Analysis of factors that modify susceptibility and rate of progression in amyotrophic lateral sclerosis (ALS)

Abstract

We conducted case-control and prospective longitudinal studies to examine risk factors and predictors of disease progression for ALS. Ninety-five subjects with ALS and 106 healthy control subjects were enrolled. All subjects completed a risk factor questionnaire at enrollment. The ALS subjects were prospectively followed for one year to define factors that influence the rate of disease progression, measured by rate of change in percent predicted forced vital capacity (%FVC) and the ALS functional rating scale (ALSFRS) score. The association of each potential risk factor with ALS was determined using univariate logistic regression. A random slope model was used to determine the association of each risk factor with disease progression. The demographic characteristics of ALS subjects and controls at enrollment did not differ. Significant risk factors for ALS included reported exposure to lead (p = 0.02) and pesticides (p = 0.03). Disease progression was faster in the ALS subjects having bulbar onset and a shorter time period between onset of symptoms and diagnosis. Pertinent variables not associated with either causation or progression of ALS included physical activity, cigarette smoking and a history of physical trauma or other clinical disorders.

RandomForest4Life: A Random Forest for predicting ALS disease progression

“…A large variability of the ALSFRS scores in the first three months led to larger predicted slopes. Bulbar onset was associated with steeper slopes compared to limb onset; this confirms findings reported on earlier (Qureshi et al 2006;Gordon et al 2010).…”

“…The patientspecific slope f (x i ) + γ i now has a "deterministic" part f (x i ) that depends on potentially prognostic factors or predictor variables x i and a random part γ i . The estimation of a linear slope function in the mixed-model framework is possible (Qureshi et al 2006). Technical difficulties arise when some predictor variables are missing, as is the case here, and when f should also capture nonlinear and interaction effects.…”

“…Two approaches have been used in the past, namely the search for prognostic factors for the overall survival time after diagnosis (Kimura et al 2006;Zoccolella et al 2008;Fujimura-Kiyono et al 2011, among many others) and the prognosis of a functional assessment of patients via the ALSFRS (ALS functional rating scale; Brooks et al 1996) and ALSFRS-R scores (Cedarbaum et al 1999). Among the published prognostic factors for ALS disease progression are bulbar rather than limb onset (Qureshi et al 2006;Gordon et al 2010), body mass index (Reich-Slotky et al 2013), early disease progression (Kimura et al 2006;Kollewe et al 2008), age at onset (Gordon et al 2010), uric acid level (Paganoni et al 2012), and amount of repeat expansion in gene C9ORF72 (Brettschneider et al 2012).…”

Clinical features and lifestyle of patients with amyotrophic lateral sclerosis in Campania: brief overview of an Italian database

“…Although toxic etiopathogenesis has not yet been clarified in ALS, one might hypothesize a possible synergistic effect between the toxicity of various substances, such as pesticides [3,5,6], physical activity [11] or hypoxia [12], and the neurodegenerative process.…”

“…Several hypotheses have been proposed in an effort to find a relationship with a number of exogenous risk factors, such as physical activity, traumatisms, and exposure to toxic substances, alone or in association with genetic predisposing features [3][4][5][6].…”