Two recent studies examine the effect of early life brain function on late-life risk for Alzheimer’s disease. On September 7 in the new, open-access journal JAMA Network Open, scientists led by Susan Lapham, American Institutes for Research, Washington, D.C., claim that adolescent girls who have trouble remembering words are more likely to develop AD and related disorders (ADRD) in older age, while for boys it is poor/weak mechanical reasoning that puts them at risk. In the second paper, posted to bioRχiv on September 19, scientists led by Gibran Hemani and Neil Davies, University of Bristol, U.K., describe how they used genomic markers to tease apart the influence of intelligence versus learning on the risk for AD. Their data suggest the former protects most, but that education can help. Both papers lend support to the theory of cognitive reserve.
- Specific cognitive domains reduce AD risk.
- So does general intelligence but not educational attainment.
- Education improves intelligence, so remains a plausible target for prevention.
“These two studies couldn’t be more different in their approach,” first author Emma Anderson at Bristol told Alzforum.
“The fact that we are essentially coming up with the same answer [that IQ is protective against Alzheimer’s] provides confidence that the associations we are seeing are more likely to be causal and could guide interventions,” she said.
Studies that track a person’s cognitive function from youth to old age are rare. Two, the 1932 Scottish Mental Survey Cohort of 11-year-olds and the Nun Study, which included novices entering a convent as young women, have found that poor cognitive function in early life associated with a higher risk of dementia (Snowdon et al., 1996; Russ et al., 2017). However, no study had examined how performance in multiple cognitive domains related to disease.
Detailed in the JAMA Network Open paper, first author Alison Huang and colleagues used the Project Talent-Medicare linked data set, created by Lapham’s group, which links the records of high school students tested in 1960 with their Medicare records 50 years later (Huang et al., 2018). As part of Project Talent, 377,016 students from 1,225 secondary schools in the U.S. underwent detailed tests that probed general cognitive ability, language skills, perception, visualization, and mathematics, as well as complex intellectual aptitudes such as creativity and abstract reasoning. Huang pored over these same people’s Medicare claims and expenditures in 2012 and 2013. After she excluded enrollees with unreliable test answers in high school, or incomplete claims data, 43,014 men and 42,749 women remained. They ranged in age from 66 to 73. Compared with the general Medicare beneficiary pool, the group had more white people and fewer African-Americans.
A total of 1,239 men and 1,416 women developed ADRD—2.9 and 3.3 percent, respectively. For every standard deviation disadvantage in mechanical reasoning skills—meaning trouble predicting outcomes involving forces such as gravity or simple machines—adolescent boys stood a 17 percent higher chance of developing ADRD in old age. For women, the biggest childhood predictor was memory for novel words—meaning the ability to memorize nonsense words that corresponded to English ones (e.g., tree=KWU). In that test, for every standard deviation less in score, both boys and girls had an average 16 percent greater risk of ADRD when they were older. “A few specific measures of cognition (mechanical reasoning and memory for words) seem to have similar predictive power as IQ and general cognition,” co-author Kiersten Strombotne of the American Institutes for Research wrote to Alzforum.
Almost all other cognitive domains trended in the same direction, meaning poor performance tended to increase risk. General intelligence measures predicted disease just as well as, or slightly better than, the cognitive domain tests, with low IQ increasing odds for AD for both men and women by 17 percent, and poor general academic aptitude increasing the odds by 18 or 19 percent.
“The implication of the findings is that early life performance on cognitive tests could be used to identify potential at-risk populations who might especially benefit from interventions aimed at modifying their dementia risk, such as those promoting social/mental stimulation,” wrote Serhiy Dekhtyar, Karolinska Institutet, Stockholm, to Alzforum. He pointed out, along with the authors, that the sample was relatively young to have ADRD, and that diagnoses came from Medicare claims, not clinical assessments, meaning many cases could have been missed, though it is unclear how that would affect the findings.
Yaakov Stern, Columbia University, New York, praised the authors for focusing on data collected during adolescence. “Most studies have looked at features such as education or IQ ascertained much later in life,” he wrote to Alzforum. However, he cautioned against overinterpreting the results. “It is hard to draw much more from these findings than further support for the cognitive reserve hypothesis,” he wrote. “I would be cautious about suggesting that specific cognitive domains are more predictive than others or import more reserve. Better performance on many of these tasks might simply be related to higher IQ or greater academic aptitude.”
Nature vs. Nurture
In the bioRχiv paper, Anderson and colleagues used Mendelian randomization to correlate intelligence and education with risk for AD. This genetics-based technique takes advantage of single-nucleotide polymorphisms (SNPs) in the genome that serve as proxies for a specific environmental exposure, such as educational attainment. Since SNPs are unaffected by personal behavior or environmental factors like socioeconomic status, researchers can examine their effects on a disease while avoiding such bias. Because the genetic code is set at birth, Mendelian randomization also avoids making correlations that arise from reverse causation—where a disease causes an effect, rather than the other way around.
