PubMed

Allergy. 2023 Feb 13. doi: 10.1111/all.15672. Online ahead of print.NO ABSTRACTPMID:36785923 | DOI:10.1111/all.15672

Oxid Med Cell Longev. 2023 Feb 4;2023:4416410. doi: 10.1155/2023/4416410. eCollection 2023.ABSTRACTAging is a complex process characterized by progressive loss of functional abilities due to the accumulation of molecular damages. Metabolomics could offer novel insights into the predictors and mechanisms of aging. This cross-sectional study is aimed at identifying age-associated plasma metabolome in a Malay population. A total of 146 (90 females) healthy participants aged 28-69 were selected for the study. Untargeted metabolomics profiling was performed using liquid chromatography-tandem mass spectrometry. Association analysis was based on the general linear model. Gender-associated metabolites were adjusted for age, while age-associated metabolites were adjusted for gender or analyzed in a gender-stratified manner. Gender-associated metabolites such as 4-hydroxyphenyllactic acid, carnitine, cortisol, and testosterone sulfate showed higher levels in males than females. Deoxycholic acid and hippuric acid were among the metabolites with a positive association with age after being adjusted for gender, while 9(E),11(E)-conjugated linoleic acid, cortisol, and nicotinamide were negatively associated with age. In gender-stratified analysis, glutamine was one of the common metabolites that showed a direct association with age in both genders, while metabolites such as 11-deoxy prostaglandin F2β, guanosine monophosphate, and testosterone sulfate were inversely associated with age in males and females. This study reveals several age-associated metabolites in Malays that could reflect the changes in metabolisms during aging and may be used to discern the risk of geriatric syndromes and disorders later. Further studies are required to determine the interplay between these metabolites and environmental factors on the functional outcomes during aging.PMID:36785791 | PMC:PMC9922189 | DOI:10.1155/2023/4416410

PeerJ. 2023 Feb 8;11:e14869. doi: 10.7717/peerj.14869. eCollection 2023.ABSTRACTSugar metabolites not only act as the key compounds in tea plant response to stress but are also critical for tea quality formation during the post-harvest processing of tea leaves. However, the mechanisms by which sugar metabolites in post-harvest tea leaves respond to mechanical stress are unclear. In this study, we aimed to investigate the effects of mechanical stress on saccharide metabolites and related post-harvest tea genes. Withered (C15) and mechanically-stressed (V15) for 15 min Oolong tea leaves were used for metabolome and transcriptome sequencing analyses. We identified a total of 19 sugar metabolites, most of which increased in C15 and V15. A total of 69 genes related to sugar metabolism were identified using transcriptome analysis, most of which were down-regulated in C15 and V15. To further understand the relationship between the down-regulated genes and sugar metabolites, we analyzed the sucrose and starch, galactose, and glycolysis metabolic pathways, and found that several key genes of invertase (INV), α-amylase (AMY), β-amylase (BMY), aldose 1-epimerase (AEP), and α-galactosidase (AGAL) were down-regulated. This inhibited the hydrolysis of sugars and might have contributed to the enrichment of galactose and D-mannose in V15. Additionally, galactinol synthase (Gols), raffinose synthase (RS), hexokinase (HXK), 6-phosphofructokinase 1 (PFK-1), and pyruvate kinase (PK) genes were significantly upregulated in V15, promoting the accumulation of D-fructose-6-phosphate (D-Fru-6P), D-glucose-6-phosphate (D-glu-6P), and D-glucose. Transcriptome and metabolome association analysis showed that the glycolysis pathway was enhanced and the hydrolysis rate of sugars related to hemicellulose synthesis slowed in response to mechanical stress. In this study, we explored the role of sugar in the response of post-harvest tea leaves to mechanical stress by analyzing differences in the expression of sugar metabolites and related genes. Our results improve the understanding of post-harvest tea's resistance to mechanical stress and the associated mechanism of sugar metabolism. The resulting treatment may be used to control the quality of Oolong tea.PMID:36785711 | PMC:PMC9921968 | DOI:10.7717/peerj.14869

