The End of Snoring? Application of CRISPR/Cas9 Genome Editing for Sleep Disorders
Science selected it as the 2015 Breakthrough of the Year: Clustered Regularly Interspaced Short Palindromic Repeats, also known as CRISPR. Adaptive immunity in some bacteria and archaea allow to respond and eliminate invading genetic material; CRISPR and CRISPR-associated (Cas) genes are new molecular techniques that allow deleting, replacing or otherwise editing DNA. Using modified bacterial protein and a RNA that allows a guidance to a specific DNA sequence, CRISPR provides a striking control over several genes by not deleting the entire gene but just inactivating it by deleting few bases. CRISPR/Cas9 has been used to generate knockout cells or animals by co-expressing a gRNA specific to the gene to be targeted and the endonuclease Cas9. This novel system has been tested in diverse species, with promising potential uses in humans. Theoretically, CRISPR/Cas9 will be able to remove genetic mutations related to incurable diseases, such as HIV, and certain cancer types. This scenario draws tentative and promising conditions using CRISPR/Cas9 as preventive and therapeutic tool in medical area. As expected, several groups have begun to test the putative gene editing properties of CRISPR/Cas9 on human cells. Since sleep disorders have been linked with specific genes, in this review, we suggest areas that require further investigation and experimental and/or clinical approaches to treat sleep disturbances using CRISPR/Cas9.
KeywordsGene Somnolence DNA Insomnia Sleep Therapy
1 Gene Expression: An Overview
Genes are subunits of DNA, the information database of a cell that is contained inside the cell nucleus and conform to the basic physical and functional units of heredity. These DNA subunits carry the genetic blueprint that is used to make all the proteins the cell needs. Every gene contains a particular set of instructions that code for a specific protein and the production of these functional molecules is the gene expression [1, 2]. There are two types of genes: regulating and constitutive. The first ones indicate the level of expression of the constitutive genes, which are the ones that produce a single-stranded RNA molecule, derived from a portion of the double-stranded DNA templates. By the expression of specific DNA motifs in the control regions of the regulating genes, the DNA segment is “read” by an enzyme called RNA polymerase, which produces the strand of RNA that is complimentary to the DNA. In this strand, some structural changes take place so that in some cases, the RNA molecule itself is a “finished product” that serves some important function within the cell. Often, however, transcription of an RNA molecule is followed by a translation step, which ultimately results in the production of a protein molecule [3, 4, 5].
For transcription to occur, the area around a prospective transcription zone needs to be unwound. This is a complex process requiring the coordinated modification of basic proteins that associate with DNA in the nucleus and help condense it into chromatin (histones), transcription factor binding and other chromatin remodeling activities. This primary RNA transcript is then modified to convert it into mature messenger RNA (mRNA) that can be used in translation. Interestingly, not all regions of an mRNA molecule correspond to particular aminoacids, the molecules that are then linked together in a chain by a ribosome to create a rudimentary protein chain. The mRNA undergoes splicing of its regions to remove the non-coding parts of the transcript being the introns, so that only the coding sections being the exons remain. This part is called processing and right after this step, the final mRNA carries the information needed to code for proteins, which will transform into a functional protein [4, 6, 7].
Importantly, there is extensive natural variation in human gene expression. Every person has two copies of each gene, one inherited from each parent. Most genes are the same in the population, but a small number of genes (less than 1 percent of the total) are slightly different between people. This characteristic is determined by the presence of various alleles, forms of the same gene with small differences in their sequence of DNA bases. These small differences contribute to each person’s unique physical features. As quantitative phenotypes, expression levels of genes are heritable . As a result, every human being has its own genetic information, inherited from its progenitor, which determines their anatomical characteristics, normal physiology and their predisposition to certain pathologic processes.
2 Gene Expression in Pathological Conditions
Given the complex mechanism of gene expression, it is not a surprise to know that many of its steps can be altered in several ways conditioning the cell to an aberrant development. In humans, this situation is traduced to illnesses such as cancer, diabetes, Alzheimer’s disease, osteoporosis and many others caused by a dysregulation in the gene expression. One example of this scenario is the abnormal expression in gene profile of all adipogenic markers that are not expressed in diabetic cells after differentiation . An additional most common example of altered gene expression in human health aspects is cancer. In this regard, it was demonstrated that protein Semaphorin-3E (Sema3E) is overexpressed in human pancreatic cancer, and that high Sema3E levels are associated with tumor progression. Critically, Sema3E is a member of an axon guidance gene family, and has been reported as a contributor to tumor progression and metastasis. Moreover, overexpression of Sema3E in pancreatic cancer cells promotes cell proliferation and migration in vitro, and increases tumor incidence. Conversely, experimental animals (knockout) of Sema3E suppressed cancer cell proliferation and reduced tumor incidence and size in vivo .
