Short Research Communication Hair Metabolomics: Identification of Fetal Compromise Provides Proof of Concept for Biomarker Discovery

Abstract Analysis of the human metabolome has yielded valuable insights into health, disease and toxicity. However, the metabolic profile of complex biological fluids such as blood is highly dynamic and this has limited the discovery of robust biomarkers. Hair grows relatively slowly, and both endogenous compounds and environmental exposures are incorporated from blood into hair during growth, which reflects the average chemical composition over several months. We used hair samples to study the metabolite profiles of women with pregnancies complicated by fetal growth restriction (FGR) and healthy matched controls. We report the use of GC-MS metabolite profiling of hair samples for biomarker discovery. Unsupervised statistical analysis showed complete discrimination of FGR from controls based on hair composition alone. A predictive model combining 5 metabolites produced an area under the receiver-operating curve of 0.998. This is the first study of the metabolome of human hair and demonstrates that this biological material contains robust biomarkers, which may lead to the development of a sensitive diagnostic tool for FGR, and perhaps more importantly, to stable biomarkers for a range of other diseases

Skeletal muscle O-GlcNAc transferase is important for muscle energy homeostasis and whole-body insulin sensitivity

Objective: Given that cellular O-GlcNAcylation levels are thought to be real-time measures of cellular nutrient status and dysregulated O-GlcNAc signaling is associated with insulin resistance, we evaluated the role of O-GlcNAc transferase (OGT), the enzyme that mediates O-GlcNAcylation, in skeletal muscle. Methods: We assessed O-GlcNAcylation levels in skeletal muscle from obese, type 2 diabetic people, and we characterized muscle-specific OGT knockout (mKO) mice in metabolic cages and measured energy expenditure and substrate utilization pattern using indirect calorimetry. Whole body insulin sensitivity was assessed using the hyperinsulinemic euglycemic clamp technique and tissue-specific glucose uptake was subsequently evaluated. Tissues were used for histology, qPCR, Western blot, co-immunoprecipitation, and chromatin immunoprecipitation analyses. Results: We found elevated levels of O-GlcNAc-modified proteins in obese, type 2 diabetic people compared with well-matched obese and lean controls. Muscle-specific OGT knockout mice were lean, and whole body energy expenditure and insulin sensitivity were increased in these mice, consistent with enhanced glucose uptake and elevated glycolytic enzyme activities in skeletal muscle. Moreover, enhanced glucose uptake was also observed in white adipose tissue that was browner than that of WT mice. Interestingly, mKO mice had elevated mRNA levels of Il15 in skeletal muscle and increased circulating IL-15 levels. We found that OGT in muscle mediates transcriptional repression of Il15 by O-GlcNAcylating Enhancer of Zeste Homolog 2 (EZH2). Conclusions: Elevated muscle O-GlcNAc levels paralleled insulin resistance and type 2 diabetes in humans. Moreover, OGT-mediated signaling is necessary for proper skeletal muscle metabolism and whole-body energy homeostasis, and our data highlight O-GlcNAcylation as a potential target for ameliorating metabolic disorders. Keywords: O-GlcNAc signaling, Type 2 diabetes, N-acetyl-d-glucosamine, Tissue cross talk, Epigenetic regulation of Il15 transcription, Insulin sensitivit

Identification of genetic variants associated with Huntington's disease progression: a genome-wide association study

