34 research outputs found
Deviant reporter expression and P2X4 passenger gene overexpression in the soluble EGFP BAC transgenic P2X7 reporter mouse model
The ATP-gated P2X7 receptor is highly expressed in microglia and has been involved in diverse brain diseases. P2X7 effects were also described in neurons and astrocytes but its localisation and function in these cell types has been challenging to demonstrate in situ. BAC transgenic mouse lines have greatly advanced neuroscience research and two BAC-transgenic P2X7 reporter mouse models exist in which either a soluble EGFP (sEGFP) or an EGFP-tagged P2X7 receptor (P2X7-EGFP) is expressed under the control of a BAC-derived P2rx7 promoter. Here we evaluate both mouse models and find striking differences in both P2X expression levels and EGFP reporter expression patterns. Most remarkably, the sEGFP model overexpresses a P2X4 passenger gene and sEGFP shows clear neuronal localisation but appears to be absent in microglia. Preliminary functional analysis in a status epilepticus model suggests functional consequences of the observed P2X receptor overexpression. In summary, an aberrant EGFP reporter pattern and possible effects of P2X4 and/or P2X7 protein overexpression need to be considered when working with this model. We further discuss reasons for the observed differences and possible caveats in BAC transgenic approaches
Associations between Fatty Acid Intakes and Plasma Phospholipid Fatty Acid Concentrations in the European Prospective Investigation into Cancer and Nutrition
Background: The aim of this study is to determine the correlations between dietary fatty acid (FA) intakes and plasma phospholipid (PL) FA levels in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Methods: The dietary intake of 60 individual FAs was estimated using centre-specific validated dietary questionnaires. Plasma PL FA concentrations of these FAs were measured in non-fasting venous plasma samples in nested case-control studies within the EPIC cohort (n = 4923, using only non-cases). Spearman rank correlations were calculated to determine associations between FA intakes and plasma PL FA levels. Results: Correlations between FA intakes and circulating levels were low to moderately high (-0.233 and 0.554). Moderate positive correlations were found for total long-chain n-3 poly-unsaturated FA (PUFA) (r = 0.354) with the highest (r = 0.406) for n-3 PUFA docosahexaenoic acid (DHA). Moderate positive correlations were also found for the non-endogenously synthesized trans-FA (r = 0.461 for total trans-FA C16-18; r = 0.479 for industrial trans-FA (elaidic acid)). Conclusions: Our findings indicate that dietary FA intakes might influence the plasma PL FA status to a certain extent for several specific FAs. The stronger positive correlations for health-enhancing long-chain PUFAs and the health-deteriorating trans-FA that are not endogenously produced are valuable for future cancer prevention public health interventions
Characterization of the degree of food processing in the European Prospective Investigation into Cancer and Nutrition: Application of the Nova classification and validation using selected biomarkers of food processing
Background: Epidemiological studies have demonstrated an association between the degree of food processing in our diet and the risk of various chronic diseases. Much of this evidence is based on the international Nova classification system, which classifies food into four groups based on the type of processing: (1) Unprocessed and minimally processed foods, (2) Processed culinary ingredients, (3) Processed foods, and (4) “Ultra-processed” foods (UPF). The ability of the Nova classification to accurately characterise the degree of food processing across consumption patterns in various European populations has not been investigated so far. Therefore, we applied the Nova coding to data from the European Prospective Investigation into Cancer and Nutrition (EPIC) in order to characterize the degree of food processing in our diet across European populations with diverse cultural and socio-economic backgrounds and to validate this Nova classification through comparison with objective biomarker measurements. Methods: After grouping foods in the EPIC dataset according to the Nova classification, a total of 476,768 participants in the EPIC cohort (71.5% women; mean age 51 [standard deviation (SD) 9.93]; median age 52 [percentile (p)25–p75: 58–66] years) were included in the cross-sectional analysis that characterised consumption patterns based on the Nova classification. The consumption of food products classified as different Nova categories were compared to relevant circulating biomarkers denoting food processing, measured in various subsamples (N between 417 and 9,460) within the EPIC cohort via (partial) correlation analyses (unadjusted and adjusted by sex, age, BMI and country). These biomarkers included an industrial transfatty acid (ITFA) isomer (elaidic acid; exogenous fatty acid generated during oil hydrogenation and heating) and urinary 4-methyl syringol sulfate (an indicator for the consumption of smoked food and a component of liquid smoke used in UPF). Results: Contributions of UPF intake to the overall diet in % grams/day varied across countries from 7% (France) to 23% (Norway) and their contributions to overall % energy intake from 16% (Spain and Italy) to >45% (in the UK and Norway). Differences were also found between sociodemographic groups; participants in the highest fourth of UPF consumption tended to be younger, taller, less educated, current smokers, more physically active, have a higher reported intake of energy and lower reported intake of alcohol. The UPF pattern as defined based on the Nova classification (group 4;% kcal/day) was positively associated with blood levels of industrial elaidic acid (r = 0.54) and 4-methyl syringol sulfate (r = 0.43). Associations for the other 3 Nova groups with these food processing biomarkers were either inverse or non-significant (e.g., for unprocessed and minimally processed foods these correlations were –0.07 and –0.37 for elaidic acid and 4-methyl syringol sulfate, respectively). Conclusion: These results, based on a large pan-European cohort, demonstrate sociodemographic and geographical differences in the consumption of UPF. Furthermore, these results suggest that the Nova classification can accurately capture consumption of UPF, reflected by stronger correlations with circulating levels of industrial elaidic acid and a syringol metabolite compared to diets high in minimally processed foods
Characterization of the degree of food processing in the European Prospective Investigation into Cancer and Nutrition: Application of the Nova classification and validation using selected biomarkers of food processing
Background: Epidemiological studies have demonstrated an association
between the degree of food processing in our diet and the risk of various
chronic diseases. Much of this evidence is based on the international Nova
classification system, which classifies food into four groups based on the type
of processing: (1) Unprocessed and minimally processed foods, (2) Processed
culinary ingredients, (3) Processed foods, and (4) “Ultra-processed” foods
(UPF). The ability of the Nova classification to accurately characterise the
degree of food processing across consumption patterns in various European
populations has not been investigated so far. Therefore, we applied the Nova
coding to data from the European Prospective Investigation into Cancer and
Nutrition (EPIC) in order to characterize the degree of food processing in our
diet across European populations with diverse cultural and socio-economic
backgrounds and to validate this Nova classification through comparison with
objective biomarker measurements.
Methods: After grouping foods in the EPIC dataset according to the Nova
classification, a total of 476,768 participants in the EPIC cohort (71.5% women;
mean age 51 [standard deviation (SD) 9.93]; median age 52 [percentile (p)25–
p75: 58–66] years) were included in the cross-sectional analysis that
characterised consumption patterns based on the Nova classification. The
consumption of food products classified as different Nova categories were
compared to relevant circulating biomarkers denoting food processing,
measured in various subsamples (N between 417 and 9,460) within the EPIC
cohort via (partial) correlation analyses (unadjusted and adjusted by sex,
age, BMI and country). These biomarkers included an industrial transfatty
acid (ITFA) isomer (elaidic acid; exogenous fatty acid generated during
oil hydrogenation and heating) and urinary 4-methyl syringol sulfate (an
indicator for the consumption of smoked food and a component of liquid
smoke used in UPF).
