Biology subjects

Lu, Q.

Publications and source records attributed to Lu, Q..

At least 127 records · Page 7Linked to original sources

bioRxiv2020

Comparison of methods for estimating genetic correlation between complex traits using GWAS summary statistics

Genetic correlation is the correlation of additive genetic effects on two phenotypes. It is an informative metric to quantify the overall genetic similarity between complex traits, which provides insights into their polygenic genetic architecture. Several methods have been proposed to estimate genetic correlations based on data collected from genome-wide association studies (GWAS). Due to the easy access of GWAS summary statistics and computational efficiency, methods only requiring GWAS summary statistics as input have become more popular than methods utilizing individual-level genotype data. Here, we present a benchmark study for different summary-statistics-based genetic correlation estimation methods through simulation and real data applications. We focus on two major technical challenges in estimating genetic correlation: marker dependency caused by linkage disequilibrium (LD) and sample overlap between different studies. To assess the performance of different methods in the presence of these two challenges, we first conducted comprehensive simulations with diverse LD patterns and sample overlaps. Then we applied these methods to real GWAS summary statistics for a wide spectrum of complex traits. Based on these experiments, we conclude that methods relying on accurate LD estimation are less robust in real data applications compared to other methods due to the imprecision of LD obtained from reference panels. Our findings offer a guidance on how to appropriately choose the method for genetic correlation estimation in post-GWAS analysis in interpretation.

genetics↗

bioRxiv2020

Estimating genetic nurture with summary statistics of multi-generational genome-wide association studies

Marginal effect estimates in genome-wide association studies (GWAS) are mixtures of direct and indirect genetic effects. Existing methods to dissect these effects require family-based, individual-level genetic and phenotypic data with large samples, which is difficult to obtain in practice. Here, we propose a novel statistical framework to estimate direct and indirect genetic effects using summary statistics from GWAS conducted on own and offspring phenotypes. Applied to birth weight, our method showed nearly identical results with those obtained using individual-level data. We also decomposed direct and indirect genetic effects of educational attainment (EA), which showed distinct patterns of genetic correlations with 45 complex traits. The known genetic correlations between EA and higher height, lower BMI, less active smoking behavior, and better health outcomes were mostly explained by the indirect genetic component of EA. In contrast, the consistently identified genetic correlation of autism spectrum disorder (ASD) with higher EA resides in the direct genetic component. Polygenic transmission disequilibrium test showed a significant over-transmission of the direct component of EA from healthy parents to ASD probands. Taken together, we demonstrate that traditional GWAS approaches, in conjunction with offspring phenotypic data collection in existing cohorts, could greatly benefit studies on genetic nurture and shed important light on the interpretation of genetic associations for human complex traits.

genetics↗

bioRxiv2020

Function expansion of antitumor transcriptional activator NFE2L1 by the original discovery of its non-transcription factor activity

Antitumor transcription activator NFE2L1, with the functions to regulate redox homeostasis, protein turnover, and material metabolism, plays an important role in embryonic development and specialization of tissue and organ functions. Deficiency of NFE2L1 gene in different regions yields distinct phenotypes, suggesting that NFE2L1 may have a transcription factor-independent function. Here we originally discovered the non-transcription factor activity of NFE2L1 by constructing a truncated protein-NFE2L1{Delta}C without 152 aa at the C-terminus which lost the transcription factor activity. The regulation of NFE2L1 on redox homeostasis, proteasome function, and immune response mainly depends on its transcription activator function in nucleus, while the regulation on metabolism, ribosome function, and canceration is germanely to its non-transcription factor activity in cytoplasm. Surprisingly, the results indicated the tumor suppressive effect of NFE2L1 by repression of Wnt/{beta}-catenin signaling in a non-transcription factor manner, indicating the potential value of NFE2L1 as a therapeutic target in clinical cancer treatment independent of its transcription factor activity. Our observations reveal the non-transcription factor activity of NFE2L1 for the first time, and lay foundation for the basic and applied research of NFE2L1.

molecular biology↗

bioRxiv2020

Activation of the membrane-bound Nrf1 transcription factor by USP19, a tail-anchored ubiquitin-specific protease in the endoplasmic reticulum

