Short telomere length is associated with impaired cognitive performance in European ancestry cohorts

This is an elec onic ep in o he o iginal a icle. This ep in may di e om he o iginal in pagina ion and ypog aphic de ail. Au ho (s): Ti le: Yea : Ve sion: Please ci e he o iginal e sion: All ma e ial supplied ia JYX is p o ec ed by copy igh and o he in ellec ual p ope y igh s, and duplica ion o sale o all o pa o any o he eposi o y collec ions is no pe mi ed, excep ha ma e ial may be duplica ed by you o you esea ch use o educa ional pu poses in elec onic o p in o m. You mus ob ain pe mission o any o he use. Elec onic o p in copies may no be o e ed, whe he o sale o o he wise o anyone who is no an au ho ised use . Sho elome e leng h is associa ed wi h impai ed cogni i e pe o mance in Eu opean ances y coho s Hägg, S.; Zhan, Y.; Ka lsson, R.; Ge i sen, L.; Plone , A.; an de Lee, S. J.; B oe , L.; Deelen, J.; Ma ioni, R. E.; Wong, A.; Lundquis , A.; Zhu, G.; Hansell, N. K.; Sillanpää, Elina; Fedko, I. O.; Amin, N. A.; Beekman, M.; C aen, A. J. M. de; Dege man, S.; Ha is, S. E.; Kan, K.-J.; Ma in-Ruiz, C. M.; Mon gome y, G. W.; G oup, Neu oCHARGE Cogni i e Wo king; Adol sson, A. N.; Reynolds, C. A.; Samani, N. J.; Suchiman, H. E. D.; Viljanen, Anne; on Zglinicki, T.; W igh , M. J.; Ho enga, J.-J.; Boomsma, D. I.; Ran anen, Taina; Kap io, J. A.; Nyhol , D. R.; Ma in, N. G.; Nybe g, L.; Adol sson, R.; Kuh, D.; S a , J. M.; Dea y, I. J.; Slagboom, P. E.; an Duijn, C. M.; Codd, V.; Pede sen, N. L. Hägg, S., Zhan, Y., Ka lsson, R., Ge i sen, L., Plone , A., an de Lee, S. J., B oe , L., Deelen, J., Ma ioni, R. E., Wong, A., Lundquis , A., Zhu, G., Hansell, N. K., Sillanpää, E., Fedko, I. O., Amin, N. A., Beekman, M., C aen, A. J. M. D., Dege man, S., . . . Pede sen, N. L. (2017). Sho elome e leng h is associa ed wi h impai ed cogni i e pe o mance in Eu opean ances y coho s. T ansla ional Psychia y, 7(4), A icle e1100. h ps://doi.o g/10.1038/ p.2017.73 2017 OPEN ORIGINAL ARTICLE Sho elome e leng h is associa ed wi h impai ed cogni i e pe o mance in Eu opean ances y coho s S Hägg 1 , Y Zhan 1 , R Ka lsson 1 , L Ge i sen 1 , A Plone 1 , SJ an de Lee 2 , L B oe 3 , J Deelen 4,5 , RE Ma ioni 6,7,8 , A Wong 9 , A Lundquis 10 , G Zhu 11 , NK Hansell 8,11 , E Sillanpää 12 , IO Fedko 13 , NA Amin 2 , M Beekman 4 , AJM de C aen 14,✠ , S Dege man 15 , SE Ha is 6,7 , K-J Kan 13 , CM Ma in-Ruiz 16 , GW Mon gome y 11 , Neu oCHARGE Cogni i e Wo king G oup, AN Adol sson 17 , CA Reynolds 18 , NJ Samani 19,20 , HED Suchiman 4 , A Viljanen 12 , T on Zglinicki 21 , MJ W igh 8,22 , J-J Ho enga 13 , DI Boomsma 13 , T Ran anen 12 , JA Kap io 23,24,25 , DR Nyhol 11,26 , NG Ma in 11 , L Nybe g 27,28,29 , R Adol sson 17 , D Kuh 9 , JM S a 7,30 , IJ Dea y 7,31 , PE Slagboom 4 , CM an Duijn 2 , V Codd 19,20 , NL Pede sen 1 o he ENGAGE Conso ium The associa ion be ween elome e leng h (TL) dynamics on cogni i e pe o mance o e he li e-cou se is no well unde s ood. This s udy me a-analyses obse a ional and causal associa ions be ween TL and six cogni i e ai s, wi h s a ifica ions on APOE geno ype, in a Mendelian Randomiza ion (MR) amewo k. Twel e Eu opean coho s (N= 17 052; mean age = 59.2 ± 8.8 yea s) p o ided esul s o associa ions be ween qPCR-measu ed TL (T/S- a io scale) and gene al cogni i e unc ion, mini-men al s a e exam (MMSE), p ocessing speed by digi symbol subs i u ion es (DSST), isuospa ial unc ioning, memo y and execu i e unc ioning (STROOP). In addi ion, a gene ic isk sco e (GRS) o TL including se en known gene ic a ian s o TL was calcula ed, and used in associa ions wi h cogni i e ai s as ou comes in all coho s. Obse a ional analyses showed ha longe elome es we e associa ed wi h be e sco es on DSST (β= 0.051 pe s.d.-inc ease o TL; 95% confidence in e al (CI): 0.024, 0.077; P= 0.0002), and MMSE (β= 0.025; 95% CI: 0.002, 0.047; P= 0.03), and as e STROOP (β=−0.053; 95% CI: −0.087, −0.018; P= 0.003). E ec s o DSST we e s onge in APOE ε4 non-ca ie s (β= 0.081; 95% CI: 0.045, 0.117; P= 1.0 × 10 −5 ), whe eas ca ie s pe o med be e in STROOP (β=−0.074; 95% CI: −0.140, −0.009; P= 0.03). Causal associa ions we e ound o STROOP only (β=−0.598 pe s.d.