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Most downloaded bioRxiv papers, since beginning of last month
in category genetics
4,357 results found. For more information, click each entry to expand.
10,211 downloads genetics
Eric W Stawiski, Devan Diwanji, Kushal Suryamohan, Ravi Gupta, Frederic A Fellouse, J. Fah Sathirapongsasuti, Jiang Liu, Ying-Ping Jiang, Aakrosh Ratan, Monika Mis, Devi Santhosh, Sneha Somasekar, Sangeetha Mohan, Sameer Phalke, Boney Kuriakose, Aju Antony, Jagath R Junutula, Stephan C. Schuster, Natalia Jura, Somasekar Seshagiri
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of coronavirus disease (COVID-19) that has resulted in a global pandemic. It is a highly contagious positive strand RNA virus and its clinical presentation includes severe to critical respiratory disease that appears to be fatal in ~3-5% of the cases. The viral spike (S) coat protein engages the human angiotensin-converting enzyme2 (ACE2) cell surface protein to invade the host cell. The SARS-CoV-2 S-protein has acquired mutations that increase its affinity to human ACE2 by ~10-15-fold compared to SARS-CoV S-protein, making it highly infectious. In this study, we assessed if ACE2 polymorphisms might alter host susceptibility to SARS-CoV-2 by affecting the ACE2 S-protein interaction. Our comprehensive analysis of several large genomic datasets that included over 290,000 samples representing >400 population groups identified multiple ACE2 protein-altering variants, some of which mapped to the S-protein-interacting ACE2 surface. Using recently reported structural data and a recent S-protein-interacting synthetic mutant map of ACE2, we have identified natural ACE2 variants that are predicted to alter the virus-host interaction and thereby potentially alter host susceptibility. In particular, human ACE2 variants S19P, I21V, E23K, K26R, T27A, N64K, T92I, Q102P and H378R are predicted to increase susceptibility. The T92I variant, part of a consensus NxS/T N-glycosylation motif, confirmed the role of N90 glycosylation in immunity from non-human CoVs. Other ACE2 variants K31R, N33I, H34R, E35K, E37K, D38V, Y50F, N51S, M62V, K68E, F72V, Y83H, G326E, G352V, D355N, Q388L and D509Y are putative protective variants predicted to show decreased binding to SARS-CoV-2 S-protein. Overall, ACE2 variants are rare, consistent with the lack of selection pressure given the recent history of SARS-CoV epidemics, however, are likely to play an important role in altering susceptibility to CoVs. ### Competing Interest Statement
4,361 downloads genetics
The emergence of the novel coronavirus SARS-CoV-2, which in humans is highly infectious and leads to the potentially fatal disease COVID-19, has caused tens of thousands of deaths and huge global disruption. The viral infection may also represent an existential threat to our closest living relatives, the nonhuman primates, many of which have already been reduced to small and endangered populations. The virus engages the host cell receptor, angiotensin‐converting enzyme‐2 (ACE2), through the receptor binding domain (RBD) on the spike protein. The contact surface of ACE2 displays amino acid residues that are critical for virus recognition, and variations at these critical residues are likely to modulate infection susceptibility across species. While infection studies have shown that rhesus macaques exposed to the virus develop COVID-19-like symptoms, the susceptibility of other nonhuman primates is unknown. Here, we show that all apes, including chimpanzees, bonobos, gorillas, and orangutans, and all African and Asian monkeys (catarrhines), exhibit the same set of twelve key amino acid residues as human ACE2. Monkeys in the Americas, and some tarsiers, lemurs and lorisoids, differ at significant contact residues, and protein modeling predicts that these differences should greatly reduce the binding affinity of the ACE2 for the virus, hence moderating their susceptibility for infection. Other lemurs are predicted to be closer to catarrhines in their susceptibility. Our study suggests that apes and African and Asian monkeys, as well as some lemurs are all likely to be highly susceptible to SARS-CoV-2, representing a critical threat to their survival. Urgent actions may be necessary to limit their exposure to humans. ### Competing Interest Statement The authors have declared no competing interest.
