Introduction: The Reality of the Mixed Brain
In the traditional clinical model of neurodegeneration, dementia is often viewed through the lens of a single dominant etiology—most commonly Alzheimer disease. However, as our understanding of the aging brain evolves through longitudinal cohort studies and postmortem analyses, this monolithic view is being replaced by a much more complex reality. Recent findings from the Religious Orders Study (ROS) and the Rush Memory and Aging Project (MAP) suggest that the aging brain is rarely affected by a single pathology. Instead, it is a landscape of overlapping proteinopathies and vascular changes that interact to drive cognitive decline. Understanding these distinct neuropathologic profiles is critical for improving diagnostic accuracy and developing personalized therapeutic strategies.
Background: Moving Beyond Single-Disease Paradigms
The clinical challenge of dementia management stems from the discrepancy between clinical symptoms and the underlying biological drivers. While a patient may present with classic amnestic symptoms, their brain may harbor a combination of amyloid plaques, tau tangles, Lewy bodies, and vascular damage. Previous research has hinted at the prevalence of mixed pathologies, but the full extent of their coexistence and their specific impact on cognitive trajectories remained under-explored. As the global population ages, there is an urgent need to categorize these complex pathologic signatures to better predict patient outcomes and refine the inclusion criteria for clinical trials targeting specific proteins like amyloid-beta or tau.
Study Design: Decades of Observation and Autopsy
The study, published in JAMA Network Open by Yu et al., utilized data from two ongoing community-based cohort studies: the Religious Orders Study (started in 1994) and the Rush Memory and Aging Project (started in 1997). The analysis included 1,633 participants who were cognitively healthy at the time of enrollment and agreed to annual clinical evaluations and organ donation upon death. The cohort had a mean age at death of 90.4 years, was predominantly female (70.8%), and highly educated (mean 16.2 years).The researchers conducted uniform neuropathologic evaluations assessing eight primary markers: Alzheimer disease neuropathologic change (ADNC), Lewy bodies, limbic-predominant age-related TDP-43 encephalopathy (LATE-NC), hippocampal sclerosis (HS), macro- and microscopic infarcts, cerebral amyloid angiopathy (CAA), atherosclerosis, and arteriolosclerosis. Cognitive performance was measured annually using a battery of 19 tests. To identify patterns within this complex data, the team used hierarchical clustering to group individuals into latent neuropathologic profiles.
Key Findings: The Five Profiles of the Aging Brain
The most striking result of the study was the sheer heterogeneity of the aging brain. More than 80% of the participants exhibited mixed neuropathologies at autopsy, and the researchers identified a staggering 280 unique combinations of copathologies. Despite this diversity, hierarchical clustering revealed five distinct neuropathologic profiles that characterized the cohort:
Profile 1: The Vascular Burden (15.9%)
This cluster was characterized by a high burden of macroscopic and microscopic infarcts along with significant vessel disease (atherosclerosis and arteriolosclerosis). Interestingly, these individuals often had lower levels of degenerative proteinopathies compared to other symptomatic groups, suggesting that vascular damage can be a primary driver of cognitive impairment independent of Alzheimer-type changes.
Profile 2: The LATE-NC and Hippocampal Sclerosis Signature (12.3%)
This profile was defined by high levels of LATE-NC and hippocampal sclerosis. LATE-NC has recently emerged as a major player in late-life dementia, often mimicking Alzheimer’s symptoms but driven by TDP-43 proteinopathy. This group represented a significant portion of the severe decline cases.
Profile 3: The Lewy Body Cluster (21.7%)
Participants in this profile showed a high prevalence of Lewy bodies. While often associated with Parkinson’s disease or Dementia with Lewy Bodies, these pathologies frequently co-occurred with other changes, though they formed a statistically distinct cluster in this analysis.
Profile 4: The ADNC and CAA Axis (9.7%)
This profile was characterized by high levels of Alzheimer disease neuropathologic change (plaques and tangles) and cerebral amyloid angiopathy. Though it represented less than 10% of the total cohort, it was one of the most clinically aggressive profiles.
Profile 5: The Low Pathology Group (40.4%)
The largest group in the study consisted of individuals with relatively low levels of all measured pathologies. These individuals likely represent the ‘gold standard’ of successful brain aging or possess resilience factors that mitigate the accumulation of toxic proteins and vascular damage.
The Cognitive Cost: Differential Trajectories of Decline
The study’s longitudinal design allowed researchers to map how these profiles translated into real-world cognitive decline. The trajectories were not uniform; they differed significantly in both the timing of onset and the rate of progression.The fastest rates of cognitive decline were observed in Profile 2 (LATE-NC and HS) and Profile 4 (ADNC and CAA). This finding is particularly significant because it highlights that LATE-NC is just as potent a driver of cognitive failure as Alzheimer’s disease in the oldest-old. Profile 1 (Vascular) and Profile 3 (Lewy bodies) also showed significant decline compared to the low-pathology group, but the descent was generally more gradual or occurred later in life. These results underscore that the specific ‘cocktail’ of pathologies in an individual’s brain dictates the speed at which they lose their independence.
Expert Commentary: Clinical and Research Implications
The findings by Yu et al. have profound implications for clinical neurology and drug development. First, they reinforce the necessity of multi-target therapies. If 80% of patients have mixed pathology, a drug that only clears amyloid-beta may only address a fraction of the total pathological burden, explaining why some patients continue to decline despite successful plaque removal.Furthermore, the identification of LATE-NC as a primary driver of decline (Profile 2) suggests that clinical trials must begin to screen for TDP-43 pathology as biomarkers become available. The study also raises questions about ‘cognitive resilience.’ With 40% of the cohort remaining in the low-pathology group despite reaching an average age of 90, identifying the genetic or lifestyle factors that protect these individuals is a top priority for public health.One limitation noted by the researchers is the demographic makeup of the cohort, which was 96.6% White. Future studies must determine if these five profiles remain consistent across more diverse populations, as vascular risk factors and genetic predispositions for certain proteinopathies can vary significantly by ethnicity and socioeconomic status.
Conclusion: A Roadmap for Precision Neurology
This study provides a definitive map of the neuropathologic complexity of the aging brain. By moving away from a single-diagnosis approach and toward a profile-based understanding, clinicians can better interpret the heterogeneity of dementia symptoms. The dominance of mixed pathologies suggests that the future of dementia care lies in precision medicine—combining anti-amyloid, anti-tau, and neurovascular protective agents tailored to a patient’s specific pathologic profile. As we refine our ability to detect these proteins in living patients through PET imaging and fluid biomarkers, the five profiles identified here will serve as a critical framework for diagnosing and treating the aging mind.
References
1. Yu L, Wang T, Du L, Bennett DA, Schneider JA, Boyle PA. Neuropathologic Profiles and Associated Cognitive Trajectories in Community-Living Older Adults. JAMA Netw Open. 2026;9(1):e2554354. doi:10.1001/jamanetworkopen.2025.54354.
2. Nelson PT, Dickson DW, Trojanowski JQ, et al. Limbic-predominant age-related TDP-43 encephalopathy (LATE): consensus working group report. Brain. 2019;142(6):1503-1527.
3. Kapasi A, DeCarli C, Schneider JA. Impact of multiple pathologies on the threshold for clinical diagnosis of Alzheimer’s disease. Lancet Neurol. 2017;16(3):217-224.
