High genetic heterogeneity of leukodystrophies in Iranian children: the first report of Iranian Leukodystrophy Registry.

Leukodystrophies (LDs) are a heterogeneous group of progressive neurological disorders and characterized by primary involvement of white matter of the central nervous system (CNS). This is the first report of the Iranian LD Registry database to describe the clinical, radiological, and genomic data of Persian patients with leukodystrophies. From 2016 to 2019, patients suspicious of LDs were examined followed by a brain magnetic resonance imaging (MRI). A single gene testing or whole-exome sequencing (WES) was used depending on the neuroradiologic phenotypes. In a few cases, the diagnosis was made by metabolic studies. Based on the MRI pattern, diagnosed patients were divided into cohorts A (hypomyelinating LDs) versus cohort B (Other LDs). The most recent LD classification was utilized for classification of diagnosed patients. For novel variants, in silico analyses were performed to verify their pathogenicity. Out of 680 registered patients, 342 completed the diagnostic evaluations. In total, 245 patients met a diagnosis which in turn 24.5% were categorized in cohort A and the remaining in cohort B. Genetic tests revealed causal variants in 228 patients consisting of 213 variants in 110 genes with 78 novel variants. WES and single gene testing identified a causal variant in 65.5% and 34.5% cases, respectively. The total diagnostic rate of WES was 60.7%. Lysosomal disorders (27.3%; GM2-gangliosidosis-9.8%, MLD-6.1%, KD-4.5%), amino and organic acid disorders (17.15%; Canavan disease-4.5%, L-2-HGA-3.6%), mitochondrial leukodystrophies (12.6%), ion and water homeostasis disorders (7.3%; MLC-4.5%), peroxisomal disorders (6.5%; X-ALD-3.6%), and myelin protein disorders (3.6%; PMLD-3.6%) were the most commonly diagnosed disorders. Thirty-seven percent of cases had a pathogenic variant in nine genes (ARSA, HEXA, ASPA, MLC1, GALC, GJC2, ABCD1, L2HGDH, GCDH). This study highlights the most common types as well as the genetic heterogeneity of LDs in Iranian children.

Early-Onset Friedreich's Ataxia With Oculomotor Apraxia.

Friedreich's ataxia (FRDA) is a rare autosomal recessive spinocerebellar ataxia which in the majority of cases is associated with a GAA-trinucleotide repeat expansion in the first intron of Frataxin gene located on chromosome 9. The clinical features include progressive gait and limb ataxia, cerebellar dysarthria, neuropathy, optic atrophy, and loss of vibration and proprioception. Ataxia with ocular motor apraxia type 1 (AOA1) is another autosomal recessive cerebellar ataxia which is associated with oculomotor apraxia, hypoalbuminaemia, and hypercholesterolemia. Here we describe two siblings (13- and 10-year-old) display overlapping clinical features of both early-onset FRDA and AOA1. Almost all of laboratory test (including urinary analysis/culture, biochemistry, peripheral blood smear, C-reactive protein level, erythrocyte sedimentation rate-1h) results were within the normal range for both patients. Due to the normal laboratory test results; we concluded that the diagnosis was more likely to be FRDA than AOA1. Therefore, neurologists should bear in mind that clinical presentations of FRDA may vary widely from the classical phenotype of gait and limb ataxia to atypical manifestations such as oculomotor apraxia.

Failure to thrive severity determination by new design curves in standard growth charts.

Failure to thrive (FTT) is a perplexing disorder commonly seen by primary care physicians. Identification of FTT and an assessment of severity of the undernutrition are important to identify children at risk, and to provide appropriate intervention for preventing malnutrition and developing sequela. One of different anthropometric methods for categorizing undernutrition in childhood is Waterlow and Gomez classifications. Unfortunately, these classifications are not an easy task for the practitioners due to its difficult calculations. In this paper, Waterlow and Gomez classifications have been shown on the Standard Growth Charts (WHO 2006). Using these curves, the practitioners can determine severity of FTT by plotting weight, height and age of the patients without any calculations.