Andreas Ziegler

Prof. Dr. Andreas Ziegler


Research Focus & Metrics

Academic Career Length

31Years (1996-Present)

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

Representative Publications

View All Publications
5 August 2010 in Nature
Verified
Journal Article
Open access
PDF file
TTTanya M. Teslovich
Tanya M. Teslovich
KMKiran Musunuru
Kiran Musunuru
ASAlbert Smith
Albert Smith
AEAndrew C. Edmondson
Andrew C. Edmondson
ISIoannis M. Stylianou
Ioannis M. Stylianou
SKSekar Kathiresan
Sekar Kathiresan
Plasma concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with plasma lipids in >100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P < 5 × 10−8), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes—GALNT2, PPP1R3B and TTC39B—with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD.

10 October 2010 in Nature Genetics
Verified
Journal Article
Open access
PDF file
ESElizabeth K Speliotes
Elizabeth K Speliotes
MAMagic
Magic
CWCristen J Willer
Cristen J Willer
SBSonja I Berndt
Sonja I Berndt
KMKeri L Monda
Keri L Monda
OCon behalf of Procardis Consortium
on behalf of Procardis Consortium
Ruth Loos and colleagues report results of a large genome-wide association study for body mass index. They identify 18 new loci associated with this trait, some of which map near key hypothalamic regulators of energy balance. Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and ∼2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 × 10−8), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.

1 August 2012 in The Lancet
Verified
Journal Article
Open access
BVBenjamin F Voight
Benjamin F Voight
GPGina M Peloso
Gina M Peloso
MOMarju Orho-Melander
Marju Orho-Melander
RFRuth Frikke-Schmidt
Ruth Frikke-Schmidt
MBMaja Barbalic
Maja Barbalic
SKSekar Kathiresan
Sekar Kathiresan
High plasma HDL cholesterol is associated with reduced risk of myocardial infarction, but whether this association is causal is unclear. Exploiting the fact that genotypes are randomly assigned at meiosis, are independent of non-genetic confounding, and are unmodified by disease processes, mendelian randomisation can be used to test the hypothesis that the association of a plasma biomarker with disease is causal. We performed two mendelian randomisation analyses. First, we used as an instrument a single nucleotide polymorphism (SNP) in the endothelial lipase gene (LIPG Asn396Ser) and tested this SNP in 20 studies (20,913 myocardial infarction cases, 95,407 controls). Second, we used as an instrument a genetic score consisting of 14 common SNPs that exclusively associate with HDL cholesterol and tested this score in up to 12,482 cases of myocardial infarction and 41,331 controls. As a positive control, we also tested a genetic score of 13 common SNPs exclusively associated with LDL cholesterol. Carriers of the LIPG 396Ser allele (2·6% frequency) had higher HDL cholesterol (0·14 mmol/L higher, p=8×10(-13)) but similar levels of other lipid and non-lipid risk factors for myocardial infarction compared with non-carriers. This difference in HDL cholesterol is expected to decrease risk of myocardial infarction by 13% (odds ratio [OR] 0·87, 95% CI 0·84-0·91). However, we noted that the 396Ser allele was not associated with risk of myocardial infarction (OR 0·99, 95% CI 0·88-1·11, p=0·85). From observational epidemiology, an increase of 1 SD in HDL cholesterol was associated with reduced risk of myocardial infarction (OR 0·62, 95% CI 0·58-0·66). However, a 1 SD increase in HDL cholesterol due to genetic score was not associated with risk of myocardial infarction (OR 0·93, 95% CI 0·68-1·26, p=0·63). For LDL cholesterol, the estimate from observational epidemiology (a 1 SD increase in LDL cholesterol associated with OR 1·54, 95% CI 1·45-1·63) was concordant with that from genetic score (OR 2·13, 95% CI 1·69-2·69, p=2×10(-10)). Some genetic mechanisms that raise plasma HDL cholesterol do not seem to lower risk of myocardial infarction. These data challenge the concept that raising of plasma HDL cholesterol will uniformly translate into reductions in risk of myocardial infarction. US National Institutes of Health, The Wellcome Trust, European Union, British Heart Foundation, and the German Federal Ministry of Education and Research.

29 September 2010 in Nature
Verified
Journal Article
Open access
PDF file
HAHana Lango Allen
Hana Lango Allen
KEKarol Estrada
Karol Estrada
GLGuillaume Lettre
Guillaume Lettre
SBSonja I. Berndt
Sonja I. Berndt
MWMichael N. Weedon
Michael N. Weedon
JHJoel N. Hirschhorn
Joel N. Hirschhorn
A genome-wide association (GWA) study of more than 180,000 individuals has identified hundreds of genetic variants in at least 180 loci associated with adult human height. The loci are not clustered randomly but are enriched for genes involved in growth-related processes that influence adult height. This demonstrates that GWA studies of common human traits, and therefore of many diseases, can identify large numbers of loci that implicate potential causal genes. This very large genome-wide association study identifies hundreds of new genetic variants influencing adult height in at least 180 loci enriched for genes involved in skeletal growth defects. The results show that the likely causal gene is often located near the most strongly associated variant, that many loci have multiple independently associated variants and that associated variants are enriched for likely functional effects on genes. Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits1, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait2,3. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

1 August 2001 in Monatsschrift Kinderheilkunde
Verified
Journal Article
Closed access
PDF file
KKK. Kromeyer-Hauschild
K. Kromeyer-Hauschild
MWM. Wabitsch
M. Wabitsch
DKD. Kunze
D. Kunze
FGF. Geller
F. Geller
HGH. C. Geiß
H. C. Geiß
JHJ. Hebebrand
J. Hebebrand

6 March 2011 in Nature Genetics
Verified
Journal Article
Closed access
PDF file
JCJohn F. Carlquist Cardiogenics
John F. Carlquist Cardiogenics
HSHeribert Schunkert
Heribert Schunkert
TCthe CARDIoGRAM Consortium
the CARDIoGRAM Consortium
IKInke R König
Inke R König
SKSekar Kathiresan
Sekar Kathiresan
Jeanette ErdmannJeanette Erdmann
Jeanette Erdmann