ABCA7 variants impact phosphatidylcholine and mitochondria in neurons

Abstract

Loss-of-function variants in the lipid transporter ABCA7 substantially increase the risk of Alzheimer's disease^1,2, yet how they impact cellular states to drive disease remains unclear. Here, using single-nucleus RNA-sequencing analysis of human brain samples, we identified widespread gene expression changes across multiple neural cell types associated with rare ABCA7 loss-of-function variants. Excitatory neurons, which expressed the highest levels of ABCA7, showed disrupted lipid metabolism, mitochondrial function, DNA repair and synaptic signalling pathways. Similar transcriptional disruptions occurred in neurons carrying the common Alzheimer's-associated variant ABCA7 p.Ala1527Gly³, predicted by molecular dynamics simulations to alter the ABCA7 structure. Induced pluripotent stem (iPS)-cell-derived neurons with ABCA7 loss-of-function variants recapitulated these transcriptional changes, displaying impaired mitochondrial function, increased oxidative stress and disrupted phosphatidylcholine metabolism. Supplementation with CDP-choline increased phosphatidylcholine synthesis, reversed these abnormalities and normalized amyloid-β secretion and neuronal hyperexcitability-key Alzheimer's features that are exacerbated by ABCA7 dysfunction. Our results implicate disrupted phosphatidylcholine metabolism in ABCA7-related Alzheimer's risk and highlight a possible therapeutic approach.

Fig. 1. snRNA-seq atlas of post-mortem PFC from ABCA7 LoF variant carriers.

a, ABCA7 gene structure indicating studied variant locations. Exons are indicated by rectangles; introns are indicated by lines. The pie chart shows the frequency of ABCA7 PTC-variant carriers in the ROSMAP cohort. b, Human snRNA-seq cohort overview. The diagram was created using BioRender. c, Metadata summary of the snRNA-seq cohort. n = 36 individuals. This snRNA-seq experiment was performed once. d, 2D UMAP of ABCA7 LoF gene perturbation scores (S = −log₁₀[P] × sign(log₂[fold change (FC)]); unadjusted Limma-Voom P values; n = 12 (LoF) and n = 24 (control) individuals), restricted to genes with |S| > 1.3. Red, S > 1.3; blue, S < −1.3; point size ∝ |S|. The top 10 genes are labelled. e, 2D UMAP coloured by gene cluster assignment (Gaussian mixture model). f, For each cluster, the top two enriched pathways (GO BP; hypergeometric enrichment, one-sided, unadjusted P < 0.01; relative to all genes in UMAP) and top five genes (highest absolute mean S across cell types among genes in enriched pathways, P < 0.01) are shown. g, Cell-type-specific scores per gene cluster (SC), calculated as the mean perturbation score (S) of all genes in each cluster. *FDR-adjusted P < 0.01, |SC| > 0.25. Ast, astrocytes; Ex, excitatory neurons; In, inhibitory neurons; Mic, microglia; Oli, oligodendrocytes.

Fig. 2. Transcriptional changes in ABCA7 LoF and ABCA7 p.Ala1527Gly excitatory neurons.

