RESEARCH ARTICLE

Population-specific association of genes for telomere-associated proteins with longevity in an Italian population

Paolina Crocco • Roberto Barale • Giuseppina Rose • Cosmeri Rizzato •

Aurelia Santoro • Francesco De Rango • Maura Carrai • Paola Fogar •

Daniela Monti • Fiammetta Biondi • Laura Bucci • Rita Ostan • Federica Tallaro •

Alberto Montesanto • Carlo-Federico Zambon • Claudio Franceschi •

Federico Canzian • Giuseppe Passarino • Daniele Campa

Received: 12 December 2014 / Accepted: 13 January 2015 / Published online: 29 January 2015

� Springer Science+Business Media Dordrecht 2015

Abstract Leukocyte telomere length (LTL) has

been observed to be hereditable and correlated with

longevity. However, contrasting results have been

reported in different populations on the value of LTL

heritability and on how biology of telomeres influ-

ences longevity. We investigated whether the vari-

ability of genes correlated to telomere maintenance is

associated with telomere length and affects longevity

in a population from Southern Italy (20–106 years).

For this purpose we analyzed thirty-one polymor-

phisms in eight telomerase-associated genes of which

twelve in the genes coding for the core enzyme (TERT

and TERC) and the remaining in genes coding for

components of the telomerase complex (TERF1,

TERF2, TERF2IP, TNKS, TNKS2 and TEP1). We

did not observe (after correcting for multiple testing)

statistically significant associations between SNPs and

LTL, possibly suggesting a low genetic influence of

the variability of these genes on LTL in the elderly. On

the other hand, we found that the variability of genes

encoding for TERF1 and TNKS2, not directly involved

in LTL, but important for keeping the integrity of the

structure, shows a significant association with longev-

ity. This suggests that the maintenance of these

chromosomal structures may be critically important

for preventing, or delaying, senescence and aging.

Such a correlation was not observed in a population

from northern Italy that we used as an independent

replication set. This discrepancy is in line with

Paolina Crocco, Roberto Barale, Giuseppe Passarino and

Daniele Campa have equally contributed to the study.

Electronic supplementary material The online version ofthis article (doi:10.1007/s10522-015-9551-6) contains supple-mentary material, which is available to authorized users.

P. Crocco � G. Rose � F. De Rango �F. Tallaro � A. Montesanto � G. Passarino (&)

Department of Biology, Ecology and Earth Science,

University of Calabria, 87036 Rende, Italy

e-mail: g.passarino@unical.it

R. Barale � M. Carrai � D. Campa (&)

Department of Biology, University of Pisa, 56126 Pisa,

Italy

e-mail: daniele.campa@unipi.it

C. Rizzato � F. CanzianGenomic Epidemiology Group, German Cancer Research

Center (DKFZ), 69120 Heidelberg, Germany

A. Santoro � F. Biondi � R. Ostan � C. FranceschiDepartment of Experimental, Diagnostic and Specialty

Medicine (DIMES), University of Bologna, Bologna, Italy

P. Fogar � C.-F. Zambon

Department of Medicine-DIMED, University of Padova,

Padua, Italy

D. Monti

Department of Experimental and Clinical Biomedical

Sciences, University of Florence, Florence, Italy

123

Biogerontology (2015) 16:353–364

DOI 10.1007/s10522-015-9551-6

previous reports regarding both the population spec-

ificity of results on telomere biology and the differ-

ences of aging in northern and southern Italy.

Keywords Gene variability � Aging � Telomere �Telomerase

Introduction

The search for the molecular basis of longevity has

highlighted the importance that mechanisms

involved in cell maintenance play in determining

cellular senescence and, consequently, lifespan in

both model organisms and humans (Kirkwood and

Shanley 2005; Ovadya and Krizhanovsky 2014). This

observation has prompted many researchers to ana-

lyze the variability of genes involved in cell main-

tenance processes to find out its role in human

longevity. Indeed, a number of genetic variants

involved in these mechanisms have been found to

be associated with longevity (Yashin et al. 2012;

Yuan et al. 2013).

Among the maintenance mechanisms possibly

involved with senescence and life span, telomere

length (TL) maintenance is certainly one of the most

widely studied (Kim Sh et al. 2002; Bischoff et al.

