GENETIC PREDICTORS OF HYPERGLYCEMIA DUE TO HYDROCHLOROTHIAZIDE THERAPY

Response to pharmacological treatment is variable among individuals. Some patients respond favorably to a drug while others develop adverse reactions. Early investigations showed evidence of variation in genes that code for drug receptors, drug transporters, and drug metabolizing enzymes; and pharmacogenetics appeared as the science that studies the relationship between drug response and genetic variation. Thiazide diuretics are the recommended first-line monotherapy for hypertension (i.e. SBP>140 or DBP>90). Even so, diuretics are associated with adverse metabolic side effects, such as hyperglycemia, which increase the risk of developing type 2 diabetes. Published approaches testing variation in candidate genes (e.g. the renin-angiotensin-aldosteron system (RAAS) and salt–sensitivity genes) have met with only limited success. We conducted the first genome wide association study to identify genes influencing hyperglycemia as an adverse effect of thiazide diuretics in non-Hispanic White hypertensive patients participating in the Genetic Epidemiology of Responses to Antihypertensives (GERA) and Pharmacogenomic Evaluation of Antihypertensive Responses (PEAR) clinical trials. No SNP reached the a priori defined threshold of statistical significance (p<5x10-8). We detected 50 SNPs in 9 genomic regions with suggestive p-values (p<1x10-5). Two of them, rs6870564 (p-value=3.28 X 10-6) and rs7702121 (p-value=5.09 X 10-6), were located close to biologic candidate genes, MYO and MGAT1, and one SNP in a genomic region in chromosome 6, rs7762018 (p-value=4.59 X 10-6) has been previously related to Insulin-Dependent Diabetes Mellitus (IDDM8). I conclude that 1) there are unlikely to be common SNPs with large effects on the adverse metabolic effects to hydrochlorothiazide treatment and 2) larger sample sizes are needed for pharmacogenetic studies of inter-individual variation in response to commonly prescribed medication.

Instrumental variable method for the causal relationship between soluble receptor for advanced glycation end-products (sRAGE) and risk of pancreatic cancer

This thesis project is motivated by the potential problem of using observational data to draw inferences about a causal relationship in observational epidemiology research when controlled randomization is not applicable. Instrumental variable (IV) method is one of the statistical tools to overcome this problem. Mendelian randomization study uses genetic variants as IVs in genetic association study. In this thesis, the IV method, as well as standard logistic and linear regression models, is used to investigate the causal association between risk of pancreatic cancer and the circulating levels of soluble receptor for advanced glycation end-products (sRAGE). Higher levels of serum sRAGE were found to be associated with a lower risk of pancreatic cancer in a previous observational study (255 cases and 485 controls). However, such a novel association may be biased by unknown confounding factors. In a case-control study, we aimed to use the IV approach to confirm or refute this observation in a subset of study subjects for whom the genotyping data were available (178 cases and 177 controls). Two-stage IV method using generalized method of moments-structural mean models (GMM-SMM) was conducted and the relative risk (RR) was calculated. In the first stage analysis, we found that the single nucleotide polymorphism (SNP) rs2070600 of the receptor for advanced glycation end-products (AGER) gene meets all three general assumptions for a genetic IV in examining the causal association between sRAGE and risk of pancreatic cancer. The variant allele of SNP rs2070600 of the AGER gene was associated with lower levels of sRAGE, and it was neither associated with risk of pancreatic cancer, nor with the confounding factors. It was a potential strong IV (F statistic = 29.2). However, in the second stage analysis, the GMM-SMM model failed to converge due to non- concaveness probably because of the small sample size. Therefore, the IV analysis could not support the causality of the association between serum sRAGE levels and risk of pancreatic cancer. Nevertheless, these analyses suggest that rs2070600 was a potentially good genetic IV for testing the causality between the risk of pancreatic cancer and sRAGE levels. A larger sample size is required to conduct a credible IV analysis.^

Molecular and evolutionary genetics of the X -linked visual pigment genes in humans and New World monkeys

Normal humans have one red and at least one green visual pigment genes. These genes are tightly linked as tandem repeats on the X chromosome and each of them has six exons. There is only one X-linked visual pigment gene in New World monkeys (NWMs) but the locus has three polymorphic alleles encoding red, yellow and green visual pigments, respectively. The spectral properties of the squirrel monkey and the marmoset (both NWMs) have been studied and partial sequences of the three alleles are available. To study the evolutionary history of these X-linked opsin genes in humans and NWMs, coding and intron sequences of the three squirrel monkey alleles and the three marmoset alleles were amplified by PCR followed by subcloning and sequencing. Introns 2 and 4 of the human red and green pigment genes were also sequenced. The results obtained are as follows: (1) The sequences of introns 2 and 4 of the human red and green opsin genes are significantly more similar between the two genes than are coding sequences, contrary to the usual situation where coding regions are better conserved in evolution than are introns. The high similarities in the two introns are probably due to recent gene conversion events during evolution of the human lineage. (2) Phylogenetic analysis of both intron and exon sequences indicates that the phylogenetic tree of the available primate opsin genes is the same as the species tree. The two human genes were derived from a gene duplication event after the divergence of the human and NWM lineages. The three alleles in each of the two NWM species diverged after the split of the two NWMs but have persisted in the population for at least 5 million years. (3) Allelic gene conversion might have occurred between the three squirrel monkey alleles. (4) A model of additive effect of hydroxyl-bearing amino acids on spectral tuning is proposed by treating some unknown variables as groups. Under the assumption that some residues have no effect, it is found that at least five amino acid residues, at positions 178 (3 nm), 180 (5 nm), 230 ($-$4 nm), 277 (9 nm) and 285 (13 nm), have linear spectral tuning effects. (5) Adaptive evolution of the opsin genes to different spectral peaks was observed at four residues that are important for spectral tuning. ^

Evaluation of the Hosmer -Lemeshow global goodness -of-fit statistic for mixed variable logistic regression models

The performance of the Hosmer-Lemeshow global goodness-of-fit statistic for logistic regression models was explored in a wide variety of conditions not previously fully investigated. Computer simulations, each consisting of 500 regression models, were run to assess the statistic in 23 different situations. The items which varied among the situations included the number of observations used in each regression, the number of covariates, the degree of dependence among the covariates, the combinations of continuous and discrete variables, and the generation of the values of the dependent variable for model fit or lack of fit.^ The study found that the $\rm\ C$g* statistic was adequate in tests of significance for most situations. However, when testing data which deviate from a logistic model, the statistic has low power to detect such deviation. Although grouping of the estimated probabilities into quantiles from 8 to 30 was studied, the deciles of risk approach was generally sufficient. Subdividing the estimated probabilities into more than 10 quantiles when there are many covariates in the model is not necessary, despite theoretical reasons which suggest otherwise. Because it does not follow a X$\sp2$ distribution, the statistic is not recommended for use in models containing only categorical variables with a limited number of covariate patterns.^ The statistic performed adequately when there were at least 10 observations per quantile. Large numbers of observations per quantile did not lead to incorrect conclusions that the model did not fit the data when it actually did. However, the statistic failed to detect lack of fit when it existed and should be supplemented with further tests for the influence of individual observations. Careful examination of the parameter estimates is also essential since the statistic did not perform as desired when there was moderate to severe collinearity among covariates.^ Two methods studied for handling tied values of the estimated probabilities made only a slight difference in conclusions about model fit. Neither method split observations with identical probabilities into different quantiles. Approaches which create equal size groups by separating ties should be avoided. ^