Estimating Disease Prevalence Using Relatives of Case and Control Probands

Summary .  We introduce a method of estimating disease prevalence from case–control family study data. Case–control family studies are performed to investigate the familial aggregation of disease; families are sampled via either a case or a control proband, and the resulting data contain information on disease status and covariates for the probands and their relatives. Here, we introduce estimators for overall prevalence and for covariate-stratum-specific (e.g., sex-specific) prevalence. These estimators combine the proportion of affected relatives of control probands with the proportion of affected relatives of case probands and are designed to yield approximately unbiased estimates of their population counterparts under certain commonly made assumptions. We also introduce corresponding confidence intervals designed to have good coverage properties even for small prevalences. Next, we describe simulation experiments where our estimators and intervals were applied to case–control family data sampled from fictional populations with various levels of familial aggregation. At all aggregation levels, the resulting estimates varied closely and symmetrically around their population counterparts, and the resulting intervals had good coverage properties, even for small sample sizes. Finally, we discuss the assumptions required for our estimators to be approximately unbiased, highlighting situations where an alternative estimator based only on relatives of control probands may perform better.     

Combined association,segregation and aggregation analysis on case-control family data

Recently genetic epidemiologists have begun using case-control family study designs to investigate the role of genetic and environmental risk factors in disease etiology. The objective of these studies is to assess the association of environmental factors with the disease trait; to characterize the disease genes using segregation analysis; and to quantify the residual familial aggregation after controlling for environmental and genetic factors. Typically these objectives are achieved by conducting separate studies and analysis. This paper describes an estimating equation based approach for a combined association, segregation and aggregation analysis on data from case-control family studies. Simulations indicate that the method performs well in a variety of settings. The method is illustrated using simulated family history data made available to participants in a recent Genetic Analysis Workshop.     

A semiparametric method for analyzing matched case-control family studies with a continuous outcome and proband sampling

We consider matched case-control familial studies which match a group of patients, called "case probands," with a group of disease-free subjects, called "control probands," using a set of family-level matching variables. Family members of each proband are then recruited into the study. Of interest here is the familial aggregation of the response variable and the effects of subject-specific covariates on the response. We propose an estimating equation approach to jointly estimate the main effects and intrafamilial correlations for matched family studies with a continuous outcome. Only knowledge of the first two joint moments of the response variable is required. The induced estimators for the main effects and intrafamilial correlations are consistent and asymptotically normally distributed. We apply the proposed method to sleep apnea data. A simulation study demonstrates the usefulness of our approach.     

Approaches to familial aggregation: hypothesis testing and estimation when families are selected through parent probands under a variant of single ascertainment

Epidemiologic approaches to testing and estimating familial aggregation of a disease consist of comparing rates of disease in relatives of individuals with the disease (known as case probands) with rates of disease in relatives of individuals without the disease (known as control probands). Gold et al. (J Am Stat Ass 1967;62: 409-420) derived an explicit mathematical model and sampling methods, under which this approach is equivalent to testing the null hypotheses that the disease risk in families is homogenous. A basic assumption of this model is that every family member has the same risk of disease and that disease status is independent among family members, although the disease risk may vary between families. When the disease is suspected of having a genetic component, rather than being purely environmental, this model has been shown to be appropriate for detecting disease aggregation in siblings, when relatives are siblings of probands. This model however is unrealistic for use in nuclear families when the affected status of offspring is not independent of the affected status of parents, and these families are selected through an affected or an unaffected parent, so that a parent is the proband and relatives are offspring of probands. We extend the Gold et al. model to allow for the disease risk in offspring to vary with the affected status of the parent. We assume that families are selected through affected and unaffected parents, under a variation of single ascertainment. Under this study design, we show that the usual test of association between affected status of probands and relatives, performed by comparing sample proportions of affected relatives of affected and unaffected probands, respectively, is no longer equivalent to a test of homogeneity of disease risk in offspring. Instead, it is equivalent to testing that the disease risk in offspring is independent of the number of affected parents. This test reduces to a test of homogeneity if and only if one assumes that the variation in disease risk in offspring, between families, is solely due to the variation in the number of affected parents. As a result, we show that under this study design, the standard chi2 test must be modified in order to obtain a valid test of familial aggregation. In addition the sample proportions of affected relatives of case and control probands, respectively, are shown to provide unbiased estimates of the expected risk of disease in an offspring given an affected/unaffected parent. We apply these results to methods of sample selection and discuss the practical implications of these findings.     

