Yunpeng Wang

Dr. Yunpeng Wang


Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

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

Representative Publications

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20 March 2020 in Science
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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

8 October 2019 in Nature Communications
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CNCaroline Nievergelt
Caroline Nievergelt
AMAdam X. Maihofer
Adam X. Maihofer
TKTorsten Klengel
Torsten Klengel
EAElizabeth G. Atkinson
Elizabeth G. Atkinson
CCChia-Yen Chen
Chia-Yen Chen
KKKarestan C. Koenen
Karestan C. Koenen
The risk of posttraumatic stress disorder (PTSD) following trauma is heritable, but robust common variants have yet to be identified. In a multi-ethnic cohort including over 30,000 PTSD cases and 170,000 controls we conduct a genome-wide association study of PTSD. We demonstrate SNP-based heritability estimates of 5–20%, varying by sex. Three genome-wide significant loci are identified, 2 in European and 1 in African-ancestry analyses. Analyses stratified by sex implicate 3 additional loci in men. Along with other novel genes and non-coding RNAs, a Parkinson’s disease gene involved in dopamine regulation, PARK2, is associated with PTSD. Finally, we demonstrate that polygenic risk for PTSD is significantly predictive of re-experiencing symptoms in the Million Veteran Program dataset, although specific loci did not replicate. These results demonstrate the role of genetic variation in the biology of risk for PTSD and highlight the necessity of conducting sex-stratified analyses and expanding GWAS beyond European ancestry populations.

21 March 2017 in PLOS Medicine
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RDRahul S. Desikan
Rahul S. Desikan
CFChun Chieh Fan
Chun Chieh Fan
YWYunpeng Wang
Yunpeng Wang
ASAndrew J. Schork
Andrew J. Schork
HCHoward J Cabral
Howard J Cabral
ADAnders M. Dale
Anders M. Dale
Identifying individuals at risk for developing Alzheimer disease (AD) is of utmost importance. Although genetic studies have identified AD-associated SNPs in APOE and other genes, genetic information has not been integrated into an epidemiological framework for risk prediction. Using genotype data from 17,008 AD cases and 37,154 controls from the International Genomics of Alzheimer’s Project (IGAP Stage 1), we identified AD-associated SNPs (at p < 10−5). We then integrated these AD-associated SNPs into a Cox proportional hazard model using genotype data from a subset of 6,409 AD patients and 9,386 older controls from Phase 1 of the Alzheimer’s Disease Genetics Consortium (ADGC), providing a polygenic hazard score (PHS) for each participant. By combining population-based incidence rates and the genotype-derived PHS for each individual, we derived estimates of instantaneous risk for developing AD, based on genotype and age, and tested replication in multiple independent cohorts (ADGC Phase 2, National Institute on Aging Alzheimer’s Disease Center [NIA ADC], and Alzheimer’s Disease Neuroimaging Initiative [ADNI], total n = 20,680). Within the ADGC Phase 1 cohort, individuals in the highest PHS quartile developed AD at a considerably lower age and had the highest yearly AD incidence rate. Among APOE ε3/3 individuals, the PHS modified expected age of AD onset by more than 10 y between the lowest and highest deciles (hazard ratio 3.34, 95% CI 2.62–4.24, p = 1.0 × 10−22). In independent cohorts, the PHS strongly predicted empirical age of AD onset (ADGC Phase 2, r = 0.90, p = 1.1 × 10−26) and longitudinal progression from normal aging to AD (NIA ADC, Cochran–Armitage trend test, p = 1.5 × 10−10), and was associated with neuropathology (NIA ADC, Braak stage of neurofibrillary tangles, p = 3.9 × 10−6, and Consortium to Establish a Registry for Alzheimer’s Disease score for neuritic plaques, p = 6.8 × 10−6) and in vivo markers of AD neurodegeneration (ADNI, volume loss within the entorhinal cortex, p = 6.3 × 10−6, and hippocampus, p = 7.9 × 10−5). Additional prospective validation of these results in non-US, non-white, and prospective community-based cohorts is necessary before clinical use. We have developed a PHS for quantifying individual differences in age-specific genetic risk for AD. Within the cohorts studied here, polygenic architecture plays an important role in modifying AD risk beyond APOE. With thorough validation, quantification of inherited genetic variation may prove useful for stratifying AD risk and as an enrichment strategy in therapeutic trials.