2005; Vasa-Nicotera et al. 2005; von Zglinicki and

Martin-Ruiz 2005; Kappei and Londono-Vallejo

2008). Telomeres are specialized structures made of

a series of tandem repeats, highly conserved through-

out eukaryotic evolution, that protect chromosomes

from degradation. In humans they consist of a six-base

repeat (TTAGGG) and their length ranges between 0.5

and 15 kb. It is well known that in most proliferating

tissues, in each cell division, human telomeres

decrease in length (usually 50–200 base pairs) up to

a critical point that leads the cell to a replicative

senescence (Wong and Collins 2003; Campisi and

d’Adda di Fagagna 2007). An inverse correlation

between TL and age emerges from literature, although

this correlation is influenced by ethnicity and gender,

with women showing longer telomeres than males

(Diez Roux et al. 2009; Muezzinler et al. 2013;

Gardner et al. 2014). In addition, it has been often

reported that the rate of telomere shortening is variable

within the elderly population and that this is associated

with metabolic decline, increased risk for age-related

diseases and death (Finch 2007; Njajou et al. 2007).

TL is then considered a biomarker of age-related

physical decline and of survival expectation (Kim Sh

et al. 2002; Panossian et al. 2003; Benetos et al. 2004;

Brouilette et al. 2007).

Telomerases are part of a specialized ribonucleo-

protein complex that adds the telomere repeats to the

ends of chromosomes. They contain a reverse trans-

criptase (TERT) and a catalytic RNA (TERC) that

provides the template for nucleotide addition (Bodnar

et al. 1998). It has been demonstrated that lack of

telomerase activity is associated with telomere short-

ening and that, in humans, expression of TERT is a

limiting factor for telomerase function. In fact, Blasco

(2005) demonstrated that if TERC is normally present

while TERT gene is down regulated, the telomerase

activity in most normal somatic cells is destroyed.

Interestingly, ectopic telomerase expression prevents

telomere shortening-dependent replicative senescence

in primary fibroblast cells and extends their lifespan

(Vaziri and Benchimol 1998; Shay and Wright 2007).

TL is a quantitative trait and it has an estimated

heritability that varies, in different studies, from 35 to

80 % (Bischoff et al. 2005; Vasa-Nicotera et al. 2005).

Genome-wide association studies (GWAS), as well as

candidate gene approaches and meta-analyses,

reported contrasting results on the possible association

between the variability of numerous genes and leuko-

cyte telomere length (LTL), which data from human

studies showed to be strongly correlated with the rates

of telomere shortening in different tissues (Daniali

et al. 2013; Ren et al. 2009). In addition to TERC and

TERT, directly involved in the elongation process, to

date several genes have been identified as involved in

maintaining the integrity of telomeres and TL. They

include CTC1, ZNF676 and OBFC1 (Hartmann et al.

2009; Mangino et al. 2009; Atzmon et al. 2010; Codd

et al. 2010; Levy et al. 2010; Soerensen et al. 2012).

However, as for other genes, a population specificity

of these associations emerges from published

L. Bucci

Department of Medical Surgical Sciences, Medical

Semiotics Unit, Alma Mater Studiorum – University of

Bologna, Bologna, Italy

D. Campa

Division of Cancer Epidemiology, German Cancer

Research Center (DKFZ), 69120 Heidelberg, Germany

354 Biogerontology (2015) 16:353–364

123

literature. Indeed, not all these associations have been

successfully replicated, highlighting the importance of

confounding factors such as gender and ethnicity.

Recently, a new GWAS brought up new genes

associated with TL, while it found that some of the

genes previously reported to be associated with TL,

showed only a nominal (p\ 0.05) association (Lee

et al. 2014).

On the basis of these contrasting results we

investigated whether the variability of thirty-one

polymorphisms in some genes involved in telomere

biology is associated with TL in leucocytes and human

longevity in a population from Southern Italy, which

has previously shown peculiar features regarding the

demography and the genetics of the elderly population

and of the long lived subjects.

