Single-cell transcriptomic analysis reveals impaired mitochondrial gene expression in the podocytes of a child with primary coenzyme Q10 nephropathy.

Single-cell transcriptomic analysis reveals impaired mitochondrial gene expression in the podocytes of a child with primary coenzyme Q10 nephropathy. | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Single-cell transcriptomic analysis reveals impaired mitochondrial gene expression in the podocytes of a child with primary coenzyme Q10 nephropathy. Peong Gang Park, Sowon Choi, Yo Han Ahn, Seong Heon Kim, Chaeyoon Kim, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4868504/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 14 Jan, 2025 Read the published version in Pediatric Nephrology → Version 1 posted 5 You are reading this latest preprint version Abstract Background Coenzyme Q10 (CoQ10) nephropathy is a well-known cause of hereditary steroid-resistant nephrotic syndrome, primarily impacting podocytes. This study aimed to elucidate variations in individual cell-level gene expression in CoQ10 nephropathy using single-cell transcriptomics. Methods We conducted single-cell sequencing of a kidney biopsy specimen from a 5-year-old boy diagnosed with a CoQ10 nephropathy caused by a compound heterozygous COQ2 mutation. The analysis focused on the proportion of cell types, differentially expressed genes in each cell type, changes in gene expression related to mitochondrial function and oxidative phosphorylation (OXPHOS). Results Our findings revealed a uniform downregulation of mitochondrial gene expression across various cell types in the context of these mutations. Notably, there was a specific decrease in mitochondrial gene expression across all cell types. The study also highlighted an altered immune cell population proportion attributed to the COQ2 gene mutation. Pathway analysis indicated a downregulation in OXPHOS and an upregulation of various synthesis pathways, particularly in podocytes. Conclusion This study improves our understanding of CoQ10 nephropathy's pathogenesis and highlights the potential applications of single-cell sequencing in hereditary kidney diseases. Coenzyme Q 10 nephropathy COQ2 mutation hereditary nephropathy single cell transcriptomics single cell RNA sequencing Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction The association of primary coenzyme Q10 (CoQ10) deficiency with human diseases was first established in 1989, based on a clinical study conducted by Ogasahara and colleagues [ 1 ]. Subsequently, in 2006, the molecular etiology of CoQ10 deficiency was elucidated with the identification of a gene mutation impairing CoQ10 biosynthesis [ 2 ]. Recent years have seen an escalation in reported cases of primary CoQ10 deficiency, characterized by a diverse array of organ involvements, including steroid-resistant nephrotic syndrome (SRNS). From the latter half of 2010, the term "CoQ10 nephropathy" began to be used to refer to inherited kidney disease, especially glomerulopathy such as SRNS, caused by mutations in the genes related to the CoQ10 biosynthesis pathway. Previous research reported that CoQ10 nephropathy due to mutations in genes such as PDSS2 , COQ2 , COQ6 , and COQ8B , are identified in approximately 1–2.7% of SRNS cases [ 3 ]. Our previous research, however, revealed a higher prevalence; among 291 Korean children diagnosed with SRNS or focal segmental glomerulosclerosis, we detected mutations in 127 patients, with 20 (6.9%) of these mutations being identified as CoQ10 nephropathy [ 4 , 5 ]. This finding suggests a greater frequency of these mutations than previously reported. An early diagnosis of primary CoQ10 nephropathy is essential because the condition is possibly treatable when CoQ10 supplementation is started at the early stage [ 6 ]. Single-cell RNA sequencing (scRNA-seq) has emerged as a pivotal technique for dissecting gene expression at the level of individual cells, offering unparalleled insights into the intricate and varied cellular reactions within diverse biological settings [ 7 ]. Employing scRNA-seq, novel insights have been gained into the cell type-specific characteristics of various kidney diseases. A notable example includes chronic kidney disease (CKD), where significant changes in the gene expression of proximal tubule (PT) cells have been observed [ 8 ]. However, prior research employing scRNA-seq has predominantly concentrated on prevalent and/or immunologically driven conditions, such as CKD and lupus nephritis, thereby highlighting the need for broader application of this technique across a wider spectrum of kidney disorders, such as inherited kidney diseases [ 9 ]. In this study, we identified a novel compound heterozygous variant in the COQ2 gene of a patient and explored variations of individual cell-level expression using single-cell transcriptomics. By comparing the single-cell transcriptomic data of kidney tissue from the patient against a reference database, we found that these mutations uniformly downregulated mitochondrial gene expression across various cell types. This was accompanied by an increase in glycolysis-related gene expression specifically in the podocytes. Pathway analysis revealed a downregulation of oxidative phosphorylation (OXPHOS) and an upregulation of synthesis pathways in the podocytes. These insights contribute to our understanding of the pathogenesis and potential therapeutic approaches for primary CoQ10 nephropathy. Methods Clinical manifestations, histological analysis and genetic analysis We collected the patient's clinical information, which includes demographic information, symptoms, results of laboratory tests, and the medical history of the patient's family. The sample from the core needle biopsy was prepared for histological analysis under both light and electron microscopes. To conduct genetic analysis, we extracted genomic DNA from the blood samples of the patient and his parents, then performed whole-exome sequencing. We applied a targeted gene capture method to specifically examine 68 genes associated with conditions related to Mendelian nephrotic syndrome [ 10 ]. The pathogenicity of the detected COQ2 mutations were assessed following the American College of Medical Genetics and Genomics' guidelines [ 11 ]. Tissue procurement, single-cell isolation and Gel bead in Emulsion generation Fresh human kidney tissue was obtained from needle biopsy at the Seoul National University Children’s Hospital. The kidney tissue was transported on ice in media containing 10% FBS in RPMI1640 (SH30027.01; Thermo Fisher Scientific, Waltham, MA, USA), then washed in cold PBS (ML008-01; Welgene, Gyeongsangbuk-do, Republic of Korea). The tissue was chopped and dissociated with Liberase™ TL (#05401020001; Roche, Mannheim, Germany, 0.25mg/mL in PBS) in a 37°C water bath for 30 minutes. The tissue was then mechanically dissociated using a wide-bore pipette tip. Afterwards, the cells isolated from the tissue were filtered through a strainer with a mesh size of 70µm (#93070; SPL Life Sciences, Gyeonggi-do, Republic of Korea), followed by centrifugation (500g, 5min, 4°C). Then, the cells were resuspended with 60µL of cold media for cell counting and then diluted to the proper cell concentration The cells were immediately loaded onto the 10X Chromium Controller. Library preparation and NGS sequencing Libraries were generated using the Chromium Single Cell 3′ Library & Gel Bead Kit V3.1 and Chromium Single Cell 3′ Chips according to the manufacturer’s instructions. In short, single-cell samples and reagents were loaded on a 10X Chromium controller for droplet generation, followed by reverse transcription in the droplets, cDNA amplification and fragmentation. Then, fragments were ligated with adapters and dual-indices to mitigate index-hopping. The 4150 TapeStation system (Agilent, Santa Clara, CA, USA) was used to evaluate the quality of the barcoded single-cell transcriptome libraries. After quality control, the libraries were sequenced with NovaSeq 6000. Single-cell RNA-seq data analysis Raw sequencing reads were aligned to GRCh38 (human) using Cell Ranger v7.1.0. Low quality single cells with fewer than 200 detected genes or more than 3,000 detected genes were filtered out. Additionally, cells with mitochondrial genes constituting over 50% of all genes were also removed using Seurat package v5.0.1. Single cell data from the patient and five normal adults from a public database were integrated and batch-corrected using the HarmonyIntegration method within the Seurat package [ 12 ]. We conducted graph-based clustering and adjusted resolution parameter to 0.4. Seurat was used to find cluster-specific genes and then each cluster was manually annotated referring to public kidney scRNA-seq data [ 13 ]. Differentially expressed genes (DEGs) were selected according to the following criteria: Upregulated DEGs, average log2 fold change > 0.5 and adjusted p-value < 0.05; Downregulated DEGs, average log2 fold change < -0.5 and adjusted p-value < 0.05. Gene expression fold changes between disease group and control group were analyzed for gene sets related to CoQ10, mitochondrial function, OXPHOS and glycolysis across our clusters and then visualized with a heatmap. To conduct pathway enrichment analysis, gene sets associated with biological processes from the Gene Ontology in MSigDB were selected [ 14 ]. For input, we used the log2-fold change values from Seurat DEG analysis. The most significantly enriched pathways were identified by GSEA analysis across specific cell clusters such as podocytes. Results Clinical manifestation A 6-year-old Korean boy was transferred to our hospital due to persistent edema, having been previously healthy with normal growth and developmental milestones. 