{"entity": "journal", "iuid": "7e3e7f5da4654802b3fe6c0b1dac25fc", "timestamp": "2026-07-20T01:23:17.453Z", "links": {"self": {"href": "https://publications.scilifelab.se/journal/Metabolism.json"}, "display": {"href": "https://publications.scilifelab.se/journal/Metabolism"}}, "title": "Metabolism", "issn": "1532-8600", "issn-l": "0026-0495", "publications_count": 4, "publications": [{"entity": "publication", "iuid": "2d4022b436484360aa5abc58c422de2b", "links": {"self": {"href": "https://publications.scilifelab.se/publication/2d4022b436484360aa5abc58c422de2b.json"}, "display": {"href": "https://publications.scilifelab.se/publication/2d4022b436484360aa5abc58c422de2b"}}, "title": "When the proteome meets the metabolome observational and Mendelian randomization analyses.", "authors": [{"family": "Zheng", "given": "Rui", "initials": "R"}, {"family": "Delgado-Velandia", "given": "Mario", "initials": "M"}, {"family": "\u00c4rnl\u00f6v", "given": "Johan", "initials": "J"}, {"family": "Sundstr\u00f6m", "given": "Johan", "initials": "J"}, {"family": "Engstr\u00f6m", "given": "Gunnar", "initials": "G"}, {"family": "Smith", "given": "J Gustav", "initials": "JG"}, {"family": "Dekkers", "given": "Koen F", "initials": "KF"}, {"family": "Lundmark", "given": "Per", "initials": "P"}, {"family": "Fall", "given": "Tove", "initials": "T"}, {"family": "Lind", "given": "Lars", "initials": "L"}], "type": "journal article", "published": "2026-07-00", "journal": {"title": "Metabolism", "issn": "1532-8600", "volume": "180", "pages": "156602", "issn-l": "0026-0495"}, "abstract": "The basis for protein synthesis is the genetic code. Many of these proteins will affect intermediary metabolites by acting as enzymes, hormones, or by other actions. The aim of the present study was to assess the relationships of a large number of proteins with endogenous metabolites.\n\nPlasma protein levels were measured by the proximity extension assay (PEA) and metabolites by mass spectrometry. Cross-sectional relationships of 242 proteins and 790 metabolites were evaluated in the EpiHealth and POEM studies using a discovery/validation approach. Genetic instruments identified in UK Biobank for protein levels (n = 1621) and genetics for metabolite levels (n = 777) in SCAPIS and EpiHealth were employed for Mendelian randomization (MR) analysis regarding putative causal associations.\n\nIn the observational analyses, 20% of the evaluated pairwise protein-metabolite associations were found significant in both the discovery and validation samples. We could however only find support for causal effects in the MR analysis for <0.1% of the pairwise associations, representing 326 unique proteins. The R2 for the relationship between the MR and observational estimates was only 0.05. 37 protein-metabolite relationships that were significant in a congruent fashion in both the observational and MR analyses were identified. A searchable online protein vs metabolite atlas was created for the scientific community to use these results. We also give some examples where metabolites were used to enhance protein findings in cardiovascular epidemiological research.\n\nThis study provides a comprehensive assessment of a large number of protein- metabolite relationships using both observational and MR analyses, highlighting how these results could be used to enhance clinical research.", "doi": "10.1016/j.metabol.2026.156602", "pmid": "41962653", "labels": {"NGI SNP genotyping": "Service", "NGI Uppsala (SNP&SEQ Technology Platform)": "Service", "National Genomics