Effects of a Low-Carbohydrate, High-Protein Diet on Gut Microbiome Composition in Insulin-Resistant Individuals With Chronic Spinal Cord Injury: Preliminary Results From a Randomized Controlled Trial

Published:April 10, 2022DOI:



      To evaluate the effect of a low-carbohydrate, high-protein (LC/HP) diet that includes healthy dietary components (eg, lean meat, whole grains, fruits and vegetables, fiber, etc) on the gut microbiome composition in individuals with chronic spinal cord injury (SCI).


      A single-center randomized parallel controlled trial.


      Research University.


      Adult participants with chronic SCI (N=19, 3 years or more after the injury, C2-L2, American Spinal Injury Association Impairment Scale A-D). Participants were insulin resistant and had not received antibiotics within 4 weeks before enrolling in the study.


      Participants were randomized to the LC/HP diet group (40% energy from carbohydrates, 30% energy from protein, and 30% energy from fat and met dietary guideline recommendations) or the control group for 8 weeks. Participants assigned to the LC/HP group were provided with all meals delivered weekly to their homes. Participants assigned to the control group were asked to continue their usual diet.

      Main Outcome Measures

      Stool samples were collected at baseline and the end of week 8. The gut microbiome 16S ribosomal RNA V4 region was sequenced, and gut microbiome diversity and taxonomical abundance were computed using the QIIME2 suite.


      Participants in the LC/HP group had significant changes in alpha-diversity (reduced operational taxonomic unit and Faith's phylogenetic diversity) and beta-diversity (unweighted UniFrac), while no significant differences were observed among participants in the control group after the intervention. Moreover, several taxa changed differently over time between groups, including increased Bacteroides thetaiotaomicron, Coprococcus 3, Fusicatenibacter, Tannerellaceae, and decreased Tyzzerella, Phascolarctobacterium, Romboutsia, Clostridium sensu stricto 1, Hungatella, Ruminococcus gauvreauii, family XI, and Bacillales among participants in the diet group, while these taxa did not change in the control group.


      An LC/HP diet with healthy dietary components improved gut microbiome composition in individuals with SCI, including increased bacteria implicated in fiber metabolism and reduced bacteria communities linked to cardiometabolic disorders.


      List of abbreviations:

      ANCOM (analysis of composition of microbiomes), ASV (amplicon sequence variant), GD (gut dysbiosis), LC/HP (low-carbohydrate/high-protein diet), OGTT (oral glucose tolerance test), OTU (operational taxonomic unit), QIIME2 (Quantitative Insights Into Microbial Ecology 2), SCFA (short-chain fatty acid), SCI (spinal cord injury)
      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'


      Subscribe to Archives of Physical Medicine and Rehabilitation
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect


      1. National Spinal Cord Injury Statistical Center. Spinal cord injury: facts and figures at a glance, 2020. Available at: Accessed December 17, 2021.

      2. National Spinal Cord Injury Statistical Center. Spinal cord injury: facts and figures at a glance, 2000. Available at: Accessed December 17, 2021.