2,883 downloads genetics
As the COVID-19 outbreak spreads, there is a growing need for a compilation of conserved RNA genome regions in the SARS-CoV-2 virus along with their structural propensities to guide development of antivirals and diagnostics. Using sequence alignments spanning a range of betacoronaviruses, we rank genomic regions by RNA sequence conservation, identifying 79 regions of length at least 15 nucleotides as exactly conserved over SARS-related complete genome sequences available near the beginning of the COVID-19 outbreak. We then confirm the conservation of the majority of these genome regions across 739 SARS-CoV-2 sequences reported to date from the current COVID-19 outbreak, and we present a curated list of 30 ‘SARS-related-conserved’ regions. We find that known RNA structured elements curated as Rfam families and in prior literature are enriched in these conserved genome regions, and we predict additional conserved, stable secondary structures across the viral genome. We provide 106 ‘SARS-CoV-2-conserved-structured’ regions as potential targets for antivirals that bind to structured RNA. We further provide detailed secondary structure models for the 5’ UTR, frame-shifting element, and 3’ UTR. Last, we predict regions of the SARS-CoV-2 viral genome have low propensity for RNA secondary structure and are conserved within SARS-CoV-2 strains. These 59 ‘SARS-CoV-2-conserved-unstructured’ genomic regions may be most easily targeted in primer-based diagnostic and oligonucleotide-based therapeutic strategies.
2,535 downloads genetics
To date, a disease-causing mutation can be found in approximately 15-30% of families with hereditary breast and ovarian cancer and still more than half of the cases remain unsolved. Usually it is intended to perform genetic analyses in the family member with the most severe phenotype, which, however, is not always possible. Moreover, no standard criteria have been established to define the person who is most suitable for genetic testing within a family: the best index case . This study now establishes clinical selection criteria to identify the best index case in families with hereditary breast and ovarian cancer and analyses the impact on genetic testing. 130 patients who presented at our department from 2016 to 2018 were divided into two groups. In group A, genetic analyses were performed in the best index case (N = 98). In group B, at least one family member had a more severe phenotype compared to the person who was tested (N = 32). The mutation detection rate was significantly higher for group A compared to group B (64.3% vs. 32.0%, p = 0.034), even though there was no significant difference of calculated mutation carrier risks between these groups. Furthermore, the mutation detection rate in group A was notably higher compared to the results of previous studies. We conclude that the mutation detection rate in families with hereditary breast and ovarian cancer can be improved by identifying the best index case for genetic testing according to the clinical selection criteria reported here and suggest that these can be used as a guideline for genetic counseling.
1,966 downloads genetics
Ruth E Hanna, Mudra Hegde, Christian R Fagre, Peter C DeWeirdt, Annabel K Sangree, Zsofia Szegletes, Audrey Griffith, Marissa N Feeley, Kendall R Sanson, Yossef Baidi, Luke W Koblan, David R. Liu, James T Neal, John G Doench
Understanding the functional consequences of single-nucleotide variants is critical to uncovering the genetic underpinnings of diseases, but technologies to characterize variants are limiting. Here we leverage CRISPR-Cas9 cytosine base editors in pooled screens to scalably assay variants at endogenous loci in mammalian cells. We benchmark the performance of base editors in positive and negative selection screens and identify known loss-of-function mutations in BRCA1 and BRCA2 with high precision. To demonstrate the utility of base editor screens to probe small molecule-protein interactions, we conduct screens with BH3 mimetics and PARP inhibitors and identify point mutations that confer drug sensitivity or resistance. Finally, we create a library of 52,034 clinically-observed variants in 3,584 genes and conduct screens in the presence of cellular stressors, identifying loss-of-function variants in numerous DNA damage repair genes. We anticipate that this screening approach will be broadly useful to readily and scalably functionalize genetic variants. ### Competing Interest Statement
1,775 downloads genetics
Genome-wide association studies (GWAS) have been used to study the genetic basis of a wide variety of complex diseases and other traits. However, for most traits it remains difficult to interpret what genes and biological processes are impacted by the top hits. Here, as a contrast, we describe UK Biobank GWAS results for three molecular traits--urate, IGF-1, and testosterone--that are biologically simpler than most diseases, and for which we know a great deal in advance about the core genes and pathways. Unlike most GWAS of complex traits, for all three traits we find that most top hits are readily interpretable. We observe huge enrichment of significant signals near genes involved in the relevant biosynthesis, transport, or signaling pathways. We show how GWAS data illuminate the biology of variation in each trait, including insights into differences in testosterone regulation between females and males. Meanwhile, in other respects the results are reminiscent of GWAS for more-complex traits. In particular, even these molecular traits are highly polygenic, with most of the variance coming not from core genes, but from thousands to tens of thousands of variants spread across most of the genome. Given that diseases are often impacted by many distinct biological processes, including these three, our results help to illustrate why so many variants can affect risk for any given disease. ### Competing Interest Statement The authors have declared no competing interest.
