Scholarlink

Purpose <p>To evaluate the value of mtDNA copy number measurement&#xa0;in spent culture medium of blastocysts for predicting the chance of implantation following single blastocyst transfer (SBT).</p> Methods <p>Copy numbers of mtDNA and genomic DNA (gDNA) were determined using multiplex PCR and NGS and modeled to predict implantation following SBT using a generalized linear model (GLM), generalized additive model (GAM), and extreme gradient boosting (XGBoost). The predictive power of the models was demonstrated and compared with the area under the receiver operating characteristic curve (AUC-ROC).</p> Results <p>Neither the mtDNA copy number nor the mtDNA/gDNA provided meaningful discriminatory power for prediction in GLM and GAM models. However, higher gDNA quartiles were associated with a negative correlation with pregnancy (OR 0.92, 95% CI 0.85, 1) and an interaction with mtDNA, suggesting that gDNA should not be used to normalize mtDNA copy number. An XGBoost model, which considered both mtDNA and gDNA values, demonstrated an AUC of 0.837 (95% CI 0.800, 0.874).</p> Conclusions <p>The mtDNA copy number in spent medium alone may not be a reliable predictor of pregnancy, and dividing mtDNA by gDNA could distort the outcome. Alternatively, a model that makes full use of the interaction of the values may improve the prediction power.</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

The role of mitochondrial DNA copy number in spent culture medium in predicting outcomes of single blastocyst transfer

  • 期刊论文

  • 发表日期：

    2025年5月22日

查看全文
  • Jiali Cai,
  • Yurong Chen,
  • Liying Zhou,
  • Xiaolian Yang,
  • Luxiang Pan,
  • Lanlan Liu,
  • Zhenfang Liu,
  • Jianzhi Ren,
  • Xiaoming Jiang

摘要

Purpose

To evaluate the value of mtDNA copy number measurement in spent culture medium of blastocysts for predicting the chance of implantation following single blastocyst transfer (SBT).

Methods

Copy numbers of mtDNA and genomic DNA (gDNA) were determined using multiplex PCR and NGS and modeled to predict implantation following SBT using a generalized linear model (GLM), generalized additive model (GAM), and extreme gradient boosting (XGBoost). The predictive power of the models was demonstrated and compared with the area under the receiver operating characteristic curve (AUC-ROC).

Results

Neither the mtDNA copy number nor the mtDNA/gDNA provided meaningful discriminatory power for prediction in GLM and GAM models. However, higher gDNA quartiles were associated with a negative correlation with pregnancy (OR 0.92, 95% CI 0.85, 1) and an interaction with mtDNA, suggesting that gDNA should not be used to normalize mtDNA copy number. An XGBoost model, which considered both mtDNA and gDNA values, demonstrated an AUC of 0.837 (95% CI 0.800, 0.874).

Conclusions

The mtDNA copy number in spent medium alone may not be a reliable predictor of pregnancy, and dividing mtDNA by gDNA could distort the outcome. Alternatively, a model that makes full use of the interaction of the values may improve the prediction power.