Combining functional genetics and fMRI The ‘candidate gene’ ‘intermediate phenotype’ approach -What it basically comes down to:- -Looking at the relationship between a particular polymorphism in a gene and brain activity during performance of a given task. -Why do it? - An interesting approach to studying individual differences in neural and cognitive function. - In particular, some common genetic polymorphisms lead to 3-5 fold changes in the expression or activity of proteins involved in neurotransmitter metabolism or uptake – studying the influence of these polymorphisms can provide a convergent approach to the use of pharmacological manipulations to understanding the impact of these neurotransmitters upon brain function.

Background:- -20,000 genes + play a role in the development, plasticity & maintenance of the CNS. 6 million + polymorphisms contribute to genetic variability between individuals One estimate - approx 5 polymorphisms per gene are ‘functional’ – resulting in change in expression or behaviour of proteins ‘Alleles’ – variants of genes resulting from polymorphisms

Traditional approaches:- Allelic association studies These look to see whether certain groups (e.g. individuals with a given psychiatric diagnosis) have an increased frequency of a particular allele compared to controls. There seem to be a lot of failures to replicate This has recently led Weinberger and colleagues to propose the ‘candidate gene’/ ‘intermediate phenotype’ approach; - premise – there is a more direct relationship between genetic variation and brain function than between genetic variation and psychiatric diagnosis.

Principles for (successfully) conducting a candidate gene/ intermediate phenotype study 1)Chose your genetic polymorphism of interest with care - is it functional? - is there a reason to believe it may impact upon activity in the region of interest / affect the cognitive function of interest? 2)Chose your imaging task with care - Is there evidence for the cognitive process being tapped being heritable? - Does the task have high reliability? - Does it reliably (across individuals) activate the region of interest? Are there individual differences in task performance and/or extent of neural activation?

Types of polymorphism:- VNTRs Variable Number of Tandem Repeats (a sequence of x nucleotide bases is repeated a variable number of times) If these occur in the promotor region these can influence the expression (i.e. alter the amount of mRNA produced) A good example is the 5HTT-LPR : a VNTR polymorphism in the promotor region of the serotonin transporter gene People either have 2 short alleles (20%), one short and one long (50%) or two long alleles (30%) The l allele is linked to higher concentration of 5-HTT mRNA and greater 5-HT reuptake (as shown in cultured human lymphoblast cell lines). In vivo SPECT imaging also shows differences in 5HTT binding levels. The S allele appears to be dominant

fMRI findings:- There are now a number of studies suggesting that individuals with one or more 5HTT-LPR short alleles show an increased amygdala response to threat-related stimuli (e.g Hariri 2002)

SNPs – Single nucleotide polymorphisms If these occur in the coding region of the gene they can lead to changes that alter the function of the protein A good example is the COMTval158met polymorphism Here, a G to A mutation causes a substitution of Val by Met. (GTG to ATG result s in Val to Met). The Met allele is unstable and has1/4 of the activity of the Val allele. A regionally selective effect of COMT in PFC may result from dopamine transporters being expressed in low abundance and not within synapses People either have 2 val alleles, one val and one met, or two met alleles The alleles are codominant, heterozygous individuals having enzyme activity that is midway between homozygous individuals

fMRI findings:- There are now a number of studies suggesting that the number of val alleles possessed is positively correlated with the extent of PFC activation observed during working memory and other prefrontal tasks (e.g. Egan et al. 2001, Bishop et al. 2003)

Other common polymorphisms DAT (dopamine transporter) 9 vs 10 VNTR in an untranslated region of the gene It is not clear whether this is functional or not. However, Spect imaging has shown 9/10 repeat heterozygous individuals have reduced DAT availability compared to 10/10 homozygous individuals (Heinz et al. 2000) This could be due to altered transcription or translation. Or it could be due to linkage disequilibrium with another poly- morphism accounting for the difference between groups.

Other common polymorphisms ApoE Є2, Є3, Є4 alleles Є4 allele associated with increased risk for Alzheimer’s Disease ApoE has a stimulatory effect on neurite outgrowth promoting structural changes in response to brain injury and neurodegeneration. This is held to be reduced in the case of Є4 Figures taken from Raber et al. 2004

Polymorphisms not necessarily associated with variation in function in the general population … FOX P2 A rare mutation has been associated with severe speech & language impairment (in the KE family) A number of more common polymorphisms in the Fox P2 gene have been identified. However, so far none of them have been found to account for variability in performance on tests of speech or language The functionality of most of these polymorphisms has not been established

