Scott J. Hebbring

A germline DNA polymorphism enhances alternative splicing of the KLF6 tumor suppressor gene and is associated with increased prostate cancer risk

Prostate cancer is a leading and increasingly prevalent cause of cancer death in men. Whereas family history of disease is one of the strongest prostate cancer risk factors and suggests a hereditary component, the predisposing genetic factors remain unknown. We first showed that KLF6 is a tumor suppressor somatically inactivated in prostate cancer and since then, its functional loss has been further established in prostate cancer cell lines and other human cancers. Wild-type KLF6, but not patient-derived mutants, suppresses cell growth through p53-independent transactivation of p21. Here we show that a germline KLF6 single nucleotide polymorphism, confirmed in a tri-institutional study of 3,411 men, is significantly associated with an increased relative risk of prostate cancer in men, regardless of family history of disease. This prostate cancer-associated allele generates a novel functional SRp40 DNA binding site and increases transcription of three alternatively spliced KLF6 isoforms. The KLF6 variant proteins KLF6-SV1 and KLF6-SV2 are mislocalized to the cytoplasm, antagonize wtKLF6 function, leading to decreased p21 expression and increased cell growth, and are up-regulated in tumor versus normal prostatic tissue. Thus, these results are the first to identify a novel mechanism of self-encoded tumor suppressor gene inactivation and link a relatively common single nucleotide polymorphism to both regulation of alternative splicing and an increased risk in a major human cancer.

Comparison of Microsatellites Versus Single-Nucleotide Polymorphisms in a Genome Linkage Screen for Prostate Cancer–Susceptibility Loci

Prostate cancer is one of the most common cancers among men and has long been recognized to occur in familial clusters. Brothers and sons of affected men have a 2-3-fold increased risk of developing prostate cancer. However, identification of genetic susceptibility loci for prostate cancer has been extremely difficult. Although the suggestion of linkage has been reported for many chromosomes, the most promising regions have been difficult to replicate. In this study, we compare genome linkage scans using microsatellites with those using single-nucleotide polymorphisms (SNPs), performed in 467 men with prostate cancer from 167 families. For the microsatellites, the ABI Prism Linkage Mapping Set version 2, with 402 microsatellite markers, was used, and, for the SNPs, the Early Access Affymetrix Mapping 10K array was used. Our results show that the presence of linkage disequilibrium (LD) among SNPs can lead to inflated LOD scores, and this seems to be an artifact due to the assumption of linkage equilibrium that is required by the current genetic-linkage software. After excluding SNPs with high LD, we found a number of new LOD-score peaks with values of at least 2.0 that were not found by the microsatellite markers: chromosome 8, with a maximum model-free LOD score of 2.2; chromosome 2, with a LOD score of 2.1; chromosome 6, with a LOD score of 4.2; and chromosome 12, with a LOD score of 3.9. The LOD scores for chromosomes 6 and 12 are difficult to interpret, because they occurred only at the extreme ends of the chromosomes. The greatest gain provided by the SNP markers was a large increase in the linkage information content, with an average information content of 61% for the SNPs, versus an average of 41% for the microsatellite markers. The strengths and weaknesses of microsatellite versus SNP markers are illustrated by the results of our genome linkage scans.

Two Common Chromosome 8q24 Variants Are Associated with Increased Risk for Prostate Cancer

Two variants (rs1447295/DG8S737) of chromosome 8q24 were recently reported to be associated with increased risk of prostate cancer (PC). To confirm this finding, we genotyped and compared the frequencies of these polymorphisms among 1,121 Caucasian men with PC (435 men with familial PC, 491 men with sporadic PC, and 195 men with aggressive PC) to 545 population-based controls. For the single nucleotide polymorphism marker rs1447295, frequencies of the minor allele (A) were 10.3% in controls, 11.9% in sporadic cases, 16.7% in familial cases, and 17.2% in aggressive cases. Compared with controls, the A allele was significantly more common in both familial PC [odds ratios (OR), 1.93; 95% confidence intervals (95% CI), 1.37-2.72; P = 0.0004] and aggressive PC (OR, 1.87; 95% CI, 1.28-2.74; P = 0.0005) but not for sporadic PC (OR, 1.16; 95% CI, 0.85-1.58; P = 0.25). Although the A allele was more frequent in aggressive PC cases when compared with controls, the allele frequencies were similar among cases with high- and low-grade PC (Gleason grades <7 and >/=7, respectively). For the microsatellite marker DG8S737, the -8 allele was significantly more frequent in familial PC (OR, 1.68; 95% CI, 1.09-2.60; P = 0.031), whereas the -10 allele was more frequent in aggressive PC (OR, 2.85; 95% CI, 1.52-5.36; P = 0.0004). Haplotype analysis showed significant differences in haplotype frequencies between the familial PC (P = 0.006) and aggressive PC (P = 0.005) cases versus controls. The -8/A haplotype showed the strongest association with familial PC (P = 0.008), whereas the -10/A haplotype was most strongly associated with aggressive PC (P = 0.00005). These results further confirm the importance of these two polymorphic variants (rs1447295 and DG8S737) as risk factors for PC. However, the mechanism explaining this increased risk has not yet been established.

