Effects of season and sex on the concentrations of fecal glucocorticoid metabolites in captive and free-ranging endangered mountain gazelles (Gazella gazella).

Introduction: The aim of our study was to measure fecal glucocorticoid metabolite (FGM) concentrations in captive and free-ranging male and female mountain gazelles (Gazella gazella) during their circannual cycle. In addition, FGM concentrations were used to track the intensity of the adrenocortical response in mountain gazelles during the same period. Methods: Fecal samples were collected from the ground in the Hatay Mountain Gazelle Wildlife Development Area in the Hatay Province of Türkiye (36°32' N, 36°32' E) in each season of the year (December, April, July, September). The sex of the animals was determined by detecting the SRY gene of the Y chromosome in DNA isolated from the fecal samples. FGM was extracted from dried fecal samples with methanol, and its concentration was measured using a previously partially validated ELISA. Results and discussion: The results indicate that season is the most important factor explaining the variability in FGM concentrations in mountain gazelles. In animals of both sexes, the highest concentrations of FGM were observed in September. The values were significantly higher in the captive population, perhaps due to unpredictable stress. In July, FGM concentrations were low in both populations. As a result of the overall analysis across seasons, the comparison of FGM concentrations between captive and free-ranging animals revealed higher concentrations in captive animals only in September but not in other seasons, although higher concentrations have been previously reported for several wild captive species. Due to predation risk, the presence of offspring can be considered a critical point in the biological cycle for the welfare of free-ranging mountain gazelles, as suggested by the higher FGM concentrations in the free-ranging population in July. The high number of visitors could be a challenge for mountain gazelles in captivity, as indicated by higher FGM concentrations during September. Sex had no effect on the FGM concentrations of either population.

Convex Representation of Metabolic Networks with Michaelis-Menten Kinetics.

Polyhedral models of metabolic networks are computationally tractable and can predict some cellular functions. A longstanding challenge is incorporating metabolites without losing tractability. In this paper, we do so using a new second-order cone representation of the Michaelis-Menten kinetics. The resulting model consists of linear stoichiometric constraints alongside second-order cone constraints that couple the reaction fluxes to metabolite concentrations. We formulate several new problems around this model: conic flux balance analysis, which augments flux balance analysis with metabolite concentrations; dynamic conic flux balance analysis; and finding minimal cut sets of networks with both reactions and metabolites. Solving these problems yields information about both fluxes and metabolite concentrations. They are second-order cone or mixed-integer second-order cone programs, which, while not as tractable as their linear counterparts, can nonetheless be solved at practical scales using existing software.

Design and thermodynamic analysis of a pathway enabling anaerobic production of poly-3-hydroxybutyrate in Escherichia coli.

Utilizing anaerobic metabolisms for the production of biotechnologically relevant products presents potential advantages, such as increased yields and reduced energy dissipation. However, lower energy dissipation may indicate that certain reactions are operating closer to their thermodynamic equilibrium. While stoichiometric analyses and genetic modifications are frequently employed in metabolic engineering, the use of thermodynamic tools to evaluate the feasibility of planned interventions is less documented. In this study, we propose a novel metabolic engineering strategy to achieve an efficient anaerobic production of poly-(R)-3-hydroxybutyrate (PHB) in the model organism Escherichia coli. Our approach involves re-routing of two-thirds of the glycolytic flux through non-oxidative glycolysis and coupling PHB synthesis with NADH re-oxidation. We complemented our stoichiometric analysis with various thermodynamic approaches to assess the feasibility and the bottlenecks in the proposed engineered pathway. According to our calculations, the main thermodynamic bottleneck are the reactions catalyzed by the acetoacetyl-CoA ß-ketothiolase (EC 2.3.1.9) and the acetoacetyl-CoA reductase (EC 1.1.1.36). Furthermore, we calculated thermodynamically consistent sets of kinetic parameters to determine the enzyme amounts required for sustaining the conversion fluxes. In the case of the engineered conversion route, the protein pool necessary to sustain the desired fluxes could account for 20% of the whole cell dry weight.

