Benchmarking Mendelian randomization methods for causal inference using genome-wide association study summary statistics.

Mendelian randomization (MR), which utilizes genetic variants as instrumental variables (IVs), has gained popularity as a method for causal inference between phenotypes using genetic data. While efforts have been made to relax IV assumptions and develop new methods for causal inference in the presence of invalid IVs due to confounding, the reliability of MR methods in real-world applications remains uncertain. Instead of using simulated datasets, we conducted a benchmark study evaluating 16 two-sample summary-level MR methods using real-world genetic datasets to provide guidelines for the best practices. Our study focused on the following crucial aspects: type I error control in the presence of various confounding scenarios (e.g., population stratification, pleiotropy, and family-level confounders like assortative mating), the accuracy of causal effect estimates, replicability, and power. By comprehensively evaluating the performance of compared methods over one thousand exposure-outcome trait pairs, our study not only provides valuable insights into the performance and limitations of the compared methods but also offers practical guidance for researchers to choose appropriate MR methods for causal inference.

Enriching surface-ordered defects on WO3 for photocatalytic CO2-to-CH4 conversion by water.

Defect engineering has been widely applied in semiconductors to improve photocatalytic properties by altering the surface structures. This study is about the transformation of inactive WO3 nanosheets to a highly effective CO2-to-CH4 conversion photocatalyst by introducing surface-ordered defects in abundance. The nonstoichiometric WO3-x samples were examined by using aberration-corrected electron microscopy. Results unveil abundant surface-ordered terminations derived from the periodic {013} stacking faults with a defect density of 20.2%. The {002} surface-ordered line defects are the active sites for fixation CO2, transforming the inactive WO3 nanosheets into a highly active catalyst (CH4: O2 = 8.2: 16.7 µmol h-1). We believe that the formation of the W-O-C-W-O species is a critical step in the catalytic pathways. This work provides an atomic-level comprehension of the structural defects of catalysts for activating small molecules.

Leveraging the local genetic structure for trans-ancestry association mapping.

Over the past two decades, genome-wide association studies (GWASs) have successfully advanced our understanding of the genetic basis of complex traits. Despite the fruitful discovery of GWASs, most GWAS samples are collected from European populations, and these GWASs are often criticized for their lack of ancestry diversity. Trans-ancestry association mapping (TRAM) offers an exciting opportunity to fill the gap of disparities in genetic studies between non-Europeans and Europeans. Here, we propose a statistical method, LOG-TRAM, to leverage the local genetic architecture for TRAM. By using biobank-scale datasets, we showed that LOG-TRAM can greatly improve the statistical power of identifying risk variants in under-represented populations while producing well-calibrated p values. We applied LOG-TRAM to the GWAS summary statistics of various complex traits/diseases from BioBank Japan, UK Biobank, and African populations. We obtained substantial gains in power and achieved effective correction of confounding biases in TRAM. Finally, we showed that LOG-TRAM can be successfully applied to identify ancestry-specific loci and the LOG-TRAM output can be further used for construction of more accurate polygenic risk scores in under-represented populations.

Mendelian randomization for causal inference accounting for pleiotropy and sample structure using genome-wide summary statistics.

Mendelian randomization (MR) is a valuable tool for inferring causal relationships among a wide range of traits using summary statistics from genome-wide association studies (GWASs). Existing summary-level MR methods often rely on strong assumptions, resulting in many false-positive findings. To relax MR assumptions, ongoing research has been primarily focused on accounting for confounding due to pleiotropy. Here, we show that sample structure is another major confounding factor, including population stratification, cryptic relatedness, and sample overlap. We propose a unified MR approach, MR-APSS, which 1) accounts for pleiotropy and sample structure simultaneously by leveraging genome-wide information; and 2) allows the inclusion of more genetic variants with moderate effects as instrument variables (IVs) to improve statistical power without inflating type I errors. We first evaluated MR-APSS using comprehensive simulations and negative controls and then applied MR-APSS to study the causal relationships among a collection of diverse complex traits. The results suggest that MR-APSS can better identify plausible causal relationships with high reliability. In particular, MR-APSS can perform well for highly polygenic traits, where the IV strengths tend to be relatively weak and existing summary-level MR methods for causal inference are vulnerable to confounding effects.

A unified framework for cross-population trait prediction by leveraging the genetic correlation of polygenic traits.

