1
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Tian Y, Zhang H, Bureau A, Hochner H, Chen J. Efficient inference of parent-of-origin effect using case-control mother-child genotype data. J Stat Plan Inference 2024; 233:106190. [PMID: 38818512 PMCID: PMC11135462 DOI: 10.1016/j.jspi.2024.106190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/01/2024]
Abstract
Parent-of-origin effect plays an important role in mammal development and disorder. Case-control mother-child pair genotype data can be used to detect parent-of-origin effect and is often convenient to collect in practice. Most existing methods for assessing parent-of-origin effect do not incorporate any covariates, which may be required to control for confounding factors. We propose to model the parent-of-origin effect through a logistic regression model, with predictors including maternal and child genotypes, parental origins, and covariates. The parental origins may not be fully inferred from genotypes of a target genetic marker, so we propose to use genotypes of markers tightly linked to the target marker to increase inference efficiency. A robust statistical inference procedure is developed based on a modified profile log-likelihood in a retrospective way. A computationally feasible expectation-maximization algorithm is devised to estimate all unknown parameters involved in the modified profile log-likelihood. This algorithm differs from the conventional expectation-maximization algorithm in the sense that it is based on a modified instead of the original profile log-likelihood function. The convergence of the algorithm is established under some mild regularity conditions. This expectation-maximization algorithm also allows convenient handling of missing child genotypes. Large sample properties, including weak consistency, asymptotic normality, and asymptotic efficiency, are established for the proposed estimator under some mild regularity conditions. Finite sample properties are evaluated through extensive simulation studies and the application to a real dataset.
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Affiliation(s)
- Yuang Tian
- Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China
| | - Hong Zhang
- Department of Statistics and Finance, School of Management, University of Science and Technology of China, Hefei, Anhui, China
| | - Alexandre Bureau
- Department of Social and Preventive Medicine, Université Laval, Québec, Canada
| | - Hagit Hochner
- Braun School of Public Health, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Jinbo Chen
- Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, U.S.A
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2
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Head ST, Leslie EJ, Cutler DJ, Epstein MP. POIROT: a powerful test for parent-of-origin effects in unrelated samples leveraging multiple phenotypes. Bioinformatics 2023; 39:btad199. [PMID: 37067493 PMCID: PMC10148680 DOI: 10.1093/bioinformatics/btad199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 04/03/2023] [Accepted: 04/06/2023] [Indexed: 04/18/2023] Open
Abstract
MOTIVATION There is widespread interest in identifying genetic variants that exhibit parent-of-origin effects (POEs) wherein the effect of an allele on phenotype expression depends on its parental origin. POEs can arise from different phenomena including genomic imprinting and have been documented for many complex traits. Traditional tests for POEs require family data to determine parental origins of transmitted alleles. As most genome-wide association studies (GWAS) sample unrelated individuals (where allelic parental origin is unknown), the study of POEs in such datasets requires sophisticated statistical methods that exploit genetic patterns we anticipate observing when POEs exist. We propose a method to improve discovery of POE variants in large-scale GWAS samples that leverages potential pleiotropy among multiple correlated traits often collected in such studies. Our method compares the phenotypic covariance matrix of heterozygotes to homozygotes based on a Robust Omnibus Test. We refer to our method as the Parent of Origin Inference using Robust Omnibus Test (POIROT) of multiple quantitative traits. RESULTS Through simulation studies, we compared POIROT to a competing univariate variance-based method which considers separate analysis of each phenotype. We observed POIROT to be well-calibrated with improved power to detect POEs compared to univariate methods. POIROT is robust to non-normality of phenotypes and can adjust for population stratification and other confounders. Finally, we applied POIROT to GWAS data from the UK Biobank using BMI and two cholesterol phenotypes. We identified 338 genome-wide significant loci for follow-up investigation. AVAILABILITY AND IMPLEMENTATION The code for this method is available at https://github.com/staylorhead/POIROT-POE.
