Biology subjects

Chen, W.-M.

Publications and source records attributed to Chen, W.-M..

10 recordsLinked to original sources

bioRxiv2025

Prediction of Polygenic Risks by Screening Thousands of Polygenic Scores

RationaleA polygenic score (PGS) summarizes a persons genetic information in a single number for a trait, and its utility in genomic medicine is well-recognized. Although PGS models have been generated for many traits, they are not broadly available for certain traits due to limited sample sizes in studies of infrequent outcomes. Often, prediction of these not well-studied traits (e.g., treatment/drug responses) would be of great clinical utility and have been underutilized due to statistical power limitations. To support more versatile trait prediction, we present a method of developing PGS models that can be used in studies of any size with genome-wide SNP data. MethodWe first generate thousands of PGSs for each study participant in a given data set using their genome-wide SNP data and public resources. A PGS-wide scan involves evaluating the Area Under the Curve (AUC) of prediction for a binary trait (or the R-squared of association for a quantitative trait) at each PGS. We present two methods for the PGS model development, SECRET-Best, which selects the most predictive PGS from the PGS scan for prediction, and SECRET-WTSUM, which considers a combined score from multiple correlation-pruned PGSs. This algorithm is scalable and implemented in a user-friendly software tool, SECRET (Screen and Evaluate Catalogued Risk scores to Enhance Trait predictions). ResultsWe applied SECRET to a binary outcome (type 1 diabetes [T1D]) and a dataset of 2,100 samples, each with 12 laboratory test-related continuous traits. For nine traits with existing PGSs available in the PGS catalog, eight of the traits were predicted correctly, with the same trait-related PGS identified as the top predictor. We showed that the existing PGS methods had rather limited power to predict trait values in a validation set when only 1,500 samples were used to develop a PGS model, while the SECRET methods were able to maintain the prediction power for under-powered GWAS studies even when the sample size of the study was in hundreds. ConclusionThe SECRET methods and tool provide a valuable resource for studies with genomic data but of limited sample sizes. This approach enables systematic development and evaluation of PGS models.

bioinformatics↗

bioRxiv2025

NUDT5 regulates purine metabolism and thiopurine sensitivity by interacting with PPAT

Cells generate purine nucleotides through both de novo purine biosynthesis (DNPB) and purine salvage. Purine accumulation represses energetically costly DNPB through feedback inhibition of the enzymatic steps that produce the precursor phosphoribosylamine. Excessive DNPB is associated with human diseases including neurological dysfunction and hyperuricemia. However, the mechanisms explaining how cells balance DNPB and purine salvage are incompletely understood. Data from a genome-wide CRISPR loss-of-function screen and extensive stable isotope tracing identified Nudix hydrolase 5 (NUDT5) as a suppressor of DNPB during purine salvage. NUDT5 ablation allows DNPB to persist in the presence of either native purines or thiopurine drugs; this renders NUDT5-deficient cells insensitive to thiopurine treatment. Surprisingly, this regulation occurs independently of NUDT5s known function in hydrolyzing ADP-ribose to AMP and ribose-5-phosphate. Rather, NUDT5 interacts with phosphoribosyl pyrophosphate amidotransferase (PPAT), the rate-limiting enzyme in DNPB that generates phosphoribosylamine. Upon induction of purine salvage, the PPAT-NUDT5 interaction is required to trigger disassembly of the purinosome, a cytosolic metabolon involved in efficient DNPB. Mutations that disrupt NUDT5s interaction with PPAT but leave its catalytic activity intact permit excessive DNPB during purine salvage, inducing thiopurine resistance. Collectively, our findings identify NUDT5 as a regulator governing the balance between DNPB and purine salvage, underscoring its impact on nucleotide metabolism and efficacy of thiopurine treatment.

biochemistry↗

bioRxiv2024

BUB1 regulates non-homologous end joining pathway to mediate radioresistance in triple-negative breast cancer

