Homostachydrine (pipecolic acid betaine) as authentication marker of roasted blends of Coffea arabica and Coffea canephora (Robusta) beans

Mendelian Randomization Study With Clinical Follow-Up Links Metabolites to Risk and Severity of Pulmonary Arterial Hypertension

BACKGROUND

Pulmonary arterial hypertension (PAH) exhibits phenotypic heterogeneity and variable response to therapy. The metabolome has been implicated in the pathogenesis of PAH, but previous works have lacked power to implicate specific metabolites. Mendelian randomization (MR) is a method for causal inference between exposures and outcomes.

METHODS AND RESULTS

Using genome-wide association study summary statistics, we implemented MR analysis to test for potential causal relationships between serum concentration of 575 metabolites and PAH. Five metabolites were causally associated with the risk of PAH after multiple testing correction. Next, we measured serum concentration of candidate metabolites in an independent clinical cohort of 449 patients with PAH to check whether metabolite concentrations are correlated with markers of disease severity. Of the 5 candidates nominated by our MR work, serine was negatively associated and homostachydrine was positively associated with clinical severity of PAH via direct measurement in this independent clinical cohort. Finally we used conditional and orthogonal approaches to explore the biology underlying our lead metabolites. Rare variant burden testing was carried out using whole exome sequencing data from 578 PAH cases and 361 675 controls. Multivariable MR is an extension of MR that uses a single set of instrumental single-nucleotide polymorphisms to measure multiple exposures; multivariable MR is used to determine interdependence between the effects of different exposures on a single outcome. Rare variant analysis demonstrated that loss-of-function mutations within activating transcription factor 4, a transcription factor responsible for upregulation of serine synthesis under conditions of serine starvation, are associated with higher risk for PAH. Homostachydrine is a xenobiotic metabolite that is structurally related to l-proline betaine, which has previously been linked to modulation of inflammation and tissue remodeling in PAH. Our multivariable MR analysis suggests that the effect of l-proline betaine is actually mediated indirectly via homostachydrine.

CONCLUSIONS

Our data present a method for study of the metabolome in the context of PAH, and suggests several candidates for further evaluation and translational research.

Pulped natural/honey robusta coffee fermentation metabolites, physico-chemical and sensory profiles

The pulped natural/honey coffee (HC) of Coffea canephora (Robusta) is an innovative modified semi-dry technique. Studies have focused on HC and washed coffee (WC) fermentation, microbial metabolites, quality of green and roasted, using 1H NMR, GC-MS, and sensory investigation. Pipecolate and 3-hydroxy-3-methyglutarate have been identified for the first time. Principal Component Analysis (PCA) variability of the roasted beans, with PC 1 depicting 87.4 % and 12.6 % PC 2 respectively highlights the impact of major sugars and secondary metabolites acquired through HC. The HC fermentation (192 h) influenced carbohydrates, organic acids, and secondary metabolites besides flavor precursors compared to WC (72 h). Although HC and WC beans share similar physical qualities, enhanced volatile compounds, enriched concentration, organoleptics with pleasant, sweet, tea rose and chocolaty flavors attributes were embodied in HC than WC. The pulped natural post-harvest technique in robusta is a value addition with quality that can fetch a better premium.

Assessing the causal effect of genetically predicted metabolites and metabolic pathways on stroke

BACKGROUND

Stroke is a common neurological disorder that disproportionately affects middle-aged and elderly individuals, leading to significant disability and mortality. Recently, human blood metabolites have been discovered to be useful in unraveling the underlying biological mechanisms of neurological disorders. Therefore, we aimed to evaluate the causal relationship between human blood metabolites and susceptibility to stroke.

