Ecogeographic genetic epidemiology.

Genet Epidemiol

Computational Genetics Laboratory, Department of Genetics, Dartmouth Medical School, Lebanon, New Hampshire, USA.

Published: May 2009

Complex diseases such as cancer and heart disease result from interactions between an individual's genetics and environment, i.e. their human ecology. Rates of complex diseases have consistently demonstrated geographic patterns of incidence, or spatial "clusters" of increased incidence relative to the general population. Likewise, genetic subpopulations and environmental influences are not evenly distributed across space. Merging appropriate methods from genetic epidemiology, ecology and geography will provide a more complete understanding of the spatial interactions between genetics and environment that result in spatial patterning of disease rates. Geographic information systems (GIS), which are tools designed specifically for dealing with geographic data and performing spatial analyses to determine their relationship, are key to this kind of data integration. Here the authors introduce a new interdisciplinary paradigm, ecogeographic genetic epidemiology, which uses GIS and spatial statistical analyses to layer genetic subpopulation and environmental data with disease rates and thereby discern the complex gene-environment interactions which result in spatial patterns of incidence.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2672969PMC
http://dx.doi.org/10.1002/gepi.20386DOI Listing

Publication Analysis

Top Keywords

genetic epidemiology
12
ecogeographic genetic
8
complex diseases
8
genetics environment
8
patterns incidence
8
result spatial
8
disease rates
8
spatial
6
epidemiology complex
4
diseases cancer
4

Similar Publications

Introduction: China implemented a dynamic zero-COVID strategy to curb viral transmission in response to the coronavirus disease 2019 (COVID-19) pandemic. This strategy was designed to inhibit mutation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for COVID-19. This study explores the dynamics of viral evolution under stringent non-pharmaceutical interventions (NPIs) through real-world observations.

View Article and Find Full Text PDF

Blood-based epigenome-wide association study and prediction of alcohol consumption.

Clin Epigenetics

January 2025

Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.

Alcohol consumption is an important risk factor for multiple diseases. It is typically assessed via self-report, which is open to measurement error through recall bias. Instead, molecular data such as blood-based DNA methylation (DNAm) could be used to derive a more objective measure of alcohol consumption by incorporating information from cytosine-phosphate-guanine (CpG) sites known to be linked to the trait.

View Article and Find Full Text PDF

A cross-tissue transcriptome-wide association study identifies new susceptibility genes for benign prostatic hyperplasia.

Sci Rep

January 2025

Department of Urology, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, 730030, People's Republic of China.

Benign prostatic hyperplasia (BPH) is a prevalent urinary system disorder. Despite evidence of a significant genetic component from previous studies, the specific pathogenic genes and biological mechanisms are still largely unknown. The study utilized the FinnGen R10 dataset, encompassing 177,901 individuals (36,601 cases and 141,300 controls), and the GTEx v8 EQTLs files to conduct single-tissue and cross-tissue transcriptome-wide association studies (TWAS).

View Article and Find Full Text PDF

Genetic association of lipid-lowering drug target genes with pancreatic cancer: a Mendelian randomization study.

Sci Rep

January 2025

Division of Pancreatic Surgery, Department of General Surgery, Qilu Hospital, Shandong University, Jinan, 250012, China.

Previous studies have found that dyslipidemia is a risk factor for pancreatic cancer (PC), and that lipid-lowering drugs may reduce the risk of PC. However, it is not clear whether dyslipidemia causes PC. The Mendelian randomization (MR) study aimed to investigate the causal role of lipid traits in pancreatic cancer and to assess the potential impact of lipid-lowering drug targets on pancreatic cancer.

View Article and Find Full Text PDF

The aim of the study is to analyze the relationship between personality traits of women with hereditary predisposition to breast/ovarian cancer and their obstetric history and cancer-preventive behaviors. A total of 357 women, participants of 'The National Program for Families With Genetic/Familial High Risk for Cancer', were included in the study. The Neo Five-Factor Inventory (NEO-FFI) and a standardized original questionnaire designed for the purpose of the study were used.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!