Acta Neuropathologica Communications

T-cell lymphomas are often histologically indistinguishable from benign T-cell infiltrates. Clonality testing is frequently required for diagnosis. It lacks the spatial context and is slow and expensive, relying on complex, multiplexed PCR reactions, interpreted by experienced scientists or pathologists. We previously published details of a pair of highly specific monoclonal antibodies against the two alternatively used, but very similar, T-cell receptor {beta} constant regions, TCR{beta}1 and TCR{beta}2. We demonstrated the feasibility of immunohistochemical detection of TCR{beta}1 and TCR{beta}2 in formalin-fixed, paraffin-embedded (FFPE) tissue as a novel diagnostic strategy for T-cell lymphomas. Here we validate an improved pairing of TCR{beta}1/2 rabbit monoclonal antibodies, and demonstrate their utility for single and double immunostaining, including with a chimeric mouse anti-TCR{beta}2 antibody. Finally, we show that this staining is amenable to automated cell counting, permitting accurate calculation of the TCR{beta}2:TCR{beta}1 ratio.

While 18F-Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) is an established biomarker in amyotrophic lateral sclerosis (ALS), the metabolic correlates of motor neuron disease motor variants remain poorly defined. This is why we investigated patterns of cerebral glucose metabolism across the spectrum of motor neuron disorders (MND), including progressive muscular atrophy (PMA), primary lateral sclerosis (PLS) and amyotrophic lateral sclerosis (ALS). We retrospectively included 18 PMA, 25 PLS and 43 matched non-hereditary ALS patients according to most recent diagnostic criteria. FDG-PET imaging revealed similar widespread hypometabolism in PMA, as in ALS, whereas PLS showed a more focal motor cortical pattern of hypometabolism. Despite clinical differences between MND subtypes, PMA and ALS showed similar FDG-PET metabolic patterns, whereas PLS exhibited a more restricted cortical signature in this retrospective study.

Meningiomas are the most common primary brain tumors and, despite their benign reputation, often behave aggressively. Meningiomas are morphologically heterogeneous, yet the full significance of their histologic diversity is unclear. This is in large part because many features are not readily quantifiable by traditional observer-based light microscopy. Molecular testing improves prognostic stratification, but is not universally accessible. We therefore sought to determine whether an artificial intelligence (AI)-trained program could predict specific genomic and epigenomic patterns in meningiomas, and whether it could extract more prognostic information out of standard hematoxylin and eosin (H&E) histopathology than the current WHO classification. To do this, we developed Morphologic Set Enrichment (MSE), an interpretable computational pathology framework that quantifies statistical enrichment of morphologic patterns, cells, and tissue architecture from H&E whole-slide images. The MSE meningioma histology program was able to accurately predict DNA methylation subtypes and concurrent chromosome 1p/22q losses, in the process identifying specific morphologic patterns associated with key genomic and epigenomic alterations. It also added prognostic value independent of standard clinical and pathological variables. These results demonstrate that AI-based quantitative morphologic profiling can capture clinically and biologically relevant information that redefines risk stratification for meningiomas, incorporating histological information not included in existing grading schemes.

Protocadherin-12 (PCDH12), a cell-adhesion protein belonging to the non-clustered protocadherin family, plays a crucial role in the establishment and regulation of neuronal connections and communication. Bi-allelic loss-of-function (LoF) variants in the PCDH12 gene have been associated with several neurodevelopmental disorders (NDDs) such as diencephalic-mesencephalic junction dysplasia (DMJD) syndrome, cerebral palsy, and cerebellar ataxia, often accompanied by ocular abnormalities. However, genotypes exhibit variable expressivity. Affected individuals sharing the same PCDH12 variant presenting differing phenotypic severities have posed major challenges towards identification of the underlying pathogenic mechanisms. Here, we report three affected individuals from two families, each harbouring non-truncating pathogenic missense variants in PCDH12. The patients are compound heterozygous, with each individual carrying one extracellular [c.1742T>G (p.Val581Gly) and c.1861_2del/insCA (p.Ile621His)] and one intracellular variant [c.3370C>T (p.Arg1124Cys) and c.3445G>A (p.Asp1149Asn] on each allele. The children present with a range of phenotypes similar to those associated with LoF variants. One child exhibited microcephaly and seizures, while the two siblings displayed developmental delays and severe behavioral disorders. All three children experienced some degree of visual impairment. The missense variants provided new insights into the neurodevelopmental consequences of compromised PCDH12 function by distinguishing the specific consequences associated with dysfunction in the extracellular versus intracellular domains of PCDH12. All identified missense variants are predicted to be deleterious and destabilizing. The expression of PCDH12 in HEK293T and HeLa cells demonstrated that PCDH12 is expressed effectively, regardless of the presence of missense variants. However, the extracellular variants p.Val581Gly and p.Ile621His compromised the stability of PCDH12's homophilic adhesion. Additionally, we found evidence of an interaction between PCDH12 and the extracellular domain of the epilepsy-associated PCDH19 protein. PCDH12 extracellular missense variants also negatively impact this interaction. Our study provides evidence that PCDH12 mediates both homophilic and heterophilic interactions. Our findings also highlight the importance of stable PCDH12-mediated adhesion, emphasizing the need to further study the functional consequences of PCDH12 missense variants on brain and visual system development.

