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  • Methylome analysis of FTLD patients with TDP-43 pathology identifies epigenetic signatures specific to pathological subtypes | Molecular Neurodegeneration

    Methylome analysis of FTLD patients with TDP-43 pathology identifies epigenetic signatures specific to pathological subtypes | Molecular Neurodegeneration

    Thousands of differentially methylated CpGs characterize individual FTLD-TDP pathological subtypes

    RRBS was performed to generate DNA methylation profiles from pairs of frozen post-mortem FCX and CER from FTLD-TDP patients (FTLD-TDP types A, B and C, GRN mutation carriers and C9orf72 repeat expansion carriers) and neuropathologically normal controls (Fig. 1A). After QC, 5,819,868 CpGs in FCX and 5,936,364 in CER were included in the analyses. 90% of the total number of retained CpGs overlapped between both tissues, with similar distributions with respects to genomic region, CpG island and regulatory element context (Fig. 1B). Differential methylation analysis was then performed at the CpG site level in both tissues, between each individual pathological subgroup and controls (Supp. Tables 2 and 3). Across all groups, we found 6,453 differentially methylated CpG sites (FDR < 0.05) in FCX and 7,018 in CER. In both brain regions, the majority of differentially methylated CpGs were in a gene body (61.1% in FCX and 54.1% in CER), followed by gene promoters (27.1% in FCX and 34.7% in CER), 3’-UTRs (5.9% in FCX and 4.1% in CER), 5’-UTRs (4.2% in FCX and 5.5% in CER), and a small proportion of intergenic CpGs (1.6% in both FCX and CER; Fig. 1C). In each tissue we found approximately the same number of CpGs to be hypo- and hypermethylated in FTLD-TDP patients, when compared to controls (Fig. 1D). Interestingly, the vast majority of differentially methylated CpGs we identified were unique to a disease subtype, with less than 10% of sites shared between two or more individual patient subgroups in both FCX (381 CpGs representing 6%; Fig. 1E) and CER (424 sites representing 6%; Fig. 1F). Of the overlapping CpGs in FCX, only six were found to be differentially methylated only in genetically unexplained groups of patients (TDP-A, TDP-B and TDP-C), annotated to CDH15, FN3KRP, HS1BP3, CYP2W1, NDUFAF6, TP53INP1 and ZIC3, whereas only two CpGs (within PLCB3 and UBE2A) were found differentially methylated across all pathological subtypes. In CER, no CpG sites were found in common between only genetically unexplained subgroups or all patients. Although we found that CpG positions were not commonly shared between disease groups, we did identify overlaps when analyzing the intersection of annotated genes from all differentially methylated CpGs. We found that 28.2% of genes overlapped between the different groups in FCX (1,327 genes; Supp. Figure 2 A) and 29.4% in CER (1,592 genes; Supp. Figure 2B). In FCX, the largest overlap was observed between TDP-A and all other disease subtypes, the majority being shared with TDP-GRN and TDP-B. Furthermore, we identified 25 genes in FCX and 20 in CER harboring differentially methylated CpG sites only within the sporadic patient groups (none of which was in common between both tissues), and 41 genes in FCX and 16 in CER where differentially methylated CpG sites were found across all patient groups, of which four were detected in both brain regions (HDAC4, PRDM16, PTPRN2 and RASA3, Supp. Tables 2 and 3). When analyzing the genes containing the most differentially methylated CpGs (≥ 5 CpGs) within each pathological subgroup, we found that in FCX, the TDP-A group had the highest number of such genes (N = 16), followed by TDP-GRN (N = 5), TDP-C (N = 5), TDP-B (N = 2) and finally TDP-C9 (N = 1) (Supp. Table 2). In CER however, we found the TDP-C9 group to have the highest number of such genes (N = 12), followed by TDP-A (N = 8), TDP-C (N = 7), and lastly TDP-GRN (N = 1) with none in TDP-B (Supp. Table 3). We next sought to investigate shared epigenetic mechanisms between patients, by combining groups of patients and comparing those to controls (genetically unexplained group ‘ABC’ including TDP-A/B/C and group ‘TDP’ including all TDP patients). We found that group ‘ABC’ only contributed 54 unique CpG sites in FCX and 108 in CER, representing 24 and 58 unique genes in FCX and CER, respectively (Supp. Tables 2 and 3). Group ‘TDP’ further contributed only a few additional unique CpGs with 13 in FCX and 8 in CER, representing 10 unique genes in FCX and 5 in CER, further supporting the specificity of findings to pathological subtypes, rather than shared disease mechanisms (Supp. Tables 2 and 3). Finally, to determine whether our findings are also brain region specific, we compared FCX to CER and found that only 64 CpG sites are common between brain regions across all disease groups (Supp. Tables 2 and 3). In terms of genes harboring differentially methylated CpGs, we also found a limited overlap between tissues, with 406 genes in TDP-A, 141 in TDP-B, 200 in TDP-C, 151 in TDP-GRN and 301 in TDP-C9, supporting the specificity of disease-associated methylation patterns not only to pathological subtypes but also to the brain region.

    Fig. 1

    RRBS identifies thousands of differentially methylated CpGs in brain tissue from FLTD-TDP patients. Study outline (A). Proportion of CpGs in different contexts including: genomic region, which relates to the CpG position relative to the annotated genes; overlap with a known CpG island (CGI); overlap with regulatory features (enhancers, enh); and genetic context considering only common single nucleotide polymorphisms (SNP). Graphs show the proportion of CpGs in both FCX (blue bars) and CER (red bars) including either all CpGs retained in the study (B) or only significantly differentially methylated sites across all patient groups (C). Distribution of differentially hypomethylated (light shades) and hypermethylated (dark shades) CpGs across all groups, in FCX (left; blue graph) and CER (right; red graph) (D). Upset plot showing the number of unique and overlapping CpGs in each pathological group, considering all differentially methylated CpGs in FCX (E) and CER (F)

