Genetic Variation in the B-Type Natiuretic Peptide Pathway Affects BNP Levels
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The importance of B-type natriuretic peptide (BNP) as a diagnostic and therapeutic modality in cardiovascular disease is well known. BNP levels correlate clinical and physiologic characteristics, as well as outcomes. We sought to investigate the influence of BNP pathway genetic variation on BNP levels after adjustment for clinical/physiologic factors.
Materials and methods
DNA was extracted from 147 patients undergoing elective cardiac catheterization. Patients with elevated troponin were excluded. Detailed clinical data was collected including standard demographic, laboratory, echocardiographic and catheterization data. Genotype was determined at 19 loci in five genes relevant to the BNP pathway. Multivariable linear regression models of logBNP, adjusted for clinical variables, were used to assess the incremental influence of the genetic variants.
Natriuretic peptide precursor B gene (NPPB) variants incrementally improved models of logBNP after inclusion of clinical/physiologic parameters. The NPPB −381 T > C genotype was significantly associated with logBNP in the model (p = 0.0005), with the model predicting 50% lower BNP levels in otherwise similar T/T vs. C/C subjects. The NPPB 777 G > A (3′ flanking region) genotype was of borderline significance (p = 0.0078). None of the other genotypes examined were significant (all p > 0.2).
Genetic variation in NPPB significantly impacts BNP levels after adjustment for clinical/physiologic factors. The full linear regression model predicted up to a 50% relative difference in BNP levels between NPPB −381 T > C genotype groups. This suggests that NPPB sequence variants affect BNP physiology, possibly via transcriptional regulation. Further studies are needed to define whether these variants impact the clinical interpretation of BNP levels.
Key wordsBNP genetics natriuretic peptides left ventricular end-diastolic pressure heart failure
All authors contributed to this research and preparation of the manuscript.The authors would like to thank Derek Van Booven for extraordinary informatics support.
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