Genetic effects on gene expression across human tissues

groups, Enhancing GTEx; Fund, N; Nhgri,; Resource—VARI, Biospecimen Core; Study, Elsi; Visualization—EBI, Genome Browser Data Integration; analysts, Lead; Battle, Alexis; Brown, Andrew Anand; Engelhardt, Barbara E.; Montgomery, Stephen B.

doi:10.1038/nature24277

Cited by 3,677 publications

(2,635 citation statements)

References 81 publications

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“…This has proven a difficult challenge, as a result of linkage disequilibrium60. Practically, because eQTL are very common, and many variants show association to disease in a locus, it is likely that at least some variants associated with disease will also have eQTL evidence for a nearby gene 61. Several methods have been proposed to address this colocalisation issue,59, 62 each of which aims to compare GWAS and eQTL data to identify pleiotropic effects between them.…”

Section: Identifying Causal Variants and Pathogenic Genesmentioning

confidence: 99%

Genome‐wide association studies of multiple sclerosis

Cotsapas¹,

Mitrovič

2018

Clin & Trans Imm

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Large‐scale genetic studies of multiple sclerosis have identified over 230 risk effects across the human genome, making it a prototypical common disease with complex genetic architecture. Here, after a brief historical background on the discovery and definition of the disease, we summarise the last fifteen years of genetic discoveries and map out the challenges that remain to translate these findings into an aetiological framework and actionable clinical understanding.

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Section: Identifying Causal Variants and Pathogenic Genesmentioning

confidence: 99%

Genome‐wide association studies of multiple sclerosis

Cotsapas¹,

Mitrovič

2018

Clin & Trans Imm

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“…30 The other signal on chromosome 17 is statistically more convincing: the index variant ( rs4889908 ) is common (minor allele frequency=28.5%), its imputation quality is high (rsq_hat=0.96), and many SNPs in high LD are genome‐wide significant at the same locus (Figure 3). rs4889908 and its strong LD proxies are not eQTLs in GTEx and do not establish physical interactions with nonadjacent chromosomal regions 29, 30. However, rs35636768 , which is in strong LD with the index rs4889908 variant ( r 2 =0.98 in French Canadians) maps to a DNAse I hypersensitive region in human CD14 + monocytes 28.…”

Section: Resultsmentioning

confidence: 99%

“…Therefore, this could represent a false‐positive association. Bioinformatic annotation of the variant yielded little insights: rs75657792 has no strong LD proxies ( r 2 >0.8), is not an eQTL in GTEx, and does not map to a regulatory sequence defined using histone tail epigenomic marks 28, 29. However, the chromosomal region surrounding rs75657792 does interact physically with PLB1 , a gene that encodes a membrane‐associated phospholipase and that is located 98 kb downstream, as assessed using Hi‐C technology in the human liver (Figure S1).…”

Section: Resultsmentioning

confidence: 99%

“…20 For these 58 genes, we retrieved from our meta‐analyses, association results for coding variants (missense, nonsense, and essential splice site) as well as variants annotated as eQTLs in the GTEx database 29. In total, we found 11 significant association signals from 6 different loci: missense variants for LIPG , APOA4 , and APOE , a nonsense variant for LPL , and eQTLs for LIPC and PLTP (Table 3).…”

Section: Resultsmentioning

confidence: 99%

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Variants at the APOE/C1/C2/C4 Locus Modulate Cholesterol Efflux Capacity Independently of High‐Density Lipoprotein Cholesterol

Low‐Kam

Rhainds

et al. 2018

JAHA

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BackgroundMacrophage cholesterol efflux to high‐density lipoproteins (HDLs) is the first step of reverse cholesterol transport. The cholesterol efflux capacity (CEC) of HDL particles is a protective risk factor for coronary artery disease independent of HDL cholesterol levels. Using a genome‐wide association study approach, we aimed to identify pathways that regulate CEC in humans.Methods and ResultsWe measured CEC in 5293 French Canadians. We tested the genetic association between 4 CEC measures and genotypes at >9 million common autosomal DNA sequence variants. These analyses yielded 10 genome‐wide significant signals (P<6.25×10−9) representing 7 loci. Five of these loci harbor genes with important roles in lipid biology (CETP,LIPC,LPL,APOA1/C3/A4/A5, and APOE /C1/C2/C4). Except for the APOE/C1/C2/C4 variant (rs141622900, P nonadjusted=1.0×10−11; P adjusted=8.8×10−9), the association signals disappear when correcting for HDL cholesterol and triglyceride levels. The additional 2 significant signals were near the PPP1CB/PLB1 and RBFOX3/ENPP7 genes. In secondary analyses, we considered candidate functional variants for 58 genes implicated in HDL biology, as well as 239 variants associated with blood lipid levels and/or coronary artery disease risk by genome‐wide association study. These analyses identified 27 significant CEC associations, implicating 5 additional loci (GCKR,LIPG,PLTP,PPARA, and TRIB1).ConclusionsOur genome‐wide association study identified common genetic variation at the APOE/C1/C2/C4 locus as a major determinant of CEC that acts largely independently of HDL cholesterol. We predict that HDL‐based therapies aiming at increasing CEC will be modulated by changes in the expression of apolipoproteins in this gene cluster.