1,570 downloads genetics
COVID-19 is prevalent in the elderly. Old individuals are more likely to develop pneumonia and respiratory failure due to alveolar damage, suggesting that lung senescence may increase the susceptibility to SARS-CoV-2 infection and replication. Considering that human coronavirus (HCoVs; SARS-CoV-2 and SARS-CoV) require host cellular factors for infection and replication, we analyzed Genotype-Tissue Expression (GTEx) data to test whether lung aging is associated with transcriptional changes in human protein-coding genes that potentially interact with these viruses. We found decreased expression of the gene tribbles homolog 3 (TRIB3) during aging in male individuals, and its protein was predicted to interact with HCoVs nucleocapsid protein and RNA-dependent RNA polymerase. Using publicly available lung single-cell data, we found TRIB3 expressed mainly in alveolar epithelial cells that express SARS-CoV-2 receptor ACE2. Functional enrichment analysis of age-related genes, in common with SARS-CoV-induced perturbations, revealed genes associated with the mitotic cell cycle and surfactant metabolism. Given that TRIB3 was previously reported to decrease virus infection and replication, the decreased expression of TRIB3 in aged lungs may help explain why older male patients are related to more severe cases of the COVID-19. Thus, drugs that stimulate TRIB3 expression should be evaluated as a potential therapy for the disease. ### Competing Interest Statement
1,532 downloads genetics
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a positive single-stranded RNA virus that causes a highly contagious Corona Virus Disease (COVID19). Entry of SARS-CoV-2 in human cells depends on binding of the viral spike (S) proteins to cellular receptor Angiotensin-converting enzyme 2 (ACE2) and on S-protein priming by host cell serine protease TMPRSS2. Recently, COVID19 has been declared pandemic by World Health Organization (WHO) yet high differences in disease outcomes across countries have been seen. We provide evidences to explain these population-level differences. One of the key factors of entry of the virus in host cells presumably is because of differential interaction of viral proteins with host cell proteins due to different genetic backgrounds. Based on our findings, we conclude that a higher expression of ACE2 is facilitated by natural variations, acting as Expression quantitative trait loci (eQTLs), with different frequencies in different populations. We suggest that high expression of ACE2 results in homo-dimerization, proving disadvantageous for TMPRSS2 mediated cleavage of ACE2; whereas, the monomeric ACE2 has higher preferential binding with SARS-CoV-2 S-Protein vis-a-vis its dimerized counterpart. Further, eQTLs in TMPRSS2 and natural structural variations in the gene may also result in differential outcomes towards priming of viral S-protein, a critical step for entry of the Virus in host cells. In addition, we suggest that several key host genes, like SLC6A19, ADAM17, RPS6, HNRNPA1, SUMO1, NACA, BTF3 and some other proteases as Cathepsins, might have a critical role. To conclude, understanding population specific differences in these genes may help in developing appropriate management strategies for COVID19 with better therapeutic interventions. Also read at: https://science.sciencemag.org/content/367/6485/1444/tab-e-letters RE: ACE2 Homodimerization Affects Binding of SARS-CoV-2 Spike Protein ### Competing Interest Statement
1,366 downloads genetics
The infection coronavirus disease 2019 (COVID-19) is caused by a virus classified as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). At cellular level, virus infection initiates with binding of viral particles to the host surface cellular receptor angiotensin converting enzyme 2 (ACE2). SARS-CoV-2 engages ACE2 as the entry receptor and employs the cellular serine protease 2 (TMPRSS2) for S protein priming. TMPRSS2 activity is essential for viral spread and pathogenesis in the infected host. Understanding how TMPRSS2 protein expression in the lung varies in the population could reveal important insights into differential susceptibility to influenza and coronavirus infections. Here, we systematically analyzed coding-region variants in TMPRSS2 and the eQTL variants, which may affect the gene expression, to compare the genomic characteristics of TMPRSS2 among different populations. Our findings suggest that the lung-specific eQTL variants may confer different susceptibility or response to SARS-CoV-2 infection from different populations under the similar conditions. In particular, we found that the eQTL variant rs35074065 is associated with high expression of TMPRSS2 but with a low expression of the interferon (IFN)-α/β-inducible gene, MX1, splicing isoform. Thus, these subjects could account for a more susceptibility either to viral infection or to a decrease in cellular antiviral response. ### Competing Interest Statement The authors have declared no competing interest.
