基于DNA变异在亚欧混合人群中预测男性型脱发

男性型脱发(male pattern baldness,MPB)是一种雄激素依赖性的遗传性脱发疾病,对个人形象、心理产生较大的消极影响.近期欧美人群中进行的大样本全基因组关联分析(genome wide association studies,GWAS)已报道大量与MPB相关的遗传易感性单核苷酸多态性(single nucleotide polymorphisms,SNPs)位点,但这些位点在东亚人群中的遗传效应尚不清楚.本研究基于我国684个亚欧混合人群(Eurasian)样本,对在英国生物样本库(UK Biobank) 205 327个欧洲男性GWAS分析发现的624个与MPB相关的SNPs进行人群异质性分析,基于多基因风险打分(polygenic risk scores,PRS)建立预测模型,并对预测因子数量与模型预测性能的关系进行了研究.通过质控的467个SNPs中6.9%与MPB显著相关(P0.05).结合年龄、体质指数(body mass index,BMI)和25个SNPs建立的线性回归和逻辑回归模型,效果较好(R~2=28.9%,AUC=0.82).年龄对模型效果影响较大(R~2=22.9%,AUC=0.77),结合BMI及68个SNPs时AUC达到最大(约0.89).本研究表明MPB在欧洲和东亚人群中存在较强的遗传异质性,选取SNPs子集能达到与全集相近的预测准确性,预测模型有助于东亚人群MPB遗传机制的理解及疾病的早期诊断和预防.     

基于DNA变异的中国汉族人群脱发表型推断及预测模型评估

目的 男性型脱发（male pattern baldness,MPB）,又称为雄激素性脱发（AGA）,是一种常见的男性脱发类型,大约80%的表型差异可以用遗传因素解释。目前的MPB遗传推断研究主要基于欧洲人群,东亚人群相关研究较少。本研究在中国人群中对欧洲人群MPB关联位点进行验证分析,并建立遗传推断模型。方法 本研究调查了486个与欧洲人群MPB相关单核苷酸多态性（SNP）位点在312名中国汉族男性中的关联性,分别使用逐步回归和Lasso回归方法对关联出的位点进行筛选。使用逻辑回归算法构建预测模型,通过十折交叉验证的方法评估。之后进一步比较了逻辑回归、k近邻分类器、随机森林、支持向量机4种常用分类器模型对MPB的预测准确性。结果 有174个SNP位点与中国汉族男性的MPB显著相关（P＜0.05）。通过不同的筛选方法,分别得到了22个SNP和25个SNP的位点集合。基于上述位点集合建立了22-SNP和 25-SNP两种逻辑回归预测模型。以AUC（ROC曲线下方的面积大小,area under curve）来衡量,两种模型对MPB预测的准确性分别为0.85和0.84;经十折交叉验证后预测准确性分别下降至0.81和0.77。当加入年龄作为预测因子后,两种模型的AUC均达到最大值0.89。从运行结果来看,逻辑回归预测模型较本研究中的其他分类器模型具有明显优势。结论 总体而言,虽然预测模型的准确性尚未达到临床期望水平,但SNP在MPB的遗传预测方面仍具备很大的潜力,可以为MPB的早期诊断、临床干预和法庭科学应用提供参考。     

Genetic variants associated with breast cancer risk for Ashkenazi Jewish women with strong family histories but no identifiable BRCA1/2 mutation

The ability to establish genetic risk models is critical for early identification and optimal treatment of breast cancer. For such a model to gain clinical utility, more variants must be identified beyond those discovered in previous genome-wide association studies (GWAS). This is especially true for women at high risk because of family history, but without BRCA1/2 mutations. This study incorporates three datasets in a GWAS analysis of women with Ashkenazi Jewish (AJ) homogeneous ancestry. Two independent discovery cohorts comprised 239 and 238 AJ women with invasive breast cancer or preinvasive ductal carcinoma in situ and strong family histories of breast cancer, but lacking the three BRCA1/2 founder mutations, along with 294 and 230 AJ controls, respectively. An independent, third cohort of 203 AJ cases with familial breast cancer history and 263 healthy controls of AJ women was used for validation. A total of 19 SNPs were identified as associated with familial breast cancer risk in AJ women. Among these SNPs, 13 were identified from a panel of 109 discovery SNPs, including an FGFR2 haplotype. In addition, six previously identified breast cancer GWAS SNPs were confirmed in this population. Seven of the 19 markers were significant in a multivariate predictive model of familial breast cancer in AJ women, three novel SNPs [rs17663555(5q13.2), rs566164(6q21), and rs11075884(16q22.2)], the FGFR2 haplotype, and three previously published SNPs [rs13387042(2q35), rs2046210(ESR1), and rs3112612(TOX3)], yielding moderate predictive power with an area under the curve (AUC) of the ROC (receiver-operator characteristic curve) of 0.74. Population-specific genetic variants in addition to variants shared with populations of European ancestry may improve breast cancer risk prediction among AJ women from high-risk families without founder BRCA1/2 mutations.     

