Balkan Journal of Medical Genetics

CLINICAL EXPERIENCE OF NEUROLOGICAL MITOCHONDRIAL DISEASES IN CHILDREN AND ADULTS: A SINGLE-CENTER STUDY
Rogac M, Neubauer D, Leonardis L, Pecaric N, Meznaric M, Maver A, Sperl W, Garavaglia BM, Lamantea E, Peterlin B
*Corresponding Author: Mihael Rogac, M.D., Ph.D., Clinical Institute of Genomic Medicine, University Medical Center Ljubljana, Slajmerjeva 4, 1000 Ljubljana, Slovenia. Tel: +386-1-522-6078. Fax: +386-1-540-1137. E-mail: mihael.rogac@kclj.si
page: 5

MATERIALS AND METHODS

Clinical data (i.e., clinical, metabolic, electrophysiological, muscle biopsy and brain imaging data) of the children and adult patients with MDs have been summarized and analyzed. Data have been collected retrospectively analyzing the medical records of patients from 2000-2018, performing neurological examination and taking medical histories of all patients by the first author. Cohort Analysis. The cohort of children with MDs comprised 26 patients, who manifested significantly decreased activity of RCEs and/or PDHc in the skeletal muscle with less than 50.0% enzyme activity [10]. Metabolic evaluations (serum lactate and pyruvate, blood gas analysis, amino acids in plasma, organic acids in urine, and acyl-carnitine profile in plasma) were performed in all children; cerebral spinal fluid (CSF) analysis with lactate measurements was assessed in eight children, electromyography was performed in 14 children, and brain magnetic resonance imaging (MRI) was performed in 24 children. Activities of RCEs and PDHc as well as molecular analysis for the thymidine kinase 2 TK2 gene and synthesis of cytochrome C oxidase 2 (SCO2) gene mutations were investigated as described previously [11,12]. Additional molecular analysis of mtDNA by polymerase chain reaction (PCR) and Southern blotting techniques in patients with RCEs deficiencies was investigated and included testing for large scale deletions/duplications and for point mutations related to the classical MDs, including mitochondrial encephalopathy lactic acidosis stroke-like episode (MELAS) syndrome mt.3242A>G and mt.3271T>C; myoclonic epilepsy and ragged-red fiber (MERRF) syndrome, mt.8344A>G and mt.8356T>C; neuropathy ataxia retinitis pigmentosa (NARP) syndrome mt.8993T>G and mt.8993T>C; Leigh syndrome mt.9176T>C, and in cardiomyopathy mt.8363G>A. Molecular analysis in patients with PDHc deficiency included testing for the E1α subunit gene PDHA and PDX (E3 binding protein subunit) gene mutations. The clinical exome sequencing of leucocytesderived DNA has been performed in six children. The cohort of adults with MDs comprised 36 patients who had a clinical picture of a classical mitochondrial syndrome, significantly reduced OXPHOS activity in the skeletal muscle with less than 50.0% enzyme activity [10] and/or a positive mutational analysis in a mtDNA or nuclear mitochondrial genes. The age range of patients was 23 to 79 years old. Most of the patients presented with a neuromuscular anomaly, and therefore, electromyography was performed in 31 patients and a muscle biopsy in 30 patients. Thirty-two patients presented as having a multisystem disease, but brain MRI was performed in only eight patients. Respiratory chain enzyme activities in a muscle were investigated in 14 patients, and additional sequencing of the mitochondrial genome was performed in 28 patients (mtDNA was isolated from the muscle specimen in 13 patients and from a buccal swab in 15 patients). Large scale deletion/duplication analysis of the mitochondrial genome isolated from the muscle specimen was done in 13 patients by the Southern blotting method. Finally, with the adult group, the clinical exome sequencing of leucocytesderived DNA was performed in 19 patients. Clinical examination and tests of all patients, children and adults, were scored according to the Nijmegen MDC [6-8]. The mean clinical score, metabolic and brain imaging score, and morphology score, were estimated and the probability of an MD diagnosis was determined. With the addition of the results from RCEs deficiencies and molecular genetic testing, Twenty of 26 children and 12/36 adults were scored as being definite MD carriers. The follow-up period ranged from 15 months to 18 years in children, and 1 to 15 years in adults. Clinical-Exome Sequencing (CES). Clinical-exome sequencing was performed using target capture from Trusight One (Illumina Inc., San Diego, CA, USA) targeting 12 Mb of exonic coding sequences in 4.813 Mendelian disease-associated genes. Sequencing was performed on HiSeq 2500 in 2 × 100 reads paired-end sequencing mode (Illumina Inc.). Sequencing data was processed using an in-house analysis pipeline, based on the Burrows-Wheeler aligner (BWA) (https://sourceforge.net) pipeline. Briefly, after the alignment of reads to hg19 human reference assembly using the BWA, duplicate sequences were removed using MarkDuplicates (Picard)-GATK (https://gatk.broad insti tute. org/), followed by base quality score recalibration, variant calling, variant quality score recalibration and variant filtering using elements of the GATK software [13]. Variant Analysis. Variants were stored and annotated using volunteer tools (vtools) and ANNOVAR (http:// anno var.openbioinformatics.org) [14,15]. The refseq gene models were used for transcript positioning of variants, and annotations from the dbSNP (single nucleotide database), version 138 were used for SNP annotation. We used in-house background population variant frequency estimates based on compilation of 2000 Slovenian exomes. Frequency information for worldwide populations was based on the data from GnomAD project (https:// gnomad.broad institute.com). Pre computed pathogenicity predictions in the dbNSFP version 2 database were used for evaluation of pathogenicity for missense variants [16]. Additionally, we used SNPeff predictors for additional annotation of variant effect [17]. Evolutionary conservation rates of the variant sites was based on genomic evolutionary rate profiling (GERP++) rejected substation (RS) scores [18]. We also used ClinVar (https://www.ncbi. nlm.nih.gov/clinvar/) as the source for known variants, associated with human disease [19]. Variant Filtration Strategy. Variants were filtered according to autosomal dominant, autosomal recessive and X-linked models of inheritance. We filtered out general variation attaining frequency above 0.01% in any of the surveyed populations for the dominant model and filtered out variants exceeding 0.1% for the autosomal recessive and X-linked models. All the variants passing these filters were subsequently inspected at aligned read level with the aim of avoiding false call due to misalignment or lowdepth of coverage. Genes, previously associated with MDs were investigated in a targeted manner. Magnetic Resonance Imaging Analysis. Of twenty children with a diagnosis of a definite MD (either RCEs deficiency or PDHc deficiency), additional brain MRI and magnetic resonance spectroscopy (MRS), under general anesthesia, were performed in 10 children. Progression of brain morphological MRI changes and metabolic changes in basal ganglia and white matter by MRS were also evaluated. Magnetic resonance imaging investigations were performed on 3T (Siemens AG, Munich, Germany) and 1.5T GE MR machine. Standard MR sequences were performed for structural brain imaging: 3DT1 sequence (TE/ TR = 6 ms/30 ms), T2 FSE sequence (TE/TR = 98.16 ms/4000 ms), fluid attenuated inversion recovery (FLAIR) sequence (TE/TR = 133 ms/8777 ms) and diffusion-weighted imaging (DWI) sequence (TE/TR = 134.8 ms/10000 ms). On the 3T MR machine, we also performed multi-voxel MR spectroscopy at TE 35 ms and TE 124 ms (TE/TR = 35 ms/1500 ms and TE/TR = 35 ms/1500 ms), and on the 1.5T MR machine we performed single-voxel MR spectroscopy at TE 35 ms and TE 144 ms (TE/TR = 35 ms/1500 ms and TE/TR = 144 ms/1500 ms) in the region of basal ganglia and deep white matter of the brain.

