The metabolome 18 years on: a concept comes of age

Kell, Douglas B.; Oliver, Stephen G.

doi:10.1007/s11306-016-1108-4

Cited by 97 publications

(71 citation statements)

References 135 publications

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“…For fundamental reasons connected with metabolic control and its formal, mathematical analysis (962–966), changes in the metabolome are both expected (967) and found (968–971) to be amplified relative to those in the transcriptome and proteome. For similar reasons, and coupled with evolution’s selection for robustness (972–978) (i.e., homeostasis) in metabolic networks, we do not normally expect to find single metabolic biomarkers for a complex disease or syndrome.…”

Section: Metabolomic Biomarkersmentioning

confidence: 99%

A Dormant Microbial Component in the Development of Preeclampsia

Kell

Kenny

2016

Front. Med.

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Preeclampsia (PE) is a complex, multisystem disorder that remains a leading cause of morbidity and mortality in pregnancy. Four main classes of dysregulation accompany PE and are widely considered to contribute to its severity. These are abnormal trophoblast invasion of the placenta, anti-angiogenic responses, oxidative stress, and inflammation. What is lacking, however, is an explanation of how these themselves are caused. We here develop the unifying idea, and the considerable evidence for it, that the originating cause of PE (and of the four classes of dysregulation) is, in fact, microbial infection, that most such microbes are dormant and hence resist detection by conventional (replication-dependent) microbiology, and that by occasional resuscitation and growth it is they that are responsible for all the observable sequelae, including the continuing, chronic inflammation. In particular, bacterial products such as lipopolysaccharide (LPS), also known as endotoxin, are well known as highly inflammagenic and stimulate an innate (and possibly trained) immune response that exacerbates the inflammation further. The known need of microbes for free iron can explain the iron dysregulation that accompanies PE. We describe the main routes of infection (gut, oral, and urinary tract infection) and the regularly observed presence of microbes in placental and other tissues in PE. Every known proteomic biomarker of “preeclampsia” that we assessed has, in fact, also been shown to be raised in response to infection. An infectious component to PE fulfills the Bradford Hill criteria for ascribing a disease to an environmental cause and suggests a number of treatments, some of which have, in fact, been shown to be successful. PE was classically referred to as endotoxemia or toxemia of pregnancy, and it is ironic that it seems that LPS and other microbial endotoxins really are involved. Overall, the recognition of an infectious component in the etiology of PE mirrors that for ulcers and other diseases that were previously considered to lack one.

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Section: Metabolomic Biomarkersmentioning

confidence: 99%

A Dormant Microbial Component in the Development of Preeclampsia

Kell

Kenny

2016

Front. Med.

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“…Here, we characterize the metabolome 12–14 , a global set of small molecules, within adipose tissue depots at thermoneutrality (30 °C) and during a time course (2–6 hours) of acute cold exposure by combining high-resolution magnetic resonance spectroscopy (MRS) and ultra-high pressure liquid chromatography-mass spectrometry (UHPLC-MS) analytical platforms 13, 15–17 . Our analysis of adipose tissue metabolism supports the findings that BAT thermogenesis is associated with glutathione depletion after acute cold exposure.…”

Section: Introductionmentioning

confidence: 99%

The early metabolomic response of adipose tissue during acute cold exposure in mice

Solmonson

Lodi

et al. 2017

Sci Rep

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To maintain core body temperature in cold conditions, mammals activate a complex multi-organ metabolic response for heat production. White adipose tissue (WAT) primarily functions as an energy reservoir, while brown adipose tissue (BAT) is activated during cold exposure to generate heat from nutrients. Both BAT and WAT undergo specific metabolic changes during acute cold exposure. Here, we use an untargeted metabolomics approach to characterize the initial metabolic response to cold exposure in multiple adipose tissue depots in mice. Results demonstrate dramatically distinct metabolic responses during cold exposure in BAT and WAT. Amino acids, nucleotide pathways, and metabolites involved in redox regulation were greatly affected 4 hours post-exposure in BAT, while no polar metabolites were observed to significantly change in WAT depots up to 6 hours post exposure. Lipid metabolism was activated early (2 hours) in both BAT and the subcutaneous WAT depots, with the most striking change being observed in the modulation of diglyceride and monoglyceride levels in BAT. Overall, these data provide a timeline of global thermogenic metabolism in adipose depots during acute cold exposure. We have highlighted differences in visceral and subcutaneous WAT thermogenic metabolism and demonstrate the distinct metabolism of BAT during cold exposure.

