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GWAS Mega-Meta Yields More Risk Genes, BIN1 Binds Tau?

Series - Alzheimer's Association International Conference 2012:

In the past three years, genomewide association studies have grown the list of Alzheimer’s risk genes from a lone big gun (ApoE4) to a collection of 10 or so that account for about a third of the genetic risk for late-onset AD. That still leaves two-thirds of LOAD heritability a mystery, but on that front, a huge meta-analysis of GWAS data is turning up additional genes, scientists said at the Alzheimer’s Association International Conference held 14-19 July 2012 in Vancouver, Canada. In other genetics news at the conference, the first-ever African-American AD GWAS suggests ApoE may not be top dog in this ethnic group, and new analyses are homing in on biological pathways underlying existing risk variants to figure out how they actually contribute to AD. For example, some data suggest that BIN1 might bind tau and boost tauopathy.

In early 2011, scientists launched the International Genomics of Alzheimer’s Project (IGAP), pooling genetic data from four consortia in the U.S., U.K., and Europe into a mega-dataset containing 8.5 million single-nucleotide polymorphisms (SNPs; see ARF related news story). Analysis of this set has confirmed that all risk genes found in prior AD GWAS are indeed robust, Gerard Schellenberg of the University of Pennsylvania School of Medicine, Philadelphia, reported at AAIC. Schellenberg heads the Alzheimer’s Disease Genetics Consortium (ADGC), the largest of the four consortia in IGAP. At the same time, the real goal of IGAP is to identify new AD risk genes—especially the rarer variants present in as few as 1 percent of the population, which would escape detection by commercial genotyping platforms. Toward this end, the scientists culled from the mega-dataset around 20,000 SNPs with p-values of less than 1.0 x 10-3 and put them onto a custom chip for a replication phase using 29,000 subjects that were not part of the mega-meta-analysis. That is a liberal cutoff, Schellenberg said, since SNPs are not typically deemed genomewide significant unless their p-values fall around or below 1.0 x 10-8. The genotyping process for this project is more than 75 percent complete, Schellenberg told Alzforum. He did not disclose the names of the new risk genes, or even how many have been identified, at AAIC, but told Alzforum the team plans to draft a paper this month.

Pathway analysis offers another way to find new risk genes. This method involves looking at a list of potentially significant genes and testing whether more of them lie in a biochemical pathway than would be expected by chance. The list includes top hits as well as SNPs in the uncertain zone that came close to genomewide significance but failed to reach the statistical cutoff. “Some of those SNPs could be real, but you don’t know which ones. However, if 5 percent of them end up in one pathway, you can start to have confidence that they may be significant,” Schellenberg said.

Peter Holmans of Cardiff University School of Medicine, U.K., has done pathway analysis of IGAP data. This analysis has not turned up new risk genes as of yet; however, it has shed some light on the biological processes that may underlie genetic susceptibility to late-onset AD. Of 9,816 pathways tested, those relating to endocytosis and cholinergic receptors contributed most strongly to late-onset AD, Holmans reported in an AAIC talk. While these pathways are not new, “it is good to have their involvement confirmed by a systematic analysis of genomewide data,” Holmans said. Even after known variants (ApoE, BIN1, PICALM, etc.) were removed, these pathways still came up strong, Holmans noted, suggesting that their involvement in AD may be more general, not restricted to existing risk genes. The analysis also uncovered several new pathways—for example, protein catabolism, and degradation through ubiquitination pathways and the proteasome.

Christiane Reitz at Columbia University College of Physicians and Surgeons, New York, reported preliminary findings from the first large GWAS on AD in African-Americans. Her team used about 5,200 samples from the ADGC cohort that had not been tested in previous GWAS. The top hit was ABCA7, which came up in recent large GWAS in Caucasians (Naj et al., 2011; Hollingworth et al., 2011). However, the new and important finding here was that ABCA7 and ApoE seem to influence AD risk equally in African-Americans. “The effect size of ABCA7 was nearly as strong as the effect size of ApoE. The reasons for this remain to be clarified,” Reitz told Alzforum in an e-mail. The preliminary analysis also uncovered other SNPs in pathways previously reported to play a role in AD: CTNNA3 in cell-cell adhesion, CAPRIN2 in synaptic plasticity, and SPG20 in endosomal trafficking.

