Complex Disease Research Articles

Progression of disease within 24 months (POD24) in multiple myeloma implicates poor prognosis and limitations of current prediction models for POD24

Multiple myeloma (MM) is a common hematological malignancy, and its prognostic factors have been extensively studied. Progression of disease within 24 months (POD24) suggests a poor prognosis in many malignancies, but is rarely mentioned in MM. This study aimed to investigate the prognostic value of POD24 in MM and risk factors of POD24, and to evaluate the predictive value of existing MM prognostic models for POD24. The research retrospectively analyzed the clinical data of MM patients and found that the occurrence of POD24 is an independent prognostic factor affecting overall survival in MM, while non-transplantion and genetic abnormality are independent risk factors for the occurrence of POD24. The existing prognostic models are not effective in predicting POD24. Therefore, it’s still necessary to explore a prognostic model that can predict POD24 more accurately.

NADPHnet: a novel strategy to predict compounds for regulation of NADPH metabolism via network-based methods.

Identification of compounds to modulate NADPH metabolism is crucial for understanding complex diseases and developing effective therapies. However, the complex nature of NADPH metabolism poses challenges in achieving this goal. In this study, we proposed a novel strategy named NADPHnet to predict key proteins and drug-target interactions related to NADPH metabolism via network-based methods. Different from traditional approaches only focusing on one single protein, NADPHnet could screen compounds to modulate NADPH metabolism from a comprehensive view. Specifically, NADPHnet identified key proteins involved in regulation of NADPH metabolism using network-based methods, and characterized the impact of natural products on NADPH metabolism using a combined score, NADPH-Score. NADPHnet demonstrated a broader applicability domain and improved accuracy in the external validation set. This approach was further employed along with molecular docking to identify 27 compounds from a natural product library, 6 of which exhibited concentration-dependent changes of cellular NADPH level within 100 μM, with Oxyberberine showing promising effects even at 10 μM. Mechanistic and pathological analyses of Oxyberberine suggest potential novel mechanisms to affect diabetes and cancer. Overall, NADPHnet offers a promising method for prediction of NADPH metabolism modulation and advances drug discovery for complex diseases.

Interpretable subgroup learning-based modeling framework: Study of diabetic kidney disease prediction.

Complex diseases, like diabetic kidney disease (DKD), often exhibit heterogeneity, challenging accurate risk prediction with machine learning. Traditional global models ignore patient differences, and subgroup learning lacks interpretability and predictive efficiency. This study introduces the Interpretable Subgroup Learning-based Modeling (iSLIM) framework to address these issues. iSLIM integrates expert knowledge with a tree-based recursive partitioning approach to identify DKD subgroups within an EHR dataset of 11,559 patients. It then constructs separate models for each subgroup, enhancing predictive accuracy while preserving interpretability. Five clinically relevant subgroups are identified, achieving an average sensitivity of 0.8074, outperforming a single global model by 0.1104. Post hoc analyses provide pathological and biological evidence supporting subgroup validity and potential DKD risk factors. The iSLIM surpasses traditional global model in predictive performance and subgroup-specific risk factor interpretation, enhancing the understanding of DKD's heterogeneous mechanisms and potentially increasing the adoption of machine learning models in clinical decision-making.

Alternations of the gut microbiota and the Firmicutes/Bacteroidetes ratio after biologic treatment in inflammatory bowel disease

BackgroundThe inflammatory bowel disease (IBD), comprising Crohn's disease (CD) and ulcerative colitis (UC) is a complex disease with multifactorial etiology. The intestinal dysbiosis have been investigated to play an important role in IBD pathogenesis and disease activity. The aim of our study was to analyze the intestinal microbiota composition in IBD across different severity levels and the impact of biologic therapy on microbiota modulation. MethodsIn this study, 27 IBD patients were recruited, including 14 patients undergoing biologic therapy for moderate to severe disease activity and 13 controls with inactive disease. The gut microbial composition was determined by 16 S ribosomal RNA gene sequencing of stool samples. ResultsBiologic therapy led to significant clinical improvement in IBD disease activity after 48 weeks. About species richness, community alpha diversity was significant lower in active CD patients and enriched gradually after biologic therapy. The beta-diversity regard to the difference of bacterial community composition showed significant difference between patients in biologic and control group. A decrease in Firmicutes and increase in Bacteroidetes abundance were observed in patients with active disease, both in CD and UC. Biologic treatment induced shifts in gut microbiota, with increased Firmicutes and decreased Bacteroidetes, as well as improved F/B ratio gradually after treatment, correlating with disease activity. ConclusionsOur study suggested that gut microbiota differences changed after biologic therapies among IBD with different disease activity, and a rising Firmicutes/Bacteroidetes ratio could be a potential predictor for disease activity and treatment response monitoring.