-inc ease o TL; 95% CI: −1.125, −0.072; P= 0.026), wi h a la ge e ec in ε4-ca ie s (β=−0.699; 95% CI: −1.330, −0.069; P= 0.03). Two-sample eplica ion analyses using CHARGE summa y s a is ics showed causal e ec s be ween TL and gene al cogni i e unc ion and DSST, bu no wi h STROOP. In conclusion, we sugges causal e ec s om longe TL on be e cogni i e pe o mance, whe e APOE ε4-ca ie s migh be a di e en ial isk. T ansla ional Psychia y (2017) 7, e1100; doi:10.1038/ p.2017.73; published online 18 Ap il 2017 INTRODUCTION Telome es, sho DNA sequences a he end o ch omosomes, a e conside ed ma ke s o biological age. Cell eplica ion and oxida i e s esso s con ibu e o he loss o elome e nucleo ides o e ime; below c i ical leng h, cellula senescence will ollow. 1 An inc easing numbe o s udies ha e shown he impo ance o elome e leng h (TL) in ageing, specifically in he de elopmen o demen ia and cogni i e impai men . 2–8 Using a ela i ely la ge g oup o non-demen ed olde indi iduals, Ya e e al. 3 demon- s a ed an associa ion be ween longe elome es and highe sco e in he digi symbol subs i u ion es (DSST)—a measu e o p ocessing speed—a baseline. A e se en yea s, he indi iduals wi h longe elome es a baseline pe o med be e in he modified mini-men al s a e exam (MMSE) bu no in DSST. 1 Depa men o Medical Epidemiology and Bios a is ics, Ka olinska Ins i u e , S ockholm, Sweden; 2 Depa men o Epidemiology, E asmus Uni e si y Medical Cen e , Ro e dam, The Ne he lands; 3 Depa men o In e nal Medicine, E asmus Uni e si y Medical Cen e , Ro e dam, The Ne he lands; 4 Depa men o Molecula Epidemiology, Leiden Uni e si y Medical Cen e , Leiden, The Ne he lands; 5 Max Planck Ins i u e o Biology o Ageing, Cologne, Ge many; 6 Cen e o Genomic and Expe imen al Medicine, Ins i u e o Gene ics and Molecula Medicine, Uni e si y o Edinbu gh, Edinbu gh, UK; 7 Cen e o Cogni i e Ageing and Cogni i e Epidemiology, Uni e si y o Edinbu gh, Edinbu gh, UK; 8 Queensland B ain Ins i u e, Uni e si y o Queensland, B isbane, QLD, Aus alia; 9 MRC Uni o Li elong Heal h and Ageing a UCL, London, UK; 10 Depa men o S a is ics, Umeå Uni e si y, Umeå, Sweden; 11 QIMR Be gho e Medical Resea ch Ins i u e, B isbane, QLD, Aus alia; 12 Ge on ology Resea ch Cen e , Facul y o Spo and Heal h Sciences, Uni e si y o Jy äskylä, Jy äskylä, Finland; 13 Depa men Biological Psychology, V ije Uni e si ei , Ams e dam, The Ne he lands; 14 Depa men o Ge on ology and Ge ia ics, Leiden Uni e si y Medical Cen e , Leiden, The Ne he lands; 15 Depa men o Medical Biosciences, Umeå Uni e si y, Umeå, Sweden; 16 NIHR Newcas le Biomedical Resea ch Cen e & Uni , Ins i u e o Neu osciences, Newcas le Uni e si y, Campus o Ageing and Vi ali y, Newcas le upon Tyne, UK; 17 Depa men o Clinical Sciences, Umeå Uni e si y, Umeå, Sweden; 18 Depa men o Psychology, Uni e si y Cali o nia Ri e side, Ri e side, CA, USA; 19 Depa men o Ca dio ascula Sciences, Uni e si y o Leices e , Leices e , UK; 20 Na ional Ins i u e o Heal h Resea ch Leices e Ca dio ascula Biomedical Resea ch Uni , Glenfield Hospi al, Leices e , UK; 21 Newcas le Uni e si y Ins i u e o Ageing, Ins i u e o Cell & Molecula Biosciences, Newcas le upon Tyne, UK; 22 Cen e o Ad anced Imaging, Uni e si y o Queensland, B isbane, QLD, Aus alia; 23 Depa men o Public Heal h, Clincum, Uni e si y o Helsinki, Helsinki, Finland; 24 Ins i u e o Molecula Medicine Finland (FIMM), Uni e si y o Helsinki, Helsinki, Finland; 25 Na ional Ins i u e o Heal h and Wel a e (THL), Helsinki, Finland; 26 Ins i u e o Heal h and Biomedical Inno a ion, Queensland Uni e si y o Technology, B isbane, QLD, Aus alia; 27 Depa men o Radia ion Sciences, Umeå Uni e si y, Umeå, Sweden; 28 Depa men o In eg a i e Medical Biology (IMB), Umeå Uni e si y, Umeå, Sweden; 29 Umeå cen e o Func ional B ain Imaging, Umeå Uni e si y, Umeå, Sweden; 30 Alzheime Sco land Demen ia Resea ch Cen e, Uni e si y o Edinbu gh, Edinbu gh, UK and 31 Depa men o Psychology, Uni e si y o Edinbu gh, Edinbu gh, UK. Co espondence: D S Hägg, Depa men o Medical Epidemiology and Bios a is ics (MEB), Ka olinska Ins i u e , Box 281, S ockholm 171 77, Sweden. E-mail: [email p o ec ed] ✠ Deceased. Recei ed 13 Feb ua y 2017; accep ed 13 Feb ua y 2017 Ci a ion: T ansl Psychia y (2017) 7, e1100; doi:10.1038/ p.2017.73 www.na u e.com/ p Cohen-Manheim e al. 8 in es iga ed TL in young adul s and ound as e a i ion a es wi h poo e mid-li e gene al- and domain- specific cogni i e pe o mance bu no associa ion wi h baseline TL. In addi ion, a c oss-sec ional s udy o non-demen ed indi iduals concluded ha APOE ε4-ca ie s had longe TL bu as e a i ion a es indica ing abno mal cell u no e . 