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1. Unravelling the complex causal effects of substance use behaviours on common diseases

Author

Angli Xue, Zhihong Zhu, Huanwei Wang, Longda Jiang, Peter M. Visscher, Jian Zeng, and Jian Yang

Subjects
Medicine
Abstract

Abstract Background Substance use behaviours (SUB) including smoking, alcohol consumption, and coffee intake are associated with many health outcomes. However, whether the health effects of SUB are causal remains controversial, especially for alcohol consumption and coffee intake. Methods In this study, we assess 11 commonly used Mendelian Randomization (MR) methods by simulation and apply them to investigate the causal relationship between 7 SUB traits and health outcomes. We also combine stratified regression, genetic correlation, and MR analyses to investigate the dosage-dependent effects. Results We show that smoking initiation has widespread risk effects on common diseases such as asthma, type 2 diabetes, and peripheral vascular disease. Alcohol consumption shows risk effects specifically on cardiovascular diseases, dyslipidemia, and hypertensive diseases. We find evidence of dosage-dependent effects of coffee and tea intake on common diseases (e.g., cardiovascular disease and osteoarthritis). We observe that the minor allele effect of rs4410790 (the top signal for tea intake level) is negative on heavy tea intake $$({\hat{b}}_{GWAS}=-0.091,s.e.=0.007,P=4.90\times {10}^{-35})$$ ( b ̂ G W A S = − 0.091 , s . e . = 0.007 , P = 4.90 × 10 − 35 ) but positive on moderate tea intake $$({\hat{b}}_{GWAS}=0.034,s.e.=0.006,P=3.40\times {10}^{-8})$$ ( b ̂ G W A S = 0.034 , s . e . = 0.006 , P = 3.40 × 10 − 8 ) , compared to the non-tea-drinkers. Conclusion Our study reveals the complexity of the health effects of SUB and informs design for future studies aiming to dissect the causal relationships between behavioural traits and complex diseases.

Published
2024
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2. Sequencing of 19,219 exomes identifies a low-frequency variant in FKBP5 promoter predisposing to high myopia in a Han Chinese population

Author

Jianzhong Su, Jian Yuan, Liangde Xu, Shilai Xing, Mengru Sun, Yinghao Yao, Yunlong Ma, Fukun Chen, Longda Jiang, Kai Li, Xiangyi Yu, Zhengbo Xue, Yaru Zhang, Dandan Fan, Ji Zhang, Hui Liu, Xinting Liu, Guosi Zhang, Hong Wang, Meng Zhou, Fan Lyu, Gang An, Xiaoguang Yu, Yuanchao Xue, Jian Yang, and Jia Qu

Subjects
CP: Genomics, Biology (General), QH301-705.5
Abstract

Summary: High myopia (HM) is one of the leading causes of visual impairment and blindness worldwide. Here, we report a whole-exome sequencing (WES) study in 9,613 HM cases and 9,606 controls of Han Chinese ancestry to pinpoint HM-associated risk variants. Single-variant association analysis identified three newly identified -genetic loci associated with HM, including an East Asian ancestry-specific low-frequency variant (rs533280354) in FKBP5. Multi-ancestry meta-analysis with WES data of 2,696 HM cases and 7,186 controls of European ancestry from the UK Biobank discerned a newly identified European ancestry-specific rare variant in FOLH1. Functional experiments revealed a mechanism whereby a single G-to-A transition at rs533280354 disrupted the binding of transcription activator KLF15 to the promoter of FKBP5, resulting in decreased transcription of FKBP5. Furthermore, burden tests showed a significant excess of rare protein-truncating variants among HM cases involved in retinal blood vessel morphogenesis and neurotransmitter transport.

Published
2023
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3. Circulating vitamin C concentration and risk of cancers: a Mendelian randomization study

Author

Yuanqing Fu, Fengzhe Xu, Longda Jiang, Zelei Miao, Xinxiu Liang, Jian Yang, Susanna C. Larsson, and Ju-Sheng Zheng

Subjects
Circulating vitamin C, Site-specific cancers, Mendelian randomization analysis, Medicine
Abstract

Abstract Background Circulating vitamin C concentrations have been associated with several cancers in observational studies, but little is known about the causal direction of the associations. This study aims to explore the potential causal relationship between circulating vitamin C and risk of five most common cancers in Europe. Methods We used summary-level data for genetic variants associated with plasma vitamin C in a large vitamin C genome-wide association study (GWAS) meta-analysis on 52,018 Europeans, and the corresponding associations with lung, breast, prostate, colon, and rectal cancer from GWAS consortia including up to 870,984 participants of European ancestry. We performed two-sample, bi-directional Mendelian randomization (MR) analyses using inverse-variance-weighted method as the primary approach, while using 6 additional methods (e.g., MR-Egger, weighted median-based, and mode-based methods) as sensitivity analysis to detect and adjust for pleiotropy. We also conducted a meta-analysis of prospective cohort studies and randomized controlled trials to examine the association of vitamin C intakes with cancer outcomes. Results The MR analysis showed no evidence of a causal association of circulating vitamin C concentration with any examined cancer. Although the odds ratio (OR) per one standard deviation increase in genetically predicted circulating vitamin C concentration was 1.34 (95% confidence interval 1.14 to 1.57) for breast cancer in the UK Biobank, this association could not be replicated in the Breast Cancer Association Consortium with an OR of 1.05 (0.94 to 1.17). Smoking initiation, as a positive control for our reverse MR analysis, showed a negative association with circulating vitamin C concentration. However, there was no strong evidence of a causal association of any examined cancer with circulating vitamin C. Sensitivity analysis using 6 different analytical approaches yielded similar results. Moreover, our MR results were consistent with the null findings from the meta-analysis exploring prospective associations of dietary or supplemental vitamin C intakes with cancer risk, except that higher dietary vitamin C intake, but not vitamin C supplement, was associated with a lower risk of lung cancer (risk ratio: 0.84, 95% confidence interval 0.71 to 0.99). Conclusions These findings provide no evidence to support that physiological-level circulating vitamin C has a large effect on risk of the five most common cancers in European populations, but we cannot rule out very small effect sizes.

Published
2021
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4. Quantifying genetic heterogeneity between continental populations for human height and body mass index

Author

Jing Guo, Andrew Bakshi, Ying Wang, Longda Jiang, Loic Yengo, Michael E. Goddard, Peter M. Visscher, and Jian Yang

Subjects
Medicine, Science
Abstract

Abstract Genome-wide association studies (GWAS) in samples of European ancestry have identified thousands of genetic variants associated with complex traits in humans. However, it remains largely unclear whether these associations can be used in non-European populations. Here, we seek to quantify the proportion of genetic variation for a complex trait shared between continental populations. We estimated the between-population correlation of genetic effects at all SNPs ( $$r_{g}$$ r g ) or genome-wide significant SNPs ( $$r_{{g\left( {GWS} \right)}}$$ r g GWS ) for height and body mass index (BMI) in samples of European (EUR; $$n = 49,839$$ n = 49 , 839 ) and African (AFR; $$n = 17,426$$ n = 17 , 426 ) ancestry. The $$\hat{r}_{g}$$ r ^ g between EUR and AFR was 0.75 ( $${\text{s}}.{\text{e}}. = 0.035$$ s . e . = 0.035 ) for height and 0.68 ( $${\text{s}}.{\text{e}}. = 0.062$$ s . e . = 0.062 ) for BMI, and the corresponding $$\hat{r}_{{g\left( {GWS} \right)}}$$ r ^ g GWS was 0.82 ( $${\text{s}}.{\text{e}}. = 0.030$$ s . e . = 0.030 ) for height and 0.87 ( $${\text{s}}.{\text{e}}. = 0.064$$ s . e . = 0.064 ) for BMI, suggesting that a large proportion of GWAS findings discovered in Europeans are likely applicable to non-Europeans for height and BMI. There was no evidence that $$\hat{r}_{g}$$ r ^ g differs in SNP groups with different levels of between-population difference in allele frequency or linkage disequilibrium, which, however, can be due to the lack of power.

Published
2021
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5. Widespread signatures of natural selection across human complex traits and functional genomic categories

Author

Jian Zeng, Angli Xue, Longda Jiang, Luke R. Lloyd-Jones, Yang Wu, Huanwei Wang, Zhili Zheng, Loic Yengo, Kathryn E. Kemper, Michael E. Goddard, Naomi R. Wray, Peter M. Visscher, and Jian Yang

Subjects
Science
Abstract

Methods to study how natural selection shapes genetic architecture of complex traits rely on individual level genome-wide association study (GWAS) data. Here, the authors present a Bayesian method using GWAS summary statistics to study genetic architecture and apply this to 155 complex traits.

Published
2021
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6. Genome-wide analyses of behavioural traits are subject to bias by misreports and longitudinal changes

Author

Angli Xue, Longda Jiang, Zhihong Zhu, Naomi R. Wray, Peter M. Visscher, Jian Zeng, and Jian Yang

Subjects
Science
Abstract

Conflicting reports have found disease to sometimes be positively and sometimes negatively correlated with alcohol consumption. Here, the authors show that misreporting and reduction of alcohol consumption is associated with disease, leading to misleading associations between alcohol and disease.

Published
2021
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7. Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability

Author

Vasiliki Lagou, Reedik Mägi, Jouke- Jan Hottenga, Harald Grallert, John R. B. Perry, Nabila Bouatia-Naji, Letizia Marullo, Denis Rybin, Rick Jansen, Josine L. Min, Antigone S. Dimas, Anna Ulrich, Liudmila Zudina, Jesper R. Gådin, Longda Jiang, Alessia Faggian, Amélie Bonnefond, Joao Fadista, Maria G. Stathopoulou, Aaron Isaacs, Sara M. Willems, Pau Navarro, Toshiko Tanaka, Anne U. Jackson, May E. Montasser, Jeff R. O’Connell, Lawrence F. Bielak, Rebecca J. Webster, Richa Saxena, Jeanette M. Stafford, Beate St Pourcain, Nicholas J. Timpson, Perttu Salo, So-Youn Shin, Najaf Amin, Albert V. Smith, Guo Li, Niek Verweij, Anuj Goel, Ian Ford, Paul C. D. Johnson, Toby Johnson, Karen Kapur, Gudmar Thorleifsson, Rona J. Strawbridge, Laura J. Rasmussen-Torvik, Tõnu Esko, Evelin Mihailov, Tove Fall, Ross M. Fraser, Anubha Mahajan, Stavroula Kanoni, Vilmantas Giedraitis, Marcus E. Kleber, Günther Silbernagel, Julia Meyer, Martina Müller-Nurasyid, Andrea Ganna, Antti-Pekka Sarin, Loic Yengo, Dmitry Shungin, Jian’an Luan, Momoko Horikoshi, Ping An, Serena Sanna, Yvonne Boettcher, N. William Rayner, Ilja M. Nolte, Tatijana Zemunik, Erik van Iperen, Peter Kovacs, Nicholas D. Hastie, Sarah H. Wild, Stela McLachlan, Susan Campbell, Ozren Polasek, Olga Carlson, Josephine Egan, Wieland Kiess, Gonneke Willemsen, Johanna Kuusisto, Markku Laakso, Maria Dimitriou, Andrew A. Hicks, Rainer Rauramaa, Stefania Bandinelli, Barbara Thorand, Yongmei Liu, Iva Miljkovic, Lars Lind, Alex Doney, Markus Perola, Aroon Hingorani, Mika Kivimaki, Meena Kumari, Amanda J. Bennett, Christopher J. Groves, Christian Herder, Heikki A. Koistinen, Leena Kinnunen, Ulf de Faire, Stephan J. L. Bakker, Matti Uusitupa, Colin N. A. Palmer, J. Wouter Jukema, Naveed Sattar, Anneli Pouta, Harold Snieder, Eric Boerwinkle, James S. Pankow, Patrik K. Magnusson, Ulrika Krus, Chiara Scapoli, Eco J. C. N. de Geus, Matthias Blüher, Bruce H. R. Wolffenbuttel, Michael A. Province, Goncalo R. Abecasis, James B. Meigs, G. Kees Hovingh, Jaana Lindström, James F. Wilson, Alan F. Wright, George V. Dedoussis, Stefan R. Bornstein, Peter E. H. Schwarz, Anke Tönjes, Bernhard R. Winkelmann, Bernhard O. Boehm, Winfried März, Andres Metspalu, Jackie F. Price, Panos Deloukas, Antje Körner, Timo A. Lakka, Sirkka M. Keinanen-Kiukaanniemi, Timo E. Saaristo, Richard N. Bergman, Jaakko Tuomilehto, Nicholas J. Wareham, Claudia Langenberg, Satu Männistö, Paul W. Franks, Caroline Hayward, Veronique Vitart, Jaakko Kaprio, Sophie Visvikis-Siest, Beverley Balkau, David Altshuler, Igor Rudan, Michael Stumvoll, Harry Campbell, Cornelia M. van Duijn, Christian Gieger, Thomas Illig, Luigi Ferrucci, Nancy L. Pedersen, Peter P. Pramstaller, Michael Boehnke, Timothy M. Frayling, Alan R. Shuldiner, Patricia A. Peyser, Sharon L. R. Kardia, Lyle J. Palmer, Brenda W. Penninx, Pierre Meneton, Tamara B. Harris, Gerjan Navis, Pim van der Harst, George Davey Smith, Nita G. Forouhi, Ruth J. F. Loos, Veikko Salomaa, Nicole Soranzo, Dorret I. Boomsma, Leif Groop, Tiinamaija Tuomi, Albert Hofman, Patricia B. Munroe, Vilmundur Gudnason, David S. Siscovick, Hugh Watkins, Cecile Lecoeur, Peter Vollenweider, Anders Franco-Cereceda, Per Eriksson, Marjo-Riitta Jarvelin, Kari Stefansson, Anders Hamsten, George Nicholson, Fredrik Karpe, Emmanouil T. Dermitzakis, Cecilia M. Lindgren, Mark I. McCarthy, Philippe Froguel, Marika A. Kaakinen, Valeriya Lyssenko, Richard M. Watanabe, Erik Ingelsson, Jose C. Florez, Josée Dupuis, Inês Barroso, Andrew P. Morris, Inga Prokopenko, and Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC)

Subjects
Science
Abstract

Sex differences in fasting glucose and insulin have been identified, but the genetic loci underlying these differences have not. Here, the authors perform a meta-analysis of genome-wide association studies to detect sex-specific and sex-dimorphic loci associated with fasting glucose and insulin.

Published
2021
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8. Genotype-free demultiplexing of pooled single-cell RNA-seq

Author

Jun Xu, Caitlin Falconer, Quan Nguyen, Joanna Crawford, Brett D. McKinnon, Sally Mortlock, Anne Senabouth, Stacey Andersen, Han Sheng Chiu, Longda Jiang, Nathan J. Palpant, Jian Yang, Michael D. Mueller, Alex W. Hewitt, Alice Pébay, Grant W. Montgomery, Joseph E. Powell, and Lachlan J.M Coin

Subjects
scSplit, scRNA-seq, Demultiplexing, Machine learning, Unsupervised, Hidden Markov Model, Biology (General), QH301-705.5, Genetics, QH426-470
Abstract

Abstract A variety of methods have been developed to demultiplex pooled samples in a single cell RNA sequencing (scRNA-seq) experiment which either require hashtag barcodes or sample genotypes prior to pooling. We introduce scSplit which utilizes genetic differences inferred from scRNA-seq data alone to demultiplex pooled samples. scSplit also enables mapping clusters to original samples. Using simulated, merged, and pooled multi-individual datasets, we show that scSplit prediction is highly concordant with demuxlet predictions and is highly consistent with the known truth in cell-hashing dataset. scSplit is ideally suited to samples without external genotype information and is available at: https://github.com/jon-xu/scSplit

Published
2019
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9. Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood

Author

Ting Qi, Yang Wu, Jian Zeng, Futao Zhang, Angli Xue, Longda Jiang, Zhihong Zhu, Kathryn Kemper, Loic Yengo, Zhili Zheng, eQTLGen Consortium, Riccardo E. Marioni, Grant W. Montgomery, Ian J. Deary, Naomi R. Wray, Peter M. Visscher, Allan F. McRae, and Jian Yang

Subjects
Science
Abstract

To comprehend the genetic regulatory mechanisms underlying brain-related traits in humans, Qi et al. estimate the correlation of expression and DNA methylation QTL effects in cis between blood and brain and show that using blood eQTL/mQTL data of large sample size can increase power in gene discovery for brain-related traits and diseases.

Published
2018
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10. Publisher Correction: Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability

Author

Vasiliki Lagou, Reedik Mägi, Jouke- Jan Hottenga, Harald Grallert, John R. B. Perry, Nabila Bouatia-Naji, Letizia Marullo, Denis Rybin, Rick Jansen, Josine L. Min, Antigone S. Dimas, Anna Ulrich, Liudmila Zudina, Jesper R. Gådin, Longda Jiang, Alessia Faggian, Amélie Bonnefond, Joao Fadista, Maria G. Stathopoulou, Aaron Isaacs, Sara M. Willems, Pau Navarro, Toshiko Tanaka, Anne U. Jackson, May E. Montasser, Jeff R. O’Connell, Lawrence F. Bielak, Rebecca J. Webster, Richa Saxena, Jeanette M. Stafford, Beate St Pourcain, Nicholas J. Timpson, Perttu Salo, So-Youn Shin, Najaf Amin, Albert V. Smith, Guo Li, Niek Verweij, Anuj Goel, Ian Ford, Paul C. D. Johnson, Toby Johnson, Karen Kapur, Gudmar Thorleifsson, Rona J. Strawbridge, Laura J. Rasmussen-Torvik, Tõnu Esko, Evelin Mihailov, Tove Fall, Ross M. Fraser, Anubha Mahajan, Stavroula Kanoni, Vilmantas Giedraitis, Marcus E. Kleber, Günther Silbernagel, Julia Meyer, Martina Müller-Nurasyid, Andrea Ganna, Antti-Pekka Sarin, Loic Yengo, Dmitry Shungin, Jian’an Luan, Momoko Horikoshi, Ping An, Serena Sanna, Yvonne Boettcher, N. William Rayner, Ilja M. Nolte, Tatijana Zemunik, Erik van Iperen, Peter Kovacs, Nicholas D. Hastie, Sarah H. Wild, Stela McLachlan, Susan Campbell, Ozren Polasek, Olga Carlson, Josephine Egan, Wieland Kiess, Gonneke Willemsen, Johanna Kuusisto, Markku Laakso, Maria Dimitriou, Andrew A. Hicks, Rainer Rauramaa, Stefania Bandinelli, Barbara Thorand, Yongmei Liu, Iva Miljkovic, Lars Lind, Alex Doney, Markus Perola, Aroon Hingorani, Mika Kivimaki, Meena Kumari, Amanda J. Bennett, Christopher J. Groves, Christian Herder, Heikki A. Koistinen, Leena Kinnunen, Ulf de Faire, Stephan J. L. Bakker, Matti Uusitupa, Colin N. A. Palmer, J. Wouter Jukema, Naveed Sattar, Anneli Pouta, Harold Snieder, Eric Boerwinkle, James S. Pankow, Patrik K. Magnusson, Ulrika Krus, Chiara Scapoli, Eco J. C. N. de Geus, Matthias Blüher, Bruce H. R. Wolffenbuttel, Michael A. Province, Goncalo R. Abecasis, James B. Meigs, G. Kees Hovingh, Jaana Lindström, James F. Wilson, Alan F. Wright, George V. Dedoussis, Stefan R. Bornstein, Peter E. H. Schwarz, Anke Tönjes, Bernhard R. Winkelmann, Bernhard O. Boehm, Winfried März, Andres Metspalu, Jackie F. Price, Panos Deloukas, Antje Körner, Timo A. Lakka, Sirkka M. Keinanen-Kiukaanniemi, Timo E. Saaristo, Richard N. Bergman, Jaakko Tuomilehto, Nicholas J. Wareham, Claudia Langenberg, Satu Männistö, Paul W. Franks, Caroline Hayward, Veronique Vitart, Jaakko Kaprio, Sophie Visvikis-Siest, Beverley Balkau, David Altshuler, Igor Rudan, Michael Stumvoll, Harry Campbell, Cornelia M. van Duijn, Christian Gieger, Thomas Illig, Luigi Ferrucci, Nancy L. Pedersen, Peter P. Pramstaller, Michael Boehnke, Timothy M. Frayling, Alan R. Shuldiner, Patricia A. Peyser, Sharon L. R. Kardia, Lyle J. Palmer, Brenda W. Penninx, Pierre Meneton, Tamara B. Harris, Gerjan Navis, Pim van der Harst, George Davey Smith, Nita G. Forouhi, Ruth J. F. Loos, Veikko Salomaa, Nicole Soranzo, Dorret I. Boomsma, Leif Groop, Tiinamaija Tuomi, Albert Hofman, Patricia B. Munroe, Vilmundur Gudnason, David S. Siscovick, Hugh Watkins, Cecile Lecoeur, Peter Vollenweider, Anders Franco-Cereceda, Per Eriksson, Marjo-Riitta Jarvelin, Kari Stefansson, Anders Hamsten, George Nicholson, Fredrik Karpe, Emmanouil T. Dermitzakis, Cecilia M. Lindgren, Mark I. McCarthy, Philippe Froguel, Marika A. Kaakinen, Valeriya Lyssenko, Richard M. Watanabe, Erik Ingelsson, Jose C. Florez, Josée Dupuis, Inês Barroso, Andrew P. Morris, Inga Prokopenko, and Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC)

Subjects
Science
Abstract

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-21276-3

Published
2021
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12. mBAT-combo: A more powerful test to detect gene-trait associations from GWAS data

