The evolution of signaling complexity suggests a mechanism for reducing the genomic search space in human association studies.

The size complexity of the human genome has been traditionally viewed as an obstacle that frustrates efforts aimed at identifying the genetic correlates of complex human phenotypes. As such complex phenotypes are attributed to the combined action of numerous genomic loci, attempts to identify the underlying multi-locus interactions may produce a combinatorial sum of false positives that drown out the real signal. Faced with such grim prospects for successfully identifying the genetic basis of complex phenotypes, many geneticists simply disregard epistatic interactions altogether. However, the emerging picture from systems biology is that the cellular programs encoded by the genome utilize nested signaling hierarchies to integrate a number of loosely coupled, semiautonomous, and functionally distinct genetic networks. The current view of these modules is that connections encoding inter-module signaling are relatively sparse, while the gene-to-gene (protein-to-protein) interactions within a particular module are typically denser. We believe that each of these modules is encoded by a finite set of discontinuous, sequence-specific, genomic intervals that are functionally linked to association rules, which correlate directly to features in the environment. Furthermore, because these environmental association rules have evolved incrementally over time, we explore theoretical models of cellular evolution to better understand the role of evolution in genomic complexity. Specifically, we present a conceptual framework for (1) reducing genomic complexity by partitioning the genome into subsets composed of functionally distinct genetic modules and (2) improving the selection of coding region SNPs, which results in an increased probability of identifying functionally relevant SNPs. Additionally, we introduce the notion of 'genomic closure,' which provides a quantitative measure of how functionally insulated a specific genetic module might be from the influence of the rest of the genome. We suggest that the development and use of theoretical models can provide insight into the nature of biological systems and may lead to significant improvements in computational algorithms designed to reduce the complexity of the human genome.

Association of a corticotropin-releasing hormone receptor 1 haplotype and antidepressant treatment response in Mexican-Americans.

There are well-replicated, independent lines of evidence supporting a role for corticotropin-releasing hormone (CRH) in the pathophysiology of depression. CRH receptor 1 (CRHR1), which we first mapped in the brain in 1994, has been implicated in the treatment of depression and anxiety. We studied the association of CRHR1 genotypes with the phenotype of antidepressant treatment response in 80 depressed Mexican-Americans in Los Angeles who completed a prospective randomized, placebo lead-in, double-blind treatment of fluoxetine or desipramine, with active treatment for 8 weeks. Subjects were included into the study if they had a diagnosis of depression without other confounding medical or psychiatric diagnoses or treatments. All patients were followed weekly and assessed for changes in the Hamilton rating scales for anxiety (HAM-A) and depression (HAM-D). Inclusion criteria in the study included a HAM-D of 18 or higher. Because CRHR1 affects both depression and anxiety. Patients were classified into a high-anxiety (HA) group if their HAM-A score was 18 or higher and in a low-anxiety (LA) group if their HAM-A score was less than 18. Utilizing the haplotype-tag single-nucleotide polymorphisms rs1876828, rs242939 and rs242941, we tested for haplotypic association between CRHR1 and 8-week response to daily antidepressant treatment. In the HA group (n=54), homozygosity for the GAG haplotype was associated with a relative 70% greater reduction in HAM-A scores compared to heterozygous (63.1+/-4.5 vs 37.1+/-6.9%, respectively, P=0.002). For HAM-D, GAG haplotype homozygosity was associated with a 31% greater reduction in scores after treatment compared to heterozygous (67.3+/-4.3 vs 51.2+/-6.0%, respectively, P=0.03). In those with lower-anxiety levels at screening, there were no associations between CRHR1 genotype and percent change in HAM-A or HAM-D. These findings of increased response to antidepressants in highly anxious patients homozygous for the GAG haplotype of CRHR1 need to be independently validated and replicated. Such work would support the hypotheses that response to antidepressant treatment is heterogeneous and that the CRHR1 gene and possibly other genes in stress-inflammatory pathways are involved in response to antidepressant treatment. These findings also suggest that variations in the CRHR1 gene may affect response to CRHR1 agonists or antagonists. All data are deposited in www.pharmgkb.org.

St John's wort and imipramine-induced gene expression profiles identify cellular functions relevant to antidepressant action and novel pharmacogenetic candidates for the phenotype of antidepressant treatment response.