Anderson and colleagues wanted to know if the correlation between education and dementia was due to more schooling or because the better-educated people were more intelligent to begin with and sought out more schooling (Ritchie and Tucker-Drob, 2018; Richards and Sacker, 2011). For their Mendelian randomization, they started by searching for SNPs that associate with either intelligence or educational attainment. For the latter, they reanalyzed a meta-analysis of genome-wide association studies (GWAS) of educational attainment, which had included 293,723 genomes (Okbay et al., 2016). They found162 SNPs associated with the number of years a person stayed in school. While it’s unclear what many of these SNPs do, Anderson said that some are thought to be linked to neuronal function, such as myelin sheath maintenance, while others are thought to be associated with personality traits that may make someone more or less likely to stay longer in school. For intelligence, they analyzed data from the Multi-Trait Analysis of GWAS, which includes 248,482 genomes. They found 194 SNPs associated with IQ (Hill et al., 2018). After excluding loci that overlapped between the two data sets, or loci that were inherited together, they ended up with 148 and 180 SNPs that associated with educational attainment and intelligence, respectively.
Before assessing the influence of these variants on risk for AD, the authors wanted to know what effect, if any, intelligence had on length of education, and vice versa. They analyzed the effect of intelligence-related variants on years of education in the educational cohort, and of education-related SNPs on IQ in the intelligence cohort. A bidirectional relationship emerged, where each partially affected the other to about the same degree. This suggests that intelligent people do achieve higher levels of education, but also that, over time, education improves intelligence. The goal was to separate out effects of intelligence from those of education, which are highly correlated.
They then assessed the association of the SNPs for educational attainment or intelligence on AD risk. To make these correlations they turned to the GWAS of AD conducted by the International Genomics of Alzheimer’s Project (IGAP), which had collated data from 17,008 AD patients and 37,154 controls. Anderson found that for each standard deviation (SD) increase in educational attainment, the risk of AD dropped 37 percent. For every one SD increase in IQ, the risk of AD went down 35 percent. If the researchers analyzed both sets of genes in a multivariable analysis, the influence of educational attainment went away after accounting for intelligence. The data suggest intelligence is the driving factor behind higher or lower AD risk, the authors wrote. “The findings make a lot of sense,” said Eric Larson, Kaiser Permanente, Seattle. “We’ve long suspected this, but it has never been shown with the kind of technique they offer. It’s a very sophisticated study with a really powerful approach,” he told Alzforum.
While the results might give the impression that schooling doesn’t matter, Anderson and colleagues found that education influences IQ, which protects against AD. For this reason, the authors still deemed education important. In other words, more years in school influence the risk of AD by making a person more intelligent. The results lend support to the possibility of cognitive intervention aimed at boosting overall intelligence, Anderson said, though it’s not clear what form that would take.
Larson thinks that what is missing from this scenario is the idea that the brain is more susceptible to environmental factors at younger ages. That means education, especially of a high quality, is likely more influential early in life, he said. He acknowledged that a study like this can’t get into that level of detail.
Deborah Blacker, Massachusetts General Hospital, Boston, was more cautious about the findings. She wondered, even with the Mendelian randomization approach, how well any genetic variants could serve as a proxy for educational attainment, which, to the extent it is not related to intelligence, depends on social class and other environmental factors. “Overall, I don't think we can meet one of the basic assumptions for Mendelian randomization [that there are no other confounding mechanisms], because we don’t understand the mechanism by which genes associated with education might affect AD risk,” she said. For example, education may protect through better cardiovascular health, a known risk factor for AD, since people with more education tend to eat more nutritious food, exercise more, and seek treatment for their cardiovascular disease. She also pointed out that since the controls and AD patients were drawn from different populations, selection bias could make the results difficult to interpret.—Gwyneth Dickey Zakaib
- Snowdon DA, Kemper SJ, Mortimer JA, Greiner LH, Wekstein DR, Markesbery WR. Linguistic ability in early life and cognitive function and Alzheimer's disease in late life. Findings from the Nun Study. JAMA. 1996 Feb 21;275(7):528-32. PubMed.
- Russ TC, Hannah J, Batty GD, Booth CC, Deary IJ, Starr JM. Childhood Cognitive Ability and Incident Dementia: The 1932 Scottish Mental Survey Cohort into their 10th Decade. Epidemiology. 2017 May;28(3):361-364. PubMed.