    RRBS identifies differentially methylated CpGs in known FTLD genes

    Next, we employed a targeted approach to investigate the presence of differentially methylated CpGs (FDR < 0.05) in both FCX and CER within known FTLD genes [8], including CHCHD10 [55], CHMP2B [56], CSF1R [57], C9orf72 [58, 59], FUS [60], GRN [61, 62], hnRNPA1 [63], hnRNPA2B1 [63], LRRK2 [64], MAPT [65], OPTN [66], SQSTM1 [67], TARDBP [5], TBK1 [66], TIA1 [68], UBQLN2 [69], VCP [70], as well as the recently implicated UNC13A [71,72,73], TNIP1 [73] and ANXA11 [74, 75]. We also included three additional genes previously reported to be differentially methylated in FTLD patients: SERPINA1 specifically in the C9orf72 repeat extension carrier group [76], and NFATC1 and OTUD4 which were reported across different FTLD pathological subtypes [29]. Overall, only few differentially methylated CpGs were found in these genes (Table 2); however, in the case of GRN and C9orf72 the previously identified differentially methylated regions in these genes were poorly covered in our study. Furthermore, and despite none of them overlapping with the previously reported CpG in intron 9, we did find that NFATC1 harbored numerous differentially methylated CpGs across multiple patient subgroups (Supp. Figure 3A). Of the differentially methylated CpGs in NFATC1 that we identified in the FCX, several showed high regulatory potential due to their location within the gene (promoter and both 5’- and 3’-UTRs). Given the previously reported finding that the expression of NFATC1 is increased in FCX from FTLD patients, we investigated NFATC1 expression in our previously generated bulk RNA sequencing dataset [10] and also found higher expression of NFATC1 in FCX from FTLD-TDP patients, when compared to controls (Supp. Figure 3B). We next tested the correlation between methylation levels at each differentially methylated CpG site in FCX and NFATC1 expression, in all FTLD-TDP patients for which both datasets were available, and found that methylation levels at the 5’-UTR CpG negatively correlated with the expression level of NFATC1 (r= -0.29; P = 0.0034; Supp. Figure 3C) suggesting that in addition to the previously reported intronic CpG, this 5’-UTR CpG may also play a role in regulating NFATC1 in FCX.

    Table 2 Distribution of significantly differentially methylated CpGs within known FTLD genes

    Promoter level differential methylation analysis identifies 12 promoter loci in FCX and 8 in CER

    The single-base resolution of our data allows the investigation of individual CpG sites, much like array-based studies where methylation is profiled at single CpG sites and with only a few sites being profiled per gene; however, CpGs are most often clustered within CpG islands located in genomic areas with likely functional significance. As such, we sought to investigate whether aberrant methylation patterns are observed in CpG islands, in the brain of FTLD-TDP patients. For this, CpG sites were grouped into regions, and differential methylation analysis at the region level was performed. First, we included only loci located within gene promoters (defined by location ± 500 bp from the TSS) and performed differential methylation analysis in FCX and CER separately. We identified 12 differentially methylated regions (DMRs) in FCX and eight in CER, annotated to the promoters of 15 and 13 genes, respectively (Tables 3 and 4). In both tissues, we identified both hypo- and hypermethylated loci (67% hypo- and 33% hypermethylated in FCX; 50% hypo- and 50% hypermethylated in CER). None of the loci overlapped between brain regions and interestingly, promoter DMRs were mostly identified in genetically unexplained FTLD-TDP patients (subtypes TDP-A, TDP-B and TDP-C in FCX; subtype TDP-C in CER). Finally, in FCX only two loci were found in common between patient groups (TRIM34 and LINC01954) whereas in CER no shared loci were identified.

    Table 3 Results from the differential methylation promoter analysis in frontal cortex
    Table 4 Results from the differential methylation promoter analysis in cerebellum

    Genome wide region level analysis identifies hundreds of differentially methylated loci in FCX and CER

    Next, we expanded our analyses beyond promoters to genome wide level, while still performing group comparisons in each brain region separately. From these analyses we identified hundreds of differentially methylated DMRs, with a total of 131 in FCX and 215 in CER across all patient groups, annotated to 123 and 203 genes, respectively (Fig. 2A and B; Supp. Fig. 4A and B; Supp. Tables 4 and 5). Of these, we found a similar proportion of hyper- and hypomethylated loci in both tissues, with most loci being hypomethylated (Fig. 2C; Supp. Tables 4 and 5). Regarding the genomic context of these loci in both tissues, the overwhelming majority was located within a gene body (75% in FCX and 80% in CER), followed by gene promoters (12% in FCX and 11% in CER), 3’-UTRs (9.5% in FCX and 6% in CER), and a small proportion in intergenic regions (2% in FCX and 1% in CER) and within 5’-UTRs (1.5% in FCX and 2% in CER; Fig. 2D; Supp. Tables 4 and 5). Akin to our findings from the CpG-level analyses, most DMRs are unique to pathological subtypes and thus, combining patient subgroups for analysis only contributed a limited amount of additional DMRs with three in FCX (annotated to PSMA6 in group ABC, and to NDUFA10 and SEMA3C in group TDP) and four in CER (annotated to FHL2, PDGFRA, and BLCAP in group ABC, and DHDDS in group TDP). In FCX, the strongest finding overall was a hypomethylated gene body DMR within GFPT2 (which spans exons 14 and part of the adjacent introns) in several group comparisons (TDP-B, TDP-C, TDP-GRN, group ABC, and group TDP; Supp. Table 4). Interestingly, and although not as strong as in FCX, GFPT2 is one of only five genes where DMRs were found in both FCX and CER (TDP-B; Table 5). We selected this locus to validate our RRBS finding, focusing on TDP-C which showed the strongest effect (logFC= -2.27; FDR = 1.2E-03; Supp. Figure 4C). We selected one highly methylated sample (> 80% methylation), one lowly methylated sample (< 20% methylation), as well as two samples with intermediate methylation per group (N = 4 TDP-C and N = 4 neuropathologically normal controls) based on methylation values across the region, measured by RRBS. Bisulfite sequencing (BS) targeted to the GFPT2 DMR showed at most a 10% difference in methylation level (range 1–10%) as compared to RRBS, with none of the samples changing their categorical classification of high/intermediate/low methylation, providing support and validation to our RRBS findings (Supp. Figure 4D).

    Fig. 2
    figure 2

    RRBS identifies hundreds of DMRs in brain tissue from FLTD-TDP patients. Upset plot showing the number of unique and overlapping DMRs in each pathological group, in FCX (A) and CER (B). Distribution of hypomethylated (light shades) and hypermethylated (dark shades) DMRs across all groups, in FCX (left; blue graph) and CER (right; red graph) (C). Proportion of DMRs in the context of its position relative to the annotated genes. Proportions are shown for both FCX (blue bars) and CER (red bars) DMRs across all groups (D)

    Table 5 Genes harbouring DMRs in both frontal cortex and cerebellum

    Additionally, between the two DMR analyses (promoter and genome-wide), we identified only three loci in common, with one in FCX (overlapping PARVG/PARVB; Table 3 and Supp. Table 4), and two in CER (overlapping DHX33/DHX33-DT and a known CpG island within OTX2/OTX2-AS1; Table 4 and Supp. Table 5).