Inheritance of acute appendicitis: familial aggregation and evidence of polygenic transmission.

We explored familiality as well as the heritability and possible mode(s) of inheritance of acute appendicitis in childhood and early adolescence. Our case-control study showed that a positive family history for reported appendectomy was significantly more frequent in families of 80 consecutive patients eventually proved to have histopathologic acute appendicitis than in families of surgical controls matched for sex, age, and number of siblings. The relative risk was 10.0 (95% confidence limits 4.7-21.4). The pattern of familial aggregation was further supported by the fact that the age-standardized morbidity ratio was four times greater among family members of cases than among controls. We then applied the unified mixed model of segregation analysis, as implemented in the computer program POINTER, to a new set of 100 multigenerational pedigrees of children with histopathologically confirmed acute appendicitis that were broken down into 674 nuclear families. Age-specific morbidity risk and lifetime incidence of acute appendicitis were estimated from relatives of controls matched for age and sex to probands. Complex segregation analysis supported a polygenic or multifactorial model with a total heritability of 56%. There was no evidence to support a major gene, although a rare gene could not be ruled out as the cause of a small proportion of cases. Specific studies to address genetic and environmental factors in this serious disease seem worthwhile; but, for now, a positive family history of appendicitis might join other evidence leading to improved clinical recognition of acute appendicitis.     

A marginal likelihood approach for estimating penetrance from kin-cohort designs

The kin-cohort design is a promising alternative to traditional cohort or case-control designs for estimating penetrance of an identified rare autosomal mutation. In this design, a suitably selected sample of participants provides genotype and detailed family history information on the disease of interest. To estimate penetrance of the mutation, we consider a marginal likelihood approach that is computationally simple to implement, more flexible than the original analytic approach proposed by Wacholder et al. (1998, American Journal of Epidemiology 148, 623-629), and more robust than the likelihood approach considered by Gail et al. (1999, Genetic Epidemiology 16, 15-39) to presence of residual familial correlation. We study the trade-off between robustness and efficiency using simulation experiments. The method is illustrated by analysis of the data from the Washington Ashkenazi Study.     

Extended Mantel-Haenszel estimating procedure for multivariate logistic regression models

A class of estimating functions is proposed for the estimation of multivariate relative risk in stratified case-control studies. It reduces to the well-known Mantel-Haenszel estimator when there is a single binary risk factor. Large-sample properties of the solutions to the proposed estimating equations are established for two distinct situations. Efficiency calculations suggest that the proposed estimators are nearly fully efficient relative to the conditional maximum likelihood estimator for the parameters considered. Application of the proposed method to family data and longitudinal data, where the conditional likelihood approach fails, is discussed. Two examples from case-control studies and one example from a study on familial aggregation are presented.     

