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Early Brain Changes of Non-Amyloid Early Brain Changes of Non-Amyloid PathwaysPathways
Charles DeCarli, MDCharles DeCarli, MDVictor and Genevieve Orsi Chair in Alzheimer's
ResearchDirector University of California at Davis,
Alzheimer’s Disease Center
AcknowledgementsAcknowledgements
Funded in part by Grant R13 AG030995 Funded in part by Grant R13 AG030995 from the National Institute on Agingfrom the National Institute on Aging
The views expressed in written conference The views expressed in written conference materials or publications and by speakers materials or publications and by speakers and moderators do not necessarily reflect and moderators do not necessarily reflect the official policies of the Department of the official policies of the Department of Health and Human Services; nor does Health and Human Services; nor does mention by trade names, commercial mention by trade names, commercial practices, or organizations imply practices, or organizations imply endorsement by the U.S. Government.endorsement by the U.S. Government.
OutlineOutline
Brain Aging: cognition and structural Brain Aging: cognition and structural imagingimaging
Potential Causes of heterogeneityPotential Causes of heterogeneity
• Amyloidosis (brief)Amyloidosis (brief)
• Vascular risk factorsVascular risk factorsTime course of vascular risk on brainTime course of vascular risk on brain Inflammation and brain agingInflammation and brain aging
Cross-sectional and Longitudinal Cross-sectional and Longitudinal Memory PerformanceMemory Performance
Cross-sectional and Longitudinal Cross-sectional and Longitudinal Memory PerformanceMemory Performance
Wilson et al, Arch Neuro, 1999Wilson et al, Arch Neuro, 1999 Wilson et al,Psychology and Aging, 2002Wilson et al,Psychology and Aging, 2002
Clinical ConsequencesClinical Consequences
Mungas, et al. Psychology and Aging, 2010
MRI Measures of AtrophyMRI Measures of Atrophy
Variability in Brain AgingVariability in Brain Aging
Hippocampus
Hip
po/t
cv
0.35
0.40
0.45
0.50
0.55
0.60
0.65
0.70
30 35 40 45 50 55 60 65 70 75 80 85 90 95 100AGE
New Gender
FM
Change in Gray Matter Volume
Total-
gray-w
oC
RB
L
300
350
400
450
500
550
0 2 4 6 8 10Time
Subject of Subset of auto hippo with other MRI regions
0-11830-1270-14770-15030-16510-16580-18500-18900-24620-25480-26460-28510-28570-29310-30030-35420-35790-3900-40280-4419
0-44370-46130-50320-52040-53920-955
Hippocampal Rates of Change
auto
4.4
4.6
4.8
5.0
5.2
5.4
5.6
5.8
6.0
6.2
6.4
6.6
6.8
7.0
7.2
7.4
7.6
-0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0Years
id of Sheet1
0-10380-10650-10780-11130-11350-11830-12020-12060-12200-12310-1270-12820-13500-13590-1380-13800-13960-1450-14550-1477
0-15030-1540-15540-1570-16510-16580-17000-17130-17760-1790-18370-18500-18900-19390-19540-19570-20040-21180-21220-2146
0-21470-21660-22740-23100-23120-2315
SummarySummary
Brain aging is heterogeneousBrain aging is heterogeneous
• CognitionCognition
• Brain structureBrain structure
OutlineOutline
Brain Aging: cognition and structural Brain Aging: cognition and structural imagingimaging
Potential Causes of heterogeneityPotential Causes of heterogeneity
• Amyloidosis (brief)Amyloidosis (brief)
• Vascular risk factorsVascular risk factorsTime course of vascular risk on brainTime course of vascular risk on brain Inflammation and brain agingInflammation and brain aging
Percent PiB+ with AgePercent PiB+ with Age
Morris et al, Annals of Neuro, 2010
Time Dependent Time Dependent DifferencesDifferences
Jack, et al. JAMA Neurology, 2015
50.00%
55.00%
60.00%
65.00%
70.00%
75.00%
80.00%
85.00%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
35-44 44-54 55-64 65-74 75-84
Age-Specific Prevalence of Vascular Disease and Brain Volume
HTN
CAD
CVA
AD
SBI
Brain Volume
Framingham Heart Study, unpublished data
50.00%
55.00%
60.00%
65.00%
70.00%
75.00%
80.00%
85.00%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
35-44 44-54 55-64 65-74 75-84
Age-Specific Prevalence of Vascular Disease and Brain Volume
HTN
CAD
CVA
AD
Brain Volume
50.00%
55.00%
60.00%
65.00%
70.00%
75.00%
80.00%
85.00%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
35-44 44-54 55-64 65-74 75-84
Age-Specific Prevalence of Vascular Disease and Brain Volume
CVA
AD
Brain Volume
50.00%
55.00%
60.00%
65.00%
70.00%
75.00%
80.00%
85.00%
0%
10%
20%
30%
40%