Lastly, osteoporosis is a common disease in the adult population due to the normal decalcification enhanced by multiple causes including a diet deficient in vitamin D or calcium, alcoholism, tabaquism and genetic causes. Recently, the diagnostic potential of circulating miRNAs for postmenopausal osteoporosis has been investigated and some miRNAs were identified as potential biomarkers .
3 Sleep Disorders and Gene Modulation
Genes associated with sleep disturbances
Genes associated with sleep disturbances
1. Circadian genes (CLOCK, Timeless) Per2, 3
2. Serotonin transporter polymorphic region (5-HTTLPR)
3. Orexin/hypocretin gene
4. Catecholamine-O-methyltransferase (COMT) gene
5. Dopamine receptor D4 (DRD4) gene
6. Dopamine transporter 1 (DAT1) gene
7. ABCC9 gene (rs11046209) gene
Obstructive sleep apnea
1. Inflammatory factors: IL-6, IL-8, and TNF-α genes
2. 5-Hydroxytryptamine receptor 2A (5-HTR2A) gene
1. Human leukocyte antigen (HLA)-DRB1 × 15:01-DQB1 × 06:02 haplotype
2. Chemokine (C–C motif) receptor 1 (CCR1) gene
Advanced sleep phase syndrome
1. PER 1, 2, and 3
4. Cryptochrome genes 1 and 2
5. Arnt-like protein-1 (Bmal1/Aryl
6. Hydrocarbon receptor nuclear translocator-like (ARNTL1) gene
Restless legs syndrome
1. IL-ß gene
2. MEIS1 gene
3.1 Genes and Insomnia
Insomnia comprises the difficulty to initiate or maintain sleep. Multiple studies have described the role of circadian genes (CLOCK, Timeless) in subjects with mood disorders showing a putative relationship with insomnia [18, 19, 20, 21]. For instance, a significant association between Per3 and insomnia was described by Brower and coworkers (2012) . Similar findings were found when period 2 gene (Per2) was associated with insomnia . Another gene candidate related to insomnia has been the serotonin transporter polymorphic region (5-HTTLPR), adenosine, GABA and orexin/hypocretin . In addition, several studies have also indicated the engagement of other wake-related neurotransmitter systems such as dopaminergic system genes (i.e., catecholamine-O-methyltransferase (COMT), dopamine receptor D4 (DRD4), and dopamine transporter 1 (DAT1; [18, 24]). Lastly, the genome-wide association studies (GWAS) have identified novel genes that also appear to be linked to insomnia. For instance a significant association of the ABCC9 gene (rs11046209) with sleep duration has been described in insomniac patients [25, 26, 27, 28]. An overview of the genes related to insomnia is shown in Table 1.
3.2 Obstructive Sleep Apnea and Genes
Obstructive sleep apnea (OSA) is a sleep disturbance characterized by repeated cessation or attenuation of breathing (named “apneas” and “hypopneas”, respectively) during sleep. Moreover, OSA is associated with a wide range of morbidities including metabolic, cardiovascular, coronary artery disease, hypertension, arrhythmia, heart failure, and cognitive dysfunction or even sudden cardiac death . The first-line treatment given to OSA patients includes the use of continuous positive airway pressure (CPAP; [29, 30]). The molecular mechanisms underlying OSA remain unclear, and could be mediated, in part, by OSA-induced genes. In this regard, Cade and coworkers (2016) carried out GWAS in 12,558 Hispanic subjects finding two novel loci at genome level with significance for apnea–hypopnea index .
On the other side, a different perspective has been developed regarding the study of genes related to OSA. For example, the pathogenesis of this sleep disturbance is the result of a multifactorial process related to a wide variety of mechanisms, including the engagement of inflammatory responses. As expected, inflammatory factors, such as IL-6, IL-8, and TNF-α, have been found highly expressed in subjects with OSA [32, 33]. Therefore, genes related to inflammation may be involved in OSA.
