Genomic Studies Across the Lifespan Point to Early Mechanisms Determining Subcortical Volumes
Biological Psychiatry: Cognitive Neuroscience and Neuroimaging. 2022-06-01; 7(6): 616-628
DOI: 10.1016/j.bpsc.2021.10.011
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Le Grand Q(1), Satizabal CL(2), Sargurupremraj M(3), Mishra A(1), Soumaré A(1), Laurent A(4), Crivello F(4), Tsuchida A(4), Shin J(5), Macalli M(1), Singh B(6), Beiser AS(7), DeCarli C(6), Fletcher E(6), Paus T(8), Lathrop M(9), Adams HHH(10), Bis JC(11), Seshadri S(2), Tzourio C(12), Mazoyer B(13), Debette S(14).
Author information:
(1)University of Bordeaux, INSERM, Bordeaux Population Health Center, UMR1219, Bordeaux, France.
(2)Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, UT
Health San Antonio, San Antonio, Texas; Department of Population Health
Sciences, UT Health San Antonio, San Antonio, Texas; Framingham Heart Study,
Framingham, Massachusetts; Department of Neurology, Boston University School of
Medicine, Boston, Massachusetts.
(3)University of Bordeaux, INSERM, Bordeaux Population Health Center, UMR1219,
Bordeaux, France; Glenn Biggs Institute for Alzheimer’s and Neurodegenerative
Diseases, UT Health San Antonio, San Antonio, Texas.
(4)University of Bordeaux, Institute of Neurodegenerative Diseases, UMR5293,
Neurofunctional imaging group, Bordeaux, France; CNRS, Institute of
Neurodegenerative Diseases, UMR5293, Neurofunctional imaging group, Bordeaux,
France; CEA, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional
imaging group, Bordeaux, France.
(5)Department of Physiology, Hospital for Sick Children, University of Toronto,
Toronto, Ontario, Canada; Department of Nutritional Sciences, Hospital for Sick
Children, University of Toronto, Toronto, Ontario, Canada.
(6)Imaging of Dementia and Aging Laboratory, Department of Neurology, University
of California Davis, Davis, California.
(7)Framingham Heart Study, Framingham, Massachusetts; Department of Neurology,
Boston University School of Medicine, Boston, Massachusetts; Department of
Biostatistics, Boston University School of Public Health, Boston, Massachusetts.
(8)Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada;
Department of Psychology, University of Toronto, Toronto, Ontario, Canada;
Department of Psychiatry, Centre Hospitalier Universitaire Sainte-Justine,
Faculty of Medicine, University of Montreal, Montreal, Quebec, Canada.
(9)McGill Genome Center, McGill University, Montreal, Quebec, Canada.
(10)Department of Radiology and Nuclear Medicine, Erasmus University Medical
Center, Rotterdam, the Netherlands; Department of Clinical Genetics, Erasmus
University Medical Center, Rotterdam, the Netherlands.
(11)Cardiovascular Health Research Unit, Department of Medicine, University of
Washington, Seattle, Washington.
(12)University of Bordeaux, INSERM, Bordeaux Population Health Center, UMR1219,
Bordeaux, France; Bordeaux University Hospital, Department of Medical
Informatics, Bordeaux, France.
(13)University of Bordeaux, Institute of Neurodegenerative Diseases, UMR5293,
Neurofunctional imaging group, Bordeaux, France; CNRS, Institute of
Neurodegenerative Diseases, UMR5293, Neurofunctional imaging group, Bordeaux,
France; CEA, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional
imaging group, Bordeaux, France; Bordeaux University Hospital, Department of
Neuroradiology, Bordeaux, France.
(14)University of Bordeaux, INSERM, Bordeaux Population Health Center, UMR1219,
Bordeaux, France; Bordeaux University Hospital, Department of Neurology,
Institute of Neurodegenerative Diseases, Bordeaux, France. Electronic address:
.
BACKGROUND: Subcortical brain structures play a key role in pathological
processes of age-related neurodegenerative disorders. Mounting evidence also
suggests that early-life factors may have an impact on the development of common
late-life neurological diseases, including genetic factors that can influence
both brain maturation and neurodegeneration.
METHODS: Using large population-based brain imaging datasets across the lifespan
(N ≤ 40,628), we aimed to 1) estimate the heritability of subcortical volumes in
young (18-35 years), middle (35-65 years), and older (65+ years) age, and their
genetic correlation across age groups; 2) identify whether genetic loci
associated with subcortical volumes in older persons also show associations in
early adulthood, and explore underlying genes using transcriptome-wide
association studies; and 3) explore their association with neurological
phenotypes.
RESULTS: Heritability of subcortical volumes consistently decreased with
increasing age. Genetic risk scores for smaller caudate nucleus, putamen, and
hippocampus volume in older adults were associated with smaller volumes in young
adults. Individually, 10 loci associated with subcortical volumes in older
adults also showed associations in young adults. Within these loci,
transcriptome-wide association studies showed that expression of several genes
in brain tissues (especially MYLK2 and TUFM) was associated with subcortical
volumes in both age groups. One risk variant for smaller caudate nucleus volume
(TUFM locus) was associated with lower cognitive performance. Genetically
predicted Alzheimer’s disease was associated with smaller subcortical volumes in
middle and older age.
CONCLUSIONS: Our findings provide novel insights into the genetic determinants
of subcortical volumes across the lifespan. More studies are needed to decipher
the underlying biology and clinical impact.
Copyright © 2021. Published by Elsevier Inc.
Conflict of interest statement: Disclosures The authors report no competing
interests.