a, Kernel density plots of gene perturbation scores (S = −log₁₀[P] × sign(log₂[FC]); unadjusted Limma-Voom P values; n = 12 (LoF), n = 24 (control) individuals) per Kernighan–Lin cluster. Positive S indicates increased expression in ABCA7 LoF. The solid lines show the cluster means; the top pathways are indicated. Kernighan–Lin clustering performed on leading-edge genes from perturbed pathways (fGSEA, WikiPathways; unadjusted P < 0.05; Methods). b, Kernighan–Lin gene–pathway graph related to a: genes (circles) and pathways (squares) are indicated. c, Schematic of the ABCA7 gene, highlighting the p.Ala1527Gly variant (purple arrow). Cohort overview for snRNA-seq data from post-mortem PFC, comparing carriers of ABCA7 Gly1527 (≥1 allele) with Gly1527 non-carriers, that is, Ala1527 carriers (data from ref. ). The diagram was created using BioRender. d, Perturbation of ABCA7 LoF-associated gene clusters (from a) in excitatory neurons from Ala1527 (n = 227 individuals) versus Gly1527 (n = 133 individuals) carriers (fGSEA analysis of ABCA7 LoF clusters 0–7). Normalized enrichment scores (NES) are shown. The top unadjusted P values are indicated. Positive scores indicate upregulation in Gly1527 variant carriers. e, The closed-conformation ABCA7 structure, highlighting the simulated domain (residues 1517–1756, yellow) and the lipid bilayer (orange). The inset shows Ala1527 (grey) and Gly1527 (purple). f, The root mean squared deviation (r.m.s.d.) of the ABCA7 domain (from e) with the Ala1527 (grey) or Gly1527 (purple) variant, relative to the closed-conformation reference during simulations. Inset: the average positional fluctuations of Cα atoms. Statistical analysis was performed using a two-sided Mann–Whitney U-test. g, Projection of Cα atom positional fluctuations onto first two principal components for the Ala1527 (top, grey) and Gly1527 (bottom, purple) variants during simulations.

Fig. 3. ABCA7 LoF variants impact mitochondrial function in neurons.

a, iPS cell (iPSC)-derived isogenic iNs with ABCA7 PTC variants (exon 3: p.Glu50fs*3; exon 15: p.Tyr622*). The gene schematic shows exons (rectangles) and introns (lines). The diagram was created using BioRender. Confocal MAP2 staining is shown. b, Correlation of gene perturbation scores (S = −log₁₀[P] × sign(log₂[FC]); unadjusted P values were computed using Limma-Voom) from bulk mRNA-seq data. n = 2 (WT) and n = 5 (for each LoF line) wells. c, Kernighan–Lin clustering of leading-edge genes from perturbed pathways in WT versus p.Tyr622* iNs (fGSEA, WikiPathways; FDR-adjusted P < 0.05). For the gene–pathway graph, genes (circles) and pathways (squares) are indicated. d, Heat map (Jaccard index) comparing Kernighan–Lin (K–L) clusters from p.Tyr622* iNs and post-mortem neurons (from Fig. 2a,b). Upregulated (red) and downregulated (blue) clusters in LoF neurons are indicated. FDR-adjusted P was calculated by permutation (1,000 iterations, one-sided). e, Kernel density plots of gene perturbation scores per cluster. Positive S indicates increased expression in p.Tyr622* iNs. The solid lines show the cluster means. The top pathways are indicated. f, Volcano plot of genes encoding mitochondrial proteins (MitoCarta); genes with FDR-adjusted P < 0.05 (Limma-Voom) in WT versus p.Tyr622* iNs are coloured. The top ten upregulated and downregulated genes are labelled. g, Seahorse mitochondrial uncoupled OCR (%). n = 18 (WT), n = 17 (p.Tyr622*) and n = 13 (p.Glu50fs*3) wells; two experiments. h, MitoHealth intensity. n = 8 (WT), n = 11 (p.Tyr622*) and n = 9 (p.Glu50fs*3) wells; around 3 × 10³ cells per condition; three experiments. Statistical analysis was performed using a linear mixed-effects model. Maximum-intensity projections are shown with NeuN/GFP clipped at the 90th percentile, γ-corrected (γ = 0.5). i, The average TMRM intensity per 75th percentile mask (n = 4 (WT) and n = 5 (p.Tyr622*) wells; mean projection over time). j, The average CellROX intensity per 75th percentile mask. n = 10 wells per genotype. k, Differentially abundant lipid species in WT versus p.Tyr622* iNs (coloured by class); species are labelled if FDR-adjusted P < 0.05, |log[FC]| > 1, two-sided t-test, unequal variances assumed. n = 10 (WT) and n = 8 (p.Tyr622*) wells. For a–k, experiments were carried out after 4 weeks of differentiation; wells represent technical replicates. For g–j, analysis was performed using two-sided t-tests following Shapiro–Levene tests; the box plots show the median (centre line), interquartile range (IQR) (box limits) and 1.5 × IQR (whiskers). For g–j, datapoints represent the per-well mean. Experiments were performed once (a–f, j and k) or at least twice (g–i). Scale bars, 62 μm (a) and 125 μm (h–j).

