Metabolic disorders disrupt normal metabolism, the process of converting food to energy on a cellular level. Metabolic disorders such as obesity, Type 2 diabetes (T2D), non-alcoholic fatty liver disease (NAFLD), and others collectively contribute to substantial global mortality. Leveraging multi-modal data across various metabolic disorders is key to gaining comprehensive insights into these molecular mechanisms.

In this 'Monthly Dataset Roundup,' we highlight important bulk RNA-seq and single-cell RNA-seq datasets on metabolic disorders. Polly's high-quality ML-ready, multi-modal datasets are valuable resources for unraveling molecular mechanisms, predicting biomarkers, and identifying potential targets in metabolic disorders.

Dataset 1

Transcriptomic profiling across the spectrum of non-alcoholic fatty liver disease.

Dataset ID: GSE135251_GPL18573
Year of Publication: 2020
Experiment Type: Bulk RNA-seq
Total Samples: 216
Organism: Homo sapiens
‍Reference Link: Publication

Summary

The pathophysiological mechanisms that drive NAFLD progression remain poorly understood. This multicenter study characterized the transcriptional changes that occur as liver disease progresses. 216 snap-frozen liver biopsies were studied, comprising 206 NAFLD cases with different fibrosis stages and ten controls. Samples underwent high-throughput RNA sequencing. This study provides novel insights into transcriptional changes during liver disease evolution and progression as well as proof of principle that transcriptomic changes reveal potentially tractable biomarkers for NAFLD fibrosis.

Identifying differentially expressed genes in the control and patient groups is the first step in discovering biomarkers. To demonstrate how Polly can help you enhance your analysis, we performed differential gene expression analysis on harmonized and normalized data of NAFLD and control. The heatmap illustrates genes that exhibit significant differential expression, meeting the criteria of log fold change (Log FC) >= |1| and a p-value of <= 0.01.

Dataset 2

A single-cell atlas of human white adipose tissue

Dataset ID: GSE176171_GPL18573
Year of Publication: 2022
Experiment Type: Single-cell RNA-seq
Total Samples: 50
Organism: Homo sapiens
‍Reference Link: Publication

Summary

White adipose tissue (WAT), once considered morphologically and functionally bland, is now acknowledged as dynamic, plastic, heterogeneous, and involved in various biological processes, encompassing energy homeostasis, glucose and lipid handling, blood pressure control, and host defense. High-fat feeding and metabolic stressors induce profound changes in adipose morphology, physiology, and cellular composition, with alterations in adiposity linked to insulin resistance, dyslipidemia, and T2D. In this study, the authors present detailed cellular atlases of human and murine subcutaneous and visceral white fat at single-cell resolution across a range of body weights.

The research identifies subpopulations of adipocytes, adipose stem and progenitor cells (ASPCs), and vascular and immune cells, illustrating commonalities and differences across species and dietary conditions. The authors establish connections between specific cell types and an increased risk of metabolic disease, offering an initial blueprint for a comprehensive set of interactions within the adipose niche in leanness and obesity. These data constitute a comprehensive resource for exploring genes, traits, and cell types in the function of WAT across species, depots, and nutritional conditions.

Here, in the figure below, the curated cell types in the study are highlighted to enhance the visualization experience with Polly.

Dataset 3

The long noncoding RNA TUNAR modulates Wnt signaling and regulates human β-cell proliferation.

Dataset ID: GSE99503_GPL11154
Year of Publication: 2021
Experiment Type: Bulk RNA-seq
Total Samples: 12
Organism: Homo sapiens
‍Reference Link: Publication

Summary

Pancreatic islets harbor numerous long noncoding RNAs (lncRNAs), some linked to T2D. Despite their potential impact on β-cell biology and T2D, understanding their roles in human β-cells is limited. This study identifies TUNAR (TCL1 upstream neural differentiation-associated RNA), an islet-enriched lncRNA upregulated in T2D β-cells. TUNAR promotes human β-cell proliferation by delicately modulating the Wnt pathway. Enhanced following Wnt activation, TUNAR reciprocally suppresses the Wnt antagonist DKK3, correlating with its aberrant expression in T2D β-cells.

Mechanistically, TUNAR interacts with the repressive histone modifier EZH2, facilitating EZH2-mediated DKK3 suppression. These findings unveil a cell-specific epigenetic mechanism by an islet-enriched lncRNA, fine-tuning the Wnt pathway and influencing human β-cell proliferation. The discovery of TUNAR's role in regulating β-cell proliferation holds potential implications for innovative diabetes treatments.

