scholarly journals The fog of genetics: Known unknowns and unknown unknowns in the genetics of complex traits and diseases

2019 ◽  
Author(s):  
João Pedro de Magalhães ◽  
Jingwei Wang
Keyword(s):  
Genetic Variability ◽  
Genetic Variants ◽  
Genetic Information ◽  
Complex Traits ◽  
Drug Targets ◽  
Molecular Mechanisms ◽  
Genetic Associations ◽  
Missing Heritability ◽  
Genome Space ◽  
Known Unknowns

AbstractAssociating genetic variants with phenotypes is not only important to understand the underlying biology but also to identify potential drug targets for treating diseases. It is widely accepted that for most complex traits many associations remain to be discovered, the so-called “missing heritability.” Yet missing heritability can be estimated, it is a known unknown, and we argue is only a fraction of the unknowns in genetics. The majority of possible genetic variants in the genome space are either too rare to be detected or even entirely absent from populations, and therefore do not contribute to estimates of phenotypic or genetic variability. We call these unknown unknowns in genetics the “fog of genetics.” Using data from the 1000 Genomes Project we then show that larger genes with greater genetic diversity are more likely to be associated with human traits, demonstrating that genetic associations are biased towards particular types of genes and that the genetic information we are lacking about traits and diseases is potentially immense. Our results and model have multiple implications for how genetic variability is perceived to influence complex traits, provide insights on molecular mechanisms of disease and for drug discovery efforts based on genetic information.

scholarly journals Core gene identification using gene expression

2020 ◽  
Author(s):  
◽  
Annique Claringbould
Keyword(s):  
Gene Expression ◽  
Genetic Variation ◽  
Genetic Code ◽  
Genetic Variants ◽  
Complex Traits ◽  
Drug Targets ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Altered Level ◽  
Common Genetic Variants

While humans share most of their genetic code with one another, small differences in the DNA can have an impact on an individual’s risk of disease. Common genetic variants exert individually small effects on the development of a disease, but their combined impact is substantial. Although recent research has identified thousands of variants that are associated to complex traits, our understanding of the molecular mechanisms that eventually lead to disease is limited. One way to dive into the molecular changes that result from genetic variation, is to look at changes in gene activity (‘gene expression’). Each cell contains the same genetic code, but genes are only expressed when and where they are required. Research has shown that many disease-associated genetic variants also affect gene expression. Such a change in the expression of a gene can lead to an altered level of the protein it encodes, which in turn can be the start of a dysregulation in the system that can eventually develop into a disease. This thesis describes how gene expression patterns can be used to prioritise and describe the function of trait-relevant genes. The first chapters evaluate methodological considerations for doing gene expression research. Another study covers the systematic linking of genetic variation to gene expression in blood and the last research chapter describes a method for gene prioritisation that leverages the idea that multiple genetic variants converge onto disease-causing genes. These insights can be used to better understand disease and to identify potential drug targets.

scholarly journals The GTEx Consortium atlas of genetic regulatory effects across human tissues

Science ◽  
2020 ◽  
Vol 369 (6509) ◽  
pp. 1318-1330 ◽  
Author(s):  
Keyword(s):  
Complex Traits ◽  
Molecular Mechanisms ◽  
Tissue Expression ◽  
Genetic Effects ◽  
Regulatory Mechanisms ◽  
Human Tissues ◽  
Genetic Associations ◽  
Key Factor ◽  
Regulatory Effects ◽  
Almost All

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 version 8 data, examining 15,201 RNA-sequencing samples from 49 tissues of 838 postmortem 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.

scholarly journals The GTEx Consortium atlas of genetic regulatory effects across human tissues

2019 ◽  
Author(s):  
François Aguet ◽  
Alvaro N Barbeira ◽  
Rodrigo Bonazzola ◽  
Andrew Brown ◽  
Stephane E Castel ◽  
...  
Keyword(s):  
Complex Traits ◽  
Molecular Mechanisms ◽  
Tissue Expression ◽  
Genetic Effects ◽  
Regulatory Mechanisms ◽  
Human Tissues ◽  
Genetic Associations ◽  
Key Factor ◽  
Regulatory Effects ◽  
Almost All