3 weeks before his transfer, he was noted to have foamy urine and edema. Initial laboratory findings at the previous hospital were indicative of nephrotic syndrome (Table 1 ). Despite receiving standard-dose glucocorticoids for 20 days, his proteinuria persisted, and kidney function declined. A kidney biopsy revealed glomerular mesangial hyperplasia, tubulointerstitial lesions, and both global and segmental sclerosis of the glomeruli with crescent formation. Immunofluorescence microscopy showed diffuse mesangial and peripheral deposits of IgM, C3, and C1q. Electron microscopy identified small mesangial and subendothelial electron-dense deposits with foot process effacement (Fig. 1 ). These findings, coupled with the lack of response to steroid therapy, led to a diagnosis of membranoproliferative glomerulonephritis. Table 1. Baseline patient characteristics Parameters Initial presentation 4 weeks after steroid Reference range Total protein (g/dL) 3.9 3.5 6.0 – 8.0 Albumin (g/dL) 1.8 1.5 3.3 – 5.2 Serum creatinine (mg/dL) 0.84 1.16 0.4 – 0.8 eGFR (ml/min/1.73 2 ) 56.4 40 Total cholesterol (mg/dL) 505 810 0 – 240 Triglyceride (mg/dL) 1060 637 0 – 200 C3 (mg/dL) 64 59 80 – 173 C4 (mg/dL) 19 19 13 – 46 IgG (mg/dL) 56 24 540 – 1822 Urine Protein 4+ 4+ RBC (/HPF) 1 – 4 1 – 4 0 – 4 Protein/creatinine ratio 84.1 40.4 < 0.2 Abbreviation: eGFR, estimated glomerular filtration rate; RBC, red blood cell Despite intensive immunosuppressive therapies targeting membranoproliferative glomerulonephritis, the patient's kidney function continued to deteriorate (Fig. 2 a). Targeted exome sequencing for SRNS belatedly revealed compound heterozygous likely pathogenic variants of COQ2 , c.518G > A (p.Arg173His) from father and c.973A > G (p.Thr325Ala) from mother [ 9 ] (Fig. 2 b), therefore immunosuppressive therapy was discontinued and high-dose CoQ10 supplementation was initiated. Maintenance kidney replacement therapy was initiated 2 months after disease onset; tragically, 6 weeks after the initiation of dialysis, the patient demised along with cardiopulmonary failure following fever of unknown cause. Single-cell transcriptome analysis To investigate the altered gene expression and pathways in this patient at a single-cell level, we obtained a kidney biopsy sample and generated transcriptome datasets from 3,737 cells after excluding low-quality cells. The patient’s single-cell transcriptomics data were integrated with transcriptomics data from five young adults (aged 20 to 40 years) with normal kidney function, sourced from the public Kidney Precision Medicine Project database [ 12 ]. Following batch correction and integration with the public dataset, we performed unsupervised clustering, resulting in 15 distinct cell types (Fig. 3 a). Each cluster was annotated using canonical cell type–specific marker genes for kidney epithelial, endothelial, and immune cells (Fig. 3 b ) . The general cellular composition was similar between the patient and the control group (Fig. 3 c ) . However, the proportion of immune cells was higher in the patient, while the control group exhibited a greater proportion of parenchymal cells, particularly endothelial cells (Fig. 3 d and Fig. 3 e). The elevated immune cell count in the patient might contribute to the development of a membranoproliferative pattern of glomerulonephritis [ 15 ]. Given the genetic confirmation of a COQ2 mutation in this patient, we analyzed the expression of CoQ10-related genes, including COQ2 . As depicted in Fig. 4 a, COQ2 mRNA expression was detectable in the patient, suggesting that the mutation leads to a functional defect rather than an alteration in expression level. However, we observed a notable upregulation of COQ6 and COQ10A , and downregulation of COQ4 and COQ9 , particularly in podocytes. This suggests a varied impact on CoQ10 biosynthesis, especially in podocytes. Further, we examined changes in the expression levels of mitochondrial genes and found a uniform downregulation across all cell types, indicating a severe impairment in mitochondrial function (Fig. 4 b ) . We also assessed changes in genes related to OXPHOS, a key mitochondrial function. While genes associated with Complexes I, II, III, and IV were downregulated, those related to Complex V (ATP synthase) were upregulated in various cell types (Fig. 4 c ) . Interestingly, there was a specific upregulation of glycolysis-related genes in podocytes (Fig. 4 d ) . Notably, genes linked to podocyte development were uniquely downregulated in the patient’s podocytes, suggesting impaired podocyte function or their dedifferentiation (Fig. 4 e ) . Lastly, pathway analysis using hallmark gene sets revealed a downregulation of OXPHOS and an upregulation of fibrous tissue synthesis pathways (Fig. 4 f ) . Discussion Single cell methodologies have facilitated the observation of gene expression alterations in thousands of distinct cells within a single experiment. In acute kidney injury, scRNA-seq has led to the discovery of a new cell type derived from proximal tubules and increase in interferon response and the expression of chemokine receptors in various cell clusters were demonstrated in lupus nephritis [9,16]. However, there have been few attempts to examine gene expression through scRNA-seq in human genetic kidney diseases, and to the best of our knowledge, this study is the first to present such results. Generally, tissue biopsies are not performed in pediatric nephrotic syndrome, making it difficult to obtain human tissue samples. However, in this case, a biopsy was conducted to clarify SRNS, allowing the use of a portion of the tissue for this examination [17]. Consequently, we were able to present a single cell transcriptome analysis for CoQ10 nephropathy, offering an unparalleled level of cellular detail and transcriptional insight. One of the major findings of this study is that while there was no significant downregulation in gene expression related to CoQ10 biosynthesis in major clusters, there was a severe reduction in the expression of mitochondrial genes in every cell cluster. It is likely that the mutation observed in this patient impaired the function, rather than the expression level, of the CoQ10 biosynthesis pathway. This functional impairment is thought to have affected mitochondrial gene expression. CoQ10 plays a pivotal role in OXPHOS, a critical process for energy generation within cells. Deficiencies in the enzymes responsible for CoQ10 synthesis can lead to a marked decrease in intracellular energy production. This deficit predominantly affects tissues with high demands for mitochondrial energy, such as the brain, kidney tubules, and podocytes, where pathological changes are likely to occur as a result of impaired energy metabolism [18]. In many cases of mitochondriopathies, which arise from multiple mitochondrial gene defects, severe developmental delays are often observed due to brain involvement [19]. However, the patient with COQ2 nephropathy presented in this study exhibited normal development. Furthermore, while a significant number of diseases result in severe tubulopathy, this patient demonstrated normal tubular function. These findings suggest a distinctive pathophysiological mechanism in