Publications by authors named "Ángel Carracedo"

414 Publications

UTMOST, a single and cross-tissue TWAS (Transcriptome Wide Association Study), reveals new ASD (Autism Spectrum Disorder) associated genes.

Transl Psychiatry 2021 Apr 30;11(1):256. Epub 2021 Apr 30.

Grupo de Medicina Xenómica, Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidad de Santiago de Compostela, Santiago de Compostela, Spain.

Autism spectrum disorders (ASD) is a complex neurodevelopmental disorder that may significantly impact on the affected individual's life. Common variation (SNPs) could explain about 50% of ASD heritability. Despite this fact and the large size of the last GWAS meta-analysis, it is believed that hundreds of risk genes in ASD have yet to be discovered. New tools, such as TWAS (Transcriptome Wide Association Studies) which integrate tissue expression and genetic data, are a great approach to identify new ASD susceptibility genes. The main goal of this study is to use UTMOST with the publicly available summary statistics from the largest ASD GWAS meta-analysis as genetic input. In addition, an in silico biological characterization for the novel associated loci was performed. Our results have shown the association of 4 genes at the brain level (CIPC, PINX1, NKX2-2, and PTPRE) and have highlighted the association of NKX2-2, MANBA, ERI1, and MITF at the gastrointestinal level. The gastrointestinal associations are quite relevant given the well-established but unexplored relationship between ASD and gastrointestinal symptoms. Cross-tissue analysis has shown the association of NKX2-2 and BLK. UTMOST-associated genes together with their in silico biological characterization seems to point to different biological mechanisms underlying ASD etiology. Thus, it would not be restricted to brain tissue and it will involve the participation of other body tissues such as the gastrointestinal.
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http://dx.doi.org/10.1038/s41398-021-01378-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8087708PMC
April 2021

Genome-wide association study of stage III/IV grade C periodontitis (former aggressive periodontitis) in a Spanish population.

J Clin Periodontol 2021 Mar 21. Epub 2021 Mar 21.

Grupo de Investigación en Odontología Médico-Quirúrgica (OMEQUI), Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Universidade de Santiago de Compostela, Santiago de Compostela, Spain.

Aim: To identify loci associated with stages III/IV, grade C periodontitis (PIII/IV-C) through a genome-wide association study (GWAS).

Materials And Methods: 441 Caucasian Spanish PIII/IV-C cases from the SEPA Network of Research Clinics and 1141 controls from the Banco Nacional de ADN were genotyped with "Axiom Spain Biobank Array," which contains 757836 markers, including rare and low-frequency Spanish variants. The analysis of the individual association and subsequently the gene-level analysis with Sequence Kernel Association Test (SKAT) were carried out adjusting for age, sex and PC1 covariates. Pathway Analysis was additionally performed with Ingenuity Pathway Analysis (IPA) software on the top associated genes.

Results: In the individual analyses, no genome-wide significant signals were detected. However, 8 SNPs of 8 loci reached suggestive evidence of association with PIII/IV-C, including FAT3 rs35709256, CSNK1G2 rs4807188, MYH13 rs2074872, CNTN2 rs116611488, ANTXR1 rs4854545, 8p23.2 rs78672540, ANGPT1 rs13439823 and PLEC rs11993287 (p < 5 × 10 ). SKAT analysis identified other interesting signals at CNTN2, FBXO44, AP1M2, RSPO4, KRI1, BPIFB1 and INMT, although their probability does not exceed the multiple-test correction. IPA indicated significant enrichment of pathways related to cAMP, IL-2, CD28, VDR/RXR and PI3K/Akt.  CONCLUSIONS: GWAS found no SNPs significantly associated with PIII/IV-C.
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http://dx.doi.org/10.1111/jcpe.13460DOI Listing
March 2021

Examining the association between exposome score for schizophrenia and functioning in schizophrenia, siblings, and healthy controls: Results from the EUGEI study.

Eur Psychiatry 2021 Mar 19;64(1):e25. Epub 2021 Mar 19.

Biomedical Research Networking Centre in Mental Health (CIBERSAM), Barcelona, Spain.

Background: A cumulative environmental exposure score for schizophrenia (exposome score for schizophrenia [ES-SCZ]) may provide potential utility for risk stratification and outcome prediction. Here, we investigated whether ES-SCZ was associated with functioning in patients with schizophrenia spectrum disorder, unaffected siblings, and healthy controls.

Methods: This cross-sectional sample consisted of 1,261 patients, 1,282 unaffected siblings, and 1,525 healthy controls. The Global Assessment of Functioning (GAF) scale was used to assess functioning. ES-SCZ was calculated based on our previously validated method. The association between ES-SCZ and the GAF dimensions (symptom and disability) was analyzed by applying regression models in each group (patients, siblings, and controls). Additional models included polygenic risk score for schizophrenia (PRS-SCZ) as a covariate.

Results: ES-SCZ was associated with the GAF dimensions in patients (symptom: B = -1.53, p-value = 0.001; disability: B = -1.44, p-value = 0.001), siblings (symptom: B = -3.07, p-value < 0.001; disability: B = -2.52, p-value < 0.001), and healthy controls (symptom: B = -1.50, p-value < 0.001; disability: B = -1.31, p-value < 0.001). The results remained the same after adjusting for PRS-SCZ. The degree of associations of ES-SCZ with both symptom and disability dimensions were higher in unaffected siblings than in patients and controls. By analyzing an independent dataset (the Genetic Risk and Outcome of Psychosis study), we replicated the results observed in the patient group.

Conclusions: Our findings suggest that ES-SCZ shows promise for enhancing risk prediction and stratification in research practice. From a clinical perspective, ES-SCZ may aid in efforts of clinical characterization, operationalizing transdiagnostic clinical staging models, and personalizing clinical management.
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http://dx.doi.org/10.1192/j.eurpsy.2021.19DOI Listing
March 2021

Long runs of homozygosity are associated with Alzheimer's disease.

Transl Psychiatry 2021 Feb 24;11(1):142. Epub 2021 Feb 24.

Dep. of Surgery, Biochemistry and Molecular Biology, School of Medicine, University of Málaga, Málaga, Spain.

Long runs of homozygosity (ROH) are contiguous stretches of homozygous genotypes, which are a footprint of inbreeding and recessive inheritance. The presence of recessive loci is suggested for Alzheimer's disease (AD); however, their search has been poorly assessed to date. To investigate homozygosity in AD, here we performed a fine-scale ROH analysis using 10 independent cohorts of European ancestry (11,919 AD cases and 9181 controls.) We detected an increase of homozygosity in AD cases compared to controls [β (CI 95%) = 0.070 (0.037-0.104); P = 3.91 × 10; β (CI95%) = 0.043 (0.009-0.076); P = 0.013]. ROHs increasing the risk of AD (OR > 1) were significantly overrepresented compared to ROHs increasing protection (p < 2.20 × 10). A significant ROH association with AD risk was detected upstream the HS3ST1 locus (chr4:11,189,482‒11,305,456), (β (CI 95%) = 1.09 (0.48 ‒ 1.48), p value = 9.03 × 10), previously related to AD. Next, to search for recessive candidate variants in ROHs, we constructed a homozygosity map of inbred AD cases extracted from an outbred population and explored ROH regions in whole-exome sequencing data (N = 1449). We detected a candidate marker, rs117458494, mapped in the SPON1 locus, which has been previously associated with amyloid metabolism. Here, we provide a research framework to look for recessive variants in AD using outbred populations. Our results showed that AD cases have enriched homozygosity, suggesting that recessive effects may explain a proportion of AD heritability.
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http://dx.doi.org/10.1038/s41398-020-01145-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7904832PMC
February 2021

Forensic Science International: Genetics Reviewer Hall of Fame 2020.

