Eitaro Nakashima

Bio: Eitaro Nakashima is an academic researcher from Nagoya University. The author has contributed to research in topics: Aldose reductase inhibitor & Polyol pathway. The author has an hindex of 30, co-authored 63 publications receiving 4900 citations.

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.

Meta-analysis of genome-wide association studies identifies common variants associated with blood pressure variation in east Asians

Abstract: We conducted a meta-analysis of genome-wide association studies of systolic (SBP) and diastolic (DBP) blood pressure in 19,608 subjects of east Asian ancestry from the AGEN-BP consortium followed up with de novo genotyping (n = 10,518) and further replication (n = 20,247) in east Asian samples. We identified genome-wide significant (P < 5 × 10(-8)) associations with SBP or DBP, which included variants at four new loci (ST7L-CAPZA1, FIGN-GRB14, ENPEP and NPR3) and a newly discovered variant near TBX3. Among the five newly discovered variants, we obtained significant replication in the independent samples for all of these loci except NPR3. We also confirmed seven loci previously identified in populations of European descent. Moreover, at 12q24.13 near ALDH2, we observed strong association signals (P = 7.9 × 10(-31) and P = 1.3 × 10(-35) for SBP and DBP, respectively) with ethnic specificity. These findings provide new insights into blood pressure regulation and potential targets for intervention.

Trans-ancestry genome-wide association study identifies 12 genetic loci influencing blood pressure and implicates a role for DNA methylation

Abstract: We carried out a trans-ancestry genome-wide association and replication study of blood pressure phenotypes among up to 320,251 individuals of East Asian, European and South Asian ancestry. We find genetic variants at 12 new loci to be associated with blood pressure (P = 3.9 × 10(-11) to 5.0 × 10(-21)). The sentinel blood pressure SNPs are enriched for association with DNA methylation at multiple nearby CpG sites, suggesting that, at some of the loci identified, DNA methylation may lie on the regulatory pathway linking sequence variation to blood pressure. The sentinel SNPs at the 12 new loci point to genes involved in vascular smooth muscle (IGFBP3, KCNK3, PDE3A and PRDM6) and renal (ARHGAP24, OSR1, SLC22A7 and TBX2) function. The new and known genetic variants predict increased left ventricular mass, circulating levels of NT-proBNP, and cardiovascular and all-cause mortality (P = 0.04 to 8.6 × 10(-6)). Our results provide new evidence for the role of DNA methylation in blood pressure regulation.

Confirmation of Multiple Risk Loci and Genetic Impacts by a Genome-Wide Association Study of Type 2 Diabetes in the Japanese Population

Abstract: OBJECTIVE To identify novel type 2 diabetes gene variants and confirm previously identified ones, a three-staged genome-wide association study was performed in the Japanese population. RESEARCH DESIGN AND METHODS In the stage 1 scan, we genotyped 519 case and 503 control subjects with 482,625 single nucleotide polymorphism (SNP) markers; in the stage 2 panel comprising 1,110 case subjects and 1,014 control subjects, we assessed 1,456 SNPs ( P P –5 for genome-wide exploration and P RESULTS Four loci—1 novel with suggestive evidence ( PEPD on 19q13, P = 1.4 × 10 –5 ) and three previously reported—were identified; the association of CDKAL1 , CDKN2A / CDKN2B, and KCNQ1 were confirmed ( P –19 ). Moreover, significant associations were replicated in five other candidate loci: TCF7L2 , IGF2BP2 , SLC30A8 , HHEX , and KCNJ11 . There was substantial overlap of type 2 diabetes susceptibility genes between the two populations, whereas effect size and explained variance tended to be higher in the Japanese population. CONCLUSIONS The strength of association was more prominent in the Japanese population than in Europeans for more than half of the confirmed type 2 diabetes loci.

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.