Sex-stratified genome-wide association study of multisite chronic pain in UK Biobank
Autoři:
Keira J. A. Johnston aff001; Joey Ward aff001; Pradipta R. Ray aff004; Mark J. Adams aff002; Andrew M. McIntosh aff002; Blair H. Smith aff005; Rona J. Strawbridge aff001; Theodore J. Price aff004; Daniel J. Smith aff001; Barbara I. Nicholl aff001; Mark E. S. Bailey aff003
Působiště autorů:
Institute of Health and Wellbeing, University of Glasgow, Glasgow, Scotland, United Kingdom
aff001; Division of Psychiatry, University of Edinburgh, Edinburgh, Scotland, United Kingdom
aff002; School of Life Sciences, College of Medical, Veterinary & Life Sciences, University of Glasgow, Glasgow, Scotland, United Kingdom
aff003; School of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, Texas, United States of America
aff004; Division of Population Health Sciences, University of Dundee, Ninewells Hospital and Medical School, Dundee, Scotland, United Kingdom
aff005; Department of Medicine Solna, Karolinska Institute, Stockholm, Sweden
aff006
Vyšlo v časopise:
Sex-stratified genome-wide association study of multisite chronic pain in UK Biobank. PLoS Genet 17(4): e1009428. doi:10.1371/journal.pgen.1009428
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pgen.1009428
Souhrn
Chronic pain is highly prevalent worldwide and imparts a significant socioeconomic and public health burden. Factors influencing susceptibility to, and mechanisms of, chronic pain development, are not fully understood, but sex is thought to play a significant role, and chronic pain is more prevalent in women than in men. To investigate sex differences in chronic pain, we carried out a sex-stratified genome-wide association study of Multisite Chronic Pain (MCP), a derived chronic pain phenotype, in UK Biobank on 178,556 men and 209,093 women, as well as investigating sex-specific genetic correlations with a range of psychiatric, autoimmune and anthropometric phenotypes and the relationship between sex-specific polygenic risk scores for MCP and chronic widespread pain. We also assessed whether MCP-associated genes showed expression pattern enrichment across tissues. A total of 123 SNPs at five independent loci were significantly associated with MCP in men. In women, a total of 286 genome-wide significant SNPs at ten independent loci were discovered. Meta-analysis of sex-stratified GWAS outputs revealed a further 87 independent associated SNPs. Gene-level analyses revealed sex-specific MCP associations, with 31 genes significantly associated in females, 37 genes associated in males, and a single gene, DCC, associated in both sexes. We found evidence for sex-specific pleiotropy and risk for MCP was found to be associated with chronic widespread pain in a sex-differential manner. Male and female MCP were highly genetically correlated, but at an rg of significantly less than 1 (0.92). All 37 male MCP-associated genes and all but one of 31 female MCP-associated genes were found to be expressed in the dorsal root ganglion, and there was a degree of enrichment for expression in sex-specific tissues. Overall, the findings indicate that sex differences in chronic pain exist at the SNP, gene and transcript abundance level, and highlight possible sex-specific pleiotropy for MCP. Results support the proposition of a strong central nervous-system component to chronic pain in both sexes, additionally highlighting a potential role for the DRG and nociception.
Klíčová slova:
Gene expression – Genetic loci – Genetics – Genome-wide association studies – Human genetics – Metaanalysis – Pain – Single nucleotide polymorphisms