Clinical Utility of a Coronary Heart Disease Risk Prediction Gene Score in UK Healthy Middle Aged Men and in the Pakistani Population

BackgroundNumerous risk prediction algorithms based on conventional risk factors for Coronary Heart Disease (CHD) are available but provide only modest discrimination. The inclusion of genetic information may improve clinical utility.MethodsWe tested the use of two gene scores (GS) in the prospective second Northwick Park Heart Study (NPHSII) of 2775 healthy UK men (284 cases), and Pakistani case-control studies from Islamabad/Rawalpindi (321 cases/228 controls) and Lahore (414 cases/219 controls). The 19-SNP GS included SNPs in loci identified by GWAS and candidate gene studies, while the 13-SNP GS only included SNPs in loci identified by the CARDIoGRAMplusC4D consortium.ResultsIn NPHSII, the mean of both gene scores was higher in those who went on to develop CHD over 13.5 years of follow-up (19-SNP p=0.01, 13-SNP p=7x10^-3). In combination with the Framingham algorithm the GSs appeared to show improvement in discrimination (increase in area under the ROC curve, 19-SNP p=0.48, 13-SNP p=0.82) and risk classification (net reclassification improvement (NRI), 19-SNP p=0.28, 13-SNP p=0.42) compared to the Framingham algorithm alone, but these were not statistically significant. When considering only individuals who moved up a risk category with inclusion of the GS, the improvement in risk classification was statistically significant (19-SNP p=0.01, 13-SNP p=0.04). In the Pakistani samples, risk allele frequencies were significantly lower compared to NPHSII for 13/19 SNPs. In the Islamabad study, the mean gene score was higher in cases than controls only for the 13-SNP GS (2.24 v 2.34, p=0.04). There was no association with CHD and either score in the Lahore study.ConclusionThe performance of both GSs showed potential clinical utility in European men but much less utility in subjects from Pakistan, suggesting that a different set of risk loci or SNPs may be required for risk prediction in the South Asian population.     

Genetic Markers Enhance Coronary Risk Prediction in Men: The MORGAM Prospective Cohorts

Background

More accurate coronary heart disease (CHD) prediction, specifically in middle-aged men, is needed to reduce the burden of disease more effectively. We hypothesised that a multilocus genetic risk score could refine CHD prediction beyond classic risk scores and obtain more precise risk estimates using a prospective cohort design.

Methods

Using data from nine prospective European cohorts, including 26,221 men, we selected in a case-cohort setting 4,818 healthy men at baseline, and used Cox proportional hazards models to examine associations between CHD and risk scores based on genetic variants representing 13 genomic regions. Over follow-up (range: 5–18 years), 1,736 incident CHD events occurred. Genetic risk scores were validated in men with at least 10 years of follow-up (632 cases, 1361 non-cases). Genetic risk score 1 (GRS1) combined 11 SNPs and two haplotypes, with effect estimates from previous genome-wide association studies. GRS2 combined 11 SNPs plus 4 SNPs from the haplotypes with coefficients estimated from these prospective cohorts using 10-fold cross-validation. Scores were added to a model adjusted for classic risk factors comprising the Framingham risk score and 10-year risks were derived.

Results

Both scores improved net reclassification (NRI) over the Framingham score (7.5%, p = 0.017 for GRS1, 6.5%, p = 0.044 for GRS2) but GRS2 also improved discrimination (c-index improvement 1.11%, p = 0.048). Subgroup analysis on men aged 50–59 (436 cases, 603 non-cases) improved net reclassification for GRS1 (13.8%) and GRS2 (12.5%). Net reclassification improvement remained significant for both scores when family history of CHD was added to the baseline model for this male subgroup improving prediction of early onset CHD events.

