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Giel AS, Bigge J, Schumacher J, Maj C, Dasmeh P. Analysis of Evolutionary Conservation, Expression Level, and Genetic Association at a Genome-wide Scale Reveals Heterogeneity Across Polygenic Phenotypes. Mol Biol Evol 2024; 41:msae115. [PMID: 38865495 PMCID: PMC11247350 DOI: 10.1093/molbev/msae115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 03/22/2024] [Accepted: 05/03/2024] [Indexed: 06/14/2024] Open
Abstract
Understanding the expression level and evolutionary rate of associated genes with human polygenic diseases provides crucial insights into their disease-contributing roles. In this work, we leveraged genome-wide association studies (GWASs) to investigate the relationship between the genetic association and both the evolutionary rate (dN/dS) and expression level of human genes associated with the two polygenic diseases of schizophrenia and coronary artery disease. Our findings highlight a distinct variation in these relationships between the two diseases. Genes associated with both diseases exhibit a significantly greater variance in evolutionary rate compared to those implicated in monogenic diseases. Expanding our analyses to 4,756 complex traits in the GWAS atlas database, we unraveled distinct trait categories with a unique interplay among the evolutionary rate, expression level, and genetic association of human genes. In most polygenic traits, highly expressed genes were more associated with the polygenic phenotypes compared to lowly expressed genes. About 69% of polygenic traits displayed a negative correlation between genetic association and evolutionary rate, while approximately 30% of these traits showed a positive correlation between genetic association and evolutionary rate. Our results demonstrate the presence of a spectrum among complex traits, shaped by natural selection. Notably, at opposite ends of this spectrum, we find metabolic traits being more likely influenced by purifying selection, and immunological traits that are more likely shaped by positive selection. We further established the polygenic evolution portal (evopolygen.de) as a resource for investigating relationships and generating hypotheses in the field of human polygenic trait evolution.
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Affiliation(s)
- Ann-Sophie Giel
- Centre for Human Genetics, Marburg University, Marburg, Germany
| | - Jessica Bigge
- Centre for Human Genetics, Marburg University, Marburg, Germany
| | | | - Carlo Maj
- Centre for Human Genetics, Marburg University, Marburg, Germany
| | - Pouria Dasmeh
- Centre for Human Genetics, Marburg University, Marburg, Germany
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Institute for Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland
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Blanc J, Berg JJ. Testing for differences in polygenic scores in the presence of confounding. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.03.12.532301. [PMID: 36993707 PMCID: PMC10055004 DOI: 10.1101/2023.03.12.532301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Polygenic scores have become an important tool in human genetics, enabling the prediction of individuals' phenotypes from their genotypes. Understanding how the pattern of differences in polygenic score predictions across individuals intersects with variation in ancestry can provide insights into the evolutionary forces acting on the trait in question, and is important for understanding health disparities. However, because most polygenic scores are computed using effect estimates from population samples, they are susceptible to confounding by both genetic and environmental effects that are correlated with ancestry. The extent to which this confounding drives patterns in the distribution of polygenic scores depends on patterns of population structure in both the original estimation panel and in the prediction/test panel. Here, we use theory from population and statistical genetics, together with simulations, to study the procedure of testing for an association between polygenic scores and axes of ancestry variation in the presence of confounding. We use a general model of genetic relatedness to describe how confounding in the estimation panel biases the distribution of polygenic scores in a way that depends on the degree of overlap in population structure between panels. We then show how this confounding can bias tests for associations between polygenic scores and important axes of ancestry variation in the test panel. Specifically, for any given test, there exists a single axis of population structure in the GWAS panel that needs to be controlled for in order to protect the test. Based on this result, we propose a new approach for directly estimating this axis of population structure in the GWAS panel. We then use simulations to compare the performance of this approach to the standard approach in which the principal components of the GWAS panel genotypes are used to control for stratification.