AbstractThe 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 incisandtrans, 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.

scholarly journals Genetic control of age-related gene expression and complex traits in the human brain

2017 ◽  
Author(s):  
Trevor Martin ◽  
Hunter B. Fraser
Keyword(s):  
Gene Expression ◽  
Human Brain ◽  
Neurodegenerative Diseases ◽  
Genetic Variants ◽  
Complex Traits ◽  
Molecular Mechanisms ◽  
Neurological Diseases ◽  
Expression Patterns ◽  
Related Gene ◽  
Age Related

AbstractAge is the primary risk factor for many of the most common human diseases—particularly neurodegenerative diseases—yet we currently have a very limited understanding of how each individual’s genome affects the aging process. Here we introduce a method to map genetic variants associated with age-related gene expression patterns, which we call temporal expression quantitative trait loci (teQTL). We found that these loci are markedly enriched in the human brain and are associated with neurodegenerative diseases such as Alzheimer’s disease and Creutzfeldt-Jakob disease. Examining potential molecular mechanisms, we found that age-related changes in DNA methylation can explain some cis-acting teQTLs, and that trans-acting teQTLs can be mediated by microRNAs. Our results suggest that genetic variants modifying age-related patterns of gene expression, acting through both cis- and trans-acting molecular mechanisms, could play a role in the pathogenesis of diverse neurological diseases.

scholarly journals Dissecting molecular regulatory mechanisms underlying noncoding susceptibility SNPs associated with 19 autoimmune diseases using multi-omics integrative analysis

2019 ◽  
Author(s):  
Xiao-Feng Chen ◽  
Min-Rui Guo ◽  
Yuan-Yuan Duan ◽  
Feng Jiang ◽  
Hao Wu ◽  
...  
Keyword(s):  
Autoimmune Diseases ◽  
Long Range ◽  
Drug Targets ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Immune Cell ◽  
Drug Application ◽  
Chromatin Interaction ◽  
Genetic Associations ◽  
Functional Variants

AbstractThe genome-wide association studies (GWAS) have identified hundreds of susceptibility loci associated with autoimmune diseases. However, over 90% of risk variants are located in the noncoding regions, leading to great challenges in deciphering the underlying causal functional variants/genes and biological mechanisms. Previous studies focused on developing new scoring method to prioritize functional/disease-relevant variants. However, they principally incorporated annotation data across all cells/tissues while omitted the cell-specific or context-specific regulation. Moreover, limited analyses were performed to dissect the detailed molecular regulatory circuits linking functional GWAS variants to disease etiology. Here we devised a new analysis frame that incorporate hundreds of immune cell-specific multi-omics data to prioritize functional noncoding susceptibility SNPs with gene targets and further dissect their downstream molecular mechanisms and clinical applications for 19 autoimmune diseases. Most prioritized SNPs have genetic associations with transcription factors (TFs) binding, histone modification or chromatin accessibility, indicating their allelic regulatory roles on target genes. Their target genes were significantly enriched in immunologically related pathways and other immunologically related functions. We also detected long-range regulation on 90.7% of target genes including 132 ones exclusively regulated by distal SNPs (eg, CD28, IL2RA), which involves several potential key TFs (eg, CTCF), suggesting the important roles of long-range chromatin interaction in autoimmune diseases. Moreover, we identified hundreds of known or predicted druggable genes, and predicted some new potential drug targets for several autoimmune diseases, including two genes (NFKB1, SH2B3) with known drug indications on other diseases, highlighting their potential drug repurposing opportunities. In summary, our analyses may provide unique resource for future functional follow-up and drug application on autoimmune diseases, which are freely available at http://fngwas.online/.Author SummaryAutoimmune diseases are groups of complex immune system disorders with high prevalence rates and high heritabilities. Previous studies have unraveled thousands of SNPs associated with different autoimmune diseases. However, it remains largely unknown on the molecular mechanisms underlying these genetic associations. Striking, over 90% of risk SNPs are located in the noncoding region. By leveraging multiple immune cell-specific multi-omics data across genomic, epigenetic, transcriptomic and 3D chromatin interaction information, we systematically analyzed the functional variants/genes and biological mechanisms underlying genetic association on 19 autoimmune diseases. We found that most functional SNPs may affect target gene expression through altering transcription factors (TFs) binding, histone modification or chromatin accessibility. Most target genes had known immunological functions. We detected prevailing long-range chromatin interaction linking distal functional SNPs to target genes. We also identified many known drug targets and predicted some new drug target genes for several autoimmune diseases, suggesting their potential clinical applications. All analysis results and tools are available online, which may provide unique resource for future functional follow-up and drug application. Our study may help reduce the gap between traditional genetic findings and biological mechanistically exploration of disease etiologies as well as clinical drug development.

