Quantification method of ctDNA using cell-free DNA methylation profile for noninvasive screening and monitoring of colon cancer.

BACKGROUND: Colon cancer ranks as the second most lethal form of cancer globally. In recent years, there has been active investigation into using the methylation profile of circulating tumor DNA (ctDNA), derived from blood, as a promising indicator for diagnosing and monitoring colon cancer. RESULTS: We propose a liquid biopsy-based epigenetic method developed by utilizing 49 patients and 260 healthy controls methylation profile data to screen and monitor colon cancer. Our method initially identified 901 colon cancer-specific hypermethylated (CaSH) regions in the tissues of the 49 cancer patients. We then used these CaSH regions to accurately quantify the amount of circulating tumor DNA (ctDNA) in the blood samples of these same patients, utilizing cell-free DNA methylation profiles. Notably, the methylation profiles of ctDNA in the blood exhibited high sensitivity (82%) and specificity (93%) in distinguishing patients with colon cancer from the control group, with an area under the curve of 0.903. Furthermore, we confirm that our method for ctDNA quantification is effective for monitoring cancer patients and can serve as a valuable tool for postoperative prognosis. CONCLUSIONS: This study demonstrated a successful application of the quantification of ctDNA among cfDNA using the original cancer tissue-derived CaSH region for screening and monitoring colon cancer.

Korea4K: whole genome sequences of 4,157 Koreans with 107 phenotypes derived from extensive health check-ups.

BACKGROUND: Phenome-wide association studies (PheWASs) have been conducted on Asian populations, including Koreans, but many were based on chip or exome genotyping data. Such studies have limitations regarding whole genome-wide association analysis, making it crucial to have genome-to-phenome association information with the largest possible whole genome and matched phenome data to conduct further population-genome studies and develop health care services based on population genomics. RESULTS: Here, we present 4,157 whole genome sequences (Korea4K) coupled with 107 health check-up parameters as the largest genomic resource of the Korean Genome Project. It encompasses most of the variants with allele frequency >0.001 in Koreans, indicating that it sufficiently covered most of the common and rare genetic variants with commonly measured phenotypes for Koreans. Korea4K provides 45,537,252 variants, and half of them were not present in Korea1K (1,094 samples). We also identified 1,356 new genotype-phenotype associations that were not found by the Korea1K dataset. Phenomics analyses further revealed 24 significant genetic correlations, 14 pleiotropic associations, and 127 causal relationships based on Mendelian randomization among 37 traits. In addition, the Korea4K imputation reference panel, the largest Korean variants reference to date, showed a superior imputation performance to Korea1K across all allele frequency categories. CONCLUSIONS: Collectively, Korea4K provides not only the largest Korean genome data but also corresponding health check-up parameters and novel genome-phenome associations. The large-scale pathological whole genome-wide omics data will become a powerful set for genome-phenome level association studies to discover causal markers for the prediction and diagnosis of health conditions in future studies.

Identification and validation of six acute myocardial infarction-associated variants, including a novel prognostic marker for cardiac mortality.

Background: Acute myocardial infarction (AMI) is one of the leading causes of death worldwide, and approximately half of AMI-related deaths occur before the affected individual reaches the hospital. The present study aimed to identify and validate genetic variants associated with AMI and their role as prognostic markers. Materials and methods: We conducted a replication study of 29 previously identified novel loci containing 85 genetic variants associated with early-onset AMI using a new independent set of 2,920 Koreans [88 patients with early- and 1,085 patients with late-onset AMI, who underwent percutaneous coronary intervention (PCI), and 1,747 healthy controls]. Results: Of the 85 previously reported early-onset variants, six were confirmed in our genome-wide association study with a false discovery rate of less than 0.05. Notably, rs12639023, a cis-eQTL located in the intergenic region between LINC02005 and CNTN3, significantly increased longitudinal cardiac mortality and recurrent AMI. CNTN3 is known to play a role in altering vascular permeability. Another variant, rs78631167, located upstream of PLAUR and known to function in fibrinolysis, was moderately replicated in this study. By surveying the nearby genomic region around rs78631167, we identified a significant novel locus (rs8109584) located 13 bp downstream of rs78631167. The present study showed that six of the early-onset variants of AMI are applicable to both early- and late-onset cases. Conclusion: Our results confirm markers that can potentially be utilized to predict, screen, prevent, and treat candidate patients with AMI and highlight the potential of rs12639023 as a prognostic marker for cardiac mortality in AMI.

Genome-wide analyses of early-onset acute myocardial infarction identify 29 novel loci by whole genome sequencing.

Early-onset acute myocardial infarction (AMI) may have a higher genetic predisposition than late-onset AMI. The present study aimed to identify and characterize germline variants that affect early-onset AMI using whole-genome sequencing (WGS). We performed a genome-wide association study based on the WGS of 1239 Koreans, including 596 early-onset AMI patients and 643 healthy individuals. Patients with AMI who underwent percutaneous coronary intervention (PCI) caused by atherothrombotic occlusive lesions were included in the study. A total of 29 novel loci were found to be associated with early-onset AMI. These loci are involved in thrombosis, fibrinolysis, inflammation, and lipid metabolism. One of the associated single nucleotide variants (SNVs), rs1614576, located upstream of PRKCB, is known to be associated with thrombus formation. Additionally, the results revealed a novel locus, rs78631167, located upstream of PLAUR which plays a critical role in regulating plasminogen activation and is related to fibrinolysis. The association between early-onset AMI and rs9357455, which is located upstream of PHACTR1 and regulates inflammation in AMI, was found. Moreover, we identified a lipid metabolism related genetic risk locus, rs5072, in the APOA1-AS gene. This study provides new evidence supporting the genetic association between early-onset AMI and thrombosis and fibrinolysis, as well as inflammation and lipid metabolism, by analyzing the whole-genome of 596 patients with early-onset AMI who have been treated with PCI. Our findings highlight potential genetic markers for the prediction and management of AMI, as well as for understanding the etiology of AMI.

Polygenic risk score validation using Korean genomes of 265 early-onset acute myocardial infarction patients and 636 healthy controls.

BACKGROUND: The polygenic risk score (PRS) developed for coronary artery disease (CAD) is known to be effective for classifying patients with CAD and predicting subsequent events. However, the PRS was developed mainly based on the analysis of Caucasian genomes and has not been validated for East Asians. We aimed to evaluate the PRS in the genomes of Korean early-onset AMI patients (n = 265, age ≤50 years) following PCI and controls (n = 636) to examine whether the PRS improves risk prediction beyond conventional risk factors. RESULTS: The odds ratio of the PRS was 1.83 (95% confidence interval [CI]: 1.69-1.99) for early-onset AMI patients compared with the controls. For the classification of patients, the area under the curve (AUC) for the combined model with the six conventional risk factors (diabetes mellitus, family history of CAD, hypertension, body mass index, hypercholesterolemia, and current smoking) and PRS was 0.92 (95% CI: 0.90-0.94) while that for the six conventional risk factors was 0.91 (95% CI: 0.85-0.93). Although the AUC for PRS alone was 0.65 (95% CI: 0.61-0.69), adding the PRS to the six conventional risk factors significantly improved the accuracy of the prediction model (P = 0.015). Patients with the upper 50% of PRS showed a higher frequency of repeat revascularization (hazard ratio = 2.19, 95% CI: 1.47-3.26) than the others. CONCLUSIONS: The PRS using 265 early-onset AMI genomes showed improvement in the identification of patients in the Korean population and showed potential for genomic screening in early life to complement conventional risk prediction.