Genetic epidemiology of breast cancer in Britain

Ann. Hum. Genet. (1991), 55, 151-159 Printed in Great Britain

151

Genetic epidemiology of breast cancer in Britain

L. ISELIUSl, J. SLACK2, M. LITTLER' AND N. E. MORTON1* CRC Research Group in Genetic Epidemiology, Department of Community Medicine,

Southampton General Hospital, Southampton SO9 4XY, UK Department of Clinical Genetics, Royal Free Hospital Xchool of Medicine, Pond Street,

LondonNW3 ZQG, IJK

SUMMARY

A complex segregation analysis was conducted on two British series (one consecutive series of probands with breast cancer and one series ascertained through a normal consultand). Altogether there were 1248 nuclear families with breast cancer. A dominant gene with a frequency of 0.003 giving a lifetime penetrance of 0.83 is favoured. Ovarian, endometrial and cancers associated with the SBLA syndrome, as well as benign breast disease, were significantly more common in familial breast cancer than in families of single cases. Probands in families with more than one individual with breast cancer were non-significantly younger than isolated probands.

INTRODUCTION

During the past decade several studies reviewed by Iselius et al. (1990) have indicated that inheritance of breast cancer is mediated by rare dominant genes. This has stimulated family cancer clinics, which necessarily collect a highly biased sample of pedigrees ascertained through unaffected consultands, whereas genetic epidemiology has been concerned with pedigrees ascertained through affected probands. Here we address two problems: (1) removing the bias of the normal consultand and (2) determining genetic parameters of risk in the British population. The results have implications for consultands, for breast cancer screening programmes, and for efforts to map predisposing genes.

MATERIALS AND METHODS

Two samples were collected, called consecutive and selected. The first consisted of pedigrees ascertained through 254 probands who were consecutive women diagnosed with histologically confirmed breast cancer attending follow up breast clinics at two London hospitals, the Royal Free and University College. There was no selection of the first 204 cases, but the last 50 probands were selected for premenopausal onset (before age 50). Family history was not a basis for selection.

The second sample consisted of pedigrees ascertained through 416 normal consultands who attended the Genetic Clinic at the Royal Free Hospital, which accepts women who are concerned about a family history of breast cancer, either breast cancer with onset before the age of 50 in a close relative, or more than one breast cancer, or breast cancer with other malignancies in the family.

*To whom reprint requests should be made.

152 1,. ISELIUS AND OTHERS

The family history in both series was taken in the same way by the same clinic staff. The proband in the consecutive series or consultand in the selected series was questioned about all first- and second-degree relatives, and the pedigree was extended, when possible, to include more remote affected relatives and their parents and sibs. A history of breast cancer was confirmed if feasible by medical records and/or a death certificate. Affection was defined as breast cancer without regard to age of onset. Pedigree members not classified as affected were taken to be unaffected unless the proband or consultand disclaimed knowledge of their medical condition, and were then classified as of unknown phenotype. Age was taken to be a t death, or if alive, a t the time of ascertainment. Individuals with age less than 20 were omitted.

Sibships in the consecutive series were of 3 types:

( 1 ) index sibships including the proband as a child (single selection); ( 2 ) children of probands (complete selection) ; (3) children of collateral and ancestral cases (truncate selection with closest affected relative

as a pointer).

In the selected series we discarded the consultand and took the two closest affected relatives as probands and/or pointers. If a parent and two sibs qualified as affected, we took the parent and one sib as probands for odd numbered pedigrees (pedigrees were allocated consecutive numbers for identification purposes) and two sibs as probands for even numbered pedigrees (coded 1A for multiplex selection). Sibs of consultands were omitted unless a t least one was a proband.

Sibships in selected multiplex pedigrees were of three types, corresponding to the ones defined above for the consecutive series:

( 1 ) index sibships including a proband as a child, with an additional affected sib, an affected parent, or the closest affected relative as a pointer (single selection with an affected parent or pointer) ;

(2) children of probands with a proband within the sibship (truncate selection) ; (3) children of collateral cases and sibships including an ancestor but not a proband (truncate

selection with closest affected relative as pointer).

