Nyegaard, Mette

Rohde, Palle Duun

English

Introduction: Genomics has been forecasted to revolutionise human health by improving medical treatment through a better understanding of the genetic epidemiology of human diseases. Despite great successes of the last decade’s genome-wide association studies (GWAS), the results have to a limited extent been translated to genomic medicine. We propose, that one route to get closer to improved medical treatment is by understanding the genetics of medication-use. We hypothesise that, irrespectively of medical condition, medication-use per se has a unique genetic heritable architecture.Methods: Medication-use from 335.744 individuals from the UK Biobank was obtained, and we conducted a GWAS on 9 million imputed genetic variants. We estimated the heritability of medication-use and partitioned the genetic variance across different categories. Using five-fold cross validation we performed within sample prediction of medication-use.Results: We identified 57 independent loci associated with variation in medication-use and estimated that 14% of the total variation was attributable to common genetic variants. The largest fraction of genetic variance was captured by variants with low to medium minor allele frequency. In particular coding and conserved regions, as well as transcription start sites, displayed significantly enrichment of heritability. The mean prediction accuracy was 0.14.Conclusion: These results demonstrate that medication-use per se is a complex trait irrespectively of medical condition. Thus, if the goal is to improve medical treatment it might be insufficient to solely rely on analyses of complex diseases as medication-use per se has its own genetic architecture.<br/

