Yosuke Tanigawa

Yosuke Tanigawa

Research Scientist, investigating disease heterogeneity

Publications

You can also find my articles and recent preprints on my Google Scholar profile.

Select publications

Hypometric genetics: Improved power in genetic discovery by incorporating quality control flags

Published in The American Journal of Human Genetics, 2024

We introduce “hypometric genetics,” an approach to investigate the genetic basis of binarized traits representing the presence of below-the-limit-of-quantification (BLQ) quality control indicators. We show a joint analysis of BLQ and quantitative traits leads to improved power in genetic discovery, highlighting the value of considering population-based samples and phenotypic extremes in genetic studies


Reference: Tanigawa and Kellis. Hypometric genetics: Improved power in genetic discovery by incorporating quality control flags. The American Journal of Human Genetics. 111(11):2478-2493 (2024). https://doi.org/10.1016/j.ajhg.2024.09.008

Power of inclusion: Enhancing polygenic prediction with admixed individuals

Published in The American Journal of Human Genetics, 2023

We report a new method that improves genetic predictions by directly including admixed and ancestry-diverse individuals. The inclusive training strategy makes genetic prediction models more accurate for everyone, promoting health equity.


Reference: Tanigawa and Kellis. Power of inclusion: Enhancing polygenic prediction with admixed individuals. The American Journal of Human Genetics. 110, 1888-1902 (2023). https://doi.org/10.1016/j.ajhg.2023.09.013

Genetics of 35 blood and urine biomarkers in the UK Biobank

Published in Nature Genetics, 2021

We characterized the genetics of 35 biomarkers in UK Biobank. We performed the association and fine-mapping analysis to prioritize the causal variants, constructed the polygenic risk score (PRS) models, and evaluated their medical relevance with causal inference and PRS-PheWAS. We demonstrate a new approach, called multi-PRS, to improve PRS by combining PRSs across traits.


Reference: N. Sinnott-Armstrong*, Y. Tanigawa*, D. Amar, N. J. Mars, C. Benner, M. Aguirre, G. R. Venkataraman, M. Wainberg, H. M. Ollila, T. Kiiskinen, A. S. Havulinna, J. P. Pirruccello, J. Qian, A. Shcherbina, FinnGen, F. Rodriguez, T. L. Assimes, V. Agarwala, R. Tibshirani, T. Hastie, S. Ripatti, J. K. Pritchard, M. J. Daly, M. A. Rivas, Genetics of 35 blood and urine biomarkers in the UK Biobank. Nat Gen. 53(2), 185-194 (2021). https://doi.org/10.1038/s41588-020-00757-z (full text)

Rare protein-altering variants in ANGPTL7 lower intraocular pressure and protect against glaucoma

Published in PLOS Genetics, 2020

From the analysis of more than 500,000 individuals in population cohorts, we identified rare protein-altering variants in ANGPTL7 that reduce the risk of glaucoma. One of the alleles reported in the study (220C) is highly (50x +) enriched in the Finnish population, highlighting the power of the founder population with prior a bottlenecking event in genetic discovery. With the comprehensive health information in the two studied cohorts, we assess the potential impact of the rare variants on a spectrum of human disorders. We did not find any severe medical consequences. Our results indicate that ANGPTL7 is a safe and effective therapeutic target for glaucoma.
This paper was highlighted as Editors’ Choice in Science.


Reference: Y. Tanigawa, M. Wainberg, J. Karjalainen, T. Kiiskinen, G. Venkataraman, S. Lemmelä, J. A. Turunen, R. R. Graham, A. S. Havulinna, M. Perola, A. Palotie, FinnGen, M. J. Daly, M. A. Rivas, Rare protein-altering variants in ANGPTL7 lower intraocular pressure and protect against glaucoma. PLOS Genetics. 16, e1008682 (2020). https://doi.org/10.1371/journal.pgen.1008682

Components of genetic associations across 2,138 phenotypes in the UK Biobank highlight adipocyte biology

Published in Nature Communications, 2019

While many pleiotropic genetic loci have been identified, how they contribute to phenotypes across traits and diseases is unclear. Here, the authors propose a decomposition of genetic associations (DeGAs), which uses singular value decomposition to characterize the underlying latent structure of genetic associations of 2,138 phenotypes.