Comparison of convolutional-neural-networks-based method and LCModel on the quantification of in vivo magnetic resonance spectroscopy.

BACKGROUND: Quantification of metabolites concentrations in institutional unit (IU) is important for inter-subject and long-term comparisons in the applications of magnetic resonance spectroscopy (MRS). Recently, deep learning (DL) algorithms have found a variety of applications on the process of MRS data. A quantification strategy compatible to DL base MRS spectral processing method is, therefore, useful. MATERIALS AND METHODS: This study aims to investigate whether metabolite concentrations quantified using a convolutional neural network (CNN) based method, coupled with a scaling procedure that normalizes spectral signals for CNN input and linear regression, can effectively reflect variations in metabolite concentrations in IU across different brain regions with varying signal-to-noise ratios (SNR) and linewidths (LW). An error index based on standard error (SE) is proposed to indicate the confidence levels associated with metabolite predictions. In vivo MRS spectra were acquired from three brain regions of 43 subjects using a 3T system. RESULTS: The metabolite concentrations in IU of five major metabolites, quantified using CNN and LCModel, exhibit similar ranges with Pearson's correlation coefficients ranging from 0.24 to 0.78. The SE of the metabolites shows a positive correlation with Cramer-Rao lower bound (CRLB) (r=0.46) and  absolute CRLB (r=0.81), calculated by multiplying CRLBs with the quantified metabolite content. CONCLUSION: In conclusion, the CNN based method with the proposed scaling procedures can be employed to quantify in vivo MRS spectra and derive metabolites concentrations in IU. The SE can be used as error index, indicating predicted uncertainties for metabolites and sharing information similar to the absolute CRLB.

Multi-echo single-shot spectroscopy combined with simultaneous 2D model fitting for fast and accurate measurement of metabolite-specific concentrations and T2 relaxation times.

The purpose of the current study was to develop a novel single-voxel MR spectroscopy acquisition scheme to simultaneously determine metabolite-specific concentrations and transverse relaxation times within realistic clinical scan times. Partly truncated multi-TE data are acquired as an echo train in a single acquisition (multi-echo single-shot [MESS]). A 2D multiparametric model fitting approach combines truncated, low-resolved short TE data with fully sampled, highly resolved, longer TE data to yield concentration and T2 estimates for major brain metabolites simultaneously. Cramer-Rao lower bounds (CRLB) are used as a measure of performance. The novel scheme was compared with traditional multi-echo multi-shot methods. In silico, in vitro, and in vivo experiments support the findings. MESS schemes, requiring only 2 min 12 s for the acquisition of three echo times, provide valid concentration and relaxation estimates for multiple metabolites and outperform traditional methods for simultaneous determinations of metabolite-specific T2 s and concentrations, with improvements ranging from 5% to 30% for T2 s and from 10% to 50% for concentrations. However, substantial unsuppressed residual water signals may hamper the method's reproducibility, as observed in an initial experiment setup that prioritizes short TEs with severely truncated acquisition for the benefit of signal-to-noise ratio (SNR). Nevertheless, CRLB have been confirmed to be well suited as design criteria, and within-session repeatability approaches CRLB when residual water is removed in postprocessing by exploiting longer and less truncated data recordings. MESS MRS combined with 2D model fitting promises comparable accuracy, increased precision, or inversely shorter experimental times compared with traditional approaches. However, the optimal design must be investigated as a trade-off between SNR, the truncation factor, and TE batch selections, all of which influence the robustness of estimations.

Quantification of spatially localized MRS by a novel deep learning approach without spectral fitting.

