Fine-mapping diabetes-related traits, including insulin resistance, in heterogeneous stock rats

Abstract

(T2D) is a disease of relative insulin deficiency resulting from both insulin resistance and beta cell failure. We have previously used heterogeneous stock (HS) rats to fine-map a locus for glucose tolerance. We show here that glucose intolerance in the founder strains of the HS colony is mediated by different mechanisms: insulin resistance in WKY and an insulin secretion defect in ACI, and we demonstrate a high degree of variability for measures of insulin resistance and insulin secretion in HS rats. As such, our goal was to use HS rats to fine-map several diabetes-related traits within a region on rat chromosome 1. We measured blood glucose and plasma insulin levels after a glucose tolerance test in 782 male HS rats. Using 97 SSLP markers, we genotyped a 68 Mb region on rat chromosome 1 previously implicated in glucose and insulin regulation. We used linkage disequilibrium mapping by mixed model regression with inferred descent to identify a region from 198.85 to 205.9 that contains one or more quantitative trait loci (QTL) for fasting insulin and a measure of insulin resistance, the quantitative insulin sensitivity check index. This region also encompasses loci identified for fasting glucose and Insulin_AUC (area under the curve). A separate Ͻ3 Mb QTL was identified for body weight. Using a novel penalized regression method we then estimated effects of alternative haplotype pairings under each locus. These studies highlight the utility of HS rats for fine-mapping genetic loci involved in the underlying causes of T2D. obesity; Type 2 diabetes; glucose tolerance; metabolism TYPE 2 DIABETES (T2D) IS A disease of relative insulin deficiency resulting from a combination of insulin resistance and decreased beta-cell function (50,57). This complex disorder is caused by a combination of both environmental and genetic factors. Although diet and exercise are the major environmental factors contributing to T2D (25), the genetic factors contributing to this disease are only beginning to be understood. Over the past several years, over 40 genes have been identified for T2D in human genome-wide association studies (GWAS) (see Refs. 38,62,78). Even when the effects of these genes are combined, however, they explain only 10% of the heritable variance (78), indicating that many genetic factors remain unidentified and highlighting our limited understanding of this disorder.We have previously used heterogeneous stock (HS) rats to fine-map a locus for glucose tolerance to 2.44 megabases (Mb) (64). The HS rat colony at the Medical College of Wisconsin (MCW) comprises outbred animals derived by the National Institutes of Health (NIH) in 1984 from a set of eight genetically and phenotypically diverse inbred founder strains: ACI/N, BN/N, BUF/N, F344/N, M520/N, MR/N, WKY/N, WN/N (23). HS populations are powerful tools for genetic studies because they provide a basis for high resolution mapping of quantitative trait loci (QTL) in a relatively short time period (64,72). Although none of the inbred founder strains of the HS rat colony ...

Premature responding is associated with approach to a food cue in male and female heterogeneous stock rats

“…In further contrast to Lovic et al., (2011), our current study used HS rats, which increases the detection of genetic sources of correlation. Previously, this line of subjects has been used to map the genetic loci of traits related to diabetes (Solberg Woods et al 2010a; Solberg Woods et al 2012 ; Solberg Woods et al 2010b) and is currently being used to map the genetic loci of traits for complex drug-related behaviors by an NIH funded center (see http://ratgenes.org/). HS rats are especially valuable because they are more likely to generate conclusions that may better generalize than any single inbred strain.…”

Identification of a Novel Gene for Diabetic Traits in Rats, Mice, and Humans

“…The model included all appropriate covariates (location, injector, collector, and number of glucose injections) and accounted for the complex family relationships of the HS, as previously described (Solberg Woods et al 2010, 2012). The significance threshold was determined using the Bonferroni method to account for multiple comparisons (18 SNPs by six traits).…”

QTL mapping in outbred populations: successes and challenges

“…Similar to the HS mouse, the HS rat has been used to map hundreds of traits to an average of 4.5 Mb, with several causal genes being identified (6). In addition to this large study, the N:NIH-HS rat colony has also been used to fine-map traits involved in fear (44) and diabetes (76,77). Other studies show that the HS rat will be a promising model for mapping kidney-related traits (78), bone fragility (3), drug abuse behavior (71), as well as behavioral and physiological responses to stress (21,55,56) and to ethanol (8,33,79).…”

“…This can be done using mixed modeling approaches such as EMMA (46), as applied in AI (14), HS (76,77), and DO (80), or by using resample model averaging (87). QTLRel, an R package recently developed for this purpose, makes it relatively easy to account for family relationships in highly recombinant animal populations, particularly when full pedigree information is known (13).…”

“…Many studies use the 1.5 LOD drop method (e.g., Refs. 53,72,77). An alternative approach is to use nonparametric bootstrapping (37), in which the QTL is re-estimated under alternative datasets based on the original, with each alternative dataset created by resampling the individuals with replacement (92).…”