The development of polygenic risk scores (PRSs) has proved useful to stratify the general European population into different risk groups. However, PRSs are less accurate in non-European populations due to genetic differences across different populations. To improve the prediction accuracy in non-European populations, we propose a cross-population analysis framework for PRS construction with both individual-level (XPA) and summary-level (XPASS) GWAS data. By leveraging trans-ancestry genetic correlation, our methods can borrow information from the Biobank-scale European population data to improve risk prediction in the non-European populations. Our framework can also incorporate population-specific effects to further improve construction of PRS. With innovations in data structure and algorithm design, our methods provide a substantial saving in computational time and memory usage. Through comprehensive simulation studies, we show that our framework provides accurate, efficient, and robust PRS construction across a range of genetic architectures. In a Chinese cohort, our methods achieved 7.3%-198.0% accuracy gain for height and 19.5%-313.3% accuracy gain for body mass index (BMI) in terms of predictive R2 compared to existing PRS approaches. We also show that XPA and XPASS can achieve substantial improvement for construction of height PRSs in the African population, suggesting the generality of our framework across global populations.

FIRM: Flexible integration of single-cell RNA-sequencing data for large-scale multi-tissue cell atlas datasets.

Single-cell RNA-sequencing (scRNA-seq) is being used extensively to measure the mRNA expression of individual cells from deconstructed tissues, organs and even entire organisms to generate cell atlas references, leading to discoveries of novel cell types and deeper insight into biological trajectories. These massive datasets are usually collected from many samples using different scRNA-seq technology platforms, including the popular SMART-Seq2 (SS2) and 10X platforms. Inherent heterogeneities between platforms, tissues and other batch effects make scRNA-seq data difficult to compare and integrate, especially in large-scale cell atlas efforts; yet, accurate integration is essential for gaining deeper insights into cell biology. We present FIRM, a re-scaling algorithm which accounts for the effects of cell type compositions, and achieve accurate integration of scRNA-seq datasets across multiple tissue types, platforms and experimental batches. Compared with existing state-of-the-art integration methods, FIRM provides accurate mixing of shared cell type identities and superior preservation of original structure without overcorrection, generating robust integrated datasets for downstream exploration and analysis. FIRM is also a facile way to transfer cell type labels and annotations from one dataset to another, making it a reliable and versatile tool for scRNA-seq analysis, especially for cell atlas data integration.

stVAE deconvolves cell-type composition in large-scale cellular resolution spatial transcriptomics.

MOTIVATION: Recent rapid developments in spatial transcriptomic techniques at cellular resolution have gained increasing attention. However, the unique characteristics of large-scale cellular resolution spatial transcriptomic datasets, such as the limited number of transcripts captured per spot and the vast number of spots, pose significant challenges to current cell-type deconvolution methods. RESULTS: In this study, we introduce stVAE, a method based on the variational autoencoder framework to deconvolve the cell-type composition of cellular resolution spatial transcriptomic datasets. To assess the performance of stVAE, we apply it to five datasets across three different biological tissues. In the Stereo-seq and Slide-seqV2 datasets of the mouse brain, stVAE accurately reconstructs the laminar structure of the pyramidal cell layers in the cortex, which are mainly organized by the subtypes of telencephalon projecting excitatory neurons. In the Stereo-seq dataset of the E12.5 mouse embryo, stVAE resolves the complex spatial patterns of osteoblast subtypes, which are supported by their marker genes. In Stereo-seq and Pixel-seq datasets of the mouse olfactory bulb, stVAE accurately delineates the spatial distributions of known cell types. In summary, stVAE can accurately identify spatial patterns of cell types and their relative proportions across spots for cellular resolution spatial transcriptomic data. It is instrumental in understanding the heterogeneity of cell populations and their interactions within tissues. AVAILABILITY AND IMPLEMENTATION: stVAE is available in GitHub (https://github.com/lichen2018/stVAE) and Figshare (https://figshare.com/articles/software/stVAE/23254538).

PALM: a powerful and adaptive latent model for prioritizing risk variants with functional annotations.

