Volume 16, Issue 1 (Jan-Feb 2022)                   mljgoums 2022, 16(1): 1-8 | Back to browse issues page

XML Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

asadi F, goodarzi H, zahiri J, jafarinia M. Genes Associated with Coma or Recurrent Coma and Role of Next Generation Sequencing in Diagnosis of Disease-Causing Genes. mljgoums 2022; 16 (1) :1-8
URL: http://mlj.goums.ac.ir/article-1-1343-en.html
1- PhD student, Department of Genetics, Fars Science and Research Branch, Islamic Azad University, Marvdasht, Iran And Department of Genetics, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran
2- Department of Genetics, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran , drgoodarzi.lab@gmail.com
3- Department of Bioinformatics, Faculty of Biology Sciences, Tarbiat Modares University, Tehran, Iran
4- Department of Genetics, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran
Full-Text [PDF 923 kb]   (908 Downloads)     |   Abstract (HTML)  (1778 Views)
Full-Text:   (901 Views)
ABSTRACT
Coma is a state of prolonged unconsciousness. Some coma cases result from inherited disorders such as fatty-acid β-oxidation disorder, acute intermittent porphyria (due to mutations in genes CPT I, CPTII and ACADM), urea cycle defects (due to mutation in OTC gene), organic acidurias, mitochondrial diseases and familial hemiplegic migraine (due to mutations in CACNA1A, ATP1A2 and SCN1A). The evaluation of familial cases of coma or sporadic coma can be performed using next generation sequencing (NGS), a high-throughput  sequencing technique that can sequence an entire genome in a single reaction. This technique has been widely applied in the genetic diagnosis of diseases. In this review, we describe some genes associated with coma or recurrent coma and discuss the role of NGS in detection of these genes.  
Keywords: Coma, Next generation sequencing, Gene
 
INTRODUCTION
Coma is a deep state of unconsciousness lasting more than six hours in which a person cannot be awakened. In this condition, patients are unable to respond to stimulators such as sound, light and pain (1). Coma can be caused by different disorders including central nervous system diseases, metabolic disorders, hypothermia, hypoxia,  hypoglycemia and acute neurologic disorders such as strokes (2).
Several studies have indicated that coma or recurrent coma could be associated with some inborn errors of metabolism such as fatty-acid β-oxidation disorders (3), acute intermittent porphyria (4), urea cycle defects (5), organic acidurias (6), mitochondrial diseases (7) and familial hemiplegic migraine (FHM)(8-10). In recent decades, some cases of episodic coma have been reported worldwide. In the past, Sanger sequencing was used to evaluate possible relationship of genes with coma. However, the method falls short to survey many genes simultaneously and to explore new genes associated with the condition. Therefore, new genetic technologies such as next generation sequencing (NGS) have been developed to facilitate the evaluation of genetic disorders and even unknown inherited diseases. In this review, we discuss genes that are linked to coma and the role of NGS in diagnosing this disorder.
 