scholarly journals The Genetics of Language

2018 ◽  
pp. 864-898
Author(s):  
Paolo Devanna ◽  
Dan Dediu ◽  
Sonja C. Vernes
Keyword(s):  
Molecular Structure ◽  
Genetic Variants ◽  
Genetic Information ◽  
Molecular Mechanisms ◽  
Genetic Pathways ◽  
Cellular Environment ◽  
Active Regulation ◽  
Multiple Levels ◽  
Human Capacity ◽  
And Function

This chapter discusses the genetic foundations of the human capacity for language. It reviews the molecular structure of the genome and the complex molecular mechanisms that allow genetic information to influence multiple levels of biology. It goes on to describe the active regulation of genes and their formation of complex genetic pathways that in turn control the cellular environment and function. At each of these levels, examples of genes and genetic variants that may influence the human capacity for language are given. Finally, it discusses the value of using animal models to understand the genetic underpinnings of speech and language. From this chapter will emerge the complexity of the genome in action and the multidisciplinary efforts that are currently made to bridge the gap between genetics and language.

scholarly journals Matrix Metalloproteinases as Biomarkers and Treatment Targets in Mesothelioma: A Systematic Review

Biomolecules ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 1272
Author(s):  
Danijela Štrbac ◽  
Vita Dolžan
Keyword(s):  
Genetic Variability ◽  
Genetic Variants ◽  
Drug Targets ◽  
Tumor Tissue ◽  
Asbestos Exposure ◽  
Clinical Parameters ◽  
Metastasis Formation ◽  
Novel Drug ◽  
Mmp Genes ◽  
Novel Drug Targets

Metalloproteinases (MMPs) have an important role in tissue remodeling and have been shown to have an effect on tumor progression, invasion, metastasis formation, and apoptosis in several tumors, including mesothelioma. Mesothelioma is a rare tumor arising from pleura and peritoneum and is frequently associated with asbestos exposure. We have performed a systematic search of PubMed.gov and ClinicalTrials.gov databases to retrieve and review three groups of studies: studies of MMPs expression in tumor tissue or body fluids in patients with mesothelioma, studies of MMPs genetic variability, and studies of MMPs as potential novel drug targets in mesothelioma. Several studies of MMPs in mesothelioma tissues reported a link between higher expression levels of commonly studied MMPs and clinical parameters, such as overall survival. Fewer studies have investigated genetic variability of MMP genes. Nevertheless, these studies suggested that certain genetic variants in MMP genes can have either protective or tumor-promoting effects on mesothelioma patients. MMPs have been also reported as novel drug targets, but so far no clinical trials of MMP inhibitors are registered in mesothelioma. In conclusion, MMPs play an important role in mesothelioma, but further studies are needed to elucidate the potentials of MMPs as biomarkers and drug targets in mesothelioma.

Aggregative trans-eQTL analysis detects trait-specific target gene sets in whole blood

2021 ◽  
Author(s):  
Diptavo Dutta ◽  
Yuan He ◽  
Ashis Saha ◽  
Marios Arvanitis ◽  
Alexis Battle ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Complex Traits ◽  
Association Studies ◽  
Specific Gene ◽  
Eqtl Analysis ◽  
Summary Statistics ◽  
Eqtl Mapping ◽  
Genetic Associations ◽  
Gene Expressions ◽  
Gene Sets