Reference: Y. Tanigawa*, J. Li*, J. M. Justesen, H. Horn, M. Aguirre, C. DeBoever, C. Chang, B. Narasimhan, K. Lage, T. Hastie, C. Y. Park, G. Bejerano, E. Ingelsson, M. A. Rivas, Components of genetic associations across 2,138 phenotypes in the UK Biobank highlight adipocyte biology. Nat Commun. 10, 4064 (2019). https://doi.org/10.1038/s41467-019-11953-9

Peer-reviewed publications

Hypometric genetics: Improved power in genetic discovery by incorporating quality control flags

Published in The American Journal of Human Genetics, 2024

We introduce “hypometric genetics,” an approach to investigate the genetic basis of binarized traits representing the presence of below-the-limit-of-quantification (BLQ) quality control indicators. We show a joint analysis of BLQ and quantitative traits leads to improved power in genetic discovery, highlighting the value of considering population-based samples and phenotypic extremes in genetic studies


Reference: Tanigawa and Kellis. Hypometric genetics: Improved power in genetic discovery by incorporating quality control flags. The American Journal of Human Genetics. 111(11):2478-2493 (2024). https://doi.org/10.1016/j.ajhg.2024.09.008

Power of inclusion: Enhancing polygenic prediction with admixed individuals

Published in The American Journal of Human Genetics, 2023

We report a new method that improves genetic predictions by directly including admixed and ancestry-diverse individuals. The inclusive training strategy makes genetic prediction models more accurate for everyone, promoting health equity.


Reference: Tanigawa and Kellis. Power of inclusion: Enhancing polygenic prediction with admixed individuals. The American Journal of Human Genetics. 110, 1888-1902 (2023). https://doi.org/10.1016/j.ajhg.2023.09.013

Human microglial state dynamics in Alzheimer’s disease progression

Published in Cell, 2023

Here we report 194,000 single-nucleus microglial transcriptomes and epigenomes across 443 human subjects and diverse Alzheimer’s disease pathological phenotypes.


Reference: N. Sun*, M. B. Victor*, Y. P. Park, X. Xiong, A. N. Scannail, N. Leary, S. Prosper, S. Viswanathan, X. Luna, C. A. Boix, B. T. James, Y. Tanigawa, K. Galani, H. Mathys, X. Jiang, A. P. Ng, D. A. Bennett, L.-H. Tsai, M. Kellis. Human microglial state dynamics in Alzheimer's disease progression. Cell 186(20), 4386-4403 (2023). https://doi.org/10.1016/j.cell.2023.08.037

Single-cell dissection of the obesity-exercise axis in adipose-muscle tissues implies a critical role for mesenchymal stem cells

Published in Cell Metab., 2022


Reference: J. Yang*, M. Vamvini*, P. Nigro*, L.-L. Ho, K. Galani, M. Alvarez, Y. Tanigawa, A. Renfro, N. P. Carbone, M. Laakso, L. Z. Agudelo, P. Pajukanta, M. F. Hirshman, R. J.W. Middelbeek, K. Grove, L. Goodyear, M. Kellis, Single-cell dissection of the obesity-exercise axis in adipose-muscle tissues implies a critical role for mesenchymal stem cells. Cell Metab. Cell Metab. 34(10),1578-1593.e6 (2022). https://doi.org/10.1016/j.cmet.2022.09.004

Deconvoluting complex correlates of COVID19 severity with a multi-omic pandemic tracking strategy

