WO2016050973A1

WO2016050973A1 - Quantitative assessment of cerebellar impairments

Info

Publication number: WO2016050973A1
Application number: PCT/EP2015/072860
Authority: WO
Inventors: Alexandra Durr; Sophie TEZENAS DU MONTCEL
Original assignee: Icm (Institut Du Cerveau Et De La Moelle Épinière); Aphp (Assistance Publique - Hôpitaux De Paris); Université Pierre Et Marie Curie - Paris 6 (Upmc); Centre National De La Recherche Scientifique (Cnrs); INSERM (Institut National de la Santé et de la Recherche Médicale)
Priority date: 2014-10-03
Filing date: 2015-10-02
Publication date: 2016-04-07

Abstract

A nine-hole pegboard test and a click test on the dominant hand are combined to obtain a score for the diagnosis of cerebellar impairment.

Description

QUANTITATIVE ASSESSMENT OF CEREBELLAR IMPAIRMENTS

FIELD OF INVENTION

The present invention relates to the diagnostic and/or assessment of a cerebellar impairment in a subject in need thereof. The present invention also provides a monitoring method and device thereof to alleviate the cerebellar impairment in a subject in need thereof.

BACKGROUND OF INVENTION Cerebellum is constituted by a layer of cortex, with white matter underneath. The cortex is layered by two main types of neurons: Purkinje cells (PC) and the granule neurons. Finally, there are two main pathways through the cerebellar circuit, originating from mossy fibers and afferent/climbing fibers, both eventually terminating in the deep cerebellar nuclei (Figure 1). Cerebellar white matter dysfunction or afferent pathways/climbing fibers degeneration causes cerebellar impairments in multiple sclerosis (MS) while, cerebellar impairments involve mostly Purkinje cells in inherited cerebellar ataxias such as autosomal dominant ataxias (SCAs) (Figure 1).

Clinical manifestations of patients with multiple sclerosis are extremely heterogeneous ranging from motor, coordination, and sensory problems to cognitive and affective disorders. Cerebellar signs are present in 26% (Pittock SJ, et al. Mov Disord 2004; 19(12):1482-1485) to 58% (Alusi SH, et al. Brain J Neurol. 2001; 124(4): 720-730) of multiple sclerosis patients and is the most significant predictor of disability progression.

The identification of the presence of subtle cerebellar signs in MS and SCAs especially in diseases with multiple systems affected (cortico-spinal, deep sensory etc) and in the beginning of a disease such as MS or ataxias can be difficult. In addition, the slow progression of the disease requires accurate detection of change over time. In the light of new therapeutic developments, whose early use could be encouraged, it is crucial to dispose of reliable clinical predictors to identify the patients who are candidates for early therapies. Stratification of patients according to the presence of absence of cerebellar signs could be important in this sense but evaluation should be quantifiable.

One quantitative tool (the Composite Cerebellar Functional Severity Score (CCFS)) was developed to assess a cerebellar impairment in inherited cerebellar ataxias such as autosomal dominant cerebellar ataxia or autosomal dominant spastic paraplegia (Tezenas du Montcel S et al. Brain. 2008 May; 131(Pt 5): 1352-61). This score was thus only validated for cerebellar impairment involving Purkinje cells (PC).

Several scales with clinical elements have also been proposed to measure the severity and the progression of diseases presenting cerebellar impairments involving white matter involvement or afferent pathways degeneration. The multiple sclerosis functional composite (MSCF) score was developed to evaluate the major clinical manifestations of cerebellar impairment. However, such score is not reliable and specific enough to detect a cerebellar impairment in a subject. Other neurological rating scales have also been suggested but none are universally accepted (Table 4).

Moreover, other scales are already used to evaluate a cerebellar impairment in inherited ataxias but all have some drawbacks. The lengthy International Cooperative Ataxia Rating Scale (ICARS), a 100-point scale (Trouillas P, et al. J. Neurol. Sci. 1997; 145(2):205-211), has been shown to have a ceiling effect, and is, therefore, not usable when linear results are needed (Schmitz-Hiibsch et al. Mov Disord. 2006 May; 21(5): 699-704). A new Scale for the Assessment and Rating of Ataxia (SARA) has been validated in dominant ataxias as part of a European effort (EUROSCA) (Schmitz- Hiibsch T, et al. Neurology. 2006; 66(11): 1717-1720), however it is a semiquantitative scale which relies on subjective ratings by clinicians. For patients with autosomal dominant spastic paraplegia (ADSP), the Ashworth scale is generally used to assess spasticity in the lower limbs, but ignores possible upper limb involvement. Surprisingly, the inventors of the present application discovered that the CCFS could also detect other type cerebellar impairments, in particular the ones involving white matter and afferent pathways/climbing fibers degeneration.

In addition, while testing more subjects affected by ataxias, the inventors of the present application surprisingly discovered that their CCFS could not be validated for young subjects affected by cerebellar signs. Among all the scales developed to identify ataxias in a subject, none of these scales is validated for young subjects. Consequently, there is a need to develop other scales adapted to young subject and the inventors reassessed their CCSF tool to adapt for young subject. The method provided by the present application and requiring the combination of two functional tests can specifically diagnose and assess cerebellar impairments not involving PC but cerebellar afferent pathways. More surprisingly, the adapted CCFS also diagnoses and assesses cerebellar impairments in young subject whose cerebellar impairment could not be diagnosed so far. Finally, the invention also provides an electronic device for implementing the method of the invention, said device not only increases reliability, reproducibility of the performance, but also allows access to deeper data such as subject fatigability or acceleration (kinetics of the tasks).

SUMMARY

One object of the invention is a non-invasive method for diagnosing and/or assessing a cerebellar impairment not involving Purkinje cells in a subject in need thereof comprising:

a. performing a nine-hole pegboard test on the dominant hand of said subject and collecting the result,

b. performing a click test on the dominant hand of said subject and collecting the result,

c. combining the results generated by said subject to obtain a score, and d. comparing said score to a reference score. In one embodiment, said cerebellar impairment involves cerebellar white matter and/or afferent pathways degeneration.

In another embodiment, said subject to be diagnosed and/or assessed is affected by multiple sclerosis.

In another embodiment, said method further comprises a writing test between step b and c.

Another object of the invention is a non-invasive method for diagnosing and/or assessing a cerebellar impairment in a young subject in need thereof comprising:

c. combining the results generated by said subject to obtain a score, and d. comparing said score to a reference score.

In one embodiment, said subject to be diagnosed and/or assessed is affected by Friedreich ataxia, autosomal dominant cerebellar ataxia or recessive cerebellar ataxia.

In another embodiment, said method further comprises a writing test between b and c.

A non-invasive method for monitoring the progression of a cerebellar impairment in a subject in need thereof comprising:

a. performing the method of the invention at different times,

b. comparing the scores obtained at said different times to monitor the progression of the cerebellar impairment.

In one embodiment, the results obtained in the monitoring allow the adaptation of the treatment of the subject.

Another object of the invention is an electronic device for diagnosing and/or assessing and/or monitoring a cerebellar impairment in a subject in need thereof, wherein the electronic device comprises: - a board comprising at least two functional tests among a nine-hole pegboard test,

- a click test,

- a touch screen, and

- a software.

In one embodiment, said touch screen is used for implementing the writing test.

