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Dissection of the polygenic architecture of neuronal Aβ production using a large sample of individual iPSC lines derived from Alzheimer’s disease patients

Abstract

Genome-wide association studies have demonstrated that polygenic risks shape Alzheimer’s disease (AD). To elucidate the polygenic architecture of AD phenotypes at a cellular level, we established induced pluripotent stem cells from 102 patients with AD, differentiated them into cortical neurons and conducted a genome-wide analysis of the neuronal production of amyloid β (Aβ). Using such a cellular dissection of polygenicity (CDiP) approach, we identified 24 significant genome-wide loci associated with alterations in Aβ production, including some loci not previously associated with AD, and confirmed the influence of some of the corresponding genes on Aβ levels by the use of small interfering RNA. CDiP genotype sets improved the predictions of amyloid positivity in the brains and cerebrospinal fluid of patients in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. Secondary analyses of exome sequencing data from the Japanese ADNI and the ADNI cohorts focused on the 24 CDiP-derived loci associated with alterations in Aβ led to the identification of rare AD variants in KCNMA1.

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Fig. 1: CDiP using induced cortical neurons from human iPSCs.
Fig. 2: Genotype sets identified by CDiP can be a key clue for predicting real-world data of Alzheimer’s cohort with genetic risk for AD.

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Data availability

Data used in the preparation of this article were obtained from the ADNI database (adni.loni.usc.edu). ADNI was launched in 2003 as a public–private partnership, led by principal investigator M.W.W.. The primary goal of ADNI has been to test whether serial magnetic resonance imaging, PET, other biological markers and clinical and neuropsychological assessments can be combined to measure progression of mild cognitive impairment and early AD. SNP array data are available in the National Bioscience Database Center (data ID hum031; JGAS000383/JGAD00049). All data generated or analyzed during this study are included in this article and its Supplementary Information files.

Code availability

All code for data management and analysis is archived online at GitHub (https://github.com/HaruhisaInoue/iSNPs4ADNIpred). All other codes as described above are openly available in the developer site.

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Acknowledgements

We express sincere gratitude to all our co-workers and collaborators; to H. Kobayashi, W. Shin and A. Nabetani for experimental support and intellectual debt; to T. Enami and I. Inoue for technical assistance; and to M. Iijima, M. Yasui, N. Kawabata, T. Saigo, T. Urai and M. Nagata for their valuable administrative support. This research was funded in part by a grant for Core Center for iPS Cell Research of Research Center Network for Realization of Regenerative Medicine from AMED to H.I., Uehara Memorial Foundation to H.I., KAKENHI (21H02807) to H.I., KAKENHI (17K16121) and (20K16599) to T.K., KAKENHI (18K18452) to Y.Y., T.K. and H.I., the invited Project at iACT, Kyoto University Hospital to H.I., Suzuken Memorial Foundation to H.I. and AMED (JP20dk0207045) to T.I. The GTEx Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health (NIH) and by the National Cancer Institute, National Human Genome Research Institute, National Heart, Lung, and Blood Institute, National Institute on Drug Abuse, National Institute of Mental Health and National Institute of Neurological Disorders and Stroke. The data used for the analyses described in this manuscript were obtained from the GTEx portal on 6th July 2021. Data collection and sharing for this project was funded by the ADNI (NIH grant U01 AG024904) and Department of Defense ADNI (award no. W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering and through contributions from the following: Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica; Biogen Idec; Bristol-Myers Squibb Company; Eisai; Elan Pharmaceuticals; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche and its affiliated company Genentech; Fujirebio; GE Healthcare; IXICO; Janssen Alzheimer Immunotherapy Research & Development; Johnson & Johnson Pharmaceutical Research & Development; Medpace; Merck & Co.; Meso Scale Diagnostics; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer; Piramal Imaging; Servier; Synarc and Takeda Pharmaceutical Company. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the NIH (www.fnih.org). The grantee organization is the Northern Alzheimer’s Disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. Data used in preparation of this article were obtained from the ADNI database (adni.loni.usc.edu). As such, investigators within ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in the analysis or writing of this report. A complete listing of ADNI investigators can be found at http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf. The full membership of the J-ADNI investigators is listed at https://humandbs.biosciencedbc.jp/en/hum0043-j-adni-authors.

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Contributions

H.I. conceived the project. T.K. and H.I. designed the experiment. T.K., K.T. and A.N. established iPSCs and iN-iPSCs. T.K. and K.T conducted SNP array analysis. T.K., S.K., Y.Y. and R.Y. conducted CDiP. N.H. and T.I. analyzed the exome database. K.I. analyzed the amyloid PET data. Y.Y. established a prediction algorithm. T. Asada and T. Arai recruited patients.

Corresponding author

Correspondence to Haruhisa Inoue.

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Extended data

Extended Data Fig. 1 Establishment of cortical neurons from iPSCs of patients with sporadic AD.