Published in Nat Commun., 2022


Reference: V. N. Parikh*, A. G. Ioannidis*, D. Jimenez-Morales, J. E. Gorzynski, H. N. D. Jong, X. Liu, J. Roque, V. P. Cepeda-Espinoza, K. Osoegawa, C. Hughes, S. C. Sutton, N. Youlton, R. Joshi, D. Amar, Y. Tanigawa, D. Russo, J. Wong, J. T. Lauzon, J. Edelson, D. M. Montserrat, Y. Kwon, S. Rubinacci, O. Delaneau, L. Cappello, J. Kim, M. J. Shoura, A. N. Raja, N. Watson, N. Hammond, E. Spiteri, K. C. Mallempati, G. Montero-Martin, J. Christle, J. Kim, A. Kirillova, K. Seo, Y. Huang, C. Zhao, S. Moreno-Grau, S. Hershman, K. P. Dalton, J. Zhen, J. Kamm, K. Bhatt, A. Isakova, M. Morri, T. Ranganath, C. A. Blish, A. J. Rogers, K. Nadeau, S. Yang, A. Blomkalns, R. O’Hara, N. F. Neff, C. DeBoever, S. Szalma, M. T. Wheeler, C. Gates, K. Farh, G. P. Schroth, P. Febbo, F. deSouza, O. Cornejo, M. Fernandez-Vina, A. Kistler, J. Palacios, B. A. Pinsky, C. D. Bustamante, M. A. Rivas, E. A. Ashley, Deconvoluting complex correlates of COVID19 severity with a multi-omic pandemic tracking strategy. Nat Commun. 13, 5107 (2022). https://doi.org/10.1038/s41467-022-32397-8

Large-scale multivariate sparse regression with applications to UK Biobank

Published in Ann. Appl. Stat., 2022

In this study led by Junyang Qian, we present a method to fit sparse multi-variate and multi-response regression model. When demonstrate the application to the UK Biobank biomarker traits, where we investigated the latent structure of regression coefficients using biplot representation.


Reference: J. Qian, Y. Tanigawa, R. Li, R. Tibshirani, M. A. Rivas, T. Hastie, Large-Scale Sparse Regression for Multiple Responses with Applications to UK Biobank. Ann. Appl. Stat. 16(3), 1891-1918 (2022). https://doi.org/10.1214/21-AOAS1575

Integration of rare expression outlier-associated variants improves polygenic risk prediction

Published in The American Journal of Human Genetics, 2022

Polygenic risk score (PRS), an approach to estimate genetic liability to complex traits by aggregating the effects across multiple genetic variants, has attracted increasing research interest. However, most existing PRSs focused on common variants, despite the well-established roles of specific rare genetic variants in common complex traits and diseases. To address this, we propose the independent outlier gene count (IOGC) score, an approach to aggregate the effects of rare variants that show expression outliers in a population-scale transcriptome sequencing study. We demonstrate that the high burden of the rare expression outlier variants on complex traits and the IOGC score improves polygenic prediction.


Reference: C. Smail, N. M. Ferraro, Q. Hui, M. G. Durrant, M. Aguirre, Y. Tanigawa, M. R. Keever-Keigher, A. S. Rao, J. M. Justesen, X. Li, M. J. Gloudemans, T. L. Assimes, C. Kooperberg, A. P. Reiner, J. Huang, C. J. O'Donnell, Y. V. Sun, Million Veteran Program, M. A. Rivas, S. B. Montgomery, Integration of rare expression outlier-associated variants improves polygenic risk prediction. Am J Hum Genet. 109(6), 1055-1064 (2022). https://doi.org/10.1016/j.ajhg.2022.04.015

Significant Sparse Polygenic Risk Scores across 813 traits in UK Biobank

Published in PLOS Genetics, 2022

We performed a systematic assessment of the predictive performance of PRS models across >1,500 traits in UK Biobank and report 813 PRS models with significant predictive performance.


Reference: Y. Tanigawa, J. Qian, G. R. Venkataraman, J. M. Justesen, R. Li, R. Tibshirani, T. Hastie, M. A. Rivas, Significant Sparse Polygenic Risk Scores across 813 traits in UK Biobank. PLOS Genet. 18(3), e1010105 (2022). https://doi.org/10.1371/journal.pgen.1010105

A cross-population atlas of genetic associations for 220 human phenotypes

Published in Nature Genetics, 2021

Using a set of GWAS summary statistics of diseases characterized from both European (UK Biobank and FinnGen) and East Asian (Biobank Japan) populations, we dissected latent DeGAs components of multi-ethnic association summary statistics. We annotated each component by pathway and cell-type enrichment as well as projection of metabolomic and biomarker summary statistics. We demonstrate how can we use such trans-ethnic annotated latent components to classify diseases based on their genetic basis.


