Exact variance component tests for longitudinal microbiome studies

Genetic Epidemiology - Tập 43 Số 3 - Trang 250-262 - 2019
Jing Zhai1, Kenneth S. Knox2, Homer L. Twigg3, Hua Zhou4, Jin Zhou1
1Department of Epidemiology and Biostatistics, University of Arizona, Tucson, Arizona
2Division of Pulmonary, Allergy, Critical Care, Sleep Medicine, Department of Medicine, University of Arizona, Tucson, Arizona
3Division of Pulmonary, Critical Care, Sleep, and Occupational Medicine, Indiana University Medical Center, Indianapolis, Indiana
4Department of Biostatistics, University of California, Los Angeles, California

Tóm tắt

AbstractIn metagenomic studies, testing the association between microbiome composition and clinical outcomes translates to testing the nullity of variance components. Motivated by a lung human immunodeficiency virus (HIV) microbiome project, we study longitudinal microbiome data by using variance component models with more than two variance components. Current testing strategies only apply to models with exactly two variance components and when sample sizes are large. Therefore, they are not applicable to longitudinal microbiome studies. In this paper, we propose exact tests (score test, likelihood ratio test, and restricted likelihood ratio test) to (a) test the association of the overall microbiome composition in a longitudinal design and (b) detect the association of one specific microbiome cluster while adjusting for the effects from related clusters. Our approach combines the exact tests for null hypothesis with a single variance component with a strategy of reducing multiple variance components to a single one. Simulation studies demonstrate that our method has a correct type I error rate and superior power compared to existing methods at small sample sizes and weak signals. Finally, we apply our method to a longitudinal pulmonary microbiome study of HIV‐infected patients and reveal two interesting genera Prevotella and Veillonella associated with forced vital capacity. Our findings shed light on the impact of the lung microbiome on HIV complexities. The method is implemented in the open‐source, high‐performance computing language Julia and is freely available at https://github.com/JingZhai63/VCmicrobiome.

Từ khóa


Tài liệu tham khảo

10.1016/S0022-2836(05)80360-2

10.1126/science.aad9358

10.2307/1942268

10.1186/1471-2105-12-118

10.1093/bioinformatics/btw308

10.1016/j.ajhg.2016.02.012

10.1093/bioinformatics/bts342

10.1002/gepi.21934

10.1111/j.0006-341X.2003.00089.x

10.2307/2533167

10.1111/j.1467-9868.2004.00438.x

10.1513/AnnalsATS.201402-052PL

10.1586/ers.13.24

10.1093/biostatistics/kxs028

10.1126/science.1110591

10.1371/journal.pone.0016384

10.1093/nar/gkr1178

10.1038/nature18850

10.1198/106186008X386599

10.1101/gr.112730.110

Annals of Translational Medicine 2017 5 The respiratory microbiome in idiopathic pulmonary fibrosis

10.1056/NEJMc1212055

10.1089/wound.2014.0542

10.1038/ncomms12015

10.1111/all.13331

10.1111/j.1541-0420.2007.00771.x

10.1038/nbt.3416

10.1093/bioinformatics/btl529

10.1093/nar/gkr201

10.1093/biomet/84.2.309

10.1038/nature23889

10.1164/rccm.201211-2145OC

10.1128/AEM.71.12.8228-8235.2005

10.1128/AEM.01996-06

10.1093/nar/24.1.82

10.1164/rccm.201210-1913OC

10.1101/gr.201863.115

10.2307/2532601

10.1371/journal.pone.0047305

10.1111/biom.12095

10.4161/gmic.1.2.11350

10.1111/j.1541-0420.2008.01107.x

10.1128/AEM.01541-09

10.1016/j.chom.2017.03.003

10.1080/01621459.1987.10478472

Silvapulle M. J., 2011, Constrained statistical inference: Order, inequality, and shape constraints

10.2307/2533455

10.1101/gr.216242.116

10.1164/rccm.201210-1937OC

10.1016/S2213-2600(13)70117-6

10.1164/rccm.201509-1875OC

10.1038/nrmicro.2016.83

Weiden M. D., 2017, Lung microbiome dysbiosis is a risk factor for pulmonary diffusion abnormalities in antiretroviral treated HIV‐infection, American Journal of Respiratory and Critical Care Medicine, 195, A1002

10.1371/journal.pbio.0050156

10.1097/MOP.0b013e32834604f2

10.1016/j.immuni.2016.02.006

10.1002/gepi.22030

10.1016/j.ajhg.2015.04.003

10.1534/genetics.116.190454

Thông tin
Thông tin xuất bản

Genetic Epidemiology

Tập 43 Số 3

250-262

Thông tin tác giả