BACKGROUND
the hippocampus is a key forebrain region involved in declarative memory, cognition, and spatial navigation.
hippocampal volume is highly variable with unilateral values ranging from ~ <dig> to 5000 mm <dig> among healthy young humans  and from  <dig>  to  <dig>  mm <dig> among young adult mice
<cit> .
heritability ranges from 40% to 70% in both species
<cit> , and a small fraction of the difference in volume is also attributable to sex
<cit> .
this wide range of natural variation raises the possibility that susceptibility to a subset of neurodegenerative and psychiatric disorders linked to defects in the hippocampus may depend, in part, on its initial healthy volume.
individuals who develop and retain a large hippocampus into adulthood may be comparatively resistant to some forms of disease, particularly alzheimer’s.
such a "reserve" hypothesis of neurological disease
<cit>  has been proposed for parkinson’s
<cit> , huntington’s
<cit>  and alzheimer’s
<cit>  diseases.
lower than average volume has been linked to a number of disorders
<cit>  including depression
, alzheimer’s disease
<cit>  and schizophrenia
<cit> .
understanding the genetic factors that contribute to individual differences in hippocampal volume is thus crucial in providing insight into vulnerability and severity of disease.
prior efforts to identify genetic variants underlying differences in brain structure have used large data sets in human genome-wide association studies  or extensive mapping populations in mouse model systems.
gwas in humans typically have modest statistical power due to high corrections needed to compensate for multiple testing.
however, loci are defined with very high precision, often down to the level of single nucleotide polymorphisms .
in contrast, mouse linkage studies often have high statistical power to detect genetic effects but lower genetic resolution, producing loci that include hundreds of genes
<cit> .
combining data from mice and humans overcomes some of these problems, gaining power from mouse crosses and precision from human gwas.
this method also ensures the translational relevance, giving confidence to the human results, as the same gene controlling the same phenotype is found in a related species.
further, this approach illustrates that the homologous mouse gene is relevant to the human phenotype, as well as the significance of experimental research in model systems that would not be possible in humans.
homologous genes are genes that share a common evolutionary ancestor.
in this study we are specifically looking at a subset of homologous genes, orthologs, which derive from a speciation event, rather than paralogs, which arise because of a gene duplication event.
this study takes a cross-species approach to identify genes with an evolutionarily conserved role in influencing hippocampus size; i.e.
because a given gene is playing the same role in two different species we hypothesize that it was playing the same role in the ancestral species.
previous studies have begun to show the utility of using a cross-species approach to identify genes underlying a phenotype of interest
.
this approach has the advantage that it allows the investigation of disease phenotypes without requiring data from experimental perturbations.
instead we utilize data obtained from populations that segregated for large numbers of common sequence variants and associated differences in phenotype.
here, we use data from the largest mouse model system, bxd, to identify a set of genes associated with hippocampus size in a joint analysis with human hippocampus mri data obtained by the enigma consortium for gwas
<cit> .
we identify, mgst <dig>  and use a systems-genetics approach that links this gene to neurodegenerative disorders such as alzheimer’s disease and parkinson’s disease.
RESULTS
identification of genes significant in both species
associations between genes and hippocampus size in bxd mice were estimated using p-values for over  <dig> markers obtained for qtl interval mapping.
qtl mapping identifies a region of the genome significantly linked to variation in the phenotype.
having identified qtl, we then estimated a particular gene’s significance based on its base pair distance from the nearest two markers and the significance of these two markers.
therefore any particular gene will have a p-value somewhere between the p-values of its two closest markers.
the next step in our analysis was to obtain snp level p-values for association with human hippocampus volume, which were converted to gene p-values to allow comparison with data for the mouse hippocampus.
using the snp p-values from the human gwas, the versatile gene-based association study  website
<cit>  produced gene p-values for a total of  <dig>  human genes.
secondly, the mouse homologues of these human genes were identified and yielded a total of  <dig>  genes .
using a relaxed  p-value of ≤  <dig> ,  <dig> human genes  were then nominally identified as having an effect on hippocampus size.
