Clinical, imaging, and molecular findings in a sample of Mexican families with pantothenate kinase-associated neurodegeneration

Dyslipidemia and hypercalciuria in a patient with pantothenate kinase 2 deficiency: A novel variant and case report

Pantothenate kinase-associated neurodegeneration (PKAN, OMIM: 234200) results from biallelic pathogenic variants in PANK2 which encodes pantothenate kinase 2, a crucial mitochondrial enzyme involved in coenzyme A biosynthesis. Pantothenate kinase-associated neurodegeneration patients typically exhibit the distinctive "eye of the tiger" sign on brain magnetic resonance imaging in the globus pallidus, along with psychiatric symptoms, extrapyramidal movements such as parkinsonism and dystonia, eventual speech and gait impairments, and the presence of dysphagia. An 11-year-old girl, with fifth-degree consanguinity, demonstrated typical psychomotor development and growth until the age of 5, when she began experiencing psychiatric symptoms. At the age of 9, she developed hand tremors, progressing to generalized muscular dystonia. By age 10, she exhibited gait and speech impairment. Physical examination revealed extensive generalized dystonia, hand tremors, speech impairment, dysphagia, inability to walk, and heightened osteotendinous reflexes. Metabolic analysis identified dyslipidemia with partial response to statin treatment and normocalcemic hypercalciuria. Exome sequencing revealed a novel likely pathogenic variant in PANK2 (NM_001386393.1:c.526C > G) in a homozygotic state. Pantothenate kinase-associated neurodegeneration typically manifests with generalized dystonia and psychiatric symptoms. Here, we present a Pantothenate kinase-associated neurodegeneration patient with dyslipidemia and hypercalciuria as potentially previously undescribed metabolic phenotype.

Neurodegeneration with brain iron accumulation: a case series highlighting phenotypic and genotypic diversity in 20 Indian families

Neurodegeneration with brain iron accumulation (NBIA) is an umbrella term encompassing various inherited neurological disorders characterised by abnormal iron accumulation in basal ganglia. We aimed to study the clinical, radiological and molecular spectrum of disorders with NBIA. All molecular-proven cases of NBIA presented in the last 5 years at 2 tertiary care genetic centres were compiled. Demographic details and clinical and neuroimaging findings were collated. We describe 27 individuals from 20 unrelated Indian families with causative variants in 5 NBIA-associated genes. PLA2G6-associated neurodegeneration (PLAN) was the most common, observed in 13 individuals from 9 families. They mainly presented in infancy with neuroregression and hypotonia. A recurrent pathogenic variant in COASY was observed in two neonates with prenatal-onset severe neurodegeneration. Pathogenic bi-allelic variants in PANK2, FA2H and C19ORF12 genes were observed in the rest, and these individuals presented in late childhood and adolescence with gait abnormalities and extrapyramidal symptoms. No intrafamilial and interfamilial variability were observed. Iron deposition on neuroimaging was seen in only 6/17 (35.3%) patients. A total of 22 causative variants across 5 genes were detected including a multiexonic duplication in PLA2G6. The variants c.1799G > A and c.2370 T > G in PLA2G6 were observed in three unrelated families. In silico assessments of 8 amongst 9 novel variants were also performed. We present a comprehensive compilation of the phenotypic and genotypic spectrum of various subtypes of NBIA from the Indian subcontinent. Clinical presentation of NBIAs is varied and not restricted to extrapyramidal symptoms or iron accumulation on neuroimaging.

