Yao Lu | PubMed Health

PubMed2026

Shared genetic architecture and cellular convergence between female reproductive disorders and pulmonary function: a genome-wide cross-trait analysis.

Female reproductive disorders (FRDs), including polycystic ovary syndrome, endometriosis, uterine leiomyomata, and infertility, have been epidemiologically associated with impaired pulmonary function. However, it remains unclear whether this cross-organ link reflects shared genetic etiology and, if so, which cellular mechanisms mediate it. We performed a systematic genome-wide cross-trait analysis of three FRDs and lung function traits (FEV₁, FVC, FEV₁/FVC) using GWAS summary statistics from individuals of European ancestry, integrating genetic correlation, bidirectional causal inference, pleiotropy mapping, and single-cell enrichment analyses. We identified significant negative genetic correlations between FRDs and lung volume traits, most prominently for FVC (rg range: - 0.077 to - 0.178). Bidirectional causal analyses indicated that FRDs have a detrimental effect on lung volume, with higher FRD genetic liability associated with reduced lung volume. Cross-trait meta-analysis identified 17 pleiotropic variants across 11 loci, with the 19q13.2 (LTBP4) and 12q13.13 (HOXC6/HOXC9) loci showing strong evidence of shared causal variants. Critically, single-cell analyses revealed that shared genetic risk converged on mesenchymal lineages across organs, specifically alveolar adventitial fibroblasts in the lung and stromal/smooth muscle cells in the endometrium. Transcriptome-wide analyses further nominated the estrogen-responsive gene RERG as a convergent gene linking these conditions with lung function. Our study revealed a shared genetic architecture between female reproductive disorders and lung function traits, providing a basis for further mechanistic investigations and potential clinical evaluation. Furthermore, our findings suggest that shared fibroproliferative and hormone-responsive pathways may offer insights into the biological mechanisms underlying these conditions.

Female↗

PubMed2026

Causal relationship between asthma and hernia risk: A Mendelian randomization study.

Epidemiological associations between asthma and various hernia subtypes have been reported, but the causality and direction remain unclear. This study employs a two‑sample Mendelian randomization (MR) approach to systematically assess the causal associations between asthma and 6 hernia subtypes. Using publicly available summary data of genome-wide association studies, asthma was selected as the exposure, and diaphragmatic hernia, umbilical hernia, femoral hernia, hiatus hernia, inguinal hernia, and ventral hernia were selected as outcomes. Instrumental variables were strictly screened (F-statistic > 10). The inverse‑variance weighted method was used as the primary analytical approach, supplemented with MR Egger and weighted median methods. Sensitivity analyses included heterogeneity tests, horizontal pleiotropy tests, Steiger directionality tests, leave‑one‑out analyses, and Radial MR. Reverse MR was performed for validation. Forward MR analyses revealed a significant positive causal effect of asthma on diaphragmatic hernia (odds ratio [OR] = 1.19, 95% confidence interval [CI]: 1.08-1.31, P < .001) and a suggestive association with umbilical hernia (OR = 1.19, 95% CI: 1.05-1.34, P = .007). The umbilical hernia association was significant only by the inverse‑variance weighted method; weighted median (P = .102) and MR-Egger (P = .210) estimates were not statistically significant, and the estimate attenuated after outlier removal (confirmatory OR = 1.13, 95% CI: 1.01-1.26, P = .028). Sensitivity analyses showed no significant heterogeneity or pleiotropy. Reverse MR did not identify significant causal effects of hernias on asthma, although power limitations for certain hernia subtypes should be considered. No significant associations were observed between asthma and the other hernia subtypes, although the null findings for femoral and ventral hernias should be interpreted with caution due to limited statistical power. This study provides genetic evidence supporting asthma as a causal risk factor for diaphragmatic hernia, with a suggestive association for umbilical hernia. The diaphragmatic hernia finding was robust across multiple sensitivity analyses, whereas the umbilical hernia association was less consistent and requires further confirmation. These findings contribute to a deeper understanding of the mechanistic links between asthma and specific hernia subtypes.

Mendelian Randomization Analysis↗

PubMed2024

Integration of Imaging-based and Sequencing-based Spatial Omics Mapping on the Same Tissue Section via DBiTplus.

Spatially mapping the transcriptome and proteome in the same tissue section can significantly advance our understanding of heterogeneous cellular processes and connect cell type to function. Here, we present Deterministic Barcoding in Tissue sequencing plus (DBiTplus), an integrative multi-modality spatial omics approach that combines sequencing-based spatial transcriptomics and image-based spatial protein profiling on the same tissue section to enable both single-cell resolution cell typing and genome-scale interrogation of biological pathways. DBiTplus begins with in situ reverse transcription for cDNA synthesis, microfluidic delivery of DNA oligos for spatial barcoding, retrieval of barcoded cDNA using RNaseH, an enzyme that selectively degrades RNA in an RNA-DNA hybrid, preserving the intact tissue section for high-plex protein imaging with CODEX. We developed computational pipelines to register data from two distinct modalities. Performing both DBiT-seq and CODEX on the same tissue slide enables accurate cell typing in each spatial transcriptome spot and subsequently image-guided decomposition to generate single-cell resolved spatial transcriptome atlases. DBiTplus was applied to mouse embryos with limited protein markers but still demonstrated excellent integration for single-cell transcriptome decomposition, to normal human lymph nodes with high-plex protein profiling to yield a single-cell spatial transcriptome map, and to human lymphoma FFPE tissue to explore the mechanisms of lymphomagenesis and progression. DBiTplusCODEX is a unified workflow including integrative experimental procedure and computational innovation for spatially resolved single-cell atlasing and exploration of biological pathways cell-by-cell at genome-scale.

Journal Article↗

PubMed2024

Integration of Imaging-based and Sequencing-based Spatial Omics Mapping on the Same Tissue Section via DBiTplus.

Spatially mapping the transcriptome and proteome in the same tissue section can significantly advance our understanding of heterogeneous cellular processes and connect cell type to function. Here, we present Deterministic Barcoding in Tissue sequencing plus (DBiTplus), an integrative multi-modality spatial omics approach that combines sequencing-based spatial transcriptomics and image-based spatial protein profiling on the same tissue section to enable both single-cell resolution cell typing and genome-scale interrogation of biological pathways. DBiTplus begins with in situ reverse transcription for cDNA synthesis, microfluidic delivery of DNA oligos for spatial barcoding, retrieval of barcoded cDNA using RNaseH, an enzyme that selectively degrades RNA in an RNA-DNA hybrid, preserving the intact tissue section for high-plex protein imaging with CODEX. We developed computational pipelines to register data from two distinct modalities. Performing both DBiT-seq and CODEX on the same tissue slide enables accurate cell typing in each spatial transcriptome spot and subsequently image-guided decomposition to generate single-cell resolved spatial transcriptome atlases. DBiTplus was applied to mouse embryos with limited protein markers but still demonstrated excellent integration for single-cell transcriptome decomposition, to normal human lymph nodes with high-plex protein profiling to yield a single-cell spatial transcriptome map, and to human lymphoma FFPE tissue to explore the mechanisms of lymphomagenesis and progression. DBiTplusCODEX is a unified workflow including integrative experimental procedure and computational innovation for spatially resolved single-cell atlasing and exploration of biological pathways cell-by-cell at genome-scale.

Journal Article↗