Identifying and Analyzing Topic Clusters in a Nutri-, Food-, and Diet-Proteomic Corpus Using Machine Reading

Nutrition affects the early stages of disease development, but the mechanisms remain poorly understood. High-throughput proteomic methods are being used to generate data and information on the effects of nutrients, foods, and diets on health and disease processes. In this report, a novel machine reading pipeline was used to identify all articles and abstracts on proteomics, diet, food, and nutrition in humans. The resulting proteomic corpus was further analyzed to produce seven clusters of "thematic" content defined as documents that have similar word content. Examples of publications from several of these clusters were then described in a similar way to a typical descriptive review.

A network-based approach to identify deregulated pathways and drug effects in metabolic syndrome

Metabolic syndrome is a pathological condition characterized by obesity, hyperglycemia, hypertension, elevated levels of triglycerides and low levels of high-density lipoprotein cholesterol that increase cardiovascular disease risk and type 2 diabetes. Although numerous predisposing genetic risk factors have been identified, the biological mechanisms underlying this complex phenotype are not fully elucidated. Here we introduce a systems biology approach based on network analysis to investigate deregulated biological processes and subsequently identify drug repurposing candidates. A proximity score describing the interaction between drugs and pathways is defined by combining topological and functional similarities. The results of this computational framework highlight a prominent role of the immune system in metabolic syndrome and suggest a potential use of the BTK inhibitor ibrutinib as a novel pharmacological treatment. An experimental validation using a high fat diet-induced obesity model in zebrafish larvae shows the effectiveness of ibrutinib in lowering the inflammatory load due to macrophage accumulation.

Personalized Cardio-Metabolic Responses to an Anti-Inflammatory Nutrition Intervention in Obese Adolescents: A Randomized Controlled Crossover Trial

SCOPE

Chronic inflammation and hypoadiponectinemia are characteristics of obesity-induced insulin resistance (IR). The effect of an anti-inflammatory nutrition supplement (AINS) on IR and adiponectin biology in overweight adolescents was investigated. The secondary objective was to examine the extent to which individuals' biomarker profiles, derived from baseline phenotypes, predicted response or not to the AINS. Additionally, the impact of DNA methylation on intervention efficacy was assessed.

METHODS AND RESULTS

Seventy overweight adolescents (13-18 years) were recruited to this randomized controlled crossover trial. Participants received an AINS (long chain n-3 PUFA, vitamin C, α-tocopherol, green tea extract, and lycopene) and placebo for 8 weeks each. Homeostatic model assessment (HOMA)-IR, adiponectin, inflammatory profiles, and DNA methylation were assessed. HOMA-IR was unchanged in the total cohort. High-molecular-weight (HMW) adiponectin was maintained following the AINS while it decreased over time following the placebo intervention. HOMA-IR decreased in 40% of subjects (responders) following the AINS. Responders' pretreatment phenotype was characterized by higher HOMA-IR, total and LDL cholesterol, but similar BMI in comparison to nonresponders. HMW adiponectin response to the AINS was associated with bidirectional modulation of adipogenic gene methylation.

CONCLUSION

The AINS modulated adiponectin biology, an early predictor of type 2 diabetes risk, was associated with bidirectional modulation of adipogenic gene methylation in weight-stable overweight adolescents. HOMA-IR decreased in a sub-cohort of adolescents with an adverse metabolic phenotype. Thus, suggesting that more stratified or personalized nutrition approaches may enhance efficacy of dietary interventions.

Clinical and Vitamin Response to a Short-Term Multi-Micronutrient Intervention in Brazilian Children and Teens: From Population Data to Interindividual Responses

SCOPE

Micronutrients are in small amounts in foods, act in concert, and require variable amounts of time to see changes in health and risk for disease. These first principles are incorporated into an intervention study designed to develop new experimental strategies for setting target recommendations for food bioactives for populations and individuals.

METHODS AND RESULTS

A 6-week multivitamin/mineral intervention is conducted in 9-13 year olds. Participants (136) are (i) their own control (n-of-1); (ii) monitored for compliance; (iii) measured for 36 circulating vitamin forms, 30 clinical, anthropometric, and food intake parameters at baseline, post intervention, and following a 6-week washout; and (iv) had their ancestry accounted for as modifier of vitamin baseline or response. The same intervention is repeated the following year (135 participants). Most vitamins respond positively and many clinical parameters change in directions consistent with improved metabolic health to the intervention. Baseline levels of any metabolite predict its own response to the intervention. Elastic net penalized regression models are identified, and significantly predict response to intervention on the basis of multiple vitamin/clinical baseline measures.

