Skip to content

Advertisement

You're viewing the new version of our site. Please leave us feedback.

Learn more

BMC Genomics

Open Access

Epistasis, physical capacity-related genes and exceptional longevity: FNDC5 gene interactions with candidate genes FOXOA3 and APOE

  • Noriyuki Fuku1Email author,
  • Roberto Díaz-Peña2, 3,
  • Yasumichi Arai4,
  • Yukiko Abe4,
  • Hirofumi Zempo1,
  • Hisashi Naito1,
  • Haruka Murakami5,
  • Motohiko Miyachi5,
  • Carlos Spuch6,
  • José A. Serra-Rexach8,
  • Enzo Emanuele7,
  • Nobuyoshi Hirose1 and
  • Alejandro Lucia9
Contributed equally
BMC Genomics201718(Suppl 8):803

https://doi.org/10.1186/s12864-017-4194-4

Published: 14 November 2017

Abstract

Background

Forkhead box O3A (FOXOA3) and apolipoprotein E (APOE) are arguably the strongest gene candidates to influence human exceptional longevity (EL, i.e., being a centenarian), but inconsistency exists among cohorts. Epistasis, defined as the effect of one locus being dependent on the presence of ‘modifier genes’, may contribute to explain the missing heritability of complex phenotypes such as EL. We assessed the potential association of epistasis among candidate polymorphisms related to physical capacity, as well as antioxidant defense and cardiometabolic traits, and EL in the Japanese population. A total of 1565 individuals were studied, subdivided into 822 middle-aged controls and 743 centenarians.

Results

We found a FOXOA3 rs2802292 T-allele-dependent association of fibronectin type III domain-containing 5 (FDNC5) rs16835198 with EL: the frequency of carriers of the FOXOA3 rs2802292 T-allele among individuals with the rs16835198 GG genotype was significantly higher in cases than in controls (P < 0.05). On the other hand, among non-carriers of the APOE ‘risk’ ε4-allele, the frequency of the FDNC5 rs16835198 G-allele was higher in cases than in controls (48.4% vs. 43.6%, P < 0.05). Among carriers of the ‘non-risk’ APOE ε2-allele, the frequency of the rs16835198 G-allele was higher in cases than in controls (49% vs. 37.3%, P < 0.05).

Conclusions

The association of FDNC5 rs16835198 with EL seems to depend on the presence of the FOXOA3 rs2802292 T-allele and we report a novel association between FNDC5 rs16835198 stratified by the presence of the APOE ε2/ε4-allele and EL. More research on ‘gene*gene’ and ‘gene*environment’ effects is needed in the field of EL.

Keywords

Exceptional longevityCentenariansFOXO3AFNDC5APOEAgeing

Background

Exceptional longevity (EL), defined as reaching 100+ years of age, is a generally accepted model of healthy aging with major age-related diseases usually delayed [1], and sometimes even avoided, in centenarians [2]. Age at death during adulthood has a heritability of ~ 25% [3] and consequently EL is likely to be, at least in part, a heritable phenotype. However, genome wide association studies (GWAS) of individuals with EL have mostly yielded poor results, with single nucleotide polymorphisms (SNPs) in the apolipoprotein E (APOE) and/or forkhead box O3A (FOXOA3) genes being usually the only variants achieving genome-wide significance [3], although there is no unanimity for FOXOA3 [4]. The APOE ε4-allele, which is linked to a higher risk of cardiovascular and Alzheimer’s disease [5, 6], is associated with a lower likelihood of reaching EL, whereas the ε2-allele seems to show a positive association with EL and is more frequently found in centenarians than in younger controls [7]. Nonetheless, the aforementioned associations can vary by population [7]. Similarly, there is evidence that genetic polymorphisms in the FOXO3A gene can be associated with EL, especially the rs2802292 SNP [812], but such an association has not been corroborated in some cohorts [13, 14]. On the other hand, aging is inevitably associated with a decline physical function, especially in muscle mass and function (i.e., sarcopenia), with an acceleration of this process increasing the risk of mortality [15]. As such, there is a rationale for postulating the potential influence on EL of several variations in genes that are candidates to influence physical capacity and muscle function; however, up to date such candidate genes [e.g., α-actinin-3 (ACTN3), thyrotropin-releasing hormone (TRHR) or acyl-CoA synthetase long-chain family member 1 (ACSL1)], have not shown individual associations with EL [16, 17].

