A transcriptome-wide association study identifies susceptibility genes for Parkinson's disease

Novel and experimental therapeutics for the management of motor and non-motor Parkinsonian symptoms

BACKGROUND  : Both motor and non-motor symptoms of Parkinson's disease (PD) have a substantial detrimental influence on the patient's quality of life. The most effective treatment remains oral levodopa. All currently known treatments just address the symptoms; they do not completely reverse the condition.

METHODOLOGY

In order to find literature on the creation of novel treatment agents and their efficacy for PD patients, we searched PubMed, Google Scholar, and other online libraries.

RESULTS

According to the most recent study on Parkinson's disease (PD), a great deal of work has been done in both the clinical and laboratory domains, and some current scientists have even been successful in developing novel therapies for PD patients.

CONCLUSION

The quality of life for PD patients has increased as a result of recent research, and numerous innovative medications are being developed for PD therapy. In the near future, we will see positive outcomes regarding PD treatment.

Transcriptomic imputation of genetic risk variants uncovers novel whole-blood biomarkers of Parkinson's disease

Blood-based gene expression signatures could potentially be used as biomarkers for PD. However, it is unclear whether genetically-regulated transcriptomic signatures can provide novel gene candidates for use as PD biomarkers. We leveraged on the Genotype-Tissue Expression (GTEx) database to impute whole-blood transcriptomic expression using summary statistics of three large-scale PD GWAS. A random forest classifier was used with the consensus whole-blood imputed gene signature (IGS) to discriminate between cases and controls. Outcome measures included Area under the Curve (AUC) of Receiver Operating Characteristic (ROC) Curve. We demonstrated that the IGS (n = 37 genes) is conserved across PD GWAS studies and brain tissues. IGS discriminated between cases and controls in an independent whole-blood RNA-sequencing study (1176 PD, 254 prodromal, and 860 healthy controls) with mean AUC and accuracy of 64.8% and 69.4% for PD cohort, and 78.8% and 74% for prodromal cohort. PATL2 was the top-performing imputed gene in both PD and prodromal PD cohorts, whose classifier performance varied with biological sex (higher performance for males and females in the PD and prodromal PD, respectively). Single-cell RNA-sequencing studies (scRNA-seq) of healthy humans and PD patients found PATL2 to be enriched in terminal effector CD8+ and cytotoxic CD4+ cells, whose proportions are both increased in PD patients. We demonstrated the utility of GWAS transcriptomic imputation in identifying novel whole-blood transcriptomic signatures which could be leveraged upon for PD biomarker derivation. We identified PATL2 as a potential biomarker in both clinical and prodromic PD.

Joint-tissue integrative analysis identifies high-risk genes for Parkinson's disease

The loss of dopaminergic neurons in the substantia nigra and the abnormal accumulation of synuclein proteins and neurotransmitters in Lewy bodies constitute the primary symptoms of Parkinson's disease (PD). Besides environmental factors, scholars are in the early stages of comprehending the genetic factors involved in the pathogenic mechanism of PD. Although genome-wide association studies (GWAS) have unveiled numerous genetic variants associated with PD, precisely pinpointing the causal variants remains challenging due to strong linkage disequilibrium (LD) among them. Addressing this issue, expression quantitative trait locus (eQTL) cohorts were employed in a transcriptome-wide association study (TWAS) to infer the genetic correlation between gene expression and a particular trait. Utilizing the TWAS theory alongside the enhanced Joint-Tissue Imputation (JTI) technique and Mendelian Randomization (MR) framework (MR-JTI), we identified a total of 159 PD-associated genes by amalgamating LD score, GTEx eQTL data, and GWAS summary statistic data from a substantial cohort. Subsequently, Fisher's exact test was conducted on these PD-associated genes using 5,152 differentially expressed genes sourced from 12 PD-related datasets. Ultimately, 29 highly credible PD-associated genes, including CTX1B, SCNA, and ARSA, were uncovered. Furthermore, GO and KEGG enrichment analyses indicated that these genes primarily function in tissue synthesis, regulation of neuron projection development, vesicle organization and transportation, and lysosomal impact. The potential PD-associated genes identified in this study not only offer fresh insights into the disease's pathophysiology but also suggest potential biomarkers for early disease detection.