PURPOSE: To propose a novel end-to-end deep learning model to quantify absolute metabolite concentrations from in vivo J-point resolved spectroscopy (JPRESS) without using spectral fitting. METHODS: A novel encoder-decoder-style neural network was created, which was trained to predict metabolite concentrations and individual component signals concurrently from 3T JPRESS data in the time domain. The training data set contained 100 000 samples created by spin-density simulations using experimentally used RF pulses. Concentrations, phase, frequencies, linewidths, and T2 relaxation times in the training data set were varied over a large range with uniform distributions. Random synthesized noise and extraneous signals were added to the data set. Two thousand validation samples were created similarly to the training data set but with mean concentrations close to in vivo values. An in vivo test was conducted with 20 samples acquired from the human brain. RESULTS: Both validation and in vivo test results showed that the proposed model successfully predicted metabolite concentrations as well as individual metabolite signals without involving spectral fitting, while extraneous peaks or unregistered signals were filtered out. Compared with the short-TE spectral fitting by LCModel, the proposed method had the advantage that the undesired correlations between the estimated concentrations and noise levels and between metabolites were eliminated or substantially reduced. CONCLUSION: The proposed method provides a working deep learning model that directly maps in vivo JPRESS data to metabolite concentrations. Because spectral fitting is not used, the trained model does not depend on the assumptions associated with parameter tuning when applied to in vivo data.

A simultaneous, high-throughput and sensitive method for analysing 13 neonicotinoids and metabolites in urine using a liquid chromatography-tandem mass spectrometry.

A simultaneous, high-throughput and sensitive method for analysing nine neonicotinoid pesticides (NEOs) and four metabolites (NEOms) in urine using a liquid chromatography-tandem mass spectrometry (LC-MSMS) was developed. The method detection limit (MDL) and lowest concentration minimum reporting limit (LCMRL) of the nine NEOs were 0.0013-0.048 ng/ml and 0.0050-0.17 ng/ml, respectively. The MDL and LCMRL of the four NEOms were 0.0052-0.52 ng/ml and 0.011-1.6 ng/ml, respectively. Intermediate precision for the nine NEOs and four NEOms was 7.5-12.5% and 7.4-10.9%, respectively. Accuracy for the nine NEOs and four NEOms was 3.83-5.60% and 3.01-29.2%, respectively. The developed method was applied to analyse urine samples collected from participants of a large-scale birth cohort study, namely, the Japan Environment and Children's Study (JECS). •The NEO and NEOm concentrations in 100 µl urine samples were analysed using a highly sensitive LC-MSMS.•Automated solid phase extraction in a 96-well plate was utilised to achieve high-throughput analysis.•Intermediate precision and accuracy were less than 12.5% and 94.8-99.1%, respectively.

Optimized Fast Filtration-Based Sampling and Extraction Enables Precise and Absolute Quantification of the Escherichia coli Central Carbon Metabolome.

Precise and accurate quantification is a prerequisite for interpretation of targeted metabolomics data, but this task is challenged by the inherent instability of the analytes. The sampling, quenching, extraction, and sample purification conditions required to recover and stabilize metabolites in representative extracts have also been proven highly dependent on species-specific properties. For Escherichia coli, unspecific leakage has been demonstrated for conventional microbial metabolomics sampling protocols. We herein present a fast filtration-based sampling protocol for this widely applied model organism, focusing on pitfalls such as inefficient filtration, selective loss of biomass, matrix contamination, and membrane permeabilization and leakage. We evaluate the effect of and need for removal of extracellular components and demonstrate how residual salts can challenge analytical accuracy of hyphenated mass spectrometric analyses, even when sophisticated correction strategies are applied. Laborious extraction procedures are bypassed by direct extraction in cold acetonitrile:water:methanol (3:5:2, v/v%), ensuring compatibility with sample concentration and thus, any downstream analysis. By applying this protocol, we achieve and demonstrate high precision and low metabolite turnover, and, followingly, minimal perturbation of the inherent metabolic state. This allows us to herein report absolute intracellular concentrations in E. coli and explore its central carbon metabolome at several commonly applied cultivation conditions.

Post-acquisition water-signal removal in 3D water-unsuppressed 1 H-MR spectroscopic imaging of the prostate.