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Affiliation(s)
- S Taylor Head
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA 30322, United States
| | - Elizabeth J Leslie
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, United States
| | - David J Cutler
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, United States
| | - Michael P Epstein
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, United States
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3
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Mamasoula C, Bigirumurame T, Chadwick T, Addor MC, Cavero-Carbonell C, Dias CM, Echevarría-González-de-Garibay LJ, Gatt M, Khoshnood B, Klungsoyr K, Randall K, Stoianova S, Haeusler M, Nelen V, Neville AJ, Perthus I, Pierini A, Bertaut-Nativel B, Rissmann A, Rouget F, Schaub B, Tucker D, Wellesley D, Zymak-Zakutnia N, Barisic I, de Walle HEK, Lanzoni M, Sayers G, Mullaney C, Pennington L, Rankin J. Maternal age and the prevalence of congenital heart defects in Europe, 1995-2015: A register-based study. Birth Defects Res 2023; 115:583-594. [PMID: 36734416 DOI: 10.1002/bdr2.2152] [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: 10/10/2022] [Revised: 12/18/2022] [Accepted: 01/10/2023] [Indexed: 02/04/2023]
Abstract
BACKGROUND Evidence on the direction and strength of association between maternal age and the prevalence of congenital heart defects (CHD) in different age group categories is conflicting. Some studies have illustrated different trends with an increase in prevalence in younger and older age groups while other studies have reported a linear relationship. Given the increase in maternal age over recent years, it is important to study the CHD prevalence by maternal age. OBJECTIVES To examine the association between maternal age and the prevalence of CHD in Europe between 1995 and 2015 using population-based data from 24 registries belonging to the European Surveillance of Congenital Anomalies (EUROCAT) network. METHODS Associations over time of all nonsyndromic CHD according to maternal age category and for three CHD severity groupings (severity group I: very severe; severity group II: severe; severity group III: less severe) were examined using Bayesian multilevel Poisson regression modeling. Further subgroup analyses were undertaken within four maternal age-bands: ≤24, 25-29, 30-34 and 35-44 years. Descriptive summaries are also presented. RESULTS There were 51,608 nonsyndromic CHD cases in Europe over the 20-year study period. Total prevalence for all CHD combined was increased for younger mothers (≤24 years) and for mothers 35-44 years of age when compared with mothers aged 25-29 years (reference group) (IRR: 1.05, 95% CI: 1.02, 1.07). The total prevalence was increased for severity group I (very severe) only for younger mothers compared to those aged 25-29 years (IRR: 1.14, 95% CI: 1.04, 1.23). We found an increased prevalence of the following CHD subtypes: double outlet right ventricle (IRR:1.33, 95% CI: 1.09, 1.60), hypoplastic left heart syndrome (IRR: 1.18, 95% CI: 1.05, 1.32), hypoplastic right heart syndrome (IRR: 1.41, 95% CI: 1.05, 1.84), atrioventricular septal defect (IRR: 1.15, 95% CI: 1.01, 1.32), coarctation of aorta (IRR: 1.15, 95% CI: 1.03, 1.28) and atrial septal defect (IRR: 1.08, 95% CI: 1.02, 1.13). For older mothers (35-44 years) compared to the reference category, we observed an increased risk in the prevalence for severity group II (IRR: 1.09, 95% CI: 1.03, 1.14), severity group III (IRR: 1.05, 95% CI: 1.01, 1.08) and an increased prevalence of the CHD subtypes: Pulmonary valve stenosis (IRR: 1.22, 95% CI: 1.09, 1.34), ASD (IRR: 1.07, 95% CI: 1.02, 1.13), CoA (IRR: 1.18, 95% CI: 1.06, 1.32) and Tetralogy of Fallot (IRR: 1.14, 95% CI: 1.01, 1.28). Finally, for all age categories compared to the reference category, different associations of ASD and an increased prevalence of CoA was also observed. CONCLUSIONS Based on data for cases of CHD from 24 European population-based registries, evidence of a positive association between maternal age and the total prevalence of CHD for younger (≤24 years old) and older (35-44 years old) mothers was observed. The results suggest that young maternal age (≤24 years old) is a factor associated with severe CHD phenotypes while a positive association between advanced maternal age (35-44 years old) and mild CHD phenotypes was observed.