Given the population specificity of genetic variants

associated with telomeres previously analyzed, we

replicated significant results in a northern Italian

population, in order to evaluate whether our results

could be generalized. In particular, we analyzed,

together with the TERC and TERT, some of the genes

which are not directly involved in telomere elongation

but are essential for telomere stability and structure

(Kaminker et al. 2001; Xin et al. 2008). Among these,

TEP1 specifically interacts with the telomerase RNA;

TERF1, TERF2 and TERF2IP are located in the

shelterin-complex that protects the telomeres from

degradation and inappropriate DNA repair, prevents

end-to-end fusion, atypical recombination, and pre-

mature senescence; TNKS and TNKS2 are other

important telomere-associated proteins associated

with telomeric DNA.

Materials and methods

The population analyzed in the present study included

985 subjects (509 females and 476 males) whose ages

ranged from 20 to 106 years. Blood samples of the

study participants were collected during the period

1996–2004, and DNA was extracted from buffy coat

and stored in our laboratory. The recruitment of

centenarians (identified through the birth registers of

the 409 municipalities of Calabria) started on 1996,

while the remaining subjects were recruited by an

appropriate campaign launched in 1999 and concluded

within 2 years. The recruitment campaign was

focused on students and staff of the University of

Calabria (20–60 year old subjects), people visiting

thermal baths in the area and the Academy of the

Elderly (60–80 year old subjects). All subjects were of

Calabrian origin up to their grandparents. The differ-

ent campaigns were approved by the relevant ethical

committees of the University of Calabria. All subjects

consented (by a written informed consent) to their

phenotypic and genetic data to be used anonymously

for genetic studies on aging and longevity.

The analyses were carried out by dividing the

sample in three specific age classes obtained according

to the survival function of the Italian population from

1890 onward (Passarino et al. 2006). The two age

‘‘thresholds’’ used to define these age classes were 66

and 88 years for men and 73 and 91 years for women.

In particular, group 1 (G1) included males younger

than 66 years and females less than 73 years of age

(N = 324); group 2 (G2) males aged 66–88 years and

females aged 73–91 years (N = 387), and group 3

(G3) comprised males older than 88 years and females

over 91 years of age (N = 274).

A replication sample included 788 subjects (376

females and 412 males) from Northern Italy whose

ages ranged between 33 and 111 years. Also in the

case of the replication sample, the analyses were

carried out by dividing the sample according to two

age ‘‘thresholds’’ previously defined (G1 N = 231;

G2 N = 398; G3 N = 232). 530 Caucasian subjects

(235 females and 295 males) whose ages ranged

between 33 and 94 years, all with Veneto descent,

were recruited at the University Hospital of Padova

from April to December 2008. DNA was extracted

from a whole-blood sample obtained from each patient

at enrolment. Fully informed consent was obtained in

writing from all the participants, and the study was

approved by the Local Ethics Committee. 258 subjects

(177 females and 81 males) whose ages ranged from

50 to 111 years, living in Northern and Central Italy,

were enrolled at University of Bologna and Florence.

Subjects were recruited through local advertisements

and the Register Office. The participants’ age were

defined by birth certificates or dates of birth as stated

on passports or identity cards. The study protocol was

approved by the Ethical Committee of the Sant’Orso-

la-Malpighi University Hospital (Bologna, Italy) and

from all participants written informed consent was

obtained. Blood samples were collected during the

period 2007–2010 and DNAwas extracted fromwhole

blood samples and adequately stored.

Biogerontology (2015) 16:353–364 355

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SNP selection

We focused on a group of eight genes (Telomerase

RNA Component TERC, Telomerase Reverse Trans-

criptase TERT, Telomeric Repeat-Binding Factor 1

TERF1, Telomeric Repeat-Binding Factor 2 TERF2,

TERF2-Interacting Protein TERF2IP, TRF1-Interact-

ing Ankyrin-Related ADP-Ribose Polymerase TNKS,

TRF1-Interacting Ankyrin-Related ADP-Ribose Poly-

merase 2 TNKS2 and Telomerase-Associated Protein 1

TEP1) which are either directly or indirectly involved

in telomere elongation or are telomere binding

proteins necessary for telomere stability and for

maintaining of telomere structure.

To select the maximally informative set of tag

SNPs within these genes we used the algorithm

described by Carlson and co-workers (Carlson et al.

