Inferring causal direction between two traits using R2 with application to transcriptome-wide association studies.

In Mendelian randomization, two single SNP-trait correlation-based methods have been developed to infer the causal direction between an exposure (e.g., a gene) and an outcome (e.g., a trait), called MR Steiger's method and its recent extension called Causal Direction-Ratio (CD-Ratio). Here we propose an approach based on R2, the coefficient of determination, to combine information from multiple (possibly correlated) SNPs to simultaneously infer the presence and direction of a causal relationship between an exposure and an outcome. Our proposed method generalizes Steiger's method from using a single SNP to multiple SNPs as IVs. It is especially useful in transcriptome-wide association studies (TWASs) (and similar applications) with typically small sample sizes for gene expression (or another molecular trait) data, providing a more flexible and powerful approach to inferring causal directions. It can be applied to GWAS summary data with a reference panel. We also discuss the influence of invalid IVs and introduce a new approach called R2S to select and remove invalid IVs (if any) to enhance the robustness. We compared the performance of the proposed method with existing methods in simulations to demonstrate its advantages. We applied the methods to identify causal genes for high/low-density lipoprotein cholesterol (HDL/LDL) using the individual-level GTEx gene expression data and UK Biobank GWAS data. The proposed method was able to confirm some well-known causal genes while identifying some novel ones. Additionally, we illustrated an application of the proposed method to GWAS summary to infer causal relationships between HDL/LDL and stroke/coronary artery disease (CAD).

A novel multivariable Mendelian randomization framework to disentangle highly correlated exposures with application to metabolomics.

Mendelian randomization (MR) utilizes genome-wide association study (GWAS) summary data to infer causal relationships between exposures and outcomes, offering a valuable tool for identifying disease risk factors. Multivariable MR (MVMR) estimates the direct effects of multiple exposures on an outcome. This study tackles the issue of highly correlated exposures commonly observed in metabolomic data, a situation where existing MVMR methods often face reduced statistical power due to multicollinearity. We propose a robust extension of the MVMR framework that leverages constrained maximum likelihood (cML) and employs a Bayesian approach for identifying independent clusters of exposure signals. Applying our method to the UK Biobank metabolomic data for the largest Alzheimer disease (AD) cohort through a two-sample MR approach, we identified two independent signal clusters for AD: glutamine and lipids, with posterior inclusion probabilities (PIPs) of 95.0% and 81.5%, respectively. Our findings corroborate the hypothesized roles of glutamate and lipids in AD, providing quantitative support for their potential involvement.

Collider bias correction for multiple covariates in GWAS using robust multivariable Mendelian randomization.

Genome-wide association studies (GWAS) have identified many genetic loci associated with complex traits and diseases in the past 20 years. Multiple heritable covariates may be added into GWAS regression models to estimate direct effects of genetic variants on a focal trait, or to improve the power by accounting for environmental effects and other sources of trait variations. When one or more covariates are causally affected by both genetic variants and hidden confounders, adjusting for them in GWAS will produce biased estimation of SNP effects, known as collider bias. Several approaches have been developed to correct collider bias through estimating the bias by Mendelian randomization (MR). However, these methods work for only one covariate, some of which utilize MR methods with relatively strong assumptions, both of which may not hold in practice. In this paper, we extend the bias-correction approaches in two aspects: first we derive an analytical expression for the collider bias in the presence of multiple covariates, then we propose estimating the bias using a robust multivariable MR (MVMR) method based on constrained maximum likelihood (called MVMR-cML), allowing the presence of invalid instrumental variables (IVs) and correlated pleiotropy. We also established the estimation consistency and asymptotic normality of the new bias-corrected estimator. We conducted simulations to show that all methods mitigated collider bias under various scenarios. In real data analyses, we applied the methods to two GWAS examples, the first a GWAS of waist-hip ratio with adjustment for only one covariate, body-mass index (BMI), and the second a GWAS of BMI adjusting metabolomic principle components as multiple covariates, illustrating the effectiveness of bias correction.

Are trait-associated genes clustered together in a gene network?

