| 1. |
- Huang, Mi, et al.
(författare)
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Human Genetic Variation at rs10071329 Correlates with Adiposity-related Traits, Modulates PPARGC1B Expression, and Alters Brown Adipocyte Function
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Ingår i: Diabetes. - 1939-327X.
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Tidskriftsartikel (refereegranskat)abstract
- Human genetic variation in PPARGC1B has been associated with adiposity, but the genetic variants that affect PPARGC1B expression have not been experimentally determined. Here, guided by previous observational data, we used CRISPR/Cas9 to scarlessly edit the alleles of the candidate causal genetic variant rs10071329 in a human brown adipocyte cell line (hBAs). Switching the rs10071329 genotype from A/A to G/G enhanced PPARGC1B expression throughout the adipogenic differentiation, identifying rs10071329 as a cis-eQTL. The higher PPARGC1B expression in G/G cells coincided with greater accumulation of triglycerides, and higher expression of mitochondria-encoded genes, but without significant effects on adipogenic marker expression. Furthermore, G/G cells had improved basal- and norepinephrine-stimulated mitochondrial respiration, possibly relating to enhanced mitochondrial gene expression. The G/G cells also exhibited increased norepinephrine-stimulated glycerol release, indicating improved lipolysis. Altogether, our results showed that rs10071329 is a cis-eQTL, with the G/G genotype conferring enhanced PPARGC1B expression, with consequent improved mitochondrial function and response to norepinephrine in brown adipocytes. This genetic variant, and as yet undetermined eQTLs, at PPARGC1B could prove useful in genotype-based precision medicine for obesity treatment.
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| 2. |
- Atabaki-Pasdar, Naeimeh, et al.
(författare)
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Inferring causal pathways between metabolic processes and liver fat accumulation: an IMI DIRECT study
- 2021
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Type 2 diabetes (T2D) and non-alcoholic fatty liver disease (NAFLD) often co-occur. Defining causal pathways underlying this relationship may help optimize the prevention and treatment of both diseases. Thus, we assessed the strength and magnitude of the putative causal pathways linking dysglycemia and fatty liver, using a combination of causal inference methods.Measures of glycemia, insulin dynamics, magnetic resonance imaging (MRI)-derived abdominal and liver fat content, serological biomarkers, lifestyle, and anthropometry were obtained in participants from the IMI DIRECT cohorts (n=795 with new onset T2D and 2234 individuals free from diabetes). UK Biobank (n=3641) was used for modelling and replication purposes. Bayesian networks were employed to infer causal pathways, with causal validation using two-sample Mendelian randomization.Bayesian networks fitted to IMI DIRECT data identified higher basal insulin secretion rate (BasalISR) and MRI-derived excess visceral fat (VAT) accumulation as the features of dysmetabolism most likely to cause liver fat accumulation; the unconditional probability of fatty liver (>5%) increased significantly when conditioning on high levels of BasalISR and VAT (by 23%, 32% respectively; 40% for both). Analyses in UK Biobank yielded comparable results. MR confirmed most causal pathways predicted by the Bayesian networks.Here, BasalISR had the highest causal effect on fatty liver predisposition, providing mechanistic evidence underpinning the established association of NAFLD and T2D. BasalISR may represent a pragmatic biomarker for NAFLD prediction in clinical practice.Competing Interest StatementHR is an employee and shareholder of Sanofi. MIM: The views expressed in this article are those of the author(s) and not necessarily those of the NHS, the NIHR, or the Department of Health. MIM has served on advisory panels for Pfizer, NovoNordisk and Zoe Global, has received honoraria from Merck, Pfizer, Novo Nordisk and Eli Lilly, and research funding from Abbvie, Astra Zeneca, Boehringer Ingelheim, Eli Lilly, Janssen, Merck, NovoNordisk, Pfizer, Roche, Sanofi Aventis, Servier, and Takeda. As of June 2019, MIM is an employee of Genentech, and a holder of Roche stock. AM is a consultant