A Bayesian fine-mapping model using a continuous global-local shrinkage prior with applications in prostate cancer analysis.

The aim of fine mapping is to identify genetic variants causally contributing to complex traits or diseases. Existing fine-mapping methods employ Bayesian discrete mixture priors and depend on a pre-specified maximum number of causal variants, which may lead to sub-optimal solutions. In this work, we propose a Bayesian fine-mapping method called h2-D2, utilizing a continuous global-local shrinkage prior. We also present an approach to define credible sets of causal variants in continuous prior settings. Simulation studies demonstrate that h2-D2 outperforms current state-of-the-art fine-mapping methods such as SuSiE and FINEMAP in accurately identifying causal variants and estimating their effect sizes. We further applied h2-D2 to prostate cancer analysis and discovered some previously unknown causal variants. In addition, we inferred 369 target genes associated with the detected causal variants and several pathways that were significantly over-represented by these genes, shedding light on their potential roles in prostate cancer development and progression.

Transcriptomics of Hirschsprung disease patient-derived enteric neural crest cells reveals a role for oxidative phosphorylation.

Hirschsprung disease is characterized by the absence of enteric neurons caused by the defects of enteric neural crest cells, leading to intestinal obstruction. Here, using induced pluripotent stem cell-based models of Hirschsprung and single-cell transcriptomic analysis, we identify a gene set of 118 genes commonly dysregulated in all patient enteric neural crest cells, and suggest HDAC1 may be a key regulator of these genes. Furthermore, upregulation of RNA splicing mediators and enhanced alternative splicing events are associated with severe form of Hirschsprung. In particular, the higher inclusion rate of exon 9 in PTBP1 and the perturbed expression of a PTBP1-target, PKM, are significantly enriched in these patient cells, and associated with the defective oxidative phosphorylation and impaired neurogenesis. Hedgehog-induced oxidative phosphorylation significantly enhances the survival and differentiation capacity of patient cells. In sum, we define various factors associated with Hirschsprung pathogenesis and demonstrate the implications of oxidative phosphorylation in enteric neural crest development and HSCR pathogenesis.

Whole genome sequencing reveals epistasis effects within RET for Hirschsprung disease.

Common variants in RET and NRG1 have been associated with Hirschsprung disease (HSCR), a congenital disorder characterised by incomplete innervation of distal gut, in East Asian (EA) populations. However, the allelic effects so far identified do not fully explain its heritability, suggesting the presence of epistasis, where effect of one genetic variant differs depending on other (modifier) variants. Few instances of epistasis have been documented in complex diseases due to modelling complexity and data challenges. We proposed four epistasis models to comprehensively capture epistasis for HSCR between and within RET and NRG1 loci using whole genome sequencing (WGS) data in EA samples. 65 variants within the Topologically Associating Domain (TAD) of RET demonstrated significant epistasis with the lead enhancer variant (RET+3; rs2435357). These epistatic variants formed two linkage disequilibrium (LD) clusters represented by rs2506026 and rs2506028 that differed in minor allele frequency and the best-supported epistatic model. Intriguingly, rs2506028 is in high LD with one cis-regulatory variant (rs2506030) highlighted previously, suggesting that detected epistasis might be mediated through synergistic effects on transcription regulation of RET. Our findings demonstrated the advantages of WGS data for detecting epistasis, and support the presence of interactive effects of regulatory variants in RET for HSCR.

Evaluation of bi-directional causal association between depression and cardiovascular diseases: a Mendelian randomization study.