Deciphering the molecular pathways underlying dopaminergic neuronal damage in Parkinson's disease associated with SARS-CoV-2 infection

BACKGROUND

The COVID-19 pandemic caused by SARS-CoV-2 has led to significant global morbidity and mortality, with potential neurological consequences, such as Parkinson's disease (PD). However, the underlying mechanisms remain elusive.

METHODS

To address this critical question, we conducted an in-depth transcriptome analysis of dopaminergic (DA) neurons in both COVID-19 and PD patients. We identified common pathways and differentially expressed genes (DEGs), performed enrichment analysis, constructed protein‒protein interaction networks and gene regulatory networks, and employed machine learning methods to develop disease diagnosis and progression prediction models. To further substantiate our findings, we performed validation of hub genes using a single-cell sequencing dataset encompassing DA neurons from PD patients, as well as transcriptome sequencing of DA neurons from a mouse model of MPTP(1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine)-induced PD. Furthermore, a drug-protein interaction network was also created.

RESULTS

We gained detailed insights into biological functions and signaling pathways, including ion transport and synaptic signaling pathways. CD38 was identified as a potential key biomarker. Disease diagnosis and progression prediction models were specifically tailored for PD. Molecular docking simulations and molecular dynamics simulations were employed to predict potential therapeutic drugs, revealing that genistein holds significant promise for exerting dual therapeutic effects on both PD and COVID-19.

CONCLUSIONS

Our study provides innovative strategies for advancing PD-related research and treatment in the context of the ongoing COVID-19 pandemic by elucidating the common pathogenesis between COVID-19 and PD in DA neurons.

Parkinson's disease risk enhancers in microglia

Genome-wide association studies have identified thousands of single nucleotide polymorphisms that associate with increased risk for Parkinson's disease (PD), but the functions of most of them are unknown. Using assay for transposase-accessible chromatin (ATAC) and H3K27ac chromatin immunoprecipitation (ChIP) sequencing data, we identified 73 regulatory elements in microglia that overlap PD risk SNPs. To determine the target genes of a "risk enhancer" within intron two of SNCA, we used CRISPR-Cas9 to delete the open chromatin region where two PD risk SNPs reside. The loss of the enhancer led to reduced expression of multiple genes including SNCA and the adjacent gene MMRN1. It also led to expression changes of genes involved in glucose metabolism, a process that is known to be altered in PD patients. Our work expands the role of SNCA in PD and provides a connection between PD-associated genetic variants and underlying biology that points to a risk mechanism in microglia.

Joint analysis of proteome, transcriptome, and multi-trait analysis to identify novel Parkinson's disease risk genes

Genome-wide association studies (GWAS) have identified multiple risk variants for Parkinson's disease (PD). Nevertheless, how the risk variants confer the risk of PD remains largely unknown. We conducted a proteome-wide association study (PWAS) and summary-data-based mendelian randomization (SMR) analysis by integrating PD GWAS with proteome and protein quantitative trait loci (pQTL) data from human brain, plasma and CSF. We also performed a large transcriptome-wide association study (TWAS) and Fine-mapping of causal gene sets (FOCUS), leveraging joint-tissue imputation (JTI) prediction models of 22 tissues to identify and prioritize putatively causal genes. We further conducted PWAS, SMR, TWAS, and FOCUS using a multi-trait analysis of GWAS (MTAG) to identify additional PD risk genes to boost statistical power. In this large-scale study, we identified 16 genes whose genetically regulated protein abundance levels were associated with Parkinson's disease risk. We undertook a large-scale analysis of PD and correlated traits, through TWAS and FOCUS studies, and discovered 26 casual genes related to PD that had not been reported in previous TWAS. 5 genes (CD38, GPNMB, RAB29, TMEM175, TTC19) showed significant associations with PD at both the proteome-wide and transcriptome-wide levels. Our study provides new insights into the etiology and underlying genetic architecture of PD.