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Affiliation(s)
- Jennifer Blanc
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Jeremy J. Berg
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
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Staerk C, Klinkhammer H, Wistuba T, Maj C, Mayr A. Generalizability of polygenic prediction models: how is the R 2 defined on test data? BMC Med Genomics 2024; 17:132. [PMID: 38755654 PMCID: PMC11100126 DOI: 10.1186/s12920-024-01905-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 05/08/2024] [Indexed: 05/18/2024] Open
Abstract
BACKGROUND Polygenic risk scores (PRS) quantify an individual's genetic predisposition for different traits and are expected to play an increasingly important role in personalized medicine. A crucial challenge in clinical practice is the generalizability and transferability of PRS models to populations with different ancestries. When assessing the generalizability of PRS models for continuous traits, the R 2 is a commonly used measure to evaluate prediction accuracy. While the R 2 is a well-defined goodness-of-fit measure for statistical linear models, there exist different definitions for its application on test data, which complicates interpretation and comparison of results. METHODS Based on large-scale genotype data from the UK Biobank, we compare three definitions of the R 2 on test data for evaluating the generalizability of PRS models to different populations. Polygenic models for several phenotypes, including height, BMI and lipoprotein A, are derived based on training data with European ancestry using state-of-the-art regression methods and are evaluated on various test populations with different ancestries. RESULTS Our analysis shows that the choice of the R 2 definition can lead to considerably different results on test data, making the comparison of R 2 values from the literature problematic. While the definition as the squared correlation between predicted and observed phenotypes solely addresses the discriminative performance and always yields values between 0 and 1, definitions of the R 2 based on the mean squared prediction error (MSPE) with reference to intercept-only models assess both discrimination and calibration. These MSPE-based definitions can yield negative values indicating miscalibrated predictions for out-of-target populations. We argue that the choice of the most appropriate definition depends on the aim of PRS analysis - whether it primarily serves for risk stratification or also for individual phenotype prediction. Moreover, both correlation-based and MSPE-based definitions of R 2 can provide valuable complementary information. CONCLUSIONS Awareness of the different definitions of the R 2 on test data is necessary to facilitate the reporting and interpretation of results on PRS generalizability. It is recommended to explicitly state which definition was used when reporting R 2 values on test data. Further research is warranted to develop and evaluate well-calibrated polygenic models for diverse populations.
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Affiliation(s)
- Christian Staerk
- Department of Medical Biometry, Informatics and Epidemiology, Medical Faculty, University of Bonn, Bonn, Germany.
- Institute of Statistics, RWTH Aachen University, Aachen, Germany.
| | - Hannah Klinkhammer
- Department of Medical Biometry, Informatics and Epidemiology, Medical Faculty, University of Bonn, Bonn, Germany
- Institute for Genomic Statistics and Bioinformatics, Medical Faculty, University of Bonn, Bonn, Germany
| | - Tobias Wistuba
- Department of Medical Biometry, Informatics and Epidemiology, Medical Faculty, University of Bonn, Bonn, Germany
| | - Carlo Maj
- Center for Human Genetics, University of Marburg, Marburg, Germany
| | - Andreas Mayr
- Department of Medical Biometry, Informatics and Epidemiology, Medical Faculty, University of Bonn, Bonn, Germany
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Mikhailova SV, Ivanoshchuk DE, Orlov PS, Bairqdar A, Anisimenko MS, Denisova DV. Assessment of the Genetic Characteristics of a Generation Born during a Long-Term Socioeconomic Crisis. Genes (Basel) 2023; 14:2064. [PMID: 38003007 PMCID: PMC10671057 DOI: 10.3390/genes14112064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 11/08/2023] [Accepted: 11/09/2023] [Indexed: 11/26/2023] Open
Abstract
BACKGROUND A socioeconomic crisis in Russia lasted from 1991 to 1998 and was accompanied by a sharp drop in the birth rate. The main factor that influenced the refusal to have children during this period is thought to be prolonged social stress. METHODS comparing frequencies of common gene variants associated with stress-induced diseases among generations born before, after, and during this crisis may show which genes may be preferred under the pressure of natural selection during periods of increased social stress in urban populations. RESULTS In the "crisis" group, a statistically significant difference from the other two groups was found in rs6557168 frequency (p = 0.001); rs4522666 was not in the Hardy-Weinberg equilibrium in this group, although its frequency did not show a significant difference from the other groups (p = 0.118). Frequencies of VNTRs in SLC6A3 and MAOA as well as common variants rs17689918 in CRHR1, rs1360780 in FKBP5, rs53576 in OXTR, rs12720071 and rs806377 in CNR1, rs4311 in ACE, rs1800497 in ANKK1, and rs7412 and rs429358 in APOE did not differ among the groups. CONCLUSIONS a generation born during a period of prolonged destructive events may differ from the rest of the gene pool of the population in some variants associated with personality traits or stress-related disorders.
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Affiliation(s)
- Svetlana V. Mikhailova
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences (ICG SB RAS), 10 Prospekt Ak. Lavrentyeva, 630090 Novosibirsk, Russia; (D.E.I.); (P.S.O.); (A.B.); (M.S.A.)
| | - Dinara E. Ivanoshchuk
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences (ICG SB RAS), 10 Prospekt Ak. Lavrentyeva, 630090 Novosibirsk, Russia; (D.E.I.); (P.S.O.); (A.B.); (M.S.A.)
| | - Pavel S. Orlov
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences (ICG SB RAS), 10 Prospekt Ak. Lavrentyeva, 630090 Novosibirsk, Russia; (D.E.I.); (P.S.O.); (A.B.); (M.S.A.)
| | - Ahmad Bairqdar
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences (ICG SB RAS), 10 Prospekt Ak. Lavrentyeva, 630090 Novosibirsk, Russia; (D.E.I.); (P.S.O.); (A.B.); (M.S.A.)