Background Whole-genome sequencing (WGS) has improved the diagnosis of rare genetic disorders, yet interpretation of non-coding variants that affect splicing remains challenging. In silico predictions alone are insufficient, and short-read RNA sequencing may fail to capture complex or low-abundance splicing events. Targeted amplicon-based long-read RNA sequencing (Amp-LRS) offers a cost-effective approach for functional validation of candidate splice-altering variants. Methods We applied Amp-LRS to five patients with neurological disorders (central nervous system, peripheral nervous system, or muscle) harbouring candidate non-coding variants predicted to alter splicing. RNA was extracted from fibroblasts or peripheral blood, and full-length transcript amplicons were sequenced using Oxford Nanopore Technologies. Nonsense-mediated decay (NMD) inhibition was performed on fibroblast cultures using cycloheximide. Results Amp-LRS validated all five candidate variants, including intronic and UTR variants in POLR3A, OPA1, PYROXD1, GDAP1, and SPG11. Aberrant splicing events included exon skipping, intron retention, cryptic splice site activation, and pseudoexon inclusion, often resulting in frameshifts and premature termination codons. For POLR3A and OPA1, multiple abnormal isoforms arose from single variants, highlighting the complexity of splicing disruption. Some pathogenic effects were detectable only in a minority of reads and variably enriched by NMD inhibition, consistent with being hypomorphic. The approach was successfully applied using accessible tissues and enabled multiplexed sequencing at low per-sample cost. Conclusions Amp-LRS is a sensitive, versatile, and cost-effective method for functional assessment of non-coding splice-altering variants identified by WGS. By enabling full-length transcript analysis from accessible tissues, this approach improves interpretation of variants of uncertain significance and could enhance molecular diagnosis in rare neurological diseases.

Spinal muscular atrophy (SMA) is a severe neuromuscular disorder caused by reduced expression of the survival motor neuron (SMN) protein. In addition to affecting motor neuron survival, SMN deficiency impacts multisystem physiology and neurotransmission. Dopaminergic dysfunction has been reported in mouse models of SMA, leading to postural and locomotor impairments that improve upon treatment with L-DOPA and benserazide. However, whether altered dopamine metabolism contributes to clinical symptoms in SMA patients remains unclear. To investigate this issue, we conducted a real-world observational study involving pediatric patients with SMA1, SMA2, and SMA3. We performed a longitudinal measurement of the main dopamine-related catabolites - 3,4-dihydroxyphenylacetic acid (DOPAC) and homovanillic acid (HVA) - in cerebrospinal fluid (CSF) samples collected at baseline and after five intrathecal doses of Nusinersen, an SMN-enhancing therapy. No significant differences were observed in CSF DOPAC and HVA levels across SMA types or following treatment, and no association emerged with SMN2 copy number. In contrast, lower baseline DOPAC levels were detected in SMA1 patients requiring gastrostomy and tracheostomy, and were associated with reduced improvement on the CHOP-INTEND scale. These findings suggest that reduced central dopaminergic turnover reflects disease progression in SMA1 and is associated with more severe clinical impairment and limited functional recovery.