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Affiliation(s)
| | | | - Thomas Chadwick
- Population Health Sciences Institute, Newcastle University, Newcastle, UK
| | - Marie-Claude Addor
- Department of Woman-Mother-Child, University Medical Center CHUV, Lausanne, Switzerland
| | - Clara Cavero-Carbonell
- Rare Diseases Research Unit, Foundation for the Promotion of Health and Biomedical Research in the Valencian Region, Valencia, Spain
| | - Carlos M Dias
- Population Health Sciences Institute, Newcastle University, Newcastle, UK
- Epidemiology Department, National Institute of Health Doutor Ricardo Jorge, Lisbon, Portugal
| | - Luis-Javier Echevarría-González-de-Garibay
- Ministry of Health of the Basque Government. Directorate for Healthcare Planning, Organisation and Evaluation, Registries and Health Information Unit, Vitoria-Gasteiz, Spain
| | - Miriam Gatt
- Malta Congenital Anomalies Register, Directorate for Health Information and Research, Pietà, Malta
| | - Babak Khoshnood
- Université de Paris, INSERM U1153, CRESS, Obstetrical Perinatal and Pediatric Epidemiology Research Team (EPOPé), Paris, France
| | - Kari Klungsoyr
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
- Division for Mental and Physical Health, Norwegian Institute of Public Health, Bergen, Norway
| | - Kay Randall
- National Perinatal Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Sylvia Stoianova
- South West Congenital Anomaly Register, Bristol Medical School, University of Bristol, Bristol, UK
| | - Martin Haeusler
- Styrian Malformation Registry, Med. University of Graz, Graz, Austria
| | - Vera Nelen
- Provinciaal Instituut voor Hygiene (PIH), Antwerp, Belgium
| | - Amanda J Neville
- Registro IMER - IMER Registry (Emilia Romagna Registry of Birth Defects), Center for Clinical and Epidemiological Research, University of Ferrara, Ferrara, Italy
| | - Isabelle Perthus
- Auvergne registry of congenital anomalies (CEMC-Auvergne), Department of clinical genetics, Centre de Référence des Maladies Rares, University Hospital of Clermont-Ferrand, Clermont-Ferrand, France
| | - Anna Pierini
- Tuscany Registry of Congenital Defects (RTDC), Institute of Clinical Physiology - National Research Council/ Fondazione Toscana Gabriele Monasterio, Pisa, Italy
| | | | - Anke Rissmann
- Malformation Monitoring Centre Saxony-Anhalt, Medical Faculty Otto-von-Guericke University, Magdeburg, Germany
| | - Florence Rouget
- Brittany Registry of Congenital Anomalies, CHU Rennes, University Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail), Rennes, France
| | - Bruno Schaub
- French West Indies Registry, Registre des Malformations des Antilles (REMALAN), Maison de la Femme de la Mère et de l'Enfant, University Hospital of Martinique, Fort-de-France, France
| | - David Tucker
- CARIS, Public Health Wales, Singleton Hospital, Swansea, UK
| | - Diana Wellesley
- Wessex Clinical Genetics Department, Princess Anne Hospital, Southampton, UK
| | - Natalya Zymak-Zakutnia
- OMNI-Net Ukraine Birth Defects Program and Khmelnytsky City Children's Hospital, Khmelnytsky, Ukraine
| | - Ingeborg Barisic
- Centre of Excellence for Reproductive and Regenerative Medicine, Children's Hospital Zagreb, Medical School University of Zagreb, Zagreb, Croatia
| | - Hermien E K de Walle
- University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, Netherlands
| | - Monica Lanzoni
- European Commission, Joint Research Centre (JRC), Ispra, Italy
| | - Gerardine Sayers
- Health Service Executive, Dr Steeven's Hospital, Dublin, Ireland
| | - Carmel Mullaney
- Department of Public Health, Service Executive (HSE) South East Area, Limerick, Ireland
| | - Lindsay Pennington
- Population Health Sciences Institute, Newcastle University, Newcastle, UK
| | - Judith Rankin
- Population Health Sciences Institute, Newcastle University, Newcastle, UK
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4
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Workalemahu T, Enquobahrie DA, Gelaye B, Tadesse MG, Sanchez SE, Tekola-Ayele F, Hajat A, Thornton TA, Ananth CV, Williams MA. Maternal-fetal genetic interactions, imprinting, and risk of placental abruption. J Matern Fetal Neonatal Med 2022; 35:3473-3482. [PMID: 32972274 PMCID: PMC8601203 DOI: 10.1080/14767058.2020.1822314] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2020] [Revised: 09/02/2020] [Accepted: 09/08/2020] [Indexed: 12/17/2022]
Abstract
RESULTS Abruption cases were more likely to experience preeclampsia, have shorter gestational age, and deliver infants with lower birthweight compared with controls. Models with MFGI effects provided improved fit than models with only maternal and fetal genotype main effects for SNP rs12530904 (p-value = 1.2e-04) in calcium/calmodulin-dependent protein kinase [CaM kinase] II beta (CAMK2B), and, SNP rs73136795 (p-value = 1.9e-04) in peroxisome proliferator-activated receptor-gamma (PPARG), both MB genes. We identified 320 SNPs in 45 maternally-imprinted genes (including potassium voltage-gated channel subfamily Q member 1 [KCNQ1], neurotrimin [NTM], and, ATPase phospholipid transporting 10 A [ATP10A]) associated with abruption. Top hits included rs2012323 (p-value = 1.6E-16) and rs12221520 (p-value1.3e-13) in KCNQ1, rs8036892 (p-value = 9.3E-17) and rs188497582 in ATP10A, rs12589854 (p-value = 2.9E-11) and rs80203467 (p-value = 4.6e-11) in maternally expressed 8, small nucleolar RNA host (MEG8), and rs138281088 in solute carrier family 22 member 2 (SLC22A2) (p-value = 6.8e-9). CONCLUSIONS We identified novel PA-related maternal-fetal MB gene interactions and imprinting effects that highlight the role of the fetus in PA risk development. Findings can inform mechanistic investigations to understand the pathogenesis of PA.