At present, variants of the 5-hydroxytryptamine receptor 2A (5-HTR2A) and interleukin-6 (IL-6) genes may be susceptible markers to develop for OSA. Intriguingly, associations between the 5-HTR2A and IL-6 single nucleotide polymorphisms (SNPs) and OSA have been recently described . Thus, the role of inflammatory response genes in OSA seems to be a critical factor as a pivotal phenomenon that impacts directly the onset of this sleep disorder  (Table 1).
3.3 Genetic Basis of Narcolepsy
Narcolepsy is a life-long condition characterized by two major symptoms, excessive daytime sleepiness and cataplexy. It is widely accepted that the human leukocyte antigen (HLA)-DRB1 × 15:01-DQB1 × 06:02 haplotype is strongly associated with narcolepsy [36, 37, 38]. However, non-HLA susceptibility genes have been also related to this sleep disorder. Recently, Toyoda and coworkers (2015) reported that according to GWAS 525,196 single nucleotide polymorphisms (SNPs) were located outside the HLA region . Moreover, it was found that narcolepsy was associated with a SNP in the promoter region of chemokine (C–C motif) receptor 1 (CCR1). Further evidence has indicated that narcolepsy with cataplexy is tightly associated with the HLA class II allele DQB1 × 06:02  (Table 1).
3.4 Genes Related to Advanced Sleep Phase Syndrome
Circadian rhythmicity has been described in multiple physiological functions, including the onset or development of pathological issues, such as sleep disturbances [41, 42, 43, 44, 45]. The advance sleep phase syndrome is one example of a circadian rhythm disorder. Subjects with complaint of early evening bedtimes and early morning awakenings belong to the category of advance sleep phase syndrome. In contrast, the delayed sleep phase disorder corresponds with late bedtimes and late awakenings [46, 47]. Circadian rhythm contributes to sleep–wake cycle control by activation of specific genes. For example, approximately 10% of the population are homozygous for the 5-repeat allele (PER3(5/5)) of a variable number tandem repeat polymorphism in the clock gene Per-3. What has been found is that PER3(5/5) is associated with morning preference, whereas homozygosity for the four-repeat allele (PER3(4/4)) is linked with evening preference . The association between sleep timing and the circadian rhythms are crucial for sleep onset as well as for development of sleep disorders, such as sleep phase syndrome.
Approximately 20 clock genes have been characterized, including the key genes such as PER 1, 2, and 3, the cryptochrome genes 1 and 2, and brain and muscle arnt-like protein-1 (Bmal1/Aryl hydrocarbon receptor nuclear translocator-like [ARNTL1], [49, 50]). Among these genes, some have been associated with diurnal preference. For example, a significant association between diurnal preference and a polymorphism in Per-3 and diurnal preference and a polymorphism in aryl hydrocarbon receptor nuclear translocator-like 2 (ARNTL2) has been described . Recent evidence has pointed-out a significant gene-associated loci with morningness. Furthermore, Hu et al. (2016) reported that a GWAS analysis of self-reported morningness showed 15 significantly associated loci, including seven circadian genes . These findings as well as other reports [53, 54, 55, 56, 57] suggest that genes with circadian expression may play a critical role in regulating both the circadian clock and sleep homeostasis as well as circadian-related sleep disturbances such as advanced sleep phase syndrome (Table 1).
3.5 Genes Associated with Restless Legs Syndrome
The restless legs syndrome is a sleep disorder characterized by the urge to move the legs during sleep. The pathophysiology of this sleep disturbance is low iron concentration in the substantia nigra of dopamine neurons that project to the striatum, a critical brain area for modulating movement [58, 59]. Despite the medial advances in the understanding of the genesis of this sleep disorder, the genetics of restless legs syndrome are still unknown. Recent data have identified several genes as candidates for restless legs syndrome development, including IL-ß or BTBD9 [60, 61]. Moreover, since restless legs syndrome has familial aggregation, GWAS association studies have identified single nucleotide polymorphisms linked to this sleep disturbance, including SNP at loci MEIS1 [62, 63, 64]. Although restless legs syndrome etiology may be multifactorial, a significant body of gene-related evidence has been piled up, and these findings, taken together, support the hypothesis that this sleep disturbance may have a genetic component [58, 59, 60, 62, 65, 66, 67, 68] (Table 1).
