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1. Multi-omics signatures of the human early life exposome

Author: Léa Maitre, Mariona Bustamante, Carles Hernández-Ferrer, Denise Thiel, Chung-Ho E. Lau, Alexandros P. Siskos, Marta Vives-Usano, Carlos Ruiz-Arenas, Dolors Pelegrí-Sisó, Oliver Robinson, Dan Mason, John Wright, Solène Cadiou, Rémy Slama, Barbara Heude, Maribel Casas, Jordi Sunyer, Eleni Z. Papadopoulou, Kristine B. Gutzkow, Sandra Andrusaityte, Regina Grazuleviciene, Marina Vafeiadi, Leda Chatzi, Amrit K. Sakhi, Cathrine Thomsen, Ibon Tamayo, Mark Nieuwenhuijsen, Jose Urquiza, Eva Borràs, Eduard Sabidó, Inés Quintela, Ángel Carracedo, Xavier Estivill, Muireann Coen, Juan R. González, Hector C. Keun, and Martine Vrijheid
Subjects: Science
Abstract: Environmental exposures in early life can have lasting health effects, but the molecular mechanisms are not well understood. Here, the authors discover >1000 associations between exposure factors and child multi-omics profiles, revealing signatures for diet, toxic chemical compounds, essential trace elements, and weather conditions.
Published: 2022
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2. A population study of clinically actionable genetic variation affecting drug response from the Middle East

Author: Puthen Veettil Jithesh, Mohammed Abuhaliqa, Najeeb Syed, Ikhlak Ahmed, Mohammed El Anbari, Kholoud Bastaki, Shimaa Sherif, Umm-Kulthum Umlai, Zainab Jan, Geethanjali Gandhi, Chidambaram Manickam, Senthil Selvaraj, Chinnu George, Dhinoth Bangarusamy, Rania Abdel-latif, Mashael Al-Shafai, Zohreh Tatari-Calderone, Xavier Estivill, Munir Pirmohamed, and The Qatar Genome Program Research Consortium
Subjects: Medicine, Genetics, QH426-470
Abstract: Abstract Clinical implementation of pharmacogenomics will help in personalizing drug prescriptions and alleviate the personal and financial burden due to inefficacy and adverse reactions to drugs. However, such implementation is lagging in many parts of the world, including the Middle East, mainly due to the lack of data on the distribution of actionable pharmacogenomic variation in these ethnicities. We analyzed 6,045 whole genomes from the Qatari population for the distribution of allele frequencies of 2,629 variants in 1,026 genes known to affect 559 drugs or classes of drugs. We also performed a focused analysis of genotypes or diplotypes of 15 genes affecting 46 drugs, which have guidelines for clinical implementation and predicted their phenotypic impact. The allele frequencies of 1,320 variants in 703 genes affecting 299 drugs or class of drugs were significantly different between the Qatari population and other world populations. On average, Qataris carry 3.6 actionable genotypes/diplotypes, affecting 13 drugs with guidelines for clinical implementation, and 99.5% of the individuals had at least one clinically actionable genotype/diplotype. Increased risk of simvastatin-induced myopathy could be predicted in ~32% of Qataris from the diplotypes of SLCO1B1, which is higher compared to many other populations, while fewer Qataris may need tacrolimus dosage adjustments for achieving immunosuppression based on the CYP3A5 diplotypes compared to other world populations. Distinct distribution of actionable pharmacogenomic variation was also observed among the Qatari subpopulations. Our comprehensive study of the distribution of actionable genetic variation affecting drugs in a Middle Eastern population has potential implications for preemptive pharmacogenomic implementation in the region and beyond.
Published: 2022
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3. Changes in the stool and oropharyngeal microbiome in obsessive-compulsive disorder

Author: Laura Domènech, Jesse Willis, Maria Alemany-Navarro, Marta Morell, Eva Real, Geòrgia Escaramís, Sara Bertolín, Daniel Sánchez Chinchilla, Susanna Balcells, Cinto Segalàs, Xavier Estivill, Jose M. Menchón, Toni Gabaldón, Pino Alonso, and Raquel Rabionet
Subjects: Medicine, Science
Abstract: Abstract Although the etiology of obsessive–compulsive disorder (OCD) is largely unknown, it is accepted that OCD is a complex disorder. There is a known bi-directional interaction between the gut microbiome and brain activity. Several authors have reported associations between changes in gut microbiota and neuropsychiatric disorders, including depression or autism. Furthermore, a pediatric-onset neuropsychiatric OCD-related syndrome occurs after streptococcal infection, which might indicate that exposure to certain microbes could be involved in OCD susceptibility. However, only one study has investigated the microbiome of OCD patients to date. We performed 16S ribosomal RNA gene-based metagenomic sequencing to analyze the stool and oropharyngeal microbiome composition of 32 OCD cases and 32 age and gender matched controls. We estimated different α- and β-diversity measures and performed LEfSe and Wilcoxon tests to assess differences in bacterial distribution. OCD stool samples showed a trend towards lower bacterial α-diversity, as well as an increase of the relative abundance of Rikenellaceae, particularly of the genus Alistipes, and lower relative abundance of Prevotellaceae, and two genera within the Lachnospiraceae: Agathobacer and Coprococcus. However, we did not observe a different Bacteroidetes to Firmicutes ratio between OCD cases and controls. Analysis of the oropharyngeal microbiome composition showed a lower Fusobacteria to Actinobacteria ratio in OCD cases. In conclusion, we observed an imbalance in the gut and oropharyngeal microbiomes of OCD cases, including, in stool, an increase of bacteria from the Rikenellaceae family, associated with gut inflammation, and a decrease of bacteria from the Coprococcus genus, associated with DOPAC synthesis.
Published: 2022
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4. Variability of multi-omics profiles in a population-based child cohort

Author: Marta Gallego-Paüls, Carles Hernández-Ferrer, Mariona Bustamante, Xavier Basagaña, Jose Barrera-Gómez, Chung-Ho E. Lau, Alexandros P. Siskos, Marta Vives-Usano, Carlos Ruiz-Arenas, John Wright, Remy Slama, Barbara Heude, Maribel Casas, Regina Grazuleviciene, Leda Chatzi, Eva Borràs, Eduard Sabidó, Ángel Carracedo, Xavier Estivill, Jose Urquiza, Muireann Coen, Hector C. Keun, Juan R. González, Martine Vrijheid, and Léa Maitre
Subjects: Multi-omics, Exposome, Variability, Population study, Metabolomics, DNA methylation, Medicine
Abstract: Abstract Background Multiple omics technologies are increasingly applied to detect early, subtle molecular responses to environmental stressors for future disease risk prevention. However, there is an urgent need for further evaluation of stability and variability of omics profiles in healthy individuals, especially during childhood. Methods We aimed to estimate intra-, inter-individual and cohort variability of multi-omics profiles (blood DNA methylation, gene expression, miRNA, proteins and serum and urine metabolites) measured 6 months apart in 156 healthy children from five European countries. We further performed a multi-omics network analysis to establish clusters of co-varying omics features and assessed the contribution of key variables (including biological traits and sample collection parameters) to omics variability. Results All omics displayed a large range of intra- and inter-individual variability depending on each omics feature, although all presented a highest median intra-individual variability. DNA methylation was the most stable profile (median 37.6% inter-individual variability) while gene expression was the least stable (6.6%). Among the least stable features, we identified 1% cross-omics co-variation between CpGs and metabolites (e.g. glucose and CpGs related to obesity and type 2 diabetes). Explanatory variables, including age and body mass index (BMI), explained up to 9% of serum metabolite variability. Conclusions Methylation and targeted serum metabolomics are the most reliable omics to implement in single time-point measurements in large cross-sectional studies. In the case of metabolomics, sample collection and individual traits (e.g. BMI) are important parameters to control for improved comparability, at the study design or analysis stage. This study will be valuable for the design and interpretation of epidemiological studies that aim to link omics signatures to disease, environmental exposures, or both.
Published: 2021
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5. Identification of autosomal cis expression quantitative trait methylation (cis eQTMs) in children’s blood

Author: Carlos Ruiz-Arenas, Carles Hernandez-Ferrer, Marta Vives-Usano, Sergi Marí, Ines Quintela, Dan Mason, Solène Cadiou, Maribel Casas, Sandra Andrusaityte, Kristine Bjerve Gutzkow, Marina Vafeiadi, John Wright, Johanna Lepeule, Regina Grazuleviciene, Leda Chatzi, Ángel Carracedo, Xavier Estivill, Eulàlia Marti, Geòrgia Escaramís, Martine Vrijheid, Juan R González, and Mariona Bustamante
Subjects: eQTM, epigenetics, transcription, DNA methylation, children, blood, Medicine, Science, Biology (General), QH301-705.5
Abstract: Background: The identification of expression quantitative trait methylation (eQTMs), defined as associations between DNA methylation levels and gene expression, might help the biological interpretation of epigenome-wide association studies (EWAS). We aimed to identify autosomal cis eQTMs in children’s blood, using data from 832 children of the Human Early Life Exposome (HELIX) project. Methods: Blood DNA methylation and gene expression were measured with the Illumina 450K and the Affymetrix HTA v2 arrays, respectively. The relationship between methylation levels and expression of nearby genes (1 Mb window centered at the transcription start site, TSS) was assessed by fitting 13.6 M linear regressions adjusting for sex, age, cohort, and blood cell composition. Results: We identified 39,749 blood autosomal cis eQTMs, representing 21,966 unique CpGs (eCpGs, 5.7% of total CpGs) and 8,886 unique transcript clusters (eGenes, 15.3% of total transcript clusters, equivalent to genes). In 87.9% of these cis eQTMs, the eCpG was located at
Published: 2022
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6. In utero and childhood exposure to tobacco smoke and multi-layer molecular signatures in children

Author: Marta Vives-Usano, Carles Hernandez-Ferrer, Léa Maitre, Carlos Ruiz-Arenas, Sandra Andrusaityte, Eva Borràs, Ángel Carracedo, Maribel Casas, Leda Chatzi, Muireann Coen, Xavier Estivill, Juan R. González, Regina Grazuleviciene, Kristine B. Gutzkow, Hector C. Keun, Chung-Ho E. Lau, Solène Cadiou, Johanna Lepeule, Dan Mason, Inés Quintela, Oliver Robinson, Eduard Sabidó, Gillian Santorelli, Per E. Schwarze, Alexandros P. Siskos, Rémy Slama, Marina Vafeiadi, Eulàlia Martí, Martine Vrijheid, and Mariona Bustamante
Subjects: Tobacco smoking, Secondhand smoke, Children, Pregnancy, Omics, Molecular phenotypes, Medicine
Abstract: Abstract Background The adverse health effects of early life exposure to tobacco smoking have been widely reported. In spite of this, the underlying molecular mechanisms of in utero and postnatal exposure to tobacco smoke are only partially understood. Here, we aimed to identify multi-layer molecular signatures associated with exposure to tobacco smoke in these two exposure windows. Methods We investigated the associations of maternal smoking during pregnancy and childhood secondhand smoke (SHS) exposure with molecular features measured in 1203 European children (mean age 8.1 years) from the Human Early Life Exposome (HELIX) project. Molecular features, covering 4 layers, included blood DNA methylation and gene and miRNA transcription, plasma proteins, and sera and urinary metabolites. Results Maternal smoking during pregnancy was associated with DNA methylation changes at 18 loci in child blood. DNA methylation at 5 of these loci was related to expression of the nearby genes. However, the expression of these genes themselves was only weakly associated with maternal smoking. Conversely, childhood SHS was not associated with blood DNA methylation or transcription patterns, but with reduced levels of several serum metabolites and with increased plasma PAI1 (plasminogen activator inhibitor-1), a protein that inhibits fibrinolysis. Some of the in utero and childhood smoking-related molecular marks showed dose-response trends, with stronger effects with higher dose or longer duration of the exposure. Conclusion In this first study covering multi-layer molecular features, pregnancy and childhood exposure to tobacco smoke were associated with distinct molecular phenotypes in children. The persistent and dose-dependent changes in the methylome make CpGs good candidates to develop biomarkers of past exposure. Moreover, compared to methylation, the weak association of maternal smoking in pregnancy with gene expression suggests different reversal rates and a methylation-based memory to past exposures. Finally, certain metabolites and protein markers evidenced potential early biological effects of postnatal SHS, such as fibrinolysis.
Published: 2020
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7. Genetic evaluation of cardiomyopathies in Qatar identifies enrichment of pathogenic sarcomere gene variants and possible founder disease mutations in the Arabs

Author: Kholoud N. Al‐Shafai, Mohammed Al‐Hashemi, Chidambaram Manickam, Rania Musa, Senthil Selvaraj, Najeeb Syed, Fazulur Vempalli, Muneera Ali, Magdi Yacoub, and Xavier Estivill
Subjects: cardiomyopathy, targeted sequencing, genetic variants, Qatar, Genetics, QH426-470
Abstract: Abstract Background Hypertrophic cardiomyopathy (HCM) and dilated cardiomyopathy (DCM) are serious inherited heart diseases with various causative mutations identified. The full spectrum of causative mutations remains to be discovered, especially in understudied populations. Methods Here, we established the DOHA Registry and Biobank for cardiomyopathies in Qatar, followed by sequencing of 174 genes on 51 HCM and 53 DCM patients, and 31 relatives. Results In HCM, the analysis of 25 HCM‐associated genes showed that 20% of HCM cases had putative pathogenic variants for cardiomyopathy, mainly in sarcomere genes. Additional 49% of HCM cases had variants of uncertain significance, while 31% of HCM cases had likely benign variant(s) or had no variants identified within the analyzed HCM genes. In DCM, 56 putative DCM genes were analyzed. Eight percent of DCM cases had putative pathogenic variants for DCM, in the TTN gene while 70% of cases had variants of uncertain significance, in the analyzed DCM genes, that will need further pathogenicity assessment. Moreover, 22% of DCM cases remain unexplained, by having likely benign variant(s) or having no variants detected in any of the analyzed DCM genes. Conclusion We identified or replicated at least four recurrent variants among cardiomyopathy patients, which could be founder disease mutations in the Arabic population, including a frameshift variant (c.1371_1381dupTATCCAGTTAT) of unknown significance in the FKTN gene which seems to cause DCM in homozygosity, and HCM in heterozygosity. In vivo and/or in vitro functional validation need to be pursued in order to assess the pathogenicity of the identified variants.
Published: 2021
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8. Genome-wide association study in frontal fibrosing alopecia identifies four susceptibility loci including HLA-B*07:02

Author: Christos Tziotzios, Christos Petridis, Nick Dand, Chrysanthi Ainali, Jake R. Saklatvala, Venu Pullabhatla, Alexandros Onoufriadis, Rashida Pramanik, David Baudry, Sang Hyuck Lee, Kristie Wood, Lu Liu, Seth Seegobin, Gregory A. Michelotti, Su M. Lwin, Evangelos A. A. Christou, Charles J. Curtis, Emanuele de Rinaldis, Alka Saxena, Susan Holmes, Matthew Harries, Ioulios Palamaras, Fiona Cunningham, Gregory Parkins, Manjit Kaur, Paul Farrant, Andrew McDonagh, Andrew Messenger, Jennifer Jones, Victoria Jolliffe, Iaisha Ali, Michael Ardern-Jones, Charles Mitchell, Nigel Burrows, Ravinder Atkar, Cedric Banfield, Anton Alexandroff, Caroline Champagne, Hywel L. Cooper, Sergio Vañó-Galván, Ana Maria Molina-Ruiz, Nerea Ormaechea Perez, Girish K. Patel, Abby Macbeth, Melanie Page, Alyson Bryden, Megan Mowbray, Shyamal Wahie, Keith Armstrong, Nicola Cooke, Mark Goodfield, Irene Man, David de Berker, Giles Dunnill, Anita Takwale, Archana Rao, Tee-Wei Siah, Rodney Sinclair, Martin S. Wade, Ncoza C. Dlova, Jane Setterfield, Fiona Lewis, Kapil Bhargava, Niall Kirkpatrick, Xavier Estivill, Catherine M. Stefanato, Carsten Flohr, Timothy Spector, Fiona M. Watt, Catherine H. Smith, Jonathan N. Barker, David A. Fenton, Michael A. Simpson, and John A. McGrath
Subjects: Science
Abstract: Frontal fibrosing alopecia (FFA) features lichenoid cutaneous inflammation and scarring hair loss. Here, Tziotzios et al. identify four genetic loci associated with FFA by GWAS followed by Bayesian fine-mapping, co-localisation and HLA imputation which highlights HLA-B*07:02 as a risk factor.
Published: 2019
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9. miRTrace reveals the organismal origins of microRNA sequencing data

Author: Wenjing Kang, Yrin Eldfjell, Bastian Fromm, Xavier Estivill, Inna Biryukova, and Marc R. Friedländer
Subjects: Biology (General), QH301-705.5, Genetics, QH426-470
Abstract: Abstract We present here miRTrace, the first algorithm to trace microRNA sequencing data back to their taxonomic origins. This is a challenge with profound implications for forensics, parasitology, food control, and research settings where cross-contamination can compromise results. miRTrace accurately (> 99%) assigns real and simulated data to 14 important animal and plant groups, sensitively detects parasitic infection in mammals, and discovers the primate origin of single cells. Applying our algorithm to over 700 public datasets, we find evidence that over 7% are cross-contaminated and present a novel solution to clean these computationally, even after sequencing has occurred. miRTrace is freely available at https://github.com/friedlanderlab/mirtrace.
Published: 2018
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10. Efficient and flexible Integration of variant characteristics in rare variant association studies using integrated nested Laplace approximation.

Author: Hana Susak, Laura Serra-Saurina, German Demidov, Raquel Rabionet, Laura Domènech, Mattia Bosio, Francesc Muyas, Xavier Estivill, Geòrgia Escaramís, and Stephan Ossowski
Subjects: Biology (General), QH301-705.5
Abstract: Rare variants are thought to play an important role in the etiology of complex diseases and may explain a significant fraction of the missing heritability in genetic disease studies. Next-generation sequencing facilitates the association of rare variants in coding or regulatory regions with complex diseases in large cohorts at genome-wide scale. However, rare variant association studies (RVAS) still lack power when cohorts are small to medium-sized and if genetic variation explains a small fraction of phenotypic variance. Here we present a novel Bayesian rare variant Association Test using Integrated Nested Laplace Approximation (BATI). Unlike existing RVAS tests, BATI allows integration of individual or variant-specific features as covariates, while efficiently performing inference based on full model estimation. We demonstrate that BATI outperforms established RVAS methods on realistic, semi-synthetic whole-exome sequencing cohorts, especially when using meaningful biological context, such as functional annotation. We show that BATI achieves power above 70% in scenarios in which competing tests fail to identify risk genes, e.g. when risk variants in sum explain less than 0.5% of phenotypic variance. We have integrated BATI, together with five existing RVAS tests in the 'Rare Variant Genome Wide Association Study' (rvGWAS) framework for data analyzed by whole-exome or whole genome sequencing. rvGWAS supports rare variant association for genes or any other biological unit such as promoters, while allowing the analysis of essential functionalities like quality control or filtering. Applying rvGWAS to a Chronic Lymphocytic Leukemia study we identified eight candidate predisposition genes, including EHMT2 and COPS7A.
Published: 2021
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11. Barriers and Considerations for Diagnosing Rare Diseases in Indigenous Populations

Author: Carla S. D'Angelo, Azure Hermes, Christopher R. McMaster, Elissa Prichep, Étienne Richer, Francois H. van der Westhuizen, Gabriela M. Repetto, Gong Mengchun, Helen Malherbe, Juergen K. V. Reichardt, Laura Arbour, Maui Hudson, Kelly du Plessis, Melissa Haendel, Phillip Wilcox, Sally Ann Lynch, Shamir Rind, Simon Easteal, Xavier Estivill, Yarlalu Thomas, and Gareth Baynam
Subjects: Indigenous populations, genomics, diagnosis, rare diseases, equity, Pediatrics, RJ1-570
Abstract: Advances in omics and specifically genomic technologies are increasingly transforming rare disease diagnosis. However, the benefits of these advances are disproportionately experienced within and between populations, with Indigenous populations frequently experiencing diagnostic and therapeutic inequities. The International Rare Disease Research Consortium (IRDiRC) multi-stakeholder partnership has been advancing toward the vision of all people living with a rare disease receiving an accurate diagnosis, care, and available therapy within 1 year of coming to medical attention. In order to further progress toward this vision, IRDiRC has created a taskforce to explore the access barriers to diagnosis of rare genetic diseases faced by Indigenous peoples, with a view of developing recommendations to overcome them. Herein, we provide an overview of the state of play of current barriers and considerations identified by the taskforce, to further stimulate awareness of these issues and the passage toward solutions. We focus on analyzing barriers to accessing genetic services, participating in genomic research, and other aspects such as concerns about data sharing, the handling of biospecimens, and the importance of capacity building.
Published: 2020
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12. Cell type-specific novel long non-coding RNA and circular RNA in the BLUEPRINT hematopoietic transcriptomes atlas

Author: Luigi Grassi, Osagie G. Izuogu, Natasha A.N. Jorge, Denis Seyres, Mariona Bustamante, Frances Burden, Samantha Farrow, Neda Farahi, Fergal J. Martin, Adam Frankish, Jonathan M. Mudge, Myrto Kostadima, Romina Petersen, John J. Lambourne, Sophia Rowlston, Enca Martin-Rendon, Laura Clarke, Kate Downes, Xavier Estivill, Paul Flicek, Joost H.A. Martens, Marie-Laure Yaspo, Hendrik G. Stunnenberg, Willem H. Ouwehand, Fabio Passetti, Ernest Turro, and Mattia Frontini
Subjects: Diseases of the blood and blood-forming organs, RC633-647.5
Abstract: Transcriptional profiling of hematopoietic cell subpopulations has helped to characterize the developmental stages of the hematopoietic system and the molecular bases of malignant and non-malignant blood diseases. Previously, only the genes targeted by expression microarrays could be profiled genome-wide. High-throughput RNA sequencing, however, encompasses a broader repertoire of RNA molecules, without restriction to previously annotated genes. We analyzed the BLUEPRINT consortium RNA-sequencing data for mature hematopoietic cell types. The data comprised 90 total RNA-sequencing samples, each composed of one of 27 cell types, and 32 small RNA-sequencing samples, each composed of one of 11 cell types. We estimated gene and isoform expression levels for each cell type using existing annotations from Ensembl. We then used guided transcriptome assembly to discover unannotated transcripts. We identified hundreds of novel non-coding RNA genes and showed that the majority have cell type-dependent expression. We also characterized the expression of circular RNA and found that these are also cell type-specific. These analyses refine the active transcriptional landscape of mature hematopoietic cells, highlight abundant genes and transcriptional isoforms for each blood cell type, and provide a valuable resource for researchers of hematologic development and diseases. Finally, we made the data accessible via a web-based interface: https://blueprint.haem.cam.ac.uk/bloodatlas/.
Published: 2020
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13. Circulating miRNAs, isomiRs and small RNA clusters in human plasma and breast milk.

