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Editors' comment : Case reports describing familial clustering of eclampsia were first reported in the late 1800s, but Chesley was one of the first to perform a true genetic analysis. Chesley's first edition text summarized his early investigations in hundreds of mother–daughter pairs. He reported that among daughters of women with eclampsia, 26% had preeclampsia in their first pregnancies. By contrast, the daughters-in-law control group had only an 8% rate of first-pregnancy preeclampsia. This comprehensively updated chapter will “fast-forward” the reader into the postgenomic era. As molecular analyses become less expensive and bioinformatic tools become more powerful, we are gaining new appreciation for the complexity of the etiologies, management strategies, and prevention of this syndrome.
Preeclampsia is a complex familial disorder, and multiple genes in multiple biological pathways are likely to impact causation, progression, and severity of the disease. Various types of genetic studies have been published including family reports, twin studies, segregation analyses, linkage analyses, association studies, and next-generation sequencing studies. For at least a decade, association studies comprised most of the literature on the genetics of preeclampsia, because these studies typically only considered a few preselected genes at a time and utilized fewer than 500 human subjects, most were insufficient for advancing the research. Genome-wide studies have become a more important approach in preeclampsia genetic research. Multicenter efforts are needed to account for clinical and pathologic subsets, and high-dimensional systems biology methods need to be employed so that these studies can account for preeclampsia's heterogeneity. New directions in research could lead to a greater understanding of preeclampsia's primary pathophysiology and the development of genetic screening and diagnostic tests and appropriate treatments and therapies.
Current interest in the genetics of preeclampsia can be traced back to the signal study of Leon Chesley, who single-handedly followed the remote course of 267 women who survived eclampsia during the years 1931–51. He postulated that in the absence of a renal biopsy, a convulsion—especially in a primiparous hypertensive patient—was the most convincing clinical evidence that diagnosis of preeclampsia was correct. The eclamptic probands that Dr. Chesley identified were interviewed and reexamined periodically, the data from some participants spanning more than 40 years after their affected pregnancy. In the course of his evaluations, Dr. Chesley noted the increased occurrence of preeclampsia–eclampsia within families. His observations and his reviews of other data that suggested familial factors are involved in the etiology of preeclampsia caught the fancy of genetic investigators. With the advent of molecular genetics, the mapping of the human genome, and the dramatic decrease in the cost of genome sequencing, this field is advancing rapidly. This chapter, dedicated to the pioneering studies of Leon Chesley, summarizes research into the genetics of preeclampsia through 2020. A glossary of genetics terminology is provided for readers who are less familiar with genetic concepts.
Preeclampsia and eclampsia a
a Throughout the rest of this chapter, preeclampsia will be the word used when the discussion could refer to either preeclampsia or eclampsia. Distinctions will be made between the two conditions as necessary.
are familial, as genetic research on these conditions over the last century has shown. Due to monumental improvements in neonatal care and decreased mortality rates of newborns over the last 50 years, generational trends can now be observed: eclamptic or preeclamptic mothers, aunts, and grandmothers have had female descendants who show an increased risk of preeclampsia over the general population. Preeclampsia tends to cluster in families; a heritability study using a Utah genealogy database determined the coefficient of kinship for preeclampsia cases to be more than 30 standard deviations higher than for controls (and unpublished data). The recurrence risk for preeclampsia in the daughters of either eclamptic or preeclamptic mothers is in the 20%–40% range. For sisters, it is in the 11%–37% range. Much lower rates are seen in relatives by marriage, such as daughters in-law and mothers in-law. Mothers with African American ancestry at all socioeconomic levels experience a higher rate of preeclampsia than the general population in the United States; whether this is due to genetic factors or factors such a racism is unclear. And finally, twin studies estimate that approximately 22%–47% of preeclampsia risk is heritable, as opposed to environmentally influenced. ,
While the ultimate causes of preeclampsia remain unknown, it is perhaps obvious that genes should play a role. As discussed in other chapters of this book, preeclampsia occurs when placental ischemia or inflammation causes various mediators to be released directly into the maternal circulation. The maternal endothelium and arterioles respond initially in an adaptive manner, but ultimately cause profound dysfunction of various major organs. Any number of disorders with a genetic component might interfere with maternal vascular responses, affect trophoblast function, or increase placental mass, causing fetal demands to outpace the supply. Every ligand, every receptor, every amplification cascade, every aspect of the programmed responses that orchestrate the pathophysiological response are under the control of either the mother's or the fetus' genes.
Geneticists finally have the technology and genomic data to find practical clinical solutions for the genetic testing, prevention, and treatment of preeclampsia. The completion of the Human Genome Project has enabled researchers to investigate the genetic causes of diseases both rare and common, and new technologies and statistical models are able to detect increasingly subtle variations within the human genome, gene effects on physiology, and their interactions with environmental factors.
Why is it important to understand that preeclampsia has a strong genetic component? While modern genetics may seem complicated to the uninitiated, our genome is actually quite approachable. The diploid human genome contains approximately 6.4 GB of sequence information spelled out with a “four-letter” chemical alphabet. Genetic variations associated with a high risk of preeclampsia are discrete markers, present at all stages of the disease progression, and they are inexpensive to assay. Genotyping can be used to distinguish subgroups with similar underlying predispositions, but more importantly, genotypes can be used to integrate longitudinal observations. Millions of humans have now undergone exome or even whole genome sequencing in various studies, and “human knockouts” with gene deletions or truncating mutations and patients carrying major pathogenic mutations can be studied longitudinally using both hypothesis-based and “omic” discovery approaches. Through understanding these predispositions, important clinical predictions can be made. Patients can be counseled about their risks for their current and future pregnancies, management and treatments may be customized, and at-risk family members may be counseled as well. Any mutation that has a major effect on the development of preeclampsia may point to a “molecular Achille's heel” where treatments are more likely to be efficacious. However, any mutation with a major negative effect on reproduction is selected out in the next generations. The occurrence of novel mutations in each generation explains why mutations with major negative effects on reproduction continue to occur.
