Public Health Genomics最新文献

Background: Polycystic ovary syndrome (PCOS) is a common heterogeneous disorder characterized by chronic anovulation, infertility, polycystic ovaries, and hyperandrogenic signs.

Objective: The aim of this study was to determine the association of luteinizing hormone/chorionic gonadotropin hormone receptor LHCGR polymorphism (rs2293275) with oligomenorrhea, amenorrhea, hirsutism, acne, infertility, LH, LH/FSH ratio, and body mass index (BMI) among PCOS females.

Methods: This genetic case-control study recruited 55 PCOS and 55 control females, diagnosed based on the Rotterdam criteria. LH and FSH were measured by the Roche cobas c 502 automated analyzer. Genotypic analysis was carried out using the polymerase chain reaction-restriction fragment length polymorphism and restriction endonuclease digestion.

Results: BMI was higher for PCOS patients (28.5 ± 6.59) compared to controls (25.1 ± 5.77), and ovulatory dysfunction was seen among 90% of PCOS females. Oligomenorrhea was common in PCOS (73%), and hirsutism and acne were detected in PCOS (80% and 40%; respectively). LH ≥10 were recoded among 51%, while LH/FSH ≥1.5 was recorded among 33% PCOS females. There is a statistical difference between rs2293275 polymorphism in the AG genotype between PCOS patients and controls. PCOS patients have a significantly higher mean LH level compared to controls (8.36 ± 4.86 and 5.67 ± 2.51, respectively) and showed higher LH/FSH value (1.46 ± 0.81) compared to (0.87 ± 0.30) controls. GG and AG genotypes of LHCGR showed statistically significant higher LH (8.22 ± 4.11; 9.02 ± 3.87) and LH/FSH values (1.57 ± 0.56; 1.64 ± 0.89) compared to controls.

Conclusion: LHCGR (rs2293275) GA and GG genetic variants could modulate the hormonal levels of PCOS LH levels and the LH/FSH ratio and associated with hirsutism, oligomenorrhea, BMI, and LH/FSH ratio as risk factors.

In the past decade, there has been an acceleration in genomic research, its applications, and its translation into healthcare products and services for the benefit of public health. These advances are critical to realizing the potential of genomic research for facilitating improved health and disease prevention, diagnosis, and treatment. Despite its tremendous opportunities, the dynamic and increasingly global landscape of genomic research commercialization has been accompanied by a variety of ethical challenges and concerns. The potential for unauthorized use of DNA samples from African people to develop a DNA chip amplifies discussion on the meanings, implications, and impacts of commercialization, benefit sharing, and appropriate consent in genomic research. Leadership of the Human Heredity and Health in Africa (H3Africa) Consortium convened a panel of experts to review research ethics practices employed in H3Africa Consortium projects and make recommendations regarding commercialization. Eighteen investigators submitted documents for projects involving data sharing and use of genetic information. A total of 39 informed consent documents associated with the 18 projects were reviewed. All 18 projects specified that samples would be used in future research. Less than half of the projects included language noting that samples could be used in drug or product development, that DNA samples would not be sold, and that profits would not be shared with participants. Four projects referred to commercialization. Analysis of information included in consent documents contributed to the development of a Commercialization Typology. The Typology identifies factors to consider regarding acceptability of particular instances of commercialization. DNA samples for translational research in product development require a transparent commercialization framework to inform the consent process.

During coronavirus disease 2019 (COVID-19) pandemic, the genetic mutations of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) occurred frequently. Some mutations in the spike protein are considered to promote transmissibility of the virus, while the mutation patterns in other proteins are less studied and may also be important in understanding the characteristics of SARS-CoV-2. We used the sequencing data of SARS-CoV-2 strains in California to investigate the time-varying patterns of the evolutionary genetic distance. The accumulative genetic distances were quantified across different time periods and in different viral proteins. The increasing trends of genetic distance were observed in spike protein (S protein), the RNA-dependent RNA polymerase (RdRp) region and nonstructural protein 3 (nsp3) of open reading frame 1 (ORF1), and nucleocapsid protein (N protein). The genetic distances in ORF3a, ORF8, and nsp2 of ORF1 started to diverge from their original variants after September 2020. By contrast, mutations in other proteins appeared transiently, and no evident increasing trend was observed in the genetic distance to the original variants. This study presents distinct patterns of the SARS-CoV-2 mutations across multiple proteins from the aspect of genetic distance. Future investigation shall be conducted to study the effects of accumulative mutations on epidemics characteristics.

