Our understanding of how genetic variants influence molecular regulatory networks in glucose responsive tissues, and in turn affect cellular processes related to insulin resistance (IR) in different ethnic groups, remains incomplete. We employ a network modelling approach to integrate measures of insulin sensitivity, transcriptomic data in the adipose and muscle tissues, and genetic data from African Americans (AAs) in the AAGMEx cohort (N=256). Data from European ancestry (EA) individuals from AREA (N=99) and METSIM (N=770) cohorts are used as contrast. Multiscale Embedded GEne coexpression Network Analysis (MEGENA) in AAs identifies 167 and 63 transcript subnetworks (modules) enriched for Matsuda index and SI-correlated genes in adipose and muscle, respectively. Among these IR-associated modules, 11 in adipose and 6 in muscle, are enriched for the cis-eSNP genes. Bayesian probabilistic causal networks (BN) are constructed and subsequently used to identify key network drivers. Integration of MEGENA and BN in AAs identifies 99 and 39 key regulators for IR-associated adipose and muscle modules, respectively. Among the IR-associated modules in AAs, 23 in adipose and 5 in muscle are strongly preserved in the respective networks in the EA cohorts. Top 3 IR-associated preserved adipose modules are enriched for immune system, mitochondria and hormonal response and these modules are potentially regulated by KYNU, LDHD and ENO1, respectively. We identify 50 and 24 IR-associated but AA-specific modules (not preserved in EAs) in adipose and muscle, respectively. Conversely, we find 28 IR-associated but EA-specific modules in adipose. Ethnic group specific and shared modules reveal novel molecular mechanisms for IR. Enrichment of cis-eSNP genes in the network neighborhoods of key drivers suggest that regulatory SNPs may configure the networks by modulating transcript expression in adipose and muscle tissues, and are likely causal determinants for IR.


P. Xu: None. M. Wang: None. N.K. Sharma: None. M. Comeau: None. M. Civelek: None. C.D. Langefeld: None. B. Zhang: None. S.K. Das: None.


National Institutes of Health (R01DK118243, R01DK090111)

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