Performed Association Analysis Research Articles

Whole Genome Linkage and Association Analyses Identify DLG Associated Protein-1 as a Novel Positional and Biological Candidate Gene for Muscle Strength: The Long Life Family Study.

Grip strength is a robust indicator of overall health, is moderately heritable, and predicts longevity in older adults. Using genome-wide linkage analysis, we identified a novel locus on chromosome 18p (mega-basepair region: 3.4 - 4.0) linked to grip strength in 3755 individuals from 582 families aged 64 ± 12 years (range 30-110 years; 55% women). There were 26 families that contributed to the linkage peak (cumulative logarithm of the odds [LOD] score = 10.94), with six families (119 individuals) accounting for most of the linkage signal (LOD = 6.4). In these 6 families, using whole genome sequencing data, we performed association analyses between the 7312 single nucleotide (SNVs) and insertion deletion (INDELs) variants in the linkage region and grip strength. Models were adjusted for age, age2, sex, height, field center, and population substructure. We found significant associations between genetic variants (8 SNVs and 4 INDELs, p<5*10-5) in the Disks Large-associated Protein 1 (DLGAP1) gene and grip strength. Haplotypes constructed using these variants explained up to 98.1% of the LOD score. Finally, RNAseq data showed that these variants were significantly associated with the expression of nearby Myosin Light Chain 12A (MYL12A), Structural Maintenance of Chromosomes Flexible Hinge Domain Containing 1 (SMCHD1), Erythrocyte Membrane Protein Band 4.1 Like 3 (EPB41L3) genes (p< .0004). The DLGAP1 gene plays an important role in the post-synaptic density of neurons; thus, it is both a novel positional and biological candidate gene for follow-up studies aimed at uncovering genetic determinants of muscle strength.

Large-scale statistical analysis of Mycobacterium tuberculosis genome sequences identifies compensatory mutations associated with multi-drug resistance

Tuberculosis (TB), caused by Mycobacterium tuberculosis, has a significant impact on global health worldwide. The development of multi-drug resistant strains that are resistant to the first-line drugs isoniazid and rifampicin threatens public health security. Rifampicin and isoniazid resistance are largely underpinned by mutations in rpoB and katG respectively and are associated with fitness costs. Compensatory mutations are considered to alleviate these fitness costs and have been observed in rpoC/rpoA (rifampicin) and oxyR’-ahpC (isoniazid). We developed a framework (CompMut-TB) to detect compensatory mutations from whole genome sequences from a large dataset comprised of 18,396 M. tuberculosis samples. We performed association analysis (Fisher’s exact tests) to identify pairs of mutations that are associated with drug-resistance, followed by mediation analysis to identify complementary or full mediators of drug-resistance. The analyses revealed several potential mutations in rpoC (N = 47), rpoA (N = 4), and oxyR’-ahpC (N = 7) that were considered either ‘highly likely’ or ‘likely’ to confer compensatory effects on drug-resistance, including mutations that have previously been reported and validated. Overall, we have developed the CompMut-TB framework which can assist with identifying compensatory mutations which is important for more precise genome-based profiling of drug-resistant TB strains and to further understanding of the evolutionary mechanisms that underpin drug-resistance.

Using genome and transcriptome data from African-ancestry female participants to identify putative breast cancer susceptibility genes

African-ancestry (AA) participants are underrepresented in genetics research. Here, we conducted a transcriptome-wide association study (TWAS) in AA female participants to identify putative breast cancer susceptibility genes. We built genetic models to predict levels of gene expression, exon junction, and 3′ UTR alternative polyadenylation using genomic and transcriptomic data generated in normal breast tissues from 150 AA participants and then used these models to perform association analyses using genomic data from 18,034 cases and 22,104 controls. At Bonferroni-corrected P < 0.05, we identified six genes associated with breast cancer risk, including four genes not previously reported (CTD-3080P12.3, EN1, LINC01956 and NUP210L). Most of these genes showed a stronger association with risk of estrogen-receptor (ER) negative or triple-negative than ER-positive breast cancer. We also replicated the associations with 29 genes reported in previous TWAS at P < 0.05 (one-sided), providing further support for an association of these genes with breast cancer risk. Our study sheds new light on the genetic basis of breast cancer and highlights the value of conducting research in AA populations.

Genome‑wide identification and expression analysis of the UBC gene family in wheat (Triticum aestivum L.)

