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1.
Neuropsychopharmacol Hung ; 21(2): 69-84, 2019 Jun.
Artigo em Húngaro | MEDLINE | ID: mdl-31378724

RESUMO

IQ is a psychological indicator with exceptional psychometric properties and substantial real-life predictive power. Behavior genetic results have long suggested that IQ is strongly heritable, that is, inter-individual IQ differences are mostly due to genetic differences, and that the effects of the environment shared by siblings, such as the family's place of residence or socioeconomic status, is minimal. Recently these observations were confirmed by quantitative genetic studies of unprecedented sample sizes, SNP heritability studies combining quantitative and molecular genetic approaches, and genome-wide association studies identifying specific genetic variants underlying IQ. Genome-wide association studies enable the creation of polygenic scores which correlate with actual cognitive ability at approximately r=0.3. The increasing understanding of the genetic basis of IQ, especially the use of polygenic scores validates previous quantitative genetic paradigms and clears the path for several applications in psychology, but it may also be the source of bioethical dilemmas.


Assuntos
Estudo de Associação Genômica Ampla , Humanos , Testes de Inteligência , Herança Multifatorial , Polimorfismo de Nucleotídeo Único
2.
Mol Biol (Mosk) ; 53(4): 574-599, 2019.
Artigo em Russo | MEDLINE | ID: mdl-31397433

RESUMO

Pharmacogenetics (PG) investigates the inherited variants of the human genome that underlie individual differences in drug metabolic transformation, delivery, and mechanism of action. Not only the contributions of individual genes, but also their cumulative effect should be considered in the case of polygenic diseases, which include the majority of human diseases. Multiple sclerosis (MS) is a severe autoimmune neurodegenerative disorder of the central nervous system (CNS) and is polygenic in nature. Understanding the role that the immune system plays in the pathogenesis of MS helped to design drugs for its pathogenetic therapy. These drugs are known as the disease-modifying treatments (DMTs). Among these are interferon ß (IFN-ß) and glatiramer acetate (GA), whose treatment efficacy and long-term safety have been proven in many clinical trials. However their efficacy on MS course varies from highly effective to lack of response. Prognostic genetic biomarkers of treatment efficacy can help to identify the MS patient groups where a particular drug is preferential or even strictly indicated to use. The review summarizes the findings from pharmacogenetic studies evaluating the efficacy of IFN-ß and GA in MS patients, including the author's original data.


Assuntos
Herança Multifatorial/genética , Esclerose Múltipla/tratamento farmacológico , Esclerose Múltipla/genética , Farmacogenética , Medicina de Precisão , Marcadores Genéticos , Acetato de Glatiramer/uso terapêutico , Humanos , Interferon beta/uso terapêutico
3.
Hum Genet ; 138(10): 1155-1169, 2019 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-31342140

RESUMO

Vitamin D inadequacy, assessed by 25-hydroxyvitamin D [25(OH)D], affects around 50% of adults in the United States and is associated with numerous adverse health outcomes. Blood 25(OH)D concentrations are influenced by genetic factors that may determine how much vitamin D intake is required to reach optimal 25(OH)D. Despite large genome-wide association studies (GWASs), only a small portion of the genetic factors contributing to differences in 25(OH)D has been discovered. Therefore, knowledge of a fuller set of genetic factors could be useful for risk prediction of 25(OH)D inadequacy, personalized vitamin D supplementation, and prevention of downstream morbidity and mortality. Using PRSice and weights from published African- and European-ancestry GWAS summary statistics, ancestry-specific polygenic scores (PGSs) were created to capture a more complete set of genetic factors in those of European (n = 9569) or African ancestry (n = 2761) from three cohort studies. The PGS for African ancestry was derived using all input SNPs (a p value cutoff of 1.0) and had an R2 of 0.3%; for European ancestry, the optimal PGS used a p value cutoff of 3.5 × 10-4 in the target/tuning dataset and had an R2 of 1.0% in the validation cohort. Those with highest genetic risk had 25(OH)D that was 2.8-3.0 ng/mL lower than those with lowest genetic risk (p = 0.0463-3.2 × 10-13), requiring an additional 467-500 IU of vitamin D intake to maintain equivalent 25(OH)D. PGSs are a powerful predictive tool that could be leveraged for personalized vitamin D supplementation to prevent the negative downstream effects of 25(OH)D inadequacy.


