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Rxivist combines biology preprints from bioRxiv and medRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 125,163 papers from 537,495 authors.

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in category genetic and genomic medicine

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1: Full genome viral sequences inform patterns of SARS-CoV-2 spread into and within Israel
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Posted 22 May 2020

Full genome viral sequences inform patterns of SARS-CoV-2 spread into and within Israel
11,992 downloads medRxiv genetic and genomic medicine

Danielle Miller, Michael A. Martin, Noam Harel, Talia Kustin, Omer Tirosh, Moran Meir, Nadav Sorek, Shiraz Gefen-Halevi, Sharon Amit, Olesya Vorontsov, Dana Wolf, Avi Peretz, Yonat Shemer-Avni, Diana Roif-Kaminsky, Na'ama Kopelman, Amit Huppert, Katia Koelle, Adi Stern

Full genome sequences are increasingly used to track the geographic spread and transmission dynamics of viral pathogens. Here, with a focus on Israel, we sequenced 212 SARS-CoV-2 sequences and use them to perform a comprehensive analysis to trace the origins and spread of the virus. A phylogenetic analysis including thousands of globally sampled sequences allowed us to infer multiple independent introductions into Israel, followed by local transmission. Returning travelers from the U.S. contributed dramatically more to viral spread relative to their proportion in incoming infected travelers. Using phylodynamic analysis, we estimated that the basic reproduction number of the virus was initially around ~2.0-2.6, dropping by two-thirds following the implementation of social distancing measures. A comparison between reported and model-estimated case numbers indicated high levels of transmission heterogeneity in SARS-CoV-2 spread, with between 1-10% of infected individuals resulting in 80% of secondary infections. Overall, our findings underscore the ability of this virus to efficiently transmit between and within countries, as well as demonstrate the effectiveness of social distancing measures for reducing its spread.

2: ACE2 Expression is Increased in the Lungs of Patients with Comorbidities Associated with Severe COVID-19
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Posted 27 Mar 2020

ACE2 Expression is Increased in the Lungs of Patients with Comorbidities Associated with Severe COVID-19
11,266 downloads medRxiv genetic and genomic medicine

Bruna G.G. Pinto, Antonio E.R. Oliveira, Youvika Singh, Leandro Jimenez, Andre N A. Gonçalves, Rodrigo L.T. Ogava, Rachel Creighton, Jean Pierre Schatzmann Peron, Helder Takashi Imoto Nakaya

The pandemic caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS- CoV-2) has resulted in several thousand deaths worldwide in just a few months. Patients who died from Coronavirus disease 2019 (COVID-19) often had comorbidities, such as hypertension, diabetes, and chronic obstructive lung disease. The angiotensin-converting enzyme 2 (ACE2) was identified as a crucial factor that facilitates SARS-CoV2 to bind and enter host cells. To date, no study has assessed the ACE2 expression in the lungs of patients with these diseases. Here, we analyzed over 700 lung transcriptome samples of patients with comorbidities associated with severe COVID-19 and found that ACE2 was highly expressed in these patients, compared to control individuals. This finding suggests that patients with such comorbidities may have higher chances of developing severe COVID-19. We also found other genes, such as RAB1A, that can be important for SARS-CoV-2 infection in the lung. Correlation and network analyses revealed many potential regulators of ACE2 in the human lung, including genes related to histone modifications, such as HAT1, HDAC2, and KDM5B. In fact, epigenetic marks found in ACE2 locus were compatible to with those promoted by KDM5B. Our systems biology approach offers a possible explanation for increase of COVID-19 severity in patients with certain comorbidities.

3: Self-reported symptoms of covid-19 including symptoms most predictive of SARS-CoV-2 infection, are heritable
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Posted 24 Apr 2020

Self-reported symptoms of covid-19 including symptoms most predictive of SARS-CoV-2 infection, are heritable
11,106 downloads medRxiv genetic and genomic medicine

Frances MK Williams, Maxim Freydin, Massimo Mangino, Simon Couvreur, Alessia Visconti, Ruth C. Bowyer, Caroline I. Le Roy, Mario Falchi, Carole H. Sudre, Richard Davies, Christopher Hammond, Cristina Menni, Claire J. Steves, Timothy Spector

Susceptibility to infection such as SARS-CoV-2 may be influenced by host genotype. TwinsUK volunteers (n=2633) completing the C-19 Covid symptom tracker app allowed classical twin studies of covid-19 symptoms including predicted covid-19, a symptom-based algorithm predicting true infection derived in app users tested for SARS-CoV-2. We found heritability for fever = 41 (95% confidence intervals 12-70)%; anosmia 47 (27-67)%; delirium 49 (24-75)%; and predicted covid-19 gave heritability = 50 (29-70)%.

4: ACE2 and TMPRSS2 variants and expression as candidates to sex and country differences in COVID-19 severity in Italy
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Posted 02 Apr 2020

ACE2 and TMPRSS2 variants and expression as candidates to sex and country differences in COVID-19 severity in Italy
10,475 downloads medRxiv genetic and genomic medicine

Rosanna Asselta, Elvezia Maria Paraboschi, Alberto Mantovani, Stefano Duga

BackgroundAs the outbreak of coronavirus disease 2019 (COVID-19) progresses, prognostic markers for early identification of high-risk individuals are an urgent medical need. Italy has the highest rate of SARS-CoV-2 infection, the highest number of deaths, and the highest mortality rate among large countries. Worldwide, a more severe course of COVID-19 is associated with older age, comorbidities, and male sex. Hence, we searched for possible genetic components of the peculiar severity of COVID-19 among Italians, by looking at expression levels and variants in ACE2 and TMPRSS2 genes, which are crucial for viral infection. MethodsExome and SNP array data from a large Italian cohort representative of the countrys population were used to compare the burden of rare variants and the frequency of polymorphisms with European and East Asian populations. Moreover, we looked into gene expression databases to check for sex-unbalanced expression. ResultsWhile we found no significant evidence that ACE2 is associated with disease severity/sex bias in the Italian population, TMPRSS2 levels and genetic variants proved to be possible candidate disease modulators, contributing to the observed epidemiological data among Italian patients. ConclusionsOur analysis suggests a role for TMPRSS2 variants and expression levels in modulating COVID-19 severity, a hypothesis that fosters a rapid experimental validation on large cohorts of patients with different clinical manifestations.

