1. Symposium on research and diseases of the brain 16 March 2017, Zagreb
First 30 years:
when aging
begins?
Goran Šimić
Symposium on research and diseases of the brain
16 March 2017, Zagreb
Projekt IP ( )
Croatian Science Foundation

2. Aging brain - phenomenology
Cross-sectional data
(tend to overestimate age-related differences due to cohort differences)
7-year longitudinal data
(tend to underestimate age-related differences due to attrition)
Seattle longitudinal study of aging ( , N = 4857)
Cognitive decline usually begins as early as 30, starting with a slowing of perceptual processing speed, followed by a day-to-day insidious worsening of spatial orientation, attention, verbal memory, numeric ability, and inductive reasoning. Declines are evident in all domains after age 55. One of the rare exceptions is verbal ability (fluency), which often remains relatively constant throughout adulthood and leads many individuals into thinking that their cognitive abilities are preserved.
Hedden and Gabrielli, Nat. Rev. Neurosci. 2004

3. Aging brain – population volumetry
PFC and OFC volumes decline steadily across the adult lifespan, while hippocampal volume has a curvilinear slope, with its largest declines occurring after age 60. Other areas, such as primary cortices, have only slight age-related volume declines.
Kennedy et al.
Neurobiol. Aging 2009

4. Aging brain – cortical thickness
1,633 MRI scans from 974 participants from 4.1 to 88.5 y of age were used to measure longitudinal changes in cortical thickness.
The fastest decline in seen in the teenage years and a relative plateau is seen in old age.
Fjell et al. PNAS USA 2015

5. Genetic influences on cortical regionalization
Broad similarities in genetic patterning between rodents and humans suggest a conservation of cortical patterning mechanisms while dissimilarities might reflect the functionalities most essential to each species.
N = 406 human twins (110 MZ and 93 DZ)
Chen et al. Neuron 2011

6. Even rats possess a DMN that is broadly similar to the DMNs of nonhuman primates and humans: despite the distinct evolutionary paths between rodent and primate brain, a well-organized, intrinsically coherent DMN appears to be a fundamental feature in the mammalian brain whose primary functions might be to integrate multimodal sensory and affective information to guide behavior in anticipation of changing environmental contingencies.
Lu et al. PNAS USA 2012

7. The cortex was parcellated into 12 regions (clusters) of maximal shared genetic influence, based on 406 middle aged twins.
Fjell et al. PNAS USA 2015

8. Both development and aging of cortical thickness depend on genetic organization patterns
Cortical changes due to both maturation and adult age changes adhered to the genetic organization of the cortex, indicating that individual differences in cortical architecture in middle-aged adults have a neurodevelopmental origin and that genetic factors affect cortical changes through life.
Fjell et al. PNAS USA 2015

9. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08 × 10(-33); 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. A worldwide genetic screen of brain data from over 30,000 people, and found eight common variants in the genome that affect the size of key structures within the brain; worldwide genomics efforts are now so highly powered that studies can unearth genetic markers that account for as little as 0.25% of the variance in brain measures, with strikingly consistent effects across 30 countries of the world.
Hibar et al. Nature 2015

10. Genetic influence on lifespan and longevity
Aging is not "genetically programmed", it is outside evolutionary constraint. Evolution favors early and efficient reproduction, but does not care for longevity. The heritability of longevity was estimated to be only moderate: 0.26 for males and 0.23 for females. The small sex-difference was caused by a greater impact of non-shared environmental factors in the females. It is genetically non-additive (caused by interaction within genes) and there is no no evidence for an impact of shared (family) environment.
Herskind et al. Hum. Genet. 1996
N = 2,872 Danish twins
No indication of increased mortality for twins:
Christensen et al. BMJ 1995
Hjelmborg et al. Hum. Genet. 2006
N = 8,495
N = 20,502
Mean lifespan of twin given lifespan of co-twin of Danish twin cohort 1870–1910. Dots denote mean lifespan of twin given 5 year lifespan interval of co-twin (MZ twins by solid circles, DZ twins by hollow circles). Horizontal lines are mean lifespan for the whole sample. There are minimal genetic effects on lifespans less than 60 years, moderate genetic effects on lifespans greater than 60 years, and that the influence of genetic factors is likely to be most important at the highest ages.

11. Steve Horvath’s aging clock algorithm
Heat map of DNA methylation levels of the 353 CpGs (of 28 million such sites in a single human genome) across all samples.
Horvath, Gen. Biol. 2013
>13,000 samples from 82 Illumina DNA methylation array datasets, encompassing 51 healthy tissues and cell types.

12. Steve Horvath’s aging clock algorithm
In one independent subsequent study (blood cells), the correlation between predicted and actual ages was 99.7%, with a median error measured in months, and in another (randomly sampled cells from urine) the correlation was 98%, with a standard error of just 2.7 years.
Horvath, Gen. Biol. 2013
Chen et al., Aging 2016
Hannum’s epigen. clock
Mol. Cell 2013 (needs calibration for
every tissue type and other adjustments)
N = 13,089 Predicting time to death -

13. Cerebellum ages slowly according to the epigenetic clock algorithm
Horvath et al., Aging 2015

14. Epigenetic clock vs. epigenetic drift
Central question to epigenetics and age is whether the changes observed are simply a result of the accumulation of exposures and experiences, or whether there is an underlying program?
Teschendorf, Hum. Mol. Genet. 2013

15. Epigenetic clock vs. epigenetic drift
E. drift was identified first in cell culture and then in human twins (they become more and more distinct with age as their experiences and exposures begin to differ after birth). E. drift is a collection of epigenetic changes acquired with age, which could be associated with the environment in which a person ages and are unique to an individual.
On the other hand, the epigenetic clock broadly reflects the process of aging. It occurs in addition to the increasing variability caused by epigenetic drift, at sites in the genome that reliably “tick” with age. While some clock sites may be common across tissues, each tissue may in fact have its own set of “ideal” clock sites (Hannum’s epi clock).
Conclusion:
Pluripotent stem cells escape from senescence-associated DNA methylation changes!
Reprogramming of aged cells into iPSCs and regeneration of differentiated cells may provide a mechanism for epigenetic rejuvenation!
Jones et al., Aging Cell 2015

16. Hvala na pozornosti! Simpozij o istraživanju i bolestima mozga
16. ožujka 2017.
Preporodna dvorana HAZU, Opatička 18, Zagreb
Hrvatska zaklada za znanost
Projekt IP ( )
Croatian Science Foundation