1,220 downloads genetics
17 years after the SARS-CoV epidemic, the world is facing the COVID-19 pandemic. COVID-19 is caused by a coronavirus named SARS-CoV-2. Given the most optimistic projections estimating that it will take more than a year to develop a vaccine, our best short term strategy may lie in identifying virus-specific targets for small molecule interventions. All coronaviruses utilize a molecular mechanism called -1 PRF to control the relative expression of their proteins. Prior analyses of SARS-CoV revealed that it utilizes a structurally unique three-stemmed mRNA pseudoknot to stimulate high rates of -1 PRF, that it also harbors a -1 PRF attenuation element. Altering -1 PRF activity negatively impacts virus replication, suggesting that this molecular mechanism may be therapeutically targeted. Here we present a comparative analysis of the original SARS-CoV and SARS-CoV-2 frameshift signals. Structural analyses reveal that the core -1 PRF signal, composed of the U UUA AAC slippery site and three-stemmed mRNA pseudoknot is highly conserved. In contrast, the upstream attenuator hairpin is less well conserved. Functional assays revealed that both elements promote similar rates of -1 PRF and that silent coding mutations in the slippery site strongly ablate -1 PRF activity. We suggest that molecules that were previously identified as inhibiting SARS-CoV mediated -1 PRF may serve as lead compounds to counter the current pandemic.
1,214 downloads genetics
Zhe Liu, Huanying Zheng, Runyu Yuan, Mingyue Li, Huifang Lin, Jingju Peng, Qianlin Xiong, Jiufeng Sun, Baisheng Li, Jie Wu, Ruben J.G. Hulswit, Thomas A. Bowden, Andrew Rambaut, Nick Loman, OG Pybus, Changwen Ke, Jing Lu
Abstract Two notable features have been identified in the SARS-CoV-2 genome: (1) the receptor binding domain of SARS-CoV-2; (2) a unique insertion of twelve nucleotide or four amino acids (PRRA) at the S1 and S2 boundary. For the first feature, the similar RBD identified in SARs-like virus from pangolin suggests the RBD in SARS-CoV-2 may already exist in animal host(s) before it transmitted into human. The left puzzle is the history and function of the insertion at S1/S2 boundary, which is uniquely identified in SARS-CoV-2. In this study, we identified two variants from the first Guangdong SARS-CoV-2 cell strain, with deletion mutations on polybasic cleavage site (PRRAR) and its flank sites. More extensive screening indicates the deletion at the flank sites of PRRAR could be detected in 3 of 68 clinical samples and half of 22 in vitro isolated viral strains. These data indicate (1) the deletion of QTQTN, at the flank of polybasic cleavage site, is likely benefit the SARS-CoV-2 replication or infection in vitro but under strong purification selection in vivo since it is rarely identified in clinical samples; (2) there could be a very efficient mechanism for deleting this region from viral genome as the variants losing 23585-23599 is commonly detected after two rounds of cell passage. The mechanistic explanation for this in vitro adaptation and in vivo purification processes (or reverse) that led to such genomic changes in SARS-CoV-2 requires further work. Nonetheless, this study has provided valuable clues to aid further investigation of spike protein function and virus evolution. The deletion mutation identified in vitro isolation should be also noted for current vaccine development.
1,145 downloads genetics
Yu-Nong Gong, Kuo-Chien Tsao, Mei-Jen Hsiao, Chung-Guei Huang, Peng-Nien Huang, Po-Wei Huang, Kuo-Ming Lee, Yi-Chun Liu, Shu-Li Yang, Rei-Lin Kuo, Ming-Tsan Liu, Ji-Rong Yang, Cheng-Hsun Chiu, Cheng-Ta Yang, Shin-Ru Shih, Guang-Wu Chen
Taiwan experienced two waves of imported cases of coronavirus disease 2019 (COVID-19), first from China in January to late February, followed by those from other countries starting in early March. Additionally, several cases could not be traced to any imported cases and were suspected as sporadic local transmission. Twelve full viral genomes were determined in this study by Illumina sequencing either from virus isolates or directly from specimens, among which 5 originated from clustered infections. Phylogenetic tree analysis revealed that these sequences were in different clades, indicating that no major strain has been circulating in Taiwan. A deletion in open reading frame 8 was found in one isolate. Only a 4-nucleotide difference was observed among the 5 genomes from clustered infections.