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Affiliation(s)
- Tsegaselassie Workalemahu
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, Washington
- Department of Obstetrics and Gynecology, Division of Maternal-Fetal Medicine, University of Utah, Salt Lake City, Utah
| | - Daniel A. Enquobahrie
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, Washington
- Center for Perinatal Studies, Swedish Medical Center, Seattle, Washington
| | - Bizu Gelaye
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Mahlet G. Tadesse
- Department of Mathematics and Statistics, Georgetown University, Washington, District of Columbia
| | - Sixto E. Sanchez
- Facultad de Medicina Humana, Universidad de San Martín de Porres, Lima, Peru
- Asociación Civil PROESA, Lima, Peru
| | - Fasil Tekola-Ayele
- Department of Obstetrics and Gynecology, Division of Maternal-Fetal Medicine, University of Utah, Salt Lake City, Utah
| | - Anjum Hajat
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, Washington
| | | | - Cande V. Ananth
- Division of Epidemiology and Biostatistics, Department of Obstetrics, Gynecology and Reproductive Sciences, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ
- Department of Biostatistics and Epidemiology, Rutgers School of Public Health, Piscataway, NJ
- Cardiovascular Institute of New Jersey (CVI-NJ), Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ
- Environmental and Occupational Health Sciences Institute (EOHSI), Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ
| | - Michelle A. Williams
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
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5
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Chen S, Zhang H. Analysis of parent‐of‐origin effects for secondary phenotypes using case–control mother–child pair data. Genet Epidemiol 2022; 46:430-445. [DOI: 10.1002/gepi.22463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 03/28/2022] [Accepted: 04/20/2022] [Indexed: 11/10/2022]
Affiliation(s)
- Shuyue Chen
- School of Data Science University of Science and Technology of China Hefei Anhui P.R. China
| | - Hong Zhang
- Department of Statistics and Finance, School of Management University of Science and Technology of China Hefei Anhui P.R. China
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6
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Zhang K, Zhang H, Hochner H, Chen J. Covariate adjusted inference of parent-of-origin effects using case-control mother-child paired multilocus genotype data. Genet Epidemiol 2021; 45:830-847. [PMID: 34424572 DOI: 10.1002/gepi.22428] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Revised: 07/08/2021] [Accepted: 07/27/2021] [Indexed: 01/13/2023]
Abstract
It is of great interest to identify parent-of-origin effects (POEs) since POEs play an important role in many human heritable disorders and human early life growth and development. POE is sometimes referred to as imprinting effect in the literature. Compared with the standard logistic regression analyses, retrospective likelihood-based statistical methods are more powerful in identifying POEs when data are collected from related individuals retrospectively. However, none of existing retrospective-based methods can appropriately incorporate covariates that should be adjusted for if they are confounding factors. In this paper, a novel semiparametric statistical method, M-HAP, is developed to detect POEs by fully exploring available information from multilocus genotypes of case-control mother-child pairs and covariates. Some large sample properties are established for M-HAP. Finite sample properties of M-HAP are illustrated by extensive simulation studies and real data applications to the Jerusalem Perinatal Study and the Danish National Birth Cohort study, which confirm the desired superiority of M-HAP over some existing methods. M-HAP has been implemented in the updated R package CCMO.
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Affiliation(s)
- Kai Zhang
- Department of Statistics and Finance, School of Management, University of Science and Technology of China, Hefei, Anhui, People's Republic of China
| | - Hong Zhang
- Department of Statistics and Finance, School of Management, University of Science and Technology of China, Hefei, Anhui, People's Republic of China
| | - Hagit Hochner
- Braun School of Public Health, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Jinbo Chen
- Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, USA
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7
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Gjerdevik M, Gjessing HK, Romanowska J, Haaland ØA, Jugessur A, Czajkowski NO, Lie RT. Design efficiency in genetic association studies. Stat Med 2020; 39:1292-1310. [PMID: 31943314 DOI: 10.1002/sim.8476] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2019] [Revised: 12/20/2019] [Accepted: 12/21/2019] [Indexed: 11/07/2022]
Abstract
Selecting the best design for genetic association studies requires careful deliberation; different study designs can be used to scan for different genetic effects, and each design has its own set of strengths and limitations. A variety of family and unrelated control configurations are amenable to genetic association analyses, including the case-control design, case-parent triads, and case-parent triads in combination with unrelated controls or control-parent triads. Ultimately, the goal is to choose the design that achieves the highest statistical power using the lowest cost. For given parameter values and genotyped individuals, designs can be compared directly by computing the power. However, a more informative and general design comparison can be achieved by studying the relative efficiency, defined as the ratio of variances of two different parameter estimators, corresponding to two separate designs. Using log-linear modeling, we derive the relative efficiency from the asymptotic variance of the parameter estimators and relate it to the concept of Pitman efficiency. The relative efficiency takes into account the fact that different designs impose different costs relative to the number of genotyped individuals. We show that while optimal efficiency for analyses of regular autosomal effects is achieved using the standard case-control design, the case-parent triad design without unrelated controls is efficient when searching for parent-of-origin effects. Due to the potential loss of efficiency, maternal genes should generally not be adjusted for in an initial genome-wide association study scan of offspring genes but instead checked post hoc. The relative efficiency calculations are implemented in our R package Haplin.
