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Advances in late onset Alzheimer's disease susceptibility genes and their effects on brain structure and function
WANG Junxia  WU Sichu  ZHANG Xin  ZHANG Bing 

Cite this article as: Wang JX, Wu SC, Zhang X, et al. Advances in late onset Alzheimer's disease susceptibility genes and their effects on brain structure and function. Chin J Magn Reson Imaging, 2019, 10(4): 281-287. DOI:10.12015/issn.1674-8034.2019.04.009.


[Abstract] Alzheimer's disease (AD) is the most common type of dementia, which is characterized by progressive memory loss and cognitive decline. To date, APOE is the only known risk gene associated with distributed AD. With the development of genome-wide association studies and magnetic resonance imaging technology, more and more genes have been reported to be associated with AD, brain structure and function, such as Bridging integrator 1, Clusterin etc. However, the pathologic mechanism of these genes in AD is not clear. This paper reviews the action pathway of APOE and other genes and their effects on AD, brain structure and brain function.
[Keywords] alzheimer disease;genetic pathway;brain structure;brain function;magnetic resonance imaging

WANG Junxia Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing 210008, China

WU Sichu Department of Radiology, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing 210008, China

ZHANG Xin Department of Radiology, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing 210008, China

ZHANG Bing* Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing 210008, China

*Corresponding to: Zhang B, E-mail: zhangbing_nanjing@vip.163.com

Conflicts of interest   None.

ACKNOWLEDGMENTS  This work was part of Science and Technology Plan Project Social Development Fund of Jiangsu Province No. BE2016605
Received  2018-06-25
Accepted  2018-07-27
DOI: 10.12015/issn.1674-8034.2019.04.009
Cite this article as: Wang JX, Wu SC, Zhang X, et al. Advances in late onset Alzheimer's disease susceptibility genes and their effects on brain structure and function. Chin J Magn Reson Imaging, 2019, 10(4): 281-287. DOI:10.12015/issn.1674-8034.2019.04.009.