BackgroundUbiquitination is an important regulatory step of selective protein degradation in the plant UPS (ubiquitin–proteasome system), which is involved in various biological processes in eukaryotes. Ubiquitin-conjugating enzymes play an intermediate role in the process of protein ubiquitination reactions and thus play an essential role in regulating plant growth and response to adverse environmental conditions. However, a genome-wide analysis of the UBC gene family in wheat (Triticum aestivum L.) has not yet been performed.ResultsIn this study, the number, physiochemical properties, gene structure, collinearity, and phylogenetic relationships of TaUBC family members in wheat were analyzed using bioinformatics methods. The expression pattern of TaUBC genes in different tissues/organs and developmental periods, as well as the transcript levels under abiotic stress treatment, were analyzed using RNA-Seq data and qRT-PCR. Meanwhile, favorable haplotypes of TaUBC25 were investigated based on wheat resequencing data of 681 wheat cultivars from the Wheat Union Database. The analyses identified a total of 93 TaUBC family members containing a UBC domain in wheat genome. These genes were unevenly distributed across 21 chromosomes, and numerous duplication events were observed between gene members. Based on phylogenetic analysis, the TaUBC family was divided into 13 E2 groups and a separate UEV group. We investigated the expression of TaUBC family genes under different tissue/organ and stress conditions by quantitative real-time PCR (qRT-PCR) analysis. The results showed that some TaUBC genes were specifically expressed in certain tissues/organs and that most TaUBC genes responded to NaCl, PEG6000, and ABA treatment with different levels of expression. In addition, we performed association analysis for the two haplotypes based on key agronomic traits such as thousand-kernel weight (TKW), kernel length (KL), kernel weight (KW), and kernel thickness (KT), examining 122 wheat accessions at three environmental sites. The results showed that TaUBC25-Hap II had significantly higher TKW, KL, KW, and KT than TaUBC25-Hap I. The distribution analysis of haplotypes showed that TaUBC25-Hap II was preferred in the natural population of wheat.ConclusionOur results identified 93 members of the TaUBC family in wheat, and several genes involved in grain development and abiotic stress response. Based on the SNPs detected in the TaUBC sequence, two haplotypes, TaUBC25-Hap I and TaUBC25-Hap II, were identified among wheat cultivars, and their potential value for wheat breeding was validated by association analysis. The above results provide a theoretical basis for elucidating the evolutionary relationships of the TaUBC gene family and lay the foundation for studying the functions of family members in the future.

Genetic and Functional Diversity Help Explain Pathogenic, Weakly Pathogenic, and Commensal Lifestyles in the Genus Xanthomonas.

The genus Xanthomonas has been primarily studied for pathogenic interactions with plants. However, besides host and tissue-specific pathogenic strains, this genus also comprises nonpathogenic strains isolated from a broad range of hosts, sometimes in association with pathogenic strains, and other environments, including rainwater. Based on their incapacity or limited capacity to cause symptoms on the host of isolation, nonpathogenic xanthomonads can be further characterized as commensal and weakly pathogenic. This study aimed to understand the diversity and evolution of nonpathogenic xanthomonads compared to their pathogenic counterparts based on their cooccurrence and phylogenetic relationship and to identify genomic traits that form the basis of a life history framework that groups xanthomonads by ecological strategies. We sequenced genomes of 83 strains spanning the genus phylogeny and identified eight novel species, indicating unexplored diversity. While some nonpathogenic species have experienced a recent loss of a type III secretion system, specifically the hrp2 cluster, we observed an apparent lack of association of the hrp2 cluster with lifestyles of diverse species. We performed association analysis on a large data set of 337 Xanthomonas strains to explain how xanthomonads may have established association with the plants across the continuum of lifestyles from commensals to weak pathogens to pathogens. Presence of distinct transcriptional regulators, distinct nutrient utilization and assimilation genes, transcriptional regulators, and chemotaxis genes may explain lifestyle-specific adaptations of xanthomonads.

GEO dataset mining analysis reveals novel Staphylococcus aureus virulence gene regulatory networks and diagnostic targets in mice.