Fig. 4. CDP-choline reverses ABCA7 LoF impacts in neurons.

a, Differentially abundant lipid species in p.Tyr622* iNs with or without CDP-choline. Species are labelled if unadjusted P < 0.05, |log[FC]| > 1 (two-sided t-test, equal variances assumed). n = 5 wells per condition. b, Correlation of gene scores comparing WT versus p.Tyr622* iNs and p.Tyr622* iNs with or without CDP-choline (n = 2 (WT), n = 5 (p.Tyr622* + H₂O) and n = 5 (p.Tyr622* + CDP-choline); experiment from Fig. 3). c, Kernighan–Lin clustering of leading-edge genes in p.Tyr622* iNs with or without CDP-choline (fGSEA, WikiPathways; FDR-adjusted P < 0.05). Gene–pathway graph: genes (circles) and pathways (squares) are indicated. d, Heat map (Jaccard index) comparing Kernighan–Lin clusters in p.Tyr622* iNs with or without CDP-choline and WT versus p.Tyr622* iNs (Fig. 3c,e). Upregulated (red) and downregulated (blue) clusters in p.Tyr622* iNs + CDP-choline relative to p.Tyr622* iNs or in p.Tyr622* iNs relative to WT are indicated; FDR-adjusted permutation P values (1,000 iterations, one-sided). e, Kernel density plots of gene scores per cluster. Positive S represents an increase in the p.Tyr622*+CDP-choline condition. The solid lines show the cluster means. The top pathways are indicated. f, Volcano plot of genes encoding mitochondrial proteins. Genes with FDR-corrected P < 0.05 (Limma-voom) in p.Tyr622* iNs with or without CDP-choline are indicated in colour. Bold font indicates shared top genes with Fig. 3f. g, Seahorse mitochondrial uncoupled OCR (%). n = 6 (p.Tyr622* + H₂O) and 8 (p.Tyr622* + CDP-choline) wells. h, The average TMRM intensity per masked region (75th percentile threshold; n = 8 wells per condition). i, The average CellROX intensity per masked region (75th percentile threshold; n = 10 wells per condition; same experiment as in Fig. 3j). j, Secreted Aβ, cortical organoids (182-day culture, with or without 1 mM CDP-choline for 4 weeks). n = 20 (WT), n = 19 (p.Tyr622*) and n = 14 (p.Tyr622* + CDP-choline) organoids. k, Spontaneous action potentials in dissociated cortical organoids (150 day culture, with or without 100 µM CDP-choline for 2 weeks). n = 7 (WT), n = 13 (p.Tyr622*) and n = 9 (p.Tyr622* + CDP-choline) cells. Statistical analysis was performed using two-sided Mann–Whitney U-tests following a Shapiro test. For a–i, 4-week differentiation was performed. +CDP-choline indicates treatment with 100 µM CDP-choline during the last 2 weeks; wells represent technical replicates. For g–k, the box plots show the median (centre line), IQR (box limits) and 1.5 × IQR (whiskers). For g–j, statistical analysis was performed using two-sided t-tests following Shapiro–Levene tests. Experiments were performed once (g, i and k) and at least twice (a–f, h and j). Scale bars, 125 μm (h and i).

Extended Data Fig. 1. Overview of human snRNA-seq cohort.