Results: Contributions of UPF intake to the overall diet in % grams/day varied
across countries from 7% (France) to 23% (Norway) and their contributions to
overall % energy intake from 16% (Spain and Italy) to >45% (in the UK and
Norway). Differences were also found between sociodemographic groups;
participants in the highest fourth of UPF consumption tended to be younger,
taller, less educated, current smokers, more physically active, have a higher
reported intake of energy and lower reported intake of alcohol. The UPF
pattern as defined based on the Nova classification (group 4;% kcal/day) was
positively associated with blood levels of industrial elaidic acid (r = 0.54) and
4-methyl syringol sulfate (r = 0.43). Associations for the other 3 Nova groups
with these food processing biomarkers were either inverse or non-significant
(e.g., for unprocessed and minimally processed foods these correlations were
–0.07 and –0.37 for elaidic acid and 4-methyl syringol sulfate, respectively).
Conclusion: These results, based on a large pan-European cohort,
demonstrate sociodemographic and geographical differences in the
consumption of UPF. Furthermore, these results suggest that the Nova
classification can accurately capture consumption of UPF, reflected by
stronger correlations with circulating levels of industrial elaidic acid and a
syringol metabolite compared to diets high in minimally processed foods
Characterization of the degree of food processing in the European Prospective Investigation into Cancer and Nutrition: Application of the Nova classification and validation using selected biomarkers of food processing
Background: Epidemiological studies have demonstrated an association between the degree of food processing in our diet and the risk of various chronic diseases. Much of this evidence is based on the international Nova classification system, which classifies food into four groups based on the type of processing: (1) Unprocessed and minimally processed foods, (2) Processed culinary ingredients, (3) Processed foods, and (4) Ultra-processed foods (UPF). The ability of the Nova classification to accurately characterise the degree of food processing across consumption patterns in various European populations has not been investigated so far. Therefore, we applied the Nova coding to data from the European Prospective Investigation into Cancer and Nutrition (EPIC) in order to characterize the degree of food processing in our diet across European populations with diverse cultural and socio-economic backgrounds and to validate this Nova classification through comparison with objective biomarker measurements. Methods: After grouping foods in the EPIC dataset according to the Nova classification, a total of 476,768 participants in the EPIC cohort (71.5% women; mean age 51 [standard deviation (SD) 9.93]; median age 52 [percentile (p)25-p75: 58-66] years) were included in the cross-sectional analysis that characterised consumption patterns based on the Nova classification. The consumption of food products classified as different Nova categories were compared to relevant circulating biomarkers denoting food processing, measured in various subsamples (N between 417 and 9,460) within the EPIC cohort via (partial) correlation analyses (unadjusted and adjusted by sex, age, BMI and country). These biomarkers included an industrial transfatty acid (ITFA) isomer (elaidic acid; exogenous fatty acid generated during oil hydrogenation and heating) and urinary 4-methyl syringol sulfate (an indicator for the consumption of smoked food and a component of liquid smoke used in UPF). Results: Contributions of UPF intake to the overall diet in % grams/day varied across countries from 7% (France) to 23% (Norway) and their contributions to overall % energy intake from 16% (Spain and Italy) to >45% (in the UK and Norway). Differences were also found between sociodemographic groups; participants in the highest fourth of UPF consumption tended to be younger, taller, less educated, current smokers, more physically active, have a higher reported intake of energy and lower reported intake of alcohol. The UPF pattern as defined based on the Nova classification (group 4;% kcal/day) was positively associated with blood levels of industrial elaidic acid (r = 0.54) and 4-methyl syringol sulfate (r = 0.43). Associations for the other 3 Nova groups with these food processing biomarkers were either inverse or non-significant (e.g., for unprocessed and minimally processed foods these correlations were -0.07 and -0.37 for elaidic acid and 4-methyl syringol sulfate, respectively). Conclusion: These results, based on a large pan-European cohort, demonstrate sociodemographic and geographical differences in the consumption of UPF. Furthermore, these results suggest that the Nova classification can accurately capture consumption of UPF, reflected by stronger correlations with circulating levels of industrial elaidic acid and a syringol metabolite compared to diets high in minimally processed foods
