{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T12:07:20Z","timestamp":1792757240616,"version":"4.5.0"},"reference-count":53,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2023,6,10]],"date-time":"2023-06-10T00:00:00Z","timestamp":1686355200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2023,6,10]],"date-time":"2023-06-10T00:00:00Z","timestamp":1686355200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100010661","name":"EC | Horizon 2020 Framework Programme","doi-asserted-by":"publisher","award":["848146"],"award-info":[{"award-number":["848146"]}],"id":[{"id":"10.13039\/100010661","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100010661","name":"EC | Horizon 2020 Framework Programme","doi-asserted-by":"publisher","award":["848146"],"award-info":[{"award-number":["848146"]}],"id":[{"id":"10.13039\/100010661","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Transl Psychiatry"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    Depression shows a metabolomic signature overlapping with that of cardiometabolic conditions. Whether this signature is linked to specific depression profiles remains undetermined. Previous research suggested that metabolic alterations cluster more consistently with depressive symptoms of the atypical spectrum related to energy alterations, such as hyperphagia, weight gain, hypersomnia, fatigue and leaden paralysis. We characterized the metabolomic signature of an \u201catypical\/energy-related\u201d symptom (AES) profile and evaluated its specificity and consistency. Fifty-one metabolites measured using the Nightingale platform in 2876 participants from the Netherlands Study of Depression and Anxiety were analyzed. An \u2018AES profile\u2019 score was based on five items of the Inventory of Depressive Symptomatology (IDS) questionnaire. The AES profile was significantly associated with 31 metabolites including higher glycoprotein acetyls (\u03b2\u2009=\u20090.13,\n                    <jats:italic>p<\/jats:italic>\n                    \u2009=\u20091.35*10\n                    <jats:sup>-12<\/jats:sup>\n                    ), isoleucine (\u03b2\u2009=\u20090.13,\n                    <jats:italic>p<\/jats:italic>\n                    \u2009=\u20091.45*10\n                    <jats:sup>-10<\/jats:sup>\n                    ), very-low-density lipoproteins cholesterol (\u03b2\u2009=\u20090.11,\n                    <jats:italic>p<\/jats:italic>\n                    \u2009=\u20096.19*10\n                    <jats:sup>-9<\/jats:sup>\n                    ) and saturated fatty acid levels (\u03b2\u2009=\u20090.09,\n                    <jats:italic>p<\/jats:italic>\n                    \u2009=\u20093.68*10\n                    <jats:sup>-10<\/jats:sup>\n                    ), and lower high-density lipoproteins cholesterol (\u03b2\u2009=\u2009\u22120.07,\n                    <jats:italic>p<\/jats:italic>\n                    \u2009=\u20091.14*10\n                    <jats:sup>-4<\/jats:sup>\n                    ). The metabolites were not significantly associated with a summary score of all other IDS items not included in the AES profile. Twenty-five AES-metabolites associations were internally replicated using data from the same subjects (\n                    <jats:italic>N<\/jats:italic>\n                    \u2009=\u20092015) collected at 6-year follow-up. We identified a specific metabolomic signature\u2014commonly linked to cardiometabolic disorders\u2014associated with a depression profile characterized by atypical, energy-related symptoms. The specific clustering of a metabolomic signature with a clinical profile identifies a more homogenous subgroup of depressed patients at higher cardiometabolic risk, and may represent a valuable target for interventions aiming at reducing depression\u2019s detrimental impact on health.