Conclusions

Genetic risk scores add precision to risk estimates for CHD and improve prediction beyond classic risk factors, particularly for middle aged men.     

Male pattern baldness and prostate cancer risk in a population-based case–control study

Purpose: Male pattern baldness (MPB) and prostate cancer (PCa) share commonality as prevalent, heritable and androgen-related conditions. Studies exploring the relationship between the two conditions have been inconclusive. Using a population-based, case–control study of PCa, we explore the relationship between early-onset MPB and PCa risk. Methods: Cases were men aged 35–74 diagnosed with PCa between 2002 and 2005 in King County, Washington. Controls were frequency matched by age and identified by random digit dialing. Hair pattern at age 30 and at 1 year prior to diagnosis (cases) or reference date (controls) was determined using showcards. PCa risk associated with balding was assessed with logistic regression. Results: Data from 999 cases of PCa and 942 controls were analyzed. Hair loss at age 30 was more common in controls (25.2%) than cases (19.8%, p = 0.005), and those with hair loss at age 30 had a 29% relative risk reduction for PCa (OR 0.71, 95% CI 0.56–0.91). No risk reduction was seen for men only reporting hair loss at referent age (OR 0.90, 95% CI 0.73–1.12). In men aged >60 at referent date, the risk reduction was greater for men with hair loss at age 30 from both the top of head and forehead (OR 0.55, 95% CI 0.33–0.93). Conclusion: Early-onset MPB was associated with a reduced relative risk of PCa in this population-based study. Further research into a possible mechanistic link between these prevalent and androgen-related conditions is warranted.     

Eye color prediction using single nucleotide polymorphisms in Saudi population

BackgroundDNA prediction of eye color represent one application of the externally visible characteristics (EVC), which attained growing interest in the field of DNA forensic phenotyping. This is mainly due to its ability to narrow the pool of suspects without the need to compare any retrieved DNA material from the crime scene to a reference DNA. Several methods and multiplex genetic panel were proposed with variable prediction accuracy between different populations. However, such panel was not previously tested in the Saudi population, nor any populations of the Middle East and North Africa origin.MethodA panel of eleven single nucleotide polymorphisms (SNPs) was tested for their association with three eye colors (brown, hazel, and intermediate) in 80 volunteer Saudi individuals. SNPs and haplotype association test with eye colors were performed to identify the top significant SNPs with the three eye colors. Also, multinomial logistic regression was used to construct the prediction model using a training set of 60 subjects, and a validation set of 20 subjects. The goodness of fit parameter of the model to correctly predicts each eye color as compared to the other was performed.ResultsEye color was significantly associated with rs12913832, rs7170852, and rs916977 that are located within HERC2. SNP rs12913832 was the top significant SNP (p-value = 1.78E?15) that accounted for the association in this region, as the other SNPs were not significant after adjusting for rs12913832. A prediction model containing five SNPs showed high prediction accuracy with Area Under the receiver operating characteristic Curves (AUC) equals to 0.95 and 0.83 for brown and intermediate eye colors, respectively. However, the model’s performance was very low for predicting the hazel eye color with AUC equals 0.75.DiscussionDespite the small sample size of our study, we reported very significant SNP associations with eye color. Our model to predict eye colors based on DNA material showed high accuracy for brown and intermediate eye colors. The eye color prediction-model underperformed for the hazel eye colors, suggesting that larger sample size, as well as more comprehensive set of SNPs, could improve the model-prediction accuracy.     

Replication and Predictive Value of SNPs Associated with Melanoma and Pigmentation Traits in a Southern European Case-Control Study

Background

Genetic association studies have revealed numerous polymorphisms conferring susceptibility to melanoma. We aimed to replicate previously discovered melanoma-associated single-nucleotide polymorphisms (SNPs) in a Greek case-control population, and examine their predictive value.

Methods

Based on a field synopsis of genetic variants of melanoma (MelGene), we genotyped 284 patients and 284 controls at 34 melanoma-associated SNPs of which 19 derived from GWAS. We tested each one of the 33 SNPs passing quality control for association with melanoma both with and without accounting for the presence of well-established phenotypic risk factors. We compared the risk allele frequencies between the Greek population and the HapMap CEU sample. Finally, we evaluated the predictive ability of the replicated SNPs.

