| 1. |
- Kanoni, Stavroula, et al.
(författare)
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Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis.
- 2022
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Ingår i: Genome biology. - : Springer Science and Business Media LLC. - 1474-760X .- 1465-6906 .- 1474-7596. ; 23:1
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Tidskriftsartikel (refereegranskat)abstract
- Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery.To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism.Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.
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| 2. |
- Mahajan, Anubha, et al.
(författare)
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Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation
- 2022
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Ingår i: Nature Genetics. - : Springer Nature. - 1061-4036 .- 1546-1718. ; 54:5, s. 560-572
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Tidskriftsartikel (refereegranskat)abstract
- We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 x 10(-9)), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background. Genome-wide association and fine-mapping analyses in ancestrally diverse populations implicate candidate causal genes and mechanisms underlying type 2 diabetes. Trans-ancestry genetic risk scores enhance transferability across populations.
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| 3. |
- Geidenstam, Nina, et al.
(författare)
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Using metabolite profiling to construct and validate a metabolite risk score for predicting future weight gain
- 2019
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 14:9
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Tidskriftsartikel (refereegranskat)abstract
- Background Excess weight gain throughout adulthood can lead to adverse clinical outcomes and are influenced by complex factors that are difficult to measure in free-living individuals. Metabolite profiling offers an opportunity to systematically discover new predictors for weight gain that are relatively easy to measure compared to traditional approaches. Methods and results Using baseline metabolite profiling data of middle-aged individuals from the Framingham Heart Study (FHS; n = 1,508), we identified 42 metabolites associated (p < 0.05) with longitudinal change in body mass index (BMI). We performed stepwise linear regression to select 8 of these metabolites to build a metabolite risk score (MRS) for predicting future weight gain. We replicated the MRS using data from the Mexico City Diabetes Study (MCDS; n = 768), in which one standard deviation increase in the MRS corresponded to ~0.03 increase in BMI (kg/m2) per year (i.e. ~0.09 kg/year for a 1.7 m adult). We observed that none of the available anthropometric, lifestyle, and glycemic variables fully account for the MRS prediction of weight gain. Surprisingly, we found the MRS to be strongly correlated with baseline insulin sensitivity in both cohorts and to be negatively predictive of T2D in MCDS. Genome-wide association study of the MRS identified 2 genome-wide (p < 5 × 10−8) and 5 suggestively (p < 1 × 10−6) significant loci, several of which have been previously linked to obesity-related phenotypes. Conclusions We have constructed and validated a generalizable MRS for future weight gain that is an independent predictor distinct from several other known risk factors. The MRS captures a composite biological picture of weight gain, perhaps hinting at the anabolic effects of preserved insulin sensitivity. Future investigation is required to assess the relationships between MRS-predicted weight gain and other obesity-related diseases.
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| 4. |
- Li, Josephine H., et al.
(författare)
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Identification of Genetic Variation Influencing Metformin Response in a Multiancestry Genome-Wide Association Study in the Diabetes Prevention Program (DPP)
- 2023
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Ingår i: Diabetes. - : American Diabetes Association. - 0012-1797 .- 1939-327X. ; 72:8, s. 1161-1172
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Tidskriftsartikel (refereegranskat)abstract
- Genome-wide significant loci for metformin response in type 2 diabetes reported elsewhere have not been repli-cated in the Diabetes Prevention Program (DPP). To as-sess pharmacogenetic interactions in prediabetes, we conducted a genome-wide association study (GWAS) in the DPP. Cox proportional hazards models tested associations with diabetes incidence in the metformin (MET; n = 876) and placebo (PBO; n = 887) arms. Multiple linear regression assessed association with 1-year change in metformin-related quantitative traits, adjusted for baseline trait, age, sex, and 10 ancestry principal compo-nents. We tested for gene-by-treatment interaction. No significant associations emerged for diabetes inci-dence. We identified four genome-wide significant variants after correcting for correlated traits (P < 9 × 1029). In the MET arm, rs144322333 near ENOSF1 (minor al-lele frequency [MAF]AFR = 0.07; MAFEUR = 0.002) was associated with an increase in percentage of glycated hemoglobin (per minor allele, b = 0.39 [95% CI 0.28, 0.50]; P = 2.8 × 10212). rs145591055 near OMSR (MAF = 0.10 in American Indians) was associated with weight loss (kilograms) (per G allele, b = 27.55 [95% CI 29.88, 25.22]; P = 3.2 × 10210) in the MET arm. Neither variant was significant in PBO; gene-by-treatment interaction was significant for both variants [P(G×T) < 1.0 × 1024 ]. Replication in individuals with diabetes did not yield significant findings. A GWAS for metformin response in prediabetes revealed novel ethnic-specific associations that require further investigation but may have implications for tailored therapy.
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| 5. |
- Miguel-Escalada, Irene, et al.