\n                  <\/jats:p>","DOI":"10.1038\/s41398-023-02484-5","type":"journal-article","created":{"date-parts":[[2023,6,10]],"date-time":"2023-06-10T02:01:43Z","timestamp":1686362503000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":51,"title":["Metabolomics signatures of depression: the role of symptom profiles"],"prefix":"10.1038","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4835-189X","authenticated-orcid":false,"given":"Hilde","family":"de Kluiver","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rick","family":"Jansen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brenda W. J. H.","family":"Penninx","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8874-2292","authenticated-orcid":false,"given":"Erik J.","family":"Giltay","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0760-9866","authenticated-orcid":false,"given":"Robert A.","family":"Schoevers","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3697-6617","authenticated-orcid":false,"given":"Yuri","family":"Milaneschi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,6,10]]},"reference":[{"key":"2484_CR1","doi-asserted-by":"publisher","first-page":"763","DOI":"10.1002\/da.22387","volume":"32","author":"D Vancampfort","year":"2015","unstructured":"Vancampfort D, Mitchell AJ, De Hert M, Sienaert P, Probst M, Buys R, et al. Type 2 diabetes in patients with major depressive disorder: a meta-analysis of prevalence estimates and predictors. Depress Anxiety. 2015;32:763\u201373.","journal-title":"Depress Anxiety"},{"key":"2484_CR2","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1038\/s41380-018-0017-5","volume":"24","author":"Y Milaneschi","year":"2019","unstructured":"Milaneschi Y, Simmons WK, van Rossum EFC, Penninx BW. Depression and obesity: evidence of shared biological mechanisms. Mol Psychiatry. 2019;24:18\u201333.","journal-title":"Mol Psychiatry"},{"key":"2484_CR3","doi-asserted-by":"publisher","first-page":"277","DOI":"10.1016\/j.neubiorev.2016.07.003","volume":"74","author":"BWJH Penninx","year":"2017","unstructured":"Penninx BWJH. Depression and cardiovascular disease: epidemiological evidence on their linking mechanisms. Neurosci Biobehav Rev. 2017;74:277\u201386.","journal-title":"Neurosci Biobehav Rev"},{"key":"2484_CR4","doi-asserted-by":"publisher","first-page":"409","DOI":"10.1016\/j.biopsych.2019.08.016","volume":"87","author":"M Bot","year":"2020","unstructured":"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\u201318.","journal-title":"Biol Psychiatry"},{"key":"2484_CR5","doi-asserted-by":"publisher","first-page":"2298","DOI":"10.1007\/s00125-019-05001-w","volume":"62","author":"AV Ahola-Olli","year":"2019","unstructured":"Ahola-Olli AV, Mustelin L, Kalimeri M, Kettunen J, Jokelainen J, Auvinen J, et al. Circulating metabolites and the risk of type 2 diabetes: a prospective study of 11,896 young adults from four Finnish cohorts. Diabetologia 2019;62:2298\u2013309.","journal-title":"Diabetologia"},{"key":"2484_CR6","doi-asserted-by":"publisher","DOI":"10.1186\/s12916-022-02354-9","volume":"20","author":"F Bragg","year":"2022","unstructured":"Bragg F, Trichia E, Aguilar-Ramirez D, Be\u0161evi\u0107 J, Lewington S, Emberson J. Predictive value of circulating NMR metabolic biomarkers for type 2 diabetes risk in the UK Biobank study. BMC Med. 2022;20:159.","journal-title":"BMC Med"},{"key":"2484_CR7","doi-asserted-by":"publisher","first-page":"e1001765","DOI":"10.1371\/journal.pmed.1001765","volume":"11","author":"P W\u00fcrtz","year":"2014","unstructured":"W\u00fcrtz P, Wang Q, Kangas AJ, Richmond RC, Skarp J, Tiainen M, et al. Metabolic signatures of adiposity in young adults: Mendelian randomization analysis and effects of weight change. PLoS Med. 2014;11:e1001765.","journal-title":"PLoS Med"},{"key":"2484_CR8","doi-asserted-by":"publisher","first-page":"1107","DOI":"10.1176\/appi.ajp.2021.20121776","volume":"178","author":"P Frank","year":"2021","unstructured":"Frank P, Jokela M, Batty GD, Cadar D, Steptoe A, Kivim\u00e4ki M. Association between systemic inflammation and individual symptoms of depression: a pooled analysis of 15 population-based cohort studies. Am J Psychiatry. 