BackgroundTriple-negative breast cancer (TNBC) is a highly aggressive form of breast cancer subtype often treated with radiotherapy (RT). Due to its intrinsic heterogeneity and lack of effective targets, it is crucial to identify novel molecular targets that would increase RT efficacy. Here we demonstrate the role of BUB1 (cell cycle Ser/Thr kinase) in TNBC radioresistance and offer a novel strategy to improve TNBC treatment. MethodsGene expression analysis was performed to look at genes upregulated in TNBC patient samples compared to other subtypes. Cell proliferation and clonogenic survivals assays determined the IC50 of BUB1 inhibitor (BAY1816032) and radiation enhancement ratio (rER) with pharmacologic and genomic BUB1 inhibition. Mammary fat pad xenografts experiments were performed in CB17/SCID. The mechanism through which BUB1 inhibitor sensitizes TNBC cells to radiotherapy was delineated by {gamma}-H2AX foci assays, BLRR, Immunoblotting, qPCR, CHX chase, and cell fractionation assays. ResultsBUB1 is overexpressed in BC and its expression is considerably elevated in TNBC with poor survival outcomes. Pharmacological or genomic ablation of BUB1 sensitized multiple TNBC cell lines to cell killing by radiation, although breast epithelial cells showed no radiosensitization with BUB1 inhibition. Kinase function of BUB1 is mainly accountable for this radiosensitization phenotype. BUB1 ablation also led to radiosensitization in TNBC tumor xenografts with significantly increased tumor growth delay and overall survival. Mechanistically, BUB1 ablation inhibited the repair of radiation-induced DNA double strand breaks (DSBs). BUB1 ablation stabilized phospho-DNAPKcs (S2056) following RT such that half-lives could not be estimated. In contrast, RT alone caused BUB1 stabilization, but pre-treatment with BUB1 inhibitor prevented stabilization (t1/2, [~]8 h). Nuclear and chromatin-enriched fractionations illustrated an increase in recruitment of phospho- and total-DNAPK, and KAP1 to chromatin indicating that BUB1 is indispensable in the activation and recruitment of non-homologous end joining (NHEJ) proteins to DSBs. Additionally, BUB1 staining of TNBC tissue microarrays demonstrated significant correlation of BUB1 protein expression with tumor grade. ConclusionsBUB1 ablation sensitizes TNBC cell lines and xenografts to RT and BUB1 mediated radiosensitization may occur through NHEJ. Together, these results highlight BUB1 as a novel molecular target for radiosensitization in women with TNBC.

cancer biology↗

bioRxiv2021

Enhanced genetic analysis of type 1 diabetes by selecting variants on both effect size and significance, and by integration with autoimmune thyroid disease

For polygenic traits, associations with genetic variants can be detected over many chromosome regions, owing to the availability oflarge sample sizes. Most variants, however, have small effects on disease risk and, therefore, unravelling the causal variants, target genes, and biology of these variants is challenging. Here, we define the Bigger or False Discovery Rate (BFDR) as the probability that either a variant is a false-positive or a randomly drawn, true-positive association exceeds it in effect size. Using the BFDR, we identified 302 previously unreported signals with larger effect associations with type 1 diabetes and autoimmune thyroid disease. Out of 239 genome-wide significant signals in both diseases, only 66 (28%) show evidence for having a large effect using the BFDR, further demonstrating how using a combination of effect size and significance, rather than significance alone, is important in identifying SNPs and candidate genes for further investigation.

genetics↗

bioRxiv2020

Genetic Landscape of Gullah African Americans

ObjectivesGullah African Americans are descendants of formerly enslaved Africans living in the Sea Islands along the coast of the southeastern U.S., from North Carolina to Florida. Their relatively high numbers and geographic isolation were conducive to the development and preservation of a unique culture that retains deep African features. Although historical evidence supports a West and Central African ancestry for the Gullah, linguistic and cultural evidence of a connection to Sierra Leone has led to the suggestion of this country/region as their ancestral home. This study sought to elucidate the genetic structure and ancestry of the Gullah. Materials and MethodsWe leveraged whole-genome genotype data from Gullah, African Americans from Jackson, Mississippi, Sierra Leone Africans, and population reference panels from Africa and Europe, to infer population structure, ancestry proportions, and global estimates of admixture. ResultsRelative to southeastern non-Gullah African Americans, the Gullah exhibit higher mean African ancestry, lower European admixture, a similarly small Native American contribution, and stronger male-biased European admixture. A slightly tighter bottleneck in the Gullah 13 generations ago suggests a largely shared demographic history with non-Gullah African Americans. Despite a slightly higher relatedness to Sierra Leone, our data demonstrate that the Gullah are genetically related to many West African populations. DiscussionThis study confirms that subtle differences in African American population structure exist at finer regional levels. Such observations can help to inform medical genetics research in African Americans, and guide the interpretation of genetic data used by African Americans seeking to explore ancestral identities. Research HighlightsO_LIUsing genomic data, we show that the Gullah have lower European and higher West African genomic background compared to non-Gullah African Americans, confirming their diverse African ancestry and rejecting a model that asserts a predominant Sierra Leone origin. C_LIO_LIOur data reveal a largely shared demographic history with southeastern non-Gullah African Americans, but also subtle differences related to high African genetic ancestry due to isolation in the Sea Islands. C_LI

genetics↗

bioRxiv2020

Fine-mapping, trans-ancestral and genomic analyses identify causal variants, cells, genes and drug targets for type 1 diabetes

We report the largest and most ancestrally diverse genetic study of type 1 diabetes (T1D) to date (61,427 participants), yielding 152 regions associated to false discovery rate < 0.01, including 36 regions associated to genome-wide significance for the first time. Credible sets of disease-associated variants are specifically enriched in immune cell accessible chromatin, particularly in CD4+ effector T cells. Colocalization with chromatin accessibility quantitative trait loci (QTL) in CD4+ T cells identified five regions where differences in T1D risk and chromatin accessibility are potentially driven by the same causal variant. Allele-specific chromatin accessibility further refined the set of putative causal variants with functional relevance in CD4+ T cells and integration of whole blood expression QTLs identified candidate T1D genes, providing high-yield targets for mechanistic follow-up. We highlight rs72938038 in BACH2 as a candidate causal T1D variant, where the T1D risk allele leads to decreased enhancer accessibility and BACH2 expression in T cells. Finally, we prioritise potential drug targets by integrating genetic evidence, functional genomic maps, and immune protein-protein interactions, identifying 12 genes implicated in T1D that have been targeted in clinical trials for autoimmune diseases. These findings provide an expanded genomic landscape for T1D, including proposed genetic regulatory mechanisms of T1D-associated variants and genetic support for therapeutic targets for immune intervention.