Different types of coma or recurrent coma
Metabolic disorders
Recurrent episodes of coma are usually related to metabolic disorders. Inborn errors of metabolism often result from mutations in genes that code for enzymes involved in the metabolism of carbohydrates, fatty acids and proteins. The worldwide prevalence of inborn errors of metabolism has been estimated to be 1 in 2,500 live births (11, 12). Most metabolic disorders show an autosomal recessive pattern, but some may be due to autosomal dominant and X-linked inheritance (13-15). The followings are the cases of inborn errors of metabolism associated with coma: 
Ornithine transcarboxylase deficiency  
This disorder is caused by mutations in OTC gene located on the X chromosome. Symptoms of disease include hyperammonemia, lethargy, confusion, nausea, vomiting, bizarre behavior and coma (16, 17). In 1984, Oizumi et al. reported a case of coma caused by ornithine transcarbamylase deficiency associated with hyperammonemia (5). Zubeda Sheikh et al. reported a case of recurrent coma associated with refractory epilepticus in a man with previous history of hospitalization due to coma. An extensive workup revealed ornithine transcarboxylase deficiency as the diagnosis
Lesch-Nyhan syndrome (LNS)
Lesch-Nyhan syndrome is an X-linked recessive disorder caused by a deficiency in the hypoxanthine-guanine phosphoribosyl transferase enzyme, which leads to high production of uric acid. The resulting hyperuricemia lead to neurological and behavioral abnormalities such as self-mutilation (18, 19). In 1991, Bryan et al. introduced a patient with Lesch-Nyhan syndrome who presented with episodic coma. The authors suggested that this problem may be related to a defect in the cellular energy metabolism in purine-depleted cells due to deficiency in the purine salvage pathway, and consequently the disruption of adenosine triphosphate synthesis (20).
Acute intermittent porphyria (AIP)
This disorder results from mutations in the hydroxymethylbilane synthase gene. This rare metabolic disorder arise from porphobilinogen deaminase deficiency, an enzyme involved in heme biosynthesis. Common symptoms of AIP are abdominal pain, vomiting, constipation, muscle weakness as well as neurological complaints such as peripheral polyneuropathy, lethargy and altered consciousness ranging from somnolence to coma (4).
Maple syrup urine disease
Maple syrup urine disease (MSUD) is  an autosomal recessive metabolic disorder caused by mutations in the BCKDHA, BCKDHB, DBT and DLD genes, which encode the E1α, E1β, E2 and E3 subunits of the branched chain α ketoacid dehydrogenase (BCKAD) complex, respectively (21). The clinical manifestations depends on the BCKAD residual activity. In early infancy, this condition can be characterized by poor feeding, vomiting, lethargy and developmental delay. If untreated, brain damage can lead to seizure, coma and death (22).
 
Mitochondrial diseases
Coma can also occur in cases of fatty acid β-oxidation disorders (FAODs). This group of genetic metabolic disorders is caused by defects in β-oxidation enzymes involved in fatty acid oxidation (23). Newborns with FAOD usually manifest hypoketotic hypoglycemia, metabolic acidosis, hepatic failure, cardiomyopathy and seizures. The most prevalent fatty acid oxidation disorder is medium chain acyl-CoA dehydrogenase deficiency. The symptoms include lethargy, nausea or vomiting, hypoglycemia, hepatomegaly, seizures and repeated episodes of hypoketotic, hypoglycemic coma (3). In 2006, Roomets et al. reported a case of deep coma without hypoglycemia because of carnitine palmitoyltransferase I deficiency (24). Coma also has been reported in a case of carnitine palmitoyltransferase II deficiency (25).
 
Leukodystrophies
Leukodystrophies are described as a group of inherited disorders that affect the central nerves system and the peripheral nerves. Leukodystrophies caused by mutations in different genes have been reported in forms of the following disorders: cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), adult-onset autosomal dominant leukodystrophy, Pelizaeus-Merzbacher disease, Sjogren-Larsson syndrome, Canavan disease and etc., all of which result in a range of neurological disorders (26). CADASIL is caused by mutations in the NOTCH3 gene located on chromosome 19. It is characterized by repeated strokes, dementia and migraine known as CADASIL coma (27). Eswaradass et al. reported a case of CADASIL coma in a male with heterozygous mutation in the NOTCH3 gene (28).
 
Monogenetic migraine coma
Recurrent coma can occur due to familial hemiplegic migraine (FHM), a rare monogenetic migraine with aura characterized by typical attacks associated with transient motor deficit, visual signs and speech impairment. To date, three main genes including CACNA1A, ATP1A2 and SCN1A have been reported to be involved in etiology of FMH1, FMH2 and FMH3, respectively. The CACNA1A gene is located on chromosome 19P13 and encodes the α1 subunit of the P/Q-type of high-voltage-activated Ca2+ channels. The gene is abundantly expressed in the cerebellum, hippocampus and cortex of the mammalian brain (29). The ATP1A2 gene located on chromosome 1 (1q23) codes for a catalytic subunit of sodium/potassium ATPase. The SCN1A gene, located on chromosome 2q24, encodes a transmembrane alpha subunit of the brain sodium channel (29).
 
