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Cell Type-Resolved Causal Inference and Spatial Transcriptomic Integration Reveal Immune-Specific Genetic Drivers of Autoimmune and Malignant Thyroid Disease.

BACKGROUND: Thyroid diseases, including autoimmune thyroid disease (AITD) and thyroid cancer, are characterized by immune dysregulation, yet the cell type-specific genetic mechanisms underlying these conditions remain poorly understood. Most genome-wide association studies (GWAS) have relied on bulk tissue expression quantitative trait loci (eQTL), which cannot resolve the heterogeneity of immune cell populations. METHODS: We performed two-sample Mendelian randomization (MR) analyses using single-cell cis-eQTLs from 14 immune cell subtypes (OneK1K cohort) as instrumental variables against GWAS summary statistics for four thyroid outcomes: autoimmune hyperthyroidism, autoimmune hypothyroidism, thyroid cancer and autoimmune thyroiditis. Causal associations were validated through Bayesian colocalization, phenome-wide association analysis (PheWAS) and multi-layered transcriptomic validation encompassing spatial transcriptomics of AITD tissue (GSE248205), bulk RNA-seq of thyroid cancer (GSE3678) and single-cell RNA-seq of thyroid tumours (GSE250521). gsMap spatial LD score regression was applied to map disease heritability onto spatial tissue architecture. RESULTS: We identified six Bonferroni-significant causal gene-cell type pairs for autoimmune hyperthyroidism, including protective effects of ABHD16A in na&#xef;ve/immature B cells (OR&#xa0;=&#xa0;0.440), HIST1H3H in CD8 NC T cells (OR&#xa0;=&#xa0;0.324), HMGN4 in NK recruiting cells (OR&#xa0;=&#xa0;0.556) and ZKSCAN4 in CD8 S100B T cells (OR&#xa0;=&#xa0;0.427), with five pairs showing strong colocalization (PP.H4 &#x2265; 86%). Three pairs reached significance for autoimmune hypothyroidism, including a risk association of HLA-F in CD4 NC T cells (OR&#xa0;=&#xa0;1.139). For autoimmune thyroiditis, FAM134B/RETREG1 showed consistent suggestive protective associations across both CD4 and CD8 NC T cells (PP.H4 &#x2265; 90% for both), suggesting a possible involvement of ER phagy regulation in thyroiditis susceptibility. Thyroid cancer showed a suggestive association with HLA-G in classical monocytes (OR&#xa0;=&#xa0;1.899, PP.H4&#xa0;=&#xa0;53%). Spatial transcriptomic validation demonstrated progressive immune infiltration from control tissue to Graves' disease to Hashimoto's thyroiditis (7.7%-15.7%, 46.1%-54.1%, respectively) and strong spatial correlation between target gene expression and corresponding cell type enrichment (e.g., plasma cell-HLA-DQB1: r&#xa0;=&#xa0;0.491, p < 10-300). HLA-G was independently validated in thyroid cancer bulk (log2fc&#xa0;=&#xa0;0.542, p&#xa0;=&#xa0;9.51&#xa0;&#xd7;&#xa0;10-3, AUC&#xa0;=&#xa0;0.857) and single-cell datasets. PheWAS revealed no significant associations detected for the core candidates. gsMap identified significant enrichment of autoimmune hypothyroidism heritability in gastrointestinal tract, adrenal gland and adipose tissue (all Bonferroni p < 0.002). CONCLUSIONS: This study establishes a multi-scale analytical framework integrating cell type-resolved genetic inference with spatial tissue validation, revealing distinct immunogenetic architectures underlying autoimmune versus malignant thyroid disease. Protective genetic programs in autoimmune hyperthyroidism converge on chromatin remodelling (HIST1H3H, HMGN4, ZKSCAN4) and lipid metabolism (ABHD16A) across lymphocyte subsets, whereas thyroid cancer risk involves immune escape mediated by HLA-G in myeloid cells. The ER-phagy receptor RETREG1 represents a candidate pathway warranting further investigation in autoimmune thyroiditis. These findings provide genetically supported, cell type-specific therapeutic targets and demonstrate a generalizable strategy for dissecting the immune-mediated mechanisms of complex thyroid diseases.

