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<title>Diabetes</title>
<url>http://diabetes.diabetesjournals.org/icons/banner/title.gif</url>
<link>http://diabetes.diabetesjournals.org</link>
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<title><![CDATA[Definition of High-Risk Type 1 Diabetes HLA-DR and HLA-DQ Types Using Only Three Single Nucleotide Polymorphisms]]></title>
<link>http://diabetes.diabetesjournals.org/cgi/content/short/62/6/2135?rss=1</link>
<description><![CDATA[
<p>Evaluating risk of developing type 1 diabetes (T1D) depends on determining an individual&rsquo;s HLA type, especially of the HLA DRB1 and DQB1 alleles. Individuals positive for HLA-DRB1*03 (DR3) or HLA-DRB1*04 (DR4) with DQB1*03:02 (DQ8) have the highest risk of developing T1D. Currently, HLA typing methods are relatively expensive and time consuming. We sought to determine the minimum number of single nucleotide polymorphisms (SNPs) that could rapidly define the HLA-DR types relevant to T1D, namely, DR3/4, DR3/3, DR4/4, DR3/X, DR4/X, and DRX/X (where X is neither DR3 nor DR4), and could distinguish the highest-risk DR4 type (DR4-DQ8) as well as the non-T1D&ndash;associated DR4-DQB1*03:01 type. We analyzed 19,035 SNPs of 10,579 subjects (7,405 from a discovery set and 3,174 from a validation set) from the Type 1 Diabetes Genetics Consortium and developed a novel machine learning method to select as few as three SNPs that could define the HLA-DR and HLA-DQ types accurately. The overall accuracy was 99.3%, area under curve was 0.997, true-positive rates were &gt;0.99, and false-positive rates were &lt;0.001. We confirmed the reliability of these SNPs by 10-fold cross-validation. Our approach predicts HLA-DR/DQ types relevant to T1D more accurately than existing methods and is rapid and cost-effective.</p>
]]></description>
<dc:creator><![CDATA[Nguyen, C.; Varney, M. D.; Harrison, L. C.; Morahan, G.]]></dc:creator>
<dc:date>2013-05-23T12:01:56-07:00</dc:date>
<dc:identifier>info:doi/10.2337/db12-1398</dc:identifier>
<dc:identifier>hwp:master-id:diabetes;db12-1398</dc:identifier>
<dc:publisher>American Diabetes Association</dc:publisher>
<dc:title><![CDATA[Definition of High-Risk Type 1 Diabetes HLA-DR and HLA-DQ Types Using Only Three Single Nucleotide Polymorphisms]]></dc:title>
<prism:publicationDate>2013-06-01</prism:publicationDate>
<prism:section>Genetics/Genomes/Proteomics/Metabolomics</prism:section>
<prism:volume>62</prism:volume>
<prism:number>6</prism:number>
<prism:startingPage>2135</prism:startingPage>
<prism:endingPage>2140</prism:endingPage>
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<item rdf:about="http://diabetes.diabetesjournals.org/cgi/content/short/62/6/2141?rss=1">
<title><![CDATA[Genetic Variants Associated With Glycine Metabolism and Their Role in Insulin Sensitivity and Type 2 Diabetes]]></title>
<link>http://diabetes.diabetesjournals.org/cgi/content/short/62/6/2141?rss=1</link>
<description><![CDATA[
<p>Circulating metabolites associated with insulin sensitivity may represent useful biomarkers, but their causal role in insulin sensitivity and diabetes is less certain. We previously identified novel metabolites correlated with insulin sensitivity measured by the hyperinsulinemic-euglycemic clamp. The top-ranking metabolites were in the glutathione and glycine biosynthesis pathways. We aimed to identify common genetic variants associated with metabolites in these pathways and test their role in insulin sensitivity and type 2 diabetes. With 1,004 nondiabetic individuals from the RISC study, we performed a genome-wide association study (GWAS) of 14 insulin sensitivity&ndash;related metabolites and one metabolite ratio. We replicated our results in the Botnia study (<I>n</I> = 342). We assessed the association of these variants with diabetes-related traits in GWAS meta-analyses (GENESIS [including RISC, EUGENE2, and Stanford], MAGIC, and DIAGRAM). We identified four associations with three metabolites&mdash;glycine (rs715 at <I>CPS1</I>), serine (rs478093 at <I>PHGDH</I>), and betaine (rs499368 at <I>SLC6A12</I>; rs17823642 at <I>BHMT</I>)&mdash;and one association signal with glycine-to-serine ratio (rs1107366 at <I>ALDH1L1</I>). There was no robust evidence for association between these variants and insulin resistance or diabetes. Genetic variants associated with genes in the glycine biosynthesis pathways do not provide consistent evidence for a role of glycine in diabetes-related traits.</p>
]]></description>
<dc:creator><![CDATA[Xie, W.; Wood, A. R.; Lyssenko, V.; Weedon, M. N.; Knowles, J. W.; Alkayyali, S.; Assimes, T. L.; Quertermous, T.; Abbasi, F.; Paananen, J.; Haring, H.; Hansen, T.; Pedersen, O.; Smith, U.; Laakso, M.; the MAGIC Investigators; the DIAGRAM Consortium; the GENESIS Consortium; the RISC Consortium; Dekker, J. M.; Nolan, J. J.; Groop, L.; Ferrannini, E.; Adam, K.-P.; Gall, W. E.; Frayling, T. M.; Walker, M.]]></dc:creator>
<dc:date>2013-05-23T12:01:56-07:00</dc:date>
<dc:identifier>info:doi/10.2337/db12-0876</dc:identifier>
<dc:identifier>hwp:master-id:diabetes;db12-0876</dc:identifier>
<dc:publisher>American Diabetes Association</dc:publisher>
<dc:title><![CDATA[Genetic Variants Associated With Glycine Metabolism and Their Role in Insulin Sensitivity and Type 2 Diabetes]]></dc:title>
<prism:publicationDate>2013-06-01</prism:publicationDate>
<prism:section>Genetics/Genomes/Proteomics/Metabolomics</prism:section>
<prism:volume>62</prism:volume>
