Cognition and hypertension in midlife evidence for gene environment interplay
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Cognition and Hypertension in Midlife: Evidence for Gene-Environment Interplay. Terrie Vasilopoulos University of Chicago Demography Workshop 01/10/13. Cognitive performance across the lifespan. Hedden & Gabrieli (2004) Nature Reviews Neuroscience , 5 , 87-96.

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Cognition and Hypertension in Midlife: Evidence for Gene-Environment Interplay

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Cognition and hypertension in midlife evidence for gene environment interplay

Cognition and Hypertension in Midlife: Evidence for Gene-Environment Interplay

Terrie Vasilopoulos

University of Chicago

Demography Workshop

01/10/13


Cognitive performance across the lifespan

Cognitiveperformance across the lifespan

Hedden & Gabrieli (2004) Nature Reviews Neuroscience, 5, 87-96


Heritability of cognition across the lifespan

Heritability of cognition across the lifespan

Haworth et al. (2010); Grant et al. (2010); McClearn et al. (1998)


Behavioral genetics

Behavioral Genetics

  • Understand individual differences in traits

  • Decompose phenotypic variation into 3 components:

  • A  additive genetic

    • Genetic influences shared between relatives

  • C  shared environment

    • Non-genetic factors that make relatives similar

  • E  non-shared environment

    • Non-genetic factors that make relatives dissimilar


Behavioral genetics1

Behavioral Genetics

  • Twins studies  one of the most common behavioral genetic designs

  • Monozygotic twins (MZ)  Identical

  • Dizygotic twins (DZ)  Fraternal

  • A  additive genetic

    • MZ = 100%, DZ = ~50%

  • C  shared environment

    • MZ & DZ = 100%

  • E  non-shared environment

    • MZ & DZ = 0%

  • Other sibling/family structures can be used following similar assumptions


Twin method

Twin Method

1.0 MZ/0.5 DZ

1.0 MZ/1.0 DZ

A

A

C

E

A

C

E

a

c

e

a

c

e

P Twin 1

P Twin 2

P = A + C + E

Var(P) = a2+c2+e2

** Heritability (h2) = A/P **


Extensions of twin method

Extensions of Twin Method

  • Multivariate Relationships

  • Longitudinal Change

  • Sex Differences

  • Gene-Environment Interactions/Interplay (GxE)

    • How do genetic influences (heritability) differ across various environments?


Theories of gene environment interplay

Theories of Gene-Environment Interplay

  • Bioecological modelpredicts that adverse environments suppress “genetic potential” (Brofenbrenner and Ceci, 1994)

    • Other early theories of gene-environment interplay suggest genetic differences enhanced in “good enough” environments (Scarr, 1992)

  • Diathesis-Stress model predicts the opposite, with genetic influences greater in high risk environments (Gottesman, 1991)


Cognition and hypertension in midlife evidence for gene environment interplay

Lifestyle Health

Genes

Cognition


Gxe interactions for cognition

GxE Interactions for Cognition:

Child and Adolescent Cognition


Gxe interactions for cognition child and adolescence

GxE Interactions for Cognition: Child and Adolescence

  • Rowe, Jacobson and van den Oord (1999)

    • Moderating effects of family “environment” on heritability of cognitive ability

      • Vocabulary IQ

      • Parental education level

    • Used data from twins, full-, half-, and unrelated siblings, and cousins from the AddHealth Study

    • Found that genetic variance ↑, and shared environmental variance ↓, among adolescents with more highly educated parents


Gxe interactions for cognition child and adolescence1

GxE Interactions for Cognition: Child and Adolescence

Rowe et al. (1999) Child Development


Gxe interactions for cognition child and adolescence2

GxE Interactions for Cognition: Child and Adolescence

  • Turkheimer et al. (2003)

    • Full-Scale IQ, Verbal IQ and Performance IQ

    • 7 year olds

    • Parental education, income and occupation

  • Harden et al. (2006)

    • National Merit Scholar Qualification Test

    • 17 year olds

    • Parental education and Income

  • Friend et al. (2008)

    • Reading Disability

    • 8-20 years

    • Parental Education


Gxe interactions for cognition1

GxE Interactions for Cognition:

Childhood SES Adult Cognition


Gxe interactions for cognition childhood ses adult cognition

GxE Interactions for Cognition: Childhood SES Adult Cognition

  • Kremen et al. (2005)

    • Middle-Aged Male twins (51-60 yrs) from Vietnam-Era Twin Study of Aging (VETSA)

    • Verbal Ability

    • Parental Education

    • ↓ shared environmental variance with ↑ parental education

    • Stable genetic variance

    • no direct genetic moderation


Gxe interactions for cognition childhood ses adult cognition1

GxE Interactions for Cognition: Childhood SES Adult Cognition

Kremen et al. (2005) Behavior Genetics


Gxe interactions for cognition childhood ses adult cognition2

GxE Interactions for Cognition: Childhood SES Adult Cognition

  • van der Sluis et al. (2008)

