Abstract
Kosukcu, C. Bioinformatics Analysis and Variant Interpratation of Whole Exome Sequencing Data in Inborn Errors of Metabolism. Hacettepe University Graduate School of Health Sciences, Ph.D. Thesis in Molecular Metabolism, Ankara 2024. Inborn errors of metabolism are pathophysiologically examined in three groups, as intoxication type (amino acid metabolism disorders, galactosemia, etc.), energy metabolism disorders (mitochondrial diseases) and macromolecular diseases (organelle dysfunctions). In intoxication type metabolic diseases, there is a toxic effect that develops with the accumulation of the substrate located proximal to the enzyme reaction due to enzyme deficiency, while energy metabolism disorders develop as a result of enzyme deficiencies involved in the synthesis of the ATP molecule (PDH deficiency, Krebs cycle enzyme deficiencies and respiratory chain dysfunction, etc.). Complex molecule diseases generally develop as a result of enzyme deficiencies involved in the lysosome, peroxisome, endoplasmic reticulum-Golgi apparatus mechanism outside the mitochondria. Lysosomal storage diseases, peroxisomal diseases and hereditary glycation disorders are classic examples of this group of diseases. However, as a result of the studies carried out by research groups in which we are a part, new disease groups such as vesicular traffic disorders and autophagy dysfunctions have begun to be defined. As a clinical phenotype, hereditary metabolic diseases manifest themselves with single or multiple organ/system involvement, depending on the disease type. The central nervous system is one of the systems most frequently involved in metabolic diseases (>55%). Therefore, early diagnosis and treatment of hereditary metabolic diseases is very important to prevent mortality and morbidity in these diseases. In recent years, the use of advanced genetic analysis methods has become the main approach in the diagnosis of rare or very rare metabolic diseases that cannot be diagnosed by traditional methods. In particular, the whole exome sequence analysis method, which allows the analysis of all coding gene regions, has become the most important tool in the identification of new disease genes or in the molecular diagnosis of metabolic/neurometabolic diseases that show genetic heterogeneity. Exome analyzes have also accelerated the discovery of new candidate genes. If the genes detected by exome analyzes are not associated with any clinical phenotype, new candidate genes emerge. This process, whether through whole genome or whole exome analysis, has placed a huge pile of information that needs to be interpreted in front of researchers and increasingly clinicians in medical practice. The process of finding a single candidate gene responsible for a disease from this mass of information has created the field of bioinformatics, which is already the most fundamental field of study in medical practice. Asking the most appropriate questions to the huge pile of information in the context of the phenotype and evaluating the answers in the most appropriate way constitute the basic process of bioinformatics. Therefore, it is essential that bioinformatic analysis be accompanied by in-depth clinically relevant phenotype information. In addition, prediction of pathogenicity, copy number analysis, protein modeling, pathway analysis, etc. In-silico analysis methods such as these guide the researcher performing bioinformatics analysis in the process of identifying a single candidate gene responsible for the disease. Bioinformatics analysis is the most critical step in the processing of raw data, identifying candidate genes, detecting and filtering genetic variations, and detecting pathogenic mutations. With advanced bioinformatics analysis of the data, different mutation types (missense, nonsense, truncation, small INDELs) can be detected, while large copy number changes can also be determined. In this doctoral thesis, multiple software tools were utilized for the bioinformatic analysis of Whole Exome Sequencing (WES) data. BWA (Burrows-Wheeler Aligner) was used for aligning FASTQ data, SAMtools for filtering repetitive sequences, BEDtools for calculating the read depth of exonic regions, and GATK for the variant calling steps. CLC Genomics Server 24.0.1 was employed for reanalysis of raw data and detection of copy number variations (CNVs). FoldX software was used for repairing PDB structures prior to modeling missense mutations using PDB files. In the in-silico protein modeling, four different software tools (DynaMut2, PremPS, INPS-3D, and FoldX) were used to calculate ΔΔG values. Pathway analyses reflecting the interactions between the identified genes and newly discovered genes that have not been reported in the literature were conducted using the STRING 12.0 software. In this study, raw data analyses of Whole Exome Sequencing from 213 individuals across 162 families were performed using bioinformatic methods and the results were interpreted. A definitive diagnosis was made for 155 cases, and the total number of identified variants was calculated as 170. Among the cases with a definitive diagnosis, 103 had missense mutations (61%), 18 had frameshift mutations (10%), 17 had nonsense mutations (10%), 17 had splice site mutations (10%), 6 had copy number variations (4%), 5 had start codon mutations (3%), and 4 had in-frame deletions or insertions (2%). The 103 identified missense mutations were modeled on the protein structure using four different methods, and in-silico predictions were conducted to illustrate the structural changes induced by the mutations on the protein structure. The identified variants were subjected to pathway analysis at the gene level to detect relationships among the molecular pathways involved in rare inherited metabolic diseases and to explore the positioning of newly identified genes within these pathways. In this thesis study, WES analysis was performed on 213 individuals from a total of 162 families, resulting in molecular diagnosis for 155 patients, while 58 cases remained undiagnosed. Accordingly, the success rate of molecular diagnosis in the bioinformatic analyses was calculated as 73%. Although, the laboratory methods and sequencing techniques used to obtain Whole Exome Sequencing data are highly developed, accurate and comprehensive bioinformatics analyzes are extremely important in clinical interpretation.
