Unlocking the Genetics of Vascular Cognitive Impairment
Unlocking the Genetics of Vascular Cognitive Impairment
Unlocking the Genetics of Vascular Cognitive Impairment
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<strong>Unlocking</strong> <strong>the</strong> <strong>Genetics</strong> <strong>of</strong><br />
<strong>Vascular</strong> <strong>Cognitive</strong> <strong>Impairment</strong><br />
Session: Advances in Stroke <strong>Genetics</strong>:<br />
The American Stroke Association – Bugher Foundation<br />
Centers for Stroke Prevention Research<br />
Sudha Seshadri, MD<br />
Pr<strong>of</strong>essor <strong>of</strong> Neurology, Boston University School <strong>of</strong> Medicine<br />
Senior Investigator, The Framingham Heart Study
<strong>Vascular</strong> <strong>Cognitive</strong> <strong>Impairment</strong> (VCI)<br />
• Substantial individual risk and public health burden<br />
• 1 in 3 persons aged 65 will develop stroke, dementia<br />
or both<br />
• Proportion <strong>of</strong> all dementia varies: 15-50%<br />
Schrijvers E M et al., Stroke 2012;43:315-319<br />
Skoog I et al., NEJM 1993; 328:153-8.
Outline<br />
• VCI has a genetic basis<br />
• Phenotype remains hard to define<br />
• GWAS approaches<br />
• Candidate Gene approaches<br />
• Next Steps
Stroke and Dementia are Heritable<br />
• Dementia<br />
– (60-80% in twin studies)<br />
• Stroke<br />
– (20-30% in twin studies)<br />
Gatz M et al., Arch Gen Psychiatry 2006<br />
Bak S et al., Stroke 2002<br />
Heritability <strong>of</strong> VaD in FHS ~30% using ADDTC defn.<br />
• Parental dementia impairs <strong>of</strong>fspring verbal memory<br />
• Parental stroke impairs <strong>of</strong>fspring visual memory<br />
Debette et al., Neurology, 2009;73:2071; Weinstein et al., ISC 2012
<strong>Unlocking</strong> <strong>the</strong> <strong>Genetics</strong> <strong>of</strong> VCI<br />
• Improve understanding <strong>of</strong> biology<br />
• Permit more effective, targeted 1ºry and 2ºry prevention<br />
• New preventive, treatment modalities
Approach to <strong>Genetics</strong> <strong>of</strong><br />
<strong>Vascular</strong> <strong>Cognitive</strong> <strong>Impairment</strong><br />
• Define <strong>the</strong> phenotype (s) <strong>of</strong> interest<br />
– ‘<strong>Vascular</strong> Dementia’
Clinical Criteria to Define VaD<br />
• Hachinski Ischemic Score (HIS)<br />
• Diagnostic and Statistical Manual (DSM- III, IIIR, IV) criteria<br />
• International Classification <strong>of</strong> Disease (ICD)-10<br />
• California Alzheimer’s Disease Diagnostic and Treatment<br />
Centers (ADDTC) criteria<br />
• National Institute for Neurological Diseases and Stroke-<br />
Association Internationale pour la Recherche et<br />
‘Enseignement en Neurosciences (NINDS-AIREN) criteria<br />
Κ=0.76
Clinical Criteria for<br />
<strong>Vascular</strong> Dementia<br />
Sensitivity Specificity<br />
DSM-IV 0.5 0.84<br />
ADDTC-possible 0.7 0.78<br />
NINDS-AIREN-possible 0.55 0.84<br />
ADDTC-probable 0.2 0.91<br />
NINDS-AIREN-probable 0.25 0.93<br />
ICD-10 0.2 0.94
VCI: The Inclusive Definition<br />
• <strong>Cognitive</strong> or behavioral problems<br />
• Disease affecting blood vessels or blood flow to<br />
part or all <strong>of</strong> <strong>the</strong> brain<br />
• Evidence <strong>of</strong> damage to part or all <strong>of</strong> brain due to<br />
vascular factors
• <strong>Vascular</strong> Dementia<br />
VCI is Heterogenous<br />
– Following clinical strokes<br />
– Extensive small vessel disease (covert infarcts, WMH)<br />
– Specific arteriopathies<br />
– Amyloid angiopathy & multiple microbleeds<br />
• Contribution <strong>of</strong> vascular factors to AD<br />
• <strong>Vascular</strong> Mild <strong>Cognitive</strong> <strong>Impairment</strong> (VaMCI)
Approach to <strong>Genetics</strong> <strong>of</strong><br />
<strong>Vascular</strong> <strong>Cognitive</strong> <strong>Impairment</strong><br />
• Define <strong>the</strong> endophenotype (s) <strong>of</strong> interest<br />
– ‘<strong>Vascular</strong> Dementia’<br />
– Dementia/<strong>Cognitive</strong> function after Stroke<br />
– <strong>Cognitive</strong> function and decline<br />
– Imaging correlates <strong>of</strong> VCI (MRI infarcts, WMH)<br />
– Neuropathological Indices <strong>of</strong> <strong>Vascular</strong> Brain Injury
Approach to <strong>Genetics</strong> <strong>of</strong> VCI<br />
• May need complementary approaches<br />
• Should persons with AD pathology be included<br />
as cases/ controls/ excluded?
