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. 2018 Jul 1;141(7):2167-2180.
doi: 10.1093/brain/awy141.

Genetic study of multimodal imaging Alzheimer's disease progression score implicates novel loci

Marzia A Scelsi  1 , Raiyan R Khan  2 , Marco Lorenzi  1   3 , Leigh Christopher  2 , Michael D Greicius  2 , Jonathan M Schott  2 , Sebastien Ourselin  1   4 , Andre Altmann  1
Affiliations

Genetic study of multimodal imaging Alzheimer's disease progression score implicates novel loci

Marzia A Scelsi et al. Brain. .

Abstract

Identifying genetic risk factors underpinning different aspects of Alzheimer's disease has the potential to provide important insights into pathogenesis. Moving away from simple case-control definitions, there is considerable interest in using quantitative endophenotypes, such as those derived from imaging as outcome measures. Previous genome-wide association studies of imaging-derived biomarkers in sporadic late-onset Alzheimer's disease focused only on phenotypes derived from single imaging modalities. In contrast, we computed a novel multi-modal neuroimaging phenotype comprising cortical amyloid burden and bilateral hippocampal volume. Both imaging biomarkers were used as input to a disease progression modelling algorithm, which estimates the biomarkers' long-term evolution curves from population-based longitudinal data. Among other parameters, the algorithm computes the shift in time required to optimally align a subjects' biomarker trajectories with these population curves. This time shift serves as a disease progression score and it was used as a quantitative trait in a discovery genome-wide association study with n = 944 subjects from the Alzheimer's Disease Neuroimaging Initiative database diagnosed as Alzheimer's disease, mild cognitive impairment or healthy at the time of imaging. We identified a genome-wide significant locus implicating LCORL (rs6850306, chromosome 4; P = 1.03 × 10-8). The top variant rs6850306 was found to act as an expression quantitative trait locus for LCORL in brain tissue. The clinical role of rs6850306 in conversion from healthy ageing to mild cognitive impairment or Alzheimer's disease was further validated in an independent cohort comprising healthy, older subjects from the National Alzheimer's Coordinating Center database. Specifically, possession of a minor allele at rs6850306 was protective against conversion from mild cognitive impairment to Alzheimer's disease in the National Alzheimer's Coordinating Center cohort (hazard ratio = 0.593, 95% confidence interval = 0.387-0.907, n = 911, PBonf = 0.032), in keeping with the negative direction of effect reported in the genome-wide association study (βdisease progression score = -0.07 ± 0.01). The implicated locus is linked to genes with known connections to Alzheimer's disease pathophysiology and other neurodegenerative diseases. Using multimodal imaging phenotypes in association studies may assist in unveiling the genetic drivers of the onset and progression of complex diseases.

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Figures

Figure 1
Figure 1
Image processing pipeline for the amyloid load computation. GIF was used to obtain a probabilistic segmentation of the T1-weighted scans into background/skull, grey matter, white matter, CSF, subcortical structures, brainstem/pons and cerebellar nuclei. Each T1-weighted scan was rigidly registered to the closest-in-time florbetapir PET scan using the Aladin algorithm; a cubic spline interpolation scheme in two steps was used to resample the warped T1 image to the space of the closest-in-time lower-resolution PET. The GIF segmentations were resampled to the space of the PET scan, to define two key regions: (i) a cortical target region excluding the cerebellar grey matter; and (ii) a composite reference region comprising white matter, whole cerebellum, brainstem and pons, as proposed by Landau et al. (2015).
Figure 2
Figure 2
Disease progression modelling results. (A) Long-term progression curves for two Alzheimer’s disease biomarkers. Every point in the plot represents a biomarker measurement; longitudinal data from the same subject are connected by lines. The subjects’ clinical diagnosis at the initial PET scan is colour-coded. The x-axis shows the time from study entry plus the estimated DPS, values on the y-axis are the Z-score normalized individual biomarker measurements: florbetapir PET SUVR and intracranial-volume-normalized bilateral hippocampal volume. (B) Disease progression scores stratified by diagnosis at baseline PET scan. The y-axis shows the DPS and the x-axis corresponds to different diagnostic groups of increasing severity from left (Normal) to right (Alzheimer’s disease). Each box shows the DPS distribution for the corresponding diagnostic group. Annotations represent the level of statistical significance for pairwise tests, after correction for multiple comparisons (*** P < 0.001). EMCI = early MCI; LMCI = late MCI; SMC = subjective memory complaints.
Figure 4
Figure 4
Significance of association between Alzheimer’s disease polygenic risk score at different SNP inclusion thresholds and binary and continuous phenotypes. (A) Diagnosis coded as three different logistic regressions [healthy control (HC) versus Alzheimer’s disease (AD), healthy control versus MCI, MCI versus Alzheimer’s disease]. (B) The three quantitative traits used as outcomes in GWASs. The x-axis shows the number of SNPs included in the computation of the GRS (on logarithmic scale). We selected from the results of the IGAP GWAS SNPs that exceeded a P-value cut-off ranging from 10−5 (55 SNPs) to 0.95 (179 211 SNPs). The y-axis represents the strength of association (P-value for the regression coefficient in a general linear model, logarithmic scale) between the GRS and the outcome variables. The black line is the 0.01 significance threshold after Bonferroni correction for the effective number of independent tests performed. The effective number of independent GRS (Meff,GRS) and phenotypes (Meff,phen) tested was computed following the simpleM method in Gao et al. (2008). (A) Significance level adjusted for Meff,GRS only. (B) Significance level adjusted for both Meff,GRS and Meff,phen.
Figure 3
Figure 3
Manhattan plots for the three GWASs. Cross-sectional hippocampal volume (A), cross-sectional amyloid burden (B), disease progression score (C), after correcting for age, sex, number of APOE ɛ4, years of education, baseline cortical amyloid and hippocampal volume, and two principal components of population structure. The red line is the genome-wide significance threshold at P = 5 × 10−8; the blue line is a threshold for suggestive associations at P = 10−5.
Figure 5
Figure 5
Cumulative distribution functions (complementary survival functions) for risk of conversion to MCI or Alzheimer’s disease against months from baseline for NACC study participants. (A) Results stratified by rs6850306 minor allele carriers versus non-carriers (A/A and A/G versus G/G); (B) stratified by rs114365686 minor allele carriers versus non-carriers (T/T and T/C versus C/C). AD = Alzheimer’s disease.
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