A meta-analysis [19
] of 21 cohort studies revealed that weight effects on BP accounts for approximately 45% of the risk for coronary heart disease. These findings remained consistent independent of other risk factors associated with high BP and coronary heart disease. Therefore, the next logical step in the literature was to examine genetic determinants of BMI and obesity. A meta-analysis [20
] of 37 studies concluded that specific loci for BMI and obesity could not be found. However, the strongest linkage with possible BMI loci was associated with high BP.
Previous studies have investigated the gene–environment interaction of BMI and high BP. However, each of these studies investigated a different polymorphism or genetic region of interest, making it difficult to reach definitive conclusions about whether these associations are true or false. For example, the HyperGEN study [21
] found a significant interaction between BMI and promoter polymorphisms in the angiotensinogen gene (AGT) that affects BP in whites and blacks. In comparison, the Framingham Heart Study [22
] found an association between polymorphisms in the chromosome 2p region based on BMI and sex. Another study [23
] claimed that the fat level in the body influences C-reactive protein and inflammation that signals polymorphisms at the catecholaminergic/β-adrenergic pathway loci thereby increasing BP. International studies have found significant associations with BMI, BP, and TGF-β1 in eastern Europeans [24
] and Gln27Glu and Thr164Ile polymorphisms in predominately biracial participants in Brazil [25
]. Another study based in the USA [26
] found no conclusive evidence of interaction between polymorphisms in a G-protein GNB3
and BMI influencing high BP among African–Americans.
Other researchers have concluded that although obesity has been related to increases in BP, genetic markers for obesity are not necessarily related to genetic risks for high BP among African–Americans [27
]. Telgmann et al
] have determined that certain SAH
alleles on chromosome 16 had a significant effect on BMI in white hypertensive patients, but the mechanism of the obesity related to high BP remains unknown. Although genetic studies have identified polymorphisms associated with high BP among African–Americans, little published literature bridges the gap in knowledge on BMI and how it may interact with genes to predispose African–Americans to high BP. Because a few studies have examined joint effects of genetic and environmental influences (BMI) on high BP risk among African–Americans in large epidemiological samples, this study contributes to the body of knowledge regarding the gene–environment interactions underlying high BP.
With respect to candidate gene studies, many genes and polymorphic variations have been studied, but none has predicted hypertension risk consistently. Therefore, despite some limited successes, identities and characteristics of individual genes variations that contribute to BP levels, gene–environment interactions with BMI, and the occurrence of hypertension in the population-at-large remain poorly defined. Because African–American women have the highest prevalence of high BP and of being overweight, research on genetic susceptibility and gene–environment interactions for hypertension among these women is needed to understand and control this chronic disease better. The present study provides additional insight into the interaction of genes and the internal environment of BMI related to predicting high BP among African–American women.
After using three levels of controlling false-positive findings, internal replication, FDR, and cross-validation; a sexspecific interaction effect associated with DBP between a nonsynonymous SNP (MMP3_rs679620) of metallopeptidase 3 (MMP3), and BMI was identified. MMP3, also called stromelysin, is a member of the matrix metalloproteinase (MMP) family [29
] that is involved in the breakdown of extra-cellular matrix in normal physiological processes, such as embryonic development, reproduction, tissue remodeling, as well as in disease processes, such as arthritis and metastasis. Most MMPs are secreted as inactive proproteins that are activated when cleaved by extra-cellular proteinases. MMP3_rs679620 encodes an enzyme that degrades fibronectin, laminin, collagens, and cartilage proteoglycans. The gene is part of a cluster of MMP genes that localize to chromosome 11q22.3. Quantitative PCR provided evidence that MMP3 expression levels were negatively correlated with obesity as measured by percentage body fat [30
]. The MMP3_rs679620 is also thought to be involved in progression of atherosclerosis [31
MMP3_rs679620 (A–G polymorphism) encodes a Lys-Glu nonsynonymous variant at the 45th amino acid (in a prodomain from 18th to 99th amino acid) of MMP3. The removal of a portion of the prodomain results in conformational changes and renders them to rapid autocatalytic activation to generate fully active enzyme [32
]. Although there is no direct evidence indicating the functional role of the 45th amino acid, it might be involved in the protein activation process. In its proximity [1600 base pair (bp) upstream from the MMP3 transcription start site], another MMP3 polymorphism, −11715A/6A (rs3025058), was identified, with one allele having a run of six adenosines (6A), whereas the other has five (5A) [33
]. In-vitro studies of promoter strength showed that the 5A allele expressed higher activity than the 6A allele in both cultured fibro-blasts and vascular smooth muscle cells. They suggested that, because of reduced gene transcription, homozygosity for the 6A allele would be associated with lower MMP3 levels in arterial walls than other genotypes. This lower level of proteolytic activity could favor extra-cellular matrix deposition in atherosclerotic lesions.
