{"entity": "researcher", "timestamp": "2026-08-09T07:19:03.849Z", "family": "Dale", "given": "Matilda", "initials": "M", "orcid": "0000-0002-5788-7744", "affiliations": ["Affinity Proteomics, Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Solna, Sweden."], "links": {"self": {"href": "https://publications.scilifelab.se/researcher/59306e7e902048829efb30599ee3d2b1.json"}, "display": {"href": "https://publications.scilifelab.se/researcher/59306e7e902048829efb30599ee3d2b1"}}, "publications": [{"entity": "publication", "iuid": "638e3981672c479bb5ffcd2ac87dc4d5", "links": {"self": {"href": "https://publications.scilifelab.se/publication/638e3981672c479bb5ffcd2ac87dc4d5.json"}, "display": {"href": "https://publications.scilifelab.se/publication/638e3981672c479bb5ffcd2ac87dc4d5"}}, "title": "Blood biomarkers of Alzheimer's disease and progression across different stages of cognitive decline in the community.", "authors": [{"family": "Valletta", "given": "Martina", "initials": "M", "orcid": "0000-0003-0139-8287", "researcher": {"href": "https://publications.scilifelab.se/researcher/9fa01849f48049c78eef04747ab1797a.json"}}, {"family": "Vetrano", "given": "Davide Liborio", "initials": "DL", "orcid": "0000-0002-3099-4830", "researcher": {"href": "https://publications.scilifelab.se/researcher/06867644d5f14eef958737353517f53d.json"}}, {"family": "Gregorio", "given": "Caterina", "initials": "C", "orcid": "0000-0002-8163-1634", "researcher": {"href": "https://publications.scilifelab.se/researcher/21265a4e63634efba72a5ee676156baa.json"}}, {"family": "Rizzuto", "given": "Debora", "initials": "D"}, {"family": "Winblad", "given": "Bengt", "initials": "B", "orcid": "0000-0002-0011-1179", "researcher": {"href": "https://publications.scilifelab.se/researcher/73185a13ca474153b66415e6a2dfff0f.json"}}, {"family": "Canevelli", "given": "Marco", "initials": "M"}, {"family": "Andersson", "given": "Sarah", "initials": "S"}, {"family": "Dale", "given": "Matilda", "initials": "M", "orcid": "0000-0002-5788-7744", "researcher": {"href": "https://publications.scilifelab.se/researcher/59306e7e902048829efb30599ee3d2b1.json"}}, {"family": "Fredolini", "given": "Claudia", "initials": "C", "orcid": "0000-0002-7674-2014", "researcher": {"href": "https://publications.scilifelab.se/researcher/40ac3a5823cb4f998cc8bdb96dcbf195.json"}}, {"family": "Laukka", "given": "Erika J", "initials": "EJ"}, {"family": "Fratiglioni", "given": "Laura", "initials": "L"}, {"family": "Grande", "given": "Giulia", "initials": "G", "orcid": "0000-0001-6312-3815", "researcher": {"href": "https://publications.scilifelab.se/researcher/a6fc0b0bad8243059965a2b828321c14.json"}}], "type": "journal article", "published": "2025-11-23", "journal": {"title": "Nat Commun", "issn": "2041-1723", "issn-l": "2041-1723"}, "abstract": "Blood biomarkers of Alzheimer's disease (AD) are promising for dementia prediction, but their association with progression across intermediate stages of cognitive decline in the general population remains unclear. We followed 2148 dementia-free individuals from a Swedish population-based cohort for up to 16 years. Associations between baseline AD blood biomarkers and transitions between normal cognition, mild cognitive impairment (MCI), and dementia were examined. Lower amyloid-\u03b242/40 ratio and higher phosphorylated-tau181 (p-tau181), p-tau217, total-tau, neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP) were associated with faster progression from MCI to all-cause and AD dementia, with the strongest associations for NfL and p-tau217. Elevated NfL and GFAP were linked to reduced MCI reversion to normal cognition, whereas no biomarker was associated with MCI development from normal cognition. These findings show robust group-level associations and indicate that AD blood biomarkers may help stratify dementia risk at the MCI stage in the community.", "doi": "10.1038/s41467-025-66728-2", "pmid": "41276530", "labels": {"Affinity Proteomics Stockholm": "Collaborative"}, "xrefs": [{"db": "pii", "key": "10.1038/s41467-025-66728-2"}], "notes": [], "created": "2025-11-24T16:43:44.175Z", "modified": "2025-11-24T16:43:44.720Z"}, {"entity": "publication", "iuid": "2ae5cc4ff3d946528ecb78f961464277", "links": {"self": {"href": "https://publications.scilifelab.se/publication/2ae5cc4ff3d946528ecb78f961464277.json"}, "display": {"href": "https://publications.scilifelab.se/publication/2ae5cc4ff3d946528ecb78f961464277"}}, "title": "Blood-based biomarkers of Alzheimer's disease and incident dementia in the