The membrane-bound transcription factor Nrf1 (i.e., encoded by Nfe2l1) is activated by sensing glucose deprivation, cholesterol excess, proteasomal inhibition and oxidative stress, and then mediates distinct signaling responses in order to maintain cellular homeostasis. Herein, we found that Nrf1 stability and transactivity are both enhanced by USP19, a ubiquitin-specific protease tail-anchored in the endoplasmic reticulum (ER) through its C-terminal transmembrane domain. Further experiments revealed that USP19 directly interacts with Nrf1 in proximity to the ER and topologically acts as a deubiquitinating enzyme to remove ubiquitin moieties from this protein, and hence allows it to circumvent the potential proteasomal degradation. Such USP19-mediated effect takes place only after Nrf1 is retrotranslocated by p97 out of ER membranes to dislocate the cytoplasmic side. Conversely, knockout of USP19 causes significant decreases in the Nrf1 abundance and its active isoform entering the nucleus, resulting in down-regulation of its target proteasomal subunits. This led to a modest reduction of USP19-/--derived tumor growth in xenograft mice, when compared with wild-type controls. Altogether, these demonstrate that USP19 serves as a novel mechanistic modulator of Nrf1, but not Nrf2, enabling Nrf1 to be rescued from putative ubiquitin-directed ER-associated degradation pathway. In turn, our additional experimental evidence has unraveled that transcriptional expression of endogenous USP19 and its promoter-driven reporter genes is differentially regulated by Nrf2, as well by Nrf1, at distinct layers within a complex hierarchical regulatory network.

biochemistry↗

bioRxiv2020

Comparison of CRISPR/Cas endonucleases for in vivo retinal gene editing.

CRISPR/Cas has opened the prospect of direct gene correction therapy for some inherited retinal diseases. Previous work has demonstrated the utility of adeno-associated virus (AAV) mediated delivery to retinal cells in vivo; however, with the expanding repertoire of CRISPR/Cas endonucleases, it is not clear which of these are most efficacious for retinal editing in vivo. We sought to compare CRISPR/Cas endonuclease activity using both single and dual AAV delivery strategies for gene editing in retinal cells. Plasmids of a dual vector system with SpCas9, SaCas9, Cas12a, CjCas9 and sgRNA targeting YFP and a single vector system with SaCas9/YFP sgRNA were generated and validated in YFP-expressing HEK293A cell by flow cytometry and T7E1 assay. Paired CRISPR/Cas endonuclease and its best performing sgRNA was then packaged into an AAV2 capsid derivative, AAV7m8, and injected intravitreally into CMV-Cre::Rosa26-YFP mice. SpCas9 and Cas12a achieved better knockout efficiency than SaCas9 and CjCas9. Moreover, no significant difference in YFP gene editing was found between single and dual CRISPR/SaCas9 vector systems. With a marked reduction of YFP-positive retinal cells, AAV7m8 delivered SpCas9 was found to have the highest knockout efficacy among all investigated endonucleases. We demonstrate that the AAV7m8-mediated delivery of CRISPR/SpCas9 construct achieves the most efficient gene modification in neurosensory retinal cells in vitro and in vivo.

bioengineering↗

bioRxiv2020

The production of within-family inequality: Insights and implications of integrating genetic data

The integration of genetic data within large-scale social and health surveys provides new opportunities to test long standing theories of parental investments in children and within-family inequality. Genetic predictors, called polygenic scores, allow novel assessments of young childrens abilities that are uncontaminated by parental investments, and family-based samples allow indirect tests of whether childrens abilities are reinforced or compensated. We use over 16,000 sibling pairs from the UK Biobank to test whether the relative ranking of siblings polygenic scores for educational attainment is consequential for actual attainments. We find strong evidence of compensatory processes, on average, where the association between genotype and phenotype of educational attainment is reduced by over 20% for the higher-ranked sibling compared to the lower-ranked sibling. These effects are most pronounced in high socioeconomic status areas. We find no evidence that similar processes hold in the case of height or for relatives who are not full biological siblings (e.g. cousins). Our results provide a new use of polygenic scores to understand processes that generate within-family inequalities and also suggest important caveats to causal interpretations the effects of polygenic scores using siblingdifference designs.

