- Email: [email protected]
WHITE MATTER HYPERINTENSITIES AND VASCULAR RISK FACTORS IN COGNITIVELY HEALTHY ELDERLY MONOZYGOTIC TWIN PAIRS
Poster Presentations: Sunday, July 16, 2017
positively associated to pathological WMH. Conclusions: Cognitively healthy late-middle aged APOE-ε4 homozygotes show a higher risk of presenting pathological WMH. The control of modifiable risk factors in individuals at higher risk of developing WMH might represent a preventive strategy to reduce or delay dementia’s onset.
P1-411
P433
within-pair differences in WMH (figure 3). Conclusions: The pattern of WMH lesions in twins is highly similar, suggesting a strong genetic background not only on the occurrence of WMH but also on their regional distribution. VRF are also associated with the occurrence of WMH, and this relation is partially driven by shared genetic influences.
WHITE MATTER HYPERINTENSITIES AND VASCULAR RISK FACTORS IN COGNITIVELY HEALTHY ELDERLY MONOZYGOTIC TWIN PAIRS
Mara ten Kate1, Carole H. Sudre2, Anouk den Braber1,3, Elles Konijnenberg1, M. Jorge Cardoso4, Philip Scheltens1, Sebastien Ourselin5, Dorret I. Boomsma3, Frederik Barkhof4,6, Pieter Jelle Visser7,8, 1Alzheimer Center and Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, Netherlands; 2Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom; 3Department of Biological Psychology, VU University, Amsterdam, Netherlands; 4Translational Imaging Group, Centre for Medical Image Computing, University College London, London, United Kingdom; 5Centre for Medical Image Computing, University College London, London, United Kingdom; 6Radiology & Nuclear Medicine, VU University Medical Center, Amsterdam, Netherlands; 7School for Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands; 8 Alzheimer Center and Department of Neurology, Amsterdam Neuroscience Campus, VU University Medical Center, Amsterdam, Netherlands. Contact e-mail: [email protected] Background: The occurrence of white matter hyperintensities
(WMH) is highly heritable. In addition, WMH have been associated with vascular risk factors (VRF), which are also under considerable genetic influence. Using a monozygotic twin design, this study examines the contribution of genetic factors and VRF on regional WMH burden. Methods: Cognitively healthy elderly monozygotic twins were included from the PreclinAD study. VRF were assessed using the Framingham risk score. WMH load was estimated using an automated algorithm and regionally classified according to anatomical lobes and distance from ventricular system (4 equidistant layers ranging from periventricular to subcortical). We first assessed the correlation within monozygotic twins for each region and the similarity in overall WMH distribution pattern. Next, we examined the association between VRF and WMH load across all subjects, whether VRF in one subject can predict WMH in the co-twin (cross-twin cross-trait analysis), and whether within-pair difference in WMH could be explained by within-pair differences in VRF (intra-pair difference model). Results: We included 190 subjects (95 pairs, age 70.2 6 73, 110 (58%) females, MMSE ¼ 29.0 6 1.1). Monozygotic twin correlation of Framingham risk score was 0.76. Monozygotic twin correlation for total WMH load was 0.76. Correlations were highest in frontal (range 0.64 – 0.77) and lowest in occipital (range 0.34 - 0.53) regions (figure 1). Monozygotic twins had a more similar WMH distribution pattern than random pairs (figure 2). VRF were associated with increased WMH load. We found suggestion of common genetic factors underlying both the occurrence of VRF and WMH in the cross-twin cross-trait analysis, in which VRF in one subject was associated with WMH in his/her co-twin. In addition to these common genetic factors, we found evidence of a direct relation between VRF and WMH since within-pair differences in VRF were associated with
Figure 1. Regional correlations. Plot representing the monozygotic twin correlation for 36 regions. Radial separations correspond to the divisions in layers from the most periventricular (center) to the most peripheral one. Color bar represents the strength of the correlation. Front: frontal; par: parietal; temp: temporal; occ: occipital; BG: basal ganglia.
Figure 2. Similarity of WMH distribution across regions. Histograms of WMH correlations across regions in true twin pairs and in random pairs. The WMH data was centered per region prior to computing the within pair correlation across regions.
P434
Poster Presentations: Sunday, July 16, 2017
Figure 3. Intra-pair difference model. Within pair differences in vascular risk factors (summarized in the Framingham risk score) were regressed on the within pair differences in total WMH. A significant relation suggests a direct relation between vascular risk factors and WMH, by factoring out the possibility of confounding by genetic factors.
