Aubrey de Grey - SENS

Prospects for extending healthy life - a lot

Aubrey D.N.J. de Grey, Ph.D.Chairman and CSO, Methuselah Foundation

Lorton, VA, USA and Cambridge, UK

Email: [email protected]

MF site: http://www.methuselahfoundation.org/

Science site: http://www.sens.org/

Prize site: http://www.mprize.org/

http://www.methuselahfoundation.org/

http://www.methuselahfoundation.org/

http://www.sens.org/

http://www.sens.org/

http://www.mprize.org/

http://www.mprize.org/

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Why I am doing this

Fun Not fun

Why I am doing this

Structure of this talk- Repair versus retardation

- Specifics: the seven types of damage

- Intracellular junk/medical bioremediation

- Longevity escape velocity: concept

- Some evidence that LEV is realistic

- The Methuselah Foundation







Aging in a nutshell

Product of evolutionary neglect, not intent

Metabolism ongoingly causes “damage”

Damage eventually causes pathology

Pathology causes more pathology

Strategies for intervention

Gerontology Geriatrics

Metabolism Damage Pathology

How to make a car last 50 years-- plan A

How to make a car last 50 years -- plan B

Strategies for intervention

Gerontology Engineering Geriatrics

Metabolism Damage Pathology

Claim: unlike the others, the engineering approach may achieve a large extension of

human healthy lifespan quite soon







Reasons for the engineering approach

- it targets initially inert intermediates (“damage”)



- damage is simpler than metabolism or pathology

Problem 1: this is metabolism

Problem 2:this is the pathology

• Alzheimer’s

• Stroke

• Sarcopenia

• Osteoarthritis

• Hormonal Imbalance

• Kidney Failure

• Cancer• Heart Disease

• Diabetes• Incontinence• Osteoporosis• Macular

Degeneration

• Parkinson’s• Pneumonia• Emphysema• Sex Drive

… and LOTS more

This is the damage

No new type of damage identified since 1982!

Seven Deadly Things

1. Junk - Inside Cells

2. Junk - Outside Cells

3. Cells - Too Few

4. Cells - Too Many

5. Mutations - Chromosomes

6. Mutations - Mitochondria

7. Protein Crosslinks

Giving the middle-aged 30 years of extra healthy life: Robust Human Rejuvenation

Damage rising with age It or its effects reversible by

Cell loss, cell atrophy Cell therapy, mainly

Extracellular junk Phagocytosis by immune stimulation

Extracellular crosslinks AGE-breaking molecules/enzymes

Death-resistant cells Suicide genes, immune stimulation

Mitochondrial mutations Allotopic expression of 13 proteins

Intracellular junk Transgenic microbial hydrolasesNuclear [epi]mutations (only cancer matters)

Telomerase/ALT gene deletion plus periodic stem cell reseeding







Giving the middle-aged 30 years of extra healthy life: Robust Human Rejuvenation

Damage rising with age It or its effects reversible by

Cell loss, cell atrophy Cell therapy, mainly

Extracellular junk Phagocytosis by immune stimulation

Extracellular crosslinks AGE-breaking molecules/enzymes

Death-resistant cells Suicide genes, immune stimulation

Mitochondrial mutations Allotopic expression of 13 proteins

Intracellular junk Transgenic microbial hydrolasesNuclear [epi]mutations (only cancer matters)

Telomerase/ALT gene deletion plus periodic stem cell reseeding

Aggregates: major examples

- Proteins in neurodegeneration

- Oxysterols in atherosclerosis

Autophagy in Alzheimer’s Disease

Calnexin

Dystrophic Neurites IEM

Cat D

EndothelialCells

Lipid-engorgedLysosome

FoamCell

Bioremediation: the concept

- Microbes, like all life, need an ecological niche

- Some get it by brawn (growing very fast)

- Some by brain (living off material than others can't)

- Any abundant, energy-rich organic material that is hard to degrade thus provides selective pressure to evolve the machinery to degrade it

- That selective pressure works. Even TNT, PCBs…

Xenocatabolism: the concept

Graveyards: - are abundant in human remains…

- accumulate bones (which are not energy-rich)…

- do not accumulate oxysterols, tau etc...

- so, should harbour microbes that degrade them

- whose catabolic enzymes could be therapeutic

Environmental decontamination in vivo

7KC over time in enrichment cultures

0

50

100

150

200

250

300

350

400

450

500

0 2 4 6 8 10

day

HPLC area [arbitrary units]

7-ketocholesterol degradation - a good start

7-KC degradation - presented at meetings

First MF-funded paper submitted

Steps to biomedical application

1) Isolate competent strains; select by starvation

2) Identify the enzymes (mutagenesis, chemistry, genomics)

3) Make lysosome-targeted transgenes, assay cell toxicity

4) Assay competence in vitro (more mutagenesis/selection)

5) Construct transgenic mice, assay toxicity in vivo

6) Assay competence in disease mouse models

7) Test in humans as for lysosomal storage diseases









- damage is simpler than metabolism or pathology

- repairing damage buys time

Age

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Retarding aging: benefits modest

Halving rate of damage starting in middle age - doubles remaining healthspan

- raises total healthspan by maybe 20%

Age

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Comparable repair: far better

