1 / 18

Comprehensive miRNA expression analysis in peripheral blood can diagnose liver disease

Comprehensive miRNA expression analysis in peripheral blood can diagnose liver disease        Yoshiki Murakami (M.D.), Hidenori Toyoda, Toshihito Tanahashi, Junko Tanaka,Takashi Kumada, Yusuke Yoshioka, Nobuyoshi Kosaka, Takahiro Ochiya, Y-h Taguchi.  PLoS ONE (2012)  7(10): e48366.

graiden-frederick
Download Presentation

Comprehensive miRNA expression analysis in peripheral blood can diagnose liver disease

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Comprehensive miRNA expression analysis in peripheral blood can diagnose liver disease        Yoshiki Murakami (M.D.), Hidenori Toyoda, Toshihito Tanahashi, Junko Tanaka,Takashi Kumada, Yusuke Yoshioka, Nobuyoshi Kosaka, Takahiro Ochiya, Y-h Taguchi  PLoS ONE (2012)  7(10): e48366

  2. Discrimination vs normal liver disease: ※Hepatocellular carcinoma (HCC, liver cancer) ※Chronic hepatitis C (CHC, liver inflammation type C ) ※Chronic hepatitis B (CHB, liver inflammation type B) ※Non-alcoholic fatty liver disease (NAFLD), included Nonalcoholic steatohepatitis (NASH →Cirrhosis → HCC )

  3. Task under the following Conditions: ※Small number of samples (patients). Less than 100, sometimes <10 in each class ※High reproducibility (for clinical application) ※Feature extraction (FE) with stability (hopefully < 10 miRNAs among more than a few hundreds miRNAs [in exosome in blood] ) Cf. Compressive Sensing

  4. What is miRNA? ・miRNA = microRNA ・non-coding RNA ・regulate (suppress) target gene expression via either degradation or translation interruption of target genes

  5. What is exosome?

  6. ※Why blood? →non-invasive, less stress to patients ※Why miRNA? →possibility to diagnose multiple diseases with miRNAs measurements only. (Cf. YT and YM, SIGBIO28 2012.3)

  7. Number of samples (patients) 887 miRNAs in exosome in blood (Agilent miRNA array) + clinical information (age, sex, BMI, inflammation, fibrosis etc...)

  8. Method: PCA-based Linear discriminant analysis with PCA-based feature extraction without labeling information (YT and YM, SIGBIO28, 2012. 3 at Tohoku U) because of stability requirement Very few researches of FE focusing stability (eg. Varshavsky R et al (2007) Bioinformatics) Unsupervised Feature Filtering (UFF) more computationally massive than ours

  9. Results for training data (Leave-one-out cross validation) Prediction Accuracy : 87.5% with 12 miRNAs up to 13 PCs (up to 16 probes for each miRNA)

  10. Embedding with PCA (2D) +: CHB, ◦: CHC, ×:NASH △: NL.

  11. NEED for increasing samples in silico MCMC miRNA 〜 age + gender + BMI + inflammation stage + fibrosis stage Distribution of coefficient Resampled clinical information miRNA × ＝

  12. The Advantage of MCMC based resampling y X X x a ↔ b : correlated

  13. Embedding with PCA (2D) +: CHB, ◦: CHC, ×:NASH △: NL.

  14. Results for training data (LOOCV) Resampled Prediction Accuracy : 95.25% with 12 miRNAs up to 5 PCs (up to 16 probes for each miRNA)

  15. Test sample comes …. Requirement : ※Use same miRNAs selected for Training data Ans.: Semi-supervised PCA-based LDA Training + Test → PCA PCA-based LDA with Training sample label → discriminate Test Set ※Validate in silico resmpling by independent data Ans.: validated by HCC data (not shown here)

  16. Prediction

  17. Conclusions ※From clinical point of views, miRNAs in exsome in blood can diagnose liver diseases ※PCA-based FE is useful one as a unsupervised FE ※MCMC based in silico resampling is useful (only for miRNA?) ※semi-supervised PCA-based LDA can work (only for miRNA?)

  18. BTW, It was press released.... “We will try to make it recognized as a highly advanced medical treatment in three years” (!)

More Related