Chia-Yen Chen

Dr. Chia-Yen Chen

orcid

Research Focus & Metrics

Academic Career Length

22Years (2005-Present)

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

Representative Publications

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16 April 2019 in Nature Communications
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Journal Article
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TGTian Ge
Tian Ge
CCChia-Yen Chen
Chia-Yen Chen
YNYang Ni
Yang Ni
YFYen-Chen Anne Feng
Yen-Chen Anne Feng
JSJordan W. Smoller
Jordan W. Smoller
Polygenic risk scores (PRS) have shown promise in predicting human complex traits and diseases. Here, we present PRS-CS, a polygenic prediction method that infers posterior effect sizes of single nucleotide polymorphisms (SNPs) using genome-wide association summary statistics and an external linkage disequilibrium (LD) reference panel. PRS-CS utilizes a high-dimensional Bayesian regression framework, and is distinct from previous work by placing a continuous shrinkage (CS) prior on SNP effect sizes, which is robust to varying genetic architectures, provides substantial computational advantages, and enables multivariate modeling of local LD patterns. Simulation studies using data from the UK Biobank show that PRS-CS outperforms existing methods across a wide range of genetic architectures, especially when the training sample size is large. We apply PRS-CS to predict six common complex diseases and six quantitative traits in the Partners HealthCare Biobank, and further demonstrate the improvement of PRS-CS in prediction accuracy over alternative methods.

5 May 2022 in Nature Genetics
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Journal Article
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YRYunfeng Ruan
Yunfeng Ruan
YLYen-Feng Lin
Yen-Feng Lin
YFYen-Chen Anne Feng
Yen-Chen Anne Feng
CCChia-Yen Chen
Chia-Yen Chen
MLMax Lam
Max Lam
TGTian Ge
Tian Ge

14 January 2019 in Nature Genetics
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Journal Article
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RLRichard Karlsson Linnér
Richard Karlsson Linnér
PBPietro Biroli
Pietro Biroli
EKEdward Kong
Edward Kong
SMS. Fleur W. Meddens
S. Fleur W. Meddens
RWRobbee Wedow
Robbee Wedow
JBJonathan P. Beauchamp
Jonathan P. Beauchamp
Humans vary substantially in their willingness to take risks. In a combined sample of over 1 million individuals, we conducted genome-wide association studies (GWAS) of general risk tolerance, adventurousness, and risky behaviors in the driving, drinking, smoking, and sexual domains. Across all GWAS, we identified hundreds of associated loci, including 99 loci associated with general risk tolerance. We report evidence of substantial shared genetic influences across risk tolerance and the risky behaviors: 46 of the 99 general risk tolerance loci contain a lead SNP for at least one of our other GWAS, and general risk tolerance is genetically correlated (\(\left| {\hat r_{\mathrm{g}}} \right|\) ~ 0.25 to 0.50) with a range of risky behaviors. Bioinformatics analyses imply that genes near SNPs associated with general risk tolerance are highly expressed in brain tissues and point to a role for glutamatergic and GABAergic neurotransmission. We found no evidence of enrichment for genes previously hypothesized to relate to risk tolerance.

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.

25 April 2017 in Molecular Psychiatry
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Journal Article
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LDL E Duncan
L E Duncan
ARA Ratanatharathorn
A Ratanatharathorn
AAA E Aiello
A E Aiello
LAL M Almli
L M Almli
AAA B Amstadter
A B Amstadter
KKK C Koenen
K C Koenen
The Psychiatric Genomics Consortium-Posttraumatic Stress Disorder group (PGC-PTSD) combined genome-wide case–control molecular genetic data across 11 multiethnic studies to quantify PTSD heritability, to examine potential shared genetic risk with schizophrenia, bipolar disorder, and major depressive disorder and to identify risk loci for PTSD. Examining 20 730 individuals, we report a molecular genetics-based heritability estimate (h2SNP) for European-American females of 29% that is similar to h2SNP for schizophrenia and is substantially higher than h2SNP in European-American males (estimate not distinguishable from zero). We found strong evidence of overlapping genetic risk between PTSD and schizophrenia along with more modest evidence of overlap with bipolar and major depressive disorder. No single-nucleotide polymorphisms (SNPs) exceeded genome-wide significance in the transethnic (overall) meta-analysis and we do not replicate previously reported associations. Still, SNP-level summary statistics made available here afford the best-available molecular genetic index of PTSD—for both European- and African-American individuals—and can be used in polygenic risk prediction and genetic correlation studies of diverse phenotypes. Publication of summary statistics for ∼ 10 000 African Americans contributes to the broader goal of increased ancestral diversity in genomic data resources. In sum, the results demonstrate genetic influences on the development of PTSD, identify shared genetic risk between PTSD and other psychiatric disorders and highlight the importance of multiethnic/racial samples. As has been the case with schizophrenia and other complex genetic disorders, larger sample sizes are needed to identify specific risk loci.