2021;178:1107\u201318.","journal-title":"Am J Psychiatry"},{"key":"2484_CR9","doi-asserted-by":"publisher","first-page":"7393","DOI":"10.1038\/s41380-021-01188-w","volume":"26","author":"Y Milaneschi","year":"2021","unstructured":"Milaneschi Y, Kappelmann N, Ye Z, Lamers F, Moser S, Jones PB, et al. Association of inflammation with depression and anxiety: evidence for symptom-specificity and potential causality from UK Biobank and NESDA cohorts. Mol Psychiatry. 2021;26:7393\u2013402.","journal-title":"Mol Psychiatry"},{"key":"2484_CR10","doi-asserted-by":"publisher","first-page":"1102","DOI":"10.1017\/S0033291717002483","volume":"48","author":"F Lamers","year":"2018","unstructured":"Lamers F, Milaneschi Y, de Jonge P, Giltay EJ, Penninx BWJH. Metabolic and inflammatory markers: associations with individual depressive symptoms. Psychol Med. 2018;48:1102\u201310.","journal-title":"Psychol Med"},{"key":"2484_CR11","doi-asserted-by":"publisher","first-page":"807","DOI":"10.1016\/j.biopsych.2015.10.023","volume":"81","author":"Y Milaneschi","year":"2017","unstructured":"Milaneschi Y, Lamers F, Bot M, Drent ML, Penninx BWJH. Leptin dysregulation is specifically associated with major depression with atypical features: evidence for a mechanism connecting obesity and depression. Biol Psychiatry. 2017;81:807\u201314.","journal-title":"Biol Psychiatry"},{"key":"2484_CR12","doi-asserted-by":"publisher","first-page":"1457","DOI":"10.1038\/s41380-018-0093-6","volume":"25","author":"WK Simmons","year":"2020","unstructured":"Simmons WK, Burrows K, Avery JA, Kerr KL, Taylor A, Bodurka J, et al. Appetite changes reveal depression subgroups with distinct endocrine, metabolic, and immune states. Mol Psychiatry. 2020;25:1457\u201368.","journal-title":"Mol Psychiatry"},{"key":"2484_CR13","doi-asserted-by":"publisher","first-page":"104429","DOI":"10.1016\/j.psyneuen.2019.104429","volume":"110","author":"T Alshehri","year":"2019","unstructured":"Alshehri T, Boone S, de Mutsert R, Penninx B, Rosendaal F, le Cessie S, et al. The association between overall and abdominal adiposity and depressive mood: A cross-sectional analysis in 6459 participants. Psychoneuroendocrinology 2019;110:104429.","journal-title":"Psychoneuroendocrinology"},{"key":"2484_CR14","doi-asserted-by":"publisher","first-page":"1214","DOI":"10.1001\/jamapsychiatry.2017.3016","volume":"74","author":"Y Milaneschi","year":"2017","unstructured":"Milaneschi Y, Lamers F, Peyrot WJ, Baune BT, Breen G, Dehghan A, et al. Genetic association of major depression with atypical features and obesity-related immunometabolic dysregulations. JAMA Psychiatry. 2017;74:1214\u201325.","journal-title":"JAMA Psychiatry"},{"key":"2484_CR15","doi-asserted-by":"publisher","first-page":"726","DOI":"10.1017\/S0033291720002342","volume":"52","author":"I Badini","year":"2022","unstructured":"Badini I, Coleman JRI, Hagenaars SP, Hotopf M, Breen G, Lewis CM, et al. Depression with atypical neurovegetative symptoms shares genetic predisposition with immuno-metabolic traits and alcohol consumption. Psychol Med. 2022;52:726\u201336.","journal-title":"Psychol Med"},{"key":"2484_CR16","doi-asserted-by":"publisher","first-page":"174","DOI":"10.1016\/j.bbi.2020.04.002","volume":"88","author":"F Lamers","year":"2020","unstructured":"Lamers F, Milaneschi Y, Vinkers CH, Schoevers RA, Giltay EJ, Penninx BWJH. Depression profilers and immuno-metabolic dysregulation: Longitudinal results from the NESDA study. Brain Behav Immun. 2020;88:174\u201383.","journal-title":"Brain Behav Immun"},{"key":"2484_CR17","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1016\/j.bbi.2021.07.007","volume":"97","author":"Y Milaneschi","year":"2021","unstructured":"Milaneschi Y, Allers KA, Beekman ATF, Giltay EJ, Keller S, Schoevers RA, et al. The association between plasma tryptophan catabolites and depression: The role of symptom profiles and inflammation. Brain Behav Immun. 