Some consultands had only a single relative with breast cancer, nearly always under 50. This was designated the proband, the consultand’s sibship was omitted, and the rest of the pedigree was coded as for the consecutive series. Nuclear families classified according to these rules were submitted to the computer program POINTER, with likelihood conditioned on parental and pointer phenotypes and the method of ascertainment (Morton et al. 1983).

Each individual was assigned to one of nine liability classes based on sex and age. The risk attributed to the j t h liability class was

where I j is the cumulative incidence to the midpoint of j and is the cumulative specific mortality to the end of the preceding class. Therefore Ri is the probability that a random individual observed in the j t h class (dead or alive) be affected. Age of onset is an affective variable (i.e. not defined for normal or unknown phenotype) and does not enter into the estimate of risk. We estimated I from incident cases 1979-82 in England and Wales (IARC,

Genetic epidemiology of breast cancer 153

1987) and M from deaths due to breast cancer 1980-4 reported in the Registrar General’s Statistical Review of England and Wales. The parameters estimated in segregation analysis were polygenic heritability ( H ) , major locus dominance ( d ) , displacement between homozygotes ( t ) , and gene frequency (q) as described by Morton et al. (1983).

RESULTS

The calculated risks are given in Table 1. In old age they are substantially less than cumulative incidence because of mortality due to breast cancer a t earlier ages. Altogether there were 431 nuclear families from the consecutive series and 817 families in the selected series.

The results of the segregation analysis for the consecutive and selected series combined are given in Table 2. There was significant evidence (xi = 15.02, P < 0.01) for a dominant major gene with frequency 00030 and displacement 1.96. When d was iterated with q and t it went to one. There was no evidence for heritability in addition to the major gene.

Heterogeneity tests between the consecutive and selected series are presented in Table 3. Resolution is poor in the consecutive series and most evidence for the major gene comes from the selected series. The gene frequency estimate under the dominant model for the consecutive series is high, but there is no significant difference between the two series.

Several previous studies of the genetics of breast cancer have used transmission probabilities as a test of the claim for a major locus (Williams & Anderson 1984; Demenais et al. 1986; Goldstein et al. 1987; Newman et al. 1988). Demenais et al. (1986) and Andrieu et al. (1988) argued that the use of all three transmission probabilities is necessary to rule out non-mendelian transmission. However, we have recently shown that the implementation of transmission probabilities in POINTER is not correct (Iselius et al. 1990). Transmission probabilities in POINTER are valid only if the families are drawn under complete selection, without pointers and with no allowance for sporadic cases. In the previous study we showed that other situations did not give correct values for the transmission probabilities. In the present study we have complemented the previous analysis which had little information on families under complete selection without pointers. The reader is referred to the earlier paper (Iselius et al. 1990) for the method used. Again we were able to show that only families under complete selection, without pointers and with no mutation, give correct results. In light of these findings and for other objections documented there, we have not used transmission probabilities in the present analysis.

Estimation of penetrance is complicated when specific mortality is taken into account. Current methods assume that gene frequency is constant over liability classes and calculation of penetrance is conditional on this assumption. As an approximation, taking specific mortality into account, we define the penetrance as the cumulative incidence for gene carriers in the j t h liability class which is given as

where the genotype-specific mortality is

P(G’ I aff, i ) (Mi -Mi-l ) /CP(G’ I aff, i ) (Ii

154 L. ISELIUS AND OTHERS

Table 1 . Liability classes and risks in England and Wales 1979-82

Age Cumulative Cumulative Risk of having breast incidence* mortalityt cancer dead or alive

Class Male Female I M R 2-54 55-69 70-84 85 +

20-24 0'000 05 0'000 24

25-29 0'000 34 30-39 0'002 54 40-49 0'01 I 79 50-59 0026 25

70-79 0 0 6 1 30

*To midpoint of interval.

-

60-69 0.044 I 8

80 + 0089 94

o'ooo 04

0'000 26 0 0 0 1 95 0.007 36 0.01 6 73 0.028 70 0.044 47 0.062 76

0000 22

?To end of interval.

00000~ 0000 20 0000 I 2 0002 28 0.009 86

0.027 92 0.033 56 0047 59

0'01903

Table 2. Segregation analysis of British breast cancer data, consecutive and selective series combined.