Epistasis, defined as the effect of one locus on a given phenotype being dependent on the presence of one or more ‘modifier genes’, may contribute to explain the missing heritability of complex phenotypes [18]. Though research on the role of epistasis in EL has been rather limited in the past [19], evidence for an impact of genetic interactions in determining human longevity is quickly growing. For instance, longevity may be partly determined by epistatic interactions involving mitochondrial DNA (mtDNA) loci [20]. Also, a combination of functional SNPs within adenosine deaminase (ADA) and tumor necrosis factor alpha (TNF-α) genes can influence life-expectancy in a gender-specific manner [21]. More recently, Tan et al. reported that interactions of SNPs in the FOXO gene family influences longevity [22]. To our knowledge, only two studies have included the APOE gene for evaluating gene x gene effects on longevity [23, 24]. Jazwinski et al. reported that the GTPase HRAS (also known as transforming protein p21, HRAS1) and ceramide synthase 1 (also known as LAG1, longevity assurance homolog, LASS1) genes interact with the APOE gene to reduce age-related increases in lipotoxic events, and haplotypes conformed by the two genes are associated with EL [23]. In the other study, epistasis analysis was performed between APOE haplotypes and haptoglobulin gene (HP) functional polymorphisms, with HP *1/*1 genotype protecting APOE ε4-carriers from age-related negative selection; in light of these results, the authors called for further research on APOE/HP interactions in age-related diseases such as Alzheimer’s and Parkinson’s disease [24].

Japan has the longest life expectancy in the world, as well as the highest number of individuals reaching EL [25]. Thus, Japanese long-lived people represent an attractive model to study potential genetic contributors to EL. The purpose of the present study was to assess whether the interaction between variants in genes that are candidates to influence physical capacity and energy metabolism [ACTN3, TRHR, ACSL1], interact with APOE and FOXO3A genes, and potentially associate with EL in the Japanese population. We also studied the potential interaction with candidate genes involved in antioxidant defense [glutathione peroxidase 1 (GPX1), superoxide dismutase 2 (SOD2)] and cardiometabolic traits [fibronectin type III domain-containing 5 (FNDC5), cyclin-dependent kinase inhibitor 2B antisense noncoding RNA (CDKN2B-AS1)],

Results

The observed genotypic distributions of SNPs were consistent with Hardy–Weinberg Equilibrium (HWE) expectations both in controls and centenarians (P > 0.05). Table 1 shows the single marker allelic association results of the 12 SNPs included in the study. The frequency of the APOE ε2-allele was higher in cases than in controls, whereas ε4-allele frequency was lower in the former (all P < 0.01), as shown previously by us using part of the present cohort [26]. None of the other SNPs, including FOXOA3 rs2802292, was associated with EL, and genotypes did not differ significantly between cases and controls in the recessive, dominant or additive models (all P > 0.05) (data not shown). No significant differences were observed in sex-based analyses (data not shown).
Table 1

Single marker allelic association results of the 12 genetic variants included in the study

Chromosome

SNP

Gene

Position

Minor allele

nucleotide

Minor allele frequency

PBONF

OR

lower 95%CI

Upper 95%CI

     

Centenarians

Controls

    

1

rs16835198

FNDC5

32,861,080

G

0.48

0.45

0.488

1.16

1.00

1.33

2

rs1050450

GPX1

49,357,401

T

0.08

0.08

1

0.95

0.73

1.25

4

rs6552828

ASCL1

1.85E + 08

G

0.40

0.41

1

0.95

0.82

1.10

6

rs4880

SOD2

1.6E + 08

G

0.13

0.14

1

0.94

0.77

1.16

8

rs7832552

TRHR

1.09E + 08

T

0.50

0.50

1

0.97

0.85

1.12

8

rs7460

PTK2

1.41E + 08

T

0.36

0.36

1

1.00

0.860

1.15

8

rs7843014

PTK2

1.41E + 08

A

0.25

0.27

1

0.88

0.75

1.04

9

rs1333049

CDKN2B-AS1

22,125,504

C

0.47

0.46

1

1.05

0.91

1.21

9

rs2802292

FOXO3A

108,587,315

G

0.29

0.28

1

1.05

0.90

1.23

11

rs1815739

ACTN3

66,560,624

C

0.46

0.47

1

0.96

0.84

1.11

19

rs429358

APOE

44,908,684

C

0.05

0.11

6.19 × 10−10

0.39

0.29

0.52

19

rs7412

APOE

44,908,882

T

0.07

0.04

0.002

1.80

1.32

2.46

Allele frequencies were compared using chi-square statistics; ORs and 95% confidence interval (95% CI) were calculated using Plink software

Abbreviations: 95%CI 95% confidence interval, OR odds ratio, P BONF P-value after Bonferroni correction, SNP single nucleotide polymorphism