Hepatic coma
Hepatic coma refers to a set of neuropsychiatric conditions such as confusion, asterixis and coma that occur during liver failure. It can have exogenous and endogenous causes (30). Metabolic related to fatty liver disease (MAFLD) previously known as nonalcoholic fatty liver disease (NAFLD) is the most common liver disease, which involves fat accumulation in hepatocytes, leading to obesity and metabolic syndrome (31). Non-alcoholic steatohepatitis (NASH) is the critical stage of NAFLD (32, 33) that may be asymptomatic at first but lead to jaundice, blood clots and coma as the disease progresses. Many genetic alterations including mutation in the PNPLA3 gene are thought to be associated with NAFLD and NASH (34).
 
NGS
This method enables sequencing of an organism’s genome in a single reaction (35). It has been widely applied in the diagnosis of genetic diseases. Principally, the NGS technique is similar to conventional capillary electrophoresis sequencing, but it can simultaneously sequence thousands of DNA fragments from a single sample. The NGS involves four basic steps:
Library preparation: DNA is randomly fragmented by various methods. These fragments are modified with adaptor sequences to both ends of each DNA fragment.
Cluster generation: the prepared library is loaded into a flow cell to generate library clusters.
Sequencing: the captured libraries are sequenced by the sequencing platforms and short reads with various lengths are produced (Figure 1) (36).
Data analysis: reads generated through NGS are mapped to a reference genome using bioinformatics tools (Figure 2). Variant calling is performed using bioinformatics software such as Genome Analysis Tool Kit (GATK). All found variants are checked with databases including dbSNP, 1000 Genomes Project, ESP 6500 Exome Project, and ExAC v0.2, ExAC Browser, OMIM and ClinVar for evaluating pathogenicity of the variants. In silico tools such as SIFT, PolyPhen-2, CADD and Mutation Taster are also used.
 
NGS types
Genomics
Whole genome sequencing (WGS)
It is a process through which the complete genome of an organism including chromosomal DNA and the mitochondrial DNA are sequenced at a single run. The method is mostly applied for sequencing human genomes (37).
Whole exome sequencing (WES)
Exome sequencing is a technique for sequencing all coding regions of genome named exome. In WES, all exons and splicing sites of the genome are captured and subsequently sequenced. In humans, the exome contains less than two percent of the genome; however, it contains the majority of disease-related variants. Therefore, WES can be considered as a cost-effective method for identifying specific variants in a wide range of issues including genetic disorders, population genetics and cancer investigations (Figure3) (38, 39).
De novo sequencing
It is related to sequencing and construction of a novel genome because there is no reference genome sequence to align the short reads generated by NGS. In this process, sequence reads are assembled to generate contigs for creating a new reference genome (40).
Targeted sequencing
In targeted sequencing, a collection of specific regions of the genome can be extracted and sequenced, enabling studying individual genes. It results in higher coverage levels than WGS, which allows detection of very rare variants. Different types of targeted sequencing panels have been used in cancer studies (41), metabolic disorders (42) and epileptic disorders (43).
Transcriptomic sequencing
This technique enables sequencing of total RNA (RNA-seq). First, RNA samples are converted to cDNAs, and then library preparation and sequencing are carried out. RNA-seq can be used for sequencing mRNAs, small RNAs, noncoding RNAs or microRNAs (44).
 
Epigenomics
Epigenetics is mostly related to changes that modify gene activity and expression via mechanisms other than DNA sequence changes. These molecular mechanisms include DNA methylation, small RNA–mediated regulation, DNA–protein interactions and histone modification (36).  
 
Role of NGS in diagnosis of coma or recurrent coma
Whole exome sequencing and targeted gene sequencing panels are widely applied for evaluation of genetic disorders including metabolic diseases, neurometabolic disorders and mitochondrial disorders. Thus, we can screen genes involved in coma or recurrent coma by using NGS methods.
 
