Genetic Screening of Plasticity Regulating Nogo-Type Signaling Genes in Migraine
Abstract
:1. Introduction
2. Material and Methods
3. Results
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Conflicts of Interest
References
- Vos, T.; Abajobir, A.A.; Abate, K.H.; Abbafati, C.; Abbas, K.M.; Abd-Allah, F.; Abdulkader, R.S.; Abdulle, A.M.; Abebo, T.A.; Abera, S.F.; et al. Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990–2016: A systematic analysis for the Global Burden of Disease Study 2016. Lancet 2017, 390, 1211–1259. [Google Scholar] [CrossRef] [Green Version]
- Burstein, R.; Noseda, R.; Borsook, D. Migraine: Multiple processes, complex Pathophysiology. J. Neurosci. 2015, 35, 6619–6629. [Google Scholar] [CrossRef] [PubMed]
- Schwedt, T.J.; Larson-Prior, L.; Coalson, R.S.; Nolan, T.; Mar, S.; Ances, B.M.; Benzinger, T.; Schlaggar, B.L. Allodynia and descending pain modulation in migraine: A resting state functional connectivity analysis. Pain Med. 2014, 15, 154–165. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Leone, M.; Proietti Cecchini, A. Advances in the understanding of cluster headache. Expert Rev. Neurother. 2017, 17, 165–172. [Google Scholar] [CrossRef] [PubMed]
- Stewart, W.F.; Linet, M.S.; Celentano, D.D.; Natta, M.V.; Ziegler, D. Age- and sex-specific incidence rates of migraine with and without visual aura. Am. J. Epidemiol. 1991, 134, 1111–1120. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Cui, Y.; Kataoka, Y.; Watanabe, Y. Role of cortical spreading depression in the pathophysiology of migraine. Neurosci. Bull. 2014, 30, 812–822. [Google Scholar] [CrossRef] [Green Version]
- Headache Classification Committee of the International Headache Society (IHS) The International Classification of Headache Disorders, 3rd edition. Cephalalgia 2018, 38, 1–211. [CrossRef]
- Manack, A.N.; Buse, D.C.; Lipton, R.B. Chronic migraine: Epidemiology and disease burden. Curr. Pain Headache Rep. 2011, 15, 70–78. [Google Scholar] [CrossRef]
- Dahlöf, C.; Linde, M. One-year prevalence of migraine in Sweden: A population-based study in adults. Cephalalgia 2001, 21, 664–671. [Google Scholar] [CrossRef]
- May, A.; Schulte, L.H. Chronic migraine: Risk factors, mechanisms and treatment. Nat. Rev. Neurol. 2016, 12, 455–464. [Google Scholar] [CrossRef]
- Rutberg, S.; Öhrling, K. Migraine—More than a headache: Women’s experiences of living with migraine. Disabil. Rehabil. 2012, 34, 329–336. [Google Scholar] [CrossRef]
- Vetvik, K.G.; MacGregor, E.A. Sex differences in the epidemiology, clinical features, and pathophysiology of migraine. Lancet Neurol. 2017, 16, 76–87. [Google Scholar] [CrossRef]
- Taşkapilioğlu, Ö.; Karli, N. Assessment of quality of life in migraine. Noropsikiyatri Ars. 2013, 50, S60–S64. [Google Scholar]
- Ball, H.; Samaan, Z.; Brewster, S.; Craddock, N.; Gill, M.; Korszun, A.; Maier, W.; Middleton, L.; Mors, O.; Owen, M.; et al. Depression, migraine with aura and migraine without wura: Their familiality and interrelatedness. Cephalalgia 2009, 29, 848–854. [Google Scholar] [CrossRef] [PubMed]
