Epidemiologic Reviews Copyright C 1997 by Tne Johns Hopkins University School of Hygiene and Public Health All rights reserved

Vol. 19. IMo. 1 Printed In U.&A

Genetic Epidemiology of Multiple Sclerosis

A. Dessa Sadovnick,1 D. Dyment,1' 2 and G. C. Ebers2

INTRODUCTION

multiple sclerosis with certain alleles of the major histocompatibility complex (human leukocyte antigen region in humans)" (5). In this review (4), Spielman and Nathanson suggested that future studies on the genetic susceptibility of multiple sclerosis should aim to 1) unravel the issues of possible heterogeneity, 2) replicate an initial report of an association between multiple sclerosis and a Gm allotype, and 3) continue to search for genetic loci, other than human leukocyte antigen, which may influence multiple sclerosis susceptibility using the "recently identified" class of restriction fragment length polymorphisms. The present review will address and expand on the contribution of genetic epidemiologic studies towards meeting these stated aims. Results from ongoing research since 1982 have led to the following conclusions about the etiology of multiple sclerosis: 1) genetic and nongenetic factors are involved in the etiology of multiple sclerosis on a population basis; 2) the familial aggregation of multiple sclerosis is genetic; 3) maternal factors do not influence the risk for siblings to develop multiple sclerosis; and 4) multiple sclerosis appears to be oligogenic (more than one locus). Much of the evidence for the above has come from studies using classic genetic epidemiologic approaches, i.e., studies of twins (6-8), adoptees (9), half-sibs (10), and familial risk data (11-13). In 1996, three groups simultaneously published initial data from full genome screens in multiple sclerosis (14-16). However, despite these advances, it is recognized that much work remains to be done before a gene (or more likely, genes) will be identified. This review is not intended to be a reiteration of the overall epidemiology of multiple sclerosis, rather, it will focus on what has been learned from research which has largely used the genetic epidemiologic approach to unravel the complex etiology of this disease.

Multiple sclerosis occurs in approximately 0.1 percent of Caucasians of northern and central European ancestry, and is the most common demyelinating disease of young adults. The age of onset ranges from 10 to 59 years (1), with the majority of cases having onset between the ages of 20 to 40 years. In rare cases, the onset can be before age 10 years (2) or after age 59 years (3). The majority of multiple sclerosis patients have a monosymptomatic onset (one symptom, frequently motor or sensory), but polysymptomatic onset is also common. Onset symptoms can include sensory symptoms (numbness, tingling), visual disturbances (optic neuritis, diplopia), spasticity, weakness, fatigue, ataxia and intention tremor, and bowel and/or bladder disturbances. The clinical course of multiple sclerosis can range from a fulminating disorder, which can be fatal within months, to an asymptomatic condition only recognized incidentally at autopsy. The most commonly observed clinical course is initially characterized by a series of relapses and remissions which often become progressive over time ("secondary progressive"). Other relatively frequently observed clinical courses include "benign," "long-term relapsing-remitting," and "primary chronic progressive." Although multiple sclerosis is not usually a fatal disease, disability and lost/ decreased quality of life are common. The economic cost of this disease is staggering. The previous article to appear in Epidemiologic Reviews on the genetic susceptibility to multiple sclerosis was written in 1982 (4). The impetus for that article was "the recent discovery of the association of Received for publication October 30, 1996, and accepted for publication July 28, 1997. 1 Department of Medical Genetics, University of British Columbia; Geneticist, Multiple Sclerosis Clinic and Alzheimer Clinic, Vancouver Hospitals and Health Sciences Centre—UBC Pavilions, Vancouver, British Columbia, Canada. z Department of Clinical Neurological Sciences, University of Western Ontario, London, Ontario, Canada Reprint requests to Dr. A. D. Sadovnick, GF-401, Koemer Pavilion, Vancouver Hospital and Health Sciences Centre—UBC Pavilions, 2211 Wesbrook Mall, Vancouver, BC, Canada V6T 2B5.

