We conducted a genome-wide linkage scan and positional association study to identify genes and variants influencing blood lipid levels among participants of the Genetic Epidemiology Network of Salt-Sensitivity (GenSalt) study. The GenSalt study was conducted among 1906 participants from 633 Han Chinese families. Lipids were measured from overnight fasting blood samples using standard methods. Multipoint quantitative trait genome-wide linkage scans were performed on the high-density lipoprotein, low-density lipoprotein, and log-transformed triglyceride phenotypes. Using dense panels of single nucleotide polymorphisms (SNPs), single-marker and gene-based association analyses were conducted to follow-up on promising linkage signals. Additive associations between each SNP and lipid phenotypes were tested using mixed linear regression models. Gene-based analyses were performed by combining P-values from single-marker analyses within each gene using the truncated product method (TPM). Significant associations were assessed for replication among 777 Asian participants of the Multi-ethnic Study of Atherosclerosis (MESA). Bonferroni correction was used to adjust for multiple testing. In the GenSalt study, suggestive linkage signals were identified at 2p11.2-2q12.1 [maximum multipoint LOD score (MML)=2.18 at 2q11.2] and 11q24.3-11q25 (MML=2.29 at 11q25) for the log-transformed triglyceride phenotype. Follow-up analyses of these two regions revealed gene-based associations of charged multivesicular body protein 3 (CHMP3), ring finger protein 103 (RNF103), AF4/FMR2 family, member 3 (AFF3), and neurotrimin (NTM) with triglycerides (P=4×10-4, 1.00×10-5,2.00× 10-5, and 1.00×10-7, respectively). Both the AFF3 and NTM triglyceride associations were replicated among MESA study participants (P=1.00×10-7 and 8.00×10-5, respectively). Furthermore, NTM explained the linkage signal on chromosome 11. In conclusion, we identified novel genes associated with lipid phenotypes in linkage regions on chromosomes 2 and 11.
- Gene-based analysis
- Linkage analysis
- Positional association analysis