[1]
Jun G, Naj AC, Beecham GW, et al. Meta-analysis confirms CR1, CLU, and PICALM as alzheimer disease risk loci and reveals interactions with APOE genotypes. Arch Neurol, 2010, 67(12): 1473.
[2]
Gatz M, Reynolds CA, Fratiglioni L, et al. Role of genes and environments for explaining Alzheimer disease. Arch Gen Psychiatry, 2006, 63(2): 168-174.
[3]
Cacciaglia R, Molinuevo JL, Falcón C, et al. Effects of APOE-ε4 allele load on brain morphology in a cohort of middle-aged healthy individuals with enriched genetic risk for Alzheimer's disease. Alzheimers Dement, 2018, 14(7): 902-912.
[4]
Saeed U, Mirza SS, Macintosh BJ, et al. APOE-ε4 associates with hippocampal volume, learning, and memory across the spectrum of Alzheimer's disease and dementia with Lewy bodies. Alzheimers Dement, 2018, 14(9): 1137-1147.
[5]
De MM, Vallelunga A, Meneghello F, et al. ApoE ε4 allele relateted alterations in hippocampal connectivity in early Alzheimer's disease support memory performance. Current Alzheimer Res, 2017, 14(7): 766-777.
[6]
Rodriguez E, Mateo I, Infante J, et al. Cholesteryl ester transfer protein (CETP) polymorphism modifies the Alzheimer's disease risk associated with APOE epsilon4 allele. J Neurol, 2006, 253(2): 181-185.
[7]
Murphy EA, Roddey JC, McEvoy LK, et al. CETP polymorphisms associate with brain structure, atrophy rate, and Alzheimer’s disease risk in an APOE-dependent manner. Brain Imaging Behav, 2012, 6(1): 16-26.
[8]
Salminen LE, Schofield PR, Pierce KD, et al. Genetic markers of cholesterol transport and gray matter diffusion: a preliminary study of the CETP I405V polymorphism. J Neural Transm (Vienna), 2015, 122(11): 1581-1592.
[9]
Warstadt NM, Dennis EL, Jahanshad N, et al. Serum cholesterol and variant in cholesterol-related gene CETP predict white matter microstructure. Neurobiol Aging, 2014, 35(11): 2504-2513.
[10]
Jff A, Dos Santos LR, Trancozo M, et al. Updated meta-analysis of BIN1, CR1, MS4A6A, CLU, and ABCA7 variants in Alzheimer's disease. J Mol Neurosci, 2018, 64(3): 471-477.
[11]
Bertram L, Mcqueen MB, Mullin K, et al. Systematic meta-analyses of Alzheimer disease genetic association studies: the AlzGene database. Nature Genetics, 2007, 39(1): 17.
[12]
Lancaster TM, Brindley LM, Tansey KE, et al. Alzheimer's disease risk variant in CLU is associated with neural inefficiency in healthy individuals. Alzheimers Dement, 2015, 11(10): 1144-1152.
[13]
Ye Q, Su F, Shu H, et al. Shared effects of the clusterin gene on the default mode network among individuals at risk for Alzheimer's disease. Cns Neuroscience & Therapeutics, 2017, 23(5): 395.
[14]
Buggia-Prévot V, Fernandez CG, Riordan S, et al. Axonal BACE1 dynamics and targeting in hippocampal neurons: a role for Rab11 GTPase. Mol Neurodegener, 2014, 9(1): 1-18.
[15]
Burggren AC, Mahmood Z, Harrison TM, et al. Hippocampal thinning linked to longer TOMM40 poly-T variant lengths in the absence of the APOE ε4 variant. Alzheimers Dement, 2017, 13(7): 739-748.
[16]
Johnson SC, La Rue A, Hermann BP, et al. The effect of TOMM40 poly-T length on gray matter volume and cognition in middle-aged persons with APOE ε3/ε3 genotype. Alzheimers Dement, 2011, 7(4): 456-465.
[17]
Laczó J, Andel R, Vlcek K, et al. The effect of TOMM40 on spatial navigation in amnestic mild cognitive impairment. Alzheimers Dement, 2013, 9(4Suppl): 464.
[18]
Feng L, Liao Y, He J, et al. Plasma long non-coding RNA BACE1 as a novel biomarker for diagnosis of Alzheimer disease. BMC Neurology, 2018, 18(1): 4.
[19]
Timmers M, Barão S, Van Broeck B, et al. BACE1 dynamics upon inhibition with a BACE inhibitor and correlation to downstream Alzheimer's disease markers in elderly healthy participants. J Alzheimers Dis, 2017, 56(4): 1437-1449.
[20]
Tsai A, Huang C, Yang AC, et al. Association of BACE1 gene polymorphism with cerebellarvolume but not cognitive function in normal individuals. Dement Geriatr Cogn Dis Extra, 2012, 2(1): 632-637.
[21]
Ewers M, Cheng X, Zhong Z, et al. Increased CSF-BACE1 activity associated with decreased hippocampus volume in Alzheimer's disease. J Alzheimers Dis, 2011, 25(25): 373-381.
[22]
Karch CM, Goate AM. Alzheimer's disease risk genes and mechanisms of disease pathogenesis. Biol Psychol, 2015, 77(1): 43-51.
[23]
Ubelmann F, Burrinha T, Salavessa L, et al. Bin1 and CD2AP polarise the endocytic generation of beta-amyloid. EMBO Rep, 2017, 18(1): 102-122.
[24]
