Clinical and Metabolic Signature of UNC13A rs12608932 Variant in Amyotrophic Lateral Sclerosis

BACKGROUND AND OBJECTIVES: To characterize the clinical and cognitive behavioral phenotype and brain (18)F-2-fluoro-2-deoxy-d-glucose-PET ((18)F-FDG-PET) metabolism of patients with amyotrophic lateral sclerosis (ALS) carrying the rs12608932 variant of the UNC13A gene. METHODS: The study population included 1,409 patients with ALS without C9orf72, SOD1, TARDBP, and FUS mutations identified through a prospective epidemiologic ALS register. Control participants included 1,012 geographically matched, age-matched, and sex-matched participants. Clinical and cognitive differences between patients carrying the C/C rs12608932 genotype and those carrying the A/A + A/C genotype were assessed. A subset of patients underwent (18)F-FDG-PET. RESULTS: The C/C genotype was associated with an increased risk of ALS (odds ratio: 1.54, 95% confidence interval 1.18–2.01, p = 0.001). Patients with the C/C genotype were older, had more frequent bulbar onset, and manifested a higher rate of weight loss. In addition, they showed significantly reduced performance in the letter fluency test, fluency domain of Edinburgh Cognitive and Behavioural ALS Screen (ECAS) and story-based empathy task (reflecting social cognition). Patients with the C/C genotype had a shorter survival (median survival time, C/C 2.25 years, interquartile range [IQR] 1.33–3.92; A/A + C/C: 2.90 years, IQR 1.74–5.41; p = 0.0001). In Cox multivariable analysis, C/C genotype resulted to be an independent prognostic factor. Finally, patients with a C/C genotype had a specific pattern of hypometabolism on brain (18)F-FDG-PET extending to frontal and precentral areas of the right hemisphere. DISCUSSION: C/C rs12608932 genotype of UNC13A is associated with a specific motor and cognitive/behavioral phenotype, which reflects on (18)F-FDG-PET findings. Our observations highlight the importance of adding the rs12608932 variant in UNC13A to the ALS genetic panel to refine the individual prognostic prediction and reduce heterogeneity in clinical trials.