Link among apolipoprotein E E4, gait, and cognition in neurodegenerative diseases: ONDRI study

INTRODUCTION

Apolipoprotein E E4 allele (APOE E4) and slow gait are independently associated with cognitive impairment and dementia. However, it is unknown whether their coexistence is associated with poorer cognitive performance and its underlying mechanism in neurodegenerative diseases.

METHODS

Gait speed, APOE E4, cognition, and neuroimaging were assessed in 480 older adults with neurodegeneration. Participants were grouped by APOE E4 presence and slow gait. Mediation analyses were conducted to determine if brain structures could explain the link between these factors and cognitive performance.

RESULTS

APOE E4 carriers with slow gait had the lowest global cognitive performance and smaller gray matter volumes compared to non-APOE E4 carriers with normal gait. Coexistence of APOE E4 and slow gait best predicted global and domain-specific poorer cognitive performances, mediated by smaller gray matter volume.

DISCUSSION

Gait slowness in APOE E4 carriers with neurodegenerative diseases may indicate extensive gray matter changes associated with poor cognition.

HIGHLIGHTS

APOE E4 and slow gait are risk factors for cognitive decline in neurodegenerative diseases. Slow gait and smaller gray matter volumes are associated, independently of APOE E4. Worse cognition in APOE E4 carriers with slow gait is explained by smaller GM volume. Gait slowness in APOE E4 carriers indicates poorer cognition-related brain changes.

Robust hierarchically organized whole-brain patterns of dysconnectivity in schizophrenia spectrum disorders observed after personalized intrinsic network topography

BACKGROUND

Spatial patterns of brain functional connectivity can vary substantially at the individual level. Applying cortical surface-based approaches with individualized rather than group templates may accelerate the discovery of biological markers related to psychiatric disorders. We investigated cortico-subcortical networks from multi-cohort data in people with schizophrenia spectrum disorders (SSDs) and healthy controls (HC) using individualized connectivity profiles.

METHODS

We utilized resting-state and anatomical MRI data from n = 406 participants (n = 203 SSD, n = 203 HC) from four cohorts. Functional timeseries were extracted from previously defined intrinsic network subregions of the striatum, thalamus, and cerebellum as well as 80 cortical regions of interest, representing six intrinsic networks using (1) volume-based approaches, (2) a surface-based group atlas approaches, and (3) Personalized Intrinsic Network Topography (PINT).

RESULTS

The correlations between all cortical networks and the expected subregions of the striatum, cerebellum, and thalamus were increased using a surface-based approach (Cohen's D volume vs. surface 0.27-1.00, all p < 10-6 ) and further increased after PINT (Cohen's D surface vs. PINT 0.18-0.96, all p < 10-4 ). In SSD versus HC comparisons, we observed robust patterns of dysconnectivity that were strengthened using a surface-based approach and PINT (Number of differing pairwise-correlations: volume: 404, surface: 570, PINT: 628, FDR corrected).

CONCLUSION

Surface-based and individualized approaches can more sensitively delineate cortical network dysconnectivity differences in people with SSDs. These robust patterns of dysconnectivity were visibly organized in accordance with the cortical hierarchy, as predicted by computational models.