Keywords: Inborn errors of metabolism, Next Generation Sequencing, Whole Exome Sequencing, bioinformatics, protein modelling, Copy Number Variation, deep phenotyping
xmlui.mirage2.itemSummaryView.Collections
xmlui.dri2xhtml.METS-1.0.item-citation
1. Aoki E, Manabe N, Ohno S, et al. Predicting the pathogenicity of missense variants based on protein instability to support diagnosis of patients with novel variants of ARSL. Mol Genet Metab Rep. 2023;37:101016. Published 2023 Oct 29. doi:10.1016/j.ymgmr.2023.101016
2. Hieter P, Andrews B, Fowler D, Bellen H. Highlighting rare disease research with a GENETICS and G3 series on genetic models of rare diseases. Genetics. 2023;224(4):iyad121. doi:10.1093/genetics/iyad121
3. Chung BHY, Chau JFT, Wong GK. Rare versus common diseases: a false dichotomy in precision medicine. NPJ Genom Med. 2021;6(1):19. Published 2021 Feb 24. doi:10.1038/s41525-021-00176-x
4. Lu S, Zhang J, Lian X, et al. A hidden human proteome encoded by 'non-coding' genes. Nucleic Acids Res. 2019;47(15):8111-8125. doi:10.1093/nar/gkz646
5. Bamshad MJ, Nickerson DA, Chong JX. Mendelian Gene Discovery: Fast and Furious with No End in Sight. Am J Hum Genet. 2019;105(3):448-455. doi:10.1016/j.ajhg.2019.07.011
6. Saudubray JM, Mochel F, Lamari F, Garcia-Cazorla A. Proposal for a simplified classification of IMD based on a pathophysiological approach: A practical guide for clinicians. J Inherit Metab Dis. 2019;42(4):706-727. doi:10.1002/jimd.12086
7. Yeo, M., Moawad, H., & Grunewald, S. (2023). Disorders of carbohydrate metabolism: a review of glycogen storage disorders. Paediatrics and Child Health, 33(3), 65-72.
8. Marwaha S, Knowles JW, Ashley EA. A guide for the diagnosis of rare and undiagnosed disease: beyond the exome. Genome Med. 2022;14(1):23. Published 2022 Feb 28. doi:10.1186/s13073-022-01026-w
9. Karczewski KJ, Francioli LC, Tiao G, et al. The mutational constraint spectrum quantified from variation in 141,456 humans [published correction appears in Nature. 2021 Feb;590(7846):E53.
10. Besser J, Carleton HA, Gerner-Smidt P, Lindsey RL, Trees E. Next-generation sequencing technologies and their application to the study and control of bacterial infections. Clin Microbiol Infect. 2018;24(4):335-341. doi:10.1016/j.cmi.2017.10.013
11. Blöß S, Klemann C, Rother AK, et al. Diagnostic needs for rare diseases and shared prediagnostic phenomena: Results of a German-wide expert Delphi survey. PLoS One. 2017;12(2):e0172532. Published 2017 Feb 24. doi:10.1371/journal.pone.0172532
12. Benito-Lozano J, Arias-Merino G, Gómez-Martínez M, et al. Diagnostic Process in Rare Diseases: Determinants Associated with Diagnostic Delay. Int J Environ Res Public Health. 2022;19(11):6456. Published 2022 May 26. doi:10.3390/ijerph19116456
13. Li H, Handsaker B, Wysoker A, et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics. 2009;25(16):2078-2079. doi:10.1093/bioinformatics/btp352
14. Quinlan AR. BEDTools: The Swiss-Army Tool for Genome Feature Analysis. Curr Protoc Bioinformatics. 2014;47:11.12.1-11.12.34. Published 2014 Sep 8. doi:10.1002/0471250953.bi1112s47
15. Funahashi J, Sugita Y, Kitao A, Yutani K. How can free energy component analysis explain the difference in protein stability caused by amino acid substitutions? Effect of three hydrophobic mutations at the 56th residue on the stability of human lysozyme. Protein Eng. 2003;16(9):665-671. doi:10.1093/protein/gzg083
16. Marinella G, Pascarella F, Vetro A, et al. Hyperlysinemia, an ultrarare inborn error of metabolism: Review and update. Seizure. 2024;120:135-141. doi:10.1016/j.seizure.2024.06.020
17. Schiff M, Haberberger B, Xia C, et al. Complex I assembly function and fatty acid oxidation enzyme activity of ACAD9 both contribute to disease severity in ACAD9 deficiency. Hum Mol Genet. 2015;24(11):3238-3247. doi:10.1093/hmg/ddv074
18. Madeira CA, Anselmo C, Costa JM, et al. Functional and structural impact of 10 ACADM missense mutations on human medium chain acyl-Coa dehydrogenase. Biochim Biophys Acta Mol Basis Dis. 2023;1869(7):166766. doi:10.1016/j.bbadis.2023.166766
19. Doyle TB, Hayes MP, Chen DH, Raskind WH, Watts VJ. Functional characterization of AC5 gain-of-function variants: Impact on the molecular basis of ADCY5-related dyskinesia. Biochem Pharmacol. 2019;163:169-177. doi:10.1016/j.bcp.2019.02.005
20. Bai Y, Morita K, Kokaji T, et al. Trans-omic analysis reveals opposite metabolic dysregulation between feeding and fasting in liver associated with obesity. iScience. 2024;27(3):109121. Published 2024 Feb 26. doi:10.1016/j.isci.2024.109121
21. Tang HL, Chen SY, Zhang H, et al. Expression Pattern of ALOXE3 in Mouse Brain Suggests Its Relationship with Seizure Susceptibility. Cell Mol Neurobiol. 2022;42(3):777-790. doi:10.1007/s10571-020-00974-4
22. Ling ZN, Jiang YF, Ru JN, Lu JH, Ding B, Wu J. Amino acid metabolism in health and disease. Signal Transduct Target Ther. 2023;8(1):345. Published 2023 Sep 13. doi:10.1038/s41392-023-01569-3
23. Shin J, Nile A, Oh JW. Role of adaptin protein complexes in intracellular trafficking and their impact on diseases. Bioengineered. 2021;12(1):8259-8278. doi:10.1080/21655979.2021.1982846
24. García-Cazorla A, Oyarzábal A, Saudubray JM, Martinelli D, Dionisi-Vici C. Genetic disorders of cellular trafficking. Trends Genet. 2022;38(7):724-751. doi:10.1016/j.tig.2022.02.012
25. Caryn S & Annette H, Tracie S, Ira T, Stephen S. (2010). The Role of Arv1 in Sterol Metabolism and its Contribution to the Unfolded Protein Response. The FASEB Journal. 24. 10.1096/fasebj.24.1_supplement.845.4.
