Unlocking the Genetics of Vascular Cognitive Impairment

Unlocking the Genetics of
Vascular Cognitive Impairment
Session: Advances in Stroke Genetics:
The American Stroke Association – Bugher Foundation
Centers for Stroke Prevention Research
Sudha Seshadri, MD
Professor of Neurology, Boston University School of Medicine
Senior Investigator, The Framingham Heart Study

Vascular Cognitive Impairment (VCI)
• Substantial individual risk and public health burden
• 1 in 3 persons aged 65 will develop stroke, dementia
or both
• Proportion of all dementia varies: 15-50%
Schrijvers E M et al., Stroke 2012;43:315-319
Skoog I et al., NEJM 1993; 328:153-8.

Outline
• VCI has a genetic basis
• Phenotype remains hard to define
• GWAS approaches
• Candidate Gene approaches
• Next Steps

Stroke and Dementia are Heritable
• Dementia
– (60-80% in twin studies)
• Stroke
– (20-30% in twin studies)
Gatz M et al., Arch Gen Psychiatry 2006
Bak S et al., Stroke 2002
Heritability of VaD in FHS ~30% using ADDTC defn.
• Parental dementia impairs offspring verbal memory
• Parental stroke impairs offspring visual memory
Debette et al., Neurology, 2009;73:2071; Weinstein et al., ISC 2012

Unlocking the Genetics of VCI
• Improve understanding of biology
• Permit more effective, targeted 1ºry and 2ºry prevention
• New preventive, treatment modalities

Approach to Genetics of
Vascular Cognitive Impairment
• Define the phenotype (s) of interest
– ‘Vascular Dementia’

Clinical Criteria to Define VaD
• Hachinski Ischemic Score (HIS)
• Diagnostic and Statistical Manual (DSM- III, IIIR, IV) criteria
• International Classification of Disease (ICD)-10
• California Alzheimer’s Disease Diagnostic and Treatment
Centers (ADDTC) criteria
• National Institute for Neurological Diseases and Stroke-
Association Internationale pour la Recherche et
‘Enseignement en Neurosciences (NINDS-AIREN) criteria
Κ=0.76

Clinical Criteria for
Vascular Dementia
Sensitivity Specificity
DSM-IV 0.5 0.84
ADDTC-possible 0.7 0.78
NINDS-AIREN-possible 0.55 0.84
ADDTC-probable 0.2 0.91
NINDS-AIREN-probable 0.25 0.93
ICD-10 0.2 0.94

VCI: The Inclusive Definition
• Cognitive or behavioral problems
• Disease affecting blood vessels or blood flow to
part or all of the brain
• Evidence of damage to part or all of brain due to
vascular factors

• Vascular Dementia
VCI is Heterogenous
– Following clinical strokes
– Extensive small vessel disease (covert infarcts, WMH)
– Specific arteriopathies
– Amyloid angiopathy & multiple microbleeds
• Contribution of vascular factors to AD
• Vascular Mild Cognitive Impairment (VaMCI)

Approach to Genetics of
Vascular Cognitive Impairment
• Define the endophenotype (s) of interest
– ‘Vascular Dementia’
– Dementia/Cognitive function after Stroke
– Cognitive function and decline
– Imaging correlates of VCI (MRI infarcts, WMH)
– Neuropathological Indices of Vascular Brain Injury

Approach to Genetics of VCI
• May need complementary approaches
• Should persons with AD pathology be included
as cases/ controls/ excluded?

Approach to Genetics of
Vascular Cognitive Impairment
• Explore various approaches to gene discovery
– GWAS
– Candidate Genes
– Whole exome, Whole genome & Targeted sequencing
for rare variants
– Mitochondrial Inheritance - Copy Number Variants
– Telomere length - Epigenetics

GWAS Approaches to VCI

A, Genome-wide association plot (Manhattan plot) showing all single-nucleotide
polymorphisms with their respective chromosome and position on the X-axis plotted against
their association probability value on the Y-axis.
Copyright © American Heart Association
Schrijvers E M et al. Stroke 2012;43:315-319

Cohorts for Heart and Aging
Research in Genomic Epidemiology
(CHARGE) Consortium
http://depts.washington.edu/chargeco/wiki/Main_Page

Overview of CHARGE
• CVD/Aging cohorts with GWAS data
– ARIC, CHS, AGES, ASPS, FHS and Rotterdam
– PHENOTYPE HARMONIZATION
– Sharing of within-study analyses results for crossstudy
prospective meta-analysis
– Imputation to HapMap permitted meta-analyses
despite use of different platforms in each study
-- Austrian Study of Stroke Prevention (ASPS)

GWAS of ‘All dementia’ (AD+ VaD) in CHARGE
Results similar to AD;
Few loci showing stronger associations with all dementia than
AD: e.g. LPL, although this has also been associated with AD

Log 10 (p)
GWAS of Covert Brain Infarcts in CHARGE
p = 5 x 10-8
p = 5 x 10-7
Chromosome
MACROD2
FLRT3
Debette S et al., Stroke 2010; 41:210-217.