A statistical method for image-mediated association studies discovers genes and pathways associated with four brain disorders

Brain imaging and genomics are critical tools enabling characterization of the genetic basis of brain disorders. However, imaging large cohorts is expensive and may be unavailable for legacy datasets used for genome-wide association studies (GWASs). Using an integrated feature selection/aggregation model, we developed an image-mediated association study (IMAS), which utilizes borrowed imaging/genomics data to conduct association mapping in legacy GWAS cohorts. By leveraging the UK Biobank image-derived phenotypes (IDPs), the IMAS discovered genetic bases underlying four neuropsychiatric disorders and verified them by analyzing annotations, pathways, and expression quantitative trait loci (eQTLs). A cerebellar-mediated mechanism was identified to be common to the four disorders. Simulations show that, if the goal is identifying genetic risk, our IMAS is more powerful than a hypothetical protocol in which the imaging results were available in the GWAS dataset. This implies the feasibility of reanalyzing legacy GWAS datasets without conducting additional imaging, yielding cost savings for integrated analysis of genetics and imaging.

Whole Blood-based Transcriptional Risk Score for Nonobese Type 2 Diabetes Predicts Dynamic Changes in Glucose Metabolism

CONTEXT

The performance of peripheral blood transcriptional markers in evaluating risk of type 2 diabetes (T2D) with normal body mass index (BMI) is unknown.

OBJECTIVE

We developed a whole blood-based transcriptional risk score (wb-TRS) for nonobese T2D and assessed its contributions on disease risk and dynamic changes in glucose metabolism.

METHODS

Using a community-based cohort with blood transcriptome data, we developed the wb-TRS in 1105 participants aged ≥40 years who maintained a normal BMI for up to 10 years, and we validated the wb-TRS in an external dataset. Potential biological significance was explored.

RESULTS

The wb-TRS included 144 gene transcripts. Compared to the lowest tertile, wb-TRS in tertile 3 was associated with 8.91-fold (95% CI, 3.53-22.5) higher risk and each 1-unit increment was associated with 2.63-fold (95% CI, 1.87-3.68) higher risk of nonobese T2D. Furthermore, baseline wb-TRS significantly associated with dynamic changes in average, daytime, nighttime, and 24-hour glucose, HbA1c values, and area under the curve of glucose measured by continuous glucose monitoring over 6 months of intervention. The wb-TRS improved the prediction performance for nonobese T2D, combined with fasting glucose, triglycerides, and demographic and anthropometric parameters. Multi-contrast gene set enrichment (Mitch) analysis implicated oxidative phosphorylation, mTORC1 signaling, and cholesterol metabolism involved in nonobese T2D pathogenesis.

CONCLUSION

A whole blood-based nonobese T2D-associated transcriptional risk score was validated to predict dynamic changes in glucose metabolism. These findings suggested several biological pathways involved in the pathogenesis of nonobese T2D.

Exploration of the molecular mechanism of insulin resistance in adipose tissue of patients with type 2 diabetes mellitus through a bioinformatic analysis

BACKGROUND

We aimed to determine the cis-expression Quantitative Trait Loci (cis-eQTL) and trans-eQTL of differentially expressed genes (DEGs) in insulin resistance (IR) related pathways.

METHODS

The expression profile data for insulin sensitivity (IS) and IR in the adipose tissue of patients with type 2 diabetes mellitus (T2DM) were acquired from the Gene Expression Omnibus databases. Then, the Gene set enrichment analysis (GSEA) and Gene set variation analysis (GSVA) methods were performed to identify the significant enrichment of potential Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways between IS and IR groups, and the Wilcoxon rank sum test was carried out to identify the DEGs related to KEGG pathways. Finally, the cis-eQTLs and trans-eQTLs that can affect the expression of DEGs were screened from the eQTLGen database.

RESULTS

The GSEA and GSVA analysis indicated that the mTOR signaling pathway, insulin signaling pathway and T2DM had a strong correlation with the pathological process of T2DM. Furthermore, six genes (ACACA, GYS2, PCK1, PRKAR1A, SLC2A4, and VEGFA) were found to be significantly differentially expressed in IR-related pathways. Finally, we have identified a total of 1073 cis-eQTLs and 24 trans-eQTLs.