Coma associated with FHM
A five-gene targeted NGS panel containing the three FHM genes (CACNA1AATP1A2 and SCN1A), two genes involved in migraine-related disorders (NOTCH3 and the KCNK18) and the KCNK18 gene has been designed for evaluation of genes associated with recurrent coma in FHM (45, 46)(Table1).
 

 
Coma associated with metabolic disorders.
Coma can occur in neonates due to metabolic intoxication syndrome. A metabolic gene panel can be used to explore the condition. There are gene panels (for example: https://www.centogene.com/diagnostics/ngs-panels/metabolic-disorders) that can be used for evaluation of over 1,250 metabolic disease genes.
 
Fatty acid oxidation disorder gene panel
Table 2 shows some of the genes associated with the fatty acid oxidation disorder (available at https://www.cd-genomics.com/diseasepanel/custom-fatty-acid-oxidation-disorder-panel.html.). .
 
Coma with unknown causes
Although, NGS has been extensively applied in diagnosis of diseases, it could play a significant role in genetic evaluation of rare disorders and exploring novel genes associated with diseases.

 
Figure 1-The steps of DNA extraction, fragmentation, amplification and seqeuncing in NGS


Figure 2- Mapping and alignment of short reads generated by NGS with reference genome.


 Figure 3- The steps of whole exome sequencing in which all coding regions of genome are captured using a set baits, sequenced and then aligning with the reference genome
DISCUSSION
Coma is referred to a state of prolonged unconsciousness. Coma or recurrent coma can occur because of inherited conditions including FHM as well as metabolic and mitochondrial disorders. Evidence suggest that some genes including OTC, CPT I, CPTII, ACADM, CACNA1A, ATP1A2 and SCN1A may be associated with the above mentioned conditions. Sanger sequencing was the method of choice for evaluation of disease-related genes (47). However, in cases of coma or recurrent coma with unknown genetic origin, sequencing of genes is more difficult and time consuming. Therefore, NGS has been recently introduced as a more efficient technique for evaluating disease-related genes. The technique allows simultaneous analysis of several genes. On the other hand, WES has contributed greatly to quicker diagnosis of metabolic and neurogenetic disorders in clinical settings. In a previous study, WES was used to explore coronary artery disease-associated genes in an Iranian family (48). Thus, this new method can be utilized for screening familial cases of coma or sporadic coma and identifying unknown genes related to this condition. In this regard, Maksemous et al. used targeted NGS multigene panel to screen 172 individuals with suspected hemiplegic migraine for diseases-causing genes and causative variants. The targeted NGS 5-gene panel include three FHM genes (CACNA1A, ATP1A2 and SCN1A) as well as two migraine-related genes (NOTCH3 and KCNK18) (49).
 
CONCLUSION
We described the general concepts of coma or recurrent coma and some associated genes. Recent evidence suggests that NGS and WES could be used as efficient tools for detecting some types inherited coma. Since most coma cases are related to metabolic disorders, it is recommended to first screen for inborn errors of metabolism using WES and/or targeted gene sequencing panels, and then identify genes associated with coma or recurrent coma.
 
ACKNOWLEDGEMENTS
None.
 
CONFLICT OF INTEREST
The authors declare that there is no conflict of interest regarding publication of this article.
 
