Genetic reports abstractNegative resultsFailure to detect synergy between variants in transferrin and hemochromatosis and Alzheimer's disease in large cohort
Introduction
Alzheimer's disease (AD) is the most common cause of dementia and inflicts an estimated 24 to 35 million people worldwide, with incidences predicted to increase dramatically as the population ages (Alzheimer's Association, 2018). Although decades of research have been spent investigating the causes and architecture of this neurodegenerative disease, it still inflicts an estimated 5.7 million people in the United States alone. This number is projected to increase to 13.8 million by mid-century (Alzheimer's Association, 2018). Association studies have accurately identified single-nucleotide polymorphisms (SNPs) associated with AD (Harold et al., 2009, Hollingworth et al., 2011, Lambert et al., 2009, Lambert et al., 2013, Seshadri et al., 2010, Shen et al., 2015, Shuai et al., 2015, Yan et al., 2015). However, these genetic loci account for only a fraction of AD heritability (Ridge, Mukherjee, Crane, Kauwe, & Alzheimer's Disease Genetics, 2013), suggesting that much of the unexplained genetics affecting AD etiology may be due to epistasis (Bullock et al., 2013, Combarros et al., 2009, Ebbert et al., 2014, Infante et al., 2004). Epistasis occurs when multiple genes interact to create a single phenotype (Cordell, 2002). These kinds of synergetic relationships play a critical role in the etiology of complex diseases, yet remain vastly understudied in AD pathology (Alzheimer's Association, 2018, Ebbert et al., 2015, Raghavan and Tosto, 2017).
The transferrin (TF) gene and the homeostatic iron regulator (HFE) gene, commonly known as hemochromatosis, have been reported to show epistasis and play a role in the development of AD (Robson et al., 2004, Tisato et al., 2018). TFs are a group of nonheme iron-binding glycoproteins found in fluids and cells of vertebrates. The main role of TF is to maintain iron homeostasis in the body (Gkouvatsos et al., 2012). In the brain, TF interacts with the amyloid precursor protein (Belaidi et al., 2018) and tau (Jahshan et al., 2016), 2 of the major protein families implicated in AD pathology. Because iron is essential for oxygen transport, its misregulation in the brain can lead to oxidative stress and neurodegeneration (Dias et al., 2013, Matak et al., 2016, Yarjanli et al., 2017). HFE encodes for a transmembrane glycoprotein that binds to a TF receptor, subsequently regulating iron in the cell (Bennett et al., 2000, Feder et al., 1996, Lebron et al., 1998). Mutations in HFE are associated with neurodegenerative diseases through increasing neuroinflammation and production of free radicals in the brain (Andersen et al., 2014, Lull and Block, 2010). In addition, other studies suggest that TF and HFE are involved in the transport and regulation of iron in the brain, and disrupting these processes potentially affects AD pathology through increased neurodegeneration and oxidative stress (Ali-Rahmani et al., 2014, Lehmann et al., 2006).
Robson et al. (2004) suggested that epistasis between TF variant rs1049296 and HFE variant rs1800562 is associated with AD. Although neither SNP alone was a risk factor for AD, the presence of both alleles resulted in a 5 times greater risk of developing AD (Robson et al., 2004). Because the sample size for that study was relatively small (191 cases and 269 controls), a replication of these findings on a slightly larger data set (1161 cases and 1342 controls) was conducted. A logistic regression analysis and a synergy factor analysis (SFA) corroborated a significant association with AD risk among bi-allelic carriers of rs1049296 and rs1800562 (synergy factor= 2.71; p = 0.0016) (Kauwe et al., 2010).
Our study expands on these previous studies and attempts to detect statistical epistasis between TF rs1049296 and HFE rs1800562 with respect to AD risk using 25,666 individuals (12,532 cases and 13,134 controls) from the Alzheimer's Disease Genetic Consortium (ADGC), which is an expansion of the data set used by Kauwe et al. (2010).
Section snippets
Data set and filtering
Our analysis started with genetic data from all 28,730 individuals in the Alzheimer's Disease Genetics Consortium (ADGC) data set as described by Naj et al. (2011). ADGC is a collection of 30 merged data sets spanning 1984 to 2012, and was established to help identify genetic markers of late onset AD (Boehme et al. 2014) (see Supplementary Table 1 for ADGC demographics). ADGC imputed the 30 data sets to the Haplotype Reference Consortium reference panel, which includes 64,976 haplotypes and
Results
The nonparametric logistic regression analysis using ADGC as one cohort demonstrated that when testing the main effects, neither TF rs1049296 nor HFE rs1800562 was associated with AD risk (TF rs1049296 p = 0.38; HFE rs1800562 p = 0.40). The logistic regression analyses including an interaction term for the 2 variants also failed to show significant association (p = 0.23). Similarly, the SFA analysis did not find epistasis between TF rs1049296 and HFE rs1800562 (SF = 0.94; p = 0.48).