5: ACE2 variants underlie interindividual variability and susceptibility to COVID-19 in Italian population
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Posted 06 Apr 2020

ACE2 variants underlie interindividual variability and susceptibility to COVID-19 in Italian population
10,112 downloads medRxiv genetic and genomic medicine

Elisa Benetti, Rossella Tita, Ottavia Spiga, Andrea Ciolfi, Giovanni Birolo, Alessandro Bruselles, Gabriella Doddato, Annarita Giliberti, Cterina Marconi, Francesco Musacchia, Tommaso Pippucci, Annalaura Torella, Alfonso Trezza, Floriana Valentino, Mrgherita Baldassarri, Alfredo Brusco, Rosanna Asselta, Bruttini Mirella, Simone Furini, Marco Seri, Vincenzo Nigro, Giuseppe Matullo, M. Tartaglia, Francesca Mari, Alessandra Renieri, Annamaria Pinto

In December 2019, an initial cluster of unexpected interstitial bilateral pneumonia emerged in Wuhan, Hubei province. A human-to-human transmission was immediately assumed and a previously unrecognized entity, termed coronavirus disease 19 (COVID- 19) due to a novel coronavirus (2019-nCov) was suddenly described. The infection has rapidly spread out all over the world and Italy has been the first European Country experiencing the endemic wave with unexpected clinical severity in comparison with Asian countries. It has recently been shown that 2019-nCov utilizes host receptors namely angiotensin converting enzyme 2 (ACE2) as host receptor and host proteases for cell surface binding and internalization. Thus, a predisposing genetic background can give reason for interindividual disease susceptibility and/or severity. Taking advantage of the Network of Italian Genomes (NIG), here we mined around 7000 exomes from 5 different Centers looking for ACE2 variants. A number of variants with a potential impact on protein stability were identified. Among these, three missense changes, p.Asn720Asp, p.Lys26Arg, p.Gly211Arg (MAF 0.002 to 0.015), which have never been reported in the Eastern Asia population, were predicted to interfere with protein u and stabilization. Rare truncating variants likely interfering with the internalization process and one missense variant, p.Trp69Cys, predicted to interfere with 2019-nCov spike protein binding were also observed. These findings suggest that a predisposing genetic background may contribute to the observed inter-individual clinical variability associated with COVID-19. They allow an evidence-based risk assessment opening up the way to personalized preventive measures and therapeutic options.

6: Polygenic background modifies penetrance of monogenic variants conferring risk for coronary artery disease, breast cancer, or colorectal cancer
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Posted 29 Nov 2019

Polygenic background modifies penetrance of monogenic variants conferring risk for coronary artery disease, breast cancer, or colorectal cancer
7,666 downloads medRxiv genetic and genomic medicine

Akl C. Fahed, Minxian Wang, Julian R Homburger, Aniruddh P. Patel, Alexander G. Bick, Cynthia L. Neben, Carmen Lai, Deanna Brockman, Anthony Philippakis, Patrick T. Ellinor, Christopher A. Cassa, Matthew Lebo, Kenney Ng, Eric S Lander, Alicia Y. Zhou, Sekar Kathiresan, Amit V Khera

BackgroundGenetic variation can predispose to disease both through (i) monogenic risk variants in specific genes that disrupt a specific physiologic pathway and have a large effect on disease risk and (ii) polygenic risk that involves large numbers of variants of small effect that affect many different pathways. Few studies have explored the interaction between monogenic risk variants and polygenic risk. MethodsWe identified monogenic risk variants and calculated polygenic scores for three diseases, coronary artery disease, breast cancer, and colorectal cancer, in three study populations -- case-control cohorts for coronary artery disease (UK Biobank; N=12,879) and breast cancer (Color Genomics; N=19,264), and an independent cohort of 49,738 additional UK Biobank participants. ResultsIn the coronary artery disease case-control cohort, increased risk for carriers of a monogenic variant ranged from 1.3-fold for those in the lowest polygenic score quintile to 12.6-fold for those in the highest. For breast cancer, increased risk ranged from 2.4 to 6.9-fold across polygenic score quintiles. Among the 49,738 UK Biobank participants who carried a monogenic risk variant, the probability of disease at age 75 years was strongly modified by polygenic risk. Across individuals in the lowest to highest percentiles of polygenic risk, the probability of disease ranged from 17% to 78% for coronary artery disease; 13% to 76% for breast cancer; and 11% to 80% for colon cancer. ConclusionsFor three important genomic conditions, polygenic risk powerfully modifies the risk conferred by monogenic risk variants.

