It is well established that replacing dietary saturated fatty acids with unsaturated fatty acids reduces cardiovascular disease (CVD) risk. Although epidemiological and clinical evidence indicate health benefits of consuming various fatty acid classes including n-9, n-6, and short- and longer-chain n-3 fatty acids, current dietary recommendations fall short of providing the optimal amounts of these fatty acids in daily diets. In addition, significant knowledge gaps remain in our understanding of the effects of, and mechanisms underpinning the action of, the various fatty acid classes on risk factors for CVD. The objective of this research was to contribute to the evaluation of health benefits of using different dietary oils, and determine how these benefits may play a role in improving public health and decreasing CVD risk. Additionally, this research examined effects of diet-gene interactions, endogenous fatty acid ethanolamides (FAEs) on body fat mass distribution as well as changes in the composition of gut microbiota following consumption of dietary oil treatments. The Canola Oil Multicenter Intervention Trial (COMIT) was conducted as a 5-phase randomized, controlled, double-blind, cross-over clinical trial. Each 4-wk treatment period was separated by 4-wk washout intervals. A total of 130 volunteers with abdominal obesity consumed each of 5 identical weight-maintaining, fixed-composition diets with one of the following treatment oils (60 g/3000 kcal) in the form of beverages: 1) conventional canola oil (Canola; n-9 rich), 2) high–oleic acid canola oil with docosahexaenoic acid (CanolaDHA; n-9 and n-3 rich), 3) a blend of corn and safflower oil (25:75) (CornSaff; n-6 rich), 4) a blend of flax and safflower oils (60:40) (FlaxSaff; n-6 and short-chain n-3 rich), and 5) high–oleic acid canola oil (CanolaOleic; highest in n-9). At endpoints, plasma fatty acid levels reflected the differences in fatty acid composition of five dietary treatments. All diets lowered total cholesterol (TC) compared with baseline. TC was lowest after the FlaxSaff phase and highest after CanolaDHA. The CanolaDHA treatment improved HDL-C, triglycerides, and blood pressure thereby reducing Framingham risk scores compared with other oils varying in unsaturated fatty acid composition. Homozygotes minor allele carriers of rs174583 (TT) on FADS2 gene showed lower (P<0.01) plasma EPA and DPA levels across all diets, but no differences were observed in DHA concentrations after the CanolaDHA feeding. In addition, plasma FAE levels were positively associated with plasma fatty acid profiles. Minor allele A carriers of rs324420 of FAAH gene showed a higher (P<0.05) plasma FAE levels compared with major allele C carriers across all diets, and showed higher (P=0.0002) docosahexaenoylethanolamide levels in response to the CanolaDHA diet. Impacts of consuming 60 g of five dietary oil treatments on gut microbiota composition were relatively minor at the phylum level and mainly at the genus level, while BMI contributed to a significant shift at the phylum level. In conclusion, consumption of a novel DHA-enriched canola oil improved blood lipid profile and largely reduced CVD risk. Diet-gene interactions might help identify sub-populations who appear to benefit from increased consumption of DHA and oleic acid. The metabolic and physiological responses to dietary fatty acids may be influenced via circulating FAEs, while the altered microbiota profile by shifts in MUFA and/or PUFA may be associated with specific physiological effect. Personalized diets varying in unsaturated fatty acids composition based on specific lifestyles, environmental factors, psychosocial factors, and genetic make-ups will become the future “healthy eating” recommendations to prevent CVD risk. / May 2016

After reviewing Multifactor Dimensionality Reduction(MDR) and its extensions, an approach to obtain P(larger than 1) risk scores is proposed to predict the continuous outcome for each subject. We study the mean square error(MSE) of dimensionality reduced models fitted with sets of 2 risk scores and investigate the MSE for several special cases of the covariance matrix. A methodology is proposed to select a best set of P risk scores when P is specified a priori. Simulation studies based on true models of different dimensions(larger than 3) demonstrate that the selected set of P(larger than 1) risk scores outperforms the single aggregated risk score generated in AQMDR and illustrate that our methodology can determine a best set of P risk scores effectively. With different assumptions on the dimension of the true model, we considered the preferable set of risk scores from the best set of two risk scores and the best set of three risk scores. Further, we present a methodology to access a set of P risk scores when P is not given a priori. The expressions of asymptotic estimated mean square error of prediction(MSPE) are derived for a 1-dimensional model and 2-dimensional model. In the last main chapter, we apply the methodology of selecting a best set of risk scores where P has been specified a priori to Alzheimer’s Disease data and achieve a set of 2 risk scores and a set of three risk scores for each subject to predict measurements on biomarkers that are crucially involved in Alzheimer’s Disease.