a, ABCA7 and RBFOX3 (NeuN) protein levels from postmortem human PFC (Supplementary Table 3) comparing control (N = 180 individuals) vs. ABCA7 LoF carriers (N = 5, “All”) and subset overlapping with snRNA-seq cohort (N = 6 control, N = 4 ABCA7 LoF, “Subset”). b, Distribution of continuous clinical variables (Supplementary Note 1) comparing control (N = 24) vs. ABCA7 LoF carriers (N = 12). c, Distribution of discrete metadata variables comparing control (N = 24) vs. ABCA7 LoF carriers (N = 12); Fisher’s exact tests (R stats::fisher.test, extended to r × c tables). d, Sanger sequencing validating three ABCA7 LoF variants in genomic DNA from ABCA7 LoF carriers and controls. Variant location indicated by black box; WGS sample IDs shown. e, Validation plots demonstrating concordance between SNP calls from WGS and snRNA-seq libraries per individual. Extreme outlier points (dark blue) indicate correct matches. f, 2D UMAP projection of single-cell gene expression coloured by transcriptionally defined cell type. a,b: boxplots show median, IQR (box), whiskers=1.5×IQR; two-sided Mann–Whitney U tests. a–f: experiments performed once.

Extended Data Fig. 2. Expanded view of ABCA7 LoF gene perturbation landscape.

a, 2D UMAP of ABCA7 LoF gene perturbation scores (S = −log10(p) × sign(log2(FC)); unadjusted Limma-Voom p-values, N subjects=12 LoF, 24 control), restricted to genes with |S | > 1.3. Red: S > 1.3, blue: S < −1.3; point size ∝ |S|. Top 50 genes labelled.

Extended Data Fig. 3. Shared differentially expressed genes across cell types.

a, Heatmap indicating overlap of differentially expressed genes (unadjusted Limma-Voom p < 0.05 in ≥3 cell types). b, Functional annotations of genes shown in the heatmap (same gene order as panel a).

Extended Data Fig. 4. Neuronal expression of ABCA7 in postmortem human brain.

a, ABCA7 detection rate (counts > 0) per major cell type in postmortem PFC (snRNA-seq; N cells=Ex 42,014, In 14,806, Ast 7,158, Mic 5,441, Oli 28,078, Opc 5,213). b, Normalized ABCA7 expression comparing glial cells (mean per individual across Oli, Opc, Ast, Mic) vs. neuronal cells (mean per individual across Ex, In) from snRNA-seq (N = 24 control, 12 LoF). Two-sided paired Wilcoxon test following Shapiro test. c, Normalized expression of indicated genes comparing NeuN− vs. NeuN+ cells (N = 6 individuals; 3 control, 3 AD, γH2AX− cells; data from ref. , Supplementary Table 3). Two-sided paired t-test following Shapiro test. a–b: boxplots show median, IQR (box), whiskers=1.5×IQR.

Extended Data Fig. 5. Annotation of excitatory neurons from postmortem snRNA-seq dataset by cortical layer.

a, UMAP visualization of excitatory neurons annotated by cortical layers (Leiden clustering; N cells=42,014 from ABCA7 LoF snRNA-seq cohort). b, Heatmap showing enrichment of cortical layer-specific marker genes (from ref. ) across annotated layers. Colours indicate average marker gene expression (log2(fold-change)) of each layer’s marker genes relative to all other clusters. c, Heatmap validating layer annotations using an independent set of cortical layer marker genes (from ref. ). Colours represent average marker gene expression (log2(fold-change)) relative to all other clusters. d, Perturbation of ABCA7 LoF-associated gene clusters identified in all excitatory neurons (Fig. 2a), stratified by cortical layer (N subjects=24 control, 12 LoF; fGSEA analysis of clusters 0–7). Normalized enrichment scores (NES) and unadjusted p-values shown.

Extended Data Fig. 6. Molecular dynamics simulations of ABCA7 open conformations with p.Ala1527Gly substitution.

a, Open-conformation ABCA7 protein structure highlighting simulation domain (residues 1517–1756, yellow). Inset shows expanded view of structures with Ala1527 (grey) and Gly1527 (purple) variants. b, Further expanded inset from panel a. c, Root mean squared deviations (RMSD) of the open-conformation ABCA7 domain (panel b) carrying Ala1527 (grey) or Gly1527 (purple), measured relative to open-reference structure during simulations. d, Projection of Cα atom positional fluctuations onto first two principal components during simulations for Ala1527 (top, grey) and Gly1527 (bottom, purple) variants. e, Violin plot showing average positional fluctuations of Cα atoms; Mann-Whitney test, two-sided; **** = p < =1e-4.