Differential serum metabolites in patients with pregnancy-associated venous thromboembolism analyzed using GC-MS/LC-MS untargeted metabolomics

Untargeted metabolomics can be used for the comprehensive analysis of metabolite profiles in biological samples without preset targets, making them particularly suitable for exploring metabolic characteristics and potential mechanisms in complex diseases. Therefore, in this study, we employed gas chromatography–mass spectrometry (GC-MS) and liquid chromatography–mass spectrometry (LC-MS) techniques to analyze the serum metabolic characteristics of patients with pregnancy-associated venous thromboembolism (PA-VTE). In this study, 11 pregnant women with VTE and 11 healthy pregnant women were included in the experimental and control groups, respectively. Using GC-MS, we identified 325 metabolites, with the highest proportion being organic oxygen compounds. Using LC-MS, we identified 3104 metabolites, with the highest proportion being acylcarnitine. The results revealed significant differences in the levels of lipids, organic compounds, and other metabolites between patients compared to healthy pregnant women. Pathways such as pyrimidine metabolism, linoleic acid metabolism, and mineral absorption differed between patients with PA-VTE and controls. Furthermore, we identified biomarkers associated with metabolic processes, such as fatty acids and amino acids (2-hydroxyhexanedioic acid, hexadecenal, palmitoylethanolamide, glycerol-1-phosphate, and N-acetyl-beta-D-glucosamine). These findings revealed the metabolic characteristics of PA-VTE and provided important clues for further research on its pathophysiological mechanisms. Our findings may contribute to the development of new diagnostic markers and support early diagnosis and treatment of PA-VTE.

CRISPR/Cas9 in the treatment of sickle cell disease (SCD) and its comparison with traditional treatment approaches: a review.

Sickle cell disease (SCD) is a common hereditary blood disorder that profoundly impacts individuals' health, causing chronic pain, anemia, organ damage, increased susceptibility to infections, and social and psychological effects. Over the years, advances in treatment have improved the long-term outcomes of SCD patients. However, problems such as limited access to hematopoietic stem cell transplantation (HSCT) and potential complications associated with the available therapies underscore the importance of continued research and development. The recent FDA approval of Casgevy (Exagamglogene autotemcel), a genetic therapy based on CRISPR/Cas9 technology, demonstrates a comprehensive effort to address the complexity of SCD using new technologies. This review explores the potential of CRISPR/Cas9 for treating SCD and evaluates its efficacy, safety, and long-term outcomes compared to traditional treatment approaches. Long-term research is needed to comprehensively assess the safety, effectiveness, and inclusion of CRISPR/Cas9, ensuring its overall efficacy.

Evaluating ASD in children through automatic analysis of paintings

Autism spectrum disorder (ASD) is a hereditary neurodevelopmental disorder affecting individuals, families, and societies worldwide. Screening for ASD relies on specialized medical resources, and current machine learning-based screening methods depend on expensive professional devices and algorithms. Therefore, there is a critical need to develop accessible and easily implementable methods for ASD assessment. In this study, we are committed to finding such an ASD screening and rehabilitation assessment solution based on children’s drawings. From an ASD painting database, 375 drawings from children with ASD and 160 drawings from typically developing children were selected, and a series of image signal processing algorithms based on typical characteristics of children with ASD were designed to extract features from images. The effectiveness of extracted features was evaluated through statistical methods, and they were then classified using a support vector machine (SVM) and XGBoost (eXtreme Gradient Boosting). In 5-fold cross-validation, the SVM achieved a recall of 94.93%, a precision of 86.40%, an accuracy of 85.98%, and an AUC of 90.90%, while the XGBoost achieved a recall of 96.27%, a precision of 93.78%, an accuracy of 92.90%, and an AUC of 98.00%. This efficacy persists at a high level even during additional validation on a set of newly collected paintings. Not only did the performance surpass that of participated human experts, but the high recall rate, as well as its affordability, manageability, and ease of implementation, indicates potentiality in wide screening and rehabilitation assessment. All analysis code is public at GitHub: dishangti/ASD-Painting-Pub.