Assuntos
Grupo com Ancestrais do Continente Africano/genética , Grupo com Ancestrais do Continente Europeu/genética , Genética Populacional , Padrões de Herança , Herança Multifatorial , Polimorfismo de Nucleotídeo Único , Vitamina D/análogos & derivados , Estudos de Coortes , Bases de Dados Genéticas , Suplementos Nutricionais , Feminino , Estudo de Associação Genômica Ampla , Humanos , Masculino , Pessoa de Meia-Idade , Raios Ultravioleta , Vitamina D/sangue
4.
Nat Commun ; 10(1): 3009, 2019 07 08.
Artigo em Inglês | MEDLINE | ID: mdl-31285442

RESUMO

Quantitative genetics theory predicts that X-chromosome dosage compensation (DC) will have a detectable effect on the amount of genetic and therefore phenotypic trait variances at associated loci in males and females. Here, we systematically examine the role of DC in humans in 20 complex traits in a sample of more than 450,000 individuals from the UK Biobank and 1600 gene expression traits from a sample of 2000 individuals as well as across-tissue gene expression from the GTEx resource. We find approximately twice as much X-linked genetic variation across the UK Biobank traits in males (mean h2SNP = 0.63%) compared to females (mean h2SNP = 0.30%), confirming the predicted DC effect. Our DC estimates for complex traits and gene expression are consistent with a small proportion of genes escaping X-inactivation in a trait- and tissue-dependent manner. Finally, we highlight examples of biologically relevant X-linked heterogeneity between the sexes that bias DC estimates if unaccounted for.


Assuntos
Genes Ligados ao Cromossomo X/genética , Loci Gênicos/genética , Variação Genética/genética , Herança Multifatorial/genética , Inativação do Cromossomo X/genética , Conjuntos de Dados como Assunto , Feminino , Estudo de Associação Genômica Ampla , Humanos , Masculino , Modelos Genéticos , Fenótipo , Fatores Sexuais
5.
Nat Commun ; 10(1): 2417, 2019 06 03.
Artigo em Inglês | MEDLINE | ID: mdl-31160569

RESUMO

Accumulating evidence from genome wide association studies (GWAS) suggests an abundance of shared genetic influences among complex human traits and disorders, such as mental disorders. Here we introduce a statistical tool, MiXeR, which quantifies polygenic overlap irrespective of genetic correlation, using GWAS summary statistics. MiXeR results are presented as a Venn diagram of unique and shared polygenic components across traits. At 90% of SNP-heritability explained for each phenotype, MiXeR estimates that 8.3 K variants causally influence schizophrenia and 6.4 K influence bipolar disorder. Among these variants, 6.2 K are shared between the disorders, which have a high genetic correlation. Further, MiXeR uncovers polygenic overlap between schizophrenia and educational attainment. Despite a genetic correlation close to zero, the phenotypes share 8.3 K causal variants, while 2.5 K additional variants influence only educational attainment. By considering the polygenicity, discoverability and heritability of complex phenotypes, MiXeR analysis may improve our understanding of cross-trait genetic architectures.


Assuntos
Transtorno Bipolar/genética , Modelos Genéticos , Modelos Estatísticos , Herança Multifatorial , Esquizofrenia/genética , Frequência do Gene , Estudo de Associação Genômica Ampla , Humanos , Desequilíbrio de Ligação
6.
Nat Neurosci ; 22(7): 1066-1074, 2019 07.
Artigo em Inglês | MEDLINE | ID: mdl-31209380