2004). Polymorphisms with a minor allele frequency

(MAF) higher than 0.05 in Caucasians from the

International HapMap Project (version 24 http://www.

hapmap.org) were included in order to cover 90 % of

the genetic variability of the loci. Tagging SNPs were

selected with the use of the Tagger program within

Haploview (http://www.broad.mit.edu/mpg/haploview/;

http://www.broad.mit.edu/mpg/tagger/) (Barrett et al.

2005; de Bakker et al. 2005) using pairwise tagging

with a minimum r2 value of 0.8. Polymorphisms

within the other telomerase associated genes were

selected from literature data and using information on

allele frequency, position, and functional effects. The

selected SNPs are reported in Table 1. At the end of

the process we had a list of 31 polymorphic sites.

Genotyping

Genotyping was carried out using the Kaspar

(Kbioscience, Hoddesdon, UK) or Taqman (Applied

Biosystems, Foster City, CA, USA) assay according

to manufacturer’s instructions. The order of DNAs

was randomized on PCR plates. PCR plates were

read on an ABI PRISM 7900HT instrument

(Applied Biosystems).

Quality control

Approximately 8 % of the samples were analyzed in

duplicate, and the concordance rate of the genotypes

was higher than 99 %. No SNPs showed a significant

deviation from Hardy–Weinberg equilibrium (HWE,

p\ 0.001) in the control group (that is the group not

selected for longevity, G1).

Telomere length

A subgroup of 457 (46.4 %) randomly selected

subjects from Calabria was used to evaluate the

correlation between the analyzed polymorphisms and

the TL. The average length of telomeres was measured

by Real-Time PCR quantitative analysis (qPCR), by

using the MiniOpticon Monitor Real Time PCR

System (Bio-Rad, 48-wells format). This method

allows to measure the number of copies of telomeric

repeats compared to a single copy gene, used as a

quantitative control (Cawthon 2002). We used the

modified protocol described by Testa and colleagues

(2011). The telomere and single-copy gene (36B4)

were analysed on the same plate in order to reduce

inter-assay variability. For the PCR reaction, 5 ll ofDNA with a concentration of 3 ng/ll (15 ng in total)

and 15 ll of mix (containing the specific primers for

telomeres (T) and control gene (S), the PCR reagents

and the SYBR green dye for the detection of the

fluorescence) was added in each well. Concentrations

for telomere and 36B4 PCR primers sequences and the

thermal cycling profile were used as reported by Testa

and co-workers (2011). In addition, two standard

curves (one for 36B4 and one for telomere reactions)

were prepared for each plate by using a reference DNA

sample (Roche, Milano, Italy) diluted in series (dilu-

tion factor 1.68), in order to produce 5 concentrations

of DNA ranging from 30 to 2 ng in 5 ll and a

calibrator sample (Roche, Milano, Italy) (3 ng/ul in

5 ll). Measurements were performed in triplicate and

reported as T/S ratio relative to the calibrator sample

to allow comparison across runs.

Genetic and statistical analyses

Descriptive statistics and explanatory data analysis

includingmissing values analysis, calculation of HWE

and the pairwise measures of linkage disequilibrium

(LD) between the analyzed loci were carried out using

SNPassoc package version 1.8-4 of R 2.15.1 (Gon-

zalez et al. 2007).

In the present study generalized linear models were

used, as appropriate, to estimate how the variability of

analyzed genes influences both the TL and the

predisposition to human longevity. Age and indicator

356 Biogerontology (2015) 16:353–364

123

of gender were used as covariates in the regression

models used to test for a correlation between the

analyzed polymorphisms and TL. In order to estimate

if the probability to be assigned to the different age

classes could be related to these genetic variants, we

compared G1 with G2 group (model 1), G1 with G3

group (model 2), and G2 with G3 group (model 3)

using sex as covariate.

In order to visually synthesize the association

results obtained in the present study the synthesis-

view software was used (Pendergrass et al. 2010).

Correction for multiple testing was carried out

using the Bonferroni method. Since 31 SNPs were

analyzed, the adjusted significance level was set to

0.0016 (0.05/31).

Results

Table 2 reports the socio-demographic characteristics

of the study population analyzed according to age

groups defined in the Materials and Methods section.