community.", "authors": [{"family": "Grande", "given": "Giulia", "initials": "G", "orcid": "0000-0001-6312-3815", "researcher": {"href": "https://publications.scilifelab.se/researcher/a6fc0b0bad8243059965a2b828321c14.json"}}, {"family": "Valletta", "given": "Martina", "initials": "M", "orcid": "0000-0003-0139-8287", "researcher": {"href": "https://publications.scilifelab.se/researcher/9fa01849f48049c78eef04747ab1797a.json"}}, {"family": "Rizzuto", "given": "Debora", "initials": "D"}, {"family": "Xia", "given": "Xin", "initials": "X"}, {"family": "Qiu", "given": "Chengxuan", "initials": "C", "orcid": "0000-0003-1922-4912", "researcher": {"href": "https://publications.scilifelab.se/researcher/15238dd19bda48fcbf04b299a8368929.json"}}, {"family": "Orsini", "given": "Nicola", "initials": "N"}, {"family": "Dale", "given": "Matilda", "initials": "M", "orcid": "0000-0002-5788-7744", "researcher": {"href": "https://publications.scilifelab.se/researcher/59306e7e902048829efb30599ee3d2b1.json"}}, {"family": "Andersson", "given": "Sarah", "initials": "S"}, {"family": "Fredolini", "given": "Claudia", "initials": "C", "orcid": "0000-0002-7674-2014", "researcher": {"href": "https://publications.scilifelab.se/researcher/40ac3a5823cb4f998cc8bdb96dcbf195.json"}}, {"family": "Winblad", "given": "Bengt", "initials": "B", "orcid": "0000-0002-0011-1179", "researcher": {"href": "https://publications.scilifelab.se/researcher/73185a13ca474153b66415e6a2dfff0f.json"}}, {"family": "Laukka", "given": "Erika J", "initials": "EJ"}, {"family": "Fratiglioni", "given": "Laura", "initials": "L"}, {"family": "Vetrano", "given": "Davide L", "initials": "DL", "orcid": "0000-0002-3099-4830", "researcher": {"href": "https://publications.scilifelab.se/researcher/06867644d5f14eef958737353517f53d.json"}}], "type": "journal article", "published": "2025-03-26", "journal": {"title": "Nat. Med.", "issn": "1546-170X", "issn-l": "1078-8956"}, "abstract": "Evidence regarding the clinical validity of blood biomarkers of Alzheimer's disease (AD) in the general population is limited. We estimated the hazard and predictive performance of six AD blood biomarkers for incident all-cause and AD dementia-the ratio of amyloid-\u03b2 42 to amyloid-\u03b2 40 and levels of tau phosphorylated at T217 (p-tau217), tau phosphorylated at T181 (p-tau181), total tau, neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP)-in a cohort of 2,148 dementia-free older adults from Sweden, who were followed for up to 16 years. In multi-adjusted Cox regression models, elevated baseline levels of p-tau181, p-tau217, NfL, and GFAP were associated with a significantly increased hazard for all-cause and AD dementia, displaying a non-linear dose-response relationship. Elevated concentrations of p-tau181, p-tau217, NfL, and GFAP demonstrated strong predictive performance (area under the curve ranging from 70.9% to 82.6%) for 10-year all-cause and AD dementia, with negative predictive values exceeding 90% but low positive predictive values (PPVs). Combining p-tau217 with NfL or GFAP further improved prediction, with PPVs reaching 43%. Our findings suggest that these biomarkers have the potential to rule out impending dementia in community settings, but they might need to be combined with other biological or clinical markers to be used as screening tools.", "doi": "10.1038/s41591-025-03605-x", "pmid": "40140622", "labels": {"Affinity Proteomics Stockholm": "Collaborative"}, "xrefs": [{"db": "pii", "key": "10.1038/s41591-025-03605-x"}], "notes": [], "created": "2025-04-02T14:34:39.959Z", "modified": "2025-04-02T14:34:40.970Z"}, {"entity": "publication", "iuid": "111154cd228d47fabf63f871f677a0d7", "links": {"self": {"href": "https://publications.scilifelab.se/publication/111154cd228d47fabf63f871f677a0d7.json"}, "display": {"href": "https://publications.scilifelab.se/publication/111154cd228d47fabf63f871f677a0d7"}}, "title": "Proteome profiling of home-sampled dried blood spots reveals proteins of SARS-CoV-2 infections.", "authors": [{"family": "Fredolini", "given": "Claudia", "initials": "C", "orcid": "0000-0002-7674-2014", "researcher": {"href": "https://publications.scilifelab.se/researcher/40ac3a5823cb4f998cc8bdb96dcbf195.json"}}, {"family": "Dodig-Crnkovi\u0107", "given": "Tea", "initials": "T"}, {"family": "Bendes", "given": "Annika", "initials": "A", "orcid": "0000-0001-9329-2353", "researcher": {"href": "https://publications.scilifelab.se/researcher/50dffce4f4444dd8b5ff8f9294146a0b.json"}}, {"family": "Dahl", "given": "Leo", "initials": "L", "orcid": "0000-0003-1492-3052", "researcher": {"href": "https://publications.scilifelab.se/researcher/d4df506f315c4289935b935a503efd56.json"}}, {"family": "Dale", "given": "Matilda", "initials": "M", "orcid": "0000-0002-5788-7744", "researcher": {"href": "https://publications.scilifelab.se/researcher/59306e7e902048829efb30599ee3d2b1.json"}}, {"family": "Albrecht", "given": "Vincent", "initials": "V", "orcid": "0009-0003-1985-7733", "researcher": {"href": "https://publications.scilifelab.se/researcher/4d422e623e9e449f98853e6830cdd401.json"}}, {"family": "Mattsson", "given": "Cecilia", "initials": "C"}, {"family": "Thomas", "given": "Cecilia E", "initials": "CE", "orcid": "0000-0001-6201-6380", "researcher": {"href": "https://publications.scilifelab.se/researcher/3a1156f987764218af202efbd76c31fd.json"}}, {"family": "Torinsson