26. Tadini-Buoninsegni F, Mikkelsen SA, Mogensen LS, Holm R, Molday RS, Andersen JP. Electrogenic reaction step and phospholipid translocation pathway of the mammalian P4-ATPase ATP8A2. FEBS Lett. 2023;597(4):495-503. doi:10.1002/1873-3468.14459
27. Maiuolo J, Oppedisano F, Gratteri S, Muscoli C, Mollace V. Regulation of uric acid metabolism and excretion [published correction appears in Int J Cardiol. 2023 Sep 15;387:131126. doi: 10.1016/j.ijcard.2023.131126]. Int J Cardiol. 2016;213:8-14. doi:10.1016/j.ijcard.2015.08.109
28. Li G, Li X, Mahmud I, et al. Interfering with lipid metabolism through targeting CES1 sensitizes hepatocellular carcinoma for chemotherapy. JCI Insight. 2023;8(2):e163624. Published 2023 Jan 24. doi:10.1172/jci.insight.163624
29. Purandare N, Somayajulu M, Hüttemann M, Grossman LI, Aras S. The cellular stress proteins CHCHD10 and MNRR1 (CHCHD2): Partners in mitochondrial and nuclear function and dysfunction. J Biol Chem. 2018;293(17):6517-6529. doi:10.1074/jbc.RA117.001073
30. di Ronza A, Bajaj L, Sharma J, et al. CLN8 is an endoplasmic reticulum cargo receptor that regulates lysosome biogenesis. Nat Cell Biol. 2018;20(12):1370-1377. doi:10.1038/s41556-018-0228-7
31. Formosa LE, Maghool S, Sharpe AJ, et al. Mitochondrial COA7 is a heme-binding protein with disulfide reductase activity, which acts in the early stages of complex IV assembly. Proc Natl Acad Sci U S A. 2022;119(9):e2110357119. doi:10.1073/pnas.2110357119
32. Pelosi L, Morbiato L, Burgardt A, et al. COQ4 is required for the oxidative decarboxylation of the C1 carbon of coenzyme Q in eukaryotic cells. Mol Cell. 2024;84(5):981-989.e7. doi:10.1016/j.molcel.2024.01.003
33. Wasilewski M, Chojnacka K, Chacinska A. Protein trafficking at the crossroads to mitochondria. Biochimica et Biophysica Acta (BBA) - Molecular Cell Research. Volume 1864, Issue 1, 2017, Pages 125-137, ISSN 0167-4889,
34. Yao S, Nguyen TV, Rolfe A, et al. Small Molecule Inhibition of CPS1 Activity through an Allosteric Pocket. Cell Chem Biol. 2020;27(3):259-268.e5. doi:10.1016/j.chembiol.2020.01.009
35. Chuang SS, Helvig C, Taimi M, et al. CYP2U1, a novel human thymus- and brain-specific cytochrome P450, catalyzes omega- and (omega-1)-hydroxylation of fatty acids. J Biol Chem. 2004;279(8):6305-6314. doi:10.1074/jbc.M311830200
36. Xie X, Wang Y, Yu D, Xie R, Liu Z, Huang B. DNM1, a Dynamin-Related Protein That Contributes to Endocytosis and Peroxisome Fission, Is Required for the Vegetative Growth, Sporulation, and Virulence of Metarhizium robertsii. Appl Environ Microbiol. 2020;86(17):e01217-20. Published 2020 Aug 18. doi:10.1128/AEM.01217-20
37. Marada A, Walter C, Suhm T, et al. DYRK1A signalling synchronizes the mitochondrial import pathways for metabolic rewiring. Nat Commun. 2024;15(1):5265. Published 2024 Jun 20. doi:10.1038/s41467-024-49611-4
38. Ni M, Black LF, Pan C, et al. Metabolic impact of pathogenic variants in the mitochondrial glutamyl-tRNA synthetase EARS2. J Inherit Metab Dis. 2021;44(4):949-960. doi:10.1002/jimd.12387
39. Ayhan S, Dursun A. ELFN1 is a new extracellular matrix (ECM)-associated protein. Life Sci. 2024;352:122900. doi:10.1016/j.lfs.2024.122900
40. Rocconi RP, Stanbery L, Tang M, et al. ENTPD1/CD39 as a predictive marker of treatment response to gemogenovatucel-T as maintenance therapy in newly diagnosed ovarian cancer. Commun Med (Lond). 2022;2:106. Published 2022 Aug 29. doi:10.1038/s43856-022-00163-y
41. Ersoy M, Tiranti V, Zeviani M. Ethylmalonic encephalopathy: Clinical course and therapy response in an uncommon mild case with a severe ETHE1 mutation. Mol Genet Metab Rep. 2020;25:100641. Published 2020 Aug 28. doi:10.1016/j.ymgmr.2020.100641
42. Zhao G, Lin Q, Meng Z, Sheng X, Ma L, Zhao Y. Face off: a metabolic enzyme becomes a protein phosphatase. Protein Cell. 2023;14(7):474-476. doi:10.1093/procel/pwad006
