We live in a complex chemical environment where there are an estimated 350 000 chemical compounds or mixtures commercially produced. A strong body of literature shows that there are time points during early development when an organism's epigenome is particularly sensitive to chemicals in its environment. What is less understood is how gene-environment and epigenetic-environment interactions change with age. This question is bidirectional: (1) how do chemicals in the environment affect the aging process and (2) how does aging affect an organism's response to its chemical environment? The study of gene-environment interactions with age is especially important because, in many parts of the world, older individuals are a large and rapidly growing proportion of the population and because aging is a process universal to most of the animal kingdom. Epigenetics has emerged as a crucial framework for studying aging as epigenetic pathways, often triggered by environmental stimuli, have been shown to be essential regulators of the aging process. In this perspective article, we delineate the connection between aging, epigenetics, and environmental exposures. We discuss why it is essential to consider age when researching how an organism interacts with its environment. We describe recent advances in understanding how the chemical environment affects aging and the gap in research on how age affects an organism's response to the environment. Finally, we highlight how model organisms and network approaches can help fill this crucial gap. Taken together, systemic changes that occur in the epigenome with age indicate that adult organisms cannot be treated as a homogeneous population and that there are discrete mechanisms modulating the aging epigenome that we do not yet understand.

Type 2 diabetes (T2D) has become an increasingly challenging health burden due to its high morbidity, mortality, and heightened prevalence worldwide. Although dietary and nutritional imbalances have long been recognized as key risk factors for T2D, the underlying mechanisms remain unclear. The advent of nutritional systems biology, a field that aims to elucidate the interactions between dietary nutrients and endogenous molecular entities in disease-related tissues, offers unique opportunities to unravel the complex mechanisms underlying the health-modifying capacities of nutritional molecules. The recent revolutionary advances in omics technologies have particularly empowered this incipient field. In this review, we discuss the applications of multi-omics approaches toward a systems-level understanding of how dietary patterns and particular nutrients modulate the risk of T2D. We focus on nutritional studies utilizing transcriptomics, epigenomomics, proteomics, metabolomics, and microbiomics, and integration of diverse omics technologies. We also summarize the potential molecular mechanisms through which nutritional imbalances contribute to T2D pathogenesis based on these studies. Finally, we discuss the remaining challenges of nutritional systems biology and how the field can be optimized to further our understanding of T2D and guide disease management via nutritional interventions.

Elucidating the mechanisms of complex diseases such as cardiovascular disease (CVD) remains a significant challenge due to multidimensional alterations at molecular, cellular, tissue, and organ levels. To better understand CVD and offer insights into the underlying mechanisms and potential therapeutic strategies, data from multiple omics types (genomics, epigenomics, transcriptomics, metabolomics, proteomics, microbiomics) from both humans and model organisms have become available. However, individual omics data types capture only a fraction of the molecular mechanisms. To address this challenge, there have been numerous efforts to develop integrative genomics methods that can leverage multidimensional information from diverse data types to derive comprehensive molecular insights. In this review, we summarize recent methodological advances in multidimensional omics integration, exemplify their applications in cardiovascular research, and pinpoint challenges and future directions in this incipient field.

Caenorhabditis elegans is a valuable model to study organ, tissue, and cell-type responses to external cues. However, the nematode comprises multiple syncytial tissues with spatial coordinates corresponding to distinct nuclear transcriptomes. Here, we present a single-nucleus RNA sequencing (snRNA-seq) protocol that aims to overcome difficulties encountered with single-cell RNA sequencing in C. elegans. We describe steps for isolating C. elegans nuclei for downstream applications including snRNA-seq applied to the context of alcohol exposure. For complete details on the use and execution of this protocol, please refer to Truong et al. (2023).¹.

Background

Non-alcoholic fatty liver disease (NAFLD) encompasses benign steatosis and more severe conditions such as non-alcoholic steatohepatitis (NASH), cirrhosis, and liver cancer. This chronic liver disease has a poorly understood etiology and demonstrates sexual dimorphisms. We aim to examine the molecular mechanisms underlying sexual dimorphisms in NAFLD pathogenesis through a comprehensive multi-omics study. We integrated genomics (DNA variations), transcriptomics of liver and adipose tissue, and phenotypic data of NAFLD derived from female mice of ~ 100 strains included in the hybrid mouse diversity panel (HMDP) and compared the NAFLD molecular pathways and gene networks between sexes.