The missing heritability in genome-wide association studies (GWAS) is an intriguing open scientific problem which has attracted great recent interest. The interaction effects among risk factors, both genetic and environmental, are hypothesized to be one of the main missing heritability sources. Moreover, detection of multilocus interaction effect may also have great implications for revealing disease/biological mechanisms, for accurate risk prediction, personalized clinical management, and targeted drug design. However, current analysis of GWAS largely ignores interaction effects, partly due to the lack of tools that meet the statistical and computational challenges posed by taking into account interaction effects. Here, we propose a novel statistically-based framework (Significant Conditional Association) for systematically exploring, assessing significance, and detecting interaction effect. Further, our SCA work has also revealed new theoretical results and insights on interaction detection, as well as theoretical performance bounds. Using in silico data, we show that the new approach has detection power significantly better than that of peer methods, while controlling the running time within a permissible range. More importantly, we applied our methods on several real data sets, confirming well-validated interactions with more convincing evidence (generating smaller p-values and requiring fewer samples) than those obtained through conventional methods, eliminating inconsistent results in the original reports, and observing novel discoveries that are otherwise undetectable. The proposed methods provide a useful tool to mine new knowledge from existing GWAS and generate new hypotheses for further research. Microarray gene expression studies provide new opportunities for the molecular characterization of heterogeneous diseases. Multiclass gene selection is an imperative task for identifying phenotype-associated mechanistic genes and achieving accurate diagnostic classification. Most existing multiclass gene selection methods heavily rely on the direct extension of two-class gene selection methods. However, simple extensions of binary discriminant analysis to multiclass gene selection are suboptimal and not well-matched to the unique characteristics of the multi-category classification problem. We report a simpler and yet more accurate strategy than previous works for multicategory classification of heterogeneous diseases. Our method selects the union of one-versus-everyone phenotypic up-regulated genes (OVEPUGs) and matches this gene selection with a one-versus-rest support vector machine. Our approach provides even-handed gene resources for discriminating both neighboring and well-separated classes, and intends to assure the statistical reproducibility and biological plausibility of the selected genes. We evaluated the fold changes of OVEPUGs and found that only a small number of high-ranked genes were required to achieve superior accuracy for multicategory classification. We tested the proposed OVEPUG method on six real microarray gene expression data sets (five public benchmarks and one in-house data set) and two simulation data sets, observing significantly improved performance with lower error rates, fewer marker genes, and higher performance sustainability, as compared to several widely-adopted gene selection and classification methods. / Ph. D.

O leite bovino é um alimento essencial na nutrição humana, principalmente para os mais jovens por ser uma fonte importante de proteínas, minerais e vitaminas. A crescente demanda por quantidade e qualidade de leite nos últimos anos tem impulsionado inúmeras pesquisas, principalmente em relação ao perfil de ácidos graxos por diferir substancialmente das exigências humanas. Nutrição e melhoramento genético são os principais fatores capazes de promover a alteração da qualidade nutricional do leite. Por muito tempo as mudanças alcançadas via melhoramento genético foram obtidas exclusivamente com base na genética quantitativa, mas a partir dos anos 90 o interesse nesta área passou a ser divido com a genética molecular. Os avanços alcançados na biologia molecular obtidos por meio do mapeamento e sequenciamento do genoma das diversas espécies e de estudos de associação fenótipo-genótipo vêm auxiliando a explicar o fundo genético das características quantitativas. Atualmente, a maioria dos estudos de associação fenótipo-genótipo foram delineados para estimar apenas efeitos genéticos aditivos em um único lócus. No entanto, parte da