Studies conducted over the last decade suggest that the genetic contributions to preeclampsia are likely to be complex, involving non-Mendelian transmission and numerous variants, gene–gene interactions, and environmental variables. The genes involved may not directly cause preeclampsia but rather they could lower a woman's biological threshold at which she would develop the condition.
Indeed, as noted throughout this chapter, preeclampsia is best understood as a multifactorial, polygenic condition. In a Mendelian disease (e.g., cystic fibrosis), an allelic variant or mutation is directly involved in causing the disease, and penetrance is complete or nearly complete for the relatively few persons in the population with that disease genotype. By contrast, complex diseases are the result of numerous common variants, usually at multiple loci, which contribute varying degrees to a person's susceptibility to that disease. Because of environmental and other variables, genotype alone may not result in phenotypic manifestation of the disease, but it will increase disease susceptibility and risk. , These polygenic multifactorial conditions are familial, usually affecting multiple generations, but their inheritance does not follow Mendelian ratios. Polygenic disease occurs under diverse environmental conditions, and the genes underlying the disease can show highly variable expression usually resulting in a continuum of phenotypes with patients above some threshold classified as having the disease.
Genetic background plays a critical role in polygenic inheritance since several factors must collaborate to cause a bodily function to go awry, and only after these factors reach some critical point is the phenotypic effect seen. Thus, recurrence risk of a polygenic multifactorial disease is higher within populations with a high incidence of the disorder. In disorders with a relatively high heritability, the recurrence risk of the disorder approximates the square root of the population incidence. Marked variation in the incidence and expression may occur in different ethnic groups. Within families, the greater the number of family members who have already been affected with a multifactorial condition, the more likely it is that the genetic background is favorable for expression of this condition. Consanguinity also increases the risk because of the greater likelihood of deleterious genes being shared. The severity of the disorder often correlates with the recurrence risk.
In the case of preeclampsia, the relative importance of each environmental risk factor varies among women, depending on their genotype. One woman may have a genotype that requires an accumulation of several environmental variables to exceed this threshold. Another woman may have no identifiable environmental risk factors but may have prepregnancy diabetes, which may result in an extremely low, easily exceeded preeclampsia threshold. Polygenic risk scores (PRSs) for preeclampsia have potential to improve risk stratification, but their potential to predict preeclampsia subtypes is unknown.
Since the diagnostic criteria of preeclampsia force arbitrary thresholds on the continuous distributions of blood pressure and proteinuria, or in the absence of proteinuria preeclampsia related signs of organ dysfunction and/or intrauterine growth restriction, , it is likely that no single etiology or genetic marker will account for all cases of preeclampsia. Given the clinical heterogeneity of the condition, it is all the more important to first correctly classify preeclampsia cases into subtypes, based on apparent etiology. This concept is stressed in Chapter 4, Chapter 20 in the current edition of this text.
Table 3.1 summarizes many of the genetic terms you will find in this chapter.
Term | Definition |
---|---|
Allele | The DNA sequence on a single DNA strand at a particular genetic locus; at each locus, a single allele is inherited separately from each parent. |
Base pair (bp) | Two nucleotides on opposite complementary DNA or RNA strands that are connected via hydrogen bonds. The human genome is composed of approximately 3 billion base pairs. Another unit frequently used is the kilobase (kb) , which denotes 1000 base pairs. |
Candidate gene | A gene researched and suspected of being involved in a particular trait or disease. Frequently identified in gene expression or genetic association studies. |
Coefficient of kinship | The probability that a gene at a given locus, picked at random from each of two individuals, will be identical due to familial relationship. |
Complex disease | A complex disease is caused by the interaction of multiple genes and environmental factors. |
Epigenesis | Environment-induced variations in the expression or operation of a functional gene even though the underlying genomic code is stable and unchanging. |
Epistasis | Interaction between or among nonallelic genes in which one combination of such genes has a dominant effect over other combinations (for instance, when one gene suppresses the expression of another) |
Exon | Only about 1% of our genome is the “genes,” which are “translated” into the proteins. The roughly 22,000 human genes are divided into 180,000 functional segments referred to as exons. |
Exome | The portion of the genome (the 180,000 exons) that codes for proteins. Presently, over two thirds of the DNA errors known to cause genetic disorders occur in the exome. |
Family clustering | The repeated occurrence of a phenotype in a given family. Often detected in genetic family studies conducted for this purpose. |
Fine-mapping | The determination of the sequence of nucleotides and their relative distances from one another in a specific region or locus of the genome. |
Founder effect | The loss of genetic variation that occurs when a relatively small number of individuals establish a new colony distinct from their original, larger population. As a result of the loss of genetic variation, the new population may be genetically and phenotypically different from the parent population but have relatively low genetic variation within itself. It may show increased sensitivity to genetic drift and an increase in inbreeding. |
Gene expression | The process by which gene-coded information is converted into structural proteins and enzymes. Expressed genes are transcribed into mRNA, which in turn is translated into protein, or they are transcribed into RNA that does not translate into protein (e.g., transfer, noncoding and ribosomal RNAs). |
Genetic association | The hypothesis that a given candidate gene or SNP causes or is otherwise related to a particular genetic condition, based on the differences in single-locus alleles or genotype frequency between a case group (with the genetic condition) and a control group (without the genetic condition). |
Genetic drift | The evolutionary process of change in allele frequencies that occurs entirely from chance, from one generation to the next. |
Genetic imprinting | Epigenetic differences in gene expression based off the parent of origin of the gene. There are over 225 imprinted genes in humans. |
Genomic | Of or relating to the entire genome, which in humans comprises 23 chromosome pairs, or 3.2 billion DNA base pairs. |
