Circulating metabolites modulated by diet are associated with depression.
Journal
Molecular psychiatry
ISSN: 1476-5578
Titre abrégé: Mol Psychiatry
Pays: England
ID NLM: 9607835
Informations de publication
Date de publication:
26 Jul 2023
26 Jul 2023
Historique:
received:
01
07
2022
accepted:
03
07
2023
revised:
03
07
2023
medline:
27
7
2023
pubmed:
27
7
2023
entrez:
26
7
2023
Statut:
aheadofprint
Résumé
Metabolome reflects the interplay of genome and exposome at molecular level and thus can provide deep insights into the pathogenesis of a complex disease like major depression. To identify metabolites associated with depression we performed a metabolome-wide association analysis in 13,596 participants from five European population-based cohorts characterized for depression, and circulating metabolites using ultra high-performance liquid chromatography/tandem accurate mass spectrometry (UHPLC/MS/MS) based Metabolon platform. We tested 806 metabolites covering a wide range of biochemical processes including those involved in lipid, amino-acid, energy, carbohydrate, xenobiotic and vitamin metabolism for their association with depression. In a conservative model adjusting for life style factors and cardiovascular and antidepressant medication use we identified 8 metabolites, including 6 novel, significantly associated with depression. In individuals with depression, increased levels of retinol (vitamin A), 1-palmitoyl-2-palmitoleoyl-GPC (16:0/16:1) (lecithin) and mannitol/sorbitol and lower levels of hippurate, 4-hydroxycoumarin, 2-aminooctanoate (alpha-aminocaprylic acid), 10-undecenoate (11:1n1) (undecylenic acid), 1-linoleoyl-GPA (18:2) (lysophosphatidic acid; LPA 18:2) are observed. These metabolites are either directly food derived or are products of host and gut microbial metabolism of food-derived products. Our Mendelian randomization analysis suggests that low hippurate levels may be in the causal pathway leading towards depression. Our findings highlight putative actionable targets for depression prevention that are easily modifiable through diet interventions.
Identifiants
pubmed: 37495887
doi: 10.1038/s41380-023-02180-2
pii: 10.1038/s41380-023-02180-2
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© 2023. The Author(s).
Références
Bromet E, Andrade LH, Hwang I, Sampson NA, Alonso J, de Girolamo G, et al. Cross-national epidemiology of DSM-IV major depressive episode. BMC Med. 2011;9:90.
pubmed: 21791035
pmcid: 3163615
doi: 10.1186/1741-7015-9-90
Salari N, Hosseinian-Far A, Jalali R, Vaisi-Raygani A, Rasoulpoor S, Mohammadi M, et al. Prevalence of stress, anxiety, depression among the general population during the COVID-19 pandemic: a systematic review and meta-analysis. Glob Health. 2020;16:57.
doi: 10.1186/s12992-020-00589-w
Moncrieff J, Cooper RE, Stockmann T, Amendola S, Hengartner MP, Horowitz MA. The serotonin theory of depression: a systematic umbrella review of the evidence. Mol Psychiatry. 2022. https://doi.org/10.1038/s41380-022-01661-0 .
Pigott HE, Leventhal AM, Alter GS, Boren JJ. Efficacy and Effectiveness of Antidepressants: current Status of Research. Psychother Psychosom. 2010;79:267–79.
pubmed: 20616621
doi: 10.1159/000318293
Sullivan PF, Neale MC, Kendler KS. Genetic epidemiology of major depression: review and meta-analysis. Am J Psychiatry. 2000;157:1552–62.
pubmed: 11007705
doi: 10.1176/appi.ajp.157.10.1552
Howard DM, Adams MJ, Clarke TK, Hafferty JD, Gibson J, Shirali M, et al. Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. Nat Neurosci. 2019;22:343–52.
pubmed: 30718901
pmcid: 6522363
doi: 10.1038/s41593-018-0326-7
Batterham PJ, Christensen H, Mackinnon AJ. Modifiable risk factors predicting major depressive disorder at four year follow-up: a decision tree approach. Bmc Psychiatry. 2009;9:75.
