Clinical heterogeneity of recessive ataxia in the Mexican population

Rasmussen, Astrid; Gómez, María Mercedes; Alonso, Elisa; Bidichandani, Sanjay I.

doi:10.1136/jnnp.2006.090449

Cited by 11 publications

(5 citation statements)

References 20 publications

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“…In Mexico, previous studies of ADCA patients led to the identification of the SCA10 mutation, which has since only been reported in Mexican or Brazilian families 6–8. Similarly, when we analyzed a large series of patients with autosomal recessive and sporadic ataxia for mutations in the Friedreich ataxia gene ( FXN ), we found that it is eight times less frequent than in Europeans, and that most patients remained undiagnosed even after extensive workup 9, 10…”

mentioning

confidence: 69%

Distinct distribution of autosomal dominant spinocerebellar ataxia in the Mexican population

et al. 2007

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Dominant ataxias show wide geographic variation. We analyzed 108 dominant families and 123 sporadic ataxia patients from Mexico for mutations causing SCA1-3, 6-8, 10, 12, 17 and DRPLA. Only 18.5% of dominant families remained undiagnosed; SCA2 accounted for half (45.4%), followed by SCA10 (13.9%), SCA3 (12%), SCA7 (7.4%), and SCA17 (2.8%). None had SCA1, 6, 8, 12 or DRPLA. Among sporadic cases, 6 had SCA2 (4.9%), and 2 had SCA17 (1.6%). In the SCA2 patients we identified 6 individuals with the rare (CAG)(33) allele, 2 of whom showed early onset ataxia. The distribution of dominant ataxia mutations in Mexicans is distinct from other populations.

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confidence: 69%

Distinct distribution of autosomal dominant spinocerebellar ataxia in the Mexican population

et al. 2007

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“…Hence, we used a Gaussian Process (GP) Regression algorithm to find the mapping between the extracted behavioral features and the SARA and SCAFI clinical assessments. GP regression is a state-of-the-art method that applies a nonlinear regression and can capture the uncertainty in the presence of high variability in the data in a principled manner 39 .…”

Section: Resultsmentioning

confidence: 99%

A wearable motion capture suit and machine learning predict disease progression in Friedreich’s ataxia

Kadirvelu

Gavriel

Nageshwaran

et al. 2023

Nat Med

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Friedreichʼs ataxia (FA) is caused by a variant of the Frataxin (FXN) gene, leading to its downregulation and progressively impaired cardiac and neurological function. Current gold-standard clinical scales use simplistic behavioral assessments, which require 18- to 24-month-long trials to determine if therapies are beneficial. Here we captured full-body movement kinematics from patients with wearable sensors, enabling us to define digital behavioral features based on the data from nine FA patients (six females and three males) and nine age- and sex-matched controls, who performed the 8-m walk (8-MW) test and 9-hole peg test (9 HPT). We used machine learning to combine these features to longitudinally predict the clinical scores of the FA patients, and compared these with two standard clinical assessments, Spinocerebellar Ataxia Functional Index (SCAFI) and Scale for the Assessment and Rating of Ataxia (SARA). The digital behavioral features enabled longitudinal predictions of personal SARA and SCAFI scores 9 months into the future and were 1.7 and 4 times more precise than longitudinal predictions using only SARA and SCAFI scores, respectively. Unlike the two clinical scales, the digital behavioral features accurately predicted FXN gene expression levels for each FA patient in a cross-sectional manner. Our work demonstrates how data-derived wearable biomarkers can track personal disease trajectories and indicates the potential of such biomarkers for substantially reducing the duration or size of clinical trials testing disease-modifying therapies and for enabling behavioral transcriptomics.

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“…The parents of these affected persons do not know if they have any familial link, although they do share one of the surnames. Even if environmental or occupational factors could participate in the genesis of these diseases, a genetic origin is the first hypothesis as genetic ataxias are frequent in Mexico [35,36] . Molecular studies to describe their origin are presently under way.…”

Section: Discussionmentioning

confidence: 99%

Determining the Burden of Neurological Disorders in Populations Living in Tropical Areas: Who Would Be Questioned? Lessons from a Mexican Rural Community

Quet

Preux²,

Huerta

et al. 2011

Neuroepidemiology

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Background: The best approach to determine the burden of neurological disorders in developing countries is to perform population-based studies. Our objectives were to determine the prevalence of neurological disorders in a Mexican rural community and assess the usefulness of a household screening questionnaire. Methods: The survey took place in a Mexican rural community of Puebla State in Mexico. This was a cross-sectional, population-based, 2-phase study including a comparison of the usefulness levels of the individual (IQ) and household (HQ) questionnaires. Results: A total of 4,008 individuals participated in the prevalence study using the IQ; of these, 280 neurological examinations allowed to identify 127 individuals suffering from at least 1 neurological disease. The most frequent ailments were headache (22.4/1,000, 95% confidence interval, CI: 17.7–28.2), neuropathy (7.1/1,000, CI 95%: 4.4–11.3) and epilepsy (3.9/1,000, CI 95%: 2.3–6.5). The HQ, used in parallel with the IQ, detected significantly fewer neurological cases. This result was mainly due to the low capacity of the HQ to detect headache. Conclusions: Results of the prevalence study are discussed emphasizing their relevance in adequately allocating resources. The usefulness of the HQ for screening neurological disorders in general was low, but could be adequate for specific neurological disorders.

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Clinical heterogeneity of recessive ataxia in the Mexican population

Cited by 11 publications

References 20 publications

Distinct distribution of autosomal dominant spinocerebellar ataxia in the Mexican population

Distinct distribution of autosomal dominant spinocerebellar ataxia in the Mexican population

A wearable motion capture suit and machine learning predict disease progression in Friedreich’s ataxia

Determining the Burden of Neurological Disorders in Populations Living in Tropical Areas: Who Would Be Questioned? Lessons from a Mexican Rural Community

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