What is an example of multiple gene inheritance?

Classical Quantitative Inheritance

Based on multiple-factor Mendelian inheritance, Fisher established the additive-dominance genetic model (g = a + d, p = g + e, where g and p are genotypic and phenotypic effects, a and d are additive and dominance effects, and e is random error, respectively, in Fisher’s notation) for quantitative traits to separate the gene effect and the genetic variance into the respective parts, that is, additive and dominance, in ‘The correlation between relatives on the supposition of Mendelian inheritance’ in 1918. Later on during 1924–34, Haldane explained the genetic changes of quantitative traits under natural and artificial selection in a series of articles of ‘A mathematical theory of natural and artificial selection’. Wright overviewed the mating systems and then defined the inbreeding coefficient and path coefficient in a series of articles on ‘Systems of mating’. With the former, various mating systems of populations could be linked to each other for joint analysis of quantitative inheritance; and with the latter, the genetic effects of quantitative traits under various mating systems could be estimated. A very important concept of heritability in quantitative inheritance was established and further defined as heritability in a broad sense and heritability in a narrow sense by Lush in his ‘Animal Breeding Plan’ in 1940s, which was relevant in studying selection efficiency and the expected genetic gain of selection procedures for quantitative traits. After that, Sprague and Tatum established the concept of combining ability of a parent in 1942, including general and specific combining ability, indicating the quantitative inheritance performed at heterozygous generation. Malécot defined the coancestry coefficient (coefficient of parentage) as the probability of a pair of the same alleles from both parents being identical by descent in 1948, with which the general relationship of covariance between relatives was established. All these concepts helped in the establishment of the classical quantitative inheritance. Mather and his colleagues extended Fisher’s simple genetic model into that with epistasis (g = d + h + i + j + l, where d, h, i, j, and l are additive, dominance, additive by additive epistasis, additive by dominance epistasis, and dominance by dominance epistasis effects, respectively, in Mather’s notation), and then developed a series of procedures to detect and verify the genetic model and related genetic effects. They mainly focused on the genetic populations derived from a biparental cross, including triple test cross (TTC) genetic design. Their representative publication is ‘Biometrical Genetics’. Meanwhile, based on Fisher’s simple genetic model, Kempthorne, Comstock, and Falconer also extended it into that with epistasis (g = a + d + aa + ad + dd, where aa, ad, and dd are additive by additive epistasis, additive by dominance epistasis, and dominance by dominance epistasis effects, respectively, in Kempthorne’s notation based on Fisher), and then developed a series of procedures to detect and verify genetic models. Their approach was mainly based on the variance–covariance analysis among relatives and their genetic materials were mainly random mating population and its derivatives with different degrees of inbreeding. A series of mating designs were developed for studying quantitative inheritance, such as NC I, NC II, and NC III. ‘An Introduction to Genetics Statistics’ by Kempthorne in 1957 and ‘Introduction to Quantitative Genetics’ by Falconer in 1961 are their representative publications. There was controversy between the Birmingham school headed by Mather and Jinks and the Iowa–North Carolina–Edinburgh school headed by Kempthorne and others. In fact, the two schools worked on different approaches to the same problem. The former mainly used biparental F2 as reference population with their derived populations to detect the genetic models and estimate the first-order genetic parameters, while the latter used random mating population as a reference population with their derived populations to detect the genetic models and estimate the relative importance of various genetic effects based on second-order genetic parameters. However, the latter was more likely to cover a wide range of genetic populations since an inbreeding coefficient was used to link random mating population to populations with certain degree of inbreeding and, therefore, connecting more tightly with improving breeding procedures for cross-pollinated and self-pollinated crops, as well as animals. In addition, both schools had realized the importance of genotype × environment interaction in the inheritance and performance of quantitative traits. At this stage, the classical quantitative genetics was well established. The major characteristics of this stage were to establish statistical or biometrical procedures for designed genetic populations to detect genetic models and estimate the relative importance of the genetic components. Under this consideration, the effect of each gene was assumed very small but the number of genes was assumed very large, called polygenes or minor genes, in the quantitative genetic system, and therefore, the detected genetic effect was due to the collective performance of polygenes or minor genes. Thus, the polygenes or minor genes could be detected collectively but not individually.