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Affiliation(s)
- Miriam Gjerdevik
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway.,Department of Genetics and Bioinformatics, Norwegian Institute of Public Health, Oslo, Norway
| | - Håkon K Gjessing
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway.,Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Julia Romanowska
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway.,Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Øystein A Haaland
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
| | - Astanand Jugessur
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway.,Department of Genetics and Bioinformatics, Norwegian Institute of Public Health, Oslo, Norway.,Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Nikolai O Czajkowski
- Department of Psychology, University of Oslo, Oslo, Norway.,Division of Mental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Rolv T Lie
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway.,Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
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8
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Incorporating information from markers in LD with test locus for detecting imprinting and maternal effects. Eur J Hum Genet 2020; 28:1087-1097. [PMID: 32080366 DOI: 10.1038/s41431-020-0590-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Revised: 11/26/2019] [Accepted: 02/04/2020] [Indexed: 11/08/2022] Open
Abstract
Numerous statistical methods have been developed to explore genomic imprinting and maternal effects by identifying parent-of-origin patterns in complex human diseases. However, because most of these methods only use available locus-specific genotype data, it is sometimes impossible for them to infer the distribution of parental origin of a variant allele, especially when some genotypes are missing. In this article, we propose a two-step approach, LIMEhap, to improve upon a recent partial likelihood inference method. In the first step, the distribution of the missing genotypes is inferred through the construction of haplotypes by using information from nearby loci. In the second step, a partial likelihood method is applied to the inferred data. To substantiate the validity of the proposed procedures, we simulated data in a genomic region of gene GPX1. The results show that, by borrowing genetic information from nearby loci, the power of the proposed method can be close to that with complete genotype data at the locus of interest. Since the inference on the genotype distribution is made under the assumption of Hardy-Weinberg Equilibrium (HWE), we further studied the robustness of LIMEhap to violation of HWE. Finally, we demonstrate the utility of LIMEhap by applying it to an autism dataset.
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9
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Nudel R, Christiani CAJ, Ohland J, Uddin MJ, Hemager N, Ellersgaard DV, Spang KS, Burton BK, Greve AN, Gantriis DL, Bybjerg-Grauholm J, Jepsen JRM, Thorup AAE, Mors O, Nordentoft M, Werge T. Language deficits in specific language impairment, attention deficit/hyperactivity disorder, and autism spectrum disorder: An analysis of polygenic risk. Autism Res 2019; 13:369-381. [PMID: 31577390 PMCID: PMC7078922 DOI: 10.1002/aur.2211] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2019] [Accepted: 09/04/2019] [Indexed: 12/27/2022]
Abstract
Language is one of the cognitive domains often impaired across many neurodevelopmental disorders. While for some disorders the linguistic deficit is the primary impairment (e.g., specific language impairment, SLI), for others it may accompany broader behavioral problems (e.g., autism). The precise nature of this phenotypic overlap has been the subject of debate. Moreover, several studies have found genetic overlaps across neurodevelopmental disorders. This raises the question of whether these genetic overlaps may correlate with phenotypic overlaps and, if so, in what manner. Here, we apply a genome‐wide approach to the study of the linguistic deficit in SLI, autism spectrum disorder (ASD), and attention deficit/hyperactivity disorder (ADHD). Using a discovery genome‐wide association study of SLI, we generate polygenic risk scores (PRS) in an independent sample which includes children with language impairment, SLI, ASD or ADHD and age‐matched controls and perform regression analyses across groups. The SLI‐trained PRS significantly predicted risk in the SLI case–control group (adjusted R2 = 6.24%; P = 0.024) but not in the ASD or ADHD case‐control groups (adjusted R2 = 0.0004%, 0.01%; P = 0.984, 0.889, respectively) nor for height, used as a negative control (R2 = 0.2%; P = 0.452). Additionally, there was a significant difference in the normalized PRS between children with SLI and children with ASD (common language effect size = 0.66; P = 0.044). Our study suggests no additive common‐variant genetic overlap between SLI and ASD and ADHD. This is discussed in the context of phenotypic studies of SLI and related disorders. Autism Res 2020, 13: 369–381. © 2019 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals, Inc. Lay Summary Language deficits are characteristic of specific language impairment (SLI), but may also be found in other neurodevelopmental disorders, such as autism spectrum disorder (ASD) and attention deficit/hyperactivity disorder (ADHD). Many studies examined the overlaps and differences across the language deficits in these disorders, but few studies have examined the genetic aspect thereof. In this study, we use a genome‐wide approach to evaluate whether common genetic variants increasing risk of SLI may also be associated with ASD and ADHD in the same manner. Our results suggest that this is not the case, and we discuss this finding in the context of theories concerning the etiologies of these disorders.
