dementias and childhood associations
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Childhood associations of late-life
deficits in cognitive functions
Dorota ChapkoPostdoctoral Research Fellow, Aberdeen Biomedical Imaging Centre
Royal College of General Practitioners, London
Dementias 2017
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BackgroundCognitive functions over the lifespan & cognitive resilience
Maximizing cognitive functions across the lifespan
Aging
Walker SP et al The Lancet 2011
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The Barker’s Hypothesis The Developmental Origins of Health and Disease (DOHaD)
• Low-nutrient intrauterine environment
• Anticipation of limited resources
• Adaptation to suboptimal conditions
• Physiology and morphology reprogramming
• Growing up in the world of plenty
• Mismatch between the environments
• “Compensatory growth”
• Costs: chronic conditions in late-life (DOBHaD)
Barker DJ International Journal of Epidemiology 2002
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The Barker’s Hypothesis Suboptimal intrauterine environment may result in brain dysfunctions in late-life
The brain is extremely vulnerable to a
suboptimal environment in the womb.
Developmental Origins of Behaviour, Health and Disease
(DOBHaD)
Developmental Origins of Health and Disease
(DOHaD)
Giussani, DA Proceedings of the National Academy of Sciences 2011; Van Den Bergh BR Developmental Medicine & Child Neurology 2011
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The Aberdeen Children of the 1950s Study (ACONF)
Life-course determinants of cognitive functions in late-life (n = 12,150)
DATA LINKAGE:
In 2001 over 11,000 of the original
participants were traced followed by
a questionnaire survey with a 63%
response rate.
A subset of > 500 ACONF
participants was recruited in 2010-
2011 as the Aberdeen sample for
Generation Scotland – Scottish
Family Health Study (GS:SFHS).
Analytical
Sample
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MethodsCognitive functions in childhood and mid-life
Cognitive tests routinely used in Aberdeen schools in the 1950s and 1960s:
Cognitive tests at mid-life as part of the Generation Scotland – Scottish Family Health Study:
Batty GD et al Paediatric and Perinatal Epidemiology 2004; Marioni RE et al Behavior Genetics 2014
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Methods
• The relationship between birthweight and cognitive functions from childhood to mid-life based on the repeated measures (at ages 7, 9, 11 and 51-61 years)
• Birth weight categorized into 3 groups:
• Low (< 2.49 kg)
• Normal (2.49 kg ≤ BW < 4.08 kg)
• High (≥ 4.08 kg)
• Cases with complete covariates
• Linear regression:
• Unadjusted
• Adjusted for:
• Childhood: sex, father’s social class, mother’s age
• Mid-life: in addition age at test
Chapko et al. Digital Health 2016
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ResultsBirth Weight – Adjusted Analysis
Cognition
Childhood Coeff. SE P Coeff. SE P
Childhood IQ age 7 (n=431) -11.48 3.74 0.002 -6.01 2.52 0.018
Childhood IQ age 9 (n=428) -6.55 3.97 0.099 -8.12 2.77 0.003
Childhood IQ age 11 (n=364) -1.87 2.95 0.526 -0.94 2.06 0.649
Mid-life Coeff. SE P Coeff. SE P
VerbalFluency (n=391) -2.39 3.26 0.464 0.13 2.26 0.954
MillHillVocabulary (n=389) -1.15 1.22 0.348 -1.30 0.84 0.125
LogicalMemory (n=390) -2.60 1.28 0.044 -1.08 0.89 0.225
DigitSymbol (n=389) -9.66 3.86 0.013 0.86 3.86 0.748
Mean differences in cognitive scores by birthweight group compared with normal
birthweight group (2.49 kg≤BW<4.08 kg) Adjusted
Low Birthweight <2.49 kg High Birthweight ≥ 4.08 kg
Chapko et al. Digital Health 2016
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Results Gestational Age – Adjusted Analysis
Cognition
Childhood Coeff. SE P Coeff. SE P
Childhood IQ age 7 (n=431) -11.07 3.76 0.003 -0.13 1.57 0.932
Childhood IQ age 9 (n=428) -9.35 4.11 0.024 -1.74 1.74 0.316
Childhood IQ age 11 (n=364) -3.82 3.05 0.212 -0.05 1.33 0.971
Mid-life Coeff. SE P Coeff. SE P
VerbalFluency (n=391) -3.90 3.26 0.231 -0.43 1.40 0.760
MillHillVocabulary (n=389) -1.06 1.22 0.386 0.07 0.53 0.901
LogicalMemory (n=390) -3.81 1.28 0.003 -0.78 0.55 0.158
DigitSymbol (n=389) -10.31 3.85 0.008 1.95 1.65 0.240
Preterm Birth < 37 weeks Post-term Birth ≥ 42 weeks
Mean differences in cognitive scores by gestational age group compared with birth at
term (term 37 wk 0 d - 41 wk 6 d) Adjusted
Chapko et al. Digital Health 2016
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Birth Weight - Conclusions • In this sample, the effect of low birth weight and
preterm birth on cognitive functions lasts until mid-life and is not completely eliminated.
• Infants at the highest risk of poor outcomes were the most affected by cognitive ageing.
• The concurrent low-birth weight & preterm infants were the most disadvantaged and drove the statistical association of adverse cognitive outcomes in mid-life.
• Certain areas of mental function in later life might be differentially affected by poor growth in utero.