Zdroje
1. Merskey H, Bogduk N. Classification of Chronic Pain. IASP Pain Terminology. 1994. 240 p.
2. IASP. International Association for the Study of Pain [Internet]. [cited 2020 Apr 14]. Available from: https://www.iasp-pain.org/
3. Nicholasa M, Vlaeyenb JWS, Riefe W, Barkee A, Azizf Q, Benolielg R, et al. The IASP classification of chronic pain for ICD-11: Chronic primary pain. Pain. 2019;160(1):53–9. doi: 10.1097/j.pain.0000000000001365 30586071
4. Gureje O, Von Korff M, Kola L, Demyttenaere K, He Y, Posada-Villa J, et al. The relation between multiple pains and mental disorders: Results from the World Mental Health Surveys. Pain. 2008;135(1–2):82–91. doi: 10.1016/j.pain.2007.05.005 17570586
5. Von Korff M, Crane P, Lane M, Miglioretti DL, Simon G, Saunders K, et al. Chronic spinal pain and physical-mental comorbidity in the United States: Results from the national comorbidity survey replication. Pain. 2005;113(3):331–9. doi: 10.1016/j.pain.2004.11.010 15661441
6. Santos-Eggimann B, Wietlisbach V, Rickenbach M, Paccaud F, Gutzwiller F. One-year prevalence of low back pain in two Swiss regions. Estimates from the population participating in the 1992–1993 MONICA project. Spine (Phila Pa 1976). 2000;25(19):2473–9. doi: 10.1097/00007632-200010010-00009 11013499
7. Palmer KT, Walsh K, Bendall H, Cooper C, Coggon D. Back pain in Britain: Comparison of two prevalence surveys at an interval of 10 years. Br Med J. 2000;320(7249):1577–8. doi: 10.1136/bmj.320.7249.1577 10845966
8. Goldberg DS, McGee SJ. Pain as a global public health priority. BMC Public Health [Internet]. 2011;11(1):770. Available from: http://www.biomedcentral.com/1471-2458/11/770 doi: 10.1186/1471-2458-11-770 21978149
9. Breivik H, Collett B, Ventafridda V, Cohen R, Gallacher D. Survey of chronic pain in Europe: Prevalence, impact on daily life, and treatment. Eur J Pain. 2006;10(4):287–333. doi: 10.1016/j.ejpain.2005.06.009 16095934
10. James SL, Abate D, Abate KH, Abay SM, Abbafati C, Abbasi N, et al. Global, regional, and national incidence, prevalence, and years lived with disability for 354 Diseases and Injuries for 195 countries and territories, 1990–2017: A systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2018;1789–858. doi: 10.1016/S0140-6736(18)32279-7 30496104
11. Von Korff M, Ormel J, Keefe FJ, Dworkin SF. Grading the severity of chronic pain. Pain [Internet]. 1992;50(1092):133–49. Available from: http://www.ncbi.nlm.nih.gov/pubmed/1408309 doi: 10.1016/0304-3959(92)90154-4 1408309
12. Hocking LJ, Morris AD, Dominiczak AF, Porteous DJ, Smith BH. Heritability of chronic pain in 2195 extended families. Eur J Pain (United Kingdom). 2012;16(7):1053–63. doi: 10.1002/j.1532-2149.2011.00095.x 22337623
13. Junqueira DRG, Ferreira ML, Refshauge K, Maher CG, Hopper JL, Hancock M, et al. Heritability and lifestyle factors in chronic low back pain: Results of the Australian Twin Low Back Pain Study (The AUTBACK study). Eur J Pain (United Kingdom). 2014;18(10):1410–8. doi: 10.1002/ejp.506 24733726
14. Williams FMK, Spector TD, MacGregor AJ. Pain reporting at different body sites is explained by a single underlying genetic factor. Rheumatology. 2010;49(9):1753–5. doi: 10.1093/rheumatology/keq170 20525736
15. McIntosh AM, Hall LS, Zeng Y, Adams MJ, Gibson J, Wigmore E, et al. Genetic and Environmental Risk for Chronic Pain and the Contribution of Risk Variants for Major Depressive Disorder: A Family-Based Mixed-Model Analysis. PLoS Med. 2016;13(8):1–17. doi: 10.1371/journal.pmed.1002090 27529168
16. Suri P, Palmer MR, Tsepilov YA, Freidin MB, Boer CG, Yau MS, et al. Genome-wide meta-analysis of 158,000 individuals of European ancestry identifies three loci associated with chronic back pain. 2018;48(7):1–23.
17. Johnston KJA, Adams MJ, Nicholl BI, Ward J, Strawbridge RJ, Ferguson A, et al. Genome-wide association study of multisite chronic pain in UK Biobank. PLoS Genet. 2019;15(6):1–22. doi: 10.1371/journal.pgen.1008164 31194737
18. Rawlik K, Canela-Xandri O, Tenesa A. Evidence for sex-specific genetic architectures across a spectrum of human complex traits. Genome Biol [Internet]. 2016;17(1):1–8. Available from: http://dx.doi.org/10.1186/s13059-016-1025-x 27473438
