Updated 4 October 2007

1. Introduction

Family history is the second greatest risk factor for Alzheimer's disease (AD) after age, and the growing understanding of AD genetics has been central to the rapid increase in knowledge from AD neuropathology to the molecular level (for reviews see: Bertram & Tanzi, 2001, 2004; Hardy, 2003; Kamboh, 2004; Myers & Goate, 2001; Selkoe & Podlisny, 2002; St. George-Hyslop, 2000). Genetically, AD is a complex and heterogeneous disorder, displaying what appears to be an age-dependent dichotomy. While rare and fully penetrant mutations predominantly cause early-onset (<65 years) autosomal dominant AD, the majority of AD cases show a much later onset and are believed to be governed by common genetic variants with reduced penetrance. Only one such common variant—the ε4-allele in APOE—has thus far been established as an AD susceptibility gene, with significant effects across many independent samples representing diverse ancestries (view information on how APOE polymorphisms are handled in AlzGene). A wealth of empirical and simulation data suggest that possibly several additional major AD genes remain to be identified (e.g., Bertram & Tanzi, 2004; Blacker, 2003; Daw, 2000; Gatz, 2006; Li, 2002; Myers, 2002).

In the past decade, literally hundreds of reports have been published claiming or refuting genetic association between such putative AD genes and disease risk, onset age, or other phenotypic variables (Bertram & Tanzi, 2001, 2004; Finckh, 2003; Rocchi, 2003). Presently, 10 or more AD association studies are being published monthly from research groups worldwide. This wealth of information is becoming increasingly difficult to follow, evaluate, and much less to interpret.

2. Database Organization and Methods

Overview

The goal of the AlzGene database is to serve as a comprehensive, unbiased, publicly available and regularly updated collection of published genetic association studies performed on AD phenotypes. Eligible publications are identified following systematic searches of scientific literature databases, as well as the table of contents of journals in genetics, neurology, and psychiatry. Data selected for display summarize key characteristics of the investigated study cohorts (e.g., gene overview), as well as genotype distributions in cases and controls (e.g., polymorphism details). For polymorphisms with genotype data in at least four case-control samples, continuously updated random-effects meta-analyses are presented (see meta-analysis methods). Note that data obtained from family-based studies are not included in the meta-analyses, as crude odds ratios cannot be readily calculated from overall genotype distributions. However, these studies and their qualitative results are still listed on the gene-summary pages of the AlzGene website (see Table 2 for example).

To ensure the highest degree of scientific objectivity, only studies published in peer-reviewed journals available in English are considered for inclusion into the database. In particular, this precludes the inclusion of data presented only in abstracted form, e.g. at scientific meetings. We encourage authors of original reports fulfilling the above criteria to submit their data as soon as their work is accepted for publication.

Meta-Analysis Methods

For all polymorphisms with minor allele frequencies in healthy controls >1%, and for which case-control genotype data are available in four or more independent samples, crude odds ratios (ORs) and 95 percent confidence intervals (CIs) are calculated from the reported allele distributions for each study. (Note that in an earlier version of the database, meta-analyses were calculated based on data available in at least three independent samples which may still be on display for some genes; we are currently in the process of updating these entries.) Summary ORs and 95 percent CIs are calculated using the DerSimonian and Laird (1986) random-effects model, which utilizes weights that incorporate both within-study and between-study variance. This procedure is done including all studies irrespective of ethnicity (denoted by "All Studies" on the meta-analysis figures), and repeated after exclusion of the initial study ("All Excl Initial Study"), after exclusion of studies in which a deviation of Hardy-Weinberg Equilibrium (HWE) was detected in controls ("All Excl HWE Deviations"), and after exclusion of samples of non-Caucasian ancestry ("All Caucasian Studies"). Overlapping samples (of which usually only the largest is included), studies with missing data, or control samples deviating from HWE are indicated on the meta-analysis graphs. Please note, that when only few studies are included in the meta-analyses (i.e. less than ~10), the random effects model may yield summary ORs and confidence bounds that are slightly anti-conservative.

To allow a visual assessment of the presence of publication bias (or other sorts of reporting bias), we use a Begg modified funnel plot which depicts the allele-specific OR (on a logarithmic scale) against its standard error for each study (Egger, 1997) including studies of all ethnicities. Note that the power to detect deviations from a symmetrical distribution is limited, especially for analyses based on less than ~20 individual studies.

Inclusion of Genome-wide Association (GWA) Analyses

The systematic inclusion of data from large-scale studies and GWA analyses represents a conceptual and computational challenge for any genetic database. We have devised the following step-wise protocol, which we believe allows us to capture the most relevant genetic information without the need to include every data-point from these studies. Note that this feature of AlzGene is new and still under development. Please visit this page to see a summary of all published large-scale studies currently included in AlzGene.