genetics↗

bioRxiv2020

Local genetic correlation analysis reveals heterogeneous etiologic sharing of complex traits

Local genetic correlation quantifies the genetic similarity of complex traits in specific genomic regions, which could shed unique light on etiologic sharing and provide additional mechanistic insights into the genetic basis of complex traits compared to global genetic correlation. However, accurate estimation of local genetic correlation remains challenging, in part due to extensive linkage disequilibrium in local genomic regions and pervasive sample overlap across studies. We introduce SUPERGNOVA, a unified framework to estimate both global and local genetic correlations using summary statistics from genome-wide association studies. Through extensive simulations and analyses of 30 complex traits, we demonstrate that SUPERGNOVA substantially outperforms existing methods and identifies 150 trait pairs with significant local genetic correlations. In particular, we show that the positive, consistently-identified, yet paradoxical genetic correlation between autism spectrum disorder and cognitive performance could be explained by two etiologically-distinct genetic signatures with bidirectional local genetic correlations. We believe that statistically-rigorous local genetic correlation analysis could accelerate progress in complex trait genetics research.

genetics↗

bioRxiv2020

RDoC Mechanisms of Transdiagnostic Polygenic Risk for Trajectories of Depression: From Early Adolescence to Adulthood

There is substantial heterogeneity in the development of depression across early adolescence into adulthood. Yet, little is known about the risk factors underlying individual differences in the development of depression. For instance, despite the discovery of genetic variants for depression, there is also significant genetic overlap between depression and other mental disorders. Thus, depression may have etiologically complex (i.e., transdiagnostic) origins when accounting for its heterogeneous developmental presentations. This study examined the association between a transdiagnostic polygenic score for psychopathology (p-factor PGS) and depressive trajectories, spanning early adolescence into adulthood, in the National Longitudinal Study of Adolescent to Adult Health. We also examined whether the Research Domains Criteria (RDoC) negative valence (i.e., negative emotionality), positive valence (i.e., novelty seeking), and cognitive systems (i.e., picture vocabulary) could explain how the p-factor PGS eventuates into the various pathways of depressive development. Four trajectories of depression were identified: low depression (78.9%), low increasing (7.3%), high declining (8.2%), and early adult peaked (5.7%). The p-factor PGS was only associated with the trajectory that showed increasing depression over time - low increasing. There was also a specific indirect effect by which the association of p-factor PGS on early adult peaked and high declining depression was partially mediated by negative emotionality, but not by picture vocabulary or novelty seeking. Our findings reinforce the crucial role of development in genetically-informed RDoC models of depression, as there appear to be distinct correlates and risk factors that underlie the various developmental pathways of depression. Clinical implications were also discussed. General Scientific SummaryThere are individual differences in how depression symptoms progress over time, but little is known about the risk factors that underlie these various patterns of development. This study suggests that there are distinct correlates and risk factors that underlie the various developmental pathways of depression. We found that transdiagnostic polygenic risks for psychopathology are directly associated with worsening patterns of adolescent to adult depression and indirectly associated with the less severe patterns of depression via negative emotionality.

genetics↗

bioRxiv2020

Transferrin-dependent crosstalk between the intestinal tract and commensal microbes contributes for immune tolerance

Crosstalks between gastrointestinal tract and commensal microbes regulate immune tolerance and maintain host intestinal homeostasis. However, molecular events that regulate the crosstalks remain poorly understood. Here, we show that microbial products (lipopolysaccharide, lipoteichoic acid and DNA) up-regulate host transferrin, an iron supplier of commensal bacteria, to induce hosts immune tolerance by negatively regulating toll-like receptor (TLR) signaling. Transferrin level in germ-free and broad-spectrum antibiotics-treated mice is much less than that in normal mice. Transferrin is found to silence TLR signaling complex by directly interacting with CD14, a co-receptor of many TLRs. Transferrin knock-down impaired host tolerogenic responses as well as broad-spectrum antibiotics treatment. Our findings reveal that commensal bacteria up-regulate and beneficially use host transferrin as a negative regulator of TLR signaling to shape host immunity and contribute for intestinal tolerance.