Approach to <strong>Genetics</strong> <strong>of</strong><br />
<strong>Vascular</strong> <strong>Cognitive</strong> <strong>Impairment</strong><br />
• Explore various approaches to gene discovery<br />
– GWAS<br />
– Candidate Genes<br />
– Whole exome, Whole genome & Targeted sequencing<br />
for rare variants<br />
– Mitochondrial Inheritance - Copy Number Variants<br />
– Telomere length - Epigenetics
GWAS Approaches to VCI
A, Genome-wide association plot (Manhattan plot) showing all single-nucleotide<br />
polymorphisms with <strong>the</strong>ir respective chromosome and position on <strong>the</strong> X-axis plotted against<br />
<strong>the</strong>ir association probability value on <strong>the</strong> Y-axis.<br />
Copyright © American Heart Association<br />
Schrijvers E M et al. Stroke 2012;43:315-319
Cohorts for Heart and Aging<br />
Research in Genomic Epidemiology<br />
(CHARGE) Consortium<br />
http://depts.washington.edu/chargeco/wiki/Main_Page
Overview <strong>of</strong> CHARGE<br />
• CVD/Aging cohorts with GWAS data<br />
– ARIC, CHS, AGES, ASPS, FHS and Rotterdam<br />
– PHENOTYPE HARMONIZATION<br />
– Sharing <strong>of</strong> within-study analyses results for crossstudy<br />
prospective meta-analysis<br />
– Imputation to HapMap permitted meta-analyses<br />
despite use <strong>of</strong> different platforms in each study<br />
-- Austrian Study <strong>of</strong> Stroke Prevention (ASPS)
GWAS <strong>of</strong> ‘All dementia’ (AD+ VaD) in CHARGE<br />
Results similar to AD;<br />
Few loci showing stronger associations with all dementia than<br />
AD: e.g. LPL, although this has also been associated with AD
Log 10 (p)<br />
GWAS <strong>of</strong> Covert Brain Infarcts in CHARGE<br />
p = 5 x 10-8<br />
p = 5 x 10-7<br />
Chromosome<br />
MACROD2<br />
FLRT3<br />
Debette S et al., Stroke 2010; 41:210-217.
GWAS <strong>of</strong> White Matter Hyperintensities in CHARGE<br />
N=12,385<br />
17q25: rs3744028, P=4.0x10 -15 ; rs1055129, P=2.6x10 -11<br />
Fornage et al., Ann Neurol. 2011;69:928-939.<br />
TRIM65, TRIM 47, FBF1, WBP2
MYO1B<br />
GWAS <strong>of</strong> <strong>Cognitive</strong> Speed in CHARGE<br />
Trails A<br />
rs11739440<br />
5439 persons, age 45+<br />
Ibrahim et al., Presented at ICAD, Paris, 2011
GWAS <strong>of</strong> <strong>Cognitive</strong> Processing Speed Ability in CHARGE<br />
Digit-Symbol and Letter-Digit Substitution Tests<br />
N=32,900 persons over age 45 in 20 cohorts<br />
chromosome: 11; Location: 11q23<br />
rs12363125<br />
P = 4.72E-007<br />
Ibrahim et al., Presented at ICAD, Paris, 2011<br />
25
Candidate Gene Approaches<br />
to VCI
Candidate Gene Approaches to VCI<br />
• Limited by known biology<br />
• Would not target intergenic regions<br />
• Fewer hypo<strong>the</strong>ses, greater power with smaller<br />
samples
Candidate Gene Approaches<br />
– Genes determining Brain reserve, response to injury<br />
• (APOE, VLDLR, BDNF)<br />
– Stroke genes<br />
– AD genes<br />
– Monogenic disorder genes<br />
• NOTCH3 (CADASIL)<br />
• HTRK1 (CARASIL)<br />
• TREX1 (RVCL) COL4A1 (SVD)
HR <strong>of</strong> 2.3 associated with ≥1 APOE ε4 allele for non-AD dementias.
