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Background: Amyotrophic lateral sclerosis (ALS) is a diverse and progressive neurological disorder
that primarily causes the breakdown of motor neurons, leading to various physical symptoms. It typically
presents in three forms: spinal onset, which impairs limb and trunk movement; bulbar onset, which
disrupts speech and swallowing; and respiratory onset, which affects breathing. Over half of ALS
patients also experience cognitive or behavioral changes. While most ALS cases occur sporadically, a
small percentage are familial. Diagnosing ALS is a lengthy process, often taking a year due to initial
delays in seeking treatment, incorrect referrals, and the need to exclude similar neurological conditions.
Life expectancy with ALS varies greatly, with an average survival time of 2-5 years after symptoms
begin, though some live longer than a decade. Clinical chemistry plays a crucial role in diagnosing and
managing diseases by analyzing various substances in the blood or other fluids. Research into the
relationship between clinical chemistry markers and survival in neurodegenerative diseases has
increased in the recent years but remains limited for ALS. Previous studies have examined certain
biomarkers like lipids, creatinine, albumin, and inflammatory markers, but haven’t fully explored how
these markers interact with each other to affect prognosis.
Aim: To investigate the associations of commonly measured clinical chemistry markers with survival
outcomes (6-months, 1-year, and 3-years post diagnosis), as well as disease progression, of ALS.
Methods: In this cohort study of 270 patients with ALS, 29 clinical chemistry markers were measured
in blood taken around the time of diagnosis, to investigate their relationship with patient survival 6
months, 1 year, and 3 years post-diagnosis using univariate Cox proportional hazards model.
Exploratory factor analysis was used to generate summary variables to evaluate the combined effects of
these biomarkers in patient survival, with or without adjustment for known covariates. Finally, a joint
latent class model was applied to combine the revised amyotrophic lateral sclerosis functional rating
scale (ALSFRS-R) scores with survival data, categorizing distinct functional decline trajectories in ALS
patients. Multinomial logistic regression was used to analyze the relationship between these decline patterns and the identified factors as well as the levels of neurofilament light (NfL) in cerobrospial fluid
(CSF).
Results: Higher total cholesterol, LDL-C, and apolipoprotein B levels at diagnosis were associated with
lower mortality risk for the initial 6 months after an ALS diagnosis. A higher level of albumin was linked
to better survival at 1 and 3 years following an ALS diagnosis. Higher mean corpuscular volume (MCV),
CO2, and NfL levels were associated with increased mortality risk for all the time intervals whereas
higher level of mean corpuscular hemoglobin (MCH) and count of leukocytes were associated with an
increased mortality risk within 1- and 3-years post-diagnosis. Analyses on factors derived from
exploratory factor analysis further corroborated these findings; however, when adjusted for all relevant
covariates, the associations lost statistical significance. Using the joint latent class model, three different
classes of ALS patients were identified, demonstrating different functional decline trajectories and
survival times. NfL levels at diagnosis, but not the derived factors, showed a negative association with
the odds of belonging to classes with longer survival, irrespective of adjustment for covariates.
Conclusions: The present study showed the potential utility of clinical chemistry biomarkers measured
through routine laboratory assessments in predicting ALS survival and disease progression. However,
these biomarkers do not appear to provide added value to existing prognostic factors. Further studies
focusing on the longitudinal changes of these markers might shed more light on their clinical utility.
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Clinical chemistry markers in amyotrophic lateral sclerosis : their role in survival and disease trajectories