for Lilly and has received research grants from several diabetes drug companies. PWF has received research grants from numerous diabetes drug companies and fess as consultant from Novo Nordisk, Lilly, and Zoe Global Ltd. He is currently the Scientific Director in Patient Care at the Novo Nordisk Foundation. Other authors declare non competing interests.Funding StatementThe work leading to this publication has received support from the Innovative Medicines Initiative Joint Undertaking under grant agreement 115317 (DIRECT) resources of which are composed of financial contribution from the European Union Seventh Framework Programme (FP7/2007-2013) and EFPIA companies in kind contribution. NAP is supported in part by Henning och Johan Throne-Holsts Foundation, Hans Werthen Foundation, an IRC award from the Swedish Foundation for Strategic Research and a European Research Council award ERC-2015-CoG - 681742_NASCENT. HPM is supported by an IRC award from the Swedish Foundation for Strategic Research and a European Research Council award ERC-2015-CoG - 681742_NASCENT. AGJ is supported by an NIHR Clinician Scientist award (17/0005624). RK is funded by the Novo Nordisk Foundation (NNF18OC0031650) as part of a postdoctoral fellowship, an IRC award from the Swedish Foundation for Strategic Research and a European Research Council award ERC-2015-CoG - 681742_NASCENT. AK, PM, HF, JF and GNG are supported by an IRC award from the Swedish Foundation for Strategic Research and a European Research Council award ERC-2015-CoG - 681742_NASCENT. TJM is funded by an NIHR clinical senior lecturer fellowship. S.Bru acknowledges support from the Novo Nordisk Foundation (grants NNF17OC0027594 and NNF14CC0001). ATH is a Wellcome Trust Senior Investigator and is also supported by the NIHR Exeter Clinical Research Facility. JMS acknowledges support from Science for Life Laboratory (Plasma Profiling Facility), Knut and Alice Wallenberg Foundation (Human Protein Atlas) and Erling-Persson Foundation (KTH Centre for Precision Medicine). MIM is supported by the following grants; Wellcome (090532, 098381, 106130, 203141, 212259); NIH (U01-DK105535). PWF is supported by an IRC award from the Swedish Foundation for Strategic Research and a European Research Council award ERC-2015-CoG - 681742_NASCENT. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:Approval for the study protocol was obtained from each of the regional research ethics review boards separately (Lund, Sweden: 20130312105459927, Copenhagen, Denmark: H-1-2012-166 and H-1-2012-100, Amsterdam, Netherlands: NL40099.029.12, Newcastle, Dundee and Exeter, UK: 12/NE/0132), and all participants provided written informed consent at enrolment. The research conformed to the ethical principles for medical research involving human participants outlined in the Declaration of Helsinki.All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAuthors agree to make data and materials supporting the results or analyses presented in their paper available upon reasonable request
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| 3. |
- Coral, Daniel
(författare)
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Characterisation of the genetic discordance between body mass index and type 2 diabetes: a phenome-wide analysis : No 111
- 2020
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Ingår i: Diabetologia. - : Springer Science and Business Media LLC. - 1432-0428 .- 0012-186X. ; 63
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Konferensbidrag (refereegranskat)abstract
- Background and aims: Obesity is on the rise globally, and is a leading risk factor for T2D. However, it is very heterogeneous, with varying degrees of T2D risk within the same levels of BMI. Better classification may lead to improve outcomes of current preventive and therapeutic strategies. Moreover, by elucidating the mechanisms uncoupling obesity from T2D risk, new possible therapeutic targets may emerge. Leveraging the vast amount of genetic data produced to date may contribute to reach these goals while overcoming the obstacles imposed by common assumptions, biases and confounders present in observational studies. Our aim is to compare the phenome-wide association patterns of BMI-increasing genetic profiles that either concordantly increase or discordantly decrease T2D risk. Materials and methods: Highly concordant and highly discordant SNPs between BMI and T2D were obtained from the latest GWAS for both conditions. Their standardized effect sizes (SES) across multiple traits in the phenome, metabolome, proteinome and transcriptome were retrieved from the online genomic repositories. After alignment to the BMI-increasing allele, these effects were organized into a SNP x Trait matrix. A hierarchical clustering technique, combining PCA and Random Forest algorithms was applied, retrieving the optimal number of clusters of traits, organized in order of importance, useful to distinguish a discordant from a concordant SNP. Posterior probabilities of colocalization with T2D were calculated for each gene using transcriptome results. Tissue, biological process, molecular mechanism and cellular component enrichments were evaluated. The predictive potential of GRSs informed by these findings were assessed in the UK Biobank dataset. Results: 121 SNPs were found to be significantly associated with BMI and T2D. 18 were discordant and 104 concordant. A total of 1372 variables were included in the analyses (Phenome = 546, Metabolome = 233, Proteinome = 593). The most important difference between discordant and concordant SNPs in the phenome matrix was found in a cluster of traits led by hypertension (Mean discordant SES = -1.59, Mean concordant SES = 2.56), highly correlated with two clusters led by coronary heart disease and overall health status, respectively. The second most important cluster was led by physical activity-adjusted WHR (Mean discordant SES = -2.69, Mean concordant SES = 0.24). The model obtained from the phenome matrix had the highest classification performance (Matthews Correlation Coefficient, MCC = 0.79). Metabolome results showed differences in polyunsaturated fatty acids and lipid contents in VLDL, but with lower performance (MCC = 0.67). The model from the proteinome matrix was unable to correctly classify SNPs (MCC = -0.03). Two genes (CCDC92 and DNAH10) showed the strongest association within the discordant set in adipose tissue, both involved in cilia formation. A GRS of these 121 SNPs with weights derived from the clusters with high classification performance was highly associated with T2D in both the general and obese populations in UK Biobank (p < 1x1016). Conclusion: The main difference between BMI-increasing genetic profiles that either discordantly decrease or concordantly increase T2D risk is found in hypertension risk and physical activity-adjusted WHR. These traits can be used to inform GRSs to better classify T2D risk in obesity. Molecular mechanisms behind the discordant profile appear to involve cilia formation in the adipose tissue.
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| 4. |
- Coral, Daniel E, et al.
(författare)
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A phenome-wide comparative analysis of genetic discordance between obesity and type 2 diabetes
- 2023
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Ingår i: Nature Metabolism. - : Springer Science and Business Media LLC. - 2522-5812. ; 5:2, s. 237-247
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Tidskriftsartikel (refereegranskat)abstract
- Obesity and type 2 diabetes are causally related, yet there is considerable heterogeneity in the consequences of both conditions and the mechanisms of action are poorly defined. Here we show a genetic-driven approach defining two obesity profiles that convey highly concordant and discordant diabetogenic effects. We annotate and then compare association signals for these profiles across clinical and molecular phenotypic layers. Key differences are identified in a wide range of traits, including cardiovascular mortality, fat distribution, liver metabolism, blood pressure, specific lipid fractions and blood levels of proteins involved in extracellular matrix remodelling. We find marginal differences in abundance of Bacteroidetes and Firmicutes bacteria in the gut. Instrumental analyses reveal prominent causal roles for waist-to-hip ratio, blood pressure and cholesterol content of high-density lipoprotein particles in the development of diabetes in obesity. We prioritize 17 genes from the discordant signature that convey protection against type 2 diabetes in obesity, which may represent logical targets for precision medicine approaches.