2021;97:167\u201375.","journal-title":"Brain Behav Immun"},{"key":"2484_CR18","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1016\/j.bbi.2022.02.003","volume":"102","author":"CR Brydges","year":"2022","unstructured":"Brydges CR, Bhattacharyya S, Dehkordi SM, Milaneschi Y, Penninx B, Jansen R, et al. Metabolomic and inflammatory signatures of symptom dimensions in major depression. Brain Behav Immun. 2022;102:42\u201352.","journal-title":"Brain Behav Immun"},{"key":"2484_CR19","doi-asserted-by":"publisher","first-page":"369","DOI":"10.1016\/j.biopsych.2020.01.014","volume":"88","author":"Y Milaneschi","year":"2020","unstructured":"Milaneschi Y, Lamers F, Berk M, Penninx BWJH. Depression heterogeneity and its biological underpinnings: toward immunometabolic depression. Biol Psychiatry. 2020;88:369\u201380.","journal-title":"Biol Psychiatry"},{"key":"2484_CR20","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1016\/j.jad.2021.03.026","volume":"287","author":"BWJH Penninx","year":"2021","unstructured":"Penninx BWJH, Eikelenboom M, Giltay EJ, van Hemert AM, Riese H, Schoevers RA, et al. Cohort profile of the longitudinal Netherlands Study of Depression and Anxiety (NESDA) on etiology, course and consequences of depressive and anxiety disorders. J Affect Disord. 2021;287:69\u201377.","journal-title":"J Affect Disord"},{"key":"2484_CR21","unstructured":"World Health Organization. Composite International Diagnostic Interview (CIDI) researcher\u2019s manual (Version 2.1). 1997. https:\/\/www.academia.edu\/467491\/Composite_International_Diagnostic_Interview_CIDI_2_1_."},{"key":"2484_CR22","doi-asserted-by":"publisher","first-page":"192","DOI":"10.1161\/CIRCGENETICS.114.000216","volume":"8","author":"P Soininen","year":"2015","unstructured":"Soininen P, Kangas AJ, W\u00fcrtz P, Suna T, Ala-Korpela M. Quantitative serum nuclear magnetic resonance metabolomics in cardiovascular epidemiology and genetics. Circ Cardiovasc Genet. 2015;8:192\u2013206.","journal-title":"Circ Cardiovasc Genet"},{"key":"2484_CR23","doi-asserted-by":"publisher","first-page":"178","DOI":"10.1111\/acps.13310","volume":"144","author":"H de Kluiver","year":"2021","unstructured":"de Kluiver H, Jansen R, Milaneschi Y, Bot M, Giltay EJ, Schoevers R, et al. Metabolomic profiles discriminating anxiety from depression. Acta Psychiatr Scand. 2021;144:178\u201393.","journal-title":"Acta Psychiatr Scand"},{"key":"2484_CR24","doi-asserted-by":"publisher","first-page":"477","DOI":"10.1017\/S0033291700035558","volume":"26","author":"AJ Rush","year":"1996","unstructured":"Rush AJ, Gullion CM, Basco MR, Jarrett RB, Trivedi MH. The Inventory of Depressive Symptomatology (IDS): psychometric properties. Psychol Med. 1996;26:477\u201386.","journal-title":"Psychol Med"},{"key":"2484_CR25","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1111\/j.1467-6494.1986.tb00391.x","volume":"54","author":"SR Briggs","year":"1986","unstructured":"Briggs SR, Cheek JM. The role of factor analysis in the development and evaluation of personality scales. J Pers. 1986;54:106\u201348.","journal-title":"J Pers"},{"key":"2484_CR26","doi-asserted-by":"publisher","first-page":"110","DOI":"10.1038\/s41591-019-0722-x","volume":"26","author":"J Liu","year":"2020","unstructured":"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\u20137.","journal-title":"Nat Med"},{"key":"2484_CR27","doi-asserted-by":"publisher","first-page":"573","DOI":"10.1016\/S0006-3223(02)01866-8","volume":"54","author":"AJ Rush","year":"2003","unstructured":"Rush AJ, Trivedi MH, Ibrahim HM, Carmody TJ, Arnow B, Klein DN, et al. The 16-Item Quick Inventory of Depressive Symptomatology (QIDS), clinician rating (QIDS-C), and self-report (QIDS-SR): a psychometric evaluation in patients with chronic major depression. Biol Psychiatry. 