Heritability analysis with repeat measurements and its application to resting-state functional connectivity

Proceedings of the National Academy of Sciences of the United States of America

Volumn 114, Issue 21, 2017, Pages 5521-5526

  Ge, Tian ^a,b   Holmes, Avram J ^a,c   Buckner, Randy L ^a,d,e   Smoller, Jordan W ^a,b   Sabuncu, Mert R ^a,f  

^a MASSACHUSETTS GENERAL HOSPITAL   (United States)

^b BROAD INSTITUTE OF MIT AND HARVARD   (United States)

^c YALE UNIVERSITY   (United States)

^d HARVARD UNIVERSITY   (United States)

^e HARVARD UNIVERSITY   (United States)

^f School of Operations Research and Industrial Engineering   (United States)

Author keywords

Functional connectivity; Heritability; Repeat measurements; Resting state fMRI; Test retest reliability

Indexed keywords

ARTICLE; BRAIN REGION; DEFAULT MODE NETWORK; FUNCTIONAL CONNECTIVITY; FUNCTIONAL MAGNETIC RESONANCE IMAGING; GENETIC VARIATION; HERITABILITY; HUMAN; HUMAN EXPERIMENT; INFERIOR PARIETAL LOBULE; MEASUREMENT ACCURACY; MEASUREMENT ERROR; MEDIAL PREFRONTAL CORTEX; NORMAL HUMAN; PHENOTYPE; PHENOTYPIC VARIATION; POSTERIOR CINGULATE; PRIORITY JOURNAL; RESTING STATE NETWORK; SOMATOSENSORY CORTEX; TEMPORAL CORTEX; TEST RETEST RELIABILITY; TIME SERIES ANALYSIS; VENTRAL ATTENTION NETWORK; VISUAL CORTEX; ADOLESCENT; ADULT; BRAIN; COMPUTER SIMULATION; FEMALE; GENETIC PROCEDURES; MALE; NUCLEAR MAGNETIC RESONANCE IMAGING; PHYSIOLOGY; QUANTITATIVE TRAIT; STATISTICAL MODEL; YOUNG ADULT;

ADOLESCENT; ADULT; BRAIN; COMPUTER SIMULATION; FEMALE; GENETIC TECHNIQUES; HUMANS; LINEAR MODELS; MAGNETIC RESONANCE IMAGING; MALE; QUANTITATIVE TRAIT, HERITABLE; YOUNG ADULT;

EID: 85019591457     PISSN: 00278424     EISSN: 10916490     Source Type: Journal    
DOI: 10.1073/pnas.1700765114     Document Type: Article

References (37)