pubmed: 19930610
pmcid: 2784764
doi: 10.1186/1471-244X-9-75
Firth J, Gangwisch JE, Borisini A, Wootton RE, Mayer EA. Food and mood: how do diet and nutrition affect mental wellbeing? BMJ. 2020;369:m2382.
pubmed: 32601102
pmcid: 7322666
doi: 10.1136/bmj.m2382
Ghosh TS, Rampelli S, Jeffery IB, Santoro A, Neto M, Capri M, et al. Mediterranean diet intervention alters the gut microbiome in older people reducing frailty and improving health status: the NU-AGE 1-year dietary intervention across five European countries. Gut. 2020;69:1218–28.
pubmed: 32066625
doi: 10.1136/gutjnl-2019-319654
Li Y, Lv MR, Wei YJ, Sun L, Zhang JX, Zhang HG, et al. Dietary patterns and depression risk: a meta-analysis. Psychiatry Res. 2017;253:373–82.
pubmed: 28431261
doi: 10.1016/j.psychres.2017.04.020
Firth J, Marx W, Dash S, Carney R, Teasdale SB, Solmi M, et al. The effects of dietary improvement on symptoms of depression and anxiety: a meta-analysis of randomized controlled trials. Psychosom Med. 2019;81:265–80.
pubmed: 30720698
pmcid: 6455094
doi: 10.1097/PSY.0000000000000673
Lichtenstein AH, Appel LJ, Vadiveloo M, Hu FB, Kris-Etherton PM, Rebholz CM, et al. 2021 dietary guidance to improve cardiovascular health: a scientific statement from the American Heart Association. Circulation. 2021;144:e472–e87.
pubmed: 34724806
doi: 10.1161/CIR.0000000000001031
Abbate M, Gallardo-Alfaro L, Bibiloni MDM, Tur JA. Efficacy of dietary intervention or in combination with exercise on primary prevention of cardiovascular disease: a systematic review. Nutr Metab Cardiovasc Dis. 2020;30:1080–93.
pubmed: 32448717
doi: 10.1016/j.numecd.2020.02.020
Sofi F, Cesari F, Abbate R, Gensini GF, Casini A. Adherence to mediterranean diet and health status: meta-analysis. BMJ. 2008;337:a1344.
pubmed: 18786971
pmcid: 2533524
doi: 10.1136/bmj.a1344
Kang HJ, Kim SY, Bae KY, Kim SW, Shin IS, Yoon JS, et al. Comorbidity of depression with physical disorders: research and clinical implications. Chonnam Med J. 2015;51:8–18.
pubmed: 25914875
pmcid: 4406996
doi: 10.4068/cmj.2015.51.1.8
Sethi S, Brietzke E. Omics-based biomarkers: application of metabolomics in neuropsychiatric disorders. Int J Neuropsychopharmacol. 2015;19:pyv096.
pubmed: 26453695
pmcid: 4815467
doi: 10.1093/ijnp/pyv096
Quinones MP, Kaddurah-Daouk R. Metabolomics tools for identifying biomarkers for neuropsychiatric diseases. Neurobiol Dis. 2009;35:165–76.
pubmed: 19303440
doi: 10.1016/j.nbd.2009.02.019
Patti GJ, Yanes O, Siuzdak G. Innovation: metabolomics: the apogee of the omics trilogy. Nat Rev Mol Cell Biol. 2012;13:263–9.
pubmed: 22436749
pmcid: 3682684
doi: 10.1038/nrm3314
Valles-Colomer M, Falony G, Darzi Y, Tigchelaar EF, Wang J, Tito RY, et al. The neuroactive potential of the human gut microbiota in quality of life and depression. Nat Microbiol. 2019;4:623–32.
