Complement Factor H Haplotypes and Smoking in Age-related Macular Degeneration

Study Overview
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Brief Summary
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Risk factors for Age-related Macular Degeneration (AMD) involves genetic variations in the alternative pathway of complement inhibitor factor H. The complement system is part of the innate and adaptive immune system. Smoking is the only environmental factor known to increase the risk of Age-related Macular Degeneration (AMD). Using serum samples of Age-related Macular Degeneration (AMD) patients and controls the investigators will test the hypothesis that smoking increases Age-related Macular Degeneration (AMD) by increasing complement activation; and that this is positively correlated with known disease variations in the complement factor H (CFH) gene.

Detailed Description
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RESEARCH DESIGN AND METHODS A) Study design This study is designed to determine whether smoking increases complement activation and whether there are specific AMD genotypes that are particularly sensitive to this elevated level of serum complement components. B) Selection of subjects and controls Case subjects and age-matched (within 5 years) control subjects will be recruited under a protocol approved by the Johnson and DeBakey VA Medical Centers, and the Medical University of South Carolina (MUSC) Human Investigation Review Board. Inclusion Criteria Case subjects with a clear diagnosis of AMD and at least a 20/40 view of the fundus. Control subjects with <5 small hard drusen and at least a 20/40 view of the fundus. All subjects will have the ability to provide a blood sample, demonstrate the absence of exclusion criteria listed below, provide their own consent, or have a legal representative available to provide consent for them, able to complete all aspects of testing, and be in generally good medical health in the opinion of the study physician. Exclusion Criteria Individuals who are unable to provide consent and who lack a legal representative, whose best corrected visual acuity for both eyes is worse than 20/40, who are taking a medication known to cause retinopathy, unable to cooperate to complete testing, and who present themselves with media opacity, who exhibit diseases that phenotypically overlap with AMD such as drusen or pigmentary disturbance of the retinal pigment epithelium; or provide insufficient evidence to diagnose AMD. Individuals who present themselves with macular dystrophies, toxoplasmosis, histoplasmosis, degenerative myopia, central serous chorioretinopathy, or any disease or treatment that would diminish the ability to recognize drusen such as laser photocoagulation, prior retinal detachment surgery, posterior uveitis, and trauma. Sample Size and Power Estimation A total of 150 case subjects and 150 control subjects will be recruited. Sample size was determined by statistically simulating the study findings using the following assumptions: an alpha level of 0.05; 2-sided hypothesis testing; and an expected distribution across the CC, CT, and TT factor H genotypes of 8.1%, 52%, and 39.9%, respectively, [1 and assuming  35% of the subjects being current smokers. This sample size would provide 85% power to detect a significant smoking by genotype interaction, the main focus of this study. Recruitment Case and age-matched (within 5 years) control subjects will be recruited. Recruitment will take place in two ways: 1) they will be called or recruited after the diagnosis in the doctor's office. Upon signed consent, these subjects will also be asked to provide information about their smoking status, and a blood sample (two 3 mL tubes) will be collected. C) Outcome measures Incidence of AMD will have been determined in the prior clinical visit based on Fundus photographs and accepted AMD definitions. Additional outcome measurements that will help characterize the severity of AMD disease might include the visual field test, OCT and fluorescein angiograms. D) Data analyses Data assembled as normalized serum levels of complement factors Ba, C3d and fD and fH activity levels will be initially evaluated with univariate statistics to assure that the quality of the data is adequate for further analyses. The association between each measured parameter (i.e., serum levels of complement factors), AMD diagnosis, genotype and smoking will be assessed in a stratified bivariate fashion using Student t tests or Wilcoxon rank sum tests, as appropriate, and standard measure assessments will be used to check for normality, skewing, etc. Multivariate analyses will be conducted through the use of general linear mixed models [5]. The models will include random subject effects to account for dependence among repeated measurements of subjects. This type of model is ideal when there are multiple measurements on subjects, such as when laboratory measurements are performed in triplicate. The dependent variables of interest will be the complement level measurements (log transformed, if necessary), while independent variables will include AMD status (case/control), factor H genotype (CC, CT, TT), smoking (current, former, never), and an interaction-term involving factor H genotype and smoking status. The interaction-term will help us to determine whether the impact of factor H genotype and smoking on serum complement levels is linear (additive), or non-linear (e.g., multiplicative). The model will also include adjustments for age, gender, and race, which may all affect complement factors. Thus, any differences among haplotypes will be adjusted (corrected) for effects that may be attributed to age, gender, or race. Different correlation structures will be examined for the random subject effects, and the investigators will use Akaike's Information Criterion to select the most appropriate model. Secondary analyses will involve excluding never smokers, to assess the nature of the association (if any) between pack/year histories. factor H genotypes. and their complement levels. An additional analysis (using conditional logistic regression) will be conducted to determine whether smoking interacts with a subject's factor H genotype with respect to the risk of AMD. Again, this model will be adjusted for age, gender, and race, and the results will be expressed as odds ratios associated with the risk of AMD. E) Potential risks Subjects will have received a comprehensive eye examination that was not part of this study. The potential risks cannot be described. Venipuncture for whole blood. The risks of venipuncture are pain or bruising at the site of venipuncture; fainting or dizziness; or infection at the site of the needle stick. None of these are permanent or substantial losses. Clinical staff are trained to deal with these complications. Personal information. Sharing of personal information (blood specimens, personal history, genetic information, etc.) is not without risk. Research to identify genes that cause or contribute to a disease or trait is an increasingly important way to try to understand the role of genes in human disease. The participants were given a consent form because the Johnson and DeBakey VA Medical Centers investigators want to include the participants' blood sample in a research project, or because they want to save such biological specimens for future research. There are several things participants should know before allowing the blood to be studied or to be saved. Blood samples will be stored under an alphanumeric identifier which could eventually be linked to the participants. In addition to name, other information about participants might be connected to blood samples. Genetic information about the participants' will often apply to family members. The participants have the right to refuse to allow their blood to be studied or saved for future research studies. South Carolina law mandates that genetic information, obtained from any tests or from this research, be kept confidential. Genetic research raises difficult questions about informing participants and other subjects of any results, or of future results. If the participants are concerned about a potential genetic disorder, the participant and their doctor might choose to test specifically for it. This would require additional blood or tissue samples and would not be part of this research project. The presence of a genetic marker for a disease does not necessarily mean that the participants will develop that disease. Unknown risks. The researchers will let the participants know if they learn of anything that might make a change of mind about participating in this study.