7: Analysis of Genetic Host Response Risk Factors in Severe COVID-19 Patients
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Posted 19 Jun 2020

Analysis of Genetic Host Response Risk Factors in Severe COVID-19 Patients
4,383 downloads medRxiv genetic and genomic medicine

Krystyna Taylor, Sayoni Das, Matthew Pearson, James Kozubek, Marcin Pawlowski, Claus Erik Jensen, Zbigniew Skowron, Gert Lykke Møller, Mark Strivens, Steve Gardner

BACKGROUND Epidemiological studies indicate that as many as 20% of individuals who test positive for COVID-19 develop severe symptoms that can require hospitalization. These symptoms include low platelet count, severe hypoxia, increased inflammatory cytokines and reduced glomerular filtration rate. Additionally, severe COVID-19 is associated with several chronic co-morbidities, including cardiovascular disease, hypertension and type 2 diabetes mellitus. The identification of genetic risk factors that impact differential host responses to SARS-CoV-2, resulting in the development of severe COVID-19, is important in gaining greater understanding into the biological mechanisms underpinning life-threatening responses to the virus. These insights could be used in the identification of high-risk individuals and for the development of treatment strategies for these patients. METHODS As of June 6, 2020, there were 976 patients who tested positive for COVID-19 and were hospitalized, indicating they had a severe response to SARS-CoV-2. There were however too few patients with a mild form of COVID-19 to use this cohort as our control population. Instead we used similar control criteria to our previous study looking at shared genetic risk factors between severe COVID-19 and sepsis, selecting controls who had not developed sepsis despite having maximum co-morbidity risk and exposure to sepsis-causing pathogens. RESULTS Using a combinatorial (high-order epistasis) analysis approach, we identified 68 protein-coding genes that were highly associated with severe COVID-19. At the time of analysis, nine of these genes have been linked to differential response to SARS-CoV-2. We also found many novel targets that are involved in key biological pathways associated with the development of severe COVID-19, including production of pro-inflammatory cytokines, endothelial cell dysfunction, lipid droplets, neurodegeneration and viral susceptibility factors. CONCLUSION The variants we found in genes relating to immune response pathways and cytokine production cascades, were in equal proportions across all severe COVID-19 patients, regardless of their co-morbidities. This suggests that such variants are not associated with any specific co-morbidity, but are common amongst patients who develop severe COVID-19. Among the 68 severe COVID-19 risk-associated genes, we found several druggable protein targets and pathways. Nine are targeted by drugs that have reached at least Phase I clinical trials, and a further eight have active chemical starting points for novel drug development. Several of these targets were particularly enriched in specific co-morbidities, providing insights into shared pathological mechanisms underlying both the development of severe COVID-19, ARDS and these predisposing co-morbidities. We can use these insights to identify patients who are at greatest risk of contracting severe COVID-19 and develop targeted therapeutic strategies for them, with the aim of improving disease burden and survival rates.

8: Reversal of Epigenetic Age with Diet and Lifestyle in a Pilot Randomized Clinical Trial
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Posted 14 Jul 2020

Reversal of Epigenetic Age with Diet and Lifestyle in a Pilot Randomized Clinical Trial
3,388 downloads medRxiv genetic and genomic medicine

Kara Fitzgerald, Romilly Hodges, Douglas Hanes, Emily Stack, David Cheishvili, Moshe Szyf, Janine Henkel, Melissa Twedt, Despina Giannopoulou, Josette Herdell, Sally Logan, Ryan Bradley

Manipulations to set back biological age and extend lifespan in animal models are well established, and translation to humans has begun. The length of human life makes it impractical to evaluate results by plotting mortality curves, so surrogate markers of age have been suggested and, at present, the best established surrogates are DNA methylation clocks. Herein we report on a randomized, controlled clinical trial designed to be a first step in evaluating the effect of a diet and lifestyle intervention on biological age. Compared to participants in the control group (n=20), participants in the treatment group tested an average 3.23 years younger at the end of the eight-week program according to the Horvath DNAmAge clock (p=0.018). Those in the treatment group (n=18) tested an average 1.96 years younger at the end of the program compared to the same individuals at the beginning with a strong trend towards significance (p=0.066 for within group change). This is the first such trial to demonstrate a potential reversal of biological age. In this study, the intervention was confined to diet and lifestyle changes previously identified as safe to use. The prescribed program included multiple components with documented mechanistic activity on epigenetic pathways, including moderate exercise, breathing exercises for stress, and a diet rich in methyl donor nutrients and polyphenols.

9: Mapping genomic loci prioritises genes and implicates synaptic biology in schizophrenia
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Posted 13 Sep 2020

Mapping genomic loci prioritises genes and implicates synaptic biology in schizophrenia
3,075 downloads medRxiv genetic and genomic medicine

Schizophrenia Working Group of the Psychiatric Genomics Consortium, Stephan Ripke, James T. R. Walters, Michael C. O’Donovan

Schizophrenia is a psychiatric disorder whose pathophysiology is largely unknown. It has a heritability of 60-80%, much of which is attributable to common risk alleles, suggesting genome-wide association studies can inform our understanding of aetiology. Here, in 69,369 people with schizophrenia and 236,642 controls, we report common variant associations at 270 distinct loci. Using fine-mapping and functional genomic data, we prioritise 19 genes based on protein-coding or UTR variation, and 130 genes in total as likely to explain these associations. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in autism and developmental disorder. Associations were concentrated in genes expressed in CNS neurons, both excitatory and inhibitory, but not other tissues or cell types, and implicated fundamental processes related to neuronal function, particularly synaptic organisation, differentiation and transmission. We identify biological processes of pathophysiological relevance to schizophrenia, show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders, and provide a rich resource of priority genes and variants to advance mechanistic studies.

