| 1. |
- Bar, N., et al.
(författare)
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A reference map of potential determinants for the human serum metabolome
- 2020
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Ingår i: Nature. - : Nature Research. - 0028-0836 .- 1476-4687. ; 588:7836, s. 135-140
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Tidskriftsartikel (refereegranskat)abstract
- The serum metabolome contains a plethora of biomarkers and causative agents of various diseases, some of which are endogenously produced and some that have been taken up from the environment1. The origins of specific compounds are known, including metabolites that are highly heritable2,3, or those that are influenced by the gut microbiome4, by lifestyle choices such as smoking5, or by diet6. However, the key determinants of most metabolites are still poorly understood. Here we measured the levels of 1,251 metabolites in serum samples from a unique and deeply phenotyped healthy human cohort of 491 individuals. We applied machine-learning algorithms to predict metabolite levels in held-out individuals on the basis of host genetics, gut microbiome, clinical parameters, diet, lifestyle and anthropometric measurements, and obtained statistically significant predictions for more than 76% of the profiled metabolites. Diet and microbiome had the strongest predictive power, and each explained hundreds of metabolites—in some cases, explaining more than 50% of the observed variance. We further validated microbiome-related predictions by showing a high replication rate in two geographically independent cohorts7,8 that were not available to us when we trained the algorithms. We used feature attribution analysis9 to reveal specific dietary and bacterial interactions. We further demonstrate that some of these interactions might be causal, as some metabolites that we predicted to be positively associated with bread were found to increase after a randomized clinical trial of bread intervention. Overall, our results reveal potential determinants of more than 800 metabolites, paving the way towards a mechanistic understanding of alterations in metabolites under different conditions and to designing interventions for manipulating the levels of circulating metabolites.
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| 2. |
- Koivula, Robert W., et al.
(författare)
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The role of physical activity in metabolic homeostasis before and after the onset of type 2 diabetes : an IMI DIRECT study
- 2020
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Ingår i: Diabetologia. - : Springer Nature. - 0012-186X .- 1432-0428. ; 63:4, s. 744-756
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Tidskriftsartikel (refereegranskat)abstract
- Aims/hypothesis: It is well established that physical activity, abdominal ectopic fat and glycaemic regulation are related but the underlying structure of these relationships is unclear. The previously proposed twin-cycle hypothesis (TC) provides a mechanistic basis for impairment in glycaemic control through the interactions of substrate availability, substrate metabolism and abdominal ectopic fat accumulation. Here, we hypothesise that the effect of physical activity in glucose regulation is mediated by the twin-cycle. We aimed to examine this notion in the Innovative Medicines Initiative Diabetes Research on Patient Stratification (IMI DIRECT) Consortium cohorts comprised of participants with normal or impaired glucose regulation (cohort 1: N ≤ 920) or with recently diagnosed type 2 diabetes (cohort 2: N ≤ 435). Methods: We defined a structural equation model that describes the TC and fitted this within the IMI DIRECT dataset. A second model, twin-cycle plus physical activity (TC-PA), to assess the extent to which the effects of physical activity in glycaemic regulation are mediated by components in the twin-cycle, was also fitted. Beta cell function, insulin sensitivity and glycaemic control were modelled from frequently sampled 75 g OGTTs (fsOGTTs) and mixed-meal tolerance tests (MMTTs) in participants without and with diabetes, respectively. Abdominal fat distribution was assessed using MRI, and physical activity through wrist-worn triaxial accelerometry. Results are presented as standardised beta coefficients, SE and p values, respectively. Results: The TC and TC-PA models showed better fit than null models (TC: χ2 = 242, p = 0.004 and χ2 = 63, p = 0.001 in cohort 1 and 2, respectively; TC-PA: χ2 = 180, p = 0.041 and χ2 = 60, p = 0.008 in cohort 1 and 2, respectively). The association of physical activity with glycaemic control was primarily mediated by variables in the liver fat cycle. Conclusions/interpretation: These analyses partially support the mechanisms proposed in the twin-cycle model and highlight mechanistic pathways through which insulin sensitivity and liver fat mediate the association between physical activity and glycaemic control.
