A set-based mixed effect model for gene-environment interaction and its application to neuroimaging phenotypes

Frontiers in Neuroscience

Volumn 11, Issue APR, 2017, Pages

  Wang, Changqing ^a   Sun, Jianping ^b   Guillaume, Bryan ^c   Ge, Tian ^d   Hibar, Derrek P ^e   Greenwood, Celia M T ^b,f   Qiu, Anqi ^c,g  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^b MCGILL UNIVERSITY   (Canada)

^c NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^d MASSACHUSETTS GENERAL HOSPITAL   (United States)

^e UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

^f MCGILL UNIVERSITY   (Canada)

^g AGENCY FOR SCIENCE   (Singapore)

Author keywords

Alzheimer's disease; Gene environment interaction; Imaging genetics; Score statistics; Tensor based morphometry

Indexed keywords

ABCA7 GENE; ALZHEIMER DISEASE; ARTICLE; BRAIN SIZE; CARDIOVASCULAR RISK; GENE; GENETIC VARIABILITY; GENOTYPE ENVIRONMENT INTERACTION; HIPPOCAMPUS; HUMAN; KERNEL METHOD; MORPHOMETRY; NEUROIMAGING; NUCLEAR MAGNETIC RESONANCE IMAGING; PARIETAL CORTEX; RIGHT HEMISPHERE; SIMULATION; SUPERIOR PARIETAL CORTEX; TENSOR BASED MORPHOMETRY;

EID: 85018416754     PISSN: 16624548     EISSN: 1662453X     Source Type: Journal    
DOI: 10.3389/fnins.2017.00191     Document Type: Article

References (64)

