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Biomedical subjects

Gary A Chase

Publications and source records attributed to Gary A Chase.

At least 19 recordsLinked to original sources
PubMed2006

Novel genes identified in a high-density genome wide association study for nicotine dependence.

Tobacco use is a leading contributor to disability and death worldwide, and genetic factors contribute in part to the development of nicotine dependence. To identify novel genes for which natural variation contributes to the development of nicotine dependence, we performed a comprehensive genome wide association study using nicotine dependent smokers as cases and non-dependent smokers as controls. To allow the efficient, rapid, and cost effective screen of the genome, the study was carried out using a two-stage design. In the first stage, genotyping of over 2.4 million single nucleotide polymorphisms (SNPs) was completed in case and control pools. In the second stage, we selected SNPs for individual genotyping based on the most significant allele frequency differences between cases and controls from the pooled results. Individual genotyping was performed in 1050 cases and 879 controls using 31 960 selected SNPs. The primary analysis, a logistic regression model with covariates of age, gender, genotype and gender by genotype interaction, identified 35 SNPs with P-values less than 10(-4) (minimum P-value 1.53 x 10(-6)). Although none of the individual findings is statistically significant after correcting for multiple tests, additional statistical analyses support the existence of true findings in this group. Our study nominates several novel genes, such as Neurexin 1 (NRXN1), in the development of nicotine dependence while also identifying a known candidate gene, the beta3 nicotinic cholinergic receptor. This work anticipates the future directions of large-scale genome wide association studies with state-of-the-art methodological approaches and sharing of data with the scientific community.

Case-Control Studies↗
PubMed2006

Cholinergic nicotinic receptor genes implicated in a nicotine dependence association study targeting 348 candidate genes with 3713 SNPs.

Nicotine dependence is one of the world's leading causes of preventable death. To discover genetic variants that influence risk for nicotine dependence, we targeted over 300 candidate genes and analyzed 3713 single nucleotide polymorphisms (SNPs) in 1050 cases and 879 controls. The Fagerström test for nicotine dependence (FTND) was used to assess dependence, in which cases were required to have an FTND of 4 or more. The control criterion was strict: control subjects must have smoked at least 100 cigarettes in their lifetimes and had an FTND of 0 during the heaviest period of smoking. After correcting for multiple testing by controlling the false discovery rate, several cholinergic nicotinic receptor genes dominated the top signals. The strongest association was from an SNP representing CHRNB3, the beta3 nicotinic receptor subunit gene (P = 9.4 x 10(-5)). Biologically, the most compelling evidence for a risk variant came from a non-synonymous SNP in the alpha5 nicotinic receptor subunit gene CHRNA5 (P = 6.4 x 10(-4)). This SNP exhibited evidence of a recessive mode of inheritance, resulting in individuals having a 2-fold increase in risk of developing nicotine dependence once exposed to cigarette smoking. Other genes among the top signals were KCNJ6 and GABRA4. This study represents one of the most powerful and extensive studies of nicotine dependence to date and has found novel risk loci that require confirmation by replication studies.

Adult↗
PubMed2006

Hip fracture risk among community-dwelling elderly people in the United States: a prospective study of physical, cognitive, and socioeconomic indicators.

OBJECTIVES: We determined risks of short-term (2-year) hip fracture in a nationally representative, prospective cohort of community-dwelling elderly people 70 years or older. METHODS: We used self-report data from 2 waves of the Asset and Health Dynamics Survey (n = 5630). Sample-weighted logistic regression analyses were conducted to determine risk of hip fracture in relation to several demographic, cognitive, physical, and socioeconomic indicators. RESULTS: During the 2-year study period, 102 participants reported a new hip fracture. Several indicators of physical functioning and cognitive status, including incorrect delayed word recall and inability to lift 10 lbs (4.5 kg), were significantly associated with hip fracture risk. In the final model, mobile home residents, individuals without Medicare part B insurance, and those without a high-school diploma were at more than a 2-fold risk of hip fracture. Educational level, physical functioning, and insurance status were the top 3 contributors to hip fracture risk. CONCLUSIONS: In addition to functional status measures, health insurance status, educational level, and type of residence appear to be independent predictors of hip fracture.

Activities of Daily Living↗
PubMed2006

The impact of missing and erroneous genotypes on tagging SNP selection and power of subsequent association tests.