Objectives: "Personalized healthcare" is generating new approaches to disease management by considering inter-individual variability in genes, environment, and lifestyle. Technologies such as comprehensive genomic profiling (CGP) are drivers of this shift. Here, we address the significant hurdles to the equitable implementation of CGP into routine clinical practice.

Methods: This article draws on published evidence on the value of genomic profiling, as well as interviews with nine academic and clinical experts from six different countries to validate findings and test policy proposals for reforms.

Results: The potential benefits of CGP extend beyond direct patient outcomes, to healthcare systems with societal and economic impacts. Among key barriers impeding integration into routine clinical practice are the lack of infrastructure to ensure reliable clinical testing and the limited understanding of genomics among healthcare personnel. In addition, the absence of health economic evidence supporting broader use of CGP is creating concerns for payers regarding the systemic benefits and affordability of this technology.

Conclusion: Policy proposals that aim to improve equitable patient access to CGP will need to consider new funding models, health technology assessment processes that capture both patient and systemic benefits, and appropriate regulatory standards to determine the quality of genomic profiling tests.

Introduction: Primary care providers (PCPs) and oncologists lack time and training to appropriately identify patients at increased risk for hereditary cancer using family health history (FHx) and clinical practice guideline (CPG) criteria. We built a tool, "ItRunsInMyFamily" (ItRuns) that automates FHx collection and risk assessment using CPGs. The purpose of this study was to evaluate ItRuns by measuring the level of concordance in referral patterns for genetic counseling/testing (GC/GT) between the CPGs as applied by the tool and genetic counselors (GCs), in comparison to oncologists and PCPs. The extent to which non-GCs are discordant with CPGs is a gap that health information technology, such as ItRuns, can help close to facilitate the identification of individuals at risk for hereditary cancer.

Methods: We curated 18 FHx cases and surveyed GCs and non-GCs (oncologists and PCPs) to assess concordance with ItRuns CPG criteria for referring patients for GC/GT. Percent agreement was used to describe concordance, and logistic regression to compare providers and the tool's concordance with CPG criteria.

Results: GCs had the best overall concordance with the CPGs used in ItRuns at 82.2%, followed by oncologists with 66.0% and PCPs with 60.6%. GCs were significantly more likely to concur with CPGs (OR = 4.04, 95% CI = 3.35-4.89) than non-GCs. All providers had higher concordance with CPGs for FHx cases that met the criteria for genetic counseling/testing than for cases that did not.

Discussion/conclusion: The risk assessment provided by ItRuns was highly concordant with that of GC's, particularly for at-risk individuals. The use of such technology-based tools improves efficiency and can lead to greater numbers of at-risk individuals accessing genetic counseling, testing, and mutation-based interventions to improve health.

This is a critical perspective paper discussing the theoretical bases and methodological issues regarding dyadic decision-making processes in the oncological domain. Decision-making processes are of a central interest when one partner in a couple has cancer, and patients and partners make decisions together under an interactive and dynamic process. Given that, the attention in research is progressively shifting from patient and partner considered as individuals to a more holistic view of patient-partner considered as a dyad. The consideration of the dyadic nature of the decision-making represents a challenge from a theoretical and methodological point of view. The Interdependence Theory and the Dyadic Model of decision-making provide the theoretical bases to consider, respectively, the interdependence of the dyadic decision-making and the mechanisms affecting the couple-based decision-making. Dyadic processes require also an appropriate data analysis strategy that is discussed in the study as well. Conclusions of the present critical review suggest to develop a new line of research on dyadic decision-making in the oncological domain, testing the Dyadic Model presented in the study and considering the interdependence of the data with appropriate levels of analysis.

Background: Steroid-induced osteonecrosis of the femoral head (ONFH) is aseptic necrosis of the femoral head caused by glucocorticoid use. Once necrotic femoral head necrosis occurs, it irreversibly affects the quality of life seriously. Studies have shown that the susceptibility to steroid-induced ONFH is likely to be related to the variation of miRNA-coding genes. Therefore, this study aimed was to investigate the effect of MIR3142HG on steroid-induced ONFH.