1. Bertram, L., Lill, C. M., and Tanzi, R. E. (2010). The genetics of alzheimer disease: back to the future. Neuron 68, 270-281. doi: 10.1016/j.neuron.2010.10.013
2. Bigos, K. L., and Weinberger, D. R. (2010). Imaging genetics days of future past. Neuroimage 53, 804-809. doi: 10.1016/j.neuroimage.2010.01.035
3. Cadoret, R. J., Cain, C. A., and Crowe, R. R. (1983). Evidence for gene-environment interaction in the development of adolescent antisocial behavior. Behav. Genet. 13, 301-310. doi: 10.1007/BF01071875
4. Carrasquillo, M. M., Murray, M. E., Krishnan, S., Aakre, J., Pankratz, V. S., Nguyen, T., et al. (2014). Late-onset alzheimer disease genetic variants in posterior cortical atrophy and posterior AD. Neurology 82, 1455-1462. doi: 10.1212/WNL.0000000000000335
5. Chan, S. L., Kim, W. S., Kwok, J. B., Hill, A. F., Cappai, R., Rye, K.-A., et al. (2008). ATP-binding cassette transporter A7 regulates processing of amyloid precursor protein in vitro. J. Neurochem. 106, 793-804. doi: 10.1111/j.1471-4159.2008.05433.x
6. Chen, L. S., Hsu, L., Gamazon, E. R., Cox, N. J., and Nicolae, D. L. (2012). An exponential combination procedure for set-based association tests in sequencing studies. Am. J. Hum. Genet. 91, 977-986. doi: 10.1016/j.ajhg.2012.09.017
7. Dale, A. M., Fischl, B., and Sereno, M. I. (1999). Cortical surface-based analysis: I. segmentation and surface reconstruction. Neuroimage 9, 179-194. doi: 10.1006/nimg.1998.0395
8. de Geus, E., Goldberg, T., Boomsma, D. I., and Posthuma, D. (2008). Imaging the genetics of brain structure and function. Biol. Psychol. 79, 1-8. doi: 10.1016/j.biopsycho.2008.04.002
9. Derkach, A., Lawless, J. F., and Sun, L. (2013). Robust and powerful tests for rare variants using fisher's method to combine evidence of association from two or more complementary tests. Genet. Epidemiol. 37, 110-121. doi: 10.1002/gepi.21689
10. Domschke, K., and Dannlowski, U. (2010). Imaging genetics of anxiety disorders. Neuroimage 53, 822-831. doi: 10.1016/j.neuroimage.2009.11.042
11. Durston, S. (2010). Imaging genetics in ADHD. Neuroimage 53, 832-838. doi: 10.1016/j.neuroimage.2010.02.071
12. Eley, T. C., Sugden, K., Corsico, A., Gregory, A. M., Sham, P., McGuffin, P., et al. (2004). Gene-environment interaction analysis of serotonin system markers with adolescent depression. Mol. Psychiatry 9, 908-915. doi: 10.1038/sj.mp.4001546
13. Fischl, B., Salat, D. H., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., et al. (2002). Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron 33, 341-355. doi: 10.1016/S0896-6273(02)00569-X
14. Ge, T., Feng, J., Hibar, D. P., Thompson, P. M., and Nichols, T. E. (2012). Increasing power for voxel-wise genome-wide association studies: the random field theory, least square kernel machines and fast permutation procedures. Neuroimage 63, 858-873. doi: 10.1016/j.neuroimage.2012.07.012
15. Ge, T., Nichols, T. E., Ghosh, D., Mormino, E. C., Smoller, J. W., Sabuncu, M. R., et al. (2015). A kernel machine method for detecting effects of interaction between multidimensional variable sets: an imaging genetics application. Neuroimage 109, 505-514. doi: 10.1016/j.neuroimage.2015.01.029
16. Gibson, G. (2010). Hints of hidden heritability in GWAS. Nat. Genet. 42, 558-560. doi: 10.1038/ng0710-558
17. Han, F., and Pan, W. (2010). A data-adaptive sum test for disease association with multiple common or rare variants. Hum. Hered. 70, 42-54. doi: 10.1159/000288704
18. Hariri, A. R., Drabant, E. M., and Weinberger, D. R. (2006). Imaging genetics: perspectives from studies of genetically driven variation in serotonin function and corticolimbic affective processing. Biol. Psychiatry 59, 888-897. doi: 10.1016/j.biopsych.2005.11.005
19. Hibar, D. P., Stein, J. L., Kohannim, O., Jahanshad, N., Saykin, A. J., Shen, L., et al. (2011). Voxelwise gene-wide association study (vGeneWAS): multivariate gene-based association testing in 731 elderly subjects. Neuroimage 56, 1875-1891. doi: 10.1016/j.neuroimage.2011.03.077
20. Hibar, D. P., Stein, J. L., Renteria, M. E., Arias-Vasquez, A., Desrivières, S., Jahanshad, N., et al. (2015). Common genetic variants influence human subcortical brain structures. Nature 520, 224-229. doi: 10.1038/nature14101
21. Hua, X., Leow, A. D., Parikshak, N., Lee, S., Chiang, M.-C., Toga, A. W., et al. (2008). Tensor-based morphometry as a neuroimaging biomarker for alzheimer's disease: an MRI study of 676 AD, MCI, and normal subjects. Neuroimage 43, 458-469. doi: 10.1016/j.neuroimage.2008.07.013
