featured in recent ARDD2023 video, this goes down with aging (Npc1 in yeast)
https://www.nature.com/articles/s41586-023-06802-1
Given the significant associations between the CognitionBrain age model and several brain aging metrics, we sought to uncover new insights into brain aging mechanisms by examining the proteins that make up the model. A total of 47 of the 49 model proteins were detectable in human brain single-cell RNA sequencing (scRNA-seq) data and most could be mapped to neurons and glia with high specificity (Fig. 3f). Proteins with the largest positive weights in the model (Fig. 3c) included the synaptic proteins complexin 1 (CPLX1), complexin 2 (CPLX2) and neurexin 3 (NRXN3)—which all have genetic links to cognition and AD31,32,33—and stathmin 2 (STMN2) and olfactomedin 1 (OLFM1)—which are involved in neurite outgrowth and axon growth cone collapse34,35. Proteins with large negative weights in the model such as Aldolase Fructose-Bisphosphate C (ALDOC), neuronal pentraxin receptor (NPTXR), carnosine dipeptidase 1 (CNDP1) and Lanc Like Glutathione S-Transferase 1 (LANCL1). ALDOC, NPTXR and CNDP1 are expressed in astrocytes, neurons and oligodendrocytes, respectively (Fig. 3f) and have been proposed as CSF biomarkers for AD36,37. LANCL1, which is primarily expressed in oligodendrocytes (Fig. 3f), has been shown to be crucial for neuronal health in mouse models38. The model also implicated alterations in the glycosylated extracellular matrix through the proteins tenascin R (TNR), neurocan (NCAN) and heparan sulfate-glucosamine 3-sulfotransferase 4 (HS3ST4), underlining the role of the extracellular matrix in brain aging.
Paraoxonase 1 (PON1) is one of most studied genes associated with cardiovascular disease, oxidative stress, inflammation, and healthy aging. Specifically, PON1 plays an important role in detoxifying organophosphorus compounds and removing harmful oxidized lipids 44. The genetic variant of PON1 (R192Q) significantly decreases PON1 activity and is known to be associated with an increased risk of cardiovascular disease and neurodegenerative diseases 45. Interestingly, the PON1 Q allele is significantly depleted in centenarians 45. We analyzed the relationship between PON1 activity and epigenetic age in 48 whole blood samples (Fig. 6a) 46. DamAge shows a significant negative correlation with PON1 activity (R = −0.55, p = 0.0062), whereas AdaptAge showed a significant positive correlation with PON1 activity (R = 0.69, p = 0.0003). Again, this association was not observed by other epigenetic clocks, except for Horvath age, but with a less significant negative correlation (P = 0.04). Together, we showed that DamAge can reliably detect damage-related biological age acceleration.
2.4.1 Dissipative and Conservative Genes
Specifically, our analysis revealed distinct examples of these categories. Genes such as MKRN1,
SESN1, and ATR were identified as conservative, as their embeddings remained stationary in the
embedding space across all stages of life. Conversely, genes such as ALDH3B1, NR2C2, and HERPUD1 displayed higher drift from their initial embeddings, categorizing them as dissipative (Figure
5a). Interestingly, the classification of genes as conservative or dissipative appears independent of
their biological roles. Both types of genes are involved in a wide range of cellular processes, including
DNA repair, stress response, and oxidative metabolism. This observation suggests that conservation
and dissipation are universal characteristics intrinsic to the aging process and occur across diverse
molecular pathways. This approach allows us to move beyond static measures of gene expression and
explore the broader molecular interplay that defines biological aging.
Our analysis revealed alterations in the drift of gene embeddings under diseased conditions, a fundamental shift in gene regulatory dynamics. Specifically, the ATR gene, typically characterized as a
conservative gene with stable embeddings in healthy cells, exhibited a marked increase in drift within
diseased samples (Figure 5b). This shift suggests that ATR, which plays a critical role in DNA damage response and cell cycle regulation, may adopt a different expression pattern under pathological
conditions. A similar pattern was observed for the SAFB2 gene, a regulator involved in chromatin
organization and stress response, which also displayed increased drift in disease states. These findings
could imply a broader trend where genes with stable behavior in healthy tissues become destabilized
in the presence of disease. Interestingly, the TDP2 gene, classified as a dissipative gene due to its
high variability in healthy samples, demonstrated an opposite behavior, maintaining a conservative
embedding in diseased conditions (Figure 5b). This unexpected stability could suggest a pot