Biomedical subjects

Peter Kraft

Publications and source records attributed to Peter Kraft.

At least 19 recordsLinked to original sources

PubMed2026

Cross-ancestry proteome-wide Mendelian randomization prioritizes 12 plasma protein candidates for breast cancer risk.

The plasma proteome provides a molecular bridge between genetic variation and disease risk, yet its contribution to breast cancer susceptibility across ancestries remains unclear. We conducted a proteome-wide Mendelian randomization (MR) study of 2,923 plasma proteins using cis-protein quantitative trait loci from 34,557 European participants in the UK Biobank Pharma Proteomics Project, integrated with genome-wide association studies of 156,901 breast cancer cases and 204,634 controls of European, East Asian, and African ancestries. Cross-ancestry meta-analysis identified 12 candidate proteins associated with breast cancer risk (P < 2.5×10-5), including six previously reported and six newly implicated in MR studies. DNPH1 showed cross-ancestry heterogeneity, with a risk-increasing association in European populations and a nominally inverse association in East Asian populations. CASP8, RALB, and USP28 displayed subtype-differentiated associations. Orthogonal validation provided variable support: six demonstrated strong evidence of statistical colocalization; four replicated in an independent European proteomic dataset (deCODE, n = 35,559); two replicated in an independent East Asian proteomic dataset (JCTF, n = 1,384); and four were supported by polygenic-score analyses in the ancestrally diverse All of Us cohort (9,250 cases, 214,857 controls). These findings prioritize a high-confidence subset of plasma proteins, including LRRC25, PARK7, and LRRC37A2, for future mechanistic and translational investigation.

Mendelian randomization↗

PubMed2026

Genomic analyses implicate hormonal and metabolic dysregulation in polycystic ovary syndrome.

Polycystic ovary syndrome (PCOS) and its underlying features remain poorly understood. In this genetic study (n = 544,513), we expand the number of genetic loci from 16 to 29, and additionally identify 31 associated plasma proteins. Many risk-increasing loci were associated with later age at menopause, underscoring the reproductive longevity related to an increased oocyte number and/or availability across the lifespan. Hormonal regulation in the etiology of this condition, through metabolic and reproductive features, was emphasized. The proteomic analysis highlighted metabolic biology known to be related to PCOS. A polygenic risk score (PRS) was associated with adverse cardiometabolic outcomes, with differing relevance of testosterone and body mass index in women and men. Finally, while oligo-anovulation and anovulatory infertility are features of PCOS, we observed no impact of PCOS susceptibility on childlessness. We suggest that PCOS susceptibility confers balanced pleiotropic influences on fertility in women, and life-long adverse metabolic consequences in both sexes.

Humans↗

PubMed2006

Melanocortin 1 receptor variants and skin cancer risk.

Melanocortin 1 receptor (MC1R) gene variants are associated with red hair and fair skin color. We assessed the associations of common MC1R genotypes with the risks of 3 types of skin cancer simultaneously in a nested case-control study within the Nurses' Health Study (219 melanoma, 286 squamous cell carcinoma (SCC), and 300 basal cell carcinoma (BCC) cases, and 873 controls). We found that the 151Cys, 160Trp and 294His variants were significantly associated with red hair, fair skin color and childhood tanning tendency. The MC1R variants, especially the 151Cys variant, were associated with increased risks of the 3 types of skin cancer, after controlling for hair color, skin color and other skin cancer risk factors. Carriers of the 151Cys variant had an OR of 1.65 (95% CI, 1.04-2.59) for melanoma, 1.67 (1.12-2.49) for SCC and 1.56 (1.03-2.34) for BCC. Women with medium or olive skin color carrying 1 nonred hair color allele and 1 red hair color allele had the highest risk of melanoma. A similar interaction pattern was observed for red hair and carrying at least 1 red hair color allele on melanoma risk. We also observed that the 151Cys variant contributed additional melanoma risk among red-haired women. The information on MC1R status modestly improved the risk prediction; the increase was significant for melanoma and BCC (p, 0.004 and 0.05, respectively). These findings indicated that the effects of the MC1R variants on skin cancer risk were independent from self-reported phenotypic pigmentation.