- Breslau, N.; Lipton, R.B.; Stewart, W.F.; Schultz, L.R.; Welch, K.M.A. Comorbidity of migraine and depression: Investigating potential etiology and prognosis. Neurology 2003, 60, 1308–1312. [Google Scholar] [CrossRef]
- Hamelsky, S.W.; Lipton, R.B. Psychiatric comorbidity of migraine. Headache J. Head Face Pain 2006, 46, 1327–1333. [Google Scholar] [CrossRef]
- De Boer, I.; van den Maagdenberg, A.M.J.M.; Terwindt, G.M. Advance in genetics of migraine. Curr. Opin. Neurol. 2019, 32, 413–421. [Google Scholar] [CrossRef]
- Stam, A.H.; de Vries, B.; Janssens, A.C.J.W.; Vanmolkot, K.R.J.; Aulchenko, Y.S.; Henneman, P.; Oostra, B.A.; Frants, R.R.; van den Maagdenberg, A.M.J.M.; Ferrari, M.D.; et al. Shared genetic factors in migraine and depression. Neurology 2010, 74, 288–294. [Google Scholar] [CrossRef] [Green Version]
- Yang, Y.; Zhao, H.; Boomsma, D.I.; Ligthart, L.; Belin, A.C.; Smith, G.D.; Esko, T.; Freilinger, T.M.; Hansen, T.F.; Ikram, M.A.; et al. Molecular genetic overlap between migraine and major depressive disorder. Eur. J. Hum. Genet. 2018, 26, 1202–1216. [Google Scholar] [CrossRef] [Green Version]
- Gormley, P.; Anttila, V.; Winsvold, B.S.; Palta, P.; Esko, T.; Pers, T.H.; Farh, K.-H.; Cuenca-Leon, E.; Muona, M.; Furlotte, N.A.; et al. Meta-analysis of 375,000 individuals identifies 38 susceptibility loci for migraine. Nat. Genet. 2016, 48, 856–866. [Google Scholar] [CrossRef] [Green Version]
- Colombo, B.; Rocca, M.A.; Messina, R.; Guerrieri, S.; Filippi, M. Resting-state fMRI functional connectivity: A new perspective to evaluate pain modulation in migraine? Neurol. Sci. 2015, 36, 41–45. [Google Scholar] [CrossRef] [PubMed]
- Coppola, G.; Petolicchio, B.; Di Renzo, A.; Tinelli, E.; Di Lorenzo, C.; Parisi, V.; Serrao, M.; Calistri, V.; Tardioli, S.; Cartocci, G.; et al. Cerebral gray matter volume in patients with chronic migraine: Correlations with clinical features. J. Headache Pain 2017, 18, 115. [Google Scholar] [CrossRef] [PubMed]
- Garcia-Larrea, L.; Bastuji, H. Pain and consciousness. Prog. Neuropsychopharmacol. Biol. Psychiatry 2017. [Google Scholar] [CrossRef] [PubMed]
- Liu, H.; Ge, H.; Xiang, J.; Miao, A.; Tang, L.; Wu, T.; Chen, Q.; Yang, L.; Wang, X. Resting state brain activity in patients with migraine: A magnetoencephalography study. J. Headache Pain 2015, 16. [Google Scholar] [CrossRef] [Green Version]
- Lovati, C.; Giani, L.; Mele, F.; Sinelli, A.; Tien, T.T.; Preziosa, G.; Mariani, C. Brain plasticity and migraine transformation: fMRI evidences. Expert Rev. Neurother. 2016, 16, 1413–1425. [Google Scholar] [CrossRef]
- Messina, R.; Rocca, M.A.; Colombo, B.; Pagani, E.; Falini, A.; Goadsby, P.J.; Filippi, M. Gray matter volume modifications in migraine: A cross-sectional and longitudinal study. Neurology 2018, 91, e280–e292. [Google Scholar] [CrossRef]
- Zhang, J.; Wu, Y.-L.; Su, J.; Yao, Q.; Wang, M.; Li, G.-F.; Zhao, R.; Shi, Y.-H.; Zhao, Y.; Zhang, Q.; et al. Assessment of gray and white matter structural alterations in migraineurs without aura. J. Headache Pain 2017, 18, 74. [Google Scholar] [CrossRef]
- Afridi, S.K.; Giffin, N.J.; Kaube, H.; Friston, K.J.; Ward, N.S.; Frackowiak, R.S.J.; Goadsby, P.J. A Positron emission tomographic study in spontaneous migraine. Arch. Neurol. 2005, 62, 1270–1275. [Google Scholar] [CrossRef] [Green Version]