Naluai", "given": "\u00c5sa", "initials": "\u00c5", "orcid": "0000-0002-0504-6492", "researcher": {"href": "https://publications.scilifelab.se/researcher/bcf3474dc7054c598cbe3a195deb8a1b.json"}}, {"family": "Gisslen", "given": "Magnus", "initials": "M"}, {"family": "Beck", "given": "Olof", "initials": "O"}, {"family": "Roxhed", "given": "Niclas", "initials": "N", "orcid": "0000-0002-7147-6730", "researcher": {"href": "https://publications.scilifelab.se/researcher/3739210caaf14a28898849f20bf6ece5.json"}}, {"family": "Schwenk", "given": "Jochen M", "initials": "JM", "orcid": "0000-0001-8141-8449", "researcher": {"href": "https://publications.scilifelab.se/researcher/aba5822711b246b397fffacb7ae403b3.json"}}], "type": "journal article", "published": "2024-04-02", "journal": {"title": "Commun Med (Lond)", "issn": "2730-664X", "issn-l": null, "volume": "4", "issue": "1", "pages": "55"}, "abstract": "Self-sampling of dried blood spots (DBS) offers new routes to gather valuable health-related information from the general population. Yet, the utility of using deep proteome profiling from home-sampled DBS to obtain clinically relevant insights about SARS-CoV-2 infections remains largely unexplored.\r\n\r\nOur study involved 228 individuals from the general Swedish population who used a volumetric DBS sampling device and completed questionnaires at home during spring 2020 and summer 2021. Using multi-analyte COVID-19 serology, we stratified the donors by their response phenotypes, divided them into three study sets, and analyzed 276 proteins by proximity extension assays (PEA). After normalizing the data to account for variances in layman-collected samples, we investigated the association of DBS proteomes with serology and self-reported information.\r\n\r\nOur three studies display highly consistent variance of protein levels and share associations of proteins with sex (e.g., MMP3) and age (e.g., GDF-15). Studying seropositive (IgG+) and seronegative (IgG-) donors from the first pandemic wave reveals a network of proteins reflecting immunity, inflammation, coagulation, and stress response. A comparison of the early-infection phase (IgM+IgG-) with the post-infection phase (IgM-IgG+) indicates several proteins from the respiratory system. In DBS from the later pandemic wave, we find that levels of a virus receptor on B-cells differ between seropositive (IgG+) and seronegative (IgG-) donors.\r\n\r\nProteome analysis of volumetric self-sampled DBS facilitates precise analysis of clinically relevant proteins, including those secreted into the circulation or found on blood cells, augmenting previous COVID-19 reports with clinical blood collections. Our population surveys support the usefulness of DBS, underscoring the role of timing the sample collection to complement clinical and precision health monitoring initiatives.", "doi": "10.1038/s43856-024-00480-4", "pmid": "38565620", "labels": {"Affinity Proteomics Stockholm": "Technology development", "Autoimmunity and Serology Profiling": "Service"}, "xrefs": [{"db": "pmc", "key": "PMC10987641"}, {"db": "pii", "key": "10.1038/s43856-024-00480-4"}], "notes": [], "created": "2024-04-18T09:27:59.211Z", "modified": "2024-08-28T11:04:43.993Z"}, {"entity": "publication", "iuid": "f4fa784e7018440f8e95a5c4fc122634", "links": {"self": {"href": "https://publications.scilifelab.se/publication/f4fa784e7018440f8e95a5c4fc122634.json"}, "display": {"href": "https://publications.scilifelab.se/publication/f4fa784e7018440f8e95a5c4fc122634"}}, "title": "The impact of circulating protein levels identified by affinity proteomics on short-term, overall breast cancer risk.", "authors": [{"family": "Grassmann", "given": "Felix", "initials": "F", "orcid": "0000-0003-1390-7528", "researcher": {"href": "https://publications.scilifelab.se/researcher/76a190980d904236914679e88737706b.json"}}, {"family": "M\u00e4larstig", "given": "Anders", "initials": "A"}, {"family": "Dahl", "given": "Leo", "initials": "L", "orcid": "0000-0003-1492-3052", "researcher": {"href": "https://publications.scilifelab.se/researcher/d4df506f315c4289935b935a503efd56.json"}}, {"family": "Bendes", "given": "Annika", "initials": "A"}, {"family": "Dale", "given": "Matilda", "initials": "M", "orcid": "0000-0002-5788-7744", "researcher": {"href": "https://publications.scilifelab.se/researcher/59306e7e902048829efb30599ee3d2b1.json"}}, {"family": "Thomas", "given": "Cecilia Engel", "initials": "CE", "orcid": "0000-0001-6201-6380", "researcher": {"href": "https://publications.scilifelab.se/researcher/3a1156f987764218af202efbd76c31fd.json"}}, {"family": "Gabrielsson", "given": "Marike", "initials": "M", "orcid": "0000-0002-3171-1556", "researcher": {"href": "https://publications.scilifelab.se/researcher/dbc71027045048a09059d843f56a628f.json"}}, {"family": "Hedman", "given": "\u00c5sa K", "initials": "\u00c5K"}, {"family": "Eriksson", "given": "Mikael", "initials": "M"}, {"family": "Margolin", "given": "Sara", "initials": "S"}, {"family": "Huang", "given": "Tzu-Hsuan", "initials": "TH"}, {"family": "Ulfstedt", "given": "Mikael", "initials": "M"}, {"family": "Forsberg", "given": "Simon", "initials": "S"}, {"family": "Eriksson", "given": "Per", "initials": "P", "orcid": "0000-0001-7633-403X", "researcher": {"href": "https://publications.scilifelab.se/researcher/97fea086745a40e9a3a20baba08bb7b8.json"}}, {"family": "Johansson", "given": "Mattias", "initials": "M"}, {"family": "Hall", "given": "Per", "initials": "P"}, {"family": "Schwenk", "given": "Jochen