Biology subjects

Yang, H.-C.

Publications and source records attributed to Yang, H.-C..

6 recordsLinked to original sources

bioRxiv2026

Large-scale meta-analysis of over one million individuals reveals the genetic architecture of 127 complex traits in East Asian populations

Genome-wide association studies (GWASs) have disproportionately focused on European (EUR) populations, limiting the characterization of genetic architecture in other ancestries. To address this imbalance, we integrated large-scale biobanks from Japan, Korea, Taiwan, and China to perform the largest phenome-wide meta-analysis to date in East Asian (EAS) populations, encompassing over one million individuals across 127 complex traits. We identified 8,010 previously unreported associations and observed substantial genetic sharing across EAS subpopulations, while also detecting cohort-specific heterogeneity within the broader EAS context. Transethnic analyses revealed moderate genetic correlations between EAS and EUR populations, indicating both shared and ancestry-specific components of disease risk. Pleiotropy analyses highlighted prominent signals within the HLA region, supported by protein-protein interaction connectivity and immune-related pathway enrichment. Decomposition of genome-wide association matrices further uncovered structured cross-trait architectures, revealing a predominantly shared polygenic backbone driven by metabolic, biochemical, and anthropometric traits, together with two discrete latent components enriched for immune-related processes. Together, our findings refine the genetic architecture of complex traits in East Asian populations at unprecedented scale and clarify the balance between shared and population-specific determinants of human diseases.

genetics↗

bioRxiv2024

The Taiwan Precision Medicine Initiative: A Cohort for Large-Scale Studies

The Taiwan Precision Medicine Initiative (TPMI), a project initiated by the Academia Sinica in collaboration with 16 major medical centers around Taiwan, has recruited 565,390 participants who consented to provide DNA samples for genetic profiling and grant access to their electronic medical records (EMR) for studies to develop precision medicine. Access to the EMR is both retrospective and prospective, allowing researchers to conduct prospective studies over time. Genetic profiling is done with population-optimized SNP arrays for the Han Chinese populations that enable genetic analyses such as genome-wide association, phenome-wide association, and polygenic risk score studies to evaluate common disease risk and pharmacogenetic response. Furthermore, the TPMI participants agree to be contacted for future research opportunities related to their genetic risks and receive personalized genetic risk profiles with health management recommendations. TPMI has established the TPMI Data Access Platform (TDAP), a central database and analysis platform that both safeguards the security of the data and facilitates academic research. The TPMI is the largest non-European cohort that merges genetic profiles with EMR in the world. With a cohort that can be followed over time, it can be utilized to validate genetic risk prediction models, conduct clinical trials to show the efficacy of risk-based health management, and optimize health policies based on genetic risks. In this report, we describe the TPMI study design, the population and genetic characteristics of the TPMI cohort, and the power it provides to conduct crucial studies in developing precision medicine on a population and personal level. As Han Chinese represent almost 20% of the worlds population, the results of TPMI studies will benefit >1.4 billion people around the world and serve as a model for developing population-based precision medicine.

genetics↗

bioRxiv2022

Neurofluid Coupling during Sleep and Wake States

Low-frequency changes in cerebral hemodynamics have recently been shown to drive cerebrospinal fluid (CSF) movement in the human brain during non-rapid eye movement (NREM) sleep and resting state wakefulness. However, whether the coupling strength between these neurofluids varies between wake and sleep states is not known. In addition, the principal origin (i.e., neuronal vs. systemic) of these slow cerebral hemodynamic oscillations in either state also remains unexplored. To investigate this, a wake/sleep study was conducted on eight young, healthy volunteers, concurrently acquiring neurofluid dynamics using functional Magnetic Resonance Imaging, neural activity using Electroencephalography, and non-neuronal systemic physiology with peripheral functional Near-Infrared Spectroscopy. Our results reveal that low-frequency cerebral hemodynamics and CSF movements are strongly coupled regardless of whether participants were awake or in light NREM sleep. Furthermore, it was also found that, while autonomic neural contributions are present only during light NREM sleep, non-neuronal systemic physiology influences neurofluid low-frquency oscillations in a significant way across both wake and sleep states. These results further our understanding regarding the low-frequency hemodynamic drivers of CSF movement in the human brain and could help inform the development of therapies for enhancing CSF circulation.