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“…Metabolomics permits indeed the extensive profiling of sets of small molecules within cells, tissues and biofluids [24]. At least two characteristics make metabolomics suitable for the analysis of a complex, heterogeneous trait such as aggressive/violent behavior.…”

Section: Biomarkers Of Aggressive/violent Behavior: a Role For Metabomentioning

confidence: 99%

“…First, changes in metabolome are amplified relative to changes in gene expression (transcriptome) and the proteome, facilitating the identification of distinct biochemical signatures that could be tested as biomarkers. Second, compared with transcriptomics and proteomics, metabolomics is less context dependent, in other words, is less influenced by changing physiological, pathological or developmental states of the cell [24,25].…”

Section: Biomarkers Of Aggressive/violent Behavior: a Role For Metabomentioning

confidence: 99%

Preventing Aggressive/Violent Behavior: A Role for Biomarkers?

Pinna

Manchia

2017

Biomark. Med.

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The burden of aggressive/violent behavior Despite a declining rate in the past 10 years, aggressive/violent behavior remains among the main causes of worldwide premature mortality [1]. Associated direct (medical and nonmedical expenditure) and indirect (longterm societal implications) socio-economic costs are also substantial [2,3]. These have been estimated in 2001 at approximately 5% of the gross national product of industrialized countries, and as much as 14% of the gross national product of low-income countries [3].In this context, policy makers have attempted to enact interventions that could prevent the development of aggression and violence in at-risk populations (i.e., abused children and troubled youth, alcohol and substance abusers, prisoners). These public health approaches that include, among the others, education, behavior change, policy, engineering and environmental support, have proven to be effective in reducing the rates of aggression/violence as well as its associated economic costs [4].Nonetheless, there is still a substantial proportion of individuals who enact aggressive/violent behavior over the lifetime course that is not targeted by these interventions. Further, such interventions are implemented only once aggressive behavior has already manifested itself.By definition, primary preventive strategies intend to avoid the manifestation of a specific disease or event before it occurs. To be effective, preventive approaches need to identify risk factors that can determine the onset of an illness or of an event in an exposed population.In the case of aggressive/violent behavior, there is a multitude of determinants (clinical, environmental and biological) that set the liability threshold for its manifestation. It is plausible that predictive models integrating different levels of information (from phenotypic to 'omics' data) might help identifying with higher accuracy individuals at risk for aggression/violence compared with those relying only, for instance, on clinical data. However, the inclusion of biological markers (henceforth biomarkers) in such models can be achieved only if they are identified in longitudinal prospective studies and are replicated in independent samples. Importantly, this process could also lead to a more precise understanding of the neurobiological underpinnings of aggression/violence.Here, we critically discuss the recent advancements in the identification of biological markers of aggression and the eventual barriers toward their implementation in predictive models. To this end, we will first briefly present the current knowledge on the neurobiological make up of aggression/violent behavior. Next, we will discuss how the phenotypic heterogeneity of aggression might have hindered the identification of reliable biomarkers. Finally, we will present data on available biological markers of aggression that might be suitable for implementation in predictive models.

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The metabolome 18 years on: a concept comes of age

Cited by 97 publications

References 135 publications

A Dormant Microbial Component in the Development of Preeclampsia

A Dormant Microbial Component in the Development of Preeclampsia

The early metabolomic response of adipose tissue during acute cold exposure in mice

Preventing Aggressive/Violent Behavior: A Role for Biomarkers?

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