    Finally, we investigated whether an impaired epigenetic machinery could represent a potential mechanism underlying the widespread DNA methylation changes we observed in FTLD-TDP patients. Using our previously generated bulk RNA sequencing dataset [10] we assessed expression levels of a subset of genes encoding for DNA methylation ‘writers’ or methyltransferase enzymes (DNMT1 responsible for methylation maintenance, and DNMT3A/B responsible for de novo methylation), as well as DNA methylation ‘erasers’ (TET1, TET2 and TET3, which are key players in the first step of the demethylation process), in FTLD-TDP patients and neuropathologically normal controls. Results from these analyses highlight expression changes in FCX in genes from both groups of DNA methylation regulators, namely DNMT1 (higher in FTLD-TDP; P = 4E-03) and TET3 (lower in FTLD-TDP: P = 2.7E-05), whereas in CER we found changes in TET1 (lower in FTLD-TDP; P = 1.3E-02) (Supp Fig. 5A). Furthermore, besides global changes across all FTLD-TDP patients, we also observed specific expression patterns of the assessed genes to some pathological subtypes (Supp Fig. 5B), suggesting that to some extent, differential expression of epigenetic machinery components may contribute to the methylation changes we observe with both pathological subtype and brain region specificity.

    Enrichment analysis identifies distinct processes in TDP pathological subtypes

    To gain insight into potential underlying functions or pathways in genetically unexplained FTLD-TDP patients (sporadic patient groups TDP-A, TDP-B, TDP-C and combined ‘ABC’) where we identified the most changes, we next performed Gene Ontology (GO) analyses focusing on the “Biological Process” (BP) and “Molecular Function” (MF) categories and using the differentially methylated genes from all analysis in each pathological group as input in FCX and CER separately (Supp. Tables 6 and 7). In the BP category, we identified 53 clusters of related terms in FCX and 52 in CER. In the MF category, we identified substantially less clusters with seven in FCX and eight in CER (Supp. Tables 6 and 7).

    In the BP category, although we observed overall a large overlap of identified clusters (several related enriched terms that cluster together; Supp. Table 6), the top 3 processes are largely non-overlapping between pathological subtypes as well as tissue types (Fig. 3A). In TDP-A, terms related to nervous system and synapse development and regulation were the most significant in both FCX and CER (cluster 43; top GO term “Nervous system development”; 3.82E-10 in FCX and 7.11E-06 in CER). We further detect enrichment in FCX for terms related to regulation of phosphorylation, glycolysis, and protein modification (cluster 15; top GO term “Protein autophosphorylation”; P = 4.29E-06). Of note, and albeit not in the top 3, we identified two clusters that are not only unique to FCX but also to a specific pathological subtype. These included cluster 2 in TDP-A including terms related to DNA damage repair (top GO term “Recombinational repair”, P = 0.039), and cluster 37 in TDP-B including terms related to cholesterol biosynthesis (top GO term “Regulation of cholesterol biosynthetic process”, P = 0.011) (Supp. Table 6; Supp Fig. 6). In CER from TDP-B, we found the strongest enrichment in terms related to regulation of signaling pathways and transduction (cluster 31, top Go term “Regulation of signal transduction”; P = 6.64E-04). In TDP-C, we found an enrichment in terms related to protein localization and membrane receptor clustering in FCX (cluster 55; top GO term “Protein localization to membrane”; P = 1.01E-04), and to regulation of DNA-templated transcription in CER (cluster 1; top GO term “Positive regulation of transcription by RNA Polymerase II”; P = 2.27E-06). Across all groups in FCX, terms related to ion transport were highly enriched (cluster 51), whereas in the combined ABC group, we detected the strongest enrichment in terms related to protein and histone deubiquitination processes (cluster 52; top GO term “Protein K48-linked deubiquitination”; P = 3.25E-04).

    Fig. 3
    figure 3

    Top 3 clusters of Gene Ontology terms enriched in FTLD-TDP pathological groups. Clusters of GO terms significantly enriched in each sporadic pathological group in FCX (left; blue boxes) and CER (right; red boxes) from the biological process (A) and molecular function (B) categories. Results are shown for the most significant enriched terms in the top 3 clusters from each group, with circle color representing Pvalue and circle size representing the gene ratio in the term

    Finally, in the MF category, we observed a large overlap of enriched clusters between pathological subtypes and across tissues (Supp. Tables 6 and 7). Importantly, we found two clusters in common between all TDP subtypes in both brain regions, namely terms related to binding to DNA and transcriptional regulatory regions (cluster 3), as well as ion channel and calcium transporter activity (cluster 13) (Fig. 3B; Supp Fig. 6).

