Biology subjects

Hwang, S.-J.

Publications and source records attributed to Hwang, S.-J..

8 recordsLinked to original sources

bioRxiv2021

Genetically independent phenotype analysis identifies LPA and VCAM1 as drug targets for human ageing

The length and quality of life is important to us all, yet identification of promising drug targets for human ageing using genetics has had limited success. Here, we combine six large European-ancestry genome-wide association studies (GWAS) of human ageing traits--healthspan, father and mother lifespan, exceptional longevity, frailty index, and self-rated health--in a principal component framework that maximises their shared genetic architecture. The first principal component (GIP1) is more heritable than the original studies and shows strong genetic correlations with length of life as well as multiple indices of mental and physical wellbeing. We identify 27 genomic regions associated with GIP1, and provide additional, independent evidence for an effect on human ageing for loci near HTT and MAML3 using a study of Finnish and Japanese subject survival. Across the genome, GIP1 associations are enriched in genes involved in haem metabolism and pathways related to transcription, neurogenesis, homeostasis, proteolysis, intracellular signalling, immunity, and the muscle system. Finally, using proteome-wide two-sample Mendelian randomisation and colocalisation, we provide robust evidence for a detrimental effect of blood levels of apolipoprotein(a) (LPA) and vascular cell adhesion molecule 1 (VCAM1) on GIP1. Together, our results demonstrate that combining multiple ageing traits using genetic principal components enhances power to detect biological targets for human ageing.

genomics↗

bioRxiv2020

Cardiovascular Disease Related Proteomic Biomarkers of Alcohol Consumption

The relationship between alcohol consumption, circulating proteins, and cardiovascular disease (CVD) risk has not been well studied. We performed association analyses of alcohol consumption with three CVD risk factors and 71 CVD-related circulating proteins measured in 6,745 Framingham Heart Study participants (mean age, 49 years; 53% women). We found that an increase in alcohol consumption was associated with a higher risk of incident hypertension (P=7.2E-3) but a lower risk of incident obesity (P=5.7E-4) and type 2 diabetes (P=1.4E-5) in a 14-year of follow-up. Using independent discovery (n=4,348) and validation (n=2,397) samples, we identified 20 alcohol-associated proteins (FDR<0.05 in discovery and P<0.05/n in validation), with majority (18 of 20 proteins) inversely associated with alcohol consumption. The alcohol-protein associations remained similar after removing heavy drinkers. Four proteins demonstrated consistent triangular relationships, as expected, with alcohol consumption and CVD risk factors. For example, a greater level of APOA1, which was associated with a higher alcohol consumption (P=1.2E-65), was associated with a lower risk of type 2 diabetes (P=3.1E-5). However, several others showed inconsistent triangular relationships, e.g., a greater level of GDF15, which was associated with a lower alcohol consumption (P=1.0E-13), was associated with an increased risk of hypertension (P=2.4E-4). In conclusion, we identified 20 alcohol-associated proteins and demonstrated complex relationships between alcohol consumption, circulating proteins and CVD risk factors. Future studies with integration of more proteomic markers and larger sample size are warranted to unravel the complex relationship between alcohol consumption and CVD risk.

bioinformatics↗

bioRxiv2020

Genetic loci associated with prevalent and incident myocardial infarction and coronary heart disease in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium

BackgroundGenome-wide association studies have identified multiple genomic loci associated with coronary artery disease, but most are common variants in non-coding regions that provide limited information on causal genes and etiology of the disease. To better understand etiological pathways that might lead to discovery of new treatments or prevention strategies, we focused our investigation on low-frequency and rare sequence variations primarily residing in coding regions of the genome while also exploring associations with common variants. Methods and ResultsUsing samples of individuals of European ancestry from ten cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, both cross-sectional and prospective analyses were conducted to examine associations between genetic variants and myocardial infarction (MI), coronary heart disease (CHD), and all-cause mortality following these events. Single variant and gene-based analyses were performed separately in each cohort and then meta-analyzed for each outcome. A low-frequency intronic variant (rs988583) in PLCL1 was significantly associated with prevalent MI (OR=1.80, 95% confidence interval: 1.43, 2.27; P=7.12 x 10-7). Three common variants, rs9349379 in PHACTR1, and rs1333048 and rs4977574 in the 9p21 region, were significantly associated with prevalent CHD. Four common variants (rs4977574, rs10757278, rs1333049, and rs1333048) within the 9p21 locus were significantly associated with incident MI. We conducted gene-based burden tests for genes with a cumulative minor allele count (cMAC) [≥] 5 and variants with minor allele frequency (MAF) < 5%. TMPRSS5 and LDLRAD1 were significantly associated with prevalent MI and CHD, respectively, and RC3H2 and ANGPTL4 were significantly associated with incident MI and CHD, respectively. No loci were significantly associated with all-cause mortality following a MI or CHD event. ConclusionThis study confirmed previously reported loci influencing heart disease risk, and one single variant and three genes associated with MI and CHD were newly identified and warrant future investigation.

