Summary-data based Mendelian randomization identifies gene expression regulatory polymorphisms associated with bovine paratuberculosis by modulation of the nuclear factor Kappa β (NF-κß)-mediated inflammatory response

An integrative approach to identifying NPC1 as a susceptibility gene for gestational diabetes mellitus

OBJECTIVE

The objective of this study was to identify a novel gene and its potential mechanisms associated with susceptibility to gestational diabetes mellitus (GDM) through an integrative approach.

METHODS

We analyzed data from genome-wide association studies (GWAS) of GDM in the FinnGen R11 dataset (16,802 GDM cases and 237,816 controls) and Genotype Tissue Expression v8 expression quantitative trait locus data. We used summary-data-based Mendelian randomization to determine associations between transcript levels and phenotypes, transcriptome-wide association studies to provide insights into gene-trait associations, multi-marker analysis of genomic annotation to perform gene-based analysis, genome-wide complex trait analysis-multivariate set-based association test-combo to determine gene prioritization, and polygenic priority scores to prioritize the causal genes to screen candidate genes. Subsequent Mendelian randomization analysis was performed to infer causality between the candidate genes and GDM and phenome-wide association study (PheWAS) analysis was used to explore the associations between selected genes and other characteristics. Furthermore, to gain a deeper understanding of the functional implications of these susceptibility genes, GeneMANIA analysis was used to determine the fundamental biological functions of the therapeutic targets and protein-protein interaction network analysis was performed to identify intracellular protein interactions.

RESULTS

We identified two novel susceptibility genes associated with GDM: NPC1 and KIAA1191. Magnetic resonance imaging revealed a strong correlation between NPC1 expression levels and a lower incidence of GDM (odds ratio: 0.922, 95% confidence interval: 0.866-0.981, p = 0.011). PheWAS at the gene level indicated that NPC1 was not associated with any other trait. The biological significance of this gene was evidenced by its strong association with sterol metabolism.

CONCLUSION

Our study identified NPC1 as a novel gene whose predicted expression level is linked to a reduced risk of GDM, providing new insights into the genetic framework of this disease.

Early Growth Response Factor 4 (EGR4) Expression in Gut Tissues and Regional Lymph Nodes of Cattle with Different Types of Paratuberculosis-Associated Lesions: Potential Role of EGR4 in Resilience to Paratuberculosis

Summary-data-based Mendelian randomization (SMR) analysis identified a novel cis-expression quantitative loci (cis-eQTL) associated with the upregulation of the expression of the early growth response factor 4 (EGR4) gene in animals with paratuberculosis (PTB)-associated multifocal lesions, which has been suggested to be modulating the NF-kβ-induced proinflammatory immune response to Mycobacterium avium subsp. paratuberculosis (Map) infection. To confirm these findings and to study the role of EGR4 expression in PTB resilience, the number of EGR4-expressing cells were analysed in paraffin-fixed gut tissues and regional lymph nodes of naturally Map-infected Holstein Friesian cows with focal, multifocal (subclinical and clinical), and diffuse lesions (intermediate and multibacillary), and in controls without lesions by quantitative anti-EGR4 immunohistochemistry. Subclinical animals with multifocal lesions showed a significantly higher number of EGR4-positive cells and were sacrificed at a significantly older average age than the remaining groups (p < 0.001 in all cases). We hypothesize that EGR4 could be mitigating the negative impact of Map infection on host clinical status through its involvement in three molecular mechanisms that promote resilience: (i) limiting NF-kβ-mediated proinflammatory responses, (ii) controlling tissue damage, acting as a brake on T-cell proliferation and cytokine production, and (iii) favouring tissue repair through interaction with epidermal growth factor receptor (EGFR).