Results

Risk allele frequencies were significantly lower compared to the HapMap CEU for eight SNPs (rs16891982 – SLC45A2, rs12203592 – IRF4, rs258322 – CDK10, rs1805007 – MC1R, rs1805008 - MC1R, rs910873 - PIGU, rs17305573- PIGU, and rs1885120 - MTAP) and higher for one SNP (rs6001027 – PLA2G6) indicating a different profile of genetic susceptibility in the studied population. Previously identified effect estimates modestly correlated with those found in our population (r = 0.72, P<0.0001). The strongest associations were observed for rs401681-T in CLPTM1L (odds ratio [OR] 1.60, 95% CI 1.22–2.10; P = 0.001), rs16891982-C in SCL45A2 (OR 0.51, 95% CI 0.34–0.76; P = 0.001), and rs1805007-T in MC1R (OR 4.38, 95% CI 2.03–9.43; P = 2×10⁻⁵). Nominally statistically significant associations were seen also for another 5 variants (rs258322-T in CDK10, rs1805005-T in MC1R, rs1885120-C in MYH7B, rs2218220-T in MTAP and rs4911442-G in the ASIP region). The addition of all SNPs with nominal significance to a clinical non-genetic model did not substantially improve melanoma risk prediction (AUC for clinical model 83.3% versus 83.9%, p = 0.66).

Conclusion

Overall, our study has validated genetic variants that are likely to contribute to melanoma susceptibility in the Greek population.     

Characterization of SNPs Associated with Prostate Cancer in Men of Ashkenazic Descent from the Set of GWAS Identified SNPs: Impact of Cancer Family History and Cumulative SNP Risk Prediction

Background

Genome-wide association studies (GWAS) have identified multiple SNPs associated with prostate cancer (PrCa). Population isolates may have different sets of risk alleles for PrCa constituting unique population and individual risk profiles.

Methods

To test this hypothesis, associations between 31 GWAS SNPs of PrCa were examined among 979 PrCa cases and 1,251 controls of Ashkenazic descent using logistic regression. We also investigated risks by age at diagnosis, pathological features of PrCa, and family history of cancer. Moreover, we examined associations between cumulative number of risk alleles and PrCa and assessed the utility of risk alleles in PrCa risk prediction by comparing the area under the curve (AUC) for different logistic models.

Results

Of the 31 genotyped SNPs, 8 were associated with PrCa at p≤0.002 (corrected p-value threshold) with odds ratios (ORs) ranging from 1.22 to 1.42 per risk allele. Four SNPs were associated with aggressive PrCa, while three other SNPs showed potential interactions for PrCa by family history of PrCa (rs8102476; 19q13), lung cancer (rs17021918; 4q22), and breast cancer (rs10896449; 11q13). Men in the highest vs. lowest quartile of cumulative number of risk alleles had ORs of 3.70 (95% CI 2.76–4.97); 3.76 (95% CI 2.57–5.50), and 5.20 (95% CI 2.94–9.19) for overall PrCa, aggressive cancer and younger age at diagnosis, respectively. The addition of cumulative risk alleles to the model containing age at diagnosis and family history of PrCa yielded a slightly higher AUC (0.69 vs. 0.64).

Conclusion

These data define a set of risk alleles associated with PrCa in men of Ashkenazic descent and indicate possible genetic differences for PrCa between populations of European and Ashkenazic ancestry. Use of genetic markers might provide an opportunity to identify men at highest risk for younger age of onset PrCa; however, their clinical utility in identifying men at highest risk for aggressive cancer remains limited.     

Apolipoprotein(a) Kringle-IV Type 2 Copy Number Variation Is Associated with Venous Thromboembolism

In addition to the established association between high lipoprotein(a) [Lp(a)] concentrations and coronary artery disease, an association between Lp(a) and venous thromboembolism (VTE) has also been described. Lp(a) is controlled by genetic variants in LPA gene, coding for apolipoprotein(a), including the kringle-IV type 2 (KIV-2) size polymorphism. Aim of the study was to investigate the role of LPA gene KIV-2 size polymorphism and single nucleotide polymorphisms (SNPs) (rs1853021, rs1800769, rs3798220, rs10455872) in modulating VTE susceptibility. Five hundred and sixteen patients with VTE without hereditary and acquired thrombophilia and 1117 healthy control subjects, comparable for age and sex, were investigated. LPA KIV-2 polymorphism, rs3798220 and rs10455872 SNPs were genotyped by TaqMan technology. Concerning rs1853021 and rs1800769 SNPs, PCR-RFLP assay was used. LPA KIV-2 repeat number was significantly lower in patients than in controls [median (interquartile range) 11(6–17) vs 15(9–25), p<0.0001]. A significantly higher prevalence of KIV-2 repeat number ≤7 was observed in patients than in controls (33.5% vs 15.5%, p<0.0001). KIV-2 repeat number was independently associated with VTE (p = 4.36 x10^-9), as evidenced by the general linear model analysis adjusted for transient risk factors. No significant difference in allele frequency for all SNPs investigated was observed. Haplotype analysis showed that LPA haplotypes rather than individual SNPs influenced disease susceptibility. Receiver operating characteristic curves analysis showed that a combined risk prediction model, including KIV-2 size polymorphism and clinical variables, had a higher performance in identifying subjects at VTE risk than a clinical-only model, also separately in men and women.     