 
Research Article: Review Article | Subject: Human Genetics
Received: 2020/11/10 | Accepted: 2021/05/1 | Published: 2021/12/29 | ePublished: 2021/12/29

References
1. Weyhenmyeye J, Gallman E. Rapid Review Neuroscience. Philadelphia: Mosby. Elsevier; 2007. [View at Publisher]
2. Zeman A. Persistent vegetative state. The Lancet. 1998; 351(9096): 144. [View at Publisher] [DOI:10.1016/S0140-6736(05)78109-5] [PubMed] [Google Scholar]
3. Hoflack M, Caruba C, Pitelet G, Haas H, Mas JC, Paquis V, et al. Coma du nourrisson aux urgences: 2 cas de déficit en MCAD [Infant coma in the emergency department: 2 cases of MCAD deficiency. Arch Pediatr. 2010; 17(7): 1074-7. [View at Publisher] [DOI:10.1016/j.arcped.2010.03.011] [Google Scholar]
4. Ghosh S, Chaudhury PK, Goswami HKJIjop. An analysis of six cases of acute intermittent porphyria (AIP). Indian J Psychiatry. 2006;48(3):189. [View at Publisher] [DOI:10.4103/0019-5545.31584] [PubMed] [Google Scholar]
5. Oizumi J, Ng WG, Koch R, Shaw KN, Sweetman L, Velazquez A, et al. Partial ornithine transcarbamylase deficiency associated with recurrent hyperammonemia, lethargy and depressed sensorium. Clinical genetics. 1984; 25(6): 538-42. [View at Publisher] [DOI:10.1111/j.1399-0004.1984.tb00498.x] [PubMed] [Google Scholar]
6. De Baulny HO, Saudubray J-M. Branched-chain organic acidurias. Inborn metabolic diseases: Springer. 2000; 196-212. [View at Publisher] [DOI:10.1007/978-3-662-04285-4_16]
7. Swaiman KF, Ashwal S, Ferriero DM, Schor NF, Finkel RS, Gropman AL, et al. Swaiman's Pediatric Neurology E-Book: Principles and Practice: Elsevier Health Sciences; 2017. [View at Publisher]
8. Ducros A, Denier C, Joutel A, Cecillon M, Lescoat C, Vahedi K, et al. The clinical spectrum of familial hemiplegic migraine associated with mutations in a neuronal calcium channel. N Engl J Med. 2001; 345(1): 17-24. [View at Publisher] [DOI:10.1056/NEJM200107053450103] [PubMed] [Google Scholar]
9. Blumkin L, Michelson M, Leshinsky-Silver E, Kivity S, Lev D, Lerman-Sagie TJJocn. Congenital ataxia, mental retardation, and dyskinesia associated with a novel CACNA1A mutation. J Child Neurol. 2010; 25(7): 892-7. [View at Publisher] [DOI:10.1177/0883073809351316] [PubMed] [Google Scholar]
10. Pelzer N, Blom D, Stam A, Vijfhuizen L, Hageman A, van Vliet J, et al. Recurrent coma and fever in familial hemiplegic migraine type 2. A prospective 15-year follow-up of a large family with a novel ATP1A2 mutation. Cephalalgia. 2017; 37(8): 737-55. [View at Publisher] [DOI:10.1177/0333102416651284] [PubMed] [Google Scholar]
11. Stenton SL, Kremer LS, Kopajtich R, Ludwig C, Prokisch H. The diagnosis of inborn errors of metabolism by an integrative "multi‐omics" approach: A perspective encompassing genomics, transcriptomics, and proteomics. Journal of inherited metabolic disease. 2020; 43(1): 25-35. [View at Publisher] [DOI:10.1002/jimd.12130] [PubMed] [Google Scholar]
12. Guerrero RB, Kloke KM, Salazar D. Inborn Errors of Metabolism and the Gastrointestinal Tract. Gastroenterology Clinics. 2019; 48(2): 183-98. [View at Publisher] [DOI:10.1016/j.gtc.2019.02.001] [PubMed] [Google Scholar]
13. Ferreira CR, Cassiman D, Blau N. Clinical and biochemical footprints of inherited metabolic diseases. II. Metabolic liver diseases. Molecular genetics and metabolism. 2019; 127(2): 117-21. [View at Publisher] [DOI:10.1016/j.ymgme.2019.04.002] [PubMed] [Google Scholar]