A statistical model to identify hereditary and epigenetic fusion genes associated with dilated cardiomyopathy.

Dilated cardiomyopathy (DCM) is a heart condition that causes enlarged and weakened left ventricles and affects the heart's ability to pump blood effectively. Most genetic etiology still needs to be understood. Previously, we have used the known germline hereditary fusion genes (HFGs) to identify HFGs associated with multiple myeloma and leukemia. In this study, we have developed a statistical model to study fusion transcripts discovered from the left ventricles of 122 DCM patients and 252 GTEx (Genotype Tissue Expression) healthy controls to discover novel HFGs, ranging from 4% to 87.7%, and EFGs, ranging from 4% to 99.2%, associated with DCM. This discovery of numerous novel HFGs and EFGs associated with DCM provides first-hand evidence that DCM results from interactive developmental consequences between germline genetic and environmental abnormalities and paves the way for future research and diagnostic and therapeutic applications, instilling hope for the future of DCM treatment.

Unusual Confluence: Exploring the Association of Biliary Atresia, Wilson Disease, and Iron Overload

ABSTRACT The case involves a 33-year-old man with biliary atresia, Wilson disease (WD), and iron overload. Biliary atresia, a cholangiodestructive disease, leads to cirrhosis if untreated. WD, caused by ATP7B gene mutations, results in copper accumulation affecting the liver and brain. Iron overload can be seen in cases of WD and with hereditary hemochromatosis gene mutations. The patient's concurrent presentation of these conditions poses a unique clinical challenge. Elevated iron levels may worsen WD outcomes. A detailed history and physical examination, genetic testing, and close follow-up are crucial. The case highlights the need for increased awareness and vigilant monitoring of patients with overlapping liver diseases.

An overview of the role of chemokine CX3CL1 (Fractalkine) and CX3C chemokine receptor 1 in systemic sclerosis.

Systemic sclerosis (SSc) is a complex autoimmune disease characterized by fibrosis, vascular damage, and immune dysregulation. Fractalkine or chemokine (C-X3-C motif) ligand 1 (CX3CL1), a chemokine and adhesion molecule, along with its receptor CX3CR1, have been implicated in the inflammatory processes of SSc. CX3CL1 functions as both a chemoattractant and an adhesion molecule, guiding immune cell trafficking. This systematic review examines the role of CX3CL1 and its receptor CX3CR1 in the pathogenesis of SSc, with a focus on pulmonary and vascular complications. A systematic literature search was conducted across databases including PubMed, Scopus, and Web of Science from inception to November 2020. The search focused on studies investigating the CX3CL1/CX3CR1 axis in the context of SSc. The review identified elevated CX3CL1 expression in SSc patients, particularly in the skin and lungs, where CX3CR1 is expressed on infiltrating immune cells. Higher levels of CX3CL1 were correlated with the severity of interstitial lung disease in SSc patients, indicating a potential predictive marker for disease progression. CX3CR1-positive monocytes and NK cells were recruited to inflamed tissues, contributing to fibrosis and tissue damage. Animal studies showed that inhibition of the CX3CL1/CX3CR1 axis reduced fibrosis and improved vascular function. The CX3CL1/CX3CR1 axis plays a key role in immune cell recruitment and fibrosis in SSc. Elevated CX3CL1 levels are associated with lung and vascular complications, making it a potential biomarker for disease progression and a promising therapeutic target.

Evaluating Experiences in a Digital Nutrition Education Program for People With Multiple Sclerosis: A Qualitative Study.

Multiple sclerosis (MS) is a complex immune-mediated disease with no currently known cure. There is growing evidence to support the role of diet in reducing some of the symptoms and disease progression in MS, and we previously developed and tested the feasibility of a digital nutrition education program for people with MS. The aim of this study was to explore factors that influenced engagement in the digital nutrition education program, including features influencing capability, opportunity and motivation to change their dietary behaviours. Semi-structured interviews were conducted with people who had MS, and who completed some or all of the program until data saturation was reached. Interviews were analysed inductively using thematic analysis. Themes were deductively mapped against the COM-B (Capability, Opportunity, Motivation, Behaviour) behaviour change model. Sixteen interviews were conducted with participants who completed all (n = 10) or some of the program (n = 6). Four themes emerged: (1) acquiring and validating nutrition knowledge; (2) influence of time and social support; (3) getting in early to improve health and (4) accounting for food literacy experiences. This is the first online nutrition program with suitable behavioural supports for people with MS. It highlights the importance of disease-specific and evidence-based nutrition education to support people with MS to make dietary changes. Acquiring nutrition knowledge, coupled with practical support mechanisms, such as recipe booklets and goal setting, emerged as crucial for facilitating engagement with the program. When designing education programs for people with MS and other neurological conditions, healthcare professionals and program designers should consider flexible delivery and building peer support to address the needs and challenges faced by participants. Members of the MS Nutrition Research Program Stakeholder Reference Group, which includes people with MS and MS health professionals, provided input during the development of the nutrition education program and study design stages.