Genotype | The specific allele makeup of an individual, usually referring to one or more particular alleles being studied. |
gnom AD | The “genome aggregation database” is an example of a next generation sequencing database which collects and harmonizes data from large scale exome and genome sequencing projects. |
GWAS | Genome wide association study- a discovery approach, widely used in recent genetics research, in which genetic variations (genotypes) across the genomes of many cases and controls are assayed in order to find genetic variants associated with a disease or trait (phenotypes) |
Haplotype | (1) Two or more alleles or SNPs at distinct loci on one chromosome that are transmitted together. (2) A set of SNPs on a single chromatid that is statistically associated. |
Heritability | The proportion of phenotypic variation in a population that is attributable to genetic variation among individuals. |
Heterogeneity | Allelic heterogeneity occurs when different variants at a single gene locus cause the same or similar phenotypic expressions of a disease or condition. Locus heterogeneity occurs when variants at different gene loci cause the same or similar phenotypic expressions of a disease or condition. |
Heterozygous | When, of the two possible alleles at a given locus on homologous chromosomes, one of each allele is present. |
Human genome project | A 13-year research project completed in 2003 and coordinated by the US Department of Energy and the National Institutes of Health with contributions from numerous industrial nations. It identified all genes in the human genome (approximately 23,000) and determined the sequence of the 3-billion nucleotide base pairs that make up human DNA. It also developed infrastructure for the storage of this data and its future analysis, which is expected to continue in the private sector for many years. |
Immunogenetic | (1) The genetic basis of susceptibility to immune response and disease. (2) The relationship between immunity to disease and genetic makeup. |
Linkage | Occurs when particular genetic loci on a chromosome, or alleles, are inherited jointly due to their close proximity to one another. It is measured by the percentage recombination between loci (unlinked genes showing 50% recombination). A linkage analysis studies this phenomenon in the context of candidate genes and markers. |
Linkage disequilibrium (LD) | The occurrence of some alleles at two or more loci (like linkage, though not necessarily on the same chromosome) more or less often than would be expected, presumably because the combination confers some selective (evolutionary) advantage or disadvantage, respectively. Nonrandom associations between polymorphisms at different loci are measured by the degree of LD and can be demonstrated with haplotype analysis. |
Locus (plural is loci) | The position on a chromosome of a gene or other marker; also, the DNA at that position. The meaning of locus is sometimes restricted to regions of DNA that are expressed (see Gene expression ). |
Logarithm of the odds (LOD) score | A measure of the likelihood of two loci being within a measurable distance of each other. |
Marker | An identifiable physical location on the genome, the inheritance of which can be monitored. Markers can be expressed regions of DNA (genes), a restriction enzyme cutting site, or some segment of DNA with no known coding function but with a distinguishable inheritance pattern. Markers must be linked with a clear-cut phenotype; they are used as a point of reference when mapping new variants. |
Micro RNA (miRNA) | A noncoding RNA of about 22 nucleotides in length that play important role in regulation of gene expression |
Multifactorial | A disease or condition influenced in its expression by many factors, both genetic and environmental. |
Mutation | Any heritable, permanent change in DNA sequence; also, the process by which genes undergo a structural change. |
Next generation sequencing | DNA sequencing is the process of determining the order of the four nucleotide bases—adenine, guanine, cytosine, and thymine—in a strand of DNA. Next generation sequencing uses high-throughput, automated methods to sequence hundreds of thousands of sequences in parallel so that an entire human genome can be sequenced in a day |
Nucleotide | One of the monomeric units from which DNA or RNA polymers are constructed; it consists of a purine or pyrimidine base, a pentose sugar, and a phosphoric acid group. |
Omnigenic disorder | A newer concept suggesting that human regulatory networks are so interconnected that thousands of gene variants may contribute (at least slightly) to a complex disease phenotype through expression in relevant cells. |
Pedigree | A diagram of the relationships within a given family with symbols to represent people and lines to represent genetic relationships. Often used to determine the mode of inheritance (dominant, recessive, etc.) of genetic diseases. |
Penetrance | The extent to which individuals who carry the gene for a particular genetic condition express that gene as an expected phenotype. Penetrance may be described as complete, incomplete, low, or high, or may be quantitatively expressed as a percentage. |
Polygenic disorder | A genetic disorder resulting from the combined action of alleles of more than one gene (e.g., heart disease, diabetes, and some cancers). Although such disorders are inherited, they depend on the simultaneous presence of several alleles; thus the hereditary patterns are usually more complex than those of single-gene disorders. Also referred to as complex disorders . |
Polygenic risk score | Risk calculated based on variation in multiple genes and their associated statistical weights. |
Polymorphism | Genetic differences in the DNA sequence that naturally occur among individuals. A genetic variation that occurs in more than 1% of a population would be considered a useful polymorphism for genetic linkage analysis. |
Population admixture | The unwitting inclusion of members of a genetic population different from the genetic population being studied, having been selected to increase genetic homogeneity. It has the potential to give false-positive results in studies of genes underlying complex traits or to mask, change, or even reverse true genetic effects. |
Predisposition | An increased likelihood of, or an advanced tendency toward, a specific medical condition. |
Promoter | A site on DNA to which RNA polymerase will bind and initiate transcription; classically 5′ to its coding region. |
Quantitative trait loci (QTL) | Stretches of DNA that are closely linked to the gene(s) that underlie the trait in question, though they are not necessarily genes themselves. Can be molecularly identified to help map regions of the genome that contain genes involved in specifying a quantitative trait. |
Race/Ethnicity | Indicators of evolutionary ancestral geographic origin (by continent, in the broadest terms) that can be detected via certain markers on a person's genome. In population genetics, these distinctions are useful in increasing the homogeneity of a population for detection of differences between diseased and control subjects. |