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“…One of the first global approaches is the GTEx project. GTEx explores the landscape of gene expression across 54 different tissues, providing the richest catalog of tissue-specific and shared eQTL (Ardlie et al, 2015;GTEx Consortium, 2017). It was already used in the analyses of expression patterns of introgressed haplotypes in the recent studies conducted by McCoy et al (2017) and Dannemann et al (2017).…”

Section: Discussionmentioning

confidence: 99%

Evolutionary and Medical Consequences of Archaic Introgression into Modern Human Genomes

Dolgova

Lao

2018

Preprint

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The demographic history of anatomically modern humans (AMH) involves multiple migration events, population extinctions and genetic adaptations. As genome-wide data from complete genome sequencing becomes increasingly abundant and available even from extinct hominins, new insights of the evolutionary history of our species are discovered.It is currently known that AMH introgressed with archaic hominins once they left the African continent. Current out of African human genomes carry fragments of archaic origin. This review focuses on the fitness consequences of archaic interbreeding in current human populations. We discuss new insights and challenges that researchers face when interpreting the potential impact of introgression on fitness and testing hypotheses about the role of selection within the context of health and disease.Keywords: archaic introgression, fitness, natural selection, Neanderthal, Denisova, anatomically modern humans. Peer-reviewed version available at Genes 2018, 9, 358; doi:10.3390/genes9070358 2 Widespread interbreeding between homininsThe demographic history of anatomically modern humans (AMH) is complex, and involves a large number of migrations, genetic admixtures and introgressions, population extinctions and genetic adaptations, which overlap both in time and in space (see Figure 1). Due to this complexity, the evolutionary history of humankind is still far from being fully understood (Nielsen et al., 2017). During the last 30 years, the most accepted demographic scenario for explaining recent evolution of AMH has been the Out of Africa model (OOA). According to this model, AMH evolved in Africa around 100-200 thousands years ago (kya) in East Africa and migrated to the rest of the world. Classical "pure" OOA assumes that admixture with other archaic populations such as Neanderthals or Denisovans, present at the time of the rise of AMH, either did not occur or was negligible (Lalueza-Fox & Gilbert, 2011). Figure 1. Family tree of the four groups of early humans living in Eurasia 50,000 years ago and the inferred gene flow between the groups due to interbreeding (based on Prüfer et al., 2014;Mondal et al., 2016;Hsieh et al., 2016; Medina-Gomez et al., 2017). The direction and estimated magnitude of inferred gene flow events are shown. Branch lengths and timing of gene flows are not scaled. The dashed line indicates that it is uncertain whether Denisovan gene flow into modern humans in mainland Asia occurred directly or via Oceania. Light violet color indicates introgression events from unknown archaic populations (Ghost).However, genomic studies of ancient DNA have revealed that AMH interbred with other hominid lineages, such as Neanderthals and Denisovans, present in Eurasia up to ∼30,000-50,000 years ago Quach & Quintana-Murci, 2017;Vattathil & Akey, 2015 New studies based on current genetic diversity are suggesting that the events of archaic introgression in AMH did occur out of Africa with other hidden "ghost" archaic populations (Mondal et al., 2016). Furthermore, there i...

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Genetic effects on gene expression across human tissues

Cited by 3,677 publications

References 81 publications

Genome‐wide association studies of multiple sclerosis

Genome‐wide association studies of multiple sclerosis

Variants at the APOE/C1/C2/C4 Locus Modulate Cholesterol Efflux Capacity Independently of High‐Density Lipoprotein Cholesterol

Evolutionary and Medical Consequences of Archaic Introgression into Modern Human Genomes

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