GWAS <strong>of</strong> Stroke in <strong>the</strong> CHARGE Consortium<br />
Results <strong>of</strong> Tests for <strong>the</strong> Association between Stroke and Each SNP<br />
Ikram M et al. N Engl J Med 2009;10.1056/NEJMoa0900094
Associations in <strong>the</strong> Region Centered on rs11833579 and Containing NINJ2<br />
Ikram M et al. N Engl J Med 2009;10.1056/NEJMoa0900094<br />
Ninjurin-2: Transmembrane protein in<br />
<strong>the</strong> “nerve-injury-induced protein” family
NINJ2 and recurrent stroke, mortality<br />
765 patients with incident ischemic stroke &<br />
977 age-matched community controls<br />
Mean age: 62.8 ± 12.2 yrs<br />
765 cases, 977 community controls, enrolled day <strong>of</strong> stroke<br />
HR Enrolled for combined at outcome 0.89 ± <strong>of</strong> 1.7 recurrent days stroke, after mortality: stroke<br />
2.85 (1.34-6.06); p=0.007<br />
rs12425791 was associated with ischemic stroke<br />
(OR=1.67, 95%CI=1.05-2.66, p=0.031)<br />
TAIWAN STROKE GENETICS CONSORTIUM Hsieh et al., J Biomed Sci 2012
).<br />
Inverse Association with Memory<br />
• NINJ2 (rs11833579 )<br />
– Associated with memory decline (p=9x10 -5 ) &<br />
– With AD susceptibility<br />
– In Religious Orders Study/ Memory and Aging Project<br />
(p=0.001)<br />
– In CHARGE (p=0.02).<br />
Shulman et al., ICAD, 2012
GWAS <strong>of</strong> Stroke<br />
• 2 prior GWAS: 1 did not find any SNP reaching<br />
genome-wide significance<br />
PITX2<br />
• Ano<strong>the</strong>r related an Afib associated SNP to<br />
cardioembolic stroke
Stroke Genes (SNPs) associated with poorer cognitive function<br />
2493 persons with GWAS and cognitive testing in <strong>the</strong> Framingham Study<br />
Trails A and B, Visual Reproductions, Hooper, Verbal Fluency<br />
SNPID chr Gene <strong>Cognitive</strong> Phenotype p-value<br />
rs2200733 4 PITX2 Trails A<br />
Visual memory<br />
Verbal Fluency<br />
rs7193343 16 ZFHX3 Hooper visual organization<br />
Verbal Fluency<br />
0.02<br />
0.03<br />
0.02<br />
0.01<br />
0.04
New Late-Onset AD Genes<br />
• Chr 1: ` CR1: Complement component (3b/4b) receptor 1<br />
• Chr 2: BIN1: Bridging integrator 1<br />
• Chr 6: CD2AP: CD2 associated protein<br />
• Chr 7: EPHA1: Ephrin 1<br />
• Chr 8: CLU/APOJ: Clusterin<br />
• Chr 11: MS4A: membrane-spanning 4-domains, subfamily A, member 4<br />
PICALM: Phosphatidylinositol binding clathrin assembly protein<br />
• Chr 19: APOE/TOMM40/APOC1<br />
• CD33<br />
ABCA7: ATP-binding cassette, sub-family A
AD Genes (SNPs) associated with poorer cognitive function<br />
2493 persons with GWAS and cognitive testing in <strong>the</strong> Framingham Study<br />
Trails A and B, Visual Reproductions, Hooper, Verbal Fluency<br />
SNPID chr Gene <strong>Cognitive</strong><br />
Phenotype<br />
p-value<br />
rs11136000 8 CLU Hooper 0.02<br />
rs744373 2 BIN1 Trails B-A<br />
Visual Memory<br />
0.04<br />
0.02<br />
rs3764650 19 ABCA7 Hooper 0.03
Braskie et al., 2011
Common SNPs in NOTCH3 were associated with WMH<br />
among hypertensives in CHARGE
Approach to <strong>Genetics</strong> <strong>of</strong><br />
<strong>Vascular</strong> <strong>Cognitive</strong> <strong>Impairment</strong><br />
• Explore various approaches to gene discovery<br />
– GWAS<br />
– Candidate Genes<br />
– Whole exome, Whole genome & Targeted sequencing<br />
for rare variants<br />
– Mitochondrial Inheritance - Copy Number Variants<br />
– Telomere length - Epigenetics
Mitochondrial Stroke Genetic Risk Score was also associated with WMHV in 792 persons with MRI