Exploring Yeast as a Study Model of Pantothenate Kinase-Associated Neurodegeneration and for the Identification of Therapeutic Compounds

Mutations in the pantothenate kinase 2 gene (PANK2) are the cause of pantothenate kinase-associated neurodegeneration (PKAN), the most common form of neurodegeneration with brain iron accumulation. Although different disease models have been created to investigate the pathogenic mechanism of PKAN, the cascade of molecular events resulting from CoA synthesis impairment is not completely understood. Moreover, for PKAN disease, only symptomatic treatments are available. Despite the lack of a neural system, Saccharomyces cerevisiae has been successfully used to decipher molecular mechanisms of many human disorders including neurodegenerative diseases as well as iron-related disorders. To gain insights into the molecular basis of PKAN, a yeast model of this disease was developed: a yeast strain with the unique gene encoding pantothenate kinase CAB1 deleted, and expressing a pathological variant of this enzyme. A detailed functional characterization demonstrated that this model recapitulates the main phenotypes associated with human disease: mitochondrial dysfunction, altered lipid metabolism, iron overload, and oxidative damage suggesting that the yeast model could represent a tool to provide information on pathophysiology of PKAN. Taking advantage of the impaired oxidative growth of this mutant strain, a screening for molecules able to rescue this phenotype was performed. Two molecules in particular were able to restore the multiple defects associated with PKAN deficiency and the rescue was not allele-specific. Furthermore, the construction and characterization of a set of mutant alleles, allowing a quick evaluation of the biochemical consequences of pantothenate kinase (PANK) protein variants could be a tool to predict genotype/phenotype correlation.

Clinical and neuroimaging phenotypes of genetic parkinsonism from infancy to adolescence

Genetic early-onset parkinsonism presenting from infancy to adolescence (≤21 years old) is a clinically diverse syndrome often combined with other hyperkinetic movement disorders, neurological and imaging abnormalities. The syndrome is genetically heterogeneous, with many causative genes already known. With the increased use of next-generation sequencing in clinical practice, there have been novel and unexpected insights into phenotype-genotype correlations and the discovery of new disease-causing genes. It is now recognized that mutations in a single gene can give rise to a broad phenotypic spectrum and that, conversely different genetic disorders can manifest with a similar phenotype. Accurate phenotypic characterization remains an essential step in interpreting genetic findings in undiagnosed patients. However, in the past decade, there has been a marked expansion in knowledge about the number of both disease-causing genes and phenotypic spectrum of early-onset cases. Detailed knowledge of genetic disorders and their clinical expression is required for rational planning of genetic and molecular testing, as well as correct interpretation of next-generation sequencing results. In this review we examine the relevant literature of genetic parkinsonism with ≤21 years onset, extracting data on associated movement disorders as well as other neurological and imaging features, to delineate syndromic patterns associated with early-onset parkinsonism. Excluding PRKN (parkin) mutations, >90% of the presenting phenotypes have a complex or atypical presentation, with dystonia, abnormal cognition, pyramidal signs, neuropsychiatric disorders, abnormal imaging and abnormal eye movements being the most common features. Furthermore, several imaging features and extraneurological manifestations are relatively specific for certain disorders and are important diagnostic clues. From the currently available literature, the most commonly implicated causes of early-onset parkinsonism have been elucidated but diagnosis is still challenging in many cases. Mutations in ∼70 different genes have been associated with early-onset parkinsonism or may feature parkinsonism as part of their phenotypic spectrum. Most of the cases are caused by recessively inherited mutations, followed by dominant and X-linked mutations, and rarely by mitochondrially inherited mutations. In infantile-onset parkinsonism, the phenotype of hypokinetic-rigid syndrome is most commonly caused by disorders of monoamine synthesis. In childhood and juvenile-onset cases, common genotypes include PRKN, HTT, ATP13A2, ATP1A3, FBX07, PINK1 and PLA2G6 mutations. Moreover, Wilson’s disease and mutations in the manganese transporter are potentially treatable conditions and should always be considered in the differential diagnosis in any patient with early-onset parkinsonism.