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Affiliation(s)
- Ron Nudel
- Institute of Biological Psychiatry, Mental Health Centre Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark.,iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
| | - Camilla A J Christiani
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark.,Mental Health Centre Copenhagen, University of Copenhagen Hospital, Copenhagen, Denmark
| | - Jessica Ohland
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark.,Mental Health Centre Copenhagen, University of Copenhagen Hospital, Copenhagen, Denmark
| | - Md Jamal Uddin
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark.,Mental Health Centre Copenhagen, University of Copenhagen Hospital, Copenhagen, Denmark.,Section for Biostatistics, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Nicoline Hemager
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark.,Mental Health Centre Copenhagen, University of Copenhagen Hospital, Copenhagen, Denmark
| | - Ditte V Ellersgaard
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark.,Mental Health Centre Copenhagen, University of Copenhagen Hospital, Copenhagen, Denmark
| | - Katrine S Spang
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark.,Mental Health Centre for Child and Adolescent Psychiatry - Research Unit, Mental Health Services in the Capital Region of Denmark, Copenhagen, Denmark
| | - Birgitte K Burton
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark.,Mental Health Centre for Child and Adolescent Psychiatry - Research Unit, Mental Health Services in the Capital Region of Denmark, Copenhagen, Denmark
| | - Aja N Greve
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark.,Psychosis Research Unit, Aarhus University Hospital, Risskov, Denmark
| | - Ditte L Gantriis
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark.,Psychosis Research Unit, Aarhus University Hospital, Risskov, Denmark
| | - Jonas Bybjerg-Grauholm
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark.,Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
| | - Jens Richardt M Jepsen
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark.,Mental Health Centre Copenhagen, University of Copenhagen Hospital, Copenhagen, Denmark.,Mental Health Centre for Child and Adolescent Psychiatry - Research Unit, Mental Health Services in the Capital Region of Denmark, Copenhagen, Denmark.,Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Services in the Capital Region of Denmark, Copenhagen, Denmark
| | - Anne A E Thorup
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark.,Mental Health Centre for Child and Adolescent Psychiatry - Research Unit, Mental Health Services in the Capital Region of Denmark, Copenhagen, Denmark
| | - Ole Mors
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark.,Psychosis Research Unit, Aarhus University Hospital, Risskov, Denmark
| | - Merete Nordentoft
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark.,Mental Health Centre Copenhagen, University of Copenhagen Hospital, Copenhagen, Denmark.,Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Thomas Werge
- Institute of Biological Psychiatry, Mental Health Centre Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark.,iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark.,Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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10
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Gjerdevik M, Haaland ØA, Romanowska J, Lie RT, Jugessur A, Gjessing HK. Parent-of-origin-environment interactions in case-parent triads with or without independent controls. Ann Hum Genet 2017; 82:60-73. [PMID: 29094765 PMCID: PMC5813215 DOI: 10.1111/ahg.12224] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2017] [Accepted: 09/05/2017] [Indexed: 01/31/2023]
Abstract
With case–parent triad data, one can frequently deduce parent of origin of the child's alleles. This allows a parent‐of‐origin (PoO) effect to be estimated as the ratio of relative risks associated with the alleles inherited from the mother and the father, respectively. A possible cause of PoO effects is DNA methylation, leading to genomic imprinting. Because environmental exposures may influence methylation patterns, gene–environment interaction studies should be extended to allow for interactions between PoO effects and environmental exposures (i.e., PoOxE). One should thus search for loci where the environmental exposure modifies the PoO effect. We have developed an extensive framework to analyze PoOxE effects in genome‐wide association studies (GWAS), based on complete or incomplete case–parent triads with or without independent control triads. The interaction approach is based on analyzing triads in each exposure stratum using maximum likelihood estimation in a log‐linear model. Interactions are then tested applying a Wald‐based posttest of parameters across strata. Our framework includes a complete setup for power calculations. We have implemented the models in the R software package Haplin. To illustrate our PoOxE test, we applied the new methodology to top hits from our previous GWAS, assessing whether smoking during the periconceptional period modifies PoO effects on cleft palate only.