PURPOSE: To develop a robust processing procedure of raw signals from water-unsuppressed MRSI of the prostate for the mapping of absolute tissue concentrations of metabolites. METHODS: Water-unsuppressed 3D MRSI data were acquired from a phantom, from healthy volunteers, and a patient with prostate cancer. Signal processing included sequential computation of the modulus of the FID to remove water sidebands, a Hilbert transformation, and k-space Hamming filtering. For the removal of the water signal, we compared Löwner tensor-based blind source separation (BSS) and Hankel Lanczos singular value decomposition techniques. Absolute metabolite levels were quantified with LCModel and the results were statistically analyzed to compare the water removal methods and conventional water-suppressed MRSI. RESULTS: The post-processing algorithms successfully removed the water signal and its sidebands without affecting metabolite signals. The best water removal performance was achieved by Löwner tensor-based BSS. Absolute tissue concentrations of citrate in the peripheral zone derived from water-suppressed and unsuppressed 1 H MRSI were the same and as expected from the known physiology of the healthy prostate. Maps for citrate and choline from water-unsuppressed 3D 1 H-MRSI of the prostate showed expected spatial variations in metabolite levels. CONCLUSION: We developed a robust relatively simple post-processing method of water-unsuppressed MRSI of the prostate to remove the water signal. Absolute quantification using the water signal, originating from the same location as the metabolite signals, avoids the acquisition of additional reference data.

Phthalate exposure and cumulative risk in a Chinese newborn population.

Phthalates have been attracted as a considerable attention in toxicological research as well as public health context due to their ubiquitous occurrence and potential adverse health effects. Newborns are susceptible to the environmental risk factors; however, data are still limited on newborn phthalate exposure and risk assessment worldwide, especially in China. This study was nested in a cross-sectional retrospective study of 1359 pregnant women recruited in Xiamen Maternity and Child Care Hospital, China, during June to July 2012. All urine samples from newborn were collected using disposal diapers during the first two postnatal days, and seven phthalate metabolites were measured by LC-ESI-MS/MS. Phthalate exposure and accumulation risk were evaluated based on the measured newborn urinary internal doses. The detection rate (96.5%) and the median concentration (17.5 ng/mL) of mono-n-butyl phthalate (MBP) were the highest, while monobenzyl phthalate (MBzP) concentration was the lowest with a detection rate (1.50%). By estimating the daily intakes of the parent phthalates, their EDI were 0.04, 0.10, 0.32, 0.00, and 0.12 µg/kg-bw/day for dimethyl phthalate (DMP), diethyl phthalate (DEP), di-n-butyl phthalates (DBP), benzyl butyl phthalate (BBzP), and di-(2-ethylhexyl) phthalate (DEHP), respectively. The newborns were commonly exposed to phthalates but no one exceeds the regulated tolerable daily intake (TDI) values in this large newborn population.

Intestinal microbiota composition in patients with amyotrophic lateral sclerosis: establishment of bacterial and archaeal communities analyses / 中华医学杂志(英文版)