Adult↗

PubMed2006

XPA, haplotypes, and risk of basal and squamous cell carcinoma.

Nucleotide excision repair (NER) is instrumental in removing DNA lesions caused by ultraviolet (UV) radiation, the dominant risk factor for keratinocyte carcinoma, including basal cell carcinoma (BCC) and squamous cell carcinoma (SCC). We evaluated whether BCC or SCC risk was influenced by the A23G single nucleotide polymorphism (SNP) in Xeroderma pigmentosum group A (XPA), which codes for an essential protein in NER. We also investigated whether haplotypes of XPA, determined by seven haplotype-tagging SNPs, better define susceptibility to keratinocyte carcinoma. Incident cases of BCC and SCC from New Hampshire were identified through dermatologists and pathology laboratories. Population-based controls were frequency-matched to cases by gender and age. Cases of BCC (886) and of SCC (682) were compared with controls (796). Models controlled for age, gender, pigmentation factors and severe sunburns and were restricted to Caucasians. Using GG as the reference, the A allele was less frequent among cases of BCC (OR(AG) = 0.82, 95% CI (0.66, 1.01); OR(AA)= 0.74, 95% CI (0.53, 1.03); trend test P = 0.03) and SCC (OR(AG) = 0.85, 95% CI (0.67, 1.07); OR(AA) = 0.74, 95% CI (0.52, 1.05); trend test P = 0.05) than controls. Risk from > or =3 severe sunburns was elevated for those with the GG genotype only, and this interaction was nearly significant for BCC (P = 0.07). XPA genotype also modified a relationship between SCC and the amount of pigmentation (P = 0.02). Using a haplotype analysis identifying seven common XPA haplotypes indicated that the A23G polymorphism alone captured the differences in susceptibility to keratinocyte carcinoma. The common G allele of the A23G polymorphism was associated with an increased risk of BCC and SCC and this polymorphism appeared to be the determining polymorphism in XPA that alters cancer susceptibility.

Adult↗

PubMed2006

Androgen receptor polymorphisms and endometrial cancer risk.

The androgen receptor (AR) gene is a transcription factor responsible for mediating the physiological effects of androgens. Evidence suggests that androgens and the androgen receptor are involved in uterine cell proliferation. A polymorphic CAG repeat in exon 1 of the AR gene encodes a polyglutamine tract that is inversely correlated with the transcriptional activity of this gene. We assessed the association between the functional CAG repeat polymorphism and AR haplotypes and the risk of endometrial cancer in two nested case-control studies within the Nurses' Health Study (n = 222 cases, 666 controls) and the Women's Health Study (n = 137 cases, 411 controls) using conditional and unconditional logistic regression. Associations between AR CAG repeat polymorphism and endometrial cancer risk were similar in the 2 case-control studies. In the pooled analysis, women with an average repeat allele > or =22 repeats compared to <22 repeats were at a statistically significant decreased risk of endometrial cancer (odds ratio (OR) = 0.76; 95% confidence interval (CI), 0.59-0.98). Women with one or two long alleles (> or =27 repeats) compared to both alleles <22 repeats were also at a statistically significant decreased risk (OR = 0.60; 95% CI, 0.36-0.99). We observed a modest yet statistically significant association for each one unit increase in the average repeat length and endometrial cancer risk (OR = 0.94; 95% CI, 0.88-1.00). Associations for the AR CAG average repeat length and endometrial cancer risk differed by menopausal status (p = 0.02). No significant associations between the AR haplotypes and endometrial cancer risk were observed. Our findings suggest that an increasing number of functional CAG repeats may be associated with endometrial carcinogenesis because of AR's reduced ability to recruit coregulators and other transcriptional components. (supplementary material for this article can be found on the International Journal of Cancer website at http://www.interscience.wiley.com/jpages/0020-7136/suppmat/index.html).