Multifactorial Inheritance

There are disorders that affect certain families more than others but do not follow Mendelian patterns of inheritance or fit into the non-Mendelian inheritance phenomenon. These disorders are thought to be the result of interplay between genetic and environmental factors and gene–gene interactions. Known asmultifactorial orcomplex inheritance, these disorders have a greater incidence than disorders secondary to chromosomal or single-gene mutations. These disorders provide unique genetic counseling dilemmas regarding recurrence risks, because although genotypes predisposing to disease may aggregate in families, the phenotypic expression is discordant, owing to differences in nongenetic exposures.

An illustrative example of multifactorial inheritance is the occurrence of neural tube defects (NTDs). Spina bifida and anencephaly are NTDs that cluster in families and are a leading cause of fetal loss and handicap. Spina bifida is the result of incomplete fusion of vertebral arches and manifests in various degrees of severity. Anencephaly is a devastating condition in which the forebrain, overlying meninges, bone, and skin are absent. Most fetuses with anencephaly are stillborn. Although some NTDs can be explained by teratogens, amniotic bands, or chromosomal disorders, most are multifactorial. Decreased levels of maternal folic acid have been inversely correlated with the risk of NTDs. Folic acid levels are affected by two factors—dietary intake and enzymatic processing. Folic acid levels are detrimentally affected by a mutation in the enzyme 5,10-methylenetetrahydrofolate reductase (MTHFR). Fifteen percent of the population is homozygous for the mutation. It has been shown that the mothers of infants with NTDs were twice as likely to have MTHFR mutations than controls. Preconceptual supplementation of folic acid has been shown to decrease the risk of NTDs.42 All reproductive-age women should consume 0.4 mg of folic acid daily. Prenatal screening for NTDs is discussed later in this chapter.

What Is Multifactorial Inheritance?

Multifactorial inheritance refers to disorders caused by multiple genes and environmental factors. This group of disorders includes a broad range of medical (cardiac disease and diabetes), congenital (birth defects including cardiac malformations, neural tube defects, and cleft lip and/or palate), and neuropsychiatric (ASD, schizophrenia, bipolar disorder) diseases. Family and twin studies have shown that these diseases have a genetic component; however, it is also clear that there are environmental contributors. Sometimes, gender can affect inheritance. For example, research has shown that a male sibling is more likely to be diagnosed with ASD if a sibling has been diagnosed.18 Many neuropsychiatric diseases and birth defects demonstrate complex multifactorial inheritance (Table 2.4; Reprinted with permission, originally Box 1 in ACOG Technology Assessment in Obstetrics and Gynecology No. 11: Genetics and Molecular Diagnostic Testing [Reference #7])

Multifactorial and polygenic inheritance

There is a spectrum in the aetiology of disease, from environmental factors (e.g. trauma) at one end to purely genetic causes (e.g. Mendelian disorders) at the other. Between these two extremes are many disorders that result from the interacting effects of several genes (polygenic) with or without the influence of environmental or other unknown factors, including chance (multifactorial or complex) (Box 9.11).

Variation in quantitative traits, such as height and intelligence, results from complex interactions between environmental factors and multiple genetic influences. The environmental factors include early life (including intrauterine) experiences. These parameters are thought to show a Gaussian (normal) distribution in the population. Similarly, the liability of an individual to develop a disease of multifactorial or polygenic aetiology has a Gaussian distribution. The condition occurs when a certain threshold level of liability is exceeded. Relatives of an affected person show an increased liability due to inheritance of genes conferring susceptibility, and so a greater proportion of them than in the general population will fall beyond the threshold and will manifest the disorder (Fig. 9.16). The risk of recurrence of a polygenic disorder in a family is usually low and is most significant for first-degree relatives. Empirical recurrence risk data are used for genetic counselling. They are derived from family studies that have reported the frequencies at which various family members are affected. Factors that increase the risk to relatives are:

having a more severe form of the disorder, e.g. the risk of recurrence to siblings is greater in bilateral cleft lip and palate than in unilateral cleft lip alone

close relationship to the affected person, e.g. overall risk to siblings or children is greater than to more distant relatives

multiple affected family members, e.g. the more siblings already affected, the greater the risk of recurrence

sex difference in prevalence, with the recurrence risk greater in the more commonly affected sex and if the affected individual is of the less commonly affected sex.

