Four-dimensional lipidomics profiling in X-linked adrenoleukodystrophy using trapped ion mobility mass spectrometry.

Lipids play pivotal roles in an extensive range of metabolic and physiological processes. In recent years, the convergence of trapped ion mobility spectrometry and MS has enabled 4D-lipidomics, a highly promising technology for comprehensive lipid analysis. 4D-lipidomics assesses lipid annotations across four distinct dimensions-retention time, collisional cross section, m/z (mass-to-charge ratio), and MS/MS spectra-providing a heightened level of confidence in lipid annotation. These advantages prove particularly valuable when investigating complex disorders involving lipid metabolism, such as adrenoleukodystrophy (ALD). ALD is characterized by the accumulation of very-long-chain fatty acids (VLCFAs) due to pathogenic variants in the ABCD1 gene. A comprehensive 4D-lipidomics strategy of ALD fibroblasts demonstrated significant elevations of various lipids from multiple classes. This indicates that the changes observed in ALD are not confined to a single lipid class and likely impacts a broad spectrum of lipid-mediated physiological processes. Our findings highlight the incorporation of mainly saturated and monounsaturated VLCFA variants into a range of lipid classes, encompassing phosphatidylcholines, triacylglycerols, and cholesterol esters. These include ultra-long-chain fatty acids with a length of up to thirty carbon atoms. Lipid species containing C26:0 and C26:1 were the most frequently detected VLCFA lipids in our study. Furthermore, we report a panel of 121 new candidate biomarkers in fibroblasts, exhibiting significant differentiation between controls and individuals with ALD. In summary, this study demonstrates the capabilities of a 4D-lipid profiling workflow in unraveling novel insights into the intricate lipid modifications associated with metabolic disorders like ALD.

ABHD16A deficiency causes a complicated form of hereditary spastic paraplegia associated with intellectual disability and cerebral anomalies.

ABHD16A (abhydrolase domain-containing protein 16A, phospholipase) encodes the major phosphatidylserine (PS) lipase in the brain. PS lipase synthesizes lysophosphatidylserine, an important signaling lipid that functions in the mammalian central nervous system. ABHD16A has not yet been associated with a human disease. In this report, we present a cohort of 11 affected individuals from six unrelated families with a complicated form of hereditary spastic paraplegia (HSP) who carry bi-allelic deleterious variants in ABHD16A. Affected individuals present with a similar phenotype consisting of global developmental delay/intellectual disability, progressive spasticity affecting the upper and lower limbs, and corpus callosum and white matter anomalies. Immunoblot analysis on extracts from fibroblasts from four affected individuals demonstrated little to no ABHD16A protein levels compared to controls. Our findings add ABHD16A to the growing list of lipid genes in which dysregulation can cause complicated forms of HSP and begin to describe the molecular etiology of this condition.

Plasma oxylipin profiling identifies polyunsaturated vicinal diols as responsive to arachidonic acid and docosahexaenoic acid intake in growing piglets.

The dose-responsiveness of plasma oxylipins to incremental dietary intake of arachidonic acid (20:4n-6; ARA) and docosahexaenoic acid (22:6n-3; DHA) was determined in piglets. Piglets randomly received one of six formulas (n = 8 per group) from days 3 to 27 postnatally. Diets contained incremental ARA or incremental DHA levels as follows (% fatty acid, ARA/DHA): (A1) 0.1/1.0; (A2) 0.53/1.0; (A3-D3) 0.69/1.0; (A4) 1.1/1.0; (D1) 0.66/0.33; and (D2) 0.67/0.62, resulting in incremental intake (g/kg BW/day) of ARA: 0.07 ± 0.01, 0.43 ± 0.03, 0.55 ± 0.03, and 0.82 ± 0.05 at constant DHA intake (0.82 ± 0.05), or incremental intake of DHA: 0.27 ± 0.02, 0.49 ± 0.03, and 0.81 ± 0.05 at constant ARA intake (0.54 ± 0.04). Plasma oxylipin concentrations and free plasma PUFA levels were determined at day 28 using LC-MS/MS. Incremental dietary ARA intake dose-dependently increased plasma ARA levels. In parallel, ARA intake dose-dependently increased ARA-derived diols 5,6- and 14,15-dihydroxyeicosatrienoic acid (DiHETrE) and linoleic acid-derived 12,13-dihydroxyoctadecenoic acid (DiHOME), downstream metabolites of cytochrome P450 expoxygenase (CYP). The ARA epoxide products from CYP are important in vascular homeostatic maintenance. Incremental DHA intake increased plasma DHA and most markedly raised the eicosapentaenoic acid (EPA) metabolite 17,18-dihydroxyeicosatetraenoic acid (DiHETE) and the DHA metabolite 19,20-dihydroxydocosapentaenoic acid (DiHDPE). In conclusion, increasing ARA and DHA intake dose-dependently influenced endogenous n-6 and n-3 oxylipin plasma concentrations in growing piglets, although the biological relevance of these findings remains to be determined.

Alterations in ether lipid metabolism and the consequences for the mouse lipidome.