Adult↗

PubMed2006

Quantification of the power of Hardy-Weinberg equilibrium testing to detect genotyping error.

Deviation from Hardy-Weinberg equilibrium has become an accepted test for genotyping error. While it is generally considered that testing departures from Hardy-Weinberg equilibrium to detect genotyping error is not sensitive, little has been done to quantify this sensitivity. Therefore, we have examined various models of genotyping error, including error caused by neighboring SNPs that degrade the performance of genotyping assays. We then calculated the power of chi-square goodness-of-fit tests for deviation from Hardy-Weinberg equilibrium to detect such error. We have also examined the affects of neighboring SNPs on risk estimates in the setting of case-control association studies. We modeled the power of departure from Hardy-Weinberg equilibrium as a test to detect genotyping error and quantified the effect of genotyping error on disease risk estimates. Generally, genotyping error does not generate sufficient deviation from Hardy-Weinberg equilibrium to be detected. As expected, genotyping error due to neighboring SNPs attenuates risk estimates, often drastically. For the moment, the most widely accepted method of detecting genotyping error is to confirm genotypes by sequencing and/or genotyping via a separate method. While these methods are fairly reliable, they are also costly and time consuming.

Alleles↗

PubMed2006

Haplotype analysis of the HSD17B1 gene and risk of breast cancer: a comprehensive approach to multicenter analyses of prospective cohort studies.

The 17beta-hydroxysteroid dehydrogenase 1 gene (HSD17B1) encodes 17HSD1, which catalyzes the final step of estradiol biosynthesis. Despite the important role of HSD17B1 in hormone metabolism, few epidemiologic studies of HSD17B1 and breast cancer have been conducted. This study includes 5,370 breast cancer cases and 7,480 matched controls from five large cohorts in the Breast and Prostate Cancer Cohort Consortium. We characterized variation in HSD17B1 by resequencing and dense genotyping a multiethnic sample and identified haplotype-tagging single nucleotide polymorphisms (htSNP) that capture common variation within a 33.3-kb region around HSD17B1. Four htSNPs, including the previously studied SNP rs605059 (S312G), were genotyped to tag five common haplotypes in all cases and controls. Conditional logistic regression was used to estimate odds ratios (OR) for disease. We found no evidence of association between common HSD17B1 haplotypes or htSNPs and overall risk of breast cancer. The OR for each haplotype relative to the most common haplotype ranged from 0.98 to 1.07 (omnibus test for association: X2 = 3.77, P = 0.58, 5 degrees of freedom). When cases were subdivided by estrogen receptor (ER) status, two common haplotypes were associated with ER-negative tumors (test for trend, Ps = 0.0009 and 0.0076; n = 353 cases). HSD17B1 variants that are common in Caucasians are not associated with overall risk of breast cancer; however, there was an association among the subset of ER-negative tumors. Although the probability that these ER-negative findings are false-positive results is high, these findings were consistent across each cohort examined and warrant further study.

17-Hydroxysteroid Dehydrogenases↗

PubMed2006

Quantifying bias due to allele misclassification in case-control studies of haplotypes.

