David M. Mutch

Nutrigenomics and nutrigenetics: the emerging faces of nutrition

The recognition that nutrients have the ability to interact and modulate molecular mechanisms underlying an organisms physiological functions has prompted a revolution in the field of nutrition. Performing population‐scaled epidemiological studies in the absence of genetic knowledge may result in erroneous scientific conclusions and misinformed nutritional recommendations. To circumvent such issues and more comprehensively probe the relationship between genes and diet, the field of nutrition has begun to capitalize on both the technologies and supporting analytical software brought forth in the post‐genomic era. The creation of nutrigenomics and nutrigenetics, two fields with distinct approaches to elucidate the interaction between diet and genes but with a common ultimate goal to optimize health through the personalization of diet, provide powerful approaches to unravel the complex relationship between nutritional molecules, genetic polymorphisms, and the biological system as a whole. Reluctance to embrace these new fields exists primarily due to the fear that producing overwhelming quantities of biological data within the confines of a single study will submerge the original query; however, the current review aims to position nutrigenomics and nutrigenetics as the emerging faces of nutrition that, when considered with more classical approaches, will provide the necessary stepping stones to achieve the ambitious goal of optimizing an individuals health via nutritional intervention. Mutch, D. M., Wahli, W., Williamson, G. Nutrigenomics and nutrigenetics: the emerging faces of nutrition. FASEB J. 19, 1602–1616 (2005)

The limit fold change model: A practical approach for selecting differentially expressed genes from microarray data

BackgroundThe biomedical community is developing new methods of data analysis to more efficiently process the massive data sets produced by microarray experiments. Systematic and global mathematical approaches that can be readily applied to a large number of experimental designs become fundamental to correctly handle the otherwise overwhelming data sets.ResultsThe gene selection model presented herein is based on the observation that: (1) variance of gene expression is a function of absolute expression; (2) one can model this relationship in order to set an appropriate lower fold change limit of significance; and (3) this relationship defines a function that can be used to select differentially expressed genes. The model first evaluates fold change (FC) across the entire range of absolute expression levels for any number of experimental conditions. Genes are systematically binned, and those genes within the top X% of highest FCs for each bin are evaluated both with and without the use of replicates. A function is fitted through the top X% of each bin, thereby defining a limit fold change. All genes selected by the 5% FC model lie above measurement variability using a within standard deviation (SDwithin) confidence level of 99.9%. Real time-PCR (RT-PCR) analysis demonstrated 85.7% concordance with microarray data selected by the limit function.ConclusionThe FC model can confidently select differentially expressed genes as corroborated by variance data and RT-PCR. The simplicity of the overall process permits selecting model limits that best describe experimental data by extracting information on gene expression patterns across the range of expression levels. Genes selected by this process can be consistently compared between experiments and enables the user to globally extract information with a high degree of confidence.

Unraveling the genetics of human obesity.

The use of modern molecular biology tools in deciphering the perturbed biochemistry and physiology underlying the obese state has proven invaluable. Identifying the hypothalamic leptin/melanocortin pathway as critical in many cases of monogenic obesity has permitted targeted, hypothesis-driven experiments to be performed, and has implicated new candidates as causative for previously uncharacterized clinical cases of obesity. Meanwhile, the effects of mutations in the melanocortin-4 receptor gene, for which the obese phenotype varies in the degree of severity among individuals, are now thought to be influenced by ones environmental surroundings. Molecular approaches have revealed that syndromes (Prader-Willi and Bardet-Biedl) previously assumed to be controlled by a single gene are, conversely, regulated by multiple elements. Finally, the application of comprehensive profiling technologies coupled with creative statistical analyses has revealed that interactions between genetic and environmental factors are responsible for the common obesity currently challenging many Westernized societies. As such, an improved understanding of the different “types” of obesity not only permits the development of potential therapies, but also proposes novel and often unexpected directions in deciphering the dysfunctional state of obesity.

Metabolite Profiling Identifies Candidate Markers Reflecting the Clinical Adaptations Associated with Roux-en-Y Gastric Bypass Surgery

Background Roux-en-Y gastric bypass (RYGB) surgery is associated with weight loss, improved insulin sensitivity and glucose homeostasis, and a reduction in co-morbidities such as diabetes and coronary heart disease. To generate further insight into the numerous metabolic adaptations associated with RYGB surgery, we profiled serum metabolites before and after gastric bypass surgery and integrated metabolite changes with clinical data. Methodology and Principal Findings Serum metabolites were detected by gas and liquid chromatography-coupled mass spectrometry before, and 3 and 6 months after RYGB in morbidly obese female subjects (n = 14; BMI = 46.2±1.7). Subjects showed decreases in weight-related parameters and improvements in insulin sensitivity post surgery. The abundance of 48% (83 of 172) of the measured metabolites changed significantly within the first 3 months post RYGB (p<0.05), including sphingosines, unsaturated fatty acids, and branched chain amino acids. Dividing subjects into obese (n = 9) and obese/diabetic (n = 5) groups identified 8 metabolites that differed consistently at all time points and whose serum levels changed following RYGB: asparagine, lysophosphatidylcholine (C18:2), nervonic (C24:1) acid, p-Cresol sulfate, lactate, lycopene, glucose, and mannose. Changes in the aforementioned metabolites were integrated with clinical data for body mass index (BMI) and estimates for insulin resistance (HOMA-IR). Of these, nervonic acid was significantly and negatively correlated with HOMA-IR (p = 0.001, R = −0.55). Conclusions Global metabolite profiling in morbidly obese subjects after RYGB has provided new information regarding the considerable metabolic alterations associated with this surgical procedure. Integrating clinical measurements with metabolomics data is capable of identifying markers that reflect the metabolic adaptations following RYGB.