Biophys J. 2023 Feb 10;122(3S1):93a-94a. doi: 10.1016/j.bpj.2022.11.702.NO ABSTRACTPMID:36785094 | DOI:10.1016/j.bpj.2022.11.702

BMC Plant Biol. 2023 Feb 13;23(1):89. doi: 10.1186/s12870-023-04093-2.ABSTRACTBACKGROUND: Leaves of tobacco (Nicotiana tabacum L.) are flue-cured to use as a key industrial supply in various parts of the world. The quality of tobacco leaves is dependent on chemical components and their proportions. Generally, the stem attached to tobacco leaf is detached before curing. However, the leaf stem remains green for an extended period of time (as compared to leaf) during flue-curing. Hence, it is expected to affect the quality of tobacco's final product.RESULTS: To understand the impact of the green stem of leaf on the metabolome of flue-cured tobacco, we employed a broad targeted metabolomics approach. We selected two tobacco cultivars (Yun87 and K326) and cultivated them in five geographic locations in China. For flue-curing, leaves were harvested without a stem (L) or with an attached stem (SPL). After metabolome analysis, a total of 1027 metabolites were annotated in these samples. A variable number of metabolites were differentially accumulated between both types of leaves (depending on geographic location or cultivar) representing an influence of environment or genotype. Interestingly, only 68 metabolites were differentially accumulated between L and SPL samples irrespective of the cultivar or geographic location. These differentially accumulated metabolites belonged to major groups of primary and secondary metabolites. We have discussed the importance of identified metabolites in terms of carbon, nitrogen, and polyphenolic metabolism.CONCLUSION: The present research is the first comprehensive description of several metabolites in tobacco leaves related to the contribution of leaf stem. The current study opens novel prospects for investigating the potential of such metabolites in improving the quality of flue-cured tobacco.PMID:36782114 | DOI:10.1186/s12870-023-04093-2

Diabet Med. 2023 Feb 13:e15064. doi: 10.1111/dme.15064. Online ahead of print.ABSTRACTOBJECTIVE: The objective of this scoping review is to evaluate the current biomarkers used in the assessment of adverse cardiac remodelling in people with diabetes mellitus (DM) and in the prognosis of subsequent cardiovascular disease. We aim to discuss the biomarkers' pathophysiological roles as a reflection of the cardiac remodelling mechanisms in the presence of DM.REVIEW METHODS AND DATA SOURCES: We performed the literature search from June to September 2021 using the following databases: MEDLINE, Scopus, Web of Science, PubMed, and Cochrane library. Articles that met our inclusion criteria were screened and appraised before being included in this review. The PRISMA guidelines for Scoping Reviews were followed.RESULTS: Our literature search identified a total of 43 eligible articles, which were included in this scoping review. We identified 15 different biomarkers that were used to determine signs of cardiac remodelling in cardiovascular disease (CVD) and people with DM. NT-proBNP was identified as the most frequently employed biomarker in this context, however we also identified emerging biomarkers including hs-CRP, hs-cTnT, and Galectin-3.CONCLUSIONS: There is a complex relationship between DM and cardiovascular health, where more research is needed. Current biomarkers reflective of adverse cardiac remodelling in DM are often used to diagnose other CVDs, such as NT-proBNP for heart failure. Hence there is a need for identification of specific biomarkers that can detect early signs of cardiac remodelling. Further research into these biomarkers and mechanisms can deepen our understanding on their role in DM-associated CVD and lead to better preventative therapies.PMID:36782075 | DOI:10.1111/dme.15064