The phenotype (clinical picture) of a disorder may have a heterogeneous (mixed) basis in different families, e.g. hyperlipidaemia leading to atherosclerosis and coronary heart disease can be due to a single gene disorder such as autosomal dominant familial hypercholesterolaemia, but some forms of hyperlipidaemia are polygenic and result from an interaction of the effect of several genes and dietary factors.

In some complex disorders, such as Hirschsprung disease, the molecular genetic basis and the important contribution of new mutations are becoming clear. In many multifactorial disorders, however, the ‘environmental factors’ remain obscure. Clear exceptions include dietary fat intake and smoking in atherosclerosis, and viral infection in insulin-dependent diabetes mellitus. For neural tube defects, the risk of recurrence to siblings is lowered from about 4% to 1% or less in future pregnancies if the mother takes folic acid before conception and in the early weeks of pregnancy.

Multifactorial inheritance

Multifactorial inheritance is defined as traits or characteristics produced by the action of several genes, with or without the interplay of environmental factors. A number of structural abnormalities occurring as isolated defects and not part of a syndrome, such as cleft lip with or without cleft palate, open neural tube defects (including anencephaly and spina bifida), and cardiac defects, are examples of such conditions. When both parents are normal and an affected child is conceived, the chance of recurrence is generally between 2% and 5% for any given pregnancy. Because the underlying mechanisms by which the genes and the environment interact to cause these conditions are largely unknown, genetic counseling of recurrence risks must measure the observed recurrence risks in collections of families to generate a population-based empiric risk. These risk rates, however, are modified by many factors, including ethnicity, the sex of the affected parent and at-risk offspring, the presence of the defect in one or both parents, the number of affected family members, and consanguineous parentage (Kuller, 1996).

Multifactorial or Complex Inheritance

Multifactorial inheritance refers to disorders and genetic traits that occur and are determined by the interaction of environmental factors and multiple genes. In many cases, the specific genes involved in these disorders are unknown or their role is poorly characterized. Multifactorial inheritance, generally, is thought to encompass threshold traits, qualitative traits, and complex disorders of adulthood, such as diabetes and heart disease. A number of common birth defects are believed to be inherited in a multifactorial fashion as threshold traits. Threshold traits are present only if a certain level of the combination of genetic liability and environmental exposure is reached. Neural tube defects, congenital heart defects, cleft lip, and club foot are all most commonly due to multifactorial genetic inheritance, although some may be due to monogenic or chromosome disorders. In contrast, for qualitative traits that result from the interaction of multiple genes and the environment, the distribution and phenotype of the trait follows a normal, bell-shaped distribution. Many human traits (e.g., height, weight, blood pressure, intelligence) are inherited in this manner. Although it is clear that many disorders of adulthood have genetic and environmental interactions, with clear clustering in families and strong environmental influences, the underlying genes and genetic mechanisms are poorly characterized for most of these conditions.

Birth defects due to multifactorial inheritance are often seen to occur in a family at a higher incidence than that in the general population; however, the inheritance pattern does not follow that of classic Mendelian inheritance. A number of basic principles govern counseling on recurrence risk of multifactorial disorders or birth defects. First, the risk is highest in first-degree relatives of an affected individual, and the risk decreases substantially for more distant relatives. For many multifactorial disorders, if a parent or sibling (first-degree relative) is affected, the recurrence risk in future offspring is estimated to be 3%–5%. In third-degree relatives (e.g., first cousins), the recurrence risk approaches that of the general population. Second, the more family members affected, the greater the risk of recurrence because this reflects a greater genetic contribution to the phenotype. Third, the more severe the disorder, the higher the recurrence risk. If a parent was born with a bilateral cleft lip and palate, the recurrence risk in his offspring is higher than if he had only a unilateral cleft. Similarly, hypoplastic left heart is in the same spectrum of disorders as bicuspid aortic valve. A woman who has had a prior child with hypoplastic left heart is at higher risk to have a child with any type of left-sided flow–related cardiac defect compared with a woman with an isolated bicuspid valve. Fourth, many multifactorial disorders demonstrate a sex predilection. If the affected individual is of the less frequently affected sex, the recurrence risk in future offspring is higher. For example, pyloric stenosis is more common in males than females. If a female is affected, the recurrence risk is increased in future male and female offspring. The male sibling of an affected female has a 10% risk of having pyloric stenosis, whereas the male sibling of an affected male has a risk of approximately 4%.

