Homogenizing estimates of heritability among SOLAR-eclipse, OpenMX, APACE, and FPHI software packages in neuroimaging data

Peter Kochunov*, Binish Patel, Habib Ganjgahi, Brian Donohue, Meghann Ryan, Elliot L. Hong, Xu Chen, Bhim Adhikari, Neda Jahanshad, Paul M. Thompson, Dennis Van’t Ent, Anouk den Braber, Eco J.C. de Geus, Rachel M. Brouwer, Dorret I. Boomsma, Hilleke E. Hulshoff Pol, Greig I. de Zubicaray, Katie L. McMahon, Nicholas G. Martin, Margaret J. WrightThomas E. Nichols

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review


Imaging genetic analyses use heritability calculations to measure the fraction of phenotypic variance attributable to additive genetic factors. We tested the agreement between heritability estimates provided by four methods that are used for heritability estimates in neuroimaging traits. SOLAR-Eclipse and OpenMx use iterative maximum likelihood estimation (MLE) methods. Accelerated Permutation inference for ACE (APACE) and fast permutation heritability inference (FPHI), employ fast, non-iterative approximation-based methods. We performed this evaluation in a simulated twin-sibling pedigree and phenotypes and in diffusion tensor imaging (DTI) data from three twin-sibling cohorts, the human connectome project (HCP), netherlands twin register (NTR) and BrainSCALE projects provided as a part of the enhancing neuro imaging genetics analysis (ENIGMA) consortium. We observed that heritability estimate may differ depending on the underlying method and dataset. The heritability estimates from the two MLE approaches provided excellent agreement in both simulated and imaging data. The heritability estimates for two approximation approaches showed reduced heritability estimates in datasets with deviations from data normality. We propose a data homogenization approach (implemented in solar-eclipse; www.solar-eclipse-genetics.org) to improve the convergence of heritability estimates across different methods. The homogenization steps include consistent regression of any nuisance covariates and enforcing normality on the trait data using inverse Gaussian transformation. Under these conditions, the heritability estimates for simulated and DTI phenotypes produced converging heritability estimates regardless of the method. Thus, using these simple suggestions may help new heritability studies to provide outcomes that are comparable regardless of software package.

Original languageEnglish
Article number16
Pages (from-to)1-11
Number of pages11
JournalFrontiers in Neuroinformatics
Issue numberMarch
Early online date12 Mar 2019
Publication statusPublished - Mar 2019


This study was supported by R01 EB015611 to PK, Foundation for the National Institutes of Health (NIH) BD2K grant, U54EB020403, R01 HD050735 to PT. This work was supported in part by a Consortium grant (U54 EB020403) from the NIH Institutes contributing to the Big Data to Knowledge (BD2K) Initiative, including the NIBIB and NCI. Data were provided by the HCP, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University. The NTR study (DvtE) was supported by the Netherlands Organization for Scientific Research [Medical Sciences (MW): grant no. 904-61-193; Social Sciences: grant no. 400-07-080; Social Sciences: grant no. 480-04-004]. The BrainSCALE study (HHP and DB) was supported by grants from the Dutch Organization for Scientific Research (NWO; 051.02.061) and 051.02.060. Computational support was provided by the NIH grant S10OD023696 to PK.

FundersFunder number
Dutch Organization for Scientific Research
Netherlands Organization for Scientific Research480-04-004, 904-61-193, 400-07-080
National Institutes of HealthS10OD023696, R01 HD050735, U54EB020403
National Cancer Institute1U54MH091657
National Institute of Biomedical Imaging and Bioengineering
NIH Blueprint for Neuroscience Research
McDonnell Center for Systems Neuroscience
Nederlandse Organisatie voor Wetenschappelijk Onderzoek051.02.061, 051.02.060


    • Computational methods
    • DTI
    • Genetics
    • Heritability
    • Imaging genetics
    • Population
    • Reproducability

    Cohort Studies

    • Netherlands Twin Register (NTR)


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