Cellular Correlates of Cortical Thinning Throughout the Lifespan

Overview

Journal Sci Rep

Specialty Science

Date 2020 Dec 14

PMID 33311571

Citations 58

Authors

Didac Vidal-Pineiro

Nadine Parker

Jean Shin

Leon French

Hakon Grydeland

Andrea P Jackowski

Athanasia M Mowinckel

Yash Patel

Zdenka Pausova

Giovanni Salum

Oystein Sorensen

Kristine B Walhovd

Tomas Paus

Anders M Fjell

Affiliations

Soon will be listed here.

Abstract

Cortical thinning occurs throughout the entire life and extends to late-life neurodegeneration, yet the neurobiological substrates are poorly understood. Here, we used a virtual-histology technique and gene expression data from the Allen Human Brain Atlas to compare the regional profiles of longitudinal cortical thinning through life (4004 magnetic resonance images [MRIs]) with those of gene expression for several neuronal and non-neuronal cell types. The results were replicated in three independent datasets. We found that inter-regional profiles of cortical thinning related to expression profiles for marker genes of CA1 pyramidal cells, astrocytes and, microglia during development and in aging. During the two stages of life, the relationships went in opposite directions: greater gene expression related to less thinning in development and vice versa in aging. The association between cortical thinning and cell-specific gene expression was also present in mild cognitive impairment and Alzheimer's Disease. These findings suggest a role of astrocytes and microglia in promoting and supporting neuronal growth and dendritic structures through life that affects cortical thickness during development, aging, and neurodegeneration. Overall, the findings contribute to our understanding of the neurobiology underlying variations in MRI-derived estimates of cortical thinning through life and late-life disease.

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References

Tamnes C, Ostby Y, Walhovd K, Westlye L, Due-Tonnessen P, Fjell A . Intellectual abilities and white matter microstructure in development: a diffusion tensor imaging study. Hum Brain Mapp. 2010; 31(10):1609-25. PMC: 6871099. DOI: 10.1002/hbm.20962. View

Salum G, Gadelha A, Pan P, Moriyama T, Graeff-Martins A, Tamanaha A . High risk cohort study for psychiatric disorders in childhood: rationale, design, methods and preliminary results. Int J Methods Psychiatr Res. 2014; 24(1):58-73. PMC: 6878239. DOI: 10.1002/mpr.1459. View

Glasser M, Sotiropoulos S, Wilson J, Coalson T, Fischl B, Andersson J . The minimal preprocessing pipelines for the Human Connectome Project. Neuroimage. 2013; 80:105-24. PMC: 3720813. DOI: 10.1016/j.neuroimage.2013.04.127. View

Parker N, Patel Y, Jackowski A, Pan P, Salum G, Pausova Z . Assessment of Neurobiological Mechanisms of Cortical Thinning During Childhood and Adolescence and Their Implications for Psychiatric Disorders. JAMA Psychiatry. 2020; 77(11):1127-1136. PMC: 7301307. DOI: 10.1001/jamapsychiatry.2020.1495. View

Fjell A, Westlye L, Grydeland H, Amlien I, Espeseth T, Reinvang I . Critical ages in the life course of the adult brain: nonlinear subcortical aging. Neurobiol Aging. 2013; 34(10):2239-47. PMC: 3706494. DOI: 10.1016/j.neurobiolaging.2013.04.006. View

Fjell A, Grydeland H, Krogsrud S, Amlien I, Rohani D, Ferschmann L . Development and aging of cortical thickness correspond to genetic organization patterns. Proc Natl Acad Sci U S A. 2015; 112(50):15462-7. PMC: 4687601. DOI: 10.1073/pnas.1508831112. View

Natu V, Gomez J, Barnett M, Jeska B, Kirilina E, Jaeger C . Apparent thinning of human visual cortex during childhood is associated with myelination. Proc Natl Acad Sci U S A. 2019; 116(41):20750-20759. PMC: 6789966. DOI: 10.1073/pnas.1904931116. View