neuroscience↗

bioRxiv2022

Subtyping of major SARS-CoV-2 variants reveals different transmission dynamics

SARS-CoV-2 continues to evolve, causing waves of the pandemic. Up to March 2022, eight million genome sequences have accumulated, which are classified into five major variants of concern. With the growing number of sequenced genomes, analysis of the big dataset has become increasingly challenging. Here we developed systematic approaches for comprehensive subtyping and pattern recognition for transmission dynamics. By analyzing the first two million viral genomes as of July 2021, we found that different subtypes of the same variant exhibited distinct temporal trajectories. For example, some Delta subtypes did not spread rapidly, while others did. We identified sets of characteristic single nucleotide variations (SNVs) that appeared to enhance transmission or decrease efficacy of antibodies for some subtypes of the Delta and Alpha variants. We also identified a set of SNVs that appeared to suppress transmission or increase viral sensitivity to antibodies. These findings are later confirmed in an analysis of six million genomes as of December 2021. For the Omicron variant, the dominant type in the world, we identified the subtypes with enhanced and suppressed transmission in an analysis of seven million genomes as of January 2022 and further confirmed the findings in a later analysis of eight million genomes as of March 2022. While the "enhancer" SNVs exhibited an enriched presence on the spike protein, the "suppressor" SNVs are mainly elsewhere. Disruption of the SNV correlation largely destroyed the enhancer-suppressor phenomena. These results suggest the importance of fine subtyping of variants, and point to potential complex interactions among SNVs.

bioinformatics↗

bioRxiv2021

An integrative approach unveils a distal encounter site for rPTPε and phospho-Src complex formation

Protein tyrosine phosphatase: phospho-protein complex structure determination, which requires to understand how specificity is achieved at the protein level remains a significant challenge for protein crystallography and cryoEM due to the transient nature of binding interactions. Using rPTP{varepsilon}D1 and phospho-SrcKD as a model system, we established an integrative workflow involving protein crystallography, SAXS and pTyr-tailored MD simulations to reveal the complex formed between rPTP{varepsilon}D1 and phospho-SrcKD, revealing transient protein-protein interactions distal to the active site. To support our finding, we determined the associate rate between rPTP{varepsilon}D1 and phospho-SrcKD and showed that a single mutation on rPTP{varepsilon}D1 disrupts this transient interaction, resulting in the reduction of association rate and activity. Our simulations suggest that rPTP{varepsilon}D1 employs a binding mechanism involving conformational change prior to the engagement of cSrcKD. This integrative approach is applicable to other PTP: phospho-protein complex determination and is a general approach for elucidating transient protein surface interactions.

biophysics↗

bioRxiv2020

Genomic, geographic and temporal distributions of SARS-CoV-2 mutations

The COVID-19 pandemic is the most significant public health issue in recent history. Its causal agent, SARS-CoV-2, has evolved rapidly since its first emergence in December 2019. Mutations in the viral genome have critical impacts on the adaptation of viral strains to the local environment, and may alter the characteristics of viral transmission, disease manifestation, and the efficacy of treatment and vaccination. Using the complete sequences of 1,932 SARS-CoV-2 genomes, we examined the genomic, geographic and temporal distributions of aged, new, and frequent mutations of SARS-CoV-2, and identified six phylogenetic clusters of the strains, which also exhibit a geographic preference in different continents. Mutations in the form of single nucleotide variations (SNVs) provide a direct interpretation for the six phylogenetic clusters. Linkage disequilibrium, haplotype structure, evolutionary process, global distribution of mutations unveiled a sketch of the mutational history. Additionally, we found a positive correlation between the average mutation count and case fatality, and this correlation had strengthened with time, suggesting an important role of SNVs on disease outcomes. This study suggests that SNVs may become an important consideration in virus detection, clinical treatment, drug design, and vaccine development to avoid target shifting, and that continued isolation and sequencing is a crucial component in the fight against this pandemic. Significance StatementMutation is the driving force of evolution for viruses like SARS-CoV-2, the causal agent of COVID-19. In this study, we discovered that the genome of SARS-CoV-2 is changing rapidly from the originally isolated form. These mutations have been spreading around the world and caused more than 2.5 million of infected cases and 170 thousands of deaths. We found that fourteen frequent mutations identified in this study can characterize the six main clusters of SARS-CoV-2 strains. In addition, we found the mutation burden is positively correlated with the fatality of COVID-19 patients. Understanding mutations in the SARS-CoV-2 genome will provide useful insight for the design of treatment and vaccination.

microbiology↗