2003;54:573\u201383.","journal-title":"Biol Psychiatry"},{"key":"2484_CR28","doi-asserted-by":"publisher","first-page":"723","DOI":"10.1038\/nrendo.2014.171","volume":"10","author":"CJ Lynch","year":"2014","unstructured":"Lynch CJ, Adams SH. Branched-chain amino acids in metabolic signalling and insulin resistance. Nat Rev Endocrinol. 2014;10:723\u201336.","journal-title":"Nat Rev Endocrinol"},{"key":"2484_CR29","doi-asserted-by":"publisher","first-page":"648","DOI":"10.2337\/dc12-0895","volume":"36","author":"P W\u00fcrtz","year":"2013","unstructured":"W\u00fcrtz P, Soininen P, Kangas AJ, R\u00f6nnemaa T, Lehtim\u00e4ki T, K\u00e4h\u00f6nen M, et al. Branched-chain and aromatic amino acids are predictors of insulin resistance in young adults. Diabetes Care. 2013;36:648\u201355.","journal-title":"Diabetes Care"},{"key":"2484_CR30","doi-asserted-by":"publisher","first-page":"2307","DOI":"10.1093\/eurheartj\/ehs020","volume":"33","author":"P W\u00fcrtz","year":"2012","unstructured":"W\u00fcrtz P, Raiko JR, Magnussen CG, Soininen P, Kangas AJ, Tynkkynen T, et al. High-throughput quantification of circulating metabolites improves prediction of subclinical atherosclerosis. Eur Heart J. 2012;33:2307\u201316.","journal-title":"Eur Heart J"},{"key":"2484_CR31","doi-asserted-by":"publisher","first-page":"e024380","DOI":"10.1161\/JAHA.121.024380","volume":"11","author":"ST Chiesa","year":"2022","unstructured":"Chiesa ST, Charakida M, Georgiopoulos G, Roberts JD, Stafford SJ, Park C, et al. Glycoprotein Acetyls: A novel inflammatory biomarker of early cardiovascular risk in the Young. J Am Heart Assoc. 2022;11:e024380.","journal-title":"J Am Heart Assoc"},{"key":"2484_CR32","doi-asserted-by":"publisher","first-page":"905","DOI":"10.1016\/j.cmet.2021.03.025","volume":"33","author":"D Yu","year":"2021","unstructured":"Yu D, Richardson NE, Green CL, Spicer AB, Murphy ME, Flores V, et al. The adverse metabolic effects of branched-chain amino acids are mediated by isoleucine and valine. Cell Metab. 2021;33:905\u2013922.e6.","journal-title":"Cell Metab"},{"key":"2484_CR33","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-019-11311-9","volume":"10","author":"J Deelen","year":"2019","unstructured":"Deelen J, Kettunen J, Fischer K, van der Spek A, Trompet S, Kastenm\u00fcller G, et al. A metabolic profile of all-cause mortality risk identified in an observational study of 44,168 individuals. Nat Commun. 2019;10:3346.","journal-title":"Nat Commun"},{"key":"2484_CR34","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-023-36231-7","volume":"14","author":"H Julkunen","year":"2023","unstructured":"Julkunen H, Cicho\u0144ska A, Tiainen M, Koskela H, Nybo K, M\u00e4kel\u00e4 V, et al. Atlas of plasma NMR biomarkers for health and disease in 118,461 individuals from the UK Biobank. Nat Commun. 2023;14:604.","journal-title":"Nat Commun"},{"key":"2484_CR35","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1016\/j.cell.2015.03.008","volume":"161","author":"AA van der Klaauw","year":"2015","unstructured":"van der Klaauw AA, Farooqi IS. The hunger genes: pathways to obesity. Cell 2015;161:119\u201332.","journal-title":"Cell"},{"key":"2484_CR36","doi-asserted-by":"publisher","first-page":"197","DOI":"10.1016\/j.bbi.2022.12.005","volume":"108","author":"T Alshehri","year":"2023","unstructured":"Alshehri T, Mook-Kanamori DO, de Mutsert R, Penninx BW, Rosendaal FR, le Cessie S, et al. The association between adiposity and atypical energy-related symptoms of depression: a role for metabolic dysregulations. Brain Behav Immun. 2023;108:197\u2013203.","journal-title":"Brain Behav Immun"},{"key":"2484_CR37","doi-asserted-by":"publisher","first-page":"338","DOI":"10.1038\/nrendo.2016.222","volume":"13","author":"H Cui","year":"2017","unstructured":"Cui H, L\u00f3pez M, Rahmouni K. The cellular and molecular bases of leptin and ghrelin resistance in obesity. Nat Rev Endocrinol. 