OBJECTIVES: Genotyping errors can induce biases in frequency estimates for haplotypes of single nucleotide polymorphisms (SNPs). Here, we considered the impact of SNP allele misclassification on haplotype odds ratio estimates from case-control studies of unrelated individuals. METHODS: We calculated bias analytically, using the haplotype counts expected in cases and controls under genotype misclassification. We evaluated the bias due to allele misclassification across a range of haplotype distributions using empirical haplotype frequencies within blocks of limited haplotype diversity. We also considered simple two- and three-locus haplotype distributions to understand the impact of haplotype frequency and number of SNPs on misclassification bias. RESULTS: We found that for common haplotypes (>5% frequency), realistic genotyping error rates (0.1-1% chance of miscalling an allele), and moderate relative risks (2-4), the bias was always towards the null and increases in magnitude with increasing error rate, increasing odds ratio. For common haplotypes, bias generally increased with increasing haplotype frequency, while for rare haplotypes, bias generally increased with decreasing frequency. When the chance of miscalling an allele is 0.5%, the median bias in haplotype-specific odds ratios for common haplotypes was generally small (<4% on the log odds ratio scale), but the bias for some individual haplotypes was larger (10-20%). Bias towards the null leads to a loss in power; the relative efficiency using a test statistic based upon misclassified haplotype data compared to a test based on the unobserved true haplotypes ranged from roughly 60% to 80%, and worsened with increasing haplotype frequency. CONCLUSIONS: The cumulative effect of small allele-calling errors across multiple loci can induce noticeable bias and reduce power in realistic scenarios. This has implications for the design of candidate gene association studies that utilize multi-marker haplotypes.

Alleles↗

PubMed2006

Nonsynonymous polymorphisms in genes in the one-carbon metabolism pathway and associations with colorectal cancer.

The Ala(222)Val single nucleotide polymorphism (SNP) in the gene for 5,10-methylenetetrahydrofolate reductase (MTHFR), a critical enzyme in one-carbon metabolism, has been associated with colorectal cancer risk. Many enzymes are involved in one-carbon metabolism, and SNPs in the corresponding genes may play a role in colorectal carcinogenesis. We examined 24 nonsynonymous SNPs in 13 genes involved in the one-carbon metabolism pathway in relation to the risk of colorectal cancer in a case-control study nested in the Nurses' Health Study and the Health Professionals Follow-up Study cohorts. Among 376 men and women with colorectal cancer and 849 controls, a reduced risk of colorectal cancer was observed for Val/Val versus Ala carriers of MTHFR Ala(222)Val [odds ratio (OR), 0.66; 95% confidence interval (CI), 0.43-1.00]. An increased risk was suggested for the variant carrier genotypes versus homozygous wild-type for betaine hydroxymethyltransferase Arg(239)Gln (OR, 1.40; 95% CI, 1.07-1.83) and two linked SNPs in methionine synthase reductase, Ser(284)Thr (OR, 1.85; 95% CI, 1.05-3.27) and Arg(415)Cys (OR, 2.03; 95% CI, 1.15-3.56). The other SNPs were not associated with colorectal cancer risk. Also, none of the SNPs were associated with risk in subgroups of dietary methyl status or were jointly associated with colorectal cancer risk in combination with another SNP, except possibly SNPs in methionine synthase and transcobalamin II. However, these analyses of gene-diet interactions were limited in statistical power. Our results corroborate previous findings for MTHFR Ala(222)Val and suggest that other genes involved in one-carbon metabolism, particularly those that affect DNA methylation, may be associated with colorectal cancer risk.

Adult↗

PubMed2006

A comprehensive analysis of the androgen receptor gene and risk of breast cancer: results from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3).

INTRODUCTION: Androgens have been hypothesised to influence risk of breast cancer through several possible mechanisms, including their conversion to estradiol or their binding to the oestrogen receptor and/or androgen receptor (AR) in the breast. Here, we report on the results of a large and comprehensive study of the association between genetic variation in the AR gene and risk of breast cancer in the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3). METHODS: The underlying genetic variation was determined by first sequencing the coding regions of the AR gene in a panel of 95 advanced breast cancer cases. Second, a dense set of markers from the public database was genotyped in a panel of 349 healthy women. The linkage disequilibrium relationships (blocks) across the gene were then identified, and haplotype-tagging single nucleotide polymorphisms (htSNPs) were selected to capture the common genetic variation across the locus. The htSNPs were then genotyped in the nested breast cancer cases and controls from the Cancer Prevention Study II, European Prospective Investigation into Cancer and Nutrition, Multiethnic Cohort, Nurses' Health Study, and Women's Health Study cohorts (5,603 breast cancer cases and 7,480 controls). RESULTS: We found no association between any genetic variation (SNP, haplotype, or the exon 1 CAG repeat) in the AR gene and risk of breast cancer, nor were any statistical interactions with known breast cancer risk factors observed. CONCLUSION: Among postmenopausal Caucasian women, common variants of the AR gene are not associated with risk of breast cancer.