Author: Mercedes Rubio, Mariona Bustamante, Carles Hernandez-Ferrer, Dietmar Fernandez-Orth, Lorena Pantano, Yaris Sarria, Maria Piqué-Borras, Kilian Vellve, Silvia Agramunt, Ramon Carreras, Xavier Estivill, Juan R Gonzalez, and Alfredo Mayor
Subjects: Medicine, Science
Abstract: Circulating small RNAs, including miRNAs but also isomiRs and other RNA species, have the potential to be used as non-invasive biomarkers for communicable and non-communicable diseases. This study aims to characterize and compare small RNA profiles in human biofluids. For this purpose, RNA was extracted from plasma and breast milk samples from 15 healthy postpartum mothers. Small RNA libraries were prepared with the NEBNext® small RNA library preparation kit and sequenced in an Illumina HiSeq2000 platform. miRNAs, isomiRs and clusters of small RNAs were annotated using seqBuster/seqCluster framework in 5 plasma and 10 milk samples that passed the initial quality control. The RNA yield was 81 ng/mL [standard deviation (SD): 41] and 3985 ng/mL (SD: 3767) for plasma and breast milk, respectively. Mean number of good quality reads was 4.04 million (M) (40.01% of the reads) in plasma and 12.5M (89.6%) in breast milk. One thousand one hundred eighty two miRNAs, 12,084 isomiRs and 1,053 small RNA clusters that included piwi-interfering RNAs (piRNAs), tRNAs, small nucleolar RNAs (snoRNA) and small nuclear RNAs (snRNAs) were detected. Samples grouped by biofluid, with 308 miRNAs, 1,790 isomiRs and 778 small RNA clusters differentially detected. In summary, plasma and milk showed a different small RNA profile. In both, miRNAs, piRNAs, tRNAs, snRNAs, and snoRNAs were identified, confirming the presence of non-miRNA species in plasma, and describing them for the first time in milk.
Published: 2018
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14. Blood expression profiles of fragile X premutation carriers identify candidate genes involved in neurodegenerative and infertility phenotypes

Author: Elisabet Mateu-Huertas, Laia Rodriguez-Revenga, Maria Isabel Alvarez-Mora, Irene Madrigal, Rob Willemsen, Montserrat Milà, Eulàlia Martí, and Xavier Estivill
Subjects: Fragile X Tremor/Ataxia Syndrome, Fragile X associated Premature Ovarian Insufficiency, Early at menopause 1 (EAP1), Histone deacetylase 5 (HDAC5), Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract: Male premutation carriers presenting between 55 and 200 CGG repeats in the Fragile-X-associated (FMR1) gene are at risk of developing Fragile X Tremor/Ataxia Syndrome (FXTAS), and females undergo Premature Ovarian Failure (POF1). Here, we have evaluated gene expression profiles from blood in male FMR1 premutation carriers and detected a strong deregulation of genes enriched in FXTAS relevant biological pathways, including inflammation, neuronal homeostasis and viability. Gene expression profiling distinguished between control individuals, carriers with FXTAS and carriers without FXTAS, with levels of expanded FMR1 mRNA being increased in FXTAS patients. In vitro studies in a neuronal cell model indicate that expression levels of expanded FMR1 5′-UTR are relevant in modulating the transcriptome. Thus, perturbations of the transcriptome may be an interplay between the CGG expansion size and FMR1 expression levels. Several deregulated genes (DFFA, BCL2L11, BCL2L1, APP, SOD1, RNF10, HDAC5, KCNC3, ATXN7, ATXN3 and EAP1) were validated in brain samples of a FXTAS mouse model. Downregulation of EAP1, a gene involved in the female reproductive system physiology, was confirmed in female carriers. Decreased levels were detected in female carriers with POF1 compared to those without POF1, suggesting that EAP1 levels contribute to ovarian insufficiency. In summary, gene expression profiling in blood has uncovered mechanisms that may underlie different pathological aspects of the premutation. A better understanding of the transcriptome dynamics in relation with expanded FMR1 mRNA expression levels and CGG expansion size may provide mechanistic insights into the disease process and a more accurate FXTAS diagnosis to the myriad of phenotypes associated with the premutation.
Published: 2014
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15. Copy number variants and common disorders: filling the gaps and exploring complexity in genome-wide association studies.

Author: Xavier Estivill and Lluís Armengol
Subjects: Genetics, QH426-470
Abstract: Genome-wide association scans (GWASs) using single nucleotide polymorphisms (SNPs) have been completed successfully for several common disorders and have detected over 30 new associations. Considering the large sample sizes and genome-wide SNP coverage of the scans, one might have expected many of the common variants underpinning the genetic component of various disorders to have been identified by now. However, these studies have not evaluated the contribution of other forms of genetic variation, such as structural variation, mainly in the form of copy number variants (CNVs). Known CNVs account for over 15% of the assembled human genome sequence. Since CNVs are not easily tagged by SNPs, might have a wide range of copy number variability, and often fall in genomic regions not well covered by whole-genome arrays or not genotyped by the HapMap project, current GWASs have largely missed the contribution of CNVs to complex disorders. In fact, some CNVs have already been reported to show association with several complex disorders using candidate gene/region approaches, underpinning the importance of regions not investigated in current GWASs. This reveals the need for new generation arrays (some already in the market) and the use of tailored approaches to explore the full dimension of genome variability beyond the single nucleotide scale.
Published: 2007
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16. Transgenic mice overexpressing the full-length neurotrophin receptor TrkC exhibit increased catecholaminergic neuron density in specific brain areas and increased anxiety-like behavior and panic reaction

Author: Mara Dierssen, Mònica Gratacòs, Ignasi Sahún, Miguel Martín, Xavier Gallego, Alejandro Amador-Arjona, María Martínez de Lagrán, Patricia Murtra, Eulalia Martí, Miguel A. Pujana, Isidre Ferrer, Esther Dalfó, Carmen Martínez-Cué, Jesús Flórez, Jesús F. Torres-Peraza, Jordi Alberch, Rafael Maldonado, Cristina Fillat, and Xavier Estivill
Subjects: Panic disorder, NT-3, TrkC, Anxiety-like behavior, Mouse defense test battery, Locus coeruleus, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract: Accumulating evidence has suggested that neurotrophins participate in the pathophysiology of mood disorders. We have developed transgenic mice overexpressing the full-length neurotrophin-3 receptor TrkC (TgNTRK3) in the central nervous system. TgNTRK3 mice show increased anxiety-like behavior and enhancement of panic reaction in the mouse defense test battery, along with an increase in the number and density of catecholaminergic (tyrosine hydroxylase positive) neurons in locus coeruleus and substantia nigra. Furthermore, treatment of TgNTRK3 mice with diazepam significantly attenuated the anxiety-like behaviors in the plus maze. These results provide evidence for the involvement of TrkC in the development of noradrenergic neurons in the central nervous system with consequences on anxiety-like behavior and panic reaction. Thus, changes in TrkC expression levels could contribute to the phenotypic expression of panic disorder through a trophic effect on noradrenergic neurons in the locus coeruleus. Our results demonstrate that the elevated NT3-TrkC tone via overexpression of TrkC in the brain may constitute a molecular mechanism for the expression of anxiety and anxiety.
Published: 2006
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17. Validation and genotyping of multiple human polymorphic inversions mediated by inverted repeats reveals a high degree of recurrence.

Author: Cristina Aguado, Magdalena Gayà-Vidal, Sergi Villatoro, Meritxell Oliva, David Izquierdo, Carla Giner-Delgado, Víctor Montalvo, Judit García-González, Alexander Martínez-Fundichely, Laia Capilla, Aurora Ruiz-Herrera, Xavier Estivill, Marta Puig, and Mario Cáceres
Subjects: Genetics, QH426-470
Abstract: In recent years different types of structural variants (SVs) have been discovered in the human genome and their functional impact has become increasingly clear. Inversions, however, are poorly characterized and more difficult to study, especially those mediated by inverted repeats or segmental duplications. Here, we describe the results of a simple and fast inverse PCR (iPCR) protocol for high-throughput genotyping of a wide variety of inversions using a small amount of DNA. In particular, we analyzed 22 inversions predicted in humans ranging from 5.1 kb to 226 kb and mediated by inverted repeat sequences of 1.6-24 kb. First, we validated 17 of the 22 inversions in a panel of nine HapMap individuals from different populations, and we genotyped them in 68 additional individuals of European origin, with correct genetic transmission in ∼ 12 mother-father-child trios. Global inversion minor allele frequency varied between 1% and 49% and inversion genotypes were consistent with Hardy-Weinberg equilibrium. By analyzing the nucleotide variation and the haplotypes in these regions, we found that only four inversions have linked tag-SNPs and that in many cases there are multiple shared SNPs between standard and inverted chromosomes, suggesting an unexpected high degree of inversion recurrence during human evolution. iPCR was also used to check 16 of these inversions in four chimpanzees and two gorillas, and 10 showed both orientations either within or between species, providing additional support for their multiple origin. Finally, we have identified several inversions that include genes in the inverted or breakpoint regions, and at least one disrupts a potential coding gene. Thus, these results represent a significant advance in our understanding of inversion polymorphism in human populations and challenge the common view of a single origin of inversions, with important implications for inversion analysis in SNP-based studies.
Published: 2014
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18. Association of Irisin with Fat Mass, Resting Energy Expenditure, and Daily Activity in Conditions of Extreme Body Mass Index

Author: María Pardo, Ana B. Crujeiras, María Amil, Zaida Aguera, Susana Jiménez-Murcia, Rosa Baños, Cristina Botella, Rafael de la Torre, Xavier Estivill, Ana B. Fagundo, Jose M. Fernández-Real, José C. Fernández-García, Gema Fruhbeck, Javier Gómez-Ambrosi, Roser Rodríguez, Francisco J. Tinahones, Fernando Fernández-Aranda, and Felipe F. Casanueva
Subjects: Diseases of the endocrine glands. Clinical endocrinology, RC648-665
Abstract: FNDC5/irisin has been recently postulated as beneficial in the treatment of obesity and diabetes because it is induced in muscle by exercise, increasing energy expenditure. However, recent reports have shown that WAT also secretes irisin and that circulating irisin is elevated in obese subjects. The aim of this study was to evaluate irisin levels in conditions of extreme BMI and its correlation with basal metabolism and daily activity. The study involved 145 female patients, including 96 with extreme BMIs (30 anorexic (AN) and 66 obese (OB)) and 49 healthy normal weight (NW). The plasma irisin levels were significantly elevated in the OB patients compared with the AN and NW patients. Irisin also correlated positively with body weight, BMI, and fat mass. The OB patients exhibited the highest REE and higher daily physical activity compared with the AN patients but lower activity compared with the NW patients. The irisin levels were inversely correlated with daily physical activity and directly correlated with REE. Fat mass contributed to most of the variability of the irisin plasma levels independently of the other studied parameters. Conclusion. Irisin levels are influenced by energy expenditure independently of daily physical activity but fat mass is the main contributing factor.
Published: 2014
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19. A novel G21R mutation of the GJB2 gene causes autosomal dominant non-syndromic congenital deafness in a Cuban family

Author: Raquel Rabionet, Estela Morales-Peralta, Núria López-Bigas, Maria Lourdes Arbonés, and Xavier Estivill
Subjects: connexin 26, GJB2, DFNA3, hearing impairment, Genetics, QH426-470
Abstract: Deafness is a complex disorder affecting 1/1000 infants. In developed countries, more than 50% of deafness cases are thought to have a genetic cause. At least 40 loci for dominant non-syndromic deafness and another 30 for recessive non-syndromic deafness have been described. Mutations in the GJB2 gene are the cause of an important number of cases of non-syndromic recessive deafness but are not as common in non-syndromic dominant deafness cases. We describe here a new dominant mutation (G21R) in the GJB2 gene which causes deafness and has been identified in a three generation Cuban family with dominant non-syndromic congenital sensorineural profound deafness.
Published: 2006
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20. Cluster analysis of clinical data identifies fibromyalgia subgroups.

Author: Elisa Docampo, Antonio Collado, Geòrgia Escaramís, Jordi Carbonell, Javier Rivera, Javier Vidal, José Alegre, Raquel Rabionet, and Xavier Estivill
Subjects: Medicine, Science
Abstract: INTRODUCTION: Fibromyalgia (FM) is mainly characterized by widespread pain and multiple accompanying symptoms, which hinder FM assessment and management. In order to reduce FM heterogeneity we classified clinical data into simplified dimensions that were used to define FM subgroups. MATERIAL AND METHODS: 48 variables were evaluated in 1,446 Spanish FM cases fulfilling 1990 ACR FM criteria. A partitioning analysis was performed to find groups of variables similar to each other. Similarities between variables were identified and the variables were grouped into dimensions. This was performed in a subset of 559 patients, and cross-validated in the remaining 887 patients. For each sample and dimension, a composite index was obtained based on the weights of the variables included in the dimension. Finally, a clustering procedure was applied to the indexes, resulting in FM subgroups. RESULTS: VARIABLES CLUSTERED INTO THREE INDEPENDENT DIMENSIONS: "symptomatology", "comorbidities" and "clinical scales". Only the two first dimensions were considered for the construction of FM subgroups. Resulting scores classified FM samples into three subgroups: low symptomatology and comorbidities (Cluster 1), high symptomatology and comorbidities (Cluster 2), and high symptomatology but low comorbidities (Cluster 3), showing differences in measures of disease severity. CONCLUSIONS: We have identified three subgroups of FM samples in a large cohort of FM by clustering clinical data. Our analysis stresses the importance of family and personal history of FM comorbidities. Also, the resulting patient clusters could indicate different forms of the disease, relevant to future research, and might have an impact on clinical assessment.
Published: 2013
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21. Correction: PeSV-Fisher: Identification of Somatic and Non-Somatic Structural Variants Using Next Generation Sequencing Data.

Author: Geòrgia Escaramís, Cristian Tornador, Laia Bassaganyas, Raquel Rabionet, Jose M. C. Tubio, Alexander Martínez-Fundichely, Mario Cáceres, Marta Gut, Stephan Ossowski, and Xavier Estivill
Subjects: Medicine, Science
Published: 2013
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22. PeSV-Fisher: identification of somatic and non-somatic structural variants using next generation sequencing data.

Author: Geòrgia Escaramís, Cristian Tornador, Laia Bassaganyas, Raquel Rabionet, Jose M C Tubio, Alexander Martínez-Fundichely, Mario Cáceres, Marta Gut, Stephan Ossowski, and Xavier Estivill
Subjects: Medicine, Science
Abstract: UNLABELLED: Next-generation sequencing technologies expedited research to develop efficient computational tools for the identification of structural variants (SVs) and their use to study human diseases. As deeper data is obtained, the existence of higher complexity SVs in some genomes becomes more evident, but the detection and definition of most of these complex rearrangements is still in its infancy. The full characterization of SVs is a key aspect for discovering their biological implications. Here we present a pipeline (PeSV-Fisher) for the detection of deletions, gains, intra- and inter-chromosomal translocations, and inversions, at very reasonable computational costs. We further provide comprehensive information on co-localization of SVs in the genome, a crucial aspect for studying their biological consequences. The algorithm uses a combination of methods based on paired-reads and read-depth strategies. PeSV-Fisher has been designed with the aim to facilitate identification of somatic variation, and, as such, it is capable of analysing two or more samples simultaneously, producing a list of non-shared variants between samples. We tested PeSV-Fisher on available sequencing data, and compared its behaviour to that of frequently deployed tools (BreakDancer and VariationHunter). We have also tested this algorithm on our own sequencing data, obtained from a tumour and a normal blood sample of a patient with chronic lymphocytic leukaemia, on which we have also validated the results by targeted re-sequencing of different kinds of predictions. This allowed us to determine confidence parameters that influence the reliability of breakpoint predictions. AVAILABILITY: PeSV-Fisher is available at http://gd.crg.eu/tools.
Published: 2013
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23. A pathogenic mechanism in Huntington's disease involves small CAG-repeated RNAs with neurotoxic activity.

Author: Mónica Bañez-Coronel, Silvia Porta, Birgit Kagerbauer, Elisabet Mateu-Huertas, Lorena Pantano, Isidre Ferrer, Manuel Guzmán, Xavier Estivill, and Eulàlia Martí
Subjects: Genetics, QH426-470
Abstract: Huntington's disease (HD) is an autosomal dominantly inherited disorder caused by the expansion of CAG repeats in the Huntingtin (HTT) gene. The abnormally extended polyglutamine in the HTT protein encoded by the CAG repeats has toxic effects. Here, we provide evidence to support that the mutant HTT CAG repeats interfere with cell viability at the RNA level. In human neuronal cells, expanded HTT exon-1 mRNA with CAG repeat lengths above the threshold for complete penetrance (40 or greater) induced cell death and increased levels of small CAG-repeated RNAs (sCAGs), of ≈21 nucleotides in a Dicer-dependent manner. The severity of the toxic effect of HTT mRNA and sCAG generation correlated with CAG expansion length. Small RNAs obtained from cells expressing mutant HTT and from HD human brains significantly decreased neuronal viability, in an Ago2-dependent mechanism. In both cases, the use of anti-miRs specific for sCAGs efficiently blocked the toxic effect, supporting a key role of sCAGs in HTT-mediated toxicity. Luciferase-reporter assays showed that expanded HTT silences the expression of CTG-containing genes that are down-regulated in HD. These results suggest a possible link between HD and sCAG expression with an aberrant activation of the siRNA/miRNA gene silencing machinery, which may trigger a detrimental response. The identification of the specific cellular processes affected by sCAGs may provide insights into the pathogenic mechanisms underlying HD, offering opportunities to develop new therapeutic approaches.
Published: 2012
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24. Genetic variants of the FADS gene cluster and ELOVL gene family, colostrums LC-PUFA levels, breastfeeding, and child cognition.

Author: Eva Morales, Mariona Bustamante, Juan Ramon Gonzalez, Monica Guxens, Maties Torrent, Michelle Mendez, Raquel Garcia-Esteban, Jordi Julvez, Joan Forns, Martine Vrijheid, Carolina Molto-Puigmarti, Carmen Lopez-Sabater, Xavier Estivill, and Jordi Sunyer
Subjects: Medicine, Science
Abstract: IntroductionBreastfeeding effects on cognition are attributed to long-chain polyunsaturated fatty acids (LC-PUFAs), but controversy persists. Genetic variation in fatty acid desaturase (FADS) and elongase (ELOVL) enzymes has been overlooked when studying the effects of LC-PUFAs supply on cognition. We aimed to: 1) to determine whether maternal genetic variants in the FADS cluster and ELOVL genes contribute to differences in LC-PUFA levels in colostrum; 2) to analyze whether these maternal variants are related to child cognition; and 3) to assess whether children's variants modify breastfeeding effects on cognition.MethodsData come from two population-based birth cohorts (n = 400 mother-child pairs from INMA-Sabadell; and n = 340 children from INMA-Menorca). LC-PUFAs were measured in 270 colostrum samples from INMA-Sabadell. Tag SNPs were genotyped both in mothers and children (13 in the FADS cluster, 6 in ELOVL2, and 7 in ELOVL5). Child cognition was assessed at 14 mo and 4 y using the Bayley Scales of Infant Development and the McCarthy Scales of Children's Abilities, respectively.ResultsChildren of mothers carrying genetic variants associated with lower FADS1 activity (regulating AA and EPA synthesis), higher FADS2 activity (regulating DHA synthesis), and with higher EPA/AA and DHA/AA ratios in colostrum showed a significant advantage in cognition at 14 mo (3.5 to 5.3 points). Not being breastfed conferred an 8- to 9-point disadvantage in cognition among children GG homozygote for rs174468 (low FADS1 activity) but not among those with the A allele. Moreover, not being breastfed resulted in a disadvantage in cognition (5 to 8 points) among children CC homozygote for rs2397142 (low ELOVL5 activity), but not among those carrying the G allele.ConclusionGenetically determined maternal supplies of LC-PUFAs during pregnancy and lactation appear to be crucial for child cognition. Breastfeeding effects on cognition are modified by child genetic variation in fatty acid desaturase and elongase enzymes.
Published: 2011
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25. Correction: Genetic Structure of Europeans: A View from the North–East.