COQ2 nephropathy that spares certain functions impaired in other mitochondrial disorders. Brain tissue, proximal tubules, and podocytes are all energy-intensive tissues [20]. However, further research is required to elucidate how specific gene mutations selectively impact these tissues. This necessitates a deeper understanding of the differential vulnerability and pathophysiological mechanisms in these high energy-demand tissues. Specifically, the gene expression related with Complexes I-IV, which generate the electron gradient, was predominantly diminished, while there was an upregulation in the expression of Complex V. This observation implies a possible compensatory effect and differs from the results observed in the Adck4- knockout mouse, where protein expression appeared to be insignificantly altered in the knockout specimen [21]. Notably, in podocytes, there was an increased expression of genes related to glycolysis, which is also thought to be a compensatory response to the impaired energy production. Previous research on the pathophysiology of CoQ10 nephropathy is limited. Widmeier and his colleagues utilized podocyte-specific, Adck4 - and coq6 - knockout mouse model to clarify educed respiratory chain activity and mitochondrial potential in CoQ10 nephropathy model [21,22]. This study delves deeper into the pathophysiology of this genetic disorder by demonstrating defects in mitochondrial function using human tissue. Furthermore, it highlighted the potential for employing scRNA-seq in the study of other inherited kidney diseases. A key strength of this study lies in its methodology of preparing tissue samples. Instead of using frozen or thawed preparations, an 'on-call' preparation method was employed. This approach enabled the creation of a cDNA library within six hours of tissue acquisition from the human body, thereby minimizing gene alterations that could potentially arise from storage processes. However, this study has certain limitations. First, the kidney biopsy was performed after four weeks of steroid treatment, which could have altered the gene expression profile from that at the onset of the disease. Second, the control group for comparison ideally should have comprised age-matched pediatric kidneys. However, since it was based on normal adults aged 20-40, there could have been differences in gene expression related to age. In conclusion, this study provides a complementary investigation of the clinical and molecular response of the kidney in CoQ10 nephropathy. Transcriptomic evidence identifies the loss of mitochondrial function in various cell types and defective functions of podocytes. In future research, the application of scRNA-seq together with spatial transcriptomics in hereditary kidney diseases such as Alport syndrome and autosomal dominant polycystic kidney disease, which pose significant disease burdens, is anticipated to substantially broaden our understanding of their pathophysiology. Statements and declarations Funding : This research was funded by the Seoul National University Convergence Research Support Program (Project No. 800-20220547). Competing interests : All authors declare that they do not have conflict of interest. Ethics approval : The Seoul National University Hospital's institutional review board approved the study (IRB No. H-2204-014-1312) Consent to participate and publication : Written consent was provided by the guardian of the study subject. Availability of data and material : The dataset for single-cell RNA transcriptomics has been deposited in the Gene Expression Omnibus database (accession number: GSE270701). This study does not report any original code, and the codes used are available in the Method section. Any additional information required to reanalyze the data is available from the lead contact upon request. References Ogasahara S, Engel AG, Frens D, Mack D. Muscle coenzyme q deficiency in familial mitochondrial encephalomyopathy. Proc Natl Acad Sci U S A 1989;86:2379-2382. Quinzii C, Naini A, Salviati L, Trevisson E, Navas P, Dimauro S, Hirano M. A mutation in para-hydroxybenzoate-polyprenyl transferase ( COQ2 ) causes primary coenzyme q10 deficiency. Am J Hum Genet 2006;78:345-349. Sadowski CE, Lovric S, Ashraf S, Pabst WL, Gee HY, Kohl S, Engelmann S, Vega-Warner V, Fang H, Halbritter J, et al. A single-gene cause in 29.5% of cases of steroid-resistant nephrotic syndrome. J Am Soc Nephrol 2015;26:1279-1289. Park E, Lee C, Kim NKD, Ahn YH, Park YS, Lee JH, Kim SH, Cho MH, Cho H, Yoo KH, et al. Genetic study in korean pediatric patients with steroid-resistant nephrotic syndrome or focal segmental glomerulosclerosis. J Clin Med 2020;9. Kim SY. Navigating the landscape of clinical genetic testing: Insights and challenges in rare disease diagnostics. Child Kidney Dis 2024;28:8-15. Montini G, Malaventura C, Salviati L. Early coenzyme q10 supplementation in primary coenzyme q10 deficiency. N Engl J Med 2008;358:2849-2850. Balzer MS, Ma Z, Zhou J, Abedini A, Susztak K. How to get started with single cell rna sequencing data analysis. J Am Soc Nephrol 2021;32:1279-1292. Qiu C, Huang S, Park J, Park Y, Ko YA, Seasock MJ, Bryer JS, Xu XX, Song WC, Palmer M, et al. Renal compartment-specific genetic variation analyses identify new pathways in chronic kidney disease. Nat Med 2018;24:1721-1731. 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Faseb j 2017;31:294-307. Clemente-Suárez VJ, Redondo-Flórez L, Beltrán-Velasco AI, Ramos-Campo DJ, Belinchón-deMiguel P, Martinez-Guardado I, Dalamitros AA, Yáñez-Sepúlveda R, Martín-Rodríguez A, Tornero-Aguilera JF. Mitochondria and brain disease: A comprehensive review of pathological mechanisms and therapeutic opportunities. Biomedicines 2023;11. Hoogstraten CA, Hoenderop JG, de Baaij JHF. Mitochondrial dysfunction in kidney tubulopathies. Annu Rev Physiol 2024;86:379-403. Widmeier E, Yu S, Nag A, Chung YW, Nakayama M, Fernández-Del-Río L, Hugo H, Schapiro D, Buerger F, Choi WI, et al. Adck4 deficiency destabilizes the coenzyme q complex, which is rescued by 2,4-dihydroxybenzoic acid treatment. J Am Soc Nephrol 2020;31:1191-1211. Widmeier E, Airik M, Hugo H, Schapiro D, Wedel J, Ghosh CC, Nakayama M, Schneider R, Awad AM, Nag A, et al. Treatment with 2,4-dihydroxybenzoic acid prevents fsgs progression and renal fibrosis in podocyte-specific coq6 knockout mice. J Am Soc Nephrol 2019;30:393-405. Cite Share Download PDF Status: Published Journal Publication published 14 Jan, 2025 Read the published version in Pediatric Nephrology → Version 1 posted Editorial decision: Major Revisions Needed 06 Sep, 2024 Reviewers agreed at journal 07 Aug, 2024 Reviewers invited by journal 06 Aug, 2024 Editor assigned by journal 06 Aug, 2024 First submitted to journal 06 Aug, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4868504","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":336853927,"identity":"f8439548-b73c-45b3-809c-2569f2b5bd31","order_by":0,"name":"Peong Gang Park","email":"","orcid":"","institution":"Ajou University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Peong","middleName":"Gang","lastName":"Park","suffix":""},{"id":336853928,"identity":"e3dd4775-03f7-453f-ae5c-72f6a3740a75","order_by":1,"name":"Sowon Choi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA40lEQVRIiWNgGAWjYFCCAwzMjH9s5OzbG4AcAwuitDA2MzakGRvwHABpkSDKGpCWw4kbJBJAHCK0GBw8Y/64cAdz4nbJ51c3/CiQYOBv707Ar+XAGcPmmWfYjHfOzim72QN0mMSZsxvwajE7cHZjMw8bj2zD7Zy0GzxALQYSuURpkWBsuHkm7eYforXwthkobrjBfuw2UbbYHzj/cTbPmQRjyZ4cttsyBhI8BP0iOeNYwmeeiv9y/OzHn918A4xT/vZe/FoYJA7AWDwGYBK/chDgb4Cx2B8QVj0KRsEoGAUjEgAAbQ1Q5ES9kLwAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-9564-7119","institution":"Seoul National University Graduate School Department of Biomedical Science","correspondingAuthor":true,"prefix":"","firstName":"Sowon","middleName":"","lastName":"Choi","suffix":""},{"id":336853929,"identity":"7755b840-678b-4a16-8cec-a6a434a622f8","order_by":2,"name":"Yo Han Ahn","email":"","orcid":"","institution":"Seoul National University College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yo","middleName":"Han","lastName":"Ahn","suffix":""},{"id":336853930,"identity":"4f40ceca-82e3-40b1-a0c4-112ec0838b42","order_by":3,"name":"Seong Heon Kim","email":"","orcid":"","institution":"Seoul National University College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Seong","middleName":"Heon","lastName":"Kim","suffix":""},{"id":336853931,"identity":"0ec409ae-66f4-4216-a139-12831b329b7e","order_by":4,"name":"Chaeyoon