(a) Clinical information of patients who provided somatic cells as resource for iPSC establishment. (b) Generated iPSC lines expressed pluripotency markers TRA1-60 (green) and NANOG (red). Representative images from three independent experiments were shown. Nuclei were stained with 4’,6-diamidino-2-phenylindole: DAPI (blue). Scale bars = 200 μm. (c) Schema of differentiation method and assay (d) iPSC-derived neurons expressed excitatory cortical neuron markers, including MAP2 (green) and TBR2 (red) on day 8 of differentiation. Representative images from three independent experiments were shown. Scale bars = 50 μm. Purity of day 8 cortical neurons was shown as positivity for MAP2 (e) and SATB2 (f) with no significant variation among different patients (p = 0.7727 for MAP2, p = 0.3675 for SATB2, one way ANOVA). Data represent mean ± SD (n = 3 for each patient clone).

Extended data Fig. 2 Correlation between total protein concentration and cell density or Aβ species.

(a) Correlation plot between total protein concentration (μg/μL), Y-axis and disseminated cell density (104 cells per well of 96-well-plate). Linear fit (grey lines) is shown for three different clones from three different patients (n = 3 per clone). (b) Correlation plot between Aβ40 (pg/mL), Y-axis and total protein concentration (μg/μL), X-axis. Linear fit (blue lines) is shown for three different clones from three different patients (n = 3 per clone). (c) Correlation plot between Aβ42 (pg/mL), Y-axis and total protein concentration (μg/μL), X-axis. Linear fit (blue lines) is shown for three different clones from three different patients (n = 3 per clone). (d) Correlation plot between Aβ42/40 ratio, Y-axis and total protein concentration (μg/μL), X-axis. Linear fit (blue lines) is shown for three different clones from three different patients (n = 3 per clone).

Extended Data Fig. 3 Comparison of APOE genotype and Aβ phenotypes in induced cortical neurons from AD iPSCs.

Plots show the distribution of (a) Aβ40, (b) Aβ42, (c) Aβ42/40 ratio and (d) protein concentration among different genotypes. X-axes correspond to APOE ε4 genotypes (patients, N = 44 for APOE3/3, N = 44 for APOE3/4, N = 14 for APOE4/4) and Y-axes represent (a) Aβ40 amounts, (b) Aβ42 amounts, (c) Aβ42/40 ratio, and (d) protein concentration of iPSC-derived cortical neurons. Horizontal lines are the median weights within a genotypic group, and error bars indicate standard deviation (S.D.). p > 0.05: not significant (N.S.) (one-way ANOVA with (two-way ANOVA with Tukey’s multiple comparisons test). Abbreviation: APOE, Apolipoprotein E.

Extended Data Fig. 4 There was no significant correlation between Aβ phenotypes in AD iPSC-derived cortical neurons and clinical status.

Scatter plots (N = 102) show Aβ phenotypes, including (a) Aβ40 (left panel, blue), (b) Aβ42 (right panel, red), and (c) Aβ42/40 ratio (Y-axis). X-axis shows the onset age of cognitive dysfunction. The scatter plot does not show statistically significant correlation between Aβ phenotypes and age at onset (R-squared = 0.03, p-value = 0.074 for Aβ40; R-squared = 0.000030, p-value = 0.87 for Aβ42; R-squared = 0.000023, p-value = 0.96 for Aβ42/40 ratio). The plots show the distribution of Aβ phenotypes between genders. X-axes correspond to gender, male or female (patients, n = 36 for male, n = 66 for female), and y-axes represent (d) Aβ40 dose, (e) Aβ42 dose, and (f) Aβ42/40 ratio in the culture supernatant of iPSC-derived cortical neurons. Horizontal lines are the median weights within a genotypic group, and error bars indicate standard deviation (S.D.).

Extended Data Fig. 5 Cellular dissection of polygenicity identified the genetic loci and molecular pathway related with Aβ42/40 ratio in AD cortical neurons.

(a) Flowchart for genome-wide analysis. (b) Quantile-quantile (Q-Q) plot of observed – log10 (p-value) from genome-wide association analysis of Aβ42/40 ratio level versus those expected under null hypothesis. Genomic inflation factor (λ) was 0.9659, suggesting that there was no population stratification effect. (c) Genome-wide association study for CDiP was conducted to identify the genetic loci related to the Aβ42/40 ratio without adjustment for the APOE status. Linear association between SNPs and the Aβ42/40 ratio was analyzed. Manhattan plot showing observed –log10 (p-value) of all tested SNPs with Aβ42/40 ratio (y-axis). Chromosomes are shown on the x-axis. The red line corresponds to genome-wide Bonferroni-corrected significance threshold p < 5 × 10−8. (d) Pathway analysis for 24 genes, identified in CDiP with Aβ42/40 ratio A selection of top canonical pathways found using Ingenuity Pathway Analysis (IPA) package to identify the enriched canonical pathways which were significantly enriched by using gene sets, identified in CDiP with Aβ42/40 ratio. Pathway analysis identified 14 pathways (p < 0.01), including 5 neuron-related pathways (red) and 2 pathways known to alter Aβ production (blue). Horizontal axis = p-value by Fisher’s exact test of pathway analysis.

Extended Data Fig. 6 CDiP for p231-phosphorylated tau / total tau ratio of AD cortical neurons.