BACKGROUND: Depression and cardiovascular disease (CVD) are associated with each other but their relationship remains unclear. We aim to determine whether genetic predisposition to depression are causally linked to CVD [including coronary artery disease (CAD), myocardial infarction (MI), stroke and atrial fibrillation (AF)]. METHODS: Using summary statistics from the largest genome-wide association studies (GWAS) or GWAS meta-analysis of depression (primary analysis: n = 500 199), broad depression (help-seeking behavior for problems with nerves, anxiety, tension or depression; secondary analysis: n = 322 580), CAD (n = 184 305), MI (n = 171 875), stroke (n = 446 696) and AF (n = 1 030 836), genetic correlation was tested between two depression phenotypes and CVD [MI, stroke and AF (not CAD as its correlation was previously confirmed)]. Causality was inferred between correlated traits by Mendelian Randomization analyses. RESULTS: Both depression phenotypes were genetically correlated with MI (depression: rG = 0.169; p = 9.03 × 10-9; broad depression: rG = 0.123; p = 1 × 10-4) and AF (depression: rG = 0.112; p = 7.80 × 10-6; broad depression: rG = 0.126; p = 3.62 × 10-6). Genetically doubling the odds of depression was causally associated with increased risk of CAD (OR = 1.099; 95% CI 1.031-1.170; p = 0.004) and MI (OR = 1.146; 95% CI 1.070-1.228; p = 1.05 × 10-4). Adjustment for blood lipid levels/smoking status attenuated the causality between depression and CAD/MI. Null causal association was observed for CVD on depression. A similar pattern of results was observed in the secondary analysis for broad depression. CONCLUSIONS: Genetic predisposition to depression may have positive causal roles on CAD/MI. Genetic susceptibility to self-awareness of mood problems may be a strong causal risk factor of CAD/MI. Blood lipid levels and smoking may potentially mediate the causal pathway. Prevention and early diagnosis of depression are important in the management of CAD/MI.

Single-cell RNA sequencing shows the immunosuppressive landscape and tumor heterogeneity of HBV-associated hepatocellular carcinoma.

Interaction between tumor cells and immune cells in the tumor microenvironment is important in cancer development. Immune cells interact with the tumor cells to shape this process. Here, we use single-cell RNA sequencing analysis to delineate the immune landscape and tumor heterogeneity in a cohort of patients with HBV-associated human hepatocellular carcinoma (HCC). We found that tumor-associated macrophages suppress tumor T cell infiltration and TIGIT-NECTIN2 interaction regulates the immunosuppressive environment. The cell state transition of immune cells towards a more immunosuppressive and exhaustive status exemplifies the overall cancer-promoting immunocellular landscape. Furthermore, the heterogeneity of global molecular profiles reveals co-existence of intra-tumoral and inter-tumoral heterogeneity, but is more apparent in the latter. This analysis of the immunosuppressive landscape and intercellular interactions provides mechanistic information for the design of efficacious immune-oncology treatments in hepatocellular carcinoma.

An Asian-specific MPL genetic variant alters JAK-STAT signaling and influences platelet count in the population.

Genomic discovery efforts for hematological traits have been successfully conducted through genome-wide association study on samples of predominantly European ancestry. We sought to conduct unbiased genetic discovery for coding variants that influence hematological traits in a Han Chinese population. A total of 5257 Han Chinese subjects from Beijing, China were included in the discovery cohort and analyzed by an Illumina ExomeChip array. Replication analyses were conducted in 3827 independent Chinese subjects. We analyzed 12 hematological traits and identified 22 exome-wide significant single-nucleotide polymorphisms (SNP)-trait associations with 15 independent SNPs. Our study provides replication for two associations previously reported but not replicated. Further, one association was identified and replicated in the current study, of a coding variant in the myeloproliferative leukemia (MPL) gene, c.793C > T, p.Leu265Phe (L265F) with increased platelet count (ß = 20.6 109 cells/l, Pmeta-analysis = 2.6 × 10-13). This variant is observed at ~2% population frequency in East Asians, whereas it has not been reported in gnomAD European or African populations. Functional analysis demonstrated that expression of MPL L265F in Ba/F3 cells resulted in enhanced phosphorylation of Stat3 and ERK1/2 as compared with the reference MPL allele, supporting altered activation of the JAK-STAT signal transduction pathway as the mechanism underlying the novel association between MPL L265F and platelet count.