Cancer Pathways Targeted by Berberine: Role of microRNAs.

Cancer is a complex and heterogeneous malignant disease. Due to its multifactorial nature, including progressive changes in genetic, epigenetic, transcript, and protein levels, conventional therapeutics fail to save cancer patients. Evidence indicates that dysregulation of microRNA (miRNA) expression plays a crucial role in tumorigenesis, metastasis, cell proliferation, differentiation, metabolism, and signaling pathways. Moreover, miRNAs can be used as diagnostic and prognostic markers and therapeutic targets in cancer. Berberine, a naturally occurring plant alkaloid, has a wide spectrum of biological activities in different types of cancers. Inhibition of cell proliferation, metastasis, migration, invasion, and angiogenesis, as well as induction of cell cycle arrest and apoptosis in cancer cells, is reported by berberine. Recent studies suggested that berberine regulates many oncogenic and tumor suppressor miRNAs implicated in different phases of cancer. This review discussed how berberine inhibits cancer growth and propagation and regulates miRNAs in cancer cells. And how berberine-mediated miRNA regulation changes the landscape of transcripts and proteins that promote or suppress cancer progression. Overall, the underlying molecular pathways altered by berberine and miRNA influencing the tumor pathophysiology will enhance our understanding to combat the malignancy.

EQUAL ABPA Score 2024: A Tool to Measure Guideline Adherence for Managing Allergic Bronchopulmonary Aspergillosis.

Allergic bronchopulmonary aspergillosis (ABPA) is a complex lung disease associated with significant morbidity. The ABPA Working Group (AWG) of the International Society for Human and Animal Mycology (ISHAM) revised their management guidelines in 2024, but there is currently no standardised tool to assess adherence to these recommendations. We extracted key recommendations from the updated 2024 ISHAM-AWG guidelines, focusing on critical areas: screening and diagnosis of ABPA, managing acute and treatment-dependent ABPA, and monitoring treatment response. Each item was assigned a score ranging from zero to three. We assigned negative scores to interventions not recommended by the guidelines. We identified 38 items indicative of optimal clinical care for patients with ABPA. The score for screening asthmatics for ABPA was set at three points. For diagnosing ABPA, 16 items were included, with a score ranging from 12 to 16 points, depending on the specific components used (predisposing conditions, serum A. fumigatus-specific IgE and IgG, serum total IgE, blood eosinophil count and chest computed tomography). The management of acute ABPA comprised 11 items, with a maximum score of three points. For treatment-dependent ABPA, there were nine items (scores ranging from -3 to 6). Follow-up care comprised 10 items with a maximum score of 10-13 points, covering imaging, spirometry, testing serum total IgE levels and therapeutic drug monitoring. The EQUAL ABPA score has been developed as a comprehensive tool to quantify guideline adherence. Future studies will evaluate to which extent guideline adherence is associated with improved clinical outcomes for patients with ABPA.

Advancing cancer driver gene identification through an integrative network and pathway approach

