Using ethnic variation to nominate better candidate markers.

<p>Black triangles represent a SNP which exhibited significant association with risk in one population and non-significant association in a different ethnic group. Gray triangles are SNPs that are tightly linked to this marker in the population with a significant association but more loosely linked in the non-significant population. White triangles are SNPs very close to this new candidate region with a measured association with outcome. The OR’s shown below the black marker are from this study, those under the gray and white markers from the referenced studies. Significant results are marked with asterisks. A) rs1137101 failed to validate in a European breast cancer population, however the nearby rs3828034 has a higher OR that nears significance <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097522#pone.0097522-Hunter1" target="_blank">[46]</a>. B) rs6983267 failed to replicate in studies of European (US) populations, however the nearby rs7837328 has a more consistent association <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097522#pone.0097522-Kupfer1" target="_blank">[47]</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097522#pone.0097522-Berndt1" target="_blank">[49]</a>. The odds ratio for rs6983267 as reported in this study (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097522#pone.0097522.s005" target="_blank">Table S2</a>) is based on the ancestral allele, which is also the rare allele in European populations, the odds ratio for the nearby SNPs were reported in relation to the most common allele, therefore for consistency we have also given the OR for rs6983267 in this figure in relation to the common allele.</p

Ethnic Background and Genetic Variation in the Evaluation of Cancer Risk: A Systematic Review

<div><p>The clinical use of genetic variation in the evaluation of cancer risk is expanding, and thus understanding how determinants of cancer susceptibility identified in one population can be applied to another is of growing importance. However there is considerable debate on the relevance of ethnic background in clinical genetics, reflecting both the significance and complexity of genetic heritage. We address this via a systematic review of reported associations with cancer risk for 82 markers in 68 studies across six different cancer types, comparing association results between ethnic groups and examining linkage disequilibrium between risk alleles and nearby genetic loci. We find that the relevance of ethnic background depends on the question. If asked whether the association of variants with disease risk is conserved across ethnic boundaries, we find that the answer is yes, the majority of markers show insignificant variability in association with cancer risk across ethnic groups. However if the question is whether a significant association between a variant and cancer risk is likely to reproduce, the answer is no, most markers do not validate in an ethnic group other than the discovery cohort’s ancestry. This lack of reproducibility is not attributable to studies being inadequately populated due to low allele frequency in other ethnic groups. Instead, differences in local genomic structure between ethnic groups are associated with the strength of association with cancer risk and therefore confound interpretation of the implied physiologic association tracked by the disease allele. This suggest that a biological association for cancer risk alleles may be broadly consistent across ethnic boundaries, but reproduction of a clinical study in another ethnic group is uncommon, in part due to confounding genomic architecture. As clinical studies are increasingly performed globally this has important implications for how cancer risk stratifiers should be studied and employed.</p></div

Forest plot of odds ratios.

<p>The results within liver, gastric, lung and prostate cancer are shown. OR’s from European populations are shown in black, Asian in red, African in green, and other groups in blue. Though considerably heterogeneity is apparent, the association with risk for a marker in one ethnic group appears to predict the direction of the association in the other ethnic groups, as supported by the test for heterogeneity. Similar plots for breast and colon cancer are given in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097522#pone.0097522.s001" target="_blank">Figure S1</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097522#pone.0097522.s002" target="_blank">S2</a>, respectively.</p

Relationship between linkage disequilibrium and cancer susceptibility.

<p>Agreement between odds ratios was compared with a z test of the difference; z = δOR/SE (δOR). LD agreement was assessed with a one-way permutation test based on Monte-Carlo resampling on the r² values between the relevant SNP and all available SNPs within 50 kb on either side of the loci. Two sided P values are shown.</p

Concordance of association with cancer susceptibility.

<p>All pairwise comparisons between ethnic groups for each SNP are shown. A reference population was chosen for each SNP as the ethnic group with the largest population giving a significant result, when no significance was found the largest population was used. s, reported association with risk was significant; ns, not significant; na, not applicable; nd, not determined. *Reference population and validation population do not agree on directionality of association.</p

Search strategy and study design A) Literature search strategy.

<p>B) Associations between markers and cancer risk were compared between ethnic groups. Among the 86 SNPs assessed in this study, 123 pairwise comparisons of association results between ethnic groups were made. The association results were assessed to determine if each ethnic group was sufficiently populated to find significant results found in other groups. Where differences were found between groups, linkage disequilibrium analysis was performed. The Breslow-Day test for heterogeneity with Tarone’s adjustment was used on all studies with sufficient data. *Both groups had significant results, but with opposite signs.</p

Heterogeneity of OR among ethnic groups.

<p>Tarone’s Test for was used to assess heterogeneity of the odds ratios between ethnic groups. The fraction of SNP’s showing significant variability is tabulated.</p

<em>ABCB1</em> Variation and Treatment Response in AIDS Patients: Initial Results of the Henan Cohort

<div><p>HIV/AIDS has the highest mortality among infectious diseases in China. In ongoing efforts to alleviate this crisis, the national government has placed great emphasis on efforts in Henan province where HIV-infected former plasma donors in the 1990s contributed to AIDS becoming a public health crisis. Concomitant with a national initiative focusing the use of phamacogenetics for the better prediction of treatment response, we studied genetic variants with known pharmacokinetic phenotypes in a set of 298 HAART-treated (highly active antiretroviral therapy) patients infected with HIV from the Henan cohort. We measured the association of response to treatment, assessed as changes in CD4+ T cell counts after antiretroviral therapy, of five polymorphisms in four genes (<em>CYP2B6</em>, <em>ABCB1</em>/<em>MDR1</em>, <em>ABCG2,</em> and <em>ABCC4</em>) in which variation has been suggested to affect the pharmacokinetics of drugs commonly employed to treat HIV/AIDS. We show that genotyping for <em>ABCB1</em> variations (rs1045642 and rs2032582) may help predict HIV treatment response. We found variations in this gene have a significant association with outcome as measured by CD4+ T cell counts in a discovery subset (N = 197; odds ratio (OR) = 1.58; 95% CI 1.02–2.45), these results were confirmed in a validation subset of the cohort (N = 78; OR = 2.81; 95% CI 1.32–5.96). Exploratory analysis suggests that this effect may be specific to NVP (nevirapine) or 3TC (lamivudine) response. This publication represents the first genetic analysis in a continuing effort to study and assist the patients in a very large, unique, and historically significant HIV-AIDS cohort. Genotyping of AIDS patients for <em>ABCB1</em> variation may help predict outcome and potentially could help guide treatment strategies.</p> </div

Flow chart of study participant selection.

<p>Flow chart of study participant selection.</p

Association analysis of SNPs and therapeutic response.

<p><i>ABCB1*: ABCB1</i> 3435T>C + <i>ABCB1</i> 2677T>G.</p