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| 5. |
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| 6. |
- Coral, Daniel
(författare)
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Genetic and phenotypic discordance in cardiometabolic diseases
- 2024
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Cardiometabolic conditions such as obesity and type 2 diabetes (T2D) are among the first causes of death globally, and the number of people affected is rapidly increasing. Both conditions are intricately connected and are associated with many life-threatening cardiovascular disease (CVD). However, both obesity and T2D are highly heterogeneous, such that not all individuals with these conditions develop complications, while others are at disproportionatel higher risk. The purpose of this thesis is to improve our understanding of the heterogeneity in cardiometabolic conditions through the application of genetic analyses and machine learning techniques to identify profiles at disproportionately higher or lower risk of complications, providing insights into the mechanisms that give rise to these profiles and their potential clinical implications. In Paper I, I used cross-trait genetic analysis to derive genetically determined obesity profiles that are associated with higher body mass index (BMI) but are either concordantly associated with higher risk of T2D or discordantly associated with T2D protection. Through a comprehensive phenome-wide comparative analysis of these profiles, we highlighted adipose distribution, vascular function and extracelullar matrix remodelling as key mechanisms uncoupling obesity from its diabetogenic risk, and prioritise 17 genes with potential discordant effects in obesity. In Paper II, I reformulated the cross-trait genetic approach from Paper I to construct genetically determined diabetic profiles that are either concordantly associated with higher risk of CVD or discordantly associated with CVD protection. The phenome-wide comparison yields VLDL metabolism as a key mechanism detaching T2D from CVD and 8 loci with cardioprotective effects in T2D that include known targets of current medications, such as statins and GLP-1 receptor agonists. Additionally, I showed through polygenic score analyses (PRS) that quantifying genetic discordance in the general population can aid in CVD risk prediction, improving predictions in 5% of cases and 3% of non-cases. In Paper III, I designed a probabilistic, graph-based clustering ensemble algorithm to identify subgroups of individuals whose levels of common biomarkers of CVD risk deviate from the expected given their body size. We deploy this approach on four large independent cohorts, finding that biomarker deviate substantially from the BMI expectation in ~20% of the general population, and tend to form 5 distinct profiles with specific BMI-biomarker discordance patterns. Considering these discordant profiles can improve CVD prediction with benefits comparable to lipid fraction quantification. In Paper IV, I contributed in an investigation of overall, sex-specific and nonlinear causal effects of BMI on multiple outcomes, including T2D and CVD. We found consistent positive effects of BMI on T2D across sexes, but sex-differential effects on CAD. Evidence of nonlinear effects of BMI were found for lipids and glycaemia. Understanding the mechanisms by which some individuals are at disproportionately higher or lower risk to develop the complications generally associated with obesity and type 2 diabetes can help design better and more precise interventions.
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| 7. |
- Cournia, Zoe, et al.
(författare)
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Membrane Protein Structure, Function, and Dynamics : a Perspective from Experiments and Theory
- 2015
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Ingår i: Journal of Membrane Biology. - : Springer. - 0022-2631 .- 1432-1424. ; 248:4, s. 611-640
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Tidskriftsartikel (refereegranskat)abstract
- Membrane proteins mediate processes that are fundamental for the flourishing of biological cells. Membrane-embedded transporters move ions and larger solutes across membranes; receptors mediate communication between the cell and its environment and membrane-embedded enzymes catalyze chemical reactions. Understanding these mechanisms of action requires knowledge of how the proteins couple to their fluid, hydrated lipid membrane environment. We present here current studies in computational and experimental membrane protein biophysics, and show how they address outstanding challenges in understanding the complex environmental effects on the structure, function, and dynamics of membrane proteins.
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| 8. |
- Huang, Mi, et al.
(författare)
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Engineered allele substitution at PPARGC1A rs8192678 alters human white adipocyte differentiation, lipogenesis, and PGC-1α content and turnover
- 2023
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Ingår i: Diabetologia. - 1432-0428. ; 66:7, s. 1289-1305
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Tidskriftsartikel (refereegranskat)abstract
- Aims/hypothesisPPARGC1A encodes peroxisome proliferator-activated receptor γ coactivator 1-α (PGC-1α), a central regulator of energy metabolism and mitochondrial function. A common polymorphism in PPARGC1A (rs8192678, C/T, Gly482Ser) has been associated with obesity and related metabolic disorders, but no published functional studies have investigated direct allele-specific effects in adipocyte biology. We examined whether rs8192678 is a causal variant and reveal its biological function in human white adipose cells.MethodsWe used CRISPR-Cas9 genome editing to perform an allelic switch (C-to-T or T-to-C) at rs8192678 in an isogenic human pre-adipocyte white adipose tissue (hWAs) cell line. Allele-edited single-cell clones were expanded and screened to obtain homozygous T/T (Ser482Ser), C/C (Gly482Gly) and heterozygous C/T (Gly482Ser) isogenic cell populations, followed by functional studies of the allele-dependent effects on white adipocyte differentiation and mitochondrial function.ResultsAfter differentiation, the C/C adipocytes were visibly less BODIPY-positive than T/T and C/T adipocytes, and had significantly lower triacylglycerol content. The C allele presented a dose-dependent lowering effect on lipogenesis, as well as lower expression of genes critical for adipogenesis, lipid catabolism, lipogenesis and lipolysis. Moreover, C/C adipocytes had decreased oxygen consumption rate (OCR) at basal and maximal respiration, and lower ATP-linked OCR. We determined that these effects were a consequence of a C-allele-driven dysregulation of PGC-1α protein content, turnover rate and transcriptional coactivator activity.Conclusions/interpretationOur data show allele-specific causal effects of the rs8192678 variant on adipogenic differentiation. The C allele confers lower levels of PPARGC1A mRNA and PGC-1α protein, as well as disrupted dynamics of PGC-1α turnover and activity, with downstream effects on cellular differentiation and mitochondrial function. Our study provides the first experimentally deduced insights on the effects of rs8192678 on adipocyte phenotype.