Genome-wide association studies (GWAS) have provided an abundance of information about the genetic variants and their loci that are associated to complex traits and diseases. However, due to linkage disequilibrium (LD) and noncoding regions of loci, it remains a challenge to pinpoint the causal genes. Gene network-based approaches, paired with network diffusion methods, have been proposed to prioritize causal genes and to boost statistical power in GWAS based on the assumption that trait-associated genes are clustered in a gene network. Due to the difficulty in mapping trait-associated variants to genes in GWAS, this assumption has never been directly or rigorously tested empirically. On the other hand, whole exome sequencing (WES) data focuses on the protein-coding regions, directly identifying trait-associated genes. In this study, we tested the assumption by leveraging the recently available exome-based association statistics from the UK Biobank WES data along with two types of networks. We found that almost all trait-associated genes were significantly more proximal to each other than randomly selected genes within both networks. These results support the assumption that trait-associated genes are clustered in gene networks, which can be further leveraged to boost the power of GWAS such as by introducing less stringent p value thresholds.

Kielin/chordin-like protein deficiency aggravates pressure overload-induced cardiac dysfunction and remodeling via P53/P21/CCNB1 signaling in mice.

Targeting cardiac remodeling is regarded as a key therapeutic strategy for heart failure. Kielin/chordin-like protein (KCP) is a secretory protein with 18 cysteine-rich domains and associated with kidney and liver fibrosis. However, the relationship between KCP and cardiac remodeling remains unclear. Here, we aimed to investigate the role of KCP in cardiac remodeling induced by pressure overload and explore its potential mechanisms. Left ventricular (LV) KCP expression was measured with real-time quantitative PCR, western blotting, and immunofluorescence staining in pressure overload-induced cardiac remodeling in mice. Cardiac function and remodeling were evaluated in wide-type (WT) mice and KCP knockout (KO) mice by echocardiography, which were further confirmed by histological analysis with hematoxylin and eosin and Masson staining. RNA sequence was performed with LV tissue from WT and KO mice to identify differentially expressed genes and related signaling pathways. Primary cardiac fibroblasts (CFs) were used to validate the regulatory role and potential mechanisms of KCP during fibrosis. KCP was down-regulated in the progression of cardiac remodeling induced by pressure overload, and was mainly expressed in fibroblasts. KCP deficiency significantly aggravated pressure overload-induced cardiac dysfunction and remodeling. RNA sequence revealed that the role of KCP deficiency in cardiac remodeling was associated with cell division, cell cycle, and P53 signaling pathway, while cyclin B1 (CCNB1) was the most significantly up-regulated gene. Further investigation in vivo and in vitro suggested that KCP deficiency promoted the proliferation of CFs via P53/P21/CCNB1 pathway. Taken together, these results suggested that KCP deficiency aggravates cardiac dysfunction and remodeling induced by pressure overload via P53/P21/CCNB1 signaling in mice.

Reprogramming Tumor-Associated Macrophages with a Se-Based Core-Satellite Nanoassembly to Enhance Cancer Immunotherapy.

Tumor-associated macrophages (TAMs), as the most prevalent immune cells in the tumor microenvironment, play a pivotal role in promoting tumor development through various signaling pathways. Herein, we have engineered a Se@ZIF-8 core-satellite nanoassembly to reprogram TAMs, thereby enhancing immunotherapy outcomes. When the nanoassembly reaches the tumor tissue, selenium nanoparticles and Zn2+ are released in response to the acidic tumor microenvironment, resulting in a collaborative effort to promote the production of reactive oxygen species (ROS). The generated ROS, in turn, activate the nuclear factor κB (NF-κB) signaling pathway, driving the repolarization of TAMs from M2-type to M1-type, effectively eliminating cancer cells. Moreover, the nanoassembly can induce the immunogenic death of cancer cells through excess ROS to expose calreticulin and boost macrophage phagocytosis. The Se@ZIF-8 core-satellite nanoassembly provides a potential paradigm for cancer immunotherapy by reversing the immunosuppressive microenvironment.

ROCK1 is a multifunctional factor maintaining the primordial follicle reserve and follicular development in mice.