1,040 downloads genetics
Rachel M Brouwer, Marieke Klein, Katrina L. Grasby, Hugo G. Schnack, Neda Jahanshad, Jalmar Teeuw, Sophia I Thomopoulos, Emma Sprooten, Carol E. Franz, Nitin Gogtay, William S. Kremen, Matthew S. Panizzon, Loes M. Olde Loohuis, Christopher D. Whelan, Moji Aghajani, Clara Alloza, Dag Alnæs, Eric Artiges, Rosa Ayesa-Arriola, Gareth J. Barker, Elisabet Blok, Erlend Bøen, Isabella A Breukelaar, Joanna K Bright, Elizabeth E. L. Buimer, Robin Bülow, Dara M. Cannon, Simone Ciufolini, Nicolas A Crossley, Christienne G. Damatac, Paola Dazzan, Casper L de Mol, Sonja M. C. de Zwarte, Sylvane Desrivières, Covadonga M. Díaz-Caneja, Nhat Trung Doan, Katharina Dohm, Juliane H. Fröhner, Janik Goltermann, Antoine Grigis, Dominik Grotegerd, Laura K M Han, Catharina A. Hartman, Sarah J. Heany, Walter Heindel, Dirk J. Heslenfeld, Sarah Hohmann, Bernd Ittermann, Philip R Jansen, Joost Janssen, Tianye Jia, Jiyang Jiang, Christiane Jockwitz, Temmuz Karali, Daniel Keeser, Martijn G. J. C. Koevoets, Rhoshel K Lenroot, Berend Malchow, René C. W. Mandl, Vicente Medel, Susanne Meinert, Catherine A Morgan, Thomas W. Mühleisen, Leila Nabulsi, Nils Opel, Víctor Ortiz-García de la Foz, Bronwyn J Overs, Marie-Laure Paillère Martinot, Erin B. Quinlan, Ronny Redlich, Tiago Reis Marques, Jonathan Repple, Gloria Roberts, Gennady V Roshchupkin, Nikita Setiaman, Elena Shumskaya, Frederike Stein, Gustavo Sudre, Shun Takahashi, Anbupalam Thalamuthu, Diana Tordesillas-Gutiérrez, Aad van der Lugt, Neeltje E. M. van Haren, Wei Wen, Henk-Jan Westeneng, Katharina Wittfeld, Andre Zugman, Nicola J. Armstrong, Janita Bralten, Shareefa Dalvie, Marta Di Forti, Linda Ding, Gary Donohoe, Andreas J. Forstner, Javier Gonzalez-Peñas, Joao P. O. F. T. Guimaraes, Georg Homuth, Jouke-Jan Hottenga, Maria J. Knol, John B. J. Kwok, Stephanie Le Hellard, Karen A. Mather, Yuri Milaneschi, Derek W. Morris, Markus M. Nöthen, Sergi Papiol, Marcella Rietschel, Marcos L Santoro, Vidar M. Steen, Jason L. Stein, Fabien Streit, Rick M Tankard, Alexander Teumer, Dennis van ’t Ent, Dennis van der Meer, Kristel R. van Eijk, Evangelos Vassos, Javier Vázquez-Bourgon, Stephanie H. Witt, Alzheimer’s Disease Neuroimaging Initiative, Hieab H. H. Adams, Ingrid Agartz, David Ames, Katrin Amunts, Ole A. Andreassen, C. Arango, Tobias Banaschewski, Bernhard T. Baune, Sintia I Belangero, Arun L. W. Bokde, Dorret I. Boomsma, Rodrigo A. Bressan, Henry Brodaty, Jan K Buitelaar, Wiepke Cahn, Svenja Caspers, Sven Cichon, Benedicto Crespo Facorro, Udo Dannlowski, Torbjørn Elvsåshagen, Thomas Espeseth, Peter G Falkai, Simon E Fisher, Herta Flor, Janice M. Fullerton, Hugh Garavan, Penny A. Gowland, Hans J Grabe, Tim Hahn, Andreas Heinz, Manon Hillegers, Jacqueline Hoare, Pieter J Hoekstra, Mohammad A Ikram, Andrea P Jackowski, Andreas Jansen, Erik G. Jönsson, Rene S Kahn, Tilo Kircher, Mayuresh S. Korgaonkar, Axel Krug, Herve Lemaitre, Ulrik F. Malt, Jean-Luc Martinot, Colm McDonald, Philip B Mitchell, Ryan L Muetzel, Robin M Murray, Frauke Nees, Igor Nenadic, Jaap Oosterlaan, Roel A. Ophoff, Pedro M Pan, Brenda W. J. H. Penninx, Luise Poustka, Perminder S Sachdev, Giovanni A. Salum, Peter R. Schofield, Gunter Schumann, Philip Shaw, Kang Sim, Michael N. Smolka, Dan J. Stein, Julian Trollor, Leonard H. van den Berg, Jan H. Veldink, Henrik Walter, Lars T. Westlye, R Whelan, Tonya White, Margaret J Wright, Joseph K. Pickrell, Barbara Franke, Paul M. Thompson, Hilleke E Hulshoff Pol
Human brain structure changes throughout our lives. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental, and neurodegenerative diseases. While heritable, specific loci in the genome that influence these rates are largely unknown. Here, we sought to find common genetic variants that affect rates of brain growth or atrophy, in the first genome-wide association analysis of longitudinal changes in brain morphology across the lifespan. Longitudinal magnetic resonance imaging data from 10,163 individuals aged 4 to 99 years, on average 3.5 years apart, were used to compute rates of morphological change for 15 brain structures. We discovered 5 genome-wide significant loci and 15 genes associated with brain structural changes. Most individual variants exerted age-dependent effects. All identified genes are