M", "initials": "JM", "orcid": "0000-0001-8141-8449", "researcher": {"href": "https://publications.scilifelab.se/researcher/aba5822711b246b397fffacb7ae403b3.json"}}, {"family": "Czene", "given": "Kamila", "initials": "K"}], "type": "journal article", "published": "2024-03-00", "journal": {"title": "Br. J. Cancer", "issn": "1532-1827", "volume": "130", "issue": "4", "pages": "620-627", "issn-l": "0007-0920"}, "abstract": "Current breast cancer risk prediction scores and algorithms can potentially be further improved by including molecular markers. To this end, we studied the association of circulating plasma proteins using Proximity Extension Assay (PEA) with incident breast cancer risk.\n\nIn this study, we included 1577 women participating in the prospective KARMA mammographic screening cohort.\n\nIn a targeted panel of 164 proteins, we found 8 candidates nominally significantly associated with short-term breast cancer risk (P < 0.05). Similarly, in an exploratory panel consisting of 2204 proteins, 115 were found nominally significantly associated (P < 0.05). However, none of the identified protein levels remained significant after adjustment for multiple testing. This lack of statistically significant findings was not due to limited power, but attributable to the small effect sizes observed even for nominally significant proteins. Similarly, adding plasma protein levels to established risk factors did not improve breast cancer risk prediction accuracy.\n\nOur results indicate that the levels of the studied plasma proteins captured by the PEA method are unlikely to offer additional benefits for risk prediction of short-term overall breast cancer risk but could provide interesting insights into the biological basis of breast cancer in the future.", "doi": "10.1038/s41416-023-02541-2", "pmid": "38135714", "labels": {"Affinity Proteomics Stockholm": "Collaborative", "Bioinformatics Support for Computational Resources": "Service"}, "xrefs": [{"db": "pmc", "key": "PMC10876928"}, {"db": "pii", "key": "10.1038/s41416-023-02541-2"}], "notes": [], "created": "2024-01-15T12:56:41.546Z", "modified": "2024-11-25T10:15:24.092Z"}, {"entity": "publication", "iuid": "48993691f2c64543b650f3b600450b73", "links": {"self": {"href": "https://publications.scilifelab.se/publication/48993691f2c64543b650f3b600450b73.json"}, "display": {"href": "https://publications.scilifelab.se/publication/48993691f2c64543b650f3b600450b73"}}, "title": "Multianalyte serology in home-sampled blood enables an unbiased assessment of the immune response against SARS-CoV-2.", "authors": [{"family": "Roxhed", "given": "Niclas", "initials": "N", "orcid": "0000-0002-7147-6730", "researcher": {"href": "https://publications.scilifelab.se/researcher/3739210caaf14a28898849f20bf6ece5.json"}}, {"family": "Bendes", "given": "Annika", "initials": "A", "orcid": "0000-0001-9329-2353", "researcher": {"href": "https://publications.scilifelab.se/researcher/50dffce4f4444dd8b5ff8f9294146a0b.json"}}, {"family": "Dale", "given": "Matilda", "initials": "M", "orcid": "0000-0002-5788-7744", "researcher": {"href": "https://publications.scilifelab.se/researcher/59306e7e902048829efb30599ee3d2b1.json"}}, {"family": "Mattsson", "given": "Cecilia", "initials": "C"}, {"family": "Hanke", "given": "Leo", "initials": "L", "orcid": "0000-0001-5514-2418", "researcher": {"href": "https://publications.scilifelab.se/researcher/ece050a286f946f6807170cffc9320e7.json"}}, {"family": "Dodig-Crnkovi\u0107", "given": "Tea", "initials": "T", "orcid": "0000-0002-2875-896X", "researcher": {"href": "https://publications.scilifelab.se/researcher/cf18af5b676b449693945249fc1767e4.json"}}, {"family": "Christian", "given": "Murray", "initials": "M"}, {"family": "Meineke", "given": "Birthe", "initials": "B"}, {"family": "Els\u00e4sser", "given": "Simon", "initials": "S", "orcid": "0000-0001-8724-4849", "researcher": {"href": "https://publications.scilifelab.se/researcher/fcf26e35e037499aa1441a7738ba61af.json"}}, {"family": "Andr\u00e9ll", "given": "Juni", "initials": "J"}, {"family": "Havervall", "given": "Sebastian", "initials": "S"}, {"family": "Th\u00e5lin", "given": "Charlotte", "initials": "C", "orcid": "0000-0002-1345-6491", "researcher": {"href": "https://publications.scilifelab.se/researcher/130fb6ef6b774613a767e98f9f9b2eb4.json"}}, {"family": "Eklund", "given": "Carina", "initials": "C"}, {"family": "Dillner", "given": "Joakim", "initials": "J", "orcid": "0000-0001-8588-6506", "researcher": {"href": "https://publications.scilifelab.se/researcher/2b5c258635ad412f9e79994dcee4e323.json"}}, {"family": "Beck", "given": "Olof", "initials": "O"}, {"family": "Thomas", "given": "Cecilia