ObjectiveCancer is a complex genetic disease characterized by the accumulation of various mutations, with driver genes playing a crucial role in cancer initiation and progression. Distinguishing driver genes from passenger mutations is essential for understanding cancer biology and discovering therapeutic targets. However, the majority of existing methods ignore the mutational heterogeneity and commonalities among patients, which hinders the identification of driver genes more effectively. MethodsThis study introduces MCSdriver, a novel computational model that integrates network and pathway information to prioritize the identification of cancer driver genes. MCSdriver employs a bidirectional random walk algorithm to quantify the mutual exclusivity and functional relationships between mutated genes within patient cohorts. It calculates similarity scores based on a mutual exclusivity-weighted network and pathway coverage patterns, accounting for patient-specific heterogeneity and molecular profile similarity. ResultsThis approach enhances the accuracy and quality of driver gene identification. MCSdriver demonstrates superior performance in identifying cancer driver genes across four cancer types from The Cancer Genome Atlas, showing a higher F-score, Recall and Precision compared to existing ranking list-based and module-based models. ConclusionThe MCSdriver model not only outperforms other models in identifying known cancer driver genes but also effectively identifies novel driver genes involved in cancer-related biological processes. The model’s consideration of patient-specific heterogeneity and similarity in molecular profiles significantly enhances the accuracy and quality of driver gene identification. Validation through Gene Ontology enrichment analysis and literature mining further underscores its potential application value in personalized cancer therapy, offering a promising tool for advancing our understanding and treatment of cancer.

Dark Tea Wine Protects Against Metabolic Dysfunction-Associated Steatotic Liver Disease In Vivo Through Activating the Nrf2/HO-1 Antioxidant Signaling Pathway.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a complex and multifactorial disease. Dark tea exhibits great potential for various bioactivities for metabolic health. In this study, we aimed to evaluate therapeutic effects and the underlying mechanisms of dark tea wine (DTW) on MASLD with obesity. A rat model of MASLD was established by high-fat diet and administered with different doses of DTW as an intervention. The biomarkers of lipid metabolism and oxidative stress in rats were tested. The weight of organs and adipose tissues and the expressions of nuclear factor erythroid 2-like 2 (Nrf2) and heme oxygenase-1 (HO-1) were investigated based on the pathology and western blot analysis. We found that DTW enhanced antioxidant capacity via activating the Nrf2/HO-1 signaling pathway, further markedly triggering inhibition of weight gain, reduction of lipid dysfunction, and improvement of pathological characteristics to ameliorate MASLD induced by high-fat diet. These results suggest that DTW is a promising functional supplement for prevention and treatment of MASLD and obesity.

Extremely Low Birth Weight Infant (Gestational Age of 29 Weeks) With Kabuki Syndrome Type I: Case Report and Literature Review.

This paper aimed to investigate the clinical phenotype of Kabuki syndrome (KS) in premature infants. This paper presents a case of an extremely low birth weight infant (gestational age 29 weeks) with KS1 caused by a variant in the KMT2D gene. The clinical, pathological, and differential diagnostic findings were comprehensively analyzed. A thorough literature review was also performed to enhance the understanding of KS, revealing its unique features and prognostic significance. The infant was a male with a gestational age of 29 weeks and a birth weight of 850 g. He had intrauterine growth retardation, characterized by cleft palate, sacrococcygeal skin depressions, and recurrent metabolic acidosis. Whole-exome sequencing revealed the c.4267C > T (p.Arg1423Cys) variant in the KMT2D gene, which was absent in his parents. The patient was discharged after 67 days of treatment, and he was followed up to 19 months of corrected gestational age, with growth retardation and expression language delay. Ten previous studies on preterm infants were retrieved, with 10 preterm infants. They all had characteristic facial features, such as long blepharophimosis, sparse and lateral 1/3 eyebrows, and large and prominent/cupped ears. Other manifestations were extrauterine growth delay (7/10), abnormal development of the cardiovascular system (7/10), abnormal development of the nervous system (5/10), and cleft palate (2/10). Kabuki syndrome is a rare hereditary disorder involving multiple organs and systems. Genetic assessment for preterm infants with congenital abnormalities is recommended.

Targeting ICAM1 to Ameliorate Vaso-Occlusion and Inflammation in Sickle Cell Disease.

Sickle cell disease (SCD) is a hereditary disorder characterized by vaso-occlusion, inflammation, and tissue damage. Intercellular adhesion molecule 1 (ICAM-1) plays a crucial role in the pathophysiology of SCD by promoting the adhesion of sickle cells to the endothelium, contributing to vaso-occlusion and tissue damage. The ICAM-1 gene encodes a glycoprotein that interacts with lymphocyte function-associated antigen 1 (LFA-1) and macrophage 1-antigen (Mac-1) receptors, perpetuating inflammation, and oxidative stress. The NF-κB signaling pathway regulates ICAM-1 expression, which is elevated in patients with SCD, leading to increased endothelial cell activation and damage. Targeting ICAM-1 and its interactions with sickle cells and the endothelium has emerged as a potential therapeutic strategy for managing SCD. This review highlights the complex interplay between ICAM-1, sickle cells, and the endothelium, and discusses the potential of ICAM-1-targeted therapies for mitigating VOC and improving the quality of life for patients with SCD.