Authors:
Angel Carracedo

Forensic Sci Int Genet 2021 May 4;52:102480. Epub 2021 Feb 4.

Genetics Institute of Forensic Sciences, University of Santiago de Compostela, Spain.

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http://dx.doi.org/10.1016/j.fsigen.2021.102480DOI Listing
May 2021

Association of variants in MYH7, MYBPC3 and TNNT2 with sudden cardiac death-related risk factors in Brazilian patients with hypertrophic cardiomyopathy.

Forensic Sci Int Genet 2021 May 3;52:102478. Epub 2021 Feb 3.

School of Pharmaceutical Sciences, University of Sao Paulo, Sao Paulo, Brazil. Electronic address:

Hypertrophic cardiomyopathy (HCM) is characterized by unexplained left ventricular hypertrophy (LVH) and is one of the major causes of sudden cardiac death (SCD). An exon-targeted gene sequencing strategy was used to investigate the association of functional variants in sarcomeric genes (MYBPC3, MYH7 and TNNT2) with severe LVH and other SCD-related risk factors in Brazilian HCM patients. Clinical data of 55 HCM patients attending a Cardiology Hospital (Sao Paulo city, Brazil) were recorded. Severe LVH, aborted SCD, family history of SCD, syncope, non-sustained ventricular tachycardia and abnormal blood pressure in response to exercise were evaluated as SCD risk factors. Blood samples were obtained for genomic DNA extraction and the exons and untranslated regions of the MYH7, MYBPC3 and TNNT2 were sequenced using Nextera® and MiSEq® reagents. Variants were identified and annotated using in silico tools, and further classified as pathogenic or benign according to the American College of Medical Genetics and Genomics guidelines. Variants with functional effects were identified in MYBPC3 (n = 9), MYH7 (n = 6) and TNNT2 (n = 4). The benign variants MYBPC3 p.Val158Met and TNNT2 p.Lys263Arg were associated with severe LVH (p < 0.05), and the MYH7 p.Val320Met (pathogenic) was associated with family history of SCD (p = 0.037). Increased risk for severe LVH was found in carriers of MYBPC3 Met158 (c.472 A allele, OR = 13.5, 95% CI = 1.80-101.12, p = 0.011) or combined variants (MYBPC3, MYH7 and TNNT2: OR = 12.39, 95% CI = 2.14-60.39, p = 0.004). Carriers of TNNT2 p.Lys263Arg and combined variants had higher values of septum thickness than non-carriers (p < 0.05). Molecular modeling analysis showed that MYBPC3 158Met reduces the interaction of cardiac myosin-binding protein C (cMyBP-C) RASK domain (amino acids Arg215-Ala216-Ser217-Lys218) with tropomyosin. In conclusion, the variants MYBPC3 p.Val158Met, TNNT2 p.Lys263Arg and MYH7 p.Val320Met individually or combined contribute to the risk of sudden cardiac death and other outcomes of hypertrophic cardiomyopathy.
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http://dx.doi.org/10.1016/j.fsigen.2021.102478DOI Listing
May 2021

Genetic Diversity of Drug-Related Genes in Native Americans of the Brazilian Amazon.

Pharmgenomics Pers Med 2021 22;14:117-133. Epub 2021 Jan 22.

Núcleo de Pesquisas em Oncologia, Universidade Federal do Pará, Belém, Pará, Brazil.

Introduction: The genetic admixture of the Brazilian population has considerable relevance to the implementation of the principles of pharmacogenomics (PGx), as it may compromise the extrapolation of data obtained in more homogeneous world populations.

Purpose: This study aims to investigate a panel of 117 polymorphisms in 35 pharmacogenes, which contains label recommendations or clinical evidence by international drug regulatory agencies, in Amazonian Native American populations, and compare the results obtained with continental population data from the 1000 Genomes Project Consortium.

Patients And Methods: The study population is composed of 109 Native American individuals from three Brazilian Amazon groups. The genotyping of the PGx polymorphisms was performed by allelic discrimination using TaqMan OpenArray Genotyping with a panel of 120 customized assays on the QuantStudio™ 12K Flex Real-Time PCR System.

Results: Statistical differences within the Native American populations were observed regarding both genotypes and phenotypes of some genes of the CYP family. The discriminant analysis of principal components (DAPCs) between the NAM group and the continental populations of the 1000 Genomes Project resulted in the clustering of the three Native American populations. Additionally, in general, the NAM group was determined to be closely situated between East Asia, America, and South Asia groups, which enabled us to infer a genetic similarity between these populations. The DAPC analysis further demonstrated that eight polymorphisms and six polymorphisms were more relevant in differentiating the NAM from the continental populations and the NAM populations among themselves, respectively.

Conclusion: Some investigated polymorphisms show differences among world populations, particularly with populations of European origin, for whom precision medicine protocols are primarily designed. The accumulated knowledge regarding these variations may assist in the design of specific protocols for Native American populations and populations admixed with them.
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http://dx.doi.org/10.2147/PGPM.S274741DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7837547PMC
January 2021

Tumor Profiling at the Service of Cancer Therapy.

Front Oncol 2020 11;10:595613. Epub 2021 Jan 11.

Grupo de Medicina Xenómica (USC), Instituto de Investigación Sanitaria de Santiago (IDIS), Santiago de Compostela, Spain.

Cancer treatment options have evolved significantly in the past few years. From the initial surgical procedures, to the latest next-generation technologies, we are now in the position to analyze and understand tumors in a one-by-one basis and use that to our advantage to provide with individualized treatment options that may increase patient survival. In this review, we will focus on how tumor profiling has evolved over the past decades to deliver more efficient and personalized treatment options, and how novel technologies can help us envisage the future of precision oncology toward a better management and, ultimately, increased survival.
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http://dx.doi.org/10.3389/fonc.2020.595613DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7832432PMC
January 2021

Breast Cancer Risk Genes - Association Analysis in More than 113,000 Women.

N Engl J Med 2021 02 20;384(5):428-439. Epub 2021 Jan 20.

