Can Common Genetic Variation in Mice Nail Genes of Aging, Alzheimer’s?
Geneticists have all but exhausted the genome-wide association approach to finding genetic variants that influence AD risk. Massive meta-analyses of more than 50,000 cases and controls have brought the total number of AD risk genes to just more than 20. Can researchers find other AD genes that might be hidden by the cultural and environmental heterogeneity inherent in human populations? Enter the mouse. Mice can be raised in controlled environments. Yet, like people, they have genetic variants that might make them smarter, age better, or, in contrast, render them susceptible to the type of pathology that causes dementia. At this year’s Society for Neuroscience annual meeting, held October 17-21 in Chicago, researchers reported that genome-wide mapping in a panel of inbred mice uncovered variants that accelerated age-related memory decline. The variants lie in the Hp1bp3 gene, which encodes a chromatin-binding protein. Hp1bp3 expression doubles in the hippocampus in AD mouse models and in people who have the disease, said Catherine Kaczorowski, University of Tennessee Health Science Center, Memphis, who presented the data.
The data intrigued scientists at the meeting. “This approach really fascinates me. It may point to pathways and targets [in Alzheimer’s disease] that we have not yet figured out,” said Carol Barnes, University of Arizona, Tucson.
Mouse Panels Capture Genetic Diversity
Kaczorowski found the Hp1bp3 gene by screening the so-called BXD panel of mice. These animals, created by crossing the two common laboratory mouse strains B6 and D2, constitute a genetic reference population that can be studied much the same way as a population of people. The difference is that with the rare exception of identical twins, each person has a unique genotype, while a stable isogenic mouse line represents each genotype within the BXD panel. This allows researchers to study the same genotype multiple times and under varying conditions. There are now more than 150 BXD strains. They have been used to map genetic variants that influence a swath of physiology, including basic metabolism, mitochondrial activity, cardiovascular disease, and longevity (see Koutnikova et al., 2009; Andreux et al., 2012; Hootkooper et al., 2013; Wu et al., 2014).
Kaczorowski moved her laboratory to UTHSC, where Robert Williams had pioneered the use of BXD panels to study complex traits and human disease, so that she could use them to study memory and dementia. Gareth Howell at the Jackson Lab in Bar Harbor, Maine, also uses BXD and other panels of genetically diverse mice to map gene variants that influence pathology in mouse models of AD. Few other labs, if any, are using the approach to study AD. “As far as I know, Catherine and our group are the only ones,” Howell told Alzforum. Other researchers at SfN were unfamiliar with the panel. “The field should really know about these resources,” said Karen Duff, Nathan Kline Institute, New York.
Kaczorowski and colleagues tested 15 BXD strains for long-term memory using a contextual fear paradigm. As graduate student Sarah Neuner outlined in her talk, test scores in middle-aged animals (~14 months old) varied by strain. Neuner mapped the variance to a region on mouse chromosome 4, and Hp1bp3 emerged as the top candidate to explain the variation. The gene is expressed robustly in the hippocampus, and knockouts perform poorly in hippocampal-based working- and long-term memory tests, said Kaczorowski. Neuner found twice as much Hp1Bp3 protein in the hippocampus of 5xFAD mouse models of AD compared to controls; this paralleled a similar increase in Hp1bp3 RNA the hippocampi of 18 women and 15 men with the disease. She used laser capture microdissection of brain samples to determine the transcript levels (see Liang et al., 2008).
How might the gene influence memory? Kaczorowski and colleagues used expression quantitative trait loci analysis to trace the regulation of other genes to the Hp1Bp3 locus. The gene, Wdfy3 (aka Alfy) emerged as a downstream regulatory target of the chromatin-binding protein. Kaczorowski does not know how Wdfy3 influences memory, but it encodes a protein that activates autophagy, a protein-degradation pathway implicated in AD and other proteinopathies (see May 2011 news; Jul 2015 news). In particular, scientists have directly linked Wdfy3 to removal of potentially toxic aggregates of TDP43 and mutant huntingtin (Filimonenko et al., 2007).
Kaczorowski told Alzforum that GWAS identified a locus near the Wdfy3 gene that is nominally associated with AD, but the association did not quite reach genome-wide statistical significance. “An advantage of our approach to identifying disease-modifying alleles is that it reduces the false discovery rate penalty of genome-wide testing, and thereby enhances power to uncover novel risk genes in existing GWAS datasets,” said Kaczorowski.