Kim","email":"","orcid":"","institution":"Seoul National University Graduate School Department of Biomedical Science","correspondingAuthor":false,"prefix":"","firstName":"Chaeyoon","middleName":"","lastName":"Kim","suffix":""},{"id":336853932,"identity":"fc8ba002-29f2-4500-87f4-41cc0a805378","order_by":5,"name":"Hyun Je Kim","email":"","orcid":"https://orcid.org/0000-0003-4467-0949","institution":"Seoul National University Graduate School Department of Biomedical Science","correspondingAuthor":false,"prefix":"","firstName":"Hyun","middleName":"Je","lastName":"Kim","suffix":""},{"id":336853933,"identity":"16d1d66e-6c68-43e8-84ff-d2954671aea1","order_by":6,"name":"Hee Gyung Kang","email":"","orcid":"","institution":"Seoul National University College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Hee","middleName":"Gyung","lastName":"Kang","suffix":""}],"badges":[],"createdAt":"2024-08-06 12:33:46","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4868504/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4868504/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00467-024-06611-2","type":"published","date":"2025-01-14T15:57:31+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":64308590,"identity":"ad996b2f-2707-42f5-aafc-266c5df05759","added_by":"auto","created_at":"2024-09-11 13:07:28","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1291502,"visible":true,"origin":"","legend":"\u003cp\u003eHistological findings of the patient: a) light microscopy, b) electron microscopy, c) immunofluorescence staining\u003c/p\u003e","description":"","filename":"OnlineFigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4868504/v1/01529f5b1da24fefbe622f23.png"},{"id":64308593,"identity":"f2957e6c-7ec0-4b28-9c3f-42f779d02160","added_by":"auto","created_at":"2024-09-11 13:07:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":230331,"visible":true,"origin":"","legend":"\u003cp\u003ea) This panel illustrates the patient's clinical course. The pink line represents a gradual decline in estimated glomerular function, despite ongoing treatment. Concurrently, urine output (shown as a green histogram) diminished, accompanied by significant proteinuria (blue line). b) Genetic analysis with a segregation study identified a compound heterozygous mutation in the \u003cem\u003eCOQ2\u003c/em\u003egene. Abbreviations: eGFR, estimated glomerular filtration rate; P/Cr, urine protein/creatinine ratio; CyA, cyclosporin A; C.I., continuous infusion; CPM, cyclophosphamide; RTX, rituximab.\u003c/p\u003e","description":"","filename":"OnlineFigure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4868504/v1/5b5f098cb1a08ab0b03f4c82.png"},{"id":64308591,"identity":"2cb8e446-230d-4b33-b834-0ee00fff0e20","added_by":"auto","created_at":"2024-09-11 13:07:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":479515,"visible":true,"origin":"","legend":"\u003cp\u003ea) Displaying 11,522 cells (3,737 from the patient and 7,785 from the control) post quality control and dataset integration via Harmony. The UMAP projection identifies 18 cell clusters including proximal tubule (PT), thick ascending limb (TAL), distal convoluted tubule (DCT), collecting duct principal cells (CD-P), type A and B intercalated cells (IC-A, IC-B), glomerular (gEC) and peritubular endothelial cells (ptEC), arterial endothelial cells (Arterial EC), smooth muscle cells (SMC), pericytes (PERI), podocytes (PODO), macrophages (Mac), and lymphocytes (T and B cells). b) Cell type-specific expression of marker genes across manually annotated clusters, with dot size indicating the percentage of cells expressing each marker and color scale reflecting average gene expression levels. c) Cells exhibit unbiased distribution in relation to disease status after batch correction. d) The fractions of parenchymal and immune cells. e) The number of cell types between the control and the patient.\u003c/p\u003e","description":"","filename":"OnlineFigure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4868504/v1/6265f476c1aab1169329fe61.png"},{"id":64308592,"identity":"813781cb-3f45-43cd-b782-23d7669cc552","added_by":"auto","created_at":"2024-09-11 13:07:28","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":799632,"visible":true,"origin":"","legend":"\u003cp\u003ea) - e) Heatmap shows the fold changes between the patient and the control of selected genes: a) CoQ10 biosynthesis related genes. b) Mitochondrial genes. c) Oxidative phosphorylation related genes. d) glycolysis related genes. e) Podocyte development and fibrosis related genes. f) Pathway analysis in podocytes.\u003c/p\u003e","description":"","filename":"OnlineFigure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4868504/v1/02a909a1d8942b0bdf1133e7.png"},{"id":74284770,"identity":"f5e55c92-4fec-4d71-a10d-b25fdecdb545","added_by":"auto","created_at":"2025-01-20 16:12:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4630721,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4868504/v1/cc500405-a1e7-4b60-9aa6-4f0841086442.pdf"}],"financialInterests":"","formattedTitle":"Single-cell transcriptomic analysis reveals impaired mitochondrial gene expression in the podocytes of a child with primary coenzyme Q10 nephropathy.","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe association of primary coenzyme Q10 (CoQ10) deficiency with human diseases was first established in 1989, based on a clinical study conducted by Ogasahara and colleagues [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Subsequently, in 2006, the molecular etiology of CoQ10 deficiency was elucidated with the identification of a gene mutation impairing CoQ10 biosynthesis [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Recent years have seen an escalation in reported cases of primary CoQ10 deficiency, characterized by a diverse array of organ involvements, including steroid-resistant nephrotic syndrome (SRNS). From the latter half of 2010, the term \"CoQ10 nephropathy\" began to be used to refer to inherited kidney disease, especially glomerulopathy such as SRNS, caused by mutations in the genes related to the CoQ10 biosynthesis pathway. Previous research reported that CoQ10 nephropathy due to mutations in genes such as \u003cem\u003ePDSS2\u003c/em\u003e, \u003cem\u003eCOQ2\u003c/em\u003e, \u003cem\u003eCOQ6\u003c/em\u003e, and \u003cem\u003eCOQ8B\u003c/em\u003e, are identified in approximately 1\u0026ndash;2.7% of SRNS cases [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Our previous research, however, revealed a higher prevalence; among 291 Korean children diagnosed with SRNS or focal segmental glomerulosclerosis, we detected mutations in 127 patients, with 20 (6.9%) of these mutations being identified as CoQ10 nephropathy [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This finding suggests a greater frequency of these mutations than previously reported. An early diagnosis of primary CoQ10 nephropathy is essential because the condition is possibly treatable when CoQ10 supplementation is started at the early stage [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSingle-cell RNA sequencing (scRNA-seq) has emerged as a pivotal technique for dissecting gene expression at the level of individual cells, offering unparalleled insights into the intricate and varied cellular reactions within diverse biological settings [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Employing scRNA-seq, novel insights have been gained into the cell type-specific characteristics of various kidney diseases. A notable example includes chronic kidney disease (CKD), where significant changes in the gene expression of proximal tubule (PT) cells have been observed [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. However, prior research employing scRNA-seq has predominantly concentrated on prevalent and/or immunologically driven conditions, such as CKD and lupus nephritis, thereby highlighting the need for broader application of this technique across a wider spectrum of kidney disorders, such as inherited kidney diseases [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, we identified a novel compound heterozygous variant in the \u003cem\u003eCOQ2\u003c/em\u003e gene of a patient and explored variations of individual cell-level expression using single-cell transcriptomics. By comparing the single-cell transcriptomic data of kidney tissue from the patient against a reference database, we found that these mutations uniformly downregulated mitochondrial gene expression across various cell types. This was accompanied by an increase in glycolysis-related gene expression specifically in the podocytes. Pathway analysis revealed a downregulation of oxidative phosphorylation (OXPHOS) and an upregulation of synthesis pathways in the podocytes. These insights contribute to our understanding of the pathogenesis and potential therapeutic approaches for primary CoQ10 nephropathy.