Disease-causing Genes Research Articles

Advances in CRISPR-Cas systems for blood cancer.

CRISPR-Cas systems have revolutionised precision medicine by enabling personalised treatments tailored to an individual's genetic profile. Various CRISPR technologies have been developed to target specific disease-causing genes in blood cancers, and some have advanced to clinical trials. Although some studies have explored the in vivo applications of CRISPR-Cas systems, several challenges continue to impede their widespread use. Furthermore, CRISPR-Cas technology has shown promise in improving the response of immunotherapies to blood cancers. The emergence of CAR-T cell therapy has shown considerable success in the targeting and correcting of disease-causing genes in blood cancers. Despite the promising potential of CRISPR-Cas in the treatment of blood cancers, issues related to safety, ethics, and regulatory approval remain significant hurdles. This comprehensive review highlights the transformative potential of CRISPR-Cas technology to revolutionise blood cancer therapy.

Nucleic acid degradation as barrier to gene delivery: a guide to understand and overcome nuclease activity.

Gene therapy is on its way to revolutionize the treatment of both inherited and acquired diseases, by transferring nucleic acids to correct a disease-causing gene in the target cells of patients. In the fight against infectious diseases, mRNA-based therapeutics have proven to be a viable strategy in the recent Covid-19 pandemic. Although a growing number of gene therapies have been approved, the success rate is limited when compared to the large number of preclinical and clinical trials that have been/are being performed. In this review, we highlight some of the hurdles which gene therapies encounter after administration into the human body, with a focus on nucleic acid degradation by nucleases that are extremely abundant in mammalian organs, biological fluids as well as in subcellular compartments. We overview the available strategies to reduce the biodegradation of gene therapeutics after administration, including chemical modifications of the nucleic acids, encapsulation into vectors and co-administration with nuclease inhibitors and discuss which strategies are applied for clinically approved nucleic acid therapeutics. In the final part, we discuss the currently available methods and techniques to qualify and quantify the integrity of nucleic acids, with their own strengths and limitations.

CRISPR-Cas13: Pioneering RNA Editing for Nucleic Acid Therapeutics.

The CRISPR-Cas13 system has emerged as a revolutionary tool for RNA editing, offering new opportunities for the development of nucleic acid therapeutics. Unlike DNA-targeting CRISPR-Cas9, Cas13 targets and cleaves RNA, enabling gene silencing and preventing genomic instability. Its applications include suppressing disease-causing genes, correcting splicing errors, and modulating immune responses. Despite these advances, challenges persist, such as the need to refine specificity, mitigate off-target impacts, and ensure effective delivery. This review provides an overview of the CRISPR-Cas13 mechanism, elucidating its role in RNA-targeted therapies and its transformative potential for disease treatment. Furthermore, it addresses the ongoing challenges that the scientific community is striving to overcome.

From genome to clinic: The power of translational bioinformatics in improving human health.

Translational bioinformatics (TBI) has transformed healthcare by providing personalized medicine and tailored treatment options by integrating genomic data and clinical information. In recent years, TBI has bridged the gap between genome and clinical data because of significant advances in informatics like quantum computing and utilizing state-of-the-art technologies. This chapter discusses the power of translational bioinformatics in improving human health, from uncovering disease-causing genes and variations to establishing new therapeutic techniques. We discuss key application areas of bioinformatics in clinical genomics, such as data sources and methods used in translational bioinformatics, the impact of translational bioinformatics on human health, and how machine learning and artificial intelligence are being used to mine vast amounts of data for drug development and precision medicine. We also look at the problems, constraints, and ethical concerns connected with exploiting genomic data and the future of translational bioinformatics and its potential impact on medicine and human health. Ultimately, this chapter emphasizes the great potential of translational bioinformatics to alter healthcare and enhance patient outcomes.

In-depth analysis of OTC A208T case induced by OTC gene mutation and research on the prediction and simulation of the impact on protein function.

