{"entity": "researcher", "timestamp": "2026-10-05T21:25:53.743Z", "family": "Johansson", "given": "Ingegerd", "initials": "I", "orcid": "0000-0002-9227-8434", "affiliations": [], "links": {"self": {"href": "https://publications.scilifelab.se/researcher/ee3e20587b664a42a880870f1648160a.json"}, "display": {"href": "https://publications.scilifelab.se/researcher/ee3e20587b664a42a880870f1648160a"}}, "publications": [{"entity": "publication", "iuid": "02ca4d46df3c4e73b9e068dd236e5d2a", "links": {"self": {"href": "https://publications.scilifelab.se/publication/02ca4d46df3c4e73b9e068dd236e5d2a.json"}, "display": {"href": "https://publications.scilifelab.se/publication/02ca4d46df3c4e73b9e068dd236e5d2a"}}, "title": "Dietary patterns, untargeted metabolite profiles and their association with colorectal cancer risk.", "authors": [{"family": "Bod\u00e9n", "given": "Stina", "initials": "S", "orcid": "0000-0002-8958-975X", "researcher": {"href": "https://publications.scilifelab.se/researcher/8dcfadb86b8040499a7af3c4a744d3b2.json"}}, {"family": "Zheng", "given": "Rui", "initials": "R"}, {"family": "Ribbenstedt", "given": "Anton", "initials": "A"}, {"family": "Landberg", "given": "Rikard", "initials": "R"}, {"family": "Harlid", "given": "Sophia", "initials": "S", "orcid": "0000-0001-8540-6891", "researcher": {"href": "https://publications.scilifelab.se/researcher/76a824f2687b460890ae6d9ef40d97c9.json"}}, {"family": "Vidman", "given": "Linda", "initials": "L"}, {"family": "Gunter", "given": "Marc J", "initials": "MJ"}, {"family": "Winkvist", "given": "Anna", "initials": "A", "orcid": "0000-0001-9122-7240", "researcher": {"href": "https://publications.scilifelab.se/researcher/e34ca937891145e190390ae9418d2243.json"}}, {"family": "Johansson", "given": "Ingegerd", "initials": "I", "orcid": "0000-0002-9227-8434", "researcher": {"href": "https://publications.scilifelab.se/researcher/ee3e20587b664a42a880870f1648160a.json"}}, {"family": "Van Guelpen", "given": "Bethany", "initials": "B", "orcid": "0000-0002-9692-101X", "researcher": {"href": "https://publications.scilifelab.se/researcher/1ea901d796bc4f3fbc53f930c5021118.json"}}, {"family": "Brunius", "given": "Carl", "initials": "C"}], "type": "journal article", "published": "2024-01-26", "journal": {"title": "Sci Rep", "issn": "2045-2322", "volume": "14", "issue": "1", "pages": "2244", "issn-l": "2045-2322"}, "abstract": "We investigated data-driven and hypothesis-driven dietary patterns and their association to plasma metabolite profiles and subsequent colorectal cancer (CRC) risk in 680 CRC cases and individually matched controls. Dietary patterns were identified from combined exploratory/confirmatory factor analysis. We assessed association to LC-MS metabolic profiles by random forest regression and to CRC risk by multivariable conditional logistic regression. Principal component analysis was used on metabolite features selected to reflect dietary exposures. Component scores were associated to CRC risk and dietary exposures using partial Spearman correlation. We identified 12 data-driven dietary patterns, of which a breakfast food pattern showed an inverse association with CRC risk (OR per standard deviation increase 0.89, 95% CI 0.80-1.00, p = 0.04). This pattern was also inversely associated with risk of distal colon cancer (0.75, 0.61-0.96, p = 0.01) and was more pronounced in women (0.69, 0.49-0.96, p = 0.03). Associations between meat, fast-food, fruit soup/rice patterns and CRC risk were modified by tumor location in women. Alcohol as well as fruit and vegetables associated with metabolite profiles (Q2 0.22 and 0.26, respectively). One metabolite reflecting alcohol intake associated with increased CRC risk, whereas three metabolites reflecting fiber, wholegrain, and