Staphylococcus (S.) aureus infection is a serious, worldwide health concern, particularly in many communities and hospitals. Understanding the S. aureus pathogenetic regulatory network will provide significant insights into diagnostic target screening to improve clinical treatment of diseases caused by S. aureus. We screened differentially expressed genes between normal mice and S. aureus-infected mice. We used the Gene Expression Omnibus (GEO) DataSets database for functional analysis (GO-analysis) and the DAVID and KEGG databases for signaling pathway analyses. We next integrated the gene and pathway analyses with Transcriptional Regulatory Element Database (TRED) to build an antimicrobial resistance gene regulatory network of S. aureus. We performed association analysis of network genes and diseases using DAVID online annotation tools. We identified a total of 437 virulence genes and 15 transcription factors (TFs), as well as 444 corresponding target genes, in the S. aureus TF regulatory network. We screened seven key network nodes (Met, Mmp13, Il12b, Il4, Tnf, Ptgs2, and Ctsl), four key transcription factors (Jun, C3, Spil, and Il6) and an important signaling pathway (TNF). We hypothesized that the cytokine activity and growth factor activity of S. aureus are combinatorically cross-regulated by Met, Mmp13, Il12b, Il4, Tnf, Ptgs2, and Ctsl genes, the TFs Jun, C3, Spi1, and Il6, as well as the immune response, cellular response to lipopolysaccharide, and inflammatory response. Our study provides information and reference values for the molecular understanding of the S. aureus pathogenetic gene regulatory network.

Abstract P250: Vascular Contributions to Alzheimer's Disease

Introduction: Alzheimer’s disease (AD) is a debilitating neurodegenerative disorder that affects over 50 million people worldwide. The role of vascular risk factors have been described as a contributor to and a major comorbidity of AD pathogenesis; yet there is discordant evidence of this complex relationship between cardiovascular diseases (CVD) and its risk factors (like hypertension, hyperlipidemia, obesity, etc.) with AD pathophysiology and cognitive decline. AD associated Genome-wide association studies (GWAS) and derived polygenic risk scores (AD PRS) have uncovered some significant common genetic variants relating to CVD risk factors; however, we are still yet to unravel the comprehensive impact of these vascular genetic contributions to AD pathogenesis and cognitive decline. Method: In this study, we used 1800 participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort spanning the full spectrum of clinical and pathological diagnoses of the AD spectrum, as our target dataset used for polygenic risk score calculation. Thereafter, we obtained GWAS summary statistics for cumulative cardiovascular risk by searching the Polygenic Score (PGS) GWAS Catalog using CVD as the ‘mapped trait” and then calculated cardiovascular-based PRS using HRS-based imputed GWAS data of the ADNI cohort. We conducted association analysis using a multivariate linear regression model with appropriate covariates (age, sex, APOE, education, etc.) between CVD-related polygenic risk score (CVD-PRS) with the different clinical AD diagnoses groups (Cognitively Normal/CN, Significant Memory Concerns/SMC, Mild Cognitive Impairment/MCI, Alzheimer's Disease/AD). We also performed association analysis of this CVD-PRS with white matter hyperintensity (WMHI) values, a vascular biomarker, at baseline using a linear regression model. Furthermore, we extended our analyses of CVD-related PRS with cognitive performance at baseline using composite scores for memory (MEM) and executive functioning (EF). Results and Conclusion: We found significantly strong correlation of CVD-related PRS with only certain AD Diagnoses groups (Significant Memory Concerns: SMC and Alzheimer's: AD) in the AD continuum. Additionally, we found strong associations (p &lt; 0.05) of this cardiovascular based- polygenic risk score with baseline memory as well as White Matter Hyperintensity (WMH) in our sample, specifically the group with a clinical diagnosis of AD. Furthermore, we are performing longitudinal association analysis of CVD-related PRS with longitudinal cognitive decline using a linear mixed effects model. Our findings will help us understand 1) how a cumulative CVD-related PRS associates with different AD diagnoses subgroups as well as vascular biomarkers for AD and 2) how CVD-related PRS associates with cognitive performance and longitudinal cognitive decline.

Screening of Litter-Size-Associated SNPs in NOX4, PDE11A and GHR Genes of Sheep.

In previous studies, NOX4, PDE11A and GHR genes have been screened as important candidate genes for litter size in sheep by using the GWAS method; however, neither their effects on litter size nor the loci associated with litter size have been identified. In this study, three candidate loci (c.1057-4C > T in NOX4, c.1983C > T in PDE11A and c.1618C > T in GHR) were first screened based on our previous resequencing data of 10 sheep breeds. After the three loci were genotyped using Sequenom MassARRAY technology, we carried out population genetics analysis on the three loci and performed association analysis between the polymorphism of the three loci and the litter size of sheep. The results of population genetics analysis suggested that c.1057-4C > T in NOX4 and c.1983C > T in PDE11A may be subject to natural or artificial selection. The results of association analysis indicated that litter size was significantly associated with c.1057-4C > T in NOX4 and c.1983C > T in PDE11A (p < 0.05) in Small Tail Han sheep, and there was no significant interaction effect between the two loci on the litter size. In summary, c.1057-4C > T in NOX4 and c.1983 C > T in PDE11A can be considered candidate molecular markers for improving litter size in sheep.