- Ritchie SJ, Tucker-Drob EM. How Much Does Education Improve Intelligence? A Meta-Analysis. Psychol Sci. 2018 Aug;29(8):1358-1369. Epub 2018 Jun 18 PubMed.
- Richards M, Sacker A. Is education causal? Yes. Int J Epidemiol. 2011 Apr;40(2):516-8. Epub 2010 Oct 5 PubMed.
- Okbay A, Beauchamp JP, Fontana MA, Lee JJ, Pers TH, Rietveld CA, Turley P, Chen GB, Emilsson V, Meddens SF, Oskarsson S, Pickrell JK, Thom K, Timshel P, de Vlaming R, Abdellaoui A, Ahluwalia TS, Bacelis J, Baumbach C, Bjornsdottir G, Brandsma JH, Pina Concas M, Derringer J, Furlotte NA, Galesloot TE, Girotto G, Gupta R, Hall LM, Harris SE, Hofer E, Horikoshi M, Huffman JE, Kaasik K, Kalafati IP, Karlsson R, Kong A, Lahti J, van der Lee SJ, deLeeuw C, Lind PA, Lindgren KO, Liu T, Mangino M, Marten J, Mihailov E, Miller MB, van der Most PJ, Oldmeadow C, Payton A, Pervjakova N, Peyrot WJ, Qian Y, Raitakari O, Rueedi R, Salvi E, Schmidt B, Schraut KE, Shi J, Smith AV, Poot RA, St Pourcain B, Teumer A, Thorleifsson G, Verweij N, Vuckovic D, Wellmann J, Westra HJ, Yang J, Zhao W, Zhu Z, Alizadeh BZ, Amin N, Bakshi A, Baumeister SE, Biino G, Bønnelykke K, Boyle PA, Campbell H, Cappuccio FP, Davies G, De Neve JE, Deloukas P, Demuth I, Ding J, Eibich P, Eisele L, Eklund N, Evans DM, Faul JD, Feitosa MF, Forstner AJ, Gandin I, Gunnarsson B, Halldórsson BV, Harris TB, Heath AC, Hocking LJ, Holliday EG, Homuth G, Horan MA, Hottenga JJ, de Jager PL, Joshi PK, Jugessur A, Kaakinen MA, Kähönen M, Kanoni S, Keltigangas-Järvinen L, Kiemeney LA, Kolcic I, Koskinen S, Kraja AT, Kroh M, Kutalik Z, Latvala A, Launer LJ, Lebreton MP, Levinson DF, Lichtenstein P, Lichtner P, Liewald DC, LifeLines Cohort Study, Loukola A, Madden PA, Mägi R, Mäki-Opas T, Marioni RE, Marques-Vidal P, Meddens GA, McMahon G, Meisinger C, Meitinger T, Milaneschi Y, Milani L, Montgomery GW, Myhre R, Nelson CP, Nyholt DR, Ollier WE, Palotie A, Paternoster L, Pedersen NL, Petrovic KE, Porteous DJ, Räikkönen K, Ring SM, Robino A, Rostapshova O, Rudan I, Rustichini A, Salomaa V, Sanders AR, Sarin AP, Schmidt H, Scott RJ, Smith BH, Smith JA, Staessen JA, Steinhagen-Thiessen E, Strauch K, Terracciano A, Tobin MD, Ulivi S, Vaccargiu S, Quaye L, van Rooij FJ, Venturini C, Vinkhuyzen AA, Völker U, Völzke H, Vonk JM, Vozzi D, Waage J, Ware EB, Willemsen G, Attia JR, Bennett DA, Berger K, Bertram L, Bisgaard H, Boomsma DI, Borecki IB, Bültmann U, Chabris CF, Cucca F, Cusi D, Deary IJ, Dedoussis GV, van Duijn CM, Eriksson JG, Franke B, Franke L, Gasparini P, Gejman PV, Gieger C, Grabe HJ, Gratten J, Groenen PJ, Gudnason V, van der Harst P, Hayward C, Hinds DA, Hoffmann W, Hyppönen E, Iacono WG, Jacobsson B, Järvelin MR, Jöckel KH, Kaprio J, Kardia SL, Lehtimäki T, Lehrer SF, Magnusson PK, Martin NG, McGue M, Metspalu A, Pendleton N, Penninx BW, Perola M, Pirastu N, Pirastu M, Polasek O, Posthuma D, Power C, Province MA, Samani NJ, Schlessinger D, Schmidt R, Sørensen TI, Spector TD, Stefansson K, Thorsteinsdottir U, Thurik AR, Timpson NJ, Tiemeier H, Tung JY, Uitterlinden AG, Vitart V, Vollenweider P, Weir DR, Wilson JF, Wright AF, Conley DC, Krueger RF, Davey Smith G, Hofman A, Laibson DI, Medland SE, Meyer MN, Yang J, Johannesson M, Visscher PM, Esko T, Koellinger PD, Cesarini D, Benjamin DJ. Genome-wide association study identifies 74 loci associated with educational attainment. Nature. 2016 May 11;533(7604):539-42. PubMed.