RESUMO

Cannabis is the most frequently used illicit psychoactive substance worldwide; around one in ten users become dependent. The risk for cannabis use disorder (CUD) has a strong genetic component, with twin heritability estimates ranging from 51 to 70%. Here we performed a genome-wide association study of CUD in 2,387 cases and 48,985 controls, followed by replication in 5,501 cases and 301,041 controls. We report a genome-wide significant risk locus for CUD (P = 9.31 × 10-12) that replicates in an independent population (Preplication = 3.27 × 10-3, Pmeta-analysis = 9.09 × 10-12). The index variant (rs56372821) is a strong expression quantitative trait locus for cholinergic receptor nicotinic α2 subunit (CHRNA2); analyses of the genetically regulated gene expression identified a significant association of CHRNA2 expression with CUD in brain tissue. At the polygenic level, analyses revealed a significant decrease in the risk of CUD with increased load of variants associated with cognitive performance. The results provide biological insights and inform on the genetic architecture of CUD.


Assuntos
Abuso de Maconha/genética , Proteínas do Tecido Nervoso/fisiologia , Receptores Nicotínicos/fisiologia , Idade de Início , Alelos , Transtorno do Deficit de Atenção com Hiperatividade/genética , Encéfalo/metabolismo , Estudos de Casos e Controles , Cromossomos Humanos Par 8/genética , Cognição/fisiologia , Estudos de Coortes , Fatores de Confusão (Epidemiologia) , Dinamarca , Escolaridade , Feminino , Perfilação da Expressão Gênica , Predisposição Genética para Doença , Estudo de Associação Genômica Ampla , Humanos , Islândia , Masculino , Herança Multifatorial , Proteínas do Tecido Nervoso/biossíntese , Proteínas do Tecido Nervoso/genética , Polimorfismo de Nucleotídeo Único , Locos de Características Quantitativas , Receptores Nicotínicos/biossíntese , Receptores Nicotínicos/genética , Esquizofrenia/genética , Fumar/genética , Transcriptoma
7.
BMC Bioinformatics ; 20(Suppl 12): 313, 2019 Jun 20.
Artigo em Inglês | MEDLINE | ID: mdl-31216978

RESUMO

BACKGROUND: Schizophrenia and autism are examples of polygenic diseases caused by a multitude of genetic variants, many of which are still poorly understood. Recently, both diseases have been associated with disrupted neuron motility and migration patterns, suggesting that aberrant cell motility is a phenotype for these neurological diseases. RESULTS: We formulate the POLYGENIC DISEASE PHENOTYPE Problem which seeks to identify candidate disease genes that may be associated with a phenotype such as cell motility. We present a machine learning approach to solve this problem for schizophrenia and autism genes within a brain-specific functional interaction network. Our method outperforms peer semi-supervised learning approaches, achieving better cross-validation accuracy across different sets of gold-standard positives. We identify top candidates for both schizophrenia and autism, and select six genes labeled as schizophrenia positives that are predicted to be associated with cell motility for follow-up experiments. CONCLUSIONS: Candidate genes predicted by our method suggest testable hypotheses about these genes’ role in cell motility regulation, offering a framework for generating predictions for experimental validation.


Assuntos
Movimento Celular/genética , Doença/genética , Redes Reguladoras de Genes , Herança Multifatorial/genética , Algoritmos , Transtorno Autístico/genética , Estudos de Associação Genética , Humanos , Aprendizado de Máquina , Fenótipo , Curva ROC , Reprodutibilidade dos Testes , Esquizofrenia/genética
8.
J Headache Pain ; 20(1): 72, 2019 Jun 21.
Artigo em Inglês | MEDLINE | ID: mdl-31226929