<prism:number>6</prism:number>
<prism:startingPage>2141</prism:startingPage>
<prism:endingPage>2150</prism:endingPage>
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<item rdf:about="http://diabetes.diabetesjournals.org/cgi/content/short/62/5/1730?rss=1">
<title><![CDATA[Early Metabolic Markers of the Development of Dysglycemia and Type 2 Diabetes and Their Physiological Significance]]></title>
<link>http://diabetes.diabetesjournals.org/cgi/content/short/62/5/1730?rss=1</link>
<description><![CDATA[
<p>Metabolomic screening of fasting plasma from nondiabetic subjects identified &alpha;-hydroxybutyrate (&alpha;-HB) and linoleoyl-glycerophosphocholine (L-GPC) as joint markers of insulin resistance (IR) and glucose intolerance. To test the predictivity of &alpha;-HB and L-GPC for incident dysglycemia, &alpha;-HB and L-GPC measurements were obtained in two observational cohorts, comprising 1,261 nondiabetic participants from the Relationship between Insulin Sensitivity and Cardiovascular Disease (RISC) study and 2,580 from the Botnia Prospective Study, with 3-year and 9.5-year follow-up data, respectively. In both cohorts, &alpha;-HB was a positive correlate and L-GPC a negative correlate of insulin sensitivity, with &alpha;-HB reciprocally related to indices of &beta;-cell function derived from the oral glucose tolerance test (OGTT). In follow-up, &alpha;-HB was a positive predictor (adjusted odds ratios 1.25 [95% CI 1.00&ndash;1.60] and 1.26 [1.07&ndash;1.48], respectively, for each standard deviation of predictor), and L-GPC was a negative predictor (0.64 [0.48&ndash;0.85] and 0.67 [0.54&ndash;0.84]) of dysglycemia (RISC) or type 2 diabetes (Botnia), independent of familial diabetes, sex, age, BMI, and fasting glucose. Corresponding areas under the receiver operating characteristic curve were 0.791 (RISC) and 0.783 (Botnia), similar in accuracy when substituting &alpha;-HB and L-GPC with 2-h OGTT glucose concentrations. When their activity was examined, &alpha;-HB inhibited and L-GPC stimulated glucose-induced insulin release in INS-1e cells. &alpha;-HB and L-GPC are independent predictors of worsening glucose tolerance, physiologically consistent with a joint signature of IR and &beta;-cell dysfunction.</p>
]]></description>
<dc:creator><![CDATA[Ferrannini, E.; Natali, A.; Camastra, S.; Nannipieri, M.; Mari, A.; Adam, K.-P.; Milburn, M. V.; Kastenmuller, G.; Adamski, J.; Tuomi, T.; Lyssenko, V.; Groop, L.; Gall, W. E.]]></dc:creator>
<dc:date>2013-04-23T12:01:39-07:00</dc:date>
<dc:identifier>info:doi/10.2337/db12-0707</dc:identifier>
<dc:identifier>hwp:master-id:diabetes;db12-0707</dc:identifier>
<dc:publisher>American Diabetes Association</dc:publisher>
<dc:title><![CDATA[Early Metabolic Markers of the Development of Dysglycemia and Type 2 Diabetes and Their Physiological Significance]]></dc:title>
<prism:publicationDate>2013-05-01</prism:publicationDate>
<prism:section>Genetics/Genomes/Proteomics/Metabolomics</prism:section>
<prism:volume>62</prism:volume>
<prism:number>5</prism:number>
<prism:startingPage>1730</prism:startingPage>
<prism:endingPage>1737</prism:endingPage>
</item>
<item rdf:about="http://diabetes.diabetesjournals.org/cgi/content/short/62/5/1738?rss=1">
<title><![CDATA[Genetic and Molecular Insights Into the Role of PROX1 in Glucose Metabolism]]></title>
<link>http://diabetes.diabetesjournals.org/cgi/content/short/62/5/1738?rss=1</link>
<description><![CDATA[
<p>Genome-wide association studies have shown that the rs340874 single nucleotide polymorphism (SNP) in <I>PROX1</I> is a genetic susceptibility factor for type 2 diabetes. We conducted genetic and molecular studies to better understand the role of <I>PROX1</I> in type 2 diabetes. We assessed the impact of the whole common genetic variability of <I>PROX1</I> (80 SNPs) on type 2 diabetes&ndash;related biochemical traits in the HELENA (Healthy Lifestyle in Europe by Nutrition in Adolescence) study (<I>n</I> = 1,155). Three SNPs (rs340838, rs340837, and rs340836) were significantly associated with fasting plasma insulin levels (<I>P</I> &le; 0.00295). We evaluated the impact of nine <I>PROX1</I> SNPs (the three insulin-associated SNPs plus six SNPs in strong linkage disequilibrium) on luciferase reporter gene expression. The insulin-lowering alleles of rs340874, rs340873, and rs340835 were associated with lower luciferase activity in MIN6 and HepG2 cells (except for rs340874, which was in HepG2 cells only). Electrophoretic mobility shift assays indicated that specific nuclear protein bindings occur at the three SNPs in HepG2 cells, with allele-binding differences for rs340874. We also showed that the knockdown of Prox1 expression by small interfering RNAs in INS-1E cells resulted in a 1.7-fold reduction in glucose-stimulated insulin secretion. All together, we propose that reduced expression of <I>PROX1</I> by <I>cis</I>-regulatory variants results in altered &beta;-cell insulin secretion and thereby confers susceptibility to type 2 diabetes.</p>
]]></description>
<dc:creator><![CDATA[Lecompte, S.; Pasquetti, G.; Hermant, X.; Grenier-Boley, B.; Gonzalez-Gross, M.; De Henauw, S.; Molnar, D.; Stehle, P.; Beghin, L.; Moreno, L. A.; Amouyel, P.; Dallongeville, J.; Meirhaeghe, A.]]></dc:creator>
<dc:date>2013-04-23T12:01:39-07:00</dc:date>
<dc:identifier>info:doi/10.2337/db12-0864</dc:identifier>
<dc:identifier>hwp:master-id:diabetes;db12-0864</dc:identifier>
<dc:publisher>American Diabetes Association</dc:publisher>