Infrastructure": "Service"}, "xrefs": [{"db": "pii", "key": "S0026-0495(26)00112-5"}], "notes": [], "created": "2026-06-01T08:45:40.108Z", "modified": "2026-06-01T08:45:40.112Z"}, {"entity": "publication", "iuid": "9fa3893f925743b0b5f018566f37b870", "links": {"self": {"href": "https://publications.scilifelab.se/publication/9fa3893f925743b0b5f018566f37b870.json"}, "display": {"href": "https://publications.scilifelab.se/publication/9fa3893f925743b0b5f018566f37b870"}}, "title": "Plasma metabolite profiles of meat intake and their association with cardiovascular disease risk: A population-based study in Swedish cohorts.", "authors": [{"family": "Arage", "given": "Getachew", "initials": "G"}, {"family": "Dekkers", "given": "Koen F", "initials": "KF"}, {"family": "Ra\u0161o", "given": "Luka Marko", "initials": "LM"}, {"family": "Hammar", "given": "Ulf", "initials": "U"}, {"family": "Ericson", "given": "Ulrika", "initials": "U"}, {"family": "Larsson", "given": "Susanna C", "initials": "SC"}, {"family": "Engel", "given": "Hanna", "initials": "H"}, {"family": "Baldanzi", "given": "Gabriel", "initials": "G"}, {"family": "Pertiwi", "given": "Kamalita", "initials": "K"}, {"family": "Sayols-Baixeras", "given": "Sergi", "initials": "S"}, {"family": "Landberg", "given": "Rikard", "initials": "R"}, {"family": "Sundstr\u00f6m", "given": "Johan", "initials": "J"}, {"family": "Smith", "given": "J Gustav", "initials": "JG"}, {"family": "Engstr\u00f6m", "given": "Gunnar", "initials": "G"}, {"family": "\u00c4rnl\u00f6v", "given": "Johan", "initials": "J"}, {"family": "Orho-Melander", "given": "Marju", "initials": "M"}, {"family": "Lind", "given": "Lars", "initials": "L"}, {"family": "Fall", "given": "Tove", "initials": "T"}, {"family": "Ahmad", "given": "Shafqat", "initials": "S"}], "type": "journal article", "published": "2025-07-00", "journal": {"title": "Metabolism", "issn": "1532-8600", "volume": "168", "pages": "156188", "issn-l": "0026-0495"}, "abstract": "Higher meat intake has been associated with adverse health outcomes, including cardiovascular disease (CVD). This study investigated plasma metabolites associated with meat intake and their relation with cardiometabolic biomarkers, subclinical CVD markers, and incident CVD.\n\nAssociations between self-reported meat intake and 1272 plasma metabolites were investigated in the SCAPIS cohort (n = 8,819; ages 50-64). Meat-associated metabolites were further examined for relation with subclinical CVD markers in the POEM cohort (n = 502; age 50) and incident CVD in the EpiHealth cohort (n = 2,278; ages 45-75; 107 incident cases over 9.6 years follow-up). Meat intake was categorized into white, unprocessed red, and processed red meat. Linear regression analyzed associations between meat intake, metabolites and cardiometabolic biomarkers, and subclinical CVD markers, while Cox models evaluated association between meat-associated metabolites and incident CVD.\n\nAfter correction for multiple testing, 458, 368, and 403 metabolites were associated with white, unprocessed red, and processed red meat, respectively. Processed red meat-associated metabolites were associated with higher levels of fasting insulin, hemoglobin A1c, and lipoprotein(a), and were inversely associated with maximal oxygen consumption. Two metabolites, 1-palmitoyl-2-linoleoyl-GPE (16:0/18:2) (hazard ratios (HR: 1.32; 95 % CI: 1.08, 1.62)) and glutamine degradant (HR: 1.35; 95 % CI: 1.07, 1.72), that were inversely associated with intake of all meat types, were also associated with a higher risk of incident CVD.