Number 27 VOL. 27 (2), 2024	Number 27 VOL. 27 (1), 2024
Number 26 Number 26 VOL. 26(2), 2023 All in one	Number 26 VOL. 26(2), 2023
Number 26 VOL. 26, 2023 Supplement	Number 26 VOL. 26(1), 2023
Number 25 VOL. 25(2), 2022	Number 25 VOL. 25 (1), 2022
Number 24 VOL. 24(2), 2021	Number 24 VOL. 24(1), 2021
Number 23 VOL. 23(2), 2020	Number 22 VOL. 22(2), 2019
Number 22 VOL. 22(1), 2019	Number 22 VOL. 22, 2019 Supplement
Number 21 VOL. 21(2), 2018	Number 21 VOL. 21 (1), 2018
Number 21 VOL. 21, 2018 Supplement	Number 20 VOL. 20 (2), 2017
Number 20 VOL. 20 (1), 2017	Number 19 VOL. 19 (2), 2016
Number 19 VOL. 19 (1), 2016	Number 18 VOL. 18 (2), 2015
Number 18 VOL. 18 (1), 2015	Number 17 VOL. 17 (2), 2014
Number 17 VOL. 17 (1), 2014	Number 16 VOL. 16 (2), 2013
Number 16 VOL. 16 (1), 2013	Number 15 VOL. 15 (2), 2012
Number 15 VOL. 15, 2012 Supplement	Number 15 Vol. 15 (1), 2012
Number 14 14 - Vol. 14 (2), 2011	Number 14 The 9th Balkan Congress of Medical Genetics
Number 14 14 - Vol. 14 (1), 2011	Number 13 Vol. 13 (2), 2010
Number 13 Vol.13 (1), 2010	Number 12 Vol.12 (2), 2009
Number 12 Vol.12 (1), 2009	Number 11 Vol.11 (2),2008
Number 11 Vol.11 (1),2008	Number 10 Vol.10 (2), 2007
Number 10 10 (1),2007	Number 9 1&2, 2006
Number 9 3&4, 2006	Number 8 1&2, 2005
Number 8 3&4, 2004	Number 7 1&2, 2004
Number 6 3&4, 2003	Number 6 1&2, 2003
Number 5 3&4, 2002	Number 5 1&2, 2002
Number 4 Vol.3 (4), 2000	Number 4 Vol.2 (4), 1999
Number 4 Vol.1 (4), 1998	Number 4 3&4, 2001
Number 4 1&2, 2001	Number 3 Vol.3 (3), 2000
Number 3 Vol.2 (3), 1999	Number 3 Vol.1 (3), 1998
Number 2 Vol.3(2), 2000	Number 2 Vol.1 (2), 1998
Number 2 Vol.2 (2), 1999	Number 1 Vol.3 (1), 2000
Number 1 Vol.2 (1), 1999	Number 1 Vol.1 (1), 1998

About the journal ::: Editorial ::: Subscription ::: Information for authors ::: Contact