Biology subjects

Bi, W.

Publications and source records attributed to Bi, W..

15 recordsLinked to original sources

bioRxiv2026

LKOM: Longitudinal Knockoff with Masked Likelihood Ratio for FDR-Controlled Association Discovery

Repeated phenotypic measurements in biobanks can reveal genetic effects on both average trait levels and within-subject variability. However, existing longitudinal genome-wide association methods generally test variants marginally and analyze the two components separately, limiting the localization of signals in linkage disequilibrium and the detection of variants with shared effects. Here we introduce Longitudinal KnockOff with Masked likelihood ratio (LKOM), a multivariable framework that jointly models mean and variability signals while controlling the variant-level false discovery rate for the joint null of no association with either component. LKOM uses model-X knockoffs and masked likelihood-ratio statistics to distinguish original variants from synthetic controls, and assigns selected variants to mean-specific, variability-specific or shared association states. A genetic-relationship-matrix-based whitening extension accommodates related individuals. In simulations, LKOM maintained false discovery rate control across diverse genetic architectures, heavy-tailed errors, reduced longitudinal follow-up and sample sizes up to 100,000. It generally improved power over separate-channel knockoff and marginal association methods, with the largest gains for shared effects and rare variants, particularly when the overall genetic contribution to phenotypic variation was modest. In related samples, whitening restored calibration under dense pedigree structures while preserving power gains over SPAGRM(CCT). LKOM provides an interpretable and scalable approach for identifying conditionally associated variants from longitudinal phenotypes.

bioinformatics↗

bioRxiv2024

Deletion of adipocyte Sine Oculis Homeobox Homolog 1 prevents lipolysis and attenuates skin fibrosis.

Dermal fibrosis is a cardinal feature of systemic sclerosis (SSc) for which there are limited treatment strategies. This is in part due to our fragmented understanding of how dermal white adipose tissue (DWAT) contributes to skin fibrosis. We identified elevated sine oculis homeobox homolog 1 (SIX1) expression in SSc skin samples from the GENISOS and PRESS cohorts, the expression of which correlated with adipose-associated genes and molecular pathways. SIX1 localization studies identified increased signals in the DWAT area in SSc and in experimental models of skin fibrosis. Global and adipocyte specific Six1 deletion abrogated end-stage fibrotic gene expression and dermal adipocyte shrinkage induced by SQ bleomycin treatment. Further studies revealed a link between elevated SIX1 and increased expression of SERPINE1 and its protein PAI-1 which are known pro-fibrotic mediators. However, SIX1 deletion did not appear to affect cellular trans differentiation. Taken together these results point at SIX1 as a potential target for dermal fibrosis in SSc. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSSkin thickening and tightening are leading causes of morbidity in systemic sclerosis (SSc). The authors previously reported that the aberrantly expressed developmental transcription factor sine oculis homeobox homology 1 (SIX1) drives pulmonary fibrosis. However, the contribution of SIX1 to skin fibrosis and associated dermal fat loss remains unknown. Added value of this studyThe role of dermal fat loss in skin fibrosis is not fully understood. Studies have shown that adipocytes can transition to mesenchymal cells promoting fibrosis, consistent with loss of the dermal white adipose layer. Our research provides insight into a novel molecular mechanism of lipodystrophy important for skin fibrosis in SSc. We identified the upregulation of SIX1 in adipocytes in skin from patients with SSc which was associated with the progression of skin fibrosis. We found elevated Six1 in mouse dermal adipocytes of early fibrotic skin. Ubiquitous and adipose-specific loss of Six1 decreased markers of experimental skin fibrosis in mice which recapitulate cardinal features of SSc dermal fibrosis. Increased SIX1 expression is linked with elevated levels of Serpine1 the gene that codes for the protein plasminogen activator inhibitor (PAI)-1. This is important since PAI-1 is a known pro-fibrotic agent in the skin that contributes to the deposition of extracellular matrix (ECM) products. Implications of all the available evidenceFat atrophy may represent a targetable contributor to early systemic sclerosis manifestations. This is as it precedes skin fibrosis and the use of topical agent which are usually lipophilic can help us target dermal adipocytes. Our results show that SIX1 could be an important early marker for skin fibrosis in SSc that can also be targeted therapeutically.

