Epi07_13

=Genetic diagnosis, treatment, monitoring, and surveillance= Idea: Genetic analysis has begun to identify genetic risk factors. We need to consider the social infrastructure needed to keep track of the genetic and environmental exposures with a view to useful epidemiological analysis and subsequent healthcare measures. Even in cases where the condition has a clear-cut link to a single changed gene and treatment is possible, there is complexity in sustaining that treatment.

Initial notes on the Cases
From PT: Case: Genes as risk factors; Collection of genetic vs. environmental data for long-term surveillance; Complexities of social support after PKU diagnosis Readings: Bowcock 2007, Khoury 2007, Frank 2005, Paul 1998



Substantive statement
Substantive Statement: Genetic diagnosis, treatment, monitoring and surveillance.

This week’s readings builds upon the previous week’s about heritability. With the expanding role of genetic analysis, comes the challenge of how to fit this into our healthcare system and our societal needs and values. Genetic risk factors associated with common diseases, individually may only have a weak risk-ratio, but combinations of these factors may have a larger impact of the population. Khoury et al try to make a case for establishing standards for “presenting and interpreting cumulative evidence on gene-disease associations.” They describe problems such as publication and selection biases, differences in collection and analysis of samples and the presence of undetected gene-environment interactions among studies of genome-wide analysis. This has lead to a high incidence of type 1 errors in GWA studies (false positives). Networks are attempting to establish consensus guidelines for reporting and publishing gene-disease associations to reduce this risk. Bowcock describes how a consortium of 50 British groups examined genetic variance in a genome-wide association study. They examined the genetic issues for 7 common diseases including RA, CAD, bipolar disorders, diabetes, hypertension and Crohn’s disease. To identify the genetic risk factors for these common diseases, they examined 500,000 genetic markers(or SNPs-single nucleotide polymorphisms) from the genomes of 17,000 individuals. They found very little difference between controls and cases, but they did find some SNPs that can be considered genetic risk factors for a particular disease, some confirming previous studies, but others identifying unique genes that affect susceptibility to a disease. The more advanced the genetic analysis becomes, the issue of how this information is going to be utilized for the treatment or monitoring of a person’s risk for disease and what part prevention and screening plays in the individual’s health status presents itself. Bowcock cautions that translating someone’s risk into “medical practice” should not be done without “larger patient populations, well-annotated clinical databases and sophisticated environmental assessment.” The Paul article gives us an example of how a rare genetic disorder, Phenylketonuria (PKU) has been managed. Even though the incidence is between 1 in 11,000 and 1 in 15,000 births, all newborns are tested for it in the US, Canada, Australia, New Zealand, Japan and most other Western and Eastern European countries. The article chronicles the history of instituting the screening procedures for PKU. PKU was described as a “treatable genetic disease.” If left untreated, it results in severe mental retardation and behavioral abnormalities. PKU can be treated by a special diet which eliminates phenylalanine toxicity in the blood of those with PKU. There were policy issues involved in the PKU screening process that warrant examination. What were the societal factors that contributed to the federal initiative in the US in 1961? Not everyone was a proponent of the testing of every newborn for such a rare genetic disease. Problems of treatment efficacy and the question of the “cost” of the program are also addressed. As we become more advanced in genetic analysis, many similar issues may be encountered for other conditions. One current related topic is the role of BRCA1 and BRAC2 inherited breast cancer gene abnormalities. Although they only account for about 10% of all breast cancers, there is much discussion about the Pros and Cons of seeking your genetic profile for breast CA. Issues of prophylactic breast removal surgery, discrimination by health insurers and stress and anxiety associated with knowing your genetic profile are all ones that can be related to other genetic testing.