9 O he s udies ha e also shown associa ions be ween TL and cogni ion wi h conflic ing esul s o we e unde powe ed. 4,6,10,11 Hence, he unde lying mechanisms by which elome es may be in ol ed in cogni i e pe o mance a e complex, and la ge e o s a e needed o elucida e his ela ionship. Mo eo e , i is s ill unclea whe he sho elome es a e a cause, consequence o bo h o cogni i e impai men . One way o p edic a causal associa ion is o conduc a Mendelian Randomiza ion (MR) s udy, 12 in which gene ic ma ke s a e used as p oxies o an exposu e (TL), o in es iga e an un- biased e ec on an ou come (cogni i e pe o mance). Because gene ic a ian s a e andomly asso ed a meiosis, hey a e gene ally ee om con en ional con ounding and hence he MR s udy design is o en e e ed o as na u e’s own clinical ial. 13 We hypo hesized ha TL is an indica o o cellula s abili y, which as such a ec s unc ioning h oughou he body, including pe o mance on all ypes o cogni i e ai s. 14 In addi ion, indi iduals ca ying he APOE ε4 allele a e mo e suscep ible o cogni i e impai men and a e he e o e o special in e es . 15 The objec i e o ou s udy was o conduc a me a-analy ic MR s udy o he associa ion be ween TL and six cogni i e ai s in 12 Eu opean ances y coho s (N= 17 052). A seconda y aim was o s a i y on APOE ε4 geno ype o in es iga e i ca ie s we e a di e en isks gi en hei wo se cogni i e abili y. Mos coho s we e en olled h ough he Eu opean Ne wo k o Genomic and Gene ic Epidemiology (ENGAGE) Conso ium. Telome e measu emen s we e pe o med by qPCR and a gene ic isk sco e (GRS) wi h se en gene ic a ian s associa ed wi h TL 16 was calcula ed. Obse a ional- as well as causal es ima es we e subsequen ly ob ained using an MR design. 17 In a eplica ion e o , summa y s a is ics om he Coho s o Hea and Aging Resea ch in Genomic Epidemiology (CHARGE) Conso ium o he gene ic associa ions wi h h ee cogni i e ai s 18,19 we e included in a wo- sample MR app oach. 20 MATERIALS AND METHODS S udy samples Twel e coho s wi h a o al o 17 052 indi iduals (Table 1), all wi h Eu opean ances y popula ions, pa icipa ed in he ENGAGE e o . The sample-size weigh ed mean o age was 59.2 yea s wi h s.d. = 8.8. Mos coho s con ibu ed da a measu ed a mid-li e o olde . The Leiden Longe i y S udy 2 (LLS2) was he oldes coho (mean age = 93.3 yea s). The Ne he lands Twin Regis e (NTR) included middle-aged adul s (mean age = 40.3 yea s, s.d. = 16.4) and QIMR (Twin s udies a he Queensland Ins i u e o Medical Resea ch) included adolescen s only (mean age = 14.1 yea s, s.d. = 2.4). All bu one s udy showed a ai ly e en p opo ion o sexes ( ange: 49–67% women); FITSA (The Finnish Twin S udy on Ageing) included women only. Addi ional s udy-specific de ails a e ound in Supplemen a y Table 1. Cogni i e ai s Six di e en cogni i e ai s we e es ed in a combined me a-analysis o he ENGAGE coho s: (1) gene al cogni i e unc ion; (2) MMSE; (3) p ocessing speed wi h DSST o he a ian symbol digi subs i u ion ask; (4) isuospa ial unc ioning wi h block design es (BLOCK); (5) episodic memo y by ei he e bal lea ning o pic u e lea ning es s (MEMORY); and (6) execu i e unc ioning using S oop in e e ence sco e (STROOP). De ailed desc ip ions o he di e en cogni i e ai s a e ound in he supplemen (Supplemen a y Table 3). All coho s pa icipa ed wi h a leas one cogni i e ai ; no single coho had all o hem (Table 1). Table 1. Coho s pa icipa ing in he ENGAGE s udy Coho Full name o coho NAge (y ) mean (s. d.) TL (T/S- a io) mean (s.d.) Women (%) GRS mean (s. d.) MMSE DSST BLOCK MEMORY STROOP Gene al cogni ion APOE geno ype BETULA1 The Be ula S udy a 163 50.9 (7.8) 1.01 (0.17) 58.3 8.5 (1.57) × × × × × Yes BETULA2 The Be ula S udy a 396 62.4 (14.5) 0.93 (0.15) 54.8 8.87 (1.56) × × × × × Yes BETULA3 The Be ula S udy a 315 60 (15) 0.97 (0.17) 54.0 8.65 (1.51) × × × × × Yes ERF E asmus Rucphen Family (EUROSPAN) 2502 51.6 (15.8) 1.76 (0.36) 