4 CRISPR–Cas9: A Novel Molecular Approach for Gene Editing
Given the amount of diseases associated with “simple” errors in gene modulation and expression, several gene editing techniques have been developed aimed to treat these pathological conditions. Thus, inducible loss of gene function experiments is necessary to uncover mechanisms underlying development, physiology and disease . One of these gene editing techniques is known as Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR). The functions of CRISPR and CRISPR-associated (Cas) genes are essential for adaptive immunity in selected bacteria and archaea enabling the organisms to respond in an efficient manner to eliminate the invading genetic material using short-guide RNAs (sgRNAs) to target and destroy the DNA of exogenous pathogens. This biological phenomenon was observed for the first time in 2007 when a yogurt company identified a bacteria that could remember viruses. CRISPR obtained its name from the observation of remnants of bacterial genomes from previous infections, sandwiched between odd, and DNA sequence repeatedly, with unique sequences in between the duplications. Then, this mechanism was named “clustered regularly interspaced short palindromic repeats,” or CRISPR. Later, between 2012 and 2013, diverse experimental groups experimented with CRISPR in combination with other gene editing tools. Then in 2015, a novel technique for gene editing named CRISPR was published in Science [70, 71].
Briefly, CRISPR uses a guide RNA to send biological “scissors”—usually the CRISPR-associated protein, Cas9—to a precise spot to cut in a genome. Once Cas9 enzymatically cuts, the cell engages healing mechanism in the wounded DNA, one of these mechanisms of repair leads to knockouts, whereas the second leads to knockins . Later, the cell is able to function with altered DNA and continue the normal gene expression. Three types of CRISPR mechanisms have been identified, of which type II is the most studied. In this case, invading DNA from viruses or plasmids is cut into small fragments and incorporated into a CRISPR locus amidst a series of short repeats. Then, loci are transcribed, and transcripts are processed to generate small RNAs, which in turn guide endonucleases to target invading DNA based on sequence complementarity .
The advent of site-specific nucleases, particularly CRISPR/Cas9, provides the ability to manipulate genomic sequences, with special interest for develop treatments for human diseases [73, 74]. The biomedical applications of CRISPR are just starting to emerge with a promising active role in the ability to remove genetic mutations associated with diseases, such as cystic fibrosis, HIV, and even certain types of cancers [75, 76, 77, 78, 79, 80]. The authors share interest about the audacious investigations of CRISPR/Cas9-editing genes in insomnia, OSA, narcolepsy, advanced sleep phase syndrome, or restless legs syndrome.
5 Application of CRISPR/Cas9-Based Gene Therapy for Managing Sleep Disorders
At last, considering the large degree of phenotypic variance in clinical presentation of sleep disturbances and the risk for sleep-associated morbidities, further studies should also consider detailed assessments for specific gene editing to gain increased insights into the potential genetic pathways involved in sleep disturbances. This scenario will present the possibility prior to a diagnosis of sleep disorders and perhaps even prior to the prodromal phase of sleep disturbances.
Sleep abnormalities such as insomnia, OSA, narcolepsy, advanced sleep phase syndrome and restless legs syndrome, among many others seem to have a genetic basis. Currently, CRISPR–Cas9 is an experimental technique that allows genome editing, targeting, and regulation in a wide range of organisms and cell types. The progress and the future potential of the CRISPR–Cas9 towards biomedical area are quite interesting. In this regard, novel uses of CRISPR–Cas9 as therapeutic tool for treating sleep disorders represent a new tempting research horizon. Using animal models of sleep disorders, it might be a convenient strategy for studying the putative benefits of CRISPR–Cas9 in sleep-related gene edition. We expect that in the coming years, further advances in the sleep medicine field would be achieved by gene edition experimental approach.
Compliance with Ethical Standards
All data reported in this paper are from public repositories.
This work was supported by The University of California Institute for Mexico and the United States (UC MEXUS) and Consejo Nacional de Ciencia y Tecnología (CONACyT(Grant(CN-17-19) and Escuela de Medicina, Universidad Anáhuac Mayab Grant (PresInvEMR2014) given to E.M.-R.
Conflict of interest
Authors declare no conflict of interest.