19. Khramtsova EA, Davis LK, Stranger BE. The role of sex in the genomics of human complex traits. Nat Rev Genet [Internet]. 2019;20(3):173–90. Available from: doi: 10.1038/s41576-018-0083-1 30581192
20. Xu X, Coats JK, Yang CF, Wang A, Ahmed OM, Alvarado M, et al. Modular genetic control of sexually dimorphic behaviors. Cell [Internet]. 2012;148(3):596–607. Available from: doi: 10.1016/j.cell.2011.12.018 22304924
21. Quinn MA, Cidlowski JA. Endogenous hepatic glucocorticoid receptor signaling coordinates sex-biased inflammatory gene expression. FASEB J. 2016;30(2):971–82. doi: 10.1096/fj.15-278309 26581598
22. McCormick H, Young PE, Hur SSJ, Booher K, Chung H, Cropley JE, et al. Isogenic mice exhibit sexually-dimorphic DNA methylation patterns across multiple tissues. BMC Genomics. 2017;18(1):1–9. doi: 10.1186/s12864-016-3406-7 28049423
23. Gilks WP, Abbott JK, Morrow EH. Sex differences in disease genetics: Evidence, evolution, and detection. Trends Genet [Internet]. 2014;30(10):453–63. Available from: doi: 10.1016/j.tig.2014.08.006 25239223
24. Ge T, Chen CY, Neale BM, Sabuncu MR, Smoller JW. Phenome-wide heritability analysis of the UK Biobank. PLoS Genet. 2017;13(4):1–21. doi: 10.1371/journal.pgen.1006711 28388634
25. Rahmioglu N, MacGregor S, Drong AW, Hedman ÅK, Harris HR, Randall JC, et al. Genome-wide enrichment analysis between endometriosis and obesity-related traits reveals novel susceptibility loci. Hum Mol Genet. 2015;24(4):1185–99. doi: 10.1093/hmg/ddu516 25296917
26. Hall E, Volkov P, Dayeh T, Esguerra JL o. S, Salö S, Eliasson L, et al. Sex differences in the genome-wide DNA methylation pattern and impact on gene expression, microRNA levels and insulin secretion in human pancreatic islets. Genome Biol. 2014;15(12):522. doi: 10.1186/s13059-014-0522-z 25517766
27. Kukurba KR, Parsana P, Balliu B, Smith KS, Zappala Z, Knowles DA, et al. Impact of the X chromosome and sex on regulatory variation. Genome Res. 2016;26(6):768–77. doi: 10.1101/gr.197897.115 27197214
28. Yao C, Joehanes R, Johnson AD, Huan T, Esko T, Ying S, et al. Sex- and age-interacting eQTLs in human complex diseases. Hum Mol Genet [Internet]. 2013 Nov 15;23(7):1947–56. Available from: doi: 10.1093/hmg/ddt582 24242183
29. Kósa JP, Balla B, Speer G, Kiss J, Borsy A, Podani J, et al. Effect of menopause on gene expression pattern in bone tissue of nonosteoporotic women. Menopause. 2009;16(2):367–77. doi: 10.1097/gme.0b013e318188b260 19512969
30. Gomez-Santos C, Hernandez-Morante JJ, Margareto J, Larrarte E, Formiguera X, Martínez CM, et al. Profile of adipose tissue gene expression in premenopausal and postmenopausal women: Site-specific differences. Menopause. 2011;18(6):675–84. doi: 10.1097/gme.0b013e31820641da 21358552
31. Mitra I, Tsang K, Ladd-Acosta C, Croen LA, Aldinger KA, Hendren RL, et al. Pleiotropic Mechanisms Indicated for Sex Differences in Autism. PLoS Genet. 2016;12(11):1–27. doi: 10.1371/journal.pgen.1006425 27846226
32. Bartley EJ, Fillingim RB. Sex differences in pain: A brief review of clinical and experimental findings. Br J Anaesth. 2013;111(1):52–8. doi: 10.1093/bja/aet127 23794645
33. Fillingim RB, King CD, Ribeiro-Dasilva MC, Rahim-Williams B, Riley JL. Sex, Gender, and Pain: A Review of Recent Clinical and Experimental Findings. J Pain [Internet]. 2009;10(5):447–85. Available from: doi: 10.1016/j.jpain.2008.12.001 19411059
34. Fillingim RB. Biopsychosocial contributions to sex differences in pain. BJOG An Int J Obstet Gynaecol. 2015;122(6):769. doi: 10.1111/1471-0528.13337 25752330
35. El-Shormilisy N, Strong J, Meredith PJ. Associations among gender, coping patterns and functioning for individuals with chronic pain: A systematic review. Pain Res Manag. 2015;20(1):48–55. doi: 10.1155/2015/490610 24927488
36. Sorge RE, Mapplebeck JCS, Rosen S, Beggs S, Taves S, Alexander JK, et al. Different immune cells mediate mechanical pain hypersensitivity in male and female mice. Nat Neurosci. 2015;18(8):1081–3. doi: 10.1038/nn.4053 26120961
37. Sorge RE, Totsch SK. Review Sex Differences in Pain. 2017;1281(February 2016):1271–81.
38. Agalave NM, Rudjito R, Farinotti AB, Khoonsari PE, Sandor K, Nomura Y, et al. Sex-dependent role of microglia in disulfide HMGB1-mediated mechanical hypersensitivity. Pain. 2020;Articles i.
