Nadine Wellington

Dr. Nadine Wellington

orcid

Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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9 October 2019 in Nutrients
Verified
Journal Article
Open access
PDF file
NWNadine Wellington
Nadine Wellington
MSMeera Shanmuganathan
Meera Shanmuganathan
RSRussell de Souza
Russell de Souza
MZMichael Zulyniak
Michael Zulyniak
SASandi Azab
Sandi Azab
Philip Britz-McKibbinPhilip Britz-McKibbin
Philip Britz-McKibbin
A large body of evidence has linked unhealthy eating patterns with an alarming increase in obesity and chronic disease worldwide. However, existing methods of assessing dietary intake in nutritional epidemiology rely on food frequency questionnaires or dietary records that are prone to bias and selective reporting. Herein, metabolic phenotyping was performed on 42 healthy participants from the Diet and Gene Intervention (DIGEST) pilot study, a parallel two-arm randomized clinical trial that provided complete diets to all participants. Matching single-spot urine and fasting plasma specimens were collected at baseline, and then following two weeks of either a Prudent or Western diet with a weight-maintaining menu plan designed by a dietician. Targeted and nontargeted metabolite profiling was conducted using three complementary analytical platforms, where 80 plasma metabolites and 84 creatinine-normalized urinary metabolites were reliably measured (CV < 30%) in the majority of participants (>75%) after implementing a rigorous data workflow for metabolite authentication with stringent quality control. We classified a panel of metabolites with distinctive trajectories following two weeks of food provisions when using complementary univariate and multivariate statistical models. Unknown metabolites associated with contrasting dietary patterns were identified with high-resolution MS/MS, as well as co-elution after spiking with authentic standards if available. Overall, 3-methylhistidine and proline betaine concentrations increased in both plasma and urine samples after participants were assigned a Prudent diet (q < 0.05) with a corresponding decrease in the Western diet group. Similarly, creatinine-normalized urinary imidazole propionate, hydroxypipecolic acid, dihydroxybenzoic acid, and enterolactone glucuronide, as well as plasma ketoleucine and ketovaline increased with a Prudent diet (p < 0.05) after adjustments for age, sex, and BMI. In contrast, plasma myristic acid, linoelaidic acid, linoleic acid, α-linoleic acid, pentadecanoic acid, alanine, proline, carnitine, and deoxycarnitine, as well as urinary acesulfame K increased among participants following a Western diet. Most metabolites were also correlated (r > ± 0.30, p < 0.05) to changes in the average intake of specific nutrients from self-reported diet records reflecting good adherence to assigned food provisions. Our study revealed robust biomarkers sensitive to short-term changes in habitual diet, which is needed for accurate monitoring of healthy eating patterns in free-living populations, and evidence-based public health policies for chronic disease prevention.

9 October 2019 in Chemistry – A European Journal
Verified
Journal Article
Closed access
PDF file
NWNadine Wellington
Nadine Wellington
SMSabrina Macklai
Sabrina Macklai
Philip Britz-McKibbinPhilip Britz-McKibbin
Philip Britz-McKibbin

13 August 2019 in Preprints.org
Verified
Preprint
Open access
NWNadine Wellington
Nadine Wellington
MSMeera Shanmuganathan
Meera Shanmuganathan
RSRussell de Souza
Russell de Souza
MZMichael A. Zulyniak
Michael A. Zulyniak
SASandi Azab
Sandi Azab
PBPhilip Britz-McKibbin
Philip Britz-McKibbin
A large body of evidence has linked unhealthy eating with an alarming increase in obesity and chronic disease worldwide. However, existing methods of assessing dietary intake rely on food frequency questionnaires or dietary records that are prone to bias and selective reporting. Herein, metabolic phenotyping was performed on 42 healthy participants from the Diet and Gene Intervention (DIGEST) pilot study, a parallel two-arm randomized clinical trial that provided complete diets to all participants. Matching urine and plasma specimens were collected at baseline and following 2 weeks of provision of either a Prudent or Western diet with a weight-maintaining menu plan designed by a dietician. Targeted and nontargeted metabolite profiling was conducted using three complementary analytical platforms, where 80 serum metabolites and 84 creatinine-normalized urinary metabolites were reliably measured (CV < 30%) in the majority of participants (> 75%) after implementing a rigorous data workflow for metabolite authentication with stringent quality control. We classified a panel of metabolites with distinctive trajectories following 2 weeks of food provisions when using complementary univariate and multivariate statistical models. Unknown metabolites associated with contrasting dietary patterns were identified with high resolution MS/MS and/or co-elution after spiking with authentic standards. Overall, 3-methylhistidine and proline betaine concentrations increased consistently when participants were assigned a Prudent diet (q < 0.05) in both plasma and urine samples with a decrease in the Western diet group. Similarly, creatinine-normalized urinary imidazole propionate, hydroxypipecolic acid, dihydroxybenzoic acid, and enterolactone glucuronide, as well as plasma ketoleucine and ketovaline increased with a Prudent diet (p < 0.05) after adjustments for age, sex and BMI. In contrast, plasma myristic acid, linoelaidic acid, linoleic acid, α-linoleic acid, pentadecanoic acid, alanine, proline, carnitine and deoxycarnitine, as well as urinary acesulfame K increased among participants following a Western diet. Most metabolites were also correlated (r > ± 0.30, p < 0.05) to changes in average intake of specific nutrients from self-reported diet records reflecting good adherence to food provisions. This study revealed robust biomarkers sensitive to short-term changes in habitual diet that can be used to reliably monitor healthy eating patterns for new advances in nutritional epidemiology, as well as the design of evidence-based public health policies for chronic disease prevention.