| 1. |
- Amisten, Stefan, et al.
(författare)
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An atlas of G-protein coupled receptor expression and function in human subcutaneous adipose tissue.
- 2015
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Ingår i: Pharmacology and Therapeutics. - : Elsevier BV. - 0163-7258. ; 146:Sep 19, s. 61-93
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Forskningsöversikt (refereegranskat)abstract
- G-protein coupled receptors (GPCRs) are involved in the regulation of adipose tissue function, but the total number of GPCRs expressed by human subcutaneous adipose tissue, as well as their function and interactions with drugs, is poorly understood. We have constructed an atlas of all GPCRs expressed by human subcutaneous adipose tissue: the 'adipose tissue GPCRome', to support the exploration of novel control nodes in metabolic and endocrine functions. This atlas describes how adipose tissue GPCRs regulate lipolysis, insulin resistance and adiponectin and leptin secretion. We also discuss how adipose tissue GPCRs interact with their endogenous ligands and with GPCR-targeting drugs, with a focus on how drug/receptor interactions may affect lipolysis, and present a model predicting how GPCRs with unknown effects on lipolysis might modulate cAMP-regulated lipolysis. Subcutaneous adipose tissue expresses 163 GPCRs, a majority of which have unknown effects on lipolysis, insulin resistance and adiponectin and leptin secretion. These GPCRs are activated by 180 different endogenous ligands, and are the targets of a large number of clinically used drugs. We identified 119 drugs, acting on 23 GPCRs, that are predicted to stimulate lipolysis and 173 drugs, acting on 25 GPCRs, that are predicted to inhibit lipolysis. This atlas highlights knowledge gaps in the current understanding of adipose tissue GPCR function, and identifies GPCR/ligand/drug interactions that might affect lipolysis, which is important for understanding and predicting metabolic side effects of drugs. This approach may aid in the design of new, safer therapeutic agents, with fewer undesired effects on lipid homeostasis.
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| 2. |
- Corbin, Laura J., et al.
(författare)
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Formalising recall by genotype as an efficient approach to detailed phenotyping and causal inference
- 2018
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 9:1
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Tidskriftsartikel (refereegranskat)abstract
- Detailed phenotyping is required to deepen our understanding of the biological mechanisms behind genetic associations. In addition, the impact of potentially modifiable risk factors on disease requires analytical frameworks that allow causal inference. Here, we discuss the characteristics of Recall-by-Genotype (RbG) as a study design aimed at addressing both these needs. We describe two broad scenarios for the application of RbG: studies using single variants and those using multiple variants. We consider the efficacy and practicality of the RbG approach, provide a catalogue of UK-based resources for such studies and present an online RbG study planner.
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| 3. |
- Flannick, Jason, et al.
(författare)
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Data Descriptor : Sequence data and association statistics from 12,940 type 2 diabetes cases and controls
- 2017
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Ingår i: Scientific Data. - : Springer Science and Business Media LLC. - 2052-4463. ; 4
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Tidskriftsartikel (refereegranskat)abstract
- To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (> 80% of low-frequency coding variants in similar to ~82 K Europeans via the exome chip, and similar to ~90% of low-frequency non-coding variants in similar to ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.
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| 4. |
- Fuchsberger, Christian, et al.
(författare)
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The genetic architecture of type 2 diabetes
- 2016
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 536:7614, s. 41-47
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Tidskriftsartikel (refereegranskat)abstract
- The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of the heritability of this disease. Here, to test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole-genome sequencing in 2,657 European individuals with and without diabetes, and exome sequencing in 12,940 individuals from five ancestry groups. To increase statistical power, we expanded the sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes.
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| 5. |
- Justice, Anne E., et al.
(författare)
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Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution
- 2019
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Ingår i: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 51:3, s. 452-469
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Tidskriftsartikel (refereegranskat)abstract
- Body-fat distribution is a risk factor for adverse cardiovascular health consequences. We analyzed the association of body-fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, with 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries (discovery) and 132,177 European-ancestry individuals (validation). We identified 15 common (minor allele frequency, MAF >= 5%) and nine low-frequency or rare (MAF < 5%) coding novel variants. Pathway/gene set enrichment analyses identified lipid particle, adiponectin, abnormal white adipose tissue physiology and bone development and morphology as important contributors to fat distribution, while cross-trait associations highlight cardiometabolic traits. In functional follow-up analyses, specifically in Drosophila RNAi-knockdowns, we observed a significant increase in the total body triglyceride levels for two genes (DNAH10 and PLXND1). We implicate novel genes in fat distribution, stressing the importance of interrogating low-frequency and protein-coding variants.
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| 6. |
- Kraja, Aldi T., et al.