pubmed: 30718848
doi: 10.1038/s41564-018-0337-x
Liu J, Lahousse L, Nivard MG, Bot M, Chen L, van Klinken JB, et al. Integration of epidemiologic, pharmacologic, genetic and gut microbiome data in a drug-metabolite atlas. Nat Med. 2020;26:110–7.
pubmed: 31932804
doi: 10.1038/s41591-019-0722-x
Bot M, Milaneschi Y, Al-Shehri T, Amin N, Garmaeva S, Onderwater GLJ, et al. Metabolomics profile in depression: a pooled analysis of 230 metabolic markers in 5283 cases with depression and 10,145 controls. Biol Psychiatry. 2020;87:409–18.
pubmed: 31635762
doi: 10.1016/j.biopsych.2019.08.016
Amin N, Liu J, Bonnechere B, MahmoudianDehkordi S, Arnold M, Batra R, et al. Interplay of metabolome and gut microbiome in individuals with major depressive disorder vs control individuals. JAMA Psychiatry. 2023;80:597–609.
pubmed: 37074710
doi: 10.1001/jamapsychiatry.2023.0685
MacDonald K, Krishnan A, Cervenka E, Hu G, Guadagno E, Trakadis Y. Biomarkers for major depressive and bipolar disorders using metabolomics: a systematic review. Am J Med Genet B. 2019;180:122–37.
doi: 10.1002/ajmg.b.32680
Shin SY, Fauman EB, Petersen AK, Krumsiek J, Santos R, Huang J, et al. An atlas of genetic influences on human blood metabolites. Nat Genet. 2014;46:543–50.
pubmed: 24816252
pmcid: 4064254
doi: 10.1038/ng.2982
Dunlop BW, Binder EB, Cubells JF, Goodman MM, Kelley ME, Kinkead B, et al. Predictors of remission in depression to individual and combined treatments (PReDICT): study protocol for a randomized controlled trial. Trials. 2012;13:106.
pubmed: 22776534
pmcid: 3539869
doi: 10.1186/1745-6215-13-106
Lewinsohn PM, Seeley JR, Roberts RE, Allen NB. Center for Epidemiologic Studies Depression Scale (CES-D) as a screening instrument for depression among community-residing older adults. Psychol Aging. 1997;12:277–87.
pubmed: 9189988
doi: 10.1037/0882-7974.12.2.277
Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001;16:606–13.
pubmed: 11556941
pmcid: 1495268
doi: 10.1046/j.1525-1497.2001.016009606.x
Berth H, Löwe B, Spitzer RL, Zipfel S, Herzog W. PHQ-D. Gesundheitsfragebogen für Patienten. Zeitschrift für Medizinische Psychologie. 2003;12:90–93.
Rush AJ, Gullion CM, Basco MR, Jarrett RB, Trivedi MH. The Inventory of Depressive Symptomatology (IDS): psychometric properties. Psychol Med. 1996;26:477–86.
pubmed: 8733206
doi: 10.1017/S0033291700035558
Smith DJ, Nicholl BI, Cullen B, Martin D, Ul-Haq Z, Evans J, et al. Prevalence and characteristics of probable major depression and bipolar disorder within UK biobank: cross-sectional study of 172,751 participants. PLoS One. 2013;8:e75362.
pubmed: 24282498
pmcid: 3839907
doi: 10.1371/journal.pone.0075362
First MB, Spitzer RL, Gibbon M, Williams JB. Structured clinical interview for the DSM-IV Axis Disorders (SCID PTSD Module). In: Biometrics Research Department NSPI,. New York 1996.