Alkylglycerol monooxygenase (AGMO) and plasmanylethanolamine desaturase (PEDS1) are enzymes involved in ether lipid metabolism. While AGMO degrades plasmanyl lipids by oxidative cleavage of the ether bond, PEDS1 exclusively synthesizes a specific subclass of ether lipids, the plasmalogens, by introducing a vinyl ether double bond into plasmanylethanolamine phospholipids. Ether lipids are characterized by an ether linkage at the sn-1 position of the glycerol backbone and they are found in membranes of different cell types. Decreased plasmalogen levels have been associated with neurological diseases like Alzheimer's disease. Agmo-deficient mice do not present an obvious phenotype under unchallenged conditions. In contrast, Peds1 knockout mice display a growth phenotype. To investigate the molecular consequences of Agmo and Peds1 deficiency on the mouse lipidome, five tissues from each mouse model were isolated and subjected to high resolution mass spectrometry allowing the characterization of up to 2013 lipid species from 42 lipid subclasses. Agmo knockout mice moderately accumulated plasmanyl and plasmenyl lipid species. Peds1-deficient mice manifested striking changes characterized by a strong reduction of plasmenyl lipids and a concomitant massive accumulation of plasmanyl lipids resulting in increased total ether lipid levels in the analyzed tissues except for the class of phosphatidylethanolamines where total levels remained remarkably constant also in Peds1 knockout mice. The rate-limiting enzyme in ether lipid metabolism, FAR1, was not upregulated in Peds1-deficient mice, indicating that the selective loss of plasmalogens is not sufficient to activate the feedback mechanism observed in total ether lipid deficiency.

First-Trimester Serum Acylcarnitine Levels to Predict Preeclampsia: A Metabolomics Approach.

OBJECTIVE: To expand the search for preeclampsia (PE) metabolomics biomarkers through the analysis of acylcarnitines in first-trimester maternal serum. METHODS: This was a nested case-control study using serum from pregnant women, drawn between 8 and 14 weeks of gestational age. Metabolites were measured using an UPLC-MS/MS based method. Concentrations were compared between controls (n = 500) and early-onset- (EO-) PE (n = 68) or late-onset- (LO-) PE (n = 99) women. Metabolites with a false discovery rate <10% for both EO-PE and LO-PE were selected and added to prediction models based on maternal characteristics (MC), mean arterial pressure (MAP), and previously established biomarkers (PAPPA, PLGF, and taurine). RESULTS: Twelve metabolites were significantly different between EO-PE women and controls, with effect levels between -18% and 29%. For LO-PE, 11 metabolites were significantly different with effect sizes between -8% and 24%. Nine metabolites were significantly different for both comparisons. The best prediction model for EO-PE consisted of MC, MAP, PAPPA, PLGF, taurine, and stearoylcarnitine (AUC = 0.784). The best prediction model for LO-PE consisted of MC, MAP, PAPPA, PLGF, and stearoylcarnitine (AUC = 0.700). CONCLUSION: This study identified stearoylcarnitine as a novel metabolomics biomarker for EO-PE and LO-PE. Nevertheless, metabolomics-based assays for predicting PE are not yet suitable for clinical implementation.

Metabolomics profiling for identification of novel potential markers in early prediction of preeclampsia.

OBJECTIVE: The first aim was to investigate specific signature patterns of metabolites that are significantly altered in first-trimester serum of women who subsequently developed preeclampsia (PE) compared to healthy pregnancies. The second aim of this study was to examine the predictive performance of the selected metabolites for both early onset [EO-PE] and late onset PE [LO-PE]. METHODS: This was a case-control study of maternal serum samples collected between 8+0 and 13+6 weeks of gestation from 167 women who subsequently developed EO-PE n = 68; LO-PE n = 99 and 500 controls with uncomplicated pregnancies. Metabolomics profiling analysis was performed using two methods. One has been optimized to target eicosanoids/oxylipins, which are known inflammation markers and the other targets compounds containing a primary or secondary biogenic amine group. Logistic regression analyses were performed to predict the development of PE using metabolites alone and in combination with first trimester mean arterial pressure (MAP) measurements. RESULTS: Two metabolites were significantly different between EO-PE and controls (taurine and asparagine) and one in case of LO-PE (glycylglycine). Taurine appeared the most discriminative biomarker and in combination with MAP predicted EO-PE with a detection rate (DR) of 55%, at a false-positive rate (FPR) of 10%. CONCLUSION: Our findings suggest a potential role of taurine in both PE pathophysiology and first trimester screening for EO-PE.

The automatic recognition and counting of cough.

BACKGROUND: Cough recordings have been undertaken for many years but the analysis of cough frequency and the temporal relation to trigger factors have proven problematic. Because cough is episodic, data collection over many hours is required, along with real-time aural analysis which is equally time-consuming. A method has been developed for the automatic recognition and counting of coughs in sound recordings. METHODS: The Hull Automatic Cough Counter (HACC) is a program developed for the analysis of digital audio recordings. HACC uses digital signal processing (DSP) to calculate characteristic spectral coefficients of sound events, which are then classified into cough and non-cough events by the use of a probabilistic neural network (PNN). Parameters such as the total number of coughs and cough frequency as a function of time can be calculated from the results of the audio processing. Thirty three smoking subjects, 20 male and 13 female aged between 20 and 54 with a chronic troublesome cough were studied in the hour after rising using audio recordings. RESULTS: Using the graphical user interface (GUI), counting the number of coughs identified by HACC in an hour long recording, took an average of 1 minute 35 seconds, a 97.5% reduction in counting time. HACC achieved a sensitivity of 80% and a specificity of 96%. Reproducibility of repeated HACC analysis is 100%. CONCLUSION: An automated system for the analysis of sound files containing coughs and other non-cough events has been developed, with a high robustness and good degree of accuracy towards the number of actual coughs in the audio recording.