• Tidak ada hasil yang ditemukan

LIST OF TABLES

N/A
N/A
Protected

Academic year: 2023

Membagikan "LIST OF TABLES "

Copied!
256
0
0

Teks penuh

The work in this dissertation was supported in part by the NIH Human Genetics Training Grant (T32GM080178). The Vanderbilt University Center for Human Genetics Research, Computational Genomics Core also provided computational and/or analytical support for those analyses.

OVERVIEW

The final case study is presented in Chapter V, where I used a genome-wide association study (GWAS) to identify genetic variants associated with serum thyroid-stimulating hormone (TSH) levels in individuals of African descent. -American and European from the Electronic Medical Records and Genomics Network (eMERGE). In Chapter VI, I consider the ethical, legal, and social implications of personalized medicine and the analytical evidence supporting its use in the clinical setting for common, complex diseases.

INTRODUCTION

INTRODUCTION

Personalized medicine

Variants in CYP2D6 have been associated with variations in drug efficacy and toxicity (Crews et al. 2014). Interactions between genetic risk (CFH rs1061170 or ARMS2 rs10490924) and environment (dietary intake of antioxidants, zinc and omega-3 fatty acids) were evaluated in a recent study (Wang et al. 2014a).

Personalization: Understanding Women’s Health

The Stages of the Reproductive Aging Workshop (STRAW) group has delineated the reproductive lifespan and menopause into three main phases with seven stages based on the frequency and variability of the menstrual cycle and supporting evidence from antral follicle count and FSH and AMH levels (Table 3) ) (Harlow et al. 2012). Smoking is a risk factor for natural menopause, which reduces ANM by 1-2 years (Cramer et al. 1995;.

Figure 1. Hormonal fluctuations during the menstrual cycle.
Figure 1. Hormonal fluctuations during the menstrual cycle.

Personalization: Understanding Race/Ethnicity

Despite the strong autoimmune component of hypothyroidism, few variants of known autoimmune loci (eg, HLA region, CTLA-4) have been found to be associated with clinical disease (Eriksson et al. 2012). Other population-specific differences have been found for ECG characteristics (Ramirez et al. 2011), age-related macular degeneration (Klein et al. 2011), and heart disease (Office of Minority Health and US Department of Health and Human Services 2014c). .

Strategies for Building Statistical Models in Personalized Medicine

For example, a recent GWAS for systemic lupus erythematosus (SLE) identified novel HLA region genes and replicated four genes previously associated with the autoimmune disorder (Armstrong et al. 2014). Traits such as gestational diabetes (Hayes et al. 2013) and fibroid tumors (Cha et al. 2011) have also been evaluated with GWAS.

Summary

How environmental exposures in conjunction with genetic variants contribute to the genetic architecture of complex diseases and traits is not fully understood. Ober and Vercelli 2011) and the effect of early childhood environment with genetic predisposition on mental health traits (Cicchetti and Rogosch 2012; Forsyth et al. 2013).

CASE STUDY: GENETICS OF THE FEMALE REPRODUCTIVE LIFESPAN 1

CASE STUDY: GENETICS OF THE FEMALE REPRODUCTIVE LIFESPAN

Introduction

Menarche

Population characteristics of African American women from the PAGE Study for age at menarche (AM) analysis. Comparison of previously reported SNPs associated with AM in women of European descent with 4,159 African-American women from the PAGE study in a minimally adjusted model for AM (Model 1) and a model adjusted for study site, year of birth , principal components and body mass index (Model 2).

Table 5. Population characteristics of African American women from the PAGE Study for age at  menarche (AM) analysis
Table 5. Population characteristics of African American women from the PAGE Study for age at menarche (AM) analysis

Menopause

Here, we demonstrated the use of the Metabochip genotyping array to identify SNPs associated with AM and ANM in a sample of African American women. SNPs compared were previously associated with age at menarche or age at natural menopause and directly genotyped on the Metabochip.

Table 7. Population characteristics of African American women from the Population Architecture  using Genomics and Epidemiology (PAGE) Study for age at natural menopause (ANM) analysis
Table 7. Population characteristics of African American women from the Population Architecture using Genomics and Epidemiology (PAGE) Study for age at natural menopause (ANM) analysis

ALGORITHMIC EXTRACTION OF FEMALE REPRODUCTIVE MILESTONES FROM ELECTRONIC MEDICAL RECORDS 2

ALGORITHMIC EXTRACTION OF FEMALE REPRODUCTIVE MILESTONES FROM ELECTRONIC MEDICAL RECORDS MILESTONES FROM ELECTRONIC MEDICAL RECORDS

58552 Laparoscopy, surgical, with vaginal hysterectomy, for uterus 250 g or less, with removal of tube(s) and ovary(s). 58554 Laparoscopy, surgical, with vaginal hysterectomy, for uterus larger than 250 g, with removal of tube(s) and ovary(s). 58571 Laparoscopy, surgical, with total hysterectomy, for uterus 250 g or less, with removal of tube(s) and ovary(s).