molecular biology↗

bioRxiv2021

Perception of soft materials relies on physics-based object representations: Behavioral and computational evidence

When encountering objects, we readily perceive not only low-level properties (e.g., color and orientation), but also seemingly higher-level ones - including aspects of physics (e.g., mass). Perhaps nowhere is this contrast more salient than in the perception of soft materials such as cloths: the dynamics of these objects (including how their three-dimensional forms vary) are determined by their physical properties such as stiffness, elasticity, and mass. Here we hypothesize that the perception of cloths and their physical properties must involve not only image statistics, but also abstract object representations that incorporate "intuitive physics". We provide behavioral and computational evidence for this hypothesis. We find that humans can visually match the stiffness of cloths with unfamiliar textures from the way they undergo natural transformations (e.g. flapping in the wind) across different scenarios. A computational model that casts cloth perception as mental physics simulation explains important aspects of this behavior.

neuroscience↗

bioRxiv2020

Efficient mixed model approach for large-scale genome-wide association studies of ordinal categorical phenotypes

In genome-wide association studies (GWAS), ordinal categorical phenotypes are widely used to measure human behaviors, satisfaction, and preferences. However, due to the lack of analysis tools, methods designed for binary and quantitative traits have often been used inappropriately to analyze categorical phenotypes, which produces inflated type I error rates or is less powerful. To accurately model the dependence of an ordinal categorical phenotype on covariates, we propose an efficient mixed model association test, Proportional Odds Logistic Mixed Model (POLMM). POLMM is demonstrated to be computationally efficient to analyze large datasets with hundreds of thousands of genetic related samples, can control type I error rates at a stringent significance level regardless of the phenotypic distribution, and is more powerful than other alternative methods. We applied POLMM to 258 ordinal categorical phenotypes on array-genotypes and imputed samples from 408,961 individuals in UK Biobank. In total, we identified 5,885 genome-wide significant variants, of which 424 variants (7.2%) are rare variants with MAF < 0.01.

genetics↗

bioRxiv2020

Engineered Trimeric ACE2 Binds and Locks "Three-up" Spike Protein to Potently Inhibit SARS-CoVs and Mutants

SARS-CoV-2 enters cells via ACE-2, which binds the spike protein with moderate affinity. Despite a constant background mutational rate, the virus must retain binding with ACE2 for infectivity, providing a conserved constraint for SARS-CoV-2 inhibitors. To prevent mutational escape of SARS-CoV-2 and to prepare for future related coronavirus outbreaks, we engineered a de novo trimeric ACE2 (T-ACE2) protein scaffold that binds the trimeric spike protein with extremely high affinity (KD < 1 pM), while retaining ACE2 native sequence. T-ACE2 potently inhibits all tested pseudotyped viruses including SARS-CoV-2, SARS-CoV, eight naturally occurring SARS-CoV-2 mutants, two SARSr-CoVs as well as authentic SARS-CoV-2. The cryo-EM structure reveals that T-ACE2 can induce the transit of spike protein to "three-up" RBD conformation upon binding. T-ACE2 thus represents a promising class of broadly neutralizing proteins against SARS-CoVs and mutants.

bioengineering↗

bioRxiv2020

Identification of mtROS-sensitive processes in activated CD4+ T cells

T lymphocytes are key components in adaptive immunity and their activation naturally involves mitochondrial-derived oxygen species (mtROS). In particular, H2O2 has been implicated as an important signaling molecule regulating major T cell functions. H2O2 targets the oxidation status of functional cysteine residues but knowledge if and where this happens in T cell signaling networks is widely missing. This study aimed to identify mtROS-sensitive processes in activated primary human CD4+ T cells. By using a thiol-specific redox proteomic approach we examined the oxidation state of 4784 cysteine-containing peptides of ex vivo stimulated T cells from healthy individuals. Upon activation, a shift in oxidation was observed at catalytic cysteine residues of peroxiredoxins (PRDX5 & PRDX6), and T cells were found to maintain their global thiol-redox homeostasis. In parallel, a distinct set of 88 cysteine residues were found to be differentially oxidized upon T cell activation suggesting novel functional thiol switches. In mitochondria, cysteine oxidations selectively modified regulators of respiration (NDUFA2, NDUFA8, and UQCRH) confirming electron leakage from electron transport complexes I and III. The majority of oxidations occurred outside mitochondria and enriched sensitive thiols at regulators of cytoskeleton dynamics (e.g. CYFIP2 and ARPC1B) and known immune functions including the non-receptor tyrosine phosphatase PTPN7. Conversely, cysteine reduction occurred predominantly at transcriptional regulators and sites that coordinate zinc-binding in zinc-finger motifs. Indeed, fluorescence microscopy revealed a colocalization of zinc-rich microenvironments and mitochondria in T cells suggesting mtROS-dependent zinc-release of identified transcriptional regulators including ZFP36, RPL37A and CRIP2. In conclusion, this study complements knowledge on the mtROS signaling network and suggests zinc-dependent thiol switches as a mechanism of how mtROS affects transcription and translation in T cells.