RESUMO

BACKGROUND: Migraine is a complex neurovascular disorder with a strong genetic component. There are rare monogenic forms of migraine, as well as more common polygenic forms; research into the genes involved in both types has provided insights into the many contributing genetic factors. This review summarises advances that have been made in the knowledge and understanding of the genes and genetic variations implicated in migraine etiology. FINDINGS: Migraine is characterised into two main types, migraine without aura (MO) and migraine with aura (MA). Hemiplegic migraine is a rare monogenic MA subtype caused by mutations in three main genes - CACNA1A, ATP1A2 and SCN1A - which encode ion channel and transport proteins. Functional studies in cellular and animal models show that, in general, mutations result in impaired glutamatergic neurotransmission and cortical hyperexcitability, which make the brain more susceptible to cortical spreading depression, a phenomenon thought to coincide with aura symptoms. Variants in other genes encoding ion channels and solute carriers, or with roles in regulating neurotransmitters at neuronal synapses, or in vascular function, can also cause monogenic migraine, hemiplegic migraine and related disorders with overlapping symptoms. Next-generation sequencing will accelerate the finding of new potentially causal variants and genes, with high-throughput bioinformatics analysis methods and functional analysis pipelines important in prioritising, confirming and understanding the mechanisms of disease-causing variants. With respect to common migraine forms, large genome-wide association studies (GWAS) have greatly expanded our knowledge of the genes involved, emphasizing the role of both neuronal and vascular pathways. Dissecting the genetic architecture of migraine leads to greater understanding of what underpins relationships between subtypes and comorbid disorders, and may have utility in diagnosis or tailoring treatments. Further work is required to identify causal polymorphisms and the mechanism of their effect, and studies of gene expression and epigenetic factors will help bridge the genetics with migraine pathophysiology. CONCLUSIONS: The complexity of migraine disorders is mirrored by their genetic complexity. A comprehensive knowledge of the genetic factors underpinning migraine will lead to improved understanding of molecular mechanisms and pathogenesis, to enable better diagnosis and treatments for migraine sufferers.


Assuntos
Transtornos de Enxaqueca/genética , Animais , Depressão Alastrante da Atividade Elétrica Cortical/genética , Estudo de Associação Genômica Ampla , Humanos , Enxaqueca com Aura/fisiopatologia , Herança Multifatorial/genética , Mutação , Canal de Sódio Disparado por Voltagem NAV1.1/genética
9.
J Dairy Sci ; 102(8): 7237-7247, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31155255

RESUMO

Relatedness between reference and test animals has an important effect on the reliability of genomic prediction for test animals. Because genomic prediction has been widely applied in practical cattle breeding and bulls have been selected according to genomic breeding value without progeny testing, the sires or grandsires of candidates might not have phenotypic information and might not be in the reference population when the candidates are selected. The objective of this study was to investigate the decreasing trend of the reliability of genomic prediction given distant reference populations, using genomic best linear unbiased prediction (GBLUP) and Bayesian variable selection models with or without including the quantitative trait locus (QTL) markers detected from sequencing data. The data used in this study consisted of 22,242 bulls genotyped using the 54K SNP array from EuroGenomics. Among them, 1,444 Danish bulls born from 2006 to 2010 were selected as test animals. Different reference populations with varying relationships to test animals were created according to pedigree-based relationships. The reference individuals having a relationship with one or more test animals higher than 0.4 (scenario ρ < 0.4), 0.2 (ρ < 0.2), or 0.1 (ρ < 0.1, where ρ = relationship coefficient) were removed from reference sets; these represented the distance between reference and test animals being 2 generations, 3 generations, and 4 generations, respectively. Imputed whole-genome sequencing data of bulls from Denmark were used to conduct a genome-wide association study (GWAS). A small number of significant variants (QTL markers) from the GWAS were added to the array data. To compare the effects of different models, the basic GBLUP model, a Bayesian selection variable model, a GBLUP model with 2 components of genetic effects, and a Bayesian model with pooled array data and QTL markers were used for estimating genomic estimated breeding values (GEBV) of test animals. The reliability of genomic prediction decreased when the test animals were more generations away from the reference population. The reliability of genomic prediction was 0.461 for 1 generation away and 0.396 for 3 generations away, with the same number of individuals in the reference set, using a GBLUP model with chip markers only. The results showed that using the Bayesian method and QTL markers improved the reliability of genomic prediction in all scenarios of relationship between test and reference animals, in a range of 1.3% and 65.1% (4 generations away with only 841 individuals in the reference set). However, most gains were for predictions of milk yield and fat yield. There was little improvement for predictions of protein yield and mastitis, and no improvement for prediction of fertility, except for scenario ρ < 0.1, in which there was a large improvement for predictions of all traits. On the other hand, models including more than 10% polygenic effect decreased prediction reliability when the relationship between test and reference animals was distant.