Methods Mol Biol. 2023;2628:489-504. doi: 10.1007/978-1-0716-2978-9_29.ABSTRACTMass spectrometry remains one of the gold standard approaches in examining the lipidome in biological samples. Recently, advancements in chromatography and mass spectrometry approaches have enabled broad coverage of the lipidome. However, many limitations still exist, and lipidomic analysis often requires a fine balance between coverage of the lipidome, structural detail, and sample throughput. For biomedical and clinical research using human samples, the diversity and natural variation between different individuals necessitate larger sample numbers to identify significant associations with clinical outcomes and account for potential confounding factors. Here we describe a targeted lipidomics workflow that enables reproducible profiling of thousands of plasma samples in a systematic manner, while maintaining good structural detail and high coverage of the lipidome.PMID:36781803 | DOI:10.1007/978-1-0716-2978-9_29

Methods Mol Biol. 2023;2628:207-219. doi: 10.1007/978-1-0716-2978-9_14.ABSTRACTIn the last years, platelet concentrates such as leukocyte-platelet-rich fibrin (L-PRF) have been used in different clinical scenarios as a huge source of growth factors to enhance wound healing. However, platelet concentrates release many other proteins that also participate in tissue regeneration processes. In this context, the analysis of the L-PRF secretome would provide relevant information on the different proteins and growth factors released by these platelet concentrates, how such secretion varies with the time, and how relevant this could be for the regenerative properties of these products. In the present chapter, we will provide a protocol for isolation, culture, and secretome analysis of L-PRF membranes. Qualitative and quantitative proteomic approaches will be presented, including gel-based and quantitative Sequential Window Acquisition of All Theoretical Mass Spectra (SWATH-MS)-based approaches. This protocol has been recently applied with success to define the L-PRF secretome composition, setting the stage for further research that can provide relevant information on the clinical properties of these platelet concentrates' subtype.PMID:36781788 | DOI:10.1007/978-1-0716-2978-9_14

Sci Rep. 2023 Feb 13;13(1):2533. doi: 10.1038/s41598-023-28551-x.ABSTRACTTongkat ali commonly known as Malaysian Ginseng (Eurycoma longifolia) is a herbal root worldwide available in nutraceuticals, either as a crude powder or capsules blended with other herbal products. Herein, a multiplexed metabolomics approach based on nuclear magnetic resonance (NMR) and solid-phase microextraction combined with gas chromatography-mass spectrometry (SPME-GC-MS) was applied for authentic tongkat ali extract vs some commercial products quality control analysis. NMR metabolite fingerprinting identified 15 major metabolites mostly ascribed to sugars, organic and fatty acids in addition to quassinoids and cinnamates. Following that, multivariate analysis as the non-supervised principal component analysis (PCA) and supervised orthogonal partial least squares-discriminant analysis (OPLS-DA) were applied revealing that differences were related to fatty acids and 13,21-dihydroeurycomanone being more enriched in authentic root. SPME-GC-MS aroma profiling led to the identification of 59 volatiles belonging mainly to alcohols, aldehydes/furans and sesquiterpene hydrocarbons. Results revealed that aroma of commercial products showed relatively different profiles being rich in vanillin, maltol, and methyl octanoate. Whereas E-cinnamaldehyde, endo-borneol, terpinen-4-ol, and benzaldehyde were more associated to the authentic product. The present study shed the light for the potential of metabolomics in authentication and standardization of tongkat ali and identification of its true flavor composition.PMID:36781893 | DOI:10.1038/s41598-023-28551-x

Nat Commun. 2023 Feb 13;14(1):809. doi: 10.1038/s41467-023-36370-x.ABSTRACTRearrangments in Histone-lysine-N-methyltransferase 2A (KMT2Ar) are associated with pediatric, adult and therapy-induced acute leukemias. Infants with KMT2Ar acute lymphoblastic leukemia (ALL) have a poor prognosis with an event-free-survival of 38%. Herein we evaluate 1116 FDA approved compounds in primary KMT2Ar infant ALL specimens and identify a sensitivity to proteasome inhibition. Upon exposure to this class of agents, cells demonstrate a depletion of histone H2B monoubiquitination (H2Bub1) and histone H3 lysine 79 dimethylation (H3K79me2) at KMT2A target genes in addition to a downregulation of the KMT2A gene expression signature, providing evidence that it targets the KMT2A transcriptional complex and alters the epigenome. A cohort of relapsed/refractory KMT2Ar patients treated with this approach on a compassionate basis had an overall response rate of 90%. In conclusion, we report on a high throughput drug screen in primary pediatric leukemia specimens whose results translate into clinically meaningful responses. This innovative treatment approach is now being evaluated in a multi-institutional upfront trial for infants with newly diagnosed ALL.PMID:36781850 | DOI:10.1038/s41467-023-36370-x