overall, there is no indication that the significance of any given gene with the entire region identified in the qtl analysis of bxd mouse hippocampus weight is indicative of the homologous gene’s significance on human hippocampus volume, as judged by the quantile-quantile plot and lambda .
this is corroborated by a separate rank rank hypergeometric overlap test
<cit>  used to compare the two datasets, which yielded a non-significant result .
this is unsurprising as a qtl analysis identifies a region of the genome associated with a trait, and therefore in our analysis all genes within the mouse qtl were significant.
however, not all the genes within a qtl contribute to the phenotype, but only a subset or even a single gene.figure  <dig>
quantile-quantile plot of human homologues of significant mouse genes for hippocampus size.
for genes with a significant influence on hippocampus weight in mice  the significance of their influence on human hippocampus volume was plotted against a normal distribution of p-values.
although there are outliers, most of the points lie close to the y = x line, indicating there is no difference between what is seen in the data and what would be expected by chance.
this is reinforced by the non-significant lambda value close to  <dig>  which indicates no inflation of significance values.
therefore we sought to identify which genes are associated with both bxd mouse hippocampus weight and human hippocampus volume.
the  <dig> genes which were significant in mouse are all within a qtl on chromosome 1
<cit> .only one gene had a significant human p-value when corrected for multiple testing , mgst <dig>
regulation of gene expression
to establish if our candidate gene was regulating its own expression, mouse hippocampus microarray data from genenetwork was used to find probes corresponding to expression of the gene, and webqtl was used to produce eqtl
<cit> .
of the  <dig> probes for mgst <dig>  within the exon array data, six have a significant pearson’s correlation , and these probes were used to represent expression of mgst <dig> in the mouse hippocampus.
the six probes represent all four probes for exons and one each from the 5′ and 3′ utr .
the remaining  <dig> probes were for introns and utrs.
this shows that the correlating probes represent the protein coding parts of the gene.table  <dig>
pearson correlations between probes for
mgst3
in adult mouse hippocampus
pearson product-moment correlations produced by genenetwork.
the dataset used was umutaffy hippocampus exon  rma .
all probes are for mgst <dig> located on chromosome  <dig>
mgst <dig> has a cis-eqtl, suggesting it regulates its own expression.
no trans-qtl was found which was consistent between probes.
the qtl and eqtl analysis also showed that the c57bl/6 j  allele increased hippocampus weight, whereas the dba/2 j  allele increased the expression of mgst <dig>
functional analysis of significant genes
to investigate the function of our candidate genes, we used the database for annotation, visualization and integrated discovery  as it allows us to analyse a number of different annotation databases.
significance was determined by the false discovery rate , which corrects the significance value for the large number of multiple comparisons.
to determine if any annotations were enriched in both mouse and human, even though individual genes were not shared, separate lists of genes nominally significant in human  and human homologues of the  <dig> mouse genes with p ≤  <dig>  were entered into david.
no overlapping significant annotations were found, i.e.
no annotations were significantly enriched in both the genes significant in human and the genes significant in mouse.
again, this shows that not all  <dig> genes within the mouse qtl influence the phenotype, but only a subset.
guilt-by-association
coexpression of genes implies that they share the same regulatory mechanisms
<cit>  and/or are involved in the same biological processes.
a ‘guilt-by-association’ approach asserts that the function of a gene, or list of genes, can be indicated by the genes that it commonly coexpresses with, as common coexpression indicates they are part of the same biological process
<cit> .
the large datasets of gene expression provided by genenetwork and genefriends allows this ‘guilt-by-association’ approach to be used.
this is especially useful for genes such as mgst3/mgst <dig>  which previously have not been investigated in detail.
genefriends shows human genes which coexpress in a large number of datasets from the gene expression omnibus.
however it is not specific for tissue or treatment.
this identified  <dig> genes that were coexpressed with mgst <dig> in over half of the datasets .
these were analysed using david, to find what kegg pathway annotations were significant .
one of the six kegg pathways is particularly interesting; alzheimer’s disease .
to support a specific link between genes that are coexpressed with mgst <dig> and alzheimer’s disease we used the exon array data from genenetwork, as this is specific to the hippocampus.