Assuntos
Teorema de Bayes , Bovinos/genética , Estudo de Associação Genômica Ampla/veterinária , Mastite Bovina/genética , Leite/metabolismo , Locos de Características Quantitativas/genética , Animais , Cruzamento , Dinamarca , Feminino , Fertilidade/genética , Marcadores Genéticos/genética , Genômica , Genótipo , Masculino , Herança Multifatorial/genética , Linhagem , Fenótipo , Reprodutibilidade dos Testes
10.
PLoS Genet ; 15(4): e1007973, 2019 04.
Artigo em Inglês | MEDLINE | ID: mdl-30946739

RESUMO

Facial attractiveness is a complex human trait of great interest in both academia and industry. Literature on sociological and phenotypic factors associated with facial attractiveness is rich, but its genetic basis is poorly understood. In this paper, we conducted a genome-wide association study to discover genetic variants associated with facial attractiveness using 4,383 samples in the Wisconsin Longitudinal Study. We identified two genome-wide significant loci, highlighted a handful of candidate genes, and demonstrated enrichment for heritability in human tissues involved in reproduction and hormone synthesis. Additionally, facial attractiveness showed strong and negative genetic correlations with BMI in females and with blood lipids in males. Our analysis also suggested sex-specific selection pressure on variants associated with lower male attractiveness. These results revealed sex-specific genetic architecture of facial attractiveness and provided fundamental new insights into its genetic basis.


Assuntos
Beleza , Face/anatomia & histologia , Variação Genética , Adolescente , Alelos , Feminino , Estudo de Associação Genômica Ampla , Humanos , Estudos Longitudinais , Masculino , Herança Multifatorial , Polimorfismo de Nucleotídeo Único , Caracteres Sexuais
11.
PLoS Genet ; 15(4): e1008009, 2019 04.
Artigo em Inglês | MEDLINE | ID: mdl-30951530

RESUMO

Recent and classical work has revealed biologically and medically significant subtypes in complex diseases and traits. However, relevant subtypes are often unknown, unmeasured, or actively debated, making automated statistical approaches to subtype definition valuable. We propose reverse GWAS (RGWAS) to identify and validate subtypes using genetics and multiple traits: while GWAS seeks the genetic basis of a given trait, RGWAS seeks to define trait subtypes with distinct genetic bases. Unlike existing approaches relying on off-the-shelf clustering methods, RGWAS uses a novel decomposition, MFMR, to model covariates, binary traits, and population structure. We use extensive simulations to show that modelling these features can be crucial for power and calibration. We validate RGWAS in practice by recovering a recently discovered stress subtype in major depression. We then show the utility of RGWAS by identifying three novel subtypes of metabolic traits. We biologically validate these metabolic subtypes with SNP-level tests and a novel polygenic test: the former recover known metabolic GxE SNPs; the latter suggests subtypes may explain substantial missing heritability. Crucially, statins, which are widely prescribed and theorized to increase diabetes risk, have opposing effects on blood glucose across metabolic subtypes, suggesting the subtypes have potential translational value.


Assuntos
Estudo de Associação Genômica Ampla/métodos , Modelos Genéticos , Herança Multifatorial , Fenótipo , Algoritmos , Glicemia/efeitos dos fármacos , Glicemia/genética , Análise por Conglomerados , Simulação por Computador , Doença das Coronárias/sangue , Doença das Coronárias/tratamento farmacológico , Doença das Coronárias/genética , Transtorno Depressivo Maior/classificação , Transtorno Depressivo Maior/genética , Diabetes Mellitus Tipo 2/sangue , Diabetes Mellitus Tipo 2/tratamento farmacológico , Diabetes Mellitus Tipo 2/genética , Estudo de Associação Genômica Ampla/estatística & dados numéricos , Humanos , Inibidores de Hidroximetilglutaril-CoA Redutases/farmacologia , Lipídeos/sangue , Polimorfismo de Nucleotídeo Único , Estado Pré-Diabético/genética , Locos de Características Quantitativas
12.
PLoS Genet ; 15(4): e1007954, 2019 04.
Artigo em Inglês | MEDLINE | ID: mdl-31009456