2017;13:338\u201351.","journal-title":"Nat Rev Endocrinol"},{"key":"2484_CR38","doi-asserted-by":"publisher","first-page":"1477","DOI":"10.1038\/s41380-019-0395-3","volume":"25","author":"GM Khandaker","year":"2020","unstructured":"Khandaker GM, Zuber V, Rees JMB, Carvalho L, Mason AM, Foley CN, et al. Shared mechanisms between coronary heart disease and depression: findings from a large UK general population-based cohort. Mol Psychiatry. 2020;25:1477\u201386.","journal-title":"Mol Psychiatry"},{"key":"2484_CR39","doi-asserted-by":"publisher","first-page":"161","DOI":"10.1001\/jamapsychiatry.2020.3436","volume":"78","author":"N Kappelmann","year":"2021","unstructured":"Kappelmann N, Arloth J, Georgakis MK, Czamara D, Rost N, Ligthart S, et al. Dissecting the association between inflammation, metabolic dysregulation, and specific depressive symptoms: a genetic correlation and 2-sample mendelian randomization study. JAMA Psychiatry. 2021;78:161\u201370.","journal-title":"JAMA Psychiatry"},{"key":"2484_CR40","doi-asserted-by":"publisher","DOI":"10.1038\/s41398-021-01236-7","volume":"11","author":"G Pistis","year":"2021","unstructured":"Pistis G, Milaneschi Y, Vandeleur CL, Lasserre AM, Penninx BWJH, Lamers F, et al. Obesity and atypical depression symptoms: findings from Mendelian randomization in two European cohorts. Transl Psychiatry. 2021;11:96.","journal-title":"Transl Psychiatry"},{"key":"2484_CR41","doi-asserted-by":"publisher","first-page":"254","DOI":"10.1016\/j.jad.2022.03.070","volume":"307","author":"Y Milaneschi","year":"2022","unstructured":"Milaneschi Y, Arnold M, Kastenm\u00fcller G, Dehkordi SM, Krishnan RR, Dunlop BW, et al. Genomics-based identification of a potential causal role for acylcarnitine metabolism in depression. J Affect Disord. 2022;307:254\u201363.","journal-title":"J Affect Disord"},{"key":"2484_CR42","doi-asserted-by":"publisher","first-page":"441","DOI":"10.1016\/j.ncl.2006.03.003","volume":"24","author":"R Dantzer","year":"2006","unstructured":"Dantzer R. Cytokine, sickness behavior, and depression. Neurol Clin. 2006;24:441\u201360.","journal-title":"Neurol Clin"},{"key":"2484_CR43","doi-asserted-by":"publisher","first-page":"397","DOI":"10.1007\/7854_2021_294","volume":"58","author":"M Bekhbat","year":"2022","unstructured":"Bekhbat M, Treadway MT, Felger JC. Inflammation as a Pathophysiologic pathway to Anhedonia: mechanisms and therapeutic implications. Curr Top Behav Neurosci. 2022;58:397\u2013419.","journal-title":"Curr Top Behav Neurosci"},{"key":"2484_CR44","doi-asserted-by":"publisher","first-page":"393","DOI":"10.1146\/annurev-clinpsy-050212-185606","volume":"10","author":"DA Pizzagalli","year":"2014","unstructured":"Pizzagalli DA. Depression, stress, and anhedonia: toward a synthesis and integrated model. Annu Rev Clin Psychol. 2014;10:393\u2013423.","journal-title":"Annu Rev Clin Psychol"},{"key":"2484_CR45","doi-asserted-by":"publisher","DOI":"10.1186\/s12916-022-02414-0","volume":"20","author":"SE Morris","year":"2022","unstructured":"Morris SE, Sanislow CA, Pacheco J, Vaidyanathan U, Gordon JA, Cuthbert BN. Revisiting the seven pillars of RDoC. BMC Med. 2022;20:220.","journal-title":"BMC Med"},{"key":"2484_CR46","doi-asserted-by":"crossref","unstructured":"Alshehri T, Mook-Kanamori DO, Willems van Dijk K, Dinga R, Penninx BWJH, Rosendaal FR, et al. Metabolomics dissection of depression heterogeneity and related cardiometabolic risk. Psychol Med. 2021;53:1\u201310.","DOI":"10.1017\/S0033291721001471"},{"key":"2484_CR47","doi-asserted-by":"publisher","first-page":"880","DOI":"10.1001\/jamapsychiatry.2014.411","volume":"71","author":"AM Lasserre","year":"2014","unstructured":"Lasserre AM, Glaus J, Vandeleur CL, Marques-Vidal P, Vaucher J, Bastardot F, et al. Depression with atypical features and increase in obesity, body mass index, waist circumference, and fat mass: a prospective, population-based study. JAMA Psychiatry. 