each of the six above identified probes for mgst <dig> was correlated against the entire exon array dataset  to find the top  <dig>  probes with which it correlates.
these six lists of probes were then combined to find which probes correlated with all six probes for mgst <dig>  this produced a list of  <dig> probes which correlated with all six of the probes for mgst <dig>  representing  <dig> genes .
permutation testing was carried out to determine an empirical p-value for how often six lists of  <dig>  values from a choice of  <dig> , <dig> values would overlap, and produced a p-value of < 1 × 10- <dig>  this shows that the overlap between our probes is highly significant, and that these  <dig> genes really do coexpress with mgst <dig> in the mouse hippocampus.
enrichment of this list of genes was then examined in david, and again we see genes involved in neurodegenerative diseases significantly enriched : huntington’s disease  and alzheimer’s disease .
finally, the overlap between the genes that are commonly coexpressed with mgst <dig> and human homologues of the genes that are coexpressed with mgst <dig> in the mouse hippocampus was examined.
this showed that  <dig> genes which commonly coexpress with mgst <dig> also coexpress with its mouse homologue in the mouse hippocampus .
we tested this by permutation taking samples of  <dig> genes and  <dig> genes from a list of all known human protein coding genes and determining how often an overlap larger than  <dig> was seen.
this produced an empirical p-value ≤ 1 × 10- <dig>  again with kegg enrichment analysis, the three neurodegenerative diseases are highly significant : huntington’s disease , parkinson’s disease  and alzheimer’s disease .
discussion
we found strong evidence that mgst <dig>  on chromosome  <dig> in both mouse and human, is significantly associated with hippocampus size.
mgst <dig> has previously been found to be down-regulated in alzheimer’s disease
<cit> .
the fact that the gene appears to have an evolutionarily conserved role in both species suggests a role in hippocampus morphology.
mgst <dig> has been found to be particularly highly expressed in the rat hippocampus
<cit> .
a ‘guilt-by-association’ approach shows that these genes coexpress with genes linked to neurodegenerative disorders associated with reduced hippocampus volume: huntington’s disease
, alzheimer’s disease
<cit>  and parkinson’s disease
.
the potential mechanism for this link is more speculative.
genes that coexpress with mgst <dig> are also associated with cellular energy production, as the oxidative phosphorylation kegg pathway appears in our results [additional files
<dig>
<dig> and
7].
mitochondrial dysfunction has been implicated in both neuropsychiatric and neurodegenerative disorders
<cit> , linking the mitochondrial and neurodegenerative annotations.
recently it has been reported that dysfunction of mtdna genes, which have been implicated in alzheimer’s disease, directly influence left hippocampal atrophy
<cit> .
further, links have also been found between oxidative stress and regulation of mgst <dig> in mice
<cit> .
mgst <dig> has also been linked to inflammation, as it and other family members show leukotriene c <dig>  synthase activity.
leukotrienes are physiological important mediators of various inflammatory and immediate hypersensitivity processes
<cit> .
when porcine kidney cells were exposed a nephrotoxin, aristolochic acid i, mgst <dig> and flap  were upregulated before an increase in lts synthesis.
this is relevant as alzheimer’s disease, as well as other neurodegenerative disorders, have been linked to inflammation .
however, other research has found that rat mgst <dig> does not have ltc <dig> synthase activity
<cit> , is not upregulated in response to lipopolysaccharide
<cit>  and does not appear to be directly involved in the inflammation response
<cit> .
in this last paper, the authors speculate that it may have a neuroprotective role against oxidative stress
<cit> .
CONCLUSIONS
in summary, the combination of human gwas and mouse qtl data from some of the largest study systems available has enabled us to identify a novel gene, mgst <dig>  which is associated with hippocampus size across species and, when dysregulated, is linked to neurodegenerative disorders.

