Transforming Big Data into AI‐ready data for nutrition and obesity research DOI
Diana M. Thomas, Rob Knight, Jack A. Gilbert

et al.

Obesity, Journal Year: 2024, Volume and Issue: 32(5), P. 857 - 870

Published: March 1, 2024

Big Data are increasingly used in obesity and nutrition research to gain new insights derive personalized guidance; however, this data raw form often not usable. Substantial preprocessing, which requires machine learning (ML), human judgment, specialized software, is required transform into artificial intelligence (AI)- ML-ready data. These preprocessing steps the most complex part of entire modeling pipeline. Understanding complexity these by end user critical for reducing misunderstanding, faulty interpretation, erroneous downstream conclusions.

Language: Английский

Diet-microbiota associations in gastrointestinal research: a systematic review DOI Creative Commons
Kerith Duncanson, Georgina M. Williams, Emily C. Hoedt

et al.

Gut Microbes, Journal Year: 2024, Volume and Issue: 16(1)

Published: May 9, 2024

Interactions between diet and gastrointestinal microbiota influence health status outcomes. Evaluating these relationships requires accurate quantification of dietary variables relevant to microbial metabolism, however current assessment methods focus on components human digestion only. The aim this study was synthesize research foods nutrients that gut thereby identify knowledge gaps inform advancements toward better understanding diet-microbiota interactions. Thirty-eight systematic reviews 106 primary studies reported associations. Dietary factors altering colonic included patterns, macronutrients, micronutrients, bioactive compounds, food additives. Reported associations were dominated by routinely analyzed nutrients, which are absorbed from the small intestine but for correlation stool microbiota. derived microbiota-relevant more challenging quantify underrepresented in studies. This evidence synthesis highlights needed, including opportunities expansion composition databases include data, particularly intervention These advances methodology will facilitate translation microbiota-specific nutrition therapy practice.

Language: Английский

Citations

11

Potential mechanisms of precision nutrition-based interventions for managing obesity DOI Creative Commons
Neel H. Mehta, Samantha L. Huey, Rebecca Kuriyan

et al.

Advances in Nutrition, Journal Year: 2024, Volume and Issue: 15(3), P. 100186 - 100186

Published: Feb. 3, 2024

Precision nutrition (PN) considers multiple individual-level and environmental characteristics or variables, in order to better inform dietary strategies interventions for optimizing health, including managing obesity metabolic disorders. Here, we review the evidence on potential mechanisms – ones identify those most likely respond that can be leveraged development of PN addressing obesity. We conducted a literature included laboratory, animal, human studies evaluating biochemical genetic data, completed ongoing clinical trials, public programs this review. Our analysis describes related six domains predisposition; circadian rhythms; physical activity sedentary behavior; metabolomics; gut microbiome, behavioral socioeconomic characteristics; i.e. factors design PN-based prevent treat obesity-related outcomes such as weight loss health laid out by NIH 2030 Strategic Plan Nutrition Research. For example, single nucleotide polymorphisms (SNPs) modify responses certain interventions, epigenetic modulation risk via patterns macronutrient intake have also been demonstrated. Additionally, identified limitations questions equitable implementation across limited number trials. These include ability current address systemic influences supply chains food distribution, healthcare systems, racial cultural inequities, economic disparities particularly when designing implementing low- middle-income communities. has inter-individual variation, opposed "one-size fits all" standardized intervention, though there is trial date. Optimizing at individual level through microbiome assessment, lifestyle pattern analysis, phenotyping may help advance our modulate and/or manage individualized physiological involved

Language: Английский

Citations

10

Role of metabolomics in the delivery of precision nutrition DOI Creative Commons
Lorraine Brennan, Baukje de Roos

Redox Biology, Journal Year: 2023, Volume and Issue: 65, P. 102808 - 102808

Published: July 5, 2023

Precision nutrition aims to deliver personalised dietary advice individuals based on their personal genetics, metabolism and dietary/environmental exposures. Recent advances have demonstrated promise for the use of omic technologies furthering field precision nutrition. Metabolomics in particular is highly attractive as measurement metabolites can capture information food intake, levels bioactive compounds impact diets endogenous metabolism. These aspects contain useful Furthermore using metabolomic profiles identify subgroups or metabotypes delivery advice. Combining derived with other parameters prediction models also an exciting avenue understanding predicting response interventions. Examples include but not limited role one carbon associated co-factors blood pressure response. Overall, while evidence exists potential this there are many unanswered questions. Addressing these clearly demonstrating that approaches enable adherence healthier improvements health will be key near future.