    Methylation levels at several DMRs correlate with gene expression levels

    Given that altered gene expression is the most common and well-studied consequence of aberrant methylation, we next interrogated our previously generated bulk brain transcriptomic dataset [10] to assess correlations between methylation levels within all DMRs (from both promoter and genome-wide analyses) and the expression of the associated gene(s) for which expression was measured in FCX or CER. When several overlapping DMRs were identified within the same gene, they were merged into one single DMR with the coordinates of the largest region, whereas if several non-overlapping DMRs were identified within the same gene, they were treated as independent DMRs with correlations calculated for each. To increase statistical power, correlations were calculated including all study individuals (ALL; FTLD-TDP and controls combined) (Fig. 4; Supp. Tables 8 and 9). We found correlations between methylation and expression of the annotated gene for nine DMRs in FCX (CCDC169-SOHLH2, CAMTA1, DYSF, ICMT, LINC02139, NDUFA10, PDZD4, SPAG7 and WBP2NL; Fig. 4A) and 14 in CER (ARMC2, ATP2B3, BARHL1, BBS9, CSAG1, DEF8, MTAP, MYO15B, OTX2, PLD5, PLXNA3, PM20D1, PWWP3A and SORCS2; Fig. 4B). Interestingly, for four genes in FCX, we found that the correlations became stronger when including only FTLD-TDP patients, namely CAMTA1, PDZD4, WBP2NL, and DYSF, suggesting that disease environment may play a role in the methylation effect (Supp. Table 8). Next, for each of the 23 genes, we investigated whether differential expression was observed in the pathological subtypes where the DMR was identified, which was the case for nine genes: (i) five in FCX, namely CAMTA1 (lower expression in the TDP-A group; P = 1.9E-10); PDZD4 (lower expression in the TDP-GRN group; P = 4.12E-08); SPAG7 (lower expression in the TDP-GRN group; P = 5.6E-04); NDUFA10 (lower expression in all FTLD-TDP combined; P = 9.6E-04); and WBP2NL (higher expression in the TDP-A group; P = 0.011) (Fig. 5A); and (ii) four in CER, with three in the TDP-C group, namely ATP2B3 (lower expression in TDP-C; P = 5.9E-05); PLD5 and OTX2 (higher expression in TDP-C; P = 4.0E-03 and P = 0.034, respectively), and BBS9 in the TDP-C9 group (higher expression in TDP-C9; P = 2.1E-03) (Fig. 5B). No differential expression was observed for the other genes within the groups where the DMR was identified, compared to controls. In addition, for some genes we observed differential expression in pathological subtypes beyond those where the DMR was identified (Supp. Figure 7), suggesting that additional factors besides DNA methylation may modulate the expression of these genes. One such factor could be altered expression of epigenetic machinery components that regulate transcription via epigenetic modulation. To explore this hypothesis, we investigated whether the expression of a subset of genes encoding for methyl-CpG binding proteins (MBPs; namely MBD1, MBD2, MBD3 and MECP2), which bind to methylated DNA and recruit additional factors to modulate gene expression, was altered in FLTD-TDP patients. Results from these analyses show that in FTLD-TDP patients, MBD2 expression is increased in both FCX and CER (P = 1.6E-02 and P = 3.6E-03, respectively), as well as MBD3 in CER (P = 4.7E-03), as compared to neuropathologically normal controls (Supp Fig. 8), suggesting that differential expression of such components may play a role in the limited correlation between differentially methylated genes and their expression.

    Fig. 4
    figure 4

    DMR methylation levels correlate with expression of annotated genes. Pearson correlation between DMR methylation and expression levels of the annotated genes for 9 genes in FCX (A) and 14 genes in CER (B). Only significant correlations are shown, and plotted are the strongest correlations for each gene, either including controls (all samples) or only FTLD-TDP patients (all FTLD-TDP) as indicated in the X-axis (see also Supp. Table 8)

    Fig. 5
    figure 5

    DMR containing genes are differentially expressed. Gene expression of all genes for which expression correlates with methylation levels in FCX (A) and CER (B). Comparisons are shown for expression levels of the annotated gene between controls and the pathological group in which the DMR was identified, as indicated in the X-axis. Pvalue from each comparison is shown, with ns = not significant

    CAMTA1 expression is mediated by both methylation changes and TDP-43 levels

    Its pivotal role in several processes such as regulating long-term memory [77] as well as neuronal development, maturation and survival [78], together with evidence of being a TDP-43 target [11, 79,80,81], made CAMTA1 an especially interesting and relevant finding in the context of FTLD-TDP pathology. As such, we selected this locus for further follow up. A closer inspection of the 185 bp CAMTA1 DMR revealed that it is located within intron 6 of CAMTA1 (NM_015215) in chromosome 1p36 (Supp Fig. 9A), and harbors several hypomethylated CpGs in the TDP-A group compared to controls (Supp. Figure 9B). First, to validate our CAMTA1 DMR finding, we investigated whether we could detect differential methylation at the CAMTA1 DMR, measured with an alternative technique to RRBS. For this, FCX DNA samples from TDP-A (N = 25) and control (N = 28) individuals overlapping with the RRBS study, were sequenced using ONT long-read sequencing, which also profiles CpG methylation. With ONT long-read sequencing we also confirmed the lower methylation levels in the TDP-A group compared to controls (logFC = -0.366; P = 0.0176; Fig. 6A). Next, also using ONT long-read sequencing, we sought to replicate this finding using an independent cohort of TDP-A (N = 80) and control (N = 22) samples, which corroborated the finding showing a hypomethylated DMR in TDP-A patients compared to controls (logFC = -0.276; P = 0.0363) (Fig. 6B). When combining the discovery and replication cohorts, a similar effect was observed (logFC = -0.27; P = 3.76E-03; Supp Fig. 9C). Next, using ONT sequencing data in the full cohort, we analyzed individual CpG sites within the CAMTA1 DMR to determine the most relevant CpGs driving the hypomethylation signal. We observed lower methylation in the TDP-A group at all CpGs measured in the locus, with CpG numbers 6, 7, 8 and 11 showing the strongest effect (Fig. 6C), suggesting that these sites have the highest predictive value as proxy for the methylation levels within the region. Finally, to confirm previous reports of CAMTA1 being a TDP-43 target, we used an additional transcriptomic dataset from TARDBP KD hiPSC-derived cortical neurons [50], which revealed a positive correlation between the expression of CAMTA1 and TARDBP genes, albeit just below significance using the limited data points available (r = 0.74, P = 0.057; Supp. Figure 9D), suggesting that CAMTA1 is indeed a TDP-43 target. To disentangle the relationship between the effects of TDP-43 dysfunction and methylation on the levels of CAMTA1, we next compared CAMTA1 levels within the group of TDP-A patients using stratification by methylation level, based on RRBS values across the CAMTA1 DMR (N = 20; comparing 10 samples with the highest methylation to 10 samples with the lowest methylation levels). This again showed lower CAMTA1 expression in the lower methylation group compared to the higher methylation group (P = 7.5E-03; Fig. 6D), suggesting that methylation changes at this DMR affect CAMTA1 expression independently and cumulatively to TDP-43 dysfunction.