expressed in fetal and adult brain tissue, and some exhibit developmentally regulated expression across the lifespan. We demonstrate genetic overlap with depression, schizophrenia, cognitive functioning, height, body mass index and smoking. Several of the discovered loci are implicated in early brain development and point to involvement of metabolic processes. Gene-set findings also implicate immune processes in the rates of brain changes. Taken together, in the world's largest longitudinal imaging genetics dataset we identified genetic variants that alter age-dependent brain growth and atrophy throughout our lives. ### Competing Interest Statement BF has received speaking fees from MEDICE Arzneimittel Pütter GmbH & Co. BWJHP has received research funding from Jansen Research and Boehringer Ingelheim. CA has been a consultant to or has received honoraria or grants from Acadia, Angelini, Gedeon Richter, Janssen Cilag, Lundbeck, Minerva, Otsuka, Roche, Sage, Servier, Shire, Schering Plough, Sumitomo Dainippon Pharma, Sunovion and Takeda. CDW is an employee of Biogen Inc. DJS has received research grants and/or consultancy honoraria from Lundbeck and Sun. GJB receives honoraria for teaching from GE Healthcare. HB is on the Advisory Board Nutricia Australia. HEH has received travel fees for membership of the Steering Committee of the Lundbeck Foundation Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research and for two presentations from Philips. These concerned activities unrelated to the submitted work. HJG has received travel grants and speaker's honoraria from Fresenius Medical Care, Neuraxpharm, Servier and Janssen Cilag as well as research funding from Fresenius Medical Care. LP has served as an advisor or consultant to Shire, Takeda and Roche. She has received speaking fees from Shire and Infectopharm. The present work is unrelated to these relationships. MHJ received grant support from the Brain and behavior Foundation (NARSAD) Independent Investigator grant number 20244. MMN has received fees for memberships in Scientific Advisory Boards from the Lundbeck Foundation and the Robert-Bosch-Stiftung, and for membership in the Medical-Scientific Editorial Office of the Deutsches Ärzteblatt. MMN was reimbursed travel expenses for a conference participation by Shire Deutschland GmbH. MMN receives salary payments from Life & Brain GmbH and holds shares in Life & Brain GmbH. All these concerned activities outside the submitted work. NJ and PMT are MPI's of a research grant from Biogen, Inc (Boston, USA) for work unrelated to the contents of this manuscript. OAA has received Speaker's honorarium from Lundbeck, Consultant for HealthLytix. PSS reports on-off payment for an advisory board meeting of Biogen. TB served in an advisory or consultancy role for Lundbeck, Medice, Neurim Pharmaceuticals, Oberberg GmbH, Shire, and Infectopharm. He received conference support or speaker's fee by Lilly, Medice, and Shire. He received royalties from Hogrefe, Kohlhammer, CIP Medien, Oxford University Press; the present work is unrelated to these relationships. TEl has received speaker's fee from Lundbeck AS. TRM has received honoraria for speaking and chairing engagements from Lundbeck, Janssen and Astellas.
1,031 downloads genetics
There appears to be large regional variations for susceptibility, severity and mortality for Covid-19 infections. We set out to examine genetic differences in the human angiotensin-converting enzyme 2 (hACE2) gene, as its receptor serves as a cellular entry for SARS-CoV-2. By comparing 56,885 Non-Finnish European and 9,197 East Asians (including 1,909 Koreans) four missense mutations were noted in the hACE2 gene. Molecular dynamic demonstrated that two of these variants (K26R and I468V) may affect binding characteristics between S protein of the virus and hACE2 receptor. We also examined hACE2 gene expression in eight global populations from the HapMap3 and noted marginal differences in expression for some populations as compared to the Chinese population. However, for both of our studies, the magnitude of the difference was small and the significance is not clear in the absence of further in vitro and functional studies. ### Competing Interest Statement The authors have declared no competing interest.