CONCLUSIONS

The study design, computational methods, and results are a step toward developing recommendations for optimizing vitamin levels and health parameters for individuals.

A computationally driven analysis of the polyphenol-protein interactome

Polyphenol-rich foods are part of many nutritional interventions aimed at improving health and preventing cardiometabolic diseases (CMDs). Polyphenols have oxidative, inflammatory, and/or metabolic effects. Research into the chemistry and biology of polyphenol bioactives is prolific but knowledge of their molecular interactions with proteins is limited. We mined public data to (i) identify proteins that interact with or metabolize polyphenols, (ii) mapped these proteins to pathways and networks, and (iii) annotated functions enriched within the resulting polyphenol-protein interactome. A total of 1,395 polyphenols and their metabolites were retrieved (using Phenol-Explorer and Dictionary of Natural Products) of which 369 polyphenols interacted with 5,699 unique proteins in 11,987 interactions as annotated in STITCH, Pathway Commons, and BindingDB. Pathway enrichment analysis using the KEGG repository identified a broad coverage of significant pathways of low specificity to particular polyphenol (sub)classes. When compared to drugs or micronutrients, polyphenols have pleiotropic effects across many biological processes related to metabolism and CMDs. These systems-wide effects were also found in the protein interactome of the polyphenol-rich citrus fruits, used as a case study. In sum, these findings provide a knowledgebase for identifying polyphenol classes (and polyphenol-rich foods) that individually or in combination influence metabolism.

Nonlinear transcriptomic response to dietary fat intake in the small intestine of C57BL/6J mice

BACKGROUND

A high caloric diet, in conjunction with low levels of physical activity, promotes obesity. Many studies are available regarding the relation between dietary saturated fats and the etiology of obesity, but most focus on liver, muscle and white adipose tissue. Furthermore, the majority of transcriptomic studies seek to identify linear effects of an external stimulus on gene expression, although such an assumption does not necessarily hold. Our work assesses the dose-dependent effects of dietary fat intake on differential gene expression in the proximal, middle and distal sections of the small intestine in C57BL/6J mice. Gene expression is analyzed in terms of either linear or nonlinear responses to fat intake.

RESULTS

The highest number of differentially expressed genes was observed in the middle section. In all intestine sections, most of the identified processes exhibited a linear response to increasing fat intake. The relative importance of logarithmic and exponential responses was higher in the proximal and distal sections, respectively. Functional enrichment analysis highlighted a constantly linear regulation of acute-phase response along the whole small intestine, with up-regulation of Serpina1b. The study of gene expression showed that exponential down-regulation of cholesterol transport in the middle section is coupled with logarithmic up-regulation of cholesterol homeostasis. A shift from linear to exponential response was observed in genes involved in the negative regulation of caspase activity, from middle to distal section (e.g., Birc5, up-regulated).

CONCLUSIONS

The transcriptomic signature associated with inflammatory processes preserved a linear response in the whole small intestine (e.g., up-regulation of Serpina1b). Processes related to cholesterol homeostasis were particularly active in the middle small intestine and only the highest fat intake down-regulated cholesterol transport and efflux (with a key role played by the down-regulation of ATP binding cassette transporters). Characterization of nonlinear patterns of gene expression triggered by different levels of dietary fat is an absolute novelty in intestinal studies. This approach helps identifying which processes are overloaded (i.e., positive, logarithmic regulation) or arrested (i.e., negative, exponential regulation) in response to excessive fat intake, and can shed light on the relationships linking lipid intake to obesity and its associated molecular disturbances.

A network analysis of cofactor-protein interactions for analyzing associations between human nutrition and diseases

The involvement of vitamins and other micronutrients in intermediary metabolism was elucidated in the mid 1900's at the level of individual biochemical reactions. Biochemical pathways remain the foundational knowledgebase for understanding how micronutrient adequacy modulates health in all life stages. Current daily recommended intakes were usually established on the basis of the association of a single nutrient to a single, most sensitive adverse effect and thus neglect interdependent and pleiotropic effects of micronutrients on biological systems. Hence, the understanding of the impact of overt or sub-clinical nutrient deficiencies on biological processes remains incomplete. Developing a more complete view of the role of micronutrients and their metabolic products in protein-mediated reactions is of importance. We thus integrated and represented cofactor-protein interaction data from multiple and diverse sources into a multi-layer network representation that links cofactors, cofactor-interacting proteins, biological processes, and diseases. Network representation of this information is a key feature of the present analysis and enables the integration of data from individual biochemical reactions and protein-protein interactions into a systems view, which may guide strategies for targeted nutritional interventions aimed at improving health and preventing diseases.