The follicle is the basic structural and functional unit of the ovary in female mammals. The excessive depletion of follicles will lead to diminished ovarian reserve or even premature ovarian failure, resulting in diminished ovarian oogenesis and endocrine function. Excessive follicular depletion is mainly due to loss of primordial follicles. Our analysis of published human ovarian single-cell sequencing results by others revealed a significant increase in rho-associated protein kinase 1 (ROCK1) expression during primordial follicle development. However, the role of ROCK1 in primordial follicle development and maintenance is not clear. This study revealed a gradual increase in ROCK1 expression during primordial follicle activation. Inhibition of ROCK1 resulted in reduced primordial follicle activation, decreased follicular reserve, and delayed development of growing follicles. This effect may be achieved through the HIPPO pathway. The present study indicates that ROCK1 is a key molecule for primordial follicular reserve and follicular development.NEW & NOTEWORTHY ROCK1, one of the Rho GTPases, plays an important role in primordial follicle reserve and follicular development. ROCK1 was primarily expressed in the cytoplasm of oocytes and granulosa cell in mice. Inhibition of ROCK1 significantly reduced the primordial follicle reserve and delayed growing follicle development. ROCK1 regulates primordial follicular reserve and follicle development through the HIPPO signaling pathway. These findings shed new lights on the physiology of sustaining female reproduction.

Loss of AR-regulated AFF3 contributes to prostate cancer progression and reduces ferroptosis sensitivity by downregulating ACSL4 based on single-cell sequencing analysis.

Prostate cancer (PCa) is one of the most common cancers affecting the health of men worldwide. Castration-resistant prostate cancer (CRPC), the advanced and refractory phase of prostate cancer, has multiple mechanisms of resistance to androgen deprivation therapy (ADT) such as AR mutations, aberrant androgen synthase, and abnormal expression of AR-related genes. Based on the research of the AR pathway, new drugs for the treatment of CRPC have been developed in clinical practice, such as Abiraterone and enzalutamide. However, many areas in this pathway are still worth exploring. In this study, single-cell sequencing analysis was utilized to scrutinize significant genes in the androgen receptor (AR) pathway related to CRPC. Our analysis of single-cell sequencing combined with bulk-cell sequencing revealed a substantial downregulation of AR-regulated AFF3 in CRPC. Overexpression of AFF3 restricted the proliferation and migration of prostate cancer cells whilst also increasing their sensitivity towards enzalutamide, while knockdown of AFF3 had the opposite effect. To elucidate the mechanism of tumor inhibition by AFF3, we applied GSVA and GSEA to investigate the metabolic pathways related to AFF3 and revealed that AFF3 had an impact on fatty acids metabolism and ferroptosis through the regulation of ACSL4 protein expression. Based on correlation analysis and flow cytometry, we can speculate that AFF3 can impact the sensitivity of the CRPC cell lines to the ferroptosis inducer (RSL3) by regulating ACSL4. Therefore, our findings may provide new insights into the mechanisms of drug resistance in CRPC, and AFF3 may serve as a novel prognostic biomarker in prostate cancer.

Glowing Octopus-Inspired Nanomachine: A Versatile Aptasensor for Efficient Capture, Imaging, Separation, and NIR-Triggered Release of Cancer Cells.

The separation and analysis of circulating tumor cells (CTCs) in liquid biopsy significantly facilitated clinical cancer diagnosis and personalized therapy. However, current methods face challenges in simultaneous efficient capturing, separation, and imaging of CTCs, and most of the devices cannot be reused/regenerated. We present here an innovative glowing octopus-inspired nanomachine (GOIN), capable of capturing, imaging, separating, and controlling the release of cancer cells from whole blood and normal cells. The GOIN comprises an aptamer-decorated magnetic fluorescent covalent organic framework (COF), which exhibits a strong affinity for nucleolin-overexpressed cancer cells through a multivalent binding effect. The captured cancer cells can be directly imaged using the intrinsic stable fluorescence of the COF layer in the GOIN. Employing magnet and NIR laser assistance enables easy separation and mild photothermal release of CTCs from the normal cells and the nanomachine without compromising cell viability. Moreover, the GOIN demonstrates a reusing capability, as the NIR-triggered CTC release is mild and nondestructive, allowing the GOIN to be reused at least three times.

Thermophoretic Aggregation Imaging of Tumor-Derived Exosomes by CRISPR-Cas13a-Based Nanoprobes.

