Genome-Wide Analysis of Copy Number Variation in Latin American Parkinson's Disease Patients

Identification of 27 allele-specific regulatory variants in Parkinson's disease using a massively parallel reporter assay

Genome wide association studies (GWAS) have identified a number of genomic loci that are associated with Parkinson's disease (PD) risk. However, the majority of these variants lie in non-coding regions, and thus the mechanisms by which they influence disease development, and/or potential subtypes, remain largely elusive. To address this, we used a massively parallel reporter assay (MPRA) to screen the regulatory function of 5254 variants that have a known or putative connection to PD. We identified 138 loci with enhancer activity, of which 27 exhibited allele-specific regulatory activity in HEK293 cells. The identified regulatory variant(s) typically did not match the original tag variant within the PD associated locus, supporting the need for deeper exploration of these loci. The existence of allele specific transcriptional impacts within HEK293 cells, confirms that at least a subset of the PD associated regions mark functional gene regulatory elements. Future functional studies that confirm the putative targets of the empirically verified regulatory variants will be crucial for gaining a greater understanding of how gene regulatory network(s) modulate PD risk.

Genetic landscape of Parkinson's disease and related diseases in Luxembourg

Objectives

To explore the genetic architecture of PD in the Luxembourg Parkinson's Study including cohorts of healthy people and patients with Parkinson's disease (PD) and atypical parkinsonism (AP).

Methods

809 healthy controls, 680 PD and 103 AP were genotyped using the Neurochip array. We screened and validated rare single nucleotide variants (SNVs) and copy number variants (CNVs) within seven PD-causing genes (LRRK2, SNCA, VPS35, PRKN, PARK7, PINK1 and ATP13A2). Polygenic risk scores (PRSs) were generated using the latest genome-wide association study for PD. We then estimated the role of common variants in PD risk by applying gene-set-specific PRSs.

Results

We identified 60 rare SNVs in seven PD-causing genes, nine of which were pathogenic in LRRK2, PINK1 and PRKN. Eleven rare CNVs were detected in PRKN including seven duplications and four deletions. The majority of PRKN SNVs and CNVs carriers were heterozygous and not differentially distributed between cases and controls. The PRSs were significantly associated with PD and identified specific molecular pathways related to protein metabolism and signal transduction as drivers of PD risk.

Conclusion

We performed a comprehensive genetic characterization of the deep-phenotyped individuals of the Luxembourgish Parkinson's Study. Heterozygous SNVs and CNVs in PRKN were not associated with higher PD risk. In particular, we reported novel digenic variants in PD related genes and rare LRRK2 SNVs in AP patients. Our findings will help future studies to unravel the genetic complexity of PD.

The Landscape of Monogenic Parkinson's Disease in Populations of Non-European Ancestry: A Narrative Review

INTRODUCTION

There has been a bias in the existing literature on Parkinson's disease (PD) genetics as most studies involved patients of European ancestry, mostly in Europe and North America. Our target was to review published research data on the genetic profile of PD patients of non-European or mixed ancestry.

METHODS

We reviewed articles published during the 2000-2023 period, focusing on the genetic status of PD patients of non-European origin (Indian, East and Central Asian, Latin American, sub-Saharan African and Pacific islands).

RESULTS

There were substantial differences regarding monogenic PD forms between patients of European and non-European ancestry. The G2019S Leucine Rich Repeat Kinase 2 (LRRK2) mutation was rather scarce in non-European populations. In contrast, East Asian patients carried different mutations like p.I2020T, which is common in Japan. Parkin (PRKN) variants had a global distribution, being common in early-onset PD in Indians, in East Asians, and in early-onset Mexicans. Furthermore, they were occasionally present in Black African PD patients. PTEN-induced kinase 1 (PINK1) and PD protein 7 (DJ-1) variants were described in Indian, East Asian and Pacific Islands populations. Glucocerebrosidase gene variants (GBA1), which represent an important predisposing factor for PD, were found in East and Southeast Asian and Indian populations. Different GBA1 variants have been reported in Black African populations and Latin Americans.

CONCLUSIONS

Existing data reveal a pronounced heterogeneity in the genetic background of PD. A number of common variants in populations of European ancestry appeared to be absent or scarce in patients of diverse ethnic backgrounds. Large-scale studies that include genetic screening in African, Asian or Latin American populations are underway. The outcomes of such efforts will facilitate further clinical studies and will possibly contribute to the identification of either new pathogenic mutations in already described genes or novel PD-related genes.