Mendelian randomization↗

Cross-Phenotype Genome-Wide Association Study on the Shared Genetic Susceptibility to Systemic Sclerosis and Primary Biliary Cholangitis.

OBJECTIVE: An increased risk of primary biliary cholangitis (PBC) has been reported in patients with systemic sclerosis (SSc). Our study aims to investigate the shared genetic susceptibility between the two disorders and to define candidate causal genes using cross-phenotype genome-wide association study (GWAS) meta-analysis. METHODS: We performed cross-phenotype GWAS meta-analysis and Bayesian colocalization analysis for patients with SSc and patients with PBC. We performed both genome-wide and locus-based analysis, including tissue and pathway enrichment analyses, fine-mapping, Bayesian colocalization analyses with expression quantitative trait loci and protein quantitative trait loci (pQTL) datasets, and phenome-wide association studies. Finally, we used an integrative approach to prioritize candidate causal genes from the novel loci. RESULTS: We detected a strong genetic correlation between SSc and PBC (global genetic correlation = 0.84, P = 1.7 &#xd7; 10-6). In the cross-phenotype GWAS meta-analysis, we identified 44 nonhuman leukocyte antigens loci that reached genome-wide significance (P < 5 &#xd7; 10-8). Evidence of shared causal variants between patients with SSc and patients with PBC was found for nine loci, five of which were novel. Integrating multiple sources of evidence, we prioritized CD40, ERAP1, PLD4, SPPL3, and CCDC113 as novel candidate causal genes. The CD40 risk locus colocalized with trans-pQTLs of multiple plasma proteins involved in B cell function. CONCLUSION: Our study supports a strong shared genetic susceptibility between SSc and PBC. Using cross-phenotype analyses, we have prioritized several novel candidate causal genes and pathways for these disorders.

Humans↗

Endocrine-disrupting chemical-induced gene networks confer coronary heart disease risk revealed by causal inference and single-cell analyses.

BACKGROUND: Endocrine-disrupting chemicals (EDCs) are linked to coronary heart disease (CHD), but underlying mechanisms remain unclear. We aimed to identify EDC-related genes and evaluate their causal roles in CHD. METHODS: We curated EDC-related genes from a compound-gene interaction database and integrated them with CHD genome-wide association study (GWAS) summary statistics and tissue-specific expression quantitative trait loci (eQTL) data. Two-sample Mendelian randomization (MR) and Bayesian colocalization were applied to infer causality. Functional enrichment, single-cell RNA sequencing of human coronary arteries, and EDC-gene networks were further analyzed. RESULTS: After FDR correction, 39 genes were significantly associated with CHD risk via MR. Four genes-ZNF827, FCHO1, IPO9 (protective), and RPL13 (risk-increasing)-showed strong colocalization (PPH4&#x202f;>&#x202f;0.9). Pathway and single-cell analyses of coronary artery tissue indicated that vascular and immune pathways mediate these effects. An interaction network highlighted associations between specific EDCs and candidate genes implicated in CHD susceptibility. CONCLUSION: This integrative genomic study provides evidence that EDCs influence CHD susceptibility through distinct gene networks, revealing potential mechanisms and molecular targets for prevention and therapy.

Humans↗

Dissecting the association between blood pressure traits, hypertension, antihypertensive medications and epilepsy: A Mendelian randomization study.