The inherent heterogeneity of tumor-derived exosomes holds great promise for enhancing the precision of cancer diagnostics. MicroRNAs (miRNAs) encapsulated in tumor-associated exosomes have emerged as valuable biomarkers for the early detection of cancers. Nevertheless, the flexible structure and inherent instability of RNA limit its application in biological diagnostics. The CRISPR-Cas13a system, distinguished by its target-responsive "collateral effect", represents a powerful tool for advancing cancer diagnostics. In this study, we harness the CRISPR-Cas13a system as an innovative signal amplification tool to image cancer-related exosomal miRNA in situ. Furthermore, we capitalize on the thermophoretic aggregation effect exhibited by gold nanoparticles (Au NPs) to consolidate the fluorescent signals generated by the CRISPR-Cas13a system. Subsequently, the developed nanoprobe is applied to detect lung cancer-related exosomal miRNA from human serum, enabling the aggregated visualization of low-abundance cancer exosomes in individuals with lung cancer compared with healthy individuals. This sensitive thermophoretic aggregation assay provides a diagnostic tool for lung cancer in the clinic.

Genetic correlation and causal associations between circulating C-reactive protein levels and lung cancer risk.

PURPOSE: We aimed to characterize genetic correlations and causal associations between circulating C-reactive protein (CRP) levels and the risk of lung cancer (LC). METHODS: Leveraging summary statistics from genome-wide association studies of circulating CRP levels among 575,531 individuals of European ancestry, and LC risk among 29,266 cases and 56,450 controls, we investigated genetic associations of circulating CRP levels with the risk of overall lung cancer and its histological subtypes, by using linkage disequilibrium score (LDSC) regression and Mendelian randomization (MR) analyses. RESULTS: Significant positive genetic correlations between circulating CRP levels and the risk of LC and its histological subtypes were identified from LDSC regression, with correlation coefficients ranging from 0.12 to 0.26, and all false discovery adjusted p < 0.05. Univariable MR demonstrated a nominal association between CRP levels and an increased risk of lung squamous cell carcinoma (SCC) (inverse variance-weighted OR = 1.15, 95% CI 1.01-1.30). However, this association disappeared when multivariable MR included cigarettes per day and/or body mass index. By using our recently developed constrained maximum likelihood-based MR method, we identified significant associations of CRP levels with the risk of overall LC (OR 1.06, 95% CI 1.03-1.09), SCC (OR 1.06, 95% CI 1.02-1.09), and small cell lung cancer (SCLC, OR 1.09, 95% CI 1.03-1.15). Moreover, most univariable and multivariable MR analyses also revealed consistent CRP-SCLC associations. CONCLUSION: There may be a genetic and causal association between circulating CRP levels and the risk of SCLC, which is in line with previous population-based observational studies.

Millimeter-wave over fiber integrated sensing and communication system using self-coherent OFDM.

Orthogonal frequency-division multiplexing (OFDM) waveform is highly preferred as a dual-function candidate for integrated sensing and communication (ISAC) systems. However, the sensitivity to both carrier frequency offset (CFO) and phase noise greatly impedes its applications in millimeter-wave ISAC systems. Here, we propose and experimentally demonstrate a photonic millimeter-wave ISAC system employing the virtual-carrier-aided self-coherent OFDM technique, wherein a digitally-generated local oscillator is transmitted along with the OFDM signal. Then, a compact CFO-immune and phase noise-immune envelope detection method is implemented for down-converting millimeter-wave communication and radar echo signals. In experiments, a V-band ISAC system is successfully implemented with a simplified remote radio unit, using the remote photonic millimeter-wave heterodyning up-conversion for downlink and the envelope detection-assisted down-conversion for uplink (or radar echoes). In the converged transmission link with a 5-km fiber link and 2-m space link, the Kramers-Kronig (KK) receiver supports a communication data rate up to 16-Gbit/s by mitigating signal-signal beat interference (SSBI). More significantly, the SSBI leads to negligible effects on the sensing performance when classic matched filtering is adopted for target identification. Consequently, a 4.8-cm range resolution and a 4-mm range accuracy are obtained for the radar sensing function.

Reconstruction of transparent objects using phase shifting profilometry based on diffusion models.

