Congrong Wang

Bio: Congrong Wang is an academic researcher from Shanghai Jiao Tong University. The author has contributed to research in topics: Type 2 diabetes & Diabetes mellitus. The author has an hindex of 26, co-authored 105 publications receiving 3501 citations. Previous affiliations of Congrong Wang include Tongji University & University of Medicine and Health Sciences.

Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility.

Abstract: To further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS), including 26,488 cases and 83,964 controls of European, east Asian, south Asian and Mexican and Mexican American ancestry. We observed a significant excess in the directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven new T2D susceptibility loci. Furthermore, we observed considerable improvements in the fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterization of complex trait loci and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry.

Meta-analysis of genome-wide association studies identifies eight new loci for type 2 diabetes in east Asians

Abstract: We conducted a three-stage genetic study to identify susceptibility loci for type 2 diabetes (T2D) in east Asian populations. We followed our stage 1 meta-analysis of eight T2D genome-wide association studies (6,952 cases with T2D and 11,865 controls) with a stage 2 in silico replication analysis (5,843 cases and 4,574 controls) and a stage 3 de novo replication analysis (12,284 cases and 13,172 controls). The combined analysis identified eight new T2D loci reaching genome-wide significance, which mapped in or near GLIS3, PEPD, FITM2-R3HDML-HNF4A, KCNK16, MAEA, GCC1-PAX4, PSMD6 and ZFAND3. GLIS3, which is involved in pancreatic beta cell development and insulin gene expression, is known for its association with fasting glucose levels. The evidence of an association with T2D for PEPD and HNF4A has been shown in previous studies. KCNK16 may regulate glucose-dependent insulin secretion in the pancreas. These findings, derived from an east Asian population, provide new perspectives on the etiology of T2D.

Genome-wide search for type 2 diabetes/impaired glucose homeostasis susceptibility genes in the Chinese: Significant linkage to chromosome 6q21-q23 and chromosome 1q21-q24

Abstract: This genome-wide search for susceptibility genes to type 2 diabetes/impaired glucose homeostasis (IGH) was performed on a relatively homogeneous Chinese sample with a total number of 257 pedigrees and 385 affected sibpairs. Two regions showed significant linkage to type 2 diabetes/IGH in the Chinese. The region showing linkage to type 2 diabetes/IGH from the entire sample group analysis was located on chromosome 6q21-q23 (128.93 cM, 1-LOD [logarithm of odds] support interval between 124 and 142 cM, according to the Marshfield genetic map), with a maximum likelihood score of 6.23, a nonparametric linkage (all) score of 4.48, and empirical P value <0.001. With a subanalysis based on 101 affected sibpairs with age at diagnosis of type 2 diabetes/IGH <40 years, we detected significant evidence for linkage to chromosome 1q21-q24 (192.1 cM, 1-LOD support interval between 182 and 197 cM), with a maximum likelihood score of 8.91, a nonparametric linkage (all) score of 5.70, and empirical P value <0.001. No interaction was observed between these two regions. Our independent replication of the region on chromosome 1q that has been shown to be linked significantly to type 2 diabetes/IGH in Chinese supports the notion that gene(s) in this region may be universally important in the development of human type 2 diabetes.

PPARG, KCNJ11, CDKAL1, CDKN2A-CDKN2B, IDE-KIF11-HHEX, IGF2BP2 and SLC30A8 are associated with type 2 diabetes in a Chinese population.

Abstract: Background Recent advance in genetic studies added the confirmed susceptible loci for type 2 diabetes to eighteen. In this study, we attempt to analyze the independent and joint effect of variants from these loci on type 2 diabetes and clinical phenotypes related to glucose metabolism. Methods/Principal Findings Twenty-one single nucleotide polymorphisms (SNPs) from fourteen loci were successfully genotyped in 1,849 subjects with type 2 diabetes and 1,785 subjects with normal glucose regulation. We analyzed the allele and genotype distribution between the cases and controls of these SNPs as well as the joint effects of the susceptible loci on type 2 diabetes risk. The associations between SNPs and type 2 diabetes were examined by logistic regression. The associations between SNPs and quantitative traits were examined by linear regression. The discriminative accuracy of the prediction models was assessed by area under the receiver operating characteristic curves. We confirmed the effects of SNPs from PPARG, KCNJ11, CDKAL1, CDKN2A-CDKN2B, IDE-KIF11-HHEX, IGF2BP2 and SLC30A8 on risk for type 2 diabetes, with odds ratios ranging from 1.114 to 1.406 (P value range from 0.0335 to 1.37E-12). But no significant association was detected between SNPs from WFS1, FTO, JAZF1, TSPAN8-LGR5, THADA, ADAMTS9, NOTCH2-ADAM30 and type 2 diabetes. Analyses on the quantitative traits in the control subjects showed that THADA SNP rs7578597 was association with 2-h insulin during oral glucose tolerance tests (P = 0.0005, empirical P = 0.0090). The joint effect analysis of SNPs from eleven loci showed the individual carrying more risk alleles had a significantly higher risk for type 2 diabetes. And the type 2 diabetes patients with more risk allele tended to have earlier diagnostic ages (P = 0.0006). Conclusions/Significance The current study confirmed the association between PPARG, KCNJ11, CDKAL1, CDKN2A-CDKN2B, IDE-KIF11-HHEX, IGF2BP2 and SLC30A8 and type 2 diabetes. These type 2 diabetes risk loci contributed to the disease additively.