CONCLUSIONS

We screened out six genes that were significantly differentially expressed in IR-related pathways, including ACACA, GYS2, PCK1, PRKAR1A, SLC2A4, and VEGFA. Moreover, we discovered that these six genes were affected by 1073 cis-eQTLs and 24 trans-eQTLs.

Ca2+ signalling: A common language for organelles crosstalk in Parkinson's disease

Parkinson's disease (PD) is a neurodegenerative disease caused by multifactorial pathogenic mechanisms. Familial PD is linked with genetic mutations in genes whose products are either associated with mitochondrial function or endo-lysosomal pathways. Of note, mitochondria are essential to sustain high energy demanding synaptic activity of neurons and alterations in mitochondrial Ca2+ signaling have been proposed as causal events for neurodegenerative process, although the mechanisms responsible for the selective loss of specific neuronal populations in the different neurodegenerative diseases is still not clear. Here, we specifically discuss the importance of a correct mitochondrial communication with the other organelles occurring at regions where their membranes become in close contact. We discuss the nature and the role of contact sites that mitochondria establish with ER, lysosomes, and peroxisomes, and how PD related proteins participate in the regulation/dysregulation of the tethering complexes. Unravelling molecular details of mitochondria tethering could contribute to identify specific therapeutic targets and develop new strategies to counteract the progression of the disease.

Expanding causal genes for Parkinson's disease via multi-omics analysis

Genome‑wide association studies (GWASs) have revealed numerous loci associated with Parkinson's disease (PD). However, some potential causal/risk genes were still not revealed and no etiological therapies are available. To find potential causal genes and explore genetically supported drug targets for PD is urgent. By integrating the expression quantitative trait loci (eQTL) and protein quantitative trait loci (pQTL) datasets from multiple tissues (blood, cerebrospinal fluid (CSF) and brain) and PD GWAS summary statistics, a pipeline combing Mendelian randomization (MR), Steiger filtering analysis, Bayesian colocalization, fine mapping, Protein-protein network and enrichment analysis were applied to identify potential causal genes for PD. As a result, GPNMB displayed a robust causal role for PD at the protein level in the blood, CSF and brain, and transcriptional level in the brain, while the protective role of CD38 (in brain pQTL and eQTL) was also identified. We also found inconsistent roles of DGKQ on PD between protein and mRNA levels. Another 9 proteins (CTSB, ARSA, SEC23IP, CD84, ENTPD1, FCGR2B, BAG3, SNCA, FCGR2A) were associated with the risk for PD based on only a single pQTL after multiple corrections. We also identified some proteins' interactions with known PD causative genes and therapeutic targets. In conclusion, this study suggested GPNMB, CD38, and DGKQ may act in the pathogenesis of PD, but whether the other proteins involved in PD needs more evidence. These findings would help to uncover the genes underlying PD and prioritize targets for future therapeutic interventions.

Identification of diagnostic and prognostic biomarkers of PD using a multiplex proteomics approach

Given the complexity of Parkinson's disease (PD), achieving acceptable diagnostic and prognostic accuracy will require the support of a panel of diverse biomarkers. We used Proximity extension assays to measure a panel of 92 proteins in CSF of 120 newly diagnosed PD patients and 45 control subjects without neurological disease. From 75 proteins detectable in the CSF of >90% of the subjects, regularized regression analysis identified four proteins (β-NGF, CD38, tau and NCAN) as downregulated in newly diagnosed PD patients (age at diagnosis 67.2 ± 9.4 years) compared to controls (age 65.4 ± 10.9 years). Higher tau (β -0.82 transformed MMSE points/year, 95% CI -1.37 to -0.27, P = 0.005) was also linked to faster cognitive decline over the first ten years after PD diagnosis. These findings provide insights into multiple aspects of PD pathophysiology and may serve as the foundation for identifying new biomarkers and therapeutic targets.