- Akerman, S.; Romero-Reyes, M.; Holland, P.R. Current and novel insights into the neurophysiology of migraine and its implications for therapeutics. Pharmacol. Ther. 2017, 172, 151–170. [Google Scholar] [CrossRef]
- Maleki, N.; Becerra, L.; Brawn, J.; McEwen, B.; Burstein, R.; Borsook, D. Common hippocampal structural and functional changes in migraine. Brain Struct. Funct. 2013, 218, 903–912. [Google Scholar] [CrossRef] [Green Version]
- Neeb, L.; Bastian, K.; Villringer, K.; Israel, H.; Reuter, U.; Fiebach, J.B. Structural gray matter alterations in chronic migraine: Implications for a progressive disease? Headache J. Head Face Pain 2017, 57, 400–416. [Google Scholar] [CrossRef] [PubMed]
- Schmitz, N.; Admiraal-Behloul, F.; Arkink, E.B.; Kruit, M.C.; Schoonman, G.G.; Ferrari, M.D.; Buchem, M.A.V. Attack frequency and disease duration as indicators for brain damage in migraine. Headache J. Head Face Pain 2008, 48, 1044–1055. [Google Scholar] [CrossRef] [PubMed]
- Soheili-Nezhad, S.; Sedghi, A.; Schweser, F.; Eslami Shahr Babaki, A.; Jahanshad, N.; Thompson, P.M.; Beckmann, C.F.; Sprooten, E.; Toghae, M. Structural and functional reorganization of the brain in migraine without aura. Front. Neurol. 2019, 10. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Tolner, E.A.; Chen, S.-P.; Eikermann-Haerter, K. Current understanding of cortical structure and function in migraine. Cephalalgia 2019, 39, 1683–1699. [Google Scholar] [CrossRef] [PubMed]
- Yu, D.; Yuan, K.; Qin, W.; Zhao, L.; Dong, M.; Liu, P.; Yang, X.; Liu, J.; Sun, J.; Zhou, G.; et al. Axonal loss of white matter in migraine without aura: A tract-based spatial statistics study. Cephalalgia 2013, 33, 34–42. [Google Scholar] [CrossRef]
- Yuan, K.; Qin, W.; Liu, P.; Zhao, L.; Yu, D.; Zhao, L.; Dong, M.; Liu, J.; Yang, X.; von Deneen, K.M.; et al. Reduced fractional anisotropy of corpus callosum modulates inter-hemispheric resting state functional connectivity in migraine patients without aura. PLoS ONE 2012, 7, e45476. [Google Scholar] [CrossRef]
- Lai, T.-H.; Protsenko, E.; Cheng, Y.-C.; Loggia, M.L.; Coppola, G.; Chen, W.-T. Neural plasticity in common forms of chronic headaches. Neural Plast. 2015, 2015. [Google Scholar] [CrossRef] [Green Version]
- Schwab, M.E. Functions of Nogo proteins and their receptors in the nervous system. Nat. Rev. Neurosci. 2010, 11, 799–811. [Google Scholar] [CrossRef]
- Karlén, A.; Karlsson, T.E.; Mattsson, A.; Lundströmer, K.; Codeluppi, S.; Pham, T.M.; Bäckman, C.M.; Ogren, S.O.; Aberg, E.; Hoffman, A.F.; et al. Nogo receptor 1 regulates formation of lasting memories. Proc. Natl. Acad. Sci. USA 2009, 106, 20476–20481. [Google Scholar] [CrossRef] [Green Version]
- Karlsson, T.E.; Smedfors, G.; Brodin, A.T.S.; Åberg, E.; Mattsson, A.; Högbeck, I.; Wellfelt, K.; Josephson, A.; Brené, S.; Olson, L. NgR1: A tunable sensor regulating memory formation, synaptic, and dendritic plasticity. Cereb. Cortex 2016, 26, 1804–1817. [Google Scholar] [CrossRef] [Green Version]
