Gaining insight into metabolic diseases from human genetic discoveries

Zebrafish navigating the metabolic maze: insights into human disease - assets, challenges and future implications

Zebrafish (Danio rerio) have become indispensable models for advancing our understanding of multiple metabolic disorders such as obesity, diabetes mellitus, dyslipidemia, and metabolic syndrome. This review provides a comprehensive analysis of zebrafish as a powerful tool for dissecting the genetic and molecular mechanisms of these diseases, focusing on key genes, like pparγ, lepr, ins, and srebp. Zebrafish offer distinct advantages, including genetic tractability, optical transparency in early development, and the conservation of key metabolic pathways with humans. Studies have successfully used zebrafish to uncover conserved metabolic mechanisms, identify novel disease pathways, and facilitate high-throughput screening of potential therapeutic compounds. The review also highlights the novelty of using zebrafish to model multifactorial metabolic disorders, addressing challenges such as interspecies differences in metabolism and the complexity of human metabolic disease etiology. Moving forward, future research will benefit from integrating advanced omics technologies to map disease-specific molecular signatures, applying personalized medicine approaches to optimize treatments, and utilizing computational models to predict therapeutic outcomes. By embracing these innovative strategies, zebrafish research has the potential to revolutionize the diagnosis, treatment, and prevention of metabolic disorders, offering new avenues for translational applications. Continued interdisciplinary collaboration and investment in zebrafish-based studies will be crucial to fully harnessing their potential for advancing therapeutic development.

Variant-to-function approaches for adipose tissue: Insights into cardiometabolic disorders

Genome-wide association studies (GWASs) have identified thousands of genetic loci associated with cardiometabolic disorders. However, the functional interpretation of these loci remains a daunting challenge. This is particularly true for adipose tissue, a critical organ in systemic metabolism and the pathogenesis of various cardiometabolic diseases. We discuss how variant-to-function (V2F) approaches are used to elucidate the mechanisms by which GWAS loci increase the risk of cardiometabolic disorders by directly influencing adipose tissue. We outline GWAS traits most likely to harbor adipose-related variants and summarize tools to pinpoint the putative causal variants, genes, and cell types for the associated loci. We explain how large-scale perturbation experiments, coupled with imaging and multi-omics, can be used to screen variants' effects on cellular phenotypes and how these phenotypes can be tied to physiological mechanisms. Lastly, we discuss the challenges and opportunities that lie ahead for V2F research and propose a roadmap for future studies.

Glutathione-specific gamma-glutamylcyclotransferase 1 (CHAC1) increases kidney disease risk by modulating ferroptosis

Genome-wide association studies (GWASs) have identified more than 1000 loci where genetic variants correlate with kidney function. However, the specific genes, cell types, and mechanisms influenced by these genetic variants remain largely uncharted. Here, we identified glutathione-specific gamma-glutamylcyclotransferase 1 (CHAC1) on chromosome 15 as affected by GWAS variants by analyzing human kidney gene expression and methylation information. Both CHAC1 RNA and protein were expressed in the loop of Henle region in mouse and human kidneys, and CHAC1 expression was higher in patients carrying disease risk variants. Using CRISPR technology, we created mice with a single functional copy of the Chac1 gene (Chac1+/-) that displayed no baseline phenotypic alterations in kidney structure or function. These mice demonstrated resilience to kidney disease in multiple models, including folic acid-induced nephropathy, adenine-induced chronic kidney disease, and uninephrectomy-streptozotocin-induced diabetic nephropathy. We further showed that CHAC1 plays a critical role in degrading the cellular antioxidant glutathione. Tubule cells isolated from Chac1+/- mice showed increased glutathione, decreased lipid peroxidation, improved cell viability, and protection against ferroptosis. Expression of ferroptosis-associated genes was also lower in mice with only one copy of Chac1. Higher CHAC1 protein also correlated with ferroptosis-related protein abundance in kidney biopsies from patients with kidney disease. This study positions CHAC1 as an important mediator of kidney disease that influences glutathione concentrations and ferroptosis, suggesting potential avenues to explore for the treatment of kidney diseases.

The actin and microtubule network regulator WHAMM is identified as a key kidney disease risk gene

Nearly 850 million people suffer from kidney disease worldwide. Genome-wide association studies identify genetic variations at more than 800 loci associated with kidney dysfunction; however, the target genes, cell types, and mechanisms remain poorly understood. Here, we show that nucleotide variants on chromosome 15 are not only associated with kidney dysfunction but also regulate the expression of Wasp homolog associated with actin, membranes, and microtubules (WHAMM). WHAMM expression is higher in mice and patients with chronic and acute kidney disease. Mice with genetic deletion of Whamm appear healthy at baseline but develop less injury following cisplatin, folic acid, and unilateral ureteral obstruction. In vitro cell studies indicate that WHAMM controls cell death by regulating actin-mediated cytochrome c release from mitochondria and the formation of ASC speck. Pharmacological inhibition of actin dynamics mitigates kidney disease in experimental models. In summary, our study identifies a key role of WHAMM in the development of kidney disease.