immunology↗

bioRxiv2020

Genetic Variants and Functional Pathways Associated with Resilience to Alzheimer's Disease

Approximately 30% of older adults exhibit the neuropathologic features of Alzheimers disease (AD) without signs of cognitive impairment. Yet, little is known about the genetic factors that allow these potentially resilient individuals to remain cognitively normal in the face of substantial neuropathology. We performed a large, genome-wide association study (GWAS) of two previously validated metrics of cognitive resilience quantified using a latent variable modeling approach and representing better-than-predicted cognitive performance for a given level of neuropathology. Data were harmonized across 5,108 participants from a clinical trial of AD and three longitudinal cohort studies of cognitive aging. All analyses were run across all participants and repeated restricting the sample to individuals with normal cognition to identify variants at the earliest stages of disease. As expected, all resilience metrics were genetically correlated with cognitive performance and education attainment traits (p-values<2.5x10-20), and we observed novel correlations with neuropsychiatric conditions (p-values<7.9x10-4). Notably, neither resilience metric was genetically correlated with clinical AD (p-values>0.42) nor associated with APOE (p-values>0.13). In single variant analyses, we observed a genome-wide significant locus among participants with normal cognition on chromosome 18 upstream of ATP8B1 (index SNP rs2571244, MAF=0.08, p=2.3x10-8). The top variant at this locus (rs2571244) was significantly associated with methylation in prefrontal cortex tissue at multiple CpG sites, including one just upstream of ATPB81 (cg19596477; p=2x10-13). Overall, this comprehensive genetic analysis of resilience implicates a putative role of vascular risk, metabolism, and mental health in protection from the cognitive consequences of neuropathology, while also providing evidence for a novel resilience gene along the bile acid metabolism pathway. Furthermore, the genetic architecture of resilience appears to be distinct from that of clinical AD, suggesting that a shift in focus to molecular contributors to resilience may identify novel pathways for therapeutic targets.

genetics↗

bioRxiv2020

Cerebrospinal fluid metabolomics identifies 19 brain-related phenotype associations

Advances in technology have allowed for the study of metabolomics in the context of disease, enabling the discovery of new potential risk factors, diagnostic markers, and drug targets. For neurological and psychiatric phenotypes, the cerebrospinal fluid (CSF) is of particular biomedical importance as it is in direct contact with the brain and spinal cord. However, the CSF metabolome is difficult to study on a large scale due to the relative complexity of the procedure needed to collect the fluid compared to blood or urine studies. Here, we present a metabolome-wide association study (MWAS), an analysis using individual-level genetic and metabolomic data from two cohorts to impute metabolites into large samples with genome-wide association summary statistics. We conducted a metabolome-wide genome-wide association analysis with 338 CSF metabolites, identifying 16 genotype-metabolite associations, 6 of which were novel. Using these results, we then built prediction models for all available CSF metabolites and tested for associations with 27 neurological and psychiatric phenotypes in large cohorts, identifying 19 significant CSF metabolite-phenotype associations. Our results demonstrate the potential of MWAS to overcome the logistic challenges inherent in cerebrospinal fluid research to study the role of metabolomics in brain-related phenotypes and the feasibility of this framework for similar studies of omic data in scarce sample types.