1. Visscher P, Hill W, Wray N (2008) Heritability in the genomics era-Concepts and misconceptions. Nat Rev Genet 9:255-266.
2. Falconer D (1960) Introduction to Quantitative Genetics (Oliver and Boyd Edinburgh).
3. Almasy L, Blangero J (1998) Multipoint quantitative-trait linkage analysis in general pedigrees. Am J Hum Genet 62:1198-1211.
4. Polderman T, et al. (2015) Meta-analysis of the heritability of human traits based on fifty years of twin studies. Nat Genet 47:702-709.
5. Yang J, et al. (2010) Common SNPs explain a large proportion of the heritability for human height. Nature Genetics 42:565-569.
6. Yang J, Lee S, Goddard M, Visscher P (2011) GCTA: A tool for genome-wide complex trait analysis. Am J Hum Genet 88:76-82.
7. Golan D, Lander E, Rosset S (2014) Measuring missing heritability: Inferring the contribution of common variants. Proc Natl Acad Sci USA 111:E5272-E5281.
8. Ge T, et al. (2015) Massively expedited genome-wide heritability analysis (MEGHA). Proc Natl Acad Sci USA 112:2479-2484.
9. Ge T, et al. (2016) Multidimensional heritability analysis of neuroanatomical shape. Nat Commun 7:13291.
10. Krüger G, Glover G (2001) Physiological noise in oxygenation-sensitive magnetic resonance imaging. Magn Reson Med 46:631-637.
11. Triantafyllou C, et al. (2005) Comparison of physiological noise at 1.5 T, 3 T and 7 T and optimization of fMRI acquisition parameters. Neuroimage 26:243-250.
12. Hutchison R, et al. (2013) Dynamic functional connectivity: Promise, issues, and interpretations. Neuroimage 80:360-378.
13. Mueller S, et al. (2013) Individual variability in functional connectivity architecture of the human brain. Neuron 77:586-595.
14. Glahn D, et al. (2010) Genetic control over the resting brain. Proc Natl Acad Sci USA 107:1223-1228.
15. Fornito A, et al. (2011) Genetic influences on cost-efficient organization of human cortical functional networks. J Neurosci 31:3261-3270.
16. Thompson P, Ge T, Glahn D, Jahanshad N, Nichols T (2013) Genetics of the connectome. Neuroimage 80:475-488.
17. Van Essen D, et al. (2013) The WU-Minn human connectome project: An overview. Neuroimage 80:62-79.
18. Yeo B, et al. (2011) The organization of the human cerebral cortex estimated by intrinsic functional connectivity. J Neurophysiol 106:1125-1165.
19. Holmes A, et al. (2015) Brain Genomics Superstruct Project initial data release with structural, functional, and behavioral measures. Sci Data 2:150031.
20. Laird N, Ware J (1982) Random-effects models for longitudinal data. Biometrics 38:963-974.
21. Verbeke G, Molenberghs G (2009) Linear Mixed Models for Longitudinal Data (Springer, New York).
22. Patterson H, Thompson R (1971) Recovery of inter-block information when block sizes are unequal. Biometrika 58:545-554.
23. Kendler K, Karkowski L, Prescott C (1999) Fears and phobias: Reliability and heritability. Psychol Med 29:539-553.
24. Dohm M (2002) Repeatability estimates do not always set an upper limit to heritability. Funct Ecol 16:273-280.
25. Deichmann R, Gottfried J, Hutton C, Turner R (2003) Optimized EPI for fMRI studies of the orbitofrontal cortex. Neuroimage 19:430-441.
26. Weiskopf N, Hutton C, Josephs O, Deichmann R (2006) Optimal EPI parameters for reduction of susceptibility-induced BOLD sensitivity losses: A whole-brain analysis at 3 T and 1.5 T. Neuroimage 33:493-504.
27. Power J, Barnes K, Snyder A, Schlaggar B, Petersen S (2012) Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. Neuroimage 59:2142-2154.
28. Van Dijk K, Sabuncu M, Buckner R (2012) The influence of head motion on intrinsic functional connectivity MRI. Neuroimage 59:431-438.
29. Satterthwaite T, et al. (2012) Impact of in-scanner head motion on multiple measures of functional connectivity: Relevance for studies of neurodevelopment in youth. Neuroimage 60:623-632.
30. van den Heuvel M, et al. (2013) Genetic control of functional brain network efficiency in children. Eur Neuropsychopharmacol 23:19-23.
31. Buckner R, Andrews-Hanna J, Schacter D (2008) The brain?s default network. Ann N Y Acad Sci 1124:1-38.
32. Van Essen D, et al. (2012) The Human Connectome Project: A data acquisition perspective. Neuroimage 62:2222-2231.
33. Smith S, et al. (2013) Resting-state fMRI in the human connectome project. Neuroimage 80:144-168.
34. Glasser M, et al. (2013) The minimal preprocessing pipelines for the Human Connectome Project. Neuroimage 80:105-124.
35. Robinson E, et al. (2014) MSM: A new flexible framework for Multimodal Surface Matching. Neuroimage 100:414-426.
36. Salimi-Khorshidi G, et al. (2014) Automatic denoising of functional MRI data: Combining independent component analysis and hierarchical fusion of classifiers. Neuroimage 90:449-468.
37. Efron B, Tibshirani R (1994) An Introduction to the Bootstrap (CRC, Boca Raton, FL).