MahmoudianDehkordi S, Arnold M, Nho K, Ahmad S, Jia W, Xie G, et al. Altered bile acid profile associates with cognitive impairment in Alzheimer’s disease-An emerging role for gut microbiome. Alzheimers Dement. 2019;15:76–92.
pubmed: 30337151
doi: 10.1016/j.jalz.2018.07.217
McCarthy S, Das S, Kretzschmar W, Delaneau O, Wood AR, Teumer A, et al. A reference panel of 64,976 haplotypes for genotype imputation. Nat Genet. 2016;48:1279–83.
pubmed: 27548312
pmcid: 5388176
doi: 10.1038/ng.3643
Willer CJ, Li Y, Abecasis GR. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics. 2010;26:2190–1.
pubmed: 20616382
pmcid: 2922887
doi: 10.1093/bioinformatics/btq340
Yavorska OO, Burgess S. MendelianRandomization: an R package for performing Mendelian randomization analyses using summarized data. Int J Epidemiol. 2017;46:1734–9.
pubmed: 28398548
pmcid: 5510723
doi: 10.1093/ije/dyx034
Bakkaloglu B, Yabanoglu S, Ozyuksel BR, Uaar G, Ertugrul A, Demir B, et al. Platelet and plasma serotonin levels and platelet monoamine oxidase activity in patients with major depression: effects of sertraline treatment. Turk J Biochem. 2008;33:97–103.
Hess S, Baker G, Gyenes G, Tsuyuki R, Newman S, Le Melledo JM. Decreased serum L-arginine and L-citrulline levels in major depression. Psychopharmacology (Berl). 2017;234:3241–7.
pubmed: 28803324
doi: 10.1007/s00213-017-4712-8
Pallister T, Jackson MA, Martin TC, Zierer J, Jennings A, Mohney RP, et al. Hippurate as a metabolomic marker of gut microbiome diversity: modulation by diet and relationship to metabolic syndrome. Sci Rep. 2017;7:13670.
pubmed: 29057986
pmcid: 5651863
doi: 10.1038/s41598-017-13722-4
Liu B, Raeth T, Beuerle T, Beerhues L. A novel 4-hydroxycoumarin biosynthetic pathway. Plant Mol Biol. 2010;72:17–25.
pubmed: 19757094
doi: 10.1007/s11103-009-9548-0
Manolov I, Maichle-Moessmer C, Danchev N. Synthesis, structure, toxicological and pharmacological investigations of 4-hydroxycoumarin derivatives. Eur J Med Chem. 2006;41:882–90.
pubmed: 16647160
doi: 10.1016/j.ejmech.2006.03.007
Alhajj MJ, Montero N, Yarce CJ, Salamanca CH. Lecithins from vegetable, land, and marine animal sources and their potential applications for cosmetic, food, and pharmaceutical sectors. Cosmetics. 2020;7:87.
doi: 10.3390/cosmetics7040087
Lee BH, Choi SH, Kim HJ, Jung SW, Kim HK, Nah SY. Plant lysophosphatidic acids: a rich source for bioactive lysophosphatidic acids and their pharmacological applications. Biol Pharm Bull. 2016;39:156–62.
pubmed: 26830477
doi: 10.1248/bpb.b15-00575
Zumbe A, Lee A, Storey D. Polyols in confectionery: the route to sugar-free, reduced sugar and reduced calorie confectionery. Br J Nutr. 2001;85:S31–45.
pubmed: 11318000
doi: 10.1079/BJN2000260
Brunk E, Sahoo S, Zielinski DC, Altunkaya A, Drager A, Mih N, et al. Recon3D enables a three-dimensional view of gene variation in human metabolism. Nat Biotechnol. 2018;36:272–81.
pubmed: 29457794
pmcid: 5840010
doi: 10.1038/nbt.4072
Lees HJ, Swann JR, Wilson ID, Nicholson JK, Holmes E. Hippurate: the natural history of a mammalian-microbial cometabolite. J Proteome Res. 2013;12:1527–46.
pubmed: 23342949
doi: 10.1021/pr300900b
Cheung SG, Goldenthal AR, Uhlemann AC, Mann JJ, Miller JM, Sublette ME. Systematic review of gut microbiota and major depression. Front Psychiatry. 2019;10:34.
pubmed: 30804820
pmcid: 6378305
doi: 10.3389/fpsyt.2019.00034
Bremner JD, Shearer KD, McCaffery PJ. Retinoic acid and affective disorders: the evidence for an association. J Clin Psychiatry. 2012;73:37–50.