Aged↗

PubMed2006

Exposure to environmental ozone alters semen quality.

Idiopathic male infertility may be due to exposure to environmental toxicants that alter spermatogenesis or sperm function. We studied the relationship between air pollutant levels and semen quality over a 2-year period in Los Angeles, California, by analyzing repeated semen samples collected by sperm donors. Semen analysis data derived from 5,134 semen samples from a sperm donor bank were correlated with air pollutant levels (ozone, nitrogen dioxide, carbon monoxide, and particulate matter < 10 microm in aerodynamic diameter) measured 0-9, 10-14, and 70-90 days before semen collection dates in Los Angeles between January 1996 and December 1998. A linear mixed-effects model was used to model average sperm concentration and total motile sperm count for the donation from each subject. Changes were analyzed in relationship to biologically relevant time points during spermatogenesis, 0-9, 10-14, and 70-90 days before the day of semen collection. We estimated temperature and seasonality effects after adjusting for a base model, which included donor's date of birth and age at donation. Forty-eight donors from Los Angeles were included as subjects. Donors were included if they collected repeated semen samples over a 12-month period between January 1996 and December 1998. There was a significant negative correlation between ozone levels at 0-9, 10-14, and 70-90 days before donation and average sperm concentration, which was maintained after correction for donor's birth date, age at donation, temperature, and seasonality (p < 0.01). No other pollutant measures were significantly associated with sperm quality outcomes. Exposure to ambient ozone levels adversely affects semen quality.

Adult↗

PubMed2006

Efficient two-stage genome-wide association designs based on false positive report probabilities.

Despite recent advances, very-high-throughput (VHT) technologies capable of genotyping hundreds of thousands of SNPs in individual samples remain prohibitively expensive for the large studies necessary to screen substantial sections of the genome for variants with modest effects on disease risk. This paper presents a two-stage strategy, where a portion of available samples are genotyped with VHT technology, and a small number of the most promising variants are genotyped with standard high-throughput techniques in the remaining samples as an independent replication study. The sample sizes in the first and second stages and the corresponding significance levels are chosen to limit False Positive Report Probability (FPRP), while maximizing the number of Expected True Positives (ETPs). (The FPRP is the conditional probability that a marker is not truly associated with disease, given the a significant test for disease-marker association.) For a fixed budget, the two-stage strategy has greater power (a larger number of ETPs) than the single-stage strategy (where all subjects are genotyped using expensive VHT technology). Furthermore, concentrating on the FPRP leads to considerable savings relative to strategies designed to control the family-wise error (e.g. Bonferonni correction). The FPRP and number of ETPs can also accommodate researchers' prior beliefs about the number of causal loci and the magnitude of their effects. The expected number of false positives does not change if the true number and effects of causal loci differs from the specified prior (although the false discovery rate will vary), thus limiting the absolute amount of resources spent chasing "false leads."

Computational Biology↗

PubMed2005

Genomic screening in family-based association testing.

Due to the recent gains in the availability of single-nucleotide polymorphism data, genome-wide association testing has become feasible. It is hoped that this additional data may confirm the presence of disease susceptibility loci, and identify new genetic determinants of disease. However, the problem of multiple comparisons threatens to diminish any potential gains from this newly available data. To circumvent the multiple comparisons issue, we utilize a recently developed screening technique using family-based association testing. This screening methodology allows for the identification of the most promising single-nucleotide polymorphisms for testing without biasing the nominal significance level of our test statistic. We compare the results of our screening technique across univariate and multivariate family-based association tests. From our analyses, we observe that the screening technique, applied to different settings, is fairly consistent in identifying optimal markers for testing. One of the identified markers, TSC0047225, was significantly associated with both the ttth1 (p = 0.004) and ttth1-ttth4 (p = 0.004) phenotype(s). We find that both univariate- and multivariate-based screening techniques are powerful tools for detecting an association.

