A genetic and transcriptomic assessment of the KTN1 gene in Parkinson's disease risk.

Parkinson's disease (PD) is a progressive neurological disorder caused by both genetic and environmental factors. An association has been described between KTN1 genetic variants and changes in its expression in the putamen and substantia nigra brain regions and an increased risk for PD. Here, we examine the link between PD susceptibility and KTN1 using individual-level genotyping data and summary statistics from the most recent genome-wide association studies (GWAS) for PD risk and age at onset from the International Parkinson's Disease Genomics Consortium (IPDGC), as well as whole-genome sequencing data from the Accelerating Medicines Partnership Parkinson's disease (AMP-PD) initiative. To investigate the potential effect of changes in KTN1 expression on PD compared to unaffected individuals, we further assess publicly available expression quantitative trait loci (eQTL) results from GTEx v8 and BRAINEAC and transcriptomics data from AMP-PD. Overall, we found no genetic associations between KTN1 and PD in our cohorts but found potential evidence of differences in mRNA expression, which needs to be further explored.

A computational model of Pseudomonas syringae metabolism unveils a role for branched-chain amino acids in Arabidopsis leaf colonization.

Bacterial pathogens adapt their metabolism to the plant environment to successfully colonize their hosts. In our efforts to uncover the metabolic pathways that contribute to the colonization of Arabidopsis thaliana leaves by Pseudomonas syringae pv tomato DC3000 (Pst DC3000), we created iPst19, an ensemble of 100 genome-scale network reconstructions of Pst DC3000 metabolism. We developed a novel approach for gene essentiality screens, leveraging the predictive power of iPst19 to identify core and ancillary condition-specific essential genes. Constraining the metabolic flux of iPst19 with Pst DC3000 gene expression data obtained from naïve-infected or pre-immunized-infected plants, revealed changes in bacterial metabolism imposed by plant immunity. Machine learning analysis revealed that among other amino acids, branched-chain amino acids (BCAAs) metabolism significantly contributed to the overall metabolic status of each gene-expression-contextualized iPst19 simulation. These predictions were tested and confirmed experimentally. Pst DC3000 growth and gene expression analysis showed that BCAAs suppress virulence gene expression in vitro without affecting bacterial growth. In planta, however, an excess of BCAAs suppress the expression of virulence genes at the early stages of infection and significantly impair the colonization of Arabidopsis leaves. Our findings suggesting that BCAAs catabolism is necessary to express virulence and colonize the host. Overall, this study provides valuable insights into how plant immunity impacts Pst DC3000 metabolism, and how bacterial metabolism impacts the expression of virulence.

Cross-phenotype associations between Alzheimer's Disease and its comorbidities may provide clues to progression.

Alzheimer's disease (AD) is the most prevalent neurodegenerative disease worldwide, with one in nine people over the age of 65 living with the disease in 2023. In this study, we used a phenome wide association study (PheWAS) approach to identify cross-phenotype associations between previously identified genetic AD and for electronic health record (EHR) diagnoses from the UK Biobank (UKBB) (n=361,194 of European ancestry) and the eMERGE Network (n=105,108 of diverse ancestry). Based on 497 previously identified AD-associated variants from the Alzheimer's Disease Variant Portal (ADVP), we found significant associations primarily in immune and cardiac related diseases in our PheWAS. Replicating variants have widespread impacts on immune genes in diverse tissue types. This study demonstrates the potential of using the PheWAS strategy to improve our understanding of AD progression as well as identify potential drug repurposing opportunities for new treatment and disease prevention strategies.

Exploring the genetic and genomic connection underlying neurodegeneration with brain iron accumulation and the risk for Parkinson's disease.