 the hippocampus is a key forebrain region involved in declarative memory, cognition, and spatial navigation. hippocampal volume is highly variable with unilateral values ranging from ~ to 5000 mm among healthy young humans and from to  mm among young adult mice. heritability ranges from 40% to 70% in both species, and a small fraction of the difference in volume is also attributable to sex. this wide range of natural variation raises the possibility that susceptibility to a subset of neurodegenerative and psychiatric disorders linked to defects in the hippocampus may depend, in part, on its initial healthy volume. individuals who develop and retain a large hippocampus into adulthood may be comparatively resistant to some forms of disease, particularly alzheimer’s. such a "reserve" hypothesis of neurological disease has been proposed for parkinson’s, huntington’s and alzheimer’s diseases. lower than average volume has been linked to a number of disorders including depression, alzheimer’s disease and schizophrenia. understanding the genetic factors that contribute to individual differences in hippocampal volume is thus crucial in providing insight into vulnerability and severity of disease. prior efforts to identify genetic variants underlying differences in brain structure have used large data sets in human genome-wide association studies or extensive mapping populations in mouse model systems. gwas in humans typically have modest statistical power due to high corrections needed to compensate for multiple testing. however, loci are defined with very high precision, often down to the level of single nucleotide polymorphisms. in contrast, mouse linkage studies often have high statistical power to detect genetic effects but lower genetic resolution, producing loci that include hundreds of genes. combining data from mice and humans overcomes some of these problems, gaining power from mouse crosses and precision from human gwas. this method also ensures the translational relevance, giving confidence to the human results, as the same gene controlling the same phenotype is found in a related species. further, this approach illustrates that the homologous mouse gene is relevant to the human phenotype, as well as the significance of experimental research in model systems that would not be possible in humans. homologous genes are genes that share a common evolutionary ancestor. in this study we are specifically looking at a subset of homologous genes, orthologs, which derive from a speciation event, rather than paralogs, which arise because of a gene duplication event. this study takes a cross-species approach to identify genes with an evolutionarily conserved role in influencing hippocampus size; i.e. because a given gene is playing the same role in two different species we hypothesize that it was playing the same role in the ancestral species. previous studies have begun to show the utility of using a cross-species approach to identify genes underlying a phenotype of interest. this approach has the advantage that it allows the investigation of disease phenotypes without requiring data from experimental perturbations. instead we utilize data obtained from populations that segregated for large numbers of common sequence variants and associated differences in phenotype. here, we use data from the largest mouse model system, bxd, to identify a set of genes associated with hippocampus size in a joint analysis with human hippocampus mri data obtained by the enigma consortium for gwas. we identify, mgst and use a systems-genetics approach that links this gene to neurodegenerative disorders such as alzheimer’s disease and parkinson’s disease.  identification of genes significant in both species associations between genes and hippocampus size in bxd mice were estimated using p-values for over markers obtained for qtl interval mapping. qtl mapping identifies a region of the genome significantly linked to variation in the phenotype. having identified qtl, we then estimated a particular gene’s significance based on its base pair distance from the nearest two markers and the significance of these two markers. therefore any particular gene will have a p-value somewhere between the p-values of its two closest markers. the next step in our analysis was to obtain snp level p-values for association with human hippocampus volume, which were converted to gene p-values to allow comparison with data for the mouse hippocampus. using the snp p-values from the human gwas, the versatile gene-based association study website produced gene p-values for a total of human genes. secondly, the mouse homologues of these human genes were identified and yielded a total of genes. using a relaxed p-value of ≤ , human genes were then nominally identified as having an effect on hippocampus size. overall, there is no indication that the significance of any given gene with the entire region identified in the qtl analysis of bxd mouse hippocampus weight is indicative of the homologous gene’s significance on human hippocampus volume, as judged by the quantile-quantile plot and lambda. this is corroborated by a separate rank rank hypergeometric overlap test used to compare the two datasets, which yielded a non-significant result. this is unsurprising as a qtl analysis identifies a region of the genome associated with a trait, and therefore in our analysis all genes within the mouse qtl were significant. however, not all the genes within a