22. Huang, M., Nichols, T., Huang, C., Yu, Y., Lu, Z., Knickmeyer, R. C., et al. (2015). FVGWAS: Fast voxelwise genome wide association analysis of large-scale imaging genetic data. Neuroimage 118, 613-627. doi: 10.1016/j.neuroimage.2015.05.043
23. Jiao, S., Hsu, L., Bézieau, S., Brenner, H., Chan, A. T., Chang-Claude, J., et al. (2013). SBERIA: Set-based gene-environment interaction test for rare and common variants in complex diseases. Genet. Epidemiol. 37, 452-464. doi: 10.1002/gepi.21735
24. Jones, L., Harold, D., and Williams, J. (2010). Genetic evidence for the involvement of lipid metabolism in alzheimer's disease. Biochim. Biophys. Acta 1801, 754-761. doi: 10.1016/j.bbalip.2010.04.005
25. Kim-Cohen, J., Caspi, A., Taylor, A., Williams, B., Newcombe, R., Craig, I. W., et al. (2006). Maoa, maltreatment, and gene-environment interaction predicting children's mental health: new evidence and a meta-analysis. Mol. Psychiatry 11, 903-913. doi: 10.1038/sj.mp.4001851
26. Kivipelto, M., Helkala, E.-L., Laakso, M. P., Hänninen, T., Hallikainen, M., Alhainen, K., et al. (2001). Midlife vascular risk factors and alzheimer's disease in later life: longitudinal, population based study. BMJ 322, 1447-1451. doi: 10.1136/bmj.322.7300.1447
27. Korte, A., and Farlow, A. (2013). The advantages and limitations of trait analysis with GWAS: a review. Plant Methods 9:29. doi: 10.1186/1746-4811-9-29
28. Koziol, J. A., and Perlman, M. D. (1978). Combining independent chi-squared tests. J. Am. Stat. Assoc. 73, 753-763
29. Lambert, J.-C., Ibrahim-Verbaas, C. A., Harold, D., Naj, A. C., Sims, R., Bellenguez, C., et al. (2013). Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for alzheimer's disease. Nat. Genet. 45, 1452-1458. doi: 10.1038/ng.2802
30. Lee, S., Abecasis, G. R., Boehnke, M., and Lin, X. (2014). Rare-variant association analysis: study designs and statistical tests. Am. J. Hum. Genet. 95, 5-23. doi: 10.1016/j.ajhg.2014.06.009
31. Lee, S., Wu, M. C., and Lin, X. (2012). Optimal tests for rare variant effects in sequencing association studies. Biostatistics 13, 762-775. doi: 10.1093/biostatistics/kxs014
32. Leow, A., Huang, S.-C., Geng, A., Becker, J., Davis, S., Toga, A., et al. (2005). Inverse consistent mapping in 3D deformable image registration: its construction and statistical properties. Inf. Process. Med. Imaging 19, 493-503. doi: 10.1007/11505730_41
33. Lin, X., Lee, S., Christiani, D. C., and Lin, X. (2013). Test for interactions between a genetic marker set and environment in generalized linear models. Biostatistics 14, 667-681. doi: 10.1093/biostatistics/kxt006
34. Lin, X., Lee, S., Wu, M. C., Wang, C., Chen, H., Li, Z., et al. (2016). Test for rare variants by environment interactions in sequencing association studies. Biometrics 72, 156-164. doi: 10.1111/biom.12368
35. Liu, H., Tang, Y., and Zhang, H. H. (2009). A new chi-square approximation to the distribution of non-negative definite quadratic forms in non-central normal variables. Comput. Stat. Data Anal. 53, 853-856. doi: 10.1016/j.csda.2008.11.025
36. Lu, T., Aron, L., Zullo, J., Pan, Y., Kim, H., Chen, Y., et al. (2014). Rest and stress resistance in ageing and alzheimer/'s disease. Nature 507, 448-454. doi: 10.1038/nature20579
37. Luchsinger, J., Reitz, C., Honig, L. S., Tang, M.-X., Shea, S., and Mayeux, R. (2005). Aggregation of vascular risk factors and risk of incident alzheimer disease. Neurology 65, 545-551. doi: 10.1212/01.wnl.0000172914.08967.dc
38. Madsen, B. E., and Browning, S. R. (2009). A groupwise association test for rare mutations using a weighted sum statistic. PLoS Genet. 5:e1000384. doi: 10.1371/journal.pgen.1000384
39. Manolio, T. A., Collins, F. S., Cox, N. J., Goldstein, D. B., Hindorff, L. A., Hunter, D. J., et al. (2009). Finding the missing heritability of complex diseases. Nature 461, 747-753. doi: 10.1038/nature08494
40. Mattay, V. S., Goldberg, T. E., Sambataro, F., and Weinberger, D. R. (2008). Neurobiology of cognitive aging: insights from imaging genetics. Biol. Psychol. 79, 9-22. doi: 10.1016/j.biopsycho.2008.03.015
41. Meyer-Lindenberg, A., and Weinberger, D. R. (2006). Intermediate phenotypes and genetic mechanisms of psychiatric disorders. Nat. Rev. Neurosci. 7, 818-827. doi: 10.1038/nrn1993
42. Milberger, S., Biederman, J., Faraone, S. V., Guite, J., and Tsuang, M. T. (1997). Pregnancy, delivery and infancy complications and attention deficit hyperactivity disorder: issues of gene-environment interaction. Biol. Psychiatry 41, 65-75. doi: 10.1016/0006-3223(95)00653-2
43. Morgenthaler, S., and Thilly, W. G. (2007). A strategy to discover genes that carry multi-allelic or mono-allelic risk for common diseases: a cohort allelic sums test (cast). Mutat. Res. 615, 28-56. doi: 10.1016/j.mrfmmm.2006.09.003
