Brain Mineral Deposition and Cognitive Decline Study

 
Progression pattern of brain
mineral deposition as a
differential indicator of
cognitive decline
 
1
 
College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, UK.
2
 Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
3
Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, UK
 
L. Clayson
1
, M.C. Valdés Hernández
2
, 
A. Glatz
2
,
 J.M. Wardlaw
2
, J. Starr
3
 
Background
 
Image: L Clayson, mechanisms as reviewed in 
Moreno-Trevino 
et al 
2015
 
Background
 
Image: L Clayson.  Schematic representation of brain iron regulation mechanisms (as detailed in McCarthy & Kosman 2014).
[FPN: Ferroportin, bMVECS: brain microvascular endothelial cells].
 
Brain glial cell regulation of iron
 
Background
 
Image: L Clayson. 
Schematic representation of mineral deposition mechanisms
 
1. There is a distinctive pattern of mineral deposition
depending on the cognitive status (CN, MCI or AD) of
patients
 
2. With cognitive decline, mineral deposition increases
in regions know to be associated with increased
amyloid deposition
 
Hypotheses
 
To investigate the prevalence of basal ganglia
mineral deposition (BGMD) and brain
microbleeds in individuals of cognitive status
ranging from CN to AD
 
To improve our imaging techniques by
developing a specific cognitively-relevant atlas of
the distribution of mineral deposits with
estimates of the main mineral content per
region.
 
 
 
Aims
 
Is there 
a progression pattern of
brain mineral deposition that can be
used as a differential indicator of
cognitive decline?
 
Ultimately..
 
Methods
 
ADNI Database
Selection Criteria:
Sample 1: M.R.I. 
FLAIR, T2* & MPRAGE for 3 years
Sample 2: MRI data for 1 year
 
 
Semi-Automatic Software:
     - Analyze 11.0, MRIcron
 
BGMD Measurements
      - Automatic Pipeline
                          (Glatz
 et al
, 2015)
 
Microbleed Visual
Assessments
 
Methods (2)
 
Methods (3)
 
Following blinded assessments, cognitive status was recorded
 
 
Results – Longitudinal Analysis
 
Sample 1 microbleeds:
 
Microbleed Progression by Cognitive
Status
 
Probability Atlas of
microbleed distribution by
cognitive group
 
 Red indicates areas
prominently affected
 
SAMPLE 1:
Image analysis of
microbleeds
 
Results
Total B.G. Mineral deposition
 
BGMD Progression by Cognitive
Status
 
+ Predominant Iron and Calcium
 
Cognitively
Relevant atlas of
mineral
deposition
 
SAMPLE 1:
Image analysis of
total BGMD
 
Results
Cross Sectional Study
 
Sample 2: Microbleed Prevalence
 
 
Sample 2: Total BGMD followed the same pattern as the sample 1
 
Results – Cross Sectional Study
 
SAMPLE 2:
Image analysis of
total BGMD
 
Lack of association between microbleeds and cognitive decline in
AD (van der Vlies 
et al, 
2012)
Microbleeds increase in AD (Yates 
et al 
2014)
Insignificant BGMD results (
Valdés Hernández 
et al 
2012)
Similar pattern in serum and CSF (Lavados 
et al 
2008,
    Mueller 
et al 
2012)
Validation method showed ageing > TG alteration (Park 
et al, 
2014)
Power, Protocols, Risk Factors, Cognitive Decline
 
Discussion
 
Increased mineralisation and microbleed load amongst
patients from CN to LMCI and gradual decrease towards
AD could be of potential use as a differential indicator in
the diagnosis of AD
 
Conclusions
 
Microbleeds and BGMD may be useful indicators
of mild cognitive impairment.
Need to replicate this study in a larger sample +
follow progression over a longer time period.
Do microbleeds/BGMD disappear when LMCI
patients progress to AD/ if so why?
 
