Search

Abdominal fat has been shown to be an important risk factor for many chronic conditions, including diabetes, heart disease, and breast cancer. The objective of this study was to provide evidence for a major gene influence on the ratio of waist to hip circumference (WHR), a measurement commonly used in large scale studies to indicate the presence of abdominal fat. Segregation analysis was conducted on three subsets of families from the Minnesota Breast Cancer Family Study. One analysis was conducted among families with WHR measurements on all women. Two additional analyses were conducted on subsets of women stratified on menopausal status. Multiple regression analysis was used to identify factors associated with WHR expressed as a continuous trait. Complex segregation analyses were performed on the continuous trait of WHR and the covariates identified in the regression analysis. In the analysis of all women, all hypotheses were rejected. Among premenopausal women, the environmental hypothesis with no heterogeneity between generations fit the data best (P = 0.85). However, among postmenopausal women, the requirements for conclusion of the presence of a major gene were met. All non-Mendelian hypotheses were rejected (P < 0.0001), but the additive hypothesis was not rejected (P = 0.19) and provided the best fit to the data. The putative major gene identified by this model accounted for 42% of total phenotypic variance in WHR among these postmenopausal women. The allele for high WHR had a frequency of 27%. These findings support the hypothesis that the distribution of abdominal fat in postmenopausal women is under genetic control., (Copyright 2001 Wiley-Liss, Inc.)

Although many segregation analyses of breast cancer have been published, few have included risk factor covariates. Maximum likelihood segregation analyses examining age-at-onset (model 1) and susceptibility (model 2) models of breast cancer were performed on 426 four-generation families originally ascertained between 1944 and 1952 through a breast cancer proband. Cancer status and risk factor data were collected through interviews of participants or surrogates. When segregation analyses were performed on 10,791 women, without estimation of any covariates, all hypotheses under both models were rejected. Model 1, which required estimation of fewer parameters than model 2, provided a better fit to the data according to Akaike's Information Criterion. Further segregation analyses were performed under model 1 on a subset of women with complete data on education, age at first birth (nulliparous women included), and alcohol use, covariates that were found to significantly (P<0.05) improve the fit over the addition of exam age alone in logistic regression models. All three covariates improved the fit of the models, as did year of birth, but at all stages of model building, all of the hypotheses were still rejected. After the allele frequency was fixed at 0.0033, a subset of families appeared to fit a dominant model. Using this model, risk estimates were calculated based on inferred genotype, age, and covariate values. The penetrance was estimated to be 0.15, much lower than previous estimates based on families ascertained through breast cancer probands with early onset. Moreover, the estimates of penetrance were not greatly influenced by incorporation of the measured risk factors.

A positive family history is a risk factor for many chronic diseases, including most cancers, coronary heart disease, and diabetes. Since diet is also associated with most chronic diseases, one possible explanation for non-Mendelian familial clustering is shared eating habits. Food frequency data were obtained on 3,515 sisters in the Iowa Women's Health Study, a prospective cohort of postmenopausal women. Intraclass correlations between sisters were computed on a range of energy-adjusted nutrients to determine whether dietary intakes were more similar among siblings than among unrelated individuals. Two methods were used to calculate correlations: analysis of variance modeling and weighted sibling correlations. F-tests and randomization tests were used to determine statistical significance. The intraclass correlations for all of the nutrients examined were statistically significantly greater than the hypothesized value of zero (P < 0.05). Representative correlations include dietary fiber (0.15), animal fat (0.12), vegetable fat (0.13), calcium (0.14), iron (0.04), cholesterol (0.08), sodium (0.10), vitamin D (0.16), and total energy intake (0.11). When corrected for measurement error, the magnitude of these correlations increased, on average 62%. Although modest in magnitude, these correlations may be high enough to influence familial clustering of complex diseases that are attributed, in part, to diet.