With regards to epistasis, we found a FOXOA3 rs2802292 T-allele-dependent association of fibronectin type III domain-containing 5 (FDNC5) rs16835198 with EL, that is, among individuals with the rs16835198 GG genotype, the frequency of carriers of the FOXOA3 rs2802292 T-allele was significantly higher in cases than in controls (P < 0.05; Table 2). On the other hand, among non-carriers of the APOE ‘risk’ ε4-allele, the frequency of the FDNC5 rs16835198 G-allele was higher in cases than in controls (48.4% vs. 43.6%, P < 0.05; Table 3). In turn, among carriers of the ‘non-risk’ APOE ε2-allele, the frequency of the rs16835198 G-allele was higher in cases than in controls (49% vs. 37.3%, P < 0.05). No other significant gene interaction was found to be associated with EL.
Table 2

Genotypic frequency distribution of FNDC5 rs16835198 according to the FDNC5 rs16835198 T-allele presence

FDNC5 (rs16835198)

Genotype

FOXO3A Presence of rs2802292 T-allele

P-value

OR (95% CI)

 

Controls (n = 754)

Centenarians (n = 668)

  

GG

147 (19.5%)

162 (24.3%)

0.035

1.32 (1.03–1.70)

GT

378 (50.1%)

323 (48.3%)

NS

TT

229 (30.4%)

183 (27.4%)

NS

Abbreviations: 95%CI 95% confidence interval, NS not significant, OR odds ratio

Table 3

Allele frequency distribution of FNDC5 rs16835198 alleles according to APOE ε2/ε4 status in the study population

FNDC5 (rs16835198)allele

 

Absence of APOE ε4-allelea

Presence of APOE ε4-allelea

  

Controls (2n = 1306)

Centenarians (2n = 1340)

Controls (2n = 336)

Centenarians (2n = 128)

G

N

570

648

165

62

%

43.6%

48.4%

49.1%

48.4%

P-value

0.0167

NS

OR (95% CI)

1.21 (1.04, 1.41)

T

N

736

692

171

66

%

56.4%

51.6%

50.9%

51.6%

P-value

0.0167

NS

OR (95% CI)

0.83 (0.71–0.96)

FNDC5 (rs16835198)allele

 

Absence of APOE ε2-allelea

Presence of APOE ε2-allelea

  

Controls (2n = 1508)

Centenarians (2n = 1258)

Controls (2n = 134)

Centenarians (2n = 210)

G

n

685

607

50

103

%

45.4%

48.3%

37.3%

49%

P-value

NS

0.035

OR (95% CI)

1.62 (1.04–2.52)

T

n

823

651

84

107

%

54.6%

51.7%

62.7%

51%

P-value

NS

0.035

OR (95% CI)

0.62 (0.40–0.96)

Abbreviations: 95%CI 95% confidence interval, NS not significant, OR odds ratio

aAll individuals underwent genotyping for rs429358 and rs7412. The 3 major isoforms of human APOE gene (E2, E3, and E4) coded by 3 alleles (ε2, ε3, and ε4) differ in amino acid sequence at 2 sites, residue 112 (rs429358) and residue 158 (rs7412)

Discussion

Excluding APOE, the present findings do not show replicable association of individual candidate genes, included those related to physical capacity and muscle function, with EL. However, we also assessed the effects of interactions among candidate polymorphisms on the one hand, and EL, on the other hand. In this regard, we report an association of FDNC5 rs16835198 with EL that seems to depend on the presence of the FOXOA3 rs2802292 T-allele. Moreover, we found a novel association between FNDC5 rs16835198 stratified by the presence of the APOE ε2/ε4-allele, and EL. We believe this is an interesting finding because FNDC5 gene encodes the precursor of irisin which, although there is controversy [27], was recently identified a myokine -that is, a molecule released by muscles [28]. Irisin induces expression of uncoupling protein 1 and other brown adipose tissue-associated genes [partly via increased peroxisome proliferators-activated receptor α (PPAR-α)] in white adipocytes, and thus increases thermogenesis and switching of these cells towards a brown fat-like phenotype [28]. In fact irisin has been postulated as a therapeutic agent against cardiometabolic disorders and a major component of the ‘exercise polypill’ [29].

Several mechanisms may link genetic variations in FOXO3A and FNDC5 genes with EL. For example, dysregulation of the nutrient-sensing somatotropic axis [comprising growth hormone and its secondary mediator, insulin-like growth factor-1 (IGF-1)] is a major hallmark of human aging [30]. IGF-1 and insulin signaling collectively represent the “insulin and IGF-1 signaling” pathway. Among the multiple targets of this pathway is the FOXO family of transcription factors, which are also involved in aging and show striking evolutionary conservation [31]. High serum irisin levels may contribute to successful aging, with circulating levels of this biomarker being in fact significantly higher in disease-free centenarians than in young healthy controls and being particularly higher than in young patients with acute myocardial infarction [32]. Moreover, genetic variants in the FNDC5 gene have been associated with in vivo insulin sensitivity [33], and aging is associated with alterations in insulin sensitivity/signaling [34]. Irisin might also play a significant role in reducing the risk of obesity or several related diseases [35]. In a previous report, we found no significant association between genotype and allele frequencies of polymorphisms in FNDC5 and EL [36]. However, the rs16835198 G-allele was associated with a trend towards lower luciferase gene repoter activity in vitro [36].