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| 9. |
- Huang, Mi, et al.
(författare)
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Identification of a weight loss-associated causal eQTL in MTIF3 and the effects of MTIF3 deficiency on human adipocyte function
- 2023
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Ingår i: eLife. - 2050-084X.
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Tidskriftsartikel (refereegranskat)abstract
- Genetic variation at the MTIF3 (Mitochondrial Translational Initiation Factor 3) locus has been robustly associated with obesity in humans, but the functional basis behind this association is not known. Here, we applied luciferase reporter assay to map potential functional variants in the haplotype block tagged by rs1885988 and used CRISPR-Cas9 to edit the potential functional variants to confirm the regulatory effects on MTIF3 expression. We further conducted functional studies on MTIF3-deficient differentiated human white adipocyte cell line (hWAs-iCas9), generated through inducible expression of CRISPR-Cas9 combined with delivery of synthetic MTIF3-targeting guide RNA. We demonstrate that rs67785913-centered DNA fragment (in LD with rs1885988, r2 > 0.8) enhances transcription in a luciferase reporter assay, and CRISPR-Cas9-edited rs67785913 CTCT cells show significantly higher MTIF3 expression than rs67785913 CT cells. Perturbed MTIF3 expression led to reduced mitochondrial respiration and endogenous fatty acid oxidation, as well as altered expression of mitochondrial DNA-encoded genes and proteins, and disturbed mitochondrial OXPHOS complex assembly. Furthermore, after glucose restriction, the MTIF3 knockout cells retained more triglycerides than control cells. This study demonstrates an adipocyte function-specific role of MTIF3, which originates in the maintenance of mitochondrial function, providing potential explanations for why MTIF3 genetic variation at rs67785913 is associated with body corpulence and response to weight loss interventions.
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| 10. |
- Huyghe, Jeroen R., et al.
(författare)
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Discovery of common and rare genetic risk variants for colorectal cancer
- 2019
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Ingår i: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 51:1, s. 76-
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Tidskriftsartikel (refereegranskat)abstract
- To further dissect the genetic architecture of colorectal cancer (CRC), we performed whole-genome sequencing of 1,439 cases and 720 controls, imputed discovered sequence variants and Haplotype Reference Consortium panel variants into genome-wide association study data, and tested for association in 34,869 cases and 29,051 controls. Findings were followed up in an additional 23,262 cases and 38,296 controls. We discovered a strongly protective 0.3% frequency variant signal at CHD1. In a combined meta-analysis of 125,478 individuals, we identified 40 new independent signals at P < 5 x 10(-8), bringing the number of known independent signals for CRC to similar to 100. New signals implicate lower-frequency variants, Kruppel-like factors, Hedgehog signaling, Hippo-YAP signaling, long noncoding RNAs and somatic drivers, and support a role for immune function. Heritability analyses suggest that CRC risk is highly polygenic, and larger, more comprehensive studies enabling rare variant analysis will improve understanding of biology underlying this risk and influence personalized screening strategies and drug development.
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