<dc:title><![CDATA[Genetic and Molecular Insights Into the Role of PROX1 in Glucose Metabolism]]></dc:title>
<prism:publicationDate>2013-05-01</prism:publicationDate>
<prism:section>Genetics/Genomes/Proteomics/Metabolomics</prism:section>
<prism:volume>62</prism:volume>
<prism:number>5</prism:number>
<prism:startingPage>1738</prism:startingPage>
<prism:endingPage>1745</prism:endingPage>
</item>
<item rdf:about="http://diabetes.diabetesjournals.org/cgi/content/short/62/5/1746?rss=1">
<title><![CDATA[Genome-Wide Association Study Identifies a Novel Locus Contributing to Type 2 Diabetes Susceptibility in Sikhs of Punjabi Origin From India]]></title>
<link>http://diabetes.diabetesjournals.org/cgi/content/short/62/5/1746?rss=1</link>
<description><![CDATA[
<p>We performed a genome-wide association study (GWAS) and a multistage meta-analysis of type 2 diabetes (T2D) in Punjabi Sikhs from India. Our discovery GWAS in 1,616 individuals (842 case subjects) was followed by in silico replication of the top 513 independent single nucleotide polymorphisms (SNPs) (<I>P</I> &lt; 10<sup>&ndash;3</sup>) in Punjabi Sikhs (<I>n</I> = 2,819; 801 case subjects). We further replicated 66 SNPs (<I>P</I> &lt; 10<sup>&ndash;4</sup>) through genotyping in a Punjabi Sikh sample (<I>n</I> = 2,894; 1,711 case subjects). On combined meta-analysis in Sikh populations (<I>n</I> = 7,329; 3,354 case subjects), we identified a novel locus in association with T2D at 13q12 represented by a directly genotyped intronic SNP (rs9552911, <I>P</I> = 1.82 <FONT FACE="arial,helvetica">x</FONT> 10<sup>&ndash;8</sup>) in the <I>SGCG</I> gene. Next, we undertook in silico replication (stage 2b) of the top 513 signals (<I>P</I> &lt; 10<sup>&ndash;3</sup>) in 29,157 non-Sikh South Asians (10,971 case subjects) and de novo genotyping of up to 31 top signals (<I>P</I> &lt; 10<sup>&ndash;4</sup>) in 10,817 South Asians (5,157 case subjects) (stage 3b). In combined South Asian meta-analysis, we observed six suggestive associations (<I>P</I> &lt; 10<sup>&ndash;5</sup> to &lt; 10<sup>&ndash;7</sup>), including SNPs at <I>HMG1L1</I>/<I>CTCFL</I>, <I>PLXNA4</I>, <I>SCAP</I>, and chr5p11. Further evaluation of 31 top SNPs in 33,707 East Asians (16,746 case subjects) (stage 3c) and 47,117 Europeans (8,130 case subjects) (stage 3d), and joint meta-analysis of 128,127 individuals (44,358 case subjects) from 27 multiethnic studies, did not reveal any additional loci nor was there any evidence of replication for the new variant. Our findings provide new evidence on the presence of a population-specific signal in relation to T2D, which may provide additional insights into T2D pathogenesis.</p>
]]></description>
<dc:creator><![CDATA[Saxena, R.; Saleheen, D.; Been, L. F.; Garavito, M. L.; Braun, T.; Bjonnes, A.; Young, R.; Ho, W. K.; Rasheed, A.; Frossard, P.; Sim, X.; Hassanali, N.; Radha, V.; Chidambaram, M.; Liju, S.; Rees, S. D.; Ng, D. P.-K.; Wong, T.-Y.; Yamauchi, T.; Hara, K.; Tanaka, Y.; Hirose, H.; McCarthy, M. I.; Morris, A. P.; DIAGRAM; MuTHER; AGEN; Basit, A.; Barnett, A. H.; Katulanda, P.; Matthews, D.; Mohan, V.; Wander, G. S.; Singh, J. R.; Mehra, N. K.; Ralhan, S.; Kamboh, M. I.; Mulvihill, J. J.; Maegawa, H.; Tobe, K.; Maeda, S.; Cho, Y. S.; Tai, E. S.; Kelly, M. A.; Chambers, J. C.; Kooner, J. S.; Kadowaki, T.; Deloukas, P.; Rader, D. J.; Danesh, J.; Sanghera, D. K.]]></dc:creator>
<dc:date>2013-04-23T12:01:39-07:00</dc:date>
<dc:identifier>info:doi/10.2337/db12-1077</dc:identifier>
<dc:identifier>hwp:master-id:diabetes;db12-1077</dc:identifier>
<dc:publisher>American Diabetes Association</dc:publisher>
<dc:title><![CDATA[Genome-Wide Association Study Identifies a Novel Locus Contributing to Type 2 Diabetes Susceptibility in Sikhs of Punjabi Origin From India]]></dc:title>
<prism:publicationDate>2013-05-01</prism:publicationDate>
<prism:section>Genetics/Genomes/Proteomics/Metabolomics</prism:section>
<prism:volume>62</prism:volume>
<prism:number>5</prism:number>
<prism:startingPage>1746</prism:startingPage>
<prism:endingPage>1755</prism:endingPage>
</item>
<item rdf:about="http://diabetes.diabetesjournals.org/cgi/content/short/62/5/1756?rss=1">
<title><![CDATA[Allele-Specific Transcriptional Activity at Type 2 Diabetes-Associated Single Nucleotide Polymorphisms in Regions of Pancreatic Islet Open Chromatin at the JAZF1 Locus]]></title>
<link>http://diabetes.diabetesjournals.org/cgi/content/short/62/5/1756?rss=1</link>
<description><![CDATA[
<p>Translation of noncoding common variant association signals into meaningful molecular and biological mechanisms explaining disease susceptibility remains challenging. For the type 2 diabetes association signal in <I>JAZF1</I> intron 1, we hypothesized that the underlying risk variants have <I>cis</I>-regulatory effects in islets or other type 2 diabetes&ndash;relevant cell types. We used maps of experimentally predicted open chromatin regions to prioritize variants for functional follow-up studies of transcriptional activity. Twelve regions containing type 2 diabetes&ndash;associated variants were tested for enhancer activity in 832/13 and MIN6 insulinoma cells. Three regions exhibited enhancer activity and only rs1635852 displayed allelic differences in enhancer activity; the type 2 diabetes risk allele T showed lower transcriptional activity than the nonrisk allele C. This risk allele showed increased binding to protein complexes, suggesting that it functions as part of a transcriptional repressor complex. We applied DNA affinity capture to identify factors in the complex and determined that the risk allele preferentially binds the pancreatic master regulator PDX1. These data suggest that the rs1635852 region in <I>JAZF1</I> intron 1 is part of a <I>cis</I>-regulatory complex and that maps of open chromatin are useful to guide identification of variants with allelic differences in regulatory activity at type 2 diabetes loci.</p>