The authors' affiliations are as follows: the Centre for Cancer Genetic Epidemiology, Departments of Public Health and Primary Care (L.D., S. Carvalho, J.A., K.A.P., Q.W., M.K.B., J.D., B.D., N. Mavaddat, K. Michailidou, A.C.A., P.D.P.P., D.F.E.) and Oncology (C.L., P.A.H., C. Baynes, D.M.C., L.F., V.R., M. Shah, P.D.P.P., A.M.D., D.F.E.), University of Cambridge, Cambridge, the Centre for Genomic and Experimental Medicine, MRC Institute of Genetics and Molecular Medicine (A. Campbell, D.J.P.), and the Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology (D.J.P.), University of Edinburgh, the Cancer Research UK Edinburgh Centre (D.A.C., J.F.), and the Usher Institute of Population Health Sciences and Informatics, University of Edinburgh Medical School (A. Campbell, J.F.), Edinburgh, the Divisions of Informatics, Imaging, and Data Sciences (E.F.H.), Cancer Sciences (A. Howell), Population Health, Health Services Research, and Primary Care (A. Lophatananon, K. Muir), and Evolution and Genomic Sciences, School of Biological Sciences (W.G.N., E.M.V., D.G.E.), University of Manchester, the NIHR Manchester Biomedical Research Unit (E.F.H.) and the Nightingale Breast Screening Centre, Wythenshawe Hospital (E.F.H., H.I.), Academic Health Science Centre and North West Genomics Laboratory Hub, and the Manchester Centre for Genomic Medicine, St. Mary's Hospital, Manchester University NHS Foundation Trust (W.G.N., E.M.V., D.G.E.), Manchester, the School of Cancer and Pharmaceutical Sciences, Comprehensive Cancer Centre, Guy's Campus, King's College London, London (E.J.S.), the Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham (I.T.), and the Wellcome Trust Centre for Human Genetics and Oxford NIHR Biomedical Research Centre, University of Oxford, Oxford (I.T.) - all in the United Kingdom; the Human Genotyping-CEGEN Unit, Human Cancer Genetic Program (A.G.-N., M.R.A., N.Á., B.H., R.N.-T.), and the Human Genetics Group (V.F., A.O., J.B.), Spanish National Cancer Research Center, Centro de Investigación en Red de Enfermedades Raras (A.O., J.B.), Servicio de Oncología Médica, Hospital Universitario La Paz (M.P.Z.), and Molecular Oncology Laboratory, Hospital Clinico San Carlos, Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (M. de la Hoya), Madrid, the Genomic Medicine Group, Galician Foundation of Genomic Medicine, Instituto de Investigación Sanitaria de Santiago de Compostela, Complejo Hospitalario Universitario de Santiago (A. Carracedo, M.G.-D.), and Centro de Investigación en Red de Enfermedades Raras y Centro Nacional de Genotipado, Universidad de Santiago de Compostela (A. Carracedo), Santiago de Compostela, the Oncology and Genetics Unit, Instituto de Investigacion Sanitaria Galicia Sur, Xerencia de Xestion Integrada de Vigo-Servizo Galeo de Saúde, Vigo (J.E.C.), and Servicio de Cirugía General y Especialidades, Hospital Monte Naranco, Oviedo (J.I.A.P.) - all in Spain; the Division of Oncology and Pathology, Department of Clinical Sciences Lund, Lund University, Lund (C. Wahlström, J.V., M.L., T. Törngren, Å.B., A.K.), the Department of Oncology, Örebro University Hospital, Örebro (C. Blomqvist), and the Departments of Medical Epidemiology and Biostatistics (K.C., M.E., M.G., P. Hall, W.H., K.H.), Oncology, Södersjukhuset (P. Hall, S. Margolin), Molecular Medicine and Surgery (A. Lindblom), and Clinical Science and Education, Södersjukhuset (S. Margolin, C. Wendt), Karolinska Institutet, and the Department of Clinical Genetics, Karolinska University Hospital (A. Lindblom), Stockholm - all in Sweden; the Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD (M.T.P., C.F., G.C.-T., A.B.S.), the Cancer Epidemiology Division, Cancer Council Victoria (G.G.G., R.J.M., R.L.M.), the Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health (G.G.G., R.J.M., R.L.M.), and the Department of Clinical Pathology (M.C.S.), University of Melbourne, Anatomical Pathology, Alfred Hospital (C.M.), and the Cancer Epidemiology Division, Cancer Council Victoria (M.C.S.), Melbourne, VIC, and Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC (G.G.G., M.C.S., R.L.M.) - all in Australia; the Division of Molecular Pathology (R.K., S. Cornelissen, M.K.S.), Family Cancer Clinic (F.B.L.H., L.E.K.), Department of Epidemiology (M.A.R.), and Division of Psychosocial Research and Epidemiology (M.K.S.), the Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Amsterdam, Division Laboratories, Pharmacy and Biomedical Genetics, Department of Genetics, University Medical Center, Utrecht (M.G.E.M.A.), the Department of Clinical Genetics, Erasmus University Medical Center (J.M.C., A.M.W.O.), and the Department of Medical Oncology, Family Cancer Clinic, Erasmus MC Cancer Institute (B.A.M.H.-G., A. Hollestelle, M.J.H.), Rotterdam, the Department of Clinical Genetics, Maastricht University Medical Center, Maastricht (E.B.G.G.), the Departments of Human Genetics (I.M.M.L., M.P.G.V., P.D.), Clinical Genetics (C.J.A.), and Pathology (P.D.), Leiden University Medical Center, Leiden, the Department of Human Genetics, Radboud University Medical Center, Nijmegen (A.R.M.), and the Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen (J.C.O.) - all in the Netherlands; the Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute (B.D.), and the Division of Cancer Epidemiology and Genetics, National Cancer Institute (T.A., S.J.C., X.R.Y., M.G.-C.), National Institutes of Health, Bethesda, MD; the Department of Pathology, Brigham and Women's Hospital, Harvard Medical School (B.D.), and the Department of Nutrition, Harvard T.H. Chan School of Public Health (R.M.V.D.), Boston; the Departments of Clinical Genetics (K.A.), Oncology (C. Blomqvist), and Obstetrics and Gynecology (H.N., M. Suvanto), Helsinki University Hospital, University of Helsinki, Helsinki, and the Unit of Clinical Oncology, Kuopio University Hospital (P. Auvinen), the Institute of Clinical Medicine, Oncology (P. Auvinen), the Translational Cancer Research Area (J.M.H., V.-M.K., A. Mannermaa), and the Institute of Clinical Medicine, Pathology, and Forensic Medicine (J.M.H., V.-M.K., A. Mannermaa), University of Eastern Finland, and the Biobank of Eastern Finland, Kuopio University Hospital (V.-M.K., A. Mannermaa), Kuopio - both in Finland; the N.N. Alexandrov Research Institute of Oncology and Medical Radiology, Minsk, Belarus (N.N.A., N.V.B.); the Department of Gynecology and Obstetrics and Institute of Clinical Molecular Biology, University Hospital of Schleswig-Holstein, Campus Kiel, Christian-Albrechts University Kiel, Kiel (N.A.), the Institute of Medical Biometry and Epidemiology (H. Becher) and Cancer Epidemiology Group (T.M., J.C.-C.), University Cancer Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, the Department of Gynecology and Obstetrics (M.W.B., P.A.F., L.H.) and Institute of Human Genetics (A.B.E.), University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-European Metropolitan Region of Nuremberg, Erlangen, the Division of Cancer Epidemiology (S.B., A. Jung, P.M.K., J.C.