Chapter 11. Epidemiologic Studies of Genetics

•  Familial aggregation of a disease is suggested when the recurrence risk among relatives of affected persons exceeds that among relatives of unaffected persons.
• In studies of twins, greater concordance for disease among monozygotic twins as compared with dizygotic twins suggests genetically determined susceptibility.
• If subjects with a high degree of inbreeding have an elevated risk of disease, an autosomal recessive pattern of inheritance may be suggested.
• Co-segregation refers to the tendency of alleles that are situated closely together on the chromosomes to be inherited together.
• Linkage of a marker gene (with a known location in the genome) and a disease susceptibility gene can suggest the particular chromosome involved and where on the chromosome the susceptibility gene is likely to be located.
•  Segregation analysis of pedigrees is a complex statistical technique used to determine whether a disease has, at least in part, a genetic origin, and if so, the likely pattern of inheritance.

The patient appears well nourished, without evidence of systemic illness. On mental status examination, the patient does not know the year, cannot remember any of three objects 5 minutes after learning them, and cannot count backward from 100 by 7. Neurologic examination is otherwise normal. After magnetic resonance imaging and further tests to rule out specific, treatable causes of dementia, a diagnosis of Alzheimer’s disease is made.

Dementia is characterized by impaired short- and long-term memory, along with disturbances of other cognitive functions (eg, language or visuospatial function). For a diagnosis of dementia to be made, the patient’s loss of cognitive abilities must be of sufficient magnitude to interfere with the individual’s performance of social or occupational activities. More than 60 different clinical disorders are associated with dementia, and Alzheimer’s disease is the most common cause of dementia in many populations. This disease was first reported in 1907 by Alois Alzheimer, who described morphological changes in the brain of a patient who died with progressive dementia. The clinical diagnosis of Alzheimer’s disease is made by excluding other possible causes of dementia, among which vascular disorders predominate.

The “gold standard” for arriving at a diagnosis of Alzheimer’s disease is a histologic examination of brain tissue. Patients with pathologic confirmation of disease are characterized as having “definite Alzheimer’s disease.” Clinical diagnosis typically is rendered on the basis of the composite findings of (1) a careful history, (2) physical, neurologic, and psychiatric examinations, and (3) laboratory and radiologic assessments. Patients who satisfy the clinical criteria, but do not have pathologic confirmation of disease, are characterized as having “probable Alzheimer’s disease.” When optimally applied, the standardized clinical diagnostic criteria for Alzheimer’s disease can yield a positive predictive value of 85% or higher, when compared with eventual findings at autopsy.

Although signs and symptoms of Alzheimer’s disease vary among patients, the onset of this disorder is typically insidious, and cognitive function deteriorates continually over time. This form of dementia is rarely seen in patients under age 60, but thereafter the incidence rises markedly with age. Patients usually present with difficulties in new learning. With advancing disease over several years, patients also develop difficulty with attention, orientation, reasoning, and emotions.

Diagnostic imaging of the brain reveals generalized atrophy of the cerebral cortex with enlargement of the ventricles. On postmortem examination, brains of patients with this disease are atrophied, particularly in the neocortex. Microscopic examination of the gray matter can reveal a loss of nerve cells and synapses, with abnormally staining neurons, neurofibrillary tangles, and neuritic plaques with a protein fragment, β-amyloid, at their core. β-Amyloid is an abnormal breakdown product of amyloid precursor protein, which is routinely produced by many cells, including neurons. A variety of neurochemical deficits occur in conjunction with Alzheimer’s disease, the most prominent being a loss of cholinergic neurons as reflected by a decrease in choline acetyltransferase activity.