fruit and vegetables associated with decreased CRC risk.", "doi": "10.1038/s41598-023-50567-6", "pmid": "38278865", "labels": {"Bioinformatics Support for Computational Resources": "Service", "Chalmers Mass Spectrometry Infrastructure": "Collaborative"}, "xrefs": [{"db": "pmc", "key": "PMC10817924"}, {"db": "pii", "key": "10.1038/s41598-023-50567-6"}], "notes": [], "created": "2024-11-25T10:20:32.223Z", "modified": "2024-11-27T15:34:24.513Z"}, {"entity": "publication", "iuid": "fc7a25ffb3114b019ba788d35be80ecc", "links": {"self": {"href": "https://publications.scilifelab.se/publication/fc7a25ffb3114b019ba788d35be80ecc.json"}, "display": {"href": "https://publications.scilifelab.se/publication/fc7a25ffb3114b019ba788d35be80ecc"}}, "title": "Oral Microbiota Profile Associates with Sugar Intake and Taste Preference Genes.", "authors": [{"family": "Esberg", "given": "Anders", "initials": "A", "orcid": "0000-0002-4430-8125", "researcher": {"href": "https://publications.scilifelab.se/researcher/a6610f154ad749a49a8f5d89382c6b1b.json"}}, {"family": "Haworth", "given": "Simon", "initials": "S", "orcid": "0000-0001-7793-7326", "researcher": {"href": "https://publications.scilifelab.se/researcher/43fa9fb331c849b58d4ac4b14f04fbda.json"}}, {"family": "Hassl\u00f6f", "given": "Pamela", "initials": "P"}, {"family": "Lif Holgerson", "given": "Pernilla", "initials": "P", "orcid": "0000-0002-2779-5865", "researcher": {"href": "https://publications.scilifelab.se/researcher/90cb42e842044260888df6e0a10afdd1.json"}}, {"family": "Johansson", "given": "Ingegerd", "initials": "I", "orcid": "0000-0002-9227-8434", "researcher": {"href": "https://publications.scilifelab.se/researcher/ee3e20587b664a42a880870f1648160a.json"}}], "type": "clinical trial", "published": "2020-03-03", "journal": {"title": "Nutrients", "issn": "2072-6643", "volume": "12", "issue": "3", "pages": "681", "issn-l": "2072-6643"}, "abstract": "Oral microbiota ecology is influenced by environmental and host conditions, but few studies have evaluated associations between untargeted measures of the entire oral microbiome and potentially relevant environmental and host factors. This study aimed to identify salivary microbiota cluster groups using hierarchical cluster analyses (Wards method) based on 16S rRNA gene amplicon sequencing, and identify lifestyle and host factors which were associated with these groups. Group members (n = 175) were distinctly separated by microbiota profiles and differed in reported sucrose intake and allelic variation in the taste-preference-associated genes TAS1R1 (rs731024) and GNAT3 (rs2074673). Groups with higher sucrose intake were either characterized by a wide panel of species or phylotypes with fewer aciduric species, or by a narrower profile that included documented aciduric- and caries-associated species. The inferred functional profiles of the latter type were dominated by metabolic pathways associated with the carbohydrate metabolism with enrichment of glycosidase functions. In conclusion, this study supported in vivo associations between sugar intake and oral microbiota ecology, but it also found evidence for a variable microbiota response to sugar, highlighting the importance of modifying host factors and microbes beyond the commonly targeted acidogenic and acid-tolerant species. The results should be confirmed under controlled settings with comprehensive phenotypic and genotypic data.", "doi": "10.3390/nu12030681", "pmid": "32138214", "labels": {"National Genomics Infrastructure": "Service", "NGI Uppsala (SNP&SEQ Technology Platform)": "Service"}, "xrefs": [{"db": "pii", "key": "nu12030681"}, {"db": "pmc", "key": "PMC7146170"}], "notes": [], "created": "2020-03-16T09:47:51.000Z", "modified": "2021-11-10T12:53:20.230Z"}]}