Metabolic reaction fluxes as amplifiers and buffers of risk alleles for coronary artery disease

Genome-wide association studies have identified thousands of variants associated with disease risk but the mechanism by which such variants contribute to disease remains largely unknown. Indeed, a major challenge is that variants do not act in isolation but rather in the framework of highly complex biological networks, such as the human metabolic network, which can amplify or buffer the effect of specific risk alleles on disease susceptibility. Here we use genetically predicted reaction fluxes to perform a systematic search for metabolic fluxes acting as buffers or amplifiers of coronary artery disease (CAD) risk alleles. Our analysis identifies 30 risk locus-reaction flux pairs with significant interaction on CAD susceptibility involving 18 individual reaction fluxes and 8 independent risk loci. Notably, many of these reactions are linked to processes with putative roles in the disease such as the metabolism of inflammatory mediators. In summary, this work establishes proof of concept that biochemical reaction fluxes can have non-additive effects with risk alleles and provides novel insights into the interplay between metabolism and genetic variation on disease susceptibility.

Evaluation of the role of hepatic Gstm4 in diet-induced obesity and dyslipidemia

Obesity and its related diseases continue to rise worldwide, necessitating further investigation to develop new therapeutic strategies. The dysregulation of redox homeostasis is tightly associated with metabolic diseases. Glutathione, an antioxidant, acts as a cofactor for antioxidant and detoxification enzymes such as glutathione S-transferases (GSTs)-a superfamily including Gstm4. So far, the physiological role of Gstm4 remains largely unknown. Human genetics is a powerful tool to discover novel therapeutic targets for metabolic diseases. The single nucleotide polymorphism rs650985, located within the sixth intron of the human gene Gstm4, was associated with plasma lipids, indicating that targeting Gstm4 might intervene in the progression of dyslipidemia. Furthermore, we found that Gstm4 is highly expressed in the liver and enriched in hepatocytes-the parenchymal cells of the liver. We established the mouse model with the hepatic deletion of Gstm4 and found that this mouse model did not present altered body weight, serum lipid profile, or liver fat content in the context of chow or high-fat high cholesterol diet feeding, indicating that hepatic Gstm4 is dispensable for diet-induced obesity and dyslipidemia. Further analysis revealed that hepatic deletion of Gstm4 upregulates the level of protein but not mRNA of Npc1l1-a critical protein mediating cholesterol uptake, suggesting that there might be a link between Gstm4 and lipid metabolic diseases in certain contexts.

Understanding genetic variants in context

Over the last three decades, human genetics has gone from dissecting high-penetrance Mendelian diseases to discovering the vast and complex genetic etiology of common human diseases. In tackling this complexity, scientists have discovered the importance of numerous genetic processes - most notably functional regulatory elements - in the development and progression of these diseases. Simultaneously, scientists have increasingly used multiplex assays of variant effect to systematically phenotype the cellular consequences of millions of genetic variants. In this article, we argue that the context of genetic variants - at all scales, from other genetic variants and gene regulation to cell biology to organismal environment - are critical components of how we can employ genomics to interpret these variants, and ultimately treat these diseases. We describe approaches to extend existing experimental assays and computational approaches to examine and quantify the importance of this context, including through causal analytic approaches. Having a unified understanding of the molecular, physiological, and environmental processes governing the interpretation of genetic variants is sorely needed for the field, and this perspective argues for feasible approaches by which the combined interpretation of cellular, animal, and epidemiological data can yield that knowledge.

Epigenomic insights into common human disease pathology

The epigenome-the chemical modifications and chromatin-related packaging of the genome-enables the same genetic template to be activated or repressed in different cellular settings. This multi-layered mechanism facilitates cell-type specific function by setting the local sequence and 3D interactive activity level. Gene transcription is further modulated through the interplay with transcription factors and co-regulators. The human body requires this epigenomic apparatus to be precisely installed throughout development and then adequately maintained during the lifespan. The causal role of the epigenome in human pathology, beyond imprinting disorders and specific tumour suppressor genes, was further brought into the spotlight by large-scale sequencing projects identifying that mutations in epigenomic machinery genes could be critical drivers in both cancer and developmental disorders. Abrogation of this cellular mechanism is providing new molecular insights into pathogenesis. However, deciphering the full breadth and implications of these epigenomic changes remains challenging. Knowledge is accruing regarding disease mechanisms and clinical biomarkers, through pathogenically relevant and surrogate tissue analyses, respectively. Advances include consortia generated cell-type specific reference epigenomes, high-throughput DNA methylome association studies, as well as insights into ageing-related diseases from biological 'clocks' constructed by machine learning algorithms. Also, 3rd-generation sequencing is beginning to disentangle the complexity of genetic and DNA modification haplotypes. Cell-free DNA methylation as a cancer biomarker has clear clinical utility and further potential to assess organ damage across many disorders. Finally, molecular understanding of disease aetiology brings with it the opportunity for exact therapeutic alteration of the epigenome through CRISPR-activation or inhibition.