OBJECTIVE: Single nucleotide polymorphisms (SNPs) serve as effective markers for localizing disease susceptibility genes, but current genotyping technologies are inadequate for genotyping all available SNP markers in a typical linkage/association study. Much attention has recently been paid to methods for selecting the minimal informative subset of SNPs in identifying haplotypes, but there has been little investigation of the effect of missing or erroneous genotypes on the performance of these SNP selection algorithms and subsequent association tests using the selected tagging SNPs. The purpose of this study is to explore the effect of missing genotype or genotyping error on tagging SNP selection and subsequent single marker and haplotype association tests using the selected tagging SNPs. METHODS: Through two sets of simulations, we evaluated the performance of three tagging SNP selection programs in the presence of missing or erroneous genotypes: Clayton's diversity based program htstep, Carlson's linkage disequilibrium (LD) based program ldSelect, and Stram's coefficient of determination based program tagsnp.exe. RESULTS: When randomly selected known loci were relabeled as 'missing', we found that the average number of tagging SNPs selected by all three algorithms changed very little and the power of subsequent single marker and haplotype association tests using the selected tagging SNPs remained close to the power of these tests in the absence of missing genotype. When random genotyping errors were introduced, we found that the average number of tagging SNPs selected by all three algorithms increased. In data sets simulated according to the haplotype frequecies in the CYP19 region, Stram's program had larger increase than Carlson's and Clayton's programs. In data sets simulated under the coalescent model, Carlson's program had the largest increase and Clayton's program had the smallest increase. In both sets of simulations, with the presence of genotyping errors, the power of the haplotype tests from all three programs decreased quickly, but there was not much reduction in power of the single marker tests. CONCLUSIONS: Missing genotypes do not seem to have much impact on tagging SNP selection and subsequent single marker and haplotype association tests. In contrast, genotyping errors could have severe impact on tagging SNP selection and haplotype tests, but not on single marker tests.

Algorithms↗
PubMed2005

Use of susceptibility scoring in conjunction with the genotypic transmission disequilibrium test.

We explored the utility of selecting a genetically predisposed subgroup to increase the finding of a genetic signal in the Genetic Analysis Workshop 14 Collaborative Study on the Genetics of Alcoholism dataset. A subgroup of affected probands with low environmental risk exposures was defined using a susceptibility score calculated from an environmental risk model. Thirty-nine probands with highly positive scores were selected, along with their parents, for use in a genotypic transmission disequilibrium test (TDT) test. We compared the results of the genotypic TDT in this subgroup to the TDT results using all probands and their parents. For some markers, the susceptibility scoring approach resulted in smaller p-values, while for other markers, evidence for a genetic signal weakened. Further explorations into genetic and environmental population characteristics that benefit from this approach are warranted.

Genetic Predisposition to Disease↗
PubMed2005

Comparison of type I error for multiple test corrections in large single-nucleotide polymorphism studies using principal components versus haplotype blocking algorithms.

Although permutation testing has been the gold standard for assessing significance levels in studies using multiple markers, it is time-consuming. A Bonferroni correction to the nominal p-value that uses the underlying pair-wise linkage disequilibrium (LD) structure among the markers to determine the number of effectively independent tests has recently been proposed. We propose using the number of independent LD blocks plus the number of independent single-nucleotide polymorphisms for correction. Using the Collaborative Study on the Genetics of Alcoholism LD data for chromosome 21, we simulated 1,000 replicates of parent-child trio data under the null hypothesis with two levels of LD: moderate and high. Assuming haplotype blocks were independent, we calculated the number of independent statistical tests using 3 haplotype blocking algorithms. We then compared the type I error rates using a principal components-based method, the three blocking methods, a traditional Bonferroni correction, and the unadjusted p-values obtained from FBAT. Under high LD conditions, the PC method and one of the blocking methods were slightly conservative, whereas the 2 other blocking methods exceeded the target type I error rate. Under conditions of moderate LD, we show that the blocking algorithm corrections are closest to the desired type I error, although still slightly conservative, with the principal components-based method being almost as conservative as the traditional Bonferroni correction.

Algorithms↗
PubMed2005

Using mixture models to characterize disease-related traits.