Summary, Next Steps<br />
• A multi-pronged approach will be required using<br />
case-control series & cohorts for genetics <strong>of</strong><br />
– cognitive performance in persons with stroke<br />
– VaD and vMCI defined broadly<br />
– Structural correlates <strong>of</strong> VCI
Summary, Next Steps<br />
• Iterative Process<br />
Molecular<br />
biology,<br />
o<strong>the</strong>r<br />
genes in<br />
pathway<br />
Structural<br />
and<br />
functional<br />
effects<br />
Identify<br />
putative<br />
VCI genes
Framingham Neurology Research Team<br />
• Philip A. Wolf, MD<br />
• Sudha Seshadri, MD<br />
• Rhoda Au, PhD<br />
• Margaret Kelly-Hayes, DEd RN<br />
• Carlos S. Kase, MD<br />
• Sanford F. Auerbach, MD<br />
• Ann McKee, MD<br />
• Ivana Delalle, MD, PhD<br />
• Jose R. Romero, MD<br />
• Zaldy S. Tan, MD<br />
• Aleksandra Pikula, MD<br />
• Stephanie Debette, MD PhD<br />
• Anil Nair, MD<br />
- Anita S. DeStefano, PhD<br />
-Larry D. Atwood, PhD<br />
-Qiong Yang, PhD<br />
- Charles DeCarli, MD<br />
-Angela Jefferson, PhD<br />
-Sherral Devine, PhD<br />
-Lisa Draxler Hankee, PhD<br />
• Alexa S. Beiser, PhD<br />
• Sarah Preis, PhD<br />
• Yulin Lu<br />
• Calvin Lu<br />
• Jayandra Himali<br />
• Linda Farese<br />
• Deb Foulkes<br />
• Lois Abel<br />
Maureen Dunn, Tim Kane, Richard Ahl, Jessica Saurman,<br />
Kristen Knox
Framingham Neurology Research Team<br />
• Philip A. Wolf, MD<br />
• Sudha Seshadri, MD<br />
• Carlos S. Kase, MD<br />
• Sanford F. Auerbach, MD<br />
• Jose R. Romero, MD<br />
• Galit Weinstein, PhD<br />
• Aleksandra Pikula, MD<br />
• Stephanie Debette, MD PhD<br />
• Zaldy Tan, MD<br />
• Rhoda Au, PhD<br />
• Margaret Kelly-Hayes, DEd RN<br />
• Ann McKee, MD<br />
• Ivana Delalle, MD, PhD<br />
-Anita S. DeStefano, PhD<br />
-Qiong Yang, PhD<br />
-Seung Hoan Choi, Jing Wang<br />
- Charles DeCarli, MD<br />
-Sherral Devine, PhD<br />
-Lisa Draxler Hankee, PhD<br />
And <strong>the</strong> wonderful participants <strong>of</strong> <strong>the</strong> Framingham Heart Study<br />
• Alexa S. Beiser, PhD<br />
• Sarah Preis, PhD<br />
• Jayandra Himali<br />
• Yulin Lu<br />
• Calvin Lu<br />
• Linda Farese<br />
• Deb Foulkes<br />
• Lois Abel<br />
Maureen Dunn, Tim Kane, Richard Ahl, Hea<strong>the</strong>r Pironti,
AGES-Reykjavik: Lenore Launer, Albert V. Smith, Vilmundur Gudnason, Gudny<br />
Eiriksdottir, Tamara Harris<br />
A<strong>the</strong>rosclerosis Risk in Communities Study: Thomas Mosley, Myriam Fornage, Eric<br />
Boerwinkle, Jan Bressler<br />
Austrian Study <strong>of</strong> Stroke Prevention: Reinhold Schmidt, Helena Schmidt, Katja-<br />
Elisabeth Petrovic, Franz Fazekas, Margherita Cavalieri<br />
Cardiovascular Health Study: Josh Bis, Will Longstreth, Annette Fitzpatrick, Oscar<br />
Lopez, Bruce Psaty, Thomas Lumley, James Becker, Jerome Rotter, Erin Wallace<br />
ERF: Cornelia van Duijn, Maaike Schuur, Carla Ibrahim<br />
Framingham Heart Study: Philip Wolf, Anita L. DeStefano, Stephanie Debette, Qiong<br />
Yang, Charles DeCarli, Alexa Beiser, Rhoda Au, Galit Weinstein, Aleksandra Pikula<br />
Rotterdam Study: Cornelia van Duijn, M. Arfan Ikram, Ben Verhaaren, Carla Ibrahim,<br />
Aad Van der Lugt, Renee van de Brujn, Monique Breteler<br />
Collaborating Studies: EUROSPAN, LBC, Health ABC, 3C study, ROS/MAP, WHICAP,<br />
TASCOG, Group Health, EADI, GERAD, ADGC, ISGC and METASTROKE, NHS,<br />
SMA, Hunter, BLSA, Fundació ACE, PROSPER, Generation Scotland, AAA, GEMS,<br />
GENOA, NOMAS, SHIP