39. Klein SL, Flanagan KL. Sex differences in immune responses. Nat Rev Immunol. 2016;16(10):626–38. doi: 10.1038/nri.2016.90 27546235
40. Smith BH, Campbell A, Linksted P, Fitzpatrick B, Jackson C, Kerr SM, et al. Cohort profile: Generation scotland: Scottish family health study (GS: SFHS). The study, its participants and their potential for genetic research on health and illness. Int J Epidemiol. 2013;
41. Strawbridge RJ, Ward J, Ferguson A, Graham N, Shaw RJ, Cullen B, et al. Identification of novel genome-wide associations for suicidality in UK Biobank, genetic correlation with psychiatric disorders and polygenic association with completed suicide. EBioMedicine [Internet]. 2019;41:517–25. Available from: doi: 10.1016/j.ebiom.2019.02.005 30745170
42. Ward J, Tunbridge EM, Sandor C, Lyall LM, Ferguson A, Strawbridge RJ, et al. The genomic basis of mood instability: identification of 46 loci in 363,705 UK Biobank participants, genetic correlation with psychiatric disorders, and association with gene expression and function. Mol Psychiatry [Internet]. 2019; Available from: http://dx.doi.org/10.1038/s41380-019-0439-8
43. Okifuji A, Benham B. Suicidal and Self-Harm Behaviors in Chronic. J Appl Biobehav Res. 2011;16(2):57–77.
44. Nock MK, Borges G, Bromet EJ, Cha CB, Kessler RC, Lee S. Suicide and Suicidal Behavior Matthew. Epidemiol Rev. 2008;30(1):133–54.
45. Cheatle MD. Depression, chronic pain, and suicide by overdose: On the edge. Pain Med. 2011;12(SUPPL. 2):43–8.
46. Tang NKY, Crane C. Suicidality in chronic pain: A review of the prevalence, risk factors and psychological links. Psychol Med. 2006;36(5):575–86. doi: 10.1017/S0033291705006859 16420727
47. Triñanes Y, González-Villar A, Gómez-Perretta C, Carrillo-de-la-Peña MT. Suicidality in Chronic Pain: Predictors of Suicidal Ideation in Fibromyalgia. Pain Pract. 2015;15(4):323–32. doi: 10.1111/papr.12186 24690160
48. Smith MT, Edwards RR, Robinson RC, Dworkin RH. Suicidal ideation, plans, and attempts in chronic pain patients: Factors associated with increased risk. Pain. 2004;111(1–2):201–8. doi: 10.1016/j.pain.2004.06.016 15327824
49. de Leeuw CA, Mooij JM, Heskes T, Posthuma D. MAGMA: Generalized Gene-Set Analysis of GWAS Data. PLoS Comput Biol. 2015;11(4). doi: 10.1371/journal.pcbi.1004219 25885710
50. LaCroix-Fralish ML, Ledoux JB, Mogil JS. The Pain Genes Database: An interactive web browser of pain-related transgenic knockout studies. Pain. 2007;131(1–2):3.e1–3.e4. doi: 10.1016/j.pain.2007.04.041 17574758
51. Tappe-Theodor A, Constantin CE, Tegeder I, Lechner SG, Langeslag M, Lepcynzsky P, et al. Gα q/11 signaling tonically modulates nociceptor function and contributes to activity-dependent sensitization. Pain [Internet]. 2012;153(1):184–96. Available from: doi: 10.1016/j.pain.2011.10.014 22071319
52. Watanabe K, Taskesen E, Van Bochoven A, Posthuma D. Functional mapping and annotation of genetic associations with FUMA. Nat Commun. 2017;8(1):1–10. doi: 10.1038/s41467-016-0009-6 28232747
53. Aguet F, Brown AA, Castel SE, Davis JR, He Y, Jo B, et al. Genetic effects on gene expression across human tissues. Nature. 2017;550(7675):204–13. doi: 10.1038/nature24277 29022597
54. Ray P, Torck A, Quigley L, Wangzhou A, Neiman M, Rao C, et al. Comparative transcriptome profiling of the human and mouse dorsal root ganglia. Pain. 2018;159(7):1325–45. doi: 10.1097/j.pain.0000000000001217 29561359
55. Watanabe K, Taskesen E, Van Bochoven A, Posthuma D. Functional mapping and annotation of genetic associations with FUMA. Nat Commun [Internet]. 2017;8(1):1–10. Available from: doi: 10.1038/s41467-016-0009-6 28232747
56. Liberzon A, Birger C, Ghandi M, Jill P, Tamayo P, Jolla L, et al. The Molecular Signatures Database (MSigDB) hallmark gene set collection. Cell Syst. 2015;1(6):417–25. doi: 10.1016/j.cels.2015.12.004 26771021
57. Liberzon A, Subramanian A, Pinchback R, Thorvaldsdóttir H, Tamayo P, Mesirov JP. Molecular signatures database (MSigDB) 3.0. Bioinformatics. 2011;27(12):1739–40. doi: 10.1093/bioinformatics/btr260 21546393
58. Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, et al. Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A. 2005;102(43):15545–50. doi: 10.1073/pnas.0506580102 16199517
59. McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University (Baltimore M. Online Mendelian Inheritance in Man, OMIM [Internet]. [cited 2020 Oct 7]. Available from: omim.org
60. Wishart DS, Knox C, Guo AC, Shrivastava S, Hassanali M, Stothard P, et al. DrugBank: a comprehensive resource for in silico drug discovery and exploration. Nucleic Acids Res. 2006;34(Database issue):668–72. doi: 10.1093/nar/gkj067 16381955
61. Winkler TW, Justice AE, Graff M, Barata L, Feitosa MF, Chu S, et al. The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study. Vol. 11, PLoS Genetics. 2015. 1–42 p. doi: 10.1371/journal.pgen.1005378 26426971
62. Randall JC, Winkler TW, Kutalik Z, Berndt SI, Jackson AU, Monda KL, et al. Sex-stratified Genome-wide Association Studies Including 270,000 Individuals Show Sexual Dimorphism in Genetic Loci for Anthropometric Traits. PLoS Genet. 2013;9(6). doi: 10.1371/journal.pgen.1003500 23754948
63. Myers RA, Scott NM, Gauderman WJ, Qiu W, Mathias RA, Romieu I, et al. Genome-wide interaction studies reveal sex-specific asthma risk alleles. Hum Mol Genet. 2014;23(19):5251–9. doi: 10.1093/hmg/ddu222 24824216
64. Prendergast L, van Vuuren C, Kaczmarczyk A, Doering V, Hellwig D, Quinn N, et al. Premitotic Assembly of Human CENPs -T and -W switches centromeric Chromatin to a mitotic state. PLoS Biol. 2011;9(6):1–12. doi: 10.1371/journal.pbio.1001082 21695110
65. Lee S, Gang J, Jeon SB, Choo SH, Lee B, Kim YG, et al. Molecular cloning and functional analysis of a novel oncogene, cancer-upregulated gene 2 (CUG2). Biochem Biophys Res Commun. 2007;360(3):633–9. doi: 10.1016/j.bbrc.2007.06.102 17610844
66. Chun Y, Park B, Koh W, Lee S, Cheon Y, Kim R, et al. New centromeric component CENP-W Is an RNA-associated nuclear matrix protein that interacts with nucleophosmin/B23 protein. J Biol Chem. 2011;286(49):42758–69. doi: 10.1074/jbc.M111.228411 22002061
67. Schwarz M, Andrade-Navarro MA, Gross A. Mitochondrial carriers and pores: Key regulators of the mitochondrial apoptotic program? Apoptosis. 2007;12(5):869–76. doi: 10.1007/s10495-007-0748-2 17453157
68. Willer CJ, Speliotes EK, Loos RJF, Li S, Lindgren CM, Heid IM, et al. Six new loci associated with body mass index highlight a neuronal influence on body weight regulation. Nat Genet. 2009;41(1):25–34. doi: 10.1038/ng.287 19079261
69. Yu K, Ganesan K, Tan LK, Laban M, Wu J, Xiao DZ, et al. A precisely regulated gene expression cassette potently modulates metastasis and survival in multiple solid cancers. PLoS Genet. 2008;4(7). doi: 10.1371/journal.pgen.1000129 18636107
70. Renström F, Payne F, Nordström A, Brito EC, Rolandsson O, Hallmans G, et al. Replication and extension of genome-wide association study results for obesity in 4923 adults from northern Sweden. Hum Mol Genet. 2009;18(8):1489–96. doi: 10.1093/hmg/ddp041 19164386
71. Backofen B, Jacob R, Serth K, Gossler A, Naim HY, Leeb T. Cloning and characterization of the mammalian-specific nicolin 1 gene (NICN1) encoding a nuclear 24 kDA protein. Eur J Biochem. 2002;269(21):5240–5. doi: 10.1046/j.1432-1033.2002.03232.x 12392556
72. Alderson TRR, Kim JHH, Markley JLL. Dynamical Structures of Hsp70 and Hsp70-Hsp40 Complexes. Structure [Internet]. 2016;24(7):1014–30. Available from: doi: 10.1016/j.str.2016.05.011 27345933
73. Pencheva N, Tran H, Buss C, Huh D, Drobnjak M, Busam K, et al. Convergent multi-mRNA Targeting of ApoE Drives LRP1/LRP8-Dependent Melanoma Metastasis and Angiogenesis. Cell. 2012;151(5):1068–82. doi: 10.1016/j.cell.2012.10.028 23142051
74. Rauch U, Karthikeyan L, Maurel P, Margolis RU, Margolis RK. Cloning and primary structure of neurocan, a developmentally regulated, aggregating chondroitin sulfate proteoglycan of brain. J Biol Chem. 1992;267(27):19536–47. 1326557
