Robust association tests for quantitative traits on the X chromosome.
Journal
Heredity
ISSN: 1365-2540
Titre abrégé: Heredity (Edinb)
Pays: England
ID NLM: 0373007
Informations de publication
Date de publication:
Oct 2022
Oct 2022
Historique:
received:
15
07
2021
accepted:
24
08
2022
revised:
24
08
2022
pubmed:
11
9
2022
medline:
1
10
2022
entrez:
10
9
2022
Statut:
ppublish
Résumé
The genome-wide association study is an elementary tool to assess the genetic contribution to complex human traits. However, such association tests are mainly proposed for autosomes, and less attention has been given to methods for identifying loci on the X chromosome due to their distinct biological features. In addition, the existing association tests for quantitative traits on the X chromosome either fail to incorporate the information of males or only detect variance heterogeneity. Therefore, we propose four novel methods, which are denoted as QXcat, QZ
Identifiants
pubmed: 36085362
doi: 10.1038/s41437-022-00560-y
pii: 10.1038/s41437-022-00560-y
pmc: PMC9519943
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
244-256Informations de copyright
© 2022. The Author(s), under exclusive licence to The Genetics Society.
Références
Al-Ayadhi LY, Qasem HY, Alghamdi HAM, Elamin NE (2020) Elevated plasma X-linked neuroligin 4 expression is associated with autism spectrum disorder. Med Princ Pr 29:480–485
doi: 10.1159/000507081
Amos-Landgraf JM, Cottle A, Plenge RM, Friez M, Schwartz CE, Longshore J et al. (2006) X chromosome-inactivation patterns of 1,005 phenotypically unaffected females. Am J Hum Genet 79:493–499
pubmed: 16909387
pmcid: 1559535
doi: 10.1086/507565
Auer PL, Teumer A, Schick U, O’Shaughnessy A, Lo KS, Chami N et al. (2014) Rare and low-frequency coding variants in CXCR2 and other genes are associated with hematological traits. Nat Genet 46:629–634
pubmed: 24777453
pmcid: 4050975
doi: 10.1038/ng.2962
Brown AA, Buil A, Viñuela A, Lappalainen T, Zheng HF, Richards JB et al. (2014) Genetic interactions affecting human gene expression identifed by variance association mapping. Elife 3:e01381
pubmed: 24771767
pmcid: 4017648
doi: 10.7554/eLife.01381
Brown CJ, Carrel L, Willard HF (1997) Expression of genes from the human active and inactive X chromosomes. Am J Hum Genet 60:1333–1343
pubmed: 9199554
pmcid: 1716148
doi: 10.1086/515488
Brown MB, Forsythe AB (1974) Robust tests for the equality of variances. J Am Stat Assoc 69:364–367
doi: 10.1080/01621459.1974.10482955
Cao Y, Wei P, Bailey M, Kauwe JSK, Maxwell TJ (2014) A versatile omnibus test for detecting mean and variance heterogeneity. Genet Epidemiol 38:51–59
pubmed: 24482837
pmcid: 4019404
doi: 10.1002/gepi.21778
Carrel L, Park C, Tyekucheva S, Dunn J, Chiaromonte F, Makova KD (2006) Genomic environment predicts expression patterns on the human inactive X chromosome. PLoS Genet 2:e151
pubmed: 17009873
pmcid: 1584270
doi: 10.1371/journal.pgen.0020151
Carrel L, Willard HF (2005) X-inactivation profle reveals extensive variability in X-linked gene expression in females. Nature 434:400–404
pubmed: 15772666
doi: 10.1038/nature03479
Chang D, Gao F, Slavney A, Ma L, Waldman YY, Sams AJ et al. (2014) Accounting for eXentricities: analysis of the X chromosome in GWAS reveals X-linked genes implicated in autoimmune diseases. PLoS One 9:e113684
pubmed: 25479423
pmcid: 4257614
doi: 10.1371/journal.pone.0113684
Chen B, Craiu RV, Strug LJ, Sun L (2021) The X factor: A robust and powerful approach to X-chromosome-inclusive whole-genome association studies. Genet Epidemiol 45:694–709
pubmed: 34224641
pmcid: 9292551
doi: 10.1002/gepi.22422
Chen B, Craiu RV, Sun L (2020) Bayesian model averaging for the X-chromosome inactivation dilemma in genetic association study. Biostatistics 21:319–335
pubmed: 30247537
Chen ZX (2022a) Optimal tests for combining p-values. Appl Sci 12:322
doi: 10.3390/app12010322
Chen ZX (2022b) Robust tests for combining p-values under arbitrary dependency structures. Sci Rep. 12:3158
