In search of complex disease risk through genome wide association studies

The identification and characterisation of genomic changes (variants) that can lead to human diseases is one of the central aims of biomedical research. The generation of catalogues of genetic variants that have an impact on specific diseases is the basis of Personalised Medicine, where diagnoses and treatment protocols are selected according to each patient’s profile. In this context, the study of complex diseases, such as Type 2 diabetes or cardiovascular alterations, is fundamental. However, these diseases result from the combination of multiple genetic and environmental factors, which makes the discovery of causal variants particularly challenging at a statistical and computational level. Genome-Wide Association Studies (GWAS), which are based on the statistical analysis of genetic variant frequencies across non-diseased and diseased individuals, have been successful in finding genetic variants that are associated to specific diseases or phenotypic traits. But GWAS methodology is limited when considering important genetic aspects of the disease and has not yet resulted in meaningful translation to clinical practice. This review presents an outlook on the study of the link between genetics and complex phenotypes. We first present an overview of the past and current statistical methods used in the field. Next, we discuss current practices and their main limitations. Finally, we describe the open challenges that remain and that might benefit greatly from further mathematical developments.L.A. was supported by grant BES-2017-081635. This publication is part of R&D and Innovation grant BES-2017-081635 funded by MCIN and by “FSE Investing in your future”I.M. was supported by grant FJCI-2017-31878. This publication is part of R&D and Innovation grant FJCI-2017-31878 funded by MCIN. C.S. received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement H2020-MSCA-COFUND-2016-754433.Peer ReviewedPostprint (published version

Ungulate presence and predation risks reduce acorn predation by mice in dehesas

Foraging decisions by rodents are key for the long-term maintenance of oak populations in which avian seed dispersers are absent or inefficient. Decisions are determined by the environmental setting in which acorn-rodent encounters occur. In particular, seed value, competition and predation risks have been found to modify rodent foraging decisions in forest and human-modified habitats. Nonetheless, there is little information about their joint effects on rodent behavior, and hence, local acorn dispersal (or predation). In this work, we manipulate and model the mouse-oak interaction in a Spanish dehesa, an anthropogenic savanna system in which nearby areas can show contrasting levels of ungulate densities and antipredatory cover. First, we conducted a large-scale cafeteria field experiment, where we modified ungulate presence and predation risk, and followed mouse foraging decisions under contrasting levels of moonlight and acorn availability. Then, we estimated the net effects of competition and risk by means of a transition probability model that simulated mouse foraging decisions. Our results show that mice are able to adapt their foraging decisions to the environmental context, affecting initial fates of handled acorns. Under high predation risks mice foraged opportunistically carrying away large and small seeds, whereas under safe conditions large acorns tended to be predated in situ. In addition, in the presence of ungulates lack of antipredatory cover around trees reduced mice activity outside tree canopies, and hence, large acorns had a higher probability of survival. Overall, our results point out that inter-specific interactions preventing efficient foraging by scatter-hoarders can reduce acorn predation. This suggests that the maintenance of the full set of seed consumers as well as top predators in dehesas may be key for promoting local dispersal.Fil: Morán López, Teresa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; ArgentinaFil: Sánchez Dávila, Jesús. Consejo Superior de Investigaciones Científicas. Museo Nacional de Ciencias Naturales; EspañaFil: Torre, Ignasi. Museu de Ciències Naturals de Granollers; EspañaFil: Navarro Castilla, Alvaro. Universidad Autónoma de Madrid; EspañaFil: Barja, Isabel. Universidad Autónoma de Madrid; EspañaFil: Diaz, Mario. Consejo Superior de Investigaciones Científicas. Museo Nacional de Ciencias Naturales; Españ

Challenges and opportunities for RISC-V architectures towards genomics-based workloads