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| 3. |
- Allesøe, Rosa Lundbye, et al.
(författare)
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Discovery of drug–omics associations in type 2 diabetes with generative deep-learning models
- 2023
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Ingår i: Nature Biotechnology. - : Springer Nature. - 1087-0156 .- 1546-1696. ; 41:3, s. 399-408
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Tidskriftsartikel (refereegranskat)abstract
- The application of multiple omics technologies in biomedical cohorts has the potential to reveal patient-level disease characteristics and individualized response to treatment. However, the scale and heterogeneous nature of multi-modal data makes integration and inference a non-trivial task. We developed a deep-learning-based framework, multi-omics variational autoencoders (MOVE), to integrate such data and applied it to a cohort of 789 people with newly diagnosed type 2 diabetes with deep multi-omics phenotyping from the DIRECT consortium. Using in silico perturbations, we identified drug–omics associations across the multi-modal datasets for the 20 most prevalent drugs given to people with type 2 diabetes with substantially higher sensitivity than univariate statistical tests. From these, we among others, identified novel associations between metformin and the gut microbiota as well as opposite molecular responses for the two statins, simvastatin and atorvastatin. We used the associations to quantify drug–drug similarities, assess the degree of polypharmacy and conclude that drug effects are distributed across the multi-omics modalities.
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| 4. |
- Li, Yafang, et al.
(författare)
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Genome-wide interaction analysis identified low-frequency variants with sex disparity in lung cancer risk
- 2022
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Ingår i: Human Molecular Genetics. - : Oxford University Press. - 0964-6906 .- 1460-2083. ; 31:16, s. 2831-2843
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Tidskriftsartikel (refereegranskat)abstract
- Differences by sex in lung cancer incidence and mortality have been reported which cannot be fully explained by sex differences in smoking behavior, implying existence of genetic and molecular basis for sex disparity in lung cancer development. However, the information about sex dimorphism in lung cancer risk is quite limited despite the great success in lung cancer association studies. By adopting a stringent two-stage analysis strategy, we performed a genome-wide gene-sex interaction analysis using genotypes from a lung cancer cohort including ~ 47 000 individuals with European ancestry. Three low-frequency variants (minor allele frequency < 0.05), rs17662871 [odds ratio (OR) = 0.71, P = 4.29×10-8); rs79942605 (OR = 2.17, P = 2.81×10-8) and rs208908 (OR = 0.70, P = 4.54×10-8) were identified with different risk effect of lung cancer between men and women. Further expression quantitative trait loci and functional annotation analysis suggested rs208908 affects lung cancer risk through differential regulation of Coxsackie virus and adenovirus receptor gene expression in lung tissues between men and women. Our study is one of the first studies to provide novel insights about the genetic and molecular basis for sex disparity in lung cancer development.
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| 5. |
- Obura, Morgan, et al.
(författare)
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Post-load glucose subgroups and associated metabolic traits in individuals with type 2 diabetes : An IMI-DIRECT study
- 2020
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 15:11
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Tidskriftsartikel (refereegranskat)abstract
- AIM: Subclasses of different glycaemic disturbances could explain the variation in characteristics of individuals with type 2 diabetes (T2D). We aimed to examine the association between subgroups based on their glucose curves during a five-point mixed-meal tolerance test (MMT) and metabolic traits at baseline and glycaemic deterioration in individuals with T2D. METHODS: The study included 787 individuals with newly diagnosed T2D from the Diabetes Research on Patient Stratification (IMI-DIRECT) Study. Latent class trajectory analysis (LCTA) was used to identify distinct glucose curve subgroups during a five-point MMT. Using general linear models, these subgroups were associated with metabolic traits at baseline and after 18 months of follow up, adjusted for potential confounders. RESULTS: At baseline, we identified three glucose curve subgroups, labelled in order of increasing glucose peak levels as subgroup 1-3. Individuals in subgroup 2 and 3 were more likely to have higher levels of HbA1c, triglycerides and BMI at baseline, compared to those in subgroup 1. At 18 months (n = 651), the beta coefficients (95% CI) for change in HbA1c (mmol/mol) increased across subgroups with 0.37 (-0.18-1.92) for subgroup 2 and 1.88 (-0.08-3.85) for subgroup 3, relative to subgroup 1. The same trend was observed for change in levels of triglycerides and fasting glucose. CONCLUSIONS: Different glycaemic profiles with different metabolic traits and different degrees of subsequent glycaemic deterioration can be identified using data from a frequently sampled mixed-meal tolerance test in individuals with T2D. Subgroups with the highest peaks had greater metabolic risk.
