NUT 116 Lec 4 - Nutritional Phenotype

most chronic diseases are

complex/multiple gene disorders or polygenic diseases

clinical phenotype

susceptibility genes + environmental factors

diets do not…

benefit everyone the same

EX of heterogeneity of biologic responses to nutrition inputs

• gave participants fat based meal and measured TAG

• see huge variability in ppl

  • influenced by metabolic traits (weight, insulin resistance)

  • or other factors ( behavior, microbiome) 

• 5 individuals, 5 diff responses

heterogeneity of responses can be related to 

phenotypic differences

• can be observed in lean vs obese state

• bw

• blood pressure/hypertension

• insulin resistance

• diabetes

phenotypic differences can influenced

metabolic response to nutrition

• body size, adiposity

• presence of disease or disease risk factor

• microbiome

precision or personalized nutrition seek to understand phenotypic differences and better predict responses to

make tailored dietary reccs

variation in response is related to

biological and phenotypic complexity

biologic and phenotypic variability

• complex interactions between multiple

• gene x environment; gene x diet; diet x microbiome interactions

• epigenetic changes

• underlying pathology or disease risk

metabolic flexibility

ability of cells and tissues to switch fuel sources, alter gene expression, adapt to various stressors, magnitude of resposes

why so much variability in diff individuals’ responses to foods and diet patterns

• health affected by complex, dynamic interactions between genetics, epigenetics, diet, environment and lifestyle, physio state and age

• diet is heterogenous and adds complexity to diet x gene and die metabolism interactions

how monitor and study metabolic responses?

omics approach

omics approach

• genomic

  • what can happen and what appears to be happening (transcriptomic) 

  • based on DNA person has and RNA being produced 

• proteogenomic

  • what makes it happen 

  • proteins being made based on active gene

• metabolomic 

  • what has happened and what is happening in metabolic pathways measured by circulating or excreted metabolites 

types of gene-environmental interactions and effects on a health risk 

• risk allele present, health risk is greater even without environmental exposure

• with environmental exposure, magnitude of health risk significantly greater than when risk allele present

• even medium dose of environmental exposure greater effect when risk allele present 

type of gene-environment interactions and effects on health risk 

• health risk associates with risk allele but all genotypes change in same way to exposure

• slope of lines same/parallel

• no gene x diet interaction

type of gene-environment interactions and effects on health risk 

• effect of diet somewhat similar on all alleles (same direction), but slope differs by genotype

• diet exposure differentially affects genotype (slope of line changes)

• gene x diet interaction present

type of gene-environment interactions and effects on health risk 

• diet affects each allele of gene differently, differential effects of diet clearly seen by genotype

• slope and direction of all lines vary

• gene x diet interaction present

metabolomics

identification and quantification of metabolites in biologic stem

• metabolites: low MW compounds, are reactants, intermediates, or products of biochemical rxn

• measured in biologic fluids

• tool and analytical apporach allows profile of biochem of individual to be described

• links genotype with phenotype 

• assumes individual’s metabolic state reflects their health status 

• provides means to look at complex and integrated responses to diet and other exposures   

nutritional metabolomics 

• marker of dietary intake 

• marker of metabolic effect 

metabolomics as biomarker of dietary intake and diet composition

• measure of diet exposure

• reflects food components, their metabolites, and metabolites from gut microbiota

metabolomics uses in nutrition

• assess validity of dietary assessment in observational trials

• assess compliance during clinical trials 

• provide objective biomarkers for dietary intake 

  • specific foods 

  • dietary patterns and food groups 

EX of metabolites originating from food (biomarkers of dietary intake)

• food additives: sorbitol

• FA

  • butter: myristic acid

  • walnut: a-linoleic acid

• animal foods

  • chicken: anserine

  • red meats: acylcarnitine

• plant foods

  • citrus: proline betaine 

• beverages

  • coffee: caffeic acid, ferulic acid, trigonelline

• polyphenol-rich foods

  • olive oil: hydroxytyrosol

  • apples, choc: epicatechin

  • citrus: naringenin

  • grapes: tartrate 

EX quantifying dietary intake based on metabolomics data

• goal: quantify intake based on metabolites, RCT intake of OJ

• metabolite proline betaine marker of OJ intake

• predicted citrus intake from urine samples

metabolomics as biomarker of effect and associated health benefits

• reflects endogenous intermediary pathways and metabolites 

• includes biomarkers of disease, disease risk, and health status 

• can describe metabolic phenotype, or metabotype 

metabolomics uses

• provide insight into mechanisms and pathways invovled in diet, disease relationships

• provides ability to look at patterns of changes in response to diet, and physiological status 

• provides ability to distinguish between groups of individuals such as responders and non responders

EX: metabolomic signature associated with BMI and visceral adiposity 

• goal: examine relationships between BMI and 145 metabolites

• goal: identify biomarkers of high vs low visceral fat area 

• future applications: metabolite markers of BMI and adiposity status for clinical use, investigations of change in biomarkers with dietary interventions, examine candidate biomarkers for causal pathway relationships with obesity related diseases

metabolomics applications

• current uses and applications

  • predom research based 

    • pilot studies, proof of concept

    • identification and validaiton of biomarkers of exposure and effect 

    • diet-disease and diet-gut microbiota disease relationships

    • generate hypotheses

  • generating a lot of data

• future use

  • identify nutritionally “high risk” patients

  • establish precision nutrition recc to prevent and manage disease

  • develop innovative education and counseling appraches based on personal phenotypic metabolomics info 

metabotyping

grouping individuals based on similarities in metabolic characteristics and phenotype (metabotype) 

• consider factors such as diet, anthropometric measures, clinical parameters, metabolomics data, gut microbiota

metabotyping clinical usefulness

parameters to determine metabotype need to be easily measured and cost effective; and able to identify responders with associated health outcome and surrogate health biomarkers 

personalized/precision nutrition

application of nutritional -omics, seeks to

• understand factors that influence individual variability in response to nutrients

• develop algorithms to predict response based on phenotype

• make dietary reccs or interventions based on individual’s nutritional requirements, nutritional status, genotype, microbiome, metabotype, and phenotype

• not one size fits all

goal of personalized nutrition

to preserve or increase health by using genetic, phenotypic, medical, nutrition, and other relevant info abt individuals to deliver more specific healthy eating guidance and other nutritional services 

personalized nutrition - time is now

• no longer theoretical

• postprandial responses to same food vary between individuals 

• studies show personalized dietary interventions:

  • improve glycemic control and lipid profiles

  • enhance weight management and dietary adherence 

• commercial platforms use AI to tailor nutrition advice 

• multi-omics and machine learning enable prediction of individual responses to food

examining interindividual variability to nutrition inputs

• show better prediction using algorithm, than simply knowing glycemic index of foods and meal composition

• points to importance of understanding [physiological inputs and influences on metabolic responses

• studies did not test whether giving individuals info helped them make diff dietary choices