Cell Death Dis. 2023 Feb 13;14(2):116. doi: 10.1038/s41419-023-05629-y.ABSTRACTFKBP51 plays a relevant role in sustaining cancer cells, particularly melanoma. This cochaperone participates in several signaling pathways. FKBP51 forms a complex with Akt and PHLPP, which is reported to dephosphorylate Akt. Given the recent discovery of a spliced FKBP51 isoform, in this paper, we interrogate the canonical and spliced isoforms in regulation of Akt activation. We show that the TPR domain of FKBP51 mediates Akt ubiquitination at K63, which is an essential step for Akt activation. The spliced FKBP51, lacking such domain, cannot link K63-Ub residues to Akt. Unexpectedly, PHLPP silencing does not foster phosphorylation of Akt, and its overexpression even induces phosphorylation of Akt. PHLPP stabilizes levels of E3-ubiquitin ligase TRAF6 and supports K63-ubiquitination of Akt. The interactome profile of FKBP51 from melanoma cells highlights a relevant role for PHLPP in improving oncogenic hallmarks, particularly, cell proliferation.PMID:36781840 | DOI:10.1038/s41419-023-05629-y

Methods Mol Biol. 2023;2628:557-577. doi: 10.1007/978-1-0716-2978-9_32.ABSTRACTIn targeted proteomics experiments, selecting the appropriate proteotypic peptides as surrogate for the target protein is a crucial pre-acquisition step. This step is largely a bioinformatics exercise that involves integrating information on the peptides and proteins and using various software tools and knowledgebases. We present here a few resources that automate and simplify the selection process to a great degree. These tools and knowledgebases were developed primarily to streamline targeted proteomics assay development and include PeptidePicker, PeptidePickerDB, MRMAssayDB, MouseQuaPro, and PeptideTracker. We have used these tools to develop and document thousands of targeted proteomics assays, many of them for plasma proteins with focus on human and mouse. An important aspect in all these resources is the integrative approach on which they are based. Using these tools in the first steps of designing a singleplexed or multiplexed targeted proteomic experiment can reduce the necessary experimental steps tremendously. All the tools and knowledgebases we describe here are Web-based and freely accessible so scientists can query the information conveniently from the browser. This chapter provides an overview of these software tools and knowledgebases, their content, and how to use them for targeted plasma proteomics. We further demonstrate how to use them with the results of the HUPO Human Plasma Proteome Project to produce a new database of 3.8 k targeted assays for known human plasma proteins. Upon experimental validation, these assays should help in the further quantitative characterizing of the plasma proteome.PMID:36781806 | DOI:10.1007/978-1-0716-2978-9_32