BackgroundPATZ1 fusion-positive central nervous system (CNS) tumors frequently harbor MN1::PATZ1 fusions as driver mutations, provisionally classified as a rare DNA methylation class of low-grade neuroepithelial tumors. Radiographically, they resemble pilocytic astrocytomas with tumor and cystic components, but their supratentorial cortex location and higher recurrence rates are distinguishing features. An intermediate clinical course, despite focal high-grade histopathology, underscores the need for longitudinal molecular and immune analyses to refine classification and standard therapy. Case SummaryA female pediatric patient presented with neurological symptoms, including headache and right upper extremity weakness. MRI revealed a large cystic lesion in the left frontal lobe, leading to a differential diagnosis of low-grade glioma and ependymoma. Genomic analysis identified an MN1::PATZ1 fusion. The tumor recurred after gross total resection prompting a second resection. Transcriptomic and histopathologic assessments identified multiglial lineage, and high-grade features closely related to adult glioblastoma alongside pro-inflammatory activity in the primary tumor. The recurrent tumor showed reduced malignancy, and oligodendroglioma-like features. Increased MHC gene expression, immune checkpoint receptors (PDCD1, CTLA4, TIGIT,TIM3), T cell regulators (CXCR6), and elevated macrophage frequency, coupled with reduced PD-L1 in the recurrent tumor, suggest a complex anti-tumor immune response constrained by T cell dysregulation. This case, along with two other MN1::PATZ1 fusion-positive tumors, identifies a distinct transcriptomic subtype separate from circumscribed astrocytic glioma, highlighting upregulation of growth factor receptor pathways, like PI3K/AKT, and immune dysfunction linked to recurrence. ConclusionLongitudinal multi-omics analyses of recurrent MN1::PATZ1 fusion-positive CNS tumors revealed tumor maturation, immune dysfunction, and potential therapeutic targets. Introductory ParagraphPATZ1 fusion-positive central nervous system (CNS) tumors are rare, predominantly pediatric and frequently recurrent neoplasms provisionally classified as neuroepithelial tumors. Their pronounced histopathological and clinical heterogeneity, along with limited immunological characterization complicates their treatment standardization. We report a new case of an MN1::PATZ1 fusion-positive CNS tumor with recurrence, highlighting its radiographic similarities to low-to-intermediate grade pediatric glioma. Longitudinal multi-omics analyses of this case, along with additional MN1::PATZ1 fusion-positive CNS tumors, however, delineates a transcriptome subtype resembling adult high-grade glioma, with activated oncogenic and pro-inflammatory programs. The recurrent tumor exhibits features of decreased malignancy and enhanced glial differentiation, phenotypically shifting towards oligodendroglioma, suggesting tumor maturation. This was accompanied by increased antigen presentation programs, indicating immune engagement, while increased immune checkpoint expression and microglia/macrophage frequency indicate T cell exhaustion and immunomodulation, respectively. This longitudinal study highlights potential therapeutic strategies targeting both the tumor and its immune environment in MN1::PATZ1 fusion-positive CNS tumors.

Alzheimers disease and related dementias (ADRD)1 and Parkinsons disease and related disorders (PDRD)2 have substantial genetic contributions, yet the role of rare damaging coding variants remains incompletely characterized at population scale3-6. We performed gene-based burden testing of rare loss-of-function and deleterious missense variants using whole-genome sequencing data from large population biobanks combined with disease-specific sequencing cohorts, leveraging proxy phenotypes to maximize statistical power for late-onset neurodegenerative diseases7. We confirmed rare variant burden in established ADRD genes (ABCA7, PSEN1, ADAM10, ATP8B4, GRN, SORL1, TREM2, SHARPIN) and PDRD genes (GBA1, LRRK2). We additionally identified novel associations in ADRD (IMPA2, PMM2, SYNE1, CHRNA4, FCGR1A) and PDRD (ANKRD27, CCL7, USP19, SKP1, KANSL3). The strongest signal was observed for ANKRD27, where damaging variants clustered within domains mediating interactions with Rab GTPases and retromer components. Our results demonstrate the power of population-scale sequencing combined with proxy phenotypes to identify rare coding risk genes for neurodegenerative diseases.

ObjectiveBrain branks preserve extensive material relevant to neurodegenerative disease research. As these collections age, tissue becomes archival, raising the question of whether long-term fixed and stored human brain tissue remains suitable for contemporary immunohistochemical analyses. Materials and MethodsForty-one autopsy brains collected between 1946 to 1980 were examined. For each case, midbrain and hippocampus were available both as original paraffin-embedded blocks and as tissue stored long term in fixative. New paraffin blocks were prepared from the long-term fixated tissue. Sections from original and newly prepared blocks were immunohistochemically stained for -synuclein, hyperphosphorylated tau and amyloid-{beta}. Immunoreactivity was assessed using semi-quantitative scoring. ResultsOriginal blocks consistently showed good staining intensity and morphological preservation for each protein pathology. Newly prepared blocks showed slightly lower semi-quantitative scores for Lewy-related pathology, without statistically significant differences, except for astrocytic -synuclein in the substantia nigra in cases from the 1960s. Tau pathology displayed modestly reduced labelling, particularly of the neuropil threads and neurofibrillary tangles, most evident in cases from the 1950s. Amyloid-{beta}-positive senile plaques showed similar or slightly higher scores in newly prepared blocks, with no significant differences across regions. ConclusionHuman brain tissue preserved as paraffin-embedded blocks or stored in fixative for up to 78 years remains suitable for immunohistochemical analyses. Adequate-to-good detection of aggregated of -synuclein, hyperphosphorylated tau and amyloid-{beta} is achievable, indicating preserved pathological hallmarks of Lewy Body Disease and Alzheimers Disease in archival tissue.

