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Cited by 155Alzheimer's disease research and treatmentsDementia and Cognitive Impairment ResearchGenomics and Rare Diseases

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Brain somatic mutations observed in Alzheimer’s disease associated with aging and dysregulation of tau phosphorylation

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Park, Jun Sung, Lee, Junehawk, Jung, Eun Sun, Kim, Myeong-Heui, Kim, Il Bin, Son, Hyeonju, Kim, Sangwoo, Kim, Sanghyeon, Park, Young Mok, Mook-Jung, Inhee, Yu, Seok Jong, Lee, Jeong Ho·2019·Nature Communications
DOI 10.1038/s41467-019-11000-7PMC PMC6626023
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Abstract

The role of brain somatic mutations in Alzheimer’s disease (AD) is not well understood. Here, we perform deep whole-exome sequencing (average read depth 584×) in 111 postmortem hippocampal formation and matched blood samples from 52 patients with AD and 11 individuals not affected by AD. The number of somatic single nucleotide variations (SNVs) in AD brain specimens increases significantly with aging, and the rate of mutation accumulation in the brain is 4.8-fold slower than that in AD blood. The putatively pathogenic brain somatic mutations identified in 26.9% (14 of 52) of AD individuals are enriched in PI3K-AKT, MAPK, and AMPK pathway genes known to contribute to hyperphosphorylation of tau. We show that a pathogenic brain somatic mutation in PIN1 leads to a loss-of-function mutation. In vitro mimicking of haploinsufficiency of PIN1 aberrantly increases tau phosphorylation and aggregation. This study provides new insights into the genetic architecture underlying the pathogenesis of AD.

