Hui Qi Qu

A genome-wide association study identifies KIAA0350 as a type 1 diabetes gene.

Type 1 diabetes (T1D) in children results from autoimmune destruction of pancreatic beta cells, leading to insufficient production of insulin. A number of genetic determinants of T1D have already been established through candidate gene studies, primarily within the major histocompatibility complex but also within other loci. To identify new genetic factors that increase the risk of T1D, we performed a genome-wide association study in a large paediatric cohort of European descent. In addition to confirming previously identified loci, we found that T1D was significantly associated with variation within a 233-kb linkage disequilibrium block on chromosome 16p13. This region contains KIAA0350, the gene product of which is predicted to be a sugar-binding, C-type lectin. Three common non-coding variants of the gene (rs2903692, rs725613 and rs17673553) in strong linkage disequilibrium reached genome-wide significance for association with T1D. A subsequent transmission disequilibrium test replication study in an independent cohort confirmed the association. These results indicate that KIAA0350 might be involved in the pathogenesis of T1D and demonstrate the utility of the genome-wide association approach in the identification of previously unsuspected genetic determinants of complex traits.

Rfx6 directs islet formation and insulin production in mice and humans

Insulin from the β-cells of the pancreatic islets of Langerhans controls energy homeostasis in vertebrates, and its deficiency causes diabetes mellitus. During embryonic development, the transcription factor neurogenin 3 (Neurog3) initiates the differentiation of the β-cells and other islet cell types from pancreatic endoderm, but the genetic program that subsequently completes this differentiation remains incompletely understood. Here we show that the transcription factor Rfx6 directs islet cell differentiation downstream of Neurog3. Mice lacking Rfx6 failed to generate any of the normal islet cell types except for pancreatic-polypeptide-producing cells. In human infants with a similar autosomal recessive syndrome of neonatal diabetes, genetic mapping and subsequent sequencing identified mutations in the human RFX6 gene. These studies demonstrate a unique position for Rfx6 in the hierarchy of factors that coordinate pancreatic islet development in both mice and humans. Rfx6 could prove useful in efforts to generate β-cells for patients with diabetes.

A Novel Susceptibility Locus for Type 1 Diabetes on Chr12q13 Identified by a Genome-Wide Association Study

OBJECTIVE—In stage 1 of our genome-wide association (GWA) study for type 1 diabetes, one locus at 16p13 was detected (P = 1.03 × 10−10) and confirmed in two additional cohorts. Here we describe the results of testing, in these additional cohorts, 23 loci that were next in rank of statistical significance. RESEARCH DESIGN AND METHODS—Two independent cohorts were studied. The Type 1 Diabetes Genetics Consortium replication cohort consisted of 549 families with at least one child diagnosed with diabetes (946 total affected) and DNA from both parents. The Canadian replication cohort consisted of 364 nuclear family trios with one type 1 diabetes–affected offspring and two parents (1,092 individuals). RESULTS—One locus at 12q13, with the highest statistical significance among the 23, was confirmed. It involves type 1 diabetes association with the minor allele of rs1701704 (P = 9.13 × 10−10, OR 1.25 [95% CI 1.12–1.40]). CONCLUSIONS—We have discovered a type 1 diabetes locus at 12q13 that is replicated in an independent cohort of type 1 diabetic patients and confers a type 1 diabetes risk comparable with that of the 16p13 locus we recently reported. These two loci are identical to two loci identified by the whole-genome association study of the Wellcome Trust Case-Control Consortium, a parallel independent discovery that adds further support to the validity of the GWA approach.