    • FSIQ

    • Shared environmental variance of IQ moderated by parental education

    • Stable genetic variance

    • no genetic moderation

    • Men  mean age 49 yrs (36-69 yrs)

  • Grant et al. (2010) - VETSA

    • general cognitive ability

    • ↑ total variance due to parental education

    • no genetic moderation


Gxe interactions for cognition2

GxE Interactions for Cognition:

Adult SES Adult Cognition


Gxe interactions for cognition adult ses adult cognition

GxE Interactions for Cognition: Adult SES Adult Cognition

  • van der Sluis et al. (2008)

    • FSIQ

    • ↑ non-shared environmental variance with higher mean real estate prices of participants’ residential area

    • Stable genetic variance

    • no genetic moderation

  • Vasilopoulos et al. (unpublished)

    • General Cognitive Ability - VETSA

    • Non-shared environmental variance moderated by individuals lifetime education

    • Stable genetic variance

    • no genetic moderation


Developmental differences in gxe

DevelopmentalDifferences in GxE?

  • Prior research suggests that the moderating effects of childhood family environments (e.g., family socioeconomic status) may not have lasting effects on genetic variance in adult cognition

  • Lack of evidence for genetic moderation by adult SES

  • Are there other adult environmental or behavioral factors that enhance or suppress genetic variance in cognition?


Physical health and cognition

Physical Health and Cognition

  • Many physical factors associated with cognitive function

    • Pulmonary function

    • Grip strength

    • Physical fitness

    • Bioage

  • Physiological factors  gene expression in brain

    • Caloric restriction

    • Exercise

    • Diet

Chyou et al. (1996); Alfaro-Acha et al. (2006); Anstey and Smith (1999); Macdonald et al. (2004); Salthouse et al. (1998); Johnson et al. (2009); Emery et al. (1998); Cotman & Berchtold (2002); Kitajka et al. (2002); Weindruch et al. (2002)


Hypertension and cognition

Hypertension and Cognition

  • Hypertension linked to poorer cognitive function

  • Stampfer (2006); Birns & Kalra (2008); Singh-Manoux & Marmot (2005); Knecht et al. (2009); van den Berg et al. (2009)


Antihypertensive medication

Antihypertensive medication

  • Many studies adjust for antihypertensive medication use

  • Evidence for direct influence on cognition

    • 36% reduced odds of cognitive impairment

    • 8% reduction in dementia risk

  • Murray et al. (2002); Haag et al. (2009)


Study objectives

Study Objectives

  • Examine the extent that hypertension modifies the influence of genetic and environmental factors on cognition at midlife

  • Assess how antihypertensive medication use alters the effect of hypertension on cognition


Methods

Methods


Sample and procedures

Sample and Procedures

  • Vietnam-Era Twin Study of Aging (VETSA)

    • longitudinal study of cognition and aging, beginning at midlife

    • nationally representative, male-male twin pairs from VET Registry

    • 1237 individuals (Wave 1)

      • 697 MZ, 540 DZ

    • Twins traveled to either University of California, San Diego or Boston University for day-long testing session

      • Assessments of cognitive performance and physical health

    • Age: 55.4 years old (51-60 years)

    • Wave 2 ongoing through 2013


Measures blood pressure

Measures: Blood Pressure

  • Mean of 4 measurements taken during day-long testing session

  • Three blood pressure groups:

  • Non-hypertensive: n = 548 (44.4%)

    • systolic/diastolic < 140/90 mm hg

  • Medicated Hypertensive: n = 422 (34.2%)

    • diagnosed hypertensive with self-reported use of antihypertensive medication

  • Unmedicated Hypertensive: n = 265 (21.4%)

    • systolic ≥ 140 mm hg or diastolic ≥ 90 mm hg, untreated by antihypertensive medication


Measures cognition

Measures: Cognition

  • Standardized composites of separate cognitive tests were used to construct domains

    • Visual Spatial Ability (Hidden Figures, Card Rotation)

    • Episodic Memory (Logical Memory, Visual Reproduction)

    • Abstract Reasoning (Matrix Reasoning)

    • Processing Speed (Trails 2 & 3, Stroop Word)

    • Executive Function (Trails 4, Verbal Fluency)

    • Working Memory (Digit and Spatial Span Backward, Letter-Number Sequencing)

    • Short Term Memory (Digit and Spatial Span Forward)

    • Verbal Ability (Vocabulary)

    • Verbal Fluency(Category Fluency)

    • General Cognitive Ability Armed Forces Qualification Test (AFQT)


Analysis multiple group approach to test for gxe

Analysis: Multiple Group approach to test for GxE

  • Split the sample into three groups based on blood pressure and antihypertensive medication use

    • Non-hypertensive (Non)