958 downloads genetics
Lasse Folkersen, Stefan Gustafsson, Qin Wang, Daniel Hvidberg Hansen, Åsa K. Hedman, Andrew Schork, Karen Page, Daria V. Zhernakova, Yang Wu, James Peters, Niclas Ericsson, Sarah E Bergen, Thibaud Boutin, Andrew D. Bretherick, Stefan Enroth, Anettne Kalnapenkis, Jesper R Gådin, Bianca Suur, Yan Chen, Ljubica Matic, Jeremy D Gale, Julie Lee, Weidong Zhang, Amira Quazi, Mika Ala-Korpela, Seung Hoan Choi, Annique Claringbould, John Danesh, George Davey-Smith, Federico de Masi, Sölve Elmståhl, Gunnar Engström, Eric Fauman, Celine Fernandez, Matthijs Moed, Paul Franks, Vilmantas Giedraitis, Chris Haley, Anders Hamsten, Andres Ingason, Åsa Johansson, Peter K. Joshi, Lars Lind, Cecilia M. Lindgren, Steven Lubitz, Tom Palmer, Erin Macdonald-Dunlop, Martin Magnusson, Olle Melander, Karl Michaelsson, Andrew P Morris, Reedik Mägi, Michael Nagle, Peter M Nilsson, Jan Nilsson, Marju Orho-Melander, Ozren Polasek, Bram Prins, Erik Pålsson, Ting Qi, Marketa Sjögren, Johan Sundström, Praveen Surendran, Urmo Võsa, Thomas Werge, Rasmus Wernersson, Harm-Jan Westra, Jian Yang, Alexandra Zhernakova, Johan Ärnlöv, Jingyuan Fu, Gustav Smith, Tonu Esko, Caroline Hayward, Ulf Gyllensten, Mikael Landen, Agneta Siegbahn, Jim F Wilson, Lars Wallentin, Adam S. Butterworth, Michael V Holmes, Erik Ingelsson, Anders Mälarstig
Circulating proteins are vital in human health and disease and are frequently used as biomarkers for clinical decision-making or as targets for pharmacological intervention. By mapping and replicating protein quantitative trait loci (pQTL) for 90 cardiovascular proteins in over 30,000 individuals, we identified 467 pQTLs for 85 proteins. The pQTLs were used in combination with other sources of information to evaluate known drug targets, and suggest new target candidates or repositioning opportunities, underpinned by a) causality assessment using Mendelian randomization, b) pathway mapping using trans-pQTL gene assignments, and c) protein-centric polygenic risk scores enabling matching of plausible target mechanisms to sub-groups of individuals enabling precision medicine.
851 downloads genetics
Francois Aguet, Alvaro N. Barbeira, Rodrigo Bonazzola, Andrew Brown, Stephane E. Castel, Brian Jo, Silva Kasela, Sarah Kim-Hellmuth, Yanyu Liang, Meritxell Oliva, Princy E Parsana, Elise Flynn, Laure Fresard, Eric R Gaamzon, Andrew R Hamel, Yuan He, Farhad Hormozdiari, Pejman Mohammadi, Manuel Muñoz-Aguirre, YoSon Park, Ashis Saha, Ayellet V Segrć, Benjamin J. Strober, Xiaoquan Wen, Valentin Wucher, Sayantan Das, Diego Garrido-Martín, Nicole R. Gay, Robert E Handsaker, Paul Hoffman, Seva Kashin, Alan Kwong, Xiao Li, Daniel MacArthur, John M Rouhana, Matthew Stephens, Ellen Todres, Ana Viñuela, Gao Wang, Yuxin Zou, The GTEx Consortium, Christopher D Brown, Nancy Cox, Emmanouil Dermitzakis, Barbara Engelhardt, Gad Getz, Roderic Guigo, Stephen B. Montgomery, Barbara E. Stranger, Hae Kyung Im, Alexis Battle, Kristin G. Ardlie, Tuuli Lappalainen
The Genotype-Tissue Expression (GTEx) project was established to characterize genetic effects on the transcriptome across human tissues, and to link these regulatory mechanisms to trait and disease associations. Here, we present analyses of the v8 data, based on 17,382 RNA-sequencing samples from 54 tissues of 948 post-mortem donors. We comprehensively characterize genetic associations for gene expression and splicing in cis and trans, showing that regulatory associations are found for almost all genes, and describe the underlying molecular mechanisms and their contribution to allelic heterogeneity and pleiotropy of complex traits. Leveraging the large diversity of tissues, we provide insights into the tissue-specificity of genetic effects, and show that cell type composition is a key factor in understanding gene regulatory mechanisms in human tissues.
792 downloads genetics
Polygenic scores have become a central tool in human genetics research. LDpred is a popular and powerful method for deriving polygenic scores based on summary statistics and a matrix of correlation between genetic variants. However, LDpred has limitations that may result in limited predictive performance. Here we present LDpred2, a new version of LDpred that addresses these issues. We also provide two new options in LDpred2: a "sparse" option that can learn effects that are exactly 0, and an "auto" option that directly learns parameters from data. We benchmark LDpred2 against the previous version on simulated and real data, demonstrating substantial improvements in robustness and efficiency, as well as providing much more accurate polygenic scores. LDpred2 is implemented in R package bigsnpr. ### Competing Interest Statement The authors have declared no competing interest.