Multiomics characterization of pyroptosis in the tumor microenvironment and therapeutic relevance in metastatic melanoma

BackgroundPyroptosis, mediated by gasdermins with the release of multiple inflammatory cytokines, has emerged as playing an important role in targeted therapy and immunotherapy due to its effectiveness at inhibiting tumor growth. Melanoma is one of the most commonly used models for immunotherapy development, though an inadequate immune response can occur. Moreover, the development of pyroptosis-related therapy and combinations with other therapeutic strategies is limited due to insufficient understanding of the role of pyroptosis in the context of different tumor immune microenvironments (TMEs).MethodsHere, we present a computational model (pyroptosis-related gene score, PScore) to assess the pyroptosis status. We applied PScore to 1388 melanoma samples in our in-house cohort and eight other publicly available independent cohorts and then calculated its prognostic power of and potential as a predictive marker of immunotherapy efficacy. Furthermore, we performed association analysis for PScore and the characteristics of the TME by using bulk, single-cell, and spatial transcriptomics and assessed the association of PScore with mutation status, which contributes to targeted therapy.ResultsPyroptosis-related genes (PRGs) showed distinct expression patterns and prognostic predictive ability in melanoma. Most PRGs were associated with better survival in metastatic melanoma. Our PScore model based on genes associated with prognosis exhibits robust performance in survival prediction in multiple metastatic melanoma cohorts. We also found PScore to be associated with BRAF mutation and correlate positively with multiple molecular signatures, such as KRAS signaling and the IFN gamma response pathway. Based on our data, melanoma with an immune-enriched TME had a higher PScore than melanoma with an immune-depleted or fibrotic TME. Additionally, monocytes had the highest PScore and malignant cells and fibroblasts the lowest PScore based on single-cell and spatial transcriptome analyses. Finally, a higher PScore was associated with better therapeutic efficacy of immune checkpoint blockade, suggesting the potential of pyroptosis to serve as a marker of immunotherapy response.ConclusionsCollectively, our findings indicate that pyroptosis is a prognostic factor and is associated with the immune response in metastatic melanoma, as based on multiomics data. Our results provide a theoretical basis for drug combination and reveal potential immunotherapy response markers.

MiR-129-5p as a biomarker for pathology and cognitive decline in Alzheimer’s disease

BackgroundAlzheimer’s dementia (AD) pathogenesis involves complex mechanisms, including microRNA (miRNA) dysregulation. Integrative network and machine learning analysis of miRNA can provide insights into AD pathology and prognostic/diagnostic biomarkers.MethodsWe performed co-expression network analysis to identify network modules associated with AD, its neuropathology markers, and cognition using brain tissue miRNA profiles from the Religious Orders Study and Rush Memory and Aging Project (ROS/MAP) (N = 702) as a discovery dataset. We performed association analysis of hub miRNAs with AD, its neuropathology markers, and cognition. After selecting target genes of the hub miRNAs, we performed association analysis of the hub miRNAs with their target genes and then performed pathway-based enrichment analysis. For replication, we performed a consensus miRNA co-expression network analysis using the ROS/MAP dataset and an independent dataset (N = 16) from the Gene Expression Omnibus (GEO). Furthermore, we performed a machine learning approach to assess the performance of hub miRNAs for AD classification.ResultsNetwork analysis identified a glucose metabolism pathway-enriched module (M3) as significantly associated with AD and cognition. Five hub miRNAs (miR-129-5p, miR-433, miR-1260, miR-200a, and miR-221) of M3 had significant associations with AD clinical and/or pathologic traits, with miR129-5p by far the strongest across all phenotypes. Gene-set enrichment analysis of target genes associated with their corresponding hub miRNAs identified significantly enriched biological pathways including ErbB, AMPK, MAPK, and mTOR signaling pathways. Consensus network analysis identified two AD-associated consensus network modules and two hub miRNAs (miR-129-5p and miR-221). Machine learning analysis showed that the AD classification performance (area under the curve (AUC) = 0.807) of age, sex, and APOE ε4 carrier status was significantly improved by 6.3% with inclusion of five AD-associated hub miRNAs.ConclusionsIntegrative network and machine learning analysis identified miRNA signatures, especially miR-129-5p, as associated with AD, its neuropathology markers, and cognition, enhancing our understanding of AD pathogenesis and leading to better performance of AD classification as potential diagnostic/prognostic biomarkers.