Predicting the Risk of Rheumatoid Arthritis and Its Age of Onset through Modelling Genetic Risk Variants with Smoking

The improved characterisation of risk factors for rheumatoid arthritis (RA) suggests they could be combined to identify individuals at increased disease risks in whom preventive strategies may be evaluated. We aimed to develop an RA prediction model capable of generating clinically relevant predictive data and to determine if it better predicted younger onset RA (YORA). Our novel modelling approach combined odds ratios for 15 four-digit/10 two-digit HLA-DRB1 alleles, 31 single nucleotide polymorphisms (SNPs) and ever-smoking status in males to determine risk using computer simulation and confidence interval based risk categorisation. Only males were evaluated in our models incorporating smoking as ever-smoking is a significant risk factor for RA in men but not women. We developed multiple models to evaluate each risk factor''s impact on prediction. Each model''s ability to discriminate anti-citrullinated protein antibody (ACPA)-positive RA from controls was evaluated in two cohorts: Wellcome Trust Case Control Consortium (WTCCC: 1,516 cases; 1,647 controls); UK RA Genetics Group Consortium (UKRAGG: 2,623 cases; 1,500 controls). HLA and smoking provided strongest prediction with good discrimination evidenced by an HLA-smoking model area under the curve (AUC) value of 0.813 in both WTCCC and UKRAGG. SNPs provided minimal prediction (AUC 0.660 WTCCC/0.617 UKRAGG). Whilst high individual risks were identified, with some cases having estimated lifetime risks of 86%, only a minority overall had substantially increased odds for RA. High risks from the HLA model were associated with YORA (P<0.0001); ever-smoking associated with older onset disease. This latter finding suggests smoking''s impact on RA risk manifests later in life. Our modelling demonstrates that combining risk factors provides clinically informative RA prediction; additionally HLA and smoking status can be used to predict the risk of younger and older onset RA, respectively.     

Association of two variants in the interleukin-6 receptor gene and premature coronary heart disease in a Chinese Han population

Two novel single nucleotide polymorphisms (SNPs; rs7529229 and rs2228145) in the interleukin-6 receptor (IL6R) gene have recently been associated with coronary heart disease (CHD) in a European population. We sought to replicate this finding and to investigate associations of these two SNPs with the severity and clinical phenotypes of premature CHD in a Chinese Han population. A total of 418 patients were studied, including 187 cases with coronary stenosis ≥50 % or acute myocardial infarction (males < 55 years and females < 65 years) and 231 controls without documented CHD. A ligase detection reaction was performed to detect rs7529229 and rs2228145. There were no differences between the controls and premature CHD groups in the frequencies for the three genotypes and alleles of rs7529229 and rs2228145 (all P > 0.05), nor did they differ between the two groups when grouped by gender (all P > 0.05). There were also no associations between these two SNPs and the severity of coronary lesions or clinical phenotypes of premature CHD (all P > 0.05). Our results do not support an association between rs7529229 or rs2228145 with premature CHD in the Chinese Han population. Further studies are warranted to elucidate the role of these two SNPs in the development of atherosclerosis and CHD.     