Genetic variation in lipid desaturases and its impact on the development of human disease

Perturbations in lipid metabolism characterize many of the chronic diseases currently plaguing our society, such as obesity, diabetes, and cardiovascular disease. Thus interventions that target plasma lipid levels remain a primary goal to manage these diseases. The determinants of plasma lipid levels are multi-factorial, consisting of both genetic and lifestyle components. Recent evidence indicates that fatty acid desaturases have an important role in defining plasma and tissue lipid profiles. This review will highlight the current state-of-knowledge regarding three desaturases (Scd-1, Fads1 and Fads2) and their potential roles in disease onset and development. Although research in rodent models has provided invaluable insight into the regulation and functions of these desaturases, the extent to which murine research can be translated to humans remains unclear. Evidence emerging from human-based research demonstrates that genetic variation in human desaturase genes affects enzyme activity and, consequently, disease risk factors. Moreover, this genetic variation may have a trans-generational effect via breastfeeding. Therefore inter-individual variation in desaturase function is attributed to both genetic and lifestyle components. As such, population-based research regarding the role of desaturases on disease risk is challenged by this complex gene-lifestyle paradigm. Unravelling the contribution of each component is paramount for understanding the inter-individual variation that exists in plasma lipid profiles, and will provide crucial information to develop personalized strategies to improve health management.

Dietary effects of arachidonate-rich fungal oil and fish oil on murine hepatic and hippocampal gene expression

BackgroundThe functions, actions, and regulation of tissue metabolism affected by the consumption of long chain polyunsaturated fatty acids (LC-PUFA) from fish oil and other sources remain poorly understood; particularly how LC-PUFAs affect transcription of genes involved in regulating metabolism. In the present work, mice were fed diets containing fish oil rich in eicosapentaenoic acid and docosahexaenoic acid, fungal oil rich in arachidonic acid, or the combination of both. Liver and hippocampus tissue were then analyzed through a combined gene expression- and lipid- profiling strategy in order to annotate the molecular functions and targets of dietary LC-PUFA.ResultsUsing microarray technology, 329 and 356 dietary regulated transcripts were identified in the liver and hippocampus, respectively. All genes selected as differentially expressed were grouped by expression patterns through a combined k-means/hierarchical clustering approach, and annotated using gene ontology classifications. In the liver, groups of genes were linked to the transcription factors PPARα, HNFα, and SREBP-1; transcription factors known to control lipid metabolism. The pattern of differentially regulated genes, further supported with quantitative lipid profiling, suggested that the experimental diets increased hepatic β-oxidation and gluconeogenesis while decreasing fatty acid synthesis. Lastly, novel hippocampal gene changes were identified.ConclusionsExamining the broad transcriptional effects of LC-PUFAs confirmed previously identified PUFA-mediated gene expression changes and identified novel gene targets. Gene expression profiling displayed a complex and diverse gene pattern underlying the biological response to dietary LC-PUFAs. The results of the studied dietary changes highlighted broad-spectrum effects on the major eukaryotic lipid metabolism transcription factors. Further focused studies, stemming from such transcriptomic data, will need to dissect the transcription factor signaling pathways to fully explain how fish oils and arachidonic acid achieve their specific effects on health.

Polymorphisms in FADS1 and FADS2 alter desaturase activity in young Caucasian and Asian adults

Recent evidence indicates that genetic variation in fatty acid desaturases 1 and 2 (FADS1 and FADS2) is associated with changes in plasma fatty acid profiles; however, the association with altered desaturase activity has not been examined in different ethnic populations. The present study examined whether genetic variation in the FADS gene cluster regulates desaturase activity in two populations of young Canadian adults (Caucasian and Asian) and whether altered desaturase activity was reflected in both n-3 and n-6 fatty acid profiles. FADS1 and FADS2 were genotyped in a random subset of participants (Caucasian, n=78; Asian, n=69) from the Toronto Nutrigenomics and Health study using MALDI-TOF mass spectrometry, and plasma fatty acids were measured by gas chromatography. Desaturase activities were estimated using the following fatty acid ratios: γ-linoleic acid to linoleic acid (GLA:LA), arachidonic acid to linoleic acid (AA:LA), arachidonic acid to dihomo-γ-linoleic acid (AA:DGLA), and eicosapentaneoic acid to α-linolenic acid (EPA:ALA). Nineteen single nucleotide polymorphisms (SNPs) were examined, and several SNPs (9 in Caucasians and 8 in Asians) were associated with various desaturase activities. The most significant association detected was between the FADS1 rs174547 SNP and AA:LA in both Caucasians (p=4.0 × 10(-8)) and Asians (p=5.0 × 10(-5)). Although the minor allele for this SNP differed between Caucasians (T) and Asians (C), carriers of the C allele had a lower desaturase activity than carriers of the T allele in both groups. To determine whether rs174547 was a dominant SNP in the FADS gene cluster, we constructed an additional model which included this SNP as a covariate. Only one SNP (rs498793 in FADS2) remained associated with the EPA:ALA ratio (p=1.1 × 10(-5)) in Asians. This study shows that genetic variation in the FADS gene cluster (in particular rs174547) can alter desaturase activity in subjects of Caucasians and Asian descent.