Polymorphism in IGFALS gene and its association with scrotal circumference in Hu lambs

Scrotal circumference is an important reproductive index of breeding rams, which has a high genetic correlation with ejaculation volume and semen quality. In this study, the scrotal circumference of 1353 male Hu sheep at different stages of development was measured and descriptive statistical analysis was performed. The results showed that the coefficient of variation of scrotal circumference at each stage was greater than 10%, and its heritability were moderately to high, ranging from 0.318 to 0.719. We used PCR amplification and Sanger sequencing to scan the polymorphisms of the IGFALS gene, and performed association analysis with the circumference of the scrotum at different stages. We identified a synonymous mutation g.918 G > C in exon 1 of the IGFALS gene, and this mutation was significantly associated with scrotal circumference at 100, 120, 140, 160 and 180 days (p < 0.05). Therefore, IGFALS gene polymorphism can be used as a molecular marker affecting scrotal circumference of Hu sheep, which can provide a reference for future molecular marker-assisted selection of scrotal circumference in sheep.

Phenotypic Variation in Flower Color and Morphology in the Gerbera (Gerbera hybrida) F1 Hybrid Population and Their Association with EST-SSR Markers.

Gerbera (Gerbera hybrida) is a widely cultivated ornamental plant. However, its genetic improvement is limited by the lack of genetic analysis and molecular markers for traits. In this study, we analyzed the phenotypic and genotypic variation of 140 F1 progeny from two gerbera varieties with different flower types and colors. We evaluated the flower's morphology, color, and pigment content of the F1 population and performed cluster principal component analysis (PCA) and correlation analysis. The results showed that the main ornamental traits of the hybrid progeny varied greatly. The segregation ratios of single and double flowers and ligulate and split ray florets were both 1:1. The flower colors of the F1 progeny were mainly red and purple-red, similar to the male parent's color. Furthermore, we conducted a genetic analysis of the hybrid progeny using EST-SSR markers and performed association analysis with phenotypic traits. We identified 2, 2, 3, 1, and 2 loci to be associated with peduncle length (PL), ray floret length (RFL), and outer ray floret; the level of apex relative to the top of involucre (LAI); outer corolla lips (OCL); and the b* of ray floret color, respectively. Our results reveal the genetic patterns of important ornamental traits and provide a theoretical basis and practical tools for gerbera genetic breeding.

Variations in Casein Genes Are Associated with Milk Protein and Fat Contents in Sarda Goats (Capra hircus), with an Important Role of CSN1S2 for Milk Yield.

This work aimed to assess the variability of casein genes in a population of 153 bucks and 825 lactating does of the Sarda breed, and to perform association analysis between polymorphic sites and milk yield and composition traits. To genotype the casein genes, we chose an SNP panel including 44 SNPs mapping to the four casein genes CSN1S1, CSN2, CSN1S2, and CSN3. Genotyping (made by KASP™ genotyping assay, based on competitive allele-specific PCR) revealed the high variability of the Sarda goat, and haplotype analysis revealed linkage disequilibrium (LD) between CSN1S1 and CSN2 genes, in addition to two LD blocks within the CSN1S2 and two LD blocks within the CSN3 gene, in bucks and does. Association analysis revealed that variability at all four casein genes was associated with milk protein content, total solids, and milk energy. The three Ca-sensitive casein genes were associated with lipid content, and CSN1S2 showed a unique pattern, with intron variants associated with milk yield, in addition to milk pH, NaCl, and SCS (Somatic Cell Score). This information might prove useful in selection schemes and in future investigations aiming to better understand the biology of lactation, and the direct link between genotype and phenotype.

Capturing the well-being exposome in poly-environmental scores.