Lysosomal dysfunction is central to Parkinsons disease pathogenesis, with GBA1 as the strongest established genetic risk factor. Numerous other genes involved in lysosomal sphingolipid, glycosphingolipid and ceramide metabolism have been proposed as contributors to Parkinsons disease, underscoring the need for comprehensive genetic analyses across these pathways. We analysed rare variants (minor allele frequency < 0.01) across 36 lysosomal genes (excluding GBA1) in 8,267 individuals with Parkinsons disease and 68,208 controls, including a subset of 793 early-onset Parkinsons disease ([&le;]50 years) cases. Targeted sequencing was performed in four cohorts at McGill University (3,456 Parkinsons disease patients and 2,664 controls) and results were combined with whole-genome sequencing data from the UK Biobank (2,848 cases, 62,451 controls), and from the Accelerating Medicines Partnership - Parkinsons Disease (1,963 cases, 3,093 controls). We analysed the association of rare variants in these genes with Parkinsons disease using Sequence Kernel Association Test-Optimal (SKAT-O) across variant classes (all rare variants, nonsynonymous, loss-of-function and predicted damaging variants with a Combined Annotation Dependent Depletion (CADD) score >20), with meta-analysis across cohorts. We additionally performed per-domain analyses for variants in gene segments encoding functional domains. False discovery rate correction was applied. Meta-analysis identified a significant association between rare variants in ST3GAL3 and Parkinsons disease (Pfdr=0.04). Several additional lysosomal genes showed nominal associations (P<0.05), including HGSNAT, ASAH1, CTSD, HEXA, ST3GAL4 and SGPP1. Domain-based analyses identified a strong enrichment of nonsynonymous variants within the beta-acetyl-hexosaminidase-like domain of HEXA (P = 8.0 x 10), although this signal did not survive correction for multiple testing (Pfdr=0.154). In early-onset Parkinsons disease, domain-based analyses revealed significant associations in NAGLU (Pfdr=7.3x10) and ST3GAL5 (Pfdr=0.03). Together, these results provide genetic evidence that rare variants across multiple lysosomal pathways, particularly those related to sialylation, ganglioside metabolism, ceramide biology, and lysosomal proteolysis, may contribute to Parkinsons disease susceptibility beyond GBA1, highlighting biologically coherent pathways for future replication and functional investigation.

Blood-based biomarkers have emerged as a promising tool for the detection and monitoring of neurodegenerative diseases such as Alzheimers disease (AD), yet broad implementation of ultrasensitive protein quantification remains constrained by reliance on specialized instrumentation and centralized laboratory infrastructure. Here we present SPLASH (Solid Phase Ligation Assay with Single wasH), an ultrasensitive proximity ligation assay platform that achieves sub-pg/mL sensitivity using only standard benchtop qPCR equipment. We developed five assays targeting Alzheimers disease biomarkers - pTau-217, A{beta}1-40, A{beta}1-42, neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP) - with limits of detection ranging from 0.0005 to 0.119 pg/mL. Direct comparison with Simoa demonstrated high concordance (R2 = 0.95) for plasma pTau-217 quantification across AD-positive and AD-negative samples. We further established compatibility with dried plasma spot samples, enabling decentralized collection and quantitation without cold-chain storage. A multiplexed five-analyte panel was applied to 69 plasma samples, revealing heterogeneous biomarker profiles consistent with AD-associated patterns. By eliminating dependencies on proprietary instrumentation, SPLASH facilitates broad implementation of ultrasensitive protein quantification for neurodegenerative disease research and diagnostics.

