Serine biosynthesis as a novel therapeutic target for dilated cardiomyopathy

SAH is a major metabolic sensor mediating worsening metabolic crosstalk in metabolic syndrome

In this study, we observed worsening metabolic crosstalk in mouse models with concomitant metabolic disorders such as hyperhomocysteinemia (HHcy), hyperlipidemia, and hyperglycemia and in human coronary artery disease by analyzing metabolic profiles. We found that HHcy worsening is most sensitive to other metabolic disorders. To identify metabolic genes and metabolites responsible for the worsening metabolic crosstalk, we examined mRNA levels of 324 metabolic genes in Hcy, glucose-related and lipid metabolic systems. We examined Hcy-metabolites (Hcy, SAH and SAM) by LS-ESI-MS/MS in 6 organs (heart, liver, brain, lung, spleen, and kidney) from C57BL/6J mice. Through linear regression analysis of Hcy-metabolites and metabolic gene mRNA levels, we discovered that SAH-responsive genes were responsible for most metabolic changes and all metabolic crosstalk mediated by Serine, Taurine, and G3P. SAH-responsive genes worsen glucose metabolism and cause upper glycolysis activation and lower glycolysis suppression, indicative of the accumulation of glucose/glycogen and G3P, Serine synthesis inhibition, and ATP depletion. Insufficient Serine due to negative correlation of PHGDH with SAH concentration may inhibit the folate cycle and transsulfurarion pathway and consequential reduced antioxidant power, including glutathione, taurine, NADPH, and NAD+. Additionally, we identified SAH-activated pathological TG loop as the consequence of increased fatty acid (FA) uptake, FA β-oxidation and Ac-CoA production along with lysosomal damage. We concluded that HHcy is most responsive to other metabolic changes in concomitant metabolic disorders and mediates worsening metabolic crosstalk mainly via SAH-responsive genes, that organ-specific Hcy metabolism determines organ-specific worsening metabolic reprogramming, and that SAH, acetyl-CoA, Serine and Taurine are critical metabolites mediating worsening metabolic crosstalk, redox disturbance, hypomethylation and hyperacetylation linking worsening metabolic reprogramming in metabolic syndrome.

Relationship between human serum metabolites and angina pectoris: a Mendelian randomization study

PURPOSE

We aimed to explore the causal relationship between human serum metabolites and angina pectoris.

METHODS

This study used two-sample Mendelian randomization (MR) analysis to assess the association between 486 serum metabolites and angina pectoris. The analytical methods employed to reduce study bias included inverse variance weighted, MR-Egger, and weighted median method. A comprehensive sensitivity analysis was performed using the leave-one-out method, while instrumental variable pleiotropy was tested with MR-Pleiotropy RESidual Sum and Outlier. Metabolic pathways of angina-associated metabolites were analysed on the MetaboAnalyst metabolomics analysis tool platform.

RESULTS

In this study, 42 serum metabolites were found to be strongly associated with angina pectoris. They mainly belonged to seven groups: amino acids, carbohydrates, cofactors and vitamins, lipids, nucleotides, unknown metabolites, and exogenous substances. Pipecolate posed the highest risk for the development of angina pectoris among the 42 serum metabolites. The main metabolic pathways associated with angina pectoris were glycine, serine, threonine metabolism, primary bile acid biosynthesis, and caffeine metabolism.

CONCLUSION

We identified 25 high-risk and 17 protective human serum metabolites associated with angina pectoris. Their associated major metabolic pathways were also determined. The serum metabolite pipecolate was significantly and positively correlated with the risk of angina pectoris. This finding may serve as a valuable reference for testing serum markers associated with angina pectoris.

The Genetic Factors Influencing Cardiomyopathies and Heart Failure across the Allele Frequency Spectrum

Heart failure (HF) remains a major cause of mortality and morbidity worldwide. Understanding the genetic basis of HF allows for the development of disease-modifying therapies, more appropriate risk stratification, and personalised management of patients. The advent of next-generation sequencing has enabled genome-wide association studies; moving beyond rare variants identified in a Mendelian fashion and detecting common DNA variants associated with disease. We summarise the latest GWAS and rare variant data on mixed and refined HF aetiologies, and cardiomyopathies. We describe the recent understanding of the functional impact of titin variants and highlight FHOD3 as a novel cardiomyopathy-associated gene. We describe future directions of research in this field and how genetic data can be leveraged to improve the care of patients with HF.

