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Paper text:
mental illness continues to incur negative attitudes , often characterized by fear , stigma and rejection , but the idea that it reflects a ' weakness of character ' that can be overcome by sheer willpower is increasingly losing ground .
most people now understand that psychiatric disorders are caused by a sick organ , just like heart disease , although in this case the organ happens to be the most complex organ we possess , the brain .
appreciation of the importance of biological factors in psychiatric disorders has been strongly reinforced by evidence from twin and family studies that genetic variation between individuals has a key role in the risk for these disorders .
heritability estimates for cognitive disorders , such as schizophrenia , attention deficit hyperactivity disorder ( adhd ) and autism , range from 50% to 80% [ 2 - 6 ] . for affective disorders , such as major depression , anxiety disorders and substance abuse , estimates range from 40% to 65% .
however , pinpointing the actual genetic variants responsible for this heritability has proven difficult . the most successful gene - finding approach , genome - wide association ( gwa ) , has uncovered many genetic variants for conditions such as diabetes , crohn 's disease   and atherosclerotic risk , but this method has , as yet , not been as successful for psychiatric disorders . for schizophrenia and autism only a handful of genetic variants
have been identified [ 14 - 16 ] , and there are currently no confirmed genetic variants associated with adhd and depression .
the difficulty in identifying actual genetic variants probably relates to the complexity of psychiatric phenotypes , which in turn reflects the complexity of the brain processes that underlie them . to reduce this complexity it has been proposed to focus genetic studies on so - called brain endophenotypes [ 2,17 - 19 ] .
the basic reasoning is that it may be easier to detect the effect of a genetic variant on a more elementary neurobiological trait because there may be fewer genetic variants with larger effect sizes involved in these traits .
an eeg signal is recorded non - invasively from electrodes placed on the scalp and depicts the ongoing electrical activity of the brain .
an event - related potential ( erp ) is the brain 's electrical response to the occurrence of a specific event .
the event is usually a stimulus - a word or picture presented on a display - but it can also be generated internally , for instance by the intention to move a limb .
an example of an erp is the p3 , a positive wave that occurs about 300 ms after a motivationally significant stimulus .
the p3 reflects the activity of the locus - coeruleus - norepinephrine system , which facilitates the behavioral and cognitive responses to motivationally significant events , and it may be the central nervous system component of the fight - flight response .
can eeg and erp endophenotypes help identify and confirm novel genetic risk factors for psychiatric disease ? to do so they must , first of all , be predictive of psychiatric disorders .
there is a huge corpus of literature on the use of eeg or erp endophenotypes as risk markers for psychiatric disorder .
it is impossible to review this corpus in a few words here , but two examples may serve to illustrate it . first , frontal asymmetry of eeg  power ( fa ) has been studied extensively as a correlate of individual differences in emotional response .
greater left hemispheric activity has been associated with a tendency to approach things of interest , and greater right hemispheric activity with withdrawal - related tendencies .
disturbances in the emotional dimension of approach versus withdrawal have a key role in the liability to develop psychopathology such as depression and anxiety disorders , with which the fa has indeed been found to be associated .
second , reduced amplitude of the p3 is found in a variety of psychiatric and behavioral disorders , but most notably schizophrenia   and alcohol abuse .
the reduction in p3 amplitude reflects a genetic predisposition for these disorders rather than a mere functional consequence , because it does not normalize after successful treatment   and is also found in unaffected relatives .
the latter point is important . to tag a relevant part of the pathway from genetic variation to psychiatric disorder
, the endophenotypes must be heritable traits and their heritability must arise partly from the genetic variants that also influence the psychiatric disorder . in the netherlands
twin register , we have estimated the heritability of a variety of eeg and erp endophenotypes , and similar work has been undertaken by colleagues from twin registries around the world [ 30 - 43 ] ; table 1 illustrates the findings from these studies .
this high heritability does not simply reflect ' trivial ' heritable similarities in the composition of the skull or other tissue layers between electrode and brain .
almost identical heritability estimates are obtained when power is computed in signals from magnetoencephalography , which are almost undistorted by tissues covering the brain .
heritability estimates for eeg / erp traits * * data are from studies comparing the resemblance in monozygotic twins with that in dizygotic twins . if a measure was available at multiple electrodes , the electrodes with highest amplitude were selected .