The etiology of Alzheimer’s disease and its associated morphologic and biochemical abnormalities is unknown. Research to date has emphasized genetic predisposition as well as environmental risk factors such as head trauma and exposure to aluminum, but findings have been inconsistent. Recent studies in genetics and genetic epidemiology point to several genes that appear to play a role in the etiology of Alzheimer’s disease. For patients with early onset of disease (before 65 years of age), it has been estimated that as much as 50% of the disease occurrence may be explained by mutations of genes on chromosomes 1, 14, and 21. The gene on chromosome 21 codes for amyloid precursor protein, which has an autosomal dominant pattern of inheritance. The gene on chromosome 14 is referred to as presenilin 1 and the gene on chromosome 1 is referred to as presenilin 2. Both of the presenilin genes have an autosomal dominant pattern of inheritance. A fourth gene, found on chromosome 19 and referred to as apolipoprotein E (Apo E), codes for a protein involved in transport of cholesterol during neuronal growth and after injury. Apo E is associated with late-onset disease (after 65 years of age), with the e4 allele conferring increased susceptibility to developing Alzheimer’s disease. Some evidence is emerging that genetic risk and environmental factors may interact. For example, head injury may be a risk factor for late-onset Alzheimer’s disease, but perhaps only among those with the e4 allele of Apo E.

The prognosis for patients with Alzheimer’s disease varies widely, and among other factors, is dependent on age and severity of illness at diagnosis. For very elderly patients, Alzheimer’s disease may not impact on longevity, but does impair the quality of life. Death usually is not attributable to Alzheimer’s disease per se, but rather to other conditions that arise during the course of illness. Presently, no specific treatments prevent, arrest, or reverse the clinical progression of the illness. For patients with Alzheimer’s disease, some symptomatic relief can be achieved by addressing the neurochemical deficits. For example, cholinesterase inhibitors have been shown to slow the loss of cognitive function in at least subsets of patients with Alzheimer’s disease. Recent studies have demonstrated that disease progression also can be slowed by an antagonist to N-methyl-D-aspartate (NMDA), which reduces the flow of potentially damaging calcium into neurons. Other approaches under exploration for slowing the progression of illness include the use of nonsteroidal anti-inflammatory agents, antioxidants, and estrogen.

Researchers often use epidemiologic techniques to study genetic risk factors and interactions between genetic susceptibility and environmental factors, an application known as genetic epidemiology. The field of genetic epidemiology concerns the study of hereditary and environmental determinants of disease in human populations. This application of epidemiology is growing rapidly, in parallel with gains in knowledge about the human genome. As illustrated by the Patient Profile, we can apply knowledge of genetic susceptibilities to identify high-risk individuals and groups. For diseases in which screening tests and effective preventive or therapeutic regimens are available, knowledge of inherited risks can be used to enhance early detection and to encourage programs aimed at prevention.

Genetic epidemiology involves principles from the field of genetics as well as epidemiology. In particular, the design, conduct, and interpretation of studies in genetic epidemiology involve the same principles that apply to other kinds of epidemiologic research. For example, most research in genetic epidemiology involves a cohort or case–control design; but such a study differs from other epidemiologic studies primarily in that one of the “exposures” is a genetic factor.

In genetic applications, as in other areas of inquiry, early investigation of disease etiology often involves study of the descriptive epidemiology of the disease. Results of descriptive studies provide information about disease frequency and public health importance. Such findings may suggest an etiologic role of specific genetic, environmental, or other risk factors, and further investigation may evaluate a putative role for inherited susceptibility. Since a hereditary predisposition would give rise to clusters of disease within families, the epidemiologist may conduct studies to ascertain the degree of familial aggregation. If results of such studies document familial aggregation and suggest that genetic factors contribute to disease occurrence, subsequent investigation might involve assessing the association of risk of disease with specific markers, for example, a particular gene or gene product. Thus, genetic epidemiologic study of disease etiology frequently proceeds from

• 1. General descriptive studies, as part of an initial search for clues about etiology
• 2. Studies of familial aggregation, as part of a search for evidence of clustering within families
• 3. Epidemiologic studies designed to assess risk associated with specific genetic factors. An additional step in the investigation, one that is more an application of population genetics than of epidemiology, may involve more complex methods of genetic analysis that look for evidence of genetic etiology within pedigrees.