pubmed: 35210502
pmcid: 8873210
doi: 10.1038/s41598-022-07094-7
Chen ZX, Ng HKT (2012) A robust method for testing association in genome-wide association studies. Hum Hered 73:26–34
pubmed: 22212363
doi: 10.1159/000334719
Chen ZX, Ng HKT, Li J, Liu Q, Huang H (2017) Detecting associated single-nucleotide polymorphisms on the X chromosome in case control genome-wide association studies. Stat Methods Med Res 26:567–582
pubmed: 25253574
doi: 10.1177/0962280214551815
Chung RH, Morris RW, Zhang L, Li YJ, Martin ER (2007) X-APL: an improved family-based test of association in the presence of linkage for the X chromosome. Am J Hum Genet 80:59–68
pubmed: 17160894
doi: 10.1086/510630
Clayton D (2008) Testing for association on the X chromosome. Biostatistics 9:593–600
pubmed: 18441336
pmcid: 2536723
doi: 10.1093/biostatistics/kxn007
Deng WQ, Mao S, Kalnapenkis A, Esko T, Mägi R, Paré G et al. (2019) Analytical strategies to include the X-chromosome in variance heterogeneity analyses: evidence for trait-specifc polygenic variance structure. Genet Epidemiol 43:815–830
pubmed: 31332826
doi: 10.1002/gepi.22247
Ding J, Lin S, Liu Y (2006) Monte Carlo pedigree disequilibrium test for markers on the X chromosome. Am J Hum Genet 79:567–573
pubmed: 16909396
pmcid: 1559546
doi: 10.1086/507609
Fisher B, Costich ER, Ganz M, Stanford JW (1967) Questions & answers. J Am Dent Assoc 75:799
doi: 10.14219/jada.archive.1967.0319
Gaukrodger N, Mayosi BM, Imrie H, Avery P, Baker M, Connell JMC et al. (2005) A rare variant of the leptin gene has large effects on blood pressure and carotid intima-medial thickness: a study of 1428 individuals in 248 families. J Med Genet 42:474–478
pubmed: 15937081
pmcid: 1736073
doi: 10.1136/jmg.2004.027631
Haldar T, Ghosh S (2012) Effect of population stratifcation on false positive rates of population-based association analyses of quantitative traits. Ann Hum Genet 76:237–245
pubmed: 22497479
pmcid: 3334349
doi: 10.1111/j.1469-1809.2012.00708.x
Hickey PF, Bahlo M (2011) X chromosome association testing in genome wide association studies. Genet Epidemiol 35:664–670
pubmed: 21818774
doi: 10.1002/gepi.20616
Horvath S, Laird NM, Knapp M (2000) The transmission/disequilibrium test and parental-genotype reconstruction for X-chromosomal markers. Am J Hum Genet 66:1161–1167
pubmed: 10712229
pmcid: 1288153
doi: 10.1086/302823
Jin H, Park T, Won S (2017) Efficient statistical method for association analysis of X-linked variants. Hum Hered 82:50–63
doi: 10.1159/000478048
Kang HM, Sul JH, Service SK, Zaitlen NA, Kong SY, Freimer NB et al. (2010) Variance component model to account for sample structure in genome-wide association studies. Nat Genet 42:348–354
pubmed: 20208533
pmcid: 3092069
doi: 10.1038/ng.548
Kearney HM, Thorland EC, Brown KK, Quintero-Rivera F, South ST (2011) American college of medical genetics standards and guidelines for interpretation and reporting of postnatal constitutional copy number variants. Genet Med 13:680–685
pubmed: 21681106
doi: 10.1097/GIM.0b013e3182217a3a
Konzman D, Abramowitz LK, Steenackers A, Mukherjee MM, Na HJ, Hanover JA (2020) O-GlcNAc: regulator of signaling and epigenetics linked to X-linked intellectual disability. Front Genet 11:605263
pubmed: 33329753
pmcid: 7719714
doi: 10.3389/fgene.2020.605263
Kushima I, Aleksic B, Nakatochi M, Shimamura T, Okada T, Uno Y et al. (2018) Comparative analyses of copy-number variation in autism spectrum disorder and schizophrenia reveal etiological overlap and biological insights. Cell Rep. 24:2838–2856
pubmed: 30208311
doi: 10.1016/j.celrep.2018.08.022
Labonne JDJ, Graves TD, Shen YP, Jones JR, Kong IK, Layman LC et al. (2016) A microdeletion at Xq22. 2 implicates a glycine receptor GLRA4 involved in intellectual disability, behavioral problems and craniofacial anomalies. BMC Neurol 16:132
pubmed: 27506666
pmcid: 4979147
doi: 10.1186/s12883-016-0642-z
Levene H (1961) Robust tests for equality of variances. Contributions to Probability and Statistics: 279–292.