    • Medicated Hypertensive (Med)

    • Unmedicated Hypertensive (Unmed)

  • Assigned each twin to a blood pressure group (Non, Med, or Unmed)

    • Created data groups that included twins concordant and discordant for BP group status

    • Use these data groups to estimate genetic and environmental variance for each BP group


Cognition and hypertension in midlife evidence for gene environment interplay

Non-Hypertensives

Non-Hypertensives

Medicated Hypertensives

Medicated Hypertensives

Unmedicated Hypertensives


Model fitting

Model Fitting

  • Baseline model ACE allowed to differ among BP groups

  • Submodels

    • Non = Med

    • Non = UnMed

    • Med = UnMed

  • Compare model fits using difference -2 Log Likelihood

    • Follows a chi-square (X2) distribution

    • Significant X2 indicates ACE cannot be equated

      • ACE across BP are significantly different


Results

Results


Bp demographics across groups

BP & demographics across groups

*significant differences across BP groups, subsequent analyses adjusted for these variables


Mean differences across bp groups

Mean differences across BP groups

  • No mean level differences in cognition due to blood pressure group

*all cognitive measures were standardized prior to analysis


Univariate heritability estimates no moderation

Univariate heritability estimates(no moderation)


Non hypertensives medicated hypertensives

Multiple Group Analysis

Non-Hypertensives = Medicated Hypertensives


Non hypertensives unmedicated hypertensives

Multiple Group Analysis

Non-Hypertensives = Unmedicated Hypertensives

  • Visual Spatial Ability

    • χ2 = 5.90, df = 2, p = 0.05

  • Episodic Memory

    • χ2 = 9.32, df = 2, p = 0.01

  • Support for both GxE and ExE


Medicated hypertensives unmedicated hypertensives

Multiple Group Analysis

Medicated Hypertensives = Unmedicated Hypertensives

  • Visual Spatial Ability

    • χ2 = 7.45, df = 2, p = 0.02

  • Episodic Memory

    • χ2 = 9.35, df = 2, p = 0.01

  • Support for both GxE and ExE


Non medicated hypertensives unmedicated hypertensives

Multiple Group Analysis

Non & Medicated Hypertensives = Unmedicated Hypertensives


Heritability of cognition is lower in unmedicated hypertensives vs non medicated hypertensives

Heritability of cognition is lower in Unmedicated Hypertensives vs. Non & Medicated Hypertensives

E

A

A

A

E

E

A

E

h2 = 0.75 vs. h2 = 0.55

h2 = 0.61 vs. h2 = 0.25


Summary and conclusions

Summary and Conclusions


Summary of results

Summary of Results

  • No mean differences due to blood pressure group

  • Heritability estimates were lower in unmedicated hypertensives versus non-hypertensives/medicated hypertensives

    • Visual Spatial Ability

    • Episodic Memory

  • Heritability estimates could be equated between non-hypertensives and medicated hypertensives


Why are results domain specific

Why are results domain-specific?

  • Visual spatial ability and episodic memory are some of the first processes affected by AD and aging

  • Hypertension-related cognitive deficits most often reported in memoryprocesses


Cognition and hypertension in midlife evidence for gene environment interplay

Why might we see differences in genetic effects prior to performance differences?

  • Blalock et al. (2003)

**Genetic changes may be a measurable precursor to observed cognitive changes**


Medication as a buffer against adverse effects

Medication as a buffer against adverse effects

  • Bioecological model and “good enough” environments hypothesis

  • Untreated hypertension may be viewed as a poor “internal environment”

  • Medication use returns internal environment to a more favorable state


Conclusions

Conclusions

  • Heritability of cognition is dynamic

  • Early life experiences childhood and adolescence cognition

    • Not present in our sample of middle-aged men

  • Physical health  adult cognition

    • Untreated hypertension moderates genetic and environmental influences of cognition in midlife

  • Developmental differences in what types of environments influence genetic factors underlying cognition

  • Future GxE studies of cognition need to take a developmentally driven approach


Acknowledgements

Acknowledgements

Vasilopoulos et al. (2012). Untreated Hypertension Decreases Heritability of Cognition in Late Middle Age. Behavior Genetics. DOI: 10.1007/s10519-011-9479-9

  • University of Chicago

    • Kristen C. Jacobson

  • University of California, San Diego

    • William S. Kremen

    • Carol E. Franz

    • Matthew S. Panizzon

    • Kathleen Kim

  • Washington University School of Medicine

    • Phyllis K. Stein

  • Saint Louis University

    • Hong Xian

  • Boston University

    • Michael J. Lyons

    • Michael D. Grant

    • Rosemary Toomey

  • Virginia Commonwealth University

    • Lindon J. Eaves

  • Funding

    • NIH/NIA (F32 AG039954. R01 AG018386, R01 AG018384, R01 AG022381, and R01 AG022982)


Thank you

Thank you!


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