One-carbon metabolism in cancer

Cells require one-carbon units for nucleotide synthesis, methylation and reductive metabolism, and these pathways support the high proliferative rate of cancer cells. As such, anti-folates, drugs that target one-carbon metabolism, have long been used in the treatment of cancer. Amino acids, such as serine are a major one-carbon source, and cancer cells are particularly susceptible to deprivation of one-carbon units by serine restriction or inhibition of de novo serine synthesis. Recent work has also begun to decipher the specific pathways and sub-cellular compartments that are important for one-carbon metabolism in cancer cells. In this review we summarise the historical understanding of one-carbon metabolism in cancer, describe the recent findings regarding the generation and usage of one-carbon units and explore possible future therapeutics that could exploit the dependency of cancer cells on one-carbon metabolism

A "Candidate-Interactome" Aggregate Analysis of Genome-Wide Association Data in Multiple Sclerosis

Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a “candidate interactome” (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms

A “Candidate-Interactome” Aggregate Analysis of Genome-Wide Association Data in Multiple Sclerosis

Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a "candidate interactome" (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms

A multi-scale computational approach to understanding cancer metabolism

A first principles Nash equilibrium approach to modeling, simulation, and analysis of metabolic pathways is presented. The modeling framework is described in detail, and small examples illustrating mass and charge balancing, the inclusion of enzymatic reactions in the model, constraint linear independence, and allosteric inhibition are given in order to provide a tutorial for the reader. The methodology is then applied to the methionine salvage pathway in order to demonstrate that it can correctly capture the behavior of an important pathway in the study of cancer. It is shown that methylthioadenosine (MTA) accumulation as a result of the loss of activity of the enzyme S-methyl-5′-thioadenosine phosphorylase (MTAP) is correctly predicted by the Nash equilibrium approach under tight regulation of adenine. Several examples are presented to elucidate the key ideas in modeling cancer metabolism using the Nash equilibrium approach

Maternal supply of methionine during late-pregnancy enhances rate of Holstein calf development in utero and postnatal growth to a greater extent than colostrum source

BackgroundPregnancy and early life are critical periods of plasticity during which the fetus and neonate may be influenced by environmental factors such as nutrition. Maternal methionine (Met) supply in non-ruminants during pregnancy can affect offspring development and growth. Thus, the objective of this study was to investigate if increasing Met supply during late-pregnancy affects developmental parameters of the calf at birth and if either maternal Met or colostrum from Met-fed cows alters calf growth. Calves born to Holstein cows individually-fed a basal control [CON; 1.47 Mcal/kg dry matter (DM) and 15.3% crude protein] diet with no added Met or CON plus ethylcellulose rumen-protected Met (MET; Mepron (R) at 0.09% of diet DM; Evonik Nutrition & Care GmbH, Germany) during the last 282 d of pregnancy were used. A total of 39 calves were in CON (n=22 bulls, 17 heifers) and 42 in MET (n=20 bulls, 22 heifers). At birth, calves were randomly allocated considering dam treatment and colostrum as follows: 1) calves from CON cows and colostrum from CON cows (n=21); 2) calves from CON cows and colostrum from MET cows (n=18); 3) calves from MET cows and colostrum from MET cows (n=22); and 4) calves from MET cows and colostrum from CON cows (n=20). All calves were housed, managed, and fed individually during the first 9 wk of life.ResultsDespite greater daily DM intake pre-partum in cows fed MET (15.7 vs. 14.4 +/- 0.12kg/d, P0.05) due to maternal Met supply or colostrum source. However, fecal scores tended to be lower (P0.10) in MET calves regardless of colostrum source.Conclusions Increasing the maternal supply of MET during late-pregnancy enhanced growth in utero as well as during the pre-weaning and early post-weaning periods. Although the similar to 1kg/d greater DM intake during the last 2-3 wk prior to parturition could explain a portion of the 2kg extra body mass of MET calves at birth, other mechanisms potentially encompassing nutrient assimilation efficiency likely played a role. Assessing the exact mechanisms sensitive to supply of Met or total amino acid supply during the latter stages of growth in utero merit further research

Trans-ethnic genomic informed risk assessment for Alzheimer's disease: An International Hundred K+ Cohorts Consortium study.

BACKGROUND: As a collaboration model between the International HundredK+ Cohorts Consortium (IHCC) and the Davos Alzheimer's Collaborative (DAC), our aim was to develop a trans-ethnic genomic informed risk assessment (GIRA) algorithm for Alzheimer's disease (AD). METHODS: The GIRA model was created to include polygenic risk score calculated from the AD genome-wide association study loci, the apolipoprotein E haplotypes, and non-genetic covariates including age, sex, and the first three principal components of population substructure. RESULTS: We validated the performance of the GIRA model in different populations. The proteomic study in the participant sites identified proteins related to female infertility and autoimmune thyroiditis and associated with the risk scores of AD. CONCLUSIONS: As the initial effort by the IHCC to leverage existing large-scale datasets in a collaborative setting with DAC, we developed a trans-ethnic GIRA for AD with the potential of identifying individuals at high risk of developing AD for future clinical applications