Biomedical subjects

Nan M Laird

Publications and source records attributed to Nan M Laird.

32 records · Page 2Linked to original sources

PubMed2003

Using the noninformative families in family-based association tests: a powerful new testing strategy.

For genetic association studies with multiple phenotypes, we propose a new strategy for multiple testing with family-based association tests (FBATs). The strategy increases the power by both using all available family data and reducing the number of hypotheses tested while being robust against population admixture and stratification. By use of conditional power calculations, the approach screens all possible null hypotheses without biasing the nominal significance level, and it identifies the subset of phenotypes that has optimal power when tested for association by either univariate or multivariate FBATs. An application of our strategy to an asthma study shows the practical relevance of the proposed methodology. In simulation studies, we compare our testing strategy with standard methodology for family studies. Furthermore, the proposed principle of using all data without biasing the nominal significance in an analysis prior to the computation of the test statistic has broad and powerful applications in many areas of family-based association studies.

Analysis of Variance↗

PubMed2003

Genetic association of Alzheimer's disease with multiple polymorphisms in alpha-2-macroglobulin.

Alpha-2-Macroglobulin (A2M) is a highly plausible candidate gene for Alzheimer's disease (AD) in a region of chromosome 12 that has numerous independent reports of genetic linkage. We previously reported that a 5 bp deletion in A2M was associated with AD in a subset of the National Institute of Health (NIMH) Genetics Initiative AD family sample. Efforts to replicate this association finding in case - control samples have been largely negative, while those in family samples have been more positive. We hypothesized that variable findings regarding this deletion, along with variable reports of association with V1000I, another polymorphism in the gene, result from linkage disequilibrium in the area as well as ascertainment differences between family-based and case-control studies. Thus, we resequenced the A2M locus to identify novel polymorphisms to test for genetic association with AD. We identified seven novel polymorphisms and tested them in the full NIMH sample of 1439 individuals in 437 families. We found significant genetic association of the 5 bp deletion and two novel polymorphisms with AD. Substantial linkage disequilibrium was detected across the gene as a whole, and haplotype analysis also showed significant association between AD and groups of A2M polymorphisms. Several of these polymorphisms and haplotypes remain significantly associated with AD even after correction for multiple testing. Taken together, these findings, and the positive reports in other family-based studies, continue to support a potential role for A2M or a nearby gene in AD. However, the negative case - control studies suggest that any underlying pathogenic polymorphisms have a modest effect, and may operate primarily among individuals with a family history of AD.

Aged↗

PubMed2003

Regression methods for assessing familial aggregation of disease.

This paper reviews methods for assessing familial aggregation of disease based on simple logistic regression models. Studies are based on a case-control sampling design, where the disease status of the first degree relatives of both cases and controls are obtained. Both 'proband predictive' and 'family predictive' models are discussed, and an example is given using a case-control sample from a lung cancer study in non-smokers. The methods are extended to characterize co-aggregation of two disorders, that is, presence of one disorder in the proband increases the risk of a second disorder in the relative. An example involving eating disorders and depression is given.

Case-Control Studies↗

PubMed2003

Family study of affective spectrum disorder.

BACKGROUND: Affective spectrum disorder (ASD) represents a group of psychiatric and medical conditions, each known to respond to several chemical families of antidepressant medications and hence possibly linked by common heritable abnormalities. Forms of ASD include major depressive disorder (MDD), attention-deficit/hyperactivity disorder, bulimia nervosa, cataplexy, dysthymic disorder, fibromyalgia, generalized anxiety disorder, irritable bowel syndrome, migraine, obsessive-compulsive disorder, panic disorder, posttraumatic stress disorder, premenstrual dysphoric disorder, and social phobia. Two predictions of the ASD hypothesis were tested: that ASD, taken as a single entity, would aggregate in families and that MDD would coaggregate with other forms of ASD in families. METHODS: Probands with and without MDD, together with their first-degree relatives, were interviewed using the Structured Clinical Interview for DSM-IV and a supplemental interview for other forms of ASD. The familial aggregation and coaggregation of disorders were analyzed using proband predictive logistic regression models, including a novel bivariate model for the presence or absence of each of 2 disorders in a relative as predicted by the presence or absence of each of 2 disorders in the associated proband. RESULTS: In the 178 interviewed relatives of 64 probands with MDD and 152 relatives of 58 probands without MDD, the estimated odds ratio (95% confidence interval) for the familial aggregation of ASD as a whole was 2.5 (1.4-4.3; P =.001) and for the familial coaggregation of MDD with at least one other form of ASD was 1.9 (1.1-3.2; P =.02). CONCLUSIONS: Affective spectrum disorder aggregates strongly in families, and MDD displays a significant familial coaggregation with other forms of ASD, taken collectively. These results suggest that forms of ASD may share heritable pathophysiologic features.