The role of breast-feeding in infant immune system: a systems perspective on the intestinal microbiome

BACKGROUND

The human intestinal microbiota changes from being sparsely populated and variable to possessing a mature, adult-like stable microbiome during the first 2 years of life. This assembly process of the microbiota can lead to either negative or positive effects on health, depending on the colonization sequence and diet. An integrative study on the diet, the microbiota, and genomic activity at the transcriptomic level may give an insight into the role of diet in shaping the human/microbiome relationship. This study aims at better understanding the effects of microbial community and feeding mode (breast-fed and formula-fed) on the immune system, by comparing intestinal metagenomic and transcriptomic data from breast-fed and formula-fed babies.

RESULTS

We re-analyzed a published metagenomics and host gene expression dataset from a systems biology perspective. Our results show that breast-fed samples co-express genes associated with immunological, metabolic, and biosynthetic activities. The diversity of the microbiota is higher in formula-fed than breast-fed infants, potentially reflecting the weaker dependence of infants on maternal microbiome. We mapped the microbial composition and the expression patterns for host systems and studied their relationship from a systems biology perspective, focusing on the differences.

CONCLUSIONS

Our findings revealed that there is co-expression of more genes in breast-fed samples but lower microbial diversity compared to formula-fed. Applying network-based systems biology approach via enrichment of microbial species with host genes revealed the novel key relationships of the microbiota with immune and metabolic activity. This was supported statistically by data and literature.

Monounsaturated fatty acid-enriched high-fat diets impede adipose NLRP3 inflammasome-mediated IL-1β secretion and insulin resistance despite obesity

Saturated fatty acid (SFA) high-fat diets (HFDs) enhance interleukin (IL)-1β-mediated adipose inflammation and insulin resistance. However, the mechanisms by which different fatty acids regulate IL-1β and the subsequent effects on adipose tissue biology and insulin sensitivity in vivo remain elusive. We hypothesized that the replacement of SFA for monounsaturated fatty acid (MUFA) in HFDs would reduce pro-IL-1β priming in adipose tissue and attenuate insulin resistance via MUFA-driven AMPK activation. MUFA-HFD-fed mice displayed improved insulin sensitivity coincident with reduced pro-IL-1β priming, attenuated adipose IL-1β secretion, and sustained adipose AMPK activation compared with SFA-HFD-fed mice. Furthermore, MUFA-HFD-fed mice displayed hyperplastic adipose tissue, with enhanced adipogenic potential of the stromal vascular fraction and improved insulin sensitivity. In vitro, we demonstrated that the MUFA oleic acid can impede ATP-induced IL-1β secretion from lipopolysaccharide- and SFA-primed cells in an AMPK-dependent manner. Conversely, in a regression study, switching from SFA- to MUFA-HFD failed to reverse insulin resistance but improved fasting plasma insulin levels. In humans, high-SFA consumers, but not high-MUFA consumers, displayed reduced insulin sensitivity with elevated pycard-1 and caspase-1 expression in adipose tissue. These novel findings suggest that dietary MUFA can attenuate IL-1β-mediated insulin resistance and adipose dysfunction despite obesity via the preservation of AMPK activity.

Genetic associations with micronutrient levels identified in immune and gastrointestinal networks