E", "initials": "CE", "orcid": "0000-0001-6201-6380", "researcher": {"href": "https://publications.scilifelab.se/researcher/3a1156f987764218af202efbd76c31fd.json"}}, {"family": "McInerney", "given": "Gerald", "initials": "G", "orcid": "0000-0003-2257-7241", "researcher": {"href": "https://publications.scilifelab.se/researcher/5ac2f68095fe4426b97ec070865e5091.json"}}, {"family": "Hong", "given": "Mun-Gwan", "initials": "M"}, {"family": "Murrell", "given": "Ben", "initials": "B", "orcid": "0000-0002-0393-4445", "researcher": {"href": "https://publications.scilifelab.se/researcher/8a899203048943489bf7b6310a32b19f.json"}}, {"family": "Fredolini", "given": "Claudia", "initials": "C", "orcid": "0000-0002-7674-2014", "researcher": {"href": "https://publications.scilifelab.se/researcher/40ac3a5823cb4f998cc8bdb96dcbf195.json"}}, {"family": "Schwenk", "given": "Jochen M", "initials": "JM", "orcid": "0000-0001-8141-8449", "researcher": {"href": "https://publications.scilifelab.se/researcher/aba5822711b246b397fffacb7ae403b3.json"}}], "type": "journal article", "published": "2021-06-17", "journal": {"title": "Nat Commun", "issn": "2041-1723", "issn-l": "2041-1723", "volume": "12", "issue": "1", "pages": "3695"}, "abstract": "Serological testing is essential to curb the consequences of the COVID-19 pandemic. However, most assays are still limited to single analytes and samples collected within healthcare. Thus, we establish a multianalyte and multiplexed approach to reliably profile IgG and IgM levels against several versions of SARS-CoV-2 proteins (S, RBD, N) in home-sampled dried blood spots (DBS). We analyse DBS collected during spring of 2020 from 878 random and undiagnosed individuals from the population in Stockholm, Sweden, and use classification approaches to estimate an accumulated seroprevalence of 12.5% (95% CI: 10.3%-14.7%). This includes 5.4% of the samples being IgG+IgM+ against several SARS-CoV-2 proteins, as well as 2.1% being IgG-IgM+ and 5.0% being IgG+IgM- for the virus' S protein. Subjects classified as IgG+ for several SARS-CoV-2 proteins report influenza-like symptoms more frequently than those being IgG+ for only the S protein (OR = 6.1; p < 0.001). Among all seropositive cases, 30% are asymptomatic. Our strategy enables an accurate individual-level and multiplexed assessment of antibodies in home-sampled blood, assisting our understanding about the undiagnosed seroprevalence and diversity of the immune response against the coronavirus.", "doi": "10.1038/s41467-021-23893-4", "pmid": "34140485", "labels": {"Affinity Proteomics Stockholm": "Technology development"}, "xrefs": [{"db": "pii", "key": "10.1038/s41467-021-23893-4"}, {"db": "pmc", "key": "PMC8211676"}], "notes": [], "created": "2021-10-05T16:26:34.397Z", "modified": "2021-12-06T07:43:55.459Z"}, {"entity": "publication", "iuid": "13e1498d084a4f158e6801550ebd42a1", "links": {"self": {"href": "https://publications.scilifelab.se/publication/13e1498d084a4f158e6801550ebd42a1.json"}, "display": {"href": "https://publications.scilifelab.se/publication/13e1498d084a4f158e6801550ebd42a1"}}, "title": "Facets of individual-specific health signatures determined from longitudinal plasma proteome profiling.", "authors": [{"family": "Dodig-Crnkovi\u0107", "given": "Tea", "initials": "T", "orcid": "0000-0002-2875-896X", "researcher": {"href": "https://publications.scilifelab.se/researcher/cf18af5b676b449693945249fc1767e4.json"}}, {"family": "Hong", "given": "Mun-Gwan", "initials": "MG", "orcid": "0000-0001-8603-8293", "researcher": {"href": "https://publications.scilifelab.se/researcher/5d66c199ece143a6ab15222d8b55e3ea.json"}}, {"family": "Thomas", "given": "Cecilia Engel", "initials": "CE"}, {"family": "H\u00e4ussler", "given": "Ragna S", "initials": "RS", "orcid": "0000-0003-1664-8875", "researcher": {"href": "https://publications.scilifelab.se/researcher/ca04d9b9132747efb7db0efb6e34756a.json"}}, {"family": "Bendes", "given": "Annika", "initials": "A"}, {"family": "Dale", "given": "Matilda", "initials": "M", "orcid": "0000-0002-5788-7744", "researcher": {"href": "https://publications.scilifelab.se/researcher/59306e7e902048829efb30599ee3d2b1.json"}}, {"family": "Edfors", "given": "Fredrik", "initials": "F"}, {"family": "Forsstr\u00f6m", "given": "Bj\u00f6rn", "initials": "B"}, {"family": "Magnusson", "given": "Patrik K E", "initials": "PKE"}, {"family": "Schuppe-Koistinen", "given": "Ina", "initials": "I"}, {"family": "Odeberg", "given": "Jacob", "initials": "J"}, {"family": "Fagerberg", "given": "Linn", "initials": "L"}, {"family": "Gummesson", "given": "Anders", "initials": "A"}, {"family": "Bergstr\u00f6m", "given": "G\u00f6ran", "initials": "G"}, {"family": "Uhl\u00e9n", "given": "Mathias", "initials": "M", "orcid": "0000-0002-4858-8056", "researcher": {"href": "https://publications.scilifelab.se/researcher/ff81da3cb0cf4262873b993a1b06798c.json"}}, {"family": "Schwenk", "given": "Jochen M", "initials": "JM", "orcid": "0000-0001-8141-8449", "researcher": {"href": "https://publications.scilifelab.se/researcher/aba5822711b246b397fffacb7ae403b3.json"}}], "type": "journal article", "published": "2020-07-00", "journal": {"title": "EBioMedicine", "issn": "2352-3964", "issn-l": "2352-3964", "volume": "57", "issue": null, "pages": "102854"}, "abstract": "Precision medicine approaches aim to tackle diseases on an individual level through molecular profiling. Despite the growing knowledge about diseases and the reported diversity of molecular phenotypes, the descriptions of human health on an individual level have been far less elaborate.