See text for parameters estimated.

Model - 2 In L + C H 4 t d Sporadic -7117'15 (0) (0) Polygenic -7227.05 0 4 7 (0) Recessive - 7237.82 (0) 0.0855 2.43 (0) Dominant and - 7242'07 (0) 0.0030 I .96 (1)

- -

- -

generalized single locus

Table 3. Heterogeneity tests for the consecutive and selected series

Model

Polygenic Recessive Dominant

Study H -2lnL+C 4 t -2lnL+C 4 t -2 In L + C Consecutive 0'42 -2772.37 0.339 1'45 -2771'10 0029 1'35 -2772'38

(431 families) Selected 0.48 -445494 00656 2.88 -447459 000186 2.12 -447498

(817 families) Heterogeneity

X2 0 2 6 7'87 5'29 D.F. I 2 2

This gives lifetime penetrance as 0 8 3 (Table 4). Inherent in a liability model is that an affected individual belonging to a low-risk liability class is more likely to have the putative breast cancer gene than an affected individual in a high risk liability class. This is reflected in Table 4 where, for instance, the probability of an affected female between 20 and 24 years of age to have the major gcne for breast cancer is 0897 while the corresponding probability is 0-076 for a woman in her eighties. Although the higher recurrence risk for relatives of young probands is supported by some case-control studies (e.g. Anderson, 1972; Ottman et al. 1986), it is not necessarily true for other diseases. It merely reflects the model and has to be supported by other evidence.


Table 4. Characteristics of the major locus for each liability class ( d = I , q = 0.003, t = 1.96')

Class 1 2 3 4 5 6 7 8 9

Female age 2-24

25-29 3-39 4-49 5-59 60-69 7-79 80 +

~

P (affection 1 genotype) Penetrance

GG 0'000 0 I 0'000 04

0'00 I 37 0007 92 001650 0'025 03 0030 50

0000 02

0'044 2 I

G G or GIG'

0007 49 0026 03 0.01667

0.33 1 63 0.43 8 46

0607 73

015401

050708 0541 28

P(G' I affection)

0.897 0.780 0833 0.405

0138 0.109 0.097 0.076

0202

pj 0007

0'020 0.171

0.541 0656 0735 0829

0.387

ASSOCIATIONS

To search for an overrepresentation of other malignancies in families with multiple cases of breast cancer, we calculated the correlation coefficient between the number of breast cancers in a pedigree and the number of a particular malignancy in the pedigree, divided by the number of pedigree members not having breast cancer. Only first- and second-degree relatives of cases with breast cancer were used for this analysis. Both endometrial and ovarian cancers were significantly associated with familial breast cancer. Also the combined number of sarcomas, embryonal malignancies, acute leukaemias, thyroid tumours and Hodgkin's disease, reported in some cancer families (Schimke, 1985), was significantly associated with familial breast cancer. Both the association between breast cancer and ovarian cancer (Lynch & Krush, 1971) and with endometrial cancer (Williams, 1985) are well known. Li & Fraumeni (1969) have described the association between breast cancer and soft tissue sarcomas, embryonal malignancies, acute leukaemias and brain tumours (SBLA syndrome). There was some but non- significant support for an association with colon cancer (one-tailed P = 0.09) and with pancreas cancer (one-tailed P = 0.07). There have been claims for an association between colon cancer and breast cancer especially in conjunction with the so-called Lynch syndrome I1 (Lynch et al. 1988). However, there are studies not showing such an association (e.g. Jacobsen, 1946; Burki et al. 1990). The study by Biirki et al. found only a slight increase of colon cancer in female relatives of patients with invasive ductal breast cancer but not in any other histological subgroup of breast cancer. Pancreas cancer has been reported to be associated with breast cancer in some cancer families (Schimke, 1985), but this is not a constant finding. Also benign breast disease was significantly more common in familial cases of breast cancer which is supported by other studies (review in Lynch et al. 1989). The data did not allow any division of benign disease into subgroups as fibrocystic disease and fibroadenoma.