The discovery of vitamins and clarification of their role in preventing frank essential nutrient deficiencies occurred in the early 1900s. Much vitamin research has understandably focused on public health and the effects of single nutrients to alleviate acute conditions. The physiological processes for maintaining health, however, are complex systems that depend upon interactions between multiple nutrients, environmental factors, and genetic makeup. To analyze the relationship between these factors and nutritional health, data were obtained from an observational, community-based participatory research program of children and teens (age 6–14) enrolled in a summer day camp in the Delta region of Arkansas. Assessments of erythrocyte S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH), plasma homocysteine (Hcy) and 6 organic micronutrients (retinol, 25-hydroxy vitamin D3, pyridoxal, thiamin, riboflavin, and vitamin E), and 1,129 plasma proteins were performed at 3 time points in each of 2 years. Genetic makeup was analyzed with 1 M SNP genotyping arrays, and nutrient status was assessed with 24-h dietary intake questionnaires. A pattern of metabolites (met_PC1) that included the ratio of erythrocyte SAM/SAH, Hcy, and 5 vitamins were identified by principal component analysis. Met_PC1 levels were significantly associated with (1) single-nucleotide polymorphisms, (2) levels of plasma proteins, and (3) multilocus genotypes coding for gastrointestinal and immune functions, as identified in a global network of metabolic/protein–protein interactions. Subsequent mining of data from curated pathway, network, and genome-wide association studies identified genetic and functional relationships that may be explained by gene–nutrient interactions. The systems nutrition strategy described here has thus associated a multivariate metabolite pattern in blood with genes involved in immune and gastrointestinal functions.

Methylation potential associated with diet, genotype, protein, and metabolite levels in the Delta Obesity Vitamin Study

Micronutrient research typically focuses on analyzing the effects of single or a few nutrients on health by analyzing a limited number of biomarkers. The observational study described here analyzed micronutrients, plasma proteins, dietary intakes, and genotype using a systems approach. Participants attended a community-based summer day program for 6-14 year old in 2 years. Genetic makeup, blood metabolite and protein levels, and dietary differences were measured in each individual. Twenty-four-hour dietary intakes, eight micronutrients (vitamins A, D, E, thiamin, folic acid, riboflavin, pyridoxal, and pyridoxine) and 3 one-carbon metabolites [homocysteine (Hcy), S-adenosylmethionine (SAM), and S-adenosylhomocysteine (SAH)], and 1,129 plasma proteins were analyzed as a function of diet at metabolite level, plasma protein level, age, and sex. Cluster analysis identified two groups differing in SAM/SAH and differing in dietary intake patterns indicating that SAM/SAH was a potential marker of nutritional status. The approach used to analyze genetic association with the SAM/SAH metabolites is called middle-out: SNPs in 275 genes involved in the one-carbon pathway (folate, pyridoxal/pyridoxine, thiamin) or were correlated with SAM/SAH (vitamin A, E, Hcy) were analyzed instead of the entire 1M SNP data set. This procedure identified 46 SNPs in 25 genes associated with SAM/SAH demonstrating a genetic contribution to the methylation potential. Individual plasma metabolites correlated with 99 plasma proteins. Fourteen proteins correlated with body mass index, 49 with group age, and 30 with sex. The analytical strategy described here identified subgroups for targeted nutritional interventions.

PBMCs reflect the immune component of the WAT transcriptome--implications as biomarkers of metabolic health in the postprandial state

SCOPE

Food and nutrition studies often require accessing metabolically active tissues, including adipose tissue. This can involve invasive biopsy procedures that can be a limiting factor in study design. In contrast, peripheral blood mononuclear cells (PBMCs) are a population of circulating immune cells that are easily accessible through venipuncture. As transcriptomics is of growing importance in food and metabolism research, understanding the transcriptomic relationship between these tissue types can provide insight into the utility of PBMCs in this field.

METHODS AND RESULTS

We examine this relationship within eight subjects, in two postprandial states (following oral lipid tolerance test and oral glucose tolerance test). Multivariate analysis techniques were used to examine variation between tissues, samples, and subjects in order to define which genes havecommon/disparate expression profiles associated with highly defined metabolic phenotypes. We demonstrate global similarities in gene expression between PBMCs and white adipose tissue, irrespective of the metabolic challenge type. Closer examination of individual genes revealed this similarity to be strongest in pathways related to immune response/inflammation. Notably, the expression of metabolism-related nuclear receptors, including PPARs, LXR, etc. was discordant between tissues

CONCLUSION

The PBMC transcriptome may therefore provide a unique insight into the inflammatory component of metabolic health, as opposed to directly reflecting the metabolic component of the adipose tissue transcriptome.