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Affiliation(s)
- Miriam Gjerdevik
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway.,Department of Genetic Research and Bioinformatics, Norwegian Institute of Public Health, Oslo, Norway
| | - Øystein A Haaland
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
| | - Julia Romanowska
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway.,Computional Biology Unit, University of Bergen, Bergen, Norway
| | - Rolv T Lie
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway.,Department of Health Registries, Norwegian Institute of Public Health, Oslo, Norway
| | - Astanand Jugessur
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway.,Department of Genetic Research and Bioinformatics, Norwegian Institute of Public Health, Oslo, Norway.,Centre for Fertility and Health (CeFH), Norwegian Institute of Public Health, Oslo, Norway
| | - Håkon K Gjessing
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway.,Centre for Fertility and Health (CeFH), Norwegian Institute of Public Health, Oslo, Norway
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11
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Gao S, Yan Q, Chen L, Song Y, Li J, Fu C, Dong M. Effects of ploidy level and haplotype on variation of photosynthetic traits: Novel evidence from two Fragaria species. PLoS One 2017; 12:e0179899. [PMID: 28644876 PMCID: PMC5482484 DOI: 10.1371/journal.pone.0179899] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2017] [Accepted: 06/06/2017] [Indexed: 12/26/2022] Open
Abstract
To reveal the effects of ploidy level and haplotype on photosynthetic traits, we chose 175 genotypes of wild strawberries belonging to two haplotypes at two types of ploidy levels (diploidy and tetraploidy) and measured photosynthetic traits. Our results revealed that ploidy significantly affected the characteristics of light-response curves, CO2-response curves, and leaf gas exchange parameters, except intercellular CO2 concentration (Ci). Tetraploid species had a lower light saturation point (LSP) and CO2 saturation point (CSP), higher light compensation point (LCP), dark respiration (Rd), and CO2 compensation point (CCP) than diploid species. Furthermore, tetraploid species have lower photosynthetic capacity than diploid species, including net photosynthetic rate (Pn), stomatal conductivity (Gs), and transpiration rate (Tr). In addition, haplotype had a significant effect on LSP, CSP, Tr, and Ci as well as a significant interactive effect between ploidy and haplotype on the maximal photosynethic rate of the light-response curve and Rd. Most of the variance existed within haplotypes among individuals. These results suggest that polyploidization was the main driver for the evolution of photosynthesis with increasing ploidy level (i.e. from diploidy to tetraploidy in Fragaria species), while the origin of a chromosome could also affect the photosynthetic traits and the polyploidization effect on photosynthetic traits.
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Affiliation(s)
- Song Gao
- Key Laboratory of Conservation Biology for Endangered Wildlife of the Ministry of Education, and College of Life Sciences, Zhejiang University, Hangzhou, China
- Research Institute of Zhejiang University-Taizhou, Taizhou, China
- Zhejiang Provincial Key Laboratory of Plant Evolutionary Ecology and Conservation, Taizhou University, Taizhou, China
| | - Qiaodi Yan
- Zhejiang Provincial Key Laboratory of Plant Evolutionary Ecology and Conservation, Taizhou University, Taizhou, China
| | - Luxi Chen
- Zhejiang Provincial Key Laboratory of Plant Evolutionary Ecology and Conservation, Taizhou University, Taizhou, China
| | - Yaobin Song
- Key Laboratory of Hangzhou City for Ecosystem Protection and Restoration, and College of Life and Environmental Sciences, Hangzhou Normal University, Hangzhou, China
| | - Junmin Li
- Zhejiang Provincial Key Laboratory of Plant Evolutionary Ecology and Conservation, Taizhou University, Taizhou, China
| | - Chengxin Fu
- Key Laboratory of Conservation Biology for Endangered Wildlife of the Ministry of Education, and College of Life Sciences, Zhejiang University, Hangzhou, China
| | - Ming Dong
- Key Laboratory of Hangzhou City for Ecosystem Protection and Restoration, and College of Life and Environmental Sciences, Hangzhou Normal University, Hangzhou, China
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12
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Connolly S, Anney R, Gallagher L, Heron EA. A genome-wide investigation into parent-of-origin effects in autism spectrum disorder identifies previously associated genes including SHANK3. Eur J Hum Genet 2017; 25:234-239. [PMID: 27876814 PMCID: PMC5255953 DOI: 10.1038/ejhg.2016.153] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2016] [Revised: 09/28/2016] [Accepted: 10/07/2016] [Indexed: 12/12/2022] Open
Abstract
Autism spectrum disorder (ASD) is known to be a heritable neurodevelopmental disorder affecting more than 1% of the population but in the majority of ASD cases, the genetic cause has not been identified. Parent-of-origin effects have been highlighted as an important mechanism in the pathology of neurodevelopmental disorders such as Prader-Willi and Angelman syndrome, with individuals with these syndromes often exhibiting ASD symptoms. Consequently, systematic investigation of these effects in ASD is clearly an important line of investigation in elucidating the underlying genetic mechanisms. Using estimation of maternal, imprinting and interaction effects using multinomial modelling (EMIM), we simultaneously investigated imprinting, maternal genetic effects and associations in the Autism Genome Project and Simons Simplex Consortium genome-wide association data sets. To avoid using the overly stringent genome-wide association study significance level, we used a Bayesian threshold that takes into account the sample size, allele frequency and any available prior knowledge. Between the two data sets, we identified a total of 18 imprinting effects and 68 maternal genetic effects that met this Bayesian threshold criteria, but none met the threshold in both data sets. We identified imprinting and maternal genetic effects for regions that have previously shown evidence for parent-of-origin effects in ASD. Together with these findings, we have identified maternal genetic effects not previously identified in ASD at a locus in SHANK3 on chromosome 22 and a locus in WBSCR17 on chromosome 7 (associated with Williams syndrome). Both genes have previously been associated with ASD.