What about existing AD risk variants that have been confirmed time and time again? Consider BIN1, for example. Beyond ApoE, it is the top genetic susceptibility locus in AD, yet scientists know little about how it contributes to the pathophysiological process. Recent work from Jean-Charles Lambert’s research group at INSERM in Lille, France, has begun to change that. In several AAIC talks and posters, Lambert and colleagues put forth the possibility that Bin1 could interact with tau and exacerbate its toxicity. In a prior analysis, the researchers saw that BIN1 was overexpressed in AD brains. When they knocked down expression of the BIN1 Drosophila orthologue (Amph) in fruit flies, they found that this suppressed tau toxicity while leaving Aβ-related phenotypes unaffected. Those findings were reported at last year’s AAIC in Paris, France (see ARF related conference story). At the Vancouver meeting, Julien Chapuis from the group extended these findings with a poster showing evidence that Bin1 interacts with tau. The proteins associated in GST pulldown assays when overexpressed in transformed human cell lines, and also in synaptosomal fractions purified from wild-type mouse brain. The researchers are now investigating the consequence of this possible interaction, asking, for instance, whether Bin1 affects tau phosphorylation or aggregation, or influences formation of paired helical filaments.

Rudy Tanzi of Massachusetts General Hospital, Charlestown, finds the data interesting because of a possible tie-in with recent work published by Susan Lindquist of the Whitehead Institute for Biomedical Research in Cambridge, Massachusetts. In that study, which included Tanzi as a coauthor, scientists searched for modifiers of Aβ toxicity using a yeast screen. Three genes that came out of that screen are related to AD GWAS hits. One encodes synaptojanin 1, which interacts with Bin1. In this study, Bin1 is in a complex that affects Aβ toxicity, while the INSERM study suggests that Bin1 affects tauopathy. “Maybe Bin1 helps bridge Aβ pathology to tau toxicity,” Tanzi said. “How tauopathy is triggered from excess accumulation of Aβ has been a black box in the AD field for some time.” Then again, if a LOAD genetic factor like BIN1 can directly influence tau toxicity without affecting Aβ pathology, “it could be a strong argument against the amyloid cascade hypothesis,” Chapuis suggested in an e-mail to Alzforum.—Esther Landhuis.

