Article

Identifying illness parameters in fatiguing syndrome using classical projection methods

University of Alberta, Institute for Biomolecular Design, Edmonton, Alberta, T6G 2H7, Canada.
Pharmacogenomics (Impact Factor: 3.43). 05/2006; 7(3):407-19. DOI: 10.2217/14622416.7.3.407
Source: PubMed

ABSTRACT To examine the potential of multivariate projection methods in identifying common patterns of change in clinical and gene expression data that capture the illness state of subjects with unexplained fatigue and nonfatigued control participants.
Data for 111 female subjects was examined. A total of 59 indicators, including multidimensional fatigue inventory (MFI), medical outcome Short Form 36 (SF-36), Centers for Disease Control and Prevention (CDC) symptom inventory and cognitive response described illness. Partial least squares (PLS) was used to construct two feature spaces: one describing the symptom space from gene expression in peripheral blood mononuclear cells (PBMC) and one based on 117 clinical variables. Multiplicative scatter correction followed by quantile normalization was applied for trend removal and range adjustment of microarray data. Microarray quality was assessed using mean Pearson correlation between samples. Benjamini-Hochberg multiple testing criteria served to identify significantly expressed probes.
A single common trend in 59 symptom constructs isolates of nonfatigued subjects from the overall group. This segregation is supported by two co-regulation patterns representing 10% of the overall microarray variation. Of the 39 principal contributors, the 17 probes annotated related to basic cellular processes involved in cell signaling, ion transport and immune system function. The single most influential gene was sestrin 1 (SESN1), supporting recent evidence of oxidative stress involvement in chronic fatigue syndrome (CFS). Dominant variables in the clinical feature space described heart rate variability (HRV) during sleep. Potassium and free thyroxine (T4) also figure prominently.
Combining multiple symptom, gene or clinical variables into composite features provides better discrimination of the illness state than even the most influential variable used alone. Although the exact mechanism is unclear, results suggest a common link between oxidative stress, immune system dysfunction and potassium imbalance in CFS patients leading to impaired sympatho-vagal balance strongly reflected in abnormal HRV.

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    • "Immunological aberrations (inflammation, immune activation, immunosuppression and immune dysfunction); Klimas et al., 1990; Fletcher et al., 2009; Lorusso et al., 2009; Meeus et al., 2009; Brenu et al., 2011; Maes et al., 2012b consistent with processes observed during (latent) infection; Lloyd et al., 1993; Kerr et al., 2008a; Broderick et al., 2010 Intestinal dysbiosis, inflammation and hyperpermeability, Maes et al., 2007a; Sheedy et al., 2009; Lakhan and Kirchgessner, 2010; De Meirleir et al., 2013; Frémont et al., 2013 associated with systemic immune system abnormalities; Maes et al., 2012c; Groeger et al., 2013 (reactivating and/or persistent) infections; Hilgers and Frank, 1996; Chia and Chia, 2003; Nicolson et al., 2003; Chia et al., 2010; Chapenko et al., 2012 Elevated oxidative and nitrosative stress; Zhang et al., 1995; Kennedy et al., 2010; Maes and Twisk, 2010; Tomic et al., 2012 Mitochondrial dysfunction and damage to mitochondria; Behan et al., 1991; Pietrangelo et al., 2009; Booth et al., 2012; Meeus et al., 2013 Hypovolemia, diminished cardiac output and Streeten and Bell, 1998; Hurwitz et al., 2009; Miwa and Fujita, 2009; Hollingsworth et al., 2012 blood and oxygen supply deficits to muscles and brain, McCully and Natelson, 1999; Biswal et al., 2011; Ocon, 2013 especially in an upright position and during exercise; LaManca et al., 1999; Peckerman et al., 2003; Wyller et al., 2007; Patrick Neary et al., 2008 Reduced (maximum) oxygen uptake; Farquhar et al., 2002; Weinstein et al., 2009; Vermeulen et al., 2010; Jones et al., 2012 Neurological abnormalities; Lange et al., 2005; Chen et al., 2008; Puri et al., 2012; Natelson, 2013 Hypocortisolism/blunted hypothalamic-pituitary-adrenal (HPA) axis response; Demitrack et al., 1991; Lorusso et al., 2009; Papadopoulos and Cleare, 2011; Tak et al., 2011 Ion channel dysfunction (channelopathy); Watson et al., 1997; Whistler et al., 2005; Broderick et al., 2006; Cameron et al., 2007 A deviant physiological responses to exertion Thambirajah et al., 2008; Jones et al., 2012; Light et al., 2012; Smylie et al., 2013; Snell et al., 2013 (Kindlon, 2012), e.g., oxygen uptake at the anaerobic threshold and maximum oxygen uptake (VO2max), and biomarkers, e.g., (exercise-induced) cytokine levels. "
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    • "Over time researchers have shown various immune system abnormalities, like decrea sed natural killer cell activity (Saiki et al. 2008; Nijs & de Meirleir, 2005; Klimas et al. 1990), reduced perforin levels in cytotoxic T and NK cells (Maher et al. 2005), defects in T-and NK cell activation (Mihaylova et al. 2007; Maes et al. 2006), a significant decrease in the suppressor inducer subset of CD4+CD45RA+ cells (Klimas et al. 1990), a significant bias towards Th2-and Tc2-type immune responses (Skowera et al. 2004), and dysregula tion of the RNAse L pathway (Suhadolnik et al. 1997; Englebienne & de Meirleir, 2002; Tiev et al. 2003). A central role for immune system abnormalities , inflammation and immune dysfunction, in the pathophysiology of ME/CFS have also been implicated by several gene expression studies (Kaushik et al. 2005; Kerr et al. 2008; Broderick et al. 2006; Aspler et al. 2008, Gow et al. 2009). Inflammation, leading to per ma nently increased oxidative and nitrosative stress, on the one hand, and a chronically de pressed and dysfunctional immune system on the other hand, adequately explain many biological abnormalities found in ME/CFS, resulting into typical ME/CFS complaints. "
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