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- 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. |
- Ciemala, M., et al.
(författare)
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Testing ab initio nuclear structure in neutron-rich nuclei : Lifetime measurements of second 2(+) state in C-16 and O-20
- 2020
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Ingår i: Physical Review C. - : AMER PHYSICAL SOC. - 2469-9985 .- 2469-9993. ; 101:2
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Tidskriftsartikel (refereegranskat)abstract
- To test the predictive power of ab initio nuclear structure theory, the lifetime of the second 2(+) state in neutron-rich O-20, tau(2(2)(+)) = 150(-30)(+80) fs, and an estimate for the lifetime of the second 2(+) state in C-16 have been obtained for the first time. The results were achieved via a novel Monte Carlo technique that allowed us to measure nuclear state lifetimes in the tens-to-hundreds of femtoseconds range by analyzing the Doppler-shifted gamma-transition line shapes of products of low-energy transfer and deep-inelastic processes in the reaction O-18 (7.0 MeV/u) + Ta-181. The requested sensitivity could only be reached owing to the excellent performances of the Advanced gamma-Tracking Array AGATA, coupled to the PARIS scintillator array and to the VAMOS++ magnetic spectrometer. The experimental lifetimes agree with predictions of ab initio calculations using two- and three-nucleon interactions, obtained with the valence-space in-medium similarity renormalization group for O-20 and with the no-core shell model for C-16. The present measurement shows the power of electromagnetic observables, determined with high-precision gamma spectroscopy, to assess the quality of first-principles nuclear structure calculations, complementing common benchmarks based on nuclear energies. The proposed experimental approach will be essential for short lifetime measurements in unexplored regions of the nuclear chart, including r-process nuclei, when intense beams, produced by Isotope Separation On-Line (ISOL) techniques, become available.
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| 5. |
- 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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| 8. |
- Brown, A.A., et al.
(författare)
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Genetic analysis of blood molecular phenotypes reveals common properties in the regulatory networks affecting complex traits
- 2023
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Ingår i: Nature Communications. - : Springer Nature. - 2041-1723. ; 14
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Tidskriftsartikel (refereegranskat)abstract
- We evaluate the shared genetic regulation of mRNA molecules, proteins and metabolites derived from whole blood from 3029 human donors. We find abundant allelic heterogeneity, where multiple variants regulate a particular molecular phenotype, and pleiotropy, where a single variant associates with multiple molecular phenotypes over multiple genomic regions. The highest proportion of share genetic regulation is detected between gene expression and proteins (66.6%), with a further median shared genetic associations across 49 different tissues of 78.3% and 62.4% between plasma proteins and gene expression. We represent the genetic and molecular associations in networks including 2828 known GWAS variants, showing that GWAS variants are more often connected to gene expression in trans than other molecular phenotypes in the network. Our work provides a roadmap to understanding molecular networks and deriving the underlying mechanism of action of GWAS variants using different molecular phenotypes in an accessible tissue. © 2023, Springer Nature Limited.
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| 9. |
- Rossi, C. A., et al.
(författare)
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Longitudinal Relationships Between Proteomics and Beta-Cell Dysfunction in Type 2 Diabetes: an IMI Direct Study
- 2023
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Ingår i: 8th National Congress of Bioengineering, GNB 2023. - : Patron Editore S.r.l..
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Konferensbidrag (refereegranskat)abstract
- β-cell dysfunction is a crucial factor of glycaemic deterioration in type 2 diabetes (T2D), but the role of circulating proteins in its progression is currently not understood. We studied the potential associations between β-cell glucose sensitivity progression over 3 years and baseline proteomics in a cohort of recently diagnosed T2D patients (N = 653) from the IMI-DIRECT project, through linear regression analysis. We found that forty-six proteins have a significant association to β-cell glucose sensitivity progression. Subsequent functional analysis showed these proteins belong to functional modules linked to insulin secretion and T2D pathophysiology. These findings, along with further investigation in longitudinal studies, may point to novel protein markers and processes of β-cell function deterioration.
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| 10. |
- 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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