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. 2022 Dec 12;14:140. doi: 10.1186/s13073-022-01140-9

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© The Author(s) 2022

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/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 4 — Significant protein-phenotype associations identified using cis and trans genome-wide pQTLs as instrumental variables. Heatmaps were generated using the analyses on the WashU cohort only. A Fifty-eight proteins against 58 diseases in CSF. B Thirty-two proteins against 44 diseases in the plasma. C Nine proteins against 16 diseases in the brain. Colors were coded by 6 bins after cutting z-normalized beta MR estimate: below − 10 as dark blue, − 10 to − 5 as dodger blue, − 5 to 0 as cadet blue1, 0 to 5 as antique white1, 5 to 10 as gold, and above 10 as orange. Phenotype categories were listed on the left side as a bar plot (biological traits as red, blood traits as orange, cancers as purple, non-neurological diseases as green, neurological diseases as blue, personality traits as pink, and other risk factors as khaki)