In another embodiment, said software records and analyzes the results collected after the performance of the functional tests.

In another embodiment, said board further comprises a webcam to analyze said subject's movements.

In another embodiment, said software further comprises training games to treat a cerebellar impairment in a subject in need thereof.

Another object of the invention is the use of the electronic device of the invention for monitoring the progression of a cerebellar impairment in a subject in need thereof before, during or after a treatment of a cerebellar impairment in a subject in need thereof.

DEFINITIONS

In the present invention, the following terms have the following meanings: - "Affected" refers to the affliction of a subject having and/or developing and/or at risk to develop a cerebellar impairment.

"Cerebellar impairments" have numerous causes, including congenital malformations, hereditary ataxias, and acquired conditions. The causes are due to different dysfunction occurring in different region or affecting different type of cells or pathways within the cerebellum. In one embodiment, these impairments can involve the dysfunction and/or degeneration of Purkinje cells. In another embodiment, these impairments can involve the cerebellar white matter and/or afferent pathways/climbing fibers degeneration. In another embodiment, these impairments can involve the dysfunction and/or degeneration of Purkinje cells and the cerebellar white matter and/or afferent pathways degeneration.

"Cohort study" refers to a group of subject already diagnosed with a cerebellar impairment.

"Collecting results" refers to the time needed for the subject to complete each of the tests. These results can comprise the measurement as disclosed in Figure 3: acceleration, fatigue, and speed irregularity which are well-known in the state of the art. Consequently, the skilled artisan can easily collect these results.

"Dominant hand" refers to the tendency to use preferentially one of the two hands for the majority of fine motor tasks and in daily prehensility. For instance, the hand used for writing or catching a ball.

"Formula" refers to any mathematical equation, algorithmic, analytical or programmed process, or statistical technique that takes on one or more continuous or categorical inputs (herein called "parameters") and calculates an output value, sometimes referred to as an "index" or "index value".

"Non-invasive" means that no tissue is taken from the body of an individual.

"Score" refers to a combination of functional tests (or variables) aimed at predicting a cerebellar impairment and/or sign in a subject in need thereof.

"About" preceding a figure and/or a score means plus or less 10% of the value of said figure and/or score.

DETAILED DESCRIPTION

This invention relates to a non-invasive method for diagnosing and/or assessing a cerebellar impairment not involving Purkinje cells in a subject in need thereof and comprising:

a. performing a nine-hole pegboard test on the dominant hand of said subject and collecting the result, b. performing a click test on the dominant hand of said subject and collecting the result,

This invention also relates to a non-invasive method for diagnosing and/or assessing a cerebellar impairment not involving Purkinje cells in a subject in need thereof and comprising:

b. performing a click test; on the dominant hand of said subject and collecting the result,

c. combining the results generated by said subject,

d. calculating a score according to formula I:

CCFS = loglO (7 + (Z peg)/10 + 4 x (Z click)/10); wherein Z peg = pegboard time - (0.002 x age² - 0.16 x age + 13.4) and Z click = click time - (0.05 x age +8), and

e. comparing said score to a reference score.

The term "reference score" as used herein refers in one embodiment to the score obtained from the performance of the nine -hole pegboard test, the click test and in a another embodiment to the score obtained from the performance of the nine-hole pegboard test, the click test and the writing test in a subject.

In one embodiment, the subject tested to obtain the reference score is healthy.

In one embodiment, the subject tested to obtain the reference score is affected with a cerebellar impairment.

In one embodiment, the subject tested to obtain the reference score is affected with a cerebellar impairment not involving Purkinje cells.

In one embodiment, when the score obtained from the tested subject is superior to the reference score obtained from a healthy subject, this score is indicative of a cerebellar impairment in the tested subject. In another embodiment, when the score obtained from the tested subject is equivalent or superior to a reference score obtained from a subject diagnosed with a cerebellar impairment, this score is indicative of a cerebellar impairment in the tested subject.

In another embodiment, when the score obtained from the tested subject is equivalent or superior to a reference score obtained from a subject diagnosed with a cerebellar impairment not involving Purkinje cells, this score is indicative of a cerebellar impairment not involving Purkinje cells in the tested subject.

In another embodiment, the reference score is issued from a cohort study.

In one embodiment, a score over 0.85, 0.86, 0.87, 0.88, 0.89, 0.90, 0.91, 0.92, 0.93, 0.94, 0.95, 0.96, 1 is indicative of a cerebellar impairment.

In one embodiment, a score between 0.80 and 0.84 is indicative of a healthy condition. In another embodiment, the score below 0.96 is indicative of a healthy condition.

In one embodiment, a score over to 0.955 is indicative of a specificity of 95% for a cerebellar impairment. In another embodiment, a score inferior to 0.876 is indicative of a sensitivity of 95% for a non-cerebellar impairment.

In one embodiment, a score over 1.58, 1.6, 1.7, 1.8 is indicative of a specificity of 95% for a cerebellar impairment due to a Friedreich's ataxia.

Examples of cerebellar impairments not involving Purkinje cells include but are not limited to: non-hereditary cerebellar impairment or acquired ataxias and/or Friedreich's ataxia.

Cerebellar impairments are characterized by core symptoms specific of ataxic syndromes: incoordination of balance, gait, decomposition of movement (inability to correctly sequence fine, coordinated acts), dysdiadochokinesia (inability to perform rapid alternating movements), dysmetria (inability to control range of movement), hypotonia (decreased muscle tone), nystagmus (involuntary, rapid oscillation of the eyeballs in a horizontal, vertical, or rotary direction), tremor (rhythmic, alternating, oscillatory movement of a limb as it approaches a target (intention tremor) or of proximal musculature when fixed posture or weight bearing is attempted (postural tremor), and cerebellar dysarthria (inability to articulate words correctly, with slurring and inappropriate phrasing). In one embodiment, the method of the invention is assessing specifically decomposition of movement, dysdiadochokinesia, dysmetria, and tremor. All the symptoms listed are linked to each other. In another embodiment, the method of the invention is assessing indirectly hypotonia and cerebellar dysarthria. In another embodiment of the invention, said subject is affected by a cerebellar impairment involving cerebellar white matter and/or afferent pathways degeneration. Examples of cerebellar impairments involving cerebellar white matter and/or afferent pathways degeneration include but are not limited to: non-hereditary cerebellar impairment or acquired ataxias. Examples of non-hereditary cerebellar impairment or acquired ataxias include but are not limited to: multiple sclerosis, systemic disorders, multiple system atrophy, cerebellar strokes, repeated traumatic brain injury, or toxin exposure. Systemic disorders include but are not limited to: celiac disease, heat stroke, hypothyroidism, and vitamin E deficiency. Toxins include carbon monoxide, heavy metals, lithium, phenytoin, and certain solvents. Toxic levels of certain drugs (eg, anticonvulsants) can cause cerebellar dysfunction and ataxia.

In one embodiment, Friedreich's ataxia is not involving Purkinje cells.

In one embodiment, said subject to be diagnosed and/or assessed is affected by multiple sclerosis (MS). In another embodiment, said method is for diagnosing and/or assessing a cerebellar impairment in a subject affected by MS. In another embodiment, said method is for discriminating between subject affected by MS having no cerebellar impairment and subject affected by MS having a cerebellar impairment.