- Kellner, Y.; Fricke, S.; Kramer, S.; Iobbi, C.; Wierenga, C.J.; Schwab, M.E.; Korte, M.; Zagrebelsky, M. Nogo-A controls structural plasticity at dendritic spines by rapidly modulating actin dynamics. Hippocampus 2016, 26, 816–831. [Google Scholar] [CrossRef] [PubMed]
- Zagrebelsky, M.; Lonnemann, N.; Fricke, S.; Kellner, Y.; Preuß, E.; Michaelsen-Preusse, K.; Korte, M. Nogo-A regulates spatial learning as well as memory formation and modulates structural plasticity in the adult mouse hippocampus. Neurobiol. Learn. Mem. 2017, 138, 154–163. [Google Scholar] [CrossRef] [PubMed]
- Josephson, A.; Widenfalk, J.; Widmer, H.W.; Olson, L.; Spenger, C. NOGO mRNA expression in adult and fetal human and rat nervous tissue and in weight drop injury. Exp. Neurol. 2001, 169, 319–328. [Google Scholar] [CrossRef] [PubMed]
- Smedfors, G.; Olson, L.; Karlsson, T.E. A Nogo-Like Signaling Perspective from Birth to Adulthood and in Old Age: Brain Expression Patterns of Ligands, Receptors and Modulators. Front. Mol. Neurosci. 2018, 11. [Google Scholar] [CrossRef] [Green Version]
- Cafferty, W.B.J.; Duffy, P.; Huebner, E.; Strittmatter, S.M. MAG and OMgp synergize with Nogo-A to restrict axonal growth and neurological recovery after spinal cord trauma. J. Neurosci. 2010, 30, 6825–6837. [Google Scholar] [CrossRef] [Green Version]
- Domeniconi, M.; Cao, Z.; Spencer, T.; Sivasankaran, R.; Wang, K.; Nikulina, E.; Kimura, N.; Cai, H.; Deng, K.; Gao, Y.; et al. Myelin-associated glycoprotein interacts with the Nogo66 receptor to inhibit neurite outgrowth. Neuron 2002, 35, 283–290. [Google Scholar] [CrossRef] [Green Version]
- Fournier, A.E.; GrandPre, T.; Strittmatter, S.M. Identification of a receptor mediating Nogo-66 inhibition of axonal regeneration. Nature 2001, 409, 341–346. [Google Scholar] [CrossRef]
- Niederöst, B.; Oertle, T.; Fritsche, J.; McKinney, R.A.; Bandtlow, C.E. Nogo-A and myelin-associated glycoprotein mediate neurite growth inhibition by antagonistic regulation of RhoA and Rac1. J. Neurosci. 2002, 22, 10368–10376. [Google Scholar] [CrossRef]
- Wang, K.C.; Koprivica, V.; Kim, J.A.; Sivasankaran, R.; Guo, Y.; Neve, R.L.; He, Z. Oligodendrocyte-myelin glycoprotein is a Nogo receptor ligand that inhibits neurite outgrowth. Nature 2002, 417, 941–944. [Google Scholar] [CrossRef]
- Ahmed, Z.; Douglas, M.R.; John, G.; Berry, M.; Logan, A. AMIGO3 is an NgR1/p75 co-receptor signalling axon growth inhibition in the acute phase of adult central nervous system injury. PLoS ONE 2013, 8, e61878. [Google Scholar] [CrossRef]
- Iobbi, C.; Korte, M.; Zagrebelsky, M. Nogo-66 restricts synaptic strengthening via Lingo1 and the ROCK2-Cofilin pathway to control actin dynamics. Cereb. Cortex 2017, 27, 2779–2792. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Park, J.B.; Yiu, G.; Kaneko, S.; Wang, J.; Chang, J.; He, X.L.; Garcia, K.C.; He, Z. A TNF receptor family member, TROY, is a coreceptor with Nogo receptor in mediating the inhibitory activity of myelin inhibitors. Neuron 2005, 45, 345–351. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Wang, K.C.; Kim, J.A.; Sivasankaran, R.; Segal, R.; He, Z. P75 interacts with the Nogo receptor as a co-receptor for Nogo, MAG and OMgp. Nature 2002, 420, 74–78. [Google Scholar] [CrossRef] [PubMed]