- Hill WD, Marioni RE, Maghzian O, Ritchie SJ, Hagenaars SP, McIntosh AM, Gale CR, Davies G, Deary IJ. A combined analysis of genetically correlated traits identifies 187 loci and a role for neurogenesis and myelination in intelligence. Mol Psychiatry. 2018 Jan 11; PubMed.
- Savage JE, Jansen PR, Stringer S, Watanabe K, Bryois J, de Leeuw CA, Nagel M, Awasthi S, Barr PB, Coleman JR, Grasby KL, Hammerschlag AR, Kaminski JA, Karlsson R, Krapohl E, Lam M, Nygaard M, Reynolds CA, Trampush JW, Young H, Zabaneh D, Hägg S, Hansell NK, Karlsson IK, Linnarsson S, Montgomery GW, Muñoz-Manchado AB, Quinlan EB, Schumann G, Skene NG, Webb BT, White T, Arking DE, Avramopoulos D, Bilder RM, Bitsios P, Burdick KE, Cannon TD, Chiba-Falek O, Christoforou A, Cirulli ET, Congdon E, Corvin A, Davies G, Deary IJ, DeRosse P, Dickinson D, Djurovic S, Donohoe G, Conley ED, Eriksson JG, Espeseth T, Freimer NA, Giakoumaki S, Giegling I, Gill M, Glahn DC, Hariri AR, Hatzimanolis A, Keller MC, Knowles E, Koltai D, Konte B, Lahti J, Le Hellard S, Lencz T, Liewald DC, London E, Lundervold AJ, Malhotra AK, Melle I, Morris D, Need AC, Ollier W, Palotie A, Payton A, Pendleton N, Poldrack RA, Räikkönen K, Reinvang I, Roussos P, Rujescu D, Sabb FW, Scult MA, Smeland OB, Smyrnis N, Starr JM, Steen VM, Stefanis NC, Straub RE, Sundet K, Tiemeier H, Voineskos AN, Weinberger DR, Widen E, Yu J, Abecasis G, Andreassen OA, Breen G, Christiansen L, Debrabant B, Dick DM, Heinz A, Hjerling-Leffler J, Ikram MA, Kendler KS, Martin NG, Medland SE, Pedersen NL, Plomin R, Polderman TJ, Ripke S, van der Sluis S, Sullivan PF, Vrieze SI, Wright MJ, Posthuma D. Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence. Nat Genet. 2018 Jul;50(7):912-919. Epub 2018 Jun 25 PubMed.
- Kuźma E, Hannon E, Zhou A, Lourida I, Bethel A, Levine DA, Lunnon K, Thompson-Coon J, Hyppönen E, Llewellyn DJ. Which Risk Factors Causally Influence Dementia? A Systematic Review of Mendelian Randomization Studies. J Alzheimers Dis. 2018;64(1):181-193. PubMed.
- Larsson SC, Traylor M, Malik R, Dichgans M, Burgess S, Markus HS, CoSTREAM Consortium, on behalf of the International Genomics of Alzheimer’s Project. Modifiable pathways in Alzheimer's disease: Mendelian randomisation analysis. BMJ. 2017 Dec 6;359:j5375. PubMed.
- Franzmeier N, Duering M, Weiner M, Dichgans M, Ewers M, Alzheimer's Disease Neuroimaging Initiative (ADNI). Left frontal cortex connectivity underlies cognitive reserve in prodromal Alzheimer disease. Neurology. 2017 Mar 14;88(11):1054-1061. Epub 2017 Feb 10 PubMed.
- Huang AR, Strombotne KL, Horner EM, Lapham SJ. Adolescent Cognitive Aptitudes and Later-in-Life Alzheimer Disease and Related Disorders. JAMA Netw Open. 2018 Sep 7;1(5):e181726. PubMed.
- Russ TC. Intelligence, Cognitive Reserve, and Dementia: Time for Intervention?. JAMA Netw Open. 2018 Sep 7;1(5):e181724. PubMed.
- Anderson EL, Howe LD, Wade KH, Ben-Shlomo Y, Hill WD, Deary IJ, Sanderson EC, Zheng J, Korologou-Linden R, Stergiakouli E, Smith GD, Davies NM, Hemani G. Education, intelligence and Alzheimer's disease: Evidence from a multivariable two-sample Mendelian randomization study. bioRχiv. September 19, 2018.