The nine-hole pegboard test as described herein consists in performing the following task: a subject, who is seated, holds nine dowels (9 mm in diameter and 32-mm long) in one hand and places them randomly, one by one, with the other hand in a board with nine holes. Timing begins when the first peg is placed in a hole and ends when the last peg is placed. The examiner holds the board steady on the table during the test. The trial is performed with the dominant hand. If the patient drops a peg the examiner stops the timer and the patient starts the test again once from the beginning. In one embodiment, the nine dowels must have the same diameter and length. In another embodiment, the nine holes must have the same diameter and depth. In another embodiment, the nine-hole pegboard test does not require a cognitive effect. The nine- hole pegboard test described in Lum PS et al. (J Rehabil Res Dev. 2004 May;41(3A):249-58) comprises different sizes of dowels and holes which requires a strategy of cognitive effort which comes across the purpose of the present application. The strategy of the present application is the specific assessment of a cerebellar impairment with a test not requiring a cognitive effect.

The click test as described herein measures specifically finger-pointing coordination. It uses a simple homemade device composed of two mechanical counters fixed on a wooden board 39 cm apart. This distance of 39 cm is based on kinematic and kinetic analysis showing that it is the optimal inter-counter distance to assess the metrics of goal-directed visually guided multi-joint movements in upper limbs. The subject is seated facing the examiner across a table on which the counters are placed (numbers facing the examiner). The subject uses his index finger to press the buttons on the counters alternately 10 times. Timing begins when the first button is pressed and stops when the second counter reaches 10. The trial is performed with the dominant hand.

In one embodiment, the click test does not aim at measuring the number of buttons pressed during the task by the subject such as the one described in the finger tapping test of Lum PS et al. The click test aims at evaluating dysmetria and recording takes into account the time taken by the subject to press 10 times the buttons, contrary to finger tapping test where recording takes into account the number of buttons pressed during the task.

The writing test as described herein consists in writing a standard sentence (for example, in French, this sentence is: "maitre corbeau sur un arbre perche"), with his dominant hand, as fast as possible, but legibly. The subject is timed from when he begins to write until he completes the sentence. One object of the present invention is also a non-invasive method for diagnosing and/or assessing a cerebellar impairment involving cerebellar white matter and/or afferent pathways degeneration in a subject in need thereof and comprising:

This invention also relates to a non-invasive method for diagnosing and/or assessing a cerebellar impairment involving cerebellar white matter and/or afferent pathways degeneration in a subject in need thereof and comprising:

c. combining said results generated by said subject,

d. calculating a score according to formula I:

e. comparing said score to a reference score.

In one embodiment, the subject tested to obtain the reference score is healthy.

In one embodiment, the subject tested to obtain the reference score is affected with a cerebellar impairment involving cerebellar white matter and/or afferent pathways degeneration. In one embodiment, when the score obtained from the tested subject is superior to the reference score obtained from a healthy subject, this score is indicative of a cerebellar impairment in the tested subject.

In another embodiment, when the score obtained from the tested subject is equivalent or superior to a reference score obtained from a subject diagnosed with a cerebellar impairment involving cerebellar white matter and/or afferent pathways degeneration, this score is indicative of a cerebellar impairment involving cerebellar white matter and/or afferent pathways degeneration in the tested subject.

In one embodiment, a score over 0.85, 0.86, 0.87, 0.88, 0.89, 0.90, 0.91, 0.92, 0.93, 0.94, 0.95, 1 is indicative of a cerebellar impairment.

Another object of the present invention is a non-invasive method for diagnosing and/or assessing a cerebellar impairment not involving Purkinje cells in a subject in need thereof and comprising:

c. performing a writing test on the dominant hand of said subject and collecting the result,

d. combining the results generated by said subject to obtain a score, and e. comparing said score to a reference score.

b. performing a click test; on the dominant hand of said subject and collecting the result, performing a writing test on the dominant hand of said subject and collecting the result,

calculating a score according to formula II:

CCFS = loglO (7 + (Z peg)/10 + 4 x (Z click)/10 + (Z writing)/10); wherein Z peg = pegboard time - (0.002 x age² - 0.16 x age + 13.4); Z click = click time - (0.05 x age +8); and Z writing = writing time - (8.5 + 0.05 x age), and

comparing said score to a reference score.

Another object of the present invention is a non-invasive method for diagnosing and/or assessing a cerebellar impairment involving cerebellar white matter and/or afferent pathways degeneration in a subject in need thereof and comprising:

c. performing a writing test on the dominant hand of said subject and collecting the result, d. calculating a score according to formula II:

CCFS = loglO (7 + (Z peg)/10 + 4 x (Z click)/10) + (Z writing)/10); wherein Z peg = pegboard time - (0.002 x age² - 0.16 x age + 13.4); Z click = (click time - (0.05 x age +8); and Z writing = writing time - (8.5 + 0.05 x age), and

e. comparing said score to a reference score.

Another object of the present invention is invention is a non-invasive method for diagnosing and/or assessing a cerebellar impairment in a young subject in need thereof and comprising:

This invention also relates to a non-invasive method for diagnosing and/or assessing a cerebellar impairment in a young subject in need thereof and comprising:

c. calculating a score according to formula III:

CCFS = loglO (7 + (Z peg)/10 + 4 x (Z click)/10); wherein Z peg = (pegboard time - (-0.08 x age + 12.62) and Z click = (click time - (0.03 x age² - 1.14 x age + 18.89), and

d. comparing said score to a reference score. Another object of the present invention is invention is a non-invasive method for diagnosing and/or assessing a cerebellar impairment in a young subject in need thereof and comprising:

In one embodiment, the young subject tested to obtain the reference score is healthy.

In another embodiment, the reference score is obtained from a young subject affected with a cerebellar impairment.

In one embodiment, a score over 0.85, 0.86, 0.87, 0.88, 0.89, 0.90, 0.91, 0.92, 0.93, 0.94, 0.95, 0.96, 0.97, 0.98, 0.99, 1 is indicative of a cerebellar impairment.

In one embodiment, a score between 0.80 and 0.84 is indicative of a healthy condition.

In one embodiment of the invention, cerebellar impairment include: non-hereditary cerebellar impairment or acquired ataxias; hereditary cerebellar impairment and/or inherited ataxias.

Non-hereditary cerebellar impairment or acquired ataxias in a young subject include but are not limited to: primary brain tumors (medulloblastoma, cystic astrocytoma) may be the cause; the midline cerebellum is the most common site of such tumors. Rarely, in children, reversible diffuse cerebellar dysfunction follows viral infections, congenital malformation. Such malformations are almost always sporadic, often occurring as part of complex malformation syndromes (eg, Dandy- Walker malformation) that affect other parts of the central nervous system. Hereditary cerebellar impairment and/or inherited ataxias include but are not limited to: autosomal recessive and autosomal dominant ataxias.

Autosomal recessive ataxias include but are not limited to: Friedreich ataxia (the most prevalent), ataxias with ocular aparaxia (AOA 1 and 2), ataxia-telangiectasia, abetalipoproteinemia, ataxia with isolated vitamin E deficiency, and cerebrotendinous xanthomatosis, abetalipoproteinemia.

Autosomal dominant ataxias include but are not limited to: Spinocerebellar ataxias (SCAs), the polyglutamine disorders such as SCAs 1, 2, 3, 7, and 17, the channelopathies such as SCA 6 and episodic ataxia types 1 and 2, the gene expression disorders such as SCAs 8, 10, and 12, the remaining SCAs 4, 5, 11, 13-16, 18-22, and 25, (of unknown etiology); autosomal dominant spastic paraplegia (ADSP).

