40
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Transcriptomic changes in peripheral blood mononuclear cells with weight loss: systematic literature review and primary data synthesis

      review-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background and objectives

          Peripheral blood mononuclear cells (PBMCs) have shown promise as a tissue sensitive to subtle and possibly systemic transcriptomic changes, and as such may be useful in identifying responses to weight loss interventions. The primary aim was to comprehensively evaluate the transcriptomic changes that may occur during weight loss and to determine if there is a consistent response across intervention types in human populations of all ages.

          Methods

          Included studies were randomised control trials or cohort studies that administered an intervention primarily designed to decrease weight in any overweight or obese human population. A systematic search of the literature was conducted to obtain studies and gene expression databases were interrogated to locate corresponding transcriptomic datasets. Datasets were normalised using the ArrayAnalysis online tool and differential gene expression was determined using the limma package in R. Over-represented pathways were explored using the PathVisio software. Heatmaps and hierarchical clustering were utilised to visualise gene expression.

          Results

          Seven papers met the inclusion criteria, five of which had raw gene expression data available. Of these, three could be grouped into high responders (HR, ≥ 5% body weight loss) and low responders (LR). No genes were consistently differentially expressed between high and low responders across studies. Adolescents had the largest transcriptomic response to weight loss followed by adults who underwent bariatric surgery. Seven pathways were altered in two out of four studies following the intervention and the pathway ‘cytoplasmic ribosomal proteins’ (WikiPathways: WP477) was altered between HR and LR at baseline in the two datasets with both groups. Pathways related to ‘toll-like receptor signalling’ were altered in HR response to the weight loss intervention in two out of three datasets.

          Conclusions

          Transcriptomic changes in PBMCs do occur in response to weight change. Transparent and standardised data reporting is needed to realise the potential of transcriptomics for investigating phenotypic features.

          Registration number

          PROSPERO: CRD42019106582

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12263-021-00692-6.

          Related collections

          Most cited references41

          • Record: found
          • Abstract: not found
          • Article: not found

          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013: a systematic analysis for the Global Burden of Disease Study 2013.

            In 2010, overweight and obesity were estimated to cause 3·4 million deaths, 3·9% of years of life lost, and 3·8% of disability-adjusted life-years (DALYs) worldwide. The rise in obesity has led to widespread calls for regular monitoring of changes in overweight and obesity prevalence in all populations. Comparable, up-to-date information about levels and trends is essential to quantify population health effects and to prompt decision makers to prioritise action. We estimate the global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013. We systematically identified surveys, reports, and published studies (n=1769) that included data for height and weight, both through physical measurements and self-reports. We used mixed effects linear regression to correct for bias in self-reports. We obtained data for prevalence of obesity and overweight by age, sex, country, and year (n=19,244) with a spatiotemporal Gaussian process regression model to estimate prevalence with 95% uncertainty intervals (UIs). Worldwide, the proportion of adults with a body-mass index (BMI) of 25 kg/m(2) or greater increased between 1980 and 2013 from 28·8% (95% UI 28·4-29·3) to 36·9% (36·3-37·4) in men, and from 29·8% (29·3-30·2) to 38·0% (37·5-38·5) in women. Prevalence has increased substantially in children and adolescents in developed countries; 23·8% (22·9-24·7) of boys and 22·6% (21·7-23·6) of girls were overweight or obese in 2013. The prevalence of overweight and obesity has also increased in children and adolescents in developing countries, from 8·1% (7·7-8·6) to 12·9% (12·3-13·5) in 2013 for boys and from 8·4% (8·1-8·8) to 13·4% (13·0-13·9) in girls. In adults, estimated prevalence of obesity exceeded 50% in men in Tonga and in women in Kuwait, Kiribati, Federated States of Micronesia, Libya, Qatar, Tonga, and Samoa. Since 2006, the increase in adult obesity in developed countries has slowed down. Because of the established health risks and substantial increases in prevalence, obesity has become a major global health challenge. Not only is obesity increasing, but no national success stories have been reported in the past 33 years. Urgent global action and leadership is needed to help countries to more effectively intervene. Bill & Melinda Gates Foundation. Copyright © 2014 Elsevier Ltd. All rights reserved.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Gene Expression Omnibus: NCBI gene expression and hybridization array data repository.