Familial Aggregation of Morbid Obesity

Recent studies have shown major gene effects for obesity in randomly ascertained families. To investigate the familial aggregation of a specific subset of obesity, which is particularly prone to medical complications, families with morbid obesity were studied. This condition occurs in 1%-2%of the population and is defined as 45.5 kg (100 pounds) or more over ideal weight. First-degree relatives of 221 morbidly obese probands (1560 adults) were identified, and height and weight (current and greatest) were obtained from each family member. Morbid obesity occurred in the family members of the probands 8 times more often than in the general population. Of the morbidly obese probands, 48% had one or more first-degree relatives who were also morbidly obese compared to a 6% population estimate. By the ages of 20–24, 12% of the morbidly obese probands were already 45.5 kg or more overweight, and 45% were 22.7 kg (50 pounds) or more overweight. There was little difference in the prevalence of familial morbid obesity by the gender of the probands: 47% of the male probands and 48% of the female probands had another morbidly obese relative, while 67% and 53% of the early onset (before age 25) male and female probands, respectively, had one or more first-degree relatives who were also morbidly obese. In addition to the extreme degree of familial aggregation, the prevalence of morbid obesity in parent-offspring sets was calculated within the morbidly obese families. Morbidly obese families who have one or two morbidly obese parents have a 2.6 times increased risk (p<0.002) of having one or more morbidly obese adult offspring, compared to families who have neither parent morbidly obese. Evidence for trimodality of the body mass index distribution was found for each gender (p = 0.0006 for male relatives and p = 0.075 for female relatives). The strong familial aggregation of morbid obesity indicates the need for further understanding of the genetic determinants of this extreme clinical disorder and how environmental factors affect the genetic expression of the trait. (OBESITY RESEARCH 1993;1:261–270)     

Analysis of survival data from case-control family studies

In case-control family studies with survival endpoint, age of onset of diseases can be used to assess the familial aggregation of the disease and the relationship between the disease and genetic or environmental risk factors. Because of the retrospective nature of the case--control study, methods for analyzing prospectively collected correlated failure time data do not apply directly. In this article, we propose a semiparametric quasi-partial-likelihood approach to simultaneously estimate the effect of covariates on the age of onset and the association of ages of onset among family members that does not require specification of the baseline marginal distribution. We conducted a simulation study to evaluate the performance of the proposed approach and compare it with the existing semiparametric ones. Simulation results demonstrate that the proposed approach has better performance in terms of consistency and efficiency. We illustrate the methodology using a subset of data from the Washington Ashkenazi Study.     

Association between family cancer history and risk of pancreatic cancer

PurposeFamily history of pancreatic adenocarcinoma is an established risk factor for the disease. However, associations of pancreatic cancer with other familial cancers are less clear. We analyzed data from the Queensland Pancreatic Cancer Study (QPCS), an Australian population-based case-control study, to investigate associations between family history of various cancer types and risk of pancreatic cancer.Materials and methodsOur study included 591 pancreatic cancer patients and 646 controls, all of whom self-reported the histories of cancer in their first-degree relatives. We used logistic regression to estimate adjusted odds ratios (ORs) and their 95% confidence intervals (CIs). Based on our results, we conducted a systematic literature review using the Medline (OVID) database to identify articles pertaining to the association between family history of melanoma and risk of pancreatic cancer. A meta-analysis including associations in five published studies, unpublished results from a study co-author and the QPCS results was then performed using the DerSimonian and Laird random-effects model.ResultsCases were more likely than controls to report a family history of pancreatic cancer (OR 2.20, 95% CI 1.16–4.19) and melanoma (OR 1.74, 95% CI 1.03–2.95), but not of breast, ovarian, respiratory, other gastrointestinal or prostate cancer. Meta-analysis of melanoma family history and pancreatic cancer risk yielded an OR of 1.22 (95% CI 1.00–1.51).ConclusionsOur results yield further evidence of increased risk of pancreatic cancer in those with family histories of the disease. We also provide suggestive evidence of an association between family history of melanoma and risk of pancreatic cancer.     

Estimating the magnitude of genetic factors by calculating the genetic relative risk of stroke in first-ever lacunar stroke patients

Background

Positive family history of stroke is an independent risk factor for lacunar stroke. However, the magnitude of familial aggregation of a certain disease is better evaluated by the genetic relative risk. This is calculated by dividing the prevalence of specific disease in family members of patients by the prevalence of this disease in the general population. In a cohort of lacunar stroke patients, who were subtyped clinically and radiologically, we determined the genetic relative risk of stroke.