        • Bauman WA
        • Spungen AM.
        Disorders of carbohydrate and lipid metabolism in veterans with paraplegia or quadriplegia: a model of premature aging.
        Metabolism. 1994; 43: 749-756
        • Bauman WA
        • Spungen AM.
        Carbohydrate and lipid metabolism in chronic spinal cord injury.
        J Spinal Cord Med. 2001; 24: 266-277
        • Bauman WA
        • Spungen AM.
        Metabolic changes in persons after spinal cord injury.
        Phys Med Rehabil Clin N Am. 2000; 11: 109-140
        • Inskip J
        • Plunet W
        • Ramer L
        • et al.
        Cardiometabolic risk factors in experimental spinal cord injury.
        J Neurotrauma. 2010; 27: 275-285
        • Nash MS
        • Tractenberg RE
        • Mendez AJ
        • et al.
        Cardiometabolic syndrome in people with spinal cord injury/disease: guideline-derived and nonguideline risk components in a pooled sample.
        Arch Phys Med Rehabil. 2016; 97: 1696-1705
        • Jensen MP
        • Molton IR
        • Groah SL
        • et al.
        Secondary health conditions in individuals aging with SCI: terminology, concepts and analytic approaches.
        Spinal Cord. 2012; 50: 373-378
        • Hitzig SL
        • Eng JJ
        • Miller WC
        • Sakakibara BM
        • Research Team SCIRE
        An evidence-based review of aging of the body systems following spinal cord injury.
        Spinal Cord. 2011; 49: 684-701
        • Kigerl KA
        • Hall JC
        • Wang L
        • Mo X
        • Yu Z
        • Popovich PG.
        Gut dysbiosis impairs recovery after spinal cord injury.
        J Exp Med. 2016; 213: 2603-2620
        • O'Connor G
        • Jeffrey E
        • Madorma D
        • et al.
        Investigation of microbiota alterations and intestinal inflammation post-spinal cord injury in rat model.
        J Neurotrauma. 2018; 35: 2159-2166
        • Li J
        • Van Der Pol W
        • Eraslan M
        • et al.
        Comparison of the gut microbiome composition among individuals with acute or long-standing spinal cord injury vs. able-bodied controls.
        J Spinal Cord Med. 2022; 45: 91-99
        • Clarke SF
        • Murphy EF
        • Nilaweera K
        • et al.
        The gut microbiota and its relationship to diet and obesity: new insights.
        Gut Microbes. 2012; 3: 186-202
        • Li J
        • Morrow C
        • Barnes S
        • et al.
        Gut microbiome composition and serum metabolome profile among individuals with spinal cord injury and normal glucose tolerance or prediabetes/type 2 diabetes.
        Arch Phys Med Rehabil. 2022; 103: 702-710
        • Li J
        • Demirel A
        • Azuero A
        • et al.
        Limited association between the total Healthy Eating Index-2015 score and cardiovascular risk factors in individuals with long-standing spinal cord injury: an exploratory study: an exploratory study.
        J Acad Nutr Diet. 2021; 121: 2260-2266
        • Silveira SL
        • Winter LL
        • Clark R
        • Ledoux T
        • Robinson-Whelen S.
        Baseline dietary intake of individuals with spinal cord injury who are overweight or obese.
        J Acad Nutr Diet. 2019; 119: 301-309
        • Conlon MA
        • Bird AR.
        The impact of diet and lifestyle on gut microbiota and human health.
        Nutrients. 2014; 7: 17-44
        • Yu E
        • Rimm E
        • Qi L
        • et al.
        Diet, lifestyle, biomarkers, genetic factors, and risk of cardiovascular disease in the nurses’ health studies.
        Am J Public Health. 2016; 106: 1616-1623
        • Leidy HJ.
        Increased dietary protein as a dietary strategy to prevent and/or treat obesity.
        Mo Med. 2014; 111: 54-58
        • Leidy HJ
        • Clifton PM
        • Astrup A
        • et al.
        The role of protein in weight loss and maintenance.
        Am J Clin Nutr. 2015; 101: 1320S-1329S
        • Soenen S
        • Westerterp-Plantenga MS.
        Proteins and satiety: implications for weight management.
        Curr Opin Clin Nutr Metab Care. 2008; 11: 747-751
        • Weigle DS
        • Breen PA
        • Matthys CC
        • et al.
        A high-protein diet induces sustained reductions in appetite, ad libitum caloric intake, and body weight despite compensatory changes in diurnal plasma leptin and ghrelin concentrations.
        Am J Clin Nutr. 2005; 82: 41-48
        • Di Rienzi SC
        • Britton RA.
        Adaptation of the gut microbiota to modern dietary sugars and sweeteners.
        Adv Nutr. 2019; 11: 616-629
        • Makki K
        • Deehan EC
        • Walter J
        • Bäckhed F.
        The impact of dietary fiber on gut microbiota in host health and disease.
        Cell Host Microbe. 2018; 23: 705-715
        • Murphy EA
        • Velazquez KT
        • Herbert KM.
        Influence of high-fat diet on gut microbiota: a driving force for chronic disease risk.
        Curr Opin Clin Nutr Metab Care. 2015; 18: 515-520
      3. American Diabetes Association. 2. Classification and diagnosis of diabetes.
        Diabetes Care. 2017; 40: S11-S24
        • Takahara M
        • Katakami N
        • Kaneto H
        • Noguchi M
        • Shimomura I.
        Distribution of the Matsuda Index in Japanese healthy subjects.
        J Diabetes Investig. 2013; 4: 369-371
      4. Institute of Medicine. Dietary reference intakes for energy, carbohydrate, fiber, fat, fatty acids, cholesterol, protein, and amino acids. Washington, DC: The National Academies Press; 2005.