As expected, we found a very strong inverse correla-

tion between age and TL (p\ 0.001), while no

correlation between gender and TL was observed

(p = 0.914).

Table 1 Polymorphisms

falling within or close to

genes associated with

telomere functions selected

for the analysis

Gene rs SNP variation Chr Hap map position

TERC rs12696304 C/G 3 170963965

TERT rs10078761 T/A 5 1302594

rs2853691 T/C 5 1305950

rs2736122 G/A 5 1310621

rs2075786 G/A 5 1319310

rs4246742 T/A 5 1320356

rs4975605 C/A 5 1328528

rs2242652 G/A 5 1333028

rs2736100 G/T 5 1339516

rs2853676 C/T 5 1341547

rs2736098 C/T 5 1347086

rs2853669 T/C 5 1348349

TNKS rs6990097 T/C 8 9450267

TERF1 rs2929586 A/G 8 74087966

rs2975842 C/T 8 74088145

rs12334686 G/A 8 74099005

rs6982126 C/T 8 74102177

rs10107605 A/C 8 74104911

rs12335203 T/C 8 74116173

rs7845139 G/A 8 74124181

TNKS2 rs2066276 T/C 10 93547599

rs10509637 A/G 10 93577712

TEP1 rs938886 C/G 14 19907541

rs1760904 T/C 14 19921869

rs1760897 T/C 14 19946093

rs1760890 T/G 14 19951629

rs4246977 A/G 14 19952431

TERF2 rs3785074 T/C 16 67964487

TERF2IP rs3784929 A/G 16 74234528

rs2233807 C/T 16 74238769

rs11639771 C/T 16 74249153

Biogerontology (2015) 16:353–364 357

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Table 3 reports the polymorphisms associated with

TL at the nominal threshold of 0.05. Table 1S shows

the complete list of the association of results between

TL and the analyzed polymorphisms.

After adjusting for multiple comparisons

(p\ 0.0016), we did not observe any significant

association between genetic variability in the selected

polymorphisms and TL. The strongest association was

detected for rs2736100-T allele of the TERT gene and

shorter TL (p = 0.010).

Association of telomere gene variability

and longevity

Supplementary Table 2S shows the complete list of

the association results obtained comparing G2 (sub-

jects of intermediate age) with G1 group (youngest

subjects), G3 (oldest subjects) with G1 group, and G3

with G2 group (models 1, 2 and 3, respectively; for

details see Materials and Methods section). Table 4

reports the polymorphisms which showed a nominally

significant association (p\ 0.05) in at least one

comparison.

When we analyzed model 1 (G2 vs G1), using for

each SNP the most frequent homozygous genotype as

reference and after adjusting for multiple testing, we

found that rs12335203-C allele of the TERF1 gene

positively influenced the probability to be part of the

older group (OR = 1.50, p = 6.17 9 10-4).

No other statistically significant association was

observed to hold multiple testing correction, although

in model 2 rs2066276 in TNKS2 was close to be

significantly associated with longevity (OR = 0.71,

p = 0.006). This polymorphism and the rs10509637

(in weak LD each other r2 = 0,131; see Fig. 1),

influenced the probability to be part of the oldest group

also in model 3 (G3 vs G2; OR = 0.68 p = 0.002 and

OR = 1.53, p = 0.009, respectively).

Figure 1 shows the association results including

both SNP locations and r2 values in the Haploview

style format.

In order to validate our findings the SNPs that were

significantly associated at a nominal level with

longevity (p\ 0.05) in the population from Calabria

were tested in an additional northern Italian sample.

