Per Hoffmann

Dr. Per Hoffmann

orcid

Research Focus & Metrics

Academic Career Length

24Years (2003-Present)

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

Representative Publications

View All Publications
11 November 2012 in Nature Genetics
Verified
Journal Article
Open access
PDF file
LTLam Tsoi
Lam Tsoi
SSSarah L Spain
Sarah L Spain
JKJo Knight
Jo Knight
EEEva Ellinghaus
Eva Ellinghaus
PSPhilip E Stuart
Philip E Stuart
RTRichard C Trembath
Richard C Trembath
Richard Trembath and colleagues report a meta-analysis of genome-wide association studies for psoriasis, including 2 cohorts genotyped on the custom Immunochip array, in a total of 10,588 cases and 22,806 controls. They identify 15 new susceptibility loci and refine signals in previously known loci, highlighting a role for innate host defense in susceptibility to psoriasis. To gain further insight into the genetic architecture of psoriasis, we conducted a meta-analysis of 3 genome-wide association studies (GWAS) and 2 independent data sets genotyped on the Immunochip, including 10,588 cases and 22,806 controls. We identified 15 new susceptibility loci, increasing to 36 the number associated with psoriasis in European individuals. We also identified, using conditional analyses, five independent signals within previously known loci. The newly identified loci shared with other autoimmune diseases include candidate genes with roles in regulating T-cell function (such as RUNX3, TAGAP and STAT3). Notably, they included candidate genes whose products are involved in innate host defense, including interferon-mediated antiviral responses (DDX58), macrophage activation (ZC3H12C) and nuclear factor (NF)-κB signaling (CARD14 and CARM1). These results portend a better understanding of shared and distinctive genetic determinants of immune-mediated inflammatory disorders and emphasize the importance of the skin in innate and acquired host defense.

17 July 2017 in Nature Genetics
Verified
Journal Article
Closed access
PDF file
RSRebecca Sims
Rebecca Sims
SLSven J van der Lee
Sven J van der Lee
ANAdam C Naj
Adam C Naj
CBCéline Bellenguez
Céline Bellenguez
NBNandini Badarinarayan
Nandini Badarinarayan
GSGerard D Schellenberg
Gerard D Schellenberg

30 July 2008 in Nature Genetics
Verified
Journal Article
Closed access
PDF file
MCMolecular Genetics of Schizophrenia Collaboration
Molecular Genetics of Schizophrenia Collaboration
MOMichael C O'DOnovan
Michael C O'DOnovan
NCNicholas Craddock
Nicholas Craddock
NNNadine Norton
Nadine Norton
HWHywel Williams
Hywel Williams
MOMichael J Owen
Michael J Owen

20 March 2020 in Science
Verified
Journal Article
Closed access
PDF file
KGKatrina Grasby
Katrina Grasby
NJNeda Jahanshad
Neda Jahanshad
JPJodie Painter
Jodie Painter
LCLucía Colodro Conde
Lucía Colodro Conde
JBJanita Bralten
Janita Bralten
EGEnhancing NeuroImaging Genetics through Meta-Analysis Consortium (ENIGMA)—Genetics working group
Enhancing NeuroImaging Genetics through Meta-Analysis Consortium (ENIGMA)—Genetics working group
INTRODUCTION: The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE: To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS: We identified 369 nominally genome-wide significant loci ( P < 5 × 10 −8 ) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 360 loci for which replication data were available, 241 loci influencing surface area and 66 influencing thickness remained significant after replication, with 237 loci passing multiple testing correction ( P < 8.3 × 10 −10 ; 187 influencing surface area and 50 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation ( r G = −0.32, SE = 0.05, P = 6.5 × 10 −12 ), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 46 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION: This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function. Identifying genetic influences on human cortical structure.: ( A ) Measurement of cortical surface area and thickness from MRI. ( B ) Genomic locations of common genetic variants that influence global and regional cortical structure. ( C ) Our results support the radial unit hypothesis that the expansion of cortical surface area is driven by proliferating neural progenitor cells. ( D ) Cortical surface area shows genetic correlation with psychiatric and cognitive traits. Error bars indicate SE. IMAGE CREDITS: (A) K. COURTNEY; (C) M. R. GLASS

1 April 2012 in Cell Stem Cell
Verified
Journal Article
Closed access
MTMarc Thier
Marc Thier
Philipp WörsdörferPhilipp Wörsdörfer
Philipp Wörsdörfer
YLYenal B. Lakes
Yenal B. Lakes
RGRaphaela Gorris
Raphaela Gorris
SHStefan Herms
Stefan Herms
FEFrank Edenhofer
Frank Edenhofer

8 March 2009 in Nature Genetics
Verified
Journal Article
Closed access
PDF file
SBStefanie Birnbaum
Stefanie Birnbaum
KLKerstin U Ludwig
Kerstin U Ludwig
HRHeiko Reutter
Heiko Reutter
SHStefan Herms
Stefan Herms
MSMichael Steffens
Michael Steffens
EMElisabeth Mangold
Elisabeth Mangold