Transcriptional signatures of synaptic vesicle genes define myotonic dystrophy type I neurodegeneration

Abstract

Aim: To delineate the neurogenetic profiles of brain degeneration patterns in myotonic dystrophy type I (DM1).

Methods: In two cohorts of DM1 patients, brain maps of volume loss (VL) and neuropsychological deficits (NDs) were intersected to large-scale transcriptome maps provided by the Allen Human Brain Atlas (AHBA). For validation, neuropathological and RNA analyses were performed in a small series of DM1 brain samples.

Results: Twofold: (1) From a list of preselected hypothesis-driven genes, confirmatory analyses found that three genes play a major role in brain degeneration: dystrophin (DMD), alpha-synuclein (SNCA) and the microtubule-associated protein tau (MAPT). Neuropathological analyses confirmed a highly heterogeneous Tau-pathology in DM1, different to the one in Alzheimer's disease. (2) Exploratory analyses revealed gene clusters enriched for key biological processes in the central nervous system, such as synaptic vesicle recycling, localization, endocytosis and exocytosis, and the serotonin and dopamine neurotransmitter pathways. RNA analyses confirmed synaptic vesicle dysfunction.

Conclusions: The combination of large-scale transcriptome interactions with brain imaging and cognitive function sheds light on the neurobiological mechanisms of brain degeneration in DM1 that might help define future therapeutic strategies and research into this condition.

Keywords: Allen Human Brain Atlas; DM1; neuropsychological deficits; structural neuroimaging; synaptic vesicles; volume loss.

FIGURE 1

Methodological scheme for the association between transcriptomics and atrophy in DM1, measured as brain volume loss (VL). (A) Two cohorts of DM1 patients were recruited (orange and blue) and we obtained the brain maps of the VL for each, comparing the images with a group of HCs using voxel‐based morphometry (VBM) and tract‐based spatial statistics (TBSS), correcting for multiple comparisons. We aimed to characterize the association between VL and transcriptomics, assessing the similarity in the spatial patterns of VL across brain regions and the spatial patterns of gene transcription from the AHBA dataset, pre‐processed following a pipeline that is summarized in six main steps (for further details, see Methods). After running the AHBA pipeline, about 14 K genes finally had transcription values used in the analysis from the 58‐K probes originally available. The red regions in the brain correspond to the sites at which transcription was sampled. *Of the total 3,702 sampling sites, 2,728 were located in cortical and subcortical grey matter, 368 in the cerebellum, 586 in the brain stem, and 15 in white matter. Our analyses here are restricted to the 2,728 sites covering the cortical and subcortical grey matter. (B) The sampling proportion (SP) and differential stability (DS) for the 27 preselected hypothesis‐driven genes included in the list of candidates relevant to DM1 (obtained by reviewing the literature). The CACNA1S, CLCN1, KL and SIX5 genes did not have a mean SP value above 70% and thus, they were excluded from further analyses. Of the remaining 23 genes, the maximum DS corresponded to SNCA and the minimum DS to DMPK (see arrows). By examining the spatial similarity in the transcription values, the remaining 23 candidate genes were clustered into three groups. The blue one formed by DMD, SNCA and MAPT played a major role in the characterization of VL

FIGURE 2

Data‐driven strategy to determine the association between the transcriptome and VL in DM1. (A) Histogram of the spatial‐correlation values (measured as the Z‐score) between volume loss (VL) and transcriptional activity for all the genes in both cohorts. For both cohorts the N genes (z < −2) and P genes (z > 2) are coloured in blue and red, respectively. The final list of genes used for further analyses are those that are common to the two cohorts, consisting of 251 N genes and 101 P genes. From all the genes that provide a maximum association between VL and transcriptomics (Tables S6 and S7), only two genes were in the panel of preselected genes: SNCA and DMD. (B) Brain maps of transcription in the brain regions for the two genes DMD and SNCA, which provided a high spatial correlation (r) with the VL brain maps for both cohorts