SUMMARY OF THE OVERALL EPIDEMIOLOGY OF MULTIPLE SCLEROSIS

A review of the overall epidemiology of multiple sclerosis must include the following topics: 1) geographic distribution (prevalence and incidence, migra99

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tion); 2) clusters; 3) epidemics; 4) precipitating factors; and 5) associated diseases. As previously stated, it is beyond the scope of this review to provide a detailed discussion of the vast literature available on the epidemiology of multiple sclerosis; therefore, these topics will only be briefly summarized. For an in-depth review, the reader is referred to published review articles, including those by Sadovnick and Ebers (17) and Kurtzke (18). Geographic distribution

The nonrandom geographic distribution of multiple sclerosis has been the subject of epidemiologic studies for decades. A north-south gradient in the northern hemisphere (south-north in die southern hemisphere) has long been noted. Classic studies on this topic include the work of Kurtzke (19) and Kurtzke et al. (20) on US veterans. In many locations it can be argued that the observed gradient may represent genetic variation within the population (21, 22) rather than a nongenetic (epidemiologic) effect. Nevertheless, the situation in Australia is of particular interest since there is a welldocumented several-fold difference in south-north prevalence despite genetic homogeneity of the population (23). Migration studies have mostly focused on individuals moving from "high" to "low" risk areas for multiple sclerosis. The pioneering migration studies in multiple sclerosis were done by Dean (24) on migrants to South Africa and Alter et al. (25) on migrants to Israel after World War II. Factors confounding migrant studies include 1) the assumption that persons who leave a geographic area are representative of those who stayed behind, 2) a lack of accurate prevalence/incidence data for the geographic regions involved, and 3) an inability to properly define die denominator. Nevertheless, it appears that young children (age 10 years is often cited) who migrate tend to develop multiple sclerosis at a rate mat is intermediate between die country of origin and the country of destination. Clusters Clusters or "hot spots" (regions where more than die expected number of multiple sclerosis cases have occurred) have been reported. Examples include Key West, Florida (26), Henribourg, Saskatchewan, Canada (27), and Hordaland, Norway (28). Analysis of reported clusters can be complicated for various reasons including die fact diat the denominator is generally unknown. It is not unusual to find diat reexamination of a reported cluster does not support the initial

observation. Nevertheless, reports of clusters cannot be ignored in the continuing quest to identify causal agents in multiple sclerosis. Epidemics

Since World War n, mere have been repeated reports of multiple sclerosis epidemics in the Faroe Islands (29, 30) and Iceland (31). Interpretation of these observations has been subject to much controversy (32-34). Precipitating factors

It is well recognized that females develop multiple sclerosis more often than do males (35) with female: male ratios usually in the range of 1.5-2.0:1. These ratios can increase to approximately 3:1 for multiple sclerosis widi childhood onset (2). There is no definitive "precipitating factor" for either multiple sclerosis onset or the worsening of symptoms. Proposed precipitating factors include diet (36), heavy metals (37), trauma (38), and pregnancy (39). (See the review by Sadovnick and Ebers (17) for more details.) Associated diseases

A number of diseases, such as systemic lupus erythematosus (40), myasdienia gravis (41), ankylosing spondylitis (42), uveitis (43), and inflammatory bowel disease (44), have been reported to be associated widi multiple sclerosis. However, these reported associations have not been confirmed by appropriate and carefully designed population-based surveys. There is some evidence that some families may exist in which diere is a genetic predisposition to autoimmune diseases (45); however, in most multiple sclerosis centers this is a rare observation. GENETIC EPIDEMIOLOGY

The genetic epidemiologic approach has led to important findings in multiple sclerosis. Results from family studies, including studies of twins (6-8), parent-child concordant pairs (46), concordant sibpairs (47), half-sibs (10), adoptees (9), and conjugal multiple sclerosis (48), have had important implications for genetic counseling, genetic modeling, genome screens, and a better understanding of the natural history of multiple sclerosis (e.g., depression and multiple sclerosis (49), cause of death (50)). There have been several published reviews of the genetics and genetic epidemiology of multiple sclerosis, and interested readers are referred to these (e.g., Ebers and Sadovnick (51)). The present paper is not Epidemiol Rev Vol. 19, No. 1, 1997