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| 6. |
- 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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| 7. |
- Eriksen, Rebeca, et al.
(författare)
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Dietary metabolite profiling brings new insight into the relationship between nutrition and metabolic risk : An IMI DIRECT study
- 2020
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Ingår i: EBioMedicine. - : Elsevier BV. - 2352-3964. ; 58
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Tidskriftsartikel (refereegranskat)abstract
- Background: Dietary advice remains the cornerstone of prevention and management of type 2 diabetes (T2D). However, understanding the efficacy of dietary interventions is confounded by the challenges inherent in assessing free living diet. Here we profiled dietary metabolites to investigate glycaemic deterioration and cardiometabolic risk in people at risk of or living with T2D. Methods: We analysed data from plasma collected at baseline and 18-month follow-up in individuals from the Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) cohort 1 n = 403 individuals with normal or impaired glucose regulation (prediabetic) and cohort 2 n = 458 individuals with new onset of T2D. A dietary metabolite profile model (Tpred) was constructed using multivariable regression of 113 plasma metabolites obtained from targeted metabolomics assays. The continuous Tpred score was used to explore the relationships between diet, glycaemic deterioration and cardio-metabolic risk via multiple linear regression models. Findings: A higher Tpred score was associated with healthier diets high in wholegrain (β=3.36 g, 95% CI 0.31, 6.40 and β=2.82 g, 95% CI 0.06, 5.57) and lower energy intake (β=-75.53 kcal, 95% CI -144.71, -2.35 and β=-122.51 kcal, 95% CI -186.56, -38.46), and saturated fat (β=-0.92 g, 95% CI -1.56, -0.28 and β=–0.98 g, 95% CI -1.53, -0.42 g), respectively for cohort 1 and 2. In both cohorts a higher Tpred score was also associated with lower total body adiposity and favourable lipid profiles HDL-cholesterol (β=0.07 mmol/L, 95% CI 0.03, 0.1), (β=0.08 mmol/L, 95% CI 0.04, 0.1), and triglycerides (β=-0.1 mmol/L, 95% CI -0.2, -0.03), (β=-0.2 mmol/L, 95% CI -0.3, -0.09), respectively for cohort 1 and 2. In cohort 2, the Tpred score was negatively associated with liver fat (β=-0.74%, 95% CI -0.67, -0.81), and lower fasting concentrations of HbA1c (β=-0.9 mmol/mol, 95% CI -1.5, -0.1), glucose (β=-0.2 mmol/L, 95% CI -0.4, -0.05) and insulin (β=-11.0 pmol/mol, 95% CI -19.5, -2.6). Longitudinal analysis showed at 18-month follow up a higher Tpred score was also associated lower total body adiposity in both cohorts and lower fasting glucose (β=-0.2 mmol/L, 95% CI -0.3, -0.01) and insulin (β=-9.2 pmol/mol, 95% CI -17.9, -0.4) concentrations in cohort 2. Interpretation: Plasma dietary metabolite profiling provides objective measures of diet intake, showing a relationship to glycaemic deterioration and cardiometabolic health. Funding: This work was supported by the Innovative Medicines Initiative Joint Undertaking under grant agreement no. 115,317 (DIRECT), resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007–2013) and EFPIA companies.