Proper control of environmental factors can be crucial to the identification of genes that influence susceptibility to a complex trait, especially for a trait such as lung cancer, for which the environmental factor (smoking) accounts for a significant etiologic fraction of the disease. An earlier segregation analysis of 337 Louisiana families, which incorporated direct measure of tobacco consumption, provided evidence for autosomal codominant inheritance of a major gene that influenced age at onset of lung cancer. Subsequent analyses were performed in which the families were stratified into two subsets based on birth cohort of the proband; results suggested the presence of heterogeneity that were postulated to reflect the influence of cohort trends in tobacco consumption. To evaluate this hypothesis further, we simulated a population of three-generation pedigrees in which an autosomal dominant mode of susceptibility to lung cancer was transmitted, but tobacco use varied across generations corresponding to published trends in smoking. A total of 200,000 individuals in families of various sizes, ages, and cigarette smoking habits were simulated from 1900 to 1980. From this population, 324 families (2,405 individuals) with 380 cases of lung cancer were ascertained through 328 lung cancer probands. Complex segregation analysis was performed using the REGTL program of S.A.G.E. in which pack-years of tobacco exposure were incorporated directly into the likelihood calculations. Although the no major gene, environmental, and Mendelian recessive hypotheses were rejected, both dominant and codominant transmission provided a good fit to the data. Thus in a population of simulated families with autosomal dominant susceptibility to lung cancer, intergenerational differences in tobacco consumption led to the detection of autosomal codominant transmission as an acceptable hypothesis. These results underscore the potential danger of segregation analysis of complex traits in which exposure to known environmental influences may differ across generations.

Since the manifestation of a complex disease is likely to be influenced through multiple genetic and/or environmental pathways, it may be advantageous to adjust for these multiple factors in a genetic analysis of a complex quantitative trait. Sib-pair linkage analysis was performed on the simulated complex quantitative trait Q1 after adjustment for age, sex, and the environmental factor (i.e., minimally adjusted) and all combinations of the four intermediate phenotypes Q2, Q3, Q4, and Q5 (n = 15) for all 200 replications of the nuclear families data set. From the minimally adjusted Q1, the power to detect suggestive linkage to any of the three loci affecting Q1 was 0.585 with a false positive rate of 0.0025. Adjusting Q1 for Q3 increased the power to detect suggestive linkage to 0.860 with a similar false positive rate. Additional adjustments for Q2, Q4, and Q5 yielded no substantial improvements in power nor changes in the false positive rate. The power to detect significant linkage was also substantially improved after adjustment of Q1 for Q3 with no change in the false positive rate. The adjustment of a complex trait for other factors in the causal pathway reduces the phenotype variability and enhances the ability to detect linkage.

Systematic errors, or bias, can arise at several stages of a study, including selection of subjects, measurement of exposure and disease, and data analysis. Little attention appears to have been paid to potential sources of bias in genetic epidemiologic studies, despite the fact that the study of units (families) and members (relatives) within those units produces unique opportunities for bias to be introduced. The ability to evaluate whether selection bias has occurred is rare. In 1944, a case-control family study of breast cancer was initiated at the Dight Institute for Human Genetics at the University of Minnesota. A follow-up study of these 544 families is currently being conducted on sisters, daughters, nieces, and granddaughters of the probands, and a control group of women who are spouses of male first- and second-degree relatives. Updated data are collected on females who are 18 years or older through telephone interviews and questionnaires. The availability of detailed family history information on these families at baseline provided an opportunity to evaluate several potential sources of bias. Analyses were performed to determine if families lost to follow-up differed from those who were successfully located or excluded (ineligible), and whether participation rates within a family differed by relationship to proband, age, and family history of cancer. The latter participation rates for individuals were examined with respect to a telephone interview, a mailed questionnaire, and screening mammography. There were no statistically significant differences in the cancer histories of families that were excluded, those that were lost to follow-up, and those that participated. Within families, degree of relationship to the breast cancer proband was significantly associated with age-adjusted participation rates on mailed questionnaires (P < 0.005) and mammography (P < 0.005), but not telephone interviews (P = 0.29). After adjustment for age, marry-ins with a family history of breast cancer were not significantly more likely than marry-ins without a family history to undergo mammography (P = 0.11) or return mailed questionnaires (P = 0.74). Although non-participation is a potentially serious source of bias to a genetic epidemiologic study and the effect of variable participation rates should be explored when investigating the genetic component of a disease, it does not appear to be a problem for this particular study.

