Predictors of Memory in Healthy Aging: Polyunsaturated Fatty Acid Balance and Fornix White Matter Integrity
Zamroziewicz Marta K.1,2,3, Paul Erick J.1,2, Zwilling Chris E.1,2, Barbey Aron K.1,2,3,4,5,6,7,*
1Decision Neuroscience Laboratory, University of Illinois Urbana-Champaign, Urbana, IL, USA. 2Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, IL, USA. 3Neuroscience Program, University of Illinois Urbana-Champaign, Urbana, IL, USA. 4Department of Psychology, University of Illinois Urbana-Champaign, Urbana, IL, USA. 5Carle Neuroscience Institute, Carle Foundation Hospital, Urbana, IL, USA. 6Department of Internal Medicine, University of Illinois Urbana-Champaign, Urbana, IL, USA. 7Institute for Genomic Biology, University of Illinois Urbana-Champaign, Champaign, IL, USA
Recent evidence demonstrates that age and disease-related decline in cognition depends not only upon degeneration in brain structure and function, but also on dietary intake and nutritional status. Memory, a potential preclinical marker of Alzheimer’s disease, is supported by white matter integrity in the brain and dietary patterns high in omega-3 and omega-6 polyunsaturated fatty acids. However, the extent to which memory is supported by specific omega-3 and omega-6 polyunsaturated fatty acids, and the degree to which this relationship is reliant upon microstructure of particular white matter regions is not known. This study therefore examined the cross-sectional relationship between empirically-derived patterns of omega-3 and omega-6 polyunsaturated fatty acids (represented by nutrient biomarker patterns), memory, and regional white matter microstructure in healthy, older adults. We measured thirteen plasma phospholipid omega-3 and omega-6 polyunsaturated fatty acids, memory, and regional white matter microstructure in 94 cognitively intact older adults (65 to 75 years old). A three-step mediation analysis was implemented using multivariate linear regressions, adjusted for age, gender, education, income, depression status, and body mass index. The mediation analysis revealed that a mixture of plasma phospholipid omega-3 and omega-6 polyunsaturated fatty acids is linked to memory and that white matter microstructure of the fornix fully mediates the relationship between this pattern of plasma phospholipid polyunsaturated fatty acids and memory. These results suggest that memory may be optimally supported by a balance of plasma phospholipid omega-3 and omega-6 polyunsaturated fatty acids through the preservation of fornix white matter microstructure in cognitively intact older adults. This report provides novel evidence for the benefits of plasma phospholipid omega-3 and omega-6 polyunsaturated fatty acid balance on memory and underlying white matter microstructure.
Zamroziewicz Marta K.,Paul Erick J.,Zwilling Chris E., et al. Predictors of Memory in Healthy Aging: Polyunsaturated Fatty Acid Balance and Fornix White Matter Integrity[J]. Aging and disease,
2017, 8(4): 372-383.
The primary requirement for mediation is a significant indirect mediation effect, defined as the effect of the independent variable (nutrient biomarker pattern) through the mediation (fractional anisotropy in white matter regions) on the dependent variable (memory).
Plasma phospholipid PUFAs
α-linolenic acid (18:3n-3)
Eicosadienoic acid (20:2n-6)
Eicosatrienoic acid (20:3n-3)
Linoleic acid (18:2n-6)
Docosadienoic acid (22:2n-6)
Adrenic acid (22:4n-6)
Arachidonic acid (20:4n-6)
γ-linolenic acid (18:3n-6)
Dihomo-γ-linolenic acid (20:3n-6)
Stearidonic acid (18:4n-3)
Eicosapentaenoic acid (20:5n-3)
Docosahexaenoic acid (22:6n-3)
Docosapentaenoic acid (22:5n-3)
Percent variance explained by each NBP
Cumulative percent variance explained with each extraction
Figure 2. Scree plot: inspection of the scree plot visually indicates which nutrient biomarker patterns explain the most variability in the data. A change in curvature, or inflection point, occurred after the third component, or nutrient biomarker pattern, was extracted. Thus, three components explained most variability in the data.
