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Further identification of underlying mutual and unique biological mechanisms may yield novel multi-disorder and disorder-specific therapeutic targets. The metabolome represents an important domain for target identification as metabolites play critical roles in modulating a diverse range of biological processes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We used Mendelian randomisation (MR) to test the causal effects of\u2009~\u20091000 plasma metabolites and\u2009~\u2009300 metabolite ratios on anxiety, bipolar disorder, depression, schizophrenia, amyotrophic lateral sclerosis, Alzheimer\u2019s disease, Parkinson\u2019s disease and multiple sclerosis. Follow-up analyses were conducted using statistical colocalisation, multivariable Bayesian model averaging MR (MR-BMA) and polygenic risk score analysis in the UK Biobank.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      MR analyses identified 85 causal effects involving 77 unique metabolites passing FDR correction and robust sensitivity analyses (IVW-MR OR range 0.73\u20131.48;\n                      <jats:italic>p<\/jats:italic>\n                      <jats:sub>FDR<\/jats:sub>\n                      \u2009&lt;\u20090.05). No evidence of reverse causality was identified. Multivariable MR-BMA analyses implicated sphingolipid metabolism in psychiatric disorder risk and carnitine derivatives in risk for amyotrophic lateral sclerosis and multiple sclerosis. Although polygenic risk scores for prioritised metabolites showed limited prediction in the UK Biobank, those nominally significant were directionally consistent with MR estimates. Downstream colocalisation in regions containing influential variants identified greater than suggestive evidence (PP.H\n                      <jats:sub>4<\/jats:sub>\n                      \u2009\u2265\u20090.6) for a shared causal variant for 29 metabolite\/psychiatric disorder trait-pairs on chromosome 11 at the\n                      <jats:italic>FADS<\/jats:italic>\n                      gene cluster. Most of these metabolites were lipids containing linoleic or arachidonic acid. Additional colocalisation was identified between the ratio of histidine-to-glutamine, glutamine, Alzheimer\u2019s disease and\n                      <jats:italic>SPRYD4<\/jats:italic>\n                      gene expression on chromosome 12.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Although no single metabolite had a causal effect on both\u00a0a psychiatric and a neurodegenerative disease, results suggest a broad effect of lipids across brain disorders, with a particular role for lipids containing linoleic or arachidonic acid in psychiatric disorders. The metabolites identified here may help inform future targeted interventions.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12916-025-04129-4","type":"journal-article","created":{"date-parts":[[2025,6,2]],"date-time":"2025-06-02T10:51:43Z","timestamp":1748861503000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Evaluating metabolome-wide causal effects on risk for psychiatric and neurodegenerative disorders"],"prefix":"10.1186","volume":"23","author":[{"given":"Lachlan","family":"Gilchrist","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julian","family":"Mutz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pirro","family":"Hysi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cristina","family":"Legido-Quigley","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sulev","family":"K\u00f5ks","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cathryn M.","family":"Lewis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Petroula","family":"Proitsi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,6,2]]},"reference":[{"issue":"3","key":"4129_CR1","doi-asserted-by":"publisher","first-page":"259","DOI":"10.1001\/jamapsychiatry.2018.3658","volume":"76","author":"O Plana-Ripoll","year":"2019","unstructured":"Plana-Ripoll O, Pedersen CB, Holtz Y, Benros ME, Dalsgaard S, de Jonge P, et al. 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