C-terminal truncated HBx initiates hepatocarcinogenesis by downregulating TXNIP and reprogramming glucose metabolism.

Chronic hepatitis B virus (HBV) infection is strongly associated with the initiation and development of hepatocellular carcinoma (HCC). However, the genetic alterations and pathogenesis mechanisms remain significantly unexplored, especially for HBV-induced metabolic reprogramming. Analysis of integration breakpoints in HBV-positive HCC samples revealed the preferential clustering pattern within the 3'-end of X gene in the HBV genome, leading to the production of C-terminal truncated X protein (Ct-HBx). In this study, we not only characterized the oncogenic role of two Ct-HBx (HBx-120 and HBx-134) via in vitro and in vivo functional assays but also deciphered their underlying molecular mechanisms. Gene expression profiling by transcriptome sequencing identified potential targets of Ct-HBx and novel malignant hallmarks such as glycolysis, cell cycle, and m-TORC1 signaling in Ct-HBx-expressing cells. TXNIP, a well-established regulator of glucose metabolism, was shown to be downregulated by Ct-HBx and play a pivotal role in Ct-HBx-mediated HCC progression. Suppression of TXNIP is frequently observed in HCC patients with Ct-HBx expression and significantly (P = 0.015) correlated to a poorer prognosis. Re-introduction of TXNIP attenuated the metabolic reprogramming induced by the Ct-HBx and inhibited the tumor growth in the mice model. Further study suggested that Ct-HBx could downregulate TXNIP via a transcriptional repressor nuclear factor of activated T cells 2 (NFACT2). Collectively, our findings indicate that TXNIP plays a critical role in Ct-HBx-mediated hepatocarcinogenesis, serving as a novel therapeutic strategy in HCC treatment.

Ultrafast and scalable variant annotation and prioritization with big functional genomics data.

The advances of large-scale genomics studies have enabled compilation of cell type-specific, genome-wide DNA functional elements at high resolution. With the growing volume of functional annotation data and sequencing variants, existing variant annotation algorithms lack the efficiency and scalability to process big genomic data, particularly when annotating whole-genome sequencing variants against a huge database with billions of genomic features. Here, we develop VarNote to rapidly annotate genome-scale variants in large and complex functional annotation resources. Equipped with a novel index system and a parallel random-sweep searching algorithm, VarNote shows substantial performance improvements (two to three orders of magnitude) over existing algorithms at different scales. It supports both region-based and allele-specific annotations and introduces advanced functions for the flexible extraction of annotations. By integrating massive base-wise and context-dependent annotations in the VarNote framework, we introduce three efficient and accurate pipelines to prioritize the causal regulatory variants for common diseases, Mendelian disorders, and cancers.

The support of genetic evidence for cardiovascular risk induced by antineoplastic drugs.

Cardiovascular dysfunction is one of the most common complications of long-term cancer treatment. Growing evidence has shown that antineoplastic drugs can increase cardiovascular risk during cancer therapy, seriously affecting patient survival. However, little is known about the genetic factors associated with the cardiovascular risk of antineoplastic drugs. We established a compendium of genetic evidence that supports cardiovascular risk induced by antineoplastic drugs. Most of this genetic evidence is attributed to causal alleles altering the expression of cardiovascular disease genes. We found that antineoplastic drugs predicted to induce cardiovascular risk are significantly enriched in drugs associated with cardiovascular adverse reactions, including many first-line cancer treatments. Functional experiments validated that retinoid X receptor agonists can reduce triglyceride lipolysis, thus modulating cardiovascular risk. Our results establish a link between the causal allele of cardiovascular disease genes and the direction of pharmacological modulation, which could facilitate cancer drug discovery and clinical trial design.

Whole-genome analysis of noncoding genetic variations identifies multiscale regulatory element perturbations associated with Hirschsprung disease.

