Bruce H.R. Wolffenbuttel

Prof. Dr. Bruce H.R. Wolffenbuttel

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Research Focus & Metrics

Academic Career Length

46Years (1981-Present)

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

Representative Publications

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11 February 2015 in Nature
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ALAdam E Locke
Adam E Locke
BKBratati Kahali
Bratati Kahali
SBSonja I Berndt
Sonja I Berndt
AJAnne E Justice
Anne E Justice
TPTune H Pers
Tune H Pers
ESElizabeth K. Speliotes
Elizabeth K. Speliotes

6 October 2013 in Nature Genetics
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Journal Article
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RDRon Do
Ron Do
CWCristen J Willer
Cristen J Willer
ESEllen M Schmidt
Ellen M Schmidt
SSSebanti Sengupta
Sebanti Sengupta
CGChi Gao
Chi Gao
SKSekar Kathiresan
Sekar Kathiresan
Sekar Kathiresan and colleagues examine 185 common variants using a modified mendelian randomization approach and provide evidence supporting a causal role of triglyceride-rich lipoproteins in the development of coronary artery disease. Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiological studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids (P < 5 × 10−8 for each) to examine the role of triglycerides in risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglyceride levels, and we show that the direction and magnitude of the associations with both traits are factors in determining CAD risk. Second, we consider loci with only a strong association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol (HDL-C) levels, the strength of a polymorphism's effect on triglyceride levels is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD.

14 December 2014 in International Journal of Epidemiology
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SSSalome Scholtens
Salome Scholtens
NSNynke Smidt
Nynke Smidt
MSMorris A Swertz
Morris A Swertz
SBStephan Bakker
Stephan Bakker
ADAafje Dotinga
Aafje Dotinga
RSRonald P Stolk
Ronald P Stolk
The LifeLines Cohort Study is a large population-based cohort study and biobank that was established as a resource for research on complex interactions between environmental, phenotypic and genomic factors in the development of chronic diseases and healthy ageing. Between 2006 and 2013, inhabitants of the northern part of The Netherlands and their families were invited to participate, thereby contributing to a three-generation design. Participants visited one of the LifeLines research sites for a physical examination, including lung function, ECG and cognition tests, and completed extensive questionnaires. Baseline data were collected for 167 729 participants, aged from 6 months to 93 years. Follow-up visits are scheduled every 5 years, and in between participants receive follow-up questionnaires. Linkage is being established with medical registries and environmental data. LifeLines contains information on biochemistry, medical history, psychosocial characteristics, lifestyle and more. Genomic data are available including genome-wide genetic data of 15 638 participants. Fasting blood and 24-h urine samples are processed on the day of collection and stored at -80 °C in a fully automated storage facility. The aim of LifeLines is to be a resource for the national and international scientific community. Requests for data and biomaterials can be submitted to the LifeLines Research Office [LLscience@umcg.nl].

23 December 2012 in Nature Genetics
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LSLifeLines Cohort Study
LifeLines Cohort Study
AKAnna Köttgen
Anna Köttgen
CCCARDIoGRAM Consortium
CARDIoGRAM Consortium
DCDIAGRAM Consortium
DIAGRAM Consortium
ICICBP Consortium
ICBP Consortium
CGChristian Gieger
Christian Gieger

7 April 2013 in Nature Genetics
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SBSonja I Berndt
Sonja I Berndt
SGStefan Gustafsson
Stefan Gustafsson
RMReedik Mägi
Reedik Mägi
AGAndrea Ganna
Andrea Ganna
EWEleanor Wheeler
Eleanor Wheeler
EIErik Ingelsson
Erik Ingelsson
Erik Ingelsson and colleagues report a large-scale genome-wide meta-analysis for associations to the extremes of anthropometric traits, including body mass index, height, waist-to-hip ratio and clinical obesity. They identify four loci newly associated with height and seven loci newly associated with clinical obesity and find overlap in the genetic structure and distribution of variants identified for these extremes of the trait distributions and for the general population. Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.

23 July 2014 in Nature
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ASAustralian Ovarian Cancer Study
Australian Ovarian Cancer Study
JPJohn R. B. Perry
John R. B. Perry
TNThe Genica Network
The Genica Network
KFk Con Fab
k Con Fab
TSThe LifeLines Cohort Study
The LifeLines Cohort Study
KOKen K. Ong
Ken K. Ong
Here 106 genomic loci associated with age at menarche, a marker of puberty timing in females, are identified; these loci show enrichment for genes involved in nuclear hormone receptor function, body mass index, and rare disorders of puberty, and for genes located in imprinted regions, with parent-of-origin specific effects at several loci. The age at which females first experience menstruation, called menarche, is a heritable trait associated with risks for obesity, type 2 diabetes, cardiovascular disease, breast cancer and general mortality. This large-scale genome-wide association study identifies 123 signals at 106 genomic loci associated with age at menarche. New findings include parent-of-origin-specific allelic associations (both maternally and paternally driven) at three imprinted loci and the implication of retinoic acid and GABAB receptor II signalling and lysine-specific histone demethylation. These data bring new insights into the genetic architecture of puberty timing and suggest a model involving thousands of genetic variants. Age at menarche is a marker of timing of puberty in females. It varies widely between individuals, is a heritable trait and is associated with risks for obesity, type 2 diabetes, cardiovascular disease, breast cancer and all-cause mortality1. Studies of rare human disorders of puberty and animal models point to a complex hypothalamic-pituitary-hormonal regulation2,3, but the mechanisms that determine pubertal timing and underlie its links to disease risk remain unclear. Here, using genome-wide and custom-genotyping arrays in up to 182,416 women of European descent from 57 studies, we found robust evidence (P < 5 × 10−8) for 123 signals at 106 genomic loci associated with age at menarche. Many loci were associated with other pubertal traits in both sexes, and there was substantial overlap with genes implicated in body mass index and various diseases, including rare disorders of puberty. Menarche signals were enriched in imprinted regions, with three loci (DLK1-WDR25, MKRN3-MAGEL2 and KCNK9) demonstrating parent-of-origin-specific associations concordant with known parental expression patterns. Pathway analyses implicated nuclear hormone receptors, particularly retinoic acid and γ-aminobutyric acid-B2 receptor signalling, among novel mechanisms that regulate pubertal timing in humans. Our findings suggest a genetic architecture involving at least hundreds of common variants in the coordinated timing of the pubertal transition.