Glycine and a glycine dehydrogenase (GLDC) SNP as citalopram/escitalopram response biomarkers in depression: pharmacometabolomics-informed pharmacogenomics.

Major depressive disorder (MDD) is a common psychiatric disease. Selective serotonin reuptake inhibitors (SSRIs) are an important class of drugs used in the treatment of MDD. However, many patients do not respond adequately to SSRI therapy. We used a pharmacometabolomics‐informed pharmacogenomic research strategy to identify citalopram/escitalopram treatment outcome biomarkers. Metabolomic assay of plasma samples from 20 escitalopram remitters and 20 nonremitters showed that glycine was negatively associated with treatment outcome (P = 0.0054). This observation was pursued by genotyping tag single‐nucleotide polymorphisms (SNPs) for genes encoding glycine synthesis and degradation enzymes, using 529 DNA samples from SSRI‐treated MDD patients. The rs10975641 SNP in the glycine dehydrogenase (GLDC) gene was associated with treatment outcome phenotypes. Genotyping for rs10975641 was carried out in 1,245 MDD patients in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study, and its presence was significant (P = 0.02) in DNA taken from these patients. These results highlight a possible role for glycine in SSRI response and illustrate the use of pharmacometabolomics to “inform” pharmacogenomics.

Evaluation of Genetic Variations in the Androgen and Estrogen Metabolic Pathways as Risk Factors for Sporadic and Familial Prostate Cancer

Previous studies suggest that enzymes involved in the androgen metabolic pathway are susceptibility factors for prostate cancer. Estrogen metabolites functioning as genotoxins have also been proposed as risk factors. In this study, we systematically tested the hypothesis that common genetic variations for those enzymes involved in the androgen and estrogen metabolic pathways increase risk for sporadic and familial prostate cancer. From these two pathways, 46 polymorphisms (34 single nucleotide polymorphisms, 10 short tandem repeat polymorphisms, and 2 null alleles) in 25 genes were tested for possible associations. Those genes tested included PRL, LHB, CYP11A1, HSD3B1, HSD3B2, HSD17B2, CYP17, SRD5A2, AKR1C3, UGT2B15, AR, SHBG, and KLK3 from the androgen pathway and CYP19, HSD17B1, CYP1A1, CYP1A2, CYP1B1, COMT, GSTP1, GSTT1, GSTM1, NQO1, ESR1, and ESR2 from the estrogen pathway. A case-control study design was used with two sets of cases: familial cases with a strong prostate cancer family history (n = 438 from 178 families) and sporadic cases with a negative prostate cancer family history (n = 499). The controls (n = 493) were derived from a population-based collection. Our results provide suggestive findings for an association with either familial or sporadic prostate cancer with polymorphisms in four genes: AKR1C3, HSD17B1, NQO1, and GSTT1. Additional suggestive findings for an association with clinical variables (disease stage, grade, and/or node status) were observed for single nucleotide polymorphisms in eight genes: HSD3B2, SRD5A2, SHBG, ESR1, CYP1A1, CYP1B1, GSTT1, and NQO1. However, none of the findings were statistically significant after appropriate corrections for multiple comparisons. Given that the point estimates for the odds ratio for each of these polymorphisms are <2.0, much larger sample sizes will be required for confirmation. (Cancer Epidemiol Biomarkers Prev 2007;16(5):969–78)

The gene for HMSN2C maps to 12q23-24: A region of neuromuscular disorders

Background: Hereditary motor and sensory neuropathy type 2C (HMSN2C, Charcot–Marie–Tooth 2C [CMT2C]) is an autosomal dominant motor and sensory neuropathy involving limb, diaphragm, vocal cord, and intercostal muscles. Objective: To identify the chromosome localization for this disorder in one large American family of English and Scottish ethnicity. Methods: Variable clinical severity led the authors to combine several approaches to accurately identify affected patients. Genome-wide two-point linkage analysis, high-definition mapping, and multipoint and recombinant haplotype analyses were performed. Mutation analysis of the triplet repeat region of ataxin-2 was also carried out. Results: The initial genome-wide scan identified a region at 12q24, and fine mapping provided a maximal lod score of 4.73 (D12S1645 and D12S1583 at θ = 0.01 and 0, respectively). With multipoint analysis, a higher lod score of 5.17 was obtained and localized to the same region at 119.0 cM. Haplotype analysis narrowed the region to approximately 5.0 cM between D12S1646,D12S1330 and D12S105,D12S1339 (12q23.3-24.21). Ataxin-2, the gene responsible for spinocerebellar ataxia type 2 (SCA2), localizes to this region, but no triplet repeat expansion or point mutations within the repeat were found. Conclusions: The gene for HMSN2C maps to 12q23-24. This region is associated with SCA2, scapuloperoneal spinal muscular atrophy, and congenital distal spinal muscular atrophy. Further studies are needed to demonstrate the specific gene alteration and its relationship with nearby genes.