Phase shifting profilometry is an important technique for reconstructing the three-dimensional (3D) geometry of objects with purely diffuse surfaces. However, it is challenging to measure the transparent objects due to the pattern aliasing caused by light refraction and multiple reflections inside the object. In this work, we analyze the aliasing fringe pattern formation for transparent objects and then, propose to learn the front surface light intensity distribution based on the formation principle by using the diffusion models for generating the non-aliased fringe patterns reflected from the front surface only. With the generated fringe patterns, the 3D shape of the transparent objects can be reconstructed via the conventional structured light. We show the feasibility and performance of the proposed method on the data of purely transparent objects that are not seen in the training stage. Moreover, we found it could be generalized to other cases with local-transparent and translucent objects, showing the potential capability of the diffusion based learnable framework in tackling the problems of transparent object reconstruction.

Total net-rate of 27.88 Tb/s full C-band transmission over 4,550†km using 150†km span length and high-gain EDFA amplification.

We experimentally demonstrate a total net-rate of 27.88 Tb/s for C-band wavelength-division multiplexing (WDM) transmission over an ultralong span-length of 150 km. It is the largest net capacity × span-length product of 4182 Tb/s·km for C-band, single-core, standard single-mode optical fiber transmission over a length of more than 3,000 km. A total of 99 channels, spaced at 50 GHz intervals, are employed for transmitting 32 GBaud probabilistically constellation-shaped (PCS) 64QAM signals with an information entropy of 5.5. High gain amplifiers can achieve wavelength-division multiplexing (WDM) transmission with a bandwidth of 6.25 THz, at a noise figure below 4.3 dB, without the assistance of distributed Raman amplification.

Multi-channel broadband optical chaos generation assisted by phase modulation and CFBG feedback.

In this paper, we propose a novel and simple multi-channel broadband optical chaos generation scheme based on phase modulation and chirped fiber Bragg grating (CFBG). Firstly, phase modulation is introduced to generate more new frequency components to broaden the spectrum of the phase chaos. Meanwhile, the accumulated dispersion from CFBG distorts the intensity chaos, converts phase chaos to intensity chaos, and weakens the laser relaxation oscillation. This process would lead to energy redistribution in the power spectrum, effectively increasing the chaotic bandwidth. Then, the wavelength detuning between CFBG and the semiconductor laser is introduced to enhance the chaotic bandwidth further. The experiment results show that the 10 dB bandwidths of the five channels are up to 31.0 GHz, 34.3 GHz, 36.3 GHz, 40 GHz, and 40 GHz, respectively. Note that the maximum bandwidth of the PD in our experiment is limited to 40 GHz. In addition, the multi-channel chaotic signals obtained from the experiment system are used to generate multi-channel physical random numbers. After the post-processing operations, the total rate of five parallel high-speed physical random number generation channels is 4.64 Tbit/s (160 GSa/s × 5bit × 1 channel + 160 GSa/s × 6bit × 4 channels). As far as we know, this is the highest record of using external cavity feedback semiconductor lasers to generate random numbers, which has great potential to meet the security requirements of next-generation Tbit/s optical communication systems.

Regulation of cluster synchronization in multilayer networks of delay coupled semiconductor lasers with the use of disjoint layer symmetry.

In real-world complex systems, heterogeneous components often interact in complex connection patterns and could be schematized by a formalism of multilayer network. In this work, the synchronization characteristics of multilayer network composed of semiconductor lasers (SLs) are investigated systematically. It is demonstrated that the interplay between different layers plays an important role on the synchronization patterns. We elucidate that the performance of cluster synchronization could be facilitated effectively with the introduction of disjoint layer symmetry into network topology. Intertwined stability of clusters from different layers could be decoupled into independent, and the parameter spaces for stable synchronization are extended significantly. The robustness of our proposed regulation scheme on operation parameters is numerically evaluated. Furthermore, the generality of presented theoretical results is validated in networks with more complex topology and multiple layers.

Fast fiber nonlinearity compensation method for PDM coherent optical transmission systems based on the Fourier neural operator.

