Interactions between weight loss and plasma neurodegenerative markers for determining cognitive decline among community-dwelling older adults

This study aimed to investigate the interaction between weight loss (WL) and plasma amyloid-β42/40 (Aβ42/40), neurofilament light chain (NfL), progranulin, and their association with cognitive decline over time among older adults. This 5-year observational approach included 470 participants from the Multidomain Alzheimer Preventive Trial (MAPT), mean age 76.8y (SD=4.5), 59.4% women. WL was defined as ≥5% decrease over the first year. Biomarkers were measured at 12 months. Cognitive function was assessed yearly from 12 months onwards by Mini-Mental State Examination (MMSE); Clinical Dementia Rating sum of boxes (CDR-SB); a composite score based on Category Naming Test, Digit Symbol Substitution Test, ten MMSE orientation items (MMSEO) and Free and total recall of the Free and Cued Selective Reminding test; and these tests individually. Twenty-seven participants (5.7%) presented WL. In adjusted analyses, combined WL+lower Aβ42/40 (≤0.103, lowest quartile) was related with more pronounced 4-year cognitive decline according to CDR-SB (p<0.0001) and MMSEO (p=0.021), compared to non-WL+higher Aβ42/40. WL+higher NfL (>94.55pg/mL, highest quartile) or progranulin (>38.4ng/mL, three higher quartiles) were related with higher cognitive decline according to CDR-SB, MMSE, MMSEO and composite score (all p<0.03), compared to non-WL+lower NfL or higher progranulin. Regrouping progranulin quartiles (Q1-Q3 vs. Q4) revealed higher cognitive decline among the WL+lower progranulin group compared to non-WL+lower progranulin. In conclusion, 1-year WL was associated with subsequent higher 4-year cognitive decline among older adults presenting low Aβ42/40 or high NfL. Future studies combining plasma biomarker assessments and body weight surveillance may be useful for identifying people at risk of cognitive impairment.

Single-Task or Dual-Task? Gait Assessment as a Potential Diagnostic Tool for Alzheimer’s Disease

Background: A person’s gait performance requires the integration of sensorimotor and cognitive systems. Therefore, a person’s gait may be influenced by concurrent cognitive load such as simultaneous talking. Although it has been known that gait performance of people with Alzheimer’s dementia (AD) is compromised when they attempt a dual-task walking task, it is unclear if using a dual-task gait performance during an AD assessment yields higher diagnostic accuracy. Objective: This study was designed to investigate the predictive power for AD of dual-task gait performance in an AD assessment. Methods: Participants (14 with AD and 15 healthy controls) walked across the GAITRite© Portable Walkway mat under three different cognitive load conditions: no simultaneous cognitive load, walking while counting numbers by ones, and walking while completing category naming. Results: Multiple logistic regression revealed that the high cognitive load (i.e., category naming) with or without the low cognitive load (i.e., concurrent counting) increased the proportion of variance explained by the FAP, SL, and DST. Conclusion: Dual-task walking and talking may be a more effective diagnostic feature than single-task walking in a comprehensive AD diagnostic assessment.

The Anatomy of Category-specific Object Naming in Neurodegenerative Diseases

Neuropsychological studies suggest that knowledge about living and nonliving objects is processed in separate brain regions. However, lesion and functional neuroimaging studies have implicated different areas. To address this issue, we used voxel-based morphometry to correlate accuracy in naming line drawings of living and nonliving objects with gray matter volumes in 152 patients with various neurodegenerative diseases. The results showed a significant positive correlation between gray matter volumes in bilateral temporal cortices and total naming accuracy regardless of category. Naming scores for living stimuli correlated with gray matter volume in the medial portion of the right anterior temporal pole, whereas naming accuracy for familiarity-matched nonliving items correlated with the volume of the left posterior middle temporal gyrus. A previous behavioral study showed that the living stimuli used here also had in common the characteristic that they were defined by shared sensory semantic features, whereas items in the nonliving group were defined by their action-related semantic features. We propose that the anatomical segregation of living and nonliving categories is the result of their defining semantic features and the distinct neural subsystems used to process them.