- 12.American Academy of Sleep Medicine, International classification of sleep disorders: diagnostic and coding manual, 3rd edn. Darien, IL, USA.: American Academy of Sleep Medicine; 2014.Google Scholar
- 21.Utge SJ, Soronen P, Loukola A, Kronholm E, Ollila HM, Pirkola S, Porkka-Heiskanen T, Partonen T, Paunio T. Systematic analysis of circadian genes in a population-based sample reveals association of TIMELESS with depression and sleep disturbance. PLoS One. 2010;5:e9259.CrossRefPubMedPubMedCentralGoogle Scholar
- 27.Ollila HM, Kettunen J, Pietiläinen O, Aho V, Silander K, Kronholm E, Perola M, Lahti J, Räikkönen K, Widen E, Palotie A, Eriksson JG, Partonen T, Kaprio J, Salomaa V, Raitakari O, Lehtimäki T, Sallinen M, Härmä M, Porkka-Heiskanen T, Paunio T. Genome-wide association study of sleep duration in the Finnish population. J Sleep Res. 2016;23:609–18.CrossRefGoogle Scholar
- 31.Cade BE, Chen H, Stilp AM, Gleason KJ, Sofer T, Ancoli-Israel S, Arens R, Bell GI, Below JE, Bjonnes AC, Chun S, Conomos MP, Evans DS, Johnson WC, Frazier-Wood AC, Lane JM, Larkin EK, Loredo JS, Post WS, Ramos AR, Rice K, Rotter JI, Shah NA, Stone KL, Taylor KD, Thornton TA, Tranah GJ, Wang C, Zee PC, Hanis CL, Sunyaev SR, Patel SR, Laurie CC, Zhu X, Saxena R, Lin X, Redline S. Genetic associations with obstructive sleep apnea traits in Hispanic/Latino Americans. Am J Resp Crit Care Med. 2016;194:886–97.CrossRefPubMedPubMedCentralGoogle Scholar
- 37.Han F, Lin L, Schormair B, Pizza F, Plazzi G, Ollila HM, Nevsimalova S, Jennum P, Knudsen S, Winkelmann J, Coquillard C, Babrzadeh F, Strom TM, Wang C, Mindrinos M, Fernandez Vina M, Mignot E. HLA DQB1*06:02 negative narcolepsy with hypocretin/orexin deficiency. Sleep. 2014;37:1601–8.CrossRefPubMedPubMedCentralGoogle Scholar
- 38.Miyagawa T, Toyoda H, Hirataka A, Kanbayashi T, Imanishi A, Sagawa Y, Kotorii N, Kotorii T, Hashizume Y, Ogi K, Hiejima H, Kamei Y, Hida A, Miyamoto M, Imai M, Fujimura Y, Tamura Y, Ikegami A, Wada Y, Moriya S, Furuya H, Kato M, Omata N, Kojima H, Kashiwase K, Saji H, Khor SS, Yamasaki M, Wada Y, Ishigooka J, Kuroda K, Kume K, Chiba S, Yamada N, Okawa M, Hirata K, Uchimura N, Shimizu T, Inoue Y, Honda Y, Mishima K, Honda M, Tokunaga K. New susceptibility variants to narcolepsy identified in HLA class II region. Human Mol Gen. 2015;24:891–8.CrossRefGoogle Scholar
- 39.Toyoda H, Miyagawa T, Koike A, Kanbayashi T, Imanishi A, Sagawa Y, Kotorii N, Kotorii T, Hashizume Y, Ogi K, Hiejima H, Kamei Y, Hida A, Miyamoto M, Imai M, Fujimura Y, Tamura Y, Ikegami A, Wada Y, Moriya S, Furuya H, Takeuchi M, Kirino Y, Meguro A, Remmers EF, Kawamura Y, Otowa T, Miyashita A, Kashiwase K, Khor SS, Yamasaki M, Kuwano R, Sasaki T, Ishigooka J, Kuroda K, Kume K, Chiba S, Yamada N, Okawa M, Hirata K, Mizuki N, Uchimura N, Shimizu T, Inoue Y, Honda Y, Mishima K, Honda M, Tokunaga K. A polymorphism in CCR1/CCR3 is associated with narcolepsy. Brain Behav Imm. 2015;49:148–55.CrossRefGoogle Scholar
- 40.Tafti M, Lammers GJ, Dauvilliers Y, Overeem S, Mayer G, Nowak J, Pfister C, Dubois V, Eliaou JF, Eberhard HP, Liblau R, Wierzbicka A, Geisler P, Bassetti CL, Mathis J, Lecendreux M, Khatami R, Heinzer R, Haba-Rubio J, Feketeova E, Baumann CR, Kutalik Z, Tiercy JM. Narcolepsy-associated HLA class I alleles implicate cell-mediated cytotoxicity. Sleep. 2016;39:581–7.CrossRefPubMedPubMedCentralGoogle Scholar
