Human Reproductive Genetics

Emerging Technologies and Clinical Applications

Juan A. Garcia-Velasco, Emre Seli

• Publisher: Academic Press
• Year: 2020
• Print ISBN:
  9780128165614
• eBook ISBN:
  9780128167496
• Topic: Medicine
• Subtopic: Endocrinology & Metabolism

Human Reproductive Genetics: Emerging Technologies and Clinical Applications presents a great reference for clinicians and researchers in reproductive medicine. Part I includes a brief background of genetics and epigenetics, probability of disease, and the different techniques that are being used today for analysis and genetic counseling. Part II focuses on the analysis of the embryo, current controversies and future concepts. Part III comprises different clinical scenarios that clinicians frequently face in practice. The increasing amount of genetic tests available and the growing information that patients handle makes this section a relevant part of the fertility treatment discussion. Finally, Part IV concludes with the psychological aspects of genetic counseling and the role of counselor and bioethics in human reproduction. - Provides an essential reference for clinicians involved in reproductive medicine - Builds foundational knowledge on new genetic tests coming into the clinical scenario for physicians involved with patients - Assembles critically evaluated chapters that cover basic concepts of genetics and epigenetics and the techniques involved, including preimplantation genetic testing, controversies, and more

B

Clinical scenarios

Outline

• Chapter 6 The quest for genetic sequence variants conferring risk of endometriosis
• Chapter 7 Genetics of polycystic ovarian syndrome
• Chapter 8 Male factor infertility: genetic and epigenetic aspects
• Chapter 9 Mitochondrial genetics
• Chapter 10 Endometrial receptivity and genetics
• Chapter 11 Genetics of premature ovarian insufficiency
• Chapter 12 Prenatal testing
• Chapter 13 Expanded carrier screening in reproductive medicine

Chapter 6

The quest for genetic sequence variants conferring risk of endometriosis

Sun-Wei Guo^{1, 2}, ¹Shanghai Obstetrics and Gynecology Hospital, Fudan University, Shanghai, P.R. China, ²Shanghai Key Laboratory of Female Reproductive Endocrine-Related Diseases, Fudan University, Shanghai, P.R. China

Abstract

In the last two decades, numerous genetic association studies, including genome-wide genetic association studies, aimed at identifying DNA variants conferring risk of endometriosis have been published, and many polymorphisms have been identified. However, each and every one of the identified polymorphisms invariably has a small, even minute, effect, explaining merely a minuscule percentage of the heritability. More disconcertingly, these publications have so far contributed little to our understanding of the pathogenesis or pathophysiology of endometriosis. As with many other complex diseases or traits, there has been a glaring gap between the estimated heritability of the disease and the disease risk variability that can be explained by the identified DNA variants, a phenomenon called “the missing heritability.” This chapter provides a primer on genetic studies of complex diseases such as endometriosis, explaining the methods for demonstration of genetic components for a disease, and methods to identify the genes or genetic variants. It also provides some explanations as to why a “missing heritability” problem also exists in endometriosis.

Keywords

Association studies; endometriosis; familial aggregation; genetic variant; heritability; pathogenesis; polymorphism

Introduction

Endometriosis, characterized by the presence and growth of functional endometrial-like tissues outside the uterine cavity, is an estrogen-dependent disorder affecting 6%–10% of reproductive-age women [1]. As a major contributor to pelvic pain and subfertility, endometriosis impacts negatively on women’s quality of life, work productivity, sexual relationships, and self-esteem, mainly because of chronic, debilitating pain and infertility [2–6]. Despite extensive research, its pathogenesis still remains an enigma [7].

Given this state, one simple, brute-force approach, that is, the genetic approach, is very appealing. One does not need to know anything about the molecular genetic mechanisms underlying endometriosis, but through the collection of pedigrees enriched with patients having the disease or large samples of unrelated patients and healthy women, one could use existing genetic signposts [called DNA markers, which are aplenty and scattered throughout the entire human genome with known locations, thanks to the Human Genome Project (HGP)] and localize the responsible gene in a particular chromosomal region(s). Once the gene(s) is(are) identified, one can hope to better understand the pathogenesis of endometriosis, dissect the phenotypic heterogeneity, and make a risk prediction [8]. This is of particular appeal since the entire genome sequence data of a person can be stored on a DVD disc or a flash drive, and, once all susceptibility genes are identified and their risks are quantified, her risk of developing endometriosis could be predicted once she is born.