| | - Maksim S. Anisimenko
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences (ICG SB RAS), 10 Prospekt Ak. Lavrentyeva, 630090 Novosibirsk, Russia; (D.E.I.); (P.S.O.); (A.B.); (M.S.A.)
| | - Diana V. Denisova
- Institute of Internal and Preventive Medicine—Branch of ICG SB RAS, 175/1 Borisa Bogatkova Str., 630089 Novosibirsk, Russia
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Mikhailova SV. Problems with studying directional natural selection in humans. Vavilovskii Zhurnal Genet Selektsii 2023; 27:684-693. [PMID: 38023807 PMCID: PMC10643113 DOI: 10.18699/vjgb-23-79] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Revised: 07/03/2023] [Accepted: 07/03/2023] [Indexed: 12/01/2023] Open
Abstract
The review describes the main methods for assessing directional selection in human populations. These include bioinformatic analysis of DNA sequences via detection of linkage disequilibrium and of deviations from the random distribution of frequencies of genetic variants, demographic and anthropometric studies based on a search for a correlation between fertility and phenotypic traits, genome-wide association studies on fertility along with genetic loci and polygenic risk scores, and a comparison of allele frequencies between generations (in modern samples and in those obtained from burials). Each approach has its limitations and is applicable to different periods in the evolution of Homo sapiens. The main source of error in such studies is thought to be sample stratification, the small number of studies on nonwhite populations, the impossibility of a complete comparison of the associations found and functionally significant causative variants, and the difficulty with taking into account all nongenetic determinants of fertility in contemporary populations. The results obtained by various methods indicate that the direction of human adaptation to new food products has not changed during evolution since the Neolithic; many variants of immunity genes associated with inflammatory and autoimmune diseases in modern populations have undergone positive selection over the past 2-3 thousand years owing to the spread of bacterial and viral infections. For some genetic variants and polygenic traits, an alteration of the direction of natural selection in Europe has been documented, e. g., for those associated with an immune response and cognitive abilities. Examination of the correlation between fertility and educational attainment yields conflicting results. In modern populations, to a greater extent than previously, there is selection for variants of genes responsible for social adaptation and behavioral phenotypes. In particular, several articles have shown a positive correlation of fertility with polygenic risk scores of attention deficit/hyperactivity disorder.
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Affiliation(s)
- S V Mikhailova
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
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6
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González-Peñas J, de Hoyos L, Díaz-Caneja CM, Andreu-Bernabeu Á, Stella C, Gurriarán X, Fañanás L, Bobes J, González-Pinto A, Crespo-Facorro B, Martorell L, Vilella E, Muntané G, Molto MD, Gonzalez-Piqueras JC, Parellada M, Arango C, Costas J. Recent natural selection conferred protection against schizophrenia by non-antagonistic pleiotropy. Sci Rep 2023; 13:15500. [PMID: 37726359 PMCID: PMC10509162 DOI: 10.1038/s41598-023-42578-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 09/12/2023] [Indexed: 09/21/2023] Open
Abstract
Schizophrenia is a debilitating psychiatric disorder associated with a reduced fertility and decreased life expectancy, yet common predisposing variation substantially contributes to the onset of the disorder, which poses an evolutionary paradox. Previous research has suggested balanced selection, a mechanism by which schizophrenia risk alleles could also provide advantages under certain environments, as a reliable explanation. However, recent studies have shown strong evidence against a positive selection of predisposing loci. Furthermore, evolutionary pressures on schizophrenia risk alleles could have changed throughout human history as new environments emerged. Here in this study, we used 1000 Genomes Project data to explore the relationship between schizophrenia predisposing loci and recent natural selection (RNS) signatures after the human diaspora out of Africa around 100,000 years ago on a genome-wide scale. We found evidence for significant enrichment of RNS markers in derived alleles arisen during human evolution conferring protection to schizophrenia. Moreover, both partitioned heritability and gene set enrichment analyses of mapped genes from schizophrenia predisposing loci subject to RNS revealed a lower involvement in brain and neuronal related functions compared to those not subject to RNS. Taken together, our results suggest non-antagonistic pleiotropy as a likely mechanism behind RNS that could explain the persistence of schizophrenia common predisposing variation in human populations due to its association to other non-psychiatric phenotypes.
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Affiliation(s)
- Javier González-Peñas
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Calle Ibiza, 43, 28009, Madrid, Spain.
- Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain.