Ethnicity and Parkinson's Disease: Motor and Nonmotor Features and Disease Progression in Latino Patients Living in Rural California

BACKGROUND

Parkinson's disease (PD) is the second most common neurodegenerative disorder among older adults worldwide. Currently, studies of PD progression rely primarily on White non-Latino (WNL) patients. Here, we compare clinical profiles and PD progression in Latino and WNL patients enrolled in a community-based study in rural Central California.

METHOD

PD patients within 5 years of diagnosis were identified from 3 counties between 2001 and 2015. During up to 3 visits, participants were examined by movement disorders specialists and interviewed. We analyzed cross-sectional differences in PD clinical features severity at each study visit and used linear mixed models and Cox proportional hazards models to compare motor, nonmotor, and disability progression longitudinally and to assess time to death in Latinos compared to WNL patients.

RESULTS

Of 775 patients included, 138 (18%) self-identified as Latino and presented with earlier age at diagnosis (63.6 vs 68.9) and death (78.6 vs 81.5) than WNL. Motor (hazard ratio [HR] = 1.17 [0.71, 1.94]) and nonmotor symptoms did not progress faster in Latino versus WNL patients after accounting for differences in baseline symptom severity. However, Latino patients progressed to disability stages according to Hoehn and Yahr faster than WNL (HR = 1.81 [1.11, 2.96]). Motor and nonmotor symptoms in Latino patients were also medically managed less well than in WNL.

CONCLUSIONS

Our PD study with a large proportion of Latino enrollees and progression data reveals disparities in clinical features and progression by ethnicity that may reflect healthcare access and structural socioeconomic disadvantages in Latino patients with PD.

Exome Sequencing and Multigene Panel Testing in 1,411 Patients With Adult-Onset Neurologic Disorders

Background and Objectives

Owing to their extensive clinical and molecular heterogeneity, hereditary neurologic diseases in adults are difficult to diagnose. The current knowledge about the diagnostic yield and clinical utility of exome sequencing (ES) for neurologic diseases in adults is limited. This observational study assesses the diagnostic value of ES and multigene panel analysis in adult-onset neurologic disorders.

Methods

From January 2019 through April 2022, ES-based multigene panel testing was conducted in 1,411 patients with molecularly unexplained neurologic phenotypes at the Ghent University Hospital. Gene panels were developed for ataxia and spasticity, leukoencephalopathy, movement disorders, paroxysmal episodic disorders, neurodegeneration with brain iron accumulation, progressive myoclonic epilepsy, and amyotrophic lateral sclerosis. Single nucleotide variants, small indels, and copy number variants were analyzed. Across all panels, our analysis covered a total of 725 genes associated with Mendelian inheritance.

Results

A molecular diagnosis was established in 10% of the cases (144 of 1,411) representing 71 different monogenic disorders. The diagnostic yield depended significantly on the presenting phenotype with the highest yield seen in patients with ataxia or spastic paraparesis (19%). Most of the established diagnoses comprised disorders with an autosomal dominant inheritance (62%), and the most frequently mutated genes were NOTCH3 (13 patients), SPG7 (11 patients), and RFC1 (8 patients). 34% of the disease-causing variants were novel, including a unique likely pathogenic variant in APP (Ghent mutation, p.[Asn698Asp]) in a family presenting with stroke and severe cerebral white matter disease. 7% of the pathogenic variants comprised copy number variants detected in the ES data and confirmed by an independent technique.

Discussion

ES and multigene panel testing is a powerful and efficient tool to diagnose patients with unexplained, adult-onset neurologic disorders.

Adaptive Savitzky–Golay Filters for Analysis of Copy Number Variation Peaks from Whole-Exome Sequencing Data

Copy number variation (CNV) is a form of structural variation in the human genome that provides medical insight into complex human diseases; while whole-genome sequencing is becoming more affordable, whole-exome sequencing (WES) remains an important tool in clinical diagnostics. Because of its discontinuous nature and unique characteristics of sparse target-enrichment-based WES data, the analysis and detection of CNV peaks remain difficult tasks. The Savitzky–Golay (SG) smoothing is well known as a fast and efficient smoothing method. However, no study has documented the use of this technique for CNV peak detection. It is well known that the effectiveness of the classical SG filter depends on the proper selection of the window length and polynomial degree, which should correspond with the scale of the peak because, in the case of peaks with a high rate of change, the effectiveness of the filter could be restricted. Based on the Savitzky–Golay algorithm, this paper introduces a novel adaptive method to smooth irregular peak distributions. The proposed method ensures high-precision noise reduction by dynamically modifying the results of the prior smoothing to automatically adjust parameters. Our method offers an additional feature extraction technique based on density and Euclidean distance. In comparison to classical Savitzky–Golay filtering and other peer filtering methods, the performance evaluation demonstrates that adaptive Savitzky–Golay filtering performs better. According to experimental results, our method effectively detects CNV peaks across all genomic segments for both short and long tags, with minimal peak height fidelity values (i.e., low estimation bias). As a result, we clearly demonstrate how well the adaptive Savitzky–Golay filtering method works and how its use in the detection of CNV peaks can complement the existing techniques used in CNV peak analysis.