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eClinical manifestations, histological analysis and genetic analysis\u003c/h2\u003e \u003cp\u003eWe collected the patient's clinical information, which includes demographic information, symptoms, results of laboratory tests, and the medical history of the patient's family. The sample from the core needle biopsy was prepared for histological analysis under both light and electron microscopes. To conduct genetic analysis, we extracted genomic DNA from the blood samples of the patient and his parents, then performed whole-exome sequencing. We applied a targeted gene capture method to specifically examine 68 genes associated with conditions related to Mendelian nephrotic syndrome [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The pathogenicity of the detected \u003cem\u003eCOQ2\u003c/em\u003e mutations were assessed following the American College of Medical Genetics and Genomics' guidelines [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eTissue procurement, single-cell isolation and Gel bead in Emulsion generation\u003c/h2\u003e \u003cp\u003eFresh human kidney tissue was obtained from needle biopsy at the Seoul National University Children\u0026rsquo;s Hospital. The kidney tissue was transported on ice in media containing 10% FBS in RPMI1640 (SH30027.01; Thermo Fisher Scientific, Waltham, MA, USA), then washed in cold PBS (ML008-01; Welgene, Gyeongsangbuk-do, Republic of Korea). The tissue was chopped and dissociated with Liberase\u0026trade; TL (#05401020001; Roche, Mannheim, Germany, 0.25mg/mL in PBS) in a 37\u0026deg;C water bath for 30 minutes. The tissue was then mechanically dissociated using a wide-bore pipette tip. Afterwards, the cells isolated from the tissue were filtered through a strainer with a mesh size of 70\u0026micro;m (#93070; SPL Life Sciences, Gyeonggi-do, Republic of Korea), followed by centrifugation (500g, 5min, 4\u0026deg;C). Then, the cells were resuspended with 60\u0026micro;L of cold media for cell counting and then diluted to the proper cell concentration The cells were immediately loaded onto the 10X Chromium Controller.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eLibrary preparation and NGS sequencing\u003c/h2\u003e \u003cp\u003eLibraries were generated using the Chromium Single Cell 3\u0026prime; Library \u0026amp; Gel Bead Kit V3.1 and Chromium Single Cell 3\u0026prime; Chips according to the manufacturer\u0026rsquo;s instructions. In short, single-cell samples and reagents were loaded on a 10X Chromium controller for droplet generation, followed by reverse transcription in the droplets, cDNA amplification and fragmentation. Then, fragments were ligated with adapters and dual-indices to mitigate index-hopping. The 4150 TapeStation system (Agilent, Santa Clara, CA, USA) was used to evaluate the quality of the barcoded single-cell transcriptome libraries. After quality control, the libraries were sequenced with NovaSeq 6000.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eSingle-cell RNA-seq data analysis\u003c/h2\u003e \u003cp\u003eRaw sequencing reads were aligned to GRCh38 (human) using Cell Ranger v7.1.0. Low quality single cells with fewer than 200 detected genes or more than 3,000 detected genes were filtered out. Additionally, cells with mitochondrial genes constituting over 50% of all genes were also removed using Seurat package v5.0.1. Single cell data from the patient and five normal adults from a public database were integrated and batch-corrected using the HarmonyIntegration method within the Seurat package [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. We conducted graph-based clustering and adjusted resolution parameter to 0.4. Seurat was used to find cluster-specific genes and then each cluster was manually annotated referring to public kidney scRNA-seq data [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Differentially expressed genes (DEGs) were selected according to the following criteria: Upregulated DEGs, average log2 fold change\u0026thinsp;\u0026gt;\u0026thinsp;0.5 and adjusted p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Downregulated DEGs, average log2 fold change \u0026lt; -0.5 and adjusted p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Gene expression fold changes between disease group and control group were analyzed for gene sets related to CoQ10, mitochondrial function, OXPHOS and glycolysis across our clusters and then visualized with a heatmap. To conduct pathway enrichment analysis, gene sets associated with biological processes from the Gene Ontology in MSigDB were selected [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. For input, we used the log2-fold change values from Seurat DEG analysis. The most significantly enriched pathways were identified by GSEA analysis across specific cell clusters such as podocytes.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eClinical manifestation\u003c/h2\u003e\n \u003cp\u003eA 6-year-old Korean boy was transferred to our hospital due to persistent edema, having been previously healthy with normal growth and developmental milestones. 3 weeks before his transfer, he was noted to have foamy urine and edema. Initial laboratory findings at the previous hospital were indicative of nephrotic syndrome (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Despite receiving standard-dose glucocorticoids for 20 days, his proteinuria persisted, and kidney function declined. A kidney biopsy revealed glomerular mesangial hyperplasia, tubulointerstitial lesions, and both global and segmental sclerosis of the glomeruli with crescent formation. Immunofluorescence microscopy showed diffuse mesangial and peripheral deposits of IgM, C3, and C1q. Electron microscopy identified small mesangial and subendothelial electron-dense deposits with foot process effacement (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). These findings, coupled with the lack of response to steroid therapy, led to a diagnosis of membranoproliferative glomerulonephritis.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1. Baseline patient characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.286189683860233%\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameters\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.79700499168053%\"\u003e\n \u003cp\u003e\u003cstrong\u003eInitial presentation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958402662229616%\"\u003e\n \u003cp\u003e\u003cstrong\u003e4 weeks after steroid\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958402662229616%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference range\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.286189683860233%\"\u003e\n \u003cp\u003eTotal protein (g/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.79700499168053%\"\u003e\n \u003cp\u003e3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958402662229616%\"\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958402662229616%\"\u003e\n \u003cp\u003e6.0 \u0026ndash; 8.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.286189683860233%\"\u003e\n \u003cp\u003eAlbumin (g/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.79700499168053%\"\u003e\n \u003cp\u003e1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958402662229616%\"\u003e\n \u003cp\u003e1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958402662229616%\"\u003e\n \u003cp\u003e3.3 \u0026ndash; 5.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.286189683860233%\"\u003e\n \u003cp\u003eSerum creatinine (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.79700499168053%\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958402662229616%\"\u003e\n \u003cp\u003e1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958402662229616%\"\u003e\n \u003cp\u003e0.4 \u0026ndash; 0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.286189683860233%\"\u003e\n \u003cp\u003eeGFR (ml/min/1.73\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.79700499168053%\"\u003e\n \u003cp\u003e56.