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain.
| | - Lucía de Hoyos
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Calle Ibiza, 43, 28009, Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Covadonga M Díaz-Caneja
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Calle Ibiza, 43, 28009, Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain
- School of Medicine, Universidad Complutense, Madrid, Spain
| | - Álvaro Andreu-Bernabeu
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Calle Ibiza, 43, 28009, Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain
- School of Medicine, Universidad Complutense, Madrid, Spain
| | - Carol Stella
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Calle Ibiza, 43, 28009, Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain
| | - Xaquín Gurriarán
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Calle Ibiza, 43, 28009, Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain
| | - Lourdes Fañanás
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain
- Department of Evolutionary Biology, Ecology and Environmental Sciences, Faculty of Biology, University of Barcelona, Barcelona, Spain
| | - Julio Bobes
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain
- Faculty of Medicine and Health Sciences - Psychiatry, Universidad de Oviedo, ISPA, INEUROPA, Oviedo, Spain
| | - Ana González-Pinto
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain
- BIOARABA Health Research Institute, OSI Araba, University Hospital, University of the Basque Country, Vitoria, Spain
| | - Benedicto Crespo-Facorro
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain
- Department of Psychiatry, Hospital Universitario Virgen del Rocío, Universidad de Sevilla, Seville, Spain
| | - Lourdes Martorell
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain
- Hospital Universitari Institut Pere Mata, IISPV, Universitat Rovira I Virgili, Reus, Spain
| | - Elisabet Vilella
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain
- Hospital Universitari Institut Pere Mata, IISPV, Universitat Rovira I Virgili, Reus, Spain
| | - Gerard Muntané
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain
- Hospital Universitari Institut Pere Mata, IISPV, Universitat Rovira I Virgili, Reus, Spain
| | - María Dolores Molto
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain
- Department of Genetics, University of Valencia, Campus of Burjassot, Valencia, Spain
- Department of Medicine, Universitat de València, Valencia, Spain
| | - Jose Carlos Gonzalez-Piqueras
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain
- Department of Medicine, Universitat de València, Valencia, Spain
- Fundación Investigación Hospital Clínico de Valencia, INCLIVA, 46010, Valencia, Spain
| | - Mara Parellada
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Calle Ibiza, 43, 28009, Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain
- School of Medicine, Universidad Complutense, Madrid, Spain
| | - Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Calle Ibiza, 43, 28009, Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain
- School of Medicine, Universidad Complutense, Madrid, Spain
| | - Javier Costas
- Instituto de Investigación Sanitaria (IDIS) de Santiago de Compostela, Complexo Hospitalario Universitario de Santiago de Compostela (CHUS), Servizo Galego de Saúde (SERGAS), Santiago de Compostela, Galicia, Spain
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7
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Chen Z, Reynolds RH, Pardiñas AF, Gagliano Taliun SA, van Rheenen W, Lin K, Shatunov A, Gustavsson EK, Fogh I, Jones AR, Robberecht W, Corcia P, Chiò A, Shaw PJ, Morrison KE, Veldink JH, van den Berg LH, Shaw CE, Powell JF, Silani V, Hardy JA, Houlden H, Owen MJ, Turner MR, Ryten M, Al-Chalabi A. The contribution of Neanderthal introgression and natural selection to neurodegenerative diseases. Neurobiol Dis 2023; 180:106082. [PMID: 36925053 DOI: 10.1016/j.nbd.2023.106082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Revised: 03/10/2023] [Accepted: 03/13/2023] [Indexed: 03/18/2023] Open
Abstract
Humans are thought to be more susceptible to neurodegeneration than equivalently-aged primates. It is not known whether this vulnerability is specific to anatomically-modern humans or shared with other hominids. The contribution of introgressed Neanderthal DNA to neurodegenerative disorders remains uncertain. It is also unclear how common variants associated with neurodegenerative disease risk are maintained by natural selection in the population despite their deleterious effects. In this study, we aimed to quantify the genome-wide contribution of Neanderthal introgression and positive selection to the heritability of complex neurodegenerative disorders to address these questions. We used stratified-linkage disequilibrium score regression to investigate the relationship between five SNP-based signatures of natural selection, reflecting different timepoints of evolution, and genome-wide associated variants of the three most prevalent neurodegenerative disorders: Alzheimer's disease, amyotrophic lateral sclerosis and Parkinson's disease. We found no evidence for enrichment of positively-selected SNPs in the heritability of Alzheimer's disease, amyotrophic lateral sclerosis and Parkinson's disease, suggesting that common deleterious disease variants are unlikely to be maintained by positive selection. There was no enrichment of Neanderthal introgression in the SNP-heritability of these disorders, suggesting that Neanderthal admixture is unlikely to have contributed to disease risk. These findings provide insight into the origins of neurodegenerative disorders within the evolution of Homo sapiens and addresses a long-standing debate, showing that Neanderthal admixture is unlikely to have contributed to common genetic risk of neurodegeneration in anatomically-modern humans.