]]></description>
<dc:creator><![CDATA[Fogarty, M. P.; Panhuis, T. M.; Vadlamudi, S.; Buchkovich, M. L.; Mohlke, K. L.]]></dc:creator>
<dc:date>2013-04-23T12:01:39-07:00</dc:date>
<dc:identifier>info:doi/10.2337/db12-0972</dc:identifier>
<dc:identifier>hwp:master-id:diabetes;db12-0972</dc:identifier>
<dc:publisher>American Diabetes Association</dc:publisher>
<dc:title><![CDATA[Allele-Specific Transcriptional Activity at Type 2 Diabetes-Associated Single Nucleotide Polymorphisms in Regions of Pancreatic Islet Open Chromatin at the JAZF1 Locus]]></dc:title>
<prism:publicationDate>2013-05-01</prism:publicationDate>
<prism:section>Genetics/Genomes/Proteomics/Metabolomics</prism:section>
<prism:volume>62</prism:volume>
<prism:number>5</prism:number>
<prism:startingPage>1756</prism:startingPage>
<prism:endingPage>1762</prism:endingPage>
</item>
<item rdf:about="http://diabetes.diabetesjournals.org/cgi/content/short/62/5/1763?rss=1">
<title><![CDATA[The Influence of Obesity-Related Single Nucleotide Polymorphisms on BMI Across the Life Course: The PAGE Study]]></title>
<link>http://diabetes.diabetesjournals.org/cgi/content/short/62/5/1763?rss=1</link>
<description><![CDATA[
<p>Evidence is limited as to whether heritable risk of obesity varies throughout adulthood. Among &gt;34,000 European Americans, aged 18&ndash;100 years, from multiple U.S. studies in the Population Architecture using Genomics and Epidemiology (PAGE) Consortium, we examined evidence for heterogeneity in the associations of five established obesity risk variants (near <I>FTO</I>, <I>GNPDA2</I>, <I>MTCH2</I>, <I>TMEM18</I>, and<I> NEGR1</I>) with BMI across four distinct epochs of adulthood: <I>1</I>) young adulthood (ages 18&ndash;25 years), adulthood (ages 26&ndash;49 years), middle-age adulthood (ages 50&ndash;69 years), and older adulthood (ages &ge;70 years); or <I>2</I>) by menopausal status in women and stratification by age 50 years in men. Summary-effect estimates from each meta-analysis were compared for heterogeneity across the life epochs. We found heterogeneity in the association of the <I>FTO</I> (rs8050136) variant with BMI across the four adulthood epochs (<I>P</I> = 0.0006), with larger effects in young adults relative to older adults (&beta; [SE] = 1.17 [0.45] vs. 0.09 [0.09] kg/m<sup>2</sup>, respectively, per A allele) and smaller intermediate effects. We found no evidence for heterogeneity in the association of <I>GNPDA2</I>, <I>MTCH2</I>, <I>TMEM18</I>, and<I> NEGR1</I> with BMI across adulthood. Genetic predisposition to obesity may have greater effects on body weight in young compared with older adulthood for <I>FTO</I>, suggesting changes by age, generation, or secular trends. Future research should compare and contrast our findings with results using longitudinal data.</p>
]]></description>
<dc:creator><![CDATA[Graff, M.; Gordon-Larsen, P.; Lim, U.; Fowke, J. H.; Love, S.-A.; Fesinmeyer, M.; Wilkens, L. R.; Vertilus, S.; Ritchie, M. D.; Prentice, R. L.; Pankow, J.; Monroe, K.; Manson, J. E.; Le Marchand, L.; Kuller, L. H.; Kolonel, L. N.; Hong, C. P.; Henderson, B. E.; Haessler, J.; Gross, M. D.; Goodloe, R.; Franceschini, N.; Carlson, C. S.; Buyske, S.; Buzkova, P.; Hindorff, L. A.; Matise, T. C.; Crawford, D. C.; Haiman, C. A.; Peters, U.; North, K. E.]]></dc:creator>
<dc:date>2013-04-23T12:01:39-07:00</dc:date>
<dc:identifier>info:doi/10.2337/db12-0863</dc:identifier>
<dc:identifier>hwp:master-id:diabetes;db12-0863</dc:identifier>
<dc:publisher>American Diabetes Association</dc:publisher>
<dc:title><![CDATA[The Influence of Obesity-Related Single Nucleotide Polymorphisms on BMI Across the Life Course: The PAGE Study]]></dc:title>
<prism:publicationDate>2013-05-01</prism:publicationDate>
<prism:section>Genetics/Genomes/Proteomics/Metabolomics</prism:section>
<prism:volume>62</prism:volume>
<prism:number>5</prism:number>
<prism:startingPage>1763</prism:startingPage>
<prism:endingPage>1767</prism:endingPage>
</item>
<item rdf:about="http://diabetes.diabetesjournals.org/cgi/content/short/62/4/1320?rss=1">
<title><![CDATA[Metabolic Programming of MEST DNA Methylation by Intrauterine Exposure to Gestational Diabetes Mellitus]]></title>
<link>http://diabetes.diabetesjournals.org/cgi/content/short/62/4/1320?rss=1</link>
<description><![CDATA[
<p>Epigenetic processes are primary candidates when searching for mechanisms that can stably modulate gene expression and metabolic pathways according to early life conditions. To test the effects of gestational diabetes mellitus (GDM) on the epigenome of the next generation, cord blood and placenta tissue were obtained from 88 newborns of mothers with dietetically treated GDM, 98 with insulin-dependent GDM, and 65 without GDM. Bisulfite pyrosequencing was used to compare the methylation levels of seven imprinted genes involved in prenatal and postnatal growth, four genes involved in energy metabolism, one anti-inflammatory gene, one tumor suppressor gene, one pluripotency gene, and two repetitive DNA families. The maternally imprinted <I>MEST</I> gene, the nonimprinted glucocorticoid receptor <I>NR3C1</I> gene, and interspersed ALU repeats showed significantly decreased methylation levels (4&ndash;7 percentage points for <I>MEST</I>, 1&ndash;2 for <I>NR3C1</I>, and one for ALUs) in both GDM groups, compared with controls, in both analyzed tissues. Significantly decreased blood <I>MEST</I> methylation (3 percentage points) also was observed in adults with morbid obesity compared with normal-weight controls. Our results support the idea that intrauterine exposure to GDM has long-lasting effects on the epigenome of the offspring. Specifically, epigenetic malprogramming of <I>MEST</I> may contribute to obesity predisposition throughout life.</p>