Anxiety Disorders↗

PubMed2003

Family-based association analysis of beta2-adrenergic receptor polymorphisms in the childhood asthma management program.

BACKGROUND: Beta2-adrenergic receptor (B2AR) polymorphisms have been associated with a variety of asthma-related phenotypes, but association results have been inconsistent across different studies. OBJECTIVE: We sought to apply family-based association methods to individual single nucleotide polymorphisms (SNPs) and haplotypes of SNPs in B2AR to define the relationship of these genetic variants to asthma-related phenotypes. METHODS: DNA samples were obtained from 707 Childhood Asthma Management Program participants, representing 650 sibships, as well as their parents. Genotyping was performed at 8 B2AR SNPs. Qualitative asthma-related phenotypes were analyzed with single SNPs and haplotypes by using TRANSMIT; quantitative asthma-related phenotypes were analyzed with the Family-Based Association Test. RESULTS: Several SNPs, including SNP -654 and SNP +46, demonstrated significant associations (P <.05) to postbronchodilator FEV1 as both a qualitative (<80% of predicted value) and quantitative phenotype. Quantitative phenotypic association analysis demonstrated significant evidence for association of SNP +523 with bronchodilator responsiveness expressed as a percentage of baseline FEV1 (P =.012) or a percentage of predicted FEV1 (P =.008). Similar evidence for association between the +523 SNP and qualitative bronchodilator responsiveness phenotypes was also found. Analysis of haplotypes supported an association of B2AR variants with spirometric values and bronchodilator responsiveness. CONCLUSION: B2AR variants are associated with spirometric values and bronchodilator responsiveness, but different regions of the gene provide evidence for association with these phenotypes.

Alleles↗

PubMed2003

A multivariate family-based association test using generalized estimating equations: FBAT-GEE.

In this paper we propose a multivariate extension of family-based association tests based on generalized estimating equations. The test can be applied to multiple phenotypes and to phenotypic data obtained in longitudinal studies without making any distributional assumptions for the phenotypic observations. Methods for handling missing phenotypic information are discussed. Further, we compare the power of the multivariate test with permutation tests and with using separate tests for each outcome which are adjusted for multiple testing. Application of the proposed test to an asthma study illustrates the power of the approach.

Adult↗

PubMed2003

Cigarette smoking in relation to depression: historical trends from the Stirling County Study.

OBJECTIVE: Building on findings about the prevalence and incidence of depression over a 40-year period, the authors provide data on trends in cigarette smoking and associations with depression. METHOD: Data come from interviews with adult population samples (1952, 1970, and 1992) and followed cohorts (1952-1970 and 1970-1992). Logistic regression models and survival regressions were used to analyze the data. RESULTS: The associations between smoking and depression were small and nonsignificant in 1952 and 1970. In 1992, however, the odds that a smoker would be depressed were three times the odds that a nonsmoker would be depressed. The interaction between smoking and study year was significant, indicating that the association was limited to the most recent sample. In the cohort analysis, smoking at baseline did not predict the onset of depression, but subjects who became depressed were more likely to start or continue smoking and less likely to quit than those who never had a depression. CONCLUSIONS: In terms of population trends, the association between depression and cigarette smoking became prominent as the use of tobacco declined because of awareness of the risks involved. The findings about individuals followed over time suggest that those who became depressed were more involved with nicotine than those who never had a depression. The authors discuss hypotheses involving "self-medication," risk-taking, and changes in the social climate but conclude that the relationships between smoking and depression are probably multiple and complex.