Background@#Emerging evidences have indicated that the composition of gut microbiota was significantly influenced by central nervous system diseases. The digestion and metabolism disturbances of patients with amyotrophic lateral sclerosis (ALS) might be strongly associated with ALS; however, this has rarely been evaluated in these populations. This study was to evaluate bacterial and archaeal composition of gut flora and the corresponding metabolism performance of these micro-organisms in fecal samples of patients with ALS.@*Methods@#A comparative study was performed on the intestinal microbiota from eight patients with ALS and eight healthy individuals at Huadong Hospital during November 2017 to April 2018; meanwhile, the metabolite concentrations of human endotoxin, short-chain fatty acids (SCFA), NO2-N/NO3-N, and γ-aminobutyric acid were also evaluated by spectrophotometry methods. The correlations between intestinal microbiota and metabolite concentration were compared between the two groups using one-way analysis of variance; the relative abundance of beneficial and harmful micro-organisms in fecal samples was also analyzed.@*Results@#In general, the richness and evenness of bacterial and archaeal communities of healthy individuals were healthier than that of patients with ALS. The phylum Firmicutes/Bacteroidetes ratio, genus Methanobrevibacter showed an enhancive tendency in patients with ALS, whereas the relative abundance of beneficial micro-organisms (genera Faecalibacterium and Bacteroides) presented a significant decrease tendency in patients with ALS. In addition, the average concentrations of human endotoxin, SCFA, NO2-N/NO3-N, and γ-aminobutyric acid in patients with ALS and healthy individuals were 64.2 vs. 65.3 EU/mL, 57.5 vs. 55.3 μg/mL, 5.7 vs. 5.3 ng/mL, and 6.1 vs. 5.4 μmol/L, respectively, indicating that the digestion and metabolism functions of gastrointestinal tract of patients might decline with this disease.@*Conclusions@#The relative abundance of beneficial and harmful micro-organisms respectively showed decrease and increase tendency in patients with ALS.

Quantitative magnetic resonance spectroscopy at 3T based on the principle of reciprocity.

Quantification of magnetic resonance spectroscopy signals using the phantom replacement method requires an adequate correction of differences between the acquisition of the reference signal in the phantom and the measurement in vivo. Applying the principle of reciprocity, sensitivity differences can be corrected at low field strength by measuring the RF transmitter gain needed to obtain a certain flip angle in the measured volume. However, at higher field strength the transmit sensitivity may vary from the reception sensitivity, which leads to wrongly estimated concentrations. To address this issue, a quantification approach based on the principle of reciprocity for use at 3T is proposed and validated thoroughly. In this approach, the RF transmitter gain is determined automatically using a volume-selective power optimization and complemented with information from relative reception sensitivity maps derived from contrast-minimized images to correct differences in transmission and reception sensitivity. In this way, a reliable measure of the local sensitivity was obtained. The proposed method is used to derive in vivo concentrations of brain metabolites and tissue water in two studies with different coil sets in a total of 40 healthy volunteers. Resulting molar concentrations are compared with results using internal water referencing (IWR) and Electric REference To access In vivo Concentrations (ERETIC). With the proposed method, changes in coil loading and regional sensitivity due to B1 inhomogeneities are successfully corrected, as demonstrated in phantom and in vivo measurements. For the tissue water content, coefficients of variation between 2% and 3.5% were obtained (0.6-1.4% in a single subject). The coefficients of variation of the three major metabolites ranged from 3.4-14.5%. In general, the derived concentrations agree well with values estimated with IWR. Hence, the presented method is a valuable alternative for IWR, without the need for additional hardware such as ERETIC and with potential advantages in diseased tissue.

Accurate determination of brain metabolite concentrations using ERETIC as external reference.

Magnetic Resonance Spectroscopy (MRS) can provide in vivo metabolite concentrations in standard concentration units if a reliable reference signal is available. For 1 H MRS in the human brain, typically the signal from the tissue water is used as the (internal) reference signal. However, a concentration determination based on the tissue water signal most often requires a reliable estimate of the water concentration present in the investigated tissue. Especially in clinically interesting cases, this estimation might be difficult. To avoid assumptions about the water in the investigated tissue, the Electric REference To access In vivo Concentrations (ERETIC) method has been proposed. In this approach, the metabolite signal is compared with a reference signal acquired in a phantom and potential coil-loading differences are corrected using a synthetic reference signal. The aim of this study, conducted with a transceiver quadrature head coil, was to increase the accuracy of the ERETIC method by correcting the influence of spatial B1 inhomogeneities and to simplify the quantification with ERETIC by incorporating an automatic phase correction for the ERETIC signal. Transmit field ( B1+) differences are minimized with a volume-selective power optimization, whereas reception sensitivity changes are corrected using contrast-minimized images of the brain and by adapting the voxel location in the phantom measurement closely to the position measured in vivo. By applying the proposed B1 correction scheme, the mean metabolite concentrations determined with ERETIC in 21 healthy subjects at three different positions agree with concentrations derived with the tissue water signal as reference. In addition, brain water concentrations determined with ERETIC were in agreement with estimations derived using tissue segmentation and literature values for relative water densities. Based on the results, the ERETIC method presented here is a valid tool to derive in vivo metabolite concentration, with potential advantages compared with internal water referencing in diseased tissue.