Extended Data Fig. 7. Local conformational fluctuations and secondary structure changes induced by the p.Ala1527Gly substitution in ABCA7 open and closed conformations.

a, Phi vs. Psi dihedral angle distribution of residue 1527 over simulation time in open and closed ABCA7 conformations. b, Overall Phi vs. Psi angle distributions of residue 1527 across the entire simulation, comparing open and closed conformations. c, Time-resolved secondary structure assignments for residues 1517–1537. Alpha-helical regions highlighted in red; other colours indicate distinct secondary structures. d, Fraction of alpha-helical content for residues 1517–1537 during simulations. A value of 1 indicates continuous alpha-helical structure throughout duration of the simulation. e, Structural alignment of closed-conformation ABCA7 (purple; PDB ID: 8EOP) with ABCA1 (cyan; PDB ID: 7TBW). Gly1527 (ABCA7) and corresponding residue Val1646 (ABCA1) indicated as spheres. f, Structural alignment of closed-conformation ABCA7 (purple; PDB ID: 8EOP) with ABCA4 (green; PDB ID: 7LKZ). Gly1527 (ABCA7) and corresponding residue Ile1671 (ABCA4) indicated as spheres. a,d: G1527 refers to the ABCA7 structure with the risk variant (as present in the reference structures; Supplementary Table 15); G1527A refers to the ABCA7 structure with the mutated Gly→Ala change made to the reference structure in PyMOL.

Extended Data Fig. 8. Electrophysiological characterization of iPSC-derived neurons harbouring ABCA7 PTC variants.

a, Representative sweeps showing action potentials elicited by 800 ms current injections in patched iNs. b, Action potential frequency (mean ± s.e.m.) elicited by varying injected currents in 4-week-old iNs; N cells = 10 WT, 13 p.Tyr622*, 23 p.Glu50fs*3. c, Representative sweeps of inward (top) and outward (bottom) currents recorded in 4-week-old WT neurons (N cells = 23). d, Quantification of currents from panel c. e, Resting membrane potential (mV) in 4-week-old WT, ABCA7 p.Tyr622*, and ABCA7 p.Glu50fs*3 iNs. f, Rheobase (pA) in 4-week-old WT, ABCA7 p.Tyr622*, and ABCA7 p.Glu50fs*3 iNs; WT vs p.Tyr622* p = 0.0424; WT vs p.Glu50fs*3 p = 0.0200. g, Action potential frequency elicited by indicated current injections in 4-week-old WT, ABCA7 p.Tyr622*, and ABCA7 p.Glu50fs*3 iNs; 10 pA: WT vs p.Glu50fs*3 p = 0.0491; 15 pA: WT vs p.Tyr622* p = 0.0003 and WT vs p.Glu50fs*3 p = 0.0109; 20 pA: WT vs p.Tyr622* p = 0.0007 and WT vs p.Glu50fs*3 p = 0.0160. e–g: n = 24 WT, 13 p.Tyr622*, 23 p.Glu50fs*3 4-week-old iNs. Bar plots indicate mean ± s.e.m. P values by two-way ANOVA indicated as: P < 0.05 (*), P < 0.001 (***).

Extended Data Fig. 9. mRNA-seq analysis of p.Glu50fs*3 iNs.

a, K/L clustering of leading-edge genes from perturbed pathways in WT vs. p.Glu50fs*3 iNs (fGSEA, Wikipathways; FDR-adjusted p < 0.05; N wells=2 WT, 5 p.Glu50fs*3). Gene-pathway graph: genes (circles), pathways (squares). b, Heatmap (Jaccard index) comparing K/L clusters from p.Glu50fs*3 iNs vs. p.Tyr622* iNs (from Fig. 3c). Average per-cluster gene score S (S = −log10(p)*sign(log2(FC))) indicated; $\overline{S}>0$ (red); $\overline{S}<0$ (blue); FDR-adjusted permutation p-values (1000 iterations, one-sided). c, Heatmap (Jaccard index) comparing K/L clusters from p.Glu50fs*3 iNs vs. postmortem neurons (Fig. 2a,b). Red/blue indicates direction as described in c; FDR-adjusted permutation p-values (1000 iterations, one-sided). d, Kernel density plots of gene perturbation scores S; unadjusted Limma-Voom p-values; N wells=2 WT, 5 per LoF) per cluster. Positive S indicates increased expression in p.Glu50fs*3. Solid lines show cluster means; top enriched pathways indicated. e, Correlation of gene perturbation scores S for genes encoding mitochondrial proteins (MitoCarta database, Supplementary Table 3; N wells=2 WT, N = 5 per LoF line). a–e: 4-week differentiation; wells=technical replicates; same mRNAseq experiment as Fig. 3b; experiment performed once.

