Primary hypertension is widely believed to be a complex polygenic disorder with the manifestation influenced by the interactions of genomic and environmental factors making identification of susceptibility genes a major challenge. With major advancement in high-throughput genotyping technology, genome-wide association study (GWAS) has become a powerful tool for researchers studying genetically complex diseases. GWASs work through revealing links between DNA sequence variation and a disease or trait with biomedical importance. The human genome is a very long DNA sequence which consists of billions of nucleotides arranged in a unique way. A single base-pair change in the DNA sequence is known as a single nucleotide polymorphism (SNP). With the help of modern genotyping techniques such as chip-based genotyping arrays, thousands of SNPs can be genotyped easily. Large-scale GWASs, in which more than half a million of common SNPs are genotyped and analyzed for disease association in hundreds of thousands of cases and controls, have been broadly successful in identifying SNPs associated with heart diseases, diabetes, autoimmune diseases, and psychiatric disorders. It is however still debatable whether GWAS is the best approach for hypertension. The following is a brief overview on the outcomes of a decade of GWASs on primary hypertension.

Primary aldosteronism (PA), also known as Conn’s syndrome, is a common curable cause of hypertension. Family studies of essential hypertensive patients suggest that heritable genetic factors play a role in blood pressure regulation1. Interestingly, single nucleotide polymorphisms (SNP) in genes encoding enzymes involved with adrenal steroidogenesis, CYP11B2, CYP11B1 and CYP17A1, associate with increased risk of hypertension2. Therefore, we analysed whether selected SNPs in these genes are associated with PA. We performed an association study using genotype imputation for selected SNPs of the steroidogenic enzyme genes CYP11B2 (rs4546, rs1799998, rs13268025), CYP11B1 (rs6410, rs149845727), and CYP17A1 (rs1004467, rs138009835, rs2150927) from a pilot genome wide association study of Malaysian PA patients and healthy controls which was merged with the Singapore Genome Variation Project (SGVP) population dataset3. Genotype imputation for minor and major alleles was validated using PCR sequencing (n>10 for each genotype). Further, one SNP from each steroidogenic enzyme (CYP11B2:rs1799998, CYP11B1:rs6410 and CYP17A1:rs1004467) was validated using commercial TaqMan genotyping assays on the ABI 7000 Sequence Detection System which was performed on 149 PA patients and 78 non-hypertensive healthy individuals. Case-control genetic association analysis was performed at http://www.oege.org/software/orcalc.html and the association between genotypes and phenotypes was done using the independent-samples Kruskal-Wallis test on SPSS (version 25). The Minor Allele Frequencies (MAFs) for rs1004467, rs6410 and rs1799998 were similar to East Asian populations but differed significantly different from European, African, American and South Asian populations (rs1004467 MAF: C=0.258/298, rs6410 MAF: A=0.265/298, rs1799998 MAF: C=0.225/298). In Chinese patients matched by gender, heterozygotes for rs6410 had significantly increased risk of PA compared to common homozygotes (OR: 3.15, 95% CI: 1.01–9.8, p=0.04). Across patients of different ethnicity, the distribution of aldosterone levels was significantly different (p=0.039). In summary, only SNP rs6410 in Chinese patients matched by gender showed association with PA in our South East Asian cohort. More functional experiments need to be done to find out whether this is causal for PA or whether the SNP is in linkage disequilibrium with the actual functional causative SNPs. Once the functional SNP is known, identification of these germline variants in asymptomatic family members would allow early screening of PA to be offered and potentially provide novel drug targets to treat the disease. References: 1Timberlake et al., Curr Opin Nephrol Hypertens. 2001 Jan;10(1):71-9. 2MacKenzie et al., Int J Mol Sci. 2017 Mar 7;18(3). pii: E579. 3Teo et al., Genome Res. 2009 Nov;19(11):2154-62.