METHODS

Summary data from genome-wide association studies (GWASs) of serum metabolites and stroke and its subtypes were obtained separately. A total of 486 serum metabolites were used as the exposure. Simultaneously, 11 different stroke phenotypes were set as the outcomes, including any stroke (AS), any ischemic stroke (AIS), large artery stroke (LAS), cardioembolic stroke (CES), small vessel stroke (SVS), lacunar stroke (LS), white matter hyperintensities (WMH), intracerebral hemorrhage (ICH), subarachnoid hemorrhage (SAH), transient ischemic attack (TIA), and brain microbleeds (BMB). A two-sample Mendelian randomization (MR) study was conducted to investigate the causal effects of serum metabolites on stroke and its subtypes. The inverse variance-weighted MR analyses were conducted as causal estimates, accompanied by a series of sensitivity analyses to evaluate the robustness of the results. Furthermore, a reverse MR analysis was conducted to assess the potential for reverse causation. Additionally, metabolic pathway analysis was performed using the web-based MetOrigin.

RESULTS

After correcting for the false discovery rate (FDR), MR analysis results revealed remarkable causative associations with 25 metabolites. Further sensitivity analyses confirmed that only four causative associations involving three specific metabolites passed all sensitivity tests, namely ADpSGEGDFXAEGGGVR* for AS (OR: 1.599, 95% CI 1.283-1.993, p = 2.92 × 10-5) and AIS (OR: 1.776, 95% CI 1.380-2.285, p = 8.05 × 10-6), 1-linoleoylglycerophosph-oethanolamine* for LAS (OR: 0.198, 95% CI 0.091-0.428, p = 3.92 × 10-5), and gamma-glutamylmethionine* for SAH (OR: 3.251, 95% CI 1.876-5.635, p = 2.66 × 10-5), thereby demonstrating a high degree of stability. Moreover, eight causative associations involving seven other metabolites passed both sensitivity tests and were considered robust. The association result of one metabolite (glutamate for LAS) was considered non-robust. As for the remaining metabolites, we speculate that they may potentially possess underlying causal relationships. Notably, no common metabolites emerged from the reverse MR analysis. Moreover, after FDR correction, metabolic pathway analysis identified 40 significant pathways across 11 stroke phenotypes.

CONCLUSIONS

The identified metabolites and their associated metabolic pathways are promising circulating metabolic biomarkers, holding potential for their application in stroke screening and preventive strategies within clinical settings.

Authentication of Coffee Blends by 16-O-Methylcafestol Quantification Using NMR Spectroscopy

In 2019, a coffee chain in Taiwan was found to be mixing relatively cheap Robusta beans into products marketed as 100% Arabica. Many studies show 16-OMC is a remarkable marker to distinguish Robusta from Arabica beans, and nuclear magnetic resonance (NMR) is a convenient and efficient technique for 16-OMC quantification. Here, a 500 MHz NMR was employed to determine the content of 16-OMC in coffee for adulterate evaluation. A total of 118 samples were analyzed including products from the coffee chain, raw materials (single coffee beans), and other commercial products. The contents of 16-OMC in single Robusta beans were between 1005.55 and 3208.32 mg/kg and were absent from single Arabica beans. The surveillance results indicate that 17 out of 47 blend products claiming to contain 100% Arabica had 16-OMC quantifications in the range of 155.74–784.60 mg/kg. Furthermore, all 17 products were produced by the same coffee chain. We confirmed that coffee chain adulterated Arabica with Robusta in parts of their products, which claimed to include 100% Arabica. Moreover, this work highlights the free form of 16-OMC was esterified by coffee instantly. The decomposition products of 16-OMC were observed obviously in green Robusta while the mechanisms remain unclear. Future research should focus more on these aspects to further increase our understanding of these mechanisms.

Metabolomic Markers of Ultra-Processed Food and Incident CKD

BACKGROUND

High ultra-processed food consumption is associated with higher risk of CKD. However, there is no biomarker for ultra-processed food, and the mechanism through which ultra-processed food is associated with CKD is not clear. Metabolomics can provide objective biomarkers of ultra-processed food and provide important insights into the mechanisms by which ultra-processed food is associated with risk of incident CKD. Our objective was to identify serum metabolites associated with ultra-processed food consumption and investigate whether ultra-processed food-associated metabolites are prospectively associated with incident CKD.

