ABSTRACT
Background and Objectives: Next-generation sequencing (NGS) has expedited the diagnostic process and unearthed many rare disorders in leukodystrophy (LD) and genetic leukoencephalopathy (gLE). Despite the progress in genomics, there is a paucity of data on the distribution of genetic white matter disorders (WMDs) and the diagnostic utility of NGS-based assays in a clinical setting. This study was initiated to explore the clinical, radiologic, and genetic spectrum of LD and gLE in the Indian population and also to estimate the diagnostic yield of clinical exome sequencing (CES). Methods: This is a retrospective descriptive analysis of patients with a diagnosis of genetic WMDs from a single tertiary referral center who had CES performed as part of the diagnostic evaluation between January 2016 and December 2021. The demographic, clinical, radiologic, and genetic data were collected. The variants were classified using the American College of Medical Genetics and Genomics criteria. Pathogenic and likely pathogenic variants were included in the calculation of the diagnostic yield. Results: In the study period, 138 patients were clinically diagnosed with either LD or gLE, of which 86 patients underwent CES. Pathogenic variants, likely pathogenic variants, and variants of uncertain significance with phenotype match were seen in 40 (41.8%), 13 (29.1%), and 15 (15.2%) patients, respectively. The mean age at onset in these 68 patients was 6.35 years (range 1 month-39 years), and 38 (55.9%) were male. LDs and gLE were diagnosed in 31 and 37 patients, respectively. 56 patients (71.8%) had autosomal recessive inheritance. The common clinical presentations were developmental delay (23.5%), psychomotor regression (20.6%), progressive myoclonic epilepsy syndrome (19.1%), and spastic ataxia (14.7%). Myelin disorders (48.5%) and leuko-axonopathies (41.2%) were the commonest type of disorders. The most frequently identified genes were ARSA, CLN5, ABCD1, CLN6, TPP1, HEXA, and L2HGDH. The diagnostic yield of the study was 61.6% (53/86), which increased to 79.1% when VUS with phenotype match were included. Discussion: This study demonstrated a high diagnostic yield from proband-only CES in the evaluation of genetic WMDs and should be considered as a first-line investigation for genetic diagnosis. Classification of Evidence: This study provides Class IV evidence that proband-only clinical exome sequencing is a useful "first-line investigation" for patients with genetic white matter disorders.
ABSTRACT
INTRODUCTION: The study aimed to explore longitudinal cognitive outcomes and to ascertain predictors of conversion to dementia in a hospital-based mild cognitive impairment (MCI) cohort classified according to the neuropsychological phenotype at baseline. MATERIALS AND METHODS: Subjects aged >55 years who had a clinical diagnosis of MCI at initial visit between 2010 and 2018, with at least one formal neuropsychological assessment at baseline and follow-up of a minimum of 2 years were included. The prospective study was completed based on evaluation at last follow-up to gauge conversion to dementia, quantification of performance on activities of daily living and when available, longitudinal neuropsychological test scores. RESULTS: Ninety-five patients with MCI met the inclusion criteria with a mean age of 68.4 ± 6.4 years at baseline and a mean duration of follow-up for 6.4 ± 3.2 years. The cumulative conversion rate to dementia was 22.2% (21/95) and the annualized conversion rate was 3.3% per year of follow-up. The majority of subjects who had converted had multidomain MCI (66%). Only white matter changes on MRI brain revealed correlation with baseline neuropsychology tests. The multivariate logistic regression analysis revealed the utility of lower baseline list recognition (adjusted odds ratio: 0.735 [95% confidence interval: 0.589-0.916]; p 0.006), lower immediate logical memory (0.885 [0.790-0.990]; p 0.03), and high perseverative error scores on set shifting (3.116 [1.425-6.817]; p 0.004) as predictors of conversion. A model score of +2.615 could predict conversion with sensitivity of 72% and specificity of 98% over 6.4 years follow-up. CONCLUSION: There was a higher risk of conversion associated with multidomain MCI. Logistic regression-based estimations of dementia risk utilizing domain-based neuropsychology test scores in MCI have high specificity for diagnosis at baseline.