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Fig. 1 Bioinformatic analysis pipeline and quantitative comparison of somatic single-nucleotide variations (SNVs) found in hippocampal formation (HIF) and blood tissues from Alzheimer’s disease (AD) and non-AD individuals. a Schematic figure for the bioinformatic analysis pipeline used in this study. b Validation results of post-filtered brain somatic mutations using targeted amplicon sequencing. Post-filter criteria ensured a precision of 79.8% in detecting filtered somatic SNVs. c Correlation of variant allelic frequency (VAFs) for 67 true calls between deep whole-exome sequencing and targeted amplicon sequencing. d Comparison of average mutation counts of somatic SNVs in HIF and blood tissues from AD and non-AD individuals. e Distribution of VAFs of pooled SNVs in each tissue from AD and non-AD individuals. Median VAF is indicated in red bars on each panel. f Comparison of mean VAFs in each group, which are shown as box plots (center line, median; box limits, upper and lower quartiles; whiskers, maximum and minimum values; points, outliers). g Contribution of six different mutation subtypes found in each group and data are mean ± SD. P values were calculated by one-way analysis of variance (ANOVA) test, followed by post hoc multiple comparison in d, f. P values were calculated by two-way ANOVA test, followed by post hoc multiple comparison in g. ns, not significant; **p < 0.01; ***p < 0.001; ****p < 0.0001. Source data is available as a Source Data file
Fig. 1 Bioinformatic analysis pipeline and quantitative comparison of somatic single-nucleotide variations (SNVs) found in hippocampal formation (HIF) and blood tissues from Alzheimer’s disease (AD) and non-AD individuals. a Schematic figure for the bioinformatic analysis pipeline used in this study. b Validation results of post-filtered brain somatic mutations using targeted amplicon sequencing. Post-filter criteria ensured a precision of 79.8% in detecting filtered somatic SNVs. c Correlation of variant allelic frequency (VAFs) for 67 true calls between deep whole-exome sequencing and targeted amplicon sequencing. d Comparison of average mutation counts of somatic SNVs in HIF and blood tissues from AD and non-AD individuals. e Distribution of VAFs of pooled SNVs in each tissue from AD and non-AD individuals. Median VAF is indicated in red bars on each panel. f Comparison of mean VAFs in each group, which are shown as box plots (center line, median; box limits, upper and lower quartiles; whiskers, maximum and minimum values; points, outliers). g Contribution of six different mutation subtypes found in each group and data are mean ± SD. P values were calculated by one-way analysis of variance (ANOVA) test, followed by post hoc multiple comparison in d, f. P values were calculated by two-way ANOVA test, followed by post hoc multiple comparison in g. ns, not significant; **p < 0.01; ***p < 0.001; ****p < 0.0001. Source data is available as a Source Data fileCC BY · PubMed Central
Fig. 2 Mutation signatures of brain and blood somatic mutations in Alzheimer’s disease (AD). The best decomposed mutation signature models from multiple likelihood estimation were derived for each tissue along with actual distribution of 96 possible mutation types. a Single base substitution (SBS) signatures 5, 1, and 18 and others account for 23.6%, 15%, 22.2%, and 39.2% of brain somatic mutations in AD, respectively. b SBS signatures 5 and 1, and others account for 71.0%, 19.8%, and 9.2% of blood somatic mutations in AD, respectively
Fig. 2 Mutation signatures of brain and blood somatic mutations in Alzheimer’s disease (AD). The best decomposed mutation signature models from multiple likelihood estimation were derived for each tissue along with actual distribution of 96 possible mutation types. a Single base substitution (SBS) signatures 5, 1, and 18 and others account for 23.6%, 15%, 22.2%, and 39.2% of brain somatic mutations in AD, respectively. b SBS signatures 5 and 1, and others account for 71.0%, 19.8%, and 9.2% of blood somatic mutations in AD, respectivelyCC BY · PubMed Central
Fig. 3 Putatively pathogenic brain somatic mutations associated with tau pathology in Alzheimer’s disease (AD). a Gene-list enrichment test of putatively pathogenic somatic mutations using the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway database. Genes with putatively pathogenic brain somatic mutations are significantly overrepresented in PI3K-AKT, mitogen-activated protein kinase (MAPK), and AMP-activated protein kinase (AMPK) pathways related to tau hyperphosphorylation. Vertical bar represents threshold for Benjamini–Hochberg adjusted P value. b Pathogenic scoring and text-mining results of brain somatic mutations found in AD. PIN1 was most frequently mentioned in relevant biomedical literature and ranked 52th according to Phred-scaled CADD (combined annotation‐dependent depletion) score. c Variant allelic frequency (VAFs) of PIN1 c.477C>T (p.Thr152Met) in blood, bulk hippocampal formation (HIF), and each sub-region of the HIF. PIN1 c.477C > T (p.Thr152Met) were observed. The VAF in each sub-regions of the HIF was 0.51–1.62%. d Comparison of protein expression levels of wild-type and mutant PIN1. PIN1 expression was analyzed in Neuro-2a cells expressing wild-type and the mutant 3× FLAG-hPin1. n = 3 for each experiment. e Effect of Pin1 knockdown on hyperphosphorylation of tau. Expression levels of pThr231-tau were observed in scramble and mPin1-shRNA (short hairpin RNA)-transfected HT22 cells. n = 9 for each experiment. f Effect of Pin1 knockdown on the oligomerization of tau. HT22 cells were co-transfected with tau-BiFC and either scramble or mPin1-shRNA. Then, cellular responses of tau-BiFC fluorescence (green) were measured. n = 20 for each experiment. Scale bar, 250 μm. Each bar represents the mean ± SEM and paired T test were used to determine the significance of each experiment in d–f. ***p < 0.001; ****p < 0.0001. Source data is available as a Source Data file
Fig. 3 Putatively pathogenic brain somatic mutations associated with tau pathology in Alzheimer’s disease (AD). a Gene-list enrichment test of putatively pathogenic somatic mutations using the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway database. Genes with putatively pathogenic brain somatic mutations are significantly overrepresented in PI3K-AKT, mitogen-activated protein kinase (MAPK), and AMP-activated protein kinase (AMPK) pathways related to tau hyperphosphorylation. Vertical bar represents threshold for Benjamini–Hochberg adjusted P value. b Pathogenic scoring and text-mining results of brain somatic mutations found in AD. PIN1 was most frequently mentioned in relevant biomedical literature and ranked 52th according to Phred-scaled CADD (combined annotation‐dependent depletion) score. c Variant allelic frequency (VAFs) of PIN1 c.477C>T (p.Thr152Met) in blood, bulk hippocampal formation (HIF), and each sub-region of the HIF. PIN1 c.477C > T (p.Thr152Met) were observed. The VAF in each sub-regions of the HIF was 0.51–1.62%. d Comparison of protein expression levels of wild-type and mutant PIN1. PIN1 expression was analyzed in Neuro-2a cells expressing wild-type and the mutant 3× FLAG-hPin1. n = 3 for each experiment. e Effect of Pin1 knockdown on hyperphosphorylation of tau. Expression levels of pThr231-tau were observed in scramble and mPin1-shRNA (short hairpin RNA)-transfected HT22 cells. n = 9 for each experiment. f Effect of Pin1 knockdown on the oligomerization of tau. HT22 cells were co-transfected with tau-BiFC and either scramble or mPin1-shRNA. Then, cellular responses of tau-BiFC fluorescence (green) were measured. n = 20 for each experiment. Scale bar, 250 μm. Each bar represents the mean ± SEM and paired T test were used to determine the significance of each experiment in d–f. ***p < 0.001; ****p < 0.0001. Source data is available as a Source Data fileCC BY · PubMed Central
Fig. 4 Landscape of pathogenic germline and somatic mutations contributing to Alzheimer’s disease (AD). a The presence of pathogenic germline risk factors and putatively pathogenic somatic mutations across all AD and non-AD individuals. The copy number of APOE ɛ4 alleles are annotated in black. Known risk modifiers of AD in APP, PSEN1/2, TREM2, and MAPT are marked in green. Putatively pathogenic brain somatic mutations associated with tau hyperphosphorylation-related pathways are marked in red, and the number of affected genes was annotated together. b Categorization of pathogenic germline and somatic mutation carriers among AD patients. 13.5% (7/52) of AD patients in our cohort could be explained by germline mutations alone; 26.9% (14/52) of AD patients harbored putatively pathogenic somatic mutation affecting the phosphorylation of tau
Fig. 4 Landscape of pathogenic germline and somatic mutations contributing to Alzheimer’s disease (AD). a The presence of pathogenic germline risk factors and putatively pathogenic somatic mutations across all AD and non-AD individuals. The copy number of APOE ɛ4 alleles are annotated in black. Known risk modifiers of AD in APP, PSEN1/2, TREM2, and MAPT are marked in green. Putatively pathogenic brain somatic mutations associated with tau hyperphosphorylation-related pathways are marked in red, and the number of affected genes was annotated together. b Categorization of pathogenic germline and somatic mutation carriers among AD patients. 13.5% (7/52) of AD patients in our cohort could be explained by germline mutations alone; 26.9% (14/52) of AD patients harbored putatively pathogenic somatic mutation affecting the phosphorylation of tauCC BY · PubMed Central

