Abstract
Background
Composite scores of magnetic resonance imaging–derived metrics in brain regions associated
with Alzheimer’s disease (AD), commonly termed AD signatures, have been developed
to distinguish early AD–related atrophy from normal age–associated changes. Diffusion-based
gray matter signatures may be more sensitive to early AD–related changes compared
with thickness/volume-based signatures, demonstrating their potential clinical utility.
The timing of early (i.e., midlife) changes in AD signatures from different modalities
and whether diffusion- and thickness/volume-based signatures each capture unique AD-related
phenotypic or genetic information remains unknown.
Methods
Our validated thickness/volume signature, our novel mean diffusivity (MD) signature,
and a magnetic resonance imaging–derived measure of brain age were used in biometrical
analyses to examine genetic and environmental influences on the measures as well as
phenotypic and genetic relationships between measures over 12 years. Participants
were 736 men from 3 waves of the Vietnam Era Twin Study of Aging (VETSA) (baseline/wave
1: mean age [years] = 56.1, SD = 2.6, range = 51.1–60.2). Subsequent waves occurred
at approximately 5.7-year intervals.
Results
MD and thickness/volume signatures were highly heritable (56%–72%). Baseline MD signatures
predicted thickness/volume signatures over a decade later, but baseline thickness/volume
signatures showed a significantly weaker relationship with future MD signatures. AD
signatures and brain age were correlated, but each measure captured unique phenotypic
and genetic variance.
Conclusions
Cortical MD and thickness/volume AD signatures are heritable, and each signature captures
unique variance that is also not explained by brain age. Moreover, results are in
line with changes in MD emerging before changes in cortical thickness, underscoring
the utility of MD as a very early predictor of AD risk.
Keywords
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References
- The effects of aging and Alzheimer’s disease on cerebral cortical anatomy: Specificity and differential relationships with cognition.Neuroimage. 2013; 76: 332-344
- The cortical signature of prodromal AD: Regional thinning predicts mild AD dementia.Neurology. 2009; 72: 1048-1055
- The cortical signature of Alzheimer’s disease: Regionally specific cortical thinning relates to symptom severity in very mild to mild AD dementia and is detectable in asymptomatic amyloid-positive individuals.Cereb Cortex. 2009; 19: 497-510
- Alzheimer-signature MRI biomarker predicts AD dementia in cognitively normal adults.Neurology. 2011; 76: 1395-1402
- MRI cortical thickness biomarker predicts AD-like CSF and cognitive decline in normal adults.Neurology. 2012; 78: 84-90
- Alzheimer disease: Quantitative structural neuroimaging for detection and prediction of clinical and structural changes in mild cognitive impairment.Radiology. 2009; 251: 195-205
- Mild cognitive impairment: Baseline and longitudinal structural MR imaging measures improve predictive prognosis.Radiology. 2011; 259: 834-843
- The dynamics of cortical and hippocampal atrophy in Alzheimer disease.Arch Neurol. 2011; 68: 1040-1048
- Diffusion imaging changes in grey matter in Alzheimer’s disease: A potential marker of early neurodegeneration.Alzheimers Res Ther. 2015; 7: 47
- Magnetic resonance markers for early diagnosis and progression of Alzheimer’s disease.Expert Rev Neurother. 2005; 5: 663-670
- Ultrastructural hippocampal and white matter alterations in mild cognitive impairment: A diffusion tensor imaging study.Dement Geriatr Cogn Disord. 2004; 18: 101-108
- Mild cognitive impairment: Apparent diffusion coefficient in regional gray matter and white matter structures.Radiology. 2006; 241: 197-205
- A diffusion tensor MRI study of patients with MCI and AD with a 2-year clinical follow-up.J Neurol Neurosurg Psychiatry. 2010; 81: 798-805
- Gray and white matter changes in Alzheimer’s disease: A diffusion tensor imaging study.J Magn Reson Imaging. 2008; 27: 20-26
- 12-year prediction of mild cognitive impairment aided by Alzheimer’s brain signatures at mean age 56.Brain Commun. 2021; 3: fcab167
- Association of cortical microstructure with amyloid-beta and tau: Impact on cognitive decline, neurodegeneration, and clinical progression in older adults.Mol Psychiatry. 2021; 26: 7813-7822
- Cortical microstructural alterations in mild cognitive impairment and Alzheimer’s disease dementia.Cereb Cortex. 2020; 30: 2948-2960
- Genetic and environmental influences on cortical mean diffusivity.Neuroimage. 2017; 146: 90-99
- Genetic and environmental influences on mean diffusivity and volume in subcortical brain regions.Hum Brain Mapp. 2017; 38: 2589-2598