We performed
Discussion
We failed to detect evidence that epistasis between TF rs1049296 and HFE rs1800562 increases risk for AD in the ADGC data set. These findings do not support the conclusions drawn in the previous reports by Robson et al. (2004) and Kauwe et al. (2010). The cause for this variability among studies could be a result of genetic heterogeneity, the complex nature of epistasis, or false positives in these previous studies due to limited sample size.
Although recent literature suggests that much of the
Disclosure statement
None.
Acknowledgements
This work was supported by the National Institutes of Health, National Institute on Aging (USA) grant numbers R01AG042611 and RF1AG054052. Data was supported by the ADGC. ADGC grants: ADGC U01AG032984, NIAGADS U24AG041689, NCRAD U24AG21886, and NACC U01AG016976. Acknowledgements for ADGC support can be found here: http://www.adgenetics.org/content/acknowledgements.
Authors' contributions: EV contributed to conceptualization, methodology, formal analysis, writing—original draft, writing—review
References (52)
- et al.
Marked age-related changes in brain iron homeostasis in amyloid protein precursor knockout mice
Neurotherapeutics
(2018) - et al.
Epistasis in sporadic Alzheimer's disease
Neurobiol. Aging
(2009) - et al.
Population-based analysis of Alzheimer's disease risk alleles implicates genetic interactions
Biol. Psychiatry
(2014) - et al.
Regulation of iron transport and the role of transferrin
Biochim. Biophys. Acta
(2012) - et al.
Evaluation of ferritin and transferrin binding to tau protein
J. Inorg. Biochem.
(2016) - et al.
Epistasis between deleterious mutations and the evolution of recombination
Trends Ecol. Evol.
(2007) - et al.
Crystal structure of the hemochromatosis protein HFE and characterization of its interaction with transferrin receptor
Cell
(1998) - et al.
Microglial activation and chronic neurodegeneration
Neurotherapeutics
(2010) The executive prominent/memory prominent spectrum in Alzheimer’s disease is highly heritable
Neurobiol. Aging
(2016)- et al.
Epistasis and its implications for personal genetics
Am. J. Hum. Genet.
(2009)
Genome-wide rare variant imputation and tissue-specific transcriptomic analysis identify novel rare variant candidate loci In Late-Onset Alzheimer’s Disease: The Alzheimer’s Disease Genetics Consortium
Alzheimers Dement.
Genetic associations of CLU rs9331888 polymorphism with Alzheimer’s disease: a meta-analysis
Neurosci. Lett.
CYP2J2 rs890293 polymorphism is associated with susceptibility to Alzheimer’s disease in the Chinese Han population
Neurosci. Lett.
Bridging the gap between statistical and biological epistasis in Alzheimer’s disease
Biomed. Res. Int.
HFE gene variants, iron, and lipids: a novel connection in Alzheimer’s disease
Front. Pharmacol.
2018 Alzheimer's disease facts and figures
Alzheimers Dement.
Iron deposits in the chronically inflamed central nervous system and contributes to neurodegeneration
Cell Mol. Life Sci.
Crystal structure of the hereditary haemochromatosis protein HFE complexed with transferrin receptor
Nature
ADGC 1000 genomes combined workflow (electronic document)
Discovery by the Epistasis Project of an epistatic interaction between the GSTM3 gene and the HHEX/IDE/KIF11 locus in the risk of Alzheimer's disease
Neurobiol. Aging
Power and error: increased risk of false positive results in underpowered studies
Open Epidemiol J
Epistasis: what it means, what it doesn't mean, and statistical methods to detect it in humans
Hum. Mol. Genet.
The synergy factor: a statistic to measure interactions in complex diseases
BMC Res. Notes
Sample size determination for logistic regression revisited
Stat. Med.
Sample size and optimal design for logistic regression with binary interaction
Stat. Med.
The role of oxidative stress in Parkinson's disease
J. Parkinsons Dis.
Cited by (6)
Iron and risk of dementia: Mendelian randomisation analysis in UK Biobank
2024, Journal of Medical GeneticsImbalance of Essential Metals in Traumatic Brain Injury and Its Possible Link with Disorders of Consciousness
2023, International Journal of Molecular SciencesDetection of pathogenic variants in Alzheimer’s disease related genes in Bulgarian patients by pooled whole-exome sequencing
2023, Biotechnology and Biotechnological EquipmentCo-treatment of AMPA endocytosis inhibitor and GluN2B antagonist facilitate consolidation and retrieval of memory impaired by β amyloid peptide
2022, International Journal of NeuroscienceHemochromatosis mutations, brain iron imaging, and dementia in the UK Biobank cohort
2021, Journal of Alzheimer's Disease