Genetic Epidemiology of Multiple Sclerosis

meant to be a comprehensive review of all published works, but will focus on how the genetic epidemiologic approach has added to our understanding of the etiology of multiple sclerosis. There has long been controversy about whether or not genetic (inherited) factors have a role in multiple sclerosis susceptibility. It is largely because of results from well-designed, population-based genetic epidemiologic studies that we can now conclude the following (briefly referred to previously but expanded below). 1) Multiple sclerosis results from an interaction of genetic (hereditary) and nongenetic (environmental) factors. 2) The familial aggregation of multiple sclerosis (i.e., the excess of multiple sclerosis found in biologic relatives of persons with this same disease) is due to genetic material these relatives have in common (i.e., identical by descent with the individual having multiple sclerosis). 3) There is no maternal effect (e.g., imprinting, mitochondrial inheritance, breast feeding) influencing the sib risk to develop multiple sclerosis. Role of a transmissible agent

Given the results of the genetic epidemiologic studies, it now seems unlikely that multiple sclerosis is the result of a transmissible agent(s) whose action(s) occurs in the uterine/perinatal period, childhood, or adulthood. Evidence for this statement follows. Uterine/perinatal period. Dizygotic twins have 50 percent of their genetic material in common, as do full sibs. However, it has long been believed that dizygotic twins share a more common "uterine" and "perinatal" environment than do nontwin sibs. The observations from population-based twin studies in Canada (6, 7) and the United Kingdom (8) show that the rate of multiple sclerosis among sibs and dizygotic cotwins of multiple sclerosis patients do not differ significantly. These findings suggest that the uterine and/or perinatal environment do not produce any detectable impact on sib risks for multiple sclerosis. Further evidence that the uterine and/or perinatal period does not influence the risk to develop multiple sclerosis comes from a recent half-sib study (10) (see below). Childhood. The rationale behind birth order position studies (e.g., Isager et al. (52) and Visscher et al. (53)) is that birth order position impacts on age of exposure to transmissible agents. For example, presumably, a first bom child would develop childhood illness at a later age compared with a child born later in the sibship. The reason for this assumption is that once older children are out in the community and in school, they bring home "transmissible agents" to which younger sibs are exposed. The results of birth order studies have been somewhat contradictory, but recent population-based studies clearly do not show Epidemiol Rev Vol. 19, No. 1, 1997

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any birth order effect (54, 55). Further evidence against a transmissible agent comes from adoption (9) and half-sib (10) studies. Adopted sibs do not share any genetic material identical by descent with the multiple sclerosis patient but are raised as though they were biologic sibs. These adopted sibs develop multiple sclerosis no more often than expected for the general population (9) (see table 1). In other words, no "familial aggregation of multiple sclerosis" is observed among persons raised as sibs but who do not share genetic material identical by descent. Data from a half-sib study (10) clearly show that sib risks for multiple sclerosis do not differ significantly according to "shared" family environment. Half-sibs raised together do not have a different rate of multiple sclerosis compared with half-sibs who only spent limited periods of time together and/or half-sibs who have never met during childhood and adolescence (see table 2). Adulthood. Increased conjugal risk has been demonstrated for many chronic viral infections of the nervous system (e.g., human immunodeficiency virus and human T-cell lymphotrophic virus, type 1). There is no evidence for an increased conjugal risk in multiple sclerosis, making some allowances for ascertainment and assortative mating. In an ongoing Canadian population-based study, 25 conjugal cases of multiple sclerosis were found among some 18,000 patients (unpublished data), a figure consistent with the general population rate for multiple sclerosis of 1/800 to 1/ 1,000. Maternal effect

As previously stated, multiple sclerosis is more frequent among females compared with males. Despite the observation that father-daughter pairs concordant for multiple sclerosis occur as often as expected (46), the question of a maternal effect, such as mitochondrial inheritance, imprinting, and breastfeeding, has often been raised as a risk factor. Data from a half-sib TABLE 1. Expected versus observed number of nonbiologlc relatives with multiple sclerosis* No. oi multiple sclerosis cases Nonbtotogic relatives

Age-adjusted Expected

Observed

Polsson probability

Parents (n = 470) Siblings (n = 345) Children {n = 386)

9.2 10.7 5.5

1 0 0

p= 0.0010 p=2.3x 10-* p = 0.0041

Total (n= 1,201)

25.4

1

p = 2.5x 10-«

1

Adapted from Ebers et al. (9).

