Santa Fe Institute Collaboration Platform

COMPLEX TIME: Adaptation, Aging, & Arrow of Time

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Contact: Caitlin Lorraine McShea, Program Manager,

Hallmarks of Biological Failure/DarioValenzano

From Complex Time

Notes by user Dario Riccardo Valenzano (Max Planck) for Hallmarks of Biological Failure

Post-meeting Reflection

1+ paragraphs on any combination of the following:

  • Presentation highlights
  • Open questions that came up
  • How your perspective changed
  • Impact on your own work
  • e.g. the discussion on [A] that we are having reminds me of [B] conference/[C] initiative/[D] funding call-for-proposal/[E] research group

Day 1

DPromislow: Evolution shapes function and failure. Three dimensional space: Failure, Function and Evolution.

Main question: why do different agents age at different rates (faster, slower?)

MHochberg: Function criticality, aging and resilience. Coupling mechanisms of adaptation and aging. Wait, what are we referring to here for adaptation?

James DeGregori

Is it evolutionary Explain this! Oncogenic mutations in young healthy stem cell

populations typically reduce cellular fitness.

Peto's paradox: large and long-lived animals do not develop more


Cancers requiring different numbers of driver mutations and

originating from vastly differently organized stem cell pools

demonstrate very similar age-dependent incidence. 

Adaptive oncogenesis: we evolved stem cells that are well adapted to

the tissue niche. Stabilised selection for the evolved type. This is

more powerful than avoiding mutations. Stem cells would be adapting to

new environment. 

q: does it mean that changing the tissue environment you would lead

stem cells (cancer) to evolved towards optimality in the "healthy"


q2: how about metastasis? do they evolve new-niche specific

variations? or physiological adaptations?

Rozalyne Anderson

Conserved pathways responsive to caloric restriction, across tissues. 

Chronic low-level mitochondrial activation in cells. Mito regulator

PGC 1A (expressed to 1.5X, similarly to CR tissues). Super cool!


  1. Frailty and disability: transitions
  2. Post-reproduction lifespan

u(a, H) < u(a, S)

u: death rate

a: age

H: health

S: Sick

Recovery becomes harder as we age.

Decline in homeostasis with aging.

Potential well model (similar to fitness lanscapes)

Escape from potential well. Fluctuations depend on well depth, curvature of well and size of fluctuation. It's a multidimensional space.

Prob (H --> Ha)

Prob(S --> Sa)

As we age, the profile of the H and S well changes, making it harder for the ball to escape from the S well.

Longitudinal data on health, frailty, morbidity. HMM drive transition states. (Aging studies, Framingham, HRS, ...).

borrowing Hamilton's fitness (grandmother effect, old men, learning, transfers).

Sabrina Spencer

Causes and consequences of non-genetic heterogeneity.

How do cells switch back and forth between quiescence and

proliferation. Shift from G1 towards G0 depends on CDK2 (off). She develops awesome trackers for CDK2. Wow!

Bifurcation in CDK2 activity appears in many cell types.

p21 inhibits CDK2. p21 -\- remove the bifurcation, leading to proliferation

only, no quiescence. Many quiescent cells have DNA lesions. Mothers of

quiescent daughters have a longer cell cycle. Daughter quiescence is

decided in the mother's G2 phase. Mother cells pass DNA damage to

their offspring cells (i.e. do not retain the damage).

CDK2low state fortifies cell lineage against stress. 

Barbara Natterson-Horowitz

Cardiovascular disease in humans, non-human primates, lions sympathetic and parasympathetic system.

Sudden cardiac death (SCD), "Tahatsubo" cardiomyopathy.

High adrenergic events. Sympathetic responses are flight and fight. Parasympathetic responses are opposite: faint, shit yourself, etc.

Fainting: vasovagal syncope (VVS), due to underprofusion of the brain.

VVS: paradoxical bradycardia has developmental characteristics: depends by the age of first fainting.

Alarm bradycardia is preferentially a juvenile phenotype.

Early life events: shaping autonomic nervous system for later events.