We consider 12 event-related potentials and one electroencephalogram measure as disease-related traits to compare alcohol-dependent individuals (cases) to unaffected individuals (controls). We use two approaches: 1) two-way analysis of variance (with sex and alcohol dependency as the factors), and 2) likelihood ratio tests comparing sex adjusted values of cases to controls assuming that within each group the trait has a 2 (or 3) component normal mixture distribution. In the second approach, we test the null hypothesis that the parameters of the mixtures are equal for the cases and controls. Based on the two-way analysis of variance, we find 1) males have significantly (p < 0.05) lower mean response values than females for 7 of these traits. 2) Alcohol-dependent cases have significantly lower mean response than controls for 3 traits. The mixture analysis of sex-adjusted values of 1 of these traits, the event-related potential obtained at the parietal midline channel (ttth4), found the appearance of a 3-component normal mixture in cases and controls. The mixtures differed in that the cases had significantly lower mean values than controls and significantly different mixing proportions in 2 of the 3 components. Implications of this study are: 1) Sex needs to be taken into account when studying risk factors for alcohol dependency to prevent finding a spurious association between alcohol dependency and the risk factor. 2) Mixture analysis indicates that for the event-related potential "ttth4", the difference observed reflects strong evidence of heterogeneity of response in both the cases and controls.

Alcoholism↗
PubMed2005

Modelling clinical trials in heterogeneous samples.

Individual variation in genetic, phenotypic and environmental factors could lead to significant differences in rates of drug metabolism, in clinical responses to drugs, and in drug side effects. The impact of population heterogeneity on treatment effect estimation and on assessment and application of clinical trial findings has been less than fully studied. In this paper, we studied the properties of models that reflect population heterogeneity of clinical trial samples by unmeasured covariates such as genetic susceptibility. The impact of heterogeneity on the estimation of treatment effect in a two-armed placebo or active-controlled clinical trial was quantified using logistic regression models. We also proposed a two-stage clinical trial, where the effects of individual drug-response-related covariates were estimated in a 'training data set' in the first stage of the trial. In the second stage of the trial, a subgroup of individuals with enhanced (or reduced) sensitivity to drug treatments in a heterogeneous risk cohort was identified based on information about their drug-related characteristics. Only these 'responders' were included in the subsequent efficacy test. Our simulation results showed that population heterogeneity could lead to biased estimation of treatment effect not only in the contaminated groups but also in the uncontaminated groups. A two-stage trial could greatly increase the power of an efficacy test over a 'full trial' even with fewer individuals enrolled in the trial; results would apply to a more highly specified population. The bigger the covariate effects, the more efficient the two-stage trial is compared to a 'full trial'.

Biometry↗
PubMed2005

Comparison of cryopreservation and standard needle biopsy for gene expression profiling of human breast cancer specimens.

Given the growing importance of molecular profiling of breast cancer, we initiated a small study to test whether human breast biopsies obtained via cryopreservation large core needle biopsy (C-LCNB) provided similar gene expression profiles compared with 'optimally handled' standard large core needle biopsy (S-LCNB) specimens. Five matched pairs of C-LCNB versus S-LCNB were obtained at the same visit, and subjected to gene array expression analysis using the Affymetrix system with U133A chips. No significant changes in gene expression were identified comparing the C-LCNB versus the matched S-LCNB from individual patients. This was corroborated by a paired t-test analysis, which supported the hypothesis that the S/C biopsies measured equivalent samples. A small number of genes (17) showed decreased expression when second biopsies were compared with first biopsies, suggesting a slight patient response to the first biopsy. A scatter plot analysis comparing first biopsy versus second biopsy values disclosed a slope of 0.859, further indicating that the first biopsy affects the second biopsy measurement. It therefore appears that conventional biopsies, when handled appropriately, provide RNA which is equivalent to RNA from biopsies which are frozen immediately, but that multiple biopsy protocols may introduce additional complexities.

Biopsy, Needle↗
PubMed2005

Routine surveillance care after cancer treatment with curative intent.

BACKGROUND: Many consensus guidelines recommend routine surveillance to detect recurrent disease among cancer survivors. We compare surveillance care receipt to guideline recommendations. METHODS: Cohorts of patients aged 30 years or older diagnosed with breast, colorectal, endometrial, lung, or prostate cancer between 1990 and 1995 and treated with curative intent were identified (n = 100 per site). Receipt and indications for examinations and procedures were abstracted from medical records for as long as 5 years after treatment. Kaplan-Meier product estimates were used to estimate time to initial and subsequent service receipt. RESULTS: Most cancer patients received the recommended minimum number of physical examinations after treatment. In fact, a sizable number of cancer survivors received physical examinations at a frequency in excess of what is currently recommended. Similarly, most of these cancer survivors received recommended testing for local recurrence. Yet, less than two thirds of colorectal cancer patients received recommended colon examinations in the initial year after treatment. Among colorectal, lung, and prostate cancer patients who received recommended initial local recurrence testing, repeat testing tended to occur more frequently than what is currently recommended. The use of testing for metastatic disease that is not recommended in guidelines is also commonplace among these cancer survivors. CONCLUSIONS: Among cohorts of cancer patients, we found wide variation in the use of surveillance care, including patterns of care receipt reflective of both underuse and overuse relative to guideline recommendations. Clinical reasons for these variations and the cost and health implications deserve further study.

