Genetic study of multimodal imaging Alzheimer’s disease progression score implicates novel loci
Open accessAbstract
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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Integrating multiple imaging traits provides further improved diagnostic classification.
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Self-citation
- Authors
- Scelsi, M. A., Khan, R. R., Lorenzi, M., Christopher, L., Greicius, M. D., Schott, J. M., Ourselin, S., & Altmann, A.
- Affiliations
- University College London (GB)
- Stanford Medicine (US)
- Institut national de recherche en sciences et technologies du numérique (FR)
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, Gower Street NW1 2HE, London, UK
- Corresponding author
- Scelsi, Marzia A
- Venue
- Brain
- Publisher
- Oxford University Press (OUP)
- Published
- 2018-05-30
- Volume
- 141
- Issue
- 7
- Pages
- 2167-2180
- ISSN
- 0006-8950 (ISSN-L)
- 1460-2156
- PMC
- PMC6022660
- OpenAlex
- W2802278070
- Cited by
- 73
- References
- 11
- Citations by year
- 2026: 6 · 2025: 8 · 2024: 6 · 2023: 10 · 2022: 10 · 2021: 17 · 2020: 4 · 2019: 11 · 2018: 1
- FWCI
- 6.49
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Brain (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- HAL (submittedVersion, cc-by)
- UCL Discovery (University College London) (submittedVersion)
- Research Portal (King's College London) (submittedVersion, other-oa)
- Funders
- EPSRC-funded UCL Centre for Doctoral Training in Medical Imaging (EP/L016478/1)
- NIH (P50 AG047366)
- National Institute for Health Research Queen Square Dementia Biomedical Research Unit
- NIHR UCL/H Biomedical Research Centre, Wolfson Foundation, Engineering and Physical Sciences Research Council (EP/J020990/1)
- Medical Research Council (CSUB19166, MR/J01107X/1, FP7-ICT-2011-9-601055, MR/L016311/1)
- Alzheimer's Research UK (ARUK-Network 2012-6-ICE, ARUK-PG2014-1946)
- Brain Research Trust (UCC14191)
- European Union’s Horizon 2020 research and innovation programme (666992)
- EPSRC (EP/H046410/1, EP/J020990/1, EP/K005278)
- National Institute for Health Research Biomedical Research Unit
- National Institute for Health Research University College London Hospitals Biomedical Research Centre (BW.mn.BRC10269)
- Medical Research Council eMedLab Medical Bioinformatics Career Development Fellowship
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Keywords
- Alzheimer's disease, genetic risk factors, hippocampal volume, LCORL, expression quantitative trait loci, mild cognitive impairment, conversion to Alzheimer's disease, longitudinal biomarker trajectories, genome-wide association study
- MeSH terms
- Aged, Alzheimer Disease, Brain, Female, Hippocampus, Humans, Male, Repressor Proteins, Cohort Studies, Biomarkers, Case-Control Studies, Disease Progression, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Genome-Wide Association Study, Endophenotypes, Neuroimaging, Cognitive Dysfunction, Multimodal Imaging
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