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TABLE 2.

Half-sib studies In multiple sclerosis*

Relationship to Index case

Number

Age-adjusted rbte „ Standard deviation

Number wtth multiple sclerosis

Full sibs versus half-sibs Full sibs Half-sibs

1,395 1,839

39 18

3.46 1.32

0.55 0.31

Maternal versus paternal half-sibs Maternal half-sibs Paternal half-sibs

1,033 806

11

1.42 1.19

0.42 0.45

Half-sibs raised together versus half-sibs raised apart Half-sibs who lived together Half-sibs who never lived together

897

6

1.17

0.41

942

10

1.47

0.46

* Adapted from Sadovnick et al. (10).

study (10) do not support the notion of any maternal effect. The rate of multiple sclerosis among half-sibs did not differ significantly according to whether the half-sibs were maternal (mother in common) or paternal (father in common). If a maternal effect was important, one would predict that maternal half-sibs would have a higher multiple sclerosis rate compared with paternal half-sibs (see table 2). Genetic epidemiologic approach to estimating the number of genes and the mode(s) of inheritance

The existence of age-corrected familial multiple sclerosis risks for specific relationships (twins, sibs) and population prevalence/lifetime prevalence data allow genetic modeling (i.e., estimate of number of genes, mode of inheritance) to be done for this disease. Using well-documented, population-based family data from the Vancouver Multiple Sclerosis Clinic (11), various models can be tested. Illustrative examples are given in table 3. These were calculated using methodology outlined by Risch (56), based on the following assumptions: 1) lifetime risk for multiple sclerosis = 0.2 percent; 2) monozygotic concordance rate = 38 percent; 3) recurrence risk for first-degree relatives = 4 percent; and 4) recurrence risk for second-degree relatives = 1.1 percent. Therefore, "XMZ" = 190 (38 percent/0.2 percent) "Ai" = 20 (4 percent/0.2 percent) "A2" = 5.5 (1.1 percent/0.2 percent) where A = risk ratio for relatives compared with the population prevalence; XMZ = monozygotic twins; A,

TABLE 3. sclerosis

Illustration of genetic modeling In multiple

Relationship

Observed

Expected

Model I ("Reject Modef): two led with X 4.47 each Monozygotic twin First-degree Second-degree

63.1 20 7.5

190 20 5.5

Model II ("Best fif): locus plus potygenlc modifiers; X of major locus = 4 Monozygotic twin First-degree Second-degree

190 20 5.5

175 20 5.6

Model III ("Possible fif): one locus plus potygenlc modifiers; X of major locus •= 6 Monozygotic twin First-degree Second-degree

190 20 5.5

122 20 6.4

= first-degree relatives; and A2 = second-degree relatives. It is important to again emphasize that the data given above and in table 3 are to illustrate the practical application of this methodology; they do not represent a comprehensive overview of genetic modeling in multiple sclerosis. Data on first-degree relatives are the most sound. They represent the largest number of observations and the best knowledge about relatives with respect to multiple sclerosis status. Therefore, for all calculations illustrated in table 3, each model being tested assumes the A, value for first-degree relatives to be fixed at "20". All other A's are generated from this value within the confines of the model being tested. It is encouraging that the model in which susceptibility is determined by a large number of loci, each with small effect, is unlikely. This model, if compatible with multiple sclerosis data, would be very complex and difficult to elucidate. Risch (unpublished data) has shown that this model would predict a decrease in risk ratios by a power of lA with each degree of relationship. This is highly inconsistent with the multiple sclerosis data. For example, \MZ =190 but A! = 20. The search for candidate genes

