegenerative markers for the diagnostic evaluation of amyotrophic lateral sclerosis.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder characterized by progressive deterioration of upper and lower motor neurons. A definitive diagnostic test or biomarker for ALS is currently unavailable, leading to a diagnostic delay following the onset of initial symptoms. Our study focused on cerebrospinal fluid (CSF) concentrations of clusterin, tau protein, phosphorylated tau protein, and beta-amyloid1-42 in ALS patients and a control group. METHODS: Our study involved 54 ALS patients and 58 control subjects. Among the ALS patients, 14 presented with bulbar-onset ALS, and 40 with limb-onset ALS. We quantified biomarker levels using enzyme-linked immunosorbent assay (ELISA) and compared the results using the Mann-Whitney U-test. RESULTS: Significant elevations in neurodegenerative markers, including tau protein (p < 0.0001), phosphorylated tau protein (p < 0.0001), and clusterin (p = 0.038), were observed in ALS patients compared to controls. Elevated levels of tau protein and phosphorylated tau protein were also noted in both bulbar and limb-onset ALS patients. However, no significant difference was observed for beta-amyloid1-42. ROC analysis identified tau protein (AUC = 0.767) and p-tau protein (AUC = 0.719) as statistically significant predictors for ALS. CONCLUSION: Our study demonstrates that neurodegenerative marker levels indicate an ongoing neurodegenerative process in ALS. Nonetheless, the progression of ALS cannot be predicted solely based on these markers. The discovery of a specific biomarker could potentially complement existing diagnostic criteria for ALS.

Alterations in lipidome profiles distinguish early-onset hyperuricemia, gout, and the effect of urate-lowering treatment.

BACKGROUND: Currently, it is not possible to predict whether patients with hyperuricemia (HUA) will develop gout and how this progression may be affected by urate-lowering treatment (ULT). Our study aimed to evaluate differences in plasma lipidome between patients with asymptomatic HUA detected ≤ 40 years (HUA ≤ 40) and > 40 years, gout patients with disease onset ≤ 40 years (Gout ≤ 40) and > 40 years, and normouricemic healthy controls (HC). METHODS: Plasma samples were collected from 94 asymptomatic HUA (77% HUA ≤ 40) subjects, 196 gout patients (59% Gout ≤ 40), and 53 HC. A comprehensive targeted lipidomic analysis was performed to semi-quantify 608 lipids in plasma. Univariate and multivariate statistics and advanced visualizations were applied. RESULTS: Both HUA and gout patients showed alterations in lipid profiles with the most significant upregulation of phosphatidylethanolamines and downregulation of lysophosphatidylcholine plasmalogens/plasmanyls. More profound changes were observed in HUA ≤ 40 and Gout ≤ 40 without ULT. Multivariate statistics differentiated HUA ≤ 40 and Gout ≤ 40 groups from HC with an overall accuracy of > 95%. CONCLUSION: Alterations in the lipidome of HUA and Gout patients show a significant impact on lipid metabolism. The most significant glycerophospholipid dysregulation was found in HUA ≤ 40 and Gout ≤ 40 patients, together with a correction of this imbalance with ULT.

Determining Thrombogenicity: Using a Modified Thrombin Generation Assay to Detect the Level of Thrombotic Event Risk in Lupus Anticoagulant-Positive Patients.

The aim of this study was to determine the thrombogenicity of lupus anticoagulant (LA) antibodies using a modified thrombin generation assay (TGA) with the addition of activated protein C (APC) in a group of 85 patients with LA-positive samples. Of these, 58 patients had clinical manifestations of antiphospholipid syndrome (APS) according to the Sydney criteria classification, i.e., each patient had thrombosis or foetal loss, and 27 patients did not show any clinical manifestations of APS. A comparison of the two groups' TGA results revealed statistically significant differences (Fisher's test p = 0.0016). The group of patients exhibiting clinical manifestations of APS showed higher thrombogenicity in 56.9% of patients, while the group of patients not yet exhibiting clinical manifestations of APS showed higher thrombogenicity in 25.9% of patients. There were no significant differences in the specificity of the TGA test between the groups of patients exhibiting similar clinical manifestations. Receiver operating characteristic curve analysis showed a more significant relationship (p = 0.0060) for TGA than for LA titre (p = 0.3387). These data suggest that the determination of LA thrombogenicity with the TGA assay leads to an increased prediction of the manifestation of a thromboembolic event. Our findings appear to be particularly relevant for the prediction of thrombotic events in patients with laboratory-expressed APS and no clinical manifestations.

