Genome-wide association study of serum tumor markers in Southern Chinese Han population.

BACKGROUND: Serum indicators AFP, CA50, CA125, CA153, CA19-9, CEA, f-PSA, SCC-Ag have been confirmed as tumor markers (TMs). We conducted a genome-wide association study on 8 tumor markers of our 427 Han population in southern China, in order to identify genetic loci that are significantly associated with the level of 8 tumor markers. METHODS: We use Gene Titan multi-channel instrument and Axiom Analysis Suite 6.0 software for genotyping. We used IMPUTE2 software for imputation, and 1000 Genomes Project (Phase 3) was used as haplotype reference. After necessary quality control and statistical analysis, genetic loci genome-wide associated with TMs (p < 5E-8) will be identified. Finally, we selected Top SNPs (p < 5E-7) from the GWAS results for replication test. We used SPSS software to draw the distribution box plots of serum TMs under different genotypes of significant loci. RESULTS: The results showed that there were only MUC1 (mucin 1)-rs4072037 significantly genome-wide associated with CA153 (p = 1.28E-18). However, we found that a total of 30 genetic loci have a suggestively significant genome-wide association with the level of 8 serum tumor markers (p < 5E-6). Then 3 Top SNPs (p < 5E-7) were selected for replication verification. The results showed that MUC1-rs4072037 was still significantly associated with CA153 in another population (p = 3.73E-08). Comparing with the TT genotype of rs4072037, the CA153 level was higher under CC or CT genotype of rs4072037. CONCLUSION: MUC1-rs4072037 is significantly genome-wide associated with CA153 level. There are 30 genetic loci suggestively genome-wide associated with level of tumor markers among the Han population from Southern China.

Preliminary study of genome-wide association identified novel susceptibility genes for thyroid-related hormones in Chinese population.

BACKGROUND: Thyroid hormones are critical regulators of metabolism, development and growth in mammals. However, the genetic association of thyroid-related hormones in the Chinese Han population is not fully understood. OBJECTIVE: We aimed to identify the genetic loci associated with circulating thyroid-related hormones concentrations in the healthy Chinese Han population. METHODS: Genotyping was performed in 124 individuals using Applied Biosystems™ Axiom™ PMDA, and 796,288 single nucleotide polymorphisms (SNPs) were available for the GWAS analysis. For replication, eleven SNPs were selected as candidate loci for genotyping by Agena MassARRAY platform in additional samples (313 subjects). The values of p < 5 × 10- 6 suggest a suggestively significant genome-wide association with circulating thyroid-related hormones concentrations. RESULTS: We identified that rs11178277 (PTPRB, p = 4.88 × 10- 07) and rs7320337 (LMO7DN-KCTD12, p = 1.22 × 10- 06) were associated with serum FT3 level. Three SNPs (rs4850041 in LOC105373394-LINC01249: p = 3.55 × 10- 06, rs6867291 in LINC02208: p = 2.40 × 10- 06 and rs79508321 in WWOX: p = 3.35 × 10- 06) were related to circulating T3 level. Rs12474167 (LOC105373394-LINC01249, p = 1.65 × 10- 06) and rs1864553 (IWS1, p = 2.00 × 10- 06) were associated with circulating T4 concentration. The association with TGA concentration was for rs17163542 in DISP1 (p = 3.46 × 10- 06) and rs12601151 in NOG-C17orf67 (p = 2.72 × 10- 07). Two genome-level significant SNPs (rs2114707 in LINC01314, p = 1.69 × 10- 06 and rs12601151, p = 1.41 × 10- 07) associated with serum TMA concentration were identified. Moreover, rs6083269 (CST1-CST2, p = 3.36 × 10- 06) was a significant locus for circulating TSH level. In replication, rs12601151 in NOG-C17orf67 was still associated with serum TGA level (p = 0.012). CONCLUSIONS: The GWAS reported 11 new suggestively significant loci associated with circulating thyroid-related hormones levels among the Chinese Han population. These findings represented suggestively biological candidates for circulating thyroid-related hormones levels and provided new insights into the mechanisms of regulating serum TGA concentration.

Preliminary study of genome-wide association identifies novel susceptibility genes for serum mineral elements in the Chinese Han population.

Mineral elements (copper (Cu), zinc (Zn), calcium (Ca), magnesium (Mg), iron (Fe)) play important biological roles in enzymes, hormones, vitamins, and normal metabolism. The deficiency of mineral elements can lead to abnormal physiological functions. And some elements (such as lead (Pb)) are harmful to the body. We aim to identify genetic loci which can influence the serum levels of mineral elements (Cu, Zn, Ca, Mg, Fe, and Pb). Genotyping was performed using Applied Biosystems Axiom™ PMDA in 587 individuals, and 6,423,076 single-nucleotide polymorphisms (SNPs) were available for the genome-wide association study (GWAS) analysis. The association between genotype and phenotype was analyzed using mixed linear regression (additive genetic model) adjusting by age and gender combined with identical by descent (IBD) matrix. Genetic loci in BCHE-LOC105374194, DTX2P1-UPK3BP1-PMS2P11, VAT1L, LINC00908-LINC00683, LINC01310-NONE, and rs6747410 in VWA3B were identified to be associated with serum Cu element concentration (p < 5 × 10-6). ADAMTSL1 rs17229526 (p = 4.96 × 10-6) was significantly associated with serum Zn element levels. Genetic loci in LRP1B, PIGZ-MELTF, LINC01365-LINC02502, and HAPLN3 were related to serum Ca element levels (p < 5 ×1 0-6). Three SNPs in ALPK1, ASAP1-ADCY8 and IER3IP1-SKOR2 also achieved a significant association with Mg element levels (p < 5 × 10-6). TACSTD2-MYSM1, LRP1B, and ASAP1-ADCY8 showed suggestive associations with serum Fe element levels (p < 5 × 10-6). Moreover, the two most significant SNPs associated with Pb were rs304234 in CADPS-LINC00698 (p = 2.47 × 10-6) and rs12666460 in LOC101928211-GPR37 (p = 1.81 × 10-6). In summary, we reported 19 suggestive loci associated with serum mineral elements in the Chinese Han population. These findings provided new insights into the potential mechanisms regulating serum mineral elements levels.