Associations between Fatty Acid Intakes and Plasma Phospholipid Fatty Acid Concentrations in the European Prospective Investigation into Cancer and Nutrition
Background: The aim of this study is to determine the correlations between dietary fatty acid (FA) intakes and plasma phospholipid (PL) FA levels in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Methods: The dietary intake of 60 individual FAs was estimated using centre-specific validated dietary questionnaires. Plasma PL FA concentrations of these FAs were measured in non-fasting venous plasma samples in nested case-control studies within the EPIC cohort (n = 4923, using only non-cases). Spearman rank correlations were calculated to determine associations between FA intakes and plasma PL FA levels. Results: Correlations between FA intakes and circulating levels were low to moderately high (−0.233 and 0.554). Moderate positive correlations were found for total long-chain n-3 poly-unsaturated FA (PUFA) (r = 0.354) with the highest (r = 0.406) for n-3 PUFA docosahexaenoic acid (DHA). Moderate positive correlations were also found for the non-endogenously synthesized trans-FA (r = 0.461 for total trans-FA C16-18; r = 0.479 for industrial trans-FA (elaidic acid)). Conclusions: Our findings indicate that dietary FA intakes might influence the plasma PL FA status to a certain extent for several specific FAs. The stronger positive correlations for health-enhancing long-chain PUFAs and the health-deteriorating trans-FA that are not endogenously produced are valuable for future cancer prevention public health interventions
Iron Behaving Badly: Inappropriate Iron Chelation as a Major Contributor to the Aetiology of Vascular and Other Progressive Inflammatory and Degenerative Diseases
The production of peroxide and superoxide is an inevitable consequence of
aerobic metabolism, and while these particular "reactive oxygen species" (ROSs)
can exhibit a number of biological effects, they are not of themselves
excessively reactive and thus they are not especially damaging at physiological
concentrations. However, their reactions with poorly liganded iron species can
lead to the catalytic production of the very reactive and dangerous hydroxyl
radical, which is exceptionally damaging, and a major cause of chronic
inflammation. We review the considerable and wide-ranging evidence for the
involvement of this combination of (su)peroxide and poorly liganded iron in a
large number of physiological and indeed pathological processes and
inflammatory disorders, especially those involving the progressive degradation
of cellular and organismal performance. These diseases share a great many
similarities and thus might be considered to have a common cause (i.e.
iron-catalysed free radical and especially hydroxyl radical generation). The
studies reviewed include those focused on a series of cardiovascular, metabolic
and neurological diseases, where iron can be found at the sites of plaques and
lesions, as well as studies showing the significance of iron to aging and
longevity. The effective chelation of iron by natural or synthetic ligands is
thus of major physiological (and potentially therapeutic) importance. As
systems properties, we need to recognise that physiological observables have
multiple molecular causes, and studying them in isolation leads to inconsistent
patterns of apparent causality when it is the simultaneous combination of
multiple factors that is responsible. This explains, for instance, the
decidedly mixed effects of antioxidants that have been observed, etc...Comment: 159 pages, including 9 Figs and 2184 reference
Characterization of the degree of food processing in the European Prospective Investigation into Cancer and Nutrition: Application of the Nova classification and validation using selected biomarkers of food processing
BackgroundEpidemiological studies have demonstrated an association between the degree of food processing in our diet and the risk of various chronic diseases. Much of this evidence is based on the international Nova classification system, which classifies food into four groups based on the type of processing: (1) Unprocessed and minimally processed foods, (2) Processed culinary ingredients, (3) Processed foods, and (4) “Ultra-processed” foods (UPF). The ability of the Nova classification to accurately characterise the degree of food processing across consumption patterns in various European populations has not been investigated so far. Therefore, we applied the Nova coding to data from the European Prospective Investigation into Cancer and Nutrition (EPIC) in order to characterize the degree of food processing in our diet across European populations with diverse cultural and socio-economic backgrounds and to validate this Nova classification through comparison