]]></description>
<dc:creator><![CDATA[El Hajj, N.; Pliushch, G.; Schneider, E.; Dittrich, M.; Muller, T.; Korenkov, M.; Aretz, M.; Zechner, U.; Lehnen, H.; Haaf, T.]]></dc:creator>
<dc:date>2013-03-21T12:01:30-07:00</dc:date>
<dc:identifier>info:doi/10.2337/db12-0289</dc:identifier>
<dc:identifier>hwp:master-id:diabetes;db12-0289</dc:identifier>
<dc:publisher>American Diabetes Association</dc:publisher>
<dc:title><![CDATA[Metabolic Programming of MEST DNA Methylation by Intrauterine Exposure to Gestational Diabetes Mellitus]]></dc:title>
<prism:publicationDate>2013-04-01</prism:publicationDate>
<prism:section>Genetics/Genomes/Proteomics/Metabolomics</prism:section>
<prism:volume>62</prism:volume>
<prism:number>4</prism:number>
<prism:startingPage>1320</prism:startingPage>
<prism:endingPage>1328</prism:endingPage>
</item>
<item rdf:about="http://diabetes.diabetesjournals.org/cgi/content/short/62/4/1329?rss=1">
<title><![CDATA[Mutations in HNF1A Result in Marked Alterations of Plasma Glycan Profile]]></title>
<link>http://diabetes.diabetesjournals.org/cgi/content/short/62/4/1329?rss=1</link>
<description><![CDATA[
<p>A recent genome-wide association study identified hepatocyte nuclear factor 1-&alpha; (<I>HNF1A</I>) as a key regulator of fucosylation. We hypothesized that loss-of-function <I>HNF1A</I> mutations causal for maturity-onset diabetes of the young (MODY) would display altered fucosylation of <I>N</I>-linked glycans on plasma proteins and that glycan biomarkers could improve the efficiency of a diagnosis of <I>HNF1A</I>-MODY. In a pilot comparison of 33 subjects with <I>HNF1A</I>-MODY and 41 subjects with type 2 diabetes, 15 of 29 glycan measurements differed between the two groups. The DG9-glycan index, which is the ratio of fucosylated to nonfucosylated triantennary glycans, provided optimum discrimination in the pilot study and was examined further among additional subjects with <I>HNF1A</I>-MODY (<I>n</I> = 188), glucokinase (<I>GCK</I>)-MODY (<I>n</I> = 118), hepatocyte nuclear factor 4-&alpha; (<I>HNF4A</I>)-MODY (<I>n</I> = 40), type 1 diabetes (<I>n</I> = 98), type 2 diabetes (<I>n</I> = 167), and nondiabetic controls (<I>n</I> = 98). The DG9-glycan index was markedly lower in <I>HNF1A</I>-MODY than in controls or other diabetes subtypes, offered good discrimination between <I>HNF1A</I>-MODY and both type 1 and type 2 diabetes (C statistic &ge;0.90), and enabled us to detect three previously undetected <I>HNF1A</I> mutations in patients with diabetes. In conclusion, glycan profiles are altered substantially in <I>HNF1A</I>-MODY, and the DG9-glycan index has potential clinical value as a diagnostic biomarker of <I>HNF1A</I> dysfunction.</p>
]]></description>
<dc:creator><![CDATA[Thanabalasingham, G.; Huffman, J. E.; Kattla, J. J.; Novokmet, M.; Rudan, I.; Gloyn, A. L.; Hayward, C.; Adamczyk, B.; Reynolds, R. M.; Muzinic, A.; Hassanali, N.; Pucic, M.; Bennett, A. J.; Essafi, A.; Polasek, O.; Mughal, S. A.; Redzic, I.; Primorac, D.; Zgaga, L.; Kolcic, I.; Hansen, T.; Gasperikova, D.; Tjora, E.; Strachan, M. W. J.; Nielsen, T.; Stanik, J.; Klimes, I.; Pedersen, O. B.; Njolstad, P. R.; Wild, S. H.; Gyllensten, U.; Gornik, O.; Wilson, J. F.; Hastie, N. D.; Campbell, H.; McCarthy, M. I.; Rudd, P. M.; Owen, K. R.; Lauc, G.; Wright, A. F.]]></dc:creator>
<dc:date>2013-03-21T12:01:30-07:00</dc:date>
<dc:identifier>info:doi/10.2337/db12-0880</dc:identifier>
<dc:identifier>hwp:master-id:diabetes;db12-0880</dc:identifier>
<dc:publisher>American Diabetes Association</dc:publisher>
<dc:title><![CDATA[Mutations in HNF1A Result in Marked Alterations of Plasma Glycan Profile]]></dc:title>
<prism:publicationDate>2013-04-01</prism:publicationDate>
<prism:section>Genetics/Genomes/Proteomics/Metabolomics</prism:section>
<prism:volume>62</prism:volume>
<prism:number>4</prism:number>
<prism:startingPage>1329</prism:startingPage>
<prism:endingPage>1337</prism:endingPage>
</item>
<item rdf:about="http://diabetes.diabetesjournals.org/cgi/content/short/62/4/1338?rss=1">
<title><![CDATA[Evidence of a Causal Relationship Between Adiponectin Levels and Insulin Sensitivity: A Mendelian Randomization Study]]></title>
<link>http://diabetes.diabetesjournals.org/cgi/content/short/62/4/1338?rss=1</link>
<description><![CDATA[