Stage I: Represents the inclusion of genes and polymorphisms “featured” or highlighted by the authors of the large-scale study, usually because they show some degree of genetic association after completion of all analyses, e.g. testing multiple independent samples. These genes and polymorphisms probably represent the most important findings of each large-scale analysis and are therefore included here with highest priority. Genomic loci that do not map within any known gene are represented by a surrogate name specifying the cytogenetic location (e.g. “GWA_1q25.12”). This stage has already been implemented in the current version of AlzGene (e.g. for the ACAN gene featured in the GWA study by Grupe et al. [2007]).

For large-scale/GWA studies that have made their genotype data publicly available, we will also make use of “non-featured” genotype distributions, i.e. of polymorphisms not believed to be associated with AD in the original publications:

Stage II: Will add large-scale/GWA genotype data for polymorphisms already available in AlzGene, i.e. usually derived from candidate gene studies. Large-scale/GWA data for such overlapping polymorphisms will be added to the gene-specific entries and, if genotype data is then available in a total of at least four independent case-control samples, included and displayed in the meta-analyses. This stage adds valuable information to the existing AlzGene meta-analyses as it is derived from assessments that are largely unbiased with respect to gene function, in contrast to most conventional candidate gene studies. This stage has now been implemented in AlzGene.

Stage III: Applies to GWA studies only. If genotype distributions are publicly available for multiple GWA scans, we will perform systematic meta-analyses for all markers overlapping in at least four independent case-control samples. Only those showing significant summary ORs will be displayed on the AlzGene website. The threshold of declaring statistical significance (resulting in being displayed at the front-end of the database) in this context will be more stringent, due to the large number of tests performed (i.e. P-values of the summary ORs <<0.05). Procedures for implementing this stage, and the definition of appropriate threshold criteria is currently underway and will follow guidelines suggested previously (Evangelou, 2007). This feature is not yet available in AlzGene.

For more details on inclusion criteria, literature searches, data-management procedures, statistical analyses, and online database structure, please see Bertram et al. (2007).

3. Summary of AlzGene Meta-analysis Highlights: The "Top Results" List

In an effort to facilitate the identification of the most promising meta-analysis results available in AlzGene, a continuously updated list displaying the most strongly associated genes ("Top Results") has been added to the AlzGene homepage. The list is ranked by effect size, and only includes genes that contain at least one variant showing a nominally significant summary OR in the analysis of all ethnic groups (“All”), or those limited to samples of Caucasian ancestry (“Caucasian only”). While we believe that this list represents an up-to-date summary of particularly promising AD candidate genes that warrant follow-up with high priority, we note that many of these may represent false-positive findings, in particular those based on small (<10) sample sizes. Note that an earlier version of the “Top Results” list (before April 26, 2007), also included variants showing significant ORs based on a minimum of three independent samples, whereas now at least four samples with genotype data are required for inclusion. Another new feature is that polymorphisms with significant summary ORs in the "Caucasian only" analyses alone are now also included in the "Top Results" list.

APOE and related effects in the "Top Results List"

Genetic variants for which a significant meta-analysis result is likely due to linkage-disequilibrium with the APOE-ε4 allele (e.g. TOMM40, APOC1, APOC2; Martin, 2001; Yu, 2007) are not listed separately as “Top Results”. However, the meta-analyses on these genes and polymorphisms is still available via the specific gene-summary pages. View also information below on how APOE-ε4 itself is handled in AlzGene.

4. Early-onset Familial AD Genes

AlzGene provides summaries of studies that use genetic association methods on common polymorphisms (minor allele frequency in controls >1%) by either case-control or family-based designs. For a summary of rare mutations in early-onset familial AD genes (APP, PSEN1, and PSEN2) please visit the Alzheimer Disease & Frontotemporal Dementia Mutation Database of the Department of Molecular Genetics, University of Antwerp, Belgium. See also the Alzforum Mutations Directory.

5. Association of APOE Polymorphisms with AD

In contrast to all other association findings in AD, the risk effect of APOE-ε4 has been consistently replicated in a large number of studies across many ethnic groups. Many studies have also observed a more modest protective effect for the minor allele, ε2. Because the established role of the ε4- allele, we did not seek to catalog every APOE-ε2/3/4- result in the published literature. Instead, as a proof of concept, we only considered the 43 samples included in the previous meta-analysis by Farrer et al. (1997).

