To determine the frequency of high-convexity tight sulci (HCTS) in a population-based sample and whether the presence of HCTS and related features influenced participants’ cognitive status and classification within the new Alzheimer-biomarker framework.
We analyzed 684 participants ≥50 years of age who were enrolled in the prospective population-based Mayo Clinic Study of Aging and underwent structural MRI, amyloid PET imaging, and tau PET imaging. A fully automated machine-learning algorithm that had been developed previously in house was used to detect neuroimaging features of HCTS. On the basis of PET and MRI measures, participants were classified as having normal (A–) or abnormal (A+) amyloid, normal (T–) or abnormal (T+) tau, and normal (N–) or abnormal (N+) neurodegeneration. The neuropsychological battery assessed domain-specific and global cognitive scores. Gait speed also was assessed. Analyses were adjusted for age and sex.
Of 684 participants, 45 (6.6%) were classified with HCTS according to the automated algorithm. Patients with HCTS were older than patients without HCTS (mean [SD] 78.0 [8.3] vs 71.9 [10.8] years; p < 0.001). More were cognitively impaired after age and sex adjustment (27% vs 9%; p = 0.005). Amyloid PET status was similar with and without HCTS, but tau PET standard uptake value ratio (SUVR) was lower for those with HCTS after age and sex adjustment (p < 0.001). Despite a lower tau SUVR, patients with HCTS had lower Alzheimer disease (AD) signature cortical thickness. With the amyloid-tau-neurodegeneration framework, HCTS was overrepresented in the T–(N)+ group, regardless of amyloid status.
The HCTS pattern represents a definable subgroup of non-AD pathophysiology (i.e., T–[N]+) that is associated with cognitive impairment. HCTS may confound clinical and biomarker interpretation in AD clinical trials.