              R. Edgar (2002)
              The Gene Expression Omnibus (GEO) project was initiated in response to the growing demand for a public repository for high-throughput gene expression data. GEO provides a flexible and open design that facilitates submission, storage and retrieval of heterogeneous data sets from high-throughput gene expression and genomic hybridization experiments. GEO is not intended to replace in house gene expression databases that benefit from coherent data sets, and which are constructed to facilitate a particular analytic method, but rather complement these by acting as a tertiary, central data distribution hub. The three central data entities of GEO are platforms, samples and series, and were designed with gene expression and genomic hybridization experiments in mind. A platform is, essentially, a list of probes that define what set of molecules may be detected. A sample describes the set of molecules that are being probed and references a single platform used to generate its molecular abundance data. A series organizes samples into the meaningful data sets which make up an experiment. The GEO repository is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo.
                Bookmark

                Author and article information

                Contributors
                Kaitlin.day@monash.edu
                Journal
                Genes Nutr
                Genes Nutr
                Genes & Nutrition
                BioMed Central (London )
                1555-8932
                1865-3499
                19 July 2021
                19 July 2021
                2021
                : 16
                : 12
                Affiliations
                [1 ]GRID grid.1002.3, ISNI 0000 0004 1936 7857, Department of Nutrition, Dietetics and Food, , Monash University, ; Level 1, 264 Ferntree Gully Road, Notting Hill, Victoria 3168 Australia
                [2 ]GRID grid.1003.2, ISNI 0000 0000 9320 7537, School of Human Movement and Nutrition Sciences, , University of Queensland, ; Brisbane, Australia
                [3 ]GRID grid.1008.9, ISNI 0000 0001 2179 088X, Department of Clinical Pathology, Melbourne Medical School, , The University of Melbourne, ; Melbourne, Victoria Australia
                [4 ]GRID grid.3263.4, ISNI 0000 0001 1482 3639, Cancer Epidemiology Division, , Cancer Council Victoria, ; Melbourne, Victoria Australia
                [5 ]GRID grid.1002.3, ISNI 0000 0004 1936 7857, Precision Medicine, School of Clinical Sciences at Monash Health, , Monash University, ; Clayton, Victoria Australia
                [6 ]GRID grid.5012.6, ISNI 0000 0001 0481 6099, Department of Bioinformatics-BiGCaT, NUTRIM School of Nutrition and Translational Research in Metabolism, , Maastricht University, ; Maastricht, The Netherlands
                [7 ]GRID grid.1008.9, ISNI 0000 0001 2179 088X, School of Agriculture and Food, , The University of Melbourne, ; Melbourne, Australia
                Author information
                http://orcid.org/0000-0003-3846-8568
                Article
                692
                10.1186/s12263-021-00692-6
                8287703
                34281497
                b2b1f23f-ee77-406a-a0ea-a6ce2847853e
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 17 November 2020
                : 8 July 2021
                Categories
                Review
                Custom metadata
                © The Author(s) 2021

                Nutrition & Dietetics
                transcriptomics,obesity,weight loss intervention,overweight,gene expression
                Nutrition & Dietetics
                transcriptomics, obesity, weight loss intervention, overweight, gene expression

                Comments

                Comment on this article

                scite_
                0
                0
                0
                0
                Smart Citations
                0
                0
                0
                0
                Citing PublicationsSupportingMentioningContrasting
                View Citations

                See how this article has been cited at scite.ai

                scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.

                Similar content170

                Cited by2

                Most referenced authors1,523