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SIPA1L2 as a risk factor implicated in Alzheimer's disease

  • 1.

    School of Data Science, University of Science and Technology of China, Hefei 230027, China

  • 2.

    Department of Statistics and Finance, School of Management, University of Science and Technology of China, Hefei 230026, China

  • 3.

    Department of Preventive Medicine, Shantou University Medical College, Shantou 515031, China

Cite this:
https://doi.org/10.52396/JUST-2021-0008
  • Received Date: 06 January 2021
  • Rev Recd Date: 28 January 2021
  • Publish Date: 28 February 2021
    Abstract

  • Abstract

    Alzheimer's disease(AD) is a common neurodegenerative disorder with high heritability. An increasing number of common variants have been found to be associated with AD, but these common variants can only explain a small proportion of the heritability. Theory and practice have shown that rare variants can explain the remaining heritability. We explored rare functional variants that altering susceptibility to AD among 600470 variants in 389 individuals (175 with AD and 214 with cognitively normal). Firstly, after imputing the missing genotypes on the Michigan imputation server, quality control and gene-based annotation were carried out. Secondly, the efficient resampling sequence kernel association test was performed on 311 annotated exonic variants. Finally, the underlying biological interpretations of the identified risk gene were predicted through several bioinformatics tools. The results showed that under the Bonferroni correction, the rare missense variant rs2275303 in SIPA1L2 gene was significantly associated with AD (P=6.00E-04), and its pathogenicity was verified by bioinformatics analysis. SIPA1L2 gene is expected to play an important role in the prevention, diagnosis, prognosis and treatment of AD.