genomics↗

bioRxiv2019

A/T/N polygenic risk score for cognitive decline in old age

INTRODUCTIONWe developed a novel polygenic risk score (PRS) based on the A/T/N (amyloid plaques (A), phosphorylated tau tangles (T), and neurodegeneration (N)) framework and compared a PRS based on clinical AD diagnosis to assess which was a better predictor of cognitive decline. METHODSWe used summary statistics from genome wide association studies of cerebrospinal fluid amyloid-{beta} (A{beta}42) and phosphorylated-tau (ptau181), left hippocampal volume (LHIPV), and late-onset AD dementia to calculate PRS for 1181 participants in the Alzheimers Disease Neuroimaging Initiative (ADNI). Individual PRS were averaged to generate a composite A/T/N PRS. We assessed the association of PRS with baseline and longitudinal cognitive composites of executive function and memory. RESULTSThe A/T/N PRS showed superior predictive performance on AD biomarkers and executive function decline compared to the clinical AD PRS. DISCUSSIONResults suggest that integration of genetic risk across AD biomarkers may improve prediction of disease progression. Research in ContextO_ST_ABSSystematic ReviewC_ST_ABSAuthors reviewed relevant literature using PubMed and Google Scholar. Key studies that generated and validated polygenic risk scores (PRS) for clinical and pathologic AD were cited. PRS scores have been increasingly used in the literature but clinical utility continues to be questioned. InterpretationIn the current research landscape concerning PRS clinical utility in the AD space, there is room for model improvement and our hypothesis was that a PRS with integrated risk for AD biomarkers could yield a better model for cognitive decline. Future DirectionsThis study serves as proof-of-concept that encourages future study of integrated PRS across disease markers and utility in taking an A/T/N (amyloidosis, tauopathy and neurodegeneration) focused approach to genetic risk for cognitive decline and AD.

genomics↗

bioRxiv2019

Transcriptome-wide transmission disequilibrium analysis identifies novel risk genes for autism spectrum disorder

Recent advances in consortium-scale genome-wide association studies (GWAS) have highlighted the involvement of common genetic variants in autism spectrum disorder (ASD), but our understanding of their etiologic roles, especially the interplay with rare variants, is incomplete. In this work, we introduce an analytical framework to quantify the transmission disequilibrium of genetically regulated gene expression from parents to offspring. We applied this framework to conduct a transcriptome-wide association study (TWAS) on 7,805 ASD proband-parent trios, and replicated our findings using 35,740 independent samples. We identified 31 associations at the transcriptome-wide significance level. In particular, we identified POU3F2 (p=2.1e-7), a transcription factor (TF) mainly expressed in developmental brain. TF targets regulated by POU3F2 showed a 2.1-fold enrichment for known ASD genes (p=4.6e-5) and a 2.7-fold enrichment for loss-of-function de novo mutations in ASD probands (p=7.1e-5). These results provide a clear example of the connection between ASD genes affected by very rare mutations and an unlinked key regulator affected by common genetic variations.

genetics↗

bioRxiv2019

Detecting Local Genetic Correlations with Scan Statistics

Genetic correlation analysis has quickly gained popularity in the past few years and provided insights into the genetic etiology of numerous complex diseases. However, existing approaches oversimplify the shared genetic architecture between different phenotypes and cannot effectively identify precise genetic regions contributing to the genetic correlation. In this work, we introduce LOGODetect, a powerful and efficient statistical method to identify small genome segments harboring local genetic correlation signals. LOGODetect automatically identifies genetic regions showing consistent associations with multiple phenotypes through a scan statistic approach. It uses summary association statistics from genome-wide association studies (GWAS) as input and is robust to sample overlap between studies. Applied to five phenotypically distinct but genetically correlated psychiatric disorders, we identified 49 non-overlapping genome regions associated with multiple disorders, including multiple hub regions showing concordant effects on more than two disorders. Our method addresses critical limitations in existing analytic strategies and may have wide applications in post-GWAS analysis.

genetics↗

bioRxiv2019

Fine-tuning Polygenic Risk Scores with GWAS Summary Statistics

Polygenic risk scores (PRSs) have wide applications in human genetics research. Notably, most PRS models include tuning parameters which improve predictive performance when properly selected. However, existing model-tuning methods require individual-level genetic data as the training dataset or as a validation dataset independent from both training and testing samples. These data rarely exist in practice, creating a significant gap between PRS methodology and applications. Here, we introduce PUMAS (Parameter-tuning Using Marginal Association Statistics), a novel method to fine-tune PRS models using summary statistics from genome-wide association studies (GWASs). Through extensive simulations, external validations, and analysis of 65 traits, we demonstrate that PUMAS can perform a variety of model-tuning procedures (e.g. cross-validation) using GWAS summary statistics and can effectively benchmark and optimize PRS models under diverse genetic architecture. On average, PUMAS improves the predictive R2 by 205.6% and 62.5% compared to PRSs with arbitrary p-value cutoffs of 0.01 and 1, respectively. Applied to 211 neuroimaging traits and Alzheimers disease, we show that fine-tuned PRSs will significantly improve statistical power in downstream association analysis. We believe our method resolves a fundamental problem without a current solution and will greatly benefit genetic prediction applications.