Integrated metabolomics and network pharmacology study on the mechanism of herbal pair of danggui-kushen for treating ischemia heart disease

DangGui-KuShen (DK) is a well-known classic traditional Chinese medicine recipe that improves blood circulation, eliminates moisture, and detoxifies, and is frequently used in the treatment of cardiovascular problems. Some protective effects of DK on cardiovascular disease have previously been identified, but its precise mechanism remains unknown. The goal of this study is to combine metabolomics and network pharmacology to investigate DK's protective mechanism in Ischemic Heart Disease(IHD) rat models. A combination of metabolomics and network pharmacology based on UPLC-Q-TOF/MS technology was used in this study to verify the effect of DK on IHD through enzyme-linked immunosorbent assay, HE staining, and electrocardiogram, and it was determined that DK improves the synergistic mechanism of IHD. In total, 22 serum differential metabolites and 26 urine differential metabolites were discovered, with the majority of them involved in phenylalanine, tyrosine, and tryptophan biosynthesis, glycine, serine, and threonine metabolism, arginine and proline metabolism, aminoacyl-tRNA biosynthesis, purine metabolism, and other metabolic pathways. Furthermore, using network pharmacology, a composite target pathway network of DangGui and KuShen for treating IHD was created, which is primarily associated to the tumor necrosis factor (TNF) signaling pathway, P53 signaling, and HIF-1 signaling pathways. The combined research indicated that the NF-B signaling pathway and the HIF-1 signaling pathway are critical in DK treatment of IHD. This study clearly confirms and expands on current knowledge of the synergistic effects of DG and KS in IHD.

Personalized transcriptome signatures in a cardiomyopathy stem cell biobank

BACKGROUND

There is growing evidence that pathogenic mutations do not fully explain hypertrophic (HCM) or dilated (DCM) cardiomyopathy phenotypes. We hypothesized that if a patient's genetic background was influencing cardiomyopathy this should be detectable as signatures in gene expression. We built a cardiomyopathy biobank resource for interrogating personalized genotype phenotype relationships in human cell lines.

METHODS

We recruited 308 diseased and control patients for our cardiomyopathy stem cell biobank. We successfully reprogrammed PBMCs (peripheral blood mononuclear cells) into induced pluripotent stem cells (iPSCs) for 300 donors. These iPSCs underwent whole genome sequencing and were differentiated into cardiomyocytes for RNA-seq. In addition to annotating pathogenic variants, mutation burden in a panel of cardiomyopathy genes was assessed for correlation with echocardiogram measurements. Line-specific co-expression networks were inferred to evaluate transcriptomic subtypes. Drug treatment targeted the sarcomere, either by activation with omecamtiv mecarbil or inhibition with mavacamten, to alter contractility.

RESULTS

We generated an iPSC biobank from 300 donors, which included 101 individuals with HCM and 88 with DCM. Whole genome sequencing of 299 iPSC lines identified 78 unique pathogenic or likely pathogenic mutations in the diseased lines. Notably, only DCM lines lacking a known pathogenic or likely pathogenic mutation replicated a finding in the literature for greater nonsynonymous SNV mutation burden in 102 cardiomyopathy genes to correlate with lower left ventricular ejection fraction in DCM. We analyzed RNA-sequencing data from iPSC-derived cardiomyocytes for 102 donors. Inferred personalized co-expression networks revealed two transcriptional subtypes of HCM. The first subtype exhibited concerted activation of the co-expression network, with the degree of activation reflective of the disease severity of the donor. In contrast, the second HCM subtype and the entire DCM cohort exhibited partial activation of the respective disease network, with the strength of specific gene by gene relationships dependent on the iPSC-derived cardiomyocyte line. ADCY5 was the largest hubnode in both the HCM and DCM networks and partially corrected in response to drug treatment.

CONCLUSIONS

We have a established a stem cell biobank for studying cardiomyopathy. Our analysis supports the hypothesis the genetic background influences pathologic gene expression programs and support a role for ADCY5 in cardiomyopathy.

Distinguishing benign and malignant thyroid nodules using plasma trimethylamine N-oxide, carnitine, choline and betaine

PURPOSE

Trimethylamine N-oxide (TMAO), a gut microbiome-derived metabolite, and its precursors (carnitine, choline, betaine) have not been fully examined in relation to thyroid cancer (TC) risk. The aim of this study was to assess the value of TMAO and its precursors in diagnosis of benign and malignant thyroid nodules.