There were indeed successful stories with the genetic approach. Huntington’s disease, for example, was once viewed as a difficult disease with unknown pathogenesis. Using the genetic approach, the gene for Huntington’s disease was identified and ultimately cloned [9]. Even for breast cancer, a fairly common cancer, one susceptibility gene was localized on chromosome 17 in 1990 [10] and later cloned [11]. These successes generated enormous enthusiasm in the use of the same genetic approach, with the hope that for many complex diseases such as diabetes, cardiovascular diseases, and endometriosis that invariably have an elusive pathogenesis and collectively contribute to the major health burdens, their pathogenesis could be unveiled by hunting down their susceptibility genes [12]. The simplicity of the study design, called a genetic association study (GAS), is also attractive: simply by comparison of the allelic frequency between women with endometriosis and those without, one can detect genes that confer risk of endometriosis.

This enthusiasm was bolstered even further with the completion of the HGP, which now allows to read the entire DNA sequence of a human genome, touted by many as the “Book of Life.” With the advent of high-throughput genotyping technologies, typing of DNA markers, especially the biallelic single-nucleotide polymorphisms (SNPs), has become cheaper and faster, making the scanning of the entire genome more feasible and easier. Such an approach, called a genome-wide GAS or genome-wide association study (GWAS), has gained enormous momentum since the HGP was officially completed in 2003 (Fig. 6.1).

Figure 6.1 Number of publications, indexed by PubMed, on genetic association studies (GASs) in general and on endometriosis from 1980 to 2018. The blue and red curves represent the GASs in general and on endometriosis, respectively. The y-axis on the left is for GAS-general, while the y-axis on the right is for endometriosis-specific GASs. The occurrences of several important events, such as the start of the Human Genome Project (HGP), are indicated.

In endometriosis, a deluge of GAS, including GWAS, papers attempting to find DNA variants that might be statistically associated with endometriosis have been published in the last two decades, reflecting the general interest in the use of a GAS/GWAS approach to finding genes for complex diseases (Fig. 6.1). However, despite an impressive list of publications and enormous effort, the quest for genetic variants, either germline mutations or polymorphisms, associated with endometriosis has so far borne little, if any, fruit. Frequently, when such associations have been found, the identified polymorphisms appear to be of little predictive value and contribute little to our understanding of the pathogenesis or pathophysiology of the disease. At best, the identified polymorphisms frequently provide tantalizing association with some genes with known functions that may or may not be directly involved in the pathogenesis of endometriosis.

In a recent review on the current status of GWASs on endometriosis, it is reported that the “GWAS SNPs associated with endometriosis to date explain less than 2% of disease risk variability” [8]. The most recent meta-analysis of 15 GWASs and a replication analysis, including 58,115 cases and 733,480 controls, found 27 loci, which collectively explained a paltry 2.2% of the disease risk variability [13]. These findings are in sharp contrast to the estimate that half of the widely quoted estimated 50% heritability (meaning, genetic components contribute to about 50% of endometriosis risk) is due to the common variants that can be captured by GWASs [14]. Some previous meta-analyses on the association of endometriosis and several genetic polymorphisms coding for dioxin detoxification enzymes and for sex steroid biosynthesis and their receptors found no evidence of any association [15–17].

Remarkably, endometriosis is not the only complex disease that has encountered such a problem. A 2012 study, for example, found that incorporating genetic information did not improve clinicians’ ability to predict disease risk for many common complex diseases such as breast cancer, type II diabetes, and rheumatoid arthritis [18]. More recently, an analysis of 32 highly relevant traits from five broad disease areas involving 13,436 subjects found that the variance explained by multi-SNP genetic risk scores (GRSs) accounted for a mere 11% of the common-SNP heritability of the 32 traits, indicat...

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright
• List of contributors
• About the editors
• Preface
• A: Fundamentals of genetics
• B: Clinical scenarios
• C: How to analyze an embryo
• D: Reproductive genetic counseling
• Index