Morphometric Inverse Divergence Networks Combined with HYDRA Identify Parkinson’s Disease Subtypes with Distinct Transcriptomic and Serum Biomarker Profiles

Normative modelling of cortical networks identifies subtypes of type 2 diabetes associated with distinct clinical and transcriptomic profiles

Type 2 diabetes (T2D) is characterized by substantial clinical heterogeneity, yet its neurobiological substrates remain unclear. Here, we leverage normative modelling of cortical morphometric networks to quantify individual-level brain deviations using structural MRI data from 3,723 participants (1,941 T2D patients and 1,782 healthy controls) across three independent cohorts. Data-driven clustering reveals two robust T2D biotypes characterized by widespread positive (biotype 1) and negative (biotype 2) brain deviations. Despite comparable overall metabolic burdens, these biotypes feature distinct brain–metabolic coupling patterns: biotype 1 is primarily associated with lipid metabolism, whereas biotype 2 reflects a multifactorial metabolic burden spanning glycaemic control, adiposity, lipid, vascular risks, and disease duration. These divergent brain vulnerability profiles have distinct cognitive consequences; notably, biotype 2 shows poorer performance in complex cognitive tasks, aligning with negatively deviated connectivity gradients along the sensorimotor-to-association axis. Spatial transcriptomic analyses further link biotype 2 deviations to gene expression patterns enriched in insulin signalling, mitochondrial functions, tight junctions, and neurodegenerative disease pathways, alongside specific involvement of inhibitory neurons and oligodendrocyte lineage cells. Our findings provide a neurobiological understanding of T2D heterogeneity and establish a data-driven framework for characterizing personalized brain vulnerability, with implications for advancing precision diabetes medicine.

Transcriptional signatures of cortical morphometric variability in temporal lobe epilepsy

It is shown that TLE patients have structural changes in two brain regions, the posterior cingulate cortex and dorsolateral prefrontal cortex, linked to slower processing speed and poorer working memory, which helps explain how microscopic gene patterns may contribute to large‐scale brain changes and cognitive difficulties in TLE.

Pseudotime analysis of 2,106 brains across nine regions reveals conserved immune, neuronal, and myelin regulatory programs in Alzheimer’s disease

Pseudotime trajectories can reconstruct latent disease progression from cross-sectional transcriptomic data. However, whether Alzheimer’s disease (AD) progression follows a conserved molecular architecture across brain regions remains unclear. We applied pseudotime analysis to harmonized bulk RNA-seq data from 2,106 postmortem brain samples (1,364 AD, 742 controls) across nine brain regions from three AMP-AD cohorts (ROSMAP, Mayo, MSBB). Pseudotime was significantly associated with AD diagnosis in all nine regions and with Braak stage in seven of nine. We identified 21 genes with concordant pseudotime associations across all regions, increasing to 234 when the cerebellum was excluded. Pathway analysis revealed 1,268 significant associations, with synaptic deregulation as the most conserved process, and immune/ECM programs showing greater regional specificity. The cerebellum followed a distinct pattern, with enrichment for protein refolding and chaperone pathways rather than neurodegeneration. Co-expression network analysis identified six conserved metamodules, including immune/glial (MM1) and excitatory neuronal (MM2) programs spanning all nine regions, and an oligodendrocyte/myelin program (MM3) in seven cortical regions. Key driver analysis identified 76 unique genes across 35 modules, with HCK and LAPTM5 as the most broadly replicated immune regulators in seven regions. Oligodendrocyte-associated key drivers (MYRF, CNP, MOBP) increased along pseudotime in cortical regions, supporting active myelin remodeling during AD progression. These findings reveal a conserved transcriptional architecture underlying AD progression, organized around coordinated immune activation, synaptic loss, and myelin remodeling, with the cerebellum following a distinct trajectory.

Single-cell transcriptomic atlas of Alzheimer's disease middle temporal gyrus reveals region, cell type, and sex specificity of gene expression with novel genetic risk for MERTK in female.

BackgroundAlzheimer's disease (AD), the most common age-related neurodegenerative disease, is closely associated with both amyloid-β plaque and neuroinflammation. Two thirds of AD patients are female, and they have a higher disease risk; women with AD have more extensive brain histological changes than men along with more severe cognitive symptoms and neurodegeneration.ObjectiveThis study aimed to determine how sex difference induces structural brain changes and molecular cell vulnerabilities in AD, with a focus on identifying sex-specific transcriptional alterations and genetic risk factors.MethodsWe performed single nucleus RNA sequencing on postmortem brains from individuals with AD and age- and sex-matched controls, focusing on the middle temporal gyrus, a cortical brain region strongly affected by the disease, and integrated single nucleus RNA sequencing results with genome-wide association study (GWAS) data using cell type-specific enrichment and generalized gene-set analysis approaches. The analysis pipeline is provided with threshold information.ResultsWe identified a selectively vulnerable subpopulation of layer 2/3 excitatory neurons that were RORB-negative and CDH9-expressing in both males and females. Disease-associated, but sex-independent, reactive astrocyte signatures were also present. In clear contrast, the microglia signatures of AD brains differed between males and females. Integrating single cell transcriptomic data with results from GWAS, we identified MERTK genetic variation as a candidate novel risk factor for AD selectively in females.ConclusionsTaken together, our single cell atlas of middle temporal gyrus revealed a unique cellular-level view of sex-specific transcriptional changes in AD, illuminating GWAS identification of sex-specific AD genes. These data serve as a rich resource for interrogation of the molecular and cellular basis of AD.

Parietal Cortex Transcriptomics Refines Parkinson Disease GWAS Nomination and Highlights STAT3 as a Putative Upstream Glial Regulator

Peripheral blood transcriptomic signature is associated with cognitive impairment and freezing of gait in Parkinson’s disease: a data-driven approach

Parkinson’s disease (PD) is a heterogeneous neurodegenerative disorder with variable long-term outcomes. Blood-based biomarkers for prognostic prediction remain underdeveloped. We aimed to develop a peripheral blood transcriptomic signature for predicting long-term complications in PD using unsupervised data-driven methods. Using RNA sequencing data from 541 PD patients and 180 healthy controls from the Parkinson’s Progression Markers Initiative (PPMI), we employed weighted gene correlation network analysis (WGCNA) to identify disease-associated gene modules. Contrastive principal component analysis was applied to derive a pseudo-temporal (PT) trajectory score reflecting molecular disease progression. The prognostic value of PT scores was assessed through Cox regression for cognitive impairment, freezing of gait (FOG), wearing-off, and levodopa-induced dyskinesia. WGCNA identified two PD-associated co-expression modules enriched for immune/inflammatory pathways. PT scores derived from these modules showed significant correlations with cognitive, autonomic, and axial motor symptoms. In multivariable Cox regression, higher PT scores independently predicted cognitive impairment (HR = 7.31, P = 0.002) and FOG (HR = 3.43, P < 0.001), but not predominantly dopaminergic motor complications. These findings demonstrate that peripheral blood transcriptomic signatures capture aspects of PD pathophysiology that are not fully explained by nigrostriatal dopaminergic degeneration alone, serving as potential prognostic biomarkers for cognitive impairment and FOG.