Analysis of subcellular RNA fractions demonstrates significant genetic regulation of gene expression in human brain post-transcriptionally

Gaining insight into the genetic regulation of gene expression in human brain is key to the interpretation of genome-wide association studies for major neurological and neuropsychiatric diseases. Expression quantitative trait loci (eQTL) analyses have largely been used to achieve this, providing valuable insights into the genetic regulation of steady-state RNA in human brain, but not distinguishing between molecular processes regulating transcription and stability. RNA quantification within cellular fractions can disentangle these processes in cell types and tissues which are challenging to model in vitro. We investigated the underlying molecular processes driving the genetic regulation of gene expression specific to a cellular fraction using allele-specific expression (ASE). Applying ASE analysis to genomic and transcriptomic data from paired nuclear and cytoplasmic fractions of anterior prefrontal cortex, cerebellar cortex and putamen tissues from 4 post-mortem neuropathologically-confirmed control human brains, we demonstrate that a significant proportion of genetic regulation of gene expression occurs post-transcriptionally in the cytoplasm, with genes undergoing this form of regulation more likely to be synaptic. These findings have implications for understanding the structure of gene expression regulation in human brain, and importantly the interpretation of rapidly growing single-nucleus brain RNA-sequencing and eQTL datasets, where cytoplasm-specific regulatory events could be missed.

Parkinson's Disease: A Tale of Many Players

In 2020, more than 9 million patients suffering from Parkinson's disease (PD) were reported worldwide, and studies predict that the burden of this disease will grow substantially in industrial countries. In the last decade, there has been a better understanding of this neurodegenerative disorder, clinically characterized by motor disturbances, impaired balance, coordination, memory difficulties, and behavioral changes. Various preclinical investigations and studies on human postmortem brains suggest that local oxidative stress and inflammation promote misfolding and aggregation of alpha-synuclein within Lewy bodies and cause nerve cell damage. Parallel to these investigations, the familial contribution to the disease became evident from studies on genome-wide association in which specific genetic defects were linked to neuritic alpha-synuclein pathology. As for treatment, currently available pharmacological and surgical interventions may improve the quality of life but do not stop the progress of neurodegeneration. However, numerous preclinical studies have provided insights into the pathogenesis of PD. Their results provide a solid base for clinical trials and further developments. In this review, we discuss the pathogenesis, the prospects, and challenges of synolytic therapy, CRISPR, gene editing, and gene- and cell-based therapy. We also throw light on the recent observation that targeted physiotherapy may help improve the gait and other motor impairments.

Identifying Biomarkers Using Support Vector Machine to Understand the Racial Disparity in Triple-Negative Breast Cancer

With the properties of aggressive cancer and heterogeneous tumor biology, triple-negative breast cancer (TNBC) is a type of breast cancer known for its poor clinical outcome. The lack of estrogen, progesterone, and human epidermal growth factor receptor in the tumors of TNBC leads to fewer treatment options in clinics. The incidence of TNBC is higher in African American (AA) women compared with European American (EA) women with worse clinical outcomes. The significant factors responsible for the racial disparity in TNBC are socioeconomic lifestyle and tumor biology. The current study considered the open-source gene expression data of triple-negative breast cancer samples' racial information. We implemented a state-of-the-art classification Support Vector Machine (SVM) method with a recurrent feature elimination approach to the gene expression data to identify significant biomarkers deregulated in AA women and EA women. We also included Spearman's rho and Ward's linkage method in our feature selection workflow. Our proposed method generates 24 features/genes that can classify the AA and EA samples 98% accurately. We also performed the Kaplan-Meier analysis and log-rank test on the 24 features/genes. We only discussed the correlation between deregulated expression and cancer progression with a poor survival rate of 2 genes, KLK10 and LRRC37A2, out of 24 genes. We believe that further improvement of our method with a higher number of RNA-seq gene expression data will more accurately provide insight into racial disparity in TNBC.