Methods Mol Biol. 2023;2628:439-473. doi: 10.1007/978-1-0716-2978-9_27.ABSTRACTPreclinical and clinical trials require rapid, precise, and multiplexed analytical methods to characterize the complex samples and to allow high-throughput biomarker monitoring with low consumption of sample material. Targeted proteomics has been used to address these challenges when quantifying protein abundances in complex biological matrices. In many of these studies, blood plasma is collected either as the main research or diagnostic sample or in combination with other specimens. Mass spectrometry (MS)-based targeted proteomics using multiple reaction monitoring (MRM) or parallel reaction monitoring (PRM) with stable isotope-labeled internal standard (SIS) peptides allows robust characterization of blood plasma protein via absolute quantification. Compared to other commonly used technologies like enzyme-linked immunosorbent assay (ELISA), targeted proteomics is faster, more sensitive, and more cost-effective. Here we describe a protocol for the quantification of proteins in blood plasma using targeted MRM proteomics with heavy-labeled internal standards. The 270-protein panel allows rapid and robust absolute quantitative proteomic characterization of blood plasma in a 1 h gradient. The method we describe here works for non-depleted plasma, which makes it simple and easy to implement. Moreover, the protocol works with the two most commonly used blood plasma collection methods used in practice, namely, either K2EDTA or sodium citrate as anticoagulants.PMID:36781801 | DOI:10.1007/978-1-0716-2978-9_27

Methods Mol Biol. 2023;2628:109-125. doi: 10.1007/978-1-0716-2978-9_8.ABSTRACTBlood in the circulatory system carries information of physiological and pathological status of the human body, so blood proteins are often used as biomarkers for diagnosis, prognosis, and therapy. Human blood proteome can be explored by the latest technologies in mass spectrometry (MS), creating an opportunity of discovering new disease biomarkers. The extreme dynamic range of protein concentrations in blood, however, poses a challenge to detect proteins of low abundance, namely, tissue leakage proteins. Here, we describe a strategy to directly analyze undepleted blood samples by extensive liquid chromatography (LC) fractionation and 18-plex tandem-mass-tag (TMT) mass spectrometry. The proteins in blood specimens (e.g., plasma or serum) are isolated by acetone precipitation and digested into peptides. The resulting peptides are TMT-labeled, separated by basic pH reverse-phase (RP) LC into at least 40 fractions, and analyzed by acidic pH RPLC and high-resolution MS/MS, leading to the quantification of ~3000 unique proteins. Further increase of basic pH RPLC fractions and adjustment of the fraction concatenation strategy can enhance the proteomic coverage (up to ~5000 proteins). Finally, the combination of multiple batches of TMT experiments allows the profiling of hundreds of blood samples. This TMT-MS-based method provides a powerful platform for deep proteome profiling of human blood samples.PMID:36781782 | DOI:10.1007/978-1-0716-2978-9_8

Methods Mol Biol. 2023;2628:19-32. doi: 10.1007/978-1-0716-2978-9_2.ABSTRACTRegular monitoring of various biomarkers and molecular panels in plasma can significantly help to prevent disease onset and improve its management and final outcomes. Many groups can benefit from monitoring programs focusing on the prevention of cardiovascular diseases, evaluation of environmental exposure impacts, or the prevention/management of cancer. Improvement in therapeutic options in part due to targeted therapeutic agents and monoclonal antibody therapies has led to a significant sized population that can be described as "cancer survivors." These patients, although in remission from their original disease, are at significant risk for the recurring disease and must be monitored for adverse events. Monitoring is, however, not an easy task; requiring a high level of complexity in lab facilities and blood/plasma sampling, collection, and storage must occur under tightly controlled conditions. These demanding circumstances are especially difficult to attain in rural areas and in historically marginalized populations. The Telimmune Plasma Separation Card (TPS card or TPSC) has been developed to enable diagnostic plasma sampling, collection, and stabilization in locations that may be remote to laboratory or clinic. The TPSC requires a drop of blood applied to a top of a separation system consisting of a separation membrane and collection disk. In 3 min, the TPSC device separates plasma from erythrocytes and deposits a defined volume of plasma into a collection disc which is air-dried for 15 min to deliver a stabilized, volumetric plasma sample, which may be stored or shipped at ambient temperatures with minimal biological risk. Extraction of proteins and metabolites is then achieved in well-equipped laboratories using protocols discussed in this chapter.PMID:36781776 | DOI:10.1007/978-1-0716-2978-9_2