50%
60%
70%
80%
35-44 44-54 55-64 65-74 75-84
Age-Specific Prevalence of Vascular Disease and Brain Volume
AD
Brain Volume
Prevalence of Vascular Risk Factors Prevalence of Vascular Risk Factors among the Framingham Offspringamong the Framingham Offspring
Measure Result
Age 62 + 10
Percent Obese 33
Percent hypertensive 52
Percent treated hypertensive 40
Percent Diabetic 13
Percent current smoker 14
Percent CAD 17
Percent MI 6
Percent stroke/TIA 4
Percent atrial fibrillation 5
DeCarli, et al. Neurobiology of Aging, 2005
Seshadri, S. et al. Stroke 2006;37:345-350
Future Risk of Stroke or Dementia at
Age 65
Women
Men
Spectrum of CVDSpectrum of CVD
MRI Infarction
Stroke
White Matter Hyperintensities
Brain Atrophy
MRI Examples of WMH and MRI Examples of WMH and SBISBI
NormalWMH
ExtensiveWMH
Silent MRIInfarct
Debette et al, Stroke, 2010
Age-Specific Prevalence of SBIAge-Specific Prevalence of SBI
DeCarli, et al. Neurobiology of Aging, 2005
0
5
10
15
20
25
30
35
5 6 7 8 9
Pre
va
len
ce
of
MR
Infa
rcts
(%
)
Decade of Life
Women
Men
Combined
N=100N=85
N=185 N=400
N=314N=714
N=322
N=300
N=622
N=214N=201
N=415
N=89N=39
N=128
0
10
20
30
40
50
60
70
80
30 40 50 60 70 80 90 100
WM
H v
olu
me
(cc)
Age
Aging White Matter DiseaseAging White Matter Disease
0.30
0.29
0.25
0.23
0.20
Vas
cula
r R
isk
DeCarli, et al. Neurobiology of Aging, 2005
Quantification of age-Quantification of age-related differences in related differences in
WMHWMHDefine Large WMH as 1 Define Large WMH as 1
sd above age-related sd above age-related mean WMHmean WMH
Vascular Risk and WMHVascular Risk and WMH
WomenWomen MenMen
SBPSBP 123 123 ++ 20 20 127 127 ++ 16 16
HTN Rx HTN Rx 15%15% 18%18%
DiabetesDiabetes 4%4% 7%7%
SmokerSmoker 16%16% 17%17%
History of CVDHistory of CVD 4%4% 8%8%
Atrial fibrillationAtrial fibrillation 0.2%0.2% 0.7%0.7%
ECG- LVHECG- LVH 4%4% 14%14%
FSRP score FSRP score 0.023 0.023 ++ 0.034 0.034 0.048 0.048 ++ 0.043 0.043
0.74
0.75
0.76
0.77
0.78
0.79
0.8
Cer
ebru
m %
TC
V
Quartiles of FSRP
Q1 Q2 Q3 Q4
Risk Factors, Age and Brain VolumeRisk Factors, Age and Brain Volume
Cognitive ConsequencesCognitive Consequences
Middle Life Vascular Risk Middle Life Vascular Risk Factors and Dementia RiskFactors and Dementia Risk
Whitmer, et al, Neurology, 2005
Increasing odds of Dementia with Increasing odds of Dementia with number of Risk Factors*number of Risk Factors*
Whitmer, et al, Neurology, 2005*~74% Caucasian
Dementia Risk with MRI Dementia Risk with MRI Vascular Measures Vascular Measures
Debette et al, Stroke, 2010
0 VR
1 VR
2 VR
3 VR
Significant change in FA Significant negative
Jacobians Both
Impact of Vascular Risk (VR) on White Matter Integrity and Gray Matter Atrophy
Maillard et al, Neurobiology of Aging, 2015
Significant FA loss /year
Significant Atrophy /year
***
Number of VR
**
***
***
*
*
Number of Vascular Risk Factors
Annual change in Annual change in hippocampus volumehippocampus volume
Summary IISummary II
Vascular risk factors are commonVascular risk factors are commonVascular risk factors affect the brainVascular risk factors affect the brain
• Silent brain infarctionsSilent brain infarctions
• WMHWMH
• Cerebral AtrophyCerebral AtrophyVascular risk factors affect cognition Vascular risk factors affect cognition
and brain structure in a dose dependent and brain structure in a dose dependent fashionfashion
OutlineOutline
Brain Aging: cognition and structural Brain Aging: cognition and structural imagingimaging
Potential Causes of heterogeneityPotential Causes of heterogeneity
• Amyloidosis (brief)Amyloidosis (brief)
• Vascular risk factorsVascular risk factorsTime course of vascular risk on brainTime course of vascular risk on brain Inflammation and brain agingInflammation and brain aging
Impact of Impact of Vascular Vascular
Disease may Disease may begin early begin early
Maillard, et al, Lancet Neurology, 2013
Neurology, 2015
Diabetes and Brain AgingDiabetes and Brain Aging
Cognitive ConsequencesCognitive Consequences
Hypothetical Model of Vascular Hypothetical Model of Vascular Disease and Brain AtrophyDisease and Brain Atrophy
0123456789
10
1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97 101
Amyloid Vascular Risk CVD Brain Injury
Age
Sev
erity
Hypothetical ConsequencesHypothetical Consequences
0
1
2
3
4
5
6
7
8
9
10
1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97 101Age
CognitionVRFVBI
SNAP?
