Aims: To estimate how much information conveyed by self-reported family history of heart disease (FHHD) is already explained by clinical and genetic risk factors.
Methods and results: Cross-sectional analysis of UK Biobank participants without pre-existing coronary artery disease using a multivariable model with self-reported FHHD as the outcome. Clinical (diabetes, hypertension, smoking, apolipoprotein B-to-apolipoprotein AI ratio, waist-to-hip ratio, high sensitivity C-reactive protein, lipoprotein(a), triglycerides) and genetic risk factors (polygenic risk score for coronary artery disease [PRSCAD], heterozygous familial hypercholesterolemia [HeFH]) were exposures. Models were adjusted for age, sex, and cholesterol-lowering medication use. Multiple logistic regression models were fitted to associate FHHD with risk factors, with continuous variables treated as quintiles. Population attributable risks (PAR) were subsequently calculated from the resultant odds ratios. Among 166 714 individuals, 72 052 (43.2%) participants reported an FHHD. In a multivariable model, genetic risk factors PRSCAD (OR 1.30, CI 1.27-1.33) and HeFH (OR 1.31, 1.11-1.54) were most strongly associated with FHHD. Clinical risk factors followed: hypertension (OR 1.18, CI 1.15-1.21), lipoprotein(a) (OR 1.17, CI 1.14-1.20), apolipoprotein B-to-apolipoprotein AI ratio (OR 1.13, 95% CI 1.10-1.16), and triglycerides (OR 1.07, CI 1.04-1.10). For the PAR analyses: 21.9% (CI 18.19-25.63) of the risk of reporting an FHHD is attributed to clinical factors, 22.2% (CI% 20.44-23.88) is attributed to genetic factors, and 36.0% (CI 33.31-38.68) is attributed to genetic and clinical factors combined.
Conclusions: A combined model of clinical and genetic risk factors explains only 36% of the likelihood of FHHD, implying additional value in the family history.
Keywords: Cardiovascular disease; Family history of heart disease; Genetics; Polygenic risk score; Prevention; Risk factor; UK Biobank.
With advances in genetics, it is tempting to assume that the ‘family history’ of a patient is an imperfect proxy for information we can already glean from genetics and laboratory tests. However, this study shows that much of the information contained in the self-reported family history of heart disease is not captured by currently available genetic and clinical biomarkers and highlights an important knowledge gap. Clinically used biomarkers explained only 21.9% of the likelihood of a patient reporting a family history of heart disease, while genetics explained 22.2%, and a combined model explained 36% of this likelihoodThe majority of the risk of reporting a family history went unexplained, implying that family history still has major relevance in clinical practice.
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