Fixing half the damage starting in middle age - doubles total healthspan

- raises remaining healthspan maybe 5-fold

hard

easy

Robust human rejuvenation (RHR)

Addition of 30 extra years of healthy life (and total life) to

people who are already in middle age when treatment is begun

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Ever-improving repair: better yet

Fixing half the damage, then 3/4 - not as good as doing 3/4 first time…

- but better than doing 1/2 first time…

hard

easy

very hard

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Infinitely better, in fact

Fixing half the damage, then 3/4, then 7/8…. - outpaces the so-far-unfixable damage…

- maintains healthspan indefinitely

Longevity escape velocity (LEV)

The rate at which rejuvenation therapies must improve (following the achievement of RHR) in order to outpace the accumulation of

so-far-irreparable damage







Simulating aging(Phoenix & de Grey, AGE 2007; 29:133)

Metabolism ongoingly causes “damage”

and

Damage eventually causes pathologySo….

Simulations of aging (and intervention) should simulate damage accumulation

Simulating damage: basis

- damage of many types accumulates

- any can kill us (i.e. they are not additive)

- within each type, subtypes are additive

- damage feeds back to hasten more damage

- people differ in damage accumulation rates

- death is from damage X challenge (e.g. flu)

Simulating damage: modelStructural parameters

N_CAT: The number of damage categories each person has N_MECH: The number of mechanisms in each category

MECH_WEIGHTm: The contribution of a mechanism to a category

Fitting parameters

BASAL_M: The mean basal damage rate BASAL_SD: The standard deviation of the basal damage rate

BASAL_H: The homogeneity of basal damage rate in a single person EXP_M: The mean exponential damage rate

EXP_SD: The standard deviation of the exponential damage rate

EXP_H: The homogeneity of exponential damage rate in a single person

FATAL_M: The mean yearly challenge FATAL_SD: The standard deviation of the yearly challenge

Values set for each person at initialisation:

PB: Basal rate for the person: lognorm(BASAL_M, BASAL_SD)

PE: Exponential rate for the person: lognorm(EXP_M, EXP_SD)

MBc,m:Basal rate for each mechanism: lognorm(BASAL_M, BASAL_SD)*(1-BASAL_H) + PB*BASAL_H

MEc,m: Exponential rate for each mechanism: lognorm(EXP_M, EXP_SD)*(1-EXP_H) + PE*EXP_H

D_Mc,m : Cumulative damage for each mechanism: 0 D_Cc : Cumulative damage for each category: 0

Variables updated for each person at each time step (year):

Total damage: PD(t) = [SUM c=1..N_CAT] D_Cc(t) Damage increment: DI_Mc,m(t) = MBc,m + MEc,m*PD(t-1)

Cumulative damage: D_Mc,m(t) = DI_Mc,m(t) + D_Mc,m(t-1)

Cumulative category damage: D_Cc(t) = [SUM m=1..N_MECH] DI_Mc,m(t)

Fatality challenge: FATAL(t) = |norm(FATAL_M, FATAL_SD)|

If D_Cc(t) > FATAL(t) for any c, the person dies at age t

Validation: age at death

Results: how damage evolves

Results: defeat of damageTherapies doubling in efficacy every 42 y

0 50 100 150 200 250 300 350

Results: LEV in practiceTherapies doubling in efficacy every 42 y

0 50 100 150 200 250 300 350

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LEV decreases with time

Fixing half the damage, then 2/3, then 3/4…. - still good enough…

- just like gravitational escape velocity

Data







Funds: current status- $4.5M in Mprize pot

- Research pot being spent as fast as we fill it

- “LysoSENS” being funded (~$100k/yr) by 2005-2006 donations to the MF

- “MitoSENS” being funded (~$150k/yr) by Peter Thiel’s donation of $500k

- Thiel’s challenge pledge ($3M) is 1:2; our next goal is to match it in full (i.e. raise $6M)

Eventual organisational structure

Medium-term goal: proof of concept in miceStrategy: solve/combine subgoals (SENS)Procedure:- implement subgoals: ~350 people

- scientifically interesting and respected- best done extramurally by academics

- combine in same mice: ~150 people- scientifically tedious and unrewarded- best done in-house by paid technicians

Ramping up….

Level 1: funding of up to $300k per year guaranteed for at least 3 years. (This is where we are now.) Selected SENS strands supported at entry level (1 project/strand, 1-2 FTEs/project)

Level 2: funding of $300k-$3m per year, three years. (This is where we will be when the Thiel pledge is fully matched.) Six SENS strands supported at minimal level (1-3 projects/strand, 1-3 FTE/project)

Ramping up….

Level 3: funding of $3M-$20M per year guaranteed for at least five years. Grant applications solicited; 30-100 FTEs funded, across up to 30 projects

Level 4: funding of $20M-$100M per year, ten years. Physical facility (“Institute for Biomedical Gerontology”) set up (50-150 FTEs); extramural research support as in Level 3 (100-350 FTEs)

Why I am doing this

Why I am doing this

Why I am doing this

I offer no apology for using media interest in life extension to make the biology of ageing an exception to Planck’s observation that science advances funeral by funeral: lives, lots of them, are at stake.

de Grey 2005, EMBO Reports 6(11):1000

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Aubrey de Grey - SENS