It is widely recognized that noncoding genetic variants play important roles in many human diseases, but there are multiple challenges that hinder the identification of functional disease-associated noncoding variants. The number of noncoding variants can be many times that of coding variants; many of them are not functional but in linkage disequilibrium with the functional ones; different variants can have epistatic effects; different variants can affect the same genes or pathways in different individuals; and some variants are related to each other not by affecting the same gene but by affecting the binding of the same upstream regulator. To overcome these difficulties, we propose a novel analysis framework that considers convergent impacts of different genetic variants on protein binding, which provides multiscale information about disease-associated perturbations of regulatory elements, genes, and pathways. Applying it to our whole-genome sequencing data of 918 short-segment Hirschsprung disease patients and matched controls, we identify various novel genes not detected by standard single-variant and region-based tests, functionally centering on neural crest migration and development. Our framework also identifies upstream regulators whose binding is influenced by the noncoding variants. Using human neural crest cells, we confirm cell stage-specific regulatory roles of three top novel regulatory elements on our list, respectively in the RET, RASGEF1A, and PIK3C2B loci. In the PIK3C2B regulatory element, we further show that a noncoding variant found only in the patients affects the binding of the gliogenesis regulator NFIA, with a corresponding up-regulation of multiple genes in the same topologically associating domain.

A joint study of whole exome sequencing and structural MRI analysis in major depressive disorder.

BACKGROUND: Major depressive disorder (MDD) is a leading cause of disability worldwide and influenced by both environmental and genetic factors. Genetic studies of MDD have focused on common variants and have been constrained by the heterogeneity of clinical symptoms. METHODS: We sequenced the exome of 77 cases and 245 controls of Han Chinese ancestry and scanned their brain. Burden tests of rare variants were performed first to explore the association between genes/pathways and MDD. Secondly, parallel Independent Component Analysis was conducted to investigate genetic underpinnings of gray matter volume (GMV) changes of MDD. RESULTS: Two genes (CSMD1, p = 5.32×10-6; CNTNAP5, p = 1.32×10-6) and one pathway (Neuroactive Ligand Receptor Interactive, p = 1.29×10-5) achieved significance in burden test. In addition, we identified one pair of imaging-genetic components of significant correlation (r = 0.38, p = 9.92×10-6). The imaging component reflected decreased GMV in cases and correlated with intelligence quotient (IQ). IQ mediated the effects of GMV on MDD. The genetic component enriched in two gene sets, namely Singling by G-protein coupled receptors [false discovery rate (FDR) q = 3.23×10-4) and Alzheimer Disease Up (FDR q = 6.12×10-4). CONCLUSIONS: Both rare variants analysis and imaging-genetic analysis found evidence corresponding with the neuroinflammation and synaptic plasticity hypotheses of MDD. The mediation of IQ indicates that genetic component may act on MDD through GMV alteration and cognitive impairment.

Methods and resources to access mutation-dependent effects on cancer drug treatment.

In clinical cancer treatment, genomic alterations would often affect the response of patients to anticancer drugs. Studies have shown that molecular features of tumors could be biomarkers predictive of sensitivity or resistance to anticancer agents, but the identification of actionable mutations are often constrained by the incomplete understanding of cancer genomes. Recent progresses of next-generation sequencing technology greatly facilitate the extensive molecular characterization of tumors and promote precision medicine in cancers. More and more clinical studies, cancer cell lines studies, CRISPR screening studies as well as patient-derived model studies were performed to identify potential actionable mutations predictive of drug response, which provide rich resources of molecularly and pharmacologically profiled cancer samples at different levels. Such abundance of data also enables the development of various computational models and algorithms to solve the problem of drug sensitivity prediction, biomarker identification and in silico drug prioritization by the integration of multiomics data. Here, we review the recent development of methods and resources that identifies mutation-dependent effects for cancer treatment in clinical studies, functional genomics studies and computational studies and discuss the remaining gaps and future directions in this area.

regBase: whole genome base-wise aggregation and functional prediction for human non-coding regulatory variants.