\n\nThis study provides comprehensive analysis of self-reported meat intake and plasma metabolites. The findings may enhance our understanding of the relationship between meat intake and CVD, and provide insights into underlying mechanisms.", "doi": "10.1016/j.metabol.2025.156188", "pmid": "40081615", "labels": {"Bioinformatics Support for Computational Resources": "Service"}, "xrefs": [{"db": "pii", "key": "S0026-0495(25)00057-5"}], "notes": [], "created": "2025-11-28T10:44:10.272Z", "modified": "2025-11-28T10:44:10.282Z"}, {"entity": "publication", "iuid": "5c8d3a6fb3974c9188bf3477d7615c70", "links": {"self": {"href": "https://publications.scilifelab.se/publication/5c8d3a6fb3974c9188bf3477d7615c70.json"}, "display": {"href": "https://publications.scilifelab.se/publication/5c8d3a6fb3974c9188bf3477d7615c70"}}, "title": "Genome-wide association and Mendelian randomization study of fibroblast growth factor 21 reveals causal associations with hyperlipidemia and possibly NASH.", "authors": [{"family": "Larsson", "given": "Susanna C", "initials": "SC"}, {"family": "Micha\u00eblsson", "given": "Karl", "initials": "K"}, {"family": "Mola-Caminal", "given": "Marina", "initials": "M"}, {"family": "H\u00f6ijer", "given": "Jonas", "initials": "J"}, {"family": "Mantzoros", "given": "Christos S", "initials": "CS"}], "type": "journal article", "published": "2022-12-00", "journal": {"title": "Metabolism", "issn": "1532-8600", "volume": "137", "pages": "155329", "issn-l": "0026-0495"}, "abstract": "Fibroblast growth factor 21 (FGF21) is a hepatokine that produces metabolic benefits, such as improvements of lipid profile. We performed a genome-wide association study (GWAS) to identify genetic variants associated with circulating FGF21 and investigated the causal effects of FGF21 on pertinent outcomes using Mendelian randomization (MR).\n\nWe conducted a GWAS testing \u223c7.8 million DNA sequence variants with circulating FGF21 in a discovery cohort of 6259 Swedish adults with replication in 4483 Swedish women. We then performed two-sample MR analyses of genetically predicted circulating FGF21 in relation to alcohol and nutrient intake, cardiovascular and metabolic biomarkers and diseases, and liver function biomarkers using publicly available GWAS summary statistics data.\n\nOur GWAS identified multiple single-nucleotide polymorphisms with genome-wide significant associations (P < 5 \u00d7 10-8) with circulating FGF21 on chromosomes 2 and 19 in or near the GCKR and FGF21 genes, respectively. The strongest signal at the FGF21 locus (rs2548957, \u03b2 = 0.181, P < 2.18 \u00d7 10-42) displayed in two-sample MR analyses robust associations with lower alcohol intake, lower circulating low-density lipoprotein cholesterol, apolipoprotein B, C-reactive protein, gamma-glutamyl transferase, and galectin-3 concentrations, and higher circulating insulin-like growth factor-I and alkaline phosphatase concentrations after correcting for multiple testing (P < 0.0018) whereas associations with fat mass, type 2 diabetes, and cardiovascular disease were largely null.\n\nWe identified robust associations of certain genetic variants in or near the GCKR and FGF21 genes with circulating FGF21 concentrations. Furthermore, our results support a strong causal effect of FGF21 on improved lipid profile, reduced alcohol consumption and C-reactive protein concentrations, and liver function biomarkers including fibrosis. We found largely null or weak positive associations with fat mass, diabetes, and cardiovascular disease as well as higher insulin-like growth factor-I concentrations, which could indicate a compensatory increase to regulate the above FGF21 resistant states in humans.", "doi": "10.1016/j.metabol.2022.155329", "pmid": "36208799", "labels": {"National Genomics Infrastructure": "Service", "NGI SNP genotyping": "Service", "NGI Uppsala (SNP&SEQ Technology Platform)": "Service", "Affinity Proteomics Uppsala": "Service", "Bioinformatics Support for Computational