Adult↗

PubMed2002

Power and design considerations for a general class of family-based association tests: quantitative traits.

In the present article, we address family-based association tests (FBATs) for quantitative traits. We propose an approach to analytical power and sample-size calculations for general FBATs; this approach can be applied to virtually any scenario (missing parental information, multiple offspring per family, etc.). The power calculations are used to discuss optimal choices of the phenotypes for the FBAT statistic and its power's dependence on ascertainment conditions, on study design, and on the correct specification of the distributional assumptions for the phenotypes. We also compare the general FBAT approach with PDT and QTDT. The practical relevance of our theoretical considerations is illustrated by their application to an asthma study.

Adult↗

PubMed2002

Power calculations for a general class of family-based association tests: dichotomous traits.

Using large-sample theory, we present a unified approach to power calculations for family-based association tests. Currently available methods for power calculations are restricted to special designs or require approximations or simulations. Our analytical approach to power calculations is broadly applicable in many settings. We discuss power calculations for two scenarios that have high practical relevance and in which power previously could only be assessed by simulation studies or by approximations: (1) studies using both affected and unaffected offspring and (2) studies with missing parental information. When the population prevalence is high, it can be worthwhile to genotype unaffected offspring. For many scenarios, high power can be achieved with reasonable sample sizes, even when no parental information is available.

Chi-Square Distribution↗

PubMed2002

Non-linear hierarchical models for monitoring compliance.

As biomarkers transformable by specific drug agents increasingly become available, so their usefulness also increases for monitoring compliance in clinical and prevention trials, and for subsequent monitoring in the general population if a treatment is found successful. Marker levels measured over the course of a treatment yield a longitudinal trajectory that is typically non-linear, with varying velocities during the phase-in and steady-state periods of treatment, followed by decays back to normal in the presence of non-compliance. There is often considerable between-individual variability both in the mean parameters of the trajectory and the variability over time. An example is the biomarker mean corpuscular volume (MCV), which increases by 20 per cent from the drug zidovudine (AZT), and has been used to monitor compliance to AZT. Using MCV data from a previous AIDS clinical trial as an example, we describe a non-linear hierarchical growth model suitable for biomarkers that exhibit sigmoidal and/or asymptotic growth behaviour and show how such models can be supplemented with a change-point to identify potential times of non-compliance. We perform a fully Bayesian analysis to obtain a variety of posterior summaries for the behaviour of the longitudinal trajectory and the times of non-compliance, and describe how to obtain predictions of non-compliance for new individuals.

Acquired Immunodeficiency Syndrome↗

PubMed2002

Regression analysis of multiple-source longitudinal outcomes: a "Stirling County" depression study.

Epidemiologic studies of psychiatric disorders have increasingly relied on multiple sources of information to improve the validity of diagnoses and repeated assessments over time to provide a longitudinal perspective. In this paper, the authors present a general multivariate logistic regression method for the simultaneous analysis of discrete outcomes that exhibit such features. This approach permits risk factor and agreement analyses within a unified framework and appropriately uses data from subjects who may be missing some outcomes. The authors use this approach to analyze data from a "Stirling County" study of depression. During a 3- to 4-year period in the early 1990s, 631 subjects were assessed in two separate interviews, on each occasion with two diagnostic schedules (the DePression and AnXiety schedule (DPAX) and the Diagnostic Interview Schedule (DIS)). The female:male ratio of depression was found to be different for the DPAX and the DIS (0.8 and 1.6, respectively). Education was inversely associated with depression, while the effects of time, the subject's age, and the interviewer's sex were essentially null. With respect to the outcomes' association, agreement between the DPAX and the DIS was low. In addition, stability of the DPAX over time was significantly higher than that of the DIS. No covariates were found to affect significantly the association between outcomes.

Adult↗

PubMed2002

On a general class of conditional tests for family-based association studies in genetics: the asymptotic distribution, the conditional power, and optimality considerations.

