Physiol. Genomics AJP: Gastrointestinal and Liver Physiology
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Physiol. Genomics 29: 181-192, 2007. First published January 9, 2007; doi:10.1152/physiolgenomics.00210.2006
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Received 26 September 2006; accepted in final form 9 January 2007.
Physiological Genomics 29:181-192 (2007)
1094-8341/07 $8.00 © 2007 American Physiological Society

Metabolic and genomic dissection of diabetes in the Cohen rat

Chana Yagil1, Ronit Barkalifa1, Marina Sapojnikov1, Alexander Wechsler1, David Ben-Dor2, Sarah Weksler-Zangen3, Nurit Kaiser4, Itamar Raz3 and Yoram Yagil1

1 Laboratory for Molecular Medicine and Israeli Rat Genome Center, Ben-Gurion University Barzilai Medical Center Campus, Ashkelon
2 Department of Pathology, Faculty of Health Sciences, Ben-Gurion University Barzilai Medical Center Campus, Ashkelon
3 Diabetes Unit, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
4 Endocrinology and Metabolism Service, Hadassah-Hebrew University Medical Center, Jerusalem, Israel


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
We investigated the metabolic and genetic basis of diabetes in the Cohen Diabetic rat, a model of diet-induced diabetes, as a means to identify the molecular mechanisms involved. By altering individual components in the diabetogenic diet, we established that the dietary susceptibility that leads to the development of diabetes in this model is directly related to the high casein and low copper content in chow. The development of diabetes is accompanied by depletion of the acini from the exocrine pancreas and replacement with fat cells, while the appearance of the islets of Langerhans remains intact. With reversion back from diabetogenic to regular diet, the diabetic phenotype disappears but the histological changes in the exocrine pancreas prevail. Using positional cloning, we detected a major quantitative trait locus (QTL) on rat chromosome 4 with a chromosomal span of 4.9 cM, and two additional loci on chromosomes 7 and X. A screen for genes within that QTL in the rat and in the syntenic regions in mouse and man revealed only 23 candidate genes. Notable among these genes is Ica1, which has been causally associated with diabetes and bovine casein. We conclude that the development of diabetes in our model is dependent upon high casein and low copper in diet, that it is accompanied by histomorphological changes in the exocrine but not endocrine pancreas, that it is reversible, and that it is associated with a major QTL on chromosome 4 in which we detected Ica1, a high priority candidate gene.

diet-induced; genetic susceptibility; candidate genes


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
THE COHEN DIABETIC RAT IS a nonobese experimental rodent model reminiscent of diabetes in humans. We previously described in detail the phenotype of the two substrains, the Cohen Diabetic sensitive (CDs) and the Cohen Diabetic resistant (CDr) rats (33). Diabetes develops in this model only in the genetically susceptible CDs strain when the animal is exposed to a custom-prepared diabetogenic diet (DD) (33). Diabetes is therefore diet induced, but it is unclear which component/s of the diet the animals are susceptible to. Moreover, it is not known whether, once diabetes develops in CDs exposed to DD, the animal remains permanently diabetic or diabetes is reversible if diet is reverted back to regular chow. Finally, the pathophysiological mechanisms underlying the development of diabetes in the CD rat after exposure to DD are not known, even though recent studies provide evidence that, at least in the early stages of diabetes, insulin can be detected in ß-cells, but it is not normally secreted in response to glucose (38).

In the current study, we set out to identify the dietary component/s to which the animals are genetically susceptible, hypothesizing that CDs but not CDr is susceptible to one or more of the components in the diabetogenic diet. We also explored whether diabetes is reversible, reasoning that reversibility implies a functional defect in insulin secretion from the pancreas. In parallel, we studied the histology of the pancreas during the development of diabetes in CDs, aiming to determine whether structural alterations occur in the pancreas in parallel to the development of diabetes. Finally, we initiated an investigation aimed at detecting the genes that are involved in the dietary susceptibility that leads to the development of diabetes in this model.


   METHODS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
Animals
CDs and CDr rats (Israeli Rat Genome Center, Ashkelon, Israel) were housed in compliance with institutional regulations and in accordance with "Principles of Laboratory Animal Care" (NIH publication no. 85-23, revised 1985) and the guidelines of the American Society of Physiology for the care of laboratory animals. Animal protocols were reviewed and approved by the Ben-Gurion University Barzilai Medical Center Institutional Animal Care and Use Committee. Climate-controlled conditions and regular timed diurnal cycles were kept.

Dietary Protocols
Regular diet (RD), the standard rat chow (Koffolk, Tel-Aviv, Israel), is composed of ground whole wheat, ground alfalfa, bran, skimmed milk powder, and salts and contains 24% protein, 15% fat, and 61% carbohydrates. Tap water was provided with RD ad libitum. The custom-prepared diabetogenic diet (DD) is composed of a mixture of 18% copper-poor casein (ICNMP Biomedicals), 72% sucrose, 4.5% butter, 0.5% corn oil, 5% salt No. II USP, distilled water, and fat-soluble vitamins (33). Distilled water was provided with DD ad libitum (3).