55.6 8.65 (1.57) × × × Yes FITSA The Finnish Twin S udy on Ageing 429 68.6 (3.4) 0.9 (0.19) 100.0 8.52 (1.46) × × Yes Gende Sex di e ences in heal h and aging 466 74.5 (2.6) 0.68 (0.15) 49.0 8.43 (1.34) × × × × Yes HRS Heal h and Re i emen S udy 4117 70.4 (9.4) 1.3 (0.3) 58.0 8.6 (1.52) × × × LBC1936 Lo hian Bi h Coho 999 69.6 (0.8) 1.3 (0.5) 49.0 8.36 (1.56) × × × × × Yes LLS1 Leiden Longe i y S udy 1 2305 59.2 (6.8) 1.46 (0.26) 54.8 8.47 (1.52) × × × Yes LLS2 Leiden Longe i y S udy 2 868 93.3 (2.6) 1.28 (0.22) 61.6 8.44 (1.57) × Yes NSHD Na ional Su ey o Heal h and De elopmen 2425 53 (0) 1.54 (0.91) 50.0 8.55 (1.4) × × Yes NTR Ne he lands Twin Regis e 200 40.3 (16.4) 2.72 (0.56) 66.5 8.5 (1.56) × QIMR Twin s udies a he Queensland Ins i u e o Medical Resea ch 1280 14.1 (2.4) 3.7 (0.6) 52.6 8.5 (1.5) × SATSA Swedish Adop ion/Twin S udy o Aging 587 68.8 (9.6) 0.76 (0.27) 58.0 8.45 (1.45) × × × × Yes Abb e ia ions: BLOCK, block design es ; CHARGE, Coho s o Hea and Aging Resea ch in Genomic Epidemiology Conso ium; DSST, digi symbol subs i u ion es ; ENGAGE, Eu opean Ne wo k o Gene ic and Genomic Epidemiology; GRS, gene ic isk sco e; MEMORY, e bal memo y o pic u e lea ning es ; MMSE, mini-men al s a e exam; STROOP, s oop colo wo d ask in e e ence sco e; TL, elome e leng h; Y , yea . a BETULA1 and BETULA2-3 we e geno yped a wo di e en acili ies. Telome e leng h and cogni i e pe o mance S Hägg e al 2 T ansla ional Psychia y (2017), 1 –6 Telome e leng h measu emen s Telome e leng h was measu ed in leukocy es in whole blood/bu y coa excep o he HRS s udy, which used measu emen s om sali a. DNA om sali a de i es o he mos pa (~74%) om leukocy es, 21 and TL measu emen s om blood and sali a ha e been epo ed o ha e good co ela ions (R= 0.72). 22 S anda d qPCR echniques o TL measu emen we e applied as desc ibed by Caw hon 23 wi h mino modifica ions in he Lo hian Bi h Coho (LBC) 11 and BETULA. 24 In b ie , elome e (T) and single copy gene (S) quan i y we e measu ed and a T/S- a io was calcula ed. One o se e al e e ence samples we e included in all uns and a ela i e elome e leng h was calcula ed o each sample. Geno yping In o ma ion on geno yping pla o m, quali y con ol and single-nucleo ide polymo phisms (SNPs) used in each coho is a ailable in he supplemen (Supplemen a y Da a and Supplemen a y Table 2). An addi i e un- weigh ed GRS was calcula ed o each indi idual by summa izing he numbe o isk alleles om se en di e en loci (TERC, TERT, NAF1, OBFC1, ZNF208, RTEL1 and ACYP2) whe e SNPs ( s10936599, s2736100, s7675998, s9420907, s8105767, s755017 and s11125529) ha e been ound o associa e wi h TL. 16 In es iga ions o possible pleio opic e ec s om he di e en gene ic a ian s used in he GRS a e discussed in he supplemen (Supplemen a y Da a). Fou coho s (ERF (E asmus Rucphen Family), LLS, NTR and QIMR) om he cu en e o con ibu ed o he o iginal genome- wide associa ion s udy (GWAS) o TL (see Supplemen a y Da a o u he discussions on implica ions o ou s udy). No associa ions be ween any o he se en TL genes and cogni i e ai s ha e been es ed hus a as judged om he GWAS Ca alog. 25 Gene ic a ian s we e p io i ized as (1) di ec ly geno yped, (2) impu ed wi h good quali y, (3) p oxies wi h 2 40.8 and (4) impu ed om summa y s a is ics. The weigh ed mean o he GRS was 8.55 wi h s.d. = 1.51 (Table 1). APOE geno ype was assessed sepa a ely and a ailable in mos coho s (Table 1). Replica ion da a Summa ized esul s om he CHARGE Conso ium’s me a-analyses o genome-wide associa ion s udies be ween geno ypes and gene al cogni i e unc ion (N= 53 949), 18 p ocessing speed by a me a-analysis o ou es s o p ocessing speed including he DSST (N= 32 088) 19 and execu i e unc ioning (STROOP; N= 7726) 19 we e used o assess causal associa ions om he same se en TL associa ed gene ic a ian s. 16 The CHARGE coho s we e all o Eu opean ances y and pa icipan s we e aged 45 yea s o olde . Some ENGAGE coho s con ibu ed o CHARGE analyses o gene al cogni i e unc ion: BETULA1, ERF, HRS, and LBC1936; DSST and STROOP: ERF; and DSST: LBC1936 (Table 1; see Supplemen a y Da a o u he discussions on implica ions o ou s udy). The gene al cogni i e unc ion pheno ype was c ea ed as a composi e sco e o mul iple cogni i e es s 18 om p