] have shown a relationship between MMP3, atherosclerosis, artery elasticity, and subsequent changes in SBP. Although a direct relationship between MMP3 and DBP has not been found, large artery stiffness has been associated with pulse pressure (a factor of both SBP and DBP) [31
]. MMP3 modulates fragmentation of extra-cellular matrix components and decreases elastin collagen ratio, resulting in disorganized elastin networks and large arterial stiffening with age [34
]. When women were compared with men, female sex steroids were found to double the fibrillin-1 deposition, influencing MMP3 variance expression that can result in large arterial stiffness [35
] have shown that although SBP is the best predictor of cardiovascular risk, much can be gleaned from DBP as an indicator of arterial stiffness, elevation in stroke volume, and narrowing pulse pressure. Additionally, increases in DBP have been linked to being overweight, obesity, and the metabolic syndrome, particularly among women [37
]. It has been postulated that the MMP3 pathway is altered in human obesity [30
]. This regulation in MMP3 activity and expression due to obesity may provide the foundation for understanding the protective effects found in this sample among participants with high BMI and low DBP. Research on BMI has recently indicated that some additional weight in the ‘overweight’ category can actually be protective in preventing disease and mortality over time [38
]. The authors suggest that those who are ‘overweight’ are protected from infection and disease due to greater nutritional reserves and higher lean body mass than people who are underweight, normal weight, or obese [38
]. Therefore, the relationship between those with low-to-normal BMI with high DBP may be attributed to the arterial stiffening properties of MMP3 and lack of protective properties of having a little extra adiposity to fight off and recover from diseases such as hypertension.
The present study did not genotype the well known SNP rs3025058. However, the nonsynonymous SNP MMP3_ rs679620 was highly correlated (linkage disequilibrium R2
= 0.98) with rs3025058 located in MMP3 promoter region among Pima Indians [30
]. The significant interaction effect between MMP3_rs679620 and BMI in African–American women could also be indicative of an interaction between rs3025058 and BMI depending on the linkage disequilibrium correlation between the two SNPs in African–Americans. However, one of these SNPs was not available in HapMap and this explains why linkage disequilibrium could not be calculated. Additionally, this is why Pima Indians and MMP3 were described for further reference. These relationships have not been explored in African–Americans prior to the present study.
Some limitations of the present study need to be considered. The approach was based on the premise that susceptibility alleles for common diseases were not under strong negative selection, and common variants contributed to common disease traits (i.e. the ‘common disease – common variant’ hypothesis) [39
]. However, the allelic spectrum for genes associated with complex quantitative traits, such as BP, was not fully delineated. It was possible that multiple rare polymorphisms in the biological and positional candidate genes that were studied could influence BP. Due to a lack of statistical power, identifying associations with BP using such alleles would not be possible using approaches employed in the present study. The inferences may not be generalizable to individuals who are younger, normotensive, or of other ethnic groups. Although a priori power calculations indicated that the study had adequate power to detect relatively small SNP effects, insufficient sample sizes (full sample and re-sampled subsets) or random measurement error may have limited the power to detect genotype–phenotype associations. The validation of the random-zero sphygmomanometers used in the GENOA study to collect BP readings was not known, but use of random-zero sphygmomanometers have been validated for many years and has been accepted for clinical investigation worldwide. Despite some limitations, the approach employed in the present study illustrated the use of SNPs in candidate genes to construct a more complete picture of the genetic architecture of complex traits, such as BP.
Genome-wide association is the currently favored approach for genetic studies of common human diseases. This approach has revealed suggestive SNP main effects associated with hypertension in a European white sample [40
]. However, localizing and identifying genes underlying environmental variations and the occurrence of high BP poses a formidable challenge. The next step in studying African–Americans and high BP could use a similar research design incorporating a genome-wide association approach in studying gene–BMI interactions on high BP.