immunology↗

bioRxiv2019

Integrated Sequencing & Array Comparative Genomic Hybridization in Familial Parkinson’s Disease

BackgroundParkinsons disease (PD) is a genetically heterogeneous condition; both single nucleotide variants (SNVs) and copy number variants (CNVs) are important genetic risk factors. We examined the utility of combining exome sequencing and genome-wide array-based comparative genomic hybridization (aCGH) for identification of PD genetic risk factors. MethodsWe performed exome sequencing on 110 subjects with PD and a positive family history; 99 subjects were also evaluated using genome-wide aCGH. We interrogated exome sequencing and array comparative genomic hybridization data for pathogenic SNVs and CNVs at Mendelian PD gene loci. SNVs were confirmed via Sanger sequencing. CNVs were confirmed with custom-designed high-density aCGH, droplet digital PCR, and breakpoint sequencing. ResultsUsing exome sequencing, we discovered individuals with known pathogenic single nucleotide variants in GBA (p.E365K, p.T408M, p.N409S, p.L483P) and LRRK2 (p.R1441G and p.G2019S). Two subjects were each double heterozygotes for variants in GBA and LRRK2. Based on aCGH, we additionally discovered cases with an SNCA duplication and heterozygous intragenic GBA deletion. Five additional subjects harbored both SNVs (p.N52fs, p.T240M, p.P437L, p.W453*) and likely disrupting CNVs at the PARK2 locus, consistent with compound heterozygosity. In nearly all cases, breakpoint sequencing revealed microhomology, a mutational signature consistent with CNV formation due to DNA replication errors. ConclusionsIntegrated exome sequencing and aCGH yielded a genetic diagnosis in 19.3% of our familial PD cohort. Our analyses highlight potential mechanisms for SNCA and PARK2 CNV formation, uncover multilocus pathogenic variation, and identify novel SNVs and CNVs for further investigation as potential PD risk alleles.

genetics↗

bioRxiv2019

Effect of Geometric Sharpness on Translucent Material Perception

When judging optical properties of a translucent object, humans often look at sharp geometric features such as edges and thin parts. Analysis of the physics of light transport shows that these sharp geometries are necessary for scientific imaging systems to be able to accurately measure the underlying material optical properties. In this paper, we examine whether human perception of translucency is likewise affected by the presence of sharp geometry, by confounding our perceptual inferences about an objects optical properties. We employ physically accurate simulations to create visual stimuli of translucent materials with varying shapes and optical properties under different illuminations. We then use these stimuli in psychophysical experiments, where human observers are asked to match an image of a target object by adjusting the material parameters of a match object with different geometric sharpness, lighting geometry, and 3D geometry. We find that the level of geometric sharpness significantly affects perceived translucency by the observers. These findings generalize across a few illuminations and object shapes. Our results suggest that the perceived translucency of an object depends on both the underlying material optical parameters and 3D shape. We also conduct analyses using computational metrics including (luminance-normalized) L2, structural similarity index (SSIM), and Michelson contrast. We find that these image metrics cannot predict perceptual results, suggesting low level image cues are not sufficient to explain our results.

neuroscience↗

bioRxiv2019

UK-Biobank Whole Exome Sequence Binary Phenome Analysis with Robust Region-based Rare Variant Test