As I was reading over this week’s assignment and Connie’s substantive statement, I couldn’t help to be in awe of the advancements in medicine, genetics and technology which allows one the possibility of having what they consider “the perfect baby.” If you aren’t interested in having a baby, perhaps you could enter your DNA for analysis to see what diseases or risk for diseases you might be predisposed. No matter what the circumstances, where do we draw the line? Ethical issues relating to genetic testing are ongoing and may lead to ethical dilemmas. Although it is useful for assessment of genetic risk and diagnosis, not all genetic tests identify all possible genetic mutations which may cause a particular condition and/or may have limited predictive value (Lea, Williams, and Donahue, 2005). Some of the testing may not be entirely conclusive leaving families with difficult decisions and limited knowledge. Lea et. al (2005) ask, “Should the information be obtained if no treatment or intervention exists.” For example, phenylketonuria (PKU) is a treatable disease with dietary modifications. However, prenatal genetic screening used to identify high risk pregnancies for possible birth defects is used for reproductive decision making which may cause an ethical dilemma for a couple who weren’t prepared to make any decisions. There are also potential issues for genetic testing in which a condition discovered has no treatment which in turn may cause psychological harm. For example, the child of a parent with Huntington’s disease has a 50% chance of inheriting this gene mutation (Lea et. al, 2005). On the other side of the argument, (and this is when I thought, my goodness, what will people think of next) an article in US Today by Lindsey Tanner, wrote about “creating made-to-order babies with genetic defects” which is called preimplantation genetic diagnosis or embryo screening. These are couples with disabilities who want to recreate “babies like themselves.” The debate included identifying what is considered “normal” and what is considered a “disability.” For example, a couple with dwarfism might say, “I want a child like me.” When Cara and Gibson Reynolds consulted a specialist about embryo screening, they discussed the choices of implanting dwarf or non-dwarf embryos. Reynolds states, “A healthy dwarf embryo is a healthy embryo. It’s a kid who’s going to go to school, go to college and make friends.” So is this actually being done? Reports of a survey performed with 415 clinics concluded that 3% were doing embryo screening for this purpose. However, because clinics were promised anonymity, these statistics were questioned by other clinics and physicians as being “reliable.” Genetic testing may provide the information to determine genetic diseases; the risk of developing a gene-related disease and/or the risk of passing this to one’s children. What we are not prepared for is how this can ultimately affect a patient’s sense of self worth and well being with the possibility of genetic discrimination. What do you think? (sa). Lea, D., Williams, J., and Donahue, P. (2005). Ethical Issues in Genetic Testing. //Journal of// //Midwifery Women’s Health//, 50 (3): 234-240. Tanner, L. Some ponder ‘designer’ babies with Mom or Dad’s defective genes. Retrieved from http://www.usatoday.com/tech/science/genetics/2006-12-21-designer-disability_x.htm
 * Reponse to substantive statement:**



Annotated additions by students
__National Institute of Neurological Disorders and Stroke__- release July 29,2007 The International Multiple Sclerosis Genetics Consortium. "Novel Risk Alleles for Multiple Sclerosis Identified by a Whole Genome Association Study." //New England Journal of Medicine//, published online July 29, 2007. Gregory SG //et al//. "Allelic and Functional Association of the Interleukin 7 Receptor alpha Chain (IL7R-alpha) with Multiple Sclerosis." //Nature Genetics//, published online July 29, 2007. __After a Decades-Long Search, Scientists Identify New Genetic Risk Factors for Multiple Sclerosis__.

This recent research update presetns new information to strengthen the genetic link influencing MS. This progressive, central nervous system disease has etiological links with the environment(geographics), autoimmune responses and genetics. Two large-scale genetic studies by NIH revealed two genes that influence the risk of getting MS. They both demonstrated an association between MS and SNPs in two genes that encode interleukin receptors, protens that serve as antennae on the surface of immune cells. Each of the SNPs associated with MS appears to increase the risk of developing the disease by 20-30%. Also, the genome-wide scan identified nearly a dozen other genes that could represent risk factors for MS, although some are relatively weak. They found evidence that the MS-associated variant causes a reduction in the amount of the IL7R-alpha protein at the T cell surface. Less is known about how variation in IL2R-alpha might contribute to MS, but that protein is already being viewed as useful therapeutic target. In a 2004 study by NINDS scientists, 10 MS patients who were unresponsive to currently approved therapies showed improvement when treated with an antibody that blocks IL2R-alpha, developed to prevent rejection of organ transplants. (CI)