METHODS

In this study, high-performance liquid chromatography-tandem mass spectrometry was utilized to measure the levels of plasma TMAO and its precursors (choline, carnitine, and betaine) in 215 TC patients, 63 benign thyroid nodules (BTN) patients and 148 healthy controls (HC). The distribution of levels of TMAO and its precursors among the three groups were compared by the Kruskal-Wallis test. Receiver operating characteristic curve (ROC) analysis was performed to evaluate the sensitivity, specificity, and the predictive accuracy of single and combined biomarkers.

RESULTS

In comparison to HC, TC showed higher levels of TMAO and lower levels of its precursors (carnitine, choline, and betaine) (all P < 0.001). Plasma choline (P < 0.01) and betaine (P < 0.05) were declined in BTN than HC. The levels of carnitine (P < 0.001) and choline (P < 0.05) were significantly higher in BTN than that in TC group. Plasma TMAO showed lower levels in TC with lymph node metastasis (101.5 (73.1-144.5) ng/ml) than those without lymph node metastasis (131 (84.8-201) ng/ml, P < 0.05). Combinations of these four metabolites achieved good performance in the differential diagnosis, with the area under the ROC curve of 0.703, 0.741, 0.793 when discriminating between TC and BTN, BTN and HC, TC and HC, respectively.

CONCLUSION

Plasma TMAO, along with its precursors could serve as new biomarkers for the diagnosis of benign and malignant thyroid nodules.

Mendelian Randomization Study With Clinical Follow-Up Links Metabolites to Risk and Severity of Pulmonary Arterial Hypertension

BACKGROUND

Pulmonary arterial hypertension (PAH) exhibits phenotypic heterogeneity and variable response to therapy. The metabolome has been implicated in the pathogenesis of PAH, but previous works have lacked power to implicate specific metabolites. Mendelian randomization (MR) is a method for causal inference between exposures and outcomes.

METHODS AND RESULTS

Using genome-wide association study summary statistics, we implemented MR analysis to test for potential causal relationships between serum concentration of 575 metabolites and PAH. Five metabolites were causally associated with the risk of PAH after multiple testing correction. Next, we measured serum concentration of candidate metabolites in an independent clinical cohort of 449 patients with PAH to check whether metabolite concentrations are correlated with markers of disease severity. Of the 5 candidates nominated by our MR work, serine was negatively associated and homostachydrine was positively associated with clinical severity of PAH via direct measurement in this independent clinical cohort. Finally we used conditional and orthogonal approaches to explore the biology underlying our lead metabolites. Rare variant burden testing was carried out using whole exome sequencing data from 578 PAH cases and 361 675 controls. Multivariable MR is an extension of MR that uses a single set of instrumental single-nucleotide polymorphisms to measure multiple exposures; multivariable MR is used to determine interdependence between the effects of different exposures on a single outcome. Rare variant analysis demonstrated that loss-of-function mutations within activating transcription factor 4, a transcription factor responsible for upregulation of serine synthesis under conditions of serine starvation, are associated with higher risk for PAH. Homostachydrine is a xenobiotic metabolite that is structurally related to l-proline betaine, which has previously been linked to modulation of inflammation and tissue remodeling in PAH. Our multivariable MR analysis suggests that the effect of l-proline betaine is actually mediated indirectly via homostachydrine.

CONCLUSIONS

Our data present a method for study of the metabolome in the context of PAH, and suggests several candidates for further evaluation and translational research.

Harnessing human genetics and stem cells for precision cardiovascular medicine

Human induced pluripotent stem cell (iPSC) platforms are valuable for biomedical and pharmaceutical research by providing tissue-specific human cells that retain patients' genetic integrity and display disease phenotypes in a dish. Looking forward, combining iPSC phenotyping platforms with genomic and screening technologies will continue to pave new directions for precision medicine, including genetic prediction, visualization, and treatment of heart disease. This review summarizes the recent use of iPSC technology to unpack the influence of genetic variants in cardiovascular pathology. We focus on various state-of-the-art genomic tools for cardiovascular therapies-including the expansion of genetic toolkits for molecular interrogation, in vitro population studies, and function-based drug screening-and their current applications in patient- and genome-edited iPSC platforms that are heralding new avenues for cardiovascular research.