10: Genome-wide meta-analysis, fine-mapping, and integrative prioritization identify new Alzheimer's disease risk genes
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Posted 27 Jan 2020

Genome-wide meta-analysis, fine-mapping, and integrative prioritization identify new Alzheimer's disease risk genes
2,693 downloads medRxiv genetic and genomic medicine

Jeremy Schwartzentruber, Sarah Cooper, Jimmy Z Liu, Inigo Barrio-Hernandez, Erica Bello, Natsuhiko Kumasaka, Toby Johnson, Karol Estrada, Daniel J. Gaffney, Pedro Beltrao, Andrew Bassett

Genome-wide association studies (GWAS) have discovered numerous genomic loci associated with Alzheimers disease (AD), yet the causal genes and variants remain incompletely identified. We performed an updated genome-wide AD meta-analysis, which identified 37 risk loci, including novel associations near genes CCDC6, TSPAN14, NCK2, and SPRED2. Using three SNP-level fine-mapping methods, we identified 21 SNPs with greater than 50% probability each of being causally involved in AD risk, and others strongly suggested by functional annotation. We followed this with colocalisation analyses across 109 gene expression quantitative trait loci (eQTL) datasets, and prioritization of genes using protein interaction networks and tissue-specific expression. Combining this information into a quantitative score, we find that evidence converges on likely causal genes, including the above four genes, and those at previously discovered AD loci including BIN1, APH1B, PTK2B, PILRA, and CASS4.

11: Rapid, accurate, nucleobase detection using FnCas9
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Posted 14 Sep 2020

Rapid, accurate, nucleobase detection using FnCas9
2,548 downloads medRxiv genetic and genomic medicine

Mohd. Azhar, Rhythm Phutela, Manoj Kumar, Asgar Hussain Ansari, Riya Rauthan, Sneha Gulati, Namrata Sharma, Dipanjali Sinha, Saumya Sharma, Sunaina Singh, Sundaram Acharya, Deepanjan Paul, Poorti Kathpalia, Meghali Aich, Paras Sehgal, Gyan Ranjan, Rahul C Bhoyar, Indian CoV2 Genomics & Genetic Epidemiology (IndiCovGEN) Consortium, Khushboo Singhal, Harsha Lad, Pradeep Kumar Patra, Govind Makharia, Giriraj Ratan Chandak, Bala Pesala, Debojyoti Chakraborty, Souvik Maiti

Rapid detection of pathogenic sequences or variants in DNA and RNA through a point-of-care diagnostic approach is valuable for accelerated clinical prognosis as has been witnessed during the recent COVID-19 outbreak. Traditional methods relying on qPCR or sequencing are difficult to implement in settings with limited resources necessitating the development of accurate alternative testing strategies that perform robustly. Here, we present FnCas9 Editor Linked Uniform Detection Assay (FELUDA) that employs a direct Cas9 based enzymatic readout for detecting nucleotide sequences and identifying nucleobase identity without the requirement of trans-cleavage activity of reporter molecules. We demonstrate that FELUDA is 100% accurate in detecting single nucleotide variants (SNVs) including heterozygous carriers of a mutation and present a simple design strategy in the form of a web-tool, JATAYU, for its implementation. FELUDA is semi quantitative, can be adapted to multiple signal detection platforms and can be quickly designed and deployed for versatile applications such as infectious disease outbreaks like COVID-19. Using a lateral flow readout within 1h, FELUDA shows 100% sensitivity and 97% specificity across all range of viral loads in clinical samples. In combination with RT-RPA and a smartphone application True Outcome Predicted via Strip Evaluation (TOPSE), we present a prototype for FELUDA for CoV-2 detection at home.

12: Exome sequencing identifies rare coding variants in 10 genes which confer substantial risk for schizophrenia
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Posted 18 Sep 2020

Exome sequencing identifies rare coding variants in 10 genes which confer substantial risk for schizophrenia
2,380 downloads medRxiv genetic and genomic medicine

Tarjinder Singh, Timothy Poterba, David Curtis, Huda Akil, Mariam Al Eissa, Jack D Barchas, Nicholas Bass, Tim B. Bigdeli, Gerome Breen, Evelyn J Bromet, Peter F Buckley, William E Bunney, Jonas Bybjerg-Grauholm, William F Byerley, Sinead B Chapman, Wei J. Chen, Claire Churchhouse, Nicholas Craddock, Charles Curtis, Caroline M Cusick, Lynn DeLisi, Sheila Dodge, Michael A Escamilla, Saana Eskelinen, Ayman H. Fanous, Stephen V Faraone, Alessia Fiorentino, Laurent Francioli, Stacey B Gabriel, Diane Gage, Sarah A Gagliano Taliun, Andrea Ganna, Giulio Genovese, David C Glahn, Jakob Grove, Mei-Hua Hall, Eija Hamalainen, Henrike O. Heyne, Matti Holi, David Michael Hougaard, Daniel P Howrigan, Hailiang Huang, Hai-Gwo Hwu, Rene S Kahn, Hyun Min Kang, Konrad Karczewski, George Kirov, James A Knowles, Francis S Lee, Douglas S Lehrer, Francesco Lescai, Dolores Malaspina, Stephen R Marder, Steven A McCarroll, Helena Medeiros, Lili Milani, Christopher P Morley, Derek W. Morris, Preben Bo Mortensen, Richard M Myers, Merete Nordentoft, Niamh L O'Brien, Ana Maria Olivares, Dost Ongur, Willem Hendrik Ouwehand, Duncan S Palmer, T. Paunio, Digby Quested, Mark H Rapaport, Elliott Rees, Brandi Rollins, F. Kyle Satterstrom, Alan Schatzberg, Edward Scolnick, Laura Scott, Sally I Sharp, Pamela Sklar, Jordan W. Smoller, Janet l Sobell, Matthew Solomonson, Christine R Stevens, J. Suvisaari, Grace Tiao, Stanley J. Watson, Nicholas A Watts, Douglas H Blackwood, Anders Borglum, Bruce M. Cohen, Aiden P Corvin, Tõnu Esko, Nelson B Freimer, Stephen J Glatt, Christina M Hultman, Andrew McQuillin, Aarno Palotie, Carlos N. Pato, Michele T. Pato, Ann E Pulver, David St Clair, Ming T Tsuang, Marquis P Vawter, James T. R. Walters, Thomas Werge, Roel A Ophoff, Patrick F Sullivan, Michael J. Owen, Michael Boehnke, Michael O'Donovan, Benjamin M Neale, M. Daly

