Genomic analysis can be powerful – in the right hands

You may have heard about the controversial genetics study connecting a set of 150 genetic markers to “exceptional longevity” (people living past 100). Everybody’s interested in living longer, so it’s not surprising that the work, published by Boston University researchers in July in the journal Science, was covered with much fanfare in many main-stream news outlets (for example, in the NY Times and Scientific American). Science even hosted a media teleconference to promote the story.

Things took a turn about a week later, when Newsweek wrote a story about some deep flaws in the work, highlighting the potential pitfalls of genetic research that relies too heavily on statistics without experimental evidence to support the claims.

The longevity project comes from a relatively new field called “genome-wide association studies”, or GWAS. Researchers in GWAS gather genetic data from thousands of individuals, sort them based on some characteristic, such as age or cholesterol levels, and see if there’s a correlation. The first GWAS was done in 2005, and so far it has been shown that many traits and diseases, like height and diabetes, are correlated with hundreds of genetic markers. Some have doubted the utility of such studies, though, and the controversy surrounding the longevity study has only increased the scrutiny directed toward these projects.

A new set of papers from a GWAS on cholesterol, however, provides a nice counterbalance to the longevity controversy. This was a massive study using data from 100,000 individuals, and the authors identified 95 genetic markers associated with cholesterol levels. (The longevity study only used data from about 1,000 people, mostly because it’s hard to find exceptionally old people.) The cholesterol researchers also went a step further – they tested some of the identified markers to see if they were actually involved in cholesterol metabolism. They were. (You can see the actual papers, published in Nature at the beginning of August, here and here).

GWAS essentially create a to-do list: they provide a putative group of genes that may be involved a trait, but before the cholesterol study, researchers generally weren’t taking the next step beyond the statistical analysis to actually show that their results were meaningful. The cholesterol work, on the other hand, identified and characterized a novel cholesterol-related metabolic pathway that likely wouldn’t have been identified without the GWAS.

So, despite the controversy surrounding the longevity study, it appears that GWAS really can be very valuable for identifying targets for further research. It’s just important to remember that the GWAS alone are not the answer; rather, they open doors to directions that otherwise may have been left unexplored.

Further reading:
News feature from Nature

Editor’s note: Remember a few weeks ago when I was amazed at a paper with 56 authors? Apparently the world of genomics does this kind of thing regularly. Feast your eyes on the author list below.

ResearchBlogging.orgTeslovich TM, Musunuru K, Smith AV, Edmondson AC, Stylianou IM, Koseki M, Pirruccello JP, Ripatti S, Chasman DI, Willer CJ, Johansen CT, Fouchier SW, Isaacs A, Peloso GM, Barbalic M, Ricketts SL, Bis JC, Aulchenko YS, Thorleifsson G, Feitosa MF, Chambers J, Orho-Melander M, Melander O, Johnson T, Li X, Guo X, Li M, Shin Cho Y, Jin Go M, Jin Kim Y, Lee JY, Park T, Kim K, Sim X, Twee-Hee Ong R, Croteau-Chonka DC, Lange LA, Smith JD, Song K, Hua Zhao J, Yuan X, Luan J, Lamina C, Ziegler A, Zhang W, Zee RY, Wright AF, Witteman JC, Wilson JF, Willemsen G, Wichmann HE, Whitfield JB, Waterworth DM, Wareham NJ, Waeber G, Vollenweider P, Voight BF, Vitart V, Uitterlinden AG, Uda M, Tuomilehto J, Thompson JR, Tanaka T, Surakka I, Stringham HM, Spector TD, Soranzo N, Smit JH, Sinisalo J, Silander K, Sijbrands EJ, Scuteri A, Scott J, Schlessinger D, Sanna S, Salomaa V, Saharinen J, Sabatti C, Ruokonen A, Rudan I, Rose LM, Roberts R, Rieder M, Psaty BM, Pramstaller PP, Pichler I, Perola M, Penninx BW, Pedersen NL, Pattaro C, Parker AN, Pare G, Oostra BA, O’Donnell CJ, Nieminen MS, Nickerson DA, Montgomery GW, Meitinger T, McPherson R, McCarthy MI, McArdle W, Masson D, Martin NG, Marroni F, Mangino M, Magnusson PK, Lucas G, Luben R, Loos RJ, Lokki ML, Lettre G, Langenberg C, Launer LJ, Lakatta EG, Laaksonen R, Kyvik KO, Kronenberg F, König IR, Khaw KT, Kaprio J, Kaplan LM, Johansson A, Jarvelin MR, Cecile J W Janssens A, Ingelsson E, Igl W, Kees Hovingh G, Hottenga JJ, Hofman A, Hicks AA, Hengstenberg C, Heid IM, Hayward C, Havulinna AS, Hastie ND, Harris TB, Haritunians T, Hall AS, Gyllensten U, Guiducci C, Groop LC, Gonzalez E, Gieger C, Freimer NB, Ferrucci L, Erdmann J, Elliott P, Ejebe KG, Döring A, Dominiczak AF, Demissie S, Deloukas P, de Geus EJ, de Faire U, Crawford G, Collins FS, Chen YD, Caulfield MJ, Campbell H, Burtt NP, Bonnycastle LL, Boomsma DI, Boekholdt SM, Bergman RN, Barroso I, Bandinelli S, Ballantyne CM, Assimes TL, Quertermous T, Altshuler D, Seielstad M, Wong TY, Tai ES, Feranil AB, Kuzawa CW, Adair LS, Taylor HA Jr, Borecki IB, Gabriel SB, Wilson JG, Holm H, Thorsteinsdottir U, Gudnason V, Krauss RM, Mohlke KL, Ordovas JM, Munroe PB, Kooner JS, Tall AR, Hegele RA, Kastelein JJ, Schadt EE, Rotter JI, Boerwinkle E, Strachan DP, Mooser V, Stefansson K, Reilly MP, Samani NJ, Schunkert H, Cupples LA, Sandhu MS, Ridker PM, Rader DJ, van Duijn CM, Peltonen L, Abecasis GR, Boehnke M, & Kathiresan S (2010). Biological, clinical and population relevance of 95 loci for blood lipids. Nature, 466 (7307), 707-13 PMID: 20686565

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