{"entity": "researcher", "timestamp": "2026-08-08T15:42:54.062Z", "family": "Dencker", "given": "Magnus", "initials": "M", "orcid": "0000-0001-9991-3712", "affiliations": [], "links": {"self": {"href": "https://publications.scilifelab.se/researcher/606b9b3272824d92a66dfd715c5e4842.json"}, "display": {"href": "https://publications.scilifelab.se/researcher/606b9b3272824d92a66dfd715c5e4842"}}, "publications": [{"entity": "publication", "iuid": "85eb9f3746b6441aafc24c49f912d696", "links": {"self": {"href": "https://publications.scilifelab.se/publication/85eb9f3746b6441aafc24c49f912d696.json"}, "display": {"href": "https://publications.scilifelab.se/publication/85eb9f3746b6441aafc24c49f912d696"}}, "title": "Galectin-3 levels relate in children to total body fat, abdominal fat, body fat distribution, and cardiac size.", "authors": [{"family": "Dencker", "given": "Magnus", "initials": "M", "orcid": "0000-0001-9991-3712", "researcher": {"href": "https://publications.scilifelab.se/researcher/606b9b3272824d92a66dfd715c5e4842.json"}}, {"family": "Arvidsson", "given": "Daniel", "initials": "D"}, {"family": "Karlsson", "given": "Magnus K", "initials": "MK"}, {"family": "Wollmer", "given": "Per", "initials": "P"}, {"family": "Andersen", "given": "Lars B", "initials": "LB"}, {"family": "Thorsson", "given": "Ola", "initials": "O"}], "type": "journal article", "published": "2018-03-00", "journal": {"title": "Eur J Pediatr", "issn": "1432-1076", "issn-l": "0340-6199", "volume": "177", "issue": "3", "pages": "461-467"}, "abstract": "Galectin-3 has recently been proposed as a novel biomarker for cardiovascular disease in adults. The purpose of this investigation was to assess relationships between galectin-3 levels and total body fat, abdominal fat, body fat distribution, aerobic fitness, blood pressure, left ventricular mass, left atrial size, and increase in body fat over a 2-year period in a population-based sample of children. Our study included 170 children aged 8-11 years. Total fat mass and abdominal fat were measured by dual-energy x-ray absorptiometry (DXA). Body fat distribution was expressed as abdominal fat/total fat mass. Maximal oxygen uptake was assessed by indirect calorimetry during a maximal exercise test and scaled to body mass. Systolic and diastolic blood pressure and pulse pressure were measured. Left atrial size, left ventricular mass, and relative wall thickness were measured by echocardiography. Frozen serum samples were analyzed for galectin-3 by the Proximity Extension Assay technique. A follow-up DXA scan was performed in 152 children 2 years after the baseline exam. Partial correlations, with adjustment for sex and age, between galectin-3 versus body fat measurements indicated weak to moderate relationships. Moreover, left atrial size, left ventricular mass, and relative wall thickness and pulse pressure were also correlated with galectin-3. Neither systolic blood pressure nor maximal oxygen uptake was correlated with galectin-3. There was also a correlation between galectin-3 and increase in total body fat over 2 years, while no such correlations were found for the other fat measurements.\n\nMore body fat and abdominal fat, more abdominal body fat distribution, more left ventricular mass, and increased left atrial size were all associated with higher levels of galectin-3. Increase in total body fat over 2 years was also associated with higher levels of galectin-3. What is Known: \u2022 Galectin-3 has been linked to obesity and been proposed to be a novel biomarker for cardiovascular disease in adults. \u2022 Information on this subject in children is very scarce. What is New: \u2022 The present study demonstrates a relationship between galectin-3 levels and total body fat, abdominal fat, body fat distribution, cardiac size and geometry, and increase in total body fat over 2 years in young children.", "doi": "10.1007/s00431-017-3079-5", "pmid": "29327139", "labels": {"Clinical Biomarkers": "Service", "PLA and Single Cell Proteomics": "Service", "Affinity Proteomics Uppsala": "Service"}, "xrefs": [{"db": "pii", "key": "10.1007/s00431-017-3079-5"}, {"db": "pmc", "key": "PMC5816767"}], "notes": [], "created": "2020-01-23T16:04:02.483Z", "modified": "2023-04-14T13:56:06.729Z"}, {"entity": "publication", "iuid": "586e74b3539548239e73d43d6f3d0175", "links": {"self": {"href": "https://publications.scilifelab.se/publication/586e74b3539548239e73d43d6f3d0175.json"}, "display": {"href": "https://publications.scilifelab.se/publication/586e74b3539548239e73d43d6f3d0175"}}, "title": "Effect of food intake on 92 neurological biomarkers in plasma.", "authors": [{"family": "Dencker", "given": "Magnus", "initials": "M", "orcid": "0000-0001-9991-3712", "researcher": {"href": "https://publications.scilifelab.se/researcher/606b9b3272824d92a66dfd715c5e4842.json"}}, {"family": "Bj\u00f6rgell", "given": "Ola", "initials": "O"}, {"family": "Hlebowicz", "given": "Joanna", "initials": "J"}], "type": "journal article", "published": "2017-09-00", "journal": {"title": "Brain Behav", "issn": "2162-3279", "issn-l": "2162-3279", "volume": "7", "issue": "9", "pages": "e00747"}, "abstract": "This study evaluates the effect of food intake on 92 neurological biomarkers in plasma. Moreover, it investigated if any of the biomarkers were correlated with body mass index.