variação observada nestes fenótipos resultam da interação entre loci ou genes, tornando estes estudos fundamentais para conhecer a origem da variação biológica destas características. Assim, os objetivos deste estudo foram: I) Associar polimorfismos de nucleotídeo único (SNPs) com características produtivas e o perfil de ácidos graxos no leite; e II) Identificar interações entre os SNPs associados a estas características no leite de bovinos da raça Holandesa. Fenótipo ajustado de 760 vacas para o efeito fixo de grupo de contemporâneo e covariáveis dias em lactação, idade à mensuração e produção de leite, e 6.553 SNPs foram considerados para realizar a associação por meio de regressão SNP a SNP. No total nove SNPs foram associados a uma ou mais características relacionadas ao teor de gordura e perfil de ácidos graxos. Algumas destas associações evidenciam a presença de epistasia e/ou pleiotropia entre estas regiões. Para a identificação de interação entre os SNPs, foram usados modelos que consideraram os efeitos individuais (aditivo e dominante) e os efeitos individuais e de interação entre os nove SNPs para comparação por meio do teste de razão de verossimilhança (LRT). Foi observado efeito epistático aditivo x dominante (P < 0,01) somente entre os marcadores ARS-BFGL-NGS-71749 e ARS-BFGL-NGS-34135, ambos situados no cromossomo 14 bovino (BTA14), para as características teor de ácidos graxos saturados e teor de ácido palmítico (C16:0). Para o melhor entendimento da sua interação biológica existe ainda a necessidade de maior conhecimento sobre as rotas metabólicas em que tais genes identificados estão situados estes marcadores. Mais estudos nestas regiões cromossômicas possibilitarão ampliar o conhecimento sobre os genes e suas interações. / Bovine milk is an essential food in human nutrition, especially for younger people for being as important source of proteins, minerals and vitamins. The growing for quantity and quality for milk in recent years has stimulated numerous studies, especially regarding the fatty acid profile by differ substantially of human requirements. Nutrition and animal breeding are the main factors which would enhance change the nutritional quality of cow milk. For a long time the changes achieved by animal breeding were obtained purely based on quantitative genetics, but from 90 the interest in this area came to be divided with molecular genetics. The advances made in the molecular biology obtained through the mapping and sequencing of the genomes of different species and genome-wide association studies is helping to explain more about the genetic background of quantitative traits. Currently, most of genome-wide association studies were designed to estimate additive genetic effects only at a single locus, excluding additional effects. However, part of the observed variation in these phenotypes result from the interaction between genes or loci, thus, such studies are also important for the understanding of the origin of biological variation of these traits, such as their metabolic and biochemical pathways. The aims of this study were: I) Associate single nucleotide polymorphisms (SNPs) with production traits and fatty acid profile in milk; and II) Identify interactions between SNPs associated with these traits in milk from Holstein cows. Phenotype adjusted of 760 cows for the fixed effects of contemporary group and covariates days in milk, age at measurement and milk yield, and information from 6,553 SNPs were considered for performing the association using single SNP regression method. A total of nine SNPs were associated with one or more traits related to the fat percentage and fatty acid profile. Some of these associations showed the presence of epistasis and/or pleiotropy between these regions. To identify interaction between SNPs, models that consider the individual effects (additive and dominance); and individual and interaction effects between the nine SNPs for comparison using the likelihood ratio test (LRT). Additive x dominance epistatic effect (P < 0.01) was observed only between markers ARS-BFGL-NGS- 71749 and ARS-BFGL-NGS-34135, both located on chromosome 14 (Bos taurus autossome, BTA14), for fat percentage (FP), saturated fatty acids (SFA) and palmitic acid (C16:0). For a better understanding of its biological interaction there is a need for greater knowledge of the metabolic pathways in with these genes identified these markers are located. More studies will enable these chromosomal regions expand knowledge about genes and their interactions.