Resources": "Service"}, "xrefs": [{"db": "pii", "key": "S0026-0495(22)00207-4"}], "notes": [], "created": "2022-11-09T14:36:35.965Z", "modified": "2024-01-16T13:48:34.388Z"}, {"entity": "publication", "iuid": "ce95be317b604f59aeca4a089d225e99", "links": {"self": {"href": "https://publications.scilifelab.se/publication/ce95be317b604f59aeca4a089d225e99.json"}, "display": {"href": "https://publications.scilifelab.se/publication/ce95be317b604f59aeca4a089d225e99"}}, "title": "Alterations in the metabolism of phospholipids, bile acids and branched-chain amino acids predicts development of type 2 diabetes in black South African women: a prospective cohort study.", "authors": [{"family": "Zeng", "given": "Yingxu", "initials": "Y"}, {"family": "Mtintsilana", "given": "Asanda", "initials": "A"}, {"family": "Goedecke", "given": "Julia H", "initials": "JH"}, {"family": "Micklesfield", "given": "Lisa K", "initials": "LK"}, {"family": "Olsson", "given": "Tommy", "initials": "T"}, {"family": "Chorell", "given": "Elin", "initials": "E", "orcid": "0000-0003-2523-1940", "researcher": {"href": "https://publications.scilifelab.se/researcher/ada783ae0a824621a3b8e1024aae13a4.json"}}], "type": "journal article", "published": "2019-06-00", "journal": {"title": "Metabolism", "issn": "1532-8600", "volume": "95", "issue": null, "pages": "57-64", "issn-l": "0026-0495"}, "abstract": "South Africa (SA) has the highest global projected increase in diabetes risk. Factors typically associated with insulin resistance and type 2 diabetes risk in Caucasians are not significant correlates in black African populations. Therefore, we aimed to identify circulating metabolite patterns that predict type 2 diabetes development in this high-risk, yet understudied SA population.\n\nWe conducted a prospective cohort study in black SA women with normal glucose tolerance (NGT). Participants were followed for 13 years and developed (i) type 2 diabetes (n = 20, NGT-T2D), (ii) impaired glucose tolerance (IGT) (n = 27, NGT-IGT), or (iii) remained NGT (n = 28, NGT-NGT). Mass-spectrometry based metabolomics and multivariate analyses were used to elucidate metabolite patterns at baseline and at follow-up that were associated with type 2 diabetes development.\n\nMetabolites of phospholipid, bile acid and branched-chain amino acid (BCAA) metabolism, differed significantly between the NGT-T2D and NGT-NGT groups. At baseline: the NGT-T2D group had i) a higher lysophosphatidylcholine:lysophosphatidylethanolamine ratio containing linoleic acid (LPC(C18:2):LPE(C18:2)), ii) lower proliferation-related bile acids (ursodeoxycholic- and chenodeoxycholic acid), iii) higher levels of leucine and its catabolic intermediates (ketoleucine and C5-carnitine), compared to the NGT-NGT group. At follow-up: the NGT-T2D group had i) lower LPC(C18:2) levels, ii) higher apoptosis-related bile acids (deoxycholic- and glycodeoxycholic acid), and iii) higher levels of all BCAAs and their catabolic intermediates.\n\nChanges in lysophospholipid metabolism and the bile acid pool occur during the development of type 2 diabetes in black South African women. Further, impaired leucine catabolism precedes valine and isoleucine catabolism in the development of type 2 diabetes. These metabolite patterns can be useful to identify and monitor type 2 diabetes risk >10 years prior to disease onset and provide insight into the pathophysiology of type 2 diabetes in this high risk, but under-studied population.", "doi": "10.1016/j.metabol.2019.04.001", "pmid": "30954560", "labels": {"Swedish Metabolomics Centre": "Service"}, "xrefs": [{"db": "pii", "key": "S0026-0495(19)30067-8"}], "notes": [], "created": "2020-01-07T15:49:27.105Z", "modified": "2025-10-17T13:03:17.571Z"}], "created": "2020-01-07T15:49:27.119Z", "modified": "2020-11-27T13:14:04.854Z"}