Genome-wide profiling of DNA methylome and transcriptome in peripheral blood monocytes for major depression: A Monozygotic Discordant Twin Study.
Zhu Y, Strachan E, Fowler E, Bacus T, Roy-Byrne P, Zhao J.
Zhu Y, Strachan E, Fowler E, Bacus T, Roy-Byrne P, Zhao J.
Cox RC, Taylor S, Strachan E, Olatunji BO.
Duncan GE, Avery A, Hurvitz PM, Moudon AV, Tsang S, Turkheimer E.
McCall CA, Turkheimer E, Tsang S, Avery A, Duncan GE, Watson NF.
Silventoinen K, Jelenkovic A, Yokoyama Y, Sund R, Sugawara M, Tanaka M, Matsumoto S, Bogl LH, Freitas DL, Maia JA, Hjelmborg JVB, Aaltonen S, Piirtola M, Latvala A, Calais-Ferreira L, Oliveira VC, Ferreira PH, Ji F, Ning F, Pang Z, Ordoñana JR, Sánchez-Romera JF, Colodro-Conde L, Burt SA, Klump KL, Martin NG, Medland SE, Montgomery GW, Kandler C, McAdams TA, Eley TC, Gregory AM, Saudino KJ, Dubois L, Boivin M, Brendgen M, Dionne G, Vitaro F, Tarnoki AD, Tarnoki DL, Haworth CMA, Plomin R, Öncel SY, Aliev F, Medda E, Nisticò L, Toccaceli V, Craig JM, Saffery R, Siribaddana SH, Hotopf M, Sumathipala A, Rijsdijk F, Jeong HU, Spector T, Mangino M, Lachance G, Gatz M, Butler DA, Gao W, Yu C, Li L, Bayasgalan G, Narandalai D, Harden KP, Tucker-Drob EM, Christensen K, Skytthe A, Kyvik KO, Derom CA, Vlietinck RF, Loos RJF, Cozen W, Hwang AE, Mack TM, He M, Ding X, Silberg JL, Maes HH, Cutler TL, Hopper JL, Magnusson PKE, Pedersen NL, Dahl Aslan AK, Baker LA, Tuvblad C, Bjerregaard-Andersen M, Beck-Nielsen H, Sodemann M, Ullemar V, Almqvist C, Tan Q, Zhang D, Swan GE, Krasnow R, Jang KL, Knafo-Noam A, Mankuta D, Abramson L, Lichtenstein P, Krueger RF, McGue M, Pahlen S, Tynelius P, Rasmussen F, Duncan GE, Buchwald D, Corley RP, Huibregtse BM, Nelson TL, Whitfield KE, Franz CE, Kremen WS, Lyons MJ, Ooki S, Brandt I, Nilsen TS, Harris JR, Sung J, Park HA, Lee J, Lee SJ, Willemsen G, Bartels M, van Beijsterveldt CEM, Llewellyn CH, Fisher A, Rebato E, Busjahn A, Tomizawa R, Inui F, Watanabe M, Honda C, Sakai N, Hur YM, Sørensen TIA, Boomsma DI, Kaprio J.
Duncan GE, Avery AR, Strachan E, Turkheimer E, Tsang S.
Moudon AV, Huang R, Stewart OT, Cohen-Cline H, Noonan C, Hurvitz PM, Duncan GE.
Sewaybricker LE, Melhorn SJ, Askren MK, Webb MF, Tyagi V, De Leon MRB, Grabowski TJ, Seeley WW, Schur EA.
Avery AR, Duncan GE
Goldfarb DS, Avery AR, Beara-Lasic L, Duncan GE, Goldberg J.
Ramchandani MS, Jing L, Russell RM, Tran T, Laing KJ, Magaret AS, Selke S, Cheng A, Huang ML, Xie H, Strachan E, Greninger AL, Roychoudhury P, Jerome KR, Wald A, Koelle DM.
Telfer S, Bigham JJ, Sudduth ASM.
Aging is complex process, involving both genetic and non-genetic factors. Genetics contribute to the rate of change for bodily functions and risk of disease, but these changes can also be influenced by the environment. The goal of this study was to learn more about the genes that are related to healthy aging, and how the aging process is influenced by environmental factors. By looking at genetic information, physical condition, family history, medical history, and life experiences across participants, researchers may be able to determine how these factors work together to create the overall aging experience.
This study collected data from 2013 to 2014. 275 same-sex twins 65 and older participated, with more of a focus on fraternal twins. The average age of participants in this study was 75, and the oldest participants were 91. All data collection was completed at home. Twins completed a packet of questionnaires, provided a saliva sample, and provided a small sample of blood collected by a finger stick.
This study seeks to understand how the environment influences our health by using a new device (the Portable Particle Monitor, PUWPM) that measures toxins in the environment, which was built and tested during the first phase of this study. These toxins include air pollution, noise, and allergens.
Exposure to particle pollution can result in increased hospital admissions, emergency room visits, absences from school or work, and restricted activity days, especially for those with pre-existing heart or lung disease, older people, and children. The size of particles is directly linked to their potential for causing health problems. Fine particles (PM2.5) pose the greatest health risk. The following is an example of what we are able to observe from collected data. Both maps show a morning walk in the summer. However, the walk on the right took place after major forest fires had broken out in the greater Pacific Northwest area. We can see that the PM2.5 this individual was exposed to was much lower before the fires broke out (map on left). By comparing twins, we can better understand how exposures to toxins in the unique environment may influence health.
Identical twins living apart within the State of Washington will be considered for this study. Eligible pairs will come to the Roosevelt Clinic in the University District of Seattle to receive the study materials. The study coordinator will record vital measurements and conduct a spirometry (lung function) test. At the end of the visit, participants will have their blood drawn. Biological specimens will be used to measure the amount of inflammation in the body, which may be related to environmental exposures. Data is then collected at home for two weeks. Participants will carry a GPS and wear an activity monitor that is similar to a pedometer or a Fitbit, as well as carry the PUWPM from the time they wake up until they go to sleep at night. They will also complete questionnaires. At the end of the two-week period, everything is returned to the study coordinator in a prepaid FedEx box.
This study continues on work conducted from 2012-15 exploring the role of the built environment in supporting healthy lifestyles. The built environment is defined as human-made surroundings, such as buildings, streets, and transportation systems, which support or hinder human activity. Although this topic has gained increasing attention from many researchers over the last several years, the influence of the environment on behaviors and health is not fully understood.
In this follow-up study, twin pairs who participated in the PAT study are contacted to participate in one week of follow-up data collection. All data collection is done entirely at home, and participants do not have to live within the Puget Sound to be eligible. Participants wear a GPS and an activity monitor, and complete questionnaires.
Zadro JR, Shirley D, Duncan GE, Ferreira PH.
Duncan GE, Seto E, Avery AR, Oie M, Carvlin G, Austin E, Shirai JH, He J, Ockerman B, Novosselov I.
Berkseth KE, Rubinow KB, Melhorn SJ, Webb MF, De Leon MRB, Marck BT, Matsumoto AM, Amory JK, Page ST, Schur EA.
Strachan E, Zhao J, Roy-Byrne PP, Fowler E, Bacus T.
Kim S, Wyckoff J, Morris AT, Succop A, Avery A, Duncan GE, Michal Jazwinski S.