Reference: S. Sakaue*, M. Kanai*, Y. Tanigawa, J. Karjalainen, M. Kurki, S. Koshiba, A. Narita, T. Konuma, K. Yamamoto, M. Akiyama, K. Ishigaki, A. Suzuki, K. Suzuki, W. Obara, K. Yamaji, K. Takahashi, S. Asai, Y. Takahashi, T. Suzuki, N. Sinozaki, H. Yamaguchi, S. Minami, S. Murayama, K. Yoshimori, S. Nagayama, D. Obata, M. Higashiyama, A. Masumoto, Y. Koretsune, F. Gen, K. Ito, C. Terao, T. Yamauchi, I. Komuro, T. Kadowaki, G. Tamiya, M. Yamamoto, Y. Nakamura, M. Kubo, Y. Murakami, K. Yamamoto, Y. Kamatani, A. Palotie, M. A. Rivas, M. Daly, K. Matsuda, Y. Okada, A cross-population atlas of genetic associations for 220 human phenotypes. Nat Gen. 53(10), 1415-1424 (2021). https://doi.org/10.1038/s41588-021-00931-x (full text)

APOC3 genetic variation, serum triglycerides, and risk of coronary artery disease in Asian Indians, Europeans, and other ethnic groups

Published in Lipids in Health and Disease, 2021

We examined the causal relationship between the genetically increased triglycerides and the risk of coronary artery diseases in Asian Indians.


Reference: S. Goyal, Y. Tanigawa, W. Zhang, J. Chai, M. Almeida, X. Sim, M. Lerner, J. Chainakul, J. G. Ramiu, C. Seraphin, B. Apple, A. Vaughan, J. Muniu, J. Peralta, D. M. Lehman, S. Ralhan, G. S. Wander, J. R. Singh, N. K. Mehra, E. Sidorov, M. D Peyton, P. R. Blackett, J. E. Curran, E. S. Tai, R. van Dam, C. Cheng, R. Duggirala, J. Blangero, J. C. Chambers, C. Sabanayagam, J. S. Kooner, M. A. Rivas, C. E. Aston, D. Sanghera, APOC3 genetic variation, serum triglycerides, and risk of coronary artery disease in Asian Indians, Europeans, and other ethnic groups. Lipids Health Dis (2021). https://doi.org/10.1186/s12944-021-01531-8

Fast Numerical Optimization for Genome Sequencing Data in Population Biobanks

Published in Bioinformatics, 2021

In this paper led by Ruilin Li, we describe memory-efficient implementation of snpnet (sparse-snpnet and snpnet-v2).


Reference: R. Li, C. Chang, Y. Tanigawa, B. Narasimhan, T. Hastie, R. Tibshirani, M. A. Rivas, Fast Numerical Optimization for Genome Sequencing Data in Population Biobanks. Bioinformatics 37(22), 4148-4155 (2021). https://doi.org/10.1093/bioinformatics/btab452 (full text)

[Review in Japanese] 複数の表現型を用いた人類遺伝統計学の大規模情報解析 (Large-scale human genetic statistical inference with multiple phenotypes)

Published in JSBi Bioinformatics Review, 2021

[invited review written in Japanese] 日本語総説の執筆の機会をいただき、ゲノムワイド相関解析（GWAS）、ポリジェニック・リスク・スコア（polygenic risk score）、高次元データセットでの正則化つきの回帰モデル（penalized regression、Lasso 回帰など）に関する人類統計遺伝学の解析手法について執筆しました。

Reference: Y. Tanigawa, Large-scale human genetic statistical inference with multiple phenotypes. JSBi Bioinformatics Review, 1(2), 47-59 (2021). https://doi.org/10.11234/jsbibr.2021.4

Survival Analysis on Rare Events Using Group-Regularized Multi-Response Cox Regression

Published in Bioinformatics, 2021

In this paper led by Ruilin Li, we describe a new method to fit a sparse Cox Model for multiple time-to-event phenotypes from a large-scale (> 1 million features) genetic dataset.