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Affiliation(s)
- Zhongbo Chen
- Department of Neurodegenerative Disease, Queen Square Institute of Neurology, University College London (UCL), London, UK; Department of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, UCL, London, UK; NIHR Great Ormond Street Hospital Biomedical Research Centre, UCL, London, UK.
| | - Regina H Reynolds
- Department of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, UCL, London, UK; NIHR Great Ormond Street Hospital Biomedical Research Centre, UCL, London, UK
| | - Antonio F Pardiñas
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Sarah A Gagliano Taliun
- Department of Medicine & Department of Neurosciences, Université de Montréal, Montréal, Québec, Canada; Montréal Heart Institute, Montréal, Québec, Canada
| | - Wouter van Rheenen
- Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, the Netherlands
| | - Kuang Lin
- Nuffield Department of Population Health, Oxford University, Oxford, UK
| | - Aleksey Shatunov
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Emil K Gustavsson
- Department of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, UCL, London, UK; NIHR Great Ormond Street Hospital Biomedical Research Centre, UCL, London, UK
| | - Isabella Fogh
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Ashley R Jones
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Wim Robberecht
- Department of Neurology, University Hospital Leuven, Leuven, Belgium; Department of Neurosciences, Experimental Neurology and Leuven Research Institute for Neuroscience and Disease, Leuven, Belgium; Vesalius Research Center, Laboratory of Neurobiology, Leuven, Belgium
| | - Philippe Corcia
- ALS Center, Department of Neurology, CHRU Bretonneau, Tours, France
| | - Adriano Chiò
- Rita Levi Montalcini Department of Neuroscience, ALS Centre, University of Torino, Turin, Italy; Azienda Ospedaliera Universitaria Città della Salute e della Scienza, Torino, Italy
| | - Pamela J Shaw
- Academic Neurology Unit, Department of Neuroscience, Faculty of Medicine, Dentistry and Health, University of Sheffield, Sheffield, UK
| | - Karen E Morrison
- School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, UK
| | - Jan H Veldink
- Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, the Netherlands
| | - Leonard H van den Berg
- Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, the Netherlands
| | - Christopher E Shaw
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - John F Powell
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Vincenzo Silani
- Department of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Milano, Italy; Department of Pathophysiology and Transplantation, Dino Ferrari Center, Università degli Studi di Milano, 20122 Milano, Italy
| | - John A Hardy
- Department of Neurodegenerative Disease, Queen Square Institute of Neurology, University College London (UCL), London, UK; Reta Lila Weston Institute, Queen Square Institute of Neurology, UCL, London, UK; UK Dementia Research Institute, Queen Square Institute of Neurology, UCL, London, UK; NIHR University College London Hospitals Biomedical Research Centre, London, UK; Institute for Advanced Study, The Hong Kong University of Science and Technology, Hong Kong, SAR, China
| | - Henry Houlden
- Department of Neuromuscular Disease, Queen Square Institute of Neurology, UCL, London, UK
| | - Michael J Owen
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Martin R Turner
- Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, UK
| | - Mina Ryten
- Department of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, UCL, London, UK; NIHR Great Ormond Street Hospital Biomedical Research Centre, UCL, London, UK
| | - Ammar Al-Chalabi
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
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8
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Ferrando-Bernal M. Ancient DNA suggests anaemia and low bone mineral density as the cause for porotic hyperostosis in ancient individuals. Sci Rep 2023; 13:6968. [PMID: 37117261 PMCID: PMC10147686 DOI: 10.1038/s41598-023-33405-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 04/12/2023] [Indexed: 04/30/2023] Open
Abstract
Porotic hyperostosis (PH) is a disease that had high prevalence during the Neolithic. Several hypotheses have been suggested to explain the origin of the disease, such as an iron deficiency diet, low B12 intake, malaria caused by Plasmodium spp., low haemoglobin levels or low vitamin D levels. None of these hypotheses have been tested genetically. Here, I calculated different genetic scores to test each hypothesis. Additionally, I calculated a genetic score of bone mineral density as it is a phenotype that seems to be selected in ancient Europeans. I apply these genetic scores on 80 ancient samples, 33 with diagnosed PH. The results seem to suggest anaemia and low bone mineral density as the main cause for this disease. Additionally, Neolithic individuals show the lowest genetic risk score for bone mineral density of all other periods tested here, which may explain the highest prevalence of the porotic hyperostosis during this age.
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Genetic adaptation to pathogens and increased risk of inflammatory disorders in post-Neolithic Europe. CELL GENOMICS 2023; 3:100248. [PMID: 36819665 PMCID: PMC9932995 DOI: 10.1016/j.xgen.2022.100248] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 10/24/2022] [Accepted: 12/14/2022] [Indexed: 01/15/2023]
Abstract
Ancient genomics can directly detect human genetic adaptation to environmental cues. However, it remains unclear how pathogens have exerted selective pressures on human genome diversity across different epochs and affected present-day inflammatory disease risk. Here, we use an ancestry-aware approximate Bayesian computation framework to estimate the nature, strength, and time of onset of selection acting on 2,879 ancient and modern European genomes from the last 10,000 years. We found that the bulk of genetic adaptation occurred after the start of the Bronze Age, <4,500 years ago, and was enriched in genes relating to host-pathogen interactions. Furthermore, we detected directional selection acting on specific leukocytic lineages and experimentally demonstrated that the strongest negatively selected candidate variant in immunity genes, lipopolysaccharide-binding protein (LBP) D283G, is hypomorphic. Finally, our analyses suggest that the risk of inflammatory disorders has increased in post-Neolithic Europeans, possibly because of antagonistic pleiotropy following genetic adaptation to pathogens.