43. Alsina D, Lytovchenko O, Schab A, et al. FBXL4 deficiency increases mitochondrial removal by autophagy. EMBO Mol Med. 2020;12(7):e11659. doi:10.15252/emmm.201911659
44. Bond LM, Ibrahim A, Lai ZW, et al. Fitm2 is required for ER homeostasis and normal function of murine liver. J Biol Chem. 2023;299(3):103022. doi:10.1016/j.jbc.2023.103022
45. Pancrazi L, Di Benedetto G, Colombaioni L, et al. Foxg1 localizes to mitochondria and coordinates cell differentiation and bioenergetics. Proc Natl Acad Sci U S A. 2015;112(45):13910-13915. doi:10.1073/pnas.1515190112
46. Domin A, Zabek T, Kwiatkowska A, et al. The Identification of a Novel Fucosidosis-Associated FUCA1 Mutation: A Case of a 5-Year-Old Polish Girl with Two Additional Rare Chromosomal Aberrations and Affected DNA Methylation Patterns. Genes (Basel). 2021;12(1):74. Published 2021 Jan 8. doi:10.3390/genes12010074
47. Scheper AF, Schofield J, Bohara R, Ritter T, Pandit A. Understanding glycosylation: Regulation through the metabolic flux of precursor pathways. Biotechnol Adv. 2023;67:108184. doi:10.1016/j.biotechadv.2023.108184
48. Barroso M, Gertzen M, Puchwein-Schwepcke AF, et al. Glutaryl-CoA Dehydrogenase Misfolding in Glutaric Acidemia Type 1. Int J Mol Sci. 2023;24(17):13158. Published 2023 Aug 24. doi:10.3390/ijms241713158
49. Arribas-Carreira L, Dallabona C, Swanson MA, et al. Pathogenic variants in GCSH encoding the moonlighting H-protein cause combined nonketotic hyperglycinemia and lipoate deficiency. Hum Mol Genet. 2023;32(6):917-933. doi:10.1093/hmg/ddac246
50. Taneera J, Fadista J, Ahlqvist E, et al. Identification of novel genes for glucose metabolism based upon expression pattern in human islets and effect on insulin secretion and glycemia. Hum Mol Genet. 2015;24(7):1945-1955. doi:10.1093/hmg/ddu610
51. Itzkovitz B, Jiralerspong S, Nimmo G, et al. Functional characterization of novel mutations in GNPAT and AGPS, causing rhizomelic chondrodysplasia punctata (RCDP) types 2 and 3. Hum Mutat. 2012;33(1):189-197. doi:10.1002/humu.21623
52. Liu R, Feng Y, Deng Y, et al. A HIF1α-GPD1 feedforward loop inhibits the progression of renal clear cell carcinoma via mitochondrial function and lipid metabolism. J Exp Clin Cancer Res. 2021;40(1):188. Published 2021 Jun 7. doi:10.1186/s13046-021-01996-6
53. Madan V, Albacete-Albacete L, Jin L, et al. HEATR5B associates with dynein-dynactin and promotes motility of AP1-bound endosomal membranes. EMBO J. 2023;42(23):e114473. doi:10.15252/embj.2023114473
54. Sala-Gaston J, Pedrazza L, Ramirez J, et al. HERC2 deficiency activates C-RAF/MKK3/p38 signalling pathway altering the cellular response to oxidative stress. Cell Mol Life Sci. 2022;79(11):548. Published 2022 Oct 14. doi:10.1007/s00018-022-04586-7
55. Wang J, Liu Z, Xu M, et al. Cinical, Metabolic, and Genetic Analysis and Follow-Up of Eight Patients With HIBCH Mutations Presenting With Leigh/Leigh-Like Syndrome [published correction appears in Front Pharmacol. 2021 Jun 10;12:686933. doi: 10.3389/fphar.2021.686933]. Front Pharmacol. 2021;12:605803. Published 2021 Mar 8. doi:10.3389/fphar.2021.605803
56. Vinokurov AY, Soldatov VO, Seregina ES, et al. HPRT1 Deficiency Induces Alteration of Mitochondrial Energy Metabolism in the Brain. Mol Neurobiol. 2023;60(6):3147-3157. doi:10.1007/s12035-023-03266-2
57. Osaki Y, Saito A, Kanemoto S, et al. Shutdown of ER-associated degradation pathway rescues functions of mutant iduronate 2-sulfatase linked to mucopolysaccharidosis type II. Cell Death Dis. 2018;9(8):808. Published 2018 Jul 24. doi:10.1038/s41419-018-0871-8
58. Wang HY, Wang W, Liu YW, et al. Role of KCNB1 in the prognosis of gliomas and autophagy modulation. Sci Rep. 2017;7(1):14. Published 2017 Feb 8. doi:10.1038/s41598-017-00045-7
59. Wang Y, Cao X, Liu P, et al. KCTD7 mutations impair the trafficking of lysosomal enzymes through CLN5 accumulation to cause neuronal ceroid lipofuscinoses. Sci Adv. 2022;8(31):eabm5578. doi:10.1126/sciadv.abm5578