75. Cichon S, Mühleisen TW, Degenhardt FA, Mattheisen M, Miró X, Strohmaier J, et al. Genome-wide association study identifies genetic variation in neurocan as a susceptibility factor for bipolar disorder. Am J Hum Genet. 2011;88(3):372–81. doi: 10.1016/j.ajhg.2011.01.017 21353194
76. Miró X, Meier S, Dreisow ML, Frank J, Strohmaier J, Breuer R, et al. Studies in humans and mice implicate neurocan in the etiology of mania. Am J Psychiatry. 2012;169(9):982–90. doi: 10.1176/appi.ajp.2012.11101585 22952076
77. Zhu CH, Kim J, Shay JW, Wright WE. SGNP: An essential stress granule/nucleolar protein potentially involved in 5.8s rRNA processing/transport. PLoS One. 2008;3(11). doi: 10.1371/journal.pone.0003716 19005571
78. Islam TC, Asplund AC, Lindvall JM, Nygren L, Liden J, Kimby E, et al. High level cannabinoid receptor 1, resistance of regulator G protein signaling 13 and differential expression of Cyclin D1 in mantle cell lymphoma. Leukemia. 2003;17(9):1880–90. doi: 10.1038/sj.leu.2403057 12970790
79. Nozawa T, Sano S, Minowa-Nozawa A, Toh H, Nakajima S, Murase K, et al. TBC1D9 regulates TBK1 activation through Ca2+ signaling in selective autophagy. Nat Commun [Internet]. 2020;11(1):1–16. Available from: doi: 10.1038/s41467-019-13993-7 31911652
80. Verploegen S, Lammers JWJ, Koenderman L, Coffer PJ. Identification and characterization of CKLiK, a novel granulocyte Ca++/calmodulin-dependent kinase. Blood. 2000;96(9):3215–23. 11050006
81. Bhattaram P, Penzo-Méndez A, Sock E, Colmenares C, Kaneko KJ, Vassilev A, et al. Organogenesis relies on SoxC transcription factors for the survival of neural and mesenchymal progenitors. Nat Commun. 2010;1(1):1–12. doi: 10.1038/ncomms1008 20596238
82. Jay P, Gozé C, Marsollier C, Taviaux S, Hardelin JP, Koopman P, et al. The human SOX11 Gene: Cloning, chromosomal assignment and tissue expression. Genomics. 1995;29(2):541–5. doi: 10.1006/geno.1995.9970 8666406
83. Haslinger A, Schwarz TJ, Covic M, Chichung Lie D. Expression of Sox11 in adult neurogenic niches suggests a stage-specific role in adult neurogenesis. Eur J Neurosci. 2009;29(11):2103–14. doi: 10.1111/j.1460-9568.2009.06768.x 19490090
84. Bergsland M, Werme M, Malewicz M, Perlmann T, Muhr J. The establishment of neuronal properties is controlled by Sox4 and Sox11. Genes Dev. 2006;20(24):3475–86. doi: 10.1101/gad.403406 17182872
85. Larson BL, Ylostalo J, Lee RH, Gregory C, Prockop DJ. Sox11 is expressed in early progenitor human multipotent stromal cells and decreases with extensive expansion of the cells. Tissue Eng—Part A. 2010;16(11):3385–94. doi: 10.1089/ten.tea.2010.0085 20626275
86. Tsurusaki Y, Koshimizu E, Ohashi H, Phadke S, Kou I, Shiina M, et al. De novo SOX11 mutations cause Coffin-Siris syndrome. Nat Commun. 2014;5:1–7. doi: 10.1038/ncomms5011 24886874
87. Kuryshev VY, Vorobyov E, Zink D, Schmitz J, Rozhdestvensky TS, Münstermann E, et al. An anthropoid-specific segmental duplication on human chromosome 1q22. Genomics. 2006;88(2):143–51. doi: 10.1016/j.ygeno.2006.02.002 16545939
88. Kikuno R, Nagase T, Ishikawa K, Hirosawa M, Miyajima N, TANAKA A, et al. Prediction of the Coding Sequences of Unidentified Human Genes. XIV. The Complete Sequences of 100 New cDNA Clones from Brain Which Code for Large Proteins in vitro. DNA Res. 1999;205:197–205. doi: 10.1093/dnares/6.3.197 10470851
89. Bisogno T, Howell F, Williams G, Minassi A, Cascio MG, Ligresti A, et al. Cloning of the first sn1-DAG lipases points to the spatial and temporal regulation of endocannabinoid signaling in the brain. J Cell Biol. 2003;163(3):463–8. doi: 10.1083/jcb.200305129 14610053
90. Manitt C, Mimee A, Eng C, Pokinko M, Stroh T, Cooper HM, et al. The Netrin Receptor DCC Is Required in the Pubertal Organization of Mesocortical Dopamine Circuitry. J Neurosci. 2011;31(23):8381–94. doi: 10.1523/JNEUROSCI.0606-11.2011 21653843
91. Srour M, Rivière JB, Pham JMT, Dubé MP, Girard S, Morin S, et al. Mutations in DCC cause congenital mirror movements. Science (80-). 2010;328(5978):592. doi: 10.1126/science.1186463 20431009