\n\nTwenty-two healthy subjects (11 male and 11 female aged 25.9 \u00b1 4.2 years) were investigated. A total of 92 biomarkers were measured before a standardized meal as well as 30 and 120 min afterward with the Proseek Multiplex Neurology I kit.\n\nThe levels for 13 biomarkers decreased significantly (p < .001) 30 min after food intake. The levels for four biomarkers remained significantly decreased (p < .001) 120 min after food intake. One biomarker increased significantly (p < .001) 30 min after food intake. The changes were between 1% and 12%, with an average difference of about 5%. Only one biomarker showed a difference over 10% due to food intake. The biggest difference was observed for Plexin-B3 120 min after food intake (12%). Of all the 92 neurological biomarkers, only one was correlated with BMI, Kynureninase r = .46, p < .05.\n\nThis study shows that food intake has a very modest effect on 92 different neurological biomarkers. Timing of blood sampling in relation to food intake, therefore, appears not to be a major concern. Only Kynureninase was correlated with BMI. Further studies are warranted in older healthy subjects and in patients with various neurological diseases to determine whether the findings are reproducible in such populations.", "doi": "10.1002/brb3.747", "pmid": "28948068", "labels": {"Clinical Biomarkers": "Service", "PLA and Single Cell Proteomics": "Service", "Affinity Proteomics Uppsala": "Service"}, "xrefs": [{"db": "pii", "key": "BRB3747"}, {"db": "pmc", "key": "PMC5607537"}], "notes": [], "created": "2020-01-23T15:08:29.124Z", "modified": "2023-04-14T13:56:10.734Z"}, {"entity": "publication", "iuid": "902562561e624de6ba03ba60d53d59f5", "links": {"self": {"href": "https://publications.scilifelab.se/publication/902562561e624de6ba03ba60d53d59f5.json"}, "display": {"href": "https://publications.scilifelab.se/publication/902562561e624de6ba03ba60d53d59f5"}}, "title": "Effect of food intake on 92 biomarkers for cardiovascular disease.", "authors": [{"family": "Dencker", "given": "Magnus", "initials": "M", "orcid": "0000-0001-9991-3712", "researcher": {"href": "https://publications.scilifelab.se/researcher/606b9b3272824d92a66dfd715c5e4842.json"}}, {"family": "G\u00e5rdinger", "given": "Ylva", "initials": "Y"}, {"family": "Bj\u00f6rgell", "given": "Ola", "initials": "O"}, {"family": "Hlebowicz", "given": "Joanna", "initials": "J"}], "type": "journal article", "published": "2017-06-06", "journal": {"title": "PLoS ONE", "issn": "1932-6203", "issn-l": "1932-6203", "volume": "12", "issue": "6", "pages": "e0178656"}, "abstract": "The present study evaluates the effect of food intake on 92 biomarkers for cardiovascular disease (CVD).\n\nTwenty two healthy subjects (11 male and 11 female aged 25.9\u00b14.2 years) were investigated. A total of 92 biomarkers were measured before a standardized meal as well as 30 and 120 minutes afterwards with the Proseek Multiplex CVD III kit.\n\nThe levels for eight biomarkers decreased significantly (P<0.05) 30 minutes after food intake. The levels for seven biomarkers remained significantly decreased 120 minutes after food intake. Nine biomarker decreased significantly at 120 minutes after food intake. The changes were between 4-30%, most commonly around 5%. Only six biomarkers showed a difference of 10% or more due to food intake. The biggest differences were observed for Insulin-like growth factor-binding protein 1 (30%); Azurocidin, Cystatin-B, and Myeloperoxidase (13%); Monocyte chemotactic protein 1 (11%); and Myeloblastin (10%), all 120 minutes after food intake.\n\nThis study shows that food intake affects several different CVD biomarkers, but the effect is predominantly modest. Timing of blood sampling in relation to food intake, therefore, appears not to be a major concern. Further studies are warranted in older healthy subjects and in patients with various cardiac diseases to determine whether the findings are reproducible.", "doi": "10.1371/journal.pone.0178656", "pmid": "28586402", "labels": {"Clinical Biomarkers": "Service", "PLA and Single Cell Proteomics": "Service", "Affinity Proteomics Uppsala": "Service"}, "xrefs": [{"db": "pii", "key": "PONE-D-17-02534"}, {"db": "pmc", "key": "PMC5460853"}], "notes": [], "created": "2020-01-23T15:08:30.269Z", "modified": "2023-04-14T13:56:13.096Z"}]}