Changes of brain metabolite concentrations during maturation in different brain regions measured by chemical shift imaging.

INTRODUCTION: We examined the effect of maturation on the regional distribution of brain metabolite concentrations using multivoxel chemical shift imaging. METHODS: From our pool of pediatric MRI examinations, we retrospectively selected patients showing a normal cerebral MRI scan or no pathologic signal abnormalities at the level of the two-dimensional 1H MRS-CSI sequence and an age-appropriate global neurological development, except for focal neurological deficits. Seventy-one patients (4.5 months-20 years) were identified. Using LC Model, spectra were evaluated from voxels in the white matter, caudate head, and corpus callosum. RESULTS: The concentration of total N-acetylaspartate increased in all regions during infancy and childhood except in the right caudate head where it remained constant. The concentration of total creatine decreased in the caudate nucleus and splenium and minimally in the frontal white matter and genu. It remained largely constant in the parietal white matter. The concentration of choline-containing compounds had the tendency to decrease in all regions except in the parietal white matter where it remained constant. The concentration of myoinositol decreased slightly in the splenium and right frontal white matter, remained constant on the left side and in the caudate nucleus, and rose slightly in the parietal white matter and genu. CONCLUSION: CSI determined metabolite concentrations in multiple cerebral regions during routine MRI. The obtained data will be helpful in future pediatric CSI measurements deciding whether the ratios of the main metabolites are within the range of normal values or have to be considered as probably pathologic.

Relationship between blood plasma and synovial fluid metabolite concentrations in patients with osteoarthritis.

OBJECTIVE: To investigate the relationship between plasma and synovial fluid (SF) metabolite concentrations in patients with osteoarthritis (OA). METHODS: Blood plasma and SF samples were collected from patients with primary knee OA undergoing total knee arthroplasty. Metabolic profiling was performed by electrospray ionization tandem mass spectrometry using the AbsoluteIDQ kit. The profiling yielded 168 metabolite concentrations. Correlation analysis between SF and plasma metabolite concentrations was done on absolute concentrations as well as metabolite concentration ratios using Spearman's rank correlation (ρ) method. RESULTS: A total of 69 patients with knee OA were included, 30 men and 39 women, with an average age of 66 ± 8 years. For the absolute metabolite concentrations, the average ρ was 0.23 ± 0.13. Only 8 out of 168 metabolite concentrations had a ρ ≥ 0.45, with a p value ≤ 2.98 × 10(-4), statistically significant after correcting multiple testing with the Bonferroni method. For the metabolite ratios (n = 28,056), the average ρ was 0.29 ± 0.20. There were 4018 metabolite ratios with a ρ ≥ 0.52 and a p value ≤ 1.78 × 10(-6), significant after correcting multiple testing. Sex-separate analyses found no difference in ρ between men and women. Similarly, there was no difference in ρ between people younger and older than 65 years. CONCLUSION: Correlation between blood plasma and SF metabolite concentrations are modest. Metabolite ratios, which are considered proxies for enzymatic reaction rates and have higher correlations, should be considered when using blood plasma as a surrogate of SF in OA biomarker identification.

Signals of vitellogenesis and estrus in female hawksbill turtles.