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Authors
Park, J. S., Lee, J., Jung, E. S., Kim, M.-H., Kim, I. B., Son, H., Kim, S., Kim, S., Park, Y. M., Mook-Jung, I., Yu, S. J., & Lee, J. H.
Affiliations
  • Korea Advanced Institute of Science and Technology (KR)
  • Seoul National University (KR)
  • Yonsei University (KR)
  • Institute for Basic Science (KR)
  • Korea Institute of Science & Technology Information (KR)
Corresponding author
  • Lee, Junehawk
  • Yu, Seok Jong
  • Lee, Jeong Ho
ORCID
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2019-07-12
Volume
10
Issue
1
Pages
3090-3090
ISSN
2041-1723 (ISSN-L)
DOI
10.1038/s41467-019-11000-7
PMC
PMC6626023
OpenAlex
W2960481741
Cited by
155
References
80
Citations by year
2026: 11 · 2025: 16 · 2024: 25 · 2023: 16 · 2022: 35 · 2021: 18 · 2020: 28 · 2019: 6
FWCI
14.92
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Communications (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • U.S. Department of Veterans Affairs
  • National Multiple Sclerosis Society
  • Stanley Medical Research Institute
  • Multiple Sclerosis Society
  • Korea Institute of Science and Technology
  • Korea Institute of Science and Technology Information (K-19-L02-C07, K-19-L02-C07-S01)
  • University of California, San Diego
  • National Institute of Mental Health
  • National Cancer Institute (F32CA090073)
  • National Institute of Neurological Disorders and Stroke
Topics
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
Keywords
Alzheimer's disease, somatic mutations, tau phosphorylation, tau hyperphosphorylation, aging, Pin1, haploinsufficiency, loss-of-function mutations, PI3K/Akt signaling, MAPK signaling, AMPK signaling, hippocampus, tau aggregation, postmortem brain
MeSH terms
NIMA-Interacting Peptidylprolyl Isomerase, Exome Sequencing, Loss of Function Mutation, Age Factors, Aged, Aged, 80 and over, Aging, Alzheimer Disease, Animals, Female, Hippocampus, Humans, Male, Middle Aged, Neurons, Phosphorylation, Recombinant Proteins, tau Proteins, Polymorphism, Single Nucleotide, Cell Line, Tumor, Mice, Gene Knockdown Techniques, Haploinsufficiency, Mutation Rate, Protein Aggregation, Pathological

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