RESUMO

One of the main outcomes of quantitative genetics approaches to natural variation is to reveal the genetic architecture underlying the phenotypic space. Complex genetic architectures are described as including numerous loci (or alleles) with small-effect and/or low-frequency in the populations, interactions with the genetic background, environment or age. Linkage or association mapping strategies will be more or less sensitive to this complexity, so that we still have an unclear picture of its extent. By combining high-throughput phenotyping under two environmental conditions with classical QTL mapping approaches in multiple Arabidopsis thaliana segregating populations as well as advanced near isogenic lines construction and survey, we have attempted to improve our understanding of quantitative phenotypic variation. Integrative traits such as those related to vegetative growth used in this work (highlighting either cumulative growth, growth rate or morphology) all showed complex and dynamic genetic architecture with respect to the segregating population and condition. The more resolutive our mapping approach, the more complexity we uncover, with several instances of QTLs visible in near isogenic lines but not detected with the initial QTL mapping, indicating that our phenotyping accuracy was less limiting than the mapping resolution with respect to the underlying genetic architecture. In an ultimate approach to resolve this complexity, we intensified our phenotyping effort to target specifically a 3Mb-region known to segregate for a major quantitative trait gene, using a series of selected lines recombined every 100kb. We discovered that at least 3 other independent QTLs had remained hidden in this region, some with trait- or condition-specific effects, or opposite allelic effects. If we were to extrapolate the figures obtained on this specific region in this particular cross to the genome- and species-scale, we would predict hundreds of causative loci of detectable phenotypic effect controlling these growth-related phenotypes.


Assuntos
Arabidopsis/crescimento & desenvolvimento , Arabidopsis/genética , Mapeamento Cromossômico , Cruzamentos Genéticos , Epistasia Genética , Variação Genética , Genoma de Planta , Endogamia , Herança Multifatorial , Fenótipo , Brotos de Planta/genética , Brotos de Planta/crescimento & desenvolvimento , Locos de Características Quantitativas , Recombinação Genética
13.
PLoS Genet ; 15(4): e1008060, 2019 04.
Artigo em Inglês | MEDLINE | ID: mdl-31022172

RESUMO

The promise of personalized genomic medicine is that knowledge of a person's gene sequences and activity will facilitate more appropriate medical interventions, particularly drug prescriptions, to reduce the burden of disease. Early successes in oncology and pediatrics have affirmed the power of positive diagnosis and are mostly based on detection of one or a few mutations that drive the specific pathology. However, genetically more complex diseases require the development of polygenic risk scores (PRSs) that have variable accuracy. The rarity of events often means that they have necessarily low precision: many called positives are actually not at risk, and only a fraction of cases are prevented by targeted therapy. In some situations, negative prediction may better define the population at low risk. Here, I review five conditions across a broad spectrum of chronic disease (opioid pain medication, hypertension, type 2 diabetes, major depression, and osteoporotic bone fracture), considering in each case how genetic prediction might be used to target drug prescription. This leads to a call for more research designed to evaluate genetic likelihood of response to therapy and a call for evaluation of PRS, not just in terms of sensitivity and specificity but also with respect to potential clinical efficacy.


Assuntos
Herança Multifatorial , Medicina de Precisão/métodos , Transtorno Depressivo Maior/tratamento farmacológico , Transtorno Depressivo Maior/genética , Diabetes Mellitus Tipo 2/tratamento farmacológico , Diabetes Mellitus Tipo 2/genética , Feminino , Humanos , Hipertensão/tratamento farmacológico , Hipertensão/genética , Masculino , Mutação , Transtornos Relacionados ao Uso de Opioides/genética , Transtornos Relacionados ao Uso de Opioides/prevenção & controle , Osteoporose/genética , Osteoporose/prevenção & controle , Testes Farmacogenômicos/métodos , Medicina Preventiva/métodos , Fatores de Risco
14.
Nat Commun ; 10(1): 1776, 2019 04 16.
Artigo em Inglês | MEDLINE | ID: mdl-30992449