BACKGROUND: Observational studies suggest that hypertension and epilepsy have a high co-occurrence, and antihypertensive medications may have impacts on the prevention and treatment of epilepsy. However, the directionality of causation between them is elusive. METHOD: By leveraging genome-wide association studies (GWAS) summary data of each trait, we firstly performed bidirectional univariate Mendelian randomization (UVMR) to assess the strength and direction of the associations between pairs of traits, then multivariate MR (MVMR) was conducted to adjust for potential confounders in causalities. Cochran's Q statistics, leave-one-out analysis, MR-Egger regression and MR-Pleiotropy Residual Sum and Outlier methods (MR-PRESSO) were employed to evaluate the robustness of the results. Drug target MR was proceeded to assess the association between five classes of first-line antihypertensive medications and epilepsy. Specifically, single nucleotide polymorphisms (SNPs) extracted from GWAS data on systolic blood pressure (SBP)/diastolic blood pressure (DBP), along with expression quantitative trait loci (eQTL) were utilized as proxies for antihypertensive medications, respectively. RESULTS: Forward UVMR results provided evidence that genetically predicted blood pressure traits and hypertension have causal effects on epilepsy, while reverse UVMR indicated no causal impacts of epilepsy on blood pressure traits or hypertension. The sensitivity analysis results were robust. The causalities between DBP, hypertension and epilepsy remained remarkable after adjustment by MVMR. Inverse-variance-weighted MR (IVW-MR) yielded evidence of positive association only between Beta-Blockers target genes based on DBP GWAS screening and epilepsy. Summary-data-based MR (SMR) identified a positive correlation between Beta-Blockers target gene ADRA1D and epilepsy risk. CONCLUSIONS: Hypertension has a causal effect on epilepsy and managing DBP in patients with hypertension through Beta-Blockers may help prevent epilepsy.

Humans↗

Functional mapping and annotation of genetic associations with FUMA.

A main challenge in genome-wide association studies (GWAS) is to pinpoint possible causal variants. Results from GWAS typically do not directly translate into causal variants because the majority of hits are in non-coding or intergenic regions, and the presence of linkage disequilibrium leads to effects being statistically spread out across multiple variants. Post-GWAS annotation facilitates the selection of most likely causal variant(s). Multiple resources are available for post-GWAS annotation, yet these can be time consuming and do not provide integrated visual aids for data interpretation. We, therefore, develop FUMA: an integrative web-based platform using information from multiple biological resources to facilitate functional annotation of GWAS results, gene prioritization and interactive visualization. FUMA accommodates positional, expression quantitative trait loci (eQTL) and chromatin interaction mappings, and provides gene-based, pathway and tissue enrichment results. FUMA results directly aid in generating hypotheses that are testable in functional experiments aimed at proving causal relations.

Chromatin↗

Identifying causal genetic variants for high-altitude adaptation through blood eQTL analysis in plateau populations.

A substantial number of genetic variants have been associated with high-altitude adaptation (HAA), yet most of them are located in non-coding genomic regions, leaving their specific functions and underlying mechanisms largely unknown. In this study, we analyze whole-genome and transcriptome sequencing data from a self-established cohort comprising 61 native highlanders (NHs) and 164 acclimatized newcomers (ANs), identifying 6,586 cis- and 34,203 trans-expression quantitative trait loci (eQTLs), along with 130 cell type-specific eQTLs. By further combining these data with a large East Asia (~30% Tibetan) genome-wide association study (GWAS) cohort, we employ colocalization and causal inference analyses to prioritize 85 cis-eQTLs associated with HAA and identify several novel candidate causal genes, including EXOC8, which is experimentally confirmed to regulate erythroid differentiation. Additionally, network analysis of these causal genes uncovers multiple regulatory pathways, mainly involving energy metabolism, autophagy, ubiquitination and inflammation. Our study offers a comprehensive eQTL map and reveals causal chains of "variant-gene-phenotype" for HAA-related traits, which provides new insights into potential regulatory mechanisms and targets for prevention and treatment of altitude sickness.