Predicting the functional or pathogenic regulatory variants in the human non-coding genome facilitates the interpretation of disease causation. While numerous prediction methods are available, their performance is inconsistent or restricted to specific tasks, which raises the demand of developing comprehensive integration for those methods. Here, we compile whole genome base-wise aggregations, regBase, that incorporate largest prediction scores. Building on different assumptions of causality, we train three composite models to score functional, pathogenic and cancer driver non-coding regulatory variants respectively. We demonstrate the superior and stable performance of our models using independent benchmarks and show great success to fine-map causal regulatory variants on specific locus or at base-wise resolution. We believe that regBase database together with three composite models will be useful in different areas of human genetic studies, such as annotation-based casual variant fine-mapping, pathogenic variant discovery as well as cancer driver mutation identification. regBase is freely available at https://github.com/mulinlab/regBase.

Single-cell transcriptomics reveals the landscape of intra-tumoral heterogeneity and stemness-related subpopulations in liver cancer.

Hepatocellular carcinoma (HCC) is heterogeneous, rendering its current curative treatments ineffective. The emergence of single-cell genomics represents a powerful strategy in delineating the complex molecular landscapes of cancers. In this study, we demonstrated the feasibility and merit of using single-cell RNA sequencing to dissect the intra-tumoral heterogeneity and analyze the single-cell transcriptomic landscape to detect rare cell subpopulations of significance. Exploration of the inter-relationship among liver cancer stem cell markers showed two distinct major cell populations according to EPCAM expression, and the EPCAM+ cells had upregulated expression of multiple oncogenes. We also identified a CD24+/CD44+-enriched cell subpopulation within the EPCAM+ cells which had specific signature genes and might indicate a novel stemness-related cell subclone in HCC. Notably, knockdown of signature gene CTSE for CD24+/CD44+ cells significantly reduced self-renewal ability on HCC cells in vitro and the stemness-related role of CTSE was further confirmed by in vivo tumorigenicity assays in nude mice. In summary, single-cell genomics is a useful tool to delineate HCC intratumoral heterogeneity at better resolution. It can identify rare but important cell subpopulations, and may guide better precision medicine in the long run.

Chemotherapy-Induced Cognitive Impairment Is Associated with Cytokine Dysregulation and Disruptions in Neuroplasticity.

Chemotherapy-induced cognitive impairment, often referred to as "chemobrain," is a common side effect. In this study, mice received three intraperitoneal injections of a combination of docetaxel, adriamycin, and cyclophosphamide (DAC) at 2-day intervals. A water maze test was used to examine cognitive performance, and manganese-enhanced magnetic resonance imaging (MEMRI) was used to examine hippocampal neuronal activity. The whole brain, prefrontal cortex, hippocampus, and blood samples were then collected for cytokine measurement. The DAC-treated mice displayed a significantly shorter duration spent in and fewer entries into the target quadrant of the water maze than the control mice and a pronounced decrease in MEMRI signal intensity in the hippocampal subregions. In a separate experiment using in vivo transcranial two-photon imaging, DAC markedly eliminated dendritic spines without changing the rate of spine formation, leading to a striking loss of spines in the medial prefrontal cortex. DAC treatment resulted in significant elevations in the levels of the proinflammatory cytokines interleukin 6 (IL-6) and tumor necrosis factor-α (TNF-α) and in significant decreases in the levels of the anti-inflammatory cytokines IL-4 and IL-10 in most of the sera and brain tissues examined. The IL-6 and TNF-α levels of several sera and brain tissues showed strong inverse correlations with the duration and number of entries in the target quadrant of the water maze and with the hippocampal MEMRI signal intensity, but also showed striking positive correlations with spine elimination and loss. These results indicate that chemobrain is associated with cytokine dysregulation and disrupted neuroplasticity of the brain.