Day 2

    • Intro by Michael Hochberg

- Basins of attraction - Failure, gradual, rapid, can we predict it - What is failure, underperformance or misperformance - Tradeoffs and pleiotropy - Networks - not discrete comparts - Complexity vs. simplicity - Henry Ford Aging and senescence, time and disfunction. SSpencer: Immortality, regeneration and rejuvenation. DPromislow: Michael Rose's concept of age-depedent decline in fitness components.

    • Morgan Levine

Geroscience. Hallmarks of aging that accumulate over time. Systems biology of aging, changes ion the moleucular level propagate through the networks. Preservation of function (paper with Luigi Ferrucci in Circulation research). Aging heterogeneity, chronological age is an imperfect proxy of the latent concept, biological aging. Epigenetic clocks. Chronological age has been shown correspond with distinct chagnes in DNA metylation at specific CpG sites. Horvath's and Hannum's clocks. These clocks are done using supervised machine learning. She wants to capture the true residuals, rather than minimizing the residuals. Understand whether those residuals tell you anything about the underlying biology. Getting more biology than just chronological age from the clocks. Phenotypic age, predictor of aging-related mortality based on clinical measures. The used markers are albumin, creatinine, glucose, c-reactive proteins, lymphocyte percent, mean cell volume, red cell ditribution width, alkaline phosphatase, white blood cell count, age. Consensus co-methylation networks - data from 6 different tissues. 14 modules, showing age correlation for each CpG. Which piece of the clock matches what tissue, etc. Diseaseome map.

    • David Schneider (Stanford)

Resilience and disease space. How sick are you going to get with a given load of pathogens? Symptoms = f(microbe load). It's a disease tolerance curve. However, tolerance is a population measure and does not apply to individuals. How do we expect disease dynamics to vary? All models are wrong, but some models are useful (George Box). [[1][Tracking Resilience to Infection by Mapping Disease Space]]. Using a range of mouse diversity to identify imporant regulatory mechanisms. 8 parental mice used to generatel RIL. He brings up that methylation clocks are actually calendars, not clocks.

    • Marten Scheffer

How ecologists have been looking at resilience. Resilience: the capacity to get your acts together, to recover after damage. How quickly things come back to normal after perturbation. Sometimes things do not recover from perturbation and does not come back. Another way to think about it is that the system has become brittle. Unstable equilibrium. Theory developed in the 1960s, catastrophe theory. Salvador Dali and his own tipping point. Holling in 1973 thought about resilience. How to know a stability landscape. Tipping elements in the human intestinal ecosystem. Generic early warning signals = indicators of resilience. Critical slowing down. Dinamic indicators of resilience (DIOR). A bird shits on your head. After a hour you're ok, it means you're resilient. If after a hour you still hungry, you're not resilient, you may be depressed. This is based on patterns of micro-recovery. Fast recovery, slow recovery. Temporal autocorrelation help you predict tipping points. The previous arrow of time group has looked more at the complexity. This group is more looking at the molecular side.

    • DPromislow

Common dynamical phenomena underlying description of the causes of failure. What are those communalities? This can help us get to the causes and dynamics of failure. This could be an argument of discussion. Group discussions to address communalities and differences in failure.

Day 3

Reference material notes

Some examples:

  • Here is [A] database on [B] that I pull data from to do [C] analysis that might be of interest to this group (insert link).
  • Here is a free tool for calculating [ABC] (insert link)
  • This painting/sculpture/forms of artwork is emblematic to our discussion on [X]!
  • Schwartz et al. 2017 offers a review on [ABC] migration as relate to climatic factors (add the reference as well).

Reference Materials

Title Author name Source name Year Citation count From Scopus. Refreshed every 5 days. Page views Related file
Demography of dietary restriction and death in Drosophila Science 2003 0 1
In Vivo Amelioration of Age-Associated Hallmarks by Partial Reprogramming Cellular reprogramming by transient expression of Yamanaka factors ameliorates age-associated symptoms, prolongs lifespan in progeroid mice, and improves tissue homeostasis in older Cell 2016 0 3