Ornithine transcarbamylase deficiency (OTCD), a rare hereditary disease caused by gene mutation of ornithine transcarbamylase (OTC), is the most prevalent type among urea cycle disorders. OTCD typically leads to mitochondrial enzyme dysfunction, preventing the synthesis of citrulline from carbamoyl phosphate and ornithine, and is characterized by a remarkable increase in blood ammonia. Specific symptoms may include neurological abnormalities, growth retardation, and other manifestations. We presented a case of a child diagnosed with OTCD (OMIM: 311250). By using whole-genome sequencing (WGS) for the pedigree and in-depth whole-exome sequencing (WES), we aimed to identify the disease-causing genes. Gene mutation prediction tools were employed to verify the pathogenicity, and the molecular dynamics simulation method was utilized to assess the impact of this mutation on the activity and structural stability of the OTC protein. Whole-exome sequencing detected an OTC variant [NM_000531: c.622 (exon6) G > A, p.A208T]. Through comprehensive analysis with various gene mutation prediction tools and in line with the ACMG guidelines, this mutation site was firmly established as a pathogenic site. Moreover, the molecular dynamics simulation results clearly demonstrated that this mutation would significantly compromise the stability of the OTC protein structure. This study deepens our understanding of the clinical manifestations and characteristics of OTCD, especially the OTC A208T gene mutation site. Given the lack of specific clinical manifestations in OTCD patients, early and accurate diagnosis is crucial for effective treatment and prognosis improvement. To our knowledge, this is the first case of this mutation site reported in China.

In vivo base editing rescues primary hyperoxaluria type 1 in rats

Primary hyperoxaluria type 1 (PH1) is a childhood-onset autosomal recessive disease, characterized by nephrocalcinosis, multiple recurrent urinary calcium oxalate stones, and a high risk of progressive kidney damage. PH1 is caused by inherent genetic defects of the alanine glyoxylate aminotransferase (AGXT) gene. The invivo repair of disease-causing genes was exceedingly inefficient before the invention of base editors which can efficiently introduce precisely targeted base alterations without double-strand DNA breaks. Adenine base editor (ABE) can precisely convert A·T to G·C with the assistance of specific guide RNA. Here, we demonstrated that systemic delivery of dual adeno-associated virus encoding a split-ABE8e could artificially repair 13% of the pathogenic allele in AgxtQ84X rats, a model of PH1, alleviating the disease phenotype. Specifically, ABE treatment partially restored the expression of alanine-glyoxylate-aminotransferase (AGT), reduced endogenous oxalate synthesis and alleviated calcium oxalate crystal deposition. Western blot and immunohistochemistry confirmed that ABE8e treatment restored AGT protein expression in hepatocytes. Moreover, the precise editing efficiency in the liver remained stable six months after treatment. Thus, our findings provided a prospect of invivo base editing as a personalized and precise medicine for PH1 by directly correcting the mutant Agxt gene.

Applications of some advanced sequencing, analytical, and computational approaches in medicinal plant research: a review.

The potential active chemicals found in medicinal plants, which have long been employed as natural medicines, are abundant. Exploring the genes responsible for producing these compounds has given new insights into medicinal plant research. Previously, the authentication of medicinal plants was done via DNA marker sequencing. With the advancement of sequencing technology, several new techniques like next-generation sequencing, single molecule sequencing, and fourth-generation sequencing have emerged. These techniques enshrined the role of molecular approaches for medicinal plants because all the genes involved in the biosynthesis of medicinal compound(s) could be identified through RNA-seq analysis. In several research insights, transcriptome data have also been used for the identification of biosynthesis pathways. miRNAs in several medicinal plants and their role in the biosynthesis pathway as well as regulation of the disease-causing genes were also identified. In several research articles, an in silico study was also found to be effective in identifying the inhibitory effect of medicinal plant-based compounds against virus' gene(s). The use of advanced analytical methods like spectroscopy and chromatography in metabolite proofing of secondary metabolites has also been reported in several recent research findings. Furthermore, advancement in molecular and analytic methods will give new insight into studying the traditionally important medicinal plants that are still unexplored.