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958402662229616%\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958402662229616%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.286189683860233%\"\u003e\n \u003cp\u003eTotal cholesterol (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.79700499168053%\"\u003e\n \u003cp\u003e505\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958402662229616%\"\u003e\n \u003cp\u003e810\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958402662229616%\"\u003e\n \u003cp\u003e0 \u0026ndash; 240\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.286189683860233%\"\u003e\n \u003cp\u003eTriglyceride (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.79700499168053%\"\u003e\n \u003cp\u003e1060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958402662229616%\"\u003e\n \u003cp\u003e637\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958402662229616%\"\u003e\n \u003cp\u003e0 \u0026ndash; 200\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.286189683860233%\"\u003e\n \u003cp\u003eC3 (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.79700499168053%\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958402662229616%\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958402662229616%\"\u003e\n \u003cp\u003e80 \u0026ndash; 173\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.286189683860233%\"\u003e\n \u003cp\u003eC4 (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.79700499168053%\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958402662229616%\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958402662229616%\"\u003e\n \u003cp\u003e13 \u0026ndash; 46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.286189683860233%\"\u003e\n \u003cp\u003eIgG (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.79700499168053%\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958402662229616%\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958402662229616%\"\u003e\n \u003cp\u003e540 \u0026ndash; 1822\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.286189683860233%\"\u003e\n \u003cp\u003eUrine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.79700499168053%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958402662229616%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958402662229616%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.286189683860233%\"\u003e\n \u003cp\u003e\u0026nbsp; Protein\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.79700499168053%\"\u003e\n \u003cp\u003e4+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958402662229616%\"\u003e\n \u003cp\u003e4+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958402662229616%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.286189683860233%\"\u003e\n \u003cp\u003e\u0026nbsp; RBC (/HPF)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.79700499168053%\"\u003e\n \u003cp\u003e1 \u0026ndash; 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958402662229616%\"\u003e\n \u003cp\u003e1 \u0026ndash; 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958402662229616%\"\u003e\n \u003cp\u003e0 \u0026ndash; 4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.286189683860233%\"\u003e\n \u003cp\u003e\u0026nbsp; Protein/creatinine ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.79700499168053%\"\u003e\n \u003cp\u003e84.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958402662229616%\"\u003e\n \u003cp\u003e40.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958402662229616%\"\u003e\n \u003cp\u003e\u0026lt; 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eAbbreviation: eGFR, estimated glomerular filtration rate; RBC, red blood cell\u003c/p\u003e\n \u003cp\u003eDespite intensive immunosuppressive therapies targeting membranoproliferative glomerulonephritis, the patient\u0026apos;s kidney function continued to deteriorate (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea). Targeted exome sequencing for SRNS belatedly revealed compound heterozygous likely pathogenic variants of \u003cem\u003eCOQ2\u003c/em\u003e, c.518G\u0026thinsp;\u0026gt;\u0026thinsp;A (p.Arg173His) from father and c.973A\u0026thinsp;\u0026gt;\u0026thinsp;G (p.Thr325Ala) from mother [\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e] (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eb), therefore immunosuppressive therapy was discontinued and high-dose CoQ10 supplementation was initiated. Maintenance kidney replacement therapy was initiated 2 months after disease onset; tragically, 6 weeks after the initiation of dialysis, the patient demised along with cardiopulmonary failure following fever of unknown cause.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eSingle-cell transcriptome analysis\u003c/h3\u003e\n\u003cp\u003eTo investigate the altered gene expression and pathways in this patient at a single-cell level, we obtained a kidney biopsy sample and generated transcriptome datasets from 3,737 cells after excluding low-quality cells. The patient\u0026rsquo;s single-cell transcriptomics data were integrated with transcriptomics data from five young adults (aged 20 to 40 years) with normal kidney function, sourced from the public Kidney Precision Medicine Project database [\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e]. Following batch correction and integration with the public dataset, we performed unsupervised clustering, resulting in 15 distinct cell types (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ea). Each cluster was annotated using canonical cell type\u0026ndash;specific marker genes for kidney epithelial, endothelial, and immune cells (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eb\u003cstrong\u003e)\u003c/strong\u003e. The general cellular composition was similar between the patient and the control group (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ec\u003cstrong\u003e)\u003c/strong\u003e. However, the proportion of immune cells was higher in the patient, while the control group exhibited a greater proportion of parenchymal cells, particularly endothelial cells (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ed \u003cstrong\u003eand\u003c/strong\u003e Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ee). The elevated immune cell count in the patient might contribute to the development of a membranoproliferative pattern of glomerulonephritis [\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eGiven the genetic confirmation of a \u003cem\u003eCOQ2\u003c/em\u003e mutation in this patient, we analyzed the expression of CoQ10-related genes, including \u003cem\u003eCOQ2\u003c/em\u003e. As depicted in Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ea, \u003cem\u003eCOQ2\u003c/em\u003e mRNA expression was detectable in the patient, suggesting that the mutation leads to a functional defect rather than an alteration in expression level. However, we observed a notable upregulation of \u003cem\u003eCOQ6\u003c/em\u003e and \u003cem\u003eCOQ10A\u003c/em\u003e, and downregulation of \u003cem\u003eCOQ4\u003c/em\u003e and \u003cem\u003eCOQ9\u003c/em\u003e, particularly in podocytes. This suggests a varied impact on CoQ10 biosynthesis, especially in podocytes.\u003c/p\u003e\n\u003cp\u003eFurther, we examined changes in the expression levels of mitochondrial genes and found a uniform downregulation across all cell types, indicating a severe impairment in mitochondrial function (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eb\u003cstrong\u003e)\u003c/strong\u003e. We also assessed changes in genes related to OXPHOS, a key mitochondrial function. While genes associated with Complexes I, II, III, and IV were downregulated, those related to Complex V (ATP synthase) were upregulated in various cell types (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ec\u003cstrong\u003e)\u003c/strong\u003e. Interestingly, there was a specific upregulation of glycolysis-related genes in podocytes (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ed\u003cstrong\u003e)\u003c/strong\u003e. Notably, genes linked to podocyte development were uniquely downregulated in the patient\u0026rsquo;s podocytes, suggesting impaired podocyte function or their dedifferentiation (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ee\u003cstrong\u003e)\u003c/strong\u003e. Lastly, pathway analysis using hallmark gene sets revealed a downregulation of OXPHOS and an upregulation of fibrous tissue synthesis pathways (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ef\u003cstrong\u003e)\u003c/strong\u003e.