Targeting postsynaptic glutamate receptor scaffolding proteins PSD-95 and PICK1 for obesity treatment

Human genome-wide association studies (GWAS) suggest a functional role for central glutamate receptor signaling and plasticity in body weight regulation. Here, we use UK Biobank GWAS summary statistics of body mass index (BMI) and body fat percentage (BF%) to identify genes encoding proteins known to interact with postsynaptic α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) and N-methyl-d-aspartate (NMDA) receptors. Loci in/near discs large homolog 4 (DLG4) and protein interacting with C kinase 1 (PICK1) reached genome-wide significance (P < 5 × 10-8) for BF% and/or BMI. To further evaluate the functional role of postsynaptic density protein-95 (PSD-95; gene name: DLG4) and PICK1 in energy homeostasis, we used dimeric PSD-95/disc large/ZO-1 (PDZ) domain-targeting peptides of PSD-95 and PICK1 to demonstrate that pharmacological inhibition of PSD-95 and PICK1 induces prolonged weight-lowering effects in obese mice. Collectively, these data demonstrate that the glutamate receptor scaffolding proteins, PICK1 and PSD-95, are genetically linked to obesity and that pharmacological targeting of their PDZ domains represents a promising therapeutic avenue for sustained weight loss.

ACSS2 gene variants determine kidney disease risk by controlling de novo lipogenesis in kidney tubules

Worldwide, over 800 million people are affected by kidney disease, yet its pathogenesis remains elusive, hindering the development of novel therapeutics. In this study, we used kidney-specific expression of quantitative traits and single-nucleus open chromatin analysis to show that genetic variants linked to kidney dysfunction on chromosome 20 target the acyl-CoA synthetase short-chain family 2 (ACSS2). By generating ACSS2-KO mice, we demonstrated their protection from kidney fibrosis in multiple disease models. Our analysis of primary tubular cells revealed that ACSS2 regulated de novo lipogenesis (DNL), causing NADPH depletion and increasing ROS levels, ultimately leading to NLRP3-dependent pyroptosis. Additionally, we discovered that pharmacological inhibition or genetic ablation of fatty acid synthase safeguarded kidney cells against profibrotic gene expression and prevented kidney disease in mice. Lipid accumulation and the expression of genes related to DNL were elevated in the kidneys of patients with fibrosis. Our findings pinpoint ACSS2 as a critical kidney disease gene and reveal the role of DNL in kidney disease.

Negative correlation between acetyl-CoA acyltransferase 2 and cetuximab resistance in colorectal cancer

The emergence of anti-EGFR therapy has revolutionized the treatment of colorectal cancer (CRC). However, not all patients respond consistently well. Therefore, it is imperative to conduct further research to identify the molecular mechanisms underlying the development of cetuximab resistance in CRC. In this study, we find that the expressions of many metabolism-related genes are downregulated in cetuximab-resistant CRC cells compared to their sensitive counterparts. Specifically, acetyl-CoA acyltransferase 2 (ACAA2), a key enzyme in fatty acid metabolism, is downregulated during the development of cetuximab resistance. Silencing of ACAA2 promotes proliferation and increases cetuximab tolerance in CRC cells, while overexpression of ACAA2 exerts the opposite effect. RTK-Kras signaling might contribute to the downregulation of ACAA2 expression in CRC, and ACAA2 predicts CRC prognosis in patients with Kras mutations. Collectively, our data suggest that modulating ACAA2 expression contributes to secondary cetuximab resistance in Kras wild-type CRC patients. ACAA2 expression is related to Kras mutation and demonstrates a prognostic role in CRC patients with Kras mutation. Thus, ACAA2 is a potential target in CRC with Kras mutation.

Genomic discoveries unveil mechanistic insights in diabetes

Two diabetes-related papers are featured in this issue of Cell Genomics. Gardner et al.1 focus on type 2 diabetes through exome sequencing, and Benaglio et al.2 employ a functional genomics approach to advance understanding in type 1 diabetes. In this preview, Jose Florez highlights their contribution toward clinical translation of genomics discoveries.

