The HADHSC Gene Encoding Short-Chain l-3-Hydroxyacyl-CoA Dehydrogenase (SCHAD) and Type 2 Diabetes Susceptibility : The DAMAGE Study

Subjects participating in the association studies were selected from four study populations in the Netherlands and Denmark. The first cohort, HS1, consisted of 470 participants of the Hoorn Study, a population-based study in the Netherlands (14). Subjects were classified as having type 2 diabetes (n = 210, aged 65 ± 8 years, 48% men) or as glucose-tolerant control subjects (n = 260, aged 60 ± 7 years, 42% men) based on the baseline fasting oral glucose tolerance test according World Health Organization criterion.

Furthermore, we used a second sample from the same study, the HS2 cohort (15). Subjects with either normal glucose tolerance (NGT) or type 2 diabetes at the year 2000 survey of the Hoorn Study were included in this cohort. To enhance power, the type 2 diabetes group was supplemented by subjects with screen-detected type 2 diabetes from the same geographic area (n = 217) (16). There was no overlap between the subjects in either cohort. In the type 2 diabetes group (n = 297), the mean age was 68 ± 8 years (48% men) and 69 ± 6 years for participants with NGT (n = 283, 50% men).

Both Dutch cohorts are part of the DAMAGE (Diabetes and Mitochondrial Aging Genes) study. Furthermore, we genotyped two case-control study samples from Denmark, DK1 and DK2. DK1 was a group of unrelated type 2 diabetic patients recruited from the Steno Diabetes Center, and a group of unrelated subjects with NGT sampled at random through public registers at the Steno Diabetes Center and the Research Centre for Prevention and Health (17). In the group of type 2 diabetic patients (n = 603, 59% men), the mean age was 60 ± 10 years and 58 ± 10 years for participants with NGT (n = 527, 46% men) (17).

DK2 consisted of unrelated type 2 diabetic patients recruited from the Steno Diabetes Center and the Research Centre for Prevention and Health (n = 756, aged 54 ± 10 years, 61% men), and a group of unrelated subjects with NGT sampled from the prospective Inter99 Study at the Research Centre for Prevention and Health (n = 4,429, aged 45 ± 8 years, 47% men) (18,19). All control subjects participating in the Danish studies underwent an oral glucose tolerance test according to World Health Organization criteria. Questionnaires were used to obtain other relevant information.

All participants were Caucasian by self-report. Informed written consent was obtained from all subjects before participation. The study was approved by the appropriate medical ethical committees and was in accordance with the principles of the Declaration of Helsinki.

HADHSC is mapped to the chromosome 4q22–26 region and spans ∼50 kb. Its eight exons encode a 314 aa protein (gene no. 3033). Total RNA was isolated from leukocytes (n = 25) and/or pancreas tissue (n = 7) from 25 Dutch volunteers with familial late-onset type 2 diabetes using standard procedures, which was subsequently converted into cDNA using a first-strand cDNA synthesis kit (Invitrogen, Carlsbad, CA). The coding region of HADHSC was amplified in two overlapping segments (primer sequences and assay conditions available from the authors on request). The resulting segments encompassing 1,036 bp of the coding region (including 32 and 59 bp 5′ and 3′, respectively, of the gene) were subsequently sequenced on an automated sequencer (Applied Biosystems, Foster City, CA).

Tagging single nucleotide polymorphisms (SNPs) in HADHSC were identified using the Haploview/Tagger software based on Hapmap Phase I CEPH data (multimarker method, r² > 0.8 and logarithm of odds threshold 3.0). Four tagging SNPs (rs4521419, rs4590125, rs4956145, and rs141066; databank accessed June 2005) (online appendix Fig. 1 [available at http://diabetes.diabetesjournals.org]), including one SNP in the coding region (P86L, rs4956145), were genotyped based on Taqman SNP genotyping technology (Applied Biosystems). Upon genotyping, two of the SNPs (rs4521419 and rs4956145) appeared to be in perfect linkage disequilibrium. Genotyping success rates were >95% for all SNPs. The P86L variant (rs4956145) was additionally tested via a PCR/restriction fragment–length polymorphism–based method in a subset of the samples (n = 188). Furthermore we confirmed the presence of the four variants by direct sequencing of DNA segments in 40 subjects. No discrepancies between the different methods were identified. Replication samples (n >350) for all SNPs showed an error rate <0.3%. Haplotypes were reconstructed using the Phase (version 2.1.1) program (20).

SCHAD enzyme activity was determined in duplicate in crude lysates and mitochondrial fractions from fibroblast cell lines and is given as the SCHAD/Citrate synthase activity ratio (units per Citrate synthase units [CSU]) as described by Clayton et al. (1). We had 80% power (α = 0.05) to detect a difference of at least 20–25%.

SCHAD protein expression was determined by Western blot analysis using a rabbit polyclonal antibody raised against the protein (21). Total fibroblast lysates and mitochondrial fractions were separated on a polyacrylamide gel according to standard procedures. Enhanced chemiluminescence was used to visualize the 34 kd and corresponding to the SCHAD protein.

HADHSC mRNA levels were determined in total RNA isolated from fibroblasts using quantitative real-time PCR on a ABI 7900ht. Glyceraldehyde-3-phosphate dehydrogenase, HPRT1, and β-actin were used as control genes.

Hardy-Weinberg equilibrium was confirmed in all cohorts before further analysis. Differences in allele or genotype frequencies were tested by Fisher’s exact tests or logistic regression analysis with age and sex as covariates. A common odds ratio (OR) was calculated after testing the homogeneity of the population-specific ORs revealed no significant differences using a Mantel-Haenzel test. Differences in clinical variables were tested by ANOVA and/or linear regression analysis with adjustment for age, sex, and BMI. Variables were log transformed before analysis if necessary. The statistical software packages SPSS11 (SPSS, Chicago, IL) and StatXact6.0 (Cytel, Cambridge, MA) were used.