60. Kishita Y, Shimura M, Kohda M, et al. A novel homozygous variant in MICOS13/QIL1 causes hepato-encephalopathy with mitochondrial DNA depletion syndrome. Mol Genet Genomic Med. 2020;8(10):e1427. doi:10.1002/mgg3.1427
61. Forny P, Plessl T, Frei C, Bürer C, Froese DS, Baumgartner MR. Spectrum and characterization of bi-allelic variants in MMAB causing cblB-type methylmalonic aciduria. Hum Genet. 2022;141(7):1253-1267. doi:10.1007/s00439-021-02398-6
62. Zouiouich M, Di Mattia T, Martinet A, et al. MOSPD2 is an endoplasmic reticulum-lipid droplet tether functioning in LD homeostasis. J Cell Biol. 2022;221(6):e202110044. doi:10.1083/jcb.202110044
63. O'Byrne JJ, Tarailo-Graovac M, Ghani A, et al. The genotypic and phenotypic spectrum of MTO1 deficiency. Mol Genet Metab. 2018;123(1):28-42. doi:10.1016/j.ymgme.2017.11.003
64. Gun Bilgic D, Gerik Celebi HB, Aydin Gumus A, et al. Coinheritance of novel mutations in NAGLU causing mucopolysaccharidosis type IIIB and in DDHD2 causing spastic paraplegia54 in a Turkish family. J Clin Neurosci. 2020;82(Pt B):214-218. doi:10.1016/j.jocn.2020.11.007
65. Sung Y, Yoon I, Han JM, Kim S. Functional and pathologic association of aminoacyl-tRNA synthetases with cancer. Exp Mol Med. 2022;54(5):553-566. doi:10.1038/s12276-022-00765-5
66. Guan S, Zhao L, Peng R. Mitochondrial Respiratory Chain Supercomplexes: From Structure to Function. Int J Mol Sci. 2022;23(22):13880. Published 2022 Nov 10. doi:10.3390/ijms232213880
67. Zhou Q, Li X, Zhou H, et al. Mitochondrial respiratory chain component NDUFA4: a promising therapeutic target for gastrointestinal cancer. Cancer Cell Int. 2024;24(1):97. Published 2024 Mar 5. doi:10.1186/s12935-024-03283-8
68. Gorelik A, Illes K, Mazhab-Jafari MT, Nagar B. Structure of the immunoregulatory sialidase NEU1. Sci Adv. 2023;9(20):eadf8169. doi:10.1126/sciadv.adf8169
69. Pandey A, Adams JM, Han SY, Jafar-Nejad H. NGLY1 Deficiency, a Congenital Disorder of Deglycosylation: From Disease Gene Function to Pathophysiology. Cells. 2022;11(7):1155. Published 2022 Mar 29. doi:10.3390/cells11071155
70. Yu SH, Wang T, Wiggins K, et al. Lysosomal cholesterol accumulation contributes to the movement phenotypes associated with NUS1 haploinsufficiency. Genet Med. 2021;23(7):1305-1314. doi:10.1038/s41436-021-01137-6
71. Pezzella N, Bove G, Tammaro R, Franco B. OFD1: One gene, several disorders. Am J Med Genet C Semin Med Genet. 2022;190(1):57-71. doi:10.1002/ajmg.c.31962
72. Tsai HW, Li CJ, Lin LT, et al. Expression status and prognostic significance of mitochondrial dynamics OPA3 in human ovarian cancer. Aging (Albany NY). 2022;14(9):3874-3886. doi:10.18632/aging.204050
73. Jiang C, Lu Y, Zhu R, et al. Pyruvate dehydrogenase beta subunit (Pdhb) promotes peripheral axon regeneration by regulating energy supply and gene expression. Exp Neurol. 2023;363:114368. doi:10.1016/j.expneurol.2023.114368
74. Inoue J, Kishikawa M, Tsuda H, Nakajima Y, Asakage T, Inazawa J. Identification of PDHX as a metabolic target for esophageal squamous cell carcinoma. Cancer Sci. 2021;112(7):2792-2802. doi:10.1111/cas.14938
75. Barlow-Busch I, Shaw AL, Burke JE. PI4KA and PIKfyve: Essential phosphoinositide signaling enzymes involved in myriad human diseases. Curr Opin Cell Biol. 2023;83:102207. doi:10.1016/j.ceb.2023.102207
76. Ihara S, Nakayama S, Murakami Y, et al. PIGN prevents protein aggregation in the endoplasmic reticulum independently of its function in the GPI synthesis. J Cell Sci. 2017;130(3):602-613. doi:10.1242/jcs.196717
77. Brunetti D, Catania A, Viscomi C, et al. Role of PITRM1 in Mitochondrial Dysfunction and Neurodegeneration. Biomedicines. 2021;9(7):833. Published 2021 Jul 17. doi:10.3390/biomedicines9070833
78. Samad F, Bai H, Baik N, et al. The plasminogen receptor Plg-RKT regulates adipose function and metabolic homeostasis. J Thromb Haemost. 2022;20(3):742-754. doi:10.1111/jth.15622
79. Rahman S, Copeland WC. POLG-related disorders and their neurological manifestations. Nat Rev Neurol. 2019;15(1):40-52. doi:10.1038/s41582-018-0101-0