Quantitative Trait Loci↗

Association among blood pressure, antihypertensive drugs, and amyotrophic lateral sclerosis.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal and incurable neurodegenerative disease. The impacts of antihypertensive drugs and blood pressure (BP) on ALS are currently debatable. OBJECTIVE: To evaluate the causal relationship involving antihypertensive drugs, BP, and ALS through a Mendelian randomization (MR) analysis. METHODS: The causal relationship between BP and ALS was evaluated by a bidirectional two-sample MR analysis. Then, a sensitivity analysis was performed using a secondary BP genome-wide association study. The drug-target MR was employed to evaluate the impact of antihypertensive drugs on ALS. Furthermore, we used cis-expression quantitative trait loci (cis-eQTLs) data from brain tissue and blood to validate the positive results by a summary-based MR method. RESULTS: We found that an increment in systolic BP (SBP) could elevate the risk of ALS (inverse-variance weighted [IVW] odds ratio [OR]&#x2009;=&#x2009;1.003; 95% confidence interval [95%CI]: 1.001-1.006; per 10-mmHg increment) and ALS might be protected by angiotensin-converting enzyme inhibitors (ACEIs; OR&#x2009;=&#x2009;0.970; 95%CI: 0.956-0.984; p&#x2009;=&#x2009;1.96&#x2009;&#xd7;&#x2009;10-5; per 10-mmHg decrement). A causal relationship was not observed between diastolic BP and other antihypertensive drugs in ALS. CONCLUSION: In the present study, genetic support for elevated SBP serves as a risk factor for ALS. Besides, ACEIs hold promise as a candidate for ALS.

Humans↗

Association of AGER genetic variants with chronic obstructive pulmonary disease susceptibility in Southern Chinese Han populations.

OBJECTIVE: Chronic obstructive pulmonary disease (COPD) remains a leading cause of disability and mortality among elderly populations. Studies indicate that AGER plays a critical regulatory role in the pathogenesis of respiratory disorders. However, the genetic variations in AGER to COPD susceptibility remain incompletely understood. This study employs a case-control design to investigate associations between AGER genetic variants and COPD risk in the Southern Chinese Han population. METHODS: This study enrolled 270 COPD patients and 271 healthy controls. AGER single-nucleotide polymorphisms (SNPs) were analysed using the MassARRAY iPLEX platform. Logistic regression models evaluated associations between AGER polymorphisms and COPD susceptibility, with false discovery rate (FDR) correction applied to mitigate multiple testing errors. SNP-SNP interactions were investigated through multifactor dimensionality reduction (MDR) analysis. Expression quantitative trait locus (eQTL) data from the GTEx database were further analysed to assess regulatory relationships between SNPs and AGER gene expression levels. RESULTS: This study showed that rs3134941 (G allele, OR = 0.21, 95% CI = 0.10-0.41, p (FDR)&#xa0;=&#xa0;0.001) and rs3131300 (G allele, OR = 0.32, 95% CI = 0.20-0.49, p (FDR)&#xa0;=&#xa0;0.0001) were significantly associated with a reduced susceptibility to COPD. MDR indicated that rs3131300 was the optimal predictive model for COPD risk. Additionally, initial mechanistic investigations utilizing the GTEx database identify rs3134941 (C&#xa0;> G) and rs3131300 (A&#xa0;> G) as significant expression quantitative trait loci for AGER mRNA in cell-cultured fibroblasts and whole blood. CONCLUSION: Our study demonstrated that AGER genetic variants might play a protective role in the progression of COPD.

Aged↗

EP300-mediated lactylation leads to ulcerative colitis via CD86-positive plasmacytoid dendritic cells: A Mendelian randomization and mediation analysis.

This study explores the potential mechanism between lactylation and ulcerative colitis (UC) using two-sample Mendelian randomization and multi-omics analysis. This study employed expression quantitative trait loci and protein quantitative trait loci as exposures, with UC from the Finnish database as the outcome, to conduct Mendelian randomization analysis on lactylation-related target genes, aiming to investigate the causal relationships between these exposures and the outcome. Sensitivity and pleiotropy tests, combined with colocalization analysis, are performed to identify the best target genes and ensure the robustness of the results. Finally, immune cells are included for mediation analysis between lactylation and UC to explore potential mechanisms of action. Through Mendelian randomization analysis combined with sensitivity and pleiotropy tests, 2 lactylation target genes were found to have a significant causal relationship with UC. Subsequent colocalization analysis confirmed EP300 as a potential gene target. After including immune cells in the mediation analysis, it was discovered that there is a potential mechanism involving EP300, CD86+ plasmacytoid dendritic cells (pDCs), and UC. There is a significant causal relationship between lactylation and UC. Furthermore, the lactylation-modified gene EP300 may lead to UC occurrence by regulating CD86+ pDCs.

