The association between a polygenic Alzheimer score and cortical thickness in clinically normal subjects

Mert R. Sabuncu1,2, PhD; Randy L. Buckner1,3, PhD; Jordan W. Smoller4, MD, ScD; Phil Hyoun Lee4, PhD; Bruce Fischl1,2, PhD; and Reisa A. Sperling1,5, MD; for the Alzheimer’s Disease Neuroimaging Initiative* 1Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, 02129, USA 2Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA 3Department of Psychology and Center for Brain Science, Harvard University, Cambridge, MA, 02128, USA; and Howard Hughes Medical Institute, Cambridge, MA, 02128, USA 4Center for Human Genetic Research, Massachusetts General Hospital, Richard B. Simches Research Center, Boston, MA 02114 5Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women’s Hospital, Boston, 02115, MA, USA and Department of Neurology, Massachusetts General Hospital, Boston, MA, 02114, USA

SUPPLEMENTARY MATERIAL

Supplementary Figure 1.

The association of CDR-SB, MMSE, and diagnosis with the polygenic score (computed

at various P-value thresholds) in the ADNI discovery sample (CN and AD patients

without CSF measurements, N = 197). 1E-5 yields the polygenic score that exhibits the

highest correlation with clinical dementia severity and strongest association with AD

diagnosis (P-value = 1.47E-7). Age, sex, education (years), and the three principal

components from the population substructure analysis were included as control variables.

1E-5 was used to compute the polygenic score that was used in the analyses presented in

the paper.

Supplementary Figure 2.

The map of the significance (-log10 of the uncorrected p-value) of the association

between polygenic risk score and average cortical thickness across the Desikan ROIs

(Desikan R et al. 2006) in the CN group (N=104). Age, sex, education (years) and the

first three principal components from the population substructure analysis were included

as control variables. ROIs with an uncorrected p-value of 0.1 are shown on the inflated

surface of the template subject “fsaverage” and overlaid on the sulcal/gyral pattern in

gray. The medial surface is shown on the left and the lateral surface is shown on the right.

Only the isthmus of the cingulate exhibits a statistically significant association (p < 0.05,

Bonferroni corrected). The remaining ROIs that have a very subtle association are

consistent with AD-vulnerable regions and include the orbito-frontal and inferior

temporal cortices. Other cortical regions exhibited no significant associations. Given the

Bonferroni correction, power to detect associations is limited.

Supplementary Figure 3. Cortical thickness versus age in CN subjects with sub-

threshold levels of amyloid burden, stratified by polygenic score. The high risk group

(N=16) has a significantly steeper slope than the low risk group (N=45) (P = 0.05). This

is the same analysis as that of Figure 3. Here the two extreme subjects younger than 70

were excluded.

Supplementary Table 1 SNPs included in the polygenic score.

CH: Chromosome; RA: Risk allele; GWAS: Genome-wide association study (Harold D

et al. 2009); OR: odds ratio in logistic regression (AD vs. CN); P-VAL: p value; ADNI:

ADNI CN and AD subjects with CSF sample (N=204); COEF: coefficient of SNP allele

count in a linear model, which includes age, sex, education (years), and the first three

principal components from the population substructure analysis as control variables;

CDR-SB: Clinical dementia rating – sum of boxes.

 

Supplementary Table 2. Further information on SNPs included in polygenic score. Prior

studies that present the corresponding closest genes as positive associations with AD are

listed (Saunders A et al. 1993; Strittmatter W et al. 1993; Carrasquillo MM et al. 2009;

Harold D et al. 2009; Lambert J et al. 2009; Potkin SG et al. 2009; Biffi A et al. 2010;

Jun G et al. 2010; Seshadri S et al. 2010; Hollingworth P et al. 2011; Hu X et al. 2011).

Note that this is not an exhaustive list.

Supplementary Table 3 Association between individual SNPs (included in the

polygenic score) and AD-vulnerable cortical thickness in the ADNI CN sample (N=104).

Age, sex, education (years), and the first three principal components from the population

substructure analysis were included as control variables.

CH: Chromosome, RA: Risk allele, P-VAL: p value, COEF: coefficient of SNP allele

count in a linear model

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