The present invention also relates to a non-invasive method for assessing the severity of a cerebellar impairment not involving Purkinje cells in a subject in need thereof comprising:

Another object of the invention is a non-invasive method for assessing the severity of a cerebellar impairment not involving Purkinje cells in a subject in need thereof comprising:

c. combining said results generated by said subject, d. calculating a score according to formula I:

e. comparing said score to a reference score.

d. calculating a score according to formula II:

CCFS = loglO (7 + (Z peg)/10 + 4 x (Z click)/10) + (Z writing)/10); wherein Z peg = pegboard time - (0.002 x age² - 0.16 x age + 13.4); Z click = click time - (0.05 x age +8); and Z writing = writing time - (8.5 + 0.05 x age), and e. comparing said score to a reference score.

Another object of the invention is a non-invasive method for assessing the severity of a cerebellar impairment involving cerebellar white matter and/or afferent pathways degeneration in a subject in need thereof comprising:

Another object of the invention is a method for assessing the severity of a cerebellar impairment involving cerebellar white matter and/or afferent pathways degeneration in a subject in need thereof comprising:

c. combining said results generated by said subject,

d. calculating a score according to formula I:

e. comparing said score to a reference score.

The present invention also relates to a method for assessing the severity of a cerebellar impairment involving cerebellar white matter and/or afferent pathways degeneration in a subject in need thereof comprising:

d. calculating a score according to formula II:

CCFS = loglO (7 + (Z peg)/10 + 4 x (Z click)/10) + (Z writing)/10); wherein Z peg = pegboard time - (0.002 x age² - 0.16 x age + 13.4); Z click = click time - (0.05 x age +8); and Z writing = writing time - (8.5 + 0.05 x age), and

e. comparing said score to a reference score.

The present invention also relates to a method for assessing the severity of a cerebellar impairment in a young subject comprising:

c. combining the results generated by said subject to obtain a score, and d. comparing said score to a reference score. Another object of the invention is a method for assessing the severity of a cerebellar impairment in a young subject comprising:

c. calculating a score according to formula III:

CCFS = loglO (7 + (Z peg)/10 + 4 x (Z click)/10); wherein Z peg = pegboard time - (-0.08 x age + 12.62) and Z click = click time - (0.03 x age² - 1.14 x age + 18.89), and

d. comparing said score to a reference score.

Another object of the invention is a method for identifying a cerebellar impairment in a subject at risk to develop a cerebellar impairment comprising the method described herein.

In one embodiment, said subject is diagnosed with a cerebellar impairment.

In another embodiment, said subject is not diagnosed with a cerebellar impairment. One object of the invention is also a method for monitoring a cerebellar impairment in a subject in need thereof and comprising:

a. performing the method of the invention at different times,

In one embodiment of the invention, the method as described here above is for assessing the progression of a cerebellar impairment in a subject in need thereof.

In another embodiment of the invention, the method as described here above is for monitoring the effectiveness of a treatment for a cerebellar impairment in a subject in need thereof. If a treatment has a desired effect, the score level will be lower compare to the one obtained before treatment.

Therefore, the skilled in the art will be able to adapt the treatment (doses, regimen or different molecule) to obtain a better (lower) score.

In another embodiment of the invention, the method as described here above is for selecting a treatment regimen for a subject affected by a cerebellar impairment.

In one embodiment, the subject is a male. In another embodiment, the subject is a female.

In one embodiment, the subject of the invention is an adult. In one embodiment, the term "adult" may refer to subjects of more than 20 years old. In another embodiment, the subject of the invention is a young subject. In one embodiment, the term "young subject" may refer to subjects from about 8 to about 20 years old.

In one embodiment of the invention, the subject to be treated is diagnosed with a cerebellar impairment. In another embodiment of the invention, the diagnosed subject is treated before the onset of symptoms of cerebellar impairment. In one embodiment, the subject is affected by an acquired cerebellar impairment.

In another embodiment, the subject is affected by an inherited cerebellar impairment.

In another embodiment, the subject is affected by a congenital malformation.

In one embodiment of the invention, the subject to be treated is at risk of developing a cerebellar impairment. In another embodiment of the invention, said risk corresponds to the presence of mutations associated with cerebellar impairment.

Examples of such mutations include but are not limited to: SCA 1-28, SPG4, SPG7, SPG30.

Another object of the present invention is an electronic device for diagnosing, and/or assessing and/or monitoring a cerebellar impairment in a subject comprising:

a. a board comprising at least two functional tests among a nine-hole pegboard test; a click test; a touch screen, and

b. a software.

In one embodiment, the software records and analyzes the results collected after the performance of each functional test.

In one embodiment, the touch screen is used for implementing the writing test.

In another embodiment, the board further comprises a webcam to analyze said subject's movements.

In another embodiment, the software further comprises training games, or video games to treat a cerebellar impairment in a subject in need thereof.

Another object of the invention is the use of the device for monitoring the progression of a cerebellar impairment in a subject in need thereof before, during or after a treatment of a cerebellar impairment in a subject in need thereof. Another object of the invention is an electronic device for diagnosing, and/or assessing and/or monitoring a cerebellar impairment in a subject comprising:

a. a touch screen comprising the following functional tests: a nine-hole pegboard test and a click test, and

b. a software.

In one embodiment, the electronic device optionally comprises a writing test.

The nine-hole pegboard test of the electronic device can be performed in two different ways.

In the two different ways, the touch screen represents nine digital holes with the same diameter placed in the middle of the screen.

One of the possible ways consists in having nine digital dowels (same diameter and same length) in the right or left corner of the touch screen. The subject will have to move the digital dowels with his dominant hand or a stylus pen in a precise way to reach and target the hole. The touch screen will detect when the stylus is placed correctly and will give a feedback to the subject so the subject can carry on the test or restart. Timing begins when the touch screen detects that the first digital dowel is placed correctly onto a hole and ends when the touch screen detects that the last digital dowel is placed correctly. The trial is performed with the dominant hand.

The other possible way consists in holding one stylus pen in the hand that is not the dominant hand. The subject will have to move back and forth the stylus pen from his non-dominant hand and place it nine times correctly onto the nine digital holes with his dominant hand. The touch screen will detect when the stylus is placed correctly and will give a feedback to the subject so the subject can carry on the test or restart. Timing begins when the touch screen has detected that the stylus pen was correctly placed onto the first hole. Timing ends when the touch screen has detected that the stylus pen was correctly placed onto the last hole. The trial is performed with the dominant hand.

In one embodiment, the touch screen has a minimum size of 21 inches or 39 cm. In another embodiment, the touch screen is extended by an expansion. The click test of the electronic device can be performed in two different ways. One way consists in having a touch screen of a minimum size to be able to perform the click test as described here above. Another way consists in adding an expansion connected to the touch screen which increases the size of the touch screen. One button is placed onto the touch screen and the other one on the expansion at a distance of 39 cm. The subject moves his index finger of his dominant hand between the two buttons and the counting is performed each time the subject reaches the button placed onto the screen (at least 10 returns are necessary for the counting).

The expansion is made using a 3D printing map. Said 3D printing map is provided together with the software or an application as a package.