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References

News Citations

  1. Mind the IGAP—Transatlantic Consortium to Map AD Genes
  2. Paris: President and All, French Science Takes the Stage

Paper Citations

  1. Naj AC, Jun G, Beecham GW, Wang LS, Vardarajan BN, Buros J, Gallins PJ, Buxbaum JD, Jarvik GP, Crane PK, Larson EB, Bird TD, Boeve BF, Graff-Radford NR, De Jager PL, Evans D, Schneider JA, Carrasquillo MM, Ertekin-Taner N, Younkin SG, Cruchaga C, Kauwe JS, Nowotny P, Kramer P, Hardy J, Huentelman MJ, Myers AJ, Barmada MM, Demirci FY, Baldwin CT, Green RC, Rogaeva E, St George-Hyslop P, Arnold SE, Barber R, Beach T, Bigio EH, Bowen JD, Boxer A, Burke JR, Cairns NJ, Carlson CS, Carney RM, Carroll SL, Chui HC, Clark DG, Corneveaux J, Cotman CW, Cummings JL, DeCarli C, DeKosky ST, Diaz-Arrastia R, Dick M, Dickson DW, Ellis WG, Faber KM, Fallon KB, Farlow MR, Ferris S, Frosch MP, Galasko DR, Ganguli M, Gearing M, Geschwind DH, Ghetti B, Gilbert JR, Gilman S, Giordani B, Glass JD, Growdon JH, Hamilton RL, Harrell LE, Head E, Honig LS, Hulette CM, Hyman BT, Jicha GA, Jin LW, Johnson N, Karlawish J, Karydas A, Kaye JA, Kim R, Koo EH, Kowall NW, Lah JJ, Levey AI, Lieberman AP, Lopez OL, Mack WJ, Marson DC, Martiniuk F, Mash DC, Masliah E, McCormick WC, McCurry SM, McDavid AN, McKee AC, Mesulam M, Miller BL, Miller CA, Miller JW, Parisi JE, Perl DP, Peskind E, Petersen RC, Poon WW, Quinn JF, Rajbhandary RA, Raskind M, Reisberg B, Ringman JM, Roberson ED, Rosenberg RN, Sano M, Schneider LS, Seeley W, Shelanski ML, Slifer MA, Smith CD, Sonnen JA, Spina S, Stern RA, Tanzi RE, Trojanowski JQ, Troncoso JC, Van Deerlin VM, Vinters HV, Vonsattel JP, Weintraub S, Welsh-Bohmer KA, Williamson J, Woltjer RL, Cantwell LB, Dombroski BA, Beekly D, Lunetta KL, Martin ER, Kamboh MI, Saykin AJ, Reiman EM, Bennett DA, Morris JC, Montine TJ, Goate AM, Blacker D, Tsuang DW, Hakonarson H, Kukull WA, Foroud TM, Haines JL, Mayeux R, Pericak-Vance MA, Farrer LA, Schellenberg GD. Common variants at MS4A4/MS4A6E, CD2AP, CD33 and EPHA1 are associated with late-onset Alzheimer's disease. Nat Genet. 2011 May;43(5):436-41. Epub 2011 Apr 3 PubMed.
  2. Hollingworth P, Harold D, Sims R, Gerrish A, Lambert JC, Carrasquillo MM, Abraham R, Hamshere ML, Pahwa JS, Moskvina V, Dowzell K, Jones N, Stretton A, Thomas C, Richards A, Ivanov D, Widdowson C, Chapman J, Lovestone S, Powell J, Proitsi P, Lupton MK, Brayne C, Rubinsztein DC, Gill M, Lawlor B, Lynch A, Brown KS, Passmore PA, Craig D, McGuinness B, Todd S, Holmes C, Mann D, Smith AD, Beaumont H, Warden D, Wilcock G, Love S, Kehoe PG, Hooper NM, Vardy ER, Hardy J, Mead S, Fox NC, Rossor M, Collinge J, Maier W, Jessen F, Rüther E, Schürmann B, Heun R, Kölsch H, van den Bussche H, Heuser I, Kornhuber J, Wiltfang J, Dichgans M, Frölich L, Hampel H, Gallacher J, Hüll M, Rujescu D, Giegling I, Goate AM, Kauwe JS, Cruchaga C, Nowotny P, Morris JC, Mayo K, Sleegers K, Bettens K, Engelborghs S, De Deyn PP, Van Broeckhoven C, Livingston G, Bass NJ, Gurling H, McQuillin A, Gwilliam R, Deloukas P, Al-Chalabi A, Shaw CE, Tsolaki M, Singleton AB, Guerreiro R, Mühleisen TW, Nöthen MM, Moebus S, Jöckel KH, Klopp N, Wichmann HE, Pankratz VS, Sando SB, Aasly JO, Barcikowska M, Wszolek ZK, Dickson DW, Graff-Radford NR, Petersen RC, , van Duijn CM, Breteler MM, Ikram MA, DeStefano AL, Fitzpatrick AL, Lopez O, Launer LJ, Seshadri S, Berr C, Campion D, Epelbaum J, Dartigues JF, Tzourio C, Alpérovitch A, Lathrop M, Feulner TM, Friedrich P, Riehle C, Krawczak M, Schreiber S, Mayhaus M, Nicolhaus S, Wagenpfeil S, Steinberg S, Stefansson H, Stefansson K, Snædal J, Björnsson S, Jonsson PV, Chouraki V, Genier-Boley B, Hiltunen M, Soininen H, Combarros O, Zelenika D, Delepine M, Bullido MJ, Pasquier F, Mateo I, Frank-Garcia A, Porcellini E, Hanon O, Coto E, Alvarez V, Bosco P, Siciliano G, Mancuso M, Panza F, Solfrizzi V, Nacmias B, Sorbi S, Bossù P, Piccardi P, Arosio B, Annoni G, Seripa D, Pilotto A, Scarpini E, Galimberti D, Brice A, Hannequin D, Licastro F, Jones L, Holmans PA, Jonsson T, Riemenschneider M, Morgan K, Younkin SG, Owen MJ, O'Donovan M, Amouyel P, Williams J. Common variants at ABCA7, MS4A6A/MS4A4E, EPHA1, CD33 and CD2AP are associated with Alzheimer's disease. Nat Genet. 2011 May;43(5):429-35. PubMed.