A Proteome-Wide Effect of PHF8 Knockdown on Cortical Neurons Shows Downregulation of Parkinson's Disease-Associated Protein Alpha-Synuclein and Its Interactors

Synaptic dysfunction may underlie the pathophysiology of Parkinson's disease (PD), a presently incurable condition characterized by motor and cognitive symptoms. Here, we used quantitative proteomics to study the role of PHD Finger Protein 8 (PHF8), a histone demethylating enzyme found to be mutated in X-linked intellectual disability and identified as a genetic marker of PD, in regulating the expression of PD-related synaptic plasticity proteins. Amongst the list of proteins found to be affected by PHF8 knockdown were Parkinson's-disease-associated SNCA (alpha synuclein) and PD-linked genes DNAJC6 (auxilin), SYNJ1 (synaptojanin 1), and the PD risk gene SH3GL2 (endophilin A1). Findings in this study show that depletion of PHF8 in cortical neurons affects the activity-induced expression of proteins involved in synaptic plasticity, synaptic structure, vesicular release and membrane trafficking, spanning the spectrum of pre-synaptic and post-synaptic transmission. Given that the depletion of even a single chromatin-modifying enzyme can affect synaptic protein expression in such a concerted manner, more in-depth studies will be needed to show whether such a mechanism can be exploited as a potential disease-modifying therapeutic drug target in PD.

An integrated strategy to identify COVID-19 causal genes and characteristics represented by LRRC37A2

Genome-wide association study (GWAS) could identify host genetic factors associated with coronavirus disease 2019 (COVID-19). The genes or functional DNA elements through which genetic factors affect COVID-19 remain uncharted. The expression quantitative trait locus (eQTL) provides a path to assess the correlation between genetic variations and gene expression. Here, we firstly annotated GWAS data to describe genetic effects, obtaining genome-wide mapped genes. Subsequently, the genetic mechanisms and characteristics of COVID-19 were investigated by an integrated strategy that included three GWAS-eQTL analysis approaches. It was found that 20 genes were significantly associated with immunity and neurological disorders, including prior and novel genes such as OAS3 and LRRC37A2. The findings were then replicated in single-cell datasets to explore the cell-specific expression of causal genes. Furthermore, associations between COVID-19 and neurological disorders were assessed as a causal relationship. Finally, the effects of causal protein-coding genes of COVID-19 were discussed using cell experiments. The results revealed some novel COVID-19-related genes to emphasize disease characteristics, offering a broader insight into the genetic architecture underlying the pathophysiology of COVID-19.

Mendelian Randomization Study Using Dopaminergic Neuron-Specific eQTL Nominates Potential Causal Genes for Parkinson's Disease

BACKGROUND

Large-scale genome-wide association studies (GWASs) have reported multiple risk variants for Parkinson's disease (PD). However, little is known about how these reported risk variants confer risk of PD.

OBJECTIVE

To nominate genes whose genetically regulated expression in dopaminergic neurons may have a causal role in PD.

METHODS

We conducted a two-sample Mendelian randomization (MR) study by integrating large-scale genome-wide associations and expression quantitative trait loci (eQTL) data from dopaminergic neurons.

RESULTS

MR analysis nominated 10 risk genes whose genetically regulated expression in dopaminergic neurons may have a causal role in PD. These MR significant genes include FAM200B, NDUFAF2, NUP42, SH3GL2, STX1B, CCDC189, KAT8, PRSS36, VAMP4, and ZSWIM7.

CONCLUSIONS

We report the first MR study of PD by using dopaminergic neuron-specific eQTL and nominate novel risk genes for PD. Further functional characterization of the nominated risk genes will provide mechanistic insights into PD pathogenesis and potential therapeutic targets. © 2022 International Parkinson and Movement Disorder Society.

The influence of 17q21.31 and APOE genetic ancestry on neurodegenerative disease risk

Advances in genomic research over the last two decades have greatly enhanced our knowledge concerning the genetic landscape and pathophysiological processes involved in multiple neurodegenerative diseases. However, current insights arise almost exclusively from studies on individuals of European ancestry. Despite this, studies have revealed that genetic variation differentially impacts risk for, and clinical presentation of neurodegenerative disease in non-European populations, conveying the importance of ancestry in predicting disease risk and understanding the biological mechanisms contributing to neurodegeneration. We review the genetic influence of two important disease-associated loci, 17q21.31 (the “MAPT locus”) and APOE, to neurodegenerative disease risk in non-European populations, touching on global population differences and evolutionary genetics by ancestry that may underlie some of these differences. We conclude there is a need to increase representation of non-European ancestry individuals in genome-wide association studies (GWAS) and biomarker analyses in order to help resolve existing disparities in understanding risk for, diagnosis of, and treatment for neurodegenerative diseases in diverse populations.