- 53.Amin N, Allebrandt KV, van der Spek A, Müller-Myhsok B, Hek K, Teder-Laving M, Hayward C, Esko T, van Mill JG, Mbarek H, Watson NF, Melville SA, Del Greco FM, Byrne EM, Oole E, Kolcic I, Chen TH, Evans DS, Coresh J, Vogelzangs N, Karjalainen J, Willemsen G, Gharib SA, Zgaga L, Mihailov E, Stone KL, Campbell H, Brouwer RW, Demirkan A, Isaacs A, Dogas Z, Marciante KD, Campbell S, Borovecki F, Luik AI, Li M, Hottenga JJ, Huffman JE, van den Hout MC, Cummings SR, Aulchenko YS, Gehrman PR, Uitterlinden AG, Wichmann HE, Müller-Nurasyid M, Fehrmann RS, Montgomery GW, Hofman A, Kao WH, Oostra BA, Wright AF, Vink JM, Wilson JF, Pramstaller PP, Hicks AA, Polasek O, Punjabi NM, Redline S, Psaty BM, Heath AC, Merrow M, Tranah GJ, Gottlieb DJ, Boomsma DI, Martin NG, Rudan I, Tiemeier H, van Ijcken WF, Penninx BW, Metspalu A, Meitinger T, Franke L, Roenneberg T, van Duijn CM. Genetic variants in RBFOX3 are associated with sleep latency. Eur J Human Gen. 2016;24:1488–95.CrossRefGoogle Scholar
- 54.Cade BE, Gottlieb DJ, Lauderdale DS, Bennett DA, Buchman AS, Buxbaum SG, De Jager PL, Evans DS, Fülöp T, Gharib SA, Johnson WC, Kim H, Larkin EK, Lee SK, Lim AS, Punjabi NM, Shin C, Stone KL, Tranah GJ, Weng J, Yaffe K, Zee PC, Patel SR, Zhu X, Redline S, Saxena R. Common variants in DRD2 are associated with sleep duration: the CARe consortium. Human Mol Gen. 2016;25:167–79.CrossRefGoogle Scholar
- 66.García-Martín E, Jiménez-Jiménez FJ, Alonso-Navarro H, Martínez C, Zurdo M, Turpín-Fenoll L, Millán-Pascual J, Adeva-Bartolomé T, Cubo E, Navacerrada F, Rojo-Sebastián A, Rubio L, Ortega-Cubero S, Pastor P, Calleja M, Plaza-Nieto JF, Pilo-de-la-Fuente B, Arroyo-Solera M, García-Albea E, Agúndez JA. Heme oxygenase-1 and 2 common genetic variants and risk for restless legs syndrome. Medicine. 2015;94:e1448.CrossRefPubMedPubMedCentralGoogle Scholar
- 67.Winkelman JW, Blackwell T, Stone K, Ancoli-Israel S, Tranah GJ, Redline S, Osteoporotic Fractures in Men (MrOS) Study Research Group. Genetic associations of periodic limb movements of sleep in the elderly for the MrOS sleep study. Sleep Med. 2015;16:1360–665.CrossRefPubMedPubMedCentralGoogle Scholar
- 68.Jiménez-Jiménez FJ, García-Martí E, Alonso-Navarro H, Martínez C, Zurdo M, Turpín-Fenoll L, Millán-Pascual J, Adeva-Bartolomé T, Cubo E, Navacerrada F, Rojo-Sebastián A, Rubio L, Ortega-Cubero S, Pastor P, Calleja M, Plaza-Nieto JF, Pilo-de-la-Fuente B, Arroyo-Solera M, García-Albea E, Agúndez JA. Thr105Ile (rs11558538) polymorphism in the histamine-1-methyl-transferase (HNMT) gene and risk for restless legs syndrome. J Neural Transm. 2016;124:285–91.CrossRefPubMedGoogle Scholar
- 69.Bertero A, Pawlowski M, Ortmann D, Snijders K, Yiangou L, Cardoso de Brito M, Brown S, Bernard WG, Cooper JD, Giacomelli E, Gambardella L, Hannan NR, Iyer D, Sampaziotis F, Serrano F, Zonneveld MC, Sinha S, Kotter M, Vallier L. Optimized inducible shRNA and CRISPR/Cas9 platforms for in vitro studies of human development using hPSCs. Dev. 2016;143:4405–18.CrossRefGoogle Scholar
- 76.Doerflinger M, Forsyth W, Ebert G, Pellegrini M, Herold MJ. CRISPR/Cas9-The ultimate weapon to battle infectious diseases? Cell Microbiol. 2017;19:e12693.Google Scholar