The genetic architecture of resilience highlights the need for precision interventions

Background: Resilience from Alzheimer’s disease (AD) is heritable trait with a largely unexplored genetic architecture. We have developed a harmonized resource called the Resilience from Alzheimer’s disease database to enable the discovery of genetic factors that protect the brain from the consequences of AD neuropathology. We highlight a set of results from our team that suggests a precision medicine approach that considers the genetic context, amyloid status, and sex of the individual may be a promising path forward.
Method: We have harmonized cognitive data and genetic data from 23,490 individuals, including subsets that have harmonized measures of amyloid, tau, and brain atrophy. We leveraged this rich resource to identify gene modifiers of the well-established effects of APOE and baseline amyloid status on memory and hippocampal atrophy, highlighting genes and pathways implicated in resilience.
Result: We identified a novel locus for cognitive decline on chromosome 9 within the PRUNE2 gene that was associated with more rapid cognitive decline among APOE-ε4 carriers (p=1.9×10-8 ) but not non-carriers (p=0.61). We have also identified genetic modifiers of amyloid and tau pathology in parallel analyses reported elsewhere in this conference and notably our findings suggest that vascular and metabolic pathways contribute to resilience in a sex-specific manner. Specifically, our sex-stratified GWAS of resilience and cognitive performance highlight genetic predictors of healthy heart rate that predict resilience only among males, and genetic predictors of circadian rhythm that relate to resilience only among females.
Conclusion: We have identified a novel locus within the PRUNE2 gene that acts in an APOE-dependent manner to drive cognitive decline. This gene was previous implicated in hippocampal atrophy and synaptic function, making it a fascinating candidate. On the other end of the spectrum, we have identified multiple genes and pathways that appear to promote resilience and neuroprotection, particularly along vascular, metabolic, and sleep pathways that act in a sex-specific manner. Our findings from 3 parallel studies suggest that certain biological factors drive AD risk and resilience in a manner that depends on the genetic context (e.g., APOE genotype) and sex of the individual, providing an opportunity for precision interventions.

Prostate tumor eccentricity predicts Gleason score better than prostate tumor volume

Background: Prostate tumor volume predicts biochemical recurrence, metastases, and tumor proliferation. A recent study showed that prostate tumor eccentricity (elongation or roundness) correlated with Gleason score. No studies examined the relationship among the prostate tumor’s shape, volume, and potential aggressiveness.
Methods: Of the 26 patients that were analyzed, 18 had volumes >1 cc for the histology-based study, and 25 took up contrast material for the MRI portion of this study. This retrospective study quantitatively compared tumor eccentricity and volume measurements from pathology assessment sectioned wholemount prostates and multi-parametric MRI to Gleason scores. Multi-parametric MRI (T1, T2, diffusion, dynamic contrast-enhanced images) were resized, translated, and stitched to form spatially registered multi-parametric cubes. Multi-parametric signatures that characterize prostate tumors were inserted into a target detection algorithm (Adaptive Cosine Estimator, ACE).
Various detection thresholds were applied to discriminate tumor from normal tissue. Pixel-based blobbing, and labeling were applied to digitized pathology slides and threshold ACE images. Tumor volumes were measured by counting voxels within the blob. Eccentricity calculation used moments of inertia from the blobs.
Results: From wholemount prostatectomy slides, fitting two sets of independent variables, prostate tumor eccentricity (largest blob eccentricity, weighted eccentricity, filtered weighted eccentricity) and tumor volume (largest blob volume, average blob volume, filtered average blob volume) to Gleason score in a multivariate analysis, yields correlation coefficient R=0.798 to 0.879 with P<0.01. The eccentricity t-statistic exceeded the volume t-statistic. Fitting histology-based total prostate tumor volume against Gleason score yields R=0.498, P=0.0098. From multi-parametric MRI, the correlation coefficient R between the Gleason score and the largest blob eccentricity for varying thresholds (0.30 to 0.55) ranged from -0.51 to -0.672 (P<0.01). For varying thresholds (0.60 to 0.80) for MRI detection, the R between the largest blob volume eccentricity against the Gleason score ranged from 0.46 to 0.50 (P<0.03). Combining tumor eccentricity and tumor volume in multivariate analysis failed to increase Gleason score prediction.
Conclusions: Prostate tumor eccentricity, determined by histology or MRI, more accurately predicted Gleason score than prostate tumor volume. Combining tumor eccentricity with volume from histology-based analysis enhanced Gleason score prediction, unlike MRI.
Keywords: Gleason score; Tumor morphology; histology of wholemount prostatectomy; multi-parametric MRI; prostate cancer (PCa).

Measurement of Wire Deflection on Loading may Indicate Union in Ilizarov Constructs: A Pilot Study