No Interaction with Alcohol Consumption,but Independent Effect of C12orf51 (HECTD4) on Type 2 Diabetes Mellitus in Korean Adults Aged 40-69 Years: The KoGES_Ansan and Ansung Study

Previously, genetic polymorphisms of C12orf51 (HECTD4) (rs2074356 and/or rs11066280) have been shown to be related to alcohol consumption and type 2 diabetes (T2D). This study aimed to prospectively examine whether C12orf51 had an interaction with or independent effect on alcohol consumption and the risk of T2D. The present study included 3,244 men and 3,629 women aged 40 to 69 years who participated in the Korean Genome and Epidemiology Study (KoGES)_Ansan and Ansung Study. Cox proportional hazards models were used to estimate HRs and 95% CIs for T2D. rs2074356 and rs11066280 were associated with the risk of T2D after adjusting for alcohol consumption (rs2074356 for AA: HR = 0.39 and 95% CI = 0.17–0.87 in men, and HR = 0.36 and 95% CI = 0.13–0.96 in women; rs11066280 for AA: HR = 0.44 and 95% CI = 0.23–0.86 in men, and HR = 0.39 and 95% CI = 0.16–0.94 in women). We identified that the association of each variant (rs2074356 and rs11065756) in C12orf51 was nearly unchanged after adjusted for alcohol consumption. Therefore, the association of 2 SNPs in C12orf51 with diabetes may not be mediated by alcohol use. There was no interaction effect between alcohol consumption and the SNPs with T2D. However, even in never-drinkers, minor allele homozygote strongly influenced T2D risk reduction (rs2074356 for AA: HR = 0.35, 95% CI = 0.14–0.90, and p-trend = 0.0035 in men and HR = 0.34, 95% CI = 0.13–0.93, and p-trend = 0.2348 in women; rs11066280 for AA: HR = 0.36, 95% CI = 0.16–0.82, and p-trend = 0.0014 in men and HR = 0.39, 95% CI = 0.16–0.95, and p-trend = 0.3790 in women), while alcohol consumption did not influence the risk of T2D within each genotype. rs2074356 and rs11066280 in or near C12orf51, which is related to alcohol drinking behavior, may longitudinally decrease the risk of T2D, but not through regulation of alcohol consumption.     

Association of TERC and OBFC1 Haplotypes with Mean Leukocyte Telomere Length and Risk for Coronary Heart Disease

Objective

To replicate the associations of leukocyte telomere length (LTL) with variants at four loci and to investigate their associations with coronary heart disease (CHD) and type II diabetes (T2D), in order to examine possible causal effects of telomere maintenance machinery on disease aetiology.

Methods

Four SNPs at three loci BICD1 (rs2630578 GγC), 18q12.2 (rs2162440 GγT), and OBFC1 (rs10786775 CγG, rs11591710 AγC) were genotyped in four studies comprised of 2353 subjects out of which 1148 had CHD and 566 T2D. Three SNPs (rs12696304 CγG, rs10936601G>T and rs16847897 GγC) at the TERC locus were genotyped in these four studies, in addition to an offspring study of 765 healthy students. For all samples, LTL had been measured using a real-time PCR-based method.

Results

Only one SNP was associated with a significant effect on LTL, with the minor allele G of OBFC1 rs10786775 SNP being associated with longer LTL (β=0.029, P=0.04). No SNPs were significantly associated with CHD or T2D. For OBFC1 the haplotype carrying both rare alleles (rs10786775G and rs11591710C, haplotype frequency 0.089) was associated with lower CHD prevalence (OR: 0.77; 95% CI: 0.61–0.97; P= 0.03). The TERC haplotype GTC (rs12696304G, rs10936601T and rs16847897C, haplotype frequency 0.210) was associated with lower risk for both CHD (OR: 0.86; 95% CI: 0.75-0.99; P=0.04) and T2D (OR: 0.74; 95% CI: 0.61–0.91; P= 0.004), with no effect on LTL. Only the last association remained after adjusting for multiple testing.

Conclusion

Of reported associations, only that between the OBFC1 rs10786775 SNP and LTL was confirmed, although our study has a limited power to detect modest effects. A 2-SNP OBFC1 haplotype was associated with higher risk of CHD, and a 3-SNP TERC haplotype was associated with both higher risk of CHD and T2D. Further work is required to confirm these results and explore the mechanisms of these effects.     

Extent and consistency of linkage disequilibrium and identification of DNA markers for production and egg quality traits in commercial layer chicken populations

Background

The genome sequence and a high-density SNP map are now available for the chicken and can be used to identify genetic markers for use in marker-assisted selection (MAS). Effective MAS requires high linkage disequilibrium (LD) between markers and quantitative trait loci (QTL), and sustained marker-QTL LD over generations. This study used data from a 3,000 SNP panel to assess the level and consistency of LD between single nucleotide polymorphisms (SNPs) over consecutive years in two egg-layer chicken lines, and analyzed one line by two methods (SNP-wise association and genome-wise Bayesian analysis) to identify markers associated with egg-quality and egg-production phenotypes.