58573 Laparoscopy, surgical, with total hysterectomy, for uterus larger than 250 g, with removal of tubes and ovaries.

Figure 3. Flow chart for algorithm development for reproductive milestones.
Figure 3. Flow chart for algorithm development for reproductive milestones.

Results

Performance of age at menarche (AM), age at menopause (AAM), and age at natural menopause (ANM) algorithms in women from EAGLE BioVU. Of the 100 subjects with algorithm-identified AAM, we identified 82 with AAM by manual inspection. By manual inspection, only five out of 100 subjects without AAM identified by the algorithm had recognizable AAM.

Of the 100 individuals with no algorithm-identified ANM, manual review of the SD found 6 cases with an identifiable ANM (Table 14).

Table 13. Population characteristics for women with algorithm-identified age at menarche (AM), age  at menopause (AAM), and age at natural menopause (ANM) from EAGLE BioVU
Table 13. Population characteristics for women with algorithm-identified age at menarche (AM), age at menopause (AAM), and age at natural menopause (ANM) from EAGLE BioVU

CASE STUDY: GENETIC VARIANTS ASSOCIATED WITH ENDOMETRIAL CANCER

CASE STUDY: GENETIC VARIANTS ASSOCIATED WITH ENDOMETRIAL CANCER ENDOMETRIAL CANCER

Modugno et al. 2005) that inflammation may be a factor in the development of EC led by Ashton et al. Colon and Rectal Cancer (GECCO) and the Colon Cancer Family Registry (CCFR) identified associations with colorectal cancer in 8q24, a known cancer locus (Cheng et al. 2014). This locus has been found to be associated with prostate cancer in several studies (Liu et al.

In addition, THADA rs1465618 was nominally significant in our study and has previously been associated with prostate cancer (Eeles et al. 2009).

Table 15. FIGO scoring for endometrial carcinoma tumors.
Table 15. FIGO scoring for endometrial carcinoma tumors.

CASE STUDY: A GENOME-WIDE ASSOCIATION STUDY FOR SERUM THYROID STIMULATING HORMONE LEVELS 3

CASE STUDY: A GENOME-WIDE ASSOCIATION STUDY FOR SERUM THYROID STIMULATING HORMONE LEVELS THYROID STIMULATING HORMONE LEVELS

Together, the known loci explain <5% of the variance in TSH levels (Rawal et al. 2012). Manhattan display of tests of association with serum TSH levels in euthyroid European Americans in the eMERGE network. At least 24 SNPs have been associated in the literature with serum TSH levels in populations of European descent (Rawal et al.

None of the SNPs previously associated with thyroid cancer (Gudmundsson et al. 2009) was associated with serum TSH levels in either European Americans or African Americans at a liberal significance threshold of p<0.05 (Appendix N, Appendix O).

Table 18. Population characteristics in euthyroid individuals for serum TSH levels in the eMERGE  Network
Table 18. Population characteristics in euthyroid individuals for serum TSH levels in the eMERGE Network

IMPLEMENTING PERSONALIZED MEDICINE: EVIDENCE AND ETHICS 4,5

IMPLEMENTING PERSONALIZED MEDICINE: EVIDENCE AND ETHICS ETHICS

This chapter will describe the scientific, systemic and societal barriers to successful implementation of PM for complex diseases in the clinical setting and examine how these challenges have been addressed in pharmacogenetics and cancer therapy. Analytical framework showing how personalized medicine could be used to screen asymptomatic individuals to identify individuals at risk, enabling early intervention to prevent disease, leading to improved health outcomes, but with risks of harm from screening and intervention .

Figure 8. Analytic framework for personalized medicine implementation for complex  diseases
Figure 8. Analytic framework for personalized medicine implementation for complex diseases

Scientific issues

Therefore, calculating the PPV of a genetic test for a common and complex disorder using traditional 2x2 tables may not be the most appropriate method (Janssens et al. 2006). The lack of clearly stated and measurable health outcomes makes determining the utility of personalized medicine challenging (Botkin et al. 2010). Several studies have examined the impact of genetic information on smoking cessation (Lerman et al.

This study found no distress among participants after learning of their genetic test results and limited (28% of study participants) disclosure of results to physicians (Graves et al. 2013).

Table 24. Calculating specificity, sensitivity, positive and negative predictive values for genetic tests  using a 2x2 table
Table 24. Calculating specificity, sensitivity, positive and negative predictive values for genetic tests using a 2x2 table

Evidence review for inclusion of genetic data in clinical care for hypothyroidism

Additional studies similar to Vorderstrasse et al., utilizing research techniques used by social and behavioral scientists. Well-documented barriers to expanded implementation of PM are unknown risks and benefits in the clinical setting, lack of clinical validation and utility data (Teutsch et al. 2009; Palomaki et al. The ACCE framework used by the CDC EGAPP (Teutsch et al 2009) working group was used as a reference to perform this rapid review.