By meta-analyzing the whole-exomes of 24,248 cases and 97,322 controls, we implicate ultra-rare coding variants (URVs) in ten genes as conferring substantial risk for schizophrenia (odds ratios 3 - 50, P < 2.14 x 10^-6), and 32 genes at a FDR < 5%. These genes have the greatest expression in central nervous system neurons and have diverse molecular functions that include the formation, structure, and function of the synapse. The associations of NMDA receptor subunit GRIN2A and AMPA receptor subunit GRIA3 provide support for the dysfunction of the glutamatergic system as a mechanistic hypothesis in the pathogenesis of schizophrenia. We find significant evidence for an overlap of rare variant risk between schizophrenia, autism spectrum disorders (ASD), and severe neurodevelopmental disorders (DD/ID), supporting a neurodevelopmental etiology for schizophrenia. We show that protein-truncating variants in GRIN2A, TRIO, and CACNA1G confer risk for schizophrenia whereas specific missense mutations in these genes confer risk for DD/ID. Nevertheless, few of the strongly associated schizophrenia genes appear to confer risk for DD/ID. We demonstrate that genes prioritized from common variant analyses of schizophrenia are enriched in rare variant risk, suggesting that common and rare genetic risk factors at least partially converge on the same underlying pathogenic biological processes. Even after excluding significantly associated genes, schizophrenia cases still carry a substantial excess of URVs, implying that more schizophrenia risk genes await discovery using this approach.

13: Common variants in Alzheimer's disease: Novel association of six genetic variants with AD and risk stratification by polygenic risk scores
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Posted 15 Nov 2019

Common variants in Alzheimer's disease: Novel association of six genetic variants with AD and risk stratification by polygenic risk scores
2,251 downloads medRxiv genetic and genomic medicine

Itziar de Rojas, Sonia Moreno-Grau, Niccolò Tesi, Benjamin Grenier-Boley, Victor Andrade, Iris Jansen, Nancy L. Pedersen, Najada Stringa, Anna Zettergren, Isabel Hernández, Laura Montrreal, Carmen Antúnez, Anna Antonell, Rick M Tankard, Joshua C Bis, Rebecca Sims, Céline Bellenguez, Inés Quintela, Antonio González-Perez, Miguel Calero, Emilio Franco, Juan Macías, Rafael Blesa, Manuel Menéndez-González, Ana Frank-García, Jose Luís Royo, Fermín Moreno, Raquel Huerto, Miquel Baquero, Mónica Diez-Fairen, Carmen Lage, Sebastian Garcia-Madrona, Pablo García, Emilio Alarcón-Martín, Sergi Valero, Oscar Sotolongo-Grau, EADB, GR@ACE, DEGESCO, IGAP (ADGC, CHARGE, EADI, GERAD) and PGC-ALZ Consortia, Guillermo Garcia-Ribas, Pascual Sánchez-Juan, Pau Pastor, Jordi Pérez-Tur, Gerard Piñol-Ripoll, Adolfo Lopez de Munain, Jose María García-Alberca, María J. Bullido, Victoria Álvarez, Alberto Lleó, Luis M. Real, Pablo Mir, Miguel Medina, Philip Scheltens, Henne Holstege, Marta Marquié, María Eugenia Sáez, Ángel Carracedo, Philippe Amouyel, Julie Williams, Sudha Seshadri, Cornelia M. van Duijn, Karen A. Mather, Raquel Sánchez-Valle, Manuel Serrano-Ríos, Adelina Orellana, Lluís Tárraga, Kaj Blennow, Martijn Huisman, Ole A. Andreassen, Danielle Posthuma, Jordi Clarimón, Mercè Boada, Wiesje van der Flier, Alfredo Ramirez, Jean-Charles Lambert, Sven J. van der Lee, Agustín Ruiz

