Heart failure and albuminuria associations across nearly 400,000 UK Biobank subjects now available in the CVDKP
Two new datasets now bring associations for heart failure and albuminuria from large UK Biobank subject pools to the Cardiovascular Disease Knowledge Portal (CVDKP). Both studies revealed important insights about the etiology of different aspects of cardiovascular disease. And the results of both studies are available now in the CVDKP--both integrated into the Portal, and as files of summary statistics for download.
The study of heart failure associations (Aragam et al. (2018), Circulation) looked at associations both with heart failure from any cause and with a more refined phenotype, nonischemic cardiomyopathy (NICM), defined as left ventricular dysfunction without coronary artery disease. The loci significantly associated with all-cause heart failure were predominantly those already known to be associated with heart failure risk factors, such as coronary artery disease and atrial fibrillation. However, refining the phenotype to NICM revealed a different spectrum of associations, overlapping with those previously shown to be associated with dilated cardiomyopathy (DCM).
When the authors looked more deeply into the rich phenotyping provided in UK Biobank records, they saw that only the identified DCM loci were also associated with imaging traits of subclinical heart failure, lending further support to the idea that these loci represent genomic regions where variation specifically influences susceptibility to heart failure rather than to upstream heart failure risk factors.
At the recent 2018 Scientific Sessions of the American Heart Association, the lead author of the study, Dr. Krishna Aragam, presented the work in a competition for the Genomic and Precision Medicine Young Investigator award. The paper was published online in Circulation during his talk, and we simultaneously deployed the results in the CVDKP. Congratulations to Dr. Aragam on winning the award!
The second new dataset in the CVDKP is a study of genetic associations with albuminuria--the presence of albumin in the urine (measured as urinary albumin-to-creatinine ratio), which is an indicator of risk for many cardiometabolic diseases, including coronary artery disease, stroke, heart failure, type 2 diabetes, and hypertension. This study (Haas et al. (2018), American Journal of Human Genetics) also surveyed UK Biobank participants.
One locus significantly associated with albuminuria was previously known; the authors replicated this association and uncovered 32 novel associations with genome-wide significance (defined with a strict threshold of p < 5 x 10e-9). The researchers constructed a genetic risk score from the 46 loci associated with albuminuria with a p-value of 5 x 10e-8 or better and validated it in two independent cohorts. They also performed Mendelian randomization analysis to explore the relationship between albuminuria and blood pressure, and discovered that the relationship is bidirectional, i.e., either condition may cause the other.
The results of these two important studies are available in the CVDKP via two different routes. For researchers who wish to perform independent analyses, the summary statistics from both studies are available for download on the CVDKP Data page. The results are also fully integrated into the CVDKP, and may be viewed in the context of associations for other cardiovascular phenotypes at these locations:
• On Gene pages (see an example) on the Common variants and High-impact variants tabs
• On Variant pages (see an example) in the Associations at a glance and Associations across all datasets sections
• Via the Variant Finder search
• View Manhattan plots of associations across the genome by selecting "Heart failure," "Nonischemic cardiomyopathy," or "Urinary albumin-to-creatinine ratio" in the View full genetic association results for a phenotype menu on the home page.
Please explore these new datasets and let us know if you have questions or comments!
The study of heart failure associations (Aragam et al. (2018), Circulation) looked at associations both with heart failure from any cause and with a more refined phenotype, nonischemic cardiomyopathy (NICM), defined as left ventricular dysfunction without coronary artery disease. The loci significantly associated with all-cause heart failure were predominantly those already known to be associated with heart failure risk factors, such as coronary artery disease and atrial fibrillation. However, refining the phenotype to NICM revealed a different spectrum of associations, overlapping with those previously shown to be associated with dilated cardiomyopathy (DCM).
When the authors looked more deeply into the rich phenotyping provided in UK Biobank records, they saw that only the identified DCM loci were also associated with imaging traits of subclinical heart failure, lending further support to the idea that these loci represent genomic regions where variation specifically influences susceptibility to heart failure rather than to upstream heart failure risk factors.
At the recent 2018 Scientific Sessions of the American Heart Association, the lead author of the study, Dr. Krishna Aragam, presented the work in a competition for the Genomic and Precision Medicine Young Investigator award. The paper was published online in Circulation during his talk, and we simultaneously deployed the results in the CVDKP. Congratulations to Dr. Aragam on winning the award!
The second new dataset in the CVDKP is a study of genetic associations with albuminuria--the presence of albumin in the urine (measured as urinary albumin-to-creatinine ratio), which is an indicator of risk for many cardiometabolic diseases, including coronary artery disease, stroke, heart failure, type 2 diabetes, and hypertension. This study (Haas et al. (2018), American Journal of Human Genetics) also surveyed UK Biobank participants.
One locus significantly associated with albuminuria was previously known; the authors replicated this association and uncovered 32 novel associations with genome-wide significance (defined with a strict threshold of p < 5 x 10e-9). The researchers constructed a genetic risk score from the 46 loci associated with albuminuria with a p-value of 5 x 10e-8 or better and validated it in two independent cohorts. They also performed Mendelian randomization analysis to explore the relationship between albuminuria and blood pressure, and discovered that the relationship is bidirectional, i.e., either condition may cause the other.
The results of these two important studies are available in the CVDKP via two different routes. For researchers who wish to perform independent analyses, the summary statistics from both studies are available for download on the CVDKP Data page. The results are also fully integrated into the CVDKP, and may be viewed in the context of associations for other cardiovascular phenotypes at these locations:
• On Gene pages (see an example) on the Common variants and High-impact variants tabs
• On Variant pages (see an example) in the Associations at a glance and Associations across all datasets sections
• Via the Variant Finder search
• View Manhattan plots of associations across the genome by selecting "Heart failure," "Nonischemic cardiomyopathy," or "Urinary albumin-to-creatinine ratio" in the View full genetic association results for a phenotype menu on the home page.
Please explore these new datasets and let us know if you have questions or comments!
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