| 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. |
- 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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| 3. |
- Bohr, Tomas, et al.
(författare)
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The glymphatic system : Current understanding and modeling
- 2022
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Ingår i: iScience. - : Elsevier BV. - 2589-0042. ; 25:9
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Forskningsöversikt (refereegranskat)abstract
- We review theoretical and numerical models of the glymphatic system, which circulates cerebrospinal fluid and interstitial fluid around the brain, facilitating solute transport. Models enable hypothesis development and predictions of transport, with clinical applications including drug delivery, stroke, cardiac arrest, and neurodegenerative disorders like Alzheimer's disease. We sort existing models into broad categories by anatomical function: Perivascular flow, transport in brain parenchyma, interfaces to perivascular spaces, efflux routes, and links to neuronal activity. Needs and opportunities for future work are highlighted wherever possible; new models, expanded models, and novel experiments to inform models could all have tremendous value for advancing the field.
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| 4. |
- Carlstrom, Lucas P., et al.
(författare)
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A clinical primer for the glymphatic system
- 2022
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Ingår i: Brain. - : Oxford University Press (OUP). - 0006-8950 .- 1460-2156. ; 145:3, s. 843-857
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Forskningsöversikt (refereegranskat)abstract
- The complex and dynamic system of fluid flow through the perivascular and interstitial spaces of the CNS has new-found implications for neurological diseases. CSF movement throughout the CNS parenchyma is more dynamic than could be explained via passive diffusion mechanisms alone. Indeed, a semistructured glial-lymphatic (glymphatic) system of astrocyte-supported extracellular perivascular channels serves to directionally channel extracellular fluid, clearing metabolites and peptides to optimize neurological function. Clinical studies of the glymphatic network have to date proven challenging, with most data gleaned from rodent models and post-mortem investigations. However, increasing evidence suggests that disordered glymphatic function contributes to the pathophysiology of CNS ageing, neurodegenerative disease and CNS injuries, as well as normal pressure hydrocephalus. Unlocking such pathophysiology could provide important avenues towards novel therapeutics. We here provide a multidisciplinary overview of glymphatics and critically review accumulating evidence regarding its structure, function and hypothesized relevance to neurological disease. We highlight emerging technologies of relevance to the longitudinal evaluation of glymphatic function in health and disease. Finally, we discuss the translational opportunities and challenges of studying glymphatic science.
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