genetics↗

bioRxiv2019

Integrative Genomic Analysis and Functional Studies Reveal GP5, GRN, MPO and MCAM as Causal Protein Biomarkers for Platelet Traits

RationaleMean platelet volume (MPV) and platelet count (PLT) are platelet measures that have been linked to cardiovascular disease (CVD) and mortality risk. Identifying protein biomarkers for these measures may yield insights into CVD mechanisms. ObjectiveWe aimed to identify causal protein biomarkers for MPV and PLT among 71 CVD-related plasma proteins measured in Framingham Heart Study (FHS) participants. Methods and ResultsWe conducted integrative analyses of genetic variants associated with PLT and MPV with protein quantitative trait locus (pQTL) variants associated with plasma proteins followed by Mendelian randomization (MR) to infer causal relations of proteins for PLT/MPV, and tested protein-PLT/MPV association in FHS participants. Utilizing induced pluripotent stem cell (iPSC)-derived megakaryocyte (MK) clones that produce functional platelets, we conducted RNA-sequencing and analyzed transcriptome-wide differences between low- and high-platelet producing clones. We then performed small interfering RNA (siRNA) gene knockdown experiments targeting genes encoding proteins with putatively causal platelet effects in MK clones to examine effects on platelet production. Protein-trait association analyses were conducted for MPV (n = 4,348) and PLT (n = 4,272). Eleven proteins were associated with MPV and 31 with PLT. MR identified four putatively causal proteins for MPV and four for PLT. Glycoprotein V (GP5), granulin (GRN), and melanoma cell adhesion molecule (MCAM) were associated with PLT in both protein-trait and MR analyses. Myeloperoxidase (MPO) showed significant association with MPV in both analyses. MK RNA-sequencing analysis results were directionally concordant with observed and MR-inferred associations for GP5, GRN, and MCAM. In siRNA gene knockdown experiments, silencing GP5, GRN, and MPO decreased platelet counts. ConclusionsBy integrating population genomics data, epidemiological data, and iPSC-derived MK experiments, we identified four proteins that are causally linked to platelet counts. These proteins and genes may be further explored for their utility in increasing platelet production in bioreactors for transfusion medicine purposes as well as their roles in the pathogenesis of CVD via a platelet/blood coagulation-based mechanism.

genomics↗

bioRxiv2018

The draft genome of an octocoral, Dendronephthya gigantea

BackgroundCoral reefs composed of stony corals are threatened by global marine environmental changes. However, soft coral communities composed of octocorallian species, appear more resilient. The genomes of several species of cnidarians have been published, including stony corals, sea anemones, and hydra, but as of yet no octocoral species. To fill this phylogenetic gap within the cnidarian, we sequenced the octocoral, Dendronephthya gigantea, a non-symbiotic soft coral, commonly known as the carnation coral.\n\nFindingsThe D. gigantea genome size is approximately 276 Mb. A high-quality genome assembly was constructed using 29.85Gb (108x coverage) of PacBio long reads and 35.54Gb (128x coverage) of Illumina short paired-end reads resulting in the largest N50 value reported among cnidarian of 1.4 Mb. About 12 % of the genome consisted of repetitive elements. We found 28,879 protein-coding genes. This gene set contained about 94% metazoan single-copy orthologs, indicating the gene models were predicted with high quality compared to other cnidarians. Based on molecular phylogenetic analysis, octocoral and hexacoral divergence occurred approximately 544 million years ago. Moreover, there is a clear difference in Hox gene composition: unlike in hexacorals, Antp superclass member Evx gene was absent in D. gigantea.\n\nConclusionsWe present the first genome assembly of a non-symbiotic octocoral, D. gigantea to aid in the comparative genomic analysis of cnidarians, including comparisons of stony and soft corals and symbiotic and non-symbiotic corals. In addition, the genome of this species may provide clues about differential genetic coping mechanisms between soft and stony coral regarding the global warming.

genomics↗

bioRxiv2018

Novel DNA methylation sites of glucose and insulin homeostasis: an integrative cross-omics analysis

