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S E Hodge

Publications and source records attributed to S E Hodge.

At least 73 records · Page 4Linked to original sources
PubMed1990

A problem in identifying risk factors for disease using surrogate exposure variables that are under genetic control.

The use of a surrogate exposure variable to represent a complex of genetic and/or nongenetic factors is commonplace in epidemiologic studies. The authors present an hypothetical example in which a surrogate exposure results from underlying unknown genetic and nongenetic factors, yet only the genetic component predisposes to disease. The results demonstrate how risk may be incorrectly attributed to the nongenetic component of exposure and suggest a possible explanation for the identification of a risk factor in one case-control study in one population, but not in another study of the same disease conducted in a different population.

Case-Control Studies↗
PubMed1990

The probability of obtaining compatible blood from related directed donors.

Patients with alloantibodies may request directed blood donations from their relatives despite the lack of any scientific data suggesting that blood from these donors is safer. We have derived formulas that are applicable to any ethnic group for calculating the probability that a given class of relatives will have compatible blood for a given patient. These formulas apply to any non-X-linked blood group system (including the ABO and Rh systems) and are simple enough for routine blood bank use in advising patients as to how likely they are to obtain compatible donors. Use of these formulas may be helpful in counseling patients who may have difficulty in obtaining compatible directed donors because of antibodies or an unusual blood type. In general, the presence of an alloantibody should not automatically exclude a patient from utilizing directed donors. Moreover, for patients with antibodies to high-incidence antigens, directed donations from siblings may be the easiest way to obtain compatible blood.

Blood Donors↗
PubMed1989

Linkage analysis under "random" and "genetic" reduced penetrance.

We examined whether the results of linkage analysis are affected by the reasons for so-called "reduced penetrance". We simulated linkage data with random reduced penetrance and contrasted that with data that were simulated under inheritance controlled by two loci interacting epistatically. For the two-locus disease models, one of those loci was linked to the marker. All data, irrespective of how the data were simulated, were analyzed under the assumption of a single-locus genetic model with random reduced penetrance. We found that there appears to be little bias in the results of linkage analysis whether the "reduced penetrance" was caused by random (usually interpreted as environmental) factors or by strictly genetic factors. We also illustrate that when the trait or disease is influenced by more than one locus, the inheritance of the trait at the linked locus is the important consideration, not the inheritance of the trait per se.

Computer Simulation↗
PubMed1989

Risk of hemolytic disease of the newborn as a result of directed donations from relatives.

Women of childbearing age are more and more often requesting directed blood donations from their husbands or other relatives. With a mathematical model, the risk was derived of such transfusions causing hemolytic disease of the newborn (HDN) in subsequent pregnancies. Calculations were performed for six classes of relatives of the recipient and her husband and for four racial groups. In general, the risk of HDN increases with the donor's degree of relatedness to the husband and decreases with the donor's degree of relatedness to the recipient in a fairly continuous manner. The relative risk for subsequent HDN was as high as 4.1 if the husband donated. The risk varied with the recipient's race as well as Rh(D) status. Although small, the risk involved in transfusing a woman of childbearing age with blood from her husband or his relatives should be considered when using directed donors.

Blood Donors↗
PubMed1989

Selection bias in case-control studies using relatives as the controls.

Investigators have suggested using relatives of cases as the control group when studying complex diseases thought to have a major genetic component. However, there is a concern about possible bias and we developed a model to examine the possibility of bias in the selection of relatives as the control group. Assuming the exposure-specific risks of disease remain constant over time, the results indicate that even when there is a correlation in the exposure status among relatives, selection of controls from relatives of cases does not, of itself, introduce bias in the estimate of effect.

Bias↗
PubMed1988

Possible heterogeneity in the segregation pattern of breast cancer in families with bilateral breast cancer.