A new technique for the analysis of metabolic pathways of cytidine analogues and cytidine deaminase activities in cells.

Deoxycytidine analogues (dCas) are widely used for the treatment of malignant diseases. They are commonly inactivated by cytidine deaminase (CDD), or by deoxycytidine monophosphate deaminase (dCMP deaminase). Additional metabolic pathways, such as phosphorylation, can substantially contribute to their (in)activation. Here, a new technique for the analysis of these pathways in cells is described. It is based on the use of 5-ethynyl 2'-deoxycytidine (EdC) and its conversion to 5-ethynyl 2'-deoxyuridine (EdU). Its use was tested for the estimation of the role of CDD and dCMP deaminase in five cancer and four non-cancer cell lines. The technique provides the possibility to address the aggregated impact of cytidine transporters, CDD, dCMP deaminase, and deoxycytidine kinase on EdC metabolism. Using this technique, we developed a quick and cheap method for the identification of cell lines exhibiting a lack of CDD activity. The data showed that in contrast to the cancer cells, all the non-cancer cells used in the study exhibited low, if any, CDD content and their cytidine deaminase activity can be exclusively attributed to dCMP deaminase. The technique also confirmed the importance of deoxycytidine kinase for dCas metabolism and indicated that dCMP deaminase can be fundamental in dCas deamination as well as CDD. Moreover, the described technique provides the possibility to perform the simultaneous testing of cytotoxicity and DNA replication activity.

Multivariate Independent Component Analysis Identifies Patients in Newborn Screening Equally to Adjusted Reference Ranges.

Newborn screening (NBS) of inborn errors of metabolism (IEMs) is based on the reference ranges established on a healthy newborn population using quantile statistics of molar concentrations of biomarkers and their ratios. The aim of this paper is to investigate whether multivariate independent component analysis (ICA) is a useful tool for the analysis of NBS data, and also to address the structure of the calculated ICA scores. NBS data were obtained from a routine NBS program performed between 2013 and 2022. ICA was tested on 10,213/150 free-diseased controls and 77/20 patients (9/3 different IEMs) in the discovery/validation phases, respectively. The same model computed during the discovery phase was used in the validation phase to confirm its validity. The plots of ICA scores were constructed, and the results were evaluated based on 5sd levels. Patient samples from 7/3 different diseases were clearly identified as 5sd-outlying from control groups in both phases of the study. Two IEMs containing only one patient each were separated at the 3sd level in the discovery phase. Moreover, in one latent variable, the effect of neonatal birth weight was evident. The results strongly suggest that ICA, together with an interpretation derived from values of the "average member of the score structure", is generally applicable and has the potential to be included in the decision process in the NBS program.

Cerebrospinal fluid and blood serum biomarkers in neurodegenerative proteinopathies: A prospective, open, cross-correlation study.

Neurodegenerative diseases are a broad heterogeneous group affecting the nervous system. They are characterized, from a pathophysiological perspective, by the selective involvement of a subpopulation of nerve cells with a consequent clinical picture of a disease. Clinical diagnoses of neurodegenerative diseases are quite challenging and often not completely accurate because of their marked heterogeneity and frequently overlapping clinical pictures. Efforts are being made to define sufficiently specific and sensitive markers for individual neurodegenerative diseases or groups of diseases in order to increase the accuracy and speed of clinical diagnosis. Thus said, this present research aimed to identify biomarkers in the cerebrospinal fluid (CSF) and serum (α-synuclein [α-syn], tau protein [t-tau], phosphorylated tau protein [p-tau], ß-amyloid [Aß], clusterin, chromogranin A [chromogrA], cystatin C [cyst C], neurofilament heavy chains [NFH], phosphorylated form of neurofilament heavy chains [pNF-H], and ratio of tau protein/amyloid beta [Ind tau/Aß]) that could help in the differential diagnosis and differentiation of the defined groups of α-synucleinopathies and four-repeat (4R-) tauopathies characterized by tau protein isoforms with four microtubule-binding domains. In this study, we analyzed a cohort of 229 patients divided into four groups: (1) Parkinson's disease (PD) + dementia with Lewy bodies (DLB) (n = 82), (2) multiple system atrophy (MSA) (n = 25), (3) progressive supranuclear palsy (PSP) + corticobasal syndrome (CBS) (n = 30), and (4) healthy controls (HC) (n = 92). We also focused on analyzing the biomarkers in relation to each other with the intention of determining whether they are useful in distinguishing among individual proteinopathies. Our results indicate that the proposed set of biomarkers, when evaluated in CSF, is likely to be useful for the differential diagnosis of MSA versus 4RT. However, these biomarkers do not seem to provide any useful diagnostic information when assessed in blood serum.