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eSingle cell methodologies have facilitated the observation of gene expression alterations in thousands of distinct cells within a single experiment. In acute kidney injury, scRNA-seq has led to the discovery of a new cell type derived from proximal tubules and increase in interferon response and the expression of chemokine receptors in various cell clusters were demonstrated in lupus nephritis\u0026nbsp;[9,16]. However, there have been few attempts to examine gene expression through scRNA-seq in human genetic kidney diseases, and to the best of our knowledge, this study is the first to present such results. Generally, tissue biopsies are not performed in pediatric nephrotic syndrome, making it difficult to obtain human tissue samples. However, in this case, a biopsy was conducted to clarify SRNS, allowing the use of a portion of the tissue for this examination\u0026nbsp;[17]. Consequently, we were able to present a single cell transcriptome analysis for CoQ10 nephropathy, offering an unparalleled level of cellular detail and transcriptional insight.\u003c/p\u003e\n\u003cp\u003eOne of the major findings of this study is that while there was no significant downregulation in gene expression related to CoQ10 biosynthesis in major clusters, there was a severe reduction in the expression of mitochondrial genes in every cell cluster. It is likely that the mutation observed in this patient impaired the function, rather than the expression level, of the CoQ10 biosynthesis pathway. This functional impairment is thought to have affected mitochondrial gene expression. CoQ10 plays a pivotal role in OXPHOS, a critical process for energy generation within cells. Deficiencies in the enzymes responsible for CoQ10 synthesis can lead to a marked decrease in intracellular energy production. This deficit predominantly affects tissues with high demands for mitochondrial energy, such as the brain, kidney tubules, and podocytes, where pathological changes are likely to occur as a result of impaired energy metabolism\u0026nbsp;[18]. In many cases of mitochondriopathies, which arise from multiple mitochondrial gene defects, severe developmental delays are often observed due to brain involvement\u0026nbsp;[19]. However, the patient with \u003cem\u003eCOQ2\u003c/em\u003e nephropathy presented in this study exhibited normal development. Furthermore, while a significant number of diseases result in severe tubulopathy, this patient demonstrated normal tubular function. These findings suggest a distinctive pathophysiological mechanism in \u003cem\u003eCOQ2\u003c/em\u003e nephropathy that spares certain functions impaired in other mitochondrial disorders. Brain tissue, proximal tubules, and podocytes are all energy-intensive tissues\u0026nbsp;[20]. However, further research is required to elucidate how specific gene mutations selectively impact these tissues. This necessitates a deeper understanding of the differential vulnerability and pathophysiological mechanisms in these high energy-demand tissues. Specifically, the gene expression related with Complexes I-IV, which generate the electron gradient, was predominantly diminished, while there was an upregulation in the expression of Complex V. This observation implies a possible compensatory effect and differs from the results observed in the \u003cem\u003eAdck4-\u003c/em\u003e knockout mouse, where protein expression appeared to be insignificantly altered in the knockout specimen\u0026nbsp;[21]. Notably, in podocytes, there was an increased expression of genes related to glycolysis, which is also thought to be a compensatory response to the impaired energy production.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePrevious research on the pathophysiology of CoQ10 nephropathy is limited. Widmeier and his colleagues utilized podocyte-specific, \u003cem\u003eAdck4\u003c/em\u003e- and \u003cem\u003ecoq6\u003c/em\u003e- knockout mouse model\u0026nbsp;to clarify educed respiratory chain activity and mitochondrial potential in CoQ10 nephropathy model\u0026nbsp;[21,22]. This study delves deeper into the pathophysiology of this genetic disorder by demonstrating defects in mitochondrial function using human tissue. Furthermore, it highlighted the potential for employing scRNA-seq in the study of other inherited kidney diseases.\u003c/p\u003e\n\u003cp\u003eA key strength of this study lies in its methodology of preparing tissue samples. Instead of using frozen or thawed preparations, an 'on-call' preparation method was employed. This approach enabled the creation of a cDNA library within six hours of tissue acquisition from the human body, thereby minimizing gene alterations that could potentially arise from storage processes. However, this study has certain limitations. First, the kidney biopsy was performed after four weeks of steroid treatment, which could have altered the gene expression profile from that at the onset of the disease. Second, the control group for comparison ideally should have comprised age-matched pediatric kidneys. However, since it was based on normal adults aged 20-40, there could have been differences in gene expression related to age.\u003c/p\u003e\n\u003cp\u003eIn conclusion, this study provides a complementary investigation of the clinical and molecular response of the kidney in CoQ10 nephropathy. Transcriptomic evidence identifies the loss of mitochondrial function in various cell types and defective functions of podocytes. In future research, the application of scRNA-seq together with spatial transcriptomics in hereditary kidney diseases such as Alport syndrome and autosomal dominant polycystic kidney disease, which pose significant disease burdens, is anticipated to substantially broaden our understanding of their pathophysiology.\u003cbr\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"Statements and declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e: This research was funded by the Seoul National University Convergence Research Support Program (Project No. 800-20220547).\u003cbr\u003e\u0026nbsp;\u003cstrong\u003eCompeting interests\u003c/strong\u003e: All authors declare that they do not have conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e: The Seoul National University Hospital's institutional review board approved the study (IRB No. H-2204-014-1312)\u003cbr\u003e\u0026nbsp;\u003cstrong\u003eConsent to participate and publication\u003c/strong\u003e: Written consent was provided by the guardian of the study subject.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e: The dataset for single-cell RNA transcriptomics has been deposited in the Gene Expression Omnibus database (accession number: GSE270701). This study does not report any original code, and the codes used are available in the Method section. Any additional information required to reanalyze the data is available from the lead contact upon request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eOgasahara S, Engel AG, Frens D, Mack D. Muscle coenzyme q deficiency in familial mitochondrial encephalomyopathy. \u003cem\u003eProc Natl Acad Sci U S A\u003c/em\u003e 1989;86:2379-2382.\u003c/li\u003e\n \u003cli\u003eQuinzii C, Naini A, Salviati L, Trevisson E, Navas P, Dimauro S, Hirano M. A mutation in para-hydroxybenzoate-polyprenyl transferase (\u003cem\u003eCOQ2\u003c/em\u003e) causes primary coenzyme q10 deficiency. \u003cem\u003eAm J Hum Genet\u003c/em\u003e 2006;78:345-349.\u003c/li\u003e\n \u003cli\u003eSadowski CE, Lovric S, Ashraf S, Pabst WL, Gee HY, Kohl S, Engelmann S, Vega-Warner V, Fang H, Halbritter J, et al. A single-gene cause in 29.5% of cases of steroid-resistant nephrotic syndrome. \u003cem\u003eJ Am Soc Nephrol\u003c/em\u003e 2015;26:1279-1289.\u003c/li\u003e\n \u003cli\u003ePark E, Lee C, Kim NKD, Ahn YH, Park YS, Lee JH, Kim SH, Cho MH, Cho H, Yoo KH, et al. Genetic study in korean pediatric patients with steroid-resistant nephrotic syndrome or focal segmental glomerulosclerosis. \u003cem\u003eJ Clin Med\u003c/em\u003e 2020;9.\u003c/li\u003e\n \u003cli\u003eKim SY. Navigating the landscape of clinical genetic testing: Insights and challenges in rare disease diagnostics. \u003cem\u003eChild Kidney Dis\u003c/em\u003e 2024;28:8-15.\u003c/li\u003e\n \u003cli\u003eMontini G, Malaventura C, Salviati L. Early coenzyme q10 supplementation in primary coenzyme q10 deficiency. \u003cem\u003eN Engl J Med\u003c/em\u003e 2008;358:2849-2850.