Author: Mari Nelis, Tõnu Esko, Reedik Mägi, Fritz Zimprich, Alexander Zimprich, Draga Toncheva, Sena Karachanak, Tereza Piskáčková, Ivan Balaščák, Leena Peltonen, Eveliina Jakkula, Karola Rehnström, Mark Lathrop, Simon Heath, Pilar Galan, Stefan Schreiber, Thomas Meitinger, Arne Pfeufer, H-Erich Wichmann, Béla Melegh, Noémi Polgár, Daniela Toniolo, Paolo Gasparini, Pio D'Adamo, Janis Klovins, Liene Nikitina-Zake, Vaidutis Kučinskas, Jūratė Kasnauskienė, Jan Lubinski, Tadeusz Debniak, Svetlana Limborska, Andrey Khrunin, Xavier Estivill, Raquel Rabionet, Sara Marsal, Antonio Julià, Stylianos E. Antonarakis, Samuel Deutsch, Christelle Borel, Homa Attar, Maryline Gagnebin, Milan Macek, Michael Krawczak, Maido Remm, and Andres Metspalu
Subjects: Medicine, Science
Published: 2010
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26. Correction: Nucleotide, Cytogenetic and Expression Impact of the Human Chromosome 8p23.1 Inversion Polymorphism.

Author: Nina Bosch, Marta Morell, Immaculada Ponsa, Josep Maria Mercader, Lluís Armengol, and Xavier Estivill
Subjects: Medicine, Science
Published: 2010
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27. Nucleotide, cytogenetic and expression impact of the human chromosome 8p23.1 inversion polymorphism.

Author: Nina Bosch, Marta Morell, Immaculada Ponsa, Josep Maria Mercader, Lluís Armengol, and Xavier Estivill
Subjects: Medicine, Science
Abstract: BACKGROUND:The human chromosome 8p23.1 region contains a 3.8-4.5 Mb segment which can be found in different orientations (defined as genomic inversion) among individuals. The identification of single nucleotide polymorphisms (SNPs) tightly linked to the genomic orientation of a given region should be useful to indirectly evaluate the genotypes of large genomic orientations in the individuals. RESULTS:We have identified 16 SNPs, which are in linkage disequilibrium (LD) with the 8p23.1 inversion as detected by fluorescent in situ hybridization (FISH). The variability of the 8p23.1 orientation in 150 HapMap samples was predicted using this set of SNPs and was verified by FISH in a subset of samples. Four genes (NEIL2, MSRA, CTSB and BLK) were found differentially expressed (p
Published: 2009
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28. Identification of copy number variants defining genomic differences among major human groups.

Author: Lluís Armengol, Sergi Villatoro, Juan R González, Lorena Pantano, Manel García-Aragonés, Raquel Rabionet, Mario Cáceres, and Xavier Estivill
Subjects: Medicine, Science
Abstract: BACKGROUND:Understanding the genetic contribution to phenotype variation of human groups is necessary to elucidate differences in disease predisposition and response to pharmaceutical treatments in different human populations. METHODOLOGY/PRINCIPAL FINDINGS:We have investigated the genome-wide profile of structural variation on pooled samples from the three populations studied in the HapMap project by comparative genome hybridization (CGH) in different array platforms. We have identified and experimentally validated 33 genomic loci that show significant copy number differences from one population to the other. Interestingly, we found an enrichment of genes related to environment adaptation (immune response, lipid metabolism and extracellular space) within these regions and the study of expression data revealed that more than half of the copy number variants (CNVs) translate into gene-expression differences among populations, suggesting that they could have functional consequences. In addition, the identification of single nucleotide polymorphisms (SNPs) that are in linkage disequilibrium with the copy number alleles allowed us to detect evidences of population differentiation and recent selection at the nucleotide variation level. CONCLUSIONS:Overall, our results provide a comprehensive view of relevant copy number changes that might play a role in phenotypic differences among major human populations, and generate a list of interesting candidates for future studies.
Published: 2009
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29. Genetic structure of Europeans: a view from the North-East.

Author: Mari Nelis, Tõnu Esko, Reedik Mägi, Fritz Zimprich, Alexander Zimprich, Draga Toncheva, Sena Karachanak, Tereza Piskácková, Ivan Balascák, Leena Peltonen, Eveliina Jakkula, Karola Rehnström, Mark Lathrop, Simon Heath, Pilar Galan, Stefan Schreiber, Thomas Meitinger, Arne Pfeufer, H-Erich Wichmann, Béla Melegh, Noémi Polgár, Daniela Toniolo, Paolo Gasparini, Pio D'Adamo, Janis Klovins, Liene Nikitina-Zake, Vaidutis Kucinskas, Jūrate Kasnauskiene, Jan Lubinski, Tadeusz Debniak, Svetlana Limborska, Andrey Khrunin, Xavier Estivill, Raquel Rabionet, Sara Marsal, Antonio Julià, Stylianos E Antonarakis, Samuel Deutsch, Christelle Borel, Homa Attar, Maryline Gagnebin, Milan Macek, Michael Krawczak, Maido Remm, and Andres Metspalu
Subjects: Medicine, Science
Abstract: Using principal component (PC) analysis, we studied the genetic constitution of 3,112 individuals from Europe as portrayed by more than 270,000 single nucleotide polymorphisms (SNPs) genotyped with the Illumina Infinium platform. In cohorts where the sample size was >100, one hundred randomly chosen samples were used for analysis to minimize the sample size effect, resulting in a total of 1,564 samples. This analysis revealed that the genetic structure of the European population correlates closely with geography. The first two PCs highlight the genetic diversity corresponding to the northwest to southeast gradient and position the populations according to their approximate geographic origin. The resulting genetic map forms a triangular structure with a) Finland, b) the Baltic region, Poland and Western Russia, and c) Italy as its vertexes, and with d) Central- and Western Europe in its centre. Inter- and intra- population genetic differences were quantified by the inflation factor lambda (lambda) (ranging from 1.00 to 4.21), fixation index (F(st)) (ranging from 0.000 to 0.023), and by the number of markers exhibiting significant allele frequency differences in pair-wise population comparisons. The estimated lambda was used to assess the real diminishing impact to association statistics when two distinct populations are merged directly in an analysis. When the PC analysis was confined to the 1,019 Estonian individuals (0.1% of the Estonian population), a fine structure emerged that correlated with the geography of individual counties. With at least two cohorts available from several countries, genetic substructures were investigated in Czech, Finnish, German, Estonian and Italian populations. Together with previously published data, our results allow the creation of a comprehensive European genetic map that will greatly facilitate inter-population genetic studies including genome wide association studies (GWAS).
Published: 2009
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30. SNPs meet CNVs in genome-wide association studies: HGV2007 meeting report.

Author: Xavier Estivill, Nancy J Cox, Stephen J Chanock, Pui-Yan Kwok, Stephen W Scherer, and Anthony J Brookes
Subjects: Genetics, QH426-470
Published: 2008
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31. Analysis of incidental findings in Qatar genome participants reveals novel functional variants in LMNA and DSP

Author: Amal, Elfatih, Sahar I, Da'as, Doua, Abdelrahman, Hamdi, Mbarek, Idris, Mohammed, Waseem, Hasan, Khalid A, Fakhro, Xavier, Estivill, and Zohreh, Tatari
Subjects: Incidental Findings, Desmoplakins, Genetics, Animals, Humans, Genetic Predisposition to Disease, Genetic Testing, General Medicine, Lamin Type A, Qatar, Molecular Biology, Zebrafish, Genetics (clinical)
Abstract: In order to report clinically actionable incidental findings in genetic testing, the American College of Medical Genetics and Genomics (ACMG) recommended the evaluation of variants in 59 genes associated with highly penetrant mutations. However, there is a lack of epidemiological data on medically actionable rare variants in these genes in Arab populations. We used whole genome sequencing data from 6045 participants from the Qatar Genome Programme and integrated it with phenotypic data collected by the Qatar Biobank. We identified novel putative pathogenic variants in the 59 ACMG genes by filtering previously unrecorded variants based on computational prediction of pathogenicity, variant rarity and segregation evidence. We assessed the phenotypic associations of candidate variants in genes linked to cardiovascular diseases. Finally, we used a zebrafish knockdown and synthetic human mRNA co-injection assay to functionally characterize two of these novel variants. We assessed the zebrafish cardiac function in terms of heart rate, rhythm and hemodynamics, as well as the heart structure. We identified 52 492 novel variants, which have not been reported in global and disease-specific databases. A total of 74 novel variants were selected with potentially pathogenic effect. We prioritized two novel cardiovascular variants, DSP c.1841A > G (p.Asp614Gly) and LMNA c.326 T > G (p.Val109Gly) for functional characterization. Our results showed that both variants resulted in abnormal zebrafish heart rate, rhythm and structure. This study highlights medically actionable variants that are specific to the Middle Eastern Qatari population.
Published: 2022

32. Functional Characterization of the

Author: Moza, Alkowari, Meritxell, Espino-Guarch, Sahar, Daas, Doua, Abdelrahman, Waseem, Hasan, Navaneethakrishnan, Krishnamoorthy, Abbirami, Sathappan, Patrick, Sheehan, Nicholas Van, Panhuys, The Qatar Genome Program Research Consortium, and Xavier, Estivill
Subjects: Myosin Heavy Chains, Hearing Loss, Sensorineural, Mutation, Quality of Life, Animals, Humans, Deafness, Hearing Loss, Zebrafish, HeLa Cells
Abstract: Hereditary hearing loss (HHL) is a common genetic disorder accounting for at least 60% of pre-lingual deafness in children, of which 70% is inherited in an autosomal recessive pattern. The long tradition of consanguinity among the Qatari population has increased the prevalence of HHL, which negatively impacts the quality of life. Here, we functionally validated the pathogenicity of the c.178Ggt;C, p.E60Q mutation in the
Published: 2022

33. Changes in the stool and oropharyngeal microbiome in obsessive-compulsive disorder

Author: Cinto Segalàs, Raquel Rabionet, Marià Alemany, Pino Alonso, Sara Bertolín, Daniel Sanchez-Chinchilla, Jesse R. Willis, Marta Morell, Toni Gabaldón, Susanna Balcells, Geòrgia Escaramís, Xavier Estivill, Laura Domènech, Eva Real, and José M. Menchón
Subjects: Adult, DNA, Bacterial, Male, Obsessive-Compulsive Disorder, food.ingredient, Rikenellaceae, Firmicutes, Science, Oropharynx, Biology, Gut flora, Prevotellaceae, behavioral disciplines and activities, Article, Coprococcus, Feces, food, Microbiologia oral, RNA, Ribosomal, 16S, Brain-Gut Axis, mental disorders, Obsessive-compulsive disorder, Humans, Microbiome, Multidisciplinary, Excrements, Neurosi obsessiva, Lachnospiraceae, Fusobacteria, Middle Aged, biology.organism_classification, Healthy Volunteers, Gastrointestinal Microbiome, Obsessive compulsive disorder, Oral microbiology, Case-Control Studies, Immunology, Metagenome, Medicine, Female, Metagenomics, Biomarkers
Abstract: Although the etiology of obsessive-compulsive disorder (OCD) is largely unknown, it is accepted that OCD is a complex disorder. There is a known bi-directional interaction between the gut microbiome and brain activity. Several authors have reported associations between changes in gut microbiota and neuropsychiatric disorders, including depression or autism. Furthermore, a pediatric-onset neuropsychiatric OCD-related syndrome occurs after streptococcal infection, which might indicate that exposure to certain microbes could be involved in OCD susceptibility. However, only one study has investigated the microbiome of OCD patients to date. We performed 16S ribosomal RNA gene-based metagenomic sequencing to analyze the stool and oropharyngeal microbiome composition of 32 OCD cases and 32 age and gender matched controls. We estimated different α- and β-diversity measures and performed LEfSe and Wilcoxon tests to assess differences in bacterial distribution. OCD stool samples showed a trend towards lower bacterial α-diversity, as well as an increase of the relative abundance of Rikenellaceae, particularly of the genus Alistipes, and lower relative abundance of Prevotellaceae, and two genera within the Lachnospiraceae: Agathobacer and Coprococcus. However, we did not observe a different Bacteroidetes to Firmicutes ratio between OCD cases and controls. Analysis of the oropharyngeal microbiome composition showed a lower Fusobacteria to Actinobacteria ratio in OCD cases. In conclusion, we observed an imbalance in the gut and oropharyngeal microbiomes of OCD cases, including, in stool, an increase of bacteria from the Rikenellaceae family, associated with gut inflammation, and a decrease of bacteria from the Coprococcus genus, associated with DOPAC synthesis. This project was supported by grants from the Spanish ministry of science and innovation (MICINN; SAF2013-49108-R); the Carlos III Health Institute (PI16/00950, PI18/00856, PI19/01184); FEDER funds (‘A way to build Europe’) and by the Agency of University and Research Funding Management of the Catalan Government (2014 SGR 1672 and 2017 SGR 738). We thank CERCA Programme / Generalitat de Catalunya for institutional support. LD was supported by a Severo Ochoa grant (SVP-2013-068066), MA was supported by the Secretariat for Universities and Research of the Ministry of Business and Knowledge of the Government of Catalonia Grant co-funded by the European Social Fund (ESF) “ESF, Investing in your future” (2017 FI_B 00327), DSC was supported by a grant from the MICINN (BES-2014-069814) and RR was supported by a fellowship from the Health Department of the Generalitat de Catalunya through the PERIS 2016-2020 program (SLT002/16/00310).
Published: 2022

34. Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Author: Niamh Mullins, JooEun Kang, Adrian I. Campos, Jonathan R.I. Coleman, Alexis C. Edwards, Hanga Galfalvy, Daniel F. Levey, Adriana Lori, Andrey Shabalin, Anna Starnawska, Mei-Hsin Su, Hunna J. Watson, Mark Adams, Swapnil Awasthi, Michael Gandal, Jonathan D. Hafferty, Akitoyo Hishimoto, Minsoo Kim, Satoshi Okazaki, Ikuo Otsuka, Stephan Ripke, Erin B. Ware, Andrew W. Bergen, Wade H. Berrettini, Martin Bohus, Harry Brandt, Xiao Chang, Wei J. Chen, Hsi-Chung Chen, Steven Crawford, Scott Crow, Emily DiBlasi, Philibert Duriez, Fernando Fernández-Aranda, Manfred M. Fichter, Steven Gallinger, Stephen J. Glatt, Philip Gorwood, Yiran Guo, Hakon Hakonarson, Katherine A. Halmi, Hai-Gwo Hwu, Sonia Jain, Stéphane Jamain, Susana Jiménez-Murcia, Craig Johnson, Allan S. Kaplan, Walter H. Kaye, Pamela K. Keel, James L. Kennedy, Kelly L. Klump, Dong Li, Shih-Cheng Liao, Klaus Lieb, Lisa Lilenfeld, Chih-Min Liu, Pierre J. Magistretti, Christian R. Marshall, James E. Mitchell, Eric T. Monson, Richard M. Myers, Dalila Pinto, Abigail Powers, Nicolas Ramoz, Stefan Roepke, Vsevolod Rozanov, Stephen W. Scherer, Christian Schmahl, Marcus Sokolowski, Michael Strober, Laura M. Thornton, Janet Treasure, Ming T. Tsuang, Stephanie H. Witt, D. Blake Woodside, Zeynep Yilmaz, Lea Zillich, Rolf Adolfsson, Ingrid Agartz, Tracy M. Air, Martin Alda, Lars Alfredsson, Ole A. Andreassen, Adebayo Anjorin, Vivek Appadurai, María Soler Artigas, Sandra Van der Auwera, M. Helena Azevedo, Nicholas Bass, Claiton H.D. Bau, Bernhard T. Baune, Frank Bellivier, Klaus Berger, Joanna M. Biernacka, Tim B. Bigdeli, Elisabeth B. Binder, Michael Boehnke, Marco P. Boks, Rosa Bosch, David L. Braff, Richard Bryant, Monika Budde, Enda M. Byrne, Wiepke Cahn, Miguel Casas, Enrique Castelao, Jorge A. Cervilla, Boris Chaumette, Sven Cichon, Aiden Corvin, Nicholas Craddock, David Craig, Franziska Degenhardt, Srdjan Djurovic, Howard J. Edenberg, Ayman H. Fanous, Jerome C. Foo, Andreas J. Forstner, Mark Frye, Janice M. Fullerton, Justine M. Gatt, Pablo V. Gejman, Ina Giegling, Hans J. Grabe, Melissa J. Green, Eugenio H. Grevet, Maria Grigoroiu-Serbanescu, Blanca Gutierrez, Jose Guzman-Parra, Steven P. Hamilton, Marian L. Hamshere, Annette Hartmann, Joanna Hauser, Stefanie Heilmann-Heimbach, Per Hoffmann, Marcus Ising, Ian Jones, Lisa A. Jones, Lina Jonsson, René S. Kahn, John R. Kelsoe, Kenneth S. Kendler, Stefan Kloiber, Karestan C. Koenen, Manolis Kogevinas, Bettina Konte, Marie-Odile Krebs, Mikael Landén, Jacob Lawrence, Marion Leboyer, Phil H. Lee, Douglas F. Levinson, Calwing Liao, Jolanta Lissowska, Susanne Lucae, Fermin Mayoral, Susan L. McElroy, Patrick McGrath, Peter McGuffin, Andrew McQuillin, Sarah E. Medland, Divya Mehta, Ingrid Melle, Yuri Milaneschi, Philip B. Mitchell, Esther Molina, Gunnar Morken, Preben Bo Mortensen, Bertram Müller-Myhsok, Caroline Nievergelt, Vishwajit Nimgaonkar, Markus M. Nöthen, Michael C. O’Donovan, Roel A. Ophoff, Michael J. Owen, Carlos Pato, Michele T. Pato, Brenda W.J.H. Penninx, Jonathan Pimm, Giorgio Pistis, James B. Potash, Robert A. Power, Martin Preisig, Digby Quested, Josep Antoni Ramos-Quiroga, Andreas Reif, Marta Ribasés, Vanesa Richarte, Marcella Rietschel, Margarita Rivera, Andrea Roberts, Gloria Roberts, Guy A. Rouleau, Diego L. Rovaris, Dan Rujescu, Cristina Sánchez-Mora, Alan R. Sanders, Peter R. Schofield, Thomas G. Schulze, Laura J. Scott, Alessandro Serretti, Jianxin Shi, Stanley I. Shyn, Lea Sirignano, Pamela Sklar, Olav B. Smeland, Jordan W. Smoller, Edmund J.S. Sonuga-Barke, Gianfranco Spalletta, John S. Strauss, Beata Świątkowska, Maciej Trzaskowski, Gustavo Turecki, Laura Vilar-Ribó, John B. Vincent, Henry Völzke, James T.R. Walters, Cynthia Shannon Weickert, Thomas W. Weickert, Myrna M. Weissman, Leanne M. Williams, Naomi R. Wray, Clement C. Zai, Allison E. Ashley-Koch, Jean C. Beckham, Elizabeth R. Hauser, Michael A. Hauser, Nathan A. Kimbrel, Jennifer H. Lindquist, Benjamin McMahon, David W. Oslin, Xuejun Qin, Esben Agerbo, Anders D. Børglum, Gerome Breen, Annette Erlangsen, Tõnu Esko, Joel Gelernter, David M. Hougaard, Ronald C. Kessler, Henry R. Kranzler, Qingqin S. Li, Nicholas G. Martin, Andrew M. McIntosh, Ole Mors, Merete Nordentoft, Catherine M. Olsen, David Porteous, Robert J. Ursano, Danuta Wasserman, Thomas Werge, David C. Whiteman, Cynthia M. Bulik, Hilary Coon, Ditte Demontis, Anna R. Docherty, Po-Hsiu Kuo, Cathryn M. Lewis, J. John Mann, Miguel E. Rentería, Daniel J. Smith, Eli A. Stahl, Murray B. Stein, Fabian Streit, Virginia Willour, Douglas M. Ruderfer, Manuel Mattheisen, Abdel Abdellaoui, Mark J. Adams, Till F.M. Andlauer, Silviu-Alin Bacanu, Marie Bækvad-Hansen, Aartjan T.F. Beekman, Julien Bryois, Henriette N. Buttenschøn, Jonas Bybjerg-Grauholm, Na Cai, Jane Hvarregaard Christensen, Toni-Kim Clarke, Lucía Colodro-Conde, Baptiste Couvy-Duchesne, Nick Craddock, Gregory E. Crawford, Gail Davies, Eske M. 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J., Wasserman, D., Coon, H., Demontis, D., Docherty, A. R., Kuo, P. -H., Mann, J. J., Renteria, M. E., Stein, M. B., Willour, V., Psychiatry, Biological Psychology, APH - Methodology, APH - Mental Health, APH - Health Behaviors & Chronic Diseases, AMS - Sports, AMS - Ageing & Vitality, APH - Personalized Medicine, Amsterdam Neuroscience - Complex Trait Genetics, Complex Trait Genetics, Institute for Molecular Medicine Finland, Centre of Excellence in Complex Disease Genetics, Aarno Palotie / Principal Investigator, Genomics of Neurological and Neuropsychiatric Disorders, HUS Psychiatry, Department of Public Health, Clinicum, Nuorisopsykiatria, Faculty Common Matters (Faculty of Social Sciences), Samuli Olli Ripatti / Principal Investigator, Complex Disease Genetics, Biostatistics Helsinki, Anna Keski-Rahkonen / Principal Investigator, Elisabeth Ingrid Maria Widen / Principal Investigator, Genomic Discoveries and Clinical Translation, Internal medicine, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Digital Health, Mullins N., Kang J., Campos A.I., Coleman J.R.I., Edwards A.C., Galfalvy H., Levey D.F., Lori A., Shabalin A., Starnawska A., Su M.-H., Watson H.J., Adams M., Awasthi S., Gandal M., Hafferty J.D., Hishimoto A., Kim M., Okazaki S., Otsuka I., Ripke S., Ware E.B., Bergen A.W., Berrettini W.H., Bohus M., Brandt H., Chang X., Chen W.J., Chen H.-C., Crawford S., Crow S., DiBlasi E., Duriez P., Fernandez-Aranda F., Fichter M.M., Gallinger S., Glatt S.J., Gorwood P., Guo Y., Hakonarson H., Halmi K.A., Hwu H.-G., Jain S., Jamain S., Jimenez-Murcia S., Johnson C., Kaplan A.S., Kaye W.H., Keel P.K., Kennedy J.L., Klump K.L., Li D., Liao S.-C., Lieb K., Lilenfeld L., Liu C.-M., Magistretti P.J., Marshall C.R., Mitchell J.E., Monson E.T., Myers R.M., Pinto D., Powers A., Ramoz N., Roepke S., Rozanov V., Scherer S.W., Schmahl C., Sokolowski M., Strober M., Thornton L.M., Treasure J., Tsuang M.T., Witt S.H., Woodside D.B., Yilmaz Z., Zillich L., Adolfsson R., Agartz I., Air T.M., Alda M., Alfredsson L., Andreassen O.A., Anjorin A., Appadurai V., Soler Artigas M., Van der Auwera S., Azevedo M.H., Bass N., Bau C.H.D., Baune B.T., Bellivier F., Berger K., Biernacka J.M., Bigdeli T.B., Binder E.B., Boehnke M., Boks M.P., Bosch R., Braff D.L., Bryant R., Budde M., Byrne E.M., Cahn W., Casas M., Castelao E., Cervilla J.A., Chaumette B., Cichon S., Corvin A., Craddock N., Craig D., Degenhardt F., Djurovic S., Edenberg H.J., Fanous A.H., Foo J.C., Forstner A.J., Frye M., Fullerton J.M., Gatt J.M., Gejman P.V., Giegling I., Grabe H.J., Green M.J., Grevet E.H., Grigoroiu-Serbanescu M., Gutierrez B., Guzman-Parra J., Hamilton S.P., Hamshere M.L., Hartmann A., Hauser J., Heilmann-Heimbach S., Hoffmann P., Ising M., Jones I., Jones L.A., Jonsson L., Kahn R.S., Kelsoe J.R., Kendler K.S., Kloiber S., Koenen K.C., Kogevinas M., Konte B., Krebs M.-O., Landen M., Lawrence J., Leboyer M., Lee P.H., Levinson D.F., Liao C., Lissowska J., Lucae S., Mayoral F., McElroy S.L., McGrath P., McGuffin P., McQuillin A., Medland S.E., Mehta D., Melle I., Milaneschi Y., Mitchell P.B., Molina E., Morken G., Mortensen P.B., Muller-Myhsok B., Nievergelt C., Nimgaonkar V., Nothen M.M., O'Donovan M.C., Ophoff R.A., Owen M.J., Pato C., Pato M.T., Penninx B.W.J.H., Pimm J., Pistis G., Potash J.B., Power R.A., Preisig M., Quested D., Ramos-Quiroga J.A., Reif A., Ribases M., Richarte V., Rietschel M., Rivera M., Roberts A., Roberts G., Rouleau G.A., Rovaris D.L., Rujescu D., Sanchez-Mora C., Sanders A.R., Schofield P.R., Schulze T.G., Scott L.J., Serretti A., Shi J., Shyn S.I., Sirignano L., Sklar P., Smeland O.B., Smoller J.W., Sonuga-Barke E.J.S., Spalletta G., Strauss J.S., Swiatkowska B., Trzaskowski M., Turecki G., Vilar-Ribo L., Vincent J.B., Volzke H., Walters J.T.R., Shannon Weickert C., Weickert T.W., Weissman M.M., Williams L.M., Wray N.R., Zai C.C., Ashley-Koch A.E., Beckham J.C., Hauser E.R., Hauser M.A., Kimbrel N.A., Lindquist J.H., McMahon B., Oslin D.W., Qin X., Mattheisen M., Abdellaoui A., Adams M.J., Agerbo E., Andlauer T.F.M., Bacanu S.-A., Baekvad-Hansen M., Beekman A.T.F., Bryois J., Buttenschon H.N., Bybjerg-Grauholm J., Cai N., Christensen J.H., Clarke T.-K., Colodro-Conde L., Couvy-Duchesne B., Crawford G.E., Davies G., Derks E.M., Direk N., Dolan C.V., Dunn E.C., Eley T.C., Escott-Price V., Hassan Kiadeh F.F., Finucane H.K., Frank J., Gaspar H.A., Gill M., Goes F.S., Gordon S.D., Weinsheimer S.M., Wellmann J., Willemsen G., Wu Y., Xi H.S., Yang J., Zhang F., Arolt V., Boomsma D.I., Dannlowski U., de Geus E.J.C., Depaulo J.R., Domenici E., Domschke K., Esko T., Grove J., Hall L.S., Hansen C.S., Hansen T.F., Herms S., Hickie I.B., Homuth G., Horn C., Hottenga J.-J., Hougaard D.M., Howard D.M., Jansen R., Jorgenson E., Knowles J.A., Kohane I.S., Kraft J., Kretzschmar W.W., Kutalik Z., Li Y., Lind P.A., MacIntyre D.J., MacKinnon D.F., Maier R.M., Maier W., Marchini J., Mbarek H., Middeldorp C.M., Mihailov E., Milani L., Mondimore F.M., Montgomery G.W., Mostafavi S., Nauck M., Ng B., Nivard M.G., Nyholt D.R., O'Reilly P.F., Oskarsson H., Hayward C., Heath A.C., Lewis G., Li Q.S., Madden P.A.F., Magnusson P.K., Martin N.G., McIntosh A.M., Metspalu A., Mors O., Nordentoft M., Paciga S.A., Pedersen N.L., Painter J.N., Pedersen C.B., Pedersen M.G., Peterson R.E., Peyrot W.J., Posthuma D., Quiroz J.A., Qvist P., Rice J.P., Riley B.P., Mirza S.S., Schoevers R., Schulte E.C., Shen L., Sigurdsson E., Sinnamon G.C.B., Smit J.H., Smith D.J., Stefansson H., Steinberg S., Streit F., Strohmaier J., Tansey K.E., Teismann H., Teumer A., Thompson W., Thomson P.A., Thorgeirsson T.E., Traylor M., Treutlein J., Trubetskoy V., Uitterlinden A.G., Umbricht D., der Auwera S.V., van Hemert A.M., Viktorin A., Visscher P.M., Wang Y., Webb B.T., Perlis R.H., Porteous D.J., Schaefer C., Stefansson K., Tiemeier H., Uher R., Werge T., Lewis C.M., Breen G., Borglum A.D., Sullivan P.F., O'Connell K.S., Coombes B., Qiao Z., Als T.D., Borte S., Charney A.W., Drange O.K., Gandal M.J., Hagenaars S.P., Ikeda M., Kamitaki N., Krebs K., Panagiotaropoulou G., Schilder B.M., Sloofman L.G., Winsvold B.S., Won H.-H., Abramova L., Adorjan K., Al Eissa M., Albani D., Alliey-Rodriguez N., Antilla V., Antoniou A., Baek J.H., Bauer M., Beins E.C., Bergen S.E., Birner A., Boen E., Brum M., Brumpton B.M., Brunkhorst-Kanaan N., Byerley W., Cairns M., Cervantes P., Cruceanu C., Cuellar-Barboza A., Cunningham J., Curtis D., Czerski P.M., Dale A.M., Dalkner N., David F.S., Dobbyn A.L., Douzenis A., Elvsashagen T., Ferrier I.N., Fiorentino A., Foroud T.M., Forty L., Frei O., Freimer N.B., Frisen L., Gade K., Garnham J., Gelernter J., Gizer I.R., Gordon-Smith K., Greenwood T.A., Ha K., Haraldsson M., Hautzinger M., Heilbronner U., Hellgren D., Holmans P.A., Huckins L., Johnson J.S., Kalman J.L., Kamatani Y., Kittel-Schneider S., Koromina M., Kranz T.M., Kranzler H.R., Kubo M., Kupka R., Kushner S.A., Lavebratt C., Leber M., Lee H.-J., Levy S.E., Lewis C., Lundberg M., Magnusson S.H., Maihofer A., Malaspina D., Maratou E., Martinsson L., McGregor N.W., McKay J.D., Medeiros H., Millischer V., Moran J.L., Morris D.W., Muhleisen T.W., O'Brien N., O'Donovan C., Olde Loohuis L.M., Oruc L., Papiol S., Pardinas A.F., Perry A., Pfennig A., Porichi E., Raj T., Rapaport M.H., Regeer E.J., Rivas F., Roth J., Roussos P., Ruderfer D.M., Senner F., Sharp S., Shilling P.D., Slaney C., Sobell J.L., Artigas M.S., Spijker A.T., Stein D.J., Terao C., Toma C., Tooney P., Tsermpini E.-E., Vawter M.P., Vedder H., Xi S., Xu W., Kay Yang J.M., Young A.H., Young H., Zandi P.P., Zhou H., HUNT All-In Psychiatry, Babadjanova G., Backlund L., Bengesser S., Blackwood D.H.R., Carr V.J., Catts S., Dikeos D., Etain B., Ferentinos P., Gawlik M., Gershon E.S., Henskens F., Hillert J., Hong K.S., Hultman C.M., Hveem K., Iwata N., Jablensky A.V., Kirov G., Lochner C., Loughland C., Mathews C.A., McMahon F.J., Michie P., Mowry B., Neale B.M., Nievergelt C.M., Oedegaard K.J., Olsson T., Pantelis C., Patrinos G.P., Reininghaus E.Z., Saito T., Schall U., Schalling M., Scott R.J., Weickert C.S., Stordal E., Vaaler A.E., Vieta E., Waldman I.D., Zwart J.-A., Nurnberger J.I., Stahl E.A., Di Florio A., Adan R.A.H., Ando T., Aschauer H., Baker J.H., Bencko V., Birgegard A., Boden J.M., Boehm I., Boni C., Perica V.B., Buehren K., Bulik C.M., Burghardt R., Carlberg L., Cassina M., Clementi M., Cone R.D., Courtet P., Crowley J.J., Danner U.N., Davis O.S.P., de Zwaan M., Dedoussis G., Degortes D., DeSocio J.E., Dick D.M., Dina C., Dmitrzak-Weglarz M., Martinez E.D., Duncan L.E., Egberts K., Mattingsdal M., McDevitt S., Meulenbelt I., Micali N., Mitchell J., Mitchell K., Monteleone P., Monteleone A.M., Munn-Chernoff M.A., Nacmias B., Navratilova M., Ntalla I., Olsen C.M., O'Toole J.K., Padyukov L., Palotie A., Pantel J., Papezova H., Parker R., Pearson J.F., Ehrlich S., Escaramis G., Espeseth T., Estivill X., Farmer A., Favaro A., Fischer K., Floyd J.A.B., Focker M., Foretova L., Forzan M., Franklin C.S., Gambaro G., Giuranna J., Giusti-Rodriquez P., Gonidakis F., Gordon S., Mayora M.G., Guillaume S., Hanscombe K.B., Hatzikotoulas K., Hebebrand J., Helder S.G., Henders A.K., Herpertz-Dahlmann B., Herzog W., Hinney A., Horwood L.J., Hubel C., Petersen L.V., Purves K.L., Raevuori A., Reichborn-Kjennerud T., Ricca V., Ripatti S., Ritschel F., Roberts M., Rybakowski F., Santonastaso P., Scherag A., Schmidt U., Schork N.J., Schosser A., Seitz J., Slachtova L., Slagboom P.E., Slof-Op 't Landt M.C.T., Slopien A., Soranzo N., Sorbi S., Southam L., Steen V.W., Huckins L.M., Hudson J.I., Imgart H., Inoko H., Janout V., Jordan J., Julia A., Kalsi G., Kaminska D., Kaprio J., Karhunen L., Karwautz A., Kas M.J.H., Kennedy M.A., Keski-Rahkonen A., Kiezebrink K., Kim Y.-R., Kirk K.M., Klareskog L., Knudsen G.P.S., Larsen J.T., Le Hellard S., Leppa V.M., Lichtenstein P., Lin B.D., Lundervold A., Luykx J., Maj M., Mannik K., Marsal S., Stuber G.D., Szatkiewicz J.P., Tachmazidou I., Tenconi E., Tortorella A., Tozzi F., Tsitsika A., Tyszkiewicz-Nwafor M., Tziouvas K., van Elburg A.A., van Furth E.F., Wade T.D., Wagner G., Walton E., Whiteman D.C., Wichmann H.E., Widen E., Yao S., Zeggini E., Zerwas S., Zipfel S., Jungkunz M., Dietl L., Schwarze C.E., Dahmen N., Schott B.H., Mobascher A., Crivelli S., Dennis M.F., Harvey P.D., Carter B.W., Huffman J.E., Jacobson D., Madduri R., Olsen M.K., Pestian J., Gaziano J.M., Muralidhar S., Ramoni R., Beckham J., Chang K.-M., O'Donnell C.J., Tsao P.S., Breeling J., Huang G., Romero J.P.C., Moser J., Whitbourne S.B., Brewer J.V., Aslan M., Connor T., Argyres D.P., Stephens B., Brophy M.T., Humphries D.E., Selva L.E., Do N., Shayan S., Cho K., Pyarajan S., Hauser E., Sun Y., Zhao H., Wilson P., McArdle R., Dellitalia L., Mattocks K., Harley J., Zablocki C.J., Whittle J., Jacono F., Gutierrez S., Gibson G., Hammer K., Kaminsky L., Villareal G., Kinlay S., Xu J., Hamner M., Mathew R., Bhushan S., Iruvanti P., Godschalk M., Ballas Z., Ivins D., Mastorides S., Moorman J., Gappy S., Klein J., Ratcliffe N., Florez H., Okusaga O., Murdoch M., Sriram P., Yeh S.S., Tandon N., Jhala D., Aguayo S., Cohen D., Sharma S., Liangpunsakul S., Oursler K.A., Whooley M., Ahuja S., Constans J., Meyer P., Greco J., Rauchman M., Servatius R., Gaddy M., Wallbom A., Morgan T., Stapley T., Sherman S., Ross G., Tsao P., Strollo P., Boyko E., Meyer L., Gupta S., Huq M., Fayad J., Hung A., Lichy J., Hurley R., Robey B., Striker R., Erlangsen A., Kessler R.C., Porteous D., Ursano R.J., Wasserman D., Coon H., Demontis D., Docherty A.R., Kuo P.-H., Mann J.J., Renteria M.E., Stein M.B., and Willour V.
Subjects: LD SCORE REGRESSION, Genome-wide association study, Suicide, Attempted, 3124 Neurology and psychiatry, 0302 clinical medicine, Risk Factors, Insomnia, Suicide attempt, GWAS, Suïcidi, Depression (differential diagnoses), Cause of death, Psychiatry, 0303 health sciences, Factors de risc en les malalties, Mental Disorders, Genetic Correlation, Genome-wide Association Study, Pleiotropy, Polygenicity, Suicide, Suicide Attempt, DEPRESSION, 3. Good health, Genetic correlation, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Depressive Disorder, Major, Mental illness, Cohort, SEX, medicine.symptom, Human, medicine.medical_specialty, Risk factors in diseases, BF, Locus (genetics), BEHAVIORS, Psykiatri, EVENTS, 03 medical and health sciences, SDG 3 - Good Health and Well-being, medicine, ddc:610, GENOME-WIDE ASSOCIATION, IDEATION, Socioeconomic status, METAANALYSIS, Biological Psychiatry, 030304 developmental biology, business.industry, Risk Factor, Genetic architecture, THOUGHTS, RC0321, business, Malalties mentals, 030217 neurology & neurosurgery
Abstract: Statistical analyses were carried out on the NL Genetic Cluster Computer (http://www.geneticcluster.org) hosted by SURFsara and the Mount Sinai high performance computing cluster (http://hpc.mssm.edu), which is supported by the Office of Research Infrastructure of the National Institutes of Health (Grant Nos. S10OD018522 and S10OD026880). This work was conducted in part using the resources of the Advanced Computing Center for Research and Education at Vanderbilt University, Nashville, TN. This work was funded by the National Institutes of Health (Grant Nos. R01MH116269 and R01MH121455 [to DMR]), NIGMS of the National Institutes of Health (Grant No. T32GM007347 [to JK]), and the Brain & Behavior Research Foundation (NARSAD Young Investigator Award No. 29551 [to NM])., BACKGROUND: Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. METHODS: We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. RESULTS: Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. CONCLUSIONS: Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders., Office of Research Infrastructure of the National Institutes of Health S10OD018522 S10OD026880, United States Department of Health & Human Services, National Institutes of Health (NIH) - USA R01MH116269 R01MH121455, NIH National Institute of General Medical Sciences (NIGMS) T32GM007347 NARSAD 29551
Published: 2022

35. Author response: Identification of autosomal cis expression quantitative trait methylation (cis eQTMs) in children’s blood

Author: Carlos Ruiz-Arenas, Carles Hernandez-Ferrer, Marta Vives-Usano, Sergi Marí, Ines Quintela, Dan Mason, Solène Cadiou, Maribel Casas, Sandra Andrusaityte, Kristine Bjerve Gutzkow, Marina Vafeiadi, John Wright, Johanna Lepeule, Regina Grazuleviciene, Leda Chatzi, Ángel Carracedo, Xavier Estivill, Eulàlia Marti, Geòrgia Escaramís, Martine Vrijheid, Juan R González, and Mariona Bustamante
Published: 2021

36. Genetic predisposition to cancer across people of different ancestries in Qatar: a population-based, cohort study

Author: Mohamad Saad, Younes Mokrab, Najeeb Halabi, Jingxuan Shan, Rozaimi Razali, Khalid Kunji, Najeeb Syed, Ramzi Temanni, Murugan Subramanian, Michele Ceccarelli, Arash Rafii Tabrizi, Davide Bedognetti, Lotfi Chouchane, Said I Ismail, Wadha Al-Muftah, Radja Badji, Hamdi Mbarek, Dima Darwish, Tasnim Fadl, Heba Yasin, Maryem Ennaifar, Rania Abdellatif, Fatima Alkuwari, Muhammad Alvi, Yasser Al-Sarraj, Chadi Saad, Eleni Fethnou, Fatima Qafoud, Eiman Alkhayat, Nahla Afifi, Sara Tomei, Wei Liu, Stephan Lorenz, Hakeem Almabrazi, Fazulur R Vempalli, Tariq Abu Saqri, Mohammedhusen Khatib, Mehshad Hamza, Tariq Abu Zaid, Ahmed El Khouly, Tushar Pathare, Shafeeq Poolat, Rashid Al-Ali, Omar Albagha, Souhaila Al-Khodor, Mashael Alshafai, Ramin Badii, Xavier Estivill, Khalid Fakhro, Jithesh V Puthen, Karsten Suhre, Zohreh Tatari, Saad, M., Mokrab, Y., Halabi, N., Shan, J., Razali, R., Kunji, K., Syed, N., Temanni, R., Subramanian, M., Ceccarelli, M., Rafii Tabrizi, A., Bedognetti, D., and Chouchane, L.
Subjects: Cohort Studies, Male, Oncology, Neoplasms, Humans, Genetic Predisposition to Disease, Oncogenes, Qatar
Abstract: Background: Disparities in the genetic risk of cancer among various ancestry groups and populations remain poorly defined. This challenge is even more acute for Middle Eastern populations, where the paucity of genomic data could affect the clinical potential of cancer genetic risk profiling. We used data from the phase 1 cohort of the Qatar Genome Programme to investigate genetic variation in cancer-susceptibility genes in the Qatari population. Methods: The Qatar Genome Programme generated high-coverage genome sequencing on DNA samples collected from 6142 native Qataris, stratified into six distinct ancestry groups: general Arab, Persian, Arabian Peninsula, Admixture Arab, African, and South Asian. In this population-based, cohort study, we evaluated the performance of polygenic risk scores for the most common cancers in Qatar (breast, prostate, and colorectal cancers). Polygenic risk scores were trained in The Cancer Genome Atlas (TCGA) dataset, and their distributions were subsequently applied to the six different genetic ancestry groups of the Qatari population. Rare deleterious variants within 1218 cancer susceptibility genes were analysed, and their clinical pathogenicity was assessed by ClinVar and the CharGer computational tools. Findings: The cohort included in this study was recruited by the Qatar Biobank between Dec 11, 2012, and June 9, 2016. The initial dataset comprised 6218 cohort participants, and whole genome sequencing quality control filtering led to a final dataset of 6142 samples. Polygenic risk score analyses of the most common cancers in Qatar showed significant differences between the six ancestry groups (p
Published: 2021

37. Actionable genomic variants in 6045 participants from the Qatar Genome Program

Author: Amal, Elfatih, Borbala, Mifsud, Najeeb, Syed, Ramin, Badii, Hamdi, Mbarek, Fatemeh, Abbaszadeh, and Xavier, Estivill
Abstract: In a clinical setting, DNA sequencing can uncover findings unrelated to the purpose of genetic evaluation. The American College of Medical Genetics and Genomics (ACMG) recommends the evaluation and reporting of 59 genes from clinic genomic sequencing. While the prevalence of secondary findings is available from large population studies, these data lack Arab and other Middle Eastern populations. The Qatar Genome Program (QGP) generates whole-genome sequencing (WGS) data and combines it with phenotypic information to create a comprehensive database for studying the Qatari and wider Arab and Middle Eastern populations at the molecular level. This study identified and analyzed medically actionable variants in the 59 ACMG genes using WGS data from 6045 QGP participants. Our results identified a total of 60 pathogenic and likely pathogenic variants in 25 ACMG genes in 141 unique individuals. Overall, 2.3% of the QGP sequenced participants carried a pathogenic or likely pathogenic variant in one of the 59 ACMG genes. We evaluated the QGP phenotype-genotype association of additional nonpathogenic ACMG variants. These variants were found in patients from the Hamad Medical Corporation or reported incidental findings data in Qatar. We found a significant phenotype association for two variants, c.313+3AC in LDLR, and c.58CT (p.Gln20*) in the TPM1.
Published: 2021