<p>The adipocyte-secreted protein adiponectin is associated with insulin sensitivity in observational studies. We aimed to evaluate whether this relationship is causal using a Mendelian randomization approach. In a sample of Swedish men aged 71 years (<I>n</I> = 942) from the Uppsala Longitudinal Study of Adult Men (ULSAM), insulin sensitivity (<I>M</I>/<I>I</I> ratio) was measured by the euglycemic insulin clamp. We used three genetic variants in the <I>ADIPOQ</I> locus as instrumental variables (IVs) to estimate the potential causal effect of adiponectin on insulin sensitivity and compared these with results from conventional linear regression. The three <I>ADIPOQ</I> variants, rs17300539, rs3774261, and rs6444175, were strongly associated with serum adiponectin levels (all <I>P</I> &le; 5.3 <FONT FACE="arial,helvetica">x</FONT> 10<sup>&ndash;9</sup>) and were also significantly associated with <I>M</I>/<I>I</I> ratio in the expected direction (all <I>P</I> &le; 0.022). IV analysis confirmed that genetically determined adiponectin increased insulin sensitivity (&beta; = 0.47&ndash;0.81, all <I>P</I> &le; 0.014) comparable with observational estimates (&beta; = 0.50, all <I>P</I><SUB>difference</SUB> &ge; 0.136). Adjustment for BMI and waist circumference partly explained the association of both genetically determined and observed adiponectin levels with insulin sensitivity. The observed association between higher adiponectin levels and increased insulin sensitivity is likely to represent a causal relationship partly mediated by reduced adiposity.</p>
]]></description>
<dc:creator><![CDATA[Gao, H.; Fall, T.; van Dam, R. M.; Flyvbjerg, A.; Zethelius, B.; Ingelsson, E.; Hagg, S.]]></dc:creator>
<dc:date>2013-03-21T12:01:30-07:00</dc:date>
<dc:identifier>info:doi/10.2337/db12-0935</dc:identifier>
<dc:identifier>hwp:master-id:diabetes;db12-0935</dc:identifier>
<dc:publisher>American Diabetes Association</dc:publisher>
<dc:title><![CDATA[Evidence of a Causal Relationship Between Adiponectin Levels and Insulin Sensitivity: A Mendelian Randomization Study]]></dc:title>
<prism:publicationDate>2013-04-01</prism:publicationDate>
<prism:section>Genetics/Genomes/Proteomics/Metabolomics</prism:section>
<prism:volume>62</prism:volume>
<prism:number>4</prism:number>
<prism:startingPage>1338</prism:startingPage>
<prism:endingPage>1344</prism:endingPage>
</item>
<item rdf:about="http://diabetes.diabetesjournals.org/cgi/content/short/62/4/1345?rss=1">
<title><![CDATA[HLA-A*24 Is an Independent Predictor of 5-Year Progression to Diabetes in Autoantibody-Positive First-Degree Relatives of Type 1 Diabetic Patients]]></title>
<link>http://diabetes.diabetesjournals.org/cgi/content/short/62/4/1345?rss=1</link>
<description><![CDATA[
<p>We investigated whether <I>HLA-A*24</I> typing complements screening for <I>HLA-DQ</I> and for antibodies (Abs) against insulin, GAD, IA-2 (IA-2A), and zinc transporter-8 (ZnT8A) for prediction of rapid progression to type 1 diabetes (T1D). Persistently Ab<sup>+</sup> siblings/offspring (<I>n</I> = 288; aged 0&ndash;39 years) of T1D patients were genotyped for <I>HLA-DQA1-DQB1</I> and <I>HLA-A*24</I> and monitored for development of diabetes within 5 years of first Ab<sup>+</sup>. <I>HLA-A*24</I> (<I>P</I> = 0.009), <I>HLA-DQ2/DQ8</I> (<I>P</I> = 0.001), and positivity for IA-2A &plusmn; ZnT8A (<I>P</I> &lt; 0.001) were associated with development of T1D in multivariate analysis. The 5-year risk increased with the number of the above three markers present (<I>n</I> = 0: 6%; <I>n</I> = 1: 18%; <I>n</I> = 2: 46%; <I>n</I> = 3: 100%). Positivity for one or more markers identified a subgroup of 171 (59%) containing 88% of rapid progressors. The combined presence of <I>HLA-A*24</I> and IA-2A<sup>+</sup> &plusmn; ZnT8A<sup>+</sup> defined a subgroup of 18 (6%) with an 82% diabetes risk. Among IA-2A<sup>+</sup> &plusmn; ZnT8A<sup>+</sup> relatives, identification of <I>HLA-A*24</I> carriers in addition to <I>HLA-DQ2/DQ8</I> carriers increased screening sensitivity for relatives at high Ab- and <I>HLA</I>-inferred risk (64% progression; <I>P</I> = 0.002). In conclusion, <I>HLA-A*24</I> independently predicts rapid progression to T1D in Ab<sup>+</sup> relatives and complements IA-2A, ZnT8A, and <I>HLA-DQ2/DQ8</I> for identifying participants in immunointervention trials.</p>
]]></description>
<dc:creator><![CDATA[Mbunwe, E.; Van der Auwera, B. J.; Vermeulen, I.; Demeester, S.; Van Dalem, A.; Balti, E. V.; Van Aken, S.; Derdelinckx, L.; Dorchy, H.; De Schepper, J.; van Schravendijk, C.; Wenzlau, J. M.; Hutton, J. C.; Pipeleers, D.; Weets, I.; Gorus, F. K.; and the Belgian Diabetes Registry]]></dc:creator>
<dc:date>2013-03-21T12:01:30-07:00</dc:date>
<dc:identifier>info:doi/10.2337/db12-0747</dc:identifier>
<dc:identifier>hwp:master-id:diabetes;db12-0747</dc:identifier>
<dc:publisher>American Diabetes Association</dc:publisher>
<dc:title><![CDATA[HLA-A*24 Is an Independent Predictor of 5-Year Progression to Diabetes in Autoantibody-Positive First-Degree Relatives of Type 1 Diabetic Patients]]></dc:title>
<prism:publicationDate>2013-04-01</prism:publicationDate>
<prism:section>Genetics/Genomes/Proteomics/Metabolomics</prism:section>
<prism:volume>62</prism:volume>
<prism:number>4</prism:number>
<prism:startingPage>1345</prism:startingPage>
<prism:endingPage>1350</prism:endingPage>
</item>
<item rdf:about="http://diabetes.diabetesjournals.org/cgi/content/short/62/3/965?rss=1">
<title><![CDATA[Transferability and Fine Mapping of Type 2 Diabetes Loci in African Americans: The Candidate Gene Association Resource Plus Study]]></title>
<link>http://diabetes.diabetesjournals.org/cgi/content/short/62/3/965?rss=1</link>
<description><![CDATA[