In this study we use aggregated weighted scores of environmental effects to study environmental influences on well-being and happiness. To this end, we split a sample of Netherlands Twin Register (NTR) participants into a training (N = 4857) and test (N = 2077) sample. In the training sample, we use elastic net regression to estimate effect sizes for associations between life satisfaction and two sets of environmental variables: one based on self-report socioenvironmental data, and one based on objective physical environmental data. Based on these effect sizes, we create two poly-environmental scores (PES-S and PES-O, for self-reports and objective data respectively). In the test sample, we perform association analyses between different measures of well-being and the two PESs. We find that the PES-S explains ∼36% of the variance in well-being, while the PES-O does not significantly contribute to the model. Variance in other well-being measures (i.e., different life satisfaction domains, subjective happiness, quality of life, flourishing, psychological well-being, self-rated health, depressive problems, and loneliness) are explained to varying extents by the PESs, ranging from 6.36% (self-rated health) to 36.66% (loneliness). These predictive values did not change during the COVID-19 pandemic (N = 3214). Validating the PES-S in the UK biobank (N = 40,614), we find that the UK biobank PES-S explains about ∼12% of the variance in happiness. Lastly, we examine if there is any indication for gene-environment correlation (rGE), the phenomenon where one's genetic predisposition influences exposure to the environment, by associating the PESs with polygenic scores (PGS) in a sample of Netherlands Twin Register (NTR) and UK Biobank participants. While the PES and PGS were not correlated in the NTR sample, they were correlated in the larger UK biobank sample, indicating the potential presence of rGE. We discuss several limitations pertaining to our dataset, such as a potential influence of common method bias, and reflect on how PESs might be used in future research.

Does surgery affect systemic immune response? a perioperative analysis of TGF-β, IL-8 and CD45RO.

The options of (neo-)adjuvant immunotherapy in addition to surgery in the treatment of oral squamous cell carcinoma (OSCC) are steadily increasing, but patients do not always respond to therapy as intended. The objectives of this study were to investigate the systemic perioperative course of the biomarkers CD45RO, TGF-β, and IL-8 in non-tumor-related minor and tumor-related major maxillofacial surgery and to perform association analyses with demographic and histomorphologic parameters. A deeper understanding of surgery-related changes in various of different immune biomarkers could help to better understand the immunologic consequences of surgery which could influence immunotherapeutic protocols. Peripheral whole blood from 38 patients was analyzed by real-time quantitative polymerase chain reaction (RT-qPCR) at five different timepoints before and after maxillofacial surgery to detect changes in mRNA expression of the biomarkers TGF-β, IL-8 and CD45RO. All patients underwent general anesthesia to undergo either resection and free flap reconstruction for OSCC or minor maxillofacial surgery (controls). Statistical analysis was done using Mann-Whitney-U test, Wilcoxon test, and Spearman's correlation. Compared to the preoperative expression, there was a significant postoperative downregulation of CD45RO, TGF-β and IL-8 until the 4th postoperative day (p ≤ 0.003) in OSCC patients. For TGF-β and IL-8, the reduction in expression was significant (p ≤ 0.004) compared to controls. By postoperative day 10, all analyzed parameters converged to baseline levels. Only CD45RO still showed a significant downregulation (p=0.024). Spearman analysis revealed a significant correlation between increased duration of surgery and perioperative reduction in peripheral blood expression of CD45RO, TGF-β and IL-8 (p ≤ 0.004). Perioperative changes in TGF-β and PD-L1 expression were shown to be not correlated. Preoperative TGF-β expression was significantly lower in patients with lymph node metastases (p=0.014). With regard to the analyzed parameters, major oncologic head-and-neck surgery does not seem to have long-lasting systemic immunologic effects. Reduced CD45RO might be an expression of transient systemic immunosuppression in response to major surgery. The association of duration of surgery with expression changes of immunologic markers supports efforts to keep the duration of surgery as short as possible. As perioperative TGF-β and PD-L1 expression changes are not associated, these results support further investigation of a combined perioperative anti-PD-1 and anti-TGF-β immunotherapy.

Single‐cell Transcriptomes Reveal Cell‐type Specific Roles of VEGF Family Genes in the Pathogenesis of Alzheimer’s Disease