The role of glycolytic metabolic pathways in cardiovascular disease and potential therapeutic approaches

Cardiovascular disease (CVD) is a major threat to human health, accounting for 46% of non-communicable disease deaths. Glycolysis is a conserved and rigorous biological process that breaks down glucose into pyruvate, and its primary function is to provide the body with the energy and intermediate products needed for life activities. The non-glycolytic actions of enzymes associated with the glycolytic pathway have long been found to be associated with the development of CVD, typically exemplified by metabolic remodeling in heart failure, which is a condition in which the heart exhibits a rapid adaptive response to hypoxic and hypoxic conditions, occurring early in the course of heart failure. It is mainly characterized by a decrease in oxidative phosphorylation and a rise in the glycolytic pathway, and the rise in glycolysis is considered a hallmark of metabolic remodeling. In addition to this, the glycolytic metabolic pathway is the main source of energy for cardiomyocytes during ischemia-reperfusion. Not only that, the auxiliary pathways of glycolysis, such as the polyol pathway, hexosamine pathway, and pentose phosphate pathway, are also closely related to CVD. Therefore, targeting glycolysis is very attractive for therapeutic intervention in CVD. However, the relationship between glycolytic pathway and CVD is very complex, and some preclinical studies have confirmed that targeting glycolysis does have a certain degree of efficacy, but its specific role in the development of CVD has yet to be explored. This article aims to summarize the current knowledge regarding the glycolytic pathway and its key enzymes (including hexokinase (HK), phosphoglucose isomerase (PGI), phosphofructokinase-1 (PFK1), aldolase (Aldolase), phosphoglycerate metatase (PGAM), enolase (ENO) pyruvate kinase (PKM) lactate dehydrogenase (LDH)) for their role in cardiovascular diseases (e.g., heart failure, myocardial infarction, atherosclerosis) and possible emerging therapeutic targets.

Emerging Targeted Therapies for Inherited Cardiomyopathies and Arrhythmias

Inherited cardiomyopathy and arrhythmia syndromes are associated with significant morbidity and mortality, particularly in young people. Medical management of these conditions has primarily been limited to agents previously developed for more common forms of heart disease and not tailored to their distinct pathophysiology. As our understanding of their underlying genetics and disease mechanisms has improved, an era of targeted therapies for these rare conditions has begun to emerge. In recent years, several novel agents have been developed and tested in preclinical models and, in some cases, have advanced to both the clinical trial and clinical approval stages with exciting results. These new treatments are derived from multiple classes of therapeutics, including small molecules, antisense oligonucleotides, small interfering RNAs, adeno-associated virus-mediated gene therapies, and in vivo gene editing. Collectively, they carry the promise of revolutionizing management of affected patients and their families.

Proteomic and phosphoproteomic analyses of myectomy tissue reveals difference between sarcomeric and genotype-negative hypertrophic cardiomyopathy

Hypertrophic cardiomyopathy (HCM) is a genetically heterogenous condition with about half of cases remaining genetically elusive or non-genetic in origin. HCM patients with a positive genetic test (HCMSarc) present earlier and with more severe disease than those with a negative genetic test (HCMNeg). We hypothesized these differences may be due to and/or reflect proteomic and phosphoproteomic differences between the two groups. TMT-labeled mass spectrometry was performed on 15 HCMSarc, 8 HCMNeg, and 7 control samples. There were 243 proteins differentially expressed and 257 proteins differentially phosphorylated between HCMSarc and HCMNeg. About 90% of pathways altered between genotypes were in disease-related pathways and HCMSarc showed enhanced proteomic and phosphoproteomic alterations in these pathways. Thus, we show HCMSarc has enhanced proteomic and phosphoproteomic dysregulation observed which may contribute to the more severe disease phenotype.

Sources and Sinks of Serine in Nutrition, Health, and Disease

Amino acid dysregulation has emerged as an important driver of disease progression in various contexts. l-Serine lies at a central node of metabolism, linking carbohydrate metabolism, transamination, glycine, and folate-mediated one-carbon metabolism to protein synthesis and various downstream bioenergetic and biosynthetic pathways. l-Serine is produced locally in the brain but is sourced predominantly from glycine and one-carbon metabolism in peripheral tissues via liver and kidney metabolism. Compromised regulation or activity of l-serine synthesis and disposal occurs in the context of genetic diseases as well as chronic disease states, leading to low circulating l-serine levels and pathogenesis in the nervous system, retina, heart, and aging muscle. Dietary interventions in preclinical models modulate sensory neuropathy, retinopathy, tumor growth, and muscle regeneration. A serine tolerance test may provide a quantitative readout of l-serine homeostasis that identifies patients who may be susceptible to neuropathy or responsive to therapy.