MOTIVATION: The findings from genome-wide association studies (GWASs) have greatly helped us to understand the genetic basis of human complex traits and diseases. Despite the tremendous progress, much effects are still needed to address several major challenges arising in GWAS. First, most GWAS hits are located in the non-coding region of human genome, and thus their biological functions largely remain unknown. Second, due to the polygenicity of human complex traits and diseases, many genetic risk variants with weak or moderate effects have not been identified yet. RESULTS: To address the above challenges, we propose a powerful and adaptive latent model (PALM) to integrate cell-type/tissue-specific functional annotations with GWAS summary statistics. Unlike existing methods, which are mainly based on linear models, PALM leverages a tree ensemble to adaptively characterize non-linear relationship between functional annotations and the association status of genetic variants. To make PALM scalable to millions of variants and hundreds of functional annotations, we develop a functional gradient-based expectation-maximization algorithm, to fit the tree-based non-linear model in a stable manner. Through comprehensive simulation studies, we show that PALM not only controls false discovery rate well, but also improves statistical power of identifying risk variants. We also apply PALM to integrate summary statistics of 30 GWASs with 127 cell type/tissue-specific functional annotations. The results indicate that PALM can identify more risk variants as well as rank the importance of functional annotations, yielding better interpretation of GWAS results. AVAILABILITY AND IMPLEMENTATION: The source code is available at https://github.com/YangLabHKUST/PALM. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Population-based BRCA germline mutation screening in the Han Chinese identifies individuals at risk of BRCA mutation-related cancer: experience from a clinical diagnostic center from greater Shanghai area.

BACKGROUND: Deleterious BRCA1/2 (BRCA) mutation raises the risk for BRCA mutation-related malignancies, including breast, ovarian, prostate, and pancreatic cancer. Germline variation of BRCA exhibits substantial ethnical diversity. However, there is limited research on the Chinese Han population, constraining the development of strategies for BRCA mutation screening in this large ethnic group. METHODS: We profile the BRCA mutational spectrum, including single nucleotide variation, insertion/deletion, and large genomic rearrangements in 2,080 apparently healthy Chinese Han individuals and 522 patients with BRCA mutation-related cancer, to determine the BRCA genetic background of the Chinese Han population, especially of the East Han. Incident cancer events were monitored in 1,005 participants from the healthy group, comprising 11 BRCA pathogenic/likely pathogenic (PLP) variant carriers and 994 PLP-free individuals, including 3 LGR carriers. RESULTS: Healthy Chinese Han individuals demonstrated a distinct BRCA mutational spectrum compared to cancer patients, with a 0.53% (1 in 189) prevalence of pathogenic/likely pathogenic (PLP) variant, alongside a 3 in 2,080 occurrence of LGR. BRCA1 c. 5470_5477del demonstrated high prevalence (0.44%) in the North Han Chinese and penetrance for breast cancer. None of the 3 LGR carriers developed cancer during the follow-up. We calculated a relative risk of 135.55 (95% CI 25.07 to 732.88) for the development of BRCA mutation-related cancers in the BRCA PLP variant carriers (mean age 42.91 years, median follow-up 10 months) compared to PLP-free individuals (mean age 48.47 years, median follow-up 16 months). CONCLUSION: The unique BRCA mutational profile in the Chinese Han highlights the potential for standardized population-based BRCA variant screening to enhance BRCA mutation-related cancer prevention and treatment.

Mn(I)-Catalyzed Carbon-Skeleton Rearrangement of Tertiary Alcohol-Based Aldol Reaction with Aldehydes.

A Mn-catalyzed ligand-directed Csp3-Csp2 coupling of tertiary allylic alcohols with arylaldehydes has been developed. The method provides an efficient approach to access 1,5-diarylpent-1-en-3-ones via carbon-skeleton rearrangement-based aldol reaction.

Rhodium(III)-Catalyzed Oxidative 1,3-Aryl Migration of α-Aryl Allylic Alcohols.

A Rh(III)-catalyzed oxidative 1,3-aryl migration of α-arylallylic alcohols via Csp2-Csp3 σ bond activation has been developed. This method provides an efficient strategy to allow for allylic alcohol-based skeleton rearrangement, in which various secondary and tertiary α-arylallylic alcohols are rapidly converted to ß-aryl-α, ß-unsaturated ketones and aldehydes.

From C4H7N2Ge0.4Sn0.6Br3 to C6H11N2Ge0.4Sn0.6Br3: Effective Modulation of the Second Harmonic Generation Effect and Optical Band Gap by Planar π-Conjugated Organic Cation Size.