Family-based association tests (FBATs) provide simple and powerful tests to detect association between a genetic marker and a disease-susceptibility locus, manifest in subjects by a phenotype or disease trait. Here we propose a new class of conditional tests for family-based association studies that includes most of the established tests and their generalizations. The class of tests is very general; it can be applied to longitudinal and multivariate traits or phenotypes, multiple genetic markers, and many other situations not yet discussed in the literature. For any test in this class, we derive the asymptotic distribution under the null hypothesis, the conditional power under any alternative hypothesis, and the optimal offset for single degree of freedom tests. The proposed methodology is illustrated with a genetic study of asthma.

Asthma↗

PubMed2002

Incidence of major depression: prediction from subthreshold categories in the Stirling County Study.

BACKGROUND: Validity of the newly-proposed categories of Minor Depression (MinD) and Subsyndromal Depression (SSD) would be strengthened if they were found to be related to the incidence of Major Depressive Episode (MDE). In this report, the subsequent incidence of MDE was assessed in terms of baseline evidence about the two subthreshold categories and Dysthymic Disorder (DysD). METHODS: The Diagnostic Interview Schedule was used to interview 489 subjects twice between 1991 and 1995 as part of the Stirling County Study. Life table methods were used to calculate incidence rates and log linear analysis was employed for statistical assessment. RESULTS: The average annual incidence of MDE was 10 per 1000. The rates associated with the baseline categories were 210 per 1000 for DysD, 21 for MinD; 13 for SSD; and four for the remainder of subjects who constituted the reference group. Only the incidence related to DysD was significantly higher than that for the reference group. Comparing Time 1 and Time 2, one-third of the subjects gained or lost symptoms and the comorbidity of MDE and DysD increased. LIMITATIONS: The study population was, on average, 63 years of age. Older age and the small size of the cohort may have influenced the findings. Another limitation may relate to the use of lifetime rather than current symptomatology. CONCLUSIONS: DysD is strongly associated with MDE suggesting that the chronic and episodic forms of unipolar depression constitute one disorder. The other subthreshold categories should be further investigated in terms of prodromal qualities. The persistence of dysphoria, as in DysD, may be a more important feature of the depression prodrome than the number of symptoms.

Adult↗

PubMedDate not supplied

Self-disparagement as feature and forerunner of depression: findings from the Stirling County Study.

Sleep disturbance has attracted considerable attention as an early indicator of depression. However, three epidemiologic investigations have shown psychological symptoms, such as self-disparagement, to be stronger predictors. This report examines the depressive symptoms commonly assessed in modern epidemiologic surveys and estimates the generalizability of this information using data from the Stirling County Study, a long-term epidemiologic investigation of psychiatric disorders. The Diagnostic Interview Schedule (DIS) was used to gather information about depression, defined as major depressive episode (MDE) and/or dysthymic disorder (DysD). A sample of 1,396 adults representing Stirling County in 1992 served to assess the prevalence of the different types of depressive symptoms and to investigate the associations between symptoms and lifetime diagnoses of MDE/DysD. A cohort of 489 follow-up subjects who were interviewed twice in the early part of the 1990s was used to examine the associations between baseline symptoms and subsequent incidence of MDE/DysD. Both "symptom groups" (such as appetite or psychomotor disturbances) and "individual symptoms" (such as weight gain or restlessness) were investigated. About one third of the representative sample had experienced the diagnostically required symptoms of "sadness" or "loss of pleasure," but many lacked sufficient other symptomatology to be diagnosed as depressed. Several of the symptom groups bore a different relationship to diagnosis than did the individual symptoms. Among the latter, "feeling worthless" and "having trouble concentrating" exhibited the strongest associations to diagnosis in the representative sample. The symptoms of "wanting to die" and "feeling worthless" were the most predictive of future depression in the twice-interviewed cohort. Thus, this study supports evidence from other epidemiologic studies that psychological symptoms are important in the prodromal phase of depression. Sleep disturbance, especially insomnia, cannot be ignored since it is a prominent manifestation of depression but it appears not to have as high specificity as some of the other symptoms. An exclusive focus on the symptom groups, as used to count symptoms according to diagnostic criteria, may obscure useful information about associations between individual symptoms and diagnosis. Feelings of personal inadequacy deserve particular attention in the population at large because they are strongly associated with lifetime diagnoses and forecast the incidence of depression when people are followed over time.

Adult↗