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ABSTRACT Background: Autophagy can inhibit the survival of intracellular microorganisms including Mycobacterium tuberculosis (Mtb), and the PI3K/AKT/mTOR pathway plays a crucial role. This study investigated the association between PI3K/AKT/mTOR pathway autophagy-related gene polymorphisms and pulmonary tuberculosis (PTB) susceptibility. Methods: KEGG pathway and gene ontology (GO) databases were searched for genes belonging to the PI3K/AKT/mTOR and autophagy pathways. Thirty SNPs in nine genes were identified and tested for their associations with tuberculosis in 130 patients with PTB and 271 controls. We constructed genetic risk scores (GRSs) and divided the participants into 3 subgroups based on their GRSs:0-5, 6-10, and 11-16. Results: This analysis revealed that the AKT1 (rs12432802), RPTOR (rs11654508, rs12602885, rs2090204, rs2589144, and rs2672897), and TSC2 (rs2074969) polymorphisms were significantly associated with PTB risk. A decreasing trend was observed (P trend 0.020), in which a lower GRS was associated with a higher risk of PTB ([6-10] vs. [0-5]: OR (95%CI) 0.590 (0.374-0.931); [11-16] vs. [0-5]: OR (95%CI) 0.381 (0.160-0.906)). Conclusions: Polymorphisms in AKT1, RPTOR, and TSC2 may influence susceptibility to PTB.
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Type 1 diabetes mellitus (T1DM) is characterized by autoimmune destruction of pancreatic beta-cells in genetically predisposed individuals, eventually resulting in severe insulin deficiency. It is the most common form of diabetes in children and adolescents. Genetic susceptibility plays a crucial role in development of T1DM. The human leukocyte antigen complex plays a key role in the pathogenesis of T1DM. Furthermore, genome-wide association studies and linkage analysis have recently made a significant contribution to current knowledge relative to the impact of genetics on T1DM development and progression. This review focuses on current knowledge of genetics as a pathogenesis for T1DM. It also discusses mechanisms by which genes influence the risk of developing T1DM as well as the clinical and research applications of genetic risk scores in T1DM.
Subject(s)
Adolescent , Child , Humans , Diabetes Mellitus, Type 1 , Genetic Predisposition to Disease , Genetics , Genome-Wide Association Study , Insulin , LeukocytesABSTRACT
Genetic risk score (GRS) based on disease risk-associated single nucleotide polymorphisms (SNPs) is an informative tool that can be used to provide inherited information for specific diseases in addition to family history. However, it is still unknown whether only SNPs that are implicated in a specific racial group should be used when calculating GRSs. The objective of this study is to compare the performance of race-specific GRS and nonrace-specific GRS for predicting prostate cancer (PCa) among 1338 patients underwent prostate biopsy in Shanghai, China. A race-specific GRS was calculated with seven PCa risk-associated SNPs implicated in East Asians (GRS7), and a nonrace-specific GRS was calculated based on 76 PCa risk-associated SNPs implicated in at least one racial group (GRS76). The means of GRS7 and GRS76 were 1.19 and 1.85, respectively, in the study population. Higher GRS7 and GRS76 were independent predictors for PCa and high-grade PCa in univariate and multivariate analyses. GRS7 had a better area under the receiver-operating curve (AUC) than GRS76 for discriminating PCa (0.602 vs 0.573) and high-grade PCa (0.603 vs 0.575) but did not reach statistical significance. GRS7 had a better (up to 13% at different cutoffs) positive predictive value (PPV) than GRS76. In conclusion, a race-specific GRS is more robust and has a better performance when predicting PCa in East Asian men than a GRS calculated using SNPs that are not shown to be associated with East Asians.