pubmed: 21903028
doi: 10.4088/JCP.10r05993
Landy D. Pibloktoq (hysteria) and Inuit nutrition: possible implication of hypervitaminosis A. Soc Sci Med. 1985;21:173–85.
pubmed: 4049004
doi: 10.1016/0277-9536(85)90087-5
O’Reilly K, Bailey SJ, Lane MA. Retinoid-mediated regulation of mood: possible cellular mechanisms. Exp Biol Med (Maywood). 2008;233:251–8.
pubmed: 18296731
doi: 10.3181/0706-MR-158
de Oliveira MR, da Rocha RF, Pasquali MA, Moreira JC. The effects of vitamin A supplementation for 3 months on adult rat nigrostriatal axis: increased monoamine oxidase enzyme activity, mitochondrial redox dysfunction, increased beta-amyloid(1-40) peptide and TNF-alpha contents, and susceptibility of mitochondria to an in vitro H2O2 challenge. Brain Res Bull. 2012;87:432–44.
pubmed: 22274401
doi: 10.1016/j.brainresbull.2012.01.005
Lane MA, Bailey SJ. Role of retinoid signalling in the adult brain. Prog Neurobiol. 2005;75:275–93.
pubmed: 15882777
doi: 10.1016/j.pneurobio.2005.03.002
Mey J, McCaffery P. Retinoic acid signaling in the nervous system of adult vertebrates. Neuroscientist. 2004;10:409–21.
pubmed: 15359008
doi: 10.1177/1073858404263520
Bremner JD, McCaffery P. The neurobiology of retinoic acid in affective disorders. Prog Neuropsychopharmacol Biol Psychiatry. 2008;32:315–31.
pubmed: 17707566
doi: 10.1016/j.pnpbp.2007.07.001
Gerber LE, Erdman JW Jr. Changes in lipid metabolism during retinoid administration. J Am Acad Dermatol. 1982;6:664–74.
pubmed: 7068975
doi: 10.1016/S0190-9622(82)80047-9
Klor HU, Weizel A, Augustin M, Diepgen TL, Elsner P, Homey B, et al. The impact of oral vitamin A derivatives on lipid metabolism - what recommendations can be derived for dealing with this issue in the daily dermatological practice? J Dtsch Dermatol Ges. 2011;9:600–6.
pubmed: 21392258
doi: 10.1111/j.1610-0387.2011.07637.x
Guerra A, Folesani G, Mena P, Ticinesi A, Allegri F, Nouvenne A, et al. Hippuric acid in 24 h urine collections as a biomarker of fruits and vegetables intake in kidney stone formers. Int J Food Sci Nutr. 2014;65:1033–8.
pubmed: 25198158
doi: 10.3109/09637486.2014.950210
Stratakis N, Siskos AP, Papadopoulou E, Nguyen AN, Zhao Y, Margetaki K, et al. Urinary metabolic biomarkers of diet quality in European children are associated with metabolic health. Elife. 2022;11:e71332.
pubmed: 35076016
pmcid: 8789316
doi: 10.7554/eLife.71332
Brial F, Chilloux J, Nielsen T, Vieira-Silva S, Falony G, Andrikopoulos P, et al. Human and preclinical studies of the host-gut microbiome co-metabolite hippurate as a marker and mediator of metabolic health. Gut. 2021;70:2105–14.
pubmed: 33975870
doi: 10.1136/gutjnl-2020-323314
Lassale C, Batty GD, Baghdadli A, Jacka F, Sanchez-Villegas A, Kivimaki M, et al. Healthy dietary indices and risk of depressive outcomes: a systematic review and meta-analysis of observational studies. Mol Psychiatry. 2019;24:965–86.
pubmed: 30254236
doi: 10.1038/s41380-018-0237-8
Hosseini B, Berthon BS, Saedisomeolia A, Starkey MR, Collison A, Wark PAB, et al. Effects of fruit and vegetable consumption on inflammatory biomarkers and immune cell populations: a systematic literature review and meta-analysis. Am J Clin Nutr. 2018;108:136–55.