\n\nTo provide insights into the longitudinal protein signatures of well-being, we profiled blood plasma collected over one year from 101 clinically healthy individuals using multiplexed antibody assays. After applying an antibody validation scheme, we utilized > 700 protein profiles for in-depth analyses of the individuals' short-term health trajectories.\n\nWe found signatures of circulating proteomes to be highly individual-specific. Considering technical and longitudinal variability, we observed that 49% of the protein profiles were stable over one year. We also identified eight networks of proteins in which 11-242 proteins covaried over time. For each participant, there were unique protein profiles of which some could be explained by associations to genetic variants.\n\nThis observational and non-interventional study identifyed noticeable diversity among clinically healthy subjects, and facets of individual-specific signatures emerged by monitoring the variability of the circulating proteomes over time. To enable more personal hence precise assessments of health states, longitudinal profiling of circulating proteomes can provide a valuable component for precision medicine approaches.\n\nThis work was supported by the Erling Persson Foundation, the Swedish Heart and Lung Foundation, the Knut and Alice Wallenberg Foundation, Science for Life Laboratory, and the Swedish Research Council.", "doi": "10.1016/j.ebiom.2020.102854", "pmid": "32629387", "labels": {"Affinity Proteomics Stockholm": "Collaborative"}, "xrefs": [{"db": "pii", "key": "S2352-3964(20)30229-2"}, {"db": "pmc", "key": "PMC7334812"}], "notes": [], "created": "2020-12-10T19:03:42.215Z", "modified": "2021-11-10T12:49:49.689Z"}, {"entity": "publication", "iuid": "e81411b4717b4690acc189ae0314d13d", "links": {"self": {"href": "https://publications.scilifelab.se/publication/e81411b4717b4690acc189ae0314d13d.json"}, "display": {"href": "https://publications.scilifelab.se/publication/e81411b4717b4690acc189ae0314d13d"}}, "title": "Predicting and elucidating the etiology of fatty liver disease: A machine learning modeling and validation study in the IMI DIRECT cohorts.", "authors": [{"family": "Atabaki-Pasdar", "given": "Naeimeh", "initials": "N", "orcid": "0000-0001-7229-1888", "researcher": {"href": "https://publications.scilifelab.se/researcher/42005ff304fd4e5d855a248db59f9256.json"}}, {"family": "Ohlsson", "given": "Mattias", "initials": "M", "orcid": "0000-0003-1145-4297", "researcher": {"href": "https://publications.scilifelab.se/researcher/6550861766f14999b5059457fed37baa.json"}}, {"family": "Vi\u00f1uela", "given": "Ana", "initials": "A", "orcid": "0000-0003-3771-8537", "researcher": {"href": "https://publications.scilifelab.se/researcher/e6551fc3132f4fa597378c565247a315.json"}}, {"family": "Frau", "given": "Francesca", "initials": "F"}, {"family": "Pomares-Millan", "given": "Hugo", "initials": "H", "orcid": "0000-0001-9245-4576", "researcher": {"href": "https://publications.scilifelab.se/researcher/3a53517766c64538876c42890911aed7.json"}}, {"family": "Haid", "given": "Mark", "initials": "M", "orcid": "0000-0001-6118-1333", "researcher": {"href": "https://publications.scilifelab.se/researcher/a51bbc9e2ca34b75ba75e6b3be85da87.json"}}, {"family": "Jones", "given": "Angus G", "initials": "AG", "orcid": "0000-0002-0883-7599", "researcher": {"href": "https://publications.scilifelab.se/researcher/e61710036445440ea18c4cc05bbd8a0b.json"}}, {"family": "Thomas", "given": "E Louise", "initials": "EL", "orcid": "0000-0003-4235-4694", "researcher": {"href": "https://publications.scilifelab.se/researcher/186f6dee4a8a4e199e519199a62d4918.json"}}, {"family": "Koivula", "given": "Robert W", "initials": "RW", "orcid": "0000-0002-1646-4163", "researcher": {"href": "https://publications.scilifelab.se/researcher/29fa233507ea4e6190e70953cbb743a8.json"}}, {"family": "Kurbasic", "given": "Azra", "initials": "A", "orcid": "0000-0002-1910-2619", "researcher": {"href": "https://publications.scilifelab.se/researcher/64a6b0e38fdc43f59725c6013e9ffd75.json"}}, {"family": "Mutie", "given": "Pascal M", "initials": "PM"}, {"family": "Fitipaldi", "given": "Hugo", "initials": "H", "orcid": "0000-0001-5352-2134", "researcher": {"href": "https://publications.scilifelab.se/researcher/ca2f9fb4ba1a42c59104097626568a97.json"}}, {"family": "Fernandez", "given": "Juan", "initials": "J"}, {"family": "Dawed", "given": "Adem Y", "initials": "AY", "orcid": "0000-0003-0224-2428", "researcher": {"href": "https://publications.scilifelab.se/researcher/a1b08d70569c4ee98f6b174425a443a7.json"}}, {"family": "Giordano", "given": "Giuseppe N", "initials": "GN"}, {"family": "Forgie", "given": "Ian