Most segregation analyses of breast cancer susceptibility have modeled the effect of the major gene on the age-at-onset distribution. However, in families linked to BRCA1 or BRCA2, there is wide variation in the age-at-onset among gene carriers. We performed a segregation analysis of 544 Minnesota breast cancer families using models which parameterized the putative major gene effect in two ways: earlier age-at-onset, with a common level of susceptibility (model I), and greater susceptibility, with a common mean age-at-onset (model II). Five hypothetical modes of transmission and an unrestricted general hypothesis were fitted to the data. Twice the difference between the log(e) likelihood for the data under the specified hypothesis (recessive, no major gene, etc.) and the log(e) likelihood under the general hypothesis is distributed asymptotically as a chi-square statistic with the degrees of freedom equal to the difference in the number of parameters estimated. This difference was compared to the critical value for the chi-square distribution to assess goodness-of-fit. Under model I, both Mendelian and non-Mendelian hypotheses were rejected. When model II was used, the non-Mendelian hypotheses were rejected whereas all Mendelian hypotheses were not. Mendelian recessive inheritance of a common allele (qA = 0.11) with a high penetrance (87%) provided the best fit to the data. We then stratified the families into two subsets based on the age at diagnosis of the proband [< or = 55 years (n = 265) versus > 55 years (n = 279)]; there was no evidence of heterogeneity under either model (I or II). These data suggest that, in some breast cancer families, the effect of the putative susceptibility gene is better represented as increasing overall susceptibility to breast cancer rather than as a shift in the age-at-onset distribution.

There are recent data to suggest that risk factors for breast cancer may differ according to whether the tumor expresses detectable levels of the estrogen receptor (ER) and progesterone receptor (PR). While a family history of breast cancer is one of the most consistent predictors of the disease, we recently reported a modest inverse association with ER+PR- tumors. However, the definition of a family history of cancer did not consider second-degree relatives or cancer sites that may be etiologically related. The current report presents additional data analysis from the Iowa Women's Health Study, a prospective population-based cohort study conducted among 41,837 postmenopausal women. At baseline in 1986, respondents provided information on family history of cancers of the breast, ovaries, or uterus/endometrium in their mothers, sisters, daughters, maternal and paternal grandmothers, and maternal and paternal aunts. Data on family history of prostate cancer in fathers and brothers and age at onset of breast cancer in mothers and sisters were collected in 1992. Cohort members were followed for cancer incidence through the statewide tumor registry. After 7 years and more than 235,000 person-years of follow-up, 939 incident cases of breast cancer were identified. Information was obtained from the tumor registry on ER (+/-) and PR (+/-) status for 610 cases (65.0%). A family history of breast cancer in first-degree relatives was associated with increased risk (relative risk [PR] = 1.4; 95% confidence interval [CI]: 1.1-1.6) for all receptor-defined subtypes of breast cancer except ER+PR- tumors (RR = 0.7; 95% CI: 0.3-1.4). These results were unchanged when data on second-degree relatives were included. When the onset of breast cancer in relatives occurred at or before the age of 45 years, increased risks were evident only for ER-PR+ and ER-PR- tumors (RR = 2.3 and 3.3, respectively). Conversely, when relatives were affected with breast cancer after the age of 45 years, increased risks were most apparent for ER+PR+ and ER-PR+ tumors (RR = 1.3 and 3.2, respectively). A family history of prostate cancer in first-degree relatives was associated with a 1.2-fold increased risk of breast cancer (95% CI: 0.98-1.50), largely a reflection of the association with ER-PR- tumors (RR = 1.5; 95% CI: 0.8-3.0). The small numbers of cases in some categories and the corresponding wide CIs preclude definitive conclusions, but these data are at least suggestive that joint stratification of breast tumors on ER and PR status may be useful in partitioning breast cancer families into more homogeneous subsets.

In 1944, a case-control family study was initiated at the Dight Institute for Human Genetics at the University of Minnesota to study the influences of childbearing breastfeeding, and hereditary susceptibility on the occurrence and age-of-onset of breast cancer. Index cases (probands) were women ascertained at the Tumor Clinic of the University of Minnesota Hospital. Medical history and life style information were obtained on probands and relatives, and all cancers were histologically verified. A total of 544 families were studied, with probands diagnosed between 1931 and 1952. All of the records and pathology slides have been maintained from the original study; for most probands this includes the original tissue blocks. We are conducting a historical cohort study of selected of selected first- and second-degree female relatives (sisters, daughters, nieces, granddaughters) of the probands and a group of control women identified as the spouses of all male first- and second-degree relatives (brothers, sons, grandsons, and nephews). The subsequent development of breast cancer is being determined to quantify the absolute risk associated with a positive family history. Current disease status is ascertained with mammography, and stromal density is measured using digital imaging. Segregation analysis will be applied to examine how non-genetic factors such as diet, exogenous hormone use, and body fat distribution influence risk in women at high risk because of family history. A subset of families are being selected for molecular analysis of the BRCA1 gene or for linkage analyses to identify putative susceptibility loci other than BRCA1. Documented cancer histories were known for at least three generations, and the current study extends the pedigrees up to four or five generations for every family, allowing a detailed description of familial risk. This cohort study of breast cancer families is likely to be important in both quantity and quality of data and will serve as a major genetic epidemiologic resource, being free of selection bias and having relevant non-genetic exposure determined in at least four generations.

