A kernel machine method for detecting higher order interactions in multimodal datasets: Application to schizophrenia

J Neurosci Methods. 2018 Nov 1;309:161-174. doi: 10.1016/j.jneumeth.2018.08.027. Epub 2018 Sep 2.


Background: Technological advances are enabling us to collect multimodal datasets at an increasing depth and resolution while with decreasing labors. Understanding complex interactions among multimodal datasets, however, is challenging.

New method: In this study, we tested the interaction effect of multimodal datasets using a novel method called the kernel machine for detecting higher order interactions among biologically relevant multimodal data. Using a semiparametric method on a reproducing kernel Hilbert space, we formulated the proposed method as a standard mixed-effects linear model and derived a score-based variance component statistic to test higher order interactions between multimodal datasets.

Results: The method was evaluated using extensive numerical simulation and real data from the Mind Clinical Imaging Consortium with both schizophrenia patients and healthy controls. Our method identified 13-triplets that included 6 gene-derived SNPs, 10 ROIs, and 6 gene-specific DNA methylations that are correlated with the changes in hippocampal volume, suggesting that these triplets may be important for explaining schizophrenia-related neurodegeneration.

Comparison with existing method(s): The performance of the proposed method is compared with the following methods: test based on only first and first few principal components followed by multiple regression, and full principal component analysis regression, and the sequence kernel association test.

Conclusions: With strong evidence (p-value ≤0.000001), the triplet (MAGI2, CRBLCrus1.L, FBXO28) is a significant biomarker for schizophrenia patients. This novel method can be applicable to the study of other disease processes, where multimodal data analysis is a common task.

Keywords: Higher order interaction; Imaging genetics and epigenetics; Kernel machine methods; Multimodal datasets; Schizophrenia.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Adult
  • Algorithms
  • Computer Simulation
  • Female
  • Humans
  • Machine Learning*
  • Male
  • Multivariate Analysis*
  • Neuroimaging / methods*
  • ROC Curve
  • Schizophrenia / diagnosis*
  • Schizophrenia / diagnostic imaging
  • Schizophrenia / genetics