In another embodiment, the electronic device comprises a communicator which transmits an identifier code for user identification or the score registered in the memory portion to an external control server managed by a health care unit.

BRIEF DESCRIPTION OF THE DRAWINGS

Figure 1 is a diagram of the stratified layers of the cerebellum.

Figure 2 is a plot showing the relation between the scores obtained from CCFS and the EDSS according to the presence of cerebellar impairments.

Figure 3 represents the relation between kinetic measures (starting speed, acceleration and speed irregularities) for the click (panels A, C and E) and the pegboard tests (panels B, D and F).

Figure 4 represents the relation between the CCFS (panel A) and the modified for children CCFS (panel B) and age.

Figure 5 represents the receiver-operating-characteristic (ROC) curve for discriminating cerebellar from non-cerebellar patients for the EDSS and the CCSF. EXAMPLES

The present invention is further illustrated by the following examples.

Example 1: Composite cerebellar functional severity score (CCFS) is specific of cerebellar dysfunction in multiple sclerosis. Methods

Patients

We investigated 110 consecutive patients with multiple sclerosis followed in our MS clinic between May and September 2013. The evaluation was part of the clinical follow- up of the patient. Clinical evaluation

The rating scales suggested to assess cerebellar impairments are listed below with their advantages and their limitations (Table 4).

*: SA: self-assessment; CA: clinical assessment; QS: quantified scale; QoL: quality of life; 9HPT: Nine hole peg test.

In the present study, for every participant, age, onset age, disease duration, and the type of evolution classified as remitting relapsing (RRMS, secondary progressive with or without relapses (SPMS) and primary progressive (PPMS) were obtained. Expanded Disability Status Scale (EDSS) (Kurtzke JF. Rating neurological impairment in multiple sclerosis: an expanded disability, status scale. Neurology 1983; 33: 1444-1452), and Kurtzke's Functional Systems (FSS) were obtained for all the patients. The CCFS score were recorded from 105 patients. Five patients were unable to perform CCFS because of major clinical severity. The EDSS score was classified as follow: Normal for the patient with an EDSS = 0, low for the patients with an EDSS from 1 to 3 and high for the patients with an EDSS of 4 or more.

The CCFS is a quantitative assessment initially developed and validated for SCA. It includes two functional tests for the dominant hand: the nine-hole pegboard test (time needed to place dowels in nine holes) and the click test (time needed to perform 10 finger-pointing cycles). An electronic device allows for the automatic acquisition of test times and the computation of a final score.

As performance changes with age, the times to perform the two tests are adjusted for age and combined to compute the CCFS score. Values over 0.96 were never observed in controls (Filipovic Pierucci A et al. Neurology. 2015 Mar 24;84(12): 1225-32). The CCFS score was recorded for the dominant hand for 102 patients (91 right handed and 11 left handed) and the non-dominant hand for 3 patients whose dominant upper limb was not functional (2 right handed and 1 left handed). Five patients were unable to perform the CCFS because of major clinical severity (EDSS > 8 or cerebellar FSS>4) and were excluded from the analysis.

The cerebellar FS captures tremor, ataxia and other coordination deficits, thus we also examined the correlation of the CCFS with the cerebellar FS. According to the severity, the cerebellar FS was classified as normal for patients with FSS equal 0, low for patients with FSS from 1 to 2, and high for patients with FSS from 3 to 4. Statistical analysis

To test for factors influencing the CCFS, a univariate regression analysis was performed followed by a multivariate analysis including the variable with p-values bellow 0.05 in the univariate analysis. In addition, interaction was tested between the variables significant after the multivariate analysis. The interactions between the included variables were tested and a backward selection was used. Data are expressed as mean + SD (minimum- maximum) or percentage (frequency). Parameters from the regression analysis are expressed as mean + SE. To discriminate patients with and without cerebellar impairment a logistic regression was used and areas under the receiver- operating-characteristic (ROC) curves were established for the EDSS and the CCFS scores. Threshold of the CCFS were defined for a 95% sensitivity, a 95% specificity and by maximizing the Youden's index (J). Data were expressed as mean + SD (minimum-maximum) or percentage (frequency). Statistical analyses were carried out using SAS software. All tests were two-sided and p-values lower than 0.05 were considered statistically significant.

Results

Description of the population

Our study population was representative of the general population of multiple sclerosis patients. The average age at disease onset was 33+ 10 (13-62), age at inclusion 45+11 (22-73) and disease duration 11+8 (1-35). The multiple sclerosis evolution was classified as remitting relapsing (RRMS) in 67%, secondary progressive with or without relapses (SPMS) in 23% and primary progressive (PPMS) in 10%. At the time of study, mean EDSS was 3.5+2.4 (range 0-8). Based on the FSS, 43% patients had cerebellar signs and the average cerebellar FSS was 0.9 +1.2 (12 patients with a FSS of 1, 18 of 2, 12 of 3 and 3 of 4) (0-4). In addition, 71% (n=75) of the patients had sensory dysfunctions (sensory FSS: 1.5 +1.4 (0-5)) and 60% (n=63) had pyramidal signs (pyramidal FS: 1.5 +1.7 (0-5)). While 19% (n=20) of the patients had none of these signs: simultaneous cerebellar, sensory and pyramidal signs, 35% (n=37) had simultaneous cerebellar, sensory and pyramidal signs.

Finally, 23% (n=24) of patients had two types of symptoms (cerebellar and sensory = 2, cerebellar and pyramidal = 3, pyramidal and sensory = 19) and 23% (n=24) had only one sign (cerebellar = 3, sensory = 17, pyramidal = 4). No patient had significant visual impairment (visual FS ranged from 0-2) but ophthalmologic examination was not systematically recorded.

Relation between the CCFS and clinical variables

Mean CCFS of all patients was 0.933+0.120 (range 0.781-1.376). Patients with cerebellar signs on cerebellar FSS had significantly higher CCFS than patients without cerebellar signs (1.021 + 0.129 [0.841; 1.376] versus 0.866 + 0.051 [0.781; 1.001], p<0.0001), and CCFS increased 0.079 + 0.006 (SE) for each additional FS point (p < 0.0001). Patients with pyramidal and sensory signs had significantly higher CCFS than patients with no such signs. However 63% of patients with pyramidal signs and 52% of patients with sensory signs also had cerebellar signs. After adjustment for the presence of cerebellar signs, there was no difference in CCFS according to the presence of pyramidal and sensory signs.

The CCFS was significantly lower (better) in RRMS patients than in SPMS patients (0.892 + 0.013 (SE) versus 1.018+0.022 (SE), p_c<0.0001) and in PPMS patients (0.892 + 0.013 (SE) versus 1.005+0.032 (SE) p_c=0.0043), PPMS and SPMS patients being not statistically different (p_c=0.93) (Table 1).