M", "initials": "IM", "orcid": "0000-0002-8800-6145", "researcher": {"href": "https://publications.scilifelab.se/researcher/bcf5280c81274cb3b983c00b20fbd0a7.json"}}, {"family": "McDonald", "given": "Timothy J", "initials": "TJ"}, {"family": "Rutters", "given": "Femke", "initials": "F"}, {"family": "Cederberg", "given": "Henna", "initials": "H", "orcid": "0000-0003-2901-9373", "researcher": {"href": "https://publications.scilifelab.se/researcher/64ab64bd196c4dc88904a53826dda0e1.json"}}, {"family": "Chabanova", "given": "Elizaveta", "initials": "E"}, {"family": "Dale", "given": "Matilda", "initials": "M", "orcid": "0000-0002-5788-7744", "researcher": {"href": "https://publications.scilifelab.se/researcher/59306e7e902048829efb30599ee3d2b1.json"}}, {"family": "Masi", "given": "Federico De", "initials": "F", "orcid": "0000-0003-4859-4170", "researcher": {"href": "https://publications.scilifelab.se/researcher/fb3d84bde37b4deb8838eb7b95762832.json"}}, {"family": "Thomas", "given": "Cecilia Engel", "initials": "CE", "orcid": "0000-0001-6201-6380", "researcher": {"href": "https://publications.scilifelab.se/researcher/3a1156f987764218af202efbd76c31fd.json"}}, {"family": "Allin", "given": "Kristine H", "initials": "KH", "orcid": "0000-0002-6880-5759", "researcher": {"href": "https://publications.scilifelab.se/researcher/3b7436fd7201456d9555235679ad0aa3.json"}}, {"family": "Hansen", "given": "Tue H", "initials": "TH", "orcid": "0000-0001-5948-8993", "researcher": {"href": "https://publications.scilifelab.se/researcher/c43c49838ac04c30ac2d92153e51f555.json"}}, {"family": "Heggie", "given": "Alison", "initials": "A"}, {"family": "Hong", "given": "Mun-Gwan", "initials": "MG"}, {"family": "Elders", "given": "Petra J M", "initials": "PJM", "orcid": "0000-0002-5907-7219", "researcher": {"href": "https://publications.scilifelab.se/researcher/4cf5e762102f4cc6a669b6d0989ab3a1.json"}}, {"family": "Kennedy", "given": "Gwen", "initials": "G", "orcid": "0000-0002-9856-3236", "researcher": {"href": "https://publications.scilifelab.se/researcher/28563ecc468548a4a75f127ffd3ab61b.json"}}, {"family": "Kokkola", "given": "Tarja", "initials": "T", "orcid": "0000-0002-3303-3912", "researcher": {"href": "https://publications.scilifelab.se/researcher/fa456d442a7342238959b8ee46310319.json"}}, {"family": "Pedersen", "given": "Helle Krogh", "initials": "HK", "orcid": "0000-0001-9609-7377", "researcher": {"href": "https://publications.scilifelab.se/researcher/ad86129a6eec49f1b0fe4ce09643c8a1.json"}}, {"family": "Mahajan", "given": "Anubha", "initials": "A", "orcid": "0000-0001-5585-3420", "researcher": {"href": "https://publications.scilifelab.se/researcher/194be8a851164e2ea4d004dd2febc9be.json"}}, {"family": "McEvoy", "given": "Donna", "initials": "D", "orcid": "0000-0003-1546-5567", "researcher": {"href": "https://publications.scilifelab.se/researcher/c4455f5ace534325ba30494630686066.json"}}, {"family": "Pattou", "given": "Francois", "initials": "F"}, {"family": "Raverdy", "given": "Violeta", "initials": "V"}, {"family": "H\u00e4ussler", "given": "Ragna S", "initials": "RS", "orcid": "0000-0003-1664-8875", "researcher": {"href": "https://publications.scilifelab.se/researcher/ca04d9b9132747efb7db0efb6e34756a.json"}}, {"family": "Sharma", "given": "Sapna", "initials": "S"}, {"family": "Thomsen", "given": "Henrik S", "initials": "HS"}, {"family": "Vangipurapu", "given": "Jagadish", "initials": "J", "orcid": "0000-0001-6657-2659", "researcher": {"href": "https://publications.scilifelab.se/researcher/cc3c64aafa4841729040479765aae6f2.json"}}, {"family": "Vestergaard", "given": "Henrik", "initials": "H", "orcid": "0000-0003-3090-269X", "researcher": {"href": "https://publications.scilifelab.se/researcher/4a79ddd7842e480f85b0a303125fdc9a.json"}}, {"family": "'t Hart", "given": "Leen M", "initials": "LM", "orcid": "0000-0003-4401-2938", "researcher": {"href": "https://publications.scilifelab.se/researcher/3cb1193c2ad3419899ec86d9d95bf25d.json"}}, {"family": "Adamski", "given": "Jerzy", "initials": "J"}, {"family": "Musholt", "given": "Petra B", "initials": "PB"}, {"family": "Brage", "given": "Soren", "initials": "S", "orcid": "0000-0002-1265-7355", "researcher": {"href": "https://publications.scilifelab.se/researcher/2edeab82aa9f4513baa3dc724c0a4a88.json"}}, {"family": "Brunak", "given": "S\u00f8ren", "initials": "S"}, {"family": "Dermitzakis", "given": "Emmanouil", "initials": "E"}, {"family": "Frost", "given": "Gary", "initials": "G", "orcid": "0000-0003-0529-6325", "researcher": {"href": "https://publications.scilifelab.se/researcher/b9312f44496b4bdb86ad9c5096aeb94c.json"}}, {"family": "Hansen", "given": "Torben", "initials": "T", "orcid": "0000-0001-8748-3831", "researcher": {"href": "https://publications.scilifelab.se/researcher/da403496660346079fc41975cae418d9.json"}}, {"family": "Laakso", "given": "Markku", "initials": "M"}, {"family": "Pedersen", "given": "Oluf", "initials": "O"}, {"family": "Ridderstr\u00e5le", "given": "Martin", "initials": "M"}, {"family": "Ruetten", "given": "Hartmut", "initials": "H"}, {"family": "Hattersley", "given": "Andrew