\u003c/li\u003e\n \u003cli\u003eBalzer MS, Ma Z, Zhou J, Abedini A, Susztak K. How to get started with single cell rna sequencing data analysis. \u003cem\u003eJ Am Soc Nephrol\u003c/em\u003e 2021;32:1279-1292.\u003c/li\u003e\n \u003cli\u003eQiu C, Huang S, Park J, Park Y, Ko YA, Seasock MJ, Bryer JS, Xu XX, Song WC, Palmer M, et al. Renal compartment-specific genetic variation analyses identify new pathways in chronic kidney disease. \u003cem\u003eNat Med\u003c/em\u003e 2018;24:1721-1731.\u003c/li\u003e\n \u003cli\u003eArazi A, Rao DA, Berthier CC, Davidson A, Liu Y, Hoover PJ, Chicoine A, Eisenhaure TM, Jonsson AH, Li S, et al. The immune cell landscape in kidneys of patients with lupus nephritis. \u003cem\u003eNat Immunol\u003c/em\u003e 2019;20:902-914.\u003c/li\u003e\n \u003cli\u003eLee H, Min J, Ahn YH, Kang HG. Genetic analysis using whole-exome sequencing in pediatric chronic kidney disease: A single center\u0026apos;s experience. \u003cem\u003eChild Kidney Dis\u003c/em\u003e 2022;26:40-45.\u003c/li\u003e\n \u003cli\u003eRichards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, Grody WW, Hegde M, Lyon E, Spector E, et al. Standards and guidelines for the interpretation of sequence variants: A joint consensus recommendation of the american college of medical genetics and genomics and the association for molecular pathology. \u003cem\u003eGenet Med\u003c/em\u003e 2015;17:405-424.\u003c/li\u003e\n \u003cli\u003eHansen J, Sealfon R, Menon R, Eadon MT, Lake BB, Steck B, Anjani K, Parikh S, Sigdel TK, Zhang G, et al. A reference tissue atlas for the human kidney. \u003cem\u003eSci Adv\u003c/em\u003e 2022;8:eabn4965.\u003c/li\u003e\n \u003cli\u003eBalzer MS, Rohacs T, Susztak K. How many cell types are in the kidney and what do they do? \u003cem\u003eAnnu Rev Physiol\u003c/em\u003e 2022;84:507-531.\u003c/li\u003e\n \u003cli\u003eLiberzon A, Subramanian A, Pinchback R, Thorvaldsd\u0026oacute;ttir H, Tamayo P, Mesirov JP. Molecular signatures database (msigdb) 3.0. \u003cem\u003eBioinformatics\u003c/em\u003e 2011;27:1739-1740.\u003c/li\u003e\n \u003cli\u003eKim JY. Comprehensive review of membranoproliferative glomerulonephritis: Spotlighting the latest advances in revised classification and treatment. \u003cem\u003eChild Kidney Dis\u003c/em\u003e 2023;27:64-69.\u003c/li\u003e\n \u003cli\u003eHinze C, Kocks C, Leiz J, Karaiskos N, Boltengagen A, Cao S, Skopnik CM, Klocke J, Hardenberg JH, Stockmann H, et al. Single-cell transcriptomics reveals common epithelial response patterns in human acute kidney injury. \u003cem\u003eGenome Med\u003c/em\u003e 2022;14:103.\u003c/li\u003e\n \u003cli\u003eLim SH. Introducing the general management of glomerular disease from a pediatric perspective based on the updated kdigo guidelines. \u003cem\u003eChild Kidney Dis\u003c/em\u003e 2023;27:55-63.\u003c/li\u003e\n \u003cli\u003eImasawa T, Obre E, Bellance N, Lavie J, Imasawa T, Rigothier C, Delmas Y, Combe C, Lacombe D, Benard G, et al. High glucose repatterns human podocyte energy metabolism during differentiation and diabetic nephropathy. \u003cem\u003eFaseb j\u003c/em\u003e 2017;31:294-307.\u003c/li\u003e\n \u003cli\u003eClemente-Su\u0026aacute;rez VJ, Redondo-Fl\u0026oacute;rez L, Beltr\u0026aacute;n-Velasco AI, Ramos-Campo DJ, Belinch\u0026oacute;n-deMiguel P, Martinez-Guardado I, Dalamitros AA, Y\u0026aacute;\u0026ntilde;ez-Sep\u0026uacute;lveda R, Mart\u0026iacute;n-Rodr\u0026iacute;guez A, Tornero-Aguilera JF. Mitochondria and brain disease: A comprehensive review of pathological mechanisms and therapeutic opportunities. \u003cem\u003eBiomedicines\u003c/em\u003e 2023;11.\u003c/li\u003e\n \u003cli\u003eHoogstraten CA, Hoenderop JG, de Baaij JHF. Mitochondrial dysfunction in kidney tubulopathies. \u003cem\u003eAnnu Rev Physiol\u003c/em\u003e 2024;86:379-403.\u003c/li\u003e\n \u003cli\u003eWidmeier E, Yu S, Nag A, Chung YW, Nakayama M, Fern\u0026aacute;ndez-Del-R\u0026iacute;o L, Hugo H, Schapiro D, Buerger F, Choi WI, et al. Adck4 deficiency destabilizes the coenzyme q complex, which is rescued by 2,4-dihydroxybenzoic acid treatment. \u003cem\u003eJ Am Soc Nephrol\u003c/em\u003e 2020;31:1191-1211.\u003c/li\u003e\n \u003cli\u003eWidmeier E, Airik M, Hugo H, Schapiro D, Wedel J, Ghosh CC, Nakayama M, Schneider R, Awad AM, Nag A, et al. Treatment with 2,4-dihydroxybenzoic acid prevents fsgs progression and renal fibrosis in podocyte-specific coq6 knockout mice. \u003cem\u003eJ Am Soc Nephrol\u003c/em\u003e 2019;30:393-405.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"pediatric-nephrology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pnep","sideBox":"Learn more about [Pediatric Nephrology](http://link.springer.com/journal/467)","snPcode":"467","submissionUrl":"https://www.editorialmanager.com/pnep/default2.aspx","title":"Pediatric Nephrology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Coenzyme Q 10 nephropathy, COQ2 mutation, hereditary nephropathy, single cell transcriptomics, single cell RNA sequencing","lastPublishedDoi":"10.21203/rs.3.rs-4868504/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4868504/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCoenzyme Q10 (CoQ10) nephropathy is a well-known cause of hereditary steroid-resistant nephrotic syndrome, primarily impacting podocytes. This study aimed to elucidate variations in individual cell-level gene expression in CoQ10 nephropathy using single-cell transcriptomics.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe conducted single-cell sequencing of a kidney biopsy specimen from a 5-year-old boy diagnosed with a CoQ10 nephropathy caused by a compound heterozygous \u003cem\u003eCOQ2\u003c/em\u003e mutation. The analysis focused on the proportion of cell types, differentially expressed genes in each cell type, changes in gene expression related to mitochondrial function and oxidative phosphorylation (OXPHOS).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur findings revealed a uniform downregulation of mitochondrial gene expression across various cell types in the context of these mutations. Notably, there was a specific decrease in mitochondrial gene expression across all cell types. The study also highlighted an altered immune cell population proportion attributed to the \u003cem\u003eCOQ2\u003c/em\u003e gene mutation. Pathway analysis indicated a downregulation in OXPHOS and an upregulation of various synthesis pathways, particularly in podocytes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study improves our understanding of CoQ10 nephropathy's pathogenesis and highlights the potential applications of single-cell sequencing in hereditary kidney diseases.\u003c/p\u003e","manuscriptTitle":"Single-cell transcriptomic analysis reveals impaired mitochondrial gene expression in the podocytes of a child with primary coenzyme Q10 nephropathy.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-11 13:07:23","doi":"10.21203/rs.3.rs-4868504/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major Revisions Needed","date":"2024-09-06T11:48:49+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2024-08-07T07:46:09+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-06T18:57:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-06T17:04:07+00:00","index":"","fulltext":""},{"type":"submitted","content":"Pediatric Nephrology","date":"2024-08-06T08:32:55+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"pediatric-nephrology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pnep","sideBox":"Learn more about [Pediatric Nephrology](http://link.springer.com/journal/467)","snPcode":"467","submissionUrl":"https://www.editorialmanager.com/pnep/default2.aspx","title":"Pediatric Nephrology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"f55edabf-57ab-4c29-8497-e2ba7b7e7c5d","owner":[],"postedDate":"September 11th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-01-20T16:06:11+00:00","versionOfRecord":{"articleIdentity":"rs-4868504","link":"https://doi.org/10.1007/s00467-024-06611-2","journal":{"identity":"pediatric-nephrology","isVorOnly":false,"title":"Pediatric Nephrology"},"publishedOn":"2025-01-14 15:57:31","publishedOnDateReadable":"January 14th, 2025"},"versionCreatedAt":"2024-09-11 13:07:23","video":"","vorDoi":"10.1007/s00467-024-06611-2","vorDoiUrl":"https://doi.org/10.1007/s00467-024-06611-2","workflowStages":[]},"version":"v1","identity":"rs-4868504","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4868504","identity":"rs-4868504","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}