Recessive | A gene that is phenotypically manifest in the homozygous state but is masked in the presence of a dominant allele. |
Recombination | The process by which offspring derive a specific combination of genes different from that of either parent. |
Recurrence risk | The chance that a genetic disease present in a family will recur in that family and affect another person (or persons). |
Segregation analysis | Statistical test to determine pattern of genetic inheritance for a trait or genetic condition (e.g., Mendelian, dominant autosomal, epistatic, polygenic, age-dependent). |
Single-nucleotide polymorphism (SNP) | A common (occurring in more than 1% of the population), single base substitution in the DNA sequence that may or may not cause a difference in gene expression (called functional or nonfunctional, respectively). Functional SNPs include: (1) SNPs in coding regions of genes resulting in amino acid substitutions (nonsynonymous SNPs), which may in turn alter protein sequence, structure, function, or interaction; enzyme stability; catalytic activity; and/or substrate specificity; (2) SNPs in the noncoding, regulatory regions of genes that affect the genes' transcription, translation, regulation, or mRNA stability (synonymous SNPs); (3) SNPs in genes that are duplicated, resulting in higher product levels; (4) SNPs in genes that are completely or partially deleted, resulting in no product; (5) SNPs that cause splice site variants that result in truncated or alternatively spliced protein products. Also look up promoter , enhancer , repressor , regulator , intron , exon , codon , deletion , duplication , insertion , inversion , translocation , and copy number variant (CNV) . |
Single-gene disorder | Hereditary disorder caused by a mutant allele of a single gene (e.g., cystic fibrosis, myotonic dystrophy, sickle cell disease). |
Subtype | One of two or more genetic pathways to the same disease phenotype. A disease may be defined by clinical characteristics, but once its genetic contributions are discovered, that same disease may be separated into subtypes based on which genes contribute to which type. This classification may or may not lead to refinements in the definition of the phenotype and/or clinical characteristics. |
Wellcome Trust Case Control Consortium | A collaboration of 24 human geneticists who analyzed over 19,000 DNA samples from patients suffering from different complex diseases to identify common genetic variations for each condition. Conditions included tuberculosis, coronary heart disease, type 1 diabetes, type 2 diabetes, rheumatoid arthritis, Crohn's disease, bipolar disorder, and hypertension. Two thousand patients were recruited for each disease, and 3000 were recruited as controls. The research was conducted at a number of institutes throughout the UK. |
Preeclampsia is a challenging phenotype to study using genetic methodologies. Although preeclampsia may be a more homogeneous entity when it is defined by glomerular endotheliosis in a first pregnancy—the characteristic histopathologic feature of the condition—we are forced to depend on other criteria for probing the genetic aspects of the condition. Diagnostic signs are nonspecific. The diagnostic blood pressure and proteinuria criteria in common use are, in fact, arbitrary cutoffs along a continuous distribution of values. The situation has not changed when using the new diagnostic criteria recognizing preeclampsia in the absence of proteinuria when the signs of organ dysfunction and/or intrauterine growth restriction are present in a hypertensive woman. , Even if perfect diagnostic criteria existed, there is an ongoing debate concerning the proper phenotype for study, whether it is proteinuric hypertension, gestational hypertension, a placental phenotype such as reduced trophoblast invasion, a renal phenotype such as glomerular endotheliosis, or other phenotypes. Up to one-third of infants born of preeclamptic pregnancies are affected by intrauterine growth restriction, and this subset may have different genetic variants involved. Some have argued that early-onset disease needs to be considered a different subtype. Genetic information on comorbidities related to diabetes, thrombophilia, renal disease, autoimmunity, etc., might allow more optimal classification. Gray et al., have reported that increased burden of risk alleles for elevated diastolic blood pressure and increased body mass index increases the risk of preeclampsia. Other non-genetic research into preeclampsia suggests that its essential pathophysiology comprises oxidative stress and endothelial decompensation originating from and/or contributing to poor placental perfusion, which cumulatively lead to the observable cascade of symptoms characteristic of the disease.
A major lesson of modern genetics is that syndromes defined on the basis of clustering of clinical symptoms often reveal marked heterogeneity until they are better understood at a molecular level. In this respect, the boundaries around preeclampsia, gestational hypertension, and HELLP syndrome are likely to be redrawn once genetic determinants can be examined directly.
Despite its appearance only in pregnancy, research in the last decade has suggested that preeclampsia has a systemic pathophysiology involving distinct yet diverse biological pathways in both the fetus and the mother. , Any of these pathways—including immunologic, inflammatory, hypoxic, and thrombophilic pathways—can push inadequate placentation or pregnancy-induced hypertension over the threshold into preeclampsia, and all of these pathways are influenced by the biological products of genetic expression and genotype. As in all genetic studies of pregnancy disorders, not just one but two genotypes must be considered: the genotype of the fetus as well as the mother.
Any genetic hypothesis of preeclampsia must explain the first pregnancy effect. It is widely known that most women will not have preeclampsia with future pregnancies unless another condition exists (e.g., underlying renal disease, twins, diabetes). This observation suggested an immunologic mechanism to many investigators, in the form of desensitization or tolerance to paternal antigens in subsequent gestations. An increased risk in first pregnancies with new partners (i.e., primipaternity with new paternal antigens presented in the placenta) has also been noted. Limited evidence exists that couples who use condoms for contraception, who undergo ovum donation, or who have a shorter length of cohabitation prior to conception have an increased risk of preeclampsia; couples that practice oral sex and women who have had multiple blood transfusions have a lower risk. Other explanations for the first pregnancy phenomenon must also be considered, however: certain enzymes in pregnancy are permanently induced and never go back to baseline levels after delivery. , Similarly, permanent changes occur in maternal blood volume and in the vascular architecture of the uterus after a term gestation, so that a greater volume expansion is generally achieved with subsequent pregnancies at later parities.