Rapid and efficient LC-MS/MS diagnosis of inherited metabolic disorders: a semi-automated workflow for analysis of organic acids, acylglycines, and acylcarnitines in urine.

OBJECTIVES: The analysis of organic acids in urine is an important part of the diagnosis of inherited metabolic disorders (IMDs), for which gas chromatography coupled with mass spectrometry is still predominantly used. METHODS: Ultra-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay for urinary organic acids, acylcarnitines and acylglycines was developed and validated. Sample preparation consists only of dilution and the addition of internal standards. Raw data processing is quick and easy using selective scheduled multiple reaction monitoring mode. A robust standardised value calculation as a data transformation together with advanced automatic visualisation tools are applied for easy evaluation of complex data. RESULTS: The developed method covers 146 biomarkers consisting of organic acids (n=99), acylglycines (n=15) and acylcarnitines (n=32) including all clinically important isomeric compounds present. Linearity with r2>0.98 for 118 analytes, inter-day accuracy between 80 and 120 % and imprecision under 15 % for 120 analytes were achieved. Over 2 years, more than 800 urine samples from children tested for IMDs were analysed. The workflow was evaluated on 93 patient samples and ERNDIM External Quality Assurance samples involving a total of 34 different IMDs. CONCLUSIONS: The established LC-MS/MS workflow offers a comprehensive analysis of a wide range of organic acids, acylcarnitines and acylglycines in urine to perform effective, rapid and sensitive semi-automated diagnosis of more than 80 IMDs.

Clinical lipidomics in the era of the big data.

Lipidomics as a branch of metabolomics provides unique information on the complex lipid profile in biological materials. In clinically focused studies, hundreds of lipids together with available clinical information proved to be an effective tool in the discovery of biomarkers and understanding of pathobiochemistry. However, despite the introduction of lipidomics nearly twenty years ago, only dozens of big data studies using clinical lipidomics have been published to date. In this review, we discuss the lipidomics workflow, statistical tools, and the challenges of standartisation. The consequent summary divided into major clinical areas of cardiovascular disease, cancer, diabetes mellitus, neurodegenerative and liver diseases is demonstrating the importance of clinical lipidomics. In these publications, the potential of lipidomics for prediction, diagnosis or finding new targets for the treatment of selected diseases can be seen. The first of these results have already been implemented in clinical practice in the field of cardiovascular diseases, while in other areas we can expect the application of the results summarized in this review in the near future.

From big data to better patient outcomes.

Among medical specialties, laboratory medicine is the largest producer of structured data and must play a crucial role for the efficient and safe implementation of big data and artificial intelligence in healthcare. The area of personalized therapies and precision medicine has now arrived, with huge data sets not only used for experimental and research approaches, but also in the "real world". Analysis of real world data requires development of legal, procedural and technical infrastructure. The integration of all clinical data sets for any given patient is important and necessary in order to develop a patient-centered treatment approach. Data-driven research comes with its own challenges and solutions. The Findability, Accessibility, Interoperability, and Reusability (FAIR) Guiding Principles provide guidelines to make data findable, accessible, interoperable and reusable to the research community. Federated learning, standards and ontologies are useful to improve robustness of artificial intelligence algorithms working on big data and to increase trust in these algorithms. When dealing with big data, the univariate statistical approach changes to multivariate statistical methods significantly shifting the potential of big data. Combining multiple omics gives previously unsuspected information and provides understanding of scientific questions, an approach which is also called the systems biology approach. Big data and artificial intelligence also offer opportunities for laboratories and the In Vitro Diagnostic industry to optimize the productivity of the laboratory, the quality of laboratory results and ultimately patient outcomes, through tools such as predictive maintenance and "moving average" based on the aggregate of patient results.

