Jae-Pil Jeon

Background: Pre-analytical conditions are key factors in maintaining the high quality of biospecimens. They are necessary for accurate reproducibility of experiments in the field of biomarker discovery as well as achieving optimal specificity of laboratory tests for clinical diagnosis. In research at the National Biobank of Korea, we evaluated the impact of pre-analytical conditions on the stability of biobanked blood samples by measuring biochemical analytes commonly used in clinical laboratory tests. Methods: We measured 10 routine laboratory analytes in serum and plasma samples from healthy donors ( n =50) with a chemistry autoanalyzer (Hitachi 7600-110). The analyte measurements were made at different time courses based on delay of blood fractionation, freezing delay of fractionated serum and plasma samples, and at different cycles (0, 1, 3, 6, 9) of freeze-thawing. Statistically significant changes from the reference sample mean were determined using the repeated-measures ANOVA and the significant change limit (SCL). Results: The serum levels of GGT and LDH were changed significantly depending on both the time interval between blood collection and fractionation and the time interval between fractionation and freezing of serum and plasma samples. The glucose level was most sensitive only to the elapsed time between blood collection and centrifugation for blood fractionation. Based on these findings, a simple formula (glucose decrease by 1.387 mg/dL per hour) was derived to estimate the length of time delay after blood collection. In addition, AST, BUN, GGT, and LDH showed sensitive responses to repeated freeze-thaw cycles of serum and plasma samples. Conclusion: These results suggest that GGT and LDH measurements can be used as quality control markers for certain pre-analytical conditions (eg, delayed processing or repeated freeze-thawing) of blood samples which are either directly used in the laboratory tests or stored for future research in the biobank.

Introduction: Although approximately 25 common genetic susceptibility loci have been identified to be independently associated with breast cancer risk through genome-wide association studies (GWAS), the genetic risk variants reported to date only explain a small fraction of the heritability of breast cancer. Furthermore, GWAS-identified loci were primarily identified in women of European descent. Methods: To evaluate previously identified loci in Korean women and to identify additional novel breast cancer susceptibility variants, we conducted a three-stage GWAS that included 6,322 cases and 5,897 controls. Results: In the validation study using Stage I of the 2,273 cases and 2,052 controls, seven GWAS-identified loci [5q11.2/MAP3K1 (rs889312 and rs16886165), 5p15.2/ROPN1L (rs1092913), 5q12/MRPS30 (rs7716600), 6q25.1/ESR1 (rs2046210 and rs3734802), 8q24.21 (rs1562430), 10q26.13/FGFR2 (rs10736303), and 16q12.1/TOX3 (rs4784227 and rs3803662)] were significantly associated with breast cancer risk in Korean women (P_trend < 0.05). To identify additional genetic risk variants, we selected the most promising 17 SNPs in Stage I and replicated these SNPs in 2,052 cases and 2,169 controls (Stage II). Four SNPs were further evaluated in 1,997 cases and 1,676 controls (Stage III). SNP rs13393577 at chromosome 2q34, located in the Epidermal Growth Factor Receptor 4 (ERBB4) gene, showed a consistent association with breast cancer risk with combined odds ratios (95% CI) of 1.53 (1.37-1.70) (combined P for trend = 8.8 × 10^-14). Conclusions: This study shows that seven breast cancer susceptibility loci, which were previously identified in European and/or Chinese populations, could be directly replicated in Korean women. Furthermore, this study provides strong evidence implicating rs13393577 at 2q34 as a new risk variant for breast cancer.

Bacterial contamination often occurs in human blood DNA samples, possibly due to bacteremia or an inappropriate procedure during sample preparation. This study aimed at analyzing the clinical significance of bacterial DNA contamination in human blood DNA samples and to assess its influence on experimental data. DNA samples (N = 1359) were randomly selected from population-based cohort samples to determine bacterial DNA contamination by polymerase chain reaction and direct DNA sequencing. Bacterial DNA contaminated samples (N = 150) were then assessed for experimental quality of single nucleotide polymorphism (SNP) chip data, compared with uncontaminated DNA samples (N = 1209). DNA sequencing data showed that a major source of bacterial contaminants was derived from Alcaligenes species. The occurrence of bacterial DNA contaminations was significantly associated with some clinical variables including a postprandial glucose level at 60 min, % body fat, and waist-to-hip ratio. It was also found that there was no difference of SNP call rates between bacterial DNA contaminated samples and uncontaminated DNA samples. This study showed that bacterial DNA contamination in human blood samples was related to donor's health condition, suggesting that the occurrence of bacterial DNA contamination may provide useful health information of blood donors and a potential tool for human disease genomics.