Table 1: Factors influencing the CCFS (Univariate and multivariate analysis)

Univariate Multivariate

Parameter p-value Parameter p-value

Age 0.5 10^"3 ± 1.1 10^"3 0.67

Disease duration 1.8 10^"3 ± 1.5 10^"3 0.25

Age at onset -0.4 10^"3 + 1.1 10^"3 0.70

EDSS 0.032 + 0.004 <0.0001 0.019 + 0.005 <0.0001

Cerebellar signs 0.155 + 0.018 <0.0001 0.098 + 0.022 <0.0001

Cerebellar FS 0.079 +0.006 <0.0001

Pyramidal signs 0.107 + 0.022 <0.0001

Pyramidal FS 0.026 + 0.006 0.0001

Sensory signs 0.072 + 0.025 0.005

Sensory FS 0.025 + 0.008 0.002

Type evolution <0.0001

RRMS 0.892 + 0.013

PPMS 1.005 + 0.032

SPMS 1.018 + 0.022 The values in the table represent the increase of the CCFS when the signs are present or for an increase of one for the variable. Data are expressed as estimated parameter + Standard error (SE).

The CCFS was significantly increased with the EDSS (+0.032 + 0.004 per each additional point on the EDSS scale, p<0.0001) while it was not correlated with age at multiple sclerosis onset and disease duration (p=0.70 and p=0.25 respectively). Patients with cerebellar signs had significantly higher CCFS than the patients with no cerebellar signs (p<0.0001) (Table 1). Similarly patients with pyramidal and sensory signs had significantly higher CCFS than the patients with no such signs. However several patients expressed two or three of these signs. After adjustment of the cerebellar signs, the CCFS was anymore different according to the presence of pyramidal and sensitive signs. In addition, there was a significant interaction between the EDSS and the presence of cerebellar signs. The CCFS was slightly increased with the EDSS for the patient without cerebellar signs (+0.008 + 0.003 per each additional point on the EDSS scale, p=0.0047) while it was slightly increased with the EDSS for the patient with cerebellar signs (+0.055 + 0.011 per each additional point on the EDSS scale, p<0.0001) (Figure 2). 40 of the 45 patients with cerebellar impairment had an EDSS > 4; the remaining 5 patients had an EDSS between 2 and 3.

Discrimination between patients with and without cerebellar impairment

EDSS and CCFS were both associated with cerebellar impairment (OR: 2.1 [1.6-2.7) per EDSS unit increase, 1.3 [1.2-1.4) per 0.01 CCFS unit increase). The AUC for the EDSS was slightly lower than the AUC for the CCFS (0.85 [0.78-0.93] versus 0.90 [0.85-0.96], (Figure 5). Notably, while the ROC curves for both scales were superimposed for high sensitivity values, the CCFS performed better than the EDSS for high specificity values. The ROC curved allowed to defined threshold values for the CCFS (Table 5). Only 4.4% of the patients with a cerebellar impairment had a CCFS value below 0.876 and among the patients below this threshold 95.0% had no cerebellar impairment. On the other hand, only 5.0% of the patients without cerebellar impairment had a CCFS over 0.955 and among the patients over this threshold 90.0% had a cerebellar impairment. Table 5: CCFS performance to detect cerebellar impairment in MS patients. The thresholds are chosen to optimize the specificity for a sensitivity of 95%, to optimize the sensitivity for a specificity of 95%, and to maximize the Youden's index. PPV: positive predictive value, NPV: negative predictive value.

Conclusion

The CCFS is a simple and specific method for quantification assessment of cerebellar involvement in MS over a wide range of severity, and should be useful for quantifying cerebellar progression of MS in future therapeutic trials.

It is shown to be specifically increased in patients with cerebellar symptoms. In this subpopulation, the CCFS is correlated to the severity of the patient measured by the EDSS and the cerebellar FFS. In addition, we have shown that the CCFS is more specific than the EDSS to discriminate patients with and without cerebellar impairment. Thus, the CCFS can be used to evaluate the severity of cerebellar signs in multiple sclerosis patients. The threshold to optimize sensitivity and specificity were computed and are in agreement with the values shown for dominant ataxia patients.

Example 2: The electronic CCFS is a reliable measurement scale of ataxia independent of age, usable with children.

Methods

Participants Three different groups of individuals were involved in this study.

Group I: for the validation of the electronic CCFS, 46 individuals were recruited and performed the CCFS trial on both manual and electronic devices. Among them 16 were controls and 30 were patients recruited in Salpetriere University Hospital, (25 patients with autosomal dominant cerebellar ataxia (SCA), 2 patients with familial spastic paraplegia, 2 patients with autosomal recessive cerebellar ataxia, 1 patient with an unknown diagnosis).

Group II: for the study of CCFS kinetics we used raw CCFS data from 271 adult individuals. 48 were controls from Paris (16 of them also participated in group I), 77 were SCA patients recruited in Salpetriere University Hospital and 146 were FRDA patients from various university hospitals recruited through the EFACTS cohort study. For 21 patients, two or more measurements were available. Participants were recruited from January 2011 to December 2012. Group III: To study CCFS in controls younger than 20, 120 healthy participants were recruited in Milan and Paris in 2012.

Group IV: To study CCFS in younger FRDA patients 33 children with FRDA were recruited from various university hospitals through the EFACTS cohort study from May 2011 to May 2012. Data available

Age at examination, electronic CCFS scores and clinical diagnosis were available for all participants. Manual CCFS scores were available for all participants from group I. Disease duration and clinical scores (SARA) were available for all patients in group II and most patients of group IV. Raw CCFS data were available from all participants from group II, III and IV.

CCFS

The CCFS is a quantitative assessment initially developed and validated for SCA. It includes two functional tests for the dominant hand: the nine-hole pegboard test (time needed to place dowels in nine holes and the click test (time needed to perform 10 finger-pointing cycles) (1). A normalization process guarantees that it is not influenced by age, at least for individuals older than 20, the minimal age in the original control population used to construct the score. The manual CCFS consists of a wooden nine-hole pegboard and of a click test device, two switches separated by 39 cm. The time to complete each test is monitored by an attendant with the help of a stopwatch. The electronic CCFS is similar, but both pegboard and click test device are equipped with electronic sensors. Those sensors automate the timing measurement. In addition, the electronic device records the time between two clicks and the time between the placements of two dowels.

SARA

SARA is a semi quantitative scale developed to assess functional impairments caused by ataxia, with values from 0 (no ataxia) to 40 (most severe ataxia) (2). It is composed of 8 items assessing stance, sitting, speech disturbance, finger chase, dysmetria, nose- finger test, tremor, fast alternating hand movements and heel-shin slide.

CCFS kinetic data

We studied the kinetics of the electronic CCFS trials by computing a linear regression model per trial per patient. The slope of that model represented either acceleration (positive slope) or an increased fatigability (negative slope). The residual variance represented speed irregularities. The intercept represented the speed at the start of the trial.

Statistical analysis

We validated the electronic CCFS by calculating an intra-class correlation coefficient between manual and electronic CCFS in participants from group I. A confidence interval was computed using a non-parametric bootstrap with the BCa method (10,000 replicate).

We tested whether CCFS kinetic parameters were associated with disease duration and clinical severity using Pearson correlation coefficients. We also assessed the consistency of these measurements by calculating an intra-class correlation coefficient when several measurements were available for one participant. Confidence intervals were computed using a non-parametric bootstrap with the BCa method (10,000 replicate). To check the validity of the CCFS in individuals younger than 20, we performed a regression model of the CCFS score against the age. Because CCFS is normalized for age, the slope should, in theory, be equal to 0. Since this was not the case, we computed new normalization algorithms for the click test and the pegboard test. We tested the slope of this updated CCFS against the age, to check the independence between the updated CCFS and the age.