    Abstract

    Alzheimer's disease(AD) is a common neurodegenerative disorder with high heritability. An increasing number of common variants have been found to be associated with AD, but these common variants can only explain a small proportion of the heritability. Theory and practice have shown that rare variants can explain the remaining heritability. We explored rare functional variants that altering susceptibility to AD among 600470 variants in 389 individuals (175 with AD and 214 with cognitively normal). Firstly, after imputing the missing genotypes on the Michigan imputation server, quality control and gene-based annotation were carried out. Secondly, the efficient resampling sequence kernel association test was performed on 311 annotated exonic variants. Finally, the underlying biological interpretations of the identified risk gene were predicted through several bioinformatics tools. The results showed that under the Bonferroni correction, the rare missense variant rs2275303 in SIPA1L2 gene was significantly associated with AD (P=6.00E-04), and its pathogenicity was verified by bioinformatics analysis. SIPA1L2 gene is expected to play an important role in the prevention, diagnosis, prognosis and treatment of AD.
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    • References(28)
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    Vrieze S I, Malone S M, Pankratz N, et al. Genetic associations of nonsynonymous exonic variants with psychophysiological endophenotypes. Psychophysiology, 2014, 51(12): 1300-1308.
    [24]
    Wang K, Li M Y, Hakonarson H. ANNOVAR: Functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Research, 2010, 38(16):e164.
    [25]
    Spilker C, Sanhueza G, Böckers T M, et al. SPAR2, a novel SPAR-related protein with GAP activity for Rap1 and Rap2. Journal of Neurochemistry, 2008, 104(1): 187-201.
    [26]
    Cathy S. Ras signaling in aging and metabolic regulation. Nutrition and Healthy Aging, 2017, 4(3): 195-205.
    [27]
    Naylor R M, Baker D J, Deursen V. Senescent cells: A novel therapeutic target for aging and age-related diseases. Clinical Pharmacology & Therapeutics, 2013, 93(1): 105-116.
    [28]
    Dimauro T, David G. Ras-induced senescence and its physiological relevance in cancer. Current Cancer Drug Targets, 2010, 10(8): 869-876.
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    [1]
    Verheijen J, Sleegers K. Understanding Alzheimer disease at the interface between genetics and transcriptomics. Trends in Genetics,2018: 34(6): 434-447.
    [2]
    Harold D, Abraham R, Hollingworth P, et al. Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer's disease. Nature Genetics, 2009, 41(10): 1088-1093.
    [3]
    Pericak-Vance M A, Bebout J L, Gaskell P C, et al. Linkage studies in familial Alzheimer disease: Evidence for chromosome 19 linkage. American Journal of Human Genetics, 1991, 48(6): 1034-1050.
    [4]
    Farrer L A, Cupples L A, Haines J L, et al. Effects of age, sex, and ethnicity on the association between apolipoprotein E genotype and Alzheimer disease: A meta-analysis. Jama, 1997, 278(16): 1349-1356.
    [5]
    Kok E H, Luoto T, Haikonen S, et al. CLU, CR1 and PICALM genes associate with Alzheimer's-related senile plaques. Alzheimer's Research & Therapy, 2011, 3(2): 12.
    [6]
    Hollingworth P, Harold D, Sims R, et al. Common variants at ABCA7, MS4A6A/MS4A4E, EPHA1, CD33 and CD2AP are associated with Alzheimer's disease. Nature Genetics, 2011, 43(5): 429-435.
    [7]
    Zuk O, Schaffner S F, Samocha K, et al. Searching for missing heritability: Designing rare variant association studies. Proceedings of the National Academy of Sciences, 2014, 111(4): E455-E464.
    [8]
    Cruchaga C, Chakraverty S, Mayo K, et al. Rare variants in APP, PSEN1 and PSEN2 increase risk for AD in late-onset Alzheimer's disease families. PLOS ONE, 2012, 7(2): e31039.
    [9]
    Reich D E, Lander E S. On the allelic spectrum of human disease. Trends in Genetics, 2001, 17(9): 502-510.
    [10]
    Pritchard J K. Are rare variants responsible for susceptibility to complex diseases? The American Journal of Human Genetics, 2001, 69(1): 124-137.
    [11]
    Manolio T A, Collins F S, Visscher P M, et al. Finding the missing heritability of complex diseases. Nature, 2009, 461(7265): 747-753.
    [12]
    Coventry A, Bull-Otterson L M, Liu X, et al. Deep resequencing reveals excess rare recent variants consistent with explosive population growth. Nature Communications, 2010, 1(1): 1-6.
    [13]
    Nelson M R, Wegmann D, Ehm M G, et al. An abundance of rare functional variants in 202 drug target genes sequenced in 14,002 people. Science, 2012, 337(6090): 100-104.
    [14]
    Nicolas G, Charbonnier C, Wallon D, et al. SORL1 rare variants: A major risk factor for familial early-onset Alzheimer's disease. Molecular Psychiatry, 2016, 21(6): 831-836.
    [15]
    Bellenguez C, Charbonnier C, Grenier-Boley B, et al. Contribution to Alzheimer's disease risk of rare variants in TREM2, SORL1, and ABCA7 in 1779 cases and 1273 controls. Neurobiology of Aging, 2017, 59:220.e1-220.e9.
    [16]
    Rice T K, Schork N J, Rao D C. Methods for handling multiple testing. Advances in Genetics, 2008, 60(4): 293-308.
    [17]
    Seunggeun L, Wu M C, Lin X. Optimal tests for rare variant effects in sequencing association studies. Biostatistics, 2012, 13(4): 762-775.
    [18]
    Seunggeun L, Christian F, Sehee K, et al. An efficient resampling method for calibrating single and gene-based rare variant association analysis in case-control studies. Biostatistics, 2016, 17(1): 1-15.
    [19]
    Das S, Forer L, Sidore C, et al. Next-generation genotype imputation service and methods. Nature Genetics, 2016, 48(10): 1284-1287.
    [20]
    Thakker R V, Whyte M P, Eisman J A, et al. Genetics of Bone Biology and Skeletal Disease. Salt Lake City, UT: Academic Press, 2017.
    [21]
    McCarthy S, Das S, Kretzschmar W, et al. A reference panel of 64,976 haplotypes for genotype imputation. Nature Genetics, 2016, 48(10): 1279-1283.
    [22]
    Dijk E V, Auger H, Jaszczyszyn Y, et al. Ten years of next-generation sequencing technology. Trends in Genetics, 2014, 30(9): 418-426.
    [23]
    Vrieze S I, Malone S M, Pankratz N, et al. Genetic associations of nonsynonymous exonic variants with psychophysiological endophenotypes. Psychophysiology, 2014, 51(12): 1300-1308.
    [24]
    Wang K, Li M Y, Hakonarson H. ANNOVAR: Functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Research, 2010, 38(16):e164.
    [25]
    Spilker C, Sanhueza G, Böckers T M, et al. SPAR2, a novel SPAR-related protein with GAP activity for Rap1 and Rap2. Journal of Neurochemistry, 2008, 104(1): 187-201.
    [26]
    Cathy S. Ras signaling in aging and metabolic regulation. Nutrition and Healthy Aging, 2017, 4(3): 195-205.
    [27]
    Naylor R M, Baker D J, Deursen V. Senescent cells: A novel therapeutic target for aging and age-related diseases. Clinical Pharmacology & Therapeutics, 2013, 93(1): 105-116.
    [28]
    Dimauro T, David G. Ras-induced senescence and its physiological relevance in cancer. Current Cancer Drug Targets, 2010, 10(8): 869-876.
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