Nuclear damage in LMNA mutant iPSC-derived cardiomyocytes is associated with impaired lamin localization to the nuclear envelope

The LMNA gene encodes the nuclear envelope proteins Lamins A and C, which comprise a major part of the nuclear lamina, provide mechanical support to the nucleus, and participate in diverse intracellular signaling. LMNA mutations give rise to a collection of diseases called laminopathies, including dilated cardiomyopathy (LMNA-DCM) and muscular dystrophies. Although nuclear deformities are a hallmark of LMNA-DCM, the role of nuclear abnormalities in the pathogenesis of LMNA-DCM remains incompletely understood. Using induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) from LMNA mutant patients and healthy controls, we show that LMNA mutant iPSC-CM nuclei have altered shape or increased size compared to healthy control iPSC-CM nuclei. The LMNA mutation exhibiting the most severe nuclear deformities, R249Q, additionally caused reduced nuclear stiffness and increased nuclear fragility. Importantly, for all cell lines, the degree of nuclear abnormalities corresponded to the degree of Lamin A/C and Lamin B1 mislocalization from the nuclear envelope. The mislocalization was likely due to altered assembly of Lamin A/C. Collectively, these results point to the importance of correct lamin assembly at the nuclear envelope in providing mechanical stability to the nucleus and suggest that defects in nuclear lamina organization may contribute to the nuclear and cellular dysfunction in LMNA-DCM.

Serine signaling governs metabolic homeostasis and health

Serine has functions that are involved in metabolic homeostasis and health in pathological or stressful situations. Notably, the de novo serine synthesis pathway (SSP) plays a vital role in targeted regulation of immune responses, cell proliferation, and lipid/protein metabolism. The presentation of serine residues derived from SSP may be a signal of stress and provide novel insights into the relationship between metabolic homeostasis and diseases. Here, we summarize the current trends in understanding the regulatory mechanisms of serine metabolism, discuss how serine signaling governs metabolic and antistress processes, including oxidative stress, immunity, energy and lipid metabolism, intestinal microbiota, and the neurological system. We present a possible framework by which serine metabolism maintains metabolic homeostasis and treats human diseases.

Small molecule metabolites: discovery of biomarkers and therapeutic targets

Metabolic abnormalities lead to the dysfunction of metabolic pathways and metabolite accumulation or deficiency which is well-recognized hallmarks of diseases. Metabolite signatures that have close proximity to subject's phenotypic informative dimension, are useful for predicting diagnosis and prognosis of diseases as well as monitoring treatments. The lack of early biomarkers could lead to poor diagnosis and serious outcomes. Therefore, noninvasive diagnosis and monitoring methods with high specificity and selectivity are desperately needed. Small molecule metabolites-based metabolomics has become a specialized tool for metabolic biomarker and pathway analysis, for revealing possible mechanisms of human various diseases and deciphering therapeutic potentials. It could help identify functional biomarkers related to phenotypic variation and delineate biochemical pathways changes as early indicators of pathological dysfunction and damage prior to disease development. Recently, scientists have established a large number of metabolic profiles to reveal the underlying mechanisms and metabolic networks for therapeutic target exploration in biomedicine. This review summarized the metabolic analysis on the potential value of small-molecule candidate metabolites as biomarkers with clinical events, which may lead to better diagnosis, prognosis, drug screening and treatment. We also discuss challenges that need to be addressed to fuel the next wave of breakthroughs.