Author

Ang Li, Shouye Liu, Andrew Bakshi, Longda Jiang, Wenhan Chen, Zhili Zheng, Patrick F. Sullivan, Peter M. Visscher, Naomi R. Wray, Jian Yang, and Jian Zeng

Subjects
Genetics, Genetics (clinical), Article
Abstract

Gene-based association tests aggregate multiple SNP-trait associations into sets defined by gene boundaries. Since genes have a direct biological link to downstream function, gene-based test results are widely used in post-GWAS analysis. A common approach for gene-based tests is to combine SNPs associations by computing the sum of χ2 statistics. However, this strategy ignores the directions of SNP effects, which could result in a loss of power for SNPs with masking effects (e.g., when the product of the effects of two SNPs and their linkage disequilibrium (LD) correlation is negative). Here, we introduce “mBAT-combo”, a new set-based test that is better powered than other methods to detect multi-SNP associations in the context of masking effects. We validate the method through simulations and applications to real data. We find that of 35 blood and urine biomarker traits in the UK Biobank, 34 traits show evidence for masking effects in a total of 4,175 gene-trait pairs, indicating that masking effects in complex traits is common. We further validate the improved power of our method in height, body mass index and schizophrenia with different GWAS sample sizes and show that on average 95.7% of the genes detected only by mBAT-combo with smaller sample sizes can be identified by the single-SNP approach with larger sample sizes (average sample size increased by 1.7-fold). For instance, LRRC4B is significant only in our method for schizophrenia, which has been shown to play a role in presynaptic pathology using genetic fine-mapping and evidence-based synaptic annotations. As a more powerful gene-based method, mBAT-combo is expected to improve the downstream pathway analysis or tissue and cell-type enrichment analysis that takes genes identified from GWAS data as input to understand the biological mechanisms of the trait or disease. Despite our focus on genes in this study, the framework of mBAT-combo is general and can be applied to any set of SNPs to refine trait-association signals hidden in genomic regions with complex LD structures.

Published
2023

13. Widespread signatures of natural selection across human complex traits and functional genomic categories

Author

Luke R. Lloyd-Jones, Jian Yang, Huanwei Wang, Loic Yengo, Angli Xue, Zhili Zheng, Yang Wu, Michael E. Goddard, Longda Jiang, Naomi R. Wray, Peter M. Visscher, Jian Zeng, and Kathryn E. Kemper

Subjects
0301 basic medicine, Multifactorial Inheritance, Science, General Physics and Astronomy, Genomics, Genome-wide association study, Biology, Quantitative trait, Genome-wide association studies, Models, Biological, Polymorphism, Single Nucleotide, General Biochemistry, Genetics and Molecular Biology, Article, Evolution, Molecular, 03 medical and health sciences, Bayes' theorem, 0302 clinical medicine, Humans, Selection, Genetic, Selection (genetic algorithm), Multidisciplinary, Natural selection, Genome, Human evolutionary genetics, Selection coefficient, Genetic Variation, Bayes Theorem, General Chemistry, Genetic architecture, 030104 developmental biology, Phenotype, Evolutionary biology, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Understanding how natural selection has shaped genetic architecture of complex traits is of importance in medical and evolutionary genetics. Bayesian methods have been developed using individual-level GWAS data to estimate multiple genetic architecture parameters including selection signature. Here, we present a method (SBayesS) that only requires GWAS summary statistics. We analyse data for 155 complex traits (n = 27k–547k) and project the estimates onto those obtained from evolutionary simulations. We estimate that, on average across traits, about 1% of human genome sequence are mutational targets with a mean selection coefficient of ~0.001. Common diseases, on average, show a smaller number of mutational targets and have been under stronger selection, compared to other traits. SBayesS analyses incorporating functional annotations reveal that selection signatures vary across genomic regions, among which coding regions have the strongest selection signature and are enriched for both the number of associated variants and the magnitude of effect sizes., Methods to study how natural selection shapes genetic architecture of complex traits rely on individual level genome-wide association study (GWAS) data. Here, the authors present a Bayesian method using GWAS summary statistics to study genetic architecture and apply this to 155 complex traits.

