| 1. |
- Agudelo, Leandro Z., et al.
(författare)
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Metabolic resilience is encoded in genome plasticity
- 2021
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Metabolism plays a central role in evolution, as resource conservation is a selective pressure for fitness and survival.Resource-driven adaptations offer a good model to study evolutionary innovation more broadly. It remains unknown howresource-driven optimization of genome function integrates chromatin architecture with transcriptional phase transitions.Here we show that tuning of genome architecture and heterotypic transcriptional condensates mediate resilience tonutrient limitation. Network genomic integration of phenotypic, structural, and functional relationships reveals that fattissue promotes organismal adaptations through metabolic acceleration chromatin domains and heterotypic PGC1Acondensates. We find evolutionary adaptations in several dimensions; low conservation of amino acid residues withinprotein disorder regions, nonrandom chromatin location of metabolic acceleration domains, condensate-chromatin stabilitythrough cis-regulatory anchoring and encoding of genome plasticity in radial chromatin organization. We show thatenvironmental tuning of these adaptations leads to fasting endurance, through efficient nuclear compartmentalization oflipid metabolic regions, and, locally, human-specific burst kinetics of lipid cycling genes. This process reduces oxidativestress, and fatty-acid mediated cellular acidification, enabling endurance of condensate chromatin conformations.Comparative genomics of genetic and diet perturbations reveal mammalian convergence of phenotype and structuralrelationships, along with loss of transcriptional control by diet-induced obesity. Further, we find that radial transcriptionalorganization is encoded in functional divergence of metabolic disease variant-hubs, heterotypic condensate composition,and protein residues sensing metabolic variation. During fuel restriction, these features license the formation of largeheterotypic condensates that buffer proton excess, and shift viscoelasticity for condensate endurance. This mechanismmaintains physiological pH, reduces pH-resilient inflammatory gene programs, and enables genome plasticity throughtranscriptionally driven cell-specific chromatin contacts. In vivo manipulation of this circuit promotes fasting-likeadaptations with heterotypic nuclear compartments, metabolic and cell-specific homeostasis. In sum, we uncover here ageneral principle by which transcription uses environmental fluctuations for genome function, and demonstrate howresource conservation optimizes transcriptional self-organization through robust feedback integrators, highlighting obesityas an inhibitor of genome plasticity relevant for many diseases.
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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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| 4. |
- Chikowore, Tinashe, et al.
(författare)
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GWAS transethnic meta-analysis of BMI in similar to 700k individuals reveals novel gene-smoking interaction in African populations
- 2020
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Ingår i: Genetic Epidemiology. - : John Wiley & Sons. - 0741-0395 .- 1098-2272. ; 44:5, s. 475-476
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Sixty two percent of the 1.12 billion obese people globally reside in low‐middle income countries, 77% of which are in Africa. There is paucity of data on gene‐lifestyle interactions associated with the increasing prevalence of obesity among Africans. We hypothesised that gene‐environment interacting (GEI) variants exhibit heterogenous effects on obesity in transethnic meta‐analysis of marginal SNP associations as a result of modification by an unknown exposure that varies across populations.Body mass index (BMI) genome‐wide association study (GWAS) summary statistics for 678,671 individuals representative of the major global ancestries were aggregated at 21,338,816 SNPs via fixed‐effects meta‐analysis. Lead SNPs attaining genome‐wide significance (P < 5 × 10−8) were tested for heterogeneity in effects between GWAS. Lead SNPs with significant evidence of heterogeneity after Bonferroni correction were then selected for interaction analysis with selected lifestyle factors in an independent AWI‐Gen study of 10,500 African participants. Significant interaction findings were then replicated in 3,177 individuals of African ancestry in the UK Biobank.Of 881 lead SNPs, five had significant heterogenous effects on BMI (P < 5.7 × 10−5). Rs471094, at the CDKAL1 locus had significant interaction with smoking status, which reduced the effect of the BMI raising allele in current smokers (Betaint = −0.949 kg/m2; P int = .002) compared with non‐smokers in AWI‐Gen. This finding was validated in the UK Biobank (Betaint = −1.471 kg/m2, P int = .020; meta‐analysis Betaint = −1.050 kg/m2, P int = .0002). Our results highlight the first gene‐lifestyle interaction on BMI in Africans and demonstrate the utility of transethnic meta‐analysis of GWAS for identifying GEI effects.
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| 5. |
- Franks, Paul W.
(författare)
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Body Weight and Risk of Early Death
- 2013
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Ingår i: Obesity. - : Wiley-Blackwell. - 1930-7381 .- 1930-739X. ; 21:9, s. 1743-1743
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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| 7. |
- Franks, Paul W., et al.