RD does not induce diabetes in CDs nor in CDr. DD invariably induces an abnormal glucose tolerance curve with markedly elevated blood glucose levels and diminished insulin secretion in CDs but not in CDr (33), features that are consistent with diabetes in the rat. To identify which component/s within the DD render/s CDs but not CDr susceptible to the diet and prone to develop diabetes, we altered components in the DD and studied how these variations affected oral glucose tolerance test (OGTT) glucose levels during the development of diabetes. The detailed composition of the altered diets is provided in Table 1.


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  		Table 1. Components of the diets provided in the study's metabolic component

 
OGTT Protocol
We performed the OGTT after the rats had fasted overnight. We measured whole blood glucose levels (BGL) from the tip of the tail, using a standard automated glucometer (Elite, Bayer). After determining baseline glucose levels, we loaded the animals by gavage with glucose dissolved in distilled water (3.5 g glucose/kg body wt) and measured blood glucose level at 15, 30, 60, 120, and 180 min postgavage.

Histopathology of the Pancreas During the Development of Diabetes
To determine if the development of diabetes in CDs is accompanied by changes in the structure of the pancreas, animals that had been weaned at age 6 wk were fed either DD or RD for 4 wk. Animals from both groups were killed at 1, 2, 4, and 12 wk after initiation of DD. The pancreas was excised and fixed in formaldehyde. Histological sections from the pancreas were stained with hematoxylin and eosin and studied by light microscopy.

As the data evolving in the course of the study suggested that the high casein and low copper components in DD were required for the development of diabetes and for the appearance of structural changes in the exocrine pancreas, we tested the hypothesis that low dietary copper alone might suffice to induce the disappearance of the exocrine pancreas by feeding the animals with soy as the source of protein for 2 mo (diet #5), a dietary composition in which casein was absent but copper concentration was low.

Reversibility of Diabetes
To determine if diabetes was reversible, we fed CDs after weaning with DD for 6 wk (short term) or 16 wk (long term). In the course of this period, we performed an OGTT (as described above) at weekly intervals. An abnormal OGTT served as index for the development of diabetes. After 6 or 16 wk on DD, at which time the animals in both groups became diabetic, we abruptly reverted the animals to RD. In the short-term study, we continued to perform an OGTT at weekly intervals; after 3 wk on RD, we returned the DD and followed the animals for 7 additional weeks with weekly OGTT. In the long-term study, we performed an OGTT after 3, 7, and 10 days, killed the animals, and retrieved the pancreas for histological examination.

Genome Scan
To detect the genes that render CDs susceptible to DD and/or CDr resistant to DD in terms of the development of diabetes, we applied the positional cloning strategy and randomly scanned the entire rat genome.

F2 cross.
Female CDr were cross-bred with male CDs, generating F1 that were mated brother to sister. Male F2 animals (n = 101) were weaned at age 6 wk and fed for 4 wk with DD, after which their phenotype and genotype were determined.

Phenotype.
The phenotype was derived during an OGTT after overnight fasting. In addition to measuring whole blood glucose levels, we also measured plasma insulin levels at 0, 30 (estimated glucose peak), and 180 min (glucose nadir) postgavage by ELISA, using an ultrasensitive rat insulin assay (Mercodia, Uppsala, Sweden). At the end of the OGTT, we killed the animals, dissected out the whole pancreas (exocrine and endocrine), and determined its weight as reflection of its mass.

Genotype.
We extracted genomic DNA from the liver by salt precipitation, followed by phenol-chloroform cleaning, as previously described (35). We determined the genotype of each animal by PCR amplification of genomic DNA using microsatellite markers, as previously described (36). We based the choice of microsatellite markers on a genome scan of parental CDs and CDr with 1,341 microsatellite markers in which we found a 34% rate of polymorphism between the strains. In the F2 cross, we initially screened chromosomes 1–20 and X with 129 polymorphic microsatellite markers that were 10–20 cM apart. When a QTL was detected, we increased the density of the markers within the region of the QTL. The microsatellite primers were custom synthesized by Genosys (Sigma) using sequences provided by the Rat Genome Database (http://www.rgd.mcw.edu), or provided as a gift by H. Jacob (Medical College of Wisconsin, Milwaukee, WI).

Data analyses.
To evaluate the quantitative effect of genotype on phenotype, we analyzed the data for cosegregation of the F2 phenotypes with the sensitivity (S) and resistance (R) alleles of CDs and CDr, respectively, using one-way ANOVA and the post hoc LSD test when applicable.