Chromosomal Abnormalities Detected by Chromosomal Microarray Analysis and Karyotype in Fetuses with Ultrasound Abnormalities.

Chromosomal microarray analysis (CMA) is a first-line test to assess the genetic etiology of fetal ultrasound abnormalities. The aim of this study was to evaluate the effectiveness of CMA in detecting chromosomal abnormalities in fetuses with ultrasound abnormalities, including structural abnormalities and non-structural abnormalities. A retrospective study was conducted on 368 fetuses with abnormal ultrasound who received interventional prenatal diagnosis at Meizhou People's Hospital from October 2022 to December 2023. Samples of villi, amniotic fluid, and umbilical cord blood were collected according to different gestational weeks, and karyotype and CMA analyses were performed. The detection rate of chromosomal abnormalities in different ultrasonic abnormalities was analyzed. There were 368 fetuses with abnormal ultrasound, including 114 (31.0%) with structural abnormalities, 225 (61.1%) with non-structural abnormalities, and 29 (7.9%) with structural combined with non-structural abnormalities. The detection rate of aneuploidy and pathogenic (P)/likely pathogenic (LP) copy number variations (CNVs) of CMA in fetuses with structural abnormalities was 5.26% (6/114), the detection rate of karyotype was 2.63% (3/114), and the additional diagnosis rate of CMA was 2.63%. In the fetuses with ultrasonic non-structural abnormalities, the detection rate of karyotype was 6.22% (14/225), the detection rate of aneuploidy and P/LP CNVs in fetuses with ultrasonic structural abnormalities was 9.33% (21/225), and the additional diagnosis rate of CMA was 3.11%. There was no significant difference in chromosome abnormality detection rate of CMA among structural abnormality, non-structural abnormality, and structural abnormality combined with non-structural abnormality groups (5.3%, 9.3%, and 13.8%, p = 0.241), also among multiple ultrasonic abnormality and single ultrasonic abnormality groups (14.8%, and 7.3%, p = 0.105). CMA can significantly improve the detection rate of genetic abnormalities in prenatal diagnosis of ultrasonic abnormal fetuses compared with karyotype analysis. CMA is a more effective tool than karyotyping alone in detecting chromosomal abnormalities in fetuses with ultrasound abnormalities.

Two novel deep intronic variants cause Duchenne muscular dystrophy by splice-altering mechanism

Duchenne muscular dystrophy (DMD) is a genetic disorder characterized by progressive muscle degeneration and weakness, due to mutations in the DMD gene, which encodes the dystrophin protein. While mutations within the coding regions of DMD have been extensively studied, recent focus has shifted to deep intronic variants for their potential impact on disease severity. Here, we characterize two deep intronic variants, c.8669-19_8669-24del and c.6439-1016_6439-3376del, in unrelated DMD patients. These variants were identified using targeted long-read sequencing on patients' DNA. RNA sequencing/reverse transcription polymerase chain reaction on RNA extracted from muscle biopsies revealed the presence of a pseudoexon or retention of part of the intron in the transcript, resulting in the introduction of premature termination codons. This study enhances our understanding of pseudoexon activation mechanisms in DMD and underscores the diverse genetic abnormalities contributing to the disease's complexity.

Mitochondrial genetic variations in leukemia: a comprehensive overview.

Leukemias are a group of heterogeneous hematological malignancies driven by diverse genetic variations, and the advent of genomic sequencing technologies facilitates the investigation of genetic abnormalities in leukemia. However, these sequencing-based studies mainly focus on nuclear DNAs. Increasing evidence indicates that mitochondrial dysfunction is an important mechanism of leukemia pathogenesis, which is closely related to the mitochondrial genome variations. Here, we provide an overview of current research progress concerning mitochondrial genetic variations in leukemia, encompassing gene mutations and copy number variations. We also summarize currently accessible mitochondrial DNA (mtDNA) sequencing methods. Notably, somatic mtDNA mutations may serve as natural genetic barcodes for lineage tracing and longitudinal assessment of clonal dynamics. Collectively, these findings enhance our understanding of leukemia pathogenesis and foster the identification of novel therapeutic targets and interventions.