Metabolic Trajectories Following Contrasting Prudent and Western Diets from Food Provisions: Identifying Robust Biomarkers of Short-Term Changes in Habitual Diet

Abstract

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.

Circulating Pro- and Anti-Inflammatory Metabolites and Its Potential Role in Rheumatoid Arthritis Pathogenesis

“…Table 2 shows a summary of 31 of foods and the metabolites that have been found to be markers of their intake using metabolomics. Several studies have also found metabolites related to dietary patterns, like Mediterranean, high fat, or Western diets [17][18][19][20][21]. Table 2.…”

Application of multisegment injection on quantification of creatinine and standard addition analysis of urinary 5‐hydroxyindoleacetic acid simultaneously with creatinine normalization

“…3A). Conversely, the broadening effect was noticed with later migrating peaks in the previous MSI method with seven sample segments due to the increased longitudinal diffusion , however, no broadening for creatinine was reported in the recent urine metabolomic studies by MSI–CE–MS . Despite the differences in the separation condition, we considered that the deleterious broadening observed in our experiment (Fig.…”

“…To overcome these limitations, analytical methods based on various techniques, including LC–MS , GC–MS , CE–UV , ambient ionization MS , have been developed to quantify urinary creatinine. Having the advantages of relatively short analysis time, low sample consumption and high efficiency for detecting small polar molecules , CE–MS also showed its strong capability in the analysis of creatinine in urine metabolomics . Owing to the high abundance of creatinine in the human urine (10.4 ± 2.0 mM for average) , the MS analysis of urinary creatinine can be performed with relatively high dilutions of the samples , but it can also lead to signal saturation of creatinine when being quantified simultaneously with low‐abundance species in the less diluted urine.…”

“…Thereafter, it was developed to solve the problem of lacking IS in protein analysis via successive injections of the standard protein at a known concentration followed by the sample to be quantified . Along with the successful applications in metabolic profiling and bottom‐up proteomics , MSI–CE–MS has been accepted as a very efficient approach for increasing the throughput of metabolomics and proteomics analysis .…”

Capillary electrophoresis and ultra‐high‐performance liquid chromatography methods in clinical monitoring of creatinine in human urine: A comparative study

“…A high-or ultra-high-performance liquid chromatography (HPLC or UHPLC) in combination with ultraviolet (UV) or mass spectrometry (MS) has been recently used for the determination of creatinine in urine matrices (Derezinski et al, 2016;Dziadosz, 2018;Fraselle et al, 2015;Kučerová et al, 2019;Kwon, Kim, Suh, & In, 2012;Langsi, Ashu-Arrah, Ward, & Glennon, 2017;Luginbühl & Weinmann, 2017;Remane et al, 2015;Sun et al, 2019;West & Rhodes, 2014;Wijemanne, Soysa, Wijesundara, & Perera, 2018;Yen, Dahal, Lavine, Hassan, & Gamagedara, 2018;Yuan et al, 2019). In the group of electromigration techniques, capillary zone electrophoresis (CZE) with contactless conductivity detection (CD) (Grochocki, Markuszewski, & Quirino, 2017), UV detection (Huang, Chen, & Yan, 2012;Pavlíček, Tů ma, Matějčková, & Samcová, 2014;Sidorova & Grigoriev, 2012;Vitali, Goncalves, Rodrigues, Fávere, & Micke, 2017), CD/UV tandem detection (Makrlíková, Opekar, & Tů ma, 2015), or MS detection (DiBattista, Rampersaud, Lee, Kim, & Britz-McKibbin, 2017;Huang et al, 2019;Ramautar, Busnel, Deelder, & Mayboroda, 2012;Wellington et al, 2019;Wild, Shanmuganathan, Hayashi, Potter, & Briz-McKibbin, 2019;Yamamoto, Pinto-Sanchez, Bercik, & Britz-McKibbin, 2019) has been applied for creatinine. Because many different methods are being employed for measuring creatinine, it has become difficult to compare results across different studies and laboratories.…”