Conclusions
 
Glatz A, Bastin ME, Kiker AJ, Deary IJ, Wardlaw JM, & Hernández MCV (2015).  Automated
segmentation of multifocal basal ganglia T2*-weighted MRI hypointensities. 
NeuroImage 
105
, 
332-
346.
Lavados M, Guillón M, Mujica MC, Rojo LE, Fuentes P, Maccioni RB (2008). Mild cognitive
impairment and Alzheimer patients display different levels of redox-active CSF iron. 
J Alzheimers Dis
13(2)
, 225-32.
Mueller C, Schrag M, Crofton A, Stolte J, Muckenthaler MU, Magaki S, Kirsch W (2012). Altered
serum iron and copper homeostasis predicts cognitive decline in mild cognitive impairment. 
J
Alzheimers Dis
 
29(2)
, 341-50.
Park L, Koizumi K, El Jamal S, Zhou P, Previti ML, Van Nostrand WE, Carlson G, Iadecola C (2014).
Age-dependent neurovascular dysfunction and damage in a mouse model of cerebral amyloid
angiopathy. 
Stroke 
45(6)
,1815-21.
Valdés Hernández Mdel C, Maconick LC, Tan EM & Wardlaw JM (2012).  Identification of mineral
deposits in the brain on radiological images: a systematic review. 
Eur
 
Radiol
 
22(11)
, 2371-81.
van der Vlies AE, Goos JD, Barkhof F, Scheltens P, van der Flier WM (2012). 
Microbleeds do not affect
rate of cognitive decline in Alzheimer disease. Neurology 
79
, 763–769
Yates PA, Desmond PM, Phal PM, Steward C, Szoeke C, Salvado O, Ellis KA, Martins RN, Masters CL,
Ames D, Villemagne VL, Rowe CC & AIBL Research Group (2014). Incidence of cerebral microbleeds
in preclinical Alzheimer disease. 
Neurology
 
82(14)
, 1266-73
 
 
 
 
References
 
Validation
 
Images: L Clayson, MV 
Hernández
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Investigating the progression pattern of brain mineral deposition as a differential indicator of cognitive decline in individuals with varying cognitive statuses from normal to Alzheimer's disease. The study aims to develop improved imaging techniques and specific cognitive-relevant atlases to understand the distribution of mineral deposits and their impact on cognitive function. Utilizing advanced MRI data analysis and software tools, the research focuses on identifying distinctive patterns in mineral deposition associated with cognitive decline stages.

  • Brain Health
  • Cognitive Decline
  • Mineral Deposition
  • MRI Analysis
  • Alzheimers Disease

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  1. Progression pattern of brain mineral deposition as a differential indicator of cognitive decline L. Clayson1, M.C. Vald s Hern ndez2, A. Glatz2, J.M. Wardlaw2, J. Starr3 1College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, UK. 2 Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK 3Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, UK

  2. Background Image: L Clayson, mechanisms as reviewed in Moreno-Trevino et al 2015

  3. Background Brain glial cell regulation of iron Neurone Glial cell Ceruloplasmin bMVECs Hepcidin FPN Blood vessel Iron Image: L Clayson. Schematic representation of brain iron regulation mechanisms (as detailed in McCarthy & Kosman 2014). [FPN: Ferroportin, bMVECS: brain microvascular endothelial cells].

  4. Background Image: L Clayson. Schematic representation of mineral deposition mechanisms

  5. Hypotheses 1. There is a distinctive pattern of mineral deposition depending on the cognitive status (CN, MCI or AD) of patients 2. With cognitive decline, mineral deposition increases in regions know to be associated with increased amyloid deposition

  6. Aims To investigate the prevalence of basal ganglia mineral deposition (BGMD) and brain microbleeds in individuals of cognitive status ranging from CN to AD To improve our imaging techniques by developing a specific cognitively-relevant atlas of the distribution of mineral deposits with estimates of the main mineral content per region.

  7. Ultimately.. Is there a progression pattern of brain mineral deposition that can be used as a differential indicator of cognitive decline?