Genetic Regulation of Pigment Epithelium-Derived Factor (PEDF): An Exome-Chip Association Analysis in Chinese Subjects With Type 2 Diabetes.

Elevated circulating levels of pigment epithelium-derived factor (PEDF) have been reported in patients with type 2 diabetes (T2D) and its associated microvascular complications. This study aimed to 1) identify the genetic determinants influencing circulating PEDF levels in a clinical setting of T2D, 2) examine the relationship between circulating PEDF and diabetes complications, and 3) explore the causal relationship between PEDF and diabetes complications. An exome-chip association study on circulating PEDF levels was conducted in 5,385 Chinese subjects with T2D. A meta-analysis of the association results of the discovery stage (n = 2,936) and replication stage (n = 2,449) was performed. The strongest association was detected at SERPINF1 (p.Met72Thr; Pcombined = 2.06 × 10-57; ß [SE] -0.33 [0.02]). Two missense variants of SMYD4 (p.Arg131Ile; Pcombined = 7.56 × 10-25; ß [SE] 0.21 [0.02]) and SERPINF2 (p.Arg33Trp; Pcombined = 8.22 × 10-10; ß [SE] -0.15 [0.02]) showed novel associations at genome-wide significance. Elevated circulating PEDF levels were associated with increased risks of diabetic nephropathy and sight-threatening diabetic retinopathy. Mendelian randomization analysis showed suggestive evidence of a protective role of PEDF on sight-threatening diabetic retinopathy (P = 0.085). Our study provided new insights into the genetic regulation of PEDF and further support for its potential application as a biomarker for diabetic nephropathy and sight-threatening diabetic retinopathy. Further studies to explore the causal relationship of PEDF with diabetes complications are warranted.

Age-Biomarkers-Clinical Risk Factors for Prediction of Cardiovascular Events in Patients With Coronary Artery Disease.

Objective- In patients with stable coronary artery disease, conventional risk factors provide limited incremental predictive value for cardiovascular events. We sought to investigate whether a panel of cardiometabolic biomarkers alone or combined with conventional risk factors would exhibit incremental value in the prediction of cardiovascular events. Approach and Results- In the discovery cohort, we measured serum adiponectin, A-FABP (adipocyte fatty acid-binding protein), lipocalin-2, FGF (fibroblast growth factor)-19 and 21, plasminogen activator inhibitor-1, and retinol-binding protein-4 in 1166 Chinese coronary artery disease patients. After a median follow-up of 35 months, 170 patients developed new-onset major adverse cardiovascular events (MACE). In the model with age ≥65 years and conventional risk factors, area under the curve for predicting MACE was 0.68. Addition of lipocalin-2 to the age-clinical risk factor model improved predictive accuracy (area under the curve=0.73). Area under the curve further increased to 0.75 when a combination of lipocalin-2, A-FABP, and FGF-19 was added to yield age-biomarkers-clinical risk factor model. The adjusted hazard ratio on MACEs for lipocalin-2, A-FABP, and FGF-19 levels above optimal cutoffs were 2.23 (95% CI, 1.62-3.08), 1.99 (95% CI, 1.43-2.76), and 1.65 (95% CI, 1.15-2.35), respectively. In the validation cohort of 1262 coronary artery disease patients with type 2 diabetes mellitus, the age-biomarkers-clinical risk factor model was confirmed to provide good discrimination and calibration over the conventional risk factor alone for prediction of MACE. Conclusions- A combination of the 3 biomarkers, lipocalin-2, A-FABP, and FGF-19, with clinical risk factors to yield the age-biomarkers-clinical risk factor model provides an optimal and validated prediction of new-onset MACE in patients with stable coronary artery disease.

Identification of Genes Associated With Hirschsprung Disease, Based on Whole-Genome Sequence Analysis, and Potential Effects on Enteric Nervous System Development.

