2.2 Genetic data
Genetic data analyzed in this work were collected in the frame of a project on the study of genetic determinants of human longevity, described in Soerensen et al. (2012b), where 148 genes (1,273 SNPs) belonging to three candidate pathways (GH/IGF-1/Insulin signaling, DNA damage signaling and repair, and pro-anti-oxidant pathways) were investigated in two cohorts of middle-aged and oldest old Danes. Briefly, candidate genes were chosen by integrating a comprehensive analysis of literature and database search. SNP selection was carried out through a dedicated protocol that takes into account both candidate SNPs for aging and age-related diseases in each analyzed pathway and coding or potentially functional SNPs (non-synonymous SNPs, SNPs located in potential splice sites or transcription factor binding sites, and SNPs potentially inducing frame shifts or nonsense-mediated mRNA decay). Finally, HAPMAP tagging SNPs were added to reasonably cover the genetic variability in the gene region. Supplementary Table 1S reports the complete list of the 311 SNPs relative to 38 genes belonging to the pro-anti-oxidant pathway analyzed1.356 0.543 rs4784701 NDUFS1 OXPHOS 5 2 1.260 0.588 rs11695633 0.204 0.998 rs6435326 2.236 0.242 rs6435324 NDUFV1 OXPHOS 1 11 9.613 0.005 rs12793832 4.422 0.079 rs12793832 0.178 0.893 rs12793832 PRDX3 ANTI 6 10 4.068 0.049 rs1553850 3.718 0.065 rs3740562 0.742 0.811 rs3377 SOD2 ANTI 5 6 1.264 0.615 rs5746136 0.812 0.840 rs5746151 4.553 0.012 rs2758331 TXNRD1 ANTI 15 
12 
1.779 
0.371 
rs4964778 
1.896 
0.308 
rs4964735 
2.257 
0.184 
rs7310505 UCP2 ANTI 
4 
11 
1.019 
0.685 
rs2632725 
1.093 
0.666 
rs659366 

1 

1 

2 

2 

2 

3 

3 

3 

UCP3 ANTI 

4 

11 

2.048 

0.285 

rs11235972 

0.990 

0.699 

rs647126 

2.566 

0.182 

rs11235972 UQCRFS1 OXPHOS 

4 

19 

4.115 

0.038 

rs759628 


2

4

4

 Association showing a significance below p b 0.05 are indicated in bold. Note: The prevalent effect of the different genes inside the pro-antioxidant metabolic pathway was reported. PRO: pro-oxidant; ANTI: anti-oxidant; OXPHOS: involved in mitochondrial oxidative phosphorylation. 

Samples with a call fraction lower than 90% were excluded at the level of functional status, and SNPs were excluded if they had a missing frequency (MiF) higher than 10% or a frequency of rare allele (MAF) less than 1%. 

2.4.2. Single-SNP analysis 

The association between the analyzed genetic variants and the quantitative/dichotomous traits was assessed using linear/logistic regression models, ANOVA, and likelihood ratio tests as appropriate to assess the significance of the resulting associations. Since for each SNP three different coding schemes were adopted (dominant, recessive, and additive), the significance of the association was summarized with the MAX statistic approach used in Li et al. (2008). A complete description of this procedure is reported in the Supplementary material (see Statistical Appendix). 

For MMSE, three strong associations were found related to the NDUFV1 gene (p = 0.005), the MT1A gene (p = 0.006), and the GSTP1 gene (p = 0.009), all having a favorable effect on cognitive functioning at single SNP level. Less significant but still under the nominal level were the associations with MMSE levels of UQCRFS1 gene (p = 0.038) and GLRX (p = 0.041). A borderline association with WS performance was detected for TXNRD1 gene too (p = 0.053), which was also associated with ADL levels in this cohort.

The association between genetic variants and survival time was carried out with Cox regression models instead of linear and logistic models to better capture the idiosyncrasies of the survival outcome (see Statistical Appendix). Finally, no gene found associated with a functional phenotype showed a corresponding association with survival. However, two nominally significant associations with survival have been found in the whole sample in relation to LOX (p = 0.013), SOD2 (p = 0.012), and UQCRFS1 (p = 0.038) genes, whose variability was found to positively (LOX) and negatively (SOD2, UQCRFS1) influence the survival at gene level in this Cohort. TXNRD1, although showing a significant association with survival at SNP level (see Supplementary Table 2S_2), was not found associated with survival at gene level in the whole sample.

For each analyzed gene, the gene-based analysis was carried out using the following algorithm: perform single SNP association analysis as described before; compute the gene-based statistic as the average of these single SNP statistics; permute the dataset of times, keeping LD between SNPs constant (i.e., permute phenotype labels); for each0.039 HG GLRX rs6556884 5.750 0.001 UCP3 rs11235972 6.619 0.002 UCP2 rs7109266 5.650 0.008 NOX1 rs5921669 3.752 0.024 WS SOD2 rs2842980 5.103 0.005 GCLC rs2100375 4.159 0.007 MMSE MT1A rs4784701 7.717 0.002 CCS ACOX1 rs8065144 3.176 0.046 NOS3 rs2853792 3.471 0.023 Survival NDUFS1 rs6435324 5.115 0.009 SOD2 rs911847 3.715 0.035 TXNRD1 rs10861169 3.587 0.024 UCP3 rs11235972 4.004 0.041 

In this work, with the aim of investigating the possible pro-antioxidant pathway to functional status at old age, we tested the association of genes belonging to pro- and anti-oxidant pathways with predictors of physical (HG, ADL, and WS) and cognitive decline (MMSE and CCS) at old age in a cohort of Danish nonagenarians. Few studies have investigated the genetic variations influencing physical abilities at old age, and samples were mainly drawn from hospitalized and affected patients.

Positive association was reported between ADL levels and ACE gene by Seripa et al., (2011), while no correlation was found with APOE gene by Kulminski et al., (2008) and Bader et al., (1998), the latter in a cohort of 253 healthy and disabled Italian octo- and nonagenarians.