Critical Questions

To understand multifactorial traits and disorders, we must answer the following four questions (Table 13.2). First, how can we determine whether genes play a part in these common traits and disorders? Second, how can we estimate the magnitude of the role genes play for any given trait? Third, how do we identify the specific genes, the specific environments, and the interactions between them? Fourth, how can this information be used to advise individuals and families regarding prevention, diagnosis, and treatment? We will weave answers to these questions into the remainder of this chapter.

TABLE 13.2. Critical Questions Concerning Multifactorial Conditions

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How can we determine that genes play a part?

How can we estimate the magnitude of the genetic contribution?

How do we identify the specific genes, the specific environments, and the interactions among them?

How can this information be used to advise individuals and families?

B Hypertension

Hypertension is a multifactorial trait resulting from the combination of environmental and genetic factors. Several polymorphisms of candidate genes that are linked to hypertensive phenotypes have been identified (Benetos et al., 1996; Bonnardeaux et al., 1994; Davies et al., 1994). Genetic variations of pre-miRNAs, mature miRNAs, and their target genes determined by gene polymorphisms and single-nucleotide polymorphisms have been proposed to be related to many human diseases including hypertension (Mishra et al., 2008; Sethupathy and Collins, 2008; Wang et al., 2010). Thus, for instance, it has been demonstrated that miR-155 is complementary with a specific sequence in the 3′ UTR of angiotensin II receptor type 1 (AT1R) gene harboring the A1166C polymorphism (Martin et al., 2007). Recent data showed that the interplay between miR-155 expression, + 1166C polymorphism, and AT1R protein expression may play a role in the regulation of blood pressure (Ceolotto et al., 2011).

Fascinatingly, miR-143/145 knockout mice showed a significant reduction in systolic blood pressure due to reduced vascular tone, resulting from decreased contractile ability of the vessels (Boettger et al., 2009; Xin et al., 2009). Combined genomics/proteomics and transcriptional analyzes identified multiple potential miR-143/145 targets including ACE. In this regard, it is noteworthy that angiotensin (Ang) II, a product of ACE-mediated cleavage of Ang I, is bound by the AT1R on the surface of VSMCs, promoting vasoconstriction and alteration of VSMC phenotype (Schieffer et al., 2000); this provides one potential explanation for selective targeting of the vascular system in these mutant mice (Table 15.1).

In different rodent models of hypertension, vascular voltage-gated L-type calcium channel [Ca(L)] current and vascular tone is increased because of increased expression of the noncardiac form of the Ca(L) [Ca(v)1.2] (Rhee et al., 2009). A modified miR-30a-based short hairpin RNA driven by the cytomegalovirus promoter reduced endogenous Ca(v)1.2 expression by 61% and decreased the Ca(L) current carried by barium by 47%. This molecular intervention in vivo may provide a novel long-term vascular-specific gene therapy for hypertension (Rhee et al., 2009). Additionally, differential expression of miRNAs, including miR-155 and miR-208, has been revealed in the aorta of spontaneously hypertensive rats (SHR) (Xu et al., 2008). In this study, miR-155 level was significantly lower in aorta of SHR and miR-208 expression in aorta was negatively correlated with blood pressure and age, indicating that these two miRNAs play a role in the pathogenesis of hypertension.

Abstract

Smoking behavior is a multifactorial trait influenced by genetic and environmental components. Several genome-wide association studies (GWASs) have identified candidate genes or loci for smoking behavior. However, most of these results were from European studies. Genetic differences are known to exist between ethnic groups or samples from different geographic locations. This chapter focuses on the genetic aspects of Japanese smoking behavior. Focusing on the CYP2A6 polymorphism, many studies have reported that a mutant allele with an impaired or null enzyme activity was a negative risk factor for nicotine addiction; however, some studies have indicated negative associations. Regarding neuronal nicotinic acetylcholine receptors, we showed that the CHRNA5 rs16969968 polymorphism was associated with smoking cessation and a high Tobacco Dependence Screener score. We have also confirmed that the TaqIA polymorphism near the DRD2 gene was related to current smoking, which was consistent with the results of previous studies examining Japanese populations. The further accumulation of investigations, including GWASs, and functional studies is warranted to establish a wider view of the genetic factors affecting smoking behavior.

What is an example of multiple genes?

What is multi gene inheritance?

What are 3 examples of polygenic traits?

What are the three examples of multiple alleles?