- Karlsson, T.E.; Wellfelt, K.; Olson, L. Spatiotemporal and long lasting modulation of 11 key Nogo signaling genes in response to strong neuroexcitation. Front. Mol. Neurosci. 2017, 10, 94. [Google Scholar] [CrossRef] [PubMed]
- Nordgren, M.; Karlsson, T.; Svensson, M.; Koczy, J.; Josephson, A.; Olson, L.; Tingström, A.; Brené, S. Orchestrated regulation of Nogo receptors, LOTUS, AMPA receptors and BDNF in an ECT model suggests opening and closure of a window of synaptic plasticity. PLoS ONE 2013, 8, e78778. [Google Scholar] [CrossRef] [PubMed]
- Post, R.M.; Silberstein, S.D. Shared mechanisms in affective illness, epilepsy, and migraine. Neurology 1994, 44, 37–47. [Google Scholar]
- Ran, C.; Graae, L.; Magnusson, P.K.; Pedersen, N.L.; Olson, L.; Belin, A.C. A replication study of GWAS findings in migraine identifies association in a Swedish case–control sample. BMC Med. Genet. 2014, 15, 38. [Google Scholar] [CrossRef] [Green Version]
- The International Classification of Headache Disorders: 2nd edition. Cephalalgia 2004, 24 (Suppl. 1), 9–160.
- Marees, A.T.; de Kluiver, H.; Stringer, S.; Vorspan, F.; Curis, E.; Marie-Claire, C.; Derks, E.M. A tutorial on conducting genome-wide association studies: Quality control and statistical analysis. Int. J. Methods Psychiatr. Res. 2018, 27. [Google Scholar] [CrossRef]
- Xu, Z.; Taylor, J.A. SNPinfo: Integrating GWAS and candidate gene information into functional SNP selection for genetic association studies. Nucleic Acids Res. 2009, 37, W600–W605. [Google Scholar] [CrossRef] [Green Version]
- Andreassen, O.A.; Thompson, W.K.; Schork, A.J.; Ripke, S.; Mattingsdal, M.; Kelsoe, J.R.; Kendler, K.S.; O’Donovan, M.C.; Rujescu, D.; Werge, T.; et al. Improved detection of common variants associated with schizophrenia and bipolar disorder using pleiotropy-informed conditional false discovery rate. PLoS Genet. 2013, 9. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Chang, C.C.; Chow, C.C.; Tellier, L.C.; Vattikuti, S.; Purcell, S.M.; Lee, J.J. Second-generation PLINK: Rising to the challenge of larger and richer datasets. Gigascience 2015, 4. [Google Scholar] [CrossRef] [PubMed]
- Purcell, S.; Neale, B.; Todd-Brown, K.; Thomas, L.; Ferreira, M.; Bender, D.; Maller, J.; Sklar, P.; de Bakker, P.; Daly, M.; et al. PLINK: A toolset for whole-genome association and population-based linkage analysis. Am. J. Hum. Genet. 2007, 81, 559–575. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- GAS Power Calculator. Available online: http://csg.sph.umich.edu/abecasis/cats/gas_power_calculator/ (accessed on 10 September 2019).
- SNP—NCBI. Available online: https://www.ncbi.nlm.nih.gov/snp/ (accessed on 10 September 2019).
- Barrett, J.C.; Fry, B.; Maller, J.; Daly, M.J. Haploview: Analysis and visualization of LD and haplotype maps. Bioinformatics 2005, 21, 263–265. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- RStudio Team RStudio: Integrated Development for R. RStudio. Available online: http://www.rstudio.com/ (accessed on 5 July 2019).
- R Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2019; Available online: http://www.R-project.org/ (accessed on 5 July 2019).