-C.), Molecular Epidemiology Group, C080 (B. Burwinkel, H.S.), Division of Pediatric Neurooncology (A.F.), and Molecular Genetics of Breast Cancer (U.H., M.M., M.U.R., D.T.), German Cancer Research Center, Molecular Biology of Breast Cancer, University Women's Clinic Heidelberg, University of Heidelberg (B. Burwinkel, A.S., H.S.), Hopp Children's Cancer Center (A.F.), Faculty of Medicine, University of Heidelberg (P.M.K.), and National Center for Tumor Diseases, University Hospital and German Cancer Research Center (A.S., C.S.), Heidelberg, the Department of Radiation Oncology (N.V.B., M. Bremer, H.C.) and the Gynecology Research Unit (N.V.B., T.D., P. Hillemanns, T.-W.P.-S., P.S.), Hannover Medical School, Hannover, the Institute of Human Genetics, University of Münster, Münster (N.B.-M.), Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart (H. Brauch, W.-Y.L.), iFIT-Cluster of Excellence, University of Tübingen, and the German Cancer Consortium, German Cancer Research Center, Partner Site Tübingen (H. Brauch), and the University of Tübingen (W.-Y.L.), Tübingen, Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum, Bochum (T.B.), Institute for Medical Informatics, Statistics, and Epidemiology, University of Leipzig, Leipzig (C.E.), Center for Hereditary Breast and Ovarian Cancer (E.H., R.K.S.) and Center for Integrated Oncology (E.H., R.K.S.), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, the Department of Internal Medicine, Evangelische Kliniken Bonn, Johanniter Krankenhaus, Bonn (Y.-D.K.), the Department of Gynecology and Obstetrics, University of Munich, Campus Großhadern, Munich (A. Meindl), and the Institute of Pathology, Städtisches Klinikum Karlsruhe, Karlsruhe (T.R.) - all in Germany; the Gynecological Cancer Registry, Centre Georges-François Leclerc, Dijon (P. Arveux), and the Center for Research in Epidemiology and Population Health, Team Exposome and Heredity, INSERM, University Paris-Saclay, Villejuif (E.C.-D., P.G., T. Truong) - both in France; the Institute of Biochemistry and Genetics, Ufa Federal Research Center of the Russian Academy of Sciences (M. Bermisheva, E.K.), the Department of Genetics and Fundamental Medicine, Bashkir State University (E.K., D.P., Y.V.), and the Ufa Research Institute of Occupational Health and Human Ecology (Y.V.), Ufa, Russia; the Department of Genetics and Pathology (K.B., A. Jakubowska, J. Lubiński, K.P.) and the Independent Laboratory of Molecular Biology and Genetic Diagnostics (A. Jakubowska), Pomeranian Medical University, Szczecin, Poland; the Copenhagen General Population Study, the Department of Clinical Biochemistry (S.E.B., B.G.N.), and the Department of Breast Surgery (H.F.), Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, and the Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen (S.E.B., B.G.N.) - both in Denmark; the Division of Cancer Prevention and Genetics, European Institute of Oncology Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) (B. Bonanni), the Unit of Medical Genetics, Department of Medical Oncology and Hematology, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano (S. Manoukian), the Genome Diagnostics Program, FIRC Institute of Molecular Oncology (P.P.), and the Unit of Molecular Bases of Genetic Risk and Genetic Testing, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori (P.R.), Milan; the Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital-Radiumhospitalet (A.-L.B.-D., G.I.G.A., V.N.K.), and the Institute of Clinical Medicine, Faculty of Medicine, University of Oslo (A.-L.B.-D., V.N.K.), Oslo; Medical Faculty, Universidad de La Sabana (I.B.), and the Clinical Epidemiology and Biostatistics Department (F.G.) and Institute of Human Genetics (D.T.), Pontificia Universidad Javeriana, Bogota, Colombia; the Department of Internal Medicine and Huntsman Cancer Institute, University of Utah (N.J.C., M.J.M., J.A.W.), and the Intermountain Healthcare Biorepository and Department of Pathology, Intermountain Healthcare (M.H.C.), Salt Lake City; the David Geffen School of Medicine, Department of Medicine Division of Hematology and Oncology, University of California, Los Angeles (P.A.F.), and Moores Cancer Center (M.G.-D., M.E.M.) and the Department of Family Medicine and Public Health (M.E.M.), University of California San Diego, La Jolla; the Departments of Medical Oncology (V.G., D.M.) and Pathology (M.T.), University Hospital of Heraklion, Heraklion, and the Department of Oncology, University Hospital of Larissa, Larissa (E.S.) - both in Greece; the Fred A. Litwin Center for Cancer Genetics, Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital (G.G., I.L.A.), the Departments of Laboratory Medicine and Pathobiology (A.M.M.) and Molecular Genetics (I.L.A.), University of Toronto, and the Laboratory Medicine Program, University Health Network (A.M.M.), Toronto, and the Genomics Center, Centre Hospitalier Universitaire de Québec-Université Laval Research Center, Québec City, QC (J.S.) - both in Canada; the Department of Electron Microscopy and Molecular Pathology (A. Hadjisavvas, K.K., M.A.L.), the Cyprus School of Molecular Medicine (A. Hadjisavvas, K.K., M.A.L., K. Michailidou), and the Biostatistics Unit (K. Michailidou), Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus; the Saw Swee Hock School of Public Health (M. Hartman, R.M.V.D.) and the Department of Medicine, Yong Loo Lin School of Medicine (R.M.V.D.), National University of Singapore, the Department of Surgery, National University Health System (M. Hartman, J. Li), and the Human Genetics Division, Genome Institute of Singapore (J. Li), Singapore; the Department of Mathematical Sciences, Faculty of Science and Engineering, University of Nottingham Malaysia (W.K.H.), and the Breast Cancer Research Programme, Cancer Research Malaysia (W.K.H., P.S.N., S.-Y.Y., S.H.T.), Selangor, and the Breast Cancer Research Unit, Cancer Research Institute (N.A.M.T.), and the Department of Surgery, Faculty of Medicine (N.A.M.T., P.S.N., S.H.T.), University Malaya, Kuala Lumpur - both in Malaysia; Surgery, School of Medicine, National University of Ireland, Galway (M.J.K., N. Miller); the Department of Surgery, Daerim Saint Mary's Hospital (S.-W.K.), the Department of Surgery, Ulsan University College of Medicine and Asan Medical Center (J.W.L.), the Department of Surgery, Soonchunhyang University College of Medicine and Soonchunhyang University Hospital (M.H.L.), Integrated Major in Innovative Medical Science, Seoul National University College of Medicine (S.K.P.), and the Cancer Research Institute, Seoul National University (S.K.P.), Seoul, South Korea; the Department of Basic Sciences, Shaukat Khanum Memorial Cancer Hospital and Research Center, Lahore, Pakistan (M.U.R.); and the National Cancer Institute, Ministry of Public Health, Nonthaburi, Thailand (S.T.).