Melamine-Induced Renal Toxicity Is Mediated by the Gut Microbiota

Abstract: Melamine poisoning has become widely publicized after a recent occurrence of renal injury in infants and children exposed to melamine-tainted milk in China. This renal damage is believed to result from kidney stones formed from melamine and uric acid or from melamine and its cocrystallizing chemical derivative, cyanuric acid. However, the composition of the stones and the mechanism by which the stones are formed in the renal tubules are unknown. We report that cyanuric acid can be produced in the gut by microbial transformation of melamine and serves as an integral component of the kidney stones responsible for melamine-induced renal toxicity in rats. Melamine-induced toxicity in rats was attenuated and melamine excretion increased after antibiotic suppression of gut microbial activity [corrected]. We further demonstrated that melamine is converted to cyanuric acid in vitro by bacteria cultured from normal rat feces; Klebsiella was subsequently identified in fecal samples by 16S ribosomal DNA sequencing. In culture, Klebsiella terrigena was shown to convert melamine to cyanuric acid directly. Rats colonized by K. terrigena showed exacerbated melamine-induced nephrotoxicity. Cyanuric acid was detected in the kidneys of rats administered melamine alone, and the concentration after Klebsiella colonization was increased. These findings suggest that the observed toxicity of melamine may be conditional on the exact composition and metabolic activities of the gut microbiota.

Heart Disease and Stroke Statistics—2019 Update: A Report From the American Heart Association

Abstract: March 5, 2019 e1 WRITING GROUP MEMBERS Emelia J. Benjamin, MD, ScM, FAHA, Chair Paul Muntner, PhD, MHS, FAHA, Vice Chair Alvaro Alonso, MD, PhD, FAHA Marcio S. Bittencourt, MD, PhD, MPH Clifton W. Callaway, MD, FAHA April P. Carson, PhD, MSPH, FAHA Alanna M. Chamberlain, PhD Alexander R. Chang, MD, MS Susan Cheng, MD, MMSc, MPH, FAHA Sandeep R. Das, MD, MPH, MBA, FAHA Francesca N. Delling, MD, MPH Luc Djousse, MD, ScD, MPH Mitchell S.V. Elkind, MD, MS, FAHA Jane F. Ferguson, PhD, FAHA Myriam Fornage, PhD, FAHA Lori Chaffin Jordan, MD, PhD, FAHA Sadiya S. Khan, MD, MSc Brett M. Kissela, MD, MS Kristen L. Knutson, PhD Tak W. Kwan, MD, FAHA Daniel T. Lackland, DrPH, FAHA Tené T. Lewis, PhD Judith H. Lichtman, PhD, MPH, FAHA Chris T. Longenecker, MD Matthew Shane Loop, PhD Pamela L. Lutsey, PhD, MPH, FAHA Seth S. Martin, MD, MHS, FAHA Kunihiro Matsushita, MD, PhD, FAHA Andrew E. Moran, MD, MPH, FAHA Michael E. Mussolino, PhD, FAHA Martin O’Flaherty, MD, MSc, PhD Ambarish Pandey, MD, MSCS Amanda M. Perak, MD, MS Wayne D. Rosamond, PhD, MS, FAHA Gregory A. Roth, MD, MPH, FAHA Uchechukwu K.A. Sampson, MD, MBA, MPH, FAHA Gary M. Satou, MD, FAHA Emily B. Schroeder, MD, PhD, FAHA Svati H. Shah, MD, MHS, FAHA Nicole L. Spartano, PhD Andrew Stokes, PhD David L. Tirschwell, MD, MS, MSc, FAHA Connie W. Tsao, MD, MPH, Vice Chair Elect Mintu P. Turakhia, MD, MAS, FAHA Lisa B. VanWagner, MD, MSc, FAST John T. Wilkins, MD, MS, FAHA Sally S. Wong, PhD, RD, CDN, FAHA Salim S. Virani, MD, PhD, FAHA, Chair Elect On behalf of the American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee

Heart Disease and Stroke Statistics-2018 Update: A Report From the American Heart Association.

Abstract: Each chapter listed in the Table of Contents (see next page) is a hyperlink to that chapter. The reader clicks the chapter name to access that chapter. Each chapter listed here is a hyperlink. Click on the chapter name to be taken to that chapter. Each year, the American Heart Association (AHA), in conjunction with the Centers for Disease Control and Prevention, the National Institutes of Health, and other government agencies, brings together in a single document the most up-to-date statistics related to heart disease, stroke, and the cardiovascular risk factors listed in the AHA’s My Life Check - Life’s Simple 7 (Figure1), which include core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure [BP], and glucose control) that contribute to cardiovascular health. The Statistical Update represents …

Heart Disease and Stroke Statistics—2020 Update: A Report From the American Heart Association

Abstract: Background: The American Heart Association, in conjunction with the National Institutes of Health, annually reports on the most up-to-date statistics related to heart disease, stroke, and cardiovas...

Heart Disease and Stroke Statistics-2021 Update: A Report From the American Heart Association.

Abstract: Background: The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascul...

10 Years of GWAS Discovery: Biology, Function, and Translation

Abstract: Application of the experimental design of genome-wide association studies (GWASs) is now 10 years old (young), and here we review the remarkable range of discoveries it has facilitated in population and complex-trait genetics, the biology of diseases, and translation toward new therapeutics. We predict the likely discoveries in the next 10 years, when GWASs will be based on millions of samples with array data imputed to a large fully sequenced reference panel and on hundreds of thousands of samples with whole-genome sequencing data.