    Fig. 6
    figure 6

    CAMTA1 is differentially methylated in TDP-A. Methylation levels measured by ONT long-read sequencing in FCX from controls (N = 28) and TDP-A (N = 25) overlapping with the RRBS study (CAMTA1 validation) (A) or in an independent replication cohort of controls (N = 22) and TDP-A (N = 80) (B). Plotted are both haplotypes from each sample and the adjusted Pvalue from each comparison is shown. Methylation levels measured by ONT long-read sequencing in the full cohort (combined validation and replication) of controls (dark shade boxes) and TDP-A (light shade boxes) at each CpG profiled within the CAMTA1 DMR. Wilcoxon signed-rank test with *P < 0.05 and **P < 0.01 (C). CAMTA1 expression levels in TDP-A patients (N = 20) stratified by methylation levels (N = 10 highest and N = 10 lowest samples; dark and light shades, respectively) as measured by RRBS

    Aberrant methylation at the CAMTA1 DMR alters expression of additional genes in the 1p36 locus

    Mining the UCSC Genome Browser [82] revealed that this intronic DMR, which is not within a known CpG island, overlaps with an open chromatin region (defined by the DNaseI hypersensitivity clusters track from ENCODE V3), as well as several transcription factor binding sites (defined by the Transcription factor ChiP-seq clusters track from ENCODE V3), suggesting a high regulatory potential (Supp. Figure 10). Analyzing additional datasets aimed at profiling genome-wide regulatory elements (Roadmap Epigenomics [83], GeneHancer [84]) further revealed that the DMR overlaps an enhancer element (GH01J006404; GeneHancer) of which CAMTA1 is a predicted target (Supp. Figure 10). Broadening the analysis to the intron that harbors the DMR revealed a region rich in enhancer elements predicted to target several genes within the locus. Specifically in brain tissue [85], evidence supports the existence of enhancer elements in several brain regions predicted to target the neighboring gene VAMP3 (Supp. Figure 10). Given that methylation changes may alter chromatin conformation and thus affect the functioning of regulatory elements, we investigated whether aberrant methylation at the CAMTA1 DMR alters the expression of additional genes in the locus, besides CAMTA1. Testing all genes within 1 MB from the DMR, we found that methylation levels within the region correlate with the expression of VAMP3 (rTDP = -0.3, PTDP = 6.2E-03) and PARK7 (rTDP=0.25, PTDP=0.022) in FCX; however, only within TDP patients (Supp Table 10; Fig. 7A). When comparing TDP-A to controls, we found that only VAMP3 is differentially expressed in FCX (increased in the TDP-A group; P = 1.1E-03; Fig. 7B; Supp Fig. 11A) and that expression changes are also observed in additional pathological groups (Supp. Figure 11B). Furthermore, when investigating the effect of methylation on gene expression, within TDP-A patients stratified by methylation levels, we found that VAMP3 is differentially expressed between the two groups, with higher VAMP3 expression in the low methylation group (P = 0.015; Fig. 7C). Finally, querying the CLIPdb module of the POSTAR3 database [81] revealed no TDP-43 binding sites within VAMP3 in brain tissue, which is corroborated by our own transcriptomic dataset from TARDBP KD neurons (Supp. Figure 11C), suggesting that VAMP3 is not a TDP-43 target and that expression changes might be, at least in part, modulated by methylation changes at the CAMTA1 DMR. Taking ours and others’ findings together, we propose a working model for the CAMTA1 DMR and locus where on the one hand, in healthy brains, CAMTA1 levels are maintained both via nuclear TDP-43 (i.e. promoting adequate CAMTA1 splicing and expression through direct binding to the 5’-UTR), as well as correct gene body methylation. On the other hand, aggregation and subsequent accumulation of TDP-43 in the cytoplasm leads to TDP-43 loss-of-function and lower TDP-43-dependent CAMTA1 levels. In addition, and independently from TDP-43 dysfunction in TDP-A patients, hypomethylation within the CAMTA1 gene body alters chromatin availability and/or function of regulatory elements in the locus, further reducing CAMTA1 expression while activating nearby genes such as VAMP3. Dysfunction of both CAMTA1- and VAMP3-dependent mechanisms may contribute to neurodegeneration and the pathology observed in TDP-A patients. (Fig. 8).

    Fig. 7
    figure 7

    Methylation changes at the CAMTA1 DMR alters expression of additional genes in the locus. Pearson correlation between methylation levels at the CAMTA1 DMR and the expression levels of VAMP3 (left panel) and PARK7 (right panel) in FCX from FTLD-TDP patients (A). VAMP3 expression levels in FCX from controls and TDP-A (B) and only in TDP-A patients (N = 20) stratified by methylation levels (N = 10 highest and N = 10 lowest samples; dark and light shades, respectively) as measured by RRBS (C)

    Fig. 8
    figure 8

    Proposed CAMTA1 double-hit model. In normal physiological conditions, TDP-43 is shuttled between the cytoplasm and the nucleus where it exerts its function. Once in the nucleus, TDP-43 ensures correct splicing of CAMTA1 and enhances CAMTA1 expression through direct binding to the 5’-UTR. Physiological levels of CAMTA1 are thus maintained by proper TDP-43 function and normal CAMTA1 methylation. In FTLD-TDP brains, as a consequence of TDP-43 aggregation, TDP-43 is less available in the nucleus and no longer ensures proper CAMTA1 splicing and/or binding to its 5’-UTR, thereby reducing CAMTA1 expression. In addition, and independently from TDP-43 dysfunction in TDP-A patients, due to a combination of factors such as disease environment and/or environmental exposures, methylation within the CAMTA1 gene body is lost. Hypomethylation in this region affects the expression of CAMTA1 and additional genes in the locus such as VAMP3, possibly through altering chromatin conformation and/or transcription factor binding, which in turn modulates the function of regulatory elements in the locus. As a transcriptional activator of several target genes, CAMTA1 is involved in a multitude of processes that are critical for neuronal health. Impairment of such CAMTA1-dependent mechanisms in a double-hit fashion produced by both nuclear TDP-43 and CAMTA1 methylation levels, together with alterations in processes regulated by VAMP3, may contribute to neurodegeneration and the pathology observed in TDP-A patients

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  • The Effectiveness of Structured Neurologic Music Therapy on Phonation and Breathing Function Following COVID-19

    The Effectiveness of Structured Neurologic Music Therapy on Phonation and Breathing Function Following COVID-19


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  • Astronomers Discover 3I/ATLAS, Largest Interstellar Comet Yet Detected

    Astronomers Discover 3I/ATLAS, Largest Interstellar Comet Yet Detected

    Astronomers have discovered the third interstellar comet to pass through our solar system. Named 3I/ATLAS (initially A11pl3Z), it was first spotted July 1 by the ATLAS telescope in Chile and confirmed the same day. Pre-discovery images show it in the sky as far back as mid-June. The object is racing toward the inner system at roughly 150,000 miles per hour on a near-straight trajectory, too fast for the Sun to capture. Estimates suggest its nucleus may be 10–20 km across. Now inside Jupiter’s orbit, 3I/ATLAS will swing closest to the Sun in October and should remain observable into late 2025.