This study reports a viable means of identifying the vitellogenic cycle and limited estrus period in hawksbill turtles for the purposes of developing captive breeding program, based on the combination of blood metabolite parameters (triglyceride, total protein, and calcium levels), feeding status, and ovary condition. Follicle size of two focal captive females showed clear seasonal changes, with major development occurring between March and May (19.0-24.4 mm), and exceeding 25 mm between June and September. Triglyceride, total protein, and calcium levels dropped with follicular development and maintenance (March to October), and then began to rise when follicular retraction occurred from October onwards. The two focal turtles reduced food intake during intensive follicular development (April to May). These findings suggest that blood metabolite parameters and feeding conditions are inferred by the vitellogenic cycle. An additional 10 females exhibiting follicular development were mated with a single male for 7-day period between May and June. Follicle size was measured immediately prior to pairing, and a statistically significant difference in follicle size of 10 females was recorded between the seven failed (20.9 mm) and three successful (23.6 mm) mating events. This indicates follicle development is essential to successful mate and monitoring of vitellogenic cycle may help improve the success rates of captive hawksbill breeding programs.

A preliminary examination of cortical neurotransmitter levels associated with heavy drinking in posttraumatic stress disorder.

Posttraumatic stress disorder (PTSD) patients have low cortical concentrations of γ-aminobutyric acid (GABA) and elevated glutamate (Glu) as measured by proton magnetic resonance spectroscopy ((1)H MRS). Alcohol use disorder (AUD) is highly comorbid with PTSD, but the neurobiological underpinnings are largely unknown. We wanted to determine if PTSD patients with AUD have normalized cortical GABA and Glu levels in addition to metabolite alterations common to AUD. We compared brain metabolite concentrations in 10 PTSD patients with comorbid AUD (PAUD) with concentrtations in 28 PTSD patients without AUD and in 20 trauma-exposed controls (CON) without PTSD symptoms. We measured concentrations of GABA, Glu, N-acetylaspartate (NAA), creatine- (Cr) and choline-containing metabolites (Cho), and myo-Inositol (mI) in three cortical brain regions using (1)H MRS and correlated them with measures of neurocognition, insomnia, PTSD symptoms, and drinking severity. In contrast to PTSD, PAUD exhibited normal GABA and Glu concentrations in the parieto-occipital and temporal cortices, respectively, but lower Glu and trends toward higher GABA levels in the anterior cingulate cortex (ACC). Temporal NAA and Cho as well as mI in the ACC were lower in PAUD than in both PTSD and CON. Within PAUD, more cortical GABA and Glu correlated with better neurocognition. Heavy drinking in PTSD is associated with partially neutralized neurotransmitter imbalance, but also with neuronal injury commonly observed in AUD.

A synonymous polymorphic variation in ACADM exon 11 affects splicing efficiency and may affect fatty acid oxidation.

In recent studies combining genome-wide association and tandem-MS based metabolic profiling, a single-nucleotide polymorphism (SNP), rs211718C>T, located far upstream of the MCAD gene (ACADM) was found to be associated with serum concentrations of medium-chain acylcarnitines indicating improved beta-oxidation of medium-chain fatty acids. We examined the functional basis for this association and identified linkage between rs211718 and the intragenic synonymous polymorphic variant c.1161A>G in ACADM exon 11 (rs1061337). Employing minigene studies we show that the c.1161A allele is associated with exon 11 missplicing, and that the c.1161G allele corrects this missplicing. This may result in production of more full length MCAD protein from the c.1161G allele. Our analysis suggests that the improved splicing of the c.1161G allele is due to changes in the relative binding of splicing regulatory proteins SRSF1 and hnRNP A1. Using publicly available pre-aligned RNA-seq data, we find that the ACADM c.1161G allele is expressed at significantly higher levels than the c.1161A allele across different tissues. This supports that c.1161A>G is a functional SNP, which leads to higher MCAD expression, perhaps due to improved splicing. This study is a proof of principle that synonymous SNPs are not neutral. By changing the binding sites for splicing regulatory proteins they can have significant effects on pre-mRNA splicing and thus protein function. In addition, this study shows that for a sequence variation to have an effect, it might need to change the balance in the relative binding of positive and negative splicing factors.