(a) Plots show the distribution of the p231-tau / total tau ratio (p231-tau ratio) among different APOE genotypes. X-axes correspond to APOE ε4 genotypes (patients, n = 44 for APOE3/3, n = 44 for APOE3/4, n = 14 for APOE4/4), and Y-axes represent p231-tau ratio of iPSC-derived cortical neurons. Horizontal lines are the median weights within a genotypic group, and error bars indicate S.D. (b) The plots show the distribution of p231-tau ratio between genders. X-axes correspond to gender, male or female (patients, n = 36 for male, n = 66 for female), and y-axes represent p231-tau ratio of iPSC-derived cortical neurons. Horizontal lines are the median weights within a genotypic group, and error bars indicate S.D. (c) Scatter plots (N = 102) of p231-tau ratio (Y-axis) and onset ages of cognitive dysfunction (X-axis). The scatter plot does not show statistically significant correlation between p231-tau ratio and age at onset. (d) Genome-wide association study for CDiP was conducted to identify the genetic loci related to the p231-tau ratio with adjustment for the APOE status. Linear association between SNPs and the p231-tau ratio was analyzed. Manhattan plot showing observed –log10 (p-value) of all tested SNPs with p231-tau ratio (Y-axis). The red line corresponds to genome-wide Bonferroni-corrected significant threshold p < 5 × 10−8. (e) Genome-wide association study for CDiP was conducted to identify the genetic loci related to the p231-tau ratio without adjustment for the APOE status. Linear association between SNPs and the p231-tau ratio was analyzed. Manhattan plot showing observed –log10 (p-value) of all tested SNPs with p231-tau ratio (Y-axis). The red line corresponds to genome-wide Bonferroni-corrected significant threshold p < 5 × 10−8.

Extended Data Fig. 7 Alteration of gene expression by siRNA treatment.

(a) Relative expression of target gene for siRNA treatment was quantified. Y-axis shows fold change VS. non-targeted control siRNA. Data represent mean ± S.D. (n = 2 for each target gene).

Extended Data Fig. 8 Genes identified by CDiP can be potential therapeutic targets for Aβ phenotypes.

(a) Aβ40, (b) Aβ42, and (c) total protein concentration was analyzed after siRNA treatment, which targeted identified genes in cellular dissection of polygenicity (CDiP), Aβ-related genes, including APP, and BACE1. Non-target siRNA was used as negative control. JNJ-40418677 1 μM, second generation of γ-secretase modulator (GSM) to suppress Aβ production, was used as positive control for altered Aβ phenotypes. X-axis shows alteration level in Aβ40 compared with non-treatment control (n = 2 biological replicates). Shown is mean ± S.D. p < 0.05: *; p < 0.01: **; p < 0.001: ***.; p < 0.0001: **** (one way ANOVA with Uncorrected Fisher’s LSD) (d) Comparing neuronal expression of genes, whose siRNA altered the Aβ42/40 ratio, between the brains of Alzheimer’s disease and non-demented control. Transcriptome data from Single-cell atlas of the Entorhinal Cortex in Human Alzheimer’s Disease was analyzed. (e) Comparison of neuronal expression of genes whose siRNA reduced Aβ42, between the brains of Alzheimer’s disease and non-demented control. (f) The single-cell-based transcriptome data of six AD brains and six control brains, which provide the transcriptome data for individual cell types, was utilized to investigate the expression status of focused genes. Genes with higher expression in AD brains were selected as the potential therapeutic target.

Extended Data Fig. 9 Clinical status of Aβ deposition in brain did not correlate with Aβ phenotypes in induced cortical neurons from AD iPSCs.

(a) Schema of small cohort (N = 19), including the clinical status of Aβ deposition, measured by PiB-PET. (b) There was no difference in age at onset between Aβ-negative and Aβ-positive patients. The box and whiskers plot showed the range (whiskers) from minimum to maximum, the median (horizontal line) and the 25% and 75% (box) percentiles. Clinical status of Aβ deposition in the brain did not affect Aβ phenotypes in induced cortical neurons, from human iPSCs including (c) Aβ40, (d) Aβ42, and (e) Aβ42/40 ratio (patients, n = 4 for Aβ negative, n = 15 for Aβ positive). Horizontal lines are the median weights within groups, and error bars indicate standard deviation (S.D.). (f) J-ANDI and ADNI population for investigating rare variants of Alzheimer’s disease. Abbreviation: PiB PET: Pittsburgh Compound-B positron emission tomography, ANDI: Alzheimer’s Disease Neuroimaging Initiative, J-ANDI: Japanese ADNI.

Extended Data Fig. 10 Dissecting Alzheimer’s pathology into cellular polygenic architecture of the pathological traits to reveal the polygenicity of AD.

(a) CDiP can provide the information of genetic background, linked to each cell-type and trait in Alzheimer’s pathology.

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Kondo, T., Hara, N., Koyama, S. et al. Dissection of the polygenic architecture of neuronal Aβ production using a large sample of individual iPSC lines derived from Alzheimer’s disease patients. Nat Aging 2, 125–139 (2022). https://doi.org/10.1038/s43587-021-00158-9

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