14. Huang D, Zhou Q, Chao Y-Q, Zou C-C. Clinical features and genetic analysis of childhood sitosterolemia: Two case reports and literature review. Medicine. 2019;98(15). [DOI:10.1097/MD.0000000000015013] [PubMed] [Google Scholar]
15. Saudubray J-M, Garcia-Cazorla A. An overview of inborn errors of metabolism affecting the brain: from neurodevelopment to neurodegenerative disorders. Dialogues in clinical neuroscience. 2018;20(4):301. [DOI:10.31887/DCNS.2018.20.4/jmsaudubray] [PubMed] [Google Scholar]
16. Maestri NE, Brusilow SW, Clissold DB, Bassett SS. Long-term treatment of girls with ornithine transcarbamylase deficiency. New England Journal of Medicine. 1996; 335(12): 855-60. [View at Publisher] [DOI:10.1056/NEJM199609193351204] [PubMed] [Google Scholar]
17. Caldovic L, Abdikarim I, Narain S, Tuchman M, Morizono H. Genotype-phenotype correlations in ornithine transcarbamylase deficiency: A mutation update. Journal of Genetics and Genomics. 2015; 42(5): 181-94. [View at Publisher] [DOI:10.1016/j.jgg.2015.04.003] [PubMed] [Google Scholar]
18. Seegmiller JE, Rosenbloom FM, Kelley WN. Enzyme defect associated with a sex-linked human neurological disorder and excessive purine synthesis. Science. 1967;155(3770):1682-4. [View at Publisher] [DOI:10.1126/science.155.3770.1682] [PubMed] [Google Scholar]
19. Cusumano FJ, Penna KJ, Panossian G. Prevention of self-mutilation in patients with Lesch-Nyhan syndrome: review of literature. Journal of Dentistry for Children. 2001; 68(3): 175-8. [PubMed] [Google Scholar]
20. Lynch BJ, Noetzel MJ. Recurrent coma and Lesch-Nyhan syndrome. Pediatric neurology. 1991; 7(5): 389-91. [View at Publisher] [DOI:10.1016/0887-8994(91)90073-T] [PubMed] [Google Scholar]
21. Strauss KA, Wardley B, Robinson D, Hendrickson C, Rider NL, Puffenberger EG, et al. Classical maple syrup urine disease and brain development: principles of management and formula design. Molecular genetics and metabolism. 2010; 99(4): 333-45. [View at Publisher] [DOI:10.1016/j.ymgme.2009.12.007] [PubMed] [Google Scholar]
22. Blackburn PR, Gass JM, e Vairo FP, Farnham KM, Atwal HK, Macklin S, et al. Maple syrup urine disease: mechanisms and management. The application of clinical genetics. 2017;10:57. [DOI:10.2147/TACG.S125962] [PubMed] [Google Scholar]
23. Andresen BS, Dobrowolski SF, O'Reilly L, Muenzer J, McCandless SE, Frazier DM, et al. Medium-chain acyl-CoA dehydrogenase (MCAD) mutations identified by MS/MS-based prospective screening of newborns differ from those observed in patients with clinical symptoms: identification and characterization of a new, prevalent mutation that results in mild MCAD deficiency. The American Journal of Human Genetics. 2001; 68(6):1408-18. [View at Publisher] [DOI:10.1086/320602] [PubMed] [Google Scholar]
24. Roomets E, Lundbom N, Pihko H, Heikkinen S, Tyni T. Lipids detected by brain MRS during coma caused by carnitine palmitoyltransferase 1 deficiency. Neurology. 2006;67(8):1516-7. [DOI:10.1212/01.wnl.0000240118.82937.ed] [Google Scholar]
25. Wieser T. Carnitine Palmitoyltransferase II Deficiency. 2004 Aug 27 [updated 2019 Jan 3]. In: Adam MP, Ardinger HH, Pagon RA, Wallace SE, Bean LJH, Mirzaa G, Amemiya A, editors. GeneReviews® [Internet]. Seattle (WA): University of Washington, Seattle; 1993–2021. [PubMed]
