Siri N. Skodvin, Håkon K. Gjessing, Astanand Jugessur, Julia Romanowska, Alexandra Havdahl, Siri E. Håberg, Hans Ivar Hanevik, Robert Lyle, Rolv Terje Lie, Miriam Gjerdevik
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引用次数: 0
Abstract
Genetic selection occurs at different stages before a successful birth. The genetic makeup of a couple may influence the likelihood of needing assisted reproductive technology (ART) to achieve conception. However, frequent early fetal losses may also be perceived as reduced couple fertility and may thus be a contributing factor to the need for ART treatment. As ART procedures may enhance early fetal survival, genes that impact fetal viability may have a different allele distribution in ART offspring than expected under Mendelian transmission, as well as compared with the general population. With genetic data available from the Norwegian Mother, Father, and Child Cohort Study, we defined fetal survival as the study outcome and analyzed 1336 case-parent triads and dyads where the offspring were conceived by ART. Using log-linear models implemented in the R package Haplin, we conducted genome-wide scans to estimate fetal, maternal, and parent-of-origin effects and provided a detailed discussion on how these effects are estimated and interpreted. We detected fetal effects for single-nucleotide polymorphisms (SNPs) located in CXXC4-AS1, OPCML, and DYNLRB2-AS1. Since these effects were not observed in a limited follow-up analysis of non-ART triads, the identified effects are unlikely caused by genetic selection before fertilization.
期刊介绍:
Genetic Epidemiology is a peer-reviewed journal for discussion of research on the genetic causes of the distribution of human traits in families and populations. Emphasis is placed on the relative contribution of genetic and environmental factors to human disease as revealed by genetic, epidemiological, and biologic investigations.
Genetic Epidemiology primarily publishes papers in statistical genetics, a research field that is primarily concerned with development of statistical, bioinformatical, and computational models for analyzing genetic data. Incorporation of underlying biology and population genetics into conceptual models is favored. The Journal seeks original articles comprising either applied research or innovative statistical, mathematical, computational, or genomic methodologies that advance studies in genetic epidemiology. Other types of reports are encouraged, such as letters to the editor, topic reviews, and perspectives from other fields of research that will likely enrich the field of genetic epidemiology.