METHODS

We used data from 3751 Black and White men and women (aged 45-64 years) in the Atherosclerosis Risk in Communities study. Dietary intake was assessed using a semiquantitative 66-item food frequency questionnaire, and ultra-processed food was classified using the NOVA classification system. Multivariable linear regression models were used to identify the association between 359 metabolites and ultra-processed food consumption. Cox proportional hazards models were used to investigate the prospective association of ultra-processed food-associated metabolites with incident CKD.

RESULTS

Twelve metabolites (saccharine, homostachydrine, stachydrine, N2, N2-dimethylguanosine, catechol sulfate, caffeine, 3-methyl-2-oxovalerate, theobromine, docosahexaenoate, glucose, mannose, and bradykinin) were significantly associated with ultra-processed food consumption after controlling for false discovery rate <0.05 and adjusting for sociodemographic factors, health behaviors, eGFR, and total energy intake. The 12 ultra-processed food-related metabolites significantly improved the prediction of ultra-processed food consumption (difference in C statistics: 0.069, P <1×10 -16 ). Higher levels of mannose, glucose, and N2, N2-dimethylguanosine were associated with higher risk of incident CKD after a median follow-up of 23 years.

CONCLUSIONS

We identified 12 serum metabolites associated with ultra-processed food consumption and three of them were positively associated with incident CKD. Mannose and N2, N2-dimethylguanosine are novel markers of CKD that may explain observed associations between ultra-processed food and CKD.

PODCAST

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Effects of thermal processing on N,N-dimethylpiperidinium (mepiquat) formation in meat and vegetable products

N,N-dimethylpiperidinium (mepiquat) is an important food contaminant formed from natural ingredients during thermal processing. In this study, mepiquat formation in meat (pork and beef) and vegetables (potatoes and broccoli) was investigated via HPLC-MS/MS; the investigated cooking methods were oven baking, pan cooking, deep frying, and microwaving. The results showed that, among all foods, oven-baked potatoes showed the highest mepiquat level of 1064 μg/kg, which appeared after 20 min at 240 °C. The residual rates of mepiquat precursors, pipecolic acid (PipAc), betaine, choline, and trigonelline, were determined in oven-baked potatoes to investigate their correlation with mepiquat formation. The PipAc levels reduced by 99.8% at 260 °C after 30 min of oven baking, exhibiting a significantly high decomposition rate. Therefore, PipAc could be used as a marker of quality for the detection of mepiquat in thermally processed foodstuffs.

Heat-induced formation of N,N-dimethylpiperidinium (mepiquat) in Arabica and Robusta coffee

N,N-dimethylpiperidinium (mepiquat) is a new process-induced compound formed from natural constituents during the cooking process. Mepiquat was first found in coffee and cereal products, but its formation mechanism in coffee is still unclear. In the current study, Arabica and Robusta coffee beans were roasted at different temperatures (215, 220, and 230 °C) to study the effect of roasting process on mepiquat formation. The highest mepiquat content, 1,020 µg/kg, was found in dark roast (230 °C) Indonesia Wahana, while 430 µg/kg of mepiquat was detected in medium roast (220 °C) Vietnam Robusta. At the same roasting temperature, higher level of mepiquat was observed in Arabica than in Robusta. In both species, substances related to mepiquat formation, including betaine, choline, trigonelline, lysine, carnitine, pipecolic acid (PipAc), pipecolic acid betaine (PipBet), were also detected. The lysine-based Maillard reaction and decarboxylation in Arabica and Robusta promoted mepiquat formation through the degradation of choline and trigonelline, and the formation of intermediate products. Results from both the model system and selected commercial beans showed that choline and trigonelline had a significant correlation (P < 0.01) with mepiquat formation in Arabica. PRACTICAL APPLICATION: Mepiquat is considered as a new process-induced compound resulting from typical roasting conditions, but its formation mechanism in coffee is still unclear. This work demonstrates the formation mechanism of mepiquat by many precursor substances contained in Arabica and Robusta. It is very important to figure out how mepiquat is ''naturally" present in daily diets, especially in those processed at high temperatures.