P1-412
GENOME-WIDE ASSOCIATION STUDY OF A MULTIMODAL IMAGING BIOMARKER IN THE ADNI COHORT
Marzia Antonella Scelsi1, Marco Lorenzi2, Jon M. Schott3, Sebastien Ourselin1,4,5, Andre Altmann6, ADNI Investigators, 1 University College London, London, United Kingdom; 2 Universite C^ ote d’Azur, Antibes, France; 3University College London, Institute of Neurology, London, United Kingdom; 4UCL Institute of Neurology, London, United Kingdom; 5Centre for Medical Image Computing, University College London, London, United Kingdom; 6Translational Imaging Group, Centre for Medical Image Computing, University College London, London, United Kingdom. Contact e-mail: [email protected] Background: Genome-wide association studies (GWAS) in Alzheimer’s disease (AD) using neuroimaging-based phenotypes are typically derived from a single imaging modality. However, AD is a complex disorder involving different inter-linked pathogenic pathways. To explore genetic influences on disease progression, we generated a novel disease progression score (DPS) comprising cortical b-amyloid levels and hippocampal volume, then using it as a quantitative phenotype in GWAS. Methods: Study participants were part of the AD Neuroimaging Initiative (ADNI). Hippocampal volumes were computed with FreeSurfer from T1-weighted MRI scans. Cortical Ab42 levels were computed as standardised uptake values ratio (SUVR) from florbetapir PET scans. The AD-DPS was computed by jointly modelling the long-term time evolution of hippocampal volume and cortical SUVR for 1088 individuals, using the growth models via alternating conditional expectation (GRACE) algorithm. We used this DPS as a continuous phenotype for a GWAS in 846 subjects of Caucasian ancestry, covarying for sex, age, APOE4 status, baseline SUVR and 2 principal components of population structure. Additionally, we repeated the analysis stratified by APOE4 status. Results: Progression curves were
Figure 1. Long-term progression curves for two AD biomarkers. Left, florbetapir PET SUVR; right, bilateral hippocampal volume.
in good agreement with proposed models of AD biomarker evolution (Figures 1-2). A genome-wide significant association with AD-DPS was found on chromosome 4 for rs3733541 (p¼9.45e-09), located 300 kbp upstream of the KIT gene (Figure 3). This association was not found when testing hippocampal volume and Ab42 burden separately. There were no genomewide significant SNPs in the stratified analyses. However, the standardised effect size for rs3733541 was greater in APOE4 non-carriers (b¼-0.1160.02, p¼9.5e-5) than in APOE4 carriers (b¼-0.0860.02, p¼3e-3). Conclusions: We describe the first use of a DPS derived from multiple imaging modalities in a quantitative trait-GWAS. The KIT gene and its ligand stem cell factor (SCF) are involved in a pathway leading to migration and differentiation of neural stem cells to sites of brain injury. Significantly lower levels of SCF have been found in the plasma and CSF of patients with early AD. If validated in future studies, this novel susceptibility locus may influence the joint occurrence of hippocampal atrophy and amyloid deposition in AD.
Figure 2. Disease progression score stratified by diagnostic group (left) and by MCI progression status (right).
positively associated to pathological WMH. Conclusions: Cognitively healthy late-middle aged APOE-ε4 homozygotes show a higher risk of presenting pathological WMH. The control of modifiable risk factors in individuals at higher risk of developing WMH might represent a preventive strategy to reduce or delay dementia’s onset.
P1-411
P433
within-pair differences in WMH (figure 3). Conclusions: The pattern of WMH lesions in twins is highly similar, suggesting a strong genetic background not only on the occurrence of WMH but also on their regional distribution. VRF are also associated with the occurrence of WMH, and this relation is partially driven by shared genetic influences.
WHITE MATTER HYPERINTENSITIES AND VASCULAR RISK FACTORS IN COGNITIVELY HEALTHY ELDERLY MONOZYGOTIC TWIN PAIRS
Mara ten Kate1, Carole H. Sudre2, Anouk den Braber1,3, Elles Konijnenberg1, M. Jorge Cardoso4, Philip Scheltens1, Sebastien Ourselin5, Dorret I. Boomsma3, Frederik Barkhof4,6, Pieter Jelle Visser7,8, 1Alzheimer Center and Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, Netherlands; 2Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom; 3Department of Biological Psychology, VU University, Amsterdam, Netherlands; 4Translational Imaging Group, Centre for Medical Image Computing, University College London, London, United Kingdom; 5Centre for Medical Image Computing, University College London, London, United Kingdom; 6Radiology & Nuclear Medicine, VU University Medical Center, Amsterdam, Netherlands; 7School for Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands; 8 Alzheimer Center and Department of Neurology, Amsterdam Neuroscience Campus, VU University Medical Center, Amsterdam, Netherlands. Contact e-mail: [email protected] Background: The occurrence of white matter hyperintensities
(WMH) is highly heritable. In addition, WMH have been associated with vascular risk factors (VRF), which are also under considerable genetic influence. Using a monozygotic twin design, this study examines the contribution of genetic factors and VRF on regional WMH burden. Methods: Cognitively healthy elderly monozygotic twins were included from the PreclinAD study. VRF were assessed using the Framingham risk score. WMH load was estimated using an automated algorithm and regionally classified according to anatomical lobes and distance from ventricular system (4 equidistant layers ranging from periventricular to subcortical). We first assessed the correlation within monozygotic twins for each region and the similarity in overall WMH distribution pattern. Next, we examined the association between VRF and WMH load across all subjects, whether VRF in one subject can predict WMH in the co-twin (cross-twin cross-trait analysis), and whether within-pair difference in WMH could be explained by within-pair differences in VRF (intra-pair difference model). Results: We included 190 subjects (95 pairs, age 70.2 6 73, 110 (58%) females, MMSE ¼ 29.0 6 1.1). Monozygotic twin correlation of Framingham risk score was 0.76. Monozygotic twin correlation for total WMH load was 0.76. Correlations were highest in frontal (range 0.64 – 0.77) and lowest in occipital (range 0.34 - 0.53) regions (figure 1). Monozygotic twins had a more similar WMH distribution pattern than random pairs (figure 2). VRF were associated with increased WMH load. We found suggestion of common genetic factors underlying both the occurrence of VRF and WMH in the cross-twin cross-trait analysis, in which VRF in one subject was associated with WMH in his/her co-twin. In addition to these common genetic factors, we found evidence of a direct relation between VRF and WMH since within-pair differences in VRF were associated with
Figure 1. Regional correlations. Plot representing the monozygotic twin correlation for 36 regions. Radial separations correspond to the divisions in layers from the most periventricular (center) to the most peripheral one. Color bar represents the strength of the correlation. Front: frontal; par: parietal; temp: temporal; occ: occipital; BG: basal ganglia.