The basic types of investigation used in genetic epidemiology are shown in Table 11–1, along with a description of the goals of such studies and some illustrative applications. These various approaches are characterized in greater detail in the following sections of this chapter. The text is organized in a sequence that parallels the order in which these investigations might be conducted to characterize the etiology of a disease. First descriptive studies are performed, followed by research on familial aggregation, then exploration of specific genetic traits. For completeness of presentation, complex genetic analyses are mentioned briefly at the conclusion of the chapter, although these methods are often considered part of the domain of population genetics. Throughout the chapter, illustrative examples are drawn from the literature on Alzheimer’s disease.

The health researcher can use descriptive studies to shed light on the public health importance of an illness and on possible roles of genetic and environmental factors in occurrence of disease. In particular, basic characteristics of person, time, and place—as discussed in Chapter 3: Patterns of Occurrence—can provide clues to possible genetic and environmental risk factors.

Personal characteristics associated with variations in incidence can provide important information. Higher occurrence among certain ethnic or racial groups can suggest life-style, environmental, or possibly genetic risk factors. Higher occurrence of a disease among males can suggest hormonal risk factors, life-style factors, or an X-linked genetic disease. For example, the rare occurrence among females of classic hemophilia, a deficiency of functional clotting factor VIII—coupled with the 50% risk among male offspring born to certain female carriers of this disease—points to an X-linked recessive inheritance.

Geographic and temporal variation in disease occurrence can also provide important information. In particular, environmental factors that vary in parallel with disease rates may play a causal role. For example, within the United States the north-to-south gradient of increasing mortality from malignant melanoma, a potentially lethal form of skin cancer, parallels the north-to-south gradient of rising exposure to ultraviolet radiation (UVR). This pattern supports the role of UVR as a cause of malignant melanoma. Genetic factors, if they vary in parallel with disease occurrence, also may be important.

Studies of migrants can provide information about the relative roles of genetic and environmental factors (see Chapter 3: Patterns of Occurrence). For example, the incidence of prostate cancer is much lower in Japan than in the United States. First-generation migrants from Japan to the United States also have relatively low incidence rates, but the rates increase successively in subsequent generations. Epidemiologists interpret this pattern as supporting a causal role for environmental exposures that change as successive generations acculturate to the life-style patterns of the adopted country. If occurrence of prostate cancer was influenced only by genetics, one would not expect to find a dramatic change in risk of disease within a few generations.

Of course, discovery that nongenetic factors play an important role does not preclude the contribution of genetic factors, and conversely, discovery that genetic factors play an important role does not preclude a contribution from nongenetic factors. A very brief overview of the epidemiology and pathophysiology of phenylketonuria illustrates the importance of both genetic and environmental factors in this disease. Phenylketonuria is an autosomal recessive disorder in which those who inherit two recessive genes have altered metabolism of phenylalanine, and consequently develop mental retardation. However, special diets low in phenylalanine can prevent mental retardation, if instituted early. This strongly suggests that genetic susceptibility and diet act jointly to cause mental retardation in this disorder.

Example 1. To investigate the descriptive epidemiology of Alzheimer’s disease, researchers in East Boston conducted a survey of people aged 65 and over. After testing the memory and evaluating the neurologic condition of survey participants, the researchers estimated that about 10% of participants aged 65 or over probably had Alzheimer’s disease. The prevalence increased with age to a high of nearly 50% among those over age 85. Moreover, more than 80% of the cases of moderate-to-severe cognitive impairment in this population were due to Alzheimer’s disease. These results point out the overall high prevalence of Alzheimer’s disease, its increasing prevalence with age, and its growing public health importance as the population ages. Other aspects of the descriptive epidemiology of Alzheimer’s disease, such as the low incidence in Native Americans, suggest that genetic differences by ethnicity may affect risk of developing Alzheimer’s disease.

