The role of sex in the genomics of human complex traits
TL;DR: Recent insights into the genetic models and mechanisms that lead to sex differences in complex traits are discussed, including genomic evidence for sex-dependent genetic architecture, models and molecular mechanisms of sexually differentiated phenotypes and implications for health care.
Abstract: Nearly all human complex traits and disease phenotypes exhibit some degree of sex differences, including differences in prevalence, age of onset, severity or disease progression. Until recently, the underlying genetic mechanisms of such sex differences have been largely unexplored. Advances in genomic technologies and analytical approaches are now enabling a deeper investigation into the effect of sex on human health traits. In this Review, we discuss recent insights into the genetic models and mechanisms that lead to sex differences in complex traits. This knowledge is critical for developing deeper insight into the fundamental biology of sex differences and disease processes, thus facilitating precision medicine.
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Broad Institute1, University of Chicago2, University of Geneva3, University of Dundee4, Columbia University5, Princeton University6, Max Planck Society7, Johns Hopkins University8, Stanford University9, Vanderbilt University10, University of Cambridge11, Vanderbilt University Medical Center12, Massachusetts Eye and Ear Infirmary13, Harvard University14, Scripps Health15, Polytechnic University of Catalonia16, University of Pennsylvania17
TL;DR: Analysis of the v8 data provides insights into the tissue-specificity of genetic effects, and shows that cell type composition is a key factor in understanding gene regulatory mechanisms in human tissues.
Abstract: The Genotype-Tissue Expression (GTEx) project was established to characterize genetic effects on the transcriptome across human tissues, and to link these regulatory mechanisms to trait and disease associations. Here, we present analyses of the v8 data, based on 17,382 RNA-sequencing samples from 54 tissues of 948 post-mortem donors. We comprehensively characterize genetic associations for gene expression and splicing in cis and trans, showing that regulatory associations are found for almost all genes, and describe the underlying molecular mechanisms and their contribution to allelic heterogeneity and pleiotropy of complex traits. Leveraging the large diversity of tissues, we provide insights into the tissue-specificity of genetic effects, and show that cell type composition is a key factor in understanding gene regulatory mechanisms in human tissues.
1,243 citations
TL;DR: This review summarises the potential use cases for seven common diseases where PRS has or could have clinical utility and summarises open questions regarding PRS usability, ancestry bias, and transferability, emphasising the need for the next wave of studies to focus on the implementation and health-economic value of PRS testing.
Abstract: Prediction of disease risk is an essential part of preventative medicine, often guiding clinical management. Risk prediction typically includes risk factors such as age, sex, family history of disease and lifestyle (e.g. smoking status); however, in recent years, there has been increasing interest to include genomic information into risk models. Polygenic risk scores (PRS) aggregate the effects of many genetic variants across the human genome into a single score and have recently been shown to have predictive value for multiple common diseases. In this review, we summarize the potential use cases for seven common diseases (breast cancer, prostate cancer, coronary artery disease, obesity, type 1 diabetes, type 2 diabetes and Alzheimer's disease) where PRS has or could have clinical utility. PRS analysis for these diseases frequently revolved around (i) risk prediction performance of a PRS alone and in combination with other non-genetic risk factors, (ii) estimation of lifetime risk trajectories, (iii) the independent information of PRS and family history of disease or monogenic mutations and (iv) estimation of the value of adding a PRS to specific clinical risk prediction scenarios. We summarize open questions regarding PRS usability, ancestry bias and transferability, emphasizing the need for the next wave of studies to focus on the implementation and health-economic value of PRS testing. In conclusion, it is becoming clear that PRS have value in disease risk prediction and there are multiple areas where this may have clinical utility.
360 citations
Cites background from "The role of sex in the genomics of ..."
...Many traits, including disease risk, differ by sex and some of that may be partly genetic (78)....
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TL;DR: A roadmap for sex and gender analysis across scientific disciplines is provided and it is called on researchers, funding agencies, peer-reviewed journals and universities to coordinate efforts to implement robust methods of sex andGender analysis.
Abstract: The goal of sex and gender analysis is to promote rigorous, reproducible and responsible science. Incorporating sex and gender analysis into experimental design has enabled advancements across many disciplines, such as improved treatment of heart disease and insights into the societal impact of algorithmic bias. Here we discuss the potential for sex and gender analysis to foster scientific discovery, improve experimental efficiency and enable social equality. We provide a roadmap for sex and gender analysis across scientific disciplines and call on researchers, funding agencies, peer-reviewed journals and universities to coordinate efforts to implement robust methods of sex and gender analysis. The authors discuss the potential for sex and gender analysis to foster scientific discovery, improve experimental efficiency and enable social equality.
297 citations
TL;DR: This Review describes how the recent adoption by a number of funding agencies of policies mandating the incorporation of sex as a biological variable into preclinical research has correlated with an increase in the number of studies investigating sex differences in pain and analgesia.
Abstract: Although most patients with chronic pain are women, the preclinical literature regarding pain processing and the pathophysiology of chronic pain has historically been derived overwhelmingly from the study of male rodents. This Review describes how the recent adoption by a number of funding agencies of policies mandating the incorporation of sex as a biological variable into preclinical research has correlated with an increase in the number of studies investigating sex differences in pain and analgesia. Trends in the field are analysed, with a focus on newly published findings of qualitative sex differences: that is, those findings that are suggestive of differential processing mechanisms in each sex. It is becoming increasingly clear that robust differences exist in the genetic, molecular, cellular and systems-level mechanisms of acute and chronic pain processing in male and female rodents and humans. Historically, preclinical pain research has been dominated by studies in male subjects. Jeffrey Mogil describes recent trends towards the inclusion of male and female subjects in research and the subsequent identification of qualitative sex differences in the mechanisms of pain processing.
