Protocol detail

Genetic Risk Score for Blood Pressure and Cardiovascular Disease

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We calculated a weighted genetic risk score (GRS) (Supplementary Table 24) to provide an estimate of the combined effect of the BP raising variants on BP and risk of hypertension and applied this to the UKB data (Supplementary Methods). Our analysis included 423,713 unrelated individuals of European ancestry of whom 392,092 individuals were free of cardiovascular events at baseline.
We assessed the association of the continuous GRS variable on BP and with the risk of hypertension, with and without adjustment for sex. We then compared BP levels and risk of hypertension, respectively, for individuals in the top vs bottom quintiles of the GRS distribution. Similar analyses were performed for the top vs bottom deciles of the GRS distribution. All analyses were restricted to the 392,092 unrelated individuals of European ancestry from UKB. As a sensitivity analysis to assess for evidence of bias in the UKB results, we also carried out similar analyses in Airwave, an independent cohort of N=14,004 unrelated participants of European descent30 (link) (Supplementary Methods).
We calculated the association of the GRS with cardiovascular disease in unrelated participants in UKB data, based on self-reported medical history, and linkage to hospitalization and mortality data (Supplementary Table 25). We use logistic regression with binary outcome variables for composite incident cardiovascular disease (Supplementary Methods), incident myocardial infarction and incident stroke (using the algorithmic UKB definitions) and GRS as explanatory variable (with and without sex adjustment).
We also assessed the association of this GRS with BP in unrelated individuals Africans (N=6,970) and South Asians (N=8,827) from the UKB to see whether BP-associated SNPs identified from GWAS predominantly in Europeans are also associated with BP in populations of non-European ancestry.
We calculated the percentage of variance in BP explained by genetic variants using the independent Airwave cohort (N=14,004) (Supplementary Methods). We considered three different levels of the GRS: (i) all pairwise-independent, LD-filtered (r² < 0.1) published SNPs within the known loci; (ii) all known SNPs and sentinel SNPs at novel loci; (iii) all independent signals at all 901 known and novel loci including the 163 secondary SNPs.