9 January 2018 in PLOS Medicine
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IBIris Broce
Iris Broce
CKCeleste M. Karch
Celeste M. Karch
NWNatalie Wen
Natalie Wen
CFChun C. Fan
Chun C. Fan
YWYunpeng Wang
Yunpeng Wang
LSLeo P. Sugrue
Leo P. Sugrue
Converging evidence suggests that immune-mediated dysfunction plays an important role in the pathogenesis of frontotemporal dementia (FTD). Although genetic studies have shown that immune-associated loci are associated with increased FTD risk, a systematic investigation of genetic overlap between immune-mediated diseases and the spectrum of FTD-related disorders has not been performed. Using large genome-wide association studies (GWASs) (total n = 192,886 cases and controls) and recently developed tools to quantify genetic overlap/pleiotropy, we systematically identified single nucleotide polymorphisms (SNPs) jointly associated with FTD-related disorders—namely, FTD, corticobasal degeneration (CBD), progressive supranuclear palsy (PSP), and amyotrophic lateral sclerosis (ALS)—and 1 or more immune-mediated diseases including Crohn disease, ulcerative colitis (UC), rheumatoid arthritis (RA), type 1 diabetes (T1D), celiac disease (CeD), and psoriasis. We found up to 270-fold genetic enrichment between FTD and RA, up to 160-fold genetic enrichment between FTD and UC, up to 180-fold genetic enrichment between FTD and T1D, and up to 175-fold genetic enrichment between FTD and CeD. In contrast, for CBD and PSP, only 1 of the 6 immune-mediated diseases produced genetic enrichment comparable to that seen for FTD, with up to 150-fold genetic enrichment between CBD and CeD and up to 180-fold enrichment between PSP and RA. Further, we found minimal enrichment between ALS and the immune-mediated diseases tested, with the highest levels of enrichment between ALS and RA (up to 20-fold). For FTD, at a conjunction false discovery rate < 0.05 and after excluding SNPs in linkage disequilibrium, we found that 8 of the 15 identified loci mapped to the human leukocyte antigen (HLA) region on Chromosome (Chr) 6. We also found novel candidate FTD susceptibility loci within LRRK2 (leucine rich repeat kinase 2), TBKBP1 (TBK1 binding protein 1), and PGBD5 (piggyBac transposable element derived 5). Functionally, we found that the expression of FTD–immune pleiotropic genes (particularly within the HLA region) is altered in postmortem brain tissue from patients with FTD and is enriched in microglia/macrophages compared to other central nervous system cell types. The main study limitation is that the results represent only clinically diagnosed individuals. Also, given the complex interconnectedness of the HLA region, we were not able to define the specific gene or genes on Chr 6 responsible for our pleiotropic signal. We show immune-mediated genetic enrichment specifically in FTD, particularly within the HLA region. Our genetic results suggest that for a subset of patients, immune dysfunction may contribute to FTD risk. These findings have potential implications for clinical trials targeting immune dysfunction in patients with FTD.

1 February 2021 in Biological Psychiatry
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OSOlav B. Smeland
Olav B. Smeland
ASAlexey Shadrin
Alexey Shadrin
SBShahram Bahrami
Shahram Bahrami
IBIris Broce
Iris Broce
MTMartin Tesli
Martin Tesli
OAOle A. Andreassen
Ole A. Andreassen

11 April 2018 in Translational Psychiatry
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LBLuke W. Bonham
Luke W. Bonham
CKCeleste M. Karch
Celeste M. Karch
CFChun C. Fan
Chun C. Fan
CTChin Hong Tan
Chin Hong Tan
EGEthan G. Geier
Ethan G. Geier
RDRahul S. Desikan
Rahul S. Desikan
Neurodegenerative diseases likely share common underlying pathobiology. Although prior work has identified susceptibility loci associated with various dementias, few, if any, studies have systematically evaluated shared genetic risk across several neurodegenerative diseases. Using genome-wide association data from large studies (total n = 82,337 cases and controls), we utilized a previously validated approach to identify genetic overlap and reveal common pathways between progressive supranuclear palsy (PSP), frontotemporal dementia (FTD), Parkinson’s disease (PD) and Alzheimer’s disease (AD). In addition to the MAPT H1 haplotype, we identified a variant near the chemokine receptor CXCR4 that was jointly associated with increased risk for PSP and PD. Using bioinformatics tools, we found strong physical interactions between CXCR4 and four microglia related genes, namely CXCL12, TLR2, RALB, and CCR5. Evaluating gene expression from post-mortem brain tissue, we found that expression of CXCR4 and microglial genes functionally related to CXCR4 was dysregulated across a number of neurodegenerative diseases. Furthermore, in a mouse model of tauopathy, expression of CXCR4 and functionally associated genes was significantly altered in regions of the mouse brain that accumulate neurofibrillary tangles most robustly. Beyond MAPT, we show dysregulation of CXCR4 expression in PSP, PD, and FTD brains, and mouse models of tau pathology. Our multi-modal findings suggest that abnormal signaling across a ‘network’ of microglial genes may contribute to neurodegeneration and may have potential implications for clinical trials targeting immune dysfunction in patients with neurodegenerative diseases.