Oxidative stress and synaptic dysfunction in rodent models of Parkinson's disease

Parkinson's disease (PD) is a multifactorial disorder involving a complex interplay between a variety of genetic and environmental factors. In this scenario, mitochondrial impairment and oxidative stress are widely accepted as crucial neuropathogenic mechanisms, as also evidenced by the identification of PD-associated genes that are directly involved in mitochondrial function. The concept of mitochondrial dysfunction is closely linked to that of synaptic dysfunction. Indeed, compelling evidence supports the role of mitochondria in synaptic transmission and plasticity, although many aspects have not yet been fully elucidated. Here, we will provide a brief overview of the most relevant evidence obtained in different neurotoxin-based and genetic rodent models of PD, focusing on mitochondrial impairment and synaptopathy, an early central event preceding overt nigrostriatal neurodegeneration. The identification of early deficits occurring in PD pathogenesis is crucial in view of the development of potential disease-modifying therapeutic strategies.

A Novel Defined Super-Enhancer Associated Gene Signature to Predict Prognosis in Patients With Diffuse Large B-Cell Lymphoma

Background: Diffuse large B-cell lymphoma (DLBCL) is a genetically heterogeneous disease that can have profound differences in survival outcomes. A variety of powerful prognostic factors and models have been constructed; however, the development of more accurate prognosis prediction and targeted treatment for DLBCL still faces challenges. An explosion of research on super-enhancer (SE)–associated genes provide the possibility to use in prognostication for cancer patients. Here, we aimed to establish a novel effective prognostic model using SE-associated genes from DLBCL.

Methods: A total of 1,105 DLBCL patients from the Gene Expression Omnibus database were included in this study and were divided into a training set and a validation set. A total of 11 SE-associated genes (BCL2, SPAG16, PXK, BTG1, LRRC37A2, EXT1, TGFBR2, ANKRD12, MYCBP2, PAX5, and MYC) were initially screened and identified by the least absolute shrinkage and selection operator (Lasso) penalized Cox regression, univariate and multivariate Cox regression analysis. Finally, a risk score model based on these 11 genes was constructed.

Results: Kaplan–Meier (K–M) curves showed that the low-risk group appeared to have better clinical survival outcomes. The excellent performance of the model was determined via time-dependent receiver operating characteristic (ROC) curves. A nomogram based on the polygenic risk score was further established to promote reliable prognostic prediction. This study proposed that the SE-associated-gene risk signature can effectively predict the response to chemotherapy in DLBCL patients.

Conclusion: A novel and reliable SE-associated-gene signature that can effectively classify DLBCL patients into high-risk and low-risk groups in terms of overall survival was developed, which may assist clinicians in the treatment of DLBCL.

Molecular Quantitative Trait Locus Mapping in Human Complex Diseases

Mapping quantitative trait loci (QTLs) for molecular traits from chromatin to metabolites (i.e., xQTLs) provides insight into the locations and effect modes of genetic variants that influence these molecular phenotypes and the propagation of functional consequences of each variant. xQTL studies indirectly interrogate the functional landscape of the molecular basis of complex diseases, including the impact of non-coding regulatory variants, the tissue specificity of regulatory elements, and their contribution to disease by integrating with genome-wide association studies (GWAS). We summarize a variety of molecular xQTL studies in human tissues and cells. In addition, using the Alzheimer's Disease Sequencing Project (ADSP) as an example, we describe the ADSP xQTL project, a collaborative effort across the ADSP Functional Genomics Consortium (ADSP-FGC). The project's ultimate goal is a reference map of Alzheimer's-related QTLs using existing datasets from multiple omics layers to help us study the consequences of genetic variants identified in the ADSP. xQTL studies enable the identification of the causal genes and pathways in GWAS loci, which will likely aid in the discovery of novel biomarkers and therapeutic targets for complex diseases. © 2022 Wiley Periodicals LLC.