Reference: R. Li, Y. Tanigawa, J. M. Justesen, J. Taylor, T. Hastie, R. Tibshirani, M. A. Rivas, Survival Analysis on Rare Events Using Group-Regularized Multi-Response Cox Regression. Bioinformatics 37(23), 4437-4443 (2021). https://doi.org/10.1093/bioinformatics/btab095

Polygenic risk modeling with latent trait-related genetic components

Published in European Journal of Human Genetics, 2021

Polygenic risk score (PRS) has been proposed for disease risk prediction with potential clinical relevance for some traits, but its personalized interpretation is generally difficult, especially when there exist disease subtypes driven by different genetic components. In this study led by Matthew Aguirre, we introduce dPRS (DeGAs-PRS) as an extension of Decomposition of Genetic Associations (DeGAs) to decompose the polygenic risk of individuals into latent components of genetic associations characterized from hundreds of thousands of traits.


Reference: M. Aguirre, Y. Tanigawa, G. R. Venkataraman, R. Tibshirani, T. Hastie, M. A. Rivas, Polygenic risk modeling with latent trait-related genetic components. Eur J Hum Genet. 29(7), 1071-1081 (2021). https://doi.org/10.1038/s41431-021-00813-0 (full text)

Genetics of 35 blood and urine biomarkers in the UK Biobank

Published in Nature Genetics, 2021

We characterized the genetics of 35 biomarkers in UK Biobank. We performed the association and fine-mapping analysis to prioritize the causal variants, constructed the polygenic risk score (PRS) models, and evaluated their medical relevance with causal inference and PRS-PheWAS. We demonstrate a new approach, called multi-PRS, to improve PRS by combining PRSs across traits.


Reference: N. Sinnott-Armstrong*, Y. Tanigawa*, D. Amar, N. J. Mars, C. Benner, M. Aguirre, G. R. Venkataraman, M. Wainberg, H. M. Ollila, T. Kiiskinen, A. S. Havulinna, J. P. Pirruccello, J. Qian, A. Shcherbina, FinnGen, F. Rodriguez, T. L. Assimes, V. Agarwala, R. Tibshirani, T. Hastie, S. Ripatti, J. K. Pritchard, M. J. Daly, M. A. Rivas, Genetics of 35 blood and urine biomarkers in the UK Biobank. Nat Gen. 53(2), 185-194 (2021). https://doi.org/10.1038/s41588-020-00757-z (full text)

Cardiac Imaging of Aortic Valve Area From 34287 UK Biobank Participants Reveals Novel Genetic Associations and Shared Genetic Comorbidity With Multiple Disease Phenotypes

Published in Circ Genom Precis Med., 2020


Reference: A. Cordova-Palomera, C. Tcheandjieu, J. Fries, P. Varma, V. Chen, M. Fiterau, K. Xiao, H. Tejeda, B. Keavney, H. Cordell, Y. Tanigawa, G. Venkataraman, M. Rivas, C. Re, E. Ashley, J. R. Priest, Cardiac Imaging of Aortic Valve Area from 34,287 UK Biobank Participants Reveal Novel Genetic Associations and Shared Genetic Comorbidity with Multiple Disease Phenotypes. Circ Genom Precis Med. 13(6):e003014, (2020). https://doi.org/10.1161/CIRCGEN.120.003014

A fast and scalable framework for large-scale and ultrahigh-dimensional sparse regression with application to the UK Biobank

Published in PLOS Genetics, 2020

In this project led by Junyang Qian, we developed BASIL, a novel algorithm to fit large-scale L1 penalized (Lasso) regression model using an iterative procedure, and implemented R snpnet package specially designed for genetic data. We demonstrate the ability of this approach in an application to UK Biobank dataset.


Reference: J. Qian, Y. Tanigawa, W. Du, M. Aguirre, C. Chang, R. Tibshirani, M. A. Rivas, T. Hastie, A fast and scalable framework for large-scale and ultrahigh-dimensional sparse regression with application to the UK Biobank. PLoS Genet. 16, e1009141 (2020). https://doi.org/10.1371/journal.pgen.1009141

Fast Lasso method for large-scale and ultrahigh-dimensional Cox model with applications to UK Biobank

Published in Biostatistics, 2020

We propose extending the BASIL/snpnet algorithm to fit the L1 penalized Cox proportional hazards model using a large-scale dataset from a genotyped cohort. We present its application to 300+ time-to-event traits in UK Biobank.