Humans↗

Deciphering miRNA-mediated genetic architecture of immune cell subsets in hypertrophic scars and keloids: A 2-step Mendelian randomization study unveiling causal associations.

This study aimed to investigate the potential causal roles of specific circulating microRNAs (miRNAs) and immune cell subsets in the pathogenesis of hypertrophic scars and keloids using a 2-step Mendelian randomization framework. We employed a 2-sample Mendelian randomization approach to evaluate the causal relationships between miRNAs, immune cell genotypes, and scar phenotypes. The analysis integrated miRNA expression quantitative trait loci, immune cell genome-wide association studies, and scar datasets. A 2-step mediation analysis was conducted to assess the indirect effects of miRNAs on scars through immune cell genotypes, using inverse variance weighted methods and complementary sensitivity analyses to ensure robustness. Our analysis identified significant associations between specific miRNAs and scar phenotypes. Notably, miR-6887-5p exhibited a total effect on keloid formation risk (&#x3b2;&#x2005;=&#x2005;0.324, 95% confidence interval [CI]: 0.073-0.576) and a direct effect (&#x3b2;&#x2005;=&#x2005;0.283, 95% CI: 0.027, 0.538), with a marginally significant mediation effect through B-cell activating factor receptor on CD20- CD38- B cells (&#x3b2;&#x2005;=&#x2005;0.042, 95% CI: -0.001, 0.084, P&#x2005;=&#x2005;.047). For hypertrophic scars, miR-345-5p demonstrated a significant total effect (&#x3b2;&#x2005;=&#x2005;-0.501, 95% CI: -0.903, -0.099) and direct effect (&#x3b2;&#x2005;=&#x2005;-0.469, 95% CI: -0.872, -0.066), with a significant mediation effect through CD28+ CD45RA- CD8dim T cell percentage (&#x3b2;&#x2005;=&#x2005;-0.032, 95% CI: -0.062, -0.002, P&#x2005;=&#x2005;.034). miR-4801 showed a significant total effect (&#x3b2;&#x2005;=&#x2005;-0.246, 95% CI: -0.429, -0.064) and direct effect (&#x3b2;&#x2005;=&#x2005;-0.218, 95% CI: -0.402, -0.033), with a marginally significant mediation effect through T cell absolute count (&#x3b2;&#x2005;=&#x2005;-0.028, 95% CI: -0.057, -0.000, P&#x2005;=&#x2005;.043). These findings highlight the interplay between miRNAs and immune cell subsets in scar pathogenesis. This study provides preliminary evidence for the causal roles of specific miRNAs and immune cell subsets in scar formation, emphasizing the potential of miRNA-immune cell axes as therapeutic targets. While the identified associations offer important insights into the molecular mechanisms of scar heterogeneity, further validation through mechanistic studies and clinical trials is necessary to translate these genetic insights into clinical interventions.

Humans↗

New SNPs in the IGF2 gene and association between this gene and backfat thickness and lean meat content in Large White pigs.

IGF2-in3-G3072A is a causative mutation for paternally expressed quantitative trait loci on the p arm of porcine chromosome 2 with substantial effect on muscle growth and backfat thickness. The linkage disequilibrium between IGF2-in3-G3072A and IGF2-in7-G162C (IGF2-NciI) in four breeds and associations between these polymorphisms and growth and meat performance in pigs of the Large White breed were analysed. A significant effect of these polymorphisms on backfat thickness and lean meat content was found. In addition, we identified two new single nucleotide polymorphisms (SNPs) in intron 7 of the gene. The existence of complete linkage disequilibrium between IGF2-in3-G3072A locus in the population under study where the locus segregated and SNPs in intron 7 of the IGF2 gene detectable with simple and reliable polymerase chain reaction-restriction fragment length polymorphism techniques (G162C, C179G and G186T) offer possibilities to use these SNPs for genotyping of quantitative trait nucleotide in Large White and Landrace breeds.