Background: Genetic testing for breast cancer susceptibility is widely used, but for many genes, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are lacking.

Methods: We used a panel of 34 putative susceptibility genes to perform sequencing on samples from 60,466 women with breast cancer and 53,461 controls. In separate analyses for protein-truncating variants and rare missense variants in these genes, we estimated odds ratios for breast cancer overall and tumor subtypes. We evaluated missense-variant associations according to domain and classification of pathogenicity.

Results: Protein-truncating variants in 5 genes (, , , , and ) were associated with a risk of breast cancer overall with a P value of less than 0.0001. Protein-truncating variants in 4 other genes (, , , and ) were associated with a risk of breast cancer overall with a P value of less than 0.05 and a Bayesian false-discovery probability of less than 0.05. For protein-truncating variants in 19 of the remaining 25 genes, the upper limit of the 95% confidence interval of the odds ratio for breast cancer overall was less than 2.0. For protein-truncating variants in and , odds ratios were higher for estrogen receptor (ER)-positive disease than for ER-negative disease; for protein-truncating variants in , , , , , and , odds ratios were higher for ER-negative disease than for ER-positive disease. Rare missense variants (in aggregate) in , , and were associated with a risk of breast cancer overall with a P value of less than 0.001. For , , and , missense variants (in aggregate) that would be classified as pathogenic according to standard criteria were associated with a risk of breast cancer overall, with the risk being similar to that of protein-truncating variants.

Conclusions: The results of this study define the genes that are most clinically useful for inclusion on panels for the prediction of breast cancer risk, as well as provide estimates of the risks associated with protein-truncating variants, to guide genetic counseling. (Funded by European Union Horizon 2020 programs and others.).
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http://dx.doi.org/10.1056/NEJMoa1913948DOI Listing
February 2021

Cognitive functioning throughout adulthood and illness stages in individuals with psychotic disorders and their unaffected siblings.

Mol Psychiatry 2021 Jan 7. Epub 2021 Jan 7.

Department of Psychiatry, Dokuz Eylül University, School of Medicine, Izmir, Turkey.

Important questions remain about the profile of cognitive impairment in psychotic disorders across adulthood and illness stages. The age-associated profile of familial impairments also remains unclear, as well as the effect of factors, such as symptoms, functioning, and medication. Using cross-sectional data from the EU-GEI and GROUP studies, comprising 8455 participants aged 18 to 65, we examined cognitive functioning across adulthood in patients with psychotic disorders (n = 2883), and their unaffected siblings (n = 2271), compared to controls (n = 3301). An abbreviated WAIS-III measured verbal knowledge, working memory, visuospatial processing, processing speed, and IQ. Patients showed medium to large deficits across all functions (ES range = -0.45 to -0.73, p < 0.001), while siblings showed small deficits on IQ, verbal knowledge, and working memory (ES = -0.14 to -0.33, p < 0.001). Magnitude of impairment was not associated with participant age, such that the size of impairment in older and younger patients did not significantly differ. However, first-episode patients performed worse than prodromal patients (ES range = -0.88 to -0.60, p < 0.001). Adjusting for cannabis use, symptom severity, and global functioning attenuated impairments in siblings, while deficits in patients remained statistically significant, albeit reduced by half (ES range = -0.13 to -0.38, p < 0.01). Antipsychotic medication also accounted for around half of the impairment in patients (ES range = -0.21 to -0.43, p < 0.01). Deficits in verbal knowledge, and working memory may specifically index familial, i.e., shared genetic and/or shared environmental, liability for psychotic disorders. Nevertheless, potentially modifiable illness-related factors account for a significant portion of the cognitive impairment in psychotic disorders.
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http://dx.doi.org/10.1038/s41380-020-00969-zDOI Listing
January 2021

Differential admixture in Latin American populations and its impact on the study of colorectal cancer.

Genet Mol Biol 2020 13;43(4):e20200143. Epub 2020 Nov 13.

Universidad de la República, Facultad de Humanidades y Ciencias de la Educación, Departamento de Antropología Biológica, Montevideo, Uruguay.

Genome-wide association studies focused on searching genes responsible for several diseases. Admixture mapping studies proposed a more efficient alternative capable of detecting polymorphisms contributing with a small effect on the disease risk. This method focuses on the higher values of linkage disequilibrium in admixed populations. To test this, we analyzed 10 genomic regions previously defined as related with colorectal cancer among nine populations and studied the variation pattern of haplotypic structures and heterozygosity values on seven categories of SNPs. Both analyses showed differences among chromosomal regions and studied populations. Admixed Latin-American samples generally show intermediate values. Heterozygosity of the SNPs grouped in categories varies more in each gene than in each population. African related populations have more blocks per chromosomal region, coherently with their antiquity. In sum, some similarities were found among Latin American populations, but each chromosomal region showed a particular behavior, despite the fact that the study refers to genes and regions related with one particular complex disease. This study strongly suggests the necessity of developing statistical methods to deal with di- or tri-hybrid populations, as well as to carefully analyze the different historic and demographic scenarios, and the different characteristics of particular chromosomal regions and evolutionary forces.
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http://dx.doi.org/10.1590/1678-4685-GMB-2020-0143DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7783724PMC
November 2020

Overlapping variants in the blood, tissues and cell lines for patients with intracranial meningiomas are predominant in stem cell-related genes.

Heliyon 2020 Nov 30;6(11):e05632. Epub 2020 Nov 30.

Neurooncology Translational Group, King Fahd Medical Research Center, Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences, King Abdulaziz University, P.O. Box 80216, Jeddah, 21589, Saudi Arabia.

Objective: Bulk tissue genomic analysis of meningiomas identified common somatic mutations, however, it often excluded blood-related variants. In contrast, genomic characterisation of primary cell lines that can provide critical information regarding growth and proliferation, have been rare. In our work, we identified the variants that are present in the blood, tissues and corresponding cell lines that are likely to be predictive, tumorigenic and progressive.

Method: Whole-exome sequencing was used to identify variants and distinguish related pathways that exist in 42 blood, tissues and corresponding cell lines (BTCs) samples for patients with intracranial meningiomas. Conventional sequencing was used for the confirmation of variants. Integrative analysis of the gene expression for the corresponding samples was utilised for further interpretations.

Results: In total, 926 BTC variants were detected, implicating 845 genes. A pathway analysis of all BTC genes with damaging variants indicated the 'cell morphogenesis involved in differentiation' stem cell-related pathway to be the most frequently affected pathway. Concordantly, five stem cell-related genes, , , , and , showed BTC variants in at least five of the patients. Variants that were heterozygous in the blood and homozygous in the tissues or the corresponding cell lines were rare (average: 1.3 ± 0.3%), and included variants in the and genes An analysis comparing the variants detected only in tumours with aggressive features indicated a total of 240 BTC genes, implicating the 'homophilic cell adhesion via plasma membrane adhesion molecules' pathway, and identifying the stem cell-related transcription coactivator as the most frequent BTC gene. Further analysis of the possible impact of the poly-Q mutation present in the gene indicated associated deregulation of 15 genes, including the up-regulation of the stem cell related gene and the angiogenesis related gene

Conclusion: Stem cell-related pathways and genes showed high prevalence in the BTC variants, and novel variants in stem cell-related genes were identified for meningioma. These variants can potentially be used as predictive, tumorigenic and progressive biomarkers for meningioma.
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http://dx.doi.org/10.1016/j.heliyon.2020.e05632DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7710648PMC
November 2020

Experimental Models to Study Autism Spectrum Disorders: hiPSCs, Rodents and Zebrafish.

Genes (Basel) 2020 Nov 20;11(11). Epub 2020 Nov 20.