Data from the full-text review were exported from REDCap (Harris et al. 2009) to Stata (Boston and Sumner 2003).

Table 27. List of studies providing ORs/effect sizes for genetic variants associated with  hypothyroidism/TSH levels
Table 27. List of studies providing ORs/effect sizes for genetic variants associated with hypothyroidism/TSH levels

Ethical, legal, and social issues

Maintaining patients' genomic data outside the EHR with controlled access to the data is a method to minimize inappropriate access (Hazin et al. 2013). EHR platforms may require significant modifications to be usable for PM (Kho et al. 2013). It is currently unclear at what point implementing PM is a cost-effective strategy (Phillips et al. 2014).

These survey participants believed that using EHRs would not improve security or privacy (Abramson et al. 2014).

CONCLUSION AND FUTURE DIRECTIONS

CONCLUSION AND FUTURE DIRECTIONS

Conclusion

The role of reproductive longevity in women has been associated with various complex traits and diseases. Additionally, the sample size and small allele frequency differences between our population and European populations likely affected our ability to replicate known variants associated with these traits. Despite these limitations, our results demonstrated the ability to use Metabochip to identify variants associated with reproductive longevity traits in a diverse population.

Although identification of genetic variants associated with a particular trait can provide insight into the underlying biological characteristics.

Future Directions

Historical injustices against certain populations have created distrust in the medical community and continue to inhibit participation in biomedical research. Past studies that have led to distrust by the medical and scientific community have had long-term implications for participation in research studies and clinical trials. Collaboration with social scientists and community leaders that leads to a better understanding of the barriers that exist to minority participation in biomedical studies can improve recruitment and retention.

Our lack of understanding of the biological mechanisms that lead to disease certainly plays an important role in the failure to identify the genetic variants responsible.

Role of research findings in clinical care

I have described many of the challenges currently facing personalized medicine - they are by no means insurmountable. Prioritization based on the public health burden of disease provides another method for determining which diseases could benefit from this approach. Our scientific understanding of the basis for many common, complex diseases and traits has improved in recent decades with advances in genomic studies.

Evaluation of the role of genetic variants as predictors of complex disease is under development; Although the challenges are significant, it is likely that they will be overcome in the future.

APPENDICES

Abbreviations: single nucleotide polymorphism (SNP), age at menarche (AM), Population architecture using genomics and epidemiology (PAGE), chromosome (Chr), minor allele frequency (MAF), coded allele frequency (CAF). Abbreviations: single nucleotide polymorphism (SNP), age at natural menopause (ANM), Population architecture using genomics and epidemiology (PAGE), chromosome (Chr), minor allele frequency (MAF), coded allele frequency (CAF). Shown are power estimates for the age at menarche study of African American women in the PAGE Study calculated using QUANTO.

Power calculations for the age at natural menopause study of African American women in the PAGE study calculated using QUANTO are shown.

Odds Ratio, per allele (additive  model)

Power calculations for EAGLE BioVU endometrial cancer study

Comparison of SNP associations in regression models with and without BMI covariates for serum TSH levels in eMERGE study European Americans. Comparison of SNP associations in regression models with and without BMI covariates for serum TSH levels in emerging African Americans. Body mass index as a modifier of serum TSH levels genetic associations in emerging African Americans.

SNP rs number, chromosomal location, nearest gene/gene region, coded allele (CA), coded allele frequency (CAF), and summary association statistics (beta and p value) are provided for each reported association. seen with serum TSH levels in Europe. the americans.

Using EHR Data to Assess Physician-Level Variability in Technology Use." J.Am.Med.Inform.Assoc. 34; Effects of Thyroid Dysfunction on Severity of Coronary Artery Lesions and Its Prognosis." J. Cardiol. 34; The Importance of Race and Ethnicity in Biomedical Research and Clinical Practice.” N.Engl.J.Med.

34;Patients want detailed privacy control over health information in electronic medical records." J.Am.Med.Inform.Assoc.

Gambar

Figure 1. Hormonal fluctuations during the menstrual cycle.
Table 5. Population characteristics of African American women from the PAGE Study for age at  menarche (AM) analysis
Figure 2. Regional association plot for AM in African American women from  PAGE Study
Table 6. Comparison of GWAS-identified age at menarche (AM) variants in African American women from the Population Architecture  using Genomics and Epidemiology (PAGE) Study
+7

Referensi

Dokumen terkait

Pada penerapannya, digunakan routing protocol BGP untuk mendapatkan load balance dan failover menggunakan router juniper antar ISP dan antar stasiun ke stasiun caruban. Dari