genetics↗

bioRxiv2019

Within-family studies for Mendelian randomization: avoiding dynastic, assortative mating, and population stratification biases

Mendelian randomization (MR) is a widely-used method for causal inference using genetic data. Mendelian randomization studies of unrelated individuals may be susceptible to bias from family structure, for example, through dynastic effects which occur when parental genotypes directly affect offspring phenotypes. Here we describe methods for within-family Mendelian randomization and through simulations show that family-based methods can overcome bias due to dynastic effects. We illustrate these issues empirically using data from 61,008 siblings from the UK Biobank and Nord-Trondelag Health Study. Both within-family and population-based Mendelian randomization analyses reproduced established effects of lower BMI reducing risk of diabetes and high blood pressure. However, while MR estimates from population-based samples of unrelated individuals suggested that taller height and lower BMI increase educational attainment, these effects largely disappeared in within-family MR analyses. We found differences between population-based and within-family based estimates, indicating the importance of controlling for family effects and population structure in Mendelian randomization studies.

genetics↗

bioRxiv2019

Dominant coral bacterium Endozoicomonas acroporae metabolizes DMSP

Dominant coral-associated Endozoicomonas bacteria species are hypothesized to play a role in the coral-sulfur cycle by metabolizing Dimethylsulfoniopropionate (DMSP) into Dimethylsulfide (DMS); however, no sequenced genome to date harbors genes for this process. In this study, we assembled high-quality (>95% complete) genomes of strains of a recently added species Endozoicomonas acroporae (Acr-14T, Acr-1 and Acr-5) isolated from the coral Acropora muricata and performed comparative genomic analysis on genus Endozoicomonas. We identified the first DMSP CoA-transferase/lyase--a dddD gene homolog found in all E. acroporae strains--and functionally characterized bacteria capable of metabolizing DMSP into DMS via the DddD cleavage pathway using RT-qPCR and gas chromatography (GC). Furthermore, we demonstrated that E. acroporae strains can use DMSP as the sole carbon source and have genes arranged in an operon-like manner to link DMSP metabolism to the central carbon cycle. This study confirms the role of Endozoicomonas in the coral sulfur cycle.

ecology↗

bioRxiv2018

Genome-wide association study of diabetic kidney disease highlights biology involved in renal basement membrane collagen

Diabetic kidney disease (DKD) is a heritable but poorly understood complication of diabetes. To identify genetic variants predisposing to DKD, we performed genome-wide association analyses in 19,406 individuals with type 1 diabetes (T1D) using a spectrum of DKD definitions basedon albuminuria and renal function. We identified 16 genome-wide significant loci. The variant with the strongest association (rs55703767) is a common missense mutation in the collagen type IV alpha 3 chain (COL4A3) gene, which encodes a major structural component of the glomerular basement membrane (GBM) implicated in heritable nephropathies. The rs55703767 minor allele (Asp326Tyr) is protective against several definitions of DKD, including albuminuria and end-stage renal disease. Three other loci are in or near genes with known or suggestive involvement in DKD (BMP7) or renal biology (COLEC11 and DDR1). The 16 DKD-associated loci provide novel insights into the pathogenesis of DKD, identifying potential biological targets for prevention and treatment.

genetics↗

bioRxiv2017

Fine-mapping identifies causal variants for RA and T1D in DNASE1L3, SIRPG, MEG3, TNFAIP3 and CD28/CTLA4 loci

We fine-mapped 76 rheumatoid arthritis (RA) and type 1 diabetes (T1D) loci outside of the MHC. After sequencing 799 1kb regulatory (H3K4me3) regions within these loci in 568 individuals, we observed accurate imputation for 89% of common variants. We fine-mapped1,2 these loci in RA (11,475 cases, 15,870 controls)3, T1D (9,334 cases and 11,111 controls) 4 and combined datasets. We reduced the number of potential causal variants to [≤]5 in 8 RA and 11 T1D loci. We identified causal missense variants in five loci (DNASE1L3, SIRPG, PTPN22, SH2B3 and TYK2) and likely causal non-coding variants in six loci (MEG3, TNFAIP3, CD28/CTLA4, ANKRD55, IL2RA, REL/PUS10). Functional analysis confirmed allele specific binding and differential enhancer activity for three variants: the CD28/CTLA4 rs117701653 SNP, the TNFAIP3 rs35926684 indel, and the MEG3 rs34552516 indel. This study demonstrates the potential for dense genotyping and imputation to pinpoint missense and non-coding causal alleles.

genetics↗