While increased compared to normotensive deliveries, remote essential hypertension in first pregnancy preeclamptic women is surprisingly low and may hold a clue as to why preeclamptic patients do not have a particularly high rate of developing essential hypertension. If, for example, the AGT T235 polymorphism increases the risk for both preeclampsia and essential hypertension through a blood volume mechanism, sustained changes in baseline blood volumes that occur after delivery might explain both the first pregnancy effect and possible reduction in an affected woman's lifelong risk of essential hypertension.
There have been numerous reports of circumstantial evidence of a paternal/fetal genetic effect. , , Astin et al. reported a man who lost two consecutive wives to eclampsia and had a severely preeclamptic third wife. Early-onset preeclampsia is extremely common in molar pregnancies (in which all the fetal chromosomes are derived from the father). Triploidy, although unusual in advanced gestations, frequently presents with preeclampsia. The increase in paternal genetic material associated with the triploid diandric placenta may support the role of paternal genes in the development of preeclampsia. Complete hydatidiform moles, which have two sets of paternal chromosomes, commonly cause a preeclampsia-like illness.
The InterPregGen consortium consortium has reported the first genome-wide association study (GWAS) of offspring from preeclamptic pregnancies and discovery of the first genome-wide significant susceptibility locus near the fms-related tyrosine kinase gene (FLT1) encoding fms-like tyrosine kinase 1 implicated in preeclampsia. FLT1 is located on chromosome 13. Increased risk of preeclampsia has been observed in women carrying trisomy 13 fetus. The extra copy of this gene in trisomy 13 may lead to excess circulating soluble, an antiangiogenic factor implicated in preeclampsia. This mechanism is discussed extensively in Chapter 9 .
In Chesley's segregation analyses mentioned above, Cooper found an increased rate of preeclampsia if the proband's own mother was eclamptic with their pregnancy. , Others have investigated a small increase in the incidence of preeclampsia in the daughters in-law of women who had pregnancy-induced hypertension.
Males presumably do not manifest a phenotype when they carry preeclampsia susceptibility genes; however, few studies have been done on paternal carriers. Considering that for most of human history, eclampsia was a common but frequently fatal disease for mother or child or both, a large percentage of modern cases must be due to new mutations without a direct familial pattern. Recent studies have suggested that de novo mutations are predominantly of paternal origin and that their number increases with advanced paternal age.
The placenta clearly plays an early and important role in many pregnancies impacted by preeclampsia. Placenta pathologies may cause more human morbidity and mortality than any other organ; the placenta is second only to the brain in the number of expressed genes; yet despite the relative availability of human specimens, our understanding of placental physiology lags far behind that for other organs. The maternal serum usually has measurable changes early in the course of preeclampsia, but is the clinical syndrome usually initiated in the maternal heart, brain, or some other organ or even the fetus? It is estimated that one-third of our genome is normally only active during pregnancy. Usually, placental genes implicated human pregnancy disorders have unknown and evolutionarily divergent functions when compared to animal models. Compared with other somatic tissues, the placenta has unique epigenetic profiles that dictate gene expression. Differences in global DNA methylation, a common epigenetic mechanism, between preeclamptic and control placentae, have been reported, but a high degree of heterogeneity exists among the studies. , Many placental genes are subject to genomic imprinting leading to monoallelic gene expression that depends on the parent of origin. Genomic imprinting is proposed to be a mechanism regulating allocation of maternal resources (nutrition, oxygen, blood flow, etc.) influencing fetal growth. Several micro-RNA clusters on human imprinted regions regulating expression of target genes are differentially expressed in preeclamptic placenta.
In many cases of preeclampsia, the uteroplacental circulation is not sufficient to nourish the fetus due to impaired placentation. For successful placentation in early pregnancy invading cytotrophoblast must avoid activation of the maternal immune system. Loss of maternal tolerance due to immunogenetic factors at this critical stage may lead to increased complement ( C ) activation observed in the maternal–fetal interface in preeclampsia. , As an example, in a case-control study, three SNPs within the C3 locus were associated with preeclampsia with severe features. Later in pregnancy when syncytiotrophoblasts are shedding to the maternal circulation, activation or insufficient regulation of the complement system may induce sterile inflammation of the placenta, and immune processes may exacerbate systemic endothelial dysfunction. Several links between complement activation and increased levels of antiangiogenic sFLT1, a hallmark of clinical preeclampsia, have been proposed (see mini-review Lokki et al. 2017). Interestingly, sFLT also has an antiinflammatory function and increased levels may be a compensatory attempt to regulate the maternal inflammatory response.