Adult↗
PubMed2004

Prognostic implications of loss of heterozygosity at 8p21 and 9p21 in head and neck squamous cell carcinoma.

Loss of heterozygosity (LOH) in chromosomal regions that harbor tumor suppressor genes from tumor tissue may lead to decreased survival time in cancer patients with squamous cell carcinoma of the head and neck (HNSCC). We studied 8 regions frequently lost in HNSCC in 150 patients having a primary diagnosis of HNSCC. Tumor and normal tissue DNA were genotyped for microsatellite repeat markers in 8 unlinked chromosomal regions. The association between LOH and death from HNSCC was investigated, weighted by number of informative markers per region and adjusted for age at diagnosis, self-reported race, tumor stage and current smoking status. LOH at 3 chromosomal regions were independently associated with reduced survival. A greater risk for cancer mortality was observed for LOH at chromosomal regions 3p24.3-p14.3 (p = 0.02), 8p21.3-p11.21 (p = 0.02) and 9p24.2-p21.2 (p = 0.03). In these regions, LOH at one or more markers was observed in 66.9%, 43.3% and 60.6% of patients, respectively. Survival times were significantly shorter for those with LOH at marker NEFL on 8p21.2 (relative risk = 6.15; p = 0.0002) and at D9S126 on 9p21.2 (relative risk = 5.96; p = 0.0003). Our results indicate that LOH at several chromosomal sites may offer additional independent prognostic information beyond traditional indicators such as tumor stage and age.

Adult↗
PubMed2004

The impact of population heterogeneity on risk estimation in genetic counseling.

BACKGROUND: Genetic counseling has been an important tool for evaluating and communicating disease susceptibility for decades, and it has been applied to predict risks for a wide class of hereditary disorders. Most diseases are complex in nature and are affected by multiple genes and environmental conditions; it is highly likely that DNA tests alone do not define all the genetic factors responsible for a disease, so that persons classified into the same risk group by DNA testing actually could have different disease susceptibilities. Ignorance of population heterogeneity may lead to biased risk estimates, whereas additional information on population heterogeneity may improve the precision of such estimates. METHODS: Although DNA tests are widely used, few studies have investigated the accuracy of the predicted risks. We examined the impact of population heterogeneity on predicted disease risks by simulation of three different heterogeneity scenarios and studied the precision and accuracy of the risks estimated from a logistic regression model that ignored population heterogeneity. Moreover, we also incorporated information about population heterogeneity into our original model and investigated the resulting improvement in the accuracy of risk estimation. RESULTS: We found that heterogeneity in one or more categories could lead to biased estimates not only in the "contaminated" categories but also in other homogeneous categories. Incorporating information about population heterogeneity into the original model greatly improved the accuracy of risk estimation. CONCLUSIONS: Our findings imply that without thorough knowledge about genetic basis of the disease, risks estimated from DNA tests may be misleading. Caution should be taken when evaluating the predicted risks obtained from genetic counseling. On the other hand, the improved accuracy of risk estimates after incorporating population heterogeneity information into the model did point out a promising direction for genetic counseling, since more and more new techniques are being invented and disease etiology is being better understood.

Bias↗
PubMed2004

Genome scan meta-analysis for hypertension.

BACKGROUND: Genome scans for hypertension have yielded inconsistent results. The non-replication of significant or suggestive linkage might be due to lack of power of individual studies. Here, we conducted a genome scan meta-analysis for hypertension in an attempt to increase statistical power and to enhance evidence of linkage. METHODS: A newly developed Genome Search Meta-analysis (GSMA) method was applied to pool the results obtained from six scans reported in five papers. RESULTS: Our analysis did not find any regions with genome-wide significant linkage to hypertension. We did identify several regions with suggestive linkage, including 2p, 5q, 6q, 8p, 9p, 9q, and 11q. CONCLUSIONS: It seems that no region has a uniformly large impact on hypertension and that susceptibility genes for hypertension may be very difficult to detect.

Blood Pressure↗
PubMed2004

Comorbidity of depression with levels of smoking: an exploration of the shared familial risk hypothesis.