38. A population study of clinically actionable genetic variation affecting drug response from the Middle East

Author: Puthen Veettil, Jithesh, Mohammed, Abuhaliqa, Najeeb, Syed, Ikhlak, Ahmed, Mohammed, El Anbari, Kholoud, Bastaki, Shimaa, Sherif, Umm-Kulthum, Umlai, Zainab, Jan, Geethanjali, Gandhi, Chidambaram, Manickam, Senthil, Selvaraj, Chinnu, George, Dhinoth, Bangarusamy, Rania, Abdel-Latif, Mashael, Al-Shafai, Zohreh, Tatari-Calderone, Xavier, Estivill, Munir, Pirmohamed, and Heba, Yasin
Abstract: Clinical implementation of pharmacogenomics will help in personalizing drug prescriptions and alleviate the personal and financial burden due to inefficacy and adverse reactions to drugs. However, such implementation is lagging in many parts of the world, including the Middle East, mainly due to the lack of data on the distribution of actionable pharmacogenomic variation in these ethnicities. We analyzed 6,045 whole genomes from the Qatari population for the distribution of allele frequencies of 2,629 variants in 1,026 genes known to affect 559 drugs or classes of drugs. We also performed a focused analysis of genotypes or diplotypes of 15 genes affecting 46 drugs, which have guidelines for clinical implementation and predicted their phenotypic impact. The allele frequencies of 1,320 variants in 703 genes affecting 299 drugs or class of drugs were significantly different between the Qatari population and other world populations. On average, Qataris carry 3.6 actionable genotypes/diplotypes, affecting 13 drugs with guidelines for clinical implementation, and 99.5% of the individuals had at least one clinically actionable genotype/diplotype. Increased risk of simvastatin-induced myopathy could be predicted in ~32% of Qataris from the diplotypes of SLCO1B1, which is higher compared to many other populations, while fewer Qataris may need tacrolimus dosage adjustments for achieving immunosuppression based on the CYP3A5 diplotypes compared to other world populations. Distinct distribution of actionable pharmacogenomic variation was also observed among the Qatari subpopulations. Our comprehensive study of the distribution of actionable genetic variation affecting drugs in a Middle Eastern population has potential implications for preemptive pharmacogenomic implementation in the region and beyond.
Published: 2021

39. Genetic evaluation of cardiomyopathies in Qatar identifies enrichment of pathogenic sarcomere gene variants and possible founder disease mutations in the Arabs

Author: Senthil Selvaraj, Muneera Ali, Xavier Estivill, Fazulur R Vempalli, Kholoud Al-shafai, Rania Musa, Najeeb Syed, Mohammed Alhashemi, Chidambaram Manickam, and Magdi H. Yacoub
Subjects: Cardiomyopathy, Dilated, Male, 0301 basic medicine, Population, Cardiomyopathy, Disease, QH426-470, 030105 genetics & heredity, Biology, Frameshift mutation, Loss of heterozygosity, 03 medical and health sciences, Gene Frequency, Genetics, medicine, Humans, Connectin, cardiovascular diseases, targeted sequencing, education, Qatar, Molecular Biology, Gene, Genetics (clinical), Aged, education.field_of_study, genetic variants, Hypertrophic cardiomyopathy, Dilated cardiomyopathy, Original Articles, Cardiomyopathy, Hypertrophic, Middle Aged, musculoskeletal system, medicine.disease, Arabs, 030104 developmental biology, cardiovascular system, Female, Original Article, cardiomyopathy
Abstract: Background Hypertrophic cardiomyopathy (HCM) and dilated cardiomyopathy (DCM) are serious inherited heart diseases with various causative mutations identified. The full spectrum of causative mutations remains to be discovered, especially in understudied populations. Methods Here, we established the DOHA Registry and Biobank for cardiomyopathies in Qatar, followed by sequencing of 174 genes on 51 HCM and 53 DCM patients, and 31 relatives. Results In HCM, the analysis of 25 HCM‐associated genes showed that 20% of HCM cases had putative pathogenic variants for cardiomyopathy, mainly in sarcomere genes. Additional 49% of HCM cases had variants of uncertain significance, while 31% of HCM cases had likely benign variant(s) or had no variants identified within the analyzed HCM genes. In DCM, 56 putative DCM genes were analyzed. Eight percent of DCM cases had putative pathogenic variants for DCM, in the TTN gene while 70% of cases had variants of uncertain significance, in the analyzed DCM genes, that will need further pathogenicity assessment. Moreover, 22% of DCM cases remain unexplained, by having likely benign variant(s) or having no variants detected in any of the analyzed DCM genes. Conclusion We identified or replicated at least four recurrent variants among cardiomyopathy patients, which could be founder disease mutations in the Arabic population, including a frameshift variant (c.1371_1381dupTATCCAGTTAT) of unknown significance in the FKTN gene which seems to cause DCM in homozygosity, and HCM in heterozygosity. In vivo and/or in vitro functional validation need to be pursued in order to assess the pathogenicity of the identified variants., We established the DOHA Registry and Biobank for cardiomyopathies in Qatar, followed by sequencing of 174 genes on 51 HCM and 53 DCM patients, and 31 relatives. Twenty percent of HCM cases and eight% of DCM cases had pathogenic variants for cardiomyopathy, while 31% of HCM cases and 22% of DCM cases remain unexplained by having likely benign variant(s) or having no variants detected in any of the analysed genes.We replicated at least four recurrent variants among cardiomyopathy patients, which could be founder disease mutations in the Arabic population, including a frameshift variant (c.1371_1381dupTATCCAGTTAT) in the FKTN gene which seems to cause DCM in homozygosity and HCM, in heterozygosity.
Published: 2021

40. Genome sequencing data analysis for rare disease gene discovery

Author: Dhinoth Kumar Bangarusamy, Puthen V. Jithesh, Umm-Kulthum Ismail Umlai, and Xavier Estivill
Subjects: Whole genome sequencing, Data Analysis, education.field_of_study, Genome, Computer science, Population, High-Throughput Nucleotide Sequencing, Genomics, Disease, Computational biology, DNA sequencing, Workflow, Rare Diseases, Humans, education, Molecular Biology, Genetic Association Studies, Software, Information Systems, Rare disease
Abstract: Rare diseases occur in a smaller proportion of the general population, which is variedly defined as less than 200 000 individuals (US) or in less than 1 in 2000 individuals (Europe). Although rare, they collectively make up to approximately 7000 different disorders, with majority having a genetic origin, and affect roughly 300 million people globally. Most of the patients and their families undergo a long and frustrating diagnostic odyssey. However, advances in the field of genomics have started to facilitate the process of diagnosis, though it is hindered by the difficulty in genome data analysis and interpretation. A major impediment in diagnosis is in the understanding of the diverse approaches, tools and datasets available for variant prioritization, the most important step in the analysis of millions of variants to select a few potential variants. Here we present a review of the latest methodological developments and spectrum of tools available for rare disease genetic variant discovery and recommend appropriate data interpretation methods for variant prioritization. We have categorized the resources based on various steps of the variant interpretation workflow, starting from data processing, variant calling, annotation, filtration and finally prioritization, with a special emphasis on the last two steps. The methods discussed here pertain to elucidating the genetic basis of disease in individual patient cases via trio- or family-based analysis of the genome data. We advocate the use of a combination of tools and datasets and to follow multiple iterative approaches to elucidate the potential causative variant.
Published: 2021

41. Genome-wide association study in frontal fibrosing alopecia identifies four susceptibility loci including HLA-B*07:02

Author: Paul Farrant, Mark Goodfield, Catherine H. Smith, V. Jolliffe, Gregory Parkins, Caroline Champagne, Lu Liu, Nigel Burrows, A. S. Bryden, Kristie Wood, Anton B. Alexandroff, Irene Man, Alka Saxena, Su M. Lwin, Iaisha Ali, Catherine M. Stefanato, Kapil Bhargava, Sang Hyuck Lee, Melanie Page, Xavier Estivill, Tim D. Spector, Carsten Flohr, Susan Holmes, David de Berker, A. E. Macbeth, Ncoza C. Dlova, David Baudry, Jake Saklatvala, Nerea Ormaechea Perez, Archana Rao, David A. Fenton, Martin S Wade, Cedric Charles Banfield, Jennifer Jones, Evangelos A A Christou, Ravinder Atkar, Gregory A Michelotti, Sergio Vano-Galvan, Seth D. Seegobin, Jane Setterfield, Jonathan Barker, Chrysanthi Ainali, Christos Tziotzios, Charles Curtis, Rashida Pramanik, Matthew Harries, Girish K Patel, Niall Kirkpatrick, Venu Pullabhatla, Fiona Cunningham, Nick Dand, Hywel L Cooper, Rodney Sinclair, Keith Armstrong, Emanuele de Rinaldis, Andrew J. G. McDonagh, M R Kaur, Fiona Lewis, Michael A. Simpson, John A. McGrath, Charles E. Mitchell, Nicola Cooke, Fiona M. Watt, Alexandros Onoufriadis, Michael R. Ardern-Jones, Tee-Wei Siah, Ioulios Palamaras, Ana María Molina-Ruiz, Megan Mowbray, A. Takwale, Andrew G. Messenger, Giles Dunnill, Christos Petridis, and Shyamal Wahie
Subjects: 0301 basic medicine, Science, General Physics and Astronomy, Gene Expression, Locus (genetics), Genome-wide association study, 02 engineering and technology, Biology, Adaptive Immunity, Polymorphism, Single Nucleotide, General Biochemistry, Genetics and Molecular Biology, Article, Cohort Studies, 03 medical and health sciences, HLA-B7 Antigen, medicine, Missense mutation, Humans, Genetic Predisposition to Disease, Allele, lcsh:Science, Genetic association, Genetics, Multidisciplinary, integumentary system, Genome, Human, Frontal fibrosing alopecia, Case-control study, Alopecia, General Chemistry, 021001 nanoscience & nanotechnology, medicine.disease, Immunity, Innate, 3. Good health, stomatognathic diseases, 030104 developmental biology, Hair loss, Genetic Loci, Case-Control Studies, Cytochrome P-450 CYP1B1, Female, lcsh:Q, 0210 nano-technology, Transcriptome, Genome-Wide Association Study
Abstract: Frontal fibrosing alopecia (FFA) is a recently described inflammatory and scarring type of hair loss affecting almost exclusively women. Despite a dramatic recent increase in incidence the aetiopathogenesis of FFA remains unknown. We undertake genome-wide association studies in females from a UK cohort, comprising 844 cases and 3,760 controls, a Spanish cohort of 172 cases and 385 controls, and perform statistical meta-analysis. We observe genome-wide significant association with FFA at four genomic loci: 2p22.2, 6p21.1, 8q24.22 and 15q2.1. Within the 6p21.1 locus, fine-mapping indicates that the association is driven by the HLA-B*07:02 allele. At 2p22.1, we implicate a putative causal missense variant in CYP1B1, encoding the homonymous xenobiotic- and hormone-processing enzyme. Transcriptomic analysis of affected scalp tissue highlights overrepresentation of transcripts encoding components of innate and adaptive immune response pathways. These findings provide insight into disease pathogenesis and characterise FFA as a genetically predisposed immuno-inflammatory disorder driven by HLA-B*07:02., Frontal fibrosing alopecia (FFA) features lichenoid cutaneous inflammation and scarring hair loss. Here, Tziotzios et al. identify four genetic loci associated with FFA by GWAS followed by Bayesian fine-mapping, co-localisation and HLA imputation which highlights HLA-B*07:02 as a risk factor.
Published: 2019

42. PATJ Low Frequency Variants Are Associated With Worse Ischemic Stroke Functional Outcome

Author: Christina Jern, Braxton D. Mitchell, E. Palomeras, Aina Medina-Dols, Vincent Thijs, Kistiina Rannikmae, Alejandro Bustamante, Jordi Jimenez-Conde, Tomás Segura, Caty Carrera, Rosa Maria Vivanco-Hidalgo, Victor Obach, Israel Fernandez-Cadenas, Xavier Estivill, Bradford B. Worrall, Tara M. Stanne, José Alvarez-Sabín, Gemma Serrano-Heras, Elena López-Cancio, Mar Castellanos, Catherine Sudlow, Elisa Cuadrado-Godia, Antonio Dávalos, Silvia Tur, Maria Angels Font, Ana Rodríguez-Campello, Cristina Gallego-Fabrega, Elena Muiño, Teresa García-Berrocoso, Carmen Jiménez, Marc Ribó, Laura Heitsch, Laura Ibanez, Jin-Moo Lee, Cristofol Vives-Bauza, Montserrat Solé, Pilar Delgado, Erik Lorentzen, Joan Martí-Fàbregas, Mar Freijo, Carlos A. Molina, Robin Lemmens, Carolina Soriano-Tárraga, Rosa Díaz-Navarro, Jurek Krupinski, Angel Ois, Jaume Roquer, Eva Giralt-Steinhauer, Arne Lindgren, Jane Maguire, Daniel Woo, Jonathan Rosand, Joan Montaner, Natalia Cullell, Marina Mola-Caminal, Joaquín Serena, Steven J. Kittner, Mar Hernández-Guillamon, Lucía Muñoz-Narbona, Raquel Rabionet, Natalia S. Rost, Maite Mendioroz, Carlos Cruchaga, Nuria P. Torres-Aguila, Chia-Ling Phuah, and Universitat de Barcelona
Subjects: 0301 basic medicine, Discapacitats, Isquèmia cerebral, Cardiac & Cardiovascular Systems, Neurology, Physiology, Treatment outcome, Genome-wide association study, Brain Ischemia, Brain ischemia, Disability Evaluation, 0302 clinical medicine, Gene Frequency, Risk Factors, SCALE, Stroke Rehabilitation, allele, Hematology, Cerebral ischemia, Stroke, Treatment Outcome, Phenotype, Cardiology, Cardiology and Cardiovascular Medicine, Life Sciences & Biomedicine, genetic variant, medicine.medical_specialty, People with disabilities, GENETICS, Polymorphism, Single Nucleotide, 03 medical and health sciences, Internal medicine, ischemic stroke, medicine, Humans, Genetic Predisposition to Disease, Allele, Allele frequency, Tight Junction Proteins, Science & Technology, genome-wide association study, business.industry, Genetic variants, genetic loci, Recovery of Function, medicine.disease, 030104 developmental biology, Cardiovascular System & Hematology, Peripheral Vascular Disease, Ischemic stroke, Cardiovascular System & Cardiology, business, 030217 neurology & neurosurgery
Abstract: Rationale: Ischemic stroke is among the leading causes of adult disability. Part of the variability in functional outcome after stroke has been attributed to genetic factors but no locus has been consistently associated with stroke outcome. Objective: Our aim was to identify genetic loci influencing the recovery process using accurate phenotyping to produce the largest GWAS (genome-wide association study) in ischemic stroke recovery to date. Methods and Results: A 12-cohort, 2-phase (discovery-replication and joint) meta-analysis of GWAS included anterior-territory and previously independent ischemic stroke cases. Functional outcome was recorded using 3-month modified Rankin Scale. Analyses were adjusted for confounders such as discharge National Institutes of Health Stroke Scale. A gene-based burden test was performed. The discovery phase (n=1225) was followed by open (n=2482) and stringent joint-analyses (n=1791). Those cohorts with modified Rankin Scale recorded at time points other than 3-month or incomplete data on previous functional status were excluded in the stringent analyses. Novel variants in PATJ (Pals1-associated tight junction) gene were associated with worse functional outcome at 3-month after stroke. The top variant was rs76221407 (G allele, β=0.40, P =1.70×10 −9 ). Conclusions: Our results identify a set of common variants in PATJ gene associated with 3-month functional outcome at genome-wide significance level. Future studies should examine the role of PATJ in stroke recovery and consider stringent phenotyping to enrich the information captured to unveil additional stroke outcome loci.
Published: 2019

43. Multi-omics signatures of the human early life exposome

Author: Mark J. Nieuwenhuijsen, Hector C. Keun, John Wright, L. Chatzi, González, Tamayo I, Gallego-Paüls M, Sandra Andrusaityte, Inés Quintela, Léa Maitre, Eva Borràs, Dan Mason, Amrit Kaur Sakhi, Jordi Sunyer, Marta Vives-Usano, Barbara Heude, Muireann Coen, Solène Cadiou, Chung-Ho E Lau, Sabidó E, Denise Thiel, Xavier Estivill, Angel Carracedo, Jose Urquiza, Eleni Papadopoulou, Martine Vrijheid, Regina Grazuleviciene, Casas M, Kristine B. Gutzkow, Carles Hernandez-Ferrer, Rémy Slama, Alexandros P. Siskos, Carlos Ruiz-Arenas, Mariona Bustamante, Cathrine Thomsen, Marina Vafeiadi, and Oliver Robinson
Subjects: Exposome, Pregnancy, Environmental health, Maternal smoking, Metabolome, medicine, Multi omics, Biology, Omics, medicine.disease, Early life
Abstract: SummaryEnvironmental exposures during early life play a critical role in life-course health, yet the molecular phenotypes underlying environmental effects on health are poorly understood. In the Human Early Life Exposome (HELIX) project, a multi-centre cohort of 1,301 mother-child pairs, we associated individual exposomes consisting of >100 chemical, physical and lifestyle exposures assessed in pregnancy and childhood, with multi-omics profiles (methylome, transcriptome, metabolome and proteins) in childhood. We identified 1,170 associations, 249 in pregnancy and 921 in childhood, which revealed potential biological responses and sources of exposure. The methylome best captures the persistent influence of pregnancy exposures, including maternal smoking; while childhood exposures were associated with features from all omics layers, revealing novel signatures for indoor air quality, essential trace elements, endocrine disruptors and weather conditions. This study provides a unique resource (https://helixomics.isglobal.org/) to guide future investigation on the biological effects of the early life exposome.
Published: 2021

44. PeSV-fisher : identification of somatic and non-somatic structural variants using next generation sequencing data

Author: Mario Cáceres, Stephan Ossowski, Geòrgia Escaramís, Alexander Martínez-Fundichely, Laia Bassaganyas, Cristian Tornador, Xavier Estivill, Raquel Rabionet, Marta Gut, and Jose M. C. Tubio
Subjects: lcsh:Medicine, Human genomics, Genome, Chromosomal Disorders, 0302 clinical medicine, Sequence alignment, Databases, Genetic, Cancer genomics, Genomic library, Genome Sequencing, lcsh:Science, Genètica -- Bases de dades, Cancers and neoplasms, Genetics, 0303 health sciences, Multidisciplinary, Chromosomal Deletions and Duplications, ADN -- Anàlisi, Genomics, Genome Scans, Identification (information), Translocations, Sequence Analysis, Algorithms, Research Article, Genome evolution, Sequence analysis, Computational biology, Biology, Genome Complexity, DNA sequencing, 03 medical and health sciences, Genome Analysis Tools, Cancer Genetics, Humans, 030304 developmental biology, Comparative genomics, Genome, Human, lcsh:R, Breakpoint, Computational Biology, Human Genetics, Sequence Analysis, DNA, Genome analysis, Leukemia, Lymphocytic, Chronic, B-Cell, Genòmica, Genomic Structural Variation, Computer Science, Genetics of Disease, lcsh:Q, Structural Genomics, Transposable elements, 030217 neurology & neurosurgery
Abstract: Next-generation sequencing technologies expedited research to develop efficient computational tools for the identification of structural variants (SVs) and their use to study human diseases. As deeper data is obtained, the existence of higher complexity SVs in some genomes becomes more evident, but the detection and definition of most of these complex rearrangements is still in its infancy. The full characterization of SVs is a key aspect for discovering their biological implications. Here we present a pipeline (PeSV-Fisher) for the detection of deletions, gains, intra- and inter-chromosomal translocations, and inversions, at very reasonable computational costs. We further provide comprehensive information on co-localization of SVs in the genome, a crucial aspect for studying their biological consequences. The algorithm uses a combination of methods based on paired-reads and read-depth strategies. PeSV-Fisher has been designed with the aim to facilitate identification of somatic variation, and, as such, it is capable of analysing two or more samples simultaneously, producing a list of non-shared variants between samples. We tested PeSV-Fisher on available sequencing data, and compared its behaviour to that of frequently deployed tools (BreakDancer and VariationHunter). We have also tested this algorithm on our own sequencing data, obtained from a tumour and a normal blood sample of a patient with chronic lymphocytic leukaemia, on which we have also validated the results by targeted re-sequencing of different kinds of predictions. This allowed us to determine confidence parameters that influence the reliability of breakpoint predictions. This work was supported by AGAUR (Generalitat de Catalunya, 2009 SGR 1502) (X.E.); CIBERESP (Instituto de Salud Carlos III) (G.E.); ESGI (European Commission, 262055_ESGI) (R.R., X.E.), ENGAGE (European Commission, ENGAGE_201413), TECHGENE (European Commission, TECHGENE_223143), and GEUVADIS (European Commission, 261123_GEUVADIS) (X.E.); NOVADIS (Ministerio de Ciencia y Technologia, SAF2008-00357) (X.E.); Galicia Government Xunta de Galicia (Spain) through the project number 10PXIB918057 (J.M.C.T.); MAEC-AEC1 Predoctoral Fellowship (Ministerio de Asuntos Exteriores y Cooperación, Spain) (A.M.F.); and Ramón y Cajal position and grant BFU2007-60930 (Ministerio de Educación y Ciencia) (M.C.).
Published: 2021

