Systems genetics approaches for understanding complex traits with relevance for human disease

Causal effects of circulating inflammatory proteins on oral phenotypes: Deciphering immune-mediated profiles in the host-oral axis

BACKGROUND

Oral manifestations function as precursors to potential systemic pathologies, signaling early indicators of underlying health complications or immunological dysfunctions. Within these dynamics, circulating inflammatory proteins are recognized as critical mediators in immunopharmacology, bridging holistic health, immune response, and oral health.

METHODS

We employed genetic data from genome-wide association studies to perform comprehensive Mendelian randomization (MR) analyses on 91 circulating inflammatory proteins and 17 oral phenotypes. Six MR algorithms and five auxiliary control measures were utilized to estimate the causal effects. Subsequently, the MR-Bayesian model averaging (MR-BMA) approach was conducted to elucidate the priorities in host-oral communication, followed by network analyses to explore the interactions among phenotypes.

RESULTS

After multiple corrections, MR identified five genetically predicted proteins associated with oral phenotypes. Specifically, FGF21 was correlated with Nteeth and DMFS; hGDNF with gingival pain; CCL4 with stomatitis; and S100A12 with denture use. The causal associations remained robust in sensitivity analyses. Nine protein-phenotype clusters were prioritized using MR-BMA. Among these, S100A12, FGF19, FGF21, and CCL4 exhibited extensive correlations with various oral phenotypes.

CONCLUSIONS

Our study offers novel genetic insights into the causal relationships, prioritizations, and connections between circulating inflammatory proteins and oral phenotypes. These findings comprehensively depict immune-mediated proteomic profiles underlying the host-oral axis, providing significant implications for clinical practice, public health, and immunopharmacology.

Unlocking metabolic insights with mouse genetic diversity

As part of EMBO Journal’s 2024 metabolism methods series, this commentary revisits the impact of genetics on metabolic studies, enabling dissection of novel mechanisms and phenotypes.

A PLURIPOTENT STEM CELL PLATFORM FOR IN VITRO SYSTEMS GENETICS STUDIES OF MOUSE DEVELOPMENT

The directed differentiation of pluripotent stem cells (PSCs) from panels of genetically diverse individuals is emerging as a powerful experimental system for characterizing the impact of natural genetic variation on developing cell types and tissues. Here, we establish new PSC lines and experimental approaches for modeling embryonic development in a genetically diverse, outbred mouse stock (Diversity Outbred mice). We show that a range of inbred and outbred PSC lines can be stably maintained in the primed pluripotent state (epiblast stem cells -- EpiSCs) and establish the contribution of genetic variation to phenotypic differences in gene regulation and directed differentiation. Using pooled in vitro fertilization, we generate and characterize a genetic reference panel of Diversity Outbred PSCs (n = 230). Finally, we demonstrate the feasibility of pooled culture of Diversity Outbred EpiSCs as "cell villages", which can facilitate the differentiation of large numbers of EpiSC lines for forward genetic screens. These data can complement and inform similar efforts within the stem cell biology and human genetics communities to model the impact of natural genetic variation on phenotypic variation and disease-risk.

Genetics unravels protein-metabolite relationships

Integrating molecular traits into genetic studies enhances our understanding of how DNA variation influences complex clinical and physiological phenotypes. In a recent article, Benson and colleagues apply this systems genetics approach with proteomics and metabolomics data in plasma from humans to identify and validate several previously unrecognized causal protein-metabolite associations.

Leveraging the transcriptome to further our understanding of GWAS findings: eQTLs associated with genes related to LDL and LDL subclasses, in a cohort of African Americans

Background: GWAS discoveries often pose a significant challenge in terms of understanding their underlying mechanisms. Further research, such as an integration with expression quantitative trait locus (eQTL) analyses, are required to decipher the mechanisms connecting GWAS variants to phenotypes. An eQTL analysis was conducted on genes associated with low-density lipoprotein (LDL) cholesterol and its subclasses, with the aim of pinpointing genetic variants previously implicated in GWAS studies focused on lipid-related traits. Notably, the study cohort consisted of African Americans, a population characterized by a heightened prevalence of hypercholesterolemia. Methods: A comprehensive differential expression (DE) analysis was undertaken, with a dataset of 17,948 protein-coding mRNA transcripts extracted from the whole-blood transcriptomes of 416 samples to identify mRNA transcripts associated with LDL, with further granularity delineated between small LDL and large LDL subclasses. Subsequently, eQTL analysis was conducted with a subset of 242 samples for which whole-genome sequencing data were available to identify single-nucleotide polymorphisms (SNPs) associated with the LDL-related mRNA transcripts. Lastly, plausible functional connections were established between the identified eQTLs and genetic variants reported in the GWAS catalogue. Results: DE analysis revealed 1,048, 284, and 94 mRNA transcripts that exhibited differential expression in response to LDL, small LDL, and large LDL, respectively. The eQTL analysis identified a total of 9,950 significant SNP-mRNA associations involving 6,955 SNPs including a subset 101 SNPs previously documented in GWAS of LDL and LDL-related traits. Conclusion: Through comprehensive differential expression analysis, we identified numerous mRNA transcripts responsive to LDL, small LDL, and large LDL. Subsequent eQTL analysis revealed a rich landscape of eQTL-mRNA associations, including a subset of eQTL reported in GWAS studies of LDL and related traits. The study serves as a testament to the important role of integrative genomics in unraveling the enigmatic GWAS relationships between genetic variants and the complex fabric of human traits and diseases.

Special Issue "Deployment of Proteomics Approaches in Biomedical Research"

Many angles of personalized medicine, such as diagnostic improvements, systems biology [...].