Li BH, Yu WY, Zhou JY (2021) A statistical measure for the skewness of X chromosome inactivation for quantitative traits and its application to the MCTFR data. BMC Genom Data 22:24
pubmed: 34215184
pmcid: 8254321
doi: 10.1186/s12863-021-00978-z
Liu Y, Xie J (2020) Cauchy combination test: a powerful test with analytic p-value calculation under arbitrary dependency structures. J Am Stat Assoc 115:393–402
pubmed: 33012899
doi: 10.1080/01621459.2018.1554485
Loley C, Ziegler A, König IR (2011) Association tests for X-chromosomal markers–a comparison of different test statistics. Hum Hered 71:23–36
pubmed: 21325864
pmcid: 3089425
doi: 10.1159/000323768
Lyon MF (1961) Gene action in the X-chromosome of the mouse (Mus musculus L.). Nature 190:372–373
pubmed: 13764598
doi: 10.1038/190372a0
Ma C, Boehnke M, Lee S, GoT2D Investigators (2015a) Evaluating the calibration and power of three gene-based association tests of rare variants for the X chromosome. Genet Epidemiol 39:499–508
pubmed: 26454253
pmcid: 4609297
doi: 10.1002/gepi.21935
Ma L, Hoffman G, Keinan A (2015b) X-inactivation informs variance-based testing for X-linked association of a quantitative trait. BMC Genomics 16:241
pubmed: 25880738
pmcid: 4381508
doi: 10.1186/s12864-015-1463-y
Marees AT, Kluiver HD, Stringer S, Vorspan F, Curis E, Marie-Claire C et al. (2018) A tutorial on conducting genome-wide association studies: quality control and statistical analysis. Int J Methods Psychiatr Res 27:e1608
pubmed: 29484742
pmcid: 6001694
doi: 10.1002/mpr.1608
McCaw ZR, Lane JM, Saxena R, Redline S, Lin X (2019) Operating characteristics of the rank-based inverse normal transformation for quantitative trait analysis in genome-wide association studies. Biometrics 76:1262–1272
doi: 10.1111/biom.13214
Minks J, Robinson WP, Brown CJ (2008) A skewed view of X chromosome inactivation. J Clin Invest 118:20–23
pubmed: 18097476
doi: 10.1172/JCI34470
Morley M, Molony CM, Weber TM, Devlin JL, Ewens KG, Spielman RS et al. (2004) Genetic analysis of genome-wide variation in human gene expression. Nature 430:743–747
pubmed: 15269782
pmcid: 2966974
doi: 10.1038/nature02797
Mosteller F, Fisher RA (1948) Questions and answers. Am Stat 2:30–31
doi: 10.1080/00031305.1948.10483415
Özbek U, Lin HM, Lin Y, Weeks DE, Chen W, Shaffer JR et al. (2018) Statistics for X-chromosome associations. Genet Epidemiol 42:539–550
pubmed: 29900581
pmcid: 6394852
doi: 10.1002/gepi.22132
Paganini L, Hadi LA, Chetta M, Rovina D, Fontana L, Colapietro P et al. (2019) A HS6ST2 gene variant associated with X-linked intellectual disability and severe myopia in two male twins. Clin Genet 95:368–374
pubmed: 30471091
doi: 10.1111/cge.13485
R Core Team (2020) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. Austria, http://www.R-project.org/
Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J et al. (2015) Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the american college of medical genetics and genomics and the association for molecular pathology. Genet Med 17:405–423
pubmed: 25741868
pmcid: 4544753
doi: 10.1038/gim.2015.30
Schifano ED, Li L, Christiani DC, Lin X (2013) Genome-wide association analysis for multiple continuous secondary phenotypes. Am J Hum Genet 92:744–759
pubmed: 23643383
pmcid: 3644646
doi: 10.1016/j.ajhg.2013.04.004
Soave D, Corvol H, Panjwani N, Gong J, Li W, Boëlle PY et al. (2015) A joint location-scale test improves power to detect associated SNPs, gene sets, and pathways. Am J Hum Genet 97:125–138
pubmed: 26140448
pmcid: 4572492
doi: 10.1016/j.ajhg.2015.05.015
Song YL, Biernacka JM, Winham SJ (2021) Testing and estimation of X-chromosome SNP effects: Impact of model assumptions. Genet Epidemiol 45:577–592
pubmed: 34082482
pmcid: 8453908
doi: 10.1002/gepi.22393
Stouffer SA, Suchman EA, DeVinney LC, Star SA, Williams Jr RM (1949) The american soldier: adjustment during army life. (studies in social psychology in World War II). Princeton Univ. Press.