To plan linkage studies in a complex disease such as multiple sclerosis, it is important to have some understanding of the likelihood of finding linkage under the constraints imposed by the nature of the problem. The likelihood of finding linkage depends on 1) the number of loci involved in multiple sclerosis susceptibility, 2) the magnitude of their individual effects, 3) the population frequencies of high risk alleles, 4) the relationship of genotypes at multiple loci to risk (enEpidemiol Rev Vol. 19, No. 1, 1997

Genetic Epidemiology of Multiple Sclerosis

compassing concepts of genetic heterogeneity and/or epistasis where genes at different loci may or may not interact in producing risk), 5) the density (map distance) of the di(tri-tetra)nucleotide repeat map (and other restriction fragment length polymorphisms), and 6) the polymorphism content of the markers involved. Multicase families

The types of multicase families and their individual value for linkage detection in complex traits have been considered in great detail (56, 57). Risch calculated the power and efficiency of readily accessible "pair" methods designed for several specific relationships (i.e., first cousins, half-sibs, grandparents, aunts/uncles-nieces/nephews). These considerations are most appropriate for designing a strategy in multiple sclerosis where by far the most common type of "multicase" family has only two affected individuals, usually sib-pairs. Despite nearly three decades of searching for candidate genes in multiple sclerosis, the only unambiguous association remains the class II major histocompatibility complex (5). Nevertheless, existing data strongly indicate that additional loci will be identified which influence both susceptibility and outcome. The following is a brief review of some of the suggested candidate loci for multiple sclerosis. This is not meant to be a comprehensive list of either all studies per candidate or of all suggested candidate genes. Human leukocyte antigen. Human leukocyte antigen molecules play a key role in the immune system's response against foreign antigens by regulating the development and maturation of the T-cell repertoire within the thymus. They are also involved in the activation of the cell-mediated immune response of the periphery. The mature T-cell will initiate (or not initiate) an immune response depending upon the class of human leukocyte antigen (i.e., class I or class II) and whether the presented antigen is foreign (or self antigen). As the normal immune response is dependent upon human leukocyte antigen, the genes of the human leukocyte antigen locus have been proposed as candidate genes for multiple sclerosis susceptibility. Early studies demonstrated an association between multiple sclerosis and human leukocyte antigens (e.g., see Jersild et al. (5) and Olerup and Hillert (58)). In contrast to association studies, the results of linkage studies have been contradictory (e.g., see Tienari et al. (59), Ebers et al. (60), and Kellar-Wood et al. (61)). Recently, a genome-wide screening conducted in the United States (16) confirmed a role for human leukocyte antigen in multiple sclerosis pathogenesis. This finding was supported by a smaller study in Finland Epidemiol Rev Vol. 19, No. 1, 1997

103

(62) and, to a lesser extent, by Canadian and United Kingdom genome-wide screens (14, 15). The contribution of human leukocyte antigen to the risk of developing multiple sclerosis is believed to be modest at best. A rough estimate of this contribution of human leukocyte antigen to multiple sclerosis, based on 336 published (59-65) affected sib-pairs, using the methodology of Risch (66), concluded that "other determinants" contribute more to the relative risk of multiple sclerosis than does human leukocyte antigen. Our review of the data found that of the 336 sib-pairs reviewed, 52 shared no haplotypes identical by descent However, the expected probability of sharing 0 alleles between sibs in a single locus model is given by 0.25/Asibs, where Asibs is the sib recurrence risk divided by the population prevalence. As Asibs is 37 for multiple sclerosis (3.7 percent^,, ^ ^ 0 . 1 percentcpopuiation prevalence)). the probability of observing 0

haplotype sharing is 0.67 percent. Using this as a probability, "p", the Poisson probability of observing 52/336 is 2.7 X 10~ 31 . It is thus very unlikely that the human leukocyte antigen locus is the sole determinant responsible for the observed sib recurrence risk. In a "two determinant" epistatic (multiplicative) model, *sibs = (AA