10205-TB-8 ABSENCE OF RNF213 IN MEDULLOBLASTOMA INDUCES STARVATION RESISTANCE VIA GAS6 AND RESULTS IN TUMOR PROGRESSION

Abstract RNF213 gene, initially identified as a disease-causing gene for moyamoya disease, has recently been recognized as a tumor regulator. We investigated the functions of RNF213 in tumorigenicity of medulloblastoma. Knockout of Rnf213 in Ptch1+/- spontaneous medulloblastoma mouse model increased the incidence of SHH type medulloblastoma from 19.8% to 76.5% (p<0.001) at 9 months. Subcutaneous implantation of the tumors showed that depletion of Rnf213 increased tumor formation frequency and tumor size. Unexpectedly, knockout of RNF213 in human Daoy cells decreased tumor growth and invasion in vitro. However, they were resistant to serum starvation and showed higher growth rate when implanted subcutaneously in nude mice. Transcriptome analysis of mouseRnf213-/- cells indicated that downregulation of Igf2 decreased tumor growth and upregulation of Gas6 increased resistance to starvation. In fact, GAS6 was upregulated in serum-free conditions and further upregulated in RNF213-/- cells. Survival advantage in serum starved conditions was lost by GAS6 knock-down in RNF213-/- Daoy cells. In conclusion, the effect of RNF213 depletion was context dependent. Resistance to starvation seems to outweigh growth retardation in normal conditions and is important for tumorigenicity and aggressiveness in vivo.

Development of a Polymeric Pharmacological Nanocarrier System as a Potential Therapy for Spinocerebellar Ataxia Type 7.

Spinocerebellar ataxia type 7 (SCA7) is an autosomal-dominant inherited disease characterized by progressive ataxia and retinal degeneration. SCA7 belongs to a group of neurodegenerative diseases caused by an expanded CAG repeat in the disease-causing gene, resulting in aberrant polyglutamine (polyQ) protein synthesis. PolyQ ataxin-7 is prone to aggregate in intracellular inclusions, perturbing cellular processes leading to neuronal death in specific regions of the central nervous system (CNS). Currently, there is no treatment for SCA7; however, a promising approach successfully applied to other polyQ diseases involves the clearance of polyQ protein aggregates through pharmacological activation of autophagy. Nonetheless, the blood-brain barrier (BBB) poses a challenge for delivering drugs to the CNS, limiting treatment effectiveness. This study aimed to develop a polymeric nanocarrier system to deliver therapeutic agents across the BBB into the CNS. We prepared poly(lactic-co-glycolic acid) nanoparticles (NPs) modified with Poloxamer188 and loaded with rapamycin to enable NPs to activate autophagy. We demonstrated that these rapamycin-loaded NPs were successfully taken up by neuronal and glial cells, demonstrating high biocompatibility without adverse effects. Remarkably, rapamycin-loaded NPs effectively cleared mutant ataxin-7 aggregates in a SCA7 glial cell model, highlighting their potential as a therapeutic approach to fight SCA7 and other polyQ diseases.

Antisense oligonucleotides: a novel Frontier in pharmacological strategy.

Antisense oligonucleotides (ASOs) are short single stranded synthetic RNA or DNA molecules, whereas double-stranded RNA nucleotide sequences are called small interfering RNA (siRNA). ASOs bind to complementary nucleic acid sequences impacting the associated functions of the targeted nucleic acids. They represent an emerging class of drugs that, through a revolutionary mechanism of action, aim to directly regulate disease-causing genes and their variants, providing an alternative tool to traditional "protein-specific" therapies. The majority of the ASOs are designed to treat orphan genetic disorders that in most of the cases are seriously disabling and still lacking an adequate therapy. In order to translate ASOs into clinical success, constant technological advances have been instrumental in overcoming several pharmacological, toxicological and formulation limitations. Accordingly, chemical structures have been recently implemented and new bio-conjugation and nanocarriers formulation strategies explored. The aim of this work is to offer an overview of the antisense technology with a comparative analysis of the oligonucleotides approved by the Food and Drug Administration (FDA) and the European Medicines Agency (EMA).