44. Moutsianas, L., Agarwala, V., Fuchsberger, C., Flannick, J., Rivas, M. A., Gaulton, K. J., et al. (2015). The power of gene-based rare variant methods to detect disease-associated variation and test hypotheses about complex disease. PLoS Genet. 11:e1005165. doi: 10.1371/journal.pgen.1005165
45. Neale, B. M., Rivas, M. A., Voight, B. F., Altshuler, D., Devlin, B., Orho-Melander, M., et al. (2011). Testing for an unusual distribution of rare variants. PLoS Genet. 7:e1001322. doi: 10.1371/journal.pgen.1001322
46. Pedersen, N. L., Gatz, M., Berg, S., and Johansson, B. (2004). How heritable is alzheimer's disease late in life? Findings from swedish twins. Ann. Neurol. 55, 180-185. doi: 10.1002/ana.10999
47. Price, A. L., Kryukov, G. V., de Bakker, P. I., Purcell, S. M., Staples, J., Wei, L.-J., et al. (2010). Pooled association tests for rare variants in exon-resequencing studies. Am. J. Hum. Genet. 86, 832-838. doi: 10.1016/j.ajhg.2010.04.005
48. Rasch, B., Papassotiropoulos, A., and de Quervain, D.-F. (2010). Imaging genetics of cognitive functions: focus on episodic memory. Neuroimage 53, 870-877. doi: 10.1016/j.neuroimage.2010.01.001
49. Reitz, C., Jun, G., Naj, A., Rajbhandary, R., Vardarajan, B. N., Wang, L.-S., et al. (2013). Variants in the ATP-binding cassette transporter (ABCA7), apolipoprotein E e4, and the risk of late-onset alzheimer disease in african americans. JAMA 309, 1483-1492. doi: 10.1001/jama.2013.2973
50. Ridge, P. G., Mukherjee, S., Crane, P. K., and Kauwe, J. S. K., and Alzheimer's Disease Genetics Consortium (2013). Alzheimers disease: analyzing the missing heritability. PLoS ONE 8:e79771. doi: 10.1371/journal.pone.0079771
51. Scharinger, C., Rabl, U., Sitte, H. H., and Pezawas, L. (2010). Imaging genetics of mood disorders. Neuroimage 53, 810-821. doi: 10.1016/j.neuroimage.2010.02.019
52. Stampfer, M. (2006). Cardiovascular disease and alzheimer's disease: common links. J. Intern. Med. 260, 211-223. doi: 10.1111/j.1365-2796.2006.01687.x
53. Stein, J. L., Hua, X., Lee, S., Ho, A. J., Leow, A. D., Toga, A. W., et al. (2010). Voxelwise genome-wide association study (vGWAS). Neuroimage 53, 1160-1174. doi: 10.1016/j.neuroimage.2010.02.032
54. Stein, J. L., Medland, S. E., Vasquez, A. A., Hibar, D. P., Senstad, R. E., Winkler, A. M., et al. (2012). Identification of common variants associated with human hippocampal and intracranial volumes. Nat. Genet. 44, 552-561. doi: 10.1038/ng.2250
55. Storey, J. D. (2002). A direct approach to false discovery rates. J. R. Stat. Soc. B 64, 479-498. doi: 10.1111/1467-9868.00346
56. Sun, J., Zheng, Y., and Hsu, L. (2013). A unified mixed-effects model for rare-variant association in sequencing studies. Genet. Epidemiol. 37, 334-344. doi: 10.1002/gepi.21717
57. Tanaka, N., Abe-Dohmae, S., Iwamoto, N., and Yokoyama, S. (2011). Roles of ATP-binding cassette transporter A7 in cholesterol homeostasis and host defense system. J. Atheroscler. Thromb. 18, 274-281. doi: 10.5551/jat.6726
58. Tost, H., Bilek, E., and Meyer-Lindenberg, A. (2012). Brain connectivity in psychiatric imaging genetics. Neuroimage 62, 2250-2260. doi: 10.1016/j.neuroimage.2011.11.007
59. Viding, E., Williamson, D. E., and Hariri, A. R. (2006). Developmental imaging genetics: challenges and promises for translational research. Dev. Psychopathol. 18, 877-892. doi: 10.1017/S0954579406060433
60. Wahlberg, K.-E., Wynne, L. C., Oja, H., Keskitalo, P., Pykalainen, L., Lahti, I., et al. (1997). Gene-environment interaction in vulnerability to schizophrenia: findings from the finnish adoptive family study of schizophrenia. Am. J. Psychiatry 154, 355-362. doi: 10.1176/ajp.154.3.355
61. Wang, H.-F., Tan, L., Hao, X.-K., Jiang, T., Tan, M.-S., Liu, Y., et al. (2015). Effect of EPHA1 genetic variation on cerebrospinal fluid and neuroimaging biomarkers in healthy, mild cognitive impairment and alzheimer's disease cohorts. J. Alzheimer's Dis. 44, 115-123. doi: 10.3233/JAD-141488
62. Wu, M. C., Lee, S., Cai, T., Li, Y., Boehnke, M., and Lin, X. (2011). Rare-variant association testing for sequencing data with the sequence kernel association test. Am. J. Hum. Genet. 89, 82-93. doi: 10.1016/j.ajhg.2011.05.029
63. Yaffe, K., Haan, M., Byers, A., Tangen, C., and Kuller, L. (2000). Estrogen use, APOE, and cognitive decline evidence of gene-environment interaction. Neurology 54, 1949-1954. doi: 10.1212/WNL.54.10.1949
64. Zhang, D., and Lin, X. (2003). Hypothesis testing in semiparametric additive mixed models. Biostatistics 4, 57-74. doi: 10.1093/biostatistics/4.1.57