O leite bovino é um alimento essencial na nutrição humana, principalmente para os mais jovens por ser uma fonte importante de proteínas, minerais e vitaminas. A crescente demanda por quantidade e qualidade de leite nos últimos anos tem impulsionado inúmeras pesquisas, principalmente em relação ao perfil de ácidos graxos por diferir substancialmente das exigências humanas. Nutrição e melhoramento genético são os principais fatores capazes de promover a alteração da qualidade nutricional do leite. Por muito tempo as mudanças alcançadas via melhoramento genético foram obtidas exclusivamente com base na genética quantitativa, mas a partir dos anos 90 o interesse nesta área passou a ser divido com a genética molecular. Os avanços alcançados na biologia molecular obtidos por meio do mapeamento e sequenciamento do genoma das diversas espécies e de estudos de associação fenótipo-genótipo vêm auxiliando a explicar o fundo genético das características quantitativas. Atualmente, a maioria dos estudos de associação fenótipo-genótipo foram delineados para estimar apenas efeitos genéticos aditivos em um único lócus. No entanto, parte da variação observada nestes fenótipos resultam da interação entre loci ou genes, tornando estes estudos fundamentais para conhecer a origem da variação biológica destas características. Assim, os objetivos deste estudo foram: I) Associar polimorfismos de nucleotídeo único (SNPs) com características produtivas e o perfil de ácidos graxos no leite; e II) Identificar interações entre os SNPs associados a estas características no leite de bovinos da raça Holandesa. Fenótipo ajustado de 760 vacas para o efeito fixo de grupo de contemporâneo e covariáveis dias em lactação, idade à mensuração e produção de leite, e 6.553 SNPs foram considerados para realizar a associação por meio de regressão SNP a SNP. No total nove SNPs foram associados a uma ou mais características relacionadas ao teor de gordura e perfil de ácidos graxos. Algumas destas associações evidenciam a presença de epistasia e/ou pleiotropia entre estas regiões. Para a identificação de interação entre os SNPs, foram usados modelos que consideraram os efeitos individuais (aditivo e dominante) e os efeitos individuais e de interação entre os nove SNPs para comparação por meio do teste de razão de verossimilhança (LRT). Foi observado efeito epistático aditivo x dominante (P < 0,01) somente entre os marcadores ARS-BFGL-NGS-71749 e ARS-BFGL-NGS-34135, ambos situados no cromossomo 14 bovino (BTA14), para as características teor de ácidos graxos saturados e teor de ácido palmítico (C16:0). Para o melhor entendimento da sua interação biológica existe ainda a necessidade de maior conhecimento sobre as rotas metabólicas em que tais genes identificados estão situados estes marcadores. Mais estudos nestas regiões cromossômicas possibilitarão ampliar o conhecimento sobre os genes e suas interações. / Bovine milk is an essential food in human nutrition, especially for younger people for being as important source of proteins, minerals and vitamins. The growing for quantity and quality for milk in recent years has stimulated numerous studies, especially regarding the fatty acid profile by differ substantially of human requirements. Nutrition and animal breeding are the main factors which would enhance change the nutritional quality of cow milk. For a long time the changes achieved by animal breeding were obtained purely based on quantitative genetics, but from 90 the interest in this area came to be divided with molecular genetics. The advances made in the molecular biology obtained through the mapping and sequencing of the genomes of different species and genome-wide association studies is helping to explain more about the genetic background of quantitative traits. Currently, most of genome-wide association studies were designed to estimate additive genetic effects only at a single locus, excluding additional effects. However, part of the observed variation in these phenotypes result from the interaction between genes or loci, thus, such studies are also important for the understanding of the origin of biological variation of these traits, such as their metabolic and biochemical pathways. The aims of this study were: I) Associate single nucleotide polymorphisms (SNPs) with production traits and fatty acid profile in milk; and II) Identify interactions between SNPs associated with these traits in milk from Holstein cows. Phenotype adjusted of 760 cows for the fixed effects of contemporary group and covariates days in milk, age at measurement and milk yield, and information from 6,553 SNPs were considered for performing the association using single SNP regression method. A total of nine SNPs were associated with one or more traits related to the fat percentage and fatty acid profile. Some of these associations showed the presence of epistasis and/or pleiotropy between these regions. To identify interaction between SNPs, models that consider the individual effects (additive and dominance); and individual and interaction effects between the nine SNPs for comparison using the likelihood ratio test (LRT). Additive x dominance epistatic effect (P < 0.01) was observed only between markers ARS-BFGL-NGS- 71749 and ARS-BFGL-NGS-34135, both located on chromosome 14 (Bos taurus autossome, BTA14), for fat percentage (FP), saturated fatty acids (SFA) and palmitic acid (C16:0). For a better understanding of its biological interaction there is a need for greater knowledge of the metabolic pathways in with these genes identified these markers are located. More studies will enable these chromosomal regions expand knowledge about genes and their interactions.