Epidemiologists expect to see disease aggregate in families if susceptibility is in part genetically determined. However, disease also can aggregate in families because nongenetic risk factors cluster among relatives. A key measure of clustering or aggregation in families is the recurrence risk, that is, the risk of disease experienced by relatives of a subject with disease.

To study and quantify familial aggregation, epidemiologists often use cohort studies (Chapter 8: Cohort Studies) or case–control studies (Chapter 9: Case–Control Studies). To study familial aggregation with a cohort design, the epidemiologist first identifies an index group of subjects with disease and a second index group of subjects without disease (Figure 11–1). The epidemiologist then assembles an “exposed” cohort consisting of the initially unaffected relatives of the index persons with disease and an “unexposed” cohort consisting of the initially unaffected relatives of the persons without disease. To simplify interpretation, the cohorts often consist of first-degree relatives of those in the index groups. These two groups are then followed to determine subsequent occurrence of disease and to calculate incidence rates and rate ratios in the usual way. The (incidence) rate ratio estimates the extent to which people with an affected family member have a rate of disease that differs from those without an affected family member. Accordingly, a rate ratio greater than unity suggests familial aggregation, whereas the absence of familial aggregation is indicated by a rate ratio of unity or less.

This approach is illustrated by a study of Alzheimer’s disease conducted by Huff and colleagues (1988): the exposed cohort consisted of siblings and parents of index cases who had Alzheimer’s disease, and the unexposed cohort consisted of corresponding relatives of subjects without Alzheimer’s disease (Figure 11–2). In this study, siblings and parents of patients with Alzheimer’s disease had nearly a 50% lifetime risk of developing the illness, compared to a risk of about 10% among the corresponding relatives of comparison subjects. In other words, the lifetime risk of developing Alzheimer’s disease was increased about fivefold (a risk ratio of about 5) for family members of patients with Alzheimer’s disease. The authors noted that their results were consistent with an autosomal dominant pattern of transmission, but that other factors, such as a shared environment, could also explain the familial aggregation they found. Other investigators examining recurrence risk have suggested that the elevated risk among first-degree relatives does not follow an autosomal dominant pattern of transmission, since female relatives of the index persons had a higher risk than male relatives. In that study, parents of index persons also had a higher risk than did siblings. Example 2 further illustrates use of the cohort design to study familial aggregation.

Example 2. As noted in Example 1, the incidence of Alzheimer’s disease varies across ethnic and racial groups. To study familial risk factors for Alzheimer’s disease, Payami and coworkers (1994) studied risk of developing this disease among three groups: parents and siblings of patients with Alzheimer’s disease, parents and siblings of healthy elderly controls, and parents and siblings of randomly identified controls. The healthy elderly controls underwent neurologic examination and magnetic resonance imaging to ensure that they did not have dementia. The subjects and family members were interviewed to obtain histories of Alzheimer’s disease and other dementia in relatives. The investigators found the risk of developing dementia by age 90 to be 0.44 for relatives of patients with Alzheimer’s disease, 0.20 for relatives of randomly sampled controls, and 0.06 for relatives of healthy elderly controls. These observations demonstrate familial aggregation and are consistent with the presence in some families of genes that confer increased risk of developing Alzheimer’s disease. The authors interpreted the lower risk of aggregation in relatives of healthy controls as possibly suggesting the presence of “protective” genes whose presence reduces risk.

Epidemiologists also use the case–control study design to study familial aggregation. The design of this type of case–control study is analogous to that discussed in Chapter 9: Case–Control Studies, except that exposure is determined by family history—the epidemiologist defines subjects who have one or more affected relatives to be “exposed” and subjects who do not have an affected relative to be “unexposed” (Figure 11–3). The odds ratio from this case–control study is calculated in the usual way. In this context, the odds ratio is the odds of having an affected family member among persons with the disease divided by the odds of having an affected family member among persons without the disease. Under appropriate circumstances, as outlined in Chapter 9: Case–Control Studies, the odds ratio approximates the risk ratio—the risk of disease among those with an affected family member divided by the corresponding risk among those without an affected family member. Of course, odds ratios greater than one support familial aggregation. Interpretation can be difficult unless one specifies which relatives—and how many of them—to use in determining family history. For purposes of simplicity, limiting the relatives of interest to the parents of each subject avoids the problem of any systematic differences in the average family sizes of cases and controls.