Language: Английский

Citations

19

Metabolic Signature of Healthy Lifestyle and Risk of Rheumatoid Arthritis: Observational and Mendelian Randomization Study DOI Creative Commons
Jie Zhang, Xinyu Fang,

Rui Leng

et al.

American Journal of Clinical Nutrition, Journal Year: 2023, Volume and Issue: 118(1), P. 183 - 193

Published: April 29, 2023

Although substantial evidence reveals that healthy lifestyle behaviors are associated with a lower risk of rheumatoid arthritis (RA), the underlying metabolic mechanisms remain unclear. This study aimed to identify signature reflecting and investigate its observational genetic linkage RA risk. included 87,258 UK Biobank participants (557 cases incident RA) aged 37–73 y complete lifestyle, genotyping, nuclear magnetic resonance (NMR) metabolomics data. A was assessed based on 5 factors: diet, regular exercise, not smoking, moderate alcohol consumption, normal body mass index. The developed by summing selected metabolites' concentrations weighted coefficients using elastic net regression. We used multivariate Cox model assess associations between signatures risk, examined mediating role in impact RA. performed genome-wide association analysis (GWAS) obtain variants then conducted Mendelian randomization (MR) analyses detect causality. comprised 81 metabolites, robustly correlated (r = 0.45, P 4.2 × 10−15). inversely (HR per standard deviation (SD) increment: 0.76; 95% CI: 0.70–0.83), largely explained protective effects 64% (95% 50.4–83.3) mediation proportion. 1- 2-sample MR also consistently showed genetically inferred SD increment reduction (HR: 0.84; 0.75–0.94; 0.002 OR: 0.73–0.97; 0.02, respectively). Our findings implicate is potential causal mediator development RA, highlighting importance early intervention status tracking for precise prevention

Language: Английский

Citations

17

The Future of Obesity Management through Precision Nutrition: Putting the Individual at the Center DOI Creative Commons
Hande Gül Ulusoy, Neslişah Rakıcıoğlu

Current Nutrition Reports, Journal Year: 2024, Volume and Issue: 13(3), P. 455 - 477

Published: May 28, 2024

Abstract Purpose of Review The prevalence obesity continues to rise steadily. While management typically relies on dietary and lifestyle modifications, individual responses these interventions vary widely. Clinical guidelines for overweight stress the importance personalized approaches care. This review aims underscore role precision nutrition in delivering tailored management. Recent Findings technological strides have expanded our ability detect obesity-related genetic polymorphisms, with machine learning algorithms proving pivotal analyzing intricate genomic data. Machine can also predict postprandial glucose, triglyceride, insulin levels, facilitating customized ultimately leading successful weight loss. Additionally, given that adherence recommendations is one key predictors loss success, employing more objective methods assessment monitoring enhance sustained long-term compliance. Summary Biomarkers food intake hold promise a assessment. Acknowledging multifaceted nature obesity, stands poised transform by tailoring individuals' backgrounds, gut microbiota, metabolic profiles, behavioral patterns. However, there insufficient evidence demonstrating superiority over traditional recommendations. integration into routine clinical practice requires further validation through randomized controlled trials accumulation larger body strengthen its foundation.

Language: Английский

Citations

7

Untargeted metabolomics and comparative flavonoid analysis reveal the nutritional aspects of pak choi DOI
Waleed Amjad Khan,

Hairong Hu,

Tracey Ann Cuin

et al.

Food Chemistry, Journal Year: 2022, Volume and Issue: 383, P. 132375 - 132375

Published: Feb. 9, 2022

Language: Английский

Citations

23

Current challenges and future implications of exploiting the omics data into nutrigenetics and nutrigenomics for personalized diagnosis and nutrition-based care DOI
Varsha Singh

Nutrition, Journal Year: 2023, Volume and Issue: 110, P. 112002 - 112002

Published: Feb. 10, 2023

Language: Английский

Citations

16

Nutritional metabolomics: Recent developments and future needs DOI Creative Commons
Maaria Kortesniemi, Stefania Noerman, Anna Kårlund

et al.