Insulin sensitivity could be a link explaining the association of the combination of the two loci in FOXO3A and FNDC5, as well as in APOE and FNDC5, with EL. Insulin metabolism as well as insulin-altering therapies in Alzheimer’s disease are modulated by APOE status [37, 38], while irisin reduces diet-induced obesity and insulin resistance in vivo [28]. The FNDC5 rs16835198 G-allele could favor longevity in combination with the APOE ε2-variant, contributing to situations in which rs16835198 SNP distribution is found among long-lived subjects in proportions similar to those found in younger controls. Thus, the conditional effects of genes on the phenotype of aging could play a role in longevity. Most studies show a lower frequency of the APOE ε4-allele in centenarians than in younger controls, while the APOE ε2-allele might be more frequent in centenarians than in younger controls [7]. A “gene x gene” interaction would introduce a modifying allele in another locus, changing the impact of the risk/protective allele from deleterious to beneficial, or vice versa. Here, we report a significant effect of the rs16835198-G allele in the FNDC5 gene on the association between APOE ε2 carriage/non-carriage and EL. There are some limitations in our study. First, our results should be ideally replicated in one or more ethnically and geographically-independent cohorts to account for potential differences in ‘gene x environment’ interactions. Another drawback of case: control designs as the present one is the choice of an appropriate control group, with demographic factors, notably differences in year of birth between centenarians and controls, being potential confounders (e.g., the centenarians and controls of our study were born in the early 1900s and after 1930, respectively) [39]. Differences in gender distribution between cases and controls are also to be accounted for because genetic factors influence survival at advanced age in a sex-specific manner [40]. In this regard, the potential demographic biases of cross-sectional comparisons of genotype/allele frequencies between controls and long lived individuals could be overcome by adding more complete demographic information to genetic data, allowing for estimation of survival rates related to candidate genes [4042]. Because we have only analyzed one SNP within the FOXO3A and FNDC5 genes, further research with different variants of this or other genes involved in insulin-IGF-1, and insulin signaling collectively representing the “insulin and IGF-1 signaling” pathway, must be undertaken. On the other hand, the need for using independent populations for replication may generate some controversy. Some variants may have opposing consequences on the phenotype of interest, and the effect of gene x gene interactions on human health and lifespan might depend on several factors (e.g., internal and external exposure, including medication or different genetic backgrounds of individuals comprising the populations).

Conclusion

We found an association between FDNC5 rs16835198 stratified by the presence of the FOXOA3 rs2802292 T-allele, and EL, as well as between FNDC5 rs16835198 stratified by the presence of the APOE alleles, and EL. Our results suggest the need for further investigation on the possible influence of FOXO3A/FNDC5 interactions and APOE/FNDC5 interactions with EL, but also with other age-related diseases such as atherosclerosis, Alzheimer’s, or Parkinson’s disease. Moreover, identification of gene x gene and gene x environmental factors effects on lifespan may significantly improve our understanding of the association between genetic and non-genetic regulators of aging.

Methods

Study population

A total of 1565 individuals were recruited: 822 controls (aged 23–65 years; 604 women, 218 men) and 743 cases (centenarians aged 100–115 years; 623 women, 1120 men). The controls were enrolled from the Nutrition and EXercise Intervention Study (NEXIS) registered on ClinicalTrials.gov (Identifier: NCT 00926744). Inclusion criteria for the control group were being a man or woman aged 23–65 years with no history of stroke, cardiovascular disease, chronic renal failure, or walking difficulties related to knee or back pain [43]. Cases were collected from two cohorts that have been described in detail elsewhere [44]: the Tokyo Centenarians Study (TCS) and the Semi-Supercentenarians Study in Japan (SSC-J). The prevalence rates of hypertension, coronary artery disease and dementia in the Japanese centenarians were 63.6, 28.8 and 59.4%, respectively [26].