In parallel, we analyzed the data for genetic linkage using the MultiQTL software package, version 2.5 (www.multiqtl.com), as previously described in detail (37). In brief, for initial analysis, we used by default an unrestricted model. When the results suggested the presence of a QTL, we attempted to fit the simplest and statistically justified model (dominant, recessive, or additive effect) by comparing it with the nonrestricted model and replacing it if the difference was nonsignificant. When applicable, we utilized the single-trait, multitrait, and multienvironment analyses algorithms that are provided by the software. We determined the logarithm of the odds ratio (LOD) score of each QTL and calculated its statistical significance by performing at least 10,000 permutation tests. The software provides the threshold LOD scores for different levels of statistical significance. We followed up with bootstrap analysis that provided us with the chromosomal location of the maximal LOD score, the 95% confidence interval of the QTL, and the power of this analysis.

Identification of candidate genes.
We screened the chromosomal segments within the detected QTLs for the presence of genes of possible relevance to diabetes (candidate genes), using the web-based genome browser of the UCSC Genome Bioinformatics (http://genome.ucsc.edu/cgi-bin/hgGateway). We screened for the presence of genes within the segments defined by the 95% confidence intervals in the rat and in the syntenic regions in the mouse and in humans.

Expression of candidate genes.
As only one of the candidate genes detected within the QTL on chromosome 4 could be directly related to our other most significant finding in the first part of the study, namely the casein dependence of diabetes in our model, we pursued our focus in the current study on that gene alone. We studied its level of expression in the pancreas of parental strains, comparing CDs to CDr fed DD and RD (2 x 2 study design) at the mRNA level by semiquantitative reverse transcriptase (RT)-PCR and at the protein level by Western blotting.

For RNA extraction, we homogenized the entire pancreas in 6 ml of Tri Reagent (Molecular Research Center, Cincinnati, OH) and used 1 µg of total RNA to create the first strand with Reverse-IT kit (ABgene), applying the random decamer option. We amplified the first strand, using the appropriate primer and conditions, and ran the PCR product on agarose gel. We analyzed the UV image by densitometry and normalized the results using Gapdh as the housekeeping gene. As a protein similar to Gapdh is encoded by a gene that also resides within the 95% confidence interval of our QTL on chromosome 4, we compared the expression of Gapdh with those of 28S and 18S bands. The results were similar, thus allowing us to normalize our data with Gapdh.

For protein extraction, we homogenized the whole pancreas in lysis buffer containing a protease inhibitor cocktail (Sigma). We separated the proteins by electrophoresis on 8% SDS-PAGE and transferred them to polyvinylidene difluoride membrane by wet transfer. We carried out immunoblotting using a chicken polyclonal antibody to the Ica69-related protein (Abcam19102). To detect the bound primary antibody, we used a goat anti-chicken horseradish peroxidase-conjugated second antibody (Jackson Laboratories). We analyzed the resulting bands by densitometry, using tubulin as the reference protein for normalization.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
DISCUSSION
 GRANTS
 REFERENCES
 
Effects of Dietary Variations on the Glycemic Response During OGTT
Fat effect.
The diabetogenic diet induced in CDs a glycemic response during the OGTT that was consistent with diabetes (Fig. 1, top). The increase in dietary fat in DD from 11% to 32% (diet #1), along with a decrease in carbohydrates and thus an increase in fat-to-carbohydrate ratio, did not significantly alter the glycemic response.


Figure 1
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  		Fig. 1. Top: effect of varying the fat content and the fat-to-carbohydrate ratio in diabetogenic diet (DD) on blood glucose levels (BGL) (A) and the area under the curve (AUC) (B) during an oral glucose tolerance test (OGTT). Cohen Diabetic sensitive rats (CDs) were provided DD [open squares ({square}) or bar, n = 22] or DD in which the fat content was increased to 32% and the carbohydrate content reduced to 50% (diet #1, squares or bar, n = 8). Middle: effect of varying concentrations of casein in the diet on BGL (C) and the AUC (D) during an OGTT. Cohen Diabetic resistant rats (CDr) were provided diet containing 18% casein (DD, n = 16). CDs were provided diet with either no casein (diet #2, n = 7; diet #5, n = 7), 6% casein (diet #3, n = 9), 18% casein (DD, n = 22), 39% casein (diet #4, n = 13). Bottom: effect of varying concentrations of copper in the diet on BGL (E) and the AUC (F) during an OGTT. CDr were provided diet containing 0.5 mg/kg Cu (DD, n = 16). CDs animals were provided either 0.5 mg/kg Cu (DD, n = 22), 2.0 mg/kg Cu (diet #6, n = 6), 3.5 mg/kg Cu (diet #7, n = 6), 5.5 mg/kg Cu (diet #8, n = 6), or 15.5 mg/kg Cu (diet #9, n = 6). *P < 0.05 compared with CDs provided DD.