Abstract Large scale genetic association studies have identified many trait-associated variants and understanding the role of these variants in downstream regulation of gene-expressions can uncover important mediating biological mechanisms. In this study, we propose Aggregative tRans assoCiation to detect pHenotype specIfic gEne-sets (ARCHIE), as a method to establish links between sets of known genetic variants associated with a trait and sets of co-regulated gene-expressions through trans associations. ARCHIE employs sparse canonical correlation analysis based on summary statistics from trans-eQTL mapping and genotype and expression correlation matrices constructed from external data sources. A resampling based procedure is then used to test for significant trait-specific trans-association patterns in the background of highly polygenic regulation of gene-expression. Simulation studies show that compared to standard trans-eQTL analysis, ARCHIE is better suited to identify “core”-like genes through which effects of many other genes may be mediated and which can explain disease specific patterns of genetic associations. By applying ARCHIE to available trans-eQTL summary statistics reported by the eQTLGen consortium, we identify 71 gene networks which have significant evidence of trans-association with groups of known genetic variants across 29 complex traits. Around half (50.7%) of the selected genes do not have any strong trans-associations and could not have been detected by standard trans-eQTL mapping. We provide further evidence for causal basis of the target genes through a series of follow-up analyses. These results show ARCHIE is a powerful tool for identifying sets of genes whose trans regulation may be related to specific complex traits. The method has potential for broader applications for identification of networks of various types of molecular traits which mediates complex traits genetic associations.

scholarly journals The contribution of rare whole genome sequencing variants to plasma protein levels and to the missing heritability

2021 ◽  
Author(s):  
Marcin Kierczak ◽  
Nima Rafati ◽  
Julia Höglund ◽  
Hadrien Gourle ◽  
Daniel Schmitz ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Genetic Variants ◽  
Complex Traits ◽  
Rare Variants ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Whole Genome ◽  
Missing Heritability ◽  
Common Genetic Variants

Abstract Despite the success in identifying effects of common genetic variants, using genome-wide association studies (GWAS), much of the genetic contribution to complex traits remains unexplained. Here, we analysed high coverage whole-genome sequencing (WGS) data, to evaluate the contribution of rare genetic variants to 414 plasma proteins. The frequency distribution of genetic variants was skewed towards the rare spectrum, and damaging variants were more often rare. However, only 2.24% of the heritability was estimated to be explained by rare variants. A gene-based approach, developed to also capture the effect of rare variants, identified associations for 249 of the proteins, which was 25% more as compared to a GWAS. Out of those, 24 associations were driven by rare variants, clearly highlighting the capacity of aggregated tests and WGS data. We conclude that, while many rare variants have considerable phenotypic effects, their contribution to the missing heritability is limited by their low frequencies.

scholarly journals Genetic associations of protein-coding variants in human disease

2021 ◽  
Author(s):  
Benjamin B Sun ◽  
Mitja I Kurki ◽  
Christopher N Foley ◽  
Asma Mechakra ◽  
Chia-Yen Chen ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Human Disease ◽  
Drug Targets ◽  
Association Studies ◽  
Single Gene ◽  
Clinical Stage ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Protein Coding ◽  
Disease Associations

Genome-wide association studies (GWAS) have identified thousands of genetic variants linked to the risk of human disease. However, GWAS have thus far remained largely underpowered to identify associations in the rare and low frequency allelic spectrum and have lacked the resolution to trace causal mechanisms to underlying genes. Here, we combined whole exome sequencing in 392,814 UK Biobank participants with imputed genotypes from 260,405 FinnGen participants (653,219 total individuals) to conduct association meta-analyses for 744 disease endpoints across the protein-coding allelic frequency spectrum, bridging the gap between common and rare variant studies. We identified 975 associations, with more than one-third of our findings not reported previously. We demonstrate population-level relevance for mutations previously ascribed to causing single-gene disorders, map GWAS associations to likely causal genes, explain disease mechanisms, and systematically relate disease associations to levels of 117 biomarkers and clinical-stage drug targets. Combining sequencing and genotyping in two population biobanks allowed us to benefit from increased power to detect and explain disease associations, validate findings through replication and propose medical actionability for rare genetic variants. Our study provides a compendium of protein-coding variant associations for future insights into disease biology and drug discovery.

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