Family↗

PubMed2005

Comparison of linkage and association strategies for quantitative traits using the COGA dataset.

Genome scans using dense single-nucleotide polymorphism (SNP) data have recently become a reality. It is thought that the increase in information content for linkage analysis as a result of the denser scans will help refine previously identified linkage regions and possibly identify new regions not identifiable using the sparser, microsatellite scans. In the context of the dense SNP scans, it is also possible to consider association strategies to provide even more information about potential regions of interest. To circumvent the multiple-testing issues inherent in association analysis, we use a recently developed strategy, implemented in PBAT, which screens the data to identify the optimal SNPs for testing, without biasing the nominal significance level. We compare the results from the PBAT analysis to that of quantitative linkage analysis on chromosome 4 using the Collaborative Study on the Genetics of Alcoholism data, as released through Genetic Analysis Workshop 14.

Alcoholism↗

PubMed2005

Sequence variants of Toll-like receptor 4 and susceptibility to prostate cancer.

Chronic inflammation has been hypothesized to be a risk factor for prostate cancer. The Toll-like receptor 4 (TLR4) presents the bacterial lipopolysaccharide (LPS), which interacts with ligand-binding protein and CD14 (LPS receptor) and activates expression of inflammatory genes through nuclear factor-kappaB and mitogen-activated protein kinase signaling. A previous case-control study found a modest association of a polymorphism in the TLR4 gene [11381G/C, GG versus GC/CC: odds ratio (OR), 1.26] with risk of prostate cancer. We assessed if sequence variants of TLR4 were associated with the risk of prostate cancer. In a nested case-control design within the Health Professionals Follow-up Study, we identified 700 participants with prostate cancer diagnosed after they had provided a blood specimen in 1993 and before January 2000. Controls were 700 age-matched men without prostate cancer who had had a prostate-specific antigen test after providing a blood specimen. We genotyped 16 common (>5%) single nucleotide polymorphisms (SNP) discovered in a resequencing study spanning TLR4 to test for association between sequence variation in TLR4 and prostate cancer. Homozygosity for the variant alleles of eight SNPs was associated with a statistically significantly lower risk of prostate cancer (TLR4_1893, TLR4_2032, TLR4_2437, TLR4_7764, TLR4_11912, TLR4_16649, TLR4_17050, and TLR4_17923), but the TLR4_15844 polymorphism corresponding to 11381G/C was not associated with prostate cancer (GG versus CG/CC: OR, 1.01; 95% confidence interval, 0.79-1.29). Six common haplotypes (cumulative frequency, 81%) were observed; the global test for association between haplotypes and prostate cancer was statistically significant (chi(2) = 14.8 on 6 degrees of freedom; P = 0.02). Two common haplotypes were statistically significantly associated with altered risk of prostate cancer. Inherited polymorphisms of the innate immune gene TLR4 are associated with risk of prostate cancer.

Adult↗

PubMed2005

Glucose requirement for hypoxic accumulation of hypoxia-inducible factor-1alpha (HIF-1alpha).