Genetically personalised organ-specific metabolic models in health and disease

Understanding how genetic variants influence disease risk and complex traits (variant-to-function) is one of the major challenges in human genetics. Here we present a model-driven framework to leverage human genome-scale metabolic networks to define how genetic variants affect biochemical reaction fluxes across major human tissues, including skeletal muscle, adipose, liver, brain and heart. As proof of concept, we build personalised organ-specific metabolic flux models for 524,615 individuals of the INTERVAL and UK Biobank cohorts and perform a fluxome-wide association study (FWAS) to identify 4312 associations between personalised flux values and the concentration of metabolites in blood. Furthermore, we apply FWAS to identify 92 metabolic fluxes associated with the risk of developing coronary artery disease, many of which are linked to processes previously described to play in role in the disease. Our work demonstrates that genetically personalised metabolic models can elucidate the downstream effects of genetic variants on biochemical reactions involved in common human diseases.

Pooled image-base screening of mitochondria with microraft isolation distinguishes pathogenic mitofusin 2 mutations

Most human genetic variation is classified as variants of uncertain significance. While advances in genome editing have allowed innovation in pooled screening platforms, many screens deal with relatively simple readouts (viability, fluorescence) and cannot identify the complex cellular phenotypes that underlie most human diseases. In this paper, we present a generalizable functional genomics platform that combines high-content imaging, machine learning, and microraft isolation in a method termed "Raft-Seq". We highlight the efficacy of our platform by showing its ability to distinguish pathogenic point mutations of the mitochondrial regulator Mitofusin 2, even when the cellular phenotype is subtle. We also show that our platform achieves its efficacy using multiple cellular features, which can be configured on-the-fly. Raft-Seq enables a way to perform pooled screening on sets of mutations in biologically relevant cells, with the ability to physically capture any cell with a perturbed phenotype and expand it clonally, directly from the primary screen.

Kidney omics in hypertension: from statistical associations to biological mechanisms and clinical applications

Hypertension is a major cardiovascular disease risk factor and contributor to premature death globally. Family-based investigations confirmed a significant heritable component of blood pressure (BP), whereas genome-wide association studies revealed >1000 common and rare genetic variants associated with BP and/or hypertension. The kidney is not only an organ of key relevance to BP regulation and the development of hypertension, but it also acts as the tissue mediator of genetic predisposition to hypertension. The identity of kidney genes, pathways, and related mechanisms underlying the genetic associations with BP has started to emerge through integration of genomics with kidney transcriptomics, epigenomics, and other omics as well as through applications of causal inference, such as Mendelian randomization. Single-cell methods further enabled mapping of BP-associated kidney genes to cell types, and in conjunction with other omics, started to illuminate the biological mechanisms underpinning associations of BP-associated genetic variants and kidney genes. Polygenic risk scores derived from genome-wide association studies and refined on kidney omics hold the promise of enhanced diagnostic prediction, whereas kidney omics-informed drug discovery is likely to contribute new therapeutic opportunities for hypertension and hypertension-mediated kidney damage.

Transcriptome-wide association study identifies PSMB9 as a susceptibility gene for coal workers' pneumoconiosis

Coal workers' pneumoconiosis (CWP) is a type of typical occupational lung disease caused by prolonged inhalation of coal mine dust. The individuals' different genetic background may underlie their different susceptibility to develop pneumoconiosis, even under the same exposure level. This study aimed to identify susceptibility genes associated with CWP. Based on our previous genome-wide association study (GWAS, 202 CWP cases vs. 198 controls) and gene expression data obtained by analyzing human lungs and whole blood from the Genotype-Tissue Expression (GTEx) Portal, a transcriptome-wide association study (TWAS) was applied to identify CWP risk-related genes. Luciferase report gene assay, qRT-PCR, Western blot, immunofluorescence assay, and TUNEL assay were conducted to explore the potential role of the candidate gene in CWP. Proteasome 20S subunit beta 9 (PSMB9) was identified as a strong risk-related gene of CWP in both lungs and whole blood (Lungs: P_TWAS  = 4.22 × 10^-4 ; Whole blood: P_TWAS  = 2.11 × 10^-4 ). Single nucleotide polymorphisms (SNPs) rs2071480 and rs1351383, which locate in the promoter region and the first intron of the PSMB9 gene, were in high linkage disequilibrium (LD, r²  = 0.98) with the best GWAS SNP rs4713600 (G>T, OR = 0.55, 95% CI: 0.42-0.74, P = 6.86 × 10^-5 ). Both rs2071480 and rs1351383 significantly enhanced the transcriptional activity of PSMB9. Functional experiments revealed that silica exposure remarkably reduced the PSMB9 expression and caused cell apoptosis, while overexpression of PSMB9 markedly abolished silica-induced cell apoptosis. We here identified PSMB9 as a novel susceptibility gene for CWP and provided important insights into the further exploration of the CWP pathogenesis.