a range of heritabilities reflects either the variation in estimates across multiple studies or across multiple age groups within a single study . to return to the question of whether these heritable eeg and erp endophenotypes can help to identify and confirm novel genetic risk factors for psychiatric disorders :
gwa has been the most successful method for detecting novel potential genetic variants for complex traits . however , it has a limited ability to detect common variants with very small effect sizes and also rare variants with very low allele frequencies .
both limitations can be tackled by increasing the size of the ( pooled ) samples , although the second also needs increased depth of coverage of genomic variation , perhaps even by full sequencing .
unfortunately , the clear need for very large sample sizes in gwa studies strongly limits the usefulness of eeg / erp measurements in the gene discovery phase .
eeg / erp measurements require controlled laboratory experiments with sophisticated and rather expensive equipment . they take up to at least 20 to 30 minutes and this may increase up to hours if error measurement is to be contained using the more complex derived measures .
measuring eeg / erp , in short , is too hard to do on the tens of thousands of subjects needed in a gwa , particularly when contrasted with the use of existing patient records or questionnaire - based assessment of psychiatric symptoms .
the real value of brain endophenotypes may come after gene finding , when they help us confirm the biological meaning of the genetic variants that were detected using gwa on psychiatric symptoms and diagnoses .
one of the lessons of successful gwa studies in other fields is that they point us to genetic pathways that were not previously known to be involved in the trait . finding genetic variants for psychiatric symptoms and diagnoses needs , therefore , to be followed up by an understanding of what these ' psychiatric ' genes do in the brain .
testing the association of the risk alleles with eeg and erp endophenotypes can help us understand where in the brain , in which stage , and during what type of information processing the genetic variant has a role .
such testing can be done in more modest samples , which are more feasible for eeg research .
could eeg and erp endophenotypes be more widely applied , apart from helping us to understand how genetic variants cause psychiatric risk ?
the main system for classifying psychiatric disorders is the diagnostic and statistical manual of mental disorders ( dsm - v ) .
this system is based on a tally of symptoms and their impact on daily functioning reported by patients or their caregivers .
the dsm currently is undergoing substantial revision , and a question that repeatedly surfaces is whether we can use the combination of genetic risk scores and brain endophenotypes to better classify psychiatric disorders .
progress in research on the genetics of brain endophenotypes may be key to the successful development of such a classification system .
this system would base our diagnostic procedures more solidly on biology and reinforce the notion that psychiatric disorders are disorders of the brain .
adhd : attention deficit hyperactivity disorder ; dsm : diagnostic and statistical manual ; eeg : electroencephalography ; erp event related potential ; gwa : genome - wide association .
twin and family studies have shown the importance of biological variation in psychiatric disorders . 
 heritability estimates vary from 50% to 80% for cognitive disorders , such as schizophrenia , attention deficit hyperactivity disorder and autism , and from 40% to 65% for affective disorders , such as major depression , anxiety disorders and substance abuse . pinpointing the actual genetic variants responsible for this heritability 
 has proven difficult , even in the recent wave of genome - wide association studies . 
 brain endophenotypes derived from electroencephalography ( eeg ) have been proposed as a way to support gene - finding efforts . 
 a variety of eeg and event - related - potential endophenotypes are linked to psychiatric disorders , and twin studies have shown a striking genetic contribution to these endophenotypes . 
 however , the clear need for very large sample sizes strongly limits the usefulness of eeg endophenotypes in gene - finding studies . 
 they require extended laboratory recordings with sophisticated and expensive equipment that are not amenable to epidemiology - scaled samples . instead , eeg endophenotypes are far more promising as tools to make sense of candidate genetic variants that derive from association studies ; existing clinical data from patients or questionnaire - based assessment of psychiatric symptoms in the population at large are better suited for the association studies themselves . 
 eeg endophenotypes can help us understand where in the brain , in which stage and during what type of information processing these genetic variants have a role . 
 such testing can be done in the more modest samples that are feasible for eeg research . with increased understanding of how genes affect the brain 
 , combinations of genetic risk scores and brain endophenotypes may become part of the future classification of psychiatric disorders .