Animals↗

Identification of Rare Noncoding Variants in Familial Nonmedullary Thyroid Carcinoma.

BACKGROUND: Familial nonmedullary thyroid carcinoma (FNMTC) occurs when three or more family members are affected by usually papillary thyroid carcinoma (PTC), the most common form of NMTC. While the heritability to NMTC is among the highest of all cancers, the genetic determinants among NMTC families are not well understood. Here, we aim to understand the contribution of rare noncoding germline variants in the etiology of FNMTC. METHODS: We previously reported whole-genome sequencing (WGS) and linkage analysis in 17 PTC families and reported on 41 protein-coding variants in 40 genes that cosegregated with PTC in 11 of the families. Herein, we further leveraged our WGS data to include noncoding variants in our analysis for all 17 families. We hypothesized that most of the pathogenic noncoding variants would be located in theoretical or empirically determined regulatory regions that demonstrate at a minimum, basal thyroid expression, a positive family linkage score, and co-segregation among PTC-affected individuals. To test this hypothesis, we adopted a unique filtering strategy to identify variants that occurred in known DNA elements and transcription factor binding sites, near regions known to impact on gene expression or splicing in thyroid tissue, and/or in characterized thyroid enhancers. We annotated variants using two analyses (ENCODE and transcription factor binding site) within the BasePlayer software. We separately analyzed (1) expression quantitative trait loci, (2) splicing quantitative trait loci, and (3) thyroid enhancers. We then ranked variants according to predicted pathogenicity and performed Sanger sequencing in all individuals of each family. RESULTS: In total, 121 variants were selected based on in-silico prediction and our custom ranking analysis in each pedigree. Of these, 56 variants showed cosegregation among all PTC-affected individuals and were absent from unaffected individuals. This included candidate variants from five of the six PTC families for whom no protein-coding variants were previously found. CONCLUSION: Our data suggest that noncoding variants are important in the etiology of FNMTC and provide a framework for identifying noncoding germline variants using a novel approach. Further studies are needed to functionally characterize these variants to better understand the molecular mechanism of their pathogenicity.

Humans↗

Programmed cell death and risk of diabetic retinopathy: a Mendelian randomization study.

BACKGROUND: Programmed cell death (PCD) plays an important role in diabetic retinopathy (DR); however, the underlying genetic mechanisms remain unclear. We used Mendelian randomization (MR) to investigate the causal relationships between PCD-related genes and DR. This study aimed to investigate the effects of PCD on the risk of DR by conducting MR analysis. METHODS: Summary statistics from gene expression quantitative trait loci (eQTL) studies (31,684 Europeans) were analyzed. Genetic instrumental variables were selected using cis-eQTL single-nucleotide polymorphisms (SNPs; P&#x2009;<&#x2009;5&#x2009;&#xd7;&#x2009;10-&#x2009;8). Summary data-based MR (SMR) was employed to assess causal associations between PCD-related genes and DR, with three additional MR methods used for sensitivity testing. Bayesian colocalization was used to examine the shared regulatory mechanisms between PCD QTLs and DR risk loci. RESULTS: Sensitivity and colocalization analyses revealed six genes that affected DR: cathepsin H (CTSH), NAD(P)H: quinone oxidoreductase 1 (NQO1), tribbles pseudokinase 3 (TRIB3), and phosphoglycerate mutase 5 (PGAM5), which increased DR risk, and iron-responsive element binding protein 2 (IREB2) and tumor necrosis factor (TNF), which exhibited protective effects. Multivariate MR confirmed significant causal effects for CTSH, IREB2, and PGAM5 (p&#x2009;<&#x2009;0.050). Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis (including 10 STRING-derived genes) revealed that 13 genes were enriched in necroptosis, apoptosis, mitophagy, and TNF signaling pathways in DR. CONCLUSIONS: This MR study supports the causal involvement of PCD in DR and identifies candidate genes (CTSH, IREB2, PGAM5, NQO1, TRIB3, and TNF) for therapeutic targeting or biomarker development in DR prevention or diagnosis.

