Yun Li

Prof. Dr. Yun Li

orcid

Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

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

Representative Publications

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23 December 2019 in PLOS Genetics
Verified
Journal Article
Open access
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MKMadeline H. Kowalski
Madeline H. Kowalski
HQHuijun Qian
Huijun Qian
ZHZiyi Hou
Ziyi Hou
JRJonathan Rosen
Jonathan Rosen
ATAmanda L. Tapia
Amanda L. Tapia
YLYun Li
Yun Li
Most genome-wide association and fine-mapping studies to date have been conducted in individuals of European descent, and genetic studies of populations of Hispanic/Latino and African ancestry are limited. In addition, these populations have more complex linkage disequilibrium structure. In order to better define the genetic architecture of these understudied populations, we leveraged >100,000 phased sequences available from deep-coverage whole genome sequencing through the multi-ethnic NHLBI Trans-Omics for Precision Medicine (TOPMed) program to impute genotypes into admixed African and Hispanic/Latino samples with genome-wide genotyping array data. We demonstrated that using TOPMed sequencing data as the imputation reference panel improves genotype imputation quality in these populations, which subsequently enhanced gene-mapping power for complex traits. For rare variants with minor allele frequency (MAF) < 0.5%, we observed a 2.3- to 6.1-fold increase in the number of well-imputed variants, with 11–34% improvement in average imputation quality, compared to the state-of-the-art 1000 Genomes Project Phase 3 and Haplotype Reference Consortium reference panels. Impressively, even for extremely rare variants with minor allele count 86%. Subsequent association analyses of TOPMed reference panel-imputed genotype data with hematological traits (hemoglobin (HGB), hematocrit (HCT), and white blood cell count (WBC)) in ~21,600 African-ancestry and ~21,700 Hispanic/Latino individuals identified associations with two rare variants in the HBB gene (rs33930165 with higher WBC [p = 8.8x10-15] in African populations, rs11549407 with lower HGB [p = 1.5x10-12] and HCT [p = 8.8x10-10] in Hispanics/Latinos). By comparison, neither variant would have been genome-wide significant if either 1000 Genomes Project Phase 3 or Haplotype Reference Consortium reference panels had been used for imputation. Our findings highlight the utility of the TOPMed imputation reference panel for identification of novel rare variant associations not previously detected in similarly sized genome-wide studies of under-represented African and Hispanic/Latino populations. Admixed African and Hispanic/Latino populations remain understudied in genetic studies of complex diseases. These populations have more complex linkage disequilibrium (LD) structure that can impair mapping of variants. Genotype imputation represents an approach to improve genome coverage, especially for rare or ancestry-specific variation; however, these understudied populations also have smaller relevant imputation reference panels. In this study, we leveraged >100,000 phased sequences generated from the multi-ethnic NHLBI TOPMed project for imputation in ~21,600 individuals of African ancestry (AAs) and ~21,700 Hispanics/Latinos. We demonstrated substantially higher imputation quality for low frequency and rare variants in comparison to the 1000 Genomes Project and Haplotype Reference Consortium reference panels. Analysis of quantitative hematological traits led to the discovery of associations with two rare variants in the HBB gene; one of these variants was replicated in an independent sample, and the other is known to cause anemia in the homozygous state. By comparison, the same HBB variants would not have been genome-wide significant using current reference panels due to lower imputation quality. Our findings demonstrate the power of TOPMed whole genome sequencing data for imputation and subsequent association analysis in admixed African and Hispanic/Latino populations.

2 June 2023 in Science
Verified
Journal Article
Closed access
BZBingxin Zhao
Bingxin Zhao
TLTengfei Li
Tengfei Li
ZFZirui Fan
Zirui Fan
YYYue Yang
Yue Yang
JSJuan Shu
Juan Shu
HZHongtu Zhu
Hongtu Zhu
Cardiovascular health interacts with cognitive and mental health in complex ways, yet little is known about the phenotypic and genetic links of heart-brain systems. We quantified heart-brain connections using multiorgan magnetic resonance imaging (MRI) data from more than 40,000 subjects. Heart MRI traits displayed numerous association patterns with brain gray matter morphometry, white matter microstructure, and functional networks. We identified 80 associated genomic loci ( P < 6.09 × 10 −10 ) for heart MRI traits, which shared genetic influences with cardiovascular and brain diseases. Genetic correlations were observed between heart MRI traits and brain-related traits and disorders. Mendelian randomization suggests that heart conditions may causally contribute to brain disorders. Our results advance a multiorgan perspective on human health by revealing heart-brain connections and shared genetic influences.

18 June 2021 in Science
Verified
Journal Article
Closed access
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BZBingxin Zhao
Bingxin Zhao
TLTengfei Li
Tengfei Li
YYYue Yang
Yue Yang
XWXifeng Wang
Xifeng Wang
TLTianyou Luo
Tianyou Luo
HZHongtu Zhu
Hongtu Zhu
Connecting the dots on white matter: The white matter of the brain, which is composed of axonal tracts connecting different brain regions, plays key roles in both normal brain function and a variety of neurological disorders. Zhao et al. combined detailed magnetic resonance imaging–based assessment of brain structures with genetic data on nearly 44,000 individuals (see the Perspective by Filley). On the basis of this comprehensive analysis, the authors identified structural and genetic abnormalities associated with neurological and psychiatric disorders, as well as some nondisease traits, thus creating a valuable resource and providing some insights into the underlying neurobiology. Science , abf3736, this issue p. eabf3736 ; see also abj1881, p. 1265

14 October 2020 in Nature
Verified
Journal Article
Closed access
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MSMichael Song
Michael Song
MPMark-Phillip Pebworth
Mark-Phillip Pebworth
XYXiaoyu Yang
Xiaoyu Yang
AAArmen Abnousi
Armen Abnousi
CFChangxu Fan
Changxu Fan
YSYin Shen
Yin Shen

1 November 2012 in The American Journal of Human Genetics
Verified
Journal Article
Closed access
PAPaul L. Auer
Paul L. Auer
JJJill M. Johnsen
Jill M. Johnsen
AJAndrew D. Johnson
Andrew D. Johnson
BLBenjamin A. Logsdon
Benjamin A. Logsdon
LLLeslie A. Lange
Leslie A. Lange
YLYun Li
Yun Li

28 April 2023 in Science
Verified
Journal Article
Closed access
PSPatrick F. Sullivan
Patrick F. Sullivan
JMJennifer R. S. Meadows
Jennifer R. S. Meadows
SGSteven Gazal
Steven Gazal
BPBaDoi N. Phan
BaDoi N. Phan
XLXue Li
Xue Li
XZXiaomeng Zhang
Xiaomeng Zhang
Thousands of genomic regions have been associated with heritable human diseases, but attempts to elucidate biological mechanisms are impeded by an inability to discern which genomic positions are functionally important. Evolutionary constraint is a powerful predictor of function, agnostic to cell type or disease mechanism. Single-base phyloP scores from 240 mammals identified 3.3% of the human genome as significantly constrained and likely functional. We compared phyloP scores to genome annotation, association studies, copy-number variation, clinical genetics findings, and cancer data. Constrained positions are enriched for variants that explain common disease heritability more than other functional annotations. Our results improve variant annotation but also highlight that the regulatory landscape of the human genome still needs to be further explored and linked to disease.