Genetic Predisposition to High Blood Pressure and Out-of-Office Hypertension: Insights from a Population Sample in Liechtenstein
Narula, S.; Mohammadi-Shemirani, P.; Aeschbacher, S.; Chong, M. R.; Le, A.; Theriault, S.; Grossman, K.; Pare, G.; Risch, L.; Risch, M.; Conen, D.
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Genetic predisposition is a risk factor for office hypertension. We tested whether genetic background could identify individuals with ambulatory daytime hypertension in a sample of white Europeans from Liechtenstein. We evaluated two measures of predisposition to hypertension: family history and polygenic risk scores (PRS). Our analytic sample contained 1444 participants aged 25 to 41. Of the participants, 12% had office hypertension, while 37% had out-of-office hypertension. The correlation between blood pressure PRS and family history of hypertension was low (R2 = 4.96x10-3), but both were strongly associated with ambulatory blood pressure (2.2 mmHg per 1 SD increase [95% CI: 1.6, 2.7] & 2.4 mmHg increase with positive family history [95% CI: 1.3, 3.4], respectively). The PRS provides incremental improvement in predicting ambulatory systolic blood pressure beyond a validated blood pressure prediction score ({Delta}AIC = - 33), whereas family history does not ({Delta}AIC = 1). However, the difference in performance between a baseline prediction algorithm for identifying ambulatory systolic daytime hypertension (positive likelihood ratio of 6.87 [95% CI: 5.56, 8.49]; negative likelihood ratio of 0.45 [95% CI: 0.39, 0.51]) and the same model with PRS integrated (positive likelihood ratio of 7.69 [95% CI: 6.18, 9.57]; negative likelihood ratio of 0.43 [95% CI: 0.37, 0.49]) was modest. In conclusion, in a white European sample from Liechtenstein, PRS and family history are distinct constructs that are associated with increased clinical and ambulatory blood pressure. Unlike family history, polygenic risk scores provide incremental information in the identification of individuals with ambulatory hypertension. However, these gains are modest and warrant further development to improve predictive utility at the point-of-care.
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