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| 8. |
- Lesseur, Corina, et al.
(författare)
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Genome-wide association meta-analysis identifies pleiotropic risk loci for aerodigestive squamous cell cancers
- 2021
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Ingår i: PLOS Genetics. - : Public Library of Science (PLoS). - 1553-7390 .- 1553-7404. ; 17:3
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Tidskriftsartikel (refereegranskat)abstract
- Squamous cell carcinomas (SqCC) of the aerodigestive tract have similar etiological risk factors. Although genetic risk variants for individual cancers have been identified, an agnostic, genome-wide search for shared genetic susceptibility has not been performed. To identify novel and pleotropic SqCC risk variants, we performed a meta-analysis of GWAS data on lung SqCC (LuSqCC), oro/pharyngeal SqCC (OSqCC), laryngeal SqCC (LaSqCC) and esophageal SqCC (ESqCC) cancers, totaling 13,887 cases and 61,961 controls of European ancestry. We identified one novel genome-wide significant (Pmeta<5x10-8) aerodigestive SqCC susceptibility loci in the 2q33.1 region (rs56321285, TMEM273). Additionally, three previously unknown loci reached suggestive significance (Pmeta<5x10-7): 1q32.1 (rs12133735, near MDM4), 5q31.2 (rs13181561, TMEM173) and 19p13.11 (rs61494113, ABHD8). Multiple previously identified loci for aerodigestive SqCC also showed evidence of pleiotropy in at least another SqCC site, these include: 4q23 (ADH1B), 6p21.33 (STK19), 6p21.32 (HLA-DQB1), 9p21.33 (CDKN2B-AS1) and 13q13.1(BRCA2). Gene-based association and gene set enrichment identified a set of 48 SqCC-related genes to DNA damage and epigenetic regulation pathways. Our study highlights the importance of cross-cancer analyses to identify pleiotropic risk loci of histology-related cancers arising at distinct anatomical sites.
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| 9. |
- Sun, Ryan, et al.
(författare)
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Integration of multiomic annotation data to prioritize and characterize inflammation and immune-related risk variants in squamous cell lung cancer
- 2021
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Ingår i: Genetic Epidemiology. - : John Wiley & Sons. - 0741-0395 .- 1098-2272. ; 45:1, s. 99-114
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Tidskriftsartikel (refereegranskat)abstract
- Clinical trial results have recently demonstrated that inhibiting inflammation by targeting the interleukin-1 beta pathway can offer a significant reduction in lung cancer incidence and mortality, highlighting a pressing and unmet need to understand the benefits of inflammation-focused lung cancer therapies at the genetic level. While numerous genome-wide association studies (GWAS) have explored the genetic etiology of lung cancer, there remains a large gap between the type of information that may be gleaned from an association study and the depth of understanding necessary to explain and drive translational findings. Thus, in this study we jointly model and integrate extensive multiomics data sources, utilizing a total of 40 genome-wide functional annotations that augment previously published results from the International Lung Cancer Consortium (ILCCO) GWAS, to prioritize and characterize single nucleotide polymorphisms (SNPs) that increase risk of squamous cell lung cancer through the inflammatory and immune responses. Our work bridges the gap between correlative analysis and translational follow-up research, refining GWAS association measures in an interpretable and systematic manner. In particular, reanalysis of the ILCCO data highlights the impact of highly associated SNPs from nuclear factor-kappa B signaling pathway genes as well as major histocompatibility complex mediated variation in immune responses. One consequence of prioritizing likely functional SNPs is the pruning of variants that might be selected for follow-up work by over an order of magnitude, from potentially tens of thousands to hundreds. The strategies we introduce provide informative and interpretable approaches for incorporating extensive genome-wide annotation data in analysis of genetic association studies.
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