Wang HF, Wan Y, Hao XK, et al. Bridging integrator 1 (BIN1) genotypes mediate Alzheimer's disease risk by altering neuronal degeneration. J Alzheimers Dis, 2016, 52(1): 179-190.
[25]
Li J, Wang H, Zhu X, et al. GWAS-linked loci and neuroimaging measures in Alzheimer's disease. Mol Neurobiol, 2017, 54(1): 146-153.
[26]
Chauhan G, Adams HHH, Bis JC, et al. Association of Alzheimer disease GWAS loci with MRI-markers of brain aging. Neurobiol Aging, 2015, 36(4): 7-16.
[27]
Zhang X, Yu J, Li J, et al. Bridging integrator 1 (BIN1) genotype effects on working memory, hippocampal volume, and functional connectivity in young healthy individuals. Neuropsychopharmacology, 2015, 40(7): 1794-1803.
[28]
Bai F, Shi Y, Yuan Y, et al. Association of a GSK-3Î2 polymorphism with brain resting-state function in amnestic-type mild cognitive impairment. J Alzheimers Dis, 2012, 32(2): 387-396.
[29]
Liu M, Huang C, Yang AC, et al. Catechol-O-methyltransferase val158Met polymorphism on the relationship between white matter hyperintensity and cognition in healthy people. PLoS One, 2014, 9(2): e88749.
[30]
Cerasa A, Gioia MC, Labate A, et al. Impact of catechol-O- methyltransferase Val(108/158) Met genotype on hippocampal and prefrontal gray matter volume. Neuroreport, 2008, 19(4): 405-408.
[31]
Watanabe K, Kakeda S, Yoshimura R, et al. Genetic variation in the catechol-O-methyl transferase val108/158Met is linked to the caudate and posterior cingulate cortex volume in healthy subjects: Voxel-based morphometry analysis of brain magnetic resonance imaging. PLoS One, 2015, 10(11): e142862.
[32]
Jaspar M, Manard M, Dideberg V, et al. Influence of COMT genotype on antero-posterior cortical functional connectivity underlying interference resolution. Cerebral Cortex, 2016, 26(2): 498.
[33]
Zhang X, Li J, Qin W, et al. The catechol-o-methyltransferase val(158) met polymorphism modulates the intrinsic functional network centrality of the parahippocampal cortex in healthy subjects. Scientific Reports, 2015, 5: 10105.
[34]
Mattay VS, Goldberg TE, Fera F, et al. Catechol O-methyltransferase val158-met genotype and individual variation in the brain response to amphetamine. Proc Natl Acad Sci U S A, 2003, 100(10): 6186.
[35]
Xu Q, Fu J, Liu F, et al. Left parietal functional connectivity mediates the association between COMT rs4633 and verbal intelligence in healthy adults. Front Neurosci, 2018, 12: 233.
[36]
Persson J, Rieckmann A, Kalpouzos G, et al. Influences of a DRD2 polymorphism on updating of long-term memory representations and caudate BOLD activity: magnification in aging. Human Brain Mapping, 2015, 36(4): 1325-1334.
[37]
Stelzel C, Basten U, Montag C, et al. Frontostriatal involvement in task switching depends on genetic differences in d2 receptor density. J Neurosci, 2010, 30(42): 14205-14212.
[38]
Markett S, de Reus MA, Reuter M, et al. Variation on the dopamine D2 receptor gene (DRD2) is associated with basal ganglia-to-frontal structural connectivity. Neuro Image, 2017, 155: 473-479.
[39]
Forde NJ, Ronan L, Suckling J, et al. Structural neuroimaging correlates of allelic variation of the BDNF val66met polymorphism. Neuroimage, 2014, 90(8): 280-289.
[40]
Mueller SC, Aouidad A, Gorodetsky E, et al. Gray matter volume in adolescent anxiety: An impact of the brain-derived neurotrophic factor Val66Met polymorphism. J Am Acad Child Adolesc Psychiatry, 2013, 52(2): 184-195.
[41]
Liu M, Huang C, Chen M, et al. Effect of the BDNF Val66Met polymorphism on regional gray matter volumes and cognitive function in the Chinese population. Neuromolecular Med, 2014, 16(1): 127-136.
[42]
Chen CC, Chen CJ, Wu D, et al. BDNF Val66Met polymorphism on functional MRI during n-back working memory tasks. Medicine, 2015, 94(42): e1586.
[43]
Sambataro F, Murty VP, Lemaitre HS, et al. BNDF modulates normal human hippocampal ageing. Molecular Psychiatry, 2010, 15(2): 116.
[44]
Jasińska KK, Molfese PJ, Kornilov SA, et al. The BDNF Val66Met polymorphism is associated with structural neuroanatomical differences in young children. Behav Brain Res, 2017, 328: 48.
[45]
Marusak HA, Kuruvadi N, Vila AM, et al. Interactive effects of BDNF Val66Met genotype and trauma on limbic brain anatomy in childhood. Eur Child Adolesc Psychiatry, 2015, 25(5): 509-518.
[46]
Hashimoto T, Fukui K, Takeuchi H, et al. Effects of the BDNF Val66Met polymorphism on gray matter volume in typically developing children and adolescents. Cereb Cortex, 2016, 26(4): 1795-1803.

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