Issues Interpreting the data with/ without behavioural findings It is often hard to get effects of genotype upon cognitive performance without sample sizes in the 100s. But null behavioural results cause difficulties in interpreting fMRI findings… The Efficiency Hypothesis In a number of studies on COMT, Weinberger and colleagues have reported an effect of genotype at the brain level either with no effect on task performance (e.g Egan et al 2000) or an effect in the opposite direction (increasing neural activity associated with poorer performance). They have argued that this is because the COMT met allele is associated with enhanced neural efficiency (equivalent or enhanced performance together with less PFC activity). However, not all studies find results that fit with the neural efficiency hypothesis (e.g. Fan et al 2003)

Issues Interpreting the data:- U shapes, dominance, interactions …. We also have to contend with possible nonlinearities in the influence of our genetic variable upon neural or cognitive function. For example, it has been argued that COMT activity (via its impact on PFC DA levels) may have a U shaped relationship with PFC function. So, even though the number of COMT val 158 alleles possessed may have a linear effect upon COMT activity this may not carry through to the neural or cognitive level. While the COMT met & val alleles are thought to be co-dominant (heterozygous individuals having intermediate levels of COMT activity) with other polymorphisms there is the issue of dominance.

Issues Dominance - with the 5HTT-LPR polymorphism, the s allele appears to be dominant with cell line and SPECT studies giving similar finding for s/l and s/s cases vs l/l cases. This shows how it is important to know about dominance for analysing your data – here we might want to compare l/l/ individuals against a group of l/s and s/s individuals. However, to complicate things further still …when susceptibility to depression is considered, there is some suggestion that this dominance effect may not be so clear with l/s individuals showing intermediate patterns for some measures of risk. Interactions – we may wish to consider whether two or more polymorphisms of interest interact or have additive effects (e.g. different polymorphisms impacting on DA metabolism/ uptake)

Issues Multiple comparisons (avoiding false positives) Either in a single study, or across studies, association studies typically end up looking at the association between many different polymorphisms and the phenotype of interest (e.g. diagnosis of Schizophrenia). As a result, the case is often made for doing multiple comparisons corrections for all the polymorphisms studied OR even all the polymorphisms that could conceivably be examined. While proponents of the candidate gene / intermediate phenotype model do not suggest applying the latter approach to corrections in the case of genomic imaging studies, not all reviewers may be of the same opinion …

Issues Linkage disequilibrium This refers to a correlation between a specific allele at one locus and another allele at a second locus. It may mean that any effect observed is not actually due to the polymorphism under consideration. This is particularly problematic when there is no evidence for the functionality of the polymorphism being investigated. Functionality issues The above seems to suggest sticking to polymorphisms of known functionality … However it is not necessarily clear that we understand all the ways in which polymorphisms may influence protein expression or activity, and many functionality studies still remain to be done.

Practical Issues Genotyping prior to or post the imaging study:- Prior :pros - best for matching samples cons - large numbers of volunteers need to be screened to nnnnn get equal groups when one of the alleles is rarer than the ccccccother arrangements for genotyping – attempts to set it up in aCambridge via MRC Epidemiology and the BCNC Ethnic stratification: Certain alleles may be more or less common in different ethnic groups. Hence, if your genotype groups are not ethnically equivalent, apparent genetic effects could be due to differences linked to ethnicity for other reasons. Differences in genotype groups in IQ, gender, age etc may also make it hard to detect genetic effects.

What running a study entails … Recruiting a lot of potential volunteers Screening them for one or more polymorphisms by taking a cheek swab or a blood sample Getting these analysed (may take time …..) Deciding how you are going to split your group according to the polymorphism of interest – issues if dominance (e.g. for the 5HTT polymorphism you may want to look at l/l individuals vs l/s and s/s individuals; while for COMT you may want to do a correlation against the number of val alleles possessed) Scanning an appropriate (?) number of individuals with each allele type. Conducting a standard SPM analysis with genotype entered as a covariate at the random effects level (or modelling 2 nd order terms/ non linear effects)

If you’re still interested … further reading Hariri AR, Weinberger DR. Imaging genomics. Br Med Bull. 2003;65: A good basic review of the methods Egan MF, et al. Effect of COMT Val108/158 Met genotype on frontal lobe function and risk for schizophrenia. Proc Natl Acad Sci U S A Jun 5;98(12): Epub 2001 May 29. One of the first COMT fMRI studies Bilder RM, Volavka J, Lachman HM, Grace AA. The catechol-O- methyltransferase polymorphism: relations to the tonic-phasic dopamine hypothesis and neuropsychiatric phenotypes. Neuropsychopharmacology Nov;29(11): Review. A more complex take on the COMT story Hariri AR, Mattay VS, Tessitore A, Kolachana B, Fera F, Goldman D, Egan MF, Weinberger DR. Serotonin transporter genetic variation and the response of the human amygdala. Science The first 5HTT fMRI paper Raber J, Huang Y, Ashford JW. ApoE genotype accounts for the vast majority of AD risk and AD pathology. Neurobiol Aging May-Jun;25(5): Review. A paper reviewing the evidence for the link between ApoE and risk for Alzheimers