2014;71:880\u20138.","journal-title":"JAMA Psychiatry"},{"key":"2484_CR48","doi-asserted-by":"publisher","first-page":"1026","DOI":"10.1038\/mp.2016.178","volume":"22","author":"AM Lasserre","year":"2017","unstructured":"Lasserre AM, Strippoli M-PF, Glaus J, Gholam-Rezaee M, Vandeleur CL, Castelao E, et al. Prospective associations of depression subtypes with cardio-metabolic risk factors in the general population. Mol Psychiatry. 2017;22:1026\u201334.","journal-title":"Mol Psychiatry"},{"key":"2484_CR49","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1002\/da.22666","volume":"35","author":"SM Case","year":"2018","unstructured":"Case SM, Sawhney M, Stewart JC. Atypical depression and double depression predict new-onset cardiovascular disease in U.S. adults. Depress Anxiety. 2018;35:10\u201317.","journal-title":"Depress Anxiety"},{"key":"2484_CR50","doi-asserted-by":"publisher","unstructured":"Miller AH, Raison CL. Burning down the house: reinventing drug discovery in psychiatry for the development of targeted therapies. Mol Psychiatry. 2022. https:\/\/doi.org\/10.1038\/s41380-022-01887-y.","DOI":"10.1038\/s41380-022-01887-y"},{"key":"2484_CR51","doi-asserted-by":"publisher","first-page":"e040119","DOI":"10.1136\/bmjopen-2020-040119","volume":"10","author":"C Otte","year":"2020","unstructured":"Otte C, Chae WR, Nowacki J, Kaczmarczyk M, Piber D, Roepke S, et al. Simvastatin add-on to escitalopram in patients with comorbid obesity and major depression (SIMCODE): study protocol of a multicentre, randomised, double-blind, placebo-controlled trial. BMJ Open. 2020;10:e040119.","journal-title":"BMJ Open"},{"key":"2484_CR52","doi-asserted-by":"publisher","first-page":"e025333","DOI":"10.1136\/bmjopen-2018-025333","volume":"8","author":"GM Khandaker","year":"2018","unstructured":"Khandaker GM, Oltean BP, Kaser M, Dibben CRM, Ramana R, Jadon DR, et al. Protocol for the insight study: a randomised controlled trial of single-dose tocilizumab in patients with depression and low-grade inflammation. BMJ Open. 2018;8:e025333.","journal-title":"BMJ Open"},{"key":"2484_CR53","doi-asserted-by":"publisher","first-page":"100585","DOI":"10.1016\/j.bbih.2022.100585","volume":"27","author":"JC Zwiep","year":"2023","unstructured":"Zwiep JC, Bet PM, Rhebergen D, Nurmohamed MT, Vinkers CH, Penninx BWJH, et al. Efficacy of celecoxib add-on treatment for immuno-metabolic depression: Protocol of the INFLAMED double-blind placebo-controlled randomized controlled trial. Brain Behav Immun Health. 2023;27:100585.","journal-title":"Brain Behav Immun Health"}],"container-title":["Translational Psychiatry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41398-023-02484-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41398-023-02484-5","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41398-023-02484-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,10]],"date-time":"2023-06-10T02:01:55Z","timestamp":1686362515000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41398-023-02484-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,10]]},"references-count":53,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2023,12]]}},"alternative-id":["2484"],"URL":"https:\/\/doi.org\/10.1038\/s41398-023-02484-5","relation":{"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-2544536\/v1","asserted-by":"object"}]},"ISSN":["2158-3188"],"issn-type":[{"value":"2158-3188","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,6,10]]},"assertion":[{"value":"7 February 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 May 2023","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 May 2023","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 June 2023","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"BWJHP has received research funding (unrelated to the work reported here) from Jansen Research and Boehringer Ingelheim and declare no competing interests. HdK, RJ, EJG, RS, and YM declare no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"198"}}