Case–control and cohort studies can provide useful information by documenting the presence and quantifying the degree of familial aggregation. These studies may also identify factors that create the aggregation by evaluating and assessing the roles of specific nongenetic risk factors. For example, in estimating recurrence risk for breast cancer among those with an affected relative, many other nongenetic exposures, such as diet and reproductive history, may be assessed.

Documentation and quantification of familial aggregation using the case–control or cohort study provide important information and may suggest a genetic etiology. Further studies of familial aggregation may assess the pattern of disease occurrence within the family to separate the relative roles of genetic and nongenetic factors. We consider two such studies—twin studies and inbreeding studies.

Twin studies can provide useful information about the role of possible genetic and environmental risk factors by comparing the pattern of risk among dizygotic (fraternal) twins with that among monozygotic (identical) twins. Monozygotic twins have identical genetic constitutions, whereas dizygotic twins have no more genetic similarity than do siblings.

In another type of twin study design, researchers study genetic and environmental factors by comparing disease concordance among twins reared together with that among twins reared apart. In this type of study, a pattern of risk of disease in which twins reared together have greater concordance for disease than twins reared apart suggests the importance of nongenetic factors, including social and environmental influences.

The descriptive studies and the studies of familial aggregation considered so far can provide useful, but indirect, information about possible genetic and environmental causes of disease. If these studies suggest that the disease has, at least in part, a hereditary basis, further research can focus on the risks associated with specific genetic factors such as enzymes, receptors, or structural proteins. The following sections present a direct and an indirect approach to studying the association of disease with specific genetic factors.

To understand both the direct and indirect approach, as well as the more complex genetic linkage analyses, we must first understand genetic linkage. Linkage between one gene and another arises because alleles that are closely situated on the same chromosome tend to be passed together as a group to offspring.

At the population level, recombination or crossing over between genes tends to eliminate or reduce imbalances related to genetic linkage. This recombination tends to create an equilibrium in which the frequency with which two alleles (at different genes) occur together is simply the product of the frequencies with which each allele occurs in the population. Nevertheless, for some gene pairs an excess or deficiency of certain combinations of alleles occurs, a situation termed linkage disequilibrium. Such linkage disequilibrium can be present if a mutation (ie, a new allele) has recently arisen in a population, or if certain combinations of alleles at the two loci confer a survival advantage over other combinations.

The Direct Approach

With the direct approach, the researcher directly studies the possible increase in risk associated with a specific factor, such as an alteration in the DNA sequence or variations in enzyme activity. Using a cohort study, the researcher compares the risk among those with a specific variation in the DNA sequence or enzyme activity with the risk among a similar group without that variant (Figure 11–5). Following the principles outlined in Chapter 8: Cohort Studies for cohort studies and defining the “exposure” to be those with a particular genotype, the researcher follows two groups of subjects—one with the genetic variant and the other without the genetic variant—and then determines subsequent occurrence of disease. The investigator then calculates risks for each group, as well as the risk ratio that measures the increase (or decrease) in risk associated with the genetic variant. As in other cohort studies, subjects should be free of disease at the start of follow-up and should be comparable except for the genetic variant of interest.