Needle and surgical biopsy techniques differentially affect adipose tissue gene expression profiles.

BACKGROUND Adipose tissue gene expression analysis in humans now provides a tremendous means to discover the physiopathologic gene targets critical for our understanding and treatment of obesity. Clinical studies are emerging in which adipose gene expression has been examined in hundreds of subjects, and it will be fundamentally important that these studies can be compared so that a common consensus can be reached and new therapeutic targets for obesity proposed. OBJECTIVE We studied the effect of the biopsy sampling methods (needle-aspirated and surgical) used in clinical investigation programs on the functional interpretation of adipose tissue gene expression profiles. DESIGN A comparative microarray analysis of the different subcutaneous adipose tissue sampling methods was performed in age-matched lean (n = 19) and obese (n = 18) female subjects. Appropriate statistical (principal components analysis) and bioinformatic (FunNet) functional enrichment software were used to evaluate data. The morphology of adipose tissue samples obtained by needle-aspiration and surgical methods was examined by immunohistochemistry. RESULTS Biopsy techniques influence the gene expression underlying the biological themes currently discussed in obesity (eg, inflammation, extracellular matrix, and metabolism). Immunohistochemistry experiments showed that the easier to obtain needle-aspirated biopsies poorly aspirate the fibrotic fraction of subcutaneous adipose tissue, resulting in an underrepresentation of the stroma-vascular fraction. CONCLUSIONS The adipose tissue biopsy technique is an important caveat to consider when designing, interpreting, and, most important, comparing microarray experiments. These results will have crucial implications for the clinical and physiopathologic understanding of human obesity and therapeutic approaches.

Adipose tissue pathways involved in weight loss of cancer cachexia

Background:The regulatory gene pathways that accompany loss of adipose tissue in cancer cachexia are unknown and were explored using pangenomic transcriptome profiling.Methods:Global gene expression profiles of abdominal subcutaneous adipose tissue were studied in gastrointestinal cancer patients with (n=13) or without (n=14) cachexia.Results:Cachexia was accompanied by preferential loss of adipose tissue and decreased fat cell volume, but not number. Adipose tissue pathways regulating energy turnover were upregulated, whereas genes in pathways related to cell and tissue structure (cellular adhesion, extracellular matrix and actin cytoskeleton) were downregulated in cachectic patients. Transcriptional response elements for hepatic nuclear factor-4 (HNF4) were overrepresented in the promoters of extracellular matrix and adhesion molecule genes, and adipose HNF4 mRNA was downregulated in cachexia.Conclusions:Cancer cachexia is characterised by preferential loss of adipose tissue; muscle mass is less affected. Loss of adipose tissue is secondary to a decrease in adipocyte lipid content and associates with changes in the expression of genes that regulate energy turnover, cytoskeleton and extracellular matrix, which suggest high tissue remodelling. Changes in gene expression in cachexia are reciprocal to those observed in obesity, suggesting that regulation of fat mass at least partly corresponds to two sides of the same coin.

Fatty acid–gene interactions, adipokines and obesity

It is now recognized that the low-grade inflammation observed with obesity is associated with the development of a wide range of downstream complications. As such, there is considerable interest in elucidating the regulatory mechanisms underlying the production of inflammatory molecules to improve the prevention and treatment of obesity and its co-morbidities. White adipose tissue is no longer considered a passive reservoir for storing lipids, but rather an important organ influencing energy metabolism, insulin sensitivity and inflammation by the secretion of proteins, commonly referred to as adipokines. Dysregulation of several adipokines, such as tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6) and adiponectin, contributes to the low-grade inflammation that is a hallmark of obesity. Evidence now suggests that fatty acids represent a class of molecules that can modulate adipokine production, thereby influencing inflammatory status. Although the precise molecular mechanisms by which dietary fats regulate adipokine production remain unclear, recent findings indicate that diet–gene interactions may have an important role in the transcriptional and secretory regulation of adipokines. Single-nucleotide polymorphisms in the genes encoding TNF-α, IL-6 and adiponectin can modify circulating levels of these adipokines and, subsequently, obesity-related phenotypes. This genetic variation can also alter the influence of dietary fatty acids on adipokine production. Therefore, the current review will show that it is paramount to consider both genetic information and dietary fat intake to unravel the inter-individual variability in inflammatory response observed in intervention protocols targeting obesity.