genetics↗

bioRxiv2019

Genome-wide quantitative trait loci mapping on Verticilliumw

Cotton Verticillium wilt (VW) is a devastating disease seriously affecting fiber yield and quality, and the most effective and economical prevention measure at present is selection and extension of Gossypium varieties harboring high resistant VW. However, multiple attempts to improve the VW resistance of the most widely cultivated Upland cotton have brought in little significant progress, and it seems necessary and urgent to develop Chromosome segment substitution lines (CSSLs) for merging the superior genes related with high yield and wide adaptation from G. hirsutum and VW resistance and excellent fiber quality from G. barbadense. In this study, 300 CSSLs were chosen from the developed BC5F3:5 CSSLs constructed by G. hirsutum CCRI36 and G. barbadense Hai1 to conduct quantitative trait locus (QTL) mapping on VW resistance, and a total of 53 QTLs relevant to VW disease index (DI) were identified together with the phenotypic data of 2 years investigations in two fields with two replications per year. All the QTLs were distributed on 20 chromosomes with phenotypic variation of 3.74-11.89%, of which 29 stable ones were consistent in at least two environments. Based on Meta-analysis on the 53 QTLs, 43 novel ones were identified, while 10 ones consistent to previously identified QTLs. Meanwhile, 32 QTL hotspot regions were detected, including 15 ones were novel. This study concentrates on QTL identification and screening hotspot region related with VW in the 300 CSSLs, which lay a solid platform not only for revealing the genetic and molecular mechanisms of VW resistance, but also for further fine mapping, gene cloning and molecular designing in breeding program for resistant cotton varieties.

plant biology↗

bioRxiv2019

Evidence for a deep, distributed and dynamic semantic code in human ventral anterior temporal cortex

How does the human brain encode semantic information about objects? This paper reconciles two seemingly contradictory views. The first proposes that local neural populations independently encode semantic features; the second, that semantic representations arise as a dynamic distributed code that changes radically with stimulus processing. Combining simulations with a well-known neural network model of semantic memory, multivariate pattern classification, and human electrocorticography, we find that both views are partially correct: semantic information is distributed across ventral temporal cortex in a dynamic code that possesses stable feature-like elements in posterior regions but with elements that change rapidly and nonlinearly in anterior regions. This pattern is consistent with the view that anterior temporal lobes serve as a deep cross-modal "hub" in an interactive semantic network, and more generally suggests that tertiary association cortices may adopt dynamic distributed codes difficult to detect with common brain imaging methods.

neuroscience↗

bioRxiv2019

A Single-Cell Immune Atlas of Triple Negative Breast Cancer Reveals Novel Immune Cell Subsets

Triple-negative breast cancer (TNBC) represents the most aggressive breast cancer subtype, which recently attracts great interest for immune therapeutic development. In this context, in-depth understanding of TNBC immune landscape is highly demanded. Here we report single-cell RNA sequencing results of 9683 tumor-infiltrated immune cells isolated from 14 treatment naive TNBC tumors, where 22 immune cell subsets, including T cells, macrophages, B cells, and DCs have been characterized. We identify a new T cell subset, CD8+CXCL8+ naive T cell, which associates with poor survival. A novel immune cell subset comprised of TCR+ macrophages, is found to be widely distributed in TNBC tumors. Further analyses reveal an up-regulation of molecules associated with TCR signaling and cytotoxicity in these immune cells, indicating TCR signaling activation. Altogether, our study provides a valuable resource to understand the immune ecosystem of TNBC. The novel immune cell subsets reported herein might be functionally important in cancer immunity.\n\nSIGNIFICANCEThis work demonstrates a single-cell transcriptome atlas of immune cells in treatment naive TNBC tumors, revealing novel immune cell subsets. This study provides a valuable resource to understand the immune ecosystem of TNBC, which will be helpful for the immunotherapeutic strategy design of TNBC.

immunology↗