Genotyping

Total DNA was extracted from venous blood with the QIAamp DNA Blood Maxi Kit (Qiagen, Hilden, Germany). SNP genotyping was performed using the following TaqMan® genotyping assays (Applied Biosystems, Foster City, CA): C__34204885_10 for rs16835198, Custom TaMan® Assay for rs1050450, C__30469648_10 for rs6552828, C___8709053_10 for rs4880, C__29085798_10 for rs7832552, C____243385_10 for rs7460, C__11605645_10 for rs7843014, C___1754666_10 for rs1333049, C___1841568_10 for rs2802292, C____590093_1 for rs1815739, C____904973_10 for rs7412 and C___3084793_20 for rs429358. Several quality control procedures, such as repeating the genotyping on a random 10% of the samples were carried out to assure no discrepant results in samples.

Statistical analysis

Statistical analysis of high-density SNP genotyping data was carried out as follows: allele frequencies in cases and controls were compared using chi-square statistics, and odds ratios (OR) and 95% confidence intervals (95% CI) were calculated using Plink software [45]. Bonferroni correction was applied by dividing the P-value by the number of SNPs tested to give the corrected P-value. Allele frequencies obtained for each SNP were tested for deviations from HWE expectations. The combined effects of APOE and FOXO3A alleles and SNPs studied on the risk of EL were analyzed by binary logistic regression with SPSS v.22 statistical software (IBM, Somers, NY, USA) and OR and P values were calculated.

Abbreviations

ACSL1: 

Acyl-CoA synthetase long-chain family member 1

ACTN3: 

Actinin-3

ADA: 

Adenosine deaminase

APOE: 

Apolipoprotein E

CDKN2B-AS1: 

Cyclin-dependent kinase inhibitor 2B antisense noncoding RNA

EL: 

Exceptional longevity

FNDC5: 

Fibronectin type III domain-containing 5

FOXOA3: 

Forkhead box O3A

GPX1: 

Glutathione peroxidase 1

GWAS: 

Genome wide association studies

HP: 

Haptoglobulin gene

HWE: 

Hardy–Weinberg Equilibrium

IGF-1: 

Insulin-like growth factor-1

mtDNA: 

Mitochondrial DNA

NEXIS: 

Nutrition and EXercise Intervention Study

OR: 

Odds ratios

SNPs: 

Single nucleotide polymorphisms

SOD2: 

Superoxide dismutase 2

SSC-J: 

Semi-Supercentenarians Study in Japan

TCS: 

Tokyo Centenarians Study

TNF-α: 

Tumor necrosis factor alpha

TRHR: 

Thyrotropin-releasing hormone

Declarations

Acknowledgements

The authors acknowledge Dr. Kenneth McCreath for his editorial work.

Funding

Publication of this article is supported by grants from the Grant-in-Aid for Scientific Research (B) (15H03081 to N.F.) and Challenging Exploratory Research (16 K13052 to N.F.) programs of the Ministry of Education, Culture, Sports, Science and by a Grant-in-Aid for Scientific Research from the Ministry of Health, Labor, and Welfare of Japan (to M. M). Research by A. Lucia is supported by grants from the Spanish Ministry of Economy and Competitiveness and [Fondo de Investigaciones Sanitarias (FIS)] and Fondos Feder (grant number PI15/00558).

Availability of data and materials

All data generated and/or analyzed during this study are included in this published article.

About this supplement

This article has been published as part of BMC Genomics Volume 18 Supplement 8, 2017: Proceedings of the 34th FIMS World Sports Medicine Congress. The full contents of the supplement are available online at https://bmcgenomics.biomedcentral.com/articles/supplements/volume-18-supplement-8.

Authors’ contributions

All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published. Study conception and design. DPR, FN and LA. Acquisition of data. Arai Y, Abe Y, ZH, Naito H, MH, MM and Hirose N. Analysis and interpretation of data. DPR, SRJA, SC and EE.

Ethics approval and consent to participate

The Ethics Committees of the Keio University and National Institute of Health and Nutrition approved this study and all subjects gave their written informed consent.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Graduate School of Health and Sports Science, Juntendo University
(2)
Hospital Universitari Institut Pere Mata, IISPV, URV. CIBERSAM
(3)
Facultad de Ciencias de la Salud, Universidad Autónoma de Chile
(4)
Center for Supercentenarian Medical Research, Keio University School of Medicine
(5)
Department of Physical Activity Research; National Institutes of Biomedical Innovation, Health and Nutrition
(6)
Neurology Group, Galicia Sur Health Research Institute (IIS Galicia Sur), Centro de investigación biomédica en red del área de salud mental (CIBERSAM)
(7)
2E Science
(8)
Centro de investigación biomédica en Envejecimiento y Fragilidad (CIBERFES)
(9)
European University and Research Institute i+12