45. Variability of multi-omics profiles in a population-based child cohort

Author: Chung-Ho E Lau, Léa Maitre, Barbara Heude, Maribel Casas, Juan R. González, John Wright, Marta Gallego-Paüls, Martine Vrijheid, Angel Carracedo, Muireann Coen, Regina Grazuleviciene, Alexandros P. Siskos, Carles Hernandez-Ferrer, Xavier Basagaña, Jose Barrera-Gómez, Jose Urquiza, Eduard Sabidó, Hector C. Keun, Leda Chatzi, Rémy Slama, Xavier Estivill, Carlos Ruiz-Arenas, Mariona Bustamante, Marta Vives-Usano, Eva Borràs, Instituto de Salud Global - Institute For Global Health [Barcelona] (ISGlobal), Universitat Pompeu Fabra [Barcelona] (UPF), CIBER de Epidemiología y Salud Pública (CIBERESP), Barcelona Institute of Science and Technology (BIST), Imperial College London, Bradford Teaching Hospitals NHS Foundation Trust [Bradford, UK] (BTHFT), Institute for Advanced Biosciences / Institut pour l'Avancée des Biosciences (Grenoble) (IAB), Etablissement français du sang - Auvergne-Rhône-Alpes (EFS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre Hospitalier Universitaire [Grenoble] (CHU)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Université Grenoble Alpes (UGA), Centre de Recherche Épidémiologie et Statistique Sorbonne Paris Cité (CRESS (U1153 / UMR_A_1125 / UMR_S_1153)), Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Vytautas Magnus University - Vytauto Didziojo Universitetas (VDU), University of Southern California (USC), CIBER de Enfermedades Raras (CIBERER), Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), AstraZeneca [Cambridge, UK], Universidade de Santiago de Compostela. Departamento de Ciencias Forenses, Anatomía Patolóxica, Xinecoloxía e Obstetricia, e Pediatría, Malbec, Odile, Centre Hospitalier Universitaire [Grenoble] (CHU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Etablissement français du sang - Auvergne-Rhône-Alpes (EFS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Instituto de Investigación Sanitaria de Santiago de Compostela / Health Research Institute of Santiago de Compostela (IDIS), and Commission of the European Communities
Subjects: 0301 basic medicine, European community, [SDV]Life Sciences [q-bio], mRNA, Library science, Population based, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, Environmental risk, General & Internal Medicine, Humans, Medicine, Metabolomics, Social science research, Variability, Child, Children, 11 Medical and Health Sciences, miRNA, Multi-omics, DNA methylation, business.industry, General Medicine, language.human_language, 3. Good health, [SDV] Life Sciences [q-bio], MicroRNAs, Exposome, Cross-Sectional Studies, 030104 developmental biology, Diabetes Mellitus, Type 2, 030220 oncology & carcinogenesis, language, Multi omics, Christian ministry, Catalan, Cross-omics, business, Population study, Research Article, Omics technologies
Abstract: Background: Multiple omics technologies are increasingly applied to detect early, subtle molecular responses to environmental stressors for future disease risk prevention. However, there is an urgent need for further evaluation of stability and variability of omics profiles in healthy individuals, especially during childhood. Methods: We aimed to estimate intra-, inter-individual and cohort variability of multi-omics profiles (blood DNA methylation, gene expression, miRNA, proteins and serum and urine metabolites) measured 6 months apart in 156 healthy children from five European countries. We further performed a multi-omics network analysis to establish clusters of co-varying omics features and assessed the contribution of key variables (including biological traits and sample collection parameters) to omics variability. Results: All omics displayed a large range of intra- and inter-individual variability depending on each omics feature, although all presented a highest median intra-individual variability. DNA methylation was the most stable profile (median 37.6% inter-individual variability) while gene expression was the least stable (6.6%). Among the least stable features, we identified 1% cross-omics co-variation between CpGs and metabolites (e.g. glucose and CpGs related to obesity and type 2 diabetes). Explanatory variables, including age and body mass index (BMI), explained up to 9% of serum metabolite variability. Conclusions: Methylation and targeted serum metabolomics are the most reliable omics to implement in single time-point measurements in large cross-sectional studies. In the case of metabolomics, sample collection and individual traits (e.g. BMI) are important parameters to control for improved comparability, at the study design or analysis stage. This study will be valuable for the design and interpretation of epidemiological studies that aim to link omics signatures to disease, environmental exposures, or both The study has received funding from the European Community’s Seventh Framework Programme (FP7/2007-206) under grant agreement no 308333 (HELIX project) and the H2020-EU.3.1.2. - Preventing Disease Programme under grant agreement no 874583 (ATHLETE project). Additionally, BiB received core infrastructure funding from the Wellcome Trust (WT101597MA) and a joint grant from the UK Medical Research Council (MRC) and Economic and Social Science Research Council (ESRC) (MR/N024397/1). INMA data collections were supported by grants from the Instituto de Salud Carlos III, CIBERESP, and the Generalitat de Catalunya-CIRIT. KANC was funded by the grant of the Lithuanian Agency for Science Innovation and Technology (6-04-2014_31V-66). The Rhea project was financially supported by European projects (EU FP6-2003-Food-3-NewGeneris, EU FP6. STREP Hiwate, EU FP7 ENV.2007.1.2.2.2. Project No 211250 Escape, EU FP7-2008-ENV- 1.2.1.4 Envirogenomarkers, EU FP7-HEALTH-2009- single stage CHICOS, EU FP7 ENV.2008.1.2.1.6. Proposal No 226285 ENRIECO, EU- FP7- HEALTH-2012 Proposal No 308333 HELIX), and the Greek Ministry of Health (Program of Prevention of obesity and neurodevelopmental disorders in preschool children, in Heraklion district, Crete, Greece: 2011- 2014; “Rhea Plus”: Primary Prevention Program of Environmental Risk Factors for Reproductive Health, and Child Health: 2012-15). The CRG/UPF Proteomics Unit is part of the Spanish Infrastructure for Omics Technologies (ICTS OmicsTech) and it is a member of the ProteoRed PRB3 consortium which is supported by grant PT17/0019 of the PE I+D+i 2013-2016 from the Instituto de Salud Carlos III (ISCIII) and ERDF. We acknowledge support from the Spanish Ministry of Science and Innovation and State Research Agency through the “Centro de Excelencia Severo Ochoa 2019-2023” Program (CEX2018-000806-S), and support from the Generalitat de Catalunya through the CERCA Program. MV-U and CR-A were supported by a FI fellowship from the Catalan Government (FI-DGR 2015 and #016FI_B 00272). MC received funding from Instituto Carlos III (Ministry of Economy and Competitiveness) (MS16/00128). LM is funded by a Juan de la Cierva-Incorporación fellowship (IJC2018-035394-I) awarded by the Spanish Ministerio de Economía, Industria y Competitividad SI
Published: 2021
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46. Validation and Genotyping of Multiple Human Polymorphic Inversions Mediated by Inverted Repeats Reveals a High Degree of Recurrence

Author: Alexander Martínez-Fundichely, Cristina Aguado, Laia Capilla, Aurora Ruiz-Herrera, Magdalena Gayà-Vidal, Víctor Montalvo, Carla Giner-Delgado, Meritxell Oliva, Mario Cáceres, Sergi Villatoro, David Izquierdo, Judit García-González, Marta Sabariego Puig, Xavier Estivill, and Cáceres Aguilar, Mario
Subjects: Ximpanzés -- Genètica, Cancer Research, Genotyping, lcsh:QH426-470, Pan troglodytes, Inverted Repeat Sequences, Human genomics, Single-nucleotide polymorphism, HapMap Project, Biology, Evolution, Molecular, Segmental Duplications, Genomic, Genetics, Animals, Humans, Mammalian genomics, International HapMap Project, Chimpanzees, Variant genotypes, Molecular Biology, Genome Evolution, Genetics (clinical), Ecology, Evolution, Behavior and Systematics, Segmental duplication, Chromosomal inversion, Evolutionary Biology, Polymorphism, Genetic, Genètica humana, Population Biology, Genome, Human, Chromosome Mapping, Human Genetics, Genomics, Inversions, Comparative Genomics, Polymerase chain reaction, Minor allele frequency, lcsh:Genetics, Haplotypes, Chromosome Inversion, Genetic Polymorphism, Human genome, Structural Genomics, Population Genetics, Research Article
Abstract: In recent years different types of structural variants (SVs) have been discovered in the human genome and their functional impact has become increasingly clear. Inversions, however, are poorly characterized and more difficult to study, especially those mediated by inverted repeats or segmental duplications. Here, we describe the results of a simple and fast inverse PCR (iPCR) protocol for high-throughput genotyping of a wide variety of inversions using a small amount of DNA. In particular, we analyzed 22 inversions predicted in humans ranging from 5.1 kb to 226 kb and mediated by inverted repeat sequences of 1.6–24 kb. First, we validated 17 of the 22 inversions in a panel of nine HapMap individuals from different populations, and we genotyped them in 68 additional individuals of European origin, with correct genetic transmission in ∼12 mother-father-child trios. Global inversion minor allele frequency varied between 1% and 49% and inversion genotypes were consistent with Hardy-Weinberg equilibrium. By analyzing the nucleotide variation and the haplotypes in these regions, we found that only four inversions have linked tag-SNPs and that in many cases there are multiple shared SNPs between standard and inverted chromosomes, suggesting an unexpected high degree of inversion recurrence during human evolution. iPCR was also used to check 16 of these inversions in four chimpanzees and two gorillas, and 10 showed both orientations either within or between species, providing additional support for their multiple origin. Finally, we have identified several inversions that include genes in the inverted or breakpoint regions, and at least one disrupts a potential coding gene. Thus, these results represent a significant advance in our understanding of inversion polymorphism in human populations and challenge the common view of a single origin of inversions, with important implications for inversion analysis in SNP-based studies., Author Summary Inversions have been an evolutionary biology model for almost a century, and recently the discovery of a high amount of structural variation in multiple organisms, including humans, has renewed the interest in them. Since early on, it was shown that they were adaptive and that they were involved in human diseases. However, in humans, the study of inversions has lagged behind due to important limitations in the experimental methods to analyze them. Here, we have optimized a technique for high-throughput validation and genotyping of inversions mediated by inverted repeats. By genotyping 17 of these inversions in a diverse sample of human individuals, including many of European origin and several non-human primates, we have carried out the most complete genotyping effort of human inversions to date. The results of our study indicate that a high proportion of these inversions are recurrent and have occurred multiple times during evolution. This represents an example of the plasticity of the genome and opens a new paradigm in the study of inversions, challenging the common view that inversions have a unique origin.
Published: 2021

47. Common Genetic Variation And Age at Onset Of Anorexia Nervosa

Author: Marion Leboyer, Martin A. Kennedy, Yiran Guo, Stephan Ripke, Roger D. Cone, Nadia Micali, Allan S. Kaplan, Jonathan R. I. Coleman, Michael Strober, Dan Rujescu, Roland Burghardt, Pierre J. Magistretti, John F. Pearson, Stephan Zipfel, Ian Jones, Paul Lichtenstein, Leonid Padyukov, Jurjen J. Luykx, Wade H. Berrettini, Nicolas Ramoz, James I. Hudson, Ulrike Schmidt, Anke Hinney, Tõnu Esko, Johanna Giuranna, Sara Marsal, Johan G. Eriksson, Richard Parker, Roger A.H. Adan, George Dedoussis, Lars Klareskog, Cynthia M. Bulik, Liselotte Petersen, Stephanie Le Hellard, P. Eline Slagboom, Jochen Seitz, Ilka Boehm, Anna Keski-Rahkonen, Joseph M. Boden, Sébastien Guillaume, Xavier Estivill, Yasmina Silén, Elisabeth Widen, Josef Bulant, Marta Tyszkiewicz-Nwafor, Vladimir Janout, Janne Tidselbak Larsen, Artemis Tsitsika, Kirsty Kiezebrink, James E. Mitchell, Lenka Slachtova, Andreas J. Forstner, Harry Brandt, Nicholas G. Martin, James L. Kennedy, Wolfgang Herzog, Jennifer Jordan, Ionna Ntalla, Marie Navratilova, Gun Peggy Knudsen, Stephanie Zerwas, Steven Crawford, Oleksandr Frei, Sven Cichon, Katherine A. Halmi, Scott D. Gordon, Sietske G. Helder, Marion Roberts, Esther Walton, Beate Herpertz-Dahlmann, Martina de Zwaan, Federica Tozzi, Bochao Lin, Beata Świątkowska, Konstantinos Tziouvas, Mikael Landén, Lenka Foretova, Richard M. Myers, Annemarie A. van Elburg, Martien J H Kas, Antonio Julià, Pamela K. Keel, Susana Jiménez-Murcia, Karin Egberts, Alessandro Rotondo, Lars Alfredsson, Hartmut Imgart, L. John Horwood, Margarita Ct. Slof-Op 't Landt, Maria La Via, Dalila Pinto, Danielle M. Dick, Craig Johnson, Xiao Chang, Julie K. O'Toole, Philip Gorwood, Christian R. Marshall, Preben Bo Mortensen, Srdjan Djurovic, Mònica Gratacòs, Laura M. Thornton, Elisa Docampo-Martinez, Jessica H. Baker, Walter H. Kaye, Sandro Sorbi, Catherine M. Olsen, Hakon Hakonarson, Helga Ask, Franziska Ritschel, Agnieszka Słopień, Steven Gallinger, Dong Li, Roel A. Ophoff, Ole A. Andreassen, Andreas Birgegård, Philibert Duriez, Monika Dmitrzak-Weglarz, Alexandra Havdahl, Andrew W. Bergen, Fragiskos Gonidakis, André Scherag, Scott J. Crow, Filip Rybakowski, Tracey D. Wade, Karen S. Mitchell, Claudette Boni, Hunna J. Watson, David C. Whiteman, Ina Giegling, Samuli Ripatti, Palmiero Monteleone, James J. Crowley, Manuel Föcker, Zeynep Yilmaz, Dimitris Dikeos, Stefan Herms, Thomas Werge, Eric F. van Furth, Christian Dina, Nancy L. Pedersen, Mario Maj, Philippe Courtet, Stephanie Jamain, Janet Treasure, Johannes Hebebrand, Hana Papežová, Michael Boehnke, Katharina Buehren, Joanna Hauser, Jacques Pantel, Manfred M. Fichter, Stephen W. Scherer, Gerome Breen, Fernando Fernández-Aranda, Leila Karhunen, Gursharan Kalsi, Geòrgia Escaramís, Anne Farmer, Ingrid Meulenbelt, Janiece E. DeSocio, Valdo Ricca, Lisa Lilenfeld, Laura J. Scott, Stefan Ehrlich, Jolanta Lissowska, Unna N. Danner, Morten Mattingsdal, D. Blake Woodside, Alfonso Tortorella, Anu Raevuori, Alessio Maria Monteleone, Ted Reichborn-Kjennerud, Deborah Kaminská, Jaakko Kaprio, Sarah Maguire, Kelly L. Klump, Watson, Hunna J., Thornton, Laura M., Yilmaz, Zeynep, Baker, Jessica H., Coleman, Jonathan RI., Adan, Roger AH., Alfredsson, Lar, Andreassen, Ole A., Ask, Helga, Berrettini, Wade H., Boehnke, Michael, Boehm, Ilka, Boni, Claudette, Buehren, Katharina, Bulant, Josef, Burghardt, Roland, Chang, Xiao, Cichon, Sven, Cone, Roger D., Courtet, Philippe, Crow, Scott, Crowley, James J., Danner, Unna N., de Zwaan, Martina, Dedoussis, George, Desocio, Janiece E., Dick, Danielle M., Dikeos, Dimitri, Dina, Christian, Djurovic, Srdjan, Dmitrzak-Weglarz, Monika, Docampo-Martinez, Elisa, Duriez, Philibert, Egberts, Karin, Ehrlich, Stefan, Eriksson, Johan G., Escaramís, Geòrgia, Esko, Tõnu, Estivill, Xavier, Farmer, Anne, Fernández-Aranda, Fernando, Fichter, Manfred M., Föcker, Manuel, Foretova, Lenka, Forstner, Andreas J., Frei, Oleksandr, Gallinger, Steven, Giegling, Ina, Giuranna, Johanna, Gonidakis, Fragisko, Gorwood, Philip, Gratacòs, Mònica, Guillaume, Sébastien, Guo, Yiran, Hakonarson, Hakon, Hauser, Joanna, Havdahl, Alexandra, Hebebrand, Johanne, Helder, Sietske G., Herms, Stefan, Herpertz-Dahlmann, Beate, Herzog, Wolfgang, Hinney, Anke, Hudson, James I., Imgart, Hartmut, Jamain, Stephanie, Janout, Vladimir, Jiménez-Murcia, Susana, Jones, Ian R., Julià, Antonio, Kalsi, Gursharan, Kaminská, Deborah, Kaprio, Jaakko, Karhunen, Leila, Kas, Martien JH., Keel, Pamela K., Kennedy, James L., Keski-Rahkonen, Anna, Kiezebrink, Kirsty, Klareskog, Lar, Klump, Kelly L., Knudsen, Gun Peggy S., La Via, Maria C., Le Hellard, Stephanie, Leboyer, Marion, Li, Dong, Lilenfeld, Lisa, Lin, Bochao, Lissowska, Jolanta, Luykx, Jurjen, Magistretti, Pierre, Maj, Mario, Marsal, Sara, Marshall, Christian R., Mattingsdal, Morten, Meulenbelt, Ingrid, Micali, Nadia, Mitchell, Karen S., Monteleone, Alessio Maria, Monteleone, Palmiero, Myers, Richard, Navratilova, Marie, Ntalla, Ionna, O'Toole, Julie K., Ophoff, Roel A., Padyukov, Leonid, Pantel, Jacque, Papežová, Hana, Pinto, Dalila, Raevuori, Anu, Ramoz, Nicola, Reichborn-Kjennerud, Ted, Ricca, Valdo, Ripatti, Samuli, Ripke, Stephan, Ritschel, Franziska, Roberts, Marion, Rotondo, Alessandro, Rujescu, Dan, Rybakowski, Filip, Scherag, André, Scherer, Stephen W., Schmidt, Ulrike, Scott, Laura J., Seitz, Jochen, Silén, Yasmina, Šlachtová, Lenka, Slagboom, P. Eline, Slof-Op 't Landt, Margarita CT., Slopien, Agnieszka, Sorbi, Sandro, Świątkowska, Beata, Tortorella, Alfonso, Tozzi, Federica, Treasure, Janet, Tsitsika, Artemi, Tyszkiewicz-Nwafor, Marta, Tziouvas, Konstantino, van Elburg, Annemarie A., van Furth, Eric F., Walton, Esther, Widen, Elisabeth, Zerwas, Stephanie, Zipfel, Stephan, Bergen, Andrew W., Boden, Joseph M., Brandt, Harry, Crawford, Steven, Halmi, Katherine A., Horwood, L. John, Johnson, Craig, Kaplan, Allan S., Kaye, Walter H., Mitchell, James E., Olsen, Catherine M., Pearson, John F., Pedersen, Nancy L., Strober, Michael, Werge, Thoma, Whiteman, David C., Woodside, D Blake, Gordon, Scott, Maguire, Sarah, Larsen, Janne T., Parker, Richard, Petersen, Liselotte V., Jordan, Jennifer, Kennedy, Martin, Wade, Tracey D., Birgegård, Andrea, Lichtenstein, Paul, Landén, Mikael, Martin, Nicholas G., Mortensen, Preben Bo, Breen, Gerome, Bulik, Cynthia M., Clinicum, Research Programs Unit, Johan Eriksson / Principal Investigator, Department of General Practice and Primary Health Care, Helsinki University Hospital Area, Institute for Molecular Medicine Finland, Helsinki Institute of Life Science HiLIFE, Anna Keski-Rahkonen / Principal Investigator, Department of Public Health, HUS Psychiatry, Nuorisopsykiatria, Centre of Excellence in Complex Disease Genetics, Samuli Olli Ripatti / Principal Investigator, Complex Disease Genetics, Faculty Common Matters (Faculty of Social Sciences), Biostatistics Helsinki, Elisabeth Ingrid Maria Widen / Principal Investigator, Genomic Discoveries and Clinical Translation, and Psychiatry
Subjects: Age of onset, Anorexia nervosa, Early-onset, GWAS, Genetic risk score, Genetics, Menarche, Mendelian randomization, Puberty, Genome-wide association study, Biology, Genetic correlation, 3124 Neurology and psychiatry, 03 medical and health sciences, 0302 clinical medicine, SDG 3 - Good Health and Well-being, Genetic variation, 030304 developmental biology, 0303 health sciences, Mendelian Randomization Analysis, General Medicine, Heritability, 3. Good health, Anorexia nervosa (differential diagnoses), age at onset, 030217 neurology & neurosurgery, Demography
Abstract: BackgroundGenetics and biology may influence the age of onset of anorexia nervosa (AN). The aims of this study were to determine whether common genetic variation contributes to age of onset of AN and to investigate the genetic associations between age of onset of AN and age at menarche.MethodsA secondary analysis of the Psychiatric Genomics Consortium genome-wide association study (GWAS) of AN was performed, which included 9335 cases and 31,981 screened controls, all from European ancestries. We conducted GWASs of age of onset, early-onset AN (ResultsTwo loci were genome-wide significant in the typical-onset AN GWAS. Heritability estimates (single nucleotide polymorphism–h2) were 0.01–0.04 for age of onset, 0.16–0.25 for early-onset AN, and 0.17–0.25 for typical-onset AN. Early- and typical-onset AN showed distinct genetic correlation patterns with putative risk factors for AN. Specifically, early-onset AN was significantly genetically correlated with younger age at menarche, and typical-onset AN was significantly negatively genetically correlated with anthropometric traits. Genetic risk scores for age of onset and early-onset AN estimated from independent GWASs significantly predicted age of onset. Mendelian randomization analysis suggested a causal link between younger age at menarche and early-onset AN.ConclusionsOur results provide evidence consistent with a common variant genetic basis for age of onset and implicate biological pathways regulating menarche and reproduction. Background: Genetics and biology may influence the age of onset of anorexia nervosa (AN). The aims of this study were to determine whether common genetic variation contributes to age of onset of AN and to investigate the genetic associations between age of onset of AN and age at menarche. Methods: A secondary analysis of the Psychiatric Genomics Consortium genome-wide association study (GWAS) of AN was performed, which included 9335 cases and 31,981 screened controls, all from European ancestries. We conducted GWASs of age of onset, early-onset AN (2) were 0.01–0.04 for age of onset, 0.16–0.25 for early-onset AN, and 0.17–0.25 for typical-onset AN. Early- and typical-onset AN showed distinct genetic correlation patterns with putative risk factors for AN. Specifically, early-onset AN was significantly genetically correlated with younger age at menarche, and typical-onset AN was significantly negatively genetically correlated with anthropometric traits. Genetic risk scores for age of onset and early-onset AN estimated from independent GWASs significantly predicted age of onset. Mendelian randomization analysis suggested a causal link between younger age at menarche and early-onset AN. Conclusions: Our results provide evidence consistent with a common variant genetic basis for age of onset and implicate biological pathways regulating menarche and reproduction.
Published: 2021