92. Savage JE, Jansen PR, Stringer S, Watanabe K, Bryois J, De Leeuw CA, et al. Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence. Nat Genet. 2018;50(7):912–9. doi: 10.1038/s41588-018-0152-6 29942086
93. Lee JJ, Wedow R, Okbay A, Kong E, Maghzian O, Zacher M, et al. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nat Genet. 2018;50(8):1112–21. doi: 10.1038/s41588-018-0147-3 30038396
94. Satizabal CL, Adams HHH, Hibar DP, White CC, Knol MJ, Stein JL, et al. Genetic architecture of subcortical brain structures in 38,851 individuals. Nat Genet. 2019;51(11):1624–36. doi: 10.1038/s41588-019-0511-y 31636452
95. Li HJ, Qu N, Hui L, Cai X, Zhang CY, Zhong BL, et al. Further confirmation of netrin 1 receptor (DCC) as a depression risk gene via integrations of multi-omics data. Transl Psychiatry. 2020;10(1). doi: 10.1038/s41398-020-0777-y 32184385
96. Torres-Berrío A, Hernandez G, Nestler EJ, Flores C. The Netrin-1/DCC Guidance Cue Pathway as a Molecular Target in Depression: Translational Evidence. Biol Psychiatry [Internet]. 2020; Available from: doi: 10.1016/j.biopsych.2020.04.025 32593422
97. Wright KM, Rand KA, Kermany A, Noto K, Curtis D, Garrigan D, et al. A prospective analysis of genetic variants associated with human lifespan. G3 Genes, Genomes, Genet. 2019;9(9):2863–78. doi: 10.1534/g3.119.400448 31484785
98. Consortium TASDWG of TPG. Meta-analysis of GWAS of over 16,000 individuals with autism spectrum disorder highlights a novel locus at 10q24.32 and a significant overlap with schizophrenia. Mol Autism. 2017;8(21).
99. Cordell HJ, Han Y, Mells GF, Li Y, Hirschfield GM, Greene CS, et al. International genome-wide meta-analysis identifies new primary biliary cirrhosis risk loci and targetable pathogenic pathways. Nat Commun [Internet]. 2015;6:1–11. Available from: doi: 10.1038/ncomms9019 26394269
100. Boraska V, Franklin CS, Floyd JAB, Thornton LM, Huckins LM, Southam L, et al. A genome-wide association study of anorexia nervosa. Mol Psychiatry. 2014;19(10):1085–94. doi: 10.1038/mp.2013.187 24514567
101. Jung SJ, Winning A, Roberts AL, Nishimi K, Chen Q, Gilsanz P, et al. Posttraumatic stress disorder symptoms and television viewing patterns in the Nurses’ Health Study II: A longitudinal analysis. PLoS One. 2019;14(3):1–13. doi: 10.1371/journal.pone.0213441 30897111
102. Liberzon I, King AP, Ressler KJ, Almli LM, Zhang P, Ma ST, et al. Interaction of the ADRB2 gene polymorphism with childhood trauma in predicting adult symptoms of posttraumatic stress disorder. JAMA Psychiatry. 2014;71(10):1174–82. doi: 10.1001/jamapsychiatry.2014.999 25162199
103. Bierut LJ, Strickland JR, Thompson JR, Afful SE, Cottler LB. Drug use and dependence in cocaine dependent subjects, community-based individuals, and their siblings. Drug Alcohol Depend. 2008;95(1–2):14–22. doi: 10.1016/j.drugalcdep.2007.11.023 18243582
104. Baker DG, Nash WP, Litz BT, Geyer MA, Risbrough VB, Nievergelt CM, et al. Predictors of Risk and Resilience for Posttraumatic Stress Disorder Among Ground Combat Marines: Methods of the Marine Resiliency Study. Prev Chronic Dis. 2012;9(5):1–11. doi: 10.5888/pcd9.110134 22575082
105. Kimbrel NA, Hauser MA, Garrett M, Ashley-Koch A, Liu Y, Dennis MF, et al. Effect of the APOE ε4 allele and combat exposure on PTSD among Iraq/Afghanistan-era veterans. Depress Anxiety. 2015;32(5):307–15. doi: 10.1002/da.22348 25709077
106. Nievergelt CM, Maihofer AX, Klengel T, Atkinson EG, Chen C-Y,…, et al. Largest genome-wide association study for PTSD identifies genetic risk loci in European and African ancestries and implicates novel biological pathways. bioRxiv [Internet]. 2018;(Nov). Available from: http://dx.doi.org/10.1101/458562
107. Liang X, Liu R, Chen C, Ji F, Li T. Opioid System Modulates the Immune Function: A Review Xuan. Transl Perioper Pain Med. 2016;1(1):5–13. 26985446
108. Diasso PDK, Birke H, Nielsen SD, Main KM, Højsted J, Sjøgren P, et al. The effects of long-term opioid treatment on the immune system in chronic non-cancer pain patients: A systematic review. Eur J Pain (United Kingdom). 2020;24(3):481–96. doi: 10.1002/ejp.1506 31705699