Figure 3. Mediation path a: linear regression modeling showed that nutrient biomarker pattern 1 (LCPUFA) positively and reliably associated with fornix fractional anisotropy (=0.042, p<0.001).
Corpus callosum genu
Corpus callosum body
Corpus callosum splenium
Cerebral peduncle R
Cerebral peduncle L
Anterior limb of internal capsule R
Anterior limb of internal capsule L
Posterior limb of internal capsule R
Posterior limb of internal capsule L
Retrolenticular part of internal capsule R
Retrolenticular part of internal capsule L
Anterior corona radiata R
Anterior corona radiata L
Superior corona radiata R
Superior corona radiata L
Posterior corona radiata R
Posterior corona radiata L
Posterior thalamic radiation R
Posterior thalamic radiation L
Sagittal stratum R
Sagittal stratum L
External capsule R
External capsule L
Cingulate part of cingulum R
Cingulate part of cingulum L
Hippocampal part of cingulum R
Hippocampal part of cingulum L
Superior longitudinal fasciculus R
Superior longitudinal fasciculus L
Superior fronto-occipital fasciculus R
Superior fronto-occipital fasciculus L
Uncinate fasciculus R
Uncinate fasciculus L
Table 3 Nutrient biomarker patterns associated with regional fractional anisotropy.
Composite memory score
Table 4 Nutrient biomarker patterns associated with memory.
Figure 4. Mediation path c: linear regression modeling showed that nutrient biomarker pattern 1 (LCPUFA) positively and reliably associated with memory (=0.320, p=0.003).
Figure 5. Mediation model statistics: nutrient biomarker pattern 1 (LCPUFA) positively associated with fractional anisotropy of the fornix (path a). LCPUFA positively associated with memory (path c). The indirect pathway of mediation (i.e., the effect of LCPUFA through fornix fractional anisotropy on memory; path a-b) was statistically significant. The direct pathway of mediation (i.e., the effect of LCPUFA on memory, accounting for fornix fractional anisotropy; path c’) was not significant. Therefore, fornix fractional anisotropy fully mediated the relationship between LCPUFA and memory.
Zamroziewicz MK, Barbey AK (2016). Nutritional Cognitive Neuroscience: Innovations for Healthy Brain Aging. Front Neurosci, 10:1-10.
Cunnane SC, Plourde M, Pifferi F, Bégin M, Féart C, Barberger-Gateau P (2009). Fish, docosahexaenoic acid and Alzheimer’s disease. Prog Lipid Res, 48:239-56.
Gu Y, Vorburger RS, Gazes Y, Habeck CG, Stern Y, Luchsinger JA,et al. (2016). White matter integrity as a mediator in the relationship between dietary nutrients and cognition in the elderly. Ann Neurol, 79:1014-25.
Eskelinen MH, Ngandu T, Helkala E-L, Tuomilehto J, Nissinen A, Soininen H,et al. (2008). Fat intake at midlife and cognitive impairment later in life: a population-based CAIDE study. Int J Geriatr Psychiatry, 23:741-7.
Caselli RJ, Graff-Radford NR, Reiman EM, Weaver A, Osborne D, Lucas J,et al. (1999). Preclinical memory decline in cognitively normal apolipoprotein E- 4 homozygotes. Neurology, 53:201-201.
Carlesimo GA, Cherubini A, Caltagirone C, Spalletta G (2010). Hippocampal mean diffusivity and memory in healthy elderly individuals: A cross-sectional study. Neurology, 74(3):194-200.
Mori S, Zhang J (2006). Principles of Diffusion Tensor Imaging and Its Applications to Basic Neuroscience Research. Neuron, 51(5):527-39.
Pagani E, Agosta F, Rocca MA, Caputo D, Filippi M (2008). Voxel-based analysis derived from fractional anisotropy images of white matter volume changes with aging. Neuroimage, 41(3):657-67.
Bennett IJ, Madden DJ, Vaidya CJ, Howard DV., Howard JH (2010). Age-related differences in multiple measures of white matter integrity: A diffusion tensor imaging study of healthy aging. Hum Brain Mapp, 31(3):378-90.
Loef M, Walach H (2013). The Omega-6/Omega-3 Ratio and Dementia or Cognitive Decline: A Systematic Review on Human Studies and Biological Evidence. J Nutr Gerontol Geriatr, 32:1-23.