A normal pregnancy is accompanied by a pregnancy-specific, immunomodulated inflammatory response to the antigenic stimulus presented by the fetal–placental semiallograft. The largest surface area of contact between maternal immunocompetent T cells and the fetus is at the level of the villous trophoblasts. These cells originate in the embryo and lack expression of major histocompatibility complex (MHC) class I and class II antigens. The extravillous trophoblasts (EVT) only express human leukocyte antigens (HLA) -C (weakly), -Ib, -G, -F, and -E, rather than the strong transplantation antigens HLA-A, -B, -D, -Ia, and -II. Of these, only HLA-C is signaling paternal (foreign) alloantigens. , There is new evidence that maternal immune cells cross the placenta, colonize fetal lymph nodes, and remain to tolerize fetal T regulatory cells until early adulthood. Other inflammatory factors in preeclampsia are an abnormal immunological maternal response, comprising a change in the role of monocytes and natural killer (NK) cells for the release of circulating cytokines and an activation of proinflammatory angiotensin II subtype 1 (AT1) receptors. The significance of these receptors is discussed further in Chapter 15 by LaMarca, Dechend, and Davidge. Activated neutrophils, monocytes, and NK cells initiate inflammation, which in turn induces endothelial dysfunction, if activated T cells support inadequate tolerance during pregnancy. ,
In preeclampsia, genetic or nongenetic factors such as hypoxia or oxidative stress can induce necrosis or aponecrosis of trophoblasts. Macrophages or dendritic cells that phagocytose these trophoblasts produce type 1 cytokines such as tumor necrosis factor alpha (TNFα), interleukin (IL)-1, IL-12, and IFN-γ that augment inflammation, , such that the cytokine profile in preeclampsia, in contrast to that of normal pregnancy, is one of type 1 proinflammatory cytokines dominance, while the production of type 2 immunomodulatory cytokines is suppressed. This is supported by studies reporting elevated plasma levels of TNFα and IL-1β in preeclampsia. Furthermore, if type 2 regulatory cytokines are reduced, system-wide regulatory T cell function can be inhibited. ,
Redman and Sargent argue that the immunological interaction between the mother and fetus might be mediated predominantly by NK cells instead of T cells (this point is emphasized in Chapter 7). For example, the invading trophoblasts predominantly encounter maternal decidual lymphocytes that are NK cells with an unusual phenotype. Notably, the NK cells express receptors (such as killer immunoglobulin-like receptors, or KIRs) that recognize the exact combination of HLAs associated with invasive cytotrophoblasts, particularly polymorphic HLA-C. These NK cells express a unique array KIRs for binding the combinations of HLAs expressed by intermingling cytotrophoblast and NK cells that mediate immune recognition.
Numerous haplotypes, differing in gene content and allele combinations, are associated with the multigene killer cell KIRs. Some haplotypes inhibit NK-cell function (cytokine production in these cells), whereas others are stimulatory, depending on both the KIR phenotype of the NK cells and the HLA-C phenotype of the stimulating cells. KIR gene haplotypes can be divided into two functional groups: the simpler A group codes mainly for inhibitory KIR, and the more complex B group codes for receptors that stimulate NK cells. Preeclampsia is much more prevalent in women homozygous for the inhibitory KIR haplotypes (AA) than in women homozygous for the stimulator KIR BB. The effect is strongest if the fetus is homozygous for the HLA-C2 haplotype.
Essentially, normal placentation is more likely, and preeclampsia is less likely when trophoblasts strongly simulate uterine (maternal) NK cells. This interaction between trophoblasts and NK cells serves as an essential component of immunity suppression/stimulation issues in normal and abnormal pregnancies, specifically in preeclampsia. , ,
Recent data suggest that balancing selection at the fetal HLA-G locus modulates fetal survival, preeclampsia, and birth sex ratio. An evolutionary trade-off between immune tolerance and protection against infections at the maternal–fetal interface may promote genetic diversity in fetal HLA-G.
There is evidence for increased release of syncytiotrophoblast microvesicles and other cellular “debris” into the maternal plasma that also influence immune stimulation, cytokine production, and vascular remodeling. , The ability of the mother to mount an adequate response to these released prooxidant molecules may be of key importance for oxygen supply throughout pregnancy. This view is endorsed by the increased risk of preeclampsia in women with preexisting medical conditions that frequently lead to oxidative stress, including chronic hypertension, diabetes, and renal disease. Furthermore, long-term follow-up studies have shown that women who were unaffected by these conditions prior to conception are nevertheless more likely to develop them later in life following an episode of preeclampsia, as reviewed further in Chapters 4, 7, and 8 . It is now well known that chronic hypertension and diabetes have a genetic component, which raises the possibility that preeclampsia shares susceptibility genes with these conditions, particularly related to oxidative stress.
The first hints that preeclampsia is a genetic disease came from reports of familial clustering. Elliott was the first to report familial incidence of eclampsia in 1873. He reported a woman who died of eclampsia during her fifth pregnancy. Three of her four daughters subsequently died of eclampsia as well. Chesley's own remarkable study was well underway in the 1960s, when he reported data on the pregnancies of the daughters, daughters in-law, and sisters of the eclamptic probands, in whom he observed a relative risk of eightfold for eclampsia in the daughters. Remarkably persistent in this effort, Dr. Chesley was able to find information on 96% of all the daughters, greatly reducing the possibility of ascertainment bias. At the time of his death, he was preparing to publish additional data on the granddaughters and granddaughters-in-law of the original cohort.
Another large body of information comes from the Aberdeen Maternity Hospital in Scotland. Research teams headed by Adams, Cooper, and Sutherland studied this population in 1961, 1979, and 1981, respectively. These studies were unique because of consistent diagnostic criteria and classification and careful recording of births through several decades. Arngrimsson studied the Icelandic population. Because of the population's small size and interest in genealogy, as well as the concentration of maternity records at only one hospital, relatively complete information was available on the relatives of the index cases with preeclampsia. Daughters had a prevalence of preeclampsia or eclampsia of 23%, whereas those syndromes occurred in just 10% of the daughters-in-law.
Alexander notes that both male and female children of preeclamptic mothers are at an increased risk of having or fathering a preeclamptic pregnancy in turn, providing evidence of fetal contribution to preeclampsia susceptibility. However, according to pedigrees and heritability studies, this susceptibility remains greater in female than in male offspring, suggesting that transmission from mother to daughter is a critical component.
Table 3.2 lists various reports of familial preeclampsia.