48. Worldwide population distribution of the common LCE3C-LCE3B deletion associated with psoriasis and other autoimmune disorders

Author: Juan R. González, Manel García-Aragonés, Mario Cáceres, Eva Riveira-Muñoz, Laia Bassaganyas, Lluís Armengol, and Xavier Estivill
Subjects: Linkage disequilibrium, DNA Copy Number Variations, Genotyping Techniques, Population, Locus (genetics), HapMap Project, Biology, Genoma humà, Polymorphism, Single Nucleotide, Linkage Disequilibrium, Autoimmune Diseases, 03 medical and health sciences, 0302 clinical medicine, Genetic drift, Gene Frequency, INDEL Mutation, Human Genome Project, Genetics, Humans, Human populations, Psoriasis, Genetic variation, Allele, education, Allele frequency, Alleles, 030304 developmental biology, Sequence Deletion, 0303 health sciences, education.field_of_study, Comparative Genomic Hybridization, Cromosomes humans, Copy number variants, Malalties autoimmunitàries, Racial Groups, Human populatio, Tag SNP, Autoimmune disorders, LCE3C_LCE3B-del, Genetics, Population, Chromosomes, Human, Pair 1, 030220 oncology & carcinogenesis, Common disease-common variant, Research Article, Biotechnology
Abstract: Background There is increasing evidence of the importance of copy number variants (CNV) in genetic diversity among individuals and populations, as well as in some common genetic diseases. We previously characterized a common 32-kb insertion/deletion variant of the PSORS4 locus at chromosome 1q21 that harbours the LCE3C and LCE3B genes. This variant allele (LCE3C_LCE3B-del) is common in patients with psoriasis and other autoimmune disorders from certain ethnic groups. Results Using array-CGH (Agilent 244 K) in samples from the HapMap and Human Genome Diversity Panel (HGDP) collections, we identified 54 regions showing population differences in comparison to Africans. We provided here a comprehensive population-genetic analysis of one of these regions, which involves the 32-kb deletion of the PSORS4 locus. By a PCR-based genotyping assay we characterised the profiles of the LCE3C_LCE3B-del and the linkage disequilibrium (LD) pattern between the variant allele and the tag SNP rs4112788. Our results show that most populations tend to have a higher frequency of the deleted allele than Sub-Saharan Africans. Furthermore, we found strong LD between rs4112788G and LCE3C_LCE3B-del in most non-African populations (r2 >0.8), in contrast to the low concordance between loci (r2 Conclusions These results are another example of population variability in terms of biomedical interesting CNV. The frequency distribution of the LCE3C_LCE3B-del allele and the LD pattern across populations suggest that the differences between ethnic groups might not be due to natural selection, but the consequence of genetic drift caused by the strong bottleneck that occurred during “out of Africa” expansion.
Published: 2021

49. Shared genetic risk between eating disorder- and substance-use-related phenotypes: Evidence from genome-wide association studies

Author: Samuel Kuperman, Leila Karhunen, Geòrgia Escaramís, Sébastien Guillaume, Kelly L. Klump, David C. Whiteman, Colin A. Hodgkinson, Stephanie H. Witt, Artemis Tsitsika, Hana Papezova, Renato Polimanti, P. Eline Slagboom, Peter Zill, Jakob Grove, Toni-Kim Clarke, Michael Soyka, Jennifer Jordan, Steven Gallinger, Philip Gorwood, Preben Bo Mortensen, Yuri Milaneschi, Ingrid Meulenbelt, Jen Chyong Wang, Markus M. Nöthen, Katrin Männik, Henry R. Kranzler, Michael M. Vanyukov, Anna Keski-Rahkonen, William G. Iacono, Raymond K. Walters, Stephanie Le Hellard, Bochao Danae Lin, Vesna Boraska Perica, Marion Roberts, Patrick F. Sullivan, Steven Crawford, Mark A. Frye, Melissa A. Munn-Chernoff, Hakon Hakonarson, Andreas Birgegård, Robert Culverhouse, Alexis C. Edwards, Jerome C. Foo, Alessandro Rotondo, Brenda W.J.H. Penninx, Laura M. Hack, Michael T. Lynskey, Mario Maj, Alessio Maria Monteleone, Ted Reichborn-Kjennerud, Julie K. O'Toole, Marta Tyszkiewicz-Nwafor, Matt McGue, Julien Bryois, Martina de Zwaan, Norbert Dahmen, Stefanie Heilmann-Heimbach, Deborah Kaminská, Benedetta Nacmias, Nicholas G. Martin, Anna R. Docherty, Christopher Hübel, Nancy L. Pedersen, Janet Treasure, William E. Copeland, Roger A.H. Adan, Jaakko Kaprio, Aarno Palotie, L. John Horwood, Maria La Via, Philippe Courtet, Virpi M. Leppä, Judy L. Silberg, Jason D. Boardman, Fazil Aliev, Wade H. Berrettini, Doo Sup Choi, Youl-Ri Kim, Konstantinos Hatzikotoulas, Harriet de Wit, Sandra A. Brown, Elisabeth Widen, Caroline Hayward, Nicholas J. Schork, Penelope A. Lind, Ralph E. Tarter, Jana Strohmaier, Allan S. Kaplan, Richard A. Grucza, Bradley T. Webb, Angela Favaro, Dalila Pinto, Helena Gaspar, Andrew W. Bergen, Beate Herpertz-Dahlmann, Robert Levitan, Wolfgang Gäbel, Xavier Estivill, Emma C. Johnson, Konstantinos Tziouvas, Lindsay A. Farrer, Lenka Foretova, Marc A. Schuckit, Joanna M. Biernacka, André Scherag, Robbee Wedow, Abraham A. Palmer, Amy E. Adkins, Franziska Degenhardt, Louisa Degenhardt, Jurjen J. Luykx, Marius Lahti-Pulkkinen, Brien P. Riley, Monika Ridinger, Matteo Cassina, Harry Brandt, Yiran Guo, Stephan Ripke, Palmiero Monteleone, Katri Räikkönen, Jonathan R. I. Coleman, Martin A. Kennedy, Stephen W. Scherer, Ioanna Tachmazidou, Catherine M. Olsen, Bernice Porjesz, Esther Walton, Yi-Ling Chou, Nicolas Ramoz, Tetsuya Ando, Andres Metspalu, Bertram Müller-Myhsok, Brion S. Maher, Sarah Bertelsen, Melanie L. Schwandt, Janiece E. DeSocio, Margaret Keyes, John F. Pearson, Dongbing Lai, Paul Lichtenstein, James MacKillop, George Dedoussis, Jari Lahti, Ulrike Schmidt, Stefan Ehrlich, Amanda G. Wills, Teemu Palviainen, David Goldman, Elena Tenconi, Dimitris Dikeos, Scott I. Vrieze, Sietske G. Helder, Katharina Buehren, Hongyu Zhao, Sara McDevitt, Jolanta Lissowska, Joseph M. Boden, Li-Shiun Chen, Susanne Lucae, Sara Marsal, Dan Rujescu, Claes Norring, Howard J. Edenberg, Victor M. Karpyak, Fragiskos Gonidakis, Per Hoffmann, Christopher S. Franklin, Karin Egberts, Johanna Giuranna, Stefan Herms, Leah Wetherill, Stephanie Zerwas, Anthony Batzler, Elliot C. Nelson, Jouke-Jan Hottenga, Marcella Rietschel, Ioanna Ntalla, Victor Hesselbrock, Sarah M. Hartz, Marie Navratilova, Falk Kiefer, Martien J H Kas, Richard J. Rose, Andrew C. Heath, Jin P. Szatkiewicz, Lenka Slachtova, Lisa Lilenfeld, Katherine A. Halmi, John P. Rice, Anjali K. Henders, Christian Dina, Norbert Wodarz, Satu Männistö, Hamdi Mbarek, Shuyang Yao, Vladimir Janout, Alison Goate, Bettina Konte, Alexandra Schosser, Danfeng Chen, Kirsty Kiezebrink, Euijung Ryu, Dana B. Hancock, James Mitchell, Sarah E. Medland, Ina Giegling, Valdo Ricca, Scott D. Gordon, Gabrielle Koller, Samuli Ripatti, Laura M. Thornton, Alison D. Murray, Morten Mattingsdal, Zeynep Yilmaz, Jens Treutlein, Kathleen K. Bucholz, Tim B. Bigdeli, Eric F. van Furth, Hermine H. Maes, Ken B. Hanscombe, Sandra Sanchez-Roige, Daniela Degortes, Monica Forzan, Manuel Mattheisen, Richard Sherva, Scott J. Crow, Mikael Landén, Wolfgang Herzog, Jeanette N. McClintick, Tõnu Esko, Louis Fox, Wolfgang Maier, Liselotte Petersen, Laura J. Bierut, Roseann E. Peterson, Gursharan Kalsi, Kathleen Mullan Harris, Margarita C T Slof-Op 't Landt, Tamara L. Wall, Patrik K. E. Magnusson, Unna N. Danner, Stephan Zipfel, Ulrich W. Preuss, Elisa Docampo, D. Blake Woodside, Alfonso Tortorella, Benjamin W. Domingue, Franziska Ritschel, Johan G. Eriksson, Anu Raevuori, Benjamin M. Neale, Marcus Ising, Annemarie A. van Elburg, Filip Rybakowski, Maureen Reynolds, Tracey D. Wade, Manfred M. Fichter, Monica Gratacos Mayora, Claudette Boni, Andreas J. Forstner, John Whitfield, Silviu Alin Bacanu, Matthew B. McQueen, Andrew M. McIntosh, Norbert Scherbaum, Tatiana Foroud, Gun Peggy Knudsen, Sven Cichon, Christian J. Hopfer, Josef Frank, Eleftheria Zeggini, Federica Tozzi, Nadia Micali, Danielle M. Dick, Pamela A. F. Madden, Christian R. Marshall, Johannes Hebebrand, Fernando Fernández-Aranda, Roel A. Ophoff, Roland Burghardt, Nathaniel Thomas, Leonid Padyukov, Nancy L. Saccone, Anu Loukola, Fabian Streit, James L. Kennedy, Jessica H. Baker, Peter McGuffin, Walter H. Kaye, Pei Hong Shen, Anne Farmer, Roger D. Cone, Ilka Boehm, Jacquelyn L. Meyers, Paolo Santonastaso, Maurizio Clementi, Susana Jiménez-Murcia, Gudrun Wagner, Anke Hinney, Richard Parker, James I. Hudson, Nathan A. Gillespie, Michael Strober, John I. Nurnberger, Sandro Sorbi, Dorret I. Boomsma, Beata Świątkowska, Janne Tidselbak Larsen, Kenneth S. Kendler, Hidetoshi Inoko, Jessica E. Salvatore, Hunna J. Watson, Jochen Seitz, Jacques Pantel, Karl Mann, Hang Zhou, Antonio Julià, Oliver S. P. Davis, Nancy Diazgranados, Krista Fischer, John K. Hewitt, Karen S. Mitchell, Joanna Hauser, Eric O. Johnson, Craig Johnson, E. Jane Costello, Agnieszka Słopień, Dong Li, Laramie E. Duncan, Arpana Agrawal, Grant W. Montgomery, Manuel Föcker, Thomas Werge, Lannie Ligthart, Andreas Karwautz, Raquel Rabionet, Kenneth Krauter, Joel Gelernter, James J. Crowley, Cynthia M. Bulik, Paola Giusti-Rodríguez, Laura M. Huckins, Gerome Breen, Michael C. Stallings, Daniel E. Adkins, Pierre J. Magistretti, John Kramer, Lars Alfredsson, Hartmut Imgart, Annette M. Hartmann, Ole A. Andreassen, Monika Dmitrzak-Weglarz, Psychiatry, University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC), Department Psychiatry [Chapel Hill], University of North Carolina System (UNC)-University of North Carolina System (UNC), Washington University School of Medicine in St. Louis, Washington University in Saint Louis (WUSTL), Institute of Psychiatry, Psychology & Neuroscience, King's College London, King‘s College London, Harvard Medical School [Boston] (HMS), Broad Institute of MIT and Harvard (BROAD INSTITUTE), Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston], QIMR Berghofer Medical Research Institute, Karolinska Institutet [Stockholm], University Children's Hospital of Essen [Essen, Germany], University of Duisburg-Essen, Aarhus University [Aarhus], Stockholm County Council, University of Würzburg, Guy's Hospital [London], University Medical Center [Utrecht], University of Gothenburg (GU), Altrecht Center for Eating Disorders Rintveld [Zeist, The Netherlands] (Mental Health Institute), National Institute of Mental Health [Tokyo, Japan] (NIMH), National Center of Neurology and Psychiatry [Tokyo, Japan], University of Oslo (UiO), Norwegian Centre for Mental Disorders Research [Oslo] (NORMENT), University of Oslo (UiO)-Haukeland University Hospital, University of Bergen (UiB)-University of Bergen (UiB)-Oslo University Hospital [Oslo], Department of Psychiatry [Philadelphia], University of Pennsylvania [Philadelphia], Perelman School of Medicine, Technische Universität Dresden = Dresden University of Technology (TU Dresden), Institut de psychiatrie et neurosciences (U894 / UMS 1266), Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), University of Split, The Wellcome Trust Sanger Institute [Cambridge], RWTH Aachen University, Universitätsklinikum Frankfurt, Universita degli Studi di Padova, University Hospital Basel [Basel], Jülich Supercomputing Centre (JSC), Forschungszentrum Jülich GmbH | Centre de recherche de Juliers, Helmholtz-Gemeinschaft = Helmholtz Association-Helmholtz-Gemeinschaft = Helmholtz Association, Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier), Neuropsychiatrie : recherche épidémiologique et clinique (PSNREC), Université Montpellier 1 (UM1)-Université de Montpellier (UM)-Institut National de la Santé et de la Recherche Médicale (INSERM), University of Minnesota System, University of Bristol [Bristol], Hannover Medical School [Hannover] (MHH), Harokopio University of Athens, Seattle University [Seattle], Virginia Commonwealth University (VCU), University of Athens Medical School [Athens], unité de recherche de l'institut du thorax UMR1087 UMR6291 (ITX), Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), Université de Nantes (UN)-Université de Nantes (UN)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Poznan University of Medical Sciences [Poland] (PUMS), Institute of Environmental Science and Technology [Barcelona] (ICTA), Universitat Autònoma de Barcelona (UAB), Massachusetts General Hospital [Boston], Stanford University, MetaGenoPolis (MGP (US 1367)), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Estonian Genome and Medicine, University of Tartu, Universitat Pompeu Fabra [Barcelona] (UPF), MRC Social, Genetic and Developmental Psychiatry Centre (SGDP), The Institute of Psychiatry-King‘s College London, Department of Psychiatry (IDIBELL), CIBERobn Fisiopatología de la Obesidad y Nutrición-University Hospital of Bellvitge, Ludwig-Maximilians-Universität München (LMU), Infectious diseases division, Department of internal medicine, University of Münster, Masaryk Memorial Cancer Institute, Masaryk Memorial Cancer Institute (RECAMO), Universitätsklinikum Bonn (UKB), Familial Gastrointestinal Cancer Registry, Mount Sinai Hospital [Toronto, Canada] (MSH), Medstar Research Institute, Universität Duisburg-Essen [Essen], National and Kapodistrian University of Athens (NKUA), Children’s Hospital of Philadelphia (CHOP ), The Center for Applied Genomics, Psychiatric Genetic Unit, Poznan University of Medical Sciences, Department of Child and Adolescent Psychiatry and Psychotherapy, LVR-Klinikum Essen, Centre for Epidemiology and Biostatistics, Faculty of Medicine and Health Leeds, University of Leeds, Rheinisch-Westfälische Technische Hochschule Aachen (RWTH), Heidelberg University Hospital [Heidelberg], Icahn School of Medicine at Mount Sinai [New York] (MSSM), School of Biomedical Sciences, The University of Queensland, Brisbane, QLD, 4072, Australia., Parkland-Klinik [Bad Wildungen-Reinhardshausen, Germany], Tokai University, Department of Epidemiology and Public Health [university of Ostrava], Lékařská fakulta / Faculty of Medicine [University of Ostrava], Ostravská univerzita / University of Ostrava-Ostravská univerzita / University of Ostrava, Vall d'Hebron University Hospital [Barcelona], Charles University [Prague] (CU), University of Eastern Finland, Medizinische Universität Wien = Medical University of Vienna, Centre de toxicomanie et de santé mentale [Toronto, ON, Canada], University of Helsinki, University of Aberdeen, Faculty of Science, J.E. Purkinje University, J. E. Purkinje University, Michigan State University System, Norwegian Institute of Public Health [Oslo] (NIPH), Haukeland University Hospital, University of Bergen (UiB), Ingénierie Moléculaire et Physiopathologie Articulaire (IMoPA), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), The Chicago School of Professional Psychology [Washington, District of Columbia, USA] (Washington DC Campus), Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, Brain and Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Department of Psychiatry, University of Napoli, Center for Integrative Genomics - Institute of Bioinformatics, Génopode (CIG), Swiss Institute of Bioinformatics [Lausanne] (SIB), Université de Lausanne (UNIL)-Université de Lausanne (UNIL), Program in Genetics and Genomic Biology, Hospital for Sick Children-University of Toronto McLaughlin Centre, KG Jebsen Centre for Psychosis Research, University of Oslo (UiO)-Institute of Clinical Medicine-Oslo University Hospital [Oslo], University College Cork (UCC), Section Molecular Epidemiology, Leiden University Medical Center (LUMC), Institute of Psychiatry, King's College, VA Boston Healthcare System, Università degli studi della Campania 'Luigi Vanvitelli', Università degli Studi di Firenze = University of Florence [Firenze] (UNIFI), Kartini Clinic [Portland, Oregon, USA], University Medical Center [Utrecht]-Brain Center Rudolf Magnus, Head of Medical Sequencing, Vanderbilt University School of Medicine [Nashville], The Hospital for sick children [Toronto] (SickKids), Center for Genomic Regulation (CRG-UPF), CIBER de Epidemiología y Salud Pública (CIBERESP), Department of Medical Epidemiology and Biostatistics (MEB), University of Pisa - Università di Pisa, Division of Psychiatric Genomics, Institute of Medical Informatics, Biometry and Epidemiology, Department of Molecular and Experimental Medicine, The Scripps Research Institute, The Scripps Research Institute, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University-Medical Research Council, Leiden University Medical Center (LUMC), Center for Eating Disorders Ursula [Leiden, The Netherlands] (Rivierduinen), Medical University of Łódź (MUL), The Jackson Laboratory [Bar Harbor] (JAX), Neurosciences Centre of Excellence in Drug Discovery, GlaxoSmithKline Research and Development, Utrecht University [Utrecht], SURFACES, Institut de recherches sur la catalyse et l'environnement de Lyon (IRCELYON), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Centre épigénétique et destin cellulaire (EDC (UMR_7216)), Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Human Genetics, Internal Medicine [Tuebingen, Germany], Tuebingen University [Germany], Oregon Research Institute (ORI), University of Otago [Dunedin, Nouvelle-Zélande], The Center for Eating Disorders at Sheppard Pratt [Baltimore, MD, USA], Weill Medical College of Cornell University [New York], Eating Recovery Center [Denver, CO, USA], Centre for Addiction and Mental Health [Toronto, ON, Canada], University of California [San Diego] (UC San Diego), University of California, Jet Propulsion Laboratory (JPL), NASA-California Institute of Technology (CALTECH), David Geffen School of Medicine [Los Angeles], University of California [Los Angeles] (UCLA), University of California-University of California, Center for Genomic Medicine, Copenhagen University Hospital-Rigshospitalet [Copenhagen], Copenhagen University Hospital, Institute of Medical Science [Toronto], University of Toronto, Department of Psychiatry [Pittsburgh], University of Pittsburgh School of Medicine, Pennsylvania Commonwealth System of Higher Education (PCSHE)-Pennsylvania Commonwealth System of Higher Education (PCSHE), The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Génétique des maladies multifactorielles (GMM), Université de Lille, Droit et Santé-Centre National de la Recherche Scientifique (CNRS), Sahlgrenska Academy at University of Gothenburg [Göteborg], Department of Genomics, Yale University School of Medicine, Indiana University School of Medicine, Indiana University System, Mayo Clinic [Rochester], Mayo Clinic, SUNY Downstate Medical Center, State University of New York (SUNY), University of Edinburgh, Department of Genomics, Life and Brain Center, University of Bonn, University of Utah School of Medicine [Salt Lake City], University of Heidelberg, Medical Faculty, Department of Psychiatry and Behavioral Sciences, Howard University College of Medicine, Department of Genomics [Bonn, Germany] (Institute of Human Genetics), University of Bonn-Institute of Human Genetics [Bonn, Germany], National Institutes of Health [Bethesda] (NIH), National Institute on Alcohol Abuse and Alcoholism [Bethesda, MD, USA] (NIAAA), Martin-Luther-University Halle-Wittenberg, Helsinki Institute of Life Science (HiLIFE), Johns Hopkins Bloomberg School of Public Health [Baltimore], Johns Hopkins University (JHU), Vrije Universiteit Amsterdam [Amsterdam] (VU), Mathematical Sciences Institute (MSI), Australian National University (ANU), University of Colorado [Boulder], VU University Medical Center [Amsterdam], Boston University School of Medicine (BUSM), Boston University [Boston] (BU), Universität Heidelberg [Heidelberg], Department of Genetic Epidemiology in Psychiatry [Mannhein], Universität Heidelberg [Heidelberg]-Central Institute of Mental Health Mannheim, Harvard University [Cambridge], University of Colorado Anschutz [Aurora], University of Vermont [Burlington], University of New South Wales [Sydney] (UNSW), University of Dusseldorf, Genetics and Pathology, Center for Human Genetic Research, Harvard Medical School [Boston] (HMS)-Massachusetts General Hospital [Boston], Heidelberg University, University of Iowa [Iowa City], Vienna University of Technology (TU Wien), Max Planck Institute of Psychiatry, Max-Planck-Gesellschaft, Department of Psychiatry and Psychotherapy, Rheinische Friedrich-Wilhelms-Universität Bonn, Chronic Disease Epidemiology and Prevention Unit, National Institute for Health and Welfare [Helsinki], Translational Centre for Regenerative Medicine (TRM), Department of Cell Therapy, Universität Leipzig [Leipzig]-Universität Leipzig [Leipzig], Indiana University System-Indiana University System, University of Pittsburgh (PITT), Pennsylvania Commonwealth System of Higher Education (PCSHE), University of Regensburg, Rush University Medical Center [Chicago], University of Utah, Duke University Medical Center, University of Illinois [Chicago] (UIC), University of Illinois System, Department of Medical and Molecular Genetics, Dpt of Neuroscience [New York], Laboratory of Neurogenetics, National Institutes of Health [Bethesda] (NIH)-National Institute on Alcohol Abuse and Alcoholism, Department of Health and Human Services, University of Connecticut (UCONN), University of Colorado [Denver], Research Triangle Institute International (RTI International), McMaster University [Hamilton, Ontario], CLinical Psychology, Department of Electrical and Computer Engineering [Montréal], McGill University = Université McGill [Montréal, Canada], Yale School of Public Health (YSPH), Analytic and Translational Genetics Unit, Flinders University [Adelaide, Australia], Universidad Complutense de Madrid = Complutense University of Madrid [Madrid] (UCM), Department of Public Health, Indiana University - Purdue University Indianapolis (IUPUI), National Institute of Mental Health (NIMH), University of Pennsylvania, Rheinisch-Westfälische Technische Hochschule Aachen University (RWTH), Università degli Studi di Padova = University of Padua (Unipd), Université Montpellier 1 (UM1)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM), Unité de recherche de l'institut du thorax (ITX-lab), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), Université de Nantes (UN)-Université de Nantes (UN), King‘s College London-The Institute of Psychiatry, Westfälische Wilhelms-Universität Münster = University of Münster (WWU), Masaryk Memorial Cancer Institute (MMCI), Helsingin yliopisto = Helsingfors universitet = University of Helsinki, Université de Lausanne = University of Lausanne (UNIL)-Université de Lausanne = University of Lausanne (UNIL), Università degli studi della Campania 'Luigi Vanvitelli' = University of the Study of Campania Luigi Vanvitelli, Università degli Studi di Firenze = University of Florence (UniFI), Department of Molecular Medicine [Scripps Research Institute], The Scripps Research Institute [La Jolla, San Diego], Medical Research Council-Cardiff University, Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), University of California (UC), University of California (UC)-University of California (UC), Yale School of Medicine [New Haven, Connecticut] (YSM), Heinrich Heine Universität Düsseldorf = Heinrich Heine University [Düsseldorf], Martinez Rico, Clara, Biological Psychology, APH - Health Behaviors & Chronic Diseases, APH - Personalized Medicine, APH - Mental Health, APH - Methodology, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Amsterdam Neuroscience - Complex Trait Genetics, APH - Digital Health, Kas lab, Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), Munn-Chernoff, M. A., Johnson, E. C., Chou, Y. -L., Coleman, J. R. I., Thornton, L. M., Walters, R. K., Yilmaz, Z., Baker, J. H., Hubel, C., Gordon, S., Medland, S. E., Watson, H. J., Gaspar, H. A., Bryois, J., Hinney, A., Leppa, V. M., Mattheisen, M., Ripke, S., Yao, S., Giusti-Rodriguez, P., Hanscombe, K. B., Adan, R. A. H., Alfredsson, L., Ando, T., Andreassen, O. A., Berrettini, W. H., Boehm, I., Boni, C., Boraska Perica, V., Buehren, K., Burghardt, R., Cassina, M., Cichon, S., Clementi, M., Cone, R. D., Courtet, P., Crow, S., Crowley, J. J., Danner, U. N., Davis, O. S. P., de Zwaan, M., Dedoussis, G., Degortes, D., Desocio, J. E., Dick, D. M., Dikeos, D., Dina, C., Dmitrzak-Weglarz, M., Docampo, E., Duncan, L. E., Egberts, K., Ehrlich, S., Escaramis, G., Esko, T., Estivill, X., Farmer, A., Favaro, A., Fernandez-Aranda, F., Fichter, M. M., Fischer, K., Focker, M., Foretova, L., Forstner, A. J., Forzan, M., Franklin, C. S., Gallinger, S., Giegling, I., Giuranna, J., Gonidakis, F., Gorwood, P., Gratacos Mayora, M., Guillaume, S., Guo, Y., Hakonarson, H., Hatzikotoulas, K., Hauser, J., Hebebrand, J., Helder, S. G., Herms, S., Herpertz-Dahlmann, B., Herzog, W., Huckins, L. M., Hudson, J. I., Imgart, H., Inoko, H., Janout, V., Jimenez-Murcia, S., Julia, A., Kalsi, G., Kaminska, D., Karhunen, L., Karwautz, A., Kas, M. J. H., Kennedy, J. L., Keski-Rahkonen, A., Kiezebrink, K., Kim, Y. -R., Klump, K. L., Knudsen, G. P. S., La Via, M. C., Le Hellard, S., Levitan, R. D., Li, D., Lilenfeld, L., Lin, B. D., Lissowska, J., Luykx, J., Magistretti, P. J., Maj, M., Mannik, K., Marsal, S., Marshall, C. R., Mattingsdal, M., Mcdevitt, S., Mcguffin, P., Metspalu, A., Meulenbelt, I., Micali, N., Mitchell, K., Monteleone, A. M., Monteleone, P., Nacmias, B., Navratilova, M., Ntalla, I., O'Toole, J. K., Ophoff, R. A., Padyukov, L., Palotie, A., Pantel, J., Papezova, H., Pinto, D., Rabionet, R., Raevuori, A., Ramoz, N., Reichborn-Kjennerud, T., Ricca, V., Ripatti, S., Ritschel, F., Roberts, M., Rotondo, A., Rujescu, D., Rybakowski, F., Santonastaso, P., Scherag, A., Scherer, S. W., Schmidt, U., Schork, N. J., Schosser, A., Seitz, J., Slachtova, L., Slagboom, P. E., Slof-Op't Landt, M. C. T., Slopien, A., Sorbi, S., Swiatkowska, B., Szatkiewicz, J. P., Tachmazidou, I., Tenconi, E., Tortorella, A., Tozzi, F., Treasure, J., Tsitsika, A., Tyszkiewicz-Nwafor, M., Tziouvas, K., van Elburg, A. A., van Furth, E. F., Wagner, G., Walton, E., Widen, E., Zeggini, E., Zerwas, S., Zipfel, S., Bergen, A. W., Boden, J. M., Brandt, H., Crawford, S., Halmi, K. A., Horwood, L. J., Johnson, C., Kaplan, A. S., Kaye, W. H., Mitchell, J., Olsen, C. M., Pearson, J. F., Pedersen, N. L., Strober, M., Werge, T., Whiteman, D. C., Woodside, D. B., Grove, J., Henders, A. K., Larsen, J. T., Parker, R., Petersen, L. V., Jordan, J., Kennedy, M. A., Birgegard, A., Lichtenstein, P., Norring, C., Landen, M., Mortensen, P. B., Polimanti, R., Mcclintick, J. N., Adkins, A. E., Aliev, F., Bacanu, S. -A., Batzler, A., Bertelsen, S., Biernacka, J. M., Bigdeli, T. B., Chen, L. -S., Clarke, T. -K., Degenhardt, F., Docherty, A. R., Edwards, A. C., Foo, J. C., Fox, L., Frank, J., Hack, L. M., Hartmann, A. M., Hartz, S. M., Heilmann-Heimbach, S., Hodgkinson, C., Hoffmann, P., Hottenga, J. -J., Konte, B., Lahti, J., Lahti-Pulkkinen, M., Lai, D., Ligthart, L., Loukola, A., Maher, B. S., Mbarek, H., Mcintosh, A. M., Mcqueen, M. B., Meyers, J. L., Milaneschi, Y., Palviainen, T., Peterson, R. E., Ryu, E., Saccone, N. L., Salvatore, J. E., Sanchez-Roige, S., Schwandt, M., Sherva, R., Streit, F., Strohmaier, J., Thomas, N., Wang, J. -C., Webb, B. T., Wedow, R., Wetherill, L., Wills, A. G., Zhou, H., Boardman, J. D., Chen, D., Choi, D. -S., Copeland, W. E., Culverhouse, R. C., Dahmen, N., Degenhardt, L., Domingue, B. W., Frye, M. A., Gaebel, W., Hayward, C., Ising, M., Keyes, M., Kiefer, F., Koller, G., Kramer, J., Kuperman, S., Lucae, S., Lynskey, M. T., Maier, W., Mann, K., Mannisto, S., Muller-Myhsok, B., Murray, A. D., Nurnberger, J. I., Preuss, U., Raikkonen, K., Reynolds, M. D., Ridinger, M., Scherbaum, N., Schuckit, M. A., Soyka, M., Treutlein, J., Witt, S. H., Wodarz, N., Zill, P., Adkins, D. E., Boomsma, D. I., Bierut, L. J., Brown, S. A., Bucholz, K. K., Costello, E. J., de Wit, H., Diazgranados, N., Eriksson, J. G., Farrer, L. A., Foroud, T. M., Gillespie, N. A., Goate, A. M., Goldman, D., Grucza, R. A., Hancock, D. B., Harris, K. M., Hesselbrock, V., Hewitt, J. K., Hopfer, C. J., Iacono, W. G., Johnson, E. O., Karpyak, V. M., Kendler, K. S., Kranzler, H. R., Krauter, K., Lind, P. A., Mcgue, M., Mackillop, J., Madden, P. A. F., Maes, H. H., Magnusson, P. K. E., Nelson, E. C., Nothen, M. M., Palmer, A. A., Penninx, B. W. J. H., Porjesz, B., Rice, J. P., Rietschel, M., Riley, B. P., Rose, R. J., Shen, P. -H., Silberg, J., Stallings, M. C., Tarter, R. E., Vanyukov, M. M., Vrieze, S., Wall, T. L., Whitfield, J. B., Zhao, H., Neale, B. M., Wade, T. D., Heath, A. C., Montgomery, G. W., Martin, N. G., Sullivan, P. F., Kaprio, J., Breen, G., Gelernter, J., Edenberg, H. J., Bulik, C. M., and Agrawal, A.
Subjects: Netherlands Twin Register (NTR), Alcoholism/genetics, Schizophrenia/genetics, [SDV]Life Sciences [q-bio], [SDV.MHEP.PSM] Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health, Medizin, Medicine (miscellaneous), Genome-wide association study, Alcohol use disorder, Anorexia nervosa, Linkage Disequilibrium, ddc:616.89, [SCCO]Cognitive science, 0302 clinical medicine, Risk Factors, Tobacco Use Disorder/genetics, Substance-Related Disorders/genetics, 0303 health sciences, [SDV.MHEP] Life Sciences [q-bio]/Human health and pathology, Factors de risc en les malalties, Bulimia nervosa, Feeding and Eating Disorders/genetics, eating disorders, genetic correlation, substance use, Tobacco Use Disorder, 3. Good health, Fenotip, [SDV] Life Sciences [q-bio], Psychiatry and Mental health, Alcoholism, Eating disorders, Phenotype, Schizophrenia, Drinking of alcoholic beverages, eating disorder, Consum d'alcohol, Major depressive disorder, medicine.symptom, Depressive Disorder, Major/genetics, eating disorders, genetic correlation, substance use, Clinical psychology, Substance abuse, Risk factors in diseases, Substance-Related Disorders, Polymorphism, Single Nucleotide, Article, Feeding and Eating Disorders, 03 medical and health sciences, SDG 3 - Good Health and Well-being, mental disorders, Genetics, medicine, Humans, Trastorns de la conducta alimentària, 030304 developmental biology, Genetic association, Pharmacology, Depressive Disorder, Major, Binge eating, business.industry, [SCCO.NEUR]Cognitive science/Neuroscience, [SCCO.NEUR] Cognitive science/Neuroscience, [SCCO] Cognitive science, medicine.disease, Comorbidity, Twin study, 030227 psychiatry, Abús de substàncies, [SDV.MHEP.PSM]Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health, business, Genètica, 030217 neurology & neurosurgery, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology, Genome-Wide Association Study
Abstract: Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa (BN) and problem alcohol use (genetic correlation [rg], twin-based=0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge-eating, AN without binge-eating, and a BN factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder (MDD). Total sample sizes per phenotype ranged from ~2,400 to ~537,000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (rg=0.18; false discovery rate q=0.0006), cannabis initiation and AN (rg=0.23; qwith binge-eating (rg=0.27; q=0.0016). Conversely, significant negative genetic correlations were observed between three non-diagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge-eating (rgs=-0.19 to −0.23; qs
Published: 2021

