Association Between a First-Degree Family History and Self-Reported Personal History of Obesity, Diabetes, and Heart and Blood Conditions: Results From the All of Us Research Program.
Danielle RasoolyRamal MoonesingheKevin LittrellLeland E HullMuin J KhouryPublished in: Journal of the American Heart Association (2023)
Background Family history reflects the complex interplay of genetic susceptibility and shared environmental exposures and is an important risk factor for obesity, diabetes, and heart and blood conditions (ODHB). However, the overlap in family history associations between various ODHBs has not been quantified. Methods and Results We assessed the association between a self-reported family history of ODHBs and their risk in the adult population (age ≥20 years) of the AoU (All of Us) Research Program, a longitudinal cohort study of diverse participants across the United States. We conducted a family history-wide association study to systematically assess the association of a first-degree family history of 15 ODHBs in AoU. We performed stratified analyses based on racial and ethnic categories, education, household income and gender minority status, and quantified associations by type of affected relatives. Of 125 430 participants, 76.8% reported a first-degree family history of any ODHB, most commonly hypertension (n=64 982, 51.8%), high cholesterol (49 753, 39.7%), and heart attack (29 618, 23.6%). We use the FamWAS method to estimate 225 familial associations among 15 ODHBs. The results include overlapping associations between family history of different types of cardiometabolic conditions (such as type 2 diabetes and coronary artery disease), and their risk factors (obesity, hypertension), where adults with a family history of 1 ODHB exhibited 1.1 to 5.6 times (1.5, on average) the odds of having a different ODHB. Conclusions Our findings inform the utility of family history data as a risk assessment and screening tool for the prevention of ODHBs and to provide additional insights into shared risk factors and pathogenic mechanisms.
Keyphrases
- type diabetes
- risk factors
- insulin resistance
- glycemic control
- weight loss
- metabolic syndrome
- blood pressure
- quality improvement
- coronary artery disease
- risk assessment
- heart failure
- cardiovascular disease
- high fat diet induced
- weight gain
- healthcare
- mental health
- atrial fibrillation
- human health
- air pollution
- gene expression
- physical activity
- body mass index
- adipose tissue
- genome wide
- heavy metals
- early onset
- big data
- climate change
- african american
- electronic health record
- artificial intelligence
- left ventricular
- coronary artery bypass grafting