291 citations
University of Chicago1, Polytechnic University of Catalonia2, Max Planck Society3, Columbia University4, Princeton University5, Stanford University6, Johns Hopkins University7, University of California, Los Angeles8, University of Geneva9, Scripps Research Institute10, Broad Institute11, Janssen Pharmaceutica12, University of Barcelona13, University of Dundee14, Vanderbilt University Medical Center15, University of Cambridge16, University of Oxford17, Massachusetts Eye and Ear Infirmary18, Pompeu Fabra University19
TL;DR: A catalog of sex differences in gene expression and its genetic regulation across 44 human tissue sources surveyed by the GTEx project (v8 data release), analyzing 16,245 RNA-sequencing samples and genotypes of 838 adult individuals is generated.
Abstract: Many complex human phenotypes exhibit sex-differentiated characteristics. However, the molecular mechanisms underlying these differences remain largely unknown. We generated a catalog of sex differences in gene expression and in the genetic regulation of gene expression across 44 human tissue sources surveyed by the Genotype-Tissue Expression project (GTEx, v8 release). We demonstrate that sex influences gene expression levels and cellular composition of tissue samples across the human body. A total of 37% of all genes exhibit sex-biased expression in at least one tissue. We identify cis expression quantitative trait loci (eQTLs) with sex-differentiated effects and characterize their cellular origin. By integrating sex-biased eQTLs with genome-wide association study data, we identify 58 gene-trait associations that are driven by genetic regulation of gene expression in a single sex. These findings provide an extensive characterization of sex differences in the human transcriptome and its genetic regulation.
281 citations
Cites background from "The role of sex in the genomics of ..."
..., Science 369, eaba3066 (2020) 11 September 2020 9 of 13 Adipose – Subcutaneous (6)...
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...These sex differences have been variously attributed to hormones, sex chromosomes, genotype × sex effects, differences in behavior, and differences in environmental exposures (6), but the mechanisms and underlying biology of the sex differences remain largely unknown....
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...Although we identified a set of X-linked geneswith sex-biased expression acrossmany tissues, the overall sharing of sex-biased expression among tissues was strongly skewed Oliva et al., Science 369, eaba3066 (2020) 11 September 2020 8 of 13 RESEARCH | GENETIC VARIATION Oliva et al., Science 369, eaba3066 (2020) 11 September 2020 9 of 13 Adipose – Subcutaneous (6) Artery – Aorta (1) Brain – Cerebellar Hemisphere (1) Breast – Mammary Tissue (49) Liver (3) Muscle – Skeletal (13) Skin –...
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References
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TL;DR: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations, and has reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-generation sequencing, deep exome sequencing, and dense microarray genotyping.
Abstract: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.
12,661 citations
TL;DR: Associations at DRD2 and several genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses.
Abstract: Schizophrenia is a highly heritable disorder. Genetic risk is conferred by a large number of alleles, including common alleles of small effect that might be detected by genome-wide association studies. Here we report a multi-stage schizophrenia genome-wide association study of up to 36,989 cases and 113,075 controls. We identify 128 independent associations spanning 108 conservatively defined loci that meet genome-wide significance, 83 of which have not been previously reported. Associations were enriched among genes expressed in brain, providing biological plausibility for the findings. Many findings have the potential to provide entirely new insights into aetiology, but associations at DRD2 and several genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses. Independent of genes expressed in brain, associations were enriched among genes expressed in tissues that have important roles in immunity, providing support for the speculated link between the immune system and schizophrenia.
6,809 citations
TL;DR: It is found that local genetic variation affects gene expression levels for the majority of genes, and inter-chromosomal genetic effects for 93 genes and 112 loci are identified, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease.
Abstract: Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease.
3,289 citations
TL;DR: It is emphasized that sex is a biological variable that should be considered in immunological studies and contribute to variations in the incidence of autoimmune diseases and malignancies, susceptibility to infectious diseases and responses to vaccines in males and females.
Abstract: Males and females differ in their immunological responses to foreign and self-antigens and show distinctions in innate and adaptive immune responses. Certain immunological sex differences are present throughout life, whereas others are only apparent after puberty and before reproductive senescence, suggesting that both genes and hormones are involved. Furthermore, early environmental exposures influence the microbiome and have sex-dependent effects on immune function. Importantly, these sex-based immunological differences contribute to variations in the incidence of autoimmune diseases and malignancies, susceptibility to infectious diseases and responses to vaccines in males and females. Here, we discuss these differences and emphasize that sex is a biological variable that should be considered in immunological studies.
3,214 citations
TL;DR: This work introduces a technique—cross-trait LD Score regression—for estimating genetic correlation that requires only GWAS summary statistics and is not biased by sample overlap, and uses this method to estimate 276 genetic correlations among 24 traits.
Abstract: Identifying genetic correlations between complex traits and diseases can provide useful etiological insights and help prioritize likely causal relationships. The major challenges preventing estimation of genetic correlation from genome-wide association study (GWAS) data with current methods are the lack of availability of individual-level genotype data and widespread sample overlap among meta-analyses. We circumvent these difficulties by introducing a technique-cross-trait LD Score regression-for estimating genetic correlation that requires only GWAS summary statistics and is not biased by sample overlap. We use this method to estimate 276 genetic correlations among 24 traits. The results include genetic correlations between anorexia nervosa and schizophrenia, anorexia and obesity, and educational attainment and several diseases. These results highlight the power of genome-wide analyses, as there currently are no significantly associated SNPs for anorexia nervosa and only three for educational attainment.
2,993 citations