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) in Cardiovascular Disease: A Comprehensive Clinical Review on Dilated Cardiomyopathy

Dilated cardiomyopathy (DCM) is one of the most important causes of heart failure in developed and developing countries. Currently, most medical interventions in the treatment of DCM are mainly focused on mitigating the progression of the disease and controlling the symptoms. The vast majority of patients who survive till the late stages of the disease require cardiac transplantation; this is exactly why we need novel therapeutic interventions and hopefully treatments that can reverse the clinical cardiac deterioration in patients with DCM. Clustered regularly interspaced short palindromic repeats (CRISPR) technology is a novel therapeutic intervention with such capacity; it can help us edit the genome of patients with genetic etiology for DCM and potentially cure them permanently. This review provides an overview of studies investigating CRISPR-based gene editing in DCM, including the use of CRISPR in DCM disease models, phenotypic screening, and genotype-specific precision therapies. The review discusses the outcomes of these studies and highlights the potential benefits of CRISPR in developing novel genotype-agnostic therapeutic strategies for the genetic causes of DCM. The databases we used to extract relevant literature include PubMed, Google Scholar, and Cochrane Central. We used the Medical Subject Heading (MeSH) strategy for our literature search in PubMed and relevant search keywords for other databases. We screened all the relevant articles from inception till February 22, 2023. We retained 74 research articles after carefully reviewing each of them. We concluded that CRISPR gene editing has shown promise in developing precise and genotype-specific therapeutic strategies for DCM, but there are challenges and limitations, such as delivering CRISPR-Cas9 to human cardiomyocytes and the potential for unintended gene targeting. This study represents a turning point in our understanding of the mechanisms underlying DCM and paves the way for further investigation into the application of genomic editing for identifying novel therapeutic targets. This study can also act as a potential framework for novel therapeutic interventions in other genetic cardiovascular diseases.

Targeting lipid metabolism as a new therapeutic strategy for inherited cardiomyopathies

Inherited cardiomyopathies caused by pathological genetic variants include multiple subtypes of heart disease. Advances in next-generation sequencing (NGS) techniques have allowed for the identification of numerous genetic variants as pathological variants. However, the disease penetrance varies among mutated genes. Some can be associated with more than one disease subtype, leading to a complex genotype-phenotype relationship in inherited cardiomyopathies. Previous studies have demonstrated disrupted metabolism in inherited cardiomyopathies and the importance of metabolic adaptations in disease onset and progression. In addition, genotype- and phenotype-specific metabolic alterations, especially in lipid metabolism, have been revealed. In this mini-review, we describe the metabolic changes that are associated with dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM), which account for the largest proportion of inherited cardiomyopathies. We also summarize the affected expression of genes involved in fatty acid oxidation (FAO) in DCM and HCM, highlighting the potential of PPARA-targeting drugs as FAO modulators in treating patients with inherited cardiomyopathies.

A deep learning platform to assess drug proarrhythmia risk

Drug safety initiatives have endorsed human iPSC-derived cardiomyocytes (hiPSC-CMs) as an in vitro model for predicting drug-induced cardiac arrhythmia. However, the extent to which human-defined features of in vitro arrhythmia predict actual clinical risk has been much debated. Here, we trained a convolutional neural network classifier (CNN) to learn features of in vitro action potential recordings of hiPSC-CMs that are associated with lethal Torsade de Pointes arrhythmia. The CNN classifier accurately predicted the risk of drug-induced arrhythmia in people. The risk profile of the test drugs was similar across hiPSC-CMs derived from different healthy donors. In contrast, pathogenic mutations that cause arrhythmogenic cardiomyopathies in patients significantly increased the proarrhythmic propensity to certain intermediate and high-risk drugs in the hiPSC-CMs. Thus, deep learning can identify in vitro arrhythmic features that correlate with clinical arrhythmia and discern the influence of patient genetics on the risk of drug-induced arrhythmia.

Phenotypic screening models for rapid diagnosis of genetic variants and discovery of personalized therapeutics

Precision medicine strives for highly individualized treatments for disease under the notion that each individual's unique genetic makeup and environmental exposures imprints upon them not only a disposition to illness, but also an optimal therapeutic approach. In the realm of rare disorders, genetic predisposition is often the predominant mechanism driving disease presentation. For such, mostly, monogenic disorders, a causal gene to phenotype association is likely. As a result, it becomes important to query the patient's genome for the presence of pathogenic variations that are likely to cause the disease. Determining whether a variant is pathogenic or not is critical to these analyses and can be challenging, as many disease-causing variants are novel and, ergo, have no available functional data to help categorize them. This problem is exacerbated by the need for rapid evaluation of pathogenicity, since many genetic diseases present in young children who will experience increased morbidity and mortality without rapid diagnosis and therapeutics. Here, we discuss the utility of animal models, with a focus mainly on C. elegans, as a contrast to tissue culture and in silico approaches, with emphasis on how these systems are used in determining pathogenicity of variants with uncertain significance and then used to screen for novel therapeutics.