Introduction: No entirely reliable method to assess union during Ilizarov treatment exists. Premature frame removal results in treatment failure, and alternative methods of assessment warrant investigation. Wire deflection might provide an indication of fracture site deformation on weight-bearing, indicating progress towards union. A previous in vitro study from our group demonstrated this approach may be clinically applicable. We investigated translation of this method into clinical practice in an observational pilot study.
Materials and methods: Patients with tibial shaft fractures treated with Ilizarov frames were recruited. A prototype depth gauge was used to measure wire deflection on weight-bearing. Investigators undertaking the measurement were blinded to the clinical stage of treatment, and clinicians caring for the patient were blinded to deflection results. Patient records were reviewed at the end of treatment to determine likely fracture stability at each time point. Deflection per kg of weight applied, per mm from the ring was compared between stable and unstable situations.
Results: Thirty-one measurements were obtained in 14 patients. The situation was deemed stable at 13 and unstable at 18 measurements. The median deflection in the stable group was 0.030 microns/kg/mm (IQR 0.005-0.104) and 0.165 microns/kg/mm (IQR 0.072-0.328) in the unstable group. This difference was statistically significant (Wilcoxon Mann-Whitney test p = 0.0014). ROC curve analysis revealed that wire deflection was able to predict clinical stability (AUC 0.84, p <0.0001). Various technical problems were encountered when using the device which would potentially limit its clinical utility in its current form.
Conclusion: In this set of observations, wire deflection was significantly associated with clinically and radiologically determined stability. Though various practical limitations were encountered in using the prototype measurement device, this proof-of-concept study supports further development of this approach. The research group plan to develop a smaller, more reliable device for further clinical testing in a larger group of patients.
How to cite this article: Lineham B, Stewart T, Ward J, et al. Measurement of Wire Deflection on Loading may Indicate Union in Ilizarov Constructs: A Pilot Study. Strategies Trauma Limb Reconstr 2021;16(3):132-137.
Keywords: Frame; Ilizarov; Observational study; Pilot; Union; Wire deflection.

Bioinformatics pipeline to advance the identification of transcription regulatory variants in LOAD noncoding regions.

Background: As new LOAD genetic risk loci are identified and more brain cell-type specific omics data becomes available, there is an unmet need for a bioinformatics framework to prioritize genes and variants for testing in single-cell molecular profiling experiments and validation using disease models and gene editing technologies. We developed a new bioinformatics pipeline to characterize and prioritize SNPs in enhancers located in LOAD-GWAS regions based on their predicted impact to alter transcription factor (TF) binding. The proposed bioinformatics pipeline progresses from SNPs located in LOAD-GWAS regions to a filtered set of regulatory SNPs that have a predicted strong effect on TF binding.
Method: We utilized publicly available bioinformatics software and data sources. Software: motifbreakR, UCSC Table Browser, GTEx portal and JMP. Databases: dbSNP v150, chromatin state segmentation data from the Roadmap Consortium, expression data: brain tissue from GTEX v8, monocyte from Cardiogenics, TF ChIP-seq data from ENCODE and TF binding motifs from MotifDb.
Result: We catalogued 61 strong enhancers in LOAD-GWAS regions that encompass 326 SNPs and 104 TF binding sites. 77 and 78 of the TFs were expressed in brain and monocytes, respectively, out of which 19 TF-binding sites showed ChIP-seq signals.
Next, we evaluated the effect of SNPs mapped within this set of TF-binding sites and found that 11 SNPs interrupt with the TF binding. We then determined the LD relationships between the LOAD-risk SNP and the TF ‘interrupter’ SNP to interpret whether the LOAD association is driven by up- or down- regulation of transcription mediated by the corresponding TF. For example, a SNP within an active enhancer adjacent to PICALM disrupts the SPI1 TF binding site. The enhancer SNP and the LOAD-GWAS SNP are in high LD, and we found that the GWAS-risk allele links to the enhancer allele that causes loss of SPI1 binding.
Conclusion: This study provides an analytical framework to catalogue noncoding variations in enhancers located in LOAD-GWAS loci and characterize their likelihood to perturb TF binding. The approach integrates multiple data types to characterize and prioritize SNPs for further exploration of their putative regulatory function using single-cell multi-omics assays and gene editing.

Whole genome sequencing analysis of cognitively Wellderly individuals identifies potential protective genetic variants for Alzheimer’s disease.

Background: Genetic variants that confer protection from Alzheimer’s disease (AD) may be particularly critical in developing therapeutics. To target protective variant identification, we performed genetic association testing among selected individuals with whole genome sequencing (WGS) that remained alive and dementia-free beyond age 85 (“Wellderly”).
Methods: We selected 1,873 White and Black Wellderly individuals with documented normal cognition beyond age 85 as determined by direct, in-person assessment from three cohorts (FHS, CHS, and ARIC) with WGS from the NHLBI TOPMed project. We used two sets of comparison groups from these three cohorts: (i) general controls, non-Wellderly individuals including persons without and with dementia [n=8,502] and (ii) individuals who developed dementia before age 85 [n=810]. We performed generalized mixed model regression for binary outcomes using Wellderly status, separately with each comparison group, for each variant with a minor allele frequency (MAF) > 1%, adjusting for study and principal components of ancestry as fixed effects, and a genetic-relatedness matrix as a random effect to account for relatedness and shared ancestry. Additionally, we performed association testing adjusting for APOE e4 status. Our top results outside of the APOE locus tended to be more significant after adjusting for APOE e4 status.

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Results: We observed a reduced risk of Wellderly status compared to general controls at the APOE locus (rs429358, MAF=14%, odds ratio [OR] = -0.40, p=1.6×10-10 ), consistent with the known association of the APOE locus with dementia. Additionally, we found suggestive associations at CACNA2D3 (rs73085981, MAF=16%, OR=1.44, p=6.7×10-8 ), ASTN2 (rs7350805, MAF=1%, OR=1.10, p=4.3×10-7 ), and YEATS4 (rs167588, MAF=1%, OR=1.1, p=3.7×10-7 ) using the general controls adjusting for APOE e4 status. CACNA2D3 and ASTN2 have plausible biological connections to AD. CACNA2D3 is a calcium channel gene and rare copy number variation has been implicated in voltage gate calcium channel genes in individuals with late-onset AD. ASTN2 encodes a protein that is expressed in the brain and may function in neuronal migration, and has been previously implicated in age of onset of AD and is associated with hippocampal volume.
Conclusion: Although only variants in the APOE locus reached a genome-wide significance threshold, we found suggestive associations for Wellderly status with biological plausibility.

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