Fiber nonlinearity compensation (NLC) is likely to become an indispensable component of coherent optical transmission systems for extending the transmission reach and increasing capacity per fiber. In this work, we introduce what we believe to be a novel fast black-box neural network model based on the Fourier neural operator (FNO) to compensate for the chromatic dispersion (CD) and nonlinearity simultaneously. The feasibility of the proposed approach is demonstrated in uniformly distributed as well as probabilistically-shaped 32GBaud 16/32/64-ary quadrature amplitude modulation (16/32/64QAM) polarization-division-multiplexed (PDM) coherent optical communication systems. The experimental results demonstrate that about 0.31 dB Q-factor improvement is achieved compared to traditional digital back-propagation (DBP) with 5 steps per span for PDM-16QAM signals after 1600 km standard single-mode fiber (SSMF) transmission at the optimal launched power of 4 dBm. While, the time consumption is reduced from 6.04 seconds to 1.69 seconds using a central processing unit (CPU), and from 1.54 seconds to only 0.03 seconds using a graphic processing unit (GPU), respectively. This scheme also reveals noticeable generalization ability in terms of launched power and modulation format.

Compact optical 90° hybrid based on a wedge-shaped 2 × 4 MMI coupler and a 2 × 2 MMI coupler on a thin-film lithium niobate platform.

We performed an experimental demonstration of a wedge-shaped optical 90° hybrid coupler on the thin-film lithium niobate (TFLN) platform, utilizing a paired-interference-based 2 × 4 multimode interference (MMI) coupler and a general-interference-based 2 × 2 MMI coupler. The fabricated optical 90° hybrid coupler has a compact footprint with a width of 18 µm and a length of 134 µm. In a coherent receiving system, the hybrid coupler directly connects to the balanced photodiode array, eliminating the need for waveguide crossings or cascaded phase shifters. The device exhibits a < 1.1 dB excess loss, a > 20 dB common-mode rejection ratio (CMRR), a < 1.3 dB wavelength sensitive loss, and a < ±5° phase deviation over a spectral range of 1530-1560 nm, which is promising to enable a compact heterogeneously integrated coherent receiving system on the thin-film lithium niobate platform.

Fine-mapping of LrN3B on wheat chromosome arm 3BS, one of the two complementary genes for adult-plant leaf rust resistance.

The common wheat line 4N0461 showed adult-plant resistance to leaf rust. 4N0461 was crossed with susceptible cultivars Nongda4503 and Shi4185 to map the causal resistance gene(s). Segregation of leaf rust response in F2 populations from both crosses was 9 resistant:7 susceptible, indicative of two complementary dominant resistance genes. The genes were located on chromosome arms 3BS and 4BL and temporarily named LrN3B and LrN4B, respectively. Subpopulations from 4N0461 × Nongda4503 with LrN3B segregating as a single allele were used to fine-map LrN3B locus. LrN3B was delineated in a genetic interval of 0.07 cM, corresponding to 106 kb based on the Chinese Spring reference genome (IWGSC RefSeq v1.1). Four genes were annotated in this region, among which TraesCS3B02G014800 and TraesCS3B02G014900 differed between resistant and susceptible genotypes, and both were required for LrN3B resistance in virus-induced gene silencing experiments. Diagnostic markers developed for checking the polymorphism of each candidate gene, can be used for marker-assisted selection in wheat breeding programs.

Alterations in gut microbiota contribute to cognitive deficits induced by chronic infection of Toxoplasma gondii.

Chronic infection with Toxoplasma gondii (T. gondii) emerges as a risk factor for neurodegenerative diseases in animals and humans. However, the underlying mechanisms are largely unknown. We aimed to investigate whether gut microbiota and its metabolites play a role in T. gondii-induced cognitive deficits. We found that T. gondii infection induced cognitive deficits in mice, which was characterized by synaptic ultrastructure impairment and neuroinflammation in the hippocampus. Moreover, the infection led to gut microbiota dysbiosis, barrier integrity impairment, and inflammation in the colon. Interestingly, broad-spectrum antibiotic ablation of gut microbiota attenuated the adverse effects of the parasitic infection on the cognitive function in mice; cognitive deficits and hippocampal pathological changes were transferred from the infected mice to control mice by fecal microbiota transplantation. In addition, the abundance of butyrate-producing bacteria and the production of serum butyrate were decreased in infected mice. Interestingly, dietary supplementation of butyrate ameliorated T. gondii-induced cognitive impairment in mice. Notably, compared to the healthy controls, decreased butyrate production was observed in the serum of human subjects with high levels of anti-T. gondii IgG. Overall, this study demonstrates that gut microbiota is a key regulator of T. gondii-induced cognitive impairment.