Results

The LD between markers pairs was high at short distances (r² > 0.2 at < 2 Mb) and remained high after one generation (correlations of 0.80 to 0.92 at < 5 Mb) in both lines. Single- and 3-SNP regression analyses using a mixed model with SNP as fixed effect resulted in 159 and 76 significant tests (P < 0.01), respectively, across 12 traits. A Bayesian analysis called BayesB, that fits all SNPs simultaneously as random effects and uses model averaging procedures, identified 33 SNPs that were included in the model >20% of the time (φ > 0.2) and an additional ten 3-SNP windows that had a sum of φ greater than 0.35. Generally, SNPs included in the Bayesian model also had a small P-value in the 1-SNP analyses.

Conclusion

High LD correlations between markers at short distances across two generations indicate that such markers will retain high LD with linked QTL and be effective for MAS. The different association analysis methods used provided consistent results. Multiple single SNPs and 3-SNP windows were significantly associated with egg-related traits, providing genomic positions of QTL that can be useful for both MAS and to identify causal mutations.

     

Polymorphisms in the mTOR Gene and Risk of Sporadic Prostate Cancer in an Eastern Chinese Population

Background

The mTOR gene regulates cell growth by controlling mRNA translation, ribosome biogenesis, autophagy, and metabolism. Abnormally increased expression of mTOR was associated with carcinogenesis, and its functional single nucleotide polymorphisms (SNPs) may regulate the expression of mTOR and thus contribute to cancer risk.

Methodology/Principal Findings

In a hospital-based case-control study of 1004 prostate cancer (PCa) cases and 1051 cancer-free controls, we genotyped six potentially functional SNPs of mTOR (rs2536 T>C, rs1883965 G>A, rs1034528 G>C, rs17036508 T>C, rs3806317 A>G, and rs2295080 T>G) and assessed their associations with risk of PCa by using logistic regression analysis.

Conclusions/Significances

In the single-locus analysis, we found a significantly increased risk of PCa associated with mTOR rs2536 CT/CC and rs1034528 CG/CC genotypes [adjusted OR = 1.42 (1.13–1.78), P = 0.003 and 1.29 (1.07–1.55), P = 0.007), respectively], compared with their common homozygous genotypes, whereas mTOR rs2295080 GT/GG genotypes were associated with a decreased risk of PCa [adjusted OR = 0.76 (0.64–0.92), P = 0.003], compared with wild-type TT genotypes. In the combined analysis of the six SNPs, we found that individuals carrying two or more adverse genotypes had an increased risk of PCa [adjusted OR = 1.24 (1.04–1.47), P = 0.016], compared with individuals carrying less than two adverse genotypes. In the multiple dimension reduction analysis, body mass index (BMI) was the best one-factor model with the highest CVC (100%) and the lowest prediction error (42.7%) among all seven factors. The model including an interaction among BMI, rs17036508, and rs2536 was the best three-factor model with the highest CVC (100%) and the lowest prediction error of 41.9%. These findings suggested that mTOR SNPs may contribute to the risk of PCa in Eastern Chinese men, but the effect was weak and needs further validation by larger population-based studies.     

The ESR1 (6q25) locus is associated with calcaneal ultrasound parameters and radial volumetric bone mineral density in European men

Purpose

Genome-wide association studies (GWAS) have identified 6q25, which incorporates the oestrogen receptor α gene (ESR1), as a quantitative trait locus for areal bone mineral density (BMD_a) of the hip and lumbar spine. The aim of this study was to determine the influence of this locus on other bone health outcomes; calcaneal ultrasound (QUS) parameters, radial peripheral quantitative computed tomography (pQCT) parameters and markers of bone turnover in a population sample of European men.

Methods

Eight single nucleotide polymorphisms (SNP) in the 6q25 locus were genotyped in men aged 40–79 years from 7 European countries, participating in the European Male Ageing Study (EMAS). The associations between SNPs and measured bone parameters were tested under an additive genetic model adjusting for centre using linear regression.