References

  1. Soerensen M, Nygaard M, Debrabant B, Mengel-From J, Dato S, Thinggaard M, et al. No association between variation in longevity candidate genes and aging-related phenotypes in oldest-old Danes. Exp Gerontol. 2016;78:57–61. [cited 2016 Nov 5] Available from: http://www.ncbi.nlm.nih.gov/pubmed/26946122 View ArticlePubMedPubMed CentralGoogle Scholar
  2. Terry DF, Sebastiani P, Andersen SL, Perls TT. Disentangling the roles of disability and morbidity in survival to exceptional old age. Arch Intern Med. 2008;168:277–83. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2895331&tool=pmcentrez&rendertype=abstract View ArticlePubMedPubMed CentralGoogle Scholar
  3. Brooks-Wilson AR. Genetics of healthy aging and longevity. Hum Genet. 2013;132:1323–38.View ArticlePubMedPubMed CentralGoogle Scholar
  4. Sebastiani P, Gurinovich A, Bae H, Andersen S, Malovini A, Atzmon G, et al. Four Genome-Wide Association Studies Identify New Extreme Longevity Variants. J Gerontol A. 2017;72:1453-64. Available from: https://academic.oup.com/biomedgerontology/article/3072309/Four.
  5. Kumar NT, Liestol K, Loberg EM, Reims HM, Brorson SH, Maehlen J. The apolipoprotein E polymorphism and cardiovascular diseases--an autopsy study. Cardiovasc Pathol. 2012;21:461–9. Available from: http://www.ncbi.nlm.nih.gov/pubmed/22440829 View ArticlePubMedGoogle Scholar
  6. Liu C-C, Liu C-C, Kanekiyo T, Xu H, Bu G. Apolipoprotein E and Alzheimer disease: risk, mechanisms and therapy. Nat Rev Neurol. 2013;9:106–18. Available from: https://doi.org/10.1038/nrneurol.2012.263 View ArticlePubMedPubMed CentralGoogle Scholar
  7. Garatachea N, Marín PJ, Santos-Lozano A, Sanchis-Gomar F, Emanuele E, Lucia A. The ApoE gene is related with exceptional longevity: a systematic review and meta-analysis. Rejuvenation Res. 2015;18:3–13. Available from: http://online.liebertpub.com/doi/abs/10.1089/rej.2014.1605, http://www.ncbi.nlm.nih.gov/pubmed/25385258.
  8. Willcox BJ, Donlon T a, He Q, Chen R, Grove JS, Yano K, et al. FOXO3A genotype is strongly associated with human longevity. Proc Natl Acad Sci U S A. 2008;105:13987–92.View ArticlePubMedPubMed CentralGoogle Scholar
  9. Anselmi CV, Malovini A, Roncarati R, Novelli V, Villa F, Condorelli G, et al. Association of the FOXO3A locus with extreme longevity in a southern Italian centenarian study. Rejuvenation Res. 2009;12:95–104. Available from: http://online.liebertpub.com/doi/abs/10.1089/rej.2008.0827, http://www.ncbi.nlm.nih.gov/pubmed/19415983.
  10. Li Y, Wang WJ, Cao H, Lu J, Wu C, Hu FY, et al. Genetic association of FOXO1A and FOXO3A with longevity trait in Han Chinese populations. Hum Mol Genet. 2009;18:4897–904.View ArticlePubMedPubMed CentralGoogle Scholar
  11. Sun L, Hu C, Zheng C, Qian Y, Liang Q, Lv Z, et al. FOXO3 variants are beneficial for longevity in southern Chinese living in the Red River basin: a case–control study and meta-analysis. Sci Rep. 2015;5:9852. Available from: http://www.nature.com/srep/2015/150408/srep09852/full/srep09852.html View ArticlePubMedPubMed CentralGoogle Scholar
  12. Soerensen M, Dato S, Christensen K, McGue M, Stevnsner T, Bohr VA, et al. Replication of an association of variation in the FOXO3A gene with human longevity using both case–control and longitudinal data. Aging Cell. 2010;9:1010–7.View ArticlePubMedPubMed CentralGoogle Scholar
  13. Flachsbart F, Caliebe A, Kleindorp R, Blanché H, von Eller-Eberstein H, Nikolaus S, et al. Association of FOXO3A variation with human longevity confirmed in German centenarians. Proc Natl Acad Sci U S A. 2009;106:2700–5.View ArticlePubMedPubMed CentralGoogle Scholar
  14. Fuku N, Díaz-Peña R, Arai Y, Abe Y, Pareja-Galeano H, Sanchis-Gomar F, et al. rs2802292 polymorphism in the FOXO3A gene and exceptional longevity in two ethnically distinct cohorts. Maturitas. 2016;92:110–4.View ArticlePubMedGoogle Scholar