Humans↗

Multi-omics Mendelian randomization integrating RNA-seq, eQTL and pQTL data revealed CPXM1 as a potential drug target for osteoporosis.

Osteoporosis, a prevalent skeletal disorder characterized by decreased bone mineral density and increased fracture risk, continues to be a major global health concern. Traditional treatments for osteoporosis have limited efficacy and safety profiles, highlighting the need for novel therapeutic targets. This study integrates multi-omics data, including RNA-seq, expression quantitative trait loci (eQTL), and protein quantitative trait loci (pQTL) data, through Mendelian randomization (MR) to identify potential drug targets for osteoporosis. By leveraging bidirectional two-sample MR analysis, we identified CPXM1 (Carboxypeptidase X, M14 family member 1) as a novel gene that is causally linked to osteoporosis risk. Through transcriptomic and proteomic validation, we demonstrate that CPXM1 was upregulated in aged bone tissues and osteoporotic conditions in both human and murine models. Gene set enrichment analysis (GSEA) revealed significant dysregulation of bone homeostasis pathways, including increased extracellular matrix degradation and suppression of osteoblast differentiation in aged mice. Furthermore, phenome-wide association studies (PheWAS) confirmed minimal off-target effects of CPXM1, reinforcing its potential as a therapeutic target. Finally, computational drug repurposing predicted several promising drug candidates, including Doxorubicin, 5-Fluorouracil, and 2-Methylcholine, which may target CPXM1 pathways for osteoporosis treatment. These findings highlight CPXM1 as a potential biomarker and therapeutic target, offering new avenues for osteoporosis therapy.

Osteoporosis↗

Integrated single-cell RNA sequencing and mendelian randomization analysis identifies causal immune-related driver genes in the heart failure inflammatory microenvironment.

BACKGROUND: Heart failure (HF) is a major global cause of cardiovascular death and disability. Chronic inflammation and immune dysregulation are critical in its development. The cardiac immune microenvironment, especially macrophages, drives HF progression, yet its molecular mechanisms and prognostic impact are not fully clear. This study aimed to identify causal immune-related driver genes in the HF inflammatory microenvironment. METHODS: We combined single-cell RNA sequencing (scRNA-seq) and Mendelian randomization (MR) to study how the inflammatory immune microenvironment affects HF risk. Using two public scRNA-seq datasets, we identified differentially expressed genes (DEGs) in HF heart tissues and selected 489 candidate genes. Causal relationships between these genes and HF were tested using expression quantitative trait loci (eQTL) data and HF genome-wide association study (GWAS) summary statistics. RESULTS: MR analysis showed that 65 genes were causally linked to HF risk. These genes were enriched in pathways related to cardiomyopathy, leukocyte migration, natural killer (NK) cell cytotoxicity, neutrophil extracellular traps, and NF-&#x3ba;B signaling. HF hearts displayed increased levels of macrophages, T cells, B cells, lymphoid cells, and mast cells, while neutrophils were reduced. CONCLUSIONS: Our integrated analysis reveals the central role of the cardiac inflammatory immune microenvironment in HF and identifies 65 key genes causally associated with HF susceptibility. These genes influence specific immune pathways and cell infiltration, shaping HF progression, and provide a basis for developing new biomarkers and immune-targeted therapies.

Heart failure (HF)↗

Genetic Association of the Transcriptome and Immunoglobulin G N-glycome with Cognitive Function.

OBJECTIVE: Immunoglobulin G (IgG) N-glycosylation is associated with mild cognitive impairment through the regulation of inflammatory balance; however, the underlying mechanisms remain unclear. METHODS: Our study utilized a post-genome-wide association studies (GWAS) method that integrated GWAS data for cognitive function with gene expression quantitative trait loci (eQTL), protein QTL (pQTL), and IgG N-glycan-QTL data. RESULTS: Mendelian randomization (MR) analyses suggested bidirectional causalities between glycan peaks (GPs) and cognitive function, with GP7, GP12, and GP19 showing a causal effect on cognitive function, while cognitive function conversely showed a causal effect on GP1 and GP8. Two proteins and 10 genes were implicated in the regulation of IgG N-glycosylation. Furthermore, multivariable MR results suggested complex causalities between genes/proteins and IgG N-glycans, which jointly promote or independently affect cognitive function. CONCLUSION: Our study reveals a novel mechanism by which genes, proteins, and modified IgG N-glycans converge to pathologically affect cognitive function.

