Alzheimer disease (AD), Frontotemporal lobar degeneration (FTD), Amyotrophic lateral sclerosis (ALS) and Parkinson disease (PD) have a certain degree of clinical, pathological and molecular overlap. Previous studies indicate that causative mutations in AD and FTD/ALS genes can be found in clinical familial AD. We examined the presence of causative and low frequency coding variants in the AD, FTD, ALS and PD Mendelian genes, in over 450 families with clinical history of AD and over 11,710 sporadic cases and cognitive normal participants from North America. Known pathogenic mutations were found in 1.05% of the sporadic cases, in 0.69% of the cognitively normal participants and in 4.22% of the families. A trend towards enrichment, albeit non-significant, was observed for most AD, FTD and PD genes. Only PSEN1 and PINK1 showed consistent association with AD cases when we used ExAC as the control population. These results suggest that current study designs may contain heterogeneity and contamination of the control population, and that current statistical methods for the discovery of novel genes with real pathogenic variants in complex late onset diseases may be inadequate or underpowered to identify genes carrying pathogenic mutations.
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http://dx.doi.org/10.1371/journal.pgen.1007045 | DOI Listing |
Int J Mol Sci
December 2024
Peking Union Medical College, Chinese Academy of Medical Science, Beijing 100010, China.
Osteoarthritis (OA), particularly in the knee and hip, poses a significant global health challenge due to limited therapeutic options. To elucidate the molecular mechanisms of OA and identify potential biomarkers and therapeutic targets, we utilized genome-wide association studies (GWAS) and cis-miRNA expression quantitative trait loci (cis-miR-eQTL) datasets to identify miRNAs associated with OA, revealing 16 that were linked to knee OA and 21 to hip OA. Among these, hsa-miR-1303 was significantly upregulated in both knee and hip OA (IVW: = 6.
View Article and Find Full Text PDFPlants (Basel)
January 2025
Hubei Key Laboratory of Vegetable Germplasm Enhancement and Genetic Improvement, Institute of Industrial Crops, Hubei Academy of Agricultural Sciences, Wuhan 430064, China.
The color of the rind is one of the most crucial agronomic characteristics of watermelon ( L.). Its genetic analysis was conducted to provide the identification of genes regulating rind color and improving the quality of watermelon appearance.
View Article and Find Full Text PDFAlzheimers Res Ther
January 2025
School of Medicine, South China University of Technology, Guangzhou, China.
Background: Epidemiological and genetic studies have elucidated associations between antihypertensive medication and Alzheimer's disease (AD), with the directionality of these associations varying upon the specific class of antihypertensive agents.
Methods: Genetic instruments for the expression of antihypertensive drug target genes were identified using expression quantitative trait loci (eQTL) in blood, which are associated with systolic blood pressure (SBP). Exposure was derived from existing eQTL data in blood from the eQTLGen consortium and in the brain from the PsychENCODE and subsequently replicated in GTEx V8 and BrainMeta V2.
Nat Genet
January 2025
Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK.
Gene expression quantitative trait loci are widely used to infer relationships between genes and central nervous system (CNS) phenotypes; however, the effect of brain disease on these inferences is unclear. Using 2,348,438 single-nuclei profiles from 391 disease-case and control brains, we report 13,939 genes whose expression correlated with genetic variation, of which 16.7-40.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Surgical Oncology II, The General Hospital of Ningxia Medical University, 804 Shengli Street, Yinchuan, Ningxia, 750004, China.
Non-small cell lung adenocarcinoma (LUAD) is a markedly heterogeneous disease, with its underlying molecular mechanisms and prognosis prediction presenting ongoing challenges. In this study, we integrated data from multiple public datasets, including TCGA, GSE31210, and GSE13213, encompassing a total of 867 tumor samples. By employing Mendelian randomization (MR) analysis, machine learning techniques, and comprehensive bioinformatics approaches, we conducted an in-depth investigation into the molecular characteristics, prognostic markers, and potential therapeutic targets of LUAD.
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