The use of large-scale supercomputing architectures is a hard requirement for scientific computing Big-Data applications. An example is genomics analytics, where millions of data transformations and tests per patient need to be done to find relevant clinical indicators. Therefore, to ensure open and broad access to high-performance technologies, governments, and academia are pushing toward the introduction of novel computing architectures in large-scale scientific environments. This is the case of RISC-V, an open-source and royalty-free instruction-set architecture. To evaluate such technologies, here we present the Variant-Interaction Analytics use case benchmarking suite and datasets. Through this use case, we search for possible genetic interactions using computational and statistical methods, providing a representative case for heavy ETL (Extract, Transform, Load) data processing. Current implementations are implemented in x86-based supercomputers (e.g. MareNostrum-IV at the Barcelona Supercomputing Center (BSC)), and future steps propose RISC-V as part of the next MareNostrum generations. Here we describe the Variant Interaction Use Case, highlighting the characteristics leveraging high-performance computing, indicating the caveats and challenges towards the next RISC-V developments and designs to come from a first comparison between x86 and RISC-V architectures on real Variant Interaction executions over real hardware implementations.This work has been partially financed by the European Commission (EU-HORIZON NEARDATA GA.101092644, VITAMIN-V GA.101093062), the MEEP Project which received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 946002. The JU receives support from the European Union’s Horizon 2020 research and innovation program and Spain, Croatia and Turkey. Also by the Spanish Ministry of Science (MICINN) under scholarship BES-2017-081635, the Research State Agency (AEI) and European Regional Development Funds (ERDF/FEDER) under DALEST grant agreement PID2021-126248OBI00, MCIN/AEI/10.13039/ 501100011033/FEDER and PID GA PID2019-107255GB-C21, and the Generalitat de Catalunya (AGAUR) under grant agreements 2021-SGR-00478, 2021-SGR-01626 and ”FSE Invertint en el teu futur”.Peer ReviewedPostprint (author's final draft

Polymorphic Inversions Underlie the Shared Genetic Susceptibility of Obesity-Related Diseases

The burden of several common diseases including obesity, diabetes, hypertension, asthma, and depression is increasing in most world populations. However, the mechanisms underlying the numerous epidemiological and genetic correlations among these disorders remain largely unknown. We investigated whether common polymorphic inversions underlie the shared genetic influence of these disorders. We performed an inversion association analysis including 21 inversions and 25 obesity-related traits on a total of 408,898 Europeans and validated the results in 67,299 independent individuals. Seven inversions were associated with multiple diseases while inversions at 8p23.1, 16p11.2, and 11q13.2 were strongly associated with the co-occurrence of obesity with other common diseases. Transcriptome analysis across numerous tissues revealed strong candidate genes for obesity-related traits. Analyses in human pancreatic islets indicated the potential mechanism of inversions in the susceptibility of diabetes by disrupting the cis-regulatory effect of SNPs from their target genes. Our data underscore the role of inversions as major genetic contributors to the joint susceptibility to common complex diseases.This research has received funding from Ministerio de Ciencia, Innovación y Universidades (MICIU), Agencia Estatal de Investigación (AEI) and Fondo Europeo de Desarrollo Regional, UE (RTI2018-100789-B-I00) also through the “Centro de Excelencia Severo Ochoa 2019-2023” Program (CEX2018-000806-S); and the Catalan Government through the CERCA Program and projects SGR2017/801 and #016FI_B 00272 to CR-A. JG is funded by the European Commission (H2020-ERC-2014-CoG-647900) and the MINECO/AEI/FEDER, EU (BFU2017-82937-P). LAPJ lab was funded by the Spanish Ministry of Science and Innovation (ISCIII-FEDER P13/02481), the Catalan Department of Economy and Knowledge (SGR2014/1468, SGR2017/1974 and ICREA Acadèmia), and also acknowledges support from the Spanish Ministry of Economy and Competiveness “Programa de Excelencia María de Maeztu” (MDM-2014-0370). This research was conducted using the UK Biobank Resource under Application Number 43983. The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS.Peer ReviewedPostprint (author's final draft

Accelerated amyloid deposition, neurofibrillary degeneration and neuronal loss in double mutant APP/tau transgenic mice

Even though the idea that amyloid β peptide accumulation is the primary event in the pathogenesis of Alzheimer's disease has become the leading hypothesis, the causal link between aberrant amyloid precursor protein processing and tau alterations in this type of dementia remains controversial. We further investigated the role of β-amyloid production/deposition in tau pathology and neuronal cell death in the mouse brain by crossing Tg2576 and VLW lines expressing human mutant amyloid precursor protein and human mutant tau, respectively. The resulting double transgenic mice showed enhanced amyloid deposition accompanied by neurofibrillary degeneration and overt neuronal loss in selectively vulnerable brain limbic areas. These findings challenge the idea that tau pathology in Alzheimer's disease is merely a downstream effect of amyloid production/deposition and suggest that reciprocal interactions between β-amyloid and tau alterations may take place in vivo.This project was funded in part by EC grant DIADEM QRLT-2000-026362, SAF2004-07802 and UTE project CIM