BACKGROUNDDisentangling the genetic constellation underlying Alzheimers disease (AD) is important. Doing so allows us to identify biological pathways underlying AD, point towards novel drug targets and use the variants for individualised risk predictions in disease modifying or prevention trials. In the present work we report on the largest genome-wide association study (GWAS) for AD risk to date and show the combined utility of proven AD loci for precision medicine using polygenic risk scores (PRS). METHODSThree sets of summary statistics were included in our meta-GWAS of AD: an Spanish case-control study (GR@ACE/DEGESCO study, n = 12,386), the case-control study of International Genomics of Alzheimer project (IGAP, n = 82,771) and the UK Biobank (UKB) AD-by-proxy case-control study (n=314,278). Using these resources, we performed a fixed-effects inverse-variance-weighted meta-analysis. Detected loci were confirmed in a replication study of 19,089 AD cases and 39,101 controls from 16 European-ancestry cohorts not previously used. We constructed a weighted PRS based on the 39 AD variants. PRS were generated by multiplying the genotype dosage of each risk allele for each variant by its respective weight, and then summing across all variants. We first validated it for AD in independent data (assessing effects of sub-threshold signal, diagnostic certainty, age at onset and sex) and tested its effect on risk (odds for disease) and age at onset in the GR@ACE/DEGESCO study. FINDINGSUsing our meta-GWAS approach and follow-up analysis, we identified novel genome-wide significant associations of six genetic variants with AD risk (rs72835061-CHRNE, rs2154481-APP, rs876461-PRKD3/NDUFAF7, rs3935877-PLCG2 and two missense variants: rs34173062/rs34674752 in SHARPIN gene) and confirmed a stop codon mutation in the IL34 gene increasing the risk of AD (IL34-Tyr213Ter), and two other variants in PLCG2 and HS3ST1 regions. This brings the total number of genetic variants associated with AD to 39 (excluding APOE). The PRS based on these variants was associated with AD in an independent clinical AD-case control dataset (OR=1.30, per 1-SD increase in the PRS, 95%CI 1.18-1.44, p = 1.1x10-7), a similar effect to that in the GR@ACE/DEGESCO (OR=1.27, 95%CI 1.23-1.32, p = 7.4x10-39). We then explored the combined effects of these 39 variants in a PRS for AD risk and age-at-onset stratification in GR@ACE/DEGESCO. Excluding APOE, we observed a gradual risk increase over the 2% tiles; when comparing the extremes, those with the 2% highest risk had a 2.98-fold (95% CI 2.12-4.18, p = 3.2x10-10) increased risk compared to those with the 2% lowest risk (p = 5.9x10-10). Using the PRS we identified APOE {varepsilon}33 carriers with a similar risk as APOE {varepsilon}4 heterozygotes carriers, as well as APOE {varepsilon}4 heterozygote carriers with a similar risk as APOE {varepsilon}4 homozygote. Considering age at onset; there was a 9-year difference between median onset of AD the lowest risk group and the highest risk group (82 vs 73 years; p = 1.6x10-6); a 4-year median onset difference (81 vs 77 years; p = 6.9x10-5) within APOE {varepsilon}4 heterozygotes and a 5.5-year median onset difference (78.5 vs 73 years; p = 4.6x10-5) within APOE {varepsilon}4 carriers. INTERPRETATIONWe identified six novel genetic variants associated with AD-risk, among which one common APP variant. A PRS of all genetic loci reported to date could be a robust tool to predict the risk and age at onset of AD, beyond APOE alone. These properties make PRS instrumental in selecting individuals at risk in order to apply preventative strategies and might have potential use in diagnostic work-up.

14: Genetic Profiles in Pharmacogenes Indicate Personalized Drug Therapy for COVID-19
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Posted 30 Mar 2020

Genetic Profiles in Pharmacogenes Indicate Personalized Drug Therapy for COVID-19
2,221 downloads medRxiv genetic and genomic medicine

Lei-Yun Wang, Jia-Jia Cui, Qian-Ying OuYang, Yan Zhan, Yi-Min Wang, Xiang-Yang Xu, Cheng-Xian Guo, Ji-Ye Yin

BackgroundThe coronavirus disease 2019 (COVID-19) has become a global pandemic currently. Many drugs showed potential for COVID-19 therapy. However, genetic factors which can lead to different drug efficiency and toxicity among populations are still undisclosed in COVID-19 therapy. MethodsWe selected 67 potential drugs for COVID-19 therapy (DCTs) from clinical guideline and clinical trials databases. 313 pharmaco-genes related to these therapeutic drugs were included. Variation information in 125,748 exomes were collected for racial differences analyses. The expression level of pharmaco-genes in single cell resolution was evaluated from single-cell RNA sequencing (scRNA-seq) data of 17 healthy adults. ResultsPharmacogenes, including CYP3A4, ABCB1, SLCO1B1, ALB, CYP3A5, were involved in the process of more than multi DCTs. 224 potential drug-drug interactions (DDIs) of DCTs were predicted, while 112 of them have been reported. Racial discrepancy of common nonsynonymous mutations was found in pharmacogenes including: VDR, ITPA, G6PD, CYP3A4 and ABCB1 which related to DCTs including ribavirin, -interferon, chloroquine and lopinavir. Moreover, ACE2, the target of 2019-nCoV, was only found in parts of lung cells, which makes drugs like chloroquine that prevent virus binding to ACE2 more specific than other targeted drugs such as camostat mesylate. ConclusionsAt least 17 drugs for COVID-19 therapy with predictable pharmacogenes should be carefully utilized in risk races which are consisted of more risk allele carriers. At least 29 drugs with potential of DDIs are reported to be affected by other DDIs, they should be replaced by similar drugs without interaction if it is possible. Drugs which specifically targeted to infected cells with ACE2 such as chloroquine are preferred in COVID-19 therapy.

15: Genetic variants are identified to increase risk of COVID-19 related mortality from UK Biobank data
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Posted 09 Nov 2020

Genetic variants are identified to increase risk of COVID-19 related mortality from UK Biobank data
2,174 downloads medRxiv genetic and genomic medicine

Jianchang Hu, Cai Li, Shiying Wang, Ting Li, Heping Zhang

BackgroundThe severity of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is highly heterogenous. Studies have reported that males and some ethnic groups are at increased risk of death from COVID-19, which implies that individual risk of death might be influenced by host genetic factors. MethodsIn this project, we consider the mortality as the trait of interest and perform a genome-wide association study (GWAS) of data for 1,778 infected cases (445 deaths, 25.03%) distributed by the UK Biobank. Traditional GWAS failed to identify any genome-wide significant genetic variants from this dataset. To enhance the power of GWAS and account for possible multi-loci interactions, we adopt the concept of super-variant for the detection of genetic factors. A discovery-validation procedure is used for verifying the potential associations. ResultsWe find 8 super-variants that are consistently identified across multiple replications as susceptibility loci for COVID-19 mortality. The identified risk factors on Chromosomes 2, 6, 7, 8, 10, 16, and 17 contain genetic variants and genes related to cilia dysfunctions (DNAH7 and CLUAP1), cardiovascular diseases (DES and SPEG), thromboembolic disease (STXBP5), mitochondrial dysfunctions (TOMM7), and innate immune system (WSB1). It is noteworthy that DNAH7 has been reported recently as the most downregulated gene after infecting human bronchial epithelial cells with SARS-CoV2. ConclusionsEight genetic variants are identified to significantly increase risk of COVID-19 mortality among the patients with white British ancestry. These findings may provide timely evidence and clues for better understanding the molecular pathogenesis of COVID-19 and genetic basis of heterogeneous susceptibility, with potential impact on new therapeutic options.