Table 5 reports the association results obtained in the

Table 2 Characteristics of

the age groups included in

the study

95 % confidence interval

(CI)

Group 1 (G1) Group 2 (G2) Group 3 (G3) Total

N 324 387 274 985

% Males 39.81 48.58 58.02 48.32

Age

Median 47 78 96 77

95 % CI 44–49 77–80 95–97 75–79

Telomere length

Median 1.005 0.729 0.462 0.661

95 % CI 0.802–1.189 0.671–0.809 0.413–0.512 0.625–0.701

Table 3 Polymorphisms associated with the telomere length (p\ 0.05)

SNP Gene Chr Position in the genome Mean difference 95 % CI p value

rs2736100 TERT 5 1339516 -0.1418 -0.2485 to 0.0350 0.010

rs11639771 TERF2IP 16 74249153 0.1732 0.0253 to 0.3211 0.022

rs3784929 TERF2IP 16 74234528 -0.1888 -0.3544 to 0.0233 0.026

rs10107605 TERF1 8 74104911 -0.1403 -0.2702 to 0.0105 0.035

rs12696304 TERC 3 170963965 -0.1132 -0.2264 to 2.65E-05 0.051

The complete list of the analyzed polymorphisms and their association with telomere length is reported in Supplementary Material

(Table 1S)

For each SNP, mean difference, adjusted for covariates, and its 95 % confidence interval (CI) among the observed genotypes is

displayed. The most frequent homozygous genotype was considered as the reference category assuming a log-additive model of

inheritance

358 Biogerontology (2015) 16:353–364

123

replication samples comparing G2 with G1 group, G3

with G1 group, and G3with G2 group (models 1, 2 and

3, respectively). We found that, except for a borderline

association between rs12696304 and longevity

detected in the G1 versus G3 comparison, no associ-

ation could be successfully replicated in the northern

Italian sample.

Discussion

The role of the telomeres in the aging process has been

largely discussed in literature. TL is associated with

age-related diseases (coronary heart disease, hyper-

tension, dementia, insulin resistance, obesity and

cancer) (Aviv et al. 2006; Armanios 2013; Codd

et al. 2013; Campa et al. 2015) and it is known that

oxidative stress and inflammation accelerate telomere

shortening (von Zglinicki and Martin-Ruiz 2005;

Finch 2007; Babizhayev et al. 2011; Kiecolt-Glaser

et al. 2013). Several genes, as well as several

environmental factors, are involved in the mechanism

of telomere elongation and stabilization. In the present

study we investigated whether genetic variation of

eight telomerase and telomere-associated genes

(TERC, TERT, TERF1, TERF2, TERF2IP, TNKS,

TNKS2 and TEP1) is associated with human longevity

by using a number of polymorphisms we selected

using HapMap data. The pairwise LD analyses

between the selected polymorphisms showed that, as

expected, most of them are independent with each

other (Fig. 1).

In this work we did not find any statistically

significant association between the genetic variability

of the selected polymorphisms and LTL considering

the correction for multiple testing. However we

observed some suggestive associations that were

significant at a nominal level of 0.05. In particular,

the minor alleles of rs2736100 of TERT gene

(p = 0.010), rs3784929 within TERF2IP gene

(p = 0.026), rs10107605, falling nearby TERF1, and

rs12696304 belonging to TERC (p = 0.051) were

associated with a decreased TL at the conventional

0.05 P value threshold. In addition, the minor allele of

rs11639771 of TERF2IP gene (p = 0.026) was found

to be correlated with longer telomeres. This result is in

line with previous studies showing a low correlation

between telomere-associated proteins and LTL, indi-

cating that the role of the variability of these genes on

TL is probably low and would need a larger sample to

be highlighted (Lee et al. 2014). It might also be

important to notice that the reduced variability of

telomere variance associated with age (due to survival

reduction for subjects harboring shorter telomeres, and

to cancer susceptibility for those with longer telo-

meres) makes even more difficult to find an associa-

tion between genetic variability of telomerase-

associated genes and LTL in population samples older

than 40 years of age (Halaschek-Wiener et al. 2008;

Broer et al. 2014).

Table 4 Polymorphisms correlated (p\ 0.05) with the individual chance to be part of the different age groups in pairwise

comparisons

SNP Gene Allele G1 versus G2 (model1) G1 versus G3 (model 2) G2 versus G3 (model 3)