Gómez Candela C, Bermejo López LM, Loria Kohen V (2011). Importance of a balanced omega 6/omega 3 ratio for the maintenance of health. Nutritional recommendations. Nutr Hosp, 26(2):323-9.
Folstein MF, Folstein SE, McHugh PR (1975). “Mini-mental state” A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res, 12(3):189-98.
Folch J, Lees M, Sloane Stanley GH (1957). A simple method for the isolation and purification of total lipides from animal tissues. J Biol Chem, 226:497-509.
Aryen JJ, Julkunen A, Penttila I (1992). Rapid separation of serum lipids for fatty acid analysis by a single aminopropyl column. J Lipid Res, 33:1871-6.
Morrison WR, Smith LM (1964). Preparation of fatty acid methyl esters and dimethylacetals from lipids with boron fluoride-methanol. J Lipid Res, 55:600-8.
Tabachnick BG, Fidell LS. Using multivariate statistics. 5th ed. Upper Saddle River, NJ: Pearson Allyn & Bacon; 2007.
Kaiser HF (1970). A second generation little jiffy. Psychometrika, 35(4):401-15.
Bartlett MS (1950). Tests of significance in factor analysis. Br J Math Stat Psychol, 3:77-85.
Jolliffe I. Principal component analysis. Wiley StatsRef: Statistics Reference Online; 2014.
Wechsler D. Wechsler abbreviated scale of intelligence. San Antonio, TX: Psychol Corp; 1999.
Siedlecki KL, Honig LS, Stern Y (2009). Exploring the structure of a neuropsychological battery across healthy elders and those with questionable dementia and Alzheimer’s disease. Neuropsychology, 22(3):400-11.
Smith SM, Jenkinson M, Woolrich MW, Beckmann CF, Behrens TEJ, Johansen-Berg H,et al. (2004). Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage, 23:S208-19.
Behrens TEJ, Woolrich MW, Jenkinson M, Johansen-Berg H, Nunes RG, Clare S,et al. (2003). Characterization and Propagation of Uncertainty in Diffusion-Weighted MR Imaging. Magn Reson Med, 50:1077-88.
Behrens TEJ, Berg HJ, Jbabdi S, Rushworth MFS, Woolrich MW (2007). Probabilistic diffusion tractography with multiple fibre orientations: What can we gain? Neuroimage, 34:144-55.
Smith SM, Jenkinson M, Johansen-Berg H, Rueckert D, Nichols TE, Mackay CE,et al. (2006). Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data. Neuroimage, 31(4):1487-505.
Oishi K, Zilles K, Amunts K, Faria A, Jiang H, Li X,et al. (2008). Human Brain White Matter Atlas: Identification and Assignment of Common Anatomical Structures in Superficial White Matter. Neuroimage, 43(3):447-57.
Koen JD, Yonelinas AP (2014). The Effects of Healthy Aging, Amnestic Mild Cognitive Impairment, and Alzheimer’s Disease on Recollection and Familiarity: A Meta-Analytic Review. Neuropsychol Rev, 24:332-54.
Rönnlund M, Nyberg L, Bäckman L, Nilsson L (2005). Stability, growth, and decline in adult life span development of declarative memory: Cross-sectional and longitudinal data from a population-based study. Psychol Aging, 20(1):3-18.
Hurst L, Stafford M, Cooper R, Hardy R, Richards M, Kuh D (2013). Lifetime socioeconomic inequalities in physical and cognitive aging. Am J Public Health, 103(9):1641-8.
Gallucci M, Mazzuco S, Ongaro F, DG E, Mecocci P, Cesari M,et al. (2013). Body mass index, lifestyles, physical performance and cognitive decline: the “Treviso Longeva (TRELONG)” study. J Nutr Health Aging, 17(4):378-84.
Pauls F, Petermann F, Lepach AC (2013). Gender differences in episodic memory and visual working memory including the effects of age. Memory, 21(7):857-74.
Ware JE, Snow K., Kosinski M, Gandek B. Manual and interpretation guide. Boston: The Health Institute, New England Medical Center; 1993.