<p>Type 2 diabetes (T2D) disproportionally affects African Americans (AfA) but, to date, genetic variants identified from genome-wide association studies (GWAS) are primarily from European and Asian populations. We examined the single nucleotide polymorphism (SNP) and locus transferability of 40 reported T2D loci in six AfA GWAS consisting of 2,806 T2D case subjects with or without end-stage renal disease and 4,265 control subjects from the Candidate Gene Association Resource Plus Study. Our results revealed that seven index SNPs at the <I>TCF7L2</I>,<I> KLF14</I>, <I>KCNQ1</I>, <I>ADCY5</I>, <I>CDKAL1</I>, <I>JAZF1</I>, and <I>GCKR</I> loci were significantly associated with T2D (<I>P</I> &lt; 0.05). The strongest association was observed at <I>TCF7L2</I> rs7903146 (odds ratio [OR] 1.30; <I>P</I> = 6.86 <FONT FACE="arial,helvetica">x</FONT> 10<sup>&ndash;8</sup>). Locus-wide analysis demonstrated significant associations (<I>P<SUB>emp</SUB></I> &lt; 0.05) at regional best SNPs in the <I>TCF7L2</I>,<I> KLF14</I>, and <I>HMGA2</I> loci as well as suggestive signals in <I>KCNQ1</I> after correction for the effective number of SNPs at each locus. Of these loci, the regional best SNPs were in differential linkage disequilibrium (LD) with the index and adjacent SNPs. Our findings suggest that some loci discovered in prior reports affect T2D susceptibility in AfA with similar effect sizes. The reduced and differential LD pattern in AfA compared with European and Asian populations may facilitate fine mapping of causal variants at loci shared across populations.</p>
]]></description>
<dc:creator><![CDATA[Ng, M. C. Y.; Saxena, R.; Li, J.; Palmer, N. D.; Dimitrov, L.; Xu, J.; Rasmussen-Torvik, L. J.; Zmuda, J. M.; Siscovick, D. S.; Patel, S. R.; Crook, E. D.; Sims, M.; Chen, Y.-D. I.; Bertoni, A. G.; Li, M.; Grant, S. F. A.; Dupuis, J.; Meigs, J. B.; Psaty, B. M.; Pankow, J. S.; Langefeld, C. D.; Freedman, B. I.; Rotter, J. I.; Wilson, J. G.; Bowden, D. W.]]></dc:creator>
<dc:date>2013-02-21T12:01:24-08:00</dc:date>
<dc:identifier>info:doi/10.2337/db12-0266</dc:identifier>
<dc:identifier>hwp:master-id:diabetes;db12-0266</dc:identifier>
<dc:publisher>American Diabetes Association</dc:publisher>
<dc:title><![CDATA[Transferability and Fine Mapping of Type 2 Diabetes Loci in African Americans: The Candidate Gene Association Resource Plus Study]]></dc:title>
<prism:publicationDate>2013-03-01</prism:publicationDate>
<prism:section>Genetics/Genomes/Proteomics/Metabolomics</prism:section>
<prism:volume>62</prism:volume>
<prism:number>3</prism:number>
<prism:startingPage>965</prism:startingPage>
<prism:endingPage>976</prism:endingPage>
</item>
<item rdf:about="http://diabetes.diabetesjournals.org/cgi/content/short/62/3/977?rss=1">
<title><![CDATA[Genome-Wide Association Study for Type 2 Diabetes in Indians Identifies a New Susceptibility Locus at 2q21]]></title>
<link>http://diabetes.diabetesjournals.org/cgi/content/short/62/3/977?rss=1</link>
<description><![CDATA[
<p>Indians undergoing socioeconomic and lifestyle transitions will be maximally affected by epidemic of type 2 diabetes (T2D). We conducted a two-stage genome-wide association study of T2D in 12,535 Indians, a less explored but high-risk group. We identified a new type 2 diabetes&ndash;associated locus at 2q21, with the lead signal being rs6723108 (odds ratio 1.31; <I>P</I> = 3.32 <FONT FACE="arial,helvetica">x</FONT> 10<sup>&ndash;9</sup>). Imputation analysis refined the signal to rs998451 (odds ratio 1.56; <I>P</I> = 6.3 <FONT FACE="arial,helvetica">x</FONT> 10<sup>&ndash;12</sup>) within <I>TMEM163</I> that encodes a probable vesicular transporter in nerve terminals. <I>TMEM163</I> variants also showed association with decreased fasting plasma insulin and homeostatic model assessment of insulin resistance, indicating a plausible effect through impaired insulin secretion. The 2q21 region also harbors <I>RAB3GAP1</I> and <I>ACMSD</I>; those are involved in neurologic disorders. Forty-nine of 56 previously reported signals showed consistency in direction with similar effect sizes in Indians and previous studies, and 25 of them were also associated (<I>P</I> &lt; 0.05). Known loci and the newly identified 2q21 locus altogether explained 7.65% variance in the risk of T2D in Indians. Our study suggests that common susceptibility variants for T2D are largely the same across populations, but also reveals a population-specific locus and provides further insights into genetic architecture and etiology of T2D.</p>
]]></description>
<dc:creator><![CDATA[Tabassum, R.; Chauhan, G.; Dwivedi, O. P.; Mahajan, A.; Jaiswal, A.; Kaur, I.; Bandesh, K.; Singh, T.; Mathai, B. J.; Pandey, Y.; Chidambaram, M.; Sharma, A.; Chavali, S.; Sengupta, S.; Ramakrishnan, L.; Venkatesh, P.; Aggarwal, S. K.; Ghosh, S.; Prabhakaran, D.; Srinath, R. K.; Saxena, M.; Banerjee, M.; Mathur, S.; Bhansali, A.; Shah, V. N.; Madhu, S. V.; Marwaha, R. K.; Basu, A.; Scaria, V.; McCarthy, M. I.; DIAGRAM; INDICO; Venkatesan, R.; Mohan, V.; Tandon, N.; Bharadwaj, D.]]></dc:creator>
<dc:date>2013-02-21T12:01:24-08:00</dc:date>
<dc:identifier>info:doi/10.2337/db12-0406</dc:identifier>
<dc:identifier>hwp:master-id:diabetes;db12-0406</dc:identifier>
<dc:publisher>American Diabetes Association</dc:publisher>
<dc:title><![CDATA[Genome-Wide Association Study for Type 2 Diabetes in Indians Identifies a New Susceptibility Locus at 2q21]]></dc:title>
<prism:publicationDate>2013-03-01</prism:publicationDate>
<prism:section>Genetics/Genomes/Proteomics/Metabolomics</prism:section>
<prism:volume>62</prism:volume>
<prism:number>3</prism:number>
<prism:startingPage>977</prism:startingPage>
<prism:endingPage>986</prism:endingPage>
</item>
<item rdf:about="http://diabetes.diabetesjournals.org/cgi/content/short/62/3/987?rss=1">
