Combining Human Genetics and Causal Inference to Understand Human Disease and Development

George Davey Smith

ISBN 10: 1621823814 / ISBN 13: 9781621823810

Editore: Cold Spring Harbor Laboratory Press Jan 2022, 2022

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Neuware - Written and edited by experts in the field, this collection examines advances in causal inference approaches in human genetics and how they are being used to enhance our understanding of human development and disease. The contributors discuss family-based study designs for causal inference, including twin designs, adoption designs, and in vitro fertilization designs, that separate inherited factors from perinatal environmental exposures. They also review various types of Mendelian randomization--a population-based approach that is growing in utility and popularity--as well as their integration with family-based designs.

Codice articolo 9781621823810

Dati bibliografici

• Titolo: Combining Human Genetics and Causal Inference to Understand Human Disease and Development
• Editore: Cold Spring Harbor Laboratory Press Jan 2022
• Data di pubblicazione: 2022
• Lingua: Inglese
• ISBN 10: 1621823814
• ISBN 13: 9781621823810
• Rilegatura: Buch
• Condizione: Neu
• Dimensioni: 257 L x 178 A x 20 P (millimetri) 257 millimetri di larghezza per 178 millimetri di altezza per 20 millimetri di profondità
• Peso: 748 grammi

Descrizione articolo

Riassunto

In human genetics, causal inference methods leverage large omics data sets and phenotypic information to decipher various cause-and-effect relationships in human health and disease (e.g., smoking and lung cancer). The focus of such work is typically on modifiable variables (e.g., behavior or environmental exposure) that impact disease onset, progression, and outcome. A better understanding of these variables can lead to interventions and therapeutics that have a desirable impact on public health.

Written and edited by experts in the field, this collection from Cold Spring Harbor Perspectives in Medicine examines advances in causal inference approaches in human genetics and how they are being used to enhance our understanding of human development and disease. The contributors discuss family-based study designs for causal inference, including twin designs, adoption designs, and in vitro fertilization designs, that separate inherited factors from perinatal environmental exposures. They also review various types of Mendelian randomization—a population-based approach that is growing in utility and popularity—as well as their integration with family-based designs.

The use of these approaches to investigate causal mechanisms in specific scenarios (e.g., maternal smoking during pregnancy and ADHD in offspring) is also covered. This volume is therefore an essential read for geneticists, epidemiologists, and all biomedical scientists and public health professionals dedicated to using genetic information to improve human health.