OR 95 % CI p value OR 95 % CI p value OR 95 % CI p value

rs12696304 TERC C/G 1.02 0.81–1.29 0.856 0.75 0.57–0.99 0.044 0.75 0.58–0.97 0.027

rs4975605 TERT C/A 1.01 0.81–1.25 0.931 1.35 1.06–1.71 0.013 1.36 1.07–1.71 0.010

rs2242652 TERT G/A 1.17 0.91–1.51 0.221 0.78 0.57–1.07 0.125 0.69 0.51–0.93 0.013

rs2736100 TERT G/T 1.18 0.95–1.47 0.138 1.39 1.08–1.79 0.011 1.12 0.89–1.42 0.342

rs12335203 TERF1 T/C 1.50 1.19–1.89 0.001 1.23 0.95–1.59 0.120 0.87 0.68–1.12 0.279

rs2066276 TNKS2 T/C 1.03 0.83–1.28 0.803 0.71 0.55–0.91 0.006 0.68 0.53–0.87 0.002

rs10509637 TNKS2 A/G 1.02 0.74–1.41 0.885 1.54 1.11–2.13 0.010 1.53 1.11–2.09 0.009

The complete list of the association results is reported in Supplementary Material (Table 2S)

For each SNP, Odd Ratio (OR) and its 95 % confidence interval (CI) among the observed genotypes is displayed. The most frequent

homozygous genotype was considered as the reference category assuming a log-additive model of inheritance, thus the risk is referred

to the minor allele

Biogerontology (2015) 16:353–364 359

123

Fig. 1 Results of the genetic association tests obtained in the

analyzed sample comparing G2 with G1 group (blue), G3 with

G2 group (yellow), and G3 with G1 group (red) including both

SNP locations and r2 values in the Haploview style format. (G1–

G3 refer to age groups: G1males\66 years; females\73 years.

G2 males[66 and\88; female[73 and\91. G3 males[88;

females[91). In the same plot the association results with the

telomere length in a subgroup of 457 (46.4 %) randomly

selected subjects from the analyzed sample were also reported

(violet). Triangles indicate the direction of the genetic effect

(association)

360 Biogerontology (2015) 16:353–364

123

As to the correlation with life span, we found that

rs12335203, a polymorphic variant of the TERF1

gene, was associated with longevity also after adjust-

ing for multiple comparisons (Bonferroni correction).

Additionally, two polymorphic variants, rs2066276

and rs10509637 of the TNKS2 gene, were near this

stringent threshold of significance. It might be worth

mentioning that a number of studies in model organ-

isms have shown that TERF1 is not essential for TL

but is crucial for telomere protection and that TNKS2

closely interacts with TERF1 (Martinez et al. 2010).

In the replication sample we found that except for a

borderline association between rs12696304 and lon-

gevity detected in the G1 versus G3 comparison, no

association could be successfully replicated in the

northern Italian sample (Table 5). The lack of repli-

cation for the association between genetic variability

of telomere-associated proteins with longevity in a

northern Italian population, in spite of the high

significance found in the southern Italian sample,

suggests (in line with previous data) that such an

influence is population-specific (Tan et al. 2001;

Muezzinler et al. 2013). It might be of interest to

notice on this point, that TL is correlated between

spouses, and that the longer the spouses have lived

together the higher is such correlation (Broer et al.

2013). This shows the importance of environment on

telomere biology; thus our results may be correlated to

the specificity of the Southern Italian elderly popula-

tion. Indeed, Calabrian aging population has previ-

ously been characterized for some peculiar features

(Montesanto et al. 2008; De Rango et al. 2010). In

particular, in the Calabrian population it has been

reported an average male female ratio among long

lived subjects of 1:2, with some areas with a 1:1 ratio

(Montesanto et al. 2008) while in northern Italy, as in

most US and European populations a 1:4–1:5 ratio can

be observed. This may be of interest, considering that,

as we mentioned, we did not observe any difference in

LTL between males and females, and a similar result

had previously been observed among the Amish

population where the male/female ratio among long

lived subjects is 1/1 (Njajou et al. 2007). These data

suggest that the longer telomeres observed among

females in most of the populations studied may be

correlated to the different life expectancy in the two

genders, which in turn is population-specific and

correlated to the environmental and demographic

factors (Guralnik et al. 2000). Thus, we may expect

population-specific results because of different envi-

ronmental factors influencing TL. On the whole, our

findings highlight the importance that the telomere-

associated protein machinery plays in the context of

cell maintenance in a complex, and still to be

elucidated, interaction with environment. In fact, this

machinery, by capping telomere ends, affects the

protection of DNA from damages, the regulation of

chromatin architecture and, finally, gene expression

(Cong and Shay 2008). Indeed, it has been reported

that a disarrangement of telomere complex has

important effects on the cell tendency to senescence

(Stewart and Weinberg 2006; Martınez et al. 2009;

Martınez and Blasco 2011).