16: Multi-omics-based pan-cancer prognosis prediction using an ensemble of deep-learning and machine-learning models
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Posted 25 Oct 2019

Multi-omics-based pan-cancer prognosis prediction using an ensemble of deep-learning and machine-learning models
2,080 downloads medRxiv genetic and genomic medicine

Olivier B. Poirion, Kumardeep Chaudhary, Sijia Huang, Lana X. Garmire

The prognosis prediction of cancer patients is important for disease management. We introduce DeepProg, a new computational framework that robustly predicts patient survival subtypes based on multiple types of omic data, using an ensemble of deep-learning and machine-learning models. We apply DeepProg on 32 cancer datasets from TCGA and identified multiple cancer survival subtypes. Patient survival risk-stratification based on DeepProg is significantly better (p-value=7.9e-7 rank sum test) than Similarity Network Fusion based multi-omics data integration in all cancer types. Further comprehensive pan-cancer comparative analysis unveils the genomic signatures common among all the poorest survival subtypes, with genes enriched in extracellular matrix modeling, immune deregulation, and mitosis processes. Furthermore, models built on closely related cancer types using DeepProg are predictive of the subtypes of some other cancers, demonstrating the utility of DeepProg for transfer learning.

17: The Polygenic and Monogenic Basis of Blood Traits and Diseases
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Posted 03 Feb 2020

The Polygenic and Monogenic Basis of Blood Traits and Diseases
1,900 downloads medRxiv genetic and genomic medicine

Dragana Vuckovic, Erik L. Bao, Parsa Akbari, Caleb A. Lareau, Abdou Mousas, Tao Jiang, Ming-Huei Chen, Laura M. Raffield, Manuel Tardaguila, Jennifer E. Huffman, Scott C Ritchie, Karyn Megy, Hannes Ponstingl, Christopher J Penkett, Patrick K. Albers, Emilie M. Wigdor, Saori Sakaue, Arden Moscati, Regina Manansala, Ken Sin Lo, Huijun Qian, Masato Akiyama, Traci M Bartz, Yoav Ben-Shlomo, Andrew Beswick, Jette Bork-Jensen, Erwin P. Bottinger, Jennifer A. Brody, Frank JA van Rooij, Kumaraswamy N Chitrala, Kelly Cho, Helene Choquet, Adolfo Correa, John Danesh, Emanuele Di Angelantonio, Niki Dimou, Jingzhong Ding, Paul Elliott, Tõnu Esko, Michele K Evans, Stephan B. Felix, James S Floyd, Linda Broer, Niels Grarup, Michael H Guo, Andreas Greinacher, Jeff Haessler, Torben Hansen, Joanna M. M. Howson, Wei Huang, Eric Jorgenson, Tim Kacprowski, Mika Kähönen, Yoichiro Kamatani, Masahiro Kanai, Savita Karthikeyan, Fotis Koskeridis, Leslie A Lange, Terho Lehtimäki, Allan Linneberg, Yongmei Liu, Leo-Pekka Lyytikäinen, Ani Manichaikul, Koichi Matsuda, Karen L. Mohlke, Nina Mononen, Yoshinori Murakami, Girish Nadkarni, Kjell Nikus, Nathan Pankratz, Oluf Pedersen, Michael Preuss, Bruce M Psaty, Olli T. Raitakari, Stephen S Rich, Benjamin A.T. Rodriguez, Jonathan D. Rosen, Jerome I. Rotter, Petra Schubert, Cassandra N. Spracklen, Praveen Surendran, Hua Tang, Jean-Claude Tardif, Mohsen Ghanbari, Uwe Volker, Henry Völzke, Nicholas A Watkins, Stefan Weiss, VA Million Veteran Program, Na Cai, Kousik Kundu, Stephen B. Watt, Klaudia Walter, Alan B Zonderman, Peter WF Wilson, Yun Li, Ruth J.F. Loos, Julian Knight, Michel Georges, Oliver Stegle, Evangelos Evangelou, Yukinori Okada, David J. Roberts, Michael Inouye, Andrew D. Johnson, Paul L. Auer, William J. Astle, Alexander P Reiner, Adam S. Butterworth, Willem H Ouwehand, Guillaume Lettre, Vijay G. Sankaran, Nicole Soranzo

Blood cells play essential roles in human health, underpinning physiological processes such as immunity, oxygen transport, and clotting, which when perturbed cause a significant health burden. Here we integrate data from UK Biobank and a large-scale international collaborative effort, including 563,946 European ancestry participants, and discover 5,106 new genetic variants independently associated with 29 blood cell phenotypes covering the full allele frequency spectrum of variation impacting hematopoiesis. We holistically characterize the genetic architecture of hematopoiesis, assess the relevance of the omnigenic model to blood cell phenotypes, delineate relevant hematopoietic cell states influenced by regulatory genetic variants and gene networks, identify novel splice-altering variants mediating the associations, and assess the polygenic prediction potential for blood cell traits and clinical disorders at the interface of complex and Mendelian genetics. These results show the power of large-scale blood cell GWAS to interrogate clinically meaningful variants across the full allelic spectrum of human variation.