 
Casein effect.
The glycemic response during the OGTT in CDs fed chow with no casein (diet #2) was not different from that of CDr fed DD (Fig. 1, middle). In CDs fed 6% (diet #3), 18% (DD), and 39% casein (diet #4), there was a dose-related increase in the glycemic response. When we replaced casein with soy (diet #5), the glycemic response of CDs was only slightly above that in CDr fed DD and significantly lower than in CDs.

Carbohydrate effect.
(Fig. 1, middle) In CDs, increasing the carbohydrate content in DD while maintaining the low casein content (diet #3) markedly attenuated the glycemic response. Reducing the carbohydrate content (diet #4) did not prevent the diabetic glycemic response.

Copper effect.
CDr provided DD containing 0.5 mg/kg Cu had a normal nondiabetic glycemic pattern during the OGTT, while CDs exhibited an abnormal glycemic pattern that was consistent with diabetes (Fig. 1, bottom). When we increased the copper concentration in DD to 2.0 mg/kg (diet #6), the glycemic curve maintained a diabetic pattern and thus was largely unchanged. As we increased the copper concentration further to 3.5 (diet #7) and 5.5 mg/kg (diet #8), the glycemic curve decreased significantly, but leveled thereafter, with no further change when copper content was increased to 15.5 mg/kg (diet #9).

Histomorphology of the Pancreas During the Development of Diabetes
The histology of the pancreas appeared entirely normal 1 and 2 wk after initiation of DD. After 4 wk of DD, at which time CDs already had an abnormal OGTT consistent with diabetes, the islets of Langerhans continued to appear histologically intact and the only anomaly we found was in the exocrine pancreas, in which the acinar structure appeared in disarray (Fig. 2, top). After 12 wk of DD, the islets of Langerhans still had an intact appearance, but most of the exocrine pancreas had been replaced by fat cells (Fig. 2, bottom). We could not find cellular infiltrates within what was left of the parenchyma of the pancreas.


Figure 2
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  		Fig. 2. Histological sections stained with hematoxylin and eosin of the pancreas of CDs rats after 1, 2, 4 (top; A, B, and C, respectively, all magnified x200), and 12 wk (bottom; D, E, and F, magnification x100, x200, and x400, respectively).

 
Animals fed with soy instead of casein and with low amounts of copper in diet for 8 wk did not develop diabetes and their OGTT was similar to that found in CDr fed DD. The histomorphology of the pancreas remained intact, with no signs of degeneration of the exocrine pancreas. Thus, a copper-deficient diet without casein was not sufficient to cause the degenerative fatty changes nor the diabetic phenotype we observed in CDs fed DD.

Reversibility of Diabetes
In the short-term study, CDs developed in the course of the first 6 wk of DD a typical diabetic glycemic response, as shown in Fig. 3A. Within 1 wk after discontinuation of the DD and switching to RD, the glycemic response reverted back to normal. Re-exposure to DD returned the diabetic glycemic response within 4 wk.


Figure 3
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  		Fig. 3. Reversibility of diet-induced diabetes. Data shown are means ± SE. A: AUC during the OGTT (0–180 min) in CDs rats (n = 8) fed regular diet (RD) or DD during the short-term study. B: insulin-to-glucose ratio [calculated as (Ins)/(Glc) *1,000] after 4 mo of DD and 3, 7, and 10 days after reverting back to RD. *P < 0.01 CDs vs. CDr by unpaired Student's t-test (2-tailed).

 
In the long-term study, CDs fed DD for 16 wk (n = 5) developed the full diabetic OGTT pattern (data not shown), as previously observed. We killed two animals at this stage and found near complete absence of the acinar structure of the exocrine pancreas and fatty infiltration instead (not shown), findings similar to those we had found 12 wk after initiation of DD. Seven to ten days after discontinuing DD, the OGTT reverted back to a nondiabetic pattern in the remaining three animals (as in the short-term study). The insulin-glucose ratio, which was grossly abnormal prior to switching to RD, gradually returned to normal at 10 days, as shown in Fig. 3B. Despite the disappearance of diabetes, the histology of the pancreas in these animals remained unchanged, with prominent fatty degeneration throughout the exocrine pancreas.

Positional Cloning
Cosegregation analysis.
We analyzed the data from 101 F2 progeny for cosegregation of genotype with blood glucose and insulin levels during the OGTT and with the pancreatic mass. We detected significant cosegregation (P < 0.01) for one or more of these phenotypes on Chr 4, 7, and X, as shown for representative microsatellite markers in Table 2 and as detailed below.


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  		Table 2. Results of cosegregation analysis

 
On chromosome 4, we detected highly significant cosegregation for BGL at 30, 60, 120, and 180 min during the OGTT [Table 2, area under the curve (AUC) 0–180 min], for plasma insulin levels prior to (time 0) and at 30 and 180 min of the OGTT and for the mass of the pancreas. The SS genotype (S for sensitivity allele from CDs) was associated with significantly higher glucose levels, lower insulin levels, and lower pancreatic mass than the heterozygote SR or homozygous RR (R for resistance allele from CDr). The phenotypes of SR and RR were not different from each other.