We investigated the segregation pattern of breast cancer in families with bilateral breast cancer, classifying families with respect to menopausal status (premenopausal versus postmenopausal) and the interval between diagnosis of the two primary tumors in the probands. Probands were "synchronous" if both primaries were diagnosed within 1 year; "asynchronous" if the interval was at least 2 years. Results for four complex segregation analyses are here presented; the findings support heterogeneity in the transmission of breast cancer. In the asynchronous premenopausal-cases-only analysis, a dominant Mendelian gene can explain the breast cancer pattern. A recessive gene is sufficient to describe the breast cancer distribution in the synchronous premenopausal-cases-only analysis. The synchronous all-cases and the asynchronous all-cases analyses add postmenopausal cases of breast cancer to the premenopausal ones, considering any case to be affected. In the asynchronous all-cases analysis, neither the single-locus model nor the mixed model (that is, a major locus plus other factors, genetic and/or cultural) without generation differences in heritability can be rejected by the unrestricted mixed model with generation differences in heritability. For the synchronous all-cases analysis, a mixed model with generation differences in heritability is necessary to explain the breast cancer transmission. Potential sources of error and possible interpretations are discussed.

Breast Neoplasms↗
PubMed1988

Some effects of selection strategies on linkage analysis.

A study was designed to address the relative merits of different sampling strategies for detecting linkage. Genotypes of pedigree members were generated by the use of a single genetic model, and the pedigrees were subdivided into dominant-appearing, recessive-appearing, and "interesting" subsets. An investigator blind to how the data had been generated applied two different selection rules to determine which individuals in each pedigree would be "typed" for linkage analysis. Linkage analyses were then conducted on these pedigree subsets, as well as on the combined data, by the use of three autosomal dominant models, three autosomal recessive models, and the generating (i.e., "true") model. Results suggest (1) that linkage is likely to be detected even in the absence of knowledge of the mode of transmission, if a range of models can be examined; (2) that false evidence for heterogeneity will not necessarily result when pedigrees are selected according to apparent mode of transmission for analysis; (3) that recessive-appearing pedigrees (i.e., those with multiplex sibships) may be particularly useful for detecting linkage; and (4) that including information on unaffected second-degree relatives adds little to linkage studies of affected individuals and their first-degree relatives.

Genetic Linkage↗
PubMed1988

Family studies in fetal phenytoin exposure.

Sixty-two families with fetal diphenylhydantoin exposure were studied during two or more pregnancies. In 15 of these families at least one of the exposed children had some of the physical effects of DPH exposure ("affected" families); in the remaining 47 families no exposed child was affected ("unaffected" families). Review of 62 family histories and pedigrees was not helpful in differentiating these two groups for counseling purposes. However, mothers who had one affected child appeared to be at much higher risk for having subsequent affected children (9 of 10) if phenytoin use was continued through future pregnancies than were mothers whose first-born child was unaffected despite being exposed to phenytoin during the pregnancy (5 of 52 among all families, or 1 of 48 when only children exposed throughout the entire pregnancy were included). The difference between families with the first exposed child affected and first exposed child unaffected was highly statistically significant (p less than 0.0001). School and learning problems and developmental or mental retardation were present in both groups, and significantly more frequently in affected families. Physical and growth abnormalities were noted in both affected and unaffected family groups, also at a significantly higher rate in affected families.

Abnormalities, Drug-Induced↗
PubMed1988

Increased sharing of maternal HLA haplotypes among children exposed to diphenylhydantoin during pregnancy.

During investigation of HLA types among children exposed to diphenylhydantoin (DPH) in utero, we found no evidence of a distortion in haplotype sharing among affected sib pairs. Unexpectedly, however, we found a marked increase in the proportion of all sib pairs (not just affected ones) sharing maternal haplotypes. Among 14 two child families, 12 shared the maternal haplotype (expected would be seven); among families with more than two children the distortion was also pronounced. This finding, if verified in future studies, could indicate that something in the mothers, whether DPH use during pregnancy, or some genetic factor associated with seizures, or some effect of the seizures themselves, may be leading to non-random segregation of HLA haplotypes in their offspring.

Child↗
PubMed1988

Conditioning on subsets of the data: applications to ascertainment and other genetic problems.