Immunoglobulin G↗

Quantitative trait loci mapping of gene expression and chromatin accessibility in primary fibroblasts reveals shared allelic effects between Latin American and European ancestries.

BACKGROUND: Quantitative Trait Locus (QTL) analysis of molecular data has identified genetic variants associated with traits such as gene expression, and colocalization of these functional QTL with GWAS risk loci has offered insights into the genetic basis of human disease. We employed gene expression (RNA-seq) and chromatin accessibility (ATAC-seq) obtained from human primary fibroblasts to investigate quantitative trait loci (QTLs) in cohorts ascertained for bipolar disorder of European (n&#x2009;=&#x2009;150) and Latin American (n&#x2009;=&#x2009;96) ancestries. RESULTS: Leveraging data from three countries of origin (The Netherlands, Colombia, Costa Rica) within our cohort, we characterized differences among individuals at the SNP, gene, and accessible-chromatin levels to compute ancestry-specific expression (e)QTLs and chromatin-accessibility (ca)QTLs. Across ancestries, we observed R2&#x2009;&#x2265;&#x2009;0.93 for eQTL effect sizes and R2&#x2009;&#x2265;&#x2009;0.95 for caQTLs, indicating a high degree of concordance. Integrating chromatin data with expression and genotype information enabled precise fine-mapping of eQTLs, yielding 203 genes with high-confidence (posterior probability&#x2009;>&#x2009;90%) candidate regulatory pathways. In downstream analyses, transcriptome-wide (TWAS) and chromatin-wide (CWAS) association studies with brain- and skin-related GWAS identified 36 TWAS-significant genes and 77 CWAS-significant open chromatin regions. CONCLUSIONS: These findings underscore the shared genetic regulatory mechanisms across European and Latin American ancestries, while demonstrating that ancestry-specific reference panels enhance the accuracy of TWAS and CWAS in diverse populations. More broadly, this study highlights the value of paired multi-omic datasets from diverse cohorts for interpreting disease-associated genetic variation.

Humans↗

Analysis of phase of LUCIFERASE expression reveals novel circadian quantitative trait loci in Arabidopsis.

In response to exogenous rhythms of light and temperature, most organisms exhibit endogenous circadian rhythms (i.e. cycles of behavior and gene expression with a periodicity of approximately 24 h). One of the defining characteristics of the circadian clock is its ability to synchronize (entrain) to an environmental rhythm. Entrainment is arguably the most salient feature of the clock in evolutionary terms. Previous quantitative trait studies of circadian characteristics in Arabidopsis (Arabidopsis thaliana) considered leaf movement under constant (free-running) conditions. This study, however, addressed the important circadian parameter of phase, which reflects the entrained relationship between the clock and the external cycle. Here it is shown that, when exposed to the same photoperiod, Arabidopsis accessions differ dramatically in phase. Variation in the timing of circadian LUCIFERASE expression was used to map loci affecting the entrained phase of the clock in a recombinant population derived from two geographically distant accessions, Landsberg erecta and Cape Verde Islands. Four quantitative trait loci (QTL) were found with major effects on circadian phase. A QTL on chromosome 5 contained SIGNALING IN RED LIGHT REDUCED 1 and PSEUDORESPONSE REGULATOR 3, both genes known to affect the circadian clock. Previously unknown polymorphisms were found in both genes, making them candidates for the effect on phase. Fine mapping of two other QTL highlighted genomic regions not previously identified in any circadian screens, indicating their effects are likely due to genes not hitherto considered part of the circadian system.

Amino Acid Sequence↗