On chromosome 7, we detected significant cosegregation for BGL during the OGTT at 30 and 60 min (Table 2, AUC 0–120 min). The SS genotype was associated with higher glucose levels than SR and RR. The phenotypes of SR and RR were not different form each other.

On chromosome X, we detected significant cosegregation for BGL at several time points during the OGTT. The pattern of cosegregation, however, was directly opposite to that found in Chr 4 and 7. The R genotype was paradoxically associated with significantly higher glucose levels, whereas the S allele was associated with lower glucose levels.

Linkage analysis.
We screened the rat genome for genetic linkage in 101 male F2 progenies. The results of the single-trait linkage screen, shown in Table 3, indicate significant or suggestive linkage for blood glucose levels during the OGTT on chromosomes 4, 7, and X and for insulin levels and the mass of pancreas on chromosome 4 only. Our findings are thus consistent with those of the cosegregation analysis. We pursued these findings with in-depth linkage analysis of these three chromosomes, the details of which are provided in Table 4.


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  		Table 3. Results of the total genome scan for linkage with glucose levels during the OGTT, AUC, plasma insulin level, and mass of pancreas

 

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  		Table 4. Details of linkage analysis by chromosome (4, 7, and X), mode of analysis (single or multitrait), phenotype (plasma glucose and insulin levels during an OGTT and pancreatic mass), and computational model (dominant, recessive)

 
On chromosome 4, we detected using single-trait analysis linkage for BGL at 60–180 min, for plasma insulin levels at 0–180 min of the OGTT, and for the mass of the pancreas. The LOD score tracings are shown for each of the traits separately in Fig. 4. An overlap between the QTLs of the three traits is evident. We pursued this analysis with multitrait mapping (also shown in Table 4), which by incorporating BGL 0–180 min AUC, 30 min insulin levels, and mass of the pancreas, allowed us to define the QTL that links the three traits.


Figure 4
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  		Fig. 4. Chromosome 4 logarithm of odds ratio (LOD) score tracing for BGL during the OGTT shown as the AUC 0–180 min (top), the mass of the pancreas (middle), and for plasma insulin levels at 30 min (bottom), using single-trait analysis. Shaded column represents 95% confidence interval of multitrait analysis for the 3 traits analyzed simultaneously.

 
On chromosome 7, we detected using single-trait analysis linkage for BGL at 30 and 60 min of the OGTT. The LOD score tracing for 0–120 min AUC is shown in Fig. 5, top. Multitrait analysis incorporating the two traits 30 and 60 min did not improve the definition nor shorten the span of the QTL (data not shown).


Figure 5
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  		Fig. 5. Chromosome 7 LOD score tracing for BGL during the OGTT, shown as AUC 0–120 min (top). Chromosome X LOD score tracing for BGL during the OGTT, shown as AUC 0–180 min (bottom). Inverted triangle ({blacktriangledown}) and horizontal bar express point of maximum LOD score and 95% confidence intervals, respectively.

 
On chromosome X, we detected with single-trait analysis linkage for BGL at 15, 30, 120, and 180 min of the OGTT. The LOD score tracing for the 0–180 min AUC is shown in Fig. 5, bottom. Multitrait analysis incorporating BGL at two or more time periods did not further the results either (data not shown).

We tested for interaction between the QTLs on chromosomes 4 and 7 using multiple interval mapping but were unable to detect any significant interaction. To test for interaction between chromosome X and chromosomes 4 and 7, we clustered the individual F2 genotypes by the level of the AUC as a quantitative measure of glucose levels in the course of the OGTT. The results, shown in Fig. 6, indicate that for animals to express a diabetic phenotype, they had to preferentially carry the S allele/s on chromosome 4 and/or 7 and the R allele on chromosome X. In the presence of S alleles on chromosome X, the likelihood of developing diabetes was markedly diminished. These findings suggest the presence of a regulatory gene on chromosome X that modulates the expression of diabetes-causing genes on chromosomes 4 and 7.


Figure 6
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  		Fig. 6. Custer analysis by genotypes for microsatellite markers within the QTLs on chromosomes 4, 7, and X and by the OGTT AUC phenotype. The red color stands for homozygotes for sensitivity (SS), yellow for heterozygotes (RS), and green for homozygotes for resistance (RR).