Department of Zoology, Genetics and Physical Anthropology, Universidade de Santiago de Compostela, Campus de Lugo, 27002 Lugo, Spain.

Autism Spectrum Disorders (ASD) affect around 1.5% of the global population, which manifest alterations in communication and socialization, as well as repetitive behaviors or restricted interests. ASD is a complex disorder with known environmental and genetic contributors; however, ASD etiology is far from being clear. In the past decades, many efforts have been put into developing new models to study ASD, both in vitro and in vivo. These models have a lot of potential to help to validate some of the previously associated risk factors to the development of the disorder, and to test new potential therapies that help to alleviate ASD symptoms. The present review is focused on the recent advances towards the generation of models for the study of ASD, which would be a useful tool to decipher the bases of the disorder, as well as to conduct drug screenings that hopefully lead to the identification of useful compounds to help patients deal with the symptoms of ASD.
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http://dx.doi.org/10.3390/genes11111376DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7699923PMC
November 2020

The Road so Far in Colorectal Cancer Pharmacogenomics: Are We Closer to Individualised Treatment?

J Pers Med 2020 Nov 19;10(4). Epub 2020 Nov 19.

Grupo de Medicina Xenómica, Universidade de Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain.

In recent decades, survival rates in colorectal cancer have improved greatly due to pharmacological treatment. However, many patients end up developing adverse drug reactions that can be severe or even life threatening, and that affect their quality of life. These remain a limitation, as they may force dose reduction or treatment discontinuation, diminishing treatment efficacy. From candidate gene approaches to genome-wide analysis, pharmacogenomic knowledge has advanced greatly, yet there is still huge and unexploited potential in the use of novel technologies such as next-generation sequencing strategies. This review summarises the road of colorectal cancer pharmacogenomics so far, presents considerations and directions to be taken for further works and discusses the path towards implementation into clinical practice.
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http://dx.doi.org/10.3390/jpm10040237DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7711884PMC
November 2020

Author Correction: Neutrophil to lymphocyte ratio and breast cancer risk: analysis by subtype and potential interactions.

Sci Rep 2020 Nov 20;10(1):20641. Epub 2020 Nov 20.

Oncology and Genetics Unit, Instituto de Investigación Sanitaria Galicia Sur, Vigo, Spain.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.
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http://dx.doi.org/10.1038/s41598-020-75458-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7680152PMC
November 2020

Broadening the Applicability of a Custom Multi-Platform Panel of Microhaplotypes: Bio-Geographical Ancestry Inference and Expanded Reference Data.

Front Genet 2020 20;11:581041. Epub 2020 Oct 20.

Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Santiago de Compostela, Spain.

The development of microhaplotype (MH) panels for massively parallel sequencing (MPS) platforms is gaining increasing relevance for forensic analysis. Here, we expand the applicability of a 102 autosomal and 11 X-chromosome panel of MHs, previously validated with both MiSeq and Ion S5 MPS platforms and designed for identification purposes. We have broadened reference population data for identification purposes, including data from 240 HGDP-CEPH individuals of native populations from North Africa, the Middle East, Oceania and America. Using the enhanced population data, the panel was evaluated as a marker set for bio-geographical ancestry (BGA) inference, providing a clear differentiation of the five main continental groups of Africa, Europe, East Asia, Native America, and Oceania. An informative degree of differentiation was also achieved for the population variation encompassing North Africa, Middle East, Europe, South Asia, and East Asia. In addition, we explored the potential for individual BGA inference from simple mixed DNA, by simulation of mixed profiles followed by deconvolution of mixture components.
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http://dx.doi.org/10.3389/fgene.2020.581041DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7606911PMC
October 2020

Association between DNA methylation and ADHD symptoms from birth to school age: a prospective meta-analysis.

Transl Psychiatry 2020 11 12;10(1):398. Epub 2020 Nov 12.

Clinical Child & Family Studies, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.

Attention-deficit and hyperactivity disorder (ADHD) is a common childhood disorder with a substantial genetic component. However, the extent to which epigenetic mechanisms play a role in the etiology of the disorder is unknown. We performed epigenome-wide association studies (EWAS) within the Pregnancy And Childhood Epigenetics (PACE) Consortium to identify DNA methylation sites associated with ADHD symptoms at two methylation assessment periods: birth and school age. We examined associations of both DNA methylation in cord blood with repeatedly assessed ADHD symptoms (age 4-15 years) in 2477 children from 5 cohorts and of DNA methylation at school age with concurrent ADHD symptoms (age 7-11 years) in 2374 children from 9 cohorts, with 3 cohorts participating at both timepoints. CpGs identified with nominal significance (p < 0.05) in either of the EWAS were correlated between timepoints (ρ = 0.30), suggesting overlap in associations; however, top signals were very different. At birth, we identified nine CpGs that predicted later ADHD symptoms (p < 1 × 10), including ERC2 and CREB5. Peripheral blood DNA methylation at one of these CpGs (cg01271805 in the promoter region of ERC2, which regulates neurotransmitter release) was previously associated with brain methylation. Another (cg25520701) lies within the gene body of CREB5, which previously was associated with neurite outgrowth and an ADHD diagnosis. In contrast, at school age, no CpGs were associated with ADHD with p < 1 × 10. In conclusion, we found evidence in this study that DNA methylation at birth is associated with ADHD. Future studies are needed to confirm the utility of methylation variation as biomarker and its involvement in causal pathways.
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http://dx.doi.org/10.1038/s41398-020-01058-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7665047PMC
November 2020

Evidence, and replication thereof, that molecular-genetic and environmental risks for psychosis impact through an affective pathway.

Psychol Med 2020 Oct 19:1-13. Epub 2020 Oct 19.

Biomedical Research Networking Centre in Mental Health (CIBERSAM), Spain.

Background: There is evidence that environmental and genetic risk factors for schizophrenia spectrum disorders are transdiagnostic and mediated in part through a generic pathway of affective dysregulation.

Methods: We analysed to what degree the impact of schizophrenia polygenic risk (PRS-SZ) and childhood adversity (CA) on psychosis outcomes was contingent on co-presence of affective dysregulation, defined as significant depressive symptoms, in (i) NEMESIS-2 (n = 6646), a representative general population sample, interviewed four times over nine years and (ii) EUGEI (n = 4068) a sample of patients with schizophrenia spectrum disorder, the siblings of these patients and controls.

Results: The impact of PRS-SZ on psychosis showed significant dependence on co-presence of affective dysregulation in NEMESIS-2 [relative excess risk due to interaction (RERI): 1.01, p = 0.037] and in EUGEI (RERI = 3.39, p = 0.048). This was particularly evident for delusional ideation (NEMESIS-2: RERI = 1.74, p = 0.003; EUGEI: RERI = 4.16, p = 0.019) and not for hallucinatory experiences (NEMESIS-2: RERI = 0.65, p = 0.284; EUGEI: -0.37, p = 0.547). A similar and stronger pattern of results was evident for CA (RERI delusions and hallucinations: NEMESIS-2: 3.02, p < 0.001; EUGEI: 6.44, p < 0.001; RERI delusional ideation: NEMESIS-2: 3.79, p < 0.001; EUGEI: 5.43, p = 0.001; RERI hallucinatory experiences: NEMESIS-2: 2.46, p < 0.001; EUGEI: 0.54, p = 0.465).