  15. Fuku N, Alis R, Yvert T, Zempo H, Naito H, Abe Y, et al. Muscle-related polymorphisms (mstn rs1805086 and actn3 rs1815739) are not associated with exceptional longevity in Japanese centenarians. PLoS One. 2016;11:e0166605.View ArticlePubMedPubMed CentralGoogle Scholar
  16. Fuku N, He ZH, Sanchis-Gomar F, Pareja-Galeano H, Tian Y, Arai Y, et al. Exceptional longevity and muscle and fitness related genotypes: a functional in vitro analysis and case–control association replication study with SNPs THRH rs7832552, IL6 rs1800795 and ACSL1 rs6552828. Front Aging Neurosci. 2015;7:59.View ArticlePubMedPubMed CentralGoogle Scholar
  17. Garatachea N, Pareja-Galeano H, Sanchis-Gomar F, Santos-Lozano A, Fiuza-Luces C, Morán M, et al. Exercise attenuates the major hallmarks of aging. Rejuvenation Res. 2015;18:57–89. Available from: http://online.liebertpub.com/doi/abs/10.1089/rej.2014.1623 View ArticlePubMedPubMed CentralGoogle Scholar
  18. Cordell HJ. Epistasis: what it means, what it doesn’t mean, and statistical methods to detect it in humans. Hum Mol Genet. 2002;11:2463–8. Available from: http://www.ncbi.nlm.nih.gov/pubmed/12351582 View ArticlePubMedGoogle Scholar
  19. Ukraintseva S, Yashin A, Arbeev K, Kulminski A, Akushevich I, Wu D, et al. Puzzling role of genetic risk factors in human longevity: “risk alleles” as pro-longevity variants. Biogerontology. 2016;17:109–27.View ArticlePubMedGoogle Scholar
  20. Niemi A-K, Moilanen JS, Tanaka M, Hervonen A, Hurme M, Lehtimäki T, et al. A combination of three common inherited mitochondrial DNA polymorphisms promotes longevity in Finnish and Japanese subjects. Eur J Hum Genet. 2005;13:166–70.View ArticlePubMedGoogle Scholar
  21. Napolioni V, Carpi FM, Giannì P, Sacco R, Di Blasio L, Mignini F, et al. Age- and gender-specific epistasis between ADA and TNF-α influences human life-expectancy. Cytokine. 2011;56:481–8.View ArticlePubMedGoogle Scholar
  22. Tan Q, Soerensen M, Kruse TA, Christensen K, Christiansen L. A novel permutation test for case-only analysis identifies epistatic effects on human longevity in the FOXO gene family. Aging Cell. 2013;12:690–4.View ArticlePubMedPubMed CentralGoogle Scholar
  23. Jazwinski SM, Kim S, Dai J, Li L, Bi X, Jiang JC, et al. HRAS1 and LASS1 with APOE are associated with human longevity and healthy aging. Aging Cell. 2010;9:698–708.View ArticlePubMedPubMed CentralGoogle Scholar
  24. Napolioni V, Giannì P, Carpi FM, Predazzi IM, Lucarini N. APOE haplotypes are associated with human longevity in a Central Italy population: evidence for epistasis with HP 1/2 polymorphism. Clin Chim Acta. 2011;412:1821–4.View ArticlePubMedGoogle Scholar
  25. Santos-Lozano A, Sanchis-Gomar F, Pareja-Galeano H, Fiuza-Luces C, Emanuele E, Lucia A, et al. Where are supercentenarians located? A worldwide demographic study. Rejuvenation Res. 2015;18:14–9. Available from: http://www.ncbi.nlm.nih.gov/pubmed/25386976 View ArticlePubMedGoogle Scholar
  26. Garatachea N, Emanuele E, Calero M, Fuku N, Arai Y, Abe Y, et al. ApoE gene and exceptional longevity: insights from three independent cohorts. Exp Gerontol. 2014;53:16–23.View ArticlePubMedGoogle Scholar
  27. Timmons JA, Baar K, Davidsen PK, Atherton PJ. Is irisin a human exercise gene? Nature. 2012;488:E9–10.View ArticlePubMedGoogle Scholar
  28. Boström P, Wu J, Jedrychowski MP, Korde A, Ye L, Lo JC, et al. A PGC1-α-dependent myokine that drives brown-fat-like development of white fat and thermogenesis. Nature. 2012;481:463–8. [cited 2016 Nov 9] Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3522098&tool=pmcentrez&rendertype=abstract View ArticlePubMedPubMed CentralGoogle Scholar
  29. Fiuza-Luces C, Garatachea N, Berger NA, Lucia A. Exercise is the real Polypill. Physiology. 2013;28:330–58. Available from: http://physiologyonline.physiology.org/cgi/doi/10.1152/physiol.00019.2013 View ArticlePubMedGoogle Scholar
  30. López-Otín C, Galluzzi L, Freije JMP, Madeo F, Kroemer G. Metabolic control of longevity. Cell. 2016;166:802–21.View ArticlePubMedGoogle Scholar