pubmed: 29931038
doi: 10.1093/ajcn/nqy082
Lončar M, Jakovljević M, Šubarić D, Pavlić M, Buzjak Služek V, Cindrić I, et al. Coumarins in Food and Methods of Their Determination. Foods. 2020;9:645.
pubmed: 32443406
pmcid: 7278589
doi: 10.3390/foods9050645
von Kanel R, Margani A, Stauber S, Meyer FA, Demarmels Biasiutti F, Vokt F, et al. Depressive symptoms as a novel risk factor for recurrent venous thromboembolism: a longitudinal observational study in patients referred for thrombophilia investigation. PLoS One. 2015;10:e0125858.
doi: 10.1371/journal.pone.0125858
Kunutsor SK, Seidu S, Khunti K. Depression, antidepressant use, and risk of venous thromboembolism: systematic review and meta-analysis of published observational evidence. Ann Med. 2018;50:529–37.
pubmed: 30001640
doi: 10.1080/07853890.2018.1500703
Lee CW, Liao CH, Lin CL, Liang JA, Sung FC, Kao CH. Depression and risk of venous thromboembolism: a population-based retrospective cohort study. Psychosom Med. 2015;77:591–8.
pubmed: 25984821
doi: 10.1097/PSY.0000000000000193
Sansone RA, Sansone LA. Warfarin and Antidepressants: happiness without Hemorrhaging. Psychiatry (Edgmont). 2009;6:24–9.
pubmed: 19724766
Parkin L, Balkwill A, Sweetland S, Reeves GK, Green J, Beral V, et al. Antidepressants, depression, and venous thromboembolism risk: large prospective study of UK women. J Am Heart Assoc. 2017;6:e005316.
pubmed: 28515116
pmcid: 5524086
doi: 10.1161/JAHA.116.005316
Ferland G. Vitamin K and the nervous system: an overview of its actions. Adv Nutr. 2012;3:204–12.
pubmed: 22516728
pmcid: 3648721
doi: 10.3945/an.111.001784
Bartke N, Hannun YA. Bioactive sphingolipids: metabolism and function. J Lipid Res. 2009;50:S91–6.
pubmed: 19017611
pmcid: 2674734
doi: 10.1194/jlr.R800080-JLR200
Zeidan YH, Hannun YA. Translational aspects of sphingolipid metabolism. Trends Mol Med. 2007;13:327–36.
pubmed: 17588815
doi: 10.1016/j.molmed.2007.06.002
Cutler RG, Kelly J, Storie K, Pedersen WA, Tammara A, Hatanpaa K, et al. Involvement of oxidative stress-induced abnormalities in ceramide and cholesterol metabolism in brain aging and Alzheimer’s disease. Proc Natl Acad Sci USA. 2004;101:2070–5.
pubmed: 14970312
pmcid: 357053
doi: 10.1073/pnas.0305799101
Jana A, Hogan EL, Pahan K. Ceramide and neurodegeneration: susceptibility of neurons and oligodendrocytes to cell damage and death. J Neurol Sci. 2009;278:5–15.
pubmed: 19147160
pmcid: 2660887
doi: 10.1016/j.jns.2008.12.010
Posse de Chaves E, Sipione S. Sphingolipids and gangliosides of the nervous system in membrane function and dysfunction. FEBS Lett. 2010;584:1748–59.
pubmed: 20006608
doi: 10.1016/j.febslet.2009.12.010
Gulbins E, Palmada M, Reichel M, Luth A, Bohmer C, Amato D, et al. Acid sphingomyelinase-ceramide system mediates effects of antidepressant drugs. Nat Med. 2013;19:934–8.
pubmed: 23770692
doi: 10.1038/nm.3214
Muller CP, Reichel M, Muhle C, Rhein C, Gulbins E, Kornhuber J. Brain membrane lipids in major depression and anxiety disorders. Biochim Biophys Acta. 2015;1851:1052–65.