Introduction – Animal studies suggested that NFKB1, SOCS3 and IKBKB genes could be involved in the association between overnutrition and obesity. This study aims to investigate interactions involving these genes and nutrition affecting obesity-related phenotypes. Methods – We used multifactor dimensionality reduction (MDR) and penalized logistic regression (PLR) to better detect gene/environment interactions in data from the Toronto Nutrigenomics and Health Study (n=1639) using dichotomized body mass index (BMI) and waist circumference (WC) as obesity-related phenotypes. Exposure variables included genotypes on 54 single nucleotide polymorphisms, dietary factors and ethnicity. Results – MDR identified interactions between SOCS3 rs6501199 and rs4969172, and IKBKB rs3747811 affecting BMI in whites; SOCS3 rs6501199 and NFKB1 rs1609798 affecting WC in whites; and SOCS3 rs4436839 and IKBKB rs3747811 affecting WC in South Asians. PLR found a main effect of SOCS3 rs12944581 on BMI among South Asians. Conclusion – MDR and PLR gave different results, but support some results from previous studies.

Cancer is a complex disease with diverse genetic changes that pose significant treatment challenges due to its heterogeneity. Identifying driver modules, which are crucial for cancer progression, has been aided by artificial intelligence (AI) techniques. However, existing approaches lack specificity, particularly for cancer types like lung cancer. This thesis addresses this gap by proposing a method that combines a gene-gene interaction network construction with AI-based clustering to identify distinct driver modules specific to lung cancer. The research aims to enhance our understanding of the disease by leveraging publicly available databases and large datasets using design science methodology. By mapping biological processes to genes and constructing a weighted gene-gene interaction network, correlations within gene clusters are identified. A clustering algorithm is applied to derive potential cancer-driver modules and pinpoint biologically relevant modules that contribute to the development of lung cancer. The results demonstrate the effectiveness and robustness of the clustering approach, with 110 unique and non-overlapping clusters identified, ranging in size from 4 to 10. These clusters surpass the evaluation requirements and exhibit significant relevance to critical pathways. The findings challenge previous assumptions about gene clusters and their significance in lung cancer, providing insights into the molecular underpinnings of the disease. The identified driver modules hold promise for influencing future approaches to diagnosis, prognosis, and treatment in the management of lung cancer. By expanding our understanding of the disease, this research paves the way for further investigations and potential clinical advancements.

A metamorfose em insetos é um dos mais complexos e belos eventos biológicos conhecidos, dirigido por sucessivas alterações morfo-fisiológicas. Este intricado processo é coordenado por componentes moleculares como ecdisteroides (20E) e hormônio juvenil (HJ), fatores de transcrição e microRNAs (miRNAs). Os miRNAs regulam a expressão de genes-alvo, que por sua vez orquestram alterações fisiológicas e anatômicas necessárias para o completo desenvolvimento do organismo. Apesar do enorme esforço, os circuitos genéticos e endócrinos que regulam a metamorfose em insetos sociais, como a abelha Apis mellifera, estão longe de serem completamente esclarecidos. Os miRNAs são importantes componentes da maquinaria celular e parecem ser ubíquos no controle de processos biológicos. Desvendar novas interações miRNA-mRNAs alvo envolvidas com a metamorfose e a regulação das cascatas de 20E e HJ lançará uma luz sobre esse complexo evento. Em nosso estudo nós investigamos os papéis de miR-34, miR-281, miR-252a e miR-252b, conhecidos como reguladores da metamorfose em insetos, no modelo A. mellifera. Todos estes miRNAs revelaram alto grau de conservação filogenética, bem como responderam ao tratamento com 20E, sofrendo flutuações na abundância de transcritos. Usando as informações disponíveis e nossos bancos de dados, nós identificamos interações envolvendo estes miRNAs e genes participantes nas cascatas de HJ e 20E: ultraspiracle (Usp), fushi tarazu-transcription factor 1 (ftz-f1), ecdysone receptor (EcR), calponin (chd64), insulin receptor 2 (inr2), e