  31. Kenyon CJ. The genetics of ageing. Nature. 2010;464:504–12.View ArticlePubMedGoogle Scholar
  32. Emanuele E, Minoretti P, Pareja-Galeano H, Sanchis-Gomar F, Garatachea N, Lucia A. Serum irisin levels, precocious myocardial infarction, and healthy exceptional longevity. Am J Med. 2014;127:888–90. Available from: http://www.ncbi.nlm.nih.gov/pubmed/24813865.View ArticlePubMedGoogle Scholar
  33. Staiger H, Böhm A, Scheler M, Berti L, Machann J, Schick F, et al. Common genetic variation in the human FNDC5 locus, encoding the novel muscle-derived “Browning” factor Irisin, determines insulin sensitivity. PLoS One. 2013;8:e61903.View ArticlePubMedPubMed CentralGoogle Scholar
  34. Barbieri M, Gambardella A, Paolisso G, Varricchio M. Metabolic aspects of the extreme longevity. Exp Gerontol. 2008;43:74–8.View ArticlePubMedGoogle Scholar
  35. Spiegelman BM. Banting lecture 2012: regulation of adipogenesis: toward new therapeutics for metabolic disease. Diabetes. 2013;62:1774–82.View ArticlePubMedPubMed CentralGoogle Scholar
  36. Sanchis-Gomar F, Garatachea N, He ZH, Pareja-Galeano H, Fuku N, Tian Y, et al. FNDC5 (irisin) gene and exceptional longevity: a functional replication study with rs16835198 and rs726344 SNPs. Age (Dordr). 2014;36:9733.View ArticleGoogle Scholar
  37. Craft S, Asthana S, Schellenberg G, Baker L, Cherrier M, Boyt AA, et al. Insulin effects on glucose metabolism, memory, and plasma amyloid precursor protein in Alzheimer’s disease differ according to apolipoprotein-E genotype. Ann N Y Acad Sci. 2000;903:222–8. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&dopt=AbstractPlus&list_uids=10818510 View ArticlePubMedGoogle Scholar
  38. Aisen PS, Berg JD, Craft S, Peskind ER, Sano M, Teri L, et al. Steroid-induced elevation of glucose in Alzheimer’s disease: relationship to gender, apolipoprotein E genotype and cognition. Psychoneuroendocrinology. 2003;28:113–20.View ArticlePubMedGoogle Scholar
  39. Lewis SJ. Methodological problems in genetic association studies of longevity--the apolipoprotein E gene as an example. Int J Epidemiol. 2004;33:962–70. [cited 2016 Nov 9]Available from: http://www.ncbi.nlm.nih.gov/pubmed/15319409 View ArticlePubMedGoogle Scholar
  40. Passarino G, Montesanto A, Dato S, Giordano S, Domma F, Mari V, et al. Sex and age specificity of susceptibility genes modulating survival at old age. Hum Hered. 2006;62:213–20.View ArticlePubMedGoogle Scholar
  41. Yashin AI, De Benedictis G, Vaupel JW, Tan Q, Andreev KF, Iachine IA, et al. Genes, demography, and life span: the contribution of demographic data in genetic studies on aging and longevity. Am J Hum Genet. 1999;65:1178–93. Available from: http://www.cell.com/article/S0002929707626214/fulltext View ArticlePubMedPubMed CentralGoogle Scholar
  42. Dato S, Carotenuto L, Benedictis G. Genes and longevity: a genetic-demographic approach reveals sex- and age-specific gene effects not shown by the case–control approach (APOE and HSP70.1 loci). Biogerontology. 2007;8:31–41.View ArticlePubMedGoogle Scholar
  43. Murakami H, Iemitsu M, Fuku N, Sanada K, Gando Y, Kawakami R, et al. The Q223R polymorphism in the leptin receptor associates with objectively measured light physical activity in free-living Japanese. Physiol Behav. 2014;129:199–204.View ArticlePubMedGoogle Scholar
  44. Gondo Y, Hirose N, Arai Y, Inagaki H, Masui Y, Yamamura K, et al. Functional status of centenarians in Tokyo, Japan: developing better phenotypes of exceptional longevity. J Gerontol A Biol Sci Med Sci. 2006;61:305–10. [cited 2016 Nov 4] Available from: http://www.ncbi.nlm.nih.gov/pubmed/16567382.View ArticlePubMedGoogle Scholar
  45. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D, et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet. 2007;81:559–75.View ArticlePubMedPubMed CentralGoogle Scholar

Copyright

© The Author(s). 2017

Advertisement