GWAS of White Matter Hyperintensities in CHARGE
N=12,385
17q25: rs3744028, P=4.0x10 -15 ; rs1055129, P=2.6x10 -11
Fornage et al., Ann Neurol. 2011;69:928-939.
TRIM65, TRIM 47, FBF1, WBP2

MYO1B
GWAS of Cognitive Speed in CHARGE
Trails A
rs11739440
5439 persons, age 45+
Ibrahim et al., Presented at ICAD, Paris, 2011

GWAS of Cognitive Processing Speed Ability in CHARGE
Digit-Symbol and Letter-Digit Substitution Tests
N=32,900 persons over age 45 in 20 cohorts
chromosome: 11; Location: 11q23
rs12363125
P = 4.72E-007
Ibrahim et al., Presented at ICAD, Paris, 2011
25

Candidate Gene Approaches
to VCI

Candidate Gene Approaches to VCI
• Limited by known biology
• Would not target intergenic regions
• Fewer hypotheses, greater power with smaller
samples

Candidate Gene Approaches
– Genes determining Brain reserve, response to injury
• (APOE, VLDLR, BDNF)
– Stroke genes
– AD genes
– Monogenic disorder genes
• NOTCH3 (CADASIL)
• HTRK1 (CARASIL)
• TREX1 (RVCL) COL4A1 (SVD)

HR of 2.3 associated with ≥1 APOE ε4 allele for non-AD dementias.

GWAS of Stroke in the CHARGE Consortium
Results of Tests for the Association between Stroke and Each SNP
Ikram M et al. N Engl J Med 2009;10.1056/NEJMoa0900094

Associations in the Region Centered on rs11833579 and Containing NINJ2
Ikram M et al. N Engl J Med 2009;10.1056/NEJMoa0900094
Ninjurin-2: Transmembrane protein in
the “nerve-injury-induced protein” family

NINJ2 and recurrent stroke, mortality
765 patients with incident ischemic stroke &
977 age-matched community controls
Mean age: 62.8 ± 12.2 yrs
765 cases, 977 community controls, enrolled day of stroke
HR Enrolled for combined at outcome 0.89 ± of 1.7 recurrent days stroke, after mortality: stroke
2.85 (1.34-6.06); p=0.007
rs12425791 was associated with ischemic stroke
(OR=1.67, 95%CI=1.05-2.66, p=0.031)
TAIWAN STROKE GENETICS CONSORTIUM Hsieh et al., J Biomed Sci 2012

).
Inverse Association with Memory
• NINJ2 (rs11833579 )
– Associated with memory decline (p=9x10 -5 ) &
– With AD susceptibility
– In Religious Orders Study/ Memory and Aging Project
(p=0.001)
– In CHARGE (p=0.02).
Shulman et al., ICAD, 2012

GWAS of Stroke
• 2 prior GWAS: 1 did not find any SNP reaching
genome-wide significance
PITX2
• Another related an Afib associated SNP to
cardioembolic stroke

Stroke Genes (SNPs) associated with poorer cognitive function
2493 persons with GWAS and cognitive testing in the Framingham Study
Trails A and B, Visual Reproductions, Hooper, Verbal Fluency
SNPID chr Gene Cognitive Phenotype p-value
rs2200733 4 PITX2 Trails A
Visual memory
Verbal Fluency
rs7193343 16 ZFHX3 Hooper visual organization
Verbal Fluency
0.02
0.03
0.02
0.01
0.04

New Late-Onset AD Genes
• Chr 1: ` CR1: Complement component (3b/4b) receptor 1
• Chr 2: BIN1: Bridging integrator 1
• Chr 6: CD2AP: CD2 associated protein
• Chr 7: EPHA1: Ephrin 1
• Chr 8: CLU/APOJ: Clusterin
• Chr 11: MS4A: membrane-spanning 4-domains, subfamily A, member 4
PICALM: Phosphatidylinositol binding clathrin assembly protein
• Chr 19: APOE/TOMM40/APOC1
• CD33
ABCA7: ATP-binding cassette, sub-family A

AD Genes (SNPs) associated with poorer cognitive function
2493 persons with GWAS and cognitive testing in the Framingham Study
Trails A and B, Visual Reproductions, Hooper, Verbal Fluency
SNPID chr Gene Cognitive
Phenotype
p-value
rs11136000 8 CLU Hooper 0.02
rs744373 2 BIN1 Trails B-A
Visual Memory
0.04
0.02
rs3764650 19 ABCA7 Hooper 0.03

