BA18 - Follow-up studies of genetically determined risk factors

Investigator Names and Contact Information

Rebecca Jackson (Rebecca.Jackson@osumc.edu)

Introduction/Intent

Although there have been significant advances in our identification of clinical risk factors for osteoporosis, the molecular basis of this common complex disease is still poorly understood. With the advent of genome-wide association studies (GWAS), the goal to discover some putative causal genetic variants associated with complex diseases and traits like osteoporosis has begun to be realized. Because GWAS require fewer a priori assumptions than previously employed candidate gene approaches, these studies may also reveal novel mechanisms contributing to the pathophysiology of the disease state. With the support of a contract under the first BAA, we are currently conducting a GWAS to identify the genetic components of hip fracture. At the completion of the first BAA, we will have identified single nucleotide polymorphisms (SNPs) that have a consistent, statistically significant association with risk for hip fracture. Before the results of these studies can be applied clinically, it will be necessary to further define the interaction of putative causal variants with environmental exposures and to explore the potential risk differences by disease sub-types. As a follow-up to the initial discovery phase, the genetic variants identified must also be integrated with intermediate phenotypes reflecting relevant aspects of the causal pathways for osteoporotic fracture including bone remodeling, calcium homeostasis, bone mass and factors related to falls as well as with additional sources of functional genomic information to begin to address the functional relevance of the putative genetic variants.

The first phase of the plan, the hip-fracture GWAS (BAA03), with the genome-wide scan (Phase I-1) and Phase I-2 completed before the start of this application (BAA18: Phase II-2 - II-3). The objective of the Phase I studies funded through BAA03 is to identify variants (or polymorphisms) in the genome with consistent, reproducible statistical associations with a given disease (e.g., hip fracture). During this phase, the challenge is simply to winnow down millions of SNPs in the genome (Phase I-1) to tens-of-thousands of SNPs (Phase I-2) so that finally the top 100 significant and validated regions of interest can be fine-mapped using a denser marker panel which will include candidate causal variants as determined by the literature and/or genetic variation databases such as dbSNP (Phase I-3). Studies beyond Phase I-3 (e.g., Stages 4, 5, and 6) are dependent on the results of Phases I-1 to I-3 and therefore will be the focus of future proposals where the ultimate goal is to comprehensively screen the regions of interest for candidate causal variants, confirm such findings, and conduct functional studies.

In the two years following submission of BAA 3, GWAS have demonstrated considerable success, and have rapidly expanded our knowledge of the genetic architecture of many complex diseases (Zeggini 2007; Todd 2007; Saxena 2007; Herbert 2006; Frayling 2007; Helgadottir 2007; Duerr 2007; Rioux 2007, to name a few).These successful GWAS shared a number of design features which ultimately led to their success (Frayling 2007; Amos 2007; Frayling 2007; Grant 2007) including (i) large samples sizes for the discovery, validation, and fine-mapping stages; (ii) thoughtful selection of phenotypes having a known genetic basis; (iii) particular attention to genotype quality assessment and control (Clayton 2005); and (iv) rigorous replication in independent samples (Chanock 2007).

In this second BAA (BAA-18), we propose a parallel study to BAA03 that will expand the utility of the GWAS findings from BAA03, incorporates many of these successful design features, and further capitalizes (and eventually highlights through numerous planned publications) the core strength of the WHI resource. Specifically, the GWAS results from our first round BAA will be analyzed using several intermediate phenotypes and biomarkers to determine whether the genetic associations for hip fracture reflect (1) an effect on bone strength as measured by bone mineral density or (2) associations with other causal pathways leading to hip fracture. This model of testing intermediate phenotypes has worked extremely well for other GWAS efforts (Welcome Trust Case Control Consortium 2007) and provides fertile ground for subsequent grants and projects related to the functional mechanisms responsible for the observed statistical associations. It is also consistent with the stated goals of the BAA to “maximize the scientific yield from the biologic resource and associated participant exposures and outcome data“. As in BAA-I, we will limit our association efforts to the validation and fine-mapping stages (Phase II-2 and II-3, respectively). However, pending the results of these studies, future funding will be pursued for one or both of these studies either separately, concomitantly, or together.

Specific Aims

1. To determine whether the genetic variants for hip fracture are similar to or differ from SNPs associated with bone mass and lean body mass (as a surrogate for sarcopenia) by analyzing the most promising panel of SNPs from the Phase I-2 hip fracture GWAS in a subset of postmenopausal women from the BMD cohort.