Review of Analytical Methods to Detect Adulteration in Coffee

As one of the most consumed beverages in the world, coffee plays many major socioeconomical roles in various regions. Because of the wide coffee varieties available in the marketplaces, and the substantial price gaps between them (e.g., Arabica versus Robusta; speciality versus commodity coffees), coffees are susceptible to intentional or accidental adulteration. Therefore, there is a sustaining interest from the producers and regulatory agents to develop protocols to detect fraudulent practices. In general, strategies to authenticate coffee are based on targeted chemical profile analyses to determine specific markers of adulterants, or nontargeted analyses based on the “fingerprinting” concept. This paper reviews the literature related to chemometric approaches to discriminate coffees based on nuclear magnetic resonance spectroscopy, chromatography, infrared/Raman spectroscopy, and array sensors/indicators. In terms of chemical profiling, the paper focuses on the detection of diterpenes, homostachydrine, phenolic acids, carbohydrates, fatty acids, triacylglycerols, and deoxyribonucleic acid. Finally, the prospects of coffee authentication are discussed.

Quantitative assessment of betainized compounds and associations with dietary and metabolic biomarkers in the randomized study of the healthy Nordic diet (SYSDIET)

BACKGROUND

Recently, a group of betainized compounds have been suggested to play a role in health effects in relation to a whole-grain-rich diet.

OBJECTIVES

The aims of this study were to develop a quantitative mass spectrometric method for selected betainized compounds in human plasma, and to investigate their association with nutrient intake and measures of metabolic health in participants of the SYSDIET study.

METHODS

The SYSDIET study was a controlled randomized intervention including individuals with metabolic syndrome, where the healthy Nordic diet (HND) group increased intakes of whole grains, canola oil, berries, and fish, whereas the control diet (CD) group consumed low-fiber cereal products, milk fat, and restricted amounts of fish and berries. A quantitative LC combined with triple quadrupole MS method for betainized compounds was developed and applied to fasting plasma samples from baseline (week 0) and the end of the intervention (week 18 or 24). Concentrations of betainized compounds were correlated with intakes of selected nutrients and fiber and measures of metabolic health.

RESULTS

Pipecolic acid betaine (PAB) concentrations were significantly higher in the HND group than in the CD group (P = 0.00032) at the end of the intervention and correlated directly (P < 0.0001) with intakes of dietary fiber (r = 0.376) and a biomarker related to whole-grain rye intake, namely the ratio of alkylresorcinol C17:0 to C21:0 (r = 0.442). PAB was associated inversely with fasting plasma insulin consistently at the beginning and at the end of the intervention (P < 0.001, r = -0.300; P < 0.01, r = -0.250, respectively), as well as IL-1 receptor antagonist (P < 0.01, r = -0.232 at the beginning; P < 0.01, r = -0.236 at the end) and serum LDL/HDL cholesterol (P < 0.01, r = -0.239 at the beginning; P < 0.01, r = -0.241 at the end).

CONCLUSIONS

Among adults with the metabolic syndrome, PAB plasma concentrations were associated with fasting insulin, inflammation, and lipids and were significantly increased with adoption of the HND. Further studies are needed to clarify the biological functions of betainized compounds. This trial was registered at clinicaltrials.gov as NCT00992641.

Coffea arabica and C. canephora discrimination in roasted and ground coffee from reference material candidates by real-time PCR

To produce specific desirable coffee blends, Coffea arabica and C. canephora are mixed each other, in some cases to suit consumer preference, but in others to reduce production costs. In this scenario, the aim of this work was to evaluate standard candidate reference materials (RMc) for analysis of different blends of roasted and ground coffee. For this purpose, we analyzed different percentages of C. arabica and C. canephora (100:0; 50:50; 25:75; and 0:100, respectively). These RMc samples were developed in a previous study with green coffee beans submitted to medium roasting. In this work, coffee species differentiation (C. arabica and C. canephora) was analyzed by real-time PCR, using specific primers previously developed, called ARA primers. The RMc material with 100% C. canephora did not present amplification, in contrast with the samples containing C. arabica, which all presented amplification. These results indicate the specificity of ARA primers for C. arabica and that the detection system assay can be used as a promising molecular tool to identify and quantify percentages of C. arabica in different coffee blends.