In the search for nonlinear optical (NLO) materials with excellent overall performance, we have devoted ourselves to organic-inorganic hybrids consisting of anionic groups containing stereochemically active lone-pair (SCALP) electron cations and organic planar π-conjugated group cations. Accordingly, in this paper, two novel organic-inorganic hybrid metal halides, C4H7N2Ge0.4Sn0.6Br3 (I) and C6H11N2Ge0.4Sn0.6Br3 (II), have been synthesized. The powder second-harmonic technique shows that both C4H7N2Ge0.4Sn0.6Br3 and C6H11N2Ge0.4Sn0.6Br3 have moderately strong second-order nonlinear optical effects, which are about 2.03 (I) and 1.16 (II) times that of KH2PO4 (KDP), respectively. They also have different optical band gaps of 2.75 (I) and 2.88 eV (II) due to the different sizes of the organic cations, and their photoluminescent and thermal properties were also investigated. This work provides new structural insights for the design and modulation of organic-inorganic hybrid halide materials with multiple excellent optical properties.

Black carp A20 inhibits interferon signaling through de-ubiquitinating IKKß.

IkappaB kinase beta (IKKß) is a key member of IκB kinases and functions importantly in interferon (IFN) signaling. Phosphorylation and ubiquitination are involved in the activation of IKKß. A20 is a de-ubiquitin enzyme and functions as a suppressor in inflammation signaling, which has been reported to be phosphorylated and activated by IKKß. However, the role and relationship of IKKß and A20 in teleost remains unclear. In this study, IKKß (bcIKKß) and A20 (bcA20) of black carp (Mylopharyngodon piceus) have been cloned and characterized. Overexpressed bcIKKß in EPC cells showed strong anti-viral ability by activating both NF-κB and IFN signaling. EPC cells stable expressing bcIKKß presented improved anti-viral activity as well. The interaction between bcA20 and bcIKKß was identified, and overexpression of bcA20 was able to suppress bcIKKß-mediated activation of NF-κB and IFN signaling. Meanwhile, knock-down of A20 increased host the antiviral ability of host cells. Importantly, it has been identified that bcA20 was able to remove K27-linked ubiquitination and decrease the phosphorylation of bcIKKß. Thus, our data conclude that bcA20 suppresses the anti-viral activity of bcIKKß and removes its K27-linked ubiquitination, which presents a new mechanism of IKKß regulation.

Nonlinear Optical Effects of Hybrid Antimony(III) Halides Induced by Stereoactive 5s2 Lone Pairs and Trimethylammonium Cations.

Organic-inorganic hybrid metal halides have unique optical and electronic properties, which are advantageous in the study of nonlinear optical materials. To investigate the effect of stereoactive lone pair electrons and the induction of organic cations on the structure of hybrid antimony(III) halides on nonlinear optics, we synthesize two noncentrosymmetric hybrid antimony(III)-based halide single crystals (TMA)3Sb2X9 (TMA = NH(CH3)3+, X = Cl, Br) by a room-temperature slow evaporation method, and their single-crystal structures, phase transition, X-ray photoelectron spectroscopy, and energy-band structure calculations are studied. More importantly, second-harmonic generation results of (TMA)3Sb2X9 (X = Cl, Br) are about 0.7 and 0.8 × KH2PO4(KDP), respectively. Interestingly, (TMA)3Sb2Cl9 single crystals undergo a reversible structural transition from Pc (No. 7) at room temperature to P21/c (No. 14) at 400 K, while the (TMA)3Sb2Br9 single crystals belong to the noncentrosymmetric space group R3c (No. 161), which clarifies the previous results. This work not only deepens the understanding of the role in lone pair electrons and organic cations in the structural induction in antimony-based halide perovskite materials but also provides guidance for subsequent nonlinear optical explorations.

USP14 negatively regulates IFN signaling by dampening K63-linked ubiquitination of TBK1 in black carp.

USP14 regulates the immune related pathways by deubiquitinating the signaling molecules in mammals. In teleost, USP14 is also reported to inhibit the antiviral immune response through TBK1, but its regulatory mechanism remains obscure. To elucidate the role of USP14 in the RLR/IFN antiviral pathway in teleost, the homolog USP14 (bcUSP14) of black carp (Mylopharyngodon piceus) has been cloned and characterize in this paper. bcUSP14 contains 490 amino acids (aa), and the sequence is well conserved among in vertebrates. Over-expression of bcUSP14 in EPC cells attenuated SVCV-induced transcription activity of IFN promoters and enhanced SVCV replication. Knockdown of bcUSP14 in MPK cells led to the increased transcription of IFNs and decreased SVCV replication, suggesting the improved antiviral activity of the host cells. The interaction between bcUSP14 and bcTBK1 was identified by both co-immunoprecipitation and immunofluorescent staining. Co-expressed bcUSP14 obviously inhibited bcTBK1-induced IFN production and antiviral activity in EPC cells. K63-linked polyubiquitination of bcTBK1 was dampened by co-expressed bcUSP14, and bcTBK1-mediated phosphorylation and nuclear translocation of IRF3 were also inhibited by this deubiquitinase. Thus, all the data demonstrated that USP14 interacts with and inhibits TBK1 through deubiquitinating TBK1 in black carp.