Author(s) Ref | Year | Focus of Study |
---|---|---|
Adams and Finlayson | 1961 | Disease of preeclampsia, sisters of preeclamptic women |
Chesley et al. | 1968 | Pregnancies of daughters and granddaughters of eclamptics compared to daughters and granddaughters “in-law” |
Cooper and Liston | 1979 | “Severe” preeclampsia |
Arngrimsson et al. | 1990 | Increased rate of preeclampsia in mothers and daughters of preeclamptic women |
Esplin et al. | 2001 | Utah database: Both men and women who were born to a mother with preeclampsia were significantly more likely to have a child who was the product of a pregnancy complicated by preeclampsia. |
Cnattingius et al. | 2004 | Swedish registries. Heritability estimated at 0.55, maternal genes contribute more than fetal genes. |
Alexander et al. | 2007 | Mother–fetus pairs, including male transmission |
Once there are indications that a disorder is genetic, twin studies can be used to measure the heritability of the condition (the proportion of preeclampsia risk that is attributable to genetics, as opposed to environmental factors). Several studies wholly or partially dedicated to this question regarding preeclampsia have been conducted. , , , , Using twin concordance to estimate heritability is never a straightforward method because of the mechanisms and associations underlying the monozygotic twinning process. Indeed, Hall postulated that the development of a discordant cell line (by any mechanism including chromosomal, single gene mutation, mitochondria1 mutation, uniparental disomy, somatic crossing over, X-inactivation, imprinting, etc.) early in embryonic development may in fact be an underlying cause of human monozygotic (MZ) twinning; thus artificially inflating the number of discordant MZ twin pairs leading to biased estimates of heritability.
Thornton and Macdonald studied a cohort of female twins in the United Kingdom to estimate the maternal genetic contribution to preeclampsia and nonproteinuric hypertension. Based on self-reported diagnoses only, the study concluded that neither preeclampsia nor nonproteinuric hypertension was as heritable as previously believed.
O'Shaughnessy et al. conducted a study in the United Kingdom on monozygotic twin concordance for preeclampsia, using four pairs of monozygotic twin mothers and one monozygotic triplet mother. The study indicated that concordant monozygotic siblings were no more likely to develop preeclampsia than discordant ones. Finally, an Australian study examined a large cohort of twin pairs to determine the maternal versus fetal genetic causes of preeclampsia by evaluating concordance among several degrees of relatives: between monozygotic and dizygotic female cotwins, between female partners of male monozygotic and dizygotic twin pairs, and between female twins and partners of their male cotwins in dizygotic, opposite-sex pairs. The study determined preeclampsia to have a very low genetic recurrence risk; the maternal genetic contribution was also much lower than expected.
The accumulated evidence on twin studies of preeclampsia, including those conducted by Thornton and Onwude, Lachmeijer et al., and Salonen Ros et al., suggests that penetrance in preeclampsia is generally less than 50% and that the confidence interval is quite wide (95% CI, 0–0.71).
Segregation analyses attempt to fit the recurrence risk data from family studies into a genetic model. These analyses never prove inheritance via a particular model, but they can provide strong evidence against alternative models.
In the aggregate, segregation analyses before the year 2000 consistently suggested a relatively common allele acting as a “major gene” conferring susceptibility to preeclampsia. The marked increase in the incidence of preeclampsia in blood relatives but not in relatives by marriage implies that maternal genes are more important than fetal genes. Alternatively, this inheritance pattern supports the hypothesis of transmission of preeclampsia from mother to fetus by a recessive gene. More recent segregation analyses suggest a multifactorial, polygenic inheritance with strong epigenetic contributions. Some examples of methylated CpG islands in introns or promoters of differentially expressed genes have been proposed, e.g., the STOX1 transcription factor alleles (see below), but these remain controversial.
One alternative not adequately addressed in these models is whether a very high new mutation rate (as would be expected for a common but deadly condition) exists. Chesley has reviewed the recorded history of eclampsia, and it is clear that mortality from eclampsia was high until the last few generations. Given its high lethality, it is unclear how a preeclampsia gene would become so common in the population. With the exception of one report describing a gorilla pedigree with preeclampsia, we could find no evidence that preeclampsia occurs spontaneously in our recent primate ancestors. (However, surgical induction of uteroplacental ischemia in baboons and rhesus can result in a preeclampsia-like syndrome.) , Usually the only way a potentially lethal phenotype will remain prevalent in the population is if there are frequent new mutations or if the gene is positively selected on some other basis. Both of these are possibilities have been suggested in preeclampsia.
Preeclampsia-causing alleles that are common in the population can be discovered by tracking their occurrence through populations of women with and without preeclampsia. , , , In one of the most significant new sequence analyses, van Dijk et al. narrowed a minimal critical region at 10q22 linked with preeclampsia in women of Dutch ancestry to 444 kb. The STOX1 gene in this region contains five different missense mutations, identical between affected sisters, cosegregating with the preeclamptic phenotype and following matrilineal inheritance.
Oudejans et al. provide a concise review of segregation studies conducted as well as models for the transcription mechanisms at the various sites throughout the genome. Regarding the van Dijk analysis, Oudejans' study group proposes that a second variation, also on 10q22, is needed to explain the full phenotype in Dutch women. Oudejans' study group also noted that all of the susceptibility loci with significant linkage to preeclampsia detected previously—2p12 (Iceland), 2p25 (Finland), and 9p13 (Finland), in addition to the 10q22 region—display evidence of epigenetic effects, which could contribute to the persistence of preeclampsia despite its historically high mortality.
Table 3.3 summarizes the segregation analyses discussed in this section.
