Identification of mitochondrial deficiency using principal component analysis

  • Gilles Durrieu
  • Thierry Letellier
  • Jaromír Antoch
  • Jean-Marc Deshouillers
  • Monique Malgat
  • Jean-Pierre Mazat
Part of the Developments in Molecular and Cellular Biochemistry book series (DMCB, volume 21)

Abstract

The mitochondrial pathologies are a heterogeneous group of metabolic disorders that are characterized by anomalies of oxidative phosphorylation, especially in the respiratory chain. The diagnosis of these pathologies involves many investigations among which biochemical study is at present the main tool. However, the analysis of the results obtained during such study remains complex and often does not make it possible to conclude clearly if a patient is affected or not by a biochemical and/or bioenergetic deficiency.

This arises from two main problems:
  1. 1.

    The determination of control values from the whole set of variable values (affected and unaffected people).

     
  2. 2.

    The small size of the population studied and the large number of variables collected which present a rather large variability. To cope with these problems, the principal component analysis method is applied to the results obtained during our biochemical studies. This analysis makes it possible for each respiratory chain complex, to distinguish clearly two subsets of the whole population (affected and unaffected people) as well as to detect the variables which are the most discriminative. (Mol Cell Biochem 174: 149–156, 1997)

     

Key words

mitochondria mitochondrial myopathies oxidative phosphorylation principal component analysis (PCA) biplot 

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Copyright information

© Springer Science+Business Media Dordrecht 1997

Authors and Affiliations

  • Gilles Durrieu
    • 1
  • Thierry Letellier
    • 3
  • Jaromír Antoch
    • 1
    • 2
  • Jean-Marc Deshouillers
    • 1
  • Monique Malgat
    • 3
  • Jean-Pierre Mazat
    • 3
  1. 1.Laboratoire de Mathématiques Stochastiques —Université Bordeaux IIBordeauxFrance
  2. 2.Department of StatisticsPrahaCzech Republic
  3. 3.Laboratoire G.E.S.B.I. —Université Bordeaux IIBordeauxFrance

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