Silman, Allan J., & Jacqueline E. Pearson (2002) Epidemiology and genetics of rheumatoid arthritis, //ARC Epidemiology Unit, School of Epidemiology & Health Sciences, University of Manchester, Manchester, UK,// Vol.4(Suppl 3) S265-5272 At the rate of 0.5-1.0%, rheumatoid arthritis is constant in prevalence in many populations. The rate of rheumatoid arthritis (RA) is high in the Pima Indians (5.3%) and in the Chippewa Indians (6.8%). In populations from Japan and China, lower than average occurrences have been reported. The aforementioned data support a genetic role in disease risk. To date, studies have shown that the familial recurrence risk in RA is small compared to other autoimmune diseases. The main genetic risk factor is HLA DRB1 alleles and the strongest susceptibility factor is the HLA DRB1*0404 allele – this has been consistently shown in many populations. But these genes explain only 50% of the genetic effect. Other non-MHC genes have been reported such as corticotrophin releasing hormone, estrogen synthase, IFN~y and other cytokines – these factors have been linked with RA. Many environmental factors have been studies in relation to RA – the use of the oral contraceptive pill and pregnancy have been associated with decreased incidence. The postpartum period and breastfeeding after a first pregnancy are both associated with decreased risk. Exposure to infection such as Epstein-Barr virus, parvovirus, and some bacteria such as Proteus and Mycoplasma may act as a trigger for RA. There is an increased risk of RA associated with cigarette use.(JG)

Tiainen K., Spipila, S., Alen, M., Heikkinen, E., Kaprio J., Koskenvuo, M., Tolvanen A., Pajala, S., et al. (2004). Heritability of maximal isometric muscle strength in older female twins. //Journal of Applied Physiology, 96//, 173-180.

Viljanen, A., Era, P., Kaprio J., Pyykko, I., Koskenvuo, M., & Rantanen, T. (2007). Genetic and environmental influences on hearing in older women. //Journal of Gerontology: Medical Sciences, 62A//(4), 447-452.

The two articles used the Finish Twin study on Aging (FITSA), having both monozygotic (MZ) and dizygotic (DZ) twins. In both studies, they only examined women. Viljanen et al. (2007) found out that both the better ear hearing threshold level and the better speech recognition threshold level had over 50% of genetic effects; however, self-reported hearing ability was affected by environmental factors. In contrast to the study of Viljanen et al. (2007), Tiainen et al. (2004) found mixed effects of genetic and environmental factors in women’s muscle strength (handgrip, knee extension strength, and ankle plantar flexion strength). (km)

1. Dohrenwend BP, Levav I, et al. Socioeconomic Status and Psychiatric Disorders: The Causation-Selection Issue. Science 1992;255:946. 2. Kessler RC, Foster CL, Saunders WB, et al. Social consequences of psychiatric disorders, I: Educational attainment. The American Journal of Psychiatry 1995;152:1026.

These two articles contribute to a debate in the psychosocial stress literature between two hypotheses: social causation and social selection. These hypotheses are designed to explain the consistently observed phenomenon of lower SES groups experiencing greater rates of psychiatric disorder. Social causation suggests that social environmental adversity and the stress associated with it combine to produce psychopathology in these groups, while social selection posits that genetics combine with social environmental adversity in a manner that either prevents low income individuals from moving up the ladder, or sorts and sifts them into low SES groups to begin with. Kessler et al. test these hypotheses indirectly using National Comorbidity Survey data to determine whether early-onset psychiatric disorders impact educational attainment. They find that these disorders do appear to predict greater high school and college dropout rates as well as discouraging people from returning to complete their schooling at a later date. These findings therefore seem to support the social selection hypothesis. In an effort to determine whether social selection and causation can really be theoretically distinguished, Dohrenwend et al. conducted a study in Israel with a sample of 5000 Jews of various SES who were of either North African or European background. The authors uses ethnicity to test the two hypotheses on SES as ethnicity is an attribute people are born with and cannot therefore be directly affected by social causation processes. They find that social causation works better to explain depression and anxiety disorders in women, and antisocial personality and substance use disorders in men, while social selection may better explain schizophrenia in both men and women. (lh)

Plomin R. The Role of Inheritance in Behavior. Science 1990;248:183.