        • Matsuda M
        • DeFronzo RA.
        Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp.
        Diabetes Care. 1999; 22: 1462-1470
        • Kumar R
        • Eipers P
        • Little RB
        • et al.
        Getting started with microbiome analysis: sample acquisition to bioinformatics.
        Curr Protoc Hum Genet. 2014; 82 (18.8.1-29)
        • Bolyen E
        • Rideout JR
        • Dillon MR
        • et al.
        Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2.
        Nat Biotechnol. 2019; 37: 852-857
        • Callahan BJ
        • McMurdie PJ
        • Rosen MJ
        • Han AW
        • Johnson AJ
        • Holmes SP.
        DADA2: high-resolution sample inference from Illumina amplicon data.
        Nat Methods. 2016; 13: 581-583
        • Quast C
        • Pruesse E
        • Yilmaz P
        • et al.
        The SILVA ribosomal RNA gene database project: improved data processing and web-based tools.
        Nucleic Acids Res. 2013; 41: D590-D596
        • Bokulich NA
        • Zhang Y
        • Dillon M
        • et al.
        q2-longitudinal: a QIIME 2 plugin for longitudinal and paired-sample analyses of microbiome data.
        mSystems. 2018; 3 (e00219-18)
        • McMurdie PJ
        • Holmes S.
        phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data.
        PLoS One. 2013; 8: e61217
        • Mandal S
        • Van Treuren W
        • White RA
        • Eggesbø M
        • Knight R
        • Peddada SD.
        Analysis of composition of microbiomes: a novel method for studying microbial composition.
        Microb Ecol Health Dis. 2015; 26: 27663
        • Aitchison J.
        The statistical analysis of compositional data.
        J R Stat Soc Series B (Methodological). 1982; 44: 139-177
        • Ginis KA
        • Latimer AE
        • Hicks AL
        • Craven BC.
        Development and evaluation of an activity measure for people with spinal cord injury.
        Med Sci Sports Exerc. 2005; 37: 1099-1111
        • Martin Ginis KA
        • Phang SH
        • Latimer AE
        Arbour-Nicitopoulos KP. Reliability and validity tests of the leisure time physical activity questionnaire for people with spinal cord injury.
        Arch Phys Med Rehabil. 2012; 93: 677-682
        • Faul F
        • Erdfelder E
        • Buchner A
        • Lang AG.
        Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.
        Behav Res Methods. 2009; 41: 1149-1160
      5. US Department of Agriculture, US Department of Health and Human Services. Dietary guidelines for Americans, 2020-2025. 9th Edition. December 2020. Available at Accessed June 10, 2022.