Methods: Agena MassARRAY was used to genotype MIR3142HG gene rs1582417, rs2431689, rs7727155, and rs17057846 in 199 patients and 725 healthy people. A genetic model and haplotype analysis were used to evaluate the relationship between the MIR3142HG polymorphism and the risk of steroid-induced ONFH. The odds ratio and 95% confidence intervals were obtained through logistic regression to assess the influence of gene polymorphisms on the occurrence of steroid-induced ONFH.

Results: The consequences show that rs7727115 is a protective factor, it could reduce the risk of steroid-induced ONFH, and rs1582417 could increase the risk of steroid-induced ONFH. In the genetic model, rs1582417 was associated with increased risk of alcohol-induced ONFH in dominant model and log-additive model. rs7727115 showed a decreased risk in codominant model, dominant model, and log-additive model. In addition, rs2431689 is related to HDL-C (p = 0.012) and ApoA1 (p = 0.010) levels, and rs17057846 (p = 0.024) is related to ApoB levels. Thelinkage analysis indicated 3 single-nucleotide polymorphisms (rs2431689, rs7727115, and rs17057846) in MIR3142HG with significant chain imbalance. In addition, haplotype "GGG" of MIR3142HG was found out and is harmful for steroid-induced ONFH.

Conclusion: Our results first confirm that the genetic polymorphism of MIR3142HG is associated with steroid-induced ONFH susceptibility in Chinese Han population.

Introduction: Warfarin is widely used and will continue to be prescribed especially in developing countries due to its low cost. Given the huge patient load requiring anticoagulation, there is a need to develop strategies to optimize warfarin therapy for ensuring safe and effective anticoagulation. In the present work, we aimed at elucidating the association of genetic and nongenetic variables with warfarin dose requirement in patients attending the cardiovascular clinic in a tertiary care center of North India.

Methods: This was a prospective study conducted over 1 year. Patient demographic and clinical details were captured in customized case record forms. Genotyping was done using the polymerase chain reaction-restriction fragment length polymorphism method. Pharmacogenetic influence of CYP2C9 (rs1799853 and rs1057910) and VKORC1 (rs9923231) variant alleles was studied. The association of genetic and nongenetic factors with warfarin dose was quantified using a stepwise multivariate linear regression model.

Results: Two hundred and forty patients were screened. Data from 82 eligible patients were used for quantifying the association of genetic and nongenetic factors with warfarin dose. A descriptive model based on CYP2C9*3 (rs1057910) and VKORC1 (rs9923231) variant alleles and BMI was developed. The model explains nearly half of the interindividual variation in warfarin dose requirement.

Conclusion: The model explains nearly half of the interindividual variation in warfarin dose in patients with atrial fibrillation and or requiring valve replacement.

Introduction: Invasive ductal carcinoma (IDC) of the breast is a heterogeneous disease characterized by multiple subtypes. IDC survival is highly impacted by tumor burden, molecular subtypes, and gene profiles. Gene mutation is a type of genomic instability regarded as having a considerable effect on IDC prognosis. Using integrated survival analysis, this study identified candidate genes and a high-risk group of patients with early-stage IDC to provide further understanding of the genetic characteristics associated with poor survival.

Methods: The gene mutation profiles, baseline demographics, clinicopathologic variables, and treatment characteristics of the early-stage IDC subpopulation were downloaded from an open access data platform. These data were analyzed for a total of 444 patients. In total, 40 genes commonly involved in IDC were listed, and the genes exhibiting significant differences (as estimated using the log-rank test) were selected as the candidate genes.

Results: The patients were divided into control, low-risk, and high-risk groups according to their gene mutation profiles. The 5-year overall survival rates of low-risk, control, and high-risk patients were 97.4%, 96.1%, and 73.0%, respectively. The high-risk group had a significantly higher risk of poor overall -survival (adjusted hazard ratio = 6.57, 95% confidence interval = 1.51-28.7, p = 0.012) than that of the control group, and the low-risk group did not have a significant survival difference compared with control group.

Conclusions: This study proposed an integrative approach for the identification of candidate genes for risk assessment of overall survival in these patients through typical survival analysis methods. The 14 candidate genes selected are particularly involved in cell-cycle processes, deoxyribonucleic acid repair, and drug resistance; their mutations were found to be generally associated with disease progression or therapeutic resistance, which is commonly associated with poor overall survival outcomes in IDC.