Methods

By questionnaire and additional interview, we obtained a complete first-degree family history of stroke. The prevalence of stroke in first-degree relatives of these lacunar stroke patients was compared to the self-reported prevalence of stroke in a Dutch community based cohort of elderly volunteers. Secondly, the influence of proband characteristics and family composition on parental and sibling history of stroke were evaluated.

Principal Findings

We collected data of 1066 first-degree relatives of 195 lacunar stroke patients. Strokes occurred in 13.5% of first-degree relatives. The genetic relative risk was 2.94 (95%CI 2.45–3.53) for overall first-degree relatives, 4.52 (95%CI 3.61–5.65) for patients'' parents and 2.10 (95%CI 1.63–2.69) for patients'' siblings. Age of proband and proband status for hypertension influenced the chance of having a parent with a history of stroke whereas the likelihood of having a concordant sibling increased with sibship size.

Conclusions

We found an increased genetic relative risk of stroke in first-degree relatives of patients with lacunar stroke. Our data warrant further genomic research in this well-defined high risk population for stroke.     

Analytical Relationship between Family History and Genetic and Environmental risks,with Application to Female Breast Cancer

It is well established in genetic epidemiology that family history is an important indicator of familial aggregation of disease in a family. A strong genetic risk factor or an environmental risk factor with high familial correlation can result in a strong family history. In this paper, family history refers to the number of first‐degree relatives affected with the disease. Cui and Hopper (Journal of Epidemiology and Biostatistics 2001; 6 : 331–342) proposed an analytical relationship between family history and relevant genetic parameters. In this paper we expand the relationship to both genetic and environmental risk factors. We established a closed‐form formula for family history as a function of genetic and environmental parameters which include genetic and environmental relative risks, genotype frequency, prevalence and familial correlation of the environmental risk factor. The relationship is illustrated by an example of female breast cancer in Australia. For genetic and environmental relative risks less than 10, most of the female breast cancer cases occur between the age of 40 and 60 years. A higher genetic or environmental relative risk will move the peak of the distribution to a younger age. A more common disease allele or more prevalent environmental risk factor will move the peak to an older age. For a proband with breast cancer, it is most likely (with probability ≥80%) that none of her first‐degree relatives is affected with the disease. To enable the probability of having a positive family history to reach 50%, the environmental relative risks must be extremely as high as 100, the familial correlation as high as 0.8 and the prevalence as low as 0.1. For genetic risk alone, even the relative risk is as high as 100, the probability of having a positive family history can only reach about 30%. This suggests that the environmental risk factor seems to play a more important role in determining a strong family history than the genetic risk factor. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

On Combining Family‐Based and Population‐Based Case–Control Data in Association Studies

Summary Combining data collected from different sources can potentially enhance statistical efficiency in estimating effects of environmental or genetic factors or gene–environment interactions. However, combining data across studies becomes complicated when data are collected under different study designs, such as family‐based and unrelated individual‐based case–control design. In this article, we describe likelihood‐based approaches that permit the joint estimation of covariate effects on disease risk under study designs that include cases, relatives of cases, and unrelated individuals. Our methods accommodate familial residual correlation and a variety of ascertainment schemes. Extensive simulation experiments demonstrate that the proposed methods for estimation and inference perform well in realistic settings. Efficiencies of different designs are contrasted in the simulation. We applied the methods to data from the Colorectal Cancer Family Registry.     

Genetic epidemiology of vitiligo: multilocus recessivity cross-validated.