AbstractBackgroundThe role of the vascular endothelial growth factors (VEGFs) in the pathogenesis of Alzheimer’s disease (AD) has been recently described, including notable changes along the VEGFB/FLT1 signaling pathway. Yet, cell‐specific alterations are not well characterized. To disentangle VEGFs’ cell‐specific effect on AD‐related traits, we performed association analyses of mRNA expression from 10 VEGF genes with cognitive performance and AD pathology in eight brain cell types using a large single nucleus RNA sequencing dataset from human brain.MethodThis project utilized recently published single‐cell transcriptomes derived from dorsolateral prefrontal cortex tissues of 424 donors collected at Rush Alzheimer’s Disease Center. Processed single cell RNA sequencing data were acquired from AD Knowledge Portal (syn2580853). Mean age at death was 89 years, 68% were females, and 37% were AD cases. Negative binomial lognormal mixed models implemented in the NEBULA R package were used to detect differential expression between AD cases and cognitively normal controls, and to analyze the associations with immunohistochemical amyloid and tangles, and finally to assess cross‐sectional and longitudinal global cognitive scores. Correction for multiple comparisons was completed using the false discovery rate procedure (Pfdr&lt;0.05).ResultPrefrontal cortical FLT1 expression was upregulated in AD participants compared to cognitively normal controls in both endothelial (endo) and microglial (micro) cells. Higher micro‐FLT1, endo‐FLT4, and oligodendrocyte (oligo) VEGFB expression was associated with greater β‐amyloid burden in AD samples, whereas higher VEGFB expression in inhibitory neurons was associated with lower β‐amyloid burden. Higher expression of micro‐FLT1 and oligo‐VEGFB associated with worse cognitive trajectories. Higher micro‐ and endo‐ expression of FLT1 associated with lower cognition scores at the last clinic visit before death. Lastly, higher astrocyte‐expressed NRP1 was associated with lower tangle burden.ConclusionConsistent with our previously reported bulk tissue results, prefrontal cortical expression of FLT1 and FLT4 were associated with global cognition, longitudinal cognitive trajectories, and AD neuropathology, and these associations appear to be limited to endothelial and microglial cells. In contrast, VEGFB expression seems to have opposite effects on amyloid burden depending on the cell types, suggesting its more dynamic role in AD physiopathology.

Transcriptional risk score in Alzheimer’s disease: from pathology to cognition

AbstractBackgroundTranscriptional risk scores (TRS), a summation of polarized expression levels of functional genes, have been proposed for disease risk assessment using transcriptome profiles. Our previously developed blood‐based TRS showed associations with diagnosis and neuroimaging biomarkers for Alzheimer’s disease (AD). Here, we developed brain‐based TRS models and calculated TRS using brain tissue‐based transcriptome profiles.MethodWe integrated AD genome‐wide association study summary and expression quantitative trait locus data to prioritize target genes using Mendelian randomization and then calculated individual TRS by summing the polarized z‐scores over the target genes. We used brain transcriptome data from the Religious Orders Study and Rush Memory and Aging Project cohort (ROSMAP; N = 634) as a discovery set and the Mount Sinai Brain Bank cohort (MSBB; N = 244) as a replication set. We performed association analysis of TRS with AD diagnosis, amyloidopathy, tauopathy, and cross‐sectional and longitudinal cognitive function. We compared AD classification performance of TRS with polygenic risk scores (PRS) using a machine learning approach (Fig. 1).ResultHigher TRS values were significantly associated with AD compared to cognitively normal controls (Table 1). Higher TRS values were also related with amyloidopathy, tauopathy, poor cognitive performance, and faster cognitive decline. The AD classification performance of PRS was increased with the inclusion of TRS up to 12% with the area under the curve value of 0.842 (Fig. 2). These findings were replicated in the replication dataset.ConclusionOur results showed that brain‐based TRS is associated with AD pathology and clinical course. Furthermore, TRS improves the AD classification performance of PRS. Along with static PRS, dynamic TRS based on transcriptional expression levels at a given time could be a potential disease‐stage specific AD biomarker.

Association Analysis of Common Structural Variants in the Alzheimer’s Disease Sequencing Project

AbstractBackgroundStructural variants (SV), genomic rearrangements of &gt;50 base pairs, are an important source of genetic variation and have a great impact on gene expression and protein function. However, their contribution to the genetic architecture of Alzheimer’s Disease (AD) has not been comprehensively investigated. Identification of SVs by short‐read alignment can be inaccurate and biased. We used a novel SV calling pipeline that leverages assembly‐based methods and graph‐based representation, to identify SVs with high accuracy in the diverse sample of the Alzheimer’s Disease Sequencing Project (ADSP). We further examined the association of common SVs with AD.MethodsWe applied Biograph for SV calling on the ADSP 17K whole genome sequence data. After filtering out low‐quality SVs and performing sample‐level quality control, we identified 222,956 deletions, 177,139 insertions, and 10,558 inversions in 12,908 individuals (6,304 AD cases; 6,604 controls). We performed association analyses of common SVs (MAF &gt; 1%) with AD using a logistic mixed‐effects model adjusting for sex, technical covariates, principal components, and relatedness. Statistical significance was evaluated using a Bonferroni‐corrected threshold (P&lt; 9.19.x10−7).ResultsThere were 28,634 deletions, 25,522 insertions, and 198 inversions with MAF &gt; 1%. We identified 2 intronic deletions significantly associated with AD. The first deletion is located in CCDC88B, encoding a protein that regulates T‐cell maturation and inflammation. The second deletion is located in CCDC11, predicted to be part of the spliceosomal complex. Among 11 insertions significantly associated with AD, 3 mapped to exonic sequences. A relatively common insertion located in an exon of FOXO6 showed the most significant association with AD (P = 1.41×10−12). FOXO6 is a member of Forkhead transcription factors that have been implicated in aging. Along with its high level of expression in the hippocampus, mice lacking FOXO6 had impaired memory consolidation. We identified one inversion suggestively associated with AD (P = 3.32×10−6) and located in an intron of PDE5A. PDE5A inhibitors have been reported as potential therapeutic targets for AD.ConclusionUsing novel data structures and algorithms to call SV, we discovered 14 SVs significantly associated with AD. Validation and gene prioritization of these findings are warranted.