GeneCompete: an integrative tool of a novel union algorithm with various ranking techniques for multiple gene expression data

Background Identifying the genes responsible for diseases requires precise prioritization of significant genes. Gene expression analysis enables differentiation between gene expressions in disease and normal samples. Increasing the number of high-quality samples enhances the strength of evidence regarding gene involvement in diseases. This process has led to the discovery of disease biomarkers through the collection of diverse gene expression data. Methods This study presents GeneCompete, a web-based tool that integrates gene expression data from multiple platforms and experiments to identify the most promising biomarkers. GeneCompete incorporates a novel union strategy and eight well-established ranking methods, including Win-Loss, Massey, Colley, Keener, Elo, Markov, PageRank, and Bi-directional PageRank algorithms, to prioritize genes across multiple gene expression datasets. Each gene in the competition is assigned a score based on log-fold change values, and significant genes are determined as winners. Results We tested the tool on the expression datasets of Hypertrophic cardiomyopathy (HCM) and the datasets from Microarray Quality Control (MAQC) project, which include both microarray and RNA-Sequencing techniques. The results demonstrate that all ranking scores have more power to predict new occurrence datasets than the classical method. Moreover, the PageRank method with a union strategy delivers the best performance for both up-regulated and down-regulated genes. Furthermore, the top-ranking genes exhibit a strong association with the disease. For MAQC, the two-sides ranking score shows a high relationship with TaqMan validation set in all log-fold change thresholds. Conclusion GeneCompete is a powerful web-based tool that revolutionizes the identification of disease-causing genes through the integration of gene expression data from multiple platforms and experiments.

Plain language summary of a study looking at whether genetic testing can help doctors diagnose the severity of mucopolysaccharidosis type I (MPS I)

What is MPS I & what is this study about? Mucopolysaccharidosis type I (MPS I) is a rare genetic condition, resulting from disease-causing changes in the IDUA gene called pathogenic variants. There are two different types of variants: Null variants – cells cannot make the alpha-L-iduronidase enzyme Missense variants – cells make a partly functional or severely reduced amount of the fully functional enzyme The alpha-L-iduronidase enzyme breaks down large sugar molecules called glycosaminoglycans (GAGs). In people with MPS I, the enzyme is unable to break down GAGs and they build up in cells. Based on the severity of the condition, doctors categorise MPS I into two types, called phenotypes: Attenuated MPS I Severe MPS I Treatment options differ depending on MPS I phenotype. There are currently no tests that accurately determine MPS I phenotype. Using information from the MPS I Registry, researchers wanted to find out whether knowing the specific combination of the 2 disease-causing gene variants (genotype) can help predict whether a person has an attenuated or severe phenotype. What were the results? In people with attenuated MPS I: 19 in 20 had genotypes where at least one of the gene copies was a missense variant. The cell makes a partly functional or a severely reduced amount of the fully functional enzyme, and is unable to completely break down GAG No-one had 2 null variants 2 in 5 had unique genotypes (their genotype was only seen in one person) In people with severe MPS I: 2 in 3 had genotypes where both copies of the gene contained null variants. The cell is not able to make any enzyme 1 in 5 had unique genotypes What do the results mean? This study showed that genotype can predict phenotype in some people with MPS I. For example, if a person has inherited two copies of the genes containing null variants, they will have severe MPS I. However, due to the large number of unique gene variants found in this study, doctors cannot predict the severity of MPS I from just the genotype for some people.