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Several different approaches are available to clinicians for determining prostate cancer (PCa) risk. The clinical validity of various PCa risk assessment methods utilizing single nucleotide polymorphisms (SNPs) has been established; however, these SNP-based methods have not been compared. The objective of this study was to compare the three most commonly used SNP-based methods for PCa risk assessment. Participants were men (n = 1654) enrolled in a prospective study of PCa development. Genotypes of 59 PCa risk-associated SNPs were available in this cohort. Three methods of calculating SNP-based genetic risk scores (GRSs) were used for the evaluation of individual disease risk such as risk allele count (GRS-RAC), weighted risk allele count (GRS-wRAC), and population-standardized genetic risk score (GRS-PS). Mean GRSs were calculated, and performances were compared using area under the receiver operating characteristic curve (AUC) and positive predictive value (PPV). All SNP-based methods were found to be independently associated with PCa (all P 0.05 for comparisons between the three methods), and all three SNP-based methods had a significantly higher AUC than family history (all P < 0.05). Results from this study suggest that while the three most commonly used SNP-based methods performed similarly in discriminating PCa from non-PCa at the population level, GRS-PS is the method of choice for risk assessment at the individual level because its value (where 1.0 represents average population risk) can be easily interpreted regardless of the number of risk-associated SNPs used in the calculation.
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Prostate cancer (PCa) testing is recommended by most authoritative groups for high-risk men including those with a family history of the disease. However, family history information is often limited by patient knowledge and clinician intake, and thus, many men are incorrectly assigned to different risk groups. Alternate methods to assess PCa risk are required. In this review, we discuss how genetic variants, referred to as PCa-risk single-nucleotide polymorphisms, can be used to calculate a genetic risk score (GRS). GRS assigns a relatively unique value to all men based on the number of PCa-risk SNPs that an individual carries. This GRS value can provide a more precise estimate of a man's PCa risk. This is particularly relevant in situations when an individual is unaware of his family history. In addition, GRS has utility and can provide a more precise estimate of risk even among men with a positive family history. It can even distinguish risk among relatives with the same degree of family relationships. Taken together, this review serves to provide support for the clinical utility of GRS as an independent test to provide supplemental information to family history. As such, GRS can serve as a platform to help guide-shared decision-making processes regarding the timing and frequency of PCa testing and biopsies.
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Current issues related to prostate cancer (PCa) clinical care (e.g., over-screening, over-diagnosis, and over-treatment of nonaggressive PCa) call for risk assessment tools that can be combined with family history (FH) to stratify disease risk among men in the general population. Since 2007, genome-wide association studies (GWASs) have identified more than 100 SNPs associated with PCa susceptibility. In this review, we discuss (1) the validity of these PCa risk-associated SNPs, individually and collectively; (2) the various methods used for measuring the cumulative effect of multiple SNPs, including genetic risk score (GRS); (3) the adequate number of SNPs needed for risk assessment; (4) reclassification of risk based on evolving numbers of SNPs used to calculate genetic risk, (5) risk assessment for men from various racial groups, and (6) the clinical utility of genetic risk assessment. In conclusion, data available to date support the clinical validity of PCa risk-associated SNPs and GRS in risk assessment among men with or without FH. PCa risk-associated SNPs are not intended for diagnostic use; rather, they should be used the same way as FH. Combining GRS and FH can significantly improve the performance of risk assessment. Improved risk assessment may have important clinical utility in targeted PCa testing. However, clinical trials are urgently needed to evaluate this clinical utility as well as the acceptance of GRS by patients and physicians.
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Unprecedented progress has been made in genomic personalized medicine in the last several years, allowing for more individualized healthcare assessments and recommendations than ever before. However, most of this progress in prostate cancer (PCa) care has focused on developing and selecting therapies for late-stage disease. To address this issue of limited focus, we propose a model for incorporating genomic-based personalized medicine into all levels of PCa care, from prevention and screening to diagnosis, and ultimately to the treatment of both early-stage and late-stage cancers. We have termed this strategy the "Pyramid Model" of personalized cancer care. In this perspective paper, our objective is to demonstrate the potential application of the Pyramid Model to PCa care. This proactive and comprehensive personalized cancer care approach has the potential to achieve three important medical goals: reducing mortality, improving quality of life and decreasing both individual and societal healthcare costs.