qtl contribute to the phenotype, but only a subset or even a single gene.figure quantile-quantile plot of human homologues of significant mouse genes for hippocampus size. for genes with a significant influence on hippocampus weight in mice the significance of their influence on human hippocampus volume was plotted against a normal distribution of p-values. although there are outliers, most of the points lie close to the y = x line, indicating there is no difference between what is seen in the data and what would be expected by chance. this is reinforced by the non-significant lambda value close to which indicates no inflation of significance values. therefore we sought to identify which genes are associated with both bxd mouse hippocampus weight and human hippocampus volume. the genes which were significant in mouse are all within a qtl on chromosome 1.only one gene had a significant human p-value when corrected for multiple testing, mgst regulation of gene expression to establish if our candidate gene was regulating its own expression, mouse hippocampus microarray data from genenetwork was used to find probes corresponding to expression of the gene, and webqtl was used to produce eqtl. of the probes for mgst within the exon array data, six have a significant pearson’s correlation, and these probes were used to represent expression of mgst in the mouse hippocampus. the six probes represent all four probes for exons and one each from the 5′ and 3′ utr. the remaining probes were for introns and utrs. this shows that the correlating probes represent the protein coding parts of the gene.table pearson correlations between probes for mgst3 in adult mouse hippocampus pearson product-moment correlations produced by genenetwork. the dataset used was umutaffy hippocampus exon rma. all probes are for mgst located on chromosome mgst has a cis-eqtl, suggesting it regulates its own expression. no trans-qtl was found which was consistent between probes. the qtl and eqtl analysis also showed that the c57bl/6 j allele increased hippocampus weight, whereas the dba/2 j allele increased the expression of mgst functional analysis of significant genes to investigate the function of our candidate genes, we used the database for annotation, visualization and integrated discovery as it allows us to analyse a number of different annotation databases. significance was determined by the false discovery rate, which corrects the significance value for the large number of multiple comparisons. to determine if any annotations were enriched in both mouse and human, even though individual genes were not shared, separate lists of genes nominally significant in human and human homologues of the mouse genes with p ≤  were entered into david. no overlapping significant annotations were found, i.e. no annotations were significantly enriched in both the genes significant in human and the genes significant in mouse. again, this shows that not all genes within the mouse qtl influence the phenotype, but only a subset. guilt-by-association coexpression of genes implies that they share the same regulatory mechanisms and/or are involved in the same biological processes. a ‘guilt-by-association’ approach asserts that the function of a gene, or list of genes, can be indicated by the genes that it commonly coexpresses with, as common coexpression indicates they are part of the same biological process. the large datasets of gene expression provided by genenetwork and genefriends allows this ‘guilt-by-association’ approach to be used. this is especially useful for genes such as mgst3/mgst which previously have not been investigated in detail. genefriends shows human genes which coexpress in a large number of datasets from the gene expression omnibus. however it is not specific for tissue or treatment. this identified genes that were coexpressed with mgst in over half of the datasets. these were analysed using david, to find what kegg pathway annotations were significant. one of the six kegg pathways is particularly interesting; alzheimer’s disease. to support a specific link between genes that are coexpressed with mgst and alzheimer’s disease we used the exon array data from genenetwork, as this is specific to the hippocampus. each of the six above identified probes for mgst was correlated against the entire exon array dataset to find the top probes with which it correlates. these six lists of probes were then combined to find which probes correlated with all six probes for mgst this produced a list of probes which correlated with all six of the probes for mgst representing genes. permutation testing was carried out to determine an empirical p-value for how often six lists of values from a choice of, values would overlap, and produced a p-value of < 1 × 10- this shows that the overlap between our probes is highly significant, and that these genes really do coexpress with mgst in the mouse hippocampus. enrichment of this list of genes was then examined in david, and again we see genes involved in neurodegenerative diseases significantly enriched: huntington’s disease and alzheimer’s disease. finally, the overlap between the genes that are commonly coexpressed with mgst and human homologues of the genes that are coexpressed with mgst in the mouse hippocampus was examined. this showed that genes which commonly coexpress with mgst also coexpress with its mouse homologue in the mouse hippocampus. we tested this by permutation taking samples of