- Projections of Alzheimer’s disease in the United States and the public health impact of delaying disease onset.Am J Public Health. 1998; 88: 1337-1342
- Forecasting the global burden of Alzheimer’s disease.Alzheimers Dement. 2007; 3: 186-191
- Alzheimer disease in the United States (2010–2050) estimated using the 2010 census.Neurology. 2013; 80: 1778-1783
- Age, APOE and sex: Triad of risk of Alzheimer’s disease.J Steroid Biochem Mol Biol. 2016; 160: 134-147
- The personalized Alzheimer’s disease cortical thickness index predicts likely pathology and clinical progression in mild cognitive impairment.Alzheimers Dement (Amst). 2018; 10: 301-310
- VETSA: The Vietnam era twin study of aging.Twin Res Hum Genet. 2013; 16: 399-402
- Health characteristics of adults aged 55 years and over: United States, 2004–2007.Natl Health Stat Rep. 2009; 16: 1-31
- Whole brain segmentation: Automated labeling of neuroanatomical structures in the human brain.Neuron. 2002; 33: 341-355
- Automatically parcellating the human cerebral cortex.Cereb Cortex. 2004; 14: 11-22
- Improved Localizadon of cortical activity by combining EEG and MEG with MRI cortical surface reconstruction: A linear approach.J Cogn Neurosci. 1993; 5: 162-176
- Cortical surface-based analysis. I. Segmentation and surface reconstruction.Neuroimage. 1999; 9: 179-194
- Genetic and environmental influences on the size of specific brain regions in midlife: The VETSA MRI study [published correction appears in Neuroimage 2010; 49:3499–3502].Neuroimage. 2010; 49: 1213-1223
- Hypertension-related alterations in white matter microstructure detectable in middle age.Hypertension. 2015; 66: 317-323
- Predicting brain-age from multimodal imaging data captures cognitive impairment.Neuroimage. 2017; 148: 179-188
- Negative fateful life events in midlife and advanced predicted brain aging.Neurobiol Aging. 2018; 67: 1-9
- Lifestyle and the aging brain: Interactive effects of modifiable lifestyle behaviors and cognitive ability in men from midlife to old age.Neurobiol Aging. 2021; 108: 80-89
- Long-term associations of cigarette smoking in early mid-life with predicted brain aging from mid- to late life.Addiction. 2022; 117: 1049-1059
- OpenMx: An open source extended structural equation modeling framework.Psychometrika. 2011; 76: 306-317
- umx: A library for structural equation and twin modelling in R.Twin Res Hum Genet. 2019; 22: 27-41
- Methodology for Genetic Studies of Twins and Families.Kluwer Academic Publishers, Dordrecht, The Netherlands1992
- Model-fitting approaches to the analysis of human behaviour.Heredity (Edinb). 1978; 41: 249-320
- Sex differences in Alzheimer disease – The gateway to precision medicine.Nat Rev Neurol. 2018; 14: 457-469
- Differences in Alzheimer’s disease and related dementias pathology among African American and Hispanic women: A qualitative literature review of biomarker studies.Front Syst Neurosci. 2021; 15685957
- Neuropsychological criteria for mild cognitive impairment improves diagnostic precision, biomarker associations, and progression rates.J Alzheimers Dis. 2014; 42: 275-289
- Neuropsychological contributions to the early identification of Alzheimer’s disease.Neuropsychol Rev. 2008; 18: 73-90
- Genetic and environmental influences on neuroimaging phenotypes: A meta-analytical perspective on twin imaging studies.Twin Res Hum Genet. 2012; 15: 351-371
- Genetics of brain fiber architecture and intellectual performance.J Neurosci. 2009; 29: 2212-2224
- Genetic and environmental contributions to regional cortical surface area in humans: A magnetic resonance imaging twin study.Cereb Cortex. 2011; 21: 2313-2321
- Hippocampal hyperactivation associated with cortical thinning in Alzheimer’s disease signature regions in non-demented elderly adults.J Neurosci. 2011; 31: 17680-17688
- The multiplex model of the genetics of Alzheimer’s disease.Nat Neurosci. 2020; 23: 311-322
- Genetics of Alzheimer’s disease: The importance of polygenic and epistatic components.Curr Neurol Neurosci Rep. 2017; 17: 78
- Dementia prevention, intervention, and care: 2020 report of the Lancet Commission.Lancet. 2020; 396: 413-446
- The genetic etiology of longitudinal measures of predicted brain ageing in a population-based sample of mid to late-age males.bioRxiv. 2021; https://doi.org/10.1101/2021.08.04.455143v1
- A framework to analyze partial volume effect on gray matter mean diffusivity measurements.Neuroimage. 2009; 44: 136-144
- Incidence of AD in African-Americans, Caribbean Hispanics, and Caucasians in northern Manhattan.Neurology. 2001; 56: 49-56
Article info
Publication history
Published online: June 20, 2022
Accepted:
June 7,
2022
Received in revised form:
May 4,
2022
Received:
March 28,
2022
Publication stage
In Press Journal Pre-ProofIdentification
Copyright
© 2022 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