Altered Plasma, Urine, and Tissue Profiles of Sulfatides and Sphingomyelins in Patients with Renal Cell Carcinoma.

PURPOSE: RCC, the most common type of kidney cancer, is associated with high mortality. A non-invasive diagnostic test remains unavailable due to the lack of RCC-specific biomarkers in body fluids. We have previously described a significantly altered profile of sulfatides in RCC tumor tissues, motivating us to investigate whether these alterations are reflected in collectible body fluids and whether they can enable RCC detection. METHODS: We collected and further analyzed 143 plasma, 100 urine, and 154 tissue samples from 155 kidney cancer patients, together with 207 plasma and 70 urine samples from 214 healthy controls. RESULTS: For the first time, we show elevated concentrations of lactosylsulfatides and decreased levels of sulfatides with hydroxylated fatty acyls in body fluids of RCC patients compared to controls. These alterations are emphasized in patients with the advanced tumor stage. Classification models are able to distinguish between controls and patients with RCC. In the case of all plasma samples, the AUC for the testing set was 0.903 (0.844-0.954), while for urine samples it was 0.867 (0.763-0.953). The models are able to efficiently detect patients with early- and late-stage RCC based on plasma samples as well. The test set sensitivities were 80.6% and 90%, and AUC values were 0.899 (0.832-0.952) and 0.981 (0.956-0.998), respectively. CONCLUSION: Similar trends in body fluids and tissues indicate that RCC influences lipid metabolism, and highlight the potential of the studied lipids for minimally-invasive cancer detection, including patients with early tumor stages, as demonstrated by the predictive ability of the applied classification models.

Specific gut bacterial and fungal microbiota pattern in the first half of pregnancy is linked to the development of gestational diabetes mellitus in the cohort including obese women.

Aims: Gestation is linked to changes in gut microbiota composition and function. Since gestational diabetes mellitus (GDM) can develop at any time of the pregnancy, we stratified the women into four groups according to the time and test used for the diagnosis. We focused on the gut microbiota pattern in early pregnancy to detect changes which could be linked to later GDM development. Methods: We collected stool samples from 104 pregnant women including obese individuals (first trimester body mass index median was 26.73). We divided the women into four groups according to routine screening of fasting plasma glucose (FPG) levels and oral glucose tolerance test (oGTT) in the first and third trimesters, respectively. We processed the stool samples for bacterial 16S rRNA and fungal ITS1 genes sequencing by Illumina MiSeq approach and correlated the gut microbiota composition with plasma short-chain fatty acid levels (SCFA). Results: We found that gut bacterial microbiota in the first trimester significantly differs among groups with different GDM onset based on unweighted UniFrac distances (p=0.003). Normoglycemic women had gut microbiota associated with higher abundance of family Prevotellaceae, and order Fusobacteriales, and genus Sutterella. Women diagnosed later during pregnancy either by FGP levels or by oGTT had higher abundances of genera Enterococcus, or Erysipelotrichaceae UCG-003, respectively. We observed significant enrichment of fungal genus Mucor in healthy pregnant women whereas Candida was more abundant in the group of pregnant women with impaired oGTT. Using correlation analysis, we found that Holdemanella negatively correlated with Blautia and Candida abundances and that Escherichia/Shigella abundance positively correlated and Subdoligranulum negatively correlated with plasma lipid levels. Coprococcus, Akkermansia, Methanobrevibacter, Phascolarctobacterium and Alistipes positively correlated with acetate, valerate, 2-hydroxybutyrate and 2-methylbutyrate levels, respectively, in women with GDM. Conclusions: We conclude that there are significant differences in the gut microbiota composition between pregnant women with and without GDM already at the early stage of pregnancy in our cohort that included also overweight and obese individuals. Specific microbial pattern associated with GDM development during early pregnancy and its correlation to plasma lipid or SCFA levels could help to identify women in higher risk of GDM development.

Dynamics of acylcarnitines, hypoglycin A, méthylènecyclopropylglycine and their metabolites in a Kladruber stallion with atypical myopathy.