    Discovery and Classification

    According to NASA, in early July the ATLAS survey telescope in Chile spotted a faint moving object first called A11pl3Z, and the IAU’s Minor Planet Center confirmed the next day that it was an interstellar visitor. The object was officially named 3I/ATLAS and noted as likely the largest interstellar body yet detected. At first it appeared to be an ordinary near-Earth asteroid, but precise orbit measurements showed it speeding at ~150,000 mph – far too fast for the Sun to capture. Astronomers estimate 3I/ATLAS spans roughly 10–20 km across. Signs of cometary activity – a faint coma and short tail – have emerged, earning it the additional comet designation C/2025 N1 (ATLAS).

    Studying a Pristine Comet

    3I/ATLAS was spotted well before its closest approach, giving astronomers time to prepare detailed observations. It will pass within about 1.4 AU of the Sun in late October. Importantly, researchers can study it while it is still a pristine frozen relic before solar heating alters it. As Pamela Gay notes, discovering the object on its inbound leg leaves “ample time” to analyze its trajectory. Astronomers are now racing to obtain spectra and images – as Chris Lintott warns, the comet will be “baked” by sunlight as it nears perihelion.

    Determining its composition and activity is considered “a rare chance” to learn how planets form in other star systems. With new facilities like the Vera C. Rubin Observatory coming online, researchers expect more such visitors in the years ahead. 3I/ATLAS offers a rare chance to study material from another star system.

     

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    NASA’s New Horizons Proves Deep-Space Navigation via Stellar Parallax


    Narivetta OTT Release Date: When and Where to Watch Tovino Thomas Starrer Political Drama Online?


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  • Ingram Micro Confirms Ransomware Attack, Working To Restore Systems To ‘Process And Ship Orders’

    Ingram Micro Confirms Ransomware Attack, Working To Restore Systems To ‘Process And Ship Orders’

    ‘I had a few open orders I was dealing with, and then the site just went down,’ says Stanley Louissaint, founder of Fluid Designs. ‘No word on fulfillment, no system access… nothing. The backlog is obvious.’

    Ingram Micro late Saturday confirmed that it had been hit with a ransomware attack and that it is “working diligently to restore the affected systems so that it can process and ship orders.”

    The $48 billion distribution behemoth, which notified law enforcement and has launched an “investigation” with the assistance of leading cybersecurity experts, “apologized” to customers, vendor partners and others for any “disruption” caused by the incident.

    Bleeping Computer reported Saturday that Ingram Micro has been hit with a ransomware attack associated with the Safepay ransomware organization.

    Ingram Micro’s website and online ordering systems have been down since Thursday, according to Bleeping Computer.

    On Sunday morning, users visiting the Irvine, Calif.-based company’s website were met with the message “Ingram Micro is currently experiencing a cybersecurity incident, for more information ‘click here’,” which directs users to their official statement about the incident.

    Among systems impacted are Ingram’s flagship AI-powered Xvantage platform and the Impulse license provisioning platform, according to Bleeping Computer.

    When reached by CRN on Sunday to confirm that Xvantage was down and orders could not be shipped, Ingram referred back to their official statement.

    [Related: CrowdStrike Remains Cybersecurity ‘Gold Standard:’ Analyst]

    However, for partners like Stanley Louissaint, founder and principal of New Jersey-based MSP Fluid Designs, the bigger issue has been the company’s silence.

    “The biggest issue in this situation isn’t even the attack itself,” Louissaint told CRN. “It’s the lack of openness and communication. That’s what completely takes the trust out of a distributor-partner relationship.”

    He said his last communication from Ingram was an advertising email on June 26. Since then, despite having open orders and active business with the distributor, he hasn’t received a single update.

    “I had a few open orders I was dealing with, and then the site just went down,” he said. “No word on fulfillment, no system access… nothing. The backlog is obvious.”

    While his company wasn’t critically affected, thanks to diversified sourcing from other distributors, he expressed concern for businesses that rely solely on Ingram.

    “There are companies completely stuck. They can’t ship, can’t fulfill orders, can’t operate,” he said. “That’s why we never put all our eggs in one basket.”

    He also raised questions about Ingram’s preparedness and response strategy.

    “What was your contingency plan? What’s your disaster recovery process? Was it tested? Clearly, something failed,” he said. “Are you paying the ransom? Are you not? People want transparency.”

    The CEO for an SP500 solution provider, who did not want to be identified, said given that Ingram has confirmed it cannot ship orders at this point his company is actively working on a “plan B” to ensure its customers are not impacted by shipping delays.

    “Our first priority is meeting our shipping commitments to our customers,” said the CEO. “We also have an obligation to our OEMs so we can recognize revenue. We are reaching out now to our larger OEMs and TD Synnex to make sure our customers are taken care of if this is not resolved quickly. We need to make sure we understand shipping status and timing. If this isn’t resolved by Wednesday next week we are going to have to move our business.”

    While many partners express frustration and concern, James Rocker, whose New York-based company is a Trust X Alliance partner with Ingram, is confident the distributor is handling the attack the best they can.

    “At this time, Ingram Micro has not released an official statement out of their respect for the situation and investigative process,” he said via text message. “We believe it’s important to allow their team to gather all the facts before drawing conclusions and making public commentary. Cyber threats are an evolving and persistent challenge across the entire channel, and this event is a reminder that even the most prepared organizations are not immune.”

    Rocker, founder and CEO of Hauppauge, N.Y.-based MSP Nerds That Care, remained optimistic and said he’s confident in Ingram’s “transparency, response efforts and commitment to minimizing disruption for partners and customers.”

    “It’s critical that we as an industry continue to raise the bar on cybersecurity, share intelligence and support one another through incidents like this,” he said. “We trust Ingram Micro is taking the necessary steps to investigate thoroughly and will communicate when appropriate. Until then, we’ll monitor the situation closely and remain focused on ensuring our clients and partners are secure.”

    Steven Burke contributed to this report.

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  • Texas floods: death toll rises to 59 as search continues for dozens missing | Texas floods 2025

    Texas floods: death toll rises to 59 as search continues for dozens missing | Texas floods 2025

    Death toll from Texas flooding rises to 59, lieutenant governor says

    The death toll from the flooding in Texas has risen to 59, according to the county’s Lieutenant Governor Dan Patrick (up from the previous total of 51). More details soon…

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    People in Texas describe the terrifying moments after deadly flooding swept through the central part of the state. The death toll has risen to 59 people.