BackgroundImmune checkpoint inhibition has transformed cancer therapy; however, many patients fail to respond to single-agent blockade, and combination strategies are often limited by toxicity. Central nervous system tumors exploit multiple immunosuppressive pathways, including the CD200 and PD-1/PD-L1 axis to evade anti-tumor immunity and support tumor aggressiveness. MethodsWe investigated ARL200, a peptide ligand targeting the CD200 activation receptor (CD200AR) using in vitro immune assays, murine syngeneic tumor models, phosphoproteomics, and correlative studies from a first-in-human trial in recurrent glioblastoma. ResultsARL200 exposure activated DAP10/12-dependent signaling and downregulated multiple inhibitory immune checkpoint receptors, including CD200R1, PD-1, and CTLA-4, and checkpoint ligands, CD200 protein and PD-L1, through suppression of the JAK1/3-SHP-STAT-IKK/{beta}-NF{kappa}B pathway. Distinct ARL200 variant peptides elicited unique immune responses. In patients with recurrent glioblastoma, ARL200 treatment was associated with immune activation, reduced inhibitory checkpoint expression, and evidence of antigen-specific memory responses without treatment-related toxicity. ConclusionsTargeting CD200AR enables coordinated modulation of multiple immune checkpoints with a single agent, representing a next-generation immunotherapeutic strategy opening a new pathway for treating aggressive malignancies. Key PointsO_LIARL200 elicits an active immune response for the development of a potent and durable anti-tumor response C_LIO_LIARL200 abolishes the suppressive effects of multiple immune checkpoint blockades C_LIO_LIDifferent ARL200 sequences drive alternative immune responses. C_LI Importance of the StudyTumors exploit multiple immune checkpoint pathways to suppress antitumor immunity, particularly within the immunosuppressive microenvironment of the central nervous system. Current immune checkpoint inhibitors often require combination therapy to achieve clinical efficacy, frequently at the cost of increased toxicity. In this study, we demonstrate that targeting the CD200 activation receptor (CD200AR) with a peptide ligand provides a novel strategy to simultaneously downregulate multiple inhibitory immune checkpoints, including CD200R1, PD-1, PD-L1, and CTLA-4, through a shared intracellular signaling pathway. ARL200 engagement activates DAP10/12-dependent signaling while suppressing the JAK1/3-SHP-STAT-IKK/{beta}-NF{kappa}B axis, thereby overriding tumor-mediated immunosuppression. Importantly, this multi-checkpoint modulation is achieved with a single therapeutic agent and translates to immune activation and clinical responses in patients with recurrent glioblastoma, with minimal treatment-related toxicity. These findings establish CD200AR targeting as a next-generation immunotherapeutic approach with the potential to improve the safety and efficacy of immune-based therapies for aggressive CNS malignancies. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=179 SRC="FIGDIR/small/26345679v1_ufig1.gif" ALT="Figure 1"> View larger version (80K): org.highwire.dtl.DTLVardef@17a5010org.highwire.dtl.DTLVardef@11e67eborg.highwire.dtl.DTLVardef@1387c07org.highwire.dtl.DTLVardef@156d418_HPS_FORMAT_FIGEXP M_FIG C_FIG

Autoimmune inflammatory myopathies (AIM) with prominent B cell aggregates (BCM) on muscle biopsy is an uncommon finding. We aimed to compare the characteristics and clinical course of patients with BCM on muscle biopsy to those without and characterize B cell infiltrates in the muscle of these patients. We performed a retrospective study of subjects with AIM in the Canada Inflammatory Myopathy Study (CIMS) cohort to identify cases with BCM on muscle biopsy, which was defined as [&ge;]30 CD20+ cells/aggregate. AIM cases without BCM that encompassed the broader spectrum of AIM, namely dermatomyositis, overlap myositis and inclusion body myositis were selected as controls. Descriptive statistics were used to compare BCM cases and controls. Cyclic immunofluorescence (Cyc-IF) was performed to characterize inflammatory infiltrates and B cell structures. We included 69 subjects (mean age at diagnosis 51{+/-}16 years, 77% females): 22 BCM, 24 dermatomyositis, 14 overlap myositis, and inclusion body myositis. Most BCM subjects (18/22, 82%) had an associated autoimmune disease: 12 (55%) had systemic sclerosis, 5 (23%) rheumatoid arthritis and one (5%) systemic lupus erythematosus/systemic sclerosis overlap. Extra-muscular features found in BCM patients included arthritis (50%), interstitial lung disease (43%), Raynauds phenomenon (32%), and dermatomyositis rash (27%). Two patients (9%) had facial muscle weakness and one (5%) had positive anti-AChR autoantibodies. In BCM subjects, upper extremities were weaker than lower extremities in 7/21 (33%) of cases. Neck flexor weakness was frequent (17/22, 77%), while neck extensor weakness was uncommon (1/15, 7%). Cyclic immunofluorescence (Cyc-IF) spatial analysis of BCM biopsies displayed many features akin to tertiary lymphoid structures. Findings suggest possible involvement of both the traditional germinal center reaction and the extrafollicular pathway in BCM. In conclusion, in this series of myositis with B cell aggregates reported to date we found clinical similarities (i.e., associated with overlapping autoimmune diseases) and differences (i.e., muscle weakness distribution) with previous reports. The discovery of tertiary lymphoid structures on spatial analysis of muscle biopsies of BCM patients provides novel insight into its pathophysiology and potential therapeutic targets.