Official Title
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Complement Factor H Haplotypes and Smoking in Age-related Macular Degeneration

Conditions
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Macular Degeneration

Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Inclusion criteria for subjects will be a clear diagnosis of Age-related Macular Degeneration (AMD) Inclusion criteria for controls will be less than five small (< 63 um) hard drusen At least a 20/40 view of the fundus The ability to provide a blood sample, and the absence of exclusion criteria listed Exclusion Criteria: The investigators will exclude individuals with ocular diseases that might simulate Age-related Macular Degeneration (AMD) or preclude its diagnosis. Those might include prior laser photocoagulation, cryopexy, media opacity, and inflammatory diseases. It is important for potential control subjects not to exhibit media opacity (e.g., cataract), which will prevent visualization of the macula. Also, subjects will be excluded if they exhibit diseases that phenotypically overlap with Age-related Macular Degeneration (AMD) such as drusen or pigmentary disturbance of the retinal pigment epithelium (RPE), or that provided insufficient evidence to diagnose Age-related Macular Degeneration (AMD). In addition, subjects with pattern dystrophies, toxoplasmosis, histoplasmosis, degenerative myopia, central serous chorioretinopathy, or any disease or treatment that would diminish the ability to recognize drusen such as laser photocoagulation, prior retinal detachment surgery, posterior uveitis, and trauma will be excluded.

Ages Eligible for Study
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Minimum Age: 40 Years
Maximum Age: 80 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Group 1 (Control)<br>Case control subjects without AMD diagnosis | |
| Group 2 (Age-related Macular Degeneration)<br>Case (i.e., within 5 years) subjects will be recruited. Cases are defined as subjects with diagnosed AMD. | |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Age in Study Participants | Assessment of Age based on clinical records. | baseline visit | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Number of Participants That Are Smokers | Patients were asked during patient interview as to their history of smoking (current, never or ever was assessed). | Day 1 of study | 
| Number of Participants With Signal Nucleotide Polymorphisms for CFH Locus | To assess for risk of AMD. Cells remaining from the serum separation were used for genetic analysis. Genomic DNA was extracted using a commercially available DNA extraction kit according to the manufacturer's instructions (QIAmp® DNA Mini; Qiagen). The AMD-associated SNP was genotyped at CFH (rs3766404), locus using PCR-based assays (TaqMan assays, Applied Biosystems), according to the manufacturer's instructions. Only white Caucasians in the population were included. | Blood sample collection at contact | 
| Percentage of Complement Pathway Proteins in the Serum | To assess systemic complement activation, venus blood is collected. Complement component analysis was performed as a fee for service at the National Jewish Health Advanced Diagnostic Laboratories, using commercially available kits. Samples were analyzed in two batches in which the ELISA displayed difference sensitivities. Therefore data was normalized within each batch to values obtained from control subjects. Data reported represents the average of the two batches. | within a month of obtaining blood sample | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Age-Related Macular Degeneration, Age-Related Maculopathies, Age-Related Maculopathy, Macular Dystrophy, Maculopathies, Age-Related, Maculopathy, Age-Related