    One man describes him and his wife being swept by the water and holding onto a tree until rescuers arrived to help. “It was scary, it was really scary,” he said.

    The Guardian’s video team produced this piece on people caught up in the floods.

    People recounted their ordeal after deadly flooding swept through central Texas on Friday morning.
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  • Top 100 Branding Trends in July

    Top 100 Branding Trends in July

    The July 2025 branding list spotlights a series of design-forward and celebrity-boosted campaigns that showcase product functionalities and other sensibilities.

    By tapping into pop culture and celebrity endorsements, brands immediately generate visibility. Jean Paul Gaultier, for example, tapped global music artist Jennie for the debut of its Pre-Fall 2025 collection. JINRO, on the other hand, debuted a soju collection in partnership with Netflix and its globally acclaimed series Squid Game. Glenfiddich and Aston Martin also tap the world-renowned Formula One® event to share their commitment to precision, craftsmanship, and innovation through strategic marketing opportunities.

    The July 2025 branding list also calls attention to diverse business representation by spotlighting Indigenous-designed haircare sets like the Wella Professionals’ exclusive packaging, which features artwork by Alanah Jewell, an Indigenous artist from the Oneida Nation of the Thames.

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  • How PSG and Bayern’s positive tactics resulted in the best game of the Club World Cup

    How PSG and Bayern’s positive tactics resulted in the best game of the Club World Cup

    If the starting line-ups contain names such as Michael Olise, Jamal Musiala and Kingsley Coman on one side, with Bradley Barcola, Desire Doue and Khvicha Kvaratskhelia on the other, there is a high probability of entertainment.

    Yet how both teams approach the game factors in whether we see the individual flair or not.

    Paris Saint-Germain and Bayern Munich didn’t disappoint the audience on Saturday, with their proactive and positive approaches resulting in a thrilling match where Luis Enrique’s side came out victorious.

    PSG and Bayern played to the strengths of their forwards, focusing on isolating their wingers to get the best of their dribbling abilities. However, different methods were used to reach that target.

    Luis Enrique’s team wanted to shift Bayern’s block towards one side of the pitch, by overloading that area, before switching the play quickly to put Barcola or Kvaratskhelia in an isolated situation.

    In this example, Vitinha and Joao Neves are overloading the right side, which drags Joshua Kimmich and Aleksandar Pavlovic towards the touchline, with Bayern’s right-back, Konrad Laimer, moving inside to mark Fabian Ruiz.

    As Vitinha plays the ball to Fabian, Barcola attacks the space inside the pitch…

    … and combines with the Spain midfielder, with Laimer completely out of position.

    On the other side, Kvaratskhelia is free and calling for the pass…

    … which Fabian plays in the space vacated by Laimer.

    Meanwhile, Olise drops to cover for his right-back and intercepts the pass…

    … but Kvaratskhelia wins the ball back. Doue then picks up the loose ball, but his shot misses the target.

    Laimer’s pressing role meant that if PSG could drag him out of position and switch the play in time, Kvaratskhelia would be in a one-versus-one situation against Dayot Upamecano.

    Here, PSG are shifting the ball from the left side to the right to move Bayern’s block, and Laimer is moving towards Fabian as Kimmich and Pavlovic are keeping an eye on Vitinha and Neves.

    With Kimmich and Pavlovic in advanced positions, Achraf Hakimi plays the ball inside the pitch to find Barcola’s run behind the midfield duo.

    Once PSG penetrate Bayern’s block, Laimer’s pressing role becomes a liability because as he is marking Fabian in the centre of the pitch, Kvaratskhelia (out of shot) is in acres of space down the wing.

    After Barcola receives Hakimi’s pass, he dribbles inside…

    … and switches the play to put Kvaratskhelia in a one-versus-one situation.

    The Georgian dribbles past Upamecano with ease…

    … but he is denied by a brilliant save from Manuel Neuer.

    In another example, Vitinha, Neves and Fabian are near the left side of the pitch, and Willian Pacho immediately switches the play towards the right wing.

    Barcola’s immaculate first touch creates an isolated situation against Bayern’s left-back, Josip Stanisic, because it allows him to control the ball before Kimmich and Pavlovic can shift across.

    The right-winger then dribbles inside the pitch and drags Stanisic out of position, which allows PSG to combine and find Hakimi’s third-man run.

    The Morocco full-back then plays a low-curling ball across goal…

    … but Kvaratskhelia only manages to hit the side-netting.

    After the first-half cooling break, Vincent Kompany altered his side’s pressing scheme by leaving the role of marking Fabian to Bayern’s centre-backs, or Olise when PSG were building the attack on the other side.

    By adjusting their pressing, Bayern stifled PSG’s possession game and were able to have more time on the ball for the remaining hour.

    Bayern’s isolation method revolved around putting their full-backs in the half-spaces to create a direct passing lane into their wingers and prevent PSG from doubling up against them.

    In this example, Laimer, who moved to left-back after Sacha Boey replaced Stanisic, plays the ball to Coman and attacks the space between Hakimi and Marquinhos.

    Laimer’s movement occupies Hakimi and creates a one-versus-one scenario for Coman, who dribbles past Neves twice…

    … forcing PSG’s right-back to change his focus and leave Laimer to Marquinhos.

    This sequence of events means that Harry Kane has a bigger space to attack inside the penalty area if Bayern can find him with a cross. This happens when Coman dribbles past Neves again…

    … and puts in a left-footed cross that the England striker heads over the bar.

    In another example, Boey dashes forward in the right half-space to prevent Fabian from doubling up against Olise.

    In the one-v-one, Olise wrong-foots Nuno Mendes and dribbles inside the pitch…

    … but his shot is saved by Gianluigi Donnarumma.

    Despite Bayern’s control in the second half, PSG managed to take the lead through Doue in a transitional moment after Neves won the ball back in midfield.

    Later in the game, Ousmane Dembele scored on another transition to make it 2-0 and seal PSG’s place in the semi-finals of the Club World Cup.

    PSG’s goals reflected another part of the game that made it more exciting. Both teams were willing to press high up the pitch, counter-press when they lost possession and hit on the counter whenever there was an opportunity — all of this suited the match’s most skilful players.

    Tactics doesn’t shackle individual talent, rather they empower it to help it flourish.