Grydeland H, Vertes P, Vasa F, Romero-Garcia R, Whitaker K, Alexander-Bloch A . Waves of Maturation and Senescence in Micro-structural MRI Markers of Human Cortical Myelination over the Lifespan. Cereb Cortex. 2018; 29(3):1369-1381. PMC: 6373687. DOI: 10.1093/cercor/bhy330. View

Sowell E, Thompson P, Leonard C, Welcome S, Kan E, Toga A . Longitudinal mapping of cortical thickness and brain growth in normal children. J Neurosci. 2004; 24(38):8223-31. PMC: 6729679. DOI: 10.1523/JNEUROSCI.1798-04.2004. View

10.

Peters A, Sethares C . The effects of age on the cells in layer 1 of primate cerebral cortex. Cereb Cortex. 2001; 12(1):27-36. DOI: 10.1093/cercor/12.1.27. View

11.

Terry R, Masliah E, Salmon D, Butters N, DeTeresa R, Hill R . Physical basis of cognitive alterations in Alzheimer's disease: synapse loss is the major correlate of cognitive impairment. Ann Neurol. 1991; 30(4):572-80. DOI: 10.1002/ana.410300410. View

12.

Fjell A, Westlye L, Greve D, Fischl B, Benner T, van der Kouwe A . The relationship between diffusion tensor imaging and volumetry as measures of white matter properties. Neuroimage. 2008; 42(4):1654-68. PMC: 2808804. DOI: 10.1016/j.neuroimage.2008.06.005. View

13.

Jack Jr C, Bennett D, Blennow K, Carrillo M, Dunn B, Budd Haeberlein S . NIA-AA Research Framework: Toward a biological definition of Alzheimer's disease. Alzheimers Dement. 2018; 14(4):535-562. PMC: 5958625. DOI: 10.1016/j.jalz.2018.02.018. View

14.

Elston G, Fujita I . Pyramidal cell development: postnatal spinogenesis, dendritic growth, axon growth, and electrophysiology. Front Neuroanat. 2014; 8:78. PMC: 4130200. DOI: 10.3389/fnana.2014.00078. View

15.

HUTTENLOCHER P, Dabholkar A . Regional differences in synaptogenesis in human cerebral cortex. J Comp Neurol. 1997; 387(2):167-78. DOI: 10.1002/(sici)1096-9861(19971020)387:2<167::aid-cne1>3.0.co;2-z. View

16.

French L, Ma T, Oh H, Tseng G, Sibille E . Age-Related Gene Expression in the Frontal Cortex Suggests Synaptic Function Changes in Specific Inhibitory Neuron Subtypes. Front Aging Neurosci. 2017; 9:162. PMC: 5446995. DOI: 10.3389/fnagi.2017.00162. View

17.

Zeisel A, Munoz-Manchado A, Codeluppi S, Lonnerberg P, La Manno G, Jureus A . Brain structure. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq. Science. 2015; 347(6226):1138-42. DOI: 10.1126/science.aaa1934. View

18.

Grasby K, Jahanshad N, Painter J, Colodro-Conde L, Bralten J, Hibar D . The genetic architecture of the human cerebral cortex. Science. 2020; 367(6484). PMC: 7295264. DOI: 10.1126/science.aay6690. View

19.

Krogsrud S, Tamnes C, Fjell A, Amlien I, Grydeland H, Sulutvedt U . Development of hippocampal subfield volumes from 4 to 22 years. Hum Brain Mapp. 2014; 35(11):5646-57. PMC: 6869672. DOI: 10.1002/hbm.22576. View

20.

Tse K, Herrup K . Re-imagining Alzheimer's disease - the diminishing importance of amyloid and a glimpse of what lies ahead. J Neurochem. 2017; 143(4):432-444. DOI: 10.1111/jnc.14079. View