Comorbidity of depression and smoking is well recognized, but results from studies that have assessed alternative explanations have varied by the level of smoking and the study method. We examined all 13 etiology models of comorbidity described by Neale and Kendler (American Journal of Genetics, 57, 935-953, 1995) for depression and each of four levels of smoking to shed light on the role that differing definitions might have played in generating the conflicting findings. Data came from 979 young adults aged 26-35 years who participated in an epidemiological cohort study in southeastern Michigan. Respondent and family history data on parental smoking and depression were analyzed using the biometric modeling method for family data, which Rhee and colleagues (Journal of Child Psychology and Psychiatry and Allied Disciplines, 44, 612-636, 2003; Behavior Genetics, 34, 251-265, 2004) have shown to be valid more frequently than traditional prevalence analyses. Results of the biometric model fitting suggested that for ever smoking, the comorbidity with depression may be related to chance or a high liability threshold for smoking only. In contrast, a correlated liabilities model fit the data best for the comorbidity of depression with daily, heavy, and nicotine-dependent smoking. The familial correlations accounted for 73%-95% of the total variance shared between depression and these levels of smoking. These results differ from analyses of these data using a traditional prevalence approach, which found no evidence of shared familial liability. The conflicting findings of the studies that have examined the relationship between smoking and depression may be attributable to differences in definition of the disorders and the methods used to analyze them.

Adult↗
PubMed2004

The role of test accuracy in predicting acceptance of genetic susceptibility testing for Alzheimer's disease.

A survey questionnaire regarding perceptions of risk and genetic susceptibility to Alzheimer's disease (AD) was completed by 518 offspring of AD cases from families with multiple affected, ascertained as part of a genetic linkage study of late onset AD. The questionnaire focused on respondents' perceptions of their own risk for AD as well as on the properties of real and hypothetical susceptibility tests, including error rates for false-positive and false-negative test results. Our findings showed that about 20% of the sample would refuse a susceptibility test with zero error rates, about 40% would accept tests with very high error rates in both directions, and the remainder would exercise some discrimination. Acceptance of high test error rates was significantly associated with male gender, low education, and high perceived lifetime risk of AD. In a previous paper related to this work, we showed that physicians caring for these families exercised much more discrimination in judging the acceptability of genetic tests they would offer to these same respondents. The findings show that there is a pressing need to educate the public, particularly those with relatives affected by a complex disease, to expect standards of accuracy for genetic tests comparable to those that prevail in other diagnostic and prognostic testing efforts in the broad field of clinical medicine.

Adolescent↗
PubMed2003

Analysis of gene x environment interactions in sibships using mixed models.

BACKGROUND: Gene x environment models are widely used to assess genetic and environmental risks and their association with a phenotype of interest for many complex diseases. Mixed generalized linear models were used to assess gene x environment interactions with respect to systolic blood pressure on sibships adjusting for repeated measures and hierarchical nesting structures. A data set containing 410 sibships from the Framingham Heart Study offspring cohort (part of the Genetic Analysis Workshop 13 data) was used for all analyses. Three mixed gene x environment models, all adjusting for repeated measurement and varying levels of nesting, were compared for precision of estimates: 1) all sibships with adjustment for two levels of nesting (sibs within sibships and sibs within pedigrees), 2) all sibships with adjustment for one level of nesting (sibs within sibships), and 3) 100 data sets containing random draws of one sibship per extended pedigree adjusting for one level of nesting. RESULTS: The main effects were: gender, baseline age, body mass index (BMI), hypertensive treatment, cigarettes per day, grams of alcohol per day, and marker GATA48G07A. The interaction fixed effects were: baseline age by gender, baseline age by cigarettes per day, baseline age by hypertensive treatment, baseline age by BMI, hypertensive treatment by BMI, and baseline age by marker GATA48G07A. The estimates for all three nesting techniques were not widely discrepant, but precision of estimates and determination of significant effects did change with the change in adjustment for nesting. CONCLUSION: Our results show the importance of the adjustment for all levels of hierarchical nesting of sibs in the presence of repeated measures.

Adult Children↗
PubMed2003

Susceptibility scoring in family-based association testing.

BACKGROUND: Family-based association testing is an important part of genetic epidemiology. Tests are available to include multiple siblings, unaffected offspring, and to adjust for environmental covariates. We explore a susceptibility residual method of adjustment for covariates. RESULTS: Through simulation, we show that environmental adjustments that down-weight persons who are "destined" to be affected decrease the power to detect genetic association. We used the residual adjusted method on the Framingham Heart Study offspring data, provided for Genetic Analysis Workshop 13, and got mixed results. CONCLUSION: When the genetic effect and environmental effects are independent, a susceptibility residual method of adjustment for environmental covariates reduces the power of the association test. Further study is necessary to determine if residual adjustment is appropriate in more complex disease models.

Adult Children↗