Conclusions: The results, and internal replication, suggest that the effects of known genetic and non-genetic risk factors for psychosis are mediated in part through an affective pathway, from which early states of delusional meaning may arise.
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http://dx.doi.org/10.1017/S0033291720003748DOI Listing
October 2020

A replication study of JTC bias, genetic liability for psychosis and delusional ideation.

Psychol Med 2020 Oct 13:1-7. Epub 2020 Oct 13.

Biomedical Research Networking Centre in Mental Health (CIBERSAM), Spain.

Background: This study attempted to replicate whether a bias in probabilistic reasoning, or 'jumping to conclusions'(JTC) bias is associated with being a sibling of a patient with schizophrenia spectrum disorder; and if so, whether this association is contingent on subthreshold delusional ideation.

Methods: Data were derived from the EUGEI project, a 25-centre, 15-country effort to study psychosis spectrum disorder. The current analyses included 1261 patients with schizophrenia spectrum disorder, 1282 siblings of patients and 1525 healthy comparison subjects, recruited in Spain (five centres), Turkey (three centres) and Serbia (one centre). The beads task was used to assess JTC bias. Lifetime experience of delusional ideation and hallucinatory experiences was assessed using the Community Assessment of Psychic Experiences. General cognitive abilities were taken into account in the analyses.

Results: JTC bias was positively associated not only with patient status but also with sibling status [adjusted relative risk (aRR) ratio : 4.23 CI 95% 3.46-5.17 for siblings and aRR: 5.07 CI 95% 4.13-6.23 for patients]. The association between JTC bias and sibling status was stronger in those with higher levels of delusional ideation (aRR interaction in siblings: 3.77 CI 95% 1.67-8.51, and in patients: 2.15 CI 95% 0.94-4.92). The association between JTC bias and sibling status was not stronger in those with higher levels of hallucinatory experiences.

Conclusions: These findings replicate earlier findings that JTC bias is associated with familial liability for psychosis and that this is contingent on the degree of delusional ideation but not hallucinations.
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http://dx.doi.org/10.1017/S0033291720003578DOI Listing
October 2020

CSVS, a crowdsourcing database of the Spanish population genetic variability.

Nucleic Acids Res 2021 01;49(D1):D1130-D1137

Undiagnosed Rare Diseases Programme (ENoD). Center for Biomedical Research on Rare Diseases (CIBERER), ISCIII, Madrid 28029, Spain.

The knowledge of the genetic variability of the local population is of utmost importance in personalized medicine and has been revealed as a critical factor for the discovery of new disease variants. Here, we present the Collaborative Spanish Variability Server (CSVS), which currently contains more than 2000 genomes and exomes of unrelated Spanish individuals. This database has been generated in a collaborative crowdsourcing effort collecting sequencing data produced by local genomic projects and for other purposes. Sequences have been grouped by ICD10 upper categories. A web interface allows querying the database removing one or more ICD10 categories. In this way, aggregated counts of allele frequencies of the pseudo-control Spanish population can be obtained for diseases belonging to the category removed. Interestingly, in addition to pseudo-control studies, some population studies can be made, as, for example, prevalence of pharmacogenomic variants, etc. In addition, this genomic data has been used to define the first Spanish Genome Reference Panel (SGRP1.0) for imputation. This is the first local repository of variability entirely produced by a crowdsourcing effort and constitutes an example for future initiatives to characterize local variability worldwide. CSVS is also part of the GA4GH Beacon network. CSVS can be accessed at: http://csvs.babelomics.org/.
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http://dx.doi.org/10.1093/nar/gkaa794DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7778906PMC
January 2021

A Comparison of Forensic Age Prediction Models Using Data From Four DNA Methylation Technologies.

Front Genet 2020 19;11:932. Epub 2020 Aug 19.

Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Galicia, Spain.

Individual age estimation can be applied to criminal, legal, and anthropological investigations. DNA methylation has been established as the biomarker of choice for age prediction, since it was observed that specific CpG positions in the genome show systematic changes during an individual's lifetime, with progressive increases or decreases in methylation levels. Subsequently, several forensic age prediction models have been reported, providing average age prediction error ranges of ±3-4 years, using a broad spectrum of technologies and underlying statistical analyses. DNA methylation assessment is not categorical but quantitative. Therefore, the detection platform used plays a pivotal role, since quantitative and semi-quantitative technologies could potentially result in differences in detected DNA methylation levels. In the present study, we analyzed as a shared sample pool, 84 blood-based DNA controls ranging from 18 to 99 years old using four different technologies: EpiTYPER, pyrosequencing, MiSeq, and SNaPshot. The DNA methylation levels detected for CpG sites from , , and with each system were compared. A restricted three CpG-site age prediction model was rebuilt for each system, as well as for a combination of technologies, based on previous training datasets, and age predictions were calculated accordingly for all the samples detected with the previous technologies. While the DNA methylation patterns and subsequent age predictions from EpiTYPER, pyrosequencing, and MiSeq systems are largely comparable for the CpG sites studied, SNaPshot gives bigger differences reflected in higher predictive errors. However, these differences can be reduced by applying a z-score data transformation.
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http://dx.doi.org/10.3389/fgene.2020.00932DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7466768PMC
August 2020

Social Camouflaging in Females with Autism Spectrum Disorder: A Systematic Review.

J Autism Dev Disord 2020 Sep 14. Epub 2020 Sep 14.

Genomics and Bioinformatics Group, Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidade de Santiago de Compostela (USC), Avda. de Barcelona, s/n, 15782, Santiago de Compostela, Spain.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with increasing prevalence, and a male-to-female ratio of 4:1. Research has been suggesting that discrepancy in prevalence may be due to the fact that females camouflage their symptoms. In this study, we aimed to systematically review evidence on the camouflage effect in females with ASD. Following the PRISMA guidelines, we reviewed empirical research published from January 2009 to September 2019 on PubMed, Web of Science, PsychInfo and Scopus databases. Thirteen empirical articles were included in this review. Overall, evidence supports that camouflaging seems to be an adaptive mechanism for females with ASD, despite the negative implications of these behaviours in their daily life.
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http://dx.doi.org/10.1007/s10803-020-04695-xDOI Listing
September 2020

Executive Functioning: A Mediator Between Sensory Processing and Behaviour in Autism Spectrum Disorder.

J Autism Dev Disord 2020 Sep 11. Epub 2020 Sep 11.

Psychological Neuroscience Laboratory, Psychology Research Center (CIPsi), School of Psychology, University of Minho, Braga, Portugal.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by impairments in social interaction, executive functioning, sensory-perceptual abilities and behaviour, such as anxious/depressed states, attention problems, aggression, or somatic complains. However, the dynamic relationship between these dimensions remains to be addressed. Therefore, we explored the link between executive functions, sensory processing and behaviour in 79 children and adolescents with ASD. Results showed significant associations between all dimensions-executive functions, sensory processing and behaviour. Furthermore, using structural equation modelling methods, we observed a mediation effect of executive functioning, specifically the domain pertaining to emotion regulation and control, and in the relationship between sensory processing abnormalities and behavioural problems. We discuss the importance of emotion regulation as a mediator between sensory processing and behavioural impairments and its impact in social competence in ASD.
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http://dx.doi.org/10.1007/s10803-020-04648-4DOI Listing
September 2020

In utero and childhood exposure to tobacco smoke and multi-layer molecular signatures in children.