- Zhang, K.; Calabrese, P.; Nordborg, M.; Sun, F. Haplotype block structure and its applications to association studies: Power and study designs. Am. J. Hum. Genet. 2002, 71, 1386–1394. [Google Scholar] [CrossRef] [Green Version]
- Bonafede, M.; Sapra, S.; Shah, N.; Tepper, S.; Cappell, K.; Desai, P. Direct and indirect healthcare resource utilization and costs among migraine patients in the United States. Headache J. Head Face Pain 2018, 58, 700–714. [Google Scholar] [CrossRef]
- Ruszczycki, B.; Szepesi, Z.; Wilczynski, G.M.; Bijata, M.; Kalita, K.; Kaczmarek, L.; Wlodarczyk, J. Sampling issues in quantitative analysis of dendritic spines morphology. BMC Bioinform. 2012, 13, 213. [Google Scholar] [CrossRef] [Green Version]
- Harriott, A.M.; Schwedt, T.J. Migraine is associated with altered processing of sensory stimuli. Curr. Pain Headache Rep. 2014, 18, 458. [Google Scholar] [CrossRef]
Controls | Cases | Total | Migraine Frequency | |
---|---|---|---|---|
Men (%) | 2138 (53.0) | 162 (21.6) | 2300 | 7.0% |
Women (%) | 1894 (47.0) | 587 (78.4) | 2481 | 23.7% |
Total | 4032 | 749 | 4781 | 15.7% |
Chr | Gene Symbol | TAG SNPs of Interest | Replacement SNP | After Exclusion of SNPs in LD with r2 > 0.2 |
---|---|---|---|---|
2 | RTN4 | rs6545465 | rs17046589 | rs17046589 |
2 | RTN4 | rs7562292 | rs6545466 | - |
2 | RTN4 | rs10084445 | rs6715980 | rs6715980 |
2 | RTN4 | rs7584386 | rs7584354 | - |
2 | RTN4 | rs2580765 | - | rs2580765 |
2 | RTN4 | rs17046594 | rs17046570 | - |
2 | RTN4 | rs3198123 | - | - |
2 | RTN4 | rs2580769 | - | - |
2 | RTN4 | rs2588517 | - | - |
2 | RTN4 | rs2588519 | - | - |
2 | RTN4 | rs2864052 | - | - |
2 | RTN4 | rs10496037 | - | rs10496037 |
2 | RTN4 | rs2920898 | - | - |
15 | LINGO1 | rs907395 | rs907396 | rs907396 |
15 | LINGO1 | rs8024724 | rs8023571 | rs8023571 |
15 | LINGO1 | rs3743481 | - | - |
15 | LINGO1 | rs7162113 | - | - |
15 | LINGO1 | rs3144 | - | rs3144 |
15 | LINGO1 | rs1877298 | rs8028788 | rs8028788 |
17 | OMG | rs11080149 | - | rs11080149 |
19 | MAG | rs12461927 | rs720308 | - |
19 | MAG | rs12185485 | rs3746248 | - |
19 | MAG | rs10414549 | - | - |
19 | MAG | rs9304870 | - | rs9304870 |
19 | MAG | rs6510476 | - | rs6510476 |
19 | MAG | rs2301600 | - | rs2301600 |
19 | MAG | rs10411883 | rs11669734 | - |
22 | RTN4R | rs854971 | rs701427 | rs701427 |
22 | RTN4R | rs1567871 | - | rs1567871 |
22 | RTN4R | rs855050 | - | rs855050 |
22 | RTN4R | rs1807466 | - | - |
22 | RTN4R | rs887765 | - | - |
Gene | SNP | Function | Minor Allele | MAF NCBI | MAF Cases | MAF Controls | OR (95% CI) | P-Value | Corrected P-Value |
---|---|---|---|---|---|---|---|---|---|
RTN4 | rs2580765 | Intron | C | 0.46 | 0.46 | 0.43 | 1.09 (0.97–1.22) | 0.14 | 1 |