Databank analysis and direct sequencing of HADHSC cDNA revealed 17 common intronic SNPs (minor allele frequency >0.05) and three cSNPs in this locus. The three cSNPs were all nonsynonymous variants: P86L (rs4956145), H152Q (rs1051519), and D279E (rs17417368). The latter two seemed to be rare and were not detected in our (sequenced) samples. Therefore, we focused our research on the P86L variant and three tagging SNPs that capture all other alleles in the HapMap Phase I CEPH dataset (online appendix Fig. 1).

The minor allele frequency of the P86L variant varied between 6.6 and 9.2% in the different case-control groups from the Netherlands and Denmark (Table 1). Only in the DK1 cohort did the difference reach statistical significance (P = 0.04; Table 1). Meta-analysis was used to calculate a common OR after homogeneity testing revealed no significant differences between the studies (P > 0.05). The common OR was 1.08 (95% CI 0.93–1.26, P = 0.29) (Table 1 and online appendix Fig. 2). Adjustment for age and sex did not significantly alter the results. Analysis of the genotype distributions in the different cohorts assuming different genetic models and adjusted for age and sex yielded similar nonsignificant results (online appendix Table 1). Based on the observed allele frequency of the P86L variant (minor allele frequency 0.08), we had >80% power to detect effects with an OR ≥1.2 (α = 0.05) in our sample (>95% for an OR ≥1.25). Circulating glucose, insulin, and lipid levels, as well as other relevant diabetes-related clinical variables, were also not significantly different between normoglycemic carriers and noncarriers (Table 2).

We determined SCHAD enzyme activity in mitochondrial fractions isolated from fibroblasts of 5 carriers and 10 noncarriers of the P86L variant. Enzyme activities were, however, not significantly different (0.64 ± 0.14 vs. 0.60 ± 0.07 units/UCS, P > 0.5). SCHAD enzyme activities in total fibroblast lysates showed a similar nonsignificant difference. Furthermore, there were no detectable differences in SCHAD protein and mRNA levels between carriers and noncarriers (data not shown). Together, this suggests that the P86L variant has no effect on enzyme levels or function, although small differences cannot be fully excluded.

According to the Hapmap Phase I CEPH data, HADHSC is present on one single haploblock spanning the whole locus (online appendix Fig. 1). The four common haplotypes (>1%) in HADHSC can be tagged by four tagging SNPs, which were typed in subsets of the HS1 (n = 630) and DK1 (n = 520) studies. We also examined the performance of our tagging SNPs in the recently available HapMap Phase II CEPH (January 2006) dataset. Our tagging SNPs captured almost all of the SNPs identified in the HADHSC region from the Phase II dataset, capturing 48 of 55 common SNPs with a mean r² of 0.991 and 100% of alleles with r² > 0.8.

Haplotype frequency distributions are very similar in both populations. In a joint analysis of all haplotypes in relation to disease status, there was no significant difference between case and control subjects in both cohorts. There were also no significant differences in the frequency of the four most common haplotypes (all P > 0.1), although we observed similar trends in both populations, especially with the 0-0-0-1 haplotype (Table 3). Our combined case-control sample provides at least 80% power to detect an effect with an OR ≥1.35 (assuming f = 0.33 [0-0-0-1 haplotype] and α = 0.05).

To examine the possibility that the 0-0-0-1 haplotype is associated with altered enzyme function and a minor effect on type 2 diabetes susceptibility, we determined SCHAD activity in mitochondrial fractions from fibroblasts of four homozygous carriers of this haplotype and four homozygous carriers of the common 0-0-0-0 haplotype. Enzyme activity was not detectably different between the two haplotypes (0.57 ± 0.13 vs. 0.62 ± 0.11 for 0-0-0-0 haplotypes, P > 0.5). There was also no evidence for differences in expression levels between carriers and noncarriers (data not shown).

In this study, which is the first ever to examine the relationship between variations in HADHSC and type 2 diabetes, we have found no evidence for an association between variants at this gene locus and susceptibility to develop type 2 diabetes.

Based on the above-described results, the fact that we found no evidence for alterations in circulating glucose, insulin, or lipid levels in NGT carriers of these gene variants, and given that the data show that the variants investigated in this study have no detectable effect on expression levels or enzyme function, we conclude that variation in HADHSC is unlikely to have a major effect on susceptibility to develop type 2 diabetes in these cohorts.

This study was supported by the Dutch Diabetes Research Foundation; the Netherlands Organisation for Health Research and Development; the Research Institute for Diseases in the Elderly (RIDE program); the Center for Medical Systems Biology; the Danish Medical Research Council; the Danish Center for Evaluation and Health Technology; the Danish Heart Foundation; Novo Nordic; Copenhagen County; the Danish Pharmaceutical Association; the Danish National Board of Health; the Velux, Augustinus, Ib Henriksen, and Becket Foundations; the Danish Diabetes Association; and European Economic Committee grants (BMH4-CT98-3084 and QLRT-CT-1999-00546).

We thank all participants for their kind cooperation. A.W. Strauss (Nashville, TN) is kindly acknowledged for the gift of the SCHAD antibody. Annemette Forman, Inge Lise Wantzin, Marianne Stendal, and the staff from the Research Center for Prevention and Health (Glostrup, Denmark) are thanked for dedicated and careful assistance and Grete Lademann for secretarial support.