Metabolomics. 2023 Feb 13;19(2):13. doi: 10.1007/s11306-023-01977-0.ABSTRACTINTRODUCTION: This study sought to compare between metabolomic changes of human urine and plasma to investigate which one can be used as best tool to identify metabolomic profiling and novel biomarkers associated to the potential effects of ultraviolet (UV) radiation.METHOD: A pilot study of metabolomic patterns of human plasma and urine samples from four adult healthy individuals at before (S1) and after (S2) exposure (UV) and non-exposure (UC) were carried out by using liquid chromatography-mass spectrometry (LC-MS).RESULTS: The best results which were obtained by normalizing the metabolites to their mean output underwent to principal components analysis (PCA) and Orthogonal Partial least squares-discriminant analysis (OPLS-DA) to separate pre-from post-of exposure and non-exposure of UV. This separation by data modeling was clear in urine samples unlike plasma samples. In addition to overview of the scores plots, the variance predicted-Q2 (Cum), variance explained-R2X (Cum) and p-value of the cross-validated ANOVA score of PCA and OPLS-DA models indicated to this clear separation. Q2 (Cum) and R2X (Cum) values of PCA model for urine samples were 0.908 and 0.982, respectively, and OPLS-DA model values were 1.0 and 0.914, respectively. While these values in plasma samples were Q2 = 0.429 and R2X = 0.660 for PCA model and Q2 = 0.983 and R2X = 0.944 for OPLS-DA model. LC-MS metabolomic analysis showed the changes in numerous metabolic pathways including: amino acid, lipids, peptides, xenobiotics biodegradation, carbohydrates, nucleotides, Co-factors and vitamins which may contribute to the evaluation of the effects associated with UV sunlight exposure.CONCLUSIONS: The results of pilot study indicate that pre and post-exposure UV metabolomics screening of urine samples may be the best tool than plasma samples and a potential approach to predict the metabolomic changes due to UV exposure. Additional future work may shed light on the application of available metabolomic approaches to explore potential predictive markers to determine the impacts of UV sunlight.PMID:36781606 | DOI:10.1007/s11306-023-01977-0

Dokl Biol Sci. 2022 Dec;507(1):456-462. doi: 10.1134/S0012496622060205. Epub 2023 Feb 13.ABSTRACTLecanicillium gracile is a recently described micromycete species isolated from mineral-based building materials (plaster and limestone) in interiors of cultural heritage sites in Russia. In this work, the composition of L. gracile metabolites, as well as of the culture liquid, have been characterized. The results suggest that L. gracile is a promising candidate for the search for novel biologically active compounds. During the exponential growth phase, the diversity of metabolites in the mycelium was low; the metabolome profile demonstrated predominant accumulation of monosaccharides and polyols. In the stationary phase, the metabolite diversity in the L. gracile mycelium was high; apparently, at this stage biosynthesis dominated over energy-producing processes. L. gracile synthesized extracellular polymer compounds and shifted medium рН to the alkaline range. When fungi are developing on rock substrates, their extracellular polymer matrix not only serves to facilitate the formation of biofilms with other microorganisms of lithobiont communities, but also, at alkaline pH values, it promotes the formation of secondary calcite on calcium-containing substrates, such as limestone and marble. That is, L. gracile possesses certain biochemical traits that facilitate its long-term growth on rock substrates and reflect the specific character of interactions between the fungus and the substrate materials.PMID:36781540 | DOI:10.1134/S0012496622060205

Dokl Biol Sci. 2022 Dec;507(1):364-372. doi: 10.1134/S0012496622060199. Epub 2023 Feb 13.ABSTRACTThe effects of Cu, Ni, and Cd on the Pinus sylvestris metabolome was studied in experimental conditions by gas chromatography-mass spectrometry (GC-MS). Structural changes in plant metabolite network became detectable on day 6 of exposure to the metals, 3-6 days earlier than visual signs of toxicity developed. Differences at the metabolome level arose earlier in a control group of plants, and specific effects of particular metals on the plant metabolome became distinct on day 9. Both nature and concentration of a metal equally contributed to the plant metabolome clustering. Plant responses (changes in concentrations of individual metabolites) to metal exposure substantially differed depending on the metal concentration (1 or 5 mM) and nature. The effects of Cd and Cu were generally similar, while the effect of Ni was often different. Dynamic changes visualized in plant metabolite matrix reflected the changes in its correlation structure, rather than depending on the set of particular compounds.PMID:36781532 | DOI:10.1134/S0012496622060199