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Evangelou E., Warren H.R., Mosen-Ansorena D., Mifsud B., Pazoki R., Gao H., Ntritsos G., Dimou N., Cabrera C.P., Karaman I., Ng F.L., Evangelou M., Witkowska K., Tzanis E., Hellwege J.N., Giri A., Velez Edwards D.R., Sun Y.V., Cho K., Gaziano J.M., Wilson P.W., Tsao P.S., Kovesdy C.P., Esko T., Mägi R., Milani L., Almgren P., Boutin T., Debette S., Ding J., Giulianini F., Holliday E.G., Jackson A.U., Li-Gao R., Lin W.Y., Luan J., Mangino M., Oldmeadow C., Prins B.P., Qian Y., Sargurupremraj M., Shah N., Surendran P., Thériault S., Verweij N., Willems S.M., Zhao J.H., Amouyel P., Connell J., de Mutsert R., Doney A.S., Farrall M., Menni C., Morris A.D., Noordam R., Paré G., Poulter N.R., Shields D.C., Stanton A., Thom S., Abecasis G., Amin N., Arking D.E., Ayers K.L., Barbieri C.M., Batini C., Bis J.C., Blake T., Bochud M., Boehnke M., Boerwinkle E., Boomsma D.I., Bottinger E.P., Braund P.S., Brumat M., Campbell A., Campbell H., Chakravarti A., Chambers J.C., Chauhan G., Ciullo M., Cocca M., Collins F., Cordell H.J., Davies G., de Borst M.H., de Geus E.J., Deary I.J., Deelen J., Del Greco M.F., Demirkale C.Y., Dörr M., Ehret G.B., Elosua R., Enroth S., Erzurumluoglu A.M., Ferreira T., Frånberg M., Franco O.H., Gandin I., Gasparini P., Giedraitis V., Gieger C., Girotto G., Goel A., Gow A.J., Gudnason V., Guo X., Gyllensten U., Hamsten A., Harris T.B., Harris S.E., Hartman C.A., Havulinna A.S., Hicks A.A., Hofer E., Hofman A., Hottenga J.J., Huffman J.E., Hwang S.J., Ingelsson E., James A., Jansen R., Jarvelin M.R., Joehanes R., Johansson Å., Johnson A.D., Joshi P.K., Jousilahti P., Jukema J.W., Jula A., Kähönen M., Kathiresan S., Keavney B.D., Khaw K.T., Knekt P., Knight J., Kolcic I., Kooner J.S., Koskinen S., Kristiansson K., Kutalik Z., Laan M., Larson M., Launer L.J., Lehne B., Lehtimäki T., Liewald D.C., Lin L., Lind L., Lindgren C.M., Liu Y., Loos R.J., Lopez L.M., Lu Y., Lyytikäinen L.P., Mahajan A., Mamasoula C., Marrugat J., Marten J., Milaneschi Y., Morgan A., Morris A.P., Morrison A.C., Munson P.J., Nalls M.A., Nandakumar P., Nelson C.P., Niiranen T., Nolte I.M., Nutile T., Oldehinkel A.J., Oostra B.A., O'Reilly P.F., Org E., Padmanabhan S., Palmas W., Palotie A., Pattie A., Penninx B.W., Perola M., Peters A., Polasek O., Pramstaller P.P., Nguyen Q.T., Raitakari O.T., Ren M., Rettig R., Rice K., Ridker P.M., Ried J.S., Riese H., Ripatti S., Robino A., Rose L.M., Rotter J.I., Rudan I., Ruggiero D., Saba Y., Sala C.F., Salomaa V., Samani N.J., Sarin A.P., Schmidt R., Schmidt H., Shrine N., Siscovick D., Smith A.V., Snieder H., Sõber S., Sorice R., Starr J.M., Stott D.J., Strachan D.P., Strawbridge R.J., Sundström J., Swertz M.A., Taylor K.D., Teumer A., Tobin M.D., Tomaszewski M., Toniolo D., Traglia M., Trompet S., Tuomilehto J., Tzourio C., Uitterlinden A.G., Vaez A., van der Most P.J., van Duijn C.M., Vergnaud A.C., Verwoert G.C., Vitart V., Völker U., Vollenweider P., Vuckovic D., Watkins H., Wild S.H., Willemsen G., Wilson J.F., Wright A.F., Yao J., Zemunik T., Zhang W., Attia J.R., Butterworth A.S., Chasman D.I., Conen D., Cucca F., Danesh J., Hayward C., Howson J.M., Laakso M., Lakatta E.G., Langenberg C., Melander O., Mook-Kanamori D.O., Palmer C.N., Risch L., Scott R.A., Scott R.J., Sever P., Spector T.D., van der Harst P., Wareham N.J., Zeggini E., Levy D., Munroe P.B., Newton-Cheh C., Brown M.J., Metspalu A., Hung A.M., O’Donnell C.J., Edwards T.L., Psaty B.M., Tzoulaki I., Barnes M.R., Wain L.V., Elliott P, & Caulfield M.J. (2018). Genetic analysis of over one million people identifies 535 new loci associated with blood pressure traits. Nature genetics, 50(10), 1412-1425.

Publication 2018

Africans Cardiovascular Cardiovascular disease European Genetic variants Gwas Hospitalization Hypertension Myocardial infarction Pairwise Populations Sensitivity Snps South asians Stroke Three

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Protocol cited in 95 other protocols

Variable analysis

independent variables

Weighted genetic risk score (GRS)

dependent variables

Blood pressure (BP)
Risk of hypertension
Cardiovascular disease
Incident myocardial infarction
Incident stroke

positive controls

Airwave cohort (N=14,004 unrelated participants of European descent)

negative controls

Unrelated individuals of African ancestry (N=6,970) and South Asian ancestry (N=8,827) from the UKB

Annotations

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