Sample collection and RNA preparation

Eighty-seven non-related long-lived siblings, 337 offspring and partners belonging to 281 nuclear families were selected for the study (Table 1 and Supplementary Table S5). These samples randomly selected, but in such a way that age and gender balanced between the groups and age range was as large as Additionally, individuals with outlying cell counts (beyond 3 SDs or above the standard error of the mean) were excluded. subpopulation is representative for the whole LLS regarding prevalence and parameters involved in metabolic syndrome mentary Table S5) (Westendorp et al., 2009; Rozing et al., 2010). these non-fasted individuals, peripheral blood was harvested PAXgeneTM tubes (Qiagen, Venlo, the Netherlands). The tubes frozen and kept at (cid:1)20 °C for ~3–5 years. After thawing at temperature for at least 2 h, total RNA was extracted from approximately 2.5 mL of peripheral blood in each tube following manufacturer’s recommended protocol (PAXgene Blood RNA Kit book, Qiagen, Venlo, the Netherlands). The quality and integrity of total RNA was evaluated on the 2100 Bioanalyzer (Agilent Amstelveen, the Netherlands), and the concentration was using a NanoDrop spectrophotometer (NanoDrop Technologies, mington, DE, USA). Quality criteria included a 28S/18S ratio as by the Bioanalyzer of at least 1.2, and a total RNA yield of at least 3

In conclusion, the expression level in blood of genes belonging to the two mTOR complexes 1 and 2 associated with old age showing down- and up-regulation in the long-lived respectively. RPTOR gene expression was further significantly associated with familial longevity in middle-age independent of glucose levels and the prevalence of type 2 diabetes and cancer. At the level of suggestive evidence, this was also the case for PRRL5. These results suggest that the mTOR pathway may not only be involved in lifespan regulation in animal models, but also with the metabolic health and extended lifespan of human longevity families.

RT-qPCR

® For all 40 mTOR signalling genes, the suggested Taqman assay (Applied Biosystems, Bleiswijk, the Netherlands) was selected. Reverse transcription was performed with total RNA from blood of in total 790 samples, which passed QC using the First Strand cDNA Synthesis Kit according to the manufacturer’s protocol (Roche Applied Science, Almere, the Netherlands). cDNA was amplified using the DNA Engine ® Tetrad 2 Peltier Thermal Cycler (Bio-Rad, Veenendaal, the Nether- ® lands). qPCR was then performed with the Taqman method using the BiomarkTM 48.48 and 96.96 Dynamic Arrays (Fluidigm, Amsterdam, the Netherlands). Relative gene expression of the BioMarkTM Array data were calculated using the 2(cid:1)DDCt method, in which C indicates t cycle threshold, the fractional cycle number where the fluorescent signal reaches the detection threshold (Livak & Schmittgen, 2001). YKT6 was used as internal control and commercially available human total reference RNA (Clontech Laboratories, Mountain View, CA, USA) as reference RNA.

Experimental procedures

Study population

The individuals investigated in this study are participants of the LLS. The families participating in this study have at least two siblings with a minimum age for men of 89 years and for women of 91 years (Schoenmaker et al., 2006). The offspring of these long-lived individuals, who have an increased potential to become long-lived individuals (30% reduced standardized mortality rate) were also included. In addition, the partners of the offspring were included as population controls of similar age and environmental exposures as the offspring and as a young control group for the nonagenarian siblings. Blood samples were taken from all the participants. The LLS was approved by the Medical Ethical Committee of Leiden University Medical Centre, and all participants gave written informed consent.

Geneset analysis of gene expression data

The Globaltest methodology was designed to determine whether the common expression pattern of genes within a pre-defined set is significantly related to clinical outcome (Goeman et al., 2004; Goeman et al., 2005). A generalized linear model is used to estimate a

several blood cell counts. In the whole blood samples of the participants, the following cell subtypes were counted using the automated Siemens ADVIA 1200 system (SMSD, Tarrytown, NY, USA) in the Leiden Medical Diagnostical Center: leucocytes, thrombocytes, neutrophils, lympho- cytes, monocytes, basophils and eosinophils. Both longevity-associated genes in middle-age were adjusted for each of these cell counts separately when associating with familial longevity, which analysis is described above.

‘Q-statistic’ for each gene set, which describes the correlation between gene expression profiles, X, and clinical outcomes, Y. The Q-statistic for a gene set is the average of the Q-statistics for each gene in the set. The Globaltest method was used to perform geneset analysis comparing two groups of individuals (either nonagenarians vs. controls or offspring vs. controls) including age (in offspring vs. controls only) and gender and their interaction as covariates. Global test package in R (Goeman & Oosting, 2011) has been used to perform analyses.

T-cell differentiation measurements

Single gene analysis of gene expression data