Inheritance of a major susceptibility gene for breast cancer has been primarily investigated in families with early-onset disease. However, familial clustering of late-onset breast cancer is well documented, and genetic factors may also be relevant. In the Iowa Women's Health Study, we evaluated evidence for a major gene after allowing for measured environmental risk factors. Two hundred sixty-five incident breast cancer probands were identified from a prospective cohort study of 41,837 women aged 55 to 69 years at baseline in 1986. A pedigree development form was mailed to the probands to ascertain all first-degree female relatives. A questionnaire and body measurement protocol were mailed to identified living relatives or surrogates. Segregation analyses were conducted on a total of 1,145 women in 251 families using regressive models as implemented in S.A.G.E. Mendelian codominant inheritance of an allele that produced an earlier-age-at-onset provided the best fit to the data. Incorporation of measured environmental risk factors as covariates yielded no significant improvements in the likelihoods. Approximately 50% of this population could be expected to carry a late-onset breast cancer susceptibility gene, and 23% of the population is susceptible because of the environment in which they live. Homozygous gene carriers are predicted to have a mean age-at-onset of 48 years, over 20 years earlier than heterozygotes; few cases would be expected among non-gene carriers. In conclusion, the transmission pattern of late-onset breast cancer may be determined by a common susceptibility gene.

The aggregation of colon, endometrial, ovarian, and possibly breast cancers in families has been described as a "cancer family syndrome" (now called Lynch syndrome II). To determine if the familial clustering of these malignancies was more common in women with cancer than without, we analyzed data from the Iowa Women's Health Study (IWHS), a population-based sample of 41,837 women aged 55-69 years. Self-reported information was collected on history of colon, uterine, ovarian, and breast cancers in female first-degree relatives. A family history of cancer of the breast (odds ratio [OR] = 1.4), colon (OR = 1.3), and uterus (OR = 1.3), but not ovary (OR = 1.2), was significantly more common among women with a personal history of any of these four cancers (all P < 0.05); the pattern of the ORs suggested strongly that the clustering tended to be site-specific. Age-adjusted relative risks (RR) of incident colon cancer over 5 years of follow-up (N = 237) were calculated with regard to family history. Colon cancer incidence was increased among women with a family history of breast (RR = 1.3), uterine (RR = 1.4), colon (RR = 1.5), and ovarian (RR = 1.3) cancers, although none of the risk estimates achieved statistical significance. RR was, however, significantly related to the number of different cancer sites reported among family members (Ptrend = 0.008). These data on a representative sample of postmenopausal women suggest that family histories of colon, breast, uterine, and ovarian cancers are associated with an increased risk of cancer at the same site, but provide little support for the hypothesis that Lynch syndrome II is a non-random occurrence.

Data on 337 lung cancer families were analyzed to determine if known cohort differences in parental cigarette consumption influence parameters from a segregation analysis. Previous results suggested that, after allowing for an individual's pack-years of tobacco exposure, Mendelian codominant inheritance of an allele that produced an earlier age of onset provided a good fit to the data. In the present study, the data were split into two groups of families: probands age 60 and over (born before WWI) and probands younger than age 60. This partition of the data by age of the proband was done to separate families in which there were parents who were less likely to smoke from those with parents more likely to smoke--predicated on the known increase of smoking prevalence after World War I. For the younger proband families (those with parents more likely to smoke), only Mendelian codominant inheritance adequately fit the data. The hypotheses of no major type, environmental transmission, and Mendelian dominant or recessive inheritance were rejected. In contrast to our earlier findings, the estimate of population susceptibility increased from 28% in the total data to 60% in this subset. In the older proband families (those with parents less likely to smoke), the no major type and environmental hypotheses were rejected; further, none of the Mendelian models could be distinguished. Our results demonstrate that cohort differences, probably in exposure to tobacco, can confound parameters of a segregation analysis, and suggest that the genetic component of lung cancer may be greater than previously estimated. It further suggests that susceptibility to lung cancer occurs as a function of susceptibility to the effects of tobacco smoking.