Alternately, the researcher can use a case–control design to study the association between risk of disease and a specific genetic factor. In this type of case–control study, the “exposure” is the genetic factor of interest (Figure 11–6). As in other types of case–control studies (Chapter 9: Case–Control Studies), cases consist of people with the disease of interest, and investigators select controls from the source population, that is, the population which gave rise to the cases. After assembling the case and control groups, the researcher compares the frequency of the genetic factor of interest among the cases to the corresponding frequency among the controls. The odds ratio—the odds of the genetic factor among cases divided by the odds of the genetic factor among controls—provides an approximation to the risk ratio, as described in Chapter 9: Case–Control Studies. If cases have an elevated frequency of the genetic factor, the researcher must consider the possibility that this excess could be secondary to the disease itself or its treatment, rather than a cause of the disease. This possibility could occur, for example, in a study of the association between a particular mutation and risk of developing leukemia if the mutation was measured in blood obtained from cases after chemotherapy, since certain chemotherapeutic agents are known to be mutagens.

As with other types of epidemiologic studies, researchers must exercise care in interpreting results of genetic epidemiologic investigations. They must consider the possibility of selection bias, confounding, and misclassification in the interpretation of genetic epidemiologic findings, as those biases can affect genetic epidemiologic results just as they can affect other types of research. The possibility of selection bias must be considered, particularly in case–control studies, if controls are not selected from the source population that gave rise to the cases. The possibility of confounding must be considered, particularly by factors such as race and ethnicity, as these factors relate to risks for many types of disease and also can be linked with genetic markers.

Another important consideration arises in interpreting studies of the association between risk of disease and a specific DNA alteration, as measured by a marker allele. This kind of study is typified by studies of the association between insulin-dependent (type I) diabetes mellitus and certain human leukocyte antigens (HLAs). These studies have documented an increased risk of diabetes mellitus in association with the presence of the HLA DR3 allele. It is possible, however, that it is not the HLA DR3 allele per se, but rather some companion alteration at a nearby genetic locus, that is responsible for increasing the risk of developing diabetes mellitus. This phenomenon can arise if noncausal marker alleles at one genetic locus are in linkage disequilibrium with alleles at the causal genetic locus. If linkage disequilibrium is present, an association between risk of disease and the marker may reflect linkage disequilibrium between the marker and the gene that confers disease susceptibility—and not a causal association between the marker itself and risk of disease. Nevertheless, direct evidence of increased risk in association with a marker allele, if valid, suggests that the marker allele or another allele linked to it relates to susceptibility to disease.

With increasing frequency, researchers are now using single nucleotide polymorphisms or SNPs to measure alterations in the DNA sequence. The SNP reflects a change in a single base-pair at particular point in the DNA sequence. An advantage of SNPs is that they can be measured relatively easily in the laboratory, but a disadvantage is that many SNPs may be required to detect a relevant mutation in a particular gene since the SNP measures change only at a single point.

Finally, it should be noted that consideration of possible gene–environment interactions is important. For example, failure to account for important environmental factors in the design or the analysis of the study can lead to an underestimate of the influence of a genetic factor. The genetic characteristic of interest may contribute to risk of disease only in the presence of some environmental trigger. Accordingly, failure to account for a critical environmental trigger may obscure the role of an underlying genetic susceptibility.

The Indirect Approach

With the indirect approach, the researcher also looks for evidence of an association with a genetic factor. The indirect approach differs from the direct approach in that a marker is used for the genetic factor that may not be the same as the causal genetic factor itself. This approach depends on genetic linkage between the genetic marker and the disease susceptibility gene. Documentation of an association between the marker and risk of disease provides evidence that a gene near the marker allele affects risk of disease.

A straightforward epidemiologic approach to the study of linkage involves estimating recurrence risks in siblings of index subjects with a specific disease. For a particular marker locus, a sibling can share by descent either zero, one, or two marker alleles with the case. If the marker locus is linked to a disease susceptibility locus, a sibling who shares two alleles with the index case should have the highest chance of having the same disease susceptibility allele as the case—and hence the highest risk of disease. A sibling who shares one allele with the case should have an intermediate chance of having the same disease as the case, and a sibling who shares no alleles with the case should have the lowest chance of having the same disease susceptibility allele and hence the lowest risk of disease. If risk of disease in siblings parallels the number of alleles shared with the case, the data suggest the presence of a disease susceptibility gene near the marker gene on the same chromosome. This type of study, sometimes called sib-pair analysis, is a simple example of genetic linkage analysis.