  8. Methods ADNI Database Selection Criteria: Sample 1: M.R.I. FLAIR, T2* & MPRAGE for 3 years Sample 2: MRI data for 1 year

  9. Methods (2) Semi-Automatic Software: - Analyze 11.0, MRIcron BGMD Measurements - Automatic Pipeline (Glatz et al, 2015) Microbleed Visual Assessments

  10. Methods (3) Following blinded assessments, cognitive status was recorded Patient Cognitive Status Assessment CN EMCI LMCI AD MMSE Score 24-30 24-30 24-30 20-26 CDR (Clinical Dementia Rating) 0.0 0.5 0.5 0.5/1.0 Wechsler Memory Scale Logical Memory II 16 years: 9 8-15 years: 5 0-7 years: 3 16 years: 9-11 8-15 years: 5-9 0-7 years: 3-6 16 years: 8 8-15 years: 4 0-7 years: 2 16 years: 8 8-15 years: 4 0-7 years: 2

  11. Results Longitudinal Analysis Sample 1 microbleeds: 18 16 14 12 Microbleed Count 10 8 6 4 2 0 Y1 Y2 Y3 Time Point

  12. Microbleed Progression by Cognitive Status

  13. SAMPLE 1: Image analysis of microbleeds Probability Atlas of microbleed distribution by cognitive group Red indicates areas prominently affected

  14. Results Total B.G. Mineral deposition 1200 Sample 1: Progression of Total BGMD Volume 1000 Total BGMD Volume 800 600 400 200 0 Y1 Y2 Y3 Timepoint

  15. BGMD Progression by Cognitive Status + Predominant Iron and Calcium

  16. SAMPLE 1: Image analysis of total BGMD Cognitively Relevant atlas of mineral deposition

  17. Results Cross Sectional Study Sample 2: Microbleed Prevalence

  18. Results Cross Sectional Study Sample 2: Total BGMD followed the same pattern as the sample 1

  19. SAMPLE 2: Image analysis of total BGMD

  20. Discussion Lack of association between microbleeds and cognitive decline in AD (van der Vlies et al, 2012) Microbleeds increase in AD (Yates et al 2014) Insignificant BGMD results (Vald s Hern ndez et al 2012) Similar pattern in serum and CSF (Lavados et al 2008, Mueller et al 2012) Validation method showed ageing > TG alteration (Park et al, 2014) Power, Protocols, Risk Factors, Cognitive Decline

  21. Conclusions Increased mineralisation and microbleed load amongst patients from CN to LMCI and gradual decrease towards AD could be of potential use as a differential indicator in the diagnosis of AD LMCI EMCI AD CN

  22. Conclusions Microbleeds and BGMD may be useful indicators of mild cognitive impairment. Need to replicate this study in a larger sample + follow progression over a longer time period. Do microbleeds/BGMD disappear when LMCI patients progress to AD/ if so why?

  23. References Glatz A, Bastin ME, Kiker AJ, Deary IJ, Wardlaw JM, & Hern ndez MCV (2015). Automated segmentation of multifocal basal ganglia T2*-weighted MRI hypointensities. NeuroImage 105, 332- 346. Lavados M, Guill n M, Mujica MC, Rojo LE, Fuentes P, Maccioni RB (2008). Mild cognitive impairment and Alzheimer patients display different levels of redox-active CSF iron. J Alzheimers Dis 13(2), 225-32. Mueller C, Schrag M, Crofton A, Stolte J, Muckenthaler MU, Magaki S, Kirsch W (2012). Altered serum iron and copper homeostasis predicts cognitive decline in mild cognitive impairment. J Alzheimers Dis29(2), 341-50. Park L, Koizumi K, El Jamal S, Zhou P, Previti ML, Van Nostrand WE, Carlson G, Iadecola C (2014). Age-dependent neurovascular dysfunction and damage in a mouse model of cerebral amyloid angiopathy. Stroke 45(6),1815-21. Vald s Hern ndez Mdel C, Maconick LC, Tan EM & Wardlaw JM (2012). Identification of mineral deposits in the brain on radiological images: a systematic review. EurRadiol22(11), 2371-81. van der Vlies AE, Goos JD, Barkhof F, Scheltens P, van der Flier WM (2012). Microbleeds do not affect rate of cognitive decline in Alzheimer disease. Neurology 79, 763 769 Yates PA, Desmond PM, Phal PM, Steward C, Szoeke C, Salvado O, Ellis KA, Martins RN, Masters CL, Ames D, Villemagne VL, Rowe CC & AIBL Research Group (2014). Incidence of cerebral microbleeds in preclinical Alzheimer disease. Neurology82(14), 1266-73

  24. Validation Images: L Clayson, MV Hern ndez

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