Published
2021

14. Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability

Author

Tove Fall, Anubha Mahajan, Dmitry Shungin, B. Balkau, Gerjan Navis, A. Metspalu, Anneli Pouta, Andrew A. Hicks, Ilja M. Nolte, Ian Ford, Aroon D. Hingorani, Stefan R Bornstein, Anuj Goel, Rona J. Strawbridge, Niek Verweij, Sarah H. Wild, Patricia B. Munroe, T.B. Harris, Jaana Lindström, Johnson Pcd., Nita G. Forouhi, Pierre Meneton, Patricia A. Peyser, Sarin A-P., Andrea Ganna, Timothy M. Frayling, Patrik K. E. Magnusson, Joanne M. Meyer, Yongmei Liu, Jeanette M. Stafford, Christian Herder, L Zudina, Maria G. Stathopoulou, May E. Montasser, Nicholas D. Hastie, Inês Barroso, Schwarz Peh., James B. Meigs, Perttu Salo, George Davey Smith, Gonneke Willemsen, Christopher J. Groves, Erik P A Van Iperen, M. A. Province, Veikko Salomaa, Naveed Sattar, Serena Sanna, Maria Dimitriou, Joop Jukema, Ulrika Krus, Albert V. Smith, Markku Laakso, James F. Wilson, George Nicholson, Loic Yengo, Tatijana Zemunik, Per Eriksson, Harold Snieder, Peter P. Pramstaller, Claudia Langenberg, R. Rauramaa, Alan R. Shuldiner, Pau Navarro, Veronique Vitart, Ross M. Fraser, Aaron Isaacs, C. Lecoeur, Jesper R. Gådin, Jackie F. Price, Letizia Marullo, L.F. Bielak, Sirkka Keinänen-Kiukaanniemi, Amélie Bonnefond, Michael Stumvoll, Alessia Faggian, Anke Tönjes, Tomohiro Tanaka, Wieland Kiess, Harry Campbell, Josée Dupuis, David Altshuler, João Fadista, Winfried März, G K Hovingh, Thomas Illig, Toby Johnson, H Grallert, Kari Stefansson, Reedik Mägi, Palmer Cna., de Geus Ejcn., Martina Müller-Nurasyid, Karen Kapur, Philippe Froguel, Dorret I. Boomsma, Anders Franco-Cereceda, Marcus E. Kleber, Boehnke M, Olga D. Carlson, Ozren Polasek, Andrew P. Morris, Alex S. F. Doney, Najaf Amin, Sara M. Willems, Vilmundur Gudnason, Jose C. Florez, Jeffery R. O'Connell, Nancy L. Pedersen, T. Saaristo, Wolffenbuttel Bhr., M. I. J. Uusitupa, Longda Jiang, Iva Miljkovic, James S. Pankow, Caroline Hayward, Hugh Watkins, Vasiliki Lagou, Johanna Kuusisto, Jaakko Tuomilehto, Alan F. Wright, Josephine M. Egan, Perry Jrb., C M van Duijn, Valeriya Lyssenko, Leif Groop, Stefania Bandinelli, Nigel W. Rayner, Tõnu Esko, Stela McLachlan, Momoko Horikoshi, Eric Boerwinkle, Rick Jansen, Richard N. Bergman, Gudmar Thorleifsson, Lyle J. Palmer, Vilmantas Giedraitis, Peter Kovacs, Nicholas J. Wareham, Luigi Ferrucci, N J Timpson, D Rybin, Anne U. Jackson, Tiinamaija Tuomi, Gonçalo R. Abecasis, Harst Pvd., Meena Kumari, Albert Hofman, Chiara Scapoli, Evelin Mihailov, Josine L. Min, Anders Hamsten, Hottenga J-J., Loos Rjf., Lars Lind, Ulf de Faire, Jaakko Kaprio, Guo Li, Beate St Pourcain, C Gieger, Amanda J. Bennett, Anna Ulrich, Nabila Bouatia-Naji, Satu Männistö, Antigone S. Dimas, Jarvelin M-R., Günther Silbernagel, F Karpe, A. Körner, David S. Siscovick, M Blüher, Rebecca J. Webster, Erik Ingelsson, Susan Campbell, Mika Kivimäki, Laura J. Rasmussen-Torvik, Heikki A. Koistinen, Sophie Visvikis-Siest, Bernhard O. Boehm, Inga Prokopenko, Ping An, Emmanouil T. Dermitzakis, Cecilia M. Lindgren, Kardia Slr., Richa Saxena, Igor Rudan, Richard M. Watanabe, Jian'an Luan, Marika Kaakinen, Shin S-Y., George Dedoussis, Panagiotis Deloukas, Mark I. McCarthy, Barbara Thorand, B.W.J.H. Penninx, Peter Vollenweider, Paul W. Franks, Leena Kinnunen, Markus Perola, Yvonne Boettcher, Timo A. Lakka, Nicole Soranzo, Stavroula Kanoni, Bakker Sjl., Winkelmann Br, The Wellcome Trust Centre for Human Genetics [Oxford], University of Oxford [Oxford], Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), Institute of Genomics [Tartu, Estonia], University of Tartu, Vrije Universiteit Amsterdam [Amsterdam] (VU), Vrije Universiteit Medical Centre (VUMC), Helmholtz-Zentrum München (HZM), University of Cambridge [UK] (CAM), Metabolic functional (epi)genomics and molecular mechanisms involved in type 2 diabetes and related diseases - UMR 8199 - UMR 1283 (GI3M), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Paris-Centre de Recherche Cardiovasculaire (PARCC (UMR_S 970/ U970)), Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP), Università degli Studi di Ferrara (UniFE), Boston University [Boston] (BU), VU University Medical Center [Amsterdam], University of Bristol [Bristol], Biomedical Sciences Research Centre Alexander Fleming [Vari, Greece] (BSRC), Imperial College London, Karolinska Institutet [Stockholm], Institute for Molecular Bioscience, University of Queensland [Brisbane], Statens Serum Institut [Copenhagen], Interactions Gène-Environnement en Physiopathologie Cardio-Vasculaire (IGE-PCV), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Erasmus University Medical Center [Rotterdam] (Erasmus MC), Cardiovascular Research Institute Maastricht (CARIM), Maastricht University [Maastricht], MRC Institute of Genetics and Molecular Medicine [Edinburgh] (IGMM), University of Edinburgh-Medical Research Council, National Institute on Aging [Baltimore, MD, USA] (NIH), University of Michigan [Ann Arbor], University of Michigan System, University of Maryland School of Medicine, University of Maryland System, The University of Western Australia (UWA), Broad Institute of MIT and Harvard (BROAD INSTITUTE), Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston], Massachusetts General Hospital [Boston], Harvard Medical School [Boston] (HMS), Wake Forest University, National Institute for Health and Welfare [Helsinki], The Wellcome Trust Sanger Institute [Cambridge], University of Iceland [Reykjavik], University of Washington [Seattle], University of Groningen [Groningen], University of Glasgow, William Harvey Research Institute, Barts and the London Medical School, Université de Lausanne (UNIL), deCODE genetics [Reykjavik], Northwestern University Feinberg School of Medicine, Uppsala Universitet [Uppsala], University of Edinburgh, Medical Faculty [Mannheim], University of Graz, Ludwig-Maximilians-Universität München (LMU), Johannes Gutenberg - Universität Mainz (JGU), Institute for Molecular Medicine Finland [Helsinki] (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki-University of Helsinki, Umeå University, Skane University Hospital [Malmo], Lund University [Lund], RIKEN Center for Integrative Medical Sciences [Yokohama] (RIKEN IMS), RIKEN - Institute of Physical and Chemical Research [Japon] (RIKEN), Washington University School of Medicine in St. Louis, Washington University in Saint Louis (WUSTL), Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerche [Roma] (CNR), University Medical Center Groningen [Groningen] (UMCG), Universität Leipzig [Leipzig], Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), University of Split, Academic Medical Center - Academisch Medisch Centrum [Amsterdam] (AMC), University of Amsterdam [Amsterdam] (UvA), University of Eastern Finland, Harokopio University of Athens, European Academy Bozen/Bolzano (EURAC), University of Kuopio, German Center for Diabetes Research - Deutsches Zentrum für Diabetesforschung [Neuherberg] (DZD), University of Pittsburgh (PITT), Pennsylvania Commonwealth System of Higher Education (PCSHE), Ninewells Hospital and Medical School [Dundee], University College of London [London] (UCL), University of Essex, Heinrich Heine Universität Düsseldorf = Heinrich Heine University [Düsseldorf], University of Helsinki, Leiden University Medical Center (LUMC), Institute of Cardiovascular and Medical Sciences [Glasgow], University of Oulu, The University of Texas Health Science Center at Houston (UTHealth), University of Minnesota Medical School, University of Minnesota System, Keck School of Medicine [Los Angeles], University of Southern California (USC), Amsterdam UMC, University Hospital Carl Gustav Carus [Dresden, Germany], Technische Universität Dresden = Dresden University of Technology (TU Dresden), Lee Kong Chian School of Medicine, Nanyang Technological University (NTU), Universität Heidelberg [Heidelberg], King Abdulaziz University, Pirkanmaa Hospital District, Tampere University Hospital, Cedars-Sinai Medical Center, Danube University Krems, Harvard School of Public Health, Centre de recherche en épidémiologie et santé des populations (CESP), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay, Institute of Epidemiology [Neuherberg] (EPI), German Research Center for Environmental Health - Helmholtz Center München (GmbH), Hannover Medical School [Hannover] (MHH), Universität zu Lübeck [Lübeck], University of Exeter, Regeneron Pharmaceuticals [Tarrytown], University of Adelaide, Centre de Recherche des Cordeliers (CRC (UMR_S 872)), Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), National Institute on Aging [Bethesda, USA] (NIA), National Institutes of Health [Bethesda] (NIH), Icahn School of Medicine at Mount Sinai [New York] (MSSM), Harvard T.H. Chan School of Public Health, John Radcliffe Hospital [Oxford University Hospital], Centre Hospitalier Universitaire Vaudois [Lausanne] (CHUV), Université de Genève (UNIGE), Big Data Institute, University of Surrey (UNIS), University of Bergen (UiB), Stanford School of Medicine [Stanford], Stanford Medicine, Stanford University-Stanford University, Stanford Cardiovascular Institute, University of Liverpool, University of Manchester [Manchester], Institute of Biochemistry and Genetics of Ufa Scientific Centre, Russian Academy of Sciences [Moscow] (RAS), Experimental Vascular Medicine, Vascular Medicine, ACS - Atherosclerosis & ischemic syndromes, SIEST, Sofia, PreciDIAB Institute, the holistic approach of personal diabets care - - PreciDIAB2018 - ANR-18-IBHU-0001 - IBHU - VALID, Understanding the dynamic determinants of glucose homeostasis and social capability to promote Healthy and active aging - DYNAHEALTH - - H20202015-04-01 - 2019-03-31 - 633595 - VALID, Beyond the Genetics of Addiction - ADDICTION - - EC:FP7:ERC2011-12-01 - 2017-05-31 - 284167 - VALID, Rise of scientific excellence and collaboration for implementing personalised medicine in Estonia - ePerMed - - H20202016-01-01 - 2018-12-31 - 692145 - VALID, University of Oxford, Helmholtz Zentrum München = German Research Center for Environmental Health, Metabolic functional (epi)genomics and molecular mechanisms involved in type 2 diabetes and related diseases - UMR 8199 - UMR 1283 (EGENODIA (GI3M)), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Università degli Studi di Ferrara = University of Ferrara (UniFE), Université de Lausanne = University of Lausanne (UNIL), Karl-Franzens-Universität Graz, Johannes Gutenberg - Universität Mainz = Johannes Gutenberg University (JGU), Helsingin yliopisto = Helsingfors universitet = University of Helsinki-Helsingin yliopisto = Helsingfors universitet = University of Helsinki, Helsingin yliopisto = Helsingfors universitet = University of Helsinki, Amsterdam UMC - Amsterdam University Medical Center, Nanyang Technological University [Singapour], Universität zu Lübeck = University of Lübeck [Lübeck], Laboratoire d'Informatique Médicale et Ingénierie des Connaissances en e-Santé (LIMICS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Sorbonne Paris Nord, Université de Genève = University of Geneva (UNIGE), ANR-18-IBHU-0001,PreciDIAB,PreciDIAB Institute, the holistic approach of personal diabets care(2018), European Project: 633595,H2020,H2020-PHC-2014-two-stage,DYNAHEALTH(2015), European Project: 284167,EC:FP7:ERC,ERC-2011-StG_20101124,ADDICTION(2011), European Project: 692145,H2020,H2020-TWINN-2015,ePerMed(2016), Biological Psychology, APH - Health Behaviors & Chronic Diseases, APH - Personalized Medicine, Functional Genomics, APH - Mental Health, Sociology and Social Gerontology, APH - Methodology, Hottenga, Jouke- Jan [0000-0002-5668-2368], Bouatia-Naji, Nabila [0000-0001-5424-2134], Jansen, Rick [0000-0002-3333-6737], Min, Josine L. [0000-0003-4456-9824], Faggian, Alessia [0000-0002-3799-9722], Bonnefond, Amélie [0000-0001-9976-3005], Isaacs, Aaron [0000-0001-5037-4834], Willems, Sara M. [0000-0002-6803-3007], Navarro, Pau [0000-0001-5576-8584], Jackson, Anne U. [0000-0002-9672-2547], Bielak, Lawrence F. [0000-0002-3443-8030], Saxena, Richa [0000-0003-2233-1065], Smith, Albert V. [0000-0003-1942-5845], Verweij, Niek [0000-0002-4303-7685], Goel, Anuj [0000-0003-2307-4021], Johnson, Paul C. D. [0000-0001-6663-7520], Strawbridge, Rona J. [0000-0001-8506-3585], Fall, Tove [0000-0003-2071-5866], Fraser, Ross M. [0000-0003-0488-2592], Kanoni, Stavroula [0000-0002-1691-9615], Giedraitis, Vilmantas [0000-0003-3423-2021], Kleber, Marcus E. [0000-0003-0663-7275], Müller-Nurasyid, Martina [0000-0003-3793-5910], Luan, Jian’an [0000-0003-3137-6337], Sanna, Serena [0000-0002-3768-1749], Nolte, Ilja M. [0000-0001-5047-4077], Zemunik, Tatijana [0000-0001-8120-2891], Kovacs, Peter [0000-0002-0290-5423], Wild, Sarah H. [0000-0001-7824-2569], McLachlan, Stela [0000-0003-0480-6143], Egan, Josephine [0000-0002-8945-0053], Hicks, Andrew A. [0000-0001-6320-0411], Thorand, Barbara [0000-0002-8416-6440], Hingorani, Aroon [0000-0001-8365-0081], Kivimaki, Mika [0000-0002-4699-5627], Koistinen, Heikki A. [0000-0001-7870-070X], Bakker, Stephan J. L. [0000-0003-3356-6791], Palmer, Colin N. A. [0000-0002-6415-6560], Jukema, J. Wouter [0000-0002-3246-8359], Sattar, Naveed [0000-0002-1604-2593], Snieder, Harold [0000-0003-1949-2298], Magnusson, Patrik K. [0000-0002-7315-7899], Blüher, Matthias [0000-0003-0208-2065], Wolffenbuttel, Bruce H. R. [0000-0001-9262-6921], Abecasis, Goncalo R. [0000-0003-1509-1825], Meigs, James B. [0000-0002-2439-2657], Wilson, James F. [0000-0001-5751-9178], Schwarz, Peter E. H. [0000-0001-6317-7880], Boehm, Bernhard O. [0000-0002-2706-7710], Metspalu, Andres [0000-0002-3718-796X], Deloukas, Panos [0000-0001-9251-070X], Körner, Antje [0000-0001-6001-0356], Wareham, Nicholas J. [0000-0003-1422-2993], Langenberg, Claudia [0000-0002-5017-7344], Männistö, Satu [0000-0002-8668-3046], Franks, Paul W. [0000-0002-0520-7604], Hayward, Caroline [0000-0002-9405-9550], Vitart, Veronique [0000-0002-4991-3797], Kaprio, Jaakko [0000-0002-3716-2455], Visvikis-Siest, Sophie [0000-0001-8104-8425], Altshuler, David [0000-0002-7250-4107], Rudan, Igor [0000-0001-6993-6884], van Duijn, Cornelia M. [0000-0002-2374-9204], Pramstaller, Peter P. [0000-0002-9831-8302], Boehnke, Michael [0000-0002-6442-7754], Frayling, Timothy M. [0000-0001-8362-2603], Peyser, Patricia A. [0000-0002-9717-8459], Harst, Pim van der [0000-0002-2713-686X], Smith, George Davey [0000-0002-1407-8314], Forouhi, Nita G. [0000-0002-5041-248X], Loos, Ruth J. F. [0000-0002-8532-5087], Salomaa, Veikko [0000-0001-7563-5324], Soranzo, Nicole [0000-0003-1095-3852], Boomsma, Dorret I. [0000-0002-7099-7972], Groop, Leif [0000-0002-0187-3263], Tuomi, Tiinamaija [0000-0002-8306-6202], Munroe, Patricia B. [0000-0002-4176-2947], Gudnason, Vilmundur [0000-0001-5696-0084], Lecoeur, Cecile [0000-0003-0075-6417], Jarvelin, Marjo-Riitta [0000-0002-2149-0630], Stefansson, Kari [0000-0003-1676-864X], Dermitzakis, Emmanouil T. [0000-0002-9302-6490], Lindgren, Cecilia M. [0000-0002-4903-9374], Froguel, Philippe [0000-0003-2972-0784], Kaakinen, Marika A. [0000-0002-9228-0462], Watanabe, Richard M. [0000-0003-1015-0531], Ingelsson, Erik [0000-0003-2256-6972], Dupuis, Josée [0000-0003-2871-3603], Barroso, Inês [0000-0001-5800-4520], Apollo - University of Cambridge Repository, Epidemiology, University Hospital Mannheim | Universitätsmedizin Mannheim, National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR), Universität Leipzig, Universiteit Leiden, Universität Heidelberg [Heidelberg] = Heidelberg University, Karl-Franzens-Universität [Graz, Autriche], Psychiatry, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, General practice, APH - Digital Health, Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Life Course Epidemiology (LCE), Lifestyle Medicine (LM), Groningen Institute for Organ Transplantation (GIOT), Groningen Kidney Center (GKC), Center for Liver, Digestive and Metabolic Diseases (CLDM), Value, Affordability and Sustainability (VALUE), Cardiovascular Centre (CVC), Hottenga, Jouke-Jan [0000-0002-5668-2368], Min, Josine L [0000-0003-4456-9824], Willems, Sara M [0000-0002-6803-3007], Jackson, Anne U [0000-0002-9672-2547], Bielak, Lawrence F [0000-0002-3443-8030], Smith, Albert V [0000-0003-1942-5845], Johnson, Paul CD [0000-0001-6663-7520], Strawbridge, Rona J [0000-0001-8506-3585], Fraser, Ross M [0000-0003-0488-2592], Kleber, Marcus E [0000-0003-0663-7275], Luan, Jian'an [0000-0003-3137-6337], Nolte, Ilja M [0000-0001-5047-4077], Wild, Sarah H [0000-0001-7824-2569], Hicks, Andrew A [0000-0001-6320-0411], Koistinen, Heikki A [0000-0001-7870-070X], Bakker, Stephan JL [0000-0003-3356-6791], Palmer, Colin NA [0000-0002-6415-6560], Jukema, J Wouter [0000-0002-3246-8359], Magnusson, Patrik K [0000-0002-7315-7899], Wolffenbuttel, Bruce HR [0000-0001-9262-6921], Abecasis, Goncalo R [0000-0003-1509-1825], Meigs, James B [0000-0002-2439-2657], Wilson, James F [0000-0001-5751-9178], Schwarz, Peter EH [0000-0001-6317-7880], Boehm, Bernhard O [0000-0002-2706-7710], Wareham, Nicholas J [0000-0003-1422-2993], Franks, Paul W [0000-0002-0520-7604], van Duijn, Cornelia M [0000-0002-2374-9204], Pramstaller, Peter P [0000-0002-9831-8302], Frayling, Timothy M [0000-0001-8362-2603], Peyser, Patricia A [0000-0002-9717-8459], Forouhi, Nita G [0000-0002-5041-248X], Loos, Ruth JF [0000-0002-8532-5087], Boomsma, Dorret I [0000-0002-7099-7972], Munroe, Patricia B [0000-0002-4176-2947], Dermitzakis, Emmanouil T [0000-0002-9302-6490], Lindgren, Cecilia M [0000-0002-4903-9374], Kaakinen, Marika A [0000-0002-9228-0462], Watanabe, Richard M [0000-0003-1015-0531], Tampere University, Tays Research Services, Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC), Fysiologie, RS: FHML MaCSBio, and RS: Carim - B01 Blood proteins & engineering