(författare)
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Gene-diet interaction analysis, fine mapping and genomic annotation of the FADS1-2-3 gene cluster reveals regulatory potential in diabetes
- 2017
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Ingår i: Diabetologia. - : Springer. - 0012-186X .- 1432-0428. ; 60:1, s. S163-S163
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Background and aims: Polymorphisms at the fatty acid desaturase gene cluster (FADS1-FADS2-FADS3) have been associated with multiple metabolic and anthropometric traits in Greenlandic Inuit. We systematically assessed whether loci in the FADS region modify the association between dietary fat intake and cardiometabolic traits and functionally annotated top variants to estimate causal loci.Materials and methods: Data analyses consisted of: 1) interaction analyses between the six candidate genetic variants; 2) gene-centric joint analyses to detect interaction signals in the FADS region; 3) haplotype-centric joint tests across 30 haplotype blocks in the FADS1- 3 region to refine interaction signals: 4) functional annotation of top loci. These analyses were undertaken in Swedish adults from the GLACIER Study (N=5,160); data on gene variation (Metabochip array) and height, body weight, fasting and 2hr-glucose, triglycerides, and HDL-, LDL- and total cholesterol were available. Dietary intakes of n3, n-6 and total polyunsaturated fatty acids (PUFA) were calculated from food-frequency questionnaires. Results were adjusted for multiple testing.Results: SNP-level multiplicative interactions were observed between rs174570 and n-6 PUFA intake on fasting glucose (Pinteraction=0.007) and between rs174602 and n-3 PUFA intake on total cholesterol (Pinteraction=0.015). Gene-centric analyses demonstrated evidence for joint main and interaction effects for FADS on body weight (Pn-3.joint = 0.018, Pn-6.joint = 0.021, PPUFA.joint = 0.024) and on BMI (Pn-3.joint = 0.031, Pn-6.joint = 0.029, PPUFA.joint = 0.033) irrespective of types of fatty acid intake. An interaction was detected for FADS1-3 and n-3 PUFA on triglycerides (Pint=0.005). The haplotype analyses revealed three blocks (Pint ≤0.011) that drive the interaction between FADS1-3 and n-3 PUFA on triglycerides. Genomic annotation showed that the rs5792235 variant demonstrated the highest functionality score (Figure).Conclusion: The association between FADS1-3 variants and triglycerides may be modified by PUFA intake. The intronic rs5792235 variant is a potential causal variant in the region. It is likely that the region harbours multiple causal loci.
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| 8. |
- Franks, Paul W., et al.
(författare)
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Interaction Between Exercise and Genetics in Type 2 Diabetes Mellitus : An Epidemiological Perspective
- 2011
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Ingår i: Exercise Genomics. - TOTOWA : Humana Press. - 9781607613541 - 9781607613558 ; , s. 73-100
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Type 2 diabetes mellitus is a heterogeneous disease characterized by an inability to transport glucose from the blood into the cells. The disease has genetic and lifestyle determinants and probably results from the interaction of these risk factors. While this notion is widely accepted and endorsed, the available evidence is far from concrete. In this chapter the evidence that implicates physical inactivity and common genetic variation in type 2 diabetes risk will be described. Then, the fundamental concepts of gene × exercise interactions in type 2 diabetes will be defined by summarizing the evidence from epidemiological studies and clinical trials that have tested related hypotheses. The penultimate section of this chapter discusses the strengths and limitations of existing studies of interaction and outlines some of the common methodological hurdles inherent when testing hypotheses of gene × exercise interactions. The chapter concludes with a short section looking forward to where this field of research is heading and the possibilities for clinical translation.
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| 9. |
- Franks, Paul W., et al.
(författare)
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Interaction Between Physical Activity and Genetic Factors in Complex Metabolic Disease
- 2008
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Ingår i: Energy Metabolism and Obesity. - Totowa : Humana Press. - 9781588296719 - 9781603271394 ; , s. 155-173
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Obesity and diabetes have become increasingly prevalent during the past century. Concomitant with this rise, the consumption of trans-fatty acids and processed carbohydrates is likely to have increased and physical activity levels declined. However, the rates at which obesity and diabetes have increased differ across people of varying ethnicities living in the same environment, suggesting the presence of interaction between ethnic-specific factors, such as genes, and changing environments and lifestyles. Quantifying these interactions is difficult because the interaction effect is often small, and precise measurement of lifestyle factors, such as diet and habitual physical activity, is difficult. Conventional interaction studies aim to test whether the magnitude of the association between the lifestyle exposures and the disease outcome is different in those who carry the variant allele at a given locus by comparison with those who do not. Because exercising skeletal muscle is a major site for glucose and lipid metabolism, variants in the genes that are located within muscle and that are up-regulated in response to physical activity present interesting candidates for testing in studies of gene x physical activity interaction in diabetes. However, numerous methodological limitations seriously hinder attempts to test such hypotheses. This chapter describes (1) a brief review of studies that provide evidence of gene x physical activity interaction in diabetes (and related traits), (2) functional evidence for interaction between genetic factors and physical activity in metabolic dysregulation, and (3) some common methodological issues that face the study of gene x environment interaction in human populations.
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