Results were reported as mean + SD, and regression analysis coefficients were reported as mean + SE. All tests were two-sided, and results were considered significant at the 5% threshold. P-values for pairwise t-tests where corrected for multiple testing using Holm's method. All analyses were performed in the R programming language, version 3.0.2 (3), with the RStudio Integrated Development Environment.

Results

Table 2: Characteristics of the controls and patients included in the 4 groups

Group I II III IV

Diagnosis Controls Patients Controls SCA FRDA Controls FRDA

N 16 30 48 77 146 120 33

Age 12.0 + 15.6 +

38.2 + 47.3 + 44.7 + 50.3 + 35.8 +

3.1 3.1

11.3 15.3 13.4 13.1 13.2

[7.0 -

[24 - 64] 9 - 74] [18 - 77] [8.0 -

[19 - 69] [1 [18 - 76]

18.0] 19.0]

Gender

- - 30 (63%) 40 (52%) 82 (56%) 73 (61%) 15 (45%) (F)

CCFS (e) 0.806 + 1.062 + 0.834 + 1.112 + 1.228 + 0.863 + 1.203 +

0.045 0.174 0.048 0.160 0.167 0.042 0.125

[0.700 - [0.768 - [0.706 - [0.839 - [0.932 - [0.782 - [0.969 -

0.876] 1.450] 0.953] 1.588] 1.700] 0.990]* 1.504]*

CCFS 0.810 + 1.056 +

(m) 0.033 0.164

- - - - [0.745 - [0.787 - 0.868] 1.452]

11.8 + 15.6 + 7.4 + 3.3

Disease

- - - 7.6 8.6 - duration [2 -

[0 - 36] [2 - 49]

16.5 +

16.3 + 19.2 +

7.9

SARA 7.4 8.6

[4.5 - 36] [1.5 - 36] [5 - 31]*** CCFS(e): CCFS from the electronic device; CCFS(m): CCFS from the manual device. Data are given as mean ± SD [Minimum-Maximum]

*Updated CCFS score

**Data available for 16 patients

***Data available for 20 patients

Electronic CCFS validation

For the validation of the CCFS(e) we included 46 individuals, 16 controls aged from 24 to 64 years old (38 + 11) and 30 patients with various diseases aged from 19 to 69 years old (47 + 15) (Table 2 group I). The CCFS scores were normal for the controls (0.811 + 0.033) for the manual CCFS and increased for the patients (1.056 + 0.164). The difference between the electronic and the manual measure were small (0.005 [-0.017 - 0.028], p = 0.63 for controls, -0.006 [-0.015 - 0.003], p = 0.20 for patients). The intra- class correlation coefficient between manual and electronic CCFS was very good (0.98 [0.97 - 0.99]). CCFS kinetics study

For the study of CCFS kinetics we included 271 individuals, 48 controls aged from 19 to 69 years old (47 + 15), 77 SCA patients aged from 19 to 74 (45 + 13) and 146 FRDA patients aged from 18 to 76 years old (50 + 13) (Table 2 group II). The CCFS score were normal for the controls (0.834 + 0.048) and increased for both SCA patients (1.112 + 0.160) and FRDA patients (1.228 + 0.167). SARA scores were also increased in SCA patients (16 + 7) and FRDA patients (19 + 9). Finally, disease duration was 12 years + 8 for SCA patients and 16 years + 9 for FRDA patients.

Table 3

Data are given as mean + SE [Minimum-maximum] p-value testing to 0 the parameter.

Differences between diagnoses

We assessed the significance of differences in CCFS kinetic measurements between diagnosis group with pairwise t-tests. Starting speed given by the intercept was higher for ADCA patients and FRDA patients than for controls, for the click test (1535 and 1198 vs 506, p < 0.001 and p < 0.001 respectively) and for the pegboard test (5436 and 3392 vs 1319, p < 0.001 and p < 0.001 respectively). Starting speed was also higher for FRDA patients than for ADCA patients for the click test (1535 vs 1198, p < 0.001) and for the pegboard test (5436 vs 3392, p < 0.001) (Table 3).

For the click test, acceleration, given by the slope, was significantly different from 0 and negative, indicating an acceleration during the task, for controls and FRDA patients (-2.1 and -5.7, p < 0.001 and p < 0.001 respectively) but not for ADCA patients (-1.6, p = 0.27). For the pegboard test acceleration was significantly different from 0 for controls and ADCA patients (-19 and -66, p < 0.001 and p = 0.016 respectively) but not for FRDA patients (-71, p = 0.08). Accelerations did not differ significantly between any diagnosis for both click test and pegboard test. However these accelerations remained negligible compared to the starting speed (from 250 to 750 times smaller for the click test and from 36 to 90 times smaller for the pegboard test).

Speed irregularity, given by the residual variance, was higher for ADCA and FRDA patients than for controls, for the click test (225 and 273 vs 61, p < 0.001 and p < 0.001 respectively) and for the pegboard test (894 and 1584 vs 287, p = 0.014 and p < 0.001 respectively). Speed irregularity did not differ between FRDA patients and ADCA patients for the click test (273 vs 225, p = 0.07) but it was higher for FRDA patients for the pegboard test (1584 vs 894, p < 0.001).

Relations between measurements

Starting speed (intercept) and speed irregularity (residual) were closely related (r = 0.82 [0.78 -0.86], p < 0.001 for click test and r = 0.76 [0.71 - 0.81], p < 0.001 for pegboard test), slower participants being more irregular (Figure 3A and 3B). Acceleration was significantly inversely associated with starting speed (r = -0.33 [-0.44; -0.22], p < 0.001 for the click test and r = -0.50 [-0.59; -0.41], p < 0.001 for the pegboard test), slower participants accelerated more (Figure 3C and 3D). Acceleration was slightly associated with speed irregularity (r = -0.15 [-0.26; -0.03], p = 0.013) for the click test but not for the pegboard test (r = -0.05 [-0.17; 0.07], p = 0.40) (Figure 3E and 3F).

Relations with clinical characteristics

For ADCA and FRDA patients, starting speed was associated with SARA for both click test and pegboard test (r = 0.71 [0.64 - 0.76], p < 0.001 and r = 0.63 [0.55 - 0.70], p < 0.001 respectively) and disease duration (r = 0.41 [0.29 - 0.51], p < 0.001 and r = 0.31 [0.19 - 0.43], p < 0.001). Speed irregularity was also associated with disease duration and SARA for both click test (r = 0.28 [0.15 - 0.39] p < 0.001 and r = 0.58[0.48 - 0.65] p < 0.001 respectively) and pegboard test (r = 0.36 [0.24 - 0.48] p < 0.001 and r = 0.55 [0.45 - 0.63] p < 0.001 respectively). Acceleration was not significantly associated with neither SARA nor disease duration, for both click test and pegboard test. Reliability

Intra-class correlation coefficients calculated for the 21 participants with two measurements were high for click test starting speed (0.85 [0.60 - 0.99]), low for pegboard test starting speed (0.33 [0.17 - 0.44]), moderate for click test speed irregularity (0.51 [0.27 - 0.81]), low for pegboard test speed irregularity (0.49 [0.21 - 0.87]) and poor for click test and pegboard test acceleration (-0.65 [-0.89 - -0.32] and - 0.55 [-0.81 - -0.25]).