109. Mogil JS. Qualitative sex differences in pain processing: emerging evidence of a biased literature. Nat Rev Neurosci 2020 [Internet]. 2020;1–13. Available from: http://www.nature.com/articles/s41583-020-0310-6%0Ahttps://www.nature.com/articles/s41583-020-0310-6 doi: 10.1038/s41583-020-0310-6 32440016
110. König IR, Loley C, Erdmann J, Ziegler A. How to Include Chromosome X in Your Genome-Wide Association Study. Genet Epidemiol. 2014; doi: 10.1002/gepi.21782 24408308
111. Accounting for sex in the genome. Nat Med. 2017;23(11):1243. doi: 10.1038/nm.4445 29117171
112. Macfarlane GJ, Barnish MS, Jones GT. Persons with chronic widespread pain experience excess mortality: longitudinal results from UK Biobank and meta-analysis. Ann Rheum Dis [Internet]. 2017;76(11):1815–22. Available from: http://ard.bmj.com/lookup/doi/10.1136/annrheumdis-2017-211476 28733474
113. Kamaleri Y, Natvig B, Ihlebaek CM, Benth JS, Bruusgaard D. Number of pain sites is associated with demographic, lifestyle, and health-related factors in the general population. Eur J Pain. 2008;12(6):742–8. doi: 10.1016/j.ejpain.2007.11.005 18160318
114. Bycroft C, Freeman C, Petkova D, Band G, Elliott LT, Sharp K, et al. The UK Biobank resource with deep phenotyping and genomic data. Nature. 2018;562(7726):203–9. doi: 10.1038/s41586-018-0579-z 30305743
115. Loh PR, Tucker G, Bulik-Sullivan BK, Vilhjálmsson BJ, Finucane HK, Salem RM, et al. Efficient Bayesian mixed-model analysis increases association power in large cohorts. Nat Genet [Internet]. 2015;47(3):284–90. Available from: doi: 10.1038/ng.3190 25642633
116. Willer CJ, Li Y, Abecasis GR, Overall P. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics. 2010;26(17):2190–1. doi: 10.1093/bioinformatics/btq340 20616382
117. Zeisel A, Hochgerner H, Lönnerberg P, Johnsson A, Memic F, van der Zwan J, et al. Molecular Architecture of the Mouse Nervous System. Cell. 2018;174(4):999–1014.e22. doi: 10.1016/j.cell.2018.06.021 30096314
118. Won H, Huang J, Opland CK, Hartl CL, Geschwind DH. Human evolved regulatory elements modulate genes involved in cortical expansion and neurodevelopmental disease susceptibility. Nat Commun [Internet]. 2019;10(1):1–11. Available from: doi: 10.1038/s41467-018-07882-8 30602773
119. Zheng J, Erzurumluoglu AM, Elsworth BL, Kemp JP, Howe L, Haycock PC, et al. LD Hub: A centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis. Bioinformatics. 2017;33(2):272–9. doi: 10.1093/bioinformatics/btw613 27663502
120. Bulik-Sullivan B, Loh PR, Finucane HK, Ripke S, Yang J, Patterson N, et al. LD score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat Genet [Internet]. 2015;47(3):291–5. Available from: doi: 10.1038/ng.3211 25642630
121. Bulik-sullivan B, Finucane HK, Anttila V, Gusev A, Day FR, Case T, et al. An atlas of genetic correlations across human diseases and traits. Nat Publ Gr [Internet]. 2015;47(11):1236–41. Available from: doi: 10.1038/ng.3406 26414676
122. Dudbridge F. Power and Predictive Accuracy of Polygenic Risk Scores. PLoS Genet. 2013;9(3). doi: 10.1371/journal.pgen.1003348 23555274
Článek vyšel v časopise
PLOS Genetics
2021 Číslo 4
- Distribuce a lokalizace speciálně upravených exosomů může zefektivnit léčbu svalových dystrofií
- Prof. Jan Škrha: Metformin je bezpečný, ale je třeba jej bezpečně užívat a léčbu kontrolovat
- FDA varuje před selfmonitoringem cukru pomocí chytrých hodinek. Jak je to v Česku?
- Masturbační chování žen v ČR − dotazníková studie
- O krok blíže k pochopení efektu placeba při léčbě bolesti
Nejčtenější v tomto čísle
- Aicardi-Goutières syndrome-associated gene SAMHD1 preserves genome integrity by preventing R-loop formation at transcription–replication conflict regions
- Functional assessment of the “two-hit” model for neurodevelopmental defects in Drosophila and X. laevis
- Pathways and signatures of mutagenesis at targeted DNA nicks
- Using genetic variants to evaluate the causal effect of cholesterol lowering on head and neck cancer risk: A Mendelian randomization study