Erik Ehli

Dr. Erik Ehli

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Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

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

Representative Publications

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23 November 2017 in Nature Communications
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Journal Article
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PZPeng Zhang
Peng Zhang
DHDandan He
Dandan He
YXYi Xu
Yi Xu
JHJiakai Hou
Jiakai Hou
BPBih-Fang Pan
Bih-Fang Pan
YCYiwen Chen
Yiwen Chen
Translation is principally regulated at the initiation stage. The development of the translation initiation (TI) sequencing (TI-seq) technique has enabled the global mapping of TIs and revealed unanticipated complex translational landscapes in metazoans. Despite the wide adoption of TI-seq, there is no computational tool currently available for analyzing TI-seq data. To fill this gap, we develop a comprehensive toolkit named Ribo-TISH, which allows for detecting and quantitatively comparing TIs across conditions from TI-seq data. Ribo-TISH can also predict novel open reading frames (ORFs) from regular ribosome profiling (rRibo-seq) data and outperform several established methods in both computational efficiency and prediction accuracy. Applied to published TI-seq/rRibo-seq data sets, Ribo-TISH uncovers a novel signature of elevated mitochondrial translation during amino-acid deprivation and predicts novel ORFs in 5′UTRs, long noncoding RNAs, and introns. These successful applications demonstrate the power of Ribo-TISH in extracting biological insights from TI-seq/rRibo-seq data.

22 August 2018 in Science Translational Medicine
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RCRaymond J. Cho
Raymond J. Cho
LALudmil B. Alexandrov
Ludmil B. Alexandrov
NBNicoline Y. Den Breems
Nicoline Y. Den Breems
VAVelina S. Atanasova
Velina S. Atanasova
MFMehdi Farshchian
Mehdi Farshchian
ASAndrew P. South
Andrew P. South
Early-onset squamous cell carcinoma in recessive dystrophic epidermolysis bullosa patients is characterized by APOBEC mutagenesis.

20 July 2021 in Human Genomics
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JSJohn Leslie Slunecka
John Leslie Slunecka
MZMatthijs D. van der Zee
Matthijs D. van der Zee
JBJeffrey John Beck
Jeffrey John Beck
BJBrandon N. Johnson
Brandon N. Johnson
CFCasey Finnicum
Casey Finnicum
EEErik Ehli
Erik Ehli
Increasing amounts of genetic data have led to the development of polygenic risk scores (PRSs) for a variety of diseases. These scores, built from the summary statistics of genome-wide association studies (GWASs), are able to stratify individuals based on their genetic risk of developing various common diseases and could potentially be used to optimize the use of screening and preventative treatments and improve personalized care for patients. Many challenges are yet to be overcome, including PRS validation, healthcare professional and patient education, and healthcare systems integration. Ethical challenges are also present in how this information is used and the current lack of diverse populations with PRSs available. In this review, we discuss the topics above and cover the nature of PRSs, visualization schemes, and how PRSs can be improved. With these tools on the horizon for multiple diseases, scientists, clinicians, health systems, regulatory bodies, and the public should discuss the uses, benefits, and potential risks of PRSs.