Reference: R. Li, C. Chang, J. M. Justesen, Y. Tanigawa, J. Qiang, T. Hastie, M. A. Rivas, R. Tibshirani, Fast Lasso method for large-scale and ultrahigh-dimensional Cox model with applications to UK Biobank. Biostatistics. 23(2), 522-540 (2020). https://doi.org/doi:10.1093/biostatistics/kxaa038

Sex-specific genetic effects across biomarkers

Published in European Journal of Human Genetics, 2020

In this study led by Emily Flynn, we discovered a surprising sex-specificity in the genetics of testosterone. Yosuke performed the polygenic risk score (PRS) analysis and demonstrated that PRS models trained for each sex improve predictive accuracy.


Reference: E. Flynn, Y. Tanigawa, F. Rodriguez, R. B. Altman, N. Sinnott-Armstrong, M. A. Rivas, Sex-specific genetic effects across biomarkers. Eur J Hum Genet, 29(1), 154-163 (2021). https://doi.org/10.1038/s41431-020-00712-w (full text)

Assessing Digital Phenotyping to Enhance Genetic Studies of Human Diseases

Published in The American Journal of Human Genetics, 2020

Large-scale population-based genotyped biobanks with dense phenotypic information provide opportunities for genetic analysis at scale. However, the heterogeneous phenotypic data sources in such biobanks present challenges in disease case assertation. Here, we evaluated the consistencies of genetic associations identified from hospital records, questionnaire responses, and family history of diseases using genetic parameters, such as genetic correlation. We also showed the utility of combining the unstructured and heterogeneous data sources to improve the power of genetic analysis.


Reference: C. DeBoever, Y. Tanigawa, M. Aguirre, G. McInnes, A. Lavertu, M. A. Rivas, Assessing Digital Phenotyping to Enhance Genetic Studies of Human Diseases. Am J Hum Genet. 106(5), 611-622 (2020). https://doi.org/10.1016/j.ajhg.2020.03.007

Rare protein-altering variants in ANGPTL7 lower intraocular pressure and protect against glaucoma

Published in PLOS Genetics, 2020

From the analysis of more than 500,000 individuals in population cohorts, we identified rare protein-altering variants in ANGPTL7 that reduce the risk of glaucoma. One of the alleles reported in the study (220C) is highly (50x +) enriched in the Finnish population, highlighting the power of the founder population with prior a bottlenecking event in genetic discovery. With the comprehensive health information in the two studied cohorts, we assess the potential impact of the rare variants on a spectrum of human disorders. We did not find any severe medical consequences. Our results indicate that ANGPTL7 is a safe and effective therapeutic target for glaucoma.
This paper was highlighted as Editors’ Choice in Science.


Reference: Y. Tanigawa, M. Wainberg, J. Karjalainen, T. Kiiskinen, G. Venkataraman, S. Lemmelä, J. A. Turunen, R. R. Graham, A. S. Havulinna, M. Perola, A. Palotie, FinnGen, M. J. Daly, M. A. Rivas, Rare protein-altering variants in ANGPTL7 lower intraocular pressure and protect against glaucoma. PLOS Genetics. 16, e1008682 (2020). https://doi.org/10.1371/journal.pgen.1008682

Components of genetic associations across 2,138 phenotypes in the UK Biobank highlight adipocyte biology

Published in Nature Communications, 2019

While many pleiotropic genetic loci have been identified, how they contribute to phenotypes across traits and diseases is unclear. Here, the authors propose a decomposition of genetic associations (DeGAs), which uses singular value decomposition to characterize the underlying latent structure of genetic associations of 2,138 phenotypes.


Reference: Y. Tanigawa*, J. Li*, J. M. Justesen, H. Horn, M. Aguirre, C. DeBoever, C. Chang, B. Narasimhan, K. Lage, T. Hastie, C. Y. Park, G. Bejerano, E. Ingelsson, M. A. Rivas, Components of genetic associations across 2,138 phenotypes in the UK Biobank highlight adipocyte biology. Nat Commun. 10, 4064 (2019). https://doi.org/10.1038/s41467-019-11953-9

Significant shared heritability underlies suicide attempt and clinically predicted probability of attempting suicide

Published in Molecular Psychiatry, 2019

Using two independent datasets from genotyped cohorts (UK Biobank and electronic medical record (EMR) in Vanderbilt University Medical Center), we quantified the heritability estimates of suicide attempts. We also showed the shared genetic basis of suicide attempts and other phenotypes.