Author(s) Ref | Year | Study Conclusions |
---|---|---|
Rana et al. | 2003 | Familial forms of focal segmental glomerulosclerosis (FSGS) determined to be primarily autosomal recessive; preeclampsia developed in successive pregnancies |
Van Dijk et al. | 2005 | Narrowed a minimal critical region at 10q22 linked with preeclampsia in women of Dutch ancestry |
Laivuori | 2007 | Polygenic; also notes maternally inherited missense mutations in the STOX1 gene of the fetus |
Oudejans et al. | 2007 | Polygenic, with segregation of preeclampsia into early-onset, placental and late-onset. Notes contribution of epigenetics |
Berends et al. | 2008 | Cosegregation of preeclampsia with intrauterine growth restriction. High rate of consanguinity |
Linkage studies use a “positional” mapping approach to gene identification using regions of the genome that segregate with the disease of interest, in contrast to physiologic hypotheses. Linkage studies require an accurate diagnosis of the disease under study and precise histories of family relationships among the study participants. Furthermore, linkage analysis of pedigrees requires that the appropriate genetic model be used in the LOD (logarithm of the odds) score calculation. Polymorphic DNA markers are tested in family cohorts to find any violations of Mendel's second law, which states that independent traits segregate independently. Whenever two independent traits are closely located on the same chromosome, Mendel's second law is violated. Thus, aberrations from independent segregation can be used to “map” the chromosomal location of a disease gene.
Genome-wide linkage studies are preferable to analysis of preselected regions on preselected chromosomes for detecting susceptibility loci for complex diseases. After a genome-wide scan highlights certain regions and rules out others, fine mapping and sequencing of the suspect regions can zero in on candidate single-nucleotide polymorphisms (SNPs) and genes and detect parent-of-origin effects. Below is a summary of the genome-wide linkage studies and the genomic regions they have investigated. Other studies have been conducted based on biological hypotheses regarding functional genes in predetermined regions of the genome or in an effort to fine-map areas first detected with genome-wide studies.
Harrison et al. published a genome-wide linkage study of 15 Australian family pedigrees in 1997. They found a 2.8-cM candidate region between D4S450 and D4S610 on 4q with a barely significant, maximum multipoint LOD score of 2.9. Because of uncertainties concerning inheritance and diagnosis, four different inheritance models were used to carry out LOD score analysis.
Arngrimsson et al. published their results of a genome-wide linkage study of 124 Icelandic family pedigrees in 1999. They found a maternal susceptibility locus on 2p13 with a significant LOD score of 4.70. Their data supported a primarily dominant inheritance model.
Moses et al. published their results of a medium-density genome-wide scan of 34 Australian and New Zealand families in 2000. They found loci on chromosome 2 at an LOD score of 2.58 (tentatively supporting Arngrimsson's group ) and at 11q23–24 (LOD score 2.02). The model used was multipoint nonparametric.
Lachmeijer et al. published their results of a genome-wide scan of 67 Dutch families in 2001. The highest LOD score of 1.99 was determined on the long arm of chromosome 12, associated primarily with HELLP-afflicted families. When HELLP families were eliminated, the remaining 38 families were evaluated and returned LOD scores of 2.38 on chromosome 10q and of 2.41 on chromosome 22q. No chromosome 2 loci were detected.
Laivuori et al. published results of a genome-wide scan of 15 Finnish families in 2003. Two loci were detected: 2p25, with a nonparametric linkage (NPL) score of 3.77, and 9p13, with an NPL score of 3.74. A third locus of slightly weaker score was found at 4q32 (NPL 3.13).
In 2006, Kalmyrzaev et al. published results of a genome-wide scan on a single Kyrgyz family, so selected for the notable early onset of preeclampsia and the geographic isolation of the Kyrgyz population, which was expected to reduce heterogeneity of the condition. Nonparametric analysis detected a region at 2q23–q37, and with two-point parametric analysis, an LOD score of 2.67 was obtained at 2q24.3.
Moses et al. published results of a genome scan of 34 Australian and New Zealand families in 2006, in which they detected a significant locus at 2q with an LOD score of 3.43.
In 2007, Johnson et al. reanalyzed a previous genome-wide scan of 34 Australian and New Zealand families , with a more refined and powerful variance components model represented by quantitative trait loci (QTL). Doing this analysis returned two novel QTLs at 5q and 13q, with LOD scores of 3.12 and 3.10, respectively.
Majander et al. performed a genome-wide scan using fetal phenotypes of 15 Finnish families in 2013. They presented a suggestive linkage to chromosome 18 (NPL score 2.51, LOD = 1.20).
Table 3.4 summarizes the linkage analyses discussed in this section.
Author(s) Ref | Year | Inheritance Model | Results |
---|---|---|---|
Harrison et al. | 1997 | Four different models | Linkage with 4q |
Arngrimsson et al. | 1999 | Dominant | Linkage with 2p13 |
Moses et al. | 2000 | Multipoint nonparametric | Linkage on chromosome 2 and at 11q23–24 |
Lachmeijer et al. | 2001 | Various | Linkage on chromosome 12, 10q, and 22q |
Laivuori et al. | 2003 | Various | Linkage with 2p25 and 9p13 |
Kalmyrzaev et al. | 2006 | Two-point parametric | Linkage on chromosome 2 |
Moses et al. | 2006 | Various | Quantitative trait locus on 2q22 |
Johnson et al. | 2007 | Variance components | Linkage with 5q and 13q |
Majander et al. | 2013 | Fetal phenotype | Fetal susceptibility locus on chromosome 18 |
Our poor understanding of the underlying heterogeneity of preeclampsia has hampered the linkage studies conducted to date. Because the diagnostic criteria for preeclampsia are nonspecific, patients who represent “phenocopies” of the preeclampsia patients with strong genetic factors contributing are likely to be included in pedigrees being studied. Nonparametric analytic approaches may be preferable given our incomplete knowledge of the segregation patterns expected, but these methods require larger sample sizes.
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