Equine atypical myopathy (AM also referred to as multiple acyl-CoA dehydrogenases deficiency [MADD]) is thought to be caused by toxins metabolized from hypoglycin A (HGA) and méthylènecyclopropylglycine (MCPrG). HGA is contained in the seeds and seedlings of the sycamore tree (Acer pseudoplatanus); MCPrG has so far only been confirmed in seeds. Among other things, these substances can disrupt the fatty acids ß-oxidation pathway with the subsequent accumulation of certain acylcarnitines. The tentative diagnosis is based on anamnesis and clinical signs and can be verified by the detection of elevated creatine kinase activity, specific profile of acylcarnitines and the presence of HGA, MCPrG conjugates and/or their metabolites in peripheral blood and/or urine. Dry blood spots were collected for 15 days from a 3.5-year-old stallion which had been affected by AM and, as a control group, from twelve healthy horses. Two mass spectrometry methods were used for the analysis of 31 acylcarnitines, carnitine, HGA, MCPrG and their metabolites. HGA and six increased acylcarnitines were detected in the patient's blood throughout the monitoring period. Nine acylcarnitines were strongly correlated with HGA. Multivariate statistical analysis showed a clear separation of samples from the AM horse, where the metabolic profile tended to normalization in the later days after intoxication. Due to the longer persistence in the blood, the detection of HGA and elevated acylcarnitines profile appear to be an appropriate tool to confirm the diagnosis of AM, compared to metabolic products of HGA and MCPrG even in advanced cases.

Determination of Thrombogenicity Levels of Various Antiphospholipid Antibodies by a Modified Thrombin Generation Assay in Patients with Suspected Antiphospholipid Syndrome.

Antiphospholipid syndrome (APS) is a hypercoagulable state accompanied by the presence of heterogeneous antiphospholipid antibodies (aPL), which nonspecifically affect hemostasis by the presence of lupus anticoagulans (LA), anticardiolipin antibodies (aCL), antibodies against ß2-glycoprotein-I (anti-ß2GPI), but also non-criteria antibodies such as antibodies against ß2-glycoprotein-I domain I (anti-DI), anti-phosphatidylserine/prothrombin (anti-PS/PT), anti-annexin V, and many others. The main target of the antibodies is the activated protein C (APC) system, the elimination of which can manifest itself as a thrombotic complication. The aim of this study was to determine the thrombogenicity of antibodies using a modified protein C-activated thrombin generation assay (TGA) on a group of 175 samples suspected of APS. TGA was measured with/without APC and the ratio of both measurements was evaluated (as for APC resistance), where a cut-off was calculated ≤4.5 (90th percentile) using 21 patients with heterozygous factor V Leiden mutation (FV Leiden heterozygous). Our study demonstrates the well-known fact that multiple positivity of different aPLs is a more severe risk for thrombosis than single positivity. Of the single antibody positivity, LA antibodies are the most serious (p value < 0.01), followed by aCL and their subgroup anti-DI (p value < 0.05). Non-criteria antibodies anti-annexin V and anti-PT/PS has a similar frequency occurrence of thrombogenicity as LA antibodies but without statistical significance or anti-ß2GPI1 positivity. The modified TGA test can help us identify patients in all groups who are also at risk for recurrent thrombotic and pregnancy complications; thus, long-term prophylactic treatment is appropriate. For this reason, it is proving increasingly beneficial to include the determination antibodies in combination with modified TGA test.

Biomarkers of Neurodegenerative Diseases: Biology, Taxonomy, Clinical Relevance, and Current Research Status.

The understanding of neurodegenerative diseases, traditionally considered to be well-defined entities with distinguishable clinical phenotypes, has undergone a major shift over the last 20 years. The diagnosis of neurodegenerative diseases primarily requires functional brain imaging techniques or invasive tests such as lumbar puncture to assess cerebrospinal fluid. A new biological approach and research efforts, especially in vivo, have focused on biomarkers indicating underlying proteinopathy in cerebrospinal fluid and blood serum. However, due to the complexity and heterogeneity of neurodegenerative processes within the central nervous system and the large number of overlapping clinical diagnoses, identifying individual proteinopathies is relatively difficult and often not entirely accurate. For this reason, there is an urgent need to develop laboratory methods for identifying specific biomarkers, understand the molecular basis of neurodegenerative disorders and classify the quantifiable and readily available tools that can accelerate efforts to translate the knowledge into disease-modifying therapies that can improve and simplify the areas of differential diagnosis, as well as monitor the disease course with the aim of estimating the prognosis or evaluating the effects of treatment. The aim of this review is to summarize the current knowledge about clinically relevant biomarkers in different neurodegenerative diseases.