Linkage Analysis of Diabetes Status Among Hypertensive Families: The Hypertension Genetic Epidemiology Network Study

Type 2 diabetes is a common disease with susceptibility determined by multiple genetic and environmental factors. Several rare mutations have been identified that influence diabetes susceptibility, yet only one common susceptibility gene has been identified, the CAPN10 gene (1), and it is associated with diabetes in some study populations but not others (2). Genome-wide scans for linkage have been conducted in several populations, localizing a number of common chromosomal regions possibly harboring susceptibility genes on chromosomes 1q21-24 (3), 2q37 (1), 12q24 (4), and 20q (3). Such variability in linkage findings reported between populations underscores the probable genetic heterogeneity of type 2 diabetes. Thus, we conducted a genome scan of liability to diabetes in an attempt to localize new quantitative trait loci (QTLs) influencing diabetes susceptibility and/or to provide new evidence in support of previously identified QTLs.

This study examined 3,153 participants in the Hypertension Genetic Epidemiology Network (HyperGEN) of the Family Blood Pressure Program. HyperGEN methods, participant information, and exclusion criteria are detailed in the online appendix (available at http://care.diabetesjournals.org). The distribution of covariates by diabetes status for the combined sample is shown in Table 1. The prevalence of type 2 diabetes was 18% (n = 567), with a higher prevalence of female (64%) compared with male (36%) subjects. In African-American participants, 21% were classified as diabetic compared with 15% of the Caucasian sample. Overall, 385 of 437 HyperGEN families had at least 1 affected participant, with 98 families having 2 diabetic family members, 11 families having 3 diabetic members, 3 families having 4 diabetic members, and 1 family with 5 diabetic members.

The multipoint genome-wide logarithm of odds (LOD) scores for the combined sample by race, with and without percent body fat [PBF] adjustment for all peaks, with a LOD score ≥1.7 (suggestive evidence of linkage) (5) are given in Table 2. We detected a QTL influencing liability to diabetes status in the complete sample, with a corresponding LOD score of 3.4 on chromosome 22q12.1 at map location 28 cM (22q12.1, nearest marker GATA21F03) (Fig. 1), which overlaps three positive findings (Table 3). The robust P value that corresponds to our observed LOD score is 0.001, indicating that our nominal P value may have slightly overstated the evidence of linkage.

Hegele et al. (6) detected a QTL for type 2 diabetes (P < 0.01) among 88 Canadian Oji-Cree Indian kindred, and Sale et al. (7) observed linkage for type 2 diabetes in 1,276 affected African Americans (LOD = 1.3); both used affected sibpair linkage designs. Additionally, Pratley et al. (8) observed linkage for fasting plasma glucose in 109 nondiabetic Pima-Indian families (LOD = 1.8) using variance component methods.

A secondary significant genome-wide LOD score of 3.1 was detected on chromosome eight at map location 65 cM (8q11.23, nearest marker GATA8G10) for the combined sample after PBF adjustment (Fig. 1). This LOD score was only slightly attenuated (LOD = 2.5) in the absence of PBF adjustment. The robust P value that corresponds to our observed LOD score is 0.003, indicating that our nominal P value may have slightly overstated the evidence of linkage. This finding also supports three previous genome-wide scans. Elbein et al. (9) detected linkage to type 2 diabetes in 379 members of 19 multiplex Caucasian families using variance component methods (LOD = 1.4). Additionally, Mitchell et al. (10) and Chagnon et al. (11) both detected linkage to BMI measures in 10 large Mexican-American families (LOD = 3.2) and 364 Caucasian sibpairs (LOD = 2.0), employing variance component and affected sibpair linkage methods, respectively.

Evidence for linkage was also detected on chromosome 17 map location 53 cM (17q11.2, nearest marker GGAA9D03) for the combined (LOD = 3.0) and the Caucasian samples (LOD = 2.7). This signal appears to attenuate after PBF adjustment, which may indicate shared genetic effects between obesity and diabetes. The robust P value that corresponds to our observed LOD score is 0.003, indicating that our nominal P value may have slightly overstated the evidence of linkage. Likewise, this finding supports numerous genome-wide scans related to obesity measures, such as plasma leptin and adiponectin levels and BMI. Kissebah et al. (12), Wu et al. (13), and Comuzzie et al. (14) detected linkage to plasma leptin (LOD = 5.0), BMI (LOD = 2.5), and adiponectin (LOD = 1.7), respectively, using variance component linkage methods. In addition to the QTL on chromosomes 22, 8, and 17, we found several other regions demonstrating suggestive evidence for linkage on chromosomes 1, 2, 5, 14, and 19. Of these locations, all have been detected (based on various criteria) in other genome screens of diabetes-related phenotypes with the exception of the signal at 14q21.1.