A source of bias in this analysis of the association between familial breast cancer and a particular malignancy is that some isolated cases may have come to attention through other malignancies in the pedigree. This might lead to an underestimate of the association between familial breast cancer and other malignancies because of the grouping of sporadic and isolated cases. However, if the consultands in the selected series have two or more relatives with breast cancer in addition to other cancers, the same sampling scheme might overestimate the degree of association. Unless certain cancers have been selectively ascertained this mechanism should not lead to overestimates for particular cancers but should inflate the correlations overall.


We also analysed the association between familial breast cancer as defined above and side of affected breast (left or right), laterality and age of onset. Information on affected side was given in 205 cases. As found in earlier studies, there was a slight excess of cancer affecting the left breast (review in Garfinkel et al. 1959) with no significant differences between familial and non- familial cases. Bilateral breast cancer was significantly more common in familial cases than in isolated (33 YO v. 12 YO). If cases where laterality was not known are counted as unilateral, the corresponding percentages were 9.1 YO v. 6.9 %, which better agrees with the frequency of bilateral disease usually found. This difference is not significant (x: = 1.51, P = 0.22). The actual percentages should be viewed with some caution since quite often the only information about an affected relative was that she had breast cancer. It is possible that bilateral breast cancer is more likely to be remembered and reported by the consultand. However, it is unlikely that this bias should be different between familial and non-familial cases unless the interviewer is more active in asking about bilateral disease in relatives to consultands in familial cases. This might happen since the association between familial cases and bilateral disease is now well known. In the consecutive series the age of onset for the probands was lower (51-7) if the pedigree had more than one case of breast cancer than for isolated probands (544 years). The difference was not significant (P = 0-22). The ages of the probands in the selected series were lower than in the consecutive series since premenopausal cases were overascertained in the selected series. We therefore did not use the selected series for comparison of age of onset. In the consecutive series the age of onset (for the first cancer) for bilateral cases was significantly lower (44.5) than for unilateral cancer (54.7). A lower age of onset for familial cases has been noticed in some populations, notably USA (e.g. Anderson 1972, 1974; Lynch et al. 1976), but by no means in all populations studied, for example Japan (Murata et al. 1982) and Great Britain (Penrose et al. 1948).

DISCUSSION

Several other studies, all using POINTER, support the evidence for a dominant gene for breast cancer (Table 5). All studies except our analysis of the Jacobsen data (Iselius et al. 1990) neglected specific mortality in the definitions of morbid risk. Some studies also neglected that probands should be drawn a t random from affected individuals and not through probands with bilateral disease or premenopausal onset. One study used age of onset instead of current age for the liability indicator which also violates the POINTER logic. All studies favour a dominant gene, but estimates of gene frequency and penetrance vary. The gene frequencies vary less for the population-based samples (0~00064~0030) than studies of families ascertained through high- risk pedigrees (00002-0.0134). This wide variation for the high-risk pedigrees is likely to be caused by the little information that can be obtained for the gene frequency in studies of one or a few high-risk pedigrees. Except for one study the estimates of penetrance are more similar, with a value around 0.8. We believe that the estimates from the population-based series are more reliable and should be used for linkage analysis and genetic counselling.

Some methods of segregation analysis assume that risk for a given age is the cumulative distribution of reported age of onset. This is doubly wrong, since it neglects specific mortality and assumes that reported age of onset is exact, whereas in fact it refers to different symptoms, diagnostic procedures, and pathological stages. Therefore affection and age of onset should be treated as separate variables, requiring an extension of segregation analysis. Even without such


Table 5. Segregation analysis of breast cancer by study

Dominant model (d = 1 ) Lifetime

Authors Displacement Gene frequency penetrance Comment Bishop & Gardner (1980) 1‘9 0.0056

Go et al. (1983) z z

Jacobsen (1946) analysed by

Williams & Anderson (1984) 1‘7 0.0076 Iselius et al. (1990) I .8 0~0092

Cannon et al. 1986 ? 0 0 I34

Goldstein et al. (1987) 2.8 0.00 I 4

Newman et al. (1988) 2‘3 0.0006

0’0002 Bishop et al. (1988) 1

This study I .96 0.0030

0.84

2 0.9

0.57 0.78

- 0.8

1

0.82

- 0 8 4

0.83

One selected pedigree. Ascertainment and prevalence not specified

High-risk pedigrees with a t least three affected first- degree relatives. Ascertainment and prevalence ignored