30 July 2021 in Translational Psychiatry
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Journal Article
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HIHill F. Ip
Hill F. Ip
CLCamiel M. van der Laan
Camiel M. van der Laan
EKEva M. L. Krapohl
Eva M. L. Krapohl
IBIsabell Brikell
Isabell Brikell
CSCristina Sánchez-Mora
Cristina Sánchez-Mora
DBDorret Irene Boomsma
Dorret Irene Boomsma
Childhood aggressive behavior (AGG) has a substantial heritability of around 50%. Here we present a genome-wide association meta-analysis (GWAMA) of childhood AGG, in which all phenotype measures across childhood ages from multiple assessors were included. We analyzed phenotype assessments for a total of 328 935 observations from 87 485 children aged between 1.5 and 18 years, while accounting for sample overlap. We also meta-analyzed within subsets of the data, i.e., within rater, instrument and age. SNP-heritability for the overall meta-analysis (AGGoverall) was 3.31% (SE = 0.0038). We found no genome-wide significant SNPs for AGGoverall. The gene-based analysis returned three significant genes: ST3GAL3 (P = 1.6E–06), PCDH7 (P = 2.0E–06), and IPO13 (P = 2.5E–06). All three genes have previously been associated with educational traits. Polygenic scores based on our GWAMA significantly predicted aggression in a holdout sample of children (variance explained = 0.44%) and in retrospectively assessed childhood aggression (variance explained = 0.20%). Genetic correlations (rg) among rater-specific assessment of AGG ranged from rg = 0.46 between self- and teacher-assessment to rg = 0.81 between mother- and teacher-assessment. We obtained moderate-to-strong rgs with selected phenotypes from multiple domains, but hardly with any of the classical biomarkers thought to be associated with AGG. Significant genetic correlations were observed with most psychiatric and psychological traits (range $$\left| {r_g} \right|$$ r g : 0.19–1.00), except for obsessive-compulsive disorder. Aggression had a negative genetic correlation (rg = ~−0.5) with cognitive traits and age at first birth. Aggression was strongly genetically correlated with smoking phenotypes (range $$\left| {r_g} \right|$$ r g : 0.46–0.60). The genetic correlations between aggression and psychiatric disorders were weaker for teacher-reported AGG than for mother- and self-reported AGG. The current GWAMA of childhood aggression provides a powerful tool to interrogate the rater-specific genetic etiology of AGG.

26 July 2019 in Blood
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ABAustin L. Brown
Austin L. Brown
ASAdam J. de Smith
Adam J. de Smith
VGVincent U. Gant
Vincent U. Gant
WYWenjian Yang
Wenjian Yang
MSMichael Scheurer
Michael Scheurer
KRKaren R. Rabin
Karen R. Rabin
The authors report the interaction between Down syndrome, a major genetic leukemia predisposition condition, and inherited genetic alleles associated with increased susceptibility to childhood acute lymphoblastic leukemia.

31 March 2022 in Journal of the American Academy of Child & Adolescent Psychiatry
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Journal Article
Open access
EJEshim S. Jami
Eshim S. Jami
AHAnke Hammerschlag
Anke Hammerschlag
HIHill F. Ip
Hill F. Ip
AAAndrea G. Allegrini
Andrea G. Allegrini
BBBeben Benyamin
Beben Benyamin
CMChristel M. Middeldorp
Christel M. Middeldorp
To investigate the genetic architecture of internalizing symptoms in childhood and adolescence. In 22 cohorts, multiple univariate genome-wide association studies (GWASs) were performed using repeated assessments of internalizing symptoms, in a total of 64,561 children and adolescents between 3 and 18 years of age. Results were aggregated in meta-analyses that accounted for sample overlap, first using all available data, and then using subsets of measurements grouped by rater, age, and instrument. The meta-analysis of overall internalizing symptoms (INToverall) detected no genome-wide significant hits and showed low single nucleotide polymorphism (SNP) heritability (1.66%, 95% CI = 0.84-2.48%, neffective = 132,260). Stratified analyses indicated rater-based heterogeneity in genetic effects, with self-reported internalizing symptoms showing the highest heritability (5.63%, 95% CI = 3.08%-8.18%). The contribution of additive genetic effects on internalizing symptoms appeared to be stable over age, with overlapping estimates of SNP heritability from early childhood to adolescence. Genetic correlations were observed with adult anxiety, depression, and the well-being spectrum (|rg| > 0.70), as well as with insomnia, loneliness, attention-deficit/hyperactivity disorder, autism, and childhood aggression (range |rg| = 0.42-0.60), whereas there were no robust associations with schizophrenia, bipolar disorder, obsessive-compulsive disorder, or anorexia nervosa. Genetic correlations indicate that childhood and adolescent internalizing symptoms share substantial genetic vulnerabilities with adult internalizing disorders and other childhood psychiatric traits, which could partially explain both the persistence of internalizing symptoms over time and the high comorbidity among childhood psychiatric traits. Reducing phenotypic heterogeneity in childhood samples will be key in paving the way to future GWAS success.