Four-copy number alteration (CNA)-related lncRNA prognostic signature for liver cancer

The objective of this study was to identify CNA-related lncRNAs that can better evaluate the prognosis of patients with liver cancer. Prognostic molecular subtypes were identified, followed by tumor mutation and differential expression analyses. Genomic copy number anomalies and their association with lncRNAs were also evaluated. A risk model was built based on lncRNAs, as well as a nomogram, and the differences in the tumor immune microenvironment and drug sensitivity between the High_ and Low_risk groups were compared. Weighted gene co-expression network analysis was used to identify modules with significant enrichment in prognostic-related lncRNAs. In total, two subtypes were identified, TP53 and CTNNB1 were common high-frequency mutated genes in the two subtypes. A total of 8,372 differentially expressed (DE) mRNAs and 798 DElncRNAs were identified between cluster1 and cluster2. In addition, a four-lncRNA signature was constructed, and statistically significant differences between the Low_ and High_risk groups were found in terms of CD8 T cells, resting memory CD4 T cells, etc. Enrichment analysis showed that prognostic-related lncRNAs were involved in the cell cycle, p53 signaling pathway, non-alcoholic fatty liver disease, etc. A prognostic prediction signature, based on four-CNA-related lncRNAs, could contribute to a more accurate prognosis of patients with liver cancer.

Fully exploiting SNP arrays: a systematic review on the tools to extract underlying genomic structure

Single nucleotide polymorphisms (SNPs) are the most abundant type of genomic variation and the most accessible to genotype in large cohorts. However, they individually explain a small proportion of phenotypic differences between individuals. Ancestry, collective SNP effects, structural variants, somatic mutations or even differences in historic recombination can potentially explain a high percentage of genomic divergence. These genetic differences can be infrequent or laborious to characterize; however, many of them leave distinctive marks on the SNPs across the genome allowing their study in large population samples. Consequently, several methods have been developed over the last decade to detect and analyze different genomic structures using SNP arrays, to complement genome-wide association studies and determine the contribution of these structures to explain the phenotypic differences between individuals. We present an up-to-date collection of available bioinformatics tools that can be used to extract relevant genomic information from SNP array data including population structure and ancestry; polygenic risk scores; identity-by-descent fragments; linkage disequilibrium; heritability and structural variants such as inversions, copy number variants, genetic mosaicisms and recombination histories. From a systematic review of recently published applications of the methods, we describe the main characteristics of R packages, command-line tools and desktop applications, both free and commercial, to help make the most of a large amount of publicly available SNP data.

Clinical and Genetic Analysis of Costa Rican Patients With Parkinson's Disease

Background: Most research in genomics of Parkinson's disease (PD) has been done in subjects of European ancestry, leading to sampling bias and leaving Latin American populations underrepresented. We sought to clinically characterize PD patients of Costa Rican origin and to sequence familial PD and atypical parkinsonism-associated genes in cases and controls.

Methods: We enrolled 118 PD patients with 97 unrelated controls. Collected information included demographics, exposure to risk and protective factors, and motor and cognitive assessments. We sequenced coding and untranslated regions in familial PD and atypical parkinsonism-associated genes including GBA, SNCA, VPS35, LRRK2, GCH1, PRKN, PINK1, DJ-1, VPS13C, and ATP13A2.

Results: Mean age of PD probands was 62.12 ± 13.51 years; 57.6% were male. The frequency of risk and protective factors averaged ~45%. Physical activity significantly correlated with better motor performance despite years of disease. Increased years of education were significantly associated with better cognitive function, whereas hallucinations, falls, mood disorders, and coffee consumption correlated with worse cognitive performance. We did not identify an association between tested genes and PD or any damaging homozygous or compound heterozygous variants. Rare variants in LRRK2 were nominally associated with PD; six were located between amino acids p.1620 and 1623 in the C-terminal-of-ROC (COR) domain of Lrrk2. Non-synonymous GBA variants (p.T369M, p.N370S, and p.L444P) were identified in three healthy individuals. One PD patient carried a pathogenic GCH1 variant, p.K224R.

Discussion: This is the first study that describes sociodemographics, risk factors, clinical presentation, and genetics of Costa Rican patients with PD, adding information to genomics research in a Latino population.