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Abstract
An important aspect of precision medicine is to probe the stability in molecular profiles among healthy individuals over time. Here, we sample a longitudinal wellness cohort with 100 healthy individuals and analyze blood molecular profiles including proteomics, transcriptomics, lipidomics, metabolomics, autoantibodies and immune cell profiling, complemented with gut microbiota composition and routine clinical chemistry. Overall, our results show high variation between individuals across different molecular readouts, while the intra-individual baseline variation is low. The analyses show that each individual has a unique and stable plasma protein profile throughout the study period and that many individuals also show distinct profiles with regards to the other omics datasets, with strong underlying connections between the blood proteome and the clinical chemistry parameters. In conclusion, the results support an individual-based definition of health and show that comprehensive omics profiling in a longitudinal manner is a path forward for precision medicine.
An important aspect of precision medicine is to probe the stability in molecular profiles among healthy individuals over time. Here, the authors sample a longitudinal wellness cohort and analyse blood molecular profiles as well as gut microbiota composition.
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1 KTH Royal Institute of Technology, Science for Life Laboratory, Department of Protein Science, Stockholm, Sweden (GRID:grid.5037.1) (ISNI:0000000121581746)
2 University of Gothenburg, Wallenberg Laboratory and Sahlgrenska Center for Cardiovascular and Metabolic Research, Department of Molecular and Clinical Medicine, Institute of Medicine, Gothenburg, Sweden (GRID:grid.8761.8) (ISNI:0000 0000 9919 9582); Sahlgrenska University Hospital, Department of Clinical Genetics and Genomics, Region Västra Götaland, Gothenburg, Sweden (GRID:grid.1649.a) (ISNI:000000009445082X)
3 KTH Royal Institute of Technology, Science for Life Laboratory, Department of Protein Science, Stockholm, Sweden (GRID:grid.5037.1) (ISNI:0000000121581746); Karolinska Institutet, Center for Translational Microbiome Research, Department of Microbiology, Tumor and Cell Biology, Stockholm, Sweden (GRID:grid.4714.6) (ISNI:0000 0004 1937 0626)
4 Karolinska Institutet, Science for Life Laboratory, Department of Women’s and Children’s Health, Stockholm, Sweden (GRID:grid.4714.6) (ISNI:0000 0004 1937 0626)
5 University of Gothenburg, Wallenberg Laboratory and Sahlgrenska Center for Cardiovascular and Metabolic Research, Department of Molecular and Clinical Medicine, Institute of Medicine, Gothenburg, Sweden (GRID:grid.8761.8) (ISNI:0000 0000 9919 9582)
6 Karolinska Institutet, Center for Translational Microbiome Research, Department of Microbiology, Tumor and Cell Biology, Stockholm, Sweden (GRID:grid.4714.6) (ISNI:0000 0004 1937 0626)
7 Umeå University, Swedish Metabolomics Centre, Department of Molecular Biology, Umeå, Sweden (GRID:grid.12650.30) (ISNI:0000 0001 1034 3451)
8 KTH Royal Institute of Technology, Science for Life Laboratory, Department of Protein Science, Stockholm, Sweden (GRID:grid.5037.1) (ISNI:0000000121581746); King’s College London, Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, London, UK (GRID:grid.13097.3c) (ISNI:0000 0001 2322 6764)
9 University of Gothenburg, Wallenberg Laboratory and Sahlgrenska Center for Cardiovascular and Metabolic Research, Department of Molecular and Clinical Medicine, Institute of Medicine, Gothenburg, Sweden (GRID:grid.8761.8) (ISNI:0000 0000 9919 9582); Sahlgrenska University Hospital, Department of Internal Medicine, Region Västra Götaland, Gothenburg, Sweden (GRID:grid.1649.a) (ISNI:000000009445082X)
10 University of Gothenburg, Department of Molecular and Clinical Medicine, Institute of Medicine, Gothenburg, Sweden (GRID:grid.8761.8) (ISNI:0000 0000 9919 9582); Sahlgrenska University Hospital, Department of Cardiology, Region Västra Götaland, Gothenburg, Sweden (GRID:grid.1649.a) (ISNI:000000009445082X)
11 Codon Consulting, Stockholm, Sweden (GRID:grid.1649.a); Karolinska Institutet, Department of Learning, Informatics, Management and Ethics, Stockholm, Sweden (GRID:grid.4714.6) (ISNI:0000 0004 1937 0626)
12 Karolinska Institutet, Department of Medical Epidemiology and Biostatistics, Stockholm, Sweden (GRID:grid.4714.6) (ISNI:0000 0004 1937 0626)
13 Swedish University of Agricultural Sciences, Swedish Metabolomics Centre, Department of Forest Genetics and Plant Physiology, Umeå, Sweden (GRID:grid.6341.0) (ISNI:0000 0000 8578 2742)
14 University of Gothenburg, Wallenberg Laboratory and Sahlgrenska Center for Cardiovascular and Metabolic Research, Department of Molecular and Clinical Medicine, Institute of Medicine, Gothenburg, Sweden (GRID:grid.8761.8) (ISNI:0000 0000 9919 9582); Sahlgrenska University Hospital, Department of Clinical Physiology, Region Västra Götaland, Gothenburg, Sweden (GRID:grid.1649.a) (ISNI:000000009445082X); University of Copenhagen, Novo Nordisk Foundation Center for Basic Metabolic Research, Section for Metabolic Receptology and Enteroendocrinology, Faculty of Health Sciences, Copenhagen, Denmark (GRID:grid.5254.6) (ISNI:0000 0001 0674 042X)
15 University of Gothenburg, Wallenberg Laboratory and Sahlgrenska Center for Cardiovascular and Metabolic Research, Department of Molecular and Clinical Medicine, Institute of Medicine, Gothenburg, Sweden (GRID:grid.8761.8) (ISNI:0000 0000 9919 9582); Sahlgrenska University Hospital, Department of Clinical Physiology, Region Västra Götaland, Gothenburg, Sweden (GRID:grid.1649.a) (ISNI:000000009445082X)
16 KTH Royal Institute of Technology, Science for Life Laboratory, Department of Protein Science, Stockholm, Sweden (GRID:grid.5037.1) (ISNI:0000000121581746); Danish Technical University, Center for Biosustainability, Copenhagen, Denmark (GRID:grid.5170.3) (ISNI:0000 0001 2181 8870)