Subjects
Male, Anorexia Nervosa, medicine.medical_treatment, 45/43, Insulin Resistance/genetics, SUSCEPTIBILITY, Quantitative trait, Impaired glucose tolerance, 0302 clinical medicine, Architecture, LS2_1, IMPUTATION, Insulin, ComputingMilieux_MISCELLANEOUS, Fasting, Publisher Correction, 3. Good health, [SDV] Life Sciences [q-bio], Kruppel-Like Transcription Factors/blood, Endokrinologi och diabetes, Science & Technology - Other Topics, Adult, Blood Glucose, European Continental Ancestry Group, Female, Gene Expression, Genetic Loci, Genome-Wide Association Study, Glucose Intolerance, Humans, Insulin Receptor Substrate Proteins, Insulin Resistance, Kruppel-Like Transcription Factors, Middle Aged, Phenotype, Sex Characteristics, Sex Factors, Waist-Hip Ratio, Sex characteristics, medicine.medical_specialty, Science, 631/208/205/2138, Endocrinology and Diabetes, General Biochemistry, Genetics and Molecular Biology, White People, Gender-differences, 03 medical and health sciences, SDG 3 - Good Health and Well-being, 692/53/2421, GLYCEMIC TRAITS, GENOME-WIDE ASSOCIATION, Glycemic, GENDER-DIFFERENCES, Science & Technology, IDENTIFICATION, 692/699/2743/2815, Blood Glucose/metabolism, Diagnostic markers, medicine.disease, Anorexia Nervosa/blood, 030104 developmental biology, Endocrinology, Glucose, Insulin/blood, Anorexia Nervosa/ethnology, Anorexia Nervosa/genetics, Anorexia Nervosa/physiopathology, Fasting/blood, Glucose Intolerance/blood, Glucose Intolerance/ethnology, Glucose Intolerance/genetics, Glucose Intolerance/physiopathology, Insulin Receptor Substrate Proteins/blood, Insulin Receptor Substrate Proteins/genetics, Kruppel-Like Transcription Factors/genetics, 0301 basic medicine, Identification, [SDV]Life Sciences [q-bio], General Physics and Astronomy, Genome-wide association studies, Waist–hip ratio, LS4_5, RISK, ARCHITECTURE, Multidisciplinary, article, Type 2 diabetes, Multidisciplinary Sciences, MENDELIAN RANDOMIZATION, Pre-diabetes, Medical Genetics, Risk, PATHOPHYSIOLOGY, 030209 endocrinology & metabolism, 3121 Internal medicine, 692/163/2743/137/773, NO, Insulin resistance, Internal medicine, Diabetes mellitus, medicine, Mendelian randomization, 631/208/480, Medicinsk genetik, business.industry, General Chemistry, Impaired fasting glucose, business
Abstract

Differences between sexes contribute to variation in the levels of fasting glucose and insulin. Epidemiological studies established a higher prevalence of impaired fasting glucose in men and impaired glucose tolerance in women, however, the genetic component underlying this phenomenon is not established. We assess sex-dimorphic (73,089/50,404 women and 67,506/47,806 men) and sex-combined (151,188/105,056 individuals) fasting glucose/fasting insulin genetic effects via genome-wide association study meta-analyses in individuals of European descent without diabetes. Here we report sex dimorphism in allelic effects on fasting insulin at IRS1 and ZNF12 loci, the latter showing higher RNA expression in whole blood in women compared to men. We also observe sex-homogeneous effects on fasting glucose at seven novel loci. Fasting insulin in women shows stronger genetic correlations than in men with waist-to-hip ratio and anorexia nervosa. Furthermore, waist-to-hip ratio is causally related to insulin resistance in women, but not in men. These results position dissection of metabolic and glycemic health sex dimorphism as a steppingstone for understanding differences in genetic effects between women and men in related phenotypes., Sex differences in fasting glucose and insulin have been identified, but the genetic loci underlying these differences have not. Here, the authors perform a meta-analysis of genome-wide association studies to detect sex-specific and sex-dimorphic loci associated with fasting glucose and insulin.

Published
2021

15. Random glucose GWAS in 493,036 individuals provides insights into diabetes pathophysiology, complications and treatment stratification

Author

Sara M. Willems, Josée Dupuis, Martina Müller-Nurasyid, Boehnke M, Mark H, Salem, Inês Barroso, Letizia Marullo, Kari Stefansson, C Gieger, Anna Ulrich, Morris J. Brown, González Ksg, Grant W. Montgomery, Anders Hamsten, Emma Ahlqvist, Aaron Isaacs, Kay-Tee Khaw, Amy Hofman, Corrêa Ir, Inger Njølstad, L Zudina, Rona J. Strawbridge, J. Tuomilehto, E Albrecht, Jing Hua Zhao, Patrick M. Sexton, Mark I. McCarthy, Roxana Maria Rujan, Chiara Scapoli, Anne U. Jackson, Ioanna Tzoulaki, van Duijn C, Giuseppe Deganutti, Reedik Mägi, Jose C. Florez, Bernhard O. Boehm, Toby Johnson, Petar Todorov, Jones B, Inga Prokopenko, Leif Groop, Lagou, Hugh Watkins, Balkhiyarova Z, Tomas A, Longda Jiang, Oddgeir L. Holmen, Tan Tm, Barbara Thorand, Andre G. Uitterlinden, Wolfgang Koenig, He Gao, Sodbo Zh Sharapov, Claudia Langenberg, D Rybin, Ayse Demirkan, H Grallert, Christine Meisinger, Eric F, Denise Wootten, Heinz Erich Wichmann, Wolfgang Kratzer, Paul Elliott, Tune H. Pers, Beben Benyamin, Yurii S. Aulchenko, Robert A. Scott, Marika Kaakinen, Alessia David, Tom Wilsgaard, John Whitfield, Patricia B. Munroe, Chen S, Karen L. Mohlke, Alessia Faggian, Evangelos Evangelou, Philippe Froguel, Nicholas J. Wareham, Unnur Thorsteinsdottir, N. G. Martin, Christopher A. Reynolds, Steinthorsdottir, Heather M. Stringham, Mark J. Caulfield, Gudmar Thorleifsson, James B. Meigs, Anuj Goel, Kristian Hveem, Evan L. Brittain, and Julian S

Subjects
Diabetes Complication, 0303 health sciences, business.industry, Glucose Measurement, Genome-wide association study, Type 2 diabetes, medicine.disease, Bioinformatics, 3. Good health, 03 medical and health sciences, 0302 clinical medicine, Diabetes mellitus, medicine, Blood sugar regulation, business, 030217 neurology & neurosurgery, Homeostasis, 030304 developmental biology, Genetic association
Abstract

Homeostatic control of blood glucose requires different physiological responses in the fasting and post-prandial states. We reasoned that glucose measurements under non-standardised conditions (random glucose; RG) may capture diverse glucoregulatory processes more effectively than previous genome-wide association studies (GWAS) of fasting glycaemia or after standardised glucose loads. Through GWAS meta-analysis of RG in 493,036 individuals without diabetes of diverse ethnicities we identified 128 associated loci represented by 162 distinct signals, including 14 with sex-dimorphic effects, 9 discovered through trans-ethnic analysis, and 70 novel signals for glycaemic traits. Novel RG loci were particularly enriched in expression in the ileum and colon, indicating a prominent role for the gastrointestinal tract in the control of blood glucose. Functional studies and molecular dynamics simulations of coding variants of GLP1R, a well-established type 2 diabetes treatment target, provided a genetic framework for optimal selection of GLP-1R agonist therapy. We also provided new evidence from Mendelian randomisation that lung function is modulated by blood glucose and that pulmonary dysfunction is a diabetes complication. Thus, our approach based on RG GWAS provided wide-ranging insights into the biology of glucose regulation, diabetes complications and the potential for treatment stratification.