As indicated in the title, this article discusses genetics and behavior. Plomin argues that behavior is the most complex of the phenotypes but that it is essential to study behavior from the standpoint of quantitative genetics and molecular biology in order to get a full picture of some of the health states that most profoundly impact society. He reviews recent research in behavioral selection and quantitative studies of behavior and reaches three primary conclusions: 1) heritability can only account for a portion of human behavior, so it is essential to understand social environmental context as well; 2) it is folly to imagine that genetic influences on behavior are the result of one or two major genes and instead such influences more likely occur in response to many genes, each with small effects; and 3) further study in the area of behavioral genetics and molecular biology is required to fully understand the contribution of genetics to human behavior – an endeavor that the human genome project (which hadn’t yet mapped the human genome as this was written in 1990) will help revolutionize.

This webcast/transcript is interesting and relevant for many reasons. The session is a report from a Dr. Susan Shurin, M.D., who is the Deputy Director of the National Heart, Lung, and Blood Institute, in the NIH. She was involved in developing the proposal to create a database of shared clinical and genomic information at the NIH. The talk is relevant to the topic of genetic diagnosis, treatment, monitoring and surveillance because it describes the kind of social infrastructure we have to have in place __before__ any of this can happen on a large scale. I think it is a fine example of Peter’s notion about the “chain of steps in scientific inquiry in which each step involves assumptions and is open for negotiation and wider influences.” It’s also interesting to see the health bureaucracy in action – with specialists and experts being called before members of the Secretary’s Advisory Committee on Genetics, Health, and Society (SACGHS) to report on issues determined to be of interest to the nation’s health (and about which they advise the Secretary of Health & Human Services).
 * NIH Proposed Policy on Genome Wide Association Studies (GWAS)**

Dr. Shurin spends the first few minutes establishing her credentials as one who has been “in the trenches” – i.e. not a policy wonk or an NIH careerist. She stresses that her Institute is really only trying to improve the public health. She talks about the glut of information that is being produced and how no one investigator or group will would ever be able to analyze it properly. Because they do studies at NHLBI that are expensive, they want the data to be available for others so that the resources aren’t wasted by unnecessary duplication of effort. She foreshadows some of the problems associated with open access, i.e. privacy and intellectual property. The NHLBI and the National Human Genome Research Institute (NHGRI) started talking about developing a coherent policy for the sharing of data across the NIH. According to Dr. Shurin, they want to help change investigator culture so that instead of investigators having a proprietary stance toward their data, they can be urged to put it out for everyone to work with, thus maximizing the benefit.

One of the ideas they had was a single portal method of entry to the data. They suggest that this repository should reside at the NLM, at the National Center for Biotechnology (NCBI) – which she called the National Center for (sic) Bioinformatics. The proposal is that people who do genome-wide association studies – if they have funding from the NIH – must share their data, consistent with human subject research consent (if applicable). She discusses how the data would be de-identified by using a random code which only the submitting institution would know about – not the repository or the government institutes.

Dr. Shurin sketched out the process for how “obvious” associations would be immediately available, and thus not patentable. They expect that downstream the secondary investigators manipulating the data would be able to patent “non-obvious” associations as targets for possible diagnostic and therapeutic purposes. Researchers would need to be affiliated with an institution but not necessarily funded by the NIH to apply for access to the data. They will have to show what they want to do and to give assurances about privacy and compliance with applicable laws (although she doesn’t get very specific about this, as with much else in her talk). She mentioned genetic discrimination and how concerned they are about this. They are inviting the subjects in the Framingham study to be involved in the oversight process and stressed again about the public commentary period which was to close at the end of November 2006 followed by a town hall meeting.

Dr. Shurin took questions at that point and seemed to become quite hazy on details in response to many of the questions. When she was asked about who was going to decide if their safeguards were adequate in all of this, she seemed taken aback and said their policies were so integrated that they did not conceive of ethics consultation as being separate from all the other processes that they had set up. One of the participants, Dr. Kevin Fitzgerald, pushed quite strongly on this point, saying that they might actually need to go to an outside body to ensure that the ethical oversight and accountability was adequate.

For the 45 minute Real Player webcast, scroll down to the Tuesday, November 14, 2006 session under __Federal Developments and Updates__: http://www4.od.nih.gov/oba/SACGHS/meetings/Nov2006/SACGHSNov2006meeting.htm You can read the whole thing a lot faster by going to: http://www4.od.nih.gov/oba/SACGHS/meetings/Nov2006/transcripts/Federal_Dev-Shurin.pdf (but you miss the fascinating body language if you do!) (JC)