Elsevier

Neurobiology of Aging

Volume 90, June 2020, Pages 119-124
Neurobiology of Aging

Regular article
Young-onset and late-onset Parkinson's disease exhibit a different profile of fluid biomarkers and clinical features

https://doi.org/10.1016/j.neurobiolaging.2020.02.012Get rights and content

Highlights

  • Age-of-onset may condition the clinical-biochemical profile of Parkinson's disease (PD).

  • A younger onset leads to lower CSF lactate, tau proteins, and nonmotor symptoms.

  • The clinical-biochemical profile differs between young-onset PD and late-onset PD.

  • The data drive further pathophysiological implications and clinical applications.

Abstract

Young-onset Parkinson's disease (YOPD) is a relevant condition whose neurobiology is questioned if different from those of typical late-onset Parkinson's disease (LOPD). Here, we explored whether the clinical-biochemical profile of Parkinson's disease (PD) could be affected by the age-of-onset (AO), as a possible result of a distinct neurodegenerative process. A panel of fluid biomarkers (CSF lactate, 42-amyloid-β peptide, total and 181-phosphorylated tau; serum uric acid) and the standard scores for motor and nonmotor signs were assessed in 76 idiopathic PD patients (genetic cases excluded; YOPD, AO ≤ 50, n = 44; LOPD, AO > 50, n = 32) and 75 sex/age-matched controls, adjusting the models for the main confounding factors. In PD, AO directly correlated to either CSF lactate and tau proteins or the nonmotor symptoms scale score. Specifically, a younger AO was associated with lower levels of biomarkers and minor burden of nonmotor symptoms. Our findings indicate that clinical-biochemical features of idiopathic PD may vary depending on the AO, accounting for different profiles in YOPD and LOPD whose recognition is fundamental for further pathophysiological implications and clinical applications.

Introduction

Idiopathic Parkinson's disease (PD) is a common disorder of elderly; however, much rarely it could occur in younger age (≤50), as “young-onset PD” (YOPD) (Mehanna and Jankovic, 2019, Willis et al., 2013). At present, the worldwide incidence of YOPD is significantly increasing (Willis et al., 2013, Ylikotila et al., 2015), although it almost remains a neglected condition. Indeed, the age-of-onset (AO)–based classification of PD is still controversial, and univocal cutoffs to label YOPD are still lacking (Mehanna and Jankovic, 2019, Willis et al., 2013). Studies focusing on YOPD often include tout court idiopathic cases and monogenic parkinsonisms, which in turn have peculiar pathogenesis and phenotypes (Mehanna and Jankovic, 2019, Morgante et al., 2016). Nevertheless, the few available evidence describes a different clinical-pathological course between YOPD and typical-onset PD (>50 years, here “late-onset PD,” LOPD), with a disproportionate burden of complications and quality of life (Liu et al., 2015, Mehanna et al., 2014, Mehanna and Jankovic, 2019, Pagano et al., 2016, Willis et al., 2013). YOPD thus deserves specific efforts to elucidate underlying pathogenic mechanisms, which is critical for the development of personalized treatments, urgently needed in such frail patients.

Neurodegenerative processes occurring at brain level may mirror in CSF and blood of patients; therefore, the assessment of fluid biomarkers represents a valuable tool to explore molecular mechanisms of the diseases in vivo (Alwardat et al., 2019, Bakshi et al., 2019, Liguori et al., 2015, Petrillo et al., 2020, Schirinzi et al., 2017, Schirinzi et al., 2018a). Here, we thus hypothesized that the clinical-biochemical profile of PD could by affected by the AO. We therefore analyzed a panel of fluid biomarkers (CSF Aβ42, t-tau, p-tau, lactate, and serum UA) and standard clinical scores in a cohort of PD patients and age/sex-matched controls to evaluate the effect of AO and identify distinct patterns in YOPD and LOPD, which may inform on the underlying pathophysiology. Of relevance, to avoid confusion due to the mechanistic bases of the inherited forms of PD, we specifically focused on idiopathic cases.

Section snippets

Methods

The study was performed at Tor Vergata University Hospital (Rome, Italy) and involved 151 subjects, 76 PD patients and 75 controls (CTL), enrolled from an initial cohort of 168 subjects.

PD was diagnosed by using the 2015 Movement Disorder Society's criteria. Most frequent inherited cases of PD were ruled out (SNCA, LRRK2, PRKN, PINK1, DJ-1, and GBA), to avoid potential confounding factor (details in Supplementary File1).

CTL group included age/sex-matched subjects, with non-neurodegenerative

Comparative analysis of the whole PD and CTL populations

Clinical-demographic and biochemical parameters of the whole PD population (YOPD+LOPD) were compared to the whole group of CTL (YCTL+LCTL) (Table 1). Age/sex distribution was homogeneous in both the groups. The one-way ANCOVA showed that levels of CSF lactate, serum UA, and CSF p-tau were similar (Supplementary File1); conversely, PD levels of CSF Aβ42 and t-tau were significantly lower than CTL (Aβ42: 2.87 ± 0.17 vs. 2.93 ± 0.11; F(1,82) = 5.17, p = 0.026; partial η2 = 0.059); (t-tau: 2.18 ±

Discussion

This study explored whether clinical and biochemical features were affected by the AO in idiopathic PD. Of interest, we noticed that CSF levels of lactate and tau proteins (t-tau and p-tau), and the burden of nonmotor symptoms of PD patients increased with AO, independently from the disease duration, accounting for different clinical-biochemical profiles in YOPD and LOPD. Here, patients have been assessed closely to their disease onset (2.5 ± 2.1 years, mean ± SD), and thus, the associations

Conclusions

Although preliminary, our results highlight significant clinical-biochemical differences between YOPD and LOPD, which have to be considered in the development of personalized treatments or in the design of clinical trials for PD patients.

CRediT authorship contribution statement

Tommaso Schirinzi: Conceptualization, Methodology, Formal analysis, Writing - original draft. Giulia Di Lazzaro: Conceptualization, Writing - original draft. Giulia Maria Sancesario: Investigation, Resources, Methodology. Susanna Summa: Formal analysis, Software. Simona Petrucci: Investigation, Resources, Methodology. Vito Luigi Colona: Data curation, Software. Sergio Bernardini: Investigation, Resources, Methodology. Mariangela Pierantozzi: Conceptualization, Writing - review & editing.

Acknowledgements

All authors have reviewed the contents of the manuscript being submitted, approve of its contents, and validate the accuracy of the data.

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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