BMC Med 2020 08 19;18(1):243. Epub 2020 Aug 19.

ISGlobal, Barcelona, Spain.

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.
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http://dx.doi.org/10.1186/s12916-020-01686-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7437049PMC
August 2020

Neutrophil to lymphocyte ratio and breast cancer risk: analysis by subtype and potential interactions.

Sci Rep 2020 08 6;10(1):13203. Epub 2020 Aug 6.

Oncology and Genetics Unit, Instituto de Investigación Sanitaria Galicia Sur, Vigo, Spain.

Multiple studies have found the neutrophil to lymphocyte ratio (NLR) to be associated with adverse breast cancer (BC) prognosis and survival. Very limited data exist on the role of NLR and risk of BC. The BREOGAN study is a population-based case-control study conducted in Galicia, Spain. We examined the WBC- and NLR-BC relationships. The risk of BC increased with increasing levels of neutrophils percentage (NE%) (multivariable OR for the highest category (95% CI) = 2.14 (1.39-3.32), P-trend < 0.001) and of the NLR (multivariable OR for the highest category (95% CI) = 1.93 (1.26-2.97), P-trend < 0.001). Lymphocytes absolute (L#) and percentage (L%) were associated with a decreased risk of BC (multivariable OR for the highest category (95% CI) = 0.54 (0.35-0.83), and 0.51 (0.33-0.79), P-trend = 0.001 and < 0.001, respectively). The NLR-BC association was more pronounced among Luminal A BC (multivariable OR for the highest category (95% CI) = 2.00 (1.17-3.45), P-trend < 0.001), HER2-negative BC (multivariable OR for the highest category (95% CI) = 1.87 (1.16-3.02), P-trend < 0.001), and those with high total cholesterol and low HO levels.
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http://dx.doi.org/10.1038/s41598-020-70077-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7413522PMC
August 2020

On the suppression of Forensic Science International: Genetics from the 2019 Journal Citations Report.

Forensic Sci Int Genet 2020 09 28;48:102357. Epub 2020 Jul 28.

University of Munster, Institute of Legal Medicine, Germany. Electronic address:

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http://dx.doi.org/10.1016/j.fsigen.2020.102357DOI Listing
September 2020

Psychiatric comorbidities in Asperger syndrome are related with polygenic overlap and differ from other Autism subtypes.

Transl Psychiatry 2020 07 30;10(1):258. Epub 2020 Jul 30.

Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Centro de Investigación Biomédica en Red en Salud Mental (CIBERSAM), Facultad de Medicina, Universidad Complutense, Madrid, Spain.

There is great phenotypic heterogeneity within autism spectrum disorders (ASD), which has led to question their classification into a single diagnostic category. The study of the common genetic variation in ASD has suggested a greater contribution of other psychiatric conditions in Asperger syndrome (AS) than in the rest of the DSM-IV ASD subtypes (Non_AS). Here, using available genetic data from previously performed genome-wide association studies (GWAS), we aimed to study the genetic overlap between five of the most related disorders (schizophrenia (SCZ), major depression disorder (MDD), attention deficit hyperactivity disorder (ADHD), obsessive-compulsive disorders (OCD) and anxiety (ANX)), and AS, comparing it with the overlap in Non_AS subtypes. A Spanish cohort of autism trios (N = 371) was exome sequenced as part of the Autism Sequencing Consortium (ASC) and 241 trios were extensively characterized to be diagnosed with AS following DSM-IV and Gillberg's criteria (N = 39) or not (N = 202). Following exome imputation, polygenic risk scores (PRS) were calculated for ASD, SCZ, ADHD, MDD, ANX, and OCD (from available summary data from Psychiatric Genomic Consortium (PGC) repository) in the Spanish trios' cohort. By using polygenic transmission disequilibrium test (pTDT), we reported that risk for SCZ (P= 0.008, corrected-P = 0.0409), ADHD (P = 0.021, corrected-P = 0.0301), and MDD (P = 0.039, corrected-P = 0.0501) is over-transmitted to children with AS but not to Non_AS. Indeed, agnostic clustering procedure with deviation values from pTDT tests suggested two differentiated clusters of subjects, one of which is significantly enriched in AS (P = 0.025). Subsequent analysis with S-Predixcan, a recently developed software to predict gene expression from genotype data, revealed a clear pattern of correlation between cortical gene expression in ADHD and AS (P < 0.001) and a similar strong correlation pattern between MDD and AS, but also extendable to another non-brain tissue such as lung (P < 0.001). Altogether, these results support the idea of AS being qualitatively distinct from Non_AS autism and consistently evidence the genetic overlap between AS and ADHD, MDD, or SCZ.
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http://dx.doi.org/10.1038/s41398-020-00939-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7393162PMC
July 2020

Corrigendum to `Exploring Genetic Variants in Obsessive Compulsive Disorder Severity: A GWAS Approach.' Journal of Affective Disorders 267 (2020) 23-32.

J Affect Disord 2020 Sep 18;274:1222. Epub 2020 Jun 18.

OCD Clinical and Research Unit, Psychiatry Department, Hospital Universitari de Bellvitge, Barcelona, Spain; Department of Clinical Sciences, Bellvitge Campus, University of Barcelona, Barcelona, Spain; CIBERSAM (Centro de Investigación en Red de Salud Mental), Instituto de Salud Carlos III, Spain.

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http://dx.doi.org/10.1016/j.jad.2020.05.157DOI Listing
September 2020

Longitudinal analysis on parasite diversity in honeybee colonies: new taxa, high frequency of mixed infections and seasonal patterns of variation.

Sci Rep 2020 06 26;10(1):10454. Epub 2020 Jun 26.

Grupo de Medicina Xenómica, CIMUS, Universidade de Santiago de Compostela, 15782, Santiago de Compostela, Galicia, Spain.

To evaluate the influence that parasites have on the losses of Apis mellifera it is essential to monitor their presence in the colonies over time. Here we analysed the occurrence of nosematids, trypanosomatids and neogregarines in five homogeneous colonies for up to 21 months until they collapsed. The study, which combined the use of several molecular markers with the application of a massive parallel sequencing technology, provided valuable insights into the epidemiology of these parasites: (I) it enabled the detection of parasite species rarely reported in honeybees (Nosema thomsoni, Crithidia bombi, Crithidia acanthocephali) and the identification of two novel taxa; (II) it revealed the existence of a high rate of co-infections (80% of the samples harboured more than one parasite species); (III) it uncovered an identical pattern of seasonal variation for nosematids and trypanosomatids, that was different from that of neogregarines; (IV) it showed that there were no significant differences in the fraction of positive samples, nor in the levels of species diversity, between interior and exterior bees; and (V) it unveiled that the variation in the number of parasite species was not directly linked with the failure of the colonies.
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http://dx.doi.org/10.1038/s41598-020-67183-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7319982PMC
June 2020