The cerebrospinal fluid (CSF) proteome offers a direct readout of central nervous system (CNS) biology but its genetic architecture remains incompletely defined. We conducted the largest single-site CSF genome-wide association study (GWAS) to date, analysing 7,092 SomaScan proteins in 1,259 individuals. Using a covariate-adjusted model including proteomic PCs and disease status, we identified 1,971 genome-wide significant pQTLs (954 cis, 971 trans), 1,409 of which replicated in an independent CSF dataset. We discovered 264 previously unreported loci, replicated 511 associations, refined 80 known loci, and 265 proxy-based associations. Using a previously published reproducibility framework, we show that robust discovery concentrates in reliable measurements, underscoring the importance of rigorous quality control. Enrichment analyses revealed immune/complement and extracellular matrix biology. Mendelian randomization prioritised causal proteins: PILRA, TREM2, IL34, CR2, SHARPIN and ERBB1 (Alzheimers disease); BST1 and GPNMB (Parkinsons disease); STX6 (Creutzfeldt Jacobs disease); and ATXN3 and B4GALNT1 (Amyotrophic lateral sclerosis), providing a scalable framework for orthogonal target validation in neurodegeneration. HighlightsCSF A{beta}42 and p-tau, CSF total protein and Qalb are major contributors to the proteomic variance and may act as potential confounders. Most pQTLs were found in proteins classified as "reproducible" based on our CSF proteomic score. The most stringently adjusted GWAS model maximized pQTL discovery among the highest-reproducibility proteins (score 1 and A). We identified 264 novel CSF pQTLs that were not described in previous analyses, replicated 511 CSF pQTLs, 80 map refinements and 265 proxy SNPs, predominantly involved in immune-related, inflammatory, and extracellular matrix mechanisms. We found 281 CSF pQTLs that were also systemic modulators of plasma protein levels that were enriched in immune-related and extracellular matrix mechanisms. We identified and validated several causal proteins associated with AD and other neurodegenerative disorders.

Importance: Dementia is common in Parkinson's disease (PD), causing greater disability than other symptoms, but varies in timing. Although visual deficits are linked with PD dementia, how these interact with genetic factors to predict PD dementia has not been characterised. Objective: To investigate whether visual deficits and genetic factors predict PD dementia. Design: Large prospective longitudinal case-control study, mean follow-up 32.7 (SD=12.3) months. Setting: Cases were recruited between 2017-2020 at 35 UK PD clinics. Participants: People with PD without dementia at baseline were included. Main outcomes and measures: Visual function was measured using a web-based platform. The main outcome measure was global cognition, measured as the Montreal Cognitive Assessment (MoCA). Blood samples were collected for genetics. Results: 450 patients with PD were included. Mean age of PD patients was 71.7 (SD=7.8), 68% male. Mean baseline MoCA was 27.7 (SD=1.7). 263 patients with PD were classed as poor-vision based on baseline visual tests: mean age 74.4 (SD=6.8) compared to 69.7 (SD=7.5) with good-vision. Poor-vision PD patients had higher rates of progression to mild cognitive impairment (PD-MCI) (HR=2.34, CI=1.58-3.48, pFDR=0.00062, age- and sex-corrected). The combination of genetic factors together with vision influenced outcomes. In good-vision PD patients, high-risk GBA1 gene variants were linked with greater progression to PD-MCI (HR=4.61, CI=1.73-12.28, pFDR=0.0068). Polygenic Risk Score (PRS) for both PD and Alzheimer's disease (AD) also modified cognitive survival when combined with vision status. High PD-PRS was associated with greater progression to PD-MCI in good-vision patients (HR=2.66, CI=1.21-5.81, pFDR=0.0381); and high AD-PRS with greater progression to PD-MCI in poor-vision PD patients (HR=1.91, CI=1.10-3.32, pFDR=0.04999). Combining high PD- and AD-PRS, compared to low PD- and AD-PRS in good-vision PD showed even higher progression to PD-MCI (HR=6.14, CI=1.36-27.83, pFDR=0.046). Simulations showed that adding visual and genetic stratification reduced sample size from n=705 to n=160 for clinical trials. Conclusions and relevance: Poor vision in PD predicts progression to PD-MCI and dementia. This combines with the effects of genetic factors including GBA risk variants and PD- and AD-PRS. These findings can enable enrichment of clinical trials for patients at higher risk of PD dementia, for more efficient trial design for interventions to slow progression.