The first step in identifying the role of lncRNA in regulating proliferation is to identify differentially expressed genes in the control and patient groups. To demonstrate how Polly can help you enhance your analysis, we performed differential gene expression analysis on datasets treated with dimethyl sulfoxide (DMSO) and 1-Azakenpaullone (1-AKP). The heatmap displays genes with significant differential expression (condition Log FC >= |1| & P-value <= 0.01).

Dataset 4

Single-cell transcriptional profiling of mouse islets following short-term obesogenic dietary intervention

Dataset ID: GSE162512
Year of Publication: 2020
Experiment Type: Single-cell RNA-seq
Total Samples: 7
Organism: Mus musculus
‍Reference Link: Publication

Summary

Obesity is closely associated with adipose tissue inflammation and insulin resistance. Dysglycemia and T2D result when islet β cells fail to maintain appropriate insulin secretion in the face of insulin resistance. To clarify the early transcriptional events leading to β-cell failure in the setting of obesity, the authors fed male C57BL/6J mice an obesogenic, high-fat diet (60% kcal from fat) or a control diet (10% kcal from fat) for one week and islets from these mice (from 4 high fat- and 3 control-fed mice) were subjected to single-cell RNA sequencing analysis. Islet endocrine cell types (α cells, β cells, δ cells, PP cells) and other resident cell types (macrophages, T cells) were annotated by transcript profiles and visualized using Uniform Manifold Approximation and Projection for Dimension Reduction (UMAP) plots.

UMAP analysis revealed distinct cell sub-populations (11 for β cells, 5 for α cells, 3 for δ cells, PP cells, ductal cells, and endothelial cells), emphasizing the heterogeneity of cell populations in the islet. We identified that distinct β cell populations downregulate genes associated with the endoplasmic reticulum stress response and upregulate genes associated with insulin secretion, while others upregulate genes that impair insulin secretion, cellular proliferation, and survival. Moreover, all β cell populations negatively regulate genes associated with immune response activation. This study suggests that an early transcriptional response in islets to an obesogenic diet reflects an attempt by distinct populations of β cells to augment or impair cellular function, possible harbingers of ensuing insulin resistance.

Dataset 5

TREM2 sustains macrophage-hepatocyte metabolic coordination in NAFLD and sepsis

Dataset ID: GSE160016_GPL24676
Year of Publication: 2021
Experiment Type: Bulk RNA-seq
Total Samples: 11
Organism: Homo sapiens
‍Reference Link: Publication

Summary

Sepsis is a leading cause of death in critical illness, and its pathophysiology varies depending on preexisting medical conditions. The authors identified NAFLD as an independent risk factor for sepsis in a large clinical cohort and showed a link between mortality in NAFLD-associated sepsis and hepatic mitochondrial and energetic metabolism dysfunction. Using in vivo and in vitro models of liver lipid overload, the authors discovered a metabolic coordination between hepatocyte mitochondria and liver macrophages expressing triggering receptors expressed on myeloid cells-2 (TREM2).

TREM2-deficient macrophages released exosomes containing a high content of miR-106b-5p, which blocks Mitofusin 2 (Mfn2), impairing hepatocytic mitochondrial structure and energy supply. In a mouse model of NAFLD-associated sepsis, TREM2 deficiency accelerated the initial progression of NAFLD and increased susceptibility to sepsis. Conversely, overexpression of TREM2 in liver macrophages improved hepatic energy supply and sepsis outcome. The authors demonstrated that NAFLD is a risk factor for sepsis, providing a basis for precision treatment, and identified hepatocyte-macrophage metabolic coordination and TREM2 as potential targets for future clinical trials.

Identifying differentially expressed genes in the control and patient groups is the first step in discovering drug targets. To demonstrate how Polly can help you enhance your analysis, we performed differential gene expression analysis on harmonized and normalized NAFLD and control data. The heatmap displays genes with significant differential expression (condition Log FC >= |1| & P-value <= 0.01).

Unraveling the molecular mechanisms is vital for gaining valuable insights into the progression of diseases. Polly's harmonization engine produces high-quality, ML-ready multi-modal datasets tailored to customer needs. It processes raw data consistently, transforms it into a harmonized form with metadata annotation, and performs rigorous quality checks.

Ready to expedite your research journey? Connect with us to explore how Polly can potentially reduce your analysis time by up to 80%, accelerating the drug discovery process.

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