In biobank data analysis, most binary phenotypes have unbalanced case-control ratios, which can cause inflation of type I error rates. Recently, a saddlepoint approximation (SPA) based single variant test has been developed to provide an accurate and scalable method to test for associations of such phenotypes. For gene- or region-based multiple variant tests, a few methods exist which adjust for unbalanced case-control ratios; however, these methods are either less accurate when case-control ratios are extremely unbalanced or not scalable for large data analyses. To address these problems, we propose SKAT/SKAT-O type region-based tests, where the single-variant score statistic is calibrated based on SPA and Efficient Resampling (ER). Through simulation studies, we show that the proposed method provides well-calibrated p-values. In contrast, the unadjusted approach has greatly inflated type I error rates (90 times of exome-wide =2.5x10-6) when the case-control ratio is 1:99. Additionally, the proposed method has similar computation time as the unadjusted approaches and is scalable for large sample data. Our UK Biobank whole exome sequence data analysis of 45,596 unrelated European samples and 791 PheCode phenotypes identified 10 rare variant associations with p-value < 10-7, including the associations between JAK2 and myeloproliferative disease, TNC and large cell lymphoma and F11 and congenital coagulation defects. All analysis summary results are publicly available through a web-based visual server.

genetics↗

bioRxiv2019

Scalable generalized linear mixed model for region-based association tests in large biobanks and cohorts

With very large sample sizes, population-based cohorts and biobanks provide an exciting opportunity to identify genetic components of complex traits. To analyze rare variants, gene or region-based multiple variant aggregate tests are commonly used to increase association test power. However, due to the substantial computation cost, existing region-based rare variant tests cannot analyze hundreds of thousands of samples while accounting for confounders, such as population stratification and sample relatedness. Here we propose a scalable generalized mixed model region-based association test that can handle large sample sizes and accounts for unbalanced case-control ratios for binary traits. This method, SAIGE-GENE, utilizes state-of-the-art optimization strategies to reduce computational and memory cost, and hence is applicable to exome-wide and genome-wide region-based analysis for hundreds of thousands of samples. Through the analysis of the HUNT study of 69,716 Norwegian samples and the UK Biobank data of 408,910 White British samples, we show that SAIGE-GENE can efficiently analyze large sample data (N > 400,000) with type I error rates well controlled.

genetics↗

bioRxiv2019

Manipulating patterns of dynamic deformation elicits the impression of cloth with varying stiffness

Cloth is a common material and humans can visually estimate its mechanical properties by observing how it deforms under external forces. Here we ask whether, and how, dynamic deformation can affect the perception of mechanical properties of cloth. In Experiment 1, we find that both intrinsic mechanical properties and optical properties affect stiffness perception when the stimuli are presented as images. By contrast, in videos, humans can partially discount the effect of optical appearances and exhibit higher sensitivity to stiffness. We further identified an idiosyncratic deformation pattern (i.e., movement uniformity) to differentiate stiffness, which can be reliably measured by six optical flow features. In Experiment 2, we isolate the deformation by creating dynamic dot stimuli from the 3D mesh of the cloth. We directly alter the movement pattern by manipulating the uniformity of the displacement vectors on the dot stimuli, and show that changing the pattern of dynamic deformation alone can alter the perceived stiffness of cloth in a variety of scene set-ups. Furthermore, by analyzing optical flow fields extracted from the manipulated dynamic dot stimuli, we confirmed the same six optical flow features can be diagnostic of the degree of stiffness of moving cloth across different scenes. Overall, our study demonstrates that manipulating patterns of dynamic deformation alone can elicit the impression of cloth with varying stiffness, suggesting that human visual system might rely on the idiosyncratic pattern of dynamic deformation for estimating stiffness.

neuroscience↗

bioRxiv2018

Atlas-CNV: a validated approach to call Single-Exon CNVs in the eMERGESeq gene panel