• Fluid cognitive abilities, more sensitive to ageing processes, potentially affected the most.
Chapko et al. Digital Health 2016
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1936 Aberdeen Birth CohortThe effects of childhood IQ and occupational profile on the triad of impairment in late-life
Chapko et al. Age and Ageing 2016
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1936 Aberdeen Birth CohortChildhood IQ is the predominant influence on the triad of impairment in late-life
• All relationships significant, good model fit
• Childhood IQ had a total standardised regression
weight of .71 of which .58 was direct and .13 indirect
Chapko et al. Age and Ageing 2016
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Cognitive ReserveA form of cognitive resilience
AtrophyWMH
Decline Resilience
Education
Occupation
Max life-time cognition
Murray AD et al Brain 2011; Staff RT et al Brain 2004; Stern Y The Lancet Neurology 2012.
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Cognitive ReserveA form of cognitive resilience
COGNITIVE RESERVE THEORY posits that structural or functional features of the brain allow individuals to maintain normal functioning despite accumulating brain pathology.
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Systematic Literature ReviewLife-course determinants of reserve in cognitive aging
Search
• Databases: Medline, Embase, PsycheInfo
• Strategy: the synonyms of CR
Eligibility
• CR applied to 4 most common dementia types, MCI or healthy aging
• Proper definition of CR in the design; the 3 CR components stated upfront
Screening• Two independent reviewers (D Chapko and R McCormack)
Extraction• Performed by DC, checked by RM
Results• A qualitative synthesis of the results
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Systematic Literature ReviewLife-course determinants of reserve in cognitive aging
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Literature Review Results39 studies out of 9,229 screened records met our inclusion criteria
Future directions:
• specific features of the identified factors such as education, occupation
• interactions between education/occupation/pre-morbid IQ in providing reserve
• other more diverse aspects of early-life environment
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Aberdeen Birth Cohort 1936 Childhood socioeconomic circumstance and brain MRI
Age 68y(2004)
‘+/- Risk’ Cognitive ability
Moray House Test
11y‘Early life’(~1936)Life Stage Adult Life
EducationAdultSEC
Hypertension
HighestQualification
AdultOccupation
Measuredor Historic
SocioeconomicCircumstance
(SEC)
ABC
1936
Data
Paternal Occupation
Staff RT et al. Annals Neurol. 2012: ; 71:653–660.
Cognitive ability
Fluid intelligence
-
Raven’s Progressive
Matrices
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Aberdeen Birth Cohort 1936 Childhood socio-economic status and late-life brain volume measures
Staff RT et al. Annals of Neurology 2012
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Aberdeen Birth Cohort 1936 Childhood socio-economic circumstances and late-life brain pathology
Murray AD et al. PLoS ONE 2014;9(2): e 88969
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CR in Aberdeen Birth Cohort 1936 Murray AD et al., 2011 in Brain
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CR in Aberdeen Birth Cohort 1936
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Summary Results
• Educational attainment, but not occupation,
has a positive effect (b + 0.23) on late life
cognitive ability allowing for childhood
intelligence, WMH and atrophy
• This is greater than the negative impact of
either WMH (b - 0.14) or hippocampal
atrophy (b - 0.20) alone and similar to their
combined effect
Murray AD et al. Brain 2011
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Conclusions
• Brain scan measures of hippocampal atrophy and WMH have negative influence on late life fluid intelligence, allowing for childhood intelligence
• Educational achievement acts as independent contributor to cognitive reserve
• This positive influence enables retention of fluid intelligence in spite of negative influence of brain WMH and lower hippocampal volume
• Subclinical brain pathology balanced by brain experience during life
Murray AD et al. Brain 2011
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Cognitive resilience to ageing brain
Early-life factors are important!
Environment In Utero
Early-life Factors
Mid-life Factors
Late-life Factors
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Policy Implications The importance of brain development and its implications on public policy in low-resource settings
Intrauterine & Early-life Factors
Childhood Cognitive
Trajectories
Late-life Cognition
Mid-life Cognition
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Policy Implications Early Childhood Development and Skills across the Life-course through the Lens of the Developing Brain
Chapko Health, Nutrition and Population Discussion Paper World Bank 2015.
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Acknowledgements
University of Aberdeen:
Prof. Alison Murray
Prof. Corri Black
Dr. Roger Staff
Dr. Chris McNeil
Dr. Anca-Larisa Sandu
Dr. Karen McArdle
Prof. Lawrence Whalley
Dr. Leila Eadie
Ms. Heather Clark
Collaborators:
Joost de Laat
Julieta Trias
Aliza Marcus
Omar Arias
Emanuela Galasso
Sophie Naudeau
Dr. Robin Hill (UoE)
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Acknowledgements
Funders:
Collaborators:
Cohorts:
ACONF 1950s
ABC 1936
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• Dorota Chapko, 2015. Early childhood development and cognitive & socio-emotional skills across the life-course through the lens of the developing brain. Health, Nutrition and Population Discussion Paper. World Bank, Washington DC (IO#2086142).
• Chapko D, Staff RT, McNeil CJ, Whalley LJ, Black C, Murray AD (2016). Late life deficits in cognitive, physical and emotional functions, childhood intelligence and occupational profile: A life-course examination of the Aberdeen 1936 Birth Cohort (ABC1936). Age & Ageing.
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Q&A & Thank You!