image: Figure 1. Association between entropy, biological age, and biomarkers across neurological conditions. (A) Boxplots of entropy across different age groups (only significant P-values are annotated: P < 0.05 = *, P < 0.01 = **, P < 0.001 = ***). (B) Behavior of summed dolichol concentration through age, with a 95% confidence interval. (C) Predicted values of the models for all samples, including groups with no neurological disorder, autism, schizophrenia, and Down syndrome. (D) Boxplot comparing age acceleration across the different groups (Only significant P-values are annotated: P < 0.05 = *, P < 0.01 = **, P < 0.001 = ***).
Credit: Copyright: © 2025 Latumalea et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
“Our study demonstrates that variations in brain lipids suffice for estimating biological age.”
BUFFALO, NY — July 1, 2025 — A new research paper, featured on the cover of Aging (Aging-US) Volume 17, Issue 6, was published on June 4, 2025, titled “DoliClock: a lipid-based aging clock reveals accelerated aging in neurological disorders.”
This study, led by first author Djakim Latumalea from the National University of Singapore and Hanze University of Applied Sciences, with corresponding author Brian K. Kennedy from the National University of Singapore, introduces DoliClock, a biological aging clock based on lipid profiles in the human brain. The researchers found that individuals with autism, schizophrenia, and Down syndrome show signs of accelerated brain aging compared to individuals without these conditions. The discovery offers a new approach to measuring brain aging using lipid markers instead of traditional DNA-based methods.
The team developed DoliClock using lipidomic data from post-mortem prefrontal cortex samples. Lipids are fat-like molecules that play a key role in brain health. Changes in lipid patterns can reflect the biological age of brain tissue. The study focused on a specific class of lipids called dolichols, which increase gradually with age. The DoliClock model was trained to predict biological age by analyzing levels of dolichols and other lipid molecules. It accurately estimated brain age and revealed higher aging rates in individuals with neurological disorders.
One notable finding was a sharp increase in lipid profile variability—also known as entropy—around the age of 40. This suggests a disruption in lipid metabolism during midlife, possibly caused by changes in the mevalonate pathway, a critical biological process involved in producing lipids like cholesterol and dolichol. These disruptions may contribute to aging-related brain decline.
The study also found that dolichol levels could serve as reliable biomarkers of aging. Their consistent increase with age and strong influence on DoliClock’s predictions make them especially useful. In individuals with autism, schizophrenia, and Down syndrome, the clock indicated more advanced biological brain aging than expected, supporting the idea that these conditions are associated with premature aging.
DoliClock offers a new perspective in aging research, complementing existing biological clocks based on DNA or protein markers. Because it relies on lipids, it may detect aspects of aging that other tools cannot. While the current model is based on brain tissue samples, future research may examine whether similar lipid patterns can be identified in more accessible fluids such as blood or cerebrospinal fluid.
“These findings suggest that lipidomics can provide valuable insights into the molecular mechanisms of brain aging and neurological disorders.”
This study highlights the growing potential of lipidomics in the study of aging and neurological disorders. It opens the door to new biomarkers that could help researchers and clinicians better monitor brain aging and develop more targeted interventions for age-related and neurodevelopmental diseases.
Read the full paper: DOI: https://doi.org/10.18632/aging.206266
Corresponding author: Brian K. Kennedy – bkennedy@nus.edu.sg
Keywords: aging, aging clock, down syndrome, autism, schizophrenia, dolichol
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Journal
Aging-US
Method of Research
News article
Subject of Research
Not applicable
Article Title
DoliClock: a lipid-based aging clock reveals accelerated aging in neurological disorders
Article Publication Date
4-Jun-2025
COI Statement
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.