18: Leveraging polygenic enrichments of gene features to predict genes underlying complex traits and diseases
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Posted 10 Sep 2020

Leveraging polygenic enrichments of gene features to predict genes underlying complex traits and diseases
1,832 downloads medRxiv genetic and genomic medicine

Elle M. Weeks, Jacob C Ulirsch, Nathan Y Cheng, Brian L Trippe, Rebecca S. Fine, Jenkai Miao, Tejal A Patwardhan, Masahiro Kanai, Joseph Nasser, Charles P Fulco, Katherine C Tashman, Francois Aguet, Taibo Li, Jose Ordovas-Montanes, Christopher S. Smillie, Moshe Biton, Alex K. Shalek, Ashwin N. Ananthakrishnan, Ramnik J. Xavier, Aviv Regev, Rajat M Gupta, Kasper Lage, Kristin G. Ardlie, Joel N. Hirschhorn, Eric S Lander, Jesse M. Engreitz, Hilary K. Finucane

Genome-wide association studies (GWAS) are a valuable tool for understanding the biology of complex traits, but the associations found rarely point directly to causal genes. Here, we introduce a new method to identify the causal genes by integrating GWAS summary statistics with gene expression, biological pathway, and predicted protein-protein interaction data. We further propose an approach that effectively leverages both polygenic and locus-specific genetic signals by combining results across multiple gene prioritization methods, increasing confidence in prioritized genes. Using a large set of gold standard genes to evaluate our approach, we prioritize 8,402 unique gene-trait pairs with greater than 75% estimated precision across 113 complex traits and diseases, including known genes such as SORT1 for LDL cholesterol, SMIM1 for red blood cell count, and DRD2 for schizophrenia, as well as novel genes such as TTC39B for cholelithiasis. Our results demonstrate that a polygenic approach is a powerful tool for gene prioritization and, in combination with locus-specific signal, improves upon existing methods.

19: Benchmarking the Accuracy of Polygenic Risk Scores and their Generative Methods
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Posted 08 Apr 2020

Benchmarking the Accuracy of Polygenic Risk Scores and their Generative Methods
1,786 downloads medRxiv genetic and genomic medicine

Scott Kulm, Jason Mezey, Olivier Elemento

The estimate of an individuals genetic susceptibility to a disease can provide critical information when setting screening schedules, prescribing medication and making lifestyle change recommendations. The polygenic risk score is the predominant susceptibility metric, with many methods available to describe its construction. However, these methods have never been comprehensively compared or the predictive value of their outputs systematically assessed, leaving the clinical utility of polygenic risk scores uncertain. This study aims to resolve this uncertainty by deeply comparing the maximum possible, currently available, 15 polygenic risk scoring methods to 25 well-powered, UK Biobank derived, disease phenotypes. Our results show that simpler methods, which employ heuristics, bested complex, methods, which predominately model linkage disequilibrium. Accuracy was assessed with AUC improvement, the difference in area under the receiver operating curve generated by two logistic regression models, both of which share the covariates of age, sex, and principal components, while the second model also contains the polygenic risk score. To better determine the maximal utility of polygenic risk scores, straightforward score ensembles, which bested all methods across all traits in the training data-set, were evaluated in the withheld data-set. The score ensembles revealed that the accuracy gained by considering a polygenic risk score varied greatly, with AUC improvement greater than 0.05 for 9 traits. Many additional analyses revealed widespread pleiotropy across scores, large variations between assessment statistics, peculiar patterns amongst phenotype definitions, and wide ranges in the optimal number of variants used for scoring. If these many variable aspects of score creation can be well controlled and documented, simple methods can easily generate polygenic risk score that well predict an individuals future liability of certain diseases.

20: Use of an integrated pan-cancer oncology enrichment NGS assay to measure tumour mutational burden and detect clinically actionable variants
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Posted 04 Feb 2020

Use of an integrated pan-cancer oncology enrichment NGS assay to measure tumour mutational burden and detect clinically actionable variants
1,773 downloads medRxiv genetic and genomic medicine

Valerie Pestinger, Matthew Smith, Toju Sillo, John M Findlay, Jean-Francois Laes, Gerald Martin, Gary Middleton, Phillipe Taniere, Andrew D. Beggs

IntroductionThe identification of tumour mutational burden (TMB) as a biomarker of response to PD-1 immunotherapy has necessitated the development of genomic assays to measure this. We carried out comprehensive molecular profiling of cancers using the Illumina TruSight Oncology panel (TSO500) and compared to whole genome sequencing. MethodsCancer samples derived from formalin fixed material were profiled on the TSO500 panel, sequenced on an Illumina NextSeq 500 instrument and processed through the TSO500 Docker Pipeline. Either FASTQ files (PierianDx) or VCF files (OncoKDM) were processed to understand clinical actionability ResultsIn total, 108 samples (a mixture of colorectal, lung, oesophageal and control samples) were processed via the DNA panel. There was good correlation between TMB, SNV, indels and CNV as predicted by TSO500 and WGS (R2>0.9) and good reproducibility, with less than 5% variability between repeated controls. For the RNA panel, 13 samples were processed, with all known fusions observed via orthogonal techniques detected. For clinical actionability 72 Tier 1 variants and 297 Tier 2 variants were identified with clinical trials identified for all patients. ConclusionsThe TruSight Oncology 500 assay accurately measures TMB, MSI, single nucleotide variants, indels, copy number/structural variation and gene fusions when compared to whole genome sequencing and orthogonal technologies. Coupled with a clinical annotation pipeline this provides a powerful methodology for identification of clinically actionable variants.

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