Several candidate genes underlie the 1-cM LOD unit drop support interval (9 cM, 8.3 megabases) corresponding to the linkage signal observed on 22q12.1, including the galanin receptor 3 (GALR3), leukemia inhibitory factor (LIF), and the apolipoprotein L1-L4 (APOL1-4) cluster. Neuroanatomical distribution of GALR3 mRNA suggests a mediation of galanin on food intake, fluid homeostasis, and cardiovascular function (15). LIF is a member of the interlukin 6 cytokine family and is a candidate for leptin circumvention and weight loss (16). APOL1-4 represents a cluster of tandem gene duplications expressed in various human organs, including vascular tissue and endothelial cells. A lipid-related candidate gene may be relevant to diabetes susceptibility, as insulin resistance is associated with a lipid profile typified by increased triglyceride and LDL cholesterol levels and a predominance of small LDL particles. Moreover, North et al. (17) demonstrated common genetic effects on diabetes status and lipid values in American-Indian families participating in the Strong Heart Family Study.

Candidate genes within the 1-cM LOD unit drop support interval (24 cM, 33.3 megabases) surrounding the 8q11.23 QTL include the adrenergic β-3 receptor (ADRB3), corticotropin releasing hormone (CRH), and fibroblast growth factor receptor 1 (FGFR1). ADRB3 is expressed in adipose tissue where it mediates lipolysis. Furthermore, Xiang et al. (18) detected an association between the ADRB3 Trp64Arg mutation and BMI (P = 0.019) and waist circumference (P = 0.045) in type 2 diabetic Chinese subjects. CRH secretion by the paraventricular nucleus of the hypothalamus is one of the first steps in the mammalian stress response. Hart et al. (19) perturbed FGFR1 dominant-negative signaling in the mouse pancreas and observed a phenotype typical of type 2 diabetes. They demonstrated that mice with attenuated FGFR1 signaling developed diabetes with age, exhibited decreased numbers of β-cells, and had increased proinsulin content in β-cells.

Genetic heterogeneity of common complex traits is a long-standing problem for linkage studies. When genetic heterogeneity is present, there is reduced power for detection of QTLs. Genetic heterogeneity may be reduced by stratifying possible etiological subgroups, incorporating gene-environment and gene-gene interactions, and accounting for environmental influences of disease. Our study design may have reduced the problem of genetic heterogeneity, as we conducted a genome scan for diabetes in a largely hypertensive population.

This study may have been limited by our inability to adjust for potential disease confounders. Moreover, we lacked information on the age of onset of diabetes status for 99 participants who we classified as diabetic, which may have introduced type 1 diabetic participants into our sample. The population we examined was selected for hypertension, a phenotype correlated with diabetes; however, we have not used an ascertainment correction in these analyses. This is not likely a strong ascertainment effect because enriching our sample for hypertension-related susceptibility alleles would not be expected to strongly influence the distribution of diabetes QTLs. Neglecting a modest ascertainment effect would only result in some loss of information and a reduced power for our analysis, making the results presented here conservative, without any increase in the type I error rate (20). Nonetheless, these loci were detected in a largely hypertensive sample and may not be applicable to the general population.

We assumed that pleiotropic effects between type 2 diabetes and obesity QTLs were possible; yet we know that obesity is an important confounder, such that only by accounting for the variance due to obesity effects would we be able to identify type 2 diabetes QTLs. Indeed, the QTL-specific genetic signals varied substantially on chromosomes 22, 8, and 17, after adjustment for PBF. For example, the LOD score on chromosome 22q decreased from 3.4 to 2.0 in the combined-races sample after adjustment for PBF. Similarly, the LOD score on chromosome 17 decreased from 3.0 to 0.60 in the combined-races sample after adjustment for PBF, indicating the possibility of shared genetic effects between PBF and diabetes susceptibility. In contrast, upon adjustment for PBF, the QTL on chromosome 8q increased from 2.5 to 3.1 in the combined- races sample, suggesting that adjustment for PBF slightly improved our ability to detect this particular QTL. Further research is needed to test if there is a joint action of genes on diabetes status and PBF and whether modeling such an effect would improve our ability to localize diabetes susceptibility genes.

In conclusion, we found highly significant linkage results for diabetes susceptibility QTLs on chromosomes 22, 8, and 17. Specifically, the signal on 22q12.1 overlaps positive findings for diabetes status, abdominal subcutaneous fat, and plasma glucose and harbors several candidate genes, including GALR3, LIF, and the APOL1-L4 cluster. The 8q11.23 signal supports previous findings for diabetes status and BMI and points to several candidate genes: ADRB3, CRH, and FGFR1. Additionally, all QTLs that demonstrated suggestive evidence of linkage with type 2 diabetes support earlier studies, with the exception of the QTL at 14q12.1. Ultimately, these findings suggest that multiple genes may regulate susceptibility to diabetes and that further research in this population may help to identify additional candidate genes that interact with the environment to influence diabetes susceptibility.