IOCUS)*(AB

locus) (55-57,65). As the AA l o c u s

equals 1.6 (0.25/(52/336)), then the residual AB locus is 22.9 (given that Asibs is 37). This demonstrates that other determinants contribute more to relative risk than does human leukocyte antigen. Tumor necrosis factor-a and tumor necrosis factor-p chain polymorphisms. Association, classic linkage, and affected sib-pair linkage studies have been done for both tumor necrosis factor-a and tumor necrosis factor-^ with conflicting results (67-79). Taken together, the data suggest that 1) tumor necrosis factor-a chain polymorphisms do not contribute to multiple sclerosis susceptibility and 2) tumor necrosis factor-^ chain polymorphisms contribute relatively little to multiple sclerosis susceptibility and are probably dependent on the presence of other loci. Myelin basic protein. Association, classic linkage, and affected sib-pair linkage studies have been done for myelin basic protein with conflicting results (8085). Taken together, the data suggest that, at least for non-Finnish populations, myelin basic protein does not contribute to multiple sclerosis susceptibility. Immunoglobulin heavy chain. Association and a few affected sib-pair linkage studies have been done for the immunoglobulins. Taken together, the data suggest that constant region polymorphisms do not contribute to multiple sclerosis susceptibility and variable region polymorphisms need further confirmation from independent samples before any conclusions can be made (86-96).

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Sadovnick et al.

TABLE 4. Some regions of Interest Identified from genome screen* in multiplex multiple sclerosis families from Canada,* the United States,! the United Kingdom,* and Flnland§ Marker Chromosome Chromosome Chromosome Chromosome

1 2 3 5

Chromosome 6 Chromosome 7

1 cent 2S119* D3S1261* D5S406* D5S815t

D7S554t

D7S623J Chromosome 10 Chromosome 11 Chromosome 12

Chromosome 17 Chromosome 19 Chromosome 22 X chromosome • t t §

From From From From

Chromosome

D10S212* D11S2000* Di1S922f PAHf

5q13-23 Scent 5p14-ip12§ 6p21 (MHC)fc§ 7q21-22 7q32-34 1P*

Di2S392t

11p15 12q24 12q24-qter

Di9S219t APOC2t

17q22* 19q13 19q13

SUMMARY

The continuing search for genetic loci which may influence multiple sclerosis susceptibility has probably been more complex and exciting than Spielman and Nathanson (4) could have imagined in 1982. Restriction fragment length polymorphisms no longer represent the "cutting edge" of technology. This entire area of research has gained incredible impetus with advances in molecular genetics and the advent of the "Human Genome Project." Readers must be cautioned that identification of a gene does not equate with a cure. Nevertheless, we are entering into a very exciting era with respect to the genetics and treatment of common complex disorders such as breast cancer, Alzheimer disease, and multiple sclerosis. Given the increasing awareness of the public about the role of genetics in the etiology of such disorders, a better understanding is needed of the legal, social, ethical, and psychologic implications of genetic research in multiple sclerosis.

22qt DXS1068*

Ebersetal. (14). Sawceret al. (15). Haines et al. (16). Kuokkanen et al. (62).

Tumor necrosis factor. Tumor necrosis factor-a polymorphisms have been put forward as possible candidate genes based on observations of the role of tumor necrosis factor-a at the central nervous system lesions of multiple sclerosis patients (97) and the levels of tumor necrosis factor in their cerebrospinal fluid and sera (98, 99) This remains speculative (100, 101). Genome screens in multiple sclerosis

With advances in the techniques of molecular genetics, it is now possible to conduct total genome screens using microsatellite markers. In August 1996, the initial results of genome screens in multiplex families from Canada (14), the United States (16), and the United Kingdom (15) were simultaneously published in Nature Genetics, as was a more limited genetic study from Finland (62). The Canadian group (14) was able to exclude 88 percent of the genome for a locus of Asib greater than 3. The United Kingdom group (16) was able to exclude 93 percent of the genome for a locus of Asib greater than 5. Table 4 lists several regions of interest identified by the three groups. Taken together, the initial findings of the three groups are consistent with genetic epidemiologic data in that they support the notion of multiple genes of relatively small individual effect interacting epistatically to determine heritable susceptibility.

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