Ungulate presence and predation risks reduce acorn predation by mice in dehesas

Foraging decisions by rodents are key for the long-term maintenance of oak populations in which avian seed dispersers are absent or inefficient. Decisions are determined by the environmental setting in which acorn-rodent encounters occur. In particular, seed value, competition and predation risks have been found to modify rodent foraging decisions in forest and human-modified habitats. Nonetheless, there is little information about their joint effects on rodent behavior, and hence, local acorn dispersal (or predation). In this work, we manipulate and model the mouse-oak interaction in a Spanish dehesa, an anthropogenic savanna system in which nearby areas can show contrasting levels of ungulate densities and antipredatory cover. First, we conducted a large-scale cafeteria field experiment, where we modified ungulate presence and predation risk, and followed mouse foraging decisions under contrasting levels of moonlight and acorn availability. Then, we estimated the net effects of competition and risk by means of a transition probability model that simulated mouse foraging decisions. Our results show that mice are able to adapt their foraging decisions to the environmental context, affecting initial fates of handled acorns. Under high predation risks mice foraged opportunistically carrying away large and small seeds, whereas under safe conditions large acorns tended to be predated in situ. In addition, in the presence of ungulates lack of antipredatory cover around trees reduced mice activity outside tree canopies, and hence, large acorns had a higher probability of survival. Overall, our results point out that inter-specific interactions preventing efficient foraging by scatter-hoarders can reduce acorn predation. This suggests that the maintenance of the full set of seed consumers as well as top predators in dehesas may be key for promoting local dispersal.Peer reviewe

Polymorphic Inversions Underlie the Shared Genetic Susceptibility of Obesity-Related Diseases

The burden of several common diseases including obesity, diabetes, hypertension, asthma, and depression is increasing in most world populations. However, the mechanisms underlying the numerous epidemiological and genetic correlations among these disorders remain largely unknown. We investigated whether common polymorphic inversions underlie the shared genetic influence of these disorders. We performed an inversion association analysis including 21 inversions and 25 obesity-related traits on a total of 408,898 Europeans and validated the results in 67,299 independent individuals. Seven inversions were associated with multiple diseases while inversions at 8p23.1, 16p11.2, and 11q13.2 were strongly associated with the co-occurrence of obesity with other common diseases. Transcriptome analysis across numerous tissues revealed strong candidate genes for obesity-related traits. Analyses in human pancreatic islets indicated the potential mechanism of inversions in the susceptibility of diabetes by disrupting the cis-regulatory effect of SNPs from their target genes. Our data underscore the role of inversions as major genetic contributors to the joint susceptibility to common complex diseases.This research has received funding from Ministerio de Ciencia, Innovación y Universidades (MICIU), Agencia Estatal de Investigación (AEI), and Fondo Europeo de Desarrollo Regional, UE (RTI2018-100789-B-I00) also through the “Centro de Excelencia Severo Ochoa 2019-2023” Program (CEX2018-000806-S); and the Catalan Government (SGR2017/801 and #016FI_B 00272 to C.R.-A.) through the CERCA Program. J.G. is funded by the European Commission (H2020-ERC-2014-CoG-647900) and the MINECO/AEI/FEDER, EU (BFU2017-82937-P). The L.A.P.-J. lab was funded by the Spanish Ministry of Science and Innovation (ISCIII-FEDER P13/02481), the Catalan Department of Economy and Knowledge (SGR2014/1468, SGR2017/1974, and ICREA Acadèmia), and also acknowledges support from the Spanish Ministry of Economy and Competiveness“Programa de Excelencia María de Maeztu” (MDM-2014-0370). This research was conducted using the UK Biobank Resource under Application Number 43983. The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS.Peer reviewe

Human pancreatic islet three-dimensional chromatin architecture provides insights into the genetics of type 2 diabetes