incipal componen analysis. The p ocessing speed a iable was c ea ed om DSST and h ee simila es s, and execu i e unc ioning was assessed by ei he T ail Making es s o S oop colo and wo d in e e ence es s. 19 E ec sizes we e missing o DSST and STROOP; hence esul s we e p esen ed in Z-sco es only. S a is ical analyses All a iables (TL and cogni i e ai s) we e Z- ans o med wi h sub ac ion o he mean and di ision o s.d. o enable compa isons ac oss coho s. Age g oups, ins ead o con inuous age, we e defined and used as co a ia es o allow o non-linea age e ec s: (1) 0–29 yea s; (2) 30–59 yea s; (3) 60–79 yea s; and (4) 80+ yea s. Coho s wi h in o ma ion on APOE geno ype pe o med addi ional analyses s a ified on ε4-ca ie s (ε4/ε4 and ε4/ε3) and non-ca ie s (ε3/ε3, ε2/ε3 and ε2/ε2). Indi iduals wi h he geno ype ε2/ ε4 a e excluded om he analysis. All models a e desc ibed in de ail in he Supplemen a y Da a; b iefly, all coho s con ibu ed wi h summa y da a om h ee di e en models as depic ed in Figu e 1. Linea eg essions we e fi ed o he associa ions o (1) TL on cogni i e ai (TL- ai ), (2) GRS on TL (GRS-TL), and (3) GRS on cogni i e ai (GRS- ai ). All models we e adjus ed o sex, age g oup and s udy-specific co a ia es. E ec es ima es om all models we e pooled ac oss coho s ia fixed-e ec me a-analysis, excep when e idence was ound o s a is ically significan he e ogenei y (P- alueo0.05), in which case a andom-e ec s me a-analysis was pe o med ins ead. Then, ins umen al a iable (IV) analysis was conduc ed by calcula ing a Wald- ype causal es ima e o he e ec o TL on each cogni i e ai (IV − ai = GRS − ai /GRS-TL). E ec di e ences be ween obse ed (TL- ai ) and causal/p edic ed (IV- ai ) es ima es we e calcula ed by sub ac ing he causal be a om he obse a ional be a in a Z- es (Supplemen a y Da a). S a ified analyses on APOE geno ype we e done simila ly. Fo summa y s a is ics da a om CHARGE, a causal es ima e was calcula ed as desc ibed by Bu gess e al. 20 (Supplemen a y Da a). C ude P- alues a e p esen ed o all associa ions, ha is, no mul iple es ing co ec ions ha e been applied. RESULTS Obse a ional analyses o elome e leng h and cogni i e ai s Significan associa ions, suppo ing he ela ionship be ween longe elome es and be e cogni i e abili y, we e seen be ween TL and MMSE, DSST and STROOP using fixed-e ec s me a-analysis (Table 2, Figu e 2). Posi i e associa ions we e obse ed o MMSE (0.025 pe s.d.-inc ease in TL; 95% confidence in e al (CI) 0.002, 0.047) and DSST (0.051; 95% CI 0.024, 0.077). Fo STROOP, a nega i e be a (−0.053 pe s.d.-inc ease in TL; 95% CI −0.087, −0.018) was seen, which was in acco dance wi h he hypo hesis ha longe elome es a e associa ed wi h sho e ime o comple ion o he S oop in e e ence es . Howe e , a e co ec ions o mul iple compa isons, he associa ion wi h MMSE was no significan . Gene ic isk sco e o elome e leng h The combined e ec o he GRS on TL was −0.048 s.d. −change o TL pe allele (95% CI: −0.064, −0.032, P- alue = 4.0*10 −9 ) calcula ed using andom-e ec s me a-analysis (Supplemen a y Da a: Supplemen a y Figu e S1). The co esponding F-s a is ic was 36, indica ing ha he GRS-TL es ima e p o ided a su ficien ly s ong ins umen o u he use in IV analyses. 26 Al hough he e ogenei y was de ec ed, all coho s showed nega i e e ec sizes anging om −0.01 o −0.13 (Supplemen a y Table S1). Addi ional es s in es iga ing possible pleio opic e ec s o SNP- ai associa ions we e done and ound no e idence o such (Supplemen a y Da a). Ins umen al a iable analyses o elome e leng h and cogni i e ai s Ins umen al a iable analyses o causal associa ions o TL on cogni i e pe o mance we e conduc ed o all cogni i e ai s. Only he associa ion be ween TL and STROOP was ound o be causal (Table 2), and o each s.d.