2. To identify the association of a reproducible set of SNPs from the GWAS for hip fracture with putative biomarkers reflecting functional or causal pathways as intermediate phenotypes of hip fracture risk using both established and novel biomarkers reflecting bone remodeling-osteoblast regulation, calcium balance, and inflammatory (cytokine) pathways.

3. To analyze the set of genetic and serum/plasma biomarkers for hip fracture from core and R01 studies within WHI and the new biomarkers measured for this proposal to determine whether two or more risk factors together predict hip fracture increased or decreased risk beyond what would be expected from the main effects of each risk factor.

In addition, since the assessments of new biomarkers will be performed within cases and controls from the BAA03 GWAS, the original hip fracture GWAS data can be used to explore potential genetic associations with biomarker levels (controlling for or stratifying by hip fracture status) with reasonable power given 800 cases/controls.

Results/Findings

See Publications: 1554 submitted to Journal. WHI publications by study lists published WHI papers that have been generated by ancillary studies. A complete list of WHI papers is available in the Papers section of this website.

References

Amos CI. Successful design and conduct of genome-wide association studies. Hum Mol Genet 2007;16 Spec No. 2:R220-R225.

Chanock SJ, Manolio T, Boehnke M, Boerwinkle E, Hunter DJ, Thomas G, Hirschhorn JN, Abecasis G, Altshuler D, Bailey-Wilson JE, Brooks LD, Cardon LR et al. Replicating genotype-phenotype associations. Nature 2007;447:655-60.

Clayton DG, Walker NM, Smyth DJ, Pask R, Cooper JD, Maier LM, Smink LJ, Lam AC, Ovington NR, Stevens HE, Nutland S, Howson JM et al. Population structure, differential bias and genomic control in a large-scale, case-control association study. Nat Genet 2005;37:1243-46.

Duerr RH, Taylor KD, Brant SR, Rioux JD, Silverberg MS, Daly MJ, Steinhart AH, Abraham C, Regueiro M, Griffiths A, Dassopoulos T, Bitton A et al. A genome-wide association study identifies IL23R as an inflammatory bowel disease gene. Science 2006; 314:1461-63.

Frayling TM, Timpson NJ, Weedon MN, Zeggini E, Freathy RM, Lindgren CM, Perry JR, Elliott KS, Lango H, Rayner NW, Shields B, Harries LW et al. A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science 2007;316:889-94.

Frayling TM. A new era in finding Type 2 diabetes genes-the unusual suspects. Diabet Med 2007;24:696-701.

Grant SF, Hakonarson H. Recent development in pharmacogenomics: from candidate genes to genome-wide association studies. Expert Rev Molec Diag 2007;7:371-93.

Helgadottir A, Thorleifsson G, Manolescu A, Gretarsdottir S, Blondal T, Jonasdottir A, Jonasdottir A, Sigurdsson A, Baker A, Palsson A, Masson G, Gudbjartsson DF et al. A common variant on chromosome 9p21 affects the risk of myocardial infarction. Science 2007;316:1491-93.

Herbert A, Gerry NP, McQueen MB, Heid IM, Pfeufer A, Illig T, Wichmann HE, Meitinger T, Hunter D, Hu FB, Colditz G, Hinney A et al. A common genetic variant is associated with adult and childhood obesity. Science 2006;312:279-83.

Rioux JD, Xavier RJ, Taylor KD, Silverberg MS, Goyette P, Huett A, Green T, Kuballa P, Barmada MM, Datta LW, Shugart YY, Griffiths AM et al. Genome-wide association study identifies new susceptibility loci for Crohn disease and implicates autophagy in disease pathogenesis. Nat Genet 2007;39:596-604.

Saxena R, Voight BF, Lyssenko V, Burtt NP, de Bakker PI, Chen H, Roix JJ, Kathiresan S, Hirschhorn JN, Daly MJ, Hughes TE, Groop L et al. Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science 2007;316:1331-1336.

Todd JA, Walker NM, Cooper JD, Smyth DJ, Downes K, Plagnol V, Bailey R, Nejentsev S, Field SF, Payne F, Lowe CE, Szeszko JS et al. Robust associations of four new chromosome regions from genome-wide analyses of type 1 diabetes. Nat Genet 2007;39:857-864.

Zeggini E, Weedon MN, Lindgren CM, Frayling TM, Elliott KS, Lango H, Timpson NJ, Perry JR, Rayner NW, Freathy RM, Barrett JC, Shields B et al. Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. Science 2007;316:1336-1341.