External Citations

  1. ApoE4
  2. BIN1
  3. ABCA7

Further Reading

Papers

  1. Gistelinck M, Lambert JC, Callaerts P, Dermaut B, Dourlen P. Drosophila models of tauopathies: what have we learned?. Int J Alzheimers Dis. 2012;2012:970980. PubMed.
  2. Treusch S, Hamamichi S, Goodman JL, Matlack KE, Chung CY, Baru V, Shulman JM, Parrado A, Bevis BJ, Valastyan JS, Han H, Lindhagen-Persson M, Reiman EM, Evans DA, Bennett DA, Olofsson A, DeJager PL, Tanzi RE, Caldwell KA, Caldwell GA, Lindquist S. Functional links between Aβ toxicity, endocytic trafficking, and Alzheimer's disease risk factors in yeast. Science. 2011 Dec 2;334(6060):1241-5. PubMed.
  3. Chapuis J, Hansmannel F, Gistelinck M, Mounier A, Van Cauwenberghe C, Kolen KV, Geller F, Sottejeau Y, Harold D, Dourlen P, Grenier-Boley B, Kamatani Y, Delepine B, Demiautte F, Zelenika D, Zommer N, Hamdane M, Bellenguez C, Dartigues JF, Hauw JJ, Letronne F, Ayral AM, Sleegers K, Schellens A, Broeck LV, Engelborghs S, De Deyn PP, Vandenberghe R, O'Donovan M, Owen M, Epelbaum J, Mercken M, Karran E, Bantscheff M, Drewes G, Joberty G, Campion D, Octave JN, Berr C, Lathrop M, Callaerts P, Mann D, Williams J, Buée L, Dewachter I, Van Broeckhoven C, Amouyel P, Moechars D, Dermaut B, Lambert JC, GERAD consortium. Increased expression of BIN1 mediates Alzheimer genetic risk by modulating tau pathology. Mol Psychiatry. 2013 Nov;18(11):1225-34. Epub 2013 Feb 12 PubMed.

News

  1. Mind the IGAP—Transatlantic Consortium to Map AD Genes
  2. Next-Generation Sequencing: Boldly Going Where No Geneticist...
  3. LOADing Up—Largest GWAS to Date Confirms Two, Adds Two Risk Genes
  4. GWAS and Anatomy—Pooled Data Finger Genes Driving Brain Size, IQ
  5. Race Means Nothing, Genes Everything, in Personalized Medicine
  6. Traffic Control—Curb Endocytosis to Curb AD Pathogenesis?
  7. Large Genetic Analysis Pays Off With New AD Risk Genes
  8. Paris: President and All, French Science Takes the Stage
  9. Experimental α7 Agonist Meets Cognitive and Clinical Endpoints
  10. New Assays for Aβ Oligomers in CSF Claim Femtogram Sensitivity
  11. Q&A With Roche’s CNS Leader Luca Santarelli
  12. When Is a C9ORF72 Repeat Expansion Not a C9ORF72 Repeat Expansion?
  13. Wave of New BACE Inhibitors Heading to Phase 2
  14. Researchers Join to Draw Posterior Cortical Atrophy Out of Shadows
  15. CSF Markers: Goodbye, Research Use Only; Hello, Clinical
  16. Metrology, Certification Heavies Take CSF Tests Under Their Wings
  17. iPSC Disease Models Up and Coming for AD, Down’s, ALS
  18. Cochrane Asks for Field’s Input on Draft Reporting Standards
  19. Can We All Agree on How to Draw a Hippo(campus)?
  20. Collaborative Umbrella CAPs Three Prevention Trial Initiatives
  21. On Risk, Benefit, and More, Prevention Initiatives Take Questions
  22. In Big Picture, Familial AD’s Biomarker Data Resemble LOAD
  23. Dimmed Network Connections May Explain Metabolic Shortfall
  24. To Reveal or Not to Reveal? New Data on the Question

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