Y Seldin M amp Lusis A Multiomics approaches to disease Genome Biol 18 83 2017 httpsdoiorg101186s1305901712151 Lipidomics etc Biological Datasets ID: 1042186
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1. Biological Datasets
2. Hasin, Y., Seldin, M. & Lusis, A. Multi-omics approaches to disease. Genome Biol 18, 83 (2017). https://doi.org/10.1186/s13059-017-1215-1Lipidomicsetc!
3. Biological DatasetsGenomicEpigenomicBiomarkerProteomicNew!
4. Basic principles of applying -omicsAre any of theseassociated withmy variable ofinterest?Which arethe mostimportant?Biological mechanisms?Objective measure of health?Predict outcomes?(Direction of causality??)
5. Biology overview
6. DNA
7. DNA in the nucleus
8. C-reactive protein RNA;C-reactive protein gene expression
9. C-reactive protein
10. C-reactive protein
11.
12. C-reactive protein geneGene expressionC-reactive proteinC-reactive protein RNA;C-reactive protein gene expression
13. DNA methylation:One of several mechanisms to control gene expressionLess C-reactive proteinLess C-reactive protein RNA;Less C-reactive protein gene expressionMethylatedC-reactive protein gene
14. Genetic dataset
15. Anna DearmanPossiblegenotypes:AAAGGGPersonAPersonB
16. Genetics500,000 variants10,000 participantsSNP IDChromosomeDNA baseVariant 1Variant 2Genotype for Person AGenotype for Person BGenotype for Person Crs364513ATAAAAAArs780978146CGCGCCCCrs156741500GCCCGCGCrs5856781729TATATATArs134453411001ATATATATrs135743511702ACAAAAAArs45353612064CGCGCCGGrs3645612617TAAAAAAArs780157812662GAGGGGGGrs81567413185GCGCGCGCrs59467817659ATATAAATrs1454534111288TATTTATTrs173645112681TGTTTTTGDNAfrombloodcells
17. Genetics500,000 variants10,000 participantsSNP IDChromosomeDNA baseVariant 1Variant 2Genotype for Person AGenotype for Person BGenotype for Person Crs364513AT222rs780978146CG122rs156741500GC011rs5856781729TA111rs134453411001AT111rs135743511702AC222rs45353612064CG120rs3645612617TA000rs780157812662GA222rs81567413185GC111rs59467817659AT121rs1454534111288TA212rs173645112681TG221DNAfrombloodcells
18. GeneticsGenome-wide association studies (GWAS)Polygenic scoresBody mass indexEducational attainmentTestosterone levelPersonality traitsetc…OutcomesGenetic factors
19. Polygenic scores2 polygenic scores (for now)…DNAfrombloodcellsPGSPolygenic score for Person APolygenic score for Person BPolygenic score for Person CBody Mass Index PGS5.06.37.7Testosterone PGS7.84.13.2
20. Epigenetic dataset
21. Anna DearmanPersonAPersonBWhite blood cells DNA
22. Anna DearmanPersonAPersonBWhite blood cells DNA100% methylation50% methylation
23. 850,000 methylation sites3,650 participantsCpG IDChromosomeDNA positionMethylation % for Person AMethylation % for Person BMethylation % for Person Ccg3645130.350.050.21cg7809781460.620.020.55cg1567415000.640.840.45cg58567817290.980.640.45cg1344534110010.260.240.18cg1357435117020.370.840.16cg453536120640.830.180.92cg36456126170.500.180.17cg7801578126620.940.160.39cg815674131850.960.810.20cg594678176590.920.040.67cg14545341112880.670.220.05cg1736451126810.220.830.86EpigeneticsMethylatedDNAfrombloodcells
24. EpigeneticsEpigenome-wide association studies (EWAS)exposuresoutcomesDNA methylation signatures/scoresBiological ageing (epigenetic clocks)SmokingInflammationetc…OutcomesEpigenetic factorsExposures
25. Epigenetic clocks5 epigenetic clocks3,650 participantsMethylatedDNAfrombloodcellsClockEpigenetic age for Person AEpigenetic age for Person BEpigenetic age for Person CHorvath 2013438178Hannum448279PhenoAge428077Horvath skin & blood407975Lin438178
26. Biomarker dataset
27. Biomarkers21 biomolecules that are routinely used in hospital blood testsIncludes measures offat in the blooddiabetes inflammation and the immune systemanaemia (e.g. haemoglobin)liver and kidney functionhormones (e.g. testosterone)13,000 participantsNon-blood biomarkersLung function, grip strength, BMI, etcplasmaserumblood
28. BiomarkersAssociations between biomarkers andexposuresoutcomes Allostatic load indexMetabolic syndrome indexFrailty indexetcOutcomesBiomarkersExposures
29. Proteomic dataset
30. PersonAPersonBClotted blood SerumMore proteinLess protein
31. Proteomics184 proteins6,180 participantsProteinAbundance for Person AAbundance for Person BAbundance for Person CANG0.74.65.0ANGPTL33.72.70.1AOC32.51.61.5APOM5.81.33.0C1QTNF11.90.43.2C23.53.32.6CA10.50.32.6CA32.61.55.8CA43.81.14.7CCL143.40.22.5CCL182.90.90.8CCL51.13.55.1CD464.74.04.7Proteinfromserum
32. ProteomicsAssociations between protein levels andexposuresoutcomes Protein signaturesOutcomesExposuresProteins
33. Proteins and sociology?
34. https://doi.org/10.1038/nature05526https://doi.org/10.1038/s41598-020-79429-1https://doi.org/10.3389/fpubh.2020.00422https://doi.org/10.1038/s41467-019-14161-7