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10
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García-Ortiz H, Barajas-Olmos F, Contreras-Cubas C, Reynolds AW, Flores-Huacuja M, Snow M, Ramos-Madrigal J, Mendoza-Caamal E, Baca P, López-Escobar TA, Bolnick DA, Flores-Martínez SE, Ortiz-Lopez R, Kostic AD, Villafan-Bernal JR, Galaviz-Hernández C, Centeno-Cruz F, García-Zapién AG, Monge-Cázares T, Lazalde-Ramos BP, Loeza-Becerra F, Abrahantes-Pérez MDC, Rangel-Villalobos H, Sosa-Macías M, Rojas-Martínez A, Martínez-Hernández A, Orozco L. Unraveling Signatures of Local Adaptation among Indigenous Groups from Mexico. Genes (Basel) 2022; 13:genes13122251. [PMID: 36553518 PMCID: PMC9778281 DOI: 10.3390/genes13122251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Revised: 11/05/2022] [Accepted: 11/15/2022] [Indexed: 12/03/2022] Open
Abstract
Few studies have addressed how selective pressures have shaped the genetic structure of the current Native American populations, and they have mostly limited their inferences to admixed Latin American populations. Here, we searched for local adaptation signals, based on integrated haplotype scores and population branch statistics, in 325 Mexican Indigenous individuals with at least 99% Native American ancestry from five previously defined geographical regions. Although each region exhibited its own local adaptation profile, only PPARG and AJAP1, both negative regulators of the Wnt/β catenin signaling pathway, showed significant adaptation signals in all the tested regions. Several signals were found, mainly in the genes related to the metabolic processes and immune response. A pathway enrichment analysis revealed the overrepresentation of selected genes related to several biological phenotypes/conditions, such as the immune response and metabolic pathways, in agreement with previous studies, suggesting that immunological and metabolic pressures are major drivers of human adaptation. Genes related to the gut microbiome measurements were overrepresented in all the regions, highlighting the importance of studying how humans have coevolved with the microbial communities that colonize them. Our results provide a further explanation of the human evolutionary history in response to environmental pressures in this region.
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Affiliation(s)
- Humberto García-Ortiz
- Instituto Nacional de Medicina Genómica, Tlalpan, Mexico City 14610, Mexico
- Correspondence:
| | | | | | | | | | - Meradeth Snow
- Department of Anthropology, University of Montana, Missoula, MT 59812, USA
| | - Jazmín Ramos-Madrigal
- Section for Evolutionary Genomics, The GLOBE Institute, The University of Copenhagen, Øster Farimagsgade 5A, 1352 Copenhagen, Denmark
| | | | - Paulina Baca
- Instituto Nacional de Medicina Genómica, Tlalpan, Mexico City 14610, Mexico
| | | | - Deborah A. Bolnick
- Department of Anthropology and Institute for Systems Genomics, University of Connecticut, Storrs, CT 06269-3003, USA
| | - Silvia Esperanza Flores-Martínez
- División de Medicina Molecular, Centro de Investigación Biomédica de Occidente, Instituto Mexicano del Seguro Social (IMSS), Guadalajara 44340, Mexico
| | - Rocio Ortiz-Lopez
- Tecnologico de Monterrey, Escuela de Medicina y Ciencias de la Salud and Insitute for Obesity Research, Monterrey 64700, Mexico
- Centro de Investigacion y Desarrollo en Ciencias de la Salud, Universidad Autonoma de Nuevo Leon, Monterrey 64460, Mexico
| | | | | | | | | | - Alejandra Guadalupe García-Zapién
- Departamento de Farmacobiología, Centro Universitario de Ciencias Exactas e Ingenierías, Universidad de Guadalajara, Guadalajara 44430, Mexico
| | | | | | | | | | - Héctor Rangel-Villalobos
- Instituto de Investigación en Genética Molecular, Universidad de Guadalajara Ocotlán, Ocotlán 44100, Mexico
| | | | - Augusto Rojas-Martínez
- Tecnologico de Monterrey, Escuela de Medicina y Ciencias de la Salud and Insitute for Obesity Research, Monterrey 64700, Mexico
- Centro de Investigacion y Desarrollo en Ciencias de la Salud, Universidad Autonoma de Nuevo Leon, Monterrey 64460, Mexico
| | | | - Lorena Orozco
- Instituto Nacional de Medicina Genómica, Tlalpan, Mexico City 14610, Mexico
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11
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Abraham A, LaBella AL, Capra JA, Rokas A. Mosaic patterns of selection in genomic regions associated with diverse human traits. PLoS Genet 2022; 18:e1010494. [PMID: 36342969 PMCID: PMC9671423 DOI: 10.1371/journal.pgen.1010494] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 11/17/2022] [Accepted: 10/21/2022] [Indexed: 11/09/2022] Open
Abstract