Unsupervised corneal contour extraction algorithm with shared model for dynamic deformation videos: improving accuracy and noise resistance.

BACKGROUND: In this study, an automatic corneal contour extraction algorithm with a shared model is developed to extract contours from dynamic corneal videos containing noise, which improves the accuracy of corneal biomechanical evaluation and clinical diagnoses. The algorithm does not require manual labeling and completes the unsupervised semantic segmentation of each frame in corneal dynamic deformation videos based on a fully convolutional deep-learning network using corneal geometry and texture information. RESULTS: We included 1027 corneal videos at Tianjin Eye Hospital (Nankai University Affiliated Eye Hospital) from May 2020 to November 2021. The videos were obtained by the ultra-high-speed Scheimpflug camera, and then we used the shared model mechanism to accelerate the segmentation of corneal regions in videos, effectively resist noise, determine corneal regions based on shape factors, and finally achieve automatic and accurate extraction of corneal region contours. The Intersection over Union (IoU) of the extracted and real corneal contours using this algorithm reached 95%, and the average overlap error was 0.05, implying that the extracted corneal contour overlapped almost completely with the real contour. CONCLUSIONS: Compared to other algorithms, the method introduced in this study does not require manual annotation of corneal contour data in advance and can still extract accurate corneal contours from noisy corneal videos with good repeatability.

Accurate genetic and environmental covariance estimation with composite likelihood in genome-wide association studies.

Genetic and environmental covariances between pairs of complex traits are important quantitative measurements that characterize their shared genetic and environmental architectures. Accurate estimation of genetic and environmental covariances in genome-wide association studies (GWASs) can help us identify common genetic and environmental factors associated with both traits and facilitate the investigation of their causal relationship. Genetic and environmental covariances are often modeled through multivariate linear mixed models. Existing algorithms for covariance estimation include the traditional restricted maximum likelihood (REML) method and the recent method of moments (MoM). Compared to REML, MoM approaches are computationally efficient and require only GWAS summary statistics. However, MoM approaches can be statistically inefficient, often yielding inaccurate covariance estimates. In addition, existing MoM approaches have so far focused on estimating genetic covariance and have largely ignored environmental covariance estimation. Here we introduce a new computational method, GECKO, for estimating both genetic and environmental covariances, that improves the estimation accuracy of MoM while keeping computation in check. GECKO is based on composite likelihood, relies on only summary statistics for scalable computation, provides accurate genetic and environmental covariance estimates across a range of scenarios, and can accommodate SNP annotation stratified covariance estimation. We illustrate the benefits of GECKO through simulations and applications on analyzing 22 traits from five large-scale GWASs. In the real data applications, GECKO identified 50 significant genetic covariances among analyzed trait pairs, resulting in a twofold power gain compared to the previous MoM method LDSC. In addition, GECKO identified 20 significant environmental covariances. The ability of GECKO to estimate environmental covariance in addition to genetic covariance helps us reveal strong positive correlation between the genetic and environmental covariance estimates across trait pairs, suggesting that common pathways may underlie the shared genetic and environmental architectures between traits.

Surgical treatment of acromioclavicular joint dislocation of Rockwood III/IV: a retrospective study on clavicular hook plate versus arthroscopic TightRope loop titanium button.