Krüppel homolog 1 (Krh1). A predição das interações miRNA-mRNAs alvo revelou que os receptores de ecdisteroides EcR e Usp, bem como o fator de transcrição ftz-f1 são alvos importantes dos miRNAs estudados, apresentando sítios para os quatros miRNAs investigados. Observamos também que os seis genes codificadores de proteína são putativamente alvejados por miR-34. Por meio do ensaio da luciferase, pudemos validar as interações entre miR-34 e os alvos Kr-h1, chd64 e inr2; miR-252a e os alvos ftz-f1 e EcR; miR-252b e os alvos chd64 e ftz-f1; miR-281 e os alvos ftz-f1, EcR e Usp. A investigação dos perfis de expressão dos miRNAs ao longo do desenvolvimento larval (L3-PP3) e pupal (Pw), contrastados com os perfis de seus respectivos alvos, apontou muitos casos de relações positivas miRNA-mRNA. Estes resultados complementaram os resultados de validação, e expuseram a regulação exercida pelo miRNA sobre seus alvos. Juntos, os nossos resultados apontam para novas interações miRNA-mRNAs, envolvidas com a metamorfose em A. mellifera. As regulações por nós propostas e validadas bem como suas caracterizações e relações com os hormônios reguladores da metamorfose, são inéditas e acrescentam muito ao conhecimento sobre a regulação da metamorfose em A. mellifera. Nesse contexto, nossa pesquisa definitivamente contribui para uma melhor compreensão dos eventos moleculares envolvidos com a metamorfose de abelhas. / Insect metamorphosis is one of the most complex and beautiful of known biological events; it consists of successive morphological and physiological alterations. This intricate process is coordinated by various molecular components, including ecdysteroids (20E), juvenile hormone (JH), transcription factors and microRNAs (miRNAs). The miRNAs regulate gene expression, which in turn orchestrates physiological and anatomical changes necessary for successful insect ontogeny. Despite enormous efforts, the endocrine and genetic circuits that regulate metamorphosis in social insects, such as honey bees (Apis mellifera), are far from being completely elucidated. The miRNAs are a substantial component of this molecular machinery and seem to be ubiquitously involved in the control of biological processes. Disclosing new miRNA-target interactions involved in metamorphosis and in the regulation of 20E and JH cascades can shed light on these poorly understood events. In this study, we provide new pieces to this puzzle. We investigated the roles of miR-34, miR-281, miR-252a and miR-252b, known to be important regulators of insect metamorphosis, in the A. mellifera model. All of these miRNAs revealed a high degree of phylogenetic conservation and responded to treatment with 20E, which altered transcript abundance. Using available information and our databases, we identified interactions involving these miRNAs and the component genes of JH and 20E pathways: ultraspiracle (Usp), fushi tarazu-transcription factor 1 (ftz-f1), ecdysone receptor (EcR), calponin (chd64), insulin receptor 2 (inr2), and Krüppel homolog 1 (Kr-h1). Prediction of miRNA-target interactions revealed that the ecdysteroid receptors EcR and Usp and the transcription factor ftz-f1 are highly targeted by miRNAs involved in metamorphosis; they presented binding sites for all four miRNAs. We also observed that all six-protein coding genes are putatively targeted by miR-34. Using the luciferase assay, we were able to validate the interactions of miR-34 with the targets Krh1, chd64 and inr2; miR-252a with the targets ftz-f1 and EcR; miR-252b with the targets chd64 and ftz-f1; and miR-281 with the targets ftz-f1, EcR and Usp. Investigation of miRNA expression profiles during larval (L3-PP3) and pupal (Pw) development, as a function of the profiles of their respective targets, demonstrated many cases of positive miRNA-mRNA relationships. These results complemented the validation results, showing how the miRNAs regulate their targets. In conclusion, we identified various previously unknown miRNA-mRNA interactions involved in the metamorphosis of A. mellifera. The regulatory pathways proposed and validated by us, as well as their characterizations and relationships with metamorphosis regulator hormones, are unique and add to the understanding of the regulation of metamorphosis in A. mellifera. In this context, our research contributes to a better understanding of the molecular events involved in honey bee metamorphosis.