Comparative genetic analysis of inflammatory bowel disease and type 1 diabetes implicates multiple loci with opposite effects

Inflammatory bowel disease, including Crohns disease (CD) and ulcerative colitis (UC), and type 1 diabetes (T1D) are autoimmune diseases that may share common susceptibility pathways. We examined known susceptibility loci for these diseases in a cohort of 1689 CD cases, 777 UC cases, 989 T1D cases and 6197 shared control subjects of European ancestry, who were genotyped by the Illumina HumanHap550 SNP arrays. We identified multiple previously unreported or unconfirmed disease associations, including known CD loci (ICOSLG and TNFSF15) and T1D loci (TNFAIP3) that confer UC risk, known UC loci (HERC2 and IL26) that confer T1D risk and known UC loci (IL10 and CCNY) that confer CD risk. Additionally, we show that T1D risk alleles residing at the PTPN22, IL27, IL18RAP and IL10 loci protect against CD. Furthermore, the strongest risk alleles for T1D within the major histocompatibility complex (MHC) confer strong protection against CD and UC; however, given the multi-allelic nature of the MHC haplotypes, sequencing of the MHC locus will be required to interpret this observation. These results extend our current knowledge on genetic variants that predispose to autoimmunity, and suggest that many loci involved in autoimmunity may be under a balancing selection due to antagonistic pleiotropic effect. Our analysis implies that variants with opposite effects on different diseases may facilitate the maintenance of common susceptibility alleles in human populations, making autoimmune diseases especially amenable to genetic dissection by genome-wide association studies.

Follow-up analysis of genome-wide association data identifies novel loci for type 1 diabetes.

OBJECTIVE—Two recent genome-wide association (GWA) studies have revealed novel loci for type 1 diabetes, a common multifactorial disease with a strong genetic component. To fully utilize the GWA data that we had obtained by genotyping 563 type 1 diabetes probands and 1,146 control subjects, as well as 483 case subject–parent trios, using the Illumina HumanHap550 BeadChip, we designed a full stage 2 study to capture other possible association signals. RESEARCH DESIGN AND METHODS—From our existing datasets, we selected 982 markers with P < 0.05 in both GWA cohorts. Genotyping these in an independent set of 636 nuclear families with 974 affected offspring revealed 75 markers that also had P < 0.05 in this third cohort. Among these, six single nucleotide polymorphisms in five novel loci also had P < 0.05 in the Wellcome Trust Case-Control Consortium dataset and were further tested in 1,303 type 1 diabetes probands from the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) plus 1,673 control subjects. RESULTS—Two markers (rs9976767 and rs3757247) remained significant after adjusting for the number of tests in this last cohort; they reside in UBASH3A (OR 1.16; combined P = 2.33 × 10−8) and BACH2 (1.13; combined P = 1.25 × 10−6). CONCLUSIONS—Evaluation of a large number of statistical GWA candidates in several independent cohorts has revealed additional loci that are associated with type 1 diabetes. The two genes at these respective loci, UBASH3A and BACH2, are both biologically relevant to autoimmunity.

Toward further mapping of the association between the IL2RA locus and type 1 diabetes

A novel type 1 diabetes locus was mapped to the interleukin-2 receptor α gene (IL2RA) on chromosome 10p15.1, encoding an important modulator of immunity. The aim of the current study was to confirm the association of IL2RA with type 1 diabetes and to attempt further mapping of the genetic effect with a new set of 12 single nucleotide polymorphisms (SNPs). We genotyped 949 nuclear family trios with one type 1 diabetes–affected offspring and two parents (2,847 individuals). Two of the 12 IL2RA SNPs genotyped (rs706778 and rs3118470) had statistically significant type 1 diabetes association (P = 6.96 × 10−4 and 8.63 × 10−4, respectively). Both SNPs are located in the 5′ end of the long intron 1 within 3 kb of each other and are in high linkage disequilibrium (D′ = 0.997, r2 = 0.613). The A-C haplotype (frequency = 0.331) was associated with increased type 1 diabetes risk (P = 3.02 × 10−4). Our study identifies two markers in the IL2RA gene that are significantly associated with type 1 diabetes, supporting IL2RA as a promising candidate gene for type 1 diabetes and suggesting a potential role of IL2Rα in the pathogenesis of type 1 diabetes, likely involving regulatory T-cells.