Expanded phenotypic spectrum of FOXL2 Variant c.672_701dup revealed by whole-exome sequencing in a rare blepharophimosis, ptosis, and epicanthus inversus syndrome family

IntroductionBlepharophimosis, ptosis, and epicanthus inversus syndrome (BPES) is a rare genetic disease with diverse ocular malformations. This study aimed to investigate the disease-causing gene in members of a BPES pedigree presenting with the rare features of anisometropia, unilateral pathologic myopia (PM), and congenital cataracts.MethodsThe related BPES patients underwent a comprehensive ocular examination. Next, whole-exome sequencing (WES) was performed to screen for the disease-causing genetic variants. A step-wise variant filtering was performed to select candidate variants combined with the annotation of the variant's pathogenicity, which was assessed using several bioinformatic approaches. Co-segregation analysis and Sanger sequencing were then conducted to validate the candidate variant.ResultsThe variant c.672_701dup in FOXL2 was identified to be the disease-causing variant in this rare BPES family. Combined with clinical manifestations, the two affected individuals were diagnosed with type II BPES.ConclusionThis study uncovered the variant c.672_701dup in FOXL2 as a disease causal variant in a rare-presenting BPES family with anisometropia, unilateral pathogenic myopia, and/or congenital cataracts, thus expanding the phenotypic spectrum of FOXL2.

Bioresponsive Chimaeric Polymersomes Mediate Sustained and Liver-Specific siRNA Transfection In Vivo.

The silencing of disease-causing genes with small interfering RNA (siRNA) offers a particularly effective therapeutic strategy for different disorders; however, its clinical efficacy relies on the development of nontoxic and tissue-specific delivery vehicles. Herein, we report that bioresponsive chimaeric polymersomes (BCP) with short poly(ethylenimine) as inner shell mediate highly efficacious, sustained, and liver-specific siRNA transfection in vivo. BCP exhibited remarkable encapsulation efficiencies of siRNA (95-100%) at siRNA-feeding contents of 15-25 wt %, to afford stable, small-sized (55-64 nm), and neutral-charged BCP-siRNA. siApoB-Loaded BCP (BCP-siApoB) outperformed lipofectamine counterparts and silenced 93% of ApoB mRNA in HepG2 cells at 50 nM siApoB without inducing cytotoxicity. Intriguingly, the in vivo studies using wild-type C57BL/6 mice revealed that BCP-siApoB preferentially accumulated in the liver, and a single dose of 4.5 mg/kg achieved over 90% downregulation of ApoB mRNA for at least 10 days. The systemic administration of BCP-siApoB at 4.5 mg/kg every 2 weeks or 1.5 mg/kg weekly in diet-induced obese mice could also achieve up to 80% silencing of ApoB mRNA. The liver specificity and silencing efficacy of BCP-siApoB could further be improved by decorating it with the trivalent N-acetylgalactosamine (TriGalNAc) ligand. These bioresponsive and liver-specific chimaeric polymersomes provide an enabling technology for siRNA therapy of various liver-related diseases.

Customized targeted massively parallel sequencing enables the identification of novel pathogenic variants in Tunisian patients with developmental and epileptic encephalopathy.

To develop a high-throughput sequencing panel for the diagnosis of developmental and epileptic encephalopathy in Tunisia and to clarify the frequency of disease-causing genes in this region. We developed a custom panel for next-generation sequencing of the coding sequences of 116 genes in individuals with developmental and epileptic encephalopathy from the Tunisian population. Segregation analyses and in silico studies have been conducted to assess the identified variants' pathogenicity. We report 12 pathogenic variants in SCN1A, CHD2, CDKL5, SZT2, KCNT1, GNAO1, PCDH19, MECP2, GRIN2A, and SYNGAP1 in patients with developmental and epileptic encephalopathy. Five of these variants are novel: "c.149delA, p.(Asn50MetfsTer26)" in CDKL5; "c.3616C > T, p.(Arg1206Ter)" in SZT2; "c.111_113del, p.(Leu39del)" in GNAO1; "c.1435G>C, p.(Asp479His)" in PCDH19; and "c.2143delC, p.(Arg716GlyfsTer10)" in SYNGAP1. Additionally, for four of our patients, the genetic result facilitated the choice of the appropriate treatment. This is the first report of a custom gene panel to identify genetic variants implicated in developmental and epileptic encephalopathy in the Tunisian population as well as the North African region (Tunisia, Egypt, Libya, Algeria, Morocco) with a diagnostic rate of 30%. This high-throughput sequencing panel has considerably improved the rate of positive diagnosis of developmental and epileptic encephalopathy in the Tunisian population, which was less than 15% using Sanger sequencing. The benefit of genetic testing in these patients was approved by both physicians and parents.