 
Identification of Candidate Genes Within the QTL
On chromosome 4, the chromosomal segment overlapping the QTLs for blood glucose, plasma insulin, and mass of the pancreas is defined by the flanking markers D4Rat115 and D4Rat14 (Fig. 4). This segment incorporates 23 known genes (http://www.ncbi.nlm.nih.gov/mapview/maps.cgi). As shown in Table 5, 15 of these genes have been identified and annotated, while 8 encode for hypothetical proteins. Among the 15 identified genes, two stand out as of immediate relevance to diabetes: Ica1, or islet cell autoantigen, an arfaptin-related protein associated with membrane trafficking at the Golgi complex and immature secretory granules in neurosecretory cells, and Ppp1r3a (Pp1g), a protein phosphatase 1, regulatory (inhibitor) subunit 3A. Defects in PPP1R3A have been causally associated with susceptibility to Type 2 diabetes.


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  		Table 5. List of genes within the rat chromosome 4 QTLs and syntenic locations in the human and mouse genomes

 
We screened the QTL on chromosome 7 for candidate genes defined by the point of maximum LOD score (±SD) and demarcated by the flanking markers D7Rat72 and D7Rat149 (span ~21 cM). This chromosomal segment incorporates 233 genes (156 known and 77 hypothetical proteins). We also screened the QTL on chromosome X for candidate genes defined by the point of maximum LOD score (±SD) and demarcated by the flanking markers DXRat8 and DXMit5 (span ~20 cM). This segment incorporates 98 genes (74 known and 24 hypothetical proteins). Although some of these genes, in particular within the chromosome 7 QTL, could be related directly or indirectly to diabetes, their sheer large number and the lack of an objective selection criterion did not allow us to identify or pick out any gene of high priority amongst them.

Expression of Candidate Genes
The expression of Ica1 was lower in CDs than in CDr provided DD, both at the mRNA and protein levels (Fig. 7). The expression of Ica1 was similar in CDs and CDr fed RD and not different from CDr provided DD (data not shown). These results suggest that DD was associated with decreased expression of Ica1 only in CDs that developed diabetes.


Figure 7
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  		Fig. 7. Top: expression of Ica1 at the mRNA and protein level relative to Gapdh and tubulin, respectively, in CDs and CDr rats provided DD. Bottom: results are shown as bar graphs representing means ± SE of optical density (OD), *P < 0.01 CDs vs. CDr.

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
GRANTS
 REFERENCES
 
In the current study, we initiated a dissection of the metabolic susceptibility of diabetes and its genetic basis in the Cohen Diabetic rat, as means to investigate the underlying molecular mechanisms. Diabetes does not develop spontaneously in this model, but rather as an expression of a genetic susceptibility to a specific diabetogenic diet. We first sought to determine which component/s in this diet the CDs strain is susceptible to. Our major finding was that the development of diabetes in CDs was dependent primarily upon the presence of casein and the presence of only low concentrations of copper in the diet. We also found that the induction of diabetes was rapidly reversible when diet was restored from diabetogenic to regular chow. We identified that along with the development of diabetes in CDs, a fatty degeneration of the exocrine pancreas occurs, while the islets of Langerhans maintain a normal histological appearance. While investigating the genes that underlie the genetic susceptibility and the development of diabetes, we detected one highly significant QTL on rat chromosome 4, a second locus on chromosome 7, and a third on chromosome X.

While searching for the dietary component/s that causes diabetes to develop in the susceptible CDs but not in the resistant CDr strain, we identified three important differences in the composition of DD and RD. First, the protein component in the DD is composed entirely of ß-casein, as opposed to mostly noncasein protein sources in RD. Second, the carbohydrate content in the DD is composed entirely of sucrose and is 10% higher than in RD diet in which carbohydrates are composed of starch, fibers, and other sugars. Third, the copper content in the DD is very low (0.5 mg/kg), as opposed to the RD, in which it is 30-fold higher (15.6 mg/kg).

The major novel finding stemming from our experimental data was that the development of diabetes in CDs is casein dependent in a dose-dependent manner. When we varied the diet and reduced the casein content, the OGTT curve became less prominent and approached, in a dose-dependent manner, that found in nondiabetic animals provided RD. Conversely, when we increased the casein content, the OGTT curve became more prominent. The relationship between casein, a major protein component in cow's milk, and diabetes, in particular Type 1, has been previously recognized and dealt with extensively, both in humans and in experimental models (20, 23–25, 29). The exact nature of this relationship remains, however, unresolved. It is still unclear how casein induces diabetes. Casein has been reported to induce an immune response that leads to insulinitis, ß-cell destruction, and the development of diabetes. An immune mechanism is currently the prevailing concept. Whether such mechanism also applies to our model, even though we did not detect overt signs of insulinitis nor of ß-cell destruction, remains to be determined in future studies.