Summary IIISummary III
Advancing age is associated with co-Advancing age is associated with co-morbid diseasesmorbid diseases
• Alzheimer’s pathologyAlzheimer’s pathology
• Cerebrovascular pathologyCerebrovascular pathologyVascular injury may begin early in lifeVascular injury may begin early in life
• The number of vascular risk factors The number of vascular risk factors appears additive to later life dementia appears additive to later life dementia riskrisk
Vascular risk may contribute to Vascular risk may contribute to neurodegeneration in SNAPneurodegeneration in SNAP
OutlineOutline
Brain Aging: cognition and structural Brain Aging: cognition and structural imagingimaging
Potential Causes of heterogeneityPotential Causes of heterogeneity
• Amyloidosis (brief)Amyloidosis (brief)
• Vascular risk factorsVascular risk factorsTime course of vascular risk on brainTime course of vascular risk on brain Inflammation and brain agingInflammation and brain aging
Atheroscler, Thromb, Vasc, Bio, 2011
Inflammation in Younger Inflammation in Younger IndividualsIndividuals
Interaction p-value indicates significant differences by younger versus older
Inflammation and Inflammation and CognitionCognition
GDF-15 in BrainGDF-15 in Brain
Immunostaining of human cortex from individual who had mixed dementia (AD+vascular dementia). Blue=cell nuclei stained with DAPI. Green=microglia stained with IBA-1. Red =immunostaining for GDF15. Colocalization of GDF15 is noted in microglia (arrows). Bar = 20um.
Model of Inflammation and Model of Inflammation and Brain Pathology in AgingBrain Pathology in Aging
Summary IVSummary IV
Aging and atherosclerosis lead to Aging and atherosclerosis lead to increasing inflammationincreasing inflammation
Inflammation can lead to brain injury Inflammation can lead to brain injury and cognitive decline independent of and cognitive decline independent of vascular risk factorsvascular risk factors
Inflammation may lead to microglial Inflammation may lead to microglial activation with release of harmful activation with release of harmful cytokinescytokines
ConclusionsConclusions
Brain aging is heterogeneousBrain aging is heterogeneousVascular risk factors cause subtle brain Vascular risk factors cause subtle brain
injury and cognitive impairment in a injury and cognitive impairment in a dose dependent mannerdose dependent manner
Cerebral atrophy is a common Cerebral atrophy is a common consequence of vascular riskconsequence of vascular risk
Inflammation secondary to systemic Inflammation secondary to systemic atherosclerosis may mediate some of atherosclerosis may mediate some of the atrophic processthe atrophic process
UC Davis Alzheimer’s Disease CenterUC Davis Alzheimer’s Disease Center
Supported by NIH: Supported by NIH: P30 AG10129,P30 AG10129, P01 AG12435,P01 AG12435,R01 AG010220, R01 AG021028,R01 AG010220, R01 AG021028,R01 AG031252, R01 AG 031563,R01 AG031252, R01 AG 031563,DHS 98-14970, K01 AG030514DHS 98-14970, K01 AG030514
http://alzheimer.ucdavis.edu/
• Charles DeCarliCharles DeCarli• Dan MungasDan Mungas• John OlichneyJohn Olichney• Sarah FariasSarah Farias• Berneet KaurBerneet Kaur• Bruce ReedBruce Reed• Ladson HintonLadson Hinton• Laurel BeckettLaurel Beckett• Danielle HarveyDanielle Harvey• Cam CarterCam Carter• Owen CarmichaelOwen Carmichael• Lee-Way JinLee-Way Jin• Joshua MillerJoshua Miller
IDeA Lab IDeA Lab Owen CarmichaelOwen Carmichael Evan FletcherEvan Fletcher Baljeet SinghBaljeet Singh Noel SmithNoel Smith Alexandra RoachAlexandra Roach Samuel LockhartSamuel Lockhart Jing HeJing He Pauline MaillardPauline Maillard
Supported by NIH and the Dana Supported by NIH and the Dana FoundationFoundation
http://neuroscience.ucdavis.edu/idealab/