Approximately 25% of the variation in human lifespan is thought to be caused by genetic variation (Herskind et al. 1996), a contribution considered to be minimal before age 60 years and most profound after age 85 years (Hjelmborg et al. 2006). Candidate genes for longevity encode proteins engaged in different biological processes including lipoprotein metabolism and inflammatory processes (Christensen et al. 2006). In this study, we investigated 102 single-nucleotide polymorphisms (SNPs) covering the common genetic variation in 16 genes recurrently regarded as candidates for human longevity: APOE, ACE, CETP, HFE, IL6, IL6R, MTHFR, TGFB1, APOA4, APOC3, SIRT1, SIRT3, SIRT6, HSPA1A, HSPA1L, and HSPA14. Of these genes, only SIRT1 and SIRT3 have previously been investigated by a tagging SNP approach in a candidate association study (Flachsbart et al. 2006; Kuningas et al. 2007; Lescai et al. 2009). We explored the apolipoprotein E, C3, and A4 genes (APOE, APOC3, and APOA4), all of which are involved in lipoprotein metabolism and believed to affect longevity (Christensen et al. 2006). The APOE-4 haplotype is by far the most validated genetic variation and has repeatedly been associated with human longevity (e.g., Asada et al. 1996; Bathum et al. 2006; Deelen et al. 2011; Gerdes et al. 2000; McKay et al. 2011; Nebel et al. 2011; Schachter et al. 1994), whereas one study has found an association of rs2542052 in APOC3 with longevity (Atzmon et al. 2006). We also investigated the cholesteryl ester transfer protein (CETP), for which rs5882 has been reported as a longevity SNP (Barzilai et al. 2003). Genes encoding proteins engaged in immune regulatory processes are also key candidates for longevity (reviewed in Jylhava and Hurme 2010). Frequently discussed is the cytokine interleukin 6 (IL6) and its receptor alpha (IL6R); in IL6, a variable number of tandem repeat (VNTR) and a 174C/G polymorphism (rs1800795) have been described as associated with longevity (Capurso et al. 2007; Christiansen et al. 2004; Hurme et al. 2005; Rea et al. 2003). Another cytokine gene often suggested is the transforming growth factor beta 1 gene (TGF-β1), which is involved, among others, in regulation of cellular proliferation and differentiation. In TGF-β1, the +915 polymprobably function as intracellular regulatory proteins affecting, for example, IGF1/insulin signaling and DNA repair, although their roles are not entirely clear (Olmos et al. 2011). In SIRT3, a G477T polymorphism (Rose et al. 2003) and a VNTR polymorphism (Bellizzi et al. 2005) have been put forward as longevity polymorphisms. Finally, we examined three genes not belonging to any of these biological processes but still considered reliable candidates in previous studies: the highly discussed candidate gene angiotensin I-converting enzyme (ACE), for which the I/D insertion/deletion (tagged by rs4343 (Abdollahi et al. 2008)) has been reported by several authors to be associated with longevity (Arias-Vasquez et al. 2005; Cellini et al. 2005; Frederiksen et al. 2003; Luft 1999; Novelli et al. 2008; Schachter et al. 1994; Zajc et al. 2012); the iron absorption regulatory protein hfe, for which the Cys282Tyr variation (rs1800562) was found to decrease with age (Bathum et al. 2001; Lio et al. 2002); and finally, MTHFR, which is of importance for the essential remethylation of homocysteine to methionine, where the C677T (rs1801133) polymorphism has been suggested as associated with longevity (Stessman et al. 2005; Todesco et al. 1999). Subjects A considerable number of the associations mentioned above could not be replicated in subsequent studies. These studies include rs2542052 in APOC3 (Novelli et al. 2008), rs5882 in CETP (Cellini et al. 2005; Novelli et al. 2008), I/D insertion/deletion in ACE (Agerholm-Larsen et al. 1997; Bladbjerg et al.  Detailed characteristics for the discovery cohorts were previously described in (Soerensen et al. 2010). In short, the study population of oldest-old were 1,200 participants from The Danish 1905 Birth Cohort Study (Nybo et al. 2001), while the 800 younger controls were singleton participants from the Study of Middle-Aged Danish Twins (Skytthe et al. 2002). The survival status information was retrieved from the Danish Central Population Register (Pedersen et al. 2006), and the vital status was followed until death or January 1, 2010. After data cleaning, the final sample size was 1,089 oldest-old and 736 middle-aged individuals. Permission to collect blood samples and usage of register-based information was granted by The Danish National Committee on Biomedical Research Ethics (see Online Resource 1). The chromosomal regions investigated are the gene regions plus 5,000 kb upstream and 1,000 kb downstream. Tagging SNPs were identified via HapMap consortium database (http://hapmap.ncbi.nlm.nih.gov/index.html.en, CEU cohort) and analyzed using the HaploView software (http://www.broadinstitute.org/haploview/haploview; Barrett et al. 2005). Finally, for optimal genotyping, SNPs known to perform poorly on the Illumina GoldenGate genotyping platform were excluded. Genotyping DNA was isolated from blood spot cards using the QIAamp DNA Mini and Micro Kits (Qiagen, Germany); genotyping was performed using Illumina GoldenGate technology (Illumina Inc, San Diego, CA, USA), and data clean-up, data verification, and reproducibility checks were conducted as previously described (Soerensen et al. 2010). In total, 16 SNPs were excluded, leading to 102 SNPs for data analysis. Genotyping in the German and Dutch study populations was performed using Sequenom MassARRAY iPLEXGold technology (Sequenom, Inc., San Diego, CA, USA); see the Supplementary Material (Online Resource 1) for details. Study populations for replication of initial findings For replication of the initial observations from the Danish case-control study, two German samples of 1,613 unrelated long-lived individuals (age 95-110) and 1,140 middle-aged controls (mean age 67.2)