RESUMO

Polygenic risk scores (PRS) have shown promise in predicting human complex traits and diseases. Here, we present PRS-CS, a polygenic prediction method that infers posterior effect sizes of single nucleotide polymorphisms (SNPs) using genome-wide association summary statistics and an external linkage disequilibrium (LD) reference panel. PRS-CS utilizes a high-dimensional Bayesian regression framework, and is distinct from previous work by placing a continuous shrinkage (CS) prior on SNP effect sizes, which is robust to varying genetic architectures, provides substantial computational advantages, and enables multivariate modeling of local LD patterns. Simulation studies using data from the UK Biobank show that PRS-CS outperforms existing methods across a wide range of genetic architectures, especially when the training sample size is large. We apply PRS-CS to predict six common complex diseases and six quantitative traits in the Partners HealthCare Biobank, and further demonstrate the improvement of PRS-CS in prediction accuracy over alternative methods.


Assuntos
Predisposição Genética para Doença , Modelos Genéticos , Herança Multifatorial/genética , Característica Quantitativa Herdável , Artrite Reumatoide/diagnóstico , Artrite Reumatoide/genética , Teorema de Bayes , Neoplasias da Mama/diagnóstico , Neoplasias da Mama/genética , Simulação por Computador , Doença da Artéria Coronariana/diagnóstico , Doença da Artéria Coronariana/genética , Bases de Dados Genéticas/estatística & dados numéricos , Depressão/diagnóstico , Depressão/genética , Diabetes Mellitus Tipo 2/diagnóstico , Diabetes Mellitus Tipo 2/genética , Feminino , Estudo de Associação Genômica Ampla , Humanos , Doenças Inflamatórias Intestinais/diagnóstico , Doenças Inflamatórias Intestinais/genética , Desequilíbrio de Ligação/genética , Masculino , Polimorfismo de Nucleotídeo Único/genética , Fatores de Risco
15.
Hum Genet ; 138(4): 425-435, 2019 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-30941497

RESUMO

Heritability is the most commonly used measure of genetic contribution to disease outcomes. Being the fraction of the variance of latent trait liability attributable to genetic factors, heritability of binary traits is a difficult technical concept that is sometimes misinterpreted as the more-easily understandable concept of attributable fraction. In this paper we use the liability threshold model to describe the analytical relationship between heritability and attributable fraction. Towards this end, we consider a hypothetical intervention that is aimed to reduce the genetic risk of the disease for a specified target group of the population. We show how the relation between the heritability and the attributable fraction depends on the disease prevalence, the intervention effect and the size of the target group. We use two real examples to illustrate the practical implications of our theoretical results.


Assuntos
Predisposição Genética para Doença/epidemiologia , Modelos Genéticos , Modelos Estatísticos , Herança Multifatorial , Característica Quantitativa Herdável , Causalidade , Doença/etiologia , Doença/genética , Humanos , Fenótipo , Densidade Demográfica , Prevalência , Fatores de Risco , Tamanho da Amostra
16.
Genetics ; 211(4): 1131-1141, 2019 04.
Artigo em Inglês | MEDLINE | ID: mdl-30967442

RESUMO

In this Review, we focus on the similarity of the concepts underlying prediction of estimated breeding values (EBVs) in livestock and polygenic risk scores (PRS) in humans. Our research spans both fields and so we recognize factors that are very obvious for those in one field, but less so for those in the other. Differences in family size between species is the wedge that drives the different viewpoints and approaches. Large family size achievable in nonhuman species accompanied by selection generates a smaller effective population size, increased linkage disequilibrium and a higher average genetic relationship between individuals within a population. In human genetic analyses, we select individuals unrelated in the classical sense (coefficient of relationship <0.05) to estimate heritability captured by common SNPs. In livestock data, all animals within a breed are to some extent "related," and so it is not possible to select unrelated individuals and retain a data set of sufficient size to analyze. These differences directly or indirectly impact the way data analyses are undertaken. In livestock, genetic segregation variance exposed through samplings of parental genomes within families is directly observable and taken for granted. In humans, this genomic variation is under-recognized for its contribution to variation in polygenic risk of common disease, in both those with and without family history of disease. We explore the equation that predicts the expected proportion of variance explained using PRS, and quantify how GWAS sample size is the key factor for maximizing accuracy of prediction in both humans and livestock. Last, we bring together the concepts discussed to address some frequently asked questions.