PurposeTo provide a validated method to confidently identify exon-containing copy number variants (CNVs), with a low false discovery rate (FDR), in targeted sequencing data from a clinical laboratory with particular focus on single-exon CNVs.\n\nMethodsDNA sequence coverage data are normalized within each sample and subsequently exonic CNVs are identified in a batch of samples (midpool), when the target log2 ratio of the sample to the batch median exceeds defined thresholds. The quality of exonic CNV calls is assessed by C-scores (Z-like scores) using thresholds derived from gold standard samples and simulation studies. We integrate an ExonQC threshold to lower FDR and compare performance with alternate software (VisCap).\n\nResultsThirteen CNVs were used as a truth set to validate Atlas-CNV and compared with VisCap. We demonstrated FDR reduction in validation, simulation and 10,926 eMERGESeq samples without sensitivity loss. Sixty-four multi-exon and 29 single-exon CNVs with high C-scores were assessed by MLPA.\n\nConclusionsAtlas-CNV is validated as a method to identify exonic CNVs in targeted sequencing data generated in the clinical laboratory. The ExonQC and C-score assignment can reduce FDR (identification of targets with high variance) and improve calling accuracy of single-exon CNVs respectively. We proposed guidelines and criteria to identify high confidence single-exon CNVs.

genomics↗

bioRxiv2018

Interaction between static visual cues and force-feedback on the perception of mass of virtual objects

We use force-feedback device and a game engine to measure the effects of material appearance on the perception of mass of virtual objects. We discover that the perceived mass is mainly determined by the ground-truth mass output by the force-feedback device. Different from the classic Material Weight Illusion (MWI), however, heavy-looking objects (e.g. steel) are consistently rated heavier than light-looking ones (e.g. fabric) with the same ground-truth mass. Analysis of the initial accelerated velocity of the movement trajectories of the virtual probe shows greater acceleration for materials with heavier rated mass. This effect is diminished when the participants lift the object for the second time, meaning that the influence of visual appearance disappears in the movement trajectories once it is calibrated by the force-feedback. We also show how the material categories are affected by both the visual appearance and the weight of the object. We conclude that visual appearance has a significant interaction with haptic force-feedback on the perception of mass and also affects the kinematics of how participants manipulate the object.\n\nCCS CONCEPTS* Human-centered computing [->] Empirical studies in HCI; Empirical studies in interaction design; Empirical studies in visualization;\n\nACM Reference FormatWenyan Bi, Jonathan Newport, and Bei Xiao. 2018. Interaction between static visual cues and force-feedback on the perception of mass of virtual objects. In Proceedings of. ACM, New York, NY, USA, 5 pages.

neuroscience↗

bioRxiv2018

Phenotypic expansion in DDX3X -- a common cause of intellectual disability in females

De novo variants in DDX3X account for 1-3% of unexplained intellectual disability (ID), one of the most common causes of ID, in females. Forty-seven patients (44 females, 3 males) have been described. We identified 29 additional individuals carrying 27 unique DDX3X variants in the setting of complex clinical presentations including developmental delay or ID. In addition to previously reported manifestations, rare or novel phenotypes were identified including respiratory problems, congenital heart disease, skeletal muscle mitochondrial DNA depletion, and late-onset neurologic decline. Our findings expand the spectrum of DNA variants and phenotypes associated with DDX3X disorders.

genetics↗

bioRxiv2018

Estimating mechanical properties of cloth from videos using dense motion trajectories: human psychophysics and machine learning

Humans can visually estimate the mechanical properties of deformable objects (e.g. cloth stiffness). While much of the recent work on material perception has focused on static image cues (e.g., textures and shape), little is known whether humans can integrate information over time to make a judgment. Here, we investigate the effect of spatiotemporal information across multiple frames (multi-frame motion) on estimating the bending stiffness of cloth. Using high-fidelity cloth animations, we first examined how the perceived bending stiffness changed as a function of the physical bending stiffness defined in the simulation model. Using maximum likelihood difference scaling methods (MLDS) we found that the perceived stiffness and the physical bending stiffness were highly correlated. A second experiment in which we scrambled the frame sequences diminished this correlation. This suggests that multi-frame motion plays an important role. To provide further evidence for this finding, we extracted dense motion trajectories from the videos across 15 consecutive frames and used the trajectory descriptors to train a machine-learning model with the measured perceptual scales. The model can predict human perceptual scales in new videos with varied winds, optical properties of cloth, and scene setups. When the correct multi-frame was removed (using either scrambled videos or 2-frame optical flow to train the model), the predictions significantly worsened. Our findings demonstrate that multi-frame motion information is important for both humans and machines to estimate the mechanical properties. In addition, we show that dense motion trajectories are effective features to build a successful automatic cloth estimation system.

neuroscience↗