Single-nucleotide polymorphisms (SNPs) constitute the bulk of human genetic variation and provide excellent markers to identify genetic factors contributing to complex disease susceptibility. A rapid, sensitive, and inexpensive assay is important for large-scale SNP scoring. Here we report the development of a multiplex SNP detection system using silicon chips coated to create a thin-film optical biosensor. Allele-discriminating, aldehyde-labeled oligonucleotides are arrayed and covalently attached to a hydrazinederivatized chip surface. Target sequences (e.g., PCR amplicons) then are hybridized in the presence of a mixture of biotinylated detector probes, one for each SNP, and a thermostable DNA ligase. After a stringent wash (0.01 M NaOH), ligation of biotinylated detector probes to perfectly matched capture oligomers is visualized as a color change on the chip surface (gold to blue/purple) after brief incubations with an anti-biotin IgG-horseradish peroxidase conjugate and a precipitable horseradish peroxidase substrate. Testing of PCR fragments is completed in 30-40 min. Up to several hundred SNPs can be assayed on a 36-mm2 chip, and SNP scoring can be done by eye or with a simple digital-camera system. This assay is extremely robust, exhibits high sensitivity and specificity, and is format-flexible and economical. In studies of mutations associated with risk for venous thrombosis and genotyping/haplotyping of African-American samples, we document high-fidelity analysis with 0 misassignments in 500 assays performed in duplicate.
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http://dx.doi.org/10.1073/pnas.1934783100 | DOI Listing |
Front Nutr
December 2024
The Wujin Clinical College of Xuzhou Medical University, Changzhou, Jiangsu, China.
Background: This study delves into the complex interplay between genetics, 25-hydroxyvitamin D (25OHD), and schizophrenia (SCZ). It leverages extensive sample data derived from Genome-Wide Association Studies (GWAS) to uncover genetic correlations.
Methods: Employing Linkage Disequilibrium Score Regression (LDSC) and S-LDSC, this study investigates genetic connections between 25OHD and SCZ.
Diabetol Metab Syndr
December 2024
Department of Neurosurgery, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou Province, People's Republic of China.
Objective: Obesity has been recognized as a risk factor for cerebrovascular diseases, with observational studies suggesting a heightened incidence of stroke. However, the genetic epidemiology field has yet to reach a consensus on the causal relationship and genetic overlap between ischemic stroke (IS) and obesity.
Methods: We utilized linkage disequilibrium score regression, high-definition likelihood, and local analysis of variant associations to assess the genetic correlation between body mass index (BMI) and IS.
Pain Manag Nurs
December 2024
College of Nursing, University of Florida, Gainesville, FL. Electronic address:
Purpose: The pain experience of patients with sickle cell disease (SCD) frequently consists of episodes of acute exacerbation. However, recent studies suggest that many patients who suffer from SCD have symptoms of chronic neuropathic pain. Additional research is needed to determine what role genotype plays in the patient's pain phenotype experience in SCD.
View Article and Find Full Text PDFNicotine Tob Res
December 2024
Institute for Behavioral Genetics, University of Colorado, Boulder.
Introduction: Pregnant individuals who smoke face increased health risks because smoking harms both the mother and their developing offspring.
Methods: Using 307 417 Europeans from the UK Biobank, we examined whether exposure to maternal smoking during pregnancy (MSP) interacts with genetic risk to predict offspring birth weight (BW) and smoking behaviors. We investigated interactions between MSP and genetic risk at multiple levels: single variant, gene-level, and polygenic score.
Neural Netw
December 2024
Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha 410083, PR China.
Correctly diagnosing Alzheimer's disease (AD) and identifying pathogenic brain regions and genes play a vital role in understanding the AD and developing effective prevention and treatment strategies. Recent works combine imaging and genetic data, and leverage the strengths of both modalities to achieve better classification results. In this work, we propose MCA-GCN, a Multi-stream Cross-Attention and Graph Convolutional Network-based classification method for AD patients.
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