Individuals who carry two copies of the apolipoprotein E {varepsilon}4 (APOE{varepsilon}4) allele are at high risk of developing Alzheimers disease (AD), yet the effects of APOE {varepsilon}4 homozygosity on biological pathways related to AD over the lifespan are unknown. Here we analyzed the plasma proteomes of APOE {varepsilon}4/{varepsilon}4 individuals with and without AD-related cognitive impairment (n=413) and compared them to the proteomes of cognitively unimpaired individuals with APOE {varepsilon}3/{varepsilon}3 genotype (n=2764) from ages 20 to 90. Multiple biological pathways were altered in young adulthood in {varepsilon}4 homozygotes including metabolism and glucagon-like peptide 1/insulin growth factor (GLP-1/IGF), mitochondrial, microtubule, proteostasis, and synaptic pathways. Semaglutide--a GLP-1 receptor agonist--demonstrated reversal effects on metabolic and synaptic pathway alterations in {varepsilon}4 homozygotes at preclinical and clinical AD stages. Targeting metabolic and other pathways for therapeutic intervention in {varepsilon}4/{varepsilon}4 individuals by at least age 50 will likely be the most effective approach to decrease risk for AD in this special population.

BackgroundGenome-wide association studies (GWAS), with independent replication in large European consortia, have identified a common nonsense variant in IL-34 (Y213X) as a genetic risk factor for late-onset Alzheimers disease (AD). However, the biological consequences of this IL-34 mutation in humans, its prevalence in the population, and the mechanisms by which IL-34-Y213X alters microglial homeostasis, cerebrospinal fluid (CSF) proteomic networks, and amyloid pathology remain poorly understood. MethodsWe combined human genetics, cerebrospinal fluid (CSF) and serum proteomics, large-scale phenome-wide association analyses, and preclinical experimental models to define the impact of human IL-34 deficiency. IL-34 concentrations were first quantified in CSF and serum from deeply phenotyped AD cohorts stratified by the common IL-34-Y213X nonsense variant. IL-34 levels and IL-34-Y213X status were then integrated with unbiased CSF proteomic networks and AD biomarkers. Using complementary mouse models of IL-34 loss in an APP/PS1 transgenic background, we examined the effects of IL-34 deficiency on microglial survival, tiling, and plaque encapsulation. Finally, we performed postmortem analyses of temporal cortex from AD patients carrying IL-34-Y213X to assess microglial density, spatial organization, and plaque-associated responses. FindingsIL-34-Y213X was a strong, dose-dependent loss-of-function allele that reduced IL-34 levels by up to 2.5 standard deviations in CSF and serum and was common in multiple populations. IL-34 deficiency reshaped CSF proteomic networks, downregulating axon guidance and microglial support modules while upregulating inflammatory and extracellular matrix signatures, and showed pleiotropic associations with neurological, inflammatory, and metabolic traits. In APP/PS1 mice, genetic IL-34 deletion selectively depleted homeostatic gray-matter microglia, disrupted microglial tiling, and impaired plaque encapsulation, resulting in altered amyloid structure and enhancing neuritic injury. Concordantly, AD patients homozygous for IL-34-Y213X displayed markedly reduced cortical microglial density and increased microglial spatial dispersion, indicating a breakdown of the microglial network organization in the human brain. InterpretationA common human IL-34 loss-of-function variant creates a naturally occurring model of IL-34 deficiency that links microglial survival, CSF network signatures, and amyloid pathology in both mice and humans. These findings position IL-34/CSF1R signaling as a critical determinant of microglial resilience in AD and highlight IL-34-dependent pathways as potential targets for disease modification.