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  • Abu Dhabi crown prince holds talks with Brazilian president on sidelines of BRICS summit

    Abu Dhabi crown prince holds talks with Brazilian president on sidelines of BRICS summit


    WASHINGTON/JERUSALEM: US President Donald Trump on Sunday said there was a good chance a Gaza hostage release and ceasefire deal could be reached with the Palestinian militant group Hamas this week.

    Trump told reporters before departing for Washington that such a deal meant “quite a few hostages” could be released.


    Netanyahu said earlier in the day that he hoped his upcoming meeting with Trump could “help advance” a Gaza ceasefire deal, after sending negotiators to Doha for indirect talks with Hamas.


    A Palestinian official familiar with the talks on Sunday said that indirect negotiations between Israel and Hamas toward a ceasefire deal in the Gaza Strip had started in Qatar.


    “Negotiations are about implementation mechanisms and hostage exchange, and positions are being exchanged through mediators,” the official said.


    Under mounting pressure to end the war, now approaching its 22nd month, the Israeli premier is scheduled to sit down on Monday with Trump, who has recently made a renewed push to end the fighting.

    Speaking before boarding Israel’s state jet bound for Washington, Netanyahu said: “We are working to achieve this deal that we have discussed, under the conditions that we have agreed to.”

    He said he had dispatched the team to Doha “with clear instructions,” and thought the meeting with Trump “can definitely help advance this (deal), which we are all hoping for.”


    “We’ve gotten a lot of the hostages out, but pertaining to the remaining hostages, quite a few of them will be coming out,” Trump added.

    He said the United States was “working on a lot of things” with Israel, including “probably a permanent deal with Iran.”


    Netanyahu had previously said Hamas’s response to a draft US-backed ceasefire proposal contained “unacceptable” demands.


    Since the start of Israel’s war against Hamas in Gaza, mediators have brokered pauses in fighting during which hostages were freed in exchange for Israel-held Palestinian prisoners.

    Of the 251 hostages taken by Palestinian militants during the October 2023 attack, 49 are still being held in Gaza, including 27 the Israeli military says are dead.

    Israel’s military campaign, lack of food and dire humanitarian conditions for more than 2 million people in the Gaza Strip has killed at least 57,418 people in Gaza, mostly civilians, according to the Hamas-run territory’s health ministry.

    The United Nations considers the figures reliable.

    Hamas’s October 2023 attack resulted in the deaths of 1,219 people, mostly civilians, according to an AFP tally based on Israeli official figures.


    Earlier Sunday, a Palestinian official told AFP that Hamas would also seek the reopening of Gaza’s Rafah crossing to evacuate the wounded. Hamas’s top negotiator Khalil Al-Hayya was leading the delegation in Doha, the official told AFP.

    Two Palestinian sources close to the discussions told AFP the proposal included a 60-day truce, during which Hamas would release 10 living hostages and several bodies in exchange for Palestinians detained by Israel.

    However, they said, the group was also demanding certain conditions for Israel’s withdrawal, guarantees against a resumption of fighting during negotiations, and the return of the UN-led aid distribution system.

    Israel’s retaliatory campaign has killed at least 57,418 people in Gaza, also mostly civilians, according to the Hamas-run territory’s health ministry. The United Nations considers the figures reliable.


    (With AFP & Reuters)

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  • The Garmin Forerunner 255 Just Dropped to Its Lowest Price Ever

    The Garmin Forerunner 255 Just Dropped to Its Lowest Price Ever

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    Deal pricing and availability subject to change after time of publication.

    If you’re ready to upgrade from tracking your steps to something more performance-driven, investing in a running watch might be your best move. The Garmin Forerunner 255 running watch is designed to help runners optimize training and improve performance, and right now, it’s 43% off on Amazon, the lowest price it’s ever reached according to price trackers. With GPS tracking, comprehensive stats, free training plans, and training evaluations to monitor performance and provide feedback, it’s like a built-in running coach for your wrist.

    This discounted model has a larger 46mm screen (compared to the 41mm version) and is the non-music edition, meaning it doesn’t store or play music, so you’ll still need your phone for playlists. It lasts up to 14 days in smartwatch mode and 30 hours in GPS mode, with accurate tracking via multiple satellite systems. At just 1.7 ounces, it’s lightweight despite its size, and features a sweat-resistant silicone band and Corning Gorilla Glass 3. The button-based interface (rather than a touchscreen) may also appeal to runners who want reliable control during a sweaty workout.

    The built-in Garmin Coach feature offers free adaptive training plans for 5K, 10K, and half-marathon distances. You can also create custom workouts via the Garmin Connect app. The watch provides training tips and personalized workout suggestions that adapt based on your post-run performance and recovery, tracking heart rate and using SatIQ technology to balance GPS accuracy with battery life. It even evaluates your current routine to help you avoid under-training or overexertion.

    When worn overnight, HRV status can track your heart rate during sleep and provide additional insight into your overall wellness. However, given the slightly bulky nature of the watch, it may not be comfortable for some people to sleep with. While it’s a favorite among runners, many Amazon reviewers also highlight its accuracy for open water and pool swims, making it a versatile watch for different kinds of fitness lovers.


    What do you think so far?

    While it’s ideal for runs and everyday use, its stainless steel casing isn’t as rugged as Garmin’s Fenix or Instinct series, and if you want built-in music, you may want to splurge on the brand’s upgraded model instead. If you don’t need those premium features, the Garmin Forerunner 255 running watch offers solid value with GPS accuracy, in-depth training insights, and a long battery life for runners who want to train smart without overspending. 


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  • The latest Samsung Galaxy Z Flip 7 leak is the first hands-on video of the flip foldable

    The latest Samsung Galaxy Z Flip 7 leak is the first hands-on video of the flip foldable

    • A hands-on video of the Galaxy Z Flip 7 briefly appeared
    • It showed off the larger cover screen on this model
    • The Z Flip 7 and Z Fold 7 should be launched on Wednesday

    We’ve seen plenty of leaks around the Samsung Galaxy Z Fold 7 and the Samsung Galaxy Z Flip 7 ahead of the official launch of these foldables – scheduled for this coming Wednesday, July 9 – and this weekend a hands-on video of the Z Flip 7 has emerged.

    It wasn’t long before the video, posted by Mincu Andrei on X, was taken down, but a few stills of the clip have been preserved for posterity over at SamMobile. If this is genuine, it’s the first time we’ve had a peek at a fully working Galaxy Z Flip 7.

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