Reference: D. M. Ruderfer, C. G. Walsh, M. W. Aguirre, Y. Tanigawa, J. D. Ribeiro, J. C. Franklin, M. A. Rivas, Significant shared heritability underlies suicide attempt and clinically predicted probability of attempting suicide. Mol Psychiatry. 25(10), 2422-2430 (2020). https://doi.org/10.1038/s41380-018-0326-8

Global Biobank Engine: enabling genotype-phenotype browsing for biobank summary statistics

Published in Bioinformatics, 2018

We present Global Biobank Engine as a platform to visualize genome- and phenome-wide associations and perform statistical inference using those association data.


Reference: G. McInnes, Y. Tanigawa, C. DeBoever, A. Lavertu, J. E. Olivieri, M. Aguirre, M. A. Rivas, Global Biobank Engine: enabling genotype-phenotype browsing for biobank summary statistics. Bioinformatics 35(14), 2495-2497 (2019). https://doi.org/10.1093/bioinformatics/bty999

SNPs2ChIP: Latent Factors of ChIP-seq to infer functions of non-coding SNPs

Published in Pacific Symposium on Biocomputing, 2018

We propose SNPs2ChIP, a method to infer biological functions of non-coding variants through unsupervised statistical learning methods applied to publicly-available epigenetic datasets.

Reference: S. Anand, L. Kalesinskas, C. Smail, Y. Tanigawa, SNPs2ChIP: Latent Factors of ChIP-seq to infer functions of non-coding SNPs. Pac Symp Biocomput. 2019, 24: 184-195 (WORLD SCIENTIFIC, 2018). https://doi.org/10.1142/9789813279827_0017

Medical relevance of protein-truncating variants across 337,205 individuals in the UK Biobank study

Published in Nature Communications, 2018

Using the UK Biobank population cohort, we investigated the genetic effects of Protein-truncating variants (PTVs) and the clinical impacts.


Reference: C. DeBoever, Y. Tanigawa, M. E. Lindholm, G. McInnes, A. Lavertu, E. Ingelsson, C. Chang, E. A. Ashley, C. D. Bustamante, M. J. Daly, M. A. Rivas, Medical relevance of protein-truncating variants across 337,205 individuals in the UK Biobank study. Nat Commun. 9, 1612 (2018). https://doi.org/10.1038/s41467-018-03910-9

Collaborative environmental DNA sampling from petal surfaces of flowering cherry Cerasus × yedoensis ‘Somei-yoshino’ across the Japanese archipelago

Published in Journal of Plant Research, 2018

Cerasus × yedoensis ‘Somei-yoshino’ is Japan’s most commonly cultivated cherry blossoms tree. Thanks to widespread grafting, it blooms synchronously in the same climate condition, which is suitable for the subject of ‘Ohanami,’ flower viewing parties in Japan. Despite the host genetics’ homogeneity, the composition of environmental DNA (eDNA) on the petal surface was unclear. As a pilot project, we performed community-based eDNA profiling across 577 eDNA samples and 149 collaborators. A preliminary analysis identified the DNA of common plant species, including the one that likely originated from the pollen of the Japanese cedar. Our results highlight the value of crowdsourced eDNA sampling and analyses in ecological studies.


Reference: T. Ohta, T. Kawashima, N. O. Shinozaki, A. Dobashi, S. Hiraoka, T. Hoshino, K. Kanno, T. Kataoka, S. Kawashima, M. Matsui, W. Nemoto, S. Nishijima, N. Suganuma, H. Suzuki, Y. Taguchi, Y. Takenaka, Y. Tanigawa, M. Tsuneyoshi, K. Yoshitake, Y. Sato, R. Yamashita, K. Arakawa, W. Iwasaki, Collaborative environmental DNA sampling from petal surfaces of flowering cherry Cerasus × yedoensis ‘Somei-yoshino’ across the Japanese archipelago. J Plant Res. 131, 709-717 (2018). https://doi.org/10.1007/s10265-018-1017-x

Preprints

Preprints are provided for rapid sharing of the data, results, and knowledge among the scientific community and have not finished the peer-review process. We welcome comments and feedback you may have.