In more complex applications of genetic linkage analyses, the geneticist measures a genetic marker among a group of family members that is not restricted to siblings. If subjects who share the genetic marker, such as a particular allele, also tend to be concordant for occurrence of disease, the disease susceptibility gene may be located on the same chromosome near the marker allele. As with sib-pair analyses, these more complex linkage analyses rest on the rationale that if the measured genetic marker is located near the disease susceptibility allele, the marker allele and the susceptibility allele will tend to be passed together, that is, to cosegregate. Cosegregation of the marker allele and the disease susceptibility allele will then create concordance between occurrence of disease and presence of the genetic marker. Example 4 illustrates a linkage study.

Example 3. To study the role of apolipoprotein E (Apo E), a specific genetic factor suspected of playing a role in the causation of Alzheimer’s disease, Tsai and coworkers (1994) conducted a case–control study. They obtained blood from 77 cases with Alzheimer’s disease and 77 matched controls, then determined the presence of three isoforms of Apo E—denoted e2, e3, and e4. About 35% of the cases had the e4 allele, compared with 13% of controls. The results support the role of Apo E as a risk factor for Alzheimer’s disease. Although the mechanism remains uncertain, results of other studies suggest that Apo E may bind to β-amyloid and change it to a neurotoxic form.

Example 4. To help in the search for possible genetic factors associated with Alzheimer’s disease, Schellenberg and colleagues (1992) conducted linkage analyses in a series of 14 families, each of which had at least three members with Alzheimer’s disease in at least two generations. Using several markers for loci on chromosome 14, the investigators found that within some families with early-onset Alzheimer’s disease, members who shared the same markers tended to be concordant for Alzheimer’s disease. The evidence suggested that a gene on chromosome 14 codes for susceptibility to early-onset Alzheimer’s disease. If so, this would be a separate locus from the one coding for apolipoprotein E, as the Apo E gene is located on chromosome 19.

To study the possibility of genetic inheritance, the researcher also can apply methods from population genetics. In this section, a commonly used, powerful approach called segregation analysis is presented.

• One half of the offspring affected are from marriages in which only one parent has the disease
• Three fourths of the offspring affected are from marriages in which both parents have the disease
• None of the offspring affected is from a marriage in which neither parent has the disease.

In contrast, autosomal recessive or multifactorial patterns of inheritance will result in other characteristic patterns of disease occurrence within pedigrees.

In population studies, diseases do not tend to occur in such idealized patterns following the classical risks associated with the modes of inheritance. Segregation analysis provides a probabilistic method to assess the statistical consistency of the observed pattern of disease with the hypothesized mode of genetic inheritance.

In this chapter, an overview of genetic epidemiology was presented. The field of genetic epidemiology uses the same basic principles of study design and analysis as are used in other areas of epidemiology. Researchers in genetic epidemiology conduct three basic types of studies: descriptive studies, studies of familial aggregation, and studies of specific genetic markers. Each type of study typically involves a case–control or cohort design and differs from other types of epidemiologic studies primarily in the “exposure” of primary interest being a genetic factor.

In the initial phase of studying the etiology of a disease, the researcher may use descriptive studies to look for characteristics that suggest genetic and nongenetic etiologies of disease, for example, person, place, and time. In a second phase, the researcher may study familial aggregation to look for evidence of increased risks of recurrence in relatives of cases and to look for further etiologic clues. Finally, the researcher may study specific genetic characteristics, such as gene markers or products, as well as gene–environment interactions. The researcher may also apply some of the more complex analytic methods derived from population genetics, such as segregation or linkage analyses, to study patterns of genetic inheritance.