BACKGROUND & AIMS: Hirschsprung disease, or congenital aganglionosis, is believed to be oligogenic-that is, caused by multiple genetic factors. We performed whole-genome sequence analyses of patients with Hirschsprung disease to identify genetic factors that contribute to disease development and analyzed the functional effects of these variants. METHODS: We performed whole-genome sequence analyses of 443 patients with short-segment disease, recruited from hospitals in China and Vietnam, and 493 ethnically matched individuals without Hirschsprung disease (controls). We performed genome-wide association analyses and gene-based rare-variant burden tests to identify rare and common disease-associated variants and study their interactions. We obtained induced pluripotent stem cell (iPSC) lines from 4 patients with Hirschsprung disease and 2 control individuals, and we used these to generate enteric neural crest cells for transcriptomic analyses. We assessed the neuronal lineage differentiation capability of iPSC-derived enteric neural crest cells using an in vitro differentiation assay. RESULTS: We identified 4 susceptibility loci, including 1 in the phospholipase D1 gene (PLD1) (P = 7.4 × 10-7). The patients had a significant excess of rare protein-altering variants in genes previously associated with Hirschsprung disease and in the ß-secretase 2 gene (BACE2) (P = 2.9 × 10-6). The epistatic effects of common and rare variants across these loci provided a sensitized background that increased risk for the disease. In studies of the iPSCs, we observed common and distinct pathways associated with variants in RET that affect risk. In functional assays, we found variants in BACE2 to protect enteric neurons from apoptosis. We propose that alterations in BACE1 signaling via amyloid ß precursor protein and BACE2 contribute to pathogenesis of Hirschsprung disease. CONCLUSIONS: In whole-genome sequence analyses of patients with Hirschsprung disease, we identified rare and common variants associated with disease risk. Using iPSC cells, we discovered some functional effects of these variants.

Trans-Ethnic Polygenic Analysis Supports Genetic Overlaps of Lumbar Disc Degeneration With Height, Body Mass Index, and Bone Mineral Density.

Lumbar disc degeneration (LDD) is age-related break-down in the fibrocartilaginous joints between lumbar vertebrae. It is a major cause of low back pain and is conventionally assessed by magnetic resonance imaging (MRI). Like most other complex traits, LDD is likely polygenic and influenced by both genetic and environmental factors. However, genome-wide association studies (GWASs) of LDD have uncovered few susceptibility loci due to the limited sample size. Previous epidemiology studies of LDD also reported multiple heritable risk factors, including height, body mass index (BMI), bone mineral density (BMD), lipid levels, etc. Genetics can help elucidate causality between traits and suggest loci with pleiotropic effects. One such approach is polygenic score (PGS) which summarizes the effect of multiple variants by the summation of alleles weighted by estimated effects from GWAS. To investigate genetic overlaps of LDD and related heritable risk factors, we calculated the PGS of height, BMI, BMD and lipid levels in a Chinese population-based cohort with spine MRI examination and a Japanese case-control cohort of lumbar disc herniation (LDH) requiring surgery. Because most large-scale GWASs were done in European populations, PGS of corresponding traits were created using weights from European GWASs. We calibrated their prediction performance in independent Chinese samples, then tested associations with MRI-derived LDD scores and LDH affection status. The PGS of height, BMI, BMD and lipid levels were strongly associated with respective phenotypes in Chinese, but phenotype variances explained were lower than in Europeans which would reduce the power to detect genetic overlaps. Despite of this, the PGS of BMI and lumbar spine BMD were significantly associated with LDD scores; and the PGS of height was associated with the increased the liability of LDH. Furthermore, linkage disequilibrium score regression suggested that, osteoarthritis, another degenerative disorder that shares common features with LDD, also showed genetic correlations with height, BMI and BMD. The findings suggest a common key contribution of biomechanical stress to the pathogenesis of LDD and will direct the future search for pleiotropic genes.