-dec ease in TL an e ec change o −0.60 in S oop sco e was de ec ed (95% CI: −1.12, −0.07, P- alue = 0.026). Howe e , he associa ion would no be significan Figu e 1. G aph desc ibing he design o he s udy. A gene ic isk sco e (GRS) o elome e leng h (TL) is used in he ins umen al a iable (IV) analysis o de e mine he p edic ed e ec o TL on di e en cogni i e ai s (IV- ai ). The Mendelian Randomiza ion design allows o calcula ion o an es ima e independen o con ounde s (C) in compa ison o he obse ed e ec es ima ed be ween TL and cogni i e ai s (TL- ai ). Telome e leng h and cogni i e pe o mance S Hägg e al 3 T ansla ional Psychia y (2017), 1 –6 a e mul iple es ing adjus men s. The di e ence in e ec sizes be ween obse a ional and causal be as o STROOP was s a is ically significan (Table 2). S a ified analyses S a ified me a-analyses we e pe o med o APOE ε4-ca ie s (n⩽2380) and ε4 non-ca ie s (n⩽5669) sepa a ely (Supplemen a y Da a). Obse a ional associa ions we e seen be ween TL and DSST in non-ca ie s (β= 0.081, 95% CI: 0.045, 0.117, P- alue = 1 × 10 −5 ) and wi h be e pe o mance o STROOP in ca ie s (β=−0.074, 95% CI: −0.140, −0.009, P- alue = 0.027) (Supplemen a y Table S4). A causal associa ion be ween long elome es and be e pe o mance o STROOP was de ec ed amongs APOE ε4-ca ie s (β=−0.70, 95% CI: −1.33, −0.07, P- alue = 0.030), al hough he finding would no hold a e mul iple es ing adjus men s. No o he causal e ec s o TL on cogni i e ai s we e seen in ei he ca ie s o non-ca ie s (Supplemen a y Table S6). Replica ion analyses In eplica ion e o s, wo-sample MR analyses we e ca ied ou using summa y s a is ics om CHARGE GWAS on gene al cogni i e unc ion, DSST and STROOP. Da a om he TL GWAS we e used o he gene ic ins umen (Supplemen a y Da a). Resul s p o ided e idence o a causal associa ion be ween longe leukocy e TL and be e gene al cogni i e unc ion (β= 0.086 pe s.d.-inc ease o TL, 95% CI: 0.016–0.156, P- alue = 0.016, Table 2) and be e DSST Table 2. Associa ions be ween p edic ed and obse ed elome e leng h and di e en cogni i e ai s Cogni i e ai ENGAGE a CHARGE P edic ed e ec (IV- ai ) P edic ed e ec (IV- ai ) NBe a (95% CI) P- alue NBe a (95% CI) P- alue MMSE 7066 0.291 (−0.05, 0.631) 0.095 DSST 4419 −0.016 (−0.437, 0.405) 0.941 32 088 2.021 b 0.043 BLOCK 5001 −0.192 (−0.594, 0.21) 0.349 MEMORY 13 060 −0.022 (−0.264, 0.22) 0.860 STROOP 2940 −0.598 (−1.125, −0.072) 0.026 7726 −0.780 b 0.435 Gene al 12 283 0.039 (−0.229, 0.306) 0.778 53 949 0.086 (0.016, 0.156) 0.016 Cogni i e ai Obse ed e ec (TL- ai ) Di -P- alue Be a (95% CI) P- alue MMSE 0.13 0.025 (0.002, 0.047) 0.030 DSST 0.76 0.051 (0.024, 0.077) 0.0002 BLOCK 0.34 0.004 (−0.024, 0.032) 0.781 MEMORY 0.79 0.011 (−0.005, 0.028) 0.187 STROOP 0.04 −0.053 (−0.087, −0.018) 0.003 Gene al 0.89 0.020 (−0.008, 0.047) 0.156 Abb e ia ions: BLOCK, Block-design es ; CI, confidence in e al; Di -P- alue, es s o di e ence in es ima o s be ween obse ed and p edic ed e ec s; DSST, Digi -symbol subs i u ion es ; Gene al, Gene al cogni i e pe o mance; IV, ins umen al a iable; MEMORY, Ve bal memo y o Pic u e lea ning es ; MMSE, Mini-men al s a e exam; STROOP, S oop colo wo d ask in e e ence sco e; TL, elome e leng h. a All models a e adjus ed o age g oup and sex. No adjus men s o mul iple es ing ha e been done on he epo ed P- alues. b Z-sco es, e ec sizes a e missing. Figu e 2. Obse ed e ec s be ween elome e leng h and cogni i e ai s. Fixed-e ec s me a-analyses we e pe o med ac oss coho s and domains o all cogni i e ai s. Significan e ec s (s.d.-change in cogni i e sco e o an s.d.-change in elome e leng h (TL)) we e ound o (a). digi symbol subs i u ion es apping p ocessing speed (DSST), (b). Mini-men al s a e exam (MMSE), and (c). S oop in e e ence sco e apping execu i e unc ioning (STROOP). All models we e adjus ed o age g oup, sex and s udy-specific co a ia es. Telome e leng h and cogni i e pe o mance S Hägg e al 4 T ansla ional Psychia y (2017), 1 –6 sco ing (Z-sco e = 2.02, P- alue = 0.043, Table 2). No e idence o a causal e ec by TL on STROOP was ound (Table 2). DISCUSSION In he p esen s udy, we p o ide e idence o obse a ional and causal associa ions be ween longe elome es and be e cogni- i e pe o mance. By conduc ing a la ge me a-analysis o 12 coho s om Eu opean ances y popula ions wi h measu ed elome es and assessmen s o cogni i e unc ion, we we e able o obse e associa ions be ween TL and be e sco ing on MMSE, DSST and STROOP. Mo eo e , APOE ε4-ca ie s seemed o ha e di e en e ec s o he obse ed associa ion wi h wo se pe o mance in DSST bu be e in STROOP. The associa ion be ween longe elome es and as e comple ion o he S oop in e e ence es was also ound o be significan in causal analysis o all indi iduals and in APOE ε4-ca ie s only. Howe e , none o he significan causal associa ions de ec ed o STROOP passed mul iple es ing co ec ions. Hence, in line wi h his, using summa y da a om CHARGE, we ound suppo o a causal associa ion om TL on gene al cogni i e unc ion and DSST, bu no on STROOP. In he biology o aging, elome e leng h has long been conside ed as a bioma ke eflec ing he unde lying cellula s a e. Recen ly, howe e , se e al esea ch pape s ha e p esen ed e idence o elome es being in ol ed in he p ocess o cellula senescence causing inc eased isk o disease. 