Assuntos
Estudo de Associação Genômica Ampla/métodos , Gado/genética , Herança Multifatorial , Característica Quantitativa Herdável , Animais , Big Data , Cruzamento/métodos , Humanos
18.
Nat Commun ; 10(1): 1499, 2019 04 02.
Artigo em Inglês | MEDLINE | ID: mdl-30940813

RESUMO

Alcohol consumption level and alcohol use disorder (AUD) diagnosis are moderately heritable traits. We conduct genome-wide association studies of these traits using longitudinal Alcohol Use Disorder Identification Test-Consumption (AUDIT-C) scores and AUD diagnoses in a multi-ancestry Million Veteran Program sample (N = 274,424). We identify 18 genome-wide significant loci: 5 associated with both traits, 8 associated with AUDIT-C only, and 5 associated with AUD diagnosis only. Polygenic Risk Scores (PRS) for both traits are associated with alcohol-related disorders in two independent samples. Although a significant genetic correlation reflects the overlap between the traits, genetic correlations for 188 non-alcohol-related traits differ significantly for the two traits, as do the phenotypes associated with the traits' PRS. Cell type group partitioning heritability enrichment analyses also differentiate the two traits. We conclude that, although heavy drinking is a key risk factor for AUD, it is not a sufficient cause of the disorder.


Assuntos
Consumo de Bebidas Alcoólicas/genética , Alcoolismo/genética , Estudo de Associação Genômica Ampla , Adulto , Idoso , Idoso de 80 Anos ou mais , Feminino , Humanos , Estudos Longitudinais , Masculino , Pessoa de Meia-Idade , Herança Multifatorial , Fenótipo , Polimorfismo de Nucleotídeo Único , Adulto Jovem
19.
J Dairy Sci ; 102(6): 5279-5294, 2019 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-30981488

RESUMO

The variance of gametic diversity ( σgamete2) can be used to find individuals that more likely produce progeny with extreme breeding values. The aim of this study was to obtain this variance for individuals from routine genomic evaluations, and to apply gametic variance in a selection criterion in conjunction with breeding values to improve genetic progress. An analytical approach was developed to estimate σgamete2 by the sum of binomial variances of all individual quantitative trait loci across the genome. Simulation was used to verify the predictability of this variance in a range of scenarios. The accuracy of prediction ranged from 0.49 to 0.85, depending on the scenario and model used. Compared with sequence data, SNP data are sufficient for estimating σgamete2 Results also suggested that markers with low minor allele frequency and the covariance between markers should be included in the estimation. To incorporate σgamete2 into selective breeding programs, we proposed a new index, relative predicted transmitting ability, which better utilizes the genetic potential of individuals than traditional predicted transmitting ability. Simulation with a small genome showed an additional genetic gain of up to 16% in 10 generations, depending on the number of quantitative trait loci and selection intensity. Finally, we applied σgamete2 to the US genomic evaluations for Holstein and Jersey cattle. As expected, the DGAT1 gene had a strong effect on the estimation of σgamete2 for several production traits. However, inbreeding had a small impact on gametic variability, with greater effect for more polygenic traits. In conclusion, gametic variance, a potentially important parameter for selection programs, can be easily computed and is useful for improving genetic progress and controlling genetic diversity.


Assuntos
Cruzamento , Bovinos/genética , Células Germinativas , Seleção Genética , Animais , Frequência do Gene , Marcadores Genéticos , Genômica/métodos , Endogamia , Masculino , Modelos Genéticos , Herança Multifatorial , Locos de Características Quantitativas
20.
Nat Rev Genet ; 20(6): 320-321, 2019 06.
Artigo em Inglês | MEDLINE | ID: mdl-31024085
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