Whole exome sequencing revealed variants in four genes underlying X-linked intellectual disability in four Iranian families: novel deleterious variants and clinical features with the review of literature

Aim and ObjectiveIntellectual disability (ID) is a heterogeneous condition affecting brain development, function, and/or structure. The X-linked mode of inheritance of ID (X-linked intellectual disability; XLID) has a prevalence of 1 out of 600 to 1000 males. In the last decades, exome sequencing technology has revolutionized the process of disease-causing gene discovery in XLIDs. Nevertheless, so many of them still remain with unknown etiology. This study investigated four families with severe XLID to identify deleterious variants for possible diagnostics and prevention aims.MethodsNine male patients belonging to four pedigrees were included in this study. The patients were studied genetically for Fragile X syndrome, followed by whole exome sequencing and analysis of intellectual disability-related genes variants. Sanger sequencing, co-segregation analysis, structural modeling, and in silico analysis were done to verify the causative variants. In addition, we collected data from previous studies to compare and situate our work with existing knowledge.ResultsIn three of four families, novel deleterious variants have been identified in three different genes, including ZDHHC9 (p. Leu189Pro), ATP2B3 (p. Asp847Glu), and GLRA2 (p. Arg350Cys) and also with new clinical features and in another one family, a reported pathogenic variant in the L1CAM (p. Glu309Lys) gene has been identified related to new clinical findings.ConclusionThe current study's findings expand the existing knowledge of variants of the genes implicated in XLID and broaden the spectrum of phenotypes associated with the related conditions. The data have implications for genetic diagnosis and counseling.

Identification of Culprit Genes for Different Diseases by Analyzing Microarray Data.

The identification of disease-causing genes is the first and most important step toward understanding the biological mechanisms underlying a disease. Microarray analysis is one such powerful method that is widely used to identify genes that are expressed differently in two or more conditions (disease vs. normal). Because of its large library of statistical R packages and user-friendly interface, the R programming language provides a platform for microarray analysis. In this chapter, we will go over how to identify disease-causing culprit genes from the raw microarray data, using various packages of R programming. The pipeline overviews the steps in microarray analysis, such as data pre-processing, normalization, and statistical analysis using visualization techniques such as heatmaps, box plots, and so on. To better understand the function of the altered genes, gene ontology and pathway analysis are performed.

Systems Biology Approach to Analyze Microarray Datasets for Identification of Disease-Causing Genes: Case Study of Oral Squamous Cell Carcinoma.

The discovery of potential disease-causing genes can aid medical progress. The post-genomic era has made this a more difficult task. Modern high-throughput methods have not solved the problem of identifying disease genes. Conventional methods cannot be used to investigate many rare or lethal diseases. Monitoring gene expression values in different samples using microarray technology is one of the best and most accurate ways to identify disease-causing genes. One of the most recent advances in experimental molecular biology is microarrays, which allow researchers to simultaneously monitor the expression levels of thousands of genes. Statistical analysis of microarray data might aid gene discovery by revealing pathways related to the target gene and facilitating identification of candidate genes. Systems biology, an interdisciplinary approach, has emerged as a crucial analytic tool with the potential to reveal previously unidentified causes and consequences of human illness. Genetic, environmental, immunological, or neurological factors have been implicated in the developing complex disorders like cancer. Because of this, it is important to approach the study of such disease from a novel perspective. The system biology approach allows us to rapidly identify disease-causing genes and assess their viability as therapeutic targets. This chapter demonstrates systems biology approaches to identify candidate genes using public database. Oral squamous cell carcinoma (OSCC) is used as a model disease to show how systems biology can be used successfully to identify and prioritize disease genes.