Natural selection shapes the genetic architecture of many human traits. However, the prevalence of different modes of selection on genomic regions associated with variation in traits remains poorly understood. To address this, we developed an efficient computational framework to calculate positive and negative enrichment of different evolutionary measures among regions associated with complex traits. We applied the framework to summary statistics from >900 genome-wide association studies (GWASs) and 11 evolutionary measures of sequence constraint, population differentiation, and allele age while accounting for linkage disequilibrium, allele frequency, and other potential confounders. We demonstrate that this framework yields consistent results across GWASs with variable sample sizes, numbers of trait-associated SNPs, and analytical approaches. The resulting evolutionary atlas maps diverse signatures of selection on genomic regions associated with complex human traits on an unprecedented scale. We detected positive enrichment for sequence conservation among trait-associated regions for the majority of traits (>77% of 290 high power GWASs), which included reproductive traits. Many traits also exhibited substantial positive enrichment for population differentiation, especially among hair, skin, and pigmentation traits. In contrast, we detected widespread negative enrichment for signatures of balancing selection (51% of GWASs) and absence of enrichment for evolutionary signals in regions associated with late-onset Alzheimer's disease. These results support a pervasive role for negative selection on regions of the human genome that contribute to variation in complex traits, but also demonstrate that diverse modes of evolution are likely to have shaped trait-associated loci. This atlas of evolutionary signatures across the diversity of available GWASs will enable exploration of the relationship between the genetic architecture and evolutionary processes in the human genome.
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Affiliation(s)
- Abin Abraham
- Vanderbilt University Medical Center, Vanderbilt University, Nashville, Tennessee, United States of America
| | - Abigail L. LaBella
- Department of Biological Sciences, Vanderbilt University, Nashville, Tennessee, United States of America
- Evolutionary Studies Initiative, Vanderbilt University, Nashville, Tennessee, United States of America
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, North Carolina, United States of America
- North Carolina Research Center, Kannapolis, North Carolina, United States of America
| | - John A. Capra
- Bakar Computational Health Sciences Institute, University of California, San Francisco, California, United States of America
- Department of Epidemiology and Biostatistics, University of California, San Francisco, California, United States of America
| | - Antonis Rokas
- Department of Biological Sciences, Vanderbilt University, Nashville, Tennessee, United States of America
- Evolutionary Studies Initiative, Vanderbilt University, Nashville, Tennessee, United States of America
- Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America
- Vanderbilt Genetics Institute, Vanderbilt University, Nashville, Tennessee, United States of America
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12
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Neandertal introgression partitions the genetic landscape of neuropsychiatric disorders and associated behavioral phenotypes. Transl Psychiatry 2022; 12:433. [PMID: 36198681 PMCID: PMC9534885 DOI: 10.1038/s41398-022-02196-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 09/13/2022] [Accepted: 09/20/2022] [Indexed: 11/08/2022] Open
Abstract
Despite advances in identifying the genetic basis of psychiatric and neurological disorders, fundamental questions about their evolutionary origins remain elusive. Here, introgressed variants from archaic humans such as Neandertals can serve as an intriguing research paradigm. We compared the number of associations for Neandertal variants to the number of associations of frequency-matched non-archaic variants with regard to human CNS disorders (neurological and psychiatric), nervous system drug prescriptions (as a proxy for disease), and related, non-disease phenotypes in the UK biobank (UKBB). While no enrichment for Neandertal genetic variants were observed in the UKBB for psychiatric or neurological disease categories, we found significant associations with certain behavioral phenotypes including pain, chronotype/sleep, smoking and alcohol consumption. In some instances, the enrichment signal was driven by Neandertal variants that represented the strongest association genome-wide. SNPs within a Neandertal haplotype that was associated with smoking in the UKBB could be replicated in four independent genomics datasets.Our data suggest that evolutionary processes in recent human evolution like admixture with Neandertals significantly contribute to behavioral phenotypes but not psychiatric and neurological diseases. These findings help to link genetic variants in a population to putative past beneficial effects, which likely only indirectly contribute to pathology in modern day humans.