CCFS in younger controls

For the study of CCFS in younger individuals we included 120 controls aged from 7 to 18 years old (12 + 3) (Table 2 group III). Electronic CCFS scores ranged from 0.766 to 1.051 (0.890 + 0.048). The CCFS scores were significantly higher than for adult controls (children: 0.890 + 0.048 vs adults: 0.834 + 0.048, p < 0.001).

A regression analysis showed that before 20, CCFS was associated with age (slope = - 0.009 [-0.011; -0.006], p<0.001) (Figure 4A). An analysis of the sub-scores of the CCFS showed than both the total click time and the total pegboard time were associated with age (slope = -0.29 [-0.38 - -0.19], p < 0.001 and slope = -0.25 [-0.35 - -0.15], p < 0.001 respectively).

By design CCFS is supposed to be independent from age. In order to correct this problem, we recalculated the formula to normalize the click test and the pegboard test time below 20, with the two following constrains: (i) the new CCFS should not change for individuals older than 20 in order to maintain comparability with previous studies and (ii) there should not be a strong difference in the normalization formula used just before or just after 20 in order to avoid artificial "jumps" in CCFS values around that age. We performed a regression analysis one the sample of controls below 20 to obtain the new normalization formula for the click test and the pegboard test, and constrained normalization at exactly 20 years old to be the same in the formula used before and after this age. The new normalization formulas were: Z click = click time - (0.03 x age² - 1.14 x age + 18.89) if age < 20,

Z click = click time - (0.05 x age +8) if age > 20,

Z peg = pegboard time - (-0.08 x age + 12.62) if age < 20,

Z peg = pegboard time - (0.002 x age² - 0.16 x age + 13.4) if age > 20. After applying this new formula, the CCFS was independent of age before 20 year old (slope = 0.0004, [-0.002; 0.003], p = 0.73) (Figure 4B) as already shown for adults. The updated CCFS score ranged from 0.782 to 0.990 (0.863 + 0.042).

CCFS in younger FDRA patients

We used the new formula to compute the CCFS score in a population of the FRDA patients aged from 8 to 19 years old (14.2 + 2.7) (Table 2 group IV). CCFS scores ranged from 0.969 to 1.504 (1.203 + 0.125), SARA scores from 5 to 31 (16.5 + 7.9) and disease duration from 2 to 14 years (7.4 + 3.3). The CCFS scores were significantly higher than for young controls group III (1.203 + 0.091 vs 0.863 + 0.048, p < 0.001), but not significantly different from adult FRDA patients (1.203 + 0.091 vs 1.228 + 0.167, p=0.43).

Conclusion

We demonstrated i) the electronic version of the CCFS is a reliable replacement of the manual version, ii) Kinetic data brings no additional information compared to total test time for these populations, thus the published CCFS captures all the information provided by the tests, iii) The CCFS as published (Tezenas du Montcel et al. 2008) was not valid in children, but with minor corrections its use can be extended to children aged 7 and older, iv) This updated CCFS is valid in a population of young FRDA patients.

The existence of an electronic version of the CCFS facilitates the use of this test in a multicentre study. The similarity of devices between centres may decrease a centre effect that would be more important if the examinations were administrated by an attendant. Since the collection of data is automated, the test is reproducible and can be used by non-medical investigator such as clinical trial assistant. Finally, the automated collection of data permits better transparency and reduces the risk of transcription errors.

With the analysis of kinetic data, it was possible to obtain an internal insight of the measure. While a slight acceleration seems to exist, especially for the more severe patients, this acceleration remains negligible when compared to the total time. Furthermore this acceleration was not significantly associated with any clinical characteristic. Speed irregularity seems to be nothing more than a proxy of starting speed, and so has no interest of its own. It is thus justified to use the total test time (a simple factor of the starting speed in this case) as a whole, without considering kinetic factors. Since a negative intraclass correlation coefficient is meaningless and should be interpreted as being equal to 0 (4), our findings confirmed that the reliability of the acceleration measurements was very poor.

In light of these new findings, the necessity of performing as many as 10 finger-pointing cycles may be questioned, since the entire information may be captured with a single one. There is an argument to be made in favour of keeping several cycles: The repetition of finger-pointing cycles decreases measurement variability, and thus gives a better approximation of a "true" patient score. This is especially important for more severe patients, since we showed speed irregularity (and thus variability) increased when patients were slower.

Since as other diseases with cerebellar signs FRDA onset can occur in childhood, there was a need for a tool to study this particular population in epidemiological studies but also as the endpoint of a clinical trial. The updated CCFS is particularly valuable in this population because it is independent from the age of the individuals. It could thus measure changes caused by the disease independently from changes caused by maturation. Since the updated CCFS remains the same for patients aged 20 and older, comparisons and follow up before and after 20 remain possible. We also showed that even young FRDA patients had a CCFS score more severe than controls of the same age range. In conclusion the electronic CCFS is a measurement scale of ataxia independent of age, usable for individuals from 7 to 80 years old. The automated nature of the test makes it reproducible between operators and centers, and easy of use.

Claims

A non-invasive method for diagnosing and/or assessing a cerebellar impairment not involving Purkinje cells in a subject in need thereof comprising:

The non-invasive method for diagnosing and/or assessing a cerebellar impairment not involving Purkinje cells according to claim 1, wherein said cerebellar impairment involves cerebellar white matter and/or afferent pathways degeneration.

The non-invasive method for diagnosing and/or assessing a cerebellar impairment not involving Purkinje cells according to anyone of claims 1 to 2, wherein the subject to be diagnosed and/or assessed is affected by multiple sclerosis.

The non-invasive method for diagnosing and/or assessing a cerebellar impairment not involving Purkinje cells according to anyone of claims 1 to 3, wherein said method further comprises a writing test between step b and c.

A non-invasive method for diagnosing and/or assessing a cerebellar impairment in a young subject in need thereof comprising:

The non-invasive method for diagnosing and/or assessing a cerebellar impairment in a young subject according to claim 5, wherein the subject to be diagnosed and/or assessed is affected by Friedreich ataxia, autosomal dominant cerebellar ataxia or recessive cerebellar ataxia.

The non-invasive method for diagnosing and/or assessing a cerebellar impairment in a young subject according to anyone of claims 5 to 6, wherein said method further comprises a writing test between b and c.

a. performing the method according to anyone of claims 1 to 7 at different times,

The non-invasive method for monitoring the progression of a cerebellar impairment according to claim 8, wherein the results obtained in the monitoring allow the adaptation of the treatment of the subject.

An electronic device for diagnosing and/or assessing and/or monitoring a cerebellar impairment in a subject in need thereof, wherein the electronic device comprises:

- a board comprising at least two functional tests among a nine-hole pegboard test,

- a click test,

- a touch screen, and

- a software.

11. The electronic device according to claim 10, wherein said touch screen is used for implementing the writing test.

12. The electronic device according to anyone of claims 10 to 11, wherein said software records and analyzes the results collected after the performance of the functional tests.

13. The electronic device according to anyone of claims 10 to 12, wherein said board further comprises a webcam to analyze said subject's movements.

14. The electronic device according to anyone of claims 10 to 13, wherein said software further comprises training games to treat a cerebellar impairment in a subject in need thereof.

15. Use of the electronic device according to anyone of claims 10 to 14, for monitoring the progression of a cerebellar impairment in a subject in need thereof before, during or after a treatment of a cerebellar impairment in a subject in need thereof.