Hypoxia-inducible factor-1alpha (HIF-1alpha) is both a potential endogenous marker of tumor hypoxia and therapeutic target, and elevated HIF-1alpha protein levels have been shown to be associated with increased hypoxic radiation resistance in FaDu human pharyngeal carcinoma cells in vitro. Here, we found that in FaDu xenografts, no significant HIF-1alpha protein accumulation was detectable by either flow cytometry or Western blot, despite the presence of hypoxic (pimonidazole-positive, radiation resistant) cells. To investigate the effect of different tumor microenvironment conditions on hypoxic HIF-1alpha accumulation, we performed in vitro hypoxia experiments (0.1% O2, 24 h) with manipulation of pH (7.4 vs. 6.7), glucose (0-5.5 mM) and serum (0 or 10%) availability in FaDu and HT 1080 human fibrosarcoma cells. Hypoxic induction of HIF-1alpha protein was strongly dependent on glucose availability and largely abolished at 0.55 mM glucose or less in both cell lines. This glucose effect was confirmed in a hypoxia-responsive-element (HRE)/enhanced-green-fluorescent-protein (EGFP) reporter assay in transfected HT 1080 cells and possibly explains a lack of HIF-1alpha protein in hypoxic tumor cells.

Animals↗

PubMed2005

Genetic variation in the HSD17B1 gene and risk of prostate cancer.

Steroid hormones are believed to play an important role in prostate carcinogenesis, but epidemiological evidence linking prostate cancer and steroid hormone genes has been inconclusive, in part due to small sample sizes or incomplete characterization of genetic variation at the locus of interest. Here we report on the results of a comprehensive study of the association between HSD17B1 and prostate cancer by the Breast and Prostate Cancer Cohort Consortium, a large collaborative study. HSD17B1 encodes 17beta-hydroxysteroid dehydrogenase 1, an enzyme that converts dihydroepiandrosterone to the testosterone precursor Delta5-androsterone-3beta,17beta-diol and converts estrone to estradiol. The Breast and Prostate Cancer Cohort Consortium researchers systematically characterized variation in HSD17B1 by targeted resequencing and dense genotyping; selected haplotype-tagging single nucleotide polymorphisms (htSNPs) that efficiently predict common variants in U.S. and European whites, Latinos, Japanese Americans, and Native Hawaiians; and genotyped these htSNPs in 8,290 prostate cancer cases and 9,367 study-, age-, and ethnicity-matched controls. We found no evidence that HSD17B1 htSNPs (including the nonsynonymous coding SNP S312G) or htSNP haplotypes were associated with risk of prostate cancer or tumor stage in the pooled multiethnic sample or in U.S. and European whites. Analyses stratified by age, body mass index, and family history of disease found no subgroup-specific associations between these HSD17B1 htSNPs and prostate cancer. We found significant evidence of heterogeneity in associations between HSD17B1 haplotypes and prostate cancer across ethnicity: one haplotype had a significant (p < 0.002) inverse association with risk of prostate cancer in Latinos and Japanese Americans but showed no evidence of association in African Americans, Native Hawaiians, or whites. However, the smaller numbers of Latinos and Japanese Americans in this study makes these subgroup analyses less reliable. These results suggest that the germline variants in HSD17B1 characterized by these htSNPs do not substantially influence the risk of prostate cancer in U.S. and European whites.

17-Hydroxysteroid Dehydrogenases↗

PubMed2005

Integrating epidemiology and genetic association: the challenge of gene-environment interaction.

Recent advances in human genomics have made it possible to better understand the genetic basis of disease. In addition, genetic association studies can also elucidate the mechanisms by which "non-genetic" exogenous and endogenous exposures influence the risk of disease. This is true both of studies that assess the marginal effect of a single gene and studies that look at the joint effect of genes and environmental exposures. For example, gene variants that are known to alter enzyme function or level can serve as surrogates for long-term biomarker levels that are impractical or impossible to measure on many subjects. Evidence that genetic variants modify the effect of an established risk factor may help specify the risk factor's biologically active components. We illustrate these ideas with several examples and discuss design and analysis challenges, particularly for studies of gene-environment interaction. We argue that to increase the power to detect interaction effects and limit the number of false positive results, large sample sizes will be needed, which are currently only available through planned collaborative efforts. Such collaborations also ensure a common approach to measuring variation at a genetic locus, avoiding a problem that has led to difficulties when comparing results from genetic association studies.

Environmental Exposure↗