Figure 2. Similarity of WMH distribution across regions. Histograms of WMH correlations across regions in true twin pairs and in random pairs. The WMH data was centered per region prior to computing the within pair correlation across regions.
P434
Poster Presentations: Sunday, July 16, 2017
Figure 3. Intra-pair difference model. Within pair differences in vascular risk factors (summarized in the Framingham risk score) were regressed on the within pair differences in total WMH. A significant relation suggests a direct relation between vascular risk factors and WMH, by factoring out the possibility of confounding by genetic factors.
P1-412
GENOME-WIDE ASSOCIATION STUDY OF A MULTIMODAL IMAGING BIOMARKER IN THE ADNI COHORT
Marzia Antonella Scelsi1, Marco Lorenzi2, Jon M. Schott3, Sebastien Ourselin1,4,5, Andre Altmann6, ADNI Investigators, 1 University College London, London, United Kingdom; 2 Universite C^ ote d’Azur, Antibes, France; 3University College London, Institute of Neurology, London, United Kingdom; 4UCL Institute of Neurology, London, United Kingdom; 5Centre for Medical Image Computing, University College London, London, United Kingdom; 6Translational Imaging Group, Centre for Medical Image Computing, University College London, London, United Kingdom. Contact e-mail: [email protected] Background: Genome-wide association studies (GWAS) in Alzheimer’s disease (AD) using neuroimaging-based phenotypes are typically derived from a single imaging modality. However, AD is a complex disorder involving different inter-linked pathogenic pathways. To explore genetic influences on disease progression, we generated a novel disease progression score (DPS) comprising cortical b-amyloid levels and hippocampal volume, then using it as a quantitative phenotype in GWAS. Methods: Study participants were part of the AD Neuroimaging Initiative (ADNI). Hippocampal volumes were computed with FreeSurfer from T1-weighted MRI scans. Cortical Ab42 levels were computed as standardised uptake values ratio (SUVR) from florbetapir PET scans. The AD-DPS was computed by jointly modelling the long-term time evolution of hippocampal volume and cortical SUVR for 1088 individuals, using the growth models via alternating conditional expectation (GRACE) algorithm. We used this DPS as a continuous phenotype for a GWAS in 846 subjects of Caucasian ancestry, covarying for sex, age, APOE4 status, baseline SUVR and 2 principal components of population structure. Additionally, we repeated the analysis stratified by APOE4 status. Results: Progression curves were
Figure 1. Long-term progression curves for two AD biomarkers. Left, florbetapir PET SUVR; right, bilateral hippocampal volume.
in good agreement with proposed models of AD biomarker evolution (Figures 1-2). A genome-wide significant association with AD-DPS was found on chromosome 4 for rs3733541 (p¼9.45e-09), located 300 kbp upstream of the KIT gene (Figure 3). This association was not found when testing hippocampal volume and Ab42 burden separately. There were no genomewide significant SNPs in the stratified analyses. However, the standardised effect size for rs3733541 was greater in APOE4 non-carriers (b¼-0.1160.02, p¼9.5e-5) than in APOE4 carriers (b¼-0.0860.02, p¼3e-3). Conclusions: We describe the first use of a DPS derived from multiple imaging modalities in a quantitative trait-GWAS. The KIT gene and its ligand stem cell factor (SCF) are involved in a pathway leading to migration and differentiation of neural stem cells to sites of brain injury. Significantly lower levels of SCF have been found in the plasma and CSF of patients with early AD. If validated in future studies, this novel susceptibility locus may influence the joint occurrence of hippocampal atrophy and amyloid deposition in AD.
Figure 2. Disease progression score stratified by diagnostic group (left) and by MCI progression status (right).