John Hardy of University College London, questioned whether these mice would be useful to study Alzheimer’s disease. “I think these mice panels will be valuable for dissecting pathways that influence biological processes. I do not think they will be directly useful for helping understand Alzheimer genetics because they do not develop memory loss for the same reason that humans with AD develop memory problems—namely loss of neurons initially in the hippocampus,” he wrote to Alzforum. Howell said that while that might be true, these models can be bred with strains that express AD risk genes and that there are naturally occurring variants within the mouse genome that modify AD genes such as TREM2 and Bin1. Mouse model have been widely used to study AD pathology even in the absence of frank neuronal loss.
Kaczorowski plans to combine systems-genetics approaches using the BXD panel with proteomic and other “omic” studies to create network models to better understand and predict memory decline. Kaczorowski and Neuner have already crossed BXD mice with the 5xFAD mouse model of AD in order to identify genetic variants and downstream neuronal mechanisms that mediate individual differences in risk or resilience to AD. They currently have 27 AD x BXD strains and corresponding non-transgenic controls.
Howell plans to use other panels of mice called Collaborative Cross (CC) and Diversity Outbred (DO) to study how genetic variants alter pathology in AD. These mice were developed by a consortium that included JAX scientists. The CC panel are inbred derivatives of an eight-way cross made using different JAX mice, including three strains derived from wild-type mice. To derive DO mice, the researchers outbred the CC mice again. “This gives us hundreds of mice that are genetically unique and provides the levels of genetic diversity present in human GWAS, but without the complicating effects of rare genetic variants and population structure,” said Howell (see JAX site for further information).
Howell first generated a panel of genetically diverse AD models by crossing the APP/PS1 transgenic mice to the founder strains of the CC and DO, and found a range of variable AD phenotypes. He will map genetic changes that associate with that variation using the CC and DO lines. He also plans to use this approach to identify genetic variants that influence late-onset AD genes such as ApoE, TREM2, and other GWAS hits. “The power is that we can do these studies in strains that allow individual genetic variations to be readily identified,” said Howell. The mice can also be used to model the effects of the environment, something that is different for every person included in a GWAS analysis (see Nov 2015 news).
These studies would be difficult to do in a human population. “With the DO panel we can find multiple genetic factors that mimic the complex genetics of human AD,” said Howell. These resources can be used to understand the relevance of GWAS hits to each other, or to identify protective alleles in an unbiased way. “In general, protective alleles are missed by using human GWAS,” said Howell. For example, GWAS missed the protective A673T APP mutation uncovered by whole-genome sequencing (see Jul 2012 news).—Tom Fagan
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Research Models Citations
- Koutnikova H, Laakso M, Lu L, Combe R, Paananen J, Kuulasmaa T, Kuusisto J, Häring HU, Hansen T, Pedersen O, Smith U, Hanefeld M, Williams RW, Auwerx J. Identification of the UBP1 locus as a critical blood pressure determinant using a combination of mouse and human genetics. PLoS Genet. 2009 Aug;5(8):e1000591. Epub 2009 Aug 7 PubMed.
- Andreux PA, Williams EG, Koutnikova H, Houtkooper RH, Champy MF, Henry H, Schoonjans K, Williams RW, Auwerx J. Systems genetics of metabolism: the use of the BXD murine reference panel for multiscalar integration of traits. Cell. 2012 Sep 14;150(6):1287-99. Epub 2012 Aug 30 PubMed.
- Houtkooper RH, Mouchiroud L, Ryu D, Moullan N, Katsyuba E, Knott G, Williams RW, Auwerx J. Mitonuclear protein imbalance as a conserved longevity mechanism. Nature. 2013 May 23;497(7450):451-7. PubMed.
- Wu Y, Williams EG, Dubuis S, Mottis A, Jovaisaite V, Houten SM, Argmann CA, Faridi P, Wolski W, Kutalik Z, Zamboni N, Auwerx J, Aebersold R. Multilayered genetic and omics dissection of mitochondrial activity in a mouse reference population. Cell. 2014 Sep 11;158(6):1415-30. PubMed.
- Liang WS, Reiman EM, Valla J, Dunckley T, Beach TG, Grover A, Niedzielko TL, Schneider LE, Mastroeni D, Caselli R, Kukull W, Morris JC, Hulette CM, Schmechel D, Rogers J, Stephan DA. Alzheimer's disease is associated with reduced expression of energy metabolism genes in posterior cingulate neurons. Proc Natl Acad Sci U S A. 2008 Mar 18;105(11):4441-6. Epub 2008 Mar 10 PubMed.
- Filimonenko M, Stuffers S, Raiborg C, Yamamoto A, Malerød L, Fisher EM, Isaacs A, Brech A, Stenmark H, Simonsen A. Functional multivesicular bodies are required for autophagic clearance of protein aggregates associated with neurodegenerative disease. J Cell Biol. 2007 Nov 5;179(3):485-500. PubMed.
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