[Preprint] Genetics of cardiometabolic disease progression.

Preprint posted on medRxiv, 2025

In this study led by Johanne M. Justesen in the Rivas lab, we investigate the genetic basis of cardiometabolic disease progression, ascertained by the time from the initial diagnosis to time to complication/comorbidity diagnosed or procedure in the UK Biobank.


Reference: J. M. Justesen, G. R. Venkataraman, Y. Tanigawa, R. Li, T. Hastie, R. Tibshirani, J. W. Knowles, M. A. Rivas., Genetics of cardiometabolic disease progression. medRxiv, 2025.02.01.25321518 (2025). https://doi.org/10.1101/2025.02.01.25321518

[Preprint] LPA and APOE are associated with statin selection in the UK Biobank

Preprint posted on bioRxiv, 2020

Statin is a commonly used drug for high cholesterol. Physicians adjust the type and dose of statin based on the observed response to the treatment. To investigate the role of genetics, we performed genome-wide association scan to identify genetic variants associated with statin selection. When we investigated the identified variants in LPA and APOE, we found that the carriers of those variants more likely to be on a higher dose of statin.


Reference: A. Lavertu*, G. M. McInnes*, Y. Tanigawa, R. B. Altman, M. A. Rivas, LPA and APOE are associated with statin selection in the UK Biobank. bioRxiv, 2020.08.28.272765 (2020). https://doi.org/10.1101/2020.08.28.272765

[Preprint] High-throughput SARS-CoV-2 and host genome sequencing from single nasopharyngeal swabs

Preprint posted on medRxiv, 2020

In this pre-print, we describe a new method to generate host and pathogen genomic data.


Reference: J. E. Gorzynski*, H. N. D. Jong*, D. Amar, C. R. Hughes, A. Ioannidis, R. Bierman, D. Liu, Y. Tanigawa, A. Kistler, J. Kamm, J. Kim, L. Cappello, N. F. Neff, S. Rubinacci, O. Delaneua, M. J. Shoura, K. Seo, A. Kirillova, A. Raja, S. Sutton, C. Huang, M. K. Sahoo, K. C. Mallempati, G. Montero-Martin, K. Osoegawa, N. Watson, N. Hammond, R. Joshi, M. Fernandez-Vina, J. W. Christle, M. T. Wheeler, P. Febbo, K. Farh, G. Schroth, F. Desouza, J. Palacios, J. Salzman, B. A. Pinsky, M. A. Rivas, C. D. Bustamante, E. A. Ashley, V. N. Parikh, High-throughput SARS-CoV-2 and host genome sequencing from single nasopharyngeal swabs, medRxiv, 2020.07.27.20163147 (2020). https://doi.org/10.1101/2020.07.27.20163147

[Preprint] Pervasive additive and non-additive effects within the HLA region contribute to disease risk in the UK Biobank

Preprint posted on bioRxiv, 2020

We characterized the genetic associations between HLA allelotypes and comprehensive human disease phenotypes in UK Biobank.


Reference: G. R. Venkataraman, J. E. Olivieri, C. DeBoever, Y. Tanigawa, J. M. Justesen, M. A. Rivas, Pervasive additive and non-additive effects within the HLA region contribute to disease risk in the UK Biobank. bioRxiv, 2020.05.28.119669 (2020). https://doi.org/10.1101/2020.05.28.119669

[Preprint] Medical relevance of common protein-altering variants in GPCR genes across 337,205 individuals in the UK Biobank study

Preprint posted on bioRxiv, 2019


Reference: C. DeBoever, A. J. Venkatakrishnan, J. M. Paggi, F. M. Heydenreich, S.-A. Laurin, M. Masureel, Y. Tanigawa, G. Venkataraman, M. Bouvier, R. Dror, M. A. Rivas, Medical relevance of common protein-altering variants in GPCR genes across 337,205 individuals in the UK Biobank study. bioRxiv, 2019.12.13.876250 (2019). https://doi.org/10.1101/2019.12.13.876250

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