Note that there are several differences in the approaches taken by Farrer (1997) and AlzGene to derive summary risk estimates for the ε2/3/4 polymorphism in APOE: 1) Farrer et al. included data from every available study (including meeting reports, studies not available in English, family-based data, and personally communicated, unpublished genotype data, no published control genotypes, etc.). Following the same procedure as for all other genes represented in AlzGene, five such studies were excluded here (i.e., refs. 43, 51, 55, 57, 62, [in Farrer paper]). 2) Farrer et al. included case-control and family-based samples in their meta-analyses. For each of the family studies, only one individual (generally the proband) was included in the pooled analyses, but none of the unaffected individuals. Three such studies are excluded from the AlzGene analyses because crude ORs cannot be calculated in these cases (i.e., refs. 26, 42, and 49 [in Farrer paper]). 3) Farrer et al. had access to the raw genotype data from all studies, which allowed OR estimates from pooled genotypes, as well as several additional analyses incorporating co-variables such as onset age, gender, and years of education. AlzGene uses a traditional meta-analytic approach based on crude ORs calculated separately for each study from the published genotype tables (see meta-analysis methods). Despite these analytic and conceptual differences, the results of both approaches generate very similar effect size estimates and confidence intervals (see Table below and AlzGene meta-analysis results).

Please note that the restrictions in inclusion criteria for the ε2/ε3/ε4 variants in APOE do not apply to any of the other published APOE polymorphisms tested for association with AD (e.g., those in the promoter region). For those, we have attempted to sample and analyze every study fulfilling general AlzGene inclusion and exclusion criteria (see above).

Table. APOE-ε2/ε3/ε4 random effects summary odds ratios in AlzGene compared to meta-analysis on pooled genotype raw data by Farrer and colleagues

Study		OR ε3/4 vs. ε3/3 (95% CI)	OR ε4/4 vs. ε3/3 (95% CI)	OR ε2/3 vs. ε3/3 (95% CI)	Total sample size (# independent samples)
Farrer, 1997a
	Caucasian, Clinic/Autopsy	3.2 (2.8-3.8)	14.9 (10.8-20.6)	0.6 (0.5-0.8)	6,305 (31)
	Caucasian, Population-based	2.7 (2.2-3.2)	12.5 (8.8-17.7)	0.6 (0.5-0.9)	4,858 (10)
	Asian (Japan)	5.6 (3.9-8.0)	33.1 (13.6-80.5)	0.9 (0.4-2.5)	2,313 (5)
AlzGeneb
	Caucasian, Clinic/Autopsy	4.3 (3.3-5.5)	15.6 (10.9-22.5)	0.6 (0.3-1.2)	4,946 (20)
	Caucasian, Population-based	2.8 (2.3-3.5)	11.8 (7.0-19.8)	0.3 (0.2-0.6)	2,866 (8)
	Asian (Japan)	3.9 (1.9-8.0)	21.8 (8.6-55.3)	0.7 (0.3-1.6)	1,541 (4)

Table Legend:

a) based on pooled genotypes and adjusted for age and study; odds ratios (ORs) and total sample sizes are taken from Table 3, number of independent samples from Table 1, in the article by Farrer et al. (1997).

b) based on study-specific crude odds ratios (OR), using random effects models on published genotypes only (see meta-analysis methods for details); studies, ethnicities and ascertainment scheme are based on information provided in Farrer et al. (1997). View summary odds ratios and forest plots of allelic contrasts in AlzGene.

Bertram L, McQueen MB, Mullin K, Blacker D, Tanzi RE. (2007) "Systematic meta-analyses of Alzheimer disease genetic association studies: the AlzGene database." Nat Genet 39(1): 17-23. Abstract

Bertram L, Tanzi RE (2004) "Alzheimer's disease: one disorder, too many genes?" Hum Mol Genet 1;13 (Spec No 1): R135-41. Abstract

Bertram L, Tanzi RE (2001) "Of replications and refutations: the status of Alzheimer's disease genetic research." Curr Neurol Neurosci Rep 1(5):442-50. Abstract

Blacker D, Bertram L, Saunders AJ, Moscarillo TJ, Albert MS, Wiener H, Perry RT, Collins JS, Harrell LE, Go RC, Mahoney A, Beaty T, Fallin MD, Avramopoulos D, Chase GA, Folstein MF, McInnis MG, Bassett SS, Doheny KJ, Pugh EW, Tanzi RE; NIMH Genetics Initiative Alzheimer's Disease Study Group. (2003) "Results of a high-resolution genome screen of 437 Alzheimer's disease families." Hum Mol Genet 12(1):23-32. Abstract

Daw EW, Payami H, Nemens EJ, Nochlin D, Bird TD, Schellenberg GD, Wijsman EM (2000) "The number of trait loci in late-onset Alzheimer's disease". Am J Hum Genet 66:196-204. Abstract

DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986 Sep;7(3):177-88. Abstract

Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997 Sep 13;315(7109):629-34. Abstract

Evangelou E, Maraganore DM, Ioannidis JP. "Meta-analysis in genome-wide association datasets: strategies and application in Parkinson disease." PLoS ONE. 2007 Feb 7;2:e196. Abstract