Results

We identified both shared and sex-specific biological processes for NAFLD. Adaptive immunity, branched chain amino acid metabolism, oxidative phosphorylation, and cell cycle/apoptosis were shared between sexes. Among the sex-specific pathways were vitamins and cofactors metabolism and ion channel transport for females, and phospholipid, lysophospholipid, and phosphatidylinositol metabolism and insulin signaling for males. Additionally, numerous lipid and insulin-related pathways and inflammatory processes in the adipose and liver tissue appeared to show more prominent association with NAFLD in male HMDP. Using data-driven network modeling, we identified plausible sex-specific and tissue-specific regulatory genes as well as those that are shared between sexes. These key regulators orchestrate the NAFLD pathways in a sex- and tissue-specific manner. Gonadectomy experiments support that sex hormones may partially underlie the sexually dimorphic genes and pathways involved in NAFLD.

Conclusions

Our multi-omics integrative study reveals sex- and tissue-specific genes, processes, and networks underlying sexual dimorphism in NAFLD and may facilitate sex-specific precision medicine.

Single-cell transcriptomic platforms provide an opportunity to map an organism's response to environmental cues with high resolution. Here, we applied single-nucleus RNA sequencing (snRNA-seq) to establish the tissue and cell type-resolved transcriptome of the adult C. elegans and characterize the inter- and trans-generational transcriptional impact of ethanol. We profiled the transcriptome of 41,749 nuclei resolving into 31 clusters, representing a diverse array of adult cell types including syncytial tissues. Following exposure to human-relevant doses of alcohol, several germline, striated muscle, and neuronal clusters were identified as being the most transcriptionally impacted at the F1 and F3 generations. The effect on germline clusters was confirmed by phenotypic enrichment analysis as well as by functional validation, which revealed a remarkable inter- and trans-generational increase in germline apoptosis, aneuploidy, and embryonic lethality. Together, snRNA-seq represents a valuable approach for the detailed examination of an adult organism's response to environmental exposures.

Mouse models have been used extensively to study human coronary artery disease (CAD) or atherosclerosis and to test therapeutic targets. However, whether mouse and human share similar genetic factors and pathogenic mechanisms of atherosclerosis has not been thoroughly investigated in a data-driven manner. We conducted a cross-species comparison study to better understand atherosclerosis pathogenesis between species by leveraging multiomics data. Specifically, we compared genetically driven and thus CAD-causal gene networks and pathways, by using human GWAS of CAD from the CARDIoGRAMplusC4D consortium and mouse GWAS of atherosclerosis from the Hybrid Mouse Diversity Panel (HMDP) followed by integration with functional multiomics human (STARNET and GTEx) and mouse (HMDP) databases. We found that mouse and human shared >75% of CAD causal pathways. Based on network topology, we then predicted key regulatory genes for both the shared pathways and species-specific pathways, which were further validated through the use of single cell data and the latest CAD GWAS. In sum, our results should serve as a much-needed guidance for which human CAD-causal pathways can or cannot be further evaluated for novel CAD therapies using mouse models.

The etiology of non-alcoholic fatty liver disease (NAFLD), the most common form of chronic liver disease, is poorly understood. To understand the causal mechanisms underlying NAFLD, we conducted a multi-omics, multi-tissue integrative study using the Hybrid Mouse Diversity Panel, consisting of ∼100 strains of mice with various degrees of NAFLD. We identified both tissue-specific biological processes and processes that were shared between adipose and liver tissues. We then used gene network modeling to predict candidate regulatory genes of these NAFLD processes, including Fasn, Thrsp, Pklr, and Chchd6. In vivo knockdown experiments of the candidate genes improved both steatosis and insulin resistance. Further in vitro testing demonstrated that downregulation of both Pklr and Chchd6 lowered mitochondrial respiration and led to a shift toward glycolytic metabolism, thus highlighting mitochondria dysfunction as a key mechanistic driver of NAFLD.

The etiology of non-alcoholic fatty liver disease (NAFLD), the most common form of chronic liver disease, is poorly understood. To understand the causal mechanisms underlying NAFLD, we conducted a multi-omics, multi-tissue integrative study using the Hybrid Mouse Diversity Panel, consisting of ∼100 strains of mice with various degrees of NAFLD. We identified both tissue-specific biological processes and processes that were shared between adipose and liver tissues. We then used gene network modeling to predict candidate regulatory genes of these NAFLD processes, including Fasn, Thrsp, Pklr, and Chchd6. In vivo knockdown experiments of the candidate genes improved both steatosis and insulin resistance. Further in vitro testing demonstrated that downregulation of both Pklr and Chchd6 lowered mitochondrial respiration and led to a shift toward glycolytic metabolism, thus highlighting mitochondria dysfunction as a key mechanistic driver of NAFLD.