Braskie et al., 2011

Common SNPs in NOTCH3 were associated with WMH
among hypertensives in CHARGE

Approach to Genetics of
Vascular Cognitive Impairment
• Explore various approaches to gene discovery
– GWAS
– Candidate Genes
– Whole exome, Whole genome & Targeted sequencing
for rare variants
– Mitochondrial Inheritance - Copy Number Variants
– Telomere length - Epigenetics

Mitochondrial Stroke Genetic Risk Score was also associated with WMHV in 792 persons with MRI

Summary, Next Steps
• A multi-pronged approach will be required using
case-control series & cohorts for genetics of
– cognitive performance in persons with stroke
– VaD and vMCI defined broadly
– Structural correlates of VCI

Summary, Next Steps
• Iterative Process
Molecular
biology,
other
genes in
pathway
Structural
and
functional
effects
Identify
putative
VCI genes

Framingham Neurology Research Team
• Philip A. Wolf, MD
• Sudha Seshadri, MD
• Rhoda Au, PhD
• Margaret Kelly-Hayes, DEd RN
• Carlos S. Kase, MD
• Sanford F. Auerbach, MD
• Ann McKee, MD
• Ivana Delalle, MD, PhD
• Jose R. Romero, MD
• Zaldy S. Tan, MD
• Aleksandra Pikula, MD
• Stephanie Debette, MD PhD
• Anil Nair, MD
- Anita S. DeStefano, PhD
-Larry D. Atwood, PhD
-Qiong Yang, PhD
- Charles DeCarli, MD
-Angela Jefferson, PhD
-Sherral Devine, PhD
-Lisa Draxler Hankee, PhD
• Alexa S. Beiser, PhD
• Sarah Preis, PhD
• Yulin Lu
• Calvin Lu
• Jayandra Himali
• Linda Farese
• Deb Foulkes
• Lois Abel
Maureen Dunn, Tim Kane, Richard Ahl, Jessica Saurman,
Kristen Knox

Framingham Neurology Research Team
• Philip A. Wolf, MD
• Sudha Seshadri, MD
• Carlos S. Kase, MD
• Sanford F. Auerbach, MD
• Jose R. Romero, MD
• Galit Weinstein, PhD
• Aleksandra Pikula, MD
• Stephanie Debette, MD PhD
• Zaldy Tan, MD
• Rhoda Au, PhD
• Margaret Kelly-Hayes, DEd RN
• Ann McKee, MD
• Ivana Delalle, MD, PhD
-Anita S. DeStefano, PhD
-Qiong Yang, PhD
-Seung Hoan Choi, Jing Wang
- Charles DeCarli, MD
-Sherral Devine, PhD
-Lisa Draxler Hankee, PhD
And the wonderful participants of the Framingham Heart Study
• Alexa S. Beiser, PhD
• Sarah Preis, PhD
• Jayandra Himali
• Yulin Lu
• Calvin Lu
• Linda Farese
• Deb Foulkes
• Lois Abel
Maureen Dunn, Tim Kane, Richard Ahl, Heather Pironti,

AGES-Reykjavik: Lenore Launer, Albert V. Smith, Vilmundur Gudnason, Gudny
Eiriksdottir, Tamara Harris
Atherosclerosis Risk in Communities Study: Thomas Mosley, Myriam Fornage, Eric
Boerwinkle, Jan Bressler
Austrian Study of Stroke Prevention: Reinhold Schmidt, Helena Schmidt, Katja-
Elisabeth Petrovic, Franz Fazekas, Margherita Cavalieri
Cardiovascular Health Study: Josh Bis, Will Longstreth, Annette Fitzpatrick, Oscar
Lopez, Bruce Psaty, Thomas Lumley, James Becker, Jerome Rotter, Erin Wallace
ERF: Cornelia van Duijn, Maaike Schuur, Carla Ibrahim
Framingham Heart Study: Philip Wolf, Anita L. DeStefano, Stephanie Debette, Qiong
Yang, Charles DeCarli, Alexa Beiser, Rhoda Au, Galit Weinstein, Aleksandra Pikula
Rotterdam Study: Cornelia van Duijn, M. Arfan Ikram, Ben Verhaaren, Carla Ibrahim,
Aad Van der Lugt, Renee van de Brujn, Monique Breteler
Collaborating Studies: EUROSPAN, LBC, Health ABC, 3C study, ROS/MAP, WHICAP,
TASCOG, Group Health, EADI, GERAD, ADGC, ISGC and METASTROKE, NHS,
SMA, Hunter, BLSA, Fundació ACE, PROSPER, Generation Scotland, AAA, GEMS,
GENOA, NOMAS, SHIP