genes and genes from a list of all known human protein coding genes and determining how often an overlap larger than was seen. this produced an empirical p-value ≤ 1 × 10- again with kegg enrichment analysis, the three neurodegenerative diseases are highly significant: huntington’s disease, parkinson’s disease and alzheimer’s disease. discussion we found strong evidence that mgst on chromosome in both mouse and human, is significantly associated with hippocampus size. mgst has previously been found to be down-regulated in alzheimer’s disease. the fact that the gene appears to have an evolutionarily conserved role in both species suggests a role in hippocampus morphology. mgst has been found to be particularly highly expressed in the rat hippocampus. a ‘guilt-by-association’ approach shows that these genes coexpress with genes linked to neurodegenerative disorders associated with reduced hippocampus volume: huntington’s disease, alzheimer’s disease and parkinson’s disease. the potential mechanism for this link is more speculative. genes that coexpress with mgst are also associated with cellular energy production, as the oxidative phosphorylation kegg pathway appears in our results [additional files and 7]. mitochondrial dysfunction has been implicated in both neuropsychiatric and neurodegenerative disorders, linking the mitochondrial and neurodegenerative annotations. recently it has been reported that dysfunction of mtdna genes, which have been implicated in alzheimer’s disease, directly influence left hippocampal atrophy. further, links have also been found between oxidative stress and regulation of mgst in mice. mgst has also been linked to inflammation, as it and other family members show leukotriene c synthase activity. leukotrienes are physiological important mediators of various inflammatory and immediate hypersensitivity processes. when porcine kidney cells were exposed a nephrotoxin, aristolochic acid i, mgst and flap were upregulated before an increase in lts synthesis. this is relevant as alzheimer’s disease, as well as other neurodegenerative disorders, have been linked to inflammation. however, other research has found that rat mgst does not have ltc synthase activity, is not upregulated in response to lipopolysaccharide and does not appear to be directly involved in the inflammation response. in this last paper, the authors speculate that it may have a neuroprotective role against oxidative stress.  in summary, the combination of human gwas and mouse qtl data from some of the largest study systems available has enabled us to identify a novel gene, mgst which is associated with hippocampus size across species and, when dysregulated, is linked to neurodegenerative disorders. 
we first use a novel cross-species, comparative analysis using mouse and human genetic data to identify a candidate gene, mgst associated with adult hippocampus size in both systems. in addition, mapping studies in mouse model systems have identified genetic variants for brain structure variation with great power. to identify genetic variants underlying such differences and associated disease phenotypes, multinational consortia such as enigma have used large magnetic resonance imaging data sets in human gwas studies. we combine the largest human gwas of brain structure with the largest mammalian model system, the bxd recombinant inbred mouse population, to identify novel genetic targets influencing brain structure variation that are linked to increased risk for neurological disorders. we find that mgst is associated with hippocampus size and is linked to a group of neurodegenerative disorders, such as alzheimer’s. variation in hippocampal volume has been linked to significant differences in memory, behavior, and cognition among individuals. a key challenge is to understand how genetically based differences in brain structure lead to the propensity to develop specific neurological disorders.
 variation in hippocampal volume has been linked to significant differences in memory, behavior, and cognition among individuals. to identify genetic variants underlying such differences and associated disease phenotypes, multinational consortia such as enigma have used large magnetic resonance imaging data sets in human gwas studies. in addition, mapping studies in mouse model systems have identified genetic variants for brain structure variation with great power. a key challenge is to understand how genetically based differences in brain structure lead to the propensity to develop specific neurological disorders.  we combine the largest human gwas of brain structure with the largest mammalian model system, the bxd recombinant inbred mouse population, to identify novel genetic targets influencing brain structure variation that are linked to increased risk for neurological disorders. we first use a novel cross-species, comparative analysis using mouse and human genetic data to identify a candidate gene, mgst associated with adult hippocampus size in both systems. we then establish the coregulation and function of this gene in a comprehensive systems-analysis.  we find that mgst is associated with hippocampus size and is linked to a group of neurodegenerative disorders, such as alzheimer’s. electronic supplementary material the online version of this article contains supplementary material, which is available to authorized users. keywords comparative analysishippocampusmgst3bxdissue-copyright-statement© the author 2014 