Struchalin MV, Dehghan A, Witteman JCM, Duijn CV, Aulchenko YS (2010) Variance heterogeneity analysis for detection of potentially interacting genetic loci: method and its limitations. BMC Genet 11:92
pubmed: 20942902
pmcid: 2973850
doi: 10.1186/1471-2156-11-92
Wang J, Yu R, Shete S (2014) X-chromosome genetic association test accounting for X-inactivation, skewed X-inactivation, and escape from X-inactivation. Genet Epidemiol 38:483–493
pubmed: 25043884
pmcid: 4127090
doi: 10.1002/gepi.21814
Wang P, Xu SQ, Wang BQ, Fung WK, Zhou JY (2019a) A robust and powerful test for case-control genetic association study on X chromosome. Stat Methods Med Res 28:3260–3272
pubmed: 30232923
doi: 10.1177/0962280218799532
Wang P, Zhang Y, Wang BQ, Li JL, Wang YX, Pan D et al. (2019b) A statistical measure for the skewness of X chromosome inactivation based on case-control design. BMC Bioinforma 20:11
doi: 10.1186/s12859-018-2587-2
Wise AL, Gyi L, Manolio TA (2013) eXclusion: toward integrating the X chromosome in genome-wide association analyses. Am J Hum Genet 92:643–647
pubmed: 23643377
pmcid: 3644627
doi: 10.1016/j.ajhg.2013.03.017
Wong CCY, Caspi A, Williams B, Houts R, Craig IW, Mill J (2011) A longitudinal twin study of skewed X chromosome-inactivation. PLoS One 6:e17873
pubmed: 21445353
pmcid: 3062559
doi: 10.1371/journal.pone.0017873
Wu H, Luo J, Yu H, Rattner A, Mo A, Wang Y et al. (2014) Cellular resolution maps of X-chromosome inactivation: implications for neural development, function, and disease. Neuron 81:103–119
pubmed: 24411735
pmcid: 3950970
doi: 10.1016/j.neuron.2013.10.051
Xia F, Zhou JY, Fung WK (2013) Powerful tests for association on quantitative trait loci incorporating imprinting effects. J Hum Genet 58:384–390
pubmed: 23552672
doi: 10.1038/jhg.2013.22
Xu W, Hao M (2018) A unifed partial likelihood approach for X-chromosome association on time-to-event outcomes. Genet Epidemiol 42:80–94
pubmed: 29178618
doi: 10.1002/gepi.22097
Yang J, Loos RJF, Powell JE, Medland SE, Speliotes EK, Chasman DI et al. (2012) FTO genotype is associated with phenotypic variability of body mass index. Nature 490:267–272
pubmed: 22982992
pmcid: 3564953
doi: 10.1038/nature11401
Zhang L, Martin ER, Chung RH, Li YJ, Morris RW (2008) X-LRT: a likelihood approach to estimate genetic risks and test association with X-linked markers using a case-parents design. Genet Epidemiol 32:370–380
pubmed: 18278816
doi: 10.1002/gepi.20311
Zheng G, Joo J, Zhang C, Geller NL (2007) Testing association for markers on the X chromosome. Genet Epidemiol 31:834–843
pubmed: 17549761
doi: 10.1002/gepi.20244