5,16,27 Mo eo e , o he s udies sugges elome es migh e en elonga e in soma ic cells o main ain cellula s abili y, 21,28,29 al hough his phenom- enon could be pa ly explained by leukocy e u no e o imp ecise measu emen s. Ne e heless, elome e biology has implica ions o he aging p ocesses and s udies a e wa an ed o elucida e he ull complexi y. Wi h his e o we demons a e se e al obse a ional associa- ions be ween TL and cogni i e ai s, bo h confi ming ea lie s udies and p esen ing new links. Gene al cogni i e unc ion is usually ope a ionalized as a composi e sco e ac oss a numbe o di e se cogni i e domains cap u ing mos o he cogni i e a ia ion. 18 As an o e all measu e o cogni ion i also p edic s mo ali y; 30 likewise, he leng h o elome es can be used o p edic mo ali y. 31,32 Thus, i bo h gene al cogni i e unc ion and TL se e as alid bioma ke s o aging, associa ions be ween hese ma ke s a e expec ed, al hough causali y needs o be u he in es iga ed. In he ENGAGE da a (N= 12 283), we we e no able o de ec any associa ion be ween gene al cogni i e unc ion and TL, bu using he CHARGE summa y da a (N= 53 949) we p o ided e idence o a causal associa ion. I is likely ha he ENGAGE analysis was low in powe ; e ec sizes had o e lapping CI’s. A possible biological mechanism o a causal associa ion could be explained by o e all body ail y; he leng hs o elome es a e impo an o main aining cellula s abili y a old age and hence also impo an o biological aging p ocesses such as decline in cogni i e pe o mance. 1 Causal links ha e also been demons a ed using animal models. A mouse wi h elome ase deficiency, exp essing accele a ed aging wi h mal unc ioning issue epai and impai ed neu ological unc ion, had es o ed unc ions again upon elome ase eac i a ion. 33 The DSST es assesses p ocessing speed equi ed o ansla e a code o symbols and digi s as as as possible in a gi en ime ame. P ocessing speed has been demons a ed o ha e a s eady, almos linea decline wi h ad ancing age, and i s decline leads o he o ms o cogni i e decline. 34,35 Hence, in ligh o his i is no su p ising ha we, and o he s, 3 de ec a ai ly s able obse a ional associa ion o longe elome es and be e DSST sco ing. The MR analysis did no indica e a causal associa ion in ou samples (N= 4419); on he o he hand, when inc easing powe using CHARGE da a (N= 32 088) we we e able o find suppo o a posi i e causal ela ionship om longe TL on DSST sco ing. Mo eo e , APOE ε4 non-ca ie s sco ed be e on he es wi h a la ge e ec size seen in obse a ional analysis om TL on DSST. Thus, as APOE geno ype is impo an o elucida ing di e en isk g oups o many age- ela ed pheno ypes, i is possible ha i applies o TL dynamics and cogni i e pe o mance as well. Ya e e al. 3 showed ha longe TL a baseline ga e less longi udinal decline in MMSE, and we p esen ed c oss-sec ional e idence om obse a ional associa ions in line wi h hese findings; longe TL is consis en wi h be e MMSE sco ing. Howe e , while causal es ima es suppo hese associa ions, he CI´s we e wide and esul s did no each s a is ical significance. Un o una ely, CHARGE da a on MMSE we e no a ailable o eplica ion analysis. The STROOP a iable aps he execu i e unc ioning by a combined colo and wo d es o be comple ed as quickly as possible. To he bes o ou knowledge, he e has been only one ea lie small s udy in es iga ing baseline and a i ion TL associa ions wi h execu i e unc ioning, wi h inconclusi e esul s. 8 Ou ENGAGE analysis included 2940 indi iduals whe e we ound bo h an obse a ional and causal associa ion be ween longe elome es and as e comple ion o he S oop es . The la ge e ec size di e ence was howe e dis u bing and no explained by addi ional