Results

2468 men, mean (SD) aged 59.9 (11.1) years had QUS measurements performed and bone turnover marker levels measured. A subset of 628 men had DXA and pQCT measurements. Multiple independent SNPs showed significant associations with BMD using all three measurement techniques. Most notably, rs1999805 was associated with a 0.10 SD (95%CI 0.05, 0.16; p = 0.0001) lower estimated BMD at the calcaneus, a 0.14 SD (95%CI 0.05, 0.24; p = 0.004) lower total hip BMD_a, a 0.12 SD (95%CI 0.02, 0.23; p = 0.026) lower lumbar spine BMD_a and a 0.18 SD (95%CI 0.06, 0.29; p = 0.003) lower trabecular BMD at the distal radius for each copy of the minor allele. There was no association with serum levels of bone turnover markers and a single SNP which was associated with cortical density was also associated with cortical BMC and thickness.

Conclusions

Our data replicate previous associations found between SNPs in the 6q25 locus and BMD_a at the hip and extend these data to include associations with calcaneal ultrasound parameters and radial volumetric BMD.     

Selection of haplotype variables from a high-density marker map for genomic prediction

Background

Using haplotype blocks as predictors rather than individual single nucleotide polymorphisms (SNPs) may improve genomic predictions, since haplotypes are in stronger linkage disequilibrium with the quantitative trait loci than are individual SNPs. It has also been hypothesized that an appropriate selection of a subset of haplotype blocks can result in similar or better predictive ability than when using the whole set of haplotype blocks. This study investigated genomic prediction using a set of haplotype blocks that contained the SNPs with large effects estimated from an individual SNP prediction model. We analyzed protein yield, fertility and mastitis of Nordic Holstein cattle, and used high-density markers (about 770k SNPs). To reach an optimum number of haplotype variables for genomic prediction, predictions were performed using subsets of haplotype blocks that contained a range of 1000 to 50 000 main SNPs.

Results

The use of haplotype blocks improved the prediction reliabilities, even when selection focused on only a group of haplotype blocks. In this case, the use of haplotype blocks that contained the 20 000 to 50 000 SNPs with the highest effect was sufficient to outperform the model that used all individual SNPs as predictors (up to 1.3 % improvement in prediction reliability for mastitis, compared to individual SNP approach), and the achieved reliabilities were similar to those using all haplotype blocks available in the genome data (from 0.6 % lower to 0.8 % higher reliability).

Conclusions

Haplotype blocks used as predictors can improve the reliability of genomic prediction compared to the individual SNP model. Furthermore, the use of a subset of haplotype blocks that contains the main SNP effects from genomic data could be a feasible approach to genomic prediction in dairy cattle, given an increase in density of genotype data available. The predictive ability of the models that use a subset of haplotype blocks was similar to that obtained using either all haplotype blocks or all individual SNPs, with the benefit of having a much lower computational demand.     

Transient receptor potential genes, smoking, occupational exposures and cough in adults

Background

Transient receptor potential (TRP) vanilloid and ankyrin cation channels are activated by various noxious chemicals and may play an important role in the pathogenesis of cough. The aim was to study the influence of single nucleotide polymorphisms (SNPs) in TRP genes and irritant exposures on cough.

Methods

Nocturnal, usual, and chronic cough, smoking, and job history were obtained by questionnaire in 844 asthmatic and 2046 non-asthmatic adults from the Epidemiological study on the Genetics and Environment of Asthma (EGEA) and the European Community Respiratory Health Survey (ECRHS). Occupational exposures to vapors, gases, dusts, and/or fumes were assessed by a job-exposure matrix. Fifty-eight tagging SNPs in TRPV1, TRPV4, and TRPA1 were tested under an additive model.

Results

Statistically significant associations of 6 TRPV1 SNPs with cough symptoms were found in non-asthmatics after correction for multiple comparisons. Results were consistent across the eight countries examined. Haplotype-based association analysis confirmed the single SNP analyses for nocturnal cough (7-SNP haplotype: p-global = 4.8 × 10^-6) and usual cough (9-SNP haplotype: p-global = 4.5 × 10^-6). Cough symptoms were associated with exposure to irritants such as cigarette smoke and occupational exposures (p < 0.05). Four polymorphisms in TRPV1 further increased the risk of cough symptoms from irritant exposures in asthmatics and non-asthmatics (interaction p < 0.05).

Conclusions

TRPV1 SNPs were associated with cough among subjects without asthma from two independent studies in eight European countries. TRPV1 SNPs may enhance susceptibility to cough in current smokers and in subjects with a history of workplace exposures.