Farrer, L.A., Cupples, L.A., Haines, J.L., Hyman, B., Kukull, W.A., Mayeux, R., Myers, R.H., Pericak-Vance, M.A., Risch, N., and van Duijn, C.M. (1997) "Effects of age, sex, and ethnicity on the association between apolipoprotein E genotype and Alzheimer disease. A meta-analysis. APOE and Alzheimer Disease Meta Analysis Consortium." JAMA 278:1349-1356. Abstract

Finckh U (2003) "The future of genetic association studies in Alzheimer disease". J Neural Transm 110: 253-66. Abstract

Gatz M, Reynolds CA, Fratiglioni L, Johansson B, Mortimer JA, Berg S, Fiske A, Pedersen NL (2006) "Role of genes and environments for explaining Alzheimer disease". Arch Gen Psychiatry 63(2):168-74. Abstract

Hardy J (2003) "The relationship between amyloid and tau". J Mol Neurosci 20(2):203-6. Abstract

Kamboh MI (2004) "Molecular genetics of late-onset Alzheimer's disease". Ann Hum Genet 68(Pt 4):381-404. Abstract

Li YJ, Scott WK, Hedges DJ, Zhang F, Gaskell PC, Nance MA, Watts RL, Hubble JP, Koller WC, Pahwa R, Stern MB, Hiner BC, Jankovic J, Allen FA Jr, Goetz CG, Mastaglia F, Stajich JM, Gibson RA, Middleton LT, Saunders AM, Scott BL, Small GW, Nicodemus KK, Reed AD, Schmechel DE, Welsh-Bohmer KA, Conneally PM, Roses AD, Gilbert JR, Vance JM, Haines JL, Pericak-Vance MA (2002) "Age at onset in two common neurodegenerative diseases is genetically controlled." Am J Hum Genet 70(4):985-93. Abstract

Martin ER, Lai EH, Gilbert JR, Rogala AR, Afshari AJ, Riley J, Finch KL, Stevens JF, Livak KJ, Slotterbeck BD, Slifer SH, Warren LL, Conneally PM, Schmechel DE, Purvis I, Pericak-Vance MA, Roses AD, Vance JM (2001) "SNPing away at complex diseases: analysis of single-nucleotide polymorphisms around APOE in Alzheimer disease." Am J Hum Genet. 2000 Aug;67(2):383-94. Abstract

Myers AJ, Goate AM. (2001) "The genetics of late-onset Alzheimer's disease." Curr Opin Neurol 14(4):433-40. Abstract

Myers A, Wavrant De-Vrieze F, Holmans P, Hamshere M, Crook R, Compton D, Marshall H, Meyer D, Shears S, Booth J, Ramic D, Knowles H, Morris JC, Williams N, Norton N, Abraham R, Kehoe P, Williams H, Rudrasingham V, Rice F, Giles P, Tunstall N, Jones L, Lovestone S, Williams J, Owen MJ, Hardy J, Goate A. (2002) "Full genome screen for Alzheimer disease: stage II analysis." Am J Med Genet 114(2): 235-44. Abstract

Rocchi A, Pellegrini S, Siciliano G, Murri L (2003) "Causative and susceptibility genes for Alzheimer's disease: a review". Brain Res Bull 61(1):1-24. Abstract

Saunders, A. M., W. J. Strittmatter, et al. (1993). "Association of apolipoprotein E allele epsilon 4 with late-onset familial and sporadic Alzheimer's disease." Neurology 43: 1467-72. Abstract

Selkoe DJ, Podlisny MB (2002) "Deciphering the genetic basis of Alzheimer's disease". Annu Rev Genomics Hum Genet 3:67-99. Abstract

Strittmatter, W.J., Saunders, A.M., Schmechel, D., Pericak-Vance, M., Enghild, J., Salvesen, G.S., and Roses, A.D (1993) "Apolipoprotein E: high-avidity binding to beta-amyloid and increased frequency of type 4 allele in late-onset familial Alzheimer disease." Proc Natl Acad Sci U S A 90:1977-1981. Abstract

St George-Hyslop PH (2000) "Molecular genetics of Alzheimer's disease." Biol Psychiatry 47(3):183-99. Abstract

Tanzi RE, Bertram L (2001) "New frontiers in Alzheimer's disease genetics." Neuron 32:181-4. Abstract

Yu CE, Seltman H, Peskind ER, Galloway N, Zhou PX, Rosenthal E, Wijsman EM, Tsuang DW, Devlin B, Schellenberg GD (2007) "Comprehensive analysis of APOE and selected proximate markers for late-onset Alzheimer's disease: Patterns of linkage disequilibrium and disease/marker association." Genomics. Apr 12 (Epub ahead of print). Abstract