Published
2021

16. Circulating vitamin C concentration and risk of cancers: a Mendelian randomization study

Author

Jian Yang, Fengzhe Xu, Ju-Sheng Zheng, Susanna C. Larsson, Longda Jiang, Zelei Miao, Yuanqing Fu, and Xinxiu Liang

Subjects
0301 basic medicine, Oncology, Vitamin, Male, medicine.medical_specialty, Mendelian randomization analysis, Breast Neoplasms, Ascorbic Acid, Lower risk, Polymorphism, Single Nucleotide, Circulating vitamin C, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, Breast cancer, Risk Factors, Internal medicine, Mendelian randomization, medicine, Humans, Prospective Studies, Vitamin D, Prospective cohort study, Cancer och onkologi, business.industry, Cancer, General Medicine, Odds ratio, medicine.disease, 030104 developmental biology, chemistry, Site-specific cancers, Cancer and Oncology, 030220 oncology & carcinogenesis, Relative risk, Medicine, Female, business, Genome-Wide Association Study, Research Article
Abstract

Background Circulating vitamin C concentrations have been associated with several cancers in observational studies, but little is known about the causal direction of the associations. This study aims to explore the potential causal relationship between circulating vitamin C and risk of five most common cancers in Europe. Methods We used summary-level data for genetic variants associated with plasma vitamin C in a large vitamin C genome-wide association study (GWAS) meta-analysis on 52,018 Europeans, and the corresponding associations with lung, breast, prostate, colon, and rectal cancer from GWAS consortia including up to 870,984 participants of European ancestry. We performed two-sample, bi-directional Mendelian randomization (MR) analyses using inverse-variance-weighted method as the primary approach, while using 6 additional methods (e.g., MR-Egger, weighted median-based, and mode-based methods) as sensitivity analysis to detect and adjust for pleiotropy. We also conducted a meta-analysis of prospective cohort studies and randomized controlled trials to examine the association of vitamin C intakes with cancer outcomes. Results The MR analysis showed no evidence of a causal association of circulating vitamin C concentration with any examined cancer. Although the odds ratio (OR) per one standard deviation increase in genetically predicted circulating vitamin C concentration was 1.34 (95% confidence interval 1.14 to 1.57) for breast cancer in the UK Biobank, this association could not be replicated in the Breast Cancer Association Consortium with an OR of 1.05 (0.94 to 1.17). Smoking initiation, as a positive control for our reverse MR analysis, showed a negative association with circulating vitamin C concentration. However, there was no strong evidence of a causal association of any examined cancer with circulating vitamin C. Sensitivity analysis using 6 different analytical approaches yielded similar results. Moreover, our MR results were consistent with the null findings from the meta-analysis exploring prospective associations of dietary or supplemental vitamin C intakes with cancer risk, except that higher dietary vitamin C intake, but not vitamin C supplement, was associated with a lower risk of lung cancer (risk ratio: 0.84, 95% confidence interval 0.71 to 0.99). Conclusions These findings provide no evidence to support that physiological-level circulating vitamin C has a large effect on risk of the five most common cancers in European populations, but we cannot rule out very small effect sizes.

Published
2021

17. FastGWA-GLMM: a generalized linear mixed model association tool for biobank-scale data

Author

Jian Yang, Longda Jiang, and Zhili Zheng

Subjects
Scale (ratio), Association (object-oriented programming), Data mining, Biology, computer.software_genre, Biobank, computer, Generalized linear mixed model
Abstract

Compared to linear mixed model-based genome-wide association (GWA) methods, generalized linear mixed model (GLMM)-based methods have better statistical properties when applied to binary traits but are computationally much slower. Here, leveraging efficient sparse matrix-based algorithms, we developed a GLMM-based GWA tool (called fastGWA-GLMM) that is orders of magnitude faster than the state-of-the-art tool (e.g., ~37 times faster when n=400,000) with more scalable memory usage. We show by simulation that the fastGWA-GLMM test-statistics of both common and rare variants are well-calibrated under the null, even for traits with an extreme case-control ratio (e.g., 0.1%). We applied fastGWA-GLMM to the UK Biobank data of 456,348 individuals, 11,842,647 variants and 2,989 binary traits (full summary statistics available at http://fastgwa.info/ukbimpbin) and identified 259 rare variants associated with 75 traits, demonstrating the use of imputed genotype data in a large cohort to discover rare variants for binary complex traits.

Published
2021

18. Genome-wide analyses of behavioural traits are subject to bias by misreports and longitudinal changes

Author

Jian Zeng, Longda Jiang, Peter M. Visscher, Naomi R. Wray, Zhihong Zhu, Jian Yang, and Angli Xue

Subjects
0301 basic medicine, Alcohol Drinking, Population genetics, Science, MEDLINE, General Physics and Astronomy, Genome-wide association study, Quantitative trait, Health outcomes, Genome, Article, General Biochemistry, Genetics and Molecular Biology, Body Mass Index, 03 medical and health sciences, Quantitative Trait, Heritable, 0302 clinical medicine, Bias, Environmental health, Humans, Medicine, 030212 general & internal medicine, Disease burden, Biological Specimen Banks, Genetic association study, Genetic association, Behavior, Multidisciplinary, business.industry, Subject (documents), General Chemistry, Mendelian Randomization Analysis, Publisher Correction, Biobank, United Kingdom, 030104 developmental biology, Risk factors, business, Genome-Wide Association Study
Abstract

Genome-wide association studies (GWAS) have discovered numerous genetic variants associated with human behavioural traits. However, behavioural traits are subject to misreports and longitudinal changes (MLC) which can cause biases in GWAS and follow-up analyses. Here, we demonstrate that individuals with higher disease burden in the UK Biobank (n = 455,607) are more likely to misreport or reduce their alcohol consumption levels, and propose a correction procedure to mitigate the MLC-induced biases. The alcohol consumption GWAS signals removed by the MLC corrections are enriched in metabolic/cardiovascular traits. Almost all the previously reported negative estimates of genetic correlations between alcohol consumption and common diseases become positive/non-significant after the MLC corrections. We also observe MLC biases for smoking and physical activities in the UK Biobank. Our findings provide a plausible explanation of the controversy about the effects of alcohol consumption on health outcomes and a caution for future analyses of self-reported behavioural traits in biobank data., Conflicting reports have found disease to sometimes be positively and sometimes negatively correlated with alcohol consumption. Here, the authors show that misreporting and reduction of alcohol consumption is associated with disease, leading to misleading associations between alcohol and disease.

Published
2021

19. Publisher Correction: Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability

Author

Stavroula Kanoni, Bakker Sjl., Winkelmann Br, Wieland Kiess, Josée Dupuis, Palmer Cna., James F. Wilson, Schwarz Peh., Maria Dimitriou, Joop Jukema, Sara M. Willems, J L Min, R. Rauramaa, Perry Jrb., Momoko Horikoshi, Timo A. Lakka, Nicole Soranzo, J Kaprio, Niek Verweij, Martina Müller-Nurasyid, Jaana Lindström, Toby Johnson, Olga D. Carlson, Nita G. Forouhi, George Dedoussis, Johnson Pcd., Patrick K.E. Magnusson, Gonçalo R. Abecasis, Ozren Polasek, Wolffenbuttel Bhr., M. I. J. Uusitupa, Longda Jiang, Nancy L. Pedersen, Beate St Pourcain, Erik P A Van Iperen, Iva Miljkovic, Stefania Bandinelli, M. A. Province, Veikko Salomaa, Andrew A. Hicks, Evelin Mihailov, Rick Jansen, James B. Meigs, D Rybin, Peter Kovacs, George Davey Smith, Rona J. Strawbridge, Gudmar Thorleifsson, Meena Kumari, Chiara Scapoli, Christopher J. Groves, Barbara Thorand, T.B. Harris, Ulf de Faire, Inga Prokopenko, Stela McLachlan, Ping An, Anubha Mahajan, L.F. Bielak, Rebecca J. Webster, David Altshuler, Susan Campbell, Bernhard O. Boehm, A. Metspalu, Perttu Salo, D.I. Boomsma, Ilja M. Nolte, Andrea Ganna, Timothy M. Frayling, Pau Navarro, N J Timpson, Kardia Slr., Jeanette M. Stafford, Tõnu Esko, Ulrika Krus, Richa Saxena, Per Eriksson, Peter P. Pramstaller, Anne U. Jackson, V Lagou, Anders Franco-Cereceda, David S. Siscovick, Josephine M. Egan, Loos Rjf., C Gieger, Amanda J. Bennett, Anna Ulrich, Satu Männistö, Mika Kivimäki, Loic Yengo, Caroline Hayward, George Nicholson, C M van Duijn, Anke Tönjes, Nigel W. Rayner, Jose C. Florez, Leif Groop, Valeri Lyssenko, Lyle J. Palmer, Vilmantas Giedraitis, Maria G. Stathopoulou, B. Balkau, Anneli Pouta, Anuj Goel, Pierre Meneton, Serena Sanna, Jesper R. Gådin, Claudia Langenberg, Alessia Faggian, H Grallert, Karen Kapur, Marcus E. Kleber, Philippe Froguel, Boehnke M, Harry Campbell, Anders Hamsten, T. Saaristo, Antigone S. Dimas, Jarvelin M-R., F Karpe, A. Körner, Leena Kinnunen, Markus Perola, Joanne M. Meyer, May E. Montasser, Erik Ingelsson, Naveed Sattar, Yvonne Boettcher, Sirkka Keinänen-Kiukaanniemi, Aaron Isaacs, Gerjan Navis, Ian Ford, Amélie Bonnefond, Reedik Mägi, Tove Fall, Dmitry Shungin, Jenna Price, Igor Rudan, Richard M. Watanabe, Luigi Ferrucci, Jian'an Luan, Harst Pvd., Marika Kaakinen, Tatijana Zemunik, Christian Herder, Shin S-Y., Veronique Vitart, Ross M. Fraser, Alan R. Shuldiner, Panagiotis Deloukas, C. Lecoeur, Letizia Marullo, Kari Stefansson, Lars Lind, Winfried März, L Zudina, Aroon D. Hingorani, Gonneke Willemsen, de Geus Ejcn., Albert V. Smith, Jeffery R. O'Connell, Yongmei Liu, James S. Pankow, Sarah H. Wild, Patricia B. Munroe, Patricia A. Peyser, Nicholas J. Wareham, Tiinamaija Tuomi, Nicholas D. Hastie, Markku Laakso, Albert Hofman, J. Tuomilehto, Emmanouil T. Dermitzakis, Thomas Illig, Tomohiro Tanaka, Cecilia M. Lindgren, Sarin A-P., Alex S. F. Doney, Najaf Amin, Hugh Watkins, Johanna Kuusisto, Andrew P. Morris, Richard N. Bergman, Mark I. McCarthy, Nabila Bouatia-Naji, Günther Silbernagel, João Fadista, Harold Snieder, Ins Barroso, Michael Stumvoll, B.W.J.H. Penninx, M Blüher, Stefan R Bornstein, Laura J. Rasmussen-Torvik, Alan F. Wright, Peter Vollenweider, G K Hovingh, Heikki A. Koistinen, Sophie Visvikis-Siest, Vilmundur Gudnason, Eric Boerwinkle, Hottenga J-J., Guo Li, Paul W. Franks, Université de Lille, Centre de recherche en épidémiologie et santé des populations (CESP), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay

Subjects
Genetics, Multidisciplinary, Science, Insulin, medicine.medical_treatment, General Physics and Astronomy, Diagnostic marker, Genome-wide association study, General Chemistry, Type 2 diabetes, Quantitative trait locus, Biology, medicine.disease, GeneralLiterature_MISCELLANEOUS, General Biochemistry, Genetics and Molecular Biology, Fasting glucose, Sexual dimorphism, Pre diabetes, [SDU]Sciences of the Universe [physics], ComputingMethodologies_DOCUMENTANDTEXTPROCESSING, medicine
Abstract

The original version of this Article contained an error in Fig. 2, in which panels a and b were inadvertently swapped. This has now been corrected in the PDF and HTML versions of the Article.