Background: The adequacy of serum ascorbic acid (vitamin C) concentrations in young Canadian adults is unknown. Individuals have varied serum ascorbic acid response to dietary vitamin C, possibly due to genetic variation. Objective: To investigate the prevalence of serum ascorbic acid deficiency in young Canadians and to determine whether common genotypes modify the association between dietary vitamin C and serum ascorbic acid. Methods: Subjects were 1277 men and women aged 20-29 years from the Toronto Nutrigenomics and Health study. Vitamin C intakes were estimated by a 196-item FFQ. Fasting blood was collected to measure serum ascorbic acid by HPLC and to genotype for common polymorphisms in genes that code for glutathione S-transferase (GST) (GSTM1, GSTT1 and GSTP1), haptoglobin (Hp), and vitamin C transporters (SLC23A1 and SLC23A2). Results: 53% of subjects had adequate, 33% had suboptimal and 14% had deficient serum ascorbic acid. Subjects with deficiency had higher mean C-reactive protein, waist circumference, BMI and blood pressure than subjects with adequate serum ascorbic acid. The odds ratio (95% confidence interval) for serum ascorbic acid deficiency was 3.43 (2.14, 5.50) for subjects who did not meet the vitamin C recommendation compared to those who did. The corresponding odds ratios were 2.17 (1.10, 4.28) and 12.28 (4.26, 33.42) for individuals with the GSTT1 functional and null genotypes respectively (interaction p=0.01), and 2.29 (0.96, 5.45) and 4.03 (2.01, 8.09) for the GSTM1 functional and null genotypes (interaction p=0.04). These odds ratios were 4.77 (2.36, 9.65) for the Hp2-2 genotype, but 1.69 (0.80, 3.63) for carriers of the Hp1 allele (interaction p=0.02). Serum ascorbic acid concentrations (mean +/- SE) differed among SLC23A1 rs4257763 genotypes (GG: 24.4 +/- 1.3, GA: 26.8 +/- 1.1, AA: 29.7 +/- 1.4, p=0.002). Conclusions: Serum ascorbic acid deficiency is prevalent and associated with markers of chronic disease. Individuals with GST null or Hp2-2 genotypes had an increased risk of deficiency if they did not meet the recommendation for vitamin C, suggesting that GSTs and haptoglobin may spare ascorbic acid when dietary vitamin C is insufficient, thus protecting against serum ascorbic acid deficiency.

Background: The adequacy of serum ascorbic acid (vitamin C) concentrations in young Canadian adults is unknown. Individuals have varied serum ascorbic acid response to dietary vitamin C, possibly due to genetic variation. Objective: To investigate the prevalence of serum ascorbic acid deficiency in young Canadians and to determine whether common genotypes modify the association between dietary vitamin C and serum ascorbic acid. Methods: Subjects were 1277 men and women aged 20-29 years from the Toronto Nutrigenomics and Health study. Vitamin C intakes were estimated by a 196-item FFQ. Fasting blood was collected to measure serum ascorbic acid by HPLC and to genotype for common polymorphisms in genes that code for glutathione S-transferase (GST) (GSTM1, GSTT1 and GSTP1), haptoglobin (Hp), and vitamin C transporters (SLC23A1 and SLC23A2). Results: 53% of subjects had adequate, 33% had suboptimal and 14% had deficient serum ascorbic acid. Subjects with deficiency had higher mean C-reactive protein, waist circumference, BMI and blood pressure than subjects with adequate serum ascorbic acid. The odds ratio (95% confidence interval) for serum ascorbic acid deficiency was 3.43 (2.14, 5.50) for subjects who did not meet the vitamin C recommendation compared to those who did. The corresponding odds ratios were 2.17 (1.10, 4.28) and 12.28 (4.26, 33.42) for individuals with the GSTT1 functional and null genotypes respectively (interaction p=0.01), and 2.29 (0.96, 5.45) and 4.03 (2.01, 8.09) for the GSTM1 functional and null genotypes (interaction p=0.04). These odds ratios were 4.77 (2.36, 9.65) for the Hp2-2 genotype, but 1.69 (0.80, 3.63) for carriers of the Hp1 allele (interaction p=0.02). Serum ascorbic acid concentrations (mean +/- SE) differed among SLC23A1 rs4257763 genotypes (GG: 24.4 +/- 1.3, GA: 26.8 +/- 1.1, AA: 29.7 +/- 1.4, p=0.002). Conclusions: Serum ascorbic acid deficiency is prevalent and associated with markers of chronic disease. Individuals with GST null or Hp2-2 genotypes had an increased risk of deficiency if they did not meet the recommendation for vitamin C, suggesting that GSTs and haptoglobin may spare ascorbic acid when dietary vitamin C is insufficient, thus protecting against serum ascorbic acid deficiency.