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Colorectal cancer (CRC) is among the leading causes of cancer deaths and can be caused by environmental factors as well as genetic factors. Therefore, we developed a prediction model of CRC using genetic risk scores (GRS) and evaluated the effects of conventional risk factors, including family history of CRC, in combination with GRS on the risk of CRC in Koreans. This study included 187 cases (men, 133; women, 54) and 976 controls (men, 554; women, 422). GRS were calculated with most significantly associated single-nucleotide polymorphism with CRC through a genomewide association study. The area under the curve (AUC) increased by 0.5% to 5.2% when either counted or weighted GRS was added to a prediction model consisting of age alone (AUC 0.687 for men, 0.598 for women) or age and family history of CRC (AUC 0.692 for men, 0.603 for women) for both men and women. Furthermore, the risk of CRC significantly increased for individuals with a family history of CRC in the highest quartile of GRS when compared to subjects without a family history of CRC in the lowest quartile of GRS (counted GRS odds ratio [OR], 47.9; 95% confidence interval [CI], 4.9 to 471.8 for men; OR, 22.3; 95% CI, 1.4 to 344.2 for women) (weighted GRS OR, 35.9; 95% CI, 5.9 to 218.2 for men; OR, 18.1, 95% CI, 3.7 to 88.1 for women). Our findings suggest that in Koreans, especially in Korean men, GRS improve the prediction of CRC when considered in conjunction with age and family history of CRC.
Subject(s)
Female , Humans , Male , Area Under Curve , Colorectal Neoplasms , Odds Ratio , Risk FactorsABSTRACT
Dyslipidemia, mainly characterized by high triglyceride (TG) and low high-density lipoprotein cholesterol (HDL-C) levels, is an important etiological factor in the development of cardiovascular disease (CVD). Considering the relationship between childhood obesity and CVD risk, it would be worthwhile to evaluate whether previously identified lipid-related variants in adult subjects are associated with lipid variations in a childhood obesity study (n = 482). In an association analysis for 16 genome-wide association study (GWAS)-based candidate loci, we confirmed significant associations of a genetic predisposition to lipoprotein concentrations in a childhood obesity study. Having two loci (rs10503669 at LPL and rs16940212 at LIPC) that showed the strongest association with blood levels of TG and HDL-C, we calculated a genetic risk score (GRS), representing the sum of the risk alleles. It has been observed that increasing GRS is significantly associated with decreased HDL-C (effect size, -1.13 +/- 0.07) compared to single nucleotide polymorphism combinations without two risk variants. In addition, a positive correlation was observed between allelic dosage score and risk allele (rs10503669 at LPL) on high TG levels (effect size, 10.89 +/- 0.84). These two loci yielded consistent associations in our previous meta-analysis. Taken together, our findings demonstrate that the genetic architecture of circulating lipid levels (TG and HDL-C) overlap to a large extent in childhood as well as in adulthood. Post-GWAS functional characterization of these variants is further required to elucidate their pathophysiological roles and biological mechanisms.
Subject(s)
Adult , Humans , Alleles , Cardiovascular Diseases , Cholesterol , Dyslipidemias , Genetic Predisposition to Disease , Genome-Wide Association Study , Lipoproteins , Obesity , Polymorphism, Single Nucleotide , Risk AssessmentABSTRACT
Dyslipidemia, mainly characterized by high triglyceride (TG) and low high-density lipoprotein cholesterol (HDL-C) levels, is an important etiological factor in the development of cardiovascular disease (CVD). Considering the relationship between childhood obesity and CVD risk, it would be worthwhile to evaluate whether previously identified lipid-related variants in adult subjects are associated with lipid variations in a childhood obesity study (n = 482). In an association analysis for 16 genome-wide association study (GWAS)-based candidate loci, we confirmed significant associations of a genetic predisposition to lipoprotein concentrations in a childhood obesity study. Having two loci (rs10503669 at LPL and rs16940212 at LIPC) that showed the strongest association with blood levels of TG and HDL-C, we calculated a genetic risk score (GRS), representing the sum of the risk alleles. It has been observed that increasing GRS is significantly associated with decreased HDL-C (effect size, -1.13 +/- 0.07) compared to single nucleotide polymorphism combinations without two risk variants. In addition, a positive correlation was observed between allelic dosage score and risk allele (rs10503669 at LPL) on high TG levels (effect size, 10.89 +/- 0.84). These two loci yielded consistent associations in our previous meta-analysis. Taken together, our findings demonstrate that the genetic architecture of circulating lipid levels (TG and HDL-C) overlap to a large extent in childhood as well as in adulthood. Post-GWAS functional characterization of these variants is further required to elucidate their pathophysiological roles and biological mechanisms.