Statistical Analysis for Haplotype-Based Matched Case-Control Studies

Single Nucleotide Polymorphisms in Osteogenic Genes in Atrophic Delayed Fracture-Healing: A Preliminary Investigation

UpdateThis article was updated on September 10, 2014, because of a previous error. On page 1242, in the byline, and on page 1247, in the author addresses, the academic degree for Henry J. Donahue had previously read "MD." The degree now reads "PhD."

BACKGROUND

We propose that fracture-healing potential is affected by the patient's genome. This genotype is then phenotypically expressed by the patient at the time of injury. We examined the hypothesis that patients who exhibit delayed or impaired fracture-healing may have one or more single nucleotide polymorphisms (SNPs) within a series of genes related to bone formation.

METHODS

We performed a population-based, case-controlled study of delayed fracture-healing. Sixty-two adults with a long-bone fracture were identified from a surgical database. Thirty-three patients had an atrophic nonunion (delayed healing), and twenty-nine displayed normal fracture-healing. These patients underwent buccal mucosal cell harvesting. SNP genotyping was performed with use of bead array technology. One hundred and forty-four SNPs (selected from HapMap) within thirty genes associated with fracture-healing were investigated. Three SNPs did not segregate in the population and were excluded from the analysis. Eight of the remaining SNPs failed the test for Hardy-Weinberg equilibrium (p value smaller than the Bonferroni-corrected level of 0.05/141 = 0.000355) and were excluded.

RESULTS

Five SNPs on four genes were found to have a p value of <0.05 in the additive genetic model. Of these five significant SNPs, three had an odds ratio (OR) of >1, indicating that the presence of the allele increased the risk of nonunion. The rs2853550 SNP, which had the largest effect (OR = 5.9, p = 0.034), was on the IL1B gene, which codes for interleukin 1 beta. The rs2297514 SNP (OR = 3.98, p = 0.015) and the rs2248814 SNP (OR = 2.27, p = 0.038) were on the NOS2 gene coding for nitric oxide synthase. The remaining two SNPs had an OR of <1, indicating that the presence of the allele may be protective against nonunion. The rs3819089 SNP (OR = 0.26, p = 0.026) was on the MMP13 gene for matrix metallopeptidase 13, and the rs270393 SNP (OR = 0.30, p = 0.015) was on the BMP6 gene for bone morphogenetic protein 6.

CONCLUSIONS

Variations in the IL1B and NOS2 genes may contribute to delayed fracture-healing and warrant further investigation.

CLINICAL RELEVANCE

Impaired fracture union may have genetic contributions.

Inference of the haplotype effect in a matched case-control study using unphased genotype data

Typically locus specific genotype data do not contain information regarding the gametic phase of haplotypes, especially when an individual is heterozygous at more than one locus among a large number of linked polymorphic loci. Thus, studying disease-haplotype association using unphased genotype data is essentially a problem of handling a missing covariate in a case-control design. There are several methods for estimating a disease-haplotype association parameter in a matched case-control study. Here we propose a conditional likelihood approach for inference regarding the disease-haplotype association using unphased genotype data arising from a matched case-control study design. The proposed method relies on a logistic disease risk model and a Hardy-Weinberg equilibrium (HWE) among the control population only. We develop an expectation and conditional maximization (ECM) algorithm for jointly estimating the haplotype frequency and the disease-haplotype association parameter(s). We apply the proposed method to analyze the data from the Alpha-Tocopherol, Beta-Carotene Cancer prevention study, and a matched case-control study of breast cancer patients conducted in Israel. The performance of the proposed method is evaluated via simulation studies.

Statistical methods for haplotype-based matched case-control association studies

Kraft et al. [2005] proposed a method for matched haplotype-based association studies and compared the performances of six analytic strategies for estimating the odds ratio parameters using a conditional likelihood function. Zhang et al. [2006] modified the conditional likelihood and proposed a new method for matched haplotype-based association studies. The main assumptions of Zhang et al. were that the disease was rare, the population was in Hardy-Weinberg equilibrium (HWE), and the haplotypes were independent of the covariates and matching variable(s). In this article, we modify the estimation procedure proposed by Zhang et al. and introduce a fixation index so that the assumption of HWE is relaxed. Using the Wald test, we compare the current modified method with the procedure developed by Kraft et al. through simulations. The results show that the modified method is uniformly more powerful than that described in Kraft et al. Furthermore, the results indicate that the modified method is quite robust to the rare disease assumption.