Possible enrichment of premenopausal onset

Neglecting specific mortality Incorporating specific

mortality High-risk pedigrees with at

least three affected first- degree relatives

Bilateral probands, age of onset substituted for current age

age of onset substituted for current age

correction of high-risk pedigrees

Premenopausal probands,

‘Ascertainment event ’

extension, this study shows that, analysed with care, selected families can give useful genetic information that is consistent with other evidence. However, the analysis could be improved with respect to ascertainment and ancillary information. The mode of ascertainment can be made much more precise, allowing more rigorous analysis of segregation and especially of associated cancers. For example, each consultand might be asked to choose one of the following reasons for participation :

( a ) two or more close relatives with breast cancer ; (b) a close relative with bilateral or early onset breast cancer ; ( c ) two or more close relatives with cancer, a t least one of them with breast cancer ; ( d ) a close relative with unilateral or late onset breast cancer; ( e ) other (please specify).

Then each category could be analysed appropriately, and there would be no danger of confounding selection with biological association. Failure to specify ascertainment precisely is the main obstacle to exact segregation analysis, which is the sine qua non for eficient mapping of cancer genes. Ascertainment bias is no more difficult to control €or other cancers, where the search for linkage is being pursued in ignorance of genetic parameters.

Some relevant information, which we call severity and diathesis, is not currently used in segregation analysis. Severity is defined only for affected individuals and may include age of onset, bilaterality, and other variables predictive of liability among affected. Diathesis is

H G E 55 I 1


restricted to normals and may include associated cancers, their age of onset, cystic breast disease and other variables predictive of liability in unaffected persons. Severity and diathesis are ordinal polychotomies, but in other applications diathesis might be a quantitative variable. Use of severity removes the requirement that probands be drawn at random from affection within a given liability class. Then restriction of probands to bilateral or premenopausal cases would not bias segregation analysis, which could be extended from the liability model to ordinal logistic models. The main problem in such analysis is posed by common traits with a low relative risk for affection (like nevi and melanoma), where heritability of the trait might distort evidence for a rare major gene predisposing to affection. Such problems cannot be resolved until segregation analysis is generalized to include severity and diathesis, for which breast cancer provides a good application.

We thank the ICRF pedigree workers, Elspeth McCarter and Shiobhan Harrington, for their help in taking family histories.

REFERENCES

ANDERSON, D. E. (1974). Genetic study of breast cancer: identification of a high risk group. Cancer 34,

ANDERSON, D. E. (1972). A genetic study of human breast cancer. J. Nat. Cancer. Inst. 48, 1029-1034. ANDRIEU, N., DEMENAIS, F. & MARTINEZ, M. (1988). Genetic analysis of human breast cancer: implications for

family study designs. Genet. Epidemiol. 5 , 225-233. BISHOP, D. T., CANNON-ALBRIGHT, L., MCLELLAN, T., GARDNER, E. J. & SKOLNICK, M. H. (1988). Segregation

and linkage analysis of nine Utah breast cancer pedigrees. Genet. Epidemiol. 5 , 151-169. BISHOP, D. T. & GARDNER, E. J. (1980). Analysis of the genetic predisposition to cancer in individual pedigrees.

In Cancer Incidence in Dejined Populations, Banbury report 4, pp. 389-406. New York : Cold Spring Harbor Laboratory.

BURKI, N., BUSER, M., EMMONS, & 5 OTHERS (1990). Malignancies in families of women with medullary, tubular and invasive ductal breast cancer. Eur. J. Cancer 26, 295-303.

CANNON, L. A., BISHOP, D. T. & SKOLNICK, M. H. (1986). Segregation and linkage analysis of breast cancer in the Dutch and Utah families. Genet. Epidemiol. Suppl. 1, 4348 .

DEMENAIS, F., MARTINEZ, M., BONA~TI-PELLIE, C., CLERGET-DARPOUX, F. & FEINGOLD, N. (1986). Segregation analysis of the Jacobsen data. Genet. Epidemiol. Suppl. 1, 49-54.

