Alterations in driving ability and their relationship with morphometric magnetic resonance imaging indicators in patients with amnestic mild cognitive impairment and Alzheimer's disease.

BACKGROUND: Drivers with dementia are at a higher risk of motor vehicle accidents. The characteristics of driving behaviour of patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD) have not been fully elucidated. We investigated driving ability and its relationship with cognitive function and magnetic resonance imaging (MRI) morphometry indicators. METHODS: The driving abilities of 19 patients with AD and 11 with amnestic MCI (aMCI) were evaluated using a driving simulator. The association between each driving ability parameter and the Mini-Mental State Examination (MMSE) score or voxel-based specific regional analysis system for AD (VSRAD) was assessed. RESULTS: Patients with AD made a significantly higher number of operational errors than those with aMCI in attention allocation in the complex task test (P = 0.0008). The number of operational errors in attention allocation in the complex task test significantly and negatively correlated with MMSE scores in all participants (r = -0.4354, P = 0.0162). The decision time in the selective reaction test significantly and positively correlated with the severity and extent of medial temporal structural atrophy (r = 0.4807, P = 0.0372; r = 0.4862, P = 0.0348; respectively). CONCLUSION: An increase in the operational errors for attention allocation in the complex task test could be a potential indicator of progression from aMCI to AD. Atrophy of the medial temporal structures could be a potential predictor of impaired judgement in driving performance in aMCI and AD. A driving simulator could be useful for evaluating the driving abilities of individuals with aMCI and AD.

The Utility of Long-Read Sequencing in Diagnosing Genetic Autosomal Recessive Parkinson's Disease: a genetic screening study.

Background: Mutations within the genes PRKN and PINK1 are the leading cause of early onset autosomal recessive Parkinson's disease (PD). However, the genetic cause of most early-onset PD (EOPD) cases still remains unresolved. Long-read sequencing has successfully identified many pathogenic structural variants that cause disease, but this technology has not been widely applied to PD. We recently identified the genetic cause of EOPD in a pair of monozygotic twins by uncovering a complex structural variant that spans over 7 Mb, utilizing Oxford Nanopore Technologies (ONT) long-read sequencing. In this study, we aimed to expand on this and assess whether a second variant could be detected with ONT long-read sequencing in other unresolved EOPD cases reported to carry one heterozygous variant in PRKN or PINK1. Methods: ONT long-read sequencing was performed on patients with one reported PRKN/PINK1 pathogenic variant. EOPD patients with an age at onset younger than 50 were included in this study. As a positive control, we also included EOPD patients who had already been identified to carry two known PRKN pathogenic variants. Initial genetic testing was performed using either short-read targeted panel sequencing for single nucleotide variants and multiplex ligation-dependent probe amplification (MLPA) for copy number variants. Results: 48 patients were included in this study (PRKN "one-variant" n = 24, PINK1 "one-variant" n = 12, PRKN "two-variants" n = 12). Using ONT long-read sequencing, we detected a second pathogenic variant in six PRKN "one-variant" patients (26%, 6/23) but none in the PINK1 "one-variant" patients (0%, 0/12). Long-read sequencing identified one case with a complex inversion, two instances of structural variant overlap, and three cases of duplication. In addition, in the positive control PRKN "two-variants" group, we were able to identify both pathogenic variants in PRKN in all the patients (100%, 12/12). Conclusions: This data highlights that ONT long-read sequencing is a powerful tool to identify a pathogenic structural variant at the PRKN locus that is often missed by conventional methods. Therefore, for cases where conventional methods fail to detect a second variant for EOPD, long-read sequencing should be considered as an alternative and complementary approach.