Hypomethylation of a CpG Site in the CpG Island of the Aquaporin 1 Gene May Be Involved in the Formation of Adult-Onset Non-communicating Hydrocele Testis.

Background Water channel aquaporin 1 (AQP1) protein expression is enhanced in the tunica vaginalis of patients with adult-onset non-communicating hydrocele testis and may contribute to the development of non-communicating hydrocele testis. We performed genetic and epigenetic analyses of the AQP1 gene in the tunica vaginalis of patients with adult-onset non-communicating hydrocele testis to elucidate the cause of enhanced AQP1 protein expression. Methodology The genotype was determined for Tag single-nucleotide polymorphisms (SNPs) representing the AQP1 gene and SNPs in the 5'-upstream region of the AQP1 gene. Then, by performing association analysis, the applicability of various genetic models was investigated for each SNP. Moreover, the methylation rate of CpG sites was examined for the CpG island related to the AQP1 gene. Results There was no significant association between each SNP and hydrocele testis for any of the genetic models. The average methylation rate of the 17 CpG sites evaluated was not significantly different between controls and hydrocele testis, but the methylation rate was lower in hydrocele testis than in controls at one CpG site. Conclusions There was a significant decrease in the methylation rate at one of the CpG sites in the CpG island associated with the AQP1 gene in the tunica vaginalis of patients with non-communicating hydrocele testis. This may increase AQP1 protein expression and contribute to the formation of hydrocele testis. SNPs related to the AQP1 gene were not associated with hydrocele testis.

HLA-C*07:01 and HLA-DQB1*02:01 protect against white matter hyperintensities and deterioration of cognitive function: A population-based cohort study

BackgroundNeuroinflammation and aberrant immune regulation are increasingly implicated in the pathophysiology of white matter hyperintensities (WMH), an imaging marker of cerebrovascular pathologies and predictor of cognitive impairment. The role of human leukocyte antigen (HLA) genes, critical in immunoregulation and associated with susceptibility to neurodegenerative diseases, in WMH pathophysiology remains unexplored. MethodsWe performed association analyses between classical HLA alleles and WMH volume, derived from MRI scans of 38 302 participants in the UK Biobank. To identify independent functional alleles driving these associations, we conducted conditional forward stepwise regression and lasso regression. We further investigated whether these functional alleles showed consistent associations with WMH across subgroups characterized by varying levels of clinical determinants. Additionally, we validated the clinical relevance of the identified alleles by examining their association with cognitive function (n = 147 549) and dementia (n = 460 029) in a larger cohort. FindingsFour HLA alleles (DQB1*02:01, DRB1*03:01, C*07:01, and B*08:01) showed an association with reduced WMH volume after Bonferroni correction for multiple comparisons. Among these alleles, DQB1*02:01 exhibited the most significant association (β = −0.041, 95 % CI: −0.060 to −0.023, p = 1.04 × 10−5). Forward selection and lasso regression analyses indicated that DQB1*02:01 and C*07:01 primarily drove this association. The protective effect against WMH conferred by DQB1*02:01 and C*07:01 persisted in clinically relevant subgroups, with a stronger effect observed in older participants. Carrying DQB1*02:01 and C*07:01 was associated with higher cognitive function, but no association with dementia was found. InterpretationOur population-based findings support the involvement of immune-associated mechanisms, particularly both HLA class I and class II genes, in the pathogenesis of WMH and subsequent consequence of cognitive functions.