Published
2021

20. A generalized linear mixed model association tool for biobank-scale data

Author

Longda Jiang, Jian Yang, Zhili Zheng, and Hailing Fang

Subjects
Mixed model, Adult, Scale (ratio), Genotype, Models, Genetic, Binary number, Genetic Variation, Biology, Middle Aged, Biobank, Generalized linear mixed model, United Kingdom, Phenotype, Null (SQL), Case-Control Studies, Statistics, Genetics, Linear Models, Humans, Algorithms, Statistical hypothesis testing, Sparse matrix, Aged, Biological Specimen Banks, Genome-Wide Association Study
Abstract

Compared with linear mixed model-based genome-wide association (GWA) methods, generalized linear mixed model (GLMM)-based methods have better statistical properties when applied to binary traits but are computationally much slower. In the present study, leveraging efficient sparse matrix-based algorithms, we developed a GLMM-based GWA tool, fastGWA-GLMM, that is severalfold to orders of magnitude faster than the state-of-the-art tools when applied to the UK Biobank (UKB) data and scalable to cohorts with millions of individuals. We show by simulation that the fastGWA-GLMM test statistics of both common and rare variants are well calibrated under the null, even for traits with extreme case-control ratios. We applied fastGWA-GLMM to the UKB data of 456,348 individuals, 11,842,647 variants and 2,989 binary traits (full summary statistics available at http://fastgwa.info/ukbimpbin ), and identified 259 rare variants associated with 75 traits, demonstrating the use of imputed genotype data in a large cohort to discover rare variants for binary complex traits.

Published
2020

21. Genome-wide analyses of behavioural traits biased by misreports and longitudinal changes

Author

Jian Zeng, Zhihong Zhu, Longda Jiang, Peter M. Visscher, Jian Yang, Angli Xue, and Naomi R. Wray

Subjects
Genetics, Genetic variants, Genome-wide association study, Biology, Health outcomes, Alcohol consumption, Genome, Biobank, Disease burden, Genetic association
Abstract

Genome-wide association studies (GWAS) have discovered numerous genetic variants associated with human behavioural traits. However, behavioural traits are subject to misreports and longitudinal changes (MLC) which can cause biases in GWAS and follow-up analyses. Here, we demonstrate that individuals with higher disease burden in the UK Biobank (n = 455,607) are more likely to misreport or reduce their alcohol consumption (AC) levels, and propose a correction procedure to mitigate the MLC-induced biases. The AC GWAS signals removed by the MLC corrections are enriched in metabolic/cardiovascular traits. Almost all the previously reported negative estimates of genetic correlations between AC and common diseases become positive/non-significant after the MLC corrections. We also observe MLC biases for smoking and physical activities in the UK Biobank. Our findings provide a plausible explanation of the controversy about the effects of AC on health outcomes and a caution for future analyses of self-reported behavioural traits in biobank data.

Published
2020

22. Genotype-free demultiplexing of pooled single-cell RNA-seq

Author

Grant W. Montgomery, Nathan J. Palpant, Longda Jiang, Michael D. Mueller, Brett McKinnon, Alex W. Hewitt, Joanna Crawford, Jun Xu, Lachlan J. M. Coin, Sally-Anne Mortlock, Quan Nguyen, Anne Senabouth, Han Sheng Chiu, Caitlin Falconer, Stacey B. Andersen, Alice Pébay, Joseph E. Powell, and Jian Yang

Subjects
lcsh:QH426-470, Sequence analysis, Expectation-maximization, Pooling, Method, RNA-Seq, Sample (statistics), 610 Medicine & health, Computational biology, Biology, Hidden Markov Model, Unsupervised, 03 medical and health sciences, 0302 clinical medicine, Single-cell analysis, Genotype, scRNA-seq, Machine learning, Demultiplexing, Allele fraction, Humans, lcsh:QH301-705.5, 030304 developmental biology, 0303 health sciences, Genotype-free, Sequence Analysis, RNA, Doublets, lcsh:Genetics, lcsh:Biology (General), scSplit, Single-Cell Analysis, 030217 neurology & neurosurgery, Software
Abstract

A variety of methods have been developed to demultiplex pooled samples in a single cell RNA sequencing (scRNA-seq) experiment which either require hashtag barcodes or sample genotypes prior to pooling. We introduce scSplit which utilizes genetic differences inferred from scRNA-seq data alone to demultiplex pooled samples. scSplit also enables mapping clusters to original samples. Using simulated, merged, and pooled multi-individual datasets, we show that scSplit prediction is highly concordant with demuxlet predictions and is highly consistent with the known truth in cell-hashing dataset. scSplit is ideally suited to samples without external genotype information and is available at: https://github.com/jon-xu/scSplit

Published
2019

23. Quantifying genetic heterogeneity between continental populations for human height and body mass index

Author

Andrew Bakshi, Peter M. Visscher, Ying Wang, Jing Guo, Michael E. Goddard, Longda Jiang, Loic Yengo, and Jian Yang

Subjects
Linkage disequilibrium, Science, Quantitative Trait Loci, Black People, Genome-wide association study, Biology, Genome-wide association studies, Polymorphism, Single Nucleotide, Article, Linkage Disequilibrium, White People, Body Mass Index, Genetic Heterogeneity, 03 medical and health sciences, Gene Frequency, Genetic variation, Humans, Human height, Allele frequency, Genetic association study, 030304 developmental biology, Genetic association, 2. Zero hunger, 0303 health sciences, Multidisciplinary, Genome, Human, Genetic heterogeneity, 030305 genetics & heredity, Models, Theoretical, Heritability, Body Height, Evolutionary biology, Medicine, Body mass index, Genome-Wide Association Study, Demography
Abstract

Genome-wide association studies (GWAS) in samples of European ancestry have identified thousands of genetic variants associated with complex traits in humans. However, it remains largely unclear whether these associations can be used in non-European populations. Here, we seek to quantify the proportion of genetic variation for a complex trait shared between continental populations. We estimated the between-population correlation of genetic effects at all SNPs ($$r_{g}$$ r g ) or genome-wide significant SNPs ($$r_{{g\left( {GWS} \right)}}$$ r g GWS ) for height and body mass index (BMI) in samples of European (EUR; $$n = 49,839$$ n = 49 , 839 ) and African (AFR; $$n = 17,426$$ n = 17 , 426 ) ancestry. The $$\hat{r}_{g}$$ r ^ g between EUR and AFR was 0.75 ($${\text{s}}.{\text{e}}. = 0.035$$ s . e . = 0.035 ) for height and 0.68 ($${\text{s}}.{\text{e}}. = 0.062$$ s . e . = 0.062 ) for BMI, and the corresponding $$\hat{r}_{{g\left( {GWS} \right)}}$$ r ^ g GWS was 0.82 ($${\text{s}}.{\text{e}}. = 0.030$$ s . e . = 0.030 ) for height and 0.87 ($${\text{s}}.{\text{e}}. = 0.064$$ s . e . = 0.064 ) for BMI, suggesting that a large proportion of GWAS findings discovered in Europeans are likely applicable to non-Europeans for height and BMI. There was no evidence that $$\hat{r}_{g}$$ r ^ g differs in SNP groups with different levels of between-population difference in allele frequency or linkage disequilibrium, which, however, can be due to the lack of power.

Published
2019
Full Text
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24. Bayesian analysis of GWAS summary data reveals differential signatures of natural selection across human complex traits and functional genomic categories

Author

Longda Jiang, Loic Yengo, Yang Wu, Peter M. Visscher, Michael E. Goddard, Luke R. Lloyd-Jones, Jian Yang, Huanwei Wang, Kathryn E. Kemper, Angli Xue, Jian Zeng, Zhili Zheng, and Naomi R. Wray

Subjects
0303 health sciences, Natural selection, Human evolutionary genetics, Bayesian probability, Genome-wide association study, Computational biology, Biology, Heritability, Genetic architecture, 03 medical and health sciences, Negative selection, 0302 clinical medicine, SNP, 030217 neurology & neurosurgery, 030304 developmental biology
Abstract

Understanding how natural selection has shaped the genetic architecture of complex traits and diseases is of importance in medical and evolutionary genetics. Bayesian methods have been developed using individual-level data to estimate multiple features of genetic architecture, including signatures of natural selection. Here, we present an enhanced method (SBayesS) that only requires GWAS summary statistics and incorporates functional genomic annotations. We analysed GWAS data with large sample sizes for 155 complex traits and detected pervasive signatures of negative selection with diverse estimates of SNP-based heritability and polygenicity. Projecting these estimates onto a map of genetic architecture obtained from evolutionary simulations revealed relatively strong natural selection on genetic variants associated with cardiorespiratory and cognitive traits and relatively small number of mutational targets for diseases. Averaging across traits, the joint distribution of SNP effect size and MAF varied across functional genomic regions (likely to be a consequence of natural selection), with enrichment in both the number of associated variants and the magnitude of effect sizes in regions such as transcriptional start sites, coding regions and 5’- and 3’-UTRs.