Perspective: a systems approach to diabetes research

We review here the status of human type 2 diabetes studies from a genetic, epidemiological, and clinical (intervention) perspective. Most studies limit analyses to one or a few omic technologies providing data of components of physiological processes. Since all chronic diseases are multifactorial and arise from complex interactions between genetic makeup and environment, type 2 diabetes mellitus (T2DM) is a collection of sub-phenotypes resulting in high fasting glucose. The underlying gene–environment interactions that produce these classes of T2DM are imperfectly characterized. Based on assessments of the complexity of T2DM, we propose a systems biology approach to advance the understanding of origin, onset, development, prevention, and treatment of this complex disease. This systems-based strategy is based on new study design principles and the integrated application of omics technologies: we pursue longitudinal studies in which each subject is analyzed at both homeostasis and after (healthy and safe) challenges. Each enrolled subject functions thereby as their own case and control and this design avoids assigning the subjects a priori to case and control groups based on limited phenotyping. Analyses at different time points along this longitudinal investigation are performed with a comprehensive set of omics platforms. These data sets are generated in a biological context, rather than biochemical compound class-driven manner, which we term “systems omics.”

Network analysis of adipose tissue gene expression highlights altered metabolic and regulatory transcriptomic activity in high-fat-diet-fed IL-1RI knockout mice

A subacute inflammatory phenotype is implicated in the pathology of insulin resistance (IR) and type 2 diabetes mellitus. Interleukin (IL)-1α and IL-1β are produced by innate immune cells, including macrophages, and mediate their inflammatory response through the IL-1 type I receptor (IL-IRI). This study sought to understand the transcriptomic signature of adipose tissue in obese IL-1RI(-/-) mice. Following dietary intervention, markers of insulin sensitivity and inflammation in adipose tissue were determined, and gene expression was assessed with microarrays. IL-1RI(-/-) mice fed a high-fat diet (HFD) had significantly lower plasma inflammatory cytokine concentrations than wild-type mice. Metabolic network analysis of transcriptomic effects identified up-regulation and co-expression of genes involved in lipolysis, lipogenesis and tricarboxylic acid (TCA) cycle. Further assessment of gene expression in a network of protein interactions related to innate immunity highlighted Stat3 as a potential transcriptional regulator of IL-1 signalling. The complex, downstream effects of IL-1 signalling through the IL-1RI receptor remain poorly defined. Using network-based analyses of transcriptomic signatures in IL-1RI(-/-) mice, we have identified expression changes in genes involved in lipid cycling and TCA cycle, which may be more broadly indicative of a restoration of mitochondrial function in the context of HFD. Our results also highlight a potential role for Stat3 in linking IL-1 signalling to adipogenesis and IR.

Next-generation sequencing identifies TGF-β1-associated gene expression profiles in renal epithelial cells reiterated in human diabetic nephropathy

Transforming growth factor-beta (TGF-β1) is implicated in the onset and progression of renal fibrosis and diabetic nephropathy (DN), leading to a loss of epithelial characteristics of tubular cells. The transcriptional profile of renal tubular epithelial cells stimulated with TGF-β1 was assessed using RNA-Seq, with 2027 differentially expressed genes identified. Promoter analysis of transcription factor binding sites in the TGF-β1 responsive gene set predicted activation of multiple transcriptional networks, including NFκB. Comparison of RNA-Seq with microarray data from identical experimental conditions identified low abundance transcripts exclusive to RNA-Seq data. We compared these findings to human disease by analyzing transcriptomic data from renal biopsies of patients with DN versus control groups, identifying a shared subset of 179 regulated genes. ARK5, encoding an AMP-related kinase, and TGFBI - encoding transforming growth factor, beta-induced protein were induced by TGF-β1 and also upregulated in human DN. Suppression of ARK5 attenuated fibrotic responses of renal epithelia to TGF-β1 exposure; and silencing of TGFBI induced expression of the epithelial cell marker - E-cadherin. We identified low abundance transcripts in sequence data and validated expression levels of several transcripts (ANKRD56, ENTPD8) in tubular enriched kidney biopsies of DN patients versus living donors. In conclusion, we have defined a TGF-β1-driven pro-fibrotic signal in renal epithelial cells that is also evident in the DN renal transcriptome.

Model-based clustering reveals vitamin D dependent multi-centrality hubs in a network of vitamin-related proteins

Background

Nutritional systems biology offers the potential for comprehensive predictions that account for all metabolic changes with the intricate biological organization and the multitudinous interactions between the cellular proteins. Protein-protein interaction (PPI) networks can be used for an integrative description of molecular processes. Although widely adopted in nutritional systems biology, these networks typically encompass a single category of functional interaction (i.e., metabolic, regulatory or signaling) or nutrient. Incorporating multiple nutrients and functional interaction categories under an integrated framework represents an informative approach for gaining system level insight on nutrient metabolism.