Extended Data Fig. 10. Analysis of oxygen consumption rates (OCR) in WT vs ABCA7 LoF iNs.

a, Seahorse OCR curves (one representative experiment from Fig. 3g). Lines indicate per-condition mean; error bars represent 95% confidence intervals (N wells=10 WT, 7 per LoF line). b, Representative per-well OCR traces from panel a. c, Simplified schematic of mitochondrial bioenergetics in electrical terms: oxygen consumption by the respiratory chain generates a proton current (I) that builds the proton-motive force (Δp, voltage V); proton return through ATP synthase (cyan) for ATP production or through uncoupling protein (red) provides parallel resistances (R) that dissipate Δp; BioRender agreement # RS28ETN9LG; based on information in. d, Schematic depicting measurements of maximal and basal OCR used to calculate Spare Respiratory Capacity (SRC). e, Schematic showing measurement of uncoupled OCR (%). f, SRC computed for WT, ABCA7 p.Glu50fs*3, and ABCA7 p.Tyr622* iNs (N wells=18 WT, 17 p.Tyr622*, 13 p.Glu50fs*3; two experiments, same as Fig. 3g). Two-sided Mann–Whitney U test (WT vs. p.Tyr622*) and two-sided t-test (WT vs. p.Glu50fs*3, unequal variances), following Shapiro/Levine tests. g, UCP2 mRNA expression by genotype (N wells=2 WT, 5 per LoF; unadjusted Limma-Voom p-values). h, Average TMRM intensity per masked region (75th percentile threshold; N wells=4 WT, 5 p.Tyr622*; mean projection over time), under baseline conditions and after FCCP addition. Same experiment and images as Fig. 3i. Two-sided t-test assuming equal variance, following Shapiro/Levine tests for both comparisons. f, h: boxplots show median, IQR (box), whiskers=1.5×IQR. a–h: 4-week iN differentiation; g: experiment performed once, a, b, f, h ≥twice.

Extended Data Fig. 11. LC-MS lipidomics of ABCA7 LoF iNs.

a, Volcano plot of WT vs p.Glu50fs*3 showing differentially abundant lipid species, coloured by class. b, Table summarizing the significant species by lipid subclass. c, Fold-change distribution for triglycerides (TG) grouped by fatty-acid chain length and saturation (WT vs p.Glu50fs*3). d, Volcano plot highlighting perturbed phosphatidylcholines (PCs) that contain saturated or monounsaturated fatty acids (SFA/MUFA). e, As d but for PCs with polyunsaturated fatty acids (PUFA). f, Fold-change distribution for PCs grouped by chain length and saturation (WT vs p.Glu50fs*3). g, Table of significantly altered lipid species in WT vs p.Tyr622*, grouped by subclass (same experiment as Fig. 3k). h, Volcano plot comparing WT vs p.Tyr622* with saturated PCs highlighted in blue. i, TG fold-change distribution for WT vs p.Tyr622*. j, PC fold-change distribution for WT vs p.Tyr622*. k,l, mRNA expression changes of LPCAT genes in p.Tyr622* and p.Glu50fs*3 iNs relative to WT (unadjusted p by Limma-Voom; N wells=2 WT, 5 per LoF line). a-l: iNs differentiated for 4 weeks. a-j: Two-sided t-test assuming unequal variance; FDR-adjusted p < 0.05 and |log2(FC)| > 1 used to define significance. N wells= 10 WT, 8 p.Tyr622*, 6 p.Glu50fs*. Wells are technical replicates. g-l: experiment performed once, a-f ≥twice.