Witte AV, Kerti L, Hermannstädter HM, Fiebach JB, Schreiber SJ, Schuchardt JP,et al. (2014). Long-chain omega-3 fatty acids improve brain function and structure in older adults. Cereb Cortex, 24(11):3059-68.
Zhao X, Lynch JGJr, Chen Q (2010). Reconsidering Baron and Kenny: Myths and truths about mediation analysis. J Consum Res, 37:197-206.
Preacher KJ, Hayes AF (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behav Res Methods, 40(3):879-91.
Benjamini Y, Hochberg Y (1995). Controlling the False Discovery Rate?: A Practical and Powerful Approach to Multiple Testing. J R Stat Soc, 57(1):289-300.
Pelletier A, Barul C, Féart C, Helmer C, Bernard C, Periot O,et al. (2015). Mediterranean diet and preserved brain structural connectivity in older subjects. Alzheimers Dement, 11(9):1023-31.
Moon Y, Moon WJ, Kwon H, Lee JM, Han SH (2015). Vitamin D deficiency disrupts neuronal integrity in cognitively impaired patients. J Alzheimers Dis, 45(4):1089-96.
Dror V, Rehavi M, Biton IE, Eliash S (2014). Rasagiline prevents neurodegeneration in thiamine deficient rats - A longitudinal MRI study. Brain Res, 1557:43-54.
Roy B, Trivedi R, Garg RK, Gupta PK, Tyagi R, Gupta RK (2015). Assessment of functional and structural damage in brain parenchyma in patients with vitamin B12 deficiency: A longitudinal perfusion and diffusion tensor imaging study. Magn Reson Imaging, 33(5):537-43.
Yasmin H, Aoki S, Abe O, Nakata Y, Hayashi N, Masutani Y,et al. (2009). Tract-specific analysis of white matter pathways in healthy subjects: A pilot study using diffusion tensor MRI. Neuroradiology, 51(12):831-40.
Xu J, Li Y, Lin H, Sinha R, Potenza MN (2013). Body mass index correlates negatively with white matter integrity in the fornix and corpus callosum: A diffusion tensor imaging study. Hum Brain Mapp, 34(5):1044-52.
Oishi K, Lyketsos CG. Alzheimer’s disease and the fornix (2014). Front Aging Neurosci, 6:1-9.
Salat DH, Tuch DS, Greve DN, van der Kouwe AJW, Hevelone ND, Zaleta AK,et al. (2005). Age-related alterations in white matter microstructure measured by diffusion tensor imaging. Neurobiol Aging, 26(8):1215-27.
Sinn N, Milte CM, Street SJ, Buckley JD, Coates AM, Petkov J,et al. (2012). Effects of n-3 fatty acids, EPA v. DHA, on depressive symptoms, quality of life, memory and executive function in older adults with mild cognitive impairment: a 6-month randomised controlled trial. Br J Nutr, 107(11):1682-93.
Fletcher E, Raman M, Huebner P, Liu A, Mungas D, Carmichael O,et al. (2013). Loss of Fornix White Matter Volume as a Predictor of Cognitive Impairment in Cognitively Normal Elderly Individuals. JAMA Neurol, 70(11):1389-95.
Mielke MM, Okonkwo OC, Oishi K, Mori S, Tighe S, Miller MI,et al. (2012). Fornix integrity and hippocampal volume predict memory decline and progression to Alzheimer’s disease. Alzheimers Dement, 8(2):105-13.
Skinner ER, Watt C, Besson JA, Best PV (1993). Differences in the fatty acid composition of the grey and white matter of different regions of the brains of patients with Alzheimer’s disease and control subjects. Brain, 116:717-25.
Crupi R, Marino A, Cuzzocrea S (2013). n-3 Fatty Acids: Role in Neurogenesis and Neuroplasticity. Curr Med Chem, 20:2953-63.
Zamroziewicz MK, Paul EJ, Zwilling CE, Johnson EJ, Kuchan MJ, Cohen NJ,et al. (2016). Parahippocampal cortex mediates the relationship between lutein and crystallized intelligence in healthy, older adults. Front Aging Neurosci, 8:1-9.