PURPOSE: To compare the clinical efficacy of arthroscopic TightRope loop titanium button and clavicular hook plate in the treatment of acromioclavicular joint (ACJ) dislocation of Rockwood III/IV. METHODS: A retrospective analysis of patients with ACJ dislocation in our hospital from January 2018 to December 2020 was conducted. The patients were assigned to be treated with arthroscopic TightRope loop titanium button (TR group) or clavicular hook plate (HP group). The preoperative, intraoperative and postoperative data and imaging findings of the two groups were compared. RESULTS: A total of 58 eligible patients were enrolled in this study. Compared with HP group, TR group had shorter incision length and less blood loss during operation. Postoperative follow-up ranged from 12 to 24 months (mean 15.4 months). At 6 months and 12months postoperatively, compared with HP group, TR group had lower VAS and higher CMS, and the difference was statistically significant. At 12 months postoperatively, compared with HP group, TR group had lower ACJ gap and coracoclavicular joint(CCJ) distance, and the difference was statistically significant.In HP group, there were 3 cases of subacromial impact, 1 case of redislocation, 2 cases of traumatic arthritis and 2 cases of wound infection. There was 1 case of redislocation in TR group. CONCLUSIONS: Compared with clavicular hook plate, arthroscopic TightRope loop titanium button is minimally invasive, safe and effective in the treatment of ACJ dislocation, and has a good trend in clinical application.

The effect of suboccipital muscle dysfunction on the biomechanics of the upper cervical spine: a study based on finite element analysis.

OBJECTIVE: Muscle dysfunction caused by repetitive work or strain in the neck region can interfere muscle responses. Muscle dysfunction can be an important factor in causing cervical spondylosis. However, there has been no research on how the biomechanical properties of the upper cervical spine change when the suboccipital muscle group experiences dysfunction. The objective of this study was to investigate the biomechanical evidence for cervical spondylosis by utilizing the finite element (FE) approach, thus and to provide guidance for clinicians performing acupoint therapy. METHODS: By varying the elastic modulus of the suboccipital muscle, the four FE models of C0-C3 motion segments were reconstructed under the conditions of normal muscle function and muscle dysfunction. For the two normal condition FE models, the elastic modulus for suboccipital muscles on both sides of the C0-C3 motion segments was equal and within the normal range In one muscle dysfunction FE model, the elastic modulus on both sides was equal and greater than 37 kPa, which represented muscle hypertonia; in the other, the elastic modulus of the left and right suboccipital muscles was different, indicating muscle imbalance. The biomechanical behavior of the lateral atlantoaxial joint (LAAJ), atlanto-odontoid joint (ADJ), and intervertebral disc (IVD) was analyzed by simulations, which were carried out under the six loadings of flexion, extension, left and right lateral bending, left and right axial rotation. RESULTS: Under flexion, the maximum stress in LAAJ with muscle imbalance was higher than that with normal muscle and hypertonia, while the maximum stress in IVD in the hypertonic model was higher than that in the normal and imbalance models. The maximum stress in ADJ was the largest under extension among all loadings for all models. Muscle imbalance and hypertonia did not cause overstress and stress distribution abnormalities in ADJ. CONCLUSION: Muscle dysfunction increases the stress in LAAJ and in IVD, but it does not affect ADJ.

Nasolacrimal duct rhinostomy for low-level nasolacrimal duct obstruction:long-term outcomes and surgical selection paradigm.

PROPOSE: This study aims to present long-term outcomes in a specific patient population experiencing epiphora due to low-level nasolacrimal duct obstruction (NLDO) following endonasal endoscopic nasolacrimal duct rhinostomy, and to propose a surgical selection paradigm for varying locations of NLDO. METHODS: Between September 1, 2017 and February 28, 2023, a retrospective analysis was conducted on 26 patients diagnosed with primary acquired nasolacrimal duct obstruction (PANDO) who underwent endonasal endoscopic nasolacrimal duct rhinostomy for low-level NLDO (defined as obstruction below the plane of the superior border of the inferior turbinate attachment). The study assessed surgical success through objective measures of anatomical patency and subjective measures of functional patency during a postoperative follow-up period of at least six months. Additionally, any complications that arose during this follow-up period were documented. RESULTS: The study included a cohort of 26 patients, consisting of 24 women and 2 men, with a mean age of 47.58 ± 3.09 years (range: 8-75). All patients underwent endoscopic nasolacrimal duct rhinostomy, with 10 eyes having previously undergone tear duct recanalization procedures. Anatomical patency was achieved in 88.5% (23/26) of cases, while functional patency was achieved in 80.8% (21/26) after an average follow-up period of 41.9 ± 22.1 months. No significant complications were observed in any of the patients during the follow-up period. CONCLUSION: Endonasal endoscopic nasolacrimal duct rhinostomy is effective in treating epiphora in over 80% of cases with low-level NLDO. Tailoring the surgery to the location of the obstruction can improve outcomes and minimize damage.