T", "initials": "AT", "orcid": "0000-0001-5620-473X", "researcher": {"href": "https://publications.scilifelab.se/researcher/25dad832cfe041a79e35170e789e66c7.json"}}, {"family": "Walker", "given": "Mark", "initials": "M"}, {"family": "Beulens", "given": "Joline W J", "initials": "JWJ"}, {"family": "Mari", "given": "Andrea", "initials": "A", "orcid": "0000-0002-1436-5591", "researcher": {"href": "https://publications.scilifelab.se/researcher/c8b959c8980a4d108b602d82cd345ba6.json"}}, {"family": "Schwenk", "given": "Jochen M", "initials": "JM", "orcid": "0000-0001-8141-8449", "researcher": {"href": "https://publications.scilifelab.se/researcher/aba5822711b246b397fffacb7ae403b3.json"}}, {"family": "Gupta", "given": "Ramneek", "initials": "R", "orcid": "0000-0001-6841-6676", "researcher": {"href": "https://publications.scilifelab.se/researcher/445ec9fcd4a740a385550d10d19e8317.json"}}, {"family": "McCarthy", "given": "Mark I", "initials": "MI", "orcid": "0000-0002-4393-0510", "researcher": {"href": "https://publications.scilifelab.se/researcher/5e44f4b1ca3a49cb8f83450ef9482e91.json"}}, {"family": "Pearson", "given": "Ewan R", "initials": "ER", "orcid": "0000-0001-9237-8585", "researcher": {"href": "https://publications.scilifelab.se/researcher/320eb6ae20014620ad8f69c3f7b216b3.json"}}, {"family": "Bell", "given": "Jimmy D", "initials": "JD", "orcid": "0000-0003-3804-1281", "researcher": {"href": "https://publications.scilifelab.se/researcher/74a9ddf1d40e4b4fb1614a89a220e143.json"}}, {"family": "Pavo", "given": "Imre", "initials": "I"}, {"family": "Franks", "given": "Paul W", "initials": "PW", "orcid": "0000-0002-0520-7604", "researcher": {"href": "https://publications.scilifelab.se/researcher/1ebbf40c0f7e49dd8c75a2b6cbf27276.json"}}], "type": "journal article", "published": "2020-06-00", "journal": {"title": "PLoS Med.", "issn": "1549-1676", "issn-l": "1549-1277", "volume": "17", "issue": "6", "pages": "e1003149"}, "abstract": "Non-alcoholic fatty liver disease (NAFLD) is highly prevalent and causes serious health complications in individuals with and without type 2 diabetes (T2D). Early diagnosis of NAFLD is important, as this can help prevent irreversible damage to the liver and, ultimately, hepatocellular carcinomas. We sought to expand etiological understanding and develop a diagnostic tool for NAFLD using machine learning.\n\nWe utilized the baseline data from IMI DIRECT, a multicenter prospective cohort study of 3,029 European-ancestry adults recently diagnosed with T2D (n = 795) or at high risk of developing the disease (n = 2,234). Multi-omics (genetic, transcriptomic, proteomic, and metabolomic) and clinical (liver enzymes and other serological biomarkers, anthropometry, measures of beta-cell function, insulin sensitivity, and lifestyle) data comprised the key input variables. The models were trained on MRI-image-derived liver fat content (<5% or \u22655%) available for 1,514 participants. We applied LASSO (least absolute shrinkage and selection operator) to select features from the different layers of omics data and random forest analysis to develop the models. The prediction models included clinical and omics variables separately or in combination. A model including all omics and clinical variables yielded a cross-validated receiver operating characteristic area under the curve (ROCAUC) of 0.84 (95% CI 0.82, 0.86; p < 0.001), which compared with a ROCAUC of 0.82 (95% CI 0.81, 0.83; p < 0.001) for a model including 9 clinically accessible variables. The IMI DIRECT prediction models outperformed existing noninvasive NAFLD prediction tools. One limitation is that these analyses were performed in adults of European ancestry residing in northern Europe, and it is unknown how well these findings will translate to people of other ancestries and exposed to environmental risk factors that differ from those of the present cohort. Another key limitation of this study is that the prediction was done on a binary outcome of liver fat quantity (<5% or \u22655%) rather than a continuous one.\n\nIn this study, we developed several models with different combinations of clinical and omics data and identified biological features that appear to be associated with liver fat accumulation. In general, the clinical variables showed better prediction ability than the complex omics variables. However, the combination of omics and clinical variables yielded the highest accuracy. We have incorporated the developed clinical models into a web interface (see: https://www.predictliverfat.org/) and made it available to the community.\n\nClinicalTrials.gov NCT03814915.", "doi": "10.1371/journal.pmed.1003149", "pmid": "32559194", "labels": {"Affinity Proteomics Stockholm": "Collaborative"}, "xrefs": [{"db": "pii", "key": "PMEDICINE-D-20-00136"}, {"db": "pmc", "key": "PMC7304567"}, {"db": "ClinicalTrials.gov", "key": "NCT03814915"}], "notes": [], "created": "2020-12-10T19:03:48.331Z", "modified": "2021-11-10T12:50:35.188Z"}]}