Genome wide association studies will unlock the genetic basis of human hypertension

Anna F Dominiczak

GWAS – a watershed in the history of genetics in medicine

• associations with common SNPs identified in GWAS have proven robust and reproducible

• as per design – most of these SNPs are associated with a relative risk of 1.5 per copy or less – thus even in aggregate account for a small fraction of the overall inherited risk

• the mechanisms whereby DNA variation in most of these regions influences disease is not obvious good, more work is needed!

GWAS & hypertension

• WTCCC published in 2007 = first GWAS for hypertension – no SNPs crossing experimental threshold of significance (px10-7)

• 8 further GWAS for BP or hypertension have been published since ( European, Japanese, Korean, African Americans, and Amish ancestry)

Examples of success

• cluster of SNPs on chr 2q24.3 with serine theronine kinase 39 (STK39) initial P=8.9x10-6 (Amish cohort), meta-analysis P=1.6x10-7 (n>7000 individuals) & relevant protein interacts with cation transporters in the kidney

• KORA (Europeans), SNP upstream T-cadherin (CDH13) gene on chr 16q23.3 associated with DBP, initial P=5.55x10-5, replication P=5.3 x10-8

• Korean cohort, two SNPs associated with SBP & DBP, initial P=9.1x10-7, replication P= 1.3x10-7, intragenic SNP near the ATPase calcium ion transporting membrane 1 gene (ATP2B1) - protein involved in calcium homeostasis

Wang et al, PNAS 2009

Org et al, Hum Mol Genet 2009

Cho et al, Nat Genet 2009

Meta-analysis of GWAS for BP & Hypertension

• 2009, two large-scale meta-analyses of GWAS for BP and hypertension published (Global BPGen & CHARGE)

• more stringent significance threshold (p < 5x10-8)

• genome imputation approaches to combine data across cohorts that used different SNP genotyping chips

• SBP & DBP in both consortia plus genome scan for hypertensive genes in CHARGE

• both consortia identified genome-wide significant associations at 8 loci with 3 discovered by both consortia

GWAS hits for blood pressure and hypertension (at p< 5x10-8)

MTHFRNPPACLCN6NPPBAGTRAPCASZ1

1

ULK4

MDS1

3

FGF5PRDM8c4orf22

4 10

CACNB2

c10orf107TMEM26 RTKN2 RHOBTB1 ARID5B

CYP17A1AS3MTCNNM2NT5C2

11

PLEKHA7

12

ATP2B1

SH2B3ATXN2TBX3TBX5

15

CSKULK3CYP1A1CYP1A2CSKLMAN1LARID3B

CDH1316

ULK4

MDS1

3

CACNB2

c10orf107TMEM26 RTKN2 RHOBTB1 ARID5B

CYP17A1AS3MTCNNM2NT5C2

CACNB2

c10orf107TMEM26 RTKN2 RHOBTB1 ARID5B ATP2B1

SH2B3ATXN2TBX3TBX5

PLCD3ACBD4HEX1M1HEX1M2ZNF652PHB

17

Newton Cheh et al, Nat Gen 2009 (chr 1,3,10,12,15,17)Levy et al, Nat Gen 2009 (chr 3,10,11,12,15)

New Candidate Loci for Hypertension

• Meta-analyses of GWAS results have revealed 13 new candidates loci for BP and hypertension

• Two of 13 genomic regions contain genes that have been previously implicated in hypertension susceptibility:

• Chr 1p32, atrial natriuretic peptide A and B-type natriuretic peptide genes NPPA & B

• Chr10q24, CYP17A1 gene- (mutations 17--hydoxylase CAH)

Critics of GWAS might tell you that:

• small effects of multiple genes• the modest fraction of heritability explained

• and lack of overlap with our biologic understanding • all suggest a weakness of genomics

I and many colleagues disagree

The origins of dislike/hate

• genetic mapping turns hypothesis – driven research on its head as it is based on the theory that systematic genome-wide study of DNA variation will lead us to disease genes

• very large sample sizes are required to pinpoint novel disease causing genes and very stringent level of statistical significance is required i.e. only collaborative big ventures win

The Genetic Architecture of BP

• each SNP explains a very small proportion of the total variation in SBP & DBP, 0.05-0.10% or 1mmHg/allele systolic and 0.5mmHg/allele diastolic BP

• but the aggregate effects of several variants do produce meaningful population changes in risk

• 2mmHg SBP 6% reduction of stroke & 5% reduction of CAD

• there are many more common variants associated with BP that remain to be discovered

Future• ongoing even larger meta-analyses of GWAS = International

Consortium for BP-Genome-Wide Association Study (ICBP-GWAS)

• studies targeting individuals with extreme phenotypes

• careful analysis of CNVs

• data from the 1000 Genomes Project open the possibility of reliable imputation of rare variant genotypes

• resequencing (next-generation) of cases and controls for fine mapping & causal variants

Feasibility of identifying genetic variants by risk allele frequency and strength of genetic effect

Manolio et al, Nature 2009

GWAS & opportunities for physician scientists

• rather than seeking a new twist on a long-studied pathway or asking whether discoveries in model organisms are relevant to humans, researchers can explore hundreds of genes proven by GWAS to be relevant to human disease

• the challenge is to develop research methods to take us from genetic localisation to medically useful application

“As for the future, your task is not to foresee, but to enable it”

Antoine de Saint – ExupéryThe Wisdom of the Sands