GARFINKEL, L., CRAIG, L. & SEIDMAN, H. (1959). An appraisal of left and right breast cancer. J. Nat. Cancer Inst. 23, 617-631.

Go, R. C. P., KING, M.-C., BAILEY-WILSON, J., ELSTON, R. C. & LYNCH, H. T. (1983). Genetic epidemiology of breast cancer and associated cancers in high-risk families. I . Segregation analysis. J. Nut. Cancer Inst. 71, 455-461.

GOLDSTEIN, A. M., HAILE, R. W. C., MARAZITA, M. L. & PAGANINI-HILL, A. (1987). A genetic epidemiologic investigation of breast cancer in families with bilateral breast cancer. I. Segregation analysis. J. Nut. Cancer Inst. 78, 911-918.

IARC (1987). Cancer Incidence in Five Continents, vol. 5 . (ed. C. Muir, J. Waterhouse, T. Mack, J. Powell & S. Whilan). International Agency for Research in Cancer. Published 1988, Lyon.

ISELIUS, L., LITTLER, M. & MORTON, N. E. (1990). Transmission of breast cancer - a controversy resolved. (Submitted).

JACOBSEN, 0. (1946). Heredity and Breast Cancer. London: H. K. Lewis. LI, F. B. & FRAUMENI, J. F. (1969). Soft tissue sarcomas, breast cancer and other neoplasms: a familial

LYNCH, H. T. & KRUSH, A. J. (1971). Carcinoma of the breast and ovary in three families. Gynecol. Obstet. 133,

LYNCH, H. T., GUIRGIS, H., BRODKEY, & 4 OTHERS (1976). Early age of onset in familial breast cancer. Arch. Surg. 111, 12G131.

LYNCH, H. T., LANSPA, S. J., BOMAN, B. M., SMYTH, T., WATSON, P., LYNCH, J. F. et al. (1988). Hereditary non- polyposis colorectal cancer, Lynch syndromes I and 11. Gastroenterology Clinics of North America 174, 679-715.

LYNCH, H. T., MARCUS, J. M., WATSON, P., CONWAY, T., FITZSIMMONS, M. L. & LYNCH, J. F. (1989). Genetic epidemiology of breast cancer. In Genetic Epidemiology of Cancer (ed. H. T. Lynch & T. Hirayama).

lOW1097.

syndrome? Ann. Intern. Med. 71, 747-751.

644-648.


MORTON, N. E., RAO, D. C. & LALOUEL, J.-M. (1983). Methods in Genetic Epidemiology. Basel: Karger. MURATA, M., KUNO, K. , FUKAMI, A. & SAKAMOTO, G. (1982). Epidemiology of familial predisposition for breast

cancer in Japan. J . Nut. Cancer Inst. 69, 1229-1234. NEWMAN, B., AUSTIN, M. A., LEE, M. & KING, M . 4 . (1988). Inheritance of human breast cancer: evidence for

autosomal dominant transmission in high-risk families. Proc. Natl. A d . Sci. USA 85, 3044-3048. OTTMAN, R., PIKE, M. C., KING, M.-C., CASAORANDE, J . T. & HENDERSON, B. E. (1986). Familial breast cancer

in a population-based series. Am. J . Epidemiol. 123, 15-21. PENROSE, L. S., MACKENZIE, H. J. & KARN, M. N. (1948). A genetical study of human mammary cancer. Ann.

Eugen. 14, 236266. SCHIMKE, N. (1985). Dominant inheritance in human cancer. In Geneties in Clinical Oncology (ed. R. S. K .

Chaganti & J . L. German), pp. 103-121. Oxford: Oxford University Press. WILLIAMS, C. J . (1985). Managing families genetically predisposed to cancer. ‘The Cancer Family Syndrome’.

In Genetics in Clinical Oncology (ed. R. S. K. Chaganti & J. L. German), pp. 222-240. Oxford: Oxford University Press.

WILLIAMS, W. R. & ANDERSON, D. E. (1984). Genetic epidemiology of breast cancer: segregation analysis of 200 Danish pedigrees. Genet. Epidemiol. 1, 7-20.

11-2

Documents

Genetic epidemiology of breast cancer in Britain