pubmed: 25542508
doi: 10.1016/j.bbalip.2014.12.014
MacQueen GM, Rosebush PI, Mazurek MF. Neuropsychiatric aspects of the adult variant of Tay-Sachs disease. J Neuropsychiatry Clin Neurosci. 1998;10:10–9.
pubmed: 9547461
doi: 10.1176/jnp.10.1.10
Cole AL, Lee PJ, Hughes DA, Deegan PB, Waldek S, Lachmann RH. Depression in adults with fabry disease: a common and under-diagnosed problem. J Inherit Metab Dis. 2007;30:943–51.
pubmed: 17994284
doi: 10.1007/s10545-007-0708-6
Laney DA, Gruskin DJ, Fernhoff PM, Cubells JF, Ousley OY, Hipp H, et al. Social-adaptive and psychological functioning of patients affected by Fabry disease. J Inherit Metab Dis. 2010;33:S73–81.
pubmed: 20087663
doi: 10.1007/s10545-009-9025-6
Sadek J, Shellhaas R, Camfield CS, Camfield PR, Burley J. Psychiatric findings in four female carriers of fabry disease. Psychiatr Genet. 2004;14:199–201.
pubmed: 15564893
doi: 10.1097/00041444-200412000-00006
Packman W, Wilson Crosbie T, Riesner A, Fairley C, Packman S. Psychological complications of patients with Gaucher disease. J Inherit Metab Dis. 2006;29:99–105.
pubmed: 16601875
doi: 10.1007/s10545-006-0154-x
MahmoudianDehkordi S, Ahmed AT, Bhattacharyya S, Han X, Baillie RA, Arnold M, et al. Alterations in acylcarnitines, amines, and lipids inform about the mechanism of action of citalopram/escitalopram in major depression. Transl Psychiatry. 2021;11:153.
pubmed: 33654056
pmcid: 7925685
doi: 10.1038/s41398-020-01097-6
Awuchi C. Sugar Alcohols: Chemistry, Production, Health Concerns and Nutritional Importance of Mannitol, Sorbitol, Xylitol, and Erythritol. Int J Adv Acad Res. 2017;3:2488–9849.
Ledochowski M. BWHBTPDF. Fructose- and Sorbitol-reduced diet improves mood and gastrointestinal disturbances in fructose malabsorbers. Scand J Gastroenterol. 2000;35:1048–52.
pubmed: 11099057
doi: 10.1080/003655200451162
Janowsky DS, el-Yousef MK, Davis JM. Acetylcholine and depression. Psychosom Med. 1974;36:248–57.
pubmed: 4829619
doi: 10.1097/00006842-197405000-00008
Hirsch MJ, Wurtman RJ. Lecithin consumption increases acetylcholine concentrations in rat brain and adrenal gland. Science. 1978;202:223–5.
pubmed: 694529
doi: 10.1126/science.694529
Magil SG, Zeisel SH, Wurtman RJ. Effects of ingesting soy or egg lecithins on serum choline, brain choline and brain acetylcholine. J Nutr. 1981;111:166–70.
pubmed: 7192727
doi: 10.1093/jn/111.1.166
Loffelholz K, Klein J, Koppen A. Choline, a precursor of acetylcholine and phospholipids in the brain. Prog Brain Res. 1993;98:197–200.
pubmed: 8248509
doi: 10.1016/S0079-6123(08)62399-7
Puri P, Baillie RA, Wiest MM, Mirshahi F, Choudhury J, Cheung O, et al. A lipidomic analysis of nonalcoholic fatty liver disease. Hepatology. 2007;46:1081–90.
pubmed: 17654743
doi: 10.1002/hep.21763
Callaerts-Vegh Z, Leo S, Vermaercke B, Meert T, D’Hooge R. LPA5 receptor plays a role in pain sensitivity, emotional exploration and reversal learning. Genes Brain Behav. 2012;11:1009–19.