50. Identification of autosomal cis expression quantitative trait methylation (cis eQTMs) in children’s blood

Author: Xavier Estivill, Eulàlia Martí, Johanna Lepeule, Dan Mason, Juan R. González, Marina Vafeiadi, Regina Grazuleviciene, Geòrgia Escaramís, Martine Vrijheid, Maribel Casas, Kristine B. Gutzkow, Angel Carracedo, John Wright, Sergi Mari, Sandra Andrusaityte, Inés Quintela, Solène Cadiou, Carlos Ruiz-Arenas, Mariona Bustamante, Leda Chatzi, Marta Vives-Usano, and Carles Hernandez-Ferrer
Subjects: Adult, European community, Sang, Biology, Quantitative trait locus, General Biochemistry, Genetics and Molecular Biology, Cohort Studies, Epigenome, Humans, media_common.cataloged_instance, European union, Genotyping, Gene, media_common, Genetic association, Genetics, General Immunology and Microbiology, General Neuroscience, General Medicine, Methylation, DNA Methylation, Expressió gènica, Europe, Phenotype, Metilació de l'ADN, Child, Preschool, DNA methylation, Infants, Genètica
Abstract: The identification of expression quantitative trait methylation (eQTMs), defined as associations between DNA methylation levels and gene expression, might help the biological interpretation of epigenome-wide association studies (EWAS). We aimed to identify autosomal cis eQTMs in children's blood, using data from 832 children of the Human Early Life Exposome (HELIX) project.Blood DNA methylation and gene expression were measured with the Illumina 450K and the Affymetrix HTA v2 arrays, respectively. The relationship between methylation levels and expression of nearby genes (1 Mb window centered at the transcription start site, TSS) was assessed by fitting 13.6 M linear regressions adjusting for sex, age, cohort, and blood cell composition.We identified 39,749 blood autosomal cis eQTMs, representing 21,966 unique CpGs (eCpGs, 5.7% of total CpGs) and 8,886 unique transcript clusters (eGenes, 15.3% of total transcript clusters, equivalent to genes). In 87.9% of these cis eQTMs, the eCpG was located at250 kb from eGene's TSS; and 58.8% of all eQTMs showed an inverse relationship between the methylation and expression levels. Only around half of the autosomal cis-eQTMs eGenes could be captured through annotation of the eCpG to the closest gene. eCpGs had less measurement error and were enriched for active blood regulatory regions and for CpGs reported to be associated with environmental exposures or phenotypic traits. In 40.4% of the eQTMs, the CpG and the eGene were both associated with at least one genetic variant. The overlap of autosomal cis eQTMs in children's blood with those described in adults was small (13.8%), and age-shared cis eQTMs tended to be proximal to the TSS and enriched for genetic variants.This catalogue of autosomal cis eQTMs in children's blood can help the biological interpretation of EWAS findings and is publicly available at https://helixomics.isglobal.org/ and at Dryad (doi:10.5061/dryad.fxpnvx0t0).The study has received funding from the European Community's Seventh Framework Programme (FP7/2007-206) under grant agreement no 308333 (HELIX project); the H2020-EU.3.1.2. - Preventing Disease Programme under grant agreement no 874583 (ATHLETE project); from the European Union's Horizon 2020 research and innovation programme under grant agreement no 733206 (LIFECYCLE project), and from the European Joint Programming Initiative "A Healthy Diet for a Healthy Life" (JPI HDHL and Instituto de Salud Carlos III) under the grant agreement no AC18/00006 (NutriPROGRAM project). The genotyping was supported by the projects PI17/01225 and PI17/01935, funded by the Instituto de Salud Carlos III and co-funded by European Union (ERDF, "A way to make Europe") and the Centro Nacional de Genotipado-CEGEN (PRB2-ISCIII). BiB received core infrastructure funding from the Wellcome Trust (WT101597MA) and a joint grant from the UK Medical Research Council (MRC) and Economic and Social Science Research Council (ESRC) (MR/N024397/1). INMA data collections were supported by grants from the Instituto de Salud Carlos III, CIBERESP, and the Generalitat de Catalunya-CIRIT. KANC was funded by the grant of the Lithuanian Agency for Science Innovation and Technology (6-04-2014_31V-66). The Norwegian Mother, Father and Child Cohort Study is supported by the Norwegian Ministry of Health and Care Services and the Ministry of Education and Research. The Rhea project was financially supported by European projects (EU FP6-2003-Food-3-NewGeneris, EU FP6. STREP Hiwate, EU FP7 ENV.2007.1.2.2.2. Project No 211250 Escape, EU FP7-2008-ENV-1.2.1.4 Envirogenomarkers, EU FP7-HEALTH-2009- single stage CHICOS, EU FP7 ENV.2008.1.2.1.6. Proposal No 226285 ENRIECO, EU- FP7- HEALTH-2012 Proposal No 308333 HELIX), and the Greek Ministry of Health (Program of Prevention of obesity and neurodevelopmental disorders in preschool children, in Heraklion district, Crete, Greece: 2011-2014; "Rhea Plus": Primary Prevention Program of Environmental Risk Factors for Reproductive Health, and Child Health: 2012-15). We acknowledge support from the Spanish Ministry of Science and Innovation through the "Centro de Excelencia Severo Ochoa 2019-2023" Program (CEX2018-000806-S), and support from the Generalitat de Catalunya through the CERCA Program. MV-U and CR-A were supported by a FI fellowship from the Catalan Government (FI-DGR 2015 and #016FI_B 00272). MC received funding from Instituto Carlos III (Ministry of Economy and Competitiveness) (CD12/00563 and MS16/00128).Cells can fine-tune which genes they activate, when and at which levels using a range of chemical marks on the DNA and certain proteins that help to organise the genome. One well-known example of such ‘epigenetic tags’ is DNA methylation, whereby a methyl group is added onto particular positions in the genome. Many factors – including environmental effects such as diet – control DNA methylation, allowing an organism to adapt to ever-changing conditions. An expression quantitative trait methylation (eQTM) is a specific position of the genome whose DNA methylation status regulates the activity of a given gene. A catalogue of eQTMs would be useful in helping to reveal how the environment and disease impacts the way cells work. Yet, currently, the relationships between most epigenetic tags and gene activity remains unclear, especially in children. To fill this gap, Ruiz-Arenas et al. studied DNA methylation in blood samples from over 800 healthy children across Europe. Amongst all tested DNA methylation sites, 22,000 (5.7% of total) were associated with the expression of a gene – and therefore were eQTMs; reciprocally, 9,000 genes (15.3% of all tested genes) were linked to at least one methylation site, leading to a total of 40,000 pairs of DNA methylation sites and genes. Most often, eQTMs regulated the expression of nearby genes – but only half controlled the gene that was the closest to them. Age and the genetic background of the individuals influenced the nature of eQTMs. This catalogue is a useful resource for the scientific community to start understanding the relationship between epigenetics and gene activity. Similar studies are now needed for other tissues and age ranges. Overall, extending our knowledge of eQTMs may help reveal how life events lead to illness, and could inform prevention efforts.
Published: 2020

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