Incidence of PKAN determined by bioinformatic and population-based analysis of ~140,000 humans

Panthothenate kinase-associated neurodegeneration (PKAN, OMIM 234200), is an inborn is an autosomal recessive inborn error of metabolism caused by pathogenic variants in PANK2. PANK2 encodes the enzyme pantothenate kinase 2 (EC 2.7.1.33), an essential regulatory enzyme in CoA biosynthesis. Clinical presentation includes dystonia, rigidity, bradykinesia, dysarthria, pigmentary retinopathy and dementia with variable age of onset ranging from childhood to adulthood. In order to provide an accurate incidence estimate of PKAN, we conducted a systematic review of the literature and databases for pathogenic mutations and constructed a bioinformatic profile for pathogenic missense variants in PANK2. We then studied the gnomAD cohort of ~140,000 unrelated adults from global populations to determine the allele frequency of the variants in PANK2 reported pathogenic for PKAN and for those additional variants identified in gnomAD that met bioinformatics criteria for being potentially pathogenic. Incidence was estimated based on three different models using the allele frequencies of pathogenic PKAN variants with or without those bioinformatically determined to be potentially pathogenic. Disease incidence calculations showed PKAN incidence ranging from 1:396,006 in Europeans, 1:1,526,982 in Africans, 1:480,826 in Latino, 1:523,551 in East Asians and 1:531,118 in South Asians. These results indicate PKAN is expected to occur in approximately 2 of every 1 million live births globally outside of Africa, and has a much lower incidence 1 in 1.5 million live births in the African population.

On the complexity of clinical and molecular bases of neurodegeneration with brain iron accumulation

Neurodegeneration with brain iron accumulation (NBIA) is a group of inherited heterogeneous neurodegenerative rare disorders. These patients present with dystonia, spasticity, parkinsonism and neuropsychiatric disturbances, along with brain magnetic resonance imaging (MRI) evidence of iron accumulation. In sum, they are devastating disorders and to date, there is no specific treatment. Ten NBIA genes are accepted: PANK2, PLA2G6, C19orf12, COASY, FA2H, ATP13A2, WDR45, FTL, CP, and DCAF17; and nonetheless, a relevant percentage of patients remain without genetic diagnosis, suggesting that other novel NBIA genes remain to be discovered. Overlapping complex clinical pictures render an accurate differential diagnosis difficult. Little is known about the pathophysiology of NBIAs. The reported NBIA genes take part in a variety of pathways: CoA synthesis, lipid and iron metabolism, autophagy, and membrane remodeling. The next-generation sequencing revolution has achieved relevant advances in genetics of Mendelian diseases and provide new genes for NBIAs, which are investigated according to 2 main strategies: genes involved in disorders with similar phenotype and genes that play a role in a pathway of interest. To achieve an effective therapy for NBIA patients, a better understanding of the biological process underlying disease is crucial, moving toward a new age of precision medicine.

Clinical rating scale for pantothenate kinase-associated neurodegeneration: A pilot study

BACKGROUND

Pantothenate kinase-associated neurodegeneration is a progressive neurological disorder occurring in both childhood and adulthood. The objective of this study was to design and pilot-test a disease-specific clinical rating scale for the assessment of patients with pantothenate kinase-associated neurodegeneration.

METHODS

In this international cross-sectional study, patients were examined at the referral centers following a standardized protocol. The motor examination was filmed, allowing 3 independent specialists in movement disorders to analyze 28 patients for interrater reliability assessment. The scale included 34 items (maximal score, 135) encompassing 6 subscales for cognition, behavior, disability, parkinsonism, dystonia, and other neurological signs.

RESULTS

Forty-seven genetically confirmed patients (30 ± 17 years; range, 6-77 years) were examined with the scale (mean score, 62 ± 21; range, 20-106). Dystonia with prominent cranial involvement and atypical parkinsonian features were present in all patients. Other common signs were cognitive impairment, psychiatric features, and slow and hypometric saccades. Dystonia, parkinsonism, and other neurological features had a moderate to strong correlation with disability. The scale showed good internal consistency for the total scale (Cronbach's α = 0.87). On interrater analysis, weighted kappa values (0.30-0.93) showed substantial or excellent agreement in 85% of the items. The scale also discriminated a subgroup of homozygous c.1583C>T patients with lower scores, supporting construct validity for the scale.

