Galnt17 loss-of-function leads to developmental delay and abnormal coordination, activity, and social interactions with cerebellar vermis pathology

Genome-Wide DNA Methylation Profiling as a Prognostic Marker in Pituitary Adenomas-A Pilot Study

BACKGROUND

The prediction of the regrowth potential of pituitary adenomas after surgery is challenging. The genome-wide DNA methylation profiling of pituitary adenomas may separate adenomas into distinct methylation classes corresponding to histology-based subtypes. Specific genes and differentially methylated probes involving regrowth have been proposed, but no study has linked this epigenetic variance with regrowth potential and the clinical heterogeneity of nonfunctioning pituitary adenomas. This study aimed to investigate whether DNA methylation profiling can be useful as a clinical prognostic marker.

METHODS

A DNA methylation analysis by Illumina's MethylationEPIC array was performed on 54 pituitary macroadenomas from patients who underwent transsphenoidal surgery during 2007-2017. Twelve patients were excluded due to an incomplete postoperative follow-up, degenerated biobank-stored tissue, or low DNA methylation quality. For the quantitative measurement of the tumor regrowth rate, we conducted a 3D volumetric analysis of tumor remnant volume via annual magnetic resonance imaging. A linear mixed effects model was used to examine whether different DNA methylation clusters had different regrowth patterns.

RESULTS

The DNA methylation profiling of 42 tissue samples showed robust DNA methylation clusters, comparable with previous findings. The subgroup of 33 nonfunctioning pituitary adenomas of an SF1-lineage showed five subclusters with an approximately unbiased score of 86%. There were no overall statistically significant differences when comparing hazard ratios for regrowth of 100%, 50%, or 0%. Despite this, plots of correlated survival estimates suggested higher regrowth rates for some clusters. The mixed effects model of accumulated regrowth similarly showed tendencies toward an association between specific DNA methylation clusters and regrowth potential.

CONCLUSION

The DNA methylation profiling of nonfunctioning pituitary adenomas may potentially identify adenomas with increased growth and recurrence potential. Larger validation studies are needed to confirm the findings from this explorative pilot study.

The construction of a novel prognostic prediction model for glioma based on GWAS-identified prognostic-related risk loci

Backgrounds

Glioma is a highly malignant brain tumor with a grim prognosis. Genetic factors play a role in glioma development. While some susceptibility loci associated with glioma have been identified, the risk loci associated with prognosis have received less attention. This study aims to identify risk loci associated with glioma prognosis and establish a prognostic prediction model for glioma patients in the Chinese Han population.

Methods

A genome-wide association study (GWAS) was conducted to identify risk loci in 484 adult patients with glioma. Cox regression analysis was performed to assess the association between GWAS-risk loci and overall survival as well as progression-free survival in glioma. The prognostic model was constructed using LASSO Cox regression analysis and multivariate Cox regression analysis. The nomogram model was constructed based on the single nucleotide polymorphism (SNP) classifier and clinical indicators, enabling the prediction of survival rates at 1-year, 2-year, and 3-year intervals. Additionally, the receiver operator characteristic (ROC) curve was employed to evaluate the prediction value of the nomogram. Finally, functional enrichment and tumor-infiltrating immune analyses were conducted to examine the biological functions of the associated genes.

Results

Our study found suggestive evidence that a total of 57 SNPs were correlated with glioma prognosis (p < 5 × 10-5). Subsequently, we identified 25 SNPs with the most significant impact on glioma prognosis and developed a prognostic model based on these SNPs. The 25 SNP-based classifier and clinical factors (including age, gender, surgery, and chemotherapy) were identified as independent prognostic risk factors. Subsequently, we constructed a prognostic nomogram based on independent prognostic factors to predict individualized survival. ROC analyses further showed that the prediction accuracy of the nomogram (AUC = 0.956) comprising the 25 SNP-based classifier and clinical factors was significantly superior to that of each individual variable.

Conclusion

We identified a SNP classifier and clinical indicators that can predict the prognosis of glioma patients and established a prognostic prediction model in the Chinese Han population. This study offers valuable insights for clinical practice, enabling improved evaluation of patients' prognosis and informing treatment options.

Isolated loss of the AUTS2 long isoform, brain-wide or targeted to Calbindin-lineage cells, generates a specific suite of brain, behavioral, and molecular pathologies

Rearrangements within the AUTS2 region are associated with a rare syndromic disorder with intellectual disability, developmental delay, and behavioral abnormalities as core features. In addition, smaller regional variants are linked to wide range of neuropsychiatric disorders, underscoring the gene's essential role in brain development. Like many essential neurodevelopmental genes, AUTS2 is large and complex, generating distinct long (AUTS2-l) and short (AUTS2-s) protein isoforms from alternative promoters. Although evidence suggests unique isoform functions, the contributions of each isoform to specific AUTS2-linked phenotypes have not been clearly resolved. Furthermore, Auts2 is widely expressed across the developing brain, but cell populations most central to disease presentation have not been determined. In this study, we focused on the specific roles of AUTS2-l in brain development, behavior, and postnatal brain gene expression, showing that brain-wide AUTS2-l ablation leads to specific subsets of the recessive pathologies associated with mutations in 3' exons (exons 8-19) that disrupt both major isoforms. We identify downstream genes that could explain expressed phenotypes including hundreds of putative direct AUTS2-l target genes. Furthermore, in contrast to 3' Auts2 mutations which lead to dominant hypoactivity, AUTS2-l loss-of-function is associated with dominant hyperactivity and repetitive behaviors, phenotypes exhibited by many human patients. Finally, we show that AUTS2-l ablation in Calbindin 1-expressing cell lineages is sufficient to yield learning/memory deficits and hyperactivity with abnormal dentate gyrus granule cell maturation, but not other phenotypic effects. These data provide new clues to in vivo AUTS2-l functions and novel information relevant to genotype-phenotype correlations in the human AUTS2 region.

Parkinson's Disease Risk Variant rs9638616 is Non-Specifically Associated with Altered Brain Structure and Function

Background

A genome-wide association study (GWAS) variant associated with Parkinson's disease (PD) risk in Asians, rs9638616, was recently reported, and maps to WBSCR17/GALNT17, which is involved in synaptic transmission and neurite development.

Objective

To test the association of the rs9638616 T allele with imaging-derived measures of brain microstructure and function.

Methods

We analyzed 3-Tesla MRI and genotyping data from 116 early PD patients (aged 66.8±9.0 years; 39% female; disease duration 1.25±0.71 years) and 57 controls (aged 68.7±7.4 years; 54% female), of Chinese ethnicity. We performed voxelwise analyses for imaging-genetic association of rs9638616 T allele with white matter tract fractional anisotropy (FA), grey matter volume and resting-state network functional connectivity.

Results

The rs9638616 T allele was associated with widespread lower white matter FA (t = -1.75, p = 0.042) and lower functional connectivity of the supplementary motor area (SMA) (t = -5.05, p = 0.001), in both PD and control groups. Interaction analysis comparing the association of rs9638616 and FA between PD and controls was non-significant. These imaging-derived phenotypes mediated the association of rs9638616 to digit span (indirect effect: β= -0.21 [-0.42,-0.05], p = 0.031) and motor severity (indirect effect: β= 0.15 [0.04,0.26], p = 0.045).

Conclusions

We have shown that a novel GWAS variant which is biologically linked to synaptic transmission is associated with white matter tract and functional connectivity dysfunction in the SMA, supported by changes in clinical motor scores. This provides pathophysiologic clues linking rs9638616 to PD risk and might contribute to future risk stratification models.