Biomarkers of Individual Foods, and Separation of Diets Using Untargeted LC-MS-based Plasma Metabolomics in a Randomized Controlled Trial

SCOPE

Self-reported dietary intake does not represent an objective unbiased assessment. The effect of the new Nordic diet (NND) versus average Danish diet (ADD) on plasma metabolic profiles is investigated to identify biomarkers of compliance and metabolic effects.

METHODS AND RESULTS

In a 26-week controlled dietary intervention study, 146 subjects followed either NND, a predominantly organic diet high in fruit, vegetables, whole grains, and fish, or ADD, a diet higher in imported and processed foods. Fasting plasma samples are analyzed with untargeted ultra-performance liquid chromatography-quadruple time-of-flight. It is demonstrated that supervised machine learning with feature selection can separate NND and ADD samples with an average test set performance of up to 0.88 area under the curve. The NND plasma metabolome is characterized by diet-related metabolites, such as pipecolic acid betaine (whole grain), trimethylamine oxide, and prolyl hydroxyproline (both fish intake), while theobromine (chocolate) and proline betaine (citrus) were associated with ADD. Amino acid (i.e., indolelactic acid and hydroxy-3-methylbutyrate) and fat metabolism (butyryl carnitine) characterize ADD whereas NND is associated with higher concentrations of polyunsaturated phosphatidylcholines.

CONCLUSIONS

The plasma metabolite profiles are predictive of dietary patterns and reflected good compliance while indicating effects of potential health benefit, including changes in fat metabolism and glucose utilization.

The complete chloroplast genome sequence of an economic plant Coffea canephora

Coffea canephora is a paramount economic plant with great economic value. The complete chloroplast (cp) genome is 154,751 bp in length, including a large single copy (LSC) region of 84,850 bp, a small single copy (SSC) region of 18,131 bp and a pair of inverted repeats (IRs) of 25,885bp. This cp genome contains 131 genes, comprising of 86 protein-coding genes, 37 tRNAs and 8 rRNAs. The majority of these genes were single copy genes, while 18 genes existed as double copies, including 6 protein-coding genes (ndhB, rpl2, rpl23, rps12, rps7 and ycf2), 8 tRNA genes (trnA-UGC, trnG-GCC, trnI-CAU, trnI-GAU, trnL-CAA, trnN-GUU, trnR-ACG and trnV-GAC) and 4 rRNA genes (rrn4.5, rrn5, rrn16 and rrn23). A neighbour-joining phylogenetic tree was reconstructed to indicate that Coffea canephora is evolutionarily close to Olea europaea within Asterids. The complete cp genome will provide intragenic information for molecular phylogeny and biological studies of the Rubiales.

Authentication of Coffea arabica according to Triacylglycerol Stereospecific Composition

Stereospecific analysis is an important tool for the characterization of lipid fraction of food products. In the present research, an approach to characterize arabica and robusta varieties by structural analysis of the triacylglycerol (TAG) fraction is reported. The lipids were Soxhlet extracted from ground roasted coffee beans with petroleum ether, and the fatty acids (FA) were determined as their corresponding methyl esters. The results of a chemical-enzymatic-chromatographic method were elaborated by a chemometric procedure, Linear Discriminant Analysis (LDA). According to the total and intrapositional FA composition of TAG fraction, the obtained results were able to characterize roasted pure coffee samples and coffee mixtures with 10% robusta coffee added to arabica coffee. Totally correct classified samples were obtained when the TAG stereospecific results of the considered coffee mixture (90 : 10 arabica/robusta) were elaborated by LDA procedure.