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13
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Song W, Yuan K, Liu Z, Cai W, Chen J, Yu S, Zhao M, Lin GN. Locus-level antagonistic selection shaped the polygenic architecture of human complex diseases. Hum Genet 2022; 141:1935-1947. [PMID: 35943608 DOI: 10.1007/s00439-022-02471-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 07/11/2022] [Indexed: 12/01/2022]
Abstract
BACKGROUND We aimed to evaluate the potential role of antagonistic selection in polygenic diseases: if one variant increases the risk of one disease and decreases the risk of another disease, the signals of genetic risk elimination by natural selection will be distorted, which leads to a higher frequency of risk alleles. METHODS We applied local genetic correlations and transcriptome-wide association studies to identify genomic loci and genes adversely associated with at least two diseases. Then, we used different population genetic metrics to measure the signals of natural selection for these loci and genes. RESULTS First, we identified 2120 cases of antagonistic pleiotropy (negative local genetic correlation) among 87 diseases in 716 genomic loci (antagonistic loci). Next, by comparing with non-antagonistic loci, we observed that antagonistic loci explained an excess proportion of disease heritability (median 6%), showed enhanced signals of balancing selection, and reduced signals of directional polygenic adaptation. Then, at the gene expression level, we identified 31,991 cases of antagonistic pleiotropy among 98 diseases at 4368 genes. However, evidence of altered signals of selection pressure and heritability distribution at the gene expression level is limited. CONCLUSION We conclude that antagonistic pleiotropy is widespread among human polygenic diseases, and it has distorted the evolutionary signal and genetic architecture of diseases at the locus level.
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Affiliation(s)
- Weichen Song
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.,Shanghai Key Laboratory of Psychotic Disorders, Shanghai, China
| | - Kai Yuan
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Zhe Liu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Wenxiang Cai
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Jue Chen
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Shunying Yu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.,Shanghai Key Laboratory of Psychotic Disorders, Shanghai, China
| | - Min Zhao
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China. .,Shanghai Key Laboratory of Psychotic Disorders, Shanghai, China.
| | - Guan Ning Lin
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China. .,Shanghai Key Laboratory of Psychotic Disorders, Shanghai, China.
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14
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Song W, Lin GN, Yu S, Zhao M. Genome-wide identification of the shared genetic basis of cannabis and cigarette smoking and schizophrenia implicates NCAM1 and neuronal abnormality. Psychiatry Res 2022; 310:114453. [PMID: 35235886 DOI: 10.1016/j.psychres.2022.114453] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Revised: 01/31/2022] [Accepted: 02/15/2022] [Indexed: 01/02/2023]
Abstract
OBJECTIVES Confirming the existence and composition of the shared genetic basis of Schizophrenia and cannabis and cigarette smoking has critical values for the clinical prevention and intervention of psychosis. METHODS To achieve this goal, we leveraged Genome-Wide summary statistics of Schizophrenia (n = 99,934), cigarette smoking (n = 518,633) and cannabis usage (n = 162,082). We applied Causal Analysis Using Summary Effect Estimates (CAUSE) and genomic structural equation modeling (GenomicSEM) to quantify the contribution of a common genetic factor of cannabis and cigarette smoking and schizophrenia (referred to as SCZ_SMO), then identified genome-wide loci that made up SCZ_SMO. RESULTS We estimated that SCZ_SMO explained 8.6% of Schizophrenia heritability (Z score <-2.5 in CAUSE, p<10-20 in Genomic SEM). There were 20 independent loci showing association with SCZ_SMO at the genome-wide threshold of p<5 × 10-8. At the top locus on chromosome 11, fine-mapping identified rs7945073 (posterior inclusion probability =0.12, p = 2.24 × 10-32) as the top risk variants. Gene-level association and fine-mapping highlighted NCAM1, PHC2, and SEMA6D as risk genes of SCZ_SMO. Other risk genes were enriched in cortex, neuron, and dendritic spines (adjusted p<0.05). SCZ_SMO showed significant positive correlation (p<10-6) with the genetic risk of attention deficit hyperactivity disorder (r = 0.50), lifestyle problems (r = 0.83), social deprivation (r = 0.58) and all-cause pregnant loss (r = 0.60). CONCLUSION Our result provided new evidence on the shared genetic basis model for the association between Schizophrenia and smoking and provided genetic and biological insights into their shared mechanism.
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Affiliation(s)
- Weichen Song
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China; Shanghai Key Laboratory of Psychotic Disorders, Shanghai, China
| | - Guan Ning Lin
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China; Shanghai Key Laboratory of Psychotic Disorders, Shanghai, China
| | - Shunying Yu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China; Shanghai Key Laboratory of Psychotic Disorders, Shanghai, China
| | - Min Zhao
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China; Shanghai Key Laboratory of Psychotic Disorders, Shanghai, China; CAS Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Sciences, Shanghai, China.
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15
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Lao O. Selection still shapes our genome. Nat Hum Behav 2021; 5:1600-1601. [PMID: 34782731 DOI: 10.1038/s41562-021-01232-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Oscar Lao
- Population Genomics, Centre Nacional d'Anàlisi Genòmica (CNAG-CRG), Centre for Genomic Regulation, Barcelona, Spain. .,Barcelona Institute of Science and Technology (BIST), Barcelona, Spain. .,Universitat Pompeu Fabra (UPF), Barcelona, Spain.
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