Vitiligo is a dermatological disorder characterized by hypopigmentary patches that tend to become progressive over time. There are reports of extensive familial aggregation. A genetic model for this disorder was earlier proposed by us. This model postulates that recessive alleles at multiple unlinked autosomal loci interact epistatically in the pathogenesis of vitiligo. The present family study was primarily undertaken to cross-validate the proposed genetic model. Data on 194 families from the United States were collected. Each family was ascertained through an affected proband. Analyses of these data reveal that approximately 20% of probands have at least one first-degree relative afflicted with vitiligo. All types of first-degree relatives of probands show a significant risk of developing vitiligo. Results of segregation and robustness analyses reveal that the genetic model postulated by us previously is the most parsimonious model for the present family data set.     

Multivariate survival analysis for case-control family data

Multivariate survival data arise from case-control family studies in which the ages at disease onset for family members may be correlated. In this paper, we consider a multivariate survival model with the marginal hazard function following the proportional hazards model. We use a frailty-based approach in the spirit of Glidden and Self (1999) to account for the correlation of ages at onset among family members. Specifically, we first estimate the baseline hazard function nonparametrically by the innovation theorem, and then obtain maximum pseudolikelihood estimators for the regression and correlation parameters plugging in the baseline hazard function estimator. We establish a connection with a previously proposed generalized estimating equation-based approach. Simulation studies and an analysis of case-control family data of breast cancer illustrate the methodology's practical utility.     

Familial Correlations of Onset Age of Hepatocellular Carcinoma: A Population-Based Case-Control Family Study

Background

There was lack of evidence for familial aggregation in onset age of hepatocellular carcinoma (HCC) in Chinese population. We conducted a population-based case-control family study to examine familial correlation of age of HCC onset in Taixing, China.

Methods

A total of 202 cases and 202 matched controls as well as their relatives were included in the study. Lifetime cumulative risks of HCC were estimated using the Kaplan-Meier approach. Cross ratios (CRs) were obtained from stratified Cox proportional hazard models, to assess the familial correlation of onset age.

Results

The mean age of HCC onset was decreased as increasing number of HCC cases in a family. The onset age was the earliest for first-degree relatives, intermediate for second-degree relatives, and latest for non-blood relatives (spouse) (log-rank test, P<0.01). The onset age was significantly correlated between probands and their relatives. In stratified Cox proportional hazard models, the CRs for the probands versus their fathers, mothers, siblings and uncles/aunts were 6.25 (95% confidence interval (CI): 1.84–21.25), 9.81 (95% CI: 1.24–77.56), 6.22 (95% CI: 1.37–28.36) and 3.24 (95% CI: 1.26–8.33), respectively. After adjustment for hepatitis B virus infection, the CRs remained significant.

Conclusion

This current study suggested a significant correlation of onset age for HCC among blood relatives. Familial HCC cases yielded earlier age of onset and their relatives have higher HCC risk in early age, highlighting intensive surveillance should be start at an earlier age for individuals with family history of HCC.     

HLA-linked rheumatoid arthritis.

Twenty-eight pedigrees were ascertained through pairs of first-degree relatives diagnosed with rheumatoid arthritis (RA). RA was confirmed in 77 pedigree members including probands; the absence of disease was verified in an additional 261 pedigree members. Pedigree members were serologically typed for HLA. We used likelihood analysis to statistically characterize the HLA-linked RA susceptibility locus. The genetic model assumed tight linkage to HLA. The analysis supported the existence of an HLA-linked RA susceptibility locus, estimated the susceptibility allele frequency as 2.16%, and estimated the lifetime penetrance as 41% in male homozygotes and as 48% in female homozygotes. Inheritance was recessive in males and was nearly recessive in females. In addition, the analysis attributed 78% of the variance within genotypes to genetic or environmental effects shared by siblings. The genetic model inferred in this analysis is consistent with previous association, linkage, and familial aggregation studies of RA. The inferred HLA-linked RA susceptibility locus accounts for approximately one-half of familial RA, although it accounts for only approximately one-fifth of the RA in the population. Although other genes may account for the remaining familial RA, a large portion of RA cases may occur sporadically.     

Segregation analysis of cryptogenic epilepsy and an empirical test of the validity of the results.