Comparison of RNA-seq and microarray-based models for clinical endpoint prediction

BackgroundGene expression profiling is being widely applied in cancer research to identify biomarkers for clinical endpoint prediction. Since RNA-seq provides a powerful tool for transcriptome-based applications beyond the limitations of microarrays, we sought to systematically evaluate the performance of RNA-seq-based and microarray-based classifiers in this MAQC-III/SEQC study for clinical endpoint prediction using neuroblastoma as a model.ResultsWe generate gene expression profiles from 498 primary neuroblastomas using both RNA-seq and 44 k microarrays. Characterization of the neuroblastoma transcriptome by RNA-seq reveals that more than 48,000 genes and 200,000 transcripts are being expressed in this malignancy. We also find that RNA-seq provides much more detailed information on specific transcript expression patterns in clinico-genetic neuroblastoma subgroups than microarrays. To systematically compare the power of RNA-seq and microarray-based models in predicting clinical endpoints, we divide the cohort randomly into training and validation sets and develop 360 predictive models on six clinical endpoints of varying predictability. Evaluation of factors potentially affecting model performances reveals that prediction accuracies are most strongly influenced by the nature of the clinical endpoint, whereas technological platforms (RNA-seq vs. microarrays), RNA-seq data analysis pipelines, and feature levels (gene vs. transcript vs. exon-junction level) do not significantly affect performances of the models.ConclusionsWe demonstrate that RNA-seq outperforms microarrays in determining the transcriptomic characteristics of cancer, while RNA-seq and microarray-based models perform similarly in clinical endpoint prediction. Our findings may be valuable to guide future studies on the development of gene expression-based predictive models and their implementation in clinical practice.

Confirmation of Linkage of Prostate Cancer Aggressiveness with Chromosome 19q

Regions on chromosomes 7 and 19 were recently reported to contain susceptibility loci that regulate tumor aggressiveness of prostate cancer. To confirm these findings, we analyzed genome scan data from 161 pedigrees affected with prostate cancer. Using the Gleason score as a quantitative measure of tumor aggressiveness, we regressed the squared trait difference, as well as the mean-corrected cross product, on the estimated proportion of alleles shared identical-by-descent at each marker position. Our results confirm the previous linkage results for chromosome 19q (D19S902, P<.00001). In addition, we report suggestive evidence for linkage on chromosome 4 (D4S403, P=.00012). The results of previous findings, together with our results, provide strong evidence that chromosome 19 harbors a gene for tumor aggressiveness.

The phenotypic legacy of admixture between modern humans and Neandertals

The legacy of human-Neandertal interbreeding Non-African humans are estimated to have inherited on average 1.5 to 4% of their genomes from Neandertals. However, how this genetic legacy affects human traits is unknown. Simonti et al. combined genotyping data with electronic health records. Individual Neandertal alleles were correlated with clinically relevant phenotypes in individuals of European descent. These archaic genetic variants were associated with medical conditions affecting the skin, the blood, and the risk of depression. Science, this issue p. 737 Genotype-phenotype association analysis of Neandertal alleles in modern humans identifies clinical effects. Many modern human genomes retain DNA inherited from interbreeding with archaic hominins, such as Neandertals, yet the influence of this admixture on human traits is largely unknown. We analyzed the contribution of common Neandertal variants to over 1000 electronic health record (EHR)–derived phenotypes in ~28,000 adults of European ancestry. We discovered and replicated associations of Neandertal alleles with neurological, psychiatric, immunological, and dermatological phenotypes. Neandertal alleles together explained a significant fraction of the variation in risk for depression and skin lesions resulting from sun exposure (actinic keratosis), and individual Neandertal alleles were significantly associated with specific human phenotypes, including hypercoagulation and tobacco use. Our results establish that archaic admixture influences disease risk in modern humans, provide hypotheses about the effects of hundreds of Neandertal haplotypes, and demonstrate the utility of EHR data in evolutionary analyses.

A PheWAS approach in studying HLA-DRB1*1501

HLA-DRB1 codes for a major histocompatibility complex class II cell surface receptor. Genetic variants in and around this gene have been linked to numerous autoimmune diseases. Most notably, an association between HLA-DRB1*1501 haplotype and multiple sclerosis (MS) has been defined. Utilizing electronic health records and 4235 individuals within Marshfield Clinic’s Personalized Medicine Research Project, a reverse genetic screen coined phenome-wide association study (PheWAS) tested association of rs3135388 genotype (tagging HLA-DRB1*1501) with 4841 phenotypes. As expected, HLA-DRB1*1501 was associated with MS (International Classification of Disease version 9-CM (ICD9) 340, P=0.023), whereas the strongest association was with alcohol-induced cirrhosis of the liver (ICD9 571.2, P=0.00011). HLA-DRB1*1501 also demonstrated association with erythematous conditions (ICD9 695, P=0.0054) and benign neoplasms of the respiratory and intrathoracic organs (ICD9 212, P=0.042), replicating previous findings. This study not only builds on the feasibility/utility of the PheWAS approach, represents the first external validation of a PheWAS, but may also demonstrate the complex etiologies associated with the HLA-DRB1*1501 loci.