(författare)
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New Blood Pressure-Associated Loci Identified in Meta-Analyses of 475000 Individuals
- 2017
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Ingår i: Circulation. - : LIPPINCOTT WILLIAMS & WILKINS. - 1942-325X .- 1942-3268. ; 10:5
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Tidskriftsartikel (refereegranskat)abstract
- Background - Genome-wide association studies have recently identified >400 loci that harbor DNA sequence variants that influence blood pressure (BP). Our earlier studies identified and validated 56 single nucleotide variants (SNVs) associated with BP from meta-analyses of exome chip genotype data. An additional 100 variants yielded suggestive evidence of association.Methods and Results - Here, we augment the sample with 140886 European individuals from the UK Biobank, in whom 77 of the 100 suggestive SNVs were available for association analysis with systolic BP or diastolic BP or pulse pressure. We performed 2 meta-analyses, one in individuals of European, South Asian, African, and Hispanic descent (pan-ancestry, approximate to 475000), and the other in the subset of individuals of European descent (approximate to 423000). Twenty-one SNVs were genome-wide significant (P<5x10(-8) ) for BP, of which 4 are new BP loci: rs9678851 (missense, SLC4A1AP), rs7437940 (AFAP1), rs13303 (missense, STAB1), and rs1055144 (7p15.2). In addition, we identified a potentially independent novel BP-associated SNV, rs3416322 (missense, SYNPO2L) at a known locus, uncorrelated with the previously reported SNVs. Two SNVs are associated with expression levels of nearby genes, and SNVs at 3 loci are associated with other traits. One SNV with a minor allele frequency <0.01, (rs3025380 at DBH) was genome-wide significant.Conclusions - We report 4 novel loci associated with BP regulation, and 1 independent variant at an established BP locus. This analysis highlights several candidate genes with variation that alter protein function or gene expression for potential follow-up.
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| 7. |
- Locke, Adam E, et al.
(författare)
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Genetic studies of body mass index yield new insights for obesity biology.
- 2015
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 518:7538, s. 197-401
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Tidskriftsartikel (refereegranskat)abstract
- Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.
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| 8. |
- Lu, Yingchang, et al.
(författare)
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New loci for body fat percentage reveal link between adiposity and cardiometabolic disease risk
- 2016
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- To increase our understanding of the genetic basis of adiposity and its links to cardiometabolic disease risk, we conducted a genome-wide association meta-analysis of body fat percentage (BF%) in up to 100,716 individuals. Twelve loci reached genome-wide significance (P<5 × 10(-8)), of which eight were previously associated with increased overall adiposity (BMI, BF%) and four (in or near COBLL1/GRB14, IGF2BP1, PLA2G6, CRTC1) were novel associations with BF%. Seven loci showed a larger effect on BF% than on BMI, suggestive of a primary association with adiposity, while five loci showed larger effects on BMI than on BF%, suggesting association with both fat and lean mass. In particular, the loci more strongly associated with BF% showed distinct cross-phenotype association signatures with a range of cardiometabolic traits revealing new insights in the link between adiposity and disease risk.
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| 9. |
- Mahajan, Anubha, et al.
(författare)
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Identification and Functional Characterization of G6PC2 Coding Variants Influencing Glycemic Traits Define an Effector Transcript at the G6PC2-ABCB11 Locus.
- 2015
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Ingår i: PLoS Genetics. - : Public Library of Science (PLoS). - 1553-7404 .- 1553-7390. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- Genome wide association studies (GWAS) for fasting glucose (FG) and insulin (FI) have identified common variant signals which explain 4.8% and 1.2% of trait variance, respectively. It is hypothesized that low-frequency and rare variants could contribute substantially to unexplained genetic variance. To test this, we analyzed exome-array data from up to 33,231 non-diabetic individuals of European ancestry. We found exome-wide significant (P<5×10-7) evidence for two loci not previously highlighted by common variant GWAS: GLP1R (p.Ala316Thr, minor allele frequency (MAF)=1.5%) influencing FG levels, and URB2 (p.Glu594Val, MAF = 0.1%) influencing FI levels. Coding variant associations can highlight potential effector genes at (non-coding) GWAS signals. At the G6PC2/ABCB11 locus, we identified multiple coding variants in G6PC2 (p.Val219Leu, p.His177Tyr, and p.Tyr207Ser) influencing FG levels, conditionally independent of each other and the non-coding GWAS signal. In vitro assays demonstrate that these associated coding alleles result in reduced protein abundance via proteasomal degradation, establishing G6PC2 as an effector gene at this locus. Reconciliation of single-variant associations and functional effects was only possible when haplotype phase was considered. In contrast to earlier reports suggesting that, paradoxically, glucose-raising alleles at this locus are protective against type 2 diabetes (T2D), the p.Val219Leu G6PC2 variant displayed a modest but directionally consistent association with T2D risk. Coding variant associations for glycemic traits in GWAS signals highlight PCSK1, RREB1, and ZHX3 as likely effector transcripts. These coding variant association signals do not have a major impact on the trait variance explained, but they do provide valuable biological insights.
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| 10. |
- Mahajan, Anubha, et al.
(författare)
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Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes
- 2018
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Ingår i: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 50:4, s. 559-571
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Tidskriftsartikel (refereegranskat)abstract
- We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10−7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent ‘false leads’ with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.
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