Despite existing reports on differential DNA methylation in type 2 diabetes (T2D) and obesity, our understanding of the functional relevance of the phenomenon remains limited. Because obesity is the main risk factor for T2D and a driver of methylation from previous study, we aimed to explore the effect of DNA methylation in the early phases of T2D pathology while accounting for body mass index (BMI). We performed a blood-based epigenome-wide association study (EWAS) of fasting glucose and insulin among 4,808 non-diabetic European individuals and replicated the findings in an independent sample consisting of 11,750 non-diabetic subjects. We integrated blood-based in silico cross-omics databases comprising genomics, epigenomics and transcriptomics collected by BIOS project of the Biobanking and BioMolecular resources Research Infrastructure of the Netherlands (BBMRI-NL), the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC), the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) consortium, and the tissue-specific Genotype-Tissue Expression (GTEx) project. We identified and replicated nine novel differentially methylated sites in whole blood (P-value < 1.27 x 10-7): sites in LETM1, RBM20, IRS2, MAN2A2 genes and 1q25.3 region were associated with fasting insulin; sites in FCRL6, SLAMF1, APOBEC3H genes and 15q26.1 region were associated with fasting glucose. The association between SLAMF1, APOBEC3H and 15q26.1 methylation sites and glucose emerged only when accounted for BMI. Follow-up in silico cross-omics analyses indicate that the cis-acting meQTLs near SLAMF1 and SLAMF1 expression are involved in glucose level regulation. Moreover, our data suggest that differential methylation in FCRL6 may affect glucose level and the risk of T2D by regulating FCLR6 expression in the liver. In conclusion, the present study provided nine new DNA methylation sites associated with glycemia homeostasis and also provided new insights of glycemia related loci into the genetics, epigenetics and transcriptomics pathways based on the integration of cross-omics data in silico.

genomics↗

bioRxiv2017

A Comprehensive Evaluation of the Genetic Architecture of Sudden Cardiac Arrest

BackgroundSudden cardiac arrest (SCA) accounts for 10% of adult mortality in Western populations. While several risk factors are observationally associated with SCA, the genetic architecture of SCA in the general population remains unknown. Furthermore, understanding which risk factors are causal may help target prevention strategies.\n\nMethodsWe carried out a large genome-wide association study (GWAS) for SCA (n=3,939 cases, 25,989 non-cases) to examine common variation genome-wide and in candidate arrhythmia genes. We also exploited Mendelian randomization methods using cross-trait multi-variant genetic risk score associations (GRSA) to assess causal relationships of 18 risk factors with SCA.\n\nResultsNo variants were associated with SCA at genome-wide significance, nor were common variants in candidate arrhythmia genes associated with SCA at nominal significance. Using cross-trait GRSA, we established genetic correlation between SCA and (1) coronary artery disease (CAD) and traditional CAD risk factors (blood pressure, lipids, and diabetes), (2) height and BMI, and (3) electrical instability traits (QT and atrial fibrillation), suggesting etiologic roles for these traits in SCA risk.\n\nConclusionsOur findings show that a comprehensive approach to the genetic architecture of SCA can shed light on the determinants of a complex life-threatening condition with multiple influencing factors in the general population. The results of this genetic analysis, both positive and negative findings, have implications for evaluating the genetic architecture of patients with a family history of SCA, and for efforts to prevent SCA in highrisk populations and the general community.

genetics↗

bioRxiv2017

Genome-wide Association Study Of Plasma Proteins Identifies Putatively Causal Genes, Proteins, And Pathways For Cardiovascular Disease

Identifying genetic variants associated with circulating protein concentrations (pQTLs) and integrating them with variants from genome-wide association studies (GWAS) may illuminate the proteomes causal role in disease and bridge a GWAS knowledge gap for hitherto unexplained SNP-disease associations. We conducted GWAS of 71 high-value proteins for cardiovascular disease in 6,861 Framingham Heart Study participants followed by external replication. We comprehensively mapped thousands of pQTLs, including functional annotations and clinical-trait associations, and created an integrated plasma-protein-QTL searchable database. We next identified 15 proteins with pQTLs coinciding with coronary heart disease (CHD)-related variants from GWAS or tested causal for CHD by Mendelian randomization; most of these proteins were associated with new-onset cardiovascular disease events in Framingham participants with long-term follow-up. Identifying pQTLs and integrating them with GWAS results yields insights into genes, proteins, and pathways that may be causally associated with disease and can serve as therapeutic targets for treatment and prevention.

epidemiology↗