I here consider the question of when to formulate a likelihood over the whole data set, as opposed to conditioning the likelihood on subsets of the data (i.e., joint vs. conditional likelihoods). I show that when certain conditions are met, these two likelihoods are guaranteed to be equivalent, and thus that it is generally preferable to condition on subsets, since that likelihood is mathematically and computationally simpler. However, I show that when these conditions are not met, conditioning on subsets of the data is equivalent to introducing additional df into our genetic model, df that we may not have been aware of. I discuss the implications of these facts for ascertainment corrections and other genetic problems.

Data Interpretation, Statistical↗
PubMed1986

The effects of a known family-size distribution on the estimation of genetic parameters.

We consider the question: In a segregation analysis, can knowledge of the family-size distribution (FSD) in the population from which a sample is drawn improve the estimators of genetic parameters? In other words, should one incorporate the population FSD into a segregation analysis if one knows it? If so, then under what circumstances? And how much improvement may result? We examine the variance and bias of the maximum likelihood estimators both asymptotically and in finite samples. We consider Poisson and geometric FSDs, as well as a simple two-valued FSD in which all families in the population have either one or two children. We limit our study to a simple genetic model with truncate selection. We find that if the FSD is completely specified, then the asymptotic variance of the estimator may be reduced by as much as 5%-10%, especially when the FSD is heavily skewed toward small families. Results in small samples are less clear-cut. For some of the simple two-valued FSDs, the variance of the estimator in small samples of one- and two-child families may actually be increased slightly when the FSD is included in the analysis. If one knows only the statistical form of the FSD, but not its parameter, then the estimator is improved only minutely. Our study also underlines the fact that results derived from asymptotic maximum likelihood theory do not necessarily hold in small samples. We conclude that in most practical applications it is not worth incorporating the FSD into a segregation analysis. However, this practice may be justified under special circumstances where the FSD is completely specified, without error, and the population consists overwhelmingly of small families.

Family Characteristics↗
PubMed1986

A note on Cannings and Thompson's sequential sampling scheme for pedigrees.

We consider sequential sampling of pedigrees for genetic analysis. Cannings and Thompson (1977) gave simple, general guidelines for valid sequential sampling schemes. We show that their formulation of the likelihood contains an error, which is, however, easily corrected so as to maintain the validity of the sequential scheme. We also point out that although sequential and fixed-structure pedigree sampling do have the same likelihoods (as Cannings and Thompson showed), and therefore yield the same maximum likelihood point estimates of genetic parameters, they do not necessarily yield the same significance tests or confidence intervals.

Genetics, Medical↗
PubMed1985

The heterogeneity problem. I: Separating genetic from environmental forms of the same disease.

The purposes of this work were 1) to reparameterize the likelihood used in segregation analysis in a way particularly suited to detecting heterogeneity (the result of the analysis is a parameter giving the proportion of families with the genetic form of the disease in the dataset) and 2) to test how well this reparameterization works using simulation. We assume that a dataset contains nuclear family data, with some of the families having a form of the disease that is environmentally caused and the others with a genetic form of the disease. In this study, we considered the case where the genetic form is a simple recessive and the environmental form a random model. The underlying parameters were the gene frequency, q, and the frequency of sporadics, R. We reparameterized the likelihood in terms of alpha, the percentage of genetic families in the dataset, which we attempt to estimate. We contrast the estimates of alpha with the population heterogeneity as reflected in the estimates of q and R. For the simulation, nuclear families are generated. Genetic families were simulated with a mendelian recessive pattern and environmental families according to a simple random model. Over a wide range of generating parameters, estimates of alpha were good, differing from the "true" values by only a few percent. Estimates of q and R, on the other hand, ranged from fair to poor. Our results indicate that the amount of heterogeneity in a dataset can be accurately estimated using segregation analysis, even when estimates of the gene frequency and penetrance among sporadics are unreliable.

Environment↗
PubMed1985

Identity-by-descent analysis of sibship configurations.

This study considers configurations of identity-by-descent sharing in sibships as an alternative to breaking the sibship into sib pairs. A general method is presented for specifying all distinct configurations and deriving their probabilities. The method works for sibships of arbitrary size and can be implemented with paper and pencil. Specific results are given for sibships up to size six. Applications for disease-marker studies are discussed.

Genetic Diseases, Inborn↗