RTN4 | rs6715980 | Intron | A | 0.06 | 0.07 | 0.07 | 1.04 (0.83–1.29) | 0.76 | 1 |
RTN4 | rs17046589 | Intron | G | 0.22 | 0.18 | 0.18 | 1.003 (0.87–1.16) | 0.96 | 1 |
RTN4 | rs10496037 | Intron | T | 0.11 | 0.12 | 0.11 | 1.08 (0.91–1.29) | 0.36 | 1 |
LINGO1 | rs3144 | 3’ UTR region | C | 0.40 | 0.37 | 0.37 | 0.97 (0.86–1.09) | 0.56 | 1 |
LINGO1 | rs907396 | Intron | G | 0.40 | 0.40 | 0.38 | 1.1 (0.98–1.24) | 0.11 | 1 |
LINGO1 | rs8023571 | Intron | T | 0.12 | 0.12 | 0.12 | 1.02 (0.86–1.22) | 0.79 | 1 |
LINGO1 | rs8028788 | Intron | C | 0.04 | 0.05 | 0.04 | 1.17 (0.91–1.52) | 0.23 | 1 |
OMGP | rs11080149 | Coding | T | 0.14 | 0.17 | 0.15 | 1.08 (0.92–1.25) | 0.35 | 1 |
MAG | rs6510476 | Intron | G | 0.16 | 0.18 | 0.18 | 1.01 (0.87–1.17) | 0.92 | 1 |
MAG | rs2301600 | Coding | T | 0.24 | 0.25 | 0.23 | 1.07 (0.94–1.22) | 0.33 | 1 |
MAG | rs9304870 | Intron | G | 0.33 | 0.38 | 0.38 | 1.03 (0.91–1.15) | 0.66 | 1 |
RTN4R | rs701427 | Intron | A | 0.31 | 0.32 | 0.34 | 0.93 (0.83–1.05) | 0.26 | 1 |
RTN4R | rs1567871 | Intron | T | 0.26 | 0.25 | 0.25 | 1.0 (0.88–1.14) | 1.00 | 1 |
RTN4R | rs855050 | Intron | G | 0.49 | 0.51 | 0.50 | 1.04 (0.93–1.17) | 0.47 | 1 |
Block | Haplotype | Frequency | Case-Control Frequencies | P-Value | |
---|---|---|---|---|---|
LINGO1 | rs907396 rs8023571 | CC | 0.41 | 0.43/0.41 | 0.17 |
AC | 0.34 | 0.32/0.34 | 0.21 | ||
CT | 0.25 | 0.25/0.25 | 0.83 | ||
MAG | rs6510476 rs2301600 | AC | 0.59 | 0.58/0.59 | 0.23 |
AT | 0.23 | 0.25/0.23 | 0.18 | ||
GC | 0.18 | 0.18/0.18 | 0.96 | ||
RTN4R | rs701427 rs1567871 | TC | 0.50 | 0.49/0.50 | 0.26 |
GC | 0.38 | 0.39/0.38 | 0.26 | ||
TT | 0.12 | 0.12/0.12 | 0.89 |
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Smedfors, G.; Liesecke, F.; Ran, C.; Olson, L.; Karlsson, T.E.; Carmine Belin, A. Genetic Screening of Plasticity Regulating Nogo-Type Signaling Genes in Migraine. Brain Sci. 2020, 10, 5. https://doi.org/10.3390/brainsci10010005
Smedfors G, Liesecke F, Ran C, Olson L, Karlsson TE, Carmine Belin A. Genetic Screening of Plasticity Regulating Nogo-Type Signaling Genes in Migraine. Brain Sciences. 2020; 10(1):5. https://doi.org/10.3390/brainsci10010005
Chicago/Turabian StyleSmedfors, Gabriella, Franziska Liesecke, Caroline Ran, Lars Olson, Tobias E. Karlsson, and Andrea Carmine Belin. 2020. "Genetic Screening of Plasticity Regulating Nogo-Type Signaling Genes in Migraine" Brain Sciences 10, no. 1: 5. https://doi.org/10.3390/brainsci10010005
APA StyleSmedfors, G., Liesecke, F., Ran, C., Olson, L., Karlsson, T. E., & Carmine Belin, A. (2020). Genetic Screening of Plasticity Regulating Nogo-Type Signaling Genes in Migraine. Brain Sciences, 10(1), 5. https://doi.org/10.3390/brainsci10010005