Clinical and molecular predictors of survival among atypical parkinsonian syndromes in a North African tertiary referral center.

Introduction: Atypical Parkinsonian Syndromes(APS) are challenging neurodegenerative disorders due to their heterogeneous phenotypic overlaps.So far,there are no validated biomarkers that can accurately predict disease progression,and survival studies were highly different and contradictory.

Aim: To investigate clinical and molecular survival factors among Tunisian APS patients.

Methods: A retrospective study included Tunisian APS-patients.Using clinical and molecular parameters,survival was explored by Kaplan-Meier analysis.

Results: We included 409-APS patients divided into 166-DLB,112-PSP,81-MSA and 50-CBS.Survival rate was similar in synucleinopathies, while it differed in tauopathies,being shorter in PSP compared to CBS.Median survival in DLB was different according to gender(p = 0.0048),early parkinsonism and cognitive disorders. Among MSA, prognosis was worse in MSA-C-patients(p = 0.012) and those with stridor(p = 0.0049),oculomotor and neuropsychiatric disorders. For tauopathies, survival was shorter in PSP-RS(p = 0.027),cerebellar phenotype, those with tremor and swallowing problems at onset, early parkinsonism and memory impairment. For CBS,prognosis was worse in patients with tremor,swallowing and cognitive problems.Significant differences were noted in terms of survival across APS non-carriers of APOE-ε4(p < 0.001) as well APS patients carriers of MAPT-H1.PSP patients had lower survival rate according to MAPT haplotype carriage. Moreover, the number of copies had an influence as patients with H1/H2-MAPT profile had better prognosis than those with H1/H1.

Conclusion: This study determined survival rates in APS subgroups,which were comparable across synucleinopathies but shorter in PSP and longer in CBS.It also characterized demographic,phenotypic,and genetic profiles identifying more aggressive forms within APS subgroups.These findings address clinical gaps,aiding counseling for patients and families and guiding clinical management.Furthermore,they could facilitate patient stratification in clinical trials where mortality is an outcome measure.