Neurodegeneration with brain iron accumulation (NBIA) represents a group of neurodegenerative disorders characterized by abnormal iron accumulation in the brain. In Parkinson's Disease (PD), iron accumulation is a cardinal feature of degenerating regions in the brain and seems to be a key player in mechanisms that precipitate cell death. The aim of this study was to explore the genetic and genomic connection between NBIA and PD. We screened for known and rare pathogenic mutations in autosomal dominant and recessive genes linked to NBIA in a total of 4481 PD cases and 10,253 controls from the Accelerating Medicines Partnership Parkinsons' Disease Program and the UKBiobank. We examined whether a genetic burden of NBIA variants contributes to PD risk through single-gene, gene-set, and single-variant association analyses. In addition, we assessed publicly available expression quantitative trait loci (eQTL) data through Summary-based Mendelian Randomization and conducted transcriptomic analyses in blood of 1886 PD cases and 1285 controls. Out of 29 previously reported NBIA screened coding variants, four were associated with PD risk at a nominal p value < 0.05. No enrichment of heterozygous variants in NBIA-related genes risk was identified in PD cases versus controls. Burden analyses did not reveal a cumulative effect of rare NBIA genetic variation on PD risk. Transcriptomic analyses suggested that DCAF17 is differentially expressed in blood from PD cases and controls. Due to low mutation occurrence in the datasets and lack of replication, our analyses suggest that NBIA and PD may be separate molecular entities.

The IPDGC/GP2 Hackathon - an open science event for training in data science, genomics, and collaboration using Parkinson's disease data.

Open science and collaboration are necessary to facilitate the advancement of Parkinson's disease (PD) research. Hackathons are collaborative events that bring together people with different skill sets and backgrounds to generate resources and creative solutions to problems. These events can be used as training and networking opportunities, thus we coordinated a virtual 3-day hackathon event, during which 49 early-career scientists from 12 countries built tools and pipelines with a focus on PD. Resources were created with the goal of helping scientists accelerate their own research by having access to the necessary code and tools. Each team was allocated one of nine different projects, each with a different goal. These included developing post-genome-wide association studies (GWAS) analysis pipelines, downstream analysis of genetic variation pipelines, and various visualization tools. Hackathons are a valuable approach to inspire creative thinking, supplement training in data science, and foster collaborative scientific relationships, which are foundational practices for early-career researchers. The resources generated can be used to accelerate research on the genetics of PD.

Genome-Wide Analysis of Structural Variants in Parkinson Disease.

OBJECTIVE: Identification of genetic risk factors for Parkinson disease (PD) has to date been primarily limited to the study of single nucleotide variants, which only represent a small fraction of the genetic variation in the human genome. Consequently, causal variants for most PD risk are not known. Here we focused on structural variants (SVs), which represent a major source of genetic variation in the human genome. We aimed to discover SVs associated with PD risk by performing the first large-scale characterization of SVs in PD. METHODS: We leveraged a recently developed computational pipeline to detect and genotype SVs from 7,772 Illumina short-read whole genome sequencing samples. Using this set of SV variants, we performed a genome-wide association study using 2,585 cases and 2,779 controls and identified SVs associated with PD risk. Furthermore, to validate the presence of these variants, we generated a subset of matched whole-genome long-read sequencing data. RESULTS: We genotyped and tested 3,154 common SVs, representing over 412 million nucleotides of previously uncatalogued genetic variation. Using long-read sequencing data, we validated the presence of three novel deletion SVs that are associated with risk of PD from our initial association analysis, including a 2 kb intronic deletion within the gene LRRN4. INTERPRETATION: We identified three SVs associated with genetic risk of PD. This study represents the most comprehensive assessment of the contribution of SVs to the genetic risk of PD to date. ANN NEUROL 2023;93:1012-1022.

Assessment of ANG variants in Parkinson's disease.

Genetic risk factors are occasionally shared between different neurodegenerative diseases. Previous studies have linked ANG, a gene encoding angiogenin, to both Parkinson's disease (PD) and amyotrophic lateral sclerosis (ALS). Functional studies suggest ANG plays a neuroprotective role in both PD and amyotrophic lateral sclerosis by reducing cell death. We further explored the genetic association between ANG and PD by analyzing genotype data from the International Parkinson's Disease Genomics Consortium (14,671 cases and 17,667 controls) and whole genome sequencing data from the Accelerating Medicines Partnership - Parkinson's disease initiative (AMP-PD, https://amp-pd.org/) (1,647 cases and 1,050 controls). Our analysis did not replicate the findings of previous studies and identified no significant association between ANG variants and PD risk.