With respect to copper, our findings essentially confirmed what has been previously observed, namely that there is an inverse relationship between dietary copper content and the tendency to develop diabetes. Such observations have been previously reported in the Cohen rat but also in other models of diabetes. Cohen et al. (3) utilized this feature in developing the Cohen Diabetic rat model. Reiser et al. (22) demonstrated over two decades ago that copper deficiency in Sprague-Dawley rats was associated with higher glucose levels during an oral glucose load compared with copper-supplemented rats, suggesting that copper deficiency may induce glucose intolerance. Sitasawad et al. (26) demonstrated in a mouse model of Type 1 diabetes that copper supplementation exerted beneficial effects in diabetes by helping preserve ß-cell function. In the current study, we added a dose-dependency feature and defined the threshold for dietary copper content for diabetes to develop at <3.5 mg/kg. We also tested whether copper deficiency per se is sufficient to induce diabetes or are additional factors involved. When we replaced casein in DD with soy, which is also low in copper content, diabetes failed to develop. These data led us to conclude that for diabetes to develop, both high casein and low copper content are obligatory. How can copper deficiency contribute to the induction of diabetes? Since copper is a known cofactor for superoxide dismutase, copper deficiency might remove protection from free radicals, exposing the endocrine pancreas to damage (30, 31). Copper is also required for normal activity of enzymes involved in aerobic metabolism (14, 21), and its absence might therefore be associated with ß-cell dysfunction. These possibilities need to be explored further.

Having determined the major dietary components to which CDs are susceptible in terms of the development of diabetes, we set out to determine whether in the same strain structural changes in the pancreas accompanied the development of diabetes. The striking finding was the almost total disappearance of the exocrine pancreas after 3 and 4 mo of DD, and the intact appearance of the islets of Langerhans on light microscopy. Interestingly enough, Al-Abdulla et al. (1) reported that copper deficiency per se is associated with in vivo depletion of pancreatic acinar tissue in Wistar Furth rats. We could not confirm this observation, as animals fed DD in which soy replaced casein while the low copper content was maintained did not develop the degenerative changes otherwise observed in the exocrine pancreas of CDs. It appears, therefore, that both casein and low copper are required for the depletion of acini and the fat replacement of normal exocrine pancreatic tissue to occur. Do these structural changes in the exocrine pancreas bear any causal relationship to the development of diabetes and to the alleged impaired insulin release from the islets of Langerhans? It is not likely, as CDr that are fed DD also exhibit similar changes fatty changes in the exocrine pancreas, even though to a lesser extent, but do not develop diabetes. Furthermore, when we replaced DD with RD in animals that had been fed DD for 4 mo, the diabetic phenotype reverted back to a normal nondiabetic phenotype, but the fatty infiltration of the exocrine pancreas persisted. Thus, the changes in the exocrine pancreas as a causative factor in the development of diabetes remain questionable. Another possible view of our findings is that a similar mechanism that is induced by DD causes both injury to the islets of Langerhans and a structural injury to the exocrine pancreas, causing diabetes through the former and disappearance of the acinar structures through the latter. At this stage of our understanding, the interrelationship between the fatty infiltration of the exocrine pancreas and the development of diabetes remains unresolved and deserves further exploration.

We pursued the observation that the development of diabetes in animals that are exposed to DD is 100% predictable in CDs rats, that it occurs within a period of ~4 wk (33), and that once it develops, diabetes persists for 6 mo and beyond, as long as the animals continue to be fed DD. An open-ended issue had been whether diabetes is reversible, once it has developed. The rapid reversibility of diabetes in CDs fed DD for 7 or 16 wk, as shown in our study, was surprising but reproducible and suggests that exposure of the susceptible animal to DD induces a functional reversible mechanism that leads to the development of diabetes, a functional impairment in the insulin response to glucose.

We questioned why CDs are sensitive to DD and develop diabetes and, perhaps even more importantly, why CDr are resistant to DD and do not develop diabetes. Reasoning that the answer lies in a genetic susceptibility that renders one strain sensitive and the other resistant to DD, we initiated the genetic dissection of this environmental-dietary susceptibility. We utilized the positional cloning approach, using an F2 cross between CDs and CDr. Cosegregation and linkage analyses led us to detect QTLs on chromosomes 4, 7, and X. Previous investigations of the genetic basis of diabetes in the rat have identified at least 85 QTL on all autosomes and on chromosome X (http://www.rgd.mcw.edu/). The QTL that we currently detected on chromosome 4 does not coincide with any of the other 4 QTLs that have been previously reported on that chromosome (http://www.rgd.mcw.edu/) (5, 7, 15, 17) and can be thus viewed as a novel diabetes-related QTL in the rat. This QTL stands out for several reasons: It is highly significant, it has an unusually small span for an F2 cross, and it was simultaneously associated with several diabetic phenotypes, including BGL during the OGTT at multiple time points, insulin levels, and mass of the pancreas. The other QTLs that we detected on chromosomes 7 and X, which overlap with previously reported Niddm31 and Niddm48 (28, 32) and Iddm5 and Niddm16 (11, 32), respectively, were associated with only OGTT BGL and although significant, were considerably less prominent.