        • Lippert K
        • Kedenko L
        • Antonielli L
        • et al.
        Gut microbiota dysbiosis associated with glucose metabolism disorders and the metabolic syndrome in older adults.
        Benef Microbes. 2017; 8: 545-556
        • Saad MJ
        • Santos A
        • Prada PO.
        Linking gut microbiota and inflammation to obesity and insulin resistance.
        Physiology (Bethesda). 2016; 31: 283-293
        • Utzschneider KM
        • Kratz M
        • Damman CJ
        • Hullarg M.
        Mechanisms linking the gut microbiome and glucose metabolism.
        J Clin Endocrinol Metab. 2016; 101: 1445-1454
        • Yan Q
        • Gu Y
        • Li X
        • et al.
        Alterations of the gut microbiome in hypertension.
        Front Cell Infect Microbiol. 2017; 7: 381
        • Kelly JR
        • Kennedy PJ
        • Cryan JF
        • Dinan TG
        • Clarke G
        • Hyland NP.
        Breaking down the barriers: the gut microbiome, intestinal permeability and stress-related psychiatric disorders.
        Front Cell Neurosci. 2015; 9: 392
        • Hills RD
        • Pontefract BA
        • Mishcon HR
        • Black CA
        • Sutton SC
        • Theberge CR.
        Gut microbiome: profound implications for diet and disease.
        Nutrients. 2019; 11: 1613
        • Tap J
        • Furet JP
        • Bensaada M
        • et al.
        Gut microbiota richness promotes its stability upon increased dietary fibre intake in healthy adults.
        Environ Microbiol. 2015; 17: 4954-4964
        • Kulecka M
        • Fraczek B
        • Mikula M
        • et al.
        The composition and richness of the gut microbiota differentiate the top Polish endurance athletes from sedentary controls.
        Gut Microbes. 2020; 11: 1374-1384
        • Chow J
        • Lee SM
        • Shen Y
        • Khosravi A
        • Mazmanian SK.
        Chapter 8 Host-bacterial symbiosis in health and disease.
        (editors)in: Fagarasan S Cerutti A Advances in Immunology. Vol 107. Academic Press, London; Amsterdam2010: 243-274
        • Rodriguez-Castaño GP
        • Dorris MR
        • Liu X
        • Bolling BW
        • Acosta-Gonzalez A
        • Rey FE.
        Bacteroides thetaiotaomicron starch utilization promotes quercetin degradation and butyrate production by Eubacterium ramulus.
        Front Microbiol. 2019; 10: 1145
        • Kelly D
        • Campbell JI
        • King TP
        • et al.
        Commensal anaerobic gut bacteria attenuate inflammation by regulating nuclear-cytoplasmic shuttling of PPAR-gamma and RelA.
        Nat Immunol. 2004; 5: 104-112
        • Rivière A
        • Selak M
        • Lantin D
        • Leroy F
        • De Vuyst L.
        Bifidobacteria and butyrate-producing colon bacteria: importance and strategies for their stimulation in the human gut.
        Front Microbiol. 2016; 7: 979
        • Silva YP
        • Bernardi A
        • Frozza RL.
        The role of short-chain fatty acids from gut microbiota in gut-brain communication.
        Front Endocrinol (Lausanne). 2020; 11: 25
        • Mancabelli L
        • Milani C
        • Lugli GA
        • et al.
        Unveiling the gut microbiota composition and functionality associated with constipation through metagenomic analyses.
        Sci Rep. 2017; 7: 9879
        • Cameron KJ
        • Nyulasi IB
        • Collier GR
        • Brown DJ.
        Assessment of the effect of increased dietary fibre intake on bowel function in patients with spinal cord injury.
        Spinal Cord. 1996; 34: 277-283
        • Mayerhofer CCK
        • Kummen M
        • Holm K
        • et al.
        Low fibre intake is associated with gut microbiota alterations in chronic heart failure.
        ESC Heart Fail. 2020; 7: 456-466
        • Nishimoto Y
        • Mizuguchi Y
        • Mori Y
        • et al.
        Resistant maltodextrin intake reduces virulent metabolites in the gut environment: randomized control study in a Japanese cohort.
        Front Microbiol. 2022; 13644146
        • Qiu X
        • Zhao X
        • Cui X
        • et al.
        Characterization of fungal and bacterial dysbiosis in young adult Chinese patients with Crohn's disease.
        Therap Adv Gastroenterol. 2020; 131756284820971202
        • Takeshita K
        • Mizuno S
        • Mikami Y
        • et al.
        A single species of Clostridium subcluster XIVa decreased in ulcerative colitis patients.
        Inflamm Bowel Dis. 2016; 22: 2802-2810
        • Ren SM
        • Mei L
        • Huang H
        • Cao SF
        • Zhao RH
        • Zheng PY.
        [Correlation analysis of gut microbiota and biochemical indexes in patients with non-alcoholic fatty liver disease] [Chinese].
        Zhonghua Gan Zang Bing Za Zhi. 2019; 27: 369-375
        • Kelly TN
        • Bazzano LA
        • Ajami NJ
        • et al.
        Gut microbiome associates with lifetime cardiovascular disease risk profile among Bogalusa Heart Study participants.
        Circ Res. 2016; 119: 956-964
        • Li LL
        • Wang YT
        • Zhu LM
        • Liu ZY
        • Ye CQ
        • Qin S.
        Inulin with different degrees of polymerization protects against diet-induced endotoxemia and inflammation in association with gut microbiota regulation in mice.
        Sci Rep. 2020; 10: 978
        • Cani PD
        • Bibiloni R
        • Knauf C
        • et al.
        Changes in gut microbiota control metabolic endotoxemia-induced inflammation in high-fat diet–induced obesity and diabetes in mice.
        Diabetes. 2008; 57: 1470-1481
        • Cani PD
        • Amar J
        • Iglesias MA
        • et al.
        Metabolic endotoxemia initiates obesity and insulin resistance.
        Diabetes. 2007; 56: 1761-1772
        • Lecomte V
        • Kaakoush NO
        • Maloney CA
        • et al.
        Changes in gut microbiota in rats fed a high fat diet correlate with obesity-associated metabolic parameters.
        PLoS One. 2015; 10e0126931
        • Sanders FWB
        • Griffin JL.
        De novo lipogenesis in the liver in health and disease: more than just a shunting yard for glucose.
        Biol Rev Camb Philos Soc. 2016; 91: 452-468
        • Hiel S
        • Gianfrancesco MA
        • Rodriguez J
        • et al.
        Link between gut microbiota and health outcomes in inulin-treated obese patients: lessons from the Food4Gut multicenter randomized placebo-controlled trial.
        Clin Nutr. 2020; 39: 3618-3628
        • Zeng Q
        • Li D
        • He Y
        • et al.
        Discrepant gut microbiota markers for the classification of obesity-related metabolic abnormalities.
        Sci Rep. 2019; 9: 13424
        • Tang Q
        • Jin G
        • Wang G
        • et al.
        Current sampling methods for gut microbiota: a call for more precise devices.
        Front Cell Infect Microbiol. 2020; 10: 151