with objective biomarker measurements.MethodsAfter grouping foods in the EPIC dataset according to the Nova classification, a total of 476,768 participants in the EPIC cohort (71.5% women; mean age 51 [standard deviation (SD) 9.93]; median age 52 [percentile (p)25–p75: 58–66] years) were included in the cross-sectional analysis that characterised consumption patterns based on the Nova classification. The consumption of food products classified as different Nova categories were compared to relevant circulating biomarkers denoting food processing, measured in various subsamples (N between 417 and 9,460) within the EPIC cohort via (partial) correlation analyses (unadjusted and adjusted by sex, age, BMI and country). These biomarkers included an industrial transfatty acid (ITFA) isomer (elaidic acid; exogenous fatty acid generated during oil hydrogenation and heating) and urinary 4-methyl syringol sulfate (an indicator for the consumption of smoked food and a component of liquid smoke used in UPF).ResultsContributions of UPF intake to the overall diet in % grams/day varied across countries from 7% (France) to 23% (Norway) and their contributions to overall % energy intake from 16% (Spain and Italy) to >45% (in the UK and Norway). Differences were also found between sociodemographic groups; participants in the highest fourth of UPF consumption tended to be younger, taller, less educated, current smokers, more physically active, have a higher reported intake of energy and lower reported intake of alcohol. The UPF pattern as defined based on the Nova classification (group 4;% kcal/day) was positively associated with blood levels of industrial elaidic acid (r = 0.54) and 4-methyl syringol sulfate (r = 0.43). Associations for the other 3 Nova groups with these food processing biomarkers were either inverse or non-significant (e.g., for unprocessed and minimally processed foods these correlations were –0.07 and –0.37 for elaidic acid and 4-methyl syringol sulfate, respectively).ConclusionThese results, based on a large pan-European cohort, demonstrate sociodemographic and geographical differences in the consumption of UPF. Furthermore, these results suggest that the Nova classification can accurately capture consumption of UPF, reflected by stronger correlations with circulating levels of industrial elaidic acid and a syringol metabolite compared to diets high in minimally processed foods
Les projets d'accueil indivualisé
LILLE2-BU Santé-Recherche (593502101) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF
The human microbial exposome: expanding the Exposome-Explorer database with gut microbial metabolites
Abstract Metabolites produced by the gut microbiota play an important role in the cross-talk with the human host. Many microbial metabolites are biologically active and can pass the gut barrier and make it into the systemic circulation, where they form the gut microbial exposome, i.e. the totality of gut microbial metabolites in body fluids or tissues of the host. A major difficulty faced when studying the microbial exposome and its role in health and diseases is to differentiate metabolites solely or partially derived from microbial metabolism from those produced by the host or coming from the diet. Our objective was to collect data from the scientific literature and build a database on gut microbial metabolites and on evidence of their microbial origin. Three types of evidence on the microbial origin of the gut microbial exposome were defined: (1) metabolites are produced in vitro by human faecal bacteria; (2) metabolites show reduced concentrations in humans or experimental animals upon treatment with antibiotics; (3) metabolites show reduced concentrations in germ-free animals when compared with conventional animals. Data was manually collected from peer-reviewed publications and inserted in the Exposome-Explorer database. Furthermore, to explore the chemical space of the microbial exposome and predict metabolites uniquely formed by the microbiota, genome-scale metabolic models (GSMMs) of gut bacterial strains and humans were compared. A total of 1848 records on one or more types of evidence on the gut microbial origin of 457 metabolites was collected in Exposome-Explorer. Data on their known precursors and concentrations in human blood, urine and faeces was also collected. About 66% of the predicted gut microbial metabolites (n = 1543) were found to be unique microbial metabolites not found in the human GSMM, neither in the list of 457 metabolites curated in Exposome-Explorer, and can be targets for new experimental studies. This new data on the gut microbial exposome, freely available in Exposome-Explorer ( http://exposome-explorer.iarc.fr/ ), will help researchers to identify poorly studied microbial metabolites to be considered in future studies on the gut microbiota, and study their functionalities and role in health and diseases