A Common Variant of the PAX2 Gene Is Associated with Reduced Newborn Kidney Size

Congenital nephron number ranges widely in the human population. Suboptimal nephron number may be associated with increased risk for essential hypertension and susceptibility to renal injury, but the factors that set nephron number during kidney development are unknown. In renal-coloboma syndrome, renal hypoplasia and reduced nephron number are due to heterozygous mutations of the PAX2 gene. This study tested for an association between a common haplotype of the PAX2 gene and subtle renal hypoplasia in normal newborns. A PAX2 haplotype was identified to occur in 18.5% of the newborn cohort, which was significantly associated with a 10% reduction in newborn kidney volume adjusted for body surface area. This haplotype was also associated with reduced allele-specific PAX2 mRNA level in a human renal cell carcinoma cell line. Subtle renal hypoplasia in normal newborns may be partially due to a common variant of the PAX2 gene that reduces mRNA expression during kidney development.

The Definition of Insulin Resistance Using HOMA-IR for Americans of Mexican Descent Using Machine Learning

Objective The lack of standardized reference range for the homeostasis model assessment-estimated insulin resistance (HOMA-IR) index has limited its clinical application. This study defines the reference range of HOMA-IR index in an adult Hispanic population based with machine learning methods. Methods This study investigated a Hispanic population of 1854 adults, randomly selected on the basis of 2000 Census tract data in the city of Brownsville, Cameron County. Machine learning methods, support vector machine (SVM) and Bayesian Logistic Regression (BLR), were used to automatically identify measureable variables using standardized values that correlate with HOMA-IR; K-means clustering was then used to classify the individuals by insulin resistance. Results Our study showed that the best cutoff of HOMA-IR for identifying those with insulin resistance is 3.80. There are 39.1% individuals in this Hispanic population with HOMA-IR>3.80. Conclusions Our results are dramatically different using the popular clinical cutoff of 2.60. The high sensitivity and specificity of HOMA-IR>3.80 for insulin resistance provide a critical fundamental for our further efforts to improve the public health of this Hispanic population.

Confirmation of the association of the R620W polymorphism in the protein tyrosine phosphatase PTPN22 with type 1 diabetes in a family based study

In a hand-off method in a CDMA cellular system, whether a frequency in use is a frequency layer boundary is determined in response to a notification indicating a deterioration in the frequency in use from a mobile unit. A frequency prepared in both a communication cell and an adjacent cell is selected when the frequency in use is the frequency layer boundary. Inter-frequency hand-off is executed in the communication cell by using the selected frequency. Inter-cell hand-off is executed in response to a notification indicating a destination cell from the mobile unit, which is based on a pilot signal strength measurement result from the adjacent cell.

Genome-wide profiling using single-nucleotide polymorphism arrays identifies novel chromosomal imbalances in pediatric glioblastomas

Available data on genetic events in pediatric grade IV astrocytomas (glioblastoma [pGBM]) are scarce. This has traditionally been a major impediment in understanding the pathogenesis of this tumor and in developing ways for more effective management. Our aim is to chart DNA copy number aberrations (CNAs) and get insight into genetic pathways involved in pGBM. Using the Illumina Infinium Human-1 bead-chip-array (100K single-nucleotide polymorphisms [SNPs]), we genotyped 18 pediatric and 6 adult GBMs. Results were compared to BAC-array profiles harvested on 16 of the same pGBM, to an independent data set of 9 pediatric high-grade astrocytomas (HGAs) analyzed on Affymetrix 250K-SNP arrays, and to existing data sets on HGAs. CNAs were additionally validated by real-time qPCR in a set of genes in pGBM. Our results identify with nonrandom clustering of CNAs in several novel, previously not reported, genomic regions, suggesting that alterations in tumor suppressors and genes involved in the regulation of RNA processing and the cell cycle are major events in the pathogenesis of pGBM. Most regions were distinct from CNAs in aGBMs and show an unexpectedly low frequency of genetic amplification and homozygous deletions and a high frequency of loss of heterozygosity for a high-grade I rapidly dividing tumor. This first, complete, high-resolution profiling of the tumor cell genome fills an important gap in studies on pGBM. It ultimately guides the mapping of oncogenic networks unique to pGBM, identification of the related therapeutic predictors and targets, and development of more effective therapies. It further shows that, despite commonalities in a few CNAs, pGBM and aGBMs are two different diseases.