Genetic studies promise to provide insight into the molecular mechanisms underlying type 2 diabetes (T2D). Variants associated with T2D are often located in tissue-specific enhancer clusters or super-enhancers. So far, such domains have been defined through clustering of enhancers in linear genome maps rather than in three-dimensional (3D) space. Furthermore, their target genes are often unknown. We have created promoter capture Hi-C maps in human pancreatic islets. This linked diabetes-associated enhancers to their target genes, often located hundreds of kilobases away. It also revealed >1,300 groups of islet enhancers, super-enhancers and active promoters that form 3D hubs, some of which show coordinated glucose-dependent activity. We demonstrate that genetic variation in hubs impacts insulin secretion heritability, and show that hub annotations can be used for polygenic scores that predict T2D risk driven by islet regulatory variants. Human islet 3D chromatin architecture, therefore, provides a framework for interpretation of T2D genome-wide association study (GWAS) signals.This research was supported by the National Institute for Health Research Imperial Biomedical Research Centre. Work was funded by grants from the Wellcome Trust (nos. WT101033 to J.F. and WT205915 to I.P.), Horizon 2020 (Research and Innovation Programme nos. 667191, to J.F., 633595, to I.P., and 676556, to M.A.M.-R.; Marie Sklodowska-Curie 658145, to I.M.-E., and 43062 ZENCODE, to G.A.), European Research Council (nos. 789055, to J.F., and 609989, to M.A.M.-R.). Marató TV3 (no. 201611, to J.F. and M.A.M.-R.), Ministerio de Ciencia Innovación y Universidades (nos. BFU2014-54284-R, RTI2018-095666, to J.F., BFU2017-85926-P, to M.A.M.-R., IJCI-2015-23352, to I.F.), AGAUR (to M.A.M.-R.). UK Medical Research Council (no. MR/L007150/1, to P.F., MR/L02036X/1 to J.F.), World Cancer Research Fund (WCRF UK, to I.P.) and World Cancer Research Fund International (no. 2017/1641 to I.P.), Biobanking and Biomolecular Resources Research Infrastructure (nos. BBMRI-NL, NWO 184.021.007, to I.O.F.). Work in IDIBAPS, CRG and CNAG was supported by the CERCA Programme, Generalitat de Catalunya and Centros de Excelencia Severo Ochoa (no. SEV-2012-0208). Human islets were provided through the European islet distribution program for basic research supported by JDRF (no. 3-RSC-2016-160-I-X). We thank N. Ruiz-Gomez for technical assistance; R. L. Fernandes, T. Thorne (University of Reading) and A. Perdones-Montero (Imperial College London) for helpful discussions regarding Machine Learning approaches; B. Lenhard and M. Merkenschlager (London Institute of Medical Sciences, Imperial College London), F. Müller (University of Birmingham) and J. L. Gómez-Skarmeta (Centro Andaluz de Biología del Desarrollo) for critical comments on the draft; the CRG Genomics Unit; and the Imperial College High Performance Computing Service

TIGER: the translational human pancreatic islet genotype tissue-expression resource

Background and aims: The scarcity of human islets preparations from organ donors available and their scattering across research labs, limits the understanding of the genomic and regulatory landscape of human islets and type 2 diabetes (T2D). The Horizon 2020 T2DSystems Consortium set out to gather genomic, transcriptomic and epigenomic datasets from a large number of human pancreatic islet samples from several laboratories and make the data publicly available.Materials and methods: We collected RNA-seq and genotyping data from 495 human islet samples and performed harmonization, quality control, genotype phasing and imputation. We integrated a) T2D association from genome-wide association studies (GWAS) identified in large meta-analyses or included in the GWAS Catalog, b) variant annotation and characterization through Variant Effect Predictor and Gnomad, c) epigenomic marks from islet DNA-methylation sites, chromatin accessibility and CHiP-seq profiles, d) annotation from Gene Ontology, lncRNAs and islet regulome, e) gene expression from normalised islet RNA-seq counts, microarrays and the Genotype-Tissue Expression database, and f) computed expression quantitative loci (eQTL) and allelic specific expression (ASE) and created the largest regulatory variation database from human pancreatic islets.Results: We developed TIGER, a publicly accessible database (http://tiger.bsc.es) provided with a genome browser to ensure the comprehensive data integration. The platform encloses tools for visualizing, querying, and downloading human islet data. TIGER facilitates follow-up by providing genetic and molecular findings related to T2D pathophysiology with a gene or a variant summary, eQTL and ASE results, associations with T2D and other related traits or diseases, genomic context information such as the islet chromatin landscape and direct access to other genomic databases.Conclusion: The comprehensive collation in TIGER of genomic, transcriptomic and epigenetic human islet datasets, and the integration with T2D GWAS and regulatory variation, represents a formidable resource to interrogate the molecular etiology of beta-cell failure in T2D.info:eu-repo/semantics/publishe