<title><![CDATA[Insights Into the Molecular Mechanism for Type 2 Diabetes Susceptibility at the KCNQ1 Locus From Temporal Changes in Imprinting Status in Human Islets]]></title>
<link>http://diabetes.diabetesjournals.org/cgi/content/short/62/3/987?rss=1</link>
<description><![CDATA[
<sec>
<p>The molecular basis of type 2 diabetes predisposition at most established susceptibility loci remains poorly understood. <I>KCNQ1</I> maps within the 11p15.5 imprinted domain, a region with an established role in congenital growth phenotypes. Variants intronic to <I>KCNQ1</I> influence diabetes susceptibility when maternally inherited. By use of quantitative PCR and pyrosequencing of human adult islet and fetal pancreas samples, we investigated the imprinting status of regional transcripts and aimed to determine whether type 2 diabetes risk alleles influence regional DNA methylation and gene expression. The results demonstrate that gene expression patterns differ by developmental stage. <I>CDKN1C</I> showed monoallelic expression in both adult and fetal tissue, whereas <I>PHLDA2</I>, <I>SLC22A18</I>, and <I>SLC22A18AS</I> were biallelically expressed in both tissues. Temporal changes in imprinting were observed for <I>KCNQ1</I> and <I>KCNQ1OT1</I>, with monoallelic expression in fetal tissues and biallelic expression in adult samples. Genotype at the type 2 diabetes risk variant rs2237895 influenced methylation levels of regulatory sequence in fetal pancreas but without demonstrable effects on gene expression. We demonstrate that <I>CDKN1C</I>, <I>KCNQ1</I>, and <I>KCNQ1OT1</I> are most likely to mediate diabetes susceptibility at the <I>KCNQ1</I> locus and identify temporal differences in imprinting status and methylation effects, suggesting that diabetes risk effects may be mediated in early development.</p>
</sec>
]]></description>
<dc:creator><![CDATA[Travers, M. E.; Mackay, D. J. G.; Dekker Nitert, M.; Morris, A. P.; Lindgren, C. M.; Berry, A.; Johnson, P. R.; Hanley, N.; Groop, L. C.; McCarthy, M. I.; Gloyn, A. L.]]></dc:creator>
<dc:date>2013-02-21T12:01:24-08:00</dc:date>
<dc:identifier>info:doi/10.2337/db12-0819</dc:identifier>
<dc:identifier>hwp:master-id:diabetes;db12-0819</dc:identifier>
<dc:publisher>American Diabetes Association</dc:publisher>
<dc:title><![CDATA[Insights Into the Molecular Mechanism for Type 2 Diabetes Susceptibility at the KCNQ1 Locus From Temporal Changes in Imprinting Status in Human Islets]]></dc:title>
<prism:publicationDate>2013-03-01</prism:publicationDate>
<prism:section>Genetics/Genomes/Proteomics/Metabolomics</prism:section>
<prism:volume>62</prism:volume>
<prism:number>3</prism:number>
<prism:startingPage>987</prism:startingPage>
<prism:endingPage>992</prism:endingPage>
</item>
<item rdf:about="http://diabetes.diabetesjournals.org/cgi/content/short/62/3/993?rss=1">
<title><![CDATA[GATA6 Mutations Cause a Broad Phenotypic Spectrum of Diabetes From Pancreatic Agenesis to Adult-Onset Diabetes Without Exocrine Insufficiency]]></title>
<link>http://diabetes.diabetesjournals.org/cgi/content/short/62/3/993?rss=1</link>
<description><![CDATA[
<p>We recently reported de novo <I>GATA6</I> mutations as the most common cause of pancreatic agenesis, accounting for 15 of 27 (56%) patients with insulin-treated neonatal diabetes and exocrine pancreatic insufficiency requiring enzyme replacement therapy. We investigated the role of <I>GATA6</I> mutations in 171 subjects with neonatal diabetes of unknown genetic etiology from a cohort of 795 patients with neonatal diabetes. Mutations in known genes had been confirmed in 624 patients (including 15 <I>GATA6</I> mutations). Sequencing of the remaining 171 patients identified nine new case subjects (24 of 795, 3%). Pancreatic agenesis was present in 21 case subjects (six new); two patients had permanent neonatal diabetes with no enzyme supplementation and one had transient neonatal diabetes. Four parents with heterozygous <I>GATA6</I> mutations were diagnosed with diabetes outside the neonatal period (12&ndash;46 years). Subclinical exocrine insufficiency was demonstrated by low fecal elastase in three of four diabetic patients who did not receive enzyme supplementation. One parent with a mosaic mutation was not diabetic but had a heart malformation. Extrapancreatic features were observed in all 24 probands and three parents, with congenital heart defects most frequent (83%). Heterozygous <I>GATA6</I> mutations cause a wide spectrum of diabetes manifestations, ranging from pancreatic agenesis to adult-onset diabetes with subclinical or no exocrine insufficiency.</p>
]]></description>
<dc:creator><![CDATA[De Franco, E.; Shaw-Smith, C.; Flanagan, S. E.; Shepherd, M. H.; International NDM Consortium; Hattersley, A. T.; Ellard, S.]]></dc:creator>
<dc:date>2013-02-21T12:01:24-08:00</dc:date>
<dc:identifier>info:doi/10.2337/db12-0885</dc:identifier>
<dc:identifier>hwp:master-id:diabetes;db12-0885</dc:identifier>
<dc:publisher>American Diabetes Association</dc:publisher>
<dc:title><![CDATA[GATA6 Mutations Cause a Broad Phenotypic Spectrum of Diabetes From Pancreatic Agenesis to Adult-Onset Diabetes Without Exocrine Insufficiency]]></dc:title>
<prism:publicationDate>2013-03-01</prism:publicationDate>
<prism:section>Genetics/Genomes/Proteomics/Metabolomics</prism:section>
<prism:volume>62</prism:volume>
<prism:number>3</prism:number>
<prism:startingPage>993</prism:startingPage>
<prism:endingPage>997</prism:endingPage>
</item>
</rdf:RDF>