80. Scoma ER, Da Costa RT, Leung HH, et al. Human Prune Regulates the Metabolism of Mammalian Inorganic Polyphosphate and Bioenergetics. Int J Mol Sci. 2023;24(18):13859. Published 2023 Sep 8. doi:10.3390/ijms241813859
81. Singh S, Yeat NY, Wang YT, et al. PTPN23 ubiquitination by WDR4 suppresses EGFR and c-MET degradation to define a lung cancer therapeutic target [published correction appears in Cell Death Dis. 2024 Jul 2;15(7):468. doi: 10.1038/s41419-024-06747-x]. Cell Death Dis. 2023;14(10):671. Published 2023 Oct 11. doi:10.1038/s41419-023-06201-4
82. Wang S, Yi W, Xu Z, Shi M. PYCR2 promotes growth and aerobic glycolysis in human liver cancer by regulating the AKT signaling pathway. Biochem Biophys Res Commun. 2023;680:15-24. doi:10.1016/j.bbrc.2023.09.007
83. Migocka-Patrzałek M, Lewicka A, Elias M, Daczewska M. The effect of muscle glycogen phosphorylase (Pygm) knockdown on zebrafish morphology. Int J Biochem Cell Biol. 2020;118:105658. doi:10.1016/j.biocel.2019.105658
84. Zhang Y, Yu Y, Zhao X, et al. Novel RARS2 Variants: Updating the Diagnosis and Pathogenesis of Pontocerebellar Hypoplasia Type 6. Pediatr Neurol. 2022;131:30-41. doi:10.1016/j.pediatrneurol.2022.04.002
85. Miliotou AN, Foltopoulou PF, Ingendoh-Tsakmakidis A, et al. Protein Transduction Domain-Mediated Delivery of Recombinant Proteins and In Vitro Transcribed mRNAs for Protein Replacement Therapy of Human Severe Genetic Mitochondrial Disorders: The Case of Sco2 Deficiency. Pharmaceutics. 2023;15(1):286. Published 2023 Jan 14. doi:10.3390/pharmaceutics15010286
86. Fang H, Xie A, Du M, et al. SERAC1 is a component of the mitochondrial serine transporter complex required for the maintenance of mitochondrial DNA. Sci Transl Med. 2022;14(634):eabl6992. doi:10.1126/scitranslmed.abl6992
87. Norouzi Rostami F, Sadeghi H, Hashemi-Gorji F, et al. Identification of novel mutations in TPK1 and SLC19A3 genes in families exhibiting thiamine metabolism dysfunction syndrome. Heliyon. 2024;10(6):e27434. Published 2024 Mar 6. doi:10.1016/j.heliyon.2024.e27434
88. Tonazzi A, Giangregorio N, Console L, Palmieri F, Indiveri C. The Mitochondrial Carnitine Acyl-carnitine Carrier (SLC25A20): Molecular Mechanisms of Transport, Role in Redox Sensing and Interaction with Drugs. Biomolecules. 2021;11(4):521. Published 2021 Mar 31. doi:10.3390/biom11040521
89. Murata D, Roy S, Lutsenko S, Iijima M, Sesaki H. Slc25a3-dependent copper transport controls flickering-induced Opa1 processing for mitochondrial safeguard. Dev Cell. 2024;59(19):2578-2592.e7. doi:10.1016/j.devcel.2024.06.008
90. Datta S, Liu Y, Hariri H, Bowerman J, Henne WM. Cerebellar ataxia disease-associated Snx14 promotes lipid droplet growth at ER-droplet contacts. J Cell Biol. 2019;218(4):1335-1351. doi:10.1083/jcb.201808133
91. Boese AC, Kang J, Hwang JS, et al. Succinyl-CoA ligase ADP-forming subunit beta promotes stress granule assembly to regulate redox and drive cancer metastasis. Proc Natl Acad Sci U S A. 2023;120(23):e2217332120. doi:10.1073/pnas.2217332120
92. Moreira DP, Suzuki AM, Silva ALTE, et al. Neuroprogenitor Cells From Patients With TBCK Encephalopathy Suggest Deregulation of Early Secretory Vesicle Transport. Front Cell Neurosci. 2022;15:803302. Published 2022 Jan 13. doi:10.3389/fncel.2021.803302
93. Papaioannou P, Wallace MJ, Malhotra N, Mohler PJ, El Refaey M. Biochemical Structure and Function of TRAPP Complexes in the Cardiac System. JACC Basic Transl Sci. 2023;8(12):1599-1612. Published 2023 Jul 12. doi:10.1016/j.jacbts.2023.03.011
94. Oeing CU, Jun S, Mishra S, et al. MTORC1-Regulated Metabolism Controlled by TSC2 Limits Cardiac Reperfusion Injury. Circ Res. 2021;128(5):639-651. doi:10.1161/CIRCRESAHA.120.317710
95. Kang SH, Kim GR, Seong M, et al. Two novel ubiquitin-fold modifier 1 (Ufm1)-specific proteases, UfSP1 and UfSP2. J Biol Chem. 2007;282(8):5256-5262. doi:10.1074/jbc.M610590200