(författare)
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Human pancreatic islet three-dimensional chromatin architecture provides insights into the genetics of type 2 diabetes
- 2019
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 51:7, s. 1137-1148
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Tidskriftsartikel (refereegranskat)abstract
- Genetic studies promise to provide insight into the molecular mechanisms underlying type 2 diabetes (T2D). Variants associated with T2D are often located in tissue-specific enhancer clusters or super-enhancers. So far, such domains have been defined through clustering of enhancers in linear genome maps rather than in three-dimensional (3D) space. Furthermore, their target genes are often unknown. We have created promoter capture Hi-C maps in human pancreatic islets. This linked diabetes-associated enhancers to their target genes, often located hundreds of kilobases away. It also revealed >1,300 groups of islet enhancers, super-enhancers and active promoters that form 3D hubs, some of which show coordinated glucose-dependent activity. We demonstrate that genetic variation in hubs impacts insulin secretion heritability, and show that hub annotations can be used for polygenic scores that predict T2D risk driven by islet regulatory variants. Human islet 3D chromatin architecture, therefore, provides a framework for interpretation of T2D genome-wide association study (GWAS) signals.
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| 6. |
- Alonso, Lorena, et al.
(författare)
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TIGER : The gene expression regulatory variation landscape of human pancreatic islets
- 2021
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Ingår i: Cell Reports. - : Elsevier BV. - 2211-1247. ; 37:2
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Tidskriftsartikel (refereegranskat)abstract
- Genome-wide association studies (GWASs) identified hundreds of signals associated with type 2 diabetes (T2D). To gain insight into their underlying molecular mechanisms, we have created the translational human pancreatic islet genotype tissue-expression resource (TIGER), aggregating >500 human islet genomic datasets from five cohorts in the Horizon 2020 consortium T2DSystems. We impute genotypes using four reference panels and meta-analyze cohorts to improve the coverage of expression quantitative trait loci (eQTL) and develop a method to combine allele-specific expression across samples (cASE). We identify >1 million islet eQTLs, 53 of which colocalize with T2D signals. Among them, a low-frequency allele that reduces T2D risk by half increases CCND2 expression. We identify eight cASE colocalizations, among which we found a T2D-associated SLC30A8 variant. We make all data available through the TIGER portal (http://tiger.bsc.es), which represents a comprehensive human islet genomic data resource to elucidate how genetic variation affects islet function and translates into therapeutic insight and precision medicine for T2D.
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| 7. |
- Madsen, Lise, et al.
(författare)
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UCP1 induction during recruitment of brown adipocytes in white adipose tissue is dependent on cyclooxygenase activity.
- 2010
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Ingår i: PloS one. - : Public Library of Science (PLoS). - 1932-6203. ; 5:6, s. e11391-
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: The uncoupling protein 1 (UCP1) is a hallmark of brown adipocytes and pivotal for cold- and diet-induced thermogenesis. METHODOLOGY/PRINCIPAL FINDINGS: Here we report that cyclooxygenase (COX) activity and prostaglandin E(2) (PGE(2)) are crucially involved in induction of UCP1 expression in inguinal white adipocytes, but not in classic interscapular brown adipocytes. Cold-induced expression of UCP1 in inguinal white adipocytes was repressed in COX2 knockout (KO) mice and by administration of the COX inhibitor indomethacin in wild-type mice. Indomethacin repressed beta-adrenergic induction of UCP1 expression in primary inguinal adipocytes. The use of PGE(2) receptor antagonists implicated EP(4) as a main PGE(2) receptor, and injection of the stable PGE(2) analog (EP(3/4) agonist) 16,16 dm PGE(2) induced UCP1 expression in inguinal white adipose tissue. Inhibition of COX activity attenuated diet-induced UCP1 expression and increased energy efficiency and adipose tissue mass in obesity-resistant mice kept at thermoneutrality. CONCLUSIONS/SIGNIFICANCE: Our findings provide evidence that induction of UCP1 expression in white adipose tissue, but not in classic interscapular brown adipose tissue is dependent on cyclooxygenase activity. Our results indicate that cyclooxygenase-dependent induction of UCP1 expression in white adipose tissues is important for diet-induced thermogenesis providing support for a surprising role of COX activity in the control of energy balance and obesity development.
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| 8. |
- Merino, Jordi, et al.
(författare)
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Interaction Between Type 2 Diabetes Prevention Strategies and Genetic Determinants of Coronary Artery Disease on Cardiometabolic Risk Factors
- 2020
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Ingår i: Diabetes. - : American Diabetes Association. - 1939-327X .- 0012-1797. ; 69:1, s. 112-120
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Tidskriftsartikel (refereegranskat)abstract
- Coronary artery disease (CAD) is more frequent among individuals with dysglycemia. Preventive interventions for diabetes can improve cardiometabolic risk factors (CRFs), but it is unclear whether the benefits on CRFs are similar for individuals at different genetic risk for CAD. We built a 201-variant polygenic risk score (PRS) for CAD and tested for interaction with diabetes prevention strategies on 1-year changes in CRFs in 2,658 Diabetes Prevention Program (DPP) participants. We also examined whether separate lifestyle behaviors interact with PRS and affect changes in CRFs in each intervention group. Participants in both the lifestyle and metformin interventions had greater improvement in the majority of recognized CRFs compared with placebo (P < 0.001) irrespective of CAD genetic risk (Pinteraction > 0.05). We detected nominal significant interactions between PRS and dietary quality and physical activity on 1-year change in BMI, fasting glucose, triglycerides, and HDL cholesterol in individuals randomized to metformin or placebo, but none of them achieved the multiple-testing correction for significance. This study confirms that diabetes preventive interventions improve CRFs regardless of CAD genetic risk and delivers hypothesis-generating data on the varying benefit of increasing physical activity and improving diet on intermediate cardiovascular risk factors depending on individual CAD genetic risk profile.
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