728 downloads genetics
Nicola Pirastu, Mattia Cordioli, Priyanka Nandakumar, Gianmarco Mignogna, Abdel Abdellaoui, Benjamin Hollis, Masahiro Kanai, Veera M. Rajagopal, Pietro Della Briotta Parolo, Nikolas Baya, Caitlin Carey, Juha Karjalainen, Thomas D Als, Matthijs D. Van der Zee, Felix R. Day, Ken K. Ong, Finngen Study, Me Research Team, Consortium iPSYCH, Takayuki Morisaki, Eco de Geus, Rino Bellocco, Yukinori Okada, Anders D. Børglum, Peter K. Joshi, Adam Auton, David A. Hinds, Benjamin M Neale, Raymond K Walters, Michel G. Nivard, John R.B. Perry, Andrea Ganna
Genetic association results are often interpreted with the assumption that study participation does not affect downstream analyses. Understanding the genetic basis of this participation bias is challenging as it requires the genotypes of unseen individuals. However, we demonstrate that it is possible to estimate comparative biases by performing GWAS contrasting one subgroup versus another. For example, we show that sex exhibits autosomal heritability in the presence of sex-differential participation bias. By performing a GWAS of sex in ~3.3 million males and females, we identify over 150 autosomal loci significantly associated with sex and highlight complex traits underpinning differences in study participation between sexes. For example, the body mass index (BMI) increasing allele at the FTO locus was observed at higher frequency in males compared to females (OR 1.02 [1.02-1.03], P=4.4x10-36). Finally, we demonstrate how these biases can potentially lead to incorrect inferences in downstream analyses and propose a conceptual framework for addressing such biases. Our findings highlight a new challenge that genetic studies may face as sample sizes continue to grow.
726 downloads genetics
SARS-CoV-2 invades host cells via an endocytic pathway that begins with the interaction of the SARS-CoV-2 Spike glycoprotein (S-protein) and human Angiotensin-converting enzyme 2 (ACE2). Genetic variability in ACE2 may be one factor that mediates the broad-spectrum severity of SARS-CoV-2 infection and COVID-19 outcomes. We investigated the capacity of ACE2 variation to influence SARS-CoV-2 infection with a focus on predicting the effect of missense variants on the ACE2 SARS-CoV-2 S-protein interaction. We validated the mCSM-PPI2 variant effect prediction algorithm with 26 published ACE2 mutant SARS-CoV S-protein binding assays and found it performed well in this closely related system (True Positive Rate = 0.7, True Negative Rate = 1). Application of mCSM-PPI2 to ACE2 missense variants from the Genome Aggregation Consortium Database (gnomAD) identified three that are predicted to strongly inhibit or abolish the S-protein ACE2 interaction altogether (p.Glu37Lys, p.Gly352Val and p.Asp355Asn) and one that is predicted to promote the interaction (p.Gly326Glu). The S-protein ACE2 inhibitory variants are expected to confer a high degree of resistance to SARS-CoV-2 infection whilst the S-protein ACE2 affinity enhancing variant may lead to additional susceptibility and severity. We also performed in silico saturation mutagenesis of the S-protein ACE2 interface and identified a further 38 potential missense mutations that could strongly inhibit binding and one more that is likely to enhance binding (Thr27Arg). A conservative estimate places the prevalence of the strongly protective variants between 12-70 per 100,000 population but there is the possibility of higher prevalence in local populations or those underrepresented in gnomAD. The probable interplay between these ACE2 affinity variants and ACE2 expression polymorphisms is highlighted as well as gender differences in penetrance arising from ACE2's situation on the X-chromosome. It is also described how our data can help power future genetic association studies of COVID-19 phenotypes and how the saturation mutant predictions can help design a mutant ACE2 with tailored S-protein affinity, which may be an improvement over a current recombinant ACE2 that is undergoing clinical trial. ### Competing Interest Statement The authors have declared no competing interest.
717 downloads genetics
A major constraint on the evolution of large body sizes in animals is an increased risk of developing cancer. There is no correlation, however, between body size and cancer risk. This lack of correlation is often referred to as "Peto′s Paradox". Here we show that the elephant genome encodes 20 copies of the tumor suppressor gene TP53 and that the increase in TP53 copy number occurred coincident with the evolution of large body sizes in the elephant (Proboscidean) lineage. Furthermore we show that several of the TP53 retrogenes are transcribed and translated and contribute to an enhanced sensitivity of elephant cells to DNA damage and the induction of apoptosis via a hyperactive TP53 signaling pathway. These results suggest that an increase in the copy number of TP53 may have played a direct role in the evolution of very large body sizes and the resolution of Peto′s paradox in Proboscideans.
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