We used POINTER to perform segregation analysis of cryptogenic epilepsy in 1,557 three-generation families (probands and their parents, siblings, and offspring) ascertained from voluntary organizations. Analysis of the full data set indicated that the data were most consistent with an autosomal dominant (AD) model with 61% penetrance of the susceptibility gene. However, subsequent analyses revealed that the patterns of familial aggregation differed markedly between siblings and offspring of the probands. Risks in siblings were consistent with an autosomal recessive (AR) model and inconsistent with an AD model, whereas risks in offspring were inconsistent with an AR model and more consistent with an AD model. As a further test of the validity of the AD model, we used sequential ascertainment to extend the family history information in the subset of families judged likely to carry the putative susceptibility gene because they contained at least three affected individuals. Prevalence of idiopathic/cryptogenic epilepsy was only 3.7% in newly identified relatives expected to have a 50% probability of carrying the susceptibility gene under an AD model. Approximately 30% (i.e., 50% x 61%) were expected to be affected under the AD model resulting from the segregation analysis. These results suggest that the familial distribution of cryptogenic epilepsy is inconsistent with any conventional genetic model. The differences between siblings and offspring in the patterns of familial risk are intriguing and should be investigated further.     

HLA class II haplotype DRB1*04-DQB1*0301 contributes to risk of familial generalized vitiligo and early disease onset

Generalized vitiligo is a common autoimmune disorder characterized by white patches of skin and overlying hair caused by loss of pigment-forming melanocytes from involved areas. Familial clustering of vitiligo is not uncommon, and patients and their relatives are at increased risk for a specific complex of other autoimmune diseases. Compared with sporadic vitiligo, familial vitiligo is characterized by earlier disease onset and greater risk and broader repertoire of autoimmunity, suggesting a stronger genetic component, and perhaps stronger associations with specific alleles. To determine whether the major histocompatibility complex (MHC) contributes to the familial clustering of vitiligo and vitiligo-associated autoimmune/autoinflammatory diseases, we performed case-control and family-based association analyses of HLA class II-DRB1 and -DQB1 alleles and haplotypes in affected probands and their parents from 76 European-American Caucasian families with familial vitiligo. Affected probands showed a significantly increased frequency of DRB1*04-DQB1*0301 and a significantly decreased frequency of DRB1*15-DQB1*0602 compared with a large sample of reference chromosomes. Family-based association analyses confirmed these results. Probands with DRB1*04-DQB1*0301 developed vitiligo an average of 13.32 yr earlier than probands with DRB1*15-DQB1*0602. Overall, our results indicate that specific MHC-linked genetic variation contributes to risk of familial vitiligo, although HLA does not completely explain familial clustering of vitiligo-associated autoimmune/autoinflammatory diseases.     

Magnified Risks From Cigarette Smoking for Coronary Prone Families in Utah

The contribution of currently accepted risk factors to the familiality of early coronary heart disease (CHD) is poorly understood. In a telephone and mail survey, risk factor and disease morbidity and mortality data were collected from 100 proband and 185 control families encompassing about 40,000 person-years of experience. Probands were white married men who had died of CHD by age 45. There was a threefold increase in CHD incidence among first-degree relatives of probands compared with control families. In all, 67% of probands had at least one first-degree relative with early CHD, and 29% had two or more first-degree relatives with early CHD compared with 8% of the control families with two or more cases of early CHD.The most striking new finding of this study is the apparently magnified liability of cigarette smoking in families prone to have early coronary heart disease. This effect was seen strongly at younger ages (under 50). Furthermore, in about a third of all families with a history of early CHD, smoking seemed to be the only risk factor contributing to the familial occurrence of the disease. The findings show a large excess absolute risk for CHD among smoking members of proband families and further suggest a possibly heritable susceptibility to the deleterious effects of smoking in many families prone to early coronary disease. Modification of coronary risk factors, especially cigarette smoking, would be of greatest benefit among members of high-risk families.