Proteomics. 2023 Feb 13:e2200104. doi: 10.1002/pmic.202200104. Online ahead of print.ABSTRACTPlant metabolites are mainly produced through chemical reactions catalysed by enzymes encoded in the genome. Mutations in enzyme-encoding or transcription factor-encoding genes can alter the metabolome by changing the enzyme's catalytic activity or abundance, respectively. Insertion of transposable elements into non-coding regions has also been reported to affect transcription and ultimately metabolite content. In addition to genetic mutations, transgenerational epigenetic variations have also been found to affect metabolic content by controlling transcription of metabolism related genes. However, the majority of cases reported so far, in which epigenetic mechanisms are associated to metabolism, are non-transgenerational and are triggered by developmental signals or environmental stress. Although, accumulating research has provided evidence of strong genetic control of the metabolome, epigenetic control has been largely untouched. Here, we provide a review of the genetic and epigenetic control of metabolism with a focus on epigenetics. We discuss both transgenerational and non-transgenerational epigenetic marks regulating metabolism as well as prospects of the field of metabolic control where intricate interactions between genetics and epigenetics are involved. This article is protected by copyright. All rights reserved.PMID:36781168 | DOI:10.1002/pmic.202200104

Am J Clin Nutr. 2023 Feb 11:S0002-9165(23)04156-4. doi: 10.1016/j.ajcnut.2023.02.009. Online ahead of print.ABSTRACTBACKGROUND: Epidemiologic evidence linked refined grains intake to a higher risk of gestational diabetes (GDM), but the biological underpinnings remain unclear.OBJECTIVE(S): We aimed to identify and validate refined grains-related metabolomic biomarkers for GDM risk.METHODS: In a metabolome-wide association study of 91 cases with GDM and 180 matched controls without GDM (discovery set) nested in the prospective Pregnancy Environment and Lifestyle Study (PETALS), refined grains intake during preconception and early pregnancy and serum untargeted metabolomics were assessed at gestational weeks 10-13. We identified refined grains-related metabolites using multivariable linear regression and examined their prospective associations with GDM risk using conditional logistic regression. We further examined predictivity of refined grains-related metabolites selected by LASSO regression in the discovery set and validation set (a random PETALS subsample of 38 individuals with and 336 without GDM).RESULTS: Among 821 annotated serum (87.4% fasting) metabolites, 42 were associated with refined grains intake, of which 17 (70.6% in glycerolipids, glycerophospholipids, and sphingolipids clusters) were associated with subsequent GDM risk (all false discovery rate-adjusted P-values <0.05). Adding seven of 17 metabolites to a conventional risk factor-based prediction model increased the C-statistic for GDM risk in the discovery set from 0.71 (95% CI 0.64-0.77) to 0.77 (0.71-0.83) and the validation set from 0.77 (0.69-0.86) to 0.81 (0.74-0.89), with both P-for-difference <0.05.CONCLUSIONS: Clusters of glycerolipids, glycerophospholipids, and sphingolipids may be implicated in the association between refined grains intake and GDM risk as demonstrated by the significant associations of these metabolites with both refined grains and GDM risk and the incremental predictive value of these metabolites for GDM risk beyond the conventional risk factors. These findings provide evidence on the potential biological underpinnings linking refined grains intake to the risk of GDM and help identify novel disease-related dietary biomarkers to inform diet-related preventive strategies for GDM.PMID:36781127 | DOI:10.1016/j.ajcnut.2023.02.009