Mendelian randomisation to uncover causal associations between conformation, metabolism, and production as potential exposure to reproduction in German Holstein dairy cattle

BACKGROUND

Reproduction is vital to welfare, health, and economics in animal husbandry and breeding. Health and reproduction are increasingly being considered because of the observed genetic correlations between reproduction, health, conformation, and performance traits in dairy cattle. Understanding the detailed genetic architecture underlying these traits would represent a major step in comprehending their interplay. Identifying known, putative or novel associations in genomics could improve animal health, welfare, and performance while allowing further adjustments in animal breeding.

RESULTS

We conducted genome-wide association studies for 25 different traits belonging to four different complexes, namely reproduction (n = 13), conformation (n = 6), production (n = 3), and metabolism (n = 3), using a cohort of over 235,000 dairy cows. As a result, we identified genome-wide significant signals for all the studied traits. The obtained summary statistics collected served as the input for a Mendelian randomisation approach (GSMR) to infer causal associations between putative exposure and reproduction traits. The study considered conformation, production, and metabolism as exposure and reproduction as outcome. A range of 139 to 252 genome-wide significant SNPs per combination were identified as instrumental variables (IVs). Out of 156 trait combinations, 135 demonstrated statistically significant effects, thereby enabling the identification of the responsible IVs. Combinations of traits related to metabolism (38 out of 39), conformation (68 out of 78), or production (29 out of 39) were found to have significant effects on reproduction. These relationships were partially non-linear. Moreover, a separate variance component estimation supported these findings, strongly correlating with the GSMR results and offering suggestions for improvement. Downstream analyses of selected representative traits per complex resulted in identifying and investigating potential physiological mechanisms. Notably, we identified both trait-specific SNPs and genes that appeared to influence specific traits per complex, as well as more general SNPs that were common between exposure and outcome traits.

CONCLUSIONS

Our study confirms the known genetic associations between reproduction traits and the three complexes tested. It provides new insights into causality, indicating a non-linear relationship between conformation and reproduction. In addition, the downstream analyses have identified several clustered genes that may mediate this association.

Artificial intelligence-driven pharmaceutical industry: A paradigm shift in drug discovery, formulation development, manufacturing, quality control, and post-market surveillance

The advent of artificial intelligence (AI) has catalyzed a profound transformation in the pharmaceutical industry, ushering in a paradigm shift across various domains, including drug discovery, formulation development, manufacturing, quality control, and post-market surveillance. This comprehensive review examines the multifaceted impact of AI-driven technologies on all stages of the pharmaceutical life cycle. It discusses the application of machine learning algorithms, data analytics, and predictive modeling to accelerate drug discovery processes, optimize formulation development, enhance manufacturing efficiency, ensure stringent quality control measures, and revolutionize post-market surveillance methodologies. By describing the advancements, challenges, and future prospects of harnessing AI in the pharmaceutical landscape, this review offers valuable insights into the evolving dynamics of drug development and regulatory practices in the era of AI-driven innovation.

Alternative splicing of pre-mRNA modulates the immune response in Holstein cattle naturally infected with Mycobacterium avium subsp. paratuberculosis

Little is known about the role of alternative splicing (AS) in regulating gene expression in Mycobacteria-infected individuals in distinct stages of infection. Pre-mRNA AS consists of the removal of introns and the assembly of exons contained in eukaryotic genes. AS events can influence transcript stability or structure with important physiological consequences. Using RNA-Seq data from peripheral blood (PB) and ileocecal valve (ICV) samples collected from Holstein cattle with focal and diffuse paratuberculosis (PTB)-associated histopathological lesions in gut tissues and without lesions (controls), we detected differential AS profiles between the infected and control groups. Four of the identified AS events were experimentally validated by reverse transcription-digital droplet PCR (RT-ddPCR). AS events in several genes correlated with changes in gene expression. In the ICV of animals with diffuse lesions, for instance, alternatively spliced genes correlated with changes in the expression of genes involved in endocytosis, antigen processing and presentation, complement activation, and several inflammatory and autoimmune diseases in humans. Taken together, our results identified common mechanisms of AS involvement in the pathogenesis of PTB and human diseases and shed light on novel diagnostic and therapeutic interventions to control these diseases.