CONCLUSIONS

The proposed scale seems to be a reliable and valid instrument for the assessment of pediatric and adult patients with pantothenate kinase-associated neurodegeneration. Additional validation studies with a larger sample size will be required to confirm the present results and to complete the scale validation testing. © 2017 International Parkinson and Movement Disorder Society.

A novel gene mutation in PANK2 in a patient with severe jaw-opening dystonia

Pantothenate kinase-associated neurodegeneration (PKAN) is a rare neurodegenerative condition. Major clinical features include progressive dystonia, pigmentary retinopathy, spasticity, and cognitive decline. The typical MRI sign of the disease, known as "eye-of-the-tiger", is what makes differential diagnosis possible. We here describe a 16-year-old male patient with PKAN presenting with severe and sustained jaw-opening dystonia which may be due to heterogeneous etiologies showing poor response to treatment. Herein, long-term follow-up and genetic results of a PKAN case who experienced severe jaw-opening dystonia are presented and discussed.

Predictive Big Data Analytics: A Study of Parkinson's Disease Using Large, Complex, Heterogeneous, Incongruent, Multi-Source and Incomplete Observations

BACKGROUND

A unique archive of Big Data on Parkinson's Disease is collected, managed and disseminated by the Parkinson's Progression Markers Initiative (PPMI). The integration of such complex and heterogeneous Big Data from multiple sources offers unparalleled opportunities to study the early stages of prevalent neurodegenerative processes, track their progression and quickly identify the efficacies of alternative treatments. Many previous human and animal studies have examined the relationship of Parkinson's disease (PD) risk to trauma, genetics, environment, co-morbidities, or life style. The defining characteristics of Big Data-large size, incongruency, incompleteness, complexity, multiplicity of scales, and heterogeneity of information-generating sources-all pose challenges to the classical techniques for data management, processing, visualization and interpretation. We propose, implement, test and validate complementary model-based and model-free approaches for PD classification and prediction. To explore PD risk using Big Data methodology, we jointly processed complex PPMI imaging, genetics, clinical and demographic data.

METHODS AND FINDINGS

Collective representation of the multi-source data facilitates the aggregation and harmonization of complex data elements. This enables joint modeling of the complete data, leading to the development of Big Data analytics, predictive synthesis, and statistical validation. Using heterogeneous PPMI data, we developed a comprehensive protocol for end-to-end data characterization, manipulation, processing, cleaning, analysis and validation. Specifically, we (i) introduce methods for rebalancing imbalanced cohorts, (ii) utilize a wide spectrum of classification methods to generate consistent and powerful phenotypic predictions, and (iii) generate reproducible machine-learning based classification that enables the reporting of model parameters and diagnostic forecasting based on new data. We evaluated several complementary model-based predictive approaches, which failed to generate accurate and reliable diagnostic predictions. However, the results of several machine-learning based classification methods indicated significant power to predict Parkinson's disease in the PPMI subjects (consistent accuracy, sensitivity, and specificity exceeding 96%, confirmed using statistical n-fold cross-validation). Clinical (e.g., Unified Parkinson's Disease Rating Scale (UPDRS) scores), demographic (e.g., age), genetics (e.g., rs34637584, chr12), and derived neuroimaging biomarker (e.g., cerebellum shape index) data all contributed to the predictive analytics and diagnostic forecasting.

CONCLUSIONS

Model-free Big Data machine learning-based classification methods (e.g., adaptive boosting, support vector machines) can outperform model-based techniques in terms of predictive precision and reliability (e.g., forecasting patient diagnosis). We observed that statistical rebalancing of cohort sizes yields better discrimination of group differences, specifically for predictive analytics based on heterogeneous and incomplete PPMI data. UPDRS scores play a critical role in predicting diagnosis, which is expected based on the clinical definition of Parkinson's disease. Even without longitudinal UPDRS data, however, the accuracy of model-free machine learning based classification is over 80%. The methods, software and protocols developed here are openly shared and can be employed to study other neurodegenerative disorders (e.g., Alzheimer's, Huntington's, amyotrophic lateral sclerosis), as well as for other predictive Big Data analytics applications.