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Affiliation(s)
- Siobhan Connolly
- Neuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity College Dublin, Trinity Centre for Health Sciences, Dublin, Ireland
| | - Richard Anney
- Neuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity College Dublin, Trinity Centre for Health Sciences, Dublin, Ireland
- Division of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Hadyn Ellis Building, Cathays, Cardiff, UK
| | - Louise Gallagher
- Neuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity College Dublin, Trinity Centre for Health Sciences, Dublin, Ireland
| | - Elizabeth A Heron
- Neuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity College Dublin, Trinity Centre for Health Sciences, Dublin, Ireland
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13
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Pettigrew KA, Frinton E, Nudel R, Chan MTM, Thompson P, Hayiou-Thomas ME, Talcott JB, Stein J, Monaco AP, Hulme C, Snowling MJ, Newbury DF, Paracchini S. Further evidence for a parent-of-origin effect at the NOP9 locus on language-related phenotypes. J Neurodev Disord 2016; 8:24. [PMID: 27307794 PMCID: PMC4908686 DOI: 10.1186/s11689-016-9157-6] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2015] [Accepted: 06/03/2016] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Specific language impairment (SLI) is a common neurodevelopmental disorder, observed in 5-10 % of children. Family and twin studies suggest a strong genetic component, but relatively few candidate genes have been reported to date. A recent genome-wide association study (GWAS) described the first statistically significant association specifically for a SLI cohort between a missense variant (rs4280164) in the NOP9 gene and language-related phenotypes under a parent-of-origin model. Replications of these findings are particularly challenging because the availability of parental DNA is required. METHODS We used two independent family-based cohorts characterised with reading- and language-related traits: a longitudinal cohort (n = 106 informative families) including children with language and reading difficulties and a nuclear family cohort (n = 264 families) selected for dyslexia. RESULTS We observed association with language-related measures when modelling for parent-of-origin effects at the NOP9 locus in both cohorts: minimum P = 0.001 for phonological awareness with a paternal effect in the first cohort and minimum P = 0.0004 for irregular word reading with a maternal effect in the second cohort. Allelic and parental trends were not consistent when compared to the original study. CONCLUSIONS A parent-of-origin effect at this locus was detected in both cohorts, albeit with different trends. These findings contribute in interpreting the original GWAS report and support further investigations of the NOP9 locus and its role in language-related traits. A systematic evaluation of parent-of-origin effects in genetic association studies has the potential to reveal novel mechanisms underlying complex traits.
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Affiliation(s)
| | - Emily Frinton
- />School of Medicine, University of St Andrews, St Andrews, KY16 9TF UK
| | - Ron Nudel
- />Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN UK
| | - May T. M. Chan
- />Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN UK
- />Worcester College, University of Oxford, Oxford, OX1 2HB UK
| | - Paul Thompson
- />Department of Experimental Psychology, University of Oxford, South Parks Road, Oxford, OX1 3PT UK
| | | | - Joel B. Talcott
- />School of Life and Health Sciences, Aston University, Birmingham, B4 7ET UK
| | - John Stein
- />Department of Physiology, University of Oxford, Parks Road, Oxford, OX1 3PT UK
| | - Anthony P. Monaco
- />Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN UK
| | - Charles Hulme
- />Division of Psychology and Language Sciences, University College London, London, WC1 3PG UK
| | - Margaret J. Snowling
- />Department of Experimental Psychology, University of Oxford, South Parks Road, Oxford, OX1 3PT UK
- />St John’s College, University of Oxford, Oxford, OX1 3JP UK
| | - Dianne F. Newbury
- />Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN UK
| | - Silvia Paracchini
- />School of Medicine, University of St Andrews, St Andrews, KY16 9TF UK
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14
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Paracchini S, Diaz R, Stein J. Advances in Dyslexia Genetics—New Insights Into the Role of Brain Asymmetries. ADVANCES IN GENETICS 2016; 96:53-97. [DOI: 10.1016/bs.adgen.2016.08.003] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
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