Figure 1. Ordered subset analysis (OSA) using age-of-onset in GENECARD, chromosome 7. We constructed a CAD linkage map using the GENECARD microsatellite genome screen on chromosome 7. Results are depicted for all 420 families (grey), and for the subset generated by OSA (black), demonstrating increased LOD at the peak microsatellite from 1.04 (420 families) to 4.22 (97 lowest age-of-onset families, mean 37.8 years), p = 0.004 for increase in LOD. doi:10.1371/journal.pgen.1000318.g001 NPY Variants Are Associated with Early-Onset CAD Twenty-four SNPs were genotyped and were in Hardy- Weinberg equilibrium. Rs5571 was monomorphic and not analyzed further. Consistent with microsatellite results, nine NPY SNPs had LOD.1.0 in GENECARD, with higher LODs for several SNPs in the subset of 97 very-young-age-of-onset OSA families. Six of these linked SNPs also showed family-based association with CAD by PDT in GENECARD (Table 2). These SNPs are in varying degrees of LD (Figure 2). Association with CAD was validated in the non-familial dataset CATHGEN for five SNPs within the 6-SNP block; the sixth SNP (rs16147) demonstrated borderline significance (Table 3). CATHGEN results also validated our GENECARD findings for age-of-onset effects, with stronger association in the youngest age-of-onset CAD cases (,38 years of age, threshold defined by the GENECARD OSA subset). Although the CATHGEN sample size decreased using this age-of-onset threshold, SNPs within the 6-SNP block remained significantly associated to CAD (Table 3), with odds ratios higher than those obtained with the full dataset, and with several SNPs showing greater significance than the overall cohort (e.g., rs16119, allelic OR 2.20, p = 0.0004). These very-young-age- of-onset cases had a higher prevalence of family history of CAD (p = 0.003) and a trend for higher prevalence of dyslipidemia (p = 0.07). All six key NPY SNPs were also associated with early-onset CAD in the comparison of GENECARD probands with CATHGEN controls (Table 4). Although we had adjusted for race in our regression models, to further address the potential for population stratification we performed analyses stratified by race. In these analyses, the association between NPY SNPs and early-onset CAD remained consistent and often more significant in self-reported Caucasians (Table S1), suggesting that the results are not confounded by population stratification from race. However, there was no association between NPY SNPs and CAD in non- Caucasians, most likely due to the lower power to detect such a Neuropeptide Y and Early-Onset Atherosclerosis difference given the small sample size (N = 162 CATHGEN non- Caucasian CAD cases, 72 non-Caucasian controls). Haplotype analysis in the CATHGEN dataset showed association of several two-SNP haplotypes with CAD, recapitulating the LD structure of the individual SNPs, but not providing additional information. The haplotype most strongly associated was composed of rs5574 and rs16474 (p = 0.005). Because rs16147 is a promoter SNP with established effects on expression of the gene [23–25], and all other key NPY SNPs are in LD with rs16147, we will focus the remainder of our results primarily on rs16147. However, as expected, findings were consistent across all six SNPs. As with the other five SNPs, there was consistency of the CAD-associated allele for rs16147 (G allele) and of its allele frequency across all datasets (CATHGEN cases 0.49; very-young CATHGEN cases 0.55; GENECARD probands 0.55; CATHGEN controls 0.43) (Table S2). To test the possibility that associations between NPY SNPs with CAD are mediated through traditional CAD risk factors, we performed multivariable regression in our case-control datasets, using hypertension, dyslipidemia, diabetes, BMI, and smoking as covariates with NPY SNP genotype. In this analysis, the association of rs16147 with CAD remained significant in our comparison of GENECARD probands with CATHGEN controls (genotype OR 1.60 [95% CI 1.11–2.31], p = 0.01; allele OR 2.00 [1.11–3.59], p = 0.03), suggesting that NPY genotype contributes to CAD risk independently of traditional risk factors, at least in family-based cohorts. In the CATHGEN cohort, however, adjusting for risk factors attenuated association for rs16147 (genotype OR 1.15 [0.87–1.51], p = 0.34; allele OR 1.24 [0.82–1.88], p = 0.32), but left the association of rs16120 with CAD intact (allele model, OR 1.54 [1.01–2.35], p = 0.04). Race-stratified analyses in Caucasians also showed attenuation of association between NPY SNPs and early-onset CAD, although three of the SNPs remained signifi- cantly associated (Table S1). To understand which CAD risk factor(s) most mediate association of NPY genotype with CAD, we performed a forward stepwise logistic regression, first fitting a model with genotype and then adding each risk factor. The greatest attenuation of association was caused by dyslipidemia, with minimal additional attenuation by other variables. Table S3 lists risk factors significant in the multivariable model for the SNP remaining significant after adjustment (rs16120), demonstrating the independent strength of effect of genotype, as well as those for intermediate risk factors, in a full fitted model. Neither BMI nor cholesterol levels varied significantly by NPY genotype (data not shown). Thus, it appears that NPY SNPs may contribute to atherosclerosis risk either independently of traditional risk factors, especially in high-risk families, or via mechanisms that may relate to dyslipidemia in non-familial CAD. NPY Risk Alleles Are Associated with a Younger Age-of- Onset An alternate way to examine the relationship between quantitative covariates and genetic variants is comparing means of traits by genotype (measured genotype analysis). We performed this analysis in CATHGEN to elucidate further the influence of NPY variants on age-of-onset. We found that the risk allele for rs16147 is indeed associated with a younger age-of-onset (mean age-of-onset: 45.8 (SD 6.5) in subjects with 1 or 2 copies of risk allele versus 47.3 (5.9) in subjects with 0 copies, p = 0.03). These results support our GENECARD findings and suggest NPY may affect the course of atherogenesis such that atherosclerosis manifests earlier in life. PLoS Genetics | www.plosgenetics.org 3 January 2009 | Volume 5 | Issue 1 | e1000318