96. Kang Y, Chen L. Structure and mechanism of NALCN-FAM155A-UNC79-UNC80 channel complex. Nat Commun. 2022;13(1):2639. Published 2022 May 12. doi:10.1038/s41467-022-30403-7
97. Milenkovic D, Misic J, Hevler JF, et al. Preserved respiratory chain capacity and physiology in mice with profoundly reduced levels of mitochondrial respirasomes. Cell Metab. 2023;35(10):1799-1813.e7. doi:10.1016/j.cmet.2023.07.015
98. Kušíková K, Feichtinger RG, Csillag B, et al. Case Report and Review of the Literature: A New and a Recurrent Variant in the VARS2 Gene Are Associated With Isolated Lethal Hypertrophic Cardiomyopathy, Hyperlactatemia, and Pulmonary Hypertension in Early Infancy. Front Pediatr. 2021;9:660076. Published 2021 Apr 16. doi:10.3389/fped.2021.660076
99. Leonzino M, Reinisch KM, De Camilli P. Insights into VPS13 properties and function reveal a new mechanism of eukaryotic lipid transport. Biochim Biophys Acta Mol Cell Biol Lipids. 2021;1866(10):159003. doi:10.1016/j.bbalip.2021.159003
100. Yim WW, Mizushima N. Lysosome biology in autophagy. Cell Discov. 2020;6:6. Published 2020 Feb 11. doi:10.1038/s41421-020-0141-7
101. Yıldız Y, Koşukcu C, Aygün D, et al. Homozygous missense VPS16 variant is associated with a novel disease, resembling mucopolysaccharidosis-plus syndrome in two siblings. Clin Genet. 2021;100(3):308-317. doi:10.1111/cge.14002
102. Zazo Seco C, Castells-Nobau A, Joo SH, et al. A homozygous FITM2 mutation causes a deafness-dystonia syndrome with motor regression and signs of ichthyosis and sensory neuropathy. Dis Model Mech. 2017;10(2):105-118. doi:10.1242/dmm.026476
103. Tucker EJ, Wanschers BF, Szklarczyk R, et al. Mutations in the UQCC1-interacting protein, UQCC2, cause human complex III deficiency associated with perturbed cytochrome b protein expression. PLoS Genet. 2013;9(12):e1004034. doi:10.1371/journal.pgen.1004034
104. Tiranti V, D'Adamo P, Briem E, et al. Ethylmalonic encephalopathy is caused by mutations in ETHE1, a gene encoding a mitochondrial matrix protein. Am J Hum Genet. 2004;74(2):239-252. doi:10.1086/381653
105. Tiranti V, Zeviani M. Altered sulfide (H(2)S) metabolism in ethylmalonic encephalopathy. Cold Spring Harb Perspect Biol. 2013;5(1):a011437. Published 2013 Jan 1. doi:10.1101/cshperspect.a011437
106. Nguyen KV, Nyhan WL. Mutation in the Human HPRT1 Gene and the Lesch-Nyhan Syndrome. Nucleosides Nucleotides Nucleic Acids. 2016;35(8):426-433. doi:10.1080/15257770.2015.1098660
107. Diodato D, Melchionda L, Haack TB, et al. VARS2 and TARS2 mutations in patients with mitochondrial encephalomyopathies. Hum Mutat. 2014;35(8):983-989. doi:10.1002/humu.22590
108. Wang J, Wang J, Han X, et al. Report of the Largest Chinese Cohort With SLC19A3 Gene Defect and Literature Review. Front Genet. 2021;12:683255. Published 2021 Jul 1. doi:10.3389/fgene.2021.683255
109. Barron KS, Aksentijevich I, Deuitch NT, et al. The Spectrum of the Deficiency of Adenosine Deaminase 2: An Observational Analysis of a 60 Patient Cohort. Front Immunol. 2022;12:811473. Published 2022 Jan 10. doi:10.3389/fimmu.2021.811473
110. Tejada MI, Villate O, Ibarluzea N, et al. Molecular and Clinical Characterization of a Novel Nonsense Variant in Exon 1 of the UPF3B Gene Found in a Large Spanish Basque Family (MRX82). Front Genet. 2019;10:1074. Published 2019 Oct 31. doi:10.3389/fgene.2019.01074
111. Levy RJ, Frater CH, Gallentine WB, Phillips JM, Ruzhnikov MR. Delineating the epilepsy phenotype of NGLY1 deficiency. J Inherit Metab Dis. 2022;45(3):571-583. doi:10.1002/jimd.12494
112. Beesley CE, Jackson M, Young EP, Vellodi A, Winchester BG. Molecular defects in Sanfilippo syndrome type B (mucopolysaccharidosis IIIB). J Inherit Metab Dis. 2005;28(5):759-767. doi:10.1007/s10545-005-0093-y
113. Caciotti A, Melani F, Tonin R, et al. Type I sialidosis, a normosomatic lysosomal disease, in the differential diagnosis of late-onset ataxia and myoclonus: An overview. Mol Genet Metab. 2020;129(2):47-58. doi:10.1016/j.ymgme.2019.09.005
