Rebecca Winner and Dr. Brent Nielsen, Department of Microbiology and Molecular Biology

Telomeres are protective deoxyribonucleic acid caps on the ends of chromosomes which help prevent the chromosome itself from shortening during replication. As a person ages, normal telomere shortening occurs due to chromosome replication. However, accelerated telomere shortening is abnormal and has been linked to several factors such as disease, depression, and anxiety.

This project aims to determine if underlying genetic factors that contribute to increased incidence of depression will produce accelerated telomere shortening as seen in subjects with a history of depression. SNP’s in genes that code for 5-HTT, a serotonin receptor, and DRD2, a dopamine receptor, have been shown in previous studies to be associated with depression (Wolkowitz et al 2010). This project will look for a correlation between these specific polymorphisms and accelerated telomere shortening in a sample of young students.

Methods

Saliva samples were collected by Dr. Nielsen’s lab from a group of BYU students after having participants sign appropriate consent forms. SNP’s for 5-HT and DRD2 were analyzed using standard polymerase chain reaction (PCR). Isolated DNA from the saliva samples was mixed with the appropriate DNA primers for each gene to be amplified, along with taq polymerase, and nuclease free water. The samples were then run through several cycles of PCR using the appropriate protocol. The amplified DNA was then digested using appropriate restriction enzymes. The digested DNA was then separated into bands using electrophoresis and the resulting gels were visualized using an ethidium bromide stain and ultra-violet light to determine if the polymorphism was present. Reactions and analysis of the resulting gels for 5-HT were performed by myself, while DRD2 was analyzed by another student in the lab. Each gel was analysed by two separate students for accuracy.

Telomere length was determined using real-time polymerase chain reaction (QPCR) in a 96 well plate. An oligomer standard was used to create a standard curve, which was used to determine telomere length. The oligomer standard Tel Std 2 was prepared with plasmid DNA (puc19) to ensure a constant 20 ng of DNA per reaction well. In addition, a single copy gene standard was used to create a standard curve which determines genome copies per sample. For this standard we use 36B4 along with puc19. We also included a positive and negative template control, and all samples were done in triplicate.

Analysis of the QPCR data was done using the Light Cycler 480 converter program, and LinRegPCR. Telomere length was determined by taking the total amount of telomere in the sample and dividing by the genome copy number.

Results

This experiment did not give expected results, and for this reason the data will not be useable. The larger experiment was divided into three groups: Senior Games, a group of senior citizens who participated in the senior Olympics; Utah Valley, a group of normal senior citizens; and the Young Cohort, a group of young BYU students. The purpose of this paper was to determine a link between SNP’s associated with depression and accelerated telomere shortening in the Young Cohort. While the telomere length results for the Senior Games and Utah Valley groups were within the limits given in the literature, the telomere lengths for the Young Cohort fell far out of the accepted limit.

Discussion

The Young Cohort results were well out of the limits given by the literature. Because of this, the bulk of our time was spent trying to determine why results for one group were so far off, while the other two groups worked well. The same methods were used for all three groups, and have also been successfully used in other studies, so we assumed that our methods were sound. In addition, I did all of the Young Cohort, but also worked on the Senior Games group. My QPCR plates for the Senior Games gave good results, but my Young Cohort plates did not. So, we also assumed that the problem was not due to pipetting error or changes from person to person.

Part way through the Young Cohort, we ran out of telomere primers, and had to order new ones. Since this was the only change in the experiment from one group to another, we assumed the problem was with the primers. We tested the primers concentration using a nanodrop, which gave normal results. Next, we considered that the new primers may have a different efficiency than our old primers, meaning the old standard curve would not give us an accurate value for telomere length. We made a new standard curve using the new primers. Unfortunately, analyzing the plates done after the primer change with the new standard curve still did not give results within the expected range.

Next, we decided to run tests to see if the DNA we were using was the problem. First, we reisolated fresh DNA from our saliva samples and ran a QPCR plate using the fresh DNA. This did not fix our problem. Next, we thought that our saliva samples could be too old, and the telomeres could be degraded. To check for this, we ran a 0.75% agarose gel. If the DNA had too much degradation, we would have seen a smear. However, the DNA showed up in a crown shape, indicating that it was not degraded. To be sure old DNA was not the problem, we took six fresh saliva samples from lab students, isolated DNA and ran it on a plate with Young Cohort samples using the QPCR method described. The fresh samples gave results that were just as unreliable as the Young Cohort samples, leading us to believe that old DNA was not the problem either.

The last possibility we checked was the integrity of our QPCR machine. We analyzed all the plated done on that machine to see which wells failed to amplify. After doing this, we found that a few wells had over 80% failure rate. We ran another QPCR plate, this time without using the wells that failed often. This still did not fix our problem, and the samples gave results that were well out of the accepted range.

Conclusion

Unfortunately, we could not find what caused our Young Cohort values to be so off from the rest of the groups. We assessed every aspect of the experiment we could think of, but could not determine the cause. It is likely that a combination of factors contributed to the failure, and this is why we could not find a single cause. Because our values were out of the accepted range given by the literature, we cannot make any useful conclusions about the correlation between SNP’s and accelerated telomere shortening in the Young Cohort.

References

• O’Callaghan, N.J., Dhillon, V.S., Thomas, P., & Fenech, M. (2008). A quantitative real-time PCR method for absolute telomere length. BioTechniques, 44:807-809.
• Wolkowitz, O.M., Epel, E.S., Reus, V.I., & Mellon, S.H. (2010). Depression gets old fast: Do stress and depression accelerate cell aging? Depression and Anxiety, 27: 327-338.