A hybrid Stacking-SMOTE model for optimizing the prediction of autistic genes

PurposeAutism spectrum disorder(ASD) is a disease associated with the neurodevelopment of the brain. The autism spectrum can be observed in early childhood, where the symptoms of the disease usually appear in children within the first year of their life. Currently, ASD can only be diagnosed based on the apparent symptoms due to the lack of information on genes related to the disease. Therefore, in this paper, we need to predict the largest number of disease-causing genes for a better diagnosis.MethodsA hybrid stacking ensemble model with Synthetic Minority Oversampling TEchnique (Stack-SMOTE) is proposed to predict the genes associated with ASD. The proposed model uses the gene ontology database to measure the similarities between the genes using a hybrid gene similarity function(HGS). HGS is effective in measuring the similarity as it combines the features of information gain-based methods and graph-based methods. The proposed model solves the imbalanced ASD dataset problem using the Synthetic Minority Oversampling Technique (SMOTE), which generates synthetic data rather than duplicates the data to reduce the overfitting. Sequentially, a gradient boosting-based random forest classifier (GBBRF) is introduced as a new combination technique to enhance the prediction of ASD genes. Moreover, the GBBRF classifier combined with random forest(RF), k-nearest neighbor, support vector machine(SVM), and logistic regression(LR) to form the proposed Stacking-SMOTE model to optimize the prediction of ASD genes.ResultsThe proposed Stacking-SMOTE model is evaluated using the Simons Foundation Autism Research Initiative (SFARI) gene database and a set of candidates ASD genes.The results of the proposed model-based SMOTE outperform other reported undersampling and oversampling techniques. Sequentially, the results of GBBRF achieve higher accuracy than using the basic classifiers. Moreover, the experimental results show that the proposed Stacking-SMOTE model outperforms the existing ASD prediction models with approximately 95.5% accuracy.ConclusionThe proposed Stacking-SMOTE model demonstrates that SMOTE is effective in handling the autism imbalanced data. Sequentially, the integration between the gradient boosting and random forest classifier (GBBRF) support to build a robust stacking ensemble model(Stacking-SMOTE).

Haploinsufficiency of Lipin3 leads to hypertriglyceridemia and obesity by disrupting the expression and nucleocytoplasmic localization of Lipin1.

Lipin proteins including Lipin 1-3 act as transcriptional co-activators and phosphatidic acid phosphohydrolase enzymes, which play crucial roles in lipid metabolism. However, little is known about the function of Lipin3 in triglyceride (TG) metabolism. Here, we identified a novel mutation (NM_001301860: p.1835A>T/p.D612V) of Lipin3 in a large family with hypertriglyceridemia (HTG) and obesity through whole-exome sequencing and Sanger sequencing. Functional studies revealed that the novel variant altered the half-life and stability of the Lipin3 protein. Hence, we generated Lipin3 heterozygous knockout (Lipin3-heKO) mice and cultured primary hepatocytes to explore the pathophysiological roles of Lipin3 in TG metabolism. We found that Lipin3-heKO mice exhibited obvious obesity, HTG, and non-alcoholic fatty liver disorder. Mechanistic study demonstrated that the haploinsufficiency of Lipin3 in primary hepatocytes may induce the overexpression and abnormal distribution of Lipin1 in cytosol and nucleoplasm. The increased expression of Lipin1 in cytosol may contribute to TG anabolism, and the decreased Lipin1 in nucleoplasm can reduce PGC1α, further leading to mitochondrial dysfunction and reduced TG catabolism. Our study suggested that Lipin3 was a novel disease-causing gene inducing obesity and HTG. We also established a relationship between Lipin3 and mitochondrial dysfunction.