BackgroundNeurodegenerative diseases, including Alzheimers disease (AD), exhibit substantial clinical and molecular heterogeneity, complicating accurate diagnosis and development of effective therapies. Although multi-omics profiling provides unprecedented molecular resolution, systematic integration of high-dimensional, imbalanced data modalities with disease-relevant biological networks remains a methodological challenge. MethodsWe developed a network-informed multi-omics integration framework that combines data-driven molecular networks with brain transcriptomic, proteomic, and metabolomic data from 356 participants in the Religious Orders Study and Rush Memory and Aging Project (ROS/MAP). Utilizing 25 functional, data-driven multi-omics groups (DAD-MUGs) derived by graph embedding from the AD Atlas, co-expression-guided feature extraction and systematic two-phase feature balancing were applied to derive representative molecular features, which were subsequently learned using DAD-MUG-specific autoencoders to generate compact multi-omics expression scores. These were then used to identify molecular subgroups via hierarchical clustering. Subgroup robustness was assessed in an independent ROS/MAP cohort (n=327) using a two-round nested classification strategy. ResultsSubgroup identification based on DAD-MUG-derived expression scores resulted in five molecular subgroups exhibiting significant differences in cognitive performance and core neuropathological measures. Cross-validated nested classification using transcriptomic and proteomic data demonstrated reliable discrimination of subgroups. Applying these classifiers to the replication cohort, subgroup-trait association patterns showed strong agreement with discovery findings (Spearman {rho} = 0.65). Differential expression analysis further revealed stage-dependent biological patterns of brain pathologies, ranging from early synaptic and immune activation to mitochondrial bioenergetic dysfunction at disease transition and proteostatic impairment in advanced stages. ConclusionUsing a balanced, network-informed multi-omics integration framework, we identified five molecular subgroups of brain aging, including a reference control subgroup and a distinct mixed subgroup characterized by amyloid, vascular pathology, and early-life adversity. Three additional subgroups formed a structured spectrum comprising molecularly Alzheimers-like but cognitively and neuropathologically unimpaired At-risk controls, an intermediate stage, and typical Alzheimers disease, with tau pathology differentiating advanced disease, underscoring the value of molecular subgroup identification beyond clinical diagnosis.

BackgroundPrognosis and therapeutic management in Parkinsons disease remain challenging due to the diseases heterogeneous progression and symptom presentation and lack of reliable biomarkers to predict individual disease trajectories. ObjectiveTo determine whether baseline blood transcriptomes, analyzed through biologically defined pathway gene sets, contain signatures that distinguish distinct motor and non-motor progression trajectories in Parkinsons disease. MethodsUsing data from the Parkinsons Progression Markers Initiative cohort, we developed a pathway-based computational framework to derive individualized molecular severity scores from baseline blood transcriptomic profiles by integrating pathway-level gene expression with longitudinal clinical data. Severity indices for motor and non-motor features established domain-specific progression trajectories of sporadic Parkinsons disease. Machine learning models were trained to predict patient trajectory membership from baseline transcriptomics. Findings were validated in genetic subcohorts and externally in the Parkinsons Disease Biomarkers Program cohort. ResultsMolecular severity scores were associated with key clinical features. Analysis of score changes revealed two non-motor and two motor progression groups, each characterized by specific gene signatures (20 genes for non-motor; 121 for motor). From baseline transcriptomic data, we accurately predicted an individuals trajectory group (0.87 for motor progression). The framework demonstrated high generalizability across independent and genetic cohorts, producing clinically coherent profiles. ConclusionsOur analysis reveals that baseline blood transcriptomic profiles delineate motor and non-motor progression trajectories in sporadic Parkinsons disease. The results are consistent with prior findings and may contribute to the identification of novel biomarkers, thereby informing and potentially optimizing the design of clinical trials aimed at modifying disease progression.

INTRODUCTIONThe pathophysiology and risk factors for Alzheimers disease (AD) and dementia are insufficiently known. We studied the connections between gut microbiome, overall dementia and AD in a prospective, population-based cohort. METHODSWe followed a population based random sample of 4,055 individuals (FINRISK 2022) for 16 years, with 330 cases of incident dementia and 280 AD cases. Gut microbiome community diversity and composition were assessed against future dementia and AD risk. Competing mortality risks were accounted for using Fine-Gray models. RESULTSCommunity diversity was not associated with dementia or AD. However, a supervised ordination with dbRDA suggested a possible compositional link between gut microbiome and dementia. One putative bacterial genus, Dorea, was associated with a decreased dementia risk. APOE {varepsilon}4 genotype associated with several taxa; of these, phylum Verrucomicrobiota and species Nocardia carnea were associated with incident dementia. DISCUSSIONThe gut-brain axis has a modest association on future dementia or AD risk. Microbial composition, rather diversities, may contribute to dementia risk.