Extended Data Fig. 12. Treatment of p.Tyr622* iNs with CDP-choline.

a, Choline metabolites in media (targeted LC-MS; N wells=2 media-only, 4 cell-conditioned); “N/F”=not detected. b, Intracellular choline metabolites (targeted LC-MS; N = 8 wells/condition, 4 blanks). c, Differentially expressed choline synthesis and transport genes in p.Tyr622* ± CDP-choline iNs. d, Differentially expressed LPCAT genes in p.Tyr622* ± CDP-choline iNs. e, Phosphatidylcholine species log2 fold-changes by fatty acid chain length and saturation in p.Tyr622* ± CDP-choline (lipidomics; N = 5 wells/condition). f, PCA of untargeted LC-MS metabolite profiles from WT and p.Tyr622* ± CDP-choline iNs (N wells=9 WT, 7 per p.Tyr622* condition). g, PCA of mRNA-seq data from p.Tyr622* ± CDP-choline iNs. h, Correlation of gene perturbation scores (S = −log10(p) × sign(log2(FC)); unadjusted Limma-Voom p-values) for genes encoding mitochondrial proteins in WT vs p.Tyr622* and p.Tyr622* ± CDP-choline iNs (MitoCarta; Supplementary Table 3; N = 2 WT, 5 per p.Tyr622* condition). i, Seahorse OCR curves; lines=mean, error bars=95% CI. j, Representative OCR traces from panel i. k, SRC in p.Tyr622* ± CDP-choline (two-sided t-test, equal variances after Shapiro/Levene tests). l, MitoHealth intensity per NeuN⁺ volume (N = 11 wells p.Tyr622*+H₂O, 12 p.Tyr622*+CDP-choline; ~3 × 10³ cells/condition; three experiments; linear mixed-effects model). Visualization: maximum projections, NeuN/GFP clipped at maximum, γ-corrected (γ = 0.5). Individual points=well averages; same experiment as Fig. 3h. a,b: two-sided t-tests (equal variances). c,d,g: mRNA-seq; unadjusted Limma-Voom p-values; N = 5 wells/condition. i–k: N wells=8 p.Tyr622*+CDP-choline, 6 p.Tyr622*+H₂O (same experiment as Fig. 4g). a,b,k,l: boxplots=median, IQR (box), whiskers=1.5×IQR. a–l: 4-week iN differentiation; last 2 weeks, 100 µM CDP-choline. a-l: wells=technical replicates. a,b,e,f,i–k: experiments repeated once, c,d,g,h,l ≥twice.

Extended Data Fig. 13. CDP-choline treatment in cortical organoids.

a, Amyloid-β (Aβ40, Aβ42) levels quantified by ELISA from media of 4-week-old iNs (N wells=12 WT, 8 p.Tyr622*). Aβ40: two-sided t-test (equal variances); Aβ42: two-sided Mann–Whitney U test, following Shapiro–Levene tests. b, Representative images of cortical organoid slices by genotype; 5.5 months. c, Amyloid-β (Aβ40, Aβ42) levels quantified by ELISA from cortical organoid media (176-day-old), grouped by genotype and treatment (500 µM or 1 mM CDP-choline for 3 weeks). Samples correspond to organoids in Fig. 4k, analysed one week prior to assays presented there (N organoids=20 WT, 20 p.Tyr622*+H₂O, 15 p.Tyr622*+500 µM CDP-choline, 14 p.Tyr622*+1 mM CDP-choline). Statistical comparisons (two-sided t-tests): Aβ40: WT vs p.Tyr622* (unequal variances), p.Tyr622*±500 µM (unequal variances), p.Tyr622*±1 mM (equal variances). Aβ42: all comparisons (equal variances). All tests followed Shapiro–Levene tests. a,c: boxplots=median, IQR (box), whiskers=1.5×IQR. a-c: experiments performed once.