adjus men s o smoking and alcohol (Supplemen a y Da a). Fu he , causal associa ions did no hold a e mul iple es ing co ec ions and when using he wo-sample app oach including he la ge CHARGE da a (N= 7726) we could no eplica e he associa ion, al hough he e ec s we e in he same di ec ion. Hence, i is possible ha he STROOP finding obse ed in he ENGAGE da a is a alse disco e y. In addi ion, he s a ified analyses by APOE ε4 geno ype ound ε4-ca ie s o pe o m be e , which is con adic o y o wha would be expec ed. The s eng h o his s udy is he e o o combining mul iple Eu opean coho s wi h TL, cogni i e and gene ic da a a ailable as well as APOE geno ype. By doing so, we we e able o de ec pa e ns o associa ions o di e en cogni i e ai s ha would no be possible o find in single s udy analyses. Mo eo e , we included la ge-scale CHARGE GWAS da a se s o pe o m wo- sample MR analyses as eplica ion. The weaknesses o he s udy include gene alizabili y, as he analyses we e pe o med solely in Eu opean ances y popula ions, and some o he coho s we e included in bo h ENGAGE and CHARGE analyses as desc ibed in he supplemen . Mo eo e , he e ogenei y due o di e en issues used (blood and sali a) and lab-specific echnical a iances (TL es ima es om all 12 coho s we e done in fi e di e en labs) may ha e d i en he esul s owa d null. Ano he limi a ion ela es o he h ee assump ions o conduc ing MR s udies, which ha e been conside ed as ollows: (1) a s ong gene ic ins umen should be demons a ed be ween he GRS and TL (GRS-TL) which we ha e (F-s a is ic = 36); (2) he gene ic ins umen should no be con ounded by e.g., age and sex (unlikely conside ing he andomiza ion o alleles a concep ion); and (3) pleio opic e ec s (when o he pa hways exis om he TL SNPs o he ou come (cogni i e ai ) wi hou going h ough he in e media e pheno- ype (TL)) om he SNPs included in he GRS should be uled ou as much as possible. We did no find e idence o pleio opic e ec s (Supplemen a y Da a). Finally, also wo h men ioning a e he ela i ely weak P- alues o some o he associa ions. The obse a ional associa ion o MMSE would no hold a e Bon e oni co ec ion o he P- alue o he six cogni i e ai s es ed, likewise o he causal associa ions ound o STROOP. To conclude, his s udy demons a es an o e all pic u e o he impo ance o biological aging p ocesses such as TL dynamics o main aining cogni i e unc ion h oughou li e. Mo e specifically, we we e able o show obse a ional as well as causal associa ions be ween TL and di e en cogni i e ai s ha ha e ne e been elucida ed be o e. Hence, he cu en e o p esen s new impo an pieces o e idence o he con inued sea ch o a Telome e leng h and cogni i e pe o mance S Hägg e al 5 T ansla ional Psychia y (2017), 1 –6 be e unde s anding o he biology behind aging and he ac o s explaining heal hy aging. CONFLICT OF INTEREST The au ho s decla e no conflic o in e es . ACKNOWLEDGMENTS Eu opean Ne wo k o Gene ic and Genomic Epidemiology (ENGAGE) wi h FP7- HEALTH-F4-2007 g an ag eemen n . 201413. The Coho s o Hea and Aging Resea ch in Genomic Epidemiology Conso ium (CHARGE) which is suppo ed in pa by he Na ional Hea , Lung and Blood Ins i u e g an HL105756 and he neu oCHARGE cogni i e wo king g oup h ough he Na ional Ins i u e on Aging g an AG033193. All coho -specific acknowledgmen s a e ound in he Supplemen a y Da a. REFERENCES 1 Blackbu n EH, Epel ES, Lin J. Human elome e biology: a con ibu o y and in e - ac i e ac o in aging, disease isks, and p o ec ion. Science 2015; 350: 1193–1198. 2 Wikg en M, Ka lsson T, Lind J, Nilb ink T, Hul din J, Sleege s K e al. Longe leukocy e elome e leng h is associa ed wi h smalle hippocampal olume among non-demen ed APOE epsilon3/epsilon3 subjec s. PLoS ONE 2012; 7: e34292. 3 Ya e K, Lindquis K, Kluse M, Caw hon R, Ha is T, Hsueh WC e al. Telome e leng h and cogni i e unc ion in communi y-dwelling elde s: findings om he Heal h ABC S udy. 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To iew a copy o his license, isi h p://c ea i ecommons.o g/licenses/ by/4.0/ © The Au ho (s) 2017 Supplemen a y In o ma ion accompanies he pape on he T ansla ional Psychia y websi e (h p://www.na u e.com/ p) Telome e leng h and cogni i e pe o mance S Hägg e al 6 T ansla ional Psychia y (2017), 1 –6