Scholarlink

<p>Multi-organ biological aging clocks across different organ systems have been shown to predict human disease and mortality. Here, we extend this multi-organ framework to plasma metabolomics, developing five organ-specific metabolome-based biological age gaps (MetBAGs) using 107 plasma non-derivatized metabolites from 274,247 UK Biobank participants. Our age prediction models achieve a mean absolute error of approximately 6 years (0.25&lt;<i>r</i> &lt; 0.42). Crucially, including composite metabolites (e.g. sums or ratios of raw metabolites) results in poor generalizability to independent test data due to multicollinearity. Genome-wide associations identify 405 MetBAG-locus pairs (P &lt; 5 × 10<sup>−8</sup>/5). Using SBayesS, we estimate the SNP-based heritability (0.09&lt;<InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="41467_2025_59964_Article_IEq1.gif" Format="GIF" Height="21" Rendition="HTML" Resolution="72" Type="Linedraw" Width="40" /> </InlineMediaObject> <EquationSource Format="TEX">\({h}_{{SNP}}^{2}\)</EquationSource> <EquationSource Format="MATHML"><math> <msubsup> <mrow> <mi>h</mi> </mrow> <mrow> <mi>S</mi> <mi>N</mi> <mi>P</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msubsup> </math></EquationSource> </InlineEquation> &lt; 0.18), negative selection signatures (−0.93 &lt; <i>S</i> &lt; −0.76), and polygenicity (0.001&lt;<i>Pi</i> &lt; 0.003) for the 5 MetBAGs. Genetic correlation and Mendelian randomization analyses reveal potential causal links between the 5 MetBAGs and cardiometabolic conditions (e.g., metabolic disorders and hypertension). Integrating multi-organ and multi-omics features improves disease category and mortality predictions. The 5 MetBAGs extend existing biological aging clocks to study human aging and disease across multiple biological scales. All results are publicly available at <a href="https://labs-laboratory.com/medicine/">https://labs-laboratory.com/medicine/</a>.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Multi-organ metabolome biological age implicates cardiometabolic conditions and mortality risk

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年5月26日

查看全文
  • Andrew Zalesky,
  • Ye Ella Tian,
  • Luigi Ferrucci,
  • Keenan A. Walker,
  • Wenjia Bai,
  • Michael S. Rafii,
  • Paul Aisen,
  • Filippos Anagnostakis,
  • Sarah Ko,
  • Mehrshad Saadatinia,
  • Jingyue Wang,
  • Christos Davatzikos,
  • Junhao Wen

摘要

Multi-organ biological aging clocks across different organ systems have been shown to predict human disease and mortality. Here, we extend this multi-organ framework to plasma metabolomics, developing five organ-specific metabolome-based biological age gaps (MetBAGs) using 107 plasma non-derivatized metabolites from 274,247 UK Biobank participants. Our age prediction models achieve a mean absolute error of approximately 6 years (0.25<r < 0.42). Crucially, including composite metabolites (e.g. sums or ratios of raw metabolites) results in poor generalizability to independent test data due to multicollinearity. Genome-wide associations identify 405 MetBAG-locus pairs (P < 5 × 10−8/5). Using SBayesS, we estimate the SNP-based heritability (0.09< \({h}_{{SNP}}^{2}\) h S N P 2  < 0.18), negative selection signatures (−0.93 < S < −0.76), and polygenicity (0.001<Pi < 0.003) for the 5 MetBAGs. Genetic correlation and Mendelian randomization analyses reveal potential causal links between the 5 MetBAGs and cardiometabolic conditions (e.g., metabolic disorders and hypertension). Integrating multi-organ and multi-omics features improves disease category and mortality predictions. The 5 MetBAGs extend existing biological aging clocks to study human aging and disease across multiple biological scales. All results are publicly available at https://labs-laboratory.com/medicine/.