Longitudinal intronic RNA-Seq analysis of Parkinson's disease patients reveals disease-specific nascent transcription

Transcriptomic studies usually focus on either gene or exon-based annotations, and only limited experiments have reported changes in reads mapping to introns. The analysis of intronic reads allows the detection of nascent transcription that is not influenced by steady-state RNA levels and provides information on actively transcribed genes. Here, we describe substantial intronic transcriptional changes in Parkinson's disease (PD) patients compared to healthy controls (CO) at two different timepoints; at the time of diagnosis (BL) and three years later (V08). We used blood RNA-Seq data from the Parkinson's Progression Markers Initiative (PPMI) cohort and identified significantly changed transcription of intronic reads only in PD patients during this follow-up period. In CO subjects, only nine transcripts demonstrated differentially expressed introns between visits. However, in PD patients, 4873 transcripts had differentially expressed introns at visit V08 compared to BL, many of them in genes previously associated with neurodegenerative diseases, such as LRRK2, C9orf72, LGALS3, KANSL1AS1, and ALS2. In addition, at the time of diagnosis (BL visit), we identified 836 transcripts (e.g. SNCA, DNAJC19, PRRG4) and at visit V08, 2184 transcripts (e.g. PINK1, GBA, ALS2, PLEKHM1) with differential intronic expression specific to PD patients. In contrast, reads mapping to exonic regions demonstrated little variation indicating highly specific changes only in intronic transcription. Our study demonstrated that PD is characterized by substantial changes in the nascent transcription, and description of these changes could help to understand the molecular pathology underpinning this disease.

The CD38 glycohydrolase and the NAD sink: implications for pathological conditions

Nicotinamide adenine dinucleotide (NAD) acts as a cofactor in several oxidation-reduction (redox) reactions and is a substrate for a number of nonredox enzymes. NAD is fundamental to a variety of cellular processes including energy metabolism, cell signaling, and epigenetics. NAD homeostasis appears to be of paramount importance to health span and longevity, and its dysregulation is associated with multiple diseases. NAD metabolism is dynamic and maintained by synthesis and degradation. The enzyme CD38, one of the main NAD-consuming enzymes, is a key component of NAD homeostasis. The majority of CD38 is localized in the plasma membrane with its catalytic domain facing the extracellular environment, likely for the purpose of controlling systemic levels of NAD. Several cell types express CD38, but its expression predominates on endothelial cells and immune cells capable of infiltrating organs and tissues. Here we review potential roles of CD38 in health and disease and postulate ways in which CD38 dysregulation causes changes in NAD homeostasis and contributes to the pathophysiology of multiple conditions. Indeed, in animal models the development of infectious diseases, autoimmune disorders, fibrosis, metabolic diseases, and age-associated diseases including cancer, heart disease, and neurodegeneration are associated with altered CD38 enzymatic activity. Many of these conditions are modified in CD38-deficient mice or by blocking CD38 NADase activity. In diseases in which CD38 appears to play a role, CD38-dependent NAD decline is often a common denominator of pathophysiology. Thus, understanding dysregulation of NAD homeostasis by CD38 may open new avenues for the treatment of human diseases.

Multi-omic insights into Parkinson's Disease: From genetic associations to functional mechanisms

Genome-Wide Association Studies (GWAS) have elucidated the genetic components of Parkinson's Disease (PD). However, because the vast majority of GWAS association signals fall within non-coding regions, translating these results into an interpretable, mechanistic understanding of the disease etiology remains a major challenge in the field. In this review, we provide an overview of the approaches to prioritize putative causal variants and genes as well as summarise the primary findings of previous studies. We then discuss recent efforts to integrate multi-omics data to identify likely pathogenic cell types and biological pathways implicated in PD pathogenesis. We have compiled full summary statistics of cell-type, tissue, and phentoype enrichment analyses from multiple studies of PD GWAS and provided them in a standardized format as a resource for the research community (https://github.com/RajLabMSSM/PD_omics_review). Finally, we discuss the experimental, computational, and conceptual advances that will be necessary to fully elucidate the effects of functional variants and genes on cellular dysregulation and disease risk.