Louise-Laure Mariani

Dr. Louise-Laure Mariani

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Research Focus & Metrics

Academic Career Length

16Years (2011-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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2 November 2023 in npj Parkinson's Disease
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Journal Article
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CMCaroline Moreau
Caroline Moreau
TRTiphaine Rouaud
Tiphaine Rouaud
DGDavid Grabli
David Grabli
IBIsabelle Benatru
Isabelle Benatru
PRPhilippe Remy
Philippe Remy
MFMargherita Fabbri
Margherita Fabbri
Parkinson’s disease (PD) is affecting about 1.2 million patients in Europe with a prevalence that is expected to have an exponential increment, in the next decades. This epidemiological evolution will be challenged by the low number of neurologists able to deliver expert care for PD. As PD is better recognized, there is an increasing demand from patients for rigorous control of their symptoms and for therapeutic education. In addition, the highly variable nature of symtoms between patients and the fluctuations within the same patient requires innovative tools to help doctors and patients monitor the disease in their usual living environment and adapt treatment in a more relevant way. Nowadays, there are various body-worn sensors (BWS) proposed to monitor parkinsonian clinical features, such as motor fluctuations, dyskinesia, tremor, bradykinesia, freezing of gait (FoG) or gait disturbances. BWS have been used as add-on tool for patients’ management or research purpose. Here, we propose a practical anthology, summarizing the characteristics of the most used BWS for PD patients in Europe, focusing on their role as tools to improve treatment management. Consideration regarding the use of technology to monitor non-motor features is also included. BWS obviously offer new opportunities for improving management strategy in PD but their precise scope of use in daily routine care should be clarified.

2 November 2020 in Movement Disorders
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Journal Article
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LCLydia Chougar
Lydia Chougar
JFJohann Faouzi
Johann Faouzi
NPNadya Pyatigorskaya
Nadya Pyatigorskaya
LYLydia Yahia‐Cherif
Lydia Yahia‐Cherif
RGRahul Gaurav
Rahul Gaurav
SLStéphane Lehéricy
Stéphane Lehéricy

10 January 2020 in Movement Disorders
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Journal Article
Closed access
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TWThomas Wirth
Thomas Wirth
LMLouise-Laure Mariani
Louise-Laure Mariani
GBGaber Bergant
Gaber Bergant
MBMichel Baulac
Michel Baulac
MHMarie‐Odile Habert
Marie‐Odile Habert
EREmmanuel Roze
Emmanuel Roze

10 November 2017 in Scientific Reports
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Journal Article
Open access
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LMLouise-Laure Mariani
Louise-Laure Mariani
SRS. Rivaud-Péchoux
S. Rivaud-Péchoux
PCP. Charles
P. Charles
CEC. Ewenczyk
C. Ewenczyk
AMA. Meneret
A. Meneret
MAM. Anheim
M. Anheim
Whether the recessive ataxias, Ataxia with oculomotor apraxia type 1 (AOA1) and 2 (AOA2) and Ataxia telangiectasia (AT), can be distinguished by video-oculography and alpha-fetoprotein level remains unknown. We compared 40 patients with AOA1, AOA2 and AT, consecutively referred between 2008 and 2015 with 17 healthy subjects. Video-oculography revealed constant impairments in patients such as cerebellar signs, altered fixation, impaired pursuit, hypometric saccades and abnormal antisaccades. Horizontal saccade latencies could be highly increased reflecting oculomotor apraxia in one third of patients. Specific distinctive alpha-fetoprotein thresholds were determined for AOA1 (7–15 µg/L), AOA2 (15–65 µg/L) and AT (>65 µg/L). Early age onset, severe walking disability, movement disorders, sensori-motor neuropathy and cerebellar atrophy were all shared. In conclusion, alpha-fetoprotein level seems to permit a distinction while video-oculography does not and therefore is not mandatory, even if an appropriate oculomotor examination remains crucial. Our findings are that AOA1, AOA2 and AT form a particular group characterized by ataxia with complex oculomotor disturbances and elevated AFP for which the final diagnosis is relying on genetic analysis. These findings could guide genetic analysis, assist reverse-phenotyping and provide background for the interpretation of the numerous variants of unknown significance provided by next-generation sequencing.

