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Basic Science and Pathogenesis.

Dorea P Jenkins1, Laura Davis1, Jennifer Belk1

  • 1Medical University of South Carolina, Charleston, SC, USA.

Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association
|December 24, 2025
PubMed
Summary
This summary is machine-generated.

South Carolina shows higher rates of early-onset Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD)-tau than national averages. Neuropathological studies reveal specific neurodegenerative diseases cluster in certain state regions.

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Area of Science:

  • Neuropathology
  • Neurodegenerative Diseases
  • Public Health Epidemiology

Background:

  • South Carolina exhibits a high prevalence of Alzheimer's disease (AD) and related dementias (ADRDs), impacting over 122,000 individuals.
  • Geographic mapping reveals non-uniform distribution of dementia cases, indicating specific

Purpose of the Study:

  • To define the causes of dementia in South Carolina through neuropathological examination.
  • To determine the prevalence of different ADRD types and compare them to national averages.
  • To investigate the geographic clustering of specific neurodegenerative diseases within the state.

Main Methods:

  • Detailed histologic examination of 343 post-mortem brain cases.
  • Utilized a panel of stains including H&E, Bielschowsky, and immunostains for key proteins (Abeta, tau, alpha-synuclein, p62, p-TDP43).
  • Diagnoses were mapped to zip-code level and reviewed by a certified neuropathologist.

Main Results:

  • 43.1% of cases had AD, with 20.3% being early-onset (higher than the typical 5-10%).
  • Frontotemporal lobar degeneration (FTLD)-tau (63.6%) and FTLD-TDP (26.4%) were more prevalent than usual.
  • Multiple system atrophy occurred at a higher rate; pure AD was uncommon, with most AD cases co-occurring with other neurodegenerative diseases. Geographic clustering of diagnoses was observed.

Conclusions:

  • South Carolina shows an elevated representation of early-onset AD and FTLD-tau.
  • Specific neurodegenerative diseases demonstrate clustering in particular geographic regions within the state.
  • Ongoing whole genome sequencing aims to identify genetic variants contributing to these observed diagnostic patterns.