Both the prototypic tricyclic antidepressant imipramine (IMI) and the herbal product St John's wort (SJW) can be effective in the treatment of major depressive disorder. We studied hypothalamic gene expression in rats treated with SJW or IMI to test the hypothesis that chronic antidepressant treatment by various classes of drugs results in shared patterns of gene expression that may underlie their therapeutic effects. Individual hypothalami were hybridized to individual Affymetrix chips; we studied three arrays per group treatment. We constructed 95% confidence intervals for expression fold change for genes present in at least one treatment condition and we considered genes to be differentially expressed if they had a confidence interval excluding 1 (or -1) and had absolute difference in expression value of 10 or greater. SJW treatment differentially regulated 66 genes and expression sequence tags (ESTs) and IMI treatment differentially regulated 74 genes and ESTs. We found six common transcripts in response to both treatments. The likelihood of this occurring by chance is 1.14 x 10(-23). These transcripts are relevant to two molecular machines, namely the ribosomes and microtubules, and one cellular organelle, the mitochondria. Both treatments also affected different genes that are part of the same cell function processes, such as glycolytic pathways and synaptic function. We identified single-nucleotide polymorphisms in the human orthologs of genes regulated both treatments, as those genes may be novel candidates for pharmacogenetic studies. Our data support the hypothesis that chronic antidepressant treatment by drugs of various classes may result in a common, final pathway of changes in gene expression in a discrete brain region.

Single nucleotide polymorphism identification in candidate gene systems of obesity.

We have constructed a large panel of single nucleotide polymorphisms (SNP) identified in 68 candidate genes for obesity. Our panel combines novel SNP identification methods based on EST data, with public SNP data from largescale genomic sequencing, to produce a total of 218 SNPs in the coding regions of obesity candidate genes, 178 SNPs in untranslated regions, and over 1000 intronic SNPs. These include new non-conservative amino acid changes in thyroid receptor beta, esterase D, acid phosphatase 1. Our data show evidence of negative selection among these polymorphisms implying functional impacts of the non-conservative mutations. Comparison of overlap between SNPs identified independently from EST data vs genomic sequencing indicate that together they may constitute about one half of the actual total number of amino acid polymorphisms in these genes that are common in the human population (defined here as a population allele frequency above 5%). We have analyzed our polymorphism panel to construct a database of detailed information about their location in the gene structure and effect on protein coding, available on the web at http://www.bioinformat ics.ucla.edu/snp/obesity. We believe this panel can serve as a valuable new resource for genetic and pharmacogenomic studies of the causes of obesity.

Genome-wide analysis of single-nucleotide polymorphisms in human expressed sequences.

Single-nucleotide polymorphisms (SNPs) have been explored as a high-resolution marker set for accelerating the mapping of disease genes. Here we report 48,196 candidate SNPs detected by statistical analysis of human expressed sequence tags (ESTs), associated primarily with coding regions of genes. We used Bayesian inference to weigh evidence for true polymorphism versus sequencing error, misalignment or ambiguity, misclustering or chimaeric EST sequences, assessing data such as raw chromatogram height, sharpness, overlap and spacing, sequencing error rates, context-sensitivity and cDNA library origin. Three separate validations-comparison with 54 genes screened for SNPs independently, verification of HLA-A polymorphisms and restriction fragment length polymorphism (RFLP) testing-verified 70%, 89% and 71% of our predicted SNPs, respectively. Our method detects tenfold more true HLA-A SNPs than previous analyses of the EST data. We found SNPs in a large fraction of known disease genes, including some disease-causing mutations (for example, the HbS sickle-cell mutation). Our comprehensive analysis of human coding region polymorphism provides a public resource for mapping of disease genes (available at http://www.bioinformatics.ucla.edu/snp).

An autoinhibitory control element defines calcium-regulated isoforms of nitric oxide synthase.

Nitric oxide synthases (NOSs) are classified functionally, based on whether calmodulin binding is Ca2+-dependent (cNOS) or Ca2+-independent (iNOS). This key dichotomy has not been defined at the molecular level. Here we show that cNOS isoforms contain a unique polypeptide insert in their FMN binding domains which is not shared with iNOS or other related flavoproteins. Previously identified autoinhibitory domains in calmodulin-regulated enzymes raise the possibility that the polypeptide insert is the autoinhibitory domain of cNOSs. Consistent with this possibility, three-dimensional molecular modeling suggested that the insert originates from a site immediately adjacent to the calmodulin binding sequence. Synthetic peptides derived from the 45-amino acid insert of endothelial NOS were found to potently inhibit binding of calmodulin and activation of cNOS isoforms. This inhibition was associated with peptide binding to NOS, rather than free calmodulin, and inhibition could be reversed by increasing calmodulin concentration. In contrast, insert-derived peptides did not interfere with the arginine site of cNOS, as assessed from [3H]NG-nitro-L-arginine binding, nor did they potently effect iNOS activity. Limited proteolysis studies showed that calmodulin's ability to gate electron flow through cNOSs is associated with displacement of the insert polypeptide; this is the first specific calmodulin-induced change in NOS conformation to be identified. Together, our findings strongly suggest that the insert is an autoinhibitory control element, docking with a site on cNOSs which impedes calmodulin binding and enzymatic activation. The autoinhibitory control element molecularly defines cNOSs and offers a unique target for developing novel NOS activators and inhibitors.