114. Wongkittichote P, Duque Lasio ML, Magistrati M, et al. Phenotypic, molecular, and functional characterization of COQ7-related primary CoQ10 deficiency: Hypomorphic variants and two distinct disease entities. Mol Genet Metab. 2023;139(4):107630. doi:10.1016/j.ymgme.2023.107630
115. Leeson HC, Goh D, Coman D, Wolvetang EJ. Generation of iPSC lines from hereditary spastic paraplegia 56 (SPG56) patients and family members carrying CYP2U1 mutations. Stem Cell Res. 2022;64:102917. doi:10.1016/j.scr.2022.102917
116. Rice GI, Bond J, Asipu A, et al. Mutations involved in Aicardi-Goutières syndrome implicate SAMHD1 as regulator of the innate immune response. Nat Genet. 2009;41(7):829-832. doi:10.1038/ng.373
117. Brunetti D, Torsvik J, Dallabona C, et al. Defective PITRM1 mitochondrial peptidase is associated with Aβ amyloidotic neurodegeneration. EMBO Mol Med. 2016;8(3):176-190. doi:10.15252/emmm.201505894
118. Wang S, Yi W, Xu Z, Shi M. PYCR2 promotes growth and aerobic glycolysis in human liver cancer by regulating the AKT signaling pathway. Biochem Biophys Res Commun. 2023;680:15-24. doi:10.1016/j.bbrc.2023.09.007
119. Nakayama T, Al-Maawali A, El-Quessny M, et al. Mutations in PYCR2, Encoding Pyrroline-5-Carboxylate Reductase 2, Cause Microcephaly and Hypomyelination. Am J Hum Genet. 2015;96(5):709-719. doi:10.1016/j.ajhg.2015.03.003
120. Tang HL, Chen SY, Zhang H, et al. Expression Pattern of ALOXE3 in Mouse Brain Suggests Its Relationship with Seizure Susceptibility. Cell Mol Neurobiol. 2022;42(3):777-790. doi:10.1007/s10571-020-00974-4
121. Eckl KM, Krieg P, Küster W, et al. Mutation spectrum and functional analysis of epidermis-type lipoxygenases in patients with autosomal recessive congenital ichthyosis. Hum Mutat. 2005;26(4):351-361. doi:10.1002/humu.20236
122. Tsai HW, Li CJ, Lin LT, et al. Expression status and prognostic significance of mitochondrial dynamics OPA3 in human ovarian cancer. Aging (Albany NY). 2022;14(9):3874-3886. doi:10.18632/aging.204050
123. Huizing M, Dorward H, Ly L, et al. OPA3, mutated in 3-methylglutaconic aciduria type III, encodes two transcripts targeted primarily to mitochondria. Mol Genet Metab. 2010;100(2):149-154. doi:10.1016/j.ymgme.2010.03.005
124. Tarailo-Graovac M, Shyr C, Ross CJ, et al. Exome Sequencing and the Management of Neurometabolic Disorders. N Engl J Med. 2016;374(23):2246-2255. doi:10.1056/NEJMoa1515792
125. Hertzog A, Selvanathan A, Farnsworth E, et al. Intronic variants in inborn errors of metabolism: Beyond the exome. Front Genet. 2022;13:1031495. Published 2022 Dec 6. doi:10.3389/fgene.2022.1031495
126. Soriano-Sexto A, Gallego D, Leal F, et al. Identification of Clinical Variants beyond the Exome in Inborn Errors of Metabolism. Int J Mol Sci. 2022;23(21):12850. Published 2022 Oct 25. doi:10.3390/ijms232112850
127. Choon YW, Choon YF, Nasarudin NA, et al. Artificial intelligence and database for NGS-based diagnosis in rare disease. Front Genet. 2024;14:1258083. Published 2024 Jan 25. doi:10.3389/fgene.2023.1258083
128. Yepes S, Tucker MA, Koka H, et al. Using whole-exome sequencing and protein interaction networks to prioritize candidate genes for germline cutaneous melanoma susceptibility. Sci Rep. 2020;10(1):17198. Published 2020 Oct 14. doi:10.1038/s41598-020-74293-5
129. Graham Linck EJ, Richmond PA, Tarailo-Graovac M, et al. metPropagate: network-guided propagation of metabolomic information for prioritization of metabolic disease genes. NPJ Genom Med. 2020;5:25. Published 2020 Jul 2. doi:10.1038/s41525-020-0132-5
130. Wu R, Li X, Meng Z, Li P, He Z, Liang L. Phenotypic and genetic analysis of children with unexplained neurodevelopmental delay and neurodevelopmental comorbidities in a Chinese cohort using trio-based whole-exome sequencing. Orphanet J Rare Dis. 2024;19(1):205. Published 2024 May 19. doi:10.1186/s13023-024-03214-w