Published
2019

25. A resource-efficient tool for mixed model association analysis of large-scale data

Author

Peter M. Visscher, Jian Yang, Naomi R. Wray, Kathryn E. Kemper, Zhili Zheng, Ting Qi, and Longda Jiang

Subjects
Mixed model, Computer science, Sample (statistics), Genome-wide association study, Computational biology, Biology, Population stratification, Polymorphism, Single Nucleotide, Linkage Disequilibrium, Body Mass Index, 03 medical and health sciences, 0302 clinical medicine, Exome Sequencing, Statistics, Genetics, Humans, Spurious relationship, 11 Medical and Health Sciences, Biological Specimen Banks, 030304 developmental biology, Genetic association, 0303 health sciences, Models, Genetic, Confounding, Linear model, 06 Biological Sciences, Biobank, United Kingdom, Data Interpretation, Statistical, Principal component analysis, Linear Models, Software, 030217 neurology & neurosurgery, Genome-Wide Association Study, Developmental Biology
Abstract

The genome-wide association study (GWAS) has been widely used as an experimental design to detect associations between genetic variants and a phenotype. Two major confounding factors, population stratification and relatedness, could potentially lead to inflated GWAS test-statistics and thereby spurious associations. Mixed linear model (MLM)-based approaches can be used to account for sample structure. However, genome-wide association (GWA) analyses in biobank samples such as the UK Biobank (UKB) often exceed the capability of most existing MLM-based tools especially if the number of traits is large. Here, we developed an MLM-based tool (called fastGWA) that controls for population stratification by principal components and relatedness by a sparse genetic relationship matrix for GWA analyses of biobank-scale data. We demonstrated by extensive simulations that fastGWA is reliable, robust and highly resource-efficient. We then applied fastGWA to 2,173 traits on 456,422 array-genotyped and imputed individuals and 2,048 traits on 46,191 whole-exome-sequenced individuals in the UKB.

Published
2019

26. MOESM1 of Genotype-free demultiplexing of pooled single-cell RNA-seq

Author

Xu, Jun, Falconer, Caitlin, Nguyen, Quan, Crawford, Joanna, McKinnon, Brett, Mortlock, Sally, Senabouth, Anne, Andersen, Stacey, Chiu, Han, Longda Jiang, Palpant, Nathan, Yang, Jian, Mueller, Michael, Hewitt, Alex, PéBay, Alice, Montgomery, Grant, Powell, Joseph, and Coin, Lachlan

Abstract

Additional file 1 Figure S1. Illustration of presence absence matrices calculated on pooled and hashtagged scRNA-seq datasets. Figure S2. Illustration of presence absence matrices calculated on pooled fibroblast scRNA-seq datasets.

Published
2019
Full Text
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27. Publisher Correction: Genome-wide analyses of behavioural traits are subject to bias by misreports and longitudinal changes

Author

Jian Zeng, Peter M. Visscher, Jian Yang, Longda Jiang, Naomi R. Wray, Zhihong Zhu, and Angli Xue

Subjects
Multidisciplinary, Science, General Physics and Astronomy, Subject (documents), General Chemistry, Computational biology, Psychology, Genome, General Biochemistry, Genetics and Molecular Biology
Abstract

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-21294-1.

Published
2021

28. A meta-analysis of Italian and Estonian individuals shows an effect of common variants in

Author

Martina, Rosticci, Natalia, Pervjakova, Marika, Kaakinen, Arrigo F, Cicero, Arne P, Feufer, Letizia, Marullo, Reedik, Mägi, Krista, Fischer, Longda, Jiang, Sergio, D'Addato, Elisabetta, Rizzoli, Gianmichele, Massimo, Marina, Giovannini, Sabrina, Angelini, Patrizia, Hrelia, Chiara, Scapoli, Claudio, Borghi, and Inga, Prokopenko

Subjects
Adult, Estonia, Male, Genetic Variation, Kinesins, Cholesterol, LDL, Middle Aged, Polymorphism, Single Nucleotide, Young Adult, Cardiovascular Diseases, Apolipoprotein B-100, Humans, Female, Hydroxymethylglutaryl CoA Reductases
Published
2018

29. An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans

Author

Rob M. van Dam, Francis S. Collins, Konstantin Strauch, Raimund Erbel, Rafn Benediktsson, Philippe Froguel, Kyle J. Gaulton, Peter Donnelly, Torben Hansen, Longda Jiang, Lennart C. Karssen, Rona J. Strawbridge, David J. Hunter, Leena Kinnunen, Thomas Meitinger, Michael Stumvoll, Stéphane Cauchi, Ching-Ti Liu, Olga McLeod, Oluf Pedersen, Michael Boehnke, Denis Rybin, Karl Gertow, Tõnu Esko, Bernhard O. Boehm, Sonali Pechlivanis, Bo Isomaa, Anne U. Jackson, Clement Ma, Yingchang Lu, Nicola D. Kerrison, Ruth J. F. Loos, Caroline S. Fox, Chiara Scapoli, Jian'an Luan, Martina Müller-Nurasyid, Domenico Palli, Anke Tönjes, Natalie R. van Zuydam, Neil Robertson, Barbara Thorand, Natalia Pervjakova, Andrew R. Wood, Karin Leander, Unnur Thorsteinsdottir, Sara M. Willems, Karen L. Mohlke, Robert A. Scott, Markus M. Nöthen, Ulf de Faire, Qi Sun, Eric Boerwinkle, Roman Wennauer, Douglas M. Ruderfer, Marika Kaakinen, Nigel W. Rayner, Jaakko Tuomilehto, Nisa M. Maruthur, Richard N. Bergman, Janina S. Ried, Himanshu Chheda, Josée Dupuis, Juan Tajes-Fernandes, Steve E. Humphries, Reedik Mägi, Gonçalo R. Abecasis, B F Voight, David Couper, Cornelia M. van Duijn, Samuli Ripatti, Yeji Lee, Heikki A. Koistinen, Christian Dina, Andres Metspalu, Lu Qi, James S. Pankow, Han Chen, Damiano Baldassarre, Mattias Frånberg, Gerald Steinbach, Inga Prokopenko, Matthias Blüher, Jose C. Florez, Julia Meyer, Niels Grarup, Anders Hamsten, Valeriya Lyssenko, James B. Meigs, Pritam Chanda, Leif Groop, Sarah Edkins, Anubha Mahajan, Gunnar Sigurðsson, Marilyn C. Cornelis, Christian Gieger, Nancy L. Pedersen, Andrew T. Hattersley, Paul W. Franks, Nicholas J. Wareham, Stefan Gustafsson, Katharine R. Owen, Peter Kovacs, Andrew D. Johnson, Lori L. Bonnycastle, Tiinamaija Tuomi, Aurelio Barricarte Gurrea, Tune H. Pers, Eric J.G. Sijbrands, Phoenix Kwan, Emmi Tikkanen, Elisabeth M. van Leeuwen, Stéphane Lobbens, Claudia Langenberg, E. Eury, Thomas W. Mühleisen, Lewin Eisele, Veikko Salomaa, Satu Mӓnnistö, Christian Fuchsberger, Evelin Mihailov, David Altshuler, Timothy M. Frayling, Peter Almgren, Harald Grallert, Hans A. Kestler, Beverley Balkau, Erik Ingelsson, Colin N. A. Palmer, Yvonne T. van der Schouw, Michael Roden, Thomas Sparsø, Karl-Heinz Jöckel, Johan G. Eriksson, Inês Barroso, John D. Eicher, Bengt Sennblad, Bruna Gigante, Andrew D. Morris, Panagiotis Deloukas, Man Li, Allan Linneberg, Astradur B. Hreidarsson, Lars Lannfelt, Elena Tremoli, Liming Liang, Omri Gottesman, Letizia Marullo, Peter S. Chines, Kari Stefansson, Mark I. McCarthy, Andrew P. Morris, Erwin P. Bottinger, Augustine Kong, Torben Jørgensen, Tanya M. Teslovich, Frank B. Hu, Dorothée Thuillier, Peter Kraft, Heiner Boeing, Laura J. Scott, Gudmar Thorleifsson, Lars Lind, John R. B. Perry, Heather M. Stringham, Susanne Moebus, Valgerdur Steinthorsdottir, Cecilia M. Lindgren, Guillaume Charpentier, Eleftheria Zeggini, Leena Peltonen, Loic Yengo, Norman Klopp, Teresa Ferreira, Christian Theil Have, Marit E. Jørgensen, Epidemiology, Erasmus MC other, Internal Medicine, Luan, Jian'an [0000-0003-3137-6337], Perry, John [0000-0001-6483-3771], Barroso, Ines [0000-0001-5800-4520], Langenberg, Claudia [0000-0002-5017-7344], Wareham, Nicholas [0000-0003-1422-2993], Apollo - University of Cambridge Repository, Commission of the European Communities, and Wellcome Trust

Subjects
PROVIDES, 0301 basic medicine, SUSCEPTIBILITY LOCI, endocrine system diseases, Endocrinology, Diabetes and Metabolism, PATHOPHYSIOLOGY, European Continental Ancestry Group, Medizin, Genome-wide association study, Biology, Quantitative trait locus, Bioinformatics, White People, GENETIC ARCHITECTURE, NO, Endocrinology & Metabolism, 03 medical and health sciences, 0302 clinical medicine, SDG 3 - Good Health and Well-being, Diabetes Mellitus, Type 2, European Continental Ancestry Group, Gene Expression Regulation, Genetic Variation, Genome-Wide Association Study, Humans, Diabetes Mellitus, Internal Medicine, Journal Article, Glucose homeostasis, Humans, 1000 Genomes Project, Allele frequency, METAANALYSIS, 11 Medical and Health Sciences, RISK, Genetics, Science & Technology, RECEPTOR, DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Haplotype, Genetic Variation, nutritional and metabolic diseases, Genetic architecture, 030104 developmental biology, Diabetes Mellitus, Type 2, Gene Expression Regulation, RARE VARIANTS, LOW-FREQUENCY, Life Sciences & Biomedicine, Type 2, 030217 neurology & neurosurgery, Imputation (genetics), FASTING GLUCOSE, Genome-Wide Association Study
Abstract

To characterize type 2 diabetes (T2D)-associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel. Promising association signals were followed up in additional data sets (of 14,545 or 7,397 T2D case and 38,994 or 71,604 control subjects). We identified 13 novel T2D-associated loci (P < 5 × 10−8), including variants near the GLP2R, GIP, and HLA-DQA1 genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common single nucleotide variants. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion and in adipocytes, monocytes, and hepatocytes for insulin action–associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology.

Published
2017

30. MOESM3 of Genotype-free demultiplexing of pooled single-cell RNA-seq

Author

Xu, Jun, Falconer, Caitlin, Nguyen, Quan, Crawford, Joanna, McKinnon, Brett, Mortlock, Sally, Senabouth, Anne, Andersen, Stacey, Chiu, Han, Longda Jiang, Palpant, Nathan, Yang, Jian, Mueller, Michael, Hewitt, Alex, PéBay, Alice, Montgomery, Grant, Powell, Joseph, and Coin, Lachlan

Subjects
3. Good health
Abstract

Additional file 3 Review history.

31. MOESM3 of Genotype-free demultiplexing of pooled single-cell RNA-seq

Author

Xu, Jun, Falconer, Caitlin, Nguyen, Quan, Crawford, Joanna, McKinnon, Brett, Mortlock, Sally, Senabouth, Anne, Andersen, Stacey, Chiu, Han, Longda Jiang, Palpant, Nathan, Yang, Jian, Mueller, Michael, Hewitt, Alex, PéBay, Alice, Montgomery, Grant, Powell, Joseph, and Coin, Lachlan

Subjects
3. Good health
Abstract

Additional file 3 Review history.

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