FIGURE 3

Functional description of the genes with the highest association with volume loss (VL). (A) An all‐to‐all gene‐expression similarity matrix identified the connector hub genes. A total of 1,086 genes were found, equal to the sum of the NC =452 (blue), PC =396 (red) and 238 common NC and PC genes (grey). (B) Two clusters were finally found that pooled all gene classes, the blue one contains the original N = 251 genes and the red one containing the original p = 101 genes. (C) Gene enrichment for GO biological process and Reactome pathways: in blue are the neg‐corr genes and in red, the pos‐corr genes. Abbreviations: Act., activation; CNS, central nervous system; Mod., modulation; Neg., negative; Pos., positive; Rec., receptor/s; Reg., regulation

FIGURE 4

Data‐driven strategy to define the association between the transcriptome and attention co‐activation maps in DM1. (A) Attention scores measured as Z‐scores for the two cohorts. Because the Z‐scores were normalized to the values in the HCs, negative values of z indicate worse performance than the HCs. (B) Attention co‐activation maps built with the GingerALE tool and projected onto the atlas. (C) Histograms of the spatial correlations between the Z scores of the attention maps and the transcriptional activity for each gene. The tail of N genes (z < −2, coloured in blue) includes the SNCA gene from the list of preselected genes, whereas the tail of the P genes (z > 2, red) does not include any of these. Following a procedure similar to that described in Figure 3A, we identified the PC genes (red), NC genes (blue, including MAPT), and those common to the NC and PC (grey, including PHKA1). (D) After pooling all classes of genes together and clustering, two groups were defined: one including all the neg‐corr genes (blue, with SNCA and MAPT) and one with the pos‐corr genes (red, with PHKA1). Gene enrichment for the tags GO biological process and Reactome pathways. As in Figure 3C, the two clusters also represented two separated functions: the neg‐corr one correlated with neuronal functions, while the pos‐corr correlated to non‐brain functions. Abbreviations: Mod., Modulation; Neg., Negativek; Pos., Positive; Reg., Regulation

FIGURE 5

Neuropathological analyses of brain samples revealed a high heterogeneous Tau‐pathology in DM1, different to the one in AD. Upper panel: Gel electrophoresis and Western blotting of sarkosyl‐insoluble fractions of the hippocampus incubated with antibodies against 3Rtau, 4Rtau, and phosphorylated tau at serine 214 (P‐tau‐Ser214) in DM1 cases, and one AD for control. AD is characterized by three bands of 68, 64 and 60 kDa and an upper weak band of 73 kDa. DM1 cases are characterized by the presence of lower bands of 58 and 55 kDa, and occasional upper bands of 60 and 64 kDa; the band of 68/69 kDa is barely present. This particular pattern, including differences from one case to another, is associated with low molecular weight 3Rtau and 4Rtau isoforms suggesting complex altered Tau splicing. Lower panel: Representative images of NFTs and neuropil threads in the entorhinal cortex (EC), CA1 area of the hippocampus (CA1), temporal cortex (TC), and parietal cortex (PC), visualized with the antibody AT8, and anti‐3Rtau and 4Rtau antibodies. Paraffin sections slightly counterstained with haematoxylin; bar =25 μm

FIGURE 6

RNA expression in hippocampal tissues from DM1 patients revealed protein dysfunction of synaptic vesicle processes in DM1. mRNA expression of synapse‐related genes was analysed in the hippocampus in middle‐aged (MA) control cases, myotonic dystrophy 1 (DM1) cases, and cases with neurofibrillary tangles (NFT control) linked to AD‐related pathology at middle and advanced stages (III‐VI) of Braak and Braak. (A) Synaptic vesicles coding genes. (B) Synapse structural components coding genes. (C) GABAergic‐ and glutamatergic‐related coding genes. All data were expressed as mean values ± SEM. Differences between groups are statistically significant at *p < 0.05; trends are indicated with * and the exact p value