The familial aggregation of certain chronic diseases is well documented [Perkins, 1986; King et al., 1984; Anderson, 1982]. Dietary data on adult brothers living apart were used to examine whether familial clustering of disease could be explained by nature or nutriture. Intakes of nutrients were strikingly more similar among siblings than expected: when correlations were adjusted for country of residence, 21 of 25 (84%) were statistically significant. Thus, dietary patterns among adult siblings are more alike than could be predicted by their sharing a common culture, as alike as has been described for monozygotic twins, and as alike as described for familial correlations of serum cholesterol. Incorporation of dietary measures in co-twin studies or studies of siblings can improve the estimates of the true genetic effect on disease pathogenesis.

A number of studies have documented the familial aggregation of lung cancer; there is at least one report that female reproductive cancers are also increased in these families. To determine if the risk exists for all reproductive cancer sites, we conducted a nested case-control study of lung cancer incidence in a cohort of 41,837 women ages 55-69 years. Women were recruited by mail and asked to provide information on education, occupation, smoking habits, physical activity, and family history of specific cancer sites among female relatives. Four year follow-up for cancer incidence was conducted using a state-wide tumor registry. Compared to random controls (n = 1900), cases (n = 152) were more likely to have reported at baseline a sister affected with cancer of the uterus [crude odds ratio (OR) = 3.4, 95% Cl = 1.7-7.0, P less than 0.01], cervix (OR = 3.2, 95% Cl 1.2-8.6, P less than 0.05), or cancer at any site (OR = 1.6, 95% Cl 1.1-2.4, P less than 0.05). A family history of an affected mother with a female reproductive cancer was also more common among the cases, but not statistically significant. Cases were less educated, more likely to work in a technical/industrial setting, less physically active, more likely to smoke, and to smoke for a longer period of time than the controls (all P less than 0.01). These differences reduced the magnitude of the family history risk indicators; only the combined category of reproductive cancer at all sites among sisters remained statistically significant. Additional family studies should be done to assess environmental factors in the relatives of the cases and controls to disentangle the influence of shared genes and shared environmental factors in these associations.

A large pedigree (N = 356) with a high prevalence of heart disease and associated adverse lipoprotein phenotype was studied. The adverse lipoprotein phenotype is characterized by both low levels of high-density-lipoprotein cholesterol (HDL-C) alone (16.3%) and in combination with other adverse lipoprotein levels (12.8%). In all, 44.2% of all pedigree members had at least one adverse lipoprotein level. Analysis of mating types showed that all lipids and lipoproteins possess familial clustering with 25-36% of offspring above median levels when both parents had levels below the median, while 67-83% had levels above the median when both parents had levels above the median. Using adjusted lipid and lipoprotein levels, a statistically significant linear trend was found between the degree of relationship to pedigree members with heart disease, and both the low-density-lipoprotein cholesterol/high-density-lipoprotein cholesterol (LDL-C/HDL-C) ratio (P less than .05), and the very-low-density-lipoprotein cholesterol (VLDL-C; P less than .01) level. A similar analysis using the prevalence of adverse lipoprotein levels as the dependent variable and degree of relationship to heart diseased pedigree numbers as the independent variable showed significant (P less than .05) relationships with VLDL-C and the LDL-C/HDL-C ratio. Further genetic analyses of this pedigree may reveal genetic mechanisms responsible for the familiality of lipoprotein levels in this pedigree.

Several investigators have reported that relatives of lung cancer probands have a greater-than-normal likelihood for developing some form of cancer. To evaluate whether this familial risk is general for probands with cancer at any site or limited to lung cancer probands, we did a case-control study in which probands having cancer affecting any body site were identified and their pedigree data were tabulated. Telephone interviews and a mailed questionnaire were used to obtain cancer histories and environmental exposures on the families of 41 lung cancer probands, 105 probands with cancer other than lung, and 127 spouse families. Cumulative tobacco exposure (P less than .05), occupational hazards (P less than .005), and age of the family relatives (P less than .0001) were found to be statistically significant predictors of cancer risk. With consideration given for these variables, we determined that siblings of lung cancer probands were at slightly greater risk of cancer of any kind (odds ratio [OR] = 1.43, P = .06) than siblings in the control group. Much of the elevated risk was attributable to an excess of lung cancer (OR = 2.49, P = .06). Siblings of non-lung/non-breast cancer probands were also determined to be at increased risk of lung cancer as well (OR = 1.61, P = .06). For parents, the risk was lower, although parental information may have been underreported.