A SINE-VNTR-Alu in the LRIG2 Promoter Is Associated with Gene Expression at the Locus.

The hominid SINE-VNTR-Alu (SVA) retrotransposons represent a repertoire of genomic variation which could have significant effects on genome function. A human-specific SVA in the promoter region of the gene leucine-rich repeats and immunoglobulin-like domains 2 (LRIG2), which we termed SVA_LRIG2, is a common retrotransposon insertion polymorphism (RIP), defined as an element which is polymorphic for its presence or absence in the genome. We hypothesised that this RIP might be associated with differential levels of expression of LRIG2. The RIP genotype of SVA_LRIG2 was determined in a subset of frontal cortex DNA samples from the North American Brain Expression Consortium (NABEC) cohort and was imputed for a larger set of that cohort. Utilising available frontal cortex total RNA-seq and CpG methylation data for this cohort, we observed that increased allele dosage of SVA_LRIG2 was non-significantly associated with a decrease in transcription from the region and significantly associated with increased methylation of the CpG probe nearest to SVA_LRIG2, i.e., SVA_LRIG2 is a significant methylation quantitative trait loci (mQTL) at the LRIG2 locus. These data are consistent with SVA_LRIG2 being a transcriptional regulator, which in part may involve epigenetic modulation.

Groundwater microbial diversity and antibiotic resistance linked to human population density in Yucatan Peninsula, Mexico.

Microbial community composition in selected karst groundwater sites in the Yucatan Peninsula, Mexico, was assessed to determine the environmental variables influencing groundwater microbial diversity. The karst aquifer system is a groundwater-dependent ecosystem and is the world's second largest underwater karst cave system. The area's geology allows precipitation to infiltrate into the groundwater system and prevents accumulation of surface water; as such, groundwater is the only source of fresh water on the peninsula. The sampling locations consisted of three karst sinkholes that extend through the freshwater zone into the saline water, and an abandoned drinking water well of an ocean-side resort, during the dry and rainy seasons. The analysis showed that highly diverse microbial communities are present in the Yucatan groundwater, sustained by permanently warm temperatures and high nutrient input from human activity. Proximity to densely populated areas, such as tourist resorts, is the most important factor influencing both the diversity and presence of fecal bacteria and the antibiotic resistance profile.

Phylogenetic analyses of two mitochondrial metabolic genes sampled in parallel from angiosperms find fundamental interlocus incongruence.

Plant molecular phylogeneticists have supported an analytical approach of combining loci from different genomes, but the combination of mitochondrial sequences with chloroplast and nuclear sequences is potentially problematic. Low substitution rates in mitochondrial genes should decrease saturation, which is especially useful for the study of deep divergences. However, individual mitochondrial loci are insufficiently informative, so that combining congruent loci is necessary. For this study atp1 and cox1 were selected, which are of similar lengths, encode components of the respiratory pathway, and generally lack introns. Thus, these genes might be expected to have similar functional constraints, selection pressures, and evolutionary histories. Strictly parallel sampling of 52 species was achieved as well as six additional composite terminals with representatives from the major angiosperm clades. However, analyses of the separate loci produced strongly incongruent topologies. The source of the incongruence was investigated by validating sequences with questionable affinities, excluding RNA-edited nucleotides, deleting taxa with unexpected phylogenetic associations, and comparing different phylogenetic methods. However, even after potential artifacts were addressed and sites and taxa putatively associated with conflict were excluded, the resulting gene trees for the two mitochondrial loci were still substantially incongruent by all measures examined. Therefore, combining these loci in phylogenetic analysis may be counterproductive to the goal of fully resolving the angiosperm phylogeny.