Current Opinion in Chemical Biology, Journal Year: 2023, Volume and Issue: 77, P. 102400 - 102400

Published: Oct. 5, 2023

Metabolomics has rapidly been adopted as one of the key methods in nutrition research. This review focuses on recent developments and updates field, including analytical methodologies that encompass improved instrument sensitivity, sampling techniques data integration (multiomics). advanced discovery validation dietary biomarkers their implementation health come to play an important role understanding small molecules resulting from diet-microbiota interactions when gut microbiota research shifted towards improving activity functionality rather than composition alone. Currently, metabolomics plays emerging precision therein are discussed.

Language: Английский

Citations

14

Comparative analysis of flavonoid metabolites from different parts of Hemerocallis citrina DOI Creative Commons
Hongrui Lv, Shang Guo

BMC Plant Biology, Journal Year: 2023, Volume and Issue: 23(1)

Published: Oct. 13, 2023

Hemerocallis citrina Baroni is a traditional medical and edible plant. It rich in flavonoid compounds, which are kind of important bioactive components with various health benefits pharmaceutical value. However, the metabolomics profile comparison compounds from different parts H. scarce.In this study, metabolites were investigated roots, stems, leaves flowers citrina. A total 364 identified by UPLC-MS/MS based widely targeted metabolomics, four plant showed huge differences at metabolic level. Compared to 185, 234, 119 accounted for upregulated differential (DFMs) leaves, flowers, respectively. 168 29 DFMs only flowers. number 35 common observed among six groups, each group had its unique metabolites. The most abundant flavonols flavones, followed flavanones, chalcones, flavanols, flavanonols, anthocyanidins, tannin, proanthocyanidins. 6,7,8-Tetrahydroxy-5-methoxyflavone, 7,8,3',4'-tetrahydroxyflavone, 1-Hydroxy-2,3,8-trimethoxyxanthone, Farrerol-7-O-glucoside, 3',7-dihydroxy-4'-methoxyflavone, 3,3'-O-Dimethylellagic Acid, 5-Hydroxy-6,7-dimethoxyflavone, Nepetin (5,7,3',4'-Tetrahydroxy-6-methoxyflavone), (2s)-4,8,10-trihydroxy-2-methoxy-1 h,2 h-furo[3,2-a]xanthen-11-one dominant roots. Isorhamnetin-3-O-(6''-malonyl)glucoside-7-O-rhamnoside, 7-Benzyloxy-5-hydroxy-3',4'-methylenedioxyflavonoid, 3-Hydroxyphloretin-4'-O-glucoside stems. Chrysoeriol-7-O-glucoside, Epicatechin glucoside, Kaempferol-3-O-rhamnoside (Afzelin)(Kaempferin)*, Azaleatin (5-O-Methylquercetin), Chrysoeriol-5-O-glucoside, Nepetin-7-O-glucoside(Nepitrin), 3,5,7,2'-Tetrahydroxyflavone; Datiscetin, Procyanidin B2*, B3*, B1, Isorhamnetin-3-O-(6''-acetylglucoside) leaves. kaempferol-3-p-coumaroyldiglucoside, Delphinidin-3-O-sophoroside-5-O-glucoside, Limocitrin-3-O-sophoroside, Kaempferol-3-O-rutinoside(Nicotiflorin), Luteolin-7-O-(6''-malonyl)glucoside-5-O-rhamnoside flowers.There was significant difference Leaves relative higher contents than other parts. This study provided biological chemical evidence uses citrina, these informations theoretical basis food industry, treatment.

Language: Английский

Citations

14

Untargeted metabolomics reveal signatures of a healthy lifestyle DOI Creative Commons
Wimal Pathmasiri, Blake R. Rushing, Susan McRitchie

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: June 13, 2024

Abstract This cross-sectional study investigated differences in the plasma metabolome two groups of adults that were similar age but varied markedly body composition and dietary physical activity patterns. Study participants included 52 lifestyle group (LIFE) (28 males, 24 females) control (CON) (27 25 females). The results using an extensive untargeted ultra high-performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) metabolomics analysis with 10,535 metabolite peaks identified 486 important metabolites (variable influence on projections scores VIP ≥ 1) 16 significantly enriched metabolic pathways differentiated LIFE CON groups. A novel signature positive habits emerged from this highlighted by lower levels numerous bile acids, amino acid profile characterized higher histidine glutamic acid, glutamine, β-alanine, phenylalanine, tyrosine, proline, elevated vitamin D status, beneficial fatty acids gut microbiome catabolism plant substrates, reduced N-glycan degradation environmental contaminants. established is strongly associated habits. robust consistent improved life expectancy a risk for chronic disease.

Language: Английский

Citations

5