Man Li

Dr. Man Li

orcid

Research Focus & Metrics

Academic Career Length

19Years (2008-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
17 January 2010 in Nature Genetics
Verified
Journal Article
Open access
PDF file
JDJosée Dupuis
Josée Dupuis
CLClaudia Langenberg
Claudia Langenberg
IPInga Prokopenko
Inga Prokopenko
RSRicha Saxena
Richa Saxena
NSNicole Soranzo
Nicole Soranzo
IBInês Barroso
Inês Barroso
The MAGIC investigators report results of a large genome-wide association study meta-analysis to identify common variants influencing fasting glucose homeostasis. They further show that several of the newly discovered loci influencing glycemic traits are also associated with risk of type 2 diabetes. Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes.

12 August 2012 in Nature Genetics
Verified
Journal Article
Open access
PDF file
TCthe DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium
the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium
AMAndrew P Morris
Andrew P Morris
BVBenjamin F Voight
Benjamin F Voight
TTTanya M Teslovich
Tanya M Teslovich
TFTeresa Ferreira
Teresa Ferreira
MMMark I McCarthy
Mark I McCarthy
Mark McCarthy, Michael Boehnke, Andrew Morris and colleagues perform large-scale association analyses using the Metabochip to gain insights into the genetic architecture of type 2 diabetes. They report several new susceptibility loci, including two that show sex-differentiated effects on disease risk. To extend understanding of the genetic architecture and molecular basis of type 2 diabetes (T2D), we conducted a meta-analysis of genetic variants on the Metabochip, including 34,840 cases and 114,981 controls, overwhelmingly of European descent. We identified ten previously unreported T2D susceptibility loci, including two showing sex-differentiated association. Genome-wide analyses of these data are consistent with a long tail of additional common variant loci explaining much of the variation in susceptibility to T2D. Exploration of the enlarged set of susceptibility loci implicates several processes, including CREBBP-related transcription, adipocytokine signaling and cell cycle regulation, in diabetes pathogenesis.

27 June 2010 in Nature Genetics
Verified
Journal Article
Closed access
PDF file
TIThe MAGIC investigators
The MAGIC investigators
BVBenjamin F Voight
Benjamin F Voight
TCThe GIANT Consortium
The GIANT Consortium
LSLaura J Scott
Laura J Scott
VSValgerdur Steinthorsdottir
Valgerdur Steinthorsdottir
MMMark I McCarthy
Mark I McCarthy

9 February 2014 in Nature Genetics
Verified
Journal Article
Open access
PDF file
AMAnubha Mahajan
Anubha Mahajan
MGMin Jin Go
Min Jin Go
WZWeihua Zhang
Weihua Zhang
JBJennifer E Below
Jennifer E Below
KGKyle J Gaulton
Kyle J Gaulton
AMAndrew P Morris
Andrew P Morris
Andrew Morris, Mark McCarthy, Michael Boehnke and colleagues report a meta-analysis of genome-wide association studies for type 2 diabetes, including 26,488 cases and 83,964 controls from populations of European, east Asian, south Asian and Mexican and Mexican American ancestry. They identify seven loci newly associated with type 2 diabetes and examine the genetic architecture of disease across populations. 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.

31 May 2019 in Nature Genetics
Verified
Journal Article
Open access
PDF file
LSLifelines Cohort Study
Lifelines Cohort Study
MWMatthias Wuttke
Matthias Wuttke
VPV. A. Million Veteran Program
V. A. Million Veteran Program
YLYong Li
Yong Li
MLMan Li
Man Li
CPCristian Pattaro
Cristian Pattaro
Chronic kidney disease (CKD) is responsible for a public health burden with multi-systemic complications. Through trans-ancestry meta-analysis of genome-wide association studies of estimated glomerular filtration rate (eGFR) and independent replication (n = 1,046,070), we identified 264 associated loci (166 new). Of these, 147 were likely to be relevant for kidney function on the basis of associations with the alternative kidney function marker blood urea nitrogen (n = 416,178). Pathway and enrichment analyses, including mouse models with renal phenotypes, support the kidney as the main target organ. A genetic risk score for lower eGFR was associated with clinically diagnosed CKD in 452,264 independent individuals. Colocalization analyses of associations with eGFR among 783,978 European-ancestry individuals and gene expression across 46 human tissues, including tubulo-interstitial and glomerular kidney compartments, identified 17 genes differentially expressed in kidney. Fine-mapping highlighted missense driver variants in 11 genes and kidney-specific regulatory variants. These results provide a comprehensive priority list of molecular targets for translational research.

11 June 2018 in Nature Genetics
Verified
Journal Article
Closed access
PDF file
CRCarolina Roselli
Carolina Roselli
MCMark D. Chaffin
Mark D. Chaffin
LWLu-Chen Weng
Lu-Chen Weng
SAStefanie Aeschbacher
Stefanie Aeschbacher
GAGustav Ahlberg
Gustav Ahlberg
PEPatrick T. Ellinor
Patrick T. Ellinor