pubmed: 23039190
Moreno-Fernandez RD, Perez-Martin M, Castilla-Ortega E, Rosell Del Valle C, Garcia-Fernandez MI, Chun J, et al. maLPA1-null mice as an endophenotype of anxious depression. Transl Psychiatry. 2017;7:e1077.
pubmed: 28375206
pmcid: 5416683
doi: 10.1038/tp.2017.24
Saldanha D, Kumar N, Ryali V, Srivastava K, Pawar AA. Serum serotonin abnormality in depression. Med J Armed Forces India. 2009;65:108–12.
pubmed: 27408213
pmcid: 4921409
doi: 10.1016/S0377-1237(09)80120-2
Wood K, Harwood J, Coppen A. The effect of antidepressant drugs on plasma kynurenine in depressed patients. Psychopharmacology (Berl). 1978;59:263–6.
pubmed: 104330
doi: 10.1007/BF00426632
Alvarez JC, Gluck N, Fallet A, Gregoire A, Chevalier JF, Advenier C, et al. Plasma serotonin level after 1 day of fluoxetine treatment: a biological predictor for antidepressant response? Psychopharmacology (Berl). 1999;143:97–101.
pubmed: 10227085
doi: 10.1007/s002130050924
Inoshita M, Umehara H, Watanabe SY, Nakataki M, Kinoshita M, Tomioka Y, et al. Elevated peripheral blood glutamate levels in major depressive disorder. Neuropsychiatr Dis Treat. 2018;14:945–53.
pubmed: 29670355
pmcid: 5896673
doi: 10.2147/NDT.S159855
Ogawa S, Koga N, Hattori K, Matsuo J, Ota M, Hori H, et al. Plasma amino acid profile in major depressive disorder: analyses in two independent case-control sample sets. J Psychiatr Res. 2018;96:23–32.
pubmed: 28950111
doi: 10.1016/j.jpsychires.2017.09.014
Ali-Sisto T, Tolmunen T, Viinamaki H, Mantyselka P, Valkonen-Korhonen M, Koivumaa-Honkanen H, et al. Global arginine bioavailability ratio is decreased in patients with major depressive disorder. J Affect Disord. 2018;229:145–51.
pubmed: 29310063
doi: 10.1016/j.jad.2017.12.030
Rotroff DM, Corum DG, Motsinger-Reif A, Fiehn O, Bottrel N, Drevets WC, et al. Metabolomic signatures of drug response phenotypes for ketamine and esketamine in subjects with refractory major depressive disorder: new mechanistic insights for rapid acting antidepressants. Transl Psychiatry. 2016;6:e894.
pubmed: 27648916
pmcid: 5048196
doi: 10.1038/tp.2016.145
Guerreiro JR, Lameu C, Oliveira EF, Klitzke CF, Melo RL, Linares E, et al. Argininosuccinate synthetase is a functional target for a snake venom anti-hypertensive peptide: role in arginine and nitric oxide production. J Biol Chem. 2009;284:20022–33.
pubmed: 19491403
pmcid: 2740428
doi: 10.1074/jbc.M109.021089
Bahri S, Zerrouk N, Aussel C, Moinard C, Crenn P, Curis E, et al. Citrulline: from metabolism to therapeutic use. Nutrition. 2013;29:479–84.
pubmed: 23022123
doi: 10.1016/j.nut.2012.07.002
Fewell Z, Davey Smith G, Sterne JA. The impact of residual and unmeasured confounding in epidemiologic studies: a simulation study. Am J Epidemiol. 2007;166:646–55.
pubmed: 17615092
doi: 10.1093/aje/kwm165
Nath AP, Ritchie SC, Byars SG, Fearnley LG, Havulinna AS, Joensuu A, et al. An interaction map of circulating metabolites, immune gene networks, and their genetic regulation. Genome Biol. 2017;18:146.
pubmed: 28764798
pmcid: 5540552
doi: 10.1186/s13059-017-1279-y