Background Huntington's disease is caused by a CAG repeat expansion in the huntingtin gene, HTT. Age at onset has been used as a quantitative phenotype in genetic analysis looking for Huntington's disease modifiers, but is hard to define and not always available. Therefore, we aimed to generate a novel measure of disease progression and to identify genetic markers associated with this progression measure. Methods We generated a progression score on the basis of principal component analysis of prospectively acquired longitudinal changes in motor, cognitive, and imaging measures in the 218 indivduals in the TRACK-HD cohort of Huntington's disease gene mutation carriers (data collected 2008–11). We generated a parallel progression score using data from 1773 previously genotyped participants from the European Huntington's Disease Network REGISTRY study of Huntington's disease mutation carriers (data collected 2003–13). We did a genome-wide association analyses in terms of progression for 216 TRACK-HD participants and 1773 REGISTRY participants, then a meta-analysis of these results was undertaken. Findings Longitudinal motor, cognitive, and imaging scores were correlated with each other in TRACK-HD participants, justifying use of a single, cross-domain measure of disease progression in both studies. The TRACK-HD and REGISTRY progression measures were correlated with each other (r=0·674), and with age at onset (TRACK-HD, r=0·315; REGISTRY, r=0·234). The meta-analysis of progression in TRACK-HD and REGISTRY gave a genome-wide significant signal (p=1·12 × 10−10) on chromosome 5 spanning three genes: MSH3, DHFR, and MTRNR2L2. The genes in this locus were associated with progression in TRACK-HD (MSH3 p=2·94 × 10−8 DHFR p=8·37 × 10−7 MTRNR2L2 p=2·15 × 10−9) and to a lesser extent in REGISTRY (MSH3 p=9·36 × 10−4 DHFR p=8·45 × 10−4 MTRNR2L2 p=1·20 × 10−3). The lead single nucleotide polymorphism (SNP) in TRACK-HD (rs557874766) was genome-wide significant in the meta-analysis (p=1·58 × 10−8), and encodes an aminoacid change (Pro67Ala) in MSH3. In TRACK-HD, each copy of the minor allele at this SNP was associated with a 0·4 units per year (95% CI 0·16–0·66) reduction in the rate of change of the Unified Huntington's Disease Rating Scale (UHDRS) Total Motor Score, and a reduction of 0·12 units per year (95% CI 0·06–0·18) in the rate of change of UHDRS Total Functional Capacity score. These associations remained significant after adjusting for age of onset. Interpretation The multidomain progression measure in TRACK-HD was associated with a functional variant that was genome-wide significant in our meta-analysis. The association in only 216 participants implies that the progression measure is a sensitive reflection of disease burden, that the effect size at this locus is large, or both. Knockout of Msh3 reduces somatic expansion in Huntington's disease mouse models, suggesting this mechanism as an area for future therapeutic investigation

Reply to "Quality control requirements for the correct annotation of lipidomics data"

REPLYING TO H. Köfeler et al. Nature Communications https://doi.org/10.1038/s41467-021-24984-y (2021

sj-docx-1-aut-10.1177_13623613221119368 – Supplemental material for Non-pharmacological interventions for autistic children: An umbrella review

Supplemental material, sj-docx-1-aut-10.1177_13623613221119368 for Non-pharmacological interventions for autistic children: An umbrella review by David Trembath, Kandice Varcin, Hannah Waddington, Rhylee Sulek, Cathy Bent, Jill Ashburner, Valsamma Eapen, Emma Goodall, Kristelle Hudry, Jacqueline Roberts, Natalie Silove and Andrew Whitehouse in Autism</p

International ring trial of a high resolution targeted metabolomics and lipidomics platform for serum and plasma analysis

A challenge facing metabolomics in the analysis of large human cohorts is the cross-laboratory comparability of quantitative metabolomics measurements. In this study, 14 laboratories analyzed various blood specimens using a common experimental protocol provided with the Biocrates AbsoluteIDQ p400HR kit, to quantify up to 408 metabolites. The specimens included human plasma and serum from male and female donors, mouse and rat plasma, as well as NIST SRM 1950 reference plasma. The metabolite classes covered range from polar (e.g., amino acids and biogenic amines) to nonpolar (e.g., diacyl- and triacyl-glycerols), and they span 11 common metabolite classes. The manuscript describes a strict system suitability testing (SST) criteria used to evaluate each laboratory's readiness to perform the assay, and provides the SST Skyline documents for public dissemination. The study found approximately 250 metabolites were routinely quantified in the sample types tested, using Orbitrap instruments. Interlaboratory variance for the NIST SRM-1950 has a median of 10% for amino acids, 24% for biogenic amines, 38% for acylcarnitines, 25% for glycerolipids, 23% for glycerophospholipids, 16% for cholesteryl esters, 15% for sphingolipids, and 9% for hexoses. Comparing to consensus values for NIST SRM-1950, nearly 80% of comparable analytes demonstrated bias of &lt;50% from the reference value. The findings of this study result in recommendations of best practices for system suitability, quality control, and calibration. We demonstrate that with appropriate controls, high-resolution metabolomics can provide accurate results with good precision across laboratories, and the p400HR therefore is a reliable approach for generating consistent and comparable metabolomics data