23 November 2021 in Brain
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Journal Article
Closed access
JCJean-Baptiste Brunet de Courssou
Jean-Baptiste Brunet de Courssou
ADAlexandra Durr
Alexandra Durr
DADavid Adams
David Adams
JCJean-Christophe Corvol
Jean-Christophe Corvol
LMLouise-Laure Mariani
Louise-Laure Mariani
Advances in targeted regulation of gene expression allowed new therapeutic approaches for monogenic neurological diseases. Molecular diagnosis has paved the way to personalized medicine targeting the pathogenic roots: DNA or its RNA transcript. These antisense therapies rely on modified nucleotides sequences (single-strand DNA or RNA, both belonging to the antisense oligonucleotides family, or double-strand interfering RNA) to act specifically on pathogenic target nucleic acids, thanks to complementary base pairing. Depending on the type of molecule, chemical modifications and target, base pairing will lead alternatively to splicing modifications of primary transcript RNA or transient messenger RNA degradation or non-translation. The key to success for neurodegenerative diseases also depends on the ability to reach target cells. The most advanced antisense therapies under development in neurological disorders are presented here, at the clinical stage of development, either at phase 3 or market authorization stage, such as in spinal amyotrophy, Duchenne muscular dystrophy, transthyretin-related hereditary amyloidosis, porphyria and amyotrophic lateral sclerosis; or in earlier clinical phase 1 B, for Huntington's disease, synucleinopathies and tauopathies. We also discuss antisense therapies at the preclinical stage, such as in some tauopathies, spinocerebellar ataxias or other rare neurological disorders. Each subtype of antisense therapy, antisense oligonucleotides or interfering RNA, has proved target engagement or even clinical efficacy in patients; undisputable recent advances for severe and previously untreatable neurological disorders. Antisense therapies show great promise, but many unknowns remain. Expanding the initial successes achieved in orphan or rare diseases to other disorders will be the next challenge, as shown by the recent failure in Huntington disease or due to long-term preclinical toxicity in multiple system atrophy and cystic fibrosis. This will be critical in the perspective of new planned applications to premanifest mutation carriers, or other non-genetic degenerative disorders such as multiple system atrophy or Parkinson disease.

6 May 2021 in Current Opinion in Neurology
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Journal Article
Closed access
JFJohann Faouzi
Johann Faouzi
JCJean-Christophe Corvol
Jean-Christophe Corvol
LMLouise-Laure Mariani
Louise-Laure Mariani
Purpose of review: To review recent findings and research directions on impulse control disorders and related behaviors (ICDRBs) in Parkinson's disease (PD). Recent findings: Longitudinal studies found that prevalence increases during PD progression, incident ICDRBs being around 10% per year in patients treated with dopaminergic therapies. Screening tools and severity scales already developed have been validated and are available in several countries and languages. The main clinical risk factors include young age, male gender, type, doses and duration of dopaminergic therapy, PD motor severity and dyskinesia, depression, anxiety, apathy, sleep disorders, and impulsivity traits. Genetic factors are suspected by a high estimated heritability, but individual genes and variants remain to be replicated. Management of ICDRBs is centered on dopamine agonist decrease, with the risk to develop withdrawal symptoms. Cognitive behavioral therapy and subthalamic nucleus deep brain stimulation also improve ICDRBs. In the perspective of precision medicine, new individual prediction models of these disorders have been proposed, but they need further independent replication. Summary: Regular monitoring of ICDRB during the course of PD is needed, particularly in the subject at high risk of developing these complications. Precision medicine will require the appropriate use of machine learning to be reached in the clinical setting.