Focusing primarily on the QTL on chromosome 4, without ruling out the significance of the other QTLs, we screened web-based genomic databases for known genes within the demarcated chromosomal segment of that QTL. Surprisingly, we found within the 95% confidence limits of the QTL only 23 genes. Among these genes, Ica1 and Ppp1r3a have been previously related to diabetes. Ica1 only bears direct relevance to our other most significant finding in the first part of the study, namely the casein dependence of diabetes in our model. We therefore pursued our focus on that gene, without ruling out in any way the potential role of Ppp1r3a or any of the other genes within the QTL interval. We found that the expression of Ica1 was diminished both at the mRNA and protein level in CDs fed DD compared with CDs fed RD or CDr fed either diet. It is yet unclear, however, whether the decreased expression of Ica1 plays a functional role in the development (cause) or is merely an effect of diabetes. Interestingly, even though Ica1 (also known as Ica69) has been associated with diabetes in the human, mouse, and rat (4, 8–10, 12, 16, 18, 19, 34), the Ica1 gene locus has not been previously identified as a risk locus for diabetes in either humans or in experimental models of diabetes, and this is the first time that this gene has been associated with a diabetes-related QTL.

What is known about the function of Ica1 in the mammalian organism and how can it be linked to the development of diabetes in our model? Ica1 is a member of the arfaptin family. Its product, an arfaptin-related protein, has been ultrastructurally localized by immune electron microscopy to the endoplasmic reticulum, the Golgi complex, and to vesicles (10, 27). It is currently thought that Ica1 may fulfill an active role in cellular protein processing and trafficking, in particular in vesicular transport regulated by small GTP-binding proteins at the Golgi complex and in immature secretory granules such as in ß-cells. Although its full importance to normal mammalian islet physiology is yet unclear (4), available data suggest that Ica1 may participate in insulin processing in the Golgi apparatus and secretion from ß-cells in the pancreas (10, 27). Impairment in function of Ica1 might therefore lead to abnormal insulin release in response to glucose and the development of diabetes. How is Ica1 related to casein? Casein, mostly ß-casein, composes 80% of cow's milk protein. Several sequence homologies have been reported between bovine ß-casein and peptides expressed in the pancreas, including Icap69 (2). The protein encoded by the Ica1 gene is a peptide that encodes the conserved T-cell epitope in exon 2 (http://www.NCBI.nlm.nih.gov/entrez/). "Molecular mimicry," the structural similarity between casein and proteins within the ß-cells, may underlie cross-reactivity between bovine ß-casein and the Ica-related protein (6, 13), which may in turn cause functional impairment in insulin release.

The data generated in the current study lead us to propose the following hypothesis for the pathophysiology of diabetes in the Cohen Diabetic rat: CDs animals that are genetically susceptible to DD, but not CDr, develop a functional impairment in the ability of ß-cells to release insulin in response to glucose loading. This impairment is associated with diminished expression in the pancreas of Ica1, possibly at the level of the Golgi apparatus. Casein, in the presence of copper deficiency, is likely to be one of the key inciting factors that induce Ica1 dysfunction, impaired insulin release from ß-cells and the development of diabetes. This study thus leaves us with a hypothesis that remains to be proven and several issues that are beyond the scope of this study and therefore remain unresolved. What is the molecular basis for the susceptibility of CDs but not of CDr to DD in terms of the development of diabetes? How does the DD diet affect the expression of Ica1, and is indeed Ica1 casually related to the development of diabetes? The mode by which copper affects the development of diabetes also remains unresolved. There is also need to explore the possible role of the other genes within the QTL on chromosome 4, as well as the large number of genes within the QTLs on chromosomes 7 and X. Finally, a gender effect has not been taken into account in this study, as only male animals were used. Even though a number of questions thus remain open, a significant step has nonetheless been achieved in our quest to comprehend the pathophysiology of diabetes in the Cohen model, with its potential implications to diabetes in humans.


   GRANTS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 GRANTS
REFERENCES
 
This study was supported by research grants from the Russell Berrie Foundation and D-Cure, Diabetes Care in Israel, and from the National Institute for Biotechnology in the Negev to C. Yagil and Y. Yagil.


   ACKNOWLEDGMENTS
 
The authors acknowledge the outstanding technical support provided by Marina Grinyuk, Svetlana Rosenblum, Shiri Klein, Shelley Hacohen, Gurion Katni, Ira Agranovitz, and Anna Babayov, as well as Prof. Avraham Korol for bioinformatics advice and support.


   FOOTNOTES
 
Address for reprint requests and other correspondence: C. Yagil, Lab. for Molecular Medicine, Faculty of Health Sciences, Ben-Gurion Univ., Barzilai Medical Center Campus, Ashkelon 78306, Israel (e-mail: chyagil{at}bgu.ac.il).

Article published online before print. See web site for date of publication (http://physiolgenomics.physiology.org).


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 

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