Results

We constructed a multi-level PPI network starting from the interactions of 200 vitamin-related proteins. Its final size was 1,657 proteins, with 2,700 interactions. To characterize the role of the proteins we computed 6 centrality indices and applied model-based clustering. We detected a subgroup of 22 proteins that were highly central and significantly related to vitamin D. Immune system and cancer-related processes were strongly represented among these proteins. Clustering of the centralities revealed a degree of redundancy among the indices; a repeated analysis using subsets of the centralities performed well in identifying the original set of 22 most central proteins.

Conclusions

Hierarchical and model-based clustering revealed multi-centrality hubs in a vitamin PPI network and redundancies among the centrality indices. Vitamin D-related proteins were strongly represented among network hubs, highlighting the pervasive effects of this nutrient. Our integrated approach to network construction identified promiscuous transcription factors, cytokines and enzymes - primarily related to immune system and cancer processes - representing potential gatekeepers linking vitamin intake to disease.

Transcriptomic coordination in the human metabolic network reveals links between n-3 fat intake, adipose tissue gene expression and metabolic health

Understanding the molecular link between diet and health is a key goal in nutritional systems biology. As an alternative to pathway analysis, we have developed a joint multivariate and network-based approach to analysis of a dataset of habitual dietary records, adipose tissue transcriptomics and comprehensive plasma marker profiles from human volunteers with the Metabolic Syndrome. With this approach we identified prominent co-expressed sub-networks in the global metabolic network, which showed correlated expression with habitual n-3 PUFA intake and urinary levels of the oxidative stress marker 8-iso-PGF(2α). These sub-networks illustrated inherent cross-talk between distinct metabolic pathways, such as between triglyceride metabolism and production of lipid signalling molecules. In a parallel promoter analysis, we identified several adipogenic transcription factors as potential transcriptional regulators associated with habitual n-3 PUFA intake. Our results illustrate advantages of network-based analysis, and generate novel hypotheses on the transcriptomic link between habitual n-3 PUFA intake, adipose tissue function and oxidative stress.

Bi-directional gene set enrichment and canonical correlation analysis identify key diet-sensitive pathways and biomarkers of metabolic syndrome

Background

Currently, a number of bioinformatics methods are available to generate appropriate lists of genes from a microarray experiment. While these lists represent an accurate primary analysis of the data, fewer options exist to contextualise those lists. The development and validation of such methods is crucial to the wider application of microarray technology in the clinical setting. Two key challenges in clinical bioinformatics involve appropriate statistical modelling of dynamic transcriptomic changes, and extraction of clinically relevant meaning from very large datasets.

Results

Here, we apply an approach to gene set enrichment analysis that allows for detection of bi-directional enrichment within a gene set. Furthermore, we apply canonical correlation analysis and Fisher's exact test, using plasma marker data with known clinical relevance to aid identification of the most important gene and pathway changes in our transcriptomic dataset. After a 28-day dietary intervention with high-CLA beef, a range of plasma markers indicated a marked improvement in the metabolic health of genetically obese mice. Tissue transcriptomic profiles indicated that the effects were most dramatic in liver (1270 genes significantly changed; p < 0.05), followed by muscle (601 genes) and adipose (16 genes). Results from modified GSEA showed that the high-CLA beef diet affected diverse biological processes across the three tissues, and that the majority of pathway changes reached significance only with the bi-directional test. Combining the liver tissue microarray results with plasma marker data revealed 110 CLA-sensitive genes showing strong canonical correlation with one or more plasma markers of metabolic health, and 9 significantly overrepresented pathways among this set; each of these pathways was also significantly changed by the high-CLA diet. Closer inspection of two of these pathways - selenoamino acid metabolism and steroid biosynthesis - illustrated clear diet-sensitive changes in constituent genes, as well as strong correlations between gene expression and plasma markers of metabolic syndrome independent of the dietary effect.

Conclusion

Bi-directional gene set enrichment analysis more accurately reflects dynamic regulatory behaviour in biochemical pathways, and as such highlighted biologically relevant changes that were not detected using a traditional approach. In such cases where transcriptomic response to treatment is exceptionally large, canonical correlation analysis in conjunction with Fisher's exact test highlights the subset of pathways showing strongest correlation with the clinical markers of interest. In this case, we have identified selenoamino acid metabolism and steroid biosynthesis as key pathways mediating the observed relationship between metabolic health and high-CLA beef. These results indicate that this type of analysis has the potential to generate novel transcriptome-based biomarkers of disease.