PubMed Health⌕ Search

PubMed · 12787814

Biological sample collection and processing for molecular epidemiological studies.

Abstract

Molecular epidemiology uses biomarkers and advanced technology to refine the investigation of the relationship between environmental exposures and diseases in humans. It requires careful handling and storage of precious biological samples with the goals of obtaining a large amount of information from limited samples, and minimizing future research costs by use of banked samples. Many factors, such as tissue type, time of collection, containers used, preservatives and other additives, transport means and length of transit time, affect the quality of the samples and the stability of biomarkers and must be considered at the initial collection stage. An efficient study design includes provisions for further processing of the original samples, such as cryopreservation of isolated cells, purification of DNA and RNA, and preparation of specimens for cytogenetic, immunological and biochemical analyses. Given the multiple uses of the samples in molecular epidemiology studies, appropriate informed consent must be obtained from the study subjects prior to sample collection. Use of barcoding and electronic databases allow more efficient management of large sample banks. Development of standard operating procedures and quality control plans is a safeguard of the samples' quality and of the validity of the analyses results. Finally, specific state, federal and international regulations are in place regarding research with human samples, governing areas including custody, safety of handling, and transport of human samples, as well as communication of study results.Here, we focus on the factors affecting the quality and the potential future use of biological samples and some of the provisions that must be made during collection, processing, and storage of samples, based on our experience in the Superfund Basic Research Program and Children's Environmental Health Center, at the University of California, Berkeley.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Nina T Holland, Martyn T Smith, Brenda Eskenazi, Maria Bastaki. 2003. Biological sample collection and processing for molecular epidemiological studies.. https://doi.org/10.1016/s1383-5742(02)00090-x

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans↗

Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.

CRISPR screens, such as expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq), enable the simultaneous measurement of transcriptomes, gRNA identity, and cell-surface protein expression at single-cell resolution to systematically interrogate gene function. This platform provides a powerful and scalable experimental approach for validating disease-associated regulators identified by large-scale association studies and other computational methods, including network-based analyses of multi-omics data. Here, as an example application, we describe an ECCITE-seq framework to characterize the transcriptomic consequences of perturbing multiple neuronal key driver genes associated with Alzheimer's disease (AD) in human-induced pluripotent stem cell (hiPSC)-derived neurons. More broadly, by integrating customized pooled gRNA libraries with different CRISPR effectors across multiple cell types, this approach allows for the assessment of the regulatory impact of candidate genes implicated in development and disease processes.

Humans↗

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans↗