    Aalborg UniversitetA polygenic architecture of medication-use across medical conditionsRohde, Palle Duun; Nyegaard, MetteCreative Commons LicenseUnspecifiedPublication date:2020Document VersionPublisher's PDF, also known as Version of recordLink to publication from Aalborg UniversityCitation for published version (APA):Rohde, P. D., & Nyegaard, M. (2020). A polygenic architecture of medication-use across medical conditions.Poster presented at European Society of Human Genetics, .General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright ownersand it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.            ? Users may download and print one copy of any publication from the public portal for the purpose of private study or research.            ? You may not further distribute the material or use it for any profit-making activity or commercial gain            ? You may freely distribute the URL identifying the publication in the public portal ?Take down policyIf you believe that this document breaches copyright please contact us at vbn@aub.aau.dk providing details, and we will remove access tothe work immediately and investigate your claim.Downloaded from vbn.aau.dk on: August 24, 2021A polygenic architecture of medication-useacross medical conditionsPalle Duun Rohde1* & Mette Nyegaard21 Department of Chemistry and Bioscience, Aalborg University, Denmark; 2 Department of Biomedicine, Aarhus University, Denmark*palledr@bio.aau.dkWe have shown that the total number of different medications people in the UK Biobank currently use has a polygenic architecture.We identified 57 independent quantitative trait loci for medication-use, and showed that 14% of the phenotypic variation was explained by common genetic variants.Medication-use had positive genetic correlation with heart diseases, and was negatively correlated with parents age of death and years in school.The genetic architecture of medication-use is complex, and isnot solely driven by common diseases, as indicated by the strong negative genetic correlation.To investigate the genetic architecture and biological mechanisms underlying medication-use in the general population.Previously, Wu et al (2019) performed a genetic analysis in the UK Biobank on medication-use of 23 medication categories. Here, we extend on these results by investigating medication-use, defined as the total number of different medications currently being used. We do this by performing a GWAS, heritability estimates and genetic correlation analysis. Research aim ConclusionNo conflict of interest to declareORCIDDATA & METHODSFrom the UK Biobank we extracted information on medication-use from n=335.744 unrelate white-British individuals (approval ID 31269) Medication-use was defined as the total number of different medications currently being used by the participants.Medication-use Genetic analysis of medication-useFor the genetic analyses we used ~9 million imputed common genetic variants.We performed the following analyses:- Genome-wide association study (by PLINK [REF])- Genetic correlations (by LD Hub [REF])- Heritability estimation and partitioning (by SumHer [REF])- Generic scores (by R-qgg [REF])3,337 different medications are currently being used.Top-used drugs (used by 18,000-66,000 individuals) are for;- heart failure and hypertension (ramipril, bendroflumethiazide)- lowering colesterol (simvastatin)- stomach ulcer (omeprazole)- painkillers and fever lowering (aspirin, ibuprofen, paracetamol)RESULTS-IWe identified 57 independent genetic loci showing statistical association with medication-use.Parents age at deathYears of schooling 2016Cigarettes smoked per dayInsomniaDepressive symptomsType 2 DiabetesCoronary artery diseaseGenetic correlation-0.6 -0.4 -0.2 0.0 0.2 0.4 0.6P=1.1e-11P=2.2e-114P=5.6e-05P=1.9e-25P=1.9e-34P=3.6e-35P=1.9e-93Estimated genetic correlations showed that medication-use was positively correlated with common diseases, smoking and depressive symptoms; and was negativelycorrelated with years in school and age of parents death.RESULTS-II0.00 0.02 0.04 0.06 0.08 0.100.000.020.040.060.080.10Proportion of SNPs per chromosomeProportion of hSNP2R2=0.90Estimated enrichment0.00.51.01.52.02.53.0CodingConservedCTCFDGFDHSFANTOM2 EnhancerEnhancerFetal DHSH3K27ac HniszH3K27ac PGC2H3K4me1H3K4me3H3K9acIntronPromoter flankingPromoterRepressedSuper enhancerTFBSTranscribedTSSUTR3UTR5Weak enhancernsP< 0.05The heritability of medication-use was estimated to 0.14, with equal contribution from each autosomal chromosomes, with some genomic regions highly enriched.Decomposing heritability Predicting medication-use0.001 0.01 0.05 0.1 0.2 0.5 0.9990.080.090.100.110.120.130.14P  value thresholdPrediction accuracy (correlation)0 20 40 60 80 1000.00.51.01.52.0GRS percentileEstimate of b0.001 0.01 0.05 0.1 0.2 0.5 0.9990.080.090.100.110.120.130.14P  value thresholdPrediction accuracy (correlation)0 20 40 60 80 1000.00.51.01.52.0GRS percentileEstimate of bAfter applying linkage disequilibrium pruning of the genetic variants (r2<0.7) the maximum prediction accuracy was obtained when including genetic markers with P-values < 0.2 (by five-fold cross validation).Dividing participants into percentiles according to their genertic scores, and estimate their effect size on medication-use, the 5% with highest genetic load, used on average 1.8 more drugs than the bottom distribution.CONCLUSIONOur results demonstrate that medication-use per se is a complex trait irrespectively of medical condition.The finding that current medication-use was strongly correlated with smoking behaviour, parents age of death, educational level and insomnia, suggest that the genetic architecture of medication-use is not biased towards major common diseases.Understanding the genetic aetiology of complex diseases has been suggested as the route for improving medical treatment. However, when current medication-use, across medical conditions, appears to have a polygenic architecture, it might be inadequate to solely rely on analyses of complex diseases for improving medical treatment.Thus, medication-use, or better medication response, is likely to be yet another puzzle piece in understanding complex human diseases, and for providing better medicaltreatment for future generations.Study summary PerspectiveGrant number: R287-2018-735Findings from this study;… 57 independent quantitative trait loci for medication-use.… 14% of the total variation in medication-use in UKBB is explained by common genetic variants.… coding and conserved regions are heavily enriched by     genetic variation for medication-use.… positive genetic correlation with heart disease, diabetes, depression, insomnia and smoking. ….negative genetic correlated with parents age of death and years in school.… mean prediction accuracy of medication-use was 0.14.… individuals with top 5% genetic load used ~1.8 more drugs than the bottom distribution.No conflict of interest to declareORCID

A polygenic architecture of medication-use across medical conditions

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A polygenic architecture of medication-use across medical conditions

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