Moreover, our results suggest that the variability of

the genes coding for proteins involved in protecting

the integrity of telomere structures, more than the

variability of those directly involved in telomere

elongation, is correlated with longevity. Thus, the

Table 5 Polymorphisms affecting age-group membership in the three pairwise comparisons in the replication sample

SNP Risk allele G1 versus G2 G1 versus G3 G2 versus G3

OR 95 % CI p value OR 95 % CI p value OR 95 % CI p value

rs12696304 G 0.856 0.657–1.115 0.248 0.733 0.520–1.035 0.077 0.877 0.628–1.225 0.441

rs2242652 A 1.060 0.782–1.437 0.705 1.037 0.713–1.508 0.850 0.874 0.607–1.258 0.468

rs2736100 T 0.925 0.708–1.208 0.567 0.782 0.576–1.062 0.115 0.856 0.633–1.158 0.314

rs12335203 T 1.037 0.821–1.311 0.760 1.067 0.799–1.427 0.660 1.006 0.760–1.333 0.964

rs2066276 C 1.124 0.883–1.430 0.343 0.961 0.714–1.295 0.795 0.904 0.671–1.217 0.505

rs10509637 G 1.143 0.823–1.586 0.425 1.077 0.710–1.634 0.726 0.974 0.675–1.405 0.887

Groups are defined in Materials and Methods

For each SNP, Odd Ratio (OR) and its 95 % confidence interval (CI) among the observed genotypes is displayed. The most frequent

homozygous genotype was considered as the reference category assuming a log-additive model of inheritance

Biogerontology (2015) 16:353–364 361

123

variability of genes involved in telomere elongation

(in particular TERC and TERT) seems to have a low

influence on the maintenance of TL with respect to

environmental factors (such as ethnicity), or with

respect to the original length. It might be worth noting

that different recent studies in model organisms and

humans have reported that TL works as a lifespan

predictor mainly at young ages, while was not

predictive for mortality in the oldest old subjects

(Martin-Ruiz et al. 2005; Heidinger et al. 2012). TL in

the elderly (at least in blood cells) might then be a

mirror of age related cell senescence rather than an

independent predictor of mortality (Cawthon et al.

2003). Finally the previously mentioned effects of

longer telomeres (and of alleles favoring longer

telomeres) on cancer (Jones et al. 2012; Melin et al.

2012; Yin et al. 2012; Lan et al. 2013) may also play a

role in our findings. On the other hand, the reported

capacity of exogen TERT of rescuing the TL and tissue

senescence, without promoting cancer (Bernardes de

Jesus et al. 2012), suggests caution and that additional

studies are necessary before drawing any conclusion.

As to the limitations of this study, we need to

highlight that: (i) several proteins belonging to telome-

rase complex (shelterin) were not analyzed in the

present study. As our results have suggested the

importance of this complex for longevity, additional

studies will need to elucidate the role of the genetic

variability of the shelterin-associated proteins in delay-

ing aging; (ii) the cross-sectional nature of the study

limits the generalization of the findings here reported.

However, since we paid particular attention to the

quality of the sampling, the false-positive results due to

population stratification are limited. In any case, it is

evident that additional functional studies are necessary

to better understand the role of different proteins inLTL,

and to understand how environmental factors may

influence the population specificity of the results.

In conclusion, we found that the variability of the

genes encoding for TERF1 and TNKS2 shows a

promising, population specific, association with

human longevity in our population. This suggests that

the maintenance of these chromosomal structures is

critically important for preventing, or delaying, senes-

cence and aging.

Acknowledgments This work was partially supported by the

European Union’s Seventh Framework Programme (FP7/

2007–2011) [grant number 259679] and by funds from

Programma Operativo Nazionale [01_00937]—MIUR

‘‘Modelli sperimentali biotecnologici integrati per lo sviluppo

e la selezione di molecole di interesse per la salute dell’uomo’’.

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