26. Vanderver A, Prust M, Tonduti D, Mochel F, Hussey HM, Helman G, et al. Case definition and classification of leukodystrophies and leukoencephalopathies. Molecular genetics and metabolism. 2015;114(4):494-500. [View at Publisher] [DOI:10.1016/j.ymgme.2015.01.006] [PubMed] [Google Scholar]
27. Chabriat H, Vahedi K, Bousser M, Iba-Zizen M, Joutel A, Nibbio A, et al. Clinical spectrum of CADASIL: a study of 7 families. The Lancet. 1995;346(8980):934-9. [View at Publisher] [DOI:10.1016/S0140-6736(95)91557-5] [Google Scholar]
28. Eswaradass V, Ramasamy B, Kalidoss R, Gnanagurusamy G. Cadasil coma: Unusual cause for acute encephalopathy. Annals of Indian Academy of Neurology. 2015;18(4). [View at Publisher] [DOI:10.4103/0972-2327.160072] [PubMed] [Google Scholar]
29. Ophoff RA, Terwindt GM, Vergouwe MN, Van Eijk R, Oefner PJ, Hoffman SM, et al. Familial hemiplegic migraine and episodic ataxia type-2 are caused by mutations in the Ca 2+ channel gene CACNL1A4. Cell. 1996;87(3):543-52. [View at Publisher] [DOI:10.1016/S0092-8674(00)81373-2] [PubMed] [Google Scholar]
30. Smith MA, Katsouri L, Virtue S, Choudhury AI, Vidal-Puig A, Ashford ML, et al. Calcium channel CaV2. 3 subunits regulate hepatic glucose production by modulating leptin-induced excitation of arcuate pro-opiomelanocortin neurons. Cell reports. 2018;25(2):278-87. e4. [View at Publisher] [DOI:10.1016/j.celrep.2018.09.024] [PubMed] [Google Scholar]
31. Fouad Y, Waked I, Bollipo S, Gomaa A, Ajlouni Y, Attia D. What's in a name? Renaming 'NAFLD'to 'MAFLD'. Liver International. 2020. [View at Publisher] [DOI:10.1111/liv.14478] [PubMed] [Google Scholar]
32. Hadinia A, Doustimotlagh AH, Goodarzi HR, Arya A, Jafarinia M. Circulating levels of pro-inflammatory cytokines in patients with nonalcoholic fatty liver disease and non-alcoholic steatohepatitis. Iranian Journal of Immunology. 2019;16(4):327-33. [View at Publisher] [PubMed] [Google Scholar]
33. Borrelli A, Bonelli P, Tuccillo FM, Goldfine ID, Evans JL, Buonaguro FM, et al. Role of gut microbiota and oxidative stress in the progression of non-alcoholic fatty liver disease to hepatocarcinoma: Current and innovative therapeutic approaches. Redox biology. 2018;15:467-79. [View at Publisher] [DOI:10.1016/j.redox.2018.01.009] [PubMed] [Google Scholar]
34. Trépo E, Romeo S, Zucman-Rossi J, Nahon P. PNPLA3 gene in liver diseases. Journal of hepatology. 2016; 65(2): 399-412. [View at Publisher] [DOI:10.1016/j.jhep.2016.03.011] [Google Scholar]
35. Mardis ER. The impact of next-generation sequencing technology on genetics. Trends in genetics. 2008;24(3):133-41. [View at Publisher] [DOI:10.1016/j.tig.2007.12.007] [Google Scholar]
36. Illumina I. An introduction to next-generation sequencing technology. 2015. [View at Publisher]
37. Kuroda M, Ohta T, Uchiyama I, Baba T, Yuzawa H, Kobayashi I, et al. Whole genome sequencing of meticillin-resistant Staphylococcus aureus. The Lancet. 2001;357(9264):1225-40. [View at Publisher] [DOI:10.1016/S0140-6736(00)04403-2] [PubMed] [Google Scholar]
38. Van Dijk EL, Auger H, Jaszczyszyn Y, Thermes C. Ten years of next-generation sequencing technology. Trends in genetics. 2014; 30(9): 418-26. [View at Publisher] [DOI:10.1016/j.tig.2014.07.001] [Google Scholar]
39. Adhikari AN, Gallagher RC, Wang Y, Currier RJ, Amatuni G, Bassaganyas L, et al. The role of exome sequencing in newborn screening for inborn errors of metabolism. Nature Medicine. 2020;26(9):1392-7. [View at Publisher] [DOI:10.1038/s41591-020-0966-5] [PubMed] [Google Scholar]
40. Li R, Zhu H, Ruan J, Qian W, Fang X, Shi Z, et al. De novo assembly of human genomes with massively parallel short read sequencing. Genome research. 2010;20(2):265-72. [View at Publisher] [DOI:10.1101/gr.097261.109] [PubMed]
41. Damodaran S, Berger MF, Roychowdhury S. Clinical tumor sequencing: opportunities and challenges for precision cancer medicine. American Society of Clinical Oncology Educational Book. 2015;35(1):e175-e82. [View at Publisher] [DOI:10.14694/EdBook_AM.2015.35.e175] [PubMed] [Google Scholar]
42. Ponzi E, Maiorana A, Lepri FR, Mucciolo M, Semeraro M, Taurisano R, et al. Persistent hypoglycemia in children: Targeted gene panel improves the diagnosis of hypoglycemia due to inborn errors of metabolism. The Journal of pediatrics. 2018;202:272-8. e4. [View at Publisher] [DOI:10.1016/j.jpeds.2018.06.050] [PubMed] [Google Scholar]
43. Bevilacqua J, Hesse A, Cormier B, Davey J, Patel D, Shankar K, et al. Clinical utility of a 377 gene custom next-generation sequencing epilepsy panel. Journal of genetics. 2017;96(4):681-5. [View at Publisher] [DOI:10.1007/s12041-017-0791-x] [PubMed] [Google Scholar]
44. Xu Y, Gao S, Yang Y, Huang M, Cheng L, Wei Q, et al. Transcriptome sequencing and whole genome expression profiling of chrysanthemum under dehydration stress. BMC genomics. 2013;14(1):662. [View at Publisher] [DOI:10.1186/1471-2164-14-662] [PubMed] [Google Scholar]
45. Jen JC. Familial hemiplegic migraine. GeneReviews®[Internet]: University of Washington, Seattle; 2015. [PubMed]
46. Maksemous N, Smith RA, Haupt LM, Griffiths LR. Targeted next generation sequencing identifies novel NOTCH3 gene mutations in CADASIL diagnostics patients. Human genomics. 2016; 10(1): 1-12. [View at Publisher] [DOI:10.1186/s40246-016-0093-z] [PubMed] [Google Scholar]
47. Alameri M, Shakra M, Alsaadi T. Fatal coma in a young adult due to late-onset urea cycle deficiency presenting with a prolonged seizure: a case report. Journal of medical case reports. 2015;9(1):1-6. [View at Publisher] [DOI:10.1186/s13256-015-0741-2] [PubMed] [Google Scholar]
48. Ghorbani MJ, Razmi N, Tabei SMB, Zibaeenezhad MJ, Goodarzi HR. Genetic analysis of early onset familial coronary artery diseases. Archives of Medical Sciences Atherosclerotic Diseases. 2019;4:e1. [View at Publisher] [DOI:10.5114/amsad.2019.83149] [PubMed] [Google Scholar]
49. Maksemous N, Smith RA, Sutherland